The technological revolutions greatly impact current and future Classrooms. These advances in technology include the revolution of artificial intelligence, virtual reality, and super highspeed internet. In the coming next generation (6G), the data rate will be very sufficient for live scenes in virtual reality applications such as telepresence and teleoperation. This paper review and discuss next-generation technologies in AI, VR, and communication. Moreover, we examine the motivation for establishing an Advanced Technology based Smart and Immersive Classroom (SIC) and the advantages of its availability to the virtual society. Recent advances in computer and communications technology have delivered capabilities to tomorrow’s SIC. Advances in virtual reality and real-time streaming on the internet have created a revolution in curricula and classrooms. Index Terms—Virtual Reality in education; 6G for education, Artificial Intelligence in education, Immersive Classroom

Efficiently identifying and resolving code smells enhances software project quality. This paper presents a novel solution, utilizing automated machine learning (AutoML) techniques, to detect code smells and apply move method refactoring. By evaluating code metrics before and after refactoring, we assessed its impact on coupling, complexity, and cohesion. Key contributions of this research include a unique dataset for code smell classification and the development of models using AutoGluon for optimal performance. Furthermore, the study identifies the top 20 influential features in classifying feature envy, a well-known code smell, stemming from excessive reliance on external classes. We also explored how move method refactoring addresses feature envy, revealing reduced coupling and complexity, and improved cohesion, ultimately enhancing code quality. In summary, this research offers an empirical, data-driven approach, integrating AutoML and move method refactoring to optimize software project quality. Insights gained shed light on the benefits of refactoring on code quality and the significance of specific features in detecting feature envy. Future research can expand to explore additional refactoring techniques and a broader range of code metrics, advancing software engineering practices and standards.

Nowadays, Cloud computing became one of the most important fields in computer paradigm researches, because it provides many advantages and benefits for all users whether the organizations or the individuals, by granting them the needed resources and services. Service level agreement (SLA) is an essential topic in terms of cloud computing, it is a contractual agreement signed between cloud user and cloud provider in order to manage and define the level of access for the resources and quality of services provided. Continues changes of technologies and requirements for both user and provider make updating SLA necessary, to ensure that services provided are meeting their needs among multiple QoS (Quality of Service) parameters. Intensive studies have been presented for building a flexible SLA. In our study, we proposed a dynamic model for updating cloud computing SLA overtime, in order to get a flexible, adaptive SLA and avoid costly violations.