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15th IEEE International Conference on Industry Applications, INDUSCON 2023

作者： de Oliveira, Iure Rosa L. de Carvalho, Kevin B. Brandão, Alexandre S. Graduate Program in Computer Science Universidade Federal de Viçosa Viçosa Brazil Electrical Engineering Department Universidade Federal de Viçosa Viçosa Brazil

ISBN: (纸本)9798350314182

Multi-robot systems can provide substantial increase in efficiency and/or flexibility in different scenarios. Applications in various settings have been studied in the literature, such as disaster management, surveillance, object transportation as well as search-and-rescue. A particular case that can highly benefit from the employment of multiple agents is the logistics in a warehouse scenario. This work proposes an multi-agent Q-learning based algorithm with curriculum learning and transfer learning to perform the path planning process. With progressively more complex stages of training as well as knowledge transfer from one stage to another, the algorithm is capable of achieve high success rates. In order to validate the proposed method, simulations were done to compare it to other combinations of the used techniques, as well as using Q-learning only. Scalability tests were also performed. The proposed method achieved up to 94% success rate after training. © 2023 IEEE.

关键词： Curriculum Learning Mobile Robotics Multi-Agent System Reinforcement Learning Transfer Learning

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SensoPatch: A Reconfigurable Haptic Feedback with High-Density Tactile Sensing Glove

SensoPatch: A Reconfigurable Haptic Feedback with High-Densi...

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IEEE biomedical Circuits and Systems (BIOCAS)

作者： Yanisa Angkanapiwat Ariel Slepyan Rebecca J. Greene Nitish Thakor Department of Biomedical Engineering Johns Hopkins University Baltimore MD USA Department of Electrical and Computer Engineering Johns Hopkins University Baltimore MD USA

ISBN: (数字)9798350354959

ISBN: (纸本)9798350354966

Haptic feedback is integral to the improved experience of prosthetic users and the reduction in prosthesis rejection. Unfortunately, existing haptic feedback systems often face challenges that impede their transition to clinical use including lack of intuitive control, reproducibility, and personalized customization. Prior studies have explored various methods to encode tactile information and deliver vibration feedback. However, a comprehensive study comparing performance across different stimulation locations and feedback modalities for wearable devices is absent and there is no robust test platform. This paper proposes an open-source reconfigurable haptic feedback system which features 25 sensors and wireless communication to allow customized number of vibration motors, adjustable motor placement, and programmable encoding of tactile data to change feedback modalities. To demonstrate the potential studies that can be investigated using the proposed system, we conducted two preliminary experiments: 1) to assess the vibration discrimination accuracy on three body parts (upper arm, shoulder, and lower back) 2) to evaluate the effect of six methods of mapping tactile data to varying number of motors on object manipulation. This proposed tool utilizes low-cost off-the-shelf components, enabling large-scale comparative studies of feedback modalities and stimulation sites to optimize vibrotactile feedback and facilitate its deployment in upper limb prostheses.

关键词： Vibrations Wireless communication Shoulder Sensor phenomena and characterization Motors Sensor systems Reproducibility of results Haptic interfaces Wearable devices Prosthetics

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Overview of object detection in low light using deep learning and polarimetric three-dimensional integral imaging

Overview of object detection in low light using deep learnin...

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3D Image Acquisition and Display: Technology, Perception and Applications, 3D 2022

作者： Usmani, Kashif O’Connor, Timothy Krishnan, Gokul Javidi, Bahram Electrical and Computer Engineering Department University of Connecticut 371 Fairfield Road StorrsCT06269 United States Biomedical Engineering Department University of Connecticut StorrsCT06269 United States

We overview the previously published work for object detection in low light and occlusion using deep learning and polarimetric 3D integral imaging. 3D polarimetric integral imaging outperformed in object detection and... 详细信息

ISBN: (纸本)9781957171098

关键词： Object detection

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Unraveling Emotional Dynamics in Conversations with Swarm Decomposition, Affect Dynamics, and Machine Learning

Unraveling Emotional Dynamics in Conversations with Swarm De...

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Mediterranean Electrotechnical Conference (MELECON)

作者： Ghada Alhussein Shiza Saleem Leontios J. Hadjileontiadis Department of Biomedical Engineering Khalifa University of Science and Technology Abu Dhabi UAE Department of Electrical & Computer Engineering Aristotle University of Thessaloniki Thessaloniki Greece

ISBN: (数字)9798350387025

ISBN: (纸本)9798350387032

Conversational Emotional Climate Recognition (CERC) endeavors to uncover the subtle emotional undercurrents inherent in spoken interactions, offering profound insights into the intricate fabric of social dynamics. This paper introduces MLSwarm, an innovative CERC method that seamlessly integrates machine learning and swarm decomposition (SWD). MLSwarm meticulously applies swarm decomposition to audio signals, extracting components, and subsequently derives Mel-frequency cepstral coefficients (MFCC) from these components, yielding nine distinctive features. Evaluated in two configurations, MLSwarm attains noteworthy accuracy: 76.7A/65.3V and 79.2A/73.6V. While SWD empowers ML-Swarm to unlock intricate patterns within audio signals, it’s the integration of affect dynamics (AD) that truly elevates its performance. This potent combination not only amplifies MLSwarm’s accuracy in deciphering emotional tones but also grants deep insights into the delicate emotional dynamics underlying social interactions. The findings emphasize MLSwarm’s effectiveness in capturing the emotional tone of conversations between peers, enriching our comprehension of the emotional dynamics at play in social interactions.

关键词： Emotion recognition Accuracy Diversity reception Signal processing Feature extraction Chatbots Real-time systems

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Multi-view DBT Grid-Attention Detection Framework

Multi-view DBT Grid-Attention Detection Framework

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Medical Imaging 2023: computer-Aided Diagnosis

作者： Liu, Xuan Ren, Yinhao Liang, Zisheng Grimm, Lars J. Ge, Jun Lo, Joseph Y. Department of Electrical and Computer Engineering Duke University DurhamNC United States Department of Biomedical Engineering Duke University DurhamNC United States Department of Radiology Duke University School of Medicine DurhamNC United States iCAD Inc. NashuaNH United States

ISBN: (纸本)9781510660359

Most of the existing CAD frameworks for digital breast tomosynthesis (DBT) are single-view only, while radiologists typically utilize information from multiple screening views to better detect breast cancer lesions. Previously, we developed the Retina-Match framework for lesion detection that performed ipsilateral matching between CC and MLO views of the same breast. In this work, we improve that framework in both sampling strategy and feature extraction processes. We proposed a "hard negative" sampling strategy to train on more difficult ipsilateral lesion pairs to increase the robustness of the matching model. We introduced a grid-attention (GA) module to apply spatial attention mechanism for ipsilateral patch similarity learning. A screening DBT dataset with 4182 cases including 1498 (36%) cancers were used for training and testing. Case specificity improved by 15% at 96% sensitivity and average False Positive numbers per detection image (FPPI) decreased from 0.6 to 0.5 at 95% case sensitivity. These experiments indicated that proper ipsilateral matching result is the key to improve performance of multi-view lesion detection framework. © 2023 SPIE.

关键词： Diseases

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ADMM-SRNet: Alternating Direction Method of Multipliers Based Sparse Representation Network for One-Class Classification

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IEEE Transactions on Image Processing 2023年 32卷 2843-2856页

作者： Chiou, Chien-Yu Lee, Kuang-Ting Huang, Chun-Rong Chung, Pau-Choo National Cheng Kung University Department of Electrical Engineering Tainan 701 Taiwan National Chung Hsing University Department of Computer Science and Engineering Taichung 402 Taiwan National Cheng Kung University Cross College Elite Program and Academy of Innovative Semiconductor and Sustainable Manufacturing Tainan 701 Taiwan

One-class classification aims to learn one-class models from only in-class training samples. Because of lacking out-of-class samples during training, most conventional deep learning based methods suffer from the feature collapse problem. In contrast, contrastive learning based methods can learn features from only in-class samples but are hard to be end-to-end trained with one-class models. To address the aforementioned problems, we propose alternating direction method of multipliers based sparse representation network (ADMM-SRNet). ADMM-SRNet contains the heterogeneous contrastive feature (HCF) network and the sparse dictionary (SD) network. The HCF network learns in-class heterogeneous contrastive features by using contrastive learning with heterogeneous augmentations. Then, the SD network models the distributions of the in-class training samples by using dictionaries computed based on ADMM. By coupling the HCF network, SD network and the proposed loss functions, our method can effectively learn discriminative features and one-class models of the in-class training samples in an end-to-end trainable manner. Experimental results show that the proposed method outperforms state-of-the-art methods on CIFAR-10, CIFAR-100 and ImageNet-30 datasets under one-class classification settings. Code is available at https://***/nchucvml/ADMM-SRNet. © 1992-2012 IEEE.

关键词： contrastive learning deep learning dictionary learning One-class classification sparse representation

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A Robust Finite Time Longitudinal Speed Control for a Catenary-based Electric Vehicle

A Robust Finite Time Longitudinal Speed Control for a Catena...

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IEEE Conference on Decision and Control

作者： Gianmario Rinaldi Antonella Ferrara Prathyush P Menon Department of Engineering Faculty of Environment Science and Economy University of Exeter United Kingdom Department of Electrical Computer and Biomedical Engineering University of Pavia Pavia Italy

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

The electrification of the transportation sector plays a crucial role in reducing the global carbon footprint. Among the various solutions, catenary-based electric vehicles have attracted a great deal of interest from researchers and practitioners. This article considers a vehicle powered by a battery energy storage system (BESS) and a catenary system and proposes a robust finite-time longitudinal speed control strategy. Drawing inspiration from the Second-Order Sliding Mode (2-SOSM) methodology, the approach ensures that the control input remains within the limits set by the maximum torque of the motor. The strategy demonstrates robustness against uncertainties and disturbances, eliminating the need to know the model parameters. The simulation case study considers the effects of real road data, including slope variations, on power management. A comparative analysis with the conventional Proportional Integral (PI) method highlights the superior performance of the proposed strategy.

关键词： Uncertainty Torque Roads Power system management Velocity control Transportation Electric vehicles Motors Robustness Regulation

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Finding a Natural Fit: A Thematic Analysis of Amputees' Prosthesis Setting Preferences during User-Guided Auto-Tuning 67th

Finding a Natural Fit: A Thematic Analysis of Amputees' Pros...

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67th International Annual Meeting of the Human Factors and Ergonomics Society, HFES 2023

作者： Yuan, Jing Bai, Xiaolu Alili, Abbas Liu, Ming Feng, Jing Huang, He Department of Psychology North Carolina State University NC United States Department of Electrical and Computer Engineering North Carolina State University NC United States Joint Department of Biomedical Engineering North Carolina State University University of North Carolina-Chapel Hill NC United States

Amputees’ preferences for prosthesis settings are critical not only for their psychological well-being but also for long-term adherence to device adoption and health. Although active lower-limb prostheses can provide enhanced functionality than passive devices, little is known about the mechanism of preferences for settings in active devices. Therefore, a think-aloud study was conducted on three amputees to unravel their preferences for a powered robotic knee prosthesis during userguided auto-tuning. The inductive thematic analysis revealed that amputee patients were more likely to use their own passive device rather than the intact leg as the reference for the natural walking that they were looking for in the powered device. There were large individual differences in factors influencing naturalness. The mental optimization of preference decisions was mostly based on the noticeableness of the differences between knee profiles. The implications on future design and research in active prostheses were discussed. © 2023 Human Factors and Ergonomics Society

关键词： Ergonomics

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CAE Optimization of Synchronous Reluctance Motor and Vibro-Acoustic Analysis for Lift Systems 11

CAE Optimization of Synchronous Reluctance Motor and Vibro-A...

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11th International Conference on Electromechanical and Energy Systems, SIELMEN 2021

作者： Bassi, Ezio Vercesi, Francesco Benzi, Francesco University of Pavia Department of Electrical Computer and Biomedical Engineering Pavia Italy

ISBN: (纸本)9781665400787

The aim of this study is to evaluate the potential of Synchronous Reluctance Motors for lift systems, by also considering the vibro-acoustic behaviour of the motor. Two types of synchronous machines are here designed, analysed and compared with an equivalent induction motor, which is the more common solution in such gearbox applications. The machine performance are further improved with optimization procedures based on a Multiobjectives Optimization Genetic Algorithm (MOGA). The difference between the two types of synchronous motors consists in the rotor geometry: a symmetric and an asymmetric rotor design were investigated. The evaluation of the vibro-acoustic performance has been conducted with a multi-variable model and finite element software taking into account electromagnetic, mechanical and thermal features of the motor, therefore carrying out a multi-physics analysis of the electrical machine. © 2021 IEEE.

关键词： Genetic algorithms

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Biological Influence of Low-Frequency Electromagnetic Field Exposition Based on Selected Cell Death Markers 15

Biological Influence of Low-Frequency Electromagnetic Field ...

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15th International Conference Elektro, ELEKTRO 2024

作者： Cichorowski, Robert Kocikowska, Olga Bajtos, Marek Radil, Roman Janousek, Ladislav De Carrillo, Daria Gendosz Student, Sebastian Silesian University of Technology Faculty of Automatic Control Electronics and Computer Science Gliwice Poland Faculty of Automatic Control Electronics and Computer Science Department of Engineering and Systems Biology Gliwice Poland Silesian University of Medicine Faculty of Medical Sciences Department of Physiology Katowice Poland Faculty of Electrical Engineering and Informational Technology Department of Electromagnetic and Biomedical Engineering Žilina Slovakia Silesian University of Medicine Faculty of Medical Sciences in Zabrze Department of Histology Zabrze Poland Silesian University of Technology Biotechnology Center Gliwice Poland

ISBN: (纸本)9798350372359

This work presents the results of the examination of the HeLa cell line exposure on the ELF-EMF (extremely low-frequency electromagnetic field). In particular, the relationship between ELF-EMF exposition time and cell death. The examination of cell death hallmarks were examined by estimation levels of selected proteins - FACL4 (a protein that is a part of the ferroptosis pathway) and CK18 (Cytokeratin related to necrosis and apoptosis pathways) in the proposed model of workers exposed to ELF-EMF week. © 2024 IEEE.

关键词： Electromagnetic fields

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