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2024 International Conference on engineering and Computing, ICECT 2024

作者： Ramzan, Aneeqa Mustafa, Rafay Kamran, Yashfa NUTECH Department of Electrical Engineering Islamabad Pakistan GIKI Faculty of Computer Science and Engg. Swabi Topi Pakistan IIUI Department of Electrical and Computer Engineering Pakistan

ISBN: (纸本)9798350349719

Providing adequate clinical and technical aid to blinds and visually impaired persons can be very challenging as it put financial strain on families due to the medical examination, treatment, surgical procedures and assistive devices expenses. The specialists to the mentioned individuals' ratio is low and exposure to ophthalmologists is limited. Either requirement of smartphone applications with need of internet connection or only direction oriented solutions but unable to avoid obstacles are the issues in existing market solutions. This paper proposes a novel technology of smart assistant aid for blind and visually impaired people (SSVIP) by developing a smart shoe prototype with sensors to detect obstacles, wet surfaces and ground vibrations, providing real-Time feedback to the user. If any of these are detected, the controller activates the buzzer and vibration motor, providing both audible alerts based on the detected sensor signal in order to alarm the wearer and tactile feedback respectively. SSVIP is then tested on 20 iterations after configuring and calibrating sensors and getting the optimized 20 units for ultrasonic sensor, 650 threshold for water sensor. Output accuracies of 87%, 80% and 83% for ultrasonic sensor, water sensor and vibration sensor resnectively and resulting overall 83% accuracy was acheived. © 2024 IEEE.

关键词： Ultrasonic sensors

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FAU Hack-a-Thons: An Introduction to Computational and Hardware, Logistical Skills, and Intense Training for Outcomes-Based Learning for Developing Internet of Things Products

FAU Hack-a-Thons: An Introduction to Computational and Hardw...

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2024 ASEE Annual Conference and Exposition

作者： Weinthal, Charles Perry Jaramillo, David Department of Computer & Electrical Engineering & Computer Science Florida Atlantic University Boca RatonFL United States

In preparation for the upcoming FAU Hack-a-Thon, we have implemented extensive support structures to ensure that all participating teams are thoroughly prepared for the competition. This preparation includes the provision of online support from a variety of programming experts from IBM and experienced Hack-a-Thon participants. This support is accessible 24/7 in the three weeks leading up to the event, aimed at ensuring all teams are up to speed and ready to participate. Our proactive approach focuses on encouraging teams to engage deeply with the training materials, consistently reminding them of their capability to successfully compete with adequate preparation. During the event, teams are expected to utilize the skills they have honed in areas such as teamwork, programming, and hardware development to create innovative Internet of Things (IoT) products. The support continues throughout the 24-hour event, with resources readily available to assist teams in overcoming any technical challenges they encounter. This setup aims to simulate real-world problem-solving scenarios that participants are likely to face in their professional careers, thus enhancing their experience and skills in a practical, hands-on manner. The Hack-a-Thon not only focuses on technical skills development but also emphasizes the cultivation of soft skills such as communication, teamwork, and time management. By the end of the event, participants are expected to present their projects to a panel of industry experts and faculty, demonstrating not only their technical prowess but also their ability to communicate their ideas effectively. This comprehensive approach ensures that participants leave the Hack-a-Thon with enhanced skills, increased confidence, and a significant competitive edge in the job market, as many past participants have noted the value of this experience during job interviews. © American Society for engineering Education, 2024.

关键词： Personnel training

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CR-SAM: Curvature Regularized Sharpness-Aware Minimization 38

CR-SAM: Curvature Regularized Sharpness-Aware Minimization

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38th AAAI Conference on Artificial Intelligence, AAAI 2024

作者： Wu, Tao Luo, Tie Wunsch, Donald C. Department of Computer Science Missouri University of Science and Technology United States Department of Electrical and Computer Engineering Missouri University of Science and Technology United States

ISBN: (纸本)1577358872

The capacity to generalize to future unseen data stands as one of the utmost crucial attributes of deep neural networks. Sharpness-Aware Minimization (SAM) aims to enhance the generalizability by minimizing worst-case loss using one-step gradient ascent as an approximation. However, as training progresses, the non-linearity of the loss landscape increases, rendering one-step gradient ascent less effective. On the other hand, multi-step gradient ascent will incur higher training cost. In this paper, we introduce a normalized Hessian trace to accurately measure the curvature of loss landscape on both training and test sets. In particular, to counter excessive non-linearity of loss landscape, we propose Curvature Regularized SAM (CR-SAM), integrating the normalized Hessian trace as a SAM regularizer. Additionally, we present an efficient way to compute the trace via finite differences with parallelism. Our theoretical analysis based on PAC-Bayes bounds establishes the regularizer’s efficacy in reducing generalization error. Empirical evaluation on CIFAR and ImageNet datasets shows that CR-SAM consistently enhances classification performance for ResNet and Vision Transformer (ViT) models across various datasets. Our code is available at https://***/TrustAIoT/CR-SAM. Copyright © 2024, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Deep neural networks

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The BRAM is the Limit: Shattering Myths, Shaping Standards, and Building Scalable PIM Accelerators 32

The BRAM is the Limit: Shattering Myths, Shaping Standards, ...

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32nd IEEE Annual International Symposium on Field-Programmable Custom Computing Machines, FCCM 2024

作者： Kabir, Md Arafat Kamucheka, Tendayi Fredricks, Nathaniel Mandebi, Joel Bakos, Jason Huang, Miaoqing Andrews, David University of Arkansas Department of Electrical Engineering and Computer Science United States University of South Carolina Department of Computer Science and Engineering United States United States

ISBN: (纸本)9798350372434

Many recent FPGA-based Processor-in-Memory (PIM) architectures have appeared with promises of impressive levels of parallelism but with performance that falls short of expectations due to reduced maximum clock frequencies, an inability to scale processing elements up to the maximum BRAM capacity, and minimal hardware support for large reduction operations. In this paper, we propose a 'Standard' set of design objectives for PIM array-based FPGA designs. We then propose a PIM array-based GEMV accelerator architecture as a case study to show the proposed Standard can be realized in practice. The GEMV accelerator serves as existence proof that dispels several myths surrounding what is normally accepted as clocking and scaling FPGA performance limitations. Specifically, the proposed accelerator clocks at the maximum frequency of the BRAM and scales to 100% of the available BRAMs. Comparative analyses show execution speeds over existing PIM-based GEMV engines on FPGAs and achieving a 2.65×-3.2× faster clock. An AMD Alveo U55 implementation achieves a system clock speed of 737 MHz, providing 64K bit serial multiply-accumulate (MAC) units for GEMV operation. © 2024 IEEE.

关键词： Memory architecture

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Mitigation of Reflected Overvoltage in Wind Turbine Generator-Converter Systems with a Smart Coil Concept 50

Mitigation of Reflected Overvoltage in Wind Turbine Generato...

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50th Annual Conference of the IEEE Industrial Electronics Society, IECON 2024

作者： Wei, Lulu Fard, Majid T. He, JiangBiao Sottile, Joseph Department of Electrical and Computer Engineering University of Kentucky LexingtonKY United States Department of Electrical Engineering and Computer Science University of Tennessee KnoxvilleTN United States

ISBN: (纸本)9781665464543

In wind-turbine power generation systems, generators are typically located in the nacelles, and medium-voltage power converters are mostly placed at the bottom of the tower for maintenance convenience, resulting in long cables (e.g., 50-150 meters) interconnected between generators and power converters. Consequently, the high dv/dt caused by fast-switching high-voltage semiconductor devices such as silicon carbide (SiC) MOSFETs coupled with the long cables induces high-frequency reflected overvoltage across the generator stator windings. Due to uneven voltage distributions across various coils in each phase, significantly higher voltage spikes will be induced in the first few coils close to the converter side, leading to insulation degradation and winding short-circuit failures. To mitigate such reflected overvoltage across the generator windings and improve the wind-turbine system reliability, a high-efficiency, ultra-compact and low-cost mitigation solution targeting the first few coils will be developed and presented in this paper. © 2024 IEEE.

关键词： Wind Turbine Generators

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International Journal of computers and Applications 2023年第5期45卷 379-390页

作者： Liu, J. Shao, H.J. Deng, X. Jiang, Y.T. School of Computer Jiangsu University of Science and Technology Zhenjiang China Department of Electrical and Computer Engineering University of Nevada Las VegasNV United States

The paper discusses the high computational costs associated with convolutional neural networks (CNNs) in real-world applications due to their complex structure, primarily in hidden layers. To overcome this issue, the paper proposes a novel channel pruning technique that leverages the correlation topology of feature maps generated by each CNNs layer to construct a network with fewer nodes, reducing computational costs significantly. Redundant channels exhibit a high degree of topological similarity and tend to increase as the number of network layers rises. Removing the channel corresponding to highly correlated feature maps allows retrieval of the ‘base’ set of characteristics needed by subsequent layers. The proposed channel pruning technique provides a promising approach to reducing the computational costs of deep convolutional neural networks while maintaining high performance levels. By designing a network structure optimized for specific input data types, the method results in more efficient and effective machine learning models. The pruning operation requires fine-tuning to optimize network performance, and experiments using X-ray, chest CT, and MNIST images show that the pruned network can eliminate approximately 80% of redundant channels with minimal performance deterioration (maintaining original CNNs performance at 99.2%). © 2023 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Topology

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GaN HEMTs based Quad-Active-Bridge DC-DC Converter for PV-Battery-EV-Grid Systems 50

GaN HEMTs based Quad-Active-Bridge DC-DC Converter for PV-Ba...

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50th Annual Conference of the IEEE Industrial Electronics Society, IECON 2024

作者： Gao, Xin Ilka, Reza Luckett, Benjamin He, JiangBiao Department of Electrical Engineering and Computer Science University of Tennessee KnoxvilleTN United States Department of Electrical and Computer Engineering University of Kentucky LexingtonKY United States

ISBN: (纸本)9781665464543

This paper aims to develop a flexible power management approach to interconnect multiple energy resources based on an isolated, monolithic multiport DC-DC power converter. Specifically, a high efficiency, ultra-compact Quad-Active-Bridge (QAB) DC-DC converter is proposed to interconnect photovoltaic (PV), battery energy storage (BES), electric vehicle (EV) charging/discharging, and a distribution grid. Fast-switching Gallium Nitride (GaN) high-electron-mobility transistors (HEMTs) are employed to achieve higher energy efficiency and power density. To meet the high voltage requirements on the DC grid port, a three-level active-neutral-point-clamped (ANPC) bridge based on 650V GaN HEMTs is developed. To provide galvanic isolation among different power ports, a high-frequency, multi-winding planar magnetic transformer is utilized to couple different power ports for flexible power management. The control and efficiency at four operating modes of the QAB converter are investigated for various weather conditions, and electro-thermal simulations for the QAB converter, including the planar transformer, are carried out in PLECS and Ansys software. Moreover, a 15-kW GaN HEMT based QAB DC-DC converter prototype is implemented for experimental verification. © 2024 IEEE.

关键词： Gallium nitride

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Edge-assisted indexing for highly dynamic and static data in mixed reality connected autonomous vehicles

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Intelligent and Converged Networks 2024年第2期5卷 167-179页

作者： Daniel Mawunyo Doe Dawei Chen Kyungtae Han Haoxin Wang Jiang Xie Zhu Han Department of Electrical and Computer Engineering University of HoustonHoustonTX 77004USA InfoTech Labs Toyota Motor North America Research and DevelopmentMountain ViewCA 94043USA Department of Computer Science Georgia State UniversityAtlantaGA 30302USA Department of Electrical and Computer Engineering University of North Carolina at CharlotteCharlotteNC 28223USA

The integration of Mixed Reality(MR)technology into Autonomous Vehicles(AVs)has ushered in a new era for the automotive industry,offering heightened safety,convenience,and passenger ***,the substantial and varied data generated by MR-Connected AVs(MR-CAVs),encompassing both highly dynamic and static information,presents formidable challenges for efficient data management and *** this paper,we formulate our indexing problem as a constrained optimization problem,with the aim of maximizing the utility function that represents the overall performance of our indexing *** optimization problem encompasses multiple decision variables and constraints,rendering it mathematically infeasible to solve ***,we propose a heuristic algorithm to address the combinatorial complexity of the *** heuristic indexing algorithm efficiently divides data into highly dynamic and static categories,distributing the index across Roadside Units(RSUs)and optimizing query *** approach takes advantage of the computational capabilities of edge servers or RSUs to perform indexing operations,thereby shifting the burden away from the vehicles *** algorithm strategically places data in the cache,optimizing cache hit rate and space utilization while reducing *** quantitative evaluation demonstrates the superiority of our proposed scheme,with significant reductions in latency(averaging 27%-49.25%),a 30.75%improvement in throughput,a 22.50%enhancement in cache hit rate,and a 32%-50.75%improvement in space utilization compared to baseline schemes.

关键词： mixed reality autonomous vehicles data indexing edge computing query optimization

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Time-delay Correction Control Strategy for HVDC Frequency Regulation Services

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CSEE Journal of Power and Energy Systems 2024年第5期10卷 2027-2037页

作者： Yuqing Dong Kaiqi Sun Jinning Wang Shunliang Wang He Huang Tianqi Liu Yilu Liu School of Electrical Engineering Shandong UniversityJinan 250061China School of Electrical Engineering Shandong UniversityJinan 250061China. Department of Electrical Engineering and Computer Science University of TennesseeKnoxville 37996USA.

With the advancements in voltage source converter(VSC)technology,VSC based high voltage direct current(VSCHVDC)systems provide system operators with a prospective approach to enhance system operating stability and *** addition to long-distance transmission,the VSC-HVDC system can also provide multiple ancillary services,such as frequency regulation,due to its power ***,if a time delay exists in the control signal,the VSC-HVDC system may bring destabilizing influences to the system,which will decrease the system resilience under the *** order to reduce control deviation caused by time delay,in this paper,a small signal model is first conducted to analyze the impact of time delay on system *** a time-delay correction control strategy for HVDC frequency regulation control is developed to reduce the influence of the time *** control performance of the proposed time-delay correction control is verified both in the established small signal model and the runtime simulation in a modified IEEE 39 bus *** results indicate that the proposed time-delay correction control strategy shows significant improvement in system stability.

关键词： Frequency regulation control HVDC small signal analysis time delay time-delay correction control strategy

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Ultrasound-based AI for COVID-19 detection: a comprehensive review of public and private lung ultrasound datasets and studies

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Multimedia Tools and Applications 2025年 1-55页

作者： Morshed, Abrar Al Shihab, Abdulla Jahin, Md Abrar Al Nahian, Md Jaber Hossain Sarker, Md Murad Ibne Wadud, Md Sharjis Uddin, Mohammad Istiaq Imtiaz Siraji, Muntequa Anjum, Nafisa Shristy, Sumiya Rajjab Rahman, Tanvin Khatun, Mahmuda Rubel Dewan, Md Hossain, Mosaddeq Sultana, Razia Chakma, Ripel Emon, Sonet Barua Islam, Towhidul Hussain, Mohammad Arafat Department of Computer Science and Engineering Ahsanullah University of Science and Technology Dhaka1208 Bangladesh Department of Electrical and Telecommunication Engineering Daffodil International University Dhaka1216 Bangladesh Khulna9203 Bangladesh Okinawa904-0412 Japan Department of Information and Communication Technology Bangladesh University of Professionals Dhaka1216 Bangladesh Department of Information and Communication Technology Comilla University Cumilla3506 Bangladesh Department of Biomedical Physics and Technology University of Dhaka Dhaka1000 Bangladesh Department of Computer Science and Engineering International Islamic University Chittagong Chittagong4318 Bangladesh Department of Electrical and Electronic Engineering Islamic University of Technology Gazipur1704 Bangladesh Department of Electronics and Telecommunication Engineering Chittagong University of Engineering and Technology Chittagong4349 Bangladesh Department of Computer Science and Engineering Notre Dame University Bangladesh Dhaka1000 Bangladesh Department of Electrical and Electronic Engineering Khulna University of Engineering & Technology Khulna9203 Bangladesh Department of Computer Science and Engineering Institute of Science and Technology Dhaka1209 Bangladesh Department of Electronics and Communication Engineering Institute of Science and Technology Dhaka1209 Bangladesh Department of Mathematics Jahangirnagar University Dhaka1342 Bangladesh Department of Electrical and Electronic Engineering Daffodil International University Dhaka1216 Bangladesh Department of Electrical and Electronic Engineering Dhaka University of Engineering and Technology Gazipur1707 Bangladesh Department of Computer Science and Telecommunication Engineering Noakhali Science and Technology University Noakhali3814 Bangladesh Department of Computer Science and Engineering Northern University Bangladesh Dhaka1230 Bangladesh Boston Children’s Hospital Harvard Medical School BostonMA02

The COVID-19 pandemic has affected millions of people globally, with respiratory organs being strongly affected in individuals with comorbidities. Medical imaging-based diagnosis and prognosis have become increasingly popular in clinical settings for detecting COVID-19 lung infections. Among various medical imaging modalities, ultrasound stands out as a low-cost, mobile, and radiation-safe imaging technology. In this comprehensive review, we focus on AI-driven studies utilizing lung ultrasound (LUS) for COVID-19 detection and analysis. We provide a detailed overview of both publicly available and private LUS datasets and categorize the AI studies according to the dataset they used. Additionally, we systematically analyzed and tabulated the studies across various dimensions, including data preprocessing methods, AI models, cross-validation techniques, and evaluation metrics. In total, we reviewed 60 articles, 41 of which utilized public datasets, while the remaining employed private data. Our findings suggest that ultrasound-based AI studies for COVID-19 detection have great potential for clinical use, especially for children and pregnant women. Our review also provides a useful summary for future researchers and clinicians who may be interested in the field. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2025.

关键词： COVID-19

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