Government website services comprise awareness programs for their citizens and others, information distribution, and perhaps data collection, online enquiries, and submissions for regulatory or funding purposes. Quality of service is fundamental to public acceptance and use of e-government websites, although this aspect is frequently overlooked during the design and implementation stages of online public services. Besides transparency, ease of navigation and comprehensive information, these websites require adequate monitoring resources, including targets for responses and reports. The intention of this study is to contribute to the development of e-government services, and to raise awareness of user attitudes to public websites among researchers, government administrators and service providers, especially in the context of Saudi Arabia. This study explores dimensions that contribute to e-government service quality, or have the capacity to detract from website support. A qualitative approach through individual interviews was taken that explored four categories of service quality: the system function category included ease of use, and system availability; and the content category included three dimensions: format, information, and personalization. Further, the procedural category comprised privacy and security, credibility, interactivity, and processing time; the citizen support category included responsiveness and contact dimensions. Development of an appropriate quantitative model and instrument is planned to facilitate research into the relationships among the e-government service quality dimensions and user satisfaction and user trust. Further, it is planned to research various environments and contexts to provide cross-cultural comparisons to understand e-government's user behaviors.

Developing a computer based system for examinations are the substitute for the current examination system based on paper. In recent days, the e-learning has become more popular because of its adaptability, integrity and user friendliness. In terms of the paper based examinations, major challenge is the proctoring techniques used. In this paper, a novel method to avoid the presence of a proctor throughout the examination is proposed by an intelligent based examination system. This method is proposed to improve the e-learning using intelligent question bank and examination system. The system is designed with different complexity levels among the questions and also it acts as a tool to assessing the understanding of student from the teaching materials. This system can be timesaving and more efficient with an adequate level of security. The proposed methodology can be classified in to two main phases such as the design of question bank along with its database, design of the Artificial Intelligence (AI) based system for examination and its evaluation in order to improve the e-learning. Future works in this system can be the addition of theory-based questions and the integration of biometric based systems for enhancing the level of security.

No abstract

No abstract

In this paper, a new optimization algorithm called motion-encoded electric charged particles optimization (ECPO-ME) is developed to find moving targets using unmanned aerial vehicles (UAV). The algorithm is based on the combination of the ECPO (i.e., the base algorithm) with the ME mechanism. This study is directly applicable to a real-world scenario, for instance the movement of a misplaced animal can be detected and subsequently its location can be transmitted to its caretaker. Using Bayesian theory, finding the location of a moving target is formulated as an optimization problem wherein the objective function is to maximize the probability of detecting the target. In the proposed ECPO-ME algorithm, the search trajectory is encoded as a series of UAV motion paths. These paths evolve in each iteration of the ECPO-ME algorithm. The performance of the algorithm is tested for six different scenarios with different characteristics. A statistical analysis is carried out to compare the results obtained from ECPO-ME with other well-known metaheuristics, widely used for benchmarking studies. The results found show that the ECPO-ME has great potential in finding moving targets, since it outperforms the base algorithm (i.e., ECPO) by as much as 2.16%, 5.26%, 7.17%, 14.72%, 0.79% and 3.38% for the investigated scenarios, respectively.

Companies continually seek efficiency by utilizing the rapid advances in technology to improve their electronic services (e-services). A perusal of the literature shows varying approaches for measuring e-service quality; these approaches have found little consent among reviewers. Therefore, this study attempts to provide a new framework, a roadmap, as a useful model for researchers to measure user perception of e-service quality. For this model, an extensive study is carried and these study findings indicate that system functionality, procedure, content, user support, and manageability should be included in an empirical research model for measuring e-service quality.

The localization of the nodes in wireless sensor networks is essential in establishing effective communication among different devices connected, within the Internet of Things. This paper proposes a novel method to accurately determine the position and distance of the wireless sensors linked in a local network. The method utilizes the signal strength received at the target node to identify its location in the localized grid system. The Most Valuable Player Algorithm is used to solve the localization problem. Initially, the algorithm is implemented on four test cases with a varying number of sensor nodes to display its robustness under different network occupancies. Afterward, the study is extended to incorporate actual readings from both indoor and outdoor environments. The results display higher accuracy in the localization of unknown sensor nodes than previously reported.

Abstract-CloudComputing is becoming an important tool for improving productivity, efficiency and cost reduction. Hence, the advantages and potential benefits of cloud computing are no longer possible to be ignored by organizations. However, organizations must evaluate factors that influence their decisions before deciding to adopt cloud computing technologies. Many studies have investigated cloud computing adoption in developed countries compared with few studies that have concentrated on examining the factors that influence cloud computing adoption in developing countries. It is not clear to see whether these factors that have been identified by these studies, can be applied in developing countries. The motive of this study is to contribute to the adoption of cloud computing, and to elevate the consciousness of cloud computing technology amongst authorities, researchers, administrators, business enterprise managers and service carriers, particularly within the Saudi Arabian context. This study explores factors that encourage the implementation of cloud or have the capacity to detract from adopting cloud computing in private and public organizations in Saudi Arabia. A qualitative approach through IT professional representatives' interviews was adopted in this study, which explored two categories, namely, a) the negative impact category which includes: security and privacy, government policy, lack of knowledge, and Loss of control; and b) the positive impact category which includes three factors: reduce expenses, improve IT performance, and promote scalability and flexibility.