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iLIAC: An approach of identifying dissimilar groups on unstructured numerical image dataset using improved agglomerative clustering technique

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Multimedia Tools and Applications 2024年第39期83卷 86359-86381页

作者： S, Sreedhar Kumar Ahmed, Syed Thouheed Fathima, Afifa Salsabil Mathivanan, Sandeep Kumar Jayagopal, Prabhu Saif, Abdu Gupta, Sachin Kumar Sinha, Garima Department of Computer Science and Engineering School of Engineering and Technology CMR University Karnataka Bengaluru India Department of Electrical Engineering Indian Institute of Technology Hyderabad Telangana Kandi India School of Computer Science and Engineering REVA University Bangalore India School of Computer Science and Engineering Galgotias University Uttar Pradesh Greater Noida203201 India School of Computer Science Engineering and Information Systems Vellore Institute of Technology Tamil Nadu Vellore632014 India Department of Communication and Computer Engineering Faculty of Engineering and IT Taiz University Taiz Yemen Katra India Department of Computer Science Engineering Jain University Bangalore India

Unstructured Numerical Image Dataset Separation (UNIDS) method employing an enhanced unsupervised clustering technique. The objective is to delineate an optimal number of distinct groups within the input grayscale (G-S) image content, utilizing the improved limited iteration agglomerative clustering (iLIAC) clustering technique for the separation and enhancement of picture elements. The UNIDS method is structured into two primary stages: partitioning and validation. In the partitioning stage, the UNIDS method identifies an appropriate number of discrete clusters within the grayscale image using the iLIAC technique, eliminating the need for predetermined procedures. Subsequently, the method evaluates the similarity and deviation among data elements within the same group in the resultant image dataset. Additionally, it assesses the proximity and inters severance among clusters in the outcome of the image dataset through the partitioning process. Empirical results indicate that the UNIDS system excels in the spontaneous identification of an optimal number of discrete clusters within the input G-S image. The system demonstrates superior thickness, reduced deviation among data elements within the same cluster, increased inter-separation, and diminished inter-closeness between cluster elements. Furthermore, empirical analysis establishes the superior performance of the UNIDS approach compared to existing clustering techniques. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Iterative methods

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Unveiling memory-window narrowing mechanism after bipolar cycling in HZO/Si FeFETs: Critical role of hole trap generation and carrier de-trapping behavior

Unveiling memory-window narrowing mechanism after bipolar cy...

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2024 IEEE International Electron Devices Meeting, IEDM 2024

作者： Cho, Seong-Kun Toprasertpong, Kasidit Takenaka, Mitsuru Takagi, Shinichi Department of Electrical Engineering and Information Systems The University of Tokyo Tokyo Japan

ISBN: (纸本)9798350365429

This study investigates the physical mechanism of memory window (MW) narrowing in HZO/Si FeFETs, which is one of the most serious reliability issues, by introducing a new viewpoint focusing on hold voltage (VHold) and a novel measurement method that allows independent evaluation of polarization (P) and threshold voltage (VTH). We find that MW narrowing can be mitigated by adjusting VHold, indicating that MW narrowing is determined by increased densities of trapped electrons and holes, which cannot be de-trapped from generated traps during the hold condition. It is also found in the obtained VTH-P relationship that rapid generation of hole traps with stress cycles plays a key role in MW narrowing, while polarization switching does not change even for devices with no MW. It is shown that material engineering to suppress trap generation is effective for improving FeFET reliability. © 2024 IEEE.

关键词： Threshold voltage

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Application of non-isolated bidirectional DC-DC converters for renewable and sustainable energy systems:a review

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Clean Energy 2023年第2期7卷 293-311页

作者： Tole Sutikno Rizky Ajie Aprilianto Hendril Satrian Purnama Department of Electrical Engineering Universitas Ahmad DahlanYogyakartaIndonesia Embedded Systems and Power Electronics Research Group YogyakartaIndonesia Department of Electrical and Information Engineering Universitas Gadjah MadaYogyakartaIndonesia

The primary challenge in renewable-energy utilization is an energy-storage system involving its power *** systems have to promise high efficiency,reliability and ***,all of these can be realized at an economical *** and boost converters connected in parallel can convert power in both *** is the basic non-isolated bidirectional topology commonly used with energy-storage *** primary issue with the buck-boost non-isolated bidirectional converter is how to enhance its performance,so the modification involving this topology is still *** paper examines 29 proposed converters from 30 research publications published in the last 10 years,the most recent of which focuses on modified non-isolated bidirectional converters based on the buck-boost *** are classified into eight modification schemes,which involve adding new components or circuits to the base *** is evaluated against six parameters:the number of components,control complexity,power-rating applications,soft-switching ability,efficiency outcome and capacity to minimize ***,each modified non-isolated bidirectional converter was compared from the renewable-energy-based power-generation-source perspective *** on these studies,researchers might think of ways to improve the buck-boost converter by changing it to make a new non-isolated bidirectional converter that can be used in systems that need it.

关键词： buck-boost converter bidirectional converter renewable energy energy-storage systems power converter

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Online information-Based Product Evolution Course Mining and Prediction

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International Journal of information Technology and Decision Making 2024年第2期23卷 599-627页

作者： Chen, Yuh-Jen Chen, Yuh-Min Department of Accounting and Information Systems College of Business Intelligence National Kaohsiung University of Science and Technology Kaohsiung City Taiwan Institute of Manufacturing Information and Systems College of Electrical Engineering and Computer Science National Cheng Kung University Tainan City Taiwan

In today’s fiercely competitive business environment, product design and development play critical roles in an enterprise’s success;therefore, consumer demand must be understood. Enterprises used to understand their consumers’ demands through time-consuming questionnaire surveys and statistical analyses. As the Internet and the popularity of virtual communities have grown, more consumers are leaving comments about their perceptions of the appeal of products on online social media platforms, thus enabling enterprises to more objectively understand consumers’ product preferences and demands. Therefore, determining how to effectively assist enterprises in analyzing valuable information beneficial to product design and development that can be gleaned from the large amount of social media data available is critical to promoting an enterprise’s competitive advantage in the product market. However, previous studies have primarily focused on understanding consumer viewpoints of products through review articles or electronic word-of-mouth (eWOM;it is a common channel for spreading product appraisals) from online social media. For these review articles and eWOM that can imply consumer demand for product features, there were no relevant studies focused on analyzing consumer demand by using both online review articles and eWOM for product feature evolution. Therefore, for new product features, this study developed a mechanism for product evolution course mining from product-related review articles (such as product functions or specifications) and eWOM on online social media to realize the prediction of future product features or specifications, and then assist enterprises in rapidly and accurately grasping product development trends to effectively discern key reference information for product design and development. The study was achieved by (1) designing a process for online information-based product evolution course mining and prediction, (ii) developing techniques related to

关键词： Forecasting

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Medical Defense Nanorobots (MDNRs): a new evaluation and selection of controller criteria for improved disease diagnosis and patient safety using NARMA(L2)-FOP + D(ANFIS)^µ – Iλ-based Archimedes Optimization Algorithm

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International Journal of information Technology (Singapore) 2024年 1-11页

作者： Marhoon, Hamzah M. Basil, Noorulden Mohammed, Abdullah Fadhil Systems Engineering Department College of Information Engineering Al-Nahrain University Jadriya Baghdad Iraq Department of Electrical Engineering College of Engineering Mustansiriyah University Baghdad Iraq

This article addresses the complexity of optimizing movements in Medical Defense Nanorobots (MDNRs) by proposing a novel integration approach. The challenge lies in selecting the Archimedes Optimization Algorithm (AOA) for MDNR movements, considering specific criteria for fractional-order proportional-integral-derivative (FOPID) controller gains. To overcome this, the study introduces a three-phase approach: MDNR-based NARMA-L2 controller Pre-process and Identification, Enhancement of NARMA-L2 controller-based NARMA(L2)-FOP+D(ANFIS)^μ-I^λ, and Evaluation of FOPID criteria-based AOA. This approach integrates NARMA-L2 for criterion weighting and ANFIS for AOA selection, validated through NARMA(L2)-FOP+D(ANFIS)^μ-I^λ evaluation, showcasing the efficacy of the proposed methodology. © The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of computer Applications and Management 2024.

关键词： ANFIS Archimedes Optimization Algorithm Fractional order proportional integral derivative controller Medical Defense Nanorobots NARMA-L2 controller

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Energy-Efficient Secure Federated Learning for UAV Swarms 7

Energy-Efficient Secure Federated Learning for UAV Swarms

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7th International Conference on Energy Conservation and Efficiency, ICECE 2024

作者： Afzal, Muhammad Usman Abdellatif, Alaa Awad Information Technology University Electrical Engineering Department Qatar University Computer Science and Engineering Department Qatar

ISBN: (纸本)9798350370898

Unmanned Aerial Vehicles (UAVs) have been recently leveraged in massive amount of Internet of Things (IoT) applications. However, given the stringent limitations of UAVs, investigating their performance in terms of their energy efficiency, tasks accuracy, and security has gained much interest recently. In this paper, we study the deployment of Federated Learning (FL) within the UAV swarms, with the aim of avoiding data exchange between different swarm's members. Specifically, we propose a secure FL framework for UAV swarms, such that the energy efficiency is maximized, while enhancing the learning performance. The suggested approach takes into account the issue of data imbalance in FL in addition to the strict energy and security limits placed on the *** findings show how effective our framework is in terms of security, energy efficiency, and classification accuracy when compared to baseline systems that don't take security or data imbalance into account. © 2024 IEEE.

关键词： Energy efficiency

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Enhancing Renewable Energy Integration:A Gaussian-Bare-Bones Levy Cheetah Optimization Approach to Optimal Power Flow in electrical Networks

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computer Modeling in engineering & Sciences 2024年第8期140卷 1339-1370页

作者： Ali S.Alghamdi Mohamed A.Zohdy Saad Aldoihi Department of Electrical Engineering College of EngineeringMajmaah UniversityAl-Majmaah11952Saudi Arabia Electrical and Computer Engineering Department Oakland UniversityRochesterMI48309USA Institute of Earth and Space Science King Abdulaziz City for Science and Technology(KACST)Riyadh11442Saudi Arabia Computer Science and Systems Engineering Institute Polytechnique de ParisPalaiseau CedexFrance

In the contemporary era,the global expansion of electrical grids is propelled by various renewable energy sources(RESs).Efficient integration of stochastic RESs and optimal power flow(OPF)management are critical for network *** study introduces an innovative solution,the Gaussian Bare-Bones Levy Cheetah Optimizer(GBBLCO),addressing OPF challenges in power generation systems with stochastic *** primary objective is to minimize the total operating costs of RESs,considering four functions:overall operating costs,voltage deviation management,emissions reduction,voltage stability index(VSI)and power loss ***,a carbon tax is included in the objective function to reduce carbon *** scrutiny,using modified IEEE 30-bus and IEEE 118-bus systems,validates GBBLCO’s superior performance in achieving optimal *** results demonstrate GBBLCO’s efficacy in six optimization scenarios:total cost with valve point effects,total cost with emission and carbon tax,total cost with prohibited operating zones,active power loss optimization,voltage deviation optimization and enhancing voltage stability index(VSI).GBBLCO outperforms conventional techniques in each scenario,showcasing rapid convergence and superior solution ***,GBBLCO navigates complexities introduced by valve point effects,adapts to environmental constraints,optimizes costs while considering prohibited operating zones,minimizes active power losses,and optimizes voltage deviation by enhancing the voltage stability index(VSI)*** research significantly contributes to advancing OPF,emphasizing GBBLCO’s improved global search capabilities and ability to address challenges related to local *** emerges as a versatile and robust optimization tool for diverse challenges in power systems,offering a promising solution for the evolving needs of renewable energy-integrated power grids.

关键词： Renewable energy integration optimal power flow stochastic renewable energy sources gaussian-bare-bones levy cheetah optimizer electrical network optimization carbon tax optimization

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Parameters Estimation of Modified Triple Diode Model of PSCs Considering Charge Accumulations and Electric Field Effects Using Puma Optimizer

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computer Modeling in engineering & Sciences 2025年第4期143卷 723-745页

作者： Amlak Abaza Ragab A.El-Sehiemy Mona Gafar Ahmed Bayoumi Electrical Engineering Department Faculty of EngineeringKafrelsheikh UniversityKafrelsheikh33516Egypt Department of Computer Engineering and Information College of Engineering inWadi AlddawasirPrince Sattam Bin Abdulaziz UniversityKharj16278Saudi Arabia Machine Learning and Information Retrieval Department Artificial IntelligenceKafrelsheikh UniversityKafrelsheikh33516Egypt Electrical Department Faculty of Engineering and TechnologyBadr University in CairoBadr11829Egypt Physics and Mathematics Department Faculty of EngineeringKafrelsheikh UniversityKafrelsheikh33516Egypt College of Engineering Al-Ayen UniversityThi-Qar64001Iraq

Promoting the high penetration of renewable energies like photovoltaic(PV)systems has become an urgent issue for expanding modern power grids and has accomplished several challenges compared to existing distribution *** study measures the effectiveness of the Puma optimizer(PO)algorithm in parameter estimation of PSC(perovskite solar cells)dynamic models with hysteresis consideration considering the electric field effects on *** models used in this study will incorporate hysteresis effects to capture the time-dependent behavior of PSCs *** PO optimizes the proposed modified triple diode model(TDM)with a variable voltage capacitor and resistances(VVCARs)considering the hysteresis *** suggested PO algorithm contrasts with other wellknown optimizers from the literature to demonstrate its *** results emphasize that the PO realizes a lower RMSE(Root mean square errors),which proves its capability and efficacy in parameter extraction for the *** statistical results emphasize the efficiency and supremacy of the proposed PO compared to the other well-known competing *** convergence rates show good,fast,and stable convergence rates with lower RMSE via PO compared to the other five competitive ***,the lowermean realized via the PO optimizer is illustrated by the box plot for all optimizers.

关键词： Dynamic model of PSCs puma optimizer parameter estimation triple diode model

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A Fully LTPS-TFT-Based Bi-Directional Biomedical Interface Circuit for Large-Area Healthcare Applications

IEEE Journal on Flexible Electronics

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IEEE Journal on Flexible Electronics 2025年第12期3卷 526-532页

作者： Zhang, Hanbo Lou, Yuqing Zhang, Zhihang Li, Yongfu Rokhan, Fakhrul Wang, Guoxing Zhao, Jian Shanghai Jiao Tong University School of Electronic Information and Electrical Engineering Shanghai200240 China Universiti Putra Malaysia Faculty of Engineering Department of Computer and Communication System Engineering Selangor Serdang43400 Malaysia

This paper proposed a fully LTPS-TFT-based bi-directional biomedical pixel interface with integrated a high linearity stimulator and a high-performance bio-potential sensing front-end circuit to amplify and digitize biological signals for high robustness data transmission. All circuits are designed and manufactured under a 3-μm LTPS process. We demonstrated the experiment in saline using the stimulator circuit to simulate stimulation inside the organism, achieving stimulation with different average currents under different duty cycles. The proposed front-end circuit has a gain of 40 dB. The referred input voltage noise of the entire signal chain is 86.2 μV/√Hz, and the ENOB is 9.13 bits at an input of 0.5 mVPP. Simultaneously conducting statistical testing on 20 chips has achieved a 1.05 dB SNDR standard deviation. Finally, we use a function signal generator to simulate the input signals of ECoG, ECG, and EOG, then use front-end circuits to read and reconstruct them to demonstrate that the proposed pixel interface can correctly read common biomedical signals for healthcare applications. © 2022 IEEE.

关键词： Image segmentation

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Performance Improvement of Adaptive N-Square PS-QAM Based on LUT for Flexible Coherent PON

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Journal of Lightwave Technology 2025年第12期43卷 5569-5578页

作者： Lin, Gengming Zhu, Yixiao Yan, Zijun Cheng, Ziyu Zhuge, Qunbi Hu, Weisheng Shanghai Jiao Tong University State Key Lab of Advanced Optical Communication Systems and Networks School of Electronic Information and Electrical Engineering Department of Electronic Engineering Shanghai200240 China

Flexible coherent passive optical network (PON) is recognized as an advanced capacity optimization strategy for beyond 100G PON due to its flexibility and adaptability, which are pivotal for the evolution of high-capacity optical access networks. In this study, we propose an adaptive N-square QAM scheme compatible with probabilistic shaping (PS), enabling a more continuous variation of shaping entropy compared to standard 2M-QAM shaping scheme and improved frequency offset estimation (FOE) accuracy in blind 4th-power Fast-Fourier-transform (FFT) algorithm. In experimental demonstrations, dynamic-range and data-rate product (DRDRP) of uniform N2-QAM surpasses that of uniform 2M-QAM by 86 dB·Gbps. The DRDRP of PS N2-QAM also outperforms that of PS 2N-QAM by around 41 dB·Gbps. The development of PON optimization scheme for multi-carrier transmission is achieved through the generation of a look-up table (LUT) based on channel signal-to-noise ratio (SNR) conditions. The feasibility of the LUT is demonstrated under different super-Gaussian filter parameter settings at the back-to-back (B2B) scenario. After 20-km standard single-mode fiber (SSMF) transmission, the normalized generalized mutual information (NGMI) is greater than 0.985 across four subcarriers with varying received optical power (ROP) from -16 to -11 dBm. © 2025 IEEE.

关键词： Single mode fibers

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