Tabla de Contenidos: “…8.3.1.2 Goals of Meetings with Senior Leadership -- 8.3.1.3 Meetings with Key Leaders -- 8.3.1.4 Execute the Communication Process -- 8.3.1.5 Conduct Interviews with Designated Leaders, Managers, and High-Priority Staff -- 8.3.1.6 Provide a Written Questionnaire for Remaining Designated Staff -- 8.3.1.7 Perform an Extensive Analysis of Findings -- 8.3.1.8 Creation of a Written Report with Detailed Study Findings -- 8.3.1.9 Present Findings to Leadership and Determine Next Steps -- 8.3.1.10 Presentation to the Organization -- 8.4 Redesigning an Organization to Execute with Data and Analytics -- 8.4.1 Business Knowledge -- 8.4.2 Data Knowledge -- 8.4.3 AI and Analytics Knowledge -- 8.4.4 Technology Stack-Architecture, Platforms, Systems -- 8.4.5 Culture -- 8.4.6 People -- 8.5 Conclusion -- References -- 9 Additional Stories on the Data Front -- 9.1 Managing the End-to-End Process of Patient Experience-Two Case Studies by Carol Maginn -- 9.1.1 Patient Case A -- 9.1.2 Patient Case B -- 9.1.3 Pricing Offers an Intuitively Simple Problem That Provides Use of the Most Complicated Mathematical Models -- 9.2 Textual Extraction, Transformation, and Learning -- 9.2.1 Some Sources of Textual Data -- 9.2.1.1 Voice Recordings -- 9.2.1.2 Printed Text -- 9.2.1.3 Internet and Social Media -- 9.2.1.4 Email -- 9.2.1.5 Electronic Texts as a Source -- 9.2.1.6 What Is a Taxonomy? …”

Tabla de Contenidos: “…3.3.4.3 Outdoor Street Canyon Scenario -- 3.3.4.4 General Frequency Trend in Delay Domain -- 3.3.5 Directional Domain Measurements -- 3.3.5.1 Indoor Of ce Wideband Results at 60 GHz -- 3.3.5.2 Indoor Of ce Multifrequency Results -- 3.3.5.3 Urban Macrocell Outdoor Results at 5 GHz -- 3.4 Channel Modeling -- 3.4.1 5G Stochastic Channel Models -- 3.4.1.1 Transmission Loss Modeling -- 3.4.1.2 Multipath Directional and Delay Modeling -- 3.4.1.3 Spatial Consistency -- 3.4.2 Geometry-Based Modeling -- 3.4.2.1 Blockage -- 3.5 Summary and Future Work -- References -- 4 Mathematical Modeling of Hardware Impairments -- 4.1 RF Power Ampli ers -- 4.1.1 The Volterra Series -- 4.1.2 Common Subsets of the Volterra Series -- 4.1.2.1 Static Polynomial -- Third-Order Static Polynomial -- 4.1.2.2 A Note on Odd-Even and Odd Orders -- 4.1.2.3 Memory Polynomial -- 4.1.2.4 Generalized Memory Polynomial -- 4.1.3 Global vs. …”

Tabla de Contenidos: “…11.2 Literature Review -- 11.2.1 Neural Networks -- 11.2.2 Trees -- 11.2.3 K-Nearest Neighbors -- 11.3 Proposed Model -- 11.3.1 Predictive Models in Health -- 11.4 Experimental Results and Discussion -- 11.4.1 Prediction of Diabetes with Artificial Neural Networks Supervised Learning Algorithms -- 11.4.2 Improving the Prediction Ratio of Diabetes Diagnoses Using Fuzzy Logic and Neural Networks -- 11.4.3 ARIC: Type 2 Diabetes Risk Predictive Model -- 11.4.4 Evaluation of Neural Network Algorithms for Prediction Models of Type 2 Diabetes -- 11.4.5 Reliable and Objective Recommendation System for the Diagnosis of Chronic Diseases -- 11.5 Conclusion -- References -- Chapter 12 Diagnosis of Neurological Disease Using Bioinspired Algorithms -- 12.1 Introduction -- 12.1.1 Neurological Diseases -- 12.1.2 Introduction to Bioinspired Algorithms -- 12.1.3 Types of Bioinspired Algorithms Commonly Used in Healthcare -- 12.1.4 Advantages and Limitations of Bioinspired Algorithms -- 12.1.5 Limitations -- 12.1.6 Applications of Bioinspired Algorithms in Healthcare -- 12.1.7 Benefits of Bioinspired Algorithms in Healthcare Over Traditional Approaches -- 12.2 Neurological Disease Diagnosis -- 12.2.1 Bioinspired Algorithms for Neurological Disease Diagnosis -- 12.2.2 Neural Networks in Neurological Disease Diagnosis -- 12.2.2.1 How NNs Can Be Trained Using Bioinspired Optimization Techniques -- 12.2.3 Other Bioinspired Algorithms in Neurological Disease Diagnosis -- 12.3 Challenges and Future Directions -- 12.4 Conclusion -- References -- Chapter 13 Optimizing Artificial Neural-Network Using Genetic Algorithm -- 13.1 Introduction -- 13.1.1 ANN -- 13.1.2 Genetic Algorithm -- 13.2 Methodology -- 13.2.1 Mathematical Working -- 13.3 Brief Study on Existing Implementations -- 13.3.1 Using Different Types of ANNs -- 13.3.2 Using MLPs…”

Tabla de Contenidos: “…-- 3.5 Assignment Operator -- 3.6 Increment (++) and Decrement (--) Operator -- 3.7 Bitwise Operators -- 3.7.1 Bitwise AND (&) -- 3.7.2 Bitwise OR (|) -- 3.7.3 Bitwise XOR (^) -- 3.7.4 1's Complement (~) -- 3.7.5 Left Shift Operator (>) -- 3.7.7 Right Shift with Zero Fill (>>>) -- 3.8 The Instance of Operator -- 3.9 The Comma Operator -- 3.10 The size of () Operator -- 3.11 Precedence of Operator -- 3.12 Type Conversion and Typecasting -- 3.13 Mathematical Functions -- 3.14 Scope and Lifetime -- 3.15 Ponderable Points -- Review Questions -- Multiple Choice Questions -- Key for Multiple Choice Questions -- Chapter 4: Working with Decision-making Statement in Java -- 4.1 Introduction -- 4.2 The if Statement -- 4.3 The if-else Statement -- 4.4 Nesting of if-else Statement -- 4.5 else-if Ladder -- 4.6 Switch-Case Statement -- 4.7 Introduction of Loops -- 4.7.1 The while Loop -- 4.7.2 The for Loop -- 4.8 Different Syntaxes of for Loop -- 4.9 Programming Examples -- 4.9.1 Nesting of for Loop -- 4.9.2 The do-while Statement -- 4.10 break and continue Statement -- 4.10.1 The break Statement -- 4.10.2 The continue Statement -- 4.10.3 Labelled break and continue Statement -- 4.11 Ponderabale Points -- Review Questions -- Multiple Choice Questions -- Key for Multiple Choice Questions -- Chapter 5: Working with Array in Java -- 5.1 Introduction -- 5.2 Creating Arrays in Java -- 5.3 Some Important Points About Array -- 5.4 Initializing 1-D Array -- 5.5 Programming Examples (Part-1) -- 5.6 Two-dimensional (2-D) Array -- 5.7 Three-dimensional (3-D) and Variable Column Length Arrays -- 5.7.1 3-D Array -- 5.8 Ponderable Points -- Review Questions…”

“…As the technology of the alphabet and of mere counting gave way to abstract symbols, the earlier "thing-mathematics" metamorphosed into the relational mathematics of modern scientific investigation. …”

“…Among these methods, mathematical programming models play a key role in optimizing a system. …”