“…Marketers need to improve speed to increase conversion rates. Designers need to create faster websites to improve the user experience. …”

Tabla de Contenidos: “…10.1.1 Calculation of the maximum power conversion efficiency -- 10.2 Low-voltage starter -- 10.2.1 Enhanced swing ring oscillator -- 10.2.2 Dickson charge pump -- 10.2.3 AC model of ESRO -- 10.2.4 Important formulas for the LVS block -- 10.3 Power equations for convertor operating in DCM -- 10.3.1 Boost convertor -- 10.3.2 Maximum extraction of power from a low-voltage source V TEG -- 10.3.3 Sizing auxiliary and main stage inductors -- 10.4 Peripheral circuits -- 10.4.1 Current starved ring oscillator -- 10.4.2 Reference generator and node sensing network -- 10.4.3 Zero current switching network -- 10.4.4 Control logic -- 10.5 Test and measurement -- 10.5.1 Inductors for ESRO coupled with DCP -- 10.6 Conclusion -- Acknowledgments -- References -- Chapter 11: Managing concept drift in IoT health data streams: A dynamic adaptive weighted ensemble approach -- 11.1 Introduction -- 11.1.1 Concept of drift -- 11.1.2 Significance of adaptive learning in IoT with machine learning for health data -- 11.2 Literature survey -- 11.2.1 Drift phenomenon -- 11.2.2 Adaptive learning models towards IoT -- 11.3 Methodology -- 11.3.1 Dataset description -- 11.3.2 Data preprocessing -- 11.3.3 Implementation of DAWE -- 11.3.3.1 Base learners -- 11.3.3.2 Proposed ensemble strategy for DAWE -- 11.4 Experimental results -- 11.5 Discussion and future scope -- 11.6 Conclusions -- Acknowledgments -- References -- Chapter 12: GraLSTM: A distributed learning model for efficient IoT resource allocation in healthcare -- 12.1 Introduction -- 12.1.1 How is IoT useful for the healthcare sector? …”

Tabla de Contenidos: “…Disclosures -- Other Sources -- 9 ASC 255 Changing Prices -- Perspective and Issues -- Subtopic -- Scope -- Definitions of Terms -- Concepts, Rules, and Examples -- Elective Disclosures -- Other Sources -- 10 ASC 260 Earnings Per Share -- Perspective and Issues -- Subtopic -- Scope and Scope Exceptions -- Overview -- Definitions of Terms -- Concepts, Rules, and Examples -- Presentation on the Income Statement -- Basic EPS Calculation-Simple Capital Structure -- Diluted Earnings per Share (DEPS) -- Examples of EPS Computation -- Effect of Contracts That May Be Settled in Stock or Cash on the Computation of DEPS -- Inclusions/Exclusions from Computation of DEPS -- Partially Paid Shares -- Effect of Certain Derivatives on EPS Computations -- Effect on EPS of Redemption or Induced Conversion of Preferred Stock -- Special Issues Affecting Basic and Diluted EPS -- Participating Securities and the Two-Class Method -- EPS Impact of Tax Effect of Dividends Paid on Unallocated ESOP Shares -- Earnings Per Share Implications of ASC 718 -- Master Limited Partnerships-Dropdown Transactions -- Comprehensive Example -- Diluted EPS (DEPS) -- Note X: Earnings per Share (Illustrative Disclosure Based on Facts from the Example) -- Other Sources -- 11 ASC 270 Interim Reporting -- Perspective and Issues -- Subtopic -- Overview -- Definitions of Terms -- Concepts, Rules, and Examples -- Differentiation between Public and Nonpublic Entities -- Requirements Applicable to All Reporting Entities -- Revenues -- Product Costs and Direct Costs -- Other Costs and Expenses -- Seasonality -- Fair Value of Financial Instruments -- Unusual or Infrequent Items and Disposals of Components -- Contingencies -- Accounting Changes -- Other Sources -- Requirements Applicable to Public Reporting Entities -- Quarterly Reporting to the SEC -- 12 ASC 272 Limited Liability Entities…”

Tabla de Contenidos: “…Multi-field join and one-to-many -- Scenario -- Populating the sample data -- Defining the aggregation pipeline -- Executing the aggregation pipeline -- Expected pipeline result -- Pipeline observations -- Summary -- Chapter 8: Fixing and Generating Data Examples -- Strongly typed conversion -- Scenario -- Populating the sample data -- Defining the aggregation pipeline -- Executing the aggregation pipeline -- Expected pipeline result -- Pipeline observations -- Converting incomplete date strings -- Scenario -- Populating the sample data -- Defining the aggregation pipeline -- Executing the aggregation pipeline -- Expected pipeline result -- Pipeline observations -- Generating mock test data -- Scenario -- Populating the sample data -- Defining the aggregation pipeline -- Executing the aggregation pipeline -- Expected pipeline result -- Pipeline observations -- Summary -- Chapter 9: Trend Analysis Examples -- Faceted classification -- Scenario -- Populating the sample data -- Defining the aggregation pipeline -- Executing the aggregation pipeline -- Expected pipeline result -- Pipeline observations -- Largest graph network -- Scenario -- Populating the sample data -- Defining the aggregation pipeline -- Executing the aggregation pipeline -- Expected pipeline result -- Pipeline observations -- Incremental analytics -- Scenario -- Populating the sample data -- Defining the aggregation pipeline -- Executing the aggregation pipeline -- Expected pipeline result -- Pipeline observations -- Summary -- Chapter 10: Securing Data Examples -- Redacted view -- Scenario -- Populating the sample data -- Defining the aggregation pipeline -- Executing the aggregation pipeline -- Expected pipeline result -- Pipeline observations -- Mask sensitive fields -- Scenario -- Populating the sample data -- Defining the aggregation pipeline -- Executing the aggregation pipeline…”

Tabla de Contenidos: “…An example functional API -- Advantages of functional APIs -- Disadvantages of functional APIs -- Data-driven APIs -- Advantages of data-driven APIs -- Disadvantages of data-driven APIs -- Supporting variant argument lists -- Case study: FMOD data-driven API -- Data-driven Web services -- Idempotency -- 6 - C++ usage -- Namespaces -- Constructors and assignment -- Defining constructors and assignment -- The explicit keyword -- Const correctness -- Method const correctness -- Parameter const correctness -- Return value const correctness -- Templates -- Template terminology -- Implicit instantiation API design -- Explicit instantiation API design -- Operator overloading -- Overloadable operators -- Free operators versus member operators -- Adding operators to a class -- Operator syntax -- Conversion operators -- Function parameters -- Pointer versus reference parameters -- Default arguments -- Avoid #define for constants -- Avoid using friends -- Exporting symbols -- Coding conventions -- 7 - C++ revisions -- Which C++ revision to use -- C++11 API features -- Move constructors and the Rule of Five -- Default and deleted functions -- Object construction -- Initializer list constructors -- Smart pointers -- Enum classes -- Override and final specifiers -- The noexcept specifier -- Inline namespaces -- Type aliases with using -- User-defined literals -- Alternate function style -- Tuples -- Constant expressions -- The nullptr keyword -- Variadic templates -- Migrating to C++11 -- C++14 API features -- The auto return type -- The deprecated attribute -- Variable templates -- Const expression improvements -- Binary literals and digit separators -- Migrating to C++14 -- C++17 API features -- Inline variables -- String views -- Optional -- Any -- Variant -- Nested namespaces -- Fold expressions -- Checking for header availability -- Byte type…”

Tabla de Contenidos: “…Concept 4.1 Biologists use microscopes and biochemistry to study cells -- Microscopy -- Cell Fractionation -- Concept 4.2 Eukaryotic cells have internal membranes that compartmentalize their functions -- Comparing Prokaryotic and Eukaryotic Cells -- A Panoramic View of the Eukaryotic Cell -- Concept 4.3 The eukaryotic cell's genetic instructions are housed in the nucleus and carried out by the ribosomes -- The Nucleus: Information Central -- Ribosomes: Protein Factories -- Concept 4.4 The endomembrane system regulates protein traffic and performs metabolic functions -- The Endoplasmic Reticulum: Biosynthetic Factory -- The Golgi Apparatus: Shipping and Receiving Center -- Lysosomes: Digestive Compartments -- Vacuoles: Diverse Compartments -- The Endomembrane System: A Review -- Concept 4.5 Mitochondria and chloroplasts change energy from one form to another -- The Evolutionary Origins of Mitochondria and Chloroplasts -- Mitochondria: Chemical Energy Conversion -- Chloroplasts: Capture of Light Energy -- Peroxisomes: Oxidation -- Concept 4.6 The cytoskeleton is a network of fibers that organizes structures and activities in the cell -- Roles of the Cytoskeleton: Support and Motility -- Components of the Cytoskeleton -- Concept 4.7 Extracellular components and connections between cells help coordinate cellular activities -- Cell Walls of Plants -- The Extracellular Matrix (ECM) of Animal Cells -- Cell Junctions -- Concept 4.8 A cell is greater than the sum of its parts -- 5 Membrane Transport and Cell Signaling -- Overview Life at the Edge -- The Fluidity of Membranes -- Evolution of Differences in Membrane Lipid Composition -- Membrane Proteins and Their Functions -- The Role of Membrane Carbohydrates in Cell-Cell Recognition -- Synthesis and Sidedness of Membranes -- Concept 5.2 Membrane structure results in selective permeability…”

Tabla de Contenidos: “…Institutional framework -- 5.3.2. Conversion of existing schemes -- 5.3.3. Required scale -- 5.4. …”

Tabla de Contenidos: “…Intersecting lines -- Polygons in the database -- Point in polygon -- Summary -- Chapter 4: Data Types, Storage, and Conversion -- Raster and vector data -- Shapefiles -- GeoJSON -- KML -- GeoPackage -- Raster data formats -- Reading and writing vector data with GeoPandas -- Reading and writing vector data with OGR -- Reading and writing raster data with Rasterio -- Reading and writing raster data using GDAL -- Summary -- Chapter 5: Vector Data Analysis -- OGR Simple Features Library -- OGR batch commands -- ogrmerge -- The OGR library and Python bindings -- OGR's main modules and classes -- Creating polygon geometry with OGR -- Creating polygon geometry from GeoJSON -- Basic geometric operations -- Writing polygon data to a newly created shapefile -- Using a spatial filter to select features -- Shapely and Fiona -- Shapely objects and classes -- Shapely methods for geospatial analysis -- Fiona's data model -- Creating geometries with Shapely -- Applying geometrical methods with Shapely -- Reading JSON geometries with Shapely -- Reading data with Fiona -- Accessing vector geometry in shapefiles using Shapely and Fiona -- GeoPandas -- Geospatial analysis with GeoPandas -- Selecting and plotting geometry data with GeoPandas and Matplotlib -- Mapping wildfire data with GeoPandas -- Why data inspection matters -- Summary -- Chapter 6: Raster Data Processing -- Raster operations using GDAL -- Using the GDAL library to load and query rasters -- Using GDAL to create rasters -- Raster operations using PostgreSQL -- Loading rasters into PostgreSQL -- Performing queries on rasters using PostgreSQL -- Querying raster metadata -- Queries returning geometry -- Queries returning values -- Summary -- Chapter 7: Geoprocessing with Geodatabases -- A crime dashboard -- Building a crime database -- Creating the tables -- Populating the data -- Mapping queries…”

Tabla de Contenidos: “…Assignment with types on the right -- Assignment with types on the left -- Value and reference types -- Type conversion -- Variable commands -- Get-Variable -- New-Variable -- Set-Variable -- Remove-Variable -- Clear-Variable -- Variable provider -- Variable scope -- Accessing variables -- Scope modifiers -- Numeric scopes -- Private variables -- About arrays -- Array type -- Creation by assignment -- Creating an array -- Arrays with a type -- Adding elements to an array -- List and ArrayList -- Selecting elements from an array -- Changing element values in an array -- Removing elements -- Removing elements by index -- Filling variables from arrays -- Multi-dimensional and jagged arrays -- About hashtables -- Creating a Hashtable -- Adding, changing, and removing keys -- Using a hashtable to filter -- Enumerating a Hashtable -- About Ordered -- Summary -- Chapter 4: Working with Objects in PowerShell -- Pipelines -- Standard output -- Non-standard output -- The Object pipeline -- Members -- The Get-Member command -- Accessing object properties -- Access modifiers -- Using methods -- Return types and argument types -- Creating and modifying objects -- Using PSCustomObject -- The New-Object command -- The Add-Member command -- Add-Member and custom objects -- Enumerating and filtering -- The ForEach-Object command -- Begin and End parameters -- The Parallel parameter -- The MemberName parameter -- The Where-Object command -- Selecting and sorting -- The Select-Object command -- Calculated properties -- The ExpandProperty parameter -- The Unique parameter -- Property sets -- The Sort-Object command -- The Unique parameter -- Grouping and measuring -- The Group-Object command -- The Measure-Object command -- Comparing -- Importing, exporting, and converting -- The Export-Csv command -- The Import-Csv command -- Export-Clixml and Import-Clixml…”

Tabla de Contenidos: “…Cover -- Title Page -- Copyright and Credits -- Foreword -- Contributors -- Table of Contents -- Preface -- Part 1: Introducing OpenAI's Whisper -- Chapter 1: Unveiling Whisper - Introducing OpenAI's Whisper -- Technical requirements -- Deconstructing OpenAI's Whisper -- The marvel of human vocalization - Understanding voice and speech -- Understanding the intricacies of speech recognition -- OpenAI's Whisper - A technological parallel -- The evolution of speech recognition and the emergence of OpenAI's Whisper -- Exploring key features and capabilities of Whisper -- Speech-to-text conversion -- Translation capabilities -- Support for diverse file formats -- Ease of use -- Multilingual capabilities -- Large input handling -- Prompts for specialized vocabularies -- Integration with GPT models -- Fine-tunability -- Voice synthesis -- Speech diarization -- Setting up Whisper -- Using Whisper via Hugging Face's web interface -- Using Whisper via Google Colaboratory -- Expanding on the basic usage of Whisper -- Summary -- Chapter 2: Understanding the Core Mechanisms of Whisper -- Technical requirements -- Delving deeper into ASR systems -- Definition and purpose of ASR systems -- ASR in the real world -- Brief history and evolution of ASR technology -- The early days - Pattern recognition approaches -- Statistical approaches emerge - Hidden Markov models and n-gram models -- The deep learning breakthrough -- Ongoing innovations -- Exploring the Whisper ASR system -- Understanding the trade-offs - End-to-end versus hybrid models -- Combining connectionist temporal classification and transformer models in Whisper -- The role of linguistic knowledge in Whisper -- Understanding Whisper's components and functions -- Audio input and preprocessing -- Acoustic modeling -- Language modeling -- Decoding -- Postprocessing…”

“…Ofrecemos las trascripción íntegra del único ejemplar conocido de la edicón hecha en Sevilla y en 1520 por el impresor salmantino Jun de Varela, texto idéntico o muy similar al que en el período 1521-1522 fue libro de cabecera del convaleciente Íñigo de Loyola, cuya conversión a Dios acompañó e inspiró…”

Tabla de Contenidos: “….- Fórmulas y listas de candidatos -- ◊ Cámara Nacional Electoral - Causa: "Mozzi Germán Diego s/acción declarativa de inconstitucionalidad -arts. 158 y 159 del CEN" - Fallos CNE 3069/2002 -- 4.- Conversión de votos en bancas o escaños -- a) Cómputo de los votos en blanco…”

Tabla de Contenidos: “…Chemical Thermodynamics Applied in Bioengineering -- Summary -- 9.0 Introduction -- 9.1 Chemical Equilibrium and Thermodynamic State Functions -- 9.2 Thermodynamic Properties Obtained from Galvanic Cells -- 9.3 Conversion of Free Energy Harbored in NADH and FADH2 to ATP in Oxidative Phosphorylation…”

Tabla de Contenidos: “…1.11 Logical Equivalences -- 1.12 Another Equivalence -- 1.13 Negation of Conditionals -- 1.14 Variations on a Theme -- 1.15 Translations -- 1.15.1 How to Handle Translations -- 1.16 Arguments -- 1.16.1 Showing an Argument as Valid -- 1.16.2 Disjunctive Addition -- 1.16.3 Conjunctive Simplification -- 1.16.4 Disjunctive Simplification -- 1.16.5 Hypothetical Syllogism -- 1.16.6 Dilemma: Proof by Division into Cases -- 1.17 Fallacies -- 1.17 .1 Converse Error -- 1.17.2 Inverse Error -- 1.18 Valid Argument with a False Conclusion -- 1.19 Contradiction Rule -- 1.20 Applications of Boolean Expressions -- 1.21 Logic Gates -- 1.21.1 AND Gates, OR Gates -- 1.21.2 Why Not Implication Gates -- 1.22 How to Construct Circuits -- 1.23 How to Derive a Boolean Expression -- 1.24 Creating a Circuit from Truth Tables -- 1.25 Adders -- 1.26 Predicate Calculus -- 1.27 Boolean Formulas -- 1.28 Understanding Quantifiers -- 1.29 Negation of Quantifiers -- 1.30 Vacuously True Statements -- 1.31 Normal Forms in Propositional Logic -- 1.32 Normal Forms in Predicate Logic -- 1.33 The Resolution Principle -- 1.34 Parenthesized Infix Notation and Polish Notation -- Chapter 2: Set Theory -- 2.1 Definitions -- 2.2 Set Specification -- 2.2.1 Explicit -- 2.2.2 By Properties -- 2.2.3 Grammar -- 2.3 Set Operations -- 2.3.1 Definitions -- 2.3.2 Properties -- 2.4 Characteristic Function -- 2.4.1 Properties of Characteristic Function -- 2.4.2 Computer Representation of Sets and Subsets -- 2.5 Fuzzy Set Theory -- 2.5.1 Introduction -- 2.6 Basic Notions of Fuzzy Set -- 2.6.1 The Concept of Fuzzy Subset -- 2.6.2 The Algebra of Fuzzy Subsets -- 2.6.3 Other Important Notions -- 2.6.4 Fuzzy Relations -- Chapter 3: Relations -- 3.1 Operations on Relations -- 3.1.1 Set Operations -- 3.1.2 Inverse -- 3.1.3 Composition -- 3.1.4 Closure -- 3.2 Computing the Transitive Closure…”

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: “….); 3.4.2 EL CONTROLADOR DE MEMORIA; 3.4.3 FORMATO FÍSICO DE LOS MÓDULOS; 3.4.4 MEMORIA EN CUANTO A SU TECNOLOGÍA; 3.5 TARJETAS GRÁFICAS; 3.5.1 CARACTERÍSTICAS PRINCIPALES; 3.5.2 CONVERSIÓN DIGITAL/ANALÓGICA; 3.5.3 VÍDEO DIGITAL; 3.5.4 PUERTOS PARA VÍDEO: AGP Y PCI EXPRESS; 3.6 LAS TARJETAS DE SONIDO…”

Tabla de Contenidos: “…NÚMERO DE ERRORES POR UNIDAD DE TIEMPO -- NÚMERO DE TAREAS QUE PUEDEN REALIZARSE -- PORCENTAJE DE ENLACES ROTOS -- PORCENTAJE DE PRESENCIA DE PROPIEDADES EN LOS OBJETOS O ELEMENTOS -- PORCENTAJE DE TAREAS FINALIZADAS CON ÉXITO -- PORCENTAJE DE TAREAS FINALIZADAS CON ÉXITO AL PRIMER INTENTO -- PORCENTAJE DE USUARIOS CAPACES DE FINALIZAR LAS TAREAS CLAVE SIN AYUDA -- TIEMPO DE PERMANENCIA -- TIEMPO DE FINALIZACIÓN DE LA TAREA -- TIEMPO DE LATENCIA -- MÉTRICAS CUALITATIVAS -- DIFICULTAD DE LA TAREA -- EXPECTATIVAS -- FACILIDAD DE MANTENIMIENTO -- NIVEL DE SATISFACCIÓN DE LA PRUEBA -- TIEMPO DE REACCIÓN DEL USUARIO -- OTRAS MÉTRICAS DE INTERÉS -- CLICK THROUGH RATE (CTR) -- PÁGINAS VISTAS / CLICS -- TASA DE CONVERSIÓN -- TASA DE REBOTE -- TICKET MEDIO -- 6- MÉTODOS DE EVALUACIÓN -- EVALUACIÓN HEURÍSTICA -- TEST HEURÍSTICO -- EJEMPLO DE CUESTIONARIO DE EVALUACIÓN HEURÍSTICA -- WALKTHROUGHS (RECORRIDO COGNITIVO) -- ANÁLISIS DE ACCIONES -- INSPECCIÓN DE CARACTERÍSTICAS -- INSPECCIÓN DE ESTÁNDARES -- FOCUS GROUP (GRUPOS DE DISCUSIÓN) -- ETHNOGRAPHIC RESEARCH (INVESTIGACIÓN ETNOGRÁFICA) -- LOGGING (GRABACIÓN DEL USO) -- ANALÍTICA DE FORMULARIOS -- SURVEYS (CUESTIONARIOS) -- ENTREVISTAS -- THINKING ALOUD (PENSANDO EN VOZ ALTA) -- CARD SORTING (CLASIFICACIÓN DE TARJETAS) -- USABILITY TESTING (PRUEBAS DE USABILIDAD) -- ¿CUÁNDO SE DEBE APLICAR UN TEST DE USABILIDAD? …”

Tabla de Contenidos: “…Getting started with CQL -- Creating a keyspace -- Single data center example -- Multi-data center example -- Creating a table -- Simple table example -- Clustering key example -- Composite partition key example -- Table options -- Data types -- Type conversion -- The primary key -- Designing a primary key -- Selecting a good partition key -- Selecting a good clustering key -- Querying data -- The IN operator -- Writing data -- Inserting data -- Updating data -- Deleting data -- Lightweight transactions -- Executing a BATCH statement -- The expiring cell -- Altering a keyspace -- Dropping a keyspace -- Altering a table -- Truncating a table -- Dropping a table -- Truncate versus drop -- Creating an index -- Caution with implementing secondary indexes -- Dropping an index -- Creating a custom data type -- Altering a custom type -- Dropping a custom type -- User management -- Creating a user and role -- Altering a user and role -- Dropping a user and role -- Granting permissions -- Revoking permissions -- Other CQL commands -- COUNT -- DISTINCT -- LIMIT -- STATIC -- User-defined functions -- cqlsh commands -- CONSISTENCY -- COPY -- DESCRIBE -- TRACING -- Summary -- Chapter 4: Configuring a Cluster -- Evaluating instance requirements -- RAM -- CPU -- Disk -- Solid state drives -- Cloud storage offerings -- SAN and NAS -- Network -- Public cloud networks -- Firewall considerations -- Strategy for many small instances versus few large instances -- Operating system optimizations -- Disable swap -- XFS -- Limits -- limits.conf -- sysctl.conf -- Time synchronization -- Configuring the JVM -- Garbage collection -- CMS -- G1GC -- Garbage collection with Cassandra -- Installation of JVM -- JCE -- Configuring Cassandra -- cassandra.yaml -- cassandra-env.sh -- cassandra-rackdc.properties -- dc -- rack -- dc_suffix -- prefer_local -- cassandra-topology.properties…”

Tabla de Contenidos: “…Superficies consacrées à l'agriculture biologique et en phase de conversion dans l'Union européenne (1985-2001) -- Figure 2.1.2. …”

Tabla de Contenidos: “…Real-life applications for labeling audio data -- Audio data fundamentals -- Hands-on with analyzing audio data -- Example code for loading and analyzing sample audio file -- Best practices for audio format conversion -- Example code for audio data cleaning -- Extracting properties from audio data -- Tempo -- Chroma features -- Mel-frequency cepstral coefficients (MFCCs) -- Zero-crossing rate -- Spectral contrast -- Considerations for extracting properties -- Visualizing audio data with matplotlib and Librosa -- Waveform visualization -- Loudness visualization -- Spectrogram visualization -- Mel spectrogram visualization -- Considerations for visualizations -- Ethical implications of audio data -- Recent advances in audio data analysis -- Troubleshooting common issues during data analysis -- Troubleshooting common installation issues for audio libraries -- Summary -- Chapter 11: Labeling Audio Data -- Technical requirements -- Downloading FFmpeg -- Azure Machine Learning -- Real-time voice classification with Random Forest -- Transcribing audio using the OpenAI Whisper model -- Step 1 - importing the Whisper model -- Step 2 - loading the base Whisper model -- Step 3 - setting up FFmpeg -- Step 4 - transcribing the YouTube audio using the Whisper model -- Classifying a transcription using Hugging Face transformers -- Hands-on - labeling audio data using a CNN -- Exploring audio data augmentation -- Introducing Azure Cognitive Services - the speech service -- Creating an Azure Speech service -- Speech to text -- Speech translation -- Summary -- Chapter 12: Hands-On Exploring Data Labeling Tools -- Technical requirements -- Azure Machine Learning data labeling -- Label Studio -- pyOpenAnnotate -- Data labeling using Azure Machine Learning -- Benefits of data labeling with Azure Machine Learning -- Data labeling steps using Azure Machine Learning…”