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Using deep learning to mine the key factors of the cost of AIDS treatment

Using deep learning to mine the key factors of the cost of A...

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International Conference on Smart Health, ICSH 2017

作者： Liu, Dong Cao, Zhidong Li, Su Beijing Key Laboratory of Big Data Technology on Food Safety Beijing Technology and Business University Beijing100048 China State Key Laboratory of Complex Systems Management and Control Institute of Automation Chinese Academy of Sciences Beijing100190 China

ISBN: (纸本)9783319679631

The medical burden of AIDS is a significant public health problem. However, it is affected by the multiple factors, among which there is yet some vague cognition, and further exploration is necessary. Thus, the artificial neural network (ANN) and restricted Boltzmann machine (RBM) be treated as the infrastructure of deep neural networks (DNN), mainly based on the features of demography, pathology and clinical manifestation of AIDS patient’s medical records to mine the impact factors of AIDS cost. And the proposed model could bring to light the previously uncharted latent knowledge and concepts. Based on reliable healthcare delivery, to inhibit the number of hospital days, intensive care and hospitalized frequency plus other sensitive factors, and avoid secondary infection and exposure to allergic reactions can obviously reduce the AIDS cost. © 2017, Springer International Publishing AG.

关键词： Costs

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Adaptive Dynamic Programming Based Decentralized Tracking control for Unknown Large-scale systems 36

Adaptive Dynamic Programming Based Decentralized Tracking Co...

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第36届中国控制会议

作者： Bo Zhao Derong Liu Yuanchun Li Qinglai Wei Ruizhuo Song The State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences School of Automation Guangdong University of Technology Department of Control Science and Engineering Changchun University of Technology School of Automation and Electrical Engineering University of Science and Technology Beijing

ISBN: (纸本)9781538629185

This paper investigates decentralized tracking control（DTC） problem for unknown large-scale systems via adaptive dynamic *** DTC consists of local desired control and local tracking error *** replacing the actual states of coupled subsystems in interconnection terms with their desired states,the norm-boundedness assumption can be *** on local neural network（NN） observers,unknown subsystems can be *** helps to obtain the local desired control with corresponding desired *** establishing a proper local cost function,the local tracking error control is derived via local critic NN and the identified input gain *** the entire error caused by replacement,identification and critic NN approximation,an adaptive robust term is added to construct the robust local cost function that reflects the entire error,regulation and control ***,the asymptotic stability can be guaranteed for the closed-loop tracking system via Lyapunov stability *** demonstrate the effectiveness of the proposed DTC,simulation on a hard spring connected parallel inverted pendulum system is given.

关键词： Adaptive dynamic programming Unknown large-scale systems Decentralized tracking control Neural networks Observer

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Artificial Intelligence Course Design: iSTREAM-based Visual Cognitive Smart Vehicles

Artificial Intelligence Course Design: iSTREAM-based Visual ...

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IEEE Symposium on Intelligent Vehicle

作者： Xiaoyan Gong Yilin Wu Zifan Ye Xiwei Liu State Key Laboratory of Management and Control for Complex Systems Intelligent Education Institute of Qingdao Academy of Intelligent Industries Qingdao China Beijing NO. 13 School Beijing China NO.2 high school of Beijing Normal University Beijing China

ISBN: (纸本)9781538644539

New intelligent era calls for new learners and thus urgently needs a series of artificial intelligence. As a good educational platform for teaching artificial intelligence, smart cars have aroused concern and practices of all parties. However, at present, most courses and training pay more attention to basic knowledge and technology of smart cars, seldom to training based on artificial intelligence curriculum system and comprehensive competency integrating science, technology, art and management. Therefore, based on concept of iSTREAM (intelligence for Science, Technology, Robotics, Engineering, Art, and management) and Raspberry intelligent vehicle teaching platform, this paper introduced a smart car-themed artificial intelligence courses including basic courses, specialized courses, specialized technical courses and elective courses. This course can guide learners to develop smart cars based on visual cognition, in-depth learning, VR and 3D printing integrated artistic creativity. It combines disciplines such as science, technology, art, games and management to upgrade a single knowledge and technology course into a comprehensive competency course that integrates knowledge, skills, emotion and management. Practice in Beijing NO.13 and NO.101 High School shows that this course allows students to experience scientific research process, learn artificial intelligence related knowledge and skills, understand scientific way of thinking and scientific research methods, stimulate learners' responsibility and scientific passion, and cultivate leadership skills through self-learning and partly project management.

关键词： Automobiles Artificial intelligence Art Hardware Software Project management Intelligent vehicles

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Seasonal Scheduling of Office Electricity Use via Adaptive Dynamic Programming

Seasonal Scheduling of Office Electricity Use via Adaptive D...

引用

Chinese control Conference (CCC)

作者： Guang Shi Bo Zhao Chao Li Xin Jin Derong Liu National Computer Network Emergency Response Technical Team/Coordination Center of China Beijing China The State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China School of Automation Guangdong University of Technology Guangzhou China

In this paper, an adaptive dynamic programming (ADP) based optimization method is proposed to schedule the electricity use of an office, where a battery is considered as the control variable, while solar and wind energies are included as additional energy supplies besides the grid. The electricity demand of an office generally contains socket, lighting and air-conditioning demands. Based on the periodic models of electricity price, electricity demand, and solar and wind energies, the optimal control strategies of the battery are determined by the proposed ADP based optimization method, so that the electricity cost from the grid can be saved. Simulation analysis demonstrates that the proposed method can achieve optimal real-time scheduling of office electricity use in different seasons of a year.

关键词： Batteries Optimization Scheduling Wind energy Performance analysis Optimal control Energy management

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End-to-End Driving Activities and Secondary Tasks Recognition Using Deep Convolutional Neural Network and Transfer Learning

End-to-End Driving Activities and Secondary Tasks Recognitio...

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IEEE Intelligent Vehicles Symposium

作者： Yang Xing Jianlin Tang Hong Liu Chen Lv Dongpu Cao Efstathios Velenis Fei-Yue Wang Advanced Vehicle Engineering Centre Cranfield University JIANGSU XCMG CONSTRUCTION MACHINERY RESEARCH INSTITUTE LTD School of Mechanical and Mechatronics Engineering University of Waterloo State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences

ISBN: (纸本)9781538644539

Drivers' decision and their corresponding behaviors are important aspects that can affect the driving safety, and it is necessary to understand the driver behaviors in real-time. In this study, an end-to-end driving-related tasks recognition system is proposed. Specifically, seven common driving activities are identified, which are normal driving, right mirror checking, rear mirror checking, left mirror checking, using in-vehicle video device, texting, and answering mobile phone. Among these, the first four activities are regarded as normal driving tasks, while the rest three are divided into distraction group. The images are collected using a consumer range camera, namely, Kinect. In total, five drivers are involved in the naturalistic data collection. Before training the identification model, the raw images are first segmented using a Gaussian mixture model (GMM) to extract the driver region from the background. Then, a pre-trained deep convolutional neural network (CNN) model is trained to classify the behaviors, which directly takes the processed RGB images as the input and outputs the identified label. In this work, the AlexNet is selected as the pre-trained CNN model. Then, to reduce the training cost, the transfer learning mechanism is applied to the CNN model. An average of 79% detection accuracy is achieved for the seven driving tasks. The proposed integration model can be used as a low-cost driver distraction and dangerous tasks recognition modeL.

关键词： Driver Behavior Religious Missions Transfer (Psychology) Automobile driving driving safety end-to-end Mirrors Drivers Neural network

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The Smart Street Lighting System Based on NB-IoT

The Smart Street Lighting System Based on NB-IoT

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Chinese Automation Congress

作者： Shichao Chen Shuangshuang Han Gang Xiong Fei-Yue Wang Jia Xu Kun Wang Macau University of Science and Technology Chinese Academy of Sciences Macau China The Cloud Computing Center Chinese Academy of Sciences Dongguan China Beijing University of Chemical Technology Chinese Academy of Sciences Beijing China The State Key Laboratory for Management and Control of Complex Systems Chinese Academy of Sciences The Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China Qingdao Academy of Intelligent Industries The State Key laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Qingdao China Beijing University of Chemical Technology Beijing China

With the development of communication technology, in order to meet the smart city's demand for intelligent infrastructure, the smart street lighting system based on NB-IoT is an effective method to realize the goal. This paper elaborates on the smart street lighting system's architecture, including the perception and control layer, the transport layer, the platform layer and the application layer. In addition, the actual system is built to verify. This system uses STM32 to build the perception and controller, and relies on China Telecom's NB-IoT communication network for the data transmission, finally using the IoT management platform-Huawei OceanConnect- to implement the connection management, the device management, the data calculation and the remote control functions. This system verifies the feasibility of the smart street lighting system based on NB-IoT technology, which provides the reference for the promotion and application. It is expected to provide intelligent, diversified, efficient and economical services for the smart cities.

关键词： Smart street lighting system NB-IoT IoT Smart city

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LoRa on the Move: Performance Evaluation of LoRa in V2X Communications

LoRa on the Move: Performance Evaluation of LoRa in V2X Comm...

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2018 IEEE Intelligent Vehicles Symposium, IV 2018

作者： Li, Yuke Han, Shuangshuang Yang, Linyao Wang, Fei-Yue Zhang, Hui State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Qingdao Academy of Intelligent Industries Qingdao266109 China School of Computer and Control Engineering University of Chinese Academy of Sciences Beijing100049 China Qingdao Huituo Intelligent Machine Company Qingdao China Research Center for Military Computational Experiments and Parallel Systems Technology National University of Defense Technology Changsha410073 China Computer Science Department School of Computer Science Carnegie Mellon University PittsburghPA15213 United States Conviva Inc. Silicon ValleyCA94404 United States

ISBN: (纸本)9781538644522

Recent years have witnessed much interest in Low Power Wide Area (LPWA) technologies, which are gaining unprecedented momentum and commercial interest towards the realisation of the Internet of Things (IoT). Long Range (LoRa), as a representative LPWA technology, has the potential to satisfy the growing demand for the longer range and larger amount connectivities in vehicular communication networks. In this paper, LoRa is firstly applied into two typical vehicular networks, namely Vehicle-to-Infrastructure (V2I)and Vehicle-to-Vehicle (V2V), and performance of LoRa schemes with different parameter configurations are evaluated and compared. Further, Monte Carlo simulations indicate that the schemes equipped with higher bandwidth or lower spreading factor exhibit significant advantages in combating the fast fading caused by Doppler effect in networks. © 2018 IEEE.

关键词： Monte Carlo methods

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Path following for a biomimetic underwater vehicle based on ADRC

Path following for a biomimetic underwater vehicle based on ...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Rui Wang Shuo Wang Yu Wang Chong Tang State Key Laboratory of Management and Control for Complex Systems University of Chinese Academy of Sciences Beijing China State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China

This paper addresses the problem of path following for a biomimetic underwater vehicle (BUV) propelled by undulatory fins with uncertain model and unknown disturbance. The mechanical structure of the BUV is briefly described. Moreover, the general kinematics and dynamics models of the vehicle are presented and the path following problem is formulated. The controller combining line-of-sight (LOS) guidance system with active disturbance rejection control (ADRC) technique is designed to maneuver the BUV to follow a predefined parameterized curve. Specifically, a guidance system based on LOS principle is implemented to decouple the multi-variable system to steer the surge speed and the course respectively. Furthermore, in order to deal with model uncertainty, ADRC is used in development of the surge speed controller and the course controller. Finally, simulations and experimental results validated the performance of the proposed path following control scheme.

关键词： Propulsion Surges Force Underwater vehicles Real-time systems Damping

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Neural Network Adaptive Critic control With Disturbance Rejection 29

Neural Network Adaptive Critic Control With Disturbance Reje...

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第29届中国控制与决策会议

作者： Ding Wang Chaoxu Mu Derong Liu The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences School of Computer and Control Engineering University of Chinese Academy of Sciences School of Electrical and Information Engineering Tianjin University School of Automation and Electrical Engineering University of Science and Technology Beijing

ISBN: (纸本)9781509046584

A neural-network-based adaptive critic control method is established for continuous-time input-affine uncertain nonlinear systems to achieve disturbance *** present problem can be formulated as a two-player zero-sum differential game and the adaptive critic mechanism is employed to solve the minimax optimization problem.A neural network identifier is developed to reconstruct the unknown dynamical *** optimal control law and the worst-case disturbance law are designed by introducing and training a critic neural *** effectiveness of the present self-learning control method is also illustrated by a simulation experiment.

关键词： Adaptive critic control Adaptive dynamic programming Approximate dynamic programming Disturbance rejection Learning systems Neural networks Nonlinear control

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Solutions Verification for Cloud-Based Networked control System using Karush-Kuhn-Tucker Conditions

Solutions Verification for Cloud-Based Networked Control Sys...

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Chinese Automation Congress

作者： Yasir Ali Zhen Shen Fenghua Zhu Gang Xiong Shichao Chen Yuanqing Xia Fei-Yue Wang The State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China Cloud Computing Center Chinese Academy of Sciences Dongguan China School of Automation Beijing Institute of Technology China Beijing Engineering Research Center of Intelligent Systems and Technology Chinese Academy of Sciences Beijing China

The rapid development of the Cloud Computing Technologies (CCTs) has amended the conventional design of resource-constrained Network control System (NCS) to the powerful and flexible design of Cloud-Based Networked control System (CB-NCS) by relocating the processing part to the cloud server. This arrangement has produced many internets based exquisite applications. However, this new arrangement has also raised many network security challenges for the cloud-based control system related to cyber-physical part of the system. In the absence of robust verification methodology, an attacker can launch the modification attack in order to destabilize or take control of NCS. It is desirable that there shall be a solution authentication methodology used to verify whether the incoming solutions are coming from the cloud or not. This paper proposes a methodology used for the verification of the receiving solution to the local control system from the cloud using Karush-Kuhn-Tucker (KKT) conditions, which is then applied to actuator after verification and thus ensure the stability in case of modification attack.

关键词： Cloud-based control system Security of NCS Analysis of solution verification for NCS KKT conditions

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