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Network-Based Rail Running Band Anomaly Recognition via Recurrent Attention Graphs

IEEE Transactions on Automation science and engineering 2025年 22卷 15381-15395页

作者： Ni, Xuefeng Fieguth, Paul W. Ma, Ziji Shi, Bo Liu, Hongli Hunan University College of Electrical and Information Engineering Changsha410012 China University of Waterloo Department of Systems Design Engineering WaterlooONN2L 3G1 Canada The Hong Kong University of Science and Technology Department of Computer Science and Engineering Sai Kung Hong Kong

Anomaly detection for rail running bands, the pattern of wheel-rail contact area, is crucial to analyze composite rail irregularities. This paper presents an all-weather vision-based solution for running-band inspection. However, two major algorithmic challenges restrict inspection effectiveness: 1) the identification of high-quality features for diversified and imbalanced data subject to noise and outliers, and 2) inferring implicit anomaly co-occurrence patterns. We regard overall running-band anomaly detection as a multi-label classification problem and develop a novel deep multi-anomaly recognition network via recurrent attention graphs (RAGRN). © 2004-2012 IEEE.

关键词： Network theory (graphs)

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Performance Analysis of 3D Stacked Memory Architectures in High Performance Computing 4

Performance Analysis of 3D Stacked Memory Architectures in H...

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4th IEEE International Conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2024

作者： Gannavaram, Venkat Tulasi Krishna Gajula, Arun Kumar Arizona State University School of Electrical Computer and Energy Engineering Tempe United States Kakatiya Institute of Technology and Science Department of Electronics and Communication Engineering Warangal India

ISBN: (纸本)9798350360165

The increasing speed of the CPU is greater than that of the RAM. The 'Memory Wall' issue, which occurs when the processor runs out of data, could occur. The I/O infrastructure is strained as the number of cores in CMPs rises because more data is needed from the memory subsystem. Memory bandwidth becomes a bottleneck in terms of performance. By layering memories on top of logic, three-dimensional integrated circuits are proposed as a solution to this problem. The widely-used compute-in-memory benchmark framework 'NeuroSim' is utilized by us to investigate the benefits of a three-dimensional design for a Neural Network application. © 2024 IEEE.

关键词： Memory architecture

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An End-to-End Concatenated CNN Attention Model for the Classification of Lung Cancer with XAI Techniques

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IEEE Access 2025年 13卷 96317-96336页

作者： Haque, Fariha Hasan, Mohammad Asif Siddique, Md Abu Ismail Roy, Tonmoy Shaha, Tonmoy Kanti Islam, Yamina Paul, Avijit Chowdhury, Muhammad E. H. Rajshahi University of Engineering & Technology Department of Electronics & Telecommunication Engineering Rajshahi Bangladesh 797-1000 United States Chittagong University of Engineering Technology Electrical Electronic Engineering Bangladesh International Islamic University Chittagong Department of Computer Science & Engineering Chittagong4318 Bangladesh Qatar University Department of Electrical Engineering Doha2713 Qatar

In the field of medical imaging, deep learning (DL) techniques have made significant contributions to the detection and classification of various cancers. Identifying the precise regions in medical images containing cancerous cells plays a crucial role in the diagnostic process. Early and accurate cancer detection is essential for effective treatment and improved patient outcomes. However, manual diagnosis is labor-intensive, requiring the specialized expertise of radiologists, and the increasing number of cancer cases presents challenges in processing large volumes of image data efficiently. To address these challenges, an end-to-end concatenated Convolutional Neural Network (CNN) attention model has been proposed for automatic lung cancer classification. This approach integrates two distinct CNNs, followed by a multi-layer perceptron (MLP) and a multi-head attention (MHA) mechanism, to enhance performance. The model leverages explainable AI techniques, such as gradient-weighted class activation mapping (grad-CAM) and Shapley additive explanations (SHAP), to highlight critical regions within the images that influence the decision-making process. This model achieves impressive performance, with an accuracy of 99.54%, precision of 99.31%, recall of 99.95%, F1-score of 99.66%, and an AUC of 99.97%. These results demonstrate that Thisapproach not only surpasses existing methods but also provides a highly accurate and interpretable solution. By reducing the need for extensive manual intervention, this model enables faster and more reliable lung cancer diagnosis, paving the way for timely and effective treatments. © 2013 IEEE.

关键词： Convolutional neural networks

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Medical ChatBot Assistance for Primary Clinical Guidance using Machine Learning Techniques 5

Medical ChatBot Assistance for Primary Clinical Guidance usi...

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5th International Conference on Innovative Data Communication Technologies and Application, ICIDCA 2024

作者： Sreedhar Kumar, S. Ahmed, Syed Thouheed Fathima, Afifa Salsabil Nishabai, M. Sophia, S. KGF Karnataka 563120 India Deaprtment of Electrical Engineering Indian Institute of Technology Telangana Hyderabad India School of Computer Science and Engineering REVA University Bengaluru India

Hospitals serve as critical hubs for global healthcare, offering essential medical services. However, a pressing issue is the lack of 24/7 medical facilities in rural areas, particularly during the overnight hours. To bridge this gap, we propose the Robotic Medical Support ChatBot (RMSCB) system. This innovative online platform leverages machine learning to autonomously predict medical diagnoses and provide temporary solutions, accessible at any time. The RMSCB system comprises three key stages: pre-processing, training, and classification. In the pre-processing stage, relevant keywords are extracted using the Pre-Fixed Stopping Words Model (PFSWM). The training stage categorizes pre-processed questions into classes based on the Pre-Fixed Class Label Model (PFCLM), associating medical solutions via the Pre-Fixed Answer and Question Model (PFAQM). In the classification stage, the RMSCB processes clinical questions from patients via mobile or personal systems, mapping and identifying solutions based on probability. Experimental results demonstrate the efficacy of the RMSCB system, offering timely first aid medication information and alleviating the need for immediate physician consultation. This technological solution addresses critical healthcare gaps, especially in regions with limited access to continuous medical services. © 2024 The Authors. Published by Elsevier B.V.

关键词： Machine learning

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A Digital Twin Based Framework for Real-Time Machine Condition Monitoring 19

A Digital Twin Based Framework for Real-Time Machine Conditi...

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

作者： Chen, Zixiao Choudhury, Madhurjya Dev Blincoe, Kelly Dhupia, Jaspreet Singh University of Auckland Department of Mechanical and Mechatronics Engineering New Zealand School of Engineering and Computer Science Victoria University of Wellington New Zealand University of Auckland Department of Electrical Computer and Software Engineering New Zealand

ISBN: (纸本)9798350320695

Condition Monitoring (CM) is an important approach to extending the life of complex equipment by forecasting the outcome of an event before catastrophic failure occurs. Recent advancements in digital twins (DT) offer additional benefits to machine condition monitoring. In this study, a framework based on DT for real-time condition monitoring of industrial machines is proposed. The multi-layer DT framework consists of a physical entity (PE), virtual equipment (VE), edge device, fidelity service and digital twin services. The virtual equipment is a replica of the physical entity or the monitored machine. It also contains a cloud platform to store data online and an application to interface with the cloud enabling users to check the data remotely. The fidelity service ensures conformity between the PE and the VE. The digital service provides optimal operation and maintenance schedules based on the data from both physical and virtual spaces. The integration of the edge layer enables real-time handling of high-frequency machine data for effective health monitoring. The validity of the proposed framework is demonstrated with a case study based on monitoring a critical component of an industrial drivetrain test rig. The features of the framework allow end-users to visualize the component's real-time health status remotely. © 2023 IEEE.

关键词： Condition monitoring

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Design of Frequency Domain Metric for Evaluation of Mode Decomposition Algorithms

Design of Frequency Domain Metric for Evaluation of Mode Dec...

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2023 IEEE International Conference on Device Intelligence, Computing and Communication Technologies, DICCT 2023

作者： Navalyal, Geeta Navalyal, Apoorva Naik, Sayali Dept. of Computer Science and Engineering Uttarakhand Dehradun India University of Florida Dept. of Electrical and Computer Engineering GainesvilleFL United States Grant Thornton Karnataka Bengaluru India

ISBN: (纸本)9781665474924

Mode decomposition algorithms have been used extensively to extract and separate signal components from composite signals which constitute the semantic information in it. The individual signal components also called modes should be independent of each other and have some sparsity properties such as having a limited bandwidth and should be compact around a center frequency. However, not all algorithms effectively segregate the constituents truthfully. Different algorithms perform differently for the same input signal. This work proposes a metric to quantify the performance of mode decomposition techniques by leveraging the analogy of having a compact central frequency in the decomposed modes. The proposed method is tested on the widely used mode decomposition algorithms. The results on simulated and real signals show the usefulness of the proposed metric in evaluating mode decomposition algorithms. © 2023 IEEE.

关键词： Mode decomposition

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Renewable energy effects on energy management based on demand response in microgrids environment

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Renewable Energy 2023年第1期213卷 205-217页

作者： Yan, Zhongzhen Zhu, Xinyuan Chang, Yiming Wang, Xianglong Ye, Zhiwei Xu, Zhigang Fars, Ashk School of Computer Science and Technology Hubei University of Technology Hubei Wuhan China Electrical Engineering Department Arian Company Yerevan Armenia

With further penetration of low-carbon energy conversion, microgrids (MGs) have become a necessary tool for expanding the consumption of renewable energies. In this paper, an optimal operation model for a microgrid-based multi-agent system is proposed. The goal is to save the total energy cost, which is expressed as a sum of locally observable convex functions. Therefore, improving the operational efficiency of microgrids is the key to promoting renewable energy development. This paper develops a three-layer multi-agent system model considering energy storage system and power thermal load demand response to solve the energy management problem of microgrids. In order to investigate the effect of energy storage system and demand response in microgrids, this paper designs three simulation cases, namely infrastructure case, energy storage case and demand response case. In order to prove the effectiveness of the proposed method, this paper uses the proposed method to solve three cases and compare the result with other meta-heuristic algorithms. The comparison results show that: (1) the multi-agent system model can realize the joint optimization of "resource, network, load and storage". (2) The introduction of energy storage and demand response system in microgrids can stabilize the output. Renewable energy units promote the use of renewable energy and reduce the overall operating cost of microgrids. Moreover, the results clearly demonstrate that the proposed algorithm has far better performance than other optimization methods. Also, the analysis obtained from the results shows that the cost is reduced by 1.82%. PV and WT output increased by 14.54% and 2.42%. In addition, their standard deviation decreases after ESS participation. The proposed approach is very effective through a simulation case study, which shows high potential for applications. © 2023 Elsevier Ltd

关键词： Demand-side management Energy management Grasshopper search algorithm Microgrid (MG) Optimization

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Automated Exoskeleton Prosthetic Suit With Monitoring System 4

Automated Exoskeleton Prosthetic Suit With Monitoring System

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4th International Conference on Power, Energy, Control and Transmission Systems, ICPECTS 2024

作者： Jeeva, C. Sagar, Lalit Kumar Srivastava, Mudit P. Abinaya, R. Narmatha, M. Shanmuga Priya, M. Sri Sairam Engineering College Department of Electrical and Electronic Engineering Tamil Nadu India Srm Institute of Science and Technology Department of Computer Science Engineering Delhi India Srm Institute of Science and Technology Department of Physics Delhi India

ISBN: (纸本)9798331508845

The Automated Exoskeleton Prosthetic Suit with Monitoring System aims to develop a fully functional prosthetic suit with coordinated strength and response time. The suit is ameliorative and can be worn or removed as needed. Designed as a wearable inner suit, it operates autonomously, incorporating sensors and navigation systems to reduce inequality. In regions where the suit is worn, it analyzes blood flow using ultrasound Doppler principles and aids in improving circulation. The exoskeletons support or replace impaired body parts, allowing users to function properly. electrical motors and precise position control form the core of its most common design. This suit explores the entire body using various actuators, tasks, and degrees of freedom. The product can be worn as an inner suit, featuring an autonomous sensor and navigation system to eliminate inequality. It measures blood flow in the regions covered by the suit, enhancing circulation. The primary goal of the product is to detect even small objects and prevent the wearer from falling. © 2024 IEEE.

关键词： Exoskeleton (Robotics)

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Anapole source based on electric dipole interactions over a low-index dielectric

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Physical Review Applied 2024年第5期21卷 054051-054051页

作者： Muhammad Rizwan Akram Abbas Semnani Department of Electrical Engineering and Computer Science The University of Toledo Toledo OH United States

Pursuing nonradiating sources and radiationless motion for accelerated charged particles has captivated physicists for generations. Nonradiating sources represent intricate current-charge configurations that do not emit radiation beyond their source domain. This study investigates a single nonradiating source comprising a low-index dielectric disk excited by a split-ring resonator. Employing analytical and numerical methods, we demonstrate that this configuration supports an anapole state, exhibiting minimal or no radiation, effectively representing a nonradiating source. The radiation suppression is accomplished through the destructive interference of electric dipoles excited on the metallic and dielectric components of the proposed prototype. Transforming the design into a cost-effective device capable of suppressing radiation, we achieve excellent numerical and experimental agreement, affirming the formation of the anapole state using the lowest-order multipoles. Moreover, the devised anapole device is remarkably compact, constructed from a low-index dielectric, and employs readily available components. As a versatile platform, the proposed device can spearhead anapole research for diverse applications, including sensing, wireless charging, radio frequency identification tags, and other nonlinear applications.

关键词： Cloaking Electric dipole-dipole interactions Optoelectronics Wireless power transfer Dielectrics Optical sources & detectors Split-ring resonators Microwave techniques

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Infant head subsurface imaging using high-density diffuse optical tomography and machine learning 9

Infant head subsurface imaging using high-density diffuse op...

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Diffuse Optical Spectroscopy and Imaging IX 2023

作者： Balasubramaniam, Ganesh M. Manavalan, Gokul Hauptman, Ami Arnon, Shlomi Department of electrical and computer engineering Ben-Gurion University of the Negev Be’er Sheva8441405 Israel Department of computer science Sapir Academic College Sderot7915600 Israel

ISBN: (数字)9781510664661

ISBN: (纸本)9781510664654

Infant head injuries and damage can be caused by various factors such as tumors or physical trauma. The treatment for a head injury will depend on the severity of the damage. Nevertheless, the infant’s head should be imaged before any treatment. High-density diffuse optical tomography (HD-DOT) is a non-invasive imaging technology that can be employed for subsurface imaging of the infant brain. However, there are problems with HD-DOT, such as low resolution, ill-posedness of the inverse problem, and high computational costs. In this study, to improve subsurface imaging of the infant head, an extreme gradient boosting (XGBoost) algorithm is combined with HD-DOT. The proposed method is then used to detect subsurface anomalies in the infant head. The proposed method achieves a similarity index greater than 0.97 in terms of cosine similarity and less than 0.12 in terms of the root mean square error, demonstrating its effectiveness. Moreover, the proposed method requires a minimal dataset compared to conventional deep learning methods and consumes significantly less time to train. The results of this study suggest that the proposed method can provide a promising alternative for subsurface imaging of the infant head, which could significantly impact the medical imaging field in the future. © 2023 SPIE.

关键词： Inverse problems

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