In this paper, a fault-tolerant-based online critic learning algorithm is developed to solve the optimal tracking control issue for nonaffine nonlinear systems with actuator faults.First, a novel augmented plant is co...In this paper, a fault-tolerant-based online critic learning algorithm is developed to solve the optimal tracking control issue for nonaffine nonlinear systems with actuator faults.First, a novel augmented plant is constructed by fusing the system state and the reference trajectory, which aims to transform the optimal fault-tolerant tracking control design with actuator faults into the optimal regulation problem of the conventional nonlinear error system. Subsequently, in order to ensure the normal execution of the online learning algorithm, a stability criterion condition is created to obtain an initial admissible tracking policy. Then, the constructed model neural network(NN) is pretrained to recognize the system dynamics and calculate trajectory control. The critic and action NNs are constructed to output the approximate cost function and approximate tracking control,respectively. The Hamilton-Jacobi-Bellman equation of the error system is solved online through the action-critic framework. In theoretical analysis, it is proved that all concerned signals are uniformly ultimately bounded according to the Lyapunov principle.The tracking control law can approach the optimal tracking control within a finite approximation error. Finally, two experimental examples are conducted to indicate the effectiveness and superiority of the developed fault-tolerant tracking control scheme.展开更多
Fuel cell electric vehicles hold great promise for a diverse range of applications in reducing greenhouse gas emissions.In power fuel cell systems,hydrogen fuel serves as an energy vector.To ensure its suitability,it ...Fuel cell electric vehicles hold great promise for a diverse range of applications in reducing greenhouse gas emissions.In power fuel cell systems,hydrogen fuel serves as an energy vector.To ensure its suitability,it is necessary for the quality of hydrogen to adhere to the standards set by ISO 14687:2019,which sets maximum limits for 14 impurities in hydrogen,aiming to prevent any degradation of fuel cell performance.Ammonia(NH_(3))is a prominent pollutant in fuel cells,and accurate measurements of its concentration are crucial for hydrogen fuel cell quantity.In this study,a novel detection platform was developed for determining NH_(3)in real hydrogen samples.The online analysis platform integrates a self-developed online dilution module with a Fourier transform infrared spectrometer(ODM-FTIR).The ODM-FTIR can be operated fully automatically with remote operation.Under the optimum conditions,this method achieved a wide linear range between(50∼1000)nmol/mol.The limit of detection(LOD)was as low as 2 nmol/mol with a relative standard deviation(RSD,n=7)of 3.6%at a content of 50 nmol/mol.To ensure that the quality of the hydrogen products meets the requirement of proton exchange membrane fuel cell vehicles(PEMFCV),the developed ODM-FTIR system was applied to monitor the NH_(3)content in Chengdu Hydrogen Energy Co.,Ltd.for 21 days during Chengdu 2021 FISU World University Games.The proposed method retains several unique advantages,including a low detection limit,excellent repeatability,high accuracy,high speed,good stability,and calibration flexibility.It is an effective analytical method for accurately quantifying NH_(3)in hydrogen,especially suitable for online analysis.It also provides a new idea for the analysis of other impurity components in hydrogen.展开更多
To address the issue of coordinated control of multiple hydrogen and battery storage units to suppress the grid-injected power deviation of wind farms,an online optimization strategy for Battery-hydrogen hybrid energy...To address the issue of coordinated control of multiple hydrogen and battery storage units to suppress the grid-injected power deviation of wind farms,an online optimization strategy for Battery-hydrogen hybrid energy storage systems based on measurement feedback is proposed.First,considering the high charge/discharge losses of hydrogen storage and the low energy density of battery storage,an operational optimization objective is established to enable adaptive energy adjustment in the Battery-hydrogen hybrid energy storage system.Next,an online optimization model minimizing the operational cost of the hybrid system is constructed to suppress grid-injected power deviations with satisfying the operational constraints of hydrogen storage and batteries.Finally,utilizing the online measurement of the energy states of hydrogen storage and batteries,an online optimization strategy based on measurement feedback is designed.Case study results show:before and after smoothing the fluctuations in wind power,the time when the power exceeded the upper and lower limits of the grid-injected power accounted for 24.1%and 1.45%of the total time,respectively,the proposed strategy can effectively keep the grid-injected power deviations of wind farms within the allowable range.Hydrogen storage and batteries respectively undertake long-term and short-term charge/discharge tasks,effectively reducing charge/discharge losses of the Battery-hydrogen hybrid energy storage systems and improving its operational efficiency.展开更多
In order to address the current inability of screen printing to monitor printing pressure online,an online printing pressure monitoring system applied to screen printing machines was designed in this study.In this stu...In order to address the current inability of screen printing to monitor printing pressure online,an online printing pressure monitoring system applied to screen printing machines was designed in this study.In this study,the consistency of printed electrodes was measured by using a confocal microscope and the pressure distribution detected by online pressure monitoring system was compared to investigate the relationship.The results demonstrated the relationship between printing pressure and the consistency of printed electrodes.As printing pressure increases,the ink layer at the corresponding position becomes thicker and that higher printing pressure enhances the consistency of the printed electrodes.The experiment confirms the feasibility of the online pressure monitoring system,which aids in predicting and controlling the consistency of printed electrodes,thereby improving their performance.展开更多
As world events have morphed teachers’roles within English medium of instruction(EMI)contexts to incorporate more online teaching practices,teachers’integration of digital tools has faced technological and curricula...As world events have morphed teachers’roles within English medium of instruction(EMI)contexts to incorporate more online teaching practices,teachers’integration of digital tools has faced technological and curricular challenges.While previous research has examined the integration of digital tools in face-to-face and hybrid EMI settings(e.g.,Finardi,2015;O’Dowd,2018),more research is needed to understand the familiarization process teachers engage in as they implement fully-online teaching to support their content and language integrated learning(CLIL)teaching.As part of a larger project,this case study sets out to fill this gap by examining the practices and perspectives of 30 Kazakhstani university teachers who adopted CLIL approaches while needing to adapt to fully-online teaching contexts.Using the concept of technological pedagogical content knowledge(Mishra&Koehler,2006)in tandem with Ball et al.’s(2016)seven CLIL principles as a framework,this study thematically analyzed workshop artifacts,survey responses,semi-structured interview transcripts,and videos from online class lessons to find that teachers were mediators and curators of content,language,pedagogy,and digital tools.The findings offer pedagogical insights for the implementation of professional development(PD)to prepare teachers to meaningfully curate and mediate technology into their CLIL pedagogy to teach content within EMI contexts.展开更多
Online learning has taken root and with the advancement in technology more and more educators are embracing online learning.During the COVID-19 pandemic,with total shut down of face-to-face learning,the Kenyan governm...Online learning has taken root and with the advancement in technology more and more educators are embracing online learning.During the COVID-19 pandemic,with total shut down of face-to-face learning,the Kenyan government had moved learning online and remotely.To find out on how learners in remote areas were experiencing learning during the COVID-19 pandemic,a study was carried out using rapid ethnography design.Five final year secondary students were sampled.Data was collected through interviews,observations,and document analysis.This paper reports on the findings of online and remote learning platforms,which were available,accessed,and preferred by the learners in remote areas of Kenya during the pandemic.It also highlights the importance of e-learning platforms in addressing learning experiences and success.展开更多
To bridge the gap between curriculum content and clinical needs,as well as address the insufficient quality of online educational resources in current postgraduate anesthesiology education,this study proposes a“libra...To bridge the gap between curriculum content and clinical needs,as well as address the insufficient quality of online educational resources in current postgraduate anesthesiology education,this study proposes a“library-style”network resource platform for anesthesia graduate students,grounded in the competency-based medical education framework.The platform’s primary focus is“classical knowledge module”,which covers six core domains in anesthesiology,such as clinical anesthesia management,anesthesia technical operation,and anesthesia pharmacology.The platform also integrates‘Internet+’technology,creating a multifunctional network resource to support comprehensive learning.The platform is characterized by modularized knowledge,diversified resources,dynamic updates,and universal accessibility,enabling postgraduate students to engage in independent and lifelong learning.This flexibility fosters the innovation of hybrid teaching models,combining both online and offline components.The study aims to strengthen the competency-oriented anesthesia training system,providing robust support for both clinical practice and academic research.展开更多
The rapid development of online education has posed brand-new challenges to the teaching quality monitoring system in colleges and universities.This paper systematically explores the three major characteristics of onl...The rapid development of online education has posed brand-new challenges to the teaching quality monitoring system in colleges and universities.This paper systematically explores the three major characteristics of online teaching quality monitoring in colleges and universities:the complexity of monitoring brought by the separation of time and space,the enhanced accuracy based on technology dependence,and the monitoring dimensions expanded by the diversification of interaction.The research reveals the key existing problems at present,including the analytical predicament caused by data fragmentation,the stability crisis triggered by technical failures,and the validity limitations due to the insufficient adaptability of teachers and students.In response to these challenges,this paper proposes systematic solutions such as building a unified data platform,strengthening the technical support system,and conducting targeted training.Through multi-dimensional analysis,this study provides a theoretical framework and practical path for constructing a quality monitoring system that ADAPTS to the characteristics of online education,and has important reference value for improving the quality of online teaching in colleges and universities.展开更多
The increased accessibility of social networking services(SNSs)has facilitated communication and information sharing among users.However,it has also heightened concerns about digital safety,particularly for children a...The increased accessibility of social networking services(SNSs)has facilitated communication and information sharing among users.However,it has also heightened concerns about digital safety,particularly for children and adolescents who are increasingly exposed to online grooming crimes.Early and accurate identification of grooming conversations is crucial in preventing long-term harm to victims.However,research on grooming detection in South Korea remains limited,as existing models trained primarily on English text and fail to reflect the unique linguistic features of SNS conversations,leading to inaccurate classifications.To address these issues,this study proposes a novel framework that integrates optical character recognition(OCR)technology with KcELECTRA,a deep learning-based natural language processing(NLP)model that shows excellent performance in processing the colloquial Korean language.In the proposed framework,the KcELECTRA model is fine-tuned by an extensive dataset,including Korean social media conversations,Korean ethical verification data from AI-Hub,and Korean hate speech data from Hug-gingFace,to enable more accurate classification of text extracted from social media conversation images.Experimental results show that the proposed framework achieves an accuracy of 0.953,outperforming existing transformer-based models.Furthermore,OCR technology shows high accuracy in extracting text from images,demonstrating that the proposed framework is effective for online grooming detection.The proposed framework is expected to contribute to the more accurate detection of grooming text and the prevention of grooming-related crimes.展开更多
This paper investigates mobility-aware online optimization for digital twin(DT)-assisted task execution in edge computing environments.In such systems,DTs,hosted on edge servers(ESs),require proactive migration to mai...This paper investigates mobility-aware online optimization for digital twin(DT)-assisted task execution in edge computing environments.In such systems,DTs,hosted on edge servers(ESs),require proactive migration to maintain proximity to their mobile physical twin(PT)counterparts.To minimize task response latency under a stringent energy consumption constraint,we jointly optimize three key components:the status data uploading frequency fromthe PT,theDT migration decisions,and the allocation of computational and communication resources.To address the asynchronous nature of these decisions,we propose a novel two-timescale mobility-aware online optimization(TMO)framework.The TMO scheme leverages an extended two-timescale Lyapunov optimization framework to decompose the long-term problem into sequential subproblems.At the larger timescale,a multi-armed bandit(MAB)algorithm is employed to dynamically learn the optimal status data uploading frequency.Within each shorter timescale,we first employ a gated recurrent unit(GRU)-based predictor to forecast the PT’s trajectory.Based on this prediction,an alternate minimization(AM)algorithm is then utilized to solve for the DT migration and resource allocation variables.Theoretical analysis confirms that the proposed TMO scheme is asymptotically optimal.Furthermore,simulation results demonstrate its significant performance gains over existing benchmark methods.展开更多
In the current trend of educational digitization,online learning platforms have proliferated,making the visual design of digital learning resources increasingly critical.However,existing visual designs for online lear...In the current trend of educational digitization,online learning platforms have proliferated,making the visual design of digital learning resources increasingly critical.However,existing visual designs for online learning resources face numerous challenges.The emergence of AIGC(Artificial Intelligence-Generated Content)technology offers innovative solutions to these issues.This paper explores the application of AIGC technology in enhancing the“new quality productive forces”of visual design for online learning resources.It emphasizes the need to balance technological innovation with humanistic care and highlights the importance of human intervention in the design process.展开更多
Online interactive learning plays a crucial role in improving online education quality.This grounded theory study examines:(1)what key factors shape EFL learners’online interactive learning,(2)how these factors form ...Online interactive learning plays a crucial role in improving online education quality.This grounded theory study examines:(1)what key factors shape EFL learners’online interactive learning,(2)how these factors form an empirically validated model,and(3)how they interact within this model,through systematic analysis of 9,207 discussion forum posts from a Chinese University MOOC platform.Results demonstrate that learning drive,course structure,teaching competence,interaction behavior,expected outcomes,and online learning context significantly influence EFL online interactive learning.The analysis reveals two key mechanisms:expected outcomes mediate the effects of learning drive(β=0.45),course structure,teaching competence,and interaction behavior(β=0.35)on learning outcomes,while online learning context moderates these relationships(β=0.25).Specifically,learning drive provides intrinsic/extrinsic motivation,whereas course structure,teaching competence,interaction behavior,and expected outcomes collectively enhance interaction quality and sustainability.These findings,derived through rigorous grounded theory methodology involving open,axial,and selective coding of large-scale interaction data,yield three key contributions:(1)a comprehensive theoretical model of EFL online learning dynamics,(2)empirical validation of mediation/moderation mechanisms,and(3)practical strategies for designing scaffolded interaction protocols and adaptive feedback systems.The study establishes that its theoretically saturated model(achieved after analyzing 7,366 posts with 1,841 verification cases)offers educators evidence-based approaches to optimize collaborative interaction in digital EFL environments.展开更多
Intensely using online social networks(OSNs)makes users concerned about privacy of data.Given the centralized nature of these platforms,and since each platform has a particular storage mechanism,authentication,and acc...Intensely using online social networks(OSNs)makes users concerned about privacy of data.Given the centralized nature of these platforms,and since each platform has a particular storage mechanism,authentication,and access control,their users do not have the control and the right over their data.Therefore,users cannot easily switch between similar platforms or transfer data from one platform to another.These issues imply,among other things,a threat to privacy since such users depend on the interests of the service provider responsible for administering OSNs.As a strategy for the decentralization of the OSNs and,consequently,as a solution to the privacy problems in these environments,the so-called decentralized online social networks(DOSNs)have emerged.Unlike OSNs,DOSNs are decentralized content management platforms because they do not use centralized service providers.Although DOSNs address some of the privacy issues encountered in OSNs,DOSNs also pose significant challenges to consider,for example,access control to user profile information with high granularity.This work proposes developing an ontological model and a service to support privacy in DOSNs.The model describes the main concepts of privacy access control in DOSNs and their relationships.In addition,the service will consume the model to apply access control according to the policies represented in the model.Our model was evaluated in two phases to verify its compliance with the proposed domain.Finally,we evaluated our service with a performance evaluation,and the results were satisfactory concerning the response time of access control requests.展开更多
To address the widespread challenges of insufficient classroom participation,difficulty maintaining learning interest,and inaccurate learning outcome assessment in existing teaching models,this study introduces a hybr...To address the widespread challenges of insufficient classroom participation,difficulty maintaining learning interest,and inaccurate learning outcome assessment in existing teaching models,this study introduces a hybrid and dual-teacher classroom model.Based on big data and online platforms,this study constructs a music teaching resource system that integrates online micro-lessons,real-time interaction,virtual choirs,collaborative composition,and learning behavior tracking to enhance the openness and personalization of teaching.Through comparative experiments,the study focuses on changes in student knowledge acquisition,musical skills,learning interest,and classroom engagement.Results show that the experimental group significantly outperforms the control group in terms of improvement in knowledge test scores,rhythm and pitch performance,task completion rate,and scores on the learning motivation questionnaire.Differences are particularly prominent in interaction frequency and the expressiveness of the work.The study shows that Group A demonstrates significant improvement in all three dimensions:interest increases from 3.1 to 4.2;autonomous learning motivation increases from 3.0 to 4.1;emotional engagement increases from 3.2 to 4.3,demonstrating strong positive effects.Experimental Group B shows the greatest improvement,with interest increasing from 3.0 to 4.5,autonomous learning motivation from 2.9 to 4.4,and emotional engagement from 3.1 to 4.6,indicating the most significant improvements in learning attitudes and emotions.展开更多
In this paper,an online midcourse guidance method for intercepting high-speed maneuvering targets is proposed.Firstly,the affine system is used to build a dynamic model and analyze the state constraints.The midcourse ...In this paper,an online midcourse guidance method for intercepting high-speed maneuvering targets is proposed.Firstly,the affine system is used to build a dynamic model and analyze the state constraints.The midcourse guidance problem is transformed into a continuous time optimization problem.Secondly,the problem is transformed into a discrete convex programming problem by affine control variable relaxation,Gaussian pseudospectral discretization and constraints linearization.Then,the off-line midcourse guidance trajectory is generated before midcourse guidance.It is used as the initial reference trajectory for online correction of midcourse guidance.An online guidance framework is used to eliminate the error caused by calculation of guidance instruction time.And the design of discrete points decreases with flight time to improve the solving efficiency.In addition,it is proposed that the terminal guidance capture is used innovatively space to judge the success of midcourse guidance.Numerical simulation shows the feasibility and effectiveness of the proposed method.展开更多
This study explored the connection between childhood psychological maltreatment and online trolling,as well as the influence of moral disengagement and mindfulness in that relationship.A total of 984 college students(...This study explored the connection between childhood psychological maltreatment and online trolling,as well as the influence of moral disengagement and mindfulness in that relationship.A total of 984 college students(54%females,Mean age=20.9 years,SD=1.57 years)took part in the current research.The students responded to standardized measures of childhood psychological maltreatment,online trolling,moral disengagement,mindfulness.Results following the regression and the mediation analyses showed that childhood psychological maltreatment was associated with higher online trolling among college students.Moral disengagement played a mediating role in the link between childhood psychological maltreatment and online trolling,predicting to increased trolling behavior.Furthermore,mindfulness moderated the direct connection between moral disengagement and online trolling.Specifically,compared to those with high mindfulness,individuals with high moral disengagement were more inclined to engage in online trolling when they had low mindfulness.These findings add to our understanding of how and when childhood psychological maltreatment relates to online trolling of which moral engagement and mindfulness would be protective.展开更多
Background:Fundamental internal factors like self-construal and its influence on problematic online game use(POGU)remain underexplored.Hence,this study aims to investigate the effects of independent and interdependent...Background:Fundamental internal factors like self-construal and its influence on problematic online game use(POGU)remain underexplored.Hence,this study aims to investigate the effects of independent and interdependent self-construal on POGU,with the mediation of basic psychological needs satisfaction.Methods:The study surveyed 418 Chinese junior high school students(50.24%male;Meanage=12.68,SD=0.65),assessing their levels of self-construal,basic psychological needs satisfaction,and POGU.Aparallelmediationmodelwas tested.Results:The findings showed that autonomy and competence needs satisfaction fully mediated the negative impact of independent self-construal on POGU(B=−0.052,p<0.05;B=−0.094,p<0.01,respectively),while interdependent self-construal and relatedness needs satisfaction did not have a significant effect on POGU(B=0.005,p=0.758).Additionally,while independent self-construal positively correlated with the satisfaction of all three psychological needs,interdependent self-construal only positively associated with relatedness need satisfaction(B=0.152,p<0.001).Conclusions:The study demonstrates that independent self-construal serves as a protective factor against POGU,mediated by autonomy and competence needs satisfaction,while the effects of interdependent self-construal are more complex.These insights highlight the need for tailored interventions that promote adaptive self-construal and psychological needs satisfaction among Chinese adolescents to prevent POGU.展开更多
Aiming to address the challenge of directly measuring the real-time adhesion coefficient between wheels and rails,this paper proposes an online estimation algorithm for the adhesion coefficient based on parameter esti...Aiming to address the challenge of directly measuring the real-time adhesion coefficient between wheels and rails,this paper proposes an online estimation algorithm for the adhesion coefficient based on parameter estimation.Firstly,a force analysis of the single-wheel pair model of the train is conducted to derive the calculation relationship for the wheel-rail adhesion coefficient in train dynamics.Then,an estimator based on parameter estimation is designed,and its stability is verified.This estimator is combined with the wheelset force analysis to estimate the wheel-rail adhesion coefficient.Finally,the approach is validated through joint simulations on the MATLAB/Simulink and AMESim platforms,as well as a hardware-in-the-loop semi-physical simulation experimental platform that accounts for system delay and noise conditions.The results indicate that the proposed algorithm effectively tracks changes in the adhesion coefficient during train braking,including the decrease in adhesion when the train brakes and slides,and the overall increase as the train speed decreases.The effectiveness of the algorithm was verified by setting different test conditions.The results show that the estimation algorithm can accurately estimate the adhesion coefficient,and through error analysis,it is found that the error between the estimated value of the adhesion coefficient and the theoretical value of the adhesion coefficient is within 5%.The adhesion coefficient obtained through the online estimation method based on the parameter estimation proposed in this paper demonstrates strong followability in both simulation and practical applications.展开更多
基金supported in part by the National Natural Science Foundation of China(62222301,62373012,62473012,62021003)the National Science and Technology Major Project(2021ZD0112302,2021ZD0112301)the Beijing Natural Science Foundation(JQ19013)
文摘In this paper, a fault-tolerant-based online critic learning algorithm is developed to solve the optimal tracking control issue for nonaffine nonlinear systems with actuator faults.First, a novel augmented plant is constructed by fusing the system state and the reference trajectory, which aims to transform the optimal fault-tolerant tracking control design with actuator faults into the optimal regulation problem of the conventional nonlinear error system. Subsequently, in order to ensure the normal execution of the online learning algorithm, a stability criterion condition is created to obtain an initial admissible tracking policy. Then, the constructed model neural network(NN) is pretrained to recognize the system dynamics and calculate trajectory control. The critic and action NNs are constructed to output the approximate cost function and approximate tracking control,respectively. The Hamilton-Jacobi-Bellman equation of the error system is solved online through the action-critic framework. In theoretical analysis, it is proved that all concerned signals are uniformly ultimately bounded according to the Lyapunov principle.The tracking control law can approach the optimal tracking control within a finite approximation error. Finally, two experimental examples are conducted to indicate the effectiveness and superiority of the developed fault-tolerant tracking control scheme.
基金financial support by Sichuan Science and Technology,China(No.2023YFG0070).
文摘Fuel cell electric vehicles hold great promise for a diverse range of applications in reducing greenhouse gas emissions.In power fuel cell systems,hydrogen fuel serves as an energy vector.To ensure its suitability,it is necessary for the quality of hydrogen to adhere to the standards set by ISO 14687:2019,which sets maximum limits for 14 impurities in hydrogen,aiming to prevent any degradation of fuel cell performance.Ammonia(NH_(3))is a prominent pollutant in fuel cells,and accurate measurements of its concentration are crucial for hydrogen fuel cell quantity.In this study,a novel detection platform was developed for determining NH_(3)in real hydrogen samples.The online analysis platform integrates a self-developed online dilution module with a Fourier transform infrared spectrometer(ODM-FTIR).The ODM-FTIR can be operated fully automatically with remote operation.Under the optimum conditions,this method achieved a wide linear range between(50∼1000)nmol/mol.The limit of detection(LOD)was as low as 2 nmol/mol with a relative standard deviation(RSD,n=7)of 3.6%at a content of 50 nmol/mol.To ensure that the quality of the hydrogen products meets the requirement of proton exchange membrane fuel cell vehicles(PEMFCV),the developed ODM-FTIR system was applied to monitor the NH_(3)content in Chengdu Hydrogen Energy Co.,Ltd.for 21 days during Chengdu 2021 FISU World University Games.The proposed method retains several unique advantages,including a low detection limit,excellent repeatability,high accuracy,high speed,good stability,and calibration flexibility.It is an effective analytical method for accurately quantifying NH_(3)in hydrogen,especially suitable for online analysis.It also provides a new idea for the analysis of other impurity components in hydrogen.
基金Supported by State Grid Zhejiang Electric Power Co.,Ltd.Science and Technology Project Funding(No.B311DS230005).
文摘To address the issue of coordinated control of multiple hydrogen and battery storage units to suppress the grid-injected power deviation of wind farms,an online optimization strategy for Battery-hydrogen hybrid energy storage systems based on measurement feedback is proposed.First,considering the high charge/discharge losses of hydrogen storage and the low energy density of battery storage,an operational optimization objective is established to enable adaptive energy adjustment in the Battery-hydrogen hybrid energy storage system.Next,an online optimization model minimizing the operational cost of the hybrid system is constructed to suppress grid-injected power deviations with satisfying the operational constraints of hydrogen storage and batteries.Finally,utilizing the online measurement of the energy states of hydrogen storage and batteries,an online optimization strategy based on measurement feedback is designed.Case study results show:before and after smoothing the fluctuations in wind power,the time when the power exceeded the upper and lower limits of the grid-injected power accounted for 24.1%and 1.45%of the total time,respectively,the proposed strategy can effectively keep the grid-injected power deviations of wind farms within the allowable range.Hydrogen storage and batteries respectively undertake long-term and short-term charge/discharge tasks,effectively reducing charge/discharge losses of the Battery-hydrogen hybrid energy storage systems and improving its operational efficiency.
文摘In order to address the current inability of screen printing to monitor printing pressure online,an online printing pressure monitoring system applied to screen printing machines was designed in this study.In this study,the consistency of printed electrodes was measured by using a confocal microscope and the pressure distribution detected by online pressure monitoring system was compared to investigate the relationship.The results demonstrated the relationship between printing pressure and the consistency of printed electrodes.As printing pressure increases,the ink layer at the corresponding position becomes thicker and that higher printing pressure enhances the consistency of the printed electrodes.The experiment confirms the feasibility of the online pressure monitoring system,which aids in predicting and controlling the consistency of printed electrodes,thereby improving their performance.
基金funding from the U.S.-Kazakhstan University Partnerships program funded by the U.S.Mission to Kazakhstan and administered by American Councils[Award number SKZ100-19-CA-0149].
文摘As world events have morphed teachers’roles within English medium of instruction(EMI)contexts to incorporate more online teaching practices,teachers’integration of digital tools has faced technological and curricular challenges.While previous research has examined the integration of digital tools in face-to-face and hybrid EMI settings(e.g.,Finardi,2015;O’Dowd,2018),more research is needed to understand the familiarization process teachers engage in as they implement fully-online teaching to support their content and language integrated learning(CLIL)teaching.As part of a larger project,this case study sets out to fill this gap by examining the practices and perspectives of 30 Kazakhstani university teachers who adopted CLIL approaches while needing to adapt to fully-online teaching contexts.Using the concept of technological pedagogical content knowledge(Mishra&Koehler,2006)in tandem with Ball et al.’s(2016)seven CLIL principles as a framework,this study thematically analyzed workshop artifacts,survey responses,semi-structured interview transcripts,and videos from online class lessons to find that teachers were mediators and curators of content,language,pedagogy,and digital tools.The findings offer pedagogical insights for the implementation of professional development(PD)to prepare teachers to meaningfully curate and mediate technology into their CLIL pedagogy to teach content within EMI contexts.
文摘Online learning has taken root and with the advancement in technology more and more educators are embracing online learning.During the COVID-19 pandemic,with total shut down of face-to-face learning,the Kenyan government had moved learning online and remotely.To find out on how learners in remote areas were experiencing learning during the COVID-19 pandemic,a study was carried out using rapid ethnography design.Five final year secondary students were sampled.Data was collected through interviews,observations,and document analysis.This paper reports on the findings of online and remote learning platforms,which were available,accessed,and preferred by the learners in remote areas of Kenya during the pandemic.It also highlights the importance of e-learning platforms in addressing learning experiences and success.
基金supported by Planning Project of Shanghai Higher Education Association(2QYB24158)Collaborative Education Project of the Ministry of Education of China(250101414020206).
文摘To bridge the gap between curriculum content and clinical needs,as well as address the insufficient quality of online educational resources in current postgraduate anesthesiology education,this study proposes a“library-style”network resource platform for anesthesia graduate students,grounded in the competency-based medical education framework.The platform’s primary focus is“classical knowledge module”,which covers six core domains in anesthesiology,such as clinical anesthesia management,anesthesia technical operation,and anesthesia pharmacology.The platform also integrates‘Internet+’technology,creating a multifunctional network resource to support comprehensive learning.The platform is characterized by modularized knowledge,diversified resources,dynamic updates,and universal accessibility,enabling postgraduate students to engage in independent and lifelong learning.This flexibility fosters the innovation of hybrid teaching models,combining both online and offline components.The study aims to strengthen the competency-oriented anesthesia training system,providing robust support for both clinical practice and academic research.
文摘The rapid development of online education has posed brand-new challenges to the teaching quality monitoring system in colleges and universities.This paper systematically explores the three major characteristics of online teaching quality monitoring in colleges and universities:the complexity of monitoring brought by the separation of time and space,the enhanced accuracy based on technology dependence,and the monitoring dimensions expanded by the diversification of interaction.The research reveals the key existing problems at present,including the analytical predicament caused by data fragmentation,the stability crisis triggered by technical failures,and the validity limitations due to the insufficient adaptability of teachers and students.In response to these challenges,this paper proposes systematic solutions such as building a unified data platform,strengthening the technical support system,and conducting targeted training.Through multi-dimensional analysis,this study provides a theoretical framework and practical path for constructing a quality monitoring system that ADAPTS to the characteristics of online education,and has important reference value for improving the quality of online teaching in colleges and universities.
基金supported by the IITP(Institute of Information&Communications Technology Planning&Evaluation)-ITRC(Information Technology Research Center)grant funded by the Korean government(Ministry of Science and ICT)(IITP-2025-RS-2024-00438056).
文摘The increased accessibility of social networking services(SNSs)has facilitated communication and information sharing among users.However,it has also heightened concerns about digital safety,particularly for children and adolescents who are increasingly exposed to online grooming crimes.Early and accurate identification of grooming conversations is crucial in preventing long-term harm to victims.However,research on grooming detection in South Korea remains limited,as existing models trained primarily on English text and fail to reflect the unique linguistic features of SNS conversations,leading to inaccurate classifications.To address these issues,this study proposes a novel framework that integrates optical character recognition(OCR)technology with KcELECTRA,a deep learning-based natural language processing(NLP)model that shows excellent performance in processing the colloquial Korean language.In the proposed framework,the KcELECTRA model is fine-tuned by an extensive dataset,including Korean social media conversations,Korean ethical verification data from AI-Hub,and Korean hate speech data from Hug-gingFace,to enable more accurate classification of text extracted from social media conversation images.Experimental results show that the proposed framework achieves an accuracy of 0.953,outperforming existing transformer-based models.Furthermore,OCR technology shows high accuracy in extracting text from images,demonstrating that the proposed framework is effective for online grooming detection.The proposed framework is expected to contribute to the more accurate detection of grooming text and the prevention of grooming-related crimes.
基金funded by the State Key Laboratory of Massive Personalized Customization System and Technology,grant No.H&C-MPC-2023-04-01.
文摘This paper investigates mobility-aware online optimization for digital twin(DT)-assisted task execution in edge computing environments.In such systems,DTs,hosted on edge servers(ESs),require proactive migration to maintain proximity to their mobile physical twin(PT)counterparts.To minimize task response latency under a stringent energy consumption constraint,we jointly optimize three key components:the status data uploading frequency fromthe PT,theDT migration decisions,and the allocation of computational and communication resources.To address the asynchronous nature of these decisions,we propose a novel two-timescale mobility-aware online optimization(TMO)framework.The TMO scheme leverages an extended two-timescale Lyapunov optimization framework to decompose the long-term problem into sequential subproblems.At the larger timescale,a multi-armed bandit(MAB)algorithm is employed to dynamically learn the optimal status data uploading frequency.Within each shorter timescale,we first employ a gated recurrent unit(GRU)-based predictor to forecast the PT’s trajectory.Based on this prediction,an alternate minimization(AM)algorithm is then utilized to solve for the DT migration and resource allocation variables.Theoretical analysis confirms that the proposed TMO scheme is asymptotically optimal.Furthermore,simulation results demonstrate its significant performance gains over existing benchmark methods.
文摘In the current trend of educational digitization,online learning platforms have proliferated,making the visual design of digital learning resources increasingly critical.However,existing visual designs for online learning resources face numerous challenges.The emergence of AIGC(Artificial Intelligence-Generated Content)technology offers innovative solutions to these issues.This paper explores the application of AIGC technology in enhancing the“new quality productive forces”of visual design for online learning resources.It emphasizes the need to balance technological innovation with humanistic care and highlights the importance of human intervention in the design process.
文摘Online interactive learning plays a crucial role in improving online education quality.This grounded theory study examines:(1)what key factors shape EFL learners’online interactive learning,(2)how these factors form an empirically validated model,and(3)how they interact within this model,through systematic analysis of 9,207 discussion forum posts from a Chinese University MOOC platform.Results demonstrate that learning drive,course structure,teaching competence,interaction behavior,expected outcomes,and online learning context significantly influence EFL online interactive learning.The analysis reveals two key mechanisms:expected outcomes mediate the effects of learning drive(β=0.45),course structure,teaching competence,and interaction behavior(β=0.35)on learning outcomes,while online learning context moderates these relationships(β=0.25).Specifically,learning drive provides intrinsic/extrinsic motivation,whereas course structure,teaching competence,interaction behavior,and expected outcomes collectively enhance interaction quality and sustainability.These findings,derived through rigorous grounded theory methodology involving open,axial,and selective coding of large-scale interaction data,yield three key contributions:(1)a comprehensive theoretical model of EFL online learning dynamics,(2)empirical validation of mediation/moderation mechanisms,and(3)practical strategies for designing scaffolded interaction protocols and adaptive feedback systems.The study establishes that its theoretically saturated model(achieved after analyzing 7,366 posts with 1,841 verification cases)offers educators evidence-based approaches to optimize collaborative interaction in digital EFL environments.
基金Fundação de AmparoàPesquisa do Estado da Bahia(FAPESB),Coordenação de Aperfeiçoamento de Pessoal de Nível Superior(CAPES)Conselho Nacional de Desenvolvimento Científico e Tecnológico(CNPq)organizations for supporting the Graduate Program in Computer Science at the Federal University of Bahia.
文摘Intensely using online social networks(OSNs)makes users concerned about privacy of data.Given the centralized nature of these platforms,and since each platform has a particular storage mechanism,authentication,and access control,their users do not have the control and the right over their data.Therefore,users cannot easily switch between similar platforms or transfer data from one platform to another.These issues imply,among other things,a threat to privacy since such users depend on the interests of the service provider responsible for administering OSNs.As a strategy for the decentralization of the OSNs and,consequently,as a solution to the privacy problems in these environments,the so-called decentralized online social networks(DOSNs)have emerged.Unlike OSNs,DOSNs are decentralized content management platforms because they do not use centralized service providers.Although DOSNs address some of the privacy issues encountered in OSNs,DOSNs also pose significant challenges to consider,for example,access control to user profile information with high granularity.This work proposes developing an ontological model and a service to support privacy in DOSNs.The model describes the main concepts of privacy access control in DOSNs and their relationships.In addition,the service will consume the model to apply access control according to the policies represented in the model.Our model was evaluated in two phases to verify its compliance with the proposed domain.Finally,we evaluated our service with a performance evaluation,and the results were satisfactory concerning the response time of access control requests.
文摘To address the widespread challenges of insufficient classroom participation,difficulty maintaining learning interest,and inaccurate learning outcome assessment in existing teaching models,this study introduces a hybrid and dual-teacher classroom model.Based on big data and online platforms,this study constructs a music teaching resource system that integrates online micro-lessons,real-time interaction,virtual choirs,collaborative composition,and learning behavior tracking to enhance the openness and personalization of teaching.Through comparative experiments,the study focuses on changes in student knowledge acquisition,musical skills,learning interest,and classroom engagement.Results show that the experimental group significantly outperforms the control group in terms of improvement in knowledge test scores,rhythm and pitch performance,task completion rate,and scores on the learning motivation questionnaire.Differences are particularly prominent in interaction frequency and the expressiveness of the work.The study shows that Group A demonstrates significant improvement in all three dimensions:interest increases from 3.1 to 4.2;autonomous learning motivation increases from 3.0 to 4.1;emotional engagement increases from 3.2 to 4.3,demonstrating strong positive effects.Experimental Group B shows the greatest improvement,with interest increasing from 3.0 to 4.5,autonomous learning motivation from 2.9 to 4.4,and emotional engagement from 3.1 to 4.6,indicating the most significant improvements in learning attitudes and emotions.
文摘In this paper,an online midcourse guidance method for intercepting high-speed maneuvering targets is proposed.Firstly,the affine system is used to build a dynamic model and analyze the state constraints.The midcourse guidance problem is transformed into a continuous time optimization problem.Secondly,the problem is transformed into a discrete convex programming problem by affine control variable relaxation,Gaussian pseudospectral discretization and constraints linearization.Then,the off-line midcourse guidance trajectory is generated before midcourse guidance.It is used as the initial reference trajectory for online correction of midcourse guidance.An online guidance framework is used to eliminate the error caused by calculation of guidance instruction time.And the design of discrete points decreases with flight time to improve the solving efficiency.In addition,it is proposed that the terminal guidance capture is used innovatively space to judge the success of midcourse guidance.Numerical simulation shows the feasibility and effectiveness of the proposed method.
基金supported by the National Social Science Funds of China“A Study of the Psychosocial Mechanisms of Youth Online Trolling”(23BSH143).
文摘This study explored the connection between childhood psychological maltreatment and online trolling,as well as the influence of moral disengagement and mindfulness in that relationship.A total of 984 college students(54%females,Mean age=20.9 years,SD=1.57 years)took part in the current research.The students responded to standardized measures of childhood psychological maltreatment,online trolling,moral disengagement,mindfulness.Results following the regression and the mediation analyses showed that childhood psychological maltreatment was associated with higher online trolling among college students.Moral disengagement played a mediating role in the link between childhood psychological maltreatment and online trolling,predicting to increased trolling behavior.Furthermore,mindfulness moderated the direct connection between moral disengagement and online trolling.Specifically,compared to those with high mindfulness,individuals with high moral disengagement were more inclined to engage in online trolling when they had low mindfulness.These findings add to our understanding of how and when childhood psychological maltreatment relates to online trolling of which moral engagement and mindfulness would be protective.
基金supported by The National Social Science Fund of China(24ASH013).
文摘Background:Fundamental internal factors like self-construal and its influence on problematic online game use(POGU)remain underexplored.Hence,this study aims to investigate the effects of independent and interdependent self-construal on POGU,with the mediation of basic psychological needs satisfaction.Methods:The study surveyed 418 Chinese junior high school students(50.24%male;Meanage=12.68,SD=0.65),assessing their levels of self-construal,basic psychological needs satisfaction,and POGU.Aparallelmediationmodelwas tested.Results:The findings showed that autonomy and competence needs satisfaction fully mediated the negative impact of independent self-construal on POGU(B=−0.052,p<0.05;B=−0.094,p<0.01,respectively),while interdependent self-construal and relatedness needs satisfaction did not have a significant effect on POGU(B=0.005,p=0.758).Additionally,while independent self-construal positively correlated with the satisfaction of all three psychological needs,interdependent self-construal only positively associated with relatedness need satisfaction(B=0.152,p<0.001).Conclusions:The study demonstrates that independent self-construal serves as a protective factor against POGU,mediated by autonomy and competence needs satisfaction,while the effects of interdependent self-construal are more complex.These insights highlight the need for tailored interventions that promote adaptive self-construal and psychological needs satisfaction among Chinese adolescents to prevent POGU.
基金supported by the National Natural Science Foundation of China(grant/award number 52072266).
文摘Aiming to address the challenge of directly measuring the real-time adhesion coefficient between wheels and rails,this paper proposes an online estimation algorithm for the adhesion coefficient based on parameter estimation.Firstly,a force analysis of the single-wheel pair model of the train is conducted to derive the calculation relationship for the wheel-rail adhesion coefficient in train dynamics.Then,an estimator based on parameter estimation is designed,and its stability is verified.This estimator is combined with the wheelset force analysis to estimate the wheel-rail adhesion coefficient.Finally,the approach is validated through joint simulations on the MATLAB/Simulink and AMESim platforms,as well as a hardware-in-the-loop semi-physical simulation experimental platform that accounts for system delay and noise conditions.The results indicate that the proposed algorithm effectively tracks changes in the adhesion coefficient during train braking,including the decrease in adhesion when the train brakes and slides,and the overall increase as the train speed decreases.The effectiveness of the algorithm was verified by setting different test conditions.The results show that the estimation algorithm can accurately estimate the adhesion coefficient,and through error analysis,it is found that the error between the estimated value of the adhesion coefficient and the theoretical value of the adhesion coefficient is within 5%.The adhesion coefficient obtained through the online estimation method based on the parameter estimation proposed in this paper demonstrates strong followability in both simulation and practical applications.
