检索结果-内蒙古大学图书馆

Conference on Lasers and Electro-Optics (CLEO)

作者： Ankita Sharma Alperen Govdeli Tianyuan Xue Fu-Der Chen Xianshu Luo Hongyao Chua Guo-Qiang Lo Wesley D. Sacher Joyce K.S. Poon Max Planck Institute of Microstructure Physics Halle (Saale) Germany Department of Electrical and Computer Engineering University of Toronto Toronto Ontario Canada Advanced Micro Foundry Pte Ltd Singapore

We demonstrate single-lobe beam-steering over ~50° at λ=440-460 nm using an end-fire optical phased array coupled to a 1D grating for out-of-plane emission. The devices were integrated on implantable neural prob... 详细信息

ISBN: (纸本)9781957171258

关键词： Array waveguide devices Beam steering Emission Gradient index lenses Optogenetics Phased arrays

来源：评论

学校读者我要写书评

暂无评论

Multi-modal Image and Radio Frequency Fusion for Optimizing Vehicle Positioning

arXiv

引用

arXiv 2024年

作者： Huan, Ouwen Luo, Tao Chen, Mingzhe Beijing Laboratory of Advanced Information Network Beijing University of Posts and Telecommunications Beijing100876 China Department of Electrical and Computer Engineering Institute for Data Science and Computing University of Miami Coral GablesFL33146 United States

In this paper, a multi-modal vehicle positioning framework that jointly localizes vehicles with channel state information (CSI) and images is designed. In particular, we consider an outdoor scenario where each vehicle can communicate with only one BS, and hence, it can upload its estimated CSI to only its associated BS. Each BS is equipped with a set of cameras, such that it can collect a small number of labeled CSI, a large number of unlabeled CSI, and the images taken by cameras. To exploit the unlabeled CSI data and position labels obtained from images, we design an meta-learning based hard expectation-maximization (EM) algorithm. Specifically, since we do not know the corresponding relationship between unlabeled CSI and the multiple vehicle locations in images, we formulate the calculation of the training objective as a minimum matching problem. To reduce the impact of label noises caused by incorrect matching between unlabeled CSI and vehicle locations obtained from images and achieve better convergence, we introduce a weighted loss function on the unlabeled datasets, and study the use of a meta-learning algorithm for computing the weighted loss. Subsequently, the model parameters are updated according to the weighted loss function of unlabeled CSI samples and their matched position labels obtained from images. Simulation results show that the proposed method can reduce the positioning error by up to 61% compared to a baseline that does not use images and uses only CSI fingerprint for vehicle positioning. Copyright © 2024, The Authors. All rights reserved.

关键词： Expectation maximization algorithm

来源：评论

学校读者我要写书评

暂无评论

AI-Aided Height Optimization for NOMA-UAV Networks

AI-Aided Height Optimization for NOMA-UAV Networks

引用

computer Science, Information Technology and engineering (ICCoSITE), International Conference on

作者： Amira O. Hashesh Adly S. Tag Eldien Mostafa M. Fouda Rokaia M. Zaki Department of Electrical Engineering Faculty of Engineering at Shoubra Benha University Cairo Egypt High Institute for Engineering and Technology - Obour Egypt Department of Electrical and Computer Engineering Idaho State University Pocatello ID USA Center for Advanced Energy Studies (CAES) Idaho Falls ID USA Higher Institute of Engineering and Technology Kafrelsheikh Egypt

Currently, Unmanned Aerial Vehicles (UAVs) are gaining significant attention due to their potential to effectively carry out a variety of tasks with superior performance through the use of fifth-generation (5G) and sixth-generation (6G) networks. Non-orthogonal multiple access (NOMA) techniques can further improve the performance and efficiency while reducing the interference. In this paper, we propose the application of machine learning (ML) techniques to evaluate the outage performance of a NOMA-enabled UAV network. Specifically, this study investigates the optimal UAV height that allows two users on the ground to receive the best service when they are simultaneously served by one UAV. We generated our own dataset which included several network parameters. We then trained various machine learning techniques on this dataset, including artificial neural networks (ANN), support vector regression (SVR), and linear regression (LR). Our results indicate that ANN provides the best accuracy compared with SVR and LR, with an average root mean squared error (RMSE) of 0.0931.

关键词： Support vector machines NOMA Linear regression Artificial neural networks Machine learning Interference Autonomous aerial vehicles

来源：评论

学校读者我要写书评

暂无评论

LARGE LANGUAGE MODELS FOR FORECASTING AND ANOMALY DETECTION: A SYSTEMATIC LITERATURE REVIEW

arXiv

引用

arXiv 2024年

作者： Su, Jing Jiang, Chufeng Jin, Xin Qiao, Yuxin Xiao, Tingsong Ma, Hongda Wei, Rong Jing, Zhi Xu, Jiajun Lin, Junhong AT&T Center for Virtualization Southern Methodist University DallasTX United States Department of Computer Science and Engineering Ohio State University ColumbusOH United States Department of Computer Science The University of Texas at Austin AustinTX United States Department of Information System Universidad Internacional Isabel I de Castilla Burgos Spain Department of Computer & Information Science & Engineering University of Florida GainesvilleFL United States Academy for Advanced Interdisciplinary Studies Peking University Beijing China School of Computer Science Carnegie Mellon University PittsburghPA United States Department of Electrical and Computer Engineering University of Southern California Los AngelesCA United States Electrical Engineering & Computer Science Department Massachusetts Institute of Technology CambridgeMA United States

This systematic literature review comprehensively examines the application of Large Language Models (LLMs) in forecasting and anomaly detection, highlighting the current state of research, inherent challenges, and prospective future directions. LLMs have demonstrated significant potential in parsing and analyzing extensive datasets to identify patterns, predict future events, and detect anomalous behavior across various domains. However, this review identifies several critical challenges that impede their broader adoption and effectiveness, including the reliance on vast historical datasets, issues with generalizability across different contexts, the phenomenon of model hallucinations, limitations within the models’ knowledge boundaries, and the substantial computational resources required. Through detailed analysis, this review discusses potential solutions and strategies to overcome these obstacles, such as integrating multimodal data, advancements in learning methodologies, and emphasizing model explainability and computational efficiency. Moreover, this review outlines critical trends that are likely to shape the evolution of LLMs in these fields, including the push toward real-time processing, the importance of sustainable modeling practices, and the value of interdisciplinary collaboration. Conclusively, this review underscores the transformative impact LLMs could have on forecasting and anomaly detection while emphasizing the need for continuous innovation, ethical considerations, and practical solutions to realize their full potential. Copyright © 2024, The Authors. All rights reserved.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

First-principle Molecular Dynamics Studies of the Thermophysical Properties of LiF-NaF-ThF4

First-principle Molecular Dynamics Studies of the Thermophys...

引用

2022 Transactions of the American Nuclear Society Winter Meeting and Technology Expo, ANS 2022

作者： Grizzi, Vitor Department of Nuclear Plasma and Radiological Engineering University of Illinois at Urbana-Champaign UrbanaIL61801 United States Beckman Institute for Advanced Science and Technology University of Illinois at Urbana-Champaign UrbanaIL61801 United States Department of Electrical and Computer Engineering University of Illinois at Urbana-Champaign UrbanaIL61801 United States

来源：评论

学校读者我要写书评

暂无评论

Controllable multi-level switching of optical phase change materials via microheater temperature profile engineering

Controllable multi-level switching of optical phase change m...

引用

2024 Conference on Lasers and Electro-Optics, CLEO 2024

作者： Sun, Hongyi Lian, Chuanyu Vásquez-Aza, Francis Huang, Yi-Siou Vitale, Steven A. Takeuchi, Ichiro Hu, Juejun Youngblood, Nathan Pavlidis, Georges Ríos Ocampo, Carlos A. Department of Materials Science & Engineering University of Maryland College ParkMD20742 United States Institute for Research in Electronics and Applied Physics University of Maryland College ParkMD20742 United States Department of Mechanical Engineering University of Connecticut StorrsCT06269 United States Advanced Materials and Microsystems Group MIT Lincoln Laboratory LexingtonMA02139 United States Quantum Materials Center Department of Physics University of Maryland College ParkMD20742 United States Department of Materials Science & Engineering MIT CambridgeMA02139 United States Electrical & Computer Engineering Department The University of Pittsburgh PittsburghPA15213 United States

ISBN: (纸本)9781957171395

We demonstrate doped-silicon-on-insulator microheaters with triangle-like temperature profiles. Such devices control the hotspot size and temperature and, thus, the area that undergoes amorphization or crystallization in optical phase-change materials, leading to controllable multilevel, nonvolatile response. © Optica Publishing Group 2024 © 2024 The Author(s)

关键词： Optical materials

来源：评论

学校读者我要写书评

暂无评论

A Privacy Preserving and Byzantine Robust Collaborative Federated Learning Method Design

A Privacy Preserving and Byzantine Robust Collaborative Fede...

引用

IEEE International Conference on Communications (ICC)

作者： Nuocheng Yang Sihua Wang Mingzhe Chen Changchuan Yin Christopher G. Brinton Beijing Laboratory of Advanced Information Network Beijing University of Posts and Telecommunications Beijing China State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China Department of Electrical and Computer Engineering Institute for Data Science and Computing University of Miami Coral Gables FL USA School of Electrical and Computer Engineering Purdue University West Lafayette IN USA

ISBN: (数字)9781728190549

ISBN: (纸本)9781728190556

Collaborative federated learning (CFL) enables device cooperation in training shared machine learning models without reliance on a parameter server. However, the absence of a parameter server also impacts vulnerabilities associated with adversarial attacks, including privacy inference and Byzantine attacks. In this context, this paper introduces a novel CFL framework that enables each device to individually determine the subset of devices to transmit FL parameters to over the wireless network, based on its neighboring devices' location, current loss, and connection information, to achieve privacy protection and robust aggregation. This is formulated as an optimization problem whose goal is to minimize CFL training loss while satisfying the privacy preservation, robust aggregation, and transmission delay requirements. To solve this problem, a proximal policy optimization (PPO)-based reinforcement learning (RL) algorithm integrated with a graph neural network (GNN) is proposed. Compared to traditional algorithms that use global information with high computational complexity, the proposed GNN-RL method can be deployed on devices based on neighboring information with lower computational overhead. Simulation results show that the proposed algorithm can protect data privacy and increase identification accuracy by 15% compared to an algorithm in which devices are partially clustered for model aggregation.

关键词： Training Privacy Federated learning Simulation Collaboration Clustering algorithms Propagation losses

来源：评论

学校读者我要写书评

暂无评论

A Time-Frequency Analysis for Broken Rotor Bar Detection in Closed Loop Inverter Fed Induction Motor at Imposed Speed

A Time-Frequency Analysis for Broken Rotor Bar Detection in ...

引用

IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives (SDEMPED)

作者： Lorenzo Mantione Vanesa Fernandez-Cavero Daniel Morinigo-Sotelo Lucia Frosini Department of Electrical Computer and Biomedical Engineering University of Pavia Pavia Italy Department of Electrical Engineering School of Industrial Engineering Universidad de Valladolid Valladolid Spain GIR ADIRE-HSP Digital Institute of Advanced Production Technologies (ITAP) Universidad de Valladolid Valladolid Spain

In this paper, an analysis to detect broken rotor bars while the motor is operating in closed loop control is presented. Due to changes in the supply frequency, which occur to keep the speed constant, a time-frequency technique is required even when the transient is completed. Signals from the phase current of the induction motor are analysed using traditional methods such as the Fast Fourier Transform and the Short Time Fourier Transform. Finally, the same signals are analysed through the Dragon Transform, that ensures high resolution frequency and time and allows to detect trajectories of the harmonics with different load conditions.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Controllable multi-level switching of optical phase change materials via microheater temperature profile engineering

Controllable multi-level switching of optical phase change m...

引用

CLEO: Science and Innovations in CLEO 2024, CLEO: S and I 2024 - Part of Conference on Lasers and Electro-Optics

关键词： Amorphization

来源：评论

学校读者我要写书评

暂无评论

Capillaric field effect transistors

引用

Microsystems & Nanoengineering 2022年第2期8卷 59-71页

作者： Claude Meffan Julian Menges Fabian Dolamore Daniel Mak Conan Fee Renwick C.J.Dobson Volker Nock Department of Electrical and Computer Engineering University of CanterburyChristchurch 8041New Zealand Department of Microengineering Kyoto University615-8540 KyotoJapan School of Biological Sciences University of CanterburyChristchurch 8041New Zealand Biomolecular Interaction Centre School of Biological SciencesUniversity of CanterburyChristchurch 8041New Zealand School of Product Design University of CanterburyChristchurch 8041New Zealand Department of Biochemistry and Molecular Biology Bio21 Molecular Science and Biotechnology InstituteUniversity of MelbourneParkvilleVIC 3010Australia The MacDiarmid Institute for Advanced Materials and Nanotechnology Wellington 6140New Zealand

Controlling fluid flow in capillaric circuits is a key requirement to increase their uptake for assay *** action off-valves provide such functionality by pushing an occluding bubble into the channel using a difference in capillary ***,we utilized the binary switching mode of this structure to develop a powerful set of fundamental fluidic valving *** this work,we study the transistor-like qualities of the off-valve and provide evidence that these structures are in fact functionally complementary to electronic junction field effect *** view of this,we propose the new term capillaric field effect transistor to describe these types of *** support this conclusion,we present a theoretical description,experimental characterization,and practical application of analog flow resistance *** addition,we demonstrate that the valves can also be *** show modulation of the flow resistance from fully open to pinch-off,determine the flow rate-trigger channel volume relationship and demonstrate that the latter can be modeled using Shockley's equation for electronic ***,we provide a first example of how the valves can be opened and closed repeatedly.

关键词： transistors effect field

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：