With the cross-fertilization of artificial intelligence(AI)technology and spintronics,the traditional AI teaching system has revealed its limitations in terms of industrial adaptability and interdisciplinary integrati...With the cross-fertilization of artificial intelligence(AI)technology and spintronics,the traditional AI teaching system has revealed its limitations in terms of industrial adaptability and interdisciplinary integration.In order to cope with this challenge,this study takes Introduction to Artificial Intelligence as the basis,and proposes a conceptual framework of“technical-legal”double helix teaching model,aiming at reconstructing the existing curriculum through three-dimensional teaching design innovation:(1)In the technical level,adding the cutting-edge topic of“Spintronics and Neuromorphic Computing,”through simulation and literature study,students are guided to explore the principle of brain-like computation based on STT-MRAM;(2)at the legal level,the teaching paradigm of“integrating the awareness of legal compliance into technological research and development”is constructed,and it is planned to develop a library of legal science and technology seminars containing cases such as analysis of intelligent contracts;(3)at the practical level,the establishment of an“industry-academia-research”program is explored and improve the comprehensive practical ability of students by simulating the cooperation projects between schools and enterprises.The expected goal of this teaching reform program is to enhance students’technological innovation thinking and legal risk prevention awareness,and to provide a teaching reform idea with reference value for exploring the cultivation path of“AI+Law”composite talents.展开更多
Although multi-view monitoring techniques have been widely applied in skinned model reconstruction and movement analysis,traditional systems using high-performance Personal Computers(PCs),or industrial cameras are oft...Although multi-view monitoring techniques have been widely applied in skinned model reconstruction and movement analysis,traditional systems using high-performance Personal Computers(PCs),or industrial cameras are often prohibitive due to high costs and limited scalability.Here,we introduce an affordable,scalable multi-view image acquisition system for skinned model reconstruction in animal studies,utilizing consumer Android devices and a wireless network for synchronized monitoring named Rodent Arena Multi-View Monitor(RAMM).It uses smartphones as camera nodes with local data storage,enabling cost-effective scalability.Its custom synchronization solution and portability make it ideal for research and education in rodent behavior analysis,offering a practical alternative for institutions with limited budgets.Furthermore,the portability and flexibility of this system make it an ideal tool for rodent skinned model research based on multi-view image acquisition.To evaluate the performance,we perform an oscilloscope analysis to ensure effectiveness of synchronization.A 45-camera node setup is built to highlight RAMM’s cost efficiency and ease in constructing large-scale systems.Additionally,the data quality is validated using the Instant Neural Graphics Primitives(Instant-NGP)method.Remarkable results were achieved with a 30.49 dB PSNR by utilizing only 25 images with intrinsic and extrinsic parameters,fulfilling the requirements for well-synchronized data used in 3D representation algorithms.展开更多
文摘With the cross-fertilization of artificial intelligence(AI)technology and spintronics,the traditional AI teaching system has revealed its limitations in terms of industrial adaptability and interdisciplinary integration.In order to cope with this challenge,this study takes Introduction to Artificial Intelligence as the basis,and proposes a conceptual framework of“technical-legal”double helix teaching model,aiming at reconstructing the existing curriculum through three-dimensional teaching design innovation:(1)In the technical level,adding the cutting-edge topic of“Spintronics and Neuromorphic Computing,”through simulation and literature study,students are guided to explore the principle of brain-like computation based on STT-MRAM;(2)at the legal level,the teaching paradigm of“integrating the awareness of legal compliance into technological research and development”is constructed,and it is planned to develop a library of legal science and technology seminars containing cases such as analysis of intelligent contracts;(3)at the practical level,the establishment of an“industry-academia-research”program is explored and improve the comprehensive practical ability of students by simulating the cooperation projects between schools and enterprises.The expected goal of this teaching reform program is to enhance students’technological innovation thinking and legal risk prevention awareness,and to provide a teaching reform idea with reference value for exploring the cultivation path of“AI+Law”composite talents.
文摘Although multi-view monitoring techniques have been widely applied in skinned model reconstruction and movement analysis,traditional systems using high-performance Personal Computers(PCs),or industrial cameras are often prohibitive due to high costs and limited scalability.Here,we introduce an affordable,scalable multi-view image acquisition system for skinned model reconstruction in animal studies,utilizing consumer Android devices and a wireless network for synchronized monitoring named Rodent Arena Multi-View Monitor(RAMM).It uses smartphones as camera nodes with local data storage,enabling cost-effective scalability.Its custom synchronization solution and portability make it ideal for research and education in rodent behavior analysis,offering a practical alternative for institutions with limited budgets.Furthermore,the portability and flexibility of this system make it an ideal tool for rodent skinned model research based on multi-view image acquisition.To evaluate the performance,we perform an oscilloscope analysis to ensure effectiveness of synchronization.A 45-camera node setup is built to highlight RAMM’s cost efficiency and ease in constructing large-scale systems.Additionally,the data quality is validated using the Instant Neural Graphics Primitives(Instant-NGP)method.Remarkable results were achieved with a 30.49 dB PSNR by utilizing only 25 images with intrinsic and extrinsic parameters,fulfilling the requirements for well-synchronized data used in 3D representation algorithms.
