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Computer Science and Intelligent Systems

Computer Science and Intelligent Systems

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People keep track. In the eighteenth century, Benjamin Franklin kept charts of time spent and virtues lived up to. Today, people use technology to self-track: hours slept, steps taken, calories consumed, medications administered. Ninety million wearable sensors were shipped in 2014 to help us gather data about our lives. This book examines how people record, analyze, and reflect on this data, looking at the tools they use and the communities they become part of.

Habitual New Media

New media—we are told—exist at the bleeding edge of obsolescence. We thus forever try to catch up, updating to remain the same. Meanwhile, analytic, creative, and commercial efforts focus exclusively on the next big thing: figuring out what will spread and who will spread it the fastest. But what do we miss in this constant push to the future? In Updating to Remain the Same, Wendy Hui Kyong Chun suggests another approach, arguing that our media matter most when they seem not to matter at all—when they have moved from “new” to habitual.

Principles and Best Practice

This book addresses an often-neglected aspect of the creation of VHDL designs. A VHDL description is also source code, and VHDL designers can use the best practices of software development to write high-quality code and to organize it in a design. This book presents this unique set of skills, teaching VHDL designers of all experience levels how to apply the best design principles and coding practices from the software world to the world of hardware.

What Every Research Assistant Should Know

This book offers a practical guide to the computational methods at the heart of most modern quantitative research. It will be essential reading for research assistants needing hands-on experience; students entering PhD programs in business, economics, and other social or natural sciences; and those seeking quantitative jobs in industry. No background in computer science is assumed; a learner need only have a computer with access to the Internet.

The Birth of Computer Science

In 1936, when he was just twenty-four years old, Alan Turing wrote a remarkable paper in which he outlined the theory of computation, laying out the ideas that underlie all modern computers. This groundbreaking and powerful theory now forms the basis of computer science. In Turing’s Vision, Chris Bernhardt explains the theory, Turing’s most important contribution, for the general reader. Bernhardt argues that the strength of Turing’s theory is its simplicity, and that, explained in a straightforward manner, it is eminently understandable by the nonspecialist.

This book presents the "great ideas" of computer science, condensing a large amount of complex material into a manageable, accessible form; it does so using the Java programming language. The book is based on the problem-oriented approach that has been so successful in traditional quantitative sciences.

A Gentle Introduction

In Great Ideas in Computer Science: A Gentle Introduction, Alan Biermann presents the "great ideas" of computer science that together comprise the heart of the field. He condenses a great deal of complex material into a manageable, accessible form. His treatment of programming, for example, presents only a few features of Pascal and restricts all programs to those constructions. Yet most of the important lessons in programming can be taught within these limitations.

This book introduces programming to readers with a background in the arts and humanities; there are no prerequisites, and no knowledge of computation is assumed. In it, Nick Montfort reveals programming to be not merely a technical exercise within given constraints but a tool for sketching, brainstorming, and inquiring about important topics. He emphasizes programming’s exploratory potential—its facility to create new kinds of artworks and to probe data for new ideas.

Biosensing Technologies in Everyday Life
Edited by Dawn Nafus

Today anyone can purchase technology that can track, quantify, and measure the body and its environment. Wearable or portable sensors detect heart rates, glucose levels, steps taken, water quality, genomes, and microbiomes, and turn them into electronic data. Is this phenomenon empowering, or a new form of social control? Who volunteers to enumerate bodily experiences, and who is forced to do so? Who interprets the resulting data? How does all this affect the relationship between medical practice and self care, between scientific and lay knowledge?

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