Dear Data

This Book, through its various chapters presenting the Recent Advances in Modern Artificial Intelligence and Data Science as well as their Applications, aims to set up lasting and real applications necessary for both academics and professionals.

This book highlights applied artificial intelligence techniques, tools, and systems to drive strategic advantages, improve operational efficiency, and create added value. The focus is very much on practical applications and how to maximize the value of these technologies. They are being applied across businesses to enhance innovation, improve performance, increase profit, support critical thinking, and ultimately create customer-added value.

“Latin American journalism is currently experiencing some important transformations, with potential changes to how news is produced, shared, financed and consumed. This book provides a comprehensive overview of current journalism in Latin America, contextualized by global literature and regional empirical evidence. It is an important addition to our understanding of digital journalism and a must-read for those interested in journalism in Latin America.”

R for Cloud Computing looks at some of the tasks performed by business analysts on the desktop (PC era) and helps the user navigate the wealth of information in R and its 4000 packages as well as transition the same analytics using the cloud. With this information the reader can select both cloud vendors and the sometimes confusing cloud ecosystem as well as the R packages that can help process the analytical tasks with minimum effort, cost and maximum usefulness and customization.

This book constitutes the refereed proceedings of the Second International Conference on Big Data and Security, ICBDS 2020, held in Singapore, Singapore, in December 2020.
The 44 revised full papers and 8 short papers were carefully reviewed and selected out of 153 submissions. The papers included in this book are orfanized according to the topical sections on cybersecurity and privacy, big data, blockchain and internet of things, and artificial intelligence/ machine learning security.

Interest in statistical methodology is increasing so rapidly in the astronomical community that accessible introductory material in this area is long overdue. This book fills the gap by providing a presentation of the most useful techniques in multivariate statistics. A wide-ranging annotated set of general and astronomical bibliographic references follows each chapter, providing valuable entry-points for research workers in all astronomical sub-disciplines. Although the applications considered focus on astronomy, the algorithms used can be applied to similar problems in other branches of science. Fortran programs are provided for many of the methods described.

The statistical analysis of discrete multivariate data has received a great deal of attention in the statistics literature over the past two decades. The develop­ ment ofappropriate models is the common theme of books such as Cox (1970), Haberman (1974, 1978, 1979), Bishop et al. (1975), Gokhale and Kullback (1978), Upton (1978), Fienberg (1980), Plackett (1981), Agresti (1984), Goodman (1984), and Freeman (1987). The objective of our book differs from those listed above. Rather than concentrating on model building, our intention is to describe and assess the goodness-of-fit statistics used in the model verification part of the inference process.