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Among all types of computations, the polynomial function evaluation is a fundamental, yet an important one due to its wide usage in the engineering and scientific problems. In this paper, we investigate publicly verifiable outsourced computation for polynomial evaluation with the support of multiple data sources. Our proposed verification scheme is universally applicable to all types of polynomial...
State Grid Jibei Electric Power Company (Jibei) has accumulated a large number of operation data through the maintenance of the equipment, devices in power grids. It is of great significance to study this data and extract the useful information by the data mining and statistics techniques. While the theories and methods of Naive Bayes have been widely studied, this paper utilizes such technique to...
Device-to-device (D2D) communications provide a promising paradigm for data dissemination with low resource cost and high energy efficiency. In this paper, we propose a three-phase approach for D2D data dissemination, which exploits social-awareness and addresses users' incentive constraints via moneyless mechanisms. The proposed approach includes one phase of seed selection and two subsequent phases...
With the high penetration rate of smart mobile devices, it is appealing to exploit device-to-device (D2D) communications for data dissemination, e.g., in disaster alerts and event notifications. The popularity of social networks also offers good opportunities to improve the efficiency of data dissemination. Though there have been some existing works on data dissemination with D2D and mobile social...
With the rapid development and popularity of the Internet technology, more and more people like to share their feelings and experiences on the Internet. The increasing rich in network resources, such as personal blogs, online reviews, etc., provide us with new opportunities and challenges. Opinion mining is talking about how to use information technology to mining, and understand the views of others...
The high-accuracy retrieval of sea remote sensing information, such as wind field, wave height and Permittivity, is determined by the microwave scattering model at the sea surface. Thus it is meaningful to study the accurate microwave scattering characteristic of rough sea surface. Based on the current Two-Scale model, this paper modifies the model of microwave scattering from three aspects:the correction...
In this paper, we focus on student study quality evaluation in the educational system. To achieve a better performance on the teaching thinking of the students and improve teaching efficiency and learning quality, we proposed a new method based on the cloud model. The results of the experiments show that the new method is effective and operable. The application of the cloud model in the personalized...
In the era of "big data", the emergence and increasing adoptions of the related enabling technologies make it possible for Map-Reduce to accommodate DSS (Decision Support Systems) load, which is commonly targeted for high-performance Data Warehouse analyses in the context of RDBMS. However, the non-predetermined mapping of the Map-Reduce tasks to the physical machines makes it difficult...
So far, many spatio-temporal data models have been proposed in GIS and database domain, but only a few of them can be actually implemented in Cadastral Information System. In order to maintain the cadastral spatio-temporal data and make them accessible to users, many efforts have been made by academic and user communities to develop cadastral spatiotemporal data model. In this paper, we propose a...
When noise exists in data, it is a very meaningful topic to reveal the dependency between the parameter h (i.e. the threshold value used to measure degree of fit) in Fuzzy linear regression (FLR) model and the input noise. In this paper, the FLR model is first extended to its regularized version, i.e. regularized fuzzy linear regression (RFLR) model, so as to enhance its generalization capability;...
In services and cloud computing, processes need to be continually adapted to changing environments and requirements. Undisciplined process adaptation could easily lead to data flow anomalies, e.g., input missing for some activities in the process. In this paper, we study the problem of data-flow-correctness-preserving adaptation and propose three important criteria that can maintain the data flow...
Based on the micro-panel data of 116 farmer households in 28 Chinese provinces from 2001 to 2007, the paper conducts an empirical analysis of the microfinance performance in different regions. The results show that rural microfinance exerts a significant effect on raising farmers' income. However, due to regional differences, the performance varies a lot. The key factors that affect the performance,...
As two most popular wireless networks, the third generation (3G) cellular networks and wireless local area networks (WLANs) can be integrated to enhance service provisioning. However, most of the previous studies on cellular/WLAN interworking focus on WLANs in a static indoor environment such as offices, hotels, and cafes. Actually, the two heterogeneous technologies can be integrated to support mobile...
As specified by the third-generation (3G) wireless networks such as the universal mobile telecommunication system (UMTS), interactive data services, such as Web browsing, voice messaging, and file transfer, represent a major service class in operation nowadays. In this paper, we develop an analytical approach to evaluate the performance of interactive data services under sharing and preemptive scheduling...
How to reduce the number of frequent itemsets effectively is a hot topic in data mining research. Clustering frequent itemsets is one solution to the problem. Since generators are lossless concise representations of all frequent itemsets, clustering generators is equivalent to clustering all frequent itemsets. This paper proposes a new algorithm for clustering frequent itemsets based on generators...
Stock market forecasting has attracted a lot of research interests in previous literature. Traditionally, the autoregressive moving average (ARMA) model has been one of the most widely used linear models in time series forecasting. However, the ARMA model cannot easily capture the nonlinear patterns. And recent studies have shown that artificial neural networks (ANN) method achieved better performance...
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