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A self-supervised mixed-curvature graph neural network

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arXiv 2021年

作者： Sun, Li Zhang, Zhongbao Ye, Junda Peng, Hao Zhang, Jiawei Su, Sen Yu, Philip S. School of Control and Computer Engineering North China Electric Power University Beijing102206 China School of Computer Science Beijing University of Posts and Telecommunications China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100191 China Ifm Lab Department of Computer Science University of California DavisCA United States Department of Computer Science University of Illinois at Chicago IL United States

Graph representation learning received increasing attentions in recent years. Most of the existing methods ignore the complexity of the graph structures and restrict graphs in a single constant-curvature representation space, which is only suitable to particular kinds of graph structure indeed. Additionally, these methods follow the supervised or semisupervised learning paradigm, and thereby notably limit their deployment on the unlabeled graphs in real applications. To address these aforementioned limitations, we take the first attempt to study the self-supervised graph representation learning in the mixed-curvature spaces. In this paper, we present a novel Self-supervised Mixed-curvature Graph Neural Network (SELFMGNN). To capture the complex graph structures, we construct a mixed-curvature space via the Cartesian product of multiple Riemannian component spaces, and design hierarchical attention mechanisms for learning and fusing graph representations across these component spaces. To enable the self-supervisd learning, we propose a novel dual contrastive approach. The constructed mixed-curvature space actually provides multiple Riemannian views for the contrastive learning. We introduce a Riemannian projector to reveal these views, and utilize a welldesigned Riemannian discriminator for the single-view and cross-view contrastive learning within and across the Riemannian views. Finally, extensive experiments show that SELFMGNN captures the complex graph structures and outperforms state-of-the-art baselines. © 2021, CC BY-NC-SA.

关键词： Graph neural networks

Time-varying formation tracking control for UAV-UGV heterogeneous swarm systems with switching directed topologies

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Time-varying formation tracking control for UAV-UGV heteroge...

International Conference on control and Automation (ICCA)

作者： Siquan Zhou Xiwang Dong Qingdong Li Zhang Ren School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beihang University Beijing P.R. China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing P.R. China

ISBN: (数字)9781728190938

ISBN: (纸本)9781728190945

This paper studies time-varying formation tracking control problems for UAV-UGV heterogeneous swarm systems. The UAVs and UGVs need to achieve the desired time-varying formation and track the reference trajectory of a leader synchronously under switching directed topologies. Firstly, the cooperative control model for UAV-UGV heterogeneous swarm system is established by using algebraic graph theory. Then, the formation tracking control protocol based on a distributed observer is designed and the convergence is proved by using piecewise Lyapunov theory. Furthermore, the feasible conditions to achieve the time-varying formation tracking are analyzed, and the algorithm to select the control parameters is proposed. Finally, a numerical simulation example is provided to demonstrate the effectiveness of the proposed control approach.

关键词： Topology Switches Time-varying systems Observers Radar tracking Manganese control systems

Finite-Time Time-Varying Group Formation Tracking for High-Order Multi-Agent Systems with Mismatched Disturbances under Directed Graphs

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Finite-Time Time-Varying Group Formation Tracking for High-O...

International Conference on control and Automation (ICCA)

作者： Lei Tian Yongzhao Hua Xiwang Dong Qingdong Li Zhang Ren School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beihang University Beijing P.R. China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing P.R. China

ISBN: (数字)9781728190938

ISBN: (纸本)9781728190945

Finite-time time-varying group formation (FT-TVGF) tracking control problems for high-order multi-agent systems (MASs) are studied in this paper. Different from previous work, the approaches proposed in this paper combine group formation tracking control with finite-time control, not only that, the agents in each group can achieve time-varying sub-formations and the relative configuration between different groups can be adjusted simultaneously. First, all agents are divided into three types, including the virtual leader, the group leader, and the follower. The virtual leader is added to plan the trajectory of MASs. Subgroups can be interacted with each other by the communication among group leaders. Followers achieve the finite-time formation tracking of group leaders. Then the disturbance observer is constructed to estimate the mismatched disturbances of all group leaders and followers in finite time. Furthermore, based on finite time control theory and observer theory, a distributed control protocol is presented to make MASs realize FT-TVGF tracking under directed graph. The proof of close-loop stability of MASs is accomplished using Lyapunov theory. Finally, numerical simulations verify the theoretical analysis of this paper.

关键词： Disturbance observers Trajectory Tracking Protocols Directed graphs Technological innovation Multi-agent systems

Parallel Building Process Management System

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Parallel Building Process Management System

Chinese Automation Congress (CAC)

作者： Sheng Liu Xisong Dong Gang Xiong Zhen Shen Bin Hu Xiaoyu Chen State Key Laboratory for Management and Control of Complex System Institute of Automation Chinese Academy of Sciences Beijing China Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Dongguan China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China Institution of Intelligent Manufacturing Qingdao Academy of Intelligent Industries Qingdao China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781665426480

With the development of industrialized building and intelligence technology, it becomes necessary and possible to realize building process intelligence management. In recent years, digital twins and parallel management get more and more attentions in academic research and industrial applications. This paper addresses how parallel building system performs intelligence management on industrialized building process. Firstly, actual building model and artificial building model are created according to actual building system. Then business driving engine and simulation engine drive actual building model and artificial building model, respectively. Participants receive and send messages by software interfaces. Business driving engine changes the status of actual building model and sends the changes to simulation engine. Simulation engine updates the status of artificial building model and runs artificial building model with various parameters. Then it sends the parameter with the best effect to business driving engine. Business driving engine sends recommendations to participants according to the best parameter. Thus, building process intelligence management is achieved.

关键词： Automation Digital twin Buildings User interfaces Software Engines Business

HAWK: Rapid Android malware detection through heterogeneous graph attention networks

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arXiv 2021年

作者： Hei, Yiming Yang, Renyu Peng, Hao Wang, Lihong Xu, Xiaolin Liu, Jianwei Liu, Hong Xu, Jie Sun, Lichao The School of Cyber Science and Technology Beihang University Beijing100083 China The School of Computing University of Leeds LeedsLS2 9JT United Kingdom The National Computer Network Emergency Response Technical Team Coordination Center of China Beijing100029 China The School of Computer Science and Software Engineering East China Normal University Shanghai Trusted Industrial Control Platform Co. Ltd. Shanghai200062 China The Department of Computer Science and Engineering Lehigh University Bethlehem United States

Android is undergoing unprecedented malicious threats daily, but the existing methods for malware detection often fail to cope with evolving camouflage in malware. To address this issue, we present HAWK, a new malware detection framework for evolutionary Android applications. We model Android entities and behavioural relationships as a heterogeneous information network (HIN), exploiting its rich semantic meta-structures for specifying implicit higher-order relationships. An incremental learning model is created to handle the applications that manifest dynamically, without the need for re-constructing the whole HIN and the subsequent embedding model. The model can pinpoint rapidly the proximity between a new application and existing in-sample applications and aggregate their numerical embeddings under various semantics. Our experiments examine more than 80,860 malicious and 100,375 benign applications developed over a period of seven years, showing that HAWK achieves the highest detection accuracy against baselines and takes only 3.5ms on average to detect an out-of-sample application, with the accelerated training time of 50x faster than the existing approach. Copyright © 2021, The Authors. All rights reserved.

关键词： Android (operating system)

A Non-Stop Double Buffering Mechanism for Dataflow Architecture

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Journal of Computer Science & Technology 2018年第1期33卷 145-157页

作者： Xu Tan Xiao-Wei Shen Xiao-Chun Ye Da Wang Dong-Rui Fan Lunkai Zhang Wen-Ming Li Zhi-Min Zhang Zhi-Min Tang State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China School of Computer and Control Engineering University of Chinese Academy of Sciences Beijing 100049 China State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi 214125 China Department of Computer Science The University of Chicago Chicago IL 60637 U.S.A.

Double buffering is an effective mechanism to hide the latency of data transfers between on-chip and off-chip memory. However, in dataflow architecture, the swapping of two buffers during the execution of many tiles decreases the performance because of repetitive filling and draining of the dataflow accelerator. In this work, we propose a non-stop double buffering mechanism for dataflow architecture. The proposed non-stop mechanism assigns tiles to the processing element array without stopping the execution of processing elements through optimizing control logic in dataflow architecture. Moreover, we propose a work-flow program to cooperate with the non-stop double buffering mechanism. After optimizations both on control logic and on work-flow program, the filling and draining of the array needs to be done only once across the execution of all tiles belonging to the same dataflow graph. Experimental results show that the proposed double buffering mechanism for dataftow architecture achieves a 16.2% average efficiency improvement over that without the optimization.

关键词： non-stop double buffering dataflow architecture high-performance computing

A data-driven approach for discovering stochastic dynamical systems with non-Gaussian Lévy noise

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arXiv 2020年

作者： Li, Yang Duan, Jinqiao State Key Laboratory of Mechanics and Control of Mechanical Structures College of Aerospace Engineering Nanjing University of Aeronautics and Astronautics 29 Yudao Street Nanjing210016 China Department of Applied Mathematics College of Computing Illinois Institute of Technology ChicagoIL60616 United States

With the rapid increase of valuable observational, experimental and simulating data for complex systems, great efforts are being devoted to discovering governing laws underlying the evolution of these systems. However, the existing techniques are limited to extract governing laws from data as either deterministic differential equations or stochastic differential equations with Gaussian noise. In the present work, we develop a new data-driven approach to extract stochastic dynamical systems with non-Gaussian symmetric Lévy noise, as well as Gaussian noise. First, we establish a feasible theoretical framework, by expressing the drift coefficient, diffusion coefficient and jump measure (i.e., anomalous diffusion) for the underlying stochastic dynamical system in terms of sample paths data. We then design a numerical algorithm to compute the drift, diffusion coefficient and jump measure, and thus extract a governing stochastic differential equation with Gaussian and non-Gaussian noise. Finally, we demonstrate the efficacy and accuracy of our approach by applying to several prototypical one-, two- and three-dimensional systems. This new approach will become a tool in discovering governing dynamical laws from noisy data sets, from observing or simulating complex phenomena, such as rare events triggered by random fluctuations with heavy as well as light tail statistical features. Copyright © 2020, The Authors. All rights reserved.

关键词： Gaussian noise (electronic)

Distributed kalman estimation with decoupled local filters

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arXiv 2020年

作者： Marelli, Damián Sui, Tianju Fu, Minyue School of Automation Guangdong University of Technology Guangzhou China French-Argentinean International Center for Information and Systems Sciences National Scientific and Technical Research Council Rosario2000 Argentina School of Control Science and Engineering Dalian University of Technology Dalian China School of Electrical Engineering and Computing University of Newcastle CallaghanNSW2308 Australia

We study a distributed Kalman filtering problem in which a number of nodes cooperate without central coordination to estimate a common state based on local measurements and data received from neighbors. This is typically done by running a local filter at each node using information obtained through some procedure for fusing data across the network. A common problem with existing methods is that the outcome of local filters at each time step depends on the data fused at the previous step. We propose an alternative approach to eliminate this error propagation. The proposed local filters are guaranteed to be stable under some mild conditions on certain global structural data, and their fusion yields the centralized Kalman estimate. The main feature of the new approach is that fusion errors introduced at a given time step do not carry over to subsequent steps. This offers advantages in many situations including when a global estimate in only needed at a rate slower than that of measurements or when there are network interruptions. If the global structural data can be fused correctly asymptotically, the stability of local filters is equivalent to that of the centralized Kalman filter. Otherwise, we provide conditions to guarantee stability and bound the resulting estimation error. Numerical experiments are given to show the advantage of our method over other existing alternatives. Copyright © 2020, The Authors. All rights reserved.

关键词： Networked control systems

A Method for Cable Failure Analysis Based on Ageing Model and with Consideration of Daily Temperatures

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A Method for Cable Failure Analysis Based on Ageing Model an...

International Conference on Condition Monitoring and Diagnosis, CMD

作者： Huajie Yi Andrew Mcdiarmid Ralph Eyre-Walker Chengke Zhou Ian Hancock Dong Chen School of Computing Engineering and Built Environment Glasgow Caledonian University Glasgow United Kingdom Future Networks Scottish Power Energy Networks Glasgow United Kingdom ED2 Protection Control and Innovation Scottish Power Energy Networks Glasgow United Kingdom

ISBN: (数字)9781728159317

ISBN: (纸本)9781728159324

The physics- based electro-thermal ageing model has been widely used for analysis of cable failures and for evaluation of insulation status for single cable circuits. However, previously published approaches only reflect increased failure probability on an annual basis which cannot be used to explain the phenomenon that higher number of cable failures have been observed during summer time by Scottish Power Energy Networks (SPEN). Despite the insulation degradation accumulated annually, higher daily temperature during summer seasons resulted in extra stochastic stress applied on cable insulation and led to increasing cable failure probability. During summer seasons, the majority of cable failures occurred when daily temperature was higher than 10 °C. This paper aims to improve the electro-thermal model to evaluate remnant insulation strength and failure probability with consideration of stochastic stress due to higher daily temperature. Failure occurs when the stochastic stress overwhelms the remnant insulation strength. With the improved model, failure probability can reflect higher number of failures during the summer season.

关键词： Analytical models Temperature distribution Stochastic processes Aging Cable insulation Integrated circuit modeling Stress