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IEEE International Conference on Communications in China Workshops (ICCC)

作者： Zhongyu Wang Gengxin Zhao Yashuai Cao Jiawei Zhang Zheng Chang Hebei Key Laboratory of Information Transmission and Signal Processing School of Information Science and Engineering Yanshan University Qinhuangdao China Department of Electronic Engineering Tsinghua University Beijing China School of Computer Science University of Electronic Science and Technology of China Chengdu China Faculty of Information Technology University of Jyäaskylä Jyväskylä Finland

ISBN: (数字)9798350377675

ISBN: (纸本)9798350377682

Reconfigurable intelligent surface (RIS) assisted communication is recognized as a promising technology in academia and industry because it offers a novel and promising solution for implementing both secure and good-quality wireless communication networks. The paper proposes installing an RIS on a sweeping robot to act as the mobile passive relay, which can flexibly deploy the location of RIS and enhance communication capacity. In this paper, the maximization problem of user throughput is formulated, and we jointly optimize transmission power at AP and reflection phase shifts at RIS. It is difficult to deal with the optimization problem. Therefore, we separate the two variables into two subproblems, i.e., the transmit power optimization problem and the reflection phase-shift optimization problem. We can solve these problems by semidefinite relaxation (SDR) and alternating optimization algorithms. The simulation results demonstrate the advantages of the proposed algorithm, which enhances the communication capacity efficiently.

关键词： Wireless communication Industries Service robots Simulation Conferences Reconfigurable intelligent surfaces Throughput Reflection Relays Optimization

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Entirety of Quantum Uncertainty and Its Experimental Verification

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Chinese Physics Letters 2021年第7期38卷 11-16页

作者： Jie Xie Li Zhou Aonan Zhang Huichao Xu Man-Hong Yung Ping Xu Nengkun Yu Lijian Zhang National Laboratory of Solid State Microstructures College of Engineering and Applied Sciences and School of PhysicsNanjing UniversityNanjing 210093China Collaborative Innovation Center of Advanced Microstructures Nanjing UniversityNanjing 210093China Department of Computer Science and Technology Tsinghua UniversityBeijing 100084China Shenzhen Institute for Quantum Science and Engineering and Department of Physics Southern University of Science and TechnologyShenzhen 518055China Shenzhen Key Laboratory of Quantum Science and Engineering Southern University of Science and TechnologyShenzhen 518055China Institute for Quantum Information&State Key Laboratory of High Performance Computing College of ComputerNational University of Defense TechnologyChangsha 410073China Centre for Quantum Software and Information School of SoftwareFaculty of Engineering and Information TechnologyUniversity of Technology SydneyNSWAustralia

As a foundation of quantum physics,uncertainty relations describe ultimate limit for the measurement uncertainty of incompatible ***,uncertainty relations are formulated by mathematical bounds for a specific *** we present a method for geometrically characterizing uncertainty relations as an entire area of variances of the observables,ranging over all possible input *** find that for the pair of position and momentum operators,Heisenberg's uncertainty principle points exactly to the attainable area of the variances of position and ***,for finite-dimensional systems,we prove that the corresponding area is necessarily semialgebraic;in other words,this set can be represented via finite polynomial equations and inequalities,or any finite union of such *** particular,we give the analytical characterization of the areas of variances of(a)a pair of one-qubit observables and(b)a pair of projective observables for arbitrary dimension,and give the first experimental observation of such areas in a photonic system.

关键词： observable union operators

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Multi-view Semantic information Guidance for Light Field Image Segmentation

Multi-view Semantic Information Guidance for Light Field Ima...

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2023 IEEE/CVF Conference on computer vision and Pattern Recognition Workshops, CVPRW 2023

作者： Li, Yiming Cong, Ruixuan Wang, Sizhe Zhao, Mingyuan Zhang, Yang Li, Fangping Sheng, Hao Beihang University State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beijing100191 China Beihang Hangzhou Innovation Institute Yuhang Xixi Octagon City Hangzhou310023 China Beijing University of Chemical Technology College of Information Science and Technology Beijing100029 China Macao Polytechnic University Faculty of Applied Sciences 999078 China

ISBN: (纸本)9798350302493

One of the great important fields of computer vision is semantic segmentation. As for single image semantic segmentation, due to limited available information, it appears poor performance when the occlusion and similar color interference occur, and has difficulty exploiting the rich scene information. In comparison, the special micro-len array structure of light field camera can record multi-view information of the scene, which provides us with a new solution to solve this issue. In this paper, we propose a multi-view semantic information guidance network (MSIGNet) for light field semantic segmentation. It can effectively utilize semantic information from multi-view images to guide pixel feature of center view image. First, we extract feature of each view image and further obtain semantic probability. Then all probabilities are aggregated through a self-adaptive multi-view probability fusion module. Last, the resulting coarse fusion representation interacts with center view feature to obtain the refined segmentation result. The proposed method shows excellent performance on both real-world and synthetic light field datasets. © 2023 IEEE.

关键词： Semantic Segmentation

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Human Activity Dataset of Top Frequent Elderly Emergencies for Monitoring Applications using Kinect

Human Activity Dataset of Top Frequent Elderly Emergencies f...

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IEEE Annual International computer Software and Applications Conference (COMPSAC)

作者： Raoudha Nouisser Salma Kammoun Jarraya Mohamed Hammami MIRACL Laboratory Faculty of Economics and Management University of Sfax Sfax Tunisia Computer Science Department Faculty of Computing and Information Technology King Abdulaziz University Jeddah Saudi Arabia MIRACL Laboratory Faculty of Sciences University of Sfax Sfax Tunisia

Gathering a dataset is essential in machine learning to develop new approaches and test their effectiveness. Despite their importance, it is difficult to find available datasets that meet researcher requirements, especially for the healthcare domain. This paper presents a new visual dataset of the top frequent elderly emergencies (heart attack, stroke, and Chronic Obstructive Pulmonary Disease (COPD) exacerbation). It is designed for the evaluation of different computational computer vision monitoring applications and human activity analysis. It can also be used for abnormal activity detection. This dataset covers the most frequent symptoms of each emergency. Each symptom is presented by different scenarios validated by a medical emergency expert. This dataset is recorded using the Kinect camera. Its samples are performed only in-depth and skeleton data to preserve the privacy of participants. Also, it is evaluated using methods based on Kinect skeleton data.

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Experimental demonstration of a flexible-grid 1×(2×3)mode-and wavelength-selective switch using silicon microring resonators and counter-tapered couplers

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Chinese Optics Letters 2024年第1期22卷 52-58页

作者：孔德军鲁昊汪鹏君符强戴世勋陈伟伟王栎沣张波豪马凌霄李军戴庭舸杨建义 Faculty of Electrical Engineering and Computer Science Ningbo UniversityNingbo 315211China College of Electrical and Electronic Engineering Wenzhou UniversityWenzhou 325035China College of Science and Technology Ningbo UniversityNingbo 315300China Laboratory of Infrared Materials and Devices The Research Institute of Advanced TechnologiesNingbo UniversityNingbo 315211China Department of Information Science and Electronics Engineering and Cyrus Tang Center for Sensor Materials and Applications Zhejiang UniversityHangzhou 310027China

A flexible-grid 1×(2×3)mode-and wavelength-selective switch which comprises counter-tapered couplers and silicon microring resonators has been proposed,optimized,and demonstrated experimentally in this *** carefully thermally tuning phase shifters and silicon microring resonators,mode and wavelength signals can be independently and flexibly conveyed to any one of the output ports,and different bandwidths can be generated as *** particle swarm optimization algorithm and finite difference time-domain method are employed to optimize structural parameters of the twomode(de)multiplexer and crossing *** bandwidth-tunable wavelength-selective optical router composed of12 microring resonators is studied by taking advantage of the transfer matrix *** results show that,for the fabricated module,cross talk less than-10.18 dB,an extinction ratio larger than 17.41 d B,an in-band ripple lower than0.79 dB,and a 3-dB bandwidth changing from 0.38 to 1.05 nm are obtained,as the wavelength-channel spacing is 0.40 *** corresponding response time is measured to be 13.64μs.

关键词： integrated optics optical waveguide mode-and wavelength-selective switch

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DEEP LEARNING APPLICATION for IMAGE ENHANCEMENT 9

DEEP LEARNING APPLICATION for IMAGE ENHANCEMENT

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9th International Conference "Distributed Computing and Grid Technologies in science and Education", GRID 2021

作者： Elaraby, Ahmed Elansary, Ismail Nechaevskiy, Andrey Department of Computer Science Faculty of Computers and Information South Valley University Qena83523 Egypt Modern Academy for Computer Science and Management Technology Cairo Egypt Meshcheryakov Laboratory of Information Technologies Joint Institute for Nuclear Research Joliot-Curie 6 Dubna 141980 Russia

Recently, deep learning has obtained a central position toward our daily life automation and delivered considerable improvements as compared to traditional algorithms of machine learning. Enhancing of image quality is a fundamental image processing task and. A high-quality image is always expected in several tasks of vision, and degradations like noise, blur, and low-resolution, are required to be removed. The deep techniques approaches can significantly and substantially boost performance compared with classical ones. One of the main research areas where deep learning can make a major impact is imaging. This work presents a survey of deep learning on image enhancement and describes its potential for future research. Copyright © 2021 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Image enhancement

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Visible Light Positioning Method for Indoor Line-of-Sight Scene Based on Time Series Coding

Visible Light Positioning Method for Indoor Line-of-Sight Sc...

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IEEE International Conference on Data science in Cyberspace (DSC)

作者： Yonghao Yu Yongde Guo Dawei Zhao Kexue Fu Yongwei Tang Qinyuan Wang Faculty of Data Science City University of Macau China Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center(National Supercomputer Center in Jinan) Qilu University of Technology (Shandong Academy of Sciences) Jinan China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Computer Networks Jinan China School of Mechanical Engineering Key Laboratory of High Efficiency and Clean Mechanical Manufacture Ministry of Education Shandong University Jinan China

ISBN: (数字)9798350391367

ISBN: (纸本)9798350391374

Existing indoor visible light positioning methods, such as those based on fingerprint database algorithms, are complex to construct and consume significant resources. In response to this issue, the text proposes an end-to-end indoor visible light positioning method that samples continuous signals at a small number of random coordinate positions in indoor environments. Through a deep learning method based on attention mechanism, a nonlinear mapping between the received signal and spatial position coordinates is constructed, and the time series properties in the received signal are encoded as a feature in the data. The method is further improved by combining residual networks to improve accuracy. Through simulation experiments, it has been verified that the deep learning based localization method described in this article can achieve sub meter level accuracy on small sample datasets, and it has been proven that time series features have a significant impact on localization accuracy in indoor visible light positioning algorithms based on deep learning.

关键词： Location awareness Deep learning Meters Training Accuracy Attention mechanisms Time series analysis Training data Encoding Data models

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QCSAS: A Quasi-Constant and Synchronized Aggregate Signature Scheme for AMI Networks

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IEEE Internet of Things Journal 2025年

作者： Sun, Yujiao Sui, Zhiyuan Wang, Huaqun de Meer, Hermann Beijing Institute of Technology MIIT Key Laboratory of Mathematical Theory and Computation in Information Security School of Mathematics and Statistics Beijing China Central University of Finance and Economics Information School Beijing China Nanjing University of Posts and Telecommunications School of Computer Science Nanjing China University of Passau Faculty of Computer Science and Mathematics Passau Germany

Smart grids must safeguard their critical infrastructures against both physical and cyber attacks. Therefore, real-time operation and cybersecurity are two fundamental requirements for smart grid systems. AMI (Advanced Metering Infrastructure) is a critical part of the smart grid that specifically deals with the measurement, collection, and analysis of electricity usage data. Digital signatures help prevent data tampering and ensure cybersecurity during AMI communications. However, as the number of smart meters and transactions in an AMI network increases, deploying digital signatures can lead to communication delays. This paper designs a quasi-constant and synchronized aggregate signature scheme (QCSAS), which can protect usage data without hash functions. The QCSAS scheme simplifies the synchronized aggregate signatures, and is proved secure against chosen message attacks in the random oracle model. The QCSAS scheme incorporates the features of synchronized aggregate signatures, such as the constant aggregate signature size, thereby minimizing the data management system’s storage space. Furthermore, the length of usage data does not exceed 12-bit, in compliance with existing governmental standards. The computational cost of multiplying a 12-bit integer is negligible compared to other cryptographic operations. Thus, the verification cost of the QCSAS scheme remains quasi-constant. © 2014 IEEE.

关键词： Advanced metering infrastructures

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Time-Aware Missing Traffic Flow Prediction for Sensors with Privacy-Preservation 11th

Time-Aware Missing Traffic Flow Prediction for Sensors with ...

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11th International Conference on computer Engineering and Networks, CENet2021

作者： Qi, Lianyong Wang, Fan Xu, Xiaolong Dou, Wanchun Zhang, Xuyun Khosravi, Mohammad R. Zhou, Xiaokang School of Computer Science Qufu Normal University Qufu China School of Computer and Software Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology Nanjing University of Information Science and Technology Nanjing China State Key Laboratory for Novel Software Technology Department of Computer Science and Technology Nanjing University Nanjing China Department of Computing Macquarie University SydneyNSW2109 Australia Department of Computer Engineering Persian Gulf University Bushehr Iran Department of Electrical and Electronic Engineering Shiraz University of Technology Shiraz Iran Faculty of Data Science Shiga University Hikone Japan

ISBN: (纸本)9789811665530

With the continuous development of IoT, a number of sensors establish on the roadside to monitor traffic conditions in real time. The continuously traffic data generated by these sensors makes traffic management feasible. However, loss of data may occur due to inevitable sensor failure, impeding traffic managers to understand traffic dynamics clearly. In this situation, it is becoming a necessity to predict missing traffic flow accurately for effective traffic management. Furthermore, the traffic sensor data are often distributed and stored by different agencies, which inhibits the multi-party sensor data sharing significantly due to privacy concerns. Therefore, it has become a major obstacle to balance the tradeoff between data sharing and vehicle privacy. In light of these challenges, we propose a privacy-aware and accurate missing traffic flow prediction approach based on time-aware Locality-Sensitive Hashing technique. At last, we deploy a set of experiments based on a real traffic dataset. Experimental reports demonstrate the feasibility of our proposal in terms of traffic flow prediction accuracy and efficiency while guaranteeing sensor data privacy. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Data privacy

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A Remote Quantum Error-correcting Code Preparation Protocol on Cluster State

arXiv

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arXiv 2023年

作者： Zhao, Qiang Mao, Haokun Qiao, Yucheng Abd El-Latif, Ahmed A. Li, Qiong Information Countermeasure Technique Institute School of Cyberspace Science Faculty of Computing Harbin Institute of Technology Harbin150001 China Department of Computer Science and Engineering The Chinese University of Hong Kong 999077 Hong Kong School of Information Engineering Guilin University of Electronic Science and Technology Guilin541004 China EIAS Data Science Laboratory College of Computer and Information Sciences Prince Sultan University Riyadh11586 Saudi Arabia Department of Mathematics and Computer Science Faculty of Science Menoufia University Shibin Al Kawm32511 Egypt

The blind quantum computation (BQC) protocol allows for privacy-preserving remote quantum computations. In this paper, we introduce a remote quantum error correction code preparation protocol for BQC using a cluster state and analyze its blindness in the measurement-based quantum computation model. Our protocol requires fewer quantum resources than previous methods, as it only needs weak coherent pulses, eliminating the need for quantum memory and limited quantum computing. The results of our theoretical analysis and simulations show that our protocol requires fewer quantum resources compared to non-coding methods with the same qubit error rate. © 2023, CC BY.

关键词： Error correction

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