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arXiv 2020年

作者： Zhong, Xiaoqing Xu, Feihu Lo, Hoi-Kwong Qian, Li Center for Quantum Information and Quantum Control Dept. of Physics University of Toronto TorontoONM5S 1A7 Canada Hefei National Laboratory for Physical Sciences at the Microscale and Department of Modern Physics University of Science and Technology of China Hefei230026 China Center for Quantum Information and Quantum Control Dept. of Electrical & Computer Engineering University of Toronto TorontoONM5S 3G4 Canada

Quantum communication complexity studies the efficiency of information communication (that is, the minimum amount of communication required to achieve a certain task) using quantum states. One representative example is quantum fingerprinting, in which the simultaneous message passing model is considered and the minimum amount of communication could be exponentially smaller than the classical fingerprinting protocol. Experimental demonstrations based on a practical quantum fingerprinting protocol where coherent states are used to construct the fingerprints, have successfully shown the superiority of quantum fingerprinting. However, as a consequence of using coherent states, the communication time in this coherent quantum fingerprinting (CQF) protocol is increased. Moreover, the minimum amount of information communicated in these experimental demonstrations is largely limited by the dark counts of the single photon detectors. Here, we propose to enhance the performance of the existing CQF protocol through applying wavelength division multiplexing (WDM) and simultaneous detection of multiple wavelength channels. We show that the new WDM-CQF protocol can potentially reduce the communication time significantly. More importantly, with the same experimental parameters, the amount of communication is much reduced in the new scheme compared with the original CQF protocol. The more wavelength channels are used, the less communication is required by WDM-CQF protocol. We also perform a proof-of-concept experimental demonstration of the new WDM-CQF protocol with 6 wavelength channels. The experimental results further validate that the new scheme with WDM not only beats the classical protocol, but also reduces the amount of communication required by the original CQF protocol by more than half. Copyright © 2020, The Authors. All rights reserved.

关键词： Demonstrations

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Method for pests detecting in stored grain based on spectral residual saliency edge detection

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Grain & Oil science and Technology 2019年第2期2卷 33-38页

作者： Yao Qin Yanli Wu Qifu Wang Suping Yu College of Information Science and Engineering Henan University of TechnologyZhengzhou 450001China Key Laboratory of Grain Information Processing and Control Henan University of TechnologyMinistry of EducationZhengzhou 450001China Henan Academy of Science Applied Physics Institute Co.LtdZhengzhou 450001China Luoyang Institute of Science and Technology Department of Computer and Information EngineeringLuoyang 471000China

Pests detecting is an important research subject in grain storage *** the past decades,many edge detection methods have been applied to the edge detection of stored grain *** some of them can realize the stored grain pests detecting,precision and robustness are not good *** residual(SR)saliency edge detection defines the logarithmic spectrumof image as novelty part of the image *** remaining spectrumis converted to the airspace to obtain edge detection *** algorithm is completely based on frequency domain *** not only can effectively simplify the target detection algorithm,but also can improve the effectiveness of target *** experimental results show that the edge results of stored grain pests detected by SR method are effective and stable.

关键词： Stored grain pests Saliency detection Spectral residual (SR) Edge detection

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Intelligent welding robot system based on deep learning

Intelligent welding robot system based on deep learning

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Chinese Automation Congress (CAC)

作者： Xufeng Ma Shuwen Pan Yanjun Li Chao Feng Aoran Wang College of Control Science and Engineering Zhejiang University Hangzhou China School of Information and Electrical Engineering Zhejiang University City College Hangzhou China College of Computer Science and Technology Zhejiang University Hangzhou China Zhejiang University City College Hangzhou China

An intelligent welding robot system based on deep learning is designed. Firstly, the binocular vision system needs to be fixed and calibrated, and correct the left and right cameras to make the polar lines of the left and right images collinear. Then, the left camera is used to take 1000 photos of arbitrary arranging fence. The position of the weld is marked by LabelImg software, and the training set and validation set are determined in a ratio of 3:1, and then used to train the convolutional neural network. After the loss function tends to converge, the training stops. The model optimizer converts the TensorFlow model into an IR model through the model optimizer in openvino, which is then deployed to the Raspberry Pi 3B+, which performs forward propagation through Intel's NCS2 edge computing stick to identify the location of the weld in the image. The exact position of the weld is found by machine vision, and the parallax of all the welds is calculated by matching with the right image, and the depth of the weld is obtained by calculation. Finally, transfer the UR3 robot through Ethernet and control it for automatic welding.

关键词： Welding Cameras Robot kinematics Calibration Robot vision systems Matrix decomposition

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Preface

Advances in Intelligent Systems and Computing

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Advances in Intelligent Systems and Computing 2020年 1241 AISC卷 v-vi页

作者： Vittorini, Pierpaolo Di Mascio, Tania Tarantino, Laura Temperini, Marco Gennari, Rosella De la Prieta, Fernando Department of Life Health and Environmental Sciences University of L’Aquila L’Aquila Italy Department of Information Engineering Computer Science and Mathematics University of L’Aquila L’Aquila Italy Computer Science Faculty Free University of Bozen-Bolzano Bolzano Italy Department of Computer Control and Management Engineering Sapienza University of Rome Rome Italy Department of Computer Science and Automation Control University of Salamanca Salamanca Spain

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Achieving data utility-privacy tradeoff in internet of medical things: A machine learning approach

arXiv

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arXiv 2019年

作者： Guan, Zhitao Lv, Zefang Du, Xiaojiang Wu, Longfei Guizani, Mohsen School of Control and Computer Engineering North China Electric Power University China School of Mathematics and Physics North China Electric Power University China Department of Computer and Information Science Temple University PhiladelphiaPA United States Department of Mathematics and Computer Science Fayetteville State University FayettevilleNC United States Electrical and Computer Engineering Department University of Idaho MoscowID United States

The emergence and rapid development of the Internet of Medical Things (IoMT), an application of the Internet of Things into the medical and healthcare systems, have brought many changes and challenges to modern medical and healthcare systems. Particularly, machine learning technology can be used to process the data involved in IoMT for medical analysis and disease diagnosis. However, in this process, the disclosure of personal privacy information must receive considerable attentions especially for sensitive medical data. Cluster analysis is an important technique for medical analysis and disease diagnosis. To enable privacy-preserving cluster analysis in IoMT, this paper proposed an Efficient Differentially Private Data Clustering scheme (EDPDCS) based on MapReduce framework. In EDPDCS, we optimize the allocation of privacy budgets and the selection of initial centroids to improve the accuracy of differentially private Kmeans clustering algorithm. Specifically, the number of iterations of the K-means algorithm is set to a fixed value according to the total privacy budget and the minimal privacy budget of each iteration. In addition, an improved initial centroids selection method is proposed to increase the accuracy and efficiency of the clustering algorithm. Finally, we prove that the proposed EDPDCS can improve the accuracy of the differentially private k-means algorithm by comparing the Normalized Intra-Cluster Variance (NICV) produced by our algorithm on two datasets with two other algorithms. Copyright © 2019, The Authors. All rights reserved.

关键词： MapReduce

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Master equations and quantum trajectories for squeezed wave packets

arXiv

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arXiv 2021年

作者： Gross, Jonathan A. Baragiola, Ben Stace, T.M. Combes, Joshua Center for Quantum Information and Control University of New Mexico AlbuquerqueNM87131-0001 United States Institut Quantique Université de Sherbrooke SherbrookeQCJ1K 2R1 Canada Centre for Quantum Computation & Communication Technology School of Science RMIT University MelbourneVIC3000 Australia ARC Centre for Engineered Quantum System Department of Physics University of Queensland BrisbaneQLD4072 Australia Department of Electrical Computer and Energy Engineering University of Colorado Boulder BoulderCO80309 United States

The interaction between matter and squeezed light has mostly been treated within the approximation that the field correlation time is small. Methods for treating squeezed light with more general correlations currently involve explicitly modeling the systems producing the light. We develop a general purpose input-output theory for a particular form of narrowband squeezed light-a squeezed wave-packet mode-that only cares about the statistics of the squeezed field and the shape of the wave packet. This formalism allows us to derive the input-output relations and the master equation. We also consider detecting the scattered field using photon counting and homodyne measurements which necessitates the derivation of the stochastic master equation. The non Markovian nature of the field manifests itself in the master equation as a coupled hierarchy of equations. We illustrate these with consequences for the decay and resonance fluorescence of two-level atoms in the presence of such fields. Copyright © 2021, The Authors. All rights reserved.

关键词： Wave packets

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Analysis of moving target defense against false data injection attacks on power grid

arXiv

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arXiv 2019年

作者： Zhang, Zhenyong Deng, Ruilong Yau, David K.Y. Cheng, Peng Chen, Jiming State Key Laboratory of Industrial Control Technology College of Control Science and Engi-neering Zhejiang University Hangzhou310027 China School of Computer Science and Engineering Nanyang Technological University 639798 Singapore Information Systems Technology and Design Singapore University of Technology and Design 487372 Singapore

Recent studies have considered thwarting false data injection (FDI) attacks against state estimation in power grids by proactively perturbing branch susceptances. This approach is known as moving target defense (MTD). However, despite of the deployment of MTD, it is still possible for the attacker to launch stealthy FDI attacks generated with former branch susceptances. In this paper, we prove that, an MTD has the capability to thwart all FDI attacks constructed with former branch susceptances only if (i) the number of branches l in the power system is not less than twice that of the system states n (i.e., l ≥ 2n, where n + 1 is the number of buses);(ii) the susceptances of more than n branches, which cover all buses, are perturbed. Moreover, we prove that the state variable of a bus that is only connected by a single branch (no matter it is perturbed or not) can always be modified by the attacker. Nevertheless, in order to reduce the attack opportunities of potential attackers, we first exploit the impact of the susceptance perturbation magnitude on the dimension of the stealthy attack space, in which the attack vector is constructed with former branch susceptances. Then, we propose that, by perturbing an appropriate set of branches, we can minimize the dimension of the stealthy attack space and maximize the number of covered buses. Besides, we consider the increasing operation cost caused by the activation of MTD. Finally, we conduct extensive simulations to illustrate our findings with IEEE standard test power systems. Copyright © 2019, The Authors. All rights reserved.

关键词： Network security

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Semi-Supervised Cross-Modal Hashing Based on Label Prediction and Distance Preserving

Semi-Supervised Cross-Modal Hashing Based on Label Predictio...

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International Conference on Tools for Artificial Intelligence (ICTAI)

作者： Xu Zhang Xin Tian Bing Yang Zuyu Zhang Yan Li Department of Computer Science and Technology Chongqing University of Posts and Telecommunications Chongqing China National Engineering Laboratory for Public Safety Risk Perception and Control by Big Data(PSRPC) China Academy of Electronics and Information Technology Department of Computer Engineering Inha University Incheon South Korea

Unlabeled data can be easily collected and help to exploit the correlations among different modalities. Existing works tried to explore label information contained in unlabeled data, however most of them suffer from difficulties in separating samples from different categories and have great interference. This paper proposes a novel method named semi-supervised cross-modal hashing based on label prediction and distance preserving(SS-LPDP). First, we use the deep neural networks to extract the feature of the labeled data among different modalities and get the feature distribution of each category. Second, the similarity of the data among different modalities is maximized based on the extracted feature and the label information. A common objective function is proposed with distance preserving constraint, which can effectively separate data into different categories and reduce interference in retrieval. An optimization algorithm is used to update the network parameters of feature learning in each modality, and the label information of unlabeled data are dynamically updated according to the changes of the feature distribution in each iteration. Experimental evaluation on Wiki, Pascal and NUS-WIDE datasets show that the proposed method outperforms recent methods when we set 25% samples without category labels.

关键词：

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Three-dimensional spin Hall effect of light in tight focusing

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Physical Review A 2020年第2期101卷 023819-023819页

作者： Weixing Shu Chuyang Lin Jun Wu Shizhen Chen Xiaohui Ling Xinxing Zhou Hailu Luo Shuangchun Wen Key Laboratory for Micro/Nano Optoelectronic Devices of Ministry of Education & Hunan Provincial Key Laboratory of Low-Dimensional Structural Physics and Devices School of Physics and Electronics Hunan University Changsha 410082 China Key Laboratory of Low Dimensional Quantum Structures and Quantum Control of Ministry of Education Hunan Normal University Changsha 410081 China College of Computer Science and Electronic Engineering Hunan University Changsha 410082 China Hunan Provincial Key Laboratory of Intelligent Information Processing and Application College of Physics and Electronic Engineering Hengyang Normal University Hengyang 421002 China

We theoretically propose the realization of a three-dimensional (3D) spin Hall effect (SHE) of light by tightly focusing a linearly polarized light. Owing to the spin-orbital interaction in focusing, the left and right circularly polarized components of light are partly converted into each other, acquiring opposite vortex phases. As the superposition of the vortex and the initial vortex-free light, the two polarized components exhibit spiral intensity patterns which rotate oppositely around the propagation axis. Consequently, the two spin components are distributed alternatively in both the azimuthal and the longitudinal directions, leading to a 3D array of split spin components, and the transverse intensity is also spit asynchronously. Moreover, that array is rotatable by the incident polarization, and the longitudinal spacing in the array can be controlled by the numerical aperture of the lens. The 3D SHE of light finds an additional degree of freedom available to control the spin state of the photon, which may be valuable in optical manipulation and quantum information.

关键词： Classical optics

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Scoring the terabit/s goal: Broadband connectivity in 6G

arXiv

引用

arXiv 2020年

作者： Rajatheva, Nandana Atzeni, Italo Bicaïs, Simon Björnson, Emil Bourdoux, André Buzzi, Stefano D'Andrea, Carmen Doré, Jean-Baptiste Erkucuk, Serhat Fuentes, Manuel Guan, Ke Hu, Yuzhou Huang, Xiaojing Hulkkonen, Jari Jornet, Josep Miquel Katz, Marcos Makki, Behrooz Nilsson, Rickard Panayirci, Erdal Rabie, Khaled Rajapaksha, Nuwanthika Salehi, Mohammadjavad Sarieddeen, Hadi Shahabuddin, Shahriar Svensson, Tommy Tervo, Oskari Tölli, Antti Wu, Qingqing Xu, Wen Centre for Wireless Communications University of Oulu Finland CEA-Leti France KTH Royal Institute of Technology Sweden Linköping University Sweden IMEC Belgium University of Cassino and Southern Latium Italy Italy Department of Electrical and Electronics Engineering Kadir Has University Turkey Fivecomm Valencia Spain State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University China The Beijing Engineering Research Center of High-Speed Railway Broadband Mobile Communications China Algorithm Department ZTE Corporation China School of Electrical and Data Engineering Faculty of Engineering and Information Technology University of Technology Sydney Australia Nokia Bell Labs Finland Institute for the Wireless Internet of Things Department of Electrical and Computer Engineering Northeastern University United States Ericsson Research Gothenburg Sweden Department of Computer Science Electrical and Space Engineering Luleå University of Technology Sweden Department of Engineering Manchester Metropolitan University United Kingdom Division of Computer Electrical and Mathematical Sciences and Engineering King Abdullah University of Science and Technology Saudi Arabia Nokia Finland Department of Electrical Engineering Chalmers University of Technology Sweden State Key Laboratory of Internet of Things for Smart City Department of Electrical and Computer Engineering University of Macau China Huawei Technologies Germany

This paper explores the road to vastly improving the broadband connectivity in future 6G wireless systems. Different categories of use cases are considered, with peak data rates up to 1 Tbps. Several categories of enablers at the infrastructure, spectrum, and protocol/algorithmic levels are required to realize the intended broadband connectivity goals in 6G. At the infrastructure level, we consider ultra-massive MIMO technology (possibly implemented using holographic radio), intelligent reflecting surfaces, user-centric cell-free networking, integrated access and backhaul, and integrated space and terrestrial networks. At the spectrum level, the network must seamlessly utilize sub-6 GHz bands for coverage and spatial multiplexing of many devices, while higher bands will be mainly used for pushing the peak rates of point-to-point links. Finally, at the protocol/algorithmic level, the enablers include improved coding, modulation, and waveforms to achieve lower latency, higher reliability, and reduced complexity. © 2020, CC BY.

关键词： MIMO systems

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