This book brings fresh insights into how social spaces shape the way we experience and understand security. Chapters unite voices from critical security studies, urban geography, criminology and political science to rethink the link between security and space, from neighbourhood crime to global conflict.By viewing security through a spatial lens, the book uncovers the social, economic and political forces that shape security issues in everyday life offering vital insights for curre...

This book stems from the growing use of learning-based techniques, such as reinforcement learning and adaptive control, in the control of autonomous and safety-critical systems. Safety is critical to many applications, such as autonomous driving, air traffic control, and robotics. As these learning-enabled technologies become more prevalent in the control of autonomous systems, it becomes increasingly important to ensure that such systems are safe. To address these challenges, the authors ...

An extended and fearless exploration on the meaning of manhood in contemporary Western culture—at a moment in time in which both Fatherhood and Manhood have become endangered concepts. Pointing out the need for strong male relationships and guidance, this book offers an essential prescription for the psychological health of modern Western societies, which have lost the thread of traditional cultures and their time-honored rites of passage.The extensive letter exchange between father...

Neoliberalism isn't working. Austerity is forcing millions into poverty and many more into precarious work, while the left remains trapped in stagnant political practices that offer no respite.Inventing the Future is a bold new manifesto for life after capitalism. Against the confused understanding of our high-tech world by both the right and the left, this book claims that the emancipatory and future-oriented possibilities of our society can be reclaimed. Instead...

Machine Learning: A Constraint-Based Approach provides readers with a refreshing look at the basic models and algorithms of machine learning, with an emphasis on current topics of interest that includes neural networks and kernel machines. The book presents the information in a truly unified manner that is based on the notion of learning from environmental constraints. While regarding symbolic knowledge bases as a collection of constraints, the book draws a path towards a deep integration ...

A comprehensive guide to getting well-versed with the mathematical techniques for building modern deep learning architecturesKey FeaturesUnderstand linear algebra, calculus, gradient algorithms, and other concepts essential for training deep neural networksLearn the mathematical concepts needed to understand how deep learning models functionUse deep learning for solving problems related to vision, image, text, and sequence applications

Global studies is a fresh and dynamic discipline area that promises to reinvigorate undergraduate and postgraduate education in the social sciences and humanities. In the Australian context, the interdisciplinary pedagogy that defines global studies is gaining wider acceptance as a coherent and necessary approach to the study of global change. Through the Global Studies Consortium (GSC), this new discipline is forming around an impressive body of international scholars who define their exp...

Edited by the people who were forerunners in creating the field, together with contributions from 34 leading international experts, this handbook provides the definitive reference on Blind Source Separation, giving a broad and comprehensive description of all the core principles and methods, numerical algorithms and major applications in the fields of telecommunications, biomedical engineering and audio, acoustic and speech processing. Going beyond a machine learning perspective, the book ...

Why do we no longer trust facts, experts and statistics? In this essential guide to the turbulent times in which we live, Marcus Gilroy-Ware investigates our era of post-truths and fake news and answers the question of where we can go from here.We are supposed to have more information at our disposal now than at any time in history. So why, in a world of rising sea levels, populist leaders, resurgent fascism and a global pandemic, do so many people believe bizarre ...

A core principle of physics is knowledge gained from data. Thus, deep learning has instantly entered physics and may become a new paradigm in basic and applied research.This textbook addresses physics students and physicists who want to understand what deep learning actually means, and what is the potential for their own scientific projects. Being familiar with linear algebra and parameter optimization is sufficient to jump-start deep learning. Adopting a pragmatic approach, basic and adva...

Design optimization is a standard concept in engineering design, and in other disciplines which utilize mathematical decision-making methods. This textbook focuses on the close relationship between a design problem's mathematical model and the solution-driven methods which optimize it. Along with extensive material on modeling problems, this book also features useful techniques for checking whether a model is suitable for computational treatment. Throughout, key concepts are discussed in t...

Group method of data handling (GMDH) is a typical inductive modeling method built on the principles of self-organization. Since its introduction, inductive modelling has been developed to support complex systems in prediction, clusterization, system identification, as well as data mining and knowledge extraction technologies in social science, science, engineering, and medicine.This is the first book to explore GMDH using MATLAB (matrix laboratory) language. Readers will learn how to imple...