Abstract-Advancement of digital technology is influencing the leaping development of various activities in our daily life. E-Learning system has also gained a competitive edge over the prevailing traditional methodology. The prevailing pedagogy is being replaced by the E-Learning teaching system. ELearning teaching-learning methodology provides more flexibility and allows freedom from time, place, physical presence, hectic, and stressful teachinglearning etc., thus plays a vital role in education system. However, there are many barriers in E-Learning methodology for successful teaching-learning. Study on such barriers will help to overcome the difficulties to the success of ELearning. Present research paper attempts to study the various barriers that are affecting the successful implementation of E-Learning in Saudi Arabian Universities. This study reviews various barriers from literatures and identified most important E-Learning barriers which are described and grouped in four dimensions such as Student, Instructor, Infrastructure and Technology, and Institutional Management. Sixteen barriers falling under these relevant dimensions were validated their importance quantitatively through university Students, Instructors, and E-Learning staffs of some well know universities in Saudi Arabia. A survey instrument was developed and tested on a sample of 257 respondents of Saudi Arabian Universities. It was found that Infrastructure and Technology Dimension is the most significant as perceived by respondents. Re- 94

Cloud computing has been regarded as one of the significant Information Technology (IT) tools. Many sectors are adopting cloud computing services for its business support. It has also become a new IT paradigm that has transformed the E-Learning system to become more user-friendly. As a result, the E-Learning usage is growing rapidly and being preferred over the conventional teaching-learning process in a big way. This revolutionary change is attributed to the advancement in digital technology. The transformation in digital technology has made the teaching-learning process flexible, easy and convenient for effective knowledge transfer. The cloud-based E-Learning process depends upon many factors of different dimensions that are of significant importance for cloud-based-E-Learning success. Hence they must be studied to successfully analyze their level of importance and fulfill Cloud-based E-Learning positive effectiveness. The current research provides a detailed literature review for cloud-based E-Learning Critical Success Factors (CSFs) of teaching-learning process. Further, the research employs the combinatorial approach to evaluate the diversified dimensions and CSFs of cloud-based E-Learning that helps in quantifying and comparing the influence of various dimensions and CSFs of cloud-based-E-Learning. Four dimensions and fourteen factors have been identified through in-depth literature review and later on evaluated for the prioritization using a combinatorial approach. The influence of such dimensions and factors will help various stakeholders to plan their strategy and resources for the betterment of knowledge transfer through cloud-based-E-Learning.INDEX TERMS Analytic hierarchy process (AHP), cloud-based E-learning, combinatorial approach, critical success factors (CSFs), Fuzzy AHP, cloud-based E-learning, group decision making (GDM).

No abstract

In today’s era of technology, especially in the Internet commerce and banking, the transactions done by the Mastercards have been increasing rapidly. The card becomes the highly useable equipment for Internet shopping. Such demanding and inflation rate causes a considerable damage and enhancement in fraud cases also. It is very much necessary to stop the fraud transactions because it impacts on financial conditions over time the anomaly detection is having some important application to detect the fraud detection. A novel framework which integrates Spark with a deep learning approach is proposed in this work. This work also implements different machine learning techniques for detection of fraudulent like random forest, SVM, logistic regression, decision tree, and KNN. Comparative analysis is done by using various parameters. More than 96% accuracy was obtained for both training and testing datasets. The existing system like Cardwatch, web service-based fraud detection, needs labelled data for both genuine and fraudulent transactions. New frauds cannot be found in these existing techniques. The dataset which is used contains transaction made by credit cards in September 2013 by cardholders of Europe. The dataset contains the transactions occurred in 2 days, in which there are 492 fraud transactions out of 284,807 which is 0.172% of all transaction.

Abstract-ElectronicLearning (E-Learning) in the education system has become the obvious choice of the community over the globe because of its numerous advantages. The main aim of the present study is to identify Critical Success Factors (CSFs) and validate them for successful implementation of the E-Leaning at Saudi Arabian Universities. This study developed a multidimensional instrument for measuring the E-Learning CSFs in the higher educational institutions of Saudi Arabia. The study reviewed various CSFs from literature and identified most important E-Learning CSFs which are described and grouped in five dimensions such as Student, Instructor, Design and Contents, System and Technological, and Institutional Management Services. The 36 CSFs falling under these relevant dimensions were then validated their importance quantitatively through university Students, Instructors, and E-Learning staffs of some well-known universities in Saudi Arabia. A survey instrument was developed and tested on a sample of 257 respondents of Saudi Arabia Universities. It was found that System and Technological dimension is the most significant as perceived by respondents. Results of the study discovered that all obtained factors are highly reliable and thus would be useful to develop and implement E-Learning systems.

Deep learning (DL) and machine learning (ML) have a pivotal role in logistic supply chain management and smart manufacturing with proven records. The ability to handle large complex data with minimal human intervention made DL and ML a success in the healthcare systems. In the present healthcare system, the implementation of ML and DL is extensive to achieve a higher quality of service and quality of health to patients, doctors, and healthcare professionals. ML and DL were found to be effective in disease diagnosis, acute disease detection, image analysis, drug discovery, drug delivery, and smart health monitoring. This work presents a state-of-the-art review on the recent advancements in ML and DL and their implementation in the healthcare systems for achieving multi-objective goals. A total of 10 papers have been thoroughly reviewed that presented novel works of ML and DL integration in the healthcare system for achieving various targets. This will help to create reference data that can be useful for future implementation of ML and DL in other sectors of healthcare system.

No abstract

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.