NoSQL databases are famed for the characteristics of high scalability, high availability and high fault-tolerance. So NoSQL databases are used in a lot of applications, especially in the Internet Applications. The com...
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ISBN:
(纸本)9781450328104
NoSQL databases are famed for the characteristics of high scalability, high availability and high fault-tolerance. So NoSQL databases are used in a lot of applications, especially in the Internet Applications. The computing model of the NoSQL database is transferred fromdata close to computing to computing close to data. So the data partition strategy and fragment allocation strategy directly affect the load balance of the system. We can not play the advantages of the NoSQL database when the load of the system is unbalance. This paper will analyze the problem of fragment allocation strategy in NoSQL databases, and analyze the strategy how affecting the load balance of system. Then we will propose the load-aware fragment allocation strategy (LAFAS) to improve the load balance of the system. At last we will use some experiments to verify the effectiveness of LAFAS which is proposed in this paper. Copyright 2014 ACM.
Original public-key encryption is viewed as a tool to encrypt point-to-point *** data is aimed at a particular user,where a sender encrypts a message x under a specified public key P *** this case,only the owner of th...
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Original public-key encryption is viewed as a tool to encrypt point-to-point *** data is aimed at a particular user,where a sender encrypts a message x under a specified public key P *** this case,only the owner of the(unique)secret key corresponding to P K can decrypt the resulting ciphertext to recover the message ***,on some occasions,encryption is necessary to implement more fine-grained control of the encrypted *** example,the sender
作者:
Chen HuangMing JiangTingting JiangLMAM
School of Mathematical Sciences Beijing International Center for Mathematical Research and Cooperative Medianet Innovation Center Peking University Beijing 100871 China NELVT
National Engineering Laboratory for Video Technology School of Electronics Engineering and Computer Science and Cooperative Medianet Innovation Center Peking University Beijing 100871 China
Image Quality Assessment (IQA) is a fundamental problem in image processing. It is a common principle that human vision is hierarchical: we first perceive global structural information such as contours then focus o...
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Image Quality Assessment (IQA) is a fundamental problem in image processing. It is a common principle that human vision is hierarchical: we first perceive global structural information such as contours then focus on local regional details if necessary. Following this principle, we propose a novel framework for IQA by quantifying the degenerations of structural information and region content separately, and mapping both to obtain the objective score. The structural information can be obtained as contours by contour detec- tion techniques. Experiments are conducted to demonstrate its performance in comparison with multiple state-of-the-art methods on two large scale datasets.
This paper proposes a mobile charging algorithm for mobile charging vehicles based on WRSNs, which uses network non-uniform clustering and low energy consumption path selection to perform reasonable charging schedulin...
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We examine the bulk electronic structure of Nd3Ni2O7 using Ni 2p core-level hard x-ray photoemission spectroscopy combined with density functional theory + dynamical mean-field theory. Our results reveal a large devia...
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The world indicators released by the World Bank or other organizations usually give the basic public knowledge about the world. However, separate and static index lacks the complex interplay among different indicators...
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To offer relevant and useful recommendations, the crucial role of recommender systems in e-commerce industry is to predict the users’ concern for various items by estimating items’ attributes and users’ preferences...
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To offer relevant and useful recommendations, the crucial role of recommender systems in e-commerce industry is to predict the users’ concern for various items by estimating items’ attributes and users’ preferences. The reliability of a recommender system is usually assessed through accuracy and speed of relevant recommendations for a variety of items. The matrix factorization-based stochastic gradient descent (SGD) methods proposed by researchers lack memory needed to capture the ratings history hidden in the previous iterations. Recently, sliding window-based SGD strategies designed for Recommender systems and Hammerstein nonlinear systems gained attention due to the improved performance in terms of convergence speed and estimated accuracy. The memory impact with regard to the historical information enhances the performance of sliding window-based SGD techniques. However, sliding window-based methods are deficient in capturing the ratings history based on the users’ rating patterns. Hence utilizing the same window length for the set of observed ratings rated by users. Therefore, we propose an improved sliding window-based SGD strategy to acquire historical information of the ratings with respect to a user’s rating patterns for efficient matrix factorization of recommender systems. The proposed strategy performs significantly by accomplishing fast convergence speed and accuracy for window sizes greater than 1. The accuracy of the suggested technique is verified for two benchmark datasets such as ML-100 K and Film-Trust. However, the authenticity of the proposed method as compared to the standard counterpart (window size = 1) is confirmed through Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). The average improvements achieved by the proposed strategy in terms of RMSE and MAE over the baseline for ML-100 K dataset are 0.726% and 2.245% respectively. Whereas the proposed method accomplishes considerable average improvement of 7.89% and 9.41% for RMSE an
The discipline of component-based modeling and simulation offers promising gains including reductions in development cost, time, and system complexity. This paradigm promotes the use and reuse of modular components fo...
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Recognizing the fruit is a critical function to achieve for an autonomous harvesting system. Since fruit commonly grows in complex environments, it is challenging for the vision system to accurately identify the fruit...
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