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Medical institutes use Electronic Medical Record (EMR) to record a series of medical events, including diagnostic information (diagnosis codes), procedures performed (procedure codes) and admission details. Plenty of data mining technologies are applied in the EMR data set for knowledge discovery, which is precious to medical practice. The knowledge found is conducive to develop treatment plans, improve...
In open and distance education field, making use of data mining technologies to understand students' practical needs and usage habits about professional courses, which will greatly enhance students learning. China Open University system is Chinese largest scale organization engaging in open and distance education, and it has taken Chinese education ministry's a rural education project, called "one...
The rapid development of financial markets make the financial data variability and unpredictability, the abnormal fluctuations in financial data often contain important information. Financial data is generated over time, so the time series mining method widely used in the financial data of anomaly detection. The traditional time series of anomaly detection method is to find out one of the biggest...
The paper proposes a cloud-based framework to abstract and analyze the meaningful rules among great amount of students' raw information. The authors abstract a set of learning skills based on the course outline from The Open University of China. The authors also present a cloud-based Apriori association algorithm to abstract the rules, followed by a reasonable analysis on educational aspect supported...
Secure and efficient data storage and computation for an outsourced database is a primary concern for users, especially with the push for cloud computing that affords both compute and resource scalability. Among the diverse secure building blocks for secure analytical computations on outsourced databases, the encrypted set intersection operation extracts common sensitive information from datasets...
By allowing the estimation of forest structural and biophysical characteristics at different temporal and spatial scales, remote sensing may contribute to our understanding and monitoring of planted forests. In this paper, we used multi-temporal data from Landsat TM to investigate 9-year time-series of the Normalized Difference Vegetation Index (NDVI) in Dongying city, Shandong province, China. According...
This paper uses GMDH method to establish a prediction model to forecast the vehicles for business transport of Guangxi in China, since the original samples of the output value of transport & storage of Guangdong are less enough to be used with the traditional methods. Compared with traditional linear regression and artificial neural network, the predicted results show that GMDH method is an effective...
Web mining focuses on extracting useful information from large volumes of Web data. Web usage mining (WUM) is one of important application which applies Web mining techniques to discovery usage patterns from Web accessing data. Meanwhile clustering performs a key role in distinguishing different kinds of usage patterns from raw data. Considering usage features of activities, information scope and...
This paper uses GMDH method to establish a prediction model to forecast the number of civil vehicles owned in Guangxi, since the original samples of the civil vehicle population of Guangxi are less enough to be used with the traditional methods. Compared with traditional linear regression and artificial neural network, the predicted results show that GMDH method is an effective way to predict car...
The Web service resource framework (WSRF) announced in January 2004 is a new mechanism to express how web services interact with the stateful resources, and it has achieved the fusion of Web services and grid services. For the grid application development, WSRF.NET is much easier than Globus Toolkit 4 and it is based on Windows. As WSRF.NET doesn't provide an available scheduler, we introduce Condor...
This article gives a detailed description of the Condor system-a distributed scheduler. A typical Condor system consists of four components: A Condor pool, the central manager, submitting machine and execution machine. The ClassAd is a flexible representation of the characteristics and constraints of both machines and jobs in the Condor system. Matchmaking is the mechanism by which Condor matches...
In case that the traffic resource is limited, cross-border traffic has great impact on urban transportation, and it is necessary for us to study characteristics of Lanzhou cross-border traffic network. In this paper, the characteristics of cross-border traffic network are studied from different aspects based on the theory of complex network. Results show that Lanzhou cross-border traffic network has...
The classification of network users is very important in user behavior analysis. The algorithm which was based entropy and latent Dirichlet allocation (LDA) was used in this paper. It is important but difficult to select an appropriate number of topics for a specific dataset. Entropy was first used to solve the problem. A concept named difference-entropy was built to determine the number of topics...
The time based feature facilitates the new opportunity to understand the network user behaviors. Research on user behavior patterns varying with time is a hot point recently. In multi-dimensional mining of user profiles, time division contributes to decline the complexity of data process. Time division consistent with user on-line regularities is significant to obtain accurate user behavior information...
In typical SOA, three parties interact with each other in the simple request-reply style by SOAP message which follows inherent drawbacks, for example, lower ratio of successful service-invoking for the simply disposal before the failure of interaction. In this paper, we try to improve the performance of the interaction among the three parties by argumentation skills. We represent the defeasible logic...
Hand-based identification have developed very recently. This paper proposes a recognizing method for defocused palmprint images using 2DPCA. In order to achieve the purpose of intercepting region of interest (ROI) of palmprint under contactlass mode, we used profile information of palm and root of fingers situations to locate characteristic points of contour. Next, the palmprint features were extracted...
Because of the complexity and polytropism of rock and the complexity of blasting proceeding, it is very difficult to obtain better blasting parameters with a certain way. In order to gain perfect blasting effects expected by designers, blasting engineers have been studying the optimizing of blasting parameters all the time. The intelligent optimizing model of blasting parameters based on fuzzy neural...
In order to evaluate the goodness of frequency hopping sequence design, the periodic Hamming correlation function is used as an important measure. Usually, the length of correlation window is shorter than the period of the chosen frequency hopping sequence, so the study of the periodic partial Hamming correlation of frequency hopping sequence is particularly important. In this paper, the periodic...
For odd prime p, two new p-ary sequence families with period pn-1 are constructed for odd n=2l+1=me and even n=2l=me respectively. It is shown that, for a given integer rho, the proposed sequence families have maximum correlation 1+pn/2+(rho-1)e+1, family size (pn-1)pnrho/2, and maximum linear span n(n+3).
GPSR-BB (Gradient Projection for Sparse Reconstruction) algorithm is a popular CS (compressed sensing) reconstruction method. lt performs well for questions which have sparse solution. This approach is originally developed in the context of unconstrained minimization of a smooth nonlinear function F, and it uses the search direction of the Quasi-Newton method. So its shortcomings is the same as the...
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