The Self Awareness Code
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The Self-Aware Universe
In this stimulating and timely book, Amit Goswami, PhD, shatters the widely popular belief held by Western science that matter is the primary "stuff" of creation and proposes instead that consciousness is the true foundation of all we know and perceive. His explanation of quantum physics for lay readers, called "a model of clarity" by Kirkus Reviews, sets the stage for a voyage of discovery through the common ground of science and religion, the entwined nature of mind and body, and our interconnectedness with all of creation.
Self-Awareness (HBR Emotional Intelligence Series)
Author: Harvard Business Review
language: en
Publisher: Harvard Business Press
Release Date: 2018-11-13
Self-awareness is the bedrock of emotional intelligence that enables you to see your talents, shortcomings, and potential. But you won't be able to achieve true self-awareness with the usual quarterly feedback and self-reflection alone. This book will teach you how to understand your thoughts and emotions, how to persuade your colleagues to share what they really think of you, and why self-awareness will spark more productive and rewarding relationships with your employees and bosses. This volume includes the work of: Daniel Goleman Robert Steven Kaplan Susan David HOW TO BE HUMAN AT WORK. The HBR Emotional Intelligence Series features smart, essential reading on the human side of professional life from the pages of Harvard Business Review. Each book in the series offers proven research showing how our emotions impact our work lives, practical advice for managing difficult people and situations, and inspiring essays on what it means to tend to our emotional well-being at work. Uplifting and practical, these books describe the social skills that are critical for ambitious professionals to master.
Self-Aware Computing Systems
This book provides formal and informal definitions and taxonomies for self-aware computing systems, and explains how self-aware computing relates to many existing subfields of computer science, especially software engineering. It describes architectures and algorithms for self-aware systems as well as the benefits and pitfalls of self-awareness, and reviews much of the latest relevant research across a wide array of disciplines, including open research challenges. The chapters of this book are organized into five parts: Introduction, System Architectures, Methods and Algorithms, Applications and Case Studies, and Outlook. Part I offers an introduction that defines self-aware computing systems from multiple perspectives, and establishes a formal definition, a taxonomy and a set of reference scenarios that help to unify the remaining chapters. Next, Part II explores architectures for self-aware computing systems, such as generic concepts and notations that allow a wide range of self-aware system architectures to be described and compared with both isolated and interacting systems. It also reviews the current state of reference architectures, architectural frameworks, and languages for self-aware systems. Part III focuses on methods and algorithms for self-aware computing systems by addressing issues pertaining to system design, like modeling, synthesis and verification. It also examines topics such as adaptation, benchmarks and metrics. Part IV then presents applications and case studies in various domains including cloud computing, data centers, cyber-physical systems, and the degree to which self-aware computing approaches have been adopted within those domains. Lastly, Part V surveys open challenges and future research directions for self-aware computing systems. It can be used as a handbook for professionals and researchers working in areas related to self-aware computing, and can also serve as an advanced textbook for lecturers and postgraduate students studying subjects like advanced software engineering, autonomic computing, self-adaptive systems, and data-center resource management. Each chapter is largely self-contained, and offers plenty of references for anyone wishing to pursue the topic more deeply.