Experience the transformative power of a Reality too vast to grasp. In Part One embark on a voyage through the enigmatic ‘Land of Mystery,’ where we learn to thrive amidst uncertainty, nourishing our curious beings with approximate yet meaningful insights. Delve into Part Two and explore the tapestry of religious practices inviting the Eternity of Profound Reality to be present in our lives. Finally in Part Three, take in the example of Christian faith, especially where ancient scriptures resonate with newfound relevance in the modern era. Through these pages find balance in being more alive within these challenging times.

As the world becomes increasingly complex, so do the statistical models required to analyse the challenging problems ahead. For the very first time in a single volume, the Handbook of Approximate Bayesian Computation (ABC) presents an extensive overview of the theory, practice and application of ABC methods. These simple, but powerful statistical techniques, take Bayesian statistics beyond the need to specify overly simplified models, to the setting where the model is defined only as a process that generates data. This process can be arbitrarily complex, to the point where standard Bayesian techniques based on working with tractable likelihood functions would not be viable. ABC methods finesse the problem of model complexity within the Bayesian framework by exploiting modern computational power, thereby permitting approximate Bayesian analyses of models that would otherwise be impossible to implement. The Handbook of ABC provides illuminating insight into the world of Bayesian modelling for intractable models for both experts and newcomers alike. It is an essential reference book for anyone interested in learning about and implementing ABC techniques to analyse complex models in the modern world.

There has been a decided shift towards desiring greater “relevance” in management education by serving the needs of management practice. The importance of a careful defi nition of “relevance” and the retention of a critical perspective needs to be asserted. In this respect, what Hugo Letiche and Geoff Lightfoot have done together, and written up in this book, is an outstanding example of a commitment to restore “relevance” via critical engagement to management pedagogy and practice. Their success is a clear demonstration of the practical relevance of imagination, commitment and scholarship. Prof Heather Hopfl (University of Essex)

This book gives a comprehensive overview of the most advanced theories, methodologies and applications in computer vision. Particularly, it gives an extensive coverage of 3D and robotic vision problems. Example chapters featured are Fourier methods for 3D surface modeling and analysis, use of constraints for calibration-free 3D Euclidean reconstruction, novel photogeometric methods for capturing static and dynamic objects, performance evaluation of robot localization methods in outdoor terrains, integrating 3D vision with force/tactile sensors, tracking via in-floor sensing, self-calibration of camera networks, etc. Some unique applications of computer vision in marine fishery, biomedical issues, driver assistance, are also highlighted.

This book serves as a single-source reference to the latest advances in Approximate Computing (AxC), a promising technique for increasing performance or reducing the cost and power consumption of a computing system. The authors discuss the different AxC design and validation techniques, and their integration. They also describe real AxC applications, spanning from mobile to high performance computing and also safety-critical applications.