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Real-Time Systems Symposium (RTSS)

作者： Zonghong Li Guoqi Xie Wenhong Ma Xiongren Xiao Yong Xie Wei Ren Wanli Chang Key Laboratory for Embedded and Network Computing of Hunan Province College of Computer Science and Electronic Engineering Hunan University China Research Institute of Hunan University in Chongqing China Nanjing University of Posts and Telecommunications China Huawei Technologies China

Virtual machines (VMs) have been increasingly deployed in real-time systems to enhance heterogeneous resource sharing. Despite being isolated for security and prevention of failure propagation, VMs need to communicate with each other to complete certain tasks jointly. A real-time inter-VM communication framework has been proposed based on VirtIO, which is in essence a mechanism of message passing with high latency and low scalability on data amount. In contrary, IVSHMEM implements inter-VM communication with shared memory, which is generally fast and large in throughput. Unfortunately, IVSHMEM does not resolve resource contention between flows and hence cannot be applied in real-time scenarios. In this work, we propose a real-time inter-VM communication framework RTISM built upon shared memory and IVSHMEM. RTISM provides priority-based scheduling and supports mixed-criticality flows. Worst-Case Response Time (WCRT) analysis is reported to bound the end-to-end communication delay and a Limited Priority Assignment (LPA) algorithm is developed to enhance schedulability. Experimental evaluation shows that (i) RTISM has about 4 times higher throughput than the VirtIO-based inter-VM communication framework; (ii) LPA improves schedulability by over 25% compared to the state-of-the-art; (iii) WCRT produces a tight bound.

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Self-Supervised Teaching and Learning of Representations on Graphs 23

Self-Supervised Teaching and Learning of Representations on ...

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2023 World Wide Web Conference, WWW 2023

作者： Wan, Liangtian Fu, Zhenqiang Sun, Lu Wang, Xianpeng Xu, Gang Yan, Xiaoran Xia, Feng Key Laboratory for Ubiquitous Network Service Software of Liaoning Province School of Software Dalian University of Technology Dalian China Department of Communication Engineering Institute of Information Science Technology Dalian Maritime University Dalian China State Key Laboratory of Marine Resource Utilization in South China Sea School of Information and Communication Engineering Hainan University Haikou China State Key Laboratory of Millimeter Waves School of Information Science and Engineering Southeast University Nanjing China Research Center of Big Data Intelligence Research Institute of Artificial Intelligence Zhejiang Lab Hangzhou China School of Computing Technologies Rmit University Melbourne Australia

ISBN: (纸本)9781450394161

Recent years have witnessed significant advances in graph contrastive learning (GCL), while most GCL models use graph neural networks as encoders based on supervised learning. In this work, we propose a novel graph learning model called GraphTL, which explores self-supervised teaching and learning of representations on graphs. One critical objective of GCL is to retain original graph information. For this purpose, we design an encoder based on the idea of unsupervised dimensionality reduction of locally linear embedding (LLE). Specifically, we map one iteration of the LLE to one layer of the network. To guide the encoder to better retain the original graph information, we propose an unbalanced contrastive model consisting of two views, which are the learning view and the teaching view, respectively. Furthermore, we consider the nodes that are identical in muti-views as positive node pairs, and design the node similarity scorer so that the model can select positive samples of a target node. Extensive experiments have been conducted over multiple datasets to evaluate the performance of GraphTL in comparison with baseline models. Results demonstrate that GraphTL can reduce distances between similar nodes while preserving network topological and feature information, yielding better performance in node classification. © 2023 ACM.

关键词： Classification (of information)

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Intelligent System of Distance Education of Engineers, Based on Modern Innovative technologies

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Procedia - Social and Behavioral Sciences 2016年 228卷 229-236页

作者： Galina Samigulina Zarina Samigulina Chief of the laboratory “Intellectual systems and forecasting” Institute of Information and Computing Technologies str. Pushkeen 125. Almaty 050010 Kazakhstan Department “Automation and control” Institute of Information and Telecommunication Technologies Kazakh National Research Technical University named after K.I. Satpayev str. Satpaev 22 Almaty 050013 Kazakhstan

Nowadays, distance education is a promising direction for the training of engineers. There was developed the intellectual system of distance education for the training of qualified specialists of technical specialties on the expensive modern equipment in the laboratories of collective use. Processing of personal data for the purpose of selecting an individual educational plan for each student is based on the biological approach of artificial immune systems.

关键词： Higher education institution distance education organizational learning intellectual technologies artificial immune systems laboratories of a common use.

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Force control for flexible robots using neural networks

Force control for flexible robots using neural networks

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American control Conference (ACC)

作者： J. Borowiec A. Tzes Network Wireless Systems Product Design & Realization Lucent Technologies Inc. Whippany NJ USA Control/Robotics Research Laboratory Mechanical Engineering Department Six Metrotech Center Polytechnic University Brooklyn NY USA

Force control for flexible link robots using neural networks is considered. The nonlinear dynamics of the robot manipulator are identified through a recurrent neural network (RNN), which is trained in an off-line manner. Inversion of the RNN-based model dynamics leads to a feedforward component. The feedback controller gains are derived from the minimization of a discrete linear quadratic cost functional, subject to the model dynamics inferred by the linearization of the neural network along the desired trajectory. Sufficient conditions for temporal gain switching bounds are provided. The proposed control scheme is employed in simulation studies on a two link rigid-flexible manipulator.

关键词： Force control Neural networks Manipulator dynamics Recurrent neural networks Force feedback Jacobian matrices Adaptive control Cost function Robot kinematics Torque

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Average Channel Capacity Analysis for Visible Light Communications with Random Receivers

Average Channel Capacity Analysis for Visible Light Communic...

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International Conference on Wireless Communications and Signal Processing (WCSP)

作者： Xian-Tao Fu Rong-Rong Lu Sheng-Hong Lin Jin-Yuan Wang Key Lab of Broadband Wireless Communication and Sensor Network Technology Ministry of Education Nanjing University of Posts and Telecommunications Nanjing China Shanghai Key Laboratory of Trustworthy Computing East China Normal University Shanghai China Key Laboratory of Opto-technology and Intelligent Control Ministry of Education Lanzhou Jiaotong University Lanzhou China National Local Joint Engineering Research Center for Communication and Network Technologies Nanjing University of Posts and Telecommunications Nanjing China

ISBN: (数字)9781728172361

ISBN: (纸本)9781728172378

For indoor visible light communications (VLC), the receivers are usually set to be fixed ones in previous studies. However, the locations and orientations of receivers are affected by random factors in practical VLC systems. In this paper, the performance of VLC with random receivers is investigated. We consider an VLC system, which consists of a transmitter and a receiver. The main noise is additive white Gaussian noise. Two random factors (i.e., random location and random orientation) of the receiver are considered. Based on the established system model, closed-form expressions of the average channel capacity for systems with random location and random orientation are derived, respectively. Numerical results verify the accuracy of the derived theoretical expressions. Moreover, the impacts of the nominal optical intensity, the dimming target, the transmitter height and the Lambertian emission order on system performance are also discussed.

关键词： Visible light communication Optical transmitters Optical receivers Light emitting diodes Channel capacity High-speed optical techniques Wireless communication

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Digital Map Generation Workflow Demonstrated on ZalaZONE Automotive Proving Ground Elements 36

Digital Map Generation Workflow Demonstrated on ZalaZONE Aut...

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36th IEEE/IFIP network Operations and Management Symposium, NOMS 2023

作者： Somogyi, Árpád Tettamanti, Tamás Varga, Pál Szalay, Zsolt Baranyai, Dániel Lovas, Tamás Budapest University of Technology and Economics Fac. of Civil Engineering Dept. of Photogrammetry and Geoinformatics Budapest Hungary Institute for Computer Science and Control The Eötvös Loránd Research Network Systems and Control Laboratory Budapest Hungary Budapest University of Technology and Economics Fac. of Electrical Engineering and Informatics Dept. of Telecommunications and Media Informatics Budapest Hungary Budapest University of Technology and Economics Fac. of Transportation Eng. and Vehicle Eng. Dept. of Automotive Technologies Budapest Hungary

ISBN: (纸本)9781665477161

One major goal of digital twin technology applied in the Architecture, Engineering, and Construction (AEC) Industry is the mapping of roads and road environments with their associated information. Such digital twins can support cost-effective testing, simulations, and the production of mapping backgrounds for automated vehicles and generally for Cooperative, Connected and Automated Mobility (CCAM) developments. The efficient workflow that leads from data acquisition to finished products depends on a number of requirements and knowledge sets. The main contribution of the paper is a general methodology of creating HD-map from point cloud and image data set. Accordingly, the most widely used survey techniques are presented and the requirements for the objects to be derived are summarized. The paper then outlines a general implementation procedure as an expert knowledge through a real-life example, where the results obtained for the ZalaZONE Automotive Proving Ground are demonstrated. © 2023 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Tabular Q-learning Based Reinforcement Learning Agent for Autonomous Vehicle Drift Initiation and Stabilization

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IFAC-PapersOnLine 2023年第2期56卷 4896-4903页

作者： Szilárd H. Tóth Ádám Bárdos Zsolt J. Viharos Department of Automotive Technologies Budapest University of Technology and Economics Budapest Hungary Research Laboratory on Engineering and Management Intelligence Intelligent Processes Research Group Institute of Computer Science and Control Centre of Excellence in Production Informatics and Control Eötvös Loránd Research Network (ELKH) Centre of Excellence of the Hungarian Academy of Sciences (MTA) Budapest Hungary Department of Management and Business Law Faculty of Economics John von Neumann University Kecskemét Hungary

This paper aims to report on novel research results about developing a reinforcement learning agent for steady-state vehicle drift motion control. Based on the previous results of this research, the primary goal was to eliminate the problems causing learning instability experienced with the Soft Actor-Critic (SAC) algorithm applying Tabular Q-learning in this work. Trained in a MATLAB/Simulink-based simulation environment, the resulting agent succeeded in this task while being able to smoothly operate the vehicle to achieve and retain the desired target drift state, regardless of the discreet nature of the algorithm used for solving an inherently continuous task.

关键词： Motion control Autonomous Vehicles Vehicle Dynamics control Reinforcement Learning Vehicle Drifting Handling Limits

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Fault diagnosis for multi-energy flows of energy internet: Framework and prospects

Fault diagnosis for multi-energy flows of energy internet: F...

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2017 IEEE Conference on Energy Internet and Energy System Integration, EI2 2017

作者： Wang, Tao Wang, Jun Fan, Zhennan Wei, Xiaoguang Zang, Tianlei Pérez-Jiménez, Mario J. Huang, Tao School of Electrical Engineering and Electronic Information Sichuan Province Key Laboratory of Power Electronics Energy-saving Technologies and Equipment Key Laboratory of Fluid and Power Machinery Ministry of Education Xihua University Chengdu China School of Electrical Engineering Southwest Jiaotong University Chengdu China State Key Laboratory of Security Control and Simulation of Power Systems and Large Scale Generation Department of Electrical Engineering Tsinghua University Beijing China Research Groupon Natural Computing Department of Computer Science and Artificial Intelligence University of Sevilla Sevilla Spain Department of Energy Politecnico di Torino Torino Italy

ISBN: (纸本)9781538614273

Energy Internet (EI) is an inevitable development trend of energy systems under the background of technology development, environmental pressure and energy transition. Multi-energy flow coupling is one of the key characteristics of the EI, which enhances the interoperability of different types of energy flows while consequently increases the probability of cascading failures. Therefore it is of great significance to study the multi-energy flow fault diagnosis of the EI to ensure its safe and stable operation as well as the continuous energy supply. This paper introduces the concept of multi-energy flow cascading fault of the EI for the first time. The energy internet framework for multi-energy flow cascading fault diagnosis is firstly proposed, and then characteristics of various energy networks in the EI are analyzed from the perspective of fault diagnosis. Finally, future research prospects are discussed. © 2017 IEEE.

关键词： Failure analysis

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Software for automated classification of probe-based confocal laser endomicroscopy videos of colorectal polyps

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World Journal of Gastroenterology 2012年第39期18卷 5560-5569页

作者： Barbara André Tom Vercauteren Anna M Buchner Murli Krishna Nicholas Ayache Michael B Wallace Image Computing Group Mauna Kea Technologies75010 ParisFrance Asclepios Research Team The National Institute for Research in Computer Science and Control Sophia Antipolis06902 Sophia AntipolisFrance Division of Gastroenterology Hospital of theUniversity of PennsylvaniaPhiladelphiaPA 19104United States Laboratory Medicine and Pathology Mayo Clinic Hospital in JacksonvilleJacksonvilleFL 3224United States Department of Gastroenterology and Hepatology Mayo Clinic Hospital in JacksonvilleJacksonvilleFL 3224United States

AIM:To support probe-based confocal laser endomi-croscopy (pCLE) diagnosis by designing software for the automated classification of colonic polyps. METHODS:Intravenous fluorescein pCLE imaging of colorectal lesions was performed on patients under-going screening and surveillance colonoscopies, followed by polypectomies. All resected specimens were reviewed by a reference gastrointestinal pathologist blinded to pCLE information. Histopathology was used as the criterion standard for the differentiation between neoplastic and non-neoplastic lesions. The pCLE video sequences, recorded for each polyp, were analyzed off-line by 2 expert endoscopists who were blinded to the endoscopic characteristics and histopathology. These pCLE videos, along with their histopathology diagnosis, were used to train the automated classification software which is a content-based image retrieval technique followed by k-nearest neighbor classification. The performance of the off-line diagnosis of pCLE videos established by the 2 expert endoscopists was compared with that of automated pCLE software classification. All evaluations were performed using leave-one-patient- out cross-validation to avoid bias. RESULTS:Colorectal lesions (135) were imaged in 71 patients. Based on histopathology, 93 of these 135 lesions were neoplastic and 42 were non-neoplastic. The study found no statistical significance for the difference between the performance of automated pCLE software classification (accuracy 89.6%, sensitivity 92.5%, specificity 83.3%, using leave-one-patient-out cross-validation) and the performance of the off-line diagnosis of pCLE videos established by the 2 expert endoscopists (accuracy 89.6%, sensitivity 91.4%, specificity 85.7%). There was very low power (< 6%) to detect the observed differences. The 95% confidence intervals for equivalence testing were:-0.073 to 0.073 for accuracy, -0.068 to 0.089 for sensitivity and -0.18 to 0.13 for specificity. The classification software proposed i

关键词： Colorectal neoplasia Computer-aided diag-nosis Content-based image retrieval Nearest neigh-bor classification software Probe-based confocal laserendomicroscopy

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Continuous Perception Garment Classification Based on Optical Flow Variation

Continuous Perception Garment Classification Based on Optica...

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IEEE International Conference on Robotics and Biomimetics

作者： Li Huang Tong Yang Yu Zhang Rongxin Jiang- Xiang Tian Yaowu Chen Institute of Advanced Digital Technologies and Instrumentation Zhejiang University Hangzhou China State Key Laboratory of Industrial Control and Technology Zhejiang University China Zhejiang Provincial Key Laboratory for Network Multimedia Technology Hangzhou China Ministry of Education of China Embedded System Engineering Research Center Hangzhou China

ISBN: (纸本)9781665481106

A novel continuous perception garment classification mechanism is proposed in this paper, with the aim to identify the correct category of the garment from a set of known categories. It has been observed that due to the severe folding and overlapped texture of garments, treating a video of the continuous deformation of cloth as a set of disordered static figures would be ineffective which leads to low classification precision performed by an image-based garment classifier. In contrast, a high-level decision making module that leverages the classification results of each single image would significantly increase the algorithm performance. In this paper, we incorporate the optical flow variation of deformable cloth between consecutive configurations as a representative of how it is traversing within the confidence interval of the image-based classifier. We claim that it is not the number of video frames but the sum of optical flow variation of the garment configuration between consecutive frames having the same category label that constitutes the belief of garment classification. In other words, if two consecutive visual appearances of the garment could be identified as the same category by the image-based classifier, then the more diverged that two configurations are, the more confident that the garment is correctly identified. Experimental comparisons between the state-of-the-art algorithm and the proposed algorithm in a public dataset have been provided which prove the validity of the proposed algorithm.

关键词： Visualization Biomimetics Clothing Decision making Robot sensing systems Classification algorithms Task analysis

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