Visual Analysis of College Sports Performance Based on Multimodal Knowledge Graph Optimization Neural Network

In this paper, through data analysis of multimodal knowledge graph optimized neural network and visual analysis of college students’ sports performance, we use huge graph, a graph database supporting distributed storage, to store domain knowledge in the form of the knowledge graph, use Spring Boot to build a server-side framework, use Vue framework combined with vis.js to visualize relational network graphs, and design and implement a knowledge-oriented. This paper proposes a visual analytics system based on the theory of visual analytics. Based on the idea of visual analytics, this paper presents a visual analytics framework combining predictive models. This framework combines the automated analysis capability of predictive models with interactive visualization as a new idea to explore the visual analysis of student behavior and performance changes. Using relevant predictive algorithms in machine learning, corresponding models are built to refine the importance of features for visual analysis and correlate behavioral data with achievement data. In this process, multiple prediction algorithms are used to build prediction models. The model effects are analyzed and compared to select the optimal model for use in the visual analytics framework. The graphical analytic view is integrated. EduRedar, an optical analytical system for sports data based on the performance prediction model, is designed and implemented to support multidimensional and multiangle data analysis and visualize the changes in college students’ sports and performance based on accurate campus exercise data.

Crime reporting and police controlling: Mobile and web-based approach for information-sharing in Iraq

Crimes are increasing in our society as a serious worldwide issue. Fast reporting of crimes is a significantly important area in anticrime. This problem is visible in Iraq as people avoid information-sharing due to the lack of trust in the security system despite some contact lines between citizens and police in Iraq. Furthermore, there has been a little empirical study in this field. We proposed a multi-approach for crime reporting and police control to address these issues. First, this study has two goals: (1) investigating the adopted method in reporting crimes to police sectors to identify the gap and, (2) developing a mobile application for crime reporting and keeping it undisclosed and exclusive for crime witnesses to report. The approach utilised 200 participants to develop the proposed app. Results have shown that the proposed system can quickly monitor and track criminals based on a cloud-based online database. In addition, the application user will specify certain details to be sent, such as location, case type and time. Other information will be sent directly by the system following the designed algorithm.