Tabla de Contenidos: “…-- 4.1.Viewing projects -- Writing a feature -- The Factory Girl -- Adding a link to a project -- 4.2.Editing projects -- The edit action -- The update action -- 4.3.Deleting projects -- Writing a feature -- Adding a destroy action -- Looking for what isn't there -- 4.4.Summary -- 5.Nested resources -- 5.1.Creating tickets -- Nested routing helpers -- Creating a tickets controller -- Defining a has_many association -- Creating tickets within a project -- Finding tickets scoped by project -- Ticket validations -- 5.2.Viewing tickets -- Listing tickets -- Culling tickets -- 5.3.Editing tickets -- Adding the edit action -- Adding the update action -- 5.4.Deleting tickets -- 5.5.Summary -- 6.Authentication and basic authorization -- 6.1.What Devise does -- Installing Devise -- 6.2.User signup -- 6.3.Confirmation link sign-in -- Testing email -- Confirming confirmation -- 6.4.Form sign-in -- 6.5.Linking tickets to users -- Attributing tickets to users -- We broke something! …”

Tabla de Contenidos: “…-- Time for action - sky factory -- What just happened? -- Time for action - fog of war -- What just happened? …”

Tabla de Contenidos: “…Testing the DAO Layer with Spring and JUnit -- Unit testing overview -- The benefits of unit testing -- Configuring the test environment -- The jdbc.properties file -- The logback.xml file -- The test-persistence.xml file -- Introducing the Spring IoC container -- Exploring the testingContext.xml file -- The Spring XML namespaces -- The property file configuration -- Creating the JDBC DataSource -- Defining helper beans -- Defining the EntityManagerFactory class -- Configuring the transaction manager -- Autowiring beans -- Thanks for the plumbing! …”

“…A social history that reveals the roots of AI in the spatial computation of industrial factories and the surveillance of collective behaviour -- Editor…”

Tabla de Contenidos: “…Replication methods -- 2.1. Factorial approach for strong replication -- 2.2. Weak replication…”

Tabla de Contenidos: “…Preface xiii Table of Engineering Applications xvii Part 1 Introduction 1 Mathematica Environment and Basic Syntax 3 1.1 Introduction 3 1.2 Selecting Notebook Characteristics 4 1.3 Notebook Cells 8 1.4 Delimiters 12 1.5 Basic Syntax 12 1.5.1 Introduction 12 1.5.2 Templates: Greek Symbols and Mathematical Notation 15 1.5.3 Variable Names and Global Variables 18 1.6 Mathematical Constants 19 1.7 Complex Numbers 21 1.8 Elementary, Trigonometric, Hyperbolic, and a Few Special Functions 22 1.9 Strings 25 1.9.1 String Creation: StringJoin[] and ToString[] 25 1.9.2 Labeled Output: Print[], NumberForm[], EngineeringForm[], and TraditionalForm[] 26 1.10 Conversions, Relational Operators, and Transformation Rule 28 1.11 Engineering Units and Unit Conversions: Quantity[] and UnitConvert[] 30 1.12 Creation of CDF Documents and Documents in Other Formats 33 1.13 Functions Introduced in Chapter 1 34 Exercises 35 2 List Creation and Manipulation: Vectors and Matrices 39 2.1 Introduction 39 2.2 Creating Lists and Vectors 39 2.2.1 Introduction 39 2.2.2 Creating a List with Table[] 45 2.2.3 Summing Elements of a List: Total[] 46 2.2.4 Selecting Elements of a List 47 2.2.5 Identifying List Elements Matching a Pattern: Position[] 49 2.3 Creating Matrices 51 2.3.1 Introduction 51 2.3.2 Matrix Generation Using Table[] 54 2.3.3 Accessing Elements of Arrays 55 2.4 Matrix Operations on Vectors and Arrays 56 2.4.1 Introduction 56 2.4.2 Matrix Inverse and Determinant: Inverse[] and Det[] 57 2.5 Solution of a Linear System of Equations: LinearSolve[] 58 2.6 Eigenvalues and Eigenvectors: EigenSystem[] 59 2.7 Functions Introduced in Chapter 2 61 References 61 Exercises 61 3 User-Created Functions, Repetitive Operations, and Conditionals 69 3.1 Introduction 69 3.2 Expressions and Procedures as Functions 69 3.2.1 Introduction 69 3.2.2 Pure Function: Function[] 74 3.2.3 Module[] 78 3.3 Find Elements of a List that Meet a Criterion: Select[] 80 3.4 Conditionals 82 3.4.1 If[] 82 3.4.2 Which[] 83 3.5 Repetitive Operations 83 3.5.1 Do[] 83 3.5.2 While[] 83 3.5.3 Nest[] 84 3.5.4 Map[] 84 3.6 Examples of Repetitive Operations and Conditionals 85 3.7 Functions Introduced in Chapter 3 92 Exercises 92 4 Symbolic Operations 95 4.1 Introduction 95 4.2 Assumption Options 101 4.3 Solutions of Equations: Solve[] 101 4.4 Limits: Limit[] 105 4.5 Power Series: Series[], Coefficient[], and CoefficientList[] 108 4.6 Optimization: Maximize[]/Minimize[] 112 4.7 Differentiation: D[] 114 4.8 Integration: Integrate[] 120 4.9 Solutions of Ordinary Differential Equations: DSolve[] 126 4.10 Solutions of Partial Differential Equations: DSolve[] 136 4.11 Laplace Transform: LaplaceTransform[] and InverseLaplaceTransform[] 138 4.12 Functions Introduced in Chapter 4 145 References 145 Exercises 146 5 Numerical Evaluations of Equations 151 5.1 Introduction 151 5.2 Numerical Integration: NIntegrate[] 151 5.3 Numerical Solutions of Differential Equations: NDSolveValue[] and ParametricNDSolveValue[] 154 5.4 Numerical Solutions of Equations: NSolve[] 178 5.5 Roots of Transcendental Equations: FindRoot[] 180 5.6 Minimum and Maximum: FindMinimum[] and FindMaximum[] 182 5.7 Fitting of Data: Interpolation[] and FindFit[] 186 5.8 Discrete Fourier Transforms and Correlation: Fourier[], InverseFourier[], and ListCorrelate[] 189 5.9 Functions Introduced in Chapter 5 194 References 195 Exercises 196 6 Graphics 209 6.1 Introduction 209 6.2 2D Graphics 209 6.2.1 Basic Plotting 209 6.2.2 Basic Graph Enhancements 213 6.2.3 Common 2D Shapes: Graphics[] 217 6.2.4 Additional Graph Enhancements 222 6.2.5 Combining Figures: Show[] and GraphicsGrid[] 238 6.2.6 Tooltip[] 241 6.2.7 Exporting Graphics 244 6.3 3D Graphics 244 6.4 Summary of Functions Introduced in Chapter 6 253 References 254 Exercises 254 7 Interactive Graphics 263 7.1 Interactive Graphics: Manipulate[] 263 References 287 Exercises 287 Part 2 Engineering Applications 8 Vibrations of Spring Mass Systems and Thin Beams 293 8.1 Introduction 293 8.2 Single Degree-of-Freedom Systems 294 8.2.1 Periodic Force on a Single Degree-of-Freedom System 294 8.2.2 Squeeze Film Damping and Viscous Fluid Damping 298 8.2.3 Electrostatic Attraction 302 8.2.4 Single Degree-of-Freedom System Energy Harvester 304 8.3 Two Degrees-of-Freedom Systems 307 8.3.1 Governing Equations 307 8.3.2 Response to Harmonic Excitation: Amplitude Response Functions 307 8.3.3 Enhanced Energy Harvester 310 8.4 Thin Beams 315 8.4.1 Natural Frequencies and Mode Shapes of a Cantilever Beam with In-Span Attachments 315 8.4.2 Effects of Electrostatic Force on the Natural Frequency and Stability of a Beam 318 8.4.3 Response of a Cantilever Beam with an In-Span Attachment to an Impulse Force 323 References 326 9 Statistics 327 9.1 Descriptive Statistics 327 9.1.1 Introduction 327 9.1.2 Location Statistics: Mean[], StandardDeviation[], and Quartile[] 327 9.1.3 Continuous Distribution Functions: PDF[] and CDF[] 329 9.1.4 Histograms and Probability Plots: Histogram[] and ProbabilityScalePlot [] 331 9.1.5 Whisker Plot: BoxWhiskerChart[] 332 9.1.6 Creating Data with Specified Distributions: RandomVariate[] 334 9.2 Probability of Continuous Random Variables 334 9.2.1 Probability for Different Distributions: NProbability[] 334 9.2.2 Inverse Cumulative Distribution Function: InverseCDF[] 337 9.2.3 Distribution Parameter Estimation: EstimatedDistribution[] and FindDistributionParameters[] 337 9.2.4 Confidence Intervals: CI[] 340 9.2.5 Hypothesis Testing: LocationTest[] and VarianceTest[] 342 9.3 Regression Analysis: LinearModelFit[] 343 9.3.1 Simple Linear Regression 343 9.3.2 Multiple Linear Regression 347 9.4 Nonlinear Regression Analysis: NonLinearModelFit[] 351 9.5 Analysis of Variance (ANOVA) and Factorial Designs: ANOVA[] 354 9.6 Functions Introduced in Chapter 9 358 10 Control Systems and Signal Processing 359 10.1 Introduction 359 10.2 Model Generation: State-Space and Transfer Function Representation 359 10.2.1 Introduction 359 10.2.2 State-Space Models: StateSpaceModel[] 360 10.2.3 Transfer Function Models: TransferFunctionModel[] 362 10.3 Model Connections Closed-Loop Systems and System Response: SystemsModelFeedbackConnect[] and SystemsModelSeriesConnect[] 363 10.4 Design Methods 369 10.4.1 Root Locus: RootLocusPlot[] 369 10.4.2 Bode Plot: BodePlot[] 371 10.4.3 Nichols Plot: NicholsPlot[] 372 10.5 Signal Processing 374 10.5.1 Filter Models: ButterworthFilterModel[], EllipticFilterModel[], ... 374 10.5.2 Windows: HammingWindow[], HannWindow[], ... 381 10.5.3 Spectrum Averaging 385 10.6 Aliasing 388 10.7 Functions Introduced in Chapter 10 390 Reference 391 11 Heat Transfer and Fluid Mechanics 393 11.1 Introduction 393 11.2 Conduction Heat Transfer 394 11.2.1 One-Dimensional Transient Heat Diffusion in Solids 394 11.2.2 Heat Transfer in Concentric Spheres: Ablation of a Tumor 398 11.2.3 Heat Flow Through Fins 401 11.3 Natural Convection Along Heated Plates 405 11.4 View Factor Between Two Parallel Rectangular Surfaces 408 11.5 Internal Viscous Flow 411 11.5.1 Laminar Flow in Horizontal Cylindrical Pipes 411 11.5.2 Flow in Three Reservoirs 412 11.6 External Flow 416 11.6.1 Pressure Coefficient of a Joukowski Airfoil 416 11.6.2 Surface Profile in Nonuniform Flow in Open Channels 419 References 423 Index 425.…”

Tabla de Contenidos: “…Recommended Settings -- Changing Default Settings -- Resetting to Factory Defaults -- Recommended Default Changes -- Chapter 4. …”

Tabla de Contenidos: “…14 Analysis of Variance and Experimental Designs -- 14.1 Introduction -- 14.2 Introduction to Experimental Designs -- 14.3 Analysis of Variance -- 14.4 Completely Randomized Design (One-Way ANOVA) -- 14.5 Randomized Block Design -- 14.6 Factorial Design (Two-Way ANOVA) -- Summary -- Key Terms -- Discussion Questions -- Numerical Problems -- Case Study -- 15 Hypothesis Testing for Categorical Data (Chi-Square Test) -- 15.1 Introduction -- 15.2 Defining x2-Test Statistic -- 15.3 x2 Goodness-of-Fit Test -- 15.4 x2 Test of Independence: Two-Way Contingency Analysis -- 15.5 x2 Test for Population Variance -- 15.6 x2 Test of Homogeneity -- Summary -- Key Terms -- Discussion Questions -- Numerical Problems -- Case Study -- 16 Correlation and Simple Linear Regression Analysis -- 16.1 Measures of Association -- 16.2 Introduction to Simple Linear Regression -- 16.3 Determining the Equation of a Regression Line -- 16.4 Using MS Excel for Simple Linear Regression -- 16.5 Using Minitab for Simple Linear Regression -- 16.6 Using SPSS for Simple Linear Regression -- 16.7 Measures of Variation -- 16.8 Statistical Inference About Slope, Correlation Coefficient of the Regression Model, and Testing the Overall Model -- Summary -- Key Terms -- Discussion Questions -- Numerical Problems -- Case Study -- 17 Multivariate Analysis I: Multiple Regression Analysis -- 17.1 Introduction -- 17.2 The Multiple Regression Model -- 17.3 Multiple Regression Model with Two Independent Variables -- 17.4 Determination of Coefficient of Multiple Determination (R2), Adjusted R2, and Standard Error of the Estimate -- 17.5 Statistical Significance Test for the Regression Model and the Coefficient of Regression -- 17.6 Indicator (Dummy Variable Model) -- 17.7 Collinearity -- Summary -- Key Terms -- Discussion Questions -- Numerical Problems -- Case Study…”

“…A biography of the German-born Jewish architect who, from the 1880s through the early 1940s, designed elegant homes, factories for Henry Ford, and industrial plants to support the United States' war effort…”

“…Topics include JMP software, two-sample t-test, ANOVA, regression, design of experiments, blocking, factorial designs, fractional-factorial designs, central composite designs, Box-Behnken designs, split-plot designs, optimal designs, mixture designs, and 2 k factorial designs. …”

“…This dissertation analyses the »factory farming system«, the central area of agricultural policy, from the perspective of constitutional law. …”

“…Recoge: Análisis multivariante; Análisis factorial; Análisis de correspondencias simple y múltiple; Análisis cluster; Escalamiento multidimensional; Regresión lineal; Análisis de varianza; Segmentación jerárquica; Análisis discriminante; Regresión logística; Correlaciones canónicas…”

“…Schizophrenia is a multi-factorial disease characterized by a high heritability and environmental risk factors (e.g. stress and cannabis use). …”

“…"EAI Endorsed Transactions on Industrial Networks and Intelligent Systems is an open access, peer-reviewed scholarly journal focused on ubiquitous computing, cloud computing, and cyber-physical system, all kinds of networks in large-scale factories, including a lot of traditional and new industries."…”

“…The people in the municipality are shocked by the newcomerʼs unorthodox life style. Amongst factories, sport clubs, and robotic lawn mowers itʼs considered a bit odd to make a living of art…”
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Tabla de Contenidos: “…ORIGEN Y DESARROLLO DE LAS INVESTIGACIONES -- 3. ANÁLISIS FACTORIAL -- 4. TRABAJOS DE FLEISHMAN -- 5. DIFERENTES TIPOS DE CAPACIDAD -- 6. …”

Tabla de Contenidos: “…3.2.1 Example: ANOVA for the One-Way Layout -- 3.2.2 Comparing Two Nested Normal Linear Models -- 3.2.3 Likelihood-Ratio Test Comparing Models -- 3.2.4 Example: Test That All Effects in a Normal Linear Model Equal Zero -- 3.2.5 Non-null Behavior of Statistic Comparing Nested Models -- 3.2.6 Expected Mean Squares and Power for One-Way ANOVA -- 3.2.7 Testing a General Linear Hypothesis -- 3.2.8 Example: Testing That a Single Model Parameter Equals Zero -- 3.2.9 Testing Terms in an Unbalanced Factorial ANOVA -- 3.3 Confidence Intervals and Prediction Intervals for Normal Linear Models -- 3.3.1 Confidence Interval for a Parameter of a Normal Linear Model -- 3.3.2 Confidence Interval for E(y) = x0 -- 3.3.3 Prediction Interval for a Future y -- 3.3.4 Example: Confidence Interval and Prediction Interval for Simple Linear Regression -- 3.3.5 Interpretation and Limitations of Prediction Intervals -- 3.4 Example: Normal Linear Model Inference -- 3.4.1 Inference for Modeling House Selling Prices -- 3.4.2 Model Checking -- 3.4.3 Conditional versus Marginal Effects: Simpson's Paradox -- 3.4.4 Partial Correlation -- 3.4.5 Testing Contrasts as a General Linear Hypothesis -- 3.4.6 Selecting or Building a Model -- 3.5 Multiple Comparisons: Bonferroni, Tukey, and FDR Methods -- 3.5.1 Bonferroni Method for Multiple Inferences -- 3.5.2 Tukey Method of Multiple Comparisons -- 3.5.3 Controlling the False Discovery Rate -- Chapter Notes -- Exercises -- 4 Generalized Linear Models: Model Fitting and Inference -- 4.1 Exponential Dispersion Family Distributions for a Glm -- 4.1.1 Exponential Dispersion Family for a Random Component -- 4.1.2 Poisson, Binomial, and Normal in Exponential Dispersion Family -- 4.1.3 The Canonical Link Function of a Generalized Linear Model -- 4.2 Likelihood and Asymptotic Distributions for GLMS -- 4.2.1 Likelihood Equations for a GLM…”