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Cloud Native Architecture and Design : A Handbook for Modern Day Architecture and Design with Enterprise-Grade Examples
Explains the fundamentals of cloud-native architecture and services, what cloud principles and patterns to use, and details of designing a cloud-native element. And Progresses to cover the details of how IT systems can modernize to embrace cloud-native architecture, and also provides details of various enterprise assessment techniques to decide what systems can move and cannot move into the cloud. Architecting and designing a cloud-native system isn’t possible without modernized software engineering principles, the culture of automation, and the culture of innovation. As such, this book covers the details of cloud-native software engineering methodologies, and process, and how to adopt an automated governance approach across enterprises with the adoption of artificial intelligence. You will: Discover cloud-native principles and patterns, and how you can leverage them to solve your business problems ; Gain the techniques and concepts you need to adapt to design a cloud-native application ; Use assessment techniques and tools for IT modernization ; Apply cloud-native engineering principles to the culture of automation and culture of innovation ; Harness the techniques and tools to run your cloud-native applications and automate infrastructure ; Operate your cloud-native applications by using AI techniques and zero operation techniques
Clinical text mining : Secondary use of electronic patient records
Describes the results of natural language processing and machine learning methods applied to clinical text from electronic patient records. It is divided into twelve chapters. Chapters 1-4 discuss the history and background of the original paper-based patient records, their purpose, and how they are written and structured. These initial chapters do not require any technical or medical background knowledge. The remaining eight chapters are more technical in nature and describe various medical classifications and terminologies such as ICD diagnosis codes, SNOMED CT, MeSH, UMLS, and ATC. Chapters 5-10 cover basic tools for natural language processing and information retrieval, and how to apply them to clinical text. The book’s closing chapters present a number of applications in clinical text mining and summarise the lessons learned from the previous chapters.
Mathematical modeling of the human brain : From magnetic resonance images to finite element simulation
This book bridges common tools in medical imaging and neuroscience with the numerical solution of brain modelling PDEs. The connection between these areas is established through the use of two existing tools, FreeSurfer and FEniCS, and one novel tool, the SVM-Tk, developed for this book. The reader will learn the basics of magnetic resonance imaging and quickly proceed to generating their first FEniCS brain meshes from T1-weighted images.
Mathematical Knowledge Management ; Vol. 4108 ; 5th International Conference, MKM 2006, Wokingham, UK, August 11-12, 2006, Proceedings
This book constitutes the refereed proceedings of the 5th International Conference on Mathematical Knowledge Management, MKM 2006, held in Wokingham, UK in August 2006 as official satellite event of the International Congress of Mathematicians, ICM 2006. The 22 revised full papers presented were carefully selected during two rounds of reviewing and improvement. The papers in this volume cover the whole area of mathematical knowledge management in the intersection of mathematics, computer science, library science, and scientific publishing. The papers are organized in topical sections on proof representations, proof processing, knowledge extraction, knowledge representation, as well as systems and tools.
Mathematical Approaches to Software Quality
This book considers the potential and limitations of the various mathematical approaches and thereby aims to give a balanced view of the usability of each mathematical approach. Written with both student and professional in mind, this book assists the reader in applying mathematical methods to solve practical problems that are relevant to software engineers. It is suitable for coursework or self-study and there is helpful material on tools to support the various mathematical approaches.
Many-Core Computing : Hardware and software
Provides a timely and coherent account of the recent advances in many-core computing research. Starting with programming models, operating systems and their applications; it presents runtime management techniques, followed by system modelling, verification and testing methods, and architectures and systems. Computing has moved away from a focus on performance-centric serial computation, instead towards energy-efficient parallel computation. This provides continued performance increases without increasing clock frequencies, and overcomes the thermal and power limitations of the dark-silicon era. As the number of parallel cores increases, we transition into the many-core computing era. There is considerable interest in developing methods, tools, architectures and applications to support many-core computing.
Making Grids Work ; Proceedings of the CoreGRID Workshop on Programming Models Grid and P2P System Architecture Grid Systems, Tools and Environments 12-13 June 2007, Heraklion, Crete, Greece
Making Grids Work includes selected articles from the CoreGRID Workshop on Grid Programming Models, Grid and P2P Systems Architecture, Grid Systems, Tools and Environments held at the Institute of Computer Science, Foundation for Research and Technology - Hellas in Crete, Greece, June 2007. This workshop brought together representatives of the academic and industrial communities performing Grid research in Europe. Organized within the context of the CoreGRID Network of Excellence, this workshop provided a forum for the presentation and exchange of views on the latest developments in Grid Technology research. This volume is the 7th in the series of CoreGRID books.
Machine Learning Refined : Foundations, Algorithms, and Applications
Provides students with the fundamental knowledge and practical tools needed to conduct research and build data-driven products. The authors prioritize geometric intuition and algorithmic thinking, and include detail on all the essential mathematical prerequisites, to offer a fresh and accessible way to learn. Practical applications are emphasized, with examples from disciplines including computer vision, natural language processing, economics, neuroscience, recommender systems, physics, and biology.
Machine learning refined : Foundations, algorithms, and applications
Providing a unique approach to machine learning, this text contains fresh and intuitive, yet rigorous, descriptions of all fundamental concepts necessary to conduct research, build products, tinker, and play. By prioritizing geometric intuition, algorithmic thinking, and practical real world applications in disciplines including computer vision, natural language processing, economics, neuroscience, recommender systems, physics, and biology, this text provides readers with both a lucid understanding of foundational material as well as the practical tools needed to solve real-world problems. With in-depth Python and MATLAB/OCTAVE-based computational exercises and a complete treatment of cutting edge numerical optimization techniques, this is an essential resource for students and an ideal reference for researchers and practitioners working in machine learning, computer science, electrical engineering, signal processing, and numerical optimization
Machine Learning for Cyber Agents : Attack and Defence
The cyber world has been both enhanced and endangered by AI. On the one hand, the performance of many existing security services has been improved, and new tools created. On the other, it entails new cyber threats both through evolved attacking capacities and through its own imperfections and vulnerabilities. Moreover, quantum computers are further pushing the boundaries of what is possible, by making machine learning cyber agents faster and smarter.
Machine Learning Approaches in Cyber Security Analytics
Introduces various machine learning methods for cyber security analytics. With an overwhelming amount of data being generated and transferred over various networks, monitoring everything that is exchanged and identifying potential cyber threats and attacks poses a serious challenge for cyber experts. Further, as cyber attacks become more frequent and sophisticated, there is a requirement for machines to predict, detect, and identify them more rapidly. Machine learning offers various tools and techniques to automate and quickly predict, detect, and identify cyber attacks.
Machine Learning and Data Mining in Pattern Recognition ; 4th International Conference, MLDM 2005, Leipzig, Germany, July 9-11, 2005, Proceedings
Today, artificial intelligence deals with large amounts of data and knowledge and finds new information using machine learning and data mining. Machine learning and data mining are irreplaceable subjects and tools for the theory of pattern recognition and in applications of pattern recognition such as bioinformatics and data retrieval. This was the fourth edition of MLDM in Pattern Recognition which is the main event of Technical Committee 17 of the International Association for Pattern Recognition; it started out as a workshop and continued as a conference in 2003. Today, there are many international meetings which are titled “machine learning” and “data mining”, whose topics are text mining, knowledge discovery, and applications. This meeting from the first focused on aspects of machine learning and data mining in pattern recognition problems. We planned to reorganize classical and well-established pattern recognition paradigms from the viewpoints of machine learning and data mining. Though it was a challenging program in the late 1990s, the idea has inspired new starting points in pattern recognition and effects in other areas such as cognitive computer vision.
Machine learning and big data : Concepts, algorithms, tools and applications
Showcase novel use-cases and applications, present empirical research results from user-centered qualitative and quantitative experiments of these new applications, and facilitate a discussion forum to explore the latest trends in big data and machine learning by providing algorithms which can be trained to perform interdisciplinary techniques such as statistics, linear algebra, and optimization and also create automated systems that can sift through large volumes of data at high speed to make predictions or decisions without human intervention
Long-Term Preservation of Digital Documents : Principles and Practices
Key to our culture is that we can disseminate information, and then maintain and access it over time. While we are rapidly advancing from vulnerable physical solutions to superior, digital media, preserving and using data over the long term involves complicated research challenges and organization efforts. Uwe Borghoff and his coauthors address the problem of storing, reading, and using digital data for periods longer than 50 years. They briefly describe several markup and document description languages like TIFF, PDF, HTML, and XML, explain the most important techniques such as migration and emulation, and present the OAIS (Open Archival Information System) Reference Model. To complement this background information on the technology issues the authors present the most relevant international preservation projects, such as the Dublin Core Metadata Initiative, and experiences from sample projects run by the Cornell University Library and the National Library of the Netherlands. A rated survey list of available systems and tools completes the book.
Logic-Based Program Synthesis and Transformation ; 17th International Symposium, LOPSTR 2007, Kongens Lyngby, Denmark, August 23-24, 2007, Revised Selected Papers
Contains a selectionofthe the paperspresentedatthe 17thInter- tional Symposium on Logic-Based Program Synthesis and Transformation, that was held in Kongens Lyngby, Denmark, August 23-24,2007. LOPSTR thus traditionally solicits papers in the areas of: specification, synthesis, verification, transformation, analysis, optimization, composition, security, reuse, applications andtools, component-baseds of tware development, software architectures, age- based software development and program refnement. Formal proceedings are produced only after the symposium, so that authors can incorporate this feed back in the published papers.
Logic Programming ; Vol. 3668 : 21st International Conference, ICLP 2005, Sitges, Spain, October 2-5, 2005, Proceedings
This volume contains the proceedings of the 21st International Conference on Logic Programming which was held in Sitges (Barcelona), Spain, from October 2nd to 5th, 2005. The conference was colocated with the International Conf- ence on ConstraintProgramming(CP 2005)and the following 6 post-conference workshops: – CICLOPS 2005: Colloquium on Implementation of Constraint and Logic Programming Systems – CSLP 2005: Constraint Solving and Language Processing – WCB 2005: Constraint Based Methods for Bioinformatics – WLPE 2005: Logic-Based Methods in Programming Environments – MoVeLog 2005: Mobile Code Safety and Program Veri?cation Using C- putational Logic Tools – CHR 2005: Constraint Handling Rules The conferencecoincided with a solareclipse
Logic Based Program Synthesis and Transformation ; Vol. 3901 ; 15th International Symposium, LOPSTR 2005, London, UK, September 7-9, 2005, Revised Selected Papers
This book constitutes the thoroughly refereed post-proceedings of the 15th International Symposium on Logic Based Program Synthesis and Transformation, LOPSTR 2005, held in September 2005. The papers are organized in topical sections on tools for program development, program transformations, and software development and program analysis.
Location, Transport and Land-Use : Modelling Spatial-Temporal Information
Shows the use of statistical tools for forecasting and analyzing implications of land-use decisions. The idea is that la- use on a map is necessarily a consequence of individual, and often conflicting, siting decisions over time.
Leveraging Data Science for Global Health
Explores ways to leverage information technology and machine learning to combat disease and promote health, especially in resource-constrained settings. It focuses on digital disease surveillance through the application of machine learning to non-traditional data sources.
Leveraging Applications of Formal Methods ; 1st International Symposium, ISoLA 2004, Paphos, Cyprus, October 30 - November 2, 2004, Revised Selected Papers
This book constitutes the thoroughly refereed post-proceedings of the First International Symposium on Leveraging Applications of Formal Methods, ISoLA 2004, held in Paphos, Cyprus in October/November 2004. The 12 revised full papers presented were carefully selected from more than 70 submissions. The papers discuss issues related to the adoption and use of rigorous tools and methods for the specification, analysis, verification, certification, construction, test, and maintenance of systems. In particular, by discussing common problems, requirements, algorithms, methodologies, and practices, ISoLA aims at supporting researchers in their quest to improve the utility, reliability, flexibility, and efficiency of tools for building systems, and users in their search for adequate solutions to their problems.
