Gerard G. Dumancas, Ghalib A. Bello, J. Hughes, R. Murimi, Lakshmi Viswanath, Casey O. Orndorff, G. Dumancas, Jacy O'Dell, Prakash Ghimire, Catherine Setijadi
{"title":"Chemometrics: From Data Preprocessing to Fog Computing","authors":"Gerard G. Dumancas, Ghalib A. Bello, J. Hughes, R. Murimi, Lakshmi Viswanath, Casey O. Orndorff, G. Dumancas, Jacy O'Dell, Prakash Ghimire, Catherine Setijadi","doi":"10.4018/IJFC.2019010101","DOIUrl":null,"url":null,"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.","PeriodicalId":218786,"journal":{"name":"Int. J. Fog Comput.","volume":"57 6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Fog Comput.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/IJFC.2019010101","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
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.