A variety of measurement methods were used comprehensively in this paper to conduct empirical research on the CE, spatial pattern characteristics and influencing causes of the YREB. Both the total factor CE and the single factor CE were discovered relatively stable. Starting around 2013, the development of the tail cities of the YREB has gradually improved. In addition to Sichuan, Hunan, Chongqing, Hubei and other places where the increase in CE had exceeded that of other cities, the development of CE in Shanghai has also increased significantly. The CE of the YREB had increased with a significant positive spatial autocorrelation and a significant spatial aggregation effect between 2006 and 2017. The spatial spillover effect of CE in the YREB is mainly transmit through factors such as economic growth, energy structure, industrial structure, government intervention, population density, foreign direct investment and the level of marketization, and the spatial interaction between each factor and CE cannot be ignored.
{"title":"Spatial distribution characteristics and influencing causes of CE in the YREB1","authors":"Jia You, Baoshuai Zhang, Jun Duan","doi":"10.3233/jcm-226844","DOIUrl":"https://doi.org/10.3233/jcm-226844","url":null,"abstract":"A variety of measurement methods were used comprehensively in this paper to conduct empirical research on the CE, spatial pattern characteristics and influencing causes of the YREB. Both the total factor CE and the single factor CE were discovered relatively stable. Starting around 2013, the development of the tail cities of the YREB has gradually improved. In addition to Sichuan, Hunan, Chongqing, Hubei and other places where the increase in CE had exceeded that of other cities, the development of CE in Shanghai has also increased significantly. The CE of the YREB had increased with a significant positive spatial autocorrelation and a significant spatial aggregation effect between 2006 and 2017. The spatial spillover effect of CE in the YREB is mainly transmit through factors such as economic growth, energy structure, industrial structure, government intervention, population density, foreign direct investment and the level of marketization, and the spatial interaction between each factor and CE cannot be ignored.","PeriodicalId":45004,"journal":{"name":"Journal of Computational Methods in Sciences and Engineering","volume":"111 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135971633","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}
With the continuous layout of intelligent processing technology in the teaching field, it has become an important trend to apply big data and Internet of Things technology to the teaching management of college students. Big data technology can comprehensively analyze the teaching situation of students through massive data, and then provide the best solution, the current big data technology already has a strong technical foundation, which can provide assistance for students’ teaching. The Internet of Things technology can collect personal information of students through sensors and miniature portable devices, and provide the data to the background server for big data analysis. In order to analyze the current status of the informationization of teaching management for college students, this paper first surveys some colleges and institutions through questionnaire surveys, and conducts data analysis on the collected questionnaires, and puts forward a solution based on big data and the Internet of Things based on the data analysis results. Finally, the combination of big data and Internet of Things technology for student teaching data collection, effect evaluation scheme, intelligent arrangement of integrated courses, intelligent recommendation scheme for students’ teaching needs, and teaching management information visualization scheme are analyzed, and it is found that the combination of big data and Internet of Things related technologies It can effectively improve the efficiency of teaching management of college students.
{"title":"Reform of college students' teaching management informatization under the background of big data and IoT","authors":"Lei Wu","doi":"10.3233/jcm-226893","DOIUrl":"https://doi.org/10.3233/jcm-226893","url":null,"abstract":"With the continuous layout of intelligent processing technology in the teaching field, it has become an important trend to apply big data and Internet of Things technology to the teaching management of college students. Big data technology can comprehensively analyze the teaching situation of students through massive data, and then provide the best solution, the current big data technology already has a strong technical foundation, which can provide assistance for students’ teaching. The Internet of Things technology can collect personal information of students through sensors and miniature portable devices, and provide the data to the background server for big data analysis. In order to analyze the current status of the informationization of teaching management for college students, this paper first surveys some colleges and institutions through questionnaire surveys, and conducts data analysis on the collected questionnaires, and puts forward a solution based on big data and the Internet of Things based on the data analysis results. Finally, the combination of big data and Internet of Things technology for student teaching data collection, effect evaluation scheme, intelligent arrangement of integrated courses, intelligent recommendation scheme for students’ teaching needs, and teaching management information visualization scheme are analyzed, and it is found that the combination of big data and Internet of Things related technologies It can effectively improve the efficiency of teaching management of college students.","PeriodicalId":45004,"journal":{"name":"Journal of Computational Methods in Sciences and Engineering","volume":"23 1","pages":"2525-2534"},"PeriodicalIF":0.5,"publicationDate":"2023-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70041617","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}
Ethnic identity is an important reason for national unity. The formation of ethnic groups is mostly due to external and internal reasons, with a complex mechanism structure. When people’s environment is destroyed, this value identity will be stronger, national cohesion and solidarity will grow sharply, an unprecedented high. Minority languages are characterized by a wide variety, cultural generation, and dynamic evolution. The languages are complex and diverse, and are deeply influenced by their cultural heritage. This has led to the fact that for a long time, minority languages have been learned almost exclusively by people of their own ethnic group. This has led to a steady decline in the number of minority language speakers. However, the birth of the Internet of Things (IoT) has created an opportunity for the development of minority languages. Foreign minority languages have the following status (1) rapid decline (2) many endangered languages (3) low willingness to learn. In order to further investigate the current situation of minority language protection, the team conducted a survey in the minority cluster A. The results of the survey are as follows: most of the villagers are in love with the ethnic language and must inherit and promote the ethnic language, which is the wealth of a nation, but there are also a few residents who think that Mandarin should be used to replace the ethnic language. This reflects that most of the residents love the national language, but their young people as the inherited generation lose their love for the national language and are not willing to inherit and promote it. To solve this problem, an Internet of Things (IoT)-based ethnic language data system has been constructed so that the data system for ethnic minority language protection built through IoT technology can become the last line of defense for protecting ethnic languages, while allowing ethnic languages to be known and understood by more people through IoT technology, fostering the love and reverence of ethnic minority people for ethnic languages, and enhancing other ethnic groups’ sense of identity and support for ethnic languages. We propose to protect minority languages. Ultimately, we propose recommendations for the preservation of minority languages. (1) Increase publicity for minority language preservation. (2) Construct laws and regulations related to minority language protection. (3) Conduct in-depth research on minority language work and build an information base. (4) Promote minority language education.
{"title":"Current situation and path of foreign minority language protection based on Internet of Things from the perspective of ethnic identity","authors":"Qian Huang","doi":"10.3233/jcm-226899","DOIUrl":"https://doi.org/10.3233/jcm-226899","url":null,"abstract":"Ethnic identity is an important reason for national unity. The formation of ethnic groups is mostly due to external and internal reasons, with a complex mechanism structure. When people’s environment is destroyed, this value identity will be stronger, national cohesion and solidarity will grow sharply, an unprecedented high. Minority languages are characterized by a wide variety, cultural generation, and dynamic evolution. The languages are complex and diverse, and are deeply influenced by their cultural heritage. This has led to the fact that for a long time, minority languages have been learned almost exclusively by people of their own ethnic group. This has led to a steady decline in the number of minority language speakers. However, the birth of the Internet of Things (IoT) has created an opportunity for the development of minority languages. Foreign minority languages have the following status (1) rapid decline (2) many endangered languages (3) low willingness to learn. In order to further investigate the current situation of minority language protection, the team conducted a survey in the minority cluster A. The results of the survey are as follows: most of the villagers are in love with the ethnic language and must inherit and promote the ethnic language, which is the wealth of a nation, but there are also a few residents who think that Mandarin should be used to replace the ethnic language. This reflects that most of the residents love the national language, but their young people as the inherited generation lose their love for the national language and are not willing to inherit and promote it. To solve this problem, an Internet of Things (IoT)-based ethnic language data system has been constructed so that the data system for ethnic minority language protection built through IoT technology can become the last line of defense for protecting ethnic languages, while allowing ethnic languages to be known and understood by more people through IoT technology, fostering the love and reverence of ethnic minority people for ethnic languages, and enhancing other ethnic groups’ sense of identity and support for ethnic languages. We propose to protect minority languages. Ultimately, we propose recommendations for the preservation of minority languages. (1) Increase publicity for minority language preservation. (2) Construct laws and regulations related to minority language protection. (3) Conduct in-depth research on minority language work and build an information base. (4) Promote minority language education.","PeriodicalId":45004,"journal":{"name":"Journal of Computational Methods in Sciences and Engineering","volume":"23 1","pages":"2677-2686"},"PeriodicalIF":0.5,"publicationDate":"2023-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70041903","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}
With the development of Internet of Things and fuzzy control theory, there are new opportunities for the conservation and utilization of museum artifacts. The traditional way of heritage restoration lacks the overall harmony of heritage restoration, which leads to the stagnation of heritage restoration level. At the same time, traditional heritage conservation is also limited to manual management, which seriously hinders the development of the overall level of museums. Artifacts are of great commemorative and research value and are objects that have been handed down to mankind for thousands of years and have been subjected to the natural environment for a long time before being excavated. Heritage conservation requires not only restoring artifacts to the greatest extent possible, but also securing the environment in which they are displayed and stored to ensure that they can be preserved for as long as possible. But the following problems exist in the conservation of cultural relics (1) the lack of strict standards for the environment in which cultural relics are stored. (2) the professional competence of the staff is not strong. (3) The lack of a strict management system (4) heritage conservation technology is backward. To solve these problems our team constructed a fuzzy control method based on fuzzy control theory to assist in the restoration of cultural relics. The model constructed by fuzzy control theory solves this problem. The fuzzy control theory constructs a model for restoration of cultural relics, taking into account the overall harmony of the relics and the accuracy of the points, which is of great significance for the restoration of museum relics. At the same time through the Internet of Things technology to build a library heritage protection system, the main content of the system is (1) the use of Internet of Things technology to build a security protection system for cultural relics (2) the use of Internet of Things technology to detect the storage environment of cultural relics (3) the use of Internet of Things technology to optimize the management process of cultural relics (4) the use of Internet of Things technology to achieve real-time monitoring of the flow of information on cultural relics. And based on this, suggestions are made to (1) improve the museum heritage protection and utilization system (2) improve the infrastructure of museum heritage protection and build a good environment for heritage storage (3) improve the quality of heritage managers. The model constructed in the article has been tested in practice and is feasible, with certain practical and theoretical values.
{"title":"The conservation and utilization of museum relics based on internet of things and fuzzy control","authors":"Yifei Nan, Nan Yao, Yukun Huang, Dandan Jiao","doi":"10.3233/jcm-226895","DOIUrl":"https://doi.org/10.3233/jcm-226895","url":null,"abstract":"With the development of Internet of Things and fuzzy control theory, there are new opportunities for the conservation and utilization of museum artifacts. The traditional way of heritage restoration lacks the overall harmony of heritage restoration, which leads to the stagnation of heritage restoration level. At the same time, traditional heritage conservation is also limited to manual management, which seriously hinders the development of the overall level of museums. Artifacts are of great commemorative and research value and are objects that have been handed down to mankind for thousands of years and have been subjected to the natural environment for a long time before being excavated. Heritage conservation requires not only restoring artifacts to the greatest extent possible, but also securing the environment in which they are displayed and stored to ensure that they can be preserved for as long as possible. But the following problems exist in the conservation of cultural relics (1) the lack of strict standards for the environment in which cultural relics are stored. (2) the professional competence of the staff is not strong. (3) The lack of a strict management system (4) heritage conservation technology is backward. To solve these problems our team constructed a fuzzy control method based on fuzzy control theory to assist in the restoration of cultural relics. The model constructed by fuzzy control theory solves this problem. The fuzzy control theory constructs a model for restoration of cultural relics, taking into account the overall harmony of the relics and the accuracy of the points, which is of great significance for the restoration of museum relics. At the same time through the Internet of Things technology to build a library heritage protection system, the main content of the system is (1) the use of Internet of Things technology to build a security protection system for cultural relics (2) the use of Internet of Things technology to detect the storage environment of cultural relics (3) the use of Internet of Things technology to optimize the management process of cultural relics (4) the use of Internet of Things technology to achieve real-time monitoring of the flow of information on cultural relics. And based on this, suggestions are made to (1) improve the museum heritage protection and utilization system (2) improve the infrastructure of museum heritage protection and build a good environment for heritage storage (3) improve the quality of heritage managers. The model constructed in the article has been tested in practice and is feasible, with certain practical and theoretical values.","PeriodicalId":45004,"journal":{"name":"Journal of Computational Methods in Sciences and Engineering","volume":" ","pages":""},"PeriodicalIF":0.5,"publicationDate":"2023-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44243094","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}
Football has always been a traditional item in sports colleges and universities in China, and is loved by teachers and students, but the traditional teaching mode of football general course has failed to meet the requirements of contemporary high-quality teaching. The author introduces the “match lead-in training” mode into the general football course to carry out teaching experimental research. Through the comparative analysis of the statistics of technical data and the test of special skills in four-person and six-person matches, the author finds that this teaching mode is more conducive to the improvement of students’ football technology, skill level and competition ability than that of the traditional football general course.
{"title":"An empirical study on the match-lead-in training mode in the general football course of physical education institute","authors":"Ji-xiang Chen, Fuli Liu, Tingyan Pu","doi":"10.3233/jcm-226901","DOIUrl":"https://doi.org/10.3233/jcm-226901","url":null,"abstract":"Football has always been a traditional item in sports colleges and universities in China, and is loved by teachers and students, but the traditional teaching mode of football general course has failed to meet the requirements of contemporary high-quality teaching. The author introduces the “match lead-in training” mode into the general football course to carry out teaching experimental research. Through the comparative analysis of the statistics of technical data and the test of special skills in four-person and six-person matches, the author finds that this teaching mode is more conducive to the improvement of students’ football technology, skill level and competition ability than that of the traditional football general course.","PeriodicalId":45004,"journal":{"name":"Journal of Computational Methods in Sciences and Engineering","volume":"23 1","pages":"2659-2675"},"PeriodicalIF":0.5,"publicationDate":"2023-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70042672","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 internal connection and rule diversification of experience marketing data make it difficult to predict the future trend of data. Therefore, it is necessary to mine sports marketing data to guide future marketing strategies. In order to improve the effect of sports marketing data mining, this paper puts forward the algorithm research of experience sports marketing data mining in the cloud computing environment. In the cloud computing environment, based on the idea of data mining, a sports marketing monitoring system is designed and implemented to obtain a large number of evaluation data. The related data is extracted from the database of sports marketing evaluation system, and the data warehouse is constructed by data preprocessing. Using association rule algorithm to realize the data mining module of sports marketing evaluation system, mining the data in the data warehouse, dividing the data set into various data blocks, and then scanning each data block for association rule mining. The experimental results show that the mining algorithm can effectively mine different factors that affect the marketing status. The customer satisfaction obtained after the practical application of this method reaches more than 90%. Sports marketing enterprises can establish benign interaction between users and enterprises according to the mining results of this method, further meet the personalized and differentiated needs of consumers, thereby expanding the influence of enterprises and promoting the realization of marketing.
{"title":"Data mining algorithm of experiential sports marketing based on cloud computing technology","authors":"Mengzhong Chen, Guixian Tian, Y. Tao","doi":"10.3233/jcm-226908","DOIUrl":"https://doi.org/10.3233/jcm-226908","url":null,"abstract":"The internal connection and rule diversification of experience marketing data make it difficult to predict the future trend of data. Therefore, it is necessary to mine sports marketing data to guide future marketing strategies. In order to improve the effect of sports marketing data mining, this paper puts forward the algorithm research of experience sports marketing data mining in the cloud computing environment. In the cloud computing environment, based on the idea of data mining, a sports marketing monitoring system is designed and implemented to obtain a large number of evaluation data. The related data is extracted from the database of sports marketing evaluation system, and the data warehouse is constructed by data preprocessing. Using association rule algorithm to realize the data mining module of sports marketing evaluation system, mining the data in the data warehouse, dividing the data set into various data blocks, and then scanning each data block for association rule mining. The experimental results show that the mining algorithm can effectively mine different factors that affect the marketing status. The customer satisfaction obtained after the practical application of this method reaches more than 90%. Sports marketing enterprises can establish benign interaction between users and enterprises according to the mining results of this method, further meet the personalized and differentiated needs of consumers, thereby expanding the influence of enterprises and promoting the realization of marketing.","PeriodicalId":45004,"journal":{"name":"Journal of Computational Methods in Sciences and Engineering","volume":" ","pages":""},"PeriodicalIF":0.5,"publicationDate":"2023-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43225379","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 social networks has facilitated the convenience of users to receive information. As a network communication platform for people’s daily use, microblog has countless information data. In view of the low efficiency and poor clustering effect of K-means algorithm, a parallel K-means clustering algorithm based on MapReduce model is studied; In order to alleviate the difficulty in calculating the similarity of microblog topic text, the space vector model and semantic similarity are used to calculate the similarity between texts to improve the quality of microblog text classification. The data expansion rate of corresponding nodes under different data sets shows that the average expansion rate of the parallel K-means algorithm reaches 0.89, and the running rate is the highest. The results show that the parallel K-means algorithm has good clustering stability and the highest clustering quality, reaching 1.24; The clustering time of the algorithm is the shortest, the average clustering time is 1.27 minutes, and the clustering effect and efficiency of the algorithm are the best. In the quality analysis of Weibo topic recommendation, the accuracy of P-K-means recommendation is 95.64%, user satisfaction is 98.64%, and the recommendation effect is also the best. It shows that the research on the parallel K-means clustering algorithm based on MapReduce has the best performance in microblogging topic mining and recommendation, which can efficiently recommend topics of interest to users and enhance users’ microblogging experience.
{"title":"A MapReduce-based approach to social network big data mining","authors":"Fuli Qi","doi":"10.3233/jcm-226903","DOIUrl":"https://doi.org/10.3233/jcm-226903","url":null,"abstract":"The rapid development of social networks has facilitated the convenience of users to receive information. As a network communication platform for people’s daily use, microblog has countless information data. In view of the low efficiency and poor clustering effect of K-means algorithm, a parallel K-means clustering algorithm based on MapReduce model is studied; In order to alleviate the difficulty in calculating the similarity of microblog topic text, the space vector model and semantic similarity are used to calculate the similarity between texts to improve the quality of microblog text classification. The data expansion rate of corresponding nodes under different data sets shows that the average expansion rate of the parallel K-means algorithm reaches 0.89, and the running rate is the highest. The results show that the parallel K-means algorithm has good clustering stability and the highest clustering quality, reaching 1.24; The clustering time of the algorithm is the shortest, the average clustering time is 1.27 minutes, and the clustering effect and efficiency of the algorithm are the best. In the quality analysis of Weibo topic recommendation, the accuracy of P-K-means recommendation is 95.64%, user satisfaction is 98.64%, and the recommendation effect is also the best. It shows that the research on the parallel K-means clustering algorithm based on MapReduce has the best performance in microblogging topic mining and recommendation, which can efficiently recommend topics of interest to users and enhance users’ microblogging experience.","PeriodicalId":45004,"journal":{"name":"Journal of Computational Methods in Sciences and Engineering","volume":"23 1","pages":"2535-2547"},"PeriodicalIF":0.5,"publicationDate":"2023-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70042734","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 urbanization has led to the gradual increase of urban residential density. Relatively speaking, the spectrum resources are increasingly scarce, which leads to the increasingly serious interference between communities, and the system performance is also greatly limited. Therefore, in order to improve the efficiency of spectrum resources and solve the problem of user interference between cells, the experiment combines the advantages of clustering by fast search and find of Density Peaks Clustering (DPC), and proposes a two-step clustering algorithm. This method is proposed based on the core idea of DPC after in-depth study of the downlink multi-cell orthogonal frequency division multiplexing system architecture. The proposed model is compared with Matching Pursuit (MP) algorithm and Graph-based algorithm with the sum of clustering distance Rs, 1.5Rs. The results show that the two-step clustering algorithm can significantly improve the spectrum efficiency and network capacity while ensuring good quality of service under the condition of channel tension or not. In addition, the minimum SINR value of the two-step clustering algorithm can reach 75 dB. Compared with the 220 dB of the Graph-based algorithm with the clustering distance Rs, it has extremely obvious advantages. Therefore, the two-step clustering algorithm constructed in this study can effectively reduce system interference, and has certain research and application value in solving the problem of mobile communication channel resource shortage.
{"title":"Mobile communication channel resource allocation technology in interference environment based on clustering algorithm","authors":"Yuan Chen, Wenqi Cao, Wenjie Xu, Juan Li","doi":"10.3233/jcm-226905","DOIUrl":"https://doi.org/10.3233/jcm-226905","url":null,"abstract":"The rapid development of urbanization has led to the gradual increase of urban residential density. Relatively speaking, the spectrum resources are increasingly scarce, which leads to the increasingly serious interference between communities, and the system performance is also greatly limited. Therefore, in order to improve the efficiency of spectrum resources and solve the problem of user interference between cells, the experiment combines the advantages of clustering by fast search and find of Density Peaks Clustering (DPC), and proposes a two-step clustering algorithm. This method is proposed based on the core idea of DPC after in-depth study of the downlink multi-cell orthogonal frequency division multiplexing system architecture. The proposed model is compared with Matching Pursuit (MP) algorithm and Graph-based algorithm with the sum of clustering distance Rs, 1.5Rs. The results show that the two-step clustering algorithm can significantly improve the spectrum efficiency and network capacity while ensuring good quality of service under the condition of channel tension or not. In addition, the minimum SINR value of the two-step clustering algorithm can reach 75 dB. Compared with the 220 dB of the Graph-based algorithm with the clustering distance Rs, it has extremely obvious advantages. Therefore, the two-step clustering algorithm constructed in this study can effectively reduce system interference, and has certain research and application value in solving the problem of mobile communication channel resource shortage.","PeriodicalId":45004,"journal":{"name":"Journal of Computational Methods in Sciences and Engineering","volume":" ","pages":""},"PeriodicalIF":0.5,"publicationDate":"2023-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48495785","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}
With the continuous development of artificial intelligence research, computer vision research has shifted from traditional “feature engineering”-based methods to deep learning-based “network engineering” methods, which automatically extracts and classifies features by using deep neural networks. Traditional methods based on artificial design features are computationally expensive and are usually used to solve simple research problems, which is not conducive for large-scale data feature extraction. Deep learning-based methods greatly reduce the difficulty of artificial features by learning features from large-scale data and are successfully applied in many visual recognition tasks. Video action recognition methods also shift from traditional methods based on artificial design features to deep learning-based methods, which is oriented to building more effective deep neural network models. Through collecting and sorting related research results found that academic for timing segment network of football and basketball video action research is relatively rich, but lack of badminton research given the above research results, this study based on timing segment network of badminton video action identification can enrich the research results, provide reference for follow-up research. This paper introduces the lightweight attention mechanism into the temporal segmentation network, forming the attention mechanism-timing segmentation network, and trains the neural network to get the classifier of badminton stroke action, which can be predicted as four common types: forehand stroke, backhand stroke, overhead stroke and pick ball. The experimental results show that the recognition recall and accuracy of various stroke movements reach more than 86%, and the average size of recall and accuracy is 91.2% and 91.6% respectively, indicating that the method based on timing segmentation network can be close to the human judgment level and can effectively conduct the identification task of badminton video strokes.
{"title":"Badminton video action recognition based on time network","authors":"Juncai Zhi, Zijie Sun, Ruijie Zhang, Zhouxiang Zhao","doi":"10.3233/jcm-226889","DOIUrl":"https://doi.org/10.3233/jcm-226889","url":null,"abstract":"With the continuous development of artificial intelligence research, computer vision research has shifted from traditional “feature engineering”-based methods to deep learning-based “network engineering” methods, which automatically extracts and classifies features by using deep neural networks. Traditional methods based on artificial design features are computationally expensive and are usually used to solve simple research problems, which is not conducive for large-scale data feature extraction. Deep learning-based methods greatly reduce the difficulty of artificial features by learning features from large-scale data and are successfully applied in many visual recognition tasks. Video action recognition methods also shift from traditional methods based on artificial design features to deep learning-based methods, which is oriented to building more effective deep neural network models. Through collecting and sorting related research results found that academic for timing segment network of football and basketball video action research is relatively rich, but lack of badminton research given the above research results, this study based on timing segment network of badminton video action identification can enrich the research results, provide reference for follow-up research. This paper introduces the lightweight attention mechanism into the temporal segmentation network, forming the attention mechanism-timing segmentation network, and trains the neural network to get the classifier of badminton stroke action, which can be predicted as four common types: forehand stroke, backhand stroke, overhead stroke and pick ball. The experimental results show that the recognition recall and accuracy of various stroke movements reach more than 86%, and the average size of recall and accuracy is 91.2% and 91.6% respectively, indicating that the method based on timing segmentation network can be close to the human judgment level and can effectively conduct the identification task of badminton video strokes.","PeriodicalId":45004,"journal":{"name":"Journal of Computational Methods in Sciences and Engineering","volume":"23 1","pages":"2739-2752"},"PeriodicalIF":0.5,"publicationDate":"2023-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70041880","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 study aims to gain insights into the basic information and behavioral characteristics of the drug abusers and provide references for drug prevention, control, and correctional strategies. First, the python development tool was used to crawl 8494 posts from 1725 users in the forum of “Dynamic Control Bar” in the Baidu Tieba. The data were cleaned and organized. Subsequently, the content of the posts in text was analyzed using a mixture of topic model, sentiment analysis, and relevance analysis. The result of the LDA indicated that the drug abusers were concerned about the living conditions of this population in their home communities, regular checkups and management by government staff, perceived social discrimination and inconvenience of living in a restrained environment, problems they encountered when consulting with each other in terms of regular medical checkups, recollection of how they came to use drugs, as well as emotions of regret. The result of the emotional analysis indicated that this population was emotionally disturbed and had more negative emotional values, but the above values were stable. Internet information dissemination is of great significance to public opinion dissemination that can indicate the real opinions and attitudes of all social strata to drug abusers, especially the discrimination, stigmatization, and labelling of drug abusers by the general public. Disseminating content to drug abusers about their problems can help them start a new life. Furthermore, the government should guide the attitudes and emotions of this population to help them start a new, more positive life.
{"title":"Drug abusers characteristics on the online community","authors":"Zufeng Zhong","doi":"10.3233/jcm-226887","DOIUrl":"https://doi.org/10.3233/jcm-226887","url":null,"abstract":"This study aims to gain insights into the basic information and behavioral characteristics of the drug abusers and provide references for drug prevention, control, and correctional strategies. First, the python development tool was used to crawl 8494 posts from 1725 users in the forum of “Dynamic Control Bar” in the Baidu Tieba. The data were cleaned and organized. Subsequently, the content of the posts in text was analyzed using a mixture of topic model, sentiment analysis, and relevance analysis. The result of the LDA indicated that the drug abusers were concerned about the living conditions of this population in their home communities, regular checkups and management by government staff, perceived social discrimination and inconvenience of living in a restrained environment, problems they encountered when consulting with each other in terms of regular medical checkups, recollection of how they came to use drugs, as well as emotions of regret. The result of the emotional analysis indicated that this population was emotionally disturbed and had more negative emotional values, but the above values were stable. Internet information dissemination is of great significance to public opinion dissemination that can indicate the real opinions and attitudes of all social strata to drug abusers, especially the discrimination, stigmatization, and labelling of drug abusers by the general public. Disseminating content to drug abusers about their problems can help them start a new life. Furthermore, the government should guide the attitudes and emotions of this population to help them start a new, more positive life.","PeriodicalId":45004,"journal":{"name":"Journal of Computational Methods in Sciences and Engineering","volume":"23 1","pages":"2727-2737"},"PeriodicalIF":0.5,"publicationDate":"2023-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70041816","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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