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Rapid stabilization of stochastic quantum systems in a unified framework

Chinese Physics B 2023年第7期32卷 216-225页

作者：温杰王芳敏史元浩贾建芳曾建潮 School of Electrical and Control Engineering North University of ChinaTaiyuan 030051China State Key Laboratory of Precision Measurement Technology and Instruments Department of Precision InstrumentTsinghua UniversityBeijing 100084China School of Computer Science and Technology North University of ChinaTaiyuan 030051China

Rapid stabilization of general stochastic quantum systems is investigated based on the rapid stability of stochastic differential *** introduce a Lyapunov-LaSalle-like theorem for a class of nonlinear stochastic systems first,based on which a unified framework of rapidly stabilizing stochastic quantum systems is *** to the proposed unified framework,we design the switching state feedback controls to achieve the rapid stabilization of singlequbit systems,two-qubit systems,and N-qubit *** the unified framework,the state space is divided into two state subspaces,and the target state is located in one state subspace,while the other system equilibria are located in the other state *** the designed state feedback controls,the system state can only transit through the boundary between the two state subspaces no more than two times,and the target state is globally asymptotically stable in *** particular,the system state can converge exponentially in(all or part of)the state subspace where the target state is ***,the effectiveness and rapidity of the designed state feedback controls are shown in numerical simulations by stabilizing GHZ states for a three-qubit system.

关键词： rapid stabilization state feedback stochastic quantum systems switching control

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A Novel Self-Attentive Neural Network Hardware Accelerator for Edge Computing 4

A Novel Self-Attentive Neural Network Hardware Accelerator f...

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4th IEEE International Conference on Data science and computer Application, ICDSCA 2024

作者： He, Fangzhou Ding, Ke He, Xiao Chen, Mingzhe Mao, Kai Zhang, Qian State Key Laboratory of Intelligent Vehicle Safety Technology Chongqing China Chongqing University of Science and Technology Chongqing China Chongqing Changan Automobile Co. Ltd. Chongqing China School of Computer Science and Information Engineering Chongqing Technology and Business University Chongqing China School of Computer Science and Engineering Chongqing University of Science and Technology Chongqing China

ISBN: (纸本)9798350368239

High-precision floating-point self-attentive neural networks have high computational complexity and power consumption, posing significant challenges for deployment on edge devices. To tackle these problems, this paper propose a novel deep neural network hardware accelerator with unique vector tiling systolic array and vector ALU designs, where vector tiling systolic array is used to accelerate matrix multiplications, and vector ALU is used to process non-linear operations. By utilizing a systolic array with a systolic pipeline data path, matrix multiplication is accelerated. The vector tiling mechanism ensures that output results are immediately fed back into the arrays for further accumulation, without additional memory access or data loading delays. This approach significantly reduces arithmetic cycle overhead. Extensive experiments show that our method achieve 70×, 160×, 6× and 9× increase on peak energy efficiency ratio from Intel i3-2320 CPU, Intel i5-9400 CPU, RTX 2060 GPU and RTX 3060 GPU, respectively. The peak arthmetic of hardware accelerator is 2.41 TOPs in 8-bit fixed-point computation. ©2024 IEEE.

关键词： Vectors

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Dynamic Handwriting Recognition of Chinese Characters Based on Pressure Sensor Array 7

Dynamic Handwriting Recognition of Chinese Characters Based ...

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7th IEEE Advanced Information technology, Electronic and Automation Control Conference, IAEAC 2024

作者： Kong, Yongkang Meng, Wujun Cheng, Guanyin Zhao, Fubang Yang, Fuping Wei, Dapeng Chongqing University of Posts and Telecommunications School of Computer Science and Technology Chongqing China Chongqing Institute of Green and Intelligent Technology Chinese Academy of Sciences Chongqing China State Key Laboratory of Trauma and Chemical Poisoning Chongqing China

ISBN: (纸本)9798350339161

Biometrics have natural uniqueness and reliability, among which handwriting is widely used for personal identification due to its non-invasive and easy-to-capture characteristics. The intricate nature of Chinese characters, a pivotal communication medium for the Chinese, presents significant recognition challenges. Predominantly, existing methods in Chinese character and handwriting recognition rely on static binarized images for identification and authentication, often overlooking individual differences in stroke order and pressure. This research proposes a novel approach for simultaneous recognition of handwritten Chinese characters and handwriting via an array of pressure sensors, which are capable of discerning variations in stroke pressure among different individuals. Moreover, a 3D convolutional neural network with multi-scale residual combined with attentional mechanism (MSR-A-Net) was designed by dynamically capturing time-series pressure data to capture the stroke order of writing. The approach achieved a 97.25% accuracy rate on a custom-compiled dataset featuring ten Chinese characters and four distinct handwriting styles. These results show the potential in the application on Biosecurity detection and human-computer interaction. © 2024 IEEE.

关键词： Time series

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Model Checking for Probabilistic Multiagent systems

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Journal of computer science & technology 2023年第5期38卷 1162-1186页

作者：付辰 Andrea Turrini 黄小炜宋磊冯元张立军 State Key Laboratory of Computer Science Institute of SoftwareChinese Academy of SciencesBeijing 100190China University of Chinese Academy of Sciences Beijing 100049China Institute of Intelligent Software Guangzhou 511455China Department of Computer Science University of LiverpoolLiverpool L693BXU.K Microsoft Research Beijing 100190China Centre for Quantum Software and Information University of Technology SydneySydney 2007Australia

In multiagent systems,agents usually do not have complete information of the whole system,which makes the analysis of such systems *** incompleteness of information is normally modelled by means of accessibility relations,and the schedulers consistent with such relations are called *** this paper,we consider probabilistic multiagent systems with accessibility relations and focus on the model checking problem with respect to the probabilistic epistemic temporal logic,which can specify both temporal and epistemic ***,the problem is undecidable in *** show that it becomes decidable when restricted to memoryless uniform ***,we present two algorithms for this case:one reduces the model checking problem into a mixed integer non-linear programming(MINLP)problem,which can then be solved by Satisfiability Modulo Theories(SMT)solvers,and the other is an approximate algorithm based on the upper confidence bounds applied to trees(UCT)algorithm,which can return a result whenever *** algorithms have been implemented in an existing model checker and then validated on *** experimental results show the efficiency and extendability of these algorithms,and the algorithm based on UCT outperforms the one based on MINLP in most cases.

关键词： probabilistic multiagent system model checking uniform scheduler probabilistic epistemic temporal logic

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An Optimal Control Based Trajectory Planning Method for Cooperative Merging Maneuvers 3

An Optimal Control Based Trajectory Planning Method for Coop...

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3rd International Symposium on intelligent Robotics and systems, ISoIRS 2023

作者： Wang, Qi Ge, Hao Duan, Xuting Zhou, Jianshan School of Transportation Science and Engineering Beihang University State Key Lab of Intelligent Transportation System Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control State Key Laboratory of Air Traffic Management System and Technology Beijing China Nanjing Research Institute of Electronic Engineering State Key Laboratory of Air Traffic Management System and Technology Nanjing China School of Transportation Science and Engineering Beihang University State Key Lab of Intelligent Transportation System Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control Beijing China

ISBN: (纸本)9798350339963

Due to the prediction errors and diverse driving styles of surrounding vehicles, traffic congestion and even accidents can occur in the traffic bottleneck area where vehicles merge into the main road. To ensure that connected and automated vehicles (CAVs) can quickly and efficiently merge into the main road, this paper proposes a cooperative trajectory planning method based on optimal control for vehicle cut-in scenarios. A optimal control model is constructed, and a quintic polynomial is used to generate the initial solution of the optimal control problem to accelerate the solution process and improve the success rate. Finally, The obtained merging trajectory is then synchronized with the movement of vehicles on the main road to optimize their actions and ensure a safe merging process. Joint simulation with Robot Operating System (ROS) and RVIZ is utilized, and the results show that the proposed algorithm can quickly obtain cooperative results, the locally successful merging trajectory meets the requirements of smoothness and safety, and if the solution does not allow merging, the merging vehicle is instructed to terminate the execution. © 2023 IEEE.

关键词： Trajectories

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Can Digital Intelligence and Cyber-Physical-Social systems Achieve Global Food Security and Sustainability?

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IEEE/CAA Journal of Automatica Sinica 2023年第11期10卷 2070-2080页

作者： Yanfen Wang Mengzhen Kang Yali Liu Juanjuan Li Kai Xue Xiujuan Wang Jianqing Du Yonglin Tian Qinghua Ni Fei-Yue Wang College of Resources and Environment University of Chinese Academy of SciencesBeijing 100049 Beijing Yanshan Earth Critical Zone National Research Station University of Chinese Academy of SciencesBeijing 101408 State Key Laboratory of Tibetan Plateau Earth System Environment and ResourcesInstitute of Tibetan Plateau ResearchChinese Academy of SciencesBeijing 100101China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of Sciences(CASIA)Beijing 100190 School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China School of Grassland Science Beijing Forestry UniversityBeijing 100083China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China State Key Laboratory of Plateau Ecology and Agriculture Qinghai UniversityXining 810016 Key Laboratory of Adaptation and Evolution of Plateau Biota Northwest Institute of Plateau BiologyChinese Academy of SciencesXining 810001 Binzhou Institute of Technology Weiqiao-UCAS Science and Technology ParkBinzhou 256606China Beijing Yanshan Earth Critical Zone National Research Station University of Chinese Academy of SciencesBeijing 101408China Department of Engineering Science Faculty of Innovation EngineeringMacao University of Science and TechnologyMacao 999078 State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of Sciences(CASIA)Beijing 100190China Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078 Beijing Engineering Research Center of Intelligent Systems and Technology Chinese Academy of SciencesBeijing 100098 State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190China IEEE

Plants sequester carbon through photosynthesis and provide primary productivity for the ecosystem. However, they also simultaneously consume water through transpiration, leading to a carbon-water balance relationship. Agricultural production can be regarded as a form of carbon sequestration *** the perspective of the natural-social-economic complex ecosystem, excessive water usage in food production will aggravate regional water pressure for both domestic and industrial purposes. Hence, achieving a harmonious equilibrium between carbon and water resources during the food production process is a key scientific challenge for ensuring food security and sustainability. Digital intelligence(DI) and cyber-physical-social systems(CPSS) are emerging as the new research paradigms that are causing a substantial shift in the conventional thinking and methodologies across various scientific fields, including ecological science and sustainability studies. This paper outlines our recent efforts in using advanced technologies such as big data, artificial intelligence(AI), digital twins, metaverses, and parallel intelligence to model, analyze, and manage the intricate dynamics and equilibrium among plants, carbon, and water in arid and semiarid ecosystems. It introduces the concept of the carbon-water balance and explores its management at three levels: the individual plant level, the community level, and the natural-social-economic complex ecosystem level. Additionally, we elucidate the significance of agricultural foundation models as fundamental technologies within this context. A case analysis of water usage shows that, given the limited availability of water resources in the context of the carbon-water balance, regional collaboration and optimized allocation have the potential to enhance the utilization efficiency of water resources in the river basin. A suggested approach is to consider the river basin as a unified entity and coordinate the relationship between the

关键词： Carbon-water balance decision-support digital intelligence(DI) foundation models planning

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BinaryAI: Binary Software Composition Analysis via intelligent Binary Source Code Matching 24

BinaryAI: Binary Software Composition Analysis via Intellige...

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44th ACM/IEEE International Conference on Software Engineering, ICSE 2024

作者： Jiang, Ling An, Junwen Huang, Huihui Tang, Qiyi Nie, Sen Wu, Shi Zhang, Yuqun Southern University of Science and Technology Shenzhen China Tencent Security Keen Lab Shanghai China Research Institute of Trustworthy Autonomous Systems Southern University of Science and Technology Shenzhen China Southern University of Science and Technol-ogy Department of Computer Science and Engineering Shenzhen China Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation China

ISBN: (纸本)9798400702174

While third-party libraries (TPLs) are extensively reused to enhance productivity during software development, they can also introduce potential security risks such as vulnerability propagation. Software composition analysis (SCA), proposed to identify reused TPLs for reducing such risks, has become an essential procedure within modern DevSecOps. As one of the mainstream SCA techniques, binary-to-source SCA identifies the third-party source projects contained in binary files via binary source code matching, which is a major challenge in reverse engineering since binary and source code exhibit substantial disparities after compilation. The existing binary-to-source SCA techniques leverage basic syntactic features that suffer from redundancy and lack robustness in the large-scale TPL dataset, leading to inevitable false positives and compromised recall. To mitigate these limitations, we introduce BinaryAI, a novel binary-to-source SCA technique with two-phase binary source code matching to capture both syntactic and semantic code features. First, BinaryAI trains a transformer-based model to produce function-level embeddings and obtain similar source functions for each binary function accordingly. Then by applying the link-time locality to facilitate function matching, BinaryAI detects the reused TPLs based on the ratio of matched source functions. Our experimental results demonstrate the superior performance of BinaryAI in terms of binary source code matching and the downstream SCA task. Specifically, our embedding model outperforms the state-of-the-art model CodeCMR, i.e., achieving 22.54% recall@l and 0.34 MRR compared with 10.75% and 0.17 respectively. Additionally, BinaryAI outperforms all existing binary-to-source SCA tools in TPL detection, increasing the precision from 73.36% to 85.84% and recall from 59.81% to 64.98% compared with the well-recognized commercial SCA product Black Duck. E-https://*** © 2024 ACM.

关键词： Syntactics

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Traffic wave transition for a new macro traffic model considering the second-order density change rate

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Chinese Journal of Physics 2025年 96卷 201-218页

作者： Zhang, Geng Ren, Yue Guo, Hai-Yan Yang, Liang-Yi College of Computer and Information Science Southwest University Chongqing 400715 China State Key Laboratory of Intelligent Vehicle Safety Technology Chongqing 401122 China China Automotive Engineering Research Institute Co. Ltd. Chongqing 401122 China

With the development of intelligent transportation systems, more and detailed traffic information could be gathered for traffic optimization and control. To reveal the impact of the second-order density change rate on traffic stability and traffic wave transition, a new macro traffic model, based on lattice hydrodynamic model and represented by a system of ordinary differential equations (ODEs) is proposed. Firstly, the proposed model is analyzed through linear stability analysis and the linear stability condition is derived. Then, the traffic wave features in the stable and unstable region are explored via nonlinear analysis by reductive perturbation method. The results show that the density wave in the stable region is consistent with the triangular shock wave of the Burgers equation and the density wave in the unstable region is in agreement with the kink-antikink solution of modified Korteweg-de Vries (mKdV) equation. Finally, the traffic feature of the model is exhibited through simulation and the density waves in the stable and unstable region are in accordance with the theoretical analyses. More specially, it is revealed that the second-order density change rate has little effect on traffic stability. This result is quite different from the impact of density information or the first-order density change rate information on traffic stability. It is of great significance for information screening in intelligent transportation systems. © 2025 The Physical Society of the Republic of China (Taiwan)

关键词： Density wave Second-order density change rate Traffic modeling Traffic stability

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RAT: A Refactoring-Aware Tool for Tracking Code History 24

RAT: A Refactoring-Aware Tool for Tracking Code History

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46th International Conference on Software Engineering: Companion, ICSE-Companion 2024

作者： Niu, Feifei Shao, Junqian Xu, Chaofan Mayr-Dorn, Christoph Assunção, Wesley K. G. Huang, Liguo Li, Chuanyi Ge, Jidong Luo, Bin Egyed, Alexander State Key Laboratory for Novel Software Technology Nanjing University Nanjing China Institute for Software Systems Engineering Johannes Kepler University Linz Austria Department of Computer Science North Carolina State University North Carolina United States Department of Computer Science and Engineering Southern Methodist University DallasTX United States

ISBN: (纸本)9798400705021

History of code elements is essential for software maintenance tasks. However, code refactoring is one of the main causes that makes obtaining a consistent view on code evolution difficult as renaming or moving source code elements break such history. To this end, this paper presents RAT, a refactoring-aware tool for keeping track of code elements evolution across time, not just in terms of revisions but also in terms of refactoring. This is the first tool that enables fine-grained code element traceability of the whole repository. Empirical evaluation of leveraging our tool in three bug localization techniques relying on code history shows significant improvement in localization accuracy. Based on our findings, we believe that many of the state-of-the-art approaches using past source code data would benefit from our tool. Demo Tool: https://***/feifeiniu-se/RAT-Demo. Demo Video: https://***/VI-xwUaIPp4. © 2024 IEEE computer Society. All rights reserved.

关键词： Rats

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Future Healthcare Recommender systems: Applications, Open Issues, and Challenges

Future Healthcare Recommender Systems: Applications, Open Is...

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2024 IEEE International Conference on E-Health Networking, Application and Services, HealthCom 2024

作者： Ju, Hongzheng Jin, Kebing Tang, Jianhang Zhang, Yang Wang, Bo Xiong, Zehui State Key Laboratory of Public Big Data Guizhou University China College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics China Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore

ISBN: (纸本)9798350350548

With the enhancement of health awareness and the development of artificial intelligent technology, healthcare recommender systems (HRS) play an increasingly important role in individual health management. Meanwhile, the widespread usage of large models has significantly improved the efficiency and accuracy in the analysis and utilization of medical data. In this paper, we comprehensively summarize the basic types of recommender systems as well as the new trends in utilizing large models. Then we introduce the recommendation applications in healthcare areas from six aspects, i.e., disease risk prediction, medication recommendation, medical resource recommendation, mental health support, health life management, and health education. At last, we explore some current issues and challenges within HRS, as well as the development of potential solutions and directions in the future. © 2024 IEEE.

关键词： Electronic health record

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