检索结果-内蒙古大学图书馆

Cost-Effective Power Delivery via Deep Reinforcement Learning-Based Dynamic Electric Vehicle Transportation

IEEE Internet of Things Journal 2025年

作者： Bao, Zheng Tang, Changbing Yu, Xinghuo Lin, Feilong Wen, Guanghui Zheng, Zhonglong Zhejiang Normal University School of Computer Science and Technology Jinhua321004 China Zhejiang Normal University College of Physics and Electronics Information Engineering Jinhua321004 China Rmit University School of Engineering VIC3000 Australia Southeast University School of Automation Nanjing211189 China

Power delivery issues are increasingly evident in cyber-physical smart grid systems as energy transactions frequently overlook the physical constraints of distribution, leading to transmission congestion and compromising network security and reliability. This paper presents a novel and cost-effective solution to power delivery challenges by utilizing electric vehicles (EVs) with dynamic transportation capabilities as free carriers. Unlike traditional approaches, a deep reinforcement learning (DRL)-based optimization framework is designed to effectively manage incomplete information in real-time. Our method first introduces an investment-free model that leverages existing EV routes to transport energy during congestion, operating in a "free-riding"transmission mode. This not only enhances network reliability but also curtails costs. Then, we develop a Markov Decision Process (MDP) for sequential decision-making of 24-hour optimal control, aimed at minimizing operational losses including load shedding and battery degradation. To deal with the stochastic nature of energy requests and EV routes in the control problem, we employ a model-free DRL algorithm to tackle the challenge of incomplete information. An Actor-Critic network, combining value-based and policy-based approaches, helps discover approximately optimal strategies in a continuous action space. Finally, the simulation results numerically demonstrate the performance of the proposed method. © 2014 IEEE.

关键词： Markov processes

来源：评论

学校读者我要写书评

暂无评论

Electromagnetic Wave Modulation for Holographic Metasurface

Electromagnetic Wave Modulation for Holographic Metasurface

引用

European Conference on Antennas and Propagation, EuCAP

作者： Xinyu Zhang Yuchen Gao Qi Luo Tao Hong National Key Laboratory of Radar Detection and Sensing Xidian University Xi'an China School of Physics Engineering and Computer Science University of Hertfordshire Hatfield United Kingdom

ISBN: (数字)9788831299107

ISBN: (纸本)9798350366327

In this paper, an innovative method for designing planar and conformal holographic metasurface (HM) to modulate electromagnetic waves in desired directions is proposed. The designed holographic metasurfaces can precisely control the scattering waves, effectively enhancing the directionality of the beam. The holographic metasurfaces achieve scattering wave deflections in the range of ±60° at 10 GHz under incident plane waves with x- and y- polarization at arbitrary angles. Prototypes of the designed conformal holographic metasurfaces with different states are fabricated and measured, and the simulation and measurement results are in good agreement. The designed holographic metasurfaces have polarization insensitivity and adaptability to cylindrical platforms, which has big potential to be deployed for the smart radio environment to support wireless power transfer and wireless communications.

关键词： Antenna measurements Wireless communication Polarization Electric potential Systematics Modulation Prototypes Europe Wireless power transfer Metasurfaces

来源：评论

学校读者我要写书评

暂无评论

Low-latency control system for feedback experiments with optical tweezer arrays

arXiv

引用

arXiv 2025年

作者： Dadpour, Amir H. Khayrullin, Timur Afiouni, Fouad Sabeh, Remy El Mouawad, Amer E. Hajj, Izzat El Cooper, Alexandre Institute for Quantum Computing University of Waterloo Canada Department of Computer Science American University of Beirut Lebanon School of Electrical and Computer Engineering Purdue University United States David R. Cheriton School of Computer Science University of Waterloo Canada Department of Physics and Astronomy University of Waterloo Canada

We present and characterize a modular, open-source system to perform feedback control experiments on configurations of atoms and molecules in arrays of optical tweezers. The system features a modular, cost-effective computer architecture with a motherboard and peripheral cards. It supports efficient data transfer to and from graphics processing units (GPUs) using Remote Direct Memory Access (RDMA), leveraging GPU efficiency in matrix multiplication and parallelism, while enabling direct data transfer between devices without involving the CPU. We first describe the architecture and workflow of the system, detailing its hardware components and software modules. We then evaluate the computational runtime for preparing defect-free chains and grids of atoms using efficient implementations of atom reconfiguration algorithms. Finally, we discuss timing bottlenecks and strategies to reduce latency. Beyond solving reconfiguration problems, the system can readily be used to implement adaptive and feedforward protocols, as well as digital quantum algorithms relying on particle displacement. Our results lay the groundwork for developing low-latency feedback control systems, benchmarking their performance, and advancing scalable quantum hardware. © 2025, CC BY.

关键词： Feedback control

来源：评论

学校读者我要写书评

暂无评论

Control of Chirality and Directionality of Nonlinear Metasurface Light Source via Moiré engineering

引用

Physical Review Letters 2025年第4期134卷 043801-043801页

作者： Huanyu Zhou Xueqi Ni Beicheng Lou Shanhui Fan Yuan Cao Haoning Tang Department of Electrical Engineering and Computer Science University of California at Berkeley Berkeley California 94720 USA Department of Physics National University of Singapore Singapore 119077 Department of Applied Physics and Ginzton Laboratory Stanford University Stanford California 94305 USA School of Engineering and Applied Sciences Harvard University Cambridge Massachusetts 02138 USA

Metasurfaces have revolutionized nonlinear and quantum light manipulation in the past decade, enabling the design of materials that can tune polarization, frequency, and direction of light simultaneously. However, tuning of metasurfaces is traditionally achieved by changing their microscopic structure, which does not allow in situ tuning and dynamic optimization of the metasurfaces. In this Letter, we explore the concept of twisted bilayer and tetralayer nonlinear metasurfaces, which offer rich tunability in its effective nonlinear susceptibilities. Using gold-based metasurfaces, we demonstrate that a number of different singularities of nonlinear susceptibilities can exist in the parameter space of twist angle and interlayer gap between different twisted layers. At the singularities, reflected or transmitted light from the nonlinear process (such as second-harmonic generation) can either become circularly polarized (for C points), or entirely vanish (for V points). By further breaking symmetries of the system, we can independently tune all aspects of the reflected and transmitted nonlinear emission, achieving unidirectional emission with full-Poincaré polarization tunability, a dark state (V−V point), or any other bidirectional output. Our work paves the way for multidimensional control of polarization and directionality in nonlinear light sources, opening new avenues in ultrafast optics, optical communication, sensing, and quantum optics.

关键词： Quantum optics

来源：评论

学校读者我要写书评

暂无评论

Dynamical Electromagnetic fields and Dynamical Electromagnetic Anomaly in heavy ion collisions at intermediate energies

arXiv

引用

arXiv 2025年

作者： Siddique, Irfan Huang, Anping Huang, Mei Wasaye, Muhammad Abdul School of Nuclear Science and Technology University of Chinese Academy of Sciences Beijing101408 China School of Material Science and Physics China University of Mining and Technology Xuzhou221116 China School of Computer Science and Engineering Hunan Institute of Technology Hunan Hengyang421001 China

Electromagnetic field produced in non-central heavy ion collisions play a crucial role in phenomena such as chiral anomalous effects, directed flow of mesons and splitting of spin polarization of Λ/Λ¯. A precise description of these fields is essential for quantitatively studying these effects. We investigate the space-time evolution of the electromagnetic fields by numerically solving Maxwell’s equations using the results from the UrQMD model, rather than relying on an ansatz. We present the space-averaged dynamic electromagnetic fields, weighted by energy density, in the central region of heavy-ion collisions. These measurements can serve as a barometer for assessing the effects induced by magnetic fields. Comparing the fields at geometric center of the collisions, the space-averaged dynamical fields weighted by the energy density are smaller at the early stage but damp much slower at the later stage. We discuss the impact of these space averaged dynamical magnetic fields on the spin polarization and spin alignment in heavy ion collisions. Additionally, we explore the opportunity to study non-perturbative regime of Quantum Electrodynamics (QED) by presenting the simulation results for space averaged dynamical electric field at intermediate collision energies. Finally, the space-averaged dynamical electromagnetic anomaly E · B weighted by energy density is also calculated and compared with experimentally measured slope parameter r. Copyright © 2025, The Authors. All rights reserved.

关键词： Spin polarization

来源：评论

学校读者我要写书评

暂无评论

Hydrodynamic Optimization Design of Underwater Glider Wings Based on Biomimetic Principles 24

Hydrodynamic Optimization Design of Underwater Glider Wings ...

引用

Proceedings of the 2024 4th International Conference on Computational Modeling, Simulation and Data Analysis

作者： Hong He Tianding Chen Hui Wang Ao Chen Xin Yu Yimei Fan School of Physics and Information Engineering Minnan Normal University Zhangzhou Fujian China School of Data and Computer Science Xiamen Institute of Technology Xiamen Fujian China School of Computing and Information Science Fuzhou Institute of Technology Fuzhou Fujian China

ISBN: (纸本)9798400711831

This paper designs a bionic sea turtle fin, which mimics the shape of the sea turtle's forelimbs and maintains an overall streamlined shape to reduce the resistance received by the outer side of the fin. This is of great significance and practical value for exploring new underwater propulsion methods and enriching and improving underwater propulsion technology. In terms of shape design, this paper uses Solid Works software to design the shape according to the contour of the sea turtle's forelimbs, and based on bionic principles, analyzes the flapping motion rules and propulsion mechanism of the sea turtle. To verify that the efficiency of the biomimetic turtle hydrofoil traction machine is higher than that of traditional traction machines, this study focuses on the optimization of the external shape configuration. The Flow Simulation plugin within the Solid Works software is applied to perform computational fluid dynamics CFD) simulations on the biomimetic turtle hydrofoil traction machine. Analyze the impact of different distances and different pitch angles between the fins on the motion performance; set the calculation domain, boundary conditions, residuals, inlet velocity, and sea conditions, etc., and perform simulation experiments on the bionic sea turtle fin tractors with different distances and different angles; analyze the obtained velocity cloud diagram and pressure cloud diagram. The results show that the ocean current resistance received by the bionic sea turtle fin tractor is significantly less than that of the traditional tractor, which verifies the feasibility of the bionic fin and its good application prospects.

关键词： Bionic Design

来源：评论

学校读者我要写书评

暂无评论

CapsPDNet: Optimized Capsule Network for Predicting Insulator Discharges Using UHF Signals

引用

IEEE Transactions on Instrumentation and Measurement 2025年 74卷

作者： Saleh, Mohammad AlShaikh Darwish, Ahmad Ghrayeb, Ali Refaat, Shady S. Abu-Rub, Haitham Khatri, Sunil P. El-Hag, Ayman H. Kumru, Celal F. Texas A&M University Department of Electrical and Computer Engineering College StationTX77843 United States Purdue University School of Electrical and Computer Engineering Birck Nanotechnology Center Elmore Family School of Electrical and Computer Engineering West LafayetteIN47907 United States Hamad Bin Khalifa University College of Science and Engineering Doha Qatar University of Hertfordshire School of Physics Engineering and Computer Science HatfieldAL10 9AB United Kingdom University of Waterloo Electrical and Computer Engineering Department WaterlooONN2L 3G1 Canada Suleyman Demirel University Electrical and Electronics Engineering Department Isparta32260 Turkey

Outdoor insulation systems often suffer from partial discharge (PD) faults that compromise the reliability of electrical grids. This article proposes an integrated approach combining a noninvasive downsized discone antenna to capture ultrahigh-frequency signals and an optimized capsule network (CapsPDNet) for robust PD fault prediction. The CapsPDNet is chosen as it overcomes the information loss associated with pooling operations and leverages vector representations, providing more nuanced predictions than scalar values, especially when the predictions are made across different antenna locations. Three typical PD fault types are targeted: surface discharges on ceramic and polymeric materials, internal discharges, and corona discharges, and then multiple signal processing techniques are evaluated to determine the most effective feature extraction and reconstruction technique. Experimental results show that the proposed model achieves up to a 18.89% improvement in PD fault prediction accuracy over benchmark approaches, demonstrating high generalizability and scalability when considering different antenna locations. The patented antenna used in this study offers a compact size through a novel size reduction technique, covers a wide bandwidth, and exhibits high sensitivity to PD activities. Additionally, discrete wavelet transform (DWT) is chosen as the feature extractor as it provides high-importance features with the lowest computational time, offering a more reliable and scalable solution for early PD fault detection and real-time condition monitoring of insulation systems. © 1963-2012 IEEE.

关键词： Electric corona

来源：评论

学校读者我要写书评

暂无评论

Predictive Modeling of Solar Power Generation Using Deep Learning for Real-Time Optimization in Photovoltaic System

Predictive Modeling of Solar Power Generation Using Deep Lea...

引用

2025 International Conference on Intelligent Control, Computing and Communications, IC3 2025

作者： Bafna, Minal Thakur, Hardeo Kumar Singh, Jagendra Reddy, P. Srinivas Ekvitayavetchanukul, Pongkit Rana, Manoj Agrawal P. G. College Department of Physics Jaipur India School of Computer Science Engineering & Technology Bennett University Greater Noida India Cvr College of Engineering Department of Mechanical Engineering Hyderabad India The Board of Khonkaen University Affaneirs Khonkaen University Thailand Teerthanker Mahaveer University Cdoe Moradabad India

ISBN: (纸本)9798331527495

This research addresses the need for precise solar power generation forecasting and optimization of energy management within photovoltaic systems;this is important as there is a greater demand for renewable energy sources. Reliable predictions of the output of solar power would enhance stability in the grid and thus ensure efficient distribution of the energy. This research uses deep learning techniques, the Long Short-Term memory (LSTM) model, to predict solar power generation from several environmental variables, including solar irradiation, air temperature, wind speed, relative humidity, air pressure, module power, and module temperature. To validate the performance of the model, rigorous use of metrics like Mean absolute error (MAE), Root Mean Square Error (RMSE), and Mean absolute percentage error (MAPE) was made. The proposed LSTM model gave an MAE of 0.25 kW, an RMSE of 0.35 kW, and a MAPE of 5%. This was better compared to other models like Gated recurrent unit (GRU), recurrent neural network (RNN), and Artificial neural network (ANN). A real-time implementation of the LSTM model depicted the fact that it is feasible to use the model to make correct predictions of the amount of solar power produced throughout the day. At peak periods, such as midday hours, accuracy levels hit 98% in some cases, whereas the model is compelling enough to pinpoint and respond accordingly to changing solar power production volumes for optimizing load management and energy supply. This research verifies the deep learning model and its efficiency in energy forecasting, with intense stress on the practical application of the LSTM model in real-time energy management, contributing a lot to the advancement of renewable energy integration and optimizing power systems. Finally, this research provides valuable insight into improving the operational efficiency of photovoltaic systems in order to make the future energy scenario more sustainable. © 2025 IEEE.

关键词： Power management (telecommunication)

来源：评论

学校读者我要写书评

暂无评论

physics-guided hierarchical neural networks for Maxwell’s equations in plasmonic metamaterials

arXiv

引用

arXiv 2025年

作者： Lynch, Sean LaMountain, Jacob Fan, Bo Bu, Jie Raju, Amogh Wasserman, Dan Karpatne, Anuj Podolskiy, Viktor A. Miner School of Computer Science University of Massachusetts Lowell LowellMA01854 United States Department of Physics and Applied Physics University of Massachusetts Lowell LowellMA01854 United States Department of Computer Science Virginia Tech United States Department of Electrical and Computer Engineering University of Texas Austin United States

While machine learning (ML) has found multiple applications in photonics, traditional "black box" ML models typically require prohibitively large training datasets. Generation of such data, as well as the training processes themselves, consume significant resources, often limiting practical applications of ML. Here we demonstrate that embedding Maxwell’s equations into ML design and training significantly reduces the required amount of data and improves the physics-consistency and generalizability of ML models, opening the road to practical ML tools that do not need extremely large training sets. The proposed physics-guided machine learning (PGML) is illustrated on the example of predicting complex field distributions within hyperbolic metamaterial-based photonic funnels. The hierarchical network design used in the study points to the emergence of effective medium theories within neural networks. Copyright © 2025, The Authors. All rights reserved.

关键词： Maxwell equations

来源：评论

学校读者我要写书评

暂无评论

Structural, magnetic, and mechanical properties enhancement in Mn-Zn ferrites via controlled lithium ion doping

引用

Physica B: Condensed Matter 2025年 713卷

作者： Torabi, Naeimeh Savabieh, Hamid Reza Elahi, Ali Atomic and Molecular Division Faculty of Physics Yazd University Yazd Iran Department of Materials Science Tarbiat Modares University Tehran Iran School of Electrical and Computer Engineering University of Tehran Tehran Iran

In this work, lithium-doped manganese-zinc (Mn-Zn) ferrites were synthesized using a conventional solid-state route to investigate the effects of lithium (Li+) incorporation on their structural, magnetic, and mechanical properties. The main objective was to develop phase-pure and mechanically robust magnetic ceramics suitable for high-frequency applications. Ferrite compositions with various Li+ contents (x = 0, 0.03, 0.05, and 0.1) were sintered under controlled atmosphere to promote densification and phase purity. XRD and FTIR analyses confirmed spinel structure formation and the suppression of hematite as a secondary phase with increasing Li+. SEM results revealed enhanced microstructural uniformity, while mechanical tests showed a 28 % increase in flexural strength. Magnetic measurements indicated that saturation magnetization (Ms) increased from 60.8 to 78.4 emu/g with Li+ addition. These results demonstrate that controlled lithium doping is an effective strategy for tailoring both the magnetic and mechanical performance of Mn-Zn ferrite ceramics. © 2025

关键词： Saturation magnetization

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：