Download or read book Animal Health General principles written by Archie Hunter and published by CTA; MacMillan. This book was released on 1996 with total page 167 pages. Available in PDF, EPUB and Kindle. Book excerpt: Animal Health Volume 1 is a practical guide for anyone involved with maintaining and establishing the health of animals in tropical and sub-tropical regions. It comprehensively explains the causes of animal diseases, how they spread and the means available for their control. The handbook should be used in conjunction with Volume 2: Specific Diseases which is already published.

Download or read book The Jewelers Circular written by and published by . This book was released on 1919 with total page 828 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Network Coding written by Khaldoun Al Agha and published by John Wiley & Sons. This book was released on 2012-12-27 with total page 171 pages. Available in PDF, EPUB and Kindle. Book excerpt: Network coding, a relatively new area of research, has evolved from the theoretical level to become a tool used to optimize the performance of communication networks – wired, cellular, ad hoc, etc. The idea consists of mixing “packets” of data together when routing them from source to destination. Since network coding increases the network performance, it becomes a tool to enhance the existing protocols and algorithms in a network or for applications such as peer-to-peer and TCP. This book delivers an understanding of network coding and provides a set of studies showing the improvements in security, capacity and performance of fixed and mobile networks. This is increasingly topical as industry is increasingly becoming more reliant upon and applying network coding in multiple applications. Many cases where network coding is used in routing, physical layer, security, flooding, error correction, optimization and relaying are given – all of which are key areas of interest. Network Coding is the ideal resource for university students studying coding, and researchers and practitioners in sectors of all industries where digital communication and its application needs to be correctly understood and implemented. Contents 1. Network Coding: From Theory to Practice, Youghourta Benfattoum, Steven Martin and Khaldoun Al Agha. 2. Fountain Codes and Network Coding for WSNs, Anya Apavatjrut, Claire Goursaud, Katia Jaffrès-Runser and Jean-Marie Gorce. 3. Switched Code for Ad Hoc Networks: Optimizing the Diffusion by Using Network Coding, Nour Kadi and Khaldoun Al Agha. 4. Security by Network Coding, Katia Jaffrès-Runser and Cédric Lauradoux. 5. Security for Network Coding, Marine Minier, Yuanyuan Zhang and Wassim Znaïdi. 6. Random Network Coding and Matroids, Maximilien Gadouleau. 7. Joint Network-Channel Coding for the Semi-Orthogonal MARC: Theoretical Bounds and Practical Design, Atoosa Hatefi, Antoine O. Berthet and Raphael Visoz. 8. Robust Network Coding, Lana Iwaza, Marco Di Renzo and Michel Kieffer. 9. Flow Models and Optimization for Network Coding, Eric Gourdin and Jeremiah Edwards.

Download or read book Memory Evolutive Systems Hierarchy Emergence Cognition written by A C Ehresmann and published by Elsevier. This book was released on 2007-05-25 with total page 403 pages. Available in PDF, EPUB and Kindle. Book excerpt: Memory Evolutive Systems; Hierarchy, Emergence, Cognition provides comprehensive and comprehensible coverage of Memory Evolutive Systems (MEM). Written by the developers of the MEM, the book proposes a mathematical model for autonomous evolutionary systems based on the Category Theory of mathematics. It describes a framework to study and possibly simulate the structure of living systems and their dynamic behavior. This book contributes to understanding the multidisciplinary interfaces between mathematics, cognition, consciousness, biology and the study of complexity. It is organized into three parts. Part A deals with hierarchy and emergence and covers such topics as net of interactions and categories; the binding problem; and complexifications and emergence. Part B is about MEM while Part C discusses MEM applications to cognition and consciousness. The book explores the characteristics of a complex evolutionary system, its differences from inanimate physical systems, and its functioning and evolution in time, from its birth to its death. This book is an ideal reference for researchers, teachers and students in pure mathematics, computer science, cognitive science, study of complexity and systems theory, Category Theory, biological systems theory, and consciousness theory. It would also be of interest to both individuals and institutional libraries. - Comprehensive and comprehensible coverage of Memory Evolutive System - Written by the developers of the Memory Evolutive Systems - Designed to explore the common language between sciences

Download or read book From Technological to Virtual Art written by Frank Popper and published by . This book was released on 2007 with total page 482 pages. Available in PDF, EPUB and Kindle. Book excerpt: Frank Popper traces the development of immersive, interactive new media art from its antecedents through today's digital, multimedia, & networked art.

Download or read book Artificial Intelligence written by David L. Poole and published by Cambridge University Press. This book was released on 2017-09-25 with total page 821 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence presents a practical guide to AI, including agents, machine learning and problem-solving simple and complex domains.

Download or read book The Acharnians written by Aristophanes and published by BoD – Books on Demand. This book was released on 2019-09-25 with total page 66 pages. Available in PDF, EPUB and Kindle. Book excerpt: Reproduction of the original: The Acharnians by Aristophanes

Download or read book Machine Learning in Action written by Peter Harrington and published by Simon and Schuster. This book was released on 2012-04-03 with total page 558 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Machine Learning in Action is unique book that blends the foundational theories of machine learning with the practical realities of building tools for everyday data analysis. You'll use the flexible Python programming language to build programs that implement algorithms for data classification, forecasting, recommendations, and higher-level features like summarization and simplification. About the Book A machine is said to learn when its performance improves with experience. Learning requires algorithms and programs that capture data and ferret out the interestingor useful patterns. Once the specialized domain of analysts and mathematicians, machine learning is becoming a skill needed by many. Machine Learning in Action is a clearly written tutorial for developers. It avoids academic language and takes you straight to the techniques you'll use in your day-to-day work. Many (Python) examples present the core algorithms of statistical data processing, data analysis, and data visualization in code you can reuse. You'll understand the concepts and how they fit in with tactical tasks like classification, forecasting, recommendations, and higher-level features like summarization and simplification. Readers need no prior experience with machine learning or statistical processing. Familiarity with Python is helpful. Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book. What's Inside A no-nonsense introduction Examples showing common ML tasks Everyday data analysis Implementing classic algorithms like Apriori and Adaboos Table of Contents PART 1 CLASSIFICATION Machine learning basics Classifying with k-Nearest Neighbors Splitting datasets one feature at a time: decision trees Classifying with probability theory: naïve Bayes Logistic regression Support vector machines Improving classification with the AdaBoost meta algorithm PART 2 FORECASTING NUMERIC VALUES WITH REGRESSION Predicting numeric values: regression Tree-based regression PART 3 UNSUPERVISED LEARNING Grouping unlabeled items using k-means clustering Association analysis with the Apriori algorithm Efficiently finding frequent itemsets with FP-growth PART 4 ADDITIONAL TOOLS Using principal component analysis to simplify data Simplifying data with the singular value decomposition Big data and MapReduce

Download or read book Artificial Evolution written by Lhassane Idoumghar and published by Springer Nature. This book was released on 2020-04-29 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-conference proceedings of the 14th International Conference on Artificial Evolution, EA 2019, held in Mulhouse, France, in October 2019. The 16 revised papers were carefully reviewed and selected from 33 submissions. The papers cover a wide range of topics in the field of artificial evolution, such as evolutionary computation, evolutionary optimization, co-evolution, artificial life, population dynamics, theory, algorithmic and modeling, implementations, application of evolutionary paradigms to the real world (industry, biosciences...), other biologically-inspired paradigms (swarm, artificial ants, artificial immune systems, cultural algorithms...), memetic algorithms, multi-objective optimization, constraint handling, parallel algorithms, dynamic optimization, machine learning and hybridization with other soft computing techniques.

Download or read book An Architecture for Fast and General Data Processing on Large Clusters written by Matei Zaharia and published by Morgan & Claypool. This book was released on 2016-05-01 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt: The past few years have seen a major change in computing systems, as growing data volumes and stalling processor speeds require more and more applications to scale out to clusters. Today, a myriad data sources, from the Internet to business operations to scientific instruments, produce large and valuable data streams. However, the processing capabilities of single machines have not kept up with the size of data. As a result, organizations increasingly need to scale out their computations over clusters. At the same time, the speed and sophistication required of data processing have grown. In addition to simple queries, complex algorithms like machine learning and graph analysis are becoming common. And in addition to batch processing, streaming analysis of real-time data is required to let organizations take timely action. Future computing platforms will need to not only scale out traditional workloads, but support these new applications too. This book, a revised version of the 2014 ACM Dissertation Award winning dissertation, proposes an architecture for cluster computing systems that can tackle emerging data processing workloads at scale. Whereas early cluster computing systems, like MapReduce, handled batch processing, our architecture also enables streaming and interactive queries, while keeping MapReduce's scalability and fault tolerance. And whereas most deployed systems only support simple one-pass computations (e.g., SQL queries), ours also extends to the multi-pass algorithms required for complex analytics like machine learning. Finally, unlike the specialized systems proposed for some of these workloads, our architecture allows these computations to be combined, enabling rich new applications that intermix, for example, streaming and batch processing. We achieve these results through a simple extension to MapReduce that adds primitives for data sharing, called Resilient Distributed Datasets (RDDs). We show that this is enough to capture a wide range of workloads. We implement RDDs in the open source Spark system, which we evaluate using synthetic and real workloads. Spark matches or exceeds the performance of specialized systems in many domains, while offering stronger fault tolerance properties and allowing these workloads to be combined. Finally, we examine the generality of RDDs from both a theoretical modeling perspective and a systems perspective. This version of the dissertation makes corrections throughout the text and adds a new section on the evolution of Apache Spark in industry since 2014. In addition, editing, formatting, and links for the references have been added.

Download or read book Supervised Sequence Labelling with Recurrent Neural Networks written by Alex Graves and published by Springer. This book was released on 2012-02-06 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt: Supervised sequence labelling is a vital area of machine learning, encompassing tasks such as speech, handwriting and gesture recognition, protein secondary structure prediction and part-of-speech tagging. Recurrent neural networks are powerful sequence learning tools—robust to input noise and distortion, able to exploit long-range contextual information—that would seem ideally suited to such problems. However their role in large-scale sequence labelling systems has so far been auxiliary. The goal of this book is a complete framework for classifying and transcribing sequential data with recurrent neural networks only. Three main innovations are introduced in order to realise this goal. Firstly, the connectionist temporal classification output layer allows the framework to be trained with unsegmented target sequences, such as phoneme-level speech transcriptions; this is in contrast to previous connectionist approaches, which were dependent on error-prone prior segmentation. Secondly, multidimensional recurrent neural networks extend the framework in a natural way to data with more than one spatio-temporal dimension, such as images and videos. Thirdly, the use of hierarchical subsampling makes it feasible to apply the framework to very large or high resolution sequences, such as raw audio or video. Experimental validation is provided by state-of-the-art results in speech and handwriting recognition.

Download or read book Tools for Thought written by Howard Rheingold and published by MIT Press. This book was released on 2000-04-13 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: In a highly engaging style, Rheingold tells the story of what he calls the patriarchs, pioneers, and infonauts of the computer, focusing in particular on such pioneers as J. C. R. Licklider, Doug Engelbart, Bob Taylor, and Alan Kay. The digital revolution did not begin with the teenage millionaires of Silicon Valley, claims Howard Rheingold, but with such early intellectual giants as Charles Babbage, George Boole, and John von Neumann. In a highly engaging style, Rheingold tells the story of what he calls the patriarchs, pioneers, and infonauts of the computer, focusing in particular on such pioneers as J. C. R. Licklider, Doug Engelbart, Bob Taylor, and Alan Kay. Taking the reader step by step from nineteenth-century mathematics to contemporary computing, he introduces a fascinating collection of eccentrics, mavericks, geniuses, and visionaries. The book was originally published in 1985, and Rheingold's attempt to envision computing in the 1990s turns out to have been remarkably prescient. This edition contains an afterword, in which Rheingold interviews some of the pioneers discussed in the book. As an exercise in what he calls "retrospective futurism," Rheingold also looks back at how he looked forward.

Download or read book Infectious and Parasitic Diseases of Livestock written by Pierre Charles Lefevre and published by Cabi. This book was released on 2010 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years infectious livestock diseases have swept across many countries, often with dramatic consequences for animal and public health. With climatic changes modifying the distribution of vector-born diseases, emerging novel pathogens can spread rapidly in new areas, at the same time as resistance spreads in places where they are established. This calls for new approaches for the control of parasitic diseases. These two volumes present in detail over 130 viral, bacterial, fungal and parasitic diseases of large livestock species from all over the world, accompanied by very valuable and informative illustrations and photographs. Particular attention is also paid to the role of wildlife in their epidemiology, stressing the potential zoonotic characteristics of diseases where applicable and their effects on humans.

Download or read book Analysis of Neural Data written by Robert E. Kass and published by Springer. This book was released on 2014-07-08 with total page 663 pages. Available in PDF, EPUB and Kindle. Book excerpt: Continual improvements in data collection and processing have had a huge impact on brain research, producing data sets that are often large and complicated. By emphasizing a few fundamental principles, and a handful of ubiquitous techniques, Analysis of Neural Data provides a unified treatment of analytical methods that have become essential for contemporary researchers. Throughout the book ideas are illustrated with more than 100 examples drawn from the literature, ranging from electrophysiology, to neuroimaging, to behavior. By demonstrating the commonality among various statistical approaches the authors provide the crucial tools for gaining knowledge from diverse types of data. Aimed at experimentalists with only high-school level mathematics, as well as computationally-oriented neuroscientists who have limited familiarity with statistics, Analysis of Neural Data serves as both a self-contained introduction and a reference work.

Download or read book Social Media Mining written by Reza Zafarani and published by Cambridge University Press. This book was released on 2014-04-28 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: Integrates social media, social network analysis, and data mining to provide an understanding of the potentials of social media mining.

Download or read book Modelling Identification and Control written by International Association of Science and Technology for Development and published by Anaheim, Calif. ; Calgary : Acta Press. This book was released on 1984 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Neural Networks written by Raul Rojas and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 511 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neural networks are a computing paradigm that is finding increasing attention among computer scientists. In this book, theoretical laws and models previously scattered in the literature are brought together into a general theory of artificial neural nets. Always with a view to biology and starting with the simplest nets, it is shown how the properties of models change when more general computing elements and net topologies are introduced. Each chapter contains examples, numerous illustrations, and a bibliography. The book is aimed at readers who seek an overview of the field or who wish to deepen their knowledge. It is suitable as a basis for university courses in neurocomputing.