Tabla de Contenidos: “…Nematicons; 1.1 Introduction; 1.1.1 Nematic Liquid Crystals; 1.1.2 Nonlinear Optics and Solitons; 1.1.3 Initial Results on Light Self-Focusing in Liquid Crystals; 1.2 Models; 1.2.1 Scalar Perturbative Model; 1.2.2 Anisotropic Perturbative Model; 1.3 Numerical Simulations; 1.3.1 Nematicon Profile; 1.3.2 Gaussian Input; 1.4 Experimental Observations; 1.4.1 Nematicon-Nematicon Interactions; 1.4.2 Modulational Instability; 1.5 Conclusions; References; Chapter 2. …”

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Tabla de Contenidos: “…3.3.1 Query by Transduction (QBT)Algorithmic formulation; 3.3.2 Generalized Query by Transduction; Algorithmic formulation; Combining multiple criteria in GQBT; 3.3.3 Multicriteria Extension to QBT; 3.4 Experimental Results; 3.4.1 Benchmark Datasets; 3.4.2 Application to Face Recognition; 3.4.3 Multicriteria Extension to QBT; 3.5 Discussion and Conclusions; Acknowledgments; 4 Anomaly Detection; 4.1 Introduction; 4.2 Background; 4.3 Conformal Prediction for Multiclass Anomaly Detection; 4.3.1 A Nonconformity Measure for Multiclass Anomaly Detection; 4.4 Conformal Anomaly Detection…”

Tabla de Contenidos: “…Standarten anfertigen -- Weitwinkelbalgen nähen -- Endmontage -- Alternative Varianten -- Aufnahmen vorbereiten -- Technische und kreative Möglichkeiten -- Kleinbildobjektiv-Adaption -- Standarte und Balgen -- Vorteile und Einschränkungen -- Panoramabox -- Objektiv und Kamera auswählen -- Das Gehäuse bauen -- Die Rückwand -- Der Schiebemechanismus -- Die Montage der Kamera -- Aufnahmen -- 360 Grad drehbares Shift-Objektiv -- Das Basisobjektiv -- Objektivaufbau -- Das Shift-Objektiv im Einsatz -- Drehbares Weitwinkel-Shift-Objektiv für APS-C -- Shift-Experimente -- Multishot-Aufnahmen erstellen und stitchen -- Aufnahmen erstellen -- Stitchen -- Automatisieren -- Photoshop -- Affinity Photo -- Autostitch -- Lochkameras -- Rasierklingenblenden- und Multi-Lochkameras -- Lochkamera-Fassungen und Kamera-Anschluss -- Lochkamera mit Rasierklingenblenden -- Schlitzkamera mit Rasierklingenblenden -- Multiple Lochkameras -- Flexible Lochkamera aus Super-8-Objektiv -- Lochkamera-Aufnahmen -- Spezielle -- Aufnahmetechniken -- 360 Grad drehbares Tilt-Objektiv -- Drehbarer Adapter -- Tilt-Aufnahmen -- Janpol-Color-Farbmischobjektiv -- Individuell filtern -- Mehrfachobjektive -- Geteiltes Bild ist doppeltes Bild -- Die Vierfach-Variante -- Kreativer Spielraum -- Digitale Slit-Kamera -- Geeignete Kameras -- Schiebevorrichtung mit Schlitzblende -- Objektivhalterung und Kamera-Anschluss -- Einstellschlitten mit Kurbelantrieb -- Erste Aufnahmen -- Effekte -- Cyanotypie-Kamera -- UV-Fotografie -- Das richtige Objektiv finden -- Die Kamera bauen -- Sandwich-Bodenplatte -- Aufnahmekassette und Mattscheibe -- Die Standartenverstellung -- Farbiger Balgen -- Objektiv und Frontplatte -- Abschließende Arbeiten -- Cyanotypie-Aufnahmen -- Digitale Entwicklung -- Linsenexperimente -- Mit und ohne Linsen experimentieren -- Einzelne Linsen adaptieren -- Lichtleck-Objektiv…”

Tabla de Contenidos: “…-- Muss ich mein LEGO für die Experimente zerstören? -- Brauche ich irgendwelche Spezialteile? …”

Tabla de Contenidos: “…2.3.2 Pulsed laser nitriding2.4 Laser carburization of materials; 2.4.1 Laser carburization of iron and carbon steel; 2.4.2 Laser carburization of austenitic stainless steel; 2.4.3 Carburization of various nonferrous materials; 2.4.4 Nitrocarburization of materials; 2.5 Future trends; 2.6 Sources of further information and advice; Acknowledgment; References; Chapter 3: Mechanical properties improvement of metallic rolls by laser surface alloying; 3.1 Introduction; 3.2 Mechanical properties improvement of metallic rolls by laser surface alloying: experimental procedures…”

Tabla de Contenidos: “…Diaz A Validation Approach for Quasistatic Numerical/Experimental Indentation Analysis in Soft Materials Using 3D Digital Image Correlation doi: 10.3390/ma10070722 -- Heng Chen, Taihua Zhang and Yi Ma Effect of Applied Stress on the Mechanical Properties of a Zr-Cu-Ag-Al Bulk Metallic Glass with Two Different Structure States doi: 10.3390/ma10070711 -- Carolina Bermudo, Lorenzo Sevilla and German Castillo Lopez Material Flow Analysis in Indentation by Two-Dimensional Digital Image Correlation and Finite Elements Method doi: 10.3390/ma10060674 -- Carolina Bermudo, Lorenzo Sevilla, Francisco Martin and Francisco Javier Trujillo Hardening Effect Analysis by Modular Upper Bound and Finite Element Methods in Indentation of Aluminum, Steel, Titanium and Superalloys doi: 10.3390/ma10050556 -- Muhammad Zeeshan Mughal, Hugues-Yanis Amanieu, Riccardo Moscatelli and Marco Sebastiani A Comparison of Microscale Techniques for Determining Fracture Toughness of LiMn2O4 Particles doi: 10.3390/ma10040403 -- Felix Rickhey, Karuppasamy Pandian Marimuthu and Hyungyil Lee Investigation on Indentation Cracking-Based Approaches for Residual Stress Evaluation doi: 10.3390/ma10040404 -- Takashi Akatsu, Shingo Numata, Yutaka Shinoda and Fumihiro Wakai Effect of the Elastic Deformation of a Point-Sharp Indenter on Nanoindentation Behavior doi: 10.3390/ma10030270 -- Giorgio Mattei, Ludovica Cacopardo and Arti Ahluwalia Micro-Mechanical Viscoelastic Properties of Crosslinked Hydrogels Using the Nano-Epsilon Dot Method doi: 10.3390/ma10080889…”

Tabla de Contenidos: “…6.2.1 System description -- 6.2.2 Theoretical modeling -- 6.2.3 Boundary conditions and initial conditions -- 6.2.4 Solution method -- 6.3 Reliability of the simulation method -- 6.4 Results and discussion -- 6.5 Conclusions -- Nomenclature -- Greek symbols -- Subscript -- References -- 7 The influence of ambient crosswind on the performance of solar updraft power plant system -- 7.1 Introduction -- 7.2 Model description -- 7.2.1 Geometric Model -- 7.2.2 Mathematical Model -- 7.2.3 Boundary Conditions -- 7.2.3.1 Inlet boundary (surface at x=0) -- 7.2.3.2 Outlet boundary (surfaces at x=400 and z=300) -- 7.2.3.3 Ground boundary (surface at z=0) -- 7.2.3.4 Side wall (surface at y=200) -- 7.2.3.5 Symmetry surface (surface at y=0) -- 7.2.3.6 Turbine coupling -- 7.2.4 Meshing Skills -- 7.2.5 Computational Procedure -- 7.2.6 Selection of Ambient Geometrical Dimensions -- 7.3 Results and discussion -- 7.3.1 Comparison of Flow Performances -- 7.3.2 Comparison of Relative Static Pressure Contours -- 7.3.3 Comparison of Temperature Contours -- 7.3.4 Comparison of System Temperature Increase, Driving Force, and Updraft Velocity -- 7.3.5 Influence of Crosswind With Turbine Pressure Drop -- 7.3.6 Main Findings -- 7.4 SC Model With Blockage -- 7.5 Results and Discussion -- 7.5.1 Comparison of Flow Performances -- 7.5.2 Comparison of Relative Static Pressure Contours -- 7.5.3 Flow Characteristics Near the Collector Inlet -- 7.5.4 Comparison of System Temperature Increase and Driving Force -- 7.5.5 Comparison of System Output Power -- 7.5.6 Main Findings -- Nomenclature -- Subscripts -- References -- 8 Experimental investigation of a solar chimney prototype -- 8.1 Introduction -- 8.2 Experimental Setup -- 8.3 Disposal of measurement points -- 8.4 Results and discussion -- 8.4.1 Variations of Temperature with Time…”

Tabla de Contenidos: “…Normalization and experimental design tables -- 3.3. Designs for the pruning of aging data -- 3.4. …”

Tabla de Contenidos: “…The EPE-HCRDH approach -- 7.6.4. Experimental results for both approaches -- 7.7. Conclusion -- 7.8. …”

Tabla de Contenidos: “…Three convergent paths between creative action and computational tools -- Technological innovation for circularity and sustainability through buildings’ life cycles: Policy, initiatives and stakeholders’ perspective -- Fair play: Why reliable data for low tech construction and non-conventional materials are needed -- Part 3: Environment -- Technological innovation for the next ecosystem transition: From a high tech -- To low tech intensity – High efficiency environment -- Technological imagination to stay within planetary boundaries -- Quality-based design for environmentally conscious architecture -- Digital transformation projects for the future digicircular society -- The regulatory apparatus at the service of sustainable planning of the built environment: The case of law 338/2000 -- From nature to architecture for low tech solutions: Biomimetic principles for climate-adaptive building envelope -- Soft technologies for the circular transition: Practical experimentation of the product “material passport” -- Imaging a carbon neutral university -- Life cycle assessment at the early stage of building design -- Design scenarios for a circular vision of post-disaster temporary settlements -- Towards climate neutrality: Progressing key actions for positive energy districts implementation -- Remanufacturing towards circularity in the construction sector: The role of digital technologies -- Territorial energy potential for energy community and climate mitigation actions: Experimentation on pilot cases in Rome -- Integrated design approach to build a safe and sustainable dual intended use center in Praslin island, Seychelles -- Part 4: Climate changes -- Climate change: New ways to inhabit the earth -- The climate report. …”

Tabla de Contenidos: “…. -- Parco Archeologico Didattico del Livelet: education, ancient technology and experimental archaeology (Revine Lago, Treviso, Italy) -- Figure 1. …”

Tabla de Contenidos: “…3.3 Computing the Best Local Alignment -- 3.3.1 StripedAlignment -- 3.3.2 ChunkedAlignment1 -- 3.3.3 ChunkedAlignment2 -- 3.3.4 Memory requirements -- 3.4 Experimental Results -- StripedScore -- StripedAlignment -- ChunkedAlignment1 -- 4 Alignment of three sequences -- 4.1 Three-Sequence Alignment Algorithm -- 4.2 Computing the Score of the Best Alignment -- 4.2.1 Layered algorithm -- GPU computational strategy -- Analysis -- 4.2.2 Sloped algorithm -- GPU computational strategy -- Analysis -- 4.3 Computing the Best Alignment -- 4.3.1 Layered-BT1 -- 4.3.2 Layered-BT2 -- 4.3.3 Layered-BT3 -- 4.4 Experimental Results -- 4.4.1 Computing the score of the best alignment -- 4.4.2 Computing the alignment -- 5 Conclusion -- References -- Chapter 9: Augmented block cimmino distributed algorithm for solving tridiagonal systems on GPU -- 1 Introduction -- 2 ABCD Solver for tridiagonal systems -- 3 GPU implementation and optimization -- 3.1 QR Method and Givens Rotation -- 3.2 Sparse Storage Format -- 3.3 Coalesced Memory Access -- 3.4 Boundary Padding -- 3.4.1 Padding of the augmented matrix -- 3.4.2 Padding for Givens rotation -- 4 Performance evaluation -- 4.1 Comparison With CPU Implementation -- 4.2 Speedup by Memory Coalescing -- 4.3 Boundary Padding -- 5 Conclusion and future work -- References -- Chapter 10: GPU computing applied to linear and mixed-integer programming -- 1 Introduction -- 2 Operations Research in Practice -- 3 Exact Optimization Algorithms -- 3.1 The Simplex Method -- 3.2 Dynamic Programming -- 3.2.1 Knapsack problems -- 3.2.2 Multiple-choice knapsack problem -- 3.3 Branch-and-Bound -- 3.3.1 Knapsack problem -- 3.3.2 Flow-shop scheduling problem -- 3.3.3 Traveling salesman problem -- 4 Metaheuristics -- 4.1 Genetic Algorithms -- 4.1.1 The traveling salesman problem -- 4.1.2 Scheduling problems -- 4.1.3 Knapsack problems…”

Tabla de Contenidos: “…11.3.2.4 Information Gain (IG) -- 11.3.2.5 Clonal Selection -- 11.3.2.6 An Overview of the Steps of the CLONALG -- 11.3.3 Hybrid CLONALG -- 11.4 Experimental Results -- 11.4.1 Results of Feature Selection Using IG with Various Classifiers -- 11.4.2 Results of Optimizing Support Vector Machine Using CLONALG Selection -- 11.5 Conclusion -- References -- Chapter 12 BCI - Challenges, Applications, and Advancements -- 12.1 Introduction -- 12.1.1 BCI Structure -- 12.2 Related Works -- 12.3 Applications -- 12.4 Challenges and Advancements -- 12.5 Conclusion -- References -- Index -- EULA…”

Tabla de Contenidos: “…4.5.4 Level process monitoring and control through SCADA replacement -- 4.6 Proposed system -- 4.6.1 Introduction to the proposed system -- 4.6.2 Flowchart of the system -- 4.6.3 Eclipse -- 4.7 Cloud description -- 4.8 Trail results -- 4.8.1 TRAIL 1 -- 4.8.2 TRAIL 2 -- 4.8.3 TRAIL 3 -- 4.8.4 TRAIL 4 -- 4.9 Project setup -- 4.10 Inference -- 4.11 Conclusion -- 4.12 Limitations of the proposed methodology -- Annexure-1 -- References -- Chapter 5: Automated computer-aided diagnosis of COVID-19 and pneumonia based on chest X-ray images using deep learning: Classification and segmentation -- 5.1 Introduction -- 5.2 Literature review -- 5.2.1 Medical image segmentation -- 5.2.2 Computer-aided detection and diagnosis -- 5.2.3 Annotation-efficient -- 5.3 Materials and methods -- 5.3.1 Dataset description -- 5.3.2 Pre-processing -- 5.3.3 Convolutional neuronal network -- 5.4 Experimental results -- 5.4.1 Experimental setup -- 5.4.2 Data augmentation -- 5.4.3 Evaluation of performance metrics -- 5.4.4 Graphical user interface -- 5.5 Conclusion and future work -- References -- Chapter 6: Fuzzy logic and applications -- 6.1 Introduction -- 6.2 Fuzzy logic concepts -- 6.3 Reasons for using fuzzy logic system -- 6.3.1 Main usage of fuzzy logic systems is prevalent in the following areas -- 6.3.2 Fuzzy logic in washing machines -- 6.4 Image processing -- 6.5 Anesthesia depth control using fuzzy logic -- 6.6 Fuzzy logic in monitoring drug dosage -- 6.7 Fuzzy logic-based water treatment system optimization -- 6.8 Applications of fuzzy logic in industrial automation -- 6.9 Software engineering -- 6.10 Power system applications -- 6.11 Fuzzy controllers' potential for use in RACs in the future -- 6.12 The benefits of fuzzy logic -- 6.13 Disadvantages of fuzzy logic -- 6.14 Conclusion -- References…”

Tabla de Contenidos: “…9.3 Artificial Intelligence: Transport System and Healthcare -- 9.4 Artificial Intelligence Algorithms -- 9.5 AI Workflow -- 9.6 AI for ITS and e-Healthcare Tasks -- 9.7 Intelligent Transportation, Healthcare, and IoT -- 9.8 AI Techniques Used in ITS and e-Healthcare -- 9.9 Challenges of AI and ML in ITS and e-Healthcare -- 9.10 Conclusions -- References -- Chapter 10 Classification of Dementia Using Statistical First-Order and Second-Order Features -- 10.1 Introduction -- 10.2 Materials and Methods -- 10.2.1 Dataset -- 10.2.2 Image Pre-Processing -- 10.3 Proposed Framework -- 10.3.1 Discrete Wavelet Transform -- 10.3.1.1 Statistical Features -- 10.3.2 Classification -- 10.3.2.1 K-Nearest Neighbor -- 10.3.2.2 Linear Discriminant Analysis -- 10.3.2.3 Support Vector Machine -- 10.3.3 Performance Measure -- 10.4 Experimental Results and Discussion -- 10.5 Conclusion -- References -- Chapter 11 Pulmonary Embolism Detection Using Machine and Deep Learning Techniques -- 11.1 Introduction -- 11.2 The State-of-the-Art of PE Detection Models -- 11.3 Literature Survey -- 11.4 Publications Analysis -- 11.5 Conclusion -- References -- Chapter 12 Computer Vision Techniques for Smart Healthcare Infrastructure -- 12.1 Introduction -- 12.2 Literature Survey -- 12.2.1 Computer Vision -- 12.2.1.1 Computer Vision Techniques for Safety and Driver Assistance -- 12.2.1.2 Types of Optical Character Recognition Systems -- 12.2.1.3 Phases of Optical Character Recognition -- 12.2.1.4 Threshold Segmentation -- 12.2.1.5 Edge Detection Operator -- 12.2.1.6 Use Cases of OCR -- 12.2.1.7 List of Research Papers -- 12.2.2 How is IoT Changing the Face of Information Science? …”

Tabla de Contenidos: “…9.2.1 Modified Training Or Modified Input -- Data Preprocessing -- Data Augmentation -- 9.2.2 Modifying Networks Architecture -- Network Distillation -- Model Regularization -- 9.2.3 Network Add-On -- Defense Against Universal Perturbations -- MegNet Model -- 9.4 Discussions and Open Issues -- 9.5 Conclusions -- References -- 10 Defensive Schemes for Cyber Security of Deep Reinforcement Learning -- 10.1 Introduction -- 10.2 Background -- 10.2.1 Model-Free RL -- 10.2.2 Deep Reinforcement Learning -- 10.2.3 Security of DRL -- 10.3 Certificated Verification For Adversarial Examples -- 10.3.1 Robustness Certification -- 10.3.2 System Architecture -- 10.3.3 Experimental Results -- 10.4 Robustness On Adversarial State Observations -- 10.4.1 State-Adversarial DRL for Deterministic Policies: DDPG -- 10.4.2 State-Adversarial DRL for Q-Learning: DQN -- 10.4.3 Experimental Results -- 10.5 Conclusion And Challenges -- Acknowledgment -- References -- 11 Adversarial Attacks On Machine Learning Models in Cyber- Physical Systems -- 11.1 Introduction -- 11.2 Support Vector Machine (SVM) Under Evasion Attacks -- 11.2.1 Adversary Model -- 11.2.2 Attack Scenarios -- 11.2.3 Attack Strategy -- 11.3 SVM Under Causality Availability Attack -- 11.4 Adversarial Label Contamination on SVM -- 11.4.1 Random Label Flips -- 11.4.2 Adversarial Label Flips -- 11.5 Conclusions -- References -- 12 Federated Learning and Blockchain:: An Opportunity for Artificial Intelligence With Data Regulation -- 12.1 Introduction -- 12.2 Data Security And Federated Learning -- 12.3 Federated Learning Context -- 12.3.1 Type of Federation -- 12.3.1.1 Model-Centric Federated Learning -- 12.3.1.2 Data-Centric Federated Learning -- 12.3.2 Techniques -- 12.3.2.1 Horizontal Federated Learning -- 12.3.2.2 Vertical Federated Learning -- 12.4 Challenges -- 12.4.1 Trade-Off Between Efficiency and Privacy…”

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: “…Harras, and Mostafa Ammar / /7.1 Introduction 159 / /7.2 Design Space with Examples 161 / /7.2.1 Mont-Blanc 162 / /7.2.2 Computing while Charging 163 / /7.2.3 FemtoCloud 164 / /7.2.4 Serendipity 166 / /7.3 FemtoCloud Performance Evaluation 168 / /7.3.1 Experimental Setup 168 / /7.3.2 FemtoCloud Simulation Results 169 / /7.3.3 FemtoCloud Prototype Evaluation 173 / /7.4 Serendipity Performance Evaluation 175 / /7.4.1 Experimental Setup 175 / /7.4.2 Serendipity's Performance Benefits 176 / /7.4.3 Impact of Network Environment 179 / /7.4.4 The Impact of the Job Properties 182 / /7.5 Challenges 186 / /References 186 / /III APPLICATIONS OF FOG 189 / /8 The Role of Fog Computing in the Future of the Automobile 191 /Flavio Bonomi, Stefan Poledna, and Wilfried Steiner / /8.1 Introduction 191 / /8.2 Current Automobile Electronic Architectures 193 / /8.3 Future Challenges of Automotive E/E Architectures and Solution Strategies 195 / /8.4 Future Automobiles as Fog Nodes on Wheels 200 / /8.5 Deterministic FOG Nodes on Wheels Through Real-Time Computing and Time-Triggered Technologies /203 / /8.5.1 Deterministic Fog Node Addressing the Scalability Challenge through Virtualization 203 / /8.5.2 Deterministic Fog Node Addressing the Connectivity and Security Challenges 204 / /8.5.3 Emerging Use Case of Deterministic Fog Nodes in Automotive Applications - Vehicle-Wide /Virtualization 206 / /8.6 Conclusion 209 / /References 209 / /9 Geographic Addressing for Field Networks 211 /Robert J. …”

Tabla de Contenidos: “…Expérimentation de nouveaux dispositifs inspirés d'un système de primes dans l'alloc... -- Encadré 23. …”