Three decades of societal and cultural alignment of new media have yielded a host of innovations, trials, and problems, accompanied by versatile popular and academic discourse. New Media Studies crystallized internationally into an established academic discipline, and this begs the question: where do we stand now? Which new questions are emerging now that new media are being taken for granted, …
Contextualizing Disaster" offers a comparative analysis of six recent highly visible disasters and several slow-burning, hidden, crises that include typhoons, tsunamis, earthquakes, chemical spills, and the unfolding consequences of rising seas and climate change. The book argues that, while disasters are increasingly represented by the media as unique, exceptional, newsworthy events, it is a m…
This exciting volume presents the work and research of the Rivers of the Anthropocene Network, an international collaborative group of scientists, social scientists, humanists, artists, policymakers, and community organizers working to produce innovative transdisciplinary research on global freshwater systems. In an attempt to bridge disciplinary divides, the essays in this volume address the c…
Developing Graphics Frameworks with Python and OpenGL shows you how to create software for rendering complete three-dimensional scenes. The authors explain the foundational theoretical concepts as well as the practical programming techniques that will enable you to create your own animated and interactive computer-generated worlds.You will learn how to combine the power of OpenGL, the most wide…
Lütkenhöner’s „Intensity Dependence of Auditory Responses“: An Instructional Example in How Not To Do Computational Neurobiology
A concise and self-contained introduction to causal inference, increasingly important in data science and machine learning. The mathematization of causality is a relatively recent development, and has become increasingly important in data science and machine learning. This book offers a self-contained and concise introduction to causal models and how to learn them from data. After explaining th…
Anomaly Detection & Behavior Prediction: Higher-Level Fusion Based on Computational Neuroscientific Principles
Think D.S.P. is an introduction to Digital Signal Processing in Python. The premise of this book (and the other books in the Think X series) is that if you know how to program, you can use that skill to learn other things. The author is writing this book because he thinks the conventional approach to digital signal processing is backward: most books (and the classes that use them) present the m…
This book is about complexity science, data structures and algorithms, intermediate programming in Python and the philosophy of science: Data structures and algorithms: A data structure is a collection that contains data elements organized in a way that supports particular operations. For example, a dictionary organizes key-value pairs in a way that provides fast mapping from keys to values, bu…