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IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives (SDEMPED)

作者： Lorenzo Mantione Vanesa Fernandez-Cavero Daniel Morinigo-Sotelo Lucia Frosini Department of Electrical Computer and Biomedical Engineering University of Pavia Pavia Italy Department of Electrical Engineering School of Industrial Engineering Universidad de Valladolid Valladolid Spain GIR ADIRE-HSP Digital Institute of Advanced Production Technologies (ITAP) Universidad de Valladolid Valladolid Spain

In this paper, an analysis to detect broken rotor bars while the motor is operating in closed loop control is presented. Due to changes in the supply frequency, which occur to keep the speed constant, a time-frequency technique is required even when the transient is completed. Signals from the phase current of the induction motor are analysed using traditional methods such as the Fast Fourier Transform and the Short Time Fourier Transform. Finally, the same signals are analysed through the Dragon Transform, that ensures high resolution frequency and time and allows to detect trajectories of the harmonics with different load conditions.

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Design Optimization and Data-driven Shallow Learning for Dynamic Modeling of a Smart Segmented Electroadhesive Clutch

Design Optimization and Data-driven Shallow Learning for Dyn...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Navid Feizi Zahra Bahrami S. Farokh Atashzar Mehrdad R. Kermani Rajni V. Patel Canadian Surgical Technologies and Advanced Robotics (CSTAR) Lawson Health Research Institute London ON Canada School of Biomedical Engineering Western University London ON Canada Institute of Geography University of Erlangen-Nuremberg Erlangen Germany Department of Mechanical and Aerospace Engineering the Department of Electrical and Computer Engineering and the Department of Biomedical Engineering New York University (NYU) New York NY USA NYU WIRELESS and NYU CUSP Department of Electrical and Computer Engineering Western University London ON Canada Department of Electrical and Computer Engineering the Department of Surgery and the Department of Clinical Neurological Sciences School of Biomedical Engineering Western University London ON Canada

Electroadhesive clutches have attracted a great deal of interest in the last decade as semi-active actuators for human-robot interaction due to their lightweight, low power consumption, and tunable high-torque output capability. However, because of the complexity of their dynamics, in most cases, they are utilized in an ON/OFF -control strategy. In this regard, the non-autonomous (time-dependent) degradation of electroadhesive behavior is an inherent challenge that injects unpredictability and uncertainty into the behavior of this family of semi-active clutches. We propose a novel approach to preventing degradation of electroadhesion using a segmented electrode design that modulates the electrical field on the dielectric surface while using a direct current signal and securing low power consumption. This paper, for the first time, presents an optimization process based on a novel analytic model of the proposed actuator. It also develops a data-driven model augmentation using a hybrid shallow learning approach composed of a long short-term memory (LSTM) architecture which is combined with the analytical model. The performance of the proposed semi-active clutch and the data-driven hybrid model is experimentally validated in this paper.

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Review of Nodule Mineral Image Segmentation Algorithms for Deep-Sea Mineral Resource Assessment

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computers, Materials & Continua 2022年第10期73卷 1649-1669页

作者： Wei Song Lihui Dong Xiaobing Zhao Jianxin Xia Tongmu Liu Yuxi Shi School of Information and Engineering Minzu University of ChinaBeijing100081China Key Laboratory of Marine Environmental Survey Technology and Application Ministry of Natural ResourceGuangzhou510300China National Language Resource Monitoring&Research Center of Minority Languages Minzu University of ChinaBeijing100081China School of Ocean Science China University of GeosciencesBeijing100191China Department of Buoy Engineering South China Sea Marine Survey and Technology Center of State Oceanic AdministrationGuangzhou510310China Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewarkNJ07102USA

A large number of nodule minerals exist in the deep *** on the factors of difficulty in shooting,high economic cost and high accuracy of resource assessment,large-scale planned commercial mining has not yet been *** experimental mining has been carried out in areas with high mineral density and obvious benefits after mineral resource *** an efficient method for deep-sea mineral resource assessment,the deep towing system is equipped with a visual system for mineral resource analysis using collected images and videos,which has become a key component of resource ***,high accuracy in deep-sea mineral image segmentation is the primary goal of the segmentation *** this paper,the existing deep-sea nodule mineral image segmentation algorithms are studied in depth and divided into traditional and deep learning-based segmentation methods,and the advantages and disadvantages of each are compared and *** deep learning methods show great advantages in deep-sea mineral image segmentation,and there is a great improvement in segmentation accuracy and efficiency compared with the traditional ***,the mineral image dataset and segmentation evaluation metrics are ***,possible future research topics and improvement measures are discussed for the reference of other researchers.

关键词： Polymetallic nodule deep-sea mining image segmentation deep learning

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Development of a UAV-based System for Technical Diagnostics of Overhead Power Lines 24

Development of a UAV-based System for Technical Diagnostics ...

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24th International Conference on Computational Problems of electrical engineering, CPEE 2023

作者： Kozlovskyi, Oleksandr Trushakov, Dmitro Rendzinyak, Serhiy Korud, Vasyl Central Ukrainian National Technical University Department of Electrical Systems and Energy Management Kropyvnytskyi Ukraine Central Ukrainian National Technical University Department of Automation and Control in Technical Systems Kropyvnytskyi Ukraine Ivan Franko National University of Lviv Faculty of Electronics and Computer Technologies Lviv Ukraine Lviv Polytechnic National University Institute of Power Engineering and Control System Lviv Ukraine

ISBN: (纸本)9798350330342

The problems associated with the operation of overhead power lines and ways of improving control over their condition with the help of UAVs are considered. A structural diagram of the system of technical diagnostics of overhead lines based on UAVs was developed, for which the necessary diagnostic parameters were selected according to informative criteria. An analysis of types of UAVs was carried out in order to determine their suitability and efficiency of use for diagnosing the condition of overhead lines. © 2023 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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RobotIQ: Empowering Mobile Robots with Human-Level Planning for Real-World Execution

arXiv

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arXiv 2025年

作者： Raptis, Emmanuel K. Kapoutsis, Athanasios Ch. Kosmatopoulos, Elias B. Department of Electrical and Computer Engineering Democritus University of Thrace Kimmeria Campus Xanthi67100 Greece Information Technologies Institute The Centre for Research & Technology Hellas 6th km Harilaou - Thermis Thessaloniki57001 Greece

This paper introduces RobotIQ, a framework that empowers mobile robots with human-level planning capabilities, enabling seamless communication via natural language instructions through any Large language Model. The proposed framework is designed in the ROS architecture and aims to bridge the gap between humans and robots, enabling robots to comprehend and execute user-expressed text or voice commands. Our research encompasses a wide spectrum of robotic tasks, ranging from fundamental logical, mathematical, and learning reasoning for transferring knowledge in domains like navigation, manipulation, and object localization, enabling the application of learned behaviors from simulated environments to real-world operations. All encapsulated within a modular crafted robot library suite of API-wise control functions, RobotIQ offers a fully functional AI-ROS-based toolset that allows researchers to design and develop their own robotic actions tailored to specific applications and robot configurations. The effectiveness of the proposed system was tested and validated both in simulated and real-world experiments focusing on a home service scenario that included an assistive application designed for elderly people. RobotIQ with an open-source, easy-to-use, and adaptable robotic library suite for any robot can be found at https://***/emmarapt/RobotIQ. © 2025, CC BY-NC-SA.

关键词： Robot programming

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DOMINO++: Domain-Aware Loss Regularization for Deep Learning Generalizability 26th

DOMINO++: Domain-Aware Loss Regularization for Deep Learning...

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26th International Conference on Medical Image Computing and computer-Assisted Intervention, MICCAI 2023

作者： Stolte, Skylar E. Volle, Kyle Indahlastari, Aprinda Albizu, Alejandro Woods, Adam J. Brink, Kevin Hale, Matthew Fang, Ruogu Gainesville United States Torch Technologies LLC ShalimarFL United States Center for Cognitive Aging and Memory McKnight Brain Institute UF Gainesville United States Department of Clinical and Health Psychology College of Public Health and Health Professions UF Gainesville United States Department of Neuroscience College of Medicine UF Gainesville United States United States Air Force Research Laboratory Eglin Air Force Base ValparaisoFL United States Department of Electrical and Computer Engineering Herbert Wertheim College of Engineering UF Gainesville United States Department of Computer Information and Science and Engineering Herbert Wertheim College of Engineering UF Gainesville United States Department of Mechanical and Aerospace Engineering Herbert Wertheim College of Engineering UF Gainesville United States

ISBN: (纸本)9783031439001

Out-of-distribution (OOD) generalization poses a serious challenge for modern deep learning (DL). OOD data consists of test data that is significantly different from the model’s training data. DL models that perform well on in-domain test data could struggle on OOD data. Overcoming this discrepancy is essential to the reliable deployment of DL. Proper model calibration decreases the number of spurious connections that are made between model features and class outputs. Hence, calibrated DL can improve OOD generalization by only learning features that are truly indicative of the respective classes. Previous work proposed domain-aware model calibration (DOMINO) to improve DL calibration, but it lacks designs for model generalizability to OOD data. In this work, we propose DOMINO++, a dual-guidance and dynamic domain-aware loss regularization focused on OOD generalizability. DOMINO++ integrates expert-guided and data-guided knowledge in its regularization. Unlike DOMINO which imposed a fixed scaling and regularization rate, DOMINO++ designs a dynamic scaling factor and an adaptive regularization rate. Comprehensive evaluations compare DOMINO++ with DOMINO and the baseline model for head tissue segmentation from magnetic resonance images (MRIs) on OOD data. The OOD data consists of synthetic noisy and rotated datasets, as well as real data using a different MRI scanner from a separate site. DOMINO++’s superior performance demonstrates its potential to improve the trustworthy deployment of DL on real clinical data. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Magnetic resonance

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A 28nm Fully Integrated End-to-End Genome Analysis Accelerator for Next-Generation Sequencing

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IEEE Transactions on Biomedical Circuits and Systems 2025年 PP卷 PP页

作者： Wu, Yi-Chung Chen, Yen-Lung Yang, Chung-Hsuan Lee, Chao-Hsi Chen, Wen-Ching Lin, Liang-Yi Chang, Nian-Shyang Lin, Chun-Pin Chen, Chi-Shi Hung, Jui-Hung National Taiwan University Graduate Institute of Electronics Engineering Taipei Taiwan National Yang Ming Chiao Tung University Institute of Electronics Taiwan GeneASIC Technologies Corporation Hsinchu30288 Taiwan Taiwan Semiconductor Research Institute Hsinchu300091 Taiwan National Yang Ming Chiao Tung University Department of Computer Science Hsinchu30010 Taiwan National Taiwan University Department of Electrical Engineering Graduate Institute of Electronics Engineering Taipei10617 Taiwan

This paper presents the first end-to-end next-generation sequencing (NGS) data analysis accelerator for short-read mapping, haplotype calling, variant calling, and genotyping. It supports both single-end and paired-end short-reads (or reads) and uses the FM-index, a compact index data structure, for exact-match in short-read mapping. For inexact match part of short-read mapping, a dynamic programming array is proposed to determine the mapping results. To reduce the workload of short-read mapping, a rapid similarity calculation is designed. A rescue technique is also adopted to increase the overall sensitivity. In haplotype calling, a parallel k-mer processing engine can construct the de Bruijn graph and assemble the haplotypes. The variant calling step determines variants between a subject and a reference genome sequence with a variant discovery engine. Lastly, genotype likelihood is computed in parallel by a genotype likelihood computing engine, which outputs genotypes of all discovered variants and corresponding Phred-scaled likelihood (PL) values. This work completes end-to-end data analysis for the 50× PrecisionFDA dataset in an average of 28.2 minutes. It achieves a 3-to-59× higher throughput than the existing solutions with higher precision (99.79%) and sensitivity (99.03%). The chip also achieves a 935× higher energy efficiency than the Illumina DRAGEN FPGA acceleration system. © 2007-2012 IEEE.

关键词： Application specific integrated circuits

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Improving Reliability of Magnetic Localization Using Input Space Transformation

TechRxiv

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TechRxiv 2023年

作者： Yaldiz, Cem O. Sebkhi, Nordine Bhavsar, Arpan Wang, Jun Inan, Omer T. The School of Electrical and Computer Engineering Georgia Institute of Technology AtlantaGA30308 United States The Department of Speech Language and Hearing Sciences The Department of Neurology The University of Texas at Austin AustinTX78712 United States

Body motion tracking for medical applications has the potential to improve quality of life for people with physical or speech motor disorders. Current solutions available in the market are either inaccurate, not affordable, or are impractical for a medical setting or at home. Magnetic localization can address these issues due to its high accuracy, simplicity of use, wearability, and use of inexpensive sensors such as magnetometers. The problem is that sources of unreliability affect magnetometers to such an extent that the localization model trained in a controlled environment might exhibit poor tracking accuracy when deployed to end users. These sources of unreliability can be attenuated with magnetic calibration but traditional methods, such as ellipsoid fit (EF), are not sufficient to reach a positional accuracy that is both consistent and satisfactory for our target applications. To improve reliability, we developed a calibration method called post-deployment input space transformation (PDIST) that reduces the distribution shift in the magnetic measurements between model training and deployment. In this paper, we focused on change in magnetization and differences in measurement between magnetometers as sources of unreliability. Our results show that PDIST performs better than EF in decreasing positional errors by a factor of ∼3 when magnetization is distorted, and up to ∼7 when our localization model is tested on a different magnetometer than the one it was trained with. Furthermore, PDIST is shown to perform reliably by providing consistent results across all our data collection that tested various combinations of the sources of unreliability. © 2023, CC BY-NC-SA.

关键词： Magnetization

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Reversed orbital rotation of dielectric particles induced by coupled-dipoles in focused Gaussian beams

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Optics Express 2025年第12期33卷 25888-25899页

作者： Lei-Ming Zhou Zong-Qiang Tao Ning-Jun Xiong Wan Sun Chan Huang Xiao-Yun Jiang Hai-Yang Huang Yu-Zhi Shi Jun Chen Zhili Wang Qiwen Zhan Ji-Gang Hu Department of Optical Engineering School of Physics Hefei University of Technology Hefei Anhui 230601 China hcrqqi@*** Institute of Precision Optical Engineering School of Physics Science and Engineering Tongji University Shanghai 200092 China State Key Laboratory of Quantum Optics Technologies and Devices Institute of Theoretical Physics Shanxi University Taiyuan 030006 China School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai 200093 China

As an important application of optical manipulation, orbital rotation of nanoparticles in optical beams can find uses in constructing micro-motors/micro-machines and the measurement of physical quantity. Here, we report an intriguing orbital rotation of nanoparticles in focused circularly-polarized Gaussian beams at the wavelength scale. Through the transverse scattering forces, off-axis trapping of nanoparticles becomes possible in the off-focal plane, allowing us to create a rotation orbit with a small radius. During the focusing of the incident circularly-polarized Gaussian beam, the spin angular momentum is converted to the orbital angular momentum that drives the particle’s orbital rotation. While gold nanoparticles always show rotation direction that is identical with that of the angular energy flux density under the dipole approximation, high-refractive index silicon nanoparticles can exhibit an opposite rotation direction. This directional inversion is due to the coupling between induced electric and magnetic dipoles in the dielectric particles. By adjusting the particle size and the position of the off-focus plane, the rotation radius and speed can be tuned. This microscale orbital rotation scheme here may advance the development of micro-motor/micro-machines and the investigation of micro-rheology. Our theoretical analysis also sheds what we believe to be new light to the particle dynamics in optical tweezers.

关键词： Gaussian beams Light beams Optical activity Optical manipulation Optical tweezers Surface plasmon resonance

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Evaluation of the Improvement in Hierarchical Lossless Video Compression

Evaluation of the Improvement in Hierarchical Lossless Video...

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International Conference on Control, Decision and Information technologies (CoDIT)

作者： Donia Ammous Amina Kessentini Naziha Khlif Fahmi Kammoun Nouri Masmoudi Electrical engineering Department Laboratory of Electronics and Information Technologies National Engineering School of Sfax Sfax University Sfax Tunisia Electronics and telecommunications department Higher Institute of Computer and Multimedia of Gabes Gabes university Gabes Tunisia

The digital medical video is widely used in several healthcare institutions and medical centers. Therefore, a considerable storage space and a high transmission bandwidth are necessary. Thus, efficient compression tools are required to reduce the storage space and fit bandwidth capacities. Indeed, several lossy and lossless compression techniques are applied. Lossy techniques ensure a good performance. But they lead to erroneous medical data, which can negatively affect the doctor's decisions about the patient's health conditions. As a result, lossless compression guarantees an optimal solution for medical applications. Among available lossless techniques, H.264/AVC (Advanced Video Coding) presents high coding performance in lossless compression. H.264/AVC was chosen since it simplicity in terms of computational complexity. It is suitable for mobile devices that require high resolution. In this paper, several techniques used with the H.264/AVC are discussed. Moreover, a new approach is applied to enhance the lossless techniques. Its results show an important compression ratio compared to the previous works. The enhanced method results in an increase in compression ratio from 8,429 to 16,159. Besides, the gain performance reaches from 32,625 to 42.074 %.

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