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2022 IEEE International Conference on High Voltage Engineering and Applications, ICHVE 2022

作者： Yin, Fei Yang, Lijun Hou, Wei Yuan, Yuan State Key Lab of Power Transmission Equipment & System Security and New Technology Chongqing China School of Materials Science and Engineering Chongqing University Chongqing China

ISBN: (数字)9781665407502

ISBN: (纸本)9781665407502

Aramid fiber insulation poles are widely used because of their excellent mechanical and electrical properties, and the type of curing agent plays an important role in the performance of insulation poles. In the work, the effects of different curing agents (tetrahydrophthalic anhydride (THPA), methyltetrahydrophthalic anhydride (MHAC) and methylnadic anhydride (MNA)) on the thermal stability and space charge characteristics of epoxy resin/PMIA composite structures were investigated based on molecular simulation calculations and experimental methods. Compared with other curing agent/epoxy systems, MHAC/epoxy (EPMH) systems has lower coefficient of thermal expansion, and it has stronger binding ability to PMIA. Under the action of the electric field, the energy gap between the highest electron-occupied orbital and the lowest empty orbital of the EPMH system is larger. The EPMH/PMIA composite system has less space charge accumulation under the electric field, and the charge dissipation rate of the material is faster when the electric field is removed. © 2022 IEEE.

关键词： Electric fields

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A direct spino-cortical circuit bypassing the thalamus modulates nociception

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细胞研究（英文版） 2023年第10期33卷 775-789页

作者： Bing Cai Dan Wu Hong Xie Yan Chen Huadong Wang Sen Jin Yuran Song Anan Li Shiqi Huang Sashuang Wang Yingjin Lu Lan Bao Fuqiang Xu Hui Gong Changlin Li Xu Zhang Guangdong Institute of Intelligence Science and Technology HengqinZhuhaiGuangdongChina SIMR Joint Lab of Drug Innovation Shanghai Advanced Research InstituteChinese Academy of Sciences(CAS) Xuhui Central Hospital ShanghaiChina Research Unit of Pain Medicine Chinese Academy of Medical SciencesHengqinZhuhaiGuangdongChina Institute of Neuroscience and State Key Laboratory of Neuroscience Center for Excellence in Brain Science and Intelligence TechnologyCASShanghaiChina SIMR Joint Lab of Drug Innovation Shanghai Advanced Research InstituteChinese Academy of Sciences(CAS) Xuhui Central Hospital ShanghaiChina Institute of Photonic Chips School of Medical Instrument and Food Engineering University of Shanghai for Science and TechnologyShanghaiChina Shenzhen Key Laboratory of Viral Vectors for Biomedicine Brain Cognition and Brain Disease InstituteShenzhen Institute of Advanced TechnologyCASShenzhenGuangdongChina HUST-Suzhou Institute for Brainsmatics JITRI Institute for BrainsmaticsSuzhouJiangsuChina SIMR Joint Lab of Drug Innovation Shanghai Advanced Research InstituteChinese Academy of Sciences(CAS) Xuhui Central Hospital ShanghaiChina School of Life Science and Technology ShanghaiTech UniversityShanghaiChina Department of Pain Medicine and Shenzhen Municipal Key Laboratory for Pain Medicine Shenzhen Nanshan People's HospitalShenzhenGuangdongChina Guangdong Institute of Intelligence Science and Technology HengqinZhuhaiGuangdongChina Guangdong Institute of Intelligence Science and Technology HengqinZhuhaiGuangdongChina School of Life Science and Technology ShanghaiTech UniversityShanghaiChina State Key Laboratory of Cell Biology Shanghai Institute of Biochemistry and Cell BiologyCenter for Excellence in Molecular Cell ScienceCASShanghaiChina Guangdong Institute of Intelligence Science and Technology HengqinZhuhaiGuangdongChina Department of Pain Medicine and Shenzhen Municipal Key Laboratory for Pain Medicine Shenzhen Nanshan People's HospitalShenzhenGuangdongChina Guang

Nociceptive signals are usually transmitted to layer 4 neurons in somatosensory cortex via the spinothalamic-thalamocortical *** layer 5 corticospinal neurons in sensorimotor cortex are reported to receive the output of neurons in superficial layers;and their descending axons innervate the spinal cord to regulate basic sensorimotor ***,we show that a subset of layer 5 neurons receives spinal inputs through a direct spino-cortical circuit bypassing the thalamus,and thus define these neurons as spino-cortical recipient neurons(SCRNs).Morphological studies revealed that the branches from spinal ascending axons formed a kind of disciform structure with the descending axons from SCRNs in the basilar pontine nucleus(BPN).Electron microscopy and calcium imaging further confirmed that the axon terminals from spinal ascending neurons and SCRNs made functional synaptic contacts in the BPN,linking the ascending sensory pathway to the descending motor control ***,behavioral tests indicated that the spino-cortical connection in the BPN was involved in nociceptive *** vivo calcium imaging showed that SCRNs responded to peripheral noxious stimuli faster than neighboring layer 4 cortical neurons in awake *** activities of SCRNs could modulate nociceptive ***,this direct spino-cortical circuit represents a noncanonical pathway,allowing a fast sensory-motor transition of the brain in response to noxious stimuli.

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Event-triggered H∞ Consensus of Leader-follower Multi-agent systems 43

Event-triggered H∞ Consensus of Leader-follower Multi-agent...

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43rd Chinese Control Conference, CCC 2024

作者： Gong, Cheng Ai, Chenguang Zuo, Xuemin Ma, Zhuang Dai, W. Hebei Jianzhi Casting Group Ltd Pangzhuangzi Yutian County Tangshan064100 China College Tangshan University Key Lab of Intelligent Data Information Processing and Control of Hebei Province Key Lab of Intelligent Motion Control System of Tangshan City Intelligence and Information Engineering Tangshan063000 China North China University of Science and Technology College of Electrical Engineering Tangshan063210 China Kernel University FullertonCA92832 United States

ISBN: (纸本)9789887581581

This paper discusses the H∞ consensus problem of leader-follower multi-agent systems. The controller for each agent is crafted to utilize comprehensive information from all connected agents, while an innovative event-triggered strategy is incorporated to minimize communication costs. Based on the Lyapunov function theory, an H∞ controller is proposed that can ensure both system stability and a prescribed disturbance attenuation level γ. Finally, a numerical example validated the effectiveness of the proposed method. © 2024 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Multi agent systems

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A Novel Hybrid DC Circuit Breaker with Current Limiting Capability

A Novel Hybrid DC Circuit Breaker with Current Limiting Capa...

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2022 IEEE Transportation Electrification Conference and Expo, Asia-Pacific, ITEC Asia-Pacific 2022

作者： Xu, Xiaoyi Huang, Dongdong Ou, Zhujian Jia, Guanlong Wu, Xinan Liu, Xiaoming State Grid Nantong Power Supply Company 1 Yuelong South Road Nantong China HeBei University of Technology State Key Lab of Reliability and Intelligence of Electrical Equipment Tianjin China

ISBN: (数字)9781665492065

ISBN: (纸本)9781665492065

DC circuit breaker is an important equipment to ensure the safety and stability of DC transmission system. It can quickly and reliably cut off the fault current in the system and maintain the normal operation of DC system. This paper presents a novel hybrid DC circuit breaker topology with current limiting capability (CL-HCB), which is composed of main branch and fault current handling branch. When the system faults, the current limiting inductor is input to suppress the rise rate of fault current and reduce the amplitude of fault current. In addition, the topology has the functions of self-charging of pre-charge capacitor and adaptive reclosing. This paper introduces the structure and working principle of the topology in detail, and builds a single-ended equivalent system in PSCAD/EMTDC to verify the accuracy of the theoretical analysis and prove the feasibility of the proposed topology. © 2022 IEEE.

关键词： Electric circuit breakers

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Modeling Larval Tumbling Locomotion Based on Differentiable Material Point Method 10

Modeling Larval Tumbling Locomotion Based on Differentiable ...

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10th IEEE Smart World Congress, SWC 2024

作者： Wang, Weishi Tang, Weihao Tang, Yue Zheng, Nenggan Zhejiang University Qiushi Academy for Advanced Studies School of Software Technology Ningbo China Zhejiang University Qiushi Academy for Advanced Studies College of Computer Science and Technology Hangzhou China Zhejiang University Qiushi Academy for Advanced Studies The State Key Lab of Brain-Machine Intelligence College of Computer Science and Technology Hangzhou China Bengbu University Bengbu China

ISBN: (纸本)9798331520861

Tumbling locomotion enables Drosophila larvae to rapidly reposition themselves to evade predators. Owing to the complex spatial postural changes involved, studies on this phenomenon are relatively scarce. Neuromechanical models can simulate sequences of biological locomotion postures and synthesize long-term multimodal movement behaviors, facilitating the analysis of the mechanisms linking the nervous system and locomotion. However, constructing neuromechanical models of larval tumbling presents significant challenges due to the extensive deformations resulting from tumbling. Here, we developed a model based on the material point method (MPM) that reflects the biological structure of Drosophila larvae, controlling muscle contractions in response to received signals. By integrating deep learning, we created an artificial neural network-based controller to generate these signals. We built this framework using differentiable physics and leveraged efficient gradient calculations for gradient-based optimization of the neural network controller. Our framework supports both straight and offset tumbling and achieves closed-loop control of a complex 3D soft-bodied neuromechanical model. Experimental results demonstrate that the optimized neural network controller enables the larval model to perform tumbling actions effectively, providing new insights into understanding and simulating larval locomotion behavior. © 2024 IEEE.

关键词： Biped locomotion

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EvHDR-NeRF: Building High Dynamic Range Radiance Fields with Single Exposure Images and Events 39

EvHDR-NeRF: Building High Dynamic Range Radiance Fields with...

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39th Annual AAAI Conference on Artificial intelligence, AAAI 2025

作者： Chen, Zehao Liao, Zhanfeng Ma, De Tang, Huajin Zheng, Qian Pan, Gang The State Key Lab of Brain-Machine Intelligence Zhejiang University Hangzhou China College of Computer Science and Technology Zhejiang University Hangzhou China

ISBN: (纸本)157735897X

We present EvHDR-NeRF to recover a High Dynamic Range (HDR) radiance field from event streams and a set of Low Dynamic Range (LDR) views with single exposures. Using the EvHDR-NeRF, we can generate both novel HDR views and novel LDR views under different exposures. The key to our method is to model the new relationship between events streams and LDR images, which considers both the Camera Response Function (CRF) and exposure time. Based on this relationship, we categorize events into inter-frame events and intra-exposure. The former is utilized for building HDR radiance field and the latter is used to deblur potentially blurred images. Compared to existing methods, this method can effectively reconstruct the HDR radiance field even when the input images are degraded. Experimental results demonstrate that our method achieves state-of-the-art HDR reconstruction, providing a more adaptable and accurate solution for complex imaging applications. © 2025, Association for the Advancement of Artificial intelligence (***). All rights reserved.

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A Vision-based Bird’s Eye View Representation Network for 3D Objects in Open-pit Mining Area 22

A Vision-based Bird’s Eye View Representation Network for 3...

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22nd IEEE International Conference on Industrial Informatics, INDIN 2024

作者： Tai, Mengen Liu, Wentao Wang, Zhangyu Zhou, Bin Yu, Guizhen Yang, Songyue School of Transportation Science and Engineering Ministry of Industry and Information Technolody Beihang University Beijing China State Key Lab of Intelligent Transportation System Ministry of Industry and Information Technolody Beihang University Beijing China The Key Laboratory of Autonomous Transportation Technology for Special Vehicles Ministry of Industry and Information Technolody Beihang University Beijing China

ISBN: (纸本)9798331527471

Autonomous transportation systems, which have reconstructed open-pit mining operations, depend on accurate and real-time obstacle detection in challenging environments. Existing methods often exhibit limitations in accuracy due to their reliance on traditional image-based techniques, leading to errors and incomplete results. To address these issues, we developed a vision-based 3D object detection algorithm designed for open-pit mining environments. Our approach leverages the BEVDepth model, enabling accurate 3D object recognition using monocular camera input. Moreover, camera parameters are integrated to enhance resilience and flexibility across diverse mining environments. Last, our algorithm was implemented on a newly customized open-pit mining dataset. The experimental results verify the algorithm efficiency by attaining a high mean Average Precision score (mAP) of 67% while offering real-time performance with inference times as short as 25ms per frame. It enables accurate and efficient obstacle detection in autonomous mining vehicles and contributes to the development of safer and more productive mining operations. © 2024 IEEE.

关键词： Obstacle detectors

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Deep learning-based activity recognition and fine motor identification using 2D skeletons of cynomolgus monkeys

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Zoological Research 2023年第5期44卷 967-980页

作者： Chuxi Li Zifan Xiao Yerong Li Zhinan Chen Xun Ji Yiqun Liu Shufei Feng Zhen Zhang Kaiming Zhang Jianfeng Feng Trevor W.Robbins Shisheng Xiong Yongchang Chen Xiao Xiao School of Information Science and Technology Micro Nano System Center Fudan UniversityShanghai 200433China Department of Anesthesiology Huashan HospitalKey Laboratory of Computational Neuroscience and Brain-Inspired IntelligenceMinistry of EducationBehavioral and Cognitive Neuroscience CenterInstitute of Science and Technology for Brain-Inspired IntelligenceMOE Frontiers Center for Brain ScienceFudan UniversityShanghai 200433China Kuang Yaming Honors School Nanjing UniversityNanjingJiangsu 210023China Shanghai Key Laboratory of Intelligent Information Processing School of Computer ScienceFudan UniversityShanghai 200433China State Key Laboratory of Primate Biomedical Research Institute of Primate Translational MedicineKunming University of Science and TechnologyKunmingYunnan 650500China New Vision World LLC. Aliso ViejoCalifornia 92656USA Behavioural and Clinical Neuroscience Institute University of CambridgeCambridgeCB21TNUK

Video-based action recognition is becoming a vital tool in clinical research and neuroscientific study for disorder detection and ***,action recognition currently used in non-human primate(NHP)research relies heavily on intense manual labor and lacks standardized *** this work,we established two standard benchmark datasets of NHPs in the laboratory:Monkeyin lab(Mi L),which includes 13 categories of actions and postures,and MiL2D,which includes sequences of two-dimensional(2D)skeleton ***,based on recent methodological advances in deep learning and skeleton visualization,we introduced the Monkey Monitor Kit(Mon Kit)toolbox for automatic action recognition,posture estimation,and identification of fine motor activity in *** the datasets and Mon Kit,we evaluated the daily behaviors of wild-type cynomolgus monkeys within their home cages and experimental environments and compared these observations with the behaviors exhibited by cynomolgus monkeys possessing mutations in the MECP2 gene as a disease model of Rett syndrome(RTT).Mon Kit was used to assess motor function,stereotyped behaviors,and depressive phenotypes,with the outcomes compared with human manual *** Kit established consistent criteria for identifying behavior in NHPs with high accuracy and efficiency,thus providing a novel and comprehensive tool for assessing phenotypic behavior in monkeys.

关键词： Action recognition Fine motor identification Two-stream deep model 2D skeleton Non-human primates Rett syndrome

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SSD-FASTER NET: A HYBRID NETWORK FOR INDUSTRIAL DEFECT INSPECTION

arXiv

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arXiv 2022年

作者： Wang, Jingyao Yu, Naigong Beijing Key Lab of the Computational Intelligence and Intelligent System Beijing University of Technology China

The quality of industrial components is critical to the production of special equipment such as robots. Defect inspection of these components is an efficient way to ensure quality. In this paper, we propose a hybrid network, SSD-Faster Net, for industrial defect inspection of rails, insulators, commutators etc. SSD-Faster Net is a two-stage network, including SSD for quickly locating defective blocks, and an improved Faster R-CNN for defect segmentation. For the former, we propose a novel slice localization mechanism to help SSD scan quickly. The second stage is based on improved Faster R-CNN, using FPN, deformable kernel(DK) to enhance representation ability. It fuses multi-scale information, and self-adapts the receptive field. We also propose a novel loss function and use ROI Align to improve accuracy. Experiments show that our SSD-Faster Net achieves an average accuracy of 84.03%, which is 13.42% higher than the nearest competitor based on Faster R-CNN, 4.14% better than GAN-based methods, more than 10% higher than that of DNN-based detectors. And the computing speed is improved by nearly 7%, which proves its robustness and superior performance. Copyright © 2022, The Authors. All rights reserved.

关键词： Inspection

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Multi-kernel-size Convolutional Supervised Autoencoders for Tactile Gesture Recognition 12

Multi-kernel-size Convolutional Supervised Autoencoders for ...

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12th International Conference on CYBER technology in Automation, Control, and Intelligent systems, CYBER 2022

作者： Ye, Chaoxiang Li, Xiaoyu Huang, Binhua Su, Yuanzhe Mi, Tingting Zhou, Zhenning Yi, Zhengkun Wu, Xinyu Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences China Siat Branch Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen518055 China

ISBN: (数字)9781665472678

ISBN: (纸本)9781665472678

With the development of human-computer interaction, tactile gesture recognition has been widely used in our life. To solve the problem of overfitting on the sample-limited tactile datasets, we apply the Supervised Autoencoders (SAE) to improve the generalization performance. Moreover, based on the SAE, we propose the Multi-kernel-size Convolutional Supervised Autoencoders (MCSAE) to further improve the generalization performance on the limited dataset, which provides models with more structure of receptive fields and enhances the feature extraction ability of SAE. In comparison with other state-of-the-art (SOTA) models, the SAE we apply has higher gesture recognition accuracy and MCSAE can further improve the generalization performance of SAE on the sample-limited publicly available dataset. © 2022 IEEE.

关键词： Gesture recognition

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