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Search Results: 1 - 10 of 14227 matches for " data "
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Research of Big Data Based on the Views of Technology and Application  [PDF]
Zan Mo, Yanfei Li
American Journal of Industrial and Business Management (AJIBM) , 2015, DOI: 10.4236/ajibm.2015.54021
Abstract: In the era of big data, large amounts of data affect our work, life and study, even national economic development. It provides a new way of thinking and approaches to analyze and solve problems, which gradually becomes a hot research. Based on describing the concept and characteristics of big data, this paper describes the development of technologies in big data analysis and storage and analyses the trends and different values in commercial applications, manufacturing, biomedical science and other applications. At last, the authors sum up the existent challenges of big data applications and put forward the view that we should deal with big data challenges correctly.
Data Modeling and Data Analytics: A Survey from a Big Data Perspective  [PDF]
André Ribeiro, Afonso Silva, Alberto Rodrigues da Silva
Journal of Software Engineering and Applications (JSEA) , 2015, DOI: 10.4236/jsea.2015.812058
Abstract: These last years we have been witnessing a tremendous growth in the volume and availability of data. This fact results primarily from the emergence of a multitude of sources (e.g. computers, mobile devices, sensors or social networks) that are continuously producing either structured, semi-structured or unstructured data. Database Management Systems and Data Warehouses are no longer the only technologies used to store and analyze datasets, namely due to the volume and complex structure of nowadays data that degrade their performance and scalability. Big Data is one of the recent challenges, since it implies new requirements in terms of data storage, processing and visualization. Despite that, analyzing properly Big Data can constitute great advantages because it allows discovering patterns and correlations in datasets. Users can use this processed information to gain deeper insights and to get business advantages. Thus, data modeling and data analytics are evolved in a way that we are able to process huge amounts of data without compromising performance and availability, but instead by “relaxing” the usual ACID properties. This paper provides a broad view and discussion of the current state of this subject with a particular focus on data modeling and data analytics, describing and clarifying the main differences between the three main approaches in what concerns these aspects, namely: operational databases, decision support databases and Big Data technologies.
Seismic Data Collection with Shakebox and Analysis Using MapReduce  [PDF]
Bin Tang, Jianchao Han, Mohsen Beheshti, Garrett Poppe, Liv Nguekap, Rashid Siddiqui
Journal of Computer and Communications (JCC) , 2015, DOI: 10.4236/jcc.2015.35012

In this paper we study a seismic sensing platform using Shakebox, a low-noise and low-power 24- bit wireless accelerometer sensor. The advances of wireless sensor offer the potential to monitor earthquake in California at unprecedented spatial and temporal scales. We are exploring the possibility of incorporating Shakebox into California Seismic Network (CSN), a new earthquake monitoring system based on a dense array of low-cost acceleration seismic sensors. Compared to the Phidget/Sheevaplug sensors currently used in CSN, the Shakebox sensors have several advantages. However, Shakebox sensor collects 4K Bytes of seismic data per second, giving around 0.4G Bytes of data in a single day. Therefore how to process such large amount of seismic data becomes a new challenge. We adopt Hadoop/MapReduce, a popular software framework for processing vast amounts of data in-parallel on large clusters of commodity hardware. In this research, the test bed-generated seismic data generation will be reported, the map and reduce function design will be presented, the application of MapReduce on the testbed-generated data will be illustrated, and the result will be analyzed.

Data Mining of Historic Hydrogeological and Socioeconomic Data Bases of the Toluca Valley, Mexico  [PDF]
Oliver López-Corona, Oscar Escolero Fuentes, Eric Morales-Casique, Pablo Padilla Longoria, Tomás González Moran
Journal of Water Resource and Protection (JWARP) , 2016, DOI: 10.4236/jwarp.2016.84044
Abstract: In this paper we used several data mining techniques to analyze the coevolution of hydrogeological and socioeconomical data for the Toluca Valley in Mexico. We found non trivial relations between two historic data bases that make clear that groundwater and economy may be much more linked than it was thought before. In particular, we found that hydrogeological data trends change during economical crisis and election years in Mexico. This shows that different macroeconomical policies implemented by several administrations have a direct impact in the way groundwater is used. We also found that hydrogoelogical data evolve in the direction of population transformation from rural to urban, which could represent a whole paradigm shift in groundwater management with profound repercussions in policy making.
The New Trend and Application of Customer Relationship Management under Big Data Background  [PDF]
Lan Wang
Modern Economy (ME) , 2016, DOI: 10.4236/me.2016.78087
Abstract: One of the important trends of marketing management is digitization. The concept of digitization has been imported to many fields and is well known to everyone. However, because of the limitation of digitization’s meaning and expansion, companies have different understandings of it. The meaning of the digital CRM is a digital customer experience that is specially built and customer-oriented. It is a business reform that improves value creation. Current companies not only focus on the effects brought by technologies, but also focus on how the digital business mode makes profits. This article explains the evolution of marketing management from traditional CRM to analytical CRM to digital CRM. Based on the characteristics of digital CRM, we discussed the new trend and application of CRM.
Research on Personal Privacy Protection of China in the Era of Big Data  [PDF]
Hui Zhao, Haoxin Dong
Open Journal of Social Sciences (JSS) , 2017, DOI: 10.4236/jss.2017.56012
Abstract: The purpose of this essay is to investigate the privacy concerns of Chinese, and to develop relevant protective measures. The groups are divided into two parts by gender and six parts by ages to analyze the different gender and different age groups of privacy concerns. The significance of this study is protecting personal data property. The data of personal information after finishing processing have economic value. These data once disclosed, will be not reversible, so it is important to study the personal privacy in the era of big data and to initiate and enforce legal and regulatory protection measures. Results show that Chinese’s privacy in public places for Internet records, friends dynamic and age’s awareness is insufficient; most people especially female lack privacy protection skills. Educators need to improve the relevant laws and regulations, promote privacy protection skills and strengthen the conception of privacy.
Precise Forecast and Application of Time Delay Receiving Schedule for a New Generation of Polar Orbit Meteorological Satellite  [PDF]
Zhaohui Cheng, Manyun Lin, Cunqun Fan
Journal of Geographic Information System (JGIS) , 2018, DOI: 10.4236/jgis.2018.101006
Abstract: In order to finely predict the receiving schedule of the new generation of polar orbit meteorological satellite time-delay data and solve the problem of rapid positioning of lost data, this paper studies and proposes the satellite data recording and satellite program-controlled program, and designs the delay data receiving timeline precision forecasting method. It is concluded that the detection load of polar orbit meteorological satellite in our country has developed from single load to multiple loads, and the detection data need to be downloaded to the ground for processing and application. And as the satellite load increases and the accuracy of each payload detection and channel increases, the amount of probing data will further increase, which in turn will require further increase of the speed of data transmission in the earth. Due to the limitation of the space data transmission frequency band, under the prior art system, the increase of the satellite data transmission rate is limited. On the basis of understanding the working principle of Fengyun-3, the new transmission system will be implemented in terms of data source compression, channel coding, modulation and polarization multiplexing by exploring new weather transmission systems for meteorological satellites in the future upgrade and at the same time analyze ways to avoid inter-satellite interference in order to solve the contradiction between the increase of data volume and the resource of terrestrial data transmission in the existing system.
Solutions for 3 Security Problems and its Application in SOA-FCA Service Components Based SDO  [PDF]
Nannan Wang, Zhiyi Fang, Kaige Yan, Yu Tang, Xingchao An
Int'l J. of Communications, Network and System Sciences (IJCNS) , 2010, DOI: 10.4236/ijcns.2010.310109
Abstract: Service-Oriented Architecture (SOA), which is an open architecture, provides developers with more freedom. However, its security problem goes from bad to worse. By taking an insurance business in Formal Concept Analysis (SOA-FCA) Service Components based Service Data Object (SDO) data model transfer with proxy as an example, the security issue of SDO data model was analyzed in this paper and this paper proposed a mechanism to make sure that the confidentiality, integrity, and non-repudiation of SDO data model are preserved by applying encryption/decryption, digest, digital signature and so on. Finally, this mechanism was developed and its performance was evaluated in SOA-FCA Service Components.
Data Mining Technology across Academic Disciplines  [PDF]
Lesley Farmer, Alan Safer, Eric Chuk
Intelligent Information Management (IIM) , 2011, DOI: 10.4236/iim.2011.32005
Abstract: University courses in data mining across the United States are taught primarily in departments of business, computer science/engineering, statistics, and library/information science. Faculty in each of these departments teach data mining with a unique emphasis, although there is considerable overlap relative to course offerings, terminology, technology, resources, and faculty publications. Content analysis research aims to describe in detail the range of data mining technology differences and overlap across academic disciplines.
Explanation vs Performance in Data Mining: A Case Study with Predicting Runaway Projects  [PDF]
Journal of Software Engineering and Applications (JSEA) , 2009, DOI: 10.4236/jsea.2009.24030
Abstract: Often, the explanatory power of a learned model must be traded off against model performance. In the case of predict-ing runaway software projects, we show that the twin goals of high performance and good explanatory power are achievable after applying a variety of data mining techniques (discrimination, feature subset selection, rule covering algorithms). This result is a new high water mark in predicting runaway projects. Measured in terms of precision, this new model is as good as can be expected for our data. Other methods might out-perform our result (e.g. by generating a smaller, more explainable model) but no other method could out-perform the precision of our learned model.
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