An Energy-Efficient Scheme for IoT Networks

With the advent of the Internet of Things era, "things-things interconnection" has become a new concept, that is, through the informatization and networking of the physical world, the traditionally separated physical world and the information world are interconnected and integrated. Different from the concept of connecting people in the information world in the Internet, the Internet of Things extends its tentacles to all aspects of the physical world. The proposed algorithm considers the periodical uplink data transmission in IEEE 802.11ah LWPAN and a real-time raw settings method is used. The uplink channel resources were divided into Beacon periods after the multiple nodes send data to the access point. First, the access point predicted the next data uploading time during the Beacon period. In the next Beacon period, the total number of devices that will upload data is predicted. Then, the optimal read-and-write parameters were calculated for minimum energy cost and broadcasted such information to all nodes. After this, the data is uploaded according the read-and-write scheduling by all the devices. Simulation results show that the proposed algorithm effectively improved the network state prediction accuracy and dynamically adjusted the configuration parameters which results in improved network energy efficiency in the IoT environment

Assessing Information Quality of Blackboard System

This paper reports on how a positivist research paradigm was conducted with the aim to assess the information quality of the Blackboard system. It outlines the application of the IS-Impact Measurement Model for the purpose of testing the variables for the construct of “Information Quality.” The investigation in this paper is a part of a research project aiming to measure the success of the Blackboard system adopted in a higher education institute. Data for this investigation are gathered from students in Saudi Electronic University in the Kingdom of Saudi Arabia. This paper explores the factors related to information quality affecting the success of the use of the Blackboard system. It concludes by confirming that information quality positively affects the use of the Blackboard system.

The Effects of Website Quality on Adoption of E-Government Service: An Empirical Study Applying UTAUT Model Using SEM

In today’s global age, e government services have become the main channel for online communication between the government and its citizens. They aim to provide citizens with more accessible, accurate, real time and high quality services. Therefore, the quality of government websites which provide e services is an essential factor in the successful adoption of e government services by the public. This paper discusses an investigation of the effect of the Website Quality (WQ) factor on the acceptance of using e government services (G2C) in the Kingdom of Saudi Arabia (KSA) by adopting the Unified Theory of Acceptance and Use of Technology (UTAUT) Model. Survey Data collected from 400 respondents were examined using the structural equation modelling (SEM) technique and utilising AMOS tools. This study found that the factors that significantly influenced the Use Behaviour of e government services in KSA (USE) include Performance Expectancy (PE), Effort expectancy (EE), Facilitating Conditions (FC) and Website Quality (WQ), while the construct known Social Influence (SI) did not. Moreover, the results confirm the importance of quality government websites and support systems as one of the main significant and influential factors of e government services adoption. The results of this study can be helpful to Saudi’s governmental sectors to adjust their corporate strategies and plans to advance successful adoption and diffusion of e government services (G2C) in KSA

The effects of website quality on adoption of e-government service : an empirical study applying UTAUT model using SEM

In today&rsquo;s global age, e-government services have become the main channel for online communication between the government and its citizens. They aim to provide citizens with more accessible, accurate, real-time and high quality services. Therefore, the quality of government websites which provide e-services is an essential factor in the successful adoption of e-government services by the public. This paper discusses an investigation of the effect of the Website Quality (WQ) factor on the acceptance of using e-government services (G2C) in the Kingdom of Saudi Arabia (KSA) by adopting the Unified Theory of Acceptance and Use of Technology (UTAUT) Model. Survey Data collected from 400 respondents were examined using the structural equation modelling (SEM) technique and utilising AMOS tools. This study found that the factors that significantly influenced the Use Behaviour of e-government services in KSA (USE) include Performance Expectancy (PE), Effort expectancy (EE), Facilitating Conditions (FC) and Website Quality (WQ), while the construct known Social Influence (SI) did not. Moreover, the results confirm the importance of quality government websites and support systems as one of the main significant and influential factors of e-government services adoption. The results of this study can be helpful to Saudi&rsquo;s governmental sectors to adjust their corporate strategies and plans to advance successful adoption and diffusion of e-government services (G2C) in KSA.<br /

Qualitative Study on Implementing Biometric Technology in M-Government Security: a Grounded Theory Approach

This paper reports on how qualitative research was conducted with the aim to find out factors for the implementation of biometric authentication in m-government security. It outlines the application of grounded theory methodology for the purpose of developing a substantive theory towards implementation of security in this developing area. The investigation in this paper is a part of ongoing PhD research. Data for this investigation includes users', service providers', and network operators' concerns and perceptions regarding the application of biometric authentication into mobile devices for government services in the Kingdom of Saudi Arabia. This paper justifies the use of grounded theory in this study and discusses the analysis process. It concludes by presenting the emerging categories with their relationships that stemmed from the theory generation process which specify the factors influencing the successful implementation of biometric authentication in m-government security.Griffith Sciences, School of Information and Communication TechnologyFull Tex

Standard Measuring of E-Learning to Assess the Quality Level of E-Learning Outcomes: Saudi Electronic University Case Study

Education in multiple forms and diverse geographical contexts delivers quality in all aspects of learning in which stakeholders such as students, instructors, and educational institutions play an important role. Quality assurance in higher education ensures the smooth functioning of the teaching and learning process by supporting the attainment of the desired quality levels of learning outcomes. This further leads to educational sustainability, as education has been acknowledged as a strategic constituent of sustainability-focused strategies in many educational contexts. Hence, it has become very important for educational institutions to maintain quality standards through the implementation of appropriate strategies, as quality is the lifeline of both Traditional Learning and E-Learning, and a lack of a suitable assessment standard affects the quality of learning. This research study attempts to address the existing gaps observed following a review of the related literature. This study collected qualitative data using an observation method through the observations and review of online software used at the Saudi Electronic University, namely Blackboard Learning Management System (LMS), Tawkeed Quality Management E-System, and Blue Survey software. In addition to this, the expertise of the research team members was also utilized for this research study in designing E-Learning quality dimensions. The purpose of this study was to propose an E-Learning Quality Assessment Standard that will help third-level educational institutions to assess their current teaching and learning practices of E-Learning and support them in enhancing the overall students’ experiences toward E-Learning within their institutions. As a research outcome, a conceptual quality assessment standard titled “SPECIFIERS” was proposed to offer a helping hand during the E-Learning quality assessment process to ensure sustainable education development of global educational institutions

Students' perceptions of social networks platforms use in higher education: a qualitative research

The use of social networks platforms for interactions, cooperative learning, and knowledge sharing for sharing information to improve students’ educational achievement seems to be one of the more widely examined topics in the Information Systems (IS) domain compared to the adoption of other technologies. However, as social networks platforms use distracts from studies and affects study habits, using social networks platforms can result in academic difficulties. Therefore, this research seeks to identify the interaction elements such as interaction with peers, cooperative learning and engagement for sharing information and perceptual elements such as perceived usefulness and perceived ease of use social networks platforms to improve educational achievement among students. This study is designed in accordance with the theory of constructivism. Qualitative research was applied to interviews conducted with a sample of 37 students. Data were analyzed using SPSS Statistics 20, and NVivo 11 was used for qualitative coding to investigate relationships between variables. The study found that interactions among students and interactions with lecturers enhance learning significantly. Additionally, the perceived overall benefits of using media platforms for learning and knowledge sharing that enhances satisfaction and affects educational achievement were high. Furthermore, the impact of social networks platforms use for education and knowledge sharing was also significant. Finally, the results indicate that students are satisfied with the use of media platforms as a means of learning and knowledge sharing. Findings show that using social networks platforms for learning and knowledge sharing should positively affected educational achievement of students

Detecting Coronary Artery Disease from Computed Tomography Images Using a Deep Learning Technique

In recent times, coronary artery disease (CAD) has become one of the leading causes of morbidity and mortality across the globe. Diagnosing the presence and severity of CAD in individuals is essential for choosing the best course of treatment. Presently, computed tomography (CT) provides high spatial resolution images of the heart and coronary arteries in a short period. On the other hand, there are many challenges in analyzing cardiac CT scans for signs of CAD. Research studies apply machine learning (ML) for high accuracy and consistent performance to overcome the limitations. It allows excellent visualization of the coronary arteries with high spatial resolution. Convolutional neural networks (CNN) are widely applied in medical image processing to identify diseases. However, there is a demand for efficient feature extraction to enhance the performance of ML techniques. The feature extraction process is one of the factors in improving ML techniques&rsquo; efficiency. Thus, the study intends to develop a method to detect CAD from CT angiography images. It proposes a feature extraction method and a CNN model for detecting the CAD in minimum time with optimal accuracy. Two datasets are utilized to evaluate the performance of the proposed model. The present work is unique in applying a feature extraction model with CNN for CAD detection. The experimental analysis shows that the proposed method achieves 99.2% and 98.73% prediction accuracy, with F1 scores of 98.95 and 98.82 for benchmark datasets. In addition, the outcome suggests that the proposed CNN model achieves the area under the receiver operating characteristic and precision-recall curve of 0.92 and 0.96, 0.91 and 0.90 for datasets 1 and 2, respectively. The findings highlight that the performance of the proposed feature extraction and CNN model is superior to the existing models