检索结果-内蒙古大学图书馆

IEEE Annual Joint Conference: INFOCOM, IEEE computer and Communications Societies

作者： Yi Zhao Zimu Zhou Xu Wang Tongtong Liu Yunhao Liu Zheng Yang School of Software and BNRist Tsinghua University Computer Engineering and Networks Laboratory ETH Zurich Department of Computer Science and Engineering Michigan State University

Understanding customer mobility patterns to commercial districts is crucial for urban planning, facility management, and business strategies. Trade areas are a widely applied measure to quantity where the visitors are from. Traditional trade area analysis is limited to small-scale or store-level studies because information such as visits to competitor commercial entities and place of residence is collected by labour-intensive questionnaires or heavily biased location-based social media data. In this paper, we propose CellTradeMap, a novel district-level trade area analysis framework using mobile flow records (MFRs), a type of fine-grained cellular network data. CellTradeMap extracts robust location information from the irregularly sampled, noisy MFRs, adapts the generic trade area analysis framework to incorporate cellular data, and enhances the original trade area model with cellular-based features. We evaluate CellTradeMap on a large-scale cellular network dataset covering 3.5 million mobile phone users in a metropolis in China. Experimental results show that the trade areas extracted by CellTradeMap are aligned with domain knowledge and CellTradeMap can model trade areas with a high predictive accuracy.

关键词： Cellular networks Base stations Mobile handsets Switches Urban areas Internet Data mining

来源：评论

学校读者我要写书评

暂无评论

Secure two-way communications via intelligent reflecting surfaces

arXiv

引用

arXiv 2020年

作者： Lv, Lu Wu, Qingqing Li, Zan Al-Dhahir, Naofal Chen, Jian State Key Laboratory of Integrated Services Networks Xidian University Xi’an710071 China State Key Laboratory of Internet of Things for Smart City University of Macau 999078 China Department of Electrical and Computer Engineering University of Texas at Dallas RichardsonTX75080 United States

In this letter, we propose to exploit an intelligent reflecting surface (IRS) to secure multiuser two-way communications. Specifically, two end users simultaneously transmit their signals, where the signal of one user is exploited as information jamming to disrupt the reception of the other user’s signal at an eavesdropper. A simple user scheduling scheme is developed to improve the secrecy rate. Analytical results in terms of a lower bound on the average secrecy rate and its scaling laws are derived to evaluate the secrecy performance and obtain valuable design insights. Simulation results are provided to confirm the accuracy of the theoretical analysis and validate the secrecy improvement of the proposed scheme over two other baseline schemes. Copyright © 2020, The Authors. All rights reserved.

关键词： Jamming

来源：评论

学校读者我要写书评

暂无评论

Motion Classification Based on sEMG Signals Using Deep Learning 4th

Motion Classification Based on sEMG Signals Using Deep Learn...

引用

4th International Conference on Machine Learning and Intelligent Communications, MLICOM 2019

作者： Shen, Shu Gu, Kang Chen, Xinrong Wang, Ruchuan School of Computer Science Nanjing University of Posts and Telecommunications Nanjing210023 China Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks Nanjing210023 China Academy for Engineering and Technology Fudan University Shanghai200433 China Shanghai Key Laboratory of Medical Image Computing and Computer Assisted Intervention Shanghai200032 China

ISBN: (纸本)9783030323875

Nowadays, surface electromyography (sEMG) signal plays an important role in helping physically disabled people during daily life. The development of electronic information technology has also led to the emergence of low-cost, multi-channel, wearable sEMG signal acquisition devices. Therefore, this paper proposes a new motion recognition model based on deep learning to improve the accuracy of motion recognition of sEMG signals. The model uses architecture including 6 convolutional layers and 6 pooling layers which enables the Batch Normalization layer to enhance network performance and prevent overfitting. In the experiment, NinaPro DB5 data set was used for training and testing. The data set consists of sEMG signal data collected by the double Myo armbands which contains data of 52 movements for 10 subjects. The results show that the accuracy of about 90% can be achieved when using 52 sEMG signal data from every single subject or all subjects. © 2019, ICST Institute for computer Sciences, Social Informatics and Telecommunications engineering.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Black-box coupled-mode theory: An Ab initio framework to model electromagnetic interactions of open, lossy, and dispersive resonators

arXiv

引用

arXiv 2020年

作者： Tali, Seied Ali Safiabadi Yuan, Luqi Zhou, Wei Department of Electrical and Computer Engineering Virginia Tech BlacksburgVA24061 United States State Key Laboratory of Advanced Optical Communication Systems and Networks School of Physics and Astronomy Shanghai Jiao Tong University Shanghai200240 China

Temporal coupled-mode theory (TCMT) provides a simple yet powerful platform to model and analyze electromagnetic resonator systems. Nevertheless, restrictive assumptions and lack of rigorous connection to Maxwell’s equations limit the TCMT formulation’s generality and robustness. Herein, we present the Black-box Coupled-Mode Theory (BBCMT), a general ab initio CMT framework developed from Maxwell’s equations and quasinormal mode (QNM) theory to model the electromagnetic interactions of dispersive, lossy, and open resonators. BBCMT development is enabled by employing Poynting’s and conjugated reciprocity theorems to rigorously normalize QNMs and calculate their expansion coefficients. Our novel QNM analysis approach allows the definition of a resonator Hamiltonian matrix to characterize the modes’ electromagnetic interactions, energy storage, and absorption. Uniquely, the BBCMT framework can capture a resonator’s non-resonant scattering and absorption by treating the resonator scattered fields as a perturbation to those of a background structure, which can be flexibly chosen considering the desired accuracy-simplicity trade-off. BBCMT modeling complexity can be further adjusted by treating user-defined subcomponents of a resonator system as black-boxes described only by their input-output transfer characteristics. Beyond the BBCMT formulation, we present two lemmas to reverse-engineer the modeling parameters from calculated or measured far-field spectra. Moreover, we introduce the signal flow graphs from control theory to illustrate, interpret, and solve the BBCMT equations. To evince BBCMT’s validity and generality, we compare the BBCMT and TCMT predictions for two plasmonic nanoresonator systems to finite-difference time-domain simulations and find BBCMT results to be a much better match. BBCMT reduces to TCMT or cavity perturbation theory under certain constraints and approximations. Copyright © 2020, The Authors. All rights reserved.

关键词： Resonators

来源：评论

学校读者我要写书评

暂无评论

UAV Communication Channel Measurement, Modeling, and Application

引用

Journal of Communications and Information networks 2019年第4期4卷 32-43页

作者： Xiang Cheng Yiran Li Lin Bai State Key Laboratory of Advanced Optical Communication Systems and Networks Department of ElectronicsSchool of Electronics Engineering and Computer SciencePeking UniversityBeijing 100871China Shenzhen Research Institute of Big Data Shenzhen 518000China School of Cyber Science and Technology Beihang UniversityBeijing 100191China

As unmanned aerial vehicles(UAV)deploy-ment is shifting from military to civilian sectors,and in particular as a means of facilitating more flexible and versatile wireless communications,the UAV channels that were previously not well understood are attracting increasing research and *** the key component facilitating the UAV-aided communications,UAV channel characteristics and modeling are of critical importance to the designed UAV system to achieve satisfactory *** this article,we will provide a comprehensive overview and the future perspective of envisioned UAV communication system benefits,the existing and needed UAV channel measurements and modeling approaches,together with the new viewpoint of UAV channel applications in different communication and networking *** existing work and future directions are extensively covered.

关键词： UAV channel measurements modeling application future challenges

来源：评论

学校读者我要写书评

暂无评论

Ultrahigh-Q AlGaAs-on-insulator microresonators for integrated nonlinear photonics

arXiv

引用

arXiv 2020年

作者： Xie, Weiqiang Chang, Lin Shu, Haowen Norman, Justin C. Peters, Jon D. Wang, Xingjun Bowers, John E. Department of Electrical and Computer Engineering University of California Santa BarbaraCA93106 United States State Key Laboratory of Advanced Optical Communications System and Networks Department of Electronics School of Electronics Engineering and Computer Science Peking University Beijing100871 China Institute for Energy Efficiency University of California Santa BarbaraCA93106 United States

Aluminum gallium arsenide (AlGaAs) and related III-V semiconductors have excellent optoelectronic properties. They also possess strong material nonlinearity as well as high refractive indices. In view of these properties, AlGaAs is a promising candidate for integrated photonics, including both linear and nonlinear devices, passive and active devices, and associated applications. For integrated photonics low propagation loss is essential, particularly in nonlinear applications. However, achieving low-loss and high-confinement AlGaAs photonic integrated circuits poses a challenge. Here we show an effective reduction of surface-roughness-induced scattering loss in fully etched high-confinement AlGaAs-on-insulator nanowaveguides, by using a heterogeneous wafer-bonding approach and optimizing fabrication techniques. We demonstrate ultrahigh-quality AlGaAs microring resonators and realize quality factors up to 3.52×106 and finesses as high as 1.4×104. We also show ultra-efficient frequency comb generations in those resonators and achieve record-low threshold powers on the order of ~20 µW and ~120 µW for the resonators with 1 THz and 90 GHz free-spectral ranges, respectively. Our result paves the way for the implementation of AlGaAs as a novel integrated material platform specifically for nonlinear photonics, and opens a new window for chip-based efficiency-demanding practical applications. Copyright © 2020, The Authors. All rights reserved.

关键词： III-V semiconductors

来源：评论

学校读者我要写书评

暂无评论

Joint Optimization of Phase Retrieval and Forward Error Correcting for Direct Detection Receiver

Joint Optimization of Phase Retrieval and Forward Error Corr...

引用

European Conference on Optical Communication (ECOC)

作者： Bin Chen Hanzi Huang Haoshuo Chen Yi Lei Nicolas K. Fontaine Roland Ryf Qianwu Zhang Yingxiong Song School of Computer Science and Information Engineering Hefei University of Technology China Key Laboratory of Specialty Fiber Optics and Optical Access Networks Joint International Research Laboratory of Specialty Fiber Optics and Advanced Communication Shanghai University China Nokia Bell Labs Holmdel New Jersey USA

We have experimentally demonstrated that performance of a phase retrieval (PR) receiver in optical systems can be significantly improved by a joint optimization of PR pilots overhead and FEC coding overhead, enabling ... 详细信息

ISBN: (数字)9781728173610

ISBN: (纸本)9781728173627

关键词： Europe Forward error correction Optical receivers Adaptive optics Optical fiber communication Resource management Optimization

来源：评论

学校读者我要写书评

暂无评论

Femtosecond fiber laser at 780 nm for two-photon autofluorescence imaging

引用

Chinese Optics Letters 2019年第7期17卷 63-65页

作者： Wan Yang Danlei Wu Runlong Wu Guanyu Liu Bingying Chen Lishuang Feng Zhigang Zhang Aimin Wang State Key Laboratory of Advanced Optical Communication System and Networks School of Electronics Engineering and Computer SciencePeking UniversityBeijing 1008711 China Key Laboratory of Precision Opto-Mechatronics Technology Ministry of EducationSchool of Instrumentation Science&Optoelectronics EngineeringBeihang UniversityBeijing 100191China

We present an Er-doped fiber(Er:fiber)-based femtosecond laser at 780 nm with 256 MHz repetition rate, 191 fs pulse duration, and over 1 W average *** from the careful third-order dispersion management, we introduce moderate self-phase modulation to broaden the output spectrum of the Er:fiber amplifier and achieve 193 fs pulse duration and 2.43W average *** 40% frequency doubling efficiency is obtained by a periodically poled lithium niobate *** through a hollow-core photonic bandgap fiber, this robust laser becomes an ideal and convenient light source for two-photon autofluorescence imaging.

关键词： Femtosecond fiber laser two-photon autofluorescence imaging

来源：评论

学校读者我要写书评

暂无评论

Enhancing Collaborative Inference on Heterogeneous Edge Devices via Adaptive Ensemble Knowledge Distillation

引用

IEEE Journal on Selected Areas in Communications 2025年

作者： Wu, Shangrui Li, Yupeng Wang, Wenhua Guo, Jianxiong Fan, Wentao Liu, Qin Jia, Weijia Yu, Shui Cao, Jiannong Wang, Tian Beijing Normal-Hong Kong Baptist University Guangdong Provincial/Zhuhai Key Laboratory of IRADS Department of Computer Science Zhuhai China Hong Kong Baptist University Hong Kong Hong Kong Hong Kong Baptist University Department of Interactive Media Hong Kong Hong Kong Beijing Normal University Institute of Artificial Intelligence and Future Networks Zhuhai China Xi'an University of Posts and Telecommunications Shaanxi Key Laboratory of Information Communication Network and Security Shaanxi Xi'an China Hunan University College of Computer Science and Electronic Engineering Changsha China University of Technology Sydney School of Computer Science Sydney Australia The Hong Kong Polytechnic University Department of Computing Hong Kong Hong Kong

The integration of edge computing with deep neural networks (DNNs) is crucial for intelligent industrial cyber-physical systems. Typically, deploying DNNs on heterogeneous edge devices relies on methods like model compression and partitioning. However, these approaches often result in homogeneous models across devices. This homogeneity limits the collective capability of edge computing systems, particularly in terms of generalization to diverse data distributions and adaptation to dynamic industrial environments. In this work, we propose to treat each DNN on an edge device as an independent model, aggregating their capabilities via ensemble learning to enhance generalization and dynamic adaptability. To realize this, we introduce the Adaptive Ensemble Knowledge Distillation Framework (AEKDF), combining cloud-based model training with edge computing based collaborative inference. In the cloud, AEKDF develops an enhanced Born Again Network that generates diverse, lightweight models tailored to specific edge devices through knowledge distillation. This process ensures model diversity which is critical to effective ensemble learning. On the edge, AEKDF employs an adaptive ensemble technique that aggregates prediction logits across devices, enabling rapid adaptation to changing environments and maintaining inference efficiency. Our extensive evaluations conducted on a realistic prototype demonstrate the substantial boost in predictive performance achieved by our AEKDF, showcasing a 4% to 10% accuracy improvement on the CIFAR-100 compared to conventional single-model approaches, while maintaining low latency. © 1983-2012 IEEE.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

Adaptive Deployment of UAV-Aided networks Based on Hybrid Deep Reinforcement Learning

Adaptive Deployment of UAV-Aided Networks Based on Hybrid De...

引用

IEEE Conference on Vehicular Technology (VTC)

作者： Xiaoyong Ma Shuting Hu Danyang Zhou Yi Zhou Ning Lu School of Computer and Information Engineering Henan University Kaifeng China International Joint Research Laboratory for Cooperative Vehicular Networks of Henan Henan China Henan Key Laboratory of Big Data Analysis and Processing Henan University Kaifeng PR China Queen’s University Kingston Ontario Canada

ISBN: (数字)9781728194844

ISBN: (纸本)9781728194851

Unmanned aerial vehicles (UAVs) can be used as air base stations to provide fast wireless connections for ground users. Due to their constraints on both mobility and energy consumption, a key problem is how to deploy UAVs adaptively in a geographic area with changing traffic demand of mobile users, while meeting the aforemetioned constraints. In this paper, we propose an adaptive deployment strategy for UAV-aided networks based on hybrid deep reinforcement learning, where a UAV can adjust its movement direction and distance to serve users who move randomly in the target area. Through hybrid deep reinforcement learning, UAVs can be trained offline to obtain the global state information and learn a completely distributed control strategy, with which each UAV only needs to take actions based on its observed state in the real deployment to be fully adaptive. Moreover, in order to improve the speed and effect of learning, we improve hybrid reinforcement learning, by adding genetic algorithms and TD-error-based resampling optimization mechanism. Simulation results show that the hybrid deep reinforcement learning algorithm has better efficiency and robustness in multi-UAV control, and has better performance in terms of coverage, energy consumption and average throughput, by which average throughput can be increased by 20% to 60%.

关键词： Energy consumption Adaptive systems Simulation Reinforcement learning Throughput Unmanned aerial vehicles Optimization

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：