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2024 Conference on Lasers and Electro-Optics/Pacific Rim, CLEO-PR 2024

作者： Kubo, Wakana Tokyo University of Agriculture and Technology Department of Electrical Engineering and Computer Science 2-24-16 Naka-cho Koganei-shi Tokyo184-8588 Japan

We report a nonradiative cooling technology that can reduce the temperature of space surrounded by an opaque container for the first time. A metamaterial-loaded thermoelectric device enables the collection of thermal radiation and the transfer of thermal energy to the exterior container, leading to a temperature reduction inside the container. © 2024 The Author(s)

关键词： Radiative Cooling

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Transformer External Fault Detection under Geomagnetically Induced Currents

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IEEE Transactions on Power Delivery 2025年第3期40卷 1788-1791页

作者： Ahmadzadeh-Shooshtari, Babak Rezaei-Zare, Afshin Hydro One Networks Inc. TorontoONM5G2P5 Canada York University Department of Electrical Engineering and Computer Science TorontoONM3J1P3 Canada

During geomagnetically induced currents (GICs), transformer differential relays are likely to remain blocked for internal faults. This issue is pinpointed by extensive studies in literature, and several solutions have been proposed to unblock the relays for the internal faults under the GIC flow in transformers. Nonetheless, such unblocking schemes require an external fault detection (EFD) technique to ensure security for some external faults during the GIC and current transformer (CT) saturation. The GIC leads to pre-fault CT saturation, which can make the transformer external fault detection challenging. This paper proposes an EFD method for transformer differential protection, especially under GIC conditions with pre-fault CT saturation. The developed EFD approach's effectiveness is verified in various fault scenarios, with and without the GIC. Moreover, case studies show higher fault detection capability of the proposed method compared with an existing differential protection's EFD logic during the GIC-caused CT saturation. © 1986-2012 IEEE.

关键词： Electric transformers

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A novel soft computing based efficient feature selection approach for timely identification of COVID-19 infection using chest computed tomography images: a human centered intelligent clinical decision support system

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Multimedia Tools and Applications 2025年第14期84卷 13717-13785页

作者： Singh, Law Kumar Khanna, Munish Garg, Hitendra Singh, Rekha Department of Computer Engineering and Applications GLA University Mathura281406 India School of Computing Science and Engineering Galgotias University Plot No.2 Sector 17-A Yamuna Expressway Gautam Buddh Nagar Greater Noida203201 India Department of Physics Uttar Pradesh Rajarshi Tandon Open University Uttar Pradesh Prayagraj India

The SARS-CoV-2 coronavirus strain’s introduction in December 2019 resulted in the development of the new coronavirus disease, COVID-19. Following its first appearance, the virus quickly spread throughout the world and is now considered to be a pandemic. There were 6,885,962 recorded deaths and 689,853,908 confirmed cases as of April 4, 2023. It is essential to put in place a thorough testing strategy in order to stop the disease from spreading. Nonetheless, a number of testing approaches are presently under consideration due to a restricted inventory and a limited supply of testing equipment. Recent expert analysis suggests that images from chest computed tomography (CT) scans could reveal important information about COVID-19, which is why we are using this modality as a focus of our investigation. Moreover, numerous recent studies have demonstrated that selecting the most informative features from the subject images improves the classification models’ efficiency and shortens the time needed for training and testing. All of this encourages us to present a study that suggests a novel, efficient, and fast feature selection system as the core of the proposed highly competent clinical decision support system for COVID-19 infection prediction. Using a publicly accessible CT image dataset, this four-phase system divides the images into two categories: "COVID-19-infected human" and "healthy human". Pre-processing is the first step in the study, after which features from different categories in the images are extracted in the next phase. In the third phase, the most influential features are then selected using three algorithms: the Teaching Learning-Based Optimization Algorithm (TLBO), the Cuckoo Search Optimization Algorithm (CSO), and a proposed hybrid of these two. To the best of the authors’ knowledge, these algorithms have rarely been applied to feature selection for COVID-19 infection prediction, which highlights the originality and inventiveness of the work. Followin

关键词： COVID-19

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A Comparative Study of Machine Learning Algorithms on Datasets of Varying Sizes 9th

A Comparative Study of Machine Learning Algorithms on Datase...

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9th Future Technologies Conference, FTC 2024

作者： Huang, Xiaoting Xi, Xuelian Wang, Siqi Sadeghi, Zahra Samir, Asif Matwin, Stan Department of Electrical and Computer Engineering Dalhousie University HalifaxNSB3H4R2 Canada Department of Computer Science Dalhousie University HalifaxNSB3H1W5 Canada

ISBN: (纸本)9783031731242

This research investigates the nuanced performance dynamics of machine learning algorithms across datasets of varying sizes. Employing three distinct datasets characterized by different sample sizes, we implement four machine learning algorithms—Logistic Regression, K Nearest Neighbors (KNN), Naïve Bayes, and Random Forest. This paper delineates the application methodologies, hyperparameter tuning procedures, and the resultant performance outcomes. Our findings reveal that Logistic Regression and Naïve Bayes exhibit relatively minor sensitivity to dataset size fluctuations. In stark contrast, KNN is markedly influenced by dataset size, showcasing significant performance variations. Notably, Random Forest demonstrates consistently superior performance across the four machine learning models considered, particularly excelling with the largest datasets. The implications of these observations are discussed, contributing to a comprehensive understanding of the interplay between machine learning algorithms and dataset characteristics. The effectiveness of a machine learning algorithm does not rely solely on expanding the dataset size. Our research indicates that once a certain threshold is reached, merely increasing the dataset size does not proportionally improve performance. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Adversarial machine learning

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Near-Field Communications: Shape and Structure Design for Uniform Planar Array

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IEEE Internet of Things Journal 2025年第11期12卷 15151-15165页

作者： Chen, Siyu Gu, Juping Duan, Wei Zhang, Lei Dang, Shuping Wen, Miaowen Ding, Zhiguo Ho, Pin-Han Nantong University School of Information Science and Technology Nantong226019 China Suzhou University of Science and Technology China Hubei Polytechnic University Department of Electronics and Information Engineering Huangshi435003 China University of Bristol School of Electrical Electronic and Mechanical Engineering BristolBS8 1UB United Kingdom South China University of Technology School of Electronic and Information Engineering Guangzhou510640 China Khalifa University Department of Electrical Engineering and Computer Science Abu Dhabi United Arab Emirates University of Electronic Science and Technology of China Shenzhen Institute for Advanced Study Shenzhen518000 China University of Waterloo Department of Electrical and Computer Engineering WaterlooONN2L 3G1 Canada

With the flourishing development of 6G wireless networks, the demand of spectrum efficiency rapidly increases, in order to support the demands of high quality data transmission and connections of massive users. Among various promising technologies, the technology of near-field communications provides a great potential to address such an issue due to the unique spherical-wave channels for electromagnetic (EM) propagation. In this paper, multiple-input single-output (MISO) near-field communications is comprehensively studied to clarify the influences of the shape and structure of uniform planar array (UPA) on the system performance, considering three cases with uniform linear array (ULA), rectangular UPA, and circular UPA. In particular, we reveal the properties of rapid deterioration for signal-to-noise ratio (SNR) from the reduced projection aperture in near-field communications and investigate the single spherical crown antenna design and spherical crown antenna array design in order to address this issue. Moreover, we also characterize the role of antenna projection aperture in details, and theoretically analyze the shape of UPA, yielding the corresponding exact closed-form expressions for SNR and outage probability (OP). Based on these above analytical results, we find out that adjusting the spacing between adjacent antennas to control the relative angle between user and selected antennas is an efficient way to improve the projection aperture of antenna and SNR. Simulation results are shown to well match analytical results, which validate the correctness of our analysis, clarifying that our proposed designs outperform the conventional works and illustrating a better stability for angle variations. © 2025 IEEE.

关键词： Spheres

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Memristor Modeling with Homeostatic Threshold Variation for Simulation and Application

Memristor Modeling with Homeostatic Threshold Variation for ...

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2023 International Conference on Neuromorphic Computing, ICNC 2023

作者： Shi, Xinming Wang, Zilu University of Birmingham School of Computer Science BirminghamB15 2TT United Kingdom Southern University of Science and Technology Department of Computer Science and Engineering Shenzhen518000 China School of Mechanical Engineering and Automation Shenzhen518000 China

ISBN: (纸本)9798350316889

This paper proposes a novel approach to emulating biological neural components using memristors. The nanoscale, resistance variability, and non-volatility of the memristor make it a suitable candidate for this task. A homeostasis-type switching mechanism is induced into the memristor modeling, inspired by the homeostatic switching behavior of biological neural components. The proposed model is generalizable and adaptable to various threshold-type memristor models. A SPICE model is proposed, and the memristor model is utilized to implement a neuron circuit that follows the homeostasis-type mechanism. A spiking neural network and its verification platform are designed, where pattern recognition can be achieved. The simulation is carried out in Cadence PSPICE, and a test comparison between scenarios with homeostasis and non-homeostasis is proposed. This work demonstrates the potential of memristors in implementing neuromorphic computing systems. © 2023 IEEE.

关键词： Memristors

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Beyond Strang:a Practical Assessment of Some Second-Order 3-Splitting Methods

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应用数学与计算数学学报 2025年第1期7卷 95-114页

作者： Raymond J.Spiteri Arash Tavassoli Siqi Wei Andrei Smolyakov Department of Computer Science University of Saskatchewan110 Science PlaceSaskatoon S7N 5K9SKCanada Department of Mathematics and Statistics University of Saskatchewan106 Wiggins RoadSaskatoon S7N 5E6SKCanada Department of Computer Science University of Saskatchewan110 Science PlaceSaskatoon S7N 5K9SKCanada Department of Physics and Engineering Physics University of Saskatchewan116 Science PlaceSaskatoon S7N 5E2SKCanada Department of Physics and Engineering Physics University of Saskatchewan116 Science PlaceSaskatoon S7N 5E2SKCanada

Operator-splitting is a popular divide-and-conquer strategy for solving differential ***,the right-hand side of the differential equation is split into a number of parts that are then integrated *** methods are known that split the right-hand side into two *** approach is limiting,however,and there are situations when 3-splitting is more natural and ultimately more *** second-order Strang operator-splitting method readily generalizes to a right-hand side splitting into any number of *** is arguably the most popular method for 3-splitting because of its efficiency,ease of implementation,and intuitive *** 3-splitting methods exist,but they are less well known,and analysis and evaluation of their performance in practice are *** demonstrate the effectiveness of some alternative 3-splitting,second-order methods to Strang splitting on two problems:the reaction-diffusion Brus-selator,which can be split into three parts that each have closed-form solutions,and the kinetic Vlasov-Poisson equations that are used in semi-Lagrangian plasma *** find alternative second-order 3-operator-splitting methods that realize efficiency gains of 10％-20％over traditional Strang *** analysis for the practical assess-ment of the efficiency of operator-splitting methods includes the computational cost of the integrators and can be used in method design.

关键词： Operator-splitting methods Fractional-step methods Brusselator Vlasov-Poisson equations

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Systolic Array Architecture for Educational Use 27

Systolic Array Architecture for Educational Use

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27th International Conference on System Theory, Control and Computing, ICSTCC 2023

作者： Oprițoiu, Flavius Vlăduțiu, Mircea Laboratory Computer Science and Engineering Department Politehnica University Timisoara 2 V.Parvan Blvd Timisoara300223 Romania

ISBN: (纸本)9798350337983

This paper presents a systolic array architecture for General Matrix Multiplication. The system was designed and verified using the Verilog description language. The architecture was constructed for educational use aiming to complement the practical activities of computer Architecture classes. The proposed solution can be used as a design space exploration tool for evaluation of matrix multiplication accelerators based on non-stationary systolic arrays. Both the width and format of the processed operands as well as the number of stages of the systolic array's Processing Elements can be customized. As a case study, the design and performance of a systolic array for accelerating the multiplication of square matrices of signed, 8-bit integers, is presented. The overall architecture was synthesized for the Altera DE2 FPGA board in order to evaluate its performance. © 2023 IEEE.

关键词： Systolic arrays

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Augmentation of Mixing Quality and Its Analysis Based on Electrode Shape Diversity in Digital Microfluidic Biochips 10th

Augmentation of Mixing Quality and Its Analysis Based on Ele...

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10th International Symposium on Applied Computing for Software and Smart systems, ACSS 2023

作者： Majumder, Riya Dutta, Amartya Pal, Rajat Kumar Department of Computer Science and Engineering Netaji Subhash Engineering College West Bengal Kolkata700152 India Department of Computer Science and Engineering B. P. Poddar Institute of Management and Technology West Bengal Kolkata700052 India Department of Computer Science and Engineering University of Calcutta Acharya Prafulla Chandra Roy Shiksha Prangan JD-2 Sector-III Salt Lake Kolkata700106 India

ISBN: (纸本)9789819977826

The lab-on-a-chip (LoC) system is principally a replacement of conventional laboratory experiments with microfluidic biochip. A microfluidic biochip with highly reconfigurable and scalable technology and the capability of handling nano- or microliter volume of discrete droplets is identified as Digital Microfluidic Biochip (DMFB). We intend to use regular hexagonal-shaped electrodes instead of traditional square electrodes to furnish the existing technology with more accuracy and enhancements. In this paper, we have focused on the geometrical features of the hexagonal-shaped electrode along with its effect on the DMFB system. Furthermore, in any bioassay synthesis, the mixing of sample and reagent is the most dominant part, and at the same time, dilution is one kind of mixing. Hence, highlighting the active mixing procedure is one of the significant challenges so that the Hexagonal DMFB (HDMFB) forefronts the square-based DMFB system. In this work, we have introduced a systematic study and analysis of hexagonal cell-based mixers and developed the algorithm for the mixer library on the proposed HDMFB system, along with all decisive factors. The computed experimental results are found to be better than the state-of-the-art research works. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Electrodes

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Optimal Codes Correcting a Substring Edit

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IEEE Transactions on Information Theory 2025年

作者： Li, Yuting Tang, Yuanyuan Lou, Hao Gabrys, Ryan Farnoud, Farzad University of Virginia Department of Computer Science United States University of Virginia Department of Electrical and Computer Engineering United States Calit2 University of California-San Diego United States University of Virginia Department of Electrical and Computer Engineering Department of Computer Science United States

The substring edit error replaces a substring u of x with another string v, where the lengths of u and v are bounded by a given constant k. It encompasses localized insertions, deletions, and substitutions within a window. Codes correcting one substring edit have redundancy at least log n + k. In this paper, we construct codes correcting one substring edit with redundancy log n + Ok(log log n), which is almost optimal. We also study the average-case document-exchange problem under one substring edit and construct a hash with an expected length of approximately 2 log n + Ok(log log n) for any iid distribution for the documents. © 1963-2012 IEEE.

关键词： Redundancy

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