Abstract-With the expansion of Internet and technology over the past decade, E-learning has grown exponentially day by day. Cheating in exams has been a widespread phenomenon all over the world regardless of the levels of development. Therefore, detection of traditional cheating methods may no longer be wholly successful to fully prevent cheating during examinations. Online examination is an integral and vital component of E-learning. Students' exams in E-learning are remotely submitted without any monitoring from physical proctors. As a result of being able to easily cheat during e-exams, E-learning universities depend on an examination process in which students take a face-to-face examination in a physical place allocated at the institution premises under supervised conditions, however this conflicts with the concept of distant Elearning environment. This paper will investigate the methods used by student for cheating detection in online exams, through continuous authentication and online proctors. In addition, we have implemented an E-exam management system, which is used to detect and prevent the cheating in online exams. The system used fingerprint reader authenticator and eye tribe tracker in exam session. We researched two parameters that can define the examinee status as cheating or non-cheating during exam. Through these two parameters: the total time on out screen and the number of times on out screen were computed.

Scholarly interest in the field of m-payment has gained prominence in the last decade owing to the shift in consumer spending patterns. However, only limited numbers of review studies are available on the topic. To overcome the limitation, the paper comprehensively reviewed the content of existing literature available on m-payment to improve understanding of the current state of knowledge. The present research paper reviews peer-reviewed literature available in the Scopus database for the period 2005-2020. A systematic literature search using the Scopus database was undertaken resulting in a total of 56 studies published in 44 peerreviewed International journals. The present study reviews the publication trend in the field of m-payment, influential articles and most prolific and influential authors. Thereafter, a bibliometric analysis using VOS Viewer was carried out to identify thematic clusters. Construction of the network map using bibliographic coupling and co-citation analysis reveals interesting patterns and themes in the field of m-payment. Our study provides a better understanding of the field of m-payment and based on the results future avenues were proposed. Abdullah ABOUT THE AUTHOR Abdullah is presently enrolled as a Full time Doctoral Candidate with the Faculty of

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This study presents the development of the STFT-based fatigue data editing technique that will be used as a tool to accelerate for accelerating fatigue testing. This technique was performed by removing low amplitude cycles contained in the original signal in order to produce a shortened signal using the Short-Time Fourier Transform (STFT) parameter. The effectiveness of STFT power spectrum was validated using an SAE random fatigue data in order to indicate the relationship between STFT parameter and fatigue damage. The data was separated into two segments, i.e., damage and nondamage segments based on the 100% retention of the original fatigue damage. For the editing process, the STFT power spectrum distribution was used as the parameter to identify the damaged segment according to the power spectrum Cut-Off Level (COL). The low amplitude cycles with power spectrum lower than COL value were then removed from the original signal. Thus, a new edited signal was obtained which has retained almost 100% of the original fatigue damage and has equivalent signal statistic. The edited signal was found to be approximately 84% of the time duration of the original signal.