检索结果-内蒙古大学图书馆

Blackout Mitigation via Physics-Guided RL

IEEE Transactions on Power Systems 2025年第3期40卷 2363-2375页

作者： Dwivedi, Anmol Paternain, Santiago Tajer, Ali Rensselaer Polytechnic Institute Electrical Computer and Systems Engineering Department TroyNY12180 United States

This paper considers the sequential design of remedial control actions in response to system anomalies to prevent blackouts. A physics-guided reinforcement learning (RL) framework is designed to identify effective sequences of real-time remedial look-ahead decisions accounting for the long-term impact on the system's stability. The paper considers a space of control actions involving both discrete-valued transmission line-switching decisions (line reconnections and removals) and continuous-valued generator adjustments. To identify an effective blackout mitigation policy, a physics-guided approach is designed that uses power-flow sensitivity factors associated with the power transmission network to guide the RL exploration during agent training. Comprehensive empirical evaluations using the open-source Grid2Op platform demonstrate the notable advantages of incorporating physical signals into RL decisions, establishing the gains of the proposed physics-guided approach compared to its black-box counterparts. One important observation is that strategically removing transmission lines, in conjunction with multiple real-time generator adjustments, often renders effective long-term decisions that are likely to prevent or delay blackouts. © 1969-2012 IEEE.

关键词： Electric load flow

来源：评论

学校读者我要写书评

暂无评论

A 500kHz Wide Output LLC-T Resonant Converter with Narrow Frequency Range, Reduced Circulating Energy, and Low Voltage Stress

引用

IEEE Transactions on Power Electronics 2025年第8期40卷 11749-11762页

作者： Hou, Zhengming Jiao, Dong Lai, Jih-Sheng Virginia Polytechnic Institute and State University Bradley Department of Electrical and Computer Engineering BlacksburgVA24061 United States

The resonant converters are promising topologies for the electric vehicle charging applications due to the soft switching feature. However, the conventional LLC resonant converter regulates the wide output voltage through a wide frequency range which leads to low efficiency with large circulating energy and the difficulty of the resonant tank optimization. This article proposes a novel LLC-T resonant converter which parallels an auxiliary transformer with the LC resonant tank for the wide output applications. The proposed LLC-T resonant converter narrows the frequency range with less circulating energy, lower voltage stress on the resonant capacitor, and smaller flux linkage in the resonant inductor compared to the conventional LLC resonant converter. Meanwhile, the zero-voltage switching turn-on is maintained throughout the wide output voltage range and load range. Furthermore, a precise time-domain based analysis and the design methodology are proposed. A 500-kHz, 1.35kW, 400V input /250V-450V output prototype is built to verify the concepts of the proposed topology and demonstrates a 97.82% peak efficiency. © 2025 IEEE.

关键词： Resonant converters

来源：评论

学校读者我要写书评

暂无评论

IC Backside Tamper Detection Using Impedance Sensing

引用

IEEE Access 2025年 13卷 90706-90725页

作者： Tahoura Mosavirik Shahin Tajik Electrical and Computer Engineering Department Worcester Polytechnic Institute Worcester MA USA

The expansion of flip-chip technologies and lack of backside protection made integrated circuits (ICs) vulnerable to certain classes of physical attacks mounted from the IC’s backside, including laser-assisted probing, electromagnetic side-channel analysis, body biasing injection (BBI), and focused ion beam (FIB) editing. Existing countermeasures are expensive, incompatible with standard IC fabrication, and unsuitable for legacy systems such as field-programmable gate arrays (FPGAs), which are widely used in industrial and defense systems. In this paper, we demonstrate how impedance monitoring of the printed circuit board (PCB) and the IC package’s power distribution network (PDN) using on-chip circuit-based network analyzers can detect IC backside tampering. Our method is based on the fact that any attempt to expose the backside silicon substrate, such as the removal of the fan and heatsinks, or polishing it, leads to changes in the equivalent impedance of the package’s PDN, and hence scanning the package impedance will reveal if the package integrity has been violated. To validate our claims, we deployed an on-FPGA network analyzer on an AMD Zynq UltraScale+ MPSoC (16 nm), which is part of a multi-PCB system. We performed a series of backside tamper attacks, including the removal of cooling components and IC backside silicon milling/polishing, across different temperatures, and evaluated detection effectiveness leveraging the difference of means as the statistical metric.

关键词： Impedance Silicon Optical sensors Integrated optics Transistors Substrates Sensors Photonics Flip-chip devices Optical imaging

来源：评论

学校读者我要写书评

暂无评论

Robust 3D point clouds classification based on declarative defenders

引用

Neural Computing and Applications 2025年第3期37卷 1209-1221页

作者： Li, Kaidong Zhang, Tianxiao Zhong, Cuncong Zhang, Ziming Wang, Guanghui Department of Electrical Engineering & Computer Science University of Kansas 1520 West 15th St. LawrenceKS66045 United States Department of Electrical & Computer Engineering Worcester Polytechnic Institute 100 Institute Rd. WorcesterMA01609 United States Department of Computer Science Toronto Metropolitan University 350 Victoria Street TorontoONM5B 2K3 Canada

3D point cloud classification requires distinct models from 2D image classification due to the divergent characteristics of the respective input data. While 3D point clouds are unstructured and sparse, 2D images are structured and dense. Bridging the domain gap between these two data types is a non-trivial challenge to enable model interchangeability. Recent research using lattice point classifier (LPC) highlights the feasibility of cross-domain applicability. However, the lattice projection operation in LPC generates 2D images with disconnected projected pixels. In this paper, we explore three distinct algorithms for mapping 3D point clouds into 2D images. Through extensive experiments, we thoroughly examine and analyze their performance and defense mechanisms. Leveraging current large foundation models, we scrutinize the feature disparities between regular 2D images and projected 2D images. The proposed approaches demonstrate superior accuracy and robustness against adversarial attacks. The generative model-based mapping algorithms yield regular 2D images, further minimizing the domain gap from regular 2D classification tasks. The source code is available at https://***/KaidongLi/***. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

Framework for Implementing Quantum Neural Networks in Wireless Communications

引用

IEEE Access 2025年 13卷 91655-91670页

作者： Salik Siddiqui Justin Holzer Joshua Malcarne Galahad M. B. Wernsing Alexander M. Wyglinski Electrical and Computer Engineering Department Worcester Polytechnic Institute Worcester MA USA

While quantum computing is already being employed in different domains to solve large scale and highly complex optimization problems, the wireless communications community has only recently begun exploring the potential of Quantum Machine Learning (QML). This paper provides a reference design approach that allows the wireless community to effectively leverage QML in optimizing their own wireless communications networks. Such an approach will become increasingly valuable as quantum computing matures and conventional computing methods reach their practical limits due to the high dimensionality of optimization problems. We present a detailed methodology enabling wireless communications practitioners to construct their own Quantum Neural Networks (QNN) implementations and benchmark their performance against conventional techniques. Optimization strategies for wireless communication channels using QNNs are explored. The resulting framework provides a generalizable, easy-to-adopt methodology for integrating QML into wireless networks, requiring minimal prior knowledge of quantum computing.

关键词： Quantum computing Wireless communication Optimization Neural networks Qubit Logic gates Quantum mechanics Machine learning computer architecture Wireless networks

来源：评论

学校读者我要写书评

暂无评论

Generalized Two-Point Visual Control Model of Human Steering for Accurate State Estimation1

引用

ASME Letters in Dynamic Systems and Control 2025年第1期5卷 011004页

作者： Mai, Rene E. Sears, Katherine Roessling, Grace Julius, Agung Mishra, Sandipan Department of Mechanical Aerospace and Nuclear Engineering Rensselaer Polytechnic Institute TroyNY12180 United States Department of Cognitive Science Rensselaer Polytechnic Institute TroyNY12180 United States Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute TroyNY12180 United States

We derive and validate a generalization of the two-point visual control model, an accepted cognitive science model for human steering behavior. The generalized model is needed as current steering models are either insufficiently accurate or too complex for online state estimation. We demonstrate that the generalized model replicates specific human steering behavior with high precision (85% reduction in modeling error) and integrate this model into a human-as-advisor framework where human steering inputs are used for state estimation. As a benchmark study, we use this framework to decipher ambiguous lane markings represented by biased lateral position measurements. We demonstrate that, with the generalized model, the state estimator can accurately estimate the true vehicle state, providing lateral state estimates with under 0.15 m error across participants. However, without the generalized model, the estimator cannot accurately estimate the vehicle's lateral state. © 2024 by ASME.

关键词： Man machine systems

来源：评论

学校读者我要写书评

暂无评论

Optimized ROI Extraction and Pixel Reduction Methods for Kidney Abnormality Detection

Optimized ROI Extraction and Pixel Reduction Methods for Kid...

引用

2025 IEEE SoutheastCon, SoutheastCon 2025

作者： Hossain, Md Junayed Monir, Md Fahad Ahmed, Tarem Department of Computer Science & Engineering Bangladesh Virginia Polytechnic Institute and State University Department of Electrical and Computer Engineering United States

ISBN: (纸本)9798331504847

A global public health concern, Chronic Kidney Disease causes renal failure, cardiovascular disease, and premature death. Given the frequency of kidney diseases and their significant impact on public health, detection of any abnormalities in the kidney is crucial. Effective patient treatment and medical care planning depend on the early and precise diagnosis of a variety of kidney abnormalities. Early detection enable treatments that enhance patient outcomes, slow the progression of disease, and lessen the strain on healthcare systems. In order to detect anomalies in kidney, we utilized the Region of Interest (ROI) and Pixel Reduction techniques separately in this work. We have applied the Bicubic Interpolation method to reduce the size of individual pixels in an image while preserving a significant data of the original image data. A novel hybrid strategy that aims to preserve diagnostic data while reducing computing complexity uses the original images for ROI extraction. The deep learning method is then independently trained and tested using the pixel-reduced and localized dataset. In order to categorize the images, we use Inception V3 and EfficientNet B7 as Deep Learning models. Using the ROI-extracted data, we were able to achieve approximately 99.75% accuracy with the EfficientNet B7 model. Moreover, the same algorithm and dataset were used to obtain 98.45%, 99.02%, and 98.78% Precision, Recall, and F1-score, respectively. This framework provides medical professionals with a helpful prognostic tool to early detect identify various forms of kidney abnormalities. © 2025 IEEE.

关键词： Surgery

来源：评论

学校读者我要写书评

暂无评论

Comparative Performance of Object Detection Algorithms Under Low Illumination Conditions

Comparative Performance of Object Detection Algorithms Under...

引用

2025 IEEE SoutheastCon, SoutheastCon 2025

作者： Hossain, Md Junayed Rahman, Shoptorshi Monir, Md Fahad Ahmed, Tarem Department of Computer Science & Engineering Bangladesh Virginia Polytechnic Institute and State University Department of Electrical and Computer Engineering United States

ISBN: (纸本)9798331504847

Real-time object detection is pivotal in various computer vision and robotics applications, such as security surveillance, autonomous navigation, and interactive systems. This study evaluates several object detection algorithms under low illumination conditions, comparing traditional methods including SIFT, SURF, ORB, BRISK, KAZE, and AKAZE with the deep learning model YOLOv5. To simulate these conditions, we utilized the COCO dataset and implemented a sequence of preprocessing procedures, such as adjusting the gamma correction throughout the dataset, introducing Gaussian noise, and equalizing the histogram to improve image contrast. Here, YOLOv5 exhibited superior performance, achieving a detection accuracy of 92.47% and a processing time of 45 milliseconds per image. Traditional algorithms like SURF and KAZE, although slower, demonstrated precision rates of 78.54% and 76.86%, respectively. YOLOv5 also identified the highest number of key points and matches. Our findings indicate that while YOLOv5 excels in real-time detection under low-light conditions, traditional methods are effective for specific tasks in resource-constrained environments. This study benchmarks these algorithms and proposes a hybrid approach to enhance real-time object detection systems under low illumination conditions. © 2025 IEEE.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Receiver Side Regulation of LCC Wireless Power Transfer System with Variable Notch Filter 14

Receiver Side Regulation of LCC Wireless Power Transfer Syst...

引用

14th Annual IEEE Applied Power Electronics Conference and Exposition, APEC 2025

作者： Hsieh, Hsin-Che Lai, Jih-Sheng Virginia Polytechnic Institute and State University The Bradley Department of Electrical and Computer Engineering BlacksburgVA United States

ISBN: (纸本)9798331516116

The robustness and relative insensitivity to misalignments and mismatches make the LCC topology popular in wireless power transfer (WPT) applications, including more challenging dynamic or multi-receiver WPT systems. The output of LCC topology based WPT systems is typically regulated by an additional dc-dc converter stage, either before or after the WPT stage. The additional dc-dc stage increases the cost and complexity of the system and would require wireless communication for output regulation if placed on the transmitter side, making the system susceptible to electromagnetic interference. In this paper, a receiver side modulation scheme based on a variable inductor controlled notch filter is proposed. By modulating the variable inductor, the output can be independently adjustable in a wide-range. The variable inductor is controlled with simple pulse width modulation (PWM). The proposed control scheme is especially suitable for multi-receiver WPT systems;where transmitter based regulation schemes cannot simultaneously accommodate multiple receivers. The proposed system is verified experimentally with a 48-Vo(max), 72-W prototype WPT system with multi-receiver capability. © 2025 IEEE.

关键词： Notch filters

来源：评论

学校读者我要写书评

暂无评论

Hybrid Islanding Detection of an Inverter-Based High-Noise Microgrid

引用

IEEE Access 2025年 13卷 73161-73172页

作者： Amini, Hossein Mehrizi-Sani, Ali Noroozian, Reza Quanta Technology Transmission & Regulatory RaleighNC27607 United States Virginia Polytechnic Institute and State University The Bradley Department of Electrical and Computer Engineering BlacksburgVA24061 United States University of Zanjan Department of Electrical Engineering Zanjan45371-38791 Iran

Unintentional islanding occurs when a microgrid continues operating independently after disconnection from the main grid, which can lead to voltage and frequency instability, power quality degradation, and safety risks. Few local and remote methods consider islanding detection in noisy environments. Noise can interfere with measurements and cause failed or delayed islanding detection. This paper proposes a hybrid islanding detection method that utilizes a Van der Pol Duffing oscillator (VDPDO), focusing on decreasing the detection period, zero power mismatch nondetection zone, and power quality degradation. The proposed method uses the fast Fourier transform (FFT) symmetry characteristic of a hybrid VDPDO (HVDPDO) output signal and addresses the set point threshold using the Melnikov function. This method detects the changes in frequency, phase, and voltage amplitude of the point of common coupling (PCC) simultaneously to distinguish islanded operation from other faults. For the asymmetric FFT waveform of the passive HVDPDO, the islanding system sends a signal to the inverter to change the mode from grid-following to grid-forming and injects perturbations into the frequency, phase, and voltage amplitude, simultaneously. The active HVDPDO detects islanded operations with a small non-detection zone. The inverter reverts to grid-following mode for other faults, and the main grid damps the intentionally small perturbations. Simulation and experimental results validate that the proposed method meets the IEEE standard 1547 criteria. © 2013 IEEE.

关键词： Power quality

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：