Chemometrics

Author:

Dumancas Gerard G.1,Bello Ghalib2,Hughes Jeff3,Murimi Renita4,Viswanath Lakshmi4,Orndorff Casey O.5,Dumancas Glenda Fe G.1,O'Dell Jacy6,Ghimire Prakash1,Setijadi Catherine1

Affiliation:

1. Louisiana State University, Alexandria, USA

2. Icahn School of Medicine at Mount Sinai, New York, USA

3. RMIT University, Melbourne, Australia

4. Oklahoma Baptist University, Shawnee, USA

5. University of the Ozarks, Clarksville, USA

6. Oklahoma Baptist University, Claremore, USA

Abstract

The accumulation of data from various instrumental analytical instruments has paved a way for the application of chemometrics. Challenges, however, exist in processing, analyzing, visualizing, and storing these data. Chemometrics is a relatively young area of analytical chemistry that involves the use of statistics and computer applications in chemistry. This article will discuss various computational and storage tools of big data analytics within the context of analytical chemistry with examples, applications, and usage details in relation to fog computing. The future of fog computing in chemometrics will also be discussed. The article will dedicate particular emphasis to preprocessing techniques, statistical and machine learning methodology for data mining and analysis, tools for big data visualization, and state-of-the-art applications for data storage using fog computing.

Publisher

IGI Global

Subject

Critical Care Nursing,Pediatrics

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5. Andrews, N. O., & Fox, E. A. (2007). Clustering for Data Reduction: A Divide and Conquer Approach. Department of Computer Science, TR-07-36. Retrieved on September 7, 2016 from http://vtechworks.lib.vt.edu/handle/10919/19848

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