In recent years, smart governance in the context of smart city networks has emerged as a new trend for governments to monitor public activities. One of such activities is controlling the traffic lights that have a vital influence on strategic planning in shaping the smart cities. Thus, in this study, our contributions presented in a twofold as (i) solving the problems of using conventional traffic lights as well as reviewing the opportunities and challenges of the traffic sensing techniques, and (ii) innovating a novel model for traffic sensing and smart traffic monitoring called Smart Traffic Sensing Approach (STSA). In particular, regarding the STSA model, we proposed new traffic sensing model using ultrasonic-acoustic and biosensors, in intelligent ecosystem environments involving LED solar cells, for controlling the intensity of cars on the intersections of roads in non-stable situations due to their high accuracy in guided sensors and their modern characteristic in independency on a dynamic time period. Consequently, this technology reduces energy consumption, solves the problem of congestions, and increases productivity and flow on intersections in a more adaptive mode. In addition, it exploits the ecosystems to facilitate monitoring the mobile phone violations on the city’s roads and highways. As a result, the STSA approach is being served as a next-generation framework for computing in smart traffic, having an effect on smart cities infrastructure planning, and achieves sustainable development chances.

Digital electrocardiogram (ECG) analysis acts as a crucial role in the clinical ECG; it is associated with high prevalence, high mortality rates, and sustained healthcare costs. The most popular ECG data and the robust deep learning algorithm made it possible to enhance the precision and scalability of electronic ECG interpretation. Still, there is no thorough evaluation of an end-to-end deep learning method used in ECG analysis. In this work, we extend a deep neural network (DNN) to classify rhythm classes using 91,232 single lead ECGs from 53,549 patients who used a single-lead ambulatory ECG monitoring device. We classify eight rhythm classes using single-lead ECGs from 53,549 patients who used a single-lead ambulatory ECG monitoring device. When validated against an independent test dataset annotated by a consensus committee of board-certified practicing cardiologists, the potential of applying Deep Neural Network (DNN) approaches to the automatic prediction of arrhythmia has been largely overlooked thus far. This study addresses this important gap by presenting a DNN model that accurately identifies arrhythmia depending on one raw electrocardiogram (ECG) heartbeat only, also collate prevailing algorithms based on Heart Rate divergence. We trained and tested the model using ECG datasets, comprising 380000 heartbeats, to achieve 100% arrhythmia prediction accuracy. Notably, the model also identifies those heartbeat sequences and ECG's morphological characteristics, which are classdiscriminative and thus prominent for arrhythmia prediction. Overall, our contribution substantially advances the current methodology for predicting arrhythmia and caters to clinical practitioners' needs by providing an accurate and fully transparent tool to support arrhythmia prediction decisions.

Covid-19 pandemic affects our life suddenly and dramatically. The most affected area was our teaching methods. Students and teachers move to distance learning without good experience and background especially for non-IT teachers.In this paper, we will discuss the opportunity to enhance distance learning and how to make it more effective, easier, and more enjoyable by activating Augmented Reality (AR) in the education field.Recently, AR has been used in various contexts to enhance our experience in mobile and wearable devices. This paper discusses the use of AR in the field of education where it has been observed that learning results have been improved. This type of application required specialized teams of software to create and maintain it and we will explain the benefits and limitations of using AR in distance learning. Using AR in education will provide powerful paradigms for the next generation advanced learning system.

Students motivation and engagement difficulties are present in higher education. Between many technologies to increase student motivation and engagement, we found that Gamification technique is the most suitable case. This paper presents our experiment of using Gamification in learning process and based on the use of the Agile methodology in-order to obtain the best results and engagements from the students. Applying Gamification in software engineering is not as straight to move as it may appear. Current research in the area has already recognized the possible use of Gamification in the context of software development. It is still an open area of research about how to design and use Gamification in this context. Higher education universities, especially in the Middle East are sometimes facing problems to get students engagement and motivation as a group structure. This paper supports the proposed idea; we presented a preliminary experiment that shows the effect of gamification on the performance of students involvement in a funded project from TRC (The Research Council) in Sultanate of Oman.

The purpose of this article is to focus on the potential of using new technologies such as Augmented Reality and Virtual Reality in science education in general and in STEM education in particular. Although Augmented Reality and Virtual Reality as a technology have strength and weaknesses, this article focus to show how those technologies may facilitate STEM education and how to improve the area of weaknesses. In this research, we address the need for STEM education and training, which is currently either limited or not interested for students. It is also overcome the distance limitation that students face in STEM education. Furthermore, Augmented Reality and Virtual Reality environments are an effective platform to encourage and attracting the new generation technology to STEM field. Technology virtualization has been used in a various way in STEM classroom to encourage creatively and innovation. However, it is also important to take in our consideration that students learning in this environment can be difficult in many directions.

This paper presents the design of an intelligent energy efficient algorithm which is based on Swarm Intelligence to increase the life time of swarmed Robots. This algorithm represents a further advancing stage to our previous work which was devoted to cluster Wireless Sensor Networks (WSNs) into independent clusters. Our Algorithm presented in this research is mainly designed to keep the optimum distribution of clustered mobile Robots while those Robots are directed as a swarm to achieve a given goal. The algorithm presented in this research is suitable for large scale mobile Robots and provides a robust and energy- efficient communication mechanism. We are using the Particle Swarm Optimization (PSO) technique to decrease the energy consumption for the entire swarms. One of the main strengths in the presented algorithm is that the number of clusters within the swarm of Robots is not predefined, this gives more flexibility for the Robots' deployment in the swarm. Another strength is that the number of Robots assigned within each swarm is not necessary to be uniformly distributed as in other swarms, since in some applications constraints, the sensing Robots need to be deployed in different densities depending on the nature of the application.

This paper discusses the new opportunity for improving the quality of teaching and learning methods by using new trends of educational technology. Those new tends are delivering materials not based on the availability of teacher or lecturer. Educational technologies currently focus on dealing with electronic learning (E-Learning) and mobile learning (M-Learning) as a useful educational tool. Many studies start to give big attention on the next step in Virtual and Augmented Reality as a useful tool for education, training, simulation ... etc. Due the increase of using mobile devices as a part of teaching methods, Mobile Augmented Reality are used as an exemplify the potentials for education process. This paper expects to encourage educators and learners to join the innovations in the educating and learning process. The mix of these technologies in the teaching and learning process can give new learning condition and enhance the educating and learning quality. The learning procedure ends up noticeably pleasant and intriguing with advances. In spite of the fact that innovation has a ton of advantage to the instruction field, instructors must be imaginative and creative to execute innovation in the educating and learning process. Therefore, educators and learners need to choose the suitable innovation as per the lesson educated. The main goal for this paper is to assist teachers to be motivated appreciate by adding new technologies in their teaching method by selecting a suitable technology based on teaching requirements and materials.

In recent years, Sultanate of Oman has formed an innovative approaches and initiatives to promote entrepreneurship education at national level. Many of the private and public sectors take this initiative through research, curriculum development, educators' trainings, and collaboration with non-governmental organization (NGOs). Various pilot projects were implemented in order to promote entrepreneurship education among youth, university students, graduates and unemployed citizens. The government encourages its citizens to participate equally in this initiative to further help the progress of economic development in the country. In academic level, the role of Oman's higher education institutions is to undergo a fundamental change in order to encourage, support, and educate young entrepreneurs and technopreneurs of the future. These approaches are all aligned to the Sultanate's Vision Oman 2020 Economic Development Plan. The main purpose of this study is to propose a concept and model to strengthen the implementation of technopreneurship in higher education institutions in the Sultanate of Oman that are beyond the traditional domain of interdisciplinary technology. In addition, the model will serve as the role player of each university's centre to spread out relevant information about technopreneur development and commercializing technology between higher education institutions and the industry.

Computer systems security plays a critical role in ensuring the confidentiality, integrity and data protection of electronic resources in a workplace. However, most web information system developers employ algorithms which are inefficient and unsecured. Therefore, organizations adopt security measures that utilize strong encryption and decryption techniques to protect confidential corporate data that reside and are communicated over the Cloud. The purpose of this research is to analyze and compare the performance of selected algorithms namely: AES (Rijndael), Blowfish and RSA. The results show that Blowfish manifested a higher time efficiency ratio when subjected to various data loads and memory size as compared to AES and RSA.

This paper describes a case study of how Agent Oriented Agile Based (AOAB) development methodology was implemented in mobile computing module to create game as a part of the module assessment requirements. Games can be used in higher education in many ways to increase students participation, enable variation in how lectures are taught and to increase students interest when they create their own game. We provide a new game development methodology and integrated with mobile computing module. The experience described in this paper is based on the feedback from the module staff member, students feedback, final student report and finally module evaluation report by students. The evaluation shows that the students who used AOAB methodology provide a better result rather than groups who used Agile game development methodology in game creation. Finally, we describe the benefit of using game in higher education and how we could enhance students progress in their study.

Game development is very complex and the success of the game is based on the game development methods. The purpose of this paper is to investigate on the existing game development methods and provide an upcoming game development method that is based on predictive and adaptive development models. A critical analysis to Agile method which are mostly used in modern game development methods is presented. We identified the weakness of Agile game development and solve it by creating a cooperation with Agent Oriented Software Engineering (AOSE) to introduce a new hybrid methodology named as Agent Agile Game Development Methodology (AAGDM) that combines both predictive and adaptive models.

In general the evaluation phase serves as a catalyst in software development and particularly within games development. Hence, it plays a vital role in the formulation of an effective a game development methodology. This paper has investigated the evaluation phase and has focused on the provision of general heuristics sets to facilitate the evaluation process. A generic evaluation framework has been defined as an output of this paper which could be used in the majority of game genres, and therefore it can be an important part of generic game development methodology. Furthermore, this evaluation process has been repeated in each iteration of the game development methodology. The results from each iteration should be compared with previous iteration to enhance and improve games before the final game release.

Over the last decade, many methodologies for developing agent based systems have been developed, however no complete evaluation frameworks have been provided. Agent Oriented Software Engineering (AOSE) methodologies enhance the ability of software engineering to develop complex applications such as games; whilst it can be difficult for researchers to select an AOSE methodology suitable for a specific application. In this paper a new framework for evaluating different types of AOSE, such as qualitative and quantitative evaluations will be introduced. The framework assists researchers to select a preferable AOSE which could be used in a game development methodology. Furthermore the results from this evaluation framework can be used to determine the existing gaps in each methodology.

Many Artificial Intelligence (AI) techniques used in the new generation of games. This paper presents the most popular techniques such as finite state machine, fuzzy logic, neural networks, genetic algorithms, agent and machine learning. It explains the most important AI requirement criterion needs to appear in games and how AI techniques could be used with different type of games.