Online teaching and learning practices in Asian universities are different from that in western universities. Western universities give emphasis on student-student interaction for learning. Online courses offered by m...Online teaching and learning practices in Asian universities are different from that in western universities. Western universities give emphasis on student-student interaction for learning. Online courses offered by most Asian universities are a kind of mixed mode that comprised simultaneous face-to-face tutorials and online interaction facility. In this situation most students use the online facility to collect resources and to contact their teachers. The quantity of student-student interaction was sporadic in many courses. So research is needed to improve the situation and create an environment for students where they can learn what peer group interaction is and practice it. This paper has presented a model of teaching and learning online for Asian universities. Possible barriers in teaching and learning situations in Asia and students' abilities have been considered to develop the model.展开更多
The article explores the effectiveness of class report in intensive reading course.This Language teaching method works well in terms of relaxing the classroom atmosphere;training students’ courage to express themselv...The article explores the effectiveness of class report in intensive reading course.This Language teaching method works well in terms of relaxing the classroom atmosphere;training students’ courage to express themselves in front of others,and focus on stimulating their interests to study English.展开更多
Deep neural networks(DNNs)have achieved great success in many data processing applications.However,high computational complexity and storage cost make deep learning difficult to be used on resource-constrained devices...Deep neural networks(DNNs)have achieved great success in many data processing applications.However,high computational complexity and storage cost make deep learning difficult to be used on resource-constrained devices,and it is not environmental-friendly with much power cost.In this paper,we focus on low-rank optimization for efficient deep learning techniques.In the space domain,DNNs are compressed by low rank approximation of the network parameters,which directly reduces the storage requirement with a smaller number of network parameters.In the time domain,the network parameters can be trained in a few subspaces,which enables efficient training for fast convergence.The model compression in the spatial domain is summarized into three categories as pre-train,pre-set,and compression-aware methods,respectively.With a series of integrable techniques discussed,such as sparse pruning,quantization,and entropy coding,we can ensemble them in an integration framework with lower computational complexity and storage.In addition to summary of recent technical advances,we have two findings for motivating future works.One is that the effective rank,derived from the Shannon entropy of the normalized singular values,outperforms other conventional sparse measures such as the?_1 norm for network compression.The other is a spatial and temporal balance for tensorized neural networks.For accelerating the training of tensorized neural networks,it is crucial to leverage redundancy for both model compression and subspace training.展开更多
This papar discusses the errors made by students out of the mother tongue interference in their English learning process and analyze the reasons for errors,which is regarded as a useful method for language teaching.
文摘Online teaching and learning practices in Asian universities are different from that in western universities. Western universities give emphasis on student-student interaction for learning. Online courses offered by most Asian universities are a kind of mixed mode that comprised simultaneous face-to-face tutorials and online interaction facility. In this situation most students use the online facility to collect resources and to contact their teachers. The quantity of student-student interaction was sporadic in many courses. So research is needed to improve the situation and create an environment for students where they can learn what peer group interaction is and practice it. This paper has presented a model of teaching and learning online for Asian universities. Possible barriers in teaching and learning situations in Asia and students' abilities have been considered to develop the model.
文摘The article explores the effectiveness of class report in intensive reading course.This Language teaching method works well in terms of relaxing the classroom atmosphere;training students’ courage to express themselves in front of others,and focus on stimulating their interests to study English.
基金supported by the National Natural Science Foundation of China(62171088,U19A2052,62020106011)the Medico-Engineering Cooperation Funds from University of Electronic Science and Technology of China(ZYGX2021YGLH215,ZYGX2022YGRH005)。
文摘Deep neural networks(DNNs)have achieved great success in many data processing applications.However,high computational complexity and storage cost make deep learning difficult to be used on resource-constrained devices,and it is not environmental-friendly with much power cost.In this paper,we focus on low-rank optimization for efficient deep learning techniques.In the space domain,DNNs are compressed by low rank approximation of the network parameters,which directly reduces the storage requirement with a smaller number of network parameters.In the time domain,the network parameters can be trained in a few subspaces,which enables efficient training for fast convergence.The model compression in the spatial domain is summarized into three categories as pre-train,pre-set,and compression-aware methods,respectively.With a series of integrable techniques discussed,such as sparse pruning,quantization,and entropy coding,we can ensemble them in an integration framework with lower computational complexity and storage.In addition to summary of recent technical advances,we have two findings for motivating future works.One is that the effective rank,derived from the Shannon entropy of the normalized singular values,outperforms other conventional sparse measures such as the?_1 norm for network compression.The other is a spatial and temporal balance for tensorized neural networks.For accelerating the training of tensorized neural networks,it is crucial to leverage redundancy for both model compression and subspace training.
文摘This papar discusses the errors made by students out of the mother tongue interference in their English learning process and analyze the reasons for errors,which is regarded as a useful method for language teaching.
