In the era of digital economy,business education lags behind the rapid iteration of industrial technology,which has become the core contradiction hindering industrial development.In order to solve the key problem of t...In the era of digital economy,business education lags behind the rapid iteration of industrial technology,which has become the core contradiction hindering industrial development.In order to solve the key problem of the disconnection between education supply and industrial demand,this paper proposes the“government,industry,academia,research and dynamic iteration”education ecological framework based on the ecological niche theory and the collaborative innovation theory,and adopts the combination of model construction and case study verification research method.The framework designs a four-dimensional collaborative nurturing mechanism that includes the linkage of multiple subjects and a double-cycle dynamic adjustment model based on feedback optimization,and constructs three major systems of technical support,resource integration and quality assurance.The research effectively breaks through the traditional linear cultivation paradigm,and the validation shows that the framework can significantly improve the matching degree and dynamic adaptability of talent cultivation and industrial demand.This paper not only provides a systematic theoretical model for the construction of a new business education system adapted to the needs of the digital economy,but also contributes an operable practical path,which is of great theoretical value and practical reference significance for promoting the digital transformation of business education.展开更多
Focusing on the transformation and upgrading of the talent cultivation mode of the new business major group under the background of digitalization.Based on the systematic combing of core literature in Chinese and Engl...Focusing on the transformation and upgrading of the talent cultivation mode of the new business major group under the background of digitalization.Based on the systematic combing of core literature in Chinese and English and the empirical evidence of mixed methods,the closed-loop path of"conceptual innovation-model innovation-learning autonomy-dynamic evaluation"is constructed from the four dimensions of nurturing concept,teaching mode,learning paradigm and assessment and evaluation.The closed-loop path of"digital empowerment→concept and mode innovation→autonomous learning→multivariate evaluation"is proposed,which provides theoretical support and practical reference for vocational colleges and applied undergraduate colleges to realize the high-quality development of new business education.展开更多
With the growing emphasis on digital technologies and cultural heritage in vocational education,the effective integration of modern technologies with traditional culture has become a central focus of current pedagogic...With the growing emphasis on digital technologies and cultural heritage in vocational education,the effective integration of modern technologies with traditional culture has become a central focus of current pedagogical reforms.This study explores strategies for incorporating Web3D technology and chuanzheng culture into the“reverse engineering technology”curriculum.By leveraging Web3D technology for the digital restoration and visualization of chuanzheng culture,students can engage deeply with its historical and technical significance in a virtual environment.Furthermore,integrating chuanzheng culture into the“reverse engineering technology”course enhances the content and instructional methods,fostering students′practical skills and cultural awareness.This innovative approach enriches the curriculum,increases student engagement,and strengthens cultural identity,offering a novel teaching model for vocational education.展开更多
This study investigates the application of Artificial Intelligence Generated Content(AIGC)in vocational education through a comprehensive questionnaire survey administered to vocational education instructors in China....This study investigates the application of Artificial Intelligence Generated Content(AIGC)in vocational education through a comprehensive questionnaire survey administered to vocational education instructors in China.It examines their awareness and utilization of AIGC,exploring its primary functions in teaching and the ethical challenges encountered.The findings reveal that the majority of teachers perceive AIGC as significantly contributing to instructional design and the provision of educational resources.While teachers generally acknowledge the educational potential of AIGC technology,they also express concerns regarding ethical issues such as privacy breaches,intellectual property infringements,and unequal access to technological resources.Consequently,AIGC technology possesses substantial potential for application within vocational education.However,its implementation must be accompanied by enhanced ethical education and technical training for both educators and students to ensure that AIGC effectively supports the reform and advancement of vocational education.展开更多
VR classroom is an integrated teaching environment of content, hardware and platform. Its use is affected by the following three aspects, including price and performance of hardware equipment, cost and difficulty of c...VR classroom is an integrated teaching environment of content, hardware and platform. Its use is affected by the following three aspects, including price and performance of hardware equipment, cost and difficulty of courseware development, and quality of teaching by VR courseware. Therefore, the future development trend of in VR classroom should be the trinity of terminal+courseware+SaaS.展开更多
NC machining of parts and components is developing in the direction of automation and intelligence.In addition,the automatic production line puts forward higher requirements for the overall layout,technological proces...NC machining of parts and components is developing in the direction of automation and intelligence.In addition,the automatic production line puts forward higher requirements for the overall layout,technological process and production tempo.The layout and simulation of the production line can more directly reflect the problems that may occur in the operation of the production line,and solve these problems through scientific methods.This project uses VisualOne software to simulate the operation of the intelligent manufacturing production line,which can directly find the existing problems in the layout of the production line and the process of the craftsmen,and optimize the layout of the production line.In addition,it can provide reliable support for the equipment procurement and on-site construction of the intelligent manufacturing automation production line in the later stage.展开更多
Purpose-In order to solve the problem that the performance of the existing local feature descriptors in uncontrolled environment is greatly affected by illumination,background,occlusion and other factors,we propose a ...Purpose-In order to solve the problem that the performance of the existing local feature descriptors in uncontrolled environment is greatly affected by illumination,background,occlusion and other factors,we propose a novel face recognition algorithm in uncontrolled environment which combines the block central symmetry local binary pattern(CS-LBP)and deep residual network(DRN)model.Design/methodology/approach-The algorithm first extracts the block CSP-LBP features of the face image,then incorporates the extracted features into the DRN model,and gives the face recognition results by using a well-trained DRN model.The features obtained by the proposed algorithm have the characteristics of both local texture features and deep features that robust to illumination.Findings-Compared with the direct usage of the original image,the usage of local texture features of the image as the input of DRN model significantly improves the computation efficiency.Experimental results on the face datasets of FERET,YALE-B and CMU-PIE have shown that the recognition rate of the proposed algorithm is significantly higher than that of other compared algorithms.Originality/value-The proposed algorithm fundamentally solves the problem of face identity recognition in uncontrolled environment,and it is particularly robust to the change of illumination,which proves its superiority.展开更多
Purpose-With the rapid development and stable operated application of lithium-ion batteries used in uninterruptible power supply(UPS),the prediction of remaining useful life(RUL)for lithium-ion battery played an impor...Purpose-With the rapid development and stable operated application of lithium-ion batteries used in uninterruptible power supply(UPS),the prediction of remaining useful life(RUL)for lithium-ion battery played an important role.More and more researchers paid more attentions on the reliability and safety for lithium-ion batteries based on prediction of RUL.The purpose of this paper is to predict the life of lithium-ion battery based on auto regression and particle filter method.Design/methodology/approach-In this paper,a simple and effective RUL prediction method based on the combination method of auto-regression(AR)time-series model and particle filter(PF)was proposed for lithiumion battery.The proposed method deformed the double-exponential empirical degradation model and reduced the number of parameters for such model to improve the efficiency of training.By using the PF algorithm to track the process of lithium-ion battery capacity decline and modified observations of the state space equations,the proposed PF t AR model fully considered the declined process of batteries to meet more accurate prediction of RUL.Findings-Experiments on CALCE dataset have fully compared the conventional PF algorithm and the AR t PF algorithm both on original exponential empirical degradation model and the deformed doubleexponential one.Experimental results have shown that the proposed PFtAR method improved the prediction accuracy,decreases the error rate and reduces the uncertainty ranges of RUL,which was more suitable for the deformed double-exponential empirical degradation model.Originality/value-In the running of UPS device based on lithium-ion battery,the proposed AR t PF combination algorithm will quickly,accurately and robustly predict the RUL of lithium-ion batteries,which had a strong application value in the stable operation of laboratory and other application scenarios.展开更多
Purpose-Aiming at the shortcomings of EEG signals generated by brain’s sensorimotor region activated tasks,such as poor performance,low efficiency and weak robustness,this paper proposes an EEG signals classification...Purpose-Aiming at the shortcomings of EEG signals generated by brain’s sensorimotor region activated tasks,such as poor performance,low efficiency and weak robustness,this paper proposes an EEG signals classification method based on multi-dimensional fusion features.Design/methodology/approach-First,the improved Morlet wavelet is used to extract the spectrum feature maps from EEG signals.Then,the spatial-frequency features are extracted from the PSD maps by using the three-dimensional convolutional neural networks(3DCNNs)model.Finally,the spatial-frequency features are incorporated to the bidirectional gated recurrent units(Bi-GRUs)models to extract the spatial-frequencysequential multi-dimensional fusion features for recognition of brain’s sensorimotor region activated task.Findings-In the comparative experiments,the data sets of motor imagery(MI)/action observation(AO)/action execution(AE)tasks are selected to test the classification performance and robustness of the proposed algorithm.In addition,the impact of extracted features on the sensorimotor region and the impact on the classification processing are also analyzed by visualization during experiments.Originality/value-The experimental results show that the proposed algorithm extracts the corresponding brain activation features for different action related tasks,so as to achieve more stable classification performance in dealing with AO/MI/AE tasks,and has the best robustness on EEGsignals of different subjects.展开更多
基金supported by Fujian Provincial Vocational Education Research Project(ZJGB2024038)Fujian Provincial Education Science Planning Project(FJJKGZ24-081)Fujian Provincial Social Science Planning Project(FJ2025C048).
文摘In the era of digital economy,business education lags behind the rapid iteration of industrial technology,which has become the core contradiction hindering industrial development.In order to solve the key problem of the disconnection between education supply and industrial demand,this paper proposes the“government,industry,academia,research and dynamic iteration”education ecological framework based on the ecological niche theory and the collaborative innovation theory,and adopts the combination of model construction and case study verification research method.The framework designs a four-dimensional collaborative nurturing mechanism that includes the linkage of multiple subjects and a double-cycle dynamic adjustment model based on feedback optimization,and constructs three major systems of technical support,resource integration and quality assurance.The research effectively breaks through the traditional linear cultivation paradigm,and the validation shows that the framework can significantly improve the matching degree and dynamic adaptability of talent cultivation and industrial demand.This paper not only provides a systematic theoretical model for the construction of a new business education system adapted to the needs of the digital economy,but also contributes an operable practical path,which is of great theoretical value and practical reference significance for promoting the digital transformation of business education.
基金supported by Fujian Provincial Education Science Planning Project(FJJKGZ24-081)Fujian Provincial Vocational Education Research Project(ZJGB2024038)Fujian Provincial Social Science Planning Project(FJ2025C048)。
文摘Focusing on the transformation and upgrading of the talent cultivation mode of the new business major group under the background of digitalization.Based on the systematic combing of core literature in Chinese and English and the empirical evidence of mixed methods,the closed-loop path of"conceptual innovation-model innovation-learning autonomy-dynamic evaluation"is constructed from the four dimensions of nurturing concept,teaching mode,learning paradigm and assessment and evaluation.The closed-loop path of"digital empowerment→concept and mode innovation→autonomous learning→multivariate evaluation"is proposed,which provides theoretical support and practical reference for vocational colleges and applied undergraduate colleges to realize the high-quality development of new business education.
基金supported by Fujian Provincial Education Science‘14th Five⁃Year Plan’2023 Annual Project(FJJKGZ23⁃055)2024 Fujian Social Science Foundation Program(FJ2024B146)2023 Fujian Provincial Vocational Education Research Project(GA2023007).
文摘With the growing emphasis on digital technologies and cultural heritage in vocational education,the effective integration of modern technologies with traditional culture has become a central focus of current pedagogical reforms.This study explores strategies for incorporating Web3D technology and chuanzheng culture into the“reverse engineering technology”curriculum.By leveraging Web3D technology for the digital restoration and visualization of chuanzheng culture,students can engage deeply with its historical and technical significance in a virtual environment.Furthermore,integrating chuanzheng culture into the“reverse engineering technology”course enhances the content and instructional methods,fostering students′practical skills and cultural awareness.This innovative approach enriches the curriculum,increases student engagement,and strengthens cultural identity,offering a novel teaching model for vocational education.
基金supported by the Fujian Province Education Science "14th Five-Year Plan" 2023 Annual Project(FJJKGZ23-055)the 2023 Fujian Province Vocational Education Research Project (GA2023007)。
文摘This study investigates the application of Artificial Intelligence Generated Content(AIGC)in vocational education through a comprehensive questionnaire survey administered to vocational education instructors in China.It examines their awareness and utilization of AIGC,exploring its primary functions in teaching and the ethical challenges encountered.The findings reveal that the majority of teachers perceive AIGC as significantly contributing to instructional design and the provision of educational resources.While teachers generally acknowledge the educational potential of AIGC technology,they also express concerns regarding ethical issues such as privacy breaches,intellectual property infringements,and unequal access to technological resources.Consequently,AIGC technology possesses substantial potential for application within vocational education.However,its implementation must be accompanied by enhanced ethical education and technical training for both educators and students to ensure that AIGC effectively supports the reform and advancement of vocational education.
文摘VR classroom is an integrated teaching environment of content, hardware and platform. Its use is affected by the following three aspects, including price and performance of hardware equipment, cost and difficulty of courseware development, and quality of teaching by VR courseware. Therefore, the future development trend of in VR classroom should be the trinity of terminal+courseware+SaaS.
基金supported by 2019 Project of the 13th Five-year Plan of Fujian Education and Science(FJJKCGZ19-016)。
文摘NC machining of parts and components is developing in the direction of automation and intelligence.In addition,the automatic production line puts forward higher requirements for the overall layout,technological process and production tempo.The layout and simulation of the production line can more directly reflect the problems that may occur in the operation of the production line,and solve these problems through scientific methods.This project uses VisualOne software to simulate the operation of the intelligent manufacturing production line,which can directly find the existing problems in the layout of the production line and the process of the craftsmen,and optimize the layout of the production line.In addition,it can provide reliable support for the equipment procurement and on-site construction of the intelligent manufacturing automation production line in the later stage.
基金The education and scientific research project of young and middle-aged teachers of Fujian Provincial Department of education(No.JAT171070).
文摘Purpose-In order to solve the problem that the performance of the existing local feature descriptors in uncontrolled environment is greatly affected by illumination,background,occlusion and other factors,we propose a novel face recognition algorithm in uncontrolled environment which combines the block central symmetry local binary pattern(CS-LBP)and deep residual network(DRN)model.Design/methodology/approach-The algorithm first extracts the block CSP-LBP features of the face image,then incorporates the extracted features into the DRN model,and gives the face recognition results by using a well-trained DRN model.The features obtained by the proposed algorithm have the characteristics of both local texture features and deep features that robust to illumination.Findings-Compared with the direct usage of the original image,the usage of local texture features of the image as the input of DRN model significantly improves the computation efficiency.Experimental results on the face datasets of FERET,YALE-B and CMU-PIE have shown that the recognition rate of the proposed algorithm is significantly higher than that of other compared algorithms.Originality/value-The proposed algorithm fundamentally solves the problem of face identity recognition in uncontrolled environment,and it is particularly robust to the change of illumination,which proves its superiority.
基金This work was supported by the Fuzhou Polytechnic research foundation(No.FZYKJJJJC202001).Funding body played the roles in supporting the experiments.The author wants to thank the members of department of information and technology in Fuzhou Polytechnic for their proofreading comments.The authors are very grateful to the anonymous reviewers for their constructive comments which have helped significantly in revising this work.
文摘Purpose-With the rapid development and stable operated application of lithium-ion batteries used in uninterruptible power supply(UPS),the prediction of remaining useful life(RUL)for lithium-ion battery played an important role.More and more researchers paid more attentions on the reliability and safety for lithium-ion batteries based on prediction of RUL.The purpose of this paper is to predict the life of lithium-ion battery based on auto regression and particle filter method.Design/methodology/approach-In this paper,a simple and effective RUL prediction method based on the combination method of auto-regression(AR)time-series model and particle filter(PF)was proposed for lithiumion battery.The proposed method deformed the double-exponential empirical degradation model and reduced the number of parameters for such model to improve the efficiency of training.By using the PF algorithm to track the process of lithium-ion battery capacity decline and modified observations of the state space equations,the proposed PF t AR model fully considered the declined process of batteries to meet more accurate prediction of RUL.Findings-Experiments on CALCE dataset have fully compared the conventional PF algorithm and the AR t PF algorithm both on original exponential empirical degradation model and the deformed doubleexponential one.Experimental results have shown that the proposed PFtAR method improved the prediction accuracy,decreases the error rate and reduces the uncertainty ranges of RUL,which was more suitable for the deformed double-exponential empirical degradation model.Originality/value-In the running of UPS device based on lithium-ion battery,the proposed AR t PF combination algorithm will quickly,accurately and robustly predict the RUL of lithium-ion batteries,which had a strong application value in the stable operation of laboratory and other application scenarios.
基金The education and scientific research project of young and middle-aged teachers of Fujian provincial department of education(No.JAT171070).
文摘Purpose-Aiming at the shortcomings of EEG signals generated by brain’s sensorimotor region activated tasks,such as poor performance,low efficiency and weak robustness,this paper proposes an EEG signals classification method based on multi-dimensional fusion features.Design/methodology/approach-First,the improved Morlet wavelet is used to extract the spectrum feature maps from EEG signals.Then,the spatial-frequency features are extracted from the PSD maps by using the three-dimensional convolutional neural networks(3DCNNs)model.Finally,the spatial-frequency features are incorporated to the bidirectional gated recurrent units(Bi-GRUs)models to extract the spatial-frequencysequential multi-dimensional fusion features for recognition of brain’s sensorimotor region activated task.Findings-In the comparative experiments,the data sets of motor imagery(MI)/action observation(AO)/action execution(AE)tasks are selected to test the classification performance and robustness of the proposed algorithm.In addition,the impact of extracted features on the sensorimotor region and the impact on the classification processing are also analyzed by visualization during experiments.Originality/value-The experimental results show that the proposed algorithm extracts the corresponding brain activation features for different action related tasks,so as to achieve more stable classification performance in dealing with AO/MI/AE tasks,and has the best robustness on EEGsignals of different subjects.
