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Aughey and Frye’s Comparative Veterinary Histology with Clinical Correlates

Small Animal Fracture Repair A Case-Based Approach

Kedi A Docalogue

Food Allergy Molecular and Clinical Practice

Ferret Medicine and Surgery

Learn Audio Electronics with Arduino Practical Audio Circuits with Arduino Control

Learn Audio Electronics with Arduino Practical Audio Circuits with Arduino Control

Learn Audio Electronics with Arduino: Practical Audio Circuits with Arduino Control teaches the reader how to use Arduino to control analogue audio circuits and introduces electronic circuit theory through a series of practical projects including a MIDI drum controller and an Arduino-controlled two-band audio equalizer amplifier. Learn Audio Electronics with Arduino provides all the theoretical knowledge needed to design analyse and build audio circuits for amplification and filtering with additional topics like C programming being introduced in a practical context for Arduino control. The reader will learn how these circuits work and also how to build them allowing them to progress to more advanced audio circuits in the future. Beginning with electrical fundamentals and control systems DC circuit theory is then combined with an introduction to C programming to build Arduino-based systems for audio (tone sequencer) and MIDI (drum controller) output. The second half of the book begins with AC circuit theory to allow analogue audio circuits for amplification and filtering to be analysed simulated and built. These circuits are then combined with Arduino control in the final project – an Arduino-controlled two-band equalizer amplifier. Building on high-school physics and mathematics in an accessible way Learn Audio Electronics with Arduino is suitable for readers of all levels. An ideal tool for those studying audio electronics including as a component within other fields of study such as computer science human-computer interaction acoustics music technology and electronics engineering. | Learn Audio Electronics with Arduino Practical Audio Circuits with Arduino Control

GBP 44.99
1

Speaking with a Purpose

Linear Models with Python

Linear Models with Python

Praise for Linear Models with R: This book is a must-have tool for anyone interested in understanding and applying linear models. The logical ordering of the chapters is well thought out and portrays Faraway’s wealth of experience in teaching and using linear models. … It lays down the material in a logical and intricate manner and makes linear modeling appealing to researchers from virtually all fields of study. Biometrical Journal Throughout it gives plenty of insight … with comments that even the seasoned practitioner will appreciate. Interspersed with R code and the output that it produces one can find many little gems of what I think is sound statistical advice well epitomized with the examples chosen…I read it with delight and think that the same will be true with anyone who is engaged in the use or teaching of linear models. Journal of the Royal Statistical Society Like its widely praised best-selling companion version Linear Models with R this book replaces R with Python to seamlessly give a coherent exposition of the practice of linear modeling. Linear Models with Python offers up-to-date insight on essential data analysis topics from estimation inference and prediction to missing data factorial models and block designs. Numerous examples illustrate how to apply the different methods using Python. Features: Python is a powerful open source programming language increasingly being used in data science machine learning and computer science. Python and R are similar but R was designed for statistics while Python is multi-talented. This version replaces R with Python to make it accessible to a greater number of users outside of statistics including those from Machine Learning. A reader coming to this book from an ML background will learn new statistical perspectives on learning from data. Topics include Model Selection Shrinkage Experiments with Blocks and Missing Data. Includes an Appendix on Python for beginners. Linear Models with Python explains how to use linear models in physical science engineering social science and business applications. It is ideal as a textbook for linear models or linear regression courses.

GBP 82.99
1

Geocomputation with R

Geocomputation with R

Geocomputation with R is for people who want to analyze visualize and model geographic data with open source software. It is based on R a statistical programming language that has powerful data processing visualization and geospatial capabilities. The book equips you with the knowledge and skills to tackle a wide range of issues manifested in geographic data including those with scientific societal and environmental implications. This book will interest people from many backgrounds especially Geographic Information Systems (GIS) users interested in applying their domain-specific knowledge in a powerful open source language for data science and R users interested in extending their skills to handle spatial data. The book is divided into three parts: (I) Foundations aimed at getting you up-to-speed with geographic data in R (II) extensions which covers advanced techniques and (III) applications to real-world problems. The chapters cover progressively more advanced topics with early chapters providing strong foundations on which the later chapters build. Part I describes the nature of spatial datasets in R and methods for manipulating them. It also covers geographic data import/export and transforming coordinate reference systems. Part II represents methods that build on these foundations. It covers advanced map making (including web mapping) bridges to GIS sharing reproducible code and how to do cross-validation in the presence of spatial autocorrelation. Part III applies the knowledge gained to tackle real-world problems including representing and modeling transport systems finding optimal locations for stores or services and ecological modeling. Exercises at the end of each chapter give you the skills needed to tackle a range of geospatial problems. Solutions for each chapter and supplementary materials providing extended examples are available at https://geocompr. github. io/geocompkg/articles/. Dr. Robin Lovelace is a University Academic Fellow at the University of Leeds where he has taught R for geographic research over many years with a focus on transport systems. Dr. Jakub Nowosad is an Assistant Professor in the Department of Geoinformation at the Adam Mickiewicz University in Poznan where his focus is on the analysis of large datasets to understand environmental processes. Dr. Jannes Muenchow is a Postdoctoral Researcher in the GIScience Department at the University of Jena where he develops and teaches a range of geographic methods with a focus on ecological modeling statistical geocomputing and predictive mapping. All three are active developers and work on a number of R packages including stplanr sabre and RQGIS.

GBP 44.99
1

Early Childhood Intervention Working with Families of Young Children with Special Needs

Early Childhood Intervention Working with Families of Young Children with Special Needs

Early childhood is considered a critical but often vulnerable period in a child’s development where early identification and intervention can be crucial for improving children’s developmental outcomes. Systems and family-centred perspectives are vital to support families and build their capacities to lead normalized lives with improved family quality of life. This book explores the family-centred practices and systems factors which influence families’ experiences raising children with complex needs. It also considers the ways in which professionals can work with families to build and support parent and child competence. Conceptual and practical work from Australia Canada Europe and the United States present descriptions of and implications for different family system frameworks and early-childhood programs. Contributors in this edited volume bring together contemporary information that bridges the research to practice gap in supporting families of young children with disabilities or delays. Chapters include: Early Intervention for Young Children with Developmental Delays: Contributions of the Developmental Systems Approach Family Composition and Family Needs in Australia: What Makes a Family? Working with Families in Early Childhood Intervention: Family-Centred Practices in an Individualised Funding Landscape Family Systems and Family-Centred Intervention Practices in Portugal and Spain: Iberian Reflections on Early Childhood Intervention This book will attract the attention scholars of Parenting and Families; Child Development and Childcare. | Early Childhood Intervention Working with Families of Young Children with Special Needs

GBP 44.99
1

Charged Particle and Photon Interactions with Matter Chemical Physicochemical and Biological Consequences with Applications

Data Mining with R Learning with Case Studies Second Edition

Data Mining with R Learning with Case Studies Second Edition

Data Mining with R: Learning with Case Studies Second Edition uses practical examples to illustrate the power of R and data mining. Providing an extensive update to the best-selling first edition this new edition is divided into two parts. The first part will feature introductory material including a new chapter that provides an introduction to data mining to complement the already existing introduction to R. The second part includes case studies and the new edition strongly revises the R code of the case studies making it more up-to-date with recent packages that have emerged in R. The book does not assume any prior knowledge about R. Readers who are new to R and data mining should be able to follow the case studies and they are designed to be self-contained so the reader can start anywhere in the document. The book is accompanied by a set of freely available R source files that can be obtained at the book’s web site. These files include all the code used in the case studies and they facilitate the do-it-yourself approach followed in the book. Designed for users of data analysis tools as well as researchers and developers the book should be useful for anyone interested in entering the world of R and data mining. About the AuthorLuís Torgo is an associate professor in the Department of Computer Science at the University of Porto in Portugal. He teaches Data Mining in R in the NYU Stern School of Business’ MS in Business Analytics program. An active researcher in machine learning and data mining for more than 20 years Dr. Torgo is also a researcher in the Laboratory of Artificial Intelligence and Data Analysis (LIAAD) of INESC Porto LA. | Data Mining with R Learning with Case Studies Second Edition

GBP 44.99
1

Telling Stories with Data With Applications in R

Telling Stories with Data With Applications in R

The book equips students with the end-to-end skills needed to do data science. That means gathering cleaning preparing and sharing data then using statistical models to analyse data writing about the results of those models drawing conclusions from them and finally using the cloud to put a model into production all done in a reproducible way. At the moment there are a lot of books that teach data science but most of them assume that you already have the data. This book fills that gap by detailing how to go about gathering datasets cleaning and preparing them before analysing them. There are also a lot of books that teach statistical modelling but few of them teach how to communicate the results of the models and how they help us learn about the world. Very few data science textbooks cover ethics and most of those that do have a token ethics chapter. Finally reproducibility is not often emphasised in data science books. This book is based around a straight-forward workflow conducted in an ethical and reproducible way: gather data prepare data analyse data and communicate those findings. This book will achieve the goals by working through extensive case studies in terms of gathering and preparing data and integrating ethics throughout. It is specifically designed around teaching how to write about the data and models so aspects such as writing are explicitly covered. And finally the use of GitHub and the open-source statistical language R are built in throughout the book. Key Features: Extensive code examples. Ethics integrated throughout. Reproducibility integrated throughout. Focus on data gathering messy data and cleaning data. Extensive formative assessment throughout. | Telling Stories with Data With Applications in R

GBP 74.99
1

Creative Storytelling with Children at Risk

Social Work Practice with Children

Designing with Creo Parametric 8.0

Designing with Creo Parametric 8.0

Designing with Creo Parametric 8. 0 provides the high school student college student or practicing engineer with a basic introduction to engineering design while learning the 3D modeling Computer-Aided Design software called Creo Parametric from PTC. The topics are presented in tutorial format with exercises at the end of each chapter to reinforce the concepts covered. It is richly illustrated with computer screen shots throughout. Above all this text is designed to help you expand your creative talents and communicate your ideas through the graphics language. Because it is easier to learn new information if you have a reason for learning it this textbook discusses design intent while you are learning Creo Parametric. At the same time it shows how knowledge covered in basic engineering courses such as statics dynamics strength of materials and design of mechanical components can be applied to design. You do not need an engineering degree nor be working toward a degree in engineering to use this textbook. Although FEA (Finite Element Analysis) is used in this textbook its theory is not covered. The first two chapters of this book describe the design process. The meat of this text learning the basic Creo Parametric software is found in Chapters three through six. Chapters seven eight and 12 deal with dimensioning and tolerancing an engineering part. Chapters nine and ten deal with assemblies and assembly drawings. Chapter 11 deals with family tables used when similar parts are to be designed or used. Chapter 13 is an introduction to Creo Simulate and FEA.

GBP 62.00
1

Designing with Creo Parametric 7.0

Designing with Creo Parametric 7.0

Designing with Creo Parametric 7. 0 provides the high school student college student or practicing engineer with a basic introduction to engineering design while learning the 3D modeling Computer-Aided Design software called Creo Parametric from PTC. The topics are presented in tutorial format with exercises at the end of each chapter to reinforce the concepts covered. It is richly illustrated with computer screen shots throughout. Above all this text is designed to help you expand your creative talents and communicate your ideas through the graphics language. Because it is easier to learn new information if you have a reason for learning it this textbook discusses design intent while you are learning Creo Parametric. At the same time it shows how knowledge covered in basic engineering courses such as statics dynamics strength of materials and design of mechanical components can be applied to design. You do not need an engineering degree nor be working toward a degree in engineering to use this textbook. Although FEA (Finite Element Analysis) is used in this textbook its theory is not covered. The first two chapters of this book describe the design process. The meat of this text learning the basic Creo Parametric software is found in Chapters three through six. Chapters seven eight and 12 deal with dimensioning and tolerancing an engineering part. Chapters nine and ten deal with assemblies and assembly drawings. Chapter 11 deals with family tables used when similar parts are to be designed or used. Chapter 13 is an introduction to Creo Simulate and FEA.

GBP 52.00
1

Designing with Creo Parametric 9.0

Designing with Creo Parametric 9.0

Designing with Creo Parametric 9. 0 provides the high school student college student or practicing engineer with a basic introduction to engineering design while learning the 3D modeling Computer-Aided Design software called Creo Parametric from PTC. The topics are presented in tutorial format with exercises at the end of each chapter to reinforce the concepts covered. It is richly illustrated with computer screen shots throughout. Above all this text is designed to help you expand your creative talents and communicate your ideas through the graphics language. Because it is easier to learn new information if you have a reason for learning it this textbook discusses design intent while you are learning Creo Parametric. At the same time it shows how knowledge covered in basic engineering courses such as statics dynamics strength of materials and design of mechanical components can be applied to design. You do not need an engineering degree nor be working toward a degree in engineering to use this textbook. Although FEA (Finite Element Analysis) is used in this textbook its theory is not covered. The first two chapters of this book describe the design process. The meat of this text learning the basic Creo Parametric software is found in Chapters three through six. Chapters seven eight and 12 deal with dimensioning and tolerancing an engineering part. Chapters nine and ten deal with assemblies and assembly drawings. Chapter 11 deals with family tables used when similar parts are to be designed or used. Chapter 13 is an introduction to Creo Simulate and FEA.

GBP 66.00
1

Green's Functions with Applications

Green's Functions with Applications

Since publication of the first edition over a decade ago Green’s Functions with Applications has provided applied scientists and engineers with a systematic approach to the various methods available for deriving a Green’s function. This fully revised Second Edition retains the same purpose but has been meticulously updated to reflect the current state of the art. The book opens with necessary background information: a new chapter on the historical development of the Green’s function coverage of the Fourier and Laplace transforms a discussion of the classical special functions of Bessel functions and Legendre polynomials and a review of the Dirac delta function. The text then presents Green’s functions for each class of differential equation (ordinary differential wave heat and Helmholtz equations) according to the number of spatial dimensions and the geometry of the domain. Detailing step-by-step methods for finding and computing Green’s functions each chapter contains a special section devoted to topics where Green’s functions particularly are useful. For example in the case of the wave equation Green’s functions are beneficial in describing diffraction and waves. To aid readers in developing practical skills for finding Green’s functions worked examples problem sets and illustrations from acoustics applied mechanics antennas and the stability of fluids and plasmas are featured throughout the text. A new chapter on numerical methods closes the book. Included solutions and hundreds of references to the literature on the construction and use of Green's functions make Green’s Functions with Applications Second Edition a valuable sourcebook for practitioners as well as graduate students in the sciences and engineering. | Green's Functions with Applications

GBP 62.99
1

Surveying with Geomatics and R

Microcontroller Engineering with MSP432 Fundamentals and Applications

Speaking with a Purpose

Population Genomics with R

Population Genomics with R

Population Genomics With R presents a multidisciplinary approach to the analysis of population genomics. The methods treated cover a large number of topics from traditional population genetics to large-scale genomics with high-throughput sequencing data. Several dozen R packages are examined and integrated to provide a coherent software environment with a wide range of computational statistical and graphical tools. Small examples are used to illustrate the basics and published data are used as case studies. Readers are expected to have a basic knowledge of biology genetics and statistical inference methods. Graduate students and post-doctorate researchers will find resources to analyze their population genetic and genomic data as well as help them design new studies. The first four chapters review the basics of population genomics data acquisition and the use of R to store and manipulate genomic data. Chapter 5 treats the exploration of genomic data an important issue when analysing large data sets. The other five chapters cover linkage disequilibrium population genomic structure geographical structure past demographic events and natural selection. These chapters include supervised and unsupervised methods admixture analysis an in-depth treatment of multivariate methods and advice on how to handle GIS data. The analysis of natural selection a traditional issue in evolutionary biology has known a revival with modern population genomic data. All chapters include exercises. Supplemental materials are available on-line (http://ape-package. ird. fr/PGR. html).

GBP 48.99
1

Stochastic Processes with R An Introduction

Computational Methods for Numerical Analysis with R