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2024 IEEE International Conference on Recent Advances in science and engineering technology, ICRASET 2024

作者： Rekha, V. Sharmila, N. Komala, M. Pavithra, G.S. Mallikarjunaswamy, S. Naveen, K.B. Shilpa, M. Sheela, S. Department of Computer Science and Engineering Bangalore India Jss Science and Technology University Dept of Electronics and Electrical Engineering Mysuru India Sjb Institute of Technology Dept of Electronics and Communication Engineering Bengaluru India Jss Academy of Technical Eduction Dept of Computer Science and Engineering Bengaluru India Jss Academy of Technical Eduction Dept of Electronics and Communication Engineering Bengaluru India Bgs Institute of Technology Adichunchanagiri University Dept of Electronics and Electrical Engineering BG Nagara India Bengaluru Institute of Technology Dept of Information Science and Engineering Bengaluru India Global Academy of Technology Dept of Computer Sceinec and Engineering Bengaluru India

ISBN: (纸本)9798350388602

The integration of renewable energy sources into smart grids requires advanced management systems to optimize energy production, storage, and distribution. Conventional methods like Static Energy Allocation (SEA) and Rule-Based Control (RBC) struggle with real-time adaptability, leading to inefficiencies in handling the variable nature of renewable energy. SEA and RBC lack the predictive capabilities needed to effectively manage dynamic energy generation, resulting in increased energy losses and operational *** paper proposes a Hybrid Edge-Cloud Renewable Energy Management System (HECREMS) using Deep Learning with Predictive Analytics (DLPA). HECREMS integrates edge computing for real-time data processing with cloud computing for enhanced predictive analytics, providing a robust framework for efficient energy management. The proposed system leverages the low latency of edge devices and the computational power of the cloud to improve energy forecasting and decision-making. HECREMS outperforms traditional SEA and RBC methods, achieving a 0.25% improvement in energy utilization efficiency, a 0.20% reduction in operational costs, and a 0.30% increase in system responsiveness. By addressing the drawbacks of conventional approaches, HECREMS demonstrates significant advancements in the efficient and sustainable management of renewable energy within smart grids. © 2024 IEEE.

关键词： Cloud analytics

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Transferable Deep Reinforce Learning With Limited Target Data 21

Transferable Deep Reinforce Learning With Limited Target Dat...

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21st International computer Conference on Wavelet Active Media technology and Information Processing, ICCWAMTIP 2024

作者： Xiaoqin, Liang Xingyu, Chen Zheng, Wang Wenyi, Xu Shijiao, Han School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu611731 China School of Computer Science and Technology Chongqing University of Posts and Telecommunications Chongqing400065 China Chengdu Aircraft Design and Research Institude Chengdu610091 China School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Chengdu611731 China

ISBN: (纸本)9798331519254

While there has been significant progress in the application of transfer learning within reinforcement learning, most existing research primarily focuses on online reinforcement learning, with few studies addressing the optimization of offline reinforcement learning. This paper proposes a novel transferable deep reinforcement learning method designed to enhance limited offline samples in the target domain by utilizing online interactive samples from a similar source domain. The method is versatile and can be integrated with any offline reinforcement learning algorithm. To validate its effectiveness, extensive evaluations were conducted across multiple Mujoco environments and D4RL datasets. The results indicate that by employing the proposed method, the algorithm's performance can approach that of using 100% of the target domain data, even when only 10% of the data is available. © 2024 IEEE.

关键词： Adversarial machine learning

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Improved Soil Quality Prediction Model Using Deep Learning for Smart Agriculture Systems

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computer Systems science & engineering 2023年第5期45卷 1545-1559页

作者： P.Sumathi V.V.Karthikeyan M.S.Kavitha S.Karthik Department of Information Technology SNS College of EngineeringCoimbatoreTamilnaduIndia Department of Electrical and Electronics Engineering SNS College of TechnologyCoimbatoreTamilnaduIndia Department of Computer Science&Engineering SNS College of TechnologyCoimbatoreTamilnaduIndia

Soil is the major source of infinite lives on Earth and the quality of soil plays significant role on Agriculture practices all ***,the evaluation of soil quality is very important for determining the amount of nutrients that the soil require for proper *** present decade,the application of deep learning models in many fields of research has created greater *** increasing soil data availability of soil data there is a greater demand for the remotely avail open source model,leads to the incorporation of deep learning method to predict the soil *** that concern,this paper proposes a novel model called Improved Soil Quality Prediction Model using Deep Learning(ISQP-DL).The work considers the chemical,physical and biological factors of soil in particular area to estimate the soil ***,pH rating of soil samples has been collected from the soil testing laboratory from which the acidic range has been categorized through soil test and the same data has been taken as input to the Deep Neural Network Regression(DNNR)***,soil nutrient data has been given as second input to the DNNR *** utilizing this data set,the DNNR method is used to evaluate the fertility rate by which the soil quality has been *** training and testing,the model uses Deep Neural Network Regression(DNNR),by utilizing the *** results show that the proposed model is effective for SQP(Soil Quality Prediction Model)with efficient good fitting and generality is enhanced with input features with higher rate of classification *** results show that the proposed model achieves 96.7%of accuracy rate compared with existing models.

关键词： Soil quality classification accuracy deep learning neural network soil features training and testing

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A Load Insensitive Model Predictive Control for a Three-phase Inverter with L-C Filter

A Load Insensitive Model Predictive Control for a Three-phas...

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2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Zeng, Jianwu Kim, Taesic Winstead, Vincent Minnesota State University Department of Electrical and Computer Engineering and Technology MankatoMN56001 United States University of Missouri Department of Electrical Engineering and Computer Science ColumbiaMO65201 United States

ISBN: (纸本)9798350376067

The traditional model predictive control (MPC) for power inverters is designed upon a certain operating point and is solved with quadratic programming (QP). The performance may deteriorate under variations of converter parameters or the load. This paper proposes a load-insensitive MPC (LI-MPC) for a three-phase inverter. The load current is first estimated from the current and voltage measured from the L-C filter, then the optimization problem is online solved with the gradient descent (GD) method, which makes the solution insensitive to the parameter's variation in the power converter. Experiment results show that the LI-MPC not only has a lower and more stable total harmonic distortion value than the QP-MPC, but has a small voltage tracking error as well. Therefore, the proposed LI-MPC can achieve better power quality than the traditional MPC. © 2024 IEEE.

关键词： Predictive control systems

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Broadband single-polarization single-mode low confinement loss hollow core anti-resonant fiber with semi-elliptical nested tube

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Optical and Quantum Electronics 2025年第4期57卷 1-12页

作者： Lin, Wen Fei, Yihong Wang, Ning Jia, Hongzhi Engineering Research Center of Optical Instruments and Systems Ministry of Education Shanghai Key Laboratory of Modern Optical Systems School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai200093 China

In this paper, a hollow-core anti-resonant optical fibre containing a semi-elliptical nested tube is proposed, which has the characteristics of single-polarization, large bandwidth, single-mode and low confinement loss. By optimizing the structural design, the polarization extinction ratio (PER) of the fiber reaches 21,0183 at a wavelength of 1.55 μm, and the y-polarized fundamental mode loss is only 0.00086 dB/m. By changing the material and thickness of the semi-ellipsoidal nested tube, a large bandwidth of 280 nm was achieved in the wavelength range of 1.51-1.78 μm, with loss limited to less than 0.001 dB/m within the bandwidth range. The PER and higher-order mode extinction ratio of 4870, 1487, respectively. The loss remains below 0.01 dB/m when the bending radius exceeds 4.5 cm. Therefore, it is expected that this optical fiber can be used in optical devices such as fiber optic sensors, fiber optic lasers and fiber optic gyroscopes. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2025.

关键词： Single mode fibers

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A Dual-Polarized Beam-Steerable Antenna Utilizing Complementary Reconfigurable Parasitic Elements

A Dual-Polarized Beam-Steerable Antenna Utilizing Complement...

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2023 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio science Meeting, AP-S/URSI 2023

作者： Zhang, Yujie Tang, Shiwen Rao, Junhui Chiu, Chi-Yuk Murch, Ross The Hong Kong University of Science and Technology Department of Electrical and Computer Engineering Kowloon Hong Kong

ISBN: (纸本)9781665442282

A new dual-port reconfigurable antenna design with both polarization and pattern diversity is described. For each polarization, beam-steerable function can be realized in the same steering range by utilizing two pairs of complementary reconfigurable parasitic elements. Four RF switches are located on these parasitic elements to provide reconfiguration. The bandwidth for each port is 3.4-3.8 GHz with more than 20 dB port isolation for all reconfigurable states. This reconfigurable antenna can be utilized in multiple wireless communication or sensing scenarios to provide performance gains. © 2023 IEEE.

关键词： Steerable antennas

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Transcriptomic and Macroscopic Architectures of Multimodal Covariance Network Reveal Molecular–Structural–Functional Co-alterations

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Research 2024年第1期2023卷 471-487页

作者： Lin Jiang Yueheng Peng Runyang He Qingqing Yang Chanlin Yi Yuqin Li Bin Zhu Yajing Si Tao Zhang Bharat B.Biswal Dezhong Yao Lan Xiong Fali Li Peng Xu The Clinical Hospital of Chengdu Brain Science Institute MOE Key Lab for NeuroinformationUniversity of Electronic Science and Technology of ChinaChengdu 611731China School of Life Science and Technology Center for Information in BioMedicineUniversity of Electronic Science and Technology of ChinaChengdu 611731China School of Psychology Xinxiang Medical UniversityXinxiang 453003China School of Science Xihua UniversityChengdu 610039China Department of Biomedical Engineering New Jersey Institute of TechnologyNewarkNJUSA School of Electrical Engineering Zhengzhou UniversityZhengzhou 450001China Research Unit of NeuroInformation Chinese Academy of Medical Sciences2019RU035ChengduChina Montreal Neurological Institute and Hospital McGill UniversityMontrealQCCanada Department of Electrical and Computer Engineering Faculty of Science and TechnologyUniversity of MacaoMacaoChina Radiation Oncology Key Laboratory of Sichuan Province 610041 ChengduChina Rehabilitation Center Qilu Hospital of Shandong UniversityJinan 250012China

Human cognition is usually underpinned by intrinsic structure and functional neural co-activation in spatially distributed brain *** to lacking an effective approach to quantifying the covarying of structure and functional responses,how the structural–functional circuits interact and how genes encode the relationships,to deepen our knowledge of human cognition and disease,are still ***,we propose a multimodal covariance network(MCN)construction approach to capture interregional covarying of the structural skeleton and transient functional activities for a single *** further explored the potential association between brain-wide gene expression patterns and structural–functional covarying in individuals involved in a gambling task and individuals with major depression disorder(MDD),adopting multimodal data from a publicly available human brain transcriptomic atlas and 2 independent *** analysis showed a replicable cortical structural–functional fine map in healthy individuals,and the expression of cognition-and disease phenotype-related genes was found to be spatially correlated with the corresponding MCN *** analysis of cell type-specific signature genes suggests that the excitatory and inhibitory neuron transcriptomic changes could account for most of the observed correlation with task-evoked MCN differences.

关键词： alterations evoked spatially

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Impact of Parametric Uncertainties on the Steady-State Performances of DFIG-Based WECS 10th

Impact of Parametric Uncertainties on the Steady-State Perfo...

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10th EAI International Conference on Advancements of science and technology, EAI ICAST 2022

作者： Ayenew, Endalew Biru, Getachew Mulatu, Asrat Berhanu, Milkias Electrical Power and Control Engineering School of Electrical Engineering and Computing Adama Science and Technology University Adama Ethiopia School of Electrical and Computer Engineering Addis Ababa Institute of Technology Addis Ababa University Addis Ababa Ethiopia Center of Excellence for Sustainable Energy College of Electrical and Mechanical Engineering Addis Ababa Science and Technology University Addis Ababa Ethiopia

ISBN: (纸本)9783031411724

This chapter presents the study carried out to discover uncertain parameters in a model of a doubly-fed induction generator (DFIG)-based wind energy conversion system (WECS) and to investigate their effects on WECS plant while harvesting energy from wind at varying speeds. This is carried out by analytically formulating the steady-state models of a DFIG-based WECS and computing the parameters of these models at different wind speeds that drive wind turbines at rotor speed from sub-synchronous to super-synchronous. The main uncertain parameters in this system are the mutual reactances between stator and rotor windings, and the reactance of rotor winding. These variations happen due to the varying wind speed. The effect of parametric uncertainties on the steady-state performances of DFIG-based WECS is examined. The results depicted that the steady-state performances of DFIG-based WECS are influenced by uncertain phenomena. Typically a 0.5% change in mutual reactances caused up to 10 kW change in the generator output power. Mainly, it causes instability in the performances of the DFIG-based WECS and slightly reduces overall efficiency at a higher value of the wind speed. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： DFIG-based WECS HAWT Performances of WECS Uncertain parameter

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COVID-19 on YouTube: A Data-Driven Analysis of Sentiment, Toxicity, and Content Recommendations 15

COVID-19 on YouTube: A Data-Driven Analysis of Sentiment, To...

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15th IEEE Annual Computing and Communication Workshop and Conference, CCWC 2025

作者： Su, Vanessa Thakur, Nirmalya Emory University Department of Computer Science AtlantaGA30322 United States South Dakota School of Mines and Technology Department of Electrical Engineering and Computer Science Rapid CitySD57701 United States

ISBN: (纸本)9798331507695

This study presents a data-driven analysis of COVID-19 discourse on YouTube, examining the sentiment, toxicity, and thematic patterns of video content published between January 2023 and October 2024. The analysis involved applying advanced natural language processing (NLP) techniques: sentiment analysis with VADER, toxicity detection with Detoxify, and topic modeling using Latent Dirichlet Allocation (LDA). The sentiment analysis revealed that 49.32% of video descriptions were positive, 36.63% were neutral, and 14.05% were negative, indicating a generally informative and supportive tone in pandemic-related content. Toxicity analysis identified only 0.91% of content as toxic, suggesting minimal exposure to toxic content. Topic modeling revealed two main themes, with 66.74% of the videos covering general health information and pandemic-related impacts and 33.26% focused on news and real-time updates, highlighting the dual informational role of YouTube. A recommendation system was also developed using TF-IDF vectorization and cosine similarity, refined by sentiment, toxicity, and topic filters to ensure relevant and context-aligned video recommendations. This system achieved 69% aggregate coverage, with monthly coverage rates consistently above 85%, demonstrating robust performance and adaptability over time. Evaluation across recommendation sizes showed coverage reaching 69% for five video recommendations and 79% for ten video recommendations per video. In summary, this work presents a framework for understanding COVID-19 discourse on YouTube and a recommendation system that supports user engagement while promoting responsible and relevant content related to COVID-19. © 2025 IEEE.

关键词： Video analysis

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Blockchain Based Enhanced ERP Transaction Integrity Architecture and PoET Consensus

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computers, Materials & Continua 2022年第1期70卷 1089-1109页

作者： Tehreem Aslam Ayesha Maqbool Maham Akhtar Alina Mirza Muhammad Anees Khan Wazir Zada Khan Shadab Alam Department of Computer Engineering National University of Sciences and TechnologyIslamabad44000Pakistan Department of Electrical Engineering National University of Sciences and TechnologyIslamabad44000Pakistan Department of Management Studies Bahria Business SchoolIslamabad44000Pakistan Department of Computer Science Capital University of Science and TechnologyIslamabad44000Pakistan Department of Computer Science College of Computer Science and ITJazan UniversityJazan67714Saudi Arabia

Enterprise Resource Planning(ERP)software is extensively used for the management of business *** offers a system of integrated applications with a shared central *** all business-critical information in a central place raises various issues such as data integrity assurance and a single point of failure,which makes the database *** paper investigates database and Blockchain integration,where the Blockchain network works in synchronization with the database system,and offers a mechanism to validate the transactions and ensure data *** research exists on Blockchain-based solutions for the single point of failure in *** established in our study that for concurrent access control andmonitoring of ERP,private permissioned Blockchain using Proof of Elapsed Time consensus is more *** study also investigated the bottleneck issue of transaction processing rates(TPR)of Blockchain consensus,specifically ERP’s *** paper presents systemarchitecture that integrates Blockchain with an ERP system using an application interface.

关键词： Transaction security enterprise systems blockchain transaction integrity hyperledger sawtooth PoET consensus

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