Long-term psychological depression can seriously damage the physical and mental growth of adolescent students, and effective interventions are needed to address students’ depression. This paper briefly introduced students’ depressive mood and surveyed students in three grades from ten high schools in Zhengzhou City in 2020 with questionnaires that included the degree of depression and family environment in addition to conventional information. After preliminary screening of indicators related to depressive mood, the influence of family environment on depressive mood was analyzed using multiple regression analysis. The results showed that factors such as intimacy, recreation, and organization in the family environment could effectively suppress depressive mood, while ambivalent and controlling factors could exacerbate depressive mood.
{"title":"A study on the relationship between students’ psychological depression and family situations using multi-factor logistic regression analysis","authors":"Zhiyi Luo","doi":"10.3233/jcm-226949","DOIUrl":"https://doi.org/10.3233/jcm-226949","url":null,"abstract":"Long-term psychological depression can seriously damage the physical and mental growth of adolescent students, and effective interventions are needed to address students’ depression. This paper briefly introduced students’ depressive mood and surveyed students in three grades from ten high schools in Zhengzhou City in 2020 with questionnaires that included the degree of depression and family environment in addition to conventional information. After preliminary screening of indicators related to depressive mood, the influence of family environment on depressive mood was analyzed using multiple regression analysis. The results showed that factors such as intimacy, recreation, and organization in the family environment could effectively suppress depressive mood, while ambivalent and controlling factors could exacerbate depressive mood.","PeriodicalId":45004,"journal":{"name":"Journal of Computational Methods in Sciences and Engineering","volume":"77 1","pages":""},"PeriodicalIF":0.5,"publicationDate":"2023-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138996297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A temperature sensor based on the combination of a temperature variable oscillator and a linear controlled oscillator is proposed, which can realize temperature detection through the characteristic of frequency changing with temperature. The changing frequency is generated by the two oscillators, and by adjusting the frequency linear change, the linearity of the sensor is also increased. Through the frequency digitizer, the digital signal can be output. Compensation through a process compensator improves the accuracy of the sensor after a single point correction. After conducting tests on 15 experimental samples, the accuracy was achieved within ± 1.2∘C across the temperature range of 0 to 125∘C, demonstrating a highly favorable level of precision.
{"title":"High performance low power CMOS temperature sensor","authors":"Hua Peng","doi":"10.3233/jcm-237012","DOIUrl":"https://doi.org/10.3233/jcm-237012","url":null,"abstract":"A temperature sensor based on the combination of a temperature variable oscillator and a linear controlled oscillator is proposed, which can realize temperature detection through the characteristic of frequency changing with temperature. The changing frequency is generated by the two oscillators, and by adjusting the frequency linear change, the linearity of the sensor is also increased. Through the frequency digitizer, the digital signal can be output. Compensation through a process compensator improves the accuracy of the sensor after a single point correction. After conducting tests on 15 experimental samples, the accuracy was achieved within ± 1.2∘C across the temperature range of 0 to 125∘C, demonstrating a highly favorable level of precision.","PeriodicalId":45004,"journal":{"name":"Journal of Computational Methods in Sciences and Engineering","volume":"51 7","pages":""},"PeriodicalIF":0.5,"publicationDate":"2023-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138999938","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Design and implementation of the system for retrieving information about mathematical formulas – MFIRS. The structure of the system is mainly divided into the modules: input normalization, mathematical formula unification, mathematical formula encoding, text information feature extraction, mathematical formula feature extraction, mathematical formula indexing, retrieval and ranking. A method for extracting mathematical formulas and keywords based on FastText word embedding technology is proposed. This method can be used not only to get the structural features of the formula, but also to facilitate the calculation of the similarity of the formula by the vector result. At the same time, the model introduces the semantic features of context-rich mathematical formulas to improve the domain correlation of search results. The MathRetEval dataset was created based on about 7.9 × 105 arXiv documents and about 1.5 × 108 mathematical formulas. The scalability of the system is verified using this data set. The mathematical formulas can be written in the language TEX or MathML. When queried in the TEX language, it can be converted to a tree representation of the MathML representation and then indexed. This MFIRS is an information retrieval system for mathematical formulas with the features of mathematical perception, which can use the search for the similarity of partial formulas.
{"title":"Mathematical formula information retrieval system","authors":"Yong Hou","doi":"10.3233/jcm-226961","DOIUrl":"https://doi.org/10.3233/jcm-226961","url":null,"abstract":"Design and implementation of the system for retrieving information about mathematical formulas – MFIRS. The structure of the system is mainly divided into the modules: input normalization, mathematical formula unification, mathematical formula encoding, text information feature extraction, mathematical formula feature extraction, mathematical formula indexing, retrieval and ranking. A method for extracting mathematical formulas and keywords based on FastText word embedding technology is proposed. This method can be used not only to get the structural features of the formula, but also to facilitate the calculation of the similarity of the formula by the vector result. At the same time, the model introduces the semantic features of context-rich mathematical formulas to improve the domain correlation of search results. The MathRetEval dataset was created based on about 7.9 × 105 arXiv documents and about 1.5 × 108 mathematical formulas. The scalability of the system is verified using this data set. The mathematical formulas can be written in the language TEX or MathML. When queried in the TEX language, it can be converted to a tree representation of the MathML representation and then indexed. This MFIRS is an information retrieval system for mathematical formulas with the features of mathematical perception, which can use the search for the similarity of partial formulas.","PeriodicalId":45004,"journal":{"name":"Journal of Computational Methods in Sciences and Engineering","volume":"39 9","pages":""},"PeriodicalIF":0.5,"publicationDate":"2023-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138997547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The rapid development of renewable energy has also had an impact on the flexibility of multi energy systems such as electricity, heat, and gas. To analyze the flexible characteristics of multi energy systems at multiple time scales, a multi-scale flexibility evaluation method based on morphological decomposition is proposed. The net load curve is decomposed using mathematical morphology methods, and a multi-scale energy storage configuration method based on the flexibility of electric heating systems is proposed. The analysis data shows that the probability of insufficient upward flexibility, margin expectation, and insufficient expectation of the scale weighted flexibility index are 1.12%, 3.98%, and 1.16%, respectively, while the probability of insufficient downward flexibility, margin expectation, and insufficient expectation are 0.73%, 4.54%, and 0.56%, respectively. The introduction of energy storage and controllable load simultaneously results in an overall downward flexibility index of 0.92% for the system. The results indicate that controllable load can improve the economy of system peak shaving, providing more options for energy storage and configuration in multi energy systems.
{"title":"Multi-scale flexibility assessment of electrical, thermal and gas multi-energy systems based on morphological decomposition","authors":"Xiaoqiang Jia, Zhiwei Wang, Songcen Wang, Kaicheng Liu, Xinhe Zhang, Jiajun Zhang","doi":"10.3233/jcm-226959","DOIUrl":"https://doi.org/10.3233/jcm-226959","url":null,"abstract":"The rapid development of renewable energy has also had an impact on the flexibility of multi energy systems such as electricity, heat, and gas. To analyze the flexible characteristics of multi energy systems at multiple time scales, a multi-scale flexibility evaluation method based on morphological decomposition is proposed. The net load curve is decomposed using mathematical morphology methods, and a multi-scale energy storage configuration method based on the flexibility of electric heating systems is proposed. The analysis data shows that the probability of insufficient upward flexibility, margin expectation, and insufficient expectation of the scale weighted flexibility index are 1.12%, 3.98%, and 1.16%, respectively, while the probability of insufficient downward flexibility, margin expectation, and insufficient expectation are 0.73%, 4.54%, and 0.56%, respectively. The introduction of energy storage and controllable load simultaneously results in an overall downward flexibility index of 0.92% for the system. The results indicate that controllable load can improve the economy of system peak shaving, providing more options for energy storage and configuration in multi energy systems.","PeriodicalId":45004,"journal":{"name":"Journal of Computational Methods in Sciences and Engineering","volume":"19 1","pages":""},"PeriodicalIF":0.5,"publicationDate":"2023-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138998781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper is focused on the field of computer vision in order to investigate the presentation properties of retinal blood vessels. Combining the structure of convolutional neural networks, activation functions, and common metrics in semantic segmentation, a dynamic network model for retinal vessel segmentation based on computer vision is constructed. The purpose of this paper is to discuss the results of retinal vascular segmentation based on computer vision. The image connection and alignment pattern selection process is also established to match retinal vessel images by computer vision. The performance of the dynamic network constructed here and the results of retinal vessel segmentation were then analyzed in three publicly available datasets, DRIVE (digital retinal images for vessel extraction), CHASE_DB1, and STARE (structured snalysis of the retinal. The ROC (retinopathy online challenge) curves on all three datasets exceeded 0.9, showing high performance, and the area under the PR curve exceeded 0.88. The accuracy of the results for retinal vessel segmentation was around 96%. Based on the semantic segmentation direction in the field of computer vision in this study, the dynamic network for retinal vessel segmentation can be well constructed.
{"title":"Construction of a dynamic network for retinal vessel segmentation based on computer vision","authors":"Runze Zhang","doi":"10.3233/jcm-237110","DOIUrl":"https://doi.org/10.3233/jcm-237110","url":null,"abstract":"This paper is focused on the field of computer vision in order to investigate the presentation properties of retinal blood vessels. Combining the structure of convolutional neural networks, activation functions, and common metrics in semantic segmentation, a dynamic network model for retinal vessel segmentation based on computer vision is constructed. The purpose of this paper is to discuss the results of retinal vascular segmentation based on computer vision. The image connection and alignment pattern selection process is also established to match retinal vessel images by computer vision. The performance of the dynamic network constructed here and the results of retinal vessel segmentation were then analyzed in three publicly available datasets, DRIVE (digital retinal images for vessel extraction), CHASE_DB1, and STARE (structured snalysis of the retinal. The ROC (retinopathy online challenge) curves on all three datasets exceeded 0.9, showing high performance, and the area under the PR curve exceeded 0.88. The accuracy of the results for retinal vessel segmentation was around 96%. Based on the semantic segmentation direction in the field of computer vision in this study, the dynamic network for retinal vessel segmentation can be well constructed.","PeriodicalId":45004,"journal":{"name":"Journal of Computational Methods in Sciences and Engineering","volume":"11 8","pages":""},"PeriodicalIF":0.5,"publicationDate":"2023-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139000441","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Traditional culture is a symbol of a country’s existence and history. The external dissemination of traditional culture is the key to expanding the country’s influence and enhancing the country’s international image. The external dissemination of culture also poses a potential impact on the country’s economy and development. In the context of the information age, the dissemination of Chinese traditional culture is attached great importance. The culture of the Forbidden City, from self-construction to borrowing, from online to offline all-media communication channels, unique and novel cultural and creative products and a young brand image provide it with a unique means of communication. The dissemination of the Forbidden City culture is of positive significance to the demonstration of cultural confidence and the innovation and development of culture, and it can be used as a typical case of the dissemination of Chinese traditional culture. Big data technology analyzes the research object through the process of data collection, data screening and data processing, combined with various data analysis tools, and the ultimate goal is to obtain favorable results for the analyst based on the analysis. The use of big data technology in cultural communication research has gradually become the focus of current scholars. This paper takes the Forbidden City culture as the research object, analyzes the current situation of the foreign communication of the traditional culture of the Forbidden City, puts forward the dilemma of the current external communication of Chinese traditional culture based on the current situation, summarizes the problems and reasons of traditional cultural communication, and designs corresponding solutions combined with big data technology. Through the data simulation of Chinese traditional cultural communication using big data solutions, it is found that the demand satisfaction, cultural benefits after cultural communication, and the direction of cultural influence have all improved after analyzing the user’s individual needs combined with big data technology.
{"title":"External communication of Chinese traditional culture under the background of big data","authors":"Xiaohan Li, W. Chai","doi":"10.3233/jcm-226939","DOIUrl":"https://doi.org/10.3233/jcm-226939","url":null,"abstract":"Traditional culture is a symbol of a country’s existence and history. The external dissemination of traditional culture is the key to expanding the country’s influence and enhancing the country’s international image. The external dissemination of culture also poses a potential impact on the country’s economy and development. In the context of the information age, the dissemination of Chinese traditional culture is attached great importance. The culture of the Forbidden City, from self-construction to borrowing, from online to offline all-media communication channels, unique and novel cultural and creative products and a young brand image provide it with a unique means of communication. The dissemination of the Forbidden City culture is of positive significance to the demonstration of cultural confidence and the innovation and development of culture, and it can be used as a typical case of the dissemination of Chinese traditional culture. Big data technology analyzes the research object through the process of data collection, data screening and data processing, combined with various data analysis tools, and the ultimate goal is to obtain favorable results for the analyst based on the analysis. The use of big data technology in cultural communication research has gradually become the focus of current scholars. This paper takes the Forbidden City culture as the research object, analyzes the current situation of the foreign communication of the traditional culture of the Forbidden City, puts forward the dilemma of the current external communication of Chinese traditional culture based on the current situation, summarizes the problems and reasons of traditional cultural communication, and designs corresponding solutions combined with big data technology. Through the data simulation of Chinese traditional cultural communication using big data solutions, it is found that the demand satisfaction, cultural benefits after cultural communication, and the direction of cultural influence have all improved after analyzing the user’s individual needs combined with big data technology.","PeriodicalId":45004,"journal":{"name":"Journal of Computational Methods in Sciences and Engineering","volume":"3 11","pages":""},"PeriodicalIF":0.5,"publicationDate":"2023-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138996421","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Safety is the lifeline of civil aviation. With the advancement of technology, human factors have become the primary factor affecting aviation safety. Among these, human errors in air traffic control (ATC) account for a significant proportion of aviation accidents. In order to investigate human errors in ATC, this paper introduces two common human factors conceptual models – the Reason model and the HFACS model, and analyzes the specific application of the HFACS model in aviation. It is found that the HFACS model can effectively establish a classification system for human errors in ATC. Moreover, this paper combines the HFACS model with AHP (Analytic Hierarchy Process) and uses the HFACS model to establish a first and second level indicator system for human errors in ATC. We calculated the weights of each specific factor using the Analytic Hierarchy Process. The results show that the most significant influencing factor in the first level indicators is organizational factors, while the most significant influencing factor in the second level indicators is Air Traffic Resource Management. Among the 13 second level indicators, the smallest weight is the controller’s violation. Based on the calculated weight results, in order to improve the safety level of ATC, the first step should be to improve the level of ATC organizational management. This is also of great significance for improving the safety level of the entire aviation system. The findings of this study suggest that the HFACS model, combined with AHP, can be an effective tool for identifying and analyzing human factors in ATC and ultimately improving the safety of the aviation industry.
{"title":"A study on human errors of air traffic controllers based on HFACS-AHP","authors":"Shouxi Zhu, Jian Chen","doi":"10.3233/jcm227000","DOIUrl":"https://doi.org/10.3233/jcm227000","url":null,"abstract":"Safety is the lifeline of civil aviation. With the advancement of technology, human factors have become the primary factor affecting aviation safety. Among these, human errors in air traffic control (ATC) account for a significant proportion of aviation accidents. In order to investigate human errors in ATC, this paper introduces two common human factors conceptual models – the Reason model and the HFACS model, and analyzes the specific application of the HFACS model in aviation. It is found that the HFACS model can effectively establish a classification system for human errors in ATC. Moreover, this paper combines the HFACS model with AHP (Analytic Hierarchy Process) and uses the HFACS model to establish a first and second level indicator system for human errors in ATC. We calculated the weights of each specific factor using the Analytic Hierarchy Process. The results show that the most significant influencing factor in the first level indicators is organizational factors, while the most significant influencing factor in the second level indicators is Air Traffic Resource Management. Among the 13 second level indicators, the smallest weight is the controller’s violation. Based on the calculated weight results, in order to improve the safety level of ATC, the first step should be to improve the level of ATC organizational management. This is also of great significance for improving the safety level of the entire aviation system. The findings of this study suggest that the HFACS model, combined with AHP, can be an effective tool for identifying and analyzing human factors in ATC and ultimately improving the safety of the aviation industry.","PeriodicalId":45004,"journal":{"name":"Journal of Computational Methods in Sciences and Engineering","volume":"4 10","pages":""},"PeriodicalIF":0.5,"publicationDate":"2023-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138998010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hongyin Chen, Songcen Wang, Ming Zhong, Lu Jin, Xiaoqiang Jia, Yi Guo, Xinhe Zhang, Wei Huang
The heat source tower heat pump system is widely used in large and medium-sized air conditioning systems due to its good energy-saving advantages. However, there is no relatively reasonable evaluation system for the applicability of heat source tower heat pumps due to significant regional climate differences. Therefore, in order to better comprehensively evaluate the applicability of the heat source tower heat pump system, a comprehensive evaluation index system for the applicability of the heat source tower heat pump system was first constructed. On the basis of this evaluation index, an applicability evaluation model based on backpropagation neural network is constructed. In response to the slow convergence speed and susceptibility to local values in the application process of this evaluation model, particle swarm optimization algorithm is used to improve it. A comprehensive evaluation model for the applicability of heat source tower heat pumps based on improved backpropagation neural networks has been constructed. For the evaluation model constructed in the study, experimental data from four different regions were selected for validation. The experimental results show that in the training set, the F-Measure value of the evaluation model reaches 0.949, and in the test set, the F-Measure value of the model reaches 0.973. The comprehensive evaluation data from four regions indicate that the heat source tower heat pump system can achieve different heating and cooling effects in different regions. This indicates that the proposed comprehensive evaluation model for the applicability of heat source tower heat pumps based on this improved method has good evaluation results. It can conduct a good analysis of the applicability of the heat source tower heat pump system, providing effective support for developing reasonable and energy-saving refrigeration and heating methods in different regions.
{"title":"A comprehensive evaluation method of heat source tower heat pump applicability considering regional climate differences","authors":"Hongyin Chen, Songcen Wang, Ming Zhong, Lu Jin, Xiaoqiang Jia, Yi Guo, Xinhe Zhang, Wei Huang","doi":"10.3233/jcm-226957","DOIUrl":"https://doi.org/10.3233/jcm-226957","url":null,"abstract":"The heat source tower heat pump system is widely used in large and medium-sized air conditioning systems due to its good energy-saving advantages. However, there is no relatively reasonable evaluation system for the applicability of heat source tower heat pumps due to significant regional climate differences. Therefore, in order to better comprehensively evaluate the applicability of the heat source tower heat pump system, a comprehensive evaluation index system for the applicability of the heat source tower heat pump system was first constructed. On the basis of this evaluation index, an applicability evaluation model based on backpropagation neural network is constructed. In response to the slow convergence speed and susceptibility to local values in the application process of this evaluation model, particle swarm optimization algorithm is used to improve it. A comprehensive evaluation model for the applicability of heat source tower heat pumps based on improved backpropagation neural networks has been constructed. For the evaluation model constructed in the study, experimental data from four different regions were selected for validation. The experimental results show that in the training set, the F-Measure value of the evaluation model reaches 0.949, and in the test set, the F-Measure value of the model reaches 0.973. The comprehensive evaluation data from four regions indicate that the heat source tower heat pump system can achieve different heating and cooling effects in different regions. This indicates that the proposed comprehensive evaluation model for the applicability of heat source tower heat pumps based on this improved method has good evaluation results. It can conduct a good analysis of the applicability of the heat source tower heat pump system, providing effective support for developing reasonable and energy-saving refrigeration and heating methods in different regions.","PeriodicalId":45004,"journal":{"name":"Journal of Computational Methods in Sciences and Engineering","volume":"120 8","pages":""},"PeriodicalIF":0.5,"publicationDate":"2023-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138999358","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The performance-related pay system in colleges and universities is one of the hot spots in the reform of the wage system in colleges and universities in recent years. It is an important measure to improve the quality of education and teaching in colleges and universities and the construction of talent teams. However, there are many problems in the performance-related pay system of colleges and universities, such as unreasonable evaluation indicators, unfair weight distribution, etc., which makes it difficult to accurately reflect the work performance of teachers and staff in the measurement of performance-related pay. Based on this background and trend, this paper conducted an in-depth discussion on the salary system in China’s colleges and universities, and used the support vector regression algorithm to study the performance-based salary management of colleges and universities based on linear programming and mathematical statistics. The research showed that with other conditions remaining unchanged, the proportions of primary, intermediate, deputy and senior high school students who were dissatisfied with the system of performance-based pay in colleges and universities were 82%, 57%, 46%, and 9%, respectively. After applying linear programming and mathematical statistics, the proportions of elementary, intermediate, sub-high and ortho-high became 1%, 2%, 5% and 7% respectively. The decline of the first three was particularly obvious, and the teachers with positive high school also dropped by 2%, indicating that linear programming and mathematical statistics were beneficial to the management of performance wages in colleges and universities.
{"title":"Investigation on the management of college performance pay with linear programming and mathematical statistics","authors":"Jinfei Lv","doi":"10.3233/jcm-226998","DOIUrl":"https://doi.org/10.3233/jcm-226998","url":null,"abstract":"The performance-related pay system in colleges and universities is one of the hot spots in the reform of the wage system in colleges and universities in recent years. It is an important measure to improve the quality of education and teaching in colleges and universities and the construction of talent teams. However, there are many problems in the performance-related pay system of colleges and universities, such as unreasonable evaluation indicators, unfair weight distribution, etc., which makes it difficult to accurately reflect the work performance of teachers and staff in the measurement of performance-related pay. Based on this background and trend, this paper conducted an in-depth discussion on the salary system in China’s colleges and universities, and used the support vector regression algorithm to study the performance-based salary management of colleges and universities based on linear programming and mathematical statistics. The research showed that with other conditions remaining unchanged, the proportions of primary, intermediate, deputy and senior high school students who were dissatisfied with the system of performance-based pay in colleges and universities were 82%, 57%, 46%, and 9%, respectively. After applying linear programming and mathematical statistics, the proportions of elementary, intermediate, sub-high and ortho-high became 1%, 2%, 5% and 7% respectively. The decline of the first three was particularly obvious, and the teachers with positive high school also dropped by 2%, indicating that linear programming and mathematical statistics were beneficial to the management of performance wages in colleges and universities.","PeriodicalId":45004,"journal":{"name":"Journal of Computational Methods in Sciences and Engineering","volume":"23 48","pages":""},"PeriodicalIF":0.5,"publicationDate":"2023-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139000870","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Chunlei Liu, Mengru Zhang, Wenshuang Zhen, Peng Wang, Yibo Ding, Yang Cai, Yong Sun
In the direction of better resolution of time lag, nonlinearity and uncertainty in the heating system, a BPNN-PID (BP neural network PID) controller is proposed in this paper. A complete heating auto-control system is designed with the experimental platform of a university heat exchange station in Zhangjiakou as the research background. The auto-control system takes Programmable Logic Controller (PLC) as the control core, uses BPNN algorithm to optimize the PID control parameters, and finally takes outlet temperature of 1# plate exchanger as the main control parameter to conduct experimental research on BPNN-PID control and single-loop feedback control respectively. The results show that compared with the single-loop feedback controller, the PID control based on BPNN algorithm has superior control quality, with shorter adjustment time, smaller overshoot, finer control accuracy and stability.
{"title":"Application research of BP neural network PID in control system of heat exchange station","authors":"Chunlei Liu, Mengru Zhang, Wenshuang Zhen, Peng Wang, Yibo Ding, Yang Cai, Yong Sun","doi":"10.3233/jcm-226972","DOIUrl":"https://doi.org/10.3233/jcm-226972","url":null,"abstract":"In the direction of better resolution of time lag, nonlinearity and uncertainty in the heating system, a BPNN-PID (BP neural network PID) controller is proposed in this paper. A complete heating auto-control system is designed with the experimental platform of a university heat exchange station in Zhangjiakou as the research background. The auto-control system takes Programmable Logic Controller (PLC) as the control core, uses BPNN algorithm to optimize the PID control parameters, and finally takes outlet temperature of 1# plate exchanger as the main control parameter to conduct experimental research on BPNN-PID control and single-loop feedback control respectively. The results show that compared with the single-loop feedback controller, the PID control based on BPNN algorithm has superior control quality, with shorter adjustment time, smaller overshoot, finer control accuracy and stability.","PeriodicalId":45004,"journal":{"name":"Journal of Computational Methods in Sciences and Engineering","volume":"92 7","pages":""},"PeriodicalIF":0.5,"publicationDate":"2023-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138998909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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