This study proposes an improved YOLOv9-based helmet wearing detection algorithm for non-motor vehicle riders, aiming to solve the problems of low accuracy and high missed detection rate under high-density and complex riding scenarios.Firstly, the Slide Loss loss function was incorporated into YOLOv9 to enhance the model's detection performance on small targets and occluded objects. Secondly, Depthwise Separable Convolution (DSConv) modules were introduced into the backbone network, reducing the model's parameter count. Lastly, a DASI small target detection module was added to the model's Head network, improving the detection capability for small targets. Compared to the YOLOv9 algorithm, the improved algorithm achieved increases of 2.3% in Precision, 1.9% in Recall, and 2.8% in mean Average Precision, while the parameter count was reduced by 9.1% compared to the original model, enabling high-precision detection of non-motor vehicle helmet wearing.

With the rapid advancement of artificial intelligence, while enhancing the efficiency of university network security, it has also spawned new types of attacks, leading to a triple contradiction of technological gaps, fragmented management, and ethical conflicts. This paper proposes a "smart perception-dynamic decision-making-hierarchical execution" trinity defense system: the perception layer achieves unsupervised anomaly detection through multi-source data collection and deep clustering; the decision layer generates adaptive strategies with second-level responses based on Markov processes and reinforcement learning; the execution layer employs priority queues to balance security and operational continuity. Experiments demonstrate an anomaly detection accuracy of 94.6%, a decision response time of 1.2 seconds, an execution accuracy of 98.9%, and successful sensitive data desensitization, providing an intelligent foundation for university network security.

Aiming at the problem of large time delay in temperature control of industrial process, the control principle and mathematical model of predictive PI control algorithm are studied. Laplace inverse transform and differential separation method are adopted to obtain the mathematical model of predictive PI controller incremental discrete control algorithm in the time domain. The PLC program of predictive PI control algorithm is designed and written, and the controller algorithm program packaged with FB function block is tested. Simulation experiments show that the control quality of temperature control system with large time delay can be effectively improved, and it has good reliability and robustness.

In response to the existing issues in the construction of ideological and political education in professional courses in higher education institutions today, this paper proposes a design scheme for an intelligent planning assistant for professional course ideological and political education construction based on the COZE platform. This professional course ideological and political education planning assistant, through user input of information such as the school's educational positioning and professional training programs, can reasonably and accurately generate professional construction objectives, ideological and political education construction objectives for courses, and implementation paths and evaluation schemes for these objectives. Research results show that the professional course ideological and political education planning assistant can effectively improve the efficiency and quality of ideological and political education construction in courses, providing a new approach and method for ideological and political education construction in professional courses in higher education institutions.

With the promotion of the "Healthy China 2030" strategy, the large health industry puts forward higher requirements for the knowledge structure and ability of food professionals. Based on the analysis of the characteristics of talent needs in the big health food industry and the limitations of the existing food professional curriculum system, the paper puts forward some ideas for the reform of food professional talent training mode to adapt to the development of the big health industry. The paper proposes a path for optimizing the curriculum system, "interdisciplinary integration, practical ability strengthening, regional characteristics integration" as the core. The paper aims to cultivate interdisciplinary talents with innovative capabilities, interdisciplinary knowledge and practical experience, provide theoretical reference for the reform of food professional education, and help the development of big health industry.

Since the implementation of the "Double Leader" cultivation project by the Party Leadership Group of the Ministry of Education, the "Double Leader" cultivation mechanism has been gradually established and improved. In the new journey of building an education power, universities should understand the strategic significance of cultivating the secretaries further, solve the problems that restrict development such as the imperfect cultivation mechanism and inadequate operation, and explore paths to optimize the cultivation mechanism. We should focus on cultivating a team of Party branch secretaries who can promote the "integration for high-quality development and high-level talent cultivation" in colleges and universities and serve national strategies and local economic and social development.

 In this paper, a guided wave model of the L(0,1) mode of the pipeline is constructed based on COMSOL to explore the influence of different defect parameters on the echo characteristics, and numerical simulation is carried out using a 35 kHz Hanning window signal. Combined with MATLAB, a defect location algorithm was developed to conduct a comparative analysis of full-penetration cracks from multiple angles. The results show that the traditional damage coefficient method has significant instability in circumferential positioning, while the circular trajectory curve method can achieve higher accuracy at all angles, especially at 45 ° to 60 ° The research verified the effectiveness and innovation points of this method in improving the circumferential positioning accuracy of defects in guided wave pipelines

In response to the reform demands of practical teaching in Welding Majors under the development of intelligent manufacturing, this study proposes an innovative path for intelligent upgrade of welding laboratories and curriculum optimization. By introducing intelligent devices such as welding robots and constructing a virtual simulation teaching platform, an experimental environment for intelligent welding technology has been created for students. The curriculum will be enhanced with intelligent welding content, and experimental designs will focus on intelligent welding techniques to achieve dual improvements in theoretical depth and technical competence. The research aims to enhance the cultivation quality of application-oriented talents through intelligent transformation, serve the upgrading needs of regional equipment manufacturing industries, and provide reference for practical teaching reforms in other institutions.