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The Emerging Intelligent Vehicles and Intelligent Vehicle Carriers Collaborative systems

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The Emerging Intelligent Vehicles and Intelligent Vehicle Ca...

IEEE Symposium on Intelligent Vehicle

作者： Zhipeng Shen Chao Huang Hailong Huang Yutong Wang Fei-Yue Wang Abbas Jamalipour Duc Truong Pham Ljubo Vlacic Andrey V. Savkin Department of Aeronautical and Aviation Engineering the Hong Kong Polytechnic University Hong Kong Department of Industrial and Systems Engineering the Hong Kong Polytechnic University Hong Kong State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Institute of Engineering Macau University of Science and Technology Macau China School of Electrical and Information Engineering University of Sydney Sydney Australia Department of Mechanical Engineering University of Birmingham Birmingham UK Institute of Intelligent & Integrated Systems and the School of Engineering and Built Environment Griffith University Brisbane Australia School of Electrical Engineering and Telecommunications University of New South Wales Sydney Australia

ISBN: (数字)9798350348811

ISBN: (纸本)9798350348828

In this paper, we propose the innovative use of Intelligent Vehicle Carriers (IVCs) as a key solution to address the energy constraints of small-scale unmanned Intelligent Vehicles (IVs). IVCs function as both transporters and charging stations, significantly boosting the operational range and efficiency of IVs. Our research delves into the IV-IVC collaborative framework, highlighting the existing challenges, exploring potential solutions, and examining a range of applications. This study offers a visionary approach to revolutionizing intelligent transportation systems by leveraging the synergistic relationship between IVs and IVCs.

关键词： Intelligent vehicles Collaboration Charging stations Boosting

Lithium Extraction from High Magnesium Salt Lake Brine with an Integrated Membrane Technology

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SSRN

SSRN 2022年

作者： Ashraf, Muhammad Awais Usman, Muhammad Hussain, Iftikhar Ahmad, Faraz Guo, Shiwei Zhang, Lu State Key Laboratory of Multiphase Complex Systems CAS Key Laboratory of Green Process and Engineering Institute of Process Engineering Chinese Academy of Sciences Beijing100190 PR China University of Chinese Academy of Sciences Beijing100049 China Washington State University United States Department of Mechanical Engineering City University of Hong Kong 83 Tat Chee Avenue Kowloon Hong Kong Key Laboratory of Coal Science and Technology Taiyuan University of Technology Taiyuan030024 China North China Electric Power University Hebei Key Lab of Power Plant Flue Gas Multi-Pollutants Control Department of Environmental Science and Engineering Baoding071000 China Faculty of Economics and Business

Lithium extraction is a great challenge from the high magnesium content salt solution. In this work, an integrated polyamide tight ultrafiltration (UF) and nanofiltration (NF) membranes are systematically investigated to separate Li+ from a high magnesium salt solution. Tight ultrafiltration UA001 and nanofiltration NF270 membranes in the integrated-cascade system not only increased Li+ permeation to 82.5% but also enhanced the high Mg2+ retention to 94.6% from the ternary salt solution of LiCl and MgCl2. The transport model was also developed to calculate the real retention of Li+ and Mg2+, under constant pressure mode. The separation efficiency SFLi/Mg for the ternary salt solution of LiCl+MgCl2+H2O was more than 15 at a constant pressure of 25 bars with an integrated membrane process, which was higher as compared to single-stage UF and NF270 membranes. Moreover, the high Mg2+/Li+ ratio was also reduced from 30 to 1.9 in the integrated-cascade membrane process. © 2022, The Authors. All rights reserved.

关键词： Magnesium compounds

Towards Realistic Face Photo-Sketch Synthesis via Composition-Aided GANs

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arXiv 2017年

作者： Yu, Jun Shi, Shengjie Gao, Fei Tao, Dacheng Huang, Qingming Key Laboratory of Complex Systems Modeling and Simulation School of Computer Science and Technology Hangzhou Dianzi University Hangzhou310018 China State Key Laboratory of Integrated Services Networks Xidian University Xian710071 China UBTech Sydney Artificial Intelligence Institute The School of Information Technologies Faculty of Engineering and Information Technologies The University of Sydney J12 Cleveland St DarlingtonNSW2008 Australia School of Computer and Control Engineering University of Chinese Academy of Sciences Beijing100190 China

Face photo-sketch synthesis aims at generating a facial sketch/photo conditioned on a given photo/sketch. It is of wide applications including digital entertainment and law enforcement. Precisely depicting face photos/sketches remains challenging due to the restrictions on structural realism and textural consistency. While existing methods achieve compelling results, they mostly yield blurred effects and great deformation over various facial components, leading to the unrealistic feeling of synthesized images. To tackle this challenge, in this work, we propose to use the facial composition information to help the synthesis of face sketch/photo. Specially, we propose a novel composition-aided generative adversarial network (CA-GAN) for face photo-sketch synthesis. In CA-GAN, we utilize paired inputs including a face photo/sketch and the corresponding pixel-wise face labels for generating a sketch/photo. In addition, to focus training on hard-generated components and delicate facial structures, we propose a compositional reconstruction loss. Finally, we use stacked CA-GANs (SCA-GAN) to further rectify defects and add compelling details. Experimental results show that our method is capable of generating both visually comfortable and identity-preserving face sketches/photos over a wide range of challenging data. Our method achieves the state-of-the-art quality, reducing best previous Fréchet Inception distance (FID) by a large margin. Besides, we demonstrate that the proposed method is of considerable generalization ability. We have made our code and results publicly available: Https://***/ca-gan/. Copyright © 2017, The Authors. All rights reserved.

关键词： Generative adversarial networks

Skin-Friction measurements Using Oil-Film Interferometry in Hypersonic Transitional Boundary Layer Flows

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SSRN

SSRN 2024年

作者： Zhang, Chuanhong Ni, Huibin Shi, Zhiwei Wu, Puyuan College of Aerospace Engineering Nanjing University of Aeronautics and Astronautics No. 29 Yudao Street Qinhuai District Jiangsu Nanjing210016 China State Key Laboratory of Turbulence and Complex Systems College of Engineering Peking University No. 5 Yiheyuan Road Haidian District Beijing100871 China Key Laboratory of Unsteady Aerodynamics and Flow Control Ministry of Industry and Information Technology Nanjing University of Aeronautics and Astronautics No. 29 Yudao Street Qinhuai District Jiangsu Nanjing210016 China

Skin-friction measurements in hypersonic transitional boundary layer (HTBL) flows on a flared cone at Mach 6 at zero angle of attack are obtained using oil-film interferometry (OFI). In addition, the amplitude evolution of instability waves is investigated using fast-response pressure sensors and Rayleigh-scattering flow visualization (RSFV). The connection between the skin-friction coefficient and near-wall dynamics during the whole transition process is illustrative and the underlying mechanism of the generation of the wall skin friction is revealed. There exist two peaks of skin-friction rise along the streamwise direction of the model. The first one is at the transitional region (denoted as FS) which is caused by the second-mode instability. The second one (denoted as FT) is at the region where the transition is completed. The drastic growth of skin friction near the end of transition is mainly attributed to the rapid boundary-layer breakdown into small scales. It is found that the strong shear in the near-wall region in the quiet zone where dominant hairpin-shaped vortices evolved from the second modes can also cause a local skin-friction rise (denoted as FQ). Further investigations show that in the region between FS and FQ, there is a slight increase in the skin friction, which is associated with the growing low-frequency waves. The skin friction coefficient value decreases slowly after FT but does not reach the expected turbulent theoretical value by the end of the test domain, indicating that the development towards the completely turbulent boundary layer appears to be a gradual process. © 2024, The Authors. All rights reserved.

关键词： Hypersonic flow

Group feature learning and domain adversarial neural network for aMCI diagnosis system based on EEG

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arXiv 2021年

作者： Fan, Chen-Chen Xie, Haiqun Peng, Liang Yang, Hongjun Ni, Zhen-Liang Wang, Guanan Zhou, Yan-Jie Chen, Sheng Fang, Zhijie Huang, Shuyun Hou, Zeng-Guang State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China CAS Center for Excellence in Brain Science and Intelligence Technology Beijing100190 China Joint Laboratory of Intelligence Science and Technology Institute of Systems Engineering Macau University of Science and Technology China Department of Neurology First People’s Hospital of Foshan FoshanGuangdong528000 China

— Medical diagnostic robot systems have been paid more and more attention due to its objectivity and accuracy. The diagnosis of mild cognitive impairment (MCI) is considered an effective means to prevent Alzheimer’s disease (AD). Doctors diagnose MCI based on various clinical examinations, which are expensive and the diagnosis results rely on the knowledge of doctors. Therefore, it is necessary to develop a robot diagnostic system to eliminate the influence of human factors and obtain a higher accuracy rate. In this paper, we propose a novel Group Feature Domain Adversarial Neural Network (GF-DANN) for amnestic MCI (aMCI) diagnosis, which involves two important modules. A Group Feature Extraction (GFE) module is proposed to reduce individual differences by learning group-level features through adversarial learning. A Dual Branch Domain Adaptation (DBDA) module is carefully designed to reduce the distribution difference between the source and target domain in a domain adaption way. On three types of data set, GF-DANN achieves the best accuracy compared with classic machine learning and deep learning methods. On the DMS data set, GF-DANN has obtained an accuracy rate of 89.47%, and the sensitivity and specificity are 90% and 89%. In addition, by comparing three EEG data collection paradigms, our results demonstrate that the DMS paradigm has the potential to build an aMCI diagnose robot system. © 2021, CC BY.

关键词： Diagnosis

Point Cloud Completion by Larger Receptive Fields for Intelligent Vehicles

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Point Cloud Completion by Larger Receptive Fields for Intell...

International Conference on Intelligent Transportation

作者： Yunqing Zhang Xiaotong Zhang Kunhua Liu Yisheng Lv Wei He Long Chen School of Computer Science and Engineering Sun Yat-Sen University Guangzhou China School of Mechanical and Automotive Engineering Qingdao University of Technology Qingdao China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Intelligence Science and Technology University of Science and Technology Beiing Beijing China Waytous Inc. Beijing China

Point cloud completion is a critical task for intelligent vehicles in the Intelligent Transportation systems (ITS). Due to the disordered nature of point clouds, current point-based point completion methods utilize max pooling operations and Convolutional Neural Networks (CNNs) with a convolution kernel size of 1 to extract point features. However, a network with a kernel size of 1 has a small receptive field and can only extract one point feature at a time; as a result, such a network struggles to precisely extract highly abstracted features. To address this issue, we propose a point cloud completion network with larger receptive fields, termed PLRF-Net, which is composed of two parts: a reconstruction network and a completion network. The reconstruction network focuses on repairing the structures of partial points and includes an offset-attention embedding module, a rearrangement module, several convolution layers with varying kernel sizes, a pooling and repeating layer, and transposed convolution layers with different kernel sizes. Meanwhile, the completion network strives to improve the precision of the completed point cloud and consists of several convolution layers, along with a downsampling and upsampling module. Experimental results indicate that our approach achieves superior quantitative and qualitative outcomes on both the Multiview Partial Point Cloud (MVP) and KITTI datasets.

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Towards Integrated Traffic control with Operating Decentralized Autonomous Organization

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Towards Integrated Traffic Control with Operating Decentrali...

International Conference on Intelligent Transportation

作者： Shengyue Yao Jingru Yu Yi Yu Jia Xu Xingyuan Dai Honghai Li Fei-Yue Wang Yilun Lin Urban Computing Shanghai AI Lab Shanghai China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Research and Development Center of Transport Industry of Autonomous Driving Technology RIOH High and Technology Group Institute of Automation Chinese Academy of Sciences Beijing China Macau Institute of Systems Engineering Macau University of Science and Technology Macau China

With a growing complexity of the intelligent traffic system (ITS), an integrated control of ITS that is capable of considering plentiful heterogeneous intelligent agents is desired. However, existing control methods based on the centralized or the decentralized scheme have not presented their competencies in considering the optimality and the scalability simultaneously. To address this issue, we propose an integrated control method based on the framework of Decentralized Autonomous Organization (DAO). The proposed method achieves a global consensus on energy consumption efficiency (ECE), meanwhile to optimize the local objectives of all involved intelligent agents, through a consensus and incentive mechanism. Furthermore, an operation algorithm is proposed regarding the issue of structural rigidity in DAO. Specifically, the proposed operation approach identifies critical agents to execute the smart contract in DAO, which ultimately extends the capability of DAO-based control. In addition, a numerical experiment is designed to examine the performance of the proposed method. The experiment results indicate that the controlled agents can achieve a consensus faster on the global objective with improved local objectives by the proposed method, compare to existing decentralized control methods. In general, the proposed method shows a great potential in developing an integrated control system in the ITS.

关键词：

A Generalized Probabilistic Monitoring Model with Both Randomand Sequential Data

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arXiv 2022年

作者： Yu, Wanke Wu, Min Huang, Biao Lu, Chengda The School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China The Department of Chemical and Materials Engineering University of Alberta EdmontonABT6G 2G6 Canada

Many multivariate statistical analysis methods and their corresponding probabilistic counterparts have been adopted to develop process monitoring models in recent decades. However, the insightful connections between them have rarely been studied. In this study, a generalized probabilistic monitoring model (GPMM) is developed with both random and sequential data. Since GPMM can be reduced to various probabilistic linear models under specific restrictions, it is adopted to analyze the connections between different monitoring methods. Using expectation maximization (EM) algorithm, the parameters of GPMM are estimated for both random and sequential cases. Based on the obtained model parameters, statistics are designed for monitoring different aspects of the process system. Besides, the distributions of these statistics are rigorously derived and proved, so that the control limits can be calculated accordingly. After that, contribution analysis methods are presented for identifying faulty variables once the process anomalies are detected. Finally, the equivalence between monitoring models based on classical multivariate methods and their corresponding probabilistic graphic models is further investigated. The conclusions of this study are verified using a numerical example and the Tennessee Eastman (TE) process. Experimental results illustrate that the proposed monitoring statistics are subject to their corresponding distributions, and they are equivalent to statistics in classical deterministic models under specific restrictions. Copyright © 2022, The Authors. All rights reserved.

关键词： Process monitoring

Towards Integrated Traffic control with Operating Decentralized Autonomous Organization

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arXiv 2023年

作者： Yao, Shengyue Yu, Jingru Yu, Yi Xu, Jia Dai, Xingyuan Li, Honghai Wang, Fei-Yue Lin, Yilun Urban Computing Shanghai AI Lab Shanghai China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China The Research and Development Center of Transport Industry of Autonomous Driving Technology RIOH High and Technology Group The Institute of Automation Chinese Academy of Sciences Beijing China The Macau Institute of Systems Engineering Macau University of Science and Technology China

关键词： Integrated control