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Enhanced Performance in PMSG-Based Wind Turbine systems: Experimental Validation of Adaptive Backstepping Control Design

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Energies 2023年第22期16卷 7481页

作者： Mourabit, Youness El Salime, Hassna Bossoufi, Badre Motahhir, Saad Derouich, Aziz Mobayen, Saleh Zhilenkov, Anton National School of Applied Sciences Abdelmalek Essaadi University Tetouan93000 Morocco LISTA Laboratory Faculty of Science Dhar El Mahraz-USMBA Fez30000 Morocco Engineering Systems and Applications Laboratory ENSA USMBA Fez30000 Morocco Industrial Technologies and Services Laboratory Higher School of Technology Sidi Mohamed Ben Abdellah University Fez30000 Morocco Graduate School of Intelligent Data Science National Yunlin University of Science and Technology 123 University Road Section 3 Yunlin Douliou640301 Taiwan Department of Cyber-Physical Systems St. Petersburg State Marine Technical University Saint-Petersburg190121 Russia

Ensuring the quality and stability of the electrical grid is of utmost importance during the phase of electrical energy production. As wind energy plays an increasingly significant role in a country’s energy composition, maintaining stability and optimal quality has emerged as a prerequisite for the generated electricity. This article aims to devise a dynamic nonlinear algorithm that can be implemented in the wind energy conversion system (WECS) featuring a direct-drive permanent magnet synchronous generator (PMSG). Notably, the adaptive backstepping control relies on the nonlinear model of the controlled system. It harnesses the principles of the Lyapunov stability theory to regulate various parameters and uphold the overall system’s stability. Employing simulation analysis through the Matlab–Simulink environment, the proposed control strategy is evaluated using a 1.5 MW wind turbine. The results showcase the robust capability of the suggested control algorithm: it effectively maintains the DC bus voltage and produces high-quality electrical energy with a total harmonic distortion (THD) below 0.38%. Moreover, the algorithm demonstrates added resilience. The practical viability of the adaptive control algorithm is validated through an experimental study on the dSPACE DS1104 prototyping platform. This study underscores the algorithm’s proficiency in achieving all control objectives under diverse wind scenarios. © 2023 by the authors.

关键词： Stability

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Recent developments in content delivery network: A survey 10th

Recent developments in content delivery network: A survey

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10th International Symposium on Parallel Architectures, Algorithms and Programming, PAAP 2019

作者： Zhao, Jiaming Liang, Pingjia Liufu, Weiming Fan, Zhengping School of Data and Computer Science SUN Yat-Sen University Guangzhou China School of Intelligent Systems Engineering SUN Yat-Sen University Guangzhou China

With the development of computer networks, the amount of network information continues to grow. To facilitate the transfer of the increasing information, a content distribution network (CDN) is developed by adding an intermediate layer on the existing network. Technically, Caching strategy of CDN is the most important mechanism, which heavily impacts the CDN performance. On the other hand, considering the cost of operating CDN, some strategies have been proposed, aiming to save the CDN cost in terms of, e.g., power energy. This paper makes a brief review on the recent developments of CDN in terms of its caching strategy and operation cost, and discusses some potential development directions of CDN. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Cache strategy Content delivery network Cost

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Facile Synthesis of Ni-Zif-8 with Improved Photodegradation Performance for Methylene Blue

SSRN

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SSRN 2024年

作者： Zulfa, Liyana Labiba Hidayat, Alvin Romadhoni Putra Utomo, Wahyu Prasetyo Subagyo, Riki Kusumawati, Etty Nurlia Kusumawati, Yuly Hartanto, Djoko Ediati, Ratna Widyastuti Department of Chemistry Faculty of Science and Data Analytics Institut Teknologi Sepuluh Nopember Jl. Arif Rahman Hakim Kampus ITS Keputih-Sukolilo Surabaya60111 Indonesia School of Energy and Environment City University of Hong Kong 999077 Hong Kong Chemistry Course Faculty of Science and Engineering Iwate University 4-3-5 Ueda Iwate Morioka020-8551 Japan Department of Materials and Metallurgical Engineering Faculty of Industrial Technology and Systems Engineering Institut Teknologi Sepuluh Nopember Jl. Arif Rahman Hakim Kampus ITS Keputih-Sukolilo Surabaya60111 Indonesia

A series of bimetallic metal-organic frameworks (MOFs) photocatalysts had been successfully synthesized by doping nickel (Ni) into zeolitic imidazolate framework-8 (ZIF-8) for enhanced photodegradation of methylene blue (MB). Optical characterization revealed that the Ni-ZIF-8 composites possessed a narrower bandgap and lower recombination rate of charge carriers than pristine ZIF-8. The Ni(20)-ZIF-8 composite showed the highest MB photodegradation efficiency of up to 93.22% in 150 min. The scavenger test clearly proved that h+ and •OH were the main active species in the degradation of MB. The synthesized bimetallic Ni(20)-ZIF-8 composite is a promising photocatalyst for removal of MB in aquatic environments. © 2024, The Authors. All rights reserved.

关键词： Wastewater treatment

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High-precision FMCW ranging with a hybrid-integrated external cavity laser

High-precision FMCW ranging with a hybrid-integrated externa...

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OptoElectronics and Communications Conference, OECC

作者： Chuxin Liu Ruiyang Xu Weihan Xu Liangjun Lu Yuyao Guo Yu Li Jianping Chen Linjie Zhou Department of Electronic Engineering State Key Laboratory of Advanced Optical Communication Systems and Networks Shanghai Key Lab of Navigation and Location Services Shanghai Institute for Advanced Communication and Data Science Shanghai Jiao Tong University Shanghai China SJTU-Pinghu Institute of Intelligent Optoelectronics Pinghu China Shanghai China

We implement an analog EO-PLL for a III/V-Si 3 N 4 hybrid integrated ECL to generate a highly-linear FMCW signal over multiple wavelengths. A high range precision of 4.2 cm is achieved for a 200-m distance.

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Virtual Plant Based Training: Exploring Innovative Educational Mode for Agriculture

Virtual Plant Based Training: Exploring Innovative Education...

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Digital Twins and Parallel Intelligence (DTPI), IEEE International Conference on

作者： Haoyu Wang Xiujuan Wang Jing Hua Zhaoxun Wang Zede Shao Mengzhen Kang State Key Laboratory of Multi Modal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China Shandong Xingke Intelligent Technology Co. Ltd. Jinan China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automatio Chinese Academy of Sciences Beijing China Faculty of Innovation Engineering Macau University of Science and Technology Macau China

ISBN: (数字)9798350349252

ISBN: (纸本)9798350349269

Traditional agricultural education mainly relies on text and images, while the teaching of smart agriculture requires new technologies. With the development of virtual reality technology, the training and teaching mode based on plant and environmental modelling are gradually becoming an innovative practice in the field of agricultural education. Based on GreenLab model and an interactive interface, a training software for uderstanding plant behaviour has been developed for the training of agricultural colleges and universities. By analysing the application of computational plant, this paper discusses how this mode can improve learning efficiency, enhance students' practical ability, and provide new ideas and methods for agricultural education.

关键词： Training Smart agriculture Solid modeling Plants (biology) Computational modeling Green products Virtual reality Software Digital twins Computational efficiency

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p-CuGaO2/β-Ga2O3 interfaces: A high-throughput approach for interface prediction and generation for power device applications

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Materials Today Advances 2025年 26卷

作者： Prasad, Chowdam Venkata Park, Jang Hyeok Hoai Ta, Qui Thanh Kim, Kyong Jae Jeon, Ho Jung Mir, Muzaffar Ali Raza, Mohsin Tri, Nguyen Ngoc Kim, Honggyun Labed, Madani Rim, You Seung Department of Semiconductor Systems Engineering and Convergence Engineering for Intelligent Drone Sejong University Seoul05006 Korea Republic of Institute of Semiconductor and System IC Sejong University Seoul05006 Korea Republic of Department of Semiconductor Systems Engineering Sejong University Seoul05006 Korea Republic of Institute of Advanced Technology Vietnam Academy of Science and Technology 1A TL29 Street Thanh Loc Ward District 12 Ho Chi Minh City700000 Viet Nam Lab of Computational Chemistry and Modelling Faculty of Natural Sciences Quy Nhon University Quy Nhon City55100 Viet Nam

This study integrates a p-type copper gallium oxide (p-CuGaO2) interlayer to enhance the performance of β-Ga2O3-based power devices, addressing challenges in achieving reliable p-type doping. The p-CuGaO2 interlayer is expected to improve breakdown voltage (BV) and reduce leakage current, increasing device efficiency and reliability under high-temperature conditions. The heterojunction (HJ) system of β-Ga2O3 and p-CuGaO2 is investigated using density functional theory (DFT) via the Vienna Ab initio Simulation Package (VASP) and experimental methods, focusing on the β-Ga2O3 (001)/p-CuGaO2 (006) interface. Binding energy, electron localization, charge density difference, and electrostatic potential drop are analyzed, identifying Configuration-1 as the optimal configuration due to its high binding energy and favorable structural properties. Annealing temperature impacts the microstructure, stoichiometry, optical, electrical, and transport properties of p-CuGaO2/β-Ga2O3 HJs. Electrical measurements reveal reduced turn-on voltage (Von), on-resistance (Ron), and leakage currents, with the highest BV of 1.62 kV achieved at 800 °C compared to Pt/β-Ga2O3 Schottky barrier diode (SBD). The interface state density (NSS) is evaluated using the high-low frequency approach. Silvaco TCAD simulations explore breakdown mechanisms, demonstrating the potential of p-CuGaO2 for β-Ga2O3 HJ power devices. These findings support the development and manufacture of robust β-Ga2O3 HJ power devices. © 2025 The Authors

关键词： Heterojunctions

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Low Rank Reduced Biquaternion Tensor Ring Decomposition and Tensor Completion

SSRN

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SSRN 2024年

作者： Luo, Hui Liu, Xin Liu, Wei Zhang, Yang School of Computer Science and Engineering Faculty of Innovation Engineering Macau University of Science and Technology Avenida Wai Long TaiPa 999078 China Macau Institute of Systems Engineering Faculty of Innovation Engineering Macau University of Science and Technology Avenida Wai Long TaiPa 999078 China School of Artificial Intelligence Sun Yat-sen University The Guangdong Key Laboratory of Big Data Analysis and Processing No.135 West Xingang Road Guangdong Provience Guangzhou510275 China Department of Mathematics University of Manitoba No.135 West Xingang Road WinnipegMBR3T 2N2 Canada

Reduced biquaternions (RBs), as an extension of complex numbers, have demonstrated exceptional capabilities in digital signal and image processing. They not only excel particularly in encoding color information but also feature multiplicative commutativity, which simplify the theoretical analysis of related algorithms. Concurrently, tensor completion methods based on tensor ring decomposition in the real domain have been proven effective in exploiting low-rank structures. Building upon these insights, this paper first introduces the Reduced Biquaternion Tensor Ring (RBTR) decomposition, along with a detailed exposition of the corresponding algorithm RBTR-SVD. Leveraging RBTR decomposition, we propose a novel low-rank tensor completion algorithm RBTR-TV integrating RBTR rank with Total Variation (TV) regularization to optimize the process. In color image completion tasks, our method exhibits remarkable stability and robustness, outperforming traditional methods, especially if there are a lot of missing data in the image. © 2024, The Authors. All rights reserved.

关键词： Tensors

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PreMatch: A Prediction-based Scheduler for dataflow Asynchronous Processing on the Computing Continuum 25

PreMatch: A Prediction-based Scheduler for Dataflow Asynchro...

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Proceedings of the 40th ACM/SIGAPP Symposium on Applied Computing

作者： Narges Mehran Zahra Najafabadi Samani Samira Afzal Radu Prodan Frank Pallas Peter Dorfinger Intelligent Connectivity Group Salzburg Research Forschungsgesellschaft mbH Salzburg Salzburg Austria Faculty of Digital and Analytical Sciences Paris Lodron University of Salzburg Salzburg Salzburg Austria Distributed and Parallel Systems Group University of Innsbruck Innsbruck Tyrol Austria Faculty of Electrical Engineering Mathematics and Computer Science University of Twente Enschede Overijssel Netherlands Institute of Information Technology Alpen-Adria-University of Klagenfurt Klagenfurt Carinthia Austria

ISBN: (纸本)9798400706295

The popularity of asynchronous data exchange patterns has recently increased, as evidenced by 23% of the communication between microservices in an Alibaba trace analysis. Such workloads necessitate methods for reducing dataflow processing and completion time by forecasting the future requirements of their microservices and (re-)scheduling them. Therefore, we investigate a prediction-based scheduling method of asynchronous dataflow processing applications by considering the stochastic changes due to dynamic user requirements. We present a microservice scaling and scheduling method named PreMatch combining a machine learning (ML) prediction strategy based on gradient boosting with ranking and game theory matching scheduling principles. Firstly, PreMatch predicts the number of microservice replicas, and then, the ranking method orders the microservice replicas and devices based on microservice and transmission times. Thereafter, the PreMatch schedules microservice replicas requiring dataflow processing on computing devices. Experimental analysis of the PreMatch method shows lower completion times on average 13% compared to a related prediction-based scheduling method.

关键词： microservice

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Two-stream Multi-level Dynamic Point Transformer for Two-person Interaction Recognition

arXiv

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arXiv 2023年

作者： Liu, Yao Cui, Gangfeng Luo, Jiahui Chang, Xiaojun Yao, Lina School of Computer Science and Engineering University of New South Wales SydneyNSW2052 Australia School of Computing and Information Systems University of Melbourne MelbourneVIC3010 Australia Faculty of Engineering and Information Technology University of Technology Sydney SydneyNSW2007 Australia Data 61 CSIRO School of Computer Science and Engineering University of New South Wales SydneyNSW2015 Australia

As a fundamental aspect of human life, two-person interactions contain meaningful information about people's activities, relationships, and social settings. Human action recognition serves as the foundation for many smart applications, with a strong focus on personal privacy. However, recognizing two-person interactions poses more challenges due to increased body occlusion and overlap compared to single-person actions. In this paper, we propose a point cloud-based network named Two-stream Multi-level Dynamic Point Transformer for two-person interaction recognition. Our model addresses the challenge of recognizing two-person interactions by incorporating local-region spatial information, appearance information, and motion information. To achieve this, we introduce a designed frame selection method named Interval Frame Sampling (IFS), which efficiently samples frames from videos, capturing more discriminative information in a relatively short processing time. Subsequently, a frame features learning module and a two-stream multi-level feature aggregation module extract global and partial features from the sampled frames, effectively representing the local-region spatial information, appearance information, and motion information related to the interactions. Finally, we apply a transformer to perform self-attention on the learned features for the final classification. Extensive experiments are conducted on two large-scale datasets, the interaction subsets of NTU RGB+D 60 and NTU RGB+D 120. The results show that our network outperforms state-of-the-art approaches in most standard evaluation settings. Copyright © 2023, The Authors. All rights reserved.

关键词： Large datasets

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Incremental Feature Selection for Dynamic Incomplete data Using Sub-Tolerance Relation

SSRN

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SSRN 2023年

作者： Zhao, Jie Ling, Yun Huang, Faliang Wang, Jiahai See-To, Eric Wing kuen Department of Data Science and Business Intelligence Guangdong University of Technology Guangzhou China Guangxi Key Lab of Human-machine Interaction and Intelligent Decision Nanning Normal University Nanning China School of Computer Science and Engineering Sun Yat-sen University Guangzhou China Department of Computing and Decision Sciences Faculty of Business Lingnan University Hong Kong

TRS theory is widely used for feature selection with incomplete data. However, the traditional positive region-based measure ignores uncertainty, resulting in redundant features and poor classification accuracy. In addition, the computation of the positive region incurs significant time and space costs. To address these limitations, we extend the tolerance class to a Subrelation Tolerance Class (STC) by decomposing the tolerance relation into two subrelations. STC transforms feature selection into a two-stage certainty measurement by partitioning the universe into certainty and uncertainty regions. By progressively filtering out certain regions, the computational space is reduced. Furthermore, we propose a new significance measure that incorporates both certain and uncertain information. This measure effectively reduces redundant features, resulting in improved computational efficiency and classification accuracy. Using STC and our measure, we develop an incremental feature selection algorithm for dealing with incomplete streaming data, which is validated through extensive experiments and comparisons. © 2023, The Authors. All rights reserved.

关键词： Feature Selection

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