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Security boundaries of an optical-power limiter for protecting quantum-key-distribution systems

Physical Review Applied 2024年第1期21卷 014026-014026页

作者： Qingquan Peng Binwu Gao Konstantin Zaitsev Dongyang Wang Jiangfang Ding Yingwen Liu Qin Liao Ying Guo Anqi Huang Junjie Wu Institute for Quantum Information and State Key Laboratory of High Performance Computing College of Computer Science and Technology National University of Defense Technology Changsha 410073 China School of Automation Central South University Changsha 410083 China China Greatwall Research Institute China Greatwall Technology Group Co. Ltd. Shenzhen 518057 China Russian Quantum Center Skolkovo Moscow 121205 Russia NTI Center for Quantum Communications National University of Science and Technology MISiS Moscow 119049 Russia Vigo Quantum Communication Center University of Vigo 36310 Vigo Spain Escuela de Ingeniería de Telecomunicación Department of Signal Theory and Communications University of Vigo 36310 Vigo Spain atlanTTic Research Center University of Vigo 36310 Vigo Spain College of Computer Science and Electronic Engineering Hunan University Changsha 410082 China School of Computer Science Beijing University of Posts and Telecommunications Beijing 100876 China

Unauthorized light injection has always been a vital threat to the practical security of a quantum-key-distribution (QKD) system. An optical-power limiter (OPL) based on the thermo-optical defocusing effect has been proposed and implemented, limiting the injected hacking light. As a hardware countermeasure, the performance of the OPL under various light-injection attacks will be tested to clarify the security boundary before it is widely deployed. To investigate the security boundary of the OPL in quantum cryptography, we comprehensively test and analyze the behavior of the OPL under continuous-wave (cw) light-injection attacks and pulse-illumination attacks with pulse repetition rates of 0.5 Hz, 40 MHz, and 1 GHz. The test results illuminate the security boundary of the OPL, which allows one to properly employ the OPL in use cases. The methodology of testing and analysis proposed here is applicable to other power-limitation components in a QKD system.

关键词： Optical quantum information processing Photonics Quantum communication Quantum cryptography Devices

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3D Face Reconstruction System From A Single Photo Based On Regression Neural Network

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IFAC-PapersOnLine 2020年第5期53卷 71-76页

作者： Yatai Ji Keqiang Li Huaiyu Wu Gang Xiong Zhen Shen Xiuqin Shang Bangwen Xi The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China Department of Automation Tsinghua University Beijing 100084 China University of Chinese Academy of Sciences Beijing 100049 China The Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Donggguan 523808 China The Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing 100190 China

3D human face modeling is one of the most popular research directions in the field of computer stereo vision. On the one hand, the complex physiological structure of human face as well as various expressions and attitude changes bring great challenges to three-dimensional modeling, which makes the modeling method of human face have high research value and reference significance. On the other hand, 3D face reconstruction has a broad application prospect, and the application demand attracts more researchers to invest in it. Based on the 3DMM and 3DDFA method, this paper utilizes regression neural network to realize end-to-end face reconstruction. After that, we build a visualization program with the training model to realize face modeling based on a single face image of any pose or expression. It’s a 3D face reconstruction system which has functions such as face alignment, face rotation and so on.

关键词： face reconstruct 3DMM 3DDFA regression network

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Future Networks 2030: Challenges in Intelligent Transportation Systems

Future Networks 2030: Challenges in Intelligent Transportati...

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International Conference on Reliability, Infocom Technologies and Optimization (ICRITO) (Trends and Future Directions)

作者： Mădălin-Dorin Pop Jitendra Pandey Velmani Ramasamy Automation and Applied Informatics University of Timișoara Timișoara România Department of Computing Middle East College Muscat Sultanate of Oman Department of Electronics and Communication Engineering Siddhartha Institute of Technology and Sciences Narapally Hyderabad India

ISBN: (数字)9781728170169

ISBN: (纸本)9781728170176

Many cities around the world implement the Intelligent Transportation Systems (ITS) concept to reduce road traffic congestion. This concept implies the usage of Internet of Things (IoT) technologies to ensure a better traffic flow, especially in crowded urban areas. Sensors networks became part of road infrastructure and have as main responsibilities to collect real-time traffic data and to send them to Traffic Management Centres (TMCs) which control further the traffic lights timings. Today's technologies meet some limitations in terms of efficiency. This paper starts with an overview of these limitations to create a path for discussing the challenges that the development of ITS will meet in the context of Future Networks (FN) 2030 concept. Based on this development path, the identification of current limitations and possible future challenges consists of an important step of this research. Further, the main contribution in this research is to show how the ITS shall adapt to meet the requirements of FN 2030 by providing an architecture for Future ITS 2030 that meets the general ITS needs.

关键词： Security Roads Sensors Computer architecture Real-time systems Smart cities Wireless communication

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Review of large vision models and visual prompt engineering

Meta-Radiology

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Meta-Radiology 2023年第3期1卷

作者： Wang, Jiaqi Liu, Zhengliang Zhao, Lin Wu, Zihao Ma, Chong Yu, Sigang Dai, Haixing Yang, Qiushi Liu, Yiheng Zhang, Songyao Shi, Enze Pan, Yi Zhang, Tuo Zhu, Dajiang Li, Xiang Jiang, Xi Ge, Bao Yuan, Yixuan Shen, Dinggang Liu, Tianming Zhang, Shu School of Computer Science Northwestern Polytechnical University Xi'an 710072 China School of Computing the University of Georgia Athens 30602 United States School of Automation Northwestern Polytechnical University Xi'an 710072 China School of Physics and Information Technology Shaanxi Normal University Xi'an 710119 China School of Biomedical Engineering ShanghaiTech University Shanghai 201210 China Shanghai Unite Imaging Intelligence Co.Ltd Shanghai 200230 China Shanghai Clinical Research and Trial Center Shanghai 20121 China Department of Electronic Engineering Chinese University of Hong Kong Hong Kong 999077 China Department of Electronic Engineering City University of Hong Kong Hong Kong 999077 China School of Life Science and Technology University of Electronic Science and Technology of China Chengdu 611731 China Glasgow College University of Electronic Science and Technology of China Chengdu 611731 China Department of Computer Science and Engineering the University of Texas at Arlington Arlington 76019 United States Department of Radiology Massachusetts General Hospital and Harvard Medical School Boston 02115 United States

Visual prompt engineering is a fundamental methodology in the field of visual and image artificial general intelligence. As the development of large vision models progresses, the importance of prompt engineering becomes increasingly evident. Designing suitable prompts for specific visual tasks has emerged as a meaningful research direction. This review aims to summarize the methods employed in the computer vision domain for large vision models and visual prompt engineering, exploring the latest advancements in visual prompt engineering. We present influential large models in the visual domain and a range of prompt engineering methods employed on these models. It is our hope that this review provides a comprehensive and systematic description of prompt engineering methods based on large visual models, offering valuable insights for future researchers in their exploration of this field. © 2023 The Authors

关键词： Artificial general intelligence Vision models Visual prompt

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Hyperchaos on the dynamics of memristive Tabu learning neuron model under influence of electromagnetic radiation: Application in biomedical data privacy

Franklin Open

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Franklin Open 2025年 10卷

作者： Boya, Bertrand Frederick Boui A Kengne, Jacques Nanfak, Arnaud Muni, Sishu Shankar Nkapkop, Jean de Dieu Kenmoe, Germaine Djuidje Babenko, Lyudmila Klimentyevna Unité de Recherche d'Automatique et d'Informatique Appliquée (UR-AIA) IUT-FV Bandjoun University of Dschang Bandjoun P.O. Box 134 Cameroon Laboratory of Energy-Electric and Electronic Systems Department of Physics Faculty of Science University of Yaoundé I Yaoundé P.O. Box 812 Cameroon Department of Physics Faculty of Science University of Yaoundé 1 Yaoundé Cameroon Institute of Computer Technology and Information Security Southern Federal University P.O. Box 347922 Taganrog Russian Federation Laboratory for electronics electrical engineering automation and telecommunications National Higher Polytechnic School of Douala University of Douala Douala PO Box 2701 Cameroon School of Digital Sciences Digital University Kerala Technocity campus Kerala Mangalapuram India Indian Institute of Information Technology and Management Kerala Technopark road Kerala India Department of Electrical Engineering and Industrial Computing University Institute of Technology Douala P.O. Box 8698 Cameroon

This paper presents a novel biological neural networks based on memristive Tabu learning neuron (MTLN) model influenced by electromagnetic radiation. Despite the model having an unstable equilibrium plane, numerical investigation without the influence of electromagnetic radiation reveal that when increasing the memristor strength induces complex phenomena, including the coexistence of infinite bubbles of bifurcations, offset plane coexistence of various attractors. Furthermore, electromagnetic radiation can significantly impact the system's behavior, giving rise to hyperchaotic dynamics. A decent understanding is seen between the mathematical outcomes, approved through trial execution on an Arduino microcontroller-based. The insights gained from neural dynamics could pave the way for applications in neuromorphic computing, engineering, and brain-machine interfaces. Based on the complex dynamics of the model, a data privacy of biomedical data has been build and reveals good results, and enable to resist to robust attacks. © 2024 The Author(s)

关键词： Data privacy Electromagnetic radiation Hyperchaos Microcontroller design MTLN model Offset plane coexisting behaviors

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A Data-driven Approach to Solve a Production Constrained Build-order Optimization Problem

A Data-driven Approach to Solve a Production Constrained Bui...

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第三十八届中国控制会议

作者： Pengpeng Wang Yifeng Zeng Bilian Chen Langcai Cao Department of Automation School of Aerospace Engineering Xiamen University School of Computing Teesside University

Production constrained build-order optimization problems challenge artificial intelligence research in computer game applications due to an uncertain set of constraints. Traditional approaches provide subjective values in the constraint formulation therefore resulting in unexpected performance of the optimal build-order in a game. In this article, we propose a data-driven approach to solve a build-order optimization problem in StarCraft. We formulate the constraint by learning the parameter values from game replay data, which complements more precise problem formulation. To solve the optimization, we use the improved genetic algorithm by learning initial solutions from the data. We show the performance of the data-driven methods in a StarCraft simulation platform.

关键词： Build-order Data-Driven Optimization StarCraft Improved Genetic Algorithm

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Robust multi-objective control for vehicle active suspension systems with structured uncertainties

Robust multi-objective control for vehicle active suspension...

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第三十九届中国控制会议

作者： Zhong Cao Sheng-Guo Wang Zhaohui Chen Xiaorong Hou Wenjing Zhao School of Physics and Electronic Engineering Guangzhou University College of Engineering and College of Computing Informatics University of North Carolina at Charlotte Department of Mathematics and Physics Chongqing University of Science and Technology School of Automation Engineering University of Electronic Science and Technology of China Lab Center Guangzhou University

A robust structural control method is proposed to solve the problems of structured uncertainties and multi-objective control for vehicle active suspension systems. The considered model is a quarter model of vehicle subject to unknown ground disturbance and structured uncertainties. The proposed method is based on robust structured control well supported by singular value decomposition(SVD) method, yielding a multi-objective control design approach, applicable to almost any active suspension systems. Some experiments show that the control performance of robust structural control for vehicle active suspension systems with structured uncertainties is significantly improved comparing with passive controlled system and existing other controlled active suspension systems.

关键词： Active suspension systems Robust structural control singular value decomposition structured uncertainties

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[email protected] , an ecosystem of virtual environments and tools for realistic indoor robotic simulation

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Expert Systems with Applications 2022年 208卷

作者： David Fernandez-Chaves Jose-Raul Ruiz-Sarmiento Alberto Jaenal Nicolai Petkov Javier Gonzalez-Jimenez Machine Perception and Intelligent Robotics group (MAPIR) Department of System Engineering and Automation Biomedical Research Institute of Malaga (IBIMA) University of Malaga Spain Johann Bernoulli Institute of Mathematics and Computing Science University of Groningen The Netherlands

Simulations and synthetic datasets have historically empower the research in different service robotics-related problems, being revamped nowadays with the utilization of rich virtual environments. However, with their use, special attention must be paid so the resulting algorithms are not biased by the synthetic data and can generalize to real world conditions. These aspects are usually compromised when the virtual environments are manually designed. This article presents [email protected] , an ecosystem of virtual environments and tools that allows for the management of realistic virtual environments where robotic simulations can be performed. Here “realistic” means that those environments have been designed by mimicking the rooms’ layout and objects appearing in 30 real houses, hence not being influenced by the designer’s knowledge. The provided virtual environments are highly customizable (lighting conditions, textures, objects’ models, etc.), accommodate meta-information about the elements appearing therein (objects’ types, room categories and layouts, etc.), and support the inclusion of virtual service robots and sensors. To illustrate the possibilities of [email protected] we show how it has been used to collect a synthetic dataset, and also exemplify how to exploit it to successfully face two service robotics-related problems: semantic mapping and appearance-based localization.

关键词： Virtual environments Robotic simulation Service robots Semantic maps Robotic dataset Unity

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Learning-Based Predictive Control via Real-Time Aggregate Flexibility

arXiv

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arXiv 2020年

作者： Li, Tongxin Sun, Bo Chen, Yue Ye, Zixin Low, Steven H. Wierman, Adam The Computing + Mathematical Sciences Department California Institute of Technology PasadenaCA91125 United States The Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong The Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong The Electrical Engineering Department California Institute of Technology PasadenaCA91125 United States

Aggregators have emerged as crucial tools for the coordination of distributed, controllable loads. To be used effectively, an aggregator must be able to communicate the available flexibility of the loads they control, as known as the aggregate flexibility to a system operator. However, most of existing aggregate flexibility measures often are slow-timescale estimations and much less attention has been paid to real-time coordination between an aggregator and an operator. In this paper, we consider solving an online optimization in a closed-loop system and present a design of real-time aggregate flexibility feedback, termed the maximum entropy feedback (MEF). In addition to deriving analytic properties of the MEF, combining learning and control, we show that it can be approximated using reinforcement learning and used as a penalty term in a novel control algorithm - the penalized predictive control (PPC), which modifies vanilla model predictive control (MPC). The benefits of our scheme are (1). Efficient Communication. An operator running PPC does not need to know the exact states and constraints of the loads, but only the MEF. (2). Fast Computation. The PPC often has much less number of variables than an MPC formulation. (3). Lower Costs. We show that under certain regularity assumptions, the PPC is optimal. We illustrate the efficacy of the PPC using a dataset from an adaptive electric vehicle charging network and show that PPC outperforms classical MPC. © 2020, CC BY.

关键词： Reinforcement learning

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The design of a quasi-time optimal cascade controller for ball and beam system

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IOP Conference Series: Materials Science and engineering 2021年第1期1029卷

作者： C X Nguyen H Ng Phan L D Hoang H Ng Tran Department of Automation and Computing Techniques Le Quy Don Technical University Vietnam Department of Software Engineering Le Quy Don Technical University Hanoi Vietnam

In this paper, a methodology for designing quasi-time optimal cascade controller for ball and beam system is presented and the result is compared with LQR method as well as implemented on real system. Ball and beam system is a highly non-linear system, its parameters are difficult to estimate accurately and easily affect by disturbance. In designed method, a mathematical model describing the system is built, including a motor that creates a rotation of beam and is divided into two subsystems when synthesizing the cascade controller for the system. The first floor is the beam subsystem with the output is the angle as the set value for the second floor, which is ball subsystem. The controller is synthesized for each subsystem based on the quasi-time optimal control. The advantage of this method is the synthesizing control law with non-linear system. The simulation results show the effectiveness of the proposed design.

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