Abstract: Ionic liquids, as green solvents have been studied widely now a days due to their appealing properties such as negligible vapour pressure, large liquid range, high thermal stability, high ionic conductivity, large electrochemical window, and ability to solvate compounds of widely varying polarity. Utilizing ionic liquids is one of the goals of green chemistry because they create a cleaner and more sustainable chemistry and are receiving increasing interest as environmental friendly solvents for many synthetic and catalytic processes. Ionic liquids have been investigated for a wide range of synthetic applications; they have fascinated considerable interest for used as non-volatile solvent based electrolytes in the field of organic synthesis, catalysis, electrochemistry, solar cells, fuel cells, etc., as they possess many benefits than volatile organic solvents.
Keywords: Green chemistry, applications, classification, ionic liquids, properties.
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Abstract: Bayesian networks tend to be increasingly used for the management of uncertainty in modelling of the learner. They have been successfully used in many systems, with different objectives. However their use as part of the cognitive process modelling raises a number of problems. On the one hand the underlying semantics of arcs is often not clearly explained, and on the other hand the evolution of the knowledge structure is not taken into account. Our work focuses on the question of the orientation of the arcs, and more generally on the structure of Bayesian network modeling of the learner. We try to show in this work how this question is crucial. In addition, the issue of structural adjustment in the network behavior of the learner sometimes had been suggested, and while different results from cognitive psychology attests to the existence of structural differences by level of expertise. The central hypothesis of our work is that has been a link between the structure of the learner model and level of expertise. We present our probabilistic graphical models of multi- networks to take into account several networks within the same model. The experiments presented in this work are arguments in favor of our hypothesis on the link between the level of expertise of the learner and the structure of Bayesian network.
Keywords: Bayesians Networks, cognitive diagnosis, Learner modeling.
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Abstract: The aim of this work is to study some properties related to fuzzy soft topological spaces particularly fuzzy soft boundary point, fuzzy soft compact space, fuzzy soft open base and fuzzy soft open sub-base.
Keywords: Fuzzy soft set, fuzzy soft topological space, fuzzy soft interior, fuzzy soft closure, fuzzy soft boundary point,fuzzy soft neighborhood, fuzzy soft compact space, fuzzy soft open base, fuzzy soft open subbase, fuzzy soft basic open cover, fuzzy soft sub basic cover fuzzy soft closed base, fuzzy soft closed subbase.
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