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International conference of Electronics, Communication and Aerospace Technology (ICECA)

作者： Kiruba Sandou D Sunad kumara A N Binod Kumar Choudhary Shashikala Gurpur Sarishma Natrayan L M. SivaramKumar Department of Robotics and Automation Manakula Vinayagar Institute of Technology Pondicherry India Department of Computer Science and Engineering BGS Institute of Technology Adichunchanagiri University Mandya Karnataka India Department of Electrical and Electronics Engineering ARKA Jain University Jamshedpur Jharkhand India Faculty of Law Symbiosis Law School (SLS) Symbiosis International (Deemed University) (SIU) Pune Maharashtra India Department of Management Studies Graphic Era Deemed to be University Dehradun Uttarakhand India Department of Mechanical Engineering Saveetha School of Engineering SIMATS Chennai Tamilnadu India Department of EEE Karpagam Academy of higher education Coimbatore Tamiinadu

Achieving precise trajectory tracking while minimizing errors, reducing settling time, and curbing overshoot presents a significant challenge in the domain of robot-manipulator control. In response, this paper proposes a novel controller design for robot manipulators, incorporating two distinct approaches: a conventional fuzzy controller and an advanced Neuro-Fuzzy controller. These controllers are tailored to elevate trajectory tracking performance by simultaneously optimizing time characteristics in robot manipulator responses. To assess their efficacy, a range of test scenarios is devised, encompassing different trajectory types, including linear and nonlinear paths. Upon comparative analysis, the results highlight an intriguing contrast: while the fuzzy controller exhibits higher maximum overshoot and longer settling times in the robot's response, the Neuro-Fuzzy controller consistently demonstrates superior performance. The comprehensive error analysis such as Integral Square Error (ISE) and Integral Absolute Error (IAE) further underscores the capability of the Neuro-Fuzzy-based robot manipulator in delivering trajectory tracking precision. This study contributes to the advancement of trajectory control techniques for robot manipulators, paving the way for enhanced automation and performance across various applications.

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Regularization with multilevel non-stationary tight framelets for image restoration

arXiv

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arXiv 2021年

作者： Li, Yan-Ran Chan, Raymond H.F. Shen, Lixin Zhuang, Xiaosheng College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China Guangdong Key Laboratory of Intelligent Information Processing Shenzhen Key Laboratory of Media Security Shenzhen University Shenzhen518060 China SZU Branch Shenzhen Institute of Artificial Intelligence and Robotics for Society China Department of Mathematics City University of Hong Kong Tat Chee Avenue Kowloon Tong Hong Kong Department of Mathematics Syracuse University SyracuseNY13244 United States

Variational regularization models are one of the popular and efficient approaches for image restoration. The regularization functional in the model carries prior knowledge about the image to be restored. The prior knowledge, in particular for natural images, are the first-order (i.e. variance in luminance) and second-order (i.e. contrast and texture) information. In this paper, we propose a model for image restoration, using a multilevel non-stationary tight framelet system that can capture the image's first-order and second-order information. We develop an algorithm to solve the proposed model and the numerical experiments show that the model is effective and efficient as compared to other higher-order models. Copyright © 2021, The Authors. All rights reserved.

关键词： Image reconstruction

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Cooperative Awareness in Cognitive Wireless Networks for Jamming Control

Cooperative Awareness in Cognitive Wireless Networks for Jam...

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IEEE World Forum on Internet of Things (WF-IoT)

作者： André Mendes Diego Brandão Miguel Diaz-Cacho Research Centre in Digitalization and Intelligent Robotics (CeDRI) Instituto Politécnico de Bragança Bragança Portugal Laboratório Associado para a Sustentabilidade e Tecnologia em Regiões de Montanha (SusTEC) Instituto Politécnico de Bragança Bragança Portugal Computer Science Depart. CEFET/RJ Rio de Janeiro Brazil Department of Systems Engineering and Automatics Universidade de Vigo Spain

ISBN: (数字)9798350311617

ISBN: (纸本)9798350311624

In cognitive wireless networks, opportunistic network devices can be programmed to take advantage of licence holders' idle times and dynamically adjust their operating parameters to improve transmissions. For this to be successful, these idle periods must be reliably detected. To support this requirement, this work proposes a cooperative detection mechanism for the signals transmitted by the licenced system through the use of positioning-enabled devices. Such devices can provide information to guide and control opportunistic network devices to limit interference to the licenced system. Simulations show that keeping interference within specification limits makes it possible to maintain opportunistic network communications in an ad hoc scenario with quality.

关键词： Wireless networks Power control Interference Ad hoc networks Reliability Internet of Things Jamming

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Challenges and Outlook in Robotic Manipulation of Deformable Objects

arXiv

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arXiv 2021年

作者： Zhu, Jihong Cherubini, Andrea Dune, Claire Navarro-Alarcon, David Alambeigi, Farshid Berenson, Dmitry Ficuciello, Fanny Harada, Kensuke Kober, Jens Li, Xiang Pan, Jia Yuan, Wenzhen Gienger, Michael Cognitive Robotics TU Delft Honda Research Institute Europe Netherlands LIRMM Université de Montpellier CNRS 161 Rue Ada Montpellier34090 France COSMER Laboratory EA 7398 Universié de Toulon La Garde83130 France The Hong Kong Polytechnic University Department of Mechanical Engineering Kowloon Hong Kong The University of Texas at Austin Austin United States The University of Michigan Ann ArborMI United States Università degli Studi di Napoli Federico II Napoli80125 Italy The Osaka University Japan The National Institute of AIST Japan Cognitive Robotics TU Delft Netherlands Department of Automation Tsinghua University Beijing China The Department of Computer Science The University of Hong Kong Pok Fu Lam Hong Kong Robotics Institute Carnegie Mellon University PittsburghPA15213 United States Honda Research Institute Europe Offenbach Germany

Deformable object manipulation (DOM) is an emerging research problem in robotics. The ability to manipulate deformable objects endows robots with higher autonomy and promises new applications in the industrial, services, and healthcare sectors. However, compared to rigid object manipulation, the manipulation of deformable objects is considerably more complex, and is still an open research problem. Addressing DOM challenges demand breakthroughs in almost all aspects of robotics, namely hardware design, sensing, (deformation) modeling, planning, and control. In this article, we review recent advances and highlight the main challenges when considering deformation in each sub-field. A particular focus of our paper lies in the discussions of these challenges and proposing future directions of research. © 2021, CC BY.

关键词： Deformation

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Limited Knowledge of Safe Driving Practice among Drivers with Diabetes in Armenia: Association with Greater Risk of Motor Vehicle Accidents

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Journal of Diabetes Mellitus 2019年第1期9卷 14-23页

作者： Lilit Petrosyan Zhanna Ghazaryan Greta Muradyan Elena Aghajanova Marek Brabece Denisa Janickova Zdarska Katarina Halciakova Jan Polak Brian MFrier Jan Broz N8 Policlinic Yerevan State Medical UniversityYerevanArmenia “SourbAstvatsamayr”Medical Centers YerevanArmenia Armenian-American Wellness Center YerevanArmenia Department of Endocrinology Yerevan State Medical University“Muratsan”University HospitalYerevanArmenia Institute of Computer Science The Czech Academy of SciencesPragueCzech Republic Czech Institute of Informatics Roboticsand CyberneticsCzech Technical University in PraguePragueCzech Republic Department of Internal Medicine Second Medical Faculty of Charles UniversityPragueCzech Republic Department for the Study of Obesity and Diabetes Third Medical Faculty of Charles UniversityPragueCzech Republic British Heart Foundation Centre for Cardiovascular Science The Queen’s Medical Research InstituteUniversity of EdinburghEdinburghUK

Aims: The aims of the study were to assess the degree of knowledge and adherence to the recommended safe practice for driving and the risk of road traffic accidents among people with diabetes mellitus in Armenia. Methods: A total of 628 respondents, including 200 drivers, out of 641 consecutive attendees at six diabetes clinics, participated in the survey. A modified British questionnaire on driving and diabetes was used to obtain the relevant data. The information from all 103 drivers treated with insulin and 73 taking sulfonylureas was reviewed. Results: The study revealed that of 176 insulin and sulfonylurea-treated drivers, 161 (91.5%) had never received any advice about safe driving practices. Among the drivers, 156 (88.6%) never measured their blood glucose before, or during driving. The survey revealed that 86 (51.2%) of 168 patients had a history of at least one motor vehicle accident within the previous 5 years. The average road traffic accident rate per person/year was 0.21. Conclusions: The study revealed a lack of knowledge among drivers with diabetes treated with insulin or sulfonylureas concerning recommended safe practices for driving. This was associated with significant hypoglycemia while driving and an elevated rate of road traffic accidents.

关键词： Driving Hypoglycemia Road Traffic Accident

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An Intrusion Detection System Dataset for a Multi-Agent Cyber-Physical Conveyor System

An Intrusion Detection System Dataset for a Multi-Agent Cybe...

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IEEE International Conference on Industrial Technology (ICIT)

作者： Gustavo Funchal Farzana Zahid Victoria Melo Matthew M. Y. Kuo Tiago Pedrosa Roopak Sinha Fernando de la Prieta Paulo Leitao Research Centre in Digitalization and Intelligent Robotics (CeDRI) Instituto Politecnico de Braganca Braganca Portugal Computer Science and Software Engineering Department Auckland University of Technology Auckland New Zealand Laboratório para a Sustentabilidade e Tecnologia em Regióes de Montanha (SusTEC) Instituto Politécnico de Bragança Bragança Portugal BISITE Digital Innovation hub University of Salamanca Salamanca Spain

Industry 4.0 is built upon the foundation of connecting devices and systems via Internet of Things (IoT) technologies, with Cyber- Physical Systems (CPS) serving as the backbone infrastructure. Although this approach brings numerous benefits like improved performance, responsiveness and reconfigurability, it also introduces security concerns, making devices and systems vulnerable to cyber attacks. There is a need for effective techniques to protect these systems, and the availability of datasets becomes essential to support the development of such techniques. This paper presents a dataset based on the collection of traffic information exchanged in a self-organizing conveyor system using the multi-agent systems (MAS) architecture and containing various intelligent conveyor modules. The dataset comprises data collected at the network and agent levels under normal system operation, denial of service (DoS) attacks, and malicious agent attacks. An intrusion detection system that integrates Fast Fourier Transform (FFT) and Machine Learning (ML) analysis is developed to demonstrate the utility of this dataset.

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Improving Referring Expression Comprehension by Suppressing Expression-unrelated Proposals

Improving Referring Expression Comprehension by Suppressing ...

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Electronic Information Engineering and computer Technology (EIECT), International Conference on

作者： Qun Wang Feng Zhu Xiang Li Ruida Ye Key Laboratory of Opto-Electronic Information Processing Chinese Academy of Sciences Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China Faculty of Computer Science and Engineering Northeastern University Shenyang China Department of Aerospace Engineering and Technology Space Engineering University Beijing China

The prevailing referring expression comprehension (REC) method is based on two stages: 1) detecting multiple candidate proposals using an object detector and 2) aligning proposals with text descriptions. Existing two-stage models have achieved significant improvements with excellent alignment modules. However, their alignment modules treat each proposal equally without filtering expression-unrelated proposals. These expression-unrelated proposals may interfere with the alignment modules’ ability to accurately reason about the target proposal. These proposals also increase the difficulty of training alignment modules. To solve this problem, we propose a new framework, that can suppress expression-unrelated proposals for alignment modules. Specifically, we first design a suppression module, which calculates the relevance scores between the proposals and the expression by using the semantics in the expression. Then, these scores are integrated into three basic alignment modules, including subject, location, and relationship modules, to guide each module to focus on the expression-related proposals. We conduct extensive experiments on three benchmark datasets, and the results show the effectiveness of our suppression module and performance improvement.

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Design and initial study of porous core electromagnet for levitation applications

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AIP Conference Proceedings 2018年第1期2029卷

作者： Adam Piłat Bartosz Sikora 1AGH University of Science and Technology Faculty of Electrical Engineering Automatics Computer Science and Biomedical Engineering Department of Automatic Control and Robotics Mickiewicza 30 30-059 Krakow Poland

A concept of the porous core electromagnet is studied. The form for the electromagnet core was printed using 3D technique. The core was manufactured manually using iron filings and cured in room temperature and air pressure. The aim of this paper is to deliver initial analysis of the proposed powder core together with the modelling procedure by the using finite element method, and to compare the experimental results of the manually manufactured electromagnet. The material property of the numerical model was adjusted to fit the experimental results. Finally, the electromagnet was tested in the levitation real–time experiment.

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Efficient MedSAMs: Segment Anything in Medical Images on Laptop

arXiv

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arXiv 2024年

作者： Ma, Jun Li, Feifei Kim, Sumin Asakereh, Reza Le, Bao-Hiep Nguyen-Vu, Dang-Khoa Pfefferle, Alexander Wei, Muxin Gao, Ruochen Lyu, Donghang Yang, Songxiao Purucker, Lennart Marinov, Zdravko Staring, Marius Lu, Haisheng Dao, Thuy Thanh Ye, Xincheng Li, Zhi Brugnara, Gianluca Vollmuth, Philipp Foltyn-Dumitru, Martha Cho, Jaeyoung Mahmutoglu, Mustafa Ahmed Bendszus, Martin Pflüger, Irada Rastogi, Aditya Ni, Dong Yang, Xin Zhou, Guang-Quan Wang, Kaini Heller, Nicholas Papanikolopoulos, Nikolaos Weight, Christopher Tong, Yubing Udupa, Jayaram K. Patrick, Cahill J. Wang, Yaqi Zhang, Yifan Contijoch, Francisco McVeigh, Elliot Ye, Xin He, Shucheng Haase, Robert Pinetz, Thomas Radbruch, Alexander Krause, Inga Kobler, Erich He, Jian Tang, Yucheng Yang, Haichun Huo, Yuankai Luo, Gongning Kushibar, Kaisar Amankulov, Jandos Toleshbayev, Dias Mukhamejan, Amangeldi Egger, Jan Pepe, Antonio Gsaxner, Christina Luijten, Gijs Fujita, Shohei Kikuchi, Tomohiro Wiestler, Benedikt Kirschke, Jan S. de la Rosa, Ezequiel Bolelli, Federico Lumetti, Luca Grana, Costantino Xie, Kunpeng Wu, Guomin Puladi, Behrus Martín-Isla, Carlos Lekadir, Karim Campello, Victor M. Shao, Wei Brisbane, Wayne Jiang, Hongxu Wei, Hao Yuan, Wu Li, Shuangle Zhou, Yuyin Wang, Bo AI Collaborative Centre University Health Network Department of Laboratory Medicine and Pathobiology University of Toronto Vector Institute Toronto Canada Peter Munk Cardiac Centre University Health Network Toronto Canada Toronto General Hospital Research Institute University Health Network Department of Computer Science University of Toronto University Health Network Vector Institute Toronto Canada University of Science Vietnam National University Ho Chi Minh City Viet Nam Institute of Computer Science University of Freiburg Freiburg Germany School of Medicine and Health Harbin Institute of Technology Harbin China Division of Image Processing Department of Radiology Leiden University Medical Center Leiden Netherlands Department of System and Control Engineering School of Engineering Institute of Science Tokyo Formerly Tokyo Institute of Technology Tokyo Japan Institute for Anthropomatics and Robotics Karlsruhe Institute of Technology Karlsruhe Germany School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China School of Electrical Engineering and Computer Science University of Queensland Brisbane Australia School of Cyberspace Hangzhou Dianzi University Hangzhou China Division for Computational Radiology and Clinical AI The Department of Neuroradiology University Hospital Bonn Germany Division for Computational Radiology and Clinical AI The Department of Neuroradiology University Hospital Bonn Germany Department of Neuroradiology Heidelberg University Hospital Heidelberg Germany Division for Computational Radiology and Clinical AI Department of Neuroradiology University Hospital Bonn Germany School of Biomedical Engineering Shenzhen University Shenzhen China School of Biological Science and Medical Engineering Southeast University Nanjing China Department of Urology Cleveland Clinic Cleveland United States Department of Computer Science University of Minnesota Minneapolis United St

Promptable segmentation foundation models have emerged as a transformative approach to addressing the diverse needs in medical images, but most existing models require expensive computing, posing a big barrier to their adoption in clinical practice. In this work, we organized the first international competition dedicated to promptable medical image segmentation, featuring a large-scale dataset spanning nine common imaging modalities from over 20 different institutions. The top teams developed lightweight segmentation foundation models and implemented an efficient inference pipeline that substantially reduced computational requirements while maintaining state-of-the-art segmentation accuracy. Moreover, the post-challenge phase advanced the algorithms through the design of performance booster and reproducibility tasks, resulting in improved algorithms and validated reproducibility of the winning solution. Furthermore, the best-performing algorithms have been incorporated into the open-source software with a user-friendly interface to facilitate clinical adoption. The data and code are publicly available to foster the further development of medical image segmentation foundation models and pave the way for impactful real-world applications. © 2024, CC BY-NC-SA.

关键词： Open source software

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The economic value of augmentative exoskeletons and their assistance

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Communications Engineering 2023年第1期2卷 43页

作者： Medrano, Roberto Leo Thomas, Gray Cortright Margolin, Drew Rouse, Elliott J. Neurobionics Lab University of Michigan Ann Arbor MI United States Mechanical Engineering University of Michigan Ann Arbor MI United States Department of Robotics University of Michigan Ann Arbor MI United States Electrical Engineering and Computer Science University of Michigan Ann Arbor MI United States Communication Cornell University Ithaca NY United States

For augmentative exoskeletons that assist able-bodied users, a clear metric of success remains an open question. Here we leverage the Vickrey second-price auction to quantify the economic value added by lower-limb exoskeletons and their assistance. We posited that if exoskeletons provided helpful assistance during a difficult task, this value could be quantified through a lowering of participant auction bids to continue walking. The bidding results were compared across different conditions to determine the economic value of the exoskeleton, bearing in mind also the cost of wearing the added mass of the exoskeleton. Results show that the total value of the exoskeleton and assistance was modest. While most participants found the assistance itself valuable, this value was mostly offset by the extra mass added of wearing the exoskeleton. Our approach provides insight into how exoskeleton wearers may value different aspects of user experience. These results suggest economic value may be a powerful tool in the design and control of exoskeletons that maximize user benefit. © The Author(s) 2023.

关键词： Mechanical engineering Biomedical engineering

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