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Collaborative Optimization of Cyber Physical Social Systems for Urban Transportation Based on Knowledge Automation

IFAC-PapersOnLine 2020年第5期53卷 572-577页

作者： Gang Xiong Xiaoyu Chen Nan Shuo Yisheng Lv Fenghua Zhu Tianci Qu Peijun Ye State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing 100049 China Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing The Cloud Computing Center Chinese Academy of Sciences Dongguan 523808 China Graduate School of System Design Tokyo Metropolitan University Tokyo 191-0065 Japan

The integration of signals from physical, social and cyber spaces, known as Cyber-Physical-Social systems (CPSS), is a new research paradigm for urban transportation, where the traffic control and management (C&M) is collaborative optimized among the three sub-systems. Though some technologies and optimization methods have been studied since its proposition, there is a lack of a systemic architecture as well as an overall implementation about how to efficiently exploit the social signals. For this reason, this paper proposes a general framework of CPSS for urban transportation and presents a feasible solution for traffic optimization based on knowledge automation. The specific implementation includes basic modeling of CPSS, knowledge evolution and reasoning, and collaborative optimization of C&P strategies. As a remarkable highlight, the influence of both individual activities and social learning is concerned during knowledge evolution and reasoning part. A case study from the application in the city of Dongguan is also given to validate our proposed framework and methods, showing that they can efficiently improve the average speed of the actual transportation.

关键词： CPSS knowledge automation urban transportation Collaborative Optimization

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Mitigating the effect of partial shading by triple-tied configuration of PV modules 10

Mitigating the effect of partial shading by triple-tied conf...

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10th IEEE PES Asia-Pacific Power and Energy engineering Conference, APPEEC 2018

作者： Kang Kho, Charles Tze Ahmed, Jubaer Then, Yi Lung Kermadi, Mostefa Faculty of Engineering Computing and Science Swinburne University of Technology Sarawak Kuching Sarawak93350 Malaysia Laboratory of Process Control National Polytechnic School of Algiers Algeria

ISBN: (纸本)9781538656860

Partial shading is the phenomenon, which occurs when PV modules receive irregular irradiance on a PV array. Due to that, shaded PV modules are bypassed by diodes and significant reduction in power is experienced. To counter such problem, PV modules are connected in different configuration to provide alternative path for current to flow, so that the effect of partial shading is lessened and power attainment is improved. A comprehensive literature review suggests that several PV configurations are proposed namely simple-series (SS), parallel (P), series-parallel (SP), total-cross-tied (TCT), bridge-linked (BL) and honey-comb (HC). In this paper, a comprehensive review is presented to highlight the benefits and limitations of each scheme. To mitigate the limitation of other approaches, a new configuration named triple-tied (TT) is proposed. Several experiments are carried out using both MATLAB Simulink and hardware implementation to validate the performance of proposed configuration. Eleven different partial shading cases are used in the experiments to analyze the output characteristics. Based on the results, the proposed TT configuration outperforms other PV configurations except TCT. However, in TT wiring connections are significantly reduced compared to TCT which makes it favorable in many large-scale PV applications. © 2018 IEEE.

关键词： Solar panels

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Fast ORB-SLAM without Keypoint Descriptors

arXiv

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arXiv 2020年

作者： Fu, Qiang Yu, Hongshan Wang, Xiaolong Yang, Zhengeng He, Yong Zhang, Hong Mian, Ajmal The National Engineering Laboratory for Robot Visual Perception and Control Technology College of Electrical and Information Engineering Hunan University China The Department of Computing Science University of Alberta Canada Quanzhou Institute of Industrial Design and Machine Intelligence Innovation Hunan University China The Southern University of Science and Technology Shenzhen China The School of Mathematics and Information Science Shaanxi Normal University China The Department of Computer Science The University of Western Australia WA6009 Australia

Indirect methods for visual SLAM are gaining popularity due to their robustness to environmental variations. ORB-SLAM2 [1] is a benchmark method in this domain, however, it consumes significant time for computing descriptors that never get reused unless a frame is selected as a keyframe. To overcome these problems, we present FastORB-SLAM which is light-weight and efficient as it tracks keypoints between adjacent frames without computing descriptors. To achieve this, a two stage descriptor-independent keypoint matching method is proposed based on sparse optical flow. In the first stage, we predict initial keypoint correspondences via a simple but effective motion model and then robustly establish the correspondences via pyramid-based sparse optical flow tracking. In the second stage, we leverage the constraints of the motion smoothness and epipolar geometry to refine the correspondences. In particular, our method computes descriptors only for keyframes. We test FastORB-SLAM on TUM and ICL-NUIM RGB-D datasets and compare its accuracy and efficiency to nine existing RGB-D SLAM methods. Qualitative and quantitative results show that our method achieves state-of-the-art accuracy and is about twice as fast as the ORB-SLAM2. Copyright © 2020, The Authors. All rights reserved.

关键词： Optical flows

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Coverage Probability-Constrained Maximum Throughput in UAV-Aided SWIPT Networks

Coverage Probability-Constrained Maximum Throughput in UAV-A...

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IEEE International Conference on Communications Workshops, ICC

作者： Ruihong Jiang Ke Xiong Tong Liu Duohua Wang Zhangdui Zhong School of Computer and Information Technology Beijing Jiaotong University Beijing China Beijing Computing Center Beijing China ZTE Corporation Xi'an China State Key Lab of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China Beijing Engineering Research Center of High-speed Railway Broadband Mobile Communications Beijing Jiaotong University Beijing China

ISBN: (数字)9781728174402

ISBN: (纸本)9781728174419

This paper investigates the coverage provability-constrained throughput in unmanned aerial vehicle (UAV)-assisted simultaneous wireless information and power transfer (SWIPT) networks, where UAVs are used as aerial base stations and their positions are modeled by the 2-dimension Poisson point process (2-D PPP). The ground users (GUs) decode information as well as harvest energy from the transmitted signals from UAVs. Both power splitting (PS) and time switching (TS) architectures are employed at GUs. By using a stochastic geometry approach, the explicit expressions of the information-energy (I-E) coverage probabilities are derived. To describe the optimal deployment density of UAVs, an optimization problem is formulated to maximize the system throughput subject to the I-E coverage probability constraint. By using Karush-Kuhn-Tucker (KKT) conditions, the closed-form solution is derived. Simulation results demonstrate the correctness of our derived analytical results and show that compared with traditional linear EH model, the nonlinear EH model yields significant difference performance behaviors of the system. Moreover, the nonlinear EH model has a greater impact on EH for the system with TS-enabled GU than that with PS-enabled one. With the increment of the outage threshold, the required density of UAVs should be increased and both the throughput and the energy first increase and then decrease.

关键词： Throughput Wireless communication Unmanned aerial vehicles Wireless sensor networks Integrated circuit modeling Analytical models Fading channels

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Study of Asymptotic Free Scalar Field Theories from Adaptive Perturbation Method

arXiv

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arXiv 2023年

作者： Ma, Chen-Te Zhang, Hui Department of Physics and Astronomy Iowa State University AmesIA50010 United States Asia Pacific Center for Theoretical Physics Pohang University of Science and Technology Gyeongsangbuk-do Pohang37673 Korea Republic of Guangdong Provincial Key Laboratory of Nuclear Science Institute of Quantum Matter South China Normal University Guangdong Guangzhou510006 China School of Physics and Telecommunication Engineering South China Normal University Guangdong Guangzhou510006 China Guangdong-Hong Kong Joint Laboratory of Quantum Matter Southern Nuclear Science Computing Center South China Normal University Guangdong Guangzhou510006 China The Laboratory for Quantum Gravity and Strings Department of Mathematics and Applied Mathematics University of Cape Town Private Bag Rondebosch7700 South Africa Key Laboratory of Atomic and Subatomic Structure and Quantum Control Institute of Quantum Matter South China Normal University Guangdong Guangzhou510006 China Physics Department Center for Exploration of Energy and Matter Indiana University BloomingtonIN47408 United States

We focus on the behavior of (2+1)d λ4 and (5+1)d λ3 or λ||3 theories in different regimes and compare the results obtained from the adaptive perturbation method with those obtained from lattice simulation. These theories are simple models that exhibit asymptotic freedom, which is a property that is also observed in more complex theories such as QCD, which describes the strong interaction between quarks and gluons. Asymptotic freedom is an important feature of these theories because it allows for a perturbative treatment of interactions at high energies. However, the standard perturbation scheme breaks down in the presence of strong interactions, and the adaptive perturbation method, which involves resuming the Feynman diagrams, is more suitable for studying these interactions. Our research involves comparing the perturbation result to lattice simulation. In the case of the 3 theory, there is no stable vacuum, so we explore evidence from the ||3 theory instead. Our results appear to show that resummation improves the strong coupling result for both the λ4 and λ||3 theories. Additionally, we improve the resummation method for the three-point coupling vertex and study the RG flow to analyze the resummation contribution and theoretical properties. Copyright © 2023, The Authors. All rights reserved.

关键词： Lattice theory

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R-CapsNet: An Improvement of Capsule Network for More Complex Data

R-CapsNet: An Improvement of Capsule Network for More Comple...

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IEEE Symposium Series on Computational Intelligence (SSCI)

作者： Lu Luo Shukai Duan Lidan Wang College of Electronic and Information Engineering Southwest University Chongqing China Brain-inspired Computing & Intelligent Control of Chongqing Key Lab National & Local Joint Engineering Laboratory of Intelligent Transmission and Control Technology Chongqing Brain Science Collaborative Innovation Center College of Artificial Intelligence Southwest University Chongqing China

ISBN: (数字)9781728124858

ISBN: (纸本)9781728124865

Convolutional neural networks (CNNs) have achieved the best performance in some fields. However, they still have some defects. CNNs need a lot of images for training; they will lose much information in the pooling layer, which reduces the spatial resolution. Facing such problems, Hinton et al. proposed a capsule network (CapsNet). Although the CapsNet has achieved the best accuracy on MNIST dataset, it has not performed well on Fashion-MNIST, Cifar-10 and other datasets. Naturally, we established an improved version of capsule network (R-CapsNet). Results have shown that when using R-CapsNet model, the loss gets decreased and the accuracy gets improved on FashionMNIST. In the meanwhile, the training parameters are reduced by nearly half. Specifically, it reduces by 4.5M. Comparisons show that our proposed model reports improved accuracy of around 0.56% over the existing state-of-the-art systems in literature. The test accuracy of R-CapsNet model is 1.32% higher than that of the original model. Furthermore, better results have been achieved on Cifar-10 with R-CapsNet model and it has easily increased by 10% compared to CapsNet.

关键词： Convolution Kernel Training Feature extraction Image recognition Image reconstruction Face recognition

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MLFD: Multi-level Feature Disentanglement Robust Network with a Novel Maximum-Minimum Algorithm for Medical Image Recognition

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Expert Systems with Applications 2025年

作者： Jianjun Yuan Fujun Wu Luoming Zhao Quan Kang College of Artificial Intelligence Southwest University Chongqing 400715 China National & Local Joint Engineering Research Center of Intelligent Transmission and Control Technology Chongqing 400715 China Chongqing Key Laboratory of Brain-inspired Computing and Intelligent Chips Chongqing 400715 China Department of General Surgery and Trauma Surgery Children’s Hospital of Chongqing Medical University No.136 Zhongshan 3rd Road Yuzhong District Chongqing 400014 China National Clinical Research Center for Child Health and Disorders Ministry of Education Key Laboratory of Child Development and Disorders Chongqing 401122 China

Current defense strategies for adversarial attacks in medical images often rely on adversarial sample saliency, neglecting the inherent differences among various features under adversarial perturbations, which hinders the extraction of disease-related robust features. To address this challenge, a novel multi-level feature disentanglement robust network is proposed, namely MLFD. The method first reconstructs input medical images using a variational autoencoder (VAE) to create an information bottleneck, aiming to filter high-frequency adversarial noise at the image level. Further, a dual-branch encoder architecture is introduced to achieve feature-level disentanglement between robust and sensitive features. Upon this architecture, we develop a new training algorithm explicitly designed for adversarial defense, called the maximum-minimum training algorithm. It implements hybrid optimization (HO) to learn essential feature representations, maximum classifier discrepancy (MCD) to effectively separate robust and sensitive features for preliminary disentanglement, and minimum mutual information (MMI) to further reduce statistical dependence between these features, thereby achieving complete feature disentanglement. Finally, we perform a theoretical elaboration for the proposed training algorithm based on domain adaptation bounds and the convergence properties of a KNN-based mutual information estimator. Extensive experiments on independent identical distribution (IID) and out-of-distribution (OoD) datasets demonstrate that the proposed method significantly outperforms state-of-the-art models under various adversarial attacks and distribution shifts.

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One family of 13315 stable periodic orbits of the non-hierarchical unequal-mass triple system

arXiv

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arXiv 2020年

作者： Li, Xiaoming Li, Xiaochen Liao, Shijun MOE Key Laboratory of Disaster Forecast and Control in Engineering School of Mechanics and Construction Engineering Jinan University Guangzhou510632 China Department of Earth Atmospheric and Planetary Sciences Massachusetts Institute of Technology CambridgeMA02139 United States School of Civil Engineering and Transportation South China University of Technology Guangzhou510641 China Department of Engineering Science University of Oxford OxfordOX1 3PJ United Kingdom Center of Advanced Computing School of Naval Architecture Ocean and Civil Engineering Shanghai Jiaotong University Shanghai200240 China School of Physics and Astronomy Shanghai Jiaotong University Shanghai200240 China

The three-body problem has been studied for more than three centuries1, 2, and has received much more attention in recent years3–5. It shows complex dynamical phenomena due to the mutual gravitational interaction of the three bodies. Triple systems are common in astronomy, but all observed periodic triple systems are hierarchical up till now6–8. It is traditionally believed that bound non-hierarchical triple systems are almost unstable and disintegrate into a stable binary system and a single star5, and thus stable periodic orbits of non-hierarchical triple systems are rather scarce. Here we report one family of 13315 stable periodic orbits of the non-hierarchical triple system with unequal mass. Compared with the narrow mass region (only 10−5) of the stable figure-eight solution9, our newly-found stable periodic orbits can have fairly large mass region. It is found that many of these newly-found stable periodic orbits have the mass ratios close to those of the hierarchical triple systems that have been measured by the astronomical observation. It implies that these stable periodic orbits of the non-hierarchical triple system with distinctly unequal masses can be quite possibly observed in practice. Our investigation also suggests that there should exist an infinite number of stable periodic orbits of non-hierarchical triple systems with distinctly unequal masses. Obviously, these stable periodic orbits of the non-hierarchical unequal-mass triple system have broad impact for the astrophysical scenario: they could inspire the theoretical and observational study of the non-hierarchical triple system, the formation of triple stars6, the gravitational waves pattern10 and the gravitational waves observation11 of the non-hierarchical triple system. Copyright © 2020, The Authors. All rights reserved.

关键词： Gravitational effects

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Comparative Study of Four Speed controllers of Brushless DC Motors for Industrial Applications

引用

IFAC-PapersOnLine 2020年第5期53卷 59-64页

作者： Tariku Sinshaw Tamir Gang Xiong Zhen Shen Xiaoyan Gong Sheng Liu Ehtisham Lodhi Li Wan Xisong Dong State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing 100049 China Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Donggguan 523808 China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing 100190 China Ten Dimensions (Guangdong) Technology Co. Ltd. Foshan 528225 China

Direct current (DC) motors are one of the most important kind of motors and are widely used in robotic and industrial applications. Recently, there have been significant efforts to develop direct current (DC) motors in an attempt to control speed of motors. However, conventional controlling approaches perform undesirably in terms of stability and quick response. Therefore, this paper presents a hybrid intelligent controller configuration for optimized speed control of brushless direct current (BLDC) motors in a factory supervisory control data acquisition (SCADA) system. We compare this hybrid intelligent controller with a conventional PID controller, fuzzy logic controller (FLC), and artificial neural network model reference controller (ANNMRC) in MATLAB , and the results show that the hybrid (neuro-fuzzy) controller performs superior in terms of stability, speed trajectory tracking capability, fast response, and simplicity for implementation.

关键词： BLDC motor fuzzy logic controller (FLC) artificial neural network model reference controller (ANNMRC) hybrid (neuro-fuzzy) control

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Multi-robot Path Planning and Trajectory Smoothing

Multi-robot Path Planning and Trajectory Smoothing

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IEEE International Conference on Automation Science and engineering (CASE)

作者： Hub Ali Gang Xiong Huaiyu Wu Bin Hu Zhen Shen Hongxing Bai School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China State Key Laboratory for Management and Control of Complex Systems 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 China Hubei Jointown Technology Co. Ltd Artificial Intelligence Research Institute Wuhan China

ISBN: (数字)9781728169040

ISBN: (纸本)9781728169057

In this paper we consider a problem in task execution for multi-robot trajectory planning with collision avoidance in a shared working environment. Consider two or more robots generating trajectories towards their respective goal positions. The collision may occur if their trajectory coordinates are intersecting at a point or follow the same path segment simultaneously. The central planner is introduced to control robot motion in the collision state and to reduce the complexity of the multi-robot path planning system. The global path for every robot is generated by the $\mathrm{A}^{*}$ algorithm in a grid-based environment. The path has presented a sequence of optimal grid numbers and later transformed into Cartesian coordinates for smooth trajectory generation. The central planner takes an optimal grid sequence for every robot to analyze the collision state according to its cost value. It regenerates the trajectories to minimize the complexity cost value and replaces the previous trajectory based on minimum cost value. In the collision state, the central planner allows one robot at a time to pass along the conflict path segment and hold others in queue at a safety offset distance until the previous robot passes safely. The algorithm has been applied to robots working in a shared environment in complex maps and the simulations is performed with MATLAB to calculate the efficiency of this approach for handling collision states in a multi-robot path planning system.

关键词： Robot kinematics Trajectory Collision avoidance Task analysis Resource management

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