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Virtual Topology and Functor Geometry

Fortran 2018 with Parallel Programming

Fortran 2018 with Parallel Programming

The programming language Fortran dates back to 1957 when a team of IBM engineers released the first Fortran Compiler. During the past 60 years the language had been revised and updated several times to incorporate more features to enable writing clean and structured computer programs. The present version is Fortran 2018. Since the dawn of the computer era there had been a constant demand for a “larger” and “faster” machine. To increase the speed there are three hurdles. The density of the active components on a VLSI chip cannot be increased indefinitely and with the increase of the density heat dissipation becomes a major problem. Finally the speed of any signal cannot exceed the velocity of the light. However by using several inexpensive processors in parallel coupled with specialized software and hardware programmers can achieve computing speed similar to a supercomputer. This book can be used to learn the modern Fortran from the beginning and the technique of developing parallel programs using Fortran. It is for anyone who wants to learn Fortran. Knowledge beyond high school mathematics is not required. There is not another book on the market yet which deals with Fortran 2018 as well as parallel programming. FEATURES Descriptions of majority of Fortran 2018 instructions Numerical Model String with Variable Length IEEE Arithmetic and Exceptions Dynamic Memory Management Pointers Bit handling C-Fortran Interoperability Object Oriented Programming Parallel Programming using Coarray Parallel Programming using OpenMP Parallel Programming using Message Passing Interface (MPI) THE AUTHOR Dr Subrata Ray is a retired Professor Indian Association for the Cultivation of Science Kolkata. | Fortran 2018 with Parallel Programming

GBP 140.00
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Statistical Design and Analysis of Stability Studies

Statistical Design and Analysis of Stability Studies

The US Food and Drug Administration's Report to the Nation in 2004 and 2005 indicated that one of the top reasons for drug recall was that stability data did not support existing expiration dates. Pharmaceutical companies conduct stability studies to characterize the degradation of drug products and to estimate drug shelf life. Illustrating how stability studies play an important role in drug safety and quality assurance Statistical Design and Analysis of Stability Studies presents the principles and methodologies in the design and analysis of stability studies. After introducing the basic concepts of stability testing the book focuses on short-term stability studies and reviews several methods for estimating drug expiration dating periods. It then compares some commonly employed study designs and discusses both fixed and random batch statistical analyses. Following a chapter on the statistical methods for stability analysis under a linear mixed effects model the book examines stability analyses with discrete responses multiple components and frozen drug products. In addition the author provides statistical methods for dissolution testing and explores current issues and recent developments in stability studies. To ensure the safety of consumers professionals in the field must carry out stability studies to determine the reliability of drug products during their expiration period. This book provides the material necessary for you to perform stability designs and analyses in pharmaceutical research and development.

GBP 44.99
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Artificial Intelligence on Dark Matter and Dark Energy Reverse Engineering of the Big Bang

Artificial Intelligence on Dark Matter and Dark Energy Reverse Engineering of the Big Bang

As we prod the cosmos at very large scales basic tenets of physics seem to crumble under the weight of contradicting evidence. This book helps mitigate the crisis. It resorts to artificial intelligence (AI) for answers and describes the outcome of this quest in terms of an ur-universe a quintessential compact multiply connected space that incorporates a fifth dimension to encode space-time as a latent manifold. In some ways AI is bolder than humans because the huge corpus of knowledge starting with the prodigious Standard Model (SM) of particle physics poses almost no burden to its conjecture-framing processes. Why not feed AI with the SM enriched by the troubling cosmological phenomenology on dark matter and dark energy and see where AI takes us vis-à-vis reconciling the conflicting data with the laws of physics? This is precisely the intellectual adventure described in this book and – to the best of our knowledge – in no other book on the shelf. As the reader will discover many AI conjectures and validations ultimately make a lot of sense even if their boldness does not feel altogether human yet. This book is written for a broad readership. Prerequisites are minimal but a background in college math/physics/computer science is desirable. This book does not merely describe what is known about dark matter and dark energy but also provides readers with intellectual tools to engage in a quest for the deepest cosmological mystery. | Artificial Intelligence on Dark Matter and Dark Energy Reverse Engineering of the Big Bang

GBP 89.99
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