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Big data, which is maturing over time, has a high impact in analyzing scenarios and coming up with decision making strategies pertaining to any sector. Consequently the number of applications are also increasing where in the past, they were limited to the confines of company sales departments. In lieu, this paper is primarily focused on applying Data Sciences within the education sector. We will be...
Quantitative research has been extensively applied in sociology. The traditional way of using data statistical computing tools of R, SPSS and Stata on the stand-alone machine can't deal with the challenges of big data; furthermore, the demand of complex computing in mobile condition is increasing due to the fieldwork characteristics of sociological researchers. Considering the computing needs of sociological...
This paper takes a blended course as an example in moodle platform. As a case study, multiple methods including statistical analysis, visualization and social network analysis were used to analyze the process and results of online learning. With the concept of Big Data, it analyzes 22 classes of 1088 students and teachers from a comprehensive perspective. It includes the access behavior, resource...
Women are active in the field of scientific research today. A large number women scientific talents have made outstanding contributions to the progress of science and technology. Female academicians of Chinese Academy of Science (CAS) and Chinese Academy of Engineering (CAE) stand as perfect examples of high-end female scientific talents. Taking female academicians as an example, some characteristics...
This paper analyses the main work of equipment support from three aspects of the equipment life-cycle, support object and support work, analyses the main data and data source from the equipment life-cycle systematically, discusses the four main features of high capacity, diversification, rapidity and low density of the data in the field of equipment support, analyses the existing problems in the construction...
In big data environment, the key of smart tourism information system is the method of semantic description and link construction to complete intensive, intelligent and unified management of tourism. We proposed a hierarchical semantic description framework of tourism Linked Data, which consists of 4 layers: Metadata Layer, Ontology Layer, Linked Data Layer, Data application Layer. Main roles of these...
The healthcare industry is changing at a dramatic rate. There are multiple processes going on within the health sector. These processes not only impact the care of individuals but also help medical practitioners and the delivery of care and services. The industry can take advantage of big data analytics to ensure that all the multiple processes within the industry are running smoothly. Big data analytics...
Dimensionality reduction of big data is becoming more and more important in many domains, such as cloud computing, human gene distribution, image processing and smart grids, which all involve high-dimensional data analysis. While traditional linear dimensionality reduction techniques are computationally efficient and simple to implement, they fail to adequately capture the intrinsic structure of complex...
Keyword search in relational databases provides a simple and interactive query interface for retrieving data from databases. In recent year's keyword search over structured or unstructured data received significant attention. KWS performs on enterprise applications based on various forms which can take some values, these values might be express verifiable, for example user identification. A large...
Expression image is depended on analyzing and studying about emotions based on expression recognition technology. However, in-depth research of emotional analysis cannot be supported because of the limited sample size, the shot scene set in constrained environment like laboratory and image with simple labeling expression information. In order to solve these issues, LDA learning emotion database is...
With the increase of network bandwidth and the popularity of Internet, cloud storage has become one of the most widely used of cloud computing. Since the user may have a variety of terminal such as PC, notebook computers, tablet PCs and smart phones, and may access data in different places and on different terminal, cloud storage provides the most suitable solution to share data between these devices...
Existing conventional RAID storage systems are unable to provide expected storage performance under the explosive growth in data volumes. One of the solution is introducing SSDs (Solid State Drives), a promising storage medium which provides high performance and power efficiency, as a cache to loosen the performance bottleneck of RAID storage systems. However, using DRAM as a universe buffer area...
Based on research and analysis of the Ceph file system, the log cache backup scheme is proposed. The log cache backup scheme reduces metadata access delays by caching logs and reducing the time of storing logs to server clusters. In order to prevent the loss of cached data in metadata servers, a cached data backup scheme is proposed. Compared to the metadata management subsystem of the Ceph, the log...
Knowledge discovery from data using clustering algorithm include stages of data preprocessing, clustering the preprocessed dataset and evaluating patterns for obtaining knowledge. Along with the popularity of Hadoop, k-Means algorithm has been enhanced based on MapReduce for clustering big dataset. We enhance this existing algorithm such that it includes the capabilities for performing data preprocessing,...
Spatial data is different from the general data, it not only contains some kind of property information of space feature, but also has the spatial feature of space or location. The spatial clustering analysis can be divided into two broad categories. Category from GIS theory and technology tools, according to an object of spatial geographical coordinates, cluster as an object of the spatial proximity...
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