检索结果-内蒙古大学图书馆

Resilience-oriented Operation of Power Distribution Networks with Line Hardening and Comprehensive Reconfiguration Measures 14

Resilience-oriented Operation of Power Distribution Networks...

引用

14th IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids, SmartGridComm 2023

作者： Li, Zhengmao Shi, Zhao Ruan, Guangchun Lin, Yuzhang Zhao, Jin Aalto University School of Electrical Engineering Espoo Finland Nanyang Technological University School of Electrical and Electronic Engineering Singapore Massachusetts Institute of Technology Laboratory for Information & Decision Systems Boston United States New York University Department of Electrical and Computer Engineering New York United States Trinity College Dublin Department of Electronic and Electrical Engineering Dublin Ireland

ISBN: (纸本)9781665455541

With the frequent occurrence of extreme events like natural disasters and man-made attacks, the resilience concept is attracting worldwide research attention. Thus, this paper proposes a resilient operation model for the power distribution network (PDN) to recover load and limit economic loss to the greatest possible extent. First, the line hardening measure is applied to strengthen the PDN to avoid the serious breakdown of distribution lines. In addition, a comprehensive single commodity flow-based reconfiguration approach is used which not only sets the buses connecting generation sources but also those at the end of broken lines as the slack buses. Then, the radiality of PDNs can still be guaranteed after reconfiguration. The resilience-oriented operation problem can be originally formulated as a nonlinear programming one while efficient linearization methods are applied to reduce computational burdens. Hence, the operation problem is reformulated as a mixed-integer linear programming one which will enjoy favorable solution performances. Finally, case studies on an IEEE 33 PDN including comparison cases with traditional benchmarks are done to show the effectiveness of our method. © 2023 IEEE.

关键词： Hardening

来源：评论

学校读者我要写书评

暂无评论

RUL Estimation for Power Electronic Devices Using RNNs

RUL Estimation for Power Electronic Devices Using RNNs

引用

Prognostics and System Health Management Conference (PHM)

作者： Congrui Cai Zhonghai Lu Embedded Systems Master Program School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Department of Electrical Engineering School of Electrical Engineering and Computer Science KTH Royal Institute of Technology

ISBN: (数字)9798350360585

ISBN: (纸本)9798350360592

Recurrent Neural Networks (RNNs) are commonly used in data-driven approaches to estimate the Remaining Useful Lifetime (RUL) of power electronic devices. RNNs are preferred because their intrinsic feedback mechanisms are better suited to model time-series data. However, the impact of RNN complexity on estimation accuracy is rarely discussed in the literature. This issue is important because choosing a lower-complexity model that delivers the same or similar performance as a higher-complexity model can increase implementation efficiency. In the paper, we use three RNN models, namely, the vanilla version, LSTM (Long Short Term Memory) and GRU (Gated Recurrent Unit) to conduct RUL estimation for power electronic devices. We use two accelerated aging datasets, one dataset targeting the package failure of MOSFETs, and the other dataset targeting package failure of power diodes. Our study shows that a lower-complexity RNN does not necessarily deliver a lower performance. Similarly, a higher-complexity model does not assure a higher performance. As such, our work highlights the importance of selecting a proper neural network for RUL estimation not biased towards complex models. This is especially useful and important for implementing such RUL estimation techniques in embedded resource-constrained and speed-limited computins platforms.

关键词： Performance evaluation Semiconductor device modeling Recurrent neural networks Computational modeling Estimation Power electronics Data models

来源：评论

学校读者我要写书评

暂无评论

FAST CHARGING ELECTRIC BUSES IN MARIBOR: A COMPARATIVE ANALYSIS OF SIMULATION AND REAL-WORLD RESULTS 12th

FAST CHARGING ELECTRIC BUSES IN MARIBOR: A COMPARATIVE ANALY...

引用

12th International Conference on Environmental engineering, ICEE 2023

作者： Klemenčič, Mitja Španer, Marijan Lep, Marjan Moharić, Matej Department of Transportation Engineering Faculty of Civil Engineering Transportation Engineering and Architecture University of Maribor Smetanova 17 Maribor Slovenia Laboratory for Power Electronics Institute of Robotics Faculty of Electrical Engineering and Computer Science University of Maribor Koroška cesta 46 Maribor Slovenia

This paper presents a study of the energy consumption of a full electric bus charged at a fast-charging station with pantographs in the city of Maribor. The results of simulated and real tests on the PT line 6 are compared and analysed. The partly electrified PT line 6 provides insights on comparison between simulated energy consumption and re-al-life energy consumption, charging time and reliability of charging. The results reveal that the simulation considered several important factors like real life turnaround time, driving cycle, regenerative braking, charging time, peak hour charging time, heating/cooling systems, full passenger load as important and critical to identify the appropriate concept for charging. Technical and operational errors were identified in real world, due to connectivity failures or driver errors in positioning the vehicle, which were not considered in the simulation. The real-world data and procedure for selection of the most appropriate charging technology represent a good basis for full electrified Public Transport in Maribor. © 2023 The Author(s). Published by Vilnius Gediminas Technical University.

关键词： Electric buses

来源：评论

学校读者我要写书评

暂无评论

Conformal Decision Theory: Safe Autonomous Decisions from Imperfect Predictions

Conformal Decision Theory: Safe Autonomous Decisions from Im...

引用

IEEE International Conference on robotics and Automation (ICRA)

作者： Jordan Lekeufack Anastasios N. Angelopoulos Andrea Bajcsy Michael I. Jordan Jitendra Malik Department of Statistics UC Berkeley Department of Electrical Engineering and Computer Science UC Berkeley Robotics Institute Carnegie Mellon University

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

We introduce Conformal Decision Theory, a framework for producing safe autonomous decisions despite imperfect machine learning predictions. Examples of such decisions are ubiquitous, from robot planning algorithms that rely on pedestrian predictions, to calibrating autonomous manufacturing to exhibit high throughput and low error, to the choice of trusting a nominal policy versus switching to a safe backup policy at run-time. The decisions produced by our algorithms are safe in the sense that they come with provable statistical guarantees of having low risk without any assumptions on the world model whatsoever; the observations need not be I.I.D. and can even be adversarial. The theory extends results from conformal prediction to calibrate decisions directly, without requiring the construction of prediction sets. Experiments demonstrate the utility of our approach in robot motion planning around humans and robot manufacturing.

关键词： Robot motion Pedestrians Machine learning algorithms Decision theory Switches Prediction algorithms Throughput

来源：评论

学校读者我要写书评

暂无评论

Scalable Self-Tallying e-Voting using Homomorphic Time-Lock Puzzles and zk-SNARKs

引用

IEEE Transactions on Network Science and engineering 2025年

作者： Elsheikh, Muhammad Youssef, Amr M. Hasan, M. Anwar University of Waterloo Department of Electrical and Computer Engineering Canada Cairo Egypt Concordia University Concordia Institute for Information Systems Engineering QC Canada

Achieving fairness, verifiability, and abandon resistance poses challenges within e-voting protocols. This paper introduces a privacy-preserving self-tallying e-voting system leveraging blockchain technology. The system supports diverse e-voting models, including 'Yes/No', approval voting with multiple candidates, and score voting. By employing linearly homomorphic time-lock puzzles (LHTLPs) along with verifiable delay functions (VDFs) and zero-knowledge Succinct Non-interactive Argument of Knowledge schemes (zk-SNARKs), the proposed system ensures crucial security properties, including voter anonymity and eligibility, as well as ballot privacy and validity. It also provides efficient individual and universal verifiability (end-to-end verifiability), and dispute-freeness. More importantly, the system demonstrates fairness and abandon resistance. Furthermore, the evaluation of the proof-of-concept implementation on the Ethereum blockchain indicates that on-chain gas costs are either fixed or increasing slowly and logarithmically with the number of voters. © 2013 IEEE.

关键词： Blockchain

来源：评论

学校读者我要写书评

暂无评论

Wavelet Convolutional Neural Network for Low-Resolution Brain MRI Images 22

Wavelet Convolutional Neural Network for Low-Resolution Brai...

引用

22nd IEEE International Symposium on Biomedical Imaging, ISBI 2025

作者： Oh, Soo Min Li, Yifan Chong, Jo Woon Massachusetts Institute of Technology Wireless Information and Network Sciences Laboratory CambridgeMA02139 United States Massachusetts Institute of Technology Laboratory for Information and Decision Systems CambridgeMA02139 United States Texas A&m University Department of Statistics College StationTX77843 United States Texas Tech University Department of Electrical and Computer Engineering LubbockTX79409 United States Sungkyunkwan University Department of Electrical and Computer Engineering Suwon16419 Korea Republic of

ISBN: (纸本)9798331520526

Low-resolution images inherently contain less information, making effective feature extraction more challenging and posing difficulties for training neural networks. However, if neural networks can be trained successfully on low-resolution images, this could significantly reduce memory storage requirements and computational costs. In this study, we address the limitations of low-resolution brain MRI images by enhancing the available information through wavelet transform techniques. Specifically, we leverage the high-frequency coefficients obtained from wavelet transforms and the Hurst exponent to improve feature representation and optimize model training for convolutional neural networks (CNN), which is referred to as the wavelet CNN (WCNN). We demonstrate that WCNN outperforms standard CNNs in multi-class classification tasks, distinguishing among four categories of brain MRI images such as normal, glioma, meningioma, and pituitary tumor images. This approach highlights the potential to achieve high classification accuracy even with low-resolution data, ultimately reducing the memory and computational resources required for data processing and model training. © 2025 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Focused Bidirectional Search Trees: A Bidirectional Optimal Fast Matching Method for Robot Path Planning

Focused Bidirectional Search Trees: A Bidirectional Optimal ...

引用

2023 IEEE International Conference on Real-Time Computing and robotics, RCAR 2023

作者： Li, Chenming Wang, Jiankun Meng, Max Q.-H. The Chinese University of Hong Kong Department of Electronic Engineering Hong Kong Hong Kong Southern University of Science and Technology Shenzhen Key Laboratory of Robotics Perception and Intelligence Department of Electronic and Electrical Engineering Shenzhen China Southern University of Science and Technology Jiaxing Research Institute Jiaxing China University of Alberta Department of Electrical and Computer Engineering Canada

ISBN: (纸本)9798350327182

Robot path planning in high-dimensional continuous space is of great significance in robotics. The conventional bidirectional fast marching method utilizes brute-force search to explore the space, which is computationally expensive. Though improving the planning efficiency, heuristic-based bidirectional fast marching search results in a suboptimal path under a predetermined number of random samples. To address these issues, we propose Focused Bidirectional Fast Marching Trees (FBFMT*), developing a novel vertex exploring sequence to constrain the forward and backward searches within the brute-force searched regions. It enables the search trees to meet in the middle of the solution path, which guarantees the optimality under the current set of samples and searches faster than the bidirectional brute-force strategy. Extensive simulations in different scenarios validate the superiority of the proposed method, showing that FBFMT∗ can speed up the planning process and find a better solution. We also extend the proposed method to general conditions so that the forward and backward searches of FBFMT∗ can meet at any portion of the path. FBFMT∗ reveals that the heuristic-based bidirectional fast marching search strategy can be a general and efficient technique for robot path planning in high-dimensional continuous spaces. © 2023 IEEE.

关键词： Robot programming

来源：评论

学校读者我要写书评

暂无评论

Analysis and Characterization of Defects in FeFETs

Analysis and Characterization of Defects in FeFETs

引用

2023 IEEE International Test Conference, ITC 2023

作者： Thapar, Dhruv Thomann, Simon Chaudhuri, Arjun Amrouch, Hussam Chakrabarty, Krishnendu Duke University Department of Electrical and Computer Engineering North Carolina United States Ai Processor Design Germany Munich Institute of Robotics and Machine Intelligence Technical University of Munich Germany Arizona United States

ISBN: (纸本)9798350343250

Emerging devices are susceptible to manufacturing defects due to immature fabrication processes. Ferroelectric field-effect transistors, referred to as FeFETs, are promising emerging devices, but the impact of manufacturing imperfections on these devices has yet to be studied. Thus, we combine a technology CAD (TCAD) model with a fault-injection technique to represent fabrication defects in a FeFET. The TCAD model is calibrated against a fabricated metal-ferroelectric-metal capacitor and uses a multi-domain ferroelectric-layer structure. We address two classes of defects in the ferroelectric layer and map them to stuck-at-fault models referred to as neutral faults (SAP°) and stuck-at-plus and stuck-at-minus (SAP+ and SAP-) faults. We also develop a machine-learning (ML) framework to characterize these fault-injected FeFET devices. The ML framework provides a significant speedup in predicting the health of the FE layer as compared to computationally heavy TCAD simulations. Our study of defects in ferroelectric FET (FeFET), which is done for the first time, and the insights gained thereof can provide valuable feedback for the fabrication and yield learning of FeFET-based circuits. © 2023 IEEE.

关键词： Defects

来源：评论

学校读者我要写书评

暂无评论

Dynamic Setpoint Optimization Using Metaheuristic Algorithms for Wastewater Treatment Plants 48

Dynamic Setpoint Optimization Using Metaheuristic Algorithms...

引用

48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022

作者： Salles, Rodrigo Mendes, Jerome Henggeler Antunes, Carlos Moura, Pedro Dias, Joana University of Coimbra Institute of Systems and Robotics Department of Electrical and Computer Engineering Pólo II Coimbra3030-290 Portugal University of Coimbra Inesc Coimbra Department of Electrical and Computer Engineering Pólo II Coimbra3030-290 Portugal Ctga Park no 70 Taveiro Coimbra3045-487 Portugal

ISBN: (数字)9781665480253

ISBN: (纸本)9781665480253

Wastewater Treatment Plants (WWTPs) are complex structures, with nonlinear characteristics, that have strict quality criteria, and carry out the treatment using various resources, with special emphasis on electricity. The optimization of WWTPs is a necessity to achieve sustainability. This work proposes the use of metaheuristic algorithms to optimize the functioning of a WWTP. Genetic Algorithm, Particle Swarm Optimization, and Simulated Annealing are used to minimize the aeration energy consumption prediction by an artificial neural network. The optimization framework aims dynamically adjusts the reference value for the proportional-integral (PI) controller. The proposed approach was able to dynamically adjust the oxygen pumping requirement and thus reduce the electricity consumption compared to the default PI controller adopted by the Benchmark Simulation Model no. 2 (BSM2). © 2022 IEEE.

关键词： Genetic algorithms

来源：评论

学校读者我要写书评

暂无评论

AR/VR Digital Twin for Simulation and Data Collection of Robotic Environments 25

AR/VR Digital Twin for Simulation and Data Collection of Rob...

引用

25th IEEE International Conference on Autonomous Robot systems and Competitions, ICARSC 2025

作者： Martins, João G. Nutonen, Karle Costa, Paulo Kuts, Vladimir Otto, Tauno Sousa, Armando Petry, Marcelo R. CRIIS - Centre for Robotics in Industry and Intelligent Systems INESC TEC - Institute for Systems and Computer Engineering Technology and Science Porto4200-465 Portugal Faculty of Engineering Porto4200-465 Portugal ViruTech - Virumaa innovation center of digitalization and green technologies Taltech Virumaa College Kohtla-Jarve30322 Estonia Taltech Department of Mechanical and Indusrial Tallinn19086 Estonia

ISBN: (纸本)9798331538606

Digital twins enable real-time modeling, simulation, and monitoring of complex systems, driving advancements in automation, robotics, and industrial applications. This study presents a large-scale digital twin-testing facility for evaluating mobile robots and pilot robotic systems in a research laboratory environment. The platform integrates high-fidelity physical and environmental models, providing a controlled yet dynamic setting for analyzing robotic behavior. A key feature of the system is its comprehensive data collection framework, capturing critical parameters such as position, orientation, and velocity, which can be leveraged for machine learning, performance optimization, and decision-making. The facility also supports the simulation of discrete operational systems, using predictive modeling to bridge informational gaps when real-time data updates are unavailable. The digital twin was validated through a matrix manufacturing system simulation, with an Augmented Reality (AR) interface on the HoloLens 2 to overlay digital information onto mobile platform controllers, enhancing situational awareness. The main contributions include a digital twin framework for deploying data-driven robotic systems and three key AR/VR integration optimization methods. Demonstrated in a laboratory setting, the system is a versatile tool for research and industrial applications, fostering insights into robotic automation and digital twin scalability while reducing costs and risks associated with real-world testing. © 2025 IEEE.

关键词： Augmented reality

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：