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21st Pacific Rim International Conference on Artificial Intelligence, PRICAI 2024

作者： Iwamoto, Yuki Kaneiwa, Ken Department of Computer Network Engineering Graduate School of Informatics and Engineering The University of Electro-Communications Tokyo Japan

ISBN: (纸本)9789819601240

Rule-induction models have demonstrated great power in the inductive setting of knowledge graph completion. In this setting, the models are tested on a knowledge graph entirely composed of unseen entities. These models learn relation patterns as rules by utilizing subgraphs. Providing the same inputs with different rules leads to differences in the model’s predictions. In this paper, we focus on the behavior of such models. We propose a re-ranking-based model called ReDistLP (Re-ranking with a Distinct Model for Link Prediction). This model enhances the effectiveness of re-ranking by leveraging the difference in the predictions between the initial retriever and the re-ranker. ReDistLP outperforms the state-of-the-art methods in 2 out of 3 benchmarks. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Knowledge graph

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A Four-Branch RLC Filter for a Grid-Tied Solar Photovoltaic System Coupled to a Weak Grid Network 15

A Four-Branch RLC Filter for a Grid-Tied Solar Photovoltaic ...

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15th International Renewable Energy Congress, IREC 2025

作者： Neku, Sinethemba Koko, Sandile Phillip Department of Electrical Electronic and Computer Engineering Bloemfontein South Africa

ISBN: (纸本)9798331516772

The reliance on fossil fuels can be reduced by adopting renewable energy technologies, such as solar photovoltaic systems, which produce clean energy. As a result, consumers connected to the local grid can use a grid-tied solar photovoltaic (PV) system to reduce their electricity bills and provide backup power during grid outages. However, the biggest problem with a grid-connected solar PV system is the intermittent nature of sunlight resource which affects the power quality of the grid network by injecting harmonics. Several studies have been conducted to design passive filters that minimize the total harmonic distortion (THD) in a grid-tied solar photovoltaic system. Such studies were conducted without accounting for the negative impact of the weak grid network itself. Hence, this paper designs a four-branch RLC passive filter that is capable to minimize the harmonics generated by the combination of a weak grid-network, non-linear load and a solar PV system. In order to analyze the THD levels, Fast Fourier Transform (FFT) tool has been used in PSIM simulator/software. The results showed that the proposed filter reduced the % THD of both the voltage and current from significant distortion levels to 5.7% and 3.6%, respectively. This meets the minimum allowable limit set by IEEE standards for low voltage systems. © 2025 IEEE.

关键词： Fast Fourier transforms

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The internet of battle things: a survey on communication challenges and recent solutions

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Discover Internet of Things 2025年第1期5卷 1-28页

作者： Kufakunesu, Rachel Myburgh, Herman De Freitas, Allan Department of Electrical Electronic and Computer Engineering University of Pretoria Cnr Lynnwood and Roper Street Pretoria0028 South Africa

The use of Internet of Things (IoT) technology in military settings has introduced the notion of "Internet of Battle Things" (IoBT), transforming modern warfare by interconnecting various equipment and systems essential for battlefield operations. This connectivity facilitates real-time communication, data sharing, and collaboration among military assets, enhancing situational awareness, decision-making processes, and overall operational effectiveness. The domain for IoBT encompasses a broad range of military assets, from drones and ground vehicles to soldier-worn wearables, sensors, and munitions. These assets are capable of collecting and transmitting critical information from the battlefield, including location data, status updates, environmental conditions, and the movements of adversaries. IoBT networks depend on robust communication networks, secure data transmission protocols, advanced data analytics for processing vast datasets, and seamless integration with command-and-control infrastructures. However, IoBT devices and systems function in dynamic and challenging battlefield conditions which present unique communication challenges. This study aims to review research efforts that provide current state-of-the-art solutions, their limitations, and emerging technologies. We classify these challenges into interoperability, power and energy management, security, and network resilience, while also discussing future research directions to improve communication in IoBT networks. © The Author(s) 2025.

关键词： Interoperability

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High-Frequency Power Loss Investigation of Pavement Materials in Roadway Inductive Charging System

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IEEE Transactions on Transportation Electrification 2025年第3期11卷 7475-7487页

作者： Zheng, Zilong Chen, Xiao Wang, Yao Zhang, Hua Wang, Hao Lu, Fei Department of Electrical and Computer Engineering Drexel University Philadelphia PA USA Department of Civil and Environmental Engineering at Rutgers The State University of New Jersey New Brunswick NJ USA School of Electrical and Electronic Engineering Nanyang Technological University Jurong West Singapore Department of Electrical and Computer Engineering Lehigh University Bethlehem PA USA

The rapid advancement of electric vehicles (EVs) offers a significant reduction in carbon emissions by replacing fossil fuels with more sustainable energy sources. This paper studies wireless charging technology for EVs, focusing on high-frequency power losses. It presents an experimental investigation into the inductive power transfer (IPT) system's efficiency under various pavement materials (specifically, asphalt and concrete), revealing significant power losses due to material electromagnetic properties. This research provides insights into optimizing IPT system design through empirical analysis of power losses across different frequencies and magnetic flux densities. Three main contributions are highlighted: quantifying power loss density, developing an empirical equation for magnetic losses, and identifying the significant impact of pavement materials on overall system efficiency. A 17.8 kW IPT system is implemented to measure and validate the power losses in pavement materials. This research underscores the critical need for interdisciplinary approaches to enhance the feasibility of IPT systems for future autonomous and smart city applications. © 2015 IEEE.

关键词： Inductive power transmission

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A Recent Review of Passive Filters as Used in Solar Photovoltaic-Based Systems to Mitigate Harmonics 15

A Recent Review of Passive Filters as Used in Solar Photovol...

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15th International Renewable Energy Congress, IREC 2025

作者： Neku, Sinethemba Koko, Sandile Phillip Department of Electrical Electronic and Computer Engineering Bloemfontein South Africa

ISBN: (纸本)9798331516772

The use of solar photovoltaic (PV) technology has significantly increased as a solution for providing electricity to off-grid or remote users, as well as for reducing energy costs for grid-connected users. The main concern, however, is the impact of fluctuating solar radiation on power quality. It has been demonstrated that low solar radiation can lead to total harmonic distortion (THD) levels as high as 130%. Additionally, harmonics are generated by electronic switching devices such as converters and inverters, as well as by non-linear loads. Passive filters have proven to be the most commonly used solution to mitigate harmonics, owing to their cost-effectiveness and high performance. Components such as inductors (L), capacitors (C) and/or damping resistors (R) are used to design passive filters. The aim of this paper is to present a review/survey on recent studies that focused on the use or design of passive filters to minimize harmonics in standalone and grid-connected solar PV systems. It has been found that using either an LC or LLCL filter significantly enhances the power quality of off-grid solar PV systems. However, an LC filter without damping resistance has been found to be less effective for a grid-connected solar PV system. Additionally, it has been found that most studies have overlooked the impedance of the grid networks and failed to ensure compliance with IEEE's allowable THD limits for both voltage and current. © 2025 IEEE.

关键词： Passive filters

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Design of Dual Polarized FMCW Radar System with Coupler Integrated Lens Antenna for Automotive SAR Application

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IEEE Transactions on Vehicular Technology 2025年第5期74卷 6991-7004页

作者： Lee, Chanhee Cho, Hyunyoung Ahn, ByungKuon Lee, Woo-Kyung Yu, Jong-Won Kim, Jeong-Wook School of Electrical Engineering Daejeon34141 Korea Republic of Soongsil University Department of Intelligent Semiconductors School of Electronic Engineering Seoul06978 Korea Republic of Korea Aerospace University School of electronic and information engineering Goyang Korea Republic of Ajou University Department of Electrical and Computer Engineering Suwon16499 Korea Republic of

This paper presents the design of a dual-polarized frequency-modulated continuous wave (FMCW) radar system with a coupler-integrated lens antenna for automotive synthetic aperture radar (SAR) applications. High-resolution radar imaging is imperative for automotive use, with dual-polarized SAR imaging providing robust support in achieving this objective. However, exploration of the system design for dual-polarized FMCW SAR systems has been limited. The paper outlines the design of the aforementioned radar system, emphasizing its suitability for automotive SAR applications. It details the requisite parameters for dual-polarized automotive SAR systems and the design considerations for the dual-polarized lens antenna. Additionally, it proposes a radar signal monitoring method employing a coupler-integrated antenna to detect the radiated radar signal. Furthermore, a dual-polarization synthesis method is introduced to enhance SAR image quality. Experimental validation of the implemented dual-polarized FMCW radar with a coupler-integrated lens antenna confirms the effectiveness of the proposed system design. © 1967-2012 IEEE.

关键词： Lens antennas

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Hybrid lightweight encryption for IoT: integrating chaotic key generators with Feistel and substitution-permutation networks for secure 3DV transmission

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Multimedia Tools and Applications 2025年 1-47页

作者： El-Shafai, Walid Mesrega, Ahmed K. Ahmed, Hossam Eldin H. Elbahnasawy, Nirmeen A. El-Samie, Fathi E. Abd Computer Science Department Prince Sultan University Riyadh11586 Saudi Arabia Deptartment of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt Department of Computer Science and Engineering Faculty of Electronic Engineering Menoufia University Menouf Egypt Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia

The Internet of Things (IoT) stands as a revolutionary leap in digital connectivity, envisioning a future network connecting billions of devices, seamlessly. Amidst the myriad benefits, there arises an intricate web of challenges, prominently centered around potential threats and data security implications. Recent cryptography techniques, such as DNA-based cryptography, 3D chaos-based cryptography, and optical cryptography, face challenges including large encryption times, high energy consumption, and suboptimal rather than optimal performance. Particularly, the burden of long encryption cycles strains the energy resources of typical low-power and compact IoT devices. These challenges render the devices vulnerable to unauthorized breaches, despite large storage capacities. The hallmark of the IoT ecosystem, characterized by its low-power compact devices, is the burgeoning volume of data they generate. This escalating data influx, while necessitating expansive storage, remains vulnerable to unauthorized access and breaches. Historically, encryption algorithms, with their multifaceted architectures, have been the bulwark against such intrusions. However, their inherently-complex nature, entailing multiple encryption cycles, strains the limited energy reserves of typical IoT devices. In response to this intricate dilemma, we present a hybrid lightweight encryption strategy. Our algorithm innovatively leverages both one-dimensional (1D) and two-dimensional (2D) chaotic key generators. Furthermore, it amalgamates a classical encryption philosophy, harmonizing the strengths of Feistel and substitution-permutation networks. The centerpiece of our strategy is achieving effective encryption in merely three rounds, tailored expressly for compressed Three-Dimensional Video (3DV) frames, ensuring their unwavering integrity. Our workflow commences with the H.264/MVC compression algorithm, setting the stage for the subsequent encryption phase. Through rigorous MATLAB simulations,

关键词： Image coding

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Bias analysis of AI models for undergraduate student admissions

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Neural Computing and Applications 2025年第12期37卷 7785-7795页

作者： Van Busum, Kelly Fang, Shiaofen Department of Computer Science and Software Engineering Butler University IndianapolisIN United States Computing and Engineering Indiana University Luddy School of Informatics Indiana University Indianapolis IndianapolisIN United States

Bias detection and mitigation is an active area of research in machine learning. This work extends previous research done by the authors Van Busum and Fang (Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing, 2023) to provide a rigorous and more complete analysis of the bias found in AI predictive models. Admissions data spanning six years was used to create an AI model to determine whether a given student would be directly admitted into the School of Science under various scenarios at a large urban research university. During this time, submission of standardized test scores as part of a student’s application became optional which led to interesting questions about the impact of standardized test scores on admission decisions. We developed and analyzed AI models to understand which variables are important in admissions decisions, and how the decision to exclude test scores affects the demographics of the students who are admitted. We then evaluated the predictive models to detect and analyze biases these models may carry with respect to three variables chosen to represent sensitive populations: gender, race, and whether a student was the first in his/her family to attend college. We also extended our analysis to show that the biases detected were persistent. Finally, we included several fairness metrics in our analysis and discussed the uses and limitations of these metrics. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Students

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RIS-Aided MIMO Downlink Transmission for Ultradense LEO Satellite-Terrestrial Networks

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IEEE Internet of Things Journal 2025年第11期12卷 15304-15318页

作者： Zhang, Xin Qin, Xiaohan Zhang, Zitian Cai, Lin X. Zhou, Haibo Zhuang, Weihua Nanjing University School of Electronic Science and Engineering Nanjing210023 China Zhejiang Gongshang University School of Information and Electronic Engineering Hangzhou310018 China Illinois Institute of Technology Department of Electrical and Computer Engineering ChicagoIL60616 United States University of Waterloo Department of Electrical and Computer Engineering WaterlooONN2L 3G1 Canada

Ultradense low-Earth orbit (LEO) satellite-terrestrial network (ULSN) has evolved as a new paradigm to provide ubiquitous and high-capacity communications in next generation wireless networks. However, the direct LEO satellite broadband connectivity faces significant challenges in urban environments due to the masking effect, which limits the reliability and availability of communication links in ULSNs. To address this, reconfigurable intelligent surface (RIS) is emerging as a promising solution in ULSNs. In this article, we investigate RIS-aided downlink data transmission in urban environments of multiusers in ULSNs. We set up a mixed-integer programming (MIP) model for maximizing the sum rate of terrestrial users in ULSNs. To solve the complex MIP problem, we propose a two-phase joint optimization algorithm with a deep learning phase and an alternative optimization (AO) phase. In the deep learning phase, a deep neural network (DNN) algorithm is employed to obtain the optimal user association matrix based on the positions of terrestrial users and LEO satellites. Then in the AO phase, successive convex approximation is utilized to transform the nonconvex subproblems of beamforming and RIS phase design into convex formulations and iteratively solve them. Simulation results demonstrate that the proposed algorithm outperforms other baseline algorithms. © 2014 IEEE.

关键词： Integer programming

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PV/Wind Smart Grid Optimization Using Machine Learning based on Improved Spider Wasp Optimizer Algorithm to Attain SDG7 33

PV/Wind Smart Grid Optimization Using Machine Learning based...

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33rd Southern African Universities Power engineering Conference, SAUPEC 2025

作者： Zulu, Musawenkosi L.T Sarma, Rudiren Tiako, Remy Durban University of Technology Department of Electronic and Computer Engineering Durban South Africa University of KwaZulu-Natal Department of Electrical Electronic and Computer Engineering Durban South Africa

ISBN: (纸本)9798331535162

The United Nations approved the Sustainable Development Goals in 2015 to help countries around the world work toward a more sustainable future. The SDG7 goal is to ensure that everyone has access to cheap, dependable, clean, renewable, and sustainable energy. In view of the shifting energy sources, modernizing the power systems is imperative to satisfy daily demands. Complex energy networks are made simpler by the power system's integration of smart grids. Furthermore, Distributed Generation (DG) is integrated with Renewable Energy Sources (RESs) such as wind and photovoltaic (PV) systems to provide converter autonomy and smart grids. However, frequency changes caused by imbalances in load and generation, together with fault outbreaks, continue to pose a challenge to smart grids. While many academics concentrate on using machine learning (ML) in steady state models, this research aims to analyze robust performance optimization and discuss potential uses of ML in the future to help with transient behavior during fault outbreaks. This research builds a power system model for a smart grid to contribute attaining SDG7. The key contribution is the tuning of the gains by the meta-heuristic optimization algorithms. The machine learning based on improved spider wasp optimizer (SWO) is used in this study, while considering the limitations of the operating system. The simulations were carried on MATLAB. Using SWO the system produced satisfactory results. © 2025 IEEE.

关键词： faults machine learning optimization renewable energy smart grid

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