Based on the complexity and regional differences of the political,economic,and cultural environments of countries along the“Belt and Road,”this paper analyzes the new characteristics of the current demand for busine...Based on the complexity and regional differences of the political,economic,and cultural environments of countries along the“Belt and Road,”this paper analyzes the new characteristics of the current demand for business English talents.Combining this with the existing problems in China’s current training models,it proposes a reform path for talent training models that are adapted to the construction of the“Belt and Road”Initiative.The aim is to provide theoretical references and practical guidance for enhancing the international competitiveness of business English talents.展开更多
Sentiment analysis,a cornerstone of natural language processing,has witnessed remarkable advancements driven by deep learning models which demonstrated impressive accuracy in discerning sentiment from text across vari...Sentiment analysis,a cornerstone of natural language processing,has witnessed remarkable advancements driven by deep learning models which demonstrated impressive accuracy in discerning sentiment from text across various domains.However,the deployment of such models in resource-constrained environments presents a unique set of challenges that require innovative solutions.Resource-constrained environments encompass scenarios where computing resources,memory,and energy availability are restricted.To empower sentiment analysis in resource-constrained environments,we address the crucial need by leveraging lightweight pre-trained models.These models,derived from popular architectures such as DistilBERT,MobileBERT,ALBERT,TinyBERT,ELECTRA,and SqueezeBERT,offer a promising solution to the resource limitations imposed by these environments.By distilling the knowledge from larger models into smaller ones and employing various optimization techniques,these lightweight models aim to strike a balance between performance and resource efficiency.This paper endeavors to explore the performance of multiple lightweight pre-trained models in sentiment analysis tasks specific to such environments and provide insights into their viability for practical deployment.展开更多
The purpose of this study is to comprehensively evaluate the modern training model of rehabilitation therapy technology talents.Selecting the third-year students of the rehabilitation therapy technology program in Sch...The purpose of this study is to comprehensively evaluate the modern training model of rehabilitation therapy technology talents.Selecting the third-year students of the rehabilitation therapy technology program in School Y as the research subject,300 questionnaires were collected and the effective response rate was 92%.The strengths and weaknesses of the modern training model were analyzed through a mixed qualitative and quantitative research method.It was found that 68%of the students thought that the modern model had obvious advantages in practical teaching,but 42%of the students thought that it still needed to be improved in personalized teaching.This study provides an empirical basis and specific suggestions for optimizing the cultivation of rehabilitation therapy technology talents.展开更多
Objective:To explore and analyze the work process-based practical training teaching model for basic nursing skills in vocational colleges and its implementation effects.Methods:A total of 82 nursing students from our ...Objective:To explore and analyze the work process-based practical training teaching model for basic nursing skills in vocational colleges and its implementation effects.Methods:A total of 82 nursing students from our school were selected for the study,which was conducted from April 2023 to April 2024.Using a random number table method,the students were divided into an observation group and a control group,each with 41 students.The control group received conventional practical training teaching,while the observation group followed the work process-based practical training model for basic nursing skills.The assessment scores and teaching satisfaction of the two groups were compared.Results:The comparison of assessment scores showed that the observation group performed significantly better than the control group(P<0.05).The comparison of teaching satisfaction also indicated that the observation group had significantly higher satisfaction than the control group(P<0.05).Conclusion:The work process-based practical training teaching model for basic nursing skills in vocational colleges can improve students’assessment scores and enhance teaching satisfaction,demonstrating its value for wider application.展开更多
Leveraging the Baidu Qianfan model platform,this paper designs and implements a highly efficient and accurate scoring system for subjective questions,focusing primarily on questions in the field of computer network te...Leveraging the Baidu Qianfan model platform,this paper designs and implements a highly efficient and accurate scoring system for subjective questions,focusing primarily on questions in the field of computer network technology.The system enhances the foundational model by utilizing Qianfan’s training tools and integrating advanced techniques,such as supervised fine-tuning.In the data preparation phase,a comprehensive collection of subjective data related to computer network technology is gathered,cleaned,and labeled.During model training and evaluation,optimal hyperparameters and tuning strategies are applied,resulting in a model capable of scoring with high accuracy.Evaluation results demonstrate that the proposed model performs well across multiple dimensions-content,expression,and development scores-yielding results comparable to those of manual scoring.展开更多
A robust parameter identification method based on Kiencke model was proposed to solve the problem of the parameter identification accuracy being affected by the rail environment change and noise interference for heavy...A robust parameter identification method based on Kiencke model was proposed to solve the problem of the parameter identification accuracy being affected by the rail environment change and noise interference for heavy-duty trains. Firstly, a Kiencke stick-creep identification model was constructed, and the parameter identification task was transformed into a quadratic programming problem. Secondly, an iterative algorithm was constructed to solve the problem, into which a time-varying forgetting factor was added to track the change of the rail environment, and to solve the uncertainty problem of the wheel-rail environment. The Granger causality test was adopted to detect the interference, and then the weights of the current data were redistributed to solve the problem of noise interference in parameter identification. Finally, simulations were carried out and the results showed that the proposed method could track the change of the track environment in time, reduce the noise interference in the identification process, and effectively identify the adhesion performance parameters.展开更多
Purpose-With the rapid advancement of China’s high-speed rail network,the density of train operations is on the rise.To address the challenge of shortening train tracking intervals while enhancing transportation effi...Purpose-With the rapid advancement of China’s high-speed rail network,the density of train operations is on the rise.To address the challenge of shortening train tracking intervals while enhancing transportation efficiency,the multi-objective dynamic optimization of the train operation process has emerged as a critical issue.Design/methodology/approach-Train dynamic model is established by analyzing the force of the train in the process of tracing operation.The train tracing operation model is established according to the dynamic mechanical model of the train tracking process,and the dynamic optimization analysis is carried out with comfort,energy saving and punctuality as optimization objectives.To achieve multi-objective dynamic optimization,a novel train tracking operation calculation method is proposed,utilizing the improved grey wolf optimization algorithm(MOGWO).The proposed method is simulated and verified based on the train characteristics and line data of CR400AF electric multiple units.Findings-The simulation results prove that the optimized MOGWO algorithm can be computed quickly during train tracks,the optimum results can be given within 5s and the algorithm can converge effectively in different optimization target directions.The optimized speed profile of the MOGWO algorithm is smoother and more stable and meets the target requirements of energy saving,punctuality and comfort while maximally respecting the speed limit profile.Originality/value-The MOGWO train tracking interval optimization method enhances the tracking process while ensuring a safe tracking interval.This approach enables the trailing train to operate more comfortably,energy-efficiently and punctually,aligning with passenger needs and industry trends.The method offers valuable insights for optimizing the high-speed train tracking process.展开更多
To cultivate new professional farmers is a key way for rural labor development, resolving existing problems such as how to farming. It is notable that government and market take advantages in training of new professio...To cultivate new professional farmers is a key way for rural labor development, resolving existing problems such as how to farming. It is notable that government and market take advantages in training of new professional farmers. Therefore, it is necessary to guarantee government and market playing the roles. The research explored market-oriented farmer training model and the characteristics and investigated training routes for new professional farmers.展开更多
加快发展现代高等职业教育,既有利于缓解当前就业压力,也是解决高技能人才短缺的战略之举。现代职场对有英语应用能力要求的岗位越来越多,一些专业技能强的学生由于无法满足用人单位在英语应用能力上的要求而与理想岗位失之交臂的情况...加快发展现代高等职业教育,既有利于缓解当前就业压力,也是解决高技能人才短缺的战略之举。现代职场对有英语应用能力要求的岗位越来越多,一些专业技能强的学生由于无法满足用人单位在英语应用能力上的要求而与理想岗位失之交臂的情况时有发生。为改变这样的现状、提高学生的英语实际应用能力,开展基于ADDIE Training Model的高职英语课程教学实践与应用研究,并将试验效果与02O教学活动和传统的"讲授型"教学活动效果进行对比分析。展开更多
Abstract： Innovation is a process of taking an original idea and converting it into a business value, in which the engineers face some inventive problems which can be solved hardly by experience. TRIZ, as a new theor...Abstract： Innovation is a process of taking an original idea and converting it into a business value, in which the engineers face some inventive problems which can be solved hardly by experience. TRIZ, as a new theory for companies in China, provides both conceptual and procedural knowledge for finding and solving inventive problems. Because the government plays a leading role in the diffusion of TRIZ, too many companies from different industries are waiting to be trained, but the quantity of the trainers mastering TRIZ is incompatible with that requirement. In this context, to improve the training effect, an interactive training model of TRIZ for the mechanical engineers in China is developed and the implementation in the form of training classes is carried out. The training process is divided into 6 phases as follows： selecting engineers, training stage-l, finding problems, training stage-2, finding solutions and summing up. The government, TRIZ institutions and companies to join the programs interact during the process. The government initiates and monitors a project in form of a training class of TRIZ and selects companies to join the programs. Each selected companies choose a few engineers to join the class and supervises the training result. The TRIZ institutions design the training courses and carry out training curriculum. With the beginning of the class, an effective communication channel is established by means of interview, discussion face to face, E-mail, QQ and so on. After two years training practices, the results show that innovative abilities of the engineers to join and pass the final examinations increased distinctly, and most of companies joined the training class have taken congnizance of the power of TRIZ for product innovation. This research proposes an interactive training model of TRIZ for mechanical engineers in China to expedite the knowledge diffusion of TRIZ.展开更多
This study proposes the use of the MERISE conceptual data model to create indicators for monitoring and evaluating the effectiveness of vocational training in the Republic of Congo. The importance of MERISE for struct...This study proposes the use of the MERISE conceptual data model to create indicators for monitoring and evaluating the effectiveness of vocational training in the Republic of Congo. The importance of MERISE for structuring and analyzing data is underlined, as it enables the measurement of the adequacy between training and the needs of the labor market. The innovation of the study lies in the adaptation of the MERISE model to the local context, the development of innovative indicators, and the integration of a participatory approach including all relevant stakeholders. Contextual adaptation and local innovation: The study suggests adapting MERISE to the specific context of the Republic of Congo, considering the local particularities of the labor market. Development of innovative indicators and new measurement tools: It proposes creating indicators to assess skills matching and employer satisfaction, which are crucial for evaluating the effectiveness of vocational training. Participatory approach and inclusion of stakeholders: The study emphasizes actively involving training centers, employers, and recruitment agencies in the evaluation process. This participatory approach ensures that the perspectives of all stakeholders are considered, leading to more relevant and practical outcomes. Using the MERISE model allows for: • Rigorous data structuring, organization, and standardization: Clearly defining entities and relationships facilitates data organization and standardization, crucial for effective data analysis. • Facilitation of monitoring, analysis, and relevant indicators: Developing both quantitative and qualitative indicators helps measure the effectiveness of training in relation to the labor market, allowing for a comprehensive evaluation. • Improved communication and common language: By providing a common language for different stakeholders, MERISE enhances communication and collaboration, ensuring that all parties have a shared understanding. The study’s approach and contribution to existing research lie in: • Structured theoretical and practical framework and holistic approach: The study offers a structured framework for data collection and analysis, covering both quantitative and qualitative aspects, thus providing a comprehensive view of the training system. • Reproducible methodology and international comparison: The proposed methodology can be replicated in other contexts, facilitating international comparison and the adoption of best practices. • Extension of knowledge and new perspective: By integrating a participatory approach and developing indicators adapted to local needs, the study extends existing research and offers new perspectives on vocational training evaluation.展开更多
The shortage of personal protective equipment and lack of proper nursing training have been endangering health care workers dealing with coronavirus disease 2019(COVID-19).In our treatment center,the implementation of...The shortage of personal protective equipment and lack of proper nursing training have been endangering health care workers dealing with coronavirus disease 2019(COVID-19).In our treatment center,the implementation of a holistic care model of time-sharing management for severe and critical COVID-19 patients has further aggravated the shortage of intensive care unit(ICU)professional nurses.Therefore,we developed a short-term specialized and targeted nursing training program to help ICU nurses to cope with stress and become more efficient,thus reducing the number of nurses required in the ICU.In order to avoid possible human-to-human spread,small teaching classes and remote training were applied.The procedural training mode included four steps:preparation,plan,implementation,and evaluation.An evaluation was conducted throughout the process of nursing training.In this study,we documented and shared experiences in transitioning from traditional face-to-face programs to remote combined with proceduralization nursing training mode from our daily work experiences during the COVID-19 pandemic,which has shown to be helpful for nurses working in the ICU.展开更多
In order to accelerate a heavy train model with great dimensions to a speed higher than 300 km h?1 in a moving train model testing system,compressed air is utilized to drive the train model indirectly.The gas from an ...In order to accelerate a heavy train model with great dimensions to a speed higher than 300 km h?1 in a moving train model testing system,compressed air is utilized to drive the train model indirectly.The gas from an air gun pushes the piston in an accelerating tube forward.The piston is connected to the trailer through a rope,and the trailer pulls the train model to the desired speed.After the testing section,the train model enters the deceleration section.The speed of the train model gradually decreases because of the braking force of the magnetic braking device on the bottom of the train model and the steel plates fixed on the floor of this device.The dissipation of kinetic energy of the trailer is also based on a similar principle.The feasibility of these methods has been examined in a 180 m-long moving train model testing system.The speed of the trailer alone reaches up to 490 km h-1.Consequently,a 34.8 kg model accelerates up to 350 km h?1;the smooth and safe stopping of the model is also possible.展开更多
AIM:To test a strategy for endoscopic submucosal dissection(ESD) training in animal models designed to overcome the initial learning curve.METHODS:ESD was attempted in ex vivo and in vivo pig models.Thirty ESD procedu...AIM:To test a strategy for endoscopic submucosal dissection(ESD) training in animal models designed to overcome the initial learning curve.METHODS:ESD was attempted in ex vivo and in vivo pig models.Thirty ESD procedures were attempted in the esophagus(n=9) or the stomach(n=21).The ex vivo model was used until initial competence was achieved.In the in vivo model,several ESD procedures were performed in up to 3 sessions.The following variables were analyzed:specimen size,complete and en bloc resection rate,time for circumferential incision,time for submucosal dissection,total ESD duration,and complications.RESULTS:Complete resection was achieved in 28 cases(en bloc 27);2 could not be completed(one perforation,one technical diff iculty).The mean ± SD time for circumferential incision was 36.2±16.8 min(range:8-87 min),and the mean±SD time for submucosal dissection was 45.1±35.7 min(range:9-196 min).The mean±SD size of the resected specimens was 45.2±17.8 mm.The mean±SD total resection time was signif icantly increased for the gastric cases performed in the f irst half of the study(n=13) than in the second half(n=8)(98.9±62.4 min vs 61.7±17.6 min,P=0.04),although the specimen size did not differ.CONCLUSION:Training in animal models could help endoscopists overcome the learning curve before starting ESD in humans.展开更多
The proliferation of maliciously coded documents as file transfers increase has led to a rise in sophisticated attacks.Portable Document Format(PDF)files have emerged as a major attack vector for malware due to their ...The proliferation of maliciously coded documents as file transfers increase has led to a rise in sophisticated attacks.Portable Document Format(PDF)files have emerged as a major attack vector for malware due to their adaptability and wide usage.Detecting malware in PDF files is challenging due to its ability to include various harmful elements such as embedded scripts,exploits,and malicious URLs.This paper presents a comparative analysis of machine learning(ML)techniques,including Naive Bayes(NB),K-Nearest Neighbor(KNN),Average One Dependency Estimator(A1DE),RandomForest(RF),and SupportVectorMachine(SVM)forPDFmalware detection.The study utilizes a dataset obtained from the Canadian Institute for Cyber-security and employs different testing criteria,namely percentage splitting and 10-fold cross-validation.The performance of the techniques is evaluated using F1-score,precision,recall,and accuracy measures.The results indicate that KNNoutperforms other models,achieving an accuracy of 99.8599%using 10-fold cross-validation.The findings highlight the effectiveness of ML models in accurately detecting PDF malware and provide insights for developing robust systems to protect against malicious activities.展开更多
Based on the characteristics and employment situation of incoming labors,we should attach great importance to their training.With rich teaching resources,the higher vocational colleges should give full play to their a...Based on the characteristics and employment situation of incoming labors,we should attach great importance to their training.With rich teaching resources,the higher vocational colleges should give full play to their advantages,get involved in the training,and enhance their studies of training models.展开更多
Inquiry training model gives children directions to explore the new areas effectively which can help students develop the intellectual discipline and skills necessary to raise questions and search out answers stemming...Inquiry training model gives children directions to explore the new areas effectively which can help students develop the intellectual discipline and skills necessary to raise questions and search out answers stemming from their curiosity. Applying this model in teaching, process skills of the students can be improved, like observing, collecting, organizing data, identifying and controlling variables, formulating and testing hypotheses, and inferring. Besides, students will develop logical thinking and they will form the attitude that all knowledge is tentative.展开更多
This paper presents a discrete-time model to describe the movements of a group of trains, in which some operational strategies, including traction operation, braking operation and impact of stochastic disturbance, are...This paper presents a discrete-time model to describe the movements of a group of trains, in which some operational strategies, including traction operation, braking operation and impact of stochastic disturbance, are defined. To show the dynamic characteristics of train traffic flow with stochastic disturbance, some numerical experiments on a railway line are simulated. The computational results show that the discrete-time movement model can well describe the movements of trains on a rail line with the moving-block signalling system. Comparing with the results of no disturbance, it finds that the traffic capacity of the rail line will decrease with the influence of stochastic disturbance. Additionally, the delays incurred by stochastic disturbance can be propagated to the subsequent trains, and then prolong their traversing time on the rail line. It can provide auxiliary information for rescheduling trains When the stochastic disturbance occurs on the railway.展开更多
The aim of this paper is to present a discrete event model-based approach to simulate train movement with the con- sidered energy-saving factor. We conduct extensive case studies to show the dynamic characteristics of...The aim of this paper is to present a discrete event model-based approach to simulate train movement with the con- sidered energy-saving factor. We conduct extensive case studies to show the dynamic characteristics of the traffic flow and demonstrate the effectiveness of the proposed approach. The simulation results indicate that the proposed discrete event model-based simulation approach is suitable for characterizing the movements of a group of trains on a single railway line with less iterations and CPU time. Additionally, some other qualitative and quantitative characteristics are investigated. In particular, because of the cumulative influence from the previous trains, the following trains should be accelerated or braked frequently to control the headway distance, leading to more energy consumption.展开更多
The numerical simulation based on Reynolds time-averaged equation is one of the approved methods to evaluate the aerodynamic performance of trains in crosswind.However,there are several turbulence models,trains may pr...The numerical simulation based on Reynolds time-averaged equation is one of the approved methods to evaluate the aerodynamic performance of trains in crosswind.However,there are several turbulence models,trains may present different aerodynamic performances in crosswind using different turbulence models.In order to select the most suitable turbulence model,the inter-city express 2(ICE2)model is chosen as a research object,6 different turbulence models are used to simulate the flow characteristics,surface pressure and aerodynamic forces of the train in crosswind,respectively.6 turbulence models are the standard k-ε,Renormalization Group(RNG)k-ε,Realizable k-ε,Shear Stress Transport(SST)k-ω,standard k-ωand Spalart-Allmaras(SPA),respectively.The numerical results and the wind tunnel experimental data are compared.The results show that the most accurate model for predicting the surface pressure of the train is SST k-ω,followed by Realizable k-ε.Compared with the experimental result,the error of the side force coefficient obtained by SST k-ωand Realizable k-εturbulence model is less than 1%.The most accurate prediction for the lift force coefficient is achieved by SST k-ω,followed by RNG k-ε.By comparing 6 different turbulence models,the SST k-ωmodel is most suitable for the numerical simulation of the aerodynamic behavior of trains in crosswind.展开更多
文摘Based on the complexity and regional differences of the political,economic,and cultural environments of countries along the“Belt and Road,”this paper analyzes the new characteristics of the current demand for business English talents.Combining this with the existing problems in China’s current training models,it proposes a reform path for talent training models that are adapted to the construction of the“Belt and Road”Initiative.The aim is to provide theoretical references and practical guidance for enhancing the international competitiveness of business English talents.
文摘Sentiment analysis,a cornerstone of natural language processing,has witnessed remarkable advancements driven by deep learning models which demonstrated impressive accuracy in discerning sentiment from text across various domains.However,the deployment of such models in resource-constrained environments presents a unique set of challenges that require innovative solutions.Resource-constrained environments encompass scenarios where computing resources,memory,and energy availability are restricted.To empower sentiment analysis in resource-constrained environments,we address the crucial need by leveraging lightweight pre-trained models.These models,derived from popular architectures such as DistilBERT,MobileBERT,ALBERT,TinyBERT,ELECTRA,and SqueezeBERT,offer a promising solution to the resource limitations imposed by these environments.By distilling the knowledge from larger models into smaller ones and employing various optimization techniques,these lightweight models aim to strike a balance between performance and resource efficiency.This paper endeavors to explore the performance of multiple lightweight pre-trained models in sentiment analysis tasks specific to such environments and provide insights into their viability for practical deployment.
基金Henan Provincial Medical Education Research Project“Research on the Innovation and Practice of Talent Cultivation Mode of Rehabilitation Therapy Technology Based on the Collaborative Education and Training”(Project number:WJLX2023208)。
文摘The purpose of this study is to comprehensively evaluate the modern training model of rehabilitation therapy technology talents.Selecting the third-year students of the rehabilitation therapy technology program in School Y as the research subject,300 questionnaires were collected and the effective response rate was 92%.The strengths and weaknesses of the modern training model were analyzed through a mixed qualitative and quantitative research method.It was found that 68%of the students thought that the modern model had obvious advantages in practical teaching,but 42%of the students thought that it still needed to be improved in personalized teaching.This study provides an empirical basis and specific suggestions for optimizing the cultivation of rehabilitation therapy technology talents.
文摘Objective:To explore and analyze the work process-based practical training teaching model for basic nursing skills in vocational colleges and its implementation effects.Methods:A total of 82 nursing students from our school were selected for the study,which was conducted from April 2023 to April 2024.Using a random number table method,the students were divided into an observation group and a control group,each with 41 students.The control group received conventional practical training teaching,while the observation group followed the work process-based practical training model for basic nursing skills.The assessment scores and teaching satisfaction of the two groups were compared.Results:The comparison of assessment scores showed that the observation group performed significantly better than the control group(P<0.05).The comparison of teaching satisfaction also indicated that the observation group had significantly higher satisfaction than the control group(P<0.05).Conclusion:The work process-based practical training teaching model for basic nursing skills in vocational colleges can improve students’assessment scores and enhance teaching satisfaction,demonstrating its value for wider application.
文摘Leveraging the Baidu Qianfan model platform,this paper designs and implements a highly efficient and accurate scoring system for subjective questions,focusing primarily on questions in the field of computer network technology.The system enhances the foundational model by utilizing Qianfan’s training tools and integrating advanced techniques,such as supervised fine-tuning.In the data preparation phase,a comprehensive collection of subjective data related to computer network technology is gathered,cleaned,and labeled.During model training and evaluation,optimal hyperparameters and tuning strategies are applied,resulting in a model capable of scoring with high accuracy.Evaluation results demonstrate that the proposed model performs well across multiple dimensions-content,expression,and development scores-yielding results comparable to those of manual scoring.
文摘A robust parameter identification method based on Kiencke model was proposed to solve the problem of the parameter identification accuracy being affected by the rail environment change and noise interference for heavy-duty trains. Firstly, a Kiencke stick-creep identification model was constructed, and the parameter identification task was transformed into a quadratic programming problem. Secondly, an iterative algorithm was constructed to solve the problem, into which a time-varying forgetting factor was added to track the change of the rail environment, and to solve the uncertainty problem of the wheel-rail environment. The Granger causality test was adopted to detect the interference, and then the weights of the current data were redistributed to solve the problem of noise interference in parameter identification. Finally, simulations were carried out and the results showed that the proposed method could track the change of the track environment in time, reduce the noise interference in the identification process, and effectively identify the adhesion performance parameters.
基金funded by the China Academy of Railway Sciences Corporation Limited Scientific Research Project(No:2023YJ080).
文摘Purpose-With the rapid advancement of China’s high-speed rail network,the density of train operations is on the rise.To address the challenge of shortening train tracking intervals while enhancing transportation efficiency,the multi-objective dynamic optimization of the train operation process has emerged as a critical issue.Design/methodology/approach-Train dynamic model is established by analyzing the force of the train in the process of tracing operation.The train tracing operation model is established according to the dynamic mechanical model of the train tracking process,and the dynamic optimization analysis is carried out with comfort,energy saving and punctuality as optimization objectives.To achieve multi-objective dynamic optimization,a novel train tracking operation calculation method is proposed,utilizing the improved grey wolf optimization algorithm(MOGWO).The proposed method is simulated and verified based on the train characteristics and line data of CR400AF electric multiple units.Findings-The simulation results prove that the optimized MOGWO algorithm can be computed quickly during train tracks,the optimum results can be given within 5s and the algorithm can converge effectively in different optimization target directions.The optimized speed profile of the MOGWO algorithm is smoother and more stable and meets the target requirements of energy saving,punctuality and comfort while maximally respecting the speed limit profile.Originality/value-The MOGWO train tracking interval optimization method enhances the tracking process while ensuring a safe tracking interval.This approach enables the trailing train to operate more comfortably,energy-efficiently and punctually,aligning with passenger needs and industry trends.The method offers valuable insights for optimizing the high-speed train tracking process.
基金Supported by Chongqing Education Science Planning Program(2013-ZJ-060)Humanities and Social Science Research Planning Program of Ministry of Education(13YJA630042)+1 种基金Humanities and Social Science Research Program of Chongqing Education Committee(14SKN03)S&T Innovation Team Construction and Planning Foundation of Yangtze Normal University(2014XJTD03)~~
文摘To cultivate new professional farmers is a key way for rural labor development, resolving existing problems such as how to farming. It is notable that government and market take advantages in training of new professional farmers. Therefore, it is necessary to guarantee government and market playing the roles. The research explored market-oriented farmer training model and the characteristics and investigated training routes for new professional farmers.
文摘加快发展现代高等职业教育,既有利于缓解当前就业压力,也是解决高技能人才短缺的战略之举。现代职场对有英语应用能力要求的岗位越来越多,一些专业技能强的学生由于无法满足用人单位在英语应用能力上的要求而与理想岗位失之交臂的情况时有发生。为改变这样的现状、提高学生的英语实际应用能力,开展基于ADDIE Training Model的高职英语课程教学实践与应用研究,并将试验效果与02O教学活动和传统的"讲授型"教学活动效果进行对比分析。
基金supported by National Natural Science Foundation of China(Grant Nos.51275153,51105128)National Innovation Project of China(Grant No.2011IM010200)Social Science Planning Fund Program of Hebei Province,China(Grant No.HB13GL050)
文摘Abstract： Innovation is a process of taking an original idea and converting it into a business value, in which the engineers face some inventive problems which can be solved hardly by experience. TRIZ, as a new theory for companies in China, provides both conceptual and procedural knowledge for finding and solving inventive problems. Because the government plays a leading role in the diffusion of TRIZ, too many companies from different industries are waiting to be trained, but the quantity of the trainers mastering TRIZ is incompatible with that requirement. In this context, to improve the training effect, an interactive training model of TRIZ for the mechanical engineers in China is developed and the implementation in the form of training classes is carried out. The training process is divided into 6 phases as follows： selecting engineers, training stage-l, finding problems, training stage-2, finding solutions and summing up. The government, TRIZ institutions and companies to join the programs interact during the process. The government initiates and monitors a project in form of a training class of TRIZ and selects companies to join the programs. Each selected companies choose a few engineers to join the class and supervises the training result. The TRIZ institutions design the training courses and carry out training curriculum. With the beginning of the class, an effective communication channel is established by means of interview, discussion face to face, E-mail, QQ and so on. After two years training practices, the results show that innovative abilities of the engineers to join and pass the final examinations increased distinctly, and most of companies joined the training class have taken congnizance of the power of TRIZ for product innovation. This research proposes an interactive training model of TRIZ for mechanical engineers in China to expedite the knowledge diffusion of TRIZ.
文摘This study proposes the use of the MERISE conceptual data model to create indicators for monitoring and evaluating the effectiveness of vocational training in the Republic of Congo. The importance of MERISE for structuring and analyzing data is underlined, as it enables the measurement of the adequacy between training and the needs of the labor market. The innovation of the study lies in the adaptation of the MERISE model to the local context, the development of innovative indicators, and the integration of a participatory approach including all relevant stakeholders. Contextual adaptation and local innovation: The study suggests adapting MERISE to the specific context of the Republic of Congo, considering the local particularities of the labor market. Development of innovative indicators and new measurement tools: It proposes creating indicators to assess skills matching and employer satisfaction, which are crucial for evaluating the effectiveness of vocational training. Participatory approach and inclusion of stakeholders: The study emphasizes actively involving training centers, employers, and recruitment agencies in the evaluation process. This participatory approach ensures that the perspectives of all stakeholders are considered, leading to more relevant and practical outcomes. Using the MERISE model allows for: • Rigorous data structuring, organization, and standardization: Clearly defining entities and relationships facilitates data organization and standardization, crucial for effective data analysis. • Facilitation of monitoring, analysis, and relevant indicators: Developing both quantitative and qualitative indicators helps measure the effectiveness of training in relation to the labor market, allowing for a comprehensive evaluation. • Improved communication and common language: By providing a common language for different stakeholders, MERISE enhances communication and collaboration, ensuring that all parties have a shared understanding. The study’s approach and contribution to existing research lie in: • Structured theoretical and practical framework and holistic approach: The study offers a structured framework for data collection and analysis, covering both quantitative and qualitative aspects, thus providing a comprehensive view of the training system. • Reproducible methodology and international comparison: The proposed methodology can be replicated in other contexts, facilitating international comparison and the adoption of best practices. • Extension of knowledge and new perspective: By integrating a participatory approach and developing indicators adapted to local needs, the study extends existing research and offers new perspectives on vocational training evaluation.
基金Supported by The National Natural Science Foundation of China,No.81772045 and No.81902000Teaching project of the First Affiliated Hospital of Harbin Medical University,No.2017014.
文摘The shortage of personal protective equipment and lack of proper nursing training have been endangering health care workers dealing with coronavirus disease 2019(COVID-19).In our treatment center,the implementation of a holistic care model of time-sharing management for severe and critical COVID-19 patients has further aggravated the shortage of intensive care unit(ICU)professional nurses.Therefore,we developed a short-term specialized and targeted nursing training program to help ICU nurses to cope with stress and become more efficient,thus reducing the number of nurses required in the ICU.In order to avoid possible human-to-human spread,small teaching classes and remote training were applied.The procedural training mode included four steps:preparation,plan,implementation,and evaluation.An evaluation was conducted throughout the process of nursing training.In this study,we documented and shared experiences in transitioning from traditional face-to-face programs to remote combined with proceduralization nursing training mode from our daily work experiences during the COVID-19 pandemic,which has shown to be helpful for nurses working in the ICU.
基金supported by the National Key Technology R&D Program (Grant No. 2009BAG12A03)the National Natural Science Foundation of China (Grant No.10472123)
文摘In order to accelerate a heavy train model with great dimensions to a speed higher than 300 km h?1 in a moving train model testing system,compressed air is utilized to drive the train model indirectly.The gas from an air gun pushes the piston in an accelerating tube forward.The piston is connected to the trailer through a rope,and the trailer pulls the train model to the desired speed.After the testing section,the train model enters the deceleration section.The speed of the train model gradually decreases because of the braking force of the magnetic braking device on the bottom of the train model and the steel plates fixed on the floor of this device.The dissipation of kinetic energy of the trailer is also based on a similar principle.The feasibility of these methods has been examined in a 180 m-long moving train model testing system.The speed of the trailer alone reaches up to 490 km h-1.Consequently,a 34.8 kg model accelerates up to 350 km h?1;the smooth and safe stopping of the model is also possible.
基金Supported by (in part) A grant from Education, Culture and Sports Council, Government of the Canary Islands ("Consejería de Educación, Cultura y Deportes, Gobierno de Canarias") (PI2002/138)the Health Institute Carlos Ⅲ ("Instituto de Salud Carlos Ⅲ") (C03/02)
文摘AIM:To test a strategy for endoscopic submucosal dissection(ESD) training in animal models designed to overcome the initial learning curve.METHODS:ESD was attempted in ex vivo and in vivo pig models.Thirty ESD procedures were attempted in the esophagus(n=9) or the stomach(n=21).The ex vivo model was used until initial competence was achieved.In the in vivo model,several ESD procedures were performed in up to 3 sessions.The following variables were analyzed:specimen size,complete and en bloc resection rate,time for circumferential incision,time for submucosal dissection,total ESD duration,and complications.RESULTS:Complete resection was achieved in 28 cases(en bloc 27);2 could not be completed(one perforation,one technical diff iculty).The mean ± SD time for circumferential incision was 36.2±16.8 min(range:8-87 min),and the mean±SD time for submucosal dissection was 45.1±35.7 min(range:9-196 min).The mean±SD size of the resected specimens was 45.2±17.8 mm.The mean±SD total resection time was signif icantly increased for the gastric cases performed in the f irst half of the study(n=13) than in the second half(n=8)(98.9±62.4 min vs 61.7±17.6 min,P=0.04),although the specimen size did not differ.CONCLUSION:Training in animal models could help endoscopists overcome the learning curve before starting ESD in humans.
文摘The proliferation of maliciously coded documents as file transfers increase has led to a rise in sophisticated attacks.Portable Document Format(PDF)files have emerged as a major attack vector for malware due to their adaptability and wide usage.Detecting malware in PDF files is challenging due to its ability to include various harmful elements such as embedded scripts,exploits,and malicious URLs.This paper presents a comparative analysis of machine learning(ML)techniques,including Naive Bayes(NB),K-Nearest Neighbor(KNN),Average One Dependency Estimator(A1DE),RandomForest(RF),and SupportVectorMachine(SVM)forPDFmalware detection.The study utilizes a dataset obtained from the Canadian Institute for Cyber-security and employs different testing criteria,namely percentage splitting and 10-fold cross-validation.The performance of the techniques is evaluated using F1-score,precision,recall,and accuracy measures.The results indicate that KNNoutperforms other models,achieving an accuracy of 99.8599%using 10-fold cross-validation.The findings highlight the effectiveness of ML models in accurately detecting PDF malware and provide insights for developing robust systems to protect against malicious activities.
基金Supported by the "Twelfth-Five Year" Research Project of National Agricultural Vocational Educationthe Program of Jiangsu society of Technical and Vocational Education(2010007)
文摘Based on the characteristics and employment situation of incoming labors,we should attach great importance to their training.With rich teaching resources,the higher vocational colleges should give full play to their advantages,get involved in the training,and enhance their studies of training models.
文摘Inquiry training model gives children directions to explore the new areas effectively which can help students develop the intellectual discipline and skills necessary to raise questions and search out answers stemming from their curiosity. Applying this model in teaching, process skills of the students can be improved, like observing, collecting, organizing data, identifying and controlling variables, formulating and testing hypotheses, and inferring. Besides, students will develop logical thinking and they will form the attitude that all knowledge is tentative.
基金Project supported by the National Natural Science Foundation of China (Grant Nos. 70901006 and 60634010)the State Key Laboratory of Rail Traffic Control and Safety (Grant Nos. RCS2009ZT001 and RCS2008ZZ001)Beijing Jiaotong University, and the Innovation Foundation of Science and Technology for Excellent Doctorial Candidate of Beijing Jiaotong University (Grant No. 141034522)
文摘This paper presents a discrete-time model to describe the movements of a group of trains, in which some operational strategies, including traction operation, braking operation and impact of stochastic disturbance, are defined. To show the dynamic characteristics of train traffic flow with stochastic disturbance, some numerical experiments on a railway line are simulated. The computational results show that the discrete-time movement model can well describe the movements of trains on a rail line with the moving-block signalling system. Comparing with the results of no disturbance, it finds that the traffic capacity of the rail line will decrease with the influence of stochastic disturbance. Additionally, the delays incurred by stochastic disturbance can be propagated to the subsequent trains, and then prolong their traversing time on the rail line. It can provide auxiliary information for rescheduling trains When the stochastic disturbance occurs on the railway.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.71271020 and 71271022)the Program for New Century Excellent Talents in University(Grant No.NCET-10-0218)
文摘The aim of this paper is to present a discrete event model-based approach to simulate train movement with the con- sidered energy-saving factor. We conduct extensive case studies to show the dynamic characteristics of the traffic flow and demonstrate the effectiveness of the proposed approach. The simulation results indicate that the proposed discrete event model-based simulation approach is suitable for characterizing the movements of a group of trains on a single railway line with less iterations and CPU time. Additionally, some other qualitative and quantitative characteristics are investigated. In particular, because of the cumulative influence from the previous trains, the following trains should be accelerated or braked frequently to control the headway distance, leading to more energy consumption.
基金Supported by National Natural Science Foundation of China(Grant No.51605397)Sichuan Provincial Science and Technology Program of China(Grant No.2019YJ0227)Self-determined Project of State Key Laboratory of Traction Power(Grant No.2019TPL_T02)
文摘The numerical simulation based on Reynolds time-averaged equation is one of the approved methods to evaluate the aerodynamic performance of trains in crosswind.However,there are several turbulence models,trains may present different aerodynamic performances in crosswind using different turbulence models.In order to select the most suitable turbulence model,the inter-city express 2(ICE2)model is chosen as a research object,6 different turbulence models are used to simulate the flow characteristics,surface pressure and aerodynamic forces of the train in crosswind,respectively.6 turbulence models are the standard k-ε,Renormalization Group(RNG)k-ε,Realizable k-ε,Shear Stress Transport(SST)k-ω,standard k-ωand Spalart-Allmaras(SPA),respectively.The numerical results and the wind tunnel experimental data are compared.The results show that the most accurate model for predicting the surface pressure of the train is SST k-ω,followed by Realizable k-ε.Compared with the experimental result,the error of the side force coefficient obtained by SST k-ωand Realizable k-εturbulence model is less than 1%.The most accurate prediction for the lift force coefficient is achieved by SST k-ω,followed by RNG k-ε.By comparing 6 different turbulence models,the SST k-ωmodel is most suitable for the numerical simulation of the aerodynamic behavior of trains in crosswind.
