检索结果-内蒙古大学图书馆

European Conference on Antennas and Propagation, EuCAP

作者： Priyangshu Sen Sherif Badran Josep M. Jornet Arjun Singh Department of Engineering SUNY Polytechnic Institute Utica NY USA Department of Electrical and Computer Engineering Northeastern University Boston MA USA

ISBN: (数字)9788831299107

ISBN: (纸本)9798350366327

Terahertz band (0.1-10 THz) communication is set to play a pivotal role in the advancement of subsequent generations of wireless technology by facilitating high data rates, ultra-secure transmission, high-resolution sensing, and low-latency links, among others. Nevertheless, the issues of low transmission power and high path loss necessitate large-aperture high-gain antennas, which can result in a considerably expanded near-field operational region. The distinctive mechanism of wave propagation within this region, as well as its transition to the far-field area, necessitates a comprehensive reevaluation of channel modeling. In this paper, we discuss the effects of antennas on path loss models and channel metrics while operating in both the near- and far-field regions. We present a detailed analysis of near-field propagation mechanisms, illustrating that an antenna-agnostic channel model is not feasible. Furthermore, we discuss the potential benefits and challenges associated with these regions.

关键词： Wireless communication Measurement Wireless sensor networks Propagation Transmitting antennas Propagation losses Transceivers Sensors Channel models Terahertz communications

来源：评论

学校读者我要写书评

暂无评论

Guest Editorial Enabling Technologies and Systems for Industry 5.0: From Foundation Models to Foundation Intelligence

引用

IEEE Transactions on Systems, Man, and Cybernetics: Systems 2024年第11期54卷 6496-6499页

作者： Tang, Ying Tian, Yonglin Lin, Yilun Lv, Chen Fanti, Maria Pia Rowan University Department of Electrical and Computer Engineering GlassboroNJ08028 United States Chinese Academy of Sciences State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing100190 China Institute of Automation Chinese Academy of Sciences Beijing100190 China Shanghai AI Laboratory Urban Computing Laboratory Shanghai200232 China Nanyang Technological University School of Mechanical and Aerospace Engineering Jurong West639798 Singapore Polytechnic University of Bari Department of Electrical and Information Engineering Bari70126 Italy

来源：评论

学校读者我要写书评

暂无评论

Principled penalty-based methods for bilevel reinforcement learning and RLHF 24

Principled penalty-based methods for bilevel reinforcement l...

引用

Proceedings of the 41st International Conference on Machine Learning

作者： Han Shen Zhuoran Yang Tianyi Chen Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute Department of Statistics and Data Science Yale University

Bilevel optimization has been recently applied to many machine learning tasks. However, their applications have been restricted to the supervised learning setting, where static objective functions with benign structures are considered. But bilevel problems such as incentive design, inverse reinforcement learning (RL), and RL from human feedback (RLHF) are often modeled as dynamic objective functions that go beyond the simple static objective structures, which pose significant challenges of using existing bilevel solutions. To tackle this new class of bilevel problems, we introduce the first principled algorithmic framework for solving bilevel RL problems through the lens of penalty formulation. We provide theoretical studies of the problem landscape and its penalty-based (policy) gradient algorithms. We demonstrate the effectiveness of our algorithms via simulations in the Stackelberg game and RLHF.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Enhancing Track Management Systems with Vehicle-To-Vehicle Enabled Sensor Fusion

Enhancing Track Management Systems with Vehicle-To-Vehicle E...

引用

IEEE Conference on Vehicular Technology (VTC)

作者： Thomas Billington Ansh Gwash Aadi Kothari Lucas Izquierdo Timothy Talty Department of Computer Science Virginia Polytechnic Institute and State University Blacksburg VA USA Department of Electrical and Computer Engineering Virginia Polytechnic Institute and State University Blacksburg VA USA

ISBN: (数字)9798331517786

ISBN: (纸本)9798331517793

In the rapidly advancing landscape of connected and automated vehicles (CAV), the integration of Vehicle-to-Everything (V2X) communication in traditional fusion systems presents a promising avenue for enhancing vehicle perception. Addressing current limitations with vehicle sensing, this paper proposes a novel Vehicle-to-Vehicle (V2V) enabled track management system that leverages the synergy between V2V signals and detections from radar and camera sensors. The core innovation lies in the creation of independent priority track lists, consisting of fused detections validated through V2V communication. This approach enables more flexible and resilient thresholds for track management, particularly in scenarios with numerous occlusions where the tracked objects move outside the field of view of the perception sensors. The proposed system considers the implications of falsification of V2X signals which is combated through an initial vehicle identification process using detection from perception sensors. Presented are the fusion algorithm, simulated environments, and validation mechanisms. Experimental results demonstrate the improved accuracy and robustness of the proposed system in common driving scenarios, highlighting its potential to advance the reliability and efficiency of autonomous vehicles.

关键词： Measurement Target tracking Error analysis Vehicular ad hoc networks Radar Sensor fusion Radar tracking Sensor systems Sensors Vehicle-to-everything

来源：评论

学校读者我要写书评

暂无评论

Efficient Sum of Squares-Based Verification and Construction of Control Barrier Functions by Sampling on Algebraic Varieties

Efficient Sum of Squares-Based Verification and Construction...

引用

IEEE Conference on Decision and Control

作者： Hongchao Zhang Zhouchi Li Hongkai Dai Andrew Clark Department of Electrical and Systems Engineering Washington University in St. Louis St. Louis MO USA Department of Electrical and Computer Engineering Worcester Polytechnic Institute Worcester MA USA Toyota Research Institute Los Altos CA USA

Safety is a critical property of control systems in vital applications such as manufacturing, energy, and autonomous vehicles. Control barrier functions have been proposed for safe control, however, verifying the safety guarantees of a given CBF and constructing CBFs to satisfy safety constraints are computationally challenging. In this paper, we propose a new approach to addressing these challenges, in which the global safety properties of CBFs are characterized based on a finite set of sample points. Specifically, we propose new algorithms for verifying CBFs for polynomial systems by solving a system of linear equalities and sum-of-squares constraints at a set of points sampled on an algebraic variety induced by the CBF. We extend this approach to high-order CBFs as well as systems with actuation constraints. Turning to the problem of constructing CBFs, we propose an algorithm that first selects a finite set of samples, and then computes a CBF such that the samples lie on the boundary of the safe region by solving a mixed-integer convex program. We prove that, if the number of samples is sufficiently large and a CBF exists, then our approach returns a function that satisfies necessary conditions of a CBF. We evaluate our approach on a linear cruise control scenario and a nonlinear quadrotor UAV, and find that both the verification and synthesis algorithms significantly outperform another state-of-the-art SOS-based algorithm.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Novel Approach to Smart Grid Energy Management Using the Osprey Optimization Algorithm 4

A Novel Approach to Smart Grid Energy Management Using the O...

引用

4th International Conference on Sentiment Analysis and Deep Learning, ICSADL 2025

作者： Rudrapogu, Nissisolomon Hemalatha, N. Warkad, Sanjay B Jayanthi, A. Vinoth, K. Jayaram, B. Lecturer in Eee Nissisolomon Rudrapogu Mbts Government Polytechnic College Department of Electrical and Electronics Engineering Section Andhra Pradesh Guntur522005 India Bharath Institute of Higher Education and Research Department of Electrical and Electronics Engineering Tamil Nadu Chennai600073 India P. R. Pote Patil College of Engineering & Management Department of Electrical Engineering Maharashtra Amravati444602 India Jeppiaar Institute of Technology Department of Physics Tamil Nadu Sriperumbudur631502 India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Electrical and Electronics Engineering Tamil Nadu Chennai600062 India Rmk Engineering College Department of Computer Science and Business Systems Tamil Nadu Thiruvallur601206 India

ISBN: (纸本)9798331523923

Smart Grid Energy Management (SGEM) denotes the function of optimizing energy flow in the grid while enhancing grid efficiency and stability. One major issue is that increased integration of Renewable Energy Sources (RESs) may add a layer of complexity to EM, which may, in turn, reduce the reliability and stability of the grid. Keeping such challenges in mind, this paper proposes the Osprey Optimization Algorithm (OOA) on its part to enhance SGEM through various facets of load balancing and energy distribution. The objective of this method is to minimize the Mean Absolute Percentage Error (MAPE), enhancing the precision of energy predictions and optimizing grid performance. The OOA optimizes energy distribution in micro grids, improving efficiency and reducing power losses. The performance of the suggested OOA method is assessed by contrasting it with other optimization approaches that are currently in use, including Particle Swarm Optimization (PSO), Multi Objective Genetic Algorithm (MOGA), Sparrow Search Algorithm (SSA), and Multi Objective Wind Driven Optimization (MOWDO). The OOA method is implemented on the MATLAB platform. The outcomes show that the proposed OOA method provides superior performance in minimizing MAPE, achieving the lowest MAPE value of 0.28%, indicating its enhanced accuracy in energy demand forecasting and optimization. © 2025 IEEE.

关键词： Clean energy

来源：评论

学校读者我要写书评

暂无评论

Artificial Intelligence assisted Electric Vehicles Fast Charging Station Design using Grid Distribution Network Model 4

Artificial Intelligence assisted Electric Vehicles Fast Char...

引用

4th International Conference on Intelligent Technologies, CONIT 2024

作者： Anitha, C. Chitra, K. Vijayalakshmi, G. Kumaran, G. Vijetha, T. Ormila, K. Saveetha Institute of Medical and Technical Sciences Saveetha University Saveetha School of Engineering Department of Computer Science and Engineering Tamil Nadu Chennai India Cmr Institute of Technology Department of Electrical and Electronics Engineering Karnataka Bengaluru India Prince Shri Venkateshwara Padmavathy Engineering College Department of Electronics and Communication Engineering Tamil Nadu Chennai India Saveetha Institute of Medical and Technical Sciences Saveetha University Saveetha School of Engineering Department of Cse Tamilnadu Chennai India Mlr Institute of Technology Department of Ece Hyderabad Dundigal India A.M.K. Technological Polytechnic College Department of Electrical and Electronics Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350349900

The electric vehicle charging station is a game-changer that supplants the older kind of charging stations. Our futuristic electric vehicle charging station may be installed virtually anywhere, takes minimal space, and operates independently of the government's power source, in contrast to the current practice of reserving these stations for major urban areas. Among the many global industries that rely on fossil fuels, transportation ranks high. The development of electric vehicles (EVs) and other forms of transportation electrification are thus essential in the fight against carbon-dioxide emissions and the over-reliance on traditional energy sources that are harmful to the environment. At the same time, electricity distribution, use, and supply have been accompanied by massive amounts of data due to the fast digitization of electrical networks and EVs. These datasets may be used to inform choices and insights by using artificial intelligence (AI) algorithms. Despite a number of recent studies in this area, no one has explicitly examined the usefulness of AI for charge-demand profiling, data augmentation, demand forecasting, explainability of demand, and charge optimization of the EVI. For the purpose of efficiently delivering the fast charging function, this study suggested a novel logic called Grid Distributed Fast EV Charging (GDFEVC). To evaluate the proposed model's efficiency, it was cross-validated with the standard Fast EV Charging Model (FEVCM). This AI framework has been empirically tested on a real-world EVI case study, and the results show that it helps with the new problems with dispersed energy supplies that are coming up with EV adoption. © 2024 IEEE.

关键词： Charging stations

来源：评论

学校读者我要写书评

暂无评论

Geometrodynamics of a 2D Curved Surface due to a Constrained Quantum Particle via its Gravitational Dual

arXiv

引用

arXiv 2024年

作者： McMillin, Connor Rodriguez, Leo Rodriguez, Shanshan Ram-Mohan, L.R. Xing, Zhenzhong Department of Physics Grinnell College GrinnellIA50112 United States Department of Physics Worcester Polytechnic Institute WorcesterMA01609 United States Department of Electrical and Computer Engineering Cornell University IthacaNY14850 United States

We provide a unique and novel extension of da Costa’s calculation of a quantum mechanically constrained particle. This is achieved by analyzing the perturbative back reaction of the quantum confined particle’s eigenstates and spectra upon the geometry of the curved surface itself, thereby addressing the problem of shape optimization in this scenario. We do this by first formulating a two dimensional action principle of the quantum constrained particle, which upon wave function variation reproduces Schrödinger’s equation including da Costa’s surface curvature induced potentials. We further demonstrate that our derived action principle is dual to a two dimensional dilation gravity theory and we vary its functional with respect to the embedded two dimensional inverse-metric to obtain the respective geometrodynamical Einstein equation. We solve this resulting Einstein equation perturbatively by first solving the da Costa’s Schrödinger equation to obtain an initial eigensystem, which is used as initial-input data for a perturbed metric inserted into the derived Einstein equation. As a proof of concept, we perform this calculation on a two-sphere and show its first iterative perturbed shape evolution. We also turn on external electromagnetic fields, which manifest themselves via a surface induced, pulled-back U(1) coupling in our two dimensional dual gravity theory, thereby revealing interesting and rich new surface physics in this specific paradigm. © 2024, CC BY.

关键词： Wave functions

来源：评论

学校读者我要写书评

暂无评论

Blackout Mitigation via Physics-guided RL

arXiv

引用

arXiv 2024年

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

This paper considers the sequential design of remedial control actions in response to system anomalies for the ultimate objective of preventing 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 that involve 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. © 2024, CC BY.

关键词： Electric load flow

来源：评论

学校读者我要写书评

暂无评论

Realistic Data Generation for 6D Pose Estimation of Surgical Instruments

arXiv

引用

arXiv 2024年

作者： Barragan, Juan Antonio Zhang, Jintan Zhou, Haoying Munawar, Adnan Kazanzides, Peter Department of Computer Science Johns Hopkins University BaltimoreMD21218 United States Department of Robotics Engineering Worcester Polytechnic Institute WorcesterMA01608 United States

Automation in surgical robotics has the potential to improve patient safety and surgical efficiency, but it is difficult to achieve due to the need for robust perception algorithms. In particular, 6D pose estimation of surgical instruments is critical to enable the automatic execution of surgical maneuvers based on visual feedback. In recent years, supervised deep learning algorithms have shown increasingly better performance at 6D pose estimation tasks;yet, their success depends on the availability of large amounts of annotated data. In household and industrial settings, synthetic data, generated with 3D computer graphics software, has been shown as an alternative to minimize annotation costs of 6D pose datasets. However, this strategy does not translate well to surgical domains as commercial graphics software have limited tools to generate images depicting realistic instrument-tissue interactions. To address these limitations, we propose an improved simulation environment for surgical robotics that enables the automatic generation of large and diverse datasets for 6D pose estimation of surgical instruments. Among the improvements, we developed an automated data generation pipeline and an improved surgical scene. To show the applicability of our system, we generated a dataset of 7.5k images with pose annotations of a surgical needle that was used to evaluate a state-of-the-art pose estimation network. The trained model obtained a mean translational error of 2.59 mm on a challenging dataset that presented varying levels of occlusion. These results highlight our pipeline’s success in training and evaluating novel vision algorithms for surgical robotics applications. Copyright © 2024, The Authors. All rights reserved.

关键词： Three dimensional computer graphics

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：