Application of Computer Remote Video Technology in Network Assisted Art Innovation by Computer Artificial Intelligence

In response to the needs of the teaching of art majors in colleges and universities today, this paper constructs a “based on campus network art major’s hybrid auxiliary teaching innovation platform system”. The system uses a perfect campus network to establish a secure network-assisted teaching platform system that integrates B/S structure and advanced ASP. NET technology with multi-level users. The platform provides a complete network-assisted teaching environment and realizes the integration and sharing of teaching resources in the largest range. Practical application shows that the highly operable courses of art majors in colleges and universities can stimulate students’ initiative and improve students’ learning ability under the application of this mode.

The Design of English Personalized Teaching Platform in Campus Network Based on Big Data

With the emergence of technologies such as cloud computing, the Internet of Things(IOT), and educational big data (BD), personalized teaching (PT) has got more technical support. This article aims to explore how to apply emerging technologies to the teaching process, help teachers to carry out PT, stimulate students’ interest in learning, meet students’ individual needs, and break through traditional teaching methods. Through examining and collating a large number of literatures such as education BD and English PT platform, this paper analyses the status quo and needs, and builds a platform based on BD on this basis. The personalized English teaching platform in the campus network is used in practical teaching, and the effect of this platform in practical teaching is tested by comparative analysis. The results show that the English PT platform has realized PT well, enhanced the pertinence and initiative of students’ learning, and improved students’ comprehensive ability.

Campus Network and Systems Security Assessment Using Penetration Testing: The Case of the University of Education Winneba, Kumasi

Network intruders are becoming more sophisticated in their approach, resulting in many difficulties in preventing them. They exploit both well-configured systems and vulnerable systems. Aims: To examines the performance of a campus network against attacks on the network systems. Place and Duration of Study: University of Education, Winneba- Kumasi campus. Methodology: Penetration testing was adopted to investigate the vulnerabilities that may occur in a university network. This helps to test for vulnerabilities on the network system that may expose the system to exploits. Results: The test revealed that system-based attacks might be propelled by malignant pariahs on the Internet and noxious insiders straightforwardly associated with inward systems. The perpetrators can exploit vulnerabilities in network foundations and frameworks, for example, servers (web servers, software servers, file and mail servers, etc.), routers, and firewalls. Conclusion: This work presents a way to deal with evaluating the security stance of a college utilizing penetration testing that meddles negligibly with the flow of traffic and activities on the network infrastructure. attack Insurance against network-based attacks is mind-boggling and, in the offer, to relieving one framework normally gives a stage that can be utilized to dispatch more attacks.

Empirical Bayesian network to improve service delivery and performance dependability on a campus network

An effective systemic approach to task will lead to efficient communication and resource sharing within a network. This has become imperative as it aids alternative delivery. With communication properly etched into the fabrics of today’s society via effective integration of informatics and communication technology, the constant upgrades to existing network infrastructure are only a start to meeting with the ever-increasing challenges. There are various criteria responsible for network performance, scalability, and resilience. To ensure best practices, we analyze the network and select parameters required to improve performance irrespective of bottlenecks, potentials, and expansion capabilities of the network infrastructure. Study compute feats via Bayesian network design alongside upgrades implementation to result in a prototype design, capable of addressing users need(s). Thus, to ensure functionality, the experimental network uses known simulation kits such as riverbed modeler edition 17.5 and cisco packet tracer 6.0.1-to conduct standardized tests such as throughput test, application response-time test, and availability test.