This book features papers from CEPE-IACAP 2015, a joint international conference focused on the philosophy of computing. Inside, readers will discover essays that explore current issues in epistemology, philosophy of mind, logic, and philosophy of science from the lens of computation. Coverage also examines applied issues related to ethical, social, and political interest. The contributors first explore how computation has changed philosophical inquiry. Computers are now capable of joining humans in exploring foundational issues. Thus, we can ponder machine-generated explanation, thought, agency, and other quite fascinating concepts. The papers are also concerned with normative aspects of the computer and information technology revolution. They examine technology-specific analyses of key challenges, from Big Data to autonomous robots to expert systems for infrastructure control and financial services. The virtue of a collection that ranges over philosophical questions, such as this one does, lies in the prospects for a more integrated understanding of issues. These are early days in the partnership between philosophy and information technology. Philosophers and researchers are still sorting out many foundational issues. They will need to deploy all of the tools of philosophy to establish this foundation. This volume admirably showcases those tools in the hands of some excellent scholars.
This volume aims to stimulate discussions on research involving the use of data and digital images as an understanding approach for analysis and visualization of phenomena and experiments. The emphasis is put not only on graphically representing data as a way of increasing its visual analysis, but also on the imaging systems which contribute greatly to the comprehension of real cases. Scientific Visualization and Imaging Systems encompass multidisciplinary areas, with applications in many knowledge fields such as Engineering, Medicine, Material Science, Physics, Geology, Geographic Information Systems, among others. This book is a selection of 13 revised and extended research papers presented in the International Conference on Advanced Computational Engineering and Experimenting -ACE-X conferences 2010 (Paris), 2011 (Algarve), 2012 (Istanbul) and 2013 (Madrid). The examples were particularly chosen from materials research, medical applications, general concepts applied in simulations and image analysis and other interesting related problems.
Learn the basics of serverless computing and how to develop event-driven architectures with the three major cloud platforms: Amazon Web Services, Microsoft Azure, and Google Cloud. This hands-on guide dives into the foundations of serverless computing, its use cases, and how to apply it using developer tools such as Node.js, Visual Studio Code, Postman, and Serverless Framework. You will apply the fundamentals of serverless technology from the ground up, and come away with a greater understanding of its power and how to make it work for you. This book teaches you how to quickly and securely develop applications without the hassle of configuring and maintaining infrastructure. You will learn how to harness serverless technology to rapidly reduce production time and minimize your costs, while still having the freedom to customize your code, without hindering functionality. Upon completion, you will have the knowledge and resources to build your own serverless application hosted in AWS, Azure, or Google Cloud and will have experienced the benefits of event-driven technology for yourself. What You´ll Learn Gain a deeper understanding of serverless computing and when to use it Use development tools such as Node.js, Postman, and VS code to quickly set up your serverless development environment and produce applications Apply triggers to your serverless functions that best suit the architecture for the problem the functions are solving Begin building applications across cloud providers that utilize the power of serverless technology Understand best development practices with serverless computing to maintain scalable and practical solutions Code with an agnostic approach to cloud providers to minimize provider dependency Who This Book Is For Any developer looking to expand current knowledge of serverless computing, its applications, and how to architect serverless solutions, or someone just beginning in these areas
Cloud Computing Native KMU - so lässt sich kurz und prägnant der Inhalt des vorliegenden Buches zusammenfassen. Dargestellt werden Grundlagen, Anwendungen, Migrationsstrategien, Sicherheitskonzepte, betriebliches Datenmanagement, technologisches Umfeld, Cloud-Initiativen und die vielen nützlichen Helfer aus dem Internet. Beschrieben, strukturiert und analysiert wird der Cloud-Markt in all seinen vielfältigen Formen und Verästlungen. Dem weiterführenden Interesse dienen sorgfältig recherchierte Hyperlinks. So bekommt der Leser ein systematisches und umfassendes Bild vom Cloud Computing unter KMU-Bedingungen.. All dies dient der optimalen Cloud-Nutzung in kleinen und mittleren Unternehmen respektive in Freiberufler-Büros, HomeOffices oder Start-up-Firmen. Eine solche Vorgehensweise ist ratsam, um diese moderne Technologie samt Umfeld besser zu verstehen und die vorhandenen Angebote am Markt optimal für den eigenen Betrieb nutzen zu können. In diesem Zusammenhang werden auch folgende Fragen thematisiert: Was heißt ´Cloud-Readiness´ für KMU? Ab wann und für wen lohnt sich die Cloud? Brauchen wir eine KMU-eigene Cloud-Policy?
Cloud Computing wird von nahezu allen führenden Analysten als einer der Top-5-IT-Trends gesehen, der gegenwärtig aus der Hype-Phase in den Status der praktischen betrieblichen Umsetzung übergeht. Inzwischen wird nicht mehr diskutiert, ob Cloud Computing überhaupt eine praktikable Möglichkeit des IT-Sourcing ist, sondern vielmehr, wie diese Möglichkeit sich sicher und mit hohem Nutzen für Firmen einsetzen lässt. Es wird aufgezeigt, wo die Vorteile aber auch die Stolpersteine liegen und welche prinzipiellen Lösungen es gibt, um die Chancen zu realisieren und Risiken möglichst zu umgehen.
High Performance Computing: Modern Systems and Practices is a fully comprehensive and easily accessible treatment of high performance computing, covering fundamental concepts and essential knowledge while also providing key skills training. With this book, domain scientists will learn how to use supercomputers as a key tool in their quest for new knowledge. In addition, practicing engineers will discover how supercomputers can employ HPC systems and methods to the design and simulation of innovative products, and students will begin their careers with an understanding of possible directions for future research and development in HPC. Those who maintain and administer commodity clusters will find this textbook provides essential coverage of not only what HPC systems do, but how they are used. Covers enabling technologies, system architectures and operating systems, parallel programming languages and algorithms, scientific visualization, correctness and performance debugging tools and methods, GPU accelerators and big data problems Provides numerous examples that explore the basics of supercomputing, while also providing practical training in the real use of high-end computers Helps users with informative and practical examples that build knowledge and skills through incremental steps Features sidebars of background and context to present a live history and culture of this unique field Includes online resources, such as recorded lectures from the authors´ HPC courses
Numerical Python by Robert Johansson shows you how to leverage the numerical and mathematical modules in Python and its Standard Library as well as popular open source numerical Python packages like NumPy, FiPy, matplotlib and more to numerically compute solutions and mathematically model applications in a number of areas like big data, cloud computing, financial engineering, business management and more. After reading and using this book, you´ll get some takeaway case study examples of applications that can be found in areas like business management, big data/cloud computing, financial engineering (i.e., options trading investment alternatives), and even games. Up until very recently, Python was mostly regarded as just a web scripting language. Well, computational scientists and engineers have recently discovered the flexibility and power of Python to do more. Big data analytics and cloud computing programmers are seeing Python´s immense use. Financial engineers are also now employing Python in their work. Python seems to be evolving as a language that can even rival C++, Fortran, and Pascal/Delphi for numerical and mathematical computations.
Leverage the numerical and mathematical modules in Python and its standard library as well as popular open source numerical Python packages like NumPy, SciPy, FiPy, matplotlib and more. This fully revised edition, updated with the latest details of each package and changes to Jupyter projects, demonstrates how to numerically compute solutions and mathematically model applications in big data, cloud computing, financial engineering, business management and more. Numerical Python, Second Edition , presents many brand-new case study examples of applications in data science and statistics using Python, along with extensions to many previous examples. Each of these demonstrates the power of Python for rapid development and exploratory computing due to its simple and high-level syntax and multiple options for data analysis. After reading this book, readers will be familiar with many computing techniques including array-based and symbolic computing, visualization and numerical file I/O, equation solving, optimization, interpolation and integration, and domain-specific computational problems, such as differential equation solving, data analysis, statistical modeling and machine learning. W hat You´ll Learn Work with vectors and matrices using NumPy Plot and visualize data with Matplotlib Perform data analysis tasks with Pandas and SciPy Review statistical modeling and machine learning with statsmodels and scikit-learn Optimize Python code using Numba and Cython Who This Book Is For Developers who want to understand how to use Python and its related ecosystem for numerical computing.
This book draws on Mark Mc Auley´s wealth of experience to provide an intuitive step-by-step guide to the modelling process. It also provides case studies detailing the creation of biological process models. Mark Mc Auley has over 15 years´ experience of applying computing to challenges in bioscience. Currently he is employed as a Senior Lecturer in Chemical Engineering at the University of Chester. He has published widely on the use of computer modelling in nutrition and uses computer modelling to both enhance and enrich the learning experience of the students that he teaches. He has taught computer modelling to individuals at a wide variety of levels and from different backgrounds, from undergraduate nutrition students to PhD and medical students. Kathleen Mooney is a Senior Lecturer in Nutrition at Edge Hill University. She has almost ten years´ experience teaching nutrition to undergraduate and postgraduate students, and uses this to ensure that the book focuses on the learner. The most difficult part of any modelling project is getting started and selecting nutrient-based biochemical systems that are familiar to all nutritionists facilitates this process. A philosophy of simplification is adopted, which involves no prior programming or modelling experience.
Learn how to define strategies for cloud adoption of your Oracle database landscape. Understand private cloud, public cloud, and hybrid cloud computing in order to successfully design and manage databases in the cloud. The Cloud DBA-Oracle provides an overview of Database-as-a-Service (DBaaS) that you can use in defining your cloud adoption strategy. In-depth details of various cloud service providers for Oracle database are given, including Oracle Cloud and Amazon Web Services (AWS). Database administration techniques relevant to hosting databases in the cloud are shown in the book as well as the technical details needed to perform all database administration tasks and activities, such as migration to the cloud, backup in the cloud, and new database setup in the cloud. You will learn from real-world business cases and practical examples of administration of Oracle database in the cloud, highlighting the challenges faced and solutions implemented. What you will learn: Cloud computing concepts from the DBA perspective, such as private cloud, public cloud, hybrid cloud Technical details of all aspects of cloud database administration Challenges faced during setup of databases in private cloud or database migration to public cloud Key points to be kept in mind during database administration in the cloud Practical examples of successful Oracle database cloud migration and support Who Is This Book For All levels of IT professionals, from executives responsible for determining database strategies to database administrators and database architects who manage and design databases.