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Determination of Polynomial Degree in the Regression of Drug Combinations

IEEE/CAA Journal of Automatica Sinica 2017年第1期4卷 41-47页

作者： Boqian Wang Xianting Ding Fei-Yue Wang School of Biomedical Engineering Shanghai Jiao Tong University IEEE State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Science (SKL-MCCS CASIA) Research Center of Computational Experiments and Parallel Systems National University of Defense Technology

Studies on drug combinations are becoming more and more popular in the past few decades, with the development of computer and algorithms. One of the most common methods in optimizing drug combinations is regression of a polynomial model based on certain number of experimental observations. In this paper, we study how to determine the degree of polynomials in different circumstances of drug combination optimization. Using cross-validation, we have found that in most cases, a high degree results in failures of accurate prediction, named overfitting. An anti-noise test has also revealed that polynomial model with high degree tends to be less resistant to random errors in the observations. © 2014 Chinese Association of Automation.

关键词： Acoustics Random errors Regression analysis

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Control 5.0: From Newton to Merton in Popper's Cyber-Social-Physical Spaces

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IEEE/CAA Journal of Automatica Sinica 2016年第3期3卷 233-234页

作者： Fei-Yue Wang IEEE State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences (SKL-MCCS CASIA) Research Center of Computational Experiments and Parallel Systems The National University of Defense Technology

The future of control in cyberspace of parallel worlds is discussed. It argues for the coming age of Control 5.0,the control technology for the new IT capable of dealing with artificial worlds with VR, AR, AI and robotics. The discipline of automation needs a new interpretation of its core knowledge and skill set of modeling, analysis, and control for cyber-socialphysical systems, and a paradigm shift from Newtonian systems with Newton's Laws or Big Laws with Small Data to Mertonian systems with Merton's Laws or Small Laws with Big Data.

关键词： Control 5.0 parallel control knowledge automation CPS CSP CPSS Merton Wiener Popper

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On social computing research collaboration patterns： a social network perspective

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Frontiers of Computer Science 2012年第1期6卷 122-130页

作者： Tao WANG Qingpeng ZHANG Zhong LIU Wenli LIU Ding WEN Science and Technology on Information Systems Engineering Lab College of Information Systems and ManagementNational University of Defense and TechnologyChangsha 410073China Department of Systems and Industrial Engineering University of ArizonaTucsonAZ 85721USA Military Computational Experiments and Parallel Systems Research Center National University of Defense and TechnologyChangsha 410073China

The field of social computing emerged more than ten years ago. During the last decade, researchers from a vari- ety of disciplines have been closely collaborating to boost the growth of social computing research. This paper aims at iden- tifying key researchers and institutions, and examining the collaboration patterns in the field. We employ co-authorship network analysis at different levels to study the bibliographic information of 6 543 publications in social computing from 1998 to 2011. This paper gives a snapshot of the current re- search in social computing and can provide an initial guid- ance to new researchers in social computing.

关键词： social computing bibliographic analysis com-putational social science social network analysis

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On Frequency Sensitivity and Mode Orthogonality of Flexible Robotic Manipulators

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IEEE/CAA Journal of Automatica Sinica 2016年第4期3卷 394-397页

作者： Fei-Yue Wang Yanqing Gao IEEE State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences Research Center of Computational Experiments and Parallel Systems the National University of Defense Technology Department of Manufacturing & Mechanical Engineering & Technology Oregon Institute of Technology

This paper presents sensitivity analysis of vibration frequencies of flexible manipulators with respect to variations of systems parameters such as rotational inertia of hub, and mass, moment, and side of tip load. Both Euler-Bernoulli and Timoshenko dynamical models of flexible manipulators are discussed. By using variational method, sensitivity indices are obtained with explicit expressions for measuring the sensitivity of frequencies. Based on variational formulations, a novel method for deriving the orthogonal relations among vibration modal shape functions of flexible manipulators is introduced. With this method, the orthogonal relations can be derived easily without invoking the tedious process of differentiation and integration by part, as commonly used in their derivation. © 2014 Chinese Association of Automation.

关键词： Dielectric waveguides Flexible manipulators Manipulators Orthogonal functions Vibration analysis

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On delay performance of peer-to-peer networks with age-dependent branching processes

On delay performance of peer-to-peer networks with age-depen...

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3rd International Conference on Multimedia Information Networking and Security, MINES 2011

作者： Xia, Youqing Wang, Hui Zhang, Yubao Li, Pei Research Center of Computational Experiment and Parallel System Technology College of Information Systems and Management National University of Defense Technology China

ISBN: (纸本)9780769545592

In this paper, we extended the Snow Ball algorithm to model Peer-to-Peer (P2P) networks based on the age-dependent branching process. We proved the extended Snow Ball algorithm approached a minimum delay bound in P2P networks. Given a fixed delay T, the maximal population to which a piece of content can be disseminated is derived, based on the age-dependent branching process. Similarly, we also mathematically analyze the minimum delay when the population N is fixed. © 2011 IEEE.

关键词： Snow

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parallel Learning:a Perspective and a Framework

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IEEE/CAA Journal of Automatica Sinica 2017年第3期4卷 389-395页

作者： Li Li Yilun Lin Nanning Zheng Fei-Yue Wang Department of Automation TNListTsinghua University IEEE State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences University of Chinese Academy of Sciences Institute of Artificial Intelligence and Robotics(IAIR) Xi'an Jiaotong University Research Center for Computational Experiments and Parallel Systems Technology National University of Defense Technology

The development of machine learning in complex system is hindered by two problems *** first problem is the inefficiency of exploration in state and action space,which leads to the data-hungry of some state-of-art data-driven *** second problem is the lack of a general theory which can be used to analyze and implement a complex learning *** this paper,we proposed a general methods that can address both two *** combine the concepts of descriptive learning,predictive learning,and prescriptive learning into a uniform framework,so as to build a parallel system allowing learning system improved by *** a new perspective of data,knowledge and action,we provide a new methodology called parallel learning to design machine learning system for real-world problems.

关键词： Descriptive learning machine learning parallel learning parallel systems predictive learning prescriptive learning

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Improving Auction Mechanisms for Online Real-Time Bidding Advertising with a Two-stage Resale Model

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IFAC-PapersOnLine 2017年第1期50卷 13575-13580页

作者： Qin, Rui Yuan, Yong Wang, Fei-Yue The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Qingdao Academy of Intelligent Industries Qingdao China Research Center of Military Computational Experiments and Parallel System National University of Defense Technology Changsha China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China

Real Time Bidding (RTB), widely publicized as one of the most promising big-data-driven business models for online computational advertising, has the potential of effectively monetizing user clicks and impressions via two-stage auctions with resale. Demand side platforms (DSPs) play a key role as intermediators in this auction process. Typically, the first-stage auctions will be conducted separately in each DSP to determine one winning advertiser registered on it, and in the second-stage auction, each DSP submits a bid based on its winning advertiser's bid to the ad exchange platform (AdX). The highest-bid DSP wins the ad impression from AdX and resells it to its winning advertiser in pursuit of the intermediate fee. This two-stage resale auction is a critical component in maintaining the effectiveness and efficiency of RTB ecosystems. In this paper, we strive to identify and design potential improvements for this auction mechanism with the aim of enhancing the total revenue of both advertisers and DSPs. We also validated our proposed auction mechanisms using the computational experiment approach. The experimental results indicate that our proposed mechanisms can make both advertisers and DSPs better off. Our work represents the first step towards a new research area of optimal mechanism design for RTB auctions, and is expected to provide useful managerial insights in RTB market practice. © 2017

关键词： Sales Commerce Machine design Auction mechanisms computational advertisings computational experiment Critical component Demand side Effectiveness and efficiencies Optimal mechanism designs Real time

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research on Information Structure of Programmatic Advertising Markets

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IFAC-PapersOnLine 2017年第1期50卷 13587-13592页

作者： Li, Juanjuan Yuan, Yong Zhao, Xueliang Wang, Fei-Yue The State Key Laboratory of Management 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 Beijing Qingdao China Research Center of Military Computational Experiments and Parallel Systems National University of Defense Technology Changsha China

With the abundance of online big data and computing resources, as well as the rapid develop-ment and diversification of business models, programmatic advertising (PA) has emerged and become the mainstream and one of the most promising advertising channels in recent years. As an effective way to precision marketing, PA relies heavily on the information elicited from analyzing Web users and pages, which can help advertisers precisely identify their best-matched audiences and evaluate the ad impressions in a real-time fashion In PA markets, publishers serve as the supplier of ad impressions, and have control on whether, what and how to reveal such key information to advertisers. These decisions play a central role in the information structure of data-driven PA markets, and attract intensive research interests. In this paper, we strive to investigate publishers’ rational preference over the symmetric and asymmetric information structures, with the aim of maximizing their revenues. Our model views publishers’ revenue as a function of the information structure among advertisers, and we hereby proved its convexity under an incentive compatible mechanism. This conclusion indicates that publishers prefer an asymmetric information structure rather than a symmetric one. Our research findings can help improve publishers’ revenue, and also can explain the underlying rationale for the hybrid PA markets mixed by public real-time bidding and private marketplaces. © 2017

关键词： Commerce Big data Marketing Advertising markets Asymmetric information Computing resource Incentive compatible mechanisms Information structures Precision marketings private marketplace Real time biddings

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A software framework for ACP in social computing

A software framework for ACP in social computing

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Chinese Automation Congress (CAC)

作者： Bin Chen Laobing Zhang Rongqing Meng Peng Zhang Gang Guo Research Center of Computational Experiments and Parallel System Technology National University of Defense Technology Changsha China

This paper proposes a novel software framework called KD-ACP. The framework implements the techniques of Artificial Society, computational experiments and parallel Execution. KD-ACP provides a systematic and automatic platform for scientists to study the emergency management problems in social computing. It is composed of a series of tools categorized into three parts correspond with the “A”, “C” and “P” respectively. The results from case study show that the most optimal emergency response decisions can be found through the software framework. In the end, the advantages of the KD-ACP and the futures work are summarized in the conclusion.

关键词： computational modeling Software Social network services Data models Databases Emergency services Sociology

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research on Social Marketing Strategies with An Agent-based Propagation Model

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IFAC-PapersOnLine 2017年第1期50卷 13581-13586页

作者： Zeng, Shuai Li, Juanjuan Ni, Xiaochun Yuan, Yong Wang, Fei-Yue The State Key Lab of Management Control for Complex Systems Institute of Automation Chinese Academy of Sciences China Qingdao Academy of Intelligent Industries BeijingShandong China Research Center of Military Computational Experiments and Parallel Systems National University of Defense Technology Changsha China

Considering the increasing complexity of social networks and user behaviors, it is very challenging for advertisers to formulate their strategies of selecting proper initial seed users in their social marketing efforts. In this paper, we tackle this challenge by proposing an agent-based propagation model and injecting it into typical social networks with three types of structures, i.e., Erds-Rényi random graph, Watt-Strogatz small world graph, and Barabási-Albert scale-free graph. We instantiate this agent-based model with demographic characteristics extracted from real-world census data collected in China. By investigating the diffusion process of advertising information in these social networks, we can analyze and compare the performance of advertisers’ targeting and influencer strategies. Our experimental results indicate that advertisers adopting influencer strategies should manipulate the initial well-connected seeds to deliver information only to the potential customers instead of a wide range of generic users. © 2017

关键词： Marketing Autonomous agents Behavioral research Commerce computational methods Population statistics Agent based model Demographic characteristics Information diffusion Potential customers Propagation modeling Seeding strategies Small world graphs Social marketings

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