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TensorFlow: Predict valuable insights of your data with TensorFlow
by Md. Rezaul KarimLearn how to solve real life problems using different methods like logic regression, random forests and SVM’s with TensorFlow.Key FeaturesUnderstand predictive analytics along with its challenges and best practices Embedded with assessments that will help you revise the concepts you have learned in this bookBook DescriptionPredictive analytics discovers hidden patterns from structured and unstructured data for automated decision making in business intelligence. Predictive decisions are becoming a huge trend worldwide, catering to wide industry sectors by predicting which decisions are more likely to give maximum results. TensorFlow, Google’s brainchild, is immensely popular and extensively used for predictive analysis.This book is a quick learning guide on all the three types of machine learning, that is, supervised, unsupervised, and reinforcement learning with TensorFlow. This book will teach you predictive analytics for high-dimensional and sequence data. In particular, you will learn the linear regression model for regression analysis. You will also learn how to use regression for predicting continuous values. You will learn supervised learning algorithms for predictive analytics. You will explore unsupervised learning and clustering using K-meansYou will then learn how to predict neighborhoods using K-means, and then, see another example of clustering audio clips based on their audio features. This book is ideal for developers, data analysts, machine learning practitioners, and deep learning enthusiasts who want to build powerful, robust, and accurate predictive models with the power of TensorFlow. This book is embedded with useful assessments that will help you revise the concepts you have learned in this book.What you will learnLearn TensorFlow features in a real-life problem, followed by detailed TensorFlow installation and configurationExplore computation graphs, data, and programming models also get an insight into an example of implementing linear regression model for predictive analyticsSolve the Titanic survival problem using logistic regression, random forests, and SVMs for predictive analyticsDig deeper into predictive analytics and find out how to take advantage of it to cluster records belonging to the certain group or class for a dataset of unsupervised observationsLearn several examples of how to apply reinforcement learning algorithms for developing predictive models on real-life datasetsWho this book is forThis book is aimed at developers, data analysts, machine learning practitioners, and deep learning enthusiasts who want to build powerful, robust, and accurate predictive models with the power of TensorFlow.
TensorFlow Deep Learning Projects: 10 real-world projects on computer vision, machine translation, chatbots, and reinforcement learning
by Alberto Boschetti Luca Massaron Alexey Grigorev Rajalingappaa Shanmugamani Abhishek ThakurLeverage the power of Tensorflow to design deep learning systems for a variety of real-world scenariosKey FeaturesBuild efficient deep learning pipelines using the popular Tensorflow frameworkTrain neural networks such as ConvNets, generative models, and LSTMsIncludes projects related to Computer Vision, stock prediction, chatbots and moreBook DescriptionTensorFlow is one of the most popular frameworks used for machine learning and, more recently, deep learning. It provides a fast and efficient framework for training different kinds of deep learning models, with very high accuracy. This book is your guide to master deep learning with TensorFlow with the help of 10 real-world projects.TensorFlow Deep Learning Projects starts with setting up the right TensorFlow environment for deep learning. Learn to train different types of deep learning models using TensorFlow, including Convolutional Neural Networks, Recurrent Neural Networks, LSTMs, and Generative Adversarial Networks. While doing so, you will build end-to-end deep learning solutions to tackle different real-world problems in image processing, recommendation systems, stock prediction, and building chatbots, to name a few. You will also develop systems that perform machine translation, and use reinforcement learning techniques to play games.By the end of this book, you will have mastered all the concepts of deep learning and their implementation with TensorFlow, and will be able to build and train your own deep learning models with TensorFlow confidently.What you will learnSet up the TensorFlow environment for deep learningConstruct your own ConvNets for effective image processingUse LSTMs for image caption generationForecast stock prediction accurately with an LSTM architectureLearn what semantic matching is by detecting duplicate Quora questionsSet up an AWS instance with TensorFlow to train GANsTrain and set up a chatbot to understand and interpret human inputBuild an AI capable of playing a video game by itself –and win it!Who this book is forThis book is for data scientists, machine learning developers as well as deep learning practitioners, who want to build interesting deep learning projects that leverage the power of Tensorflow. Some understanding of machine learning and deep learning, and familiarity with the TensorFlow framework is all you need to get started with this book.
TensorFlow for Deep Learning: From Linear Regression to Reinforcement Learning
by Bharath Ramsundar Reza Bosagh ZadehLearn how to solve challenging machine learning problems with Tensorflow, Google’s revolutionary new system for deep learning. If you have some background with basic linear algebra and calculus, this practical book shows you how to build—and when to use—deep learning architectures. You’ll learn how to design systems capable of detecting objects in images, understanding human speech, analyzing video, and predicting the properties of potential medicines.TensorFlow for Deep Learning teaches concepts through practical examples and builds understanding of deep learning foundations from the ground up. It’s ideal for practicing developers comfortable with designing software systems, but not necessarily with creating learning systems. This book is also useful for scientists and other professionals who are comfortable with scripting, but not necessarily with designing learning algorithms.Gain in-depth knowledge of the TensorFlow API and primitives.Understand how to train and tune machine learning systems with TensorFlow on large datasets.Learn how to use TensorFlow with convolutional networks, recurrent networks, LSTMs, and reinforcement learning.
TensorFlow For Dummies
by Matthew ScarpinoBecome a machine learning pro! Google TensorFlow has become the darling of financial firms and research organizations, but the technology can be intimidating and the learning curve is steep. Luckily, TensorFlow For Dummies is here to offer you a friendly, easy-to-follow book on the subject. Inside, you’ll find out how to write applications with TensorFlow, while also grasping the concepts underlying machine learning—all without ever losing your cool! Machine learning has become ubiquitous in modern society, and its applications include language translation, robotics, handwriting analysis, financial prediction, and image recognition. TensorFlow is Google's preeminent toolset for machine learning, and this hands-on guide makes it easy to understand, even for those without a background in artificial intelligence. Install TensorFlow on your computer Learn the fundamentals of statistical regression and neural networks Visualize the machine learning process with TensorBoard Perform image recognition with convolutional neural networks (CNNs) Analyze sequential data with recurrent neural networks (RNNs) Execute TensorFlow on mobile devices and the Google Cloud Platform (GCP) If you’re a manager or software developer looking to use TensorFlow for machine learning, this is the book you’ll want to have close by.
TensorFlow für Dummies (Für Dummies)
by Matthew ScarpinoTensorFlow ist Googles herausragendes Werkzeug für das maschinelle Lernen, und dieses Buch macht es zugänglich, selbst wenn Sie bisher wenig über neuronale Netze und Deep Learning wissen. Sie erfahren, auf welchen Prinzipien TensorFlow basiert und wie Sie mit TensorFlow Anwendungen 1.0 schreiben. Gleichzeitig lernen Sie die Konzepte des maschinellen Lernens kennen. Wenn Sie Softwareentwickler sind und TensorFlow in Zukunft einsetzen möchten, dann ist dieses Buch der richtige Einstieg für Sie. Greifen Sie auch zu, wenn Sie einfach mehr über das maschinelle Lernen erfahren wollen.
TensorFlow Machine Learning Cookbook: Over 60 recipes to build intelligent machine learning systems with the power of Python, 2nd Edition
by Nick McClureSkip the theory and get the most out of Tensorflow to build production-ready machine learning modelsKey FeaturesExploit the features of Tensorflow to build and deploy machine learning modelsTrain neural networks to tackle real-world problems in Computer Vision and NLPHandy techniques to write production-ready code for your Tensorflow modelsBook DescriptionTensorFlow is an open source software library for Machine Intelligence. The independent recipes in this book will teach you how to use TensorFlow for complex data computations and allow you to dig deeper and gain more insights into your data than ever before. With the help of this book, you will work with recipes for training models, model evaluation, sentiment analysis, regression analysis, clustering analysis, artificial neural networks, and more. You will explore RNNs, CNNs, GANs, reinforcement learning, and capsule networks, each using Google's machine learning library, TensorFlow. Through real-world examples, you will get hands-on experience with linear regression techniques with TensorFlow. Once you are familiar and comfortable with the TensorFlow ecosystem, you will be shown how to take it to production.By the end of the book, you will be proficient in the field of machine intelligence using TensorFlow. You will also have good insight into deep learning and be capable of implementing machine learning algorithms in real-world scenarios.What you will learnBecome familiar with the basic features of the TensorFlow libraryGet to know Linear Regression techniques with TensorFlowLearn SVMs with hands-on recipesImplement neural networks to improve predictive modelingApply NLP and sentiment analysis to your dataMaster CNN and RNN through practical recipesImplement the gradient boosted random forest to predict housing pricesTake TensorFlow into productionWho this book is forIf you are a data scientist or a machine learning engineer with some knowledge of linear algebra, statistics, and machine learning, this book is for you. If you want to skip the theory and build production-ready machine learning models using Tensorflow without reading pages and pages of material, this book is for you. Some background in Python programming is assumed.
TensorFlow Machine Learning Projects
by Ankit JainThis book is for data analysts, data scientists, machine learning professionals and developers, and deep learning enthusiasts with basic knowledge of TensorFlow. If you want to build end-to-end projects in machine learning domain this book is what you need! This book appeals for anyone who is looking to go beyond the basics of TensorFlow and want to know how it can be used in various domains.
Teradata Cookbook: Over 85 recipes to implement efficient data warehousing solutions
by Abhinav Khandelwal Rajsekhar BhamidipatiData management and analytics simplified with Teradata Key Features Take your understanding of Teradata to the next level and build efficient data warehousing applications for your organization Covers recipes on data handling, warehousing, advanced querying and the administrative tasks in Teradata. Contains practical solutions to tackle common (and not-so-common) problems you might encounter in your day to day activities Book Description Teradata is an enterprise software company that develops and sells its eponymous relational database management system (RDBMS), which is considered to be a leading data warehousing solutions and provides data management solutions for analytics. This book will help you get all the practical information you need for the creation and implementation of your data warehousing solution using Teradata. The book begins with recipes on quickly setting up a development environment so you can work with different types of data structuring and manipulation function. You will tackle all problems related to efficient querying, stored procedure searching, and navigation techniques. Additionally, you’ll master various administrative tasks such as user and security management, workload management, high availability, performance tuning, and monitoring. This book is designed to take you through the best practices of performing the real daily tasks of a Teradata DBA, and will help you tackle any problem you might encounter in the process. What you will learn Understand Teradata's competitive advantage over other RDBMSs. Use SQL to process data stored in Teradata tables. Leverage Teradata’s available application utilities and parallelism to play with large datasets Apply various performance tuning techniques to optimize the queries. Acquire deeper knowledge and understanding of the Teradata Architecture. Easy steps to load, archive, restore data and implement Teradata protection features Gain confidence in running a wide variety of Data analytics and develop applications for the Teradata environment Who this book is for This book is for Database administrator's and Teradata users who are looking for a practical, one-stop resource to solve all their problems while handling their Teradata solution. If you are looking to learn the basic as well as the advanced tasks involved in Teradata querying or administration, this book will be handy. Some knowledge of relational database concepts will be helpful to get the best out of this book.
The Test and Launch Control Technology for Launch Vehicles
by Zhengyu SongThis book presents technologies and solutions related to the test and launch control of rockets and other vehicles, and offers the first comprehensive and systematic introduction to the contributions of the Chinese Long March (Chang Zheng in Chinese, or abbreviated as CZ) rockets in this field. Moreover, it discusses the role of this technology in responsive, reliable, and economical access to space, which is essential for the competitiveness of rockets. The need for rapid development of the aerospace industry for both governmental and commercial projects is addressed. This book is a valuable reference resource for practitioners, and many examples and resources are included, not only from Chinese rockets but also from many other vehicles. It covers guidelines, technologies, and solutions on testing and launch control before rocket takeoff, covering equipment-level testing, system-level testing, simulation tests, etc.
Test-Driven Java Development, Second Edition: Invoke TDD principles for end-to-end application development, 2nd Edition
by Alex Garcia Viktor FarcicThis book will teach the concepts of test driven development in Java so you can build clean, maintainable and robust codeKey Features Explore the most popular TDD tools and frameworks and become more proficient in building applications Create applications with better code design, fewer bugs, and higher test coverage, enabling you to get them to market quickly Implement test-driven programming methods into your development workflowsBook DescriptionTest-driven development (TDD) is a development approach that relies on a test-first procedure that emphasizes writing a test before writing the necessary code, and then refactoring the code to optimize it.The value of performing TDD with Java, one of the longest established programming languages, is to improve the productivity of programmers and the maintainability and performance of code, and develop a deeper understanding of the language and how to employ it effectively.Starting with the basics of TDD and understanding why its adoption is beneficial, this book will take you from the first steps of TDD with Java until you are confident enough to embrace the practice in your day-to-day routine.You'll be guided through setting up tools, frameworks, and the environment you need, and we will dive right into hands-on exercises with the goal of mastering one practice, tool, or framework at a time. You'll learn about the Red-Green-Refactor procedure, how to write unit tests, and how to use them as executable documentation.With this book, you'll also discover how to design simple and easily maintainable code, work with mocks, utilize behavior-driven development, refactor old legacy code, and release a half-finished feature to production with feature toggles.You will finish this book with a deep understanding of the test-driven development methodology and the confidence to apply it to application programming with Java.What you will learn Explore the tools and frameworks required for effective TDD development Perform the Red-Green-Refactor process efficiently, the pillar around which all other TDD procedures are based Master effective unit testing in isolation from the rest of your code Design simple and easily maintainable code by implementing different techniques Use mocking frameworks and techniques to easily write and quickly execute tests Develop an application to implement behavior-driven development in conjunction with unit testing Enable and disable features using feature togglesWho this book is forIf you're an experienced Java developer and want to implement more effective methods of programming systems and applications, then this book is for you.
Testing and Tuning Market Trading Systems: Algorithms in C++
by Timothy MastersBuild, test, and tune financial, insurance or other market trading systems using C++ algorithms and statistics. You’ve had an idea and have done some preliminary experiments, and it looks promising. Where do you go from here? Well, this book discusses and dissects this case study approach. Seemingly good backtest performance isn't enough to justify trading real money. You need to perform rigorous statistical tests of the system's validity. Then, if basic tests confirm the quality of your idea, you need to tune your system, not just for best performance, but also for robust behavior in the face of inevitable market changes. Next, you need to quantify its expected future behavior, assessing how bad its real-life performance might actually be, and whether you can live with that. Finally, you need to find its theoretical performance limits so you know if its actual trades conform to this theoretical expectation, enabling you to dump the system if it does not live up to expectations.This book does not contain any sure-fire, guaranteed-riches trading systems. Those are a dime a dozen... But if you have a trading system, this book will provide you with a set of tools that will help you evaluate the potential value of your system, tweak it to improve its profitability, and monitor its on-going performance to detect deterioration before it fails catastrophically. Any serious market trader would do well to employ the methods described in this book.What You Will LearnSee how the 'spaghetti-on-the-wall' approach to trading system development can be done legitimatelyDetect overfitting early in developmentEstimate the probability that your system's backtest results could have been due to just good luckRegularize a predictive model so it automatically selects an optimal subset of indicator candidatesRapidly find the global optimum for any type of parameterized trading systemAssess the ruggedness of your trading system against market changesEnhance the stationarity and information content of your proprietary indicatorsNest one layer of walkforward analysis inside another layer to account for selection bias in complex trading systemsCompute a lower bound on your system's mean future performanceBound expected periodic returns to detect on-going system deterioration before it becomes severeEstimate the probability of catastrophic drawdown Who This Book Is For Experienced C++ programmers, developers, and software engineers. Prior experience with rigorous statistical procedures to evaluate and maximize the quality of systems is recommended as well.
Testing Angular Applications
by Corinna Cohn Michael Giambalvo Jesse Palmer Craig NishinaSummaryTesting Angular Applications is an example-rich, hands-on guide that gives you the real-world techniques you need to thoroughly test all parts of your Angular applications. By the end of this book, you'll be able to confidently write unit and end-to-end tests for Angular applications in TypeScript.Foreword by Brad Green, Google.Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.About the TechnologyDon't leave the success of your mission-critical Angular apps to chance. Proper testing improves code quality, reduces maintenance costs, and rewards you with happy users. New tools and best practices can streamline and automate all aspects of testing web apps, both in development and in production. This book gets you started.About the BookTesting Angular Applications teaches you how to make testing an essential part of your development and production processes. You'll start by setting up a simple unit testing system as you learn the fundamental practices. Then, you'll fine-tune it as you discover the best tests for Angular components, directives, pipes, services, and routing. Finally, you'll explore end-to-end testing, mastering the Protractor framework, and inserting Angular apps into your continuous integration pipeline.What's insideGetting to know TypeScriptWriting and debugging unit testsWriting and debugging end-to-end tests with ProtractorBuilding continuous integration for your entire test suiteAbout the ReaderThis book is for readers with intermediate JavaScript skills.About the AuthorJesse Palmer is a senior engineering manager at Handshake. Corinna Cohn is a single-page web application specialist. Mike Giambalvo and Craig Nishina are engineers at Google.Table of ContentsIntroduction to testing Angular applicationsPART 1 - Unit testingCreating your first testsTesting componentsTesting directivesTesting pipesTesting servicesTesting the routerPART 2 - End-to-end testingGetting started with ProtractorUnderstanding timeoutsAdvanced Protractor topicsPART 3 - Continuous integrationContinuous integrationAppendix A - Setting up the sample projectAppendix B - Additional resources
Testing Software and Systems: 30th IFIP WG 6.1 International Conference, ICTSS 2018, Cádiz, Spain, October 1-3, 2018, Proceedings (Lecture Notes in Computer Science #11146)
by Inmaculada Medina-Bulo Mercedes G. Merayo Robert HieronsThis book constitutes the refereed proceedings of the 30th IFIP WG 6.1 International Conference on Testing Software and Systems, ICTSS 2018, held in Cádiz, Spain, in October 2018. The 8 regular and 6 short papers presented were carefully reviewed and selected from 29 submissions. ICTSS is a series of international conferences addressing the conceptual, theoretic, and practical problems of testing software systems, including communication protocols, services, distributed platforms, middleware, embedded- and cyber-physical-systems, and security infrastructures.
Testing Vue.js Applications
by Edd YerburghSummaryTesting Vue.js Applications is a comprehensive guide to testing Vue components, methods, events, and output. Author Edd Yerburgh, creator of the Vue testing utility, explains the best testing practices in Vue along with an evergreen methodology that applies to any web dev process.Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.About the TechnologyWeb developers who use the Vue framework love its reliability, speed, small footprint, and versatility. Vue's component-based approach and use of DOM methods require you to adapt your app-testing practices. Learning Vue-specific testing tools and strategies will ensure your apps run like they should.About the BookWith Testing Vue.js Applications, you'll discover effective testing methods for Vue applications. You'll enjoy author Edd Yerburgh's engaging style and fun real-world examples as you learn to use the Jest framework to run tests for a Hacker News application built with Vue, Vuex, and Vue Router. This comprehensive guide teaches the best testing practices in Vue along with an evergreen methodology that applies to any web dev process.What's insideUnit tests, snapshot tests, and end-to-end testsWriting unit tests for Vue componentsWriting tests for Vue mixins, Vuex, and Vue RouterAdvanced testing techniques, like mockingAbout the ReaderWritten for Vue developers at any level.About the AuthorEdd Yerburgh is a JavaScript developer and Vue core team member. He's the main author of the Vue Test Utils library and is passionate about open source tooling for testing component-based applications.Table of ContentsIntroduction to testing Vue applicationsCreating your first testTesting rendered component outputTesting component methodsTesting eventsUnderstanding VuexTesting VuexOrganizing tests with factory functionsUnderstanding Vue RouterTesting Vue RouterTesting mixins and filtersWriting snapshot testsTesting server-side renderingWriting end-to-end testsAPPENDIXESA - Setting up your environmentB - Running the production buildC - Exercise answers
Tests and Proofs: 12th International Conference, TAP 2018, Held as Part of STAF 2018, Toulouse, France, June 27-29, 2018, Proceedings (Lecture Notes in Computer Science #10889)
by Catherine Dubois Burkhart WolffThis book constitutes the refereed proceedings of the 12th International Conference on Tests and Proofs, TAP 2018, held as part of STAF 2018, in Toulouse, France, in June 2018. The 8 regular papers, 2 short papers, 1 invited paper and 1 invited tutorial presented in this volume were carefully reviewed and selected from 18 submissions. The TAP conference promotes research in verification and formal methods that targets the interplay of proofs and testing: the advancement of techniques of each kind and their combination, with the ultimate goal of improving software and system dependability.
Text, Speech, and Dialogue: 21st International Conference, TSD 2018, Brno, Czech Republic, September 11-14, 2018, Proceedings (Lecture Notes in Computer Science #11107)
by Petr Sojka Aleš Horák Ivan Kopeček Karel PalaThis book constitutes the refereed proceedings of the 21st International Conference on Text, Speech, and Dialogue, TSD 2018, held in Brno, Czech Republic, in September 2018. The 56 regular papers were carefully reviewed and selected from numerous submissions. They focus on topics such as corpora and language resources, speech recognition, tagging, classification and parsing of text and speech, speech and spoken language generation, semantic processing of text and search, integrating applications of text and speech processing, machine translation, automatic dialogue systems, multimodal techniques and modeling.
Textual and Visual Information Retrieval using Query Refinement and Pattern Analysis
by S. G. Shaila A VadivelThis book offers comprehensive coverage of information retrieval by considering both Text Based Information Retrieval (TBIR) and Content Based Image Retrieval (CBIR), together with new research topics. The approach to TBIR is based on creating a thesaurus, as well as event classification and detection. N-gram thesaurus generation for query refinement offers a new method for improving the precision of retrieval, while event classification and detection approaches aid in the classification and organization of information using web documents for domain-specific retrieval applications. In turn, with regard to content based image retrieval (CBIR) the book presents a histogram construction method, which is based on human visual perceptions of color. The book’s overarching goal is to introduce readers to new ideas in an easy-to-follow manner.
Textual Data Science with R (Chapman & Hall/CRC Computer Science & Data Analysis)
by Mónica Bécue-BertautTextual Statistics with R comprehensively covers the main multidimensional methods in textual statistics supported by a specially-written package in R. Methods discussed include correspondence analysis, clustering, and multiple factor analysis for contigency tables. Each method is illuminated by applications. The book is aimed at researchers and students in statistics, social sciences, hiistory, literature and linguistics. The book will be of interest to anyone from practitioners needing to extract information from texts to students in the field of massive data, where the ability to process textual data is becoming essential.
Theoretical and Applied Aspects of Systems Biology (Computational Biology #27)
by Fabricio Alves Barbosa da Silva Nicolas Carels Floriano Paes Silva JuniorThis book presents the theoretical foundations of Systems Biology, as well as its application in studies on human hosts, pathogens and associated diseases. This book presents several chapters written by renowned experts in the field. Some topics discussed in depth in this book include: computational modeling of multiresistant bacteria, systems biology of cancer, systems immunology, networks in systems biology.
Theoretical Computer Science: 36th National Conference, NCTCS 2018, Shanghai, China, October 13–14, 2018, Proceedings (Communications in Computer and Information Science #882)
by Lian Li Pinyan Lu Kun HeThis book constitutes the thoroughly refereed proceedings of the National Conference of Theoretical Computer Science, NCTCS 2018, held in Shanghai, China, in October 2018. The 11 full papers presented were carefully reviewed and selected from 31 submissions. They present relevant trends of current research in the area of algorithms and complexity, software theory and method, data science and machine learning theory.
Theory and Applications of Image Registration
by A. Ardeshir GoshtasbyA hands-on guide to image registration theory and methods—with examples of a wide range of real-world applications Theory and Applications of Image Registration offers comprehensive coverage of feature-based image registration methods. It provides in-depth exploration of an array of fundamental issues, including image orientation detection, similarity measures, feature extraction methods, and elastic transformation functions. Also covered are robust parameter estimation, validation methods, multi-temporal and multi-modality image registration, methods for determining the orientation of an image, methods for identifying locally unique neighborhoods in an image, methods for detecting lines in an image, methods for finding corresponding points and corresponding lines in images, registration of video images to create panoramas, and much more. Theory and Applications of Image Registration provides readers with a practical guide to the theory and underpinning principles. Throughout the book numerous real-world examples are given, illustrating how image registration can be applied to problems in various fields, including biomedicine, remote sensing, and computer vision. Also provided are software routines to help readers develop their image registration skills. Many of the algorithms described in the book have been implemented, and the software packages are made available to the readers of the book on a companion website. In addition, the book: Explores the fundamentals of image registration and provides a comprehensive look at its multi-disciplinary applications Reviews real-world applications of image registration in the fields of biomedical imaging, remote sensing, computer vision, and more Discusses methods in the registration of long videos in target tracking and 3-D reconstruction Addresses key research topics and explores potential solutions to a number of open problems in image registration Includes a companion website featuring fully implemented algorithms and image registration software for hands-on learning Theory and Applications of Image Registration is a valuable resource for researchers and professionals working in industry and government agencies where image registration techniques are routinely employed. It is also an excellent supplementary text for graduate students in computer science, electrical engineering, software engineering, and medical physics.
Theory and Applications of Satisfiability Testing – SAT 2018: 21st International Conference, SAT 2018, Held as Part of the Federated Logic Conference, FloC 2018, Oxford, UK, July 9–12, 2018, Proceedings (Lecture Notes in Computer Science #10929)
by Olaf Beyersdorff Christoph M. WintersteigerThis book constitutes the refereed proceedings of the 21st International Conference on Theory and Applications of Satisfiability Testing, SAT 2018, held in Oxford, UK, in July 2018.The 20 revised full papers, 4 short papers, and 2 tool papers were carefully reviewed and selected from 58 submissions. The papers address different aspects of SAT interpreted in a broad sense, including theoretical advances (such as exact algorithms, proof complexity, and other complexity issues), practical search algorithms, knowledge compilation, implementation-level details of SAT solvers and SAT-based systems, problem encodings and reformulations, applications as well as case studies and reports on findings based on rigorous experimentation. They are organized in the following topical sections: maximum satisfiability; conflict driven clause learning; model counting; quantified Boolean formulae; theory; minimally unsatisfiable sets; satisfiability modulo theories; and tools and applications.
The Theory and Craft of Digital Preservation
by Trevor OwensA guide to managing data in the digital age.Winner of the ALCTS Outstanding Publication Award by the Association for Library Collections & Technical Services, Winner of the Waldo Gifford Leland Award by the Society of American ArchivistsMany people believe that what is on the Internet will be around forever. At the same time, warnings of an impending "digital dark age"—where records of the recent past become completely lost or inaccessible—appear with regular frequency in the popular press. It's as if we need a system to safeguard our digital records for future scholars and researchers. Digital preservation experts, however, suggest that this is an illusory dream not worth chasing. Ensuring long-term access to digital information is not that straightforward; it is a complex issue with a significant ethical dimension. It is a vocation.In The Theory and Craft of Digital Preservation, librarian Trevor Owens establishes a baseline for practice in this field. In the first section of the book, Owens synthesizes work on the history of preservation in a range of areas (archives, manuscripts, recorded sound, etc.) and sets that history in dialogue with work in new media studies, platform studies, and media archeology. In later chapters, Owens builds from this theoretical framework and maps out a more deliberate and intentional approach to digital preservation. A basic introduction to the issues and practices of digital preservation, the book is anchored in an understanding of the traditions of preservation and the nature of digital objects and media. Based on extensive reading, research, and writing on digital preservation, Owens's work will prove an invaluable reference for archivists, librarians, and museum professionals, as well as scholars and researchers in the digital humanities.
Theory and Practice of Model Transformation: 11th International Conference, ICMT 2018, Held as Part of STAF 2018, Toulouse, France, June 25–26, 2018, Proceedings (Lecture Notes in Computer Science #10888)
by Arend Rensink Jesús Sánchez CuadradoThis book constitutes the refereed proceedings of the 11th International Conference on Model Transformation, ICMT 2018, held as part of STAF 2018, in Toulouse, France, in June 2018.The 9 full papers were carefully reviewed and selected from 24 submissions. This book also presents 1 invited paper. The papers include research, application, and tool demonstration papers presented in the context of four sessions on verification of model transformations, model transformation tools, transformation reuse and graph transformations.
Theory and Practice of Natural Computing: 7th International Conference, TPNC 2018, Dublin, Ireland, December 12–14, 2018, Proceedings (Lecture Notes in Computer Science #11324)
by Michael O'Neill Carlos Martín-Vide Miguel A. Vega-Rodríguez David FaganThis book constitutes the refereed proceedings of the 7th International Conference on Theory and Practice of Natural Computing, TPNC 2017, held in Dublin, Ireland, in December 2018. The 35 full papers presented in this book, together with one invited talk, were carefully reviewed and selected from 69 submissions. The papers are organized around the following topical sections: applications of natural computing as algorithms, bioinformatics, control, cryptography, design, economics. The more theoretical contributions handle with artificial chemistry, artificial immune systems, artificial life, cellular automata, cognitive computing, cognitive engineering, cognitive robotics, collective behaviour, complex systems, computational intelligence, computational social science, computing with words, developmental systems, DNA computing, DNA nanotechnology, evolutionary algorithms, evolutionary computing, evolutionary game theory, fractal geometry, fuzzy control, fuzzy logic, fuzzy sets, fuzzy systems, genetic algorithms, genetic programming, granular computing, heuristics, intelligent agents, intelligent systems, machine intelligence, molecular programming, neural computing, neural networks, quantum communication, quantum computing, rough sets, self-assembly.