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Eastern Asian Population History and Contemporary Population Issues (SpringerBriefs in Population Studies)
by Toru SuzukiThis book interprets and explains contemporary population issues from historical and cultural perspectives. These include lowest-low fertility in the Republic of Korea and Taiwan, early population aging in China relative to the developmental level, and various modes of domestic and international migration in the region. The book shows that divergent fertility decline can be attributed to the family patterns established in the pre-modern era in each country. It also examines the diversity of international migration in Eastern Asian countries today is also understood from the long-term historical view.
Representations of Reductive p-adic Groups: International Conference, IISER, Pune, India, 2017 (Progress in Mathematics #328)
by Anne-Marie Aubert Manish Mishra Alan Roche Steven SpalloneThis book consists of survey articles and original research papers in the representation theory of reductive p-adic groups. In particular, it includes a survey by Anne-Marie Aubert on the enormously influential local Langlands conjectures. The survey gives a precise and accessible formulation of many aspects of the conjectures, highlighting recent refinements, due to the author and her collaborators, and their current status. It also features an extensive account by Colin Bushnell of his work with Henniart on the fine structure of the local Langlands correspondence for general linear groups, beginning with a clear overview of Bushnell–Kutzko’s construction of cuspidal types for such groups. The remaining papers touch on a range of topics in this active area of modern mathematics: group actions on root data, explicit character formulas, classification of discrete series representations, unicity of types, local converse theorems, completions of Hecke algebras, p-adic symmetric spaces. All meet a high level of exposition. The book should be a valuable resource to graduate students and experienced researchers alike.
Bayesian Regression Modeling with INLA (Chapman & Hall/CRC Computer Science & Data Analysis)
by Xiaofeng Wang Yu Yue Ryan Julian J. FarawayINLA stands for Integrated Nested Laplace Approximations, which is a new method for fitting a broad class of Bayesian regression models. No samples of the posterior marginal distributions need to be drawn using INLA, so it is a computationally convenient alternative to Markov chain Monte Carlo (MCMC), the standard tool for Bayesian inference. Bayesian Regression Modeling with INLA covers a wide range of modern regression models and focuses on the INLA technique for building Bayesian models using real-world data and assessing their validity. A key theme throughout the book is that it makes sense to demonstrate the interplay of theory and practice with reproducible studies. Complete R commands are provided for each example, and a supporting website holds all of the data described in the book. An R package including the data and additional functions in the book is available to download. The book is aimed at readers who have a basic knowledge of statistical theory and Bayesian methodology. It gets readers up to date on the latest in Bayesian inference using INLA and prepares them for sophisticated, real-world work. Xiaofeng Wang is Professor of Medicine and Biostatistics at the Cleveland Clinic Lerner College of Medicine of Case Western Reserve University and a Full Staff in the Department of Quantitative Health Sciences at Cleveland Clinic. Yu Ryan Yue is Associate Professor of Statistics in the Paul H. Chook Department of Information Systems and Statistics at Baruch College, The City University of New York. Julian J. Faraway is Professor of Statistics in the Department of Mathematical Sciences at the University of Bath.
Big Data in Omics and Imaging: Integrated Analysis and Causal Inference (Chapman & Hall/CRC Mathematical and Computational Biology)
by Momiao XiongBig Data in Omics and Imaging: Integrated Analysis and Causal Inference addresses the recent development of integrated genomic, epigenomic and imaging data analysis and causal inference in big data era. Despite significant progress in dissecting the genetic architecture of complex diseases by genome-wide association studies (GWAS), genome-wide expression studies (GWES), and epigenome-wide association studies (EWAS), the overall contribution of the new identified genetic variants is small and a large fraction of genetic variants is still hidden. Understanding the etiology and causal chain of mechanism underlying complex diseases remains elusive. It is time to bring big data, machine learning and causal revolution to developing a new generation of genetic analysis for shifting the current paradigm of genetic analysis from shallow association analysis to deep causal inference and from genetic analysis alone to integrated omics and imaging data analysis for unraveling the mechanism of complex diseases. FEATURES Provides a natural extension and companion volume to Big Data in Omic and Imaging: Association Analysis, but can be read independently. Introduce causal inference theory to genomic, epigenomic and imaging data analysis Develop novel statistics for genome-wide causation studies and epigenome-wide causation studies. Bridge the gap between the traditional association analysis and modern causation analysis Use combinatorial optimization methods and various causal models as a general framework for inferring multilevel omic and image causal networks Present statistical methods and computational algorithms for searching causal paths from genetic variant to disease Develop causal machine learning methods integrating causal inference and machine learning Develop statistics for testing significant difference in directed edge, path, and graphs, and for assessing causal relationships between two networks The book is designed for graduate students and researchers in genomics, epigenomics, medical image, bioinformatics, and data science. Topics covered are: mathematical formulation of causal inference, information geometry for causal inference, topology group and Haar measure, additive noise models, distance correlation, multivariate causal inference and causal networks, dynamic causal networks, multivariate and functional structural equation models, mixed structural equation models, causal inference with confounders, integer programming, deep learning and differential equations for wearable computing, genetic analysis of function-valued traits, RNA-seq data analysis, causal networks for genetic methylation analysis, gene expression and methylation deconvolution, cell –specific causal networks, deep learning for image segmentation and image analysis, imaging and genomic data analysis, integrated multilevel causal genomic, epigenomic and imaging data analysis.
The Copenhagen Conspiracy
by David FerryAt the close of the nineteenth century, we stood on the threshold of one of the greatest periods of science, in which the entire world and understanding of science would be shaken to the core and greatly modified. This explosion of knowledge led ultimately to that same information revolution that we live in today. Planck and Einstein showed that light was not continuous but made of small corpuscles that today we call photons. Einstein changed the understanding of mechanics with his theory of relativity: airplanes became conceivable; radio and television blossomed; and the microelectronics industry, which drives most of modern technology, came into being. New areas of science were greatly expanded and developed, and one of these was quantum mechanics, which is the story to be told here. Yet, the development of quantum mechanics and the leadership of Niels Bohr have distorted the understanding of quantum mechanics in a strange way. There are some who would say that Bohr set back the real understanding of quantum mechanics by half a century. I believe they underestimate his role, and it may be something more like a full century. Whether we call it the Copenhagen interpretation, or the Copenhagen orthodoxy, it is the how for the continuing mysticism provided by Mach that is still remaining in quantum mechanics. It is not the why. Why it perseveres and why it was forced on the field in the first place is an important perception to be studied. In this book, I want to trace the development of quantum mechanics and try to uncover the why.
Innovative Strategies, Statistical Solutions and Simulations for Modern Clinical Trials (Chapman & Hall/CRC Biostatistics Series)
by Mark Chang John Balser Jim Roach Robin Bliss"This is truly an outstanding book. [It] brings together all of the latest research in clinical trials methodology and how it can be applied to drug development…. Chang et al provide applications to industry-supported trials. This will allow statisticians in the industry community to take these methods seriously." Jay Herson, Johns Hopkins University The pharmaceutical industry's approach to drug discovery and development has rapidly transformed in the last decade from the more traditional Research and Development (R & D) approach to a more innovative approach in which strategies are employed to compress and optimize the clinical development plan and associated timelines. However, these strategies are generally being considered on an individual trial basis and not as part of a fully integrated overall development program. Such optimization at the trial level is somewhat near-sighted and does not ensure cost, time, or development efficiency of the overall program. This book seeks to address this imbalance by establishing a statistical framework for overall/global clinical development optimization and providing tactics and techniques to support such optimization, including clinical trial simulations. Provides a statistical framework for achieve global optimization in each phase of the drug development process. Describes specific techniques to support optimization including adaptive designs, precision medicine, survival-endpoints, dose finding and multiple testing. Gives practical approaches to handling missing data in clinical trials using SAS. Looks at key controversial issues from both a clinical and statistical perspective. Presents a generous number of case studies from multiple therapeutic areas that help motivate and illustrate the statistical methods introduced in the book. Puts great emphasis on software implementation of the statistical methods with multiple examples of software code (both SAS and R). It is important for statisticians to possess a deep knowledge of the drug development process beyond statistical considerations. For these reasons, this book incorporates both statistical and "clinical/medical" perspectives.
Modern and Interdisciplinary Problems in Network Science: A Translational Research Perspective
by Zengqiang Chen Matthias Dehmer Frank Emmert-Streib Yongtang ShiModern and Interdisciplinary Problems in Network Science: A Translational Research Perspective covers a broad range of concepts and methods, with a strong emphasis on interdisciplinarity. The topics range from analyzing mathematical properties of network-based methods to applying them to application areas. By covering this broad range of topics, the book aims to fill a gap in the contemporary literature in disciplines such as physics, applied mathematics and information sciences.
Subtlety in Relativity
by Sanjay Moreshwar WaghSubtlety in Relativity is the only book that has been written after the author’s discovery of a new way in which wave phenomena occur—the emission origin of waves. This drastically changes most issues of the old debate over the world being either deterministic or probabilistic. The emission origin of waves is not incompatible with the ideas of quantum theory; rather, this new and novel way in which waves can be generated justifies the use of mathematical and probabilistic methods of quantum theory. However, the emission origin of waves shows that quantum theory is statistically incomplete in, precisely, Einstein’s sense. There exists, then, a certain, previously unexplored, conceptual framework underlying the ideas of quantum theory. Whether this is the theory that Einstein and others were looking for then, how this way of thinking is related to the ideas of relativity, and whether this is a relativistic theory in the usual sense of this word are questions this book answers. The book demonstrates how the Doppler effect with acceleration is essential to interpreting astronomical observations. It also offers a detailed and self-sufficient technical background of mathematical ideas of category theory. The book is divided into two parts. The first is less mathematical and more conceptual in its orientation. The second focuses on mathematical ideas needed to implement physical concepts. The book is a great reference for advanced undergraduate- and graduate-level students of physics and researchers in physics, astronomy, and cosmology, who will gain a deeper understanding of relativity from it.
Mathematical Modelling for Teachers: Resources, Pedagogy and Practice
by Keng Cheng AngMathematical Modelling for Teachers: Resources, Pedagogy and Practice provides everything that teachers and mathematics educators need to design and implement mathematical modelling activities in their classroom. Authored by an expert in Singapore, the global leader in mathematics education, it is written with an international readership in mind. This book focuses on practical classroom ideas in mathematical modelling suitable to be used by mathematics teachers at the secondary level. As they are interacting with students all the time, teachers generally have good ideas for possible mathematical modelling tasks. However, many have difficulty translating those ideas into concrete modelling activities suitable for a mathematics classroom. In this book, a framework is introduced to assist teachers in designing, planning and implementing mathematical modelling activities, and its use is illustrated through the many examples included. Readers will have access to modelling activities suitable for students from lower secondary levels (Years 7 and 8) onwards, along with the underlying framework, guiding notes for teachers and suggested approaches to solve the problems. The activities are grouped according to the types of models constructed: empirical, deterministic and simulation models. Finally, the book gives the reader suggestions of different ways to assess mathematical modelling competencies in students.
Entrepreneurial Complexity: Methods and Applications
by Matthias Dehmer Frank Emmert-Streib Herbert JodlbauerEntrepreneurial Complexity: Methods and Applications deals with theoretical and practical results of Entrepreneurial Sciences and Management (ESM), emphasising qualitative and quantitative methods. ESM has been a modern and exciting research field in which methods from various disciplines have been applied. However, the existing body of literature lacks the proper use of mathematical and formal models; individuals who perform research in this broad interdisciplinary area have been trained differently. In particular, they are not used to solving business-oriented problems mathematically. This book utilises formal techniques in ESM as an advantage for developing theories and models which are falsifiable. Features Discusses methods for defining and measuring complexity in entrepreneurial sciences Summarises new technologies and innovation-based techniques in entrepreneurial sciences Outlines new formal methods and complexity-models for entrepreneurship To date no book has been dedicated exclusively to use formal models in Entrepreneurial Sciences and Management
The Learning and Teaching of Algebra: Ideas, Insights and Activities (IMPACT: Interweaving Mathematics Pedagogy and Content for Teaching #8)
by Kaye Stacey Paul Drijvers Abraham ArcaviIMPACT (Interweaving Mathematics Pedagogy and Content for Teaching) is an exciting new series of texts for teacher education which aims to advance the learning and teaching of mathematics by integrating mathematics content with the broader research and theoretical base of mathematics education. The Learning and Teaching of Algebra provides a pedagogical framework for the teaching and learning of algebra grounded in theory and research. Areas covered include: • Algebra: Setting the Scene • Some Lessons From History • Seeing Algebra Through the Eyes of a Learner • Emphases in Algebra Teaching • Algebra Education in the Digital Era This guide will be essential reading for trainee and qualified teachers of mathematics, graduate students, curriculum developers, researchers and all those who are interested in the "problématique" of teaching and learning algebra. It allows you to get involved in the wealth of knowledge that teachers can draw upon to assist learners, helping you gain the insights that mastering algebra provides.
Analytical Similarity Assessment in Biosimilar Product Development
by Shein-Chung ChowThis book focuses on analytical similarity assessment in biosimilar product development following the FDA’s recommended stepwise approach for obtaining totality-of-the-evidence for approval of biosimilar products. It covers concepts such as the tiered approach for assessment of similarity of critical quality attributes in the manufacturing process of biosimilar products, models/methods like the statistical model for classification of critical quality attributes, equivalence tests for critical quality attributes in Tier 1 and the corresponding sample size requirements, current issues, and recent developments in analytical similarity assessment.
GPU Pro 360 Guide to Geometry Manipulation
by Wolfgang EngelWolfgang Engel’s GPU Pro 360 Guide to Geometry Manipulation gathers all the cutting-edge information from his previous seven GPU Pro volumes into a convenient single source anthology that covers geometry manipulation in computer graphics. This volume is complete with 19 articles by leading programmers that focus on the ability of graphics processing units to process and generate geometry in exciting ways. GPU Pro 360 Guide to Geometry Manipulation is comprised of ready-to-use ideas and efficient procedures that can help solve many computer graphics programming challenges that may arise. Key Features: Presents tips and tricks on real-time rendering of special effects and visualization data on common consumer software platforms such as PCs, video consoles, mobile devices Covers specific challenges involved in creating games on various platforms Explores the latest developments in the rapidly evolving field of real-time rendering Takes a practical approach that helps graphics programmers solve their daily challenges
Nonparametric Models for Longitudinal Data: With Implementation in R (Chapman & Hall/CRC Monographs on Statistics and Applied Probability)
by Colin O. Wu Xin TianNonparametric Models for Longitudinal Data with Implementations in R presents a comprehensive summary of major advances in nonparametric models and smoothing methods with longitudinal data. It covers methods, theories, and applications that are particularly useful for biomedical studies in the era of big data and precision medicine. It also provides flexible tools to describe the temporal trends, covariate effects and correlation structures of repeated measurements in longitudinal data. This book is intended for graduate students in statistics, data scientists and statisticians in biomedical sciences and public health. As experts in this area, the authors present extensive materials that are balanced between theoretical and practical topics. The statistical applications in real-life examples lead into meaningful interpretations and inferences. Features: Provides an overview of parametric and semiparametric methods Shows smoothing methods for unstructured nonparametric models Covers structured nonparametric models with time-varying coefficients Discusses nonparametric shared-parameter and mixed-effects models Presents nonparametric models for conditional distributions and functionals Illustrates implementations using R software packages Includes datasets and code in the authors’ website Contains asymptotic results and theoretical derivations Both authors are mathematical statisticians at the National Institutes of Health (NIH) and have published extensively in statistical and biomedical journals. Colin O. Wu earned his Ph.D. in statistics from the University of California, Berkeley (1990), and is also Adjunct Professor at the Georgetown University School of Medicine. He served as Associate Editor for Biometrics and Statistics in Medicine, and reviewer for National Science Foundation, NIH, and the U.S. Department of Veterans Affairs. Xin Tian earned her Ph.D. in statistics from Rutgers, the State University of New Jersey (2003). She has served on various NIH committees and collaborated extensively with clinical researchers.
Knot Theory: Second Edition
by Vassily Olegovich ManturovOver the last fifteen years, the face of knot theory has changed due to various new theories and invariants coming from physics, topology, combinatorics and alge-bra. It suffices to mention the great progress in knot homology theory (Khovanov homology and Ozsvath-Szabo Heegaard-Floer homology), the A-polynomial which give rise to strong invariants of knots and 3-manifolds, in particular, many new unknot detectors. New to this Edition is a discussion of Heegaard-Floer homology theory and A-polynomial of classical links, as well as updates throughout the text. Knot Theory, Second Edition is notable not only for its expert presentation of knot theory’s state of the art but also for its accessibility. It is valuable as a profes-sional reference and will serve equally well as a text for a course on knot theory.
Introduction to Python for Science and Engineering (Series in Computational Physics)
by David J. PineSeries in Computational PhysicsSteven A. Gottlieb and Rubin H. Landau, Series Editors Introduction to Python for Science and Engineering This guide offers a quick and incisive introduction to Python programming for anyone. The author has carefully developed a concise approach to using Python in any discipline of science and engineering, with plenty of examples, practical hints, and insider tips. Readers will see why Python is such a widely appealing program, and learn the basics of syntax, data structures, input and output, plotting, conditionals and loops, user-defined functions, curve fitting, numerical routines, animation, and visualization. The author teaches by example and assumes no programming background for the reader. David J. Pine is the Silver Professor and Professor of Physics at New York University, and Chair of the Department of Chemical and Biomolecular Engineering at the NYU Tandon School of Engineering. He is an elected fellow of the American Physical Society and American Association for the Advancement of Science (AAAS), and is a Guggenheim Fellow.
Computational Blood Cell Mechanics: Road Towards Models and Biomedical Applications (Chapman & Hall/CRC Computational Biology Series)
by Ivan Cimrak Iveta JancigovaSimulating blood cells for biomedical applications is a challenging goal. Whether you want to investigate blood flow behavior on the cell scale, or use a blood cell model for fast computational prototyping in microfluidics, Computational Blood Cell Mechanics will help you get started, and show you the path forward. The text presents a step-by-step approach to cell model building that can be adopted when developing and validating models for biomedical applications, such as filtering and sorting cells, or examining flow and deformations of individual cells under various conditions. It starts with basic building-blocks that, together, model the red blood cell membrane according to its physical properties, before moving on to discuss several issues that may pose problems along the way, and finally leads to suggestions on how to set up computational experiments. More details available at www.compbloodcell.eu
Data Visualization Made Simple: Insights into Becoming Visual
by Kristen SosulskiData Visualization Made Simple is a practical guide to the fundamentals, strategies, and real-world cases for data visualization, an essential skill required in today’s information-rich world. With foundations rooted in statistics, psychology, and computer science, data visualization offers practitioners in almost every field a coherent way to share findings from original research, big data, learning analytics, and more. In nine appealing chapters, the book: examines the role of data graphics in decision-making, sharing information, sparking discussions, and inspiring future research; scrutinizes data graphics, deliberates on the messages they convey, and looks at options for design visualization; and includes cases and interviews to provide a contemporary view of how data graphics are used by professionals across industries Both novices and seasoned designers in education, business, and other areas can use this book’s effective, linear process to develop data visualization literacy and promote exploratory, inquiry-based approaches to visualization problems.
The Universal Computer: The Road from Leibniz to Turing, Third Edition
by Martin DavisThe breathtakingly rapid pace of change in computing makes it easy to overlook the pioneers who began it all. The Universal Computer: The Road from Leibniz to Turing explores the fascinating lives, ideas, and discoveries of seven remarkable mathematicians. It tells the stories of the unsung heroes of the computer age – the logicians.
Low Power Circuits for Emerging Applications in Communications, Computing, and Sensing (Devices, Circuits, and Systems)
by Fei YuanThe book addresses the need to investigate new approaches to lower energy requirement in multiple application areas and serves as a guide into emerging circuit technologies. It explores revolutionary device concepts, sensors, and associated circuits and architectures that will greatly extend the practical engineering limits of energy-efficient computation. The book responds to the need to develop disruptive new system architecutres, circuit microarchitectures, and attendant device and interconnect technology aimed at achieving the highest level of computational energy efficiency for general purpose computing systems. Features Discusses unique technologies and material only available in specialized journal and conferences Covers emerging applications areas, such as ultra low power communications, emerging bio-electronics, and operation in extreme environments Explores broad circuit operation, ex. analog, RF, memory, and digital circuits Contains practical applications in the engineering field, as well as graduate studies Written by international experts from both academia and industry
Planetary Remote Sensing and Mapping (ISPRS Book Series)
by Bo Wu Kaichang Di Jürgen Oberst Irina KarachevtsevaThe early 21st century marks a new era in space exploration. The National Aeronautics and Space Administration (NASA) of the United States, The European Space Agency (ESA), as well as space agencies of Japan, China, India, and other countries have sent their probes to the Moon, Mars, and other planets in the solar system. Planetary Remote Sensing and Mapping introduces original research and new developments in the areas of planetary remote sensing, photogrammetry, mapping, GIS, and planetary science resulting from the recent space exploration missions. Topics covered include: Reference systems of planetary bodies Planetary exploration missions and sensors Geometric information extraction from planetary remote sensing data Feature information extraction from planetary remote sensing data Planetary remote sensing data fusion Planetary data management and presentation Planetary Remote Sensing and Mapping will serve scientists and professionals working in the planetary remote sensing and mapping areas, as well as planetary probe designers, engineers, and planetary geologists and geophysicists. It also provides useful reading material for university teachers and students in the broader areas of remote sensing, photogrammetry, cartography, GIS, and geodesy.
Parallel Programming for Modern High Performance Computing Systems
by Pawel CzarnulIn view of the growing presence and popularity of multicore and manycore processors, accelerators, and coprocessors, as well as clusters using such computing devices, the development of efficient parallel applications has become a key challenge to be able to exploit the performance of such systems. This book covers the scope of parallel programming for modern high performance computing systems. It first discusses selected and popular state-of-the-art computing devices and systems available today, These include multicore CPUs, manycore (co)processors, such as Intel Xeon Phi, accelerators, such as GPUs, and clusters, as well as programming models supported on these platforms. It next introduces parallelization through important programming paradigms, such as master-slave, geometric Single Program Multiple Data (SPMD) and divide-and-conquer. The practical and useful elements of the most popular and important APIs for programming parallel HPC systems are discussed, including MPI, OpenMP, Pthreads, CUDA, OpenCL, and OpenACC. It also demonstrates, through selected code listings, how selected APIs can be used to implement important programming paradigms. Furthermore, it shows how the codes can be compiled and executed in a Linux environment. The book also presents hybrid codes that integrate selected APIs for potentially multi-level parallelization and utilization of heterogeneous resources, and it shows how to use modern elements of these APIs. Selected optimization techniques are also included, such as overlapping communication and computations implemented using various APIs. Features: Discusses the popular and currently available computing devices and cluster systems Includes typical paradigms used in parallel programs Explores popular APIs for programming parallel applications Provides code templates that can be used for implementation of paradigms Provides hybrid code examples allowing multi-level parallelization Covers the optimization of parallel programs
The Social Effects of Global Trade
by Joy Murray Arunima Malik Arne GeschkeThe inclusion of qualitative social data into global environmental and economic input-output (IO) models remained illusive for many years. It was not until around 2013 that researchers found ways to include data, for example, on poverty, inequality, and worker safety, into IO models capable of tracing global supply chains. The sustainable development goals have now propelled this work onto the world stage with some urgency. They have shone a spotlight onto social conditions around the world and brought global trade into the frame for its ability to influence social conditions for good or ill. This book provides a compilation of groundbreaking work on social indicators from the most prominent IO research groups from a wide range of academic backgrounds and from around the world. In addition, it frames this work in the real world of politics, human rights, and business, bringing together a multidisciplinary team to demonstrate the power of IO to illuminate some of the world’s most pressing problems. Edited by well-known researchers in the area, Joy Murray, Arunima Malik, and Arne Geschke, the book is designed to appeal to a broad academic and business audience. While many chapters include technical details and references for follow-up reading, it is possible to omit those sections and yet gain a deep appreciation of the power of IO to address seemingly intractable problems.
Learn RStudio IDE: Quick, Effective, and Productive Data Science
by Matthew CampbellDiscover how to use the popular RStudio IDE as a professional tool that includes code refactoring support, debugging, and Git version control integration. This book gives you a tour of RStudio and shows you how it helps you do exploratory data analysis; build data visualizations with ggplot; and create custom R packages and web-based interactive visualizations with Shiny. In addition, you will cover common data analysis tasks including importing data from diverse sources such as SAS files, CSV files, and JSON. You will map out the features in RStudio so that you will be able to customize RStudio to fit your own style of coding.Finally, you will see how to save a ton of time by adopting best practices and using packages to extend RStudio. Learn RStudio IDE is a quick, no-nonsense tutorial of RStudio that will give you a head start to develop the insights you need in your data science projects.What You Will LearnQuickly, effectively, and productively use RStudio IDE for building data science applicationsInstall RStudio and program your first Hello World applicationAdopt the RStudio workflow Make your code reusable using RStudioUse RStudio and Shiny for data visualization projectsDebug your code with RStudio Import CSV, SPSS, SAS, JSON, and other dataWho This Book Is ForProgrammers who want to start doing data science, but don’t know what tools to focus on to get up to speed quickly.
Notes from the International Autumn School on Computational Number Theory (Tutorials, Schools, and Workshops in the Mathematical Sciences)
by Ilker Inam Engin BüyükaşıkThis volume collects lecture notes and research articles from the International Autumn School on Computational Number Theory, which was held at the Izmir Institute of Technology from October 30th to November 3rd, 2017 in Izmir, Turkey. Written by experts in computational number theory, the chapters cover a variety of the most important aspects of the field. By including timely research and survey articles, the text also helps pave a path to future advancements. Topics include:Modular formsL-functionsThe modular symbols algorithmDiophantine equationsNullstellensatzEisenstein seriesNotes from the International Autumn School on Computational Number Theory will offer graduate students an invaluable introduction to computational number theory. In addition, it provides the state-of-the-art of the field, and will thus be of interest to researchers interested in the field as well.