INTRODUCTION: The research on the multi-mode fusion of college students' independent learning ability cultivation method is conducive to college students' change of learning mode and learning thinking, improvement of the utilization rate of educational resources, and the development of the academic environment as well as the reform of the educational concept. OBJECTIVES: Aiming at the problems of college students' current independent learning mode, such as the need for more in-depth research and the single study means. METHODS: A method for cultivating college students' autonomous learning ability through the integration of intelligent optimization algorithms and multiple modes has been proposed. Firstly, the practices of analyzing the current college students' autonomous learning mode and multiple learning modes are analyzed; then, using the butterfly optimization algorithm, a weight optimization method for the cultivation of college students' independent learning ability based on the fusion of multiple modes is proposed; finally, the validity and robustness of the proposed method are verified through experimental analysis. RESULTS: The results show that the proposed method has a high cultivation effect. CONCLUSION: Solves the problem of fusion of college students' independent learning ability cultivation modes.
{"title":"Method of Cultivating College Students' Independent Learning Ability Based on Integration of Multiple Algorithm","authors":"Ying You","doi":"10.4108/eetsis.4492","DOIUrl":"https://doi.org/10.4108/eetsis.4492","url":null,"abstract":"INTRODUCTION: The research on the multi-mode fusion of college students' independent learning ability cultivation method is conducive to college students' change of learning mode and learning thinking, improvement of the utilization rate of educational resources, and the development of the academic environment as well as the reform of the educational concept. OBJECTIVES: Aiming at the problems of college students' current independent learning mode, such as the need for more in-depth research and the single study means. METHODS: A method for cultivating college students' autonomous learning ability through the integration of intelligent optimization algorithms and multiple modes has been proposed. Firstly, the practices of analyzing the current college students' autonomous learning mode and multiple learning modes are analyzed; then, using the butterfly optimization algorithm, a weight optimization method for the cultivation of college students' independent learning ability based on the fusion of multiple modes is proposed; finally, the validity and robustness of the proposed method are verified through experimental analysis. RESULTS: The results show that the proposed method has a high cultivation effect. CONCLUSION: Solves the problem of fusion of college students' independent learning ability cultivation modes.","PeriodicalId":502678,"journal":{"name":"ICST Transactions on Scalable Information Systems","volume":"38 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139219521","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}
INTRODUCTION: The construction of English evaluation methods in colleges and universities, as the essential part of English teaching in colleges and universities, is conducive to the improvement of the quality of English teaching in colleges and universities, which makes the existing English teaching more objective and reasonable, and makes the means of English teaching rich in science. OBJECTIVES: Aiming at the current wisdom teaching evaluation design methods exist evaluation indexes exist objectivity is not strong, accuracy is poor, single method and other problems. METHODS:Proposes a college English teaching evaluation method based on a deep learning network. First, the evaluation index system of English in colleges and universities is constructed by analyzing the principle of selecting evaluation indexes of English in colleges and universities; then, the deep learning network is improved through self-coder and integrated learning methods to construct the evaluation model of English teaching in colleges and universities; finally, the effectiveness and efficiency of the proposed method is verified through simulation experiment analysis. RESULTS: The results show that the proposed method improves the accuracy of the evaluation model. CONCLUSION: Solved the problems of low evaluation accuracy and non-objective system indexes of English teaching evaluation methods in colleges and universities.
{"title":"Application Integrated Deep Learning Networks Evaluation Methods of College English Teaching","authors":"Jie Guo","doi":"10.4108/eetsis.4494","DOIUrl":"https://doi.org/10.4108/eetsis.4494","url":null,"abstract":"INTRODUCTION: The construction of English evaluation methods in colleges and universities, as the essential part of English teaching in colleges and universities, is conducive to the improvement of the quality of English teaching in colleges and universities, which makes the existing English teaching more objective and reasonable, and makes the means of English teaching rich in science. OBJECTIVES: Aiming at the current wisdom teaching evaluation design methods exist evaluation indexes exist objectivity is not strong, accuracy is poor, single method and other problems. METHODS:Proposes a college English teaching evaluation method based on a deep learning network. First, the evaluation index system of English in colleges and universities is constructed by analyzing the principle of selecting evaluation indexes of English in colleges and universities; then, the deep learning network is improved through self-coder and integrated learning methods to construct the evaluation model of English teaching in colleges and universities; finally, the effectiveness and efficiency of the proposed method is verified through simulation experiment analysis. RESULTS: The results show that the proposed method improves the accuracy of the evaluation model. CONCLUSION: Solved the problems of low evaluation accuracy and non-objective system indexes of English teaching evaluation methods in colleges and universities.","PeriodicalId":502678,"journal":{"name":"ICST Transactions on Scalable Information Systems","volume":"46 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139225427","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}
Fang Nan, Yanan Li, Jing Zhang, Xuesong Yin, Xintong Cui
INTRODUCTION: The quality assessment technology of distance education in colleges and universities, as the critical technology for identifying the quality of distance education in colleges and universities, is conducive to the improvement of the quality of distance teaching and the progress of the existing means and methods of distance education, which makes the means of distance teaching in colleges and universities rich in science. OBJECTIVES: Aiming at the evaluation methods of higher education institutions, there are problems such as insufficient objectivity and comprehensiveness of the evaluation system, single process, and inadequate quantitative analysis. METHODS:Proposes a decision tree and intelligent optimization algorithm for the college distance teaching quality assessment method. Firstly, the kernel principal component analysis method is used to carry out dimensionality reduction analysis on the index system of college distance teaching quality assessment; then, the decision tree parameters are optimized through the marine predator algorithm to construct a college distance teaching quality assessment model; finally, the robustness and efficiency of the proposed method are verified through simulation experimental analysis. RESULTS: The results show that the proposed method improves the accuracy of the assessment model. CONCLUSION: The problem of insufficient objective and scientific evaluation and low precision of distance teaching quality assessment methods in colleges and universities is solved.
{"title":"Application of Decision Tree Classification Algorithm in Quality Assessment of Distance Learning in Colleges","authors":"Fang Nan, Yanan Li, Jing Zhang, Xuesong Yin, Xintong Cui","doi":"10.4108/eetsis.4493","DOIUrl":"https://doi.org/10.4108/eetsis.4493","url":null,"abstract":"INTRODUCTION: The quality assessment technology of distance education in colleges and universities, as the critical technology for identifying the quality of distance education in colleges and universities, is conducive to the improvement of the quality of distance teaching and the progress of the existing means and methods of distance education, which makes the means of distance teaching in colleges and universities rich in science. OBJECTIVES: Aiming at the evaluation methods of higher education institutions, there are problems such as insufficient objectivity and comprehensiveness of the evaluation system, single process, and inadequate quantitative analysis. METHODS:Proposes a decision tree and intelligent optimization algorithm for the college distance teaching quality assessment method. Firstly, the kernel principal component analysis method is used to carry out dimensionality reduction analysis on the index system of college distance teaching quality assessment; then, the decision tree parameters are optimized through the marine predator algorithm to construct a college distance teaching quality assessment model; finally, the robustness and efficiency of the proposed method are verified through simulation experimental analysis. RESULTS: The results show that the proposed method improves the accuracy of the assessment model. CONCLUSION: The problem of insufficient objective and scientific evaluation and low precision of distance teaching quality assessment methods in colleges and universities is solved.","PeriodicalId":502678,"journal":{"name":"ICST Transactions on Scalable Information Systems","volume":"19 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139226672","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}
INTRODUCTION: The construction of the wisdom teaching evaluation system, as the essential part of the institution's teaching reform, is conducive to developing the institution's disciplines, making the existing teaching more standardized, and making the means of teaching diversified, intelligent, and convenient. OBJECTIVES: Aiming at the current intelligent teaching evaluation design method, there are evaluation indexes that need to be more comprehensive, a single method, and system standard limitations. METHODS: Proposes an intelligent optimization algorithm for a multi-dimensional innovative teaching quality evaluation method. First of all, the multi-dimensional wisdom teaching evaluation system is constructed by analyzing the influencing factors of teaching quality evaluation; then, the parameters of the depth limit learning machine are optimized by the bird foraging search algorithm, and the multi-dimensional wisdom teaching evaluation model is constructed; finally, the validity and stability of the proposed method are verified by the analysis of simulation experiments. RESULTS: The results show that the proposed method improves the accuracy of the evaluation model. CONCLUSION: Solves the problem of low evaluation accuracy and incomplete system of teaching quality evaluation methods.
{"title":"Application Deep Extreme Learning Machine in Multi-dimensional Smart Teaching Quality Evaluation System","authors":"Yanan Li, Fang Nan, Hao Zhang","doi":"10.4108/eetsis.4491","DOIUrl":"https://doi.org/10.4108/eetsis.4491","url":null,"abstract":"INTRODUCTION: The construction of the wisdom teaching evaluation system, as the essential part of the institution's teaching reform, is conducive to developing the institution's disciplines, making the existing teaching more standardized, and making the means of teaching diversified, intelligent, and convenient. OBJECTIVES: Aiming at the current intelligent teaching evaluation design method, there are evaluation indexes that need to be more comprehensive, a single method, and system standard limitations. METHODS: Proposes an intelligent optimization algorithm for a multi-dimensional innovative teaching quality evaluation method. First of all, the multi-dimensional wisdom teaching evaluation system is constructed by analyzing the influencing factors of teaching quality evaluation; then, the parameters of the depth limit learning machine are optimized by the bird foraging search algorithm, and the multi-dimensional wisdom teaching evaluation model is constructed; finally, the validity and stability of the proposed method are verified by the analysis of simulation experiments. RESULTS: The results show that the proposed method improves the accuracy of the evaluation model. CONCLUSION: Solves the problem of low evaluation accuracy and incomplete system of teaching quality evaluation methods.","PeriodicalId":502678,"journal":{"name":"ICST Transactions on Scalable Information Systems","volume":"31 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139224654","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}
José Seijas-Díaz, Karla Martell, Roi Casas, Juan Schrader, Rosa Cueto-Orbe, R. Rengifo-Amasifén, Enrique Barbachán-Ruales, Cinthya Torres-Silva
INTRODUCTION: En a global context where technology is essential for the search of information and decision-making by tourists, the creation of digital platforms is a key strategy to promote sustainable tourism practices.OBJECTIVES: We aim to develop an informative web application aimed at promoting ecotourism in Lake Cuipari, using it as a case study.METHODS: The software development followed the phases established in the Agile methodology Extreme Programming: i) Exploration, ii) Planning, iii) Interactions, iv) Production, and v) Maintenance. To ensure the quality of the software product, we applied black-box testing.RESULTS: We successfully developed a functional informational web application with two panels, administrative and visitor. The web application allows users to learn about the location of Lake Cuipari, explains access conditions, and provides information about native species in and around the lake. These species are categorized into birds, amphibians, and fish, with academic, scientific, and tourist interest.CONCLUSION: The informational web application serves as a digital platform that enables the municipality and the local community to promote ecotourism in Lake Cuipari for the sake of its preservation and sustainability. This is achieved through the increased provision of information for potential tourists.
{"title":"Development of an informative web application for the promotion of ecotourism: A case study","authors":"José Seijas-Díaz, Karla Martell, Roi Casas, Juan Schrader, Rosa Cueto-Orbe, R. Rengifo-Amasifén, Enrique Barbachán-Ruales, Cinthya Torres-Silva","doi":"10.4108/eetsis.4463","DOIUrl":"https://doi.org/10.4108/eetsis.4463","url":null,"abstract":"INTRODUCTION: En a global context where technology is essential for the search of information and decision-making by tourists, the creation of digital platforms is a key strategy to promote sustainable tourism practices.OBJECTIVES: We aim to develop an informative web application aimed at promoting ecotourism in Lake Cuipari, using it as a case study.METHODS: The software development followed the phases established in the Agile methodology Extreme Programming: i) Exploration, ii) Planning, iii) Interactions, iv) Production, and v) Maintenance. To ensure the quality of the software product, we applied black-box testing.RESULTS: We successfully developed a functional informational web application with two panels, administrative and visitor. The web application allows users to learn about the location of Lake Cuipari, explains access conditions, and provides information about native species in and around the lake. These species are categorized into birds, amphibians, and fish, with academic, scientific, and tourist interest.CONCLUSION: The informational web application serves as a digital platform that enables the municipality and the local community to promote ecotourism in Lake Cuipari for the sake of its preservation and sustainability. This is achieved through the increased provision of information for potential tourists.","PeriodicalId":502678,"journal":{"name":"ICST Transactions on Scalable Information Systems","volume":"127 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139220807","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}
Jiajia Huang, Fusheng Wei, Jingming Zhao, Huakun Que
This study delves into the realm of multi-relay assisted Internet of Things (IoT) networks within the context of mixed fading environments. Here, data transmission from the source to the destination is facilitated through a configuration involving multiple decode-and-forward relays. Specifically, our investigation revolves around mixed fading environments characterized by the first-hop relaying links conforming to a uniform distribution, while the second-hop relaying links exhibit Rayleigh fading. To bolster the overall efficacy of the network, we introduce two distinct relay selection criteria. The first criterion entails an optimal selection process hinging on the identification of the most proficient relay. This determination relies upon the evaluation of dual-hop relaying links. In contrast, the second criterion adopts a sub-optimal selection approach by singling out the optimal relay solely based on characteristics associated with the second-hop relaying links. The performance evaluation of the two aforementioned relay selection criteria entails the derivation of analytical expressions governing the system's outage probability. To validate the theoretical underpinnings presented in this research, we supplement our analysis with simulation results. Notably, our findings underscore the efficacy of augmenting network performance by augmenting the number of relays within the network topology.
{"title":"Performance Analysis of Multi-Relay Assisted IoT Networks in Mixed Fading Environments","authors":"Jiajia Huang, Fusheng Wei, Jingming Zhao, Huakun Que","doi":"10.4108/eetsis.3798","DOIUrl":"https://doi.org/10.4108/eetsis.3798","url":null,"abstract":"This study delves into the realm of multi-relay assisted Internet of Things (IoT) networks within the context of mixed fading environments. Here, data transmission from the source to the destination is facilitated through a configuration involving multiple decode-and-forward relays. Specifically, our investigation revolves around mixed fading environments characterized by the first-hop relaying links conforming to a uniform distribution, while the second-hop relaying links exhibit Rayleigh fading. To bolster the overall efficacy of the network, we introduce two distinct relay selection criteria. The first criterion entails an optimal selection process hinging on the identification of the most proficient relay. This determination relies upon the evaluation of dual-hop relaying links. In contrast, the second criterion adopts a sub-optimal selection approach by singling out the optimal relay solely based on characteristics associated with the second-hop relaying links. The performance evaluation of the two aforementioned relay selection criteria entails the derivation of analytical expressions governing the system's outage probability. To validate the theoretical underpinnings presented in this research, we supplement our analysis with simulation results. Notably, our findings underscore the efficacy of augmenting network performance by augmenting the number of relays within the network topology.","PeriodicalId":502678,"journal":{"name":"ICST Transactions on Scalable Information Systems","volume":"51 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139247255","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}
INTRODUCTION: Teachers are human resources who play an important and strategic role in the success of learning so they must fulfill adequate competencies. Teachers with low competence will not be able to produce students who excel both academically and non-academically. Efforts to improve teacher competency include education and training. OBJECTIVE: This research aims to see how information and communication technology is used in developing teachers' pedagogical and professional competencies. METHODS: This research was carried out using a descriptive qualitative approach. The data used in this research was obtained from various relevant sources. RESULTS: The results of this research found that increasing teacher pedagogical and professional competence through the integration of Information and Communication Technology (ICT) and scalable management strategies opens up new perspectives on the importance of investing in the development of teaching staff. CONCLUSION: The alignment of modern pedagogical approaches with the use of technology and efficient management strategies allows teachers to develop as more effective and competitive educators. Increasing pedagogical competence allows educators to create more dynamic and relevant learning environments for students. By incorporating innovative teaching methods, such as the use of digital tools and resources, teachers can adapt learning to students' diverse learning styles.
{"title":"Utilizing Information and Communication Technology in Scalable Management Strategies for Teacher Development","authors":"Ajat Rukajat, Iwan Nugraha Gusniar, Totoh Tauhidin Abas, Ervin Nurkhalizah, Rizal Bachruddin","doi":"10.4108/eetsis.4444","DOIUrl":"https://doi.org/10.4108/eetsis.4444","url":null,"abstract":"INTRODUCTION: Teachers are human resources who play an important and strategic role in the success of learning so they must fulfill adequate competencies. Teachers with low competence will not be able to produce students who excel both academically and non-academically. Efforts to improve teacher competency include education and training. OBJECTIVE: This research aims to see how information and communication technology is used in developing teachers' pedagogical and professional competencies. METHODS: This research was carried out using a descriptive qualitative approach. The data used in this research was obtained from various relevant sources. RESULTS: The results of this research found that increasing teacher pedagogical and professional competence through the integration of Information and Communication Technology (ICT) and scalable management strategies opens up new perspectives on the importance of investing in the development of teaching staff. CONCLUSION: The alignment of modern pedagogical approaches with the use of technology and efficient management strategies allows teachers to develop as more effective and competitive educators. Increasing pedagogical competence allows educators to create more dynamic and relevant learning environments for students. By incorporating innovative teaching methods, such as the use of digital tools and resources, teachers can adapt learning to students' diverse learning styles.","PeriodicalId":502678,"journal":{"name":"ICST Transactions on Scalable Information Systems","volume":"88 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139247754","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}
In today's world of value and improved investments, financial analysis has become a difficult task. The implementation of recurrent neural networks (RNN) and long short-term memory (LSTM) cells for stock market forecasting using time series of historical portfolio stock data is demonstrated in this study. In this study, we applied LSTM to predict stock market values using Yahoo Finance data along with Python modules Pandas and Matplotlib to evaluate the performance of the model. Our results show that the LSTM model is able to make accurate predictions of stock market prices and trends using historical data. The results of the correlation study showed a significant relationship between the daily return and the closing price of four randomly chosen companies. Overall, using LSTM, Yahoo Finance, Python Pandas, and Matplotlib modules to predict stock prices and provide useful information to investors was a successful strategy.
{"title":"Stock Market Analysis using Long Short-Term Model","authors":"Pulkit Gupta, Suhani Malik, Kumar Apoorb, Syed Mahammed Sameer, Vivek Vardhan, P. Ragam","doi":"10.4108/eetsis.4446","DOIUrl":"https://doi.org/10.4108/eetsis.4446","url":null,"abstract":"In today's world of value and improved investments, financial analysis has become a difficult task. The implementation of recurrent neural networks (RNN) and long short-term memory (LSTM) cells for stock market forecasting using time series of historical portfolio stock data is demonstrated in this study. In this study, we applied LSTM to predict stock market values using Yahoo Finance data along with Python modules Pandas and Matplotlib to evaluate the performance of the model. Our results show that the LSTM model is able to make accurate predictions of stock market prices and trends using historical data. The results of the correlation study showed a significant relationship between the daily return and the closing price of four randomly chosen companies. Overall, using LSTM, Yahoo Finance, Python Pandas, and Matplotlib modules to predict stock prices and provide useful information to investors was a successful strategy.","PeriodicalId":502678,"journal":{"name":"ICST Transactions on Scalable Information Systems","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139248376","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}
INTRODUCTION: The quality of ideological and political competence in colleges and universities is crucial to cultivating socialist builders and successors with all-round development of morality, intelligence, physical fitness, and aesthetics. OBJECTIVES: To scientifically evaluate the capacity of ideological and political competence in colleges and universities, adopt the evaluation method based on gray correlation entropy in AI to construct a complete indicator system that comprehensively reflects multiple aspects of ideological and political competence in colleges and universities. METHODS: By quantitatively analyzing the indicators and comprehensively considering the weights and degree of correlation of the hands, the evaluation results of the ideological and political competence capacity of colleges and universities can be derived, and this method can objectively and scientifically assess the strengths and weaknesses of the ideological and political competence capacity of colleges and universities and provide colleges and universities with the basis for improving and optimizing ideological and political competence. RESULTS: The evaluation method based on gray correlation entropy in the context of AI helps to improve the quality and effect of ideological and political competence in colleges and universities and promotes the overall improvement of students' ideological and political quality, as seen through the analysis of examples. CONCLUSION: The evaluation method also provides new ideas and plans for the research of the ideological and political competence capacity of colleges and universities, which has strong feasibility and practicality and offers colleges and universities the basis for the scientific evaluation of ideological and political competence, which helps to improve the quality and level of ideological and political competence in colleges and universities.
{"title":"Application of Big Data Technology to Evaluate Gray Correlation Entropy in higher Education Sector","authors":"Limei Wang","doi":"10.4108/eetsis.4448","DOIUrl":"https://doi.org/10.4108/eetsis.4448","url":null,"abstract":"INTRODUCTION: The quality of ideological and political competence in colleges and universities is crucial to cultivating socialist builders and successors with all-round development of morality, intelligence, physical fitness, and aesthetics. OBJECTIVES: To scientifically evaluate the capacity of ideological and political competence in colleges and universities, adopt the evaluation method based on gray correlation entropy in AI to construct a complete indicator system that comprehensively reflects multiple aspects of ideological and political competence in colleges and universities. METHODS: By quantitatively analyzing the indicators and comprehensively considering the weights and degree of correlation of the hands, the evaluation results of the ideological and political competence capacity of colleges and universities can be derived, and this method can objectively and scientifically assess the strengths and weaknesses of the ideological and political competence capacity of colleges and universities and provide colleges and universities with the basis for improving and optimizing ideological and political competence. RESULTS: The evaluation method based on gray correlation entropy in the context of AI helps to improve the quality and effect of ideological and political competence in colleges and universities and promotes the overall improvement of students' ideological and political quality, as seen through the analysis of examples. CONCLUSION: The evaluation method also provides new ideas and plans for the research of the ideological and political competence capacity of colleges and universities, which has strong feasibility and practicality and offers colleges and universities the basis for the scientific evaluation of ideological and political competence, which helps to improve the quality and level of ideological and political competence in colleges and universities.","PeriodicalId":502678,"journal":{"name":"ICST Transactions on Scalable Information Systems","volume":"12 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139246390","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}
Function inlining is a critical optimization technique used by compilers to improve program performance by replacing a function call with the body of the function and eliminating the overhead associated with function calls. However, the decision of when to inline functions and when not to is a nontrivial problem due to interactions with the rest of the compiler pipeline. Incorrect inlining decisions can cause runtime performance degradation, making this problem a crucial one to study. This paper reviews the different techniques used to optimize function inlining, including simple textual substitution, profile-guided inlining, interprocedural optimization, partial inlining, speculative inlining, and advanced techniques such as indirect call optimizations. Each technique has its strengths, weaknesses, and trade-offs, and ongoing research is exploring ways to overcome these challenges. Optimizing function inlining is a complex problem, and different techniques offer different tradeoffs. Further research to improve the performance of function inlining while minimizing any potential drawbacks could be pursued based on this paper.
{"title":"Techniques and Trade-Offs in Function Inlining Optimization","authors":"Priya Gupta, Aditya Jha, Brinda Gupta, Kime Sumpi, Sabyasachi Sahoo, Mukkoti Maruthi Venkata Chalapathi","doi":"10.4108/eetsis.4453","DOIUrl":"https://doi.org/10.4108/eetsis.4453","url":null,"abstract":"Function inlining is a critical optimization technique used by compilers to improve program performance by replacing a function call with the body of the function and eliminating the overhead associated with function calls. However, the decision of when to inline functions and when not to is a nontrivial problem due to interactions with the rest of the compiler pipeline. Incorrect inlining decisions can cause runtime performance degradation, making this problem a crucial one to study. This paper reviews the different techniques used to optimize function inlining, including simple textual substitution, profile-guided inlining, interprocedural optimization, partial inlining, speculative inlining, and advanced techniques such as indirect call optimizations. Each technique has its strengths, weaknesses, and trade-offs, and ongoing research is exploring ways to overcome these challenges. Optimizing function inlining is a complex problem, and different techniques offer different tradeoffs. Further research to improve the performance of function inlining while minimizing any potential drawbacks could be pursued based on this paper.","PeriodicalId":502678,"journal":{"name":"ICST Transactions on Scalable Information Systems","volume":"189 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139250535","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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