Tabla de Contenidos: “…11.3 Converting column or index values to datetimes -- 11.4 Using the DatetimeProperties object -- 11.5 Adding and subtracting durations of time -- 11.6 Date offsets -- 11.7 The Timedelta object -- 11.8 Coding challenge -- 11.8.1 Problems -- 11.8.2 Solutions -- Summary -- 12 Imports and exports -- 12.1 Reading from and writing to JSON files -- 12.1.1 Loading a JSON file Into a DataFrame -- 12.1.2 Exporting a DataFrame to a JSON file -- 12.2 Reading from and writing to CSV files -- 12.3 Reading from and writing to Excel workbooks -- 12.3.1 Installing the xlrd and openpyxl libraries in an Anaconda environment -- 12.3.2 Importing Excel workbooks -- 12.3.3 Exporting Excel workbooks -- 12.4 Coding challenge -- 12.4.1 Problems -- 12.4.2 Solutions -- Summary -- 13 Configuring pandas -- 13.1 Getting and setting pandas options -- 13.2 Precision -- 13.3 Maximum column width -- 13.4 Chop threshold -- 13.5 Option context -- Summary -- 14 Visualization -- 14.1 Installing matplotlib -- 14.2 Line charts -- 14.3 Bar graphs -- 14.4 Pie charts -- Summary -- Appendix A. …”

Tabla de Contenidos: “…7.3 Forecasting a non-stationary times series -- 7.4 Next steps -- 7.5 Exercises -- 7.5.1 Apply the ARIMA(p,d,q) model on the datasets from chapters 4, 5, and 6 -- Summary -- 8 Accounting for seasonality -- 8.1 Examining the SARIMA(p,d,q)(P,D,Q)m model -- 8.2 Identifying seasonal patterns in a time series -- 8.3 Forecasting the number of monthly air passengers -- 8.3.1 Forecasting with an ARIMA(p,d,q) model -- 8.3.2 Forecasting with a SARIMA(p,d,q)(P,D,Q)m model -- 8.3.3 Comparing the performance of each forecasting method -- 8.4 Next steps -- 8.5 Exercises -- 8.5.1 Apply the SARIMA(p,d,q)(P,D,Q)m model on the Johnson &amp -- Johnson dataset -- Summary -- 9 Adding external variables to our model -- 9.1 Examining the SARIMAX model -- 9.1.1 Exploring the exogenous variables of the US macroeconomics dataset -- 9.1.2 Caveat for using SARIMAX -- 9.2 Forecasting the real GDP using the SARIMAX model -- 9.3 Next steps -- 9.4 Exercises -- 9.4.1 Use all exogenous variables in a SARIMAX model to predict the real GDP -- Summary -- 10 Forecasting multiple time series -- 10.1 Examining the VAR model -- 10.2 Designing a modeling procedure for the VAR(p) model -- 10.2.1 Exploring the Granger causality test -- 10.3 Forecasting real disposable income and real consumption -- 10.4 Next steps -- 10.5 Exercises -- 10.5.1 Use a VARMA model to predict realdpi and realcons -- 10.5.2 Use a VARMAX model to predict realdpi and realcons -- Summary -- 11 Capstone: Forecasting the number of antidiabetic drug prescriptions in Australia -- 11.1 Importing the required libraries and loading the data -- 11.2 Visualizing the series and its components -- 11.3 Modeling the data -- 11.3.1 Performing model selection -- 11.3.2 Conducting residual analysis -- 11.4 Forecasting and evaluating the model's performance -- Next steps -- Part 3. …”

Tabla de Contenidos: “…12.2.4.1 Conversion of Glycerol into Value-Added Product…”

Tabla de Contenidos: “…6.8.3.1 Blockchain Can Store Information Coming from IoT Devices -- 6.8.3.2 Secure Data Storage with Blockchain Distribution -- 6.8.3.3 Data Encryption via Hash Key and Tested by the Miners -- 6.8.3.4 Spoofing Attacks and Data Loss Prevention -- 6.8.3.5 Unauthorized Access Prevention Using Blockchain -- 6.8.3.6 Exclusion of Centralized Cloud Servers -- 6.9 Conclusions -- References -- Chapter 7 Deep Learning Approach to Industrial Energy Sector and Energy Forecasting with Prophet -- 7.1 Introduction -- 7.2 Related Work -- 7.3 Methodology -- 7.3.1 Splitting of Data (Test/Train) -- 7.3.2 Prophet Model -- 7.3.3 Data Cleaning -- 7.3.4 Model Implementation -- 7.4 Results -- 7.4.1 Comparing Forecast to Actuals -- 7.4.2 Adding Holidays -- 7.4.3 Comparing Forecast to Actuals with the Cleaned Data -- 7.5 Conclusion and Future Scope -- References -- Chapter 8 Application of Novel AI Mechanism for Minimizing Private Data Release in Cyber-Physical Systems -- 8.1 Introduction -- 8.2 Related Work -- 8.3 Proposed Mechanism -- 8.4 Experimental Results -- 8.5 Future Directions -- 8.6 Conclusion -- References -- Chapter 9 Environmental and Industrial Applications Using Internet of Things (IoT) -- 9.1 Introduction -- 9.2 IoT-Based Environmental Applications -- 9.3 Smart Environmental Monitoring -- 9.3.1 Air Quality Assessment -- 9.3.2 Water Quality Assessment -- 9.3.3 Soil Quality Assessment -- 9.3.4 Environmental Health-Related to COVID-19 Monitoring -- 9.4 Applications of Sensors Network in Agro-Industrial System -- 9.5 Applications of IoT in Industry -- 9.5.1 Application of IoT in the Autonomous Field -- 9.5.2 Applications of IoT in Software Industries -- 9.5.3 Sensors in Industry -- 9.6 Challenges of IoT Applications in Environmental and Industrial Applications -- 9.7 Conclusions and Recommendations -- Acknowledgments -- References…”

Tabla de Contenidos:

Tabla de Contenidos: “…Deployment Services -- 5.1 Activity Planner -- 5.1.1 Activity Planner components -- 5.1.2 Roles required for the Activity Planner -- 5.1.3 Types of activities -- 5.1.4 Activity Plan Editor -- 5.1.5 Activity Plan Monitor -- 5.1.6 Activity Planner commands -- 5.2 Change Manager -- 5.2.1 Change Manager components -- 5.2.2 Sample Change Manager scenario -- 5.3 Enterprise Directory integration -- 5.3.1 Exchanging data with a directory server -- 5.3.2 Manipulating DirectoryContext objects -- 5.3.3 Directory query libraries and query directories -- 5.4 Resource Manager and pervasive devices -- 5.4.1 Choosing where to install the Resource Manager components -- 5.4.2 Web Gateway installation -- 5.4.3 Web objects -- 5.4.4 Registering the resource types -- 5.4.5 Associating endpoints with the resource gateway -- 5.4.6 Enrolling pervasive devices -- 5.4.7 Installing and configuring devices for resource manager -- 5.4.8 Installing the device agent for Windows CE devices -- 5.4.9 The user ID of palm devices -- 5.4.10 Inventory scans on pervasive devices -- 5.5 Pristine Manager -- 5.5.1 Pristine Manager architecture and new components -- 5.5.2 Supported platforms for pristine installation -- 5.5.3 Key terms -- 5.5.4 Pristine Manager concepts -- 5.5.5 Prerequisites -- 5.5.6 Installing pristine machines -- 5.5.7 Customizing Pristine Manager -- 5.5.8 Adding an Operating System Element to a reference model -- 5.5.9 Pristine Manager commands -- 5.5.10 IBM Tivoli Enterprise Console notification -- Chapter 6. …”

Tabla de Contenidos: “…4.2 A Bit of History About JavaScript -- 4.3 Organization of the Language -- 4.3.1 Basics of Client-side JavaScript -- 4.4 An Example -- 4.5 Data Types -- 4.5.1 Special Numbers -- 4.5.2 Boolean -- 4.5.3 Constants -- 4.5.4 Typeof -- 4.6 Conversions -- 4.7 Basic String Operations -- 4.7.1 Other Common String Operations -- 4.7.2 String Encoding for URIs -- 4.7.3 Reference or Value -- 4.7.4 Regular Expressions -- 4.8 Date Object -- 4.8.1 A Note on Including JavaScript File -- 4.9 Arrays -- 4.9.1 Array Implementation Basics -- 4.9.2 Array and String Operations -- 4.10 Variables and Functions -- 4.10.1 Function Literals -- 4.10.2 Function Arguments -- 4.10.3 Anonymous Functions -- 4.10.4 Inner Functions -- 4.10.5 Closures -- 4.11 Closure Scenarios -- 4.11.1 Simplify Scope -- 4.11.2 Return Methods from Functions -- 4.12 Summary of Ways to Use a Function -- 4.12.1 Client-side Cookies -- 4.13 The Concept of Classes -- 4.13.1 Creating Objects -- 4.13.2 Objects Through Function Constructors -- 4.13.3 Dynamic Addition of Methods-Prototype -- 4.13.4 Inheritance -- 4.14 Execution Contexts -- 4.15 DOM -- 4.15.1 The Bigger Picture of DOM -- 4.15.2 Representing DOM -- 4.15.3 DOM Traversal -- 4.15.4 Accessing Nodes Directly -- 4.15.5 Adding Dynamism-DOM Manipulation -- 4.16 Event Handling -- 4.16.1 Event Onclick -- 4.16.2 Event Onchange -- 4.16.3 Event Onload -- 4.16.4 Mouse Events -- 4.16.5 Default Event Listeners -- 4.16.6 Browser Specific Challenges -- 4.16.7 Event Propagation -- 4.16.8 Other Events -- 4.17 A Shopping Cart Table Sort Example -- 4.17.1 Method InnerHTML -- 4.18 Overall Observations About DOM -- 4.19 Ajax with JavaScript -- 4.19.1 Ajax Introduction -- 4.19.2 Scenarios -- 4.19.3 Technology Components Required for Ajax -- 4.19.4 XMLHttp Request Object -- 4.19.5 A Look at the Steps Involved -- 4.19.6 Sample Ajax Code -- 4.19.7 Ajax - Points of Caution…”

Tabla de Contenidos: “…Basic data transforms -- 5.2.1. Adding new columns -- 5.2.2. Other simple operations -- 5.3. …”

Tabla de Contenidos: “…6.3.2 Incorporation of Missingness -- 6.3.3 Settle on Careful Choices in defining Outcomes -- 6.3.4 Comprehend the Result in the Setting of a Social Insurance Framework -- 6.3.5 Be Careful with Mark Spillage -- 6.4 Inclined Opportunities in Healthcare -- 6.4.1 Automating Clinical Errands during Determination and Treatment -- 6.4.2 Computerizing Clinical Picture Assessment -- 6.4.3 Robotizing Routine Procedures -- 6.4.4 Streamlining Clinical Choice and Practice Support -- 6.4.5 Normalizing Clinical Procedures -- 6.4.6 Incorporating Divided Records -- 6.4.7 Growing Medicinal Capacities: New Skylines in Screening, Analysis and Treatment -- 6.4.8 Growing the Inclusion of Proof -- 6.4.9 Moving towards Constant Social Checking -- 6.5 Population Protection (Crowd Surveillance) -- 6.6 Marketing Strategy -- 6.7 Population Screening -- 6.8 Patient Advocacy -- 6.9 Role of Machine Learning in Society -- 6.10 Ayushman Bharat: A Step Forward -- 6.11 The National E-Health Authority (Neha) -- 6.12 Cancer Screening and Machine Learning -- 6.13 "Sick" Care to "Health" Care: Moving Forward -- 6.14 Machine Learning and Healthcare Opportunities -- 6.14.1 Computerizing Clinical Assignments during Determination and Treatment -- 6.14.2 Robotizing Clinical Picture Assessment -- 6.14.3 Robotizing Routine Procedures -- 6.14.4 Clinical Support and Augmentation -- 6.14.5 Expanding Clinical Capacities -- 6.14.6 Precision Medicine for Early Individualized Treatment -- 6.14.7 Open Doors for Innovative Research -- 6.14.8 Adding Communication to AI and Assessment -- 6.14.9 Distinguishing Representations in a Large and Multi-source Network -- 6.15 Common Machine Learning Applications in Healthcare -- 6.15.1 Machine Learning Application in Drug Discovery -- 6.15.2 Neuroscience and Image Computing -- 6.15.3 Cloud Computing Frameworks in building Machine Learning-based Healthcare…”

Tabla de Contenidos: “…2.6.1 Multilevel Analysis: Example Implementation -- 2.7 Structural Estimation -- 2.7.1 Model Selection -- 2.7.2 An Illustration -- 2.7.3 A Word on Standard Errors -- 2.7.4 Subject Heterogeneity: Finite Mixture Models -- 2.8 Concluding Remarks -- Acknowledgments -- References -- Chapter 3 Incorporating Behavioral Factors into Operations Theory -- 3.1 Types of Behavioral Models -- 3.1.1 Nonstandard Preferences -- 3.1.2 Nonstandard Decision‐making -- 3.1.3 Nonstandard Beliefs -- 3.2 Identifying Which Behavioral Factors to Include -- 3.2.1 Robustly Observed -- 3.2.2 One/A Few Factors Explain Many Phenomena -- 3.2.3 Boundaries and Observed Behavioral Factors -- 3.3 Nesting the Standard Model -- 3.3.1 Reference Dependence -- 3.3.2 Social Preferences and Comparison -- 3.3.3 Quantal Response Equilibrium -- 3.3.4 Cognitive Hierarchy in Games -- 3.3.5 Learning -- 3.3.6 Overconfidence -- 3.4 Developing Behavioral Operations Model -- 3.4.1 Parsimony Is Still Important -- 3.4.2 Adding One Versus Many Behavioral Factors -- 3.5 Modeling for Testable Predictions -- References -- Chapter 4 Behavioral Empirics and Field Experiments -- 4.1 Going to the Field to Study Behavioral Operations -- 4.1.1 External Validity and Identification of Effect Size -- 4.1.2 Overcome Observer Bias -- 4.1.3 Context -- 4.1.4 Time‐based Effects -- 4.1.5 Beyond Individual Decision‐making -- 4.2 Analyzing the Data: Common Empirical Methods -- 4.2.1 Reduced Form Analysis of Panel Data -- 4.2.2 Difference in Differences -- 4.2.3 Program or Policy Evaluations -- 4.2.4 Regression Discontinuity -- 4.2.5 Structural Estimation -- 4.3 Field Experiments (Creating the Data) -- 4.3.1 Experimental Design -- 4.3.2 Field Sites and Organizational Partners -- 4.3.3 Ethics and Human Subject Protocol -- 4.4 Conclusion: The Way Forward -- References -- Part II Classical Approaches to Analyzing Behavior…”

Tabla de Contenidos: “…5.5.4 Fitting Distributions to Data in R Using MLE -- 5.5.5 Likelihood Ratio Test, LRT -- 5.6 Regression: Basic Principles -- 5.6.1 Simple Linear Regression -- 5.6.2 Quantifying Uncertainty on -- 5.6.3 Analysis of Variance in Regression -- 5.6.3.1 R2 and adjusted R2 Coefficient of Determination -- 5.6.4 Some Visual Diagnostics for the Proposed Simple Regression Model -- 5.7 Multiple Regression -- 5.7.1 Introduction -- 5.7.2 Regression and MLE -- 5.7.2.1 Multivariate Regression -- 5.7.3 Tests -- 5.7.3.1 Likelihood Ratio Test in Regression -- 5.7.3.2 Akaike Information Criterion: AIC -- 5.7.3.3 AIC and Regression model selection -- 5.7.3.4 Bayesian Information Criterion: BIC -- 5.7.4 Variable Selection, Finding the Most Appropriate Sub-Model -- 5.7.5 Backward Elimination -- 5.7.6 Forward Selection -- 5.7.7 Using AIC/BIC Criteria -- 5.7.8 LRT in Model Selection -- 5.7.9 Automatic Search Using R-squared Criteria -- 5.7.10 Concluding Remarks on Test Data -- 5.7.11 Modelling Beyond Linearity -- 5.8 Dummy/Indicator Variable Regression -- 5.8.1 Introducing Categorical Variables -- 5.8.2 Continuous and Indicator Variable Predictors - Including Load in the Model -- 5.9 Recommended Reading -- 6 Multivariate Distributions, and Sums of Random Variables -- 6.1 Multivariate Distributions - Examples in Finance -- 6.2 Simulating Multivariate Normal Variables -- 6.3 The Summation of a Number of Random Variables -- 6.4 Conclusion -- 6.5 Recommended Reading -- 7 Benefits of Diversification -- 7.1 Introduction -- 7.2 Background -- 7.3 Key Mathematical Ideas -- 7.4 Running Simulations -- 7.5 Recommended Reading -- 8 Modern Portfolio Theory -- 8.1 Introduction -- 8.2 2-Asset Portfolio -- 8.3 3-Asset Portfolio -- 8.4 Introduction of a Risk-free Asset to the Portfolio -- 8.4.1 Adding a Risk-free Asset -- 8.4.2 Capital Market Line and the Sharpe Ratio…”

Tabla de Contenidos: “…Cover -- Contents -- Syllabus -- Preface -- About the Authors -- Part I: Principles of Marketing -- Chapter 1: Marketing: Adding Value to Customers -- 1.1 Satisfying Customer Needs -- 1.2 Evolution of Marketing -- 1.3 Marketing: Concepts -- 1.3.1 Traditional Concept of Marketing -- 1.3.2 Modern Concept of Marketing -- 1.4 Definition of Marketing -- 1.5 Scope of Marketing -- 1.6 Nature of Marketing -- 1.7 Features of Marketing -- 1.8 Functions of Marketing -- 1.8.1 Functions Related to Merchandizing -- 1.8.2 Functions Related to Logistics -- 1.8.3 Functions Related to Supportive Activities -- 1.9 Importance of Marketing -- 1.10 Goals of Marketing -- 1.11 Tasks of Marketing -- 1.12 Basic Elements of Marketing -- 1.12.1 Need, Want and Demand -- 1.12.2 Exchange -- 1.12.3 Market -- 1.12.4 Marketer and Prospect -- 1.12.5 Offering -- 1.12.6 Value and Satisfaction -- 1.12.7 Relationship Marketing -- 1.12.8 Marketing Channels -- 1.12.9 Supply Chain -- 1.12.10 Competition -- 1.13 Classification of Markets -- 1.14 Marketing Philosophy -- 1.14.1 Production Orientation -- 1.14.2 Product Orientation -- 1.14.3 Selling Orientation -- 1.14.4 Marketing Orientation -- 1.14.5 Societal Orientation -- 1.15 Difference Between Selling and Marketing -- 1.16 Online Marketing -- 1.17 Challenges of Marketing -- 1.18 Ethical Issues in Marketing -- 1.19 Growing Relevance of Marketing in India -- 1.20 Impact of Global Marketing on India -- 1.21 Marketing Management -- 1.21.1 Definition of Marketing Management -- 1.21.2 Scope of Marketing Management -- 1.21.3 Objectives of Marketing Management -- 1.21.4 Significance of Marketing Management -- 1.21.5 Functions of Marketing Managers -- 1.21.6 Responsibilities of Marketing Managers -- Summary -- Key Words -- Students' Ready Reckoner -- Review Questions -- References -- Chapter 2: Marketing Environment: An Ever-changing Force…”

“…Where possible, short case studies have been added to illustrate the diverse aspects of the work…”
>Acceso al texto completo en Ebscohost

“…In a developed economy such as the United States approximately 60-70% fruits and vegetables are processed into various value added products and account for nearly a third of cash crop receipts and a fifth of agricultural exports. …”

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“…Finally, he will teach you post production output, including adding DVD markers, creating an interactive DVD menu, and outputting to DVD. …”