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Multi-Branch Mutual-Distillation Transformer for EEG-Based Seizure Subtype Classification

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arXiv 2024年

作者： Peng, Ruimin Du, Zhenbang Zhao, Changming Luo, Jingwei Liu, Wenzhong Chen, Xinxing Wu, Dongrui Belt and Road Joint Laboratory on Measurement and Control Technology Huazhong University of Science and Technology Wuhan430074 China AI Platform Software Engineering Research Center Dongfeng Corporation Research & Development Institute Wuhan430072 China China Electronic System Technology Co. Ltd. Beijing100089 China Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern University of Science and Technology Shenzhen518055 China

Cross-subject electroencephalogram (EEG) based seizure subtype classification is very important in precise epilepsy diagnostics. Deep learning is a promising solution, due to its ability to automatically extract latent patterns. However, it usually requires a large amount of training data, which may not always be available in clinical practice. This paper proposes Multi-Branch Mutual-Distillation (MBMD) Transformer for cross-subject EEG-based seizure subtype classification, which can be effectively trained from small labeled data. MBMD Transformer replaces all even-numbered encoder blocks of the vanilla Vision Transformer by our designed multi-branch encoder blocks. A mutual-distillation strategy is proposed to transfer knowledge between the raw EEG data and its wavelets of different frequency bands. Experiments on two public EEG datasets demonstrated that our proposed MBMD Transformer outperformed several traditional machine learning and state-of-the-art deep learning approaches. To our knowledge, this is the first work on knowledge distillation for EEG-based seizure subtype classification. © 2024, CC BY.

关键词： Electroencephalography

A moving target detection and localization strategy based on optical flow and pin-hole imaging methods using monocular vision

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A moving target detection and localization strategy based on...

2021 IEEE International Conference on Real-Time Computing and robotics, RCAR 2021

作者： Wang, Shun Guo, Qingqiang Xu, Sheng Su, Dan School of Control Science and Engineering Shandong University Shandong Jinan250061 China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Advanced Technology Shenzhen518055 China Shandong Institute of Advanced Technology Chinese Academy of Sciences Shandong Jinan250102 China Orbbec Inc. Shenzhen518057 China

ISBN: (纸本)9781665436786

This paper proposes a new strategy for moving target detection and localization based on monocular vision. Firstly, to detect a moving target with large displacement and high speed accurately, two consecutive video images captured by a monocular camera are preprocessed using the enhancement and denoising methods. Then, the optical flow representing motion information is calculated iteratively by the modified Lucas-Kanade optical flow method. Secondly, a new interest region extraction method is developed to overcome the negative impacts caused by the noises in the background. Specifically, this proposed method combines a two-level image segmentation strategy from coarse to fine, including median filtering, two-direction dynamic threshold segmentation, the Otsu method, and morphological processing. Thirdly, a low computational cost target localization algorithm is proposed based on pin-hole imaging theory. Besides, it only uses two-dimensional image and camera parameters to obtain the moving target's position in the three-dimensional space. Finally, experimental results show that the proposed strategy can effectively eliminate noise interferences and realize moving target detection, extraction, and localization. © 2021 IEEE.

关键词： Image segmentation

Area-oriented coordinated trajectory planning of dual-arm space robot for capturing a tumbling target

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Chinese Journal of Aeronautics 2019年第9期32卷 2151-2163页

作者： Wenfu XU Lei YAN Zhonghua HU Bin LIANG School of Mechanical Engineering and Automation Harbin Institute of TechnologyShenzhen 518055China State Key Laboratory of Robotics and System Harbin Institute of TechnologyHarbin 150001China Department of Automation Tsinghua UniversityBeijing 100084China

The growing amount of space debris poses a threat to operational spacecraft and the long-term sustainability of activities in outer space. According to the orbital mechanics, an uncontrolled space object will be tumbling, bringing great challenge to capture and remove it. In this paper, a dual-arm coordinated ‘‘Area-Oriented Capture'(AOC) method is proposed to capture a non-cooperative tumbling target. Firstly, the motion equation of the tumbling target is established, based on which, the dynamic properties are analyzed. Then, the ‘‘Area-Oriented Capture'concept is presented to deal with the problem of large pose(position and attitude) deviation and tumbling motion. An area rather than fixed points/devices is taken as the object to be tracked and captured. As long as the manipulators’ end-effectors move to a specified range of the objective areas(not fixed points on the target, but areas), the target satellite will be hugged by the two *** last, the proposed method and the traditional method(i.e. fixed-point oriented capture method)are compared and analyzed through simulation. The results show that the proposed method has larger pose tolerance and takes shorter time for capturing a tumbling target.

关键词： Area-oriented capture Dual-arm coordination Space debris removal Space robot Tumbling target capturing

A New Method of Fault Detection and Diagnosis for the Tennessee Eastman Process

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A New Method of Fault Detection and Diagnosis for the Tennes...

第32届中国过程控制会议(CPCC2021)

作者： Pengbin Zhang Tao Zou Jingyang Wang Zhijia Yang State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Key Laboratory of Networked Control System Chinese Academy of Sciences Shenyang China. Institutes for Robotics and Intelligent ManufacturingChinese Academy of Sciences University of Chinese Academy of Sciences College of Mechanical and Electrical Engineering Guangzhou University State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of Sciences Key Laboratory of Networked Control System Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences

This paper proposes a new fault detection and diagnosis(FDD) method for the Tennessee Eastman(TE) large-scale chemical *** method is built integrated with a curve-type recognizer and a dynamic Bayesian network(DBN).The fault detection is carried out utilizing the curve-type recognizer,while the diagnosis is completed using the ***,the recognizer extracts fault symptoms from different times by distinguishes the curves' ***,the DBN is constructed to handle these time-related fault symptoms *** DBN will give the probability of each fault more and more accurately as time goes *** whole procedure consists of 1) deciding monitoring variables using chemical and control engineering knowledge 2) extracting fault symptoms,3) building a *** advantage over other data-driven FDD methods in reasonability and interpretability is also *** last,the simulation results demonstrate the availability of the proposed method.

关键词： A New Method of Fault Detection and Diagnosis for the Tennessee Eastman Process

Overcoming Van der Waals Forces in reconfigurable nanostructures

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arXiv 2022年

作者： Zhang, Wang Wang, Hao Tan, Alvin T.L. Ranganath, Anupama Sargur Zhang, Biao Wang, Hongtao Chan, John You En Ruan, Qifeng Liu, Hailong Ha, Son Tung Wang, Dong Ravikumar, Venkat K. Low, Hong Yee Yang, Joel K.W. Engineering Product Development Singapore University of Technology and Design Singapore487372 Singapore Northwestern Polytechnical University 127 West Youyi Road Xi'An710072 China Institute of Materials Research and Engineering Singapore138634 Singapore Robotics Institute State Key Laboratory of Mechanical System and Vibration School of Mechanical Engineering Shanghai Jiao Tong University Shanghai200240 China Advanced Micro Devices Singapore Pte Ltd Singapore Singapore

Reconfigurable metamaterials1-3 require constituent nanostructures to demonstrate switching of shapes with external stimuli. For generality, such nanostructures would touch and stick to other surfaces in one of its configurations. Yet, a longstanding challenge is in overcoming this stiction caused by Van der Waals forces, which impedes shape recovery. Here, we introduce a stiff yet self-recovering material system based on acrylic acid, and tested it in high-aspect ratio structures, where recovery is weak. This designer material has a storage modulus of ~5.2 GPa at room temperature and ~90 MPa in the rubbery state at 150 ℃, an order of magnitude higher than previous reports. A high-resolution resin for two-photon lithography was developed based on this polymer system, enabling 3D printing of nanopillars with diameters of ~400 nm and aspect ratio as high as ~10. Experimentally, we observed self-recovery as collapsed and touching structures overcome stiction to stand back up. We developed a theoretical model to explain the recoverability of these sub-micron structures. Reconfigurable structural colour prints and holograms were demonstrated, indicating potential applications of the material system as a shape memory polymer suitable for sub-micron reconfigurable metamaterials. Copyright © 2022, The Authors. All rights reserved.

关键词： Van der Waals forces

Study on Mechanical Properties of Dual-Channel Cryogenic 3d Printing Scaffold for Mandibular Defect Repair

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SSRN

SSRN 2023年

作者： Gao, Lilan Sun, Mengchao Liu, Jie Meng, Lulu Liu, Han Zheng, Xiongfei Liu, Hao Li, Ruixin Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300382 China Tianjin300382 China Beijing Friendship Hospital Capital Medical University 100050 China State Key Laboratory of Robotics Institutes for Robotics and Intelligent Manufacturing Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110017 China Tianjin Key Laboratory of Oral and Maxillofacial Function Reconstruction Tianjin Stomatological Hospital The Affiliated Stomatological Hospital of Nankai University Tianjin300041 China

Mandibular defect repair has always been a clinical challenge, facing technical bottleneck. The new materials directly affect technological breakthroughs in mandibular defect repair field. Our aim is to fabricate a scaffold for mandibular defect repairing with advanced biomaterials. Therefore, a novel dual-channel printed scaffold consisting of silk fibroin/collagen type I /hydroxyapatite (SCH) and polycaprolactone/hydroxyapatite (PCL/HA) was fabricated by 3D printing technology with double nozzles. The mechanical properties and behaviors of dual-channel printed scaffold were investigated by performing uniaxial compression, creep, stress relaxation and ratcheting experiments respectively. The experiments indicated the Young modulus of dual-channel printed scaffold was 60.1 kPa and dual-channel printed scaffold was typical nolinear viscoelastic consistent with bone tissue. Finite Element Analysis (FEA) was employed performing a numerical simulation to evaluate the implantation effect in mandible. The stress distribution of the contact area between scaffold and defect was uniform, the maximum Mises stress of cortical bone and cancellous bone in defect area were 54.52MPa and 3.196MPa, and the maximum displacement of cortical bone and cancellous bone in defect area were 0.1575mm and 0.1555mm, which were distributed in the incisor region. The peak value of the maximum Mises stress for the scaffold implanted was 3.128× MPa and the maximum displacement was 6.453×mm distributed near incisor area. The displacement distribution of the scaffold was consistent with that of cortical and cancellous bone. The scaffold recovered well when the force applied on it disappeared. Above all, dual-channel printed scaffold had excellent bio-mechanical properties in implanting mandible, which provides a new idea for the reconstruction of irregular bone defects in the mandible and has good clinical development prospects. © 2023, The Authors. All rights reserved.

关键词： 3D printing

FogROS2: An Adaptive Platform for Cloud and Fog robotics Using ROS 2

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arXiv 2022年

作者： Ichnowski, Jeffrey Chen, Kaiyuan Dharmarajan, Karthik Adebola, Simeon Danielczuk, Michael Mayoral-Vilches, Víctor Jha, Nikhil Zhan, Hugo LLontop, Edith Xu, Derek Buscaron, Camilo Kubiatowicz, John Stoica, Ion Gonzalez, Joseph Goldberg, Ken Department of Electrical Engineering and Computer Science University of California BerkeleyCA United States The AUTOLab UC Berkeley United States Department of Industrial Engineering and Operations Research University of California BerkeleyCA United States Robotics Institute Carnegie Mellon University United States Acceleration Robotics Ecuador 3 1 I Álava Vitoria Spain System Security Group Universität Klagenfurt Universitätsstr. 65-67 Klagenfurt9020 Austria

Mobility, power, and price points often dictate that robots do not have sufficient computing power on board to run contemporary robot algorithms at desired rates. Cloud computing providers such as AWS, GCP, and Azure offer immense computing power and increasingly low latency on demand, but tapping into that power from a robot is nontrivial. We present FogROS2, an open-source platform to facilitate cloud and fog robotics that is included in the Robot Operating system 2 (ROS 2) distribution. FogROS2 is distinct from its predecessor FogROS1 in 9 ways, including lower latency, overhead, and startup times;improved usability, and additional automation, such as region and computer type selection. Additionally, FogROS2 gains performance, timing, and additional improvements associated with ROS 2. In common robot applications, FogROS2 reduces SLAM latency by 50 %, reduces grasp planning time from 14 s to 1.2 s, and speeds up motion planning 45x. When compared to FogROS1, FogROS2 reduces network utilization by up to 3.8x, improves startup time by 63 %, and network round-trip latency by 97 % for images using video compression. The source code, examples, and documentation for FogROS2 are available at https://***/BerkeleyAutomation/FogROS2, and is available through the official ROS 2 repository at https://***/p/fogros2/. © 2022, CC BY.

关键词： Robot Operating system

Autonomous Power Supply Development for Hydrometeorological Monitoring Station

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Autonomous Power Supply Development for Hydrometeorological ...

IEEE International Energy Conference and Exhibition (EnergyCon)

作者： Anatoliy Prystupa Volodymyr Kazymyr Anatolijs Zabaš ta Anatoliy Revko Serhii Stepenko Kateryna Novyk Electrical Engineering Information and Measurement Technologies Department Chernihiv Polytechnic National University Chernihiv Ukraine Information and Computer system Department Chernihiv Polytechnic National University Chernihiv Ukraine Institute of Industrial Electronics and Electrical Engineering Riga Technical University Riga Latvia Electronics Automation Robotics and Mechatronics Department Chernihiv Polytechnic National University Chernihiv Ukraine

This paper presents the results of the investigation of the power supply system of the autonomous monitoring system. In particular, calculations of the system’s daily balance of energy consumption were performed. Also, the question of the influence of the angle of inclination of solar converters on energy generation is considered and the necessity of collecting solar radiation during the whole daylight, not focusing on the maximum amount of energy, is substantiated. This research aimed to develop an algorithm for calculating the power supply system for autonomous monitoring systems. The proposed algorithm takes into account the coordination of diagrams of generation and consumption of energy within the autonomous monitoring station and statistical analysis of information from the NASA website. Experiments have shown the effectiveness of this method. It can be used in future design of power supply systems for autonomous monitoring stations.

关键词： Power measurement Power supplies Statistical analysis NASA Energy measurement Reliability theory Battery charge measurement

Sample hardness based gradient loss for long-tailed cervical cell detection

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arXiv 2022年

作者： Liu, Minmin Li, Xuechen Gao, Xiangbo Chen, Junliang Shen, Linlin Wu, Huisi Computer Vision Institute School of Computer Science and Software Engineering Shenzhen University China Shenzhen Institute of Artificial Intelligence of Robotics of Society Shenzhen China Guangdong Key Laboratory of Intelligent Information Processing Shenzhen University Shenzhen518060 China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen518060 China University of California Irvine United States

Due to the difficulty of cancer samples collection and annotation, cervical cancer datasets usually exhibit a long-tailed data distribution. When training a detector to detect the cancer cells in a WSI (Whole Slice Image) image captured from the TCT (Thinprep Cytology Test) specimen, head categories (e.g. normal cells and inflammatory cells) typically have a much larger number of samples than tail categories (e.g. cancer cells). Most existing state-of-the-art long-tailed learning methods in object detection focus on category distribution statistics to solve the problem in the long-tailed scenario, without considering the "hardness" of each sample. To address this problem, in this work we propose a Grad-Libra Loss that leverages the gradients to dynamically calibrate the degree of hardness of each sample for different categories, and re-balance the gradients of positive and negative samples. Our loss can thus help the detector to put more emphasis on those hard samples in both head and tail categories. Extensive experiments on a long-tailed TCT WSI image dataset show that the mainstream detectors, e.g. RepPoints, FCOS, ATSS, YOLOF, etc. trained using our proposed Gradient-Libra Loss, achieved much higher (7.8%) mAP than that trained using cross-entropy classification loss. Copyright © 2022, The Authors. All rights reserved.

关键词： Cytology