Volume-1 Issue-12

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S. No

Volume-1 Issue-12, February 2016, ISSN: 2394-367X (Online)
Published By: Blue Eyes Intelligence Engineering & Sciences Publication

Page No.

1.

Authors:

Albina Basholli, Vasillaq Kedhi, Alisa Cangonji

1-5

Paper Title:

A Goal Programming Model for Facility Location Planning
2.

Authors:

S. Kumar, Rashmi Singh, Manish K. Srivastava, Ashish K. Srivastava 6-12

Paper Title:

Fuzzy Logic based Model to Calculate the Economic Level of any Country
3.

Authors:

M.L. Dongare, M. N. Awatade, A. D. Shaligram, A.S. Burungale 13-15

Paper Title:

Analytical Characteristics Study of Glass Electrode based pH Measurement System in Respect of mV Output and Internal Resistance
4.

Authors:

Alka Rani 17-19

Paper Title:

Evaluation of Effectiveness of Holy Basil (Ocimum Sanctum L.) Against Storage Pest Sitophilus Oryzae

Volume-2 Issue-1

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S. No

Volume-2 Issue-1, September 2016, ISSN: 2394-367X (Online)
Published By: Blue Eyes Intelligence Engineering & Sciences Publication

Page No.

1.

Authors:

Surinder Kumar

1-4

Paper Title:

Module Allocation for Maximizing Reliability of Distributed Computing Systems using Dynamic Greedy Heuristic
2.

Authors:

Kshetrimayum Raseshowri Devi, Nagulan Venugopal, Lal Bihari Singha 5-9

Paper Title:

Microscopic Features of Dominant Bladderworts of Northeast India
3.

Authors:

Shiri T, Makota T 10-16

Paper Title:

Status of Biogas Technology in Swaziland: Challenges and Opportunities
4.

Authors:

Jusman, Bambang Setiaji, Triyono, Akhmad Syoufian 17-19

Paper Title:

Characterization Physicochemical of Emulsion Solid Cooking Oil from Coconut Oil

Issue-1 October 2016

Volume-6 Issue-1 Published on October 30, 2016
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S. No

Volume-6 Issue-1, October 2016, ISSN:  2249-8958 (Online)
Published By: Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd. 

Page No.

1.

Authors:

Joseph Zacharias, Jayakrishnan S B, Vijayakumar Narayanan

Paper Title:

82 GHz Millimeter-Wave Transmission Over OFDM ROF System

Abstract: Orthogonal Frequency Division Multiplexing (OFDM) based signal transmission over Millimeter-Wave Radio-over-Fiber (mm-Wave RoF) systems is proposed.  For that an external modulator and an optical interleaver are used to generate dual octupling-frequency optical millimeter waves. Simultaneously. The frequency of local oscillator signal is reduced largely due to frequency octupling.  OFDM signal is used as the downlink data for transmission. Most of the advanced systems are using OFDM based signal such as LTE 4G or WiMAX network. So a system that uses RoF technology to transmit OFDM signal by mm-Wave will be effective. In this proposal, the advanced technologies are combined in order to get an effective model to transmit data at higher speed with a reasonable price.

Keywords:
 Orthogonal frequency division multiplexing, Radio over fiber (RoF), Millimeter-wave, wavelegth reuse.


References:

1.       Tam Hoang Thi and Mitsuji Matsumoto, “Transmission Analysis of OFDM Millimeter-Wave Radio-over-Fiber System ”, Fifth International Conference on Ubiquitous and Future Networks (ICUFN), pp. 800- 804, July 2013
2.       J. Armstrong, “OFDM for optical communications ”, J. Lightw. Technol., vol. 27, no. 3, pp. 189204, Feb. 2009.

3.       Guangming Cheng, Banghong Guo, Songhao Liu, Weijin Fang, “A novel full-duplex radio-over-fiber system based on dual octupling-frequency for 82 GHz W-band radio frequency and wavelength reuse for uplink connection ”.

4.       Jianjun Yu, Zhensheng Jia, Ting Wang, Gee-Kung Chang “A Novel Radio- Over-Fiber configuration using optical phase modulator to generate an optical mm-Wave and centralized lightwave for uplink connection ”, IEEE Photonics Technology Letters, vol. 19, no. 3, pp. 140 – 142, February 2007

5.       SPP “Planning of the 7176 GHz and 8186 GHz bands for millimeter wave highcapacity fixed link technology, ”, Australian Communication and Media Authority, 2006

6.       Colombo, M. Cirigliano, “Next-generation access network: a wireless networkusing E-band radio frequency (7186 GHz) to provide wideband connectivity, ”, Bell Labs Tech. J. , vol. 16, no. 1, pp. 187 – 206, 2011.

7.       Zizheng Cao, Jianjun Yu,Minmin Xia, Qi Tang, Yang Gao,  Wenpei Wang, and Lin Chen, “Reduction of Intersubcarrier Interference and Frequency-Selective Fading in OFDM-RoF Systems”, Journal of lightwave technology, vol. 28, no. 16, August 15, 2010

8.       R. Karthikeyan and Dr. S. Prakasam, “OFDM Signal  Improvement Using Radio over Fiber for Wireless System ”, International Journal of Computer Networks and Wireless Communications (IJCNWC), ISSN: 2250-3501 vol. 3, no. 3, June 2013.

9.       Jianjun Yu, Zhensheng Jia,Ting Wang, and Gee Kung Chang, “Centralized Lightwave Radio-Over-Fiber System With Photonic Frequency Quadrupling for High-Frequency Millimeter-Wave Generation ”,  IEEE photonics technology letters, vol. 19, no. 19, Oct 2007

10.    Wake,  C.  R.  Lima  and  P.  A.  Davies,  “Transmission  of  60-GHz Signals over 100 km of Optical Fiber Using a dual mode Semiconductor Laser Source ”, IEEE photonics technology letters, vol 8, no 4, April 1996

11.    C. van den Bos , M. H. L. Kouwenhoven and W. A. Serdijn, “The influence of non-linear distortion on OFDM bit error rate ”, IEEE International Conference on Communications, vol. 2, pp. 1125 – 1129, June 2000

12.    Lin Chen, Hong Wen, and Shuangchun Wen, “A Radio-Over-Fiber system with a novel scheme for Millimeter-Wave generation and wavelength reuse for up-link connection ”, IEEE Photonics Technology Letters, vol. 18, no. 19, pp. 2056 – 2058, October 2006

13.    G.-K. Chang, J. Yu, Z. Jia, J. Yu “Novel optical-wireless access network architecture for simultaneously providing broadband wireless and wired services ”, Proc.OFC, Paper OFM1D, Anaheim, USA, March 2006.

14.    Yoon-Khang Wong, S.M. Idrus, and I.A. Ghani, “Performance Analysis of the OFDM Scheme for Wireless over Fiber Communication Link,”, International Journal of Computer Theory and Engineering , vol. 4, no. 5, October 2012.

15.    Ajay Kumar Vyas, Dr. Navneet Agrawal, “Radio over Fiber: Future Technology of Communication, International Journal of Emerging Trends and Technology in Computer Science (IJETTCS) , vol. 1, no. 2, August 2012.

 

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2.

Authors:

Anila V M, Seena Thomas

Paper Title:

Detection of Diabetic Retinopathy from Fundus Images through Local Binary Patterns and Artificial Neural Network

Abstract:  Diabetic retinopathy (DR) is one of the most frequent cause of blindness and vision loss in diabetic patients. The diabetic retinopathy is detected earlier, the better the chance that it can be effectively treated and further vision loss prevented. This condition increases the importance of automated detection of the disease. This work focuses on distinguishing between diabetic retinopathy (DR) and normal fundus images by analyzing the texture of the retina background. Local Binary Patterns (LBP) are used as texture descriptors. They are the powerful grey-scale texture descriptors that is commonly used because of its computation simplicity. Local Binary Pattern is based on looking at the local variations around each pixel, and assigning labels to different local patterns and the labels are evaluated and used in the classification stage. Probabilistic Neural Network (PNN) is the classifier that is used for the classification of abnormal and healthy images. This work suggest that LBP is a robust texture descriptor for retinal images and the proposed method analyzing the retina background directly and avoiding difficult lesion segmentation such as exudates, microaneurysms etc. can be useful for diagnostic aid.

Keywords:
  Diabetic Retinopathy, Local Binary Patterns, Probabilistic Neural Network, Fundus Images.


References:

1.       Sandra Morales, Kjersti Engan, Valery Naranjo and Adri´an ColomerT. “Retinal Disease Screening through
2.       Local Binary Patterns” IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, VOL. 00, NO. 00, 2015

3.       Frdric Zana and Jean-Claude Klein ,Segmentation of Vessel-Like Patterns Using Mathematical Morphology and Curvature Evaluation IEEE Transactions On Image Processing, Vol. 10, No.7, July 2001

4.       Keith A. Goatman, Alan D. Fleming, Sam Philip, Graeme J.Williams, John A. Olson and Peter F. Sharp, Detection of New Vessels on the Optic Disc Using Retinal Photographs, IEEE Transactions on Medical Imaging, Vol. 30, No. 4, pp. 972 979, 2011.

5.       E. Ricci and R. Perfetti, Retinal blood vessel segmentation using line operators and support vector classification, IEEE Trans. Med. Imag., vol. 26, no. 10, pp. 13571365, Oct. 2007

6.       E. Ricci and R. Perfetti, Retinal blood vessel segmentation using line operators and support vector classification, IEEE Trans. Med. Imag., vol. 26, no. 10, pp. 3571365, Oct. 2007

7.       T. Walter, J.C. Klein, P. Massin, and A. Erginay, A contribution of image processing to the diagnosis of diabetic retinopathy-detection of exudates in colour fundus images of the human retina , IEEE Transactions on Medical Imaging , Vol. 22(10),pp. 1236 1243, 2002.

8.       Jo£o V. B. Soares, Jorge J. G. Leandro, Roberto M. Cesar Jr.,Herbert F. Jelinek, and Michael J. Cree, Retinal Vessel Segmentation Using the 2-D Gabor Wavelet and supervised Classification IEEE TRANSACTIONS ON MEDICALIMAGING, VOL. 25, NO. 9, SEPTEMBER 2006

9.       World Health Organization (WHO), Universal eye health: a global action plan 2014-2019, 2013.

10.    T. Ojala, M. Pietikinen, and T. Menp, A generalized local binary pattern operator for multiresolution gray scale and rotation invariant texture classification, in Advances in Pattern Recognition, 2nd International Conference on, 2001, pp. 397406.

11.    T. Ojala, M. Pietikainen, and T. Maenpaa, Multiresolution gray-scale and rotation invariant texture classification with local binary patterns, Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol. 24, no. 7, pp. 971987, 2002.

12.    M. Heikkil, M. Pietikinen, and C. Schmid, Description of interest regions with local binary patterns, Pattern Recognition, vol. 42, no. 3, pp. 425 436, 2009.

13.    Z. Yang and H. Ai, Demographic classification with local binary patterns, in Advances in Biometrics, ser. Lecture Notes in Computer Science, S.-W. Lee and S. Li, Eds., 2007, vol. 4642, pp. 464473.

14.    L. Nanni, A. Lumini, and S. Brahnam, Local binary patterns variants as texture descriptors for medical image analysis, Artificial Intelligence in Medicine, vol. 49, no. 2, pp. 117 125, 2010.

15.    M. Mookiah, U. R. Acharya, R. J. Martis, C. K. Chua, C. Lim, E. Ng, and A. Laude, Evolutionary algorithm based classifier parameter tuning for automatic diabetic retinopathy grading: A hybrid feature extraction approach, Knowledge-Based Systems, vol. 39, no. 0, pp. 9 22, 2013.

16.    M. M. R. Krishnan and A. Laude, An integrated diabetic retinopathy index for the diagnosis of retinopathy using digital fundus image features, Journal of Medical Imaging and Health Informatics, vol. 3, no. 2, pp. 306313, 2013.

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3.

Authors:

Wael Zaghloul ElSayad, Hussein Mahmoud Hussein

Paper Title:

Reducing the Negative Effects of Dust Storms using Solar Energy to Recycle Plastic Waste

Abstract:  A sandstorm is characterized as one that whips up extraordinary loads of sand into the air, forming a dense cloud above the ground in the process. While most of the sand will rise higher than 50 cm, some sand particles can even ascend to the height of 2 meters. According to Wikipedia, the average diameter of the particles carried by such dust storm winds will vary between 0.15 and 0.30 mm. Wind speeds such during sandstorms have been recorded at up to 16 km per hour and more, while most storms continue to blow for between three hours to five hours. The dust unleashed from sandstorms continues to pose severe environmental concerns in certain Arab and Middle East countries, causing great hardships to its citizens in the form of lost income and widespread infrastructure damage. Perhaps more importantly, when it comes to measuring the effects on people’s health, it has been well documented that sandstorms have, in many cases, led to both the death and destruction of livestock, crops and even human beings. Based on the above factors, scientific researchers continue to work tirelessly to confront sandstorms in an effort to both prevent and alleviate this dangerous natural phenomenon. This particular study will look to establish a low-cost system of erecting plastic trees built from solar energy and recycled plastic waste in order to reduce the risks of sandstorms.

Keywords:
 Middle East countries, recycled plastic, sandstorms, solar energy.


References:

1.    Sultan Ayoub Meo, Mohammad Fahad A Al-Kheraiji, Ziyad Fahad AlFaraj, Nasser abdulaziz Alwehaibi, and Ahmad Adnan Aldereihim. “ Respiratory and general health complaints in subjects exposed to sandstorm at Riyadh, Saudi Arabia”. (2013, April). Pakistan Journal of Medical Sciences. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3809255/
2.    Miller, Ron and Tegan, Ina. “Desert Dust, Dust Storms and Climate”. National Aeronautics and Space Administration Goddard Institute for Space Studies, (1997, April). http://www.giss.nasa.gov/research/briefs/miller_01/

3.    Buttiker, N & Krupp (Eds). Climatologically features of Saudi Arabia, in Fauna of Saudi Arabia, a, No.6, Meteorological Environmental Protection Administration, Saudi Arabia

4.    Ayoub Meyo, Sultan, Fahad A Al-Kheraiji, Mohammed et al. ‘Respiratory and general     health complaints in subjects exposed to sandstorm at Riyadh, Saudi Arabia.’ Pakistan Journal of Medical Sciences, April 29, 2013, 642–646.

5.    Regional Master Plan for the prevention and control of Dust and Sandstorms in Northeast Asia. Volume No. 1. March 2005.

6.    Deserts and Desertification Seminar. (2006). “Danger of dust storms leads to the transfer of germs that cause for «anthrax»” http://archive.aawsat.com/details.asp

7.    Al Turki, Ali bin Mohammed, Al Maghrbi, Salem al-Azab and Ghazi Algamd, Abdul Aziz. “Properties and the amount of soil losing by wind drift in the Riyadh region.”

8.    “High-density polyethylene.” Wikipedia. July 6, 2016. https://en.wikipedia.org/wiki/High- density polyethylene.

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4.

Authors:

Safia Yasmeen, G. Manoj Someswar

Paper Title:

Design & Development of a Suitable Model to Validate New Estimation Approaches for Effective Performance

Abstract: As COCOMO is a non-proprietary model, its details are available in the public domain, encouraging researchers and practitioners in the software engineering community to independently evaluate the model. There have been many extensions independently reported where machine learning techniques are used to generate effort models from the original COCOMO model. In our research work, we proposed a calibration method by transforming the model equation into a linear form and estimating the model parameters using standard linear regression techniques. This calibration method has been adopted by the COCOMO development team in their calibration work.  COCOMO has also been a model used to validate new estimation approaches such as fuzzy logic and neural networks. The COCOMO development team continues to calibrate and extend the model using different calibration approaches on more augmented data sets and our research work is mainly based upon these approaches wherein we have evolved newer and better approaches over the existing approaches and gave a realistic outlook to the very purpose of achieving the best performance.

Keywords:
Calibration Technique, Maintenance Function Point (MFP), Maintenance Impact Ratio (MIR), Developed for Reusability (RUSE), Required Development Schedule (SCED), Required Software Reliability (RELY)


References:

1.       Abran A., Silva I., Primera L. (2002), “Field studies using functional size measurement in building estimation models for software maintenance”, Journal of Software Maintenance and Evolution, Vol 14, part 1, pp. 31-64
2.       Albrecht A.J. (1979), “Measuring Application Development Productivity,” Proc. IBM Applications Development Symp., SHARE-Guide, pp. 83-92.

3.       Albrecht A.J. and Gaffney J. E. (1983) “Software Function, Source Lines of Code, and Development Effort Prediction: A Software Science Validation,” IEEE Transactions on Software Engineering, vol. SE-9, no. 6, November

4.       Banker R., Kauffman R., and Kumar R. (1994), “An Empirical Test of Object-Based Output Measurement Metrics in a Computer Aided Software Engineering (CASE) Environment,” Journal of Management Information System.

5.       Basili V.R., (1990) “Viewing Maintenance as Reuse-Oriented Software Development,” IEEE Software, vol. 7, no. 1, pp. 19-25, Jan.

6.       Basili V.R., Briand L., Condon S., Kim Y.M., Melo W.L., Valett J.D. (1996), “Understanding and predicting the process of software maintenance releases,” Proceedings of International Conference on Software Engineering, Berlin, Germany, pp. 464-474.

7.       Basili V.R., Condon S.E., Emam K.E., Hendrick R.B., Melo W. (1997) “Characterizing and Modeling the Cost of Rework in a Library of Reusable Software Components”. Proceedings of the 19th International Conference on Software Engineering, pp.282-291

8.       Boehm B.W. (1981), “Software Engineering Economics”, Prentice-Hall, Englewood Cliffs, NJ, 1981.

9.       Boehm B.W. (1988), “Understanding and Controlling Software Costs”, IEEE Transactions on Software Engineering.

10.    Boehm B.W., Royce W. (1989), “Ada CCCOMO and Ada Process Model,” Proc. Fifth COCOMO User’s Group Meeting, Nov.

11.    Boehm B.W., Clark B., Horowitz E., Westland C, Madachy R., Selby R. (1995), “Cost models for future software life cycle processes: COCOMO 2.0, Annals of Software Engineering 1, Dec, pp. 57-94.

12.    Boehm B.W. (1999), “Managing Software Productivity and Reuse,” Computer 32, Sept., pp.111-113

13.    Boehm B.W., Abts C, Chulani S. (2000), “Software development cost estimation approaches: A survey,” Annals of Software Engineering 10, pp. 177-205.

14.    Boehm B.W., Horowitz E., Madachy R, Reifer D., Clark B.K., Steece B., Brown A.W., Chulani S., and Abts C. (2000), “Software Cost Estimation with COCOMO II,” Prentice Hall.

15.    Boehm B.W., Valerdi R. (2008), “Achievements and Challenges in Cocomo-Based Software Resource Estimation,” IEEE Software, pp. 74-83, September/October

16.    Bradley E., Gong G. (1983), “A leisurely look at the bootstrap, the jack-knife and cross-validation”, American Statistician 37 (1), pp.836-848.

17.    Briand L.C., Basili V., Thomas W.M. (1992), “A pattern recognition approach for software engineering analysis”, IEEE Transactions on Software Engineering 18 (11)931
942.

18.    Briand L.C. & Basili V.R. (1992) “A Classification Procedure for an Effective Management of Changes during the Software Maintenance Process”, Proc. ICSM ’92, Orlando, FL.

19.    Briand L.C, El-Emam K., Maxwell K., Surmann D., and Wieczorek I., “An Assessment and Comparison of Common Cost Estimation Models,” Proc. 21st International Cor ference on Software Engineering, pp. 313-322, 1999.

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5.

Authors:

M Veera Chandra Kumar, K. Satyanarayana, M.N.V.V. Brahmam

Paper Title:

An SMC based RZVDPWM Algorithm of Vector Controlled Induction Motor Drive for Better Speed Response with Reduced Acoustical Noise

Abstract:  In this paper, an sliding mode controller (SMC) based Random Zero vector Distribution PWM (RZVDPWM) algorithm of vector controlled induction motor drive for better speed response with reduced Acoustical Noise is analyzed. In order to mitigate the difficulty faced in the conventional Space Vector PWM (SVPWM) approach, the proposed RZVDPWM algorithm is created by taking the concept of Simplified PWM sequence. This algorithm is developed by using the concept of random number generation technique. Simulation studies are carried out to validate proposed RZVDPWM algorithm, the results obtained are presented and compared. The simulation results shows that the overall performance of SMC based RZVDPWM drive is better when compared to SVPWM technique under different conditions of operation.

Keywords:
 Simplified PWM sequence, SVPWM, RZVDPWM, Vector control, SMC


References:

1.    F. Blaschke “The principle of field orientation as applied to the new transvector closed loop control system for rotating-field machines,” Siemens Review, 1972, pp 217-220.
2.    Heinz Willi Vander Broeck, Hnas-Christoph Skudelny and Georg Viktor Stanke, “Analysis and realization of a pulse width modulator based on voltage space vectors” IEEE Trans. Ind. Applicat., vol. 24, no. 1, Jan/Feb 1988, pp. 142-150.

3.    Michael M.Bech, Frede Blaabjerg, and John K. Pedersen, “Random modulation techniques with fixed switching frequency for three-phase power converters” IEEE Trans. Power Electron., vol.15, no.4, pp. 753-761, Jul, 2000.

4.    S-H Na, Y-G Jung, Y-C. Lim, and S-H. Yang, “Reduction of audible switching noise in induction motor drives using random position space vector PWM” IEE. Proc. Electr. Power Appl., vol.149, no.3, pp. 195-200, May, 2002.

5.    Andzrej M. trzynadlowski, Konstantin, Yuin Li, and Ling Qin, “A novel random PWM technique with low computational overhead and constant sampling frequency for high-volume, low-cost applications” IEEE Trans. Power Electron., vol. 20, no.1, pp.116-122, Jan, 2005.

6.    Dae-Woong Chung, Joohn-Sheok Kim and Seung-Ki Sul, “Unified voltage modulation technique for real-time three-phase power conversion” IEEE Trans. Ind. Applicat., vol. 34, no. 2, Mar/Apr 1998, pp. 374-380.

7.    T. Brahmananda Reddy, J. Amarnath and D. Subbarayudu, “Improvement of DTC performance by using hybrid space vector Pulse width modulation algorithm” International Review of Electrical Engineering, Vol.4, no.2, pp. 593-600, Jul-Aug, 2007.

8.    K. Satyanarayana1, J. Amarnath2, and A. Kailasa Rao1, “Hybrid PWM Algorithm with Low Computational Overhead for Induction Motor Drives for Reduced Current Ripple” ICGST-ACSE journal, vol.10, isuue.1, pp. 29-37, Dec, 2010.

9.    N Subba rao, K. Satyanarayana, K.Siva Prasad “Performance Improvement of Sliding Mode Controller based Indirect Vector Controlled Induction Motor Drives” International Journal of Engineering and Advanced Research Technology (IJEART)  ISSN: 2454-9290, Volume-2, Issue-1, January 2016.

 

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6.

Authors:

Thamizharasi A, Jayasudha J.S

Paper Title:

Face Recognition of Enhanced Contrast Limited Adaptive Histogram Equalization using Feature Extraction Method

Abstract:  Face recognition is most widely useful for social networks and surveillance applications. Face recognition is complex if there are variations in light. The proposed work is to develop an illumination invariant face recognition system by enhancing Contrast Limited Adaptive Histogram Equalization (CLAHE). The face recognition of Enhanced CLAHE is done using feature extraction method. The features extracted are DWT statistical features, moments, texture, regional features, shape ratios, Fourier descriptors and facial features from Enhanced CLAHE images. These features are combined to create a feature vector. The feature vector is classified using Support Vector Machine (SVM) classifier and Multilayer Perceptron (MLP) neural network. The efficiency of feature vector is tested with three public face databases AR, Yale and ORL. The testing result proves that feature vector has high recognition accuracy rate.

Keywords:
  face recognition, CLAHE, Enhanced CLAHE, feature vector, illumination invariant, SVM and MLP classifier.


References:

1.       R. Chellappa, C.L. Wilson, and S. Sirohey, “Human and machine recognition of faces: A survey,” Proceedings of. IEEE, vol. 83, pp. 705–740, 1995.
2.       Franco Scarselli and Ah Chung Tsoi, “Universal Approximation Using Feed forward Neural Networks: A Survey of Some Existing   Methods, and Some New Results”, Neural Networks, Vol 11, No 1, pp15-37, 1998

3.       Thamizharasi  and J.S. Jayasudha, “An Illumination invariant face recognition by enhanced contrast limited adaptive histogram equalization”, ICTACT Journal on Image and Video Processing, May 2016, Vol. 06, Issue: 04, ISSN: 0976-9102

4.       Rafael C.Gonzalez and Richard E.Woods, “Digital Image Processing”, Addison-Weseky, 1993.

5.       Taiping Zhang, Yuan Yan Tang, Bin Fang and Xiaoyu Liu, “Face Recognition Under Varying Illumination using Gradientfaces,” IEEE Transactions on Image Processing, Vol. 18, No. 11, pp. 2599-2606, 2009.

6.       H.Wang, S.Z.Li and Y.Wang, “Face Recognition under varying lighting conditions using self-quotient image,” in Proceedings of IEEE International Conferencec on Automatic Face and Gesture Recognition, pp. 819-824, 2004

7.       Zhang Y., Tian J., He X. and Yang X., “MQI Based Face Recognition under Uneven Illumination,” Advances in Biometircs, Vol. 4642, pp. 290-298, 2007

8.       D.J.Jobson, Z.Rahman and G.A.Woodell , “A multiscale retinex for bridging the gap between color images and the human observation of scenes,” IEEE Transactions on Image Processing, Vol. 6, pp. 965-976, 1997

9.       D.J.Jobson, Z.Rahman and G.A.Woodell , “Properties and Performance of a Center/Surround Retinex,” IEEE Transactions on Image Processing, Vol. 6, No. 3, pp. 451-462, 1997.

10.    T.Chen, W.Yin, X.S.Zhou, D.Comaniciu and T.S.Huang, “Total Variation Models for variable lighting face recognition,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 28, pp. 1519-1524, 2006.

11.    X.Tan and B.Triggs , “Enhanced local texture feature sets for face recognition under difficult lighting conditions,” IEEE Transactions on Image Processing, Vol. 19, pp. 1635-1650, 2010

12.    A.S.Georghiades , P.N.Belhumeur and D.J.Kriegman , “From few to many: Illumination cone models for face recognition under variable lighting and pose,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 23, No. 6, pp. 643-660, 2001

13.    Dao Qing Dai and Hong Yan, Wavelets and Face Recognition.: ISBN 978-3-902613-03-5, I-Tech, Austria, pp. 558, 2007

14.    X.Xie, W.Zheng, J.Lai, P.C.Yuen and C.Suen , “Normalization of face illumination based on large and small-scale features,” IEEE Transactions on Image Processing, Vol. 20, pp. 1807-1821, 2011.

15.    Zhenhua Chai, Heydi Mendez Vazquez, Ran He and Tieniu Tan, “Gabor Ordinal Measures for Face Recognition,” IEEE Transactions on Information Forensics and Security, Vol. 9, No. 1, 2014.

16.    Jiwen Lu and Yap-Peng Tan, “Cost-Sensitive Subspace Analysis and Extensions for Face Recognition,” IEEE Transactions on Information Forensics and Security, Vol. 8, No. 3, pp. 510-519, 2013

17.    Weiping Chen and Yongsheng Gao, “Face Recognition using Ensemble String Matching,” IEEE Transactions on Image Processing, Vol. 22, No. 12, pp. 4798-4808, 2013.

18.    Jiwen Lu, Venice Erin Liong, Gang Wang  and Pierre Moulin, “Joint Feature Learning for Face Recognition,” IEEE Transactions on Information Forensics and Security, Vol. 10, No. 7, pp. 1371-1383, 2015

19.    Luciano da Fontoura Costa and Roberto Marcondes Cesar Jr., “Shape Classification and Analysis:Theory and Practice”, 2nd Edition, Pages. 674, 2009

20.    Christican Walck , “Hand-book on Statistical Distributions for experimentalists”, Internal Report, University of Stockholm, Pages.190, 1996

21.    Shailendrakumar M.Mukane , Dattatraya S.Bormane , and Sachine R.Gengaje , “Wavelet and Co-occurence Matrix based Rotation Invariant Features for Texture Image Retrieval Using Fuzzy Logic,” International Journal of Computer Applications, ISSN 0975-8887, Vol. 24, No. 7, 2011

22.    Dengsheng Zhang and Guojun Lu , “A Comparative Study on Shape Retrieval Using Fourier Descriptors with Different Shape Signatures,” Journal of Visual Communication and Image Representation, Vol.14, No. 1, pp. 39-57, 2003

23.    Mark Nixon and Alberto Aguado, “Feature Extraction and Image Processing for Computer Vision”, Third Edition,  Academic Press, Pages. 350, 2012

24.    V.Vapnik , “The Nature of Statistical Learning Theory”, Springer-Verlag, Newyork, Pages.39, 1995

25.    Franco Scarselli and Ah Chung Tsoi , “Universal Approximation Using Feed Forward Neural Networks: A Survey of Some Existing Methods and Some New Results,” Neural Networks, Vol. 11, No. 1, pp. 15-37, 1998

26.    A.M.Martinez and R.Benavente, “The AR Face Database,” 24, CVC Technical Report, 1998.

27.    (Checked on 10th September 2016) ORL Face database. [Online]. http://www.cl.cam.ac.uk/research/dtg/attarchive/facedatabase.html

28.    P.N.Belhumeur, J.P.Hespanha and D.J Kriegman, “Eigenfaces vs Fisherfaces: Recognition using class specific linear projection,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 19, No. 7, 1997.

29.    Rafael C.Gonzalez , Richard E.Woods  and Steven L.Eddins, “Digital Image processing with MATLAB”, 2nd Edition, 2009

30.    (Checked on 10th September, 2016) Weka Software. [Online]. http://www.cs.waikato.ac.nz/ml/weka/

31.    Amany Farag and Randa Atta , “Illumination Invariant Face Recognition Using the Statistical Features of BDIP and Wavelet Transform,” International Journal of Machine Learning and Computing, Vol. 2, No. 1, 2012

32.    Kai Li, Zhen Liu and Peng Tang , “On Linear Discriminant Analysis and its Variants in Face Recognition,” International Journal of Artificial Intelligence and Mechatronics, Vol. 4, No. 1, 2015.

33.    Jamal Husain Shah , Muhammad Sharif, Mudassar Raza and Aisha Azeem, “A Survey: Linear and Nonlinear PCA Based Face Recognition Techniques,” The International Arab Journal of Information Technology, Vol. 10, No. 6, 2013.

34.    Liu N., Wang H. and Yau W., “Face Recognition with Weighted Kernel Principal Component Analysis,” in Proceedings of the nineth International Conference on Control, Automation, Roboticcs and Vision, pp. 1-5, 2006.

35.    Gautham Sitaram Yajia, Sankhadeep Sarkara, K Manikantana  and S Ramachandran, “DWT feature extraction based face recognition using intensity mapped unsharp masking and laplacian of Gaussian filtering with scalar multiplier,” in Second International Conference on Communication, Computing and Security (ICCCS-2012), Procedia Technology, Vol.6, pp. 475-484, 2012

36.    Zahraddeen Sufyanu, Fatma S.Mohamad, Abdulganiyu A.Yusuf and Mustafa B.Mamat, “Enhanced Face Recognition Using Discrete Cosine Transform,” Engineering Letters, Vol. 24, No. 1, pp. 52-61, 2016

37.    M.H Yang, “Kernel Eigenfaces vs Kernel Fisherfaces: Face Recognition using Kernel Methods,” in Proceedings of fifth IEEE International Conference on Automatic Face and Gesture Recognition (RGR’02), pp. 215-220, 2002

 

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7.

Authors:

K. Murali Krishna, S. Ashok Reddy, K. Siva Shankar

Paper Title:

MPPT for Standalone PV System under Partially Shaded Condition using Genetic Algorithm

Abstract:   sun oriented vitality is spotless, renewable and its decentralized character is suitable well at the scattered State of the zones with low thickness of populace. The expense of Electricity from the sun oriented cluster framework is more costly than the power from the utility network. In this way, it is important to work the PV framework at most extreme proficiency by following greatest force point at any natural condition. In this work, the Genetic algorithm is utilized to control the operation of the PV exhibit keeping in mind the end goal to separate the most extreme force. The outcomes acquired are looked at and talked about.

Keywords:
PV System, Maximum Power Point Tracking (MPPT), Genetic algorithm, P&O algorithm.


References:

1.       Bidyadhar Subudhi and Raseswari Pradhan, “A Comparative Study on Maximum Power Point Tracking Techniques for Photovoltaic Power Systems” IEEE Transactions on Sustainable Energy, 2013, Vol. 4, No. 1
2.       Moacyr Aureliano Gomes de Brito, Luigi Galotto, Jr., Leonardo Poltronieri Sampaio, Guilherme de Azevedo e Melo, and Carlos Alberto Canesin, Senior Member, “Evaluation of the Main MPPT Techniques for Photovoltaic Applications” IEEE Transactions on Industrial Electronics, 2013, Vol. 60, No. 3.

3.       M. A. S. Masoum, H. Dehbonei, and E. F. Fuchs, “Theoretical and experimental analyses of photovoltaic systems with voltage and current based maximum power point tracking,” IEEE Trans. Energy Conv., 2002, Vol. 17, No. 4, pp. 514–522

4.       Subudhi and R. Pradhan, “Characteristics evaluation and parameter extraction of a solar array based on experimental analysis,” in Proc. 9th IEEE Power Electron. Drives Syst., Singapore, 2011

5.       T. Esram, J. W. Kimball, P. T. Krein, P. L. Chapman, and P. Midya, “Dynamic maximum power point tracking of photovoltaic arrays using ripple correlation control,” IEEE Trans. Power Electron.,2006, Vol. 21, No.5, pp. 1282–1291

6.       K. Ishaque, Z. Salam, and H. Taheri, “Simple, fast and accurate two diode model for photovoltaic modules,” Solar Energy Mater. Solar Cells, 2011, Vol. 95, pp. 586–594.

7.       LI Chun, ZHU Xin, SUI Sheng and HU Wan, “Maximum Power Point Tracking of a Photovoltaic Energy System Using Neural Fuzzy Techniques”, J Shanghai Univ (Engl Ed), 2009, 13(1), pp.29-36.

8.       Abdulaziz M, S. Aldobhani and Robert John, ” Maximum Power Point Tracking of PV System Using ANFIS Prediction and Fuzzy Tracking”, Procs. Of the Inter. Multi Conf. of engineers and Computer  cientists 2008, vol. II, IMECS 2008, 19-21 March,Hong Kong.

9.       K. Abdelsalam, A. M. Massoud, S. Ahmed and P. N. Enjeti, “Highperformance adaptive perturb and observe MPPT technique for photovoltaic-based microgrids,” IEEE Trans. Power Electron., vol. 26, no. 4, pp. 1010–1021, Apr. 2011

10.    D.G. Lorente, S. Pedrazzi, G. Zini, A. Dalla Rosa, P. Tartarini, Mismatch losses inPV power plants, Sol. Energy 100 (2014) 42–49.

11.    Y.Shaiek, M.Ben Smida, A.Sakly, M.F.Mimouni“Partial Shading Impact on MPPT Methods of Solar PV Generator’ ,Solar Energy ,2013

12.    S. Silvestre, A. Boronat, A. Chouder, Study of bypass diodes configuration on PVmodules, Appl. Energy 86 (2009) 1632–1640.

13.    S.Daraban, D. Petreus, C. Morel“A novel MPPT (maximum power point tracking) algorithm based on a modified genetic algorithm specialized on tracking the global maximum power point in photovoltaic systems affected by partial shading”,Energy,2014

 

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8.

Authors:

Preethi W, Binu Rajan M R

Paper Title:

Atomic Web Service Reliability Prediction

Abstract:  Web service is one of the main supporting underlying technologies in Service Oriented Architecture (SOA). This work is focused on atomic web service reliability, as one of the most important non-functional properties. Service reliability can be defined as the probability that a service invocation gets retrieved successfully, i.e. correct response to the service invocation gets successfully retrieved under the specified conditions and the time constraints. A model-based collaborative filtering approach CLUS (CLUStering) is used to estimate the reliability of an ongoing web service. It considers user, service and environment specific parameters to provide a more accurate description of the service invocation context. Incorporating K-Strings clustering algorithm is highly prominent for clustering of high dimensional data rather than using K-Means algorithm. This aims to generate higher accuracy and efficiency to the prediction model.

Keywords:
 reliability prediction, K-Strings, atomic web services, QoS prediction, K-Means

References:
1.       M. P. Papazoglou, “Service-oriented computing: Concepts, characteristics and directions,” in Web Information Systems Engineering, 2003. WISE 2003. Proceedings of the Fourth International Conference on. IEEE, 2003, pp. 3–12.
2.       Hongbing Wang, Haixia Sun and Qi Yu, “Reliable Service Composition via Automatic QoS Prediction”, IEEE 2013.

3.       L. Zeng, B. Benatallah, A. Ngu, M. Dumas, J. Kalagnanam, and H. Chang, “Qos-aware middleware for web services composition,” Software Engineering, IEEE Transactions on, 2004.

4.       D. Wang and S. T. KISHOR, “Modeling user-perceived reliability based on user behavior graphs,” International Journal of Reliability, Quality and Safety Engineering, 2009.

5.       V. Cortellessa and V. Grassi, “Reliability modeling and analysis of service-oriented architectures,” pp. 339–362

6.       Z. Zheng and M. R. Lyu, “Collaborative reliability prediction of service-oriented systems,” in ACM/IEEE International Conference on Software Engineering – Volume 1, ACM, 2010.

7.       Z. Zheng, H. Ma, M. R. Lyu, and I. King, “Qos-aware web service recommendation by collaborative filtering,” IEEE Transactions on Services Computing, 2011.

8.       L. Baresi and S. Guinea, “Event-based multi-level service monitoring,” in ICWS, pp. 83–90, 2013.

9.       Marin Silic, Goran Delac, and Sinisa Srbljic, “Prediction of Atomic Web Services Reliability for QoS-aware Recommendation”, IEEE 2014.

10.    G. Delac, M. Silic, and S. Srbljic, “A reliability improvement method for soa-based applications,” Dependable and Secure Computing, IEEE Transactions on, vol. PP, no. 99, pp. 1–1, 2014.

11.    V.GrassiandS.Patella,“Reliability prediction for service-oriented computing environments,” IEEE Internet Computing, 2006.

12.    W. T. Tsai, D. Zhang, Y. Chen, H. Huang, R. Paul, and N. Liao, “A software reliability model for web services,” in International Conference on Software Engineering and Applications, 2004.

13.    J. Ma and H.-p. Chen, “A reliability evaluation framework on composite web service,” in IEEE International Symposium on Service-Oriented System Engineering, IEEE Computer Society, 2008.

14.    B. Li, X. Fan, Y. Zhou, and Z. Su, “Evaluating the reliability of web services based on bpel code structure analysis and runtime information capture,” in Asia Pacific Software Engineering Conference 2010, IEEE Computer Society, 2010.

15.    X. Su and T. M. Khoshgoftaar, “A survey of collaborative filtering techniques,” Adv. in Artif. Intell., vol. 2009.

16.    B. Sarwar, G. Karypis, J. Konstan, and J. Riedl, ‘‘Item-Based Collaborative Filtering Recommendation Algorithms,’’ in Proc. 10th Int’l Conf. World Wide Web, 2001, pp. 285/295.

17.    Z. Zheng and M.R. Lyu, ‘‘Collaborative Reliability Prediction of Service-Oriented Systems,’’ in Proc. 32nd ACM/IEEE Int’l Conf. Softw. Eng., New York, NY, USA, 2010, vol. 1, pp. 35/44, ACM.

18.    Klein, F. Ishikawa, and S. Honiden, ‘‘Towards NetworkAware Service Composition in the Cloud,’’ inProc. 21st Int’l Conf. World Wide Web, 2012, pp. 959/968.

19.    N.B. Mabrouk, S. Beauche, E. Kuznetsova, N. Georgantas, and V.Issarny,‘‘QoS-AwareServiceCompositioninDynamicService Oriented Environments,’’ in Proc. 10th ACM/IFIP/USENIX Int’l Conf. Middleware, 2009, pp. 123/142.

20.    Y. Wang, W.M. Lively, and D.B. Simmons, ‘‘Web Software Traffic Characteristics and Failure Prediction Model Selection,’’ J. Comput. Methods Sci. Eng., vol. 9, no. 1, pp. 23-33, Apr 2009.

21.    “Service Selection for Web Services with Probabilistic QoS” , IEEE transactions on services computing, vol. 8, no. 3, may/june 2015.

22.    Mingdong Tang et al., “Collaborative Web Service Quality Prediction via Exploiting Matrix Factorization and Network Map”, IEEE 2015.

23.    Xin Luo et al., “Generating Highly Accurate Predictions for Missing  QoS Data via Aggregating Nonnegative Latent Factor Models”, IEEE 2015.

24.    Y. Xu, J. Yin, and W. Lo, “A unified framework of QoS-based web service recommendation with neighborhood-extended matrix factorization,” in Proc. 6th IEEE Int. Conf. Service Oriented Computing and Applications (SOCA 2013), 2013, pp. 198–205.

25.    X.Luo,Y.-N.Xia,andQ.-S. Zhu, “Incremental collaborative filtering recommender based on regularized matrix factorization,” Knowl. Based Syst., vol. 27, pp. 271–280, 2012.

26.    Jianlong Xu, Zibin Zhen, and Michael R. Lyu, “Web Service Personalized Quality of Service Prediction via Reputation-Based Matrix Factorization”, IEEE transactions on reliability, vol. 65, no.1, march 2016.

27.    Xin Luo et al., “Generating Highly Accurate Predictions for Missing QoS Data via Aggregating Nonnegative Latent Factor Models”, IEEE 2015.

28.    R.XuandI.Wunsch,D.,“Survey of clustering algorithms”, Neural Networks, IEEE Transactions on, 2005.

29.    Marin Silic, Goran Delac, and Sinisa Srbljic, “Prediction of Atomic Web Services Reliability for QoS-aware Recommendation”, IEEE, 2015.

30.    Y. Wang, W. M. Lively, and D. B. Simmons, “Web software traffic characteristics and failure prediction model selection,” J. Comp. Methods in Sci. and Eng., 2009.

31.    Y. Baryshnikov, E. Coffman, G. Pierre, D. Rubenstein, M. Squillante, and T. Yimwadsana, “Predictability of web-server traffic congestion,” Web Content Caching and Distribution, International Workshop on, 2005.

32.    M. Andreolini and S. Casolari, “Load prediction models in web based systems,” in International conference on Performance evaluation methodolgies and tools, ACM, 2006.

33.    Y.-T. Lee and K.-T. Chen, “Is server consolidation beneficial to mmorpg? a case study of world of warcraft,” in Cloud Computing, 2010 IEEE 3rd International Conference on, pp. 435–442, 2010.

34.    Viet-Hoang Le and Sung-Ryul Kim, “K-strings algorithm, a new approach based on Kmeans”, ACM 2015.

 

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9.

Authors:

Hameed R. M. Al-Mishmish, H. S. Al-Raweshidy

Paper Title:

Interface and Traffic Handover Mechanism in Multi-homed Mobile IP Node

Abstract:  Network Mobility is a relatively new networking concept aimed at improving the reliability and scalability of data communications within vehicles moving at high speed. The growing use of IP devices in portable applications has created the demand for mobility support for entire networks of IP devices. Users are expected to be connected to the internet from anywhere at any time this facilities will provide to own user to more than mobile devices, there are several mobile devices such as mobile phone, laptop and PDA and other type, all these devices could have multiple network interfaces, these interfaces enable mobile devices to maintain ongoing communication while its moving from one point to another.

Keywords: Mobile IP, IETF, Network Mobility, Network Simulator (NS2), Multi-homed node, Interface selection mechanism, Throughput, Delay, Jitter.

References:

1.       Hesham Soliman, “Mobile IPv6, mobility in wireless internet,” April 2004.
2.       C. Perkins, Ed. Internet Engineering Task Force (IETF), RFC 5944, 2010.

3.       Nicolas Montavont and Thomas Noel and Thierry Ernst, “Multihoming in Nested Mobile Networking”, IEEE Jan 2004.

4.       “Introduction to Mobile IP” Cisco IOS IP. 2001.

5.       Albert Cabellos-Aparicio, Jordi Domingo Pascual, “Load Balancing in Mobile IPv6’s Correspondent Networks with Mobility Agents” IEEE 2007.

6.       M. Suthar, A. Ranavadiya, and S. Patel “A survey paper on mobile IP,”International Journal for Scientific Research and Development. IJSRD,Vol. 2, pp. 655-658, 2014.

7.       Esraa Hassan Abdelhafiz Alsaied, Sayda Maowia Alshareef Modatheir “Performance Evaluation of Mobile IP with DSDV Routing Protocol using NS2” IEEE 2015.

8.       Noureen, Z. llyas, 1. Shahzadi, M. Iqbal, M. Shafiq and A. Irshad “Mobile IP issues and their potential solutions: an overview,” Advances in Computer Science: an International Journal. ACSlJ, Vol. 3, No. 07, pp. 106-114,2014.

9.       Younghwan Choi, Bongsoo Kim, Sang-Ha Kim, Minkyo In, and Seungyun Lee. “A Multihoming Mechanism to Support Network Mobility in Next Generation Networks”, IEEE Aug 2006.

10.    Hiroshi Esaki, “Multi-Homing and Multi-Path Architecture Using Mobile IP and NEMO Framework”, IEEE, 2004.

11.    Christer Åhlund, Robert Brännström and Arkady Zaslavsky, “A Multihoming approach to Mobile IP”, Luleå University of Technology, Skellefteå Campus, SE-931 87 Skellefteå, Sweden.

 

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10.

Authors:

M Indu, Kavitha K V

Paper Title:

A Varied Efficient Approach on Sketch Based Image Retrieval System

Abstract:   Especially with the vogue of touch screen devices, retrieval of images that match with a hand-drawn query sketch became a highly desirable feature. Since 1990s, query-by sketch has been an extensive study. Due to the lack of effective and efficient matching solutions they are still very challenging. Compared to face recognition, face photo recognition using face sketch is relatively a younger area. The exceptional triumph of search techniques have encouraged to revisit the problem and focused at solving the problem of sketch based image retrieval. To this end, a novel method is presented here which is as follows: for each image in the database feature extraction is carried out and edge correspondence metric is computed which will be stored. Similarly for the query sketch the same steps are repeated. For each value the query sketch searches for a match score. The database image with highest match score is the retrieved match against the query sketch from the face photo database. An optimized algorithm is also incorporated for images that are corrupted by various types of noises. This method can handle non-facial factors such as such as hair style, hairpins, and glasses. During investigation results show that the proposed method outperforms several state of-the-arts in terms of accuracy and running time.

Keywords:
 Face sketch synthesis, Feature vector, Edge correspondence metric, Sketch based image retrieval.


References:

1.       W. Zhao, R. Chellappa, A. Rosenfeld, and J. Phillips, “Face recognition: A literature survey,” ACM Comput. Surv., vol. 35, no. 4, pp. 399–458, 2003.
2.       Chalechale, G. Naghdy, and A. Mertins, “Edge image description using angular radial partitioning,” IEEE Proc.-Vis., Image Signal Process., vol. 151, no. 2, pp. 93–101, Apr. 2004.

3.       R. Uhl, N. da Vitoria Lobo, and Y. Kwon, “Recognizing police sketches of faces,” in Proc. IEEE Workshop Appl. Comput. Vis., 1994, pp. 129–137.

4.       J. W. Brahan, K. P. Lam, H. Chan, and W. Leung, “AICAMS—Artificial intelligence crime analysis and management system,” Applications and Innovations in Expert Systems V, J. Knowl. Based Syst., pp. 143–153, 1997.

5.       Turk, M. and Pentland, A., “Eigenfaces for recognition,” Journal of Cognitive Neuroscience 3(1), 71-86 (1991).

6.       Phillips, P., Scruggs, W., OToole, A., Flynn, P., Bowyer, K., Schott, C., and Sharpe, M., “Frvt 2006 and ice 2006 large-scale results,” in [NISTIR 7408], (2007).

7.       Gross, R., Baker, S., Matthews, I., and Kanade, T., “Face recognition across pose and illumination,” in [Handbook of Face Recognition], Li, S. Z. and Jain, A. K., eds., Springer-Verlag (2004).

8.       Wright, J., Yang, A. Y., Ganesh, A., Sastry, S. S., and Ma, Y., “Robust face recognition via sparse representation,” IEEE Trans. Pattern Analysis & Machine Intelligence 31(2), 210-227 (2009).

9.       Tang, X. and Wang, X., “Face sketch synthesis and recognition,” in [Proc. of IEEE International Conference on Computer Vision], 687-694 (2003).

10.    Tang, X. and Wang, X., “Face sketch recognition,” IEEE Trans. Circuits and Systems for Video Technology 14(1), 50-57 (2004).

11.    Liu, Q., Tang, X., Jin, H., Lu, H., and Ma, S., “A nonlinear approach for face sketch synthesis and recognition,” in [Proc. of IEEE Conference on Computer Vision & Pattern Recognition], 1005-1010 (2005).

12.    Wang, X. and Tang, X., “Face photo-sketch synthesis and recognition,” IEEE Trans. Pattern Analysis & Machine Intelligence 31, 1955-1967 (Nov. 2009).

13.    W. Konen, “Comparing facial line drawings with gray-level images: A case study on PHANTOMAS,” in Proc. Int. Conf. Artif. Neural Netw., 1996, pp. 727–734.

14.    Y. Gao and M. K. H. Leung, “Face recognition using line edge map,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 24, no. 6, pp. 764–779, Jun. 2002.

15.    G. Mackenzie, “Agent-based sketch recognition,” Ph.D. dissertation, Univ. Nottingham, Nottingham, U.K., 2003.

16.    D. Marr and E. Hildreth, Theory of edge detection”, Proc. Royal Society, London, 1980, pp.187-217.

17.    E. Argyle. “Techniques for edge detection,” Proc. IEEE, vol. 59, pp. 285-286, 1971.

18.    M Sudarshan, P Ganga Mohan and Suryakanth, V Gangashetty “Optimized Edge Detection Algorithm for Face Recognition”.

 

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11.

Authors:

Gailan Abdul Qadir, Hassan Ali Salman, Sabah Shehd Abdulabas

Paper Title:

Energy Ventilation Air Flow Electronic Meter

Abstract: The measurement of ventilation losses is one of several types in the energy balance of building, depends on nonlinear single slope type analog to digital convertor (NL-ADC), in this papera digital electronics method is described which is useful in measuring the ear flow via leakage per meter of length of windows and doors. The pressure difference signal is provided as an electrical voltage through appropriate transducer, the digital instrument receives the voltage and processes it together with input coming data of the living area geometry, the resulting readout is digital output number representing of the air flow in the building, the energy ventilation meter will be tested in two different room to measure energy conservation in building related to ventilation losses measurement.

Keywords:
 (NL-ADC), measurement, papera digital electronics, measurement. Appropriate transducer


References:

1.    J.F. kreider and F.Kreith,”” Solar energy Handbook”, 1981.
2.    Moran M.J. and Shapiro H.N. Fundamentals of Engineering Thermodynamics. Second edition. New York: John Wiley & Sons, 1992.

3.    William H. Hayt , Gerold W. Neudeck ” Electronic Circuit Analysis and Design”  2nd Edition, 1989.

4.    J. Chris Stratton, W.J.N Turner, Craig P. Wray, Iain S. Walker,”Measuring Residential Ventilation  System Airflows”,2012.

5.    Lian Zhang, Yu Feng Zhang,” Research on Heat Recovery Technology for Reducing the Energy Consumption of Dedicated Ventilation Systems: An Application to the Operating Model of a Laboratory”, Energies,4 January 2016.

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12.

Authors:

Vijay Kumar, Rakesh Kumar

Paper Title:

Optimal Analysis of Economic Load Dispatch using Artificial Intelligence Techniques

Abstract:  Applications of artificial intelligence to economic load dispatch problems are discussed in the paper. The fuelcost equation of a thermal plant is generally expressed as continuous quadratic equation. In real situations the fuel cost equations can be discontinuous. Continuous and discontinuous fuel cost equations are explained here as thermal palnts cost equation are continuous which are further a quadratic equation.GA technique used for 30 bus test system have continuous fuel cost equations. Various results compared with conservative quadratic programming methods to analyze superiority of the suggested artificial intelli-gence technique. A 10-generator system each with distributed areas is considered and particle swarm algorithm engaged to reduce the cost of generation. All obtained results compared with other conventional methods.

Keywords:
GA, ELD, PSO, Evolutionary methods


References:

1.       Jiang and S. Ertem, “Economic dispatch with non-monotonically  increasing incremental cost units and transmission system losses”, IEEE Transactions on Power Systems, vol. 10, no. 2, pp. 891-897, May 1995.
2.       H.W. Dommel, “Optimal power dispatch”, IEEE Transactions on Power Apparatus and Systems, PAS93 No. 3, pp. 820–830, 1974.

3.       N. Ramaraj and K. Nagappan, “Analytical method to optimize gen-eration schedule”, Journal of The Institution of Eng-neers (India), vol. 66, p 240, 1987.

4.       C.E. Lin and G.L. Vivianib, “Hierarchical Economic Dispatch of Piecewise Quadratic Cost Functions”, IEEE Transactions of PAS, vol.103, no 6, June, 1984.

5.       N. Ramaraj and R Rajaram, “Analytical approach to optimize genera-tion schedule of plant with multiple fuel options”, Journal of The Institution of Engineers (India), vol. 68, p 106, 1987

6.       N. Ramaraj and R Rajaram, “Analytical approach to optimize genera-tion schedule of plant with multiple fuel options”, Journal of The Institution of Engineers (India), vol. 68, p 106, 1987.

7.       J.V. Guttag, The Specification and Application to Program-ming of Abstract Data Types, Ph.D. Thesis, Dept. of Computer Science, Uni-versity of Toronto (1975).

8.       J.V. Guttag and J.J. Horning, “Formal Specification as a De-sign Tool,”Seventh ACM Symposium on Principles of Program-ming Languages, Las Vegas (1998), pp-2-9.

9.       J.V. Guttag, “Notes on Type Abstraction, Version 2,’’ IEEE Transac-tions on Software Engineering,pp-46-49, vol. SE-6, no. 1 (1980).

10.    C.A.R. Hoare, “An Axiomatic Basis for Computer Pro-gramming,”Communications of the ACM, vol. 12, no. 10 (1985).

11.    A.Igelais, “Proofs of Correctness of Data Representations,” Acta Informatica, pp- 56,vol. 1, no. 4 (2006).

12.    J. H. Holland, Adaptation in Natural and Artficial Systems, Univer-sityof Michigan Press, Ann Arbor, MI, 1975.S. Koziel and Z. Michalewicz, Evolutionary algorithms, homomorphous map-pings, and constrained parameter optimization, Evolutionary Computation 7(1), 19-44, 1999.

13.    T.S. Metcalfe, P. Charbonneau, Stellar structure modeling using a parallel genetic algorithm for objective global optimiza-tion, Journal of Computational Physics 185, 176-193, 2003.

14.    Z. Michalewicz, A Survey of Constraint Handling Tech-niques in Evolutionary Computation Methods, Evolutionary Pro-gramming, Vol.4, pp.135, 1995.Z. Michalewicz, Genetic algo-rithms + data structures =evolution pro-grams,Berlin,Springer,1996

 

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13.

Authors:

Arathy S. Mohan, M. Nazeer

Paper Title:

Experimental Investigation on the Properties of Gap Graded Aggregate Medium Strength Concrete

Abstract:   Concrete is a mixture of cementations material, aggregate, and water. Aggregate is commonly considered inert filler, which accounts for 60 to 80 percent of the volume and 70 to 85 percent of the weight of concrete. Thus concrete properties are highly affected by physical properties of its aggregate. The particle size distribution of coarse and fine aggregate (grading of aggregate) may have an effect on concrete behaviour. However, due to the inherent difficulties related to the characterization of fine sized particles, little research has been made to evaluate the effect of grading. In the present investigation, packing density of combined aggregate is considered as the criteria for aggregate gradation thus selecting four combinations of gap graded aggregate for making medium strength (M40) concrete mixes. The workability, density and strength results from these concrete mixes are finally compared with conventional concrete to propose a suitable aggregate gradation. Within the premises of this study, it is concluded that gap graded concrete, though of a relatively stiffer and drier mix, can be placed and finished without undue effort for the non-structural, massive construction works demand less workability wherein continuously graded concrete has been customarily used heretofore. A considerable saving in cement content, sand and notable improvements in mechanical properties are the realistically achievable advantages through the use of gap graded concrete. Good control and, above all, care in handling, so as to avoid segregation, are essential.

Keywords:  aggregate, gap graded, gradation, packing density

References:

1.       Quiroga, P. N. (2003)The Effect of the Aggregates Characteristics on the Performance ofPortland Cement Concrete, Doctoral Dessertation,The University of Texas at Austin.
2.       Elices, M. and C.G. Rocco (2008) Effect of Aggregate Size on the Fracture and Mechanical Properties of a Simple Concrete, Journal of Engineering Fracture Mechanics,75, 3839-3851.

3.       Ashraf, W. B. and  M. A. Noor (2011) Performance-Evaluation of Concrete Properties for Different Combined Aggregate Gradation Approaches, The Twelfth East Asia-Pacific Conference on Structural Engineering and Construction, 14, 2627-2634.

4.       Hilf, J. W. (1987) Rolled Concrete Dams Using GapGraded Aggregate, Journal of Construction Engineering and Management, 1, 27-33.

5.       Meddah, M.S., Zitouni, S. and S. Belaabes (2009) Effect of content and particle size distribution of coarse aggregate on the compressive strength of concrete, construction of building materials, 24, 505-518.

6.       Shetty, M. S., Concrete Technology, Ram Nagar, New Delhi, S. ChandPublications,2012.

7.       IS: 12269-1987- Specification for 53 Grade Ordinary Portland Cement, Bureau of Indian Standards, New Delhi, 2000.

8.       IS: 383-1970, Specification for Coarse and Fine Aggregate from Natural Sources for Concrete, Bureau of Indian Standards, New Delhi.

9.       IS: 10262-1982, Recommended guidelines for Concrete Mix Design, Bureau of Indian Standards, New Delhi, 2000.

10.    IS: 2386 (Part 1) –1963, Methods of Test for Aggregates for Concrete Part 1- Particle Size and Shape, Bureau of Indian Standards, New Delhi.

11.    Al-Sahawneh, E. I. (2015) A New Approach for the Determination of Tensile and Shear Strengths of Normal Weight Concrete, International organization of Scientific Research, 05, 38-48.

12.    IS: 516-1959,Method of Tests for Strength of Concrete, Bureau of Indian Standards, New Delhi, India.

13.    IS: 1199-1959, Methods of Sampling and Analysis of Concrete, Bureau of Indian Standards, New Delhi.

 

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14.

Authors:

Ambika P, Binu Rajan M.R

Paper Title:

Link Based Overlapping Community Detection and Medical Data Mining of Social Media for Cancer Prognosis

Abstract: Social media, ranging from personal messaging to live foras, is providing unlimited opportunities for patients to exchange their views on their experiences with drugs and devices. Here the aim is to understand the correlation between user posts and positive or negative judgment on drugs along with its side effects in cancer patients with particular emphasis on analysing the notion of community detection within this social network by analysing link properties. The proposed system is a two-step analysis framework where positive negative user sentiments are evaluated using data mining tools and techniques followed by identifying overlapping community structures (influential user modules) within the user forum. The two-way process utilizes the comments on internet message boards (cancer research forums) to infer the acceptance and effectiveness of a drug in cancer treatment and maps to the influential user within the network. In the first stage of the current study, opinion labels are developed about each drug based on opinion analysis from user posts and each word is given weightage per node using data mining tools. In the second stage, networks are built from the search results of the forum, a network ranking system reflecting the opinion formation about the drug is developed. Different from traditional algorithms based on node clustering, the proposed method is based on link clustering to discover overlapping communities. Since links usually represent unique relations among nodes, the link clustering will discover groups of links that have the same characteristics. The current approach effectively searches for different levels of organization within the networks and uncovers dense modules using partition density factor. Finally, the accuracy of novel link based overlapping community detection method is compared with the traditional network based community detection model using graph benchmark. Thus the experiment is used to determine opinion from consumer and identify influential users within the retrieved modules using information derived from both term occurrence and word frequency of data and network-based properties in an accurate way.

Keywords:
Community detection, Health Informatics, Multi-scale, Markovprocess, Modularity, Overlapping communities, Random walks, Social media, Stability.


References:

1.       Reza Zafarani, Mohammad Ali Abbasi,Huan Liu, “Social Media Mining An Introduction,”, April 2014.J. Cambridge university.
2.       Zhu,F., Patumcharoenpol, P., Zhang, C., Yang, Y., Chan, J., Meechai, A. et al, “Biomedical text mining and its applications in cancer research. “J. Biomed. Inform. 2013;46:200–211.

3.       David F. Nettleton,”Data mining of social networks represented as graphs,” Expert Systems with Application, October 2012

4.       G. Angulakshmi, Dr.R. Manicka Chezian,”An Analysis on Opinion Mining: Techniques and Tools”,Intrn. Journal of Advanced Research in Computer and Communication Engineering Vol. 3,Issue 7, July 2014

5.       Richa Sharma, Shweta Nigam and Rekha Jain,”Oinion mining of movie reviews at document level”, International Journal on Information Theory (IJIT), Vol.3, No.3, July 2014.

6.       WalaaM edhat a, Ahmed Hassan b, HodaKorashy,” Sentiment analysis algorithms and applications: A survey”, Ain Shams Engineering Journal (2014) ,Volume:5,Issue:4,pp: 1093–1113

7.       Vishal Shrivastava, Rajesh Boghey, BhupendraVerma,”A Framework for Improving Target Marketing Using Collaborative Data Mining Approach”, IJICT Journal, Volume 1 No. 2, June 2011

8.       LiseGetoor,” Link Mining: A New Data Mining Challenge,”UMIACS, 415- 444,Volume 4, Issue 2,2013

9.       Mohammad Al Hasan , Mohammed J. Zaki,”A Survey of Link Prediction in Social Networks”,Springer,March,2011

10.    P.Ambika, M.R BinuRajan, “Multi-scale Community Detection in Complex Networks,” IEEE International Conference on research Advances in Integrated Navigation System,2016.

11.    V.R. Nagarajan, Monisha.P.M” Extracting Knowledge from Social Media toImprove Health Informatics”IJARCC,Vol. 4, Issue 7, July 2015.

12.    Akay, A. Dragomir, and B. E. Erlandsson, “A novel data-mining approach leveraging social media to monitor consumer opinion of sitagliptin,” J. Biomed Health Inform. Vol: PP, Issue: 99.

13.    Akay, A. Dragomir, and B. E. Erlandsson, “Network-Based Modeling and Intelligent DataMining of Social Media for Improving CareVol:19, 2015

14.    J. Vesanto, J. Himberg, E. Alhoniemi, and J. Parhankangas, “Self-Organizing Map in MATLAB: The SOM Toolbox,” in Proc. Matlab DSP Conf., Espoo, Finland, 1999, pp. 35–40.

15.    Chuan Shi, Yanan Cai, Di Fu, Yuxiao Dong, Bin Wu, “A link clustering based overlapping community detection algorithm,” Data & Knowledge Engineering, Elsevier, vol. 87, pp. 394–404, May 2013.

16.    Le Yu,BinWu,Bai Wang,“LBLP :Link-Clustering-Based Approach for Overlapping Community Detection,” ISSN, Volume 18, pp387-397, Number 4, August 2013.

17.    Erwan Le Martelot , Chris Hankin, “Multi-scale community detection using stability optimisation,” International Journal of Web Based Communities, v.9 n.3, p.323-348, June 2013

18.    E. Le Martelot and C. Hankin, “Multi-scale community detection using stability as optimization criterion in a greedy algorithm,” Proceedings of the 2011 International. Conf. erence on Knowledge Discovery and Information Retrieval (KDIR 2011), Paris, France: SciTePress, Oct. 2011, pp. 216–225.

19.    Esuli ,A., Sebastian,F.,” SENTIWORDNET: A Publicly Available Lexical Resource for Opinion Mining, ”In: Proceedings of 3rd Conf. on Intrn. Language Resource and Evaluation,pp.417-422(2006)

20.    Design and Analysis of Computer Algorithms1,David M. Mount, CMSC 451

21.    Y.Y. Ahn, J.P. Bagrow, S. Lehmann, Link communities reveal multi-scale complexity in networks, Nature 466 (2010) 761–764.

22.    Fei Zhu, Preecha Patumcharoenpol, Cheng Zhanga, Yang Yang b, Jonathan Chan ,Asawin Meechai , Wanwipa Vongsangnak , Bairong Shen ,”Biomedical text mining and its applications in cancer research ,” Journal of Biomedical Informatics 46 (2013) 200–211

 

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15.

Authors:

Ambika Omana Menon, Sakuntala S. Pillai

Paper Title:

A Paradigm Shift from OFDM to WPMCM as the Preferred Multi-Carrier Modulation Technique

Abstract: As of now, Multi-Carrier modulation (MCM) is considered an effective technique for both wired and wireless communications. Studies have been done by different researchers in this area and analysis of the comparative advantages and disadvantages of the different options for multi-carrier modulation have been extensively done. The place of OFDM, which was once considered as a very strong candidate for multi-carrier modulation technique, has almost been taken over by its successor, WPMCM. This paper reviews the paradigm shift from OFDM to WPMCM as the preferred multi-carrier modulation technique.

Keywords:
 Multicarrier modulation, WPMCM, OFDM, Discrete Wavelet Packet Transform.


References:

1.       A multicarrier primer- John M.Cioffi
2.       D. Karamehmedović, M.K. Lakshmanan, H. Nikookar, “Performance Evaluation of WPMCM with Carrier Frequency Offset and Phase Noise”, Journal of communications, vol. 4, no. 7, August  2009

3.       Ove Edfors -Magnus Sandell Jan-jaap Van De Beek, Daniel Landstrom, Frank Sjoberg, “An introduction to orthogonal frequency division multiplexing”

4.       H. Umadevi, K.S. Gurumurthy, “OFDM Technique for Multi-carrier Modulation (MCM) Signaling” Journal of Emerging Trends in Engineering and Applied Sciences (JETEAS)
2 (5): 787-794

5.       D. Karamehmedović , Dr. H. Nikookar, M. K. Lakshmanan, “A Study of Synchronization Issues of Wavelet Packet based Multicarrier Modulation”

6.       S.Haykin, “Cognitive Radio: Brain-Empowered Wireless Communications‖”, IEEE JSAC, Vol.23, No.2, pp.201-220, February 2005

7.       J.Mitola, G.Q.Maguire, “Cognitive Radio: Making Software Radios More Personal”, IEEE Personal Communications, Vol.6, No.4, pp.13-18, August 1999

8.       Sobia Baig, Fasih-ud-Din Farrukh and M. Junaid Mughal, “Discrete Wavelet Multitone Modulation for ADSL & Equalization Techniques”, Intech Open Access Publisher, pp. 3-24

9.       A.Lindsay, “Wavelet Packet Modulation for Orthogonally Transmultiplexed Communications”, IEEE Transactions on Signal Processing, Vol.45, pp.1336-1339, May 1997

10.    Haleh Hosseini, Norsheila Fisal, Sharifah K. Syed-Yusof, “Wavelet Packet based Multicarrier Modulation for Cognitive UWB Systems”, Signal Processing – An International Journal (SPIJ), Volume (4): Issue (2)

 

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16.

Authors:

M. Sghiar

Paper Title:

Turbulent Functions and Solving the Navier-Stokes Equation by Fourier Series

Abstract: I give a resolution of the Navier-Stokes [2] equation by using the series of Fourier. Résumé: Je donne une résolution de l’équation de Navier-Stokes [2] par les séries de Fourier.

Keywords:
 Navier-Stokes, Fourier, Séries de Fourier.

References:

1.    Joseph Fourier, Théorie analytique de la chaleur, Firmin Didot Père et Fils (Paris-1822). Réédition Jacques Gabay, 1988 (ISBN 2-87647-046-2)
2. http://www.claymath.org/sites/default/files/navierstokes.pdf

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17.

Authors:

Alaa Ibrahim, Ibrahim Marouf

Paper Title:

Methods and Techniques of Conservation Process for the Heritage Building Walls

Abstract: The issue of the conservation of architectural heritage has been given much attention on the political, cultural and academic level due to the heritage values for being cultural wealth for the nations. However the remains and ruins of these properties come under threat due to the propagation of structural work resulting from industrial development and urbanization. Hence, it has become the responsibility of government institutions to ensure the protection and conservation of humanity’s cultural heritage. That’s in a manner which strikes a balance and ensures harmony between the preservation of cultural heritage and the changes required by social and economic developments. All efforts have to be exerted to fulfill these two objectives in a spirit of understanding, in a planned timely manner and employing efficient technologies. Therefore, the main aim of the research is to enhance and highlight the new techniques and methods that used for maintaining the heritage building’s walls that could achieve the execution of temporary and definitive works. The most used methods that have been successfully implemented for several years for conserving walls are wall grouting injection, Cintec anchoring system, Fiber reinforced polymers, using prestressed steel in buildings consolidation and scaffolding systems .The research methodology is following a qualitative approach through first, defining each technique and it’s details (eg, characteristics, way of execution ,advantages , disadvantages and case study) . Second, by analyzing, evaluating the techniques and ensure its efficiency. The implementation of these techniques requires skilled labors, not only at the execution process, but also in the planning stages. The main mission of the conservators of the restoration process is to select the technique that keeps the heritage value of the building without deteriorating the building characteristics, elements or historical materials. To sum up using these techniques with accurate and suitable implementation methods, resulted in conserving the values of the heritage buildings and could safely transform them to the next generations. (The researcher 2016)

Keywords:
Grouting injection, Cintec anchoring system, Fiber reinforced polymers, prestressed steel, Scaffolding systems.


References:

1.       Kate Clark. (2005). Conservation Planning Methodology search, Developing policies for the conservation of historic places. Columbia: Heritage branch.
2.       Asamer Ahmed. (2005). Master Thesis: Contemporary techniques in restoration of historical buildings. Cairo: Cairo University.

3.       Jack Gillon. (2001). CONSERVATION CHARTERS AND STANDARDS. Retrieved from http://ihbc.org.uk

4.       Webber Nodro.(2009). Cultural heritage and the law search. Africa: ICCROM.

5.       WORLD HERITAGE CENTRE. (2013). Operational Guidelines for the Implementation of the World Heritage Convention. France: UNESCO World Heritage Centre.

6.       Intergovernmental Committee.(2013). Operational Guidelines for the Implementation of the World Heritage Convention. France: UNITED NATIONS EDUCATIONAL, SCIENTIFIC AND CULTURAL ORGANISATION.

7.       ICOMOS. (2001). International Council on Monuments and Sites. Retrieved from http://www.icomos.org.

8.       The parliament. (2006). قانون رقم 144. Cairo: The parliament publishing center.

9.       Ashraf Ali. (2012). Master Thesis: Restoration of historic Islamic buildings and its compliance with international standards. Egypt: Faculty of engineering, Cairo University.

10.    Adel Saad. (2002).Master Thesis: اسس وقواعد ترميم المباني الاثريه بين النظريه والتطبيق. Cairo: Faculty of archaeology, Restoration department.

11.    Lisandra Miranda. (2014). DEFINITION AND EVALUATION OF A GROUT FOR CONSOLIDATION OF ANCIENT MASONRY . SEISMIC VULNERABILITY OF A “PLACA” BUILDING. Portugal: DECivil, Instituto Superior Técnico, Universidade de Lisboa.

12.    PJ materials Consultants, 2009, Restoration of a National Historic Site Building, Fredericton City Hall, New Brunswick. Retrieved from http://www.pjmc.org.

13.    Faloon.F Construction. (2015). Scientific paper:Cementitious Sock Anchors. United States: Faloon Construction Center.

14.    Ian Hume. (1997). Scaffolding and Temporary Works for Historic Buildings. Retrieved from http://www.buildingconservation.net

15.    Cestelli Guidio. (2015). Strengthening of buildings structures – therapy search  . Berlin: ETH Zürich, Rämistrasse 101, 8092 Zürich.

16.    Lorenzo Jurina. (2003). The structural consolidation of old massive structures search . Italy: Department of Structural Engineering.

17.    Federico M. Mazzolani. (2009). Refurbishment by steelwork search .: Department of Structural Analysis and Design, University of Naples, Naples, Italy “Federico II”

18.    Peter Cox. (2012).Scientific paper:Wall Stabilization, Aniseed Park, Manchester,  Broadway Business center.

 

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18.

Authors:

Md. Lutfor Rahman, Najmus Saquib Sifat, Md. Zakaria Rahman, M. Ali

Paper Title:

Thermal Performance Analysis of a Closed Loop Pulsating Heat Pipe without Insert and with Insert

Abstract:  In this paper, thermal performance of a Closed Loop Pulsating Heat Pipe (CLPHP) without insert and with insert inside the tube has been investigated. The effect of different parameters like working fluid, the filling ratio, inclination angle and the input heat load on the thermal performance has been analyzed thoroughly. In this study, CLPHP is made from long capillary copper tubes with inner diameter of 2.0 mm and outer diameter of 3.0 mm. The heat pipe is bent into eight U-turns and divided into three sections: evaporator section (50 mm), adiabatic section (120 mm) and condenser section (80 mm). Adiabatic section is maintained by using aluminum foil surrounded by appropriate insulation. An insert made of copper wire with diameter 0.5mm is used throughout the tube of all three sections. Methanol and Ethanol are used as working fluids with different filling ratio varied from 40% to 60% in steps of 10%. The thermal resistance has been investigated with different inclination angles (viz. 0°, 30°, 45° and 60° from vertical) at various heat input from 10 to 100W in the steps of 10W. The result shows that, the thermal resistance decreases as heat input increases. CLPHP with insert structure shows better performance than the CHPHP without insert structure particularly at 45°inclination angle. CLPHP without insert structure shows better performance than the CHPHP with insert structure at 00inclinations. Methanol with 40% filling ratio and Ethanol with 60% filling ratio shows the best performance at 0° inclination angle for CLPHP without insert structure. CLPHP with insert structure shows better performance than the CLPHP without insert structure at high heat input particularly at 45°inclination angle.

Keywords:
CLPHP, filling ratio, inclination angle, working fluid, insert structure and without insert structure, PHP, thermal resistance


References:

1.       G. F. Smyrnov and G. A. Savchenkov, (USSR Patent 504065), 1971.
2.       H. Akachi, Structure of a heat pipe, U.S. Patent Number 4921041, 1990.

3.       H. Akachi, F. Polasek and P. Stulc, Pulsating heat pipes, Proc.5th International Heat Pipe Symposium, pp. 208–217, Melbourne, Australia, 1996.

4.       Y. Zhang and A. Faghri, Advances and unsolved issues in in pulsating heat pipes, Copyright Taylor and Francis Group, LLC, Heat Transfer Engineering, 29(1):20–44, 2008, ISSN: 0145-7632 print / 1521-0537 on line DOI: 10.1080/01457630701677114.

5.       S. Maezawa, R. Nakajima, Gi K. and H. Akachi, Cooling of note book PC by oscillating heat pipe, in: 10th Int. Heat Pipe Conf., Vol. 3/4, Session F, Stuttgart, Germany, 1997.

6.       M. B. Shafii, A. Faghri and Y. Zhang, Thermal modeling of un looped and looped pulsating heat pipes, asme journal of heat transfer, Vol. 123, No. 6, pp. 1159- 1172, 2001.

7.       Zhang X. M., Xu, J. L., and Zhou, Z. Q., Experimental study of a pulsating heat pipe using fc-72, ethanol, and methanol as working fluids, experimental heat transfer, vol. 17, no. 1, pp. 47–67, 2004.

8.       P. Meena, S. Rittidech and P. Tammasaeng , Effect of inner diameter and inclination angles on operation limit of closed-loop oscillating heat-pipes with check valves, American Journal of Engineering and Applied Sciences, Vol. 1 (2), pp. 100-103,2008.

9.       P. Meena and S. Rittidech, Comparisons of heat transform performance of a CLOHP and CLOHP with check valves heat exchangers, American Journal of Applied Sciences 1(1): 7-11, 2008, ISSN 1941-7020.

10.    S. Rittidech P. Meena and P. Terdtoon, effect of evaporator lengths and ratio of check valves to number of turns on internal flow patterns of a closed–loop oscillating heat-pipe with check valves, American Journal of Applied Sciences 5 (3): 184-188, 2008 ISSN 1546-9239

11.    P. Meena, S. Rittidech and P. Tammasaeng, Effect of evaporator section lengths and working fluids on operational limit of closed loop oscillating heat pipes with check valves (CLOHP/CV), American Journal of Applied Sciences, Vol.6(1), pp.133-136,  ISSN 1546-9239, 2009.

12.    P. Charoensawan, S. Khandekar, Manfred Groll, and P. Terdtoon, Closed loop pulsating heat pipes, part a: parametric experimental investigations, Applied Thermal Engineering, Vol. 23, No.16, pp. 2009–2020, 2003.

13.    S. Khandekar, N. Dollinger and M. Groll, Understanding operational regimes of closed loop pulsating heat pipes: an experimental study, Applied Thermal Engineering, Vol.23, No.6, pp.707-719, 2003.

14.    Honghai Yang, S. Khandekar, M. Groll, Operational limit of closed loop pulsating heat pipes, Applied Thermal Engineering,  Vol.28 , pp.49–59, 2008.

15.    N. Panyoyai, P. Terdtoon and P. Sakulchangsatjatai, Effects of aspect ratios and number of meandering turns on performance limit of an inclined closed-loop oscillating heat pipe, Energy Research Journal, Vol. 1 (2), pp. 91-95, 2010.

16.    Dharmapal A Baitule1 and Pramod R Pachghare, Experimental analysis of closed loop pulsating heat pipe with variable filling ratio, Int. J. Mech. Eng. & Rob. Res. ISSN 2278 – 0149   www. ijmerr.com, Vol. 2, No. 3, July 2013.

17.    Bhawna Verma, Vijay Lakshmi Yadav and Kaushal Kumar Srivastava, Experimental studies on thermal performance of a pulsating heat pipe with methanol/di methanol, Journal of Electronics Cooling and Thermal Control, pp 27-34, 3 March 2013.

18.    R. Naik, V. Varadarajan , G. Pundarika and K. R. Narasimha, Experimental investigation and performance evaluation of a closed loop pulsating heat pipe, Journal of Applied Fluid Mechanics, Vol. 6, No. 2, pp. 267-275, 2013. ISSN 1735-3572, EISSN 1735-3645.

19.    E. R. Babu and  G. V. Gnanendra Reddy,  Effect of working fluid and filling ratio on performance of a closed loop pulsating heat pipe,  Journal of Engineering Science and Technology Vol. 11, No. 6 (2016) 872 – 880 © School of Engineering, Taylor’s University

20.    ANSI/ASME, Measurement Uncertainty, Report PTC 19.1- (1985, 1986)

 

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19.

Authors:

Rishikesh Mishra, Prashant Thakare, Shreyas Patil, Kartik Kannav, Nikunj Vitalkar

Paper Title:

VC-T Engine An Advancement in 4-Stroke Engine

Abstract: The most important challenge which the car manufacturers are facing today is to offer vehicles that deliver excellent fuel efficiency and superb performance while maintaining cleaner emissions and driving comfort. This paper deals with the VC-T (Variable Compression Turbo) engine technology which is going to be one of the advanced technology in the IC engine, and also deals with it’s working principle and it’s advantages. VC-T is the brand new technology in four cylinder petrol engine family. The VC-T engine is able to maximize it’s efficiency by running a higher compression ratio at idle or low speeds and boost performance by switching over to lower compression ratio under hard acceleration or heavy engine loads. The VC-T is able to adjust it’s compression ratio anywhere between it’s lower limit of 8:1 to higher limit of 14:1. According to Infiniti, the engine intrinsic smoothness allows it to achieve the NVH (Noise vibration & harshness) level similar to that of V6 engine. The paper rounds off with conclusions and an agenda for future research in this area.

Keywords:
 VC-T Engine, Compression ratio, Nissan Infiniti, Efficiency.


References:

1.    Tanaka, Y., Hiyoshi, R., Takemura, S., Ikeda, Y. et al. (2007) “A Study of a Compression Ratio Control
2.    Mechanism for a Multiple-Link Variable Compression Ratio Engine,” SAE Technical Paper 2007-01-3547 doi: 10.4271/2007-01-3547

3.    Hiyoshi, R., Aoyama, S., Takemura, S., Ushijima, K. et al. (2006) “A Study of a Multiple-link Variable Compression Ratio System for Improving Engine Performance,” SAE Technical Paper 2006-01-0616 doi: 10.4271/2006-01-0616

4.    Takahashi, N., Aoyama, S., Moteki, K., and Hiyoshi, R. (2005) “A Study Concerning the Noise and Vibration Characteristics of an Engine with Multiple-Link Variable Compression Ratio Mechanism,” SAE Technical Paper 2005-01-1134 doi: 10.4271/2005-01-1134

5.    M Ayaz Afsar, Mr Prafulla V. Pawar, Mr Prathik Dahule, Mr. S. Papinwar. “ Experimental investigation of direct air injection scavenged two stroke engine”. 2009 International symposium on computing, communication and control (ISCCC). Proc. Of CSIT vol.1 (2001). PP. 21-24.

 

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20.

Authors:

Vivian Brian Lobo, Nazneen Ansari, Annies Minu, Sehba Siddiqui, Flevina D’souza, Jeba Sangeetha Augestin

Paper Title:

Smartphone Selection using Analytic Hierarchy Process

Abstract: Analytic hierarchy process (AHP) is a measurement theory that is used to obtain ratio scales from distinct as well as continuous paired comparisons, and such comparisons can be selected from either tangible measurements or a basic scale that imitates virtual strength of feelings and predilections. AHP is a decision-making process that was developed by Prof. Thomas L. Saaty (1970), and it aims to quantify virtual significances for a given set of alternatives on a ratio scale—based on decision maker’s judgment—and focuses on the importance of instinctive decisions of both a decision maker and the steadiness of comparison of alternatives. AHP has been an instrument at the hands of decision makers since its discovery and is one of the widely used multicriteria decision-making methods. There have been some exceptional works that have been broadcasted based on AHP in various fields such as scheduling, best alternative selection, allocation of resources, conflict resolution, and optimization. AHP’s forte is its suppleness to be integrated with techniques such as linear programming and fuzzy logic that allows a user to excerpt benefits from all techniques and helps to achieve a desired goal. Similarly, we too use AHP to meet our desired goal. That is, in this study, we consider four smartphones (i.e., ph1, ph2, ph3, and ph4) and determine which smartphone is the best by considering numerous criteria such as cost, camera, internal memory, battery life, and style and generate a rank of alternatives using AHP.

Keywords:
analytic hierarchy process, battery life, camera, cost, criteria, internal memory, smartphone, style


References:

1.       T. L. Saaty, “Axiomatic foundation of the analytic hierarchy process,” Manage. Sci., vol. 32, no.7, 1986, pp. 841–855.
2.       B. G. Merkin, Group choice, John Wiley & Sons, 1979, N.Y.

3.       T. L. Saaty, “The analytic hierarchy process,” McGraw-Hill Book Co., 1980, N.Y.

4.       T. L. Saaty, “How to make a decision: The analytic hierarchy process,” Interfaces, vol. 24, 1994a, pp. 19–43.

5.       T. L. Saaty, “Fundamentals of decision making,” RWS Publications, Pittsburgh, 1994b, P.A.

6.       “The analytic hierarchy process—An exposition,” [Online] Available: https://business.highbeam.com/412157/article-1G1-93610861/analytical-hierarchy-process-exposition [Accessed on October 23, 2016].

7.       “The analytic hierarchy process—An exposition [Online] Available: http://www.johnsaunders.com/papers/ahpexpo.pdf [Accessed on October 23, 2016].

8.       E. H. Forman and M. A. Selly, “Decision by objectives: how to convince others that you are right,” World Scientific, 2001.

9.       http://shodhganga.inflibnet.ac.in/bitstream/10603/101833/11/11_chapter%201.pdf [Online] [Accessed on October 23, 2016].

10.    H. W. Brock, “The problem of “utility weights” in group preference aggregation,” Oper. Res., vol. 28, no. 1, 1980, pp. 176–187.

11.    R. L. Keeney, “A group preference axiomatization with cardinal utility,” Manage. Sci., vol. 23, no. 2, 1976, pp. 140–145.

12.    R. L. Keeney and C. W. Kirkwood, “Group decision making using cardinal social welfare functions,” Manage. Sci., vol. 22, no. 4, 1975, pp. 430–437.

13.    P. L. Yu, “A class of solutions for group decision problems,” Manage. Sci., vol. 19, no. 8, 1973, pp. 936–946.

14.    F. Chiclana, E. Herrera-Viedma, F. Herrera, and S. Alonso, “Some induced ordered weighted averaging operators and their use for solving group decision-making problems based on fuzzy preference relations.” Eur. J. Oper. Res., vol. 182, no. 1, 2007, pp. 383–399.

15.    H. Hsi-Mei and C. Chen-Tung, “Aggregation of fuzzy opinions under group decision making.” Fuzzy Set Syst., vol. 79, no. 3, 1996, pp. 279–285.

16.    C. Tan, “A multi-criteria interval-valued intuitionistic fuzzy group decision making with Choquet integral-based TOPSIS,” Expert Syst. Appl., vol. 38, no. 4, 2011, pp. 3023–3033.

17.    T. Tanino, “Fuzzy preference orderings in group decision making,” Fuzzy Set Syst., vol. 12, no. 2, 1984, pp. 117–131.

18.    Y. Dong, Y. Xu, and S. Yu, “Computing the numerical scale of the linguistic term set for the 2-tuple fuzzy linguistic representation model,” IEEE Trans. Fuzzy Syst., vol. 17, no. 6, 2009, pp. 1366–1378.

19.    E. Herrera-Viedma, L. Martinez, F. Mata, and F. Chiclana, “A consensus support system model for group decision-making problems with multigranular linguistic preference relations,” IEEE Trans Fuzzy Syst., vol. 13, no. 5, 2005, pp. 644–658.

20.    R. -C. Wang and S. -J. Chuu, “Group decision-making using a fuzzy linguistic approach for evaluating the flexibility in a manufacturing system,” Eur. J. Oper. Res., vol. 154, no. 3, 2004, pp. 563–572.

21.    Z. Wu and J. Xu, “A concise consensus support model for group decision making with reciprocal preference relations based on deviation measures,” Fuzzy Set Syst., vol. 206, 2012a, pp. 58–73.

22.    E. H. Forman and S. I. Gass, “The analytic hierarchy process—An exposition,” Oper. Res., vol. 49, no. 4, 2001, pp. 469–486.

23.    N. Subramanian and R. Ramanathan, “A review of applications of analytic hierarchy process in operations management,” Int. J. Prod. Econ., vol. 138, no. 2, 2012, pp. 215–241.

24.    O. S. Vaidya and S. Kumar, “Analytic hierarchy process: An overview of applications,” Eur. J. Oper. Res., vol. 169, no. 1, 2006, pp. 1–29.

25.    E. Forman and K. Peniwati, “Aggregating individual judgments and priorities with the analytic hierarchy process,” Eur. J. Oper. Res., vol. 108, no. 1, 1998, pp.
165–169.

26.    R. Ramanathan and L. S. Ganesh, “Group preference aggregation methods employed in AHP: An evaluation and an intrinsic process for deriving members’ weightages,” Eur. J. Oper. Res., vol. 79, no. 2, 1994, pp. 249–265.

27.    T. L. Saaty, “Fundamentals of decision making and priority theory with the analytic hierarchy process,” RWS Publications, Pittsburgh, 1994a.

28.    Y. Xu, K. W. Li, and H. Wang, “Distance-based consensus models for fuzzy and multiplicative preference relations,” Inform. Sciences, vol. 253, 2013, pp. 56–73.

29.    S. M. Lee, “Goal programming for decision analysis,” Philadelphia: Auerbach, 1972.

30.    R. L. Keeney and H. Raiffa, “Decisions with multiple objectives: Preferences and value tradeoffs,” New York: Wiley, 1976.

31.    T. L. Saaty, “A scaling method for priorities in hierarchical structures,” J. Math. Psychol., vol. 15, no. 3, 1977, pp. 234–281.

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33.    K. D. Lawerence and G. Kleinman (Eds.), “Applications of Management Science,” vol. 15, Emerald Group Publishing, 2012.

34.    D. Golmohammadi, “A decision making model for evaluating suppliers by multi-layer feed forward neural networks,” PeoQuest, 2007.

35.    M. J. Liberatore, B. R. Myers, R. L. Nydick, and H. J. Weiss, “Revisiting the ranking of outstanding professional sports records,” J. Sport. Anal., vol. 2, no. 1, 2016, pp. 1–18.

36.    J. S. Dyer, “Remarks on the analytic hierarchy process,” Manage. Sci., vol. 36, no. 3, 1990a, pp. 249–258.

37.    J. S. Dyer, “A clarification of ‘remarks on the analytic hierarchy process,”’ Manage. Sci., vol. 36, no. 3, 1990b, pp. 274–275.

38.    P. T. Harker and L. G. Vargas, “Reply to ‘remarks on the analytic hierarchy process’ by J. S. Dyer,” Manage. Sci., vol. 36, no. 3, 1990, pp. 269–273.

39.    T. L. Saaty, “An exposition of the AHP in reply to the paper ‘remarks on the analytic hierarchy process,”’ Manage. Sci., vol. 36, no. 3, 1990, pp. 259–268.

40.    R. L. Winkler, “Decision modeling and rational choice, AHP and utility theory,” Manage. Sci., vol. 36, no. 3, 1990, pp. 247–248.

41.    Expert Choice, Inc. Expert Choice for Windows, Version 9.0, Pittsburgh, 1995, P.A.

42.    B. L. Golden, E. A. Wasil, and P. T. Harker (eds.), “The analytic hierarchy process,” New York, Springier-Verlag, 1989.

43.    F. Zahedi, “The analytic hierarchy process—A survey of the method and its applications,” Interfaces, vol. 16, no. 4, 1986, pp. 96–108.

44.    L. G. Vargas and F. Zahedi (eds.), “Special issue on the analytic hierarchy process,” Math. Comput. Model., vol. 17, no. 4–5, 1993.

45.    E. A. Wasil and B. L. Golden (eds.), “Public sector applications of the analytic hierarchy process,” Socio. Econ. Plan. Sci., vol. 25, no. 2, 1991, pp. 87–88.

46.    F. A. Lootsma, “Saaty’s priority theory and the nomination of a senior professor in operations research,” Eur. J. Oper. Res., vol. 4, no. 6, 1980, pp. 380–388.

47.    T. L. Saaty and V. Ramanujam, “An objective approach to faculty promotion and tenure by the analytic hierarchy process,” Res. High. Educ., vol. 18, no. 3, 1983, pp. 311–331.

48.    M. D. Trout and S. K. Tadisina, “The analytic hierarchy process as a model base for a merit salary recommendation system,” Math. Comput. Model., vol. 16, no. 5, 1992, pp. 99–105.

49.    V. M. R. Tummala and P. P. Sanchez, “Evaluating faculty merit awards by analytic hierarchy process,” Model., Simulat. Control C: Environ., Biomed., Hum. Soc. Syst., vol. 11, no. 4, 1988, pp. 1–13.

50.    T. L. Saaty and L. R. Rogers, “Higher education in the United States (19852000): Scenario construction using a hierarchical framework with eigenvector weighting,” Socio. Econ. Plan. Sci., vol. 10, no. 6, 1976, pp. 251–263.

51.    Arbel, “A university budget problem: A priority-based approach,” Socio. Econ. Plan. Sci., vol. 17, no. 4, 1983, pp. 181–189.

52.    N. K. Kwak and C. B. Diminnie, “A goal programming model for allocating operating budgets of academic units,” Socio. Econ. Plan. Sci., vol. 21, no. 5, 1987, pp. 333–339.

53.    R. P. Hope and J. A. Sharpe, “The use of two planning decision support systems in combination for the redesign of an MBA information technology programme,” Computers and Oper. Res., vol. 16, no. 4, 1989, pp. 325–332.

54.    S. K. Tadisina and V. Bhasin, “Doctoral program selection using pairwise comparisons,” Res. High. Educ., vol. 30, no. 4, 1989, pp. 403–418.

55.    J. R. Canada, E. H. Frazelle, R. K. Roger, and E. MacCormac, “How to make a career choice: The use of the analytic hierarchy process,” Ind. Manage., vol. 27, no. 5, 1985, pp. 16–22.

56.    D. Anderson, “An introduction to Management Science: Quantitative approaches to decision making,” Publisher: Thomas R. Williams, 2003.

57.    D. R. Anderson, D. J. Sweeney, T. A. Williams, J. D. Camm, and R. K. Martin, “An introduction to Management Science: Quantitative approaches to decision making,” revised. Cengage Learning, 2011.

58.    F. G. M. Al-Azab and M. A. Ayu, “Web based multi criteria decision making using AHP method,” Int. Conf. Info. Comm. Tech. Muslim World (ICT4M), IEEE, 2010, pp. A6–A12.

59.    D. J. Jakóbczak, “Analyzing risk through probabilistic modeling in Operations Research,” October 2015, DOI: 10.4018/978-1-4666-9458-3.

60.    “Analytic hierarchy process [Wikipedia],” [Online] Available: https://en.wikipedia.org/wiki/Analytic_hierarchy_process [Accessed on October 23, 2016].

61.    F. P. G. Márquez and B. Lev (Eds.), Advanced Business Analytics, Springer, 2015.

62.    C. C. Frangos, K. C. Fragkos, I. Sotiropoulos, I. Manolopoulos, and E. Gkika, “Student preferences of teachers and course importance using the analytic hierarchy process model,” In Proc. World Congress on Eng. (WCE 2014), vol. 2, 2014.

 

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21.

Authors:

Prakash C. Sharma, Narendra S. Chaudhari

Paper Title:

Investigation of Satisfiability Based Solution Approach for Graph Coloring Problem

Abstract: Graph k-colorability (for k ≥ 3) problem (GCP) is a well-known NP-Complete problem. There are many approaches proposed to solve graph coloring problem till date. There is an alternative approach to solve it efficiently by Satisfiability which is first known NP-Complete problem. We can reduce any NP-complete problem to/from SAT. Reduction from graph k-colorability problem to satisfiability is an important concept to solve it using efficient SAT solver. In this paper, we are presenting a polynomial 3-SAT encoding technique for k colorable graph. Our formulation generates total (((k-2)*|V| ) + (k*|E|) ) clauses in 3-CNF for k-colorable graph. We tested our encoding formulation approach on different graph coloring instances of DIMACS[8][9] and then investigated the solution of graph coloring problem as a decision problem based on SAT approach using powerful SAT solver Minisat 2.2.

Keywords:
3-SAT, CNF, DNF, graph coloring, NP-Complete, k-colorable, chromatic number, DIMACS.


References:

1.       Prakash C Sharma and Narendra S Chaudhari, “Polynomial 3-SAT Encoding for K-Colorability of Graph”, IJCA Special Issue on Evolution in Networks and Computer Communications (1): 2011, pp 19-24
2.       Garey, M. R. and Johnson, D. S., Computers and Interactability: A Guide to the Theory of NP-Completeness, Freeman, San Francisco, 1979.

3.       S. A. Cook, “The Complexity of Theorm Proving Procedures,” in Proceeding of the ACM Symposium on the Theory of Computing, 2004, pp 151-158.

4.       Koen Claessen, Niklas Een, Mary Sheeran and Niklas Sorensson, “SAT-solving in practice”, Proceedings of the 9th International Workshop on Discrete Event Systems Goteborg, Sweden, pp 61-67,May 28-30, 2008.

5.       Prakash C. Sharma and Narendra S Chaudhari, “A graph coloring approach for channel assignment in cellular network via propositional satisfiability”, International Conference on Emerging Trends in Networks and Computer Communications (ETNCC) at Udaipur,  22-24 April 2011, pp 23-26

6.       Alexander Tsiatas, “Phase Transitions in Boolean Satisfiability and Graph Coloring”, May 2008, Department of Computer Science, Cornell University,(www.cseweb.ucsd.edu/users/atsiatas/phase.pdf).

7.       L. Adleman and K. Manders, “Reducibility, randomness and intractability (abstract)”, in STOC 77: Proceedings of the ninth annual ACM symposium on Theory of computing. New York NY, USA: ACM Press, 1977, pp. 151-163.

8.       DIMACS Implementation Challenges, http://dimacs.rutgers .edu/Challenges/

9.       Petersen graph, http://en.wikipedia.org/wiki/ Petersen _graph

10.    N. Een and N. Sorensson. An extensible sat solver. In Proc. of the 6th Int. Conference onTheory and Applications of Satisfiability Testing, 2003.

11.    N. Een and N. Sorensson. MiniSat v1.13 – A SAT Solver with Conict-Clause Minimization. System description for the SAT competition 2005.

12.    The MiniSAT page by Niklas Een and N Sorensson. http://minisat.se/

13.    MiniSAT User Guide: How to use the MiniSAT SAT Solver by David A. Wheeler. http://www.dwheeler.com/ essays/minisat-user-guide.html

14.    Computational Series: Graph Coloring and Its Generalizations, http://mat.gsia.cmu.edu/COLOR04.

15.    E. Malaguti, P. Toth, “A survey on vertex coloring problems”, International Transactions in Operational Research 17, 2010, pp 1–34.

16.    W.K Hale, “Frequency Assignment: Theory and Applications”, in IEEE Proceeding, Vol.68, no.12, 1980, pp. 1497-1514.

 

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Issue-5 June 2017

S. No

Volume-6 Issue-5, June 2017, ISSN:  2249-8958 (Online)
Published By: Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd. 

Page No.

1.

Authors:

Shubhangi Pandhare, Abhishek Gautam, Sayali Chavan, Shital Sungare

Paper Title:

Co-Operative Content Downloading Framework Over Cellular Network

Abstract: The multifold advancement over wireless communication has in a way, predicted to use smartphones, laptops, and tabs vastly for downloading purpose. But due to confined data transfer capacity, the statistics of downloading quantity approximately for a distinctive person is constrained and time taking for a high precision video. The co-operative content downloading framework will permit the requested joiners inside the network to download a section of the file independently. This may aid the potential to download the document with cost effectiveness and with a reduced time consumption component. The above mentioned framework will additionally trace the real process how the transfer speed (bandwidth) will be distributed within the joiners and one requestor. The entire framework will deliver the efficient utilization of bandwidth in specific environments.

Keywords:
 Segmentation, Cluster formation, Adhoc network, Sequencing.


References:

1.       Haibo Zhou, Student Member, IEEE, Bo Liu, Member, IEEE, Tom H. Luan, Member,, “ChainCluster: Engineering a Cooperative Content Distribution Framework for Highway Vehicular Communications”, IEEE transactions on intelligent transportation systems, 2014.
2.       Chao-Hsien Lee, Chung-Ming Huang, Senior Member, IEEE, Chia-Ching Yang, and Hsiao-Yu Lin,,“ The K-hop Cooperative Video Streaming Protocol Using H.264/SVC Over the Hybrid Vehicular Networks,” , IEEE TRANSACTIONS ON MOBILE COMPUTING, VOL. 13, NO. 6, JUNE 2014.

3.       Aarti R. Thakur,  Prof. Jagdish Pimple, “Performing vehicle to vehicle communication based on two tier approach with high security using aodv protocol in VANET”, 1) International Journal of Emerging Research in Management &Technology ISSN: 2278-9359 (Volume-3, Issue-7),July 2014

4.       J. Luo and D. Guo, “Neighbor discovery in wireless ad-hoc networks based on group testing,” in Proc. 46th Annu. Allerton Conf.Communication, Control, Computing, Urbana-Champaign, IL, USA Sep. 2008, pp. 791–797.

5.       R. Khalili, D. L. Goeckel, D. Towsley, and A. Swami, “Neighbor discovery with reception status feedback to transmitters,” in Proc. 29th IEEE Conf. INFOCOM, San Diego, CA, USA, Mar. 2010,pp. 2375–2383

6.       C.-M. Huang, C.-C. Yang, and H.-Y. Lin, “A K-hop bandwidth aggregation scheme for member-based cooperative transmission over vehicular networks,” in Proc. 17th IEEE ICPADS, Tainan, Taiwan, 2011, pp. 436–443.

7.       Nandan, S. Das, G. Pau, M. Gerla, and M. Y. Sanadidi, “Cooperative downloading in vehicular ad-hoc wireless networks,” in Proc. 2nd Annu. Conf. WONS, Washington, DC, USA, 2005 pp. 32–41

8.       M. F. Tsai, N. Chilamkurti, J. H. Park, and C. K. Shieh, “Multi-path transmission control scheme combining bandwidth aggregation and packet scheduling for real-time streaming in multi-path environment,” Instit. Eng. Technol. Commun., vol. 4, no. 8, pp. 937–945, 2010.

9.       M. Y. Hsieh, Y. M. Huang, and T. C. Chiang, “Transmission of layered video streaming via multi-path on ad-hoc networks,” Multimedia Tools Appl., vol. 34, no. 2, pp. 155–177, 2007.

10.    D. Fan, V. Le, Z. Feng, Z. Hu, and X. Wang, “Adaptive joint session scheduling for multimedia services in heterogeneous wireless networks, in Proc. 70th IEEE VTC, Anchorage, AK, USA, Sep. 2009, pp. 1–5.

11.    M. Li, Z. Yang, and W. Lou, “Codeon: Cooperative popular content distribution for vehicular networks using symbol level network coding,” IEEE J. Sel. Areas Commun., vol. 29, no. 1, pp. 223–235, Jan. 2011.

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2.

Authors:

Cini K.

Paper Title:

Value Based Reliability Evaluation of Primary Power Distribution System

Abstract: Distribution system reliability is concerned with the availability and quality of power supply at each customer’s service entrance. Analysis of customer failure statistics shows that failure in distribution system contribute as much as 90% towards the unavailability of supply to a load as compared with each part of electric systems. These statistics reinforces the need for reliability evaluation of distribution systems. In recent years with the advent of smart grids the significance of distribution system has enhanced because of the importance of co generation and distributed generation. The different causes and duration of failures are analysed season wise. The failure rate of the different feeders of the system under study was calculated and the reliable feeders were identified. Suggestions are given to improve the reliability of the feeders. This type of analysis will help the operation and maintenance engineers to maintain the quality service to the customers and schedule the maintenance services.  

Keywords:
Distribution Systems, Reliability Indices, Failure Rate, Availability.

References:
1.       Biyun Chen; Qianyi Chen “The whole-process reliability evaluation  of  power  system including generation, transmission, transformation and distribution” IEEE 5th International Conference on Electric Utility Deregulation and Restructuring and Power Technologies (DRPT), pp 482-487
2.       H. 2. Andrews, Laura, Samuel” Novel Power System Reliability Indices calculation method” 23rd International Conference on Electricity Distribution, Lyon  15-18, June .

3.       Roy Billinton and Peng Wang “ Distribution System Reliability Cost/worth analysis Using Analytical and sequential Simulation Techniques” IEEE transactions on power systems, Vol.13, No.4, November 1998,pp1245-1250.

4.       R. Billinton and J. E. Billinton, “Distribution System Reliability Indices”, IEEE Trans. on Power Delivery, Vol. 4, No. 1, Jan. 1989, pp. 561-568.

5.       Vito Longo ,Walter R. Puntel, “Evaluation of Distribution System Enhancements Using Value-Based Reliability Planning” Procedures IEEE Transactions on Power
systems, vol. 15, no. 3, august 2000.

6.       Billinton, R., and Allan, R. N., “Reliability Evaluation of Power Systems”,Pitman Books, New York and London, 1984.

7.       Billinton, R., “Evaluation of Reliability Worth in an Electric Power system”. Reliability Engineering and System Safety, Vol. 46, No. 1, 1994.

8.       Carlos Eduardo Paida Tenemaza “State of Art, Reliability In Electrical Distribution Systems Based On Markov Stochastic Model”  IEEE Latin America Transactions, Volume: 14, Issue: 2, pp 799-804.

9.       Farajollah Soudi and Kevin Tomsovic  “Optimal Trade-Offs in Distribution Protection Design” IEEE  transactions on power delivery, vol. 16, no. 2, April 2001.

10.    Amir Safdarian; Mohammad Farajollahi; Mahmud Fotuhi-Firuzabad “ Impacts of Remote Control Switch Malfunction on Distribution System Reliability” IEEE Transactions on Power Systems, Volume: 32, Issue: 2, 2017, pp 1572-1573.

11.    Siripha Junlakarn; Marija Ilić , “Distribution System Reliability Options and Utility Liability”  IEEE Transactions on Smart Grid , Volume: 5, Issue: 5, 2014, pp 2227-2234.

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3.

Authors:

S. L. Deshpande, D S Chaudhari

Paper Title:

Wireless Nodes Assisted Micro-Irrigation System: an IoT Approach

Abstract: Irrigation systems deployed with Wireless Sensor Network (WSN) while transforming them to Micro-Irrigation systems are emerging as fruitful solution to ongoing ground water crisis. Field parameters like soil moisture, temperature and humidity can be monitored taking help of sensor array and can be fed back to decision making control system. Organized parametric results can help the optimized use of the water. By using wireless communication and environmental energy harvesting techniques, sensor network can be made totally wireless. Internet of Things (IoT) is another emerging technology that goals to extend the application of internet from complex computational machines (computer) to the stand alone devices such as consumer electronics. Integrating IoT to WSN not only can provide remote access but also allow two distinct information systems to frequently collaborate and provide common services. Also the user can be provided with flexible interface like mobile application. The miniaturization in technology and even more reliable communication are the strongest suits of such sensor network. This paper reviews for various technologies to fulfil requirement of such application and the shows some system characteristics.

Keywords:
 WSN, IoT, Irrigation, Moisture, Humidity, Energy Harvesting, etc.


References:

1.       Basic Botany, Physiology, and Environmental Effects on Plant Growth, AZ master gardner manual, The University of Arizona, AZ, 1998.
2.       M. Morris. (2006). Soil Moisture Monitoring: Low-Cost Tools and Methods [Online]. Available FTP: attra.ncat.org Directory: attra-pub/PDF File: soil moisture.pdf

3.       Y. Kim, R. Evans and W. Iversen, “Remote Sensing and Control of an Irrigation System Using a Distributed Wireless Sensor Network,” in IEEE Transactions on Instrumentation and Measurement, vol. 57, pp. 1379ꟷ1387, July 2008.

4.       W. Wang and S. Cao, “Application Research on Remote Intelligent Monitoring System of Greenhouse Based on ZIGBEE WSN,” 2nd International Congress on Image and Signal Processing, Tianjin, pp. 1-5, 2009.

5.       Yu, Y. Cui, L. Zhang and S. Yang, “ZigBee Wireless Sensor Network in Environmental Monitoring Applications,” 5th International Conference on Wireless Communications, Networking and Mobile Computing, Beijing, pp. 1ꟷ5, 2009.

6.       Z. Rasin, H. Hamzah and M. Aras, “Application and evaluation of high power Zigbee based wireless sensor network in water irrigation control monitoring system,” IEEE Symposium on Industrial Electronics & Applications, Kuala Lumpur, pp. 548ꟷ551, 2009.

7.       M. Zorzi, A. Gluhak, S. Lange and A. Bassi, “From today’s INTRAnet of things to a future INTERnet of things: a wireless- and mobility-related view,” in IEEE Wireless Communications, vol. 17, no. 6, pp. 44-51, December 2010.

8.       G. Kortuem, F. Kawsar, V. Sundramoorthy and D. Fitton, “Smart objects as building blocks for the Internet of things,” in IEEE Internet Computing, vol. 14, no. 1, pp. 44-51, Jan.-Feb. 2010.

9.       K. Langendoen, A. Baggio and O. Visser, “Murphy loves potatoes: experiences from a pilot sensor network deployment in precision agriculture,” Proceedings 20th IEEE International Parallel & Distributed Processing Symposium, Rhodes Island, pp. 1ꟷ8, 2006.

10.    L. Li, H. Xiaoguang, C. Ke and H. Ketai, “The applications of WiFi-based Wireless Sensor Network in Internet of Things and Smart Grid,” 6th IEEE Conference on Industrial Electronics and Applications, Beijing, pp. 789-793, 2011

11.    M. Lee, J. Hwang and H. Yoe, “Agricultural Production System Based on IoT,” IEEE 16th International Conference on Computational Science and Engineering, Sydney, NSW, pp. 833-837, 2013.

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4.

Authors:

Sajith A.G, Hariharan S

Paper Title:

A Region based Active Contour Approach for Liver CT Image Analysis Driven by Local likelihood Image Fitting Energy

Abstract: Computer tomography images are widely used in the diagnosis of liver tumor analysis because of its faster acquisition and compatibility with most life support devices. Accurate image segmentation is very sensitive in the field of medical image analysis. Active contours plays an important role in the area of medical image analysis. It constitute a powerful energy minimization criteria for image segmentation. This paper presents a region based active contour model for liver CT image segmentation based on variational level set formulation driven by local likelihood image fitting energy. The neigh bouring intensities of image pixels are described in terms of Gaussian distribution. The mean and variances of intensities in the energy functional can be estimated during the energy minimization process. The updation of mean and variance guide the contour evolving toward tumor boundaries. Also this model has been compared with different active active contour models. Our results shows that the presented model achieves superior performance in CT liver image segmentation. 

Keywords:
Active Contours, Chan-Vese model, Level sets


References:

1.       Kass, M., Witkin, A., and Terzopoulos, D.: ‘Snakes: Active contour models’, International journal of computer vision, 1988, 1, (4), pp. 321-331
2.       Osher, S., and Sethian, J.A.: ‘Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations’, Journal of computational
physics, 1988, 79, (1), pp. 12-49

3.       Caselles, V., Kimmel, R., and Sapiro, G.: ‘Geodesic active contours’, International journal of computer vision, 1997, 22, (1), pp. 61-79

4.       Kimmel, R., Amir, A., and Bruckstein, A.M.: ‘Finding shortest paths on surfaces using level sets propagation’, IEEE Transactions on Pattern Analysis and Machine Intelligence, 1995, 17, (6), pp. 635-640

5.       Li, C., Xu, C., Gui, C., and Fox, M.D.: ‘Distance regularized level set evolution and its application to image segmentation’, IEEE transactions on image processing, 2010, 19, (12), pp. 3243-3254

6.       Malladi, R., Sethian, J.A., and Vemuri, B.C.: ‘Shape modeling with front propagation: A level set approach’, IEEE transactions on pattern analysis and machine intelligence, 1995, 17, (2), pp. 158-175

7.       Vasilevskiy, A., and Siddiqi, K.: ‘Flux maximizing geometric flows’, IEEE transactions on pattern analysis and machine intelligence, 2002, 24, (12), pp. 1565-1578

8.       Xu, C., and Prince, J.L.: ‘Snakes, shapes, and gradient vector flow’, IEEE Transactions on image processing, 1998, 7, (3), pp. 359-369

9.       Chan, T.F., and Vese, L.A.: ‘Active contours without edges’, IEEE Transactions on image processing, 2001, 10, (2), pp. 266-277

10.    Cremers, D., Rousson, M., and Deriche, R.: ‘A review of statistical approaches to level set segmentation: integrating color, texture, motion and shape’, International journal of computer vision, 2007, 72, (2), pp. 195-215

11.    He, L., Peng, Z., Everding, B., Wang, X., Han, C.Y., Weiss, K.L., and Wee, W.G.: ‘A comparative study of deformable contour methods on medical image segmentation’, Image and Vision Computing, 2008, 26, (2), pp. 141-163

12.    Li, C., Huang, R., Ding, Z., Gatenby, J.C., Metaxas, D.N., and Gore, J.C.: ‘A level set method for image segmentation in the presence of intensity inhomogeneities with application to MRI’, IEEE Transactions on Image Processing, 2011, 20, (7), pp. 2007-2016

13.    Li, C., Kao, C.-Y., Gore, J.C., and Ding, Z.: ‘Minimization of region-scalable fitting energy for image segmentation’, IEEE transactions on image processing, 2008, 17, (10), pp. 1940-1949

14.    Paragios, N., and Deriche, R.: ‘Geodesic active regions and level set methods for supervised texture segmentation’, International Journal of Computer Vision, 2002, 46, (3), pp. 223-247

15.    Ronfard, R.: ‘Region-based strategies for active contour models’, International journal of computer vision, 1994, 13, (2), pp. 229-251

16.    Samson, C., Blanc-Féraud, L., Aubert, G., and Zerubia, J.: ‘A variational model for image classification and restoration’, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2000, 22, (5), pp. 460-472

17.    Tsai, A., Yezzi, A., and Willsky, A.S.: ‘Curve evolution implementation of the Mumford-Shah functional for image segmentation, denoising, interpolation, and magnification’, IEEE transactions on Image Processing, 2001, 10, (8), pp. 1169-1186

18.    Vese, L.A., and Chan, T.F.: ‘A multiphase level set framework for image segmentation using the Mumford and Shah model’, International journal of computer vision, 2002, 50, (3), pp. 271-293

19.    Li, C., Kao, C.-Y., Gore, J.C., and Ding, Z.: ‘Implicit active contours driven by local binary fitting energy’, in Editor (Ed.)^(Eds.): ‘Book Implicit active contours
driven by local binary fitting energy’ (IEEE, 2007, edn.), pp. 1-7

20.    Wang, L., He, L., Mishra, A., and Li, C.: ‘Active contours driven by local Gaussian distribution fitting energy’, Signal Processing, 2009, 89, (12), pp. 2435-2447

21.    Zhang, K., Song, H., and Zhang, L.: ‘Active contours driven by local image fitting energy’, Pattern recognition, 2010, 43, (4), pp. 1199-1206

22.    Mumford, D., and Shah, J.: ‘Optimal approximations by piecewise smooth functions and associated variational problems’, Communications on pure and applied mathematics, 1989, 42, (5), pp. 577-685

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5.

Authors:

Ogundare A.B, Ihiovi M.M

Paper Title:

Design of a 3 Phase Automatic Change-Over Switch using a PIC Microcontroller (PIC16F877A)

Abstract: Change over process involves switching electrical load from one power source to another, when the load is powered by two alternative sources (main utility and stand by generator). The process can be complex if it involves starting and stopping of source like generator and monitoring of mains. This paper presents a method to ease this rigorous process. A 3 phase automatic change over which uses generator control mechanism is designed to select between two available sources of power in this case, generator and utility with preference to the utility. The system monitors the utility mains supply and checks for complete failure as well as phase failure upon which it automatically start the generator, run it on idle for a minute, then switch the load to it. The system keeps monitoring the utility source for power restoration, it also monitor the generator output for failure upon any of which it switches back the load to utility supply and automatically switch off the generator. Once power is restored, the system delays for two minute before transferring the load to the utility supply. Success was recorded as the above processes were automated. This was achieved with the combination of discrete electrical and electronics components

Keywords:
 Electrical Load, Utility, Generator, Electrical and Electronics Components.


References:

1.       Ahmed M.S., Mohammed A.S. and Agusiobo O.B. (2006) ‘’Development of a Single Phase Automatic Change-Over Switch’’. AU J.T. 10(1): 68-74. Federal University of Technology Minna, Nigeria. (Jul. 2006)
2.       Amos, S.W. and James, M. (1981). Principles of transistor circuit: Introduction to the design of amplifiers, receivers and digital circuits. 6th ed., Hartnolls ltd., bodmin.UK.

3.       Atser A. Roy et-al, (2014). Design and Implementation of a 3-Phase Automatic Power Change-over Switch. e-ISSN : 2320-0847 p-ISSN : 2320-0936 Volume-3, Issue-9, pp-07-14

4.       Ezema L.S., Peter B.U., Harris O.O. (2012). Design of automatic change over switch with Generator control mechanism. SAVAP international.

5.       L.S. Ezema et-al, (2012). Design of Automatic Change Over Switch with Generator Control Mechanism. ISSN-L: 2223-9944. Vol.3, No.3, November 2012.

6.       Faissler, W.L. (1991). An introduction to modern Electronics, Willey, New York, NY, USA.

7.       Horowitz, P. and Winfield, H. (2002). The Art of Electronics, 2nd ed. Cambridge Univ. Press, Cambridge, UK

8.       Owen, B. (1995). Beginner’s Guide to Electronics 4th Ed. A Newness Technical Book, McGraw-Hill Companies Inc. New York, N.Y, USA.

9.       Oduobuk, E. J. et-al (2014). Design and Implementation of Automatic Three Phase Changer over Using LM324 Quad Integrated Circuit. International Journal of
Engineering and Technology Research Vol. 2, No. 4, April 2014, pp. 1 – 15, ISSN: 2327 – 0349.

10.    Rocks G. and Mazur G., (1993). Electrical motor controls. American Technical Publication, New-York, N.Y, USA.

11.    Ragnar, H. (1958). Electric Contacts Handbook. 3rd Edition, Springer-Verlag, Berlin/ Göttingen /Heidelberg. pp. 331-342.

12.    Theraja, B.L.; and Theraja, A.K. 2002. Electrical Technology, 21st ed. Ranjendra Ravida, New Delhi, India.

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6.

Authors:

Pooja C.S, K. R. Prassana Kumar 

Paper Title:

Survey on Load Balancing and Auto Scaling techniques for cloud Environment

Abstract: Cloud computing became now first choice and priority for every person who access the internet, one of the advantageous features of cloud computing is its scalability and flexibility. Auto scaling offers the facility to the individuals to scale up and scale down the resources as per their requirements, using only the needed resouce and paying for what they have used i.e “pay-as-you-use”. As everything take place in automatic manner, so human involvement errors are less and reduce the manpower and costs. so to make use of elasticity user must use auto scaling technique that balances the incoming workload, and reduce the total cost and maintain the Service Level Agreement (SLA).In this work main ideas revolve around the problems in scalable cloud computing systems. In modern days, management of resources is in boom and most talked topic in cloud environment. we present some of the existing load balancing policies and about Autoscaling categories.

Keywords:
cloud computing, scaling, auto scaling, load balancing.


References:

1.    Fang Liu, Jin Tong, Jian Mao, Robert Bohn, John Messina, Lee Badger and Dawn Leaf,”NIST Cloud Computing Reference Architecture”, NIST Special Publication 500-292, September 2011.
2.    M.Kriushanth, L. Arockiam and G. JustyMirobi,”Auto Scaling in Cloud Computing: An Overview”, International Journal of Advanced Research in Computer and Communication Engineering Vol. 2, Issue 7, July 2013, ISSN (Print): 2319-5940,ISSN (Online) : 2278-1021.

3.    Tania Lorido-Botran, Jose Miguel-Alonso , Jose A. Lozano, “A Review of Auto-scaling Techniques for Elastic Applications in Cloud Environments”, ARTICLE in JOURNAL OF GRID COMPUTING DECEMBER 2014, Impact Factor: 1.51 • DOI: 10.1007/s10723-014-9314-7.

4.    ChenhaoQu, Rodrigo N. Calheiros, and RajkumarBuyya,”A Reliable and Cost-Ecient Auto-Scaling System for Web Applications Using Heterogeneous Spot Instances”, Cloud Computing and Distributed Systems (CLOUDS) Laboratory, Department of Computing and Information Systems, The University of Melbourne, Australia, September 17, 2015.

5.    Gunpriya Makkar, Pankaj Deep Kaur,”A Review of Load Balancing in Cloud Computing”, Guru Nanak Dev University, Jalandhar, India, Volume 5, Issue 4, 2015 ISSN: 2277 128X.

6.    Priyanka P. Kukade and Geetanjali Kale “Survey of Load Balancing and Scaling approaches in cloud” vol.4 Feb 2015.

7.    Ashalatha R Evaluation of Auto Scaling and Load Balancing Features in Cloud” vol.117 may 2015.

8.    Dr. D .Ravindran, Ab Rashid Dar loud Based Resource Management with Autoscaling vol.2 .

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2.

Authors:

Cini K.

Paper Title:

Value Based Reliability Evaluation of Primary Power Distribution System

Abstract: Distribution system reliability is concerned with the availability and quality of power supply at each customer’s service entrance. Analysis of customer failure statistics shows that failure in distribution system contribute as much as 90% towards the unavailability of supply to a load as compared with each part of electric systems. These statistics reinforces the need for reliability evaluation of distribution systems. In recent years with the advent of smart grids the significance of distribution system has enhanced because of the importance of co generation and distributed generation. The different causes and duration of failures are analysed season wise. The failure rate of the different feeders of the system under study was calculated and the reliable feeders were identified. Suggestions are given to improve the reliability of the feeders. This type of analysis will help the operation and maintenance engineers to maintain the quality service to the customers and schedule the maintenance services.  

Keywords:
Distribution Systems, Reliability Indices, Failure Rate, Availability.

References:
1.       Biyun Chen; Qianyi Chen “The whole-process reliability evaluation  of  power  system including generation, transmission, transformation and distribution” IEEE 5th International Conference on Electric Utility Deregulation and Restructuring and Power Technologies (DRPT), pp 482-487
2.       H. 2. Andrews, Laura, Samuel” Novel Power System Reliability Indices calculation method” 23rd International Conference on Electricity Distribution, Lyon  15-18, June .

3.       Roy Billinton and Peng Wang “ Distribution System Reliability Cost/worth analysis Using Analytical and sequential Simulation Techniques” IEEE transactions on power systems, Vol.13, No.4, November 1998,pp1245-1250.

4.       R. Billinton and J. E. Billinton, “Distribution System Reliability Indices”, IEEE Trans. on Power Delivery, Vol. 4, No. 1, Jan. 1989, pp. 561-568.

5.       Vito Longo ,Walter R. Puntel, “Evaluation of Distribution System Enhancements Using Value-Based Reliability Planning” Procedures IEEE Transactions on Power
systems, vol. 15, no. 3, august 2000.

6.       Billinton, R., and Allan, R. N., “Reliability Evaluation of Power Systems”,Pitman Books, New York and London, 1984.

7.       Billinton, R., “Evaluation of Reliability Worth in an Electric Power system”. Reliability Engineering and System Safety, Vol. 46, No. 1, 1994.

8.       Carlos Eduardo Paida Tenemaza “State of Art, Reliability In Electrical Distribution Systems Based On Markov Stochastic Model”  IEEE Latin America Transactions, Volume: 14, Issue: 2, pp 799-804.

9.       Farajollah Soudi and Kevin Tomsovic  “Optimal Trade-Offs in Distribution Protection Design” IEEE  transactions on power delivery, vol. 16, no. 2, April 2001.

10.    Amir Safdarian; Mohammad Farajollahi; Mahmud Fotuhi-Firuzabad “ Impacts of Remote Control Switch Malfunction on Distribution System Reliability” IEEE Transactions on Power Systems, Volume: 32, Issue: 2, 2017, pp 1572-1573.

11.    Siripha Junlakarn; Marija Ilić , “Distribution System Reliability Options and Utility Liability”  IEEE Transactions on Smart Grid , Volume: 5, Issue: 5, 2014, pp 2227-2234.

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3.

Authors:

S. L. Deshpande, D S Chaudhari

Paper Title:

Wireless Nodes Assisted Micro-Irrigation System: an IoT Approach

Abstract: Irrigation systems deployed with Wireless Sensor Network (WSN) while transforming them to Micro-Irrigation systems are emerging as fruitful solution to ongoing ground water crisis. Field parameters like soil moisture, temperature and humidity can be monitored taking help of sensor array and can be fed back to decision making control system. Organized parametric results can help the optimized use of the water. By using wireless communication and environmental energy harvesting techniques, sensor network can be made totally wireless. Internet of Things (IoT) is another emerging technology that goals to extend the application of internet from complex computational machines (computer) to the stand alone devices such as consumer electronics. Integrating IoT to WSN not only can provide remote access but also allow two distinct information systems to frequently collaborate and provide common services. Also the user can be provided with flexible interface like mobile application. The miniaturization in technology and even more reliable communication are the strongest suits of such sensor network. This paper reviews for various technologies to fulfil requirement of such application and the shows some system characteristics.

Keywords:
 WSN, IoT, Irrigation, Moisture, Humidity, Energy Harvesting, etc.


References:

1.       Basic Botany, Physiology, and Environmental Effects on Plant Growth, AZ master gardner manual, The University of Arizona, AZ, 1998.
2.       M. Morris. (2006). Soil Moisture Monitoring: Low-Cost Tools and Methods [Online]. Available FTP: attra.ncat.org Directory: attra-pub/PDF File: soil moisture.pdf

3.       Y. Kim, R. Evans and W. Iversen, “Remote Sensing and Control of an Irrigation System Using a Distributed Wireless Sensor Network,” in IEEE Transactions on Instrumentation and Measurement, vol. 57, pp. 1379ꟷ1387, July 2008.

4.       W. Wang and S. Cao, “Application Research on Remote Intelligent Monitoring System of Greenhouse Based on ZIGBEE WSN,” 2nd International Congress on Image and Signal Processing, Tianjin, pp. 1-5, 2009.

5.       Yu, Y. Cui, L. Zhang and S. Yang, “ZigBee Wireless Sensor Network in Environmental Monitoring Applications,” 5th International Conference on Wireless Communications, Networking and Mobile Computing, Beijing, pp. 1ꟷ5, 2009.

6.       Z. Rasin, H. Hamzah and M. Aras, “Application and evaluation of high power Zigbee based wireless sensor network in water irrigation control monitoring system,” IEEE Symposium on Industrial Electronics & Applications, Kuala Lumpur, pp. 548ꟷ551, 2009.

7.       M. Zorzi, A. Gluhak, S. Lange and A. Bassi, “From today’s INTRAnet of things to a future INTERnet of things: a wireless- and mobility-related view,” in IEEE Wireless Communications, vol. 17, no. 6, pp. 44-51, December 2010.

8.       G. Kortuem, F. Kawsar, V. Sundramoorthy and D. Fitton, “Smart objects as building blocks for the Internet of things,” in IEEE Internet Computing, vol. 14, no. 1, pp. 44-51, Jan.-Feb. 2010.

9.       K. Langendoen, A. Baggio and O. Visser, “Murphy loves potatoes: experiences from a pilot sensor network deployment in precision agriculture,” Proceedings 20th IEEE International Parallel & Distributed Processing Symposium, Rhodes Island, pp. 1ꟷ8, 2006.

10.    L. Li, H. Xiaoguang, C. Ke and H. Ketai, “The applications of WiFi-based Wireless Sensor Network in Internet of Things and Smart Grid,” 6th IEEE Conference on Industrial Electronics and Applications, Beijing, pp. 789-793, 2011

11.    M. Lee, J. Hwang and H. Yoe, “Agricultural Production System Based on IoT,” IEEE 16th International Conference on Computational Science and Engineering, Sydney, NSW, pp. 833-837, 2013.

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4.

Authors:

Sajith A.G, Hariharan S

Paper Title:

A Region based Active Contour Approach for Liver CT Image Analysis Driven by Local likelihood Image Fitting Energy

Abstract: Computer tomography images are widely used in the diagnosis of liver tumor analysis because of its faster acquisition and compatibility with most life support devices. Accurate image segmentation is very sensitive in the field of medical image analysis. Active contours plays an important role in the area of medical image analysis. It constitute a powerful energy minimization criteria for image segmentation. This paper presents a region based active contour model for liver CT image segmentation based on variational level set formulation driven by local likelihood image fitting energy. The neigh bouring intensities of image pixels are described in terms of Gaussian distribution. The mean and variances of intensities in the energy functional can be estimated during the energy minimization process. The updation of mean and variance guide the contour evolving toward tumor boundaries. Also this model has been compared with different active active contour models. Our results shows that the presented model achieves superior performance in CT liver image segmentation. 

Keywords:
Active Contours, Chan-Vese model, Level sets


References:

1.       Kass, M., Witkin, A., and Terzopoulos, D.: ‘Snakes: Active contour models’, International journal of computer vision, 1988, 1, (4), pp. 321-331
2.       Osher, S., and Sethian, J.A.: ‘Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations’, Journal of computational
physics, 1988, 79, (1), pp. 12-49

3.       Caselles, V., Kimmel, R., and Sapiro, G.: ‘Geodesic active contours’, International journal of computer vision, 1997, 22, (1), pp. 61-79

4.       Kimmel, R., Amir, A., and Bruckstein, A.M.: ‘Finding shortest paths on surfaces using level sets propagation’, IEEE Transactions on Pattern Analysis and Machine Intelligence, 1995, 17, (6), pp. 635-640

5.       Li, C., Xu, C., Gui, C., and Fox, M.D.: ‘Distance regularized level set evolution and its application to image segmentation’, IEEE transactions on image processing, 2010, 19, (12), pp. 3243-3254

6.       Malladi, R., Sethian, J.A., and Vemuri, B.C.: ‘Shape modeling with front propagation: A level set approach’, IEEE transactions on pattern analysis and machine intelligence, 1995, 17, (2), pp. 158-175

7.       Vasilevskiy, A., and Siddiqi, K.: ‘Flux maximizing geometric flows’, IEEE transactions on pattern analysis and machine intelligence, 2002, 24, (12), pp. 1565-1578

8.       Xu, C., and Prince, J.L.: ‘Snakes, shapes, and gradient vector flow’, IEEE Transactions on image processing, 1998, 7, (3), pp. 359-369

9.       Chan, T.F., and Vese, L.A.: ‘Active contours without edges’, IEEE Transactions on image processing, 2001, 10, (2), pp. 266-277

10.    Cremers, D., Rousson, M., and Deriche, R.: ‘A review of statistical approaches to level set segmentation: integrating color, texture, motion and shape’, International journal of computer vision, 2007, 72, (2), pp. 195-215

11.    He, L., Peng, Z., Everding, B., Wang, X., Han, C.Y., Weiss, K.L., and Wee, W.G.: ‘A comparative study of deformable contour methods on medical image segmentation’, Image and Vision Computing, 2008, 26, (2), pp. 141-163

12.    Li, C., Huang, R., Ding, Z., Gatenby, J.C., Metaxas, D.N., and Gore, J.C.: ‘A level set method for image segmentation in the presence of intensity inhomogeneities with application to MRI’, IEEE Transactions on Image Processing, 2011, 20, (7), pp. 2007-2016

13.    Li, C., Kao, C.-Y., Gore, J.C., and Ding, Z.: ‘Minimization of region-scalable fitting energy for image segmentation’, IEEE transactions on image processing, 2008, 17, (10), pp. 1940-1949

14.    Paragios, N., and Deriche, R.: ‘Geodesic active regions and level set methods for supervised texture segmentation’, International Journal of Computer Vision, 2002, 46, (3), pp. 223-247

15.    Ronfard, R.: ‘Region-based strategies for active contour models’, International journal of computer vision, 1994, 13, (2), pp. 229-251

16.    Samson, C., Blanc-Féraud, L., Aubert, G., and Zerubia, J.: ‘A variational model for image classification and restoration’, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2000, 22, (5), pp. 460-472

17.    Tsai, A., Yezzi, A., and Willsky, A.S.: ‘Curve evolution implementation of the Mumford-Shah functional for image segmentation, denoising, interpolation, and magnification’, IEEE transactions on Image Processing, 2001, 10, (8), pp. 1169-1186

18.    Vese, L.A., and Chan, T.F.: ‘A multiphase level set framework for image segmentation using the Mumford and Shah model’, International journal of computer vision, 2002, 50, (3), pp. 271-293

19.    Li, C., Kao, C.-Y., Gore, J.C., and Ding, Z.: ‘Implicit active contours driven by local binary fitting energy’, in Editor (Ed.)^(Eds.): ‘Book Implicit active contours
driven by local binary fitting energy’ (IEEE, 2007, edn.), pp. 1-7

20.    Wang, L., He, L., Mishra, A., and Li, C.: ‘Active contours driven by local Gaussian distribution fitting energy’, Signal Processing, 2009, 89, (12), pp. 2435-2447

21.    Zhang, K., Song, H., and Zhang, L.: ‘Active contours driven by local image fitting energy’, Pattern recognition, 2010, 43, (4), pp. 1199-1206

22.    Mumford, D., and Shah, J.: ‘Optimal approximations by piecewise smooth functions and associated variational problems’, Communications on pure and applied mathematics, 1989, 42, (5), pp. 577-685

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5.

Authors:

Ogundare A.B, Ihiovi M.M

Paper Title:

Design of a 3 Phase Automatic Change-Over Switch using a PIC Microcontroller (PIC16F877A)

Abstract: Change over process involves switching electrical load from one power source to another, when the load is powered by two alternative sources (main utility and stand by generator). The process can be complex if it involves starting and stopping of source like generator and monitoring of mains. This paper presents a method to ease this rigorous process. A 3 phase automatic change over which uses generator control mechanism is designed to select between two available sources of power in this case, generator and utility with preference to the utility. The system monitors the utility mains supply and checks for complete failure as well as phase failure upon which it automatically start the generator, run it on idle for a minute, then switch the load to it. The system keeps monitoring the utility source for power restoration, it also monitor the generator output for failure upon any of which it switches back the load to utility supply and automatically switch off the generator. Once power is restored, the system delays for two minute before transferring the load to the utility supply. Success was recorded as the above processes were automated. This was achieved with the combination of discrete electrical and electronics components

Keywords:
 Electrical Load, Utility, Generator, Electrical and Electronics Components.


References:

1.       Ahmed M.S., Mohammed A.S. and Agusiobo O.B. (2006) ‘’Development of a Single Phase Automatic Change-Over Switch’’. AU J.T. 10(1): 68-74. Federal University of Technology Minna, Nigeria. (Jul. 2006)
2.       Amos, S.W. and James, M. (1981). Principles of transistor circuit: Introduction to the design of amplifiers, receivers and digital circuits. 6th ed., Hartnolls ltd., bodmin.UK.

3.       Atser A. Roy et-al, (2014). Design and Implementation of a 3-Phase Automatic Power Change-over Switch. e-ISSN : 2320-0847 p-ISSN : 2320-0936 Volume-3, Issue-9, pp-07-14

4.       Ezema L.S., Peter B.U., Harris O.O. (2012). Design of automatic change over switch with Generator control mechanism. SAVAP international.

5.       L.S. Ezema et-al, (2012). Design of Automatic Change Over Switch with Generator Control Mechanism. ISSN-L: 2223-9944. Vol.3, No.3, November 2012.

6.       Faissler, W.L. (1991). An introduction to modern Electronics, Willey, New York, NY, USA.

7.       Horowitz, P. and Winfield, H. (2002). The Art of Electronics, 2nd ed. Cambridge Univ. Press, Cambridge, UK

8.       Owen, B. (1995). Beginner’s Guide to Electronics 4th Ed. A Newness Technical Book, McGraw-Hill Companies Inc. New York, N.Y, USA.

9.       Oduobuk, E. J. et-al (2014). Design and Implementation of Automatic Three Phase Changer over Using LM324 Quad Integrated Circuit. International Journal of
Engineering and Technology Research Vol. 2, No. 4, April 2014, pp. 1 – 15, ISSN: 2327 – 0349.

10.    Rocks G. and Mazur G., (1993). Electrical motor controls. American Technical Publication, New-York, N.Y, USA.

11.    Ragnar, H. (1958). Electric Contacts Handbook. 3rd Edition, Springer-Verlag, Berlin/ Göttingen /Heidelberg. pp. 331-342.

12.    Theraja, B.L.; and Theraja, A.K. 2002. Electrical Technology, 21st ed. Ranjendra Ravida, New Delhi, India.

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6.

Authors:

Pooja C.S, K. R. Prassana Kumar 

Paper Title:

Survey on Load Balancing and Auto Scaling techniques for cloud Environment

Abstract: Cloud computing became now first choice and priority for every person who access the internet, one of the advantageous features of cloud computing is its scalability and flexibility. Auto scaling offers the facility to the individuals to scale up and scale down the resources as per their requirements, using only the needed resouce and paying for what they have used i.e “pay-as-you-use”. As everything take place in automatic manner, so human involvement errors are less and reduce the manpower and costs. so to make use of elasticity user must use auto scaling technique that balances the incoming workload, and reduce the total cost and maintain the Service Level Agreement (SLA).In this work main ideas revolve around the problems in scalable cloud computing systems. In modern days, management of resources is in boom and most talked topic in cloud environment. we present some of the existing load balancing policies and about Autoscaling categories.

Keywords:
cloud computing, scaling, auto scaling, load balancing.


References:

1.    Fang Liu, Jin Tong, Jian Mao, Robert Bohn, John Messina, Lee Badger and Dawn Leaf,”NIST Cloud Computing Reference Architecture”, NIST Special Publication 500-292, September 2011.
2.    M.Kriushanth, L. Arockiam and G. JustyMirobi,”Auto Scaling in Cloud Computing: An Overview”, International Journal of Advanced Research in Computer and Communication Engineering Vol. 2, Issue 7, July 2013, ISSN (Print): 2319-5940,ISSN (Online) : 2278-1021.

3.    Tania Lorido-Botran, Jose Miguel-Alonso , Jose A. Lozano, “A Review of Auto-scaling Techniques for Elastic Applications in Cloud Environments”, ARTICLE in JOURNAL OF GRID COMPUTING DECEMBER 2014, Impact Factor: 1.51 • DOI: 10.1007/s10723-014-9314-7.

4.    ChenhaoQu, Rodrigo N. Calheiros, and RajkumarBuyya,”A Reliable and Cost-Ecient Auto-Scaling System for Web Applications Using Heterogeneous Spot Instances”, Cloud Computing and Distributed Systems (CLOUDS) Laboratory, Department of Computing and Information Systems, The University of Melbourne, Australia, September 17, 2015.

5.    Gunpriya Makkar, Pankaj Deep Kaur,”A Review of Load Balancing in Cloud Computing”, Guru Nanak Dev University, Jalandhar, India, Volume 5, Issue 4, 2015 ISSN: 2277 128X.

6.    Priyanka P. Kukade and Geetanjali Kale “Survey of Load Balancing and Scaling approaches in cloud” vol.4 Feb 2015.

7.    Ashalatha R Evaluation of Auto Scaling and Load Balancing Features in Cloud” vol.117 may 2015.

8.    Dr. D .Ravindran, Ab Rashid Dar loud Based Resource Management with Autoscaling vol.2 .

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Issue-2 Published on December 30, 2016

Volume-6 Issue-2 Published on December 30, 2016
 Download Abstract Book

S. No

Volume-6 Issue-2, December 2016, ISSN:  2249-8958 (Online)
Published By: Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd. 

Page No.

1.

Authors:

Katsikides S., Markoulis S., Papaminas M.

Paper Title:

Corporate Social Responsibility and Stock Market Performance: An Event Study Approach

Abstract: This paper examines the relationship between Corporate Social Responsibility and stock market performance. To examine this relationship the “event-study” methodology is utilised to examine five events, two from the oil industry (BP and Exxon oil spills) and three from the banking industry (HSBC – money laundering; Barclays and Royal Bank of Scotland – Libor scandal). Results suggest that, apart from the HSBC money laundering event, all other events appear to have a significant effect on stock market performance as the shares of the firms involved tend to exhibit significant negative average abnormal returns during the period which followed the event. We also find some differences regarding the time-frame of the effect, since for some events it took more time to get into “full swing” and lasted longer.

Keywords:
  Event-study; Corporate Social Responsibility; Stock market performance.


References:

1.       Abbot, Walter F.,R.,Joseph, M. (1979). On the Measurement of Corporate Social Responsibility. Academy of Management Journal, pp. 501-515.
2.       Agle, B. R., Donaldson, T., Freeman, R. E., Jensen, M. C., Mitchell, R. K., & Wood, D. J. (2008). Dialogue: Towards superior stakeholder theory. Business Ethics Quarterly, 18, pp.153‒190.

3.       Alexander, Gordon J. and Buchholz, R.A. (1978). Corporate social responsibility and stock market performance. The Academy of Management Journal, 21,(3), pp. 479-486.

4.       Anderson, C. and Frankle, A.D. (1980). Voluntary social reporting: an iso-beta portfolio analysis. Accounting Review, 33, pp. 467–479.

5.       Ball, R., and P. Brown (1968). An empirical evaluation of accounting income numbers. Journal of Accounting Research 6, pp. 159-177.

6.       Brammer, S., Brooks,C. and Pavelin, S. (2006). Corporate Social Performance and Stock Returns: UK Evidence from Disaggregate Measures. Financial Management 35(3), pp. 97-116.

7.       Boulatoff, C., & Boyer, C. (2009). Green Recovery: How Are Environmental Stocks Doing? The Journal of Wealth Management. pp. 9-20.

8.       Brown, S.J. and Warner J.B. (1980). Measuring Security Price Performance. Journal of Financial Economics 8.

9.       Carroll, A. (2004). Managing ethically with global stakeholders: A present and future challenge. Academy of Management Executive, 2004, Vol. 18, No. 2.

10.    Cheung Y. L, Tan W., Ahn H-J., and Zhang Z. (2010). Does Corporate Social Responsibility Matter in Asian Emerging Markets? Journal of Business Ethics, 92, pp. 401-413.

11.    Cox, P., Brammer, S. and Millington, A. (2004). An Empirical Examination of Institutional Investor Preferences for Corporate Social Performance. Journal of Business Ethics 52(1), pp.27-43.

12.    Derwall, J., Günster, N., Bauer, R., and Koedijk, K. (2004). The Eco-Efficiency Premium Puzzle Mimeo. Rotterdam School of Management, Erasmus University.

13.    Fama, E., Fisher, L., Jensen, M., Roll, R. (1969). The adjustment of stock prices to new information. International Economic Review 10, pp. 1–21.

14.    Feldman, S.J., Soyka, P.A., and Ameer, P.G. (1997). Does Improving a Firm’s Environmental Management System and Environmental Performance Result in a Higher Stock Price? Journal of Investing 6(4), pp. 87-97.

15.    Flammer, C. (2012). Corporate Social Responsibility and Stock Prices: The Environmental Awareness of Shareholders. MIT Sloan School of Management.

16.    Freeman, R. E. (1984). Strategic management: A stakeholder approach. Boston: Pitman.

17.    M. Friedman (1962). Capitalism and Freedom. Chicago University Press.

18.    Geczy, C.C., Stambaugh, R. F., and Levin, D. (2003). Investing in socially responsible mutual funds. mimeo.

19.    Griffin, J.J. and Mahon, J.F. (1997). The corporate social performance and financial performance debate: twenty-five years of incomparable research. Business & Society, 36(1), pp. 5-31.

20.    Guerard, J.B. Jr. (1997a). Is there a Cost to being Socially Responsible? Journal of Investing 6(2), pp. 11-18.

21.    Guerard, J.B. Jr. (1997b). Additional Evidence on the Cost of being Socially Responsible in Investing Journal of Investing 6(4), pp. 31-35.

22.    Hamilton, S., Jo, H., and Statman, M. (1993). Doing Well While Doling Good? The Investment Performance of Socially Responsible Mutual Funds. Financial Analysts Journal November, pp. 62-66.

23.    Jensen, M.C (2001). Value maximization, stakeholder theory, and the corporate objective function. Journal of Applied Corporate Finance, 14, pp. 2001.

24.    Jones, T. M. (1995). Instrumental stakeholder theory: A synthesis of ethics and economics. Academy of Management Review, 20, pp. 404 ‒ 437.

25.    Kothari, S. P., & Warner, J. B. 2007. Econometrics of event studies. In B. E. Eckbo (Ed.), Handbook of corporate finance: Empirical corporate finance: pp. 3 ‒ 36. North Holland: Elsevier.

26.    Kotler, P., & Lee, N. (2005). Corporate Social Responsibility: Doing the most good for your company and your cause. New Jersey: John Wiley & Sons.

27.    MacKinlay, A. C., (1997). Event studies in economics and finance, Journal of Economic Literature 35, pp. 13-39.

28.    Moskowitz, M. R., (1972). Choosing socially responsible stocks. Business and Society review, 1, pp. 71-75.

29.    Orlitzky, M, Schmidt, F.L., and Rynes, S.L. (2003). Corporate Social and Financial Performance: A Meta-Analysis Organization Studies, 24(3), pp. 403-441.

30.    Porter, M.E. (1991). Towards a dynamic theory of strategy, Strategic Management Journal, Special Issue: Volume 12, Issue S2, pp. 95–117.

31.    Shen C-H., and Chang Y. (2009). Ambition Versus Conscience, Does Corporate Social Responsibility Pay off? The Application of Matching Methods. Journal of Business Ethics, Vol. 88, pp. 133-153.

32.    Statman, M. (2000) Socially Responsible Mutual Funds Financial Analysts Journal May, pp. 30-39

33.    Tirole, J. (2001). Corporate governance. Econometrica, 69, 1, pp. 1-35.

34.    Vance, Stanley C. (1975). Are socially responsible corporations good investment risks? Management Review, 64, pp. 18-24.

35.    William S.G. (1981). Using financial data to measure effects of   Regulation. Journal of Law and Economics, 24, pp. 121-158.

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2.

Authors:

Ramazan ŞENER

Paper Title:

Design and Thermal Analysis of Free Piston Linear Generator using In Range Extended Electric Vehicles

Abstract: Today, battery electric vehicles (BEV) have zero emission (tank to wheel) and very high efficiency. However, the most important obstacle of BEV is insufficient range. This disadvantage can be eliminated in term of range extender systems. Range extender system like generator can charge battery when required. Free Piston Linear Generator (FPLG), Wankel engine, Piston Internal Combustion Engine, Gas Turbine Engine and Fuel Cell Engine can be used as range extender unit. In this study, opposed-piston free-piston linear generator which can be used in low weight electric vehicles, which has spark ignition, 153 cm3 volume, and gasoline direct fuel injection was designed via SOLIDWORKS® software. Thermal analysis of the engine was performed by means of ANSYS® software using temperature in the literature. Finally, the engine design is determined to suit thermal operating conditions. It is find out that this system can be used as a range extender unit.

Keywords:
Finite Element Method, Thermal Analysis, Free Piston Linear Generator, Computer Aided Design.


References:

1.       Ferrari, C., Offinger, S., Schier, M., Philipps, F., et al., “Studie zu Range Extender Konzepten für den Einsatz in einem batterieelektrischen Fahrzeug – REXEL, DLR,  Hacker  Media, Stuttgart, Germany, 2012.
2.       Virsik, R., Heron, A., “Free piston linear  generator in  comparison  to  other range-extender  Technologies”  EVS  27  Electric  Vehicle  Symposium  & Exhibition, Spain, 2013.

3.       Varnhagen,  S.J., “Experimental  Investigation  of  the  Wankel  Engine  for Extending the Range of Electric Vehicles” Master thesis, University of California, Davis, 2011.

4.       (2016) Freikolben website. [online]. Available: http://www.freikolben.ch/

5.       Narayan, K.L., Rao, K.M., Sarcar, M.M.M., “Computer Aided Design and Manufacturing” New Delhi: Prentice Hall of India, ISBN 812033342X, 2008.

6.       (2016) Beetron website. [online]. Available: http://www.beetron.ch/

7.       Ferziger, J.H., Peric, M., “Computational methods for fluid dynamics” Springer, 3rd edition, 2002.

8.       Huebner, H.K., Thornton, E.A., Byrom T.G., “The finite element method for engineers” 3rd edition, John Wiley & Sons, 1999.

9.       Durat, M., Kapsiz, M., Nart, E., Ficici, F, Parlak, A., “The effects of coating materials in spark ignition engine design” Materials and Design, s. 540-545, 2012.

10.    Cerit, M., Soyhan, H.S., “Thermal analysis of a combustion chamber surrounded by deposits in an HCCI engine” Applied Thermal Engineering, s. 81-88, 2013.

11.    Çakır, U., “Seramik Kaplı Bir Dizel Motor Yanma Odasının Termal Analizi” M.Sc. Thesis, Sakarya University, 2007.

12.    Cerit, M., “Thermo mechanical analysis of a partially ceramic coated piston used in an SI engine” Surface & Coatings Technology, s. 3499-3505, 2007.

13.    Varol, B., “Turbo Dizel Bir Motorda Bir Pistonun Termal Ve Mekanik Yükler Altında Sonlu Elemanlar Yöntemiyle Gerilim Analizi” M.Sc. Thesis, Hacettepe University, 2012.

14.    Ceylan, S., “Seramik Kaplı Dizel Pistonlarda Termal Gerilmelerin Sonlu Elemanlar Metoduyla Belirlenmesi” M.Sc. Thesis, Sakarya University, 2009.

15.    (2016) Matbase website. [online]. Available: http://www.matbase.com/material-categories/

16.    (2016) Matweb website. [online]. Available: http://asm.matweb.com/

17.    (2016) Makeitfrom website. [online]. Available: http://www.makeitfrom.com/material-properties/

18.    Okur,  M., “Dört  Zamanlı,  Tek  Silindirli,  Buji  İle  Ateşlemeli  Bir  Benzin Motorunun  Sonlu  Elemanlar  Yöntemi  Kullanılarak  Tasarımı  Ve  İmali” Ph.D. thesis, Gazi University, 2007.

19.    Cornforth, J.W., “Finite element analysis of engines” Materials and Design, 1985.

 

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3.

Authors:

N. Maksimov, A. Panas

Paper Title:

Modified Ultra-Wideband Microwave Chaotic Colpitts Oscillator with a Simplified Structure: Implementation, Experiments

Abstract:  Modified Colpitts oscillator with SiGe bipolar transistor as an active element was introduced, implemented and experimentally studied. It enables generation of ultra-wideband chaotic oscillations in the microwave range. Compared to its classical analogue, the oscillator has an extremely simple structure comprising only one single external reactive element (an inductor). The transistor p-n junction capacitance performs the function of oscillator external capacitors. Stable generation of chaotic oscillations in the range of 1 to 8.5 GHz (at 10 dB level) with highest ever efficiency values (7%) for a given class of oscillators has been obtained.

Keywords:
 Chaotic Colpitts oscillator, ultra wideband chaotic oscillations, microwave band, power spectra, power efficiency, implementation, bipolar SiGe transistor


References:

1.       Dmitriev, A.S., Panas, A., Starkov, S.O.: Experiments on speech and music signals transmission using chaos. Int. J. Bifurc. Chaos 5, 1249-1254 (1995)
2.       Dmitriev, A., Panas, A., Starkov, S., Kuzmin, L.: Experiments on RF band communication using chaos. Int. J. Bifurc. Chaos 7, 2511-2527 (1997)

3.       Dmitriev, A.S., Kyarginsky, B.Ye., Panas, A.I., Starkov, S.O.: Experiments on ultra wideband direct chaotic information transmission in microwave band. Int. J. Bifurc. Chaos 13, 1495-1507 (2003)

4.       Panas, A.I., Kyarginsky, B.E., Maximov, N.A.: Single-transistor microwave chaotic oscillator. Proc. NOLTA-2000 2, Dresden, Germany, 445-448 (2000)

5.       Kyarginsky, B.E., Maximov, N.A., Panas, A.I., Starkov, S.O.: Wideband microwave chaotic oscillators. Proc. 1st IEEE Conf. Circuits and Systems for Communications (Circuits and Systems in Broadband Communication Technologies), St. Petrsburg, Russia, 296-299 (2002)

6.       Panas A.I., Kyarginsky B.E., Efremova E.V.: Ultra-wideband microwave chaotic oscillator. Proc. 12th Mediterranean microwave symposium MICROCOLL-2007, Budapest, Hungary, 14-16 May, 145-148 (2007)

7.       Efremova E.V., Nikishov A.Yu., Panas A.I.: UWB Microwave Chaotic Oscillator: from Distributed Structure to CMOS IC Realization. Proc. of 5th European Conf. Circuits and Systems for Communications ECCSC’10. Belgrade, Serbia, November 23-25, 67-70 (2010)

8.       Panas: Ultra wideband microwave chaotic oscillator. Eurasian physical technical journal. 9, 50-56 (2012)

9.       Chong, S.K. Young: UWB Direct Chaotic Communications Technology for Low-Rate WPAN Applications. IEEE Trans. on Vehicular Technology. 57, 1527-1536 (2008)

10.    Efremova E.: Generator of 3-10 GHz ultrawideband microwave chaos. Proc. of 21th Int. Conf. Nonlinear Dynamics of Electronics Systems (NDES). Bari, Italy, (2013)

11.    Kennedy M.P.: Chaos in the Colpitts oscillator. IEEE Trans. on Circuits and Systems I: Theory ans Applications. 41, 771-774 (1994)

12.    G.M. Maggio, O. De Feo, and M.P. Kennedy: Nonlinear analysis of the Colpitts oscillator and application to design. IEEE Trans. on Circuits and Systems. 46(9), 1118-1130 (1999)

13.    Tamasevicius A., Mykolaitis G., Bumelene S., Baziliauskas A., Krivickas R., Lindberg E.: Chaotic Colpitts oscillator for the ultrahigh frequency range. Nonlinear Dynamics. 44, 159-165 (2006)

14.    N.A. Maksimov, and A.I. Panas: Three-point circuits for generating band-limited chaotic oscillators. Proc. Int. Symp. Signals, Circuits, Systems (SCS’2001). Iasi, Romania, 10-11 July, 65-68 (2001)

15.    Maximov N.A., Panas A.I.: Microwave chaotic oscillators with controlled bandwidth. Proc. ICCSC’2004. Moscow, Russia, June 30-July 2, (2004)

16.    Z.G. Shi, L.X. Ran.: Microwave chaotic Colpitts oscillator: design, implementation and applications. Int. J. of Electromagn. Waves and Appl. 20, 1335-1349 (2006)

17.    W. Chen, Yu Guo, Huai Gao, G.P. Li: A novel ultra-wideband microwave chaotic Colpitts oscillator. Proc. Wireless and Microwave Technology Conference (WAMICON). Orlando, Florida, April 16, 1-4 (2013)

18.    Panas A., Maximov N.: Modified microwave chaotic Colpitts oscillator. Proc. of 23th Int. Conf. on Nonlinear Dynamics in Electronic Systems. Como, Italy, (2015)

19.    Jing Xia Li, Yun Cai Wang, Fu Chang Ma.: Experimental demonstration of 1.5 GHz chaos generation using an improved Colpitts oscillator. Nonlinear Dyn. 72, 575-580 (2013)

 

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4.

Authors:

John Kiplagat Biwott, Wanyona Githae, Charles Kabubo

Paper Title:

Challenges Facing Construction of Affordable Decent Low Cost Housing in Turkana County

Abstract: Housing problems in developed countries are characterized by overcrowding, dilapidated structures and shared bathrooms. On the other hand, developing countries like Kenya, the problem is largely complicated by lack of serviced land, lack of access to housing finances, rigid legal framework and over dependence on non-local construction materials, techniques and technologies. Although there have been significant interventions in the effort to reverse this trend in Kenya, some counties especially in marginalized areas like Turkana County have continued to lag behind in provision of decent and affordable houses for its residents. In an effort to establish where the problem is, this study, seek to determine and describe challenges faced by different stakeholders and residents of Turkana County in their endeavor to put up decent low cost housing. 

Keywords:
Affordable housing, decent housing and alternative building technologies and Turkana County


References:

1.       Ayedun, C. A. & Oluwatobi, A. O. (2011). Issues and Challenges Militating against the Sustainability of Affordable Housing Provision in Nigeria. Business Management Dynamics Journal 1(4), pp 1-8.
2.       Barrett, J. A. (1998). Sacrifice and Prophecy in Turkana Cosmology. Nairobi: Paulines Publications.

3.       Buckley, R.M. & Mayo, S. (1988). Housing Policy in Developing Countries: Evaluating the Macroeconomic Impacts. Washington, DC: International Bank for Reconstruction and Development/World Bank.

4.       Hassanali, F.M. (2009). Understanding Reduced Private- Sector Participation in Low Income Housing Delivery in Nairobi.

5.       Kenya National Bureau of Statistics (KNBS). 2007. Basic Report: Kenya Integrated Household Budget Survey (KIHBS) – 2005/06. Nairobi: The Regal Press Kenya Ltd.

6.       Kenya National Bureau of Statistics (KNBS). 2010. The 2009 Kenya Population and Housing Census. Nairobi: Government Printer.

7.       Kenya National Bureau of Statistics (March 2012). Analytical Report on Housing Conditions, Amenities and Household Assets (Vol. 9). Nairobi: Government Printer.

8.       Kothari, C.R. (2004). Research Methodology: Methods and Techniques, (2nd edition). New Delhi: New Age International Publishers.

9.       Krejcie R.V. & Morgan D.W. (1970). Determining Sample Size for Research Activities. Educational and Psychological Measurement 30, pp. 607-610.

10.    Macoloo, G. (1994). The Changing Nature of Financing Low Income Urban Housing Development in Kenya. Housing Studies (Volume 9, Issue 2), pp 189-281.

11.    Ministry of Housing (2004). Sessional Paper No. 3 of 2004: National Housing Policy for Kenya. Nairobi: Government Printers.

12.    Nabutola, W. (2004). Affordable Housing in Kenya: A Case Study of Policy on Informal Settlements, Land Administration and Housing Issues in Informal Environments. 3rd FIG Regional Conference, Jakarta, Indonesia.

13.    Otiso, K.M. (2003). State, Voluntary and Private Sector Partnerships for Slum Upgrading and Basic Service Delivery in Nairobi City. Kenya Cities, 20(4), pp 221-229.

14.    Republic of Kenya (2010). The Constitution of Kenya. Nairobi: Government Printer.

15.    Schussheim, M. J. (2004). Housing Low-Income Families: Problems, Programs Prospects.  Journal of Housing and Community Development Washington; 56(5).

16.    Shitemi, K. (2014, May 9).  Exploring Equalization Fund under Devolution. Retrieved from http://www.shitemi.com/devolution/exploring-equalization-fund-under-devolution/

17.    Wilcox, S. & Fitzpatrick, S. (2010). The Impact of Devolution Housing and Homelessness. London: Joseph Rowntree Foundation.

 

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5.

Authors:

Seyed Amin Ahmadi Olounabadi, Avula.Damodaram, V Kamakshi Prasad, Mahdi Hosseini

Paper Title:

Impact of Multi-Path Security in Wireless Ad Hoc Networks in Indoor Environments by using AOMDV Methods

Abstract:  Ad hoc Network is a decentralized type of wireless network and also is a local area network (LAN) that is built spontaneously as devices connect. , Instead of relying on a base station to coordinate the flow of messages to each node in the network, the individual network nodes forward packets to and from each other. Basically, an ad hoc network is a temporary network connection created for a specific purpose (such as transferring data from one computer to another). Multipath routing is the routing technique of using multiple alternative paths through a network, which can yield a variety of benefits such as fault tolerance, increased bandwidth, or improved security. Ad-hoc On-demand Multipath Distance Vector Routing (AOMDV) protocol is an extension to the AODV protocol for computing multiple loop-free and link disjoint paths and also increases the reliability through transmitting the messages in multiple paths with minimal redundancy, which used in present work. Simulations were conducted using the NS2 network simulator. In order to simulate most of the proposed Byzantine attacks in NS2, a protocol independent Byzantine attack simulation module was developed. This module provides the capability to simulate the black hole, Byzantine wormhole, and Byzantine overlay network wormhole attacks without modifying the routing protocol. We are considering our communication path is changeable even path or node is node failed. So data is sending through different paths, it provide high security than single path.

Keywords:
 wireless network, Ad hoc, AOMDV, Byzantine attacks


References:

1.    Reza Curtmola Cristina Nita-Rotaru, “BSMR: Byzantine- Resilient Secure Multicast Routing in Multi-hop Wireless Networks”, IEEE Transactions on Mobile Computing, vol. 8, Issue. 4, pp. 445 – 459, February 2009.
2.    A.Tsirigos and Z.J.Hass (2004), “Analysis of multi path routing, Part 1: The effects on the packet delivery ratio” IEEE Transactions on Wireless Communication., vol.3, no.2, pp: 500- 511.

3.    Banner, R. Orda, A, “Multipath Routing Algorithms for Congestion Minimization”. This paper appears in: Networking, IEEE/ACM Transactions on Publication Date: April 2007 Volume: 15, Issue: 2, on page(s): 413-424.

4.    Jun Peng, Biplab Sikdar and Liang Cheng (2009) “Multicasting with Localized Control in Wireless Ad Hoc Networks” IEEE Transaction on Mobile Computing.

5.    Papadimitratos, P. Haas, Z.J, “Secure data communication in mobile ad-hoc networks” , This paper appears in: Selected Areas in Communications, IEEE Journal on Publication Date: Feb. 2006,Volume: 24, Issue: 2,On page(s): 343- 356.

6.    Banner , R. Orda, A. “Multipath Routing Algorithms for Congestion Minimization”Conference version in Proc. IFIP Networking 2005.

7.    Papadimitratos, P. Haas, Z.J, Sirer, E, G.”Path Set Selection in Mobile Ad Hoc   Networks”. June 09 – 11, 2002. Pages 1 – 11.

 

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6.

Authors:

Immandi Solomon Raju, I Prudhvi Kumar Raju, D Krishna Chaitanya

Paper Title:

Performance Analysis of a Grid Current Compensator using Fuzzy Logic Controller

Abstract: This paper introduces an advanced current control strategy for distributed generation into the utility grid despite the distorted grid voltage and RC loads. The proposed current controller is designed in synchronous reference frame and composed of a fuzzy logic controller. The fuzzy logic controller greatly simplifies the control strategy. It does not require the local load current measurement and harmonic analysis of the grid voltage. Therefore, the proposed control method can be easily adopted into the traditional DG control system without installation of external hardware. The operation principle of the proposed control method is analyzed in detail, and its effectiveness is validated through simulated results.

Keywords:
Distributed Generation (DG), RC load, Fuzzy Logic Controller (FLC), PI Controller, PI-RC Controller


References:

1.       Quoc-Nam Trinh and Hong-HeeLee,”An enhanced grid current compensator for Grid-connected Distribuited Generation uinderNoninear loads and Grid voltage distortions”, IEEE Trans. Ind. Electron., vol. 61, no. 12, pp. 6528– 6536, December,2014.
2.       Q. Zeng and L. Chang, “An advanced SVPWM-based predictive current controller for three-phase C. A. Busada, S. Gomez Jorge, A. E. Leon, and J. A.

3.       Solsona, “Current controller based on reduced order generalized integrators for distributed generation systems,”IEEE Trans. Ind. Electron., vol. 59, no. 7, pp. 2898– 2909, Jul. 2012.

4.       M. Liserre, R. Teodorescu, and F. Blaabjerg, “Multiple harmonics control for three-phase grid converter systems with the use of PI-RES current controller in a rotating
frame,” IEEE Trans. Power Electron., vol. 21, no. 3, pp. 836–841, May 2006.

5.       M. Castilla, J. Miret, A. Camacho, J. Matas, and L. G. de Vicuna, “Reduction of current harmonic distortion in three-phase grid-connected photo- voltaic inverters via resonant current control,” IEEE Trans. Ind. Electron., vol. 60, no. 4, pp. 1464–1472, Apr. 2013.

6.       R.-J. Wai, C.-Y. Lin, Y.-C. Huang, and Y.-R. Chang, “Design of high- performance stand-alone and grid-connected inverter for distributed generation applications,”IEEE Trans. Ind. Electron., vol. 60, no. 4, pp. 1542–1555, Apr. 2013.

7.       J. Balaguer, Q. Lei, S. Yang, U. Supatti, and F. Z. Peng, “Control for grid-connected and intentional islanding operations of distributed power generation,” IEEE Trans.Ind. Electron., vol. 58, no. 1, pp. 147–157, Jan. 2011.

8.       R. C. Dugan and T. E. McDermott, “Distributed generation,” IEEE Ind. Appl. Mag., vol. 8, no. 2, pp. 19–25, Mar./Apr. 2002.

9.       F. Blaabjerg, R. Teodorescu, M. Liserre, and A. V. Timbus, “Overview of control and grid synchronization for distributed power generation systems,” IEEE Trans. Ind.Electron., vol. 53, no. 5, pp. 1398–1409, Oct. 2006.

10.    Z. Yao and L. Xiao, “Control of single-phase grid-connected inverters with nonlinear loads,” IEEE Trans.Ind. Electron., vol. 60, no. 4, pp. 1384– 1389, Apr. 2013.

11.    Z. Liu, J. Liu, and Y. Zhao, “A unified control strategy for three-phase inverter in distributed generation,”IEEE Trans. Power Electron., vol. 29, no. 3, pp. 1176– 1191, Mar. 2014.

12.    IEEE Application Guide for IEEE Std 1547, IEEE Standard for Interconnecting Distributed Resources with Electric Power Systems, IEEE Std. 1547.2-2008, 2008.

13.    Q.-N. Trinh and H.-H. Lee, “Improvement of current performance for grid connected converter under distorted grid condition,” in Proc. IET Conf. RPG, Sep. 6–8, 2011, pp. 1–6

 

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7.

Authors:

M. Bhanu Divya Bharathi, P. Krishna Chaitanya, K. Sandhya Rani

Paper Title:

Power Quality Improvement of DFIG using FLC Based Variable Wind Turbines by IPC Method

Abstract:  Because of the wind speed variation, breeze shear along with tower shadow effects, grid connected wind generators are the options for power fluctuations which could produce sparkle during constant operation. This paper presents a type of an MW-level varying speed windmill with a new doubly feasted induction generator to analyze the Flicker emission along with mitigation difficulties. Fuzzy logic controller (FLC) was designed to obtain maximum power extraction at low wind speeds to limit power extraction at 1.5MW nominal power set point. The Fuzzy logic based IPC (Individual Pitch Control) scheme is proposed along with the individual message controller is made using generator active power along the wind turbine. A 1.5MW horizontal axis breeze turbine model was designed for tuning as well as simulation performance is studied and the results show the damping of this generator active power by IPC is an efficient means for flicker minimization of varying speed wind generators during constant operation.

Keywords:
 Flicker mitigation, IPC, variable speed wind turbine, DFIG, FLC.


References:

1.       T. Sun, “Power Quality of grid-connected wind turbines with DFIG and their interaction with the grid,” Ph.D. dissertation, Aalborg Univ., Aalborg, Denmark, 2004.
2.       L. Rossetto, P. Tenti, and A. Zuccato, “Electromagnetic compatibility issues in industrial equipment,” IEEE Ind. Appl. Mag., vol. 5, no. 6, pp. 34–46, Nov./Dec. 1999.

3.       A° .Larsson, “Flicker emission of wind turbines during continuous operation,” IEEE Trans. Energy Convers., vol. 17, no. 1, pp. 114–118, Mar. 2002.

4.       H. Sharma, S. Islam, T. Pryor, and C. V. Nayar, “Power quality issues in a wind turbine driven induction generator and diesel hybrid autonomous grid,” J. Elect. Electron.Eng., vol. 21, no. 1, pp. 19–25, 2001.

5.       M. P. Papadopoulos, S. A. Papathanassiou, S. T. Tentzerakis, and N. G. Boulaxis, “Investigation of the flicker emission by grid connected wind turbines,” in Proc. 8th Int. Conf. Harmonics Quality Power, Athens, Greece, 1998, vol. 2, pp. 1152–1157.

6.       T. Sun, Z. Chen, and F. Blaabjerg, “Flicker study on variable speed wind turbines with doubly fed induction generators,” IEEE Trans. Energy Convers., vol. 20, no. 4, pp. 896–905, Dec. 2005.

7.       K. Yun-SeongandW. Dong-Jun, “Mitigation of the flicker level of a DFIG using power factor angle control,” IEEE Trans. Power Del., vol. 24, no. 4, pp. 2457–2458, Oct. 2009.

8.       W. Hu, Z. Chen, Y. Wang, and Z. Wang, “Flicker mitigation by active power control of variable-speed wind turbines with full-scale back-toback power converters,”
IEEE Trans. Energy Convers., vol. 24, no. 3, pp. 640–649, Sep. 2009.

9.       Bossanyi, “Individual blade pitch control for load reduction,” Wind Energy, vol. 6, pp. 119–128, 2002.

10.    Bossanyi, “Further load reductions with Individual pitch control,” Wind Energy, vol. 8, pp. 481–485, 2005.

11.    Y. Zhang, Z. Chen, M. Cheng, and J. Zhang, “Mitigation of fatigue loads using Individual pitch control of wind turbines based on FAST,” in Proc.46th Int. Conf. Universities’ Power Eng., Soest, Germany, 2011.

12.    J. Jonkman and M. L. J. Buhl, “FAST User’s Guide,” National Renewable Energy Laboratory (NREL), Golden, CO, USA, Tech. Rep. NREL/EL-500-38230, (2005). [Online]. Available: http://wind. nrel.gov/designcodes/simulators/fast/

13.    S. M. Muyeen,M. Hasan, R. Takahashi, T.Murata, J. Tamura, Y. Tomaki, A. Sakahara, and E. Sasano, “Comparative study on transient stability analysis of wind
turbine generator system using different drive train models,” IET Renewable Power Generation, vol. 1, no. 2, pp. 131–141, 2007.

14.    D. Wright and L. J. Fingersh, “Advanced control design for wind turbines—Part I: Control design, implementation, and initial tests,” National Renewable Energy Laboratory, NREL Rep. TP-500–42437, National Renewable Energy Laboratory, Mar. 2008.

15.    Electromagnetic Compatibility (EMC)—Part 4: Testing and Measurement Techniques—Section 15: Flickermeter—Functional and Design Specifications,IEC Std. 61 000–4–15, Nov. 1997.

16.    A° .Larsson, “Flicker emission of wind turbines during continuous operation,” IEEE Trans. Energy Convers., vol. 17, no. 1, pp. 114–118, Mar. 2002

 

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8.

Authors:

Begard Salih Hassen

Paper Title:

The Powerful Activity of DSDV Algorithm in WSN System

Abstract:   Lately, technological developments in the strategy of processors, memory and radio communications have pushed an attention in the field of sensor network. Networks of those devices are denoted as Wireless Sensor Networks (WSNs). WSNs make possible information accumulation and investigation on an unmatched scale. Indeed, they have concerned care and get wide range of application in diverse areas. The Choice of the protocols and routing are the greatest common schemes that are to be dedicated when manipulative every type of wireless networks likes WSNs. In this paper, performance investigation of “Destination Sequenced Distance Vector DSDV” protocol is done. All the cases for working the protocol are discussed and the time for transmission the information is calculated within multi cases. The results show that this protocol is more strong and robust against the worst cases of losing the nodes or link failure within the network with minimum time for transfer the information through the WSN.

Keywords:
  WSN, DSDV, transmission time, sending and receiving node.


References:

1.       Shio Kumar Singh, M P Singh and D K Singh, “Routing Protocols in Wireless Sensor Networks A Survey”, International Journal of Computer Science & Engineering Survey (IJCSES), Vol. 1, No. 2, DOI : 10.5121/ijcses.2010.1206, November 2010.
2.       Fengju An, “Density Adaptive Sleep Scheduling in Wireless Sensor Networks”, Master of Science Thesis, Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Netherlands, 2013.

3.       Bilal Mustafa and Umar Waqas Raja, “Issues of Routing in VANET”, Master thesis, School of Computing, Blekinge Institute of Technology, Sweden, 2010.

4.       Luis Gironés Quesada, “A Routing Protocol for MANETs”, Master of Science in Communication Technology, Norwegian University of Science and Technology, Department of Telematics, 2007.

5.       Heng Luo, “A Best Effort QoS Support Routing in Mobile ad hoc Networks”, Ph.D. thesis, The University of Edinburgh, 2011.

6.       Ilker Demirkol, Cem Ersoy and Fatih Alagöz, “MAC Protocols for Wireless Sensor Networks: A Survey”, IEEE Communications Magazine, 0163-6804/06, April 2006.

7.       Jennifer Yick, Biswanath Mukherjee and Dipak Ghosal, “Wireless sensor network survey”, Computer Networks, 52 (2008) 2292–2330, journal homepage: www.elsevier.com , 2008.
8.       Ravi Kumar Bansal, “Performance Analysis of Cluster Based Routing Protocol in Manets”, Master Thesis of Engineering, Computer Science and Engineering Department, Thapar Institute of Engineering and Technology, 2006.
9.       Yujie Zhu, “Energy-Efficient Communication Strategies for Wireless Sensor Networks”, Ph.D. thesis, School of Electrical and Computer Engineering, Georgia Institute of Technology, 2007.

10.    Rajeshwar Singh, Dharmendra K Singh and Lalan Kumar, “Performance Evaluation of DSR and DSDV Routing Protocols for Wireless Ad Hoc Networks”, Int. Journal of Advanced Networking and Applications, Volume: 02, Issue: 04, Pages: 732-737, 2011.

11.    Kumar Prateek, Nimish Arvind and Satish Kumar Alaria, “MANET-Evaluation of DSDV, AODV and DSR Routing Protocol”, International Journal of Innovations in Engineering and Technology (IJIET), Vol. 2 Issue 1, ISSN: 2319 – 1058, 2013.

12.    Yatendra Mohan Sharma and Saurabh Mukherjee, “Comparative Performance Exploration of AODV, DSDV & DSR Routing Protocol in Cluster Based VANET Environment” International Journal of Advances in Engineering & Technology, IJAET ISSN: 2231-1963, Vol. 4, Issue 2, pp. 120-127, 2012.

13.    Aman Kumar and  Barinderpal Singh, “Performance Analysis of DSDV, I-DSDV Routing Protocol in Monile Ad Hoc Networks in IPv6 under Black Hole Attack”, International Journal of Future Generation Communication and Networking (IJFGCN), Vol. 8, No. 4 , pp. 155-160, http://dx.doi.org/10.14257/ijfgcn.2015.8.4.15, ISSN: 2233-7857, 2015.

14.    M. Pushpadevi and M.Sakthi, “Improved Minimum Delay Routing Using TBETX Routing Over DSDV Routing Protocol in Wireless Ad Hoc Networks”, International Journal of Innovative Research in Computer and Communication Engineering, www.ijircce.com , Vol. 2, Issue 9, ISSN(Online): 2320-9801, ISSN (Print): 2320-9798, 2014.

15.    B.N. Jagdale1, Pragati Patil, P. Lahane and D. Javale, “Analysis and Comparison of Distance Vector, DSDV and AODV Protocol of MANET”, International Journal of Distributed and Parallel Systems (IJDPS) Vol.3, No.2, DOI: 10.5121/ijdps.2012.3210 121, 2012.

16.    Biswaraj Sen and Sanku Sinha, “A Simulation Based Performance Analysis of AODV and DSDV Routing Protocols in MANETs”, International Journal of Modern Engineering Research (IJMER) www.ijmer.com, Vol.2, Issue.4, pp-2404-2408, ISSN: 2249-6645, 2012.

 

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9.

Authors:

Vandana Vinayak, Sonika Jindal

Paper Title:

A Review on various Image Compression Methods in Content Based Image Retrieval

Abstract: This paper provides an overview about the various compression techniques available in the research area of Image retrieval, especially Content-Based Image Retrieval (CBIR), an evocative and authentic research area for the last decades. CBIR is used for the retrieval of the images based on the content of the images generally known as features. These features may be low level features i.e. color, shape, texture and spatial relationship or the high level features that use the concept of human brain. Now a days, the development and demand of multimedia product grows increasingly fast, contributing to insufficient storage of memory device. Therefore, the theory of data compression becomes more and more significant for reducing the data redundancy to save more hardware space. Compression is the process of reducing the amount of data required to represent the quality of information. Compression is also useful as it helps to reduce the consumption of expensive resources such as hard disk space.

Keywords:
Especially Content-Based Image Retrieval (CBIR), Therefore, increasingly fast, provides.


References:

1.       J. O. A. Tamer Mehyar, “An enhancement on content based image retrieval using color and texture features,” vol. 3, no. 4. Journal of Emerging Trends in Computing and Information Sciences, April 2012.
2.       S. J. Nitika Sharma, “A review on global features based cbir system.” International Conference on information and mathematical sciences.

3.       G. V. Tcheslavski, “Basic image compression methods,” 2008.

4.       M. Sharma, “Compression using huffman coding,” vol. 10, no. 5. IJCSNS International Journal of Computer Science and Network Security, May 2010.

5.       K. S. Julie Zelenski, “Huffman encoding and data compression.” Springer 2012, CS106B, May 23 2012.

6.       D. D. S. Mridul Kumar Mathur, Seema Loonker, “Lossless huffman coding technique for image compression and reconstruction using binary trees,” vol. Vol 3 (1). International Journal of Computer Technical Applications, pp. 76–79.

7.       J. Glen G. Langdon, “An introduction to arithmetic coding,” vol. 28, no. 2. IBM J. RES. DEVELOP., March 1984.

8.       P. P. Venkataram, Lossless Compression Algorithms, 2016, ch. 6.

9.       R. E. W. Rafael C. Gonzalez, Digital Image Processing, 3rd ed. Pearson Education, 2014.

10.    O. N. Pasi Franti and T. Kaukoranta, “Compression of digital images by block truncation coding:a survey,” no. 37(4). The Computer Journal, 1994, pp. 308–332.

11.    H. P. Jing-Ming Guo and J.-H. Chen, “Content-based image retrieval using error diffusion block truncation coding features,” vol. 25, no. 03. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY,, 2015.

 

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10.

Authors:

Paul Thomas, R.S. Moni

Paper Title:

ANN based Multilevel Classification Technique with Optimum Measurement Period for Accurate Diagnosis using Biomedical Signals

Abstract: Biomedical signals are representations of the mechanical and electrical activities within the human body. These signals contain a lot of information on the state of health of a person and their analysis have a significant role in the diagnosis of various health disorders and medical abnormalities, such as activation levels and the biomechanics of the muscles and other human organs. Of the many Biomedical signals, focus of this work is on Electro-cardiogram (ECG) and Electro-myogram (EMG). ECG provides information on the rhythm and functioning of the heart. EMG is the recording of human muscular activity. ECG signals used in this work are taken from the standard MIT-BIH, and CU data bases of PhysioNet database and EMG signals are taken from the EMGLab and PhysioNet database. Automated analysis of Biomedical signals can largely assist the physicians in their diagnostic process. The extracted spectral and temporal features represent the diverse characteristics of a Biomedical signal. In this work, more emphasis is given to spectral features since a lot of critical information on the health of a person are hidden in the spectral content of the signal. A subset from a larger set of available features is experimentally selected for optimum performance. The feature vector has a size of 11 for ECG signal analysis and a size of 9 for EMG signal analysis. Accuracy of detecting a health disorder depends on the quality of the features extracted from a Biomedical signal. A few techniques are proposed to achieve improved quality for the features. Also a method is developed to arrive at the optimum length of the Biomedical signal to be used for analysis. Accordingly, the length of the ECG signal used in this work is 10 s and the length of the EMG signal is 11 s. It is observed that the variance of the features is minimum when the signal for analysis is taken from the mid portion of the whole Biomedical signal. To make the value of a feature close to its true value, each feature value is taken as the average of the values of the feature extracted from 20 consecutive signal segments. A technique is also proposed to reduce the effect of wild points in the computation of spectral parameters. It is observed that classification accuracy also depends on the sampling rate of the Biomedical signal. The sampling rate of ECG signal in this work is 128 Hz and that of EMG signal is 750 Hz. Classifying a Biomedical signal is the process of attaching the signal to a disease state or healthy state. The work proposes a Multi level classification approach for Biomedical signals. Each classifier is a cascade of two ANN classifiers, the first ANN has a linear transfer function and the second ANN has a sigmoid transfer function. First level classification is to the broad categories of the disorders. In the second level, these disorders are drilled down to more specific categories. This concept can be extended further to achieve finer classification of Biomedical signals. In this work the classification is demonstrated to two levels for ECG signals and one level for EMG signals. The performance of the proposed method is evaluated using the standard parameters of specificity, sensitivity and classification accuracy (CA). The performance is found to be better than the reported figures in the case of both ECG and EMG signals.

Keywords:
 ECG, EMG, FFT, DWT, Pattern recognition ANN, Feature extraction, Multilevel classification, Wavelet, PhysioNet database, CA, Atrial arrhythmias, Ventricular arrhythmias, NSR, MI, MUAP, Myopathy, ALS.


References:

1.  Martis, Roshan Joy, U. Rajendra Acharya, Lim Choo Min, “ECG beat classification using PCA, LDA, ICA and Discrete Wavelet Transform,” Biomedical Signal Processing and        Control, vol 8, issue 5, pp. 437-448, 2013.
2.  Naik, Ganesh, S. Selvan, and Hung Nguyen. “Single-Channel EMG Classification With EnsembleEmpirical-Mode-Decomposition-Based ICA for Diagnosing Neuromuscular  Disorders.”,pp.1-11,2015.
3.  Rahime Ceylan, Yuksel ozbay, “Comparison of FCM, PCA and WT techniques for classification ECG arrhythmias using artificial neural network,” Expert Systems with  Applications,vol 33, issue 2, pp. 286-295, 2007.
4.  Swati Banerjee, Madhuchanda Mitra. “A classification approach for Myocardial infarction using voltage features extracted from four standard ECG leads” IEEE International  conference on recent trends in information systems, 2011, pp.325-330.
5.  Sambhu D, Umesh A. C, “Automatic Classification of ECG Signals with Feature Extraction using Wavelet Transform and Support Vector Machine,” IJAREEIE, vol.2, special issue 1,  pp. 235-241, 2013.
6.  Felipe Alonso Atienza, Eduardo Morado, Lornea Fernandez Martinez, Arcadi Garcia Alberola, Jose Luis Rojo Alvarez, “Detection of life-threatening arrhythmias using feature  selection and support vector machines.” Biomedical Engineering, IEEE Transactions vol. 61, no.3, pp.832-840, 2014.
7.  Roger Dzwonczyk, Charles G. Brown, H. A. Werman, “The median frequency of the ECG during ventricular fibrillation: its use in an algorithm for estimating the duration of  cardiac arrest,” IEEE Transactions on Biomedical Engineering, vol. 37, no. 6, pp. 640-646, 1990.
8.  Subasi, Abdulhamit. “Classification of EMG signals using combined features and soft computing techniques.” Applied soft computing, Vol.12, Issue 08, pp. 2188-2198, 2012.
9.  Phinyomark, Angkoon, Pornchai Phukpattaranont, and Chusak Limsakul. “Feature reduction and selection for EMG signal classification.” Expert Systems with Applications Vol.39, Issue 08, pp. 7420-7431, 2012.


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11.

Authors:

M. Brindha, K. Saranya, S. Rajesh

Paper Title:

Certain Investigation on Image Classification and Segmentation using Different Techniques

Abstract: A brain cancer is a tissue that structured by an addition of anomalous cells and important to detect and classify brain tumors from MRI (Magnetic Resonance Imaging) for treatment. Brain tumor segmentation and classification is considered to be more important tasks in medical imaging. MRI is used for the study of the human brain. A fully automated method plays an important role in the prediction of brain cancer. In this review paper, different classification and segmentation techniques are discussed.

Keywords:
 Image Segmentation, Classification and Mining Techniques.


References:

1.       Zeng, Hong, and Aiguo Song. “Optimizing Single-Trial EEG Classification by Stationary Matrix Logistic Regression in Brain-Computer Interface.” (2015).
2.       Al-Shaikhli, Saif Dawood Salman, Michael Ying Yang, and Bodo Rosenhahn. “Brain tumor classification using sparse coding and dictionary learning.” Image Processing (ICIP), 2014 IEEE International Conference on. IEEE, 2014.

3.       Pereira, Sérgio, et al. “Brain Tumor Segmentation using Convolutional Neural Networks in MRI Images.” (2016).

4.       Anitha, V., and S. Murugavalli. “Brain tumour classification using two-tier classifier with adaptive segmentation technique.” IET Computer Vision 10.1 (2016): 9-17.

5.       Nandpuru, Hari Babu, S. S. Salankar, and V. R. Bora. “MRI brain cancer classification using support vector machine.” Electrical, Electronics and Computer Science (SCEECS), 2014 IEEE Students’ Conference on. IEEE, 2014.

6.       Jui, Shang-Ling, et al. “Brain MR image tumor segmentation with 3-Dimensional intracranial structure deformation features.” (2015).

7.       Yang, Xiaofeng, and Baowei Fei. “A MR brain classification method based on multiscale and multiblock fuzzy C-means.” Bioinformatics and Biomedical Engineering,(iCBBE) 2011 5th International Conference on. IEEE, 2011.

8.       Ibrahim, Walaa Hussein, Ahmed AbdelRhman Ahmed Osman, and Yusra Ibrahim Mohamed. “MRI brain image classification using neural networks.” Computing, Electrical and Electronics Engineering (ICCEEE), 2013 International Conference on. IEEE, 2013.

9.       Joshi, Dipali M., N. K. Rana, and V. M. Misra. “Classification of brain cancer using artificial neural network.” Electronic Computer Technology (ICECT), 2010 International Conference on. IEEE, 2010.

10.    Othman, Mohd Fauzi Bin, Noramalina Bt Abdullah, and Nurul Fazrena Bt Kamal. “MRI brain classification using support vector machine.” Modeling, Simulation and Applied Optimization (ICMSAO), 2011 4th International Conference on. IEEE, 2011.

11.    Boberek, Marzena, and Khalid Saeed. “Segmentation of MRI brain images for automatic detection and precise localization of tumor.” Image Processing and Communications Challenges 3. Springer Berlin Heidelberg, 2011. 333-341.

12.    Ji, Zexuan, et al. “Fuzzy local Gaussian mixture model for brain MR image segmentation.” Information Technology in Biomedicine, IEEE Transactions on 16.3 (2012): 339-347.

13.    Dawngliana, Malsawm, et al. “Automatic brain tumor segmentation in MRI: Hybridized multilevel thresholding and level set.” Advanced Computing and Communication (ISACC), 2015 International Symposium on. IEEE, 2015.

 

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12.

Authors:

Revathi Nath H A, Jeena R S

Paper Title:

An Efficient Algorithm for Reversible Data Hiding in Encrypted Images by RRBE

Abstract: Recently reversible data hiding in encrypted images is gaining importance as this technique of watermarking can reconstruct the original image after extracting the desired data hidden in the image. In all the previous works, room was reserved for data in the image and the image would be encrypted using a standard stream cipher. This work proposes a technique for reversible data hiding in encrypted images where the data to be hidden is encrypted using Advanced Encryption Standard (AES) that can improve the PSNR. Also the encrypted image holding data would be permuted and transmitted, that can increase the level of security. Experimental results show that this method can achieve a PSNR of more than 60db thereby increasing the embedding rate.

Keywords:
Advanced Encryption Standard, Block merging, Image permutation, Reserving Room before encryption


References:

1.       W. Bender, D.Gruhl, N.Morimoto and A.Lu., Techniques For Data Hiding, IBM Systems Journal ,Vol.35,Pp 313-336,1996
2.       C.W.Honsinger, P.W.Jones, M.Rabbani and J.C.Stoffel, Lossless Recovery Of An Original Image Containing Embedded Data, U S Patent, Ed, 2001

3.       T.Kalker and F.M.Willems. “Capacity bounds and code construction for reversible datahiding,” in proc.14th Int. Conf. Digital Signal Processing (DSP2002), 2002, pp. 71-76.

4.       W. Zhang, B. Chen, and N. Yu, “Capacity-approaching codes for reversible data hiding,” in Proc 13th Information Hiding (IH’2011).LNCS 6958, 2011, pp. 255-269, Springer – Verlag.

5.       W. Zhang, B. Chen, and N. Yu, “ Improving various reversible data hiding shemes via optimal codes for binary covers,” IEEE Trans. Image Process., vol. 21, no. 6, pp. 2991-3003, Jun. 2012

6.       J. Fridric h and M. Goljan, “Lossless data embedding for all image for-mats,” in Proc. SPIE proc. Photonics West, Electronic Imaging, Security and Watermarking of
Multimedia Contents, San Jose, CA, USA, Jan. 2002, vol. 4675, pp. 572-583

7.       J. Tian, “Reversible data embedding using a difference expansion,” IEEE Trans. Circuits Syst. Video Technol., vol. 13, no. 8, pp. 890-896, Aug. 2003

8.       Z Ni, Y. Shi, N. Ansari, and S. Wei, “Reversible data hiding,” IEEE Trans. Circuits Syst. Video Technol., vol. 16, no. 3, pp. 354-362, Mar. 2006

9.       D.M. Thodi and J.J. Rodriguez, “Expansion embedding techniques for reversible watermarking,” IEEE Trans. Image Process., vol. 16, no. 3, pp. 721-730, Mar. 2007.

10.    X.L. Li, B. Yang, and T. Y. Zeng, “Efficient reversible watermarking based on adaptive prediction-error expansion and pixel selection,” IEEE Trans. Image Process., vol. 20, no. 12, pp. 3524-3533, Dec. 2011.

11.    P. Tsai, Y. C. Hu, and H. L. Yeh, “Reversible image hiding scheme using predictive coding and histogram shifting,” Signal Process., vol. 89, pp. 1129-1143, 2009.

12.    L. Luo et al., “Reversible image watermarking using interpolation technique,” IEEE Trans. Inf. Forensics Security, vol. 5, no. 1, pp. 187-193, Mar. 2010.

13.    Sachnev, H. J. Kim, J. Nam, S. Suresh, and Y.-Q. Shi, “Reversible Waterm- arking algorithm using sorting and prediction,” IEEE Trans. Circuits Syst. Video Technol., vol. 19, no. 7, pp. 989-999, Jul. 2009.

14.    J. Menezes, P. C. van Oorschot, and S. A. Vanstone, Handbook of Applied Cryptography. Boca Raton, FL, USA: CRC, 1996

15.    K. Hwang and D. Li, “Trusted cloud computing with secure resources and data coloring,” IEEE Internet Comput., vol. 14, no. 5, pp. 14-22, Sep./Oct. 2010.

16.    M. Johnson, P. Ishwar, V. M. Prabhakaran, D. Schonberg, and K. Ramachandran, “On compressing encrypted data,” IEEE Trans. Signal Process., vol. 52, no. 10, pp.2992-3006, Oct. 2004.

17.    W. Liu, W. Zeng, L. Dong, and Q. Yao, “Efficient compression of encrypted grayscale images,” IEEE Trans. Image Process. vol. 19, no. 4, pp. 1097-1102, Apr. 2010.

18.    X. Zhang, “Reversible data hiding in encrypted images,” IEEE Signal Process. Lett., vol. 18, no. 4, pp. 255-258, Apr. 2011.

19.    W. Hong, T. Chen, and H. Wu, “An improved reversible data hiding in encrypted images using side match,” IEEE Signal Process. Lett., vol. 19, no. 4, pp. 199-202, Apr. 2012.

20.    X. Zhang, “Separable reversible data hiding in encrypted image,” IEEE Trans. Inf. Forensics Security, vol. 7, no. 2, pp. 826-832, Apr. 2012.

21.    Kese Ma, Weiming Zhang, Xianfeng Zhao, “Reversible data hiding in Encrypted images by reserving room before encryption” IEEE Transactions on information forensics and security, Vol.8, No.3, March 2013

22.    Wien Honga, Tung-Shou Chen, Reversible Data Embedding For High Quality Images Using Interpolation And Reference Pixel Distribution Mechanism., Elsevier Journal For Visual Image R.22(2011) 131-140.

23.    Diljith.N.Thodi And Jeffrey.J.Rodriguez, Expansion Embedding Techniques For Reversible Watermarking, IEEE Transactions On Image Processing, Vol.16, No.3, March 2007

24.    Jessica Fridrich, Niroslav Goljan, Lossless Data Embedding With File Size Preservation, Proc. SPIE 5306, Security, Stenography And Watermarking Of Multimedia contents Vi, 354(June22,2004)

25.    Ching -Yu Chang, Chih – Hung Lin And Wu – Chih Hu, Reversible Data Hiding For High Quality Images Based On Integer Wavelet Transform, Journal Of Information Hiding And Multimedia Signal Processing Ubiquitous International, Volume 3,No.2, April 2012

26.    M.Pitchchaiah, Philenon Daniel, Praveen, Implementation Of Advanced Encry- ption Standard Algorithm, International Research Volume 3,Issue 3, March -2012.

27.    Miscellaneous Gray Level Images (Online) Available: http:// decsai. ugr.es/ cvg/ dbimagenes/ g512.php

 

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13.

Authors:

Bhagwat P. Dwivedi, Shiv Kumar, Babita Pathik

Paper Title:

Intrusion Detection over Networking KDD Dataset using Enhance Mining Algorithm

Abstract: The intrusion detection systems (IDSs) generate large number of alarms most of which are false positives. Fortunately, there are reasons for triggering alarms where most of these reasons are not attacks. In this research, a rule based technique which is the enhancement of genetic algorithm has been developed. For this, The networking data and intrusion over the data is find to extract to recognize various entities into it. Data mining and its algorithm to process, data extraction, and data analysis is an important phase to monitor the features in it. Intrusion detection process follows the clustering and classification technique to monitor the data flow in it. In this paper our investigation is about to observe available algorithm for the intrusion detection. Algorithm such as Genetic, SVM etc have been processed over KDD cup 10% of dataset which contain 41 attributes and large number of data availability. Here our experiment also conclude that the proposed feature extraction algorithm outperform as best than the existing algorithm with computation parameter such as precision, recall and its accuracy.

Keywords:
 Intrusion Detection, Clustering Technique, Data Mining, KDD.


References:

1.       Zhan Jiuhua Intrusion Detection System Based on Data Mining Knowledge Discovery and Data Mining, 2008. WKDD 2008.
2.       Bane Raman Raghunath Network Intrusion Detection System (NIDS)Emerging Trends in Engineering and Technology, 2008. ICETET ’08.

3.       Changxin Song Design of Intrusion Detection System Based on Data Mining Algorithm 2009 International Conference on Signal Processing Systems.

4.       Wang Pu Intrusion detection system with the data mining technologies Communication Software and Networks (ICCSN), 2011 IEEE 3rd International Conference.

5.       Gaikwad, D.P. Sonali Jagtap, Kunal Thakare, Vaishali Budhawant Anomaly Based Intrusion Detection System Using Artificial Neural Network and fuzzy clustering International Journal of Engineering Research & Technology (IJERT), ISSN: 2278-0181, 1 (9.) (2012 November).

6.       Goyal, C. Kumar GA-NIDS: A Genetic Algorithm based Network Intrusion Detection System, Electrical Engineering and Computer Science, North West University Technical Report (2008).

7.       G. Gu, P. Porras, V. Yegneswaran, M. Fong, W. Lee BotHunter: detecting malware infection through IDS-driven ialog correlation Proc. of 16th USENIX Security Symp. (SS’07) (2007 Aug), pp. 12:1–12:16.

8.       G. Gu, J. Zhang, W. Lee BotSniffer: detecting botnet command and control channels in network traffic Proc. of 15th Ann. Network and Distributed Sytem Security Symp. (NDSS’08) (2008 Feb).

9.       Ketan Sanjay Desale, Roshani Ade,” Genetic algorithm based feature selection approach for effective intrusion detection system”, IEEE 2015.

10.    Kajal rai, “Decision Tree Based Algorithm for Intrusion Detection”, Volume: 07 Issue: 04 Pages: 2828-2834 (2016) ISSN: 0975-0290.

 

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Issue-3 February 2017

Volume-6 Issue-3 Published on February 28, 2017
 Download Abstract Book

S. No

Volume-6 Issue-3, February 2017, ISSN:  2249-8958 (Online)
Published By: Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd. 

Page No.

1.

Authors:

Lerdlekha Sriratana, Sawatdee Poochong, Kridsda Bisalyaputra

Paper Title:

A Study on Thailand Solar Energy Business Opportunity in Very Small Power Producer (VSPP) Sector Contributed by Feed-in Tariff

Abstract: In recent Thailand energy business, solar power plants have high potential due to a clean and renewable energy of solar power. However, the information about solar energy business opportunity is also essential for private sector investment. Since 2013, Feed-in Tariff (FiT) has been announced to replace the Adder measure that also results in the difference of electricity cost structures. This study presents the review of solar energy business opportunity contributed by FiT focusing on Very Small Power Producer (VSPP) sector. The analysis of Adder and FiT measures in terms of business promotion was performed. Also, an 8 MW VSPP solar farm project was selected as a case study for investment analysis contributed by FiT. From analysis, it can be noted that the benefit from electricity purchase rate contributed by FiT would be lower than that of the Adder due to the high costs of PV system recently which is also included in the initial investment. However, if the technology and other related costs of PV system decrease, the solar power projects subsidized by the FiT would be more worthwhile for investment in the future.

Keywords:
Solar Energy, Policy, Subsidy, Measure, Investment


References:

1.    Department of Alternative Energy Development and Efficiency (DEDE), The Solar Map. Bangkok: Ministry of Energy, 2002.
2.    Open Energy Information. (2016). Solar Resources by Class per Country [Online]. Available http://en.openei.org/datasets/node/498

3.    Energy Policy and Planning Office (EPPO), Power Development Plan 2015–2036 (PDP2015). Bangkok: Ministry of Energy, 2015.

4.    M. Chimres and S. Wongwises, “Critical review of the current status of solar energy in Thailand,” Renewable and Sustainable Energy reviews, vol. 58, 2016, pp. 198-207. 

5.    Energy Policy and Planning Office (EPPO), Policy and Plan. Bangkok: Ministry of Energy, 2016.

6.    Energy Regulatory Commission (ERC). (2016). SPP/VSPP database [Online]. Available http://www.erc.or.th/ERCSPP/Default.aspx

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2.

Authors:

M. Shoukath Ali, R. P. Singh

Paper Title:

A Study on Game Theory Approaches for Wireless Sensor Networks

Abstract:  Game Theory approaches and their application in improving the performance of Wireless sensor networks (WSNs) are discussed in this paper. The mathematical modeling and analysis of WSNs may have low success rate due to the complexity of topology, modeling, link quality and etc, however Game Theory is a field, which can efficiently used to analyze the WSNs. Game theory is related to applied mathematics that describes and analyzes interactive decision situations. Game theory has the ability to model independent, individual decision makers whose actions affect the surrounding decision makers. The outcome of Complex interactions among rational entities can be predicted by a set of analytical tools, however the rationality demands a stringent observance to a strategy based on measured of perceived results. Researchers are adopting game theory approaches to model and analyze leading wireless communication networking issues, which includes QoS, power control, resource sharing and etc.

Keywords:
Wireless sensor network; Game Theory; Cooperative game theory; Non-cooperative game theory; Wireless communications.


References:

1.       Renita Machado, Sirin Tekinay, “A surve of game theoretic approaches in wireless sensor networks”-computer networks 52 (2008), pp 3047-3061.
2.       Erik Pertovt, Tomax javornik, Michael Mohorcic, “Game theory application for performance optimization in wireless networks”-pp287-292, 2011.

3.       Gengzhong zheng,” Study on the power control of wireless sensor networks based on Game theory”-Journal of information and computational science 7:4(2010) 957-964.

4.       Pedro O.S.Vaz De Melo, Cesar Fernandes, Raquel A.F.Mini, Aotonio. A.F.Loureiro and Virigilio.A.F.Almeda,”Game theory in wireless sensor networks”.

5.       R.J.Aumann and M.Maschler,”Game theoretic analysis of a bankruptcy problem from the Talmud” J.Econ. Theory, vol 36, pp 195-213, 1985.

6.       Ali, M. Shoukath. “Priority Based Packet Scheduling Scheme in Wireless Sensor Networks.”, IJARF, Volume 3, Issue 8, August 2016.

7.       P.Walker, “An outline of his history of game theory”, Available at: http://William – king.www.drekel.edu/top/class /histf.html April 1995.

8.       A.B.Mackenzie and Stephen B.Wicker, “Game theory and the design of self-configuring, Adaptive wireless networks”-IEEE communication, Nov 2001.

9.       S.Metha and K.S.Kwak, “Application of game theory to wireless sensor networks”- Inha university, Korea.

10.    Garth.V.Crosby, Niki Pissinou, “Evolution of cooperation in multi-class wireless sensor networks”-32nd IEEE conferences on local computer networks.

11.    J.F.Nash, “Equilibrium points in n-person game” Proc.Natl. Acad.Sci. U.S.A. vol.36, no.1, pp.48-49, January 1950.

12.    J.John F.Nash, “The bargaining problem”, Econometrica, vol.18, no.2, pp.155-162, April 1950.

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3.

Authors:

Ahammad Vazim K. A., Jesin T. A., Anil Raj B., Midhun A. R., Sreekutten K. 

Paper Title:

Design and Fabrication of a Novel Low Cost Food Waste Composting System with Accelerating Process Technology

Abstract: Waste disposal is one of the biggest problems faced by the most countries. Unless and otherwise a proper methodology is met to treat the domestic and industrial effluents the public health and environment will face serious problems. Our project finds its application in the safe treatment of food waste aerobically with the help of mechanical agitation to reduce the risk of contamination in our households. Composting can be defined as the biological decomposition of organic matter under controlled, aerobic conditions into a stable product that may be used to improve soil quality or as a potting medium. Composting also disinfects organic wastes so that they may be beneficially used in a safe matter. The purpose of the project was to design and fabricate a low cost food waste composting system which ultimately accelerate the composting process. Experimentally it was found that the composting of normal vegetable residues take about 60 days with the help of a bacterial composter, like any biochemical reaction time duration required for the completion of composting was contributed by many factors which includes particle size, water content, temperature, air circulation. The device fabricated was fully functional in controlling the major factors among the above stated and can accelerate the overall process by 50%.

Keywords:
 food waste, composting system, accelerating process technology


References:

1.    Ajinkya S Hande and Vivek Padole, International  Journal  of  Innovative  Research  in  Science  and  Technology, Volume 2, Issue 03, 2015.
2.    Tom L Richard, Tom L Richard, Biomass and Bioenergy Vol. 3, Nos 34, pp. 163-I 80. Pergamon Press Ltd, Great Britain Received 22 May 1992; accepted 7 July 1992.

3.    Delia Teresa Sponza and Osman Nuri Agdag, Microbial  Technology  36(2005)25-3-Journal  of  Environmental  Engg., 2004.

4.    M. de Bertoldi, G. Vallini and A. Pera, Notes, International Solid Waste Management Association.

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4.

Authors:

Amiya Ranjan Malik, Bibhuti Bhusan Pani, Sushant Kumar Badjena

Paper Title:

Powder Metallurgy Processed Ferrous Composites: A Review

Abstract: This paper reviews processing and synthesis of particulate reinforced ferrous based Metal Matrix Composites (MMC) and Nanocomposites through Powder Metallurgy (P/M) method. By this route it is possible to manufacture MMCs with wide range of compositions and density. As a result there is improvement of wear resistance, abrasion resistance, corrosion resistance, mechanical properties and high temperature friction properties. The reinforcing particles commonly adopted were carbides, oxides, borides, nitrides, carbonitrides, complex carbides, intermetallics, synthetic materials etc. Apart from this it also reviews how several factors affect properties of MMCs.

Keywords:
Ferrous Matrix Composites, Nanocomposites, Particle reinforcement, Powder Metallurgy.


References:

1.       O. N. Dogan, J. A. Hawk, J. H. Tylczak, R. D. Wilson, R. D. Govier, Wear of titanium carbide reinforced metal matrix composites. Wear, Volumes 225–229, Part 2, April 1999, Pages 758-769.
2.       E. Pagounis, E. Haimi, J. Pietikainen, M. Talvitie, S. Vahvaselka, V. K. Lindroos, Effect of Thermal expansion coefficients on the martensitic transformation in a steel matrix composite. Scripta Materialia, vol. 34, No.3, pp.407-413, 1996.

3.       E. Pagounis, M. Talvitie, V. K. Lindroos, Influence of metal ceramic interface on the microstructure and mechanical properties of HIPed iron-based composites. Composites Science and Technology 56 (1996) 1329-1337.

4.       T. Ram Prabhu, V. K. Varma, Srikanth Vedantam, Effect of reinforcement type ,size and volume fraction on the tribological behaviour of Fe matrix composites at high sliding speed condition. Wear 309 (2014) 247-255.

5.       T. Ram Prabhu, V. K. Varma, Srikanth Vedantam, Effect of SiC volume fraction and size on dry sliding wear of Fe/Sic/Graphite hybrid composites for high sliding wear application. Wear 309 (2004) 1-10.

6.       Sainatee Chakthin, Monnapas Morakotjinda, Thanyaporn yodkaew, Nattaya Torsangtum, Rungtip Krataithong, Pisarn Siriphol, Ornmanee Coovattanachai, Bhanu Vetayanugul, Nandh Thavarungkul, Nuchthana Poolthong, Ruangdaj Tongsri, Influence of carbides on properties of sintered Fe-based composites. Journals of Metals, Materials and Minerals, Vol.18 No.2 pp.67-70, 2008.

7.       Danqing Yi, Pengchao Yu, Bin Hu, Huiqun Liu, Bin Wang, Yong Jiang, Preparation of nickel-coated titanium carbide particulates and their use in the production of reinforced iron matrix composites. Materials and Design Volume 52, December 2013, page 572-579.

8.       XIAO Zhi-Yu, FANG Liang, ZHANG Wen, SHAO Ming, LI Yuan-Yuan, Fabrication of NbCp-reinforced iron matrix composites by PM techniques and its warm compaction. Journal of  Iron  and Steel Research, International, Volume 14, Issue 5, Supplement 1, September 2007, Pages 66-69.

9.       B. Sustarsic, M. Jenko, M. Godec, L. Kosec, Microstructural investigation of NbC-doped vacuum-sintered tool-steel-based-composites. Vacuum, Volume 71, Issues 1–2, 9 May 2003, Pages 77-82.

10.    E. Gordo, F. Velasco, N. Anton, J. M. Torralba, Wear mechanism in high speed steel reinforced with (NbC)p and (TaC)p MMCs. Wear volume 239, issue 2, April 2000, page 251-259.

11.    H. Fallahdoost, H. Khorsand, R. Eslami-Farsani, E. Ganjeh, On the tribological behaviour of nanoalumina reinforced low alloy sintered steel.  Materials and Design 57 (2014) 60-66.

12.    Pallav Gupta, Devendra Kumar, M. A. Quraishi, Om Parkash, Corrosion behaviour of Al2O3 reinforced Fe metal matrix nanocomposites produced by powder metallurgy technique. Advanced Science, engineering and medicine, volume 5, Number 4, April 2013, page.366-370(5).

13.    C. Parswajinan, B. Vijaya Ramnath, C. Elanchezhian, S. V. Pragadeesh, P. R. Ramkishore, V. Sabarish, Investigation on Mechanical Properties of Nano Ferrous Composite. Procedia engineering 97 (2014) 513-521.

14.    T. J. Goodwin, S. H. Yoo, P. Matteazzi, J. R. Groza, Cementite   Iron    Nanocomposite.  Nanostructured materials volume 8, issue 5, August 1997 page 559-566.

15.    Eugene E. Feldshtein, Larisa N. Dyachkova, On the properties and tribological behaviour of P/M composites reinforced with ultrafine particulates. Composites part: B volume 58, march 2014, page 16-24.

16.    Ping Han, Fu-ren Xiao, Wen-jun Zou, Bo Liao, Effect of different oxide addition on the thermal expansion coefficients and residual stress of Fe-based diamond composites. Ceramic International 40 (2014) 5007-5013.

17.    Katie Jo Sunday, Kristopher K. Darling, Francis G. Hanejko, Babak Anasori, Yan-Chun Li, Mitra L. Taheri, Al2O3  “self coated” iron powder composite via mechanical milling. Journals of Alloys and Compounds 653 (2015) 61-68.

18.    F. Velasco, R. Isabel, N. Anton, M. A. Martinez, J. M. Torralba, TiCN-high speed steel composites: sinterability and properties. Composite part A: Applied science and manufacturing volume 33, issue 6, June 2002, 819-827.

19.    B. Gomez, A. Jimenez-Suarez, E. Gordo, Oxidation and tribological behaviour of an Fe-based MMC reinforced with TiCN particles. Int. Journal of Refractory metals & hard materials volume 27, issue 2, march 2009, 360-366.

20.    G. Herranz, A. Romero, V. De Castro, G. P. Rodriguez, Processing of AISI M2 high speed steel reinforced with vanadium carbide by solar sintering. Material and Design volume 54, February 2014, 934-946.

21.    Guangming Zhang, Keqin Feng, Ying Li, Huifang Yue, Effect on sintering process on preparing iron-based friction material directly from vanadium bearing titanomagnetite concentrates. Materials and Design 86 (2015) 616-620.

22.    Guangming Zhang, Keqin Feng, Synthesis of iron-based friction material by in situ reactive sintering from Vanadium bearing titanomagnetite. Materials and manufacturing processes volume-31, issue-2, 2015, page 198-205.

23.    D. Lou, J. Hellman, D. Luhulima, J. Liimatainen, V. K. Lindroos, Interactions between tungsten carbide (WC) particulates and metal matrix in WC-reinforced composites. Material science and engineering: A volume 340, issue 1-2, January 2003, page 155-162.

24.    S. C. Tjong, K. C. Lau, Abrasion   resistance   of   stainless-steel composites reinforced with hard TiB2 particles. Composites science and technology volume 60, issue 8, June 2000, page 1141-1146.

25.    J. Abenojar, F. Velasco, J. M. Torralba, J. A. Bas, J. A. Calero, R. Marce, Reinforcing 316L stainless steel with intermetallic and carbide particles. Material science and engineering: A, volume 335, issue 1-2, 25 September 2002, page 1-5.

26.    J. Abenojar, F. Velasco, A. Bautista, M. Campos, J. A. Bas, J. M. Torralba, Atmosphere influences in sintering process of stainless steels matrix composites reinforced with hard particles. Composites science and technology, volume 63, issue 1, January 2003, page 69-79.

27.    Wang Jing, Wang Yisan, Ding Yichao, Production of (Ti,V)C reinforced Fe matrix composites. Material science and engineering: A volume 454-455, 25 April 2007, page 75-79.

28.    Ileana Nicoleta Popescu, Constantin Ghita, Vasile Bratu, Guillermo Palacios Navarro, Tribological behaviour and statistical experimental design of sintered iron-copper based composites. Applied Surface Science 285P (2013) 72-85.

29.    Hans Berns, Birgit Wewers, Development of an abrasion steel composite with in situ TiC particles. Wear 251(2001) 1386-1395.

30.    P. Mohan Raj, N. Selvakumar, R. Narayanasamy, C. Kailasanathan, Experimental investigation on workability and strain hardening behaviour of Fe-C-Mn sintered composites with different percentage of carbon and manganese content. Materials and Design 49 (2013) 791-801.

31.    N. Selvakumar, A. P. Mohan Raj, R. Narayanasamy, Experimental investigation on workability and strain hardening behaviour of Fe-C-0.5Mn sintered composites. Materials and Design 41 (2012) 349-357.

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5.

Authors:

Ashok R Mundhada, Arun D Pofale

Paper Title:

Concrete’s Odyssey Through Heat: A Review

Abstract: Fire is a catastrophic event to which any building can fall victim during its lifetime. Not only does it pose a direct threat to the occupants through the release of harmful gases and devastating heat, but the elevated temperatures themselves also have seriously adverse effects on the structural integrity of entire building. Though undesired, fire is an exigency that cannot be avoided altogether. Therefore, impact of fire on concrete/ RCC deserves minute scrutiny. In this study, a review is carried out based on the experimental studies on the performance of concrete/RCC when exposed to FIRE/ higher temperatures. The compiled test data revealed distinct difference in mechanical properties of normal, high strength, self compacting & improvised concrete. Shape & size of specimens, concrete grade, admixtures, temperature level, applied load, exposure time to heat, rate of heating, rate of cooling, specimen type (stressed/unstressed member), type of cooling etc were the parameters that influenced the test results. Exposure time, exposure temperature & concrete cover were observed to be the principal factors. The outcome of the review helped in identifying the main problem areas, dubious claims & gaps/ lacunae in the research works.

Keywords:
 Concrete, Fire, RCC, Spalling


References:

1.       P.D. Morley, R. Royles, “The influence of high temperature on the bond in reinforced concrete”, Fire Safety Journal, Volume 2, Issue 4, 1980, pp. 243-255
2.       Chandra S & Baerntsson L, “Some effects of polymer addition on the fire resistance of concrete”, Cement and Concrete Research, Vol.10, 1980, pp. 367-375

3.       H. Gustaferro, T. D. Lin, “Rational design of reinforced concrete members for fire resistance”, Fire Safety Journal, Volume 11, Issues 1-2, 1986, pp. 85-98

4.       Gabriel A. Khoury, Patrick J. E. Sullivan, “Research at Imperial College on the effect of elevated temperatures on concrete”, Fire Safety Journal, Volume 13, Issue 1, 1988, pp. 69-72

5.       Bruce Ellingwood and T. D. Lin, “Flexure and shear behavior of concrete beams during fires”, Journal of Structural Engineering, Vol. 117, No. 2, ©ASCE, ISSN 0733-9445/91, Paper No. 25549, 1991, pp. 440-458

6.       Bruce R. Ellingwood, “Impact of fire exposure on heat transmission in concrete slabs”, Journal of Structural Engineering, ASCE, Vol 117, 1991

7.       S. C. Chakrabari, K. N. Sharma, Abha Mittal, “Residual strength in concrete after exposure to elevated temperature”, The Indian Concrete Journal, 1994, pp. 713-717

8.       Sunil Kumar & Rao Kameswara, “Fire Load in Residential Buildings”, Elsevier Building and Environment, Vol. 30, No. 2, 1995, pp. 299-305

9.       M. M. El-Hawary, A. M. Ragab, K. M. Osman and M. M. Abd El-Razak, “Behavior investigation of concrete slabs subjected to high temperatures”, Elsevier, Computers & Structures, Vol. 61, No. 2, 1996, pp. 345-360

10.    M. M. El-Hawary, A. M. Ragab, A. Abd El-Azim and S. Elibiari, “Effect of fire on shear behaviour of R.C. beams”, Elsevier, Computers & Structures, Vol. 65, No. 2,
1997, pp. 281-287

11.    James A. Milke, “Analytical methods to evaluate fire resistance of structural members”, Journal of Structural Engineering, ASCE, 25 (10), 1999, pp. 1179-1187

12.    Y. N. Chan, G. F. Peng, M. Anson, “Residual strength and pore structure of high-strength concrete and normal strength concrete after exposure to high temperatures”, Elsevier Cement and Concrete Composites 21, 1999, pp. 23-27

13.    Long T. Phan & Nicholas J. Carino, “Fire performance of high strength concrete: Research Needs”, Proceedings of ASCE/SEI Structures Congress, Philadelphia, USA, 2000

14.    V. K. R. Kodur, “Spalling in High Strength Concrete Exposed to Fire — Concerns, Causes, Critical Parameters and Cures”, Proceedings of ASCE/SEI Structures Congress, Philadelphia, USA, 2000, pp. 1-8

15.    Jean-Marc Franssen and Venkatesh Kodur, “Residual Load Bearing Capacity of Structures Exposed to Fire”, Structures-A Structural Engg Odyssey, ASCE Conference Proceedings 109, 89 2001

16.    Beth Tubbs, “ICC Performance Code for Buildings and Facilities — Structural Fire Protection Provisions”, Structures-A Structural Engg Odyssey, ASCE Conference Proceedings 109, 80, 2001

17.    George Faller, “Fire Resistance Requirements for Buildings: A Performance Based Approach”, Structures-A Structural Engg Odyssey, ASCE Conference Proceedings, Section: 37, 2001, pp. 1-12

18.    D. Bennetts,  C. C. Goh, “Fire behaviour of steel members penetrating concrete walls”, Electronic Journal of Structural Engineering, 1, 2001, pp. 38-51

19.    R. Sri Ravindrarajah, R. Lopez and H. Reslan, “Effect of Elevated Temperature on the Properties of High-Strength Concrete containing Cement Supplementary Materials”, 9th International Conference on Durability of Building Materials and Components, Rotterdam, Netherlands, Paper 081, 2002, 8 pages

20.    Colin Bailey, “Holistic behaviour of concrete buildings in fire”, Proceedings of the Institution of Civil Engineers, Structures and Buildings 152, Issue 3, 2002, pp. 199-212

21.    W. K. Chow, “Proposed Fire Safety Ranking System EB-FSRS for Existing High-Rise Nonresidential Buildings in Hong Kong”, Journal of Architectural Engineering, ASCE, vol. 8, No. 4, 2002

22.    Dr. A Kumar, V Kumar, “Behaviour of RCC Beams after Exposure to Elevated Temperatures”, Journal of the Institution of Engineers (I), Vol. 84, 2003, pp. 165-170

23.    K.D. Hertz, “Limits of spalling of fire-exposed concrete”, Elsevier Fire Safety Journal 38, 2003, pp. 103–116

24.    Faris Ali, Ali Nadjai, Gordon Silcock, Abid Abu-Tair, “Outcomes of a major research on fire resistance of concrete columns”, Elsevier Fire Safety Journal, 39, 2004, pp. 433–445

25.    Fu-Ping Cheng; V. K. R. Kodur and Tien-Chih Wang, “Stress-Strain Curves for High Strength Concrete at Elevated Temperatures”, Journal of Materials in Civil Engineering © ASCE, 2004, pp. 84-90

26.    Bonnie E. Manley, “Rehabilitation of Existing Structures in the NFPA C3 Code Set”, Structures — Building on the Past: Securing the Future, ASCE Proceedings of Structures Congress, 2004

27.    Xudong Shi; Teng-Hooi Tan; Kang-Hai Tan; and Zhenhai Guo, “Influence of Concrete Cover on Fire Resistance of Reinforced Concrete Flexural Members”, ASCE Journal of Structural Engineering, Vol. 130, No. 8, ISSN 0733-9445, 2004,  pp. 1225-1232

28.    V. K. R. Kodur and L. A. Bisby, “Evaluation of Fire Endurance of Concrete Slabs Reinforced with Fiber-Reinforced Polymer Bars”, Journal of structural engineering © ASCE, January 2005, pp. 34-43

29.    B. Georgali, P.E. Tsakiridis 2005, “Microstructure of fire-damaged concrete: A case study”, Cement & Concrete Composites 27 © Elsevier, 2005, pp. 255-259

30.    Michael L. Tholen, Amy Reineke Trygestad, “New engineers under fire”, Concrete International, Volume 1, Issue 07, USA, July 2005, pp. 45-48

31.    Z. Huang, Ian W. Burgess & Rojer J. Plank, “Behaviour of Reinforced Concrete Structures in Fire”, Structures in Fire Workshop, 2006

32.    B Stawiski, “Attempt to estimate fire damage to concrete building structure”, Archives of Civil & Mechanical Engineering, Vol 6, No 4, 2006, pp. 23-28

33.    Richard Barnes and James Fidell, “Performance in Fire of Small-Scale CFRP Strengthened Concrete Beams”, Journal of composites for construction © ASCE / December 2006, pp. 503-508

34.    Xin Yan; Hui Li and Yuk-Lung Wong, “Assessment and Repair of Fire-Damaged HSC: Strength and Durability”, Journal of materials in civil engineering © ASCE, June 2007, pp. 462-469

35.    Ufuk Dilek, “Assessment of Fire Damage to a Reinforced Concrete Structure during Construction”, Journal of performance of constructed facilities © ASCE, 2007, pp. 257-263

36.    Ian A. Fletcher, Stephen Welch, Jose L. Torero, Richard O. Karvel, “The behaviour of concrete structures in fire”, BRE Research Publications, The University of Edinburgh, UK , 2007

37.    Ilker Bekir Topcu and Cenk Karakurt, “Properties of reinforced concrete steel rebars exposed to high temperatures”, Research Letters in Materials Science, Article ID 814137, 2008

38.    David N. Bilow, Mahmoud E. Kamara, “Fire and Concrete Structures”, Part of ASCE Structures Congress, Crossing Borders, 2008, pp. 1-10

39.    Colin Gurley, “Structural Design for Fire in Tall Buildings”, Practice Periodical on Structural Design and Construction, ASCE, Vol. 13(2), 2008, pp. 93–97

40.    Kodur V. K. R. and Dwaikat M. B., “Effect of Fire Induced Spalling on the Response of Reinforced Concrete Beams”, International Journal of Concrete Structures and Materials, V 2, No 2, 2008, pp. 71-81

41.    Javadian Alireza, Teng Susanto, Tan Teng Hooi, “High temperature effect on flexural strength of steel-fibre concrete”, Proceedings of the 3rd International Conference ACF/VCA, 2008, pp. 1160-1167

42.    V.K.R. Kodur, “Enhancing resilience of urban structures to withstand fire hazard”, Resilience of Cities to Terrorist and other Threats, Book published by Springer, 2008, pp. 189-216

43.    Prabir Kumar Chaulia; Reeta Das, “Process parameter optimization for fly ash brick by Taguchi method”, Materials Research, Print version ISSN 1516-1439, Vol. 11, No.2, 2008

44.    V. K. R. Kodur, N. K. Raut, “Design equation for predicting fire resistance of reinforced concrete columns”, Structural Concrete, Vol. 10, no. 2,  Michigan State University, USA, 2009

45.    A Ferhat Bingol & Rustam Gul, “Residual bond strength between steel bars and concrete after elevated temperatures”, Elsevier Fire Safety Journal 44, 2009, pp. 854–859

46.    Ahmed Chérif Megri, “Integration of Different Fire Protection/Life Safety Elements into the Building Design Process”, Practice periodical on structural design and
construction © ASCE, 2009, pp. 181 to 189

47.    Masoud Ghandehari; Ali Behnood and Mostafa Khanzadi, “Residual Mechanical Properties of High-Strength Concretes”, Journal of materials in civil engineering © ASCE, January 2010, pp. 59-64

48.    John L. Gross and Long T. Phan, “Summary of Best Practice Guidelines for Structural Fire Resistance Design of Concrete and Steel, ASCE Proceedings of the Structures Congress, 2010, pp. 2369-2379

49.    Zhaohui Huang,“The behaviour of reinforced concrete slabs in fire”, Elsevier Fire Safety Journal 45, 2010, pp. 271–282

50.    V. K. R. Kodur, M. B. Dwaikat, “Design equation for predicting fire resistance of reinforced concrete beams”, Enginering Structures (Elsevier), Vol. 33, Issue 2, 2011, pp. 602–614

51.    Kulkarni D. B. & Patil S. N., “Comparative Study of Effect of Sustained High Temperature on strength Properties of Self Compacting Concrete and Ordinary Conventional Concrete”, International Journal of Engineering and Technology, ISSN: 0975-4024, Vol.3 (2), 2011, pp. 106-118

52.    N. K. Raut, V. K. R. Kodur, “Response of High-Strength Concrete Columns under Design Fire Exposure”, ASCE Journal of Structural Engineering, Vol. 137, No.1, 2011, pp. 69-79

53.    Peskava S & Prochazka P.P., “Impact of high temperature on different combinations of fiber reinforced concrete”, 36th Conference on Our World in Concrete & Structures Singapore, 2011

54.    Kiang Hwee Tan and Yuqian Zhou, “Performance of FRP Strengthened Beams Subjected to high Temperatures”, Journal of composites for construction © ASCE, June 2011, pp. 304-311

55.    M. Kanéma, P. Pliya, A. Noumowé, and J-L. Gallias, “Spalling, Thermal, and Hydrous Behavior of Ordinary and High-Strength Concrete Subjected to Elevated Temperature”, Journal of materials in civil engineering © ASCE, July 2011, pp. 921-930

56.    M. Bastami, A. Chaboki-Khiabani, M. Baghbadrani, M. Kordi, “Performance of high strength concretes at elevated temperatures, Elsevier Scientia Iranica A, 18 (5),
2011, pp. 1028–1036

57.    Venkatesh Kodur and Wasim Khaliq, “Effect of temperature on thermal properties of different types of high-strength concrete”, Journal of Materials in Civil Engineering © ASCE, June 2011, pp. 793-801

58.    M.V. Krishna Rao, M. Shobha and N. R. Dakshina, “Effect of elevated temperature on strength of differently cured concretes-a study”, Asian Journal of Civil Engineering, Vol. 12, No 1, 2011, pp. 73-85

59.    Rahim, U. K. Sharma, K. Murugesan & A. Sharma, “Optimization of Post-Fire Residual Compressive Strength of Concrete by Taguchi Method”, Journal of Structural Fire Engineering, June 2012, pp169-179

60.    Samir Shihada and Mohammed Arafa, “Mechanical Properties of RC Beams with Polypropylene Fibers under High Temperature”, International Journal of Engineering and Advanced Technology (ijbsac) ISSN: 2249 – 8958, Volume-1, Issue-3, 2012, pp. 194-199

61.    Siddesh Pai & Kaushik Chandra, “Analysis of polyester fibre reinforced concrete subjected to elevated temperatures”, International Journal of Civil, Structural, Environmental and Infrastructure Engineering Research and Development (IJCSEIERD), ISSN 2249-6866, Vol. 3, Issue 1, 2013, pp. 1-10

62.    K. Srinivasa Rao, S. Rakesh kumar, A. Laxmi Narayana, “Comparison of performance of standard concrete and fibre reinforced concrete exposed to elevated temperatures”, American Journal of Engineering Research (AJER), e-ISSN: 2320-0847 p-ISSN: 2320-0936, Volume-02, Issue-03, 2013, pp. 20-26

63.    Ashok R. Mundhada & Dr Arun D. Pofale, “Behavioural study of concrete at high temperatures”, Proceedings of International conference on ‘Recent trends in engineering & technology’, published by ELSEVIER, 2014, pp 243-248

64.    Gai-Fei Peng, Xu-Jing Niu, “Fire resistance of normal concrete, high performance concrete and ultra-high performance concrete: A review”, Proceedings of UKIERI Concrete Congress, India, ISBN: 978-93-84869-83-0, 2015, pp. 1354-1371

65.    Ashok R. Mundhada & Dr Arun D. Pofale, “Effect of elevated temperatures on strength and quality of concrete”, Proceedings of UKIERI Concrete Congress, India, ISBN: 978-93-84869-83-0, 2015, pp. 1402-1410
66.    Anand N & Prince Arulraj G, “The effect of elevated temperature on concrete materials A Literature review”, International Journal of Civil and Structural Engineering, Volume 1, No 4, 2011, pp. 928-938

67.    Malhotra H L, “Design of Fire Resisting Structures”, Surrey University Press, U.K., 1982

68.    Kodur V. K. R. et al., “Structures in Fire: State-of-the-Art, Research and Training Needs”, NIST Workshop Report, NIST GCR 07-915, Dec 2007

69.    Robin P. Nicolai & Rommert Dekker, “Automated Response Surface Methodology for Stochastic Optimization Models with Unknown Variance”, Tinbergen Institute Discussion Paper, The Netherlands, TI 2005-042/4, 2005

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6.

Authors:

Neha Chouhan, Rohit Gupta

Paper Title:

Experimental Investigation for Tool Life by Optimizing Cutting Parameters in Plain Turning Operation by Statistical Methods

Abstract:  Rate of production and tool material cost plays a significant role other than the material cost of the part to be made in a production run from economic point of view.  The maximum production rate can be achieved if the total time required per piece is reduced to a minimum [1]. The paper presents an optimization technique to achieve minimum tool wear which would lead to reduced tool changing time and tooling cost. The experimental layout is designed based on the Taguchi`s L9 orthogonal array technique and analysis of variance (ANOVA) is performed to identify the effect of the cutting parameters on the response variables. Two different set of response variables are used, first, variation of cutting speed with feed and depth of cut, second, variation of rake angle with feed and depth of cut. The calculation is performed using Minitab-17 software.  

Keywords:
Optimization Technique, Taguchi`s L9 orthogonal array, analysis of variance (ANOVA), Minitab-17


References:

1.    A.Ghosh, A K Mallik, Manufacturing Science
2.    https://www.ee.iitb.ac.in/~apte/CV_PRA_TAGUCHI_L9MAN.htm

3.    S. R. Das, R. P. Nayak, & D. Dhupal, “Optimization of the cutting parameters on tool wear and workpiece surface temperature in turning of AISI D2 steel”, International Journal of Lean Thinking, 2012.

4.    K Dhameliya, J Desai, M Gandhi, D Dave, “Experimental investigation of process parameters on MRR and Surface roughness in turning operation on CNC Lathe machine for Mild Steel – E250: IS 2062”

5.    Gunay M., Korkut I., Aslan E. and Eker U., Experimental investigation of the effect of cutting tool rake angle on main cutting force, Journal of materials processing technology,166, pp 44-49, 2005

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7.

Authors:

Muhammad Abdus Samad

Paper Title:

Ergonomics and the Prevention of Musculoskeletal Strain and Back Injuries

Abstract: As technology becomes more complex, so ergonomics is undoubtedly destined to play an increasingly important role in industrial production and industrial health and safety. At the workplace, ergonomics places equal emphasis upon greater system efficiency and improved health of the individual. Ergonomics must be involved in fitting the tool and machine to the worker by design, fitting the worker to the machine by selection and training, and the optimization of the ambient environment to suit the man or the adaptation of the man to tough environmental conditions. Ergonomics aims to promote efficiency, safety and comfort at work situation in industry through better relationship between man, his tools and the work environment. This paper deals about the injuries such as backaches, neck aches, and other muscular strains due to bad seating and incorrect working posture and how to prevent them by designing of workstation that will be very comfortable and convenient to work at. This paper also discusses the optimal conditions for the workers, reduction of physical workload, improvement of working postures and facilitating psycho-sensorial functions in instrument handling, and so on.

Keywords:
Back injury, Workstation design, Human factor, Productivity and Anthropometry.  


References:

1.    Helander, Martin (1943). A Guide to the Ergonomics of Manufacturing.
2.    Kroemer, K. (1994). Egonomics: How to Design for Ease and Efficiency. Englewood Cliffs,NJ: Prentice Hall

3.    Eklund, J. (1997). Ergonomics, quality and continuous improvement— conceptual and empirical relationships in an industrial context, Ergonomics, Vol. 40, 982–1001

4.    Bunning, T. (1998). Designing ergonomically sound assembly workstations, Occupational Hazards, Vol. 60, No. 8, 63–65

5.    Bullinger, H. J. (1986). Systematische montageplanung   , Hanser, Munich (in German)

6.    Pheasant, S. and Haslegrave, C.M. (2005). Bodyspace: Anthropometry, Ergonomics and the Design of Work. Taylory & Francis group, LLC.

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8.

Authors:

Pakinam Ashraf, Hany Ayad, Dina Saadallah

Paper Title:

Sense of Community and Built Environment: How Can Built Environment, Social Economic Conditions and History of Place Shape Our Sense of Community?

Abstract:  Sense of community is a concept in community and social psychology and has been investigated in several researches. The sense of community level changes towards many independent variables and it is related to the quality of the built form. This research aims at investigating the relationship between the sense of community and some determinants such as; the physical environment, the historical background and the socio economic conditions in selected neighborhoods. Furthermore, this research examines the social interaction as it has an important role in measuring the sense of community. To achieve that, the authors propose a methodology composed mainly of two major tools; the first, a survey formed of sense of community indices, as well as other social and psychological factors according to Kim and Kaplan theory. The second tool is based on the observation of physical attributes of the neighborhood. The adopted methodology is applied on two neighborhoods in Alexandria city, Egypt. By analyzing the survey results and the researcher’s observation of physical attributes in the selected neighborhood, it was found that there is a strong correlation between the sense of community and several independent variables such as the built environment, the socio economic conditions, some demographic factors like age, monthly income, length of residence and the importance of pedestrian factors on measuring sense of community.

Keywords:
Sense of community, Built environment, Statistical analysis, Social Interaction, Alexandria neighborhoods.


References:

1.       Abdo, M. M., 2013. The “Open Cities” Approach: A Prospect for Improving the Quality of Life in the City of Alexandria, Egypt, Alexandria, Egypt: Unpublished master thesis.
2.       Alkalash, M. M. F. E., 2014. RETRIEVE THE WATERFRONT ALEXANDRIA: Strategies & Guidelines Framework Towards a Democratic Corniche, MILANO: Unpublished Master’s Thesis.

3.       Berkowitz, L., 1956. Group norms under bomber crews: Patterns of perceived crew attitudes, and crew liking related to air crew effectiveness of Far Eastern combat. Sociometry, Volume 19, pp. 141-153.

4.       Buckner, J., 1988. The Development of an Instrument to Measure Neighbourhood Cohesion. American Journal of community psychology, 16(6), pp. 771-791.

5.       CAPMAS, 2013. Statistical year book, Cairo: Central Agency For Public Mobilization and Statistics.

6.       Chavis, D., J. Hogge, D. McMillan and A. Wandersman, 1986. Sense of Community Through Brunswik’s Lens: A First Look. Journal of Community Psychology, Issue Theory, pp. 14: 24 -40.

7.       Giles-Corti, L. W. &. L. D. F. &. B., 2010. Sense of community and its relationship with walking and neighborhood design2. Social Science & Medicine Elsevier Ltd., Volume 70, pp. 1381-1390.

8.       Hussein, A., 2014. contemporary city | descriptions and projects. [Online]

9.       Available at: http://contemporarycity.org/2014/05/alexandria/[Accessed 10 7 2016].

10.    MARANS, D. O. &. A. R. &. R. W., 2009. Neighborhood satisfaction, sense of community, and attachment: Initial findings from Famagusta quality of urban life study. ITU A|Z, 6(1), pp. 6-20.

11.    Schweitzer, J., 1996. A desription of sense of Community in Lansing Neighbourhoods’ Project. University of Michigan: presented at the “Defining Community, Reinforcing Society” conference.

12.    Seymour Sarason, 1974. The psychological sense of community: Prospects for a community psychology, San Francisco: Jossey-Bass.

13.    The Sense of Commmunity Partners, 2004. Exploring Sense of Community An Annotated Bibliography. Calgary, Canada: the Sense of Community Partners, c/o The City of Calgary Community Strategies.

14.    UNDP, GOPP, MHUUD & CIDA, 2010. State of the built environment and housing indicators of seven Egyptian cities, Cairo, Egypt: comprihensive report.

15.    Strategic Leisure Pty Ltd t/a the Strategic Leisure Group, 2010. Cycling &Walking Strategy Review, Cairns, Australia: McCormick Rankin Cagney.

16.    The members of the City of Austin Design Commission, 2009. Urban Design Guidelines for Austin, City of Austin: City of Austin PECSD.

17.    Holdsworth, L & Hartman, YA, 2009. Indicators of community cohesion in an Australian country town. Commonwealth Journal of Local Governance, Volume 2, pp.76-97.

18.    Michael Quartuch, J. D. A. W. B. V. C. S. J. L. J. C.-G. K. B., 2012. Using Sense of Place and Sense of Community to Understand Landscape Change Behaviors, University of Maine, Orono, USA: Unpublished work.

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9.

Authors:

Sarah M. Sabry, Hany M. Ayad, Dina M. Saadallah

Paper Title:

Assessing the Factors Associated with Urban Mobility Behaviour: Case studies from Alexandrian Neighborhoods, Egypt

Abstract: With the rapid spread of urbanization, cities started to witness challenges related to its streets. It is becoming imperative that the mobility should be managed appropriately to minimize its negative impacts on urban areas. Unfortunately, city leaders in many developing countries like Egypt are following the same Car-Oriented development patterns made by cities in developed countries. Ironically, the developed countries are trying to recover from a car dominated development era by re-allocating road space for public and non-motorized transport. In this respect, this research aims at exploring the key aspects and factors that affect individuals’ mobility choices in Egypt. It focuses on the socio-demographic, attitudinal and physical factors that are associated with commuters’ mobility behaviour and their choice of mode for daily trips. Two neighborhoods in Alexandria are selected for comparative and analytical analyses. First, a survey is carried out in the two selected areas. Second, Pearson’s Chi-square χ2 test is performed to explore the significant differences of commuter’s attitudinal, personal and built environment factors between the two areas. Finally, cross-tabulation distribution of categorical variables are presented in terms of absolute frequencies, p-values from Pearson’s Chi-square χ2 test and t-test so as to look for the association of the urban form and non-urban form factors to mobility choices.

Keywords:
 Sustainable Urban Mobility (SUM) – Travel Behaviour – Mode choice –Non-urban form factors – Built environment factors – TOD development – Sustainable neighborhoods.


References:

1.       Paulley, N., et al. (2006). “The demand for public transport: The effects of fares, quality of service, income and car ownership.” Transport Policy 13(4): 295-306.
2.       Ortuzar J.D. & Willumsen L.G. (1999). Modelling Transport. England: John Wiley & Sons ltd.

3.       Dewi.A. (2010). “Research on factors affecting travel behaviour on choice of transportation means for working activity”. Yogyakarta, Indonesia: Faculty of Economic Sciences, Communication and IT.

4.       Aoun, C. (2014). Urban Mobility in the Smart City Age. London: ARUP, the climate group.

5.       Buis, J. (2009). A new Paradigm for Urban Transport Planning: Cyclin g Inclusive Planning at the Pre-event Training Workshop on Non-Motorized Transport in Urban Areas, 4th Regional EST Forum in Asia, 23 February 2009, Seoul, Republic of Korea.

6.       Rudolf, P. (2004). Sustainable Transport: A Sourcebook for policy-makers in developing cities module 2a (Environment and Infrastructure ed., Vol. Division 44). (D. G. für, Ed.) Deutsche Gesellschaft für (Technische Zusammenarbeit (GTZ) GmbH).

7.       Jacques, C. & Ahmed M. El-Geneidy (2010). Does travel behaviour matter in defining urban form? A quantitative analysis characterizing distinct areas within a region, The journal of transport and land-use, http://jtlu.org , Vol. 7 no. 1 [2014] pp. 1-14 doi: 10.5198/jtlu.v7i1.377

8.       Global urban development magazine GUD, 2005. Overview of our vision and purpose. [Online] Available at: http://www.globalurban.org/Vision%20and%20Purpose.htm

9.       Zegras, C. (September, 2005). Sustainable Urban Mobility: Exploring the Role of the Built Environment. Massachusetts: Massachusetts Institute of Technology.

10.    Jorge Gil. (2016). urban modality: Modelling and evaluating the sustainable mobility of urban areas in the city-region. Delft University of Technology, Faculty of Architecture and the Built Environment, Department of Urbanism.

11.    UN-Habitat. (2013). Planning and design for sustainable urban mobility. USA and Canada: Routledge.

12.    Cervero, R. and Kockelman, K. (1997). Travel demand and the 3Ds: Density, diversity, and design, Transportation Research Part D: Transport and Environment.

13.    Cervero, R., Sarmiento, Olga L., Jacoby, Enrique, Gomez, Luis Fernando & Neiman, Andrea (2009). Influences of Built Environments on Walking and Cycling: Lessons from Bogotá’, International Journal of Sustainable Transportation, 3:4,203 — 226, DOI: 10.1080/15568310802178314

14.    Handy, S. L. (2002). “Travel Behaviour–Land Use Interactions: An Overview and Assessment of the Research. In: In Perceptual Motion: Travel behaviour Research Opportunities and Application Challenges ” Pergamon, Amsterdam: pp. 223-236.

15.    Hanson, S. and M. Schwab. (1986). Describing disaggregate flows: individual and household activity patterns. The geography of urban transportation.

16.    Hanson, S. (1982). “The determinants of daily travel-activity patterns: relative location and sociodemographic factors.” Urban Geography 3(3): 179-202.

17.    Shaoli Wang & Carey Curtis. (2015).The Function of Individual Factors on Travel Behaviour: Comparative Studies on Perth and Shanghai. State of Australian Cities national Conference 2015. Queensland: Urban Research Program at Griffith University on behalf of the Australian Cities Research Network.

18.    Domencich, T. (1975). Urban travel demand: a behavioral analysis: a Charles River Associates research study / Thomas A. Domencich and Daniel McFadden.

19.    Olsson. A. (2003). Factors that influence choice of travel mode in major urban areas: The attractiveness of Park & Ride. Stockholm: Division of Transportation and Logistics.

20.    Ajzen, I. (1991). “The theory of planned behavior.” Organizational Behaviour and Human Decision Processes 50(2): 179-211.

21.    Anable, J. (2005). “‘Complacent car addicts’ or ‘aspiring environmentalists’? Identifying travel behaviour segments using attitude theory.” Transport Policy 12(1): 65-78.

22.    Ewing, R. and Cervero, R. (2010). Travel and the Built Environment. Journal of the American Planning Association, Vol. 76, No. 3, (265-94). Doi: 10.1080/01944361003766766.

23.    Brundtland, G. Harlem. (1987). Report of the World Commission on Environment and Development: Our Common Future. World Commission on Environment and Development.

24.    Jensen, M. (1999). “Passion and heart in transport: a sociological analysis on transport behavior.” Transport Policy 6(1): 19-33.

25.    The New York City Departments of Design and Construction (DDC), Health and Mental Hygiene, Transportation (DOT), and City Planning. (2010). Active Design Guidelines: Promoting physical activity and health in design. New York.

26.    OECD, (2002). OECD guidelines towards environmentally Sustainable Transport. (OECD) Organization for Economic Co-operation and Development publication.

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10.

Authors:

Nor Azlina Abd Rahman, Vinothini Kasinathan, Rajasvaran Logeswaran, Nurwahida Faradila Taharim

Paper Title:

QR IT Seek: A Conceptual Model for Teaching and Learning by Digital Natives via Edutainment Game

Abstract:  The goal of teaching and learning activities is to for the target recipient to achieve the learning outcomes. As the Digital Natives generation is being brought up in a much more sophisticated technologically advanced world, the aptitude and requirements in their studies have changed. More interactive and fun learning, out of the classroom setting, is desired. This paper proposes a conceptual framework for edutainment and reports on a primary study on a developed QR IT Seek game. The primary study, results and analysis would aid in further improvements and adaptation of such activities to improve the teaching and learning performance of the Digital Natives. 

Keywords:
edutainment, QR-Code, QR IT Seek competition, Digital Natives, pedagogy.


References:

1.    N.F. Taharim, A. Mohd Lokman, W.A.R. Wan Mohd Isa and N. L. Md Noor (2014) “Investigating Feasibility of Mobile Learning for History Lesson,” International Colloquium of Art and Design Education Research (i-CADER), Springer, pp. 51-55.
2.    GS1 Japan (2009) “QR Code Overview & Progress of QR Code Application,”. Available at: http://www.gs1jp.org/pdf/001.pdf. [Accessed on 27th March 2016]

3.    EDUCASE (2009) “7 Things You Should Know about QR Codes,” EDUCASE Learning Initiative. Available at: https://net.educause.edu/ir/library/pdf/ELI7046.pdf [Accessed on 27th March 2016].

4.    Goh, Lay Huah & Jarrett, Barry W. (2014) “Integrating QR Codes And Mobile Technology In Developing Listening And Speaking Skills In The Teaching Of English Language,”  International Journal on E-Learning Practices (IJELP), Volume 1, Issue 1.

5.    Sari Wallden, Anne Soronen (2004) “Edutainment from Television and computers to Digital  Television” . Available at: http://www.sis.uta.fi/infim/infim_2011/julkaisut/hyper/b/fitv03b.pdf [Accessed 25th June 2016]

6.    Andrew Miller (2011) “Twelve Ideas for Teaching with QR Codes”. Available at: http://www.edutopia.org/blog/QR-codes-teaching-andrew-miller [Accessed on 22th June 2016]

7.    HubPages (2013) “QR Code secrets. Dynamic vs. Static what’s the difference?”. Available at : https://qrcode.trustthisproduct.com/what-is-a-qr-code-en.html [Accessed on 28th June 2016]

8.    Ben Van Sas, Joroen Steeman (2012) “QR Codes – Linking the real world with the digital world.” Available at: http://blog.qr4.nl/Documents/Presentation-QR-Codes.pdf [Accessed on 28th June 2016]

9.    C. H. Lai, S. A. Chen, F. S. Hsiao, S. Chen, (2013) “Scan & Learn: Exploring Application of Dynamic Quick Response Codes in Digital Classrooms”. Bulletin of the Technical Committee on Learning Technology, Volume 15, Issue 3, pp. 2-5, July 2013.

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11.

Authors:

B. M. Mustapha, V. C. Ikpo, A. B. Bababe

Paper Title:

Intelligent Control for Laboratory DC Motor

Abstract: This paper presents the design of a fuzzy PD controller for laboratory DC motor (MS 150 Kit) to minimize the tracking error in applications. The Fuzzy PD controller was simulated and the responses obtained when compared with a conventional PD controller revealed better performance.

Keywords:
 Control, Direct-Current, Fuzzy, Motor


References:

1.       T. Nishiyama, S. Suzuki, M. Sato, and K. Masui, “Simple Adaptive Control with PID for MIMO Fault Tolerant Flight Control Design,” in AIAA Infotech@ Aerospace, ed, 2016, p. 0132.
2.       G.-J. Su and J. W. McKeever, “Low-cost sensorless control of brushless DC motors with improved speed range,” Power Electronics, IEEE Transactions on, vol. 19, pp. 296-302, 2004.

3.       R. Saidur, S. Mekhilef, M. Ali, A. Safari, and H. Mohammed, “Applications of variable speed drive (VSD) in electrical motors energy savings,” Renewable and Sustainable Energy Reviews, vol. 16, pp. 543-550, 2012.

4.       R. Krishnan, Electric motor drives: modeling, analysis, and control: Prentice Hall, 2001.

5.       N. Hemati, J. S. Thorp, and M. C. Leu, “Robust nonlinear control of brushless DC motors for direct-drive robotic applications,” Industrial Electronics, IEEE Transactions on, vol. 37, pp. 460-468, 1990.

6.       G.-R. Yu and R.-C. Hwang, “Optimal PID speed control of brush less DC motors using LQR approach,” in Systems, Man and Cybernetics, 2004 IEEE International Conference on, 2004, pp. 473-478.

7.       V. Vossos, K. Garbesi, and H. Shen, “Energy savings from direct-DC in US residential buildings,” Energy and Buildings, vol. 68, pp. 223-231, 2014.

8.       H. O. Ahmed, “Speed Sensorless Vector Control of Induction Motors Using Rotor Flux based Model Reference Adaptive System,” Journal of Engineering and Computer Science, vol. 17, 2016.

9.       W. Borutzky, Bond Graph Methodology. New York: Springer, 2010.

10.    B. O. B. Arun K. Samantaray, A Bond Graph Approach, Model-based Process Supervision. Scotland, UK, 2008.

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12.

Authors:

Sanjay S. Bhagwat, S. D. Pohekar

Paper Title:

Performance Assessment of CHP Cycle in Sugar Industry

Abstract:  A huge potential for power generation from waste fuels exists within the sugar cane industry. This paper presents the findings of the energy and exergy analysis of cogeneration i.e. CHP cycle in sugar industry. The study was aimed at assessing the operational performance of the bagasse based cogeneration power plant in sugar industry by evaluating both the energy and exergy efficiency.

Keywords:
  Energy, Exergy, Entropy, CHP.


References:

1.    A.Cihan, O.Hacıhafızoglu, & K. Kahveci,,  “Energy–exergy analysis and modernization suggestions for a combinedcycle power plant” International Journal of Energy Research, 30(2), 2006,pp.115-126.
2.    M.Ameri, P. Ahmadi & A.Hamidi, “Energy, exergy and exergoeconomic analysis of a steam power plant: A case study”, International Journal of Energy Research, 33(5), 2009, pp. 499-512.

3.    O.Can, N. Celik and I. Dagtekin, “Energetic–exergetic-economic analyses of a cogeneration thermic power plant in Turkey”, International Communications in Heat and Mass Transfer, 36(10),2009, pp. 1044-1049.

4.    F.Jurado, O. Can., & J. Carpio, “ Modelling of combined cycle power plants using biomass”,. Renewable Energy, 28(5), 2003, pp. 743-753.

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13.

Authors:

Raja Rao.Chella

Paper Title:

A Qualitative Review on Image Processing Algorithms to Detect Early Stage Lung Cancer

Abstract: Nowa days, the image processing algorithms are being usedwidely in medical systems for detection of lung cancer. It is observed that the life span rate of lung cancer patients increases from 15 to 50% if they were detected at early stages. Detection of cancer cells is the most important issue for medical researchers as it becomes more complex in the treatment process. The detection steps of presence of cancerous cells include image pre-processing, segmentation, feature extraction and classification. In this paper, algorithms for enhancement, segmentation and feature extractionto detect the cancerous tumors which are small and large in size from the lung CT scan images are reviewed. Finally thealgorithms are compared with one another using three parameters called accuracy, sensitivity and specificity.

Keywords:
CT Images, Image Preprocessing, Segmentation, Enhancement, Feature Extraction and Classification.


References:

1.       Ada, Rajneet Kaur “Early Detection and Prediction of Lung Cancer Survival using Neural Network Classifier”IJAIAM. Volume 2, Issue 6, June 2013
2.       Avinash. S, Dr. K. Manjunth, Dr. S. Senthil Kumar,” An Improved Image Processing Analysis for the Detection of Lung Cancer using Gabor Filters and Watershed Segmentation Technique”,IEEE,2016.

3.       P.B. Sangamithraa, S. Govindaraju.,” Lung Tumour Detection and Classification using EK-Mean Clustering”, IEEE –WiSPNET  conference,2016.

4.       Md. Badrul Alam Miah, Mohammad Abu Yousuf,” Detection of Lung Cancer from CT Image Using Image Processing and Neural Network”,  Electrical Engineering and Information &Communication Technology  (ICEEICT) 2015.

5.       Taruna Aggarwal, Asna Furqan, Kunal Kalra,” Feature Extraction and LDA based Classification of Lung Nodules in Chest CT scan Images”,IEEE,2015.

6.       Elmar Rendon-Gonzalez and Volodymyr Ponomaryov,”Automatic Lung

7.       Nodule Segmentation and Classification in CT Images Based on SVM”,IEEE-2016.

8.       T. Messay, R. Hardie and S. Rogers, “A new computationally efficient CAD system for pulmonary      nodule detection in CT imagery,”Med  Image Anal, vol. 14, pp. 390–406, 2010.

9.       D. Cascio, R. Magro, F. Fauci, M. Iacomi, and G. Raso, “Automatic detection of lung nodules in CT datasets based on stable 3D mass-spring models,” Computers in Biology and Medicine, vol. 42, no. 11, pp. 1098– 1109, 2012

10.    Saleem Iqbal et al,”Potential Lung Nodules Identification for Characterization by Variable Multistep Threshold and Shape Indices from CT     Images”, Computational and Mathematical Methods in Medicine Volume 2014 .

11.    M. Alilou, V. Kovalev, E. Snezhko, and V. Taimouri, “A comprehensive framework for automatic detection of pulmonary nodules in lung CTimages,” Image Anal Stereol, vol. 33, pp. 13-27, 2014.
12.    Dasari Hemalatha,  Raja Rao.Ch, S.J.Sugumar,” Detection of Lung Cancer Using Marker-Controlled Watershed Transform”, International Journal & Magazine Engineering, technology, management Research,Volume 3,Isuue no.10,2016.
13.    Vicky Ambule, Minal Ghute, Kanchan Kamble, Shilpa Katre,” Adaptive Median Filter for Image Enhancement”, International Journal of Engineering Science and Innovative Technology (IJESIT) Volume 2, Issue 1, January 2013.

14.    Raajan.P, Muthuselvi.S, Agnes Saleema. A,”  An Adaptive Image  Enhancement using Wiener Filtering with Compression and Segmentation”,  International Journal of Computer Applications, 2015

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14.

Authors:

Bababe Adam B., Ashish Kumar J., Rajiv Kumar

Paper Title:

Lora Based Intelligent Home Automation System

Abstract:  The home and Society are surrounded by “things” which are connected to each other, either directly or indirectly via the internet of things. To have access to controlling these devices remotely with precision within the network when required is a key factor in the process of home automation. There are numerous aspects in this automation that needs to be developed so as to enhance it. This research gives a solution to having a precise and direct control and automatic detection of current state of devices with the use of android application. It also gives a practical implementation of home automation using LoRa in comparison to other technologies.

Keywords:
 Home Automation; Internet of Things; LoRa; Android; Smart


References:

1.       Lee, K.M., Teng, W.G. and Hou, T.W., “Point-n-Press: An Intelligent Universal Remote Control System for Home Appliances,” IEEE Transactions on Automation Science and Engineering. 2016, 13(3), pp 1308 – 1317.
2.       Qu, Y., Xu, K., Wang, H., Wang, D. and Wu, B., December. “Lifetime maximization in rechargeable wireless sensor networks with charging interference,” In 2015 IEEE 34th International Performance Computing and Communications Conference (IPCCC) 2015, pp. 1-8.

3.       Hsieh, C.W., Chi, K.H., Jiang, J.H. and Ho, C.C., 2014. “Adaptive binding of wireless devices for home automation,” IEEE Wireless Communications, 21(5), pp.62-69.

4.       Sheng, W., Matsuoka, Y., Ou, Y., Liu, M. and Mastrogiovanni, F.,. “Guest Editorial Special Section on Home Automation,” IEEE Transactions on Automation Science and Engineering, 2015, 12(4), pp.1155-1156.

5.       Gill, K., Yang, S.H. and Wang, W.L., “Secure remote access to home automation networks,” IET Information Security, 2013, 7(2), pp.118-125.

6.       Langhammer, N. and Kays, R., “Performance evaluation of wireless home automation networks in indoor scenarios,” IEEE Transactions on Smart Grid, 2012, 3(4), pp.2252-2261.

7.       Kumar SP, Rao SV. RF Module Based Wireless Secured Home Automation System Using FPGA. Journal of Theoretical and Applied Information Technology. 2015, 77(2)

8.       Kumar PM, Sandhya N. “Bluetooth Based Wireless Home Automation System Using FPGA”. Journal of Theoretical and Applied Information Technology. 2015, 77(3)

9.       ElShafee A, Hamed KA. “Design and implementation of a WIFI based home automation system”. World academy of science, engineering and Technology. 2012, 2177-80.

10.    Tseng SP, Li BR, Pan JL, Lin CJ. “An application of Internet of things with motion sensing on smart house”. InOrange Technologies (ICOT), 2014 IEEE International Conference on 2014 Sep 20 pp. 65-68

11.    Teymourzadeh R, Ahmed SA, Chan KW, Hoong MV. “Smart GSM based home automation system”. InSystems, Process & Control (ICSPC), 2013 IEEE Conference on 2013 Dec 13, pp. 306-309.

12.    Sivakrishnan J., Esakki Vigneswaran E. and Sakthi Vishnu R. “Home Automation Control and Monitoring System Using BLE Device”. Middle-East Journal of Scientific Research, 2016 pp. 78-82

13.    Bor, Martin, John Edward Vidler, and Utz Roedig. “LoRa for the Internet of Things.” (2016): 361-366.

14.    Tadimeti, H.C. and Pulipati, M., “Overview of Automation Systems and Home Appliances Control using PC and Microcontroller,” Int. Jr. of Sci. Res, 2013, 2, pp.127-31.

15.    Ruçi, L., Karçanaj, L. and Shurdi, O., “Energy efficiency combined SW techniques on mobiles Android OS,” In Computer and Energy Science (SpliTech), International Multidisciplinary Conference on 2016, pp. 1-8.

16.    LoRa. https://www.lora-alliance.org. Accessed: 2016-12-23

17.    Song, S. and Issac, B., “Analysis Of Wi-fi And Wimax And Wireless Network Coexistence,” International Journal of Computer Networks & Communications, 2014, 6(6), p.63.

18.    Chowdary, U.V., Rohith, K., Sandeep, P. and Ramu, M., “Home Automation System Using IR Sensors,” International Journal of Electrical and Electronics Engineering, 2015, 4(6),  pp 11-1.

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15.

Authors:

Shaik Noor Mohammad

Paper Title:

Security Attacks in MANETS (Survey Prospective)

Abstract: Mobile Adhoc Network (MANET) is a dynamic, foundation less Network comprising of agroup of dynamic nodes which communicate with each other. Such networks find application in real-life environment as communication in Battlefields and communication among rescue personnel in disaster affected areas. Recently, mobile ad-hoc networks (MANETs) have gained the attention of research community due to increased adoption of its usage in real life applications. Due to fundamental characteristic of being Adhoc and insecure medium the most challenging job in MANETS is security. In this paper we present a brief survey of security attacks and existing prevention techniques.

Keywords:
Mobile Adhoc Network (MANET), Security, Attacks, Routing, Mobile nodes, Dynamic Topology


References:

1.       Rutvij H. Jhaveri, “MR-AODV: A Solution to Mitigate Blackhole and Grayhole Attacks in AODV Based MANETs “, (254-260)2012 Third International Conference on Advanced Computing & Communication Technologies, 978-0-7695-4941-5/12 / 2012 IEEE.
2.       Sanjay K. Dhurandher, Isaac  Woungang,  Raveena Mathur , Prashant Khurana,” GAODV: A Modified AODV against single and collaborative Black Hole attacks in MANETs”,(357-362) 2013 27th International Conference on Advanced Information Networking and Applications Workshops, 978-0-7695-4952-1/13/2013 IEEE.

3.       Yudhvir Singh, Avni Khatkar, Prabha Rani, Deepika, Dheer Dhwaj Barak ,“Wormhole Attack Avoidance Technique in Mobile Adhoc Networks”,(283-287) 2013 Third International Conference on Advanced Computing & Communication Technologies, 978-0-7695-4941-5/13/ 2013 IEEE.

4.       Indirani, Dr. K. Selvakumar, V. Sivagamasundari, “Intrusion Detection and Defense Mechanism for Packet Replication Attack over MANET Using Swarm Intelligence”, (152-156) Pattern Recognition, Informatics and Mobile Engineering (PRIME) February 21-22, 978- 1-4673-5845-3/13/2013 IEEE.

5.       P.Karthikkannan, K.P.Lavanya Priya,” Reduction of Delays in Reactive Routing Protocol for Unobservable Mobile Ad-Hoc Networks”, 2013 IEEE.

6.       Sapna Gambhir and Saurabh Sharma,” PPN: Prime Product Number based Malicious Node Detection Scheme   for   MANETs”,   (335-340)   2012   3rd   IEEE International Advance Computing Conference (IACC), 978-1-4673-4529-3/12/ 2012 IEEE.

7.       Hizbullah Khattak, Nizamuddin, Fahad Khurshid, Noor ul Amin, ” Preventing Black and Gray Hole Attacks in AODV using Optimal Path Routing and Hash”,(645-648) 978-1-4673-5200-0/13/2013 IEEE.

8.       Roopal Lakhwani , Vikram Jain , Anand Motwani , “ Detection and Prevention of Black Hole Attack in Mobile Ad-Hoc Networks”, International Journal of Computer Applications (0975 – 8887) Volume 59– No.8, December 2012.

9.       Htoo Maung Nyo, Piboonlit Viriyaphol, ” Detecting and Eliminating Black Hole in AODV Routing”, 2011 IEEE, 978-1-4244-6252-0/11

10.    Al-Shurman, M. Yoo, S. Park, “Black hole attack in Mobile Ad Hoc Networks”, in Proc. ACM Southeast Regional Conference, pp. 96-97, 2004.

11.    Pramod Kumar Singh, Govind Sharma,” An Efficient Prevention of Black Hole Problem in AODV Routing Protocol   in   MANET”,(902-906)   2012   IEEE   11th International Conference on Trust, Security and Privacy in Computing and Communications, 978-0-7695-4745- 9/12/ 2012 IEEE.

12.    Zhou L, Chao H-C, “Multimedia Traffic Security Architecture for the Internet of Things” IEEE Network 25(3):29–34. IEEE 2011.

13.    Yang H, Lou H, Ye F, Lu S, Zhang L (2004) Security in Mobile Ad Hoc Networks: Challenges and Solutions. IEEE Wireless Communications 11(1):38–47.

14.    S.Nithya, S.Prema, G.Sindhu, ” Security Issues & Challenging Attributes in Mobile Ad-Hoc Networks “, International Research Journal of Engineering and Technology (IRJET), Volume: 03 Issue: 01 , P.P 1083-1087, Jan-2016

15.    Wu B, Chen J, Wu J, Cardei M, “A Survey of Attacks and Countermeasures in Mobile Ad Hoc Networks” In: Xiao Y,Shen X, Du D-Z (eds) Wireless  Network Security.
on Signals and Communication Technology. Springer, New York 2007.

16.    Marti S, Giuli TJ, Lai K, Baker M, “Mitigating Routing Misbehavior in Mobile Ad Hoc Networks” 6th annual International Conference on Mobile Computing and Networking, Boston, Massachusetts, August 2000.

17.    Hu Y-C, Perrig A, Survey of Secure Wireless Ad   Hoc Routing. IEEE Security & Privacy 2(3):28–39, IEEE 2004.

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16.

Authors:

Sandeep P.

Paper Title:

A Comparative Analysis of Optimization Techniques  in Cognitive Radio (QoS)

Abstract: Wireless Technology has seen a tremendous advancement in recent times. There has been a huge growth in multimedia applications over the wireless networks. The requirement of significant bandwidth for multimedia services has increased the demand for radio spectrum. The scarcity of radio spectrum has become a challenge for the conventional fixed spectrum assignment policy.  Thus, Cognitive Radio (CR) has emerged as a new exclusive choice to address the spectrum underutilization problem by enabling users to opportunistically access unused spectrum bands. It offers a promising solution to meet this demand by fully utilizing available spectrum resources. It improves the utilization of the wireless spectrum by allowing the secondary users to access the primary channels in an opportunistic manner. Efficient utilization of frequency spectrum is possible using dynamic spectrum allocation. Optimization techniques like Genetic Algorithm (GA), Ant Colony Optimization (ACO) and Mutated Ant Colony Optimization (MACO) are discussed here to meet the users QoS needs in the Cognitive Radio. The transmission and environmental parameters along with performance objectives of cognitive radio are studied and compared in the paper using different optimization techniques. In this paper, the results of various optimization techniques in Cognitive Radio System along with CR objectives are analysed to meet users QoS.

Keywords:
Cognitive Radio Genetic Algorithm, Ant Colony Optimization, Mutated Ant Colony Optimization, QoS Provisioning.


References:

1.       Akyildiz, I. F., Lee, W. Y., Vuran, M. C., & Mohanty, S. (2006). Next generation dynamic spectrum access cognitive radio wireless networks: A survey. Computer Networks, 50, 2127–2159.
2.       Haykin, S. (2005). Cognitive radio: Brain-empowered  wireless communications. IEEE Journal on Selected Areas in Communications, 23(2), 201–220.

3.       Gandetto, M., & Regazzoni, C.. Spectrum sensing: A  distributed approach for cognitive terminals. IEEE Journal on Selected Areas in Communications,   25(3),2007,546–557.

4.       Federal communication commission, “spectrum policy task   force”, Report of ET Docket 02-135, 2002.

5.       J. Mitola III, “cognitive radio: An integrated Agent Architecture for Software Radio”, PhD thesis, Royal   institute of Technology (KTH), 2000.

6.       C. Rieser “Biologically inspired cognitive radio engine   model utilizing distributed genetic algorithms for secure  and robust wireless communications and networking”, PhD thesis, Virginia Tech, 2004.

7.       J Mitola III and G. Q. Maguire, Jr” Cognitive radio:     making software radios more personal,” IEEE Personal  Communications Magazine,vol.6,nr 4, pp.13–18, Aug.1999

8.       Tim R. Newman, Brett A. Barker, AlexanderM. Wyglinski, Arvin Agah, Joseph B.Evans and Gary J Minden  “Cognitive engine implementation for wireless multicarrier transceivers”, Wiley Wireless communications and mobile computing, 7(9), 1129-1142 (2007).

9.       Sebastian Herry and Christophe J.Le Martret, “parameter determination of secondary user cognitive radio network using genetic algorithm”, IEEE 2009.

10.    Maninder Jeet Kaur, Moin Uddin, Harsh K.Verma,  “Performance Evaluation of QoS parameters in cognitive radio using Genetic Algorithms”, In World Academy of Science, Engineering & Technology, vol.4, No.10,  pp.830- 835, 2010.

11.    Nan Zhao, Shuying Li, Zhilu Wu, “Cognitive radio engine design based on Ant colony optimization”, Wireless pers communication, 2012. pp 15-24

12.    Kiranjot kaur, Munish Rattan, Manjeet Singh Patterh, “optimization of cognitive radio system using simulated annealing”, wireless pers communication, 2013.

13.    Abdelfatah Elarfaoui, Noureddine Elalami, “optimization of QOS parameters in cognitive radio using combination of two crossover methods in genetic algorithm”, Int. J. Communications, Network and System Sciences, pp. 478-483, November 2013.

14.    Stephen A. Adubi, Sanjay Misra “A Comparative Study on the Ant Colony Optimization Algorithms” IEEE, 2014

15.    Ismail AlQerm and Basem Shihada, “Adaptive Multi objective optimization scheme for cognitive radio resource management”, Globecom 2014

16.    Vinutha.P, Sutha.J, QOS Parameter Optimization For Cognitive Radio Networks, IJARCST, Vol. 2 Issue  Special -1 Jan-March 2014, pp 204-208

17.    Seshadri Binaya Behera, D.D.Seth, “Resource  allocation for cognitive radio network using particle swarm optimization”, IEEE sponsored (ICECS„2015‟).

18.    Vibhuti Rana and Dr.P.S.Mundra,” A Review on QOS Parameters in Cognitive Radio Using Optimization Techniques” IJEIT Volume 5, Issue12, June 2016, pp:59

19.    Supreet Kaur, Inderdeep Kaur Aulakh” Optimization of Cognitive Radio Sensing Techniques Using Genetic Algorithm” ijircce. Vol 3, Issue 5 May 2015 pp.4131

20.    M .Dorigo, M. Birattari and T. Stuetzle, “Ant colony optimization: artificial ants as computational intelligence technique,” IEEE   Computational Intelligence, vol.I,no. 4, pp. 28-39, 2006.

21.    M. Shoukath Ali, R. P. Singh, “A Study on Game Theory Approaches for Wireless Sensor Networks” ijbsac ISSN: 2249–8958, Volume-6 Issue-3, February 2017, pp:5-7

22.    Ramlakhan Singh Jadon, Unmukh Dutta” Modified Ant Colony Optimization Algorithm with Uniform Mutation   using Self-Adaptive Approach” IJCA (0975 –8887) Volume 74–No.13, July 2013, pp 5-8

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17.

Authors:

Francis Yao Anyan

Paper Title:

Assessment of Indigenous Knowledge usage Among Small Scale Farmers in Kpando Municipality, Ghana

Abstract: The study assessed the indigenous knowledge (IK)usage among small scale farmers. The study was conducted in the Kpando Municipality with a sample size of 140 respondents. Simple random sampling technique was used to collect data from respondents. Data collected were analyzed using descriptive tools such as frequencies, percentages, mean and standard deviation. The study reveal that majority of small scale farmers in the municipality are female. Also farmers in the municipality frequently use indigenous knowledge such as Organic manure, Mulching, Bush fallowing, Harvesting with hand and Rain water harvesting.

Keywords:
 Mulching, Harvesting, Indigenous, Knowledge, Bush fallowing, standard deviation.


References:

1.       Alavi, Maryam, and Dorothy E. Leidner. “Review: Knowledge Management and Knowledge Management Systems: Conceptual Foundations and Research Issues.” MIS    Quarterly 25, no. 1 (2001): pp.107–136.
2.       Flavier, J.M. et al. (1995)””The regional program for the promotion of indigenous knowledge in    Asia”, pp. 479-487 in Warren, D.M., L.J. Slikkerveer and D. Brokensha (eds) The cultural dimension of development: Indigenous knowledge systems. London: Intermediate Technology Publications.

3.       Johnson, M., 1992. Lore: capturing traditional environmental knowledge. Ottawa: Dene Cultural Institute and the International Development Research Centre Langhill, S., 1999. Indigenous knowledge: a resource kit for sustainable development researchers in dryland Africa. Ottawa: IDRC

4.       Mugabe, F.T., et al., 2010. Use of indigenous knowledge systems and scientific methods for climate forecasting in southern Zambia and north western Zimbabwe. Zimbabwe Journal of Technological Sciences, 1 (1).

5.   Steiner, A., 2008. Indigenous knowledge in disaster management in Africa. United Nations Environment Programme (UNEP). Available from: http://www.unep.org/IK/PDF/IndigenousBooklet.pdf

6.       Sundamari, M and Ranganathan, T.T. (2003). Indigenous agricultural practices for sustainable farming. Agrobios (India). Jodhpur, India.

7.       Warren, D. M. 1991 “Using Indigenous Knowledge in Agricultural Development”; World Bank    Discussion Paper No.127. Washington, D.C.: The World Bank.

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18.

Authors:

N. Nachammai, R. Kayalvizhi

Paper Title:

Moth Flame Optimisation Algorithm for Control of LUO Converter

Abstract: Because of the effects of the parasitic elements, the output voltage and power transfer efficiency of all DC-DC converters are restricted. In order to eliminate the limitations caused by parasitic elements, the voltage lift technique is successfully applied to DC-DC converters resulting in a new series called Luo converters. Linear control methods ensure stability and good control only in small vicinity around the operating point. These classical controllers are designed using mathematical models by linearising non-linearities around the nominal operating point. Since these controllers are also sensitive to the operating points and parameters variations, a high degree of accuracy cannot be guaranteed from them. To ensure that the controllers work well in large signal conditions and to enhance their dynamic responses, intelligent method using fuzzy technique is suggested.The performance of a fuzzy logic controller depends on its control rules and membership functions. Hence, it is very important to adjust these parameters to the process to be controlled. A method is presented for tuning fuzzy control rules by Moth Flame Optimization(MFO) algorithm to make the fuzzy logic control systems behave as closely as possible to the operator or expert behavior in a control process. The tuning method fits the membership functions of the fuzzy rules given by the experts with the inference system and the defuzzification strategy selected, obtaining high-performance membership functions by minimizing an error function. Moth-flame Optimization (MFO) algorithm is one of the newest bio inspired optimization techniques in which the main inspiration of this optimizer is the navigation method of moths in nature called transverse orientation.MFO has a fast convergence rate due to use of roulette wheel selection method. Moth-Flame Optimizer (MFO) is used to control the LUO converter. MFO-Fuzzy is used to search the fuzzy rules and membership values to achieve minimum ISE, ITAE, settling time and peak overshoot. The proposed method is compared with fuzzy controller. Simulation results prove that the MFO algorithm is very competitive and achieves a high accuracy.

Keywords:
Moth Flame Optimisation Algorithm, Fuzzy Logic Controller, Positive Output Elementary LUO Converter.


References:

1.       F.L.Luo and Hong Ye, Advanced DC/DC Converters, CRC Press, LLC, 2004.
2.       S. Mirjalili, “Moth-flame optimization algorithm: A novel nature inspired heuristic paradigm”,  Knowledge-Based Systems, Elsevier, Vol . 89, 2015, pp.   228-249.

3.       Narottam Jangir, Indrajit N.Trivedi, Mahesh H. Pandya, R.H.Bhesdadiya, Pradeep Jangir and Arvind Kumar, “Moth-Flame Optimization Algorithm for Solving Real Challenging Constrained Engineering Optimization Problems”, Proceedings of IEEE Students Conference on Electrical, Electronics and Computer Science, Bhopal, 2016, pp. 1–5.

4.       Ghada M. A. Soliman, Motaz M. H. Khorshid and Tarek H. M. Abou-El-Enien “Modified Moth-Flame Optimization Algorithms For Terrorism Prediction”, International Journal of Application on Innovation in Engineering & Management, Vol. 5,Issue 7, 2016,pp. 47-58.

5.       Deepak Kumar Lal, Kiran Kumar Bhoi and Ajit Kumar Barisal, “Performance evaluation of MFO algorithm for AGC of a multi area power system”, proceedings   of International conference on Signal Processing,  Communication, Power and Embedded System, odisha, India, Oct. 2016,pp.1-6.

6.       Siddharth A. Parmar, Indrajit N. Trivedi, M. H. Pandya, Pradeep Jangir, Motilal Bhoye and Dilip Ladumor, “Optimal Active and Reactive Power Dispatch Problem Solution using Moth-Flame Optimizer Algorithm”, Proceedings on international conference on energy efficient technologies for sustainability, Oct. 2016,Nagercoil,Tamilnadu. pp. 491-496.

7.       N. Trivedi, Avani H. Ranpariya, Arvind Kumar and Pradeep Jangir, “Economic Load Dispatch Problem with Ramp Rate Limits and Prohibited Operating Zones Solve using Levy Flight Moth-Flame Optimizer”, proceedings of international conference on energy efficient technologies for sustainality, Nagercoil ,2016, pp. 442-447.

8.       Waleed Yamanya, Mohammed Fawzy, Alaa Tharwat and Aboul Ella Hassanien, “Moth-Flame Optimization for Training Multi-layer Perceptrons”, proceedings of eleventh international conference on computer Engineering, Cairo, Egypt, 2015.pp. 267-272.

9.       Pertik Garg and Ashu Gupta,“Optimised open shortest path first algorithm  based on Moth flame optimization”,Indian Journal of Science and Technology,Vol.9,Issue-6,2016,pp.1-9.

10.    Bachir Bentouati and Lakhdar Chaib and  Saliha Chettih, “Optimal power flow using moth flame optimizer” A case study of Algerian power system, Indonesian Journal of Electrical Engineering and Computer Science Engineering,Vol.1,Issue-3,2016, pp. 431-445.

11.    S.Gomariz, F.Guinjoan, E.Vidal, L.Martinz and A.Poreda, ‘On the use of the describing function in fuzzy controller design for switching DC-DC regulators’, in Proc. IEEE International Symposium on Circuits and Systems, Geneva, Switzerland, 2000, pp. 247-250.

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19.

Authors:

Vipanjot Kaur Sidhu, Vijay Kumar Joshi

Paper Title:

A Novel Technique for Fault Recovery in Mobile Cloud Computing

Abstract: Cloud computing is a technology or distributed network where user can move their data and any application software on it. But there is some issues in cloud computing, the main one is security because every user store their useful data on the network so they want their data should be protected from any unauthorized access, any changes that is not done on user’s behalf. Task allocation is one of the issue of the cloud computing. Load imbalance occurs due to limited resources available and leads to the fault occurrence situation. In this paper, a novel technique has been proposed based on weights to overcome faults occurrence problem. In this work improvement will be proposed in agent base load balancing algorithm for task reallocation and reduced fault detection time in cloud architecture.

Keywords:
Cloud computing, deployment models, load balancing, fault tolerance


References:

1.       SanjoliSingla, Jasmeet Singh, 2013  “Cloud Data Security using Authentication and Encryption Technique” International Journal of Advanced Research in Computer Engineering & Technology  (IJARCET) Volume 2, Issue 7, July 2013, pp 2232-2235
2.       Soumya Ray and Ajanta De Sarkar, “Execution Analysis of Load Balancing Algorithm in Cloud computing Environment”, International Journal on Cloud Computing: Services and Architecture (IJCCSA), Vol.2, No.5, October 2012

3.       Sean Carlin, Kevin Curran “Cloud Computing Security” International Journal of Ambient Computing and Intelligence, pp 14-19, 2011

4.       Barau M, Liang X, Lu R, Shen X. “ESPAC: Enabling Security and Patient-centric Access Control for eHealth in cloud computing”, International Journal of Security and Networks; 2011; 6(2),p.67-76

5.       Sahai A, Waters B. “Fuzzy identity-based encryption. Advances in cryptology- EUROCRYPT” 2005,pp.557

6.       Deyan Chen, Hong Zhao, “ Data Security and Privacy Protection Issues in Cloud Computing” International Conference on Computer Science and Electronics Engineering, pp 647-65, 2012
7.       M. Armbrust, A. Fox, R. Griffith, A. Joseph, R. Katz, A. Konwinski, G. Lee, D. Patterson, A. Rabkin, I. Stoica, and M. Zaharia, “A view of cloud computing” April 2010.
8.       Kuyoro S. O., Ibikunle F. &Awodele O, “Cloud Computing Security Issues and Challenges”, International Journal of Computer Networks (IJCN), Volume 3, Issue 5, pp 247-255, 2011.

9.       BhushanLalSahu, Rajesh Tiwari, “A Comprehensive study on cloud computing”, Internatioinal Journal Of Advanced Research in Computer Science and Software Engineering,Volume 2,Issue 9,September 2012 .

10.    Ertaul L, Singhal S, Gokay S,  “Security challenges in Cloud Computing”, International conference on Security andManagement SAM’10. CSREA Press, Las Vegas, US, pp 36–42,2010.

11.    Grobauer B, Walloschek T, Stocker E, “ Understanding Cloud Computing vulnerabilities”, IEEE Security Privacy, 2011.

12.    Ajay Jangra, RenuBala “Spectrum of Cloud Computing Architecture: Adoption and Avoidance Issues”, International Journal of Computing and Business Research, Volume 2, Issue 2, May 2011.

13.    C. Braun, M. Kunze, J. Nimis, and S. Tai, “Web-based Dynamic IT-Services”,SpringerVerlag, Berlin, Heidelberg, 2010.

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20.

Authors:

Sathya Jose. S. L , K. Sivaraman

Paper Title:

Modified SDROM Filter

Abstract:  Noise is any unwanted component in an image. It is important to eliminate noise in the images before some subsequent processing, such as edge detection, image segmentation and object recognition. This work mainly concentrates on automatic detection and efficient removal of impulse (salt and pepper) noise. For automatic detection of impulse noise, a method based on probability density function is proposed. The basic idea of automatic detection is that the difference between the probabilities of black and white pixels will be small. After detecting the presence of impulse noise in an image, we have to remove that noise. For the removal of impulse noise a new efficient impulse noise removal method (Modified SDROM filter) is proposed. The Modified SDROM consists of two parts 1) Impulse detector and 2) Filter. The results show that this method has higher performance than other methods in terms of PSNR values and SSIM-Index values.

Keywords:
impulse noise, probability density function, PSM Filter, SDROM Filter, PWMAD Filter, Modified SDROM, PSNR, SSIM Index.


References:

1.    Keiko Kondo, Miki Haseyama and Hideo Kitajima”An Accurate Noise Detector for Image  Restoration”, Proc. of 2002 IEEE International Conference On Image Processing, , Vol.1, pp.321-324, 2002.
2.    Z.Wang and D.Zhang,”Progressive switching median filter for the removal of impulsenoise from highly corrupted images”, IEEE Trans. Circuits and Syst.II, Analog and Digital Signal Processing,vol.46,pp.78-80,January 1999.

3.    E. Ahreu and S. K. Mitra, “A signal-dependent rank ordered mean (SDROM) filter-A new approach for removal of impulses from highly corrupted images,” in Proc. Int. Conf Acoust. Speech Signal Processing, Detroit, MI, vol. 4, May 1995, pp. 2371-2374.

4.    Vladimir Crnojevic´, Vojin ˇSenk , Željen Trpovski,,”Advanced impulse detection based on Pixel-Wise MAD (PWMAD)”, IEEE Signal Processing Letters, Vol. 11, No. 7, July 2004,pp.589-592.

5.    Handbook of Image & Video Processing, Academic Press Series in Communications, Networking, and Multimedia, Editor AL Bovik.

6.    Digital Image Processing, Second Edition, Rafael .C. Gonzalez, Richard .E. Woods, Pearson Education, inc., 2002.

7.    Fundamentals of Digital Image Processing, A.K.Jain, Prentice Hall of India Private Limited, New Delhi, 2002.

8.    Digital Image Processing, Third Edition, William .K. Pratt, John Wiley & Sons (Asia), INC 2004.

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21.

Authors:

Jeena R S, Sukesh Kumar A

Paper Title:

GUI Based Model for Stroke Prediction

Abstract:  The innovations in the field of artificial intelligence have paved way to the development of tools for assisting physicians in disease diagnosis and prognosis. Stroke is a leading cause of disability in developing countries like India. Early diagnosis of stroke is required for reducing the mortality rate. Research shows that various physiological parameters carry vital information for the prediction of stroke.  This research work focuses on the design of a graphical user interface (GUI) for the prediction of stroke using risk parameters. Data collected from International Stroke Trial database was successfully trained and tested using Support vector machine (SVM). The linear kernel of SVM gave an accuracy of 90 %. This work has been implemented in MATLAB which can be used to predict the probability of occurrence of stroke.

Keywords:
Stroke, Graphical User Interface (GUI), Support Vector machine (SVM)


References:

1.       Subha PP,Pillai  Geethakumari SM, Athira M, Nujum ZT, Pattern and risk factors of stroke in the young among stroke  parients admitted in medical college hospital, Thiruvananthapuram., Ann indian Acad Neurol 2015;18:20-3.
2.       Barry L. Zaret, M.D., Marvin Moser, M.D., Lawrence S. Cohen, Chapter 18 Stroke – Lawrence M. Brass, M.D. (pgs 215-234)

3.       MacMahon S, Rodgers A. The epidemiological association between blood pressure and stroke: implications for primary and secondary prevention. Hypertens Res. 1994;17(suppl 1):S23-S32.

4.       Shinton R, Beevers G. Meta-analysis of relation between cigarette smoking and stroke. BMJ

5.       Benjamin EJ, Levy D, Vaziri SM, D’Agostino RB, Belanger AJ, Wolf PA. Independent risk factors for atrial fibrillation in a population-based cohort: the Framingham Heart Study. JAMA. 1994;271:840-844

6.       Saangyong Uhmn, Dong-Hoi Kim, Jin Kim, Sung Won Cho, Jae Youn Cheong, “Chronic Hepatitis Classification Using SNP Data and Data Mining Techniques”, Frontiers in the Convergence of Bioscience and Information Technologies, FBIT 2007,pp.81 – 86 , 11-13 Oct. 2007B. Smith, “An approach to graphs of linear forms
(Unpublished work style),” unpublished.

7.       S. Bhatia, P. Prakash and G.N. Pillai, SVM based Decision Support System for Heart Disease Classification with Integer-coded Genetic Algorithm to select critical features, Proceedings of the World Congress on Engineering and Computer Science, San Francisco, USA, pp.34-38, 2008.

8.       Yanwei Xing, Jie Wang and Zhihong Zhao Yonghong Gao 2007 “Combination data mining methods with new medical data to predicting outcome of Coronary Heart Disease” Convergence Information Technology, 2007. International Conference November 2007, pp 868-872.

9.       Jianxin Chen, Guangcheng Xi, Yanwei Xing, Jing Chen, and Jie Wang 2007 “Predicting Syndrome by NEI Specifications: A Comparison of Five Data Mining Algorithms in Coronary Heart Disease” Life System Modeling and Simulation Lecture Notes in Computer Science, pp 129-135

10.    Alexopoulos, E., Dounias, G.D., and Vemmos, K. (1999). “Medical diagnosis of stroke using inductive machine learning”. In Proceedings of Workshop on Machine Learning in Medical Applications, Advance Course in Artificial Intelligence-ACAI99, Chania, Greece, 20-23.

11.    C. Cortes and V. Vapnik, “Support-vector networks,” Machine learning,vol. 20, no. 3, pp. 273–297, 1995..

12.    Sandercock, Peter; Niewada, Maciej; Czlonkowska, Anna. (2011). International Stroke Trial database (version 2),  University of Edinburgh. Department of Clinical Neurosciences.

13.    Jeena R S, Dr Sukesh Kumar A, ’Stroke Prediction using SVM’, Proceedings on International Conf. on Control, Instrumentation, Communication and Computational Technologies, (ICCICCT-2016),Tamil Nadu

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22.

Authors:

Neha Mahakalkar, Vaishali Sahare

Paper Title:

Survey on Privacy Preserving Authentication Protocol in Cloud Computing

Abstract: Cloud computing provides facilities of shared computer processing resources and data to computers and other device on demand. System environment will develop by using three key entities trusted third party, data owner and user. The concept of shared authority based privacy preserving authentication protocol i.e., SAPA used to develop system to perform shared access in multiple user. Security and privacy issue as well as shared access authority will be achieve by using access request matching mechanism e.g. authentication, user privacy, user can only access its own data fields. The multiple users want to share data so that purpose re-encryption is used to provide high security for user private data. Universal Composability (UC) model use to prove that design of SAPA correctness. Develop a system with high security and attack free by analysing different attack related to the system. Privacy preserving data access authority sharing is attractive for multi user collaborative cloud applications

Keywords:
 authentication, security, shared access and cloud computing


References:

1.    Hong Liu, Huansheng Ning, Qingxu Xiong, Laurence T. Yang, “Shared Authority Based     Privacy-Preserving Authentication Protocol in Cloud Computing”, IEEE transactions on parallel and distributed systems, vol. 26, no. 1, january 2015.
2.    Xuefeng Liu, Yuqing Zhang, Boyang Wang, and Jingbo Yan,” Secure Multi-Owner Data Sharing for Dynamic Groups in the Cloud, IEEE transactions on parallel and distributed systems, vol. 24, no. 6, june 2013.

3.    Mohamed Nabeel, Ning Shang, Elisa Bertino,”Privacy Preserving Policy-Based Content Sharing in Public Clouds , IEEE transactions on knowledge and data engineering, vol. 25, no. 11, november 2013.                      

4.    Smitha Sundareswaran, Anna C. Squicciarini, “Ensuring Distributed Accountability for Data Sharing in the Cloud”, IEEE transactions on dependable and secure computing, vol. 9, no. 4, july/august 2012.

5.    Mishra, R. Jain, and A. Durresi, “Cloud Computing: Networking and Communication Challenges,” IEEE Comm. Magazine, vol. 50, no. 9, pp. 24-25, Sept. 2012.

6.    R. Moreno-Voz media no, R.S. Montero, and I.M. Llorente, “Key Challenges in Cloud Compute into Enable the Future Internet of Services,” IEEE Internet Computing, vol.17, no.4, pp.1825 July/Au 2013.

7.    Privacy-preserving Authentication Protocol in Cloud Computing”,10.1109/TPDS.2014.2308218, IEEE Transactions on Parallel and Distributed Systems,2015

8.    Chia-Mu Yu, Chi-Yuan Chen, and Han Chieh Chao “Proof of Ownership in Deduplicated Cloud Storage with Mobile Device Efficiency”, IEEE Network  March/April 2015.

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23.

Authors:

Jerrin Thomas Panachakel

Paper Title:

Automatic Eigen Face Method

Abstract: Muzzle print recognition is the process of  finding any muzzle in the image. It is a two-dimension procedure used for detecting muzzles and analyzing the information contained in the muzzle image. Here the muzzle images are projected to a feature space or face space to encode the variation between the known muzzle images. In this paper Principal Component Analysis (PCA) is used for dimension reduction and the projected feature space is formed using fuzzy algorithm. The above method can be used to recognize a new muzzle in unsupervised manner.

Keywords:
 Muzzle Print, Principal Component Analysis (PCA), Membership Function.


References:

1. Brendan Barry, Ursula Gonzales Barron, Kevin McDonnell, Shane Ward “The use of muzzle pattern for biometric Identification of cattle”,  Biosystems  Engineering, University College Dublin, Earlsfort Terrace,  Dublin 2,  Ireland, 2002
2. J. Marchant, “Secure Animal Identification and Source Verification”, J M Communications  2002, UK
3. Kimura A, Itaya K, “Structural Pattern Recognition of Biological Textures with Growing Deformations:A case of Cattles Muzzle prints”, Electronics and Communications in Japan, part 2, 87(5):54-65, 2004.
4. Turk M, and Pentland A, “Eigenfaces for recognition” Cognitive Neuro Science, 2(1):71-86, 1991.
5. Wahab, S. H. Chin, E. C. Tan, “Novel approach to automated fingerprint recognition”, IEE Trans. Image Signal Process, Vol. 145, No. 3, June 1998.

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24.

Authors:

Komati Sathish

Paper Title:

A Study on Check Pointing Protocols for Mobile Distributed Systems

Abstract: A large number of distributed checkpointing protocols have appeared in the literature.a distributed checkpointing protocol could be the best in a specific environment, but not in another environment.Distributed snapshots are an important building block for distributed systems and are useful for constructing checkpointing protocols among other users. Communication-Induced Checkpointing protocols are classified into two categories in the literature: Index-based and Model-based.Recently, more attention has been paid to providing checkpointing protocols for mobile systems. check point is defined as a designated place in a program at which normal processing is interrupted specifically to preserve the status information necessary to allow resumption of processing at a later time. This paper surveys the protocols which have been appeared in the literature for checkpointing in mobile distributed systems.

Keywords:
Checkpoint/restart, checkpointing protocols, Distributed systems, rollback recovery, fault tolerant computing


References:

1.       Ch.D.V.Subba Rao and  MM Naidu :  A  new efficient coordinated checkpointing protocol combined with selective sender based message logging , IEEE,2008.
2.       Acharya and B.R.Badrinath, checkpointing distributed Applications on Mobil computers,proc.3rd Int’l conf.parallel and distributed Information systems, sept.1994.

3.       R.Prakash and M.Singhal, “Low-cost checkpointing and failure recovery in mobile computing systems,” IEEE Trans.parallel and  distributed systems pp.1035-1048,oct 1996

4.       Lalit kumar  p.kumar “A synchronous checkpointing protocol for mobile distributed systems: probabilistic approach” Int.Journal of information and computer society 2007.

5.       G.H.Forman and J.Zahorjan, The changes of Mobile computing ,computer pp 38-47,Apr-1994

6.       Ms.Pooja Sharma and Dr.Ajay khuntala ” A survey of checkpointing Algorithm in Mobile Ad Hoc Network”Globl Journal of Computer Science and Technolgy 2012.

7.       Sarmistha Neogy,Anupam siha,pradip k Das ,CCMUL: A Checkpoinying protocol for  distributed system processes,IEEE,2004.

8.       B.bhargava,S.R.Lian “Independent checkpointing and concurrent rollback for recovery in distributed systems-An Optimistic approach”. proc 7th IEEE Symp.Rliable Distributed syst. pp 3-12 1988 oct.

9.       L. Alvisi, E.N. Elnozahy, S. Rao, S. A. Husain and A. Del Mel. “An analysis of communication-induced checkpointing.” In Proceedings of the Twenty Ninth International Symposium on Fault-Tolerant Computing, Jun. 1999.

10.    D.B. Johnson. “Distributed system fault tolerance using message logging and checkpointing.” Rice University, Dec. 1989.

11.    S. Mishra and D. Wang. Choosing an Appropriate Checkpointing and Rollback Recovery Algorithm for LongRunning Parallel and Distributed Applications. In 11th ISCA International Conference on Computers and their Applications, San Francisco, CA, March 1996

12.    J. S. Plank and M. G. Thomason. Processor allocation and checkpoint interval selection in cluster computing systems. Journal of Parallel and Distributed Computing, 61(11):1570–1590, November 2001.

13.    K. S. Trivedi. Probability and Statistics with Reliablity, Queuing, and Computer Scince Applications. Prentice-Hall, USA, 1982.

14.    Nitin Vaidya. On Checkpoint Latency. In Pacific Rim International Symposium on Fault-Tolerant Systems, Newport Beach, December 1995.

15.    Nitin H. Vaidya. Another Two-Level Failure Recovery Scheme: Performance Impact of Checkpoint Placement and Checkpoint Latency. Technical Report TR94-068, Deprt. of Computer Science, Texas A&M University, 1994.

16.    Y. M. Wang. Consistent Global Checkpoints that Contain a Given Set ofCheckpoints. IEEETransactions on Computers, 42(4):456–486, April 1997.

17.    Ziv and J. Bruck. Analysis of Checkpointing Schemes for Multiprocessor Systems. In Proceeding ofthe 13th Symposium on Reliable Distributed Systems, pages 52–61, 1994.

18.    Ziv and J. Bruck. Efficient checkpointing over local area network. In IEEE Workshop on Fault-Tolerant Parallel and Distributed Systems, June 1994.

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25.

Authors:

Babak Mehravaran, Hossein Ansari, Ali Asghar Beheshti

Paper Title:

Nozzle Filter Modification for Water Pre-Treatment Technology In Water Treatment Plants (Case Study: Toroq Water Treatment Plant)

Abstract: Nozzle filtration can be considered as a major pre-treatment process for water and waste water, since they efficiency separate fine solids particles over prolonged periods without addition of chemicals. Proper nozzle performance can reduce operating costs, reduce maintenance costs, and improve cleaning quality. this review article summarized and evaluates modification to nozzle filtration technology .achieved results in this study shows that nozzle filtration may be considered as efficient pre-treatment process incase surface water is used as water supply. With pass of muddy water sample due to current rainfall in stilling basin of Toroq water treatment plant from nozzle filters in laboratory pilot, Turbidity Removal efficiency and also Suspended solids equal 9.6% and 86% respectively was obtained .And the results of Additional tests represent that Turbidity Removal and also solid suspensions efficiency by nozzle filters due to algae making inlet water to Toroq water treatment plant in warm seasons is 4/6% and 47% respectively The obtained results of the study indicate that use nozzle filters caused Increase the efficiency of the process water treatment, and it is prevents from emergency exits the Toroq water treatment plant.

Keywords:
 Nozzle filter, Muddy water, Algae water, Suspended solids, turbidity.


References:

1.       Herron. A. Hope, & Dabelko, Geoffrey,  (2006),“ Introduction:   Water Stories”, Water Stories: Expanding Opportunities in Small-Scale Water and Sanitation Projects, pp 1-8, Woodrow Wilson  International Center for Scholars
2.       P .SanjivKanade, S. Someshwar, Bhattacharya ,(2016),Chapter 1- Introduction to Water World A Guide to Filtration with String Wound Cartridges, 2016, Pages       1-10,

3.       Q . Shen, J. Zhu, L .Cheng, J. Zhang, Z. Zhang, X. Xu,(2011), Enhanced algae removal by drinking   water   treatment of chlorination coupled with   coagulation,   Desalination, Volume 271, Issues 1–3, 15 April 2011, Pages 236-240

4.       R. Srinivasan, G. A. Sorial ,(2011),Treatment of tast  and  odor causing compounds 2-methyl isoborneol and geosmin in drinking water: A critical review, Journal of  Environmental Sciences, Volume 23, Issue 1, January    2011, Pages 1-13

5.       A.J. Englande Jr., P. Krenkel, J. Shamas, Reference Module in Earth Systems and Environmental Sciences,

6.       T. Sparks, (2012), filter Design, Pages 81-124

7.       K.Sutherland,(2008), Types of Filter, Filters and Filtration Handbook (Fifth Edition), 2008, Pages 97-207

8.       T. Sparks, G. Chase,(2016),Filters and Filtration  Handbook (Sixth Edition), 2016, Pages 55-115

9.       Department of the Environment, (1990), Cryptosporidium in Water Supplies: Report of the Group of Experts. Chairman: Sir John Badenoch. HMSO, London.

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Authors:

Yao-Wen Tsai, Cong-Trang Nguyen

Paper Title:

Finite Time Sliding Mode Controller based on Reduced-Order Observer for the Mismatched Uncertain Systems with a Time Delay

Abstract:  This paper presents the design of the finite time sliding mode controller based on reduced order observer for time-delay systems with mismatched uncertainties. The main achievements of work are: (1) a suitable reduced order observer (ROO) is constructed to estimate the unmeasurable state variables, (2) a finite time sliding mode controller (FTSMC) is designed by employing the estimated variables, and (3) by the application of the Lyapunov stability theory and the linear matrix inequality (LMI) technique, the stability of the overall closed-loop mismatched uncertain systems with a time delay is guaranteed in sliding mode under sufficient condition. Finally, the design procedure is given to summarize the proposed method.

Keywords:
Variable Structure Control (VSC), reduced- order observer (ROO), finite-time convergence, mismatched uncertainty, time-varying delay.


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