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Issue-3 February 2017

Volume-6 Issue-3 Published on February 28, 2017
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S. No

Volume-6 Issue-3, February 2017, ISSN:  2249-8958 (Online)
Published By: Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd. 

Page No.



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.

Solar Energy, Policy, Subsidy, Measure, Investment


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

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





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.

Wireless sensor network; Game Theory; Cooperative game theory; Non-cooperative game theory; Wireless communications.


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 – /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.




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%.

 food waste, composting system, accelerating process technology


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.





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.

Ferrous Matrix Composites, Nanocomposites, Particle reinforcement, Powder Metallurgy.


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.




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.

 Concrete, Fire, RCC, Spalling


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





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.  

Optimization Technique, Taguchi`s L9 orthogonal array, analysis of variance (ANOVA), Minitab-17


1.    A.Ghosh, A K Mallik, Manufacturing Science

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





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.

Back injury, Workstation design, Human factor, Productivity and Anthropometry.  


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.




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.

Sense of community, Built environment, Statistical analysis, Social Interaction, Alexandria neighborhoods.


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:[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.




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.

 Sustainable Urban Mobility (SUM) – Travel Behaviour - Mode choice –Non-urban form factors – Built environment factors – TOD development – Sustainable neighborhoods.


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, , 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:

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.





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. 

edutainment, QR-Code, QR IT Seek competition, Digital Natives, pedagogy.


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: [Accessed on 27th March 2016]

3.    EDUCASE (2009) “7 Things You Should Know about QR Codes,” EDUCASE Learning Initiative. Available at: [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: [Accessed 25th June 2016]

6.    Andrew Miller (2011) “Twelve Ideas for Teaching with QR Codes”. Available at: [Accessed on 22th June 2016]

7.    HubPages (2013) “QR Code secrets. Dynamic vs. Static what's the difference?”. Available at : [Accessed on 28th June 2016]

8.    Ben Van Sas, Joroen Steeman (2012) “QR Codes – Linking the real world with the digital world.” Available at: [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.




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.

 Control, Direct-Current, Fuzzy, Motor


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.





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.

  Energy, Exergy, Entropy, CHP.


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.





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.

CT Images, Image Preprocessing, Segmentation, Enhancement, Feature Extraction and Classification.


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




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.

 Home Automation; Internet of Things; LoRa; Android; Smart


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. 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.




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.

Mobile Adhoc Network (MANET), Security, Attacks, Routing, Mobile nodes, Dynamic Topology


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.




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.

Cognitive Radio Genetic Algorithm, Ant Colony Optimization, Mutated Ant Colony Optimization, QoS Provisioning.


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




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.

 Mulching, Harvesting, Indigenous, Knowledge, Bush fallowing, standard deviation.


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:

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.




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.

Moth Flame Optimisation Algorithm, Fuzzy Logic Controller, Positive Output Elementary LUO Converter.


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.




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.

Cloud computing, deployment models, load balancing, fault tolerance


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.




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.

impulse noise, probability density function, PSM Filter, SDROM Filter, PWMAD Filter, Modified SDROM, PSNR, SSIM Index.


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.




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.

Stroke, Graphical User Interface (GUI), Support Vector machine (SVM)


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





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

 authentication, security, shared access and cloud computing


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.





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.

 Muzzle Print, Principal Component Analysis (PCA), Membership Function.


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.





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.

Checkpoint/restart, checkpointing protocols, Distributed systems, rollback recovery, fault tolerant computing


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.





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.

 Nozzle filter, Muddy water, Algae water, Suspended solids, turbidity.


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.

10.    Department of the Environment (1994) Proceedings of Workshop on Cryptosporidium in Water Supplies. Edited by A. Dawson  and A Lloyd. HMSO, London.

11.    Smethurst, George (1990) Basic Water Treatment.   Second Edition, Thomas Telford Ltd.,  London .

12.    American Water works Association. Water Quality and Treatment A Handbook of Community Water Supplies, Fourth Edition .  A .W.W.A., 6666 W. Quincy Ave., Denver, CO 80235.

13.    C .Twort, Law, F. M., Crowley, F. W., and  Ratanayaka , D.D., (1994), Water Supply. 4th Edition. Edward Arnold, London.

14.    European Communities (Quality of Water Intended for  Human Consumption ) Regulations 1988. (S. I. No 84 of 1988) Stationary Office, Dublin.

15.    Code of Practice for the Safety, Health and Welfare at Work (Chemical Agents) Regulations, 1994, (S.I. No. 445 of 1994). Stationery Office, Dublin

16.    Peavey, Howard, Rowe, Donald and Tchobanoglous (1986) Environmental Engineering Mc Graw - Hill, New York.

17.    Flanagan, P.J., (1992) Parameters of Water Quality  –Interpretation and Standards. Second Edition.  Environmental Research Unit, Dublin.

18.    Engineering School, UCD (1972). Course   Notes - Water Quality Management. Department of Civil Engineering, University College, Dublin.

19.    Safety, Health and Welfare at Work Act, 1989 (No. 7 of 1989). Stationery Office, Dublin.

20.    US EPA (1994) Water Treatment Plant Operation Volume 1: A Field Study Training Program. Third  Edition

21.    Supplies. Fourth  Edition. A. W.W.A., 6666 W. Quincy Ave., Denver, CO 80235. Edward Arnold, London.

22.    Department of the Environment (1990). Cryptosporidium   in Water Supplies: Report of   the   Group of Experts. Chairman: Sir John Badenoch. HMSO, London.

23.    T.Pujol, G. Arbat, J. Bove, J. Puig-Bargues, M. Duran-Ros, J. Velayos, F. Ramírez de Cartagena ,(2016), Effects of the underdrain design on the  pressure drop in sand filters,Biosystems Engineering, Volume  150,Pages 1-9

24.    M. Boller (1993), Filter mechanisms in rousing filters;j  water Supply Res. Technol. Aqua. 42(3): 174-85.

25.    M. Wegelin. (1996). Surface water treatment. A design,  construction and operation manual, Swiss Federal Institute for environmental science and Technology (EAWAG) and department water and Sanitation in developing countries (SANDEC)




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.

Variable Structure Control (VSC), reduced- order observer (ROO), finite-time convergence, mismatched uncertainty, time-varying delay.


1.        J . Y. Hung, W. Gao, and J. C. Hung, “Variable structure control: A survey,” IEEE Trans. on Indus. Electro., vol. 40, 1993, pp. 2–22.
2.        S. H. Zak, Systems and Control, New York: Oxford Univ. Press, 2003.

3.        Z. He, X. Wang, Z. Gao, and J. Bai, “Sliding mode control based on observer for a class of state-delayed switched systems with uncertain perturbation,” Mathematical Problems in Engineering, vol. 2013, Article ID 614878, 2013, 9 pages.

4.        S.-H. Tsai, and Y.-H. Chang,“Sliding Mode Control for A Class of Uncertain Time-Delay System,”Ap. Mathematics and Infor. Sci., 2015, pp. 267-273.

5.        H. Li, P. Shi, D. Yao, and L. Wu, “Observer-based adaptive sliding mode control for nonlinear Markovian jump systems,” Automatica, vol. 64, Feb. 2016, pp. 133–142.

6.        Z. Liu, L. Zhao, Y. Kao, and C. Gao, “Robust passive control for a class of uncertain neutral systems based on sliding mode observer,” ISA Transactions,, 2016.

7.        Boulaabi, A. Sellami, and F.B. Hmida, “A robust sensor fault reconstruction based on a new sliding mode observer design method for uncertain delayed systems: A satellite system application,” J. of Con. Engineering and Ap. Informatics, vol. 17, 2015, pp. 88–97.

8.        C.T. Chen and S. T. Peng, “A sliding mode control scheme for non-minimum phase non-linear uncertain input-delay chemical processes,” J. of Process Control, vol. 16, 2006, pp. 37–51.

9.        Rezoug, B. Tondu, M. Hamerlain, and M. Tadjine, “RBFNN-HOMS Non-singular Terminal Sliding Control of n-DOF Robotic Manipulator,” J. of Control Engineering and Ap. Infor., vol. 18, 2016, pp. 52–62.

10.     S. C. Garcia, M. C. M. Teixeira, J. P. F. Garcia, U. N. L. T. Alves, and J. M. S. Ribeiro, “Discrete-Time Sliding Mode Control for Uncertain Networked System Subject to Time Delay,” Mathematical Problems in Engineering, vol. 2015, Article ID 195120, 2015, 10 pages.

11.     Q. Zhang, “Adaptive observers for multiple–input–multiple–output (MIMO) linear time-varying systems,” IEEE Trans. Autom. Control, vol. 47, Mar. 2002, pp. 525–529.

12.     J. Koshkouei, K. J. Burnham,“Discontinuous Observers for Nonlinear Time-Delay Systems,”Int. J. Systems Science, vol. 40, 2009.

13.     F. J. Bejarano and A. Pisano, “Switched observers for switched linear systems with unknown inputs,” IEEE Trans. Automat. Control, vol. 56, Mar. 2011, pp. 681–686.

14.     F. Zhu, “State estimation and unknown input reconstruction via both reduced-order and high-order sliding mode observers,” J. Process Control, vol. 22, 2012, pp. 296-302.

15.     L. Wu and J. Lam, “Sliding mode control of switched hybrid systems with time-varying delay,” Int. J. Adapt. Control Signal Process., vol. 22, 2008, pp. 909–931.

16.     J. Lian, J. Zhao, and G. M. Dimirovski, “Robust H∞ sliding mode control for a class of uncertain switched delay systems,” Int. J. Syst. Sci., vol. 40, 2009, pp. 855–866.

17.     M. Pai,“Observer-based adaptive sliding mode control for nonlinear uncertain state-delayed systems,”International J. of Control, Auto., and Sys., vol. 7, 2009, pp.

18.     L. Liu, Z. Han, and W. Li, “H∞ non-fragile observer-based sliding mode control for uncertain time-delay systems,” J. Franklin Inst., vol. 347, 2010, pp. 567–576.

19.     S. Boyd, L. El. Ghaoui, E. Feron, and V. Balakrishnan, Linear Matrix Inequalities in Systems and Control Theory, Philadelphia, PA: SIAM, 1994.

20.     P. Gahinet, A. Nemirovskii, A. J. Laub, and M. Chilali, LMI Control Toolbox, Natick, MA: The MathWorks, Inc, 1994.

21.     Y. W. Tsai and V. V. Huynh, “Output Feedback and Single-Phase Sliding Mode Control for Complex Interconnected Systems,” Mathematical Problems in Engineering, vol. 2013, Article ID 946385, 2015, 16 pages.

22.     S. Sayyaddelshad and T. Gustafsson, “H∞ observer design for uncertain nonlinear discrete-time systems with time-delay: LMI optimization approach,” Inter. J. of Robust and Nonlinear Control, vol. 25, 2015, pp. 1514–1527.

23.     O. M. E. El-Ghezawi, A. S. I. Zinober, and S. A. Billings, “Analysis and design of variable structure systems using a geometric approach,” International J. of Control, vol 38, 1983, pp. 657-671.

24.     S. H. Zak and S. Hui, “On variable structure output feedback controllers,” IEEE Trans. Autom. Control, vol. 38, 1993, pp. 1509–1512.

25.     K. Gu, V. L. Kharitonov, and J. Chen, Stability of Time-delay Systems, Birkh¨auser: Boston, 2003.

26.     X. G. Yan, S. K. Spurgeon, and C. Edwards, “Static output feedback sliding mode control for time-varying delay systems with time-delayed nonlinear disturbances,” Inter. J. Robust Nonlinear Control, vol. 20, 2010, pp. 777–788.




Krishna Samalla

Paper Title:

A Novel Algorithm for Multiple Data Sharing Via Cloud Storage

Abstract:   As the way that computing concepts gives the cloud computing, which permits once needed and low maintenance usage of resources, but the information is shares to some cloud servers and numerous privacy connected considerations emerge from it .Various schemes like primary based on the attribute based encoding are developed to secure the cloud storage. Most of the work looking at the information privacy and therefore the access management, while less attention is given to the privilege management and the privacy. An economical scientific discipline approach for information sharing wherever information is shared among a bunch of users as information. How to firmly and with efficiency share a group of information associated with any subject areas with others in cloud storage. Development of new novel concept of Key Aggregate Searchable cryptography (KASE). This concept is enforced through development of a concrete key-aggregate searchable cryptography framework theme. This scheme is delineate as wherever knowledge an information owner solely has to generate and distribute one mixture key to a data user for sharing an outsized variety of documents and on the opposite aspect user solely has to submit one mixture trapdoor to the cloud server, so that he/she will question over the shared documents by the assistance of generated single mixture trapdoor. Advanced Key sharing system based on hint text methodology is created to share the information safely. Once the data sharing is completed then the key combination differs from its actual kind. So the user cannot guess the key combination cryptosystem and this method provides economical answer than the prevailing ones.

 Data Security, Cloud, Integrity, Bulk Request, Bulk Response, Dynamic Keys.


1.       Cloud-Storage,
2.       Amazon Web Services (AWS),

3.       Google App Engine

4.       S. Yu, C. Wang, K. Ren, and W. Lou, “Achieving Secure, Scalable, and Fine-Grained Data Access Control in Cloud Computing”, Proc. IEEE INFOCOM, pp. 534-542, 2010..

5.       X. Liu, Y. Zhang, B. Wang, and J. Yan. “Mona: secure multi-owner data sharing for dynamic groups in the cloud”, IEEE Transactions on Parallel and Distributed Systems, 2013, 24(6): 1182-1191.

6.       C. Chu, S. Chow, W. Tzeng, et al. “Key-Aggregate Cryptosystem for Scalable Data Sharing in Cloud Storage”, IEEE Transactions on Parallel and Distributed Systems, 2014, 25(2): 468- 477.

7.       X. Song, D. Wagner, A. Perrig. “Practical techniques for searches on encrypted data”, IEEE Symposium on Security and Privacy, IEEE Press, pp. 44C55, 2000.

8.       R. Curtmola, J. Garay, S. Kamara, R. Ostrovsky. “Searchable symmetric encryption: improved definitions and efficient constructions”, In: Proceedings of the 13th ACM conference on Computer and Communications Security, ACM Press, pp. 79- 88, 2006.

9.       P. Van,S. Sedghi, JM. Doumen. “Computationally efficient searchable symmetric encryption”, Secure Data Management, pp. 87-100, 2010.

10.    S. Kamara, C. Papamanthou, T. Roeder. “Dynamic searchable symmetric encryption”, Proceedings of the 2012 ACM conference on Computer and communications security (CCS), ACM, pp. 965-976, 2012.

11.    D. Boneh, C. G, R. Ostrovsky, G. Persiano. “Public Key Encryption with Keyword Search”, EUROCRYPT 2004, pp. 506C522, 2004.

12.    Y. Hwang, P. Lee. “Public Key Encryption with Conjunctive Keyword Search and Its Extension to a Multi-user System”, In: Pairing-Based Cryptography C Pairing 2007, LNCS, pp. 2-22, 2007.

13.    J. Li, Q. Wang, C. Wang. “Fuzzy keyword search over encrypt-ed data in cloud computing”, Proc. IEEE INFOCOM, pp. 1-5, 2010.

14.    C. Bosch, R. Brinkma, P. Hartel. “Conjunctive wildcard search over encrypted data”, Secure Data Management. LNCS, pp. 114-127, 2011

15.    C. Dong, G. Russello, N. Dulay. “Shared and searchable encrypted data for untrusted servers”, Journal of Computer Security, pp. 367-397, 2011.

16.    F. Zhao, T. Nishide, K. Sakurai. “Multi-User Keyword Search Scheme for Secure Data Sharing with Fine-Grained Access Control”. Information Security and Cryptology, LNCS, pp. 406-418, 2012.

17.    J. W. Li, J. Li, X. F. Chen, et al. “Efficient Keyword Search over Encrypted Data with Fine-Grained Access Control in Hybrid Cloud”, In: Network and System Security 2012, LNCS, pp. 490-502, 2012.

18.    J. Li, K. Kim. “Hidden attribute-based signatures without anonymity revocation”, Information Sciences, 180(9): 1681- 1689, Elsevier, 2010.

19.    X.F. Chen, J. Li, X.Y. Huang, J.W. Li, Y. Xiang. “Secure Outsourced Attribute-based Signatures”, IEEE Trans. on Parallel and Distributed Systems,, 2013.

20.    J.Li, X.F. Chen, M.Q. Li, J.W. Li, P. Lee, Wenjing Lou. “Secure Deduplication with Efficient and Reliable Convergent Key Management”, IEEE Transactions on Parallel and Distributed Systems, 25(6): 1615-1625, 2014. [22] Z. Liu, Z. Wang, X. Cheng, et al. “Multi-user Searchable Encryption with Coarser-Grained Access Control in Hybrid Cloud”, Fourth International Conference on Emerging Intelligent Data and Web Technologies (EIDWT), IEEE, pp. 249- 255, 2013.

21.    C. Wang, Q. Wang, K. Ren, and W. Lou, “Privacy-Preserving Public Auditing for Data Storage Security in Cloud Computing”, Proc. IEEE INFOCOM, pp. 525-533, 2010.

22.    B. Wang, B. Li, and H. Li, “Knox: Privacy-Preserving Auditing for Shared Data with Large Groups in the Cloud”, Proc. 10th Intl Conf. Applied Cryptography and Network Security, pp. 507-525, 2012.

23.    D. Boneh, C. Gentry, B. Waters. “Collusion resistant broadcast encryption with short ciphertexts and private keys”, Advances in Cryptology CCRYPTO 2005, pp. 258-275, 2005.




Ahmed Shany Khusheef, Abdulkareem Shaheed Sabr

Paper Title:

Investigation of Converting a Building to Operate by Solar Energy

Abstract: Many governments recognize the advantages of generating the electricity from solar energy and therefore, they offer generous incentives and cash rebates to install photovoltaic (PV) systems. Despite Iraq that is, as result of the electric shortages, 90% of its households are dependent on diesel generators that are controlled by independent operators, solar energy has not been widely utilized. This paper provides the fundamental information about design and constructing of PV system.  It is also presenting a cost analysis of PV system that delivers about   per day. It is found that the solar energy price (0.1368$/kWh) is almost matching the actual cost of fuel-based electrical generation (0.13$/kWh [1]). Therefore, the PV systems can be competitive with the diesel power generators that are used by Iraqis if a source of funding is offered to offset the enormous up-front (initial) cost of PV systems.

PV system, Cost analysis, Levelized cost of electricity (LCOE), Electric demand.


1.       Iraq Ministry of Electricity, electricity prices, 2015.
2.       P. Sudeepika and G. M. Gayaz Khan, "Analysis of mathematical model of PV cell codule in Matlab/Simulink environment," International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, Vol. 3, No. 3 pp. 7323-7827, 2014.  

3.       W. A. El-Basit, A. M. A. El–Maksood and F. A. E. S. Soliman, "Mathematical model for photovoltaic cells," Leonardo Journal of Sciences, pp. 13-28, 2013.

4.       S. S. Mohammed, "Modeling and Simulation of Photovoltaic module using MATLAB/Simulink," International Journal of Chemical and Environmental Engineering, Vol. 2, No. 5, pp. 350-355, 2011.

5.       S. Leva, D. Zaninelli, "Technical and Financial Analysis for Hybrid Photovoltaic Power Generation Systems", WSEAS Transactions on Power Systems, Vol. 5, No. 1, pp.831-838, 2006.

6.       S. Leva, D. Zaninelli and R. Contino, "Integrated renewable sources for supplying remote power systems," WSEAS Transactions on Power Systems, Vol. 2 No. 2, pp. 41-48, 2007.

7.       J. Schaefer, "Review of photovoltaic power plant performance and economics," IEEE Transaction of Energy Conversation, Vol. 5, pp. 232-238, June, 1990.

8.       Ecometrica, "Electricity-specific emission factors for grid electricity,"  p. 6, 2011.

9.       United Nations Development Program (UNDP), "Catalysing the use of solar photovoltaic energy," pp. 6-7&13, 2014.

10.    Free Sun Power. (last visit 2016, January 25).

11.    V. Lombardi, "A practical guide to solar power system design for homeowners," pp. 11,12&21, 2012.

12.    Catalogue, "Integrated power system, back-up and solar power systems," pp. 3&4, 2015. 

13.    C. Roos, "Solar electric system design, operation and installation: an overview for builders in the Pacific Northwest," Washington State University, Extension Energy Program, 2009.

14.    Vasudev, "The levelized cost of electricity," Stanford University, 2011.

15.    M. Cambell, "The Drivers of the Levelized Cost of Electricity for Utility-Scale Photovoltaics," 2008.

16.    De, "Solar power - 1 kW system energy generation study and cost calculation," International Journal of Electrical and Electronics Engineering (IJEEE), Vol. 3, No. 4, pp. 23-30, 2014.

17.    P. Poonpun and W. T. Jewell, "Analysis of the cost per kilowatt hour to store electricity," IEEE Transactions on Energy Conversion, Vol. 23, No. 2, pp. 529-534, 2008.

18.    D. Steward, G. Saur, M. Penev, and T. Ramsden, "Lifecycle Cost Analysis of Hydrogen Versus Other Technologies for Electrical Energy Storage," National Renewable Energy Laboratory, Technical Report, November 2009.




Poonam Rajput, Prateek Wankhade

Paper Title:

A Review Paper on Microstrip Patch Antenna Used in Wlan Systems

Abstract:  A compact microstrip patch antenna became a very useful in communication systems. Properties like compactness, light weight, high bandwidth make it a good candidate of communication system. This paper reviews the performance analysis of Compact Dual-Band Microstrip Antenna for IEEE 802.11a WLAN Application (2014), comparative analysis of s-shaped Multiband microstrip patch Antenna (2013), Dual-Band Antenna with Compact Radiator for 2.4/5.2/5.8 GHz WLAN Applications (2012), A Slot-Monopole Antenna for Dual-Band WLAN Applications (2011) and Compact Broadband Slotted Rectangular Microstrip Antenna (2009). The paper also discusses the technology used in order to bring the required changes in terms of improved performance characteristics.

 WLAN (Wireless local area network), Dual band, Transmission line, Microstrip antenna, Monopole antenna, Dual band antenna, RMSA, Water Patch, L-probe.


1.    Keisuke Noguchi et al. “Design of Wideband/Dual-Band E-Shaped Patch Antennas With the Transmission Line Mode Theory” IEEE Transactions on Antennas and Propogation, Vol. 64, Issue. 4, pp: 1183 – 1192, April 2016.
2.    Yujian li and Kwai-man luk “A Water Dense Dielectric Patch Antenna” IEEE Access, Vol. 3, pp: 274-280, 2015.

3.    Xiao Lei Sun et al. “Dual-Band Antenna with Compact Radiator for 2.4/5.2/5.8 GHz WLAN Applications” IEEE Antennas and Wireless Propogation, Vol. 60, issue 12, December 2012.

4.    Chih-Yu Huang and En-Zo Yu “A Slot-Monopole Antenna for Dual-Band WLAN Applications” IEEE Antennas and Wireless Propogation Letters, Vol. 10, 2011.

5.    Amit A. Deshmukh and K.P.Ray “Compact Broadband Slotted Rectangular Microstrip Antenna” IEEE Antennas and Wireless Propogation Letters, Vol.8, 2009.

6.    M. Ali et al. “Wide-Band/Dual-Band Packaged Antenna for 5–6 GHz WLAN Application” IEEE Antennas and Wireless Propogation, Vol. 52, Issue 2, February 2004.




Ibrahim F. Shaker, Tamer F. Fath-Allah, Mohamed M. El-Habiby, Ahmed E. Ragheb, Alaa Al-Din I. Awad

Paper Title:

Increasing PPP Accuracy using Permanent Stations Corrections

Abstract:   One of the main current problems facing Global Positioning System (GPS) is to get the positions with high accuracy and low cost, effort and time. Two techniques are used in GPS positioning, which are the relative and point positioning. In common, the first technique provides the higher accuracy, but with higher cost and effort. Another kind of point positioning is the Precise Point Positioning (PPP) which counts on GNSS precise products. It is adequate for many applications that requires the decimeter level accuracy using one receiver, but requires scientific software or online services for data processing. The main challenge here is to raise the accuracy of PPP to add other applications suited to the gained accuracy. The main objective of the current study is to test different mathematical models producing positional corrections to select the best set depending on synchronized data and validate the selected model in synchronized and non-synchronized cases depending on data of two different campaigns. These corrections -produced from permanent stations- are added to the static PPP coordinates of the tested points near the permanent stations to reach the highest possible accuracy depending on GPS single frequency observations using a scientific package. The obtained results offered a synchronized average positional error reaching to 0.074m and RMSE of 0.023m in the first campaign and 0.146m with RMSE of 0.061m in the second campaign. It reaches 0.156m with RMSE of 0.074m in the best non-synchronized case. The user can raise the accuracy of single frequency static PPP when the data of four synchronized permanent stations are available in the same observational time or within 4 days before or after the observational time.

GPS, Non-synchronized, Precise Point Positioning (PPP), Single frequency, Synchronized.


1.       T. F. Fath-Allah, “A New Approach for Cycle Slips Repairing Using  GPS Single Frequency Data”.  World Applied Science Journal 8 (3): 315-325, 2010.
2.       F. Ragab and T. F. Fath-Allah, “Towards The Improvement of 2D Coordinates Transformation Techniques between UTM and ETM”.  Royal Statistical Society Conference, Edinburgh, United Kingdom, 2009.

3.       M. El-Tokhey, A. H. Abd-Elrahman, T. F. Fath-Allah and A. I. Awad, “Preliminarily Evaluation of Baseline Relative Accuracies Using L1 Frequency Observations of Navigation-Grade GARMIN Receivers”. Journal of Surveying Engineering, Vol. 137, No. 1, February 2011.

4.       H. Wellenhof, H. Lichtenegger and J. Collins, “Global Positioning System Theory and Practice 5th edition”. Springer, Verlag, New York, USA, 2001.

5.       El-Rabbany, “Introduction to Global Positioning System (GPS)”. ArtechHousemobile communication series, Boston, London, 2002.

6.       Q. Le and C. Tiberius, “Single-frequency precise point positioning with optimal filtering”. GPS Solut (2007) 11: 61–69, DOI 10.1007/s10291-006-0033-9, Springer-Verlag, 2006.

7.       F. Shaker, T. F. Fath-Allah, M. M. El-habiby, A. E. Ragheb and A. I. Awad, “Enhancement of Precise Point Positioning Using GPS Single Frequency Data”. International Journal of Scientific & Engineering Research (IJSER), Volume 7, Issue 12, ISSN: 2229-5518, 642-650, 2016.

8.       El-Mowafy, “Decimeter Level Mapping Using Differential Phase Measurements of GPS Handheld Receivers”. The Survey Review, UK, Vol. 38, No. 295, pp. 47-57, 2005.

9.       T. F. Fath-Allah, “Quality Assessment of GPS Smoothed Codes for Different Smoothing Window Sizes and Times”. International Journal of Engineering Research & Technology (IJERT), Volume 4, Issue 5, ISSN: 2278-0181, 2015.

10.    Abdel Mageed “Assessment of the Accuracy of Processing GPS Static Baselines Up To 40 Km Using Single and Dual Frequency GPS Receivers”. International Journal of Modern Engineering Research (IJMER), Vol. 4, Iss. 1, ISSN: 2249–6645, 2014.

11.    F. Zumberge, M. B. Heflin, D. C. Jefferson, M. M Watkins, F. H. Webb “Precise Point Positioning for The Efficient and Robust Analysis of GPS Data from Large Networks”. J. Geophys. Res.  (B3), 5005–5017 (1997).

12.    Dawidowicz and G. Krzan “Coordinate estimation accuracy of static precise point positioning using on-line PPP service, a case study”. Acta Geod Geophys (2014) 49:37–55 DOI 10.1007/s40328-013-0038-0

13.    Q. Guo, “Precision Comparison and Analysis of Four Online Free PPP Services in Static Positioning and Tropospheric Delay Estimation”. Springer-Verlag Berlin Heidelberg, 2014.




M. Jeba Jeeva Rani, G. Allen Gnana Raj

Paper Title:

Synthesis, Characterization and Photocatalytic Activity of Amino Acid Doped Metal Free g-C3N4 Composite Photocatalyst

Abstract: The g-C3N4-Amino acid (CNA-g-C3N4) composite photocatalyst was synthesized by simple co-polymerization process. The photocatalyst was characterized by X-ray diffraction (XRD), Scanning election microscopy (SEM) with EDAX and FT-IR analysis. Rhodamine-B (Rh-B) dye solution under visible light irradiation was used to determine the photocatalytic activity. The photocatalytic activity of CNA-g-C3N4 composite posses long term stability and visible light activity than bare g-C3N4.

 Amino acid, composite, metal free, g-C3N4, melamine


1.       Fujishima and K. Honda, Nature, (1972),238,37.
2.       N.F. Steven and A.J. Brad, J.Am. Chem. Soc., (1977), 99, 303.

3.       B.Cao and W. Cai, J. Phys. Chem. C., (2007), 112, 680.

4.       X.C. Wang, K. Maeda, A. Thomas, K. Takanabe, G. Xin, J.M. Carlsson, K. Domen and M.Antoietti, Nat. Mater., (2009), 25, 10397.

5.       S.C. Yan, Z.S.Li and Z.G Zou, Lamgnuir, (2009), 25, 10397.

6.       E.O. Frank, Chem. Mater., (2008), 20, 35.

7.       Y.Guo, S. Chu, S.C. Yan, Y. Wang and Z.G. Zou, Chem, Commum., (2010), 46, 7325.

8.       Y.J. Zhang, T. Mori, J.H. Ye and M.Antoni etti, J. Am. Chem.Soc., (2010), 132, 6294.

9.       H.J. Yan and H. X. Yang, J. Alloys Compd.,  (2011), 509, 126.

10.    H. Harada, T. Ueda, T. Sankata, J. Phys.Chem., (1989), 93, 1542.

11.    ESKIZEYBEK, F. SARI, H. GULCE, A. GLUCE, A. AVEI, APPL. CATA., B: ENVIRON, (2012), 119-197.

12.    Q.J. Xiang, J.G. Yu and Z.G. Zou, Dalton Trans.,( 2010), 39, 1488.

13.    M.Zhang, J. Xu, R. Zong, Y. Zhu, Appl. Catat. B: Environ., (2014)




Sumaira M.Hayat Khan, Ayyaz Hussain, Imad Fakhri Taha Alshaikhli

Paper Title:

An Adequate Image Retrieval Technique Based on Global Level Feature Extraction

Abstract: Efficient and effective methods are required for the retrieval of relevant data from data stores. The two main approaches for retrieving a required image from a database are known as the local approach and the global approach. This paper presents the technique based on global approach of image feature extraction and comparison. Image features are calculated by taking into account image as a whole. All the three rudimentary image features like; color, texture and shape are utilized in the process of feature vector calculation. Besides these basic image features, Edge Histogram and Fourier Descriptors are also computed to extract edge information and shapes of the objects in the image respectively. Similarity between two images is determined by calculating Euclidean distance between their feature vectors. The experiments in this study were performed on natural images of diverse semantics from a Corel image database, and showed obvious improvement in results compared to several noble systems in the literature.

Content Based Image Retrieval, Feature Extraction, Feature Vector, Similarity Measure, Fourier descriptor, Edge Histogram Descriptor.


1.       Y. Rui, T.S. Huang, S.F. Chang, “Image retrieval: current techniques, promising directions and open issues”, J. Visual Communication, Image Representation 1999.
2.       A.W.M. Smeulders, M. Worring, et al., “Content-based image retrieval at the end of the years”, IEEE TPAMI 2000.

3.       I.K. Sethi, I.L. Coman, “Mining association rules between low-level image features and high-level concepts”, Proceedings of the SPIE Data Mining and Knowledge Discovery, vol. III, (279–290) 2001.

4.       H. Armitage and P. G. Enser, “Analysis of user need in image archives,” Journal of Information Science, vol 23, no. 4, pp. 287–299, Apr. 1997.

5.       R.S. Torres, A.X. Falco, “Content-based image retrieval, theory and applications, Rev”. April, 2006.

6.       Fallouts, R. Barberet al., “Efficient and effective querying by image content”. Journal of Intelligent Information Systems, July 1994.

7.       Pentland, R. Picard, and S. Sclaro. Photo book, “Content-based manipulation of image databases”, International Journal of Computer Vision, 1996.

8.       Carson, S. Belongie etal, “Image segmentation using expectation maximization and its application to image querying”, IEEE Transaction on Pattern Analysis and Machine Intelligence, August. 2002.

9.       M. Squire, W. Mulleretal, “Content-based query of image databases, inspirations from text retrieval: Inverted les, frequency-based weights and relevance feedback”, In Scandinavian Conference on Image Analysis, June 1999.

10.    A.W.M. Smeulders, M. Worring, et al., “Content-based image retrieval at the end of the early years”, IEEE Trans. Pattern Anal. Mach. Intel, 2000.

11.    W.Y. Ma, B.S. Manjunath, “NeTra: a toolbox for navigating large image databases”, Multimedia Systems 7 (184–198) 1999.

12.    R. S. Choras, “Image Feature Extraction Techniques and Their Applications for CBIR and Biometrics Systems,” International Journal of Biology and Biomedical Engineering, vol. 1, no. 1, 2007.

13.    H.A, Jalab, “Image retrieval system based on color layout descriptor and Gabor filters”, IEEE Conference on Open Systems,  25-28 Sept. 2011, pp. 32 – 36.

14.    G. Zhang et al., “Shape feature extraction using fourier descriptors with brightness in content-based medical image retrieval,” in IEEE Int. Conf. on Intelligent Information Hiding and Multimedia Signal Processing, 2008, pp. 71 – 74.

15.    H. Kauppinen et al., “An experimental comparison of autoregressive and Fourier based descriptors in 2D shape classification,” IEEE Transactions on Pattern Analysis and Machine Intelligence, pp. 201–207, 1995.

16.    D. S. Zhang and G. Lu, “Evaluation of MPEG-7 shape descriptors against other shape descriptors,” Multimedia Systems, vol. 9, no. 1, pp. 15–30, 2003.

17.    J. Canny, “A computational approach to edge detection,” IEEE Transactions on Pattern Analysis and Machine Intelligence, pp. 679–698, 1986.

18.    Pentland et al., “Photobook: Content-based manipulation of image databases,” International Journal of Computer Vision, vol. 18, no. 3, pp. 233-254, 1996.

19.    S. Nandagopalan et al., “A universal model for content based image retrieval,” International Journal of Computer Science, vol. 4, no. 4, pp. 242, 2009.

20.    S. Soman et al., “Content Based Image Retrieval Using Advanced Color and Texture Features”, International Journal of Computer Applications, 2012.

21.    C.M.Pun and C.F.Wong, “Fast and robust color feature extraction for content based  image  retrieval”, Internation journal of advancments in computing technolog, vol 3, no 6, July 2011.

22.    M.A.Helala, “A content based image retrieval approach based on principal region detection”, IJCSI, International journal of computer science issues, vol 9, issue 4, no 1, July 2012

23.    X. Qi and Y. Han, “A novel fusion approach to content-based image retrieval,” Pattern Recognition, vol. 38 pp. 2449–2465, 2005.

24.    Y. Chen and J. Wang, “A region-based fuzzy feature matching approach to content-based image retrieval,” IEEE Transaction on Pattern Analysis and Machine Intelligence, vol. 24, no. 9, pp. 1252–1267, 2002.

25.    J. Li et al., “SIMPLIcity: semantics sensitive integrated matching for picture libraries,” IEEE Transaction on Pattern Analysis and Machine Intelligence, vol. 23, pp. 947 – 963, 2001.

26.    B. S. Manjunath et al., Introduction to MPEG-7 multimedia content description interface. New York: Wiley, 2002.

27.    M. Swain and D. Ballard, “Color indexing,” International Journal of Computer Vision, vol. 7, no. 1, pp. 11–32, 1991.




Deshmukh Bhakti S., Gharte Sneha H., Nagare Shruti R., H. R. Deshmane

Paper Title:

Agriculrtural Robot for Plant Health Indication

Abstract:  It is difficult task for producing agricultural products, various micro-organisms, pests and bacterial diseases attack on plants. These diseases can occur through the leaves, steams or fruit inspection. This paper covers technique of image processing for early detection of plant disease through feature extraction of leaf and preprocessing of image from RGB (YCbCr) to different color space conversion, image enhancement; segment the region of interest. Minimum distance classifier is used to compare extracted features from original image and stored database. When plant disease is detected fertilizer motor gets ON. By using Graphical User Interface symptoms and fertilizer for detected disease will displayed on computer. The robot has also watering mechanism it will water the plants according to their needs by observing temperature and LCD will display the temperature. Working of the Robot is based on Bluetooth.

 Plant Health, Open Agriculture, Bluetooth, Database. 


1.       International Journal of Advanced Technology in Engineering and Science Volume No.03, Issue No. 01, January 2015 ISSN (online): 2348 – 7550 ‘Autonomous Farming Robot with Plant Health Indication’. Prof. K.V. Fale 1, Bhure Amit P 2, Mangnale Shivkumar 3 Pandharkar Suraj R 4Professor, RSCOE, Pune, (India) 2, 3, 4 Student, RSCOE, Pune, (India)
2.       F. Argenti,L. Alparone,G. Benelli ,” Fast algorithms for texture analysis using co-occurrence matrices” Radar and Signal Processing, IEE Proceedings , vol. 137, Issue 6, pp:443-448 , No. 6, December 1990.

3.       Fang Jianjun, “Present Situation and Development of Mobile Harvesting Robot” and Transactions of the Chinese Society of Agricultural Engineering, 2004, vol. 20, no. 2,pp. 273-278.

4.       Bisgaard, M. Vinther, D., and Ostergaard, K. Z. 2004. Modelling and Fault-Tolerant Control of an Autonomous Wheeled Robot. Group Report 04gr1030a. Institute of Control Engineering, Aalborg University, Denmark.

5.       Mario M. F. and Giulio R., “Agricultural Robot for Radicchio Harvesting,”Journal of Field Robotics, 2006, vol. 23, no. 6-7, pp. 363-377.

6.       Belforte, R. Deboli, P. Gay and D. Ricauda Aimonino, “Robot Design andTesting for Greenhouse Applications,” Biosystems Engineering, 2006, vol. 95, no. 3,pp. 309-321.

7.       T. Bakker, K. van Asselt, J. Bontsema, J. Müller, and G. van Straten, “Autonomous navigation using a robot platform in a sugar beet field,” Biosyst. Eng., vol. 109, no. 4, pp. 357–368, 2011.

8.       Anand H. Kulkarni, Ashwin Patil R. K., “Applying image processing technique to detect plant diseases”, International Journal of Modern Engineering Research, vol.2, Issue.5, pp: 3661-3664, 2012.

9.       P. Revathi, M. Hemalatha, “Classification of Cotton Leaf Spot Diseases Using Image Processing Edge Detection Techniques”, IEEE International Conference on Emerging Trends in Science, Engineering and Technology, pp-169-173, Tiruchirappalli, Tamilnadu, India, 2012.

10.    Tushar H. Jaware, Ravindra D. Badgujar and Prashant G. Patil, “Crop disease detection using image segmentation”, National Conference on Advances in Communication and Computing, World Journal of Science and Technology, pp:190-194, Dhule, Maharashtra, India, 2012.

11.    Prof. Sanjay B.Dhaygude, Mr.Nitin P. Kumbhar, “Agricultural plant Leaf Disease Detection Using Image Processing”, International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering , S & S Publication vol. 2, Issue 1, pp: 599-602, 2013.





Dipali Wankhede, S. G. Tuppad

Paper Title:

Improvising of web Recommendation System by using K-Means and Bitap Algorithm

Abstract: Increasing the amount of information over the Internet in recent years has led to the increased risk of flooding of information which in turn has created the problem of access to relevant data users. Also with the rise in the number of websites and web pages, webmasters find it difficult to make the content according to user need. Demand for information Users can imagine evaluating web user browsing behavior. Web Usage Mining (WUM) is used to extract knowledge from access logs Web user by using Data mining techniques. One of the applications is WUM recommendation system that is customized information filtering technique used to determine whether any of a user approved a particular article or to identify a list of items that it can be of great importance to the user. In this document architecture that integrates product information with the user access to log data and then generates a set of recommendations for it is presented that particular user. The application has registered encouraging in terms of precision, recall and F1 results metrics.

Web Usage mining, Online Web Recommendation System, Clustering, Pattern Matching, Boyer Moore, K-Means, Recommendation.


1.       Cormen, T.H., Leiserson, C.E., Rivest, R.L., Introduction to Algorithms, Chapter 34, MIT Press, 1990, pp 853-885.
2.       Knuth, D., Morris, J. H., Pratt, V., "Fast pattern matching in strings," SIAM Journal on Computing, Vol. 6, No. 2, doi: 10.1137/0206024, 1977, pp.323–350.

3.       R.S. Boyer, J.S. Moore, "A fast string searching algorithm, “Communication of the ACM, Vol. 20, No. 10,1977, pp.762– 772.

4.       R. N. Horspool, "Practical fast searching in strings," Software—Practice and Experience, Vol. 10, No. 3, 1980, 501–506.

5.       Sunday, D.M., "A very fast substring search algorithm," Communications of the ACM, Vol. 33, No. 8, 1990, pp. 132- 142.

6.       Smith, P.D., "Experiments with a very fast substring search algorithm," Software-Practice and Experience, Vol. 21, No. 10, pp.1065-1074.

7.       Crochemore, M., Czumaj, A., Gasieniec, L., Jarominek, S., Lecroq, T., Plandowski. W., Rytter, W., "Speeding up two string matching algorithms," Algorithmica, Vol. 12, No. 4/5, 1994, pp.247-267.

8.       RVVSV Prasad, V Valli Kumari “A Categorical Review of  Recommender Systems” , International Journal of  Distributed and Parallel Systems (IJDPS) Vol.3, No.5, September 2012 Hadi Khosravi Farsani, and Mohammadali Nematbakhsh “A Semantic Recommendation Procedure for Electronic Product Catalog”, World Academy of
Science, Engineering and Technology 22 2006.

9.       Neelam Duhan, A. K. Sharma and Komal Kumar Bhatia, “Page Ranking Algorithms: A survey”, in proceedings of the IEEE International Advanced Computing Conference (IACC), 2009.

10.    Balint Domolki, An algorithm for syntactical analysis, Computational Linguistics 3, Hungarian Academy of Science pp. 29–46, 1964.

11.    R. K. Shyamasundar, Precedence parsing using Domolki's algorithm, International Journal of Computer Mathematics, 6(2)pp 105–114, 1977.

12.    Udi Manber, Sun Wu. "Fast text searching with errors." Technical Report TR-91-11. Department of Computer Science, University of Arizona, Tucson, June 1991.

13.    R. Baeza-Yates and G. Navarro. A faster algorithm for approximate string matching. In Dan Hirchsberg and Gene Myers, editors, Combinatorial Pattern Matching (CPM'96), LNCS 1075, pages 1–23, Irvine, CA, June 1996.

14.    G. Myers. "A fast bit-vector algorithm for approximate string matching based on dynamic programming." Journal of the ACM 46 (3), May 1998, 395–415.

15.    Xavier Amatriain, Alejandro Jaimes, Nuria Oliver, and Josep M. Pujol, Data Mining Methods for Recommender Systems.

16.    R.Suguna, D, Sharmila, “Clustering Web log Files – A Review”, International Journal of Engineering Research & Technology (IJERT) Vol. 2 Issue 4, April – 2013 ISSN: 2278-0181]




Swagata S. Mawande, Hemlata Dakhore

Paper Title:

Review of Robust Video Watermarking Using DWT, SVD and DCT

Abstract: Due to increase in growth of internet, users of networks are increasing rapidly. Owners of the digital products are concerned about illegal copying of their products. Security and copyright protection are becoming important issues in multimedia applications and services. Digital watermarking is a technology used for copyright protection of digital media. Here ownership information data called watermark is embedded into the digital media without affecting its perceptual quality. In case of any dispute, the watermark data can be detected or extracted from the media and use as a proof of ownership. Digital video watermarking scheme based on Discrete Wavelet Transform and Singular Value Decomposition. Design of this scheme using Matlab is proposed. Embedded watermark is robust against various attacks that can be carried out on the watermarked video.

 Digital watermarking, Matlab, DWT,SVD,DCT


1.    Asna Furqan, Munish Kumar, Study and Analysis of Robust DWT-SVD Domain Based Digital Image Watermarking Technique Using MATLAB, 2015 IEEE International Conference on Computational Intelligence & Communication Technology © 2015 IEEE
2.    Madhuri Rajawat, D S Tomar, A Secure Watermarking and Tampering detection technique on RGB Image using 2 Level DWT 2015 Fifth International Conference on Communication Systems and Network Technologies, 2015 IEEE

3.    A.Umaamaheshvari, Dr.K.Thanushkodi, Robust Image Watermarking Based On Block Based Error Correction Code International Conference on Current Trends in Engineering and Technology, ICCTET’13

4.    Hemdan, N. El-Fishaw, G. Attiya and F. A. El-Samii, “Hybrid Digital Image Watermarking Technique for Data Hiding”, IEEE 30th National Radio Science Conference, (2013)

5.    Dattatherya, S. Venkata Chalam and Manoj Kumar Singh, “A Generalized Image Authentication based on Statistical Moments of Color Histogram," Int. J. on Recent Trends in Engineering and Technology,, Vol. 8, No-1, Jan. 2013

6.    Habibollah Danyali, Morteza Makhloghi, and Fardin Akhlagian Tab,“Robust Blind DWT based Digital Image Watermarking Using Singular Value Decomposition,” International Journal of Innovative Computing, Information and Control, Vol. 8, No.7, July 2012




Kanchan P. Borade, Shewale Pooja J, Tayade Dipika P

Paper Title:

“ATM Theft Monitoring and Security System using Raspberry Pi2”

Abstract: Automated Teller Machines (ATMs) security is the field of Study that gives a solution that provides multiple points of protections against theft .This project deals with prevention of ATM theft from robberies overcome the drawback found in existing technology in our society. ATM video surveillance cameras and ATM monitoring options, security specialists are ready to help the people get more out of the ATM security and ATM loss prevention systems. Most of the time it happens that theft enter in ATM, collect the money, start running police cannot capture theft so, to avoid such condition this project gives real time data of sensor, images of theft and mechanism of door and shutter lock. Here Raspberry pi2 is a series of small computer used, to interface the camera, vibration sensor, GSM, DC motor, Buzzer. There must be the installation of the raspbian operating system. The aim of using raspberry pi 2 is its ease of portability, ease of connections, and ease of handling. The setup is proposed for ATM security, comprising of the modules namely, authentication of shutter lock, web enabled control, sensors and camera control.

Raspberrypi2, Camera, Vibration Sensor,D Cmotar, GSM, Buzzer.


1.    Sivakumar, Gajjala Askok, k. Sai Venuprathap “Design and Implementation of  Security Based ATM theft  Monitoring system”. e- ISSN: 2278-7461, p-ISSN: 2319- 6491 Volume 3, Issue 1 (August 2013) PP: 01-07, ATM theft monitoring system with the help of LPC2148.
2.    S.P.Balwir, R.D.Thakare, K.R.Katole “Secured ATM transaction system”. Volume 4, Issued 4, April 2014, Transaction system is used.

3.    P.Kannan, Ms. P. Meenakshi vidya “Design and Implementation of Security Based ATM theft Monitoring system”. ISSN: 2320-0790, ATM theft monitoring system with the help of microcontrol00ler.

4.    R.Senthil Kumar, K.R.Sugavanam, D.Gajalakshmi “Novel vigilant real time monitoring and security system for ATM”. 10th September 2014. Vol. 67No.1© 2005 - 2014 JATIT & LLS, Real Time Monitoring and Security System for ATM Centre.

5.    Raj M M.E, Anita Julian “Design and Implementation of Anti-theft ATM Machine using Embedded Systems”. 2015 International Conference on Circuit, Power and Computing Technologies [ICCPCT], Embedded based ATM security system.




Srujana Rongali, Radhika Yalavarthi

Paper Title:

An Improved Ant Colony Optimization for Parameter Optimization using Support Vector Machine

Abstract:  Support Vector Machine (SVM) is one of the significant classification technique and it can be applied in various areas like meteorology, financial data analysis etc. The performance of SVM is influenced by parameters like C, which is cost constant and kernel parameter. In this paper, an improved Ant Colony Optimization (IACO) technique is proposed to optimize the parameters of SVM. To evaluate the proposed approach, the experiment adopts five benchmark datasets. The developed approach was compared with the ACO-SVM algorithm proposed by Zhang et al. The experimental results of the simulation show that performance of the proposed method is encouraging.

Support vector machines, Ant colony optimization, Parameter optimization


1.       Vapnik VN. The Nature of Statistical Learning Theory. New York, NY: Springer New York; 1995. doi:10.1007/978-1-4757-2440-0.
2.       Li X, Zheng A, Zhang X, Li C, Zhang L. Rolling element bearing fault detection using support vector machine with improved ant colony optimization. Measurement 2013;46:2726–34. doi:10.1016/j.measurement.2013.04.081.

3.       Samanta B, Al-Balushi KR, Al-Araimi SA. Artificial neural networks and support vector machines with genetic algorithm for bearing fault detection. Eng Appl Artif Intell 2003;16:657–65. doi:10.1016/j.engappai.2003.09.006.

4.       Hou S, Li Y. Short-term fault prediction based on support vector machines with parameter optimization by evolution strategy. Expert Syst Appl 2009;36:12383–91. doi:10.1016/j.eswa.2009.04.047.

5.       Wu Q, Law R, Wu E, Lin J. A hybrid-forecasting model reducing Gaussian noise based on the Gaussian support vector regression machine and chaotic particle swarm optimization. Inf Sci (Ny) 2013;238:96–110. doi:10.1016/j.ins.2013.02.017.

6.       Wu Q. A hybrid-forecasting model based on Gaussian support vector machine and chaotic particle swarm optimization. Expert Syst Appl 2010;37:2388–94. doi:10.1016/j.eswa.2009.07.057.

7.       Liu S, Tai H, Ding Q, Li D, Xu L, Wei Y. A hybrid approach of support vector regression with genetic algorithm optimization for aquaculture water quality prediction. Math Comput Model 2013;58:458–65. doi:10.1016/j.mcm.2011.11.021.

8.       Wu CH, Tzeng GH, Goo YJ, Fang WC. A real-valued genetic algorithm to optimize the parameters of support vector machine for predicting bankruptcy. Expert Syst Appl 2007;32:397–408. doi:10.1016/j.eswa.2005.12.008.

9.       Patil SG, Mandal S, Hegde A V. Genetic algorithm based support vector machine regression in predicting wave transmission of horizontally interlaced multi-layer moored floating pipe breakwater. Adv Eng Softw 2012;45:203–12. doi:10.1016/j.advengsoft.2011.09.026.

10.    Chen F, Tang B, Chen R. A novel fault diagnosis model for gearbox based on wavelet support vector machine with immune genetic algorithm. Meas J Int Meas Confed 2013;46:220–32. doi:10.1016/j.measurement.2012.06.009.

11.    Lin S-W, Lee Z-J, Chen S-C, Tseng T-Y. Parameter determination of support vector machine and feature selection using simulated annealing approach. Appl Soft Comput 2008;8:1505–12. doi:10.1016/j.asoc.2007.10.012.

12.    Huang CL, Wang CJ. A GA-based feature selection and parameters optimizationfor support vector machines. Expert Syst Appl 2006;31:231–40. doi:10.1016/j.eswa.2005.09.024.

13.    Aydin I, Karakose M, Akin E. A multi-objective artificial immune algorithm for parameter optimization in support vector machine. Appl Soft Comput 2011;11:120–9. doi:10.1016/j.asoc.2009.11.003.

14.    Zhao H, Yin S. Geomechanical parameters identification by particle swarm optimization and support vector machine. Appl Math Model 2009;33:3997–4012. doi:10.1016/j.apm.2009.01.011.

15.    Eitrich T, Lang B. Efficient optimization of support vector machine learning parameters for unbalanced datasets. J Comput Appl Math 2006;196:425–36. doi:10.1016/

16.    Wang Z, Shao YH, Wu TR. A GA-based model selection for smooth twin parametric-margin support vector machine. Pattern Recognit 2013;46:2267–77. doi:10.1016/j.patcog.2013.01.023.

17.    Zhao M, Fu C, Ji L, Tang K, Zhou M. Feature selection and parameter optimization for support vector machines: A new approach based on genetic algorithm with feature chromosomes. Expert Syst Appl 2011;38:5197–204. doi:10.1016/j.eswa.2010.10.041.

18.    Reif M, Shafait F, Dengel A. Meta-learning for evolutionary parameter optimization of classifiers. Mach Learn 2012;87:357–80. doi:10.1007/s10994-012-5286-7.

19.    Zhang Q, Shan G, Duan X, Zhang Z. Parameters optimization of Support Vector Machine based on Simulated Annealing and Genetic Algorithm. 2009 IEEE Int Conf Robot Biomimetics 2009:1302–6. doi:10.1109/ROBIO.2009.5420717.

20.    Adankon MM, Cheriet M. Genetic algorithm-based training for semi-supervised SVM. Neural Comput Appl 2010;19:1197–206. doi:10.1007/s00521-010-0358-8.

21.    Boardman M, Trappenberg T. A Heuristic for Free Parameter Optimization with Support Vector Machines. 2006 IEEE Int Jt Conf Neural Netw Proc 2006:1337–44. doi:10.1109/IJCNN.2006.246739.

22.    Yu Q, Zhang B, Wang J. Parameter Optimization of ϵ-Support Vector Machine by Genetic Algorithm. 2009 Fifth Int Conf Nat Comput 2009:540–2. doi:10.1109/ICNC.2009.628.

23.    Huaitie X, Guoyu F, Zhiyong S, Jianjun C. Hybrid Optimization Method for Parameter Selection of Support Vector Machine. 2010 IEEE Int Conf Intell Comput Intell Syst 2010;1:613–6. doi:10.1109/ICICISYS.2010.5658455.

24.    Lin S-W, Ying K-C, Chen S-C, Lee Z-J. Particle swarm optimization for parameter determination and feature selection of support vector machines. Expert Syst Appl 2008;35:1817–24. doi:10.1016/j.eswa.2007.08.088.

25.    Zhang XL, Chen XF, He ZJ. An ACO-based algorithm for parameter optimization of support vector machines. Expert Syst Appl 2010;37:6618–28. doi:10.1016/j.eswa.2010.03.067.

26.    Alwan HB, Ku-Mahamud KR. Optimizing Support Vector Machine Parameters Using Continuous Ant Colony Optimization. Proc 7th Int Conf Comput Converg Technol 2012:164–9.

27.    Zhang XL, Chen XF, Zhang ZS, He ZJ. A Grid-based ACO Algorithm for Parameters Optimization in Support Vector Machines. IEEE Int Conf Granul Comput 2008 GrC 2008 2008:805–8. doi:10.1109/GRC.2008.4664645.

28.    Vapnik VN. An overview of statistical learning theory. IEEE Trans Neural Netw 1999;10:988–99. doi:10.1109/72.788640.

29.    Cristianini N, Shawe-Taylor J. An Introduction to Support Vector Machines and Other Kernel-based Learning Methods. 1st ed. Cambridge: Cambridge University Press; 2000.

30.    Jiawei H, Kamber M. Data mining: concepts and techniques. 2006. doi:10.1007/978-3-642-19721-5.

31.    Duan K, Keerthi S, Poo A. Evaluation of simple performance measures for tuning SVM hyper parameters. Neurocomputing 2003;51:41–59.

32.    Imbault F, Lebart K. A Stochastic Optimization Approach for Parameter Tuning of Support Vector Machines. Proc 17th Int Conf Pattern Recognition, 2004ICPR 2004 2004;4:597–600. doi:10.1109/ICPR.2004.1333843.

33.    Chapelle O, Vapnik V, Bousquet O, Mukherjee S. Choosing Multiple Parameters for Support Vector Machines. Mach Learn 2002;46:131–59. doi:10.1023/ A:1012450327387.




Sonali Kadam, Rutuja Pawar, Shweta Phule, Priyansha Kher, Manisha Kumari

Paper Title:

Ensemble of Classifiers for Intrusion Detection System

Abstract:   The continuous growth in Network attacks is being a serious problem in software industry. Intrusion detection framework is utilized to distinguish and break down system assaults so IDS should be upgraded that can screen the framework and can trigger the readiness in the framework. Numerous calculations have been proposed by various creators to enhance the execution of IDS yet at the same time they can't give appropriate or finish arrangement. In proposed framework creators perform probes distinctive blends of Bayesian system, Naïve Bayes, JRip, MLP, IBK, PART and J48 classifier. What's more for each mix two pre-processing procedures Normalization and discretization will be connected. The advantage of proposed approach is the combi-nation detecting majority attacks will be ensemble with the re-spective pre-processing technique. Hence, any kind attack in the network can be detected with best accuracy.

Bayesian network, Intrusion Detection System, IBK. JRip, J48, MLP, Naïve bayes, PART.


1.    V. D. Katkar , S. V. Kulkarni, "Experiments on detection of Denial of Service attacks using ensemble of classifiers, Green Computing, Communication and Conservation of Energy (ICGCE), 2013 International Conference on, Chennai, 2013, pp. 837-842.
2.    S. Choudhury, A. Bhowal, "Comparative analysis of machine learning algorithms along with classifiers for network intrusion  detection," Smart Technologies and Management for Computing, Communication, Controls, Energy and Materials (ICSTM), 2015 International Conference on, Chennai,2015, pp. 89-95.

3.    P. Sornsuwit ,  S. Jaiyen, "Intrusion detection model based en-semble learning for U2R and R2L attacks," 2015 7th International Conference on Information Technology and Electrical Engineering (ICITEE), Chiang Mai, 2015, pp. 354-359.

4.    K. Elekar, M. M. Waghmare and A. Priyadarshi, "Use of rule base data mining algorithm for intrusion detection," Pervasive Computing (ICPC), 2015 International Conference on, Pune, 2015, pp. 1-5.

5.    T. Garg , S. S. Khurana, "Comparison of classification techniques for intrusion detection dataset using WEKA," Recent Advances and Innovations in Engineering (ICRAIE), 2014, Jaipur, 2014, pp. 1-5.

6.    H. Chauhan, V. Kumar and S. Pundir and E. S. Pilli, "A Comparative Study of Classification Techniques for Intrusion Detection ," Computational and Business Intelligence (ISCBI), 2013 International Symposium on, New Delhi, 2013, pp. 40-43.

7.    P. Amudha, S. Karthik and S. Sivakumari, "Intrusion detection based on Core Vector Machine and ensemble classification methods", 2015 International Conference on Soft-Computing and Networks Security (ICSNS), 2015.

8.    G. Nadiammai , M. Hemalatha, "Effective approach toward Intrusion Detection System using data mining   techniques”, Egyptian Informat-ics Journal, vol. 15, no. 1, pp. 37-50, 2014.

9.    F. Nia , M. Khalili, "An efficient modelling algorithm for intrusion detection systems using C5.0 and Bayesian Network  struc-tures", 2015 2nd International Conference of Knowledge-Based Engineering and Innovations (KBEI).




Ahmed F. AlHallaq, Bassam A. Tayeh, Samir Shihada

Paper Title:

Investigation of the Bond Strength Between Existing Concrete Substrate and UHPC as a Repair Material

Abstract: The performance of any repaired concrete structure, depends on the quality of the interfacial transition zone of the composite system formed by the repair material and the existing concrete substrate. The main aim of this paper is to evaluate the bonding behavior between normal strength concrete (NSC) substrate as an old concrete and Ultra High Performance Concrete (UHPC) as a repair material. In order to assess the bond behavior, standard slant shear test and splitting tensile test were carried out. The relation between surface roughness and bond strength in shear and indirect tension for different surfaces roughness has been assessed. The old concrete surfaces were roughened by mechanical wire brush, scarifying using an electrical grinder, scabbling by a mechanical drill and as cast without roughening. Analysis of the results indicates that bond strength increases when UHPC is used for shear and tension alike. For the scabbling technique, the shear strength yields values 251.8% higher than the those for as cast  surface and 153% for tension strength. In addition, UHPC show advantages that qualify it for repairing and strengthening techniques including adding a new concrete to the existing concrete substrate. In general, rough surface preparation leads to a higher bond strength. Ra coefficient is a representative parameter and related to the bond strength, particularly, for shear strength. Finally, the results showed that tension strength is less sensitive to the surface roughness level and more proportional to the repair material strength.

Bond strength; Concrete overlay; Old concrete;  Slant shear test; Splitting test; Silica fume; Substrate; Surface roughness; Ultra High Performance Concrete,


1.       Mather, B. and J. Warner. Why do Concrete Repairs Fail? Interview held at University of Wisconsin, Madison Engineering Professional Development, MD, WI,<>. 2003  Jan., 2012].
2.       Rahman, A., et al., State-of-the-art review of interface bond testing devices for pavement layers: toward the standardization procedure. Journal of adhesion science and technology, 2016: p. 1-18.

3.       Sanchez-Silva, M., G.-A. Klutke, and D.V. Rosowsky, Life-cycle performance of structures subject to multiple deterioration mechanisms. Structural Safety, 2011. 33(3): p. 206-217.

4.       Espeche, A.D. and J. León, Estimation of bond strength envelopes for old-to-new concrete interfaces based on a cylinder splitting test. Construction and Building Materials, 2011. 25(3): p. 1222-1235.

5.       Ramge, P. and H.C. Khne, Investigations on the performance of concrete repair mortars in composite specimen tests., in International Conference on Concrete Repair, Rehabilitation and Retrofitting III (ICCRRR 2012), 02-05 September 2012. 2012: Cape Town, South Africa. p. 1046-1052.

6.       Júlio, E., et al., Accuracy of design code expressions for estimating longitudinal shear strength of strengthening concrete overlays. Engineering Structures, 2010. 32(8): p. 2387-2393.

7.       Gorst, N. and L. Clark, Effects of thaumasite on bond strength of reinforcement in concrete. Cement and Concrete Composites, 2003. 25(8): p. 1089-1094.

8.       Santos, P.M.D. and E.N.B.S. Julio, Factors Affecting Bond between New and Old Concrete. ACI Materials Journal, 2011. 108(4): p. 449.

9.       Kuebitz, K., Repairing and retrofitting prestressed concrete water tanks in the  San Francisco Bay area. , in International Conference on Concrete Repair, Rehabilitation and Retrofitting III (ICCRRR 2012), 02-05 September 2012. 2012: Cape Town, South Africa.

10.    Austin, S., P. Robins, and Y. Pan, Tensile bond testing of concrete repairs. Materials and structures, 1995. 28(5): p. 249-259.

11.    Bissonnette, B., et al., Concrete repair and interfacial bond: Influence of surface preparation, in International Conference on Concrete Repair, Rehabilitation and Retrofitting II (ICCRRR 2009), 24-26 November 2009. 2009: Cape Town, South Africa. p. 345-350.

12.    Tayeh, B.A., et al., Mechanical and permeability properties of the interface between normal concrete substrate and ultra high performance fiber concrete overlay. Construction and Building Materials, 2012. 36: p. 538-548.

13.    Owayda, Y., Strengthening and Repair of RC Beams with Cemintitions Repair Materials. 2013, Master Thesis, Islamic University in Gaza.

14.    ASTM-C150/C150M, Standard Specification for Portland Cement, in American Society for Testing and Materials, West Conshohocken, PA 55555, United States. 2009.

15.    ASTM-C1240, Standard Specification for Use of Silica Fume as a Mineral Admixture in Hydraulic Cement Concrete, Mortar, and Grout., in American Society for Testing and Materials, West Conshohocken, PA 19428-2959. 2000.

16.    ASTM-C882, Standard Test Method for Bond Strength of Epoxy-Resin Systems Used with Concrete by Slant Shear, in American Society for Testing and Materials,
West Conshohocken, PA 19428-2959, United States. 1999.

17.    ASTM-C496, Standard Test Method for Splitting Tensile Strength of Cylindrical Concrete., in American Society for Testing and Materials, West Conshohocken, PA 19428-2959, United States. 1996.

18.    Mummery, L., Surface texture analysis: the handbook. 2000: Hommelwerke.

19.    Tayeh, B.A., et al., The role of silica fume in the adhesion of concrete restoration systems  Advanced Materials Research, 2013. 626: p. 265-269.

20.    Tayeh, B.A., et al., The Relationship between Substrate Roughness Parameters and Bond Strength of Ultra High- Performance Fiber Concrete. Journal of Adhesion Science and Technology, 2012.

21.    Mohammadi, M., R. Moghtadaei, and N. Samani, Influence of silica fume and metakaolin with two different types of interfacial adhesives on the bond strength of repaired concrete. Construction and Building Materials, 2014. 51: p. 141-150.

22.    Mohammed, A.N., et al., Improving the engineering and fluid transport properties of ultra-high strength concrete utilizing ultrafine palm oil fuel ash. Journal of Advanced Concrete Technology, 2014. 12(4): p. 127-137.

23.    Grigoriadis, K., Use of laser interferometry for measuring concrete substrate roughness in patch repairs. Automation in Construction, 2016. 64: p. 27-35.

24.    Tayeh, B.A., et al., Existing concrete textures: their effect on adhesion with fibre concrete overlay. Proceedings of the Institution of Civil Engineers-Structures and
Buildings, 2014. 167(6): p. 355-368.

25.    Tayeh, B.A., B. Abu Bakar, and M.M. Johari. Mechanical properties of old concrete–UHPFC interface. in Concrete Repair, Rehabilitation and Retrofitting III: 3rd International Conference on Concrete Repair, Rehabilitation and Retrofitting, ICCRRR-3, 3-5 September 2012, Cape Town, South Africa. 2012: CRC Press.

26.    Perez, F., B. Bissonnette, and R. Gagné, Parameters affecting the debonding risk of bonded overlays used on reinforced concrete slab subjected to flexural loading. Materials and structures, 2009. 42(5): p. 645-662.

27.    Abu-Tair, A., S. Rigden, and E. Burley, Testing the bond between repair materials and concrete substrate. ACI Materials Journal, 1996. 93(6).





K. Bikshalu, Prathap Soma

Paper Title:

Design and Simulation of 16 Bit Arithmetic Unit using Gating Techniques in Cadence 45nm Technology

Abstract:  In any system ALU is the most important part of a processor as it is required for calculating the address of each memory location. It performs a particular arithmetic and logic operations on each set of operands, based upon the instructions given by the processor. In some processors ALU is split into two units, an Arithmetic unit (AU) and logic unit (LU). Some processors possess a couple of Arithmetic units – one for the fixed point operations and another for the floating point operations. As AU operates at a very high speed and it is accessed by the system frequently, it contributes to one of the highest power-density locations on the processor. Because of this reason, there exist thermal hotspots and sharp temperature gradients inside the execution core, thereby reducing the reliability as well as the battery life of the system. Therefore, there is a great need for the development of a power optimized AU design. This encourages powerfully for the design of a power optimized AU that satisfies the superior needs along with the reduction of average power consumption. This paper presents the various power optimized techniques for 16bit ALU like input gating, power gating in 45nm using cadence. Finally, comparison among all proposed techniques are represented.

 Arithmetic unit (AU), Power gating, Input Gating.


1.       P. Kalyani, dr. P. Satishkumar, dr. K. Ragini-“various low power techniques for cmos circuits”, p. Kalyani et al int. Journal of engineering research and applications, issn: 2248-9622, vol. 3, issue 6, nov-dec 2013, pp.330-333.
2.       akhila abba, k amarender” improved power gating technique for leakage power reduction” international journal of engineering and science vol.4, issue 10 (october2014), pp 06-10.

3.       “adder subtractor design” islamic university of gaza, faculty of engineering department of computer engineering fall 2011 ecom 4113: digital design lab eng. Ahmed abumarasa

4.       pramod kumar. M.p, a. S. Augustine fletcher” a survey on leakage power reduction techniques by using power gating methodology” international journal of engineering trends and technology (ijett) – volume 9 number 11- mar 2014.

5.       ping huang, zuocheng xing, tianran wang, qiang wei, hongyan wang, guitao fu” a brief survey on power gating design” school of computer, national university of defense technology, changsha 410073, china.

6.       Sreenivasa rao n, y. Vishnuvardhan reddy, g.shivamanikanta, b. Vijaysree “design the 2x1 mux with 2t logic and comparing the power dissipation and area with different logics” international journal of advanced research in electrical, electronics and instrumentation engineering vol. 4, issue 3, march 2015.

7.       dursun baran, mustafa aktan and vojin g. Oklobdzija,” multiplier structures for low power applications in deep-cmos”, ieee international symposium on circuits and
systems (iscas), 2011

8.       sumit r. Vaidya, d.r. Dandekar,”delay-power performance comparison of multipliers in vlsi circuit design”, ijcnc, vol. 2,no. 4,pp. 47-56,july 2010.

9.       p.v. Rao, cyril prassana raj p, s. Ravi,“vlsi design and analysis of multipliers for low power”,ieee 2009 fifth international conference on intelligence information hiding and multipedia signal processing, pp. 1354-1357,2009.

10.    Suhwan kim, stephen v. Kosonocky, and daniel r. Knebel,“understanding and minimizing ground bounce during mode                transition of power gating structures,” proceedings of the ieeeinternational symposium on low power electronics and design (islped), pp.22 – 25, 25-27 aug. 2003.

11.    Harmander singh, kanak agarwal, dennis sylvester, and kevin j.nowka, “enhanced leakage reduction techniques using intermediate strength power gating,” ieee trans. On very large scale integration (vlsi) systems, vol. 15, no. 11, pp.12-15, november 2007.

12.    Ashoka. Sathanur, benini.l, macii.a, macii.e and poncino.m, “row-based power gating: a novel sleep transistor insertion methodologyfor leakage power optimization in nanometre cmos circuits,” ieeetrans. Vlsi syst., vol. 19, no.3, pp. 469–482, 2011.

13.    Kanak agarwal, harmander deogun , dennis sylvester and kevin nowka, “power gating with multiple sleep modes,” ieee proceedings of the international symposium on quality electronic design (isqed), pp 633-637, 27-29 march 2006.

14.    Pramod kumar.m.p and a.s.augustine fletcher, “a novel hybrid multiple mode power gating,” ieee international conference on electronics and communication system (icecs’14), feb.13-14, 2014.

15.    Prvinkumar g. Parate, prafulla s. Patil, dr (mrs) s. Subbaraman “asic implementation of 4 bit multipliers”,ieee first international conference on emerging trends in engineering and technology, pp. 408-413,2008

16.    T. Esther rani, m. Asha rani, dr. Rameshwar rao, area optimized low power arithmetic and logic unit”978-1-4244-8679-3/11/$26.00 ©2011 IEEE.





Loubna Berrich, Lahbib Zenkouar

Paper Title:

The Adaptation of a Microstrip Dipole Antenna for RFID Applications

Abstract: Radio frequency identification (Radio Frequency Identification) is a technology used primarily to identify tagged objects or to track their locations. An RFID tag is composed of integrated circuit. To design the antennas, it is necessary that the antenna must have an impedance value equal to the conjugate of the impedance of the IC to have a good adaptation allowing the maximum transfer of power. For the implementation of the impedance matching, there are several techniques. In this work, we are interested in the technique of adaptation T-match and the technique of adaptation by coupling. The T-match technique is based on the insertion of a second folded dipole at the center of the first dipole. This technique is modeled by an equivalent circuit to be able to calculate the dimension of the folded dipole to have a new input impedance of the antenna equal to the conjugate of the impedance of the integrated circuit. The second technique is based on the supply of the dipole via a small loop with inductive coupling placed in close proximity to the radiating body. The software used in this work is the Ansoft HFSS software which is based on the finite element method (FEM). The results obtained are satisfactory with a reflection coefficient that exceeds -22 dB.

Microruban Dipole Antenna, RFID, Tag.


1.    H.Stockman, ‘’ Communication by Means of Reflected Power’’, Proceeding of the IRE, October 1948 , pp.1196-1204.

3.    J.Landt, ''The History of RFID'',  IEEE Potentials , vol 24 (4), 2005, pp.8-11.

4.    al, N. &, ''Radiation Propreties od Microstrip Dipole'', IEEE Transactions on Antenna and Propagation ,  vol Ap-43 (3), , 1979,  pp.853-858.

5.    G.Marrocco, ''The Art of UHF RFID Antenna Design: Impedance Matching ande size reduction technique'', IEEE Antenna and Propagation Magazine ,  vol 50 (1), 2008, pp.66-79.



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