According to the standards of engineering education accreditation,the achievement paths and evaluation criteria of course goals are presented,aimed at the objectives of software engineering courses and the characteris...According to the standards of engineering education accreditation,the achievement paths and evaluation criteria of course goals are presented,aimed at the objectives of software engineering courses and the characteristics of hybrid teaching in Kunming University of Science and Technology.Then a multi-dimensional evaluation system for course goal achievement of software engineering is proposed.The practice’s results show that the multi-dimensional course goal achievement evaluation is helpful to the continuous improvement of course teaching,which can effectively support the evaluation of graduation outcomes.展开更多
Currently,data security and privacy protection are becoming more and more important.Access control is a method of authorization for users through predefined policies.Token-based access control(TBAC)enhances the manage...Currently,data security and privacy protection are becoming more and more important.Access control is a method of authorization for users through predefined policies.Token-based access control(TBAC)enhances the manageability of authorization through the token.However,traditional access control policies lack the ability to dynamically adjust based on user access behavior.Incorporating user reputation evaluation into access control can provide valuable feedback to enhance system security and flexibility.As a result,this paper proposes a blockchain-empowered TBAC system and introduces a user reputation evaluation module to provide feedback on access control.The TBAC system divides the access control process into three stages:policy upload,token request,and resource request.The user reputation evaluation module evaluates the user’s token reputation and resource reputation for the token request and resource request stages of the TBAC system.The proposed system is implemented using the Hyperledger Fabric blockchain.The TBAC system is evaluated to prove that it has high processing performance.The user reputation evaluation model is proved to be more conservative and sensitive by comparative study with other methods.In addition,the security analysis shows that the TBAC system has a certain anti-attack ability and can maintain stable operation under the Distributed Denial of Service(DDoS)attack environment.展开更多
Teaching involves finding out about students'misunderstandings,intervening to change them and creating a context of learning that encourages students to engage with the subject matter.This theory of making student...Teaching involves finding out about students'misunderstandings,intervening to change them and creating a context of learning that encourages students to engage with the subject matter.This theory of making student learning possible is very much concerned with the content of what students have to learn in relation to how it should be taught.Evaluation implies collecting information about our work,interpreting the information and making judgments about which actions we should take to improve practice.Evaluation is an analytical process that is intrinsic to good teaching.展开更多
The study constructed a multi-dimensional feedback mode integrating teacher feedback, peer feedback and network feedback, and applied it in the teaching of College English Writing. After 16 weeks of teaching, the stud...The study constructed a multi-dimensional feedback mode integrating teacher feedback, peer feedback and network feedback, and applied it in the teaching of College English Writing. After 16 weeks of teaching, the students in the multi-dimen-sional feedback class had significantly better overall writing scores than those in the teacher-feedback class. In terms of individual scores, multi-dimensional feedback played a better role in improving vocabulary and grammar than the class using teacher feed-back. However, there were no significant differences in the responses of writing tasks, coherence and cohesion. The study showed that most students were satisfied with the mode, believing that it was helpful to relieve writing anxiety, stimulate writing interest and improve their writing level.展开更多
Sentiment analysis attracts the attention of Egyptian Decisionmakers in the education sector.It offers a viable method to assess education quality services based on the students’feedback as well as that provides an u...Sentiment analysis attracts the attention of Egyptian Decisionmakers in the education sector.It offers a viable method to assess education quality services based on the students’feedback as well as that provides an understanding of their needs.As machine learning techniques offer automated strategies to process big data derived from social media and other digital channels,this research uses a dataset for tweets’sentiments to assess a few machine learning techniques.After dataset preprocessing to remove symbols,necessary stemming and lemmatization is performed for features extraction.This is followed by several machine learning techniques and a proposed Long Short-Term Memory(LSTM)classifier optimized by the Salp Swarm Algorithm(SSA)and measured the corresponding performance.Then,the validity and accuracy of commonly used classifiers,such as Support Vector Machine,Logistic Regression Classifier,and Naive Bayes classifier,were reviewed.Moreover,LSTM based on the SSA classification model was compared with Support Vector Machine(SVM),Logistic Regression(LR),and Naive Bayes(NB).Finally,as LSTM based SSA achieved the highest accuracy,it was applied to predict the sentiments of students’feedback and evaluate their association with the course outcome evaluations for education quality purposes.展开更多
Thermal processes on the Tibetan Plateau(TP)influence atmospheric conditions on regional and global scales.Given this,previous work has shown that soil moisture−driven surface flux variations feed back onto the atmosp...Thermal processes on the Tibetan Plateau(TP)influence atmospheric conditions on regional and global scales.Given this,previous work has shown that soil moisture−driven surface flux variations feed back onto the atmosphere.Whilst soil moisture is a source of atmospheric predictability,no study has evaluated soil moisture−atmosphere coupling on the TP in general circulation models(GCMs).In this study,we use several analysis techniques to assess soil moisture−atmosphere coupling in CMIP6 simulations including:instantaneous coupling indices;analysis of flux and atmospheric behaviour during dry spells;and a quantification of the preference for convection over drier soils.Through these metrics we partition feedbacks into their atmospheric and terrestrial components.Consistent with previous global studies,we conclude substantial inter-model differences in the representation of soil moisture−atmosphere coupling,and that most models underestimate such feedbacks.Focusing on dry spell analysis,most models underestimate increased sensible heat during periods of rainfall deficiency.For example,the model-mean bias in anomalous sensible heat flux is 10 W m−2(≈25%)smaller compared to observations.Deficient dry-spell sensible heat fluxes lead to a weaker atmospheric response.We also find that most GCMs fail to capture the negative feedback between soil moisture and deep convection.The poor simulation of feedbacks in CMIP6 experiments suggests that forecast models also struggle to exploit soil moisture−driven predictability.To improve the representation of land−atmosphere feedbacks requires developments in not only atmospheric modelling,but also surface processes,as we find weak relationships between rainfall biases and coupling indexes.展开更多
社会飞速发展,人类对健康生活的追求给予了环境新的价值和意义,环境的健康效益被深度挖掘。本文利用Citespace可视化分析工具,基于Web of Science数据库的346篇文献和中国知网166篇文献,从环境和需求两个角度梳理恢复性环境基础理论及概...社会飞速发展,人类对健康生活的追求给予了环境新的价值和意义,环境的健康效益被深度挖掘。本文利用Citespace可视化分析工具,基于Web of Science数据库的346篇文献和中国知网166篇文献,从环境和需求两个角度梳理恢复性环境基础理论及概念,分类总结研究内容和研究热点,比较分析实证研究中的材料呈现、被试筛选及实验方法。最后,针对研究内容和实验流程进行深入探讨,挖掘恢复性环境研究的新内容,思考有关样本量有效性、前期施压程度及首位效应等实验中的关键问题,以期为后续恢复性环境的实证研究提供有力参考,作为循证设计与实践结合的科学指导。展开更多
基金supported by the Undergraduate Education and Teaching Reform Research Project of Yunnan Province(JG2023157)Support Program for Yunnan Talents(CA23138L010A)+2 种基金Yunnan Higher Education Undergraduate Teaching Achievement Project(202246)National First class Undergraduate Course Construction Project of Software Engineering(109620210004)Software Engineering Virtual Teaching and Research Office Construction Project of Kunming University of Science and Technology(109620220031)。
文摘According to the standards of engineering education accreditation,the achievement paths and evaluation criteria of course goals are presented,aimed at the objectives of software engineering courses and the characteristics of hybrid teaching in Kunming University of Science and Technology.Then a multi-dimensional evaluation system for course goal achievement of software engineering is proposed.The practice’s results show that the multi-dimensional course goal achievement evaluation is helpful to the continuous improvement of course teaching,which can effectively support the evaluation of graduation outcomes.
基金supported by NSFC under Grant No.62341102National Key R&D Program of China under Grant No.2018YFA0701604.
文摘Currently,data security and privacy protection are becoming more and more important.Access control is a method of authorization for users through predefined policies.Token-based access control(TBAC)enhances the manageability of authorization through the token.However,traditional access control policies lack the ability to dynamically adjust based on user access behavior.Incorporating user reputation evaluation into access control can provide valuable feedback to enhance system security and flexibility.As a result,this paper proposes a blockchain-empowered TBAC system and introduces a user reputation evaluation module to provide feedback on access control.The TBAC system divides the access control process into three stages:policy upload,token request,and resource request.The user reputation evaluation module evaluates the user’s token reputation and resource reputation for the token request and resource request stages of the TBAC system.The proposed system is implemented using the Hyperledger Fabric blockchain.The TBAC system is evaluated to prove that it has high processing performance.The user reputation evaluation model is proved to be more conservative and sensitive by comparative study with other methods.In addition,the security analysis shows that the TBAC system has a certain anti-attack ability and can maintain stable operation under the Distributed Denial of Service(DDoS)attack environment.
文摘Teaching involves finding out about students'misunderstandings,intervening to change them and creating a context of learning that encourages students to engage with the subject matter.This theory of making student learning possible is very much concerned with the content of what students have to learn in relation to how it should be taught.Evaluation implies collecting information about our work,interpreting the information and making judgments about which actions we should take to improve practice.Evaluation is an analytical process that is intrinsic to good teaching.
文摘The study constructed a multi-dimensional feedback mode integrating teacher feedback, peer feedback and network feedback, and applied it in the teaching of College English Writing. After 16 weeks of teaching, the students in the multi-dimen-sional feedback class had significantly better overall writing scores than those in the teacher-feedback class. In terms of individual scores, multi-dimensional feedback played a better role in improving vocabulary and grammar than the class using teacher feed-back. However, there were no significant differences in the responses of writing tasks, coherence and cohesion. The study showed that most students were satisfied with the mode, believing that it was helpful to relieve writing anxiety, stimulate writing interest and improve their writing level.
文摘Sentiment analysis attracts the attention of Egyptian Decisionmakers in the education sector.It offers a viable method to assess education quality services based on the students’feedback as well as that provides an understanding of their needs.As machine learning techniques offer automated strategies to process big data derived from social media and other digital channels,this research uses a dataset for tweets’sentiments to assess a few machine learning techniques.After dataset preprocessing to remove symbols,necessary stemming and lemmatization is performed for features extraction.This is followed by several machine learning techniques and a proposed Long Short-Term Memory(LSTM)classifier optimized by the Salp Swarm Algorithm(SSA)and measured the corresponding performance.Then,the validity and accuracy of commonly used classifiers,such as Support Vector Machine,Logistic Regression Classifier,and Naive Bayes classifier,were reviewed.Moreover,LSTM based on the SSA classification model was compared with Support Vector Machine(SVM),Logistic Regression(LR),and Naive Bayes(NB).Finally,as LSTM based SSA achieved the highest accuracy,it was applied to predict the sentiments of students’feedback and evaluate their association with the course outcome evaluations for education quality purposes.
基金supported by the UK-China Research Innovation Partnership Fund through the Met Office Climate Science for Service Partnership (CSSP) China as part of the Newton Fundsupported by the Natural Environment Research Council as part of the NC-International programme (NE/X006247/1) delivering National Capability
文摘Thermal processes on the Tibetan Plateau(TP)influence atmospheric conditions on regional and global scales.Given this,previous work has shown that soil moisture−driven surface flux variations feed back onto the atmosphere.Whilst soil moisture is a source of atmospheric predictability,no study has evaluated soil moisture−atmosphere coupling on the TP in general circulation models(GCMs).In this study,we use several analysis techniques to assess soil moisture−atmosphere coupling in CMIP6 simulations including:instantaneous coupling indices;analysis of flux and atmospheric behaviour during dry spells;and a quantification of the preference for convection over drier soils.Through these metrics we partition feedbacks into their atmospheric and terrestrial components.Consistent with previous global studies,we conclude substantial inter-model differences in the representation of soil moisture−atmosphere coupling,and that most models underestimate such feedbacks.Focusing on dry spell analysis,most models underestimate increased sensible heat during periods of rainfall deficiency.For example,the model-mean bias in anomalous sensible heat flux is 10 W m−2(≈25%)smaller compared to observations.Deficient dry-spell sensible heat fluxes lead to a weaker atmospheric response.We also find that most GCMs fail to capture the negative feedback between soil moisture and deep convection.The poor simulation of feedbacks in CMIP6 experiments suggests that forecast models also struggle to exploit soil moisture−driven predictability.To improve the representation of land−atmosphere feedbacks requires developments in not only atmospheric modelling,but also surface processes,as we find weak relationships between rainfall biases and coupling indexes.
文摘社会飞速发展,人类对健康生活的追求给予了环境新的价值和意义,环境的健康效益被深度挖掘。本文利用Citespace可视化分析工具,基于Web of Science数据库的346篇文献和中国知网166篇文献,从环境和需求两个角度梳理恢复性环境基础理论及概念,分类总结研究内容和研究热点,比较分析实证研究中的材料呈现、被试筛选及实验方法。最后,针对研究内容和实验流程进行深入探讨,挖掘恢复性环境研究的新内容,思考有关样本量有效性、前期施压程度及首位效应等实验中的关键问题,以期为后续恢复性环境的实证研究提供有力参考,作为循证设计与实践结合的科学指导。