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Quality Risk management Model for Railway Construction Projects

Procedia Engineering 2014年 84卷 195-203页

作者： Li Qing Liu Rengkui Zhang Jun Sun Quanxin State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing 100044 China Shanghai Railway Bureau Construction Management Department Shanghai 200071 China MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology Beijing Jiaotong University Beijing 100044 China

Information technology has significant potential to enhance the engineering quality of the risk management of railway construction projects. The Shanghai Railway Bureau has promoted a risk management method based on the “A Figure and Four Tables” method (AFFTM) to assess the engineering quality; however, this method still suffers from several problems in railway construction project management. In this paper, we have combined the concepts and processes of the AFFTM with those of information technology and presented the implementation scheme of a new risk management system—the railway construction project quality risk management information system (RCPQRMIS)—that can be used to design and develop workable information tools for quality risk management. The paper analyzes the data standards of RCPQRMIS and creates a model for dynamically tracking the quality risk (“quality risk dynamic tracking” model) for providing pre-warning information on quality risk (“quality risk pre-warning” model) and for automatically generating publicity parameters for quality risk (“automatically generated quality risk publicity figure” model). The proposed system enables the visualization of the quality associated with the risk control, dynamic tracking, automatic pre-warning, and closed-loop management of railway construction projects. In addition, this paper presents the functional modules of the RCPQRMIS and its practical applications. Our application results show that the system successfully realized unified management of risk source information and multi-level sharing. In this manner, by using our system, we were able to significantly improve real-time tracking and pre-warning of the risk state, automatic generation of quality risk publicity figures, efficiency, and risk management levels.

关键词： railway construction project risk management a figure and four tables method MIS

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Exploring Opinion Dynamics in Security-Related Microblog Data

Exploring Opinion Dynamics in Security-Related Microblog Dat...

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IEEE Joint Intelligence and Security Informatics Conference (JISIC)

作者： Yuhao Zhang Wenji Mao Daniel Zeng Ning Zhao Xiuguo Bao State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Department of Management Information Systems University of Arizona Tucson AZ USA Beijing Police Department CNCERT/CC Beijing China

Web social media has become one of the major channels for people to express their opinions, share their feelings and communicate with others. Public opinions often ebb and flow with time due to the occurrence of social events and mutual influence of people on certain topics. The dynamic change of public opinions reflects the evolvement and trend of public attitudes and can facilitate many security-related applications. In this paper, we explore the modeling and detection of opinion dynamics on a specific topic based on textual social media data. We first define three measures to provide a thorough description of opinion dynamics, and identify the key factors that influence opinion changes, namely sentiment, social influence and dynamic factors. We then develop the computational method to capture opinion dynamics in security-related data. A preliminary empirical study is conducted based on the data from Weibo, one of the most popular microblog sites in China. The experimental results show the effectiveness of our method in modeling and predicting opinion dynamics.

关键词： Time measurement Media Logistics Data models Predictive models Learning systems Support vector machines

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Behavior modeling of internet water army in online forums 19

Behavior modeling of internet water army in online forums

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19th IFAC World Congress on International Federation of Automatic control, IFAC 2014

作者： Zeng, Ke Wang, Xiao Zhang, Qingpeng Zhang, Xinzhan Wang, Fei-Yue School of Electronic and Information Engineering Xi'an Jiaotong University Xi'an710049 China State Key Laboratory of Management and Control of Complex Systems Institute of Automation Chinese Academy of Science Beijing100190 China Tetherless World Constellation Rensselaer Polytechnic Institute TroyNY12180 United States Software Engineering Xi'an Jiaotong University Xi'an710049 China

ISBN: (纸本)9783902823625

The behavior patterns and strategies of Internet Water Army in online forums are investigated in this paper. Internet Water Army focuses on the controlling and steering of cyber collective opinions, and adjusts their behavior according to two principles: to avoid being exposed and to increase the ability to exert influence. To study how the ability of Internet Water Army to exert influence, we construct a multi-agent system with coevolution of topics and cyber collective behaviors and design the behavior patterns and strategies of Internet Water Army. Based on synthetic data and real data, we find that Internet Water Army dynamically adjusts their behavior strategy to maximize their influence and the effectiveness of strategy of Internet Water Army is closely related to the features of the users. Our work sheds insight on the design of viral marketing mechanism in e-commerce systems as well as on guiding collective behaviors in social media. © IFAC.

关键词： Social networking (online)

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An high-efficient online reinforcement learning algorithm for continuous-state systems

An high-efficient online reinforcement learning algorithm fo...

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World Congress on Intelligent control and Automation (WCICA)

作者： Yuanheng Zhu Dongbin Zhao Haibo He The State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China Department of Electrical Computer and Biomedical Engineering University of Rhode Island Kingston RI USA

In this paper, we consider continuous-state systems and pursue a near-optimal policy through online learning. A new online reinforcement learning algorithm-MSEC (Multi-Samples in Each Cell) is proposed. The proposed algorithm combines state aggregation technique and efficient exploration principle, making high utilization of samples observed online. More concretely, we apply a grid over the continuous state space and partition it into different cells. Then, a near-upper Q iteration operator is defined to use samples in each cell and produce a near-upper Q function, whose corresponding greedy policy is efficient for exploration. MSEC is a totally model-free algorithm, which means no system dynamics is required during the implementation. It collects the system knowledge during the online learning. Based on PAC (Probability Approximately Correct) principle, MSCE can find a near-optimal policy in finite time bound online. To test the performance, an inverted pendulum is simulated and the results show the new algorithm is qualified for solving online optimal control problems.

关键词： Algorithm design and analysis Heuristic algorithms Partitioning algorithms Learning (artificial intelligence) Approximation algorithms Polynomials Upper bound

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Approximation-error-ADP-based optimal tracking control for chaotic systems with convergence proof

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Chinese Physics B 2013年第9期22卷 305-311页

作者：宋睿卓肖文栋孙长银魏庆来 School of Automation and Electrical Engineering University of Science and Technology Beijing The State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences

In this paper, an optimal tracking control scheme is proposed for a class of discrete-time chaotic systems using the approximation-error-based adaptive dynamic programming （ADP） algorithm. Via the system transformation, the optimal tracking problem is transformed into an optimal regulation problem, and then the novel optimal tracking control method is proposed. It is shown that for the iterative ADP algorithm with finite approximation error, the iterative performance index functions can converge to a finite neighborhood of the greatest lower bound of all performance index functions under some convergence conditions. Two examples are given to demonstrate the validity of the proposed optimal tracking control scheme for chaotic systems.

关键词： chaotic systems approximation error adaptive dynamic programming optimal tracking control

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EEG-based classification of upper-limb ADL using SNN for active robotic rehabilitation

EEG-based classification of upper-limb ADL using SNN for act...

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IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob)

作者： Jin Hu Zeng-Guang Hou Yi-Xiong Chen Nikola Kasabov Nathan Scott State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China Knowledge Engineering and Discovery Research Institute Auckland University of Technology Auckland New Zealand

Repetitive activities of daily living (ADL) and robotic active training are commonly practised in the rehabilitation of paralyzed patients, both of which have been proven rather effective to recover the locomotor function of impaired limbs. ADL classification based on electroencephalogram (EEG) is of great significance to perform active robotic rehabilitation for patients with complete spinal cord injury (SCI) who lose locomotion of affected limbs absolutely, where surface electromyography (sEMG) or active force signal can hardly be detected. It is a challenge to achieve a satisfying result in neuro-rehabilitation robotics using EEG signals due to the high randomness of the EEG data. A classification method is proposed based on spiking neural networks (SNN) to identify the upper-limb ADL of three classes with 14-channel EEG data. The continuous real-number signals are firstly encoded into spike trains through Ben's Spike Algorithm (BSA). The generated spikes are then submitted into a 3-D brain-mapped SNN reservoir called NeuCube trained by Spike Timing Dependant Plasticity (STDP). Spike trains from all neurons of the trained reservoir are finally classified using one version of dynamic evolving spiking neuron networks (deSNN) - deSNNs. Classifications are presented with and without NeuCube respectively on the same EEG data set. Results indicate that using the reservoir improves identification accuracy which turns out pretty promising despite that EEG data is highly noisy, low frequently sampled, and only from 14 channels. The classification technique reveals a great potential for the further implementation of active robotic rehabilitation to the sufferers of complete SCI.

关键词： Neurons Electroencephalography Training Robot kinematics Encoding Reservoirs

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Information Disclosure in Real-Time Bidding Advertising Markets

Information Disclosure in Real-Time Bidding Advertising Mark...

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2014 IEEE International Conference on Service Operations and Logistics,and Informatics

作者： Juanjuan Li Yong Yuan Rui Qin The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Qingdao Academy of Intelligent Industries Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences

Real-time bidding（RTB）advertising is a fast-growing business model in online display advertising *** the guaranteed display advertising,it utilizes programmatic instantaneous auction to price and sell ad inventory on a per-impression *** enbales advertisers to target audiences at demographic,psychographic or behavioral levels across a wide range of *** RTB markets,information about target audiences is usually disclosed to advertisers,while information about publishers（*** ranking,advertising page）are typically not avaliable for advertisers,especially in real-time *** leads to a serious information asymmetry problem in RTB markets,which has significant influence on both advertisers’bidding strategies and publishers’*** this paper,we study the information disclosure strategies of publishers in case when the disclosure may incur an extra *** address this information asymmetry problem by first formulating the RTB auction as an second-price sealed-bid game,then discussing equilibrium information disclosure strategies for publishers and also investigating advertisers’bidding strategies in the three information disclosure cases:all disclosed,non-disclosed,and partially *** find that non-disclosed and partially disclosed strategies may lead to an adverse selection effect,and high-quality publishers will be forced to quit the RTB markets.

关键词： real-time bidding information disclosure asymmetric information adverse selection

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Ranking Online Memes in Emergency Events Based on Transfer Entropy

Ranking Online Memes in Emergency Events Based on Transfer E...

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IEEE Joint Intelligence and Security Informatics Conference (JISIC)

作者： Saike He Xiaolong Zheng Xiuguo Bao Hongyuan Ma Daniel Zeng Bo Xu Guanhua Tian Hongwei Hao State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China CNCERT/CC Beijing China Department of Management Information Systems University of Arizona Tucson AZ USA Institute of Automation Chinese Academy of Sciences Beijing China

The rapid proliferation of online social networks has greatly boosted the dissemination and evolution of online memes, which can be free text, trending catchphrase, or micro media. However, this information abundance is exceeding the capability of the public to consume it, especially in unusual situations such as emergency management, intelligence acquisition, and crime analysis. Thus, there calls for a reliable approach to rank meme appropriately according to its influence, which will let the public focus on the most important memes without sinking into the information flood. However, studying meme in any detail on a large scale proves to be challenging. Previous bottom-up approaches are often highly complex, while the more recent top-down network analysis approaches lack detailed modeling for meme dynamics. In this paper, we first present a formal definition for meme ranking task, and then introduce a scheme for meme ranking in the context of online social networks (OSN). To the best of our knowledge, this is the first time that memes have been ranked in a model-free manner. Empirical results on two emergency events indicate that our scheme outperforms several benchmark approaches. This scheme is also robust by insensitive to sample rate. In light of the scheme's fine-grain modeling on meme dynamics, we also reveal two key factors affecting meme influence.

关键词： Entropy Benchmark testing Social network services Robustness Security Media

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Characterizing emotion entrainment in social media

Characterizing emotion entrainment in social media

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International Conference on Advances in Social Network Analysis and Mining, ASONAM

作者： Saike He Xiaolong Zheng Xiuguo Bao Hongyuan Ma Daniel Zeng Bo Xu Changliang Li Hongwei Hao State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China CNCERT/CC Beijing China Department of Management Information Systems University of Arizona Tucson AZ USA Institute of Automation Chinese Academy of Sciences Beijing China

The sociological theory of entrainment accounts for the synchronization of human rhythmic modalities through social interactions: they coordinate in a variety of dimensions including linguistic styles, facial expressions, music pace, applause, and so on. Though highly relevant, emotion entrainment has received little attention to date. In addition, most previous studies on entrainment are done through small scale or controlled laboratory studies. In this paper, we investigate emotion entrainment in the context of online social media. To the best of our knowledge, this is the first time that emotion entrainment has been examined on a large scale, real world setting. For this purpose, we propose a framework that can model entrainment phenomenon and measure its effect. Our framework differentiates from previous research by its model-free essential and discerning in entrainment directions. These traits enable us to model entrainment dynamics under few assumptions, and distinguish emotion flow of entrainment. In our studies, we investigate entrainment patterns under different emotion states, i.e. positive, neutral and negative. We discover that entrainments under different emotions all follow a power law distribution. Besides, people are willing to entrain to others under positive emotion, and users with positive emotion are more likely to be entrained. By inspecting the interactions between entrainment and emotion, we reveal that entrainment has an effect of negotiating different emotion types toward an even distribution.

关键词： Entropy Mood Media Blogs Markov processes Conferences Social network services

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A Survey on Real Time Bidding Advertising

A Survey on Real Time Bidding Advertising

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2014 IEEE International Conference on Service Operations and Logistics,and Informatics

作者： Yong Yuan Feiyue Wang Juanjuan Li Rui Qin The State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences Qingdao Academy of Intelligent Industries Beijing Engineering Research Center of Intelligent Systems and Technology Institute of AutomationChinese Academy of Sciences

Real-time bidding(RTB)is an emerging and promising business model for online computational advertising in the age of big *** on analysis of massive amounts of Cookie data generated by Internet users,RTB advertising has the potential of identifying in real-time the characteristic and interest of the target audience in each ad impression,automatically delivering best-matched ads,and optimizing their prices via auction-based programmatic buying *** has significantly changed online advertising,evolving from the traditional pattern of"media buying"and"ad-slot buying"to"targetaudience buying",and is expected to be the standard business model for online advertising in the *** this paper,we discussed the current market practice of RTB advertising,presented the key roles and typical business processes in RTB markets,and summarized the current research progresses in the existing *** aim of this paper is to provide useful reference and guidance for future works.

关键词： real-time bidding computational advertising online advertising big data

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