The interplay of academic atmosphere,learning motivation,and strategies inherently influences English learning.Effective vocabulary acquisition strategies significantly influence the achievements of English acquisitio...The interplay of academic atmosphere,learning motivation,and strategies inherently influences English learning.Effective vocabulary acquisition strategies significantly influence the achievements of English acquisition.Vocabulary mastery,a cornerstone of middle school English education,raises a critical question:How can vocabulary strategies optimize students’memory,understanding,and vocabulary application?This article elaborates on the importance and characteristics of vocabulary learning in Chinese junior high schools,analyzes definitions and theories of learning strategies,and proposes specific vocabulary approaches tailored to junior high school students in rural-urban fringe areas.展开更多
Student engagement in learning is a concern for teachers in the implementation of blended learning,which reflects the effectiveness of the pedagogical measures taken by teachers.Blended learning encompasses traditiona...Student engagement in learning is a concern for teachers in the implementation of blended learning,which reflects the effectiveness of the pedagogical measures taken by teachers.Blended learning encompasses traditional blended,blended online,and blended synchronous,which combine synchronous and asynchronous teaching and learning activities.This paper adopts an inductive approach to investigate and analyse students‘engagement in learning from three dimensions:behavioural,affective and cognitive,specifically focusing on three meta-categories,namely,course structure and arrangement,choice of teaching and learning activities,and teacher’s role in relation to the course,to investigate the teaching of teachers of different disciplines in three vocational colleges and to analyse the pedagogical strategies that the teachers use in order to improve students’engagement in blended learning.The findings suggest that communicating about the course at the beginning of the semester,clarifying course requirements,and building a trusting relationship with students play a key role in increasing student engagement in blended learning,and that the use of digital tools is an important means of promoting students’behavioural and emotional active participation in learning.展开更多
This study examines the language learning needs and influencing factors of international MBBS students in China, to promote deep learning. Despite compulsory Chinese requirements (Level 4 HSK), a non-immersive environ...This study examines the language learning needs and influencing factors of international MBBS students in China, to promote deep learning. Despite compulsory Chinese requirements (Level 4 HSK), a non-immersive environment often leads to motivation issues. Findings reveal that students perceive their needs as phased, homogeneous yet diverse, and not universal. Daily and professional communication demands, positive teacher-student relationships, and successful language application drive deep learning. Key strategies are proposed, including enhancing teacher quality, developing structured materials that bridge general and medical Chinese, implementing scenario-based teaching that prioritizes speaking/listening, and optimizing the curriculum for continuous exposure and a balanced workload. The ultimate goal is to cultivate competent communicators for medical practice and daily life in China.展开更多
The research topic of the author’s PhD dissertation is“The Impact of Motivation Cultivation on English Autonomous Learning among University Students in Hunan,China—A Mediating Role of Learning Strategy.”Within thi...The research topic of the author’s PhD dissertation is“The Impact of Motivation Cultivation on English Autonomous Learning among University Students in Hunan,China—A Mediating Role of Learning Strategy.”Within this topic,three key variables are identified:the dependent variable(DV),the independent variable(IV),and the mediating variable(MV).Specifically,the DV refers to English autonomous learning,the IV refers to motivation,and the MV refers to learning strategy.The research establishes that the MV(learning strategy)is an integral component of information processing theory(IPT).Consequently,the dissertation incorporates integrative and instrumental motivation theories alongside IPT as its foundational theoretical framework.This paper aims to explore the theoretical framework of the PhD dissertation in detail,focusing on the interplay of these three theories.展开更多
An intelligent endo-atmospheric penetration strategy based on generative adversarialreinforcement learning is proposed in this manuscript.Firstly,attack and defense adversarial mod-els are established,and missile mane...An intelligent endo-atmospheric penetration strategy based on generative adversarialreinforcement learning is proposed in this manuscript.Firstly,attack and defense adversarial mod-els are established,and missile maneuver penetration problem is transformed into an optimal con-trol problem,considering penetration,handover position and mid-terminal guidance velocityconstraints.Then,Radau Pseudospectral method is adopted to generate data samples consideringrandom perturbations.Furthermore,Generative Adversarial Imitation Learning Combined withDeep Deterministic Policy Gradient method(GAIL-DDPG)is designed,with internal processreward signals constructed to tackle long-term sparse reward in missile manuver penetration prob-lem.Finally,penetration strategy is trained and verified.Simulation shows that using generativeadversarial reinforcement learning,with sample library to learn expert experience in training earlystage,the proposed method can quickly converge.Also,performance is further optimized with rein-forcement learning exploration strategy in the later stage of training.Simulation shows that the pro-posed method has better engineering application ability compared with traditional reinforcementlearning method.展开更多
In Internet of Vehicles,VehicleInfrastructure-Cloud cooperation supports diverse intelligent driving and intelligent transportation applications.Federated Learning(FL)is the emerging computation paradigm to provide ef...In Internet of Vehicles,VehicleInfrastructure-Cloud cooperation supports diverse intelligent driving and intelligent transportation applications.Federated Learning(FL)is the emerging computation paradigm to provide efficient and privacypreserving collaborative learning.However,in Io V environment,federated learning faces the challenges introduced by high mobility of vehicles and nonIndependently Identically Distribution(non-IID)of data.High mobility causes FL clients quit and the communication offline.The non-IID data leads to slow and unstable convergence of global model and single global model's weak adaptability to clients with different localization characteristics.Accordingly,this paper proposes a personalized aggregation strategy for hierarchical Federated Learning in Io V environment,including Fed SA(Special Asynchronous Federated Learning with Self-adaptive Aggregation)for low-level FL between a Road Side Unit(RSU)and the vehicles within its coverage,and Fed Att(Federated Learning with Attention Mechanism)for high-level FL between a cloud server and multiple RSUs.Agents self-adaptively obtain model aggregation weight based on Advantage Actor-Critic(A2C)algorithm.Experiments show the proposed strategy encourages vehicles to participate in global aggregation,and outperforms existing methods in training performance.展开更多
With the rapid popularization of artificial intelligence technology in the field of higher education,college students are increasingly dependent on AI tools such as ChatGPT,automatic writing assistants,and intelligent...With the rapid popularization of artificial intelligence technology in the field of higher education,college students are increasingly dependent on AI tools such as ChatGPT,automatic writing assistants,and intelligent translators.Behind the convenience and efficiency,a decline trend in students’core learning abilities such as autonomous learning ability,critical thinking ability,and knowledge construction ability has gradually emerged.This study aims to explore the interactive logical mechanism between college students’reliance on AI tools and the weakening of their learning abilities,and on this basis,propose practical and feasible educational intervention strategies.Research has found that while AI tools lower the learning threshold,they also weaken students’cognitive investment and independent thinking abilities,further intensifying their reliance on technology.In this regard,this paper proposes a three-dimensional intervention path based on guided usage,ability compensation,and value reconstruction to achieve the collaborative improvement of students’technical usage ability and learning ability.This research has certain theoretical value and practical enlightenment significance for solving the structural predicament of higher education in the intelligent era.展开更多
In practical combat scenarios,Hypersonic Glide Vehicles(HGV)face the challenge of evading Successive Pursuers from the Same Direction while satisfying the Homing Constraint(SPSDHC).To address this problem,this paper p...In practical combat scenarios,Hypersonic Glide Vehicles(HGV)face the challenge of evading Successive Pursuers from the Same Direction while satisfying the Homing Constraint(SPSDHC).To address this problem,this paper proposes a parameterized evasion guidance algorithm based on reinforcement learning.The three-player optimal evasion strategy is firstly analyzed and approximated by parametrization.The switching acceleration command of HGV optimal evasion strategy considering the upper limit of missile acceleration command is analyzed based on the optimal control theory.The terminal miss of HGV in the case of evading two missiles is analyzed,which means that the three-player optimal evasion strategy is a linear combination of two one-toone strategies.Then,a velocity control algorithm is proposed to increase the terminal miss by actively controlling the flight speed of the HGV based on the parametrized evasion strategy.The reinforcement learning method is used to implement the strategy in real time and a reward function is designed by deducing homing strategy for the HGV to approach the target,which ensures that the HGV satisfies the homing constraint.Experimental results demonstrate the feasibility and robustness of the proposed parameterized evasion strategy,which enables the HGV to generate maximum terminal miss and satisfy homing constraint when facing single or double missiles.展开更多
In recent years,robotic arm grasping has become a pivotal task in the field of robotics,with applications spanning from industrial automation to healthcare.The optimization of grasping strategies plays a crucial role ...In recent years,robotic arm grasping has become a pivotal task in the field of robotics,with applications spanning from industrial automation to healthcare.The optimization of grasping strategies plays a crucial role in enhancing the effectiveness,efficiency,and reliability of robotic systems.This paper presents a novel approach to optimizing robotic arm grasping strategies based on deep reinforcement learning(DRL).Through the utilization of advanced DRL algorithms,such as Q-Learning,Deep Q-Networks(DQN),Policy Gradient Methods,and Proximal Policy Optimization(PPO),the study aims to improve the performance of robotic arms in grasping objects with varying shapes,sizes,and environmental conditions.The paper provides a detailed analysis of the various deep reinforcement learning methods used for grasping strategy optimization,emphasizing the strengths and weaknesses of each algorithm.It also presents a comprehensive framework for training the DRL models,including simulation environment setup,the optimization process,and the evaluation metrics for grasping success.The results demonstrate that the proposed approach significantly enhances the accuracy and stability of the robotic arm in performing grasping tasks.The study further explores the challenges in training deep reinforcement learning models for real-time robotic applications and offers solutions for improving the efficiency and reliability of grasping strategies.展开更多
Within-Visual-Range(WVR)air combat is a highly dynamic and uncertain domain where effective strategies require intelligent and adaptive decision-making.Traditional approaches,including rule-based methods and conventio...Within-Visual-Range(WVR)air combat is a highly dynamic and uncertain domain where effective strategies require intelligent and adaptive decision-making.Traditional approaches,including rule-based methods and conventional Reinforcement Learning(RL)algorithms,often focus on maximizing engagement outcomes through direct combat superiority.However,these methods overlook alternative tactics,such as inducing adversaries to crash,which can achieve decisive victories with lower risk and cost.This study proposes Alpha Crash,a novel distributional-rein forcement-learning-based agent specifically designed to defeat opponents by leveraging crash induction strategies.The approach integrates an improved QR-DQN framework to address uncertainties and adversarial tactics,incorporating advanced pilot experience into its reward functions.Extensive simulations reveal Alpha Crash's robust performance,achieving a 91.2%win rate across diverse scenarios by effectively guiding opponents into critical errors.Visualization and altitude analyses illustrate the agent's three-stage crash induction strategies that exploit adversaries'vulnerabilities.These findings underscore Alpha Crash's potential to enhance autonomous decision-making and strategic innovation in real-world air combat applications.展开更多
The purpose of this research is to analyze the causal mechanisms of learning difficulties of middle school students and use them to propose strategies to help them.This research is particularly valuable for its focus ...The purpose of this research is to analyze the causal mechanisms of learning difficulties of middle school students and use them to propose strategies to help them.This research is particularly valuable for its focus on middle school students.Research on this critical transition period is often lacking compared to primary and high school.Therefore,this research establishes a structured equation model and analyzes the data from the survey using the partial least squares method.The data were obtained from a 13,900 Wenzhou City,China students’questionnaire.The research found that learning strategies were the most significant influences on learning effectiveness,followed by learning motivation and learning relationships.Meanwhile,learning relationships had a significant impact on learning pressure.Therefore,this research proposes targeted support strategies.It aims to enhance learning motivation(Set achievable learning goals for each student with learning difficulties based on their actual situation),optimize learning strategies(Encourage students with learning difficulties to learn self-regulatory strategies such as goal setting,time management,and self-reflection),and improve learning relationships(Establish a good social network to promote positive interaction between students with learning difficulties and their peers).At the same time,it reduces students’learning pressure.Ultimately,the learning effectiveness of students with learning difficulties is improved.展开更多
Multi-constrained pipes conveying fluid,such as aircraft hydraulic control pipes,are susceptible to resonance fatigue in harsh vibration environments,which may lead to system failure and even catastrophic accidents.In...Multi-constrained pipes conveying fluid,such as aircraft hydraulic control pipes,are susceptible to resonance fatigue in harsh vibration environments,which may lead to system failure and even catastrophic accidents.In this study,a machine learning(ML)-assisted weak vibration design method under harsh environmental excitations is proposed.The dynamic model of a typical pipe is developed using the absolute nodal coordinate formulation(ANCF)to determine its vibrational characteristics.With the harsh vibration environments as the preserved frequency band(PFB),the safety design is defined by comparing the natural frequency with the PFB.By analyzing the safety design of pipes with different constraint parameters,the dataset of the absolute safety length and the absolute resonance length of the pipe is obtained.This dataset is then utilized to develop genetic programming(GP)algorithm-based ML models capable of producing explicit mathematical expressions of the pipe's absolute safety length and absolute resonance length with the location,stiffness,and total number of retaining clips as design variables.The proposed ML models effectively bridge the dataset with the prediction results.Thus,the ML model is utilized to stagger the natural frequency,and the PFB is utilized to achieve the weak vibration design.The findings of the present study provide valuable insights into the practical application of weak vibration design.展开更多
Learning strategies are critical in the process of learning, knowing, and thinking. Without strategies, nobody can reach competence, to master certain knowledge and skills which makes him/her an independent learner. T...Learning strategies are critical in the process of learning, knowing, and thinking. Without strategies, nobody can reach competence, to master certain knowledge and skills which makes him/her an independent learner. The purose of this paper is trying to demonstrate an overview of leaning strategies based on the researches and studies have been done in the field with emphasis on strategy instruction for increasing reading comprehension and writing instruction.展开更多
According to schema theory resulting from the psycholinguistic model of reading,comprehending a text is an interactive process between the reader background knowledge and the text. This article first views the psychol...According to schema theory resulting from the psycholinguistic model of reading,comprehending a text is an interactive process between the reader background knowledge and the text. This article first views the psycholinguistic model of reading and research in learning strategies, then discusses the application of socioaffective,cognitive, metacognitive learning strategies in Chinese EFL learners’ reading comprehension.展开更多
This study explores how the Chinese learners apply the learning strategies in the language learning.The research examines how to understand EFL learners uses of learning strategies in language learning.The SILL(the St...This study explores how the Chinese learners apply the learning strategies in the language learning.The research examines how to understand EFL learners uses of learning strategies in language learning.The SILL(the Strategy Inventory for Language Learning) was the instrument of this study.The results show that the frequency of strategy use does not vary among the different levels of learners based on the SILL's mean scores.The results suggest that as the learners' levels become higher,the EFL learners tend to choose more strategies which are reflective of their active learning.展开更多
As the ultimate goal of education, autonomy in language learning has aroused a lot of attention from scholars at home and abroad. While in universities of China, students do not have strong autonomy in English languag...As the ultimate goal of education, autonomy in language learning has aroused a lot of attention from scholars at home and abroad. While in universities of China, students do not have strong autonomy in English language learning. The author tries to adopt specific meta-cognitive strategies to facilitate students＇ autonomy in learning by improving learners＇ capacities in study planning or management, monitoring and evaluating in learning to raise their consciousness and ability in autonomy, and lay a foundation for life-long learning.展开更多
The thesis introduces a comparative study of students'autonomous listening practice in a web-based autonomous learning center and the traditional teacher-dominated listening practice in a traditional language lab....The thesis introduces a comparative study of students'autonomous listening practice in a web-based autonomous learning center and the traditional teacher-dominated listening practice in a traditional language lab.The purpose of the study is to find how students'listening strategies differ in these two approaches and thereby to find which one better facilitates students'listening proficiency.展开更多
This paper concentrates on the depth of vocabulary knowledge and vocabulary learning metacognitive strategies used by Chinese non-English majors in an independent college.Results show the depth of vocabulary knowledge...This paper concentrates on the depth of vocabulary knowledge and vocabulary learning metacognitive strategies used by Chinese non-English majors in an independent college.Results show the depth of vocabulary knowledge of the subjects only reaches the passing level.And metacognitive strategies are correlated significantly with the depth of vocabulary knowledge.展开更多
文摘The interplay of academic atmosphere,learning motivation,and strategies inherently influences English learning.Effective vocabulary acquisition strategies significantly influence the achievements of English acquisition.Vocabulary mastery,a cornerstone of middle school English education,raises a critical question:How can vocabulary strategies optimize students’memory,understanding,and vocabulary application?This article elaborates on the importance and characteristics of vocabulary learning in Chinese junior high schools,analyzes definitions and theories of learning strategies,and proposes specific vocabulary approaches tailored to junior high school students in rural-urban fringe areas.
文摘Student engagement in learning is a concern for teachers in the implementation of blended learning,which reflects the effectiveness of the pedagogical measures taken by teachers.Blended learning encompasses traditional blended,blended online,and blended synchronous,which combine synchronous and asynchronous teaching and learning activities.This paper adopts an inductive approach to investigate and analyse students‘engagement in learning from three dimensions:behavioural,affective and cognitive,specifically focusing on three meta-categories,namely,course structure and arrangement,choice of teaching and learning activities,and teacher’s role in relation to the course,to investigate the teaching of teachers of different disciplines in three vocational colleges and to analyse the pedagogical strategies that the teachers use in order to improve students’engagement in blended learning.The findings suggest that communicating about the course at the beginning of the semester,clarifying course requirements,and building a trusting relationship with students play a key role in increasing student engagement in blended learning,and that the use of digital tools is an important means of promoting students’behavioural and emotional active participation in learning.
基金supported by the Chinese Testing International Co.,Ltd.(CTI)under Grant CTI2022B01.
文摘This study examines the language learning needs and influencing factors of international MBBS students in China, to promote deep learning. Despite compulsory Chinese requirements (Level 4 HSK), a non-immersive environment often leads to motivation issues. Findings reveal that students perceive their needs as phased, homogeneous yet diverse, and not universal. Daily and professional communication demands, positive teacher-student relationships, and successful language application drive deep learning. Key strategies are proposed, including enhancing teacher quality, developing structured materials that bridge general and medical Chinese, implementing scenario-based teaching that prioritizes speaking/listening, and optimizing the curriculum for continuous exposure and a balanced workload. The ultimate goal is to cultivate competent communicators for medical practice and daily life in China.
基金Swan College of Central South University of Forestry and Technology Teaching Reform Research Project“The Impact of Teachers’Task-Based Teaching Method on English Interpreting Learning among University Students in Hunan,China”(SWXYJGPJ27)Swan College of Central South University of Forestry and Technology Scientific Research Project“The Impact of Integrative Motivation and Instrumental Motivation on English Autonomous Learning among University Students in Hunan,China--A Mediating Role of Learning Strategy”(SYXY202441)。
文摘The research topic of the author’s PhD dissertation is“The Impact of Motivation Cultivation on English Autonomous Learning among University Students in Hunan,China—A Mediating Role of Learning Strategy.”Within this topic,three key variables are identified:the dependent variable(DV),the independent variable(IV),and the mediating variable(MV).Specifically,the DV refers to English autonomous learning,the IV refers to motivation,and the MV refers to learning strategy.The research establishes that the MV(learning strategy)is an integral component of information processing theory(IPT).Consequently,the dissertation incorporates integrative and instrumental motivation theories alongside IPT as its foundational theoretical framework.This paper aims to explore the theoretical framework of the PhD dissertation in detail,focusing on the interplay of these three theories.
文摘An intelligent endo-atmospheric penetration strategy based on generative adversarialreinforcement learning is proposed in this manuscript.Firstly,attack and defense adversarial mod-els are established,and missile maneuver penetration problem is transformed into an optimal con-trol problem,considering penetration,handover position and mid-terminal guidance velocityconstraints.Then,Radau Pseudospectral method is adopted to generate data samples consideringrandom perturbations.Furthermore,Generative Adversarial Imitation Learning Combined withDeep Deterministic Policy Gradient method(GAIL-DDPG)is designed,with internal processreward signals constructed to tackle long-term sparse reward in missile manuver penetration prob-lem.Finally,penetration strategy is trained and verified.Simulation shows that using generativeadversarial reinforcement learning,with sample library to learn expert experience in training earlystage,the proposed method can quickly converge.Also,performance is further optimized with rein-forcement learning exploration strategy in the later stage of training.Simulation shows that the pro-posed method has better engineering application ability compared with traditional reinforcementlearning method.
基金supported by the National Natural Science Foundation of China under Grant 61931005Beijing Natural Science Foundation under Grant L202018the Key Laboratory of Internet of Vehicle Technical Innovation and Testing(CAICT),Ministry of Industry and Information Technology under Grant No.KL-2023-001。
文摘In Internet of Vehicles,VehicleInfrastructure-Cloud cooperation supports diverse intelligent driving and intelligent transportation applications.Federated Learning(FL)is the emerging computation paradigm to provide efficient and privacypreserving collaborative learning.However,in Io V environment,federated learning faces the challenges introduced by high mobility of vehicles and nonIndependently Identically Distribution(non-IID)of data.High mobility causes FL clients quit and the communication offline.The non-IID data leads to slow and unstable convergence of global model and single global model's weak adaptability to clients with different localization characteristics.Accordingly,this paper proposes a personalized aggregation strategy for hierarchical Federated Learning in Io V environment,including Fed SA(Special Asynchronous Federated Learning with Self-adaptive Aggregation)for low-level FL between a Road Side Unit(RSU)and the vehicles within its coverage,and Fed Att(Federated Learning with Attention Mechanism)for high-level FL between a cloud server and multiple RSUs.Agents self-adaptively obtain model aggregation weight based on Advantage Actor-Critic(A2C)algorithm.Experiments show the proposed strategy encourages vehicles to participate in global aggregation,and outperforms existing methods in training performance.
基金The 2024 Higher Education Teaching Reform Project of Guangdong University of Science and Technology,“Teaching Practice of Human Resource Management Course Based on SPOC+FC Hybrid Teaching Mode”(GKZLGC2024024)。
文摘With the rapid popularization of artificial intelligence technology in the field of higher education,college students are increasingly dependent on AI tools such as ChatGPT,automatic writing assistants,and intelligent translators.Behind the convenience and efficiency,a decline trend in students’core learning abilities such as autonomous learning ability,critical thinking ability,and knowledge construction ability has gradually emerged.This study aims to explore the interactive logical mechanism between college students’reliance on AI tools and the weakening of their learning abilities,and on this basis,propose practical and feasible educational intervention strategies.Research has found that while AI tools lower the learning threshold,they also weaken students’cognitive investment and independent thinking abilities,further intensifying their reliance on technology.In this regard,this paper proposes a three-dimensional intervention path based on guided usage,ability compensation,and value reconstruction to achieve the collaborative improvement of students’technical usage ability and learning ability.This research has certain theoretical value and practical enlightenment significance for solving the structural predicament of higher education in the intelligent era.
基金supported by the National Natural Science Foundation of China(No.62103014)。
文摘In practical combat scenarios,Hypersonic Glide Vehicles(HGV)face the challenge of evading Successive Pursuers from the Same Direction while satisfying the Homing Constraint(SPSDHC).To address this problem,this paper proposes a parameterized evasion guidance algorithm based on reinforcement learning.The three-player optimal evasion strategy is firstly analyzed and approximated by parametrization.The switching acceleration command of HGV optimal evasion strategy considering the upper limit of missile acceleration command is analyzed based on the optimal control theory.The terminal miss of HGV in the case of evading two missiles is analyzed,which means that the three-player optimal evasion strategy is a linear combination of two one-toone strategies.Then,a velocity control algorithm is proposed to increase the terminal miss by actively controlling the flight speed of the HGV based on the parametrized evasion strategy.The reinforcement learning method is used to implement the strategy in real time and a reward function is designed by deducing homing strategy for the HGV to approach the target,which ensures that the HGV satisfies the homing constraint.Experimental results demonstrate the feasibility and robustness of the proposed parameterized evasion strategy,which enables the HGV to generate maximum terminal miss and satisfy homing constraint when facing single or double missiles.
文摘In recent years,robotic arm grasping has become a pivotal task in the field of robotics,with applications spanning from industrial automation to healthcare.The optimization of grasping strategies plays a crucial role in enhancing the effectiveness,efficiency,and reliability of robotic systems.This paper presents a novel approach to optimizing robotic arm grasping strategies based on deep reinforcement learning(DRL).Through the utilization of advanced DRL algorithms,such as Q-Learning,Deep Q-Networks(DQN),Policy Gradient Methods,and Proximal Policy Optimization(PPO),the study aims to improve the performance of robotic arms in grasping objects with varying shapes,sizes,and environmental conditions.The paper provides a detailed analysis of the various deep reinforcement learning methods used for grasping strategy optimization,emphasizing the strengths and weaknesses of each algorithm.It also presents a comprehensive framework for training the DRL models,including simulation environment setup,the optimization process,and the evaluation metrics for grasping success.The results demonstrate that the proposed approach significantly enhances the accuracy and stability of the robotic arm in performing grasping tasks.The study further explores the challenges in training deep reinforcement learning models for real-time robotic applications and offers solutions for improving the efficiency and reliability of grasping strategies.
基金supported by the National Key R&D Program of China(No.2021YFB3300602)。
文摘Within-Visual-Range(WVR)air combat is a highly dynamic and uncertain domain where effective strategies require intelligent and adaptive decision-making.Traditional approaches,including rule-based methods and conventional Reinforcement Learning(RL)algorithms,often focus on maximizing engagement outcomes through direct combat superiority.However,these methods overlook alternative tactics,such as inducing adversaries to crash,which can achieve decisive victories with lower risk and cost.This study proposes Alpha Crash,a novel distributional-rein forcement-learning-based agent specifically designed to defeat opponents by leveraging crash induction strategies.The approach integrates an improved QR-DQN framework to address uncertainties and adversarial tactics,incorporating advanced pilot experience into its reward functions.Extensive simulations reveal Alpha Crash's robust performance,achieving a 91.2%win rate across diverse scenarios by effectively guiding opponents into critical errors.Visualization and altitude analyses illustrate the agent's three-stage crash induction strategies that exploit adversaries'vulnerabilities.These findings underscore Alpha Crash's potential to enhance autonomous decision-making and strategic innovation in real-world air combat applications.
基金2025 Wenzhou Key Research Base of Philosophy and Social Science(Wenzhou University Learning Science and Technology Research Centre)Research Project:Investigation and Strategy Research on the Causes of Middle School Students’Learning Difficulties in the Context of the Leading Country in Education.
文摘The purpose of this research is to analyze the causal mechanisms of learning difficulties of middle school students and use them to propose strategies to help them.This research is particularly valuable for its focus on middle school students.Research on this critical transition period is often lacking compared to primary and high school.Therefore,this research establishes a structured equation model and analyzes the data from the survey using the partial least squares method.The data were obtained from a 13,900 Wenzhou City,China students’questionnaire.The research found that learning strategies were the most significant influences on learning effectiveness,followed by learning motivation and learning relationships.Meanwhile,learning relationships had a significant impact on learning pressure.Therefore,this research proposes targeted support strategies.It aims to enhance learning motivation(Set achievable learning goals for each student with learning difficulties based on their actual situation),optimize learning strategies(Encourage students with learning difficulties to learn self-regulatory strategies such as goal setting,time management,and self-reflection),and improve learning relationships(Establish a good social network to promote positive interaction between students with learning difficulties and their peers).At the same time,it reduces students’learning pressure.Ultimately,the learning effectiveness of students with learning difficulties is improved.
基金Project supported by the Foundation for Innovative Research Groups of the National Natural Science Foundation of China(No.12421002)the National Science Funds for Distinguished Young Scholars of China(No.12025204)+1 种基金the National Natural Science Foundation of China(No.12372015)China Scholarship Council(No.202206890065)。
文摘Multi-constrained pipes conveying fluid,such as aircraft hydraulic control pipes,are susceptible to resonance fatigue in harsh vibration environments,which may lead to system failure and even catastrophic accidents.In this study,a machine learning(ML)-assisted weak vibration design method under harsh environmental excitations is proposed.The dynamic model of a typical pipe is developed using the absolute nodal coordinate formulation(ANCF)to determine its vibrational characteristics.With the harsh vibration environments as the preserved frequency band(PFB),the safety design is defined by comparing the natural frequency with the PFB.By analyzing the safety design of pipes with different constraint parameters,the dataset of the absolute safety length and the absolute resonance length of the pipe is obtained.This dataset is then utilized to develop genetic programming(GP)algorithm-based ML models capable of producing explicit mathematical expressions of the pipe's absolute safety length and absolute resonance length with the location,stiffness,and total number of retaining clips as design variables.The proposed ML models effectively bridge the dataset with the prediction results.Thus,the ML model is utilized to stagger the natural frequency,and the PFB is utilized to achieve the weak vibration design.The findings of the present study provide valuable insights into the practical application of weak vibration design.
文摘Learning strategies are critical in the process of learning, knowing, and thinking. Without strategies, nobody can reach competence, to master certain knowledge and skills which makes him/her an independent learner. The purose of this paper is trying to demonstrate an overview of leaning strategies based on the researches and studies have been done in the field with emphasis on strategy instruction for increasing reading comprehension and writing instruction.
文摘According to schema theory resulting from the psycholinguistic model of reading,comprehending a text is an interactive process between the reader background knowledge and the text. This article first views the psycholinguistic model of reading and research in learning strategies, then discusses the application of socioaffective,cognitive, metacognitive learning strategies in Chinese EFL learners’ reading comprehension.
文摘This study explores how the Chinese learners apply the learning strategies in the language learning.The research examines how to understand EFL learners uses of learning strategies in language learning.The SILL(the Strategy Inventory for Language Learning) was the instrument of this study.The results show that the frequency of strategy use does not vary among the different levels of learners based on the SILL's mean scores.The results suggest that as the learners' levels become higher,the EFL learners tend to choose more strategies which are reflective of their active learning.
文摘As the ultimate goal of education, autonomy in language learning has aroused a lot of attention from scholars at home and abroad. While in universities of China, students do not have strong autonomy in English language learning. The author tries to adopt specific meta-cognitive strategies to facilitate students＇ autonomy in learning by improving learners＇ capacities in study planning or management, monitoring and evaluating in learning to raise their consciousness and ability in autonomy, and lay a foundation for life-long learning.
文摘The thesis introduces a comparative study of students'autonomous listening practice in a web-based autonomous learning center and the traditional teacher-dominated listening practice in a traditional language lab.The purpose of the study is to find how students'listening strategies differ in these two approaches and thereby to find which one better facilitates students'listening proficiency.
文摘This paper concentrates on the depth of vocabulary knowledge and vocabulary learning metacognitive strategies used by Chinese non-English majors in an independent college.Results show the depth of vocabulary knowledge of the subjects only reaches the passing level.And metacognitive strategies are correlated significantly with the depth of vocabulary knowledge.
