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With the gradual implementation of the strategic goal of strengthening the country in education, people's attention to students' learning is also increasing day by day. At the same time, the teaching effect of individual teachers depends to a large extent on the identity of teachers themselves, so it is necessary to improve the construction of teachers' identity. Most of the research on teachers' identity construction starts from the theory of identity, which does not play a significant role in the critical application in practical teaching activities. In response to these problems, this paper will use the ReliefF algorithm and the Spark algorithm in the feature selection algorithm to scientifically process the identity construction, and implement the application of the improved ReliefF feature selection algorithm and the feature selection application steps based on the Spark algorithm respectively. The experimental results show that the improved ReliefF algorithm has better feature selection accuracy when the feature range is 30% to 40%. It shows that the construction of teacher identity based on feature selection algorithm can provide an objective basis for the realization of teacher identity. [ABSTRACT FROM AUTHOR]

In recent years, with the development and extensive application of Internet technology and computer technology, and under the role of the continuous expansion and enrollment expansion of colleges and universities, how to effectively solve the Internet problems faced by teachers and students in colleges and universities has gradually become an important problem that the university information management department should solve in time. In order to continuously improve the efficiency of Internet access in universities, the Internet authentication and billing system for universities proposed in this paper take J2EE as the development platform and combines RADIUS protocol and PPPoE protocol to provide users with diversified Internet billing methods and strategies. At the same time, based on the Fourier fast transform algorithm, the development environment for the Internet authentication and billing system for colleges and universities is deployed, and after the Internet authentication and billing system is implemented, from the functional point of view of the system, the main functional modules are designed and implemented, including the authentication management function. module, billing management function module. The experimental results have shown that the throughput of PPPoE access server in the campus network using the Fourier rapid transform algorithm for traffic load balancing delay is small and stable between 200 ms and 300 ms after the optimization, which provides a feasible solution to promote the healthy and harmonious development of the university campus network. [ABSTRACT FROM AUTHOR]

Because of the increasing adoption and use of technology in primary health care (PHC), public health informatics competencies (PHIC) are becoming essential for public health workers. Unfortunately, no studies have measured PHIC in resource-limited setting. This paper describes the process of developing and validating Public Health Informatics Competencies for Primary Health Care (PHIC4PHC), an instrument for measuring PHC workers' competencies in public health informatics. Method: This study developed a questionnaire that had three stages: the Delphi technique, a pretest, and field test. Eleven academicians from a university and 13 PHC workers joined 2 rounds of group discussion in the first stage. The second stage comprised two pilot studies with 75 PHC workers in Semarang Municipality. The third stage involved validating the questionnaire with 462 PHC workers in Kendal District. This study used Pearson's product-moment correlation for the validity check and Cronbach's alpha coefficient for determining the internal consistency. This study used the K-means algorithm for clustering the results of the PHIC4PHC questionnaire. Results and Conclusion: PHIC4PHC is the first comprehensive PHIC questionnaire administered in a resource-limited setting, consisting of 11 indicators and 42 measurement items concerning knowledge of health information systems, skills required for health data management, ethical aspects of data sharing and health information literacy. The final results of PHIC4PHC were clustered into three classes based on the K-means algorithm. Overall, 45.7% PHC workers achieved medium competency, whereas 25.6% and 27.7% achieved low and high competency, respectively. Men had higher competency than women. The higher the worker's level of education, the higher the PHIC level; the longer the worker's work experience, the lower the PHIC score; and the greater the worker's age, the lower the PHIC score. Measuring and monitoring PHIC is vital to support successful health IT adoption in PHC. [ABSTRACT FROM AUTHOR]

With the popularization of standardized classrooms in colleges and universities, it is possible to collect video data of students' class status through the camera device in the classroom. With abundant video data sources, it is easy to obtain big data of students' class status images. Unstructured video big data is a topic worthy of research in improving teaching quality. First, the current teaching ability of teachers in colleges and universities is investigated, and its problems are found. Then, the You Only Look Once (YOLO) network in the object detection network is mainly studied. The deficiencies in the network structure are further explored and optimized. It is used in real classroom scenarios as well as on student expression detection problems. Finally, the proposed scheme is tested. The test results show that at present, 20% and 38% of teachers in higher vocational colleges think that they are "dissatisfied" with their classroom teaching and practical guidance ability. And 38% of teachers wanted to improve the bad situation. The accuracy of the proposed model for student expression detection is higher than that of faster-region convolutional neural network and mask-region convolutional neural network by more than 8%, higher than the YOLO v3 model by more than 4%, and higher than YOLO v3 Tiny model above 6%. The proposed model provides some ideas for the application of deep learning technology in the improvement of teachers' teaching ability. [ABSTRACT FROM AUTHOR]

The article profiles Herbert Eli "Herb" Scarf, an economics professor at Yale University and a member of Cowles Foundation for Research in Economics. It states that the use of numerical algorithms to compute equilibrium prices in a general equilibrium model of the economy was pioneered by Scarf. It also mentions that he won the 1983 John von Neumann Theory Prize and is a fellow of Institute for Operations Research and the Management Sciences (INFORMS).

The article focuses on professor Stephen C. Graves, who holds joint professorships in the Mechanical Engineering Department and the Engineering Systems Division at Massachusetts Institute of Technology (MIT). It says that Graves has been an influential scholar and his research had an impact on practice and theory. It mentions that Graves' fields of interest are operations management and applied operations research. Moreover, his development of a modeling convention and algorithm is discussed.

An interview with Mario A. de Oliveira, associate professor at Mato Grosso Federal Institute of Technology in Brazil, on his research Embedded Application of Convolutional Neural Networks on Raspberry Pi for Structural Health Monitoring, is presented. Topics of the interview include structural health monitoring (SHM), the significance of using convolutional neural networks algorithm in SHM, and his plan for the development of his work.