математика (страница 43)

Автор: Stefan Rother

Migration geht alle an: Migration ist ein globales Ph?nomen, Migrationspolitik wird aber oft nur im nationalen Kontext gedacht und gemacht. Dr. Uwe Hunger und Dr. Stefan Rother beleuchten die aktuellen Migrationsbewegungen, erkl?ren die Ursachen von Arbeitsmigration und Flucht und zeigen, wie auf nationalstaatlicher und supranationaler Ebene mit Migration umgegangen wird. Kompakte und zugleich umfassende Einf?hrung f?r Studierende und alle, die sich f?r Migration und Migrationspolitik interessieren. Mit vielen Beispielen aus dem eigenen Alltag oder den Medien Mit Infoboxen, Grafiken und Lernkontrollfragen

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Автор: Randolf Schrank

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Автор: Guillermo Sampallo

Si quiere disponer de las herramientas b?sicas para construir sus propios dispositivos, preste atenci?n a este libro. Le permitir? de un modo pr?ctico adentrarse en el mundo del Internet de las cosas (IoT), tener nociones sobre los circuitos electr?nicos y aprender c?mo estos se integran en la programaci?n de microcontroladores.
A lo largo del libro se muestra c?mo utilizar los componentes y, de manera progresiva, se avanza en el desarrollo del software que acompa?a a cada uno de los circuitos.
o Experimentar? con los componentes electr?nicos o Programar? el chip ESP8266 para conectarse a Internet o Utilizar? los GPIO del ESP8266 a distancia con su smartphone o Interactuar? con servidores en la nube o Crear? ecosistemas de dispositivos que interact?an con un fin com?n o Recibir? notificaciones en su smartphone provenientes del ESP8266
No se quede atr?s: gracias a las experiencias paso a paso y las fotos reales del libro, construir? dispositivos ?tiles y dominar? sin problemas el Internet de las cosas.

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Автор: Giorgio Celant

This book is the first of a series which focuses on the interpolation and extrapolation of optimal designs, an area with significant applications in engineering, physics, chemistry and most experimental fields. In this volume, the authors emphasize the importance of problems associated with the construction of design. After a brief introduction on how the theory of optimal designs meets the theory of the uniform approximation of functions, the authors introduce the basic elements to design planning and link the statistical theory of optimal design and the theory of the uniform approximation of functions. The appendices provide the reader with material to accompany the proofs discussed throughout the book.

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Автор: Ernesto Ortega Pacific

Esta analiza la adaptaci?n de los lentes de contacto r?gidos, a partir de la pr?ctica desarrollada por el autor como profesional en la atenci?n de pacientes, en la docencia y por medio de la investigaci?n. El primer cap?tulo trata sobre la adaptaci?n de lentes de contacto r?gidos en casos convencionales: hipermetrop?as, miop?as y astigmatismo, en ausencia de ectasias corneales y otro tipo de irregularidades que, en estos tiempos, obligan a apoyarse en otras tecnolog?as como la topograf?a corneal computarizada. El segundo est? enfocado en la comprensi?n e interpretaci?n de la topograf?a corneal. Se ofrecen algunos conceptos b?sicos para que un principiante, sin mayor conocimiento en la tem?tica, pueda utilizar de modo adecuado esta importante herramienta, b?sica para adaptaciones de lentes especiales. El tercer cap?tulo presenta algunos aspectos de las dos investigaciones dirigidas y desarrolladas por el autor, relacionados con la adaptaci?n de lentes de contacto r?gidos, apoy?ndose en la interpretaci?n del mapa topogr?fico. La primera trata sobre la identificaci?n del tipo de queratocono, analizando el tama?o de la ectasia, para seleccionar, de acuerdo con esta, el dise?o de la curva base y el di?metro. La segunda, la selecci?n de los par?metros principales de adaptaci?n de lentes r?gidos de curva base esf?rica para pacientes con c?rneas irregulares posteriores a cirug?a refractiva de tipo l?ser.

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Автор: ngel Berna Prats

Introducci? a l'enginyeria dels reactors qu?mics' es una aproximaci?n al estudio de los reactores, hecha con el rigor que caracteriza a los textos cientificot?cnicos y con la claridad expositiva propia de un manual docente. No s?lo aborda el an?lisis y el dise?o de los reactores, sino tambi?n aspectos menos tratados en el corpus bibliogr?fico, como la seguridad, los cambios de escala y el estudio de los reactores poco convencionales. Cada cap?tulo se complementa con problemas resueltos. Una obra indispensable tanto para los estudiantes de Ingenier?a Qu?mica, como de otras disciplinas que en alg?n momento se aproximan al conocimiento de los reactores.

Серия: Educaci?. S?rie Materials

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Автор: H?ctor Jorquera Gonz?lez

Este libro presenta a estudiantes universitarios una visi?n moderna de la contaminaci?n atmosf?rica, incluyendo aspectos b?sicos de ciencias de la Ingenier?­a y aplicados. Tambi?n se espera que la obra sirva de apoyo a profesionales de distintas disciplinas interesados en los distintos aspectos del problema. Cada cap?­tulo incluye problemas resueltos y propuestos, que incluyen datos reales y piden respuestas concretas. La parte final aborda como caso de estudio la zona de Temuco-Padre Las Casas, mostrando c?mo aplicar la metodolog?­a presentada en el texto para obtener resultados cuantitativos.

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Автор: Ang?lica Chappe

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Автор: Erik Cuevas Jim?nez

El Machine Learning representa una herramienta importante para la exploraci?n y la extracci?n de conocimiento. Su principal objetivo es construir modelos que permitan describir posibles patrones estructurales en la informaci?n a partir de los datos, con el objetivo de tomar decisiones o hacer predicciones.
En la ?ltima d?cada, el n?mero de usuarios de Machine Learning ha crecido de forma espectacular, pero muchos han presentado grandes dificultades a la hora de generar un plan adecuado que les permita pasar de los conceptos fundamentales a la soluci?n de problemas en sus ?reas de inter?s. El objetivo de este libro es brindar una visi?n particular de los principales m?todos de Machine Learning y de su implementaci?n, es decir, proveer de los principales conceptos en los que se basan estos m?todos y aplicarlos a problemas t?picos del procesamiento de datos.
El libro se fundamenta en MATLAB, el cual es considerado hoy en d?a como un est?ndar en la programaci?n cient?fica e industrial. MATLAB contiene, dentro de sus funciones, poderosos m?todos num?ricos que pueden ser adaptados a aplicaciones particulares. Bajo estas condiciones, el usuario puede estar m?s concentrado en la estructura de su aplicaci?n que en la programaci?n misma.
Asimismo, el libro es el resultado de un desmantelamiento completo del plan de estudios est?ndar del Machine Learning en sus componentes m?s fundamentales, as? como de un reensamblaje de esas piezas, cuidadosamente pulidas y organizadas. Contiene descripciones intuitivas y, a su vez, rigurosas de los conceptos imprescindibles para analizar informaci?n a partir de datos. Todo esto deviene en una lectura que le permitir?:
–Entender los principales conceptos en los que se basa el Machine Learning. –Implementar los m?todos de Machine Learning. –Usar los diferentes recursos online que incluyen c?digo fuente y bases de datos. –Comprender las principales t?cnicas de programaci?n con MATLAB orientadas a la implementaci?n de aplicaciones de Machine Learning.
Sin importar si tiene poca o mucha experiencia en programaci?n, con este libro obtendr? las habilidades te?ricas y pr?cticas para emplear el Machine Learning en su totalidad. H?gase con su ejemplar y descubra los detalles estructurales de la informaci?n de sus propios proyectos para predecir y manipular con precisi?n su comportamiento futuro.

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Автор: Carlos Andr?s Echeverry Restrepo

"En este cat?logo se presenta la informaci?n relativa a los proyectos nanciados por la Ponticia Universidad Javeriana Cali entre 2014-2018, para el caso de los grupos de investigaci?n de la Facultad de Humanidades y Ciencias Sociales. Durante el periodo se?alado, se han llevado a cabo dos mediciones Colciencias, as? como la promoci?n y puesta en marcha de los ejes estrat?gicos considerados por la universidad para clasicar los procesos realizados por los investigadores; este documento ofrece informaci?n para las interpretaciones que pudiesen realizarse sobre el modo en que la facultad ha dimensionado la experiencia de la investigaci?n. La unidad de an?lisis privilegiada en este documento, han sido los proyectos presentes en los archivos de la Ocina de Investigaci?n. Adicionalmente, se han considerado documentos provenientes de la coordinaci?n de investigaci?n de la facultad, as? como los complementos ofrecidos por los investigadores. El proceso de validaci?n de los datos se hizo considerando las expectativas de los grupos de investigaci?n, de cara a la realizaci?n de sus trayectorias."

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Автор: Wu Shin-Tson

Presents readers with the basic science, technology, and applications for every type of adaptive lens An adaptive lens is a lens whose shape has been changed to a different focal length by an external stimulus such as pressure, electric field, magnetic field, or temperature. Introduction to Adaptive Lenses is the first book ever to address all of the fundamental operation principles, device characteristics, and potential applications of various types of adaptive lenses. This comprehensive book covers basic material properties, device structures and performance, image processing and zooming, optical communications, and biomedical imaging. Readers will find homework problems and solutions included at the end of each chapter—and based on the described device structures, they will have the knowledge to fabricate adaptive lenses for practical applications or develop new adaptive devices or concepts for advanced investigation. Introduction to Adaptive Lenses includes chapters on: Optical lenses Elastomeric membrane lenses Electro-wetting lenses Dielectrophoretic lenses Mechanical-wetting lenses Liquid crystal lenses This is an important reference for optical engineers, research scientists, graduate students, and undergraduate seniors.

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Автор: Arkady Shemyakin

Presents an introduction to Bayesian statistics, presents an emphasis on Bayesian methods (prior and posterior), Bayes estimation, prediction, MCMC,Bayesian regression, and Bayesian analysis of statistical modelsof dependence, and features a focus on copulas for risk management Introduction to Bayesian Estimation and Copula Models of Dependence emphasizes the applications of Bayesian analysis to copula modeling and equips readers with the tools needed to implement the procedures of Bayesian estimation in copula models of dependence. This book is structured in two parts: the first four chapters serve as a general introduction to Bayesian statistics with a clear emphasis on parametric estimation and the following four chapters stress statistical models of dependence with a focus of copulas. A review of the main concepts is discussed along with the basics of Bayesian statistics including prior information and experimental data, prior and posterior distributions, with an emphasis on Bayesian parametric estimation. The basic mathematical background of both Markov chains and Monte Carlo integration and simulation is also provided. The authors discuss statistical models of dependence with a focus on copulas and present a brief survey of pre-copula dependence models. The main definitions and notations of copula models are summarized followed by discussions of real-world cases that address particular risk management problems. In addition, this book includes: • Practical examples of copulas in use including within the Basel Accord II documents that regulate the world banking system as well as examples of Bayesian methods within current FDA recommendations • Step-by-step procedures of multivariate data analysis and copula modeling, allowing readers to gain insight for their own applied research and studies • Separate reference lists within each chapter and end-of-the-chapter exercises within Chapters 2 through 8 • A companion website containing appendices: data files and demo files in Microsoft® Office Excel®, basic code in R, and selected exercise solutions Introduction to Bayesian Estimation and Copula Models of Dependence is a reference and resource for statisticians who need to learn formal Bayesian analysis as well as professionals within analytical and risk management departments of banks and insurance companies who are involved in quantitative analysis and forecasting. This book can also be used as a textbook for upper-undergraduate and graduate-level courses in Bayesian statistics and analysis. ARKADY SHEMYAKIN, PhD, is Professor in the Department of Mathematics and Director of the Statistics Program at the University of St. Thomas. A member of the American Statistical Association and the International Society for Bayesian Analysis, Dr. Shemyakin's research interests include informationtheory, Bayesian methods of parametric estimation, and copula models in actuarial mathematics, finance, and engineering. ALEXANDER KNIAZEV, PhD, is Associate Professor and Head of the Department of Mathematics at Astrakhan State University in Russia. Dr. Kniazev's research interests include representation theory of Lie algebras and finite groups, mathematical statistics, econometrics, and financial mathematics.

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Автор: Ulrich L. Rohde

Enables readers to apply the fundamentals of differential calculus to solve real-life problems in engineering and the physical sciences Introduction to Differential Calculus fully engages readers by presenting the fundamental theories and methods of differential calculus and then showcasing how the discussed concepts can be applied to real-world problems in engineering and the physical sciences. With its easy-to-follow style and accessible explanations, the book sets a solid foundation before advancing to specific calculus methods, demonstrating the connections between differential calculus theory and its applications. The first five chapters introduce underlying concepts such as algebra, geometry, coordinate geometry, and trigonometry. Subsequent chapters present a broad range of theories, methods, and applications in differential calculus, including: Concepts of function, continuity, and derivative Properties of exponential and logarithmic function Inverse trigonometric functions and their properties Derivatives of higher order Methods to find maximum and minimum values of a function Hyperbolic functions and their properties Readers are equipped with the necessary tools to quickly learn how to understand a broad range of current problems throughout the physical sciences and engineering that can only be solved with calculus. Examples throughout provide practical guidance, and practice problems and exercises allow for further development and fine-tuning of various calculus skills. Introduction to Differential Calculus is an excellent book for upper-undergraduate calculus courses and is also an ideal reference for students and professionals alike who would like to gain a further understanding of the use of calculus to solve problems in a simplified manner.

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Автор: Группа авторов

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Автор: Mohammed Ferdjallah

A unique guide to using both modeling and simulation in digital systems design Digital systems design requires rigorous modeling and simulation analysis that eliminates design risks and potential harm to users. Introduction to Digital Systems: Modeling, Synthesis, and Simulation Using VHDL introduces the application of modeling and synthesis in the effective design of digital systems and explains applicable analytical and computational methods. Through step-by-step explanations and numerous examples, the author equips readers with the tools needed to model, synthesize, and simulate digital principles using Very High Speed Integrated Circuit Hardware Description Language (VHDL) programming. Extensively classroom-tested to ensure a fluid presentation, this book provides a comprehensive overview of the topic by integrating theoretical principles, discrete mathematical models, computer simulations, and basic methods of analysis. Topical coverage includes: Digital systems modeling and simulation Integrated logic Boolean algebra and logic Logic function optimization Number systems Combinational logic VHDL design concepts Sequential and synchronous sequential logic Each chapter begins with learning objectives that outline key concepts that follow, and all discussions conclude with problem sets that allow readers to test their comprehension of the presented material. Throughout the book, VHDL sample codes are used to illustrate circuit design, providing guidance not only on how to learn and master VHDL programming, but also how to model and simulate digital circuits. Introduction to Digital Systems is an excellent book for courses in modeling and simulation, operations research, engineering, and computer science at the upper-undergraduate and graduate levels. The book also serves as a valuable resource for researchers and practitioners in the fields of operations research, mathematical modeling, simulation, electrical engineering, and computer science.

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Автор: Mohammed Ferdjallah

A unique guide to using both modeling and simulation in digital systems design Digital systems design requires rigorous modeling and simulation analysis that eliminates design risks and potential harm to users. Introduction to Digital Systems: Modeling, Synthesis, and Simulation Using VHDL introduces the application of modeling and synthesis in the effective design of digital systems and explains applicable analytical and computational methods. Through step-by-step explanations and numerous examples, the author equips readers with the tools needed to model, synthesize, and simulate digital principles using Very High Speed Integrated Circuit Hardware Description Language (VHDL) programming. Extensively classroom-tested to ensure a fluid presentation, this book provides a comprehensive overview of the topic by integrating theoretical principles, discrete mathematical models, computer simulations, and basic methods of analysis. Topical coverage includes: Digital systems modeling and simulation Integrated logic Boolean algebra and logic Logic function optimization Number systems Combinational logic VHDL design concepts Sequential and synchronous sequential logic Each chapter begins with learning objectives that outline key concepts that follow, and all discussions conclude with problem sets that allow readers to test their comprehension of the presented material. Throughout the book, VHDL sample codes are used to illustrate circuit design, providing guidance not only on how to learn and master VHDL programming, but also how to model and simulate digital circuits. Introduction to Digital Systems is an excellent book for courses in modeling and simulation, operations research, engineering, and computer science at the upper-undergraduate and graduate levels. The book also serves as a valuable resource for researchers and practitioners in the fields of operations research, mathematical modeling, simulation, electrical engineering, and computer science.

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Автор: Douglas C. Montgomery

A comprehensive and current introduction to the fundamentals of regression analysis Introduction to Linear Regression Analysis, 6th Edition is the most comprehensive, fulsome, and current examination of the foundations of linear regression analysis. Fully updated in this new sixth edition, the distinguished authors have included new material on generalized regression techniques and new examples to help the reader understand retain the concepts taught in the book. The new edition focuses on four key areas of improvement over the fifth edition: New exercises and data sets New material on generalized regression techniques The inclusion of JMP software in key areas Carefully condensing the text where possible Introduction to Linear Regression Analysis skillfully blends theory and application in both the conventional and less common uses of regression analysis in today's cutting-edge scientific research. The text equips readers to understand the basic principles needed to apply regression model-building techniques in various fields of study, including engineering, management, and the health sciences.

Исполнители: Karen Kasche

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Автор: Douglas C. Montgomery

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Автор: Frederick Tinsley

A multidisciplinary approach that emphasizes learning by analyzing real-world data sets This book is the result of the authors' hands-on classroom experience and is tailored to reflect how students best learn to analyze linear relationships. The text begins with the introduction of four simple examples of actual data sets. These examples are developed and analyzed throughout the text, and more complicated examples of data sets are introduced along the way. Taking a multidisciplinary approach, the book traces the conclusion of the analyses of data sets taken from geology, biology, economics, psychology, education, sociology, and environmental science. As students learn to analyze the data sets, they master increasingly sophisticated linear modeling techniques, including: * Simple linear models * Multivariate models * Model building * Analysis of variance (ANOVA) * Analysis of covariance (ANCOVA) * Logistic regression * Total least squares The basics of statistical analysis are developed and emphasized, particularly in testing the assumptions and drawing inferences from linear models. Exercises are included at the end of each chapter to test students' skills before moving on to more advanced techniques and models. These exercises are marked to indicate whether calculus, linear algebra, or computer skills are needed. Unlike other texts in the field, the mathematics underlying the models is carefully explained and accessible to students who may not have any background in calculus or linear algebra. Most chapters include an optional final section on linear algebra for students interested in developing a deeper understanding. The many data sets that appear in the text are available on the book's Web site. The MINITAB(r) software program is used to illustrate many of the examples. For students unfamiliar with MINITAB(r), an appendix introduces the key features needed to study linear models. With its multidisciplinary approach and use of real-world data sets that bring the subject alive, this is an excellent introduction to linear models for students in any of the natural or social sciences.

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Автор: Sami Franssila

This accessible text is now fully revised and updated, providing an overview of fabrication technologies and materials needed to realize modern microdevices. It demonstrates how common microfabrication principles can be applied in different applications, to create devices ranging from nanometer probe tips to meter scale solar cells, and a host of microelectronic, mechanical, optical and fluidic devices in between. Latest developments in wafer engineering, patterning, thin films, surface preparation and bonding are covered. This second edition includes: expanded sections on MEMS and microfluidics related fabrication issues new chapters on polymer and glass microprocessing, as well as serial processing techniques 200 completely new and 200 modified figures more coverage of imprinting techniques, process integration and economics of microfabrication 300 homework exercises including conceptual thinking assignments, order of magnitude estimates, standard calculations, and device design and process analysis problems solutions to homework problems on the complementary website, as well as PDF slides of the figures and tables within the book With clear sections separating basic principles from more advanced material, this is a valuable textbook for senior undergraduate and beginning graduate students wanting to understand the fundamentals of microfabrication. The book also serves as a handy desk reference for practicing electrical engineers, materials scientists, chemists and physicists alike. www.wiley.com/go/Franssila_Micro2e

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Автор: Группа авторов

Mixed modelling is one of the most promising and exciting areas of statistical analysis, enabling more powerful interpretation of data through the recognition of random effects. However, many perceive mixed modelling as an intimidating and specialized technique. This book introduces mixed modelling analysis in a simple and straightforward way, allowing the reader to apply the technique confidently in a wide range of situations. Introduction to Mixed Modelling shows that mixed modelling is a natural extension of the more familiar statistical methods of regression analysis and analysis of variance. In doing so, it provides the ideal introduction to this important statistical technique for those engaged in the statistical analysis of data. This essential book: Demonstrates the power of mixed modelling in a wide range of disciplines, including industrial research, social sciences, genetics, clinical research, ecology and agricultural research. Illustrates how the capabilities of regression analysis can be combined with those of ANOVA by the specification of a mixed model. Introduces the criterion of Restricted Maximum Likelihood (REML) for the fitting of a mixed model to data. Presents the application of mixed model analysis to a wide range of situations and explains how to obtain and interpret Best Linear Unbiased Predictors (BLUPs). Features a supplementary website containing solutions to exercises, further examples, and links to the computer software systems GenStat and R. This book provides a comprehensive introduction to mixed modelling, ideal for final year undergraduate students, postgraduate students and professional researchers alike. Readers will come from a wide range of scientific disciplines including statistics, biology, bioinformatics, medicine, agriculture, engineering, economics, and social sciences.

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Автор: Alexander Kukushkin

Summarizes and surveys current LTE technical specifications and implementation options for engineers and newly qualified support staff Concentrating on three mobile communication technologies, GSM, 3G-WCDMA, and LTE—while majorly focusing on Radio Access Network (RAN) technology—this book describes principles of mobile radio technologies that are used in mobile phones and service providers’ infrastructure supporting their operation. It introduces some basic concepts of mobile network engineering used in design and rollout of the mobile network. It then follows up with principles, design constraints, and more advanced insights into radio interface protocol stack, operation, and dimensioning for three major mobile network technologies: Global System Mobile (GSM) and third (3G) and fourth generation (4G) mobile technologies. The concluding sections of the book are concerned with further developments toward next generation of mobile network (5G). Those include some of the major features of 5G such as a New Radio, NG-RAN distributed architecture, and network slicing. The last section describes some key concepts that may bring significant enhancements in future technology and services experienced by customers. Introduction to Mobile Network Engineering: GSM, 3G-WCDMA, LTE and the Road to 5G covers the types of Mobile Network by Multiple Access Scheme; the cellular system; radio propagation; mobile radio channel; radio network planning; EGPRS – GPRS/EDGE; Third Generation Network (3G), UMTS; High Speed Packet data access (HSPA); 4G-Long Term Evolution (LTE) system; LTE-A; and Release 15 for 5G. Focuses on Radio Access Network technologies which empower communications in current and emerging mobile network systems Presents a mix of introductory and advanced reading, with a generalist view on current mobile network technologies Written at a level that enables readers to understand principles of radio network deployment and operation Based on the author’s post-graduate lecture course on Wireless Engineering Fully illustrated with tables, figures, photographs, working examples with problems and solutions, and section summaries highlighting the key features of each technology described Written as a modified and expanded set of lectures on wireless engineering taught by the author, Introduction to Mobile Network Engineering: GSM, 3G-WCDMA, LTE and the Road to 5G is an ideal text for post-graduate and graduate students studying wireless engineering, and industry professionals requiring an introduction or refresher to existing technologies.

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Автор: Группа авторов

Neural engineering is a discipline that uses engineering techniques to understand, repair, replace, enhance, or treat diseases of neural systems. Currently, no book other than this one covers this broad range of topics within motor rehabilitation technology. With a focus on cutting edge technology, it describes state-of-the-art methods within this field, from brain-computer interfaces to spinal and cortical plasticity. Touching on electrode design, signal processing, the neurophysiology of movement, robotics, and much more, this innovative volume collects the latest information for a wide range of readers working in biomedical engineering.

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Автор: Группа авторов

An easy-to-grasp introduction to nonparametric regression This book's straightforward, step-by-step approach provides an excellent introduction to the field for novices of nonparametric regression. Introduction to Nonparametric Regression clearly explains the basic concepts underlying nonparametric regression and features: * Thorough explanations of various techniques, which avoid complex mathematics and excessive abstract theory to help readers intuitively grasp the value of nonparametric regression methods * Statistical techniques accompanied by clear numerical examples that further assist readers in developing and implementing their own solutions * Mathematical equations that are accompanied by a clear explanation of how the equation was derived The first chapter leads with a compelling argument for studying nonparametric regression and sets the stage for more advanced discussions. In addition to covering standard topics, such as kernel and spline methods, the book provides in-depth coverage of the smoothing of histograms, a topic generally not covered in comparable texts. With a learning-by-doing approach, each topical chapter includes thorough S-Plus? examples that allow readers to duplicate the same results described in the chapter. A separate appendix is devoted to the conversion of S-Plus objects to R objects. In addition, each chapter ends with a set of problems that test readers' grasp of key concepts and techniques and also prepares them for more advanced topics. This book is recommended as a textbook for undergraduate and graduate courses in nonparametric regression. Only a basic knowledge of linear algebra and statistics is required. In addition, this is an excellent resource for researchers and engineers in such fields as pattern recognition, speech understanding, and data mining. Practitioners who rely on nonparametric regression for analyzing data in the physical, biological, and social sciences, as well as in finance and economics, will find this an unparalleled resource.

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Автор: Heinz-Otto Kreiss

Introduces both the fundamentals of time dependent differential equations and their numerical solutions Introduction to Numerical Methods for Time Dependent Differential Equations delves into the underlying mathematical theory needed to solve time dependent differential equations numerically. Written as a self-contained introduction, the book is divided into two parts to emphasize both ordinary differential equations (ODEs) and partial differential equations (PDEs). Beginning with ODEs and their approximations, the authors provide a crucial presentation of fundamental notions, such as the theory of scalar equations, finite difference approximations, and the Explicit Euler method. Next, a discussion on higher order approximations, implicit methods, multistep methods, Fourier interpolation, PDEs in one space dimension as well as their related systems is provided. Introduction to Numerical Methods for Time Dependent Differential Equations features: A step-by-step discussion of the procedures needed to prove the stability of difference approximations Multiple exercises throughout with select answers, providing readers with a practical guide to understanding the approximations of differential equations A simplified approach in a one space dimension Analytical theory for difference approximations that is particularly useful to clarify procedures Introduction to Numerical Methods for Time Dependent Differential Equations is an excellent textbook for upper-undergraduate courses in applied mathematics, engineering, and physics as well as a useful reference for physical scientists, engineers, numerical analysts, and mathematical modelers who use numerical experiments to test designs or predict and investigate phenomena from many disciplines.

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Автор: Markos V. Koutras

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Автор: Markos V. Koutras

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Автор: Michael J. Panik

A well-balanced and accessible introduction to the elementary quantitative methods and Microsoft® Office Excel® applications used to guide business decision making Featuring quantitative techniques essential for modeling modern business situations, Introduction to Quantitative Methods in Business: With Applications Using Microsoft® Office Excel® provides guidance to assessing real-world data sets using Excel. The book presents a balanced approach to the mathematical tools and techniques with applications used in the areas of business, finance, economics, marketing, and operations. The authors begin by establishing a solid foundation of basic mathematics and statistics before moving on to more advanced concepts. The first part of the book starts by developing basic quantitative techniques such as arithmetic operations, functions and graphs, and elementary differentiations (rates of change), and integration. After a review of these techniques, the second part details both linear and nonlinear models of business activity. Extensively classroom-tested, Introduction to Quantitative Methods in Business: With Applications Using Microsoft® Office Excel® also includes: Numerous examples and practice problems that emphasize real-world business quantitative techniques and applications Excel-based computer software routines that explore calculations for an assortment of tasks, including graphing, formula usage, solving equations, and data analysis End-of-chapter sections detailing the Excel applications and techniques used to address data and solutions using large data sets A companion website that includes chapter summaries, Excel data sets, sample exams and quizzes, lecture slides, and an Instructors’ Solutions Manual Introduction to Quantitative Methods in Business: With Applications Using Microsoft® Office Excel® is an excellent textbook for undergraduate-level courses on quantitative methods in business, economics, finance, marketing, operations, and statistics. The book is also an ideal reference for readers with little or no quantitative background who require a better understanding of basic mathematical and statistical concepts used in economics and business. Bharat Kolluri, Ph.D., is Professor of Economics in the Department of Economics, Finance, and Insurance at the University of Hartford. A member of the American Economics Association, his research interests include econometrics, business statistics, quantitative decision making, applied macroeconomics, applied microeconomics, and corporate finance. Michael J. Panik, Ph.D., is Professor Emeritus in the Department of Economics, Finance, and Insurance at the University of Hartford. He has served as a consultant to the Connecticut Department of Motor Vehicles as well as to a variety of health care organizations. In addition, Dr. Panik is the author of numerous books, including Growth Curve Modeling: Theory and Applications and Statistical Inference: A Short Course, both published by Wiley. Rao N. Singamsetti, Ph.D., is Associate Professor in the Department of Economics, Finance, and Insurance at the University of Hartford. A member of the American Economics Association, his research interests include the status of war on poverty in the United States since the 1960s and forecasting foreign exchange rates using econometric methods.

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Автор: Michael J. Albers

Guides readers through the quantitative data analysis process including contextualizing data within a research situation, connecting data to the appropriate statistical tests, and drawing valid conclusions Introduction to Quantitative Data Analysis in the Behavioral and Social Sciences presents a clear and accessible introduction to the basics of quantitative data analysis and focuses on how to use statistical tests as a key tool for analyzing research data. The book presents the entire data analysis process as a cyclical, multiphase process and addresses the processes of exploratory analysis, decision-making for performing parametric or nonparametric analysis, and practical significance determination. In addition, the author details how data analysis is used to reveal the underlying patterns and relationships between the variables and connects those trends to the data’s contextual situation. Filling the gap in quantitative data analysis literature, this book teaches the methods and thought processes behind data analysis, rather than how to perform the study itself or how to perform individual statistical tests. With a clear and conversational style, readers are provided with a better understanding of the overall structure and methodology behind performing a data analysis as well as the needed techniques to make informed, meaningful decisions during data analysis. The book features numerous data analysis examples in order to emphasize the decision and thought processes that are best followed, and self-contained sections throughout separate the statistical data analysis from the detailed discussion of the concepts allowing readers to reference a specific section of the book for immediate solutions to problems and/or applications. Introduction to Quantitative Data Analysis in the Behavioral and Social Sciences also features coverage of the following: • The overall methodology and research mind-set for how to approach quantitative data analysis and how to use statistics tests as part of research data analysis • A comprehensive understanding of the data, its connection to a research situation, and the most appropriate statistical tests for the data • Numerous data analysis problems and worked-out examples to illustrate the decision and thought processes that reveal underlying patterns and trends • Detailed examples of the main concepts to aid readers in gaining the needed skills to perform a full analysis of research problems • A conversational tone to effectively introduce readers to the basics of how to perform data analysis as well as make meaningful decisions during data analysis Introduction to Quantitative Data Analysis in the Behavioral and Social Sciences is an ideal textbook for upper-undergraduate and graduate-level research method courses in the behavioral and social sciences, statistics, and engineering. This book is also an appropriate reference for practitioners who require a review of quantitative research methods. Michael J. Albers, Ph.D., is Professor in the Department of English at East Carolina University. His research interests include information design with a focus on answering real-world questions, the presentation of complex information, and human–information interaction. Dr. Albers received his Ph.D. in Technical Communication and Rhetoric from Texas Tech University.

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Автор: Группа авторов

An accessible introduction to real analysis and its connection to elementary calculus Bridging the gap between the development and history of real analysis, Introduction to Real Analysis: An Educational Approach presents a comprehensive introduction to real analysis while also offering a survey of the field. With its balance of historical background, key calculus methods, and hands-on applications, this book provides readers with a solid foundation and fundamental understanding of real analysis. The book begins with an outline of basic calculus, including a close examination of problems illustrating links and potential difficulties. Next, a fluid introduction to real analysis is presented, guiding readers through the basic topology of real numbers, limits, integration, and a series of functions in natural progression. The book moves on to analysis with more rigorous investigations, and the topology of the line is presented along with a discussion of limits and continuity that includes unusual examples in order to direct readers' thinking beyond intuitive reasoning and on to more complex understanding. The dichotomy of pointwise and uniform convergence is then addressed and is followed by differentiation and integration. Riemann-Stieltjes integrals and the Lebesgue measure are also introduced to broaden the presented perspective. The book concludes with a collection of advanced topics that are connected to elementary calculus, such as modeling with logistic functions, numerical quadrature, Fourier series, and special functions. Detailed appendices outline key definitions and theorems in elementary calculus and also present additional proofs, projects, and sets in real analysis. Each chapter references historical sources on real analysis while also providing proof-oriented exercises and examples that facilitate the development of computational skills. In addition, an extensive bibliography provides additional resources on the topic. Introduction to Real Analysis: An Educational Approach is an ideal book for upper- undergraduate and graduate-level real analysis courses in the areas of mathematics and education. It is also a valuable reference for educators in the field of applied mathematics.

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Автор: Andrew Thye Shen Wee

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Автор: Группа авторов

Learn statistical methods quickly and easily with the discovery method With its emphasis on the discovery method, this publication encourages readers to discover solutions on their own rather than simply copy answers or apply a formula by rote. Readers quickly master and learn to apply statistical methods, such as bootstrap, decision trees, t-test, and permutations to better characterize, report, test, and classify their research findings. In addition to traditional methods, specialized methods are covered, allowing readers to select and apply the most effective method for their research, including: * Tests and estimation procedures for one, two, and multiple samples * Model building * Multivariate analysis * Complex experimental design Throughout the text, Microsoft Office Excel(r) is used to illustrate new concepts and assist readers in completing exercises. An Excel Primer is included as an Appendix for readers who need to learn or brush up on their Excel skills. Written in an informal, highly accessible style, this text is an excellent guide to descriptive statistics, estimation, testing hypotheses, and model building. All the pedagogical tools needed to facilitate quick learning are provided: * More than 100 exercises scattered throughout the text stimulate readers' thinking and actively engage them in applying their newfound skills * Companion FTP site provides access to all data sets discussed in the text * An Instructor's Manual is available upon request from the publisher * Dozens of thought-provoking questions in the final chapter assist readers in applying statistics to solve real-life problems * Helpful appendices include an index to Excel and Excel add-in functions This text serves as an excellent introduction to statistics for students in all disciplines. The accessible style and focus on real-life problem solving are perfectly suited to both students and practitioners.

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Автор: Группа авторов

The subject of time series is of considerable interest, especially among researchers in econometrics, engineering, and the natural sciences. As part of the prestigious Wiley Series in Probability and Statistics, this book provides a lucid introduction to the field and, in this new Second Edition, covers the important advances of recent years, including nonstationary models, nonlinear estimation, multivariate models, state space representations, and empirical model identification. New sections have also been added on the Wold decomposition, partial autocorrelation, long memory processes, and the Kalman filter. Major topics include: * Moving average and autoregressive processes * Introduction to Fourier analysis * Spectral theory and filtering * Large sample theory * Estimation of the mean and autocorrelations * Estimation of the spectrum * Parameter estimation * Regression, trend, and seasonality * Unit root and explosive time series To accommodate a wide variety of readers, review material, especially on elementary results in Fourier analysis, large sample statistics, and difference equations, has been included.

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Автор: Phillip Good I

A highly accessible alternative approach to basic statistics Praise for the First Edition: «Certainly one of the most impressive little paperback 200-page introductory statistics books that I will ever see . . . it would make a good nightstand book for every statistician.»—Technometrics Written in a highly accessible style, Introduction to Statistics through Resampling Methods and R, Second Edition guides students in the understanding of descriptive statistics, estimation, hypothesis testing, and model building. The book emphasizes the discovery method, enabling readers to ascertain solutions on their own rather than simply copy answers or apply a formula by rote. The Second Edition utilizes the R programming language to simplify tedious computations, illustrate new concepts, and assist readers in completing exercises. The text facilitates quick learning through the use of: More than 250 exercises—with selected «hints»—scattered throughout to stimulate readers' thinking and to actively engage them in applying their newfound skills An increased focus on why a method is introduced Multiple explanations of basic concepts Real-life applications in a variety of disciplines Dozens of thought-provoking, problem-solving questions in the final chapter to assist readers in applying statistics to real-life applications Introduction to Statistics through Resampling Methods and R, Second Edition is an excellent resource for students and practitioners in the fields of agriculture, astrophysics, bacteriology, biology, botany, business, climatology, clinical trials, economics, education, epidemiology, genetics, geology, growth processes, hospital administration, law, manufacturing, marketing, medicine, mycology, physics, political science, psychology, social welfare, sports, and toxicology who want to master and learn to apply statistical methods.

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Автор: Robert P. Dobrow

An introduction to stochastic processes through the use of R Introduction to Stochastic Processes with R is an accessible and well-balanced presentation of the theory of stochastic processes, with an emphasis on real-world applications of probability theory in the natural and social sciences. The use of simulation, by means of the popular statistical software R, makes theoretical results come alive with practical, hands-on demonstrations. Written by a highly-qualified expert in the field, the author presents numerous examples from a wide array of disciplines, which are used to illustrate concepts and highlight computational and theoretical results. Developing readers’ problem-solving skills and mathematical maturity, Introduction to Stochastic Processes with R features: More than 200 examples and 600 end-of-chapter exercises A tutorial for getting started with R, and appendices that contain review material in probability and matrix algebra Discussions of many timely and stimulating topics including Markov chain Monte Carlo, random walk on graphs, card shuffling, Black–Scholes options pricing, applications in biology and genetics, cryptography, martingales, and stochastic calculus Introductions to mathematics as needed in order to suit readers at many mathematical levels A companion web site that includes relevant data files as well as all R code and scripts used throughout the book Introduction to Stochastic Processes with R is an ideal textbook for an introductory course in stochastic processes. The book is aimed at undergraduate and beginning graduate-level students in the science, technology, engineering, and mathematics disciplines. The book is also an excellent reference for applied mathematicians and statisticians who are interested in a review of the topic.

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Автор: Группа авторов

A unique interdisciplinary foundation for real-world problem solving Stochastic search and optimization techniques are used in a vast number of areas, including aerospace, medicine, transportation, and finance, to name but a few. Whether the goal is refining the design of a missile or aircraft, determining the effectiveness of a new drug, developing the most efficient timing strategies for traffic signals, or making investment decisions in order to increase profits, stochastic algorithms can help researchers and practitioners devise optimal solutions to countless real-world problems. Introduction to Stochastic Search and Optimization: Estimation, Simulation, and Control is a graduate-level introduction to the principles, algorithms, and practical aspects of stochastic optimization, including applications drawn from engineering, statistics, and computer science. The treatment is both rigorous and broadly accessible, distinguishing this text from much of the current literature and providing students, researchers, and practitioners with a strong foundation for the often-daunting task of solving real-world problems. The text covers a broad range of today’s most widely used stochastic algorithms, including: Random search Recursive linear estimation Stochastic approximation Simulated annealing Genetic and evolutionary methods Machine (reinforcement) learning Model selection Simulation-based optimization Markov chain Monte Carlo Optimal experimental design The book includes over 130 examples, Web links to software and data sets, more than 250 exercises for the reader, and an extensive list of references. These features help make the text an invaluable resource for those interested in the theory or practice of stochastic search and optimization.

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Автор: Группа авторов

A complete introduction to the many mathematical tools used to solve practical problems in coding. Mathematicians have been fascinated with the theory of error-correcting codes since the publication of Shannon's classic papers fifty years ago. With the proliferation of communications systems, computers, and digital audio devices that employ error-correcting codes, the theory has taken on practical importance in the solution of coding problems. This solution process requires the use of a wide variety of mathematical tools and an understanding of how to find mathematical techniques to solve applied problems. Introduction to the Theory of Error-Correcting Codes, Third Edition demonstrates this process and prepares students to cope with coding problems. Like its predecessor, which was awarded a three-star rating by the Mathematical Association of America, this updated and expanded edition gives readers a firm grasp of the timeless fundamentals of coding as well as the latest theoretical advances. This new edition features: * A greater emphasis on nonlinear binary codes * An exciting new discussion on the relationship between codes and combinatorial games * Updated and expanded sections on the Vashamov-Gilbert bound, van Lint-Wilson bound, BCH codes, and Reed-Muller codes * Expanded and updated problem sets. Introduction to the Theory of Error-Correcting Codes, Third Edition is the ideal textbook for senior-undergraduate and first-year graduate courses on error-correcting codes in mathematics, computer science, and electrical engineering.

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Автор: Saul Stahl

Praise for the First Edition «Stahl offers the solvability of equations from the historical point of view…one of the best books available to support a one-semester introduction to abstract algebra.» —CHOICE Introductory Modern Algebra: A Historical Approach, Second Edition presents the evolution of algebra and provides readers with the opportunity to view modern algebra as a consistent movement from concrete problems to abstract principles. With a few pertinent excerpts from the writings of some of the greatest mathematicians, the Second Edition uniquely facilitates the understanding of pivotal algebraic ideas. The author provides a clear, precise, and accessible introduction to modern algebra and also helps to develop a more immediate and well-grounded understanding of how equations lead to permutation groups and what those groups can inform us about such diverse items as multivariate functions and the 15-puzzle. Featuring new sections on topics such as group homomorphisms, the RSA algorithm, complex conjugation, the factorization of real polynomials, and the fundamental theorem of algebra, the Second Edition also includes: An in-depth explanation of the principles and practices of modern algebra in terms of the historical development from the Renaissance solution of the cubic equation to Dedekind's ideals Historical discussions integrated with the development of modern and abstract algebra in addition to many new explicit statements of theorems, definitions, and terminology A new appendix on logic and proofs, sets, functions, and equivalence relations Over 1,000 new examples and multi-level exercises at the end of each section and chapter as well as updated chapter summaries Introductory Modern Algebra: A Historical Approach, Second Edition is an excellent textbook for upper-undergraduate courses in modern and abstract algebra.

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Автор: Society Actuaries of

Incorporates the many tools needed for modeling and pricing in finance and insurance Introductory Stochastic Analysis for Finance and Insurance introduces readers to the topics needed to master and use basic stochastic analysis techniques for mathematical finance. The author presents the theories of stochastic processes and stochastic calculus and provides the necessary tools for modeling and pricing in finance and insurance. Practical in focus, the book's emphasis is on application, intuition, and computation, rather than theory. Consequently, the text is of interest to graduate students, researchers, and practitioners interested in these areas. While the text is self-contained, an introductory course in probability theory is beneficial to prospective readers. This book evolved from the author's experience as an instructor and has been thoroughly classroom-tested. Following an introduction, the author sets forth the fundamental information and tools needed by researchers and practitioners working in the financial and insurance industries: * Overview of Probability Theory * Discrete-Time stochastic processes * Continuous-time stochastic processes * Stochastic calculus: basic topics The final two chapters, Stochastic Calculus: Advanced Topics and Applications in Insurance, are devoted to more advanced topics. Readers learn the Feynman-Kac formula, the Girsanov's theorem, and complex barrier hitting times distributions. Finally, readers discover how stochastic analysis and principles are applied in practice through two insurance examples: valuation of equity-linked annuities under a stochastic interest rate environment and calculation of reserves for universal life insurance. Throughout the text, figures and tables are used to help simplify complex theory and pro-cesses. An extensive bibliography opens up additional avenues of research to specialized topics. Ideal for upper-level undergraduate and graduate students, this text is recommended for one-semester courses in stochastic finance and calculus. It is also recommended as a study guide for professionals taking Causality Actuarial Society (CAS) and Society of Actuaries (SOA) actuarial examinations.

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Автор: Fabi?n Jaksic Andrade

Invasiones Biol?gicas en Chile proporciona un marco sint?tico y organizado acerca del fen?meno de las invasiones biol?gicas. Se centra en la experiencia investigativa lograda en pa?­ses sudamericanos y con un fuerte ?nfasis en Chile, pues ambos autores han desarrollado investigaci?n en este t?pico, fundamentalmente en vertebrados terrestres y en plantas vasculares. El texto aborda aspectos te?ricos y conceptuales, as?­ como estudios de casos basados es especies invasivas y los procesos y patrones en que ellas han sido involucradas. Este trabajo contribuye a satisfacer la necesidad de disponer de un texto en el campo de la ecolog?­a de invasiones para una audiencia general hispanoparlante y se establecen las fortalezas y debilidades de varios programas de investigaci?n ejecutados hasta la fecha en nuestro continente. En esto nos anima la convicci?n de estar frente a un fen?meno de car?cter global y de gran inter?s biol?gico.

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Автор: Johann Pirela Morillo

Con los diferentes desarrollos tecnol?gicos actuales, el profesional de la informaci?n se hace fundamental para la sociedad, pues inscribe en ella sus bases productivas y funcionales. De ah? que este libro se haya perfilado como una herramienta de consulta pr?ctica en dos sentidos: tanto para los futuros profesionales como para quellos que sin serlo puedan ver en este un instrumento apropiado en el desarrollo de su propia investigaci?n.

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Автор: Группа авторов

El libro trata sobre diversos temas relacionados con la historia del conocimiento del orden Chiroptera en Ecuador, aspectos ecol?gicos y geogr?ficos de varias especies, con informaci?n relacionada con preferencias de h?bitat, patrones de distribuci?n, fragmentaci?n, dieta y uso de refugios; adem?s de an?lisis de modelamientos geogr?ficos, art?culos conceptuales sobre diversidad y revisiones taxon?micas detalladas. Pero, sin lugar a dudas, el trabajo m?s importante que se ofrece en la presente obra es el presentado por Diego G. Tirira, titulado «Murci?lagos del Ecuador: una referencia geogr?fica, taxon?mica y bibliogr?fica», un compendio actualizado del estado del conocimiento sobre la diversidad, taxonom?a y distribuci?n del orden Chiroptera en el pa?s. Este cat?logo cuenta m?s de 560 referencias bibliogr?ficas que incluyen informaci?n sobre los nombres cient?ficos de cada tax?n, autor y a?o de su descripci?n, historia taxon?mica, subespecies y sin?nimos en caso de tenerlos, distintos nombres con los cuales diferentes trabajos se han referido al tax?n, localidad tipo, distribuci?n global y en el Ecuador y comentarios que aclaran el estado taxon?mico actual y los estudios cient?ficos que sobre estas especies se han realizado en el pa?s. Por estas razones, este trabajo est? llamado a convertirse en una referencia obligada para futuras investigaciones de la fauna de quir?pteros del Ecuador y de la regi?n.

Исполнители: Александр Сидоров

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Автор: Wolfgang Frank

Серия: shortcut

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Автор: Carsten Eilers

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Автор: Philip Kiefer

iPhone – Tipps und Tricks zu iOS 13 Sie behalten auch bei der enormen Bandbreite der iPhone – Funktionen den ?berblick, denn in diesem Buch werden die wichtigen iOS – Funktionen f?r Ihr iPhone auf den Punkt gebracht: Erfolgsautor Philip Kiefer erl?utert kompakt und anschaulich die wesentlichen Funktionen und Apps, die Sie tagt?glich brauchen. Die Neuheiten von iOS 13 werden ebenfalls besprochen: der neue Dunkelmodus, Tastatur mit QuickPath, Optimierungen der Mail-App, bei Erinnerungen und Siri, der neue Fotos Tab und die Fotovorschau, der Geburtstagsmodus, Verbesserungen beim Standortzugriff, die ?berarbeitete Karten-App mit ?PNV in Echtzeit und vieles andere mehr. Aus dem Inhalt: – Alles Wichtige zum neuen iOS 13 – Kommunikation auf dem iPhone – Mit Safari im Web unterwegs – Die besten Tipps rund um Ihre Apps – Tolle Tipps zu Kamera-Features und Fotos-App – Musik und Videos auf dem iPhone – iCloud, iTunes, Datensicherung und Synchronisierung – Tolle Tipps und Tricks zu weiteren Standardfunktionen – iPhone 11, iPhone XR, XS, XS Max und Modellen 8, 8 Plus und X, ab iPhone 5S, iPhone 6, iPhone 7
Der Autor Philip Kiefer wurde 1973 in Friedrichshafen geboren. Er ist seit Ende 2001 als freier Autor t?tig und hat bereits zahlreiche B?cher zu iPhone, Mac & Co. ver?ffentlicht.

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Автор: Mike Cronin

From Norman invaders, religious wars—and the struggle for independence—the fascinating, turbulent history of a tortured nation and its gifted people When Shakespeare referred to England as a «jewel set in a silver sea,» he could just as well have been speaking of Ireland. Not only has its luminous green landscape been the backdrop for bloody Catholic/Protestant conflict and a devastating famine, Ireland's great voices—like Joyce and Yeats—are now indelibly part of world literature. In Irish History For Dummies, readers will not only get a bird's-eye view of key historical events (Ten Turning Points) but, also, a detailed, chapter-by-chapter timeline of Irish history beginning with the first Stone Age farmers to the recent rise and fall of the Celtic tiger economy. In the informal, friendly For Dummies style, the book details historic highs like building an Irish Free State in the 1920s—and devastating lows (including the Troubles in the '60s and '70s), as well as key figures (like MP Charles Parnell and President Eamon de Valera) central to the cause of Irish nationalism. The book also details historic artifacts, offbeat places, and little-known facts key to the life of Ireland past and present. Includes Ten Major Documents—including the Confession of St. Patrick, The Book of Kells, the Proclamation of the Irish Republic, and Ulysses Lists Ten Things the Irish Have Given the World—including Irish coffee, U.S. Presidents, the submarine, shorthand writing, and the hypodermic syringe Details Ten Great Irish Places to Visit—including Cobh, Irish National Stud and Museum, Giants Causeway, and Derry Includes an online cheat sheet that gives readers a robust and expanded quick reference guide to relevant dates and historical figures Includes a Who's Who in Irish History section on dummies.com With a light-hearted touch, this informative guide sheds light on how this ancient land has survived wars, invasions, uprisings, and emigration to forge a unique nation, renowned the world over for its superb literature, music, and indomitable spirit.

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Автор: Helmut Albert

Are the chemical properties of the elements, instead of an electron system, better explainable by a proton-neutron system of the atom? Already Mendelejew and Meyeer saw the atomic mass as causal! Until today there is a contradiction between the views of Dmitri Mendeleev and Lothar Meyer and those of Niels Bohr on the cause of the chemical properties of the elements, which has never been discussed. While Bohr and with him today's science assume that the chemical properties of the elements depend on almost massless electrons of the atomic shell, Dmitri Mendeleev and Lothar Meyer saw it quite differently. In contrast, they postulated that the chemical properties depend on the atomic mass. However, as we know today, the carriers of the atomic mass are not the electrons, but the protons and neutrons. Therefore, the question arises whether there is a proton-neutron system instead of the electron system on which the chemical properties and valences of the elements depend?

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Автор: Mike Chapple

Smarter, faster prep for the SSCP exam (ISC)2 SSCP Systems Security Certified Practitioner Official Practice Tests is the only (ISC)2-endorsed set of questions for the SSCP exam. With SSCP certification, you will meet Department of Defense requirements for entry-level Information Assurance Technical (IAT I) roles, positioning you for a successful career in cyber-security. This book's first seven chapters cover each of the seven domains on the SSCP exam with sixty or more questions per domain, so you can focus your study efforts exactly where you need more review. When you feel well prepared, use the two complete practice exams from Sybex's online interactive learning environment as time trials to assess your readiness to take the exam. Coverage of all exam objectives, including: Access Controls Security Operations and Administration Risk Identification, Monitoring, and Analysis Incident Response and Recovery The SSCP program certifies your ability to implement, monitor, and administer IT secure and compliant IT infrastructure. It's ideal for students pursuing cyber-security degrees as well as those in the field looking to take their careers to the next level.

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Автор: Jochen K. Michels

Es handelt sich um Teil II, Teil I hat die ISBN 978-3-7375-3685-1
Informations-Technik (IT) durchzieht das Unternehmen ?hnlichwie das Nervensystem unseren K?rper. An jedem B?ro-Arbeitsplatz gibt es einen oder mehrere Computer, Bildschirme oder andere IT-Ger?te. Auch die anderen Arbeitspl?tze haben sehr h?ufig eine IT-Anbindung. Unterwegs nutzt man immer mehr mobile IT. Netze der verschiedensten Topologien verbinden diese Ger?te untereinander und mit der zentralen Datenhaltung und Computing Power. Daher l?sst sich die IT oft nicht mehr in einer Abteilung zusammenfassen, Aber einige zentrale Funktionen sind als ein Ganzes zu betrachten, werden an einer Stelle konzentriert, wie auch das Nervensystem ohne sein Zentrum im Gehirn nicht arbeitsf?hig ist. Daher ist der fr?her im engeren Sinne zutreffende Begriff «Betriebs- Abrechnungs-Bogen – BAB des Rechenzentrums» heute weiter zu verstehen, n?mlich die ganze IT-Infrastruktur umfassend, das Rechenzentrum, die Serverfarm, das Speichernetz, die Desktops, Clients, PDAs und alles, was dazwischen die Verbindung schafft.
Wir zeigen hier eine Auswahl der wichtigsten Erkenntnisse, Erfahrungen, Techniken und Resultate von ?ber dreissig Jahren projektorientierter Beratungsarbeit, Moderation von Arbeitskreisen "IT-Dienst-Abrechnung" und Fachkonferenzen «FinDV», vielen Marktpreis-Analysen und Benchmarking-Assignments. Im betrieblichen Alltag ben?tigt der Produktionsfaktor Information eine angemessene betriebswirtschaftliche und finanzielle Begleitung. Dazu soll dieses Buch einen Beitrag leisten.

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Автор: Amy Riolo

Your roadmap to cooking like an Italian your very own home For those of us not lucky enough to have our very own Italian grandmother or have attended culinary school in Italy, Italian Recipes For Dummies is stepping in to fill the gap. Award-winning chef and author Amy Riolo delivers a step-by-step guide to creating authentic Italian dishes, starting from the basics and progressing to more advanced techniques and recipes. You'll discover how to shop for, plan, and cook authentic Italian meals properly. You'll also find guidance on how to incorporate the cultural, nutritional, and historical influences that shape classic Italian cuisine. This book includes: Individual chapters on staples of the Italian pantry: wine, cheese, and olive oil More than 150 authentic Italian recipes with step-by-step instructions Access to a Facebook Page hosted by the author that provides extended resources and up-to-date information on mastering Italian cooking The perfect book for amateur chefs, Italy afficianados, homemakers, and anyone else looking for culinary inspiration, Italian Recipes For Dummies is also an indispensable guide for people seeking healthier ways of shopping, cooking, and eating without giving up amazing flavors and rich foods.

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Автор: Н. Л. Коровкина

Статья посвящена анализу подхода к организации управления ИТ-инфраструктурой сети многофункциональных придорожных комплексов (МПК) с использованием лучших практик ITSM. В результате выполнения данной работы проведен анализ проблем, связанных с отсутствием управления ИТ-инфраструктурой в сети МПК, разработана целевая модель процессов управления ИТ-инфраструктурой и продемонстрированы возможности предлагаемой системы управления по устранению выявленных проблем и снижению рисков.

Серия: Прикладная информатика. Научные статьи

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