Abstract-Mobile learning management systems are very important for training purpose. But considering the present scenario, the learners are equipped with a number of mobile devices that run by different operating systems with diverse device features. Therefore, developing a mobile application for different platforms is a cumbersome task if appropriate tools and techniques are not practiced. There are three categories of mobile application namely native, web based and hybrid. For mobile learning system, hybrid is an appropriate choice. In order to avoid re-implementation of the same hybrid application for different platform separately, several tools are proposed for example: PhoneGap, Adobe Air, Sencha Touch and QT, each with their own strength. With proper use of the strength of individual framework or the combination of frameworks, more compatible and more stable, cross-platform mobile learning application specifically for quizzes and assignments can be developed.

This paper deals with the necessary steps to be followed in upgrading the traditional e-Learning system to the new Adaptive e-Learning system. The framework, which is an important part of the implementation, is also covered in the paper. Before implementing the adaptive learning system, the existing system needs to be reviewed. A survey was conducted to find practical feedback from both the users: students and instructors to recognize their belief about the current e-Learning system. Results are discussed to frame the strategy to implement an adaptive learning system in which the issues of the current system can be addressed. To confirm the feedback, a report from the university LMS has also been taken into account and talked about. There are many open sources available in the market for the implementation of the adaptive e-learning. Along with the conceptual model, various popular LMS has also been discussed. A detailed comparison has also been exercised to identify their features. This paper can help the readers to derive all the components of a conceptual model for an adaptive e-Learning system and choose a suitable LMS for the actual implementation of the model.

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This paper is concerned with the problem of the robust stability of fractional-order memristive bidirectional associative memory (BAM) neural networks. Based on Lyapunov theory, fractional-order differential inequalities and linear matrix inequalities (LMI) are applied to obtain a robust asymptotical stability. Finally, numerical examples are presented.