Coal mine safety supervision system plays an important role in the coal mine safety management in China.However,the current supervision system is established on the basis of learning the advanced experience from other...Coal mine safety supervision system plays an important role in the coal mine safety management in China.However,the current supervision system is established on the basis of learning the advanced experience from other developed countries.It needs to be further improved according to national conditions.Therefore,the effectiveness of coal mine safety supervision system reform on three types of collieries are assessed by using time series analysis method based on comparative analysis of the supervision system before and after the reform in this paper.The regression results show that the structural reform is not conductive to the improvement of coal mine safety situation in the short term,but conductive significantly in the long term.Specifically,the effects in township coal mines are more significant than stateowned key coal mines in the long run,but negative effects also exist in the short term.The negative effects in state-owned key coal mines are non-significant compared with township coal mines.Moreover,the regression results are analyzed from the aspects of the closure policy of illegal small township coal mines at the end of 1998 and shortage of the new supervision system.Finally,the suggestions on improving the new supervision system are put forward based on the above analysis.展开更多
The ravages of COVID-19 have forced schools in countries around the world to make a temporary shift from traditional, face-to-face teaching to online teaching. Are teachers in schools prepared to deal with this change...The ravages of COVID-19 have forced schools in countries around the world to make a temporary shift from traditional, face-to-face teaching to online teaching. Are teachers in schools prepared to deal with this change? We conducted a survey in which we distributed questionnaires to primary and secondary school teachers in Guangdong Province, China, asking them about their views on various aspects of online education. We received 498,481 questionnaires back, and over 80% of teachers were satisfied with the online resources, and over 68% of teachers were satisfied with the online platform and software. Immediately afterward, we analyzed the differences between urban and rural teachers on specific issues using cross-sectional analysis and chi-square tests and built a neural network model to achieve predictions of teacher satisfaction with an accuracy of nearly 90%. Finally, we analyzed the features that influence the decisions of the neural network. This epidemic has prompted the widespread use of online learning, and the insights we gain today will be helpful in the future.展开更多
Online learning is a very important means of study, and has been adopted in many countries worldwide. However, only recently are researchers able to collect and analyze massive online learning datasets due to the COVI...Online learning is a very important means of study, and has been adopted in many countries worldwide. However, only recently are researchers able to collect and analyze massive online learning datasets due to the COVID-19 epidemic. In this article, we analyze the difference between online learner groups by using an unsupervised machine learning technique, i.e., k-prototypes clustering. Specifically, we use questionnaires designed by domain experts to collect various online learning data, and investigate students’ online learning behavior and learning outcomes through analyzing the collected questionnaire data. Our analysis results suggest that students with better learning media generally have better online learning behavior and learning result than those with poor online learning media. In addition, both in economically developed or undeveloped regions, the number of students with better learning media is less than the number of students with poor learning media. Finally, the results presented here show that whether in an economically developed or an economically undeveloped region, the number of students who are enriched with learning media available is an important factor that affects online learning behavior and learning outcomes.展开更多
The security issues of industrial control systems(ICSs)have become increasingly prevalent.As an important part of ICS security,honeypots and anti-honeypots have become the focus of offensive and defensive confrontatio...The security issues of industrial control systems(ICSs)have become increasingly prevalent.As an important part of ICS security,honeypots and anti-honeypots have become the focus of offensive and defensive confrontation.However,research on ICS honeypots still lacks breakthroughs,and it is difficult to simulate real ICS devices perfectly.In this paper,we studied ICS honeypots to identify and address their weaknesses.First,an intelligent honeypot identification framework is proposed,based on which feature data type requirements and feature data acquisition for honeypot identification is studied.Inspired by vulnerability mining,we propose a feature acquisition approach based on lightweight fuzz testing,which utilizes the differences in error handling between the ICS device and the ICS honeypot.By combining the proposed method with common feature acquisition approaches,the integrated feature data can be obtained.The experimental results show that the feature data acquired is effective for honeypot identification.展开更多
基金supported by the National Nat-ural Science Foundation Projects of China under Grant 71271206Innovation Project of Graduate Education for Jiangsu Province under Grant KYZZ_0377.
文摘Coal mine safety supervision system plays an important role in the coal mine safety management in China.However,the current supervision system is established on the basis of learning the advanced experience from other developed countries.It needs to be further improved according to national conditions.Therefore,the effectiveness of coal mine safety supervision system reform on three types of collieries are assessed by using time series analysis method based on comparative analysis of the supervision system before and after the reform in this paper.The regression results show that the structural reform is not conductive to the improvement of coal mine safety situation in the short term,but conductive significantly in the long term.Specifically,the effects in township coal mines are more significant than stateowned key coal mines in the long run,but negative effects also exist in the short term.The negative effects in state-owned key coal mines are non-significant compared with township coal mines.Moreover,the regression results are analyzed from the aspects of the closure policy of illegal small township coal mines at the end of 1998 and shortage of the new supervision system.Finally,the suggestions on improving the new supervision system are put forward based on the above analysis.
文摘The ravages of COVID-19 have forced schools in countries around the world to make a temporary shift from traditional, face-to-face teaching to online teaching. Are teachers in schools prepared to deal with this change? We conducted a survey in which we distributed questionnaires to primary and secondary school teachers in Guangdong Province, China, asking them about their views on various aspects of online education. We received 498,481 questionnaires back, and over 80% of teachers were satisfied with the online resources, and over 68% of teachers were satisfied with the online platform and software. Immediately afterward, we analyzed the differences between urban and rural teachers on specific issues using cross-sectional analysis and chi-square tests and built a neural network model to achieve predictions of teacher satisfaction with an accuracy of nearly 90%. Finally, we analyzed the features that influence the decisions of the neural network. This epidemic has prompted the widespread use of online learning, and the insights we gain today will be helpful in the future.
文摘Online learning is a very important means of study, and has been adopted in many countries worldwide. However, only recently are researchers able to collect and analyze massive online learning datasets due to the COVID-19 epidemic. In this article, we analyze the difference between online learner groups by using an unsupervised machine learning technique, i.e., k-prototypes clustering. Specifically, we use questionnaires designed by domain experts to collect various online learning data, and investigate students’ online learning behavior and learning outcomes through analyzing the collected questionnaire data. Our analysis results suggest that students with better learning media generally have better online learning behavior and learning result than those with poor online learning media. In addition, both in economically developed or undeveloped regions, the number of students with better learning media is less than the number of students with poor learning media. Finally, the results presented here show that whether in an economically developed or an economically undeveloped region, the number of students who are enriched with learning media available is an important factor that affects online learning behavior and learning outcomes.
基金This work is supported by the National Key Research and Development Plan(No.2018YFB0803504)the National Natural Science Foundation of China(Nos.61702223,61702220,61871140,61872420,61602210,U1636215)+6 种基金the Guangdong Province Key Area R&D Program of China(No.2019B010137004,2019B010136001)the Guangdong Province Universities and Colleges Pearl River Scholar Funded Scheme(2019)the Guangdong Basic and Applied Basic Research Foundation(2020A1515010450)the Science and Technology Planning Project of Guangdong(2017A040405029,2018KTSCX016,2019A050510024)the Science and Technology Planning Project of Guangzhou(201902010041)the Fundamental Research Funds for the Central Universities(21617408,21619404)the Opening Project of Shanghai Trusted Industrial Control Platform(TICPSH202003014-ZC).
文摘The security issues of industrial control systems(ICSs)have become increasingly prevalent.As an important part of ICS security,honeypots and anti-honeypots have become the focus of offensive and defensive confrontation.However,research on ICS honeypots still lacks breakthroughs,and it is difficult to simulate real ICS devices perfectly.In this paper,we studied ICS honeypots to identify and address their weaknesses.First,an intelligent honeypot identification framework is proposed,based on which feature data type requirements and feature data acquisition for honeypot identification is studied.Inspired by vulnerability mining,we propose a feature acquisition approach based on lightweight fuzz testing,which utilizes the differences in error handling between the ICS device and the ICS honeypot.By combining the proposed method with common feature acquisition approaches,the integrated feature data can be obtained.The experimental results show that the feature data acquired is effective for honeypot identification.
