Key Laboratory of Complex Systems Modeling and Simulation

Hangzhou, China

Key Laboratory of Complex Systems Modeling and Simulation

Hangzhou, China
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Shi X.,Hangzhou Dianzi University | Shi X.,Key Laboratory of Complex Systems Modeling and Simulation | Yu Z.,Hangzhou Dianzi University | Chen J.,Hangzhou Dianzi University | And 2 more authors.
Journal of Visual Languages and Computing | Year: 2017

Public Bicycle System(PBS) is an increasingly popular mode of public transit, with the advantage of pollution-free and flexibility. In this paper, we present an interactive visual analytic system for exploring complex flows generated by PBS. Four inter-linked visualization views are designed to illustrate multiple perspectives of data, such as the spatial-temporal changes, the relationships and differences between flow OD pairs and the multi-dimensional factors(weather condition, calendar events) influencing on the rental numbers. A new presentation "Parallel coordinates with line and set" combined with flexible interaction schemes is proposed to support the exploration of multivariate association. We exemplify our approach with a real citywide PBS dataset. The results of case study demonstrate that our system is helpful for visually classifying stations with different flow patterns, speculating in-depth reasons, as well as investigating abnormal behaviors, helping decision makers to gain a better understanding of the large dataset. © 2017 Elsevier Ltd.

Peng Y.,Hangzhou Dianzi University | Peng Y.,Key Laboratory of Complex Systems Modeling and Simulation | Lu B.-L.,Shanghai JiaoTong University
Multimedia Tools and Applications | Year: 2016

By representing a test sample with a linear combination of training samples, sparse representation-based classification (SRC) has shown promising performance in many applications such as computer vision and signal processing. However, there are several shortcomings in SRC such as 1) the l2-norm employed by SRC to measure the reconstruction fidelity is noise sensitive and 2) the l1-norm induced sparsity does not consider the correlation among the training samples. Furthermore, in real applications, face images with similar variations, such as illumination or expression, often have higher correlation than those from the same subject. Therefore, we correspondingly propose to improve the performance of SRC from two aspects by: 1) replacing the noise-sensitive l2-norm with an M-estimator to enhance its robustness and 2) emphasizing the sparsity in terms of the number of classes instead of the number of training samples, which leads to the structured sparsity. The formulated robust structured sparse representation (RGSR) model can be efficiently optimized via alternating minimization method under the half-quadratic (HQ) optimization framework. Extensive experiments on representative face data sets show that RGSR can achieve competitive performance in face recognition and outperforms several state-of-the-art methods in dealing with various types of noise such as corruption, occlusion and disguise. © 2016 Springer Science+Business Media New York

Ding H.,Hangzhou Dianzi University | Ding H.,Key Laboratory of Complex Systems Modeling and Simulation | Cao L.,Hangzhou Dianzi University | Qiu H.,Hangzhou Dianzi University | And 3 more authors.
Proceedings - 2015 International Conference on Identification, Information, and Knowledge in the Internet of Things, IIKI 2015 | Year: 2015

Most previous studies involving public goods games are investigated under a simplifying assumption that participators are compulsive in collective interactions and contribute unconditionally to the public pool. Nevertheless, how the conditional investment mechanism based on individual's reputation affects the evolution of cooperation in structured populations is still unclear. Here we introduce a reputation-based conditional investment rule for constituting participant groups into spatial threshold public goods game, where the public goods game can be conducted only if the participant number is not less than the threshold parameter. Interestingly, we find that large threshold parameter results in the optimal environment for cooperators' viability. © 2015 IEEE.

Ding H.,Hangzhou Dianzi University | Ding H.,Key Laboratory of Complex Systems Modeling and Simulation | Zhang Y.,Hangzhou Dianzi University | Ren Y.,Hangzhou Dianzi University | And 4 more authors.
Soft Computing | Year: 2016

Understanding and maximizing the effects of heterogeneous investment, particularly in a socially diverse society, on the evolution of cooperation have been the focus of recent research. In the most existing studies, individuals are limited to make binary decisions (i.e., either cooperate or defect). This is unrealistic in many real-world situations. In this paper, we investigate the effect of a heterogeneous investment on the evolution of cooperation in mixed strategy public goods games, wherein individuals have different probability of cooperation. Specifically, players are able to distribute heterogeneous investments into different groups, and they tend to allocate their investment into the group which achieves a higher return on investment (e.g., payoffs). Simulation results show that the formation of cooperative clusters allows cooperative players to resist the exploitation of defective players; subsequently, the cooperation level of the whole population significantly increases. Moreover, the results also show that cooperative clusters become more robust when the investment redistribution decision relies on more recent information. Our study may offer new insights into how strategy diversity promotes the evolutionary of cooperation in realistic situations. © 2016 Springer-Verlag Berlin Heidelberg

Ding H.,Hangzhou Dianzi University | Ding H.,Key Laboratory of Complex Systems Modeling and Simulation | Cao L.,Hangzhou Dianzi University | Ren Y.,Hangzhou Dianzi University | And 5 more authors.
PLoS ONE | Year: 2016

Encouraging cooperation among selfish individuals is crucial in many real-world systems, where individuals' collective behaviors can be analyzed using evolutionary public goods game. Along this line, extensive studies have shown that reputation is an effective mechanism to investigate the evolution of cooperation. In most existing studies, participating individuals in a public goods game are assumed to contribute unconditionally into the public pool, or they can choose partners based on a common reputation standard (e.g., preferences or characters). However, to assign one reputation standard for all individuals is impractical in many real-world deployment. In this paper, we introduce a reputation tolerance mechanism that allows an individual to select its potential partnersand decide whether or not to contribute an investment to the public pool based on its tolerance to other individuals' reputation. Specifically, an individual takes part in a public goods game only if the number of participants with higher reputation exceeds the value of its tolerance. Moreover, in this paper, an individual's reputation can increase or decrease in a bounded interval based on its historical behaviors.We explore the principle that how the reputation tolerance and conditional investment mechanisms can affect the evolution of cooperation in spatial lattice networks. Our simulation results demonstrate that a larger tolerance value can achieve an environment that promote the cooperation of participants. © 2016 Ding et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Xu G.,Hangzhou Dianzi University | Xu G.,Key Laboratory of Complex Systems Modeling and Simulation | Zhu Y.-G.,Hangzhou Dianzi University | Li X.,Hangzhou Dianzi University | And 4 more authors.
Ruan Jian Xue Bao/Journal of Software | Year: 2016

Efficient modeling of minimal surfaces is a challenging problem and hot topic in the field of geometric design and computation. Taking boundary closed polylines, this paper proposes a general framework to construct discrete minimal surfaces with quadrilateral meshes. First, the mathematical definition of discrete minimal surface with quadrilateral mesh is given from the intrinsic differential-geometry metric of surfaces. Next, based on the length-preserving boundary projection method, quad-mesh generation approach and non-linear numerical optimization technique, a novel framework is presented to construct discrete minimal surfaces with quadrilateral meshes from a described boundary closed discrete polylines. Finally, the effectiveness of the proposed approach is illustrated by several modeling examples. The results show that the proposed method can achieve high-quality modeling of discrete minimal surfaces and provide potential usage in architecture geometry. © Copyright 2016, Institute of Software, the Chinese Academy of Sciences. All rights reserved.

Ding H.,Hangzhou Dianzi University | Ding H.,Key Laboratory of Complex Systems Modeling and Simulation | Zhang Y.,Hangzhou Dianzi University | Hu H.,Hangzhou Dianzi University | And 4 more authors.
Proceedings - 2015 International Conference on Identification, Information, and Knowledge in the Internet of Things, IIKI 2015 | Year: 2015

Previous researches have well demonstrated the importance of costly punishment for promoting the evolution of cooperation, while it remains unconsidered sides about the punishment. Recent evidences highlight that punishment cannot promote cooperation when punishment can be targeted at cooperators. In this paper, we study the evolutionary process of cooperation in the well-mixed population when the presence of antisocial punishment. Here cooperator can optionally adopt an insurance strategy which incurs an extra cost to resist the threat of antisocial punishment, and she will obtain compensation when being punished by antisocial punisher in the future. With this strategy, cooperators can opportunistically adjust their behavior, which makes cooperators evolve advantageously, and improve individuals' average payoff in population. © 2015 IEEE.

Yin Y.,Hangzhou Dianzi University | Yin Y.,Zhejiang University | Yin Y.,Key Laboratory of Complex Systems Modeling and Simulation | Aihua S.,Hangzhou Dianzi University | And 4 more authors.
International Journal of Software Engineering and Knowledge Engineering | Year: 2016

Web service recommendation is one of the key problems in service computing, especially in the case of a large number of service candidates. The QoS (quality of service) values are usually leveraged to recommend services that best satisfy a user's demand. There are many existing methods using collaborative filtering (CF) to predict QoS missing values, but very limited works can leverage the network location information in the user side and service side. In real-world service invocation scenario, the network location of a user or a service makes great impact on QoS. In this paper, we propose a novel collaborative recommendation framework containing three novel prediction models, which are based on two techniques, i.e. matrix factorization (MF) and network location-aware neighbor selection. We first propose two individual models that have the capability of using the user and service information, respectively. Then we propose a unified model that combines the results of the two individual models. We conduct sufficient experiments on a real-world dataset. The experimental results demonstrate that our models achieve higher prediction accuracy than baseline models, and are not sensitive to the parameters. © 2016 World Scientific Publishing Company.

You X.,Hangzhou Dianzi University | You X.,Key Laboratory of Complex Systems Modeling and Simulation | Zhou R.,Hangzhou Dianzi University | Zhou R.,Key Laboratory of Complex Systems Modeling and Simulation | Zhou R.,Zhejiang Provincial Engineering Center on Data Cloud Processing and Analysis
Advances in Condensed Matter Physics | Year: 2014

A first-principles study has been performed to investigate the structural and electronic properties of the GaAs1 x Bix system. The simulations are based upon the generalized gradient approximation (GGA) within the framework of density functional theory (DFT). Calculations are performed to different Bi concentrations. The lattice constant of GaAs 1 x Bi x increases with Bi concentration while the alloy remains in the zinc-blende structure. The band gap of GaAs 1 x Bix clearly shrinks with the Bi concentration. The optical transition of Bi dopant in GaAs exhibits a red shift. Besides, other important optical constants, such as the dielectric function, reflectivity, refractive index, and loss function also change significantly. © 2014 Xindong You and Renjie Zhou.

Yu D.,Hangzhou Dianzi University | Wang R.,Key Laboratory of Complex Systems Modeling and Simulation | Wang J.,Key Laboratory of Complex Systems Modeling and Simulation | Li W.,Key Laboratory of Complex Systems Modeling and Simulation
Journal of Imaging Science and Technology | Year: 2016

City traffic often exhibits regional characteristics, such as large trucks frequently appearing in the suburbs, and the paths to playgrounds on weekends generally being congested. Discovering and visualizing these hidden traffic regions inside which roads share similar characteristics of traffic conditions simplifies the modeling complexities of whole city traffic conditions and therefore contributes significantly toward city planning. Unfortunately, such traffic regions always have irregular shapes and are time varying, which makes their discovery extremely complicated. In addition, establishing a method to visualize and explore the traffic regions interactively still remains challenging. In this article, the authors propose a latent Dirichlet allocation (LDA)-based approach to the discovery of underlying traffic regions (or region topics) from vehicle trajectories captured by surveillance devices installed along roadsides. They treat vehicle trajectories as documents and the values of different traffic features, such as locations, directions, speeds and vehicle types, as the corresponding words. After applying the LDA model, they obtain a list of region topics with combined feature values, in which the different feature values are clustered with probabilistic assignments. Meanwhile, they build a prototype system to explore the surveillance-device-based vehicle trajectories according to the discovered region topics. The prototype system, which consists of map view, cloud view, treemap view and matrix-table view, visualizes the feature values of hidden traffic regions. The authors finally research a real case based on the traffic data in Wenzhou City, a large city in eastern China with a population of more than nine million. They investigate approximately 157 surveillance devices and 750,000 moving vehicles. The case demonstrates the effectiveness of both their proposed approach and the prototype system. © 2016 Society for Imaging Science and Technology.

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