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2024 International Conference on Machine Learning, Pattern Recognition and Automation engineering, MLPRAE 2024

作者： Rao, Jinjun Wang, Cong Liu, Mei Lei, Jingtao Giernacki, Wojciech Department of Precision Mechanical Engineering School of Mechatronic Engineering and Automation Shanghai University China Institute of Robotics and Machine Intelligence Faculty of Automatic Control Robotics and Electrical Engineering Poznan University of Technology Poland

ISBN: (纸本)9798400709876

Aiming at the problem that the combination of self-play (SP) and deep reinforcement learning (DRL) only involves two-party games and the policy learning of each party is limited, a multi-party asymmetric self-play algorithm (MASP) is proposed. Firstly, by improving the ELO scoring system, the ELO scoring takes into account each party of the unmanned surface vehicle (USV) clusters, and the imbalance of the number of USV clusters, so that the frequency of exchanging strategies of all USV clusters in the confrontation process is equal. Secondly, it ensures that USV clusters have a balanced combat ability, and at the same time ensures that the combat ability of all parties is strong and weak and the gap is not too wide. In addition, the parameters are dynamically set to reduce the update frequency of the policy of the stronger party. The experimental results show that the MASP can make the USV clusters learn more effective policies, have a shorter game time, and obtain higher rewards and ELO scores in the simple 2v2 adversarial game scenario and the three-party game scenario of a warship escort mission. © 2024 ACM.

关键词： Deep reinforcement learning

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Stress Detection Using CNN on the WESAD Dataset 4

Stress Detection Using CNN on the WESAD Dataset

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4th International Conference on Emerging Systems and Intelligent Computing, ESIC 2024

作者： Shirley Benita, D. Shamila Ebenezer, A. Susmitha, L. Subathra, M.S.P. Jeba Priya, S. Karunya Institute of Technology and Sciences Department of Computer Science and Engineering Coimbatore India Karunya Institute of Technology and Sciences Departnemt of Robotics Engineering Coimbatore India

ISBN: (纸本)9798350349856

Stress, a pervasive psychological state, profoundly impacts individuals' well-being and may lead to various health issues. In this paper, the WESAD (Wearable Stress and Affect Detection) dataset serves as the primary data source, from which HRV (Heart Rate Variability) data extracted using PPG (Photoplethysmography) sensor is utilized. This data can be obtained in a non-invasive method and is instrumental in this analysis. The dataset comprises HRV data from 15 individual test subjects obtained from PPG sensors, providing a crucial foundation for the detection and classification of individuals into 'stressed' or 'not stressed' categories, thus offering a valuable tool for stress monitoring. This paper is a focused exploration into the CNN (Convolutional Neural Network) Deep Learning model, in which the feature selection process is carried out using Random Forest resulting in the selection of HR (Heart Rate), LF_BOXCOX (Low-Frequency Component - Box-Cox Transformed), MEDIAN_RR (Median of RR Intervals), SDI_BOXCOX (Standard Deviation 1 - Box-Cox Transformed), and SDRR_REL_RR (Standard Deviation of Relative RR Intervals) to optimize the model's performance. The model aims at advancing and refining stress detection methodologies to enhance overall well-being and achieves an accuracy of 98%. © 2024 IEEE.

关键词： Stresses

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Understanding URDF: A Survey Based on User Experience 19

Understanding URDF: A Survey Based on User Experience

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19th IEEE International Conference on Automation Science and engineering, CASE 2023

作者： Tola, Daniella Corke, Peter Aarhus University Department of Electrical and Computer Engineering Aarhus Denmark Centre for Robotics Qut Brisbane Australia

ISBN: (纸本)9798350320695

With the increasing complexity of robot systems, it is necessary to simulate them before deployment. To do this, a model of the robot's kinematics or dynamics is required. One of the most commonly used formats for modeling robots is the Unified Robot Description Format (URDF). The goal of this article is to understand how URDF is currently used, what challenges people face when working with it, and how the community sees the future of URDF. The outcome can potentially be used to guide future research. This article presents the results from a survey based on 510 anonymous responses from robotic developers of different backgrounds and levels of experience. We find that 96.8% of the participants have simulated robots before, and of them 95.5% have used URDF. We identify a number of challenges that complicate the use of URDF, such as the inability to model parallel linkages and closed-chain systems, no real standard, lack of documentation, and a limited number of dynamic parameters to model the robot. Future perspectives for URDF are also determined, where 53.5% believe URDF will be more commonly used in the future, 12.2% believe other standards or tools will make URDF obsolete, and 34.4% are not sure what the future of URDF will be. Most participants agree there is a need for better tools to ensure URDF's future use. © 2023 IEEE.

关键词： Robots

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Intrinsic Entropy: A Novel Adaptive Method for Measuring the Instantaneous Complexity of Time Series

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IEEE Signal Processing Letters 2023年 30卷 160-164页

作者： Huang, Po-Hsun Hsiao, Tzu-Chien Hsinchu300 Taiwan Nycu Department of Computer Science College of Cs and Institute of Biomedical Engineering College of Electrical and Computer Engineering Hsinchu300 Taiwan

The determination of appropriate parameters and an appropriate window size in most entropy-based measurements of time-series complexity is a challenging problem. Inappropriate settings can lead to the loss of intrinsic information within a time series. Therefore, two parameter-free methods, namely the intrinsic entropy (IE) and ensemble IE (eIE) methods, are proposed in this paper. The eIE method requires two parameters, which can be easily determined through an orthogonality test. The proposed approaches can measure instantaneous complexity;thus, they do not require a predetermined window size. White noise and three other varieties of colored noise were used to test the stability of the proposed methods, and five types of synthetic signals and logistic maps were applied for measuring instantaneous complexity and regularity. The results revealed that the IE and eIE methods exhibit satisfactory stability. Both methods provide point-by-point entropy measures for time series. The eIE method is useful for measuring the complexity of frequency and amplitude modulation. Furthermore, the periodicity of time series can be detected using the two proposed methods. © 1994-2012 IEEE.

关键词： Empirical mode decomposition

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DGeC: Dynamically and Globally Enhanced Convolution

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2025年第4期6卷 921-933页

作者： Zhang, Zihang Liu, Yuling Zhou, Zhili Yang, Gaobo Liao, Xin Wu, Q. M. Jonathan Hunan University College of Computer Science and Electronic Engineering Changsha410082 China Guangzhou University Institute of Artificial Intelligence and Blockchain Guangzhou510006 China University of Windsor Department of Electrical and Computer Engineering WindsorON250101 Canada

We explore the reasons for the poorer feature extraction ability of vanilla convolution and discover that there mainly exist three key factors that restrict its representation capability, i.e., regular sampling, static aggregation, and limited receptive field. With the cost of extra parameters and computations, existing approaches merely alleviate part of the limitations. It drives us to seek a more lightweight operator to further improve the extracted image features. Through a closer examination of the convolution process, we discover that it is composed of two distinct interactions: spatial-wise interaction and channel-wise interaction. Based on this discovery, we decouple the convolutional blocks into these two interactions which not only reduces the parameters and computations but also enables a richer ensemble of interactions. Then, we propose the dynamically and globally enhanced convolution (DGeC), which includes several components as follows: a dynamic area perceptor block (DAP) that dynamically samples spatial cues, an adaptive global context block (AGC) that introduces the location-aware global image information, and a channel attention perceptor block (CAP) that merges different channel-wise features. The experiments on ImageNet for image classification and on COCO-2017 for object detection validate the effectiveness of DGeC. As a result, our proposed method consistently improves the performance with fewer parameters and computations. In particular, DGeC achieves a 3.1% improvement in top-1 accuracy on ImageNet dataset compared to ResNet50. Moreover, with Faster RCNN and RetinaNet, our DGeC-ResNet50 also consistently outperforms ResNet and ResNeXt. © 2024 IEEE.

关键词： Convolutional neural networks

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Near-Optimal Scheduling for IC Packaging Operations Considering Processing-Time Variations and Factory Practices

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IEEE robotics and Automation Letters 2024年第4期9卷 3878-3885页

作者： Tsai, Tsung-Han Yan, Bing Luh, Peter B. Yang, Haw-Ching Bragin, Mikhail A. Cheng, Fan-Tien National Cheng Kung University Institute of Manufacturing Information and Systems Tainan701401 Taiwan Rochester Institute of Technology Department of Electrical and Microelectronic Engineering RochesterNY14623 United States University of Connecticut Department of Electrical and Computer Engineering StorrsCT06269 United States National Taiwan University Department of Electrical Engineering Taipei106329 Taiwan National Kaohsiung University of Science and Technology Department of Electrical Engineering Kaohsiung824005 Taiwan University of California Department of Electrical and Computer Engineering RiversideCA92507 United States

Due to the short life cycles of electronic products, trial run lots of new products are crucial in IC packaging for production verification and engineering adjustments. The processing time of trial run lots may differ significantly from production lots due to engineering adjustments and is difficult to predict without sufficient historical data. The purpose of this letter is to develop a framework for near-optimal scheduling of IC packaging considering processing time variations and factory practices. Using an orthogonal greedy algorithm and recurrent neural network, this framework extracts key features and predicts the processing times of trial run lots and production lots for each operation using these algorithms. After formulating the scheduling problem in an integer linear programming form, an ordinal optimization method is embedded within the decomposition and coordination framework to obtain dynamic and near-optimal schedules in a computationally efficient manner. This approach can improve the efficiency of IC packaging and potentially other operations by optimizing lot scheduling, reducing production tardiness, and increasing productivity in the factory, paving the way for self-optimizing factories in the future. © 2016 IEEE.

关键词： Integer programming

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Methods for class-imbalanced learning with support vector machines: a review and an empirical evaluation

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Soft Computing 2024年第20期28卷 11873-11894页

作者： Rezvani, Salim Pourpanah, Farhad Lim, Chee Peng Wu, Q. M. Jonathan Department of Computer Science Ryerson University TorontoON Canada Department of Electrical and Computer Engineering University of Windsor WindsorON Canada Institute for Intelligent Systems Research and Innovation Deakin University GeelongVIC Australia

This paper presents a review on methods for class-imbalanced learning with the Support Vector Machine (SVM) and its variants. We first explain the structure of SVM and its variants and discuss their inefficiency in learning with class-imbalanced data sets. We introduce a hierarchical categorization of SVM-based models with respect to class-imbalanced learning. Specifically, we categorize SVM-based models into re-sampling, algorithmic, and fusion methods, and discuss the principles of the representative models in each category. In addition, we conduct a series of empirical evaluations to compare the performances of various representative SVM-based models in each category using benchmark imbalanced data sets, ranging from low to high imbalanced ratios. Our findings reveal that while algorithmic methods are less time-consuming owing to no data pre-processing requirements, fusion methods, which combine both re-sampling and algorithmic approaches, generally perform the best, but with a higher computational load. A discussion on research gaps and future research directions is provided. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Support vector machines

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A machine learning approach for skin lesion classification on iOS: implementing and optimizing a convolutional transfer learning model with Create ML

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International Journal of computers and Applications 2024年第8期46卷 666-685页

作者： Benedek Szabo, Aron Katona, Jozsef Department of Software Development and Application Institute of Computer Engineering University of Dunaujvaros Dunaujvaros Hungary Department of Instrumentation and Automation Institute of Electronics and Communication Systems Kandó Kálmán Faculty of Electrical Engineering Obuda University Budapest Hungary Department of Informatics GAMF Faculty of Engineering and Computer Science Kecskemét Hungary

The integration of machine learning (ML) into mobile applications presents unique challenges, particularly in resource-constrained environments such as iOS devices. Skin lesion classification is a critical task in dermatology, where accurate and efficient diagnostic tools can significantly aid in early detection of malignant lesions. This study aims to implement a machine learning-based iOS mobile application and develop a binary classification model for skin lesion images to determine whether a lesion is malignant. The research utilized Create ML to develop a convolutional neural network optimized for iOS, employing a transfer learning approach. A logistic regression model was cascaded with the convolutional neural network N to enhance classification accuracy. The model's performance was assessed through various validation metrics, ensuring its robustness and efficiency within the constraints of mobile hardware. A curated dataset from the International Skin Imaging Collaboration archive was used for training and testing. The model achieved an accuracy of 92%, a precision of 90%, a recall of 93%, and an F1-score of 91% in classifying skin lesions. These metrics validate the model's efficacy in identifying malignant lesions. Data curation involved collecting, labeling, and preparing a dataset from publicly available sources, ensuring the inclusion of diagnostically relevant features. The final model was integrated into an iOS application using Core ML and Vision frameworks. The developed application demonstrates reliable performance in classifying skin lesions with high accuracy on iOS devices. The inclusion of comprehensive performance metrics justifies the efficacy of the proposed approach. Future work will explore enhancements in model architecture and object detection capabilities to further improve diagnostic precision and application usability. © 2024 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Image recognition

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Comprehensive analysis of BLDC motor faults in electric vehicle transportation

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International Journal of Power Electronics 2023年第1期18卷 40-64页

作者： Usman, Adil Rajpurohit, Bharat Singh School of Computing and Electrical Engineering Indian Institute of Technology HP Mandi India Electrical and Computer Engineering Department University of California Santa CruzCA United States

The faults prospective are higher for any BLDC motor, driven under a constant and continuous operating period. The possibility of getting susceptible to winding short-circuit faults and rotor demagnetisation effects, is more frequently discerned. The winding insulation breakdown introduces stator inter-turn fault (SITF) conditions in the machine which has consequent detrimental impact on the rotor permanent magnets (PMs). The cumulative effect of fault stimulates rotor demagnetisation, intensifying the effect of faults. This paper aims in classifying the motor faults employed in electric vehicle (EV) transportation. Depending upon the machine’s characteristic performance in terms of electrical signatures like, motor current signature (MCS) and back-EMF (BEMF), and mechanical signatures like frequency and vibration spectrum;a unique classification to fault is provided. The proposed research models investigate the performance of a machine drive under both individual and combined fault conditions, to give a significant outcome to the research findings. The closed loop motor drive operation is performed using an advanced field remodelling (AFR)-based technique which employs fuzzy logic controller (FLC). The developed drive-controller-system minimises the steady state error under motor operating conditions and has a clear discrepancy in terms of machine quantities during faults. Copyright © 2023 Inderscience Enterprises Ltd.

关键词： Numerical methods

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Study of Thin Film Blue-Light MicroLEDs by Laser Lift-Off and Texture Process

IEEE Electron Device Letters

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IEEE Electron Device Letters 2024年第2期45卷 212-215页

作者： Hsu, Yu-Hsuan Wan, Tsung-Chih Lo, Yu-Yun Lin, Xin-Dai Lin, Yi-Hsin Zan, Hsiao-Wen Horng, Ray-Hua National Yang Ming Chiao Tung University College of Electrical and Computer Engineering Department of Photonics Hsinchu30010 Taiwan Institute of Electronics National Yang Ming Chiao Tung University College of Electrical and Computer Engineering Hsinchu30010 Taiwan

In this study, thin-film blue-light micro-light-emitting diodes ( μ LEDs) were successfully fabricated by laser lift-off technique, which had an emission region of only 10μ m× 10μ m. Additionally, a texturing treatment was applied to the top undoped GaN surface. The texturing time was optimized to prevent a total reflective effect and further enhance the light extraction efficiency. As a result, the emission output power (@ 30 mA) and EQEmax of the μ LED textured for 2 minutes exhibited 1.35 times and 1.64 times higher values as compared with those of μ LED with a sapphire substrate, respectively. © 1980-2012 IEEE.

关键词： III-V semiconductors

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