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A credible mechanism of service about data resource in cloud computing

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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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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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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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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Convolutional neural networks for intestinal hemorrhage detection in wireless capsule endoscopy images

Convolutional neural networks for intestinal hemorrhage dete...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Panpeng Li Ziyun Li Fei Gao Li Wan Jun Yu Key Laboratory of Complex Systems Modeling and Simulation Hangzhou Dianzi University School of Communication Engineering Hangzhou Dianzi University College of Computer Science Chongqing University

ISBN: (纸本)9781509060689

Wireless capsule endoscopy (WCE) can painlessly capture a large number of images inside the intestine. However, only a small portion of these WCE images contain hemorrhage. It is thus critical to develop automated hemorrhage detection method to facilitate the diagnosis of intestinal diseases. However, automated hemorrhage detection is complicated by 1) the extreme imbalance between the amount of hemorrhage images and that of normal images; and 2) the variety of the appearance, texture, and luminance inside the intestine. In this paper, we proposed to learn a robust intestinal hemorrhage detection model via Convolutional Neural Networks (CNNs), because of CNNs' extraordinary performance in solving various image understanding tasks. Specially, we explored different CNN architectures and data augmentation methods. Besides, we investigated the correlation between hemorrhage detection accuracy and image quality. Across about 1.3k hemorrhage images and 40k normal images, the learned CNN model achieves an F-measure of 98.87%.

关键词： Hemorrhaging Optical wavelength conversion Endoscopes Machine learning Biomedical imaging Training Wireless communication

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Discovering and visualizing underlying tra-c regions from vehicle trajectories withmulti-features

Discovering and visualizing underlying tra-c regions from ve...

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Video Surveillance and Transportation Imaging Applications 2016

作者： Yu, Dongjin Wang, Ruiting Wang, Jiaojiao Li, Wanqing College of Computer Hangzhou Dianzi University Hangzhou China Key Laboratory of Complex Systems Modeling and Simulation Ministry of Education China

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.

关键词： Population statistics

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Using density peaks sentence clustering for update summary generation

Using density peaks sentence clustering for update summary g...

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2016 IEEE Canadian Conference on Electrical and computer Engineering, CCECE 2016

作者： Wu, Guohua Guo, Yutian Key Laboratory of Complex Systems Modeling and Simulation Ministry of Education School of Computer Science and Technology Hangzhou Dianzi University China

ISBN: (纸本)9781467387217

Update summarization can be a daunting task in automatic text summarization. It aims to distill evolved messages from a collection of new articles, under the assumption that the reader has already browsed the previous articles. In this paper, a number of state-of-the-art approaches were reviewed for extracting update summarization and then a method called DPC-TS was proposed. This approach is derived from the DPC-based multi-documents summarization method, which was developed in 2015. In our study, a model was established by using the topic signature algorithm, to evaluate the novelty of sentences in update documents set. In addition, the scheme of calculating similarities between sentences and sentence selection approach was improved to ensure there are diversity topics in the summary. DPC-TS update documents summarization method is a simple and effective approach, which can be reproduced and deployed in real environment. © 2016 IEEE.

关键词： update summarization DPC topic signature dedicated physical channel signature algorithm Novelty Adjudication peaks

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