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arXiv 2019年

作者： Xua, Gang Ling, Ran Zhang, Yongjie Jessica Xiao, Zhoufang Ji, Zhongping Rabczuk, Timon School of Computer Science and Technology Hangzhou Dianzi University Hangzhou310018 China Key Laboratory of Complex Systems Modeling and Simulation Ministry of Education Hangzhou310018 China Department of Mechanical Engineering Carnegie Mellon University United States Institute of Structural Mechanics Bauhaus-Universitat Weimar Germany

In this paper, we propose an improved singularity structure simplification method for hexahedral (hex) meshes using a weighted ranking approach. In previous work, the selection of to-be-collapsed base complex sheets/chords is only based on their thickness, which will introduce a few closed-loops and cause an early termination of simplification and a slow convergence rate. In this paper, a new weighted ranking function is proposed by combining the valence prediction function of local singularity structure, shape quality metric of elements and the width of base complex sheets/chords together. Adaptive refinement and local optimization are also introduced to improve the uniformity and aspect ratio of mesh elements. Compared to thickness ranking methods, our weighted ranking approach can yield a simpler singularity structure with fewer base-complex components, while achieving comparable Hausdorff distance ratio and better mesh quality. Comparisons on a hex-mesh dataset are performed to demonstrate the effectiveness of the proposed method. Copyright © 2019, The Authors. All rights reserved.

关键词： Aspect ratio

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Theoretical analysis and simulation of phase separation in a driven bidirectional two-lane system

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Physical Review E 2019年第3期100卷 032133-032133页

作者： Qing-Yi Hao Rui Jiang Mao-Bin Hu Yunxin Zhang Chao-Yun Wu Ning Guo Key Laboratory of Modeling Simulation and Control of Complex Ecosystem in Dabie Mountains of Anhui Higher Education Institutes School of Mathematics and Computational Science Anqing Normal University Anqing 246133 China School of Mathematical Sciences Fudan University Shanghai 200433 China MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology Beijing Jiaotong University Beijing 100044 China School of Engineering Science University of Science and Technology of China Hefei 230026 China School of Automotive and Transportation Engineering Hefei University of Technology Hefei 230009 China

The two-lane driven system is a type of important model to research some transport systems, and also a powerful tool to investigate properties of nonequilibrium state systems. This paper presents a driven bidirectional two-lane model. The dynamic characteristics of the model with periodic boundary are investigated by Monte Carlo simulation, simple mean field, and cluster mean field methods, respectively. By simulations, phase separations are observed in the system with some values of model parameters. When the phase separation does not occur, cluster mean field results are in good agreement with simulation results. According to the cluster mean field analysis and simulations, a conjecture about the condition that the phase separation happens is proposed. Based on the conjecture, the phase boundary distinguishing phase separation state and homogeneous state is determined, and a corresponding phase diagram is drawn. The conjecture is validated through observing directly the spatiotemporal diagram and investigating the coarsening process of the system by simulation, and a possible mechanism causing the phase separation is also discussed. These outcomes maybe contribute to understand deeply transport systems including the congestion and efficiency of the transport, and enrich explorations of nonequilibrium state systems.

关键词： Dynamical phase transitions Phase diagrams Phase separation Phase transitions Transport phenomena

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A credible mechanism of service about data resource in cloud computing

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International Journal of Network Security 2018年第4期20卷 754-761页

作者： Li, Yunfa Shen, Yangyang Li, Mingyi Key Laboratory of Complex Systems Modeling and Simulation School of Computer Hangzhou Dianzi University Xiasha Higher Education Zone Hangzhou Zhejiang Province310018 China

In order to protect the security of service in cloud computing, we propose a credible mechanism of service for data resource. In the mechanism, we first build a system model and put forward its implementation process. Then, we design an encryption method used in the system model. On this basis, we discuss the function of the third party trusted platform. All of these constitute a credible mechanism of service about data resource in cloud computing. In order to verify the feasibility of the mechanism, a series of experiments have been done. The experimental results show that it is feasible to ensure the security of service about data resource in cloud computing. © 2018, Femto Technique Co., Ltd.

关键词： Cryptography

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BthyDra+: Towards a Comprehensive Model to Conduct Cross-project Defect Prediction

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Journal of Computers (Taiwan) 2018年第6期29卷 52-65页

作者： Huang, Ning Fang, Jinglong Wei, Dan Chen, Bin Wang, Xingqi School of Computer Science Hangzhou Dianzi University ZheJiang Province China Key Laboratory of Complex Systems Modeling and Simulation Ministry of Education School of Computer Science Hangzhou Dianzi University ZheJiang Province China

Cross-project defect prediction (CPDP) is a field of study where researchers need to build a universal model by using within-project data to predict defects on other projects. However, variations in the distribution of source and target projects have an influence on the performance of classifiers. To enable effective cross-project defect prediction, we propose a comprehensive model containing data preprocessing and classifier transferring to construct a better classification space and strengthen the performance of classifiers. In preprocessing step, one baseline is calculated for every dataset from its non-defective samples based on the distance to all other non-defective samples and the data is transformed by using rank function. Genetic algorithm and ensemble learning are selected as the way in transferring step to extract effective representation from source projects and boost the capability of weak classifiers. We use Naive Bayes, Support Vector Machine and Classification and Regression Trees as classifiers and apply this model on five open resource projects (one Apache and four Eclipse projects) and NASA MDP dataset. Selecting accuracy as fitness in genetic algorithm improves the performance of classification. The model we proposed yields similar results and obtains higher precision comparing the within-project models. Meanwhile, it obtains better performance than the state-of-the-art methods on cross-project defect prediction. These results show that our model provides an opportunity to training classifiers by using more samples from different projects. © 2018 Computer Society of the Republic of China. All rights reserved.

关键词： Genetic algorithms

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DyCREM: Dynamic Credit Risk Management Using Edge-Based Blockchain

DyCREM: Dynamic Credit Risk Management Using Edge-Based Bloc...

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IEEE/ACM Symposium on Edge Computing (SEC)

作者： Youhuizi Li Weisong Shi Mohit Kumar Jun Chen Key Laboratory of Complex Systems Modeling and Simulation Hangzhou Dianzi University Hangzhou China Department of Computer Science Wayne State University Detroit USA Chain Oriental LLC Beijing China

ISBN: (纸本)9781538694466;9781538694459

Banks play an important role in the financial market, and their profit mainly comes from loan service. Traditional risk management approaches, as the key part in the loan services, still have several issues including low data credibility, unreliable checking and alert delay. We propose a novel dynamic credit risk management system which leverages edge-based blockchain technology to improve the performance and provide a fair loan environment. Besides, we discuss the potential challenges that the system may face, such as data standards, security on edge and scalability.

关键词： Risk management Edge computing Data models Computational modeling Real-time systems Analytical models

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Mining and measurement of vocational skills and their association rules based on big data 17

Mining and measurement of vocational skills and their associ...

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2017 International Conference on Digital Technology in Education, ICDTE 2017

作者： Wan, Jian Chen, Bin Bin Si, Huayou School of Computer Science and Technology Hangzhou Dianzi University Zhejiang China Key Laboratory of Complex Systems Modeling and Simulation Ministry of Education China

ISBN: (纸本)9781450352833

In recent years, researches on vocational skills are very extensive, most of them concentrated on vocational skills training, effect of vocational skill competition, vocational education and vocational skill identification and so on. But, there is very little research on the inner relationship among vocational skill based on big data. To address the issue, from LinkedIn we first collect tens of thousands of member profiles with vocational skills as empirical data. And then, we dig out high-frequency vocational skills and apply correlation analysis method to explore correlation characteristics of vocational skills. According to our studying, we figure out that there exist a large number of association rules, some of which have very high degrees of confidence, lift, and support. This research reveals the intrinsic association among different vocational skills. These relationships can reflect the general behavior and cognitive rules of human beings. We hope that our research results can provide a theoretical base for other research areas of vocational skills, such as vocational skill training, vocational skill mining, and identification of vocational skills. © 2017 Association for Computing Machinery.

关键词： Association rules

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A Unified Approach to Construct Generalized B-Splines for Isogeometric Applications

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Journal of systems Science & complexity 2017年第4期30卷 983-998页

作者： XU Gang SUN Ningning XU Jinlan HUI Kin-Chuen WANG Guozhao Department of Computer Science Hangzhou Dianzi UniversityHangzhou 310018China Key Laboratory of Complex Systems Modeling and Simulation Ministry of EducationHangzhou 310018China Department of Mechanical and Automation Engineering The Chinese University of Hong KongHong KongChina Department of Mathematics Zhejiang UniversityHangzhou 310027China

Abstract Generalized B-splines have been employed as geometric modeling and numerical simu- lation tools for isogeometric analysis （IGA for short）. However, the previous models used in IGA, such as trigonometric generalized B-splines or hyperbolic generalized B-splines, are not the unified mathematical representation of conics and polynomial parametric curves/surfaces. In this paper, a unified approach to construct the generalized non-uniform B-splines over the space spanned by {α（t）,β（t）,ξ（t）, η（t）, 1, t,……. , tn-4} is proposed, and the corresponding isogeometric analysis framework for PDE solving is also studied. Compared with the NURBS-IGA method, the proposed frameworks have several advantages such as high accuracy, easy-to-compute derivatives and integrals due to the non-rational form. Furthermore, with the proposed spline models, isogeometric analysis can be performed on the computational domain bounded by transcendental curves/surfaces, such as the involute of circle, the helix/helicoid, the catenary/catenoid and the cycloid. Several numerical examples for isogeometrie heat conduction problems are presented to show the effectiveness of the proposed methods.

关键词： Generalized B-splines heat conduction isogeometric analysis unified construction.

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Fine-grained image recognition via weakly supervised click data guided bilinear CNN model

Fine-grained image recognition via weakly supervised click d...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Guangjian Zheng Min Tan Jun Yu Qing Wu Jianping Fan Key Laboratory of Complex Systems Modeling and Simulation Hangzhou Dianzi University Department of Computer Science University of North Carolina at Charlotte

ISBN: (纸本)9781509060689

Bilinear convolutional neural networks (BCNN) model, the state-of-the-art in fine-grained image recognition, fails in distinguishing the categories with subtle visual differences. We design a novel BCNN model guided by user click data (C-BCNN) to improve the performance via capturing both the visual and semantical content in images. Specially, to deal with the heavy noise in large-scale click data, we propose a weakly supervised learning approach to learn the C-BCNN, namely W-C-BCNN. It can automatically weight the training images based on their reliability. Extensive experiments are conducted on the public Clickture-Dog dataset. It shows that: (1) integrating CNN with click feature largely improves the performance; (2) both the click data and visual consistency can help to model image reliability. Moreover, the method can be easily customized to medical image recognition. Our model performs much better than conventional BCNN models on both the Clickture-Dog and medical image dataset.

关键词： Reliability Visualization Image recognition Data models Training Feature extraction Computational modeling

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Deep Mixture of Experts with Diverse Task Spaces

Deep Mixture of Experts with Diverse Task Spaces

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International Conference on Machine Learning and Applications (ICMLA)

作者： Jianping Fan Tianyi Zhao Zhenzhong Kuang Zhou Yu Jun Yu Department of Computer Science UNC-Charlotte Charlotte NC USA Key Laboratory of Complex Systems Modeling and Simulation Hangzhou Dianzi University Hangzhou China

In this paper, a deep mixture algorithm is developed to support large-scale visual recognition (e.g., recognizing tens of thousands of object classes) by seamlessly combining a set of base deep CNNs (AlexNet) with diverse task spaces, e.g., such base deep CNNs (i.e., diverse experts) are trained to recognize different subsets of tens of thousands of object classes rather than the same set of object classes. Our experimental results have demonstrated that our deep mixture algorithm can achieve very competitive results on large-scale visual recognition.

关键词： Ontologies Proposals Prediction algorithms Visualization Semantics Atomic layer deposition

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BPaaS: A platform for artifact-centric business process customization in cloud computing 29

BPaaS: A platform for artifact-centric business process cust...

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29th International Conference on Software Engineering and Knowledge Engineering, SEKE 2017

作者： Gao, Min Yin, Yu Wang, Xingfei Li, Ying Chen, Zaidie Guo, Lipeng Key Laboratory of Complex Systems Modeling and Simulation of Ministry of Education College of Electrical Engineering Hangzhou Dianzi University Zhejiang China College of Computer Science Zhejiang University Zhejiang Hangzhou China College of Computer Science Fudan University Shanghai China Hangzhou Housing Management Bureaus Hangzhou Zhejiang China

ISBN: (纸本)1891706411

As a new service paradigm of Software-As-A-Service (SaaS),Business Process-As-A-Service (BPaaS). BPaaS is used to build a cost-effective Business Process Management (BPM) system. Based on universal Artifacts, we develop a framework named SeGA (Self-Guided Artifact). In SeGA, a BPM system is capable of executing business processes from multiple clients, and responding query at runtime. what's more, by the template-based cascading data mapping method, entity to be synchronized with database automatically, so each BP instance can modify its process entity without worrying about the database access. In this paper, we conduct a deep research and implement a prototype system for Artifact process design.

关键词： Process design

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