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5th International Conference on System Reliability and Safety engineering, SRSE 2023

作者： Li, Ruiqi Wang, Kai Zeng, Peng Cao, Jiwei Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang110016 China Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China Chinese Academy of Sciences Shenyang Institute of Automation Shenyang110016 China Harbin Institute of Technology Department of Electrical Engineering China

ISBN: (纸本)9798350305944

Active magnetic bearings (AMBs) have many advantages over traditional oil bearings due to their non-contact characteristics. They are environmentally friendly solution and have been proven to be highly reliable and available. Electromagnetic coils are vital components of AMB and they are failure prone. In this paper, the failure mode of magnetic bearing coil and its corresponding failure mechanism are reviewed by FMMEA method, and the existing coil fault diagnosis methods are introduced. Future directions for coil insulation health monitoring aiming at the application characteristics of AMBs are also discussed. © 2023 IEEE.

关键词： Failure analysis

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A Survey on Group Fairness in Federated Learning: Challenges, Taxonomy of Solutions and Directions for Future Research

arXiv

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arXiv 2024年

作者： Salazar, Teresa Araújo, Helder Cano, Alberto Abreu, Pedro Henriques Centre for Informatics and Systems Department of Informatics Engineering University of Coimbra Coimbra3030-790 Portugal Institute of Systems and Robotics Department of Electrical and Computer Engineering University of Coimbra Coimbra3030-790 Portugal Virginia Commonwealth University RichmondVA23284 United States

Group fairness in machine learning is a critical area of research focused on achieving equitable outcomes across different groups defined by sensitive attributes such as race or gender. Federated learning, a decentralized approach to training machine learning models across multiple devices or organizations without sharing raw data, amplifies the need for fairness due to the heterogeneous data distributions across clients, which can exacerbate biases. The intersection of federated learning and group fairness has attracted significant interest, with 47 research works specifically dedicated to addressing this issue. However, no dedicated survey has focused comprehensively on group fairness in federated learning. In this work, we present an in-depth survey on this topic, addressing the critical challenges and reviewing related works in the field. We create a novel taxonomy of these approaches based on key criteria such as data partitioning, location, and applied strategies. Additionally, we explore broader concerns related to this problem and investigate how different approaches handle the complexities of various sensitive groups and their intersections. Finally, we review the datasets and applications commonly used in current research. We conclude by highlighting key areas for future research, emphasizing the need for more methods to address the complexities of achieving group fairness in federated *** Codes 68T01 © 2024, CC BY.

关键词： Federated learning

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Bifurcations and Application of the Vallis - Model 11

Bifurcations and Application of the Vallis - Model

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11th IEEE International Conference on Computational Cybernetics and Cyber-Medical systems, ICCC 2024

作者： Nagy, Balint Molnar, Gyorgy Joos, Antal Nagy, Eniko Institute of Computer Engineering University of Dunaújváros Department of Mathematics Dunaújváros Hungary Budapest Business University Faculty of Finance and Accountancy Department of Applied Quantitative Methods Budapest Hungary Institute of Electrophysics Óbuda University Kandó Kálmán Faculty of Electrical Engineering Department of Natural Sciences Budapest Hungary Óbuda University Kandó Kálmán Faculty of Electrical Engineering Budapest Hungary Széchenyi University János Csere Apáczai Faculty Győr Hungary Antal Bejczy Center for Intelligent Robotics Institute of Cyberphysical Systems Óbuda University John von Neumann Faculty Budapest Hungary

ISBN: (纸本)9798350350142

Investigating chaotic systems is a fertile field considering that chaos is an exotic chapter in the theory of differential equations, and it has useful applications in the theory of communications. In this work a well-known chaotic system is investigated from the bifurcation point of view and some applications are also introduced. The data studied are also visualized for better clarity. The results observed can be helpful in the encryption methods of the implementation of different communication channels. © 2024 IEEE.

关键词： Chaotic systems

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Active Camera View Planning Based on Deep Reinforcement Learning in Indoor Exploration

Active Camera View Planning Based on Deep Reinforcement Lear...

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Chinese Control Conference (CCC)

作者： Hao-Yu Wang Qing-Hao Meng Xu-Yang Dai Tianjin Key Laboratory of Intelligent Unmanned Swarm Technology and System Institute of Robotics and Autonomous Systems School of Electrical and Information Engineering Tianjin University Tianjin China

In the last decades, significant progress has been made in the field of active vSLAM (visual simultaneous localization and mapping). However, the majority of active vSLAM methods suffer from the problem of coupling the camera's viewpoint to the robot's motion, which limits the initiative during the exploration of unknown environments. To address this issue, this study proposes a camera view planning method based on deep reinforcement learning (DRL), which makes the camera rotate independently. First, feature encoding is performed on the reconstructed navigation map using a multi-layer convolutional neural network (CNN). Second, the DRL-based camera view planning method is trained through the proximal policy optimization (PPO) algorithm. Last, a significant number of tests is performed on a public dataset of indoor environments. The simulation results show that the proposed camera view planning method improves the exploration coverage by an average of 4% (33.86 m 2 for traditional vs. 35.21 m 2 for the suggested method). Meanwhile, the kind of semantic information newly observed in each step increases by 21% (2.9 for traditional vs. 3.5 for the proposed method) on average, indicating the improvement in the efficiency of information acquisition.

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Spiking neural networks: Towards bio-inspired multimodal perception in robotics

arXiv

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arXiv 2024年

作者： Oikonomou, Katerina Maria Balaska, Vasiliki Tsintotas, Konstantinos A. Mavridis, Christos N. Kansizoglou, Ioannis Gasteratos, Antonios The Department of Production and Management Engineering Laboratory of Robotics and Automation Democritus University of Thrace Xanthi Greece The Department of Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden

Spiking neural networks (SNNs) have captured apparent interest over the recent years, stemming from neuroscience and reaching the field of artificial intelligence. However, due to their nature SNNs remain far behind in achieving the exceptional performance of deep neural networks (DNNs). As a result, many scholars are exploring ways to enhance SNNs by using learning techniques from DNNs. While this approach has been proven to achieve considerable improvements in SNN performance, we propose another perspective: enhancing the biological plausibility of the models to leverage the advantages of SNNs fully. Our approach aims to propose a brain-like combination of audio-visual signal processing for recognition tasks, intended to succeed in more bio-plausible human-robot interaction applications. © 2024, CC BY-NC-SA.

关键词： Adversarial machine learning

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Renderable Street View Map-Based Localization: Leveraging 3D Gaussian Splatting for Street-Level Positioning

Renderable Street View Map-Based Localization: Leveraging 3D...

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IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Howoong Jun Hyeonwoo Yu Songhwai Oh Artificial Intelligence (IPAI) Seoul National University and Automation and Systems Research Institute (ASRI) and Sequor Robotics Inc. Seoul Korea Republic of Department of Intelligent Robotics & Mechanical Engineering Sungkyunkwan University (SKKU) Suwon-si Korea Republic of Department of Electrical and Computer Engineering (ECE) & Interdisciplinary Program in Artificial Intelligence (IPAI) Seoul National University and Automation and Systems Research Institute (ASRI) and Sequor Robotics Inc. Seoul Korea Republic of

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

In this paper, we introduce a new method that first utilizes 3D Gaussian splatting in street-level localization problem. Robust localization with street-level real-world images such as street view is a major issue for autonomous vehicle, augmented reality (AR) navigation, and outdoor mobile robots. The objective is to determine the position and orientation of a query image that matches a street view database composed of RGB images. However, given the limited information available in the street view images, accurately determining the location solely based on this data presents a significant challenge. To address this challenge, we propose a novel method called renderable street view map-based localization (RSM-Loc). This approach enhances the localization process by augmenting 2D street view images into a renderable 3D map using 3D Gaussian splatting, to resolve street-level localization problems. Upon receiving a query RGB image without geometry information, the proposed method renders 2D images from a pre-made renderable map and compares image pose similarities between the rendered images and the query image. Through iterations of this process, the proposed method eventually estimates the pose of the given query image. The experimental results demonstrate that RSM-Loc outperforms the baselines with neural-field-based localization. Additionally, we conduct deep analysis on the proposed method to show that our method can serve as a new concept for the street-level localization problem.

关键词： Location awareness Visualization Matched filters Three-dimensional displays Image resolution Navigation Noise measurement Mobile robots Intelligent robots Image reconstruction

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Modular Sensor Integration into Soft Robots using Stretchable Wires for Nuclear Infrastructure Inspection and Radiation Spectroscopy

Modular Sensor Integration into Soft Robots using Stretchabl...

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IEEE International Conference on Soft robotics (RoboSoft)

作者： Calder Wilson Joseph Karam Callen Votzke Farhan Rozaidi Camille J. Palmer Ross L. Hatton Matthew L. Johnston School of Electrical Engineering and Computer Science Corvallis OR USA Collaborative Robotics and Intelligent Systems Institute Corvallis OR USA School of Nuclear Science & Engineering Oregon State University Corvallis OR USA

Soft robots are uniquely suited for applications in inspection, search and rescue, and exploration in confined and unstructured environments. Leveraging the benefits of these soft robots will increasingly require the integration of equally compliant electronic components for sensing, actuation, control, and computation to maintain mechanical conformability at the system level. In this work, we demonstrate the integration of modular electronic sensors into a robotic snake platform using stretchable interconnects. Aimed at applications in nuclear infrastructure inspection, included sensors include visual perception and on-board radiation spectroscopy. In addition to high mechanical compliance, the stretchable interconnect enables physical separation of analog sensors and digital electronics for use in radiation environments. We present details of stretchable electronics fabrication and integration, standalone validation of integrated sensors, and field test results from a simulated nuclear infrastructure inspection task.

关键词： Mechanical sensors Fabrication Spectroscopy Visualization Wires Soft robotics Inspection

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Adaptive ICT-based evaluation system in teaching and learning process 27

Adaptive ICT-based evaluation system in teaching and learnin...

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27th IEEE International Conference on Intelligent engineering systems, INES 2023

作者： Eva, Karl Nagy, Eniko Molnar, Gyorgy Varkerti Primary School Varpalota Hungary Gyr Hungary Obuda University Antal Bejczy Center for Intelligent Robotics John von Neumann Faculty Institute of Cyberphysical Systems Budapest Hungary Obuda University Kando Kalman Faculty of Electrical Engineering Budapest Hungary Szechenyi University Janos Csere Apaczai Faculty Gyr Hungary

ISBN: (纸本)9798350328516

Evaluation is an essential part of education. In addition to helping track student progress and learning processes, evaluations play a significant critical and important role in developing the individual's personality and forming a realistic self-image. Therefore, evaluations must be accurate, reliable, encompassing of changes, and supportive of developmental paths. Assessments can take various forms and can be carried out in-person, verbally, in writing, or through practical tasks, but they can also be conducted online, in a digital format, within a suitable framework. Regardless of these, one common element, the assessing educator is the adult who plans, integrates, and conducts the periodic control and evaluation process. Thus, there is also a generational difference inherently present and this affects the entire teaching and learning process, thereby influencing the evaluation process significantly, and reducing its efficiency. In this study, we present a self-developed system that increases the efficiency of the control and evaluation process by assisting the educator's work and reducing the communication gap due to generational differences. In addition to describing the applied technologies during the system's demonstration, we also discuss the methods and operating processes, which we conclude by evaluating the test results. © 2023 IEEE.

关键词： Students

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Replacing Gallium Oxide shell with conductive Ag: Toward printable and recyclable composite for highly stretchable electronics, electromagnetic shielding, and thermal interfaces

arXiv

引用

arXiv 2025年

作者： Hajalilou, Abdollah Parvini, Elahe Morgado, Tiago A. Lopes, Pedro Alhais Jorge, M. Estrela Melo Freitas, Marta Tavakoli, Mahmoud Institute of Systems and Robotics Department of Electrical Engineering University of Coimbra Coimbra3030-290 Portugal Instituto de Telecomunicações Department of Electrical Engineering University of Coimbra Coimbra3030-290 Portugal Faculdade de Ciências Universidade de Lisboa Lisboa1749-016 Portugal

Liquid metal (LM)-based composites hold promise for soft electronics due to their high conductivity and fluidic nature. However, the presence of α-Ga2O3 and GaOOH layers around LM droplets impairs conductivity and performance. We tackle this issue by replacing the oxide layer with conductive silver (Ag) using an ultrasonic-assisted galvanic replacement reaction. The Ag-coated nanoparticles form aggregated, porous microparticles that are mixed with Styrene-Isoprene-Styrene (SIS) polymers, resulting in a digitally printable composite with superior electrical conductivity and electromechanical properties compared to conventional fillers. Adding more LM enhances these properties further. The composite achieves EMI shielding effectiveness (SE) exceeding 75 dB in the X-band frequency range, even at 200% strain, meeting stringent military and medical standards. It is applicable in wireless communications, Bluetooth signal blocking, and as a thermal interface material (TIM). Additionally, we highlight its recyclability using a biodegradable solvent, underscoring its eco-friendly potential. This composite represents a significant advancement in stretchable electronics and EMI shielding, with implications for wearable and bioelectronic applications. © 2025, CC BY-NC-ND.

关键词： Electromagnetic shielding

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Processing of Corneal Images with A Cepstral Approach 23

Processing of Corneal Images with A Cepstral Approach

引用

23rd International Conference on Computer Theory and Applications, ICCTA 2013

作者： Tawfik, Nahed El Din, Mahmoud F. Dessouky, Moawad I. Abd Ei-Samie, Fathi E. Electronics Research Institute Computers and Systems Dept. Dokki-Giza Egypt Menoufia University Faculty of Electronic Engineering Department of Electronics and Electrical Communications Menouf Egypt

ISBN: (纸本)9781479924158

The Mel-Frequency Cepstral Coefficients (MFCCs) feature extraction approach can be used for corneal pattern recognition, and hence in the diagnosis of corneal diseases. In this method, cepstral features are extracted from a group of corneal images. Images are first transformed to 1-D signals by lexicographic ordering, and then MFCCs and polynomial shaping coefficients are extracted to form a database of features, which can be used to train a neural network. With the same method used in the training phase, features are extracted from a new group of images. These features can be tested with the neural network. Different transform domains can be used for this purpose. Experimental results show that the Discrete Cosine Transform (DCT) is the most suitable domain for feature extraction. The method in this paper is limited to feature extraction for pattern recognition and the automatic diagnosis case is left for future work. © 2013 IEEE.

关键词： Feature extraction

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