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40th Annual ACM Symposium on Applied Computing, SAC 2025

作者： Frota, Lucyanno Rocha, Rui P. Dept. of Electrical and Computer Engineering University of Coimbra Coimbra Portugal Institute of Systems and Robotics University of Coimbra Coimbra Portugal

ISBN: (纸本)9798400706295

Service robots are undergoing a massification process similar to what happened with personal computers and cell phones a few decades ago. Their ubiquitous coexistence and interaction with humans requires that their representation models of the workspace go beyond metric information used for safe navigation. They are also required to assign semantic meaning to objects and places, i.e. to build semantic maps, in order to understand scenes and engage in human-like interactions. This paper proposes the Semantic MAPping (SMAP) framework to provide a service robot operating in human populated environments with a semantic mapping layer on top of a metric SLAM layer. SMAP is modular, expandable, and efficient enough to run locally on the robot. It has been implemented in Robot Operating System 2 (ROS2) using modular Docker containers. Preliminary experiments with a Pioneer 3-DX mobile robot having a system on module Nvidia Jetson AGX Xavier demonstrated its potential for future service robotics applications. Copyright © 2025 held by the owner/author(s).

关键词： Modular robots

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Chattering-Free Fault-Tolerant Cluster Control and Fault Direction Identification for HIL UAV Swarm With Pre-Specified Performance

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 183-197页

作者： Pei-Ming Liu Xiang-Gui Guo Jian-Liang Wang Daniel Coutinho Lihua Xie the Beijing Engineering Research Center of Industrial Spectrum Imaging School of Automation and Electrical Engineering University of Science and Technology Beijing the Shunde Graduate School of University of Science and Technology Beijing IEEE Autonomous Intelligent Systems Department Hangzhou Innovation Institute of Beihang University the Department of Automation and Systems Universidade Federal de Santa Catarina the School of Electrical and Electronic Engineering Nanyang Technological University

In this paper, the problem of pre-specified performance fault-tolerant cluster consensus control and fault direction identification is solved for the human-in-the-loop(HIL) swarm unmanned aerial vehicles(UAVs) in the presence of possible nonidentical and unknown direction faults(NUDFs) in the yaw *** control strategy begins with the design of a pre-specified performance event-triggered observer for each individual *** observers estimate the outputs of the human controlled UAVs, and simultaneously achieve the distributed design of actual control signals as well as cluster consensus of the observer *** is worth mentioning that these observers require neither the high-order derivatives of the human controlled UAVs' output nor a priori knowledge of the initial conditions. The fault-tolerant controller realizes the pre-specified performance output regulation through error transformation and the Nussbaum function. It should be pointed out that there are no chattering caused by the jump of the Nussbaum function when a reverse fault occurs. In addition, to provide a basis for further solving the problem of physical malfunctions, a fault direction identification algorithm is proposed to accurately identify whether a reverse fault has occurred. Simulation results verify the effectiveness of the proposed control and fault direction identification strategies when the reverse faults occur.

关键词： Chattering-free cluster consensus fault direction identification human-in-the-loop (HIL) nonidentical and unknown direction faults (NUDFs) pre-specified performance swarm unmanned aerial vehicles (UAVs)

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A novel MODWT–local pattern transformation feature fusion approach for high-impedance fault detection in medium voltage power distribution networks

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Neural Computing and Applications 2025年 1-15页

作者： Varghese, P. Rini Subathra, M.S.P. Peter, Geno Stonier, Albert Alexander Kuppusamy, Ramya Teekaraman, Yuvaraja Department of Electrical and Electronics Engineering School of Engineering and Technology Karunya Institute of Technology and Sciences Tamil Nadu Coimbatore641114 India Department of Robotics Engineering School of Engineering and Technology Karunya Institute of Technology and Sciences Tamil Nadu Coimbatore641114 India CRISD School of Engineering and Technology University of Technology Sarawak Sarawak Malaysia School of Electrical Engineering Vellore Institute of Technology Vellore India Department of Electrical and Electronics Engineering Sri Sairam College of Engineering Bengaluru562106 India Kuwait Jahra Kuwait

Due to the arcing nature, the high-impedance fault (HIF), which typically occurs in medium voltage (MV) distribution networks, poses a risk to equipment, personnel, and livestock. Early fault detection can save lives and prevent equipment destruction. Since the fault current in a power system is contained within the normal current range, identifying the occurrence of HIF is difficult. Using maximal overlap discrete wavelet transform (MODWT) and a combination of MODWT–local pattern transformations (local binary pattern, local gradient pattern, local neighbor gradient pattern, and local neighbor descriptive pattern), the paper analyses the current signals from radial and mesh distribution networks and features extracted during HIF and non-HIF (line-to-ground (LG), double line (LL), double line-to-ground (LLG), and triple line-to-ground (LLLG) fault conditions). For the first time in power distribution networks for fault analysis, the suggested algorithm performs the HIF detection in the MV distribution system. To determine the best feature sets from the extracted features, the Kruskal–Wallis test was performed. Bidirectional long short-term memory (Bi-LSTM) was used for the chosen feature sets to classify the data as HIF or non-HIF. MODWT–LGP fusion achieves the highest accuracy for both networks among the four algorithms. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Discrete wavelet transforms

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Fully tunable Fabry-Pérot cavity based on MEMS Sagnac loop reflector with ultra-low static power consumption

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Microsystems & Nanoengineering 2024年第4期10卷 355-365页

作者： Young Jae Park Man Jae Her Youngjae Jeong Dong Ju Choi Dong Uk Kim Min Gi Lim Myung Seok Hong Hyug Su Kwon Kyoungsik Yu Sangyoon Han Department of Robotics and Mechatronics Engineering Daegu Gyeongbuk Institute of Science and Technology(DGIST)Daegu 42988Republic of Korea School of Electrical Engineering Korea Advanced Institute of Science and Technology(KAIST)Daejeon 34141Republic of Korea Agency for Defense Development DaejeonRepublic of Korea

The Fabry-Pérot interferometer,a fundamental component in optoelectronic systems,offers interesting applications such as sensors,lasers,and *** this work,we show a tunable Fabry-Pérot cavity consisting of tunable Sagnac loop reflectors(SLRs)and phase shifters based on electrostatic microelectromechanical(MEMS)*** fabrication process of the device is compatible with the standard wafer-level silicon photonics fabrication *** electrostatic actuation mechanism provides well-balanced,scalable pathways for efficient tuning *** extinction ratio of the continuously tunable SLRs’reflectivity is larger than 20 *** 2πphase shifting is achieved,and response times of all the components are less than 25μ*** actuators have extremely low static power,measuring under 20 fW and the energy needed for tuning is both below 20 pJ.

关键词： tunable tuning interferometer

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Segmentation of Retina Vessels in 2D OCT-Reconstructed Fundus Images with 3D UNet 26

Segmentation of Retina Vessels in 2D OCT-Reconstructed Fundu...

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26th IEEE Signal Processing: Algorithms, Architectures, Arrangements, and Applications, SPA 2023

作者： Marciniak, Tomasz Stankiewicz, Agnieszka Zaradzki, Przemyslaw Poznan University of Technology Division of Electronic Systems and Signal Processing Institute of Automatic Control and Robotics Department of Control Robotics and Electrical Engineering Poznan Poland

ISBN: (纸本)9798350304985

This paper presents an analysis of the effectiveness of blood vessel segmentation in human retinal images. The segmentation process was carried out for three-dimensional optical coherence tomography (OCT) scans using the author's publicly available CAVRI-C database. A 3D version of the U-Net artificial neural network was used. Various dimensions of the input blocks were investigated to determine their influence on the segmentation process. The effectiveness of the proposed solutions was evaluated using various metrics and the results obtained were compared with the 2D solution, also based on neural networks. The use of the proposed solutions allowed us to improve the segmentation even by 15% (in the case of the F1-score). © 2023 Division of Signal Processing and Electronic systems, Poznan University of Technology (DSPES PUT).

关键词： Optical tomography

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A deep learning-based model for automated STN localization using local field potentials in Parkinson’s disease

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Soft Computing 2025年第4期29卷 2343-2362页

作者： Hosny, Mohamed Naeem, Mohamed A. Zhu, Minwei Gao, Wenpeng Elshenhab, Ahmed M. Fu, Yili Department of Electrical Engineering Benha Faculty of Engineering Benha University Benha Egypt State Key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin150080 China Department of Mechatronics and Robotics Engineering Faculty of Engineering South Valley University Qena Egypt First Affiliated Hospital Harbin Medical University Harbin150001 China School of Life Science and Technology Harbin Institute of Technology Harbin150080 China Department of Mathematics Faculty of Science Mansoura University Mansoura35516 Egypt

Accurate identification of the subthalamic nucleus (STN) borders is time-consuming, relying heavily on the neurosurgeon expertise in manually interpreting the electrophysiological signals. Local field potentials (LFPs) have garnered imperative attention due to their strong correlation with the STN. However, existing detection models often face challenges with high computational complexity, hyperparameter optimization and lack of explainability, making them unreliable for clinicians. Therefore, this study introduces an explanatory framework using convolutional neural networks (CNN) for detecting the STN region from LFPs. Continuous wavelet transform is employed to convert LFPs signals into scalogram images, which are then processed by sixteen CNN models. We evaluated our framework by examining the impact of various limiting factors on the classification performance, including model size, learning rate (LR), optimizers and data scaling. Deep features are extracted from the top-performing CNN architectures to capture rich representations of the scalograms. These features are then fused and classified using k-nearest neighbour algorithm. Gradient-weighted class activation mapping is used to explain the decisions made by the proposed model. Our approach achieved an accuracy of 99.61%, outperforming individual CNN models for STN localization. The experimental results revealed that CNN models, embedded with additional hyperparameters and layers, generally outperformed smaller models. Besides, low LR significantly enhanced the performance compared to high LR. Moreover, features extracted from untuned networks produced lower performance than tuned networks. The proposed system could revolutionize deep brain stimulation surgery by increasing efficiency and reducing reliance on clinician expertise for STN detection. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.

关键词： Wavelet transforms

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Reply to comment on “Ferroelectric composite-based piezoelectric energy harvester for self-powered detection of obstructive sleep” by A. Tkach and O. Okhay

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Journal of Materiomics 2024年第5期10卷 1160-1164页

作者： Swati Panda Hyoju Shin Sugato Hajra Yumi Oh Wonjeong Oh Jeonghyeon Lee P.M.Rajaitha Basanta Kumar Panigrahi Jyoti Shukla Alok Kumar Sahu Perumal Alagarsamy Hoe Joon Kim Department of Robotics and Mechatronics Engineering Daegu Gyeongbuk Institute of Science and Technology(DGIST)Daegu 42988South Korea Department of Electrical Engineering Siksha‘O’Anusandhan UniversityBhubaneswar 751030India Department of Electrical Engineering Poornima College of EngineeringJaipur 303903India Department of Physics Indian Institute of Technology-GuwahatiAssam 781039India Robotics and Mechatronics Research Center Daegu Gyeongbuk Institute of Science and Technology(DGIST)Daegu 42988South Korea

In this contribution,we reply to comments made by Tkach et *** our publication *** 2023;9:*** main interest of our work is to synthesize a lead-free material,SrTi_(2)O_(5)(STO),and then utilize it in the formation of composites and finally design the piezoelectric nanogenerator(PENG)for self-powered sensor *** authors have observed the presence of piezoelectric voltage and current output from the *** authors humbly indicate that the PENG devices were poled using a DC poling setup as conditions mentioned in *** 2023;9:609(Panda et al.,2023)[1].The doping of STO into the PDMS increased from 2% to 20%(in mass).In this process,the piezoelectric output of the PENG device was observed to be highest for 15%(in mass)STO-PDMS ***,we agree with the comment raised by Tkach et al.,and further we have addressed the issues in a step-by-step response as follows.

关键词： Ferroelectric Lead-free Piezoelectric Polycrystalline

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A Mach-Zehnder-Modulator based FMCW Lidar Emulator in C-Band 16

A Mach-Zehnder-Modulator based FMCW Lidar Emulator in C-Band

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16th German Microwave Conference, GeMiC 2025

作者： Brockmeier, Jan Kruse, Stephan Scheytt, J. Christoph Paderborn University Heinz Nixdorf Institute Department of Electrical Engineering Germany Paderborn University Institute of Photonic Quantum Systems Department of Electrical Engineering Germany

ISBN: (纸本)9783982039749

This paper presents a frequency modulated continuous wave (FMCW) light detection and ranging (lidar) system based on Mach-Zehnder-Modulators (MZM). A thorough mathematical analysis is given to explain the basic operating principle of the system. To validate the system analysis, a laboratory setup implementing a lidar emulator in the optical C-band is built, and measurement results are given that confirm the theoretical predictions. © 2025 Institut fur Mikrowellen und Antennentechnik - IMA.

关键词： Frequency shift keying

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Robust Resource Sharing in Network Slicing via Hypothesis Testing

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IEEE Transactions on Network and Service Management 2025年第3期22卷 2731-2746页

作者： Nikolaidis, Panagiotis Baras, John Institute for Systems Research University of Maryland at College Park Department of Electrical and Computer Engineering College ParkMD20742 United States

In network slicing, the network operator needs to satisfy the service level agreements of multiple slices at the same time and on the same physical infrastructure. To do so with reduced provisioned resources, the operator may consider resource sharing mechanisms. However, each slice then becomes susceptible to traffic surges in other slices which degrades performance isolation. To maintain both high efficiency and high isolation, we propose the introduction of hypothesis testing in resource sharing. Our approach comprises two phases. In the trial phase, the operator obtains a stochastic model for each slice that describes its normal behavior, provisions resources and then signs the service level agreements. In the regular phase, whenever there is resource contention, hypothesis testing is conducted to check which slices follow their normal behavior. Slices that fail the test are excluded from resource sharing to protect the well-behaved ones. We test our approach on a mobile traffic dataset. Results show that our approach fortifies the service level agreements against unexpected traffic patterns and achieves high efficiency via resource sharing. Overall, our approach provides an appealing tradeoff between efficiency and isolation. © 2004-2012 IEEE.

关键词： Resource management Quality of service Testing Service level agreements Network slicing Bandwidth Traffic control Costs Delays Anomaly detection

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Ferroelectric composite-based piezoelectric energy harvester for selfpowered detection of obstructive sleep

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Journal of Materiomics 2023年第4期9卷 609-617页

作者： Swati Panda Hyoju Shin Sugato Hajra Yumi Oh Wonjeong Oh Jeonghyeon Lee P.M.Rajaitha Basanta Kumar Panigrahi Jyoti Shukla Alok Kumar Sahu Perumal Alagarsamy Hoe Joon Kim Department of Robotics and Mechatronics Engineering Daegu Gyeongbuk Institute of Science and Technology(DGIST)Daegu42988South Korea Department of Electrical Engineering Siksha‘O’Anusandhan UniversityBhubaneswar751030India Department of Electrical Engineering Poornima College of EngineeringJaipur303903India Department of Physics Indian Institute of Technology-GuwahatiAssam781039India Robotics and Mechatronics Research Center Daegu Gyeongbuk Institute of Science and Technology(DGIST)Daegu42988South Korea

Lead-free piezoelectric ceramic is a promising material for energy harvesters,as they have superior electromechanical,ferroelectric,and piezoelectric *** addition,piezoelectric ceramics can be blended with polymer to achieve high-flexibility polymer-ceramic composites,providing mechanical robustness and *** this context,a new lead-free ferroelectric material,having the chemical formula SrTi_(2)O_(5)(STO),was synthesized using a high-temperature solid-state *** analyses of the structural,morphological,and electrical properties of the synthesized material were *** crystallizes with orthorhombic symmetry and space group of *** frequency and temperature-dependent dielectric parameters were evaluated,and impedance spectroscopy shed light on the charge *** PDMS-STO composites at different mass fraction of the STO were prepared using a solvent casting route,and a corresponding piezoelectric nanogenerator(PENG)was *** electrical output of the different PENG by varying massfractions of STO in PDMS and varying force were *** 15%(in mass)PENG device delivered the highest peak-to-peak voltage,current,and power density of 25 V,92 nA,and 0.64 mW@500 MU,*** biomechanical energy harvesting using the PENG device by daily human motions,bending of the device,and attaching the device to laboratory equipment was *** the PENG device was attached to the human throat region,and snoring signals were recorded.A classification model was designed employing the convolutional neural network(CNN)*** have been laid to differentiate between normal and abnormal snores,which could help the patient with screening and early disease detection,contributing to self-powered healthcare applications.

关键词： Lead-free Ferroelectric Nanogenerator Sleepdisorder

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