The emergence of wireless technologies has facilitated immense opportunities for optimal and efficient communication system. WSN is an effective communication technique which has expanded the application space ranging from public utilities, industrial monitoring and control, and defense and military operations. In general, WSN plays a significant role in wireless communication tool, and it has a great potential to serve as the next generation communication technology and for the future ubiquitous network. Such robustness have widened the usability of WSNs into various major applications and as such the technological development is expanding rapidly across the scientific horizon.

In Wireless Sensor Networks (WSN), energy efficiency is a fundamental issue that requires attention in the design of communication protocols. Energy waste occurs as a result of collision and idle listening. The widely used mechanism for energy saving in WSN is duty cycling. Duty cycling coordinates the sleep/wake-up time of sensor nodes to maximize the network lifetime while achieving specific application goals such as high throughput or low latency. Most existing works focused more on static duty cycle, which cannot guarantee the desired end-to-end delay at varying network conditions. In applications with specified delay requirements, the duty cycle of every node should be adjusted separately at runtime depending on the network conditions to achieve the desired delay and energy efficiency. In this paper, we present an Energy Efficient and QoS-aware (EEQ) MAC protocol with a duty cycle scheme that adapts the node's duty cycle to the queue size and priority class of a packet to reduce the delay of high priority packets and support timebounded delivery of priority packets. By checking the queue size and the priority class of packets in the message queue of each node, the node determines whether or not to adjust its duty cycle. In this approach, a node increases the length of its active period in the event of high traffic which provides less waiting time for the packets in the queue. The sender node informs the receiver the duration for which it has to stay awake at the beginning of data transmission, both the sending and the receiver's duty cycle is controlled based on the queue length and the priority of the packets. This approach saves energy and lessen packet latency. Finally, extensive simulation experiments were conducted to evaluate its energy performance within different network topologies. Comparisons with the existing energy-aware MAC protocol verified the effect of EEQ on improving the energy efficiency and extending the lifespan of WSNs.

Authentication is a way to enable an individual to be uniquely identified usually based on passwords and personal identification number (PIN). The main problems of such authentication techniques are the unwillingness of the users to remember long and challenging combinations of numbers, letters, and symbols that can be lost, forged, stolen, or forgotten. In this paper, we investigate the current advances in the use of behavioral-based biometrics for user authentication. The application of behavioral-based biometric authentication basically contains three major modules, namely, data capture, feature extraction, and classifier. This application is focusing on extracting the behavioral features related to the user and using these features for authentication measure. The objective is to determine the classifier techniques that mostly are used for data analysis during authentication process. From the comparison, we anticipate to discover the gap for improving the performance of behavioral-based biometric authentication. Additionally, we highlight the set of classifier techniques that are best performing for behavioral-based biometric authentication.

Nowadays, people are turning to the internet to search for information and are completing their work using web systems or mobile applications as their medium. This study was conducted to determine the relationship between web systems and end-user effectiveness and performance. This study collected information using primary data, with a population of 200 students from University Sultan Zainal Abidin (UniSZA) in the Faculty of Informatics and Computing. According to Krejcie and Morgan's 1970 table, the sample size is 132. By using SPSS software, the Pearson Correlation formula tests the input. Based on the testing data, the effectiveness of the user using a web based system is 0.633, whereas the effectiveness of using a mobile application is 0.973. In conclusion, there is a moderate relationship between using web systems and the effectiveness of the end-user. Furthermore, there is a strong relationship between using mobile applications and the effectiveness of the end-user. This study recommends that future researchers and the developers of web systems or mobile applications should design better and more suitable questionnaires to achieve excellent results. Developers need to be aware of the relationship between web systems and mobile applications and their end-users so that they can improve their systems and applications.

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