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Multibit quantum digital signature with continuous variables using basis encoding over insecure channels

Physical Review A 2021年第1期103卷 012410-012410页

作者： Wei Zhao Ronghua Shi Jinjing Shi Peng Huang Ying Guo Duan Huang School of Computer Science and Engineering Central South University Changsha 410083 China State Key Laboratory of Advanced Optical Communication Systems and Networks Shanghai Key Laboratory on Navigation and Location-Based Service and Center of Quantum Information Sensing and Processing(QSIP) Shanghai Jiao Tong University Shanghai 200240 China School of Automation Central South University Changsha 410083 China

A quantum digital signature (QDS) is utilized to authenticate classical messages and offers information theoretical security guaranteed by the laws of quantum mechanics. Focusing on signing a one-bit message, previous continuous-variable quantum digital signature (CV-QDS) protocols that shared secret keys are generated by quantum key distribution, and it is only mentioned to suitably iterate the one-bit protocol for a multibit message. Although the CV-QDS protocol is unconditionally secure while sending single-bit messages, iterating the one-bit protocol in a naive way will allow some forgery attacks. In this paper, for signing one-bit and multibit messages, a CV-QDS protocol is proposed, on the condition that nonrepudiation and no forging are guaranteed. For one-bit and multibit schemes, we compare the difference in the distribution stage and messaging stage, analyzing the security as well as summarizing some formulas for calculation. We hope the protocol with continuous variables could further improve the performance of QDS.

关键词： Quantum cryptography

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Adaptive RBF-Neural-Network Control with Force Observer for Teleoperation Robotic System 1st

Adaptive RBF-Neural-Network Control with Force Observer for...

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1st International Conference on Cognitive Computation and systems, ICCCS 2022

作者： An, Zhaohui Min, Gaochen Jiang, Xiangzuo Yu, Xinbo He, Wei Silvestre, Carlos School of Intelligence Science and Technology Institute of Artificial Intelligence University of Science and Technology Beijing Beijing100083 China Beijing Advanced Innovation Center for Materials Genome Engineering University of Science and Technology Beijing Beijing100083 China Key Laboratory of Intelligent Bionic Unmanned Systems Ministry of Education University of Science and Technology Beijing Beijing100083 China Donald Bren School of Information and Computer Sciences University of California IrvineCA92697 United States Department of Electrical and Computer Engineering Faculty of Science and Technology University of Macau China LARSyS Instituto Superior Técnico Universidade de Lisboa Lisbon Portugal

ISBN: (纸本)9789819927883

In this paper, an adaptive radial basis function neural network (RBFNN) control strategy is proposed for bilateral teleoperation robotic system with uncertainty and time delay. Meantime, the force observer method is used to estimate the interaction force between the slave robot and environment. The model of teleoperation robotic system is analyzed, and then the uncertainty of bilateral teleoperation robotic system is estimated by using RBFNN. Using Lyapunov stability theorem, the stability of teleoperation robotic system under our proposed control is proved. Finally, the effectiveness of the proposed control algorithm is verified by Matlab Simulink, and position tracking and force estimation performance of the teleoperation robotic system are guaranteed. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Time delay

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$H_{\infty }$ PID Control for Discrete-Time Fuzzy systems With Infinite-Distributed Delays Under Round-Robin Communication Protocol

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IEEE Transactions on Fuzzy systems 2021年第6期30卷 1875-1888页

作者： Yezheng Wang Zidong Wang Lei Zou Hongli Dong College of Electrical Engineering and Automation Shandong University of Science and Technology Qingdao China Department of Computer Science Brunel University London Uxbridge U.K. Institute of Complex Systems and Advanced Control and the Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control Northeast Petroleum University Daqing China

This article is concerned with the $H_{\infty }$ proportional–integral–derivative (PID) control problem for class of discrete-time Takagi–Sugeno fuzzy systems subject to infinite-distributed time delays and round-robin (RR) protocol scheduling effects. The information exchange between the sensors and the controller is conducted through a shared communication network. For the purpose of alleviating possible data collision, the well-known RR communication protocol is deployed to schedule the data transmissions. To stabilize the target system with guaranteed $H_{\infty }$ performance index, a novel yet easy-to-implement fuzzy PID controller is developed whose integral term is calculated based on the past measurements defined in a limited time window with hope to improve computational efficiency and reduce accumulation error. Based on the Lyapunov stability theory and the convex optimization technique, sufficient conditions are derived to ensure the exponential stability as well as the $H_{\infty }$ disturbance attenuation/rejection capacity of the underlying system. Furthermore, by utilizing the cone complementarity linearization algorithm, the nonconvex controller design problem is transformed into an iterative optimization one that facilitates the controller implementation. Finally, simulation examples are given to show the effectiveness and correctness of the developed control method.

关键词： PD control Protocols PI control Control systems Symmetric matrices Communication networks Optimization

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NTIRE 2023 Quality Assessment of Video Enhancement Challenge

NTIRE 2023 Quality Assessment of Video Enhancement Challenge

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

作者： Liu, Xiaohong Min, Xiongkuo Sun, Wei Zhang, Yulun Zhang, Kai Timofte, Radu Zhai, Guangtao Gao, Yixuan Cao, Yuqin Kou, Tengchuan Dong, Yunlong Jia, Ziheng Li, Yilin Wu, Wei Hu, Shuming Deng, Sibin Xiao, Pengxiang Chen, Ying Li, Kai Zhao, Kai Yuan, Kun Sun, Ming Cong, Heng Wang, Hao Fu, Lingzhi Zhang, Yusheng Zhang, Rongyu Shi, Hang Xu, Qihang Xiao, Longan Ma, Zhiliang Agarla, Mirko Celona, Luigi Rota, Claudio Schettini, Raimondo Huang, Zhiwei Li, Ya'nan Wang, Xiaotao Lei, Lei Liu, Hongye Hong, Wei Chuang, Ironhead Lin, Allen Guan, Drake Chen, Iris Lou, Kae Huang, Willy Tasi, Yachun Kao, Yvonne Fan, Haotian Kong, Fangyuan Zhou, Shiqi Liu, Hao Lai, Yu Chen, Shanshan Wang, Wenqi Wu, Haoning Chen, Chaofeng Zhu, Chunzheng Guo, Zekun Zhao, Shiling Yin, Haibing Wang, Hongkui Meftah, Hanene Brachemi Fezza, Sid Ahmed Hamidouche, Wassim Déforges, Olivier Shi, Tengfei Mansouri, Azadeh Motamednia, Hossein Bakhtiari, Amir Hossein Aznaveh, Ahmad Mahmoudi Shanghai Jiao Tong University China Eth Zürich Switzerland University of Würzburg Germany Department of Tao Technology Alibaba Group China Kuaishou Technology China Interactive Entertainment Group of Netease Inc Guangzhou China Transsion China Hefei University of Technology China Department of Informatics Systems and Communication University of Milano - Bicocca Italy Xiaomi Inc. China China Ji Liang University China FreeTech Advanced Research Center KKCompany Taiwan ByteDance China Mgtv China Fuzhou University China Shopee Information Technology Co. Ltd. S-Lab Nanyang Technological University Singapore Hunan University China Hangzhou Dianzi University China Insa Rennes Cnrs Ietr - Umr 6164 Rennes France National Higher School of Telecommunications and Ict Oran Algeria Buaa Department of Electrical and Computer Engineering Faculty of Engineering Kharazmi University Tehran Iran High Performance Computing Laboratory School of Computer Science Institute for Research in Fundamental Sciences Tehran Iran Cyberspace Research Institute Shahid Beheshti University Tehran Iran

ISBN: (纸本)9798350302493

This paper reports on the NTIRE 2023 Quality Assessment of Video Enhancement Challenge, which will be held in conjunction with the New Trends in Image Restoration and Enhancement Workshop (NTIRE) at CVPR 2023. This challenge is to address a major challenge in the field of video processing, namely, video quality assessment (VQA) for enhanced videos. The challenge uses the VQA Dataset for Perceptual Video Enhancement (VDPVE), which has a total of 1211 enhanced videos, including 600 videos with color, brightness, and contrast enhancements, 310 videos with deblurring, and 301 deshaked videos. The challenge has a total of 167 registered participants. 61 participating teams submitted their prediction results during the development phase, with a total of 3168 submissions. A total of 176 submissions were submitted by 37 participating teams during the final testing phase. Finally, 19 participating teams submitted their models and fact sheets, and detailed the methods they used. Some methods have achieved better results than baseline methods, and the winning methods have demonstrated superior prediction performance. © 2023 IEEE.

关键词： Image enhancement

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High sensitivity interferometric fiber optic gyroscopes for 6-component seismograph 27

High sensitivity interferometric fiber optic gyroscopes for ...

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27th International Conference on Optical Fiber Sensors, OFS 2020

作者： Cao, Yuwen He, Dong Zhang, Dingfan Zhang, Wentao Li, Li Li, Zhengbin State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Engineering and Computer Science Peking University Beijing100871 China State Key Laboratory of Transducer Technology Institute of Semiconductors Chinese Academy of Sciences Beijing100083 China Institute of Geophysics China Earthquake Administration Beijing100081 China

The principle of dual polarized fiber optic gyroscope insensitive to the temperature and magnetic field variance is presented, and several novel experiments have been demonstrated, including earthquake detection, envi... 详细信息

ISBN: (纸本)9781557523075

关键词： Fiber optics

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Learning attributed graph representations with communicative message passing transformer

arXiv

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arXiv 2021年

作者： Chen, Jianwen Zheng, Shuangjia Song, Ying Rao, Jiahua Yang, Yuedong School of Computer Science and Engineering Sun Yat-sen University China School of Systems Science and Engineering Sun Yat-sen University China Key Laboratory of Machine Intelligence and Advanced Computing Sun Yat-sen University China Galixir Technologies Ltd Beijing China

Constructing appropriate representations of molecules lies at the core of numerous tasks such as material science, chemistry and drug designs. Recent researches abstract molecules as attributed graphs and employ graph neural networks (GNN) for molecular representation learning, which have made remarkable achievements in molecular graph modeling. Albeit powerful, current models either are based on local aggregation operations and thus miss higher-order graph properties or focus on only node information without fully using the edge information. For this sake, we propose a Communicative Message Passing Transformer (CoMPT) neural network to improve the molecular graph representation by reinforcing message interactions between nodes and edges based on the Transformer architecture. Unlike the previous transformer-style GNNs that treat molecules as fully connected graphs, we introduce a message diffusion mechanism to leverage the graph connectivity inductive bias and reduce the message enrichment explosion. Extensive experiments demonstrated that the proposed model obtained superior performances (around 4% on average) against state-of-the-art baselines on seven chemical property datasets (graph-level tasks) and two chemical shift datasets (node-level tasks). Further visualization studies also indicated a better representation capacity achieved by our model. Copyright © 2021, The Authors. All rights reserved.

关键词： Molecules

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Symbolic genetic algorithm for discovering open-form partial differential equations (SGA-PDE)

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Physical Review Research 2022年第2期4卷 023174-023174页

作者： Yuntian Chen Yingtao Luo Qiang Liu Hao Xu Dongxiao Zhang Eastern Institute for Advanced Study Yongriver Institute of Technology Ningbo Zhejiang 315201 People's Republic of China Department of Computer Science University of Washington Seattle Washington 98195 USA RealAI Beijing 100085 People's Republic of China Beijing Innovation Center for Engineering Science and Advanced Technology (BIC-ESAT) Energy and Resources Engineering (ERE) and State Key Laboratory for Turbulence and Complex Systems (SKLTCS) College of Engineering Peking University Beijing 100871 People's Republic of China National Center for Applied Mathematics Shenzhen (NCAMS) Southern University of Science and Technology Shenzhen Guangdong 518055 People's Republic of China Department of Mathematics and Theories Peng Cheng Laboratory Shenzhen Guangdong 518000 People's Republic of China

Partial differential equations (PDEs) are concise and understandable representations of domain knowledge, which are essential for deepening our understanding of physical processes and predicting future responses. However, the PDEs of many real-world problems are uncertain, which calls for PDE discovery. We propose the symbolic genetic algorithm to discover open-form PDEs (SGA-PDE) directly from data without prior knowledge about the equation structure. SGA-PDE focuses on the representation and optimization of PDEs. Firstly, SGA-PDE uses symbolic mathematics to realize the flexible representation of any given PDE, transforms a PDE into a forest, and converts each function term into a binary tree. Secondly, SGA-PDE adopts a specially designed genetic algorithm to efficiently optimize the binary trees by iteratively updating the tree topology and node attributes. The SGA-PDE is gradient free, which is a desirable characteristic in PDE discovery since it is difficult to obtain the gradient between the PDE loss and the PDE structure. In the experiment, SGA-PDE not only successfully discovered the nonlinear Burgers’ equation, the Korteweg–de Vries equation, and the Chafee-Infante equation but also handled PDEs with fractional structure and compound functions that cannot be solved by conventional PDE discovery methods.

关键词： Classical statistical mechanics Complex fluids Neuronal dynamics Shock waves Turbulence

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Anti-Collision System for Accident Prevention in Underground Mines using computer Vision 22

Anti-Collision System for Accident Prevention in Underground...

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Proceedings of the 6th International Conference on Advances in Artificial Intelligence

作者： Mohamed Imam Karim Baïna Youness Tabii Intissar Benzakour Youssef Adlaoui El Mostafa Ressami El Hassan Abdelwahed Alqualsadi Research Team Rabat IT Center ENSIAS Mohammed V University in Rabat ENSIAS Morocco and Digitalization & Microelectronic Smart Devices - MAScIR Moroccan Foundation for Advanced Science Innovation and Research (MAScIR) Morocco Alqualsadi Research Team Rabat IT Center ENSIAS Mohammed V University in Rabat ENSIAS Morocco Information Retrieval and Data Analytics (IRDA) Research Team Rabat IT Center ENSIAS ENSIAS Morocco Reminex Research and Engineering center MANAGEM Group REMINEX Morocco Digitalization & Microelectronic Smart Devices - MAScIR Moroccan Foundation for Advanced Science Innovation and Research (MAScIR) Morocco Laboratory of Computer Systems Engineering (LISI) FSSM Cadi Ayyad University FSSM Morocco

ISBN: (纸本)9781450396943

Underground prospecting operations are often characterized by critical safety issues mainly due to poor visibility and blind spots around large vehicles and equipment. This can result in vehicle-to-vehicle collisions, as well as vehicle-to-pedestrian or structural-element collisions, resulting in accidents. In this article, we discuss an anti-collision system for pedestrian identification in deep mines under the premise that we are looking to prevent collisions with moving machinery. This study presents the findings from testing an image processing module and sensory system based on deep learnig in the context of "smart connected mine" project.

关键词： Yolov5 Pedestrian detection Deep Learning Underground mining

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Application-level Benchmarking of Quantum computers using Nonlocal Game Strategies

arXiv

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arXiv 2023年

作者： Furches, Jim Chehade, Sarah Hamilton, Kathleen Wiebe, Nathan Marrero, Carlos Ortiz College of Computing Georgia Institute of Technology AtlantaGA30332 United States Physical Detection Systems and Deployment Division Pacific Northwest National Laboratory RichlandWA99354 United States Quantum Computational Science Group Oak Ridge National Laboratory Oak RidgeTN37830 United States Department of Computer Science University of Toronto ONM5S 1A1 Canada High Performance Computing Group Pacific Northwest National Laboratory RichlandWA99354 United States Canadian Institute for Advanced Research TorontoONM5G 1M1 Canada Department of Electrical & Computer Engineering North Carolina State University RaleighNC27607 United States

In a nonlocal game, two noncommunicating players cooperate to convince a referee that they possess a strategy that does not violate the rules of the game. Quantum strategies allow players to optimally win some games by performing joint measurements on a shared entangled state, but computing these strategies can be challenging. We present a variational quantum algorithm to compute quantum strategies for nonlocal games by encoding the rules of a nonlocal game into a Hamiltonian. We show how this algorithm can generate a short-depth optimal quantum strategy for a graph coloring game with a quantum advantage. This quantum strategy is then evaluated on fourteen different quantum hardware platforms to demonstrate its utility as a benchmark. Finally, we discuss potential sources of errors that can explain the observed decreased performance of the executed task and derive an expression for the number of samples required to accurately estimate the win rate in the presence of noise. Copyright © 2023, The Authors. All rights reserved.

关键词： Qubits

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A Spherical Harmonics-LSB-quantification Adaptive Watermarking Approach for 3D Multiresolution Meshes Security 19th

A Spherical Harmonics-LSB-quantification Adaptive Watermarki...

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19th International Conference on computer Analysis of Images and Patterns, CAIP 2021

作者： Sayahi, Ikbel Jallouli, Malika Mabrouk, Anouar Ben Amar, Chokri Ben Mahjoub, Mohamed Ali LATIS Laboratory of Advanced Technology and Intelligent Systems Université de Sousse Ecole Nationale d’Ingénieurs de Sousse Sousse4023 Tunisia University of SFax Research Groups on Intelligent Machines Laboratory Private National Engineering School of Monastir Monastir Tunisia Department of Mathematics Higher Institute of Applied Mathematics and Computer Science University of Kairouan Kairouan3100 Tunisia Department of Mathematics Faculty of Science University of Tabuk Tabuk Saudi Arabia College of Computers and Information Technology Taif University Taif Saudi Arabia

ISBN: (纸本)9783030891305

Since the release of the first 3D watermarking algorithm in the last decade, 3D meshes applying such an algorithm have been growing up with a diversity of techniques during the embedding of information into meshes. The main objective is always to secure data shared by remote users. The originality of the present work is issued from the use of spherical harmonics to transform the mesh to the frequency domain to be watermarked, and the entropy concept to estimate the optimal order of the reconstruction. Our algorithm includes three parts. The first is the data pre-processing based on a combination of a signature generated by the well-known Secure Hash Algorithm, and a mesh description, subject to a convolutional error correcting code. The second step is the mesh treatment, consisting in extracting spherical harmonics coefficients to be watermarked. Finally, the third part consists in inserting data into coefficients using LSB and quantification method, and next to reconstruct the watermarked mesh. The experimentation of our approach has shown a high insertion rate, while maintaining the mesh quality. It is also robust against the most popular attacks. Our results showed that the present approach improves the existing works. © 2021, Springer Nature Switzerland AG.

关键词： Entropy

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