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arXiv 2022年

作者： Li, Yuwei Yang, Bo Wu, Hao Han, Qiaoni Chen, Cailian Guan, Xinping The Department of Automation Shanghai Jiao Tong University Shanghai200240 China Huawei Technologies Co. Ltd China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China The Department of Automation Tianjin University Tianjin 300072 China

With the popularity of mobile devices and development of computationally intensive applications, researchers are focusing on offloading computation to Mobile Edge Computing (MEC) server due to its high computational efficiency and low communication delay. As the computing resources of an MEC server are limited, vehicles in the urban area who have abundant idle resources should be fully utilized. However, offloading computing tasks to vehicles faces many challenging issues. In this paper, we introduce a vehicular fog-edge computing paradigm and formulate it as a multi-stage Stackelberg game to deal with these issues. Specifically, vehicles are not obligated to share resources, let alone disclose their private information (e.g., stay time and the amount of resources). Therefore, in the first stage, we design a contract-based incentive mechanism to motivate vehicles to contribute their idle resources. Next, due to the complicated interactions among vehicles, road-side unit (RSU), MEC server and mobile device users, it is challenging to coordinate the resources of all parties and design a transaction mechanism to make all entities benefit. In the second and third stages, based on Stackelberg game, we develop pricing strategies that maximize the utilities of all parties. The analytical forms of optimal strategies for each stage are given. Simulation results demonstrate the effectiveness of our proposed incentive mechanism, reveal the trends of energy consumption and offloading decisions of users with various parameters, and present the performance comparison between our framework and existing MEC offloading paradigm in vehicular networks. © 2022, CC BY.

关键词： Fog computing

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ESNet: evolution and succession network for high-resolution salient object detection 24

ESNet: evolution and succession network for high-resolution ...

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Proceedings of the 41st International Conference on Machine Learning

作者： Hongyu Liu Runmin Cong Hua Li Qianqian Xu Qingming Huang Wei Zhang Institute of Information Science Beijing Jiaotong University & Beijing Key Laboratory of Advanced Information Science and Network Technology Beijing China School of Control Science and Engineering Shandong University & Key Laboratory of Machine Intelligence and System Control Ministry of Education Jinan China School of Computer Science and Technology Hainan University Hainan China Key Laboratory of Intelligent Information Processing Institute of Computing Technology CAS Beijing China School of Computer Science and Technology University of Chinese Academy of Sciences Beijing China

Preserving details and avoiding high computational costs are the two main challenges for the High-Resolution Salient Object Detection (HRSOD) task. In this paper, we propose a two-stage HRSOD model from the perspective of evolution and succession, including an evolution stage with Low-resolution Location Model (LrLM) and a succession stage with High-resolution Refinement Model (HrRM). The evolution stage achieves detail-preserving salient objects localization on the low-resolution image through the evolution mechanisms on supervision and feature; the succession stage utilizes the shallow high-resolution features to complement and enhance the features inherited from the first stage in a lightweight manner and generate the final high-resolution saliency prediction. Besides, a new metric named Boundary-Detail-aware Mean Absolute Error (MAEBD) is designed to evaluate the ability to detect details in high-resolution scenes. Extensive experiments on five datasets demonstrate that our network achieves superior performance at real-time speed (49 FPS) compared to state-of-the-art methods. Our code is publicly available at: https://***/rmcong/ESNet_ICML24.

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Blockchain-Based Incentive Announcement System for Internet of Vehicles

Blockchain-Based Incentive Announcement System for Internet ...

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IEEE International Conference on Big Data and Cloud Computing (BdCloud)

作者： Yang Yang Jialiang Chen Xianghan Zheng Ximeng Liu Wenzhong Guo Hairong Lv College of Mathematics and Computer Science Fuzhou University Fuzhou China Guangxi Key Laboratory of Cryptography and Information Security Guangnxi China Guangdong Provincial Key Laboratory of Data Security and Privacy Protection Guangzhou China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control (Minjiang University) Fuzhou China Ministry of Education Key Laboratory of Bioinformatics Bioinformatics Division and Center for Synthetic and Systems Biology Beijing National Research Center for Information Science and TechnologyDepartment of Automation Tsinghua University Beijing China

ISBN: (数字)9781728143286

ISBN: (纸本)9781728143293

With the rapid development of computation and communication technologies, the traditional vehicle ad hoc networks (VANETs) are changing to Internet of vehicle (IoV). Vehicular announcement networks in IoV have been widely used in the communication of vehicles. Generally, we need to solve two problems while establishing a vehicular announcement system. First, we need to protect user's privacy when broadcasting the message. Second, participants usually lack the enthusiasm to reply to the announcement. To solve these two problems, we propose a novel blockchain-based incentive announcement system that not only allows participants to anonymously announce their message on the blockchain in a non-trusted environment, but also motivates witnesses to respond to the request of the traffic information with incentive mechanism. Meanwhile, traffic messages and signatures in our system are tamper-resistant, which are recorded on the blockchain. According to the security and performance analysis, it shows that our system is privacy-preserving and efficient in computation cost.

关键词： Blockchain Privacy Smart contracts Authentication Internet Remuneration Hash functions

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Constructing multi-modality and multi-classifier radiomics predictive models through reliable classifier fusion

arXiv

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arXiv 2017年

作者： Zhou, Zhiguo Zhou, Zhi-Jie Hao, Hongxia Li, Shulong Chen, Xi Zhang, You Folkert, Michael Wang, Jing Department of Radiation Oncology UT Southwestern Medical Center DallasTX United States High-Tech Institute of Xi'an Xi'an China Department of Information and Control Engineering Xi'an University of Technology Xi'an China School of Computer Science and Technology Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education Xidian University Xi'an China School of Biomedical Engineering Southern Medical Unversity Guangzhou China Institute of Image Processing and Pattern Recognition Xi'an Jiaotong Unversity Xi'an China

Radiomics aims to extract and analyze large numbers of quantitative features from medical images and is highly promising in staging, diagnosing, and predicting outcomes of cancer treatments. Nevertheless, several challenges need to be addressed to construct an optimal radiomics predictive model. First, the predictive performance of the model may be reduced when features extracted from an individual imaging modality (e.g. PET, CT, MRI) are blindly combined into a single predictive model. Second, because many different types of classifiers are available to construct a predictive model, selecting an "optimal" classifier for a particular application is still challenging. In this work, we developed multi-modality and multi-classifier radiomics predictive models that address the aforementioned issues in currently available models. Specifically, a new reliable classifier fusion strategy was proposed to optimally combine output from different modalities and classifiers. In this strategy, modality-specific classifiers were first trained, and an analytic evidential reasoning (ER) rule was developed to fuse the output score from each modality to construct an optimal predictive model. One public datasets and two clinical case studies were performed to validate model performance. The experimental results indicated that the proposed ER rule based radiomics models outperformed the traditional models that rely on a single classifier or simply use combined features from different modalities. Copyright © 2017, The Authors. All rights reserved.

关键词： Diagnosis

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Robust quantum teleportation via a non-Markovian channel

arXiv

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arXiv 2023年

作者： Wang, Yanfang Xue, Shibei Song, Hongbin Jiang, Min Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China General Education Division Shenzhen Key Lab of Semiconductor Lasers The Chinese University of Hong Kong Guang Dong Shenzhen518116 China School of Electronics and Information Engineering Soochow University Suzhou215006 China

In this paper, we propose a non-Markovian quantum channel approach to mitigating the degradation of the average fidelity in continuous-variable quantum teleportation. The non-Markovian quantum channel is modeled by an augmented system, where ancillary systems are introduced to represent the internal modes of non-Markovian environments. With a proper non-Markovianity, enhanced effects of the channels on continuous-variable quantum teleportation are observed. Also, the logarithmic negativity of entangled states can be effectively maintained so that the decay of the average fidelity of quantum teleportation is mitigated. In addition, the analysis on different teleported quantum states shows that coherent states exhibit stronger robustness than those of squeezed states and cat states in quantum teleportation with a non-Markovian channel. Copyright © 2023, The Authors. All rights reserved.

关键词： Quantum entanglement

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Latent multi-view subspace clustering based on Laplacian regularized representation

Latent multi-view subspace clustering based on Laplacian reg...

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International Workshop on Advanced Computational Intelligence (IWACI)

作者： Wei Guo Hangjun Che Man-Fai Leung Nankun Mu Xiangguang Dai Yuming Feng School of Electronic and Information Engineering Southwest University Chongqing China School of Electronic Information Engineering Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Southwest University Chongqing China School of Computing and Information Science Faculty of Science and Engineering Anglia Ruskin University Cambridge UK Key Laboratory of Dependable Service Computing in Cyber Physical Society Ministry of Education College of Computer Science Chongqing University Chongqing China School of Computer Science and Engineering Chongqing Three Gorges University Chongqing China Key Laboratory of Intelligent Information Processing and Control Chongqing Three Gorges University Chongqing China

We propose a latent multi-view subspace clustering model based on Laplacian regularized representation. To emphasize the information of the representation matrix at the local level and reflect the grouping effect of clustering, a Laplacian regularization is imposed on the representation matrix. Additionally, To boost the efficiency o f c lustering, we apply nonnegative constraints on the representation matrix. A unified framework is designed to solve the proposed model by using ALM and LADMAP methods. The proposed model has excellent performance, as demonstrated by a number of experimental findings.

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Switched High-Gain Based Interval Observer Design for Harmonic Oscillator System

Switched High-Gain Based Interval Observer Design for Harmon...

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Chinese control Conference (CCC)

作者： Tianhang Ming Xiaoling Wang Bo Liu Housheng Su College of Automation & AI Nanjing University of Posts and Telecommunications Nanjing P. R. China Jiangsu Engineering Lab for IOT Intelligent Robots (IOTRobot) Nanjing China College of Information Engineering Minzu University of China Beijing P. R. China Key Laboratory of Image Processing and Intelligence Control of Ministry of Education Huazhong University of Science and Technology Wuhan P. R. China

In this paper, we revisit the interval observer design problem of harmonic oscillator system with unknown but bounded external disturbance and measurement noise. With the bounding information of the external disturbance and measurement noise, a high-gain interval observer is firstly defined and constructed for the harmonic oscillator system to realize the interval estimation on the state and the robust control of the system. Then, a switched high-gain interval observer is proposed to reduce the influence of the measurement noise for a tighter interval width on the state estimation. Finally, some numerical simulations are given to verify the theoretical results.

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SUNet: Scale-aware Unified Network for Panoptic Segmentation

arXiv

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arXiv 2022年

作者： Yan, Weihao Qian, Yeqiang Wang, Chunxiang Yang, Ming The Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China University of Michigan-Shanghai Jiao Tong University Joint Institute Shanghai Jiao Tong University Shanghai200240 China

Panoptic segmentation combines the advantages of semantic and instance segmentation, which can provide both pixel-level and instance-level environmental perception information for intelligent vehicles. However, it is challenged with segmenting objects of various scales, especially on extremely large and small ones. In this work, we propose two lightweight modules to mitigate this problem. First, Pixel-relation Block is designed to model global context information for large-scale things, which is based on a query-independent formulation and brings small parameter increments. Then, Convectional Network is constructed to collect extra high-resolution information for small-scale stuff, supplying more appropriate semantic features for the downstream segmentation branches. Based on these two modules, we present an end-to-end Scale-aware Unified Network (SUNet), which is more adaptable to multi-scale objects. Extensive experiments on Cityscapes and COCO demonstrate the effectiveness of the proposed methods. Copyright © 2022, The Authors. All rights reserved.

关键词： Semantics

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Inverse linear-quadratic discrete-time finite-horizon optimal control for indistinguishable homogeneous agents: a convex optimization approach

arXiv

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arXiv 2021年

作者： Zhang, Han Ringh, Axel Department of Automation School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China Department of Mathematical Sciences Chalmers University of Technology University of Gothenburg Gothenburg41296 Sweden

The inverse linear-quadratic optimal control problem is a system identification problem whose aim is to recover the quadratic cost function and hence the closed-loop system matrices based on observations of optimal trajectories. In this paper, the discrete-time, finite-horizon case is considered, where the agents are also assumed to be homogeneous and indistinguishable. The latter means that the agents all have the same dynamics and objective functions and the observations are in terms of "snap shots" of all agents at different time instants, but what is not known is "which agent moved where" for consecutive observations. This absence of linked optimal trajectories makes the problem challenging. We first show that this problem is globally identifiable. Then, for the case of noiseless observations, we show that the true cost matrix, and hence the closed-loop system matrices, can be recovered as the unique global optimal solution to a convex optimization problem. Next, for the case of noisy observations, we formulate an estimator as the unique global optimal solution to a modified convex optimization problem. Moreover, the statistical consistency of this estimator is shown. Finally, the performance of the proposed method is demonstrated by a number of numerical examples. Copyright © 2021, The Authors. All rights reserved.

关键词： Convex optimization

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Pneumatically Actuated MR-Safe Parallel Robot for Deep Brain Stimulation Electrode Implantation

Pneumatically Actuated MR-Safe Parallel Robot for Deep Brain...

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IEEE International Conference on Robotics and Biomimetics

作者： Weihang Huang Shenghao Dai Anze Xu Xianyi He Shaoping Huang Anzhu Gao School of Mechanical Engineering Shanghai Jiao Tong University Shanghai Jiao Tong University Institute of Medical Robotics and School of Biomedical Engineering Shanghai Jiao Tong University Shanghai China the Key Laboratory of System Control and Information Processing Ministry of Education Shanghai Jiao Tong University Shanghai China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China

ISBN: (纸本)9781665405362

Deep brain stimulation (DBS) has been widely used in clinical practice as an effective therapy for neurological disorders. MR-conditional robot-assisted electrode implantation has attracted more attention for DBS because of its great accuracy and high-quality guiding images by using MRI. This paper develops a pneumatically actuated MR-safe parallel robot for deep brain electrode implantation. Its fully plastic components and MR-safe pneumatic actuators enable the robotic system to be MR-safe, posing no known hazards in MR environment. A 6-DOF parallel robot is developed using six slider-crank mechanisms for prismatic motions. Inverse kinematics is built to investigate its workspace and achieve the precise control. Experiments are carried out to validate the feasibility, and results shows that the average error of the motion is 0.11 mm. The developed parallel robot shows the potential advantages in the automatic and precise robot-assisted neurosurgical surgery in future.

关键词： Electrodes Pneumatic actuators Neurological diseases Parallel robots Magnetic resonance imaging Satellite broadcasting Deep brain stimulation

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