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Big Data Applications

2014
In the previous chapter, we examined big data analysis, which is the final and most important phase of the value chain of big data. Big data analysis can provide useful values via judgments, recommendations, supports, or decisions. However, data analysis involves a wide range of applications, which frequently change and are extremely complex.
Min Chen   +3 more
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Applications: Field Data

2001
Plotting the contours of lakes and the positions of boreholes. Then bubbles in three dimensions, moving up a column in animation. A look at Darcy’s law for groundwater flow into lakes. Lastly, sulfur dioxide, carbon dioxide and ammonia contribute to the formation of acid rain.
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Data-Centric Applications

2009
Chapter 4 covers techniques to perform complex queries. In this chapter, we first present solutions for multi-dimensional queries, multi-attribute queries and skyline queries. These types of queries are important for file sharing systems where files are described by a set of attributes and it is desirable to search files through such attributes.
Quang Hieu Vu, Mihai Lupu, Beng Chin Ooi
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Data Communications Applications

2009
This chapter contains sections titled: A Full Duplex 1200/300 Bit/s Single-Chip CMOS Modem Line and Receiver Interface Circuit for High-Speed Voice-Band Modems A Single-Chip Frequency-Shift Keyed Modem Implemented Using Digital Signal Processing A CMOS Ethernet Serial Interface Chip A Single Chip NMOS Ethernet Controller
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Disruptive Data Applications

2020
The combination of ubiquitous high speed connectivity, a plethora of devices to capture vast amounts of data, the secure distribution of such data, Artificial Intelligence (AI) deployed to make sense of data across the ecosystem and automation of many business processes is leading to significant innovation in the application space.
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Data Science Applications

2020
In this chapter, we shall study a few applications of linear programming to an area of statistics called regression and to an area of machine learning called support vector machines. As a specific example for our study of regression, we shall use size and iteration-count data collected from a standard suite of linear programming problems to derive a ...
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Data and applications security

Data & Knowledge Engineering, 2002
Thuraisingham, Bhavani   +1 more
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Data-Driven Applications

2022
Benjamin Kettner, Frank Geisler
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Data Level Enterprise Applications Integration

2006
Information integration across heterogeneous systems is a key issue for successful enterprise application systems development. Particularly challenging is integration of different applications deployed on different platforms into one integrated and stable business information system.
Vujasinović, M, Marjanović, Zoran
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Data Science Applications

2018
In principle, data science can be applied to any application area or business domain. However, data science projects are intrinsically different from ordinary software development and IT projects.
openaire   +1 more source

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