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Science, Engineering Management and Information Technology: First International Conference, SEMIT 2022, Ankara, Turkey, February 2–3, 2022, Revised Selected Papers, Part I (Communications in Computer and Information Science #1808)
by Gerhard-Wilhelm Weber Arpan Kumar Kar Erfan Babaee Tirkolaee Abolfazl Mirzazadeh Babek ErdebilliThis two-volume set constitutes selected papers presented during the First First International Conference on Science, Engineering Management and Information Technology, SEMIT 2022, held virtually in Ankara, Turkey, in February 2–3, 2022 and in September 8-9, 2022. The 37 papers presented were carefully reviewed and selected from the 261 qualified submissions. The papers are organized in the following topical sections: application of computer science and technology in operations and supply chain management; advances of engineering technology and Artificial Intelligence in application management; human factors management systems based on information technology; technology-aided decision-making: systems, applications, and modern solutions.
Science, Engineering Management and Information Technology: First International Conference, SEMIT 2022, Ankara, Turkey, September 8-9, 2022, Revised Selected Papers, Part II (Communications in Computer and Information Science #1809)
by Gerhard-Wilhelm Weber Arpan Kumar Kar Erfan Babaee Tirkolaee Abolfazl Mirzazadeh Babek ErdebilliThis two-volume set constitutes selected papers presented during the First First International Conference on Science, Engineering Management and Information Technology, SEMIT 2022, held virtually in Ankara, Turkey, in February 2–3, 2022 and in September 8-9, 2022. The 37 papers presented were carefully reviewed and selected from the 261 qualified submissions. The papers are organized in the following topical sections: application of computer science and technology in operations and supply chain management; advances of engineering technology and Artificial Intelligence in application management; technology-aided decision-making: systems, applications, and modern solutions.
Science, Engineering Management and Information Technology: Second International Conference, SEMIT 2023, Ankara, Turkey, September 14–15, 2023, Proceedings, Part-I (Communications in Computer and Information Science #2198)
by Gerhard-Wilhelm Weber Zohreh Molamohamadi Erfan Babaee Tirkolaee Babek Erdebilli A. MirzazadehThis two-volume set constitutes selected papers presented during the Second International Conference on Science, Engineering Management and Information Technology, SEMIT 2023, held in Ankara, Turkey, during September 14–15, 2023. The 44 full papers and 2 short papers presented were carefully reviewed and selected from 409 submissions. The papers cover the following topics: Part I - Decision Analysis and Expert Systems; Machine Learning, Data Analysis and Computer Vision in Healthcare and Medicine; Smart Production, Transportation and Supply Chain Systems; Information Technology and Data Science in Industry. Part II - IoT, Blockchain, and Cyber Security in Complex Systems; Real-Time Data Analysis and Simulation in Engineering Systems; Digitalization and Artificial Intelligence in Manufacturing/ Service Industries; Soft Computing and Artificial Intelligence in Engineering Management and Marketing.
Science, Engineering Management and Information Technology: Second International Conference, SEMIT 2023, Ankara, Turkey, September 14–15, 2023, Proceedings, Part-II (Communications in Computer and Information Science #2199)
by Gerhard-Wilhelm Weber Zohreh Molamohamadi Erfan Babaee Tirkolaee Babek Erdebilli A. MirzazadehThis two-volume set constitutes selected papers presented during the Second International Conference on Science, Engineering Management and Information Technology, SEMIT 2023, held in Ankara, Turkey, during September 14–15, 2023. The 44 full papers and 2 short papers presented were carefully reviewed and selected from 409 submissions. The papers cover the following topics: Part I - Decision Analysis and Expert Systems; Machine Learning, Data Analysis and Computer Vision in Healthcare and Medicine; Smart Production, Transportation and Supply Chain Systems; Information Technology and Data Science in Industry. Part II - IoT, Blockchain, and Cyber Security in Complex Systems; Real-Time Data Analysis and Simulation in Engineering Systems; Digitalization and Artificial Intelligence in Manufacturing/ Service Industries; Soft Computing and Artificial Intelligence in Engineering Management and Marketing.
Science, Technology and Global Governance (Science And Technology In The Ipe Ser.)
by John R. De La MotheFirst published in 2001. Routledge is an imprint of Taylor & Francis, an informa company.
Science: Technology and Society Sourcebook
by Holt Rinehart Winston StaffScienceplus Sourcebook for High School
Scientific Astrophotography
by Gerald HubbellScientific Astrophotography is intended for those amateur astronomers who are looking for new challenges, once they have mastered visual observing and the basic imaging of various astronomical objects. It will also be a useful reference for scientifically inclined observers who want to learn the fundamentals of astrophotography with a firm emphasis on the discipline of scientific imaging. This books is not about making beautiful astronomical images; it is about recording astronomical images that are scientifically rigorous and from which accurate data can be extracted. This book is unique in that it gives readers the skills necessary for obtaining excellent images for scientific purposes in a concise and procedurally oriented manner. This not only gets the reader used to a disciplined approach to imaging to maximize quality, but also to maximize the success (and minimize the frustration!) inherent in the pursuit of astrophotography. The knowledge and skills imparted to the reader of this handbook also provide an excellent basis for "beautiful picture" astrophotography! There is a wealth of information in this book - a distillation of ideas and data presented by a diverse set of sources and based on the most recent techniques, equipment, and data available to the amateur astronomer. There are also numerous practical exercises. Scientific Astrophotography is perfect for any amateur astronomer who wants to go beyond just astrophotography and actually contribute to the science of astronomy.
Scientific Computing and Algorithms in Industrial Simulations
by Michael Griebel Marc Alexander Schweitzer Anton SchüllerThe contributions gathered here provide an overview of current research projects and selected software products of the Fraunhofer Institute for Algorithms and Scientific Computing SCAI. They show the wide range of challenges that scientific computing currently faces, the solutions it offers, and its important role in developing applications for industry. Given the exciting field of applied collaborative research and development it discusses, the book will appeal to scientists, practitioners, and students alike. The Fraunhofer Institute for Algorithms and Scientific Computing SCAI combines excellent research and application-oriented development to provide added value for our partners. SCAI develops numerical techniques, parallel algorithms and specialized software tools to support and optimize industrial simulations. Moreover, it implements custom software solutions for production and logistics, and offers calculations on high-performance computers. Its services and products are based on state-of-the-art methods from applied mathematics and information technology.
Scientific Computing and Bioinformatics and Computational Biology: 22nd International Conference, CSC 2024, and 25th International Conference, BIOCOMP 2024, Held as Part of the World Congress in Computer Science, Computer Engineering and Applied Computing, CSCE 2024, Las Vegas, NV, USA, July 22–25, 2024, Revised Selected Papers (Communications in Computer and Information Science #2258)
by Hamid R. Arabnia Leonidas Deligiannidis Michael R. Grimaila Douglas D. Hodson Torrey J. WagnerThis book constitutes the proceedings of the 22nd International Conference on Scientific Computing and Bioinformatics, CSC 2024, and the 25th International Conference on Computational Biology, BIOCOMP 2024, held as part of the 2024 World Congress in Computer Science, Computer Engineering and Applied Computing, in Las Vegas, USA, during July 22 to July 25, 2024. The proceedings include 25 papers from CSC 2024, which have been selected from a total of 128 submissions, and 27 papers from BIOCOMP 2024, that have been selected from 27 submissions. The papers have been organized in topical sections as follows: Military and defence modeling and simulation; scientific computing and applications; and bioinformatics and computational biology.
Scientific Computing and Cultural Heritage
by Willi Jäger Hans Georg Bock Michael J. WincklerThe sheer computing power of modern information technology is changing the face of research not just in science, technology and mathematics, but in humanities and cultural studies too. Recent decades have seen a major shift both in attitudes and deployment of computers, which are now vital and highly effective tools in disciplines where they were once viewed as elaborate typewriters. This revealing volume details the vast array of computing applications that researchers in the humanities now have recourse to, including the dissemination of scholarly information through virtual 'co-laboratories', data retrieval, and the modeling of complex processes that contribute to our natural and cultural heritage. One key area covered in this book is the versatility of computers in presenting images and graphics, which is transforming the analysis of data sets and archaeological reconstructions alike. The papers published here are grouped into three broad categories that cover mathematical and computational methods, research developments in information systems, and a detailed portrayal of ongoing work on documenting, restoring and presenting cultural monuments including the temples in Pompeii and the Banteay Chhmar temples of the Angkorian period in present-day Cambodia. Originally presented at a research workshop in Heidelberg, Germany, they reflect the rapidly developing identity of computational humanities as an interdisciplinary field in its own right, as well as demonstrating the breadth of perspectives in this young and vibrant research area.
Scientific Computing and Software: Go20 CSCS, Marsalforn, Malta, May 22-26, 2023 (Springer Proceedings in Mathematics & Statistics #495)
by Raymond J. Spiteri Joyce ReimerThese proceedings present a curated collection of innovative approaches to tackling challenging problems in applied mathematics. These problems, often marked by instability, inaccuracy, and high computational cost, remain at the forefront of mathematical research due to their difficulty. Addressing this demand, the contributions in this volume offer robust numerical methods designed to improve the accuracy and efficiency of their solutions. The book originates from the Go20 Conference 2023, where established experts and emerging researchers explored cutting-edge methodologies. The discussions captured here situate new advancements within a broader historical and theoretical context, providing a well-rounded perspective on these pressing mathematical challenges. Topics covered include: Ordinary Differential Equations (ODEs) with singularities Multi-dimensional and multi-rate systems of Partial Differential Equations (PDEs) High-index Differential-Algebraic Equations (DAEs) Inverse and optimal control problems This collection is a valuable resource for researchers and practitioners working on these or related topics. It offers comprehensive analyses and practical insights that bridge foundational principles with modern numerical innovations.
Scientific Computing in Electrical Engineering: SCEE 2018, Taormina, Italy, September 2018 (Mathematics in Industry #32)
by Giuseppe Nicosia Vittorio RomanoThis collection of selected papers presented at the 12th International Conference on Scientific Computing in Electrical Engineering, SCEE 2018, held in Taormina, Sicily, Italy, in September 2018, showcases the state of the art in SCEE.The aim of the SCEE 2018 conference was to bring together scientists from academia and industry, mathematicians, electrical engineers, computer scientists, and physicists, and to promote intensive discussions on industrially relevant mathematical problems, with an emphasis on the modeling and numerical simulation of electronic circuits and of electromagnetic fields. This extensive reference work is divided into five parts: Computational Electromagnetics, Device Modeling and Simulation, Circuit Simulation, Mathematical and Computational Methods, Model Order Reduction. Each part starts with a general introduction, followed by the respective contributions. The book will appeal to mathematicians and electrical engineers. Further, it introduces algorithm and program developers to recent advances in the other fields, while industry experts will be introduced to new programming tools and mathematical methods.
Scientific Computing in Electrical Engineering: Scee 2016, St. Wolfgang, Austria, October 2016 (Mathematics In Industry Ser. #28)
by Ulrich Langer Wolfgang Amrhein Walter ZulehnerThis collection of selected papers presented at the 11th International Conference on Scientific Computing in Electrical Engineering (SCEE), held in St. Wolfgang, Austria, in 2016, showcases the state of the art in SCEE. The aim of the SCEE 2016 conference was to bring together scientists from academia and industry, mathematicians, electrical engineers, computer scientists, and physicists, and to promote intensive discussions on industrially relevant mathematical problems, with an emphasis on the modeling and numerical simulation of electronic circuits and devices, electromagnetic fields, and coupled problems. The focus in methodology was on model order reduction and uncertainty quantification. This extensive reference work is divided into six parts: Computational Electromagnetics, Circuit and Device Modeling and Simulation, Coupled Problems and Multi‐Scale Approaches in Space and Time, Mathematical and Computational Methods Including Uncertainty Quantification, Model Order Reduction, and Industrial Applications. Each part starts with a general introduction, followed by the respective contributions. This book will appeal to mathematicians and electrical engineers. Further, it introduces algorithm and program developers to recent advances in the other fields, while industry experts will be introduced to new programming tools and mathematical methods.
Scientific Computing with Multicore and Accelerators (Chapman & Hall/CRC Computational Science)
by Jack Dongarra David A. Bader Jakub KurzakThe hybrid/heterogeneous nature of future microprocessors and large high-performance computing systems will result in a reliance on two major types of components: multicore/manycore central processing units and special purpose hardware/massively parallel accelerators. While these technologies have numerous benefits, they also pose substantial perfo
Scientific Computing with Python 3
by Jan Erik Solem Claus Fuhrer Olivier VerdierAn example-rich, comprehensive guide for all of your Python computational needs About This Book • Your ultimate resource for getting up and running with Python numerical computations • Explore numerical computing and mathematical libraries using Python 3.x code with SciPy and NumPy modules • A hands-on guide to implementing mathematics with Python, with complete coverage of all the key concepts Who This Book Is For This book is for anyone who wants to perform numerical and mathematical computations in Python. It is especially useful for developers, students, and anyone who wants to use Python for computation. Readers are expected to possess basic a knowledge of scientific computing and mathematics, but no prior experience with Python is needed. What You Will Learn • The principal syntactical elements of Python • The most important and basic types in Python • The essential building blocks of computational mathematics, linear algebra, and related Python objects • Plot in Python using matplotlib to create high quality figures and graphics to draw and visualize your results • Define and use functions and learn to treat them as objects • How and when to correctly apply object-oriented programming for scientific computing in Python • Handle exceptions, which are an important part of writing reliable and usable code • Two aspects of testing for scientific programming: Manual and Automatic In Detail Python can be used for more than just general-purpose programming. It is a free, open source language and environment that has tremendous potential for use within the domain of scientific computing. This book presents Python in tight connection with mathematical applications and demonstrates how to use various concepts in Python for computing purposes, including examples with the latest version of Python 3. Python is an effective tool to use when coupling scientific computing and mathematics and this book will teach you how to use it for linear algebra, arrays, plotting, iterating, functions, polynomials, and much more. Style and approach This book takes a concept-based approach to the language rather than a systematic introduction. It is a complete Python tutorial and introduces computing principles, using practical examples to and showing you how to correctly implement them in Python. You'll learn to focus on high-level design as well as the intricate details of Python syntax. Rather than providing canned problems to be solved, the exercises have been designed to inspire you to think about your own code and give you real-world insight.
Scientific Computing with Python: High-performance scientific computing with NumPy, SciPy, and pandas, 2nd Edition
by Jan Erik Solem Claus Fuhrer Olivier VerdierLeverage this example-packed, comprehensive guide for all your Python computational needsKey FeaturesLearn the first steps within Python to highly specialized conceptsExplore examples and code snippets taken from typical programming situations within scientific computing.Delve into essential computer science concepts like iterating, object-oriented programming, testing, and MPI presented in strong connection to applications within scientific computing.Book DescriptionPython has tremendous potential within the scientific computing domain. This updated edition of Scientific Computing with Python features new chapters on graphical user interfaces, efficient data processing, and parallel computing to help you perform mathematical and scientific computing efficiently using Python. This book will help you to explore new Python syntax features and create different models using scientific computing principles. The book presents Python alongside mathematical applications and demonstrates how to apply Python concepts in computing with the help of examples involving Python 3.8. You'll use pandas for basic data analysis to understand the modern needs of scientific computing, and cover data module improvements and built-in features. You'll also explore numerical computation modules such as NumPy and SciPy, which enable fast access to highly efficient numerical algorithms. By learning to use the plotting module Matplotlib, you will be able to represent your computational results in talks and publications. A special chapter is devoted to SymPy, a tool for bridging symbolic and numerical computations. By the end of this Python book, you'll have gained a solid understanding of task automation and how to implement and test mathematical algorithms within the realm of scientific computing.What you will learnUnderstand the building blocks of computational mathematics, linear algebra, and related Python objectsUse Matplotlib to create high-quality figures and graphics to draw and visualize resultsApply object-oriented programming (OOP) to scientific computing in PythonDiscover how to use pandas to enter the world of data processingHandle exceptions for writing reliable and usable codeCover manual and automatic aspects of testing for scientific programmingGet to grips with parallel computing to increase computation speedWho this book is forThis book is for students with a mathematical background, university teachers designing modern courses in programming, data scientists, researchers, developers, and anyone who wants to perform scientific computation in Python.
Scientific Computing with Scala
by Vytautas JancauskasLearn to solve scientific computing problems using Scala and its numerical computing, data processing, concurrency, and plotting libraries About This Book * Parallelize your numerical computing code using convenient and safe techniques. * Accomplish common high-performance, scientific computing goals in Scala. * Learn about data visualization and how to create high-quality scientific plots in Scala Who This Book Is For Scientists and engineers who would like to use Scala for their scientific and numerical computing needs. A basic familiarity with undergraduate level mathematics and statistics is expected but not strictly required. A basic knowledge of Scala is required as well as the ability to write simple Scala programs. However, complicated programming concepts are not used in the book. Anyone who wants to explore using Scala for writing scientific or engineering software will benefit from the book. What You Will Learn * Write and read a variety of popular file formats used to store scientific data * Use Breeze for linear algebra, optimization, and digital signal processing * Gain insight into Saddle for data analysis * Use ScalaLab for interactive computing * Quickly and conveniently write safe parallel applications using Scala's parallel collections * Implement and deploy concurrent programs using the Akka framework * Use the Wisp plotting library to produce scientific plots * Visualize multivariate data using various visualization techniques In Detail Scala is a statically typed, Java Virtual Machine (JVM)-based language with strong support for functional programming. There exist libraries for Scala that cover a range of common scientific computing tasks - from linear algebra and numerical algorithms to convenient and safe parallelization to powerful plotting facilities. Learning to use these to perform common scientific tasks will allow you to write programs that are both fast and easy to write and maintain. We will start by discussing the advantages of using Scala over other scientific computing platforms. You will discover Scala packages that provide the functionality you have come to expect when writing scientific software. We will explore using Scala's Breeze library for linear algebra, optimization, and signal processing. We will then proceed to the Saddle library for data analysis. If you have experience in R or with Python's popular pandas library you will learn how to translate those skills to Saddle. If you are new to data analysis, you will learn basic concepts of Saddle as well. Well will explore the numerical computing environment called ScalaLab. It comes bundled with a lot of scientific software readily available. We will use it for interactive computing, data analysis, and visualization. In the following chapters, we will explore using Scala's powerful parallel collections for safe and convenient parallel programming. Topics such as the Akka concurrency framework will be covered. Finally, you will learn about multivariate data visualization and how to produce professional-looking plots in Scala easily. After reading the book, you should have more than enough information on how to start using Scala as your scientific computing platform Style and approach Examples are provided on how to use Scala to do basic numerical and scientific computing tasks. All the concepts are illustrated with more involved examples in each chapter. The goal of the book is to allow you to translate existing experience in scientific computing to Scala.
Scientific Computing, Computer Arithmetic, and Validated Numerics
by Warwick Tucker Marco Nehmeier Jürgen Wolff von GudenbergThis book constitutes the refereed post proceedings of the16th International Symposium, SCAN 2014, held in Würzburg, Germany, in September 2014. The 22 full papers presented were carefullyreviewed and selected from 60 submissions. The main concerns of research addressed by SCAN conferences are validation, verification or reliable assertions of numerical computations. Interval arithmetic and other treatments of uncertainty are developed as appropriate tools.
Scientific Computing, Computer Arithmetic, and Validated Numerics: 16th International Symposium, SCAN 2014, Würzburg, Germany, September 21-26, 2014. Revised Selected Papers (Lecture Notes in Computer Science #9553)
by Warwick Tucker Marco Nehmeier Jürgen Wolff von GudenbergThis book constitutes the refereed post proceedings of the 16th International Symposium, SCAN 2014, held in Würzburg, Germany, in September 2014. The 22 full papers presented were carefully reviewed and selected from 60 submissions. The main concerns of research addressed by SCAN conferences are validation, verification or reliable assertions of numerical computations. Interval arithmetic and other treatments of uncertainty are developed as appropriate tools.
Scientific Computing: A Historical Perspective (Texts in Computational Science and Engineering #8)
by Bertil GustafssonThis book explores the most significant computational methods and the history of their development. It begins with the earliest mathematical / numerical achievements made by the Babylonians and the Greeks, followed by the period beginning in the 16th century. For several centuries the main scientific challenge concerned the mechanics of planetary dynamics, and the book describes the basic numerical methods of that time. In turn, at the end of the Second World War scientific computing took a giant step forward with the advent of electronic computers, which greatly accelerated the development of numerical methods. As a result, scientific computing became established as a third scientific method in addition to the two traditional branches: theory and experimentation. The book traces numerical methods’ journey back to their origins and to the people who invented them, while also briefly examining the development of electronic computers over the years. Featuring 163 references and more than 100 figures, many of them portraits or photos of key historical figures, the book provides a unique historical perspective on the general field of scientific computing – making it a valuable resource for all students and professionals interested in the history of numerical analysis and computing, and for a broader readership alike.
Scientific Computing: An Introductory Survey
by Michael T. HeathThis book presents a broad overview of numerical methods for solving all the major problems in scientific computing.
Scientific Data Analysis using Jython Scripting and Java
by Sergei V. ChekanovScientific Data Analysis using Jython Scripting and Java presents practical approaches for data analysis using Java scripting based on Jython, a Java implementation of the Python language. The chapters essentially cover all aspects of data analysis, from arrays and histograms to clustering analysis, curve fitting, metadata and neural networks. A comprehensive coverage of data visualisation tools implemented in Java is also included. Written by the primary developer of the jHepWork data-analysis framework, the book provides a reliable and complete reference source laying the foundation for data-analysis applications using Java scripting. More than 250 code snippets (of around 10-20 lines each) written in Jython and Java, plus several real-life examples help the reader develop a genuine feeling for data analysis techniques and their programming implementation. This is the first data-analysis and data-mining book which is completely based on the Jython language, and opens doors to scripting using a fully multi-platform and multi-threaded approach. Graduate students and researchers will benefit from the information presented in this book.
Scientific Data Management: Challenges, Technology, and Deployment
by Arie Shoshani Doron RotemDealing with the volume, complexity, and diversity of data currently being generated by scientific experiments and simulations often causes scientists to waste productive time. Scientific Data Management: Challenges, Technology, and Deployment describes cutting-edge technologies and solutions for managing and analyzing vast amounts of data, helping
Scientific Discovery in the Social Sciences (Synthese Library #413)
by Fernand Gobet Mark Addis Peter C. R. Lane Peter D. SozouThis volume offers selected papers exploring issues arising from scientific discovery in the social sciences. It features a range of disciplines including behavioural sciences, computer science, finance, and statistics with an emphasis on philosophy.The first of the three parts examines methods of social scientific discovery. Chapters investigate the nature of causal analysis, philosophical issues around scale development in behavioural science research, imagination in social scientific practice, and relationships between paradigms of inquiry and scientific fraud. The next part considers the practice of social science discovery. Chapters discuss the lack of genuine scientific discovery in finance where hypotheses concern the cheapness of securities, the logic of scientific discovery in macroeconomics, and the nature of that what discovery with the Solidarity movement as a case study. The final part covers formalising theories in social science. Chapters analyse the abstract model theory of institutions as a way of representing the structure of scientific theories, the semi-automatic generation of cognitive science theories, and computational process models in the social sciences.The volume offers a unique perspective on scientific discovery in the social sciences. It will engage scholars and students with a multidisciplinary interest in the philosophy of science and social science.
Scientific Foundations of Digital Governance and Transformation: Concepts, Approaches and Challenges (Public Administration and Information Technology #38)
by Yannis Charalabidis Gabriela Viale Pereira Leif Skiftenes FlakThis book provides the latest research advancements and findings for the scientific systematization of knowledge regarding digital governance and transformation, such as core concepts, foundational principles, theories, methodologies, architectures, assessment frameworks and future directions. It brings forward the ingredients of this new domain, proposing its needed formal and systematic tools, exploring its relation with neighbouring scientific domains and finally prescribing the next steps for laying the foundations of a new science. The book is structured into three main areas. The first section focuses on contributions towards the purpose, ingredients and structure of the scientific foundations of digital transformation in the public sector. The second looks at the identification and description of domain's scientific problems with a view to stabilizing research products, assessment methods and tools in a reusable, extendable and sustainable manner. The third envisions a pathway for future research to tackle broader governance problems via the applications of information and communication technologies in combination with innovative approaches from neighbouring scientific domains. Contributing to the analysis of the scientific perspectives of digital governance and digital transformation, this book will be an indispensable tool for students, researchers and practitioners interested in digital governance, digital transformation, information systems, as well as ICT industry experts and policymakers charged with the design, deployment and implementation of public sector information systems.