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arXiv 2020年

作者： Wu, Xiongwei Li, Qiang Li, Xiuhua Leung, Victor C.M. Ching, P.C. Department of Electronic Engineering Faculty of Engineering Chinese University of Hong Kong Shatin Hong Kong School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu611731 China Peng Cheng Laboratory Shenzhen518052 China School of Big Data and Software Engineering Chongqing University Chongqing401331 China College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China Department of Electrical and Computer Engineering University of British Columbia VancouverBCV6T 1Z4 Canada

Explosive growth of mobile data demand may impose a heavy traffic burden on fronthaul links of cloud-based small cell networks (C-SCNs), which deteriorates users’ quality of service (QoS) and requires substantial power consumption. This paper proposes an efficient maximum distance separable (MDS) coded caching framework for a cache-enabled C-SCNs, aiming at reducing long-term power consumption while satisfying users’ QoS requirements in short-term transmissions. To achieve this goal, the cache resource in small-cell base stations (SBSs) needs to be reasonably updated by taking into account users’ content preferences, SBS collaboration, and characteristics of wireless links. Specifically, without assuming any prior knowledge of content popularity, we formulate a mixed timescale problem to jointly optimize cache updating, multicast beamformers in fronthaul and edge links, and SBS clustering. Nevertheless, this problem is anti-causal because an optimal cache updating policy depends on future content requests and channel state information. To handle it, by properly leveraging historical observations, we propose a two-stage updating scheme by using Frobenius-Norm penalty and inexact block coordinate descent method. Furthermore, we derive a learning-based design, which can obtain effective tradeoff between accuracy and computational complexity. Simulation results demonstrate the effectiveness of the proposed two-stage framework. Copyright © 2020, The Authors. All rights reserved.

关键词： Electric power utilization

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Transferring orbital angular momentum to an electron beam reveals toroidal and chiral order

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Physical Review B 2023年第20期107卷 205419-205419页

作者： K. X. Nguyen Y. Jiang M. C. Cao P. Purohit A. K. Yadav P. García-Fernández M. W. Tate C. S. Chang P. Aguado-Puente J. Íñiguez F. Gomez-Ortiz S. M. Gruner J. Junquera L. W. Martin R. Ramesh D. A. Muller Department of Chemistry and Chemical Biology Cornell University Ithaca 14853 New York USA School of Applied and Engineering Physics Cornell University Ithaca 14853 New York USA Department of Physics Cornell University Ithaca 14853 New York USA Department of Electrical Engineering and Computer Sciences University of California Berkeley 94720 California USA Departamento de Ciencias de la Tierra y Física de la Materia Condensada Universidad de Cantabria Cantabria Campus Internacional Avenida de los Castros s/n 39005 Santander Cantabria Spain Atomistic Simulation Center Queen's University Belfast Belfast BT7 1NN Northern Ireland United Kingdom CIC nanoGUNE BRTA E-20018 Donostia-San Sebastian Spain Materials Research and Technology Department Luxembourg Institute of Science and Technology (LIST) 5 avenue des Hauts-Fourneaux Esch-Sur-Alzette L-4362 Luxembourg Physics and Materials Science Research Unit University of Luxembourg 41 Rue du Brill Belvaux L-4422 Luxembourg Kavli Institute at Cornell for Nanoscale Science Ithaca 14853 New York USA Cornell High Energy Synchrotron Source (CHESS) Cornell University Ithaca 14853 New York USA Department of Material Science and Engineering University of California Berkeley Berkeley 94720 California USA Materials Sciences Division Lawrence Berkeley National Laboratory Berkeley 94720 California USA Department of Physics University of California Berkeley 94720 California USA

Orbital angular momentum (OAM) and torque transfer play central roles in a wide range of magnetic textures and devices including skyrmions and spin-torque electronics. Analogous topological structures are now also being explored in ferroelectrics, including polarization vortex arrays in ferroelectric/dielectric superlattices. Unlike magnetic toroidal order, electric toroidal order does not couple directly to linear external fields. Instead, we find that the presence of an electric toroidal moment in a ferrorotational phase transfers measurable torque and OAM to a localized electron beam in the ballistic limit. We record these torque transfers from a high-energy electron beam using a momentum-resolved detector. This approach provides a high-sensitivity method to detect polarization fields and their more complex order parameters and topologies. In addition to toroidal order, we also demonstrate high-precision measurements of vorticity and chirality for polar vortexlike phases.

关键词： Chirality Electric polarization Ferroelectricity Ferroelectrics Angular momentum Electron diffraction Electron microscopy Scanning transmission electron microscopy

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Non-orthogonal multiple access for UAV-aided heterogeneous networks: A stochastic geometry model

arXiv

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arXiv 2020年

作者： Zhao, Cunzhuo Liu, Yuanwei Cai, Yunlong Zhao, Minjian Ding, Zhiguo Pengcheng Laboratory Shenzhen518052 China The School of Electronic Engineering and Computer Science Queen Mary University of London LondonE1 4NS United Kingdom The College of Information Science and Electronic Engineering Zhejiang University Hangzhou310027 China The School of Electrical and Electronic Engineering The University of Manchester ManchesterM13 9PL United Kingdom

In this work, we explore the potential benefits of deploying unmanned aerial vehicles (UAVs) as aerial base stations (ABSs) with sub-6GHz band and small cells terrestrial base stations (TBSs) with millimeter wave (mmWave) band in a hybrid heterogeneous networks (HetNets). A flexible nonorthogonal multiple access (NOMA) based user association policy is proposed. By using the tools from stochastic geometry, new analytical expressions for association probability, coverage probability and spectrum efficiency are derived for characterizing the performance of UAV-aided HetNets under the realistic Air-to-Ground (A2G) channels and the Ground-to-Ground (G2G) channels with a LoS ball blockage model. Finally, we provide insights on the proposed hybrid HetNets by numerical results. We confirm that i) the proposed NOMA enabled HetNets is capable of achieving superior performance compared with the OMA enabled ABSs by setting power allocation factors and targeted signal-to-interference-plus-noise ratio (SINR) threshold properly;ii) there is a tradeoff between the association probabilities and the spectrum efficiency in the NOMA enabled ABSs tier;iii) the coverage probability and spectrum efficiency of the NOMA enabled ABSs tier is largely affected by the imperfect successive interference cancellation (ipSIC) coefficient, power allocation factors and SINR threshold;iv) compared with only sub-6GHz ABSs, mmWave enabled TBSs are capable of enhancing the spectrum efficiency of the HetNets when the mmWave line-of-sight (LoS) link is available. Copyright © 2020, The Authors. All rights reserved.

关键词： Base stations

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Distributed resource scheduling for large-scale MEC systems: A multi-agent ensemble deep reinforcement learning with imitation acceleration

arXiv

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arXiv 2020年

作者： Jiang, Feibo Dong, Li Wang, Kezhi Yang, Kun Pan, Cunhua Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing Hunan Normal University Changsha China Key Laboratory of Hunan Province for New Retail Virtual Reality Technology Hunan University of Commerce Changsha China Department of Computer and Information Sciences Northumbria University United Kingdom School of Computer Sciences and Electrical Engineering University of Essex ColchesterCO4 3SQ United Kingdom School of Electronic Engineering and Computer Science Queen Mary University of London LondonE1 4NS United Kingdom

We consider the optimization of distributed resource scheduling to minimize the sum of task latency and energy consumption for all the Internet of things devices (IoTDs) in a large-scale mobile edge computing (MEC) system. To address this problem, we propose a distributed intelligent resource scheduling (DIRS) framework, which includes centralized training relying on the global information and distributed decision making by each agent deployed in each MEC server. More specifically, we first introduce a novel multi-agent ensemble-assisted distributed deep reinforcement learning (DRL) architecture, which can simplify the overall neural network structure of each agent by partitioning the state space and also improve the performance of a single agent by combining decisions of all the agents. Secondly, we apply action refinement to enhance the exploration ability of the proposed DIRS framework, where the near-optimal state-action pairs are obtained by a novel Lvy flight search. Finally, an imitation acceleration scheme is presented to pre-train all the agents, which can significantly accelerate the learning process of the proposed framework through learning the professional experience from a small amount of demonstration data. Extensive simulations are conducted to demonstrate that the proposed DIRS framework is efficient and outperforms the existing benchmark schemes. Copyright © 2020, The Authors. All rights reserved.

关键词： Deep learning

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Are state-of-the-art visual place recognition techniques any good for aerial robotics?

arXiv

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arXiv 2019年

作者： Zaffar, Mubariz Khaliq, Ahmad Ehsan, Shoaib Milford, Michael Alexis, Kostas McDonald-Maier, Klaus Embedded and Intelligent Systems Laboratory in Computer Science Electronic Engineering Department University of Essex Colchester United Kingdom Australian Centre for Robotic Vision and School of Electrical Engineering and Computer Science Queensland University of Technology BrisbaneQLD Australia Autonomous Robots Lab University of Nevada United States

Visual Place Recognition (VPR) has seen significant advances at the frontiers of matching performance and computational superiority over the past few years. However, these evaluations are performed for ground-based mobile platforms and cannot be generalized to aerial platforms. The degree of viewpoint variation experienced by aerial robots is complex, with their processing power and on-board memory limited by payload size and battery ratings. Therefore, in this paper, we collect 8 state-of-the-art VPR techniques that have been previously evaluated for ground-based platforms and compare them on 2 recently proposed aerial place recognition datasets with three prime focuses: a) Matching performance b) Processing power consumption c) Projected memory requirements. This gives a birds-eye view of the applicability of contemporary VPR research to aerial robotics and lays down the the nature of challenges for aerial-VPR. Copyright © 2019, The Authors. All rights reserved.

关键词： Antennas

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Gene knockout inference with variational graph autoencoder learning single-cell gene regulatory networks

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Nucleic acids research 2023年第13期51卷 6578-6592页

作者： Yongjian Yang Guanxun Li Yan Zhong Qian Xu Bo-Jia Chen Yu-Te Lin Robert S Chapkin James J Cai Department of Electrical and Computer Engineering Texas A&M University College Station TX 77843 USA. Department of Statistics Texas A&M University College Station TX 77843 USA. Key Laboratory of Advanced Theory and Application in Statistics and Data Science-MOE School of Statistics East China Normal University 3663 North Zhongshan Road Shanghai 200062 China. Department of Veterinary Integrative Biosciences Texas A&M University College Station TX 77843 USA. Graduate Institute of Microbiology and Public Health College of Veterinary Medicine National Chung Hsing University Taichung 402 Taiwan. Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei Taiwan. Program in Integrative & Complex Diseases Department of Nutrition Texas A&M University College Station TX 77843 USA. Interdisciplinary Program of Genetics Texas A&M University College Station TX 77843 USA.

In this paper, we introduce Gene Knockout Inference (GenKI), a virtual knockout (KO) tool for gene function prediction using single-cell RNA sequencing (scRNA-seq) data in the absence of KO samples when only wild-type (WT) samples are available. Without using any information from real KO samples, GenKI is designed to capture shifting patterns in gene regulation caused by the KO perturbation in an unsupervised manner and provide a robust and scalable framework for gene function studies. To achieve this goal, GenKI adapts a variational graph autoencoder (VGAE) model to learn latent representations of genes and interactions between genes from the input WT scRNA-seq data and a derived single-cell gene regulatory network (scGRN). The virtual KO data is then generated by computationally removing all edges of the KO gene-the gene to be knocked out for functional study-from the scGRN. The differences between WT and virtual KO data are discerned by using their corresponding latent parameters derived from the trained VGAE model. Our simulations show that GenKI accurately approximates the perturbation profiles upon gene KO and outperforms the state-of-the-art under a series of evaluation conditions. Using publicly available scRNA-seq data sets, we demonstrate that GenKI recapitulates discoveries of real-animal KO experiments and accurately predicts cell type-specific functions of KO genes. Thus, GenKI provides an in-silico alternative to KO experiments that may partially replace the need for genetically modified animals or other genetically perturbed systems.

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Lightweight Image Super-Resolution with Enhanced CNN

arXiv

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arXiv 2020年

作者： Tian, Chunwei Zhuge, Ruibin Wu, Zhihao Xu, Yong Zuo, Wangmeng Chen, Chen Lin, Chia-Wen Bio-Computing Research Center Harbin Institute of Technology Shenzhen ShenzhenGuangdong518055 China Shenzhen Key Laboratory of Visual Object Detection and Recognition ShenzhenGuangdong518055 China Peng Cheng Laboratory ShenzhenGuangdong518055 China School of Computer Science and Technology Harbin Institute of Technology HarbinHeilongjiang150001 China Department of Electrical and Computer Engineering University of North Carolina at Charlotte NC28223 United States Department of Electrical Engineering Institute of Communications Engineering National Tsing Hua University Hsinchu Taiwan

Deep convolutional neural networks (CNNs) with strong expressive ability have achieved impressive performances on single image super-resolution (SISR). However, their excessive amounts of convolutions and parameters usually consume high computational cost and more memory storage for training a SR model, which limits their applications to SR with resource-constrained devices in real world. To resolve these problems, we propose a lightweight enhanced SR CNN (LESRCNN) with three successive sub-blocks, an information extraction and enhancement block (IEEB), a reconstruction block (RB) and an information refinement block (IRB). Specifically, the IEEB extracts hierarchical low-resolution (LR) features and aggregates the obtained features step-by-step to increase the memory ability of the shallow layers on deep layers for SISR. To remove redundant information obtained, a heterogeneous architecture is adopted in the IEEB. After that, the RB converts low-frequency features into high-frequency features by fusing global and local features, which is complementary with the IEEB in tackling the long-term dependency problem. Finally, the IRB uses coarse high-frequency features from the RB to learn more accurate SR features and construct a SR image. The proposed LESRCNN can obtain a high-quality image by a model for different scales. Extensive experiments demonstrate that the proposed LESRCNN outperforms state-of-the-arts on SISR in terms of qualitative and quantitative evaluation. The code of LESRCNN is accessible on https://***/hellloxiaotian/LESRCNN. Copyright © 2020, The Authors. All rights reserved.

关键词： Convolutional neural networks

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Nonlinear dynamics in an optoelectronic feedback delay oscillator with piecewise linear transfer functions from the laser diode and photodiode

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Physical Review E 2020年第4期102卷 042217-042217页

作者： Géraud R. Goune Chengui Kengne Jacques Paul Woafo Yanne K. Chembo Laboratories d'Automatique et Informatique Appliquée (UR-AIA) Department of Electrical Engineering IUT-FV Bandjoun P.O. Box 134 Bandjoun Cameroon Laboratory of Modelling and Simulation in Engineering Biomimetics and Prototypes Department of Physics Faculty of Science P.O. Box 812 Yaoundé Cameroon University of Maryland A. James Clark School of Engineering Department of Electrical and Computer Engineering and Institute for Research in Electronics and Applied Physics (IREAP) 8279 Paint Branch Drive College Park Maryland 20742 USA

We investigate the nonlinear dynamics of a recent architecture of an optoelectronic oscillator, where the emitting laser and the receiving diode are connected in a head-to-tail configuration via an optical fiber delay line. The resulting nonlinear transfer function is a piecewise linear profile, and its interplay with the delay leads to many complex behaviors such as relaxation oscillations and deterministic chaos. This system belongs to a recent class of optoelectronic oscillators where the nonlinearity does not originate from the sinusoidal transfer function of an imbalanced interferometer, and, in particular, it is a simple optoelectronic oscillator configuration that is capable of displaying a chaotic behavior. The results of the analytic study are confirmed by numerical simulations and experimental measurements.

关键词： Control & applications of chaos Chaotic systems

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Correction to: Quantitative susceptibility atlas construction in Montreal Neurological Institute space: towards histological‑consistent iron‑rich deep brain nucleus subregion identification

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Brain structure & function 2023年第2期228卷 697页

作者： Chenyu He Xiaojun Guan Weimin Zhang Jun Li Chunlei Liu Hongjiang Wei Xiaojun Xu Yuyao Zhang School of Information Science and Technology ShanghaiTech University 393 Huaxia Road Shanghai 201210 China. Department of Radiology of The Second Affiliated Hospital Zhejiang University School of Medicine 88 Jiefang Road Hangzhou 310009 Zhejiang China. Electrical Engineering and Computer Science University of California at Berkeley Berkeley CA 94720 United States. School of Biomedical Engineering Shanghai Jiao Tong University 800 Dongchuan Road Shanghai 200030 China. School of Information Science and Technology ShanghaiTech University 393 Huaxia Road Shanghai 201210 China. zhangyy8@***. Shanghai Engineering Research Center of Intelligent Vision and Imaging ShanghaiTech University 393 Huaxia Road Shanghai 201210 China. zhangyy8@***.

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High performance polarization management devices based on thin-film lithium niobate

arXiv

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arXiv 2021年

作者： Lin, Zhongjin Lin, Yanmei Li, Hao Xu, Mengyue He, Mingbo Ke, Wei Li, Zhaohui Wang, Dawei Yao, X. Steve Yu, Siyuan Cai, Xinlun State Key Laboratory of Optoelectronic Materials and Technologies School of Electronics and Information Technology Sun Yat-sen University Guangzhou510275 China Department of Electrical and Computer Engineering The University of British Columbia VancouverBCV6T 1Z4 Canada Photonics Information Innovation Center Hebei Provincial Center for Optical Sensing Innovations College of Physics Science and Technology Hebei University Baoding071002 China

High-speed polarization management is highly desirable for many applications, such as remote sensing, telecommunication, and medical diagnosis. However, most of the approaches for polarization management rely on bulky optical components that are slow to respond, cumbersome to use, and sometimes with high drive voltages. Here, we overcome these limitations by harnessing photonic integrated circuits based on thin-film lithium niobate platform. We successfully realize a portfolio of thin-film lithium niobate devices for essential polarization management functionalities, including arbitrary polarization generation, fast polarization measurement, polarization scrambling, and automatic polarization control. The present devices feature ultra-fast control speed, low drive voltages, low optical losses and compact footprints. Using these devices, we achieve high fidelity polarization generation with a polarization extinction ratio up to 41.9 dB, fast polarization scrambling with a scrambling rate up to 65 Mrad/s, and endless polarization control with a tracking speed up to 10 Krad/s, all of which are best results in integrated optics. The demonstrated devices unlock a drastically new level of performance and scales in polarization management devices, leading to a paradigm shift in polarization management. © 2021, CC BY.

关键词： Thin films

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