This book focuses on solving optimization problems with MATLAB. Descriptions and solutions of nonlinear equations of any form are studied first. Focuses are made on the solutions of various types of optimization problems, including unconstrained and constrained optimizations, mixed integer, multiobjective and dynamic programming problems. Comparative studies and conclusions on intelligent global solvers are also provided.

This book focuses on solving practical problems in calculus with MATLAB. Descriptions and sketching of functions and sequences are introduced first, followed by the analytical solutions of limit, differentiation, integral and function approximation problems of univariate and multivariate functions. Advanced topics such as numerical differentiations and integrals, integral transforms as well as fractional calculus are also covered in the book.

This book focuses the solutions of linear algebra and matrix analysis problems, with the exclusive use of MATLAB. The topics include representations, fundamental analysis, transformations of matrices, matrix equation solutions as well as matrix functions. Attempts on matrix and linear algebra applications are also explored.

This textbook is aimed at computer science undergraduates late in sophomore or early in junior year, supplying a comprehensive background in qualitative and quantitative data analysis, probability, random variables, and statistical methods, including machine learning. With careful treatment of topics that fill the curricular needs for the course, Probability and Statistics for Computer Science features: * A treatment of random variables and expectations dealing primarily with the discrete case. * A practical treatment of simulation, showing how many interesting probabilities and expectations can be extracted, with particular emphasis on Markov chains. * A clear but crisp account of simple point inference strategies (maximum likelihood; Bayesian inference) in simple contexts. This is extended to cover some confidence intervals, samples and populations for random sampling with replacement, and the simplest hypothesis testing. * A chapter dealing with classification, explaining why it's useful; how to train SVM classifiers with stochastic gradient descent; and how to use implementations of more advanced methods such as random forests and nearest neighbors. * A chapter dealing with regression, explaining how to set up, use and understand linear regression and nearest neighbors regression in practical problems. * A chapter dealing with principal components analysis, developing intuition carefully, and including numerous practical examples. There is a brief description of multivariate scaling via principal coordinate analysis. * A chapter dealing with clustering via agglomerative methods and k-means, showing how to build vector quantized features for complex signals. Illustrated throughout, each main chapter includes many worked examples and other pedagogical elements such as boxed Procedures, Definitions, Useful Facts, and Remember This (short tips). Problems and Programming Exercises are at the end of each chapter, with a summary of what the reader should know. Instructor resources include a full set of model solutions for all problems, and an Instructor's Manual with accompanying presentation slides.

This book depicts a wide range of situations in which there exist finite form representations for the Meijer G and the Fox H functions. Accordingly, it will be of interest to researchers and graduate students who, when implementing likelihood ratio tests in multivariate analysis, would like to know if there exists an explicit manageable finite form for the distribution of the test statistics. In these cases, both the exact quantiles and the exact p-values of the likelihood ratio tests can be computed quickly and efficiently. The test statistics in question range from common ones, such as those used to test e.g. the equality of means or the independence of blocks of variables in real or complex normally distributed random vectors; to far more elaborate tests on the structure of covariance matrices and equality of mean vectors. The book also provides computational modules in Mathematica (R), MAXIMA and R, which allow readers to easily implement, plot and compute the distributions of any of these statistics, or any other statistics that fit into the general paradigm described here.

Addressing a broad range of big data analytics in cross-disciplinary applications, this essential handbook focuses on the statistical prospects offered by recent developments in this field. To do so, it covers statistical methods for high-dimensional problems, algorithmic designs, computation tools, analysis flows and the software-hardware co-designs that are needed to support insightful discoveries from big data. The book is primarily intended for statisticians, computer experts, engineers and application developers interested in using big data analytics with statistics. Readers should have a solid background in statistics and computer science.

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 volume presents a selection of research papers on various topics at the interface of statistics and computer science. Emphasis is put on the practical applications of statistical methods in various disciplines, using machine learning and other computational methods. The book covers fields of research including the design of experiments, computational statistics, music data analysis, statistical process control, biometrics, industrial engineering, and econometrics. Gathering innovative, high-quality and scientifically relevant contributions, the volume was published in honor of Claus Weihs, Professor of Computational Statistics at TU Dortmund University, on the occasion of his 66th birthday.

This book is the modern first treatment of experimental designs, providing a comprehensive introduction to the interrelationship between the theory of optimal designs and the theory of cubature formulas in numerical analysis. It also offers original new ideas for constructing optimal designs. The book opens with some basics on reproducing kernels, and builds up to more advanced topics, including bounds for the number of cubature formula points, equivalence theorems for statistical optimalities, and the Sobolev Theorem for the cubature formula. It concludes with a functional analytic generalization of the above classical results. Although it is intended for readers who are interested in recent advances in the construction theory of optimal experimental designs, the book is also useful for researchers seeking rich interactions between optimal experimental designs and various mathematical subjects such as spherical designs in combinatorics and cubature formulas in numerical analysis, both closely related to embeddings of classical finite-dimensional Banach spaces in functional analysis and Hilbert identities in elementary number theory. Moreover, it provides a novel communication platform for "design theorists" in a wide variety of research fields.

This book expands the foundations of general systems theory to enable progress beyond the rich heuristic practices available today. It establishes a foundational framework for the development of scientific transdisciplinary systems principles and shows how these can amplify the potential of individuals and teams working in multi-, inter- and transdisciplinary contexts or striving to translate their progress across disciplinary boundaries. Three general scientific systems principles are presented, and their relevance to the design, analysis, management and transformation of systems is explored. Applying lessons from the history and philosophy science, this book disambiguates key concepts of general systemology, clarifies the role of general systemology within the field of systemology, and explains how general systemology supports other forms of transdisciplinarity. These insights are used to develop new perspectives, strategies and tools for addressing long-standing challenges to the advancement and transdisciplinary application of general insights into the nature of complex systems.The material presented in this book includes comprehensive models of the structure of systemology as a disciplinary field, the structure and significance of the general systems worldview, and the role of general systemology as the heart of systems science, systems engineering and systems practice. It explains what a fully-fledged general theory of systems would look like, what its potential is, what routes are available to us to develop it further, and how to leverage the knowledge we have attained so far. Many examples and analogies show how general systemology has the potential to enable scientific discovery, insightful theory building, and practical innovation in all the disciplines as they study, design, nurture or transform complex systems. This book is essential reading for anyone wishing to master the concepts, terminology, models and strategies needed to make effective use of current general systems knowledge and to engage in the further development of the philosophy, science, and practice of general systemology.

This book explores inductive inference using the minimum message length (MML) principle, a Bayesian method which is a realisation of Ockham's Razor based on information theory. Accompanied by a library of software, the book can assist an applications programmer, student or researcher in the fields of data analysis and machine learning to write computer programs based upon this principle. MML inference has been around for 50 years and yet only one highly technical book has been written about the subject. The majority of research in the field has been backed by specialised one-off programs but this book includes a library of general MML-based software, in Java. The Java source code is available under the GNU GPL open-source license. The software library is documented using Javadoc which produces extensive cross referenced HTML manual pages. Every probability distribution and statistical model that is described in the book is implemented and documented in the software library. The library may contain a component that directly solves a reader's inference problem, or contain components that can be put together to solve the problem, or provide a standard interface under which a new component can be written to solve the problem. This book will be of interest to application developers in the fields of machine learning and statistics as well as academics, postdocs, programmers and data scientists. It could also be used by third year or fourth year undergraduate or postgraduate students.

Make your bookkeeping workflow smoother and faster with QuickBooks. With this Missing Manual - the Official Intuit Guide to QuickBooks 2014 - you'll be in control. You get step-by-step instructions on how and when to use specific features, along with basic accounting advice to guide you through the learning process. The important stuff you need to know: Get started. Set up your accounts, customers, jobs, and invoice items quickly. Follow the money. Track everything from billable time and expenses to income and profit. Keep your company financially fit. Examine budgets and actual spending, income, inventory, assets, and liabilities. Spend less time on bookkeeping. Use QuickBooks to create and reuse bills, invoices, sales receipts, and timesheets. Find key info fast. Rely on QuickBooks' Search and Find features, as well as the Vendor, Customer, Inventory, and Employee Centers. Exchange data with other programs. Move data between QuickBooks, Microsoft Office, and other programs.

Die Grenzen zwischen Sach- und Dienstleistung verschwimmen zunehmend - Produkte sind in der Regel hybrid. Sie sind als kundenorientierte Problemloesungen zu interpretieren, die durch das Schnuren von Leistungsbundeln aus Sach- und Dienstleistungskomponenten entstehen. UEber die Wettbewerbsvorteile und den oekonomischen Nutzen von hybriden Produkten herrscht weitgehend Einigkeit. Dennoch existieren kaum Ansatze zur integrierten Entwicklung von Sach- und Dienstleistungen. Die Tatsache, dass der wirtschaftliche Erfolg eines Leistungsbundels massgeblich von dessen Konzeption und kundenindividueller Gestaltung abhangt, wird damit vernachlassigt. In diesem Band werden neue Methoden zur Gestaltung hybrider Produkte vorgestellt. Dabei werden sowohl aktuelle Problemstellungen und Loesungsansatze als auch zukunftige Entwicklungsperspektiven betrachtet. Die einzelnen Kapitel fokussieren einerseits die Produktion und den Absatz hybrider Produkte und andererseits Informationssysteme, welche die Produktion und den Absatz hybrider Produkte unterstutzen. Es wird dem Grundgedanken gefolgt, dass die Erfullung einer Kundenanforderung nicht von vorneherein entweder an eine Sach- oder eine Dienstleistungskomponente geknupft ist - diese Zuordnung soll sich erst wahrend des Entwicklungsprozesses eines hybriden Produkts ergeben. Als "roter Faden" dient ein durchgangiges Fallbeispiel aus der technischen Gebrauchsguterbranche, bei dem die Nutzung mobiler Endgerate zu Verbesserungen in der Erbringung technischer Kundendienstleistungen fuhrt.

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This book provides practical applications of doubly classified models by using R syntax to generate the models. It also presents these models in symbolic tables so as to cater to those who are not mathematically inclined, while numerous examples throughout the book illustrate the concepts and their applications. For those who are not aware of this modeling approach, it serves as a good starting point to acquire a basic understanding of doubly classified models. It is also a valuable resource for academics, postgraduate students, undergraduates, data analysts and researchers who are interested in examining square contingency tables.

This volume features selected contributions on a variety of topics related to linear statistical inference. The peer-reviewed papers from the International Conference on Trends and Perspectives in Linear Statistical Inference (LinStat 2016) held in Istanbul, Turkey, 22-25 August 2016, cover topics in both theoretical and applied statistics, such as linear models, high-dimensional statistics, computational statistics, the design of experiments, and multivariate analysis. The book is intended for statisticians, Ph.D. students, and professionals who are interested in statistical inference.

This book provides state-of-the-art and interdisciplinary topics on solving matrix eigenvalue problems, particularly by using recent petascale and upcoming post-petascale supercomputers. It gathers selected topics presented at the International Workshops on Eigenvalue Problems: Algorithms; Software and Applications, in Petascale Computing (EPASA2014 and EPASA2015), which brought together leading researchers working on the numerical solution of matrix eigenvalue problems to discuss and exchange ideas - and in so doing helped to create a community for researchers in eigenvalue problems. The topics presented in the book, including novel numerical algorithms, high-performance implementation techniques, software developments and sample applications, will contribute to various fields that involve solving large-scale eigenvalue problems.

Combining theoretical and practical aspects of topology, this book provides a comprehensive and self-contained introduction to topological methods for the analysis and visualization of scientific data. Theoretical concepts are presented in a painstaking but intuitive manner, with numerous high-quality color illustrations. Key algorithms for the computation and simplification of topological data representations are described in detail, and their application is carefully demonstrated in a chapter dedicated to concrete use cases. With its fine balance between theory and practice, "Topological Data Analysis for Scientific Visualization" constitutes an appealing introduction to the increasingly important topic of topological data analysis for lecturers, students and researchers.

This book discusses the latest advances in algorithms for symbolic summation, factorization, symbolic-numeric linear algebra and linear functional equations. It presents a collection of papers on original research topics from the Waterloo Workshop on Computer Algebra (WWCA-2016), a satellite workshop of the International Symposium on Symbolic and Algebraic Computation (ISSAC'2016), which was held at Wilfrid Laurier University (Waterloo, Ontario, Canada) on July 23-24, 2016. This workshop and the resulting book celebrate the 70th birthday of Sergei Abramov (Dorodnicyn Computing Centre of the Russian Academy of Sciences, Moscow), whose highly regarded and inspirational contributions to symbolic methods have become a crucial benchmark of computer algebra and have been broadly adopted by many Computer Algebra systems.

This second edition is an intensively revised and updated version of the book MATLAB (R) and Design Recipes for Earth Sciences. It aims to introduce students to the typical course followed by a data analysis project in earth sciences. A project usually involves searching relevant literature, reviewing and ranking published books and journal articles, extracting relevant information from the literature in the form of text, data, or graphs, searching and processing the relevant original data using MATLAB, and compiling and presenting the results as posters, abstracts, and oral presentations using graphics design software. The text of this book includes numerous examples on the use of internet resources, on the visualization of data with MATLAB, and on preparing scientific presentations. As with the book MATLAB Recipes for Earth Sciences-4rd Edition (2015), which demonstrates the use of statistical and numerical methods on earth science data, this book uses state-of-the art software packages, including MATLAB and the Adobe Creative Suite, to process and present geoscientific information collected during the course of an earth science project. The book's supplementary electronic material (available online through the publisher's website) includes color versions of all figures, recipes with all the MATLAB commands featured in the book, the example data, exported MATLAB graphics, and screenshots of the most important steps involved in processing the graphics.

This book introduces readers to statistical methodologies used to analyze doubly truncated data. The first book exclusively dedicated to the topic, it provides likelihood-based methods, Bayesian methods, non-parametric methods, and linear regression methods. These procedures can be used to effectively analyze continuous data, especially survival data arising in biostatistics and economics. Because truncation is a phenomenon that is often encountered in non-experimental studies, the methods presented here can be applied to many branches of science. The book provides R codes for most of the statistical methods, to help readers analyze their data. Given its scope, the book is ideally suited as a textbook for students of statistics, mathematics, econometrics, and other fields.

This volume constitutes the proceedings of the 11th IFIP WG 8.1 Conference on the Practice of Enterprise Modeling held in October/November 12018 in Vienna, Austria. The conference was created by the International Federation for Information Processing (IFIP) Working Group 8.1 to offer a forum for knowledge transfer and experience sharing between the academic and practitioner communities. The 21 full papers and 5 short papers accepted were carefully reviewed and selected from 64 submissions. They are grouped by the following topics: business process modeling, model derivation; collaboration modeling; reviews and analyses of modeling methods; semantics and reasoning, experience reports; and teaching challenges.

The introduction of digital applications into businesses has revolutionized the way employees and managers carry out their jobs while also benefiting them socially. Smartphone and App Implementations that Improve Productivity looks at the benefits of apps in the workplace and introduces academic perspectives that link prospective advantages with practical commercial examples. The analysis is structured into chapters that include real world application while at the same time critically assess implied benefits of the new app technology and draw out the main findings and conclusions. Tahir M. Nisar brings into focus the emerging role of digital applications and big data in enterprise decision making. Readers will learn how companies can achieve more efficiency and effectiveness in their business operations through new types of organizational design strategies and mechanisms of employee mobility and work-life balance that draw on digital apps.

Innovationen entziehen sich immer deutlicher einer technologisch verkurzten Sichtweise. Angesichts der gestiegenen Dynamik und Komplexitat der Umfeldbedingungen fur Unternehmen kommen der Fruherkennung und dem Monitoring technologischer, wirtschaftlicher, politischer und gesellschaftlicher Entwicklungen immer grossere Bedeutung fur den Innovationserfolg zu. Dies gilt besonders fur dynamische Technologiefelder, wie dem Pervasive Computing. Die fortschreitende Nutzung des Internets, die Einbettung von Elektronikkomponenten in Alltagsgegenstande und der Trend zur standigen Vernetzung ( Always on - Anywhere & Anytime") sind unubersehbar. Die vorliegende Arbeit ermittelt okologische Veranderungspotenziale und geht der Frage nach, wie Nachhaltigkeitsanforderungen bereits fruhzeitig in Innovationsprozesse einbezogen werden konnen. Mit Blick auf diese Aufgabe wurde das Konzept der Integrierten Technologie-Roadmap" entwickelt. Mit der Integrierten Technologie-Roadmap wird es moglich, mehrere Dimensionen zukunftsfahigen Wirtschaftens in dynamischen Technologiefeldern simultan zu betrachten. Sie fragt nach technologischen Beitragen zur Bewaltigung von gesellschaftlichen, okonomischen, politischen und okologischen Herausforderungen und ruckt die Sicht der Anwender in den Mittelpunkt. Beides hilft Unsicherheiten bei Technologieentwicklung, Markteinfuhrung und Geschaftsmodellen zu minimieren und die Richtungssicherheit zu erhohen."

Mit der Globalisierung ruckt die Logistik als Wettbewerbsfaktor fur Produktionsunternehmen zunehmend in den Vordergrund. In dem Band wird erstmals ein ganzheitlicher, sozio-technischer Ansatz fur das Auftragsmanagement in der industriellen Produktion vorgestellt, der die Wechselwirkungen zwischen Systemfunktionen, Nutzern und der Organisation berucksichtigt. Unter Einbeziehung dieser Aspekte wird die Gestaltung und Einfuhrung eines Auftragsmanagement-Systems nachvollziehbar beschrieben und durch zahlreiche Bilder und Praxisbeispiele veranschaulicht."