ESL(English as a Second Language)学习者的口头表达能力成为衡量他们综合素质的重要标准。如何提高ESL学习者的口头交际沟通能力,是我国大学英语教学必须面临的一项重要任务。本文主要研究戏剧活动与ESL学习者口语习得内部动机的关系...ESL(English as a Second Language)学习者的口头表达能力成为衡量他们综合素质的重要标准。如何提高ESL学习者的口头交际沟通能力,是我国大学英语教学必须面临的一项重要任务。本文主要研究戏剧活动与ESL学习者口语习得内部动机的关系,具有一定的参考意义和实践价值。展开更多
Defect detection is vital in the nonwoven material industry,ensuring surface quality before producing finished products.Recently,deep learning and computer vision advancements have revolutionized defect detection,maki...Defect detection is vital in the nonwoven material industry,ensuring surface quality before producing finished products.Recently,deep learning and computer vision advancements have revolutionized defect detection,making it a widely adopted approach in various industrial fields.This paper mainly studied the defect detection method for nonwoven materials based on the improved Nano Det-Plus model.Using the constructed samples of defects in nonwoven materials as the research objects,transfer learning experiments were conducted based on the Nano DetPlus object detection framework.Within this framework,the Backbone,path aggregation feature pyramid network(PAFPN)and Head network models were compared and trained through a process of freezing,with the ultimate aim of bolstering the model's feature extraction abilities and elevating detection accuracy.The half-precision quantization method was used to optimize the model after transfer learning experiments,reducing model weights and computational complexity to improve the detection speed.Performance comparisons were conducted between the improved model and the original Nano Det-Plus model,YOLO,SSD and other common industrial defect detection algorithms,validating that the improved methods based on transfer learning and semi-precision quantization enabled the model to meet the practical requirements of industrial production.展开更多
This paper intends to promote a college English autonomous teaching and learning approach by introducing the whole process of its implementation and feedback from the learners. The theoretical and practical framework ...This paper intends to promote a college English autonomous teaching and learning approach by introducing the whole process of its implementation and feedback from the learners. The theoretical and practical framework of this approach is： with multiple autonomous learning research and practice models as its core, with process syllabus as its guidance, with task-based teaching as its essential principle, with group cooperation and reciprocal learning as its means, with extracurricular activities, online learning and self-access center as its learning environment, with formative assessment system as its guarantee and with cultivation of learners＇ comprehensive English practical skills and autonomy as its goal. Through this approach, we provide the learners with a favorable learning environment where they can learn by themselves and learn by reflection and practice so that they can learn how to learn and how to behave and how to survive.展开更多
To overcome the limitation that complex data types with noun attributes cannot be processed by rank learning algorithms, a new rank learning algorithm is designed. In the learning algorithm based on the decision tree,...To overcome the limitation that complex data types with noun attributes cannot be processed by rank learning algorithms, a new rank learning algorithm is designed. In the learning algorithm based on the decision tree, the splitting rule of the decision tree is revised with a new definition of rank impurity. A new rank learning algorithm, which can be intuitively explained, is obtained and its theoretical basis is provided. The experimental results show that in the aspect of average rank loss, the ranking tree algorithm outperforms perception ranking and ordinal regression algorithms and it also has a faster convergence speed. The rank learning algorithm based on the decision tree is able to process categorical data and select relative features.展开更多
Aim To investigate the model free multi step average reward reinforcement learning algorithm. Methods By combining the R learning algorithms with the temporal difference learning (TD( λ ) learning) algorithm...Aim To investigate the model free multi step average reward reinforcement learning algorithm. Methods By combining the R learning algorithms with the temporal difference learning (TD( λ ) learning) algorithms for average reward problems, a novel incremental algorithm, called R( λ ) learning, was proposed. Results and Conclusion The proposed algorithm is a natural extension of the Q( λ) learning, the multi step discounted reward reinforcement learning algorithm, to the average reward cases. Simulation results show that the R( λ ) learning with intermediate λ values makes significant performance improvement over the simple R learning.展开更多
Autonomous learning is one of the objectives of multi-media college English teaching. On basis of the test of students＇ autonomous learning ability and the analysis of the results, this paper attempts to explore the ...Autonomous learning is one of the objectives of multi-media college English teaching. On basis of the test of students＇ autonomous learning ability and the analysis of the results, this paper attempts to explore the feasibility of fostering the autonomous learning ability in college English teaching.展开更多
Learners themselves are playing an essential role in foreign language learning. ＂To teach＂ is not enough for foreign language teachers, and what is more important for them is to help the learners construct correct l...Learners themselves are playing an essential role in foreign language learning. ＂To teach＂ is not enough for foreign language teachers, and what is more important for them is to help the learners construct correct learning beliefs and instruct them how to learn. Based on the questionnaire, this paper sums up the leading deviations in English learning and makes corresponding proposals of how to help students construct correct learning beliefs.展开更多
With the enhancement of friendship between different nations, foreign language learning has become more and more important. In particular, spoken language is playing a vital role in foreign language learning and pract...With the enhancement of friendship between different nations, foreign language learning has become more and more important. In particular, spoken language is playing a vital role in foreign language learning and practice. In order to improve foreign language teaching and learning proficiency in ethnic regions, the author analyses the current situation of spoken foreign language teaching and learning in ethnic regions and suggests some ways to solve the existing problems.展开更多
The nematode Caenorhabditis elegans is an attractive model organism to study the behavioral plasticity for its simple system and ability to respond to diverse environmental stimuli, such as touch, smell, taste and tem...The nematode Caenorhabditis elegans is an attractive model organism to study the behavioral plasticity for its simple system and ability to respond to diverse environmental stimuli, such as touch, smell, taste and temperature. Learning in C. elegans encompasses both non-associative learning and associative learning. Till now, themotaxis and chemotaxis are two major paradigms for associative learning and there are at least 6 forms of chemotaxis-mediated associative learning. Three research systems have also been explored to study the mechanism of learning choice in worms. This review will discuss the forms, research models, genetic and molecular regulation of learning and learning choice in C. elegans.展开更多
Aim To find a more efficient learning method based on temporal difference learning for delayed reinforcement learning tasks. Methods A kind of Q learning algorithm based on truncated TD( λ ) with adaptive scheme...Aim To find a more efficient learning method based on temporal difference learning for delayed reinforcement learning tasks. Methods A kind of Q learning algorithm based on truncated TD( λ ) with adaptive schemes of λ value selection addressed to absorbing Markov decision processes was presented and implemented on computers. Results and Conclusion Simulations on the shortest path searching problems show that using adaptive λ in the Q learning based on TTD( λ ) can speed up its convergence.展开更多
基金National Key Research and Development Program of China(Nos.2022YFB4700600 and 2022YFB4700605)National Natural Science Foundation of China(Nos.61771123 and 62171116)+1 种基金Fundamental Research Funds for the Central UniversitiesGraduate Student Innovation Fund of Donghua University,China(No.CUSF-DH-D-2022044)。
文摘Defect detection is vital in the nonwoven material industry,ensuring surface quality before producing finished products.Recently,deep learning and computer vision advancements have revolutionized defect detection,making it a widely adopted approach in various industrial fields.This paper mainly studied the defect detection method for nonwoven materials based on the improved Nano Det-Plus model.Using the constructed samples of defects in nonwoven materials as the research objects,transfer learning experiments were conducted based on the Nano DetPlus object detection framework.Within this framework,the Backbone,path aggregation feature pyramid network(PAFPN)and Head network models were compared and trained through a process of freezing,with the ultimate aim of bolstering the model's feature extraction abilities and elevating detection accuracy.The half-precision quantization method was used to optimize the model after transfer learning experiments,reducing model weights and computational complexity to improve the detection speed.Performance comparisons were conducted between the improved model and the original Nano Det-Plus model,YOLO,SSD and other common industrial defect detection algorithms,validating that the improved methods based on transfer learning and semi-precision quantization enabled the model to meet the practical requirements of industrial production.
文摘This paper intends to promote a college English autonomous teaching and learning approach by introducing the whole process of its implementation and feedback from the learners. The theoretical and practical framework of this approach is： with multiple autonomous learning research and practice models as its core, with process syllabus as its guidance, with task-based teaching as its essential principle, with group cooperation and reciprocal learning as its means, with extracurricular activities, online learning and self-access center as its learning environment, with formative assessment system as its guarantee and with cultivation of learners＇ comprehensive English practical skills and autonomy as its goal. Through this approach, we provide the learners with a favorable learning environment where they can learn by themselves and learn by reflection and practice so that they can learn how to learn and how to behave and how to survive.
基金The Planning Program of Science and Technology of Hunan Province (No05JT1039)
文摘To overcome the limitation that complex data types with noun attributes cannot be processed by rank learning algorithms, a new rank learning algorithm is designed. In the learning algorithm based on the decision tree, the splitting rule of the decision tree is revised with a new definition of rank impurity. A new rank learning algorithm, which can be intuitively explained, is obtained and its theoretical basis is provided. The experimental results show that in the aspect of average rank loss, the ranking tree algorithm outperforms perception ranking and ordinal regression algorithms and it also has a faster convergence speed. The rank learning algorithm based on the decision tree is able to process categorical data and select relative features.
文摘Aim To investigate the model free multi step average reward reinforcement learning algorithm. Methods By combining the R learning algorithms with the temporal difference learning (TD( λ ) learning) algorithms for average reward problems, a novel incremental algorithm, called R( λ ) learning, was proposed. Results and Conclusion The proposed algorithm is a natural extension of the Q( λ) learning, the multi step discounted reward reinforcement learning algorithm, to the average reward cases. Simulation results show that the R( λ ) learning with intermediate λ values makes significant performance improvement over the simple R learning.
文摘Autonomous learning is one of the objectives of multi-media college English teaching. On basis of the test of students＇ autonomous learning ability and the analysis of the results, this paper attempts to explore the feasibility of fostering the autonomous learning ability in college English teaching.
文摘Learners themselves are playing an essential role in foreign language learning. ＂To teach＂ is not enough for foreign language teachers, and what is more important for them is to help the learners construct correct learning beliefs and instruct them how to learn. Based on the questionnaire, this paper sums up the leading deviations in English learning and makes corresponding proposals of how to help students construct correct learning beliefs.
文摘With the enhancement of friendship between different nations, foreign language learning has become more and more important. In particular, spoken language is playing a vital role in foreign language learning and practice. In order to improve foreign language teaching and learning proficiency in ethnic regions, the author analyses the current situation of spoken foreign language teaching and learning in ethnic regions and suggests some ways to solve the existing problems.
文摘The nematode Caenorhabditis elegans is an attractive model organism to study the behavioral plasticity for its simple system and ability to respond to diverse environmental stimuli, such as touch, smell, taste and temperature. Learning in C. elegans encompasses both non-associative learning and associative learning. Till now, themotaxis and chemotaxis are two major paradigms for associative learning and there are at least 6 forms of chemotaxis-mediated associative learning. Three research systems have also been explored to study the mechanism of learning choice in worms. This review will discuss the forms, research models, genetic and molecular regulation of learning and learning choice in C. elegans.
文摘Aim To find a more efficient learning method based on temporal difference learning for delayed reinforcement learning tasks. Methods A kind of Q learning algorithm based on truncated TD( λ ) with adaptive schemes of λ value selection addressed to absorbing Markov decision processes was presented and implemented on computers. Results and Conclusion Simulations on the shortest path searching problems show that using adaptive λ in the Q learning based on TTD( λ ) can speed up its convergence.
