Tabla de Contenidos: “…Autodesk Maya 2013 Essentials; Acknowledgments; About the Author; Contents; Introduction; Chapter 1: Understanding the Maya Interface; Exploring Interface Elements; Moving Views and Manipulating Objects; Using Maya Windows and Menus; Setting Preferences; Getting Help; Chapter 2: Creating Your First Animation; Using Good Scene-File Management; Creating and Animating a Bouncing Ball; Refining Movement in the Graph Editor; Using Animation Principles to Improve Your Work; Creating a Playblast of Your Animation; Chapter 3: Modeling with Polygons, Part 1; Understanding Polygons…”

Tabla de Contenidos: “…Controlling the Arduino from the iPad; An Arduino on Your iPad; Adding the Serial Library; Building the User Interface; Integrating the Serial Library; Listening for Messages on the Arduino; Putting It All Together; Going Further; Adding a Log Window; Summary; Chapter 4. Using External Sensors from the iPhone; The LV-MaxSonar-EZ1; Analog Output; Pulse Width Output…”

Tabla de Contenidos: “…Contents; Introduction; Chapter 1: Understanding the Maya Interface; Exploring Interface Elements; Moving Views and Manipulating Objects; Using Maya Windows and Menus; Setting Preferences; Getting Help; Chapter 2: Creating Your First Animation; Using Good Scene-File Management; Creating and Animating a Bouncing Ball; Refining Movement in the Graph Editor; Using Animation Principles to Improve Your Work; Creating a Playblast of Your Animation; Chapter 3: Modeling with Polygons, Part 1; Understanding Polygons; Constructing a Good Model; Getting Started and Using the Main Modeling Tools…”

Tabla de Contenidos: “…Attack and Penetration Testing -- Monitoring and Logging -- Ongoing Refinements -- Architectural Principles -- Resiliency -- Statelessness -- Parallelization -- Latency -- Automated Scaling -- Implement and Integrate Solutions -- Application Integration -- Identity Management -- Cross-Premises Integration -- Data Integration -- Testing -- Operate in the Cloud -- Support -- Management -- Monitoring -- Business Continuity and Disaster Recovery -- Measure Success -- Summary -- Epilogue: Emerging Markets and the Cloud -- Explosive Economic Growth -- The Opportunity: Leapfrogging Legacy Technology -- Case Studies -- Case Study: redBus.in, Riding the Cloud Bus -- Case Study: Infosys, "Cloudvolution" -- Case Study: India Department of Income Tax, e-Governance -- Case Study: Microsoft, Windows Azure Sandbox -- Emerging Market Challenges -- Summary -- Glossary -- Index -- About the Authors…”

Tabla de Contenidos: “…Chapter 14 Encoded Output Delivered as a Bit StreamChapter 15 Live Encoding; Chapter 16 Files and Storage Formats; Chapter 17 Tape Formats; Chapter 18 Commercial Issues, Digital Rights Management, and Licensing; Chapter 19 Network Delivery Mechanisms; Chapter 20 Streaming; Chapter 21 Players and Platforms; Chapter 22 Windows Media; Chapter 23 QuickTime; Chapter 24 Real Networks; Chapter 25 Other Player Alternatives; Chapter 26 Putting Video on the Web; Chapter 27 Digital Television; Chapter 28 Digital Video on the Move; Chapter 29 Building Your Encoding Hardware…”

Tabla de Contenidos: “…Claudia Rosiny: Innovative Kollektivarbeit/Collective Innovation/Un travail collectif novateur/Il lavoro innovativo di un collettivo -- Anne Fournier: Curieuse illusion/Curious Illusion/ Sonderbare Illusion/Curiosa illusione -- Gundega Laivina: Opening the Window -- Andreas Klaeui: Suchbewegungen in verschiedene Richtungen: Gesprach mit Helgard Haug, Stefan Kaegi und Daniel Wetzel/Exploring in Different Directions. …”

Tabla de Contenidos: “…Training a fully connected layer as a convolution layer -- Convolution implementation of sliding window -- Thinking about localization as a regression problem -- Applying regression to other problems -- Combining regression with the sliding window -- Detecting objects -- Regions of the convolutional neural network (R-CNN) -- Fast R-CNN -- Faster R-CNN -- Single shot multi-box detector -- Object detection API -- Installation and setup -- Pre-trained models -- Re-training object detection models -- Data preparation for the Pet dataset -- Object detection training pipeline -- Training the model -- Monitoring loss and accuracy using TensorBoard -- Training a pedestrian detection for a self-driving car -- The YOLO object detection algorithm -- Summary -- Chapter 5: Semantic Segmentation -- Predicting pixels -- Diagnosing medical images -- Understanding the earth from satellite imagery -- Enabling robots to see -- Datasets -- Algorithms for semantic segmentation -- The Fully Convolutional Network -- The SegNet architecture -- Upsampling the layers by pooling -- Sampling the layers by convolution -- Skipping connections for better training -- Dilated convolutions -- DeepLab -- RefiNet -- PSPnet -- Large kernel matters -- DeepLab v3 -- Ultra-nerve segmentation -- Segmenting satellite images -- Modeling FCN for segmentation -- Segmenting instances -- Summary -- Chapter 6: Similarity Learning -- Algorithms for similarity learning -- Siamese networks -- Contrastive loss -- FaceNet -- Triplet loss -- The DeepNet model -- DeepRank -- Visual recommendation systems -- Human face analysis -- Face detection -- Face landmarks and attributes -- The Multi-Task Facial Landmark (MTFL) dataset -- The Kaggle keypoint dataset -- The Multi-Attribute Facial Landmark (MAFL) dataset -- Learning the facial key points -- Face recognition…”

Tabla de Contenidos: “…Examples of setting up the xWindows Interface -- Using a Linux Intel system as a client -- Using VNC client and server -- Using Exceed with Telnet -- Appendix D. …”

Tabla de Contenidos: “…Planning and sizing for deployment -- 2.1 Tivoli Storage Manager system requirements -- 2.1.1 Windows environment requirements -- 2.1.2 UNIX environment requirements…”

Tabla de Contenidos: “…Machine generated contents note: Preface Introduction I Fundamentals of Multivariate Statistical Process Control 1 Motivation for Multivariate Statistical Process Control 1.1 Summary of Statistical Process Control 1.1.1 Roots and Evolution of Statistical Process Control 1.1.2 Principles of Statistical Process Control 1.1.3 Hypothesis Testing, Type I and II errors 1.2 Why Multivariate Statistical Process Control 1.2.1 Statistically Uncorrelated Variables 1.2.2 Perfectly Correlated Variables 1.2.3 Highly Correlated Variables 1.2.4 Type I and II Errors and Dimension Reduction 1.3 Tutorial Session 2 Multivariate Data Modeling Methods 2.1 Principal Component Analysis 2.1.1 Assumptions for Underlying Data Structure 2.1.2 Geometric Analysis of Data Structure 2.1.3 A Simulation Example 2.2 Partial Least Squares 2.2.1 Assumptions for Underlying Data Structure 2.2.2 Deflation Procedure for Estimating Data Models 2.2.3 A Simulation Example 2.3 Maximum Redundancy Partial Least Squares 2.3.1 Assumptions for Underlying Data Structure 2.3.2 Source Signal Estimation 2.3.3 Geometric Analysis of Data Structure 2.3.4 A Simulation Example 2.4 Estimating the Number of Source Signals 2.4.1 Stopping Rules for PCA Models 2.4.2 Stopping Rules for PLS Models 2.5 Tutorial Session 3 Process Monitoring Charts 3.1 Fault Detection 3.1.1 Scatter Diagrams 3.1.2 Nonnegative Quadratic Monitoring Statistics 3.2 Fault Isolation and Identification 3.2.1 Contribution Charts 3.2.2 Residual-Based Tests 3.2.3 Variable Reconstruction 3.3 Geometry of Variable Projections 3.3.1 Linear Dependency of Projection Residuals 3.3.2 Geometric Analysis of Variable Reconstruction 3.4 Tutorial Session II Application Studies 4 Application to a Chemical Reaction Process 4.1 Process Description 4.2 Identification of a Monitoring Model 4.3 Diagnosis of a Fault Condition 5 Application to a Distillation Process 5.1 Process Description 5.2 Identification of a Monitoring Model 5.3 Diagnosis of a Fault Condition III Advances in Multivariate Statistical Process Control 6 Further Modeling Issues 6.1 Accuracy of Estimating PCA Models 6.1.1 Revisiting the Eigendecomposition of Sz0z0 6.1.2 Two Illustrative Examples 6.1.3 Maximum Likelihood PCA for Known Sgg 6.1.4 Maximum Likelihood PCA for Unknown Sgg 6.1.5 A Simulation Example 6.1.6 A Stopping Rule for Maximum Likelihood PCA Models 6.1.7 Properties of Model and Residual Subspace Estimates 6.1.8 Application to a Chemical Reaction Process - Revisited 6.2 Accuracy of Estimating PLS Models 6.2.1 Bias and Variance of Parameter Estimation 6.2.2 Comparing Accuracy of PLS and OLS Regression Models 6.2.3 Impact of Error-in-Variables Structure upon PLS Models 6.2.4 Error-in-Variable Estimate for Known See 6.2.5 Error-in-Variable Estimate for Unknown See 6.2.6 Application to a Distillation Process - Revisited 6.3 Robust Model Estimation 6.3.1 Robust Parameter Estimation 6.3.2 Trimming Approaches 6.4 Small Sample Sets 6.5 Tutorial Session 7 Monitoring Multivariate Time-Varying Processes 7.1 Problem Analysis 7.2 Recursive Principal Component Analysis 7.3 MovingWindow Principal Component Analysis 7.3.1 Adapting the Data Correlation Matrix 7.3.2 Adapting the Eigendecomposition 7.3.3 Computational Analysis of the Adaptation Procedure 7.3.4 Adaptation of Control Limits 7.3.5 Process Monitoring using an Application Delay 7.3.6 MinimumWindow Length 7.4 A Simulation Example 7.4.1 Data Generation 7.4.2 Application of PCA 7.4.3 Utilizing MWPCA based on an Application Delay 7.5 Application to a Fluid Catalytic Cracking Unit 7.5.1 Process Description 7.5.2 Data Generation 7.5.3 Pre-analysis of Simulated Data 7.5.4 Application of PCA 7.5.5 Application of MWPCA 7.6 Application to a Furnace Process 7.6.1 Process Description 7.6.2 Description of Sensor Bias 7.6.3 Application of PCA 7.6.4 Utilizing MWPCA based on an Application Delay 7.7 Adaptive Partial Least Squares 7.7.1 Recursive Adaptation of Sx0x0 and Sx0y0 7.7.2 MovingWindow Adaptation of Sv0v0 and Sv0y0 7.7.3 Adapting The Number of Source Signals 7.7.4 Adaptation of the PLS Model 7.8 Tutorial Session 8 Monitoring Changes in Covariance Structure 8.1 Problem Analysis 8.1.1 First Intuitive Example 8.1.2 Generic Statistical Analysis 8.1.3 Second Intuitive Example 8.2 Preliminary Discussion of Related Techniques 8.3 Definition of Primary and Improved Residuals 8.3.1 Primary Residuals for Eigenvectors 8.3.2 Primary Residuals for Eigenvalues 8.3.3 Comparing both Types of Primary Residuals 8.3.4 Statistical Properties of Primary Residuals 8.3.5 Improved Residuals for Eigenvalues 8.4 Revisiting the Simulation Examples in Section 8.1 8.4.1 First Simulation Example 8.4.2 Second Simulation Example 8.5 Fault Isolation and Identification 8.5.1 Diagnosis of Step-Type Fault Conditions 8.5.2 Diagnosis of General Deterministic Fault Conditions 8.5.3 A Simulation Example 8.6 Application Study to a Gearbox System 8.6.1 Process Description 8.6.2 Fault Description 8.6.3 Identification of a Monitoring Model 8.6.4 Detecting a Fault Condition 8.7 Analysis of Primary and Improved Residuals 8.7.1 Central Limit Theorem 8.7.2 Further Statistical Properties of Primary Residuals 8.7.3 Sensitivity of Statistics based on Improved Residuals 8.8 Tutorial Session IV Description of Modeling Methods 9 Principal Component Analysis 9.1 The Core Algorithm 9.2 Summary of the PCA Algorithm 9.3 Properties of a PCA Model 10 Partial Least Squares 10.1 Preliminaries 10.2 The Core Algorithm 10.3 Summary of the PLS Algorithm10.4 Properties of PLS 10.5 Properties of Maximum Redundancy PLS References Index…”

Tabla de Contenidos: “…-- Now you can. . . -- Chapter 2 Creating a Model -- Placing Walls -- Adding Exterior Walls -- Using Reference Planes -- Adding More Walls -- Adding Interior Walls -- Using Temporary Dimensions to Gain Control of Your Model -- Editing Wall Joins -- Displaying Wall Joins -- Disallowing Wall Joins -- Adding Doors and Windows -- Adding Doors -- Placing Openings in Your Walls -- Adding Windows -- Are You Experienced? …”

“…What You Will Learn: The tags supported in HTML5 What comprises an HTML5 content production workflow Concepts and principles behind HTML5 content production How to install and utilize Inkscape for Windows, Mac OS X and Linux Concepts behind spline curves, strokes, fills, patterns, and rendering Digital illustration data formats and data footprint optimization Who This Book Is For: Website developers, Flash developers, user interface designers, HTML5 game designers, teachers, and educators…”

Tabla de Contenidos: “…Cover -- Title Page -- Copyright -- Contributors -- Table of Contents -- Preface -- Part 1: Getting Started with Prophet -- Chapter 1: The History and Development of Time Series Forecasting -- Understanding time series forecasting -- The problem with dependent data -- Moving averages and exponential smoothing -- ARIMA -- ARCH/GARCH -- Neural networks -- Prophet -- Recent developments -- NeuralProphet -- Google's "robust time series forecasting at scale" -- LinkedIn's Silverkite/Greykite -- Uber's Orbit -- Summary -- Chapter 2: Getting Started with Prophet -- Technical requirements -- Installing Prophet -- Installation on macOS -- Installation on Windows -- Installation on Linux -- Building a simple model in Prophet -- Interpreting the forecast DataFrame -- Understanding components plots -- Summary -- Chapter 3: How Prophet Works -- Technical requirements -- Facebook's motivation for building Prophet -- Analyst-in-the-loop forecasting -- The math behind Prophet -- Linear growth -- Logistic growth -- Seasonality -- Holidays -- Summary -- Part 2: Seasonality, Tuning, and Advanced Features -- Chapter 4: Handling Non-Daily Data -- Technical requirements -- Using monthly data -- Using sub-daily data -- Using data with regular gaps -- Summary -- Chapter 5: Working with Seasonality -- Technical requirements -- Understanding additive versus multiplicative seasonality -- Controlling seasonality with the Fourier order -- Adding custom seasonalities -- Adding conditional seasonalities -- Regularizing seasonality -- Global seasonality regularization -- Local seasonality regularization -- Summary -- Chapter 6: Forecasting Holiday Effects -- Technical requirements -- Adding default country holidays -- Adding default state/province holidays -- Creating custom holidays -- Creating multi-day holidays -- Regularizing holidays -- Global holiday regularization…”

“…Dreamweaver MX (for Mac OS 9, Mac OS X, and Windows) marks the historic union of Dreamweaver and Dreamweaver UltraDev, a package of Web-database language modules once sold separately. …”

“…You'll find up to the minute coverage on all of today's hottest technologies including the evolution of computing, from the room sized monoliths of the 1950s to today's global Internet; a preview of the next revolution, pervasive computing; computer hardware, microprocessors, memory, storage, I/O, displays, and architecture; Windows, Macintosh, UNIX/Linux, DOS, NetWare, Palm, what operating systems do, and how they compare; programming languages from machine language to advanced object oriented technologies; key software applications, databases, spreadsheets, word processing, voice recognition, and beyond; Microsoft and the software industry, where they stand where they're headed; how networks work, LANs, WANs, packet switching, hardware, media, and more; Internet, e-commerce, and security; enterprise applications, data warehousing, Web-centered development, and groupware, whether you're a consumer, investor, or marketer…”

“…On the way you get Visual C++ project files to study and software that runs on the Windows desktop. The free CD-ROM gives you a full-featured development environment for 3D character animation, so even if you find some of the maths and the code hard to follow straight away you can still create your own games. …”

“…作者是 Intel 資深工程式,有二十年以上平行與並行領域的程式設計經驗,本書能幫助讀者: ‧區分共享記憶體與分散式記憶體程式撰寫的差異 ‧學習設計多執行緒應用程式的規範,內容包含測試與調校 ‧介紹多種多執行緒函式庫的特性,包含 Windows threads、POSIX threads、OpenMP 以及 Intel Thread Building Blocks ‧介紹各種並行演算法實作方式,包含排序、搜尋、圖論以及其他實際的計算問題 《並行之美學》介紹利用新式多核心處理器的優點,維持演算法擴縮性的方式,在開發平行演算法或並行程式設計上是本不可或缺的書籍。 …”

“…Die Nachbearbeitung der Filme wird sowohl für Windows- als auch Mac-Nutzer anhand kostenloser Programme anschaulich erläutert…”

Tabla de Contenidos: “…-- 1.2 INICIAR EXCEL -- 1.2.1 Abrir Excel usando Windows 8 -- 1.2.2 Abrir Excel usando Windows 10 -- 1.3 LA PANTALLA INICIO DE EXCEL -- 1.3.1 Ahorrar tiempo sin la pantalla Inicio de Excel -- 1.4 CREAR UN LIBRO -- 1.4.1 Crear un libro en blanco -- 1.4.2 Crear un libro a partir de una plantilla prediseñada -- 1.5 EXAMINAR LA VENTANA DE EXCEL 2016 -- 1.5.1 Barra de herramientas de acceso rápido -- 1.5.2 Barra de título -- 1.5.3 Botones de control -- 1.5.4 La cinta de opciones -- 1.6 VISTAS DE PÁGINA -- 1.6.1 Vista normal -- 1.6.2 Vista diseño de página -- 1.6.3 Ver salto de página -- 1.7 HERRAMIENTAS ZOOM -- 1.8 TERMINOLOGÍA DE EXCEL -- 1.8.1 Cuadro de nombres -- 1.8.2 Barra de fórmulas -- 1.8.3 Celda activa -- 1.8.4 Encabezados de fila -- 1.8.5 Encabezados de columna -- 1.8.6 Celdas -- 1.8.7 Etiquetas de hojas -- 1.8.8 Hoja de trabajo -- 1.8.9 Puntero de celda -- 1.8.10 Rango -- 1.9 GUARDAR SUS LIBROS -- 1.9.1 Comprobar opciones de compatibilidad -- 1.10 ABRIR LIBROS -- 1.11 ORGANIZAR SUS HOJAS -- 1.11.1 Renombrar hojas -- 1.11.2 Reorganizar hojas -- 1.11.3 Aplicar colores a etiquetas -- 1.11.4 Eliminar hojas -- 1.11.5 Agrupar y desagrupar hojas -- 1.12 IMPRIMIR SU TRABAJO -- 2 MANEJO DE DATOS EN EXCEL -- 2.1 INTRODUCIR DATOS -- 2.1.1 Los valores numéricos -- 2.1.2 Los textos -- 2.1.3 Aplicar formatos a las celdas -- 2.1.4 Insertar fórmulas -- 2.2 USAR EL CONTROLADOR DE RELLENO -- 2.3 INTRODUCIR FECHAS Y HORAS -- 2.3.1 Introducir fechas -- 2.3.2 Introducir horas -- 2.4 APLICAR FORMATOS A LOS NÚMEROS -- 2.5 TRABAJAR CON FILAS Y COLUMNAS -- 2.5.1 Insertar filas o columnas -- 2.5.2 Eliminar filas o columnas -- 2.5.3 Cambiar el ancho de las columnas y el alto de las filas -- 2.6 APLICAR BORDES…”