Machine Nature
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Machine Nature
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Author : Moshe Sipper
language : en
Publisher: McGraw-Hill Companies
Release Date : 2002
Machine Nature written by Moshe Sipper and has been published by McGraw-Hill Companies this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with Business & Economics categories.
Computer scientist Moshe Sipper takes readers on a thrilling journey to the terra nova of computing to provide a compelling look at cutting-edge computers, robots, and machines now and in the decades ahead.
Machine Nature The Coming Age Of Bio Inspired Computing
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Author : Sipper
language : en
Publisher:
Release Date :
Machine Nature The Coming Age Of Bio Inspired Computing written by Sipper and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
Lithium Ion Batteries
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Author :
language : en
Publisher:
Release Date : 2019
Lithium Ion Batteries written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with Lithium ion batteries categories.
"This is the first machine-generated scientific book in chemistry published by Springer Nature. Serving as an innovative prototype defining the current status of the technology, it also provides an overview about the latest trends of lithium-ion batteries research. This book explores future ways of informing researchers and professionals. State-of-the-art computer algorithms were applied to: select relevant sources from Springer Nature publications, arrange these in a topical order, and provide succinct summaries of these articles. The result is a cross-corpora auto-summarization of current texts, organized by means of a similarity-based clustering routine in coherent chapters and sections. This book summarizes more than 150 research articles published from 2016 to 2018 and provides an informative and concise overview of recent research into anode and cathode materials as well as further aspects such as separators, polymer electrolytes, thermal behavior and modelling. With this prototype, Springer Nature has begun an innovative journey to explore the field of machine-generated content and to find answers to the manifold questions on this fascinating topic. Therefore it was intentionally decided not to manually polish or copy-edit any of the texts so as to highlight the current status and remaining boundaries of machine-generated content. Our goal is to initiate a broad discussion, together with the research community and domain experts, about the future opportunities, challenges and limitations of this technology."--Publisher's website.
Enhancing Machine Nature From The Myth Of The Machine To Sociotechnical Imaginaries Of Nonmechanical Machines
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Author : Alfred Nordmann
language : en
Publisher:
Release Date : 2016
Enhancing Machine Nature From The Myth Of The Machine To Sociotechnical Imaginaries Of Nonmechanical Machines written by Alfred Nordmann and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with categories.
Nature Inspired Computation In Data Mining And Machine Learning
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Author : Xin-She Yang
language : en
Publisher: Springer Nature
Release Date : 2019-09-03
Nature Inspired Computation In Data Mining And Machine Learning written by Xin-She Yang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-03 with Technology & Engineering categories.
This book reviews the latest developments in nature-inspired computation, with a focus on the cross-disciplinary applications in data mining and machine learning. Data mining, machine learning and nature-inspired computation are current hot research topics due to their importance in both theory and practical applications. Adopting an application-focused approach, each chapter introduces a specific topic, with detailed descriptions of relevant algorithms, extensive literature reviews and implementation details. Covering topics such as nature-inspired algorithms, swarm intelligence, classification, clustering, feature selection, cybersecurity, learning algorithms over cloud, extreme learning machines, object categorization, particle swarm optimization, flower pollination and firefly algorithms, and neural networks, it also presents case studies and applications, including classifications of crisis-related tweets, extraction of named entities in the Tamil language, performance-based prediction of diseases, and healthcare services. This book is both a valuable a reference resource and a practical guide for students, researchers and professionals in computer science, data and management sciences, artificial intelligence and machine learning.
Nature S Machines
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Author : David E. Alexander
language : en
Publisher: Academic Press
Release Date : 2017-08-15
Nature S Machines written by David E. Alexander and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-08-15 with Science categories.
Nature’s Machines: An Introduction to Organismal Biomechanics presents the fundamental principles of biomechanics in a concise, accessible way while maintaining necessary rigor. It covers the central principles of whole-organism biomechanics as they apply across the animal and plant kingdoms, featuring brief, tightly-focused coverage that does for biologists what H. M. Frost’s 1967 Introduction to Biomechanics did for physicians. Frequently encountered, basic concepts such as stress and strain, Young’s modulus, force coefficients, viscosity, and Reynolds number are introduced in early chapters in a self-contained format, making them quickly available for learning and as a refresher. More sophisticated, integrative concepts such as viscoelasticity or properties of hydrostats are covered in the later chapters, where they draw on information from multiple earlier sections of the book. Animal and plant biomechanics is now a common research area widely acknowledged by organismal biologists to have broad relevance. Most of the day-to-day activities of an animal involve mechanical processes, and to the extent that organisms are shaped by adaptive evolution, many of those adaptations are constrained and channelized by mechanical properties. The similarity in body shape of a porpoise and a tuna is no coincidence. Many may feel that they have an intuitive understanding of many of the mechanical processes that affect animals and plants, but careful biomechanical analyses often yield counterintuitive results: soft, squishy kelp may be better at withstanding pounding waves during storms than hard-shelled mollusks; really small swimmers might benefit from being spherical rather than streamlined; our bones can operate without breaking for decades, whereas steel surgical implants exhibit fatigue failures in a few months if not fully supported by bone. Offers organismal biologists and biologists in other areas a background in biomechanics to better understand the research literature and to explore the possibility of using biomechanics approaches in their own work Provides an introductory presentation of the everyday mechanical challenges faced by animals and plants Functions as recommended or required reading for advanced undergraduate biology majors taking courses in biomechanics, supplemental reading in a general organismal biology course, or background reading for a biomechanics seminar course
Climate Planetary And Evolutionary Sciences
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Author : Guido Visconti
language : en
Publisher: Springer Nature
Release Date : 2021-04-14
Climate Planetary And Evolutionary Sciences written by Guido Visconti and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-14 with Science categories.
This book presents the result of an innovative challenge, to create a systematic literature overview driven by machine-generated content. Questions and related keywords were prepared for the machine to query, discover, collate and structure by Artificial Intelligence (AI) clustering. The AI-based approach seemed especially suitable to provide an innovative perspective as the topics are indeed both complex, interdisciplinary and multidisciplinary, for example, climate, planetary and evolution sciences. Springer Nature has published much on these topics in its journals over the years, so the challenge was for the machine to identify the most relevant content and present it in a structured way that the reader would find useful. The automatically generated literature summaries in this book are intended as a springboard to further discoverability. They are particularly useful to readers with limited time, looking to learn more about the subject quickly and especially if they are new to the topics. Springer Nature seeks to support anyone who needs a fast and effective start in their content discovery journey, from the undergraduate student exploring interdisciplinary content, to Master- or PhD-thesis developing research questions, to the practitioner seeking support materials, this book can serve as an inspiration, to name a few examples. It is important to us as a publisher to make the advances in technology easily accessible to our authors and find new ways of AI-based author services that allow human-machine interaction to generate readable, usable, collated, research content.
Nature Inspired Computation In Data Mining And Machine Learning
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Author : Xin-She Yang
language : en
Publisher: Springer
Release Date : 2020-09-16
Nature Inspired Computation In Data Mining And Machine Learning written by Xin-She Yang and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-16 with Technology & Engineering categories.
This book reviews the latest developments in nature-inspired computation, with a focus on the cross-disciplinary applications in data mining and machine learning. Data mining, machine learning and nature-inspired computation are current hot research topics due to their importance in both theory and practical applications. Adopting an application-focused approach, each chapter introduces a specific topic, with detailed descriptions of relevant algorithms, extensive literature reviews and implementation details. Covering topics such as nature-inspired algorithms, swarm intelligence, classification, clustering, feature selection, cybersecurity, learning algorithms over cloud, extreme learning machines, object categorization, particle swarm optimization, flower pollination and firefly algorithms, and neural networks, it also presents case studies and applications, including classifications of crisis-related tweets, extraction of named entities in the Tamil language, performance-based prediction of diseases, and healthcare services. This book is both a valuable a reference resource and a practical guide for students, researchers and professionals in computer science, data and management sciences, artificial intelligence and machine learning.
The Deep Learning Revolution
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Author : Terrence J. Sejnowski
language : en
Publisher: MIT Press
Release Date : 2018-10-23
The Deep Learning Revolution written by Terrence J. Sejnowski and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-23 with Computers categories.
How deep learning—from Google Translate to driverless cars to personal cognitive assistants—is changing our lives and transforming every sector of the economy. The deep learning revolution has brought us driverless cars, the greatly improved Google Translate, fluent conversations with Siri and Alexa, and enormous profits from automated trading on the New York Stock Exchange. Deep learning networks can play poker better than professional poker players and defeat a world champion at Go. In this book, Terry Sejnowski explains how deep learning went from being an arcane academic field to a disruptive technology in the information economy. Sejnowski played an important role in the founding of deep learning, as one of a small group of researchers in the 1980s who challenged the prevailing logic-and-symbol based version of AI. The new version of AI Sejnowski and others developed, which became deep learning, is fueled instead by data. Deep networks learn from data in the same way that babies experience the world, starting with fresh eyes and gradually acquiring the skills needed to navigate novel environments. Learning algorithms extract information from raw data; information can be used to create knowledge; knowledge underlies understanding; understanding leads to wisdom. Someday a driverless car will know the road better than you do and drive with more skill; a deep learning network will diagnose your illness; a personal cognitive assistant will augment your puny human brain. It took nature many millions of years to evolve human intelligence; AI is on a trajectory measured in decades. Sejnowski prepares us for a deep learning future.
The Nature Of The Machine And The Collapse Of Cybernetics
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Author : Alcibiades Malapi-Nelson
language : en
Publisher: Palgrave Macmillan
Release Date : 2018-08-01
The Nature Of The Machine And The Collapse Of Cybernetics written by Alcibiades Malapi-Nelson and has been published by Palgrave Macmillan this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-01 with Philosophy categories.
This book is a philosophical exploration of the theoretical causes behind the collapse of classical cybernetics, as well as the lesson that this episode can provide to current emergent technologies. Alcibiades Malapi-Nelson advances the idea that the cybernetic understanding of the nature of a machine entails ontological and epistemological consequences that created both material and theoretical conundrums. However, he proposes that given our current state of materials research, scientific practices, and research tools, there might be a way for cybernetics to flourish this time. The book starts with a historical and theoretical articulation of cybernetics in order to proceed with a philosophical explanation of its collapse—emphasizing the work of Alan Turing, Ross Ashby and John von Neumann. Subsequently, Malapi-Nelson unveils the common metaphysical signature shared between cybernetics and emergent technologies, identifying this signature as transhumanist in nature. Finally, avenues of research that may allow these disruptive technologies to circumvent the cybernetic fate are indicated. It is proposed that emerging technologies ultimately entail an affirmation of humanity.