Discovery Atlas Hb
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Discovery Atlas Hb
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Author : Thiago de Moraes
language : en
Publisher: Alison Green Books
Release Date : 2023-01-09
Discovery Atlas Hb written by Thiago de Moraes and has been published by Alison Green Books this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-09 with categories.
Prepare to set off on a grand voyage of discovery. You might want to take a map . . . But this is no ordinary atlas. The 'maps' in Discovery Atlasare fabulous, imaginative scenes, packed with incredible inventionsand dramatic discoveries. There are twelve witty, fact-packed chaptersto explore, which show how humans discovered everything from Medicine and Technology to Food, Space and even Sport. As you travel through each gorgeously illustratedchapter, you'll meet amazing inventors, explorers, artists and astronauts from all around the globe. You'll see how we invented writing, medicine, cars and chocolate(and everything else in between!) You'll bump into robots and dinosaurs. You'll spot tiny space probes, ancient cheese and the wreck of the Titanic. It's going to be an extraordinary journey. Are you ready to explore? Packed with fascinating characters and astonishing illustrations, this is a spectacular feast of a book Full of fun and amazing facts. Guaranteed to captivate children and adults alike! A stunning, large-format hardback, gorgeously illustrated in full colour, and with gold foil detailing on the cover. A perfect gift book Thiago de Moraes is the author and illustrator of the superb Myth Atlasand History Atlas
Hammond Discovery World Atlas
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Author : Hammond Incorporated
language : en
Publisher:
Release Date : 1971
Hammond Discovery World Atlas written by Hammond Incorporated and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1971 with Atlases categories.
Atlas Of Discovery
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Author : Gail Roberts
language : en
Publisher: Smithmark Publishers
Release Date : 1989
Atlas Of Discovery written by Gail Roberts and has been published by Smithmark Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 1989 with History categories.
The Great Atlas Of Discovery
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Author : Neil Grant
language : en
Publisher: Knopf Books for Young Readers
Release Date : 1992
The Great Atlas Of Discovery written by Neil Grant and has been published by Knopf Books for Young Readers this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992 with Reference categories.
Maps and text depict major areas and routes of exploration from about 6000 B.C. to the present.
Discovery And Exploration
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Author : Frank Debenham
language : en
Publisher:
Release Date : 1960
Discovery And Exploration written by Frank Debenham and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1960 with Discoveries in geography categories.
The Times Atlas Of World Exploration
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Author : K. N. Chaudhuri
language : en
Publisher: New York, NY : HarperCollins Publishers
Release Date : 1991
The Times Atlas Of World Exploration written by K. N. Chaudhuri and has been published by New York, NY : HarperCollins Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 1991 with Biography & Autobiography categories.
A region-by-region look at the progress of world exploration recreates the process of discovery by illustrating successive visions of the world over the centuries--from 1200 B.C. to the mapping of Antarctica in 1970.
Australian Books In Print 1998
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Author : Bowker
language : en
Publisher: Bowker-Saur
Release Date : 1998-04
Australian Books In Print 1998 written by Bowker and has been published by Bowker-Saur this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998-04 with Reference categories.
"...excellent coverage...essential to worldwide bibliographic coverage."--AMERICAN REFERENCE BOOKS ANNUAL. This comprehensive reference provides current finding & ordering information on more than 75,000 in-print books published in or about Australia, or written by Australian authors, organized by title, author, & keyword. You'll also find brief profiles of more than 7,000 publishers & distributors whose titles are represented, as well as information on trade associations, local agents of overseas publishers, literary awards, & more. From D.W. Thorpe.
Hutchison S Atlas Of Pediatric Physical Diagnosis
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Author : Krishna M Goel
language : en
Publisher: JP Medical Ltd
Release Date : 2014-08-31
Hutchison S Atlas Of Pediatric Physical Diagnosis written by Krishna M Goel and has been published by JP Medical Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-08-31 with Medical categories.
Guide to diagnosis of paediatric diseases and disorders with emphasis on accurate history taking and thorough physical examination. Highly experienced, UK editors and more than 1600 images and illustrations included.
Discovery In Physics
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Author : Katharina Morik
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2022-12-31
Discovery In Physics written by Katharina Morik and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-31 with Science categories.
Machine learning is part of Artificial Intelligence since its beginning. Certainly, not learning would only allow the perfect being to show intelligent behavior. All others, be it humans or machines, need to learn in order to enhance their capabilities. In the eighties of the last century, learning from examples and modeling human learning strategies have been investigated in concert. The formal statistical basis of many learning methods has been put forward later on and is still an integral part of machine learning. Neural networks have always been in the toolbox of methods. Integrating all the pre-processing, exploitation of kernel functions, and transformation steps of a machine learning process into the architecture of a deep neural network increased the performance of this model type considerably. Modern machine learning is challenged on the one hand by the amount of data and on the other hand by the demand of real-time inference. This leads to an interest in computing architectures and modern processors. For a long time, the machine learning research could take the von-Neumann architecture for granted. All algorithms were designed for the classical CPU. Issues of implementation on a particular architecture have been ignored. This is no longer possible. The time for independently investigating machine learning and computational architecture is over. Computing architecture has experienced a similarly rampant development from mainframe or personal computers in the last century to now very large compute clusters on the one hand and ubiquitous computing of embedded systems in the Internet of Things on the other hand. Cyber-physical systems’ sensors produce a huge amount of streaming data which need to be stored and analyzed. Their actuators need to react in real-time. This clearly establishes a close connection with machine learning. Cyber-physical systems and systems in the Internet of Things consist of diverse components, heterogeneous both in hard- and software. Modern multi-core systems, graphic processors, memory technologies and hardware-software codesign offer opportunities for better implementations of machine learning models. Machine learning and embedded systems together now form a field of research which tackles leading edge problems in machine learning, algorithm engineering, and embedded systems. Machine learning today needs to make the resource demands of learning and inference meet the resource constraints of used computer architecture and platforms. A large variety of algorithms for the same learning method and, moreover, diverse implementations of an algorithm for particular computing architectures optimize learning with respect to resource efficiency while keeping some guarantees of accuracy. The trade-off between a decreased energy consumption and an increased error rate, to just give an example, needs to be theoretically shown for training a model and the model inference. Pruning and quantization are ways of reducing the resource requirements by either compressing or approximating the model. In addition to memory and energy consumption, timeliness is an important issue, since many embedded systems are integrated into large products that interact with the physical world. If the results are delivered too late, they may have become useless. As a result, real-time guarantees are needed for such systems. To efficiently utilize the available resources, e.g., processing power, memory, and accelerators, with respect to response time, energy consumption, and power dissipation, different scheduling algorithms and resource management strategies need to be developed. This book series addresses machine learning under resource constraints as well as the application of the described methods in various domains of science and engineering. Turning big data into smart data requires many steps of data analysis: methods for extracting and selecting features, filtering and cleaning the data, joining heterogeneous sources, aggregating the data, and learning predictions need to scale up. The algorithms are challenged on the one hand by high-throughput data, gigantic data sets like in astrophysics, on the other hand by high dimensions like in genetic data. Resource constraints are given by the relation between the demands for processing the data and the capacity of the computing machinery. The resources are runtime, memory, communication, and energy. Novel machine learning algorithms are optimized with regard to minimal resource consumption. Moreover, learned predictions are applied to program executions in order to save resources. The three books will have the following subtopics: Volume 1: Machine Learning under Resource Constraints - Fundamentals Volume 2: Machine Learning and Physics under Resource Constraints - Discovery Volume 3: Machine Learning under Resource Constraints - Applications Volume 2 is about machine learning for knowledge discovery in particle and astroparticle physics. Their instruments, e.g., particle accelerators or telescopes, gather petabytes of data. Here, machine learning is necessary not only to process the vast amounts of data and to detect the relevant examples efficiently, but also as part of the knowledge discovery process itself. The physical knowledge is encoded in simulations that are used to train the machine learning models. At the same time, the interpretation of the learned models serves to expand the physical knowledge. This results in a cycle of theory enhancement supported by machine learning.
Higgs Potential And Naturalness After The Higgs Discovery
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Author : Yuta Hamada
language : en
Publisher: Springer
Release Date : 2017-01-30
Higgs Potential And Naturalness After The Higgs Discovery written by Yuta Hamada and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-01-30 with Science categories.
This thesis focuses on the theoretical foundation of the Standard Model valid up to the Planck scale, based on the current experimental facts from the Large Hadron Collider. The thesis consists of two themes: (1) to open up a new window of the Higgs inflation scenario, and (2) to explore a new solution to the naturalness problem in particle physics. In the first area, on the Higgs inflation scenario, the author successfully improves a large value problem on a coupling constant relevant to the Higgs mass in the Standard Model, in which the coupling value of the order of 105 predicted in a conventional scenario is reduced to the order of 10. This result makes the Higgs inflation more attractive because the small value of coupling is natural in the context of ultraviolet completion such as string theory. In the second area, the author provides a new answer to the naturalness problem, of why the cosmological constant and the Higgs mass are extremely small compared with the Planck scale. Based on the baby universe theory originally proposed by Coleman, the smallness of those quantities is successfully explained without introducing any additional new particles relevant at the TeV energy scale.