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1st International Conference on Innovative engineering Sciences and Technological Research, ICIESTR 2024

作者： Channa, Irfan Ali Li, Dazi Dahri, Fida Hussain Abro, Ghulam E. Mustafa Zahid, Faizan University of Chemical Technology Institute of Automation Beijing Beijing100069 China Southeast University School of Computer Science and Engineering Nanjing China Saudi Arabia University of Catania Department of Electrical Electronic and Computer Engineering Italy

ISBN: (纸本)9798350348637

Distributed generation based on photo-voltaic (PV) modules play a vital role to provide continuous power supply for consumers. Power quality (PQ) events caused by integration of distributed energy sources in microgrids (MG) deteriorate the operation of distribution and utility of power supply. In this work, a new CNN-LSTM based deep learning approach is proposed to identify power quality disturbances (PQDs) in PV-integrated microgrid. In a proposed framework, full closed-loop neural architecture containing different layers to facilitate automatic feature extraction and long-time short memory (LSTM) network provide temporal feature for intelligent classifier to improve the training speed. Moreover, comparison with other deep neural networks proves that proposed approach can simplify the procedure of PQ problems with the conventional signal analysis and feature selection methods. A typical PV-integrated microgid is simulated on PSCAD software to prove the robustness of classifier for classification of PQDs in renewable energy integrated distribution networks. © 2024 IEEE.

关键词： Microgrids

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Dual-Class Leader-Following Modeling for Collective Motion of Multi-Agent systems 43

Dual-Class Leader-Following Modeling for Collective Motion o...

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43rd Chinese Control Conference, CCC 2024

作者： Zhang, Bo Li, Haoqi Meng, Bin Hu, Jiangping Ghosh, Bijoy Kumar Beijing Institute of Control Engineering Beijing100080 China University of Electronic Science and Technology of China School of Automation Engineering Chengdu611731 China University of Electronic Science and Technology of China Huzhou313000 China Texas Tech University Department of Mathematics and Statistics LubbockTX79409 United States

ISBN: (纸本)9789887581581

Leader-follower collective motion is a key multi-agent network application. However, conventional methods struggle with high dynamics or communication interferences and fail to maintain consistent motion. To address this issue, a resilient dual-class cooperative following (DCCF) model is proposed. This model uses two movement strategies for the different follower categories. Leader-connected followers use a single-tracking control based on velocity or direction, whereas leader-disjoint followers employ a modified relative speed for single tracking. The DCCF model may be more suitable for practical use than existing ones. Simulations under degraded conditions demonstrate its superior tracking performance and robustness over traditional methods. © 2024 Technical Committee on Control Theory, Chinese Association of automation.

关键词： collective motion dual-class cooperative following leader-follower tracking Multi-agent network

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Enhanced Grid Integration of PV systems Using Double-Stage Configuration and PUC7 Inverter Controlled by MPC

Enhanced Grid Integration of PV Systems Using Double-Stage C...

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International Conference on Artificial Intelligence in Renewable Energetic systems, IC-AIRES 2024

作者： Khettab, Soufian Kheldoun, Aissa Bradai, Rafik Hattabi, Intissar SET Laboratory Blida 1 University Faculty of Technology Automation and Electrical Engineering Department Blida09000 Algeria Laboratory of Signals and Systems Institute of Electrical and Electronic Engineering University M’hamed Bougara Boumerdes35000 Algeria LATSI Blida 1 University Faculty of Technology Electronics Department Blida09000 Algeria

ISBN: (纸本)9783031803000

The paper introduces a double-stage, single-phase photovoltaic (PV) system connected to the grid using a packed U-cell seven-level (PUC7) inverter, governed by Model Predictive Control (MPC). This system aims to optimize grid integration by achieving enhanced current injection with minimal Total Harmonic Distortion (THD), reactive power compensation, and efficient extraction and injection of maximum power from the PV source. Simulation results underscore the efficacy of the proposed control strategy in enhancing power quality, responsiveness, and accuracy across varying weather conditions, thereby validating the feasibility and robustness of the proposed PV system. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Predictive control systems

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An Effective Machine Learning Approach with Hyperparameter Tuning for Sentiment Analysis

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Data Intelligence 2025年第1期7卷 70-94页

作者： Saima Kanwal Ali Raza Chunyan Bai Dawei Zhang Jing Wen Dileep Kumar Engineering Research Centre of Optical Instrument and Systems Ministry of Education and Shanghai Key Lab of Modern Optical SystemUniversity of Shanghai for Science and TechnologyNo.516 Jun Gong RoadShanghai 200093China Department of Mathematics School of SciencesHebei University of TechnologyBeichen CampusTianjin 300401China Shanghai Publishing and Printing College Shanghai 200093China Zhangjiang Laboratory Shanghai 200120China Department of Electronic Engineering Faculty of EngineeringThe Islamia University of Bahawalpur63100PunjabPakistan

Sentiment analysis depends on individuals’comments and opinions on *** from social media platforms like Twitter,Quora,or Facebook poses challenges due to informal language,including acronyms,misspellings,and ambiguous ***,hyperparameters in machine learning models significantly impact *** address these issues,we propose advanced feature engineering techniques in Natural Language Processing(NLP)and hyperparameter optimization to enhance prediction accuracy and generalization *** study employs Naïve Bayes,Logistic Regression(LR),Multi-layer Perceptron(MLP),and Support Vector Machine(SVM)to classify sentiments in tweets about Elon Musk’s potential acquisition of *** dataset,consisting of 100,000 tweets,is fetched using the Twitter representational state transfer application programming interface(REST API).We outline a sentiment analysis procedure to classify unstructured Twitter data,identify influential keywords,and categorize sentiments as Positive,Negative,or *** a hybrid Lexicon NLP approach,we extract contextually significant emotionally charged words and assign sentiment *** optimization via automated search methods ensures alignment with classifier performance *** achieved an impressive accuracy rate of 97%.Cross-validation minimizes random variations,providing a reliable assessment of the model’s generalization capabilities,and demonstrating the method’s accuracy in predicting sentiments with larger new unseen standard datasets,and varying sentiment.

关键词： Hybrid lexicon Logistic regression(LR) Machine learning Natural language processing(NLP)

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Robust Pose Graph Optimization Using Two-stage Initialization and Covariance Matrix Rescaling Algorithm

Robust Pose Graph Optimization Using Two-stage Initializatio...

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2024 China automation Congress, CAC 2024

作者： Feng, Yuxuan Liu, Ziming Cui, Jimqiang Fang, Hao School of Electronic and Information Engineering Tongji University Shanghai China School of Automation Beijing Institute of Technology Beijing China Department of Strategic and intersecting Frontiers Peng Cheng Laboratory Shenzhen China

ISBN: (纸本)9798350368604

The back-end module of Simultaneous Localization and Mapping (SLAM) involves solving a nonlinear Pose Graph Optimization (PGO) problem. Typically, back-end optimization algorithms for SLAM require a good initial pose, followed by gradient-based optimization techniques such as Gauss-Newton (GN). However, in environments with outliers, these algorithms often struggle with poor initial values. To address this issue, this paper proposes a robust pose optimization algorithm. First, we begin pose initialization algorithms based on a two-stage least squares method with Tukey's Biweight kernel function. Then, we use covariance matrix rescaling algorithm, which add an adaptive constraint factor to robustly adjust the weight of each measurement, conduct iterative optimization, and verify their robustness and convergence. Experimental evaluations using both synthetic and real-world datasets in 2D and 3D environments demonstrate that this robust method handles outlier loop-closures with greater effectiveness and reliability compared to state-of-art techniques. © 2024 IEEE.

关键词： Graph algorithms

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HNN-Transformer Integrated Network for Estimating Robot Position 23

HNN-Transformer Integrated Network for Estimating Robot Posi...

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23rd International Conference on Control, automation and systems, ICCAS 2023

作者： Kang, Chang Ho Kim, Sun Young Kumoh National Institute of Technology Department of Mechanical System Engineering Department of Aeronautics Mechanical and Electronic Convergence Engineering Gumi39177 Korea Republic of School of Mechanical Engineering Kunsan National University Gunsan54150 Korea Republic of

ISBN: (纸本)9788993215274

This paper proposes a novel model architecture, the Hamiltonian neural network (HNN)-Transformer, which capitalizes on the strengths of both Hamiltonian neural networks and Transformers to effectively model and predict the behavior of physical systems. The proposed structure is designed to solve the problem that arises over time when predicting the state of a 2D robotic system. The HNN component of our model makes it possible to incorporate known physical laws into the learning process, while the Transformer component enables effective processing of sequentially input data. The performance of the proposed method was confirmed through simulation, and it was confirmed that this novel model is possible to leverage the strengths of both HNNs and Transformers to achieve improved performance than the existing independent HNN and Transformer on the challenging task, respectively. This suggests that the integration of physical understanding and sequence processing is a promising direction for modeling complex dynamic systems. © 2023 ICROS.

关键词： Hamiltonians

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Development and modeling of advanced systems Na2SnBr6-based perovskite solar cells: a comprehensive study on electron transport layers

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Optics Express 2025年第10期33卷 21152-21172页

作者： Roy, Dipta Reza, M.D. Selim Ghosh, Avijit Roy, Anup Kumar Chowdhury, Bivash Ranjan Aktarujjaman, M.D. Alrafai, H.A. Hassan, Abeer A. Department of Electrical and Computer Engineering California State University at Northridge NorthridgeCA91330 United States Department of Electrical and Electronic Engineering Begum Rokeya University Rangpur5400 Bangladesh Phillip M. Drayer Department of Electrical and Computer Engineering Lamar University BeaumontTX77710 United States Department of Management Information System International American University Los AngelesCA90010 United States Department of Information Technology Management Webster University St. LouisMO63119 United States Department of Chemistry Faculty of Science King Khalid University PO Box 9004 Abha61413 Saudi Arabia

This study simulates a n-i-p planar heterojunction for Na2SnBr6-based perovskite solar cells (PSCs), with Na2SnBr6 as the absorber layer, fluorine-doped tin oxide (FTO) as the substrate, and In2S3, IGZO, and SnS2 as electron transport layers (ETLs). Gold (Au) is used as the back contact. Na2SnBr6 was chosen for its low cost, non-toxicity, tunable band gap, excellent electrical properties, and stability. The SCAPS-1D simulator was employed to model the solar cell performance under AM 1.5 G light irradiation, focusing on factors like doping concentration, layer thickness, defect density, and interface defects across three device configurations: Device I (Au/Na2SnBr6/ In2S3/FTO/Al), Device II (Au/ Na2SnBr6/IGZO/FTO/Al), and Device III (Au/ Na2SnBr6/SnS2/FTO/Al). Device III achieved the highest PCE of 31.35%, FF of 85.95%, VOC of 0.7926 V, and JSC of 46.01 mA/cm22, making it a promising candidate for high-efficiency, lead-free perovskite solar cells. Devices I and II showed lower efficiencies of 27.47% and 30.98%, respectively. The study also analyzed quantum efficiency (QE), carrier dynamics, and recombination rates, highlighting the potential of Device III in advancing Na2SnBr6-based hybrid perovskite solar technologies for future solar energy applications. © 2025 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： Semiconductor doping

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Reseed Skipping of Linear Congruential Generator for Multi-level Image Steganography Security of Financial Data

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SN Computer Science 2023年第2期4卷 124页

作者： Danso, Juliana Mantebea Missah, Yaw Marfo Gyamfi, Enoch Opanin Dankwa, Stephen Kwabena, Sarpong Department of Computer Science Kwame Nkrumah University of Science and Technology (KNUST) Kumasi Ghana School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu China Department of Cyber Security and Computer Engineering Technology School of Computing and Information Sciences C.K. Tedam University of Technology and Applied Sciences Upper East Region Navrongo Ghana School of Automation Engineering University of Electronic Science and Technology of China Chengdu China

This paper proposed a multi-level image steganography model that integrates with image and plaintext encryption schemes. The model starts by partitioning the cover-image pixel positions into two regions of respective purposes, one is reserved to hold the data, and through the implementation of the dynamic difference expansion principle, the other sloughs some parts to the reserved region in responsive to the size of the data to embed. Continuously reseeding and initializing the parameter values of a Linear Congruential Generator (LCG), generate a set of random pixel positions as members of the reserved region. Before data embedding, the region reserved to hold the data as well as the data bits to embed, are then encrypted using AES with respective keys. Encryption keys are randomly generated using a Cryptographically Secure Pseudo-Random Number Generator (CSPRNG), the Fortuna algorithm. Multiplex security nature of using a randomization generator to reserve image region for encryption and encrypting plaintext data before performing steganography still ensures stability in computational complexities better than a logarithmic O(n log n). A visual inspection by evaluators who made 3000 choices to correctly differentiate stego images from its cover-images shows that only 47 choices were correct, 1884 choices were wrong, while 1069 choices were uncertain. An experiment shows an average Embedding Rates (ERs) of 0.00109 bpp and an average PSNR of 72. This concludes, as our integrated steganography and image encryption which implements the dynamic difference expansion principle, outputs encrypted stego mages that can deceive the naked human eyes into identifying them as rather cover-images, its embedding rate is faster (i.e. ER < 0.1), suitably good, and ensures better imperceptibility of cover-image alterations. When comparing these experimental results with existing methods, our proposed model shows significant competitiveness. We even show real-life scenarios on how this

关键词： AES encryption scheme Dynamic difference expansion principle Linear congruential generator Pseudo-random number generator Reserving room before encryption Steganography

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3D Gyroscope Wi-Fi for Robot Application with Modbus

3D Gyroscope Wi-Fi for Robot Application with Modbus

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International Conference on Control, automation and systems ( ICCAS)

作者： Anan Wongjan Rujipan Kosarat Department of Electronic Engineering and Automation Control System Faculty of Engineering Rajamangala University of Technology Lanna Chiang Mai Thailand Department of Software Engineering Faculty of Engineering Rajamangala University of Technology Lanna Chiang Mai Thailand

ISBN: (数字)9788993215380

ISBN: (纸本)9798331517939

This article aims to propose an algorithm for operating a robot gyroscope application. A gyroscope, an instrument for measuring and maintaining direction, utilizes the concept of angular momentum. The hardware architecture utilizes the GY-85 sensor modules, the ESP-32, and the OLED to accomplish communication with other linked devices. I will refer to it as the 3D gyroscope. It is possible for this gadget to function in conjunction with any kind of gyroscope or robot of any kind. For determining the values of acceleration and gravity, the application makes use of the x, y, and z axes. To communication between the devices, the algorithm makes use of the Modbus protocol for communication between the devices. You can use LabView to develop a testable gyroscope application. We rotated the constructed three-dimensional gyroscope at angles of 0 degrees, 45 degrees, and -45 degrees along the x, y, and z axes to test the results. The rotating process produced a multi-perspective, three-dimensional presentation of the constructed or developed device. Theta values in the x, y, and z axes that come from the experimental findings for angles of 45, -45, and 0 are extremely accurate.

关键词： Three-dimensional displays Protocols Instruments Organic light emitting diodes Robot sensing systems Control systems Hardware Gyroscopes Wireless fidelity Gravity

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Operando chemo-mechanical evolution in LiNi0.8Co0.1Mn0.1O2 cathodes

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National Science Review 2024年第9期11卷 253-263页

作者： Yi Zhang Shuaipeng Hao Fei Pei Xiangpeng Xiao Chang Lu Xing Lin Zhe Li Haijin Ji Yue Shen Lixia Yuan Zhen Li Yunhui Huang State Key Laboratory of Material Processing and Die & Mould Technology School of Materials Science and EngineeringHuazhong University of Science and Technology School of Optical and Electronic Information National Engineering Laboratory for Next Generation Internet Access SystemWuhan National Laboratory for OptoelectronicsHuazhong University of Science and Technology Gatan Inc.& EDAX LLC. AMETEK Commercial Enterprise (Shanghai)Co. Ltd.Pilot Free Trade Zone Department of Physics The Chinese University of Hong Kong

Ni-rich LiNixCoyMnzO2（NCMxyz,x+y+z=1,x≥0.8） layered oxide materials are considered the main cathode materials for high-energy-density Li-ion ***,the endless cracking of polycrystalline NCM materials caused by stress accelerates the loss of active materials and electrolyte decomposition,limiting the cycle ***,understanding the chemo-mechanical evolution during（de）lithiation of NCM materials is crucial to performance *** this work,an optical fiber with με resolution is designed to in operando detect the stress evolution of a polycrystalline LiNi0.8Co0.1Mn0.1O2（P-NCM811） cathode during *** integrating the sensor inside the cathode,the stress variation of P-NCM811 is completely transferred to the optical *** find that the anisotropy of primary particles leads to the appearance of structural stress,inducing the formation of microcracks in polycrystalline particles,which is the main reason for capacity *** isotropy of primary particles reduces the structural stress of polycrystalline particles,eliminating the generation of ***,the P-NCM811 with an ordered arrangement structure delivered high electrochemical performance with capacity retention of 82% over 500 *** work provides a brand-new perspective with regard to understanding the operando chemo-mechanical evolution of NCM materials during battery operation,and guides the design of electrode materials for rechargeable batteries.

关键词： Ni-rich layered oxide cathode in operando stress monitoring polycrystalline chemo-mechanical evolution

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