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IEEE Instrumentation and Measurement Technology Conference

作者： I Dewa Made Oka Dharmawan Jinvi Lee Deparment of Control Intrumentation and Robot Engineering Chosun University Gwangju Republic of Korea Department of Electronic Engineering Chosun University Gwangju Republic of Korea

ISBN: (数字)9798350380903

ISBN: (纸本)9798350380910

Fatigue cracks exhibit unpredictable and rapid propagation, presenting challenges in comprehending their initiation, influenced by various physical and chemical parameters. To gain deeper insights into the nucleation and growth, understanding the convergence phenomenon in ferromagnetic materials requires visualization of the local stresses and phase changes around the defect. This necessitates a measurement system capable of not only imaging the defect but also stress mapping at high spatial resolution, ideally at grain-level. In this study, we explore how this can be achieved by integrating three-axis tunnel magnetoresistive (TMR) sensor with optical microscopy images. This integration was expected to facilitate the visualization of self-magnetic flux density and enable microstructure analysis on the material's surface. Employing this mapping technique, we observe and discuss the stress distribution around the crack at the grain level with three variation of defect depths direction: 0, 30, and 60 degrees.

关键词： Microscopy Data visualization Fatigue Tunneling magnetoresistance Spatial resolution Surface cracks Stress

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Study on a Novel Voxel-Based 3D Printing Method on Magnetic-controlled Memory Fluid 19

Study on a Novel Voxel-Based 3D Printing Method on Magnetic-...

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19th IEEE International Conference on Automation Science and engineering, CASE 2023

作者： Zhang, Shengjie Sun, Xudong Song, Zhongru Guo, Yifei Qu, Juntian Li, Zhenkun School of Mechanical Electronic and Control Engineering Beijing Jiaotong University Beijing100044 China North China University of Science and Technology Department of Mechanical Engineering Tangshan063210 China Hebei Industrial Robot Industry Technology Research Institute Tangshan063000 China Shenzhen International Graduate School Tsinghua University Shenzhen518055 China

ISBN: (纸本)9798350320695

Combining the 'programmable' characteristics of smart materials with 3D printing technology can realize the integration of structural design and manufacturing. Magnetic controlled smart fluid owns the characteristics of flexible solid-liquid transformation, high driving efficiency and high safety. Soft robot driven by magnetic controlled intelligent fluid can realize a bionic movement similar to that of single-celled organisms. In this paper, we propose a reversible 3D printing method of magnetic phase transformation using a similar mechanism of sol-gel transformation in protoplasm. A magnetically controlled Pickering emulsion system with strong thixotropic properties was constructed and its microscopically self-assembled structure was characterized. The yielding and memory recovery characteristics of the magnetic-controlled memory fluid (MMF) were studied by means of steady-state and dynamic shear measurement, and the optimal rheological parameters suitable for printing were determined. A 3D printing platform and a memory elimination platform for coordinated control of magnetic field and motion system were built to further study and optimize the printing process. Finally, the composite structure is controlled by an array magnetic field to realize an amoeba-like motion. Novel voxel-based 3D printing and its application in soft robots can provide new ideas for space exploration, biomedicine, military reconnaissance and many other fields. © 2023 IEEE.

关键词： Emulsification

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Multi-omics graph convolutional networks for digestive system tumour classification and early-late stage diagnosis

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CAAI Transactions on Intelligence Technology 2024年第6期9卷 1572-1586页

作者： Lin Zhou Zhengzhi Zhu Hongbo Gao Chunyu Wang Muhammad Attique Khan Mati Ullah Siffat Ullah Khan School of Information Science and Technology University of Science and Technology of ChinaHefeiAnhuiChina Anhui Engineering Research Center on Information Fusion and Control of Intelligent Robot WuhuAnhuiChina Department of Breast Center West District of The Affiliated Hospital of University of Science and Technology of ChinaDivision of Life Sciences and MedicineUniversity of Science and Technology of ChinaHefeiAnhuiChina Institute of Advanced Technology University of Science and Technology of ChinaHefeiAnhuiChina School of Electrical and Electronic Engineering Nanyang Technological UniversitySingaporeSingapore School of Biological and Environmental Engineering Chaohu UniversityChaohu Regional Collaborative Technology Service Center for Rural RevitalizationHefeiChina Department of Artificial Intelligence College of Computer Engineering and SciencePrince Mohammad Bin Fahd UniversityAl-KhobarSaudi Arabia School of Automation Northwestern Polytechnical UniversityXi'anShaanxiChina Institute of Engineering and Computing Science University of Science and Technology of BannuKPKBannuPakistan

The prevalence of digestive system tumours(DST)poses a significant challenge in the global crusade against *** neoplasms constitute 20%of all documented cancer diagnoses and contribute to 22.5%of cancer-related *** accurate diagnosis of DST is paramount for vigilant patient monitoring and the judicious selection of optimal *** this challenge,the authors introduce a novel methodology,denominated as the Multi-omics Graph Transformer Convolutional Network(MGTCN).This innovative approach aims to discern various DST tumour types and proficiently discern between early-late stage tumours,ensuring a high degree of *** MGTCN model incorporates the Graph Transformer Layer framework to meticulously transform the multi-omics adjacency matrix,thereby illuminating potential associations among diverse samples.A rigorous experimental evaluation was undertaken on the DST dataset from The Cancer Genome Atlas to scrutinise the efficacy of the MGTCN *** outcomes unequivocally underscore the efficiency and precision of MGTCN in diagnosing diverse DST tumour types and successfully discriminating between early-late stage DST *** source code for this groundbreaking study is readily accessible for download at https://***/bigone1/MGTCN.

关键词： digestive system tumors early-late stage multi-omics tumor types

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Experimental evaluation of stent clot retrieval using the confront clot scrambling method with an equitable automatic withdrawal machine

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Asian Journal of Neurosurgery 2022年第4期14卷 1165-1167页

作者： Reo Kawaguchi Tomotaka Ohshima Yoshitaka Nagano Shigeru Miyachi Naoki Matsuo Masakazu Takayasu Department of Neurosurgery Aichi Medical University Aichi Neuroendovascular Therapy Center Aichi Medical University Aichi Department of Electronic Control and Robot Engineering Aichi University of Technology Aichi

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A novel technique of microcatheter shaping using real image display for endovascular aneurysmal coil embolization

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Asian Journal of Neurosurgery 2022年第3期16卷 645-647页

作者： Tomotaka Ohshima Yoshitaka Nagano Shigeru Miyachi Neuroendovascular Therapy Center Aichi Medical University Nagakute Department of Electronic Control and Robot Engineering Aichi University of Technology Gamagori Aichi Department of Neurosurgery Aichi Medical University Nagakute

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MULSAM: Multidimensional Attention with Hardware Acceleration for Efficient Intrusion Detection on Vehicular CAN Bus

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IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 2025年

作者： Xu, He Shi, Xiaokang Liu, Hansheng Wang, Yanwen Lu, Jiwu Zeng, Haibo Li, Renfa Wu, Di Hunan University National Engineering Research Center for Robot Visual Perception and Control Technology Hunan Changsha410082 China Hunan University College of Electrical and Information Engineering Hunan Changsha410082 China Hunan University Shenzhen Research Institute Shenzhen518000 China Virginia Tech Department of Electrical and Computer Engineering BlacksburgVA24061 United States Hunan University College of Computer Science and Electronic Engineering Hunan Changsha410082 China

controller Area Network (CAN) protocol is an efficient standard enabling communication among electronic control Units (ECUs). However, the CAN bus is vulnerable to malicious attacks because of a lack of defense features. In this article, a novel vehicle Intrusion Detection System (IDS) is developed. The challenge is that existing techniques of Intrusion Detection Systems (IDS) rarely consider attacks with small-batch, which are characterized by their small attack scale and concealed attack patterns, posing a significant threat to driving safety. To solve this problem, we developed an algorithm model that merges Multi-dimensional Long Short-Term Memory (MD-LSTM) and Self-Attention Mechanism (SAM), shortly named MULSAM. The MULSAM model was compared with other baseline models, including Stacked LSTM, MD-LSTM, etc. Experiments show that our approach has the best detection accuracy (98.98%) and training stability. Further, to speed up the inference of MULSAM on edge, the hardware accelerator is implemented on FPGA devices using technologies such as parallelization, modular, pipeline, and fixed-point quantization. Experiments show that our FPGA-based acceleration scheme has a better energy efficiency than the CPU platform. Even with a certain degree of quantification, the acceleration model for MULSAM still displays a high detection accuracy of 98.81% and a low latency of 1.88 ms. © 1982-2012 IEEE.

关键词： Intrusion detection

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Study on a Novel Voxel-Based 3D Printing Method on Magnetic-controlled Memory Fluid*

Study on a Novel Voxel-Based 3D Printing Method on Magnetic-...

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IEEE International Conference on Automation Science and engineering (CASE)

作者： Shengjie Zhang Xudong Sun Zhongru Song Yifei Guo Juntian Qu Zhenkun Li School of Mechanical Electronic and Control Engineering Beijing Jiaotong University Beijing Department of Mechanical Engineering North China University of Science and Technology Tangshan Hebei Industrial Robot Industry Technology Research Institute Tangshan Shenzhen International Graduate School Tsinghua University Shenzhen China

Combining the “programmable” characteristics of smart materials with 3D printing technology can realize the integration of structural design and manufacturing. Magnetic controlled smart fluid owns the characteristics of flexible solid-liquid transformation, high driving efficiency and high safety. Soft robot driven by magnetic controlled intelligent fluid can realize a bionic movement similar to that of single-celled organisms. In this paper, we propose a reversible 3D printing method of magnetic phase transformation using a similar mechanism of sol-gel transformation in protoplasm. A magnetically controlled Pickering emulsion system with strong thixotropic properties was constructed and its microscopically self-assembled structure was characterized. The yielding and memory recovery characteristics of the magnetic-controlled memory fluid (MMF) were studied by means of steady-state and dynamic shear measurement, and the optimal rheological parameters suitable for printing were determined. A 3D printing platform and a memory elimination platform for coordinated control of magnetic field and motion system were built to further study and optimize the printing process. Finally, the composite structure is controlled by an array magnetic field to realize an amoeba-like motion. Novel voxel-based 3D printing and its application in soft robots can provide new ideas for space exploration, biomedicine, military reconnaissance and many other fields.

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Remote surgery using a neuroendovascular intervention support robot equipped with a sensing function: Experimental verification

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Asian Journal of Neurosurgery 2022年第2期16卷 363-366页

作者： Shigeru Miyachi Yoshitaka Nagano Reo Kawaguchi Tomotaka Ohshima Hiroki Tadauchi Department of Neurological Surgery Aichi Medical University Nagakute Neuroendovascular Therapy Center Aichi Medical University Nagakute Department of Electronic Control and Robot Engineering Aichi University of Technology Gamagori Aichi Graduation School of System Engineering Aichi University of Technology Gamagori Aichi

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Comparison of Magneto-Optical Faraday Effect Method and Magnetic Camera for Imaging the 2-D Static Leakage Magnetic Flux Density

e-Journal of Nondestructive Testing

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e-Journal of Nondestructive Testing 2022年第9期27卷

作者： Dharmawan, I Dewa Made Oka Lee, Jinyi Wang, Dabin Department of Control Instrumentation and Robot Engineering Chosun University Gwangju61452 Korea Republic of Interdisciplinary Program in IT-BIO Convergence System Chosun University Gwangju61452 Korea Republic of Department of Electronic Engineering Chosun University Gwangju61452 Korea Republic of IT-Based Real-Time NDT Center Chosun University Gwangju61452 Korea Republic of

Recent development of electromagnetic inspection proposed auspicious results for imaging 2-D static of leakage magnetic flux density (LMFD) on surface and sub-surface defects. This ability encourages an interest in implementing electromagnetic-based magnetic flux leakage (MFL) testing for nondestructive inspection (NDI). In recent NDI technologies, advanced magnetic inspection using magneto-optical Faraday effect (MOE) and magnetic camera dominated the pre-service and in-service inspection in critical engineering industries such as aerospace, steel manufacturing, marine, railroad, and nuclear facilities. Unfortunately, a compact comparison of these approaches has not been proposed yet. This study aimed to compare MOE and magnetic camera according to five primary analyses: the target object, magnetic source, configuration of the magnetic sensor, signal processing, and AI implementation. A literature study was conducted using 47 papers to analyze the performance of each device in capturing LMFD. This comparison study successfully obtained the advantages and limitations of each imaging technique, which is very beneficial as a compact reference for developing and selecting suitable nondestructive inspection devices for MFL testing in the future. In addition, artificial intelligence (AI) as an option to escalate the inspection confidence could increase the assessment efficiency and reliability considering fast and complex engineering systems. © 2022, NDT. net GmbH and Co. KG. All rights reserved.

关键词： Nondestructive examination

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QMIX Algorithm for Coordinated Welding of Multiple robots

QMIX Algorithm for Coordinated Welding of Multiple Robots

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作者： Liangchuang Liao Yang-Yang Chen School of Electronic Science & Engineering Southeast University Robot Department Jiangsu Automation Research Institute School of Automation Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University

This paper considers the coordinated welding control based on deep multi-agent reinforcement *** discrete-time states and actions with local observation for the welding robots and the characteristics of the weld lines(e.g.,the starting points of the weld lines and the ending points of the weld lines) are defined,which is suitable to use the monotonic value function factorisation for deep multi-agent reinforcement learning(QMIX) algorithm.A novel reward composed of trajectory optimization,collision avoidance and the task done is designed,which is proved by the simulation in the grid-world environment.

关键词： Deep multi-agent reinforcement learning Welding robots QMIX

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