Tabla de Contenidos: “…id=1815) -- 4.2.2 Bioplast by Biotec (http://www.biotec.de/prod/) -- 4.2.3 Solanyl, Optimum FlourPlast, and Optimum Optinyl by Rodenburg and Solanyl Bioplastics -- 4.2.4 BIOPAR® by BIOP Biopolymer Technologies AG -- 4.2.5 Plantic by Plantic (http://www.plantic.com.au/) -- 4.2.6 Cornpole by Japan Corn Starch (http://www.nihon-cornstarch.com/product/bio_plastic/tabid/160/Default.aspx) -- 4.2.7 Wuhan Huali Environment Protection-PSM (http://www.psm.com.cn/eng/index.asp) -- 4.2.7.1 PSM Biodegradable Materials: HL-300 Series -- 4.2.8 GAÏALENE® by Roquette (http://www.gaialene.com/) -- 4.2.9 Biolice by Limagrain (http://www.biolice.com/english/index_e.html) -- 4.3 Polylactic Acid -- 4.3.1 Properties of PLA Compounds -- 4.3.2 Formulation -- 4.3.2.1 Special Additives for In-house Compounding -- Melt Strength Enhancers -- Stabilizers -- Impact Modifiers, Tougheners -- Plasticizers -- Reinforcing Additives -- FR additives…”

Tabla de Contenidos: “…3.6.6.1 Transmission lines tour inspection system characteristics -- 3.6.6.2 The advantages of tour inspection system -- References -- 4 Transmission lines detection technology -- 4.1 Faulty Insulator Detection -- 4.1.1 The Characteristics of Faulty Insulators -- 4.1.2 Detection Methods of Faulty Insulators -- 4.1.2.1 Electrical quantity detection methods -- 4.1.2.2 Nonelectric quantity detection method -- 4.2 Voltage Detection in Operation -- 4.2.1 Requirements for Voltage Detector -- 4.2.1.1 Functions and technical requirements of voltage detectors -- 4.2.1.2 Electrical insulation requirements for voltage detectors -- 4.2.2 Methods of Voltage Detection Working -- 4.2.2.1 Direct voltage detection and indirect voltage detection -- 4.2.2.2 Methods and devices of voltage detection -- 4.3 Detection of Grounding Devices -- 4.3.1 Requirements for Grounding Type and Grounding Resistance -- 4.3.1.1 Grounding type -- 4.3.1.2 The main defects of grounding devices -- 4.3.1.3 Requirements for power frequency ground resistance in poles and towers -- 4.3.2 Measurement Methods of Power Frequency of Tower Ground Resistance -- 4.3.2.1 Three-electrode method -- 4.3.2.2 Four-electrode method -- 4.3.2.3 Clamp meter measuring method -- 4.3.3 Notes for Measuring Grounding Resistance and the Operating Maintenance of the Grounding Device -- 4.3.3.1 Notes for measuring grounding resistance -- 4.3.3.2 Operation maintenance for grounding device -- 4.4 Detection of Conductors and Ground Wires and Splicing Fittings -- 4.4.1 Performance Requirements and Heating Reasons for Conductors and Ground Wires and Splicing Fittings -- 4.4.1.1 Performance requirements -- 4.4.1.2 Reasons for temperature increase -- 4.4.1.3 Measures taken -- 4.4.2 Detection Methods -- 4.4.2.1 Ocular estimate method -- 4.4.2.2 Infrared thermal imaging detection method…”

Tabla de Contenidos: “…3.2.4.2 McCabe's Design Predicate Approach to Integration -- 3.2.4.3 Hex Converter Example -- 3.2.4.4 McCabe Design Predicate Exercise -- 3.2.4.5 McCabe Design Predicate Exercise Debrief -- 3.3 Dynamic Analysis -- 3.3.1 Memory Leak Detection -- 3.3.2 Wild Pointer Detection -- 3.3.3 Dynamic Analysis Exercise -- 3.3.4 Dynamic Analysis Exercise Debrief -- 3.4 Sample Exam Questions -- 4 Quality Characteristics for Technical Testing -- 4.1 Introduction -- 4.2 Security Testing -- 4.2.1 Security Issues -- 4.2.1.1 Piracy -- 4.2.1.2 Buffer Overflow -- 4.2.1.3 Denial of Service -- 4.2.1.4 Data Transfer Interception -- 4.2.1.5 Breaking Encryption -- 4.2.1.6 Logic Bombs/Viruses/Worms -- 4.2.1.7 Cross-Site Scripting -- 4.2.1.8 Timely Information -- 4.2.1.9 Internal Security Metrics -- 4.2.1.10 External Security Metrics -- 4.2.1.11 Exercise: Security -- 4.2.1.12 Exercise: Security Debrief -- 4.3 Reliability Testing -- 4.3.1 Maturity -- 4.3.1.1 Internal Maturity Metrics -- 4.3.1.2 External Maturity Metrics -- 4.3.2 Fault Tolerance -- 4.3.2.1 Internal Fault Tolerance Metrics -- 4.3.2.2 External Fault Tolerance Metrics -- 4.3.3 Recoverability -- 4.3.3.1 Internal Recoverability Metrics -- 4.3.3.2 External Recoverability Metrics -- 4.3.4 Compliance -- 4.3.4.1 Internal Compliance Metrics -- 4.3.4.2 External Compliance Metrics -- 4.3.5 An Example of Good Reliability Testing -- 4.3.6 Exercise: Reliability Testing -- 4.3.7 Exercise: Reliability Testing Debrief -- 4.4 Efficiency Testing -- 4.4.1 Multiple Flavors of Efficiency Testing -- 4.4.2 Modeling the System -- 4.4.2.1 Identify the Test Environment -- 4.4.2.2 Identify the Performance Acceptance Criteria -- 4.4.2.3 Plan and Design Tests -- 4.4.2.4 Configure the Test Environment -- 4.4.2.5 Implement the Test Design -- 4.4.2.6 Execute the Test -- 4.4.2.7 Analyze the Results, Tune and Retest -- 4.4.3 Time Behavior…”

Tabla de Contenidos: “…-- 4.2.6 Types of Neural Networks -- 4.2.6.1 Artificial Neural Network (ANN) -- 4.2.6.2 Recurrent Neural Network (RNN) -- 4.2.6.3 Convolutional Neural Network (CNN) -- 4.2.7 Learning Techniques in Neural Network -- 4.2.8 Applications of Neural Network -- 4.2.9 Advantages of Neural Networks -- 4.2.10 Disadvantages of Neural Network -- 4.2.11 Limitations of Neural Networks -- 4.3 Back-Propagation -- 4.3.1 Working of Back-Propagation -- 4.3.2 Types of Back-Propagation -- 4.3.2.1 Static Back-Propagation -- 4.3.2.2 Recurrent Back-Propagation -- 4.3.2.3 Advantages of Back-Propagation -- 4.3.2.4 Disadvantages of Back-Propagation -- 4.4 Activation Function (AF) -- 4.4.1 Sigmoid Active Function -- 4.4.1.1 Advantages -- 4.4.1.2 Disadvantages -- 4.4.2 RELU Activation Function -- 4.4.2.1 Advantages -- 4.4.2.2 Disadvantages -- 4.4.3 TANH Active Function -- 4.4.3.1 Advantages -- 4.4.3.2 Disadvantages -- 4.4.4 Linear Function -- 4.4.5 Advantages -- 4.4.6 Disadvantages…”

Tabla de Contenidos: “…Total -- Gulf Production by State -- Dockside Value and Price -- 10.3.8.2.2 The Gulf Oyster Processing Industry -- 10.3.8.2.3 Impact of Oyster Landings on Dockside Price -- 10.3.8.3 The Commercial Reef Fish Sector -- 10.3.8.4 Menhaden -- 10.3.9 Additional Detail on Processing and Wholesaling -- 10.4 The Gulf of Mexico Recreational Sector -- 10.4.1 Expenditures and Multipliers -- 10.4.2 Gulf of Mexico Fishing Activities -- 10.4.2.1 Number of Angler Trips -- 10.4.2.1.1 Angler Trips by Mode -- 10.4.2.1.2 Angler Trips by Area Fished -- 10.4.2.1.3 Angler Trips by Wave -- 10.4.2.1.4 Angler Targeting Behavior -- 10.4.2.1.5 Aggregate Gulf of Mexico Recreational Catch/Harvest -- 10.4.2.2 Gulf of Mexico Recreational Catch/Harvest by Species/Group -- 10.4.2.2.1 Inshore Species -- Spotted Seatrout -- Red Drum -- 10.4.2.2.2 Offshore Species -- Aggregate Reef Fish -- Individual Reef Fish Species (Groups) -- Snappers -- Coastal Pelagics -- Highly Migratory Pelagics -- 10.4.3 Recreational Activities at the State Level -- 10.4.3.1 Participation by State -- 10.4.3.1.1 Florida -- 10.4.3.1.2 Alabama -- 10.4.3.1.3 Mississippi -- 10.4.3.1.4 Louisiana -- 10.4.3.2 Angler Trips by State -- 10.4.3.2.1 Florida (West Coast) -- 10.4.3.2.2 Alabama -- 10.4.3.2.3 Mississippi -- 10.4.3.2.4 Louisiana -- 10.4.3.3 Catch/Harvest by State -- 10.4.3.3.1 Florida -- Aggregate Catch/Harvest -- Analysis by Inshore and Offshore Species -- Snappers -- 10.4.3.3.2 Louisiana -- Aggregate Catch -- Inshore Species -- Red Drum -- Spotted Seatrout -- Offshore Species -- 10.4.3.3.3 Alabama and Mississippi -- 10.5 Summary -- References -- Appendix A -- Chapter 11: Sea Turtles of the Gulf of Mexico…”

Tabla de Contenidos: “…3.5.1 Conditional Probability Function -- 3.5.2 Conditional Probability Density Function -- 3.6 Expectations -- 3.6.1 Moments -- 3.6.2 Expected Value of Function of Random Variable -- 3.6.3 Covariance -- 3.7 Conditional Expectations -- 3.8 Convergence of Random Variables -- 3.9 Random Processes -- 3.10 Markov Processes -- 3.11 Hidden Markov Models -- 3.12 Gaussian Processes -- Exercises -- Part II Optimization -- Chapter 4 Optimization Theory -- 4.1 Basic Concepts and Terminology -- 4.1.1 Optimization Problems -- 4.1.2 Equivalent Problems -- 4.2 Convex Sets -- 4.2.1 Convexity‐Preserving Operations -- 4.2.1.1 Intersection -- 4.2.1.2 Affine Transformation -- 4.2.1.3 Perspective Transformation -- 4.2.2 Examples of Convex Sets -- 4.2.2.1 Hyperplanes and Halfspaces -- 4.2.2.2 Polyhedral Sets -- 4.2.2.3 Norm Balls and Ellipsoids -- 4.2.2.4 Convex Cones -- 4.2.3 Generalized Inequalities -- 4.3 Convex Functions -- 4.3.1 First‐ and Second‐Order Conditions for Convexity -- 4.3.2 Convexity‐Preserving Operations -- 4.3.2.1 Scaling, Sums, and Integrals -- 4.3.2.2 Pointwise Maximum and Supremum -- 4.3.2.3 Affine Transformation -- 4.3.2.4 Perspective Transformation -- 4.3.2.5 Partial Infimum -- 4.3.2.6 Square of Nonnegative Convex Functions -- 4.3.3 Examples of Convex Functions -- 4.3.3.1 Norms -- 4.3.3.2 Indicator and Support Functions -- 4.3.4 Conjugation -- 4.3.5 Dual Norms -- 4.4 Subdifferentiability -- 4.4.1 Subdifferential Calculus -- 4.4.1.1 Nonnegative Scaling -- 4.4.1.2 Summation -- 4.4.1.3 Affine Transformation -- 4.4.1.4 Pointwise Maximum -- 4.4.1.5 Subgradients of Conjugate Functions -- 4.5 Convex Optimization Problems -- 4.5.1 Optimality Condition -- 4.5.2 Equality Constrained Convex Problems -- 4.6 Duality -- 4.6.1 Lagrangian Duality -- 4.6.2 Lagrange Dual Problem -- 4.6.3 Fenchel Duality -- 4.7 Optimality Conditions…”

Tabla de Contenidos: “…-- 4.1 The Set of All Possible Events -- 4.1.1 Coin flips: Why you should care -- 4.2 Probability: Outside or Inside the Head -- 4.2.1 Outside the head: Long-run relative frequency -- 4.2.1.1 Simulating a long-run relative frequency -- 4.2.1.2 Deriving a long-run relative frequency -- 4.2.2 Inside the head: Subjective belief -- 4.2.2.1 Calibrating a subjective belief by preferences -- 4.2.2.2 Describing a subjective belief mathematically -- 4.2.3 Probabilities assign numbers to possibilities -- 4.3 Probability Distributions -- 4.3.1 Discrete distributions: Probability mass -- 4.3.2 Continuous distributions: Rendezvous with density -- 4.3.2.1 Properties of probability density functions -- 4.3.2.2 The normal probability density function -- 4.3.3 Mean and variance of a distribution -- 4.3.3.1 Mean as minimized variance -- 4.3.4 Highest density interval (HDI) -- 4.4 Two-Way Distributions -- 4.4.1 Conditional probability -- 4.4.2 Independence of attributes -- 4.5 Appendix: R Code for Figure 4.1 -- 4.6 Exercises -- Chapter 5: Bayes' Rule -- 5.1 Bayes' Rule -- 5.1.1 Derived from definitions of conditional probability -- 5.1.2 Bayes' rule intuited from a two-way discrete table -- 5.2 Applied to Parameters and Data -- 5.2.1 Data-order invariance -- 5.3 Complete Examples: Estimating Bias in a Coin -- 5.3.1 Influence of sample size on the posterior -- 5.3.2 Influence of the prior on the posterior -- 5.4 Why Bayesian Inference Can Be Difficult…”

Tabla de Contenidos: “…3.4 Physical layer security of cognitive ambient backscatter communications for green Internet-of-Things -- 3.4.1 System model -- 3.4.2 Performance analysis -- 3.4.2.1 Outage probability analysis -- 3.4.2.2 Intercept probability analysis -- 3.4.3 Numerical results -- 3.4.4 Conclusions -- 3.5 Future research prospects -- 3.5.1 Security and privacy -- 3.5.2 Backscatter communication circuitry design -- 3.5.3 EM energy harvester -- 3.5.4 Hardware impairments -- References -- 4 Unmanned aerial vehicle technology in IoE -- 4.1 Introduction -- 4.1.1 Research status and development trend -- 4.1.2 Research on transmission theory of UAV Communication System -- 4.1.3 Physical layer security of wireless power supply network based on IRS-UAV -- 4.1.4 Channel estimation and beamforming for UAV Communication System -- 4.2 Energy efficiency characterization in heterogeneous IoT system with UAV swarms based on wireless power transfer -- 4.2.1 System model -- 4.2.1.1 Network model -- 4.2.1.2 Air to ground channel model -- 4.2.1.3 Energy harvesting model -- 4.2.1.4 Cell association -- 4.2.1.5 Performance metrics -- 4.2.2 Transmission probability of the IoT-Ts -- 4.2.2.1 One-slot charging -- 4.2.2.2 Two-slot charging -- 4.2.3 Coverage probability -- 4.2.3.1 Coverage probability of the PAIDs -- 4.2.3.2 Coverage probability of the FAIDs -- 4.2.4 Energy efficiency -- 4.2.5 Numerical results -- 4.2.6 Conclusion -- 4.3 UAV-aided multiway NOMA networks with residual hardware impairments -- 4.3.1 System model -- 4.3.1.1 The first case -- 4.3.1.2 The first case -- 4.3.1.3 The second case -- 4.3.2 Achievable sum rate analysis -- 4.3.2.1 Achievable sum rate analysis -- 4.3.2.2 High SNR analysis -- 4.3.3 Numerical results &amp -- discussion -- 4.3.4 Conclusion -- 4.4 A unified framework for HS-UAV NOMA networks: performance analysis and location optimization…”

Tabla de Contenidos: “…3.3.2.3 SPIN Model Checker -- 3.3.3 Automated Theorem Prover -- 3.3.3.1 ALT-ERGO -- 3.3.4 Static Analysis -- 3.3.4.1 CODESONAR -- 3.4 Validation of IoRT Systems -- 3.4.1 IoRT Testing Methods -- 3.4.2 Design of IoRT Test -- 3.5 Automated Validation -- 3.5.1 Use of Service Visualization -- 3.5.2 Steps for Automated Validation of IoRT Systems -- 3.5.3 Choice of Appropriate Tool for Automated Validation -- 3.5.4 IoRT Systems Open Source Automated Validation Tools -- 3.5.5 Some Significant Open Source Test Automation Frameworks -- 3.5.6 Finally IoRT Security Testing -- 3.5.7 Prevalent Approaches for Security Validation -- 3.5.8 IoRT Security Tools -- References -- 4 Light Fidelity (Li-Fi) Technology: The Future Man-Machine-Machine Interaction Medium -- 4.1 Introduction -- 4.1.1 Need for Li-Fi -- 4.2 Literature Survey -- 4.2.1 An Overview on Man-to-Machine Interaction System -- 4.2.2 Review on Machine to Machine (M2M) Interaction -- 4.2.2.1 System Model -- 4.3 Light Fidelity Technology -- 4.3.1 Modulation Techniques Supporting Li-Fi -- 4.3.1.1 Single Carrier Modulation (SCM) -- 4.3.1.2 Multi Carrier Modulation -- 4.3.1.3 Li-Fi Specific Modulation -- 4.3.2 Components of Li-Fi -- 4.3.2.1 Light Emitting Diode (LED) -- 4.3.2.2 Photodiode -- 4.3.2.3 Transmitter Block -- 4.3.2.4 Receiver Block -- 4.4 Li-Fi Applications in Real Word Scenario -- 4.4.1 Indoor Navigation System for Blind People -- 4.4.2 Vehicle to Vehicle Communication -- 4.4.3 Li-Fi in Hospital -- 4.4.4 Li-Fi Applications for Pharmacies and the Pharmaceutical Industry -- 4.4.5 Li-Fi in Workplace -- 4.5 Conclusion -- References -- 5 Healthcare Management-Predictive Analysis (IoRT) -- 5.1 Introduction -- 5.1.1 Naive Bayes Classifier Prediction for SPAM -- 5.1.2 Internet of Robotic Things (IoRT) -- 5.2 Related Work -- 5.3 Fuzzy Time Interval Sequential Pattern (FTISPAM)…”