检索结果-内蒙古大学图书馆

arXiv 2024年

作者： Yang, Wanting Xiong, Zehui Mao, Shiwen Quek, Tony Q.S. Zhang, Ping Debbah, Mérouane Tafazolli, Rahim Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore Department of Electrical and Computer Engineering Auburn University Auburn36830 United States School of Information and Communication Engineering Beijing University of Posts and Telecommunications China The State Key Laboratory of Networking and Switching Technology Beijing100876 China KU 6G Research Center Department of Computer and Information Engineering Khalifa University Abu Dhabi127788 United Arab Emirates CentraleSupelec University Paris-Saclay Gif-sur-Yvette91192 France 5GIC & 6GIC University of Surrey Guildford SurreyGU2 7XH United Kingdom

The surge in connected devices in 6G with typical complex tasks requiring multi-user cooperation, such as smart agriculture and smart cities, poses significant challenges to unsustainable traditional communication. Fortunately, the booming artificial intelligence technology and the growing computational power of devices offer a promising 6G enabler: semantic communication (SemCom). However, existing deep learning-based SemCom paradigms struggle to extend to multi-user scenarios due to its increasing model size with the growing number of users and its limited compatibility with complex communication environments. Consequently, to truly empower 6G networks with this critical technology, this article rethinks generative SemCom for multi-user system and proposes a novel framework called "M-GSC" with the large language model (LLM) as the shared knowledge base (SKB). The LLM-based SKB plays three critical roles, that is, complex task decomposition, semantic representation specification, and semantic translation and mapping, for complex tasks, spawning a series of benefits such as semantic encoding standardization and semantic decoding personalization. Meanwhile, to enhance the performance of M-GSC framework, we highlight three optimization strategies unique to this framework: extending the LLM-based SKB into a multi-agent LLM system, offloading semantic encoding and decoding, and managing communication and computational resources. Finally, a case study is conducted to demonstrate the preliminary validation on the effectiveness of the M-GSC framework in terms of efficient decoding offloading. Copyright © 2024, The Authors. All rights reserved.

关键词： Encoding (symbols)

来源：评论

学校读者我要写书评

暂无评论

Smart photonic wristband for pulse wave monitoring

引用

Opto-Electronic Science 2024年第12期3卷 12-27页

作者： Renfei Kuang Zhuo Wang Lin Ma Heng Wang Qingming Chen Arnaldo Leal Junior Santosh Kumar Xiaoli Li Carlos Marques Rui Min Center for Cognition and Neuroergonomics State Key Laboratory of Cognitive Neuroscience and LearningBeijing Normal UniversityZhuhai 519087China College of Science Shenyang Aerospace UniversityShenyang 110136China School of Microelectronics Science and Technology Guangdong Provincial Key Laboratory of Optoelectronic Information Processing Chips and SystemsSun Yat-Sen UniversityZhuhai 519082China Graduate Program in Electrical Engineering Federal University of Espírito SantoFernando Ferrari AvenueVitoria 29075-910Brazil Department of Electronics and Communication Engineering Koneru Lakshmaiah Education FoundationVaddeswaramAndhra Pradesh 522302India CICECO-Aveiro Institute of Materials Physics DepartmentUniversity of AveiroAveiro 3810-193Portugal

Real-time acquisition of human pulse signals in daily life is clinically important for cardiovascular disease monitoring and ***,we propose a smart photonic wristband for pulse signal monitoring based on speckle pattern analysis with a polymer optical fiber(POF)integrated into a sports *** different speckle pattern processing algorithms and POFs with different core diameters were *** results indicated that the smart photonic wristband had a high signal-to-noise ratio and low latency,with the measurement error controlled at approximately 3.7%.This optimized pulse signal could be used for further medical diagnosis and was capable of objectively monitoring subtle pulse signal changes,such as the pulse waveform at different positions of Cunkou and pulse waveforms before and after *** the assistance of artificial intelligence(AI),functions such as gesture recognition have been realized through the established prediction model by processing pulse signals,in which the recognition accuracy reaches 95%.Our AI-assisted smart photonic wristband has potential applications for clinical treatment of cardiovascular diseases and home monitoring,paving the way for medical Internet of Things-enabled smart systems.

关键词： smart healthcare specklegram pulse monitoring gesture recognition artificial intelligence wearable sensor

来源：评论

学校读者我要写书评

暂无评论

SDOA-Net: An Efficient Deep Learning-Based DOA Estimation Network for Imperfect Array

arXiv

引用

arXiv 2022年

作者： Chen, Peng Chen, Zhimin Liu, Liang Chen, Yun Wang, Xianbin State Key Laboratory of Millimeter Waves Southeast University Nanjing210096 China State Key Laboratory of Integrated Chips and Systems Fudan University Shanghai201203 China School of Electronic and Information Shanghai Dianji University Shanghai201306 China Department of Electronic and Information Engineering The Hong Kong Polytechnic University Hong Kong State Key Laboratory of Integrated Chips and Systems Microelectronics School Fudan University Shanghai201203 China Department of Electrical and Computer Engineering Western University LondonONN6A 5B9 Canada

The estimation of direction of arrival (DOA) is a crucial issue in conventional radar, wireless communication, and integrated sensing and communication (ISAC) systems. However, low-cost systems often suffer from imperfect factors, such as antenna position perturbations, mutual coupling effect, inconsistent gains/phases, and non-linear amplifier effect, which can significantly degrade the performance of DOA estimation. This paper proposes a DOA estimation method named superresolution DOA network (SDOA-Net) based on deep learning (DL) to characterize the realistic array more accurately. Unlike existing DL-based DOA methods, SDOA-Net uses sampled received signals instead of covariance matrices as input to extract data features. Furthermore, SDOA-Net produces a vector that is independent of the DOA of the targets but can be used to estimate their spatial spectrum. Consequently, the same training network can be applied to any number of targets, reducing the complexity of implementation. The proposed SDOA-Net with a low-dimension network structure also converges faster than existing DL-based methods. The simulation results demonstrate that SDOA-Net outperforms existing DOA estimation methods for imperfect arrays. The SDOA-Net code is available online at https://***/chenpengseu/***. Copyright © 2022, The Authors. All rights reserved.

关键词： Direction of arrival

来源：评论

学校读者我要写书评

暂无评论

Dynamic neural network with memristive CIM and CAM for 2D and 3D vision

arXiv

引用

arXiv 2024年

作者： Zhang, Yue Zhang, Woyu Wang, Shaocong Lin, Ning Yu, Yifei He, Yangu Wang, Bo Jiang, Hao Lin, Peng Xu, Xiaoxin Qi, Xiaojuan Wang, Zhongrui Zhang, Xumeng Shang, Dashan Liu, Qi Cheng, Kwang-Ting Liu, Ming Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong Key Laboratory of Microelectronic Devices & Integrated Technology Institute of Microelectronics Chinese Academy of Sciences Beijing100049 China ACCESS – AI Chip Center for Emerging Smart Systems InnoHK Centers Hong Kong Science Park Hong Kong Institute of the Mind The University of Hong Kong Hong Kong Key Lab of Fabrication Technologies for Integrated Circuits Chinese Academy of Sciences Beijing100049 China State Key Laboratory of Integrated Chips and Systems Frontier Institute of Chip and System Fudan University Shanghai200433 China University of Chinese Academy of Sciences Beijing100049 China College of Computer Science and Technology Zhejiang University Zhejiang310027 China Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong

The brain is dynamic, associative and efficient. It reconfigures by associating the inputs with past experiences, with fused memory and processing. In contrast, AI models are static, unable to associate inputs with past experiences, and run on digital computers with physically separated memory and processing. We propose a hardware-software co-design, a semantic memory-based dynamic neural network (DNN) using memristor. The network associates incoming data with the past experience stored as semantic vectors. The network and the semantic memory are physically implemented on noise-robust ternary memristor-based Computing-In-Memory (CIM) and Content-Addressable Memory (CAM) circuits, respectively. We validate our co-designs, using a 40nm memristor macro, on ResNet and PointNet++ for classifying images and 3D points from the MNIST and ModelNet datasets, which not only achieves accuracy on par with software but also a 48.1% and 15.9% reduction in computational budget. Moreover, it delivers a 77.6% and 93.3% reduction in energy consumption. © 2024, CC BY.

关键词： Memristors

来源：评论

学校读者我要写书评

暂无评论

Investigation of Resistance Characteristics of Frozen Ballast Bed in Alpine Region Based on Mbd-Dem Coupling Simulations

SSRN

引用

SSRN 2023年

作者： Liu, Jianxing Li, Yuzhao Kou, Lei Sysyn, Mykola Fischer, Szabolcs Wang, Ping Xinyun Engineering Co. Ltd. of China Railway First Group Co Ltd. Xianyang712000 China Department of Electrical and Control Engineering Taizhou Institute of Zhejiang University Taizhou318000 China Department of Planning and Design of Railway Infrastructure Institute of Railway Systems and Public Transport Technical University of Dresden Dresden01069 Germany Department of Transport Infrastructure and Water Resources Engineering Széchenyi István University Győr9026 Hungary MOE Key Laboratory of High-speed Railway Engineering Southwest Jiaotong University Chengdu610031 China

In this paper, a simulation model of ballast bed based on the coupling of multi-body dynamics and discrete element method (MBD-DEM coupling) is established, then it is used to simulate and be validated by the single sleeper push test (SSPT) of the ballast bed in laboratory. Meanwhile, a bonding model is introduced into the coupling model to simulate the icing effect of ice layer on the ballast in different low-temperature environments. The results of meso-analysis show that the existence of ice bonding changes the forms of force bearing and force transmission of the ballast layers between the adjacent sleepers and the ballast layers at both ends of a sleeper. The force range of the ballast layer at the bottom of sleeper expands with the decrease of temperature. In addition, the ice bonding near the moving side of the sleeper is mainly subjected to pressure, and the ice bonding far from the moving side of the sleeper is mainly subjected to tension, especially at -30 °C. With the decrease of temperature, the broken rate of ice bonding decreases under the same movements of the sleepers, and the average coordination number of ballast particles decreases. © 2023, The Authors. All rights reserved.

关键词： Ice

来源：评论

学校读者我要写书评

暂无评论

Investigation on loss reduction strategies of single-core HVAC submarine cables

Investigation on loss reduction strategies of single-core HV...

引用

22nd International Symposium on High Voltage engineering (ISH 2021)

作者： X. Xu F. Meng A. Paramene X. Chen L. Qiu W. Zhou Zhejiang Provincial Key Laboratory of Electrical Machine Systems College of Electrical Engineering Zhejiang University Hangzhou 310027 China Department of Electrical Engineering National Institute of Technology Silchar Assam 788010 India Zhejiang Huayun Electric Power Engineering Design & Consultation Company Hangzhou 310027 China

Submarine cables play an important role in the cross-sea transmission system. However, the power loss in such systems should be reduced as it affects the service life and limits the ampacity of the submarine cables. This paper proposes an accurate methodology based on the multi-conductor analysis theory to investigate the loss reduction strategies of the single-core high voltage AC (HVAC) submarine cable. The coupled line model is used to improve the calculation efficiency. The case study of the 500-kV submarine cable line of Zhoushan 500 kV power transmission project is conducted. The results show that connecting resistors and reactors at the grounding ends of the cable sheath can significantly reduce power loss. The connection of reactors exhibits a higher reduction of power loss than the resistors.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Ultra-compact beam steering nanolasers

arXiv

引用

arXiv 2024年

作者： Chen, Xinghong Gu, Mingxuan Tang, Jiankai Sang, Yungang Xiang, Bingrui Zhang, Kong Zhang, Guanjie Wang, Xingyuan Guo, Xuhan Zhou, Linjie Wu, Wengang Mao, Yifei School of Sensing Science and Engineering School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai200240 China SJTU-Pinghu Institute of Intelligent Optoelectronics Pinghu314200 China Institute of Microelectronics Chinese Academy of Sciences Beijing100029 China College of Mathematics and Physics Beijing University of Chemical Technology Beijing100029 China State Key Laboratory of Advanced Optical Communication Systems and Networks Department of Electronic Engineering Shanghai Jiao Tong University Shanghai200240 China State Key Laboratory of Advanced Optical Communication Systems and Networks Shanghai Key Lab of Navigation and Location Services Shanghai Institute for Advanced Communication and Data Science Department of Electronic Engineering Shanghai Jiao Tong University Shanghai200240 China National Key Laboratory of Science and Technology on Micro/Nano Fabrication School of Integrated Circuits Peking University Beijing100871 China Beijing Advanced Innovation Center for Integrated Circuits Beijing100871 China Frontiers Science Center for Nano-optoelectronics Peking University Beijing100871 China

The miniaturization and integration of beam steering devices have consistently been the focus of the field. Conventional methods alter the eigenmode of the optical cavity by regulating the refractive index. Due to the weak nonlinear effect of the optical system, the device must be sufficiently large to achieve sufficient light modulation. The effective method for miniaturizing beam steering devices currently in use is based on metasurfaces. However, this type of device necessitates the input of a laser source, which precludes the simultaneous generation and control of light in a single device. Here we propose a miniaturized beam steering device that employs mode selection between different bound states in the continuum (BIC) states through phase change material. The device is capable of simultaneously achieving both light generation and beam steering (33°) in a single device with a size of only 25 μm and with a low threshold of 8.9 kW cm-2. Furthermore, it is possible to achieve a significant degree of dynamic wavelength tunability, with a range extending up to 296 nm. This method achieves high-efficient regulation of light properties by dynamically controlling the system’s topological charge, circumventing the problem of weak nonlinearity in traditional methods. Furthermore, the integration of phase change materials with nanolasers enables the direct alteration of lasing properties, which provides a novel idea for dynamic light control. The device process scheme based on phase change materials is straightforward, direct, and highly compatible, which will be advantageous for its intended application. Copyright © 2024, The Authors. All rights reserved.

关键词： Phase change materials

来源：评论

学校读者我要写书评

暂无评论

A decentralized power sharing strategy for wind farm de-loading

A decentralized power sharing strategy for wind farm de-load...

引用

2020 IEEE Power and Energy Society General Meeting, PESGM 2020

作者： Fan, Xinkai Crisostomi, Emanuele Thomopulos, Dimitri Zhang, Baohui Shorten, Robert Xi'An Jiaotong University State Key Laboratory of Electrical Insulation and Power Equipment Xi'an China Territory and Constructions Engineering University of Pisa Department of Energy Systems Pisa Italy Dyson School of Design Engineering Imperial College London London United Kingdom

ISBN: (纸本)9781728155081

This paper revises current power sharing algorithms used for de-loading operations in wind farms with variable speed wind turbines. In particular, we show that classic fair power sharing solutions can be obtained without requiring wind turbines to communicate local wind or power measurements, which is a very attractive feature for practical applications. For this purpose, algorithms borrowed from communication network theory, namely, Additive-Increase-Multiplicative-Decrease (AIMD) algorithms, are used to solve the power sharing problem in a decentralized fashion. Extensive simulations on wind farms consisting of ten wind turbines are provided to illustrate the potential and the efficacy of the proposed methodology. © 2020 IEEE.

关键词： Wind turbines

来源：评论

学校读者我要写书评

暂无评论

Privacy-preserving Intelligent Resource Allocation for Federated Edge Learning in Quantum Internet

arXiv

引用

arXiv 2022年

作者： Xu, Minrui Niyato, Dusit Yang, Zhaohui Xiong, Zehui Kang, Jiawen Kim, Dong In Shen, Xuemin The School of Computer Science and Engineering Nanyang Technological University Singapore The College of Information Science and Electronic Engineering Zhejiang University Hangzhou310007 China Hangzhou310007 China Zhejiang Laboratory Hangzhou31121 China The Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore 487372 Singapore The School of Automation Guangdong University of Technology China Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of The Department of Electrical and Computer Engineering University of Waterloo Waterloo ON N2L 3G1 Canada

Federated edge learning (FEL) is a promising paradigm of distributed machine learning that can preserve data privacy while training the global model collaboratively. However, FEL is still facing model confidentiality issues due to eavesdropping risks of exchanging cryptographic keys through traditional encryption schemes. Therefore, in this paper, we propose a hierarchical architecture for quantum-secured FEL systems with ideal security based on the quantum key distribution (QKD) to facilitate public key and model encryption against eavesdropping attacks. Specifically, we propose a stochastic resource allocation model for efficient QKD to encrypt FEL keys and models. In FEL systems, remote FEL workers are connected to cluster heads via quantum-secured channels to train an aggregated global model collaboratively. However, due to the unpredictable number of workers at each location, the demand for secret-key rates to support secure model transmission to the server is unpredictable. The proposed systems need to efficiently allocate limited QKD resources (i.e., wavelengths) such that the total cost is minimized in the presence of stochastic demand by formulating the optimization problem for the proposed architecture as a stochastic programming model. To this end, we propose a federated reinforcement learning-based resource allocation scheme to solve the proposed model without complete state information. The proposed scheme enables QKD managers and controllers to train a global QKD resource allocation policy while keeping their private experiences local. Numerical results demonstrate that the proposed schemes can successfully achieve the cost-minimizing objective under uncertain demand while improving the training efficiency by about 50% compared to state-of-the-art schemes. © 2022, CC BY.

关键词： Stochastic systems

来源：评论

学校读者我要写书评

暂无评论

FIRE: A Failure-Adaptive Reinforcement Learning Framework for Edge Computing Migrations

arXiv

引用

arXiv 2022年

作者： Siew, Marie Sharma, Shikhar Li, Zekai Guo, Kun Xu, Chao Lorido-Botran, Tania Quek, Tony Q.S. Joe-Wong, Carlee The Information Systems and Technology and Design Pillar Singapore University of Technology and Design Singapore487372 Singapore The Electrical and Computer Engineering department Carnegie Mellon University PittsburghPA15213 United States The Shanghai Key Laboratory of Multidimensional Information Processing School of Communications and Electronics Engineering East China Normal University Shanghai200241 China The School of Information Engineering Northwest A&F University Yangling712100 China Roblox United States

In edge computing, users’ service profiles are migrated between edge servers due to user mobility. Reinforcement learning (RL) frameworks have been proposed to do so, often trained on simulated data. However, existing RL frameworks overlook occasional server failures, which although rare, impact latency-sensitive applications like AR/VR and real- time obstacle detection. These rare failures, being not adequately represented in historical training data, pose a challenge for data-driven RL algorithms. We introduce FIRE, a framework that adapts to rare events by training a RL policy in an edge computing digital twin environment. We propose FIRE-ImRE, an importance sampling-based Q-learning algorithm, which samples rare events proportionally to their impact on the value function. FIRE considers delay, migration, failure, and backup placement costs across individual and shared service profiles. We prove FIRE-ImRE’s boundedness and convergence to optimality. Next, we introduce novel deep Q-learning (FIRE-ImDQL) and actor critic (FIRE-ImACRE) versions of our algorithm to enhance scalability. We extend our framework to accommodate users with varying risk tolerances of rare failure events. Through trace-driven experiments, we show that FIRE reduces edge computing costs compared to vanilla RL and the greedy baseline in the event of failures. © 2022, CC BY.

关键词： Mobile edge computing

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：