Tabla de Contenidos: “…Conclusions -- Notes -- Chapitre 3. La vision norvégienne de la formation tout au long de la vie : du berceau à la tombe -- 3.1. …”

Tabla de Contenidos: “…Estimaciones sobre elusión y evasión de impuestos expresadas como porcentaje del PIB -- La reforma tributaria debe ir acompañada de una reforma institucional -- Visión general de los planes de reformas tributarias -- Tabla 1.3. …”

Tabla de Contenidos:

“…On cherche aujourd'hui à comprendre et à mesurer cette activité afin que les organisations aient de meilleurs résultats et que les gouvernements puissent concevoir des politiques en vue de promouvoir ces pratiques. Ce livre offre une vision synthétique des résultats de la première enquête internationale systématique sur la gestion des connaissances réalisée par les agences nationales de statistiques du Canada, Danemark, France et Allemagne. …”

Tabla de Contenidos: “…5.4.1.2 Crop Monitoring and Disease Detection -- 5.4.1.3 Autonomous Farming and Robotics -- 5.4.1.4 Supply Chain Optimization -- 5.4.1.5 Data-Driven Farm Management -- 5.4.2 Computer Vision -- 5.4.2.1 Crop Monitoring and Disease Detection -- 5.4.2.2 Weed Identification and Management -- 5.4.2.3 Yield Estimation and Quality Assessment -- 5.4.2.4 Smart Irrigation and Resource Management -- 5.4.2.5 Plant Breeding and Genetic Improvement -- 5.4.2.6 Farm Automation and Robotics -- 5.4.2.7 Decision Support Systems -- 5.5 Introduction and Theory of IoT -- 5.5.1 Perception Layer -- 5.5.2 Network Layer -- 5.5.3 Middleware Layer -- 5.5.4 Service Layer -- 5.5.5 Analytics Layer -- 5.5.6 End-User Layer -- 5.6 Several Sensors and How They are Used in Agriculture -- 5.6.1 Level Sensors -- 5.6.1.1 Continuous Measurements -- 5.6.1.2 Point-Level Measurements -- 5.6.2 Temperature Sensors -- 5.6.3 Proximity Sensors -- 5.6.4 Infrared Sensors -- 5.6.5 Touch Sensors -- 5.7 Centralized Agriculture System -- 5.8 Conclusion -- References -- Chapter 6 Concepts of Robotics, AI, and Internet of Things (IoT) in Agriculture -- 6.1 Introduction -- 6.1.1 The Implantation of Information and Commutation Technology in Agriculture Sector -- 6.2 General Challenges Faced in the Agriculture Industry -- 6.2.1 Growing Demand for Food -- 6.2.2 Limited Resources -- 6.2.3 Climate Change -- 6.2.4 Labor Shortages -- 6.2.5 Food Demand -- 6.2.6 Specific Challenges in the Deployment of Technology of Robotics, AI, and IoT in Agriculture -- 6.3 Role of Robotics, AI, and IoT in Agriculture -- 6.4 Benefits of Robotic and AI in Improving Agriculture -- 6.4.1 Increased Efficiency -- 6.4.2 Improved Precision -- 6.4.3 Reduced Labor Costs -- 6.4.4 Sustainability -- 6.5 Collecting Data and Performing Analyses With the Help of the Internet of Things…”

Tabla de Contenidos: “…6.7.4 Canonical Correlation Forest -- 6.7.5 Extreme Gradient Boosting -- 6.7.6 Light Gradient Boosting Machines -- 6.7.7 Gradient Boosting Machines -- 6.7.8 Categorical Boosting -- 6.7.9 Natural Gradient Boosting -- 6.8 Concluding Remarks -- References -- Chapter 7 Deep Learning -- 7.1 Fundamentals -- 7.1.1 Stochastic Gradient Descent -- 7.1.2 Backpropagation -- 7.1.3 Regularization -- 7.1.3.1 Weight Decay -- 7.1.3.2 Dropout -- 7.1.3.3 Data Augmentation -- 7.1.3.4 Early Stopping -- 7.1.4 Activation Functions -- 7.1.5 Loss Functions -- 7.2 Neural Network Architectures -- 7.2.1 Multilayer Perceptron -- 7.2.2 Convolutional Neural Networks -- 7.2.2.1 Convolutional Layers -- 7.2.2.2 Pooling Layers -- 7.2.2.3 Fully Connected Layers -- 7.2.2.4 Receptive Field and Feature Map -- 7.2.2.5 Training CNNs -- 7.2.2.6 Data Structures in CNNs -- 7.2.2.7 Evolving Trends in CNN Design -- 7.2.3 Recurrent Neural Networks -- 7.2.3.1 Long- and Short-Term Memory -- 7.2.3.2 Gated Recurrent Unit -- 7.2.4 Vision Transformers -- 7.2.5 Deep Multilayer Perceptron -- 7.2.6 Generative Adversarial Networks -- 7.2.7 Deep Autoencoders -- 7.2.7.1 Undercomplete Autoencoders -- 7.2.7.2 Regularized Autoencoders -- 7.2.7.3 Sparse Autoencoders -- 7.2.7.4 Denoising Autoencoders -- 7.2.7.5 Variational Autoencoders -- 7.3 Learning Paradigms -- 7.3.1 Transfer Learning -- 7.3.2 Semi-Supervised Learning -- 7.3.3 Reinforcement Learning -- 7.3.4 Active Learning -- 7.3.5 Multitask Learning -- 7.4 Application of DL in Remote Sensing -- 7.4.1 Semantic Segmentation -- 7.4.2 Object Detection -- 7.4.3 Scene Classification -- 7.4.4 Change Detection -- 7.5 Concluding Remarks -- References -- Chapter 8 Object-B ased Image Analysis -- 8.1 Clustering-Based Segmentation -- 8.1.1 Mean-Shift Algorithm -- 8.1.2 Superpixel Segmentation -- 8.2 Thresholding-Based Segmentation -- 8.3 Edge-Based Segmentation…”

Tabla de Contenidos: “…7.3.3 Methodology Flow Chart -- 7.3.4 Data Pre-Processing -- 7.3.5 Models Deployed -- 7.3.6 Training and Testing -- 7.4 Analysis -- 7.4.1 Datasets -- 7.4.2 Feature Extraction -- 7.4.3 Splitting of Data into Samples -- 7.4.4 Algorithms Used -- 7.4.4.1 Multinomial Logistic Regression -- 7.4.4.2 K-Nearest Neighbors -- 7.4.4.3 Decision Tree -- 7.4.4.4 Support Vector Machine (SVM) -- 7.4.4.5 Random Forest -- 7.5 Results and Discussion -- 7.5.1 Importance of Classification Reports -- 7.5.2 Importance of Confusion Matrices -- 7.5.3 Decision Tree -- 7.5.4 Random Forest -- 7.5.5 K-Nearest Neighbors -- 7.5.6 Logistic Regression -- 7.5.7 Support Vector Machine -- 7.5.8 Comparison of the Algorithms -- 7.5.8.1 Accuracies -- 7.5.8.2 Precision and Recall -- 7.6 Conclusions -- 7.7 Scope of Future Work -- References -- Chapter 8 Smart Vision-Based Sensing and Monitoring of Power Plants for a Clean Environment -- 8.1 Introduction -- 8.1.1 Color Image Processing -- 8.1.2 Motivation -- 8.1.3 Objectives -- 8.2 Literature Review -- 8.2.1 Gas Turbine Power Plants -- 8.2.2 Artificial Intelligent Methods -- 8.3 Materials and Methods -- 8.3.1 Feature Extraction -- 8.3.2 Classification -- 8.4 Results and Discussion -- 8.4.1 Fisher's Linear Discriminant Function (FLDA) and Curvelet -- 8.5 Conclusion -- 8.5.1 Future Scope of Work -- References -- Chapter 9 Implementation of FEM and Machine Learning Algorithms in the Design and Manufacturing of Laminated Composite Plate -- Abbreviations -- 9.1 Introduction -- 9.2 Numerical Experimentation Program -- 9.3 Discussion of the Results -- 9.4 Conclusion -- Acknowledgements -- References -- Part II: Integration of Digital Technologies to Operations -- Chapter 10 Edge Computing-Based Conditional Monitoring -- 10.1 Introduction -- 10.1.1 Problem Statement -- 10.2 Literature Review -- 10.3 Edge Computing -- 10.4 Methodology…”

“…Metaheuristic Optimization Algorithms have become indispensable tools, with applications in data analysis, text mining, classification problems, computer vision, image analysis, pattern recognition, medicine, and many others. …”

Tabla de Contenidos: “…References -- Chapter 9. Computer Vision-based Edge Computing System to Detect Health Informatics for Oral Pre-Cancer -- 9.1. …”

Tabla de Contenidos: “…LAS ARTES DEL LENGUAJE: POESÍA Y LENGUAJE --• La Poesía: un caso de lenguaje --• Evolución de las artes poéticas y su inclusión en Literatura --• La autoría poética --• Reglas del juego poético --• Regulación rítmica y métrica --• Palabras en juego y juego de palabras --• La competencia poética del niño --• La visión poética --• Formalización y memoria --• Poesía contada y cantada --• La utilidad de la Poesía --4.1. …”
Enlace del recurso

Tabla de Contenidos: “…Efectos del entrenamiento -- Efectos del entrenamiento: visión general -- Efecto agudo del entrenamiento -- Efecto agudo del entrenamiento calculado con indicadores deportivos específicos -- Efecto agudo del entrenamiento calculado con variables psicofisiológicas -- Programación del efecto agudo del entrenamiento -- Efecto inmediato del entrenamiento -- Indicadores del efecto inmediato del entrenamiento -- Control del efecto inmediato del entrenamiento -- Efecto acumulativo del entrenamiento -- Índice de mejora de las variables fisiológicas -- Mejora de las capacidades motrices -- Mejora del rendimiento deportivo -- Comentarios finales -- Efecto retardado del entrenamiento -- Efecto residual del entrenamiento -- Concepto básico y tipos de efectos residuales del entrenamiento -- Factores que afectan los efectos residuales del entrenamiento a corto plazo -- Resumen…”

Tabla de Contenidos: “…Relativas y relativos en español (visión integrada) -- 1. Las relativas especificativas -- 1.1. …”

Tabla de Contenidos: “…-- B. 9.1-31: La conversión de Saulo -- Excurso: El llamado y los llamados -- C. 9.32-11.18: La obra de Pedro -- Excurso: El gran vuelco se revela también en la misión -- D. 11.19-30: La iglesia de Antioquía entra en escena -- E. 12.1-24: La persecución de Herodes -- V. 12.25-15.35: La misión se define -- A. 12.25-13.3: El envío -- Excurso: Misión y comunidad -- B. 13.4-12: Chipre -- Excurso: Saulo, quien también es Pablo -- C. 13.13-51a: Antioquía de Pisidia -- Excurso: Creyentes evangelizadores, pero celosos de los evangelizados -- D. 13.51b-14.6a: Iconio -- E. 14.6b-21a: Listra y Derbe -- F. 14.21b-28: El regreso -- G. 15.1-35: El concilio de Jerusalén -- Excurso: Misión y visión…”

Tabla de Contenidos: “…, o cómo el tiempo dramático modela el tiempo histórico / Françoise Gilbert -- Tiempo dramático e intriga secundaria en la comedia histórica de Lope de Vega / Alexandre Roquain -- Alternancia temporal y tensión dramática en La firmeza en la ausencia de Leonor de la Cueva / Isabelle Rouane Soupault -- Casandra y el instante : femineidad, tiempo y tragedia en El castigo sin venganza / Milagros Torres -- "La empresa más lucida y más hermosa" de Portugal : clave histórica para la datación de El muerto disimulado de Ángela de Acevedo / Alba Urban Baños -- La materia histórica en un dramaturgo desconocido : la toma de Sevilla por el santo rey Fernando de Cristóbal de Morales / Juan Manuel Carmona Tierno -- "...os iréis para Bolonia marchando" : cambios de espacio dramático en El saco de Roma de Juan de la Cueva / Martina Colombo -- El tratamiento de la historia contemporánea en El sitio de Bredá, comedia de Calderón / Lola González Martínez -- Acercamiento al problema de la representación del príncipe y la razón de estado : mayor monstruo del mundo / Aurora González Roldán -- Historia trágica y pasión individual en La cisma de Inglaterra, una visión crítica de la privanza / Susana Hernández Araico -- Historia(s) de amor y amistad : cómo han de ser los amigos y El amor y el amistad de Tirso de Molina / Isabel Ibáñez -- Rememorar el pasado como "lectio": Los Esforcias de Milán, una comedia histórica de intrigas palaciegas en la corte de Felipe IV / Elena Martínez Carro -- Historia y teatro ; Don Pelayo y Covadonga en 1613, en 1808 y en 1855 / C. …”

Tabla de Contenidos: “…Creating reports in Data Studio -- Summary -- Chapter 5: Transforming Your Data -- How to clean and prepare the data -- Google Cloud Dataprep -- Exploring Dataprep console -- Removing empty cells -- Replacing incorrect values -- Mismatched values -- Finding outliers in the data -- Visual functionality -- Statistical information -- Removing outliers -- Run Job -- Scale of features -- Min-max normalization -- z score standardization -- Google Cloud Dataflow -- Summary -- Chapter 6: Essential Machine Learning -- Applications of machine learning -- Financial services -- Retail industry -- Telecom industry -- Supervised and unsupervised machine learning -- Overview of machine learning techniques -- Objective function in regression -- Linear regression -- Decision tree -- Random forest -- Gradient boosting -- Neural network -- Logistic regression -- Objective function in classification -- Data splitting -- Measuring the accuracy of a model -- Absolute error -- Root mean square error -- The difference between machine learning and deep learning -- Applications of deep learning -- Summary -- Chapter 7: Google Machine Learning APIs -- Vision API -- Enabling the API -- Opening an instance -- Creating an instance using Cloud Shell -- Label detection -- Text detection -- Logo detection -- Landmark detection -- Cloud Translation API -- Enabling the API -- Natural Language API -- Speech-to-text API -- Video Intelligence API -- Summary -- Chapter 8: Creating ML Applications with Firebase -- Features of Firebase -- Building a web application -- Building a mobile application -- Summary -- Chapter 9: Neural Networks with TensorFlow and Keras -- Overview of a neural network -- Setting up Google Cloud Datalab -- Installing and importing the required packages -- Working details of a simple neural network -- Backpropagation -- Implementing a simple neural network in Keras…”

Tabla de Contenidos: “…Intro -- Contents -- About the Authors -- Forewords -- Acknowledgments -- Introduction -- Part I: Getting Started -- Chapter 1: Welcome to the World -- Top Ten Experiences -- The Heart of Agile Teams at 10Pines (Page 32) -- Glad, Mad, Sad in Japan (Page 157) -- Building Trust, Learning, and Understanding: An Agile Approach to Project Discovery (Page 81) -- Agile Organizations Set the Stage for Emergent Leaders (Page 252) -- Finding My Voice (Page 308) -- Trust: The Basic Building Block of Agile Teams (Page 115) -- Forced Fun (Page 278) -- Accelerating the Supply Chain of Goods and Services (Page 62) -- Retrospectives at Every Level (Page 51) -- Learntor: On a Mission to Create a Level Playing Field for Africa (Page 325) -- Understanding Culture -- When Cultures Collide -- At the Risk of Stereotyping -- Categorizing Behaviors -- The Hofstede Model -- The Lewis Model -- A Basis for Study: Cultural Behaviors and the Agile Values -- On the Road -- Part II: South America -- Agile Community Events and Meetups -- Chapter 2: Argentina -- History -- Insights -- Heart of Agile Teams at 10Pines -- People -- Great Environment -- Vision -- Self-Organization -- Communication -- Conclusion -- Getting On and Around -- Agile Community Events and Meetups -- Chapter 3: Chile -- History -- Insights -- The Accountant That Automated Himself Out of a Job and Into Development -- Getting On and Around -- Retrospectives at Every Level -- Agile Community Events and Meetups -- Chapter 4: Colombia -- History -- Insights -- Lean Change Management at a Hardware Retailer4 -- Accelerating the Supply Chain of Goods and Services -- Hypothesis 1 - Increased collaboration and shared responsibility -- Hypothesis 2 - Improved quality as perceived by the internal client -- Hypothesis 3 - Reduced delivery times of contract completion -- Geniio: Generating Integral and Timely Information…”

Tabla de Contenidos: “…Intro -- Editorial -- Acknowledgments -- Executive Summary -- Frontiers of smart education technology: Opportunities and challenges -- Current frontiers of digitalisation in education -- Key opportunities -- Policy pointers -- Concluding remarks -- Artificial intelligence in education: Bringing it all together -- Smart education technologies: Definitions and context -- The uses of artificial intelligence in classrooms and educational systems -- Future potentials -- Personalisation of learning: Towards hybrid human-AI learning technologies -- Hybrid human-AI systems: specifying the role of teachers and technology -- Speculations for the future: the ultimate role of AI -- Personalisation based on students' knowledge -- Personalisation of learning based on self-regulated learning -- Challenges for the future of personalisation of learning -- Improving student engagement in and with digital learning technologies -- The importance of engagement -- Def ining engagement -- Measuring engagement -- Improving engagement -- Conclusions and future directions -- Classroom analytics: Zooming out from a pupil to a classroom -- The vision: Classrooms as a digital system -- How did we get there? …”

Tabla de Contenidos: “…- Peter Gocke -- V Ambulante Versorgung -- 1 Die digitale Arztpraxis - Vision oder Fiktion? - lens Naumann -- 2 Patientenversorgung 4.0 - Suprasektoral und individualisiert - Lutz-O. …”

Tabla de Contenidos: “…Business Management and Strategy -- Introduction -- General Business Principles -- Business Entities, Functions, and Structures -- Less Traditional Structures -- HR as a Strategic Partner -- Mission, Vision, and Values -- Strategic Planning and Analyses -- Business Metrics -- Technology at Work -- Standing on the Shoulders of Giants: Strategies' Leading Experts -- Organizational Development (OD) -- Change Management -- The Psychology of Decision Making -- Project Management -- Organizational Restructuring -- The Role of HR -- Continuing Development -- Corporate Governance -- Suggested Study or Organizational Audit Activities -- References -- Chapter 3. …”

Tabla de Contenidos: “…-- When to Use Footprint Optimization -- Footprint Optimization: How It Works -- Step 1: Identify Business Requirements -- Step 2: Site Performance Check -- Step 3: Ideal Vision and Value-Add Strategy -- Step 4: Concept Development and Evaluation -- Step 5: Business Case and Road Map -- Chapter 10: Process Excellence: Simplify Work and Minimize Bureaucracy -- What Is Process Excellence? …”