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International Conference on 3D Imaging (IC3D)

作者： Xiaohua Zheng Yuzhen Niu Junhao Chen Yuzhong Chen College of Mathematics and Computer Science Fuzhou University Fujian Provincial Key Lab of the Network Computing and Intelligent Information Processing Fujian China

Stereoscopic 3D (S3D) image color correction is a major issue in the field of image processing. However, existing color correction algorithms have limitations. Global color correction algorithms cannot handle local color discrepancies, and local color correction algorithms are sensitive to matching quality between reference and target images. In this study, we propose an S3D image color correction algorithm that combines global and local color information to correct color discrepancies between S3D images. Sparse feature matching usually generates only a few matching features, producing error correction results in some local regions. Our algorithm uses dense stereo matching and global color correction algorithms to initialize color values, and improves the local color smoothness and global color consistency of the resulting image, while maintaining the initial color in that image as much as possible. Experimental results show that our algorithm performs better than do five state-of-the-art color correction algorithms.

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Anisotropic energy accumulation for stereoscopic image seam carving

Anisotropic energy accumulation for stereoscopic image seam ...

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International Conference on 3D Imaging (IC3D)

作者： Yuqing Lin Yuzhen Niu Shuai Zhang Junhao Chen College of Mathematics and Computer Science Fuzhou University Fujian Provincial Key Lab of the Network Computing and Intelligent Information Processing Fujian China

Seam carving is an image resizing method that aims at adapting the image to various display screens while reducing the distortion as much as possible. Severe visual distortion may be introduced by repeated removal or insertion of seams within a concentrated region of the image. To reduce such visual distortion, we propose a new AESSC method. First, we distribute the energy of each pixel on the seam to its adjacent 8-connected pixels when removing or inserting a seam. Second, since the information of each pixel is anisotropic, we use the Sobel operator to detect the direction that has the maximum edge information and continue the energy accumulation along this direction. Besides, we incorporate a 3D structure consistency constraint in the energy function and adopt a pixel visibility maintenance method. Experimental results show that the proposed method can effectively reduce visual distortion for stereo images while maintaining the geometric consistency.

关键词： Distortion Visualization Three-dimensional displays Stereo image processing Image edge detection Histograms Maintenance engineering

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Semantic keyword searchable proxy re-encryption for postquantum secure cloud storage

Semantic keyword searchable proxy re-encryption for postquan...

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作者： Yang, Yang Zheng, Xianghan Chang, Victor Tang, Chunming College of Mathematics and Computer Science Fuzhou University Fuzhou350108 China Fujian Province University Key Laboratory of Information Security of Network Systems Fuzhou University Fuzhou350108 China Key Laboratory of Information Security School of Mathematics and Information Science Guangzhou University Guangzhou510006 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou350121 China IBSS Xian Jiaotong-Liverpool University Suzhou215123 United Kingdom

With the advent of cloud computing, more and more consumers prefer to use the cloud services with the pay-as-you-consume mode. The cloud storage brings about great convenience to users, who store data in cloud and access to it using the smart devices anytime and anywhere. Consumers' information should be encrypted to guarantee the data privacy. Flexible searching on ciphertext is a critical challenge to be solved for effective data utilization. In this paper, we propose a novel semantic keyword searchable proxy re-encryption scheme for secure cloud storage. A highlight of this work is that the scheme is quantum attack resistant, while most of the available searchable encryption schemes are not. It supports not only exact keyword search but also synonym keyword search. Moreover, the data owner is capable to delegate his search right to another user using the proxy re-encryption mechanism. In the generation process of re-encryption key, the delegator and delegatee do not need to be interactive with each other. The scheme is also collusion resistant. Under the learning with errors hardness problem, this scheme is proved secure in standard model. Copyright © 2017 John Wiley & Sons, Ltd.

关键词： Semantics

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An Energy Efficient VM Migration Algorithm in Data Centers

An Energy Efficient VM Migration Algorithm in Data Centers

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2017 16th International Symposium on Distributed computing and Applications to Business,Engineering and Science（DCABES 2017）

作者： Xiaodong Wu Yuzhu Zeng Guoxin Lin Faculty of Mathematics and Computer Science Quanzhou Normal University Fujian Provincial Key Laboratory of Data Intensive Computing Key Laboratory of Intelligent Computing and Information ProcessingFujian Province University

In order to reduce operation and maintenance expense and also increase the resource utilization rate,server consolidation and virtualization solutions have been adopted in modern cloud computing data ***,the scheduling policies of virtual machine（VM） migration have been regarded as an effective method for energy *** this paper,we address the problem of VM consolidation in cloud data centers.A power aware scheduling algorithm THRUG,which is combined with a utilization threshold strategy and a VM selection policy,is *** tries to select the most appropriate VMs for migration each time when a physical machine（PM） is considered as being overloaded,such that the utilization of this PM is just not more than the utilization threshold,such that both the energy consumption and the number of VM migration can be *** experimental results show that compared with other algorithm,the proposed algorithm can effectively reduce the number of VM migrations as well as the energy consumption.

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A parallel evolutionary extreme learning machine scheme for electrical load prediction

A parallel evolutionary extreme learning machine scheme for ...

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Science and information Conference (SAI)

作者： Peikun Chen Wanhua Li Yuzhong Chen Kun Guo Yuzhen Niu College of Mathematics and Computer Science Fuzhou University Fuzhou Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou University Fuzhou Fujian Collaborative Innovation Center for Big Data Applications in Governments Fuzhou Fuzhou China

ISBN: (纸本)9781509054442

Application of cloud computing technologies in power system has made a great contribution to the establishment of smart grid. Among applications of smart grid, electrical load prediction plays an important role in efficient use of power resource. However, the exponential growth of data has posed a great challenge to the existing algorithms. In this paper, we firstly propose a novel parallel hybrid algorithm, combining the Improved Particle Swarm Optimization (PSO) with ELM, named PIPSO-ELM. Here a modified particle swarm optimization is presented to find the optimal number of hidden neurons as well as the corresponding input weights and hidden biases. Furthermore, in the iterative search process of PSO, an update strategy employs the mutation operator of evolutionary algorithms is introduced for further improving the global search capability and convergence speed of PSO. After that, to handle the large-scale dataset efficiently, the parallel implementation of PIPSO-ELM is achieved using Spark. Finally, extensive experiments on real-life electrical load data and comprehensive evaluation are conducted to verify the performance of PIPSO-ELM in electrical load prediction. Extensive experimental results demonstrate that PIPSO-ELM outperforms the compared algorithms in terms of stability, efficiency and scalability simultaneously.

关键词： Neurons Particle swarm optimization Algorithm design and analysis Prediction algorithms Smart grids Encoding Convergence

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Interest prediction in social networks based on Markov chain modeling on clustered users

Interest prediction in social networks based on Markov chain...

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作者： Zheng, Xianghan An, Dongyun Chen, Xing Guo, Wenzhong College of Mathematics and Computer Science Fuzhou University Fuzhou China Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou China

Effective user interest prediction is significant for service providers in a set of application scenarios such as user behavior analysis and resource recommendation. However, existing approaches are either incomplete or proprietary. In this paper, user interest prediction based on the Markov chain modeling on clustered users is proposed with the following procedure: collect dataset from 4613 users and more than 16 million messages from Sina Weibo;obtain each user's interest eigenvalue sequence and establish single-Markov chain model;and implement user clustering algorithm for the multi-Markov chain construction in order to divide users into a set of predefined interest categories. The proposed solution is capable of predicting both long-term and short-term user interests based on a suitable selection of the initial state distribution, λ. The proposed solution also proves that short-term interests are consistent with long-term interests if the influences of social or user-related events that cause interruptions (e.g., earthquake and birthday) are not considered. Furthermore, experiments show that the proposed solution is feasible and efficient and can achieve a higher accuracy of prediction than that of the other approaches such as Support Vector Machine (SVM) and K-means. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

关键词： Clustering algorithms

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Model-Driven Approach to Hadoop Deployment in Cloud

Model-Driven Approach to Hadoop Deployment in Cloud

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IEEE International Conference on Mobile Cloud computing, Services, and Engineering (MobileCloud)

作者： Zheyi Chen Tao Xiang Xing Chen Department of Computer Science and Technology Tsinghua National Laboratory for Information Science and Technology (TNLIST) Beijing China College of Mathematics and Computer Science Fujian Provincial Key Laboratory of Networking Computing and Intelligent Information Processing Fuzhou China

Due to the diversification of software and hardware resources in cloud and ever-changing demand for deployment, Hadoop deployment is faced with great challenges in difficulty and complexity. Most of present researches lie in environment configuration and parameter setting of deployment, they do not take into account diversification of infrastructure and scalability issues in cloud. In order to quickly customize, deploy and expand Hadoop services according to the demand, a model-driven approach to Hadoop deployment is proposed in the paper. Firstly, Hadoop demand and deployment models are presented. Secondly, the transformation method from the demand model to the deployment model is proposed. Thirdly, the bidirectional synchronization between Hadoop deployment model and running system is realized based on runtime model.

关键词： Computational modeling Runtime Cloud computing Synchronization Virtual machining

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Online optimization scheduling for scientific workflows with deadline constraint on hybrid clouds

Online optimization scheduling for scientific workflows with...

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作者： Lin, Bing Guo, Wenzhong Lin, Xiuyan School of Mathematics and Computer Science Fuzhou University Fuzhou350116 China Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou350116 China

The tremendous parallel computing ability of cloud computing encourages investigators to research its drawbacks and advantages on processing large-scale scientific applications such as workflows. The current cloud market is composed of numerous diverse public clouds and a local private cloud, and workflow scheduling is one of the biggest challenges on hybrid clouds due to the highly fragmented cloud market with respect to service provisions, pricing models, and bandwidths. In this paper, we propose an online-scheduling strategy for continuous submitted scientific workflows on hybrid clouds, which aims to complete the deadline-constrained applications as more as possible at a lower price. Firstly, a hierarchical iterative application partition (HIAP) algorithm is proposed to partition the application into a set of dependent tasks. Moreover, many online-scheduling algorithms cooperated with HIAP are presented to finish the workflows with a low average payment. Our strategy takes into account the basic characteristics on hybrid clouds such as bandwidth constraints, data transfer cost and computational cost. Various well-known workflows are used for evaluating the multiple scheduling algorithms and the results show that the MLF_ID approach can achieve a promising performance. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

关键词： Data transfer

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Design and Realization of MATLAB-based Face Recognition System

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Journal of Physics: Conference Series 2018年第6期1087卷

作者： JianMing Liu College of Mathematics and Computer Science Quanzhou Normal University Quanzhou 362000 Fujian P. R. China Key Laboratory of Intelligent Computing and Information Processing Fujian Province University Quanzhou Normal University Quanzhou 362000 Fujian P. R. China

Through MATLAB, the paper makes a comparison between Principal Component Analysis (PCA)face recognition algorithm and Adaboost recognition algorithm and selects the algorithm with higher recognition rates to develop an auto face recognition system. The paper explicates primary techniques the system adopts and its specific realization process. By downloading face database online, the paper conducts an all-round test to the system, the result of which proves that this face recognition system is completely practical and feasible.

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Analysis of smart glucose meter stability from the economic perspective

Boletin Tecnico/Technical Bulletin

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Boletin Tecnico/Technical Bulletin 2017年第9期55卷 457-462页

作者： Lin, Zhongyan Song, Libin Zheng, Dachuan Li, Zuoyong Internet Innovation Research Center College's Research Base of Humanities and Social Science in Fujian Province Minjiang University Fuzhou Fujian350108 China Fuzhou Digital Health Industry Technology Innovation Center Minjiang University Fuzhou Fujian350108 China Fuzhou Comvee Network Technology Co. Ltd. Fuzhou Fujian350001 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou Fujian350108 China

Objective: to explore and interpret the model of diabetes mobile online management from the perspective of web model. Methods: from the interdisciplinary perspective, combined with economics, management science and computer science, with the only dynamic model in microeconomics—the cobweb model, from chronic disease management, Internet + medical application, analyze the application of Internet technology in diabetes management. Results: through mobile Internet technology, optimized the unit of diabetes management and realized the "monitoring - assessment - intervention" closed-loop management. Conclusion: explore the digital medical health industry in periodic production commodity price fluctuations and other activities, can establish early warning system and mechanism, to improve patients and their families to the cognitive level of diabetes, according to the medical behavior and self management ability.

关键词： Medical applications

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