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Variable Length Multi-Objective Whale Optimization for Trust Aware Data Gathering in Wireless Sensor Network

IEEE Access 2025年 13卷 32100-32121页

作者： Saad, Mohammed Ayad Jaafar, Rosmina Chellappan, Kalaivani Faculty of Engineering and Built Environment Department of Electrical Electronics and System Engineering Selangor Bangi43600 Malaysia Al-Kitab University Department of Medical Instrumentations Technique Engineering Kirkuk36001 Iraq Universitas Airlangga Biomedical Engineering Study Program Faculty of Science and Technology Surabaya60115 Indonesia

Efficient data collection in wireless sensor networks (WSNs) is crucial. While traditional approaches rely on stationary data sinks, the use of mobile sinks, like unmanned aerial vehicles (UAVs), has shown promise in enhancing data-gathering capabilities. However, existing methods often overlook the importance of trust, leaving the network susceptible to malicious or faulty nodes. To address this issue, we propose a novel trust-aware data-gathering algorithm, Variable Length Multi-Objective Whale Optimization Data Gathering (VLMOWO-DG). Our algorithm simultaneously optimizes energy consumption, delay, and trust while employing mobile sinks to collect data from sensor nodes. By considering trust as a key performance metric, we improve data reliability and security. The VLMOWO-DG algorithm introduces flexibility through variable-length solution representation and application-oriented operators, allowing for efficient exploration of the solution space. Simulation results demonstrate that our proposed algorithm significantly outperforms established benchmarks, NSGA-II and NSGA-III, in terms of domination and hypervolume. This leads to a remarkable improvement of 200% in data gathering performance. © 2015 The Authors.

关键词： Data collection

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Compact 5G Broadband Antenna for Sub-6 GHz Wireless Applications

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IEEE Access 2025年 13卷 79444-79450页

作者： Fattoum, Manal K. Joujou, Samira M. Ibrahim, Sarah M. El-Halabi, Heba Beirut Arab University Faculty of Engineering Communications and Electronics Engineering Program Department of Electrical and Computer Engineering Debbieh Lebanon

The design and analysis of a compact broadband antenna supporting the long-term evolution (LTE) bands 41/42/43/46/48/52 and the sub-6 GHz bands N46/N77/N78/N79, Bluetooth, and Wi-Fi are presented. The proposed antenna consists of a 50-ohm microstrip feedline, a Yagi-shaped patch radiator, and a partial ground plane under the feedline. The slot-loading technique is employed to achieve a wide band of operation and to minimize the overall size of the antenna. Using the low-loss dielectric material substrate, Rogers RO4003C, the form factor of the antenna is appreciably reduced to 26 × 17 × 0.813 mm3 without compromising the performance result of the antenna. The finite element method-based high-frequency electromagnetic solver from ANSYS Corporation is used to simulate and optimize the antenna. A prototype of the designed antenna is fabricated and measured to verify its performance. It is observed that in the operating impedance bandwidth from 2.44 GHz to 5.74 GHz (voltage standing wave ratio © 2013 IEEE.

关键词： Microstrip antennas

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Optimal BESS Scheduling with Real-Time Assessment for Time-of-Use Customers Using Particle Swarm Optimization

Optimal BESS Scheduling with Real-Time Assessment for Time-o...

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Power, Energy and electrical engineering (CPEEE), International Conference on

作者： Alioune Diouf Yasuhiro Noro Electrical Engineering and Electronics Program Kogakuin University Tokyo Japan Department of Electrical and Electronics Engineering Kogakuin University Tokyo Japan

ISBN: (数字)9798331520090

ISBN: (纸本)9798331520106

This study presents an optimal day-ahead operational scheduling strategy for a battery energy storage system(BESS) to achieve savings for a time-of-use(TOU) customer. This optimization problem is solved using a Particle Swarm Optimization(PSO) algorithm with an evaluation of its sensitivity to photovoltaic(PV) and load forecast errors. A new initialization process based on two non-optimized algorithms is proposed to enhance PSO convergence during the optimal scheduling process. By charging the BESS with surplus PV generation or during off-peak periods and discharging it during peak times or when contracted demand limits are exceeded, an initial particle population is provided as an input to the PSO. The state of charge(SOC) is maintained within the normal range by stopping the BESS output selected by the PSO as needed. The PSO's performance is assessed in real-time operation using historical PV and load data. The proposed method is simulated using MATLAB software to verify its effectiveness showing 17% and 10% cost saving over one day and one month, respectively. Additionally, the PSO demonstrates robust performance for forecast error under 10%.

关键词： Schedules Costs Sensitivity Electricity Software algorithms Optimal scheduling Real-time systems Software Scheduling Particle swarm optimization

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Damage-Free Neutral Beam Etching for Gate Recess in E-Mode AlGaN/GaN HEMTs

IEEE Electron Device Letters

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IEEE Electron Device Letters 2025年第5期46卷 705-708页

作者： Chen, Yi-Ho Chu, Fu-Chuan Aslam, Muhammad Lee, Yao-Jen Li, Yiming Samukawa, Seiji National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Graduate Degree Program of College of Electrical and Computer Engineering Hsinchu300093 Taiwan National Chung-Shan Institute of Science and Technology Solid State Devices Section Electronic System Research Division Taoyuan325 Taiwan National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program Hsinchu300093 Taiwan Institute of Pioneer Semiconductor Innovation National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Institute of Pioneer Semiconductor Innovation Institute of Artificial Intelligence Innovation National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Institute of Biomedical Engineering Department of Electronics and Electrical Engineering Institute of Communications Engineering Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Institute of Communications Engineering Department of Electronics and Electrical Engineering Hsinchu300093 Taiwan

Recess gate etching is a critical technique for achieving enhancement-mode (E-mode) AlGaN/GaN high-electron mobility transistors (HEMTs) because the interface is susceptible to the etching damage. This study fabricates recess gates using the neutral beam etching (NBE) technique. By adjusting the aperture thickness in the NBE apparatus, we simulate both NB-mode and plasma-mode etching. The electrical characteristics of E-mode HEMTs fabricated using these two modes are analyzed and compared through DC, noise, and pulsed IV measurements. The results demonstrate that NB-recessed HEMTs exhibit superior performance. © 1980-2012 IEEE.

关键词： Aluminum gallium nitride

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Multi-Scale Analysis Combined Operando Elemental/Spectroscopic Measurement Techniques in Oxide-Type All-Solid-State Na Batteries

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Energy & Environmental Materials 2025年第2期8卷 38-47页

作者： Koji Hiraoka Kazuo Yamamoto Takeshi Kobayashi Tetsuo Sakamoto Shiro Seki Graduate School of Engineering Applied Chemistry and Chemical Engineering Program Kogakuin University Nanostructures Research Laboratory Japan Fine Ceramics Center Energy Transformation Research Laboratory Central Research Institute of Electric Power Industry Graduate School of Engineering Electrical Engineering and Electronics Program Kogakuin University

Understanding the charge/discharge mechanism of batteries plays an important role in the development of high-performance systems,but extremely complicated reactions are *** these complex phenomena are also bottlenecks for the establishment of all-sol id-state batteries(ASSB),we conducted multi-scale analysis using combined multi-measurement techniques,to directly observe charge/discharge reactions at hierarchical scales for the oxide-type ASSB using Na as the carrier *** particular,all of measurement techniques are applied to cross-section ASSB in the same cell,to complementarily evaluate the elemental distributions and structural *** Operando scanning electron microscopy-energy-dispersive X-ray spectroscopy,the Na concentration in the electrode layers changes on the micrometer scale under charge/discharge reactions in the first ***,Operando Raman spectroscopy reveal changes in the bonding states at the atomic scale in the active material,including changes in reversible structural *** cycling the ASSB,the elemental distributions are clearly observed along with the particle shapes and can reveal the Na migration mechanism at the nanometer scale,by time-of-flight secondary ion mass ***,this study can provide a fundamental and comprehensive understanding of the charge/discharge mechanism by observing reaction processes at multiple scales.

关键词： Operando oxide-type all-solid-state battery Raman SEM-EDS sodium battery TOF-SIMS

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Novel Hybrid Algorithm for Investigation of Dissolved Gas Analysis for Alternate Dielectric Fluids of Power Transformer

Novel Hybrid Algorithm for Investigation of Dissolved Gas An...

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Smart and Sustainable Developments in electrical engineering (SSDEE), IEEE International Conference on

作者： Rahul Soni Raymon Antony Raj Bishal Silwal Rahman Azis Prasojo M.M.F. Darwish Norazhar Abu Bakar Electrical and Electronics Engineering Program Navrachana University Vadodara Gujarat India Department of Electrical and Electronics Engineering Kongu Engineering College Perundurai Erode Tamil Nadu India Department of Electrical Engineering Tribhuvan University Institute of Engineering (Pulchowk Campus) Pulchowk Lalitpur Nepal Department of Electrical Engineering Politeknik Negeri Malang Malang Indonesia Department of Electrical Engineering Faculty of Engineering Shoubra Benha University Cairo Egypt Department of Electrical Engineering Faculty of Engineering Universiti Teknologi PETRONAS Perak Malaysia

ISBN: (数字)9798331542108

ISBN: (纸本)9798331542115

The power transformer is the most important element of equipment in an electrical transmission and distribution network. The power and voltage levels that these transformers can manage determine their size, and as the transformer's volume increases, internal isolation and cooling become more challenging. The most popular insulating fluid used in transformers for insulation and cooling is mineral-based oil, which has demonstrated exceptional dielectric and thermal qualities. However, alternative oil technologies have been sought to replace mineral-based oils in recent years because to concerns about safety, cost, and environmental impact. In this context, extensive research efforts have emerged on biological oils for use in transformers. This paper examines the sustainability, safety, and electrical performance of bio-based ester oil in transformer applications with respect to dissolved gas analysis (DGA). AI-based Fuzzy logic controller (FLC) with Duval's triangle (DT) and Duval's pentagon (DP), IEC, CIGRE reports are used in a hybrid manner to identify the possible incipient faults inside the oil-immersed transformers. The graphical analysis of various fuzzy logic plots along with DT and DP are utilized to critically analyze the possible incipient faults arrayed due to DGA. The proposed work proficient compared to previously published results. Highest efficiency of DT and DP based FLC (92%), followed by furan analysis (82.3%). Lastly, recommendations are made on potential fixes for the problems raised and the future course of study for alternate dielectric fluids-based power transformers. The suggested techniques in this research offer a higher diagnostic accuracy than the present approach.

关键词： Fuzzy logic Oils Cellulose Oil insulation Dissolved gas analysis Dielectrics Safety Dielectric liquids Sustainable development Power transformer insulation

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Numerical analysis of Ga gradient effects in ACIGS absorbers for high-efficiency tandem solar cells

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Optical and Quantum electronics 2025年第3期57卷 1-19页

作者： Boukortt, Nour El I. Loureiro, Antonio Garcia Almutairi, Ohood A. Centro Singular de Investigación en Tecnoloxías Intelixentes University of Santiago de Compostela Santiago de Compostela Spain Department of Electronics and Information Systems Ghent University Technology Park 126 Zwijnaarde Belgium Department of Electronic and Electrical Engineering University College London LondonWC1E 6BT United Kingdom Energy Systems Program College of Engineering & Energy Abdullah Al Salem University Khaldiya Kuwait

Ag-alloyed Cu(In,Ga)Se₂ (ACIGS) is a promising material for the bottom subcell in tandem solar cell structures, offering a tunable bandgap that spans the optimal range for maximum efficiency;however, the bandgap widening of ACIGS thin films poses a significant challenge in enhancing their photocurrent. This paper investigates the impact of different grading profiles, specifically focusing on the 'hockey stick'/V-like Ga gradient–induced (GGI) profiles, on the performance of thin-film ACIGS cells. To enhance the physical understanding of these grading profiles we have used Silvaco TCAD tools to analyze how these profiles' depths, notch position, and slope affect the power conversion efficiency (PCE). The optimized ACIGS cell achieves a PCE of 25.80%, compared to 23.60% for the reference device. For the tandem configuration, we pair the optimized ACIGS bottom cell (double grading profile) with a perovskite top cell (band gap ~ 1.66 eV), achieving an overall efficiency of 30.26% under AM1.5G illumination. The obtained results highlight the critical role of Ga gradient profiles in enhancing the bottom cell's performance and stability. Additionally, we compare our results with existing studies to evaluate the broader impact of Ga compositional optimization on ACIGS-based solar cells. This work provides valuable insights into advanced grading strategies and helps us understand the physical behaviour of these high-performance tandem solar cells. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Silver alloys

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A distributed gain-scheduled observer-based approach for the practical consensus of LPV multi-agent systems

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Automatica 2025年 177卷

作者： Pessim, Paulo Sergio Pereira Coutinho, Pedro Henrique Silva Lacerda, Márcio J. Puig, Vicenç Palhares, Reinaldo Martinez Federal University of Minas Gerais Graduate Program in Electrical Engineering Brazil State University of Rio de Janeiro Department of Electronics and Telecommunication Engineering Brazil School of Computing and Digital Media London Metropolitan University United Kingdom Universitat Politècnica de Catalunya Spain Federal University of Minas Gerais Department of Electronics Engineering Brazil

This paper proposes a distributed gain-scheduled observer-based technique for the practical state consensus of linear parameter-varying (LPV) multi-agent systems (MAS). In the proposed approach, the effects of considering different scheduling parameters for each agent are modeled as an internal disturbance. By applying the concepts of the Lyapunov theory, sufficient conditions are obtained for the design of a gain-scheduled observer-based consensus protocol ensuring that the trajectories of the consensus error converge exponentially to a bounded region, achieving a practical consensus. Numerical experiments illustrate the advantages of the proposed practical consensus over the non-synchronization-based scenario usually obtained when the LPV MAS is subjected to different scheduling parameters. © 2025 Elsevier Ltd

关键词： Distributed control and estimation Multi-agent systems Practical consensus

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Multi-modal Multitask Learning Model for Simultaneous Classification of Two Epilepsy Biomarkers 27th

Multi-modal Multitask Learning Model for Simultaneous Classi...

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27th International Conference on Pattern Recognition, ICPR 2024

作者： Broti, Nawara Mahmood Sawada, Masaki Takayama, Yutaro Iijima, Keiya Iwasaki, Masaki Ono, Yumie Electrical Engineering Program Graduate School of Science and Technology Meiji University Kanagawa Kawasaki Japan Department of Neurosurgery Yokohama City University Hospital Kanagawa Yokohama Japan Department of Neurosurgery National Center Hospital National Center of Neurology and Psychiatry Tokyo Kodaira Japan Department of Electronics and Bioinformatics School of Science and Technology Meiji University Kanagawa Kawasaki Japan

ISBN: (纸本)9783031781971

Accurate estimation of the epileptogenic zone is critical for surgical treatment of drug-resistant epilepsy. While epilepsy biomarkers detection for epileptogenic zone localization has traditionally relied on expert clinician knowledge, the use of deep learning in this context has recently gained appeal for objective diagnosis and reducing clinician burden. However, previously proposed classifiers for electrocorticogram data focused on only single biomarkers among many types, requiring separate models and large datasets for each. To minimize clinicians’ workload and patients’ sufferings, innovative methods to classify multiple biomarkers using small training datasets and minimal computation time is required. This research marks the first implementation of multi-modal multitask learning in epilepsy biomarker classification, proposing a model to automatically classify two biomarkers—high-frequency oscillations (HFO) and interictal epileptiform discharges (IED)—from separate datasets simultaneously. We validated the proposed model on 1500 annotated HFO and IED candidate signals each, obtained from 5 patients. Our proposed model can perform both HFO and IED classification simultaneously, with cross-validation accuracies of 90.99% and 93.99%;F1 scores were reported as 0.80 and 0.82, respectively. Our leave-one-patient-out experiments achieved 78.03% and 81.19% accuracy for HFO and IED classification, respectively. Compared to existing state-of-the-art classification architectures, our model is shown to be efficient and robust, yet simple and lightweight. The usefulness of sharing parameters between the two classifiers was confirmed in this practical clinical setting of epileptic biomarker detection, potentially contributing to minimizing the number of annotated datasets and realizing robust, accurate, and simultaneous identification of two biomarkers. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Deep learning

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BAQET: BRAM-aware Quantization for Efficient Transformer Inference via Stream-based Architecture on an FPGA 25

BAQET: BRAM-aware Quantization for Efficient Transformer Inf...

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Proceedings of the 2025 ACM/SIGDA International Symposium on Field programmable Gate Arrays

作者： Ling-Chi Yang Chi-Jui Chen Trung Le Bo-Cheng Lai Scott Hauck Shih-Chieh Hsu Institute of Electronics National Yang Ming Chiao Tung University Hsinchu Taiwan Graduate Degree Program of College of Electrical and Computer Engineering in National Yang Ming Chiao Tung University Hsinchu Taiwan Electrical and Computer Engineering in University of Washington Seattle USA Electrical and Computer Engineering University of Washington Seattle USA Physics University of Washington Seattle USA

ISBN: (纸本)9798400713965

FPGAs are a compelling substrate for supporting machine learning inference. Tools such as High-Level Synthesis and hls4ml can shorten the development cycle for deploying ML algorithms on FPGAs, but can struggle to handle the large on-chip storage needed for many of these models. In particular the high BRAM usage found in many of these flows can cause Place & Route failures during synthesis. In this paper we propose using a Simulated-Annealing based flow to perform BRAM-aware quantization. This approach trades off inference accuracy with BRAM usage, to provide a high-quality inference engine that still meets on-chip resource constraints. We demonstrate this flow for Transformer-based machine learning algorithms, which include Flash Attention in a Stream-based Dataflow architecture. Our system imposes minimal accuracy drops, yet can reduce BRAM usage by 20%-50%, and improve power efficiency by 264%-812% compared to existing Transformer-based accelerators on FPGAs

关键词： efficient transformer

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