Tabla de Contenidos: “…3.5.2 Addiction challenge -- 3.5.3 Privacy and security challenge -- 3.5.4 Ethics and morality challenge -- 3.6 Conclusion -- References -- 4 Web-based brain tumor classification app using convolutional neural network -- 4.1 Introduction -- 4.2 Methodology -- 4.2.1 Data collection -- 4.2.2 Data augmentation -- 4.2.3 Splitting -- 4.2.4 Training settings -- 4.2.4.1 CNN network architecture -- 4.2.5 Performance -- 4.2.6 Hardware and software requirements -- 4.3 Results -- 4.3.1 Confusion matrix -- 4.3.2 Performance metric of model -- 4.4 Conclusion -- Acknowledgments -- References -- 5 Traffic management system using different Internet of Things devices: literature review -- 5.1 Introduction -- 5.1.1 Selecting a template -- 5.1.2 Types of implementation methods -- 5.1.2.1 Radio frequency identification -- 5.1.2.1.1 RFID controller -- 5.1.2.1.2 RFID tag -- 5.1.2.1.3 Applications for RFID sensor -- 5.1.2.2 Analysis of video data -- 5.1.2.2.1 Problems with video analysis include -- 5.1.2.3 Wireless sensor network -- 5.1.2.4 The IR sensor -- 5.1.2.4.1 Sensor types -- 5.2 Method of evaluation -- 5.2.1 IoT device communication and addressing -- 5.2.2 IoT device security (physical and virtual) -- 5.3 Results and discussion -- 5.4 Conclusion -- References -- 6 Wireless sensor networks DV-Hop positioning based on artificial intelligence in the IoT era -- 6.1 Introduction -- 6.2 Related work -- 6.3 Methodology -- 6.4 Results -- 6.5 Conclusion -- References -- 7 Cassava leave disease image classification based on deep convolutional neural network -- 7.1 Introduction -- 7.1.1 Objective of the research -- 7.1.2 Problem of the research -- 7.2 Work related -- 7.3 Methodology -- 7.3.1 Collection of data -- 7.3.2 Preprocessing and cleaning -- 7.3.2.1Data split ratio and augmentation -- 7.4 Results -- 7.4.1 Matrix of confusion and comparative analysis -- 7.5 Conclusion…”

Tabla de Contenidos: “…3.4.2 Google Analytics Testing -- 3.4.3 Structured Data Testing -- 3.4.4 SEO Implementation -- 3.4.5 Google Analytics Implementation -- 3.4.6 Google Data Studio Implementation -- 3.4.7 Tableau Implementation -- 3.5 Result -- 3.6 Conclusion and Future Work -- References -- Chapter 4 The Need for XAI: Challenges and Its Applications -- 4.1 Introduction -- 4.2 Literature Review -- 4.3 The Need for Exploring XAI -- 4.3.1 Explain to Justify -- 4.3.2 Explain to Control -- 4.3.3 Explain to Improve -- 4.3.4 Explain to Discover -- 4.3.5 Challenges in XAI -- 4.4 Scope of Explanation -- 4.4.1 Local Explanation -- 4.4.2 Global Explanations -- 4.5 Differences in Research Methodology -- 4.5.1 Perturbation Based -- 4.5.2 Backpropagation- or Gradient-Based -- 4.5.3 XAI Applications -- 4.6 Conclusion -- References -- Chapter 5 Why Law Firms Need to Embrace Artificial Intelligence to Transform the Indian Legal Industry -- 5.1 Introduction -- 5.1.1 Research Methodology -- 5.1.2 Research Objectives -- 5.2 What Is Artificial Intelligence? …”

Tabla de Contenidos: “…4.3.1 Cost of Implementing Smart Farming Technologies -- 4.3.1.1 Hardware Costs -- 4.3.1.2 Data Management Costs -- 4.3.1.3 Training and Support Costs -- 4.3.1.4 Infrastructure Costs -- 4.3.1.5 Financing Costs -- 4.3.2 Financing and Investment Challenges -- 4.3.3 Economic Benefits and Returns on Investment -- 4.4 Social Obstacles to Smart Farming Adoption -- 4.4.1 Lack of Knowledge and Understanding Among Farmers -- 4.4.2 Behavioral and Cultural Barriers to Change -- 4.4.3 Role of Education and Awareness Raising -- 4.5 Environmental Considerations in Smart Farming -- 4.5.1 Sustainable Agricultural Practices and Smart Farming -- 4.5.2 Environmental Benefits and Concerns -- 4.5.3 Climate Change Mitigation and Adaptation -- 4.5.3.1 Mitigating Climate Change -- 4.5.3.2 Adapting to Climate Change -- 4.6 Future Prospects for Smart Farming -- 4.6.1 Emerging Trends and Innovations in Smart Farming -- 4.6.2 Prospects for Overcoming Challenges and Barriers -- 4.6.3 Future Outlook for Sustainable Agriculture -- 4.7 Conclusion and Recommendations -- 4.7.1 Summary of Key Points -- 4.7.2 Policy Recommendations for Promoting Smart Farming -- 4.7.3 Conclusion and Future Directions for Research -- References -- Chapter 5 Sustainable Development in Agriculture: Soil Management -- 5.1 Introduction -- 5.2 Reviewing the Need for Global Food Production to be Upgraded -- 5.2.1 Growing Population and Changing Dietary Preferences -- 5.2.2 Climate Change and Resource Limitations -- 5.2.3 Environmental Sustainability and Biodiversity Conservation -- 5.2.4 Food Loss and Waste -- 5.2.5 Technological Advancements and Digitalization -- 5.2.6 Socio-Economic Equity and Rural Development -- 5.2.7 Policy Interventions and Governance -- 5.3 Soil Quality and Its Impact -- 5.4 Emerging Technologies -- 5.4.1 AI Revolution -- 5.4.1.1 Precision Farming and Decision Support Systems…”

Tabla de Contenidos:

Tabla de Contenidos: “…4.3.2 Bayesian Multisource Classification Mechanism -- 4.3.3 A Refined Multisource Bayesian Model -- 4.3.4 Multisource Classification Using the MRF -- 4.3.5 Assumption of Inter-Source Independence -- 4.4 Evidential Reasoning -- 4.4.1 Concept Development -- 4.4.2 Belief Function and Belief Interval -- 4.4.3 Evidence Combination -- 4.4.4 Decision Rules for Evidential Reasoning -- 4.5 Dealing with Source Reliability -- 4.5.1 Using Classification Accuracy -- 4.5.2 Use of Class Separability -- 4.5.3 Data Information Class Correspondence Matrix -- 4.6 Concluding Remarks and Future Trends -- References -- Chapter 5 Support Vector Machines -- 5.1 Linear Classification -- 5.1.1 The Separable Case -- 5.1.2 The Nonseparable Case -- 5.2 Nonlinear Classification and Kernel Functions -- 5.2.1 Nonlinear SVMs -- 5.2.2 Kernel Functions -- 5.3 Parameter Determination -- 5.3.1 t-Fold Cross-Validations -- 5.3.2 Bound on Leave-One-Out Error -- 5.3.3 Grid Search -- 5.3.4 Gradient Descent Method -- 5.4 Multiclass Classification -- 5.4.1 One-Against-One, One-Against-Others, and DAG -- 5.4.2 Multiclass SVMs -- 5.4.2.1 Vapnik's Approach -- 5.4.2.2 Methodology of Crammer and Singer -- 5.5 Relevance Vector Machines -- 5.6 Twin Support Vector Machines -- 5.7 Deep Support Vector Machines -- 5.8 Concluding Remarks -- References -- Chapter 6 Decision Trees -- 6.1 ID3, C4.5, and SEE5.0 Decision Trees -- 6.1.1 ID3 -- 6.1.2 C4.5 -- 6.1.3 SEE5.0 (C5.0) -- 6.2 CHAID -- 6.3 CART -- 6.4 QUEST -- 6.4.1 Split Point Selection -- 6.4.2 Attribute Selection -- 6.5 Tree Induction from Artic fi ial Neural Networks -- 6.6 Pruning Decision Trees -- 6.6.1 Reduced Error Pruning -- 6.6.2 Pessimistic Error Pruning -- 6.6.3 Error-Based Pruning -- 6.6.4 Cost Complexity Pruning -- 6.6.5 Minimal Error Pruning -- 6.7 Ensemble Methods -- 6.7.1 Boosting -- 6.7.2 Random Forest -- 6.7.3 Rotation Forest…”

Tabla de Contenidos: “…Advanced configuration -- 4.1 Configuring an extended portal instance with the wizard -- 4.1.1 Basic configuration -- 4.1.2 Proxy configuration -- 4.1.3 Securing a portal instance with LDAP -- 4.1.4 Deploying default portlets -- 4.2 Manual configuration -- 4.2.1 Configuration tasks environment -- 4.2.2 Configuration tasks -- 4.2.3 Configuration properties -- 4.2.4 Parent properties files -- 4.2.5 Configuration templates -- 4.2.6 Creating stream files -- 4.3 Configuration tasks reference -- 4.3.1 Overview of configuration tasks -- 4.3.2 Startup tasks -- 4.3.3 HTTP server tasks -- 4.3.4 General purpose tasks -- 4.3.5 Portlet tasks -- 4.3.6 Security tasks -- 4.3.7 Setup tasks -- 4.3.8 Database tasks -- 4.3.9 Validation tasks -- 4.3.10 Lotus configuration tasks -- 4.4 Configuration scenarios -- 4.4.1 Scenario 1: Configuring a manual instance -- 4.4.2 Scenario 2: Configuring an external HTTP server -- 4.4.3 Scenario 3: Configuring security using LDAP for authentication -- Chapter 5. …”

Tabla de Contenidos: “…4.2.6 HA configuration summary -- 4.3 Installing and configuring WebSphere MQ -- 4.4 Message generation application -- 4.4.1 Compiling and running the message generation application -- 4.5 Messaging retrieval application -- 4.6 WebSphere MQ HA scripts and configuration -- 4.6.1 Normal scenario -- 4.6.2 Configuring brk1 and brk2 for WebSphere MQ HA -- 4.7 Running the shared-disk test -- 4.7.1 Queue manager configuration -- 4.7.2 Configuration verification -- 4.7.3 WebSphere Application Server configuration -- 4.7.4 Application in action -- 4.8 Summary -- Chapter 5. …”

Tabla de Contenidos: “…Save and Load Variables in the Workspace -- 4.1.3 Current Folder -- 4.2 MATLAB m-Files -- 4.2.1 Scripts -- 4.2.2 Commenting Code -- 4.3 MATLAB Debugging Mode -- 4.4 MATLAB Help Documentation -- 5. Logicals and Control Structures in Programming -- 5.1 Introduction: Controlling the Flow of Execution -- 5.2 Logical Data Type -- 5.2.1 Logical Operations -- 5.2.2 Combining Logical Operators -- 5.2.3 String Compare -- 5.3 Types of Control Structures -- 5.3.1 Conditional Statements -- if Statement -- else and elseif Statements -- switch Statement -- Comparison of if and switch Statements -- 5.3.2 Loops -- for Statement -- while Statement -- Comparison of for and while Statements -- 5.3.3 Functions -- Local Functions -- Programmer-Created Documentation -- 6. …”

Tabla de Contenidos: “…3.3.2 Inductively Coupled Three-Dimensional ICs -- 3.4 Vertical Interconnects for Three-Dimensional ICs -- 3.5 Summary -- 4 Electrical Properties of Through Silicon Vias -- 4.1 Physical Characteristics of a Through Silicon Via -- 4.2 Electrical Model of Through Silicon Via -- 4.3 Modeling a Three-Dimensional Via as a Cylinder -- 4.4 Compact Models -- 4.4.1 Physical Parameters of Compact Resistance Models -- 4.4.1.1 Through silicon via resistance -- 4.4.1.2 High frequency effects -- 4.4.1.3 Effect of barrier thickness on resistivity -- 4.4.1.4 Temperature effect -- 4.4.2 Physical Parameters of Compact Inductance Models -- 4.4.2.1 Through silicon via inductance -- 4.4.2.2 Internal and external magnetic field -- 4.4.2.3 High frequency effects -- 4.4.2.4 Loop inductance -- 4.4.3 Physical Parameters of Compact Capacitance Models -- 4.4.3.1 Through silicon via capacitance -- 4.4.3.2 Through silicon via model including the effects of the depletion region -- 4.4.4 Physical Parameters of Compact Conductance Models -- 4.4.4.1 Through silicon via conductance -- 4.5 Through Silicon Via Impedance Models -- 4.5.1 Compact Resistance Model of a Three-Dimensional Via -- 4.5.1.1 Compact models of through silicon via resistance -- 4.5.1.2 Closed-form resistance model of a three-dimensional via -- 4.5.1.3 Per cent variation in resistance -- 4.5.2 Compact Inductance Model of a Three-Dimensional Via -- 4.5.2.1 Compact models of through silicon via inductance -- 4.5.2.2 Closed-form inductance model of a three-dimensional via -- 4.5.2.2.1 Inductance of equal length three-dimensional vias -- 4.5.2.2.2 Inductance of non-equal length 3-D vias -- 4.5.2.3 Per cent variation in inductance -- 4.5.3 Compact Capacitance Model of a Three-Dimensional Via -- 4.5.3.1 Compact models of through silicon via capacitance -- 4.5.3.2 Closed-form capacitance model of a three-dimensional via…”

Tabla de Contenidos: “…3.2.5 Calculating CVA and DVA Using Monte Carlo Simulation -- 3.3 Overnight Index Swap Discounting -- Chapter 4 An Introduction to Derivative Instruments -- 4.1 FX Forwards -- 4.1.1 Product Description -- 4.1.2 Forward Points -- 4.2 Interest Rate Swaps -- 4.2.1 Product Description -- 4.2.2 IFRS 9 Accounting Implications -- 4.3 Cross-Currency Swaps -- 4.3.1 Product Description -- 4.3.2 IFRS 9 Accounting Implications -- 4.4 Standard (Vanilla) Options -- 4.4.1 Product Description -- 4.4.2 Standard Equity Options -- 4.4.3 Standard Foreign Exchange Options -- 4.4.4 Interest Rate Options - Caps, Floors and Collars -- 4.5 Exotic Options -- 4.6 Barrier Options -- 4.6.1 Knock-out Barrier Options - Product Description -- 4.6.2 Knock-in Barrier Options - Product Description -- 4.7 Range Accruals -- Chapter 5 Hedging Foreign Exchange Risk -- 5.1 Types of Foreign Exchange Exposure -- 5.2 Introductory Definitions -- 5.2.1 Functional Currency and Presentation Currency -- 5.2.2 Relevant Dates in an FX Transaction -- 5.3 Summary of IAS 21 Translation Rates -- 5.3.1 Monetary versus Non-monetary Items -- 5.3.2 Translation Rates -- 5.4 Foreign Currency Transactions -- 5.4.1 Summary of Most Commonly Used FX Derivatives -- 5.5 Case Study: Hedging A Forecast Sale and Subsequent Receivable with an FX Forward (Forward Element Included in Hedging Relationship) -- 5.5.1 Background -- 5.5.2 Setting the Hedging Relationship Term -- 5.5.3 Hedging Relationship Documentation -- 5.5.4 Hedge Effectiveness Assessment - Hypothetical Derivative -- 5.5.5 Hedge Effectiveness Assessment Performed at Hedge Inception -- 5.5.6 Fair Valuation of Hedged Item and Hypothetical Derivative at the Relevant Dates -- 5.5.7 Accounting Entries - Hedge Objective Unchanged: No Discontinuation -- 5.5.8 Accounting Entries - Hedge Risk Management Objective Changed: Discontinuation…”

Tabla de Contenidos: “…4.3 Flächen -- 4.3.1 Heften -- 4.3.2 Umgrenzungsfläche -- 4.3.3 Formen -- 4.3.4 Regelfläche -- 4.3.5 Stutzen -- 4.3.6 Dehnen -- 4.3.7 Fläche ersetzen -- 4.3.8 Körper reparieren -- 4.4 Übungsfragen -- Kapitel 5: Volumenkörper bearbeiten -- 5.1 Features -- 5.1.1 Bohrungen -- 5.1.2 Rundungen -- 5.1.3 Fasen -- 5.1.4 Wandung -- 5.1.5 Flächenverjüngung -- 5.1.6 Teilen -- 5.1.7 Gewinde -- 5.1.8 Biegungsteil -- 5.1.9 Verdickung/Versatz -- 5.2 Weitere Ändern-Befehle -- 5.2.1 Kombinieren -- 5.2.2 Fläche löschen -- 5.2.3 Körper verschieben -- 5.2.4 Objekt kopieren -- 5.3 Direkt bearbeiten -- 5.3.1 Verschieben -- 5.3.2 Größe -- 5.3.3 Maßstab (Skalieren) -- 5.3.4 Drehen -- 5.3.5 Löschen -- 5.4 Benutzer-Koordinaten-Systeme -- 5.5 Zwischen Bauteil und Baugruppe -- 5.6 Übungsfragen -- Kapitel 6: Baugruppen zusammenstellen (nicht in LT) -- 6.1 Projekt erstellen -- 6.2 Funktionsübersicht Baugruppen -- 6.3 Erster Zusammenbau -- 6.3.1 Die Bauteile -- 6.3.2 Das Platzieren -- 6.3.3 Abhängigkeiten erstellen -- 6.3.4 Bewegungsanzeige -- 6.4 Baugruppen-Abhängigkeiten -- 6.4.1 Passend/Fluchtend -- 6.4.2 Hilfsmittel Freie Verschiebung/Freie Drehung -- 6.4.3 Winkel -- 6.4.4 Tangential -- 6.4.5 Einfügen -- 6.4.6 Symmetrie -- 6.4.7 Abhängigkeiten unterdrücken -- 6.4.8 Passend/Fluchtend-Beispiel -- 6.4.9 Einfügen-Beispiel -- 6.4.10 Winkel-Beispiel -- 6.4.11 Tangential-Beispiel -- 6.4.12 Symmetrie-Beispiel -- 6.5 Bewegungs-Abhängigkeiten -- 6.5.1 Beispiel für Drehung -- 6.5.2 Beispiel für Drehung-Translation -- 6.5.3 Schraubbewegung -- 6.5.4 Schraubbewegung über Parametermanager -- 6.6 Adaptive Bauteile -- 6.6.1 Adaptivität nachrüsten -- 6.6.2 Bauteil in Baugruppe erstellen -- 6.7 Teile aus dem Inhaltscenter einfügen -- 6.7.1 Beispiel Kugellager -- 6.7.2 Beispiel Schrauben -- 6.8 Übungsfragen -- Kapitel 7: Zeichnungen erstellen -- 7.1 Ansichten erzeugen -- 7.1.1 Standard-Ansichten…”

Tabla de Contenidos: “…Forecasting with statistical models -- 4 Modeling a moving average process -- 4.1 Defining a moving average process -- 4.1.1 Identifying the order of a moving average process -- 4.2 Forecasting a moving average process -- 4.3 Next steps -- 4.4 Exercises -- 4.4.1 Simulate an MA(2) process and make forecasts -- 4.4.2 Simulate an MA(q) process and make forecasts -- Summary -- 5 Modeling an autoregressive process -- 5.1 Predicting the average weekly foot traffic in a retail store -- 5.2 Defining the autoregressive process -- 5.3 Finding the order of a stationary autoregressive process -- 5.3.1 The partial autocorrelation function (PACF) -- 5.4 Forecasting an autoregressive process -- 5.5 Next steps -- 5.6 Exercises -- 5.6.1 Simulate an AR(2) process and make forecasts -- 5.6.2 Simulate an AR(p) process and make forecasts -- Summary -- 6 Modeling complex time series -- 6.1 Forecasting bandwidth usage for data centers -- 6.2 Examining the autoregressive moving average process -- 6.3 Identifying a stationary ARMA process -- 6.4 Devising a general modeling procedure -- 6.4.1 Understanding the Akaike information criterion (AIC) -- 6.4.2 Selecting a model using the AIC -- 6.4.3 Understanding residual analysis -- 6.4.4 Performing residual analysis -- 6.5 Applying the general modeling procedure -- 6.6 Forecasting bandwidth usage -- 6.7 Next steps -- 6.8 Exercises -- 6.8.1 Make predictions on the simulated ARMA(1,1) process -- 6.8.2 Simulate an ARMA(2,2) process and make forecasts -- Summary -- 7 Forecasting non-stationary time series -- 7.1 Defining the autoregressive integrated moving average model -- 7.2 Modifying the general modeling procedure to account for non-stationary series…”

Tabla de Contenidos: “…4.3.1 Free-flow Parshall flume equations for the design of grit chambers -- 4.3.2 Design of rectangular grit chambers -- 4.4 BYPASS CHANNEL DESIGN -- 4.5 PROCEDURE FOR PRELIMINARY TREATMENT DESIGN WITH THE PARSHALL FLUME -- 4.5.1 Case study design: preliminary treatment, WSP system, Catacamas, Honduras -- 4.6 FINAL DISPOSAL OF SCREENINGS AND GRIT -- Chapter 5: Theory and design of facultative ponds -- 5.1 NATURAL PROCESSES AS THE DRIVING FORCE IN FACULTATIVE PONDS -- 5.1.1 Algal and bacterial processes in the aerobic zone -- 5.1.2 Bacterial processes in the anaerobic zone -- 5.1.3 Process analysis: methane emissions from facultative pond, Catacamas, Honduras -- 5.2 THEORY OF DESIGN OF FACULTATIVE PONDS -- 5.2.1 Maximum organic surface loading -- 5.2.1.1 Sources of solar radiation data -- 5.2.1.1.1 CLIMWAT and CROPWAT -- 5.2.1.1.2 NASA POWER data access viewer -- 5.2.1.2 Water temperature and algal growth -- 5.2.1.2.1 Design water temperature -- 5.2.1.2.2 Temperature effects on algal growth -- 5.2.1.3 Case study: surface loading and facultative pond performance, Nagpur, India -- 5.2.1.4 Case study: organic overloading of facultative ponds in Honduras -- 5.2.2 Wind effects in facultative ponds -- 5.2.3 Hydraulic considerations -- 5.2.3.1 Longitudinal dispersion -- 5.2.3.2 Thermal stratification and hydraulic short circuiting -- 5.2.3.3 Sludge accumulation effect on hydraulic short circuiting -- 5.2.4 Pathogen reduction -- 5.2.4.1 Helminth egg reduction -- 5.2.4.2 E. coli or fecal coliform reduction -- 5.2.5 BOD5 removal -- 5.2.6 TSS removal -- 5.2.7 Sludge accumulation -- 5.2.7.1 Sludge accumulation reported in the literature -- 5.2.7.2 Projection of sludge accumulation with flowrates and solids loadings -- 5.2.7.3 Design example part 1: projection of sludge accumulation for TSS = 200 mg/L…”

Tabla de Contenidos: “…3.1.2.1 Covalent Functionalization of Carbon Allotropes: Synthesis and Characterization -- 3.1.2.2 Noncovalent Functionalization of Carbon Allotropes: Synthesis and Characterization -- 3.2 Applications of Functionalized Carbon Allotropes -- 3.2.1 Biomedical -- 3.2.2 Waste Treatment -- 3.2.3 Pollutants Decontamination -- 3.2.4 Anticorrosive -- 3.2.5 Tribological -- 3.2.6 Catalytic -- 3.2.7 Reinforced Materials -- 3.3 Conclusions and Future Directions -- References -- Chapter 4 Carbon Allotropes in Lead Removal -- 4.1 Introduction -- 4.2 Carbon Nanomaterials (CNMs) -- 4.3 Dimension-Based Types of Carbon Nanomaterials -- 4.4 Purification of Water Using Fullerenes -- 4.5 Application of Graphene and Its Derivatives in Water Purification -- 4.6 Application of Carbon Nanotubes (CNTs) in Water Purification -- 4.7 Conclusion -- References -- Chapter 5 Carbon Allotropes in Nickel Removal -- 5.1 Introduction -- 5.2 Carbon and Its Allotropes: As Remediation Technology for Ni -- 5.2.1 Nanotubes Based on Carbon -- 5.2.1.1 Overview -- 5.2.1.2 Features of CNTs -- 5.2.2 Fullerenes -- 5.2.3 Graphene -- 5.2.3.1 Overview -- 5.2.3.2 Properties -- 5.3 Removal of Ni in Wastewater by Use of Carbon Allotropes -- 5.3.1 Carbon Nanotubes for Ni Adsorption From Aqueous Solutions -- 5.3.2 Ni Adsorption From Aqueous Solutions on Composite Material of MWCNTs -- 5.3.3 GR and GO-Based Adsorbents for Removal of Ni -- 5.4 Conclusion -- References -- Chapter 6 Molybdenum-Modified Carbon Allotropes in Wastewater Treatment -- 6.1 Introduction -- 6.2 Carbon-Based Allotropes -- 6.2.1 Graphene -- 6.2.2 Graphite -- 6.2.3 Carbon Nanotubes -- 6.2.4 Glassy Carbon (GC) -- 6.3 Molybdenum Disulfide -- 6.3.1 Synthesis of MoS2 -- 6.3.2 Physical Methods -- 6.3.3 Chemical Methods -- 6.3.4 Properties -- 6.4 Application of MoS2 -- 6.4.1 Dye-Sensitized Solar Cells (DSSCs) -- 6.4.2 Catalyst…”

Tabla de Contenidos: “…Chapter 3 Extraction Techniques for Biodiesel Production -- 3.1 Introduction -- 3.2 Direct Use and Blending -- 3.3 Microemulsion -- 3.4 Pyrolysis -- 3.5 Transesterification -- 3.5.1 Homogeneous Catalyzed Transesterification -- 3.5.2 Heterogeneous Catalyzed Transesterification -- 3.5.3 Enzyme Catalyzed Transesterification -- 3.5.4 Supercritical Alcohol Transesterification -- 3.6 Intensification Methods for Biodiesel Production -- 3.6.1 Ultrasonic Method -- 3.6.2 Microwave Method -- 3.6.3 Cosolvent Method -- 3.6.4 Membrane Technology -- 3.6.5 Reactive Distillation -- 3.7 Conclusions -- References -- Chapter 4 Role of Additives on Anaerobic Digestion, Biomethane Generation, and Stabilization of Process Parameters -- 4.1 Introduction -- 4.2 Anaerobic Digestion Process -- 4.3 Metallic Additives -- 4.4 Alkali Additives -- 4.5 Biological Additives -- 4.5.1 Microorganisms -- 4.5.2 Enzymes -- 4.6 Carbon-Based Additives -- 4.6.1 Graphene -- 4.6.2 Carbon Nanotubes -- 4.6.3 Activated Carbon -- 4.6.4 Biochar -- 4.7 Nanoparticles -- 4.7.1 Fe Nanoparticles -- 4.7.2 Nanoparticles of Ag and ZnO -- 4.7.3 Nanoparticles of Fe2O4 -- 4.8 Other Natural Additives -- 4.9 Conclusions -- Acknowledgment -- References -- Chapter 5 An Overview on Established and Emerging Biogas Upgradation Systems for Improving Biomethane Quality -- 5.1 Introduction -- 5.2 Available Biogas Upgradation Techniques -- 5.3 Microbial Methane Enrichment -- 5.4 Bioelectrochemical System -- 5.5 Photosynthetic Biogas Upgradation -- 5.6 Techno-Economics of Biological Biogas Upgradation Technologies -- 5.7 Conclusion -- Acknowledgement -- References -- Chapter 6 Renewable Feedstocks for Biofuels -- 6.1 Introduction -- 6.2 Sugar Containing Plant Crops -- 6.2.1 Sugar Cane (Saccharum officinarum) -- 6.2.2 Sugarbeet (Beta vulgaris L.) -- 6.2.3 Sweet Sorghum (Sorghum bicolor (L.) …”

Tabla de Contenidos: “…4.2.1 Challenges for Smart Manufacturing Industries -- 4.2.2 Smart Manufacturing Current Market Scenario -- 4.3 Data Drives in Smart Manufacturing -- 4.3.1 Benefits of Data-Driven Manufacturing -- 4.4 Manufacturing of Product Through 3D Printing Process -- 4.4.1 3D Printing Technology -- 4.4.2 3D Printing Technologies Classification -- 4.4.3 3D Printer Parameters -- 4.4.4 Significance of Honeycomb Structure -- 4.4.5 Acrylonitrile Butadiene Styrene (ABS) Thermoplastic Polymer Used for Honeycomb Structures Model -- 4.4.6 3D Printing Parameters and Their Descriptions -- 4.5 Conclusion -- References -- Chapter 5 Smart Inventory Control: Proposed Framework on Basis of IoT, RFID, and Supply Chain Management -- 5.1 Introduction -- 5.2 Objectives -- 5.3 Research Methodology -- 5.4 Literature Review -- 5.5 Components of SIM -- 5.5.1 Supply Chain Management (SCM) -- 5.5.2 Inventory Management System (IMS) -- 5.5.3 Internet of Things (IoT) -- 5.5.4 RFID System -- 5.5.5 Maintenance, Repair, and Operations -- 5.5.6 Deep Reinforcement Learning -- 5.6 Framework -- 5.7 Optimization -- 5.7.1 Inventory Optimization -- 5.8 Results and Discussion -- 5.9 A Mirror to Researchers and Managers -- 5.10 Conclusions -- 5.11 Future Scope -- References -- Chapter 6 Application of Machine Learning in the Machining Processes: Future Perspective Towards Industry 4.0 -- 6.1 Introduction -- 6.2 Machine Learning -- 6.3 Smart Factory -- 6.4 Intelligent Machining -- 6.5 Machine Learning Processes Used in Machining Process -- 6.6 Performance Improvement of Machine Structure Using Machine Learning -- 6.7 Conclusions -- References -- Chapter 7 Intelligent Machine Learning and Deep Learning Techniques for Bearings Fault Detection and Decision-Making Strategies -- Abbreviations -- 7.1 Introduction -- 7.2 Literature Review -- 7.3 Methodology -- 7.3.1 Dataset Preparation -- 7.3.2 CWRU Dataset…”

Tabla de Contenidos: “…Customizing Settings for Notifications -- 4.3.1. Catalogs -- 4.4. Maintenance Orders -- 4.4.1. Corrective/Reactive Maintenance Process -- 4.4.2. …”

Tabla de Contenidos: “…Chapter 4 Machine Learning Integration in Agriculture Domain: Concepts and Applications -- 4.1 Introduction -- 4.2 Fog Computing in Agriculture -- 4.2.1 Smart Farming -- 4.3 Methodology -- 4.3.1 Data Source -- 4.3.2 Data Analysis and Pre-Processing -- 4.3.3 Feature Extraction -- 4.3.4 Model Selection -- 4.3.5 Hyper-Parameter Tuning -- 4.3.6 Train-Test Split -- 4.4 Results and Discussion -- 4.4.1 Modeling Algorithms -- 4.5 Conclusion -- 4.6 Future Scope -- References -- Chapter 5 Role of Intelligent IoT Applications in Fog Computing -- 5.1 Introduction -- 5.1.1 PaaS/SaaS Platforms Have Various Benefits That are Crucial to the Success of Many Small IoT Startup Businesses -- 5.2 Cloud Service Model's Drawbacks -- 5.3 Fog Computation -- 5.3.1 Standardization -- 5.3.2 Growing Use Cases for Fog Computing -- 5.3.3 IoT Applications with Intelligence -- 5.3.4 Graphics Processing Units -- 5.4 Recompenses of FoG -- 5.5 Limitation of Fog Computing -- 5.6 Fog Computing with IoT -- 5.6.1 Benefits of Fog Computing with IoT -- 5.6.2 Challenges of Fog Computing with IoT -- 5.7 Edge AI Embedded -- 5.7.1 Key Software Characteristics in Fog Computing -- 5.7.2 Fog Cluster Management -- 5.7.3 Technology for Computing in the Fog -- 5.7.4 Concentrating Intelligence -- 5.7.5 Device-Driven Intelligence -- 5.8 Network Intelligence Objectives -- 5.9 Farming with Fog Computation (Case Study) -- 5.10 Conclusion -- References -- Chapter 6 SaaS-Based Data Visualization Platform-A Study in COVID-19 Perspective -- 6.1 Introduction -- 6.1.1 Motivation and the Problem of Interest -- 6.2 Summary of Objectives -- 6.3 What is a Pandemic? …”

Tabla de Contenidos: “…Database -- 4.1 Database support overview -- 4.1.1 DB2 Everyplace Client -- 4.1.2 DB2 Everyplace ISync Client -- 4.1.3 IBM Cloudscape Client -- 4.1.4 IBM Cloudscape ISync Client -- 4.2 DB2 Everyplace versus Cloudscape -- 4.3 Documentation and Web Links -- 4.3.1 DB2e -- 4.3.2 Cloudscape -- 4.4 Example database exercise -- 4.4.1 Description -- 4.4.2 Configuring a development system for DB2e and DB2e Sync -- 4.4.3 Extending the Tester bundle -- 4.4.4 Database bundle review -- 4.4.5 Testing the database bundle -- 4.4.6 Troubleshooting -- Chapter 5. …”