检索结果-内蒙古大学图书馆

8th Southern Power Electronics Conference and the 17th Brazilian Power Electronics Conference, SPEC / COBEP 2023

作者： Filho, José De Arimatéia O. Bressanini, Gabriel Lucas Curi Busarello, Tiago Davi De Oro Arenas, Luis Silva, Paulo Fernando Morales Paredes, Helmo Kelis Sorocaba Brazil Department of Control Automation and Computing Engineering Blumenau Brazil

ISBN: (纸本)9798350321128

In recent years, grid-connected inverters have gained wide prominence, primarily attributed to the surge in distributed energy resources. To ensure the reliable operation of these inverters, it is crucial to adequately damp the resonance peak of the LCL filter at the inverter output. By achieving this, the grid-connected inverter guarantees the system's stability while minimizing the harmonic content in the current injected into the distribution grid. To address this issue, this paper proposes the utilization of digital differentiators in conjunction with optimized wideband differentiators, which are designed using the Parks-McClellan (PM) algorithm. These differentiators are applied specifically to the LCL filter capacitor voltage to dampen the resonance peak effectively. Simulation results univocally demonstrate the effectiveness of the proposed approach. © 2023 IEEE.

关键词： Active damping capacitor voltage digital differentiator LCL-filter Parks-McClellan algorithm

来源：评论

学校读者我要写书评

暂无评论

Federated Digital Twin Construction via Distributed Sensing: A Game-Theoretic Online Optimization with Overlapping Coalitions

arXiv

引用

arXiv 2025年

作者： Chen, Ruoyang Yi, Changyan Zhou, Fuhui Kang, Jiawen Wu, Yuan Niyato, Dusit College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing211106 China College of Electronic and Information Engineering Nanjing University of Astronautics and Aeronautics Nanjing210016 China School of Automation Guangdong University of Technology Guangzhou510006 China State Key Laboratory of Internet of Things for Smart City University of Macau China Department of Computer and Information Science University of Macau China College of Computing and Data Science Nanyang Technological University Singapore639798 Singapore

In this paper, we propose a novel federated framework for constructing the digital twin (DT) model, referring to a living and self-evolving visualization model empowered by artificial intelligence, enabled by distributed sensing under edge-cloud collaboration. In this framework, the DT model to be built at the cloud is regarded as a global one being split into and integrating from multiple functional components, i.e., partial-DTs, created at various edge servers (ESs) using feature data collected by associated sensors. Considering time-varying DT evolutions and heterogeneities among partial-DTs, we formulate an online problem that jointly and dynamically optimizes partial-DT assignments from the cloud to ESs, ES-sensor associations for partial-DT creation, and as well as computation and communication resource allocations for global-DT integration. The problem aims to maximize the constructed DT’s model quality while minimizing all induced costs, including energy consumption and configuration costs, in long runs. To this end, we first transform the original problem into an equivalent hierarchical game with an upper-layer two-sided matching game and a lower-layer overlapping coalition formation game. After analyzing these games in detail, we apply the Gale-Shapley algorithm and particularly develop a switch rules-based overlapping coalition formation algorithm to obtain short-term equilibria of upper-layer and lower-layer subgames, respectively. Then, we design a deep reinforcement learning-based solution, called DMO, to extend the result into a long-term equilibrium of the hierarchical game, thereby producing the solution to the original problem. Simulations show the effectiveness of the introduced framework, and demonstrate the superiority of the proposed solution over counterparts. Copyright © 2025, The Authors. All rights reserved.

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

Unmanned aerial vehicle based multi-person detection via deep neural network models

引用

Frontiers in Neurorobotics 2025年 19卷 1582995页

作者： Alshehri, Mohammed Zahoor, Laiba AlQahtani, Yahya Alshahrani, Abdulmonem AlHammadi, Dina Abdulaziz Jalal, Ahmad Liu, Hui Department of Computer Science King Khalid University Abha Saudi Arabia Faculty of Computer Science Air University Islamabad Pakistan Department of Informatics and Computer Systems King Khalid University Abha Saudi Arabia Department of Information Systems College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University Riyadh Saudi Arabia Department of Computer Science and Engineering College of Informatics Korea University Seoul Korea Republic of Cognitive Systems Lab University of Bremen Bremen Germany Guodian Nanjing Automation Company Ltd. Nanjing China Jiangsu Key Laboratory of Intelligent Medical Image Computing School of Future Technology Nanjing University of Information Science and Technology Nanjing China

Introduction: Understanding human actions in complex environments is crucial for advancing applications in areas such as surveillance, robotics, and autonomous systems. Identifying actions from UAV-recorded videos becomes more challenging as the task presents unique challenges, including motion blur, dynamic background, lighting variations, and varying viewpoints. The presented work develops a deep learning system that recognizes multi-person behaviors from data gathered by UAVs. The proposed system provides higher recognition accuracy while maintaining robustness along with dynamic environmental adaptability through the integration of different features and neural network models. The study supports the wider development of neural network systems utilized in complicated contexts while creating intelligent UAV applications utilizing neural networks. Method: The proposed study uses deep learning and feature extraction approaches to create a novel method to recognize various actions in UAV-recorded video. The proposed model improves identification capacities and system robustness by addressing motion dynamic problems and intricate environmental constraints, encouraging advancements in UAV-based neural network systems. Results: We proposed a deep learning-based framework with feature extraction approaches that may effectively increase the accuracy and robustness of multi-person action recognition in the challenging scenarios. Compared to the existing approaches, our system achieved 91.50% on MOD20 dataset and 89.71% on Okutama-Action. These results do, in fact, show how useful neural network-based methods are for managing the limitations of UAV-based application. Discussion: Results how that the proposed framework is indeed effective at multi-person action recognition under difficult UAV conditions. Copyright © 2025 Alshehri, Zahoor, AlQahtani, Alshahrani, AlHammadi, Jalal and Liu.

关键词： Drones

来源：评论

学校读者我要写书评

暂无评论

Hybrid-Generative Diffusion Models for Attack-Oriented Twin Migration in Vehicular Metaverses

引用

IEEE Transactions on Vehicular Technology 2025年

作者： Kang, Yingkai Wen, Jinbo Kang, Jiawen Zhang, Tao Du, Hongyang Niyato, Dusit Yu, Rong Xie, Shengli Guangdong University of Technology School of Automation Guangzhou510006 China Nanjing University of Aeronautics and Astronautics College of Computer Science and Technology Nanjing210016 China Beijing Jiaotong University School of Cyberspace Science and Technology Beijing100044 China University of Hong Kong Department of Electrical and Electronic Engineering Pok Fu Lam Hong Kong Nanyang Technological University College of Computing and Data Science 639798 Singapore

The vehicular metaverse is envisioned as a blended immersive domain that promises to bring revolutionary changes to the automotive industry. As a core component of vehicular metaverses, Vehicle Twins (VTs) are digital twins that cover the entire life cycle of vehicles, providing immersive virtual services for Vehicular Metaverse Users (VMUs). Vehicles with limited resources offload the computationally intensive tasks of constructing and updating VTs to edge servers and migrate VTs between these servers, ensuring seamless and immersive experiences for VMUs. However, the high mobility of vehicles, uneven deployment of edge servers, and potential security threats pose challenges to achieving efficient and reliable VT migrations. To address these issues, we propose a secure and reliable VT migration framework in vehicular metaverses. Specifically, we design a two-layer trust evaluation model to comprehensively evaluate the reputation value of edge servers in the network communication and interaction layers. Then, we model the VT migration problem as a partially observable Markov decision process and design a hybrid-Generative Diffusion Model (GDM) algorithm based on deep reinforcement learning to generate optimal migration decisions by taking hybrid actions (i.e., continuous actions and discrete actions). Numerical results demonstrate that the hybrid-GDM algorithm outperforms the baseline algorithms, showing strong adaptability in various settings and highlighting the potential of the hybrid-GDM algorithm for addressing various optimization issues in vehicular metaverses. © 1967-2012 IEEE.

关键词： deep reinforcement learning generative diffusion models reputation twin migration Vehicular metaverse

来源：评论

学校读者我要写书评

暂无评论

A swin transformer and CNN fusion framework for accurate Parkinson disease classification in MRI

引用

Scientific Reports 2025年第1期15卷 1-14页

作者： Hussain, Sayyed Shahid Shah, Pir Masoom Dawood, Hussain Degang, Xu Alshamayleh, Ahmad Khan, Muhammad Adnan Ghazal, Taher M. School of Automation Central South University Changsha 410083 China School of Computer Science and Engineering Central South University Changsha 410010 China Department of Computer Science Bacha Khan University Charsadda Pakistan School of Computing Skyline University College Sharjah United Arab Emirates Department of Data Science and Artificial Intelligence Hourani Center for Applied Scientific Research Al-Ahliyya Amman University Amman Jordan Department of Software Faculty of Artificial Intelligence and Software Gachon University Seongnam-si 13120 South Korea Riphah School of Computing and Innovation Riphah International University Lahore Campus Lahore 54000 Pakistan Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura 140401 India Networks and Cybersecurity Department Hourani Center for Applied Scientific Research Al-Ahliyya Amman University Amman Jordan

Parkinson’s disease ranks as the second most prevalent neurological disorder after Alzheimer’s disease. Convolutional neural networks (CNNs) have been extensively employed in Parkinson’s disease (PD) detection using MR images. However, CNN models generally focus on local features while prone to capture global representations. On the other hand, the vision transformer (ViT) excels at capturing global features through its self-attention mechanism, but it compromises local feature representations. Additionally, the varying magnitude of MR data poses a challenge for ViT, potentially leading to the gradient vanishing problem. To address these limitations, this paper proposed a novel framework that combines the Swin-Transformer and CNN to capture both local and global features effectively. To mitigate the gradient vanishing issue in ViT, we used skipped connections and cosine attention mechanism in VIT that preserves the output distribution regardless of input magnitude variations. The proposed model comprises three primary blocks: Transformer-block, convolutional block, and dense-block. The input image is processed concurrently by the cosine transformer and convolutional block. Subsequently, the extracted features from both blocks are concatenated and fed to the dense block for decision-making. The proposed model achieved promesing results of 96%, 97%, 95%, and 95% in terms of accuracy, sensitivity, specificity, and area under the curve, respectively. © The Author(s) 2025.

关键词： CNN Cosine similarity MRI Parkinson’s disease Swin-transformer

来源：评论

学校读者我要写书评

暂无评论

Output Group Consensus for Heterogeneous Linear Multi-Agent Systems Communicating over Switching Topology 36

Output Group Consensus for Heterogeneous Linear Multi-Agent ...

引用

第36届中国控制会议

作者： Jiahu Qin Qichao Ma Wei Xing Zheng Department of Automation University of Science and Technology of China School of Computing Engineering and MathematicsWestern Sydney University

ISBN: (纸本)9781538629185

In this paper,we aim to investigate the output group consensus problem for a switching network of heterogeneous linear systems such that outputs of the agents synchronize with each other in every *** the internal model principle perspective,a necessary condition is first derived in terms of the system *** this necessary condition,a dynamic controller is then designed to solve the output group consensus problem in two steps,namely consensus of reference generators and output tracking for each *** is obtained that if every possible underlying topology of each cluster contains a directed spanning tree,then group consensus for the reference generators can be realized with sufficiently strong intra-cluster coupling *** appropriate controller is then designed to force the output of each agent to track the output of the reference generators.A simulation example is given at last to validate our theoretical findings.

关键词： Output group consensus switching topology heterogeneous systems internal model principle

来源：评论

学校读者我要写书评

暂无评论

Tool Sequence Optimization Based on Three Logical Modes of Robot Control via CPLEX Optimization

引用

Journal of Shanghai Jiaotong university(Science) 2011年第4期16卷 436-440页

作者：孙亮亮刘炜柴天佑 Manufacturing Computing Laboratory Electrical Engineering DepartmentUniversity of Connecticut Storrs Key Laboratory of Integrated Automation of Process Industry Northeastern University

Cluster tools have advantages of shorter cycle times,faster process development,and better yield for less *** sequence of dual-arm cluster tools is a complex logistics process during the semiconductor *** use of cluster tools is naturally very significant to competitive fab *** an optimized sequence in a computationally efficient manner and assessing the quality of the requirements to improve the fab production are the key factors for semiconductor manufacturing *** Petri net modeling is introduced to minimize the makespan of the process for the three different logical modes and select a better mode after comparing the makespan among the three logical *** tool sequence optimization problem is formulated as optimization firing transition sequences based on the Petri net and then the formulation is converted to be linearly solved by the branch-and-cut method in the standard commercial solver *** methods for the linear conversion are *** to the limited calculation time requirement for the real production and the large scale of the problem,special methods for the efficiency tuning are applied according to the characteristics of the *** testing is supported by one of the most advanced semiconductor enterprises and the computational results show significant improvement compared with the traditional manual sequence results.

关键词： logical modes CPLEX branch and cut Petri net tool sequence optimization

来源：评论

学校读者我要写书评

暂无评论

Automatic contingency selection based on a pattern analysis approach

Automatic contingency selection based on a pattern analysis ...

引用

1999 International Conference on Electric Power engineering, PowerTech Budapest 1999

作者： Rodrigues, M.S. Souza, J.C.S. Filho, M.B. Do Coutto Schilling, M.Th. Department of Electrical Engineering Applied Computing and Automation Fluminense Federal University - UFF Brazil

ISBN: (纸本)0780358368

During power system operation, it is important that load demands be met without violations of system operational constraints. Besides, for a given operating condition, the system should be capable of resisting the loss of any component, with no operational problems. Thus, contingency analysis plays an important role in real-Time power system security evaluation. Contingency analysis comprises the simulation of a set of contingencies in which the system behavior is observed. Each post- contingency scenario is evaluated in order to detect operational problems and the severity of violations. The most common operational problems are transmission equipment overloads and inadequate voltage levels at system buses. In static security analysis the identification of operational constraints violation involves the solution of an AC load flow problem, described by a set of nonlinear equations, that has to be solved for each post-contingency scenario. This procedure leads to a high computational effort, which is not desirable for real-Time applications. Some approximate models have been proposed for realtime power system static security evaluation [1J. These models reduce computational effort, but they may not classify system contingencies accurately. It is not possible to analyze system performance considering all contingencies. It is necessary to reduce the number of contingencies to only those that are more likely to occur. These form the critical contingencies set, which is in general defined based on system operation past experience and/or off-line simulations. The need for computational efficiency in real-Time contingency analysis can make not possible the analysis even for the critical contingencies set. Then, it becomes necessary to select in the critical set the contingencies that can really lead the system to an emergency state, with operational constraints violations. It is important to note that, as system operating conditions change, the harmful contingencies may als

关键词： Neural networks

来源：评论

学校读者我要写书评

暂无评论

Indices for harmonic distortion monitoring of power distribution systems

Indices for harmonic distortion monitoring of power distribu...

引用

作者： Vlahinic, Saša Brnobic, Dalibor Stojkovic, Nino Department of Automation Electronics and Computing Faculty of Engineering University of Rijeka 51000 Rijeka Croatia

Among the different power quality parameters, the voltage total harmonic distortion is important and is often studied. Different indices have previously been suggested to measure and monitor both the current and the voltage distortion in power systems, but the harmonic characterization of a power system can still not be performed in a satisfactory way. The state of the harmonic distortion is difficult to predict due to the variability and a large number of unknowns, such as detailed consumer and system characteristics. In this paper, a new index that describes the total harmonic distortion in the current measurements, i.e., the total rated distortion (TRD), is suggested to simplify and standardize the harmonic current measurements. Another index that represents the increase of the harmonic voltage distortion with TRD, i.e., the equivalent harmonic impedance zeq, is proposed as an efficient way of characterizing a particular site. It is analyzed when zeq is increased or decreased with regard to the angle between the harmonic voltages and currents. Finally, extensive harmonic measurements of a real distribution system were performed to prove the usefulness of the proposed indices. © 2008 IEEE.

关键词： Harmonic analysis

来源：评论

学校读者我要写书评

暂无评论

Influence of mounting temperature probes on the excitation winding on its temperature field

Influence of mounting temperature probes on the excitation w...

引用

19th International Conference on Electrical Machines, ICEM 2010

作者： Hanic, Zlatko Kovačić, Marinko Vražić, Mario Department of Electrical Machines and Automation Faculty of Electrical Engineering and Computing University of Zagreb Croatia

ISBN: (纸本)9781424441754

Accurate and reliable information about the temperature of the synchronous generator excitation winding hot spot is necessary to determine the dynamic limit caused by excitation winding overheating in the PQ diagram. For good estimation of a position and the hot spot temperature it was decided to mount 19 temperature probes on one pole of the 6-pole, 400 kVA, 50 Hz synchronous generator. Due to a large number of the probes and because the probes should be glued with the metal epoxy it was assumed that mounting of the probes will disrupt the temperature field of the excitation winding. To get the answer to this question the excitation winding resistance was measured before and after mounting the probes, in a hot and a cold state. Temperature rise can be estimated if the resistance ratio in the hot and the cold state is known. The paper also addresses the analysis of the measurement accuracy. ©2010 IEEE.

关键词： Temperature

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：