This book constitutes the thoroughly refereed post-proceedings of the PASCAL (pattern analysis, statistical modelling and computational learning) Statistical and Optimization Perspectives Workshop on Subspace, Latent Structure and Feature Selection techniques, SLSFS 2005. The 9 revised full papers presented together with 5 invited papers reflect the key approaches that have been developed for subspace identification and feature selection using dimension reduction techniques, subspace methods, random projection methods, among others.

The R Companion to Elementary Applied Statistics includes traditional applications covered in elementary statistics courses as well as some additional methods that address questions that might arise during or after the application of commonly used methods. Beginning with basic tasks and computations with R, readers are then guided through ways to bring data into R, manipulate the data as needed, perform common statistical computations and elementary exploratory data analysis tasks, prepare customized graphics, and take advantage of R for a wide range of methods that find use in many elementary applications of statistics. Features: Requires no familiarity with R or programming to begin using this book. Can be used as a resource for a project-based elementary applied statistics course, or for researchers and professionals who wish to delve more deeply into R. Contains an extensive array of examples that illustrate ideas on various ways to use pre-packaged routines, as well as on developing individualized code. Presents quite a few methods that may be considered non-traditional, or advanced. Includes accompanying carefully documented script files that contain code for all examples presented, and more. R is a powerful and free product that is gaining popularity across the scientific community in both the professional and academic arenas. Statistical methods discussed in this book are used to introduce the fundamentals of using R functions and provide ideas for developing further skills in writing R code. These ideas are illustrated through an extensive collection of examples. About the Author: Christopher Hay-Jahans received his Doctor of Arts in mathematics from Idaho State University in 1999. After spending three years at University of South Dakota, he moved to Juneau, Alaska, in 2002 where he has taught a wide range of undergraduate courses at University of Alaska Southeast.

Best-Practice: Webprojekte bringen hohen wirtschaftlichen Erfolg, wenn sie gelingen. Dazu bedarf es vor allem eines speziellen Projektmanagements. Dieses Handbuch fuhrt Projektleiter und Entscheider zum Erfolg: effektive Managementmethoden und Projektkommunikation, Fallstricke, heikle Projektsituationen, rechtliche Rahmenbedingungen (insbes. Internetrecht). Das Autorenteam aus erfahrenen Managern und Fachexperten stellt Best-Practices aus der Sicht von Kunden und Dienstleistern vor. Ein Buch fur Projektleiter, Entscheider, Lehrende und Studierende (E-Business, Informatik, Design). Erfolgreiche Managementmethoden in 2., uberarbeiteter Auflage."

Starting from a basic knowledge of mathematics and mechanics gained in standard foundation classes, "Theory of Lift: Introductory Computational Aerodynamics in MATLAB/Octave" takes the reader conceptually through from the fundamental mechanics of lift to the stage of actually being able to make practical calculations and predictions of the coefficient of lift for realistic wing profile and planform geometries.

The classical framework and methods of aerodynamics are covered in detail and the reader is shown how they may be used to develop simple yet powerful MATLAB or Octave programs that accurately predict and visualise the dynamics of real wing shapes, using lumped vortex, panel, and vortex lattice methods.

This book contains all the mathematical development and formulae required in standard incompressible aerodynamics as well as dozens of small but complete working programs which can be put to use immediately using either the popular MATLAB or free Octave computional modelling packages.

Key features: Synthesizes the classical foundations of aerodynamics with hands-on computation, emphasizing interactivity and visualization.Includes complete source code for all programs, all listings having been tested for compatibility with both MATLAB and Octave.Companion website (www.wiley.com/go/mcbain) hosting codes and solutions.

"Theory of Lift: Introductory Computational Aerodynamics in MATLAB/Octave" is an introductory text for graduate and senior undergraduate students on aeronautical and aerospace engineering courses and also forms a valuable reference for engineers and designers.

No book is born in a vacuum. There must always be somebody who needs the book, somebody who will read and use it, and somebody who will write it. I walked with the idea of this book for a long time. However, its final concept came into reality during my lectures, in February 2005, at the Universiti Malaysia Sabah in Borneo. I realized that my students needed a bit more than just my lectures. They needed a text that they could follow during lab sessions or after classes so they could learn at any time, at their own pace. Therefore, I decided to write a small book with just a few chapters covering the different areas of applying the Computer Algebra System called MuPAD in different areas of mathematics. I intended each chapter to be short enough to be covered in a reasonably short time, about 2 to 4 hours. Another important objective was to have each chapter completely independent of the others, so that the readers could easily select and read the chapters that they needed the most, without being forced to read the whole book. There was one obstacle for such a concept-the large number of graphics I used to visualize mathematics. Therefore, I finally decided to write a separate chapter covering the major concepts of MuPAD graphics. The graphics chapter, together with the introductory chapter, forms the base for all the remaining chapters.

This book constitutes the refereed proceedings of the Second International Congress on Mathematical Software, ICMS 2006, held in Castro Urdiales, Spain in September 2006.

The 45 revised full papers presented were carefully reviewed and selected for presentation. The papers are organized in topical sections on new developments on computer algebra packages, interfacing computer algebra on mathematical visualization, software for algebraic geometry and related topics, number-theoretical software, methods in computational number theory, free software for computer algebra, software for optimization on geometric computation, methods and software for computing mathematical functions, access to mathematics on the Web, and general issues.

The OMDoc (Open Mathematical Documents) format is a content markup scheme for collections of mathematical documents, including articles, textbooks, interactive books, and courses. OMDoc also serves as the content language for agent communication of mathematical services and a mathematical software bus.

This documentation describes version 1.2 of the OMDoc system, the final and mature release of OMDoc 1. The system features modularized language design, OPENMATH and MATHML for the representation of mathematical objects, and has been employed and validated in various applications.

Besides a complete and rigorous specification of the OMDoc document format, this book presents an OMDoc primer with paradigmatic examples for many kinds of mathematical documents. Furthermore, various applications, projects, and tool support for OMDoc are discussed. The book will become essential reading for all working mathematicians and mathematics students aspiring to take part in the new worlds of shared mathematical knowledge.

In biological research, the amount of data available to researchers has increased so much over recent years, it is becoming increasingly difficult to understand the current state of the art without some experience and understanding of data analytics and bioinformatics. An Introduction to Bioinformatics with R: A Practical Guide for Biologists leads the reader through the basics of computational analysis of data encountered in modern biological research. With no previous experience with statistics or programming required, readers will develop the ability to plan suitable analyses of biological datasets, and to use the R programming environment to perform these analyses. This is achieved through a series of case studies using R to answer research questions using molecular biology datasets. Broadly applicable statistical methods are explained, including linear and rank-based correlation, distance metrics and hierarchical clustering, hypothesis testing using linear regression, proportional hazards regression for survival data, and principal component analysis. These methods are then applied as appropriate throughout the case studies, illustrating how they can be used to answer research questions. Key Features: * Provides a practical course in computational data analysis suitable for students or researchers with no previous exposure to computer programming. * Describes in detail the theoretical basis for statistical analysis techniques used throughout the textbook, from basic principles * Presents walk-throughs of data analysis tasks using R and example datasets. All R commands are presented and explained in order to enable the reader to carry out these tasks themselves. * Uses outputs from a large range of molecular biology platforms including DNA methylation and genotyping microarrays; RNA-seq, genome sequencing, ChIP-seq and bisulphite sequencing; and high-throughput phenotypic screens. * Gives worked-out examples geared towards problems encountered in cancer research, which can also be applied across many areas of molecular biology and medical research. This book has been developed over years of training biological scientists and clinicians to analyse the large datasets available in their cancer research projects. It is appropriate for use as a textbook or as a practical book for biological scientists looking to gain bioinformatics skills.

There's a lot more to the blockchain than mining Bitcoin. This secure system for registering and verifying ownership and identity is perfect for supply chain logistics, health records, and other sensitive data management tasks. Blockchain in Action unlocks the full potential of this revolutionary technology, showing you how to build own decentralized apps for secure applications including digital democracy, private auctions, and electronic record management. Key Features * How blockchain differs from other distributed systems * Smart contract development with Ethereum and the Solidity language * Web UI for decentralized apps * Identity, privacy and security techniques * On-chain and off-chain data storage For intermediate programmers who know the basics of object-oriented languages and have a working knowledge of JavaScript. About the technology A blockchain is a decentralized record, stored across numerous devices with no central control or authority. Copies of this shared database are constantly reconciled with one another, and records are cryptographically encoded to make them unchangeable. The result is a type of database that is at once transparent and publicly accessible, and where it is impossible to falsify or alter the historic data record. Bina Ramamurthy holds a Ph.D. in fault-tolerant distributed systems, and has thirty years of experience teaching cryptography, peer-to-peer networking, and distributed systems. She is the instructor and content creator for the University of Buffalo four-course specialization on blockchain technology on the Coursera MOOC platform, and the recipient of the 2019 SUNY Chancellor's Award for Teaching Excellence.

This innovative textbook presents material for a course on modern statistics that incorporates Python as a pedagogical and practical resource. Drawing on many years of teaching and conducting research in various applied and industrial settings, the authors have carefully tailored the text to provide an ideal balance of theory and practical applications. Numerous examples and case studies are incorporated throughout, and comprehensive Python applications are illustrated in detail. A custom Python package is available for download, allowing students to reproduce these examples and explore others. The first chapters of the text focus on analyzing variability, probability models, and distribution functions. Next, the authors introduce statistical inference and bootstrapping, and variability in several dimensions and regression models. The text then goes on to cover sampling for estimation of finite population quantities and time series analysis and prediction, concluding with two chapters on modern data analytic methods. Each chapter includes exercises, data sets, and applications to supplement learning. Modern Statistics: A Computer-Based Approach with Python is intended for a one- or two-semester advanced undergraduate or graduate course. Because of the foundational nature of the text, it can be combined with any program requiring data analysis in its curriculum, such as courses on data science, industrial statistics, physical and social sciences, and engineering. Researchers, practitioners, and data scientists will also find it to be a useful resource with the numerous applications and case studies that are included. A second, closely related textbook is titled Industrial Statistics: A Computer-Based Approach with Python. It covers topics such as statistical process control, including multivariate methods, the design of experiments, including computer experiments and reliability methods, including Bayesian reliability. These texts can be used independently or for consecutive courses. The mistat Python package can be accessed at https://gedeck.github.io/mistat-code-solutions/ModernStatistics/ "In this book on Modern Statistics, the last two chapters on modern analytic methods contain what is very popular at the moment, especially in Machine Learning, such as classifiers, clustering methods and text analytics. But I also appreciate the previous chapters since I believe that people using machine learning methods should be aware that they rely heavily on statistical ones. I very much appreciate the many worked out cases, based on the longstanding experience of the authors. They are very useful to better understand, and then apply, the methods presented in the book. The use of Python corresponds to the best programming experience nowadays. For all these reasons, I think the book has also a brilliant and impactful future and I commend the authors for that." Professor Fabrizio RuggeriResearch Director at the National Research Council, ItalyPresident of the International Society for Business and Industrial Statistics (ISBIS)Editor-in-Chief of Applied Stochastic Models in Business and Industry (ASMBI)

TheInternationalConferenceonMathematicalKnowledgeManagementhasnow reached its third edition, creating and establishing an original and stimulating scienti?ccommunitytransversaltomanydi?erent?eldsandresearchtopics. The broad goal of MKM is the exploration of innovative, semantically enriched, d- ital encodings of mathematical information, and the study of new services and tools exploiting the machine-understandable nature of the information. MKM is naturally located in the border area between digital libraries and the mec- nization of mathematics, devoting a particular interest to the new developments in information technology, and fostering their application to the realm of ma- ematical information. The conference is meant to be a forum for presenting, discussing and comparing new tools and systems, standardization e?orts, cri- calsurveys, largeexperiments, andcasestudies. Atpresent, wearestillgettingto knoweachother, tounderstandtheworkdonebyotherpeople, andthepotenti- ities o?ered by their work to our own research activity. However, the conference is rapidly acquiring scienti?c strength and academic interest, attracting more and more people and research groups, and o?ering a challenging alternative to older, more conservative conferences. July 2004 Andrea Asperti Grzegorz Bancerek Andrzej Trybulec Organization MKM 2004 was organized by the Institute of Computer Science, University of Bia lystokinco-operationwiththeFacultyofComputerScience, Bia lystokTe- nical University and the Association of Mizar Users. Program Committee Andrzej Trybulec (Chair) University of Bia lystok, Poland Andrew A. Adams University of Reading, UK Andrea Asperti University of Bologna, Italy Bruno Buchberger RISC Linz, Austria Roy McCasland University of Edinburgh, UK James Davenport University of Bath, UK Will

For problems that require extensive computation, a C++ program can race through billions of examples faster than most other computing choices. C++ enables mathematicians of virtually any discipline to create programs to meet their needs quickly, and is available on most computer systems at no cost. C++ for Mathematicians: An Introduction for Students and Professionals accentuates C++ concepts that are most valuable for pure and applied mathematical research. This is the first book available on C++ programming that is written specifically for a mathematical audience; it omits the language's more obscure features in favor of the aspects of greatest utility for mathematical work. The author explains how to use C++ to formulate conjectures, create images and diagrams, verify proofs, build mathematical structures, and explore myriad examples. Emphasizing the essential role of practice as part of the learning process, the book is ideally designed for undergraduate coursework as well as self-study. Each chapter provides many problems and solutions which complement the text and enable you to learn quickly how to apply them to your own problems. Accompanying downloadable resources provide all numbered programs so that readers can easily use or adapt the code as needed. Presenting clear explanations and examples from the world of mathematics that develop concepts from the ground up, C++ for Mathematicians can be used again and again as a resource for applying C++ to problems that range from the basic to the complex.

This book explains basic principles of MuPAD commands. It teaches how to write simple programs and develop interactive environments for teaching mathematics. The text gives a large number of useful examples from different areas of undergraduate mathematics developed by the author during his long teaching experience. All the book examples are available online. Flash, SVG and JVX formats are used to display interactive and animated graphics.

Customer relationship management, or CRM, is certainly a hot topic in business today. If you have a small or medium-sized business, chances are you're already aware of all it can do for you. But with so many options and so much to think about, how do you get a CRM system in place with a minimum of hassle? Well, Microsoft Dynamics CRM 4 For Dummies is a great place to start! Written by veteran CRM experts Joel Scott and David Lee, this friendly guide will have you understanding and using Microsoft's CRM solution in a jiffy. Whether you're considering a CRM system for the first time or you've decided to switch from another system to Microsoft Dynamics CRM, this book will make it easy to: Maintain and manage all your customer information Personalize Microsoft CRM to work for your business Set up CRM to support sales, marketing, and customer service Use the Outlook client Manage territories and business units Create and manage activities Generate quotes and invoices Implement and manage a marketing campaign Work with contracts, and much more Microsoft Dynamics CRM 4 For Dummies is packed with information on the latest version, It will help you get a unified view of your customer information and interactions through integrated sales, marketing, and customer service features. And that, as every business owner knows, is important to improving your bottom line!

Age-Period-Cohort analysis has a wide range of applications, from chronic disease incidence and mortality data in public health and epidemiology, to many social events (birth, death, marriage, etc) in social sciences and demography, and most recently investment, healthcare and pension contribution in economics and finance. Although APC analysis has been studied for the past 40 years and a lot of methods have been developed, the identification problem has been a major hurdle in analyzing APC data, where the regression model has multiple estimators, leading to indetermination of parameters and temporal trends. A Practical Guide to Age-Period Cohort Analysis: The Identification Problem and Beyond provides practitioners a guide to using APC models as well as offers graduate students and researchers an overview of the current methods for APC analysis while clarifying the confusion of the identification problem by explaining why some methods address the problem well while others do not. Features * Gives a comprehensive and in-depth review of models and methods in APC analysis. * Provides an in-depth explanation of the identification problem and statistical approaches to addressing the problem and clarifying the confusion. * Utilizes real data sets to illustrate different data issues that have not been addressed in the literature, including unequal intervals in age and period groups, etc. Contains step-by-step modeling instruction and R programs to demonstrate how to conduct APC analysis and how to conduct prediction for the future Reflects the most recent development in APC modeling and analysis including the intrinsic estimator Wenjiang Fu is a professor of statistics at the University of Houston. Professor Fu's research interests include modeling big data, applied statistics research in health and human genome studies, and analysis of complex economic and social science data.

Intended as a companion for textbooks in mathematical methods for science and engineering, this book presents a large number of numerical topics and exercises together with discussions of methods for solving such problems using Mathematica(R). The accompanying CD contains Mathematica Notebooks for illustrating most of the topics in the text and for solving problems in mathematical physics. Although it is primarily designed for use with the author's "Mathematical Methods: For Students of Physics and Related Fields," the discussions in the book sufficiently self-contained that the book can be used as a supplement to any of the standard textbooks in mathematical methods for undergraduate students of physical sciences or engineering.

Most biologists use nonlinear regression more than any other statistical technique, but there are very few places to learn about curve-fitting. This book, by the author of the very successful Intuitive Biostatistics, addresses this relatively focused need of an extraordinarily broad range of scientists.

Statistical computing provides the link between statistical theory and applied statistics. The content of the book covers all aspects of this link, from the development and implementation of new statistical ideas to user experiences and software evaluation. The proceedings should appeal to anyone working in statistics and using computers, whether in universities, industrial companies, government agencies, research institutes or as software developers

This open access book provides insights into the novel Locally Refined B-spline (LR B-spline) surface format, which is suited for representing terrain and seabed data in a compact way. It provides an alternative to the well know raster and triangulated surface representations. An LR B-spline surface has an overall smooth behavior and allows the modeling of local details with only a limited growth in data volume. In regions where many data points belong to the same smooth area, LR B-splines allow a very lean representation of the shape by locally adapting the resolution of the spline space to the size and local shape variations of the region. The iterative method can be modified to improve the accuracy in particular domains of a point cloud. The use of statistical information criterion can help determining the optimal threshold, the number of iterations to perform as well as some parameters of the underlying mathematical functions (degree of the splines, parameter representation). The resulting surfaces are well suited for analysis and computing secondary information such as contour curves and minimum and maximum points. Also deformation analysis are potential applications of fitting point clouds with LR B-splines.

This comprehensive study guide delivers complete coverage of every topic on the CompTIA Project+ exam Take the challenging CompTIA Project+ (Exam PK0-005) with complete confidence using the detailed information contained in this highly effective self-study guide. You will get clear explanations of every topic on the test along with special elements that reinforce and teach practical skills, step-by-step exercises, exam tips, and notes. The book serves both a powerful exam preparation tool and an ideal on-the-job reference. Written by an expert in the field, CompTIA Project+ Certification All-in-One Exam Guide (Exam PK0-005) offers complete coverage of every topic on the test and features accurate practice questions. You will get coverage of IT project life cycles, project roles, and the skills necessary to effectively initiate, plan, execute, monitor and close a project. Sidebars throughout offer real-world insights and practical applications, and end-of-chapter summaries and review questions aid in retention. Delivers 100% coverage of all objectives for the CompTIA Project+ certification exam Contains a discount code for 10% off of the exam Online content includes 180 practice questions, video training, and downloadable worksheets and templates

This book constitutes the thoroughly refereed post-proceedings of the 10th International Symposium on Graph Drawing, GD 2002, held in Irvine, CA, USA, in August 2002.The 24 revised full papers, 9 short papers, and 7 software demonstrations presented together with a report on the GD 2002 graph drawing contest were carefully reviewed and selected from a total of 48 regular paper submissions. All current aspects of graph drawing are addressed.

All disciplines of science and engineering use numerical methods for complex problem analysis, due to the highly mathematical nature of the field. Analytical methods alone are unable to solve many complex problems engineering students and professionals confront. Introduction to MATLAB (R) Programming for Engineers and Scientists examines the basic elements of code writing, and describes MATLAB (R) methods for solving common engineering problems and applications across the range of engineering disciplines. The text uses a class-tested learning approach and accessible two-color page design to guide students from basic programming to the skills needed for future coursework and engineering practice.

This COMPSTAT 2002 book contains the Keynote, Invited, and Full Contributed papers presented in Berlin, August 2002. A companion volume including Short Communications and Posters is published on CD. The COMPSTAT 2002 is the 15th conference in a serie of biannual conferences with the objective to present the latest developments in Computational Statistics and is taking place from August 24th to August 28th, 2002. Previous COMPSTATs were in Vienna (1974), Berlin (1976), Leiden (1978), Edinburgh (1980), Toulouse (1982), Pra ue (1984), Rome (1986), Copenhagen (1988), Dubrovnik (1990), Neuchatel (1992), Vienna (1994), Barcelona (1996), Bris tol (1998) and Utrecht (2000). COMPSTAT 2002 is organised by CASE, Center of Applied Statistics and Eco nomics at Humboldt-Universitat zu Berlin in cooperation with F'reie Universitat Berlin and University of Potsdam. The topics of COMPSTAT include methodological applications, innovative soft ware and mathematical developments, especially in the following fields: statistical risk management, multivariate and robust analysis, Markov Chain Monte Carlo Methods, statistics of E-commerce, new strategies in teaching (Multimedia, In ternet), computerbased sampling/questionnaires, analysis of large databases (with emphasis on computing in memory), graphical tools for data analysis, classification and clustering, new statistical software and historical development of software."

Completely up to date and extremely student friendly, A SIMPLE GUIDE TO IBM SPSS: FOR VERSION 23.0, Fourteenth Edition, equips you with everything you need to know about the newest version of SPSS (R) for Windows (R) so you can effectively use the program in your statistics class. The guide's straightforward style frees you to concentrate on learning basic statistical concepts, while still developing familiarity with SPSS (R). Its clear, step-by-step instruction quickly gets you up to speed, enabling you to confidently use SPSS (R) to do homework problems and conduct statistical analyses for research projects.

Aufgrund des heute verbreiteten teamorientierten Arbeitens wird der Ingenieur in Entwicklung und Konstruktion mehr und mehr in den Planungs-, Beschaffungs- und Produktionsprozess involviert. Zur BewAltigung dieser Aufgaben braucht er neue Methoden der EntscheidungsunterstA1/4tzung und der Informationsbeschaffung, da die herkAmmlichen AnsAtze des Produktdatenmanagements nicht ausreichend sind. Neue Strategien fA1/4r das Product Lifecycle Management enthalten zusAtzliche FunktionsumfAnge zur UnterstA1/4tzung der unternehmensinternen und -externen Zusammenarbeit von Entwicklungspartnern, des Supply Chain Prozesses, des Product Portfolio Management und des Customer Needs Management. Das Buch unterstA1/4tzt die Planung, Entscheidungsfindung und EinfA1/4hrung geeigneter LAsungskonzepte.