Tabla de Contenidos: “…7.3.3 Localization, Mapping, and SLAM -- 7.3.4 Control Strategies -- 7.3.5 Planning Routes and Scheduling -- 7.4 Wheeled Mobile Robots in Industry -- 7.4.1 About -- 7.4.2 Setup -- 7.4.3 Sensors -- 7.4.4 Localization and Mapping -- 7.4.5 Control -- 7.4.6 Path Planning -- 7.4.7 Decision Making -- 7.5 Wheeled Mobile Robots in Domestic Environments -- 7.5.1 About -- 7.5.2 Setup -- 7.5.3 Sensors -- 7.5.4 Localization and Mapping -- 7.5.5 Path Planning -- 7.5.6 Control -- 7.5.7 Decision Making -- 7.6 Assistive Mobile Robots in Walking Rehabilitation Therapy -- 7.6.1 About -- 7.6.2 Setup -- 7.6.3 Sensors -- 7.6.4 Localization and Mapping -- 7.6.5 Control -- 7.6.6 Path Planning -- References -- Chapter 8: Project Examples for Laboratory Practice -- 8.1 Introduction -- 8.2 Localization Based on Bayesian Filter Within a Network of Paths and Crossroads -- 8.2.1 Introduction -- 8.2.2 Line Following -- 8.2.3 Odometry -- 8.2.4 Map Building -- 8.2.5 Localization -- 8.3 Localization Based on Extended Kalman Filter Using Indoor Global Positioning System and Odometry -- 8.3.1 Introduction -- 8.3.2 Experimental Setup -- 8.3.3 Extended Kalman Filter -- 8.4 Particle-Filter-Based Localization in a Pattern of Colored Tiles -- 8.4.1 Introduction -- 8.4.2 Experimental Setup -- 8.4.3 Manual Control -- 8.4.4 Wheel Odometry -- 8.4.5 Color Sensor Calibration -- 8.4.6 Particle Filter -- 8.5 Control of Vehicles in a Linear Formation -- 8.5.1 Introduction -- 8.5.2 Localization Using Odometry -- 8.5.3 Estimating Reference Trajectory -- 8.5.4 Linear Formation Control -- 8.6 Motion and Strategy Control of Multiagent Soccer Robots -- 8.6.1 Introduction -- 8.6.2 Motion Control -- 8.6.3 Behavior-Based Agent Operation -- 8.6.4 Multiagent Game Strategy -- 8.7 Image-Based Control of a Mobile Robot -- 8.7.1 Introduction -- 8.7.2 Experimental Setup -- 8.7.3 Position-Based Visual Servoing…”

Tabla de Contenidos: “…4.2.2 Microorganism-Based Biotemplates -- 4.2.2.1 Bacteria -- 4.2.2.2 Fungi -- 4.2.2.3 Yeast -- 4.2.2.4 Algae -- 4.3 Synthesis Routes -- 4.3.1 Effect of pH -- 4.3.2 Effect of Temperature -- 4.3.3 Effect of Biomolecules -- 4.3.3.1 Plant-Based -- 4.3.3.2 Microorganism-Based -- 4.4 Applications -- 4.4.1 Biomedical Application -- 4.4.1.1 Antimicrobial Activity -- 4.4.1.2 Biomedication -- 4.4.1.3 Vaccines -- 4.4.1.4 Antidiabetic -- 4.4.1.5 Diagnostic Applications -- 4.4.2 Environmental Application -- 4.4.2.1 Environmental Remediation -- 4.4.2.2 Catalytic Removal of Textile Dyes -- 4.4.2.3 Wastewater Treatment -- 4.4.2.4 Agriculture -- 4.5 Conclusion and Outlook -- References -- Chapter 5 Green Conversion Methods to Prepare Nanoparticle -- 5.0 Introduction -- 5.1 Bacteria -- 5.2 Fungi -- 5.3 Yeast -- 5.4 Viruses -- 5.5 Algae -- 5.6 Plants -- 5.7 Conclusion and Perspectives -- References -- Chapter 6 Bioinspired Green Synthesis of Nanomaterials From Algae -- 6.1 Introduction -- 6.2 Algal System-Mediated Nanomaterial Synthesis -- 6.3 Factors Affecting the Green Synthesis of Nanomaterials -- 6.3.1 Light -- 6.3.2 Temperature -- 6.3.3 Incubation Period -- 6.3.4 pH -- 6.3.5 Precursor Concentration and Bioactive Catalyst -- 6.4 Applications of the Green Synthesized Nanomaterials -- 6.4.1 Antimicrobial Agents -- 6.4.2 Anticancerous -- 6.4.3 Biosensing -- 6.4.4 Bioremediation -- 6.5 Future Perspectives -- 6.6 Conclusion -- References -- Chapter 7 Interactions of Nanoparticles with Plants: Accumulation and Effects -- 7.1 Introduction -- 7.2 Uptake and Translocation of Nanoparticles and Nanocarriers in Plants -- 7.3 Nanoparticle-Mediated Sensing and Biosensing in Plants -- 7.4 Tolerance Versus Toxicity of Nanoparticles in Plants -- 7.5 Nanoparticle-Mediated Delivery of Fertilizers, Pesticides, Other Agrochemicals in Plants…”

Tabla de Contenidos: “…Equilibrium Composition of Ceria -- References -- Chapter 2 Solar Metal Fuels for Future Transportation -- 2.1 Introduction -- 2.1.1 Sustainable Strategies to Address Climate Change -- 2.1.2 Circular Economy -- 2.1.3 Sustainable Solar Recycling of Metal Fuels -- 2.2 Direct Combustion of Solar Metal Fuels -- 2.2.1 Stabilized Metal-Fuel Flame -- 2.2.2 Combustion Engineering -- 2.2.3 Designing Metal-Fueled Engines -- 2.3 Regeneration of Metal Fuels Through the Solar Reduction of Oxides -- 2.3.1 Thermodynamics and Kinetics of Oxides Reduction -- 2.3.2 Effect of Some Parameters on the Reduction Yield -- 2.3.2.1 Carbon-Reducing Agent -- 2.3.2.2 Catalysts and Additives -- 2.3.2.3 Mechanical Milling -- 2.3.2.4 CO Partial Pressure -- 2.3.2.5 Carrier Gas -- 2.3.2.6 Fast Preheating -- 2.3.2.7 Progressive Heating -- 2.3.3 Reverse Reoxidation of the Produced Metal Powders -- 2.3.4 Reduction of Oxides Using Concentrated Solar Power…”

Tabla de Contenidos: “…Device management -- 11.1 Device management overview -- 11.2 Architecture -- 11.2.1 Device Manager -- 11.2.2 OSGi Agent -- 11.2.3 Device Manager database -- 11.2.4 Device Management portlets -- 11.2.5 Device Manager Console -- 11.3 OGSGi device sample scenario -- 11.3.1 Software distribution for OSGi bundles -- 11.3.2 Software removal for OSGi bundles -- 11.3.3 Connecting the Device Manager server and WebSphere Studio Device Developer -- 11.4 Device Manager sample scenario -- 11.4.1 Interim Fix 1 and IFix instructions -- 11.4.2 Device Manager scenario description -- 11.4.3 Device Manager bundle procedure -- 11.4.4 Update the sample application to use the new service -- 11.4.5 Device manager bundle review -- 11.4.6 Running the sample application with device management bundle -- 11.4.7 Device Troubleshooting -- 11.5 Troubleshooting with Device Manager -- Appendix A. …”

Tabla de Contenidos: “…Linux Clients for DWA 6.5 -- 8.1 Mozilla -- 8.1.1 Mozilla installation steps -- 8.2 Offline usage and Domino Offline Services for Linux -- 8.2.1 Overview of DOLS -- 8.2.2 Functionality -- 8.3 DOLS Setup on a Linux server -- 8.3.1 Configure DOLS during Domino Server setup -- 8.3.2 Configure DOLS manually -- 8.3.3 DOLS Administration -- 8.3.4 DOLS in a clustered environment -- 8.3.5 Using Web Site documents -- 8.3.6 DOLS, agents, and subscription considerations -- 8.3.7 Server configuration -- 8.4 Installing and configuring the DOLS client -- 8.4.1 Overview of supported Linux distributions and DOLS -- 8.4.2 Deployment and installation of the DOLS client -- 8.4.3 Local requirements: checklist for installing DOLS plug-in -- 8.4.4 Working offline -- 8.4.5 Preferences for Offline Users -- 8.5 Uninstalling DWA 6.5 Offline Services -- 8.5.1 Mobile or condensed Directory Catalog -- 8.6 Troubleshooting DWA 6.5 Offline Services -- 8.6.1 Common error messages with the plug-in -- 8.6.2 Linux directory structure and installed files -- 8.6.3 Case of the missing icons for DOLS -- 8.6.4 Mozilla does not start after launching DOLS -- 8.6.5 Troubleshooting DOLS from the dol.log and the command line -- 8.6.6 Using the browser for troubleshooting offline configuration -- Part 4 Customization and integration -- Chapter 9. …”

Tabla de Contenidos: “…Cluster 1600 hardware -- 2.1 Overview -- 2.2 Cluster 1600 hardware components -- 2.2.1 Nodes -- 2.2.2 Frames -- 2.2.3 Switches -- 2.2.4 PSSP control workstations -- 2.2.5 CSM for AIX management server -- 2.2.6 Hardware Management Console (HMC) -- 2.3 CSM and PSSP hardware support -- 2.3.1 CSM-managed node requirements -- 2.4 PSSP control workstation -- 2.4.1 Control workstation requirements -- 2.4.2 Supported control workstations -- 2.4.3 High Availability Control Workstation -- 2.4.4 HACWS limitations -- 2.5 CSM management server -- 2.5.1 Memory and disk space -- 2.5.2 Network requirements -- 2.5.3 Asynchronous card requirements -- 2.5.4 Using a Logical Partition (LPAR) as a CSM management server -- 2.6 Cluster 1600 server concepts -- 2.6.1 pSeries architecture -- 2.6.2 Cluster 1600 and the HMC -- 2.6.3 Firmware -- 2.6.4 Electronic Service Agent -- 2.6.5 Planning for Cluster 1600 servers -- 2.7 Hardware supported and currently marketed -- 2.8 pSeries servers -- 2.8.1 pSeries 615 server (7029-6C3 and 6E3 deskside) -- 2.8.2 pSeries 630 server (7028-6C4 and 6E4 deskside) -- 2.8.3 pSeries 650 server (7038-6M2) -- 2.8.4 pSeries 655 server (7039-651) -- 2.8.5 670 Server (7040-671) -- 2.8.6 690 server (7040-681) -- 2.8.7 xSeries servers -- 2.9 Switches -- 2.9.1 9076 model 555 -- 2.9.2 9076 model 556 -- 2.9.3 9076 model 557 -- 2.9.4 9076 model 558 -- 2.9.5 7045-SW4 pSeries HPS (High Performance Switch) -- 2.10 Switch adapters -- 2.10.1 Switch adapter placement restrictions -- 2.10.2 pSeries HPS switch network interface cards (SNI)…”

Tabla de Contenidos: “…6.1.2 Managing permissions between GitHub and CircleCI -- 6.1.3 Signing commits and tags with Git -- 6.2 Access control for container storage -- 6.2.1 Managing permissions between Docker Hub and CircleCI -- 6.2.2 Signing containers with Docker Content Trust -- 6.3 Access control for infrastructure management -- 6.3.1 Managing permissions using AWS roles and policies -- 6.3.2 Distributing secrets to production systems -- Summary -- Part 2: Watching for anomalies and protecting services against attacks -- Chapter 7: Collecting and storing logs -- 7.1 Collecting logs from systems and applications -- 7.1.1 Collecting logs from systems -- 7.1.2 Collecting application logs -- 7.1.3 Infrastructure logging -- 7.1.4 Collecting logs from GitHub -- 7.2 Streaming log events through message brokers -- 7.3 Processing events in log consumers -- 7.4 Storing and archiving logs -- 7.5 Accessing logs -- Summary -- Chapter 8: Analyzing logs for fraud and attacks -- 8.1 Architecture of a log-analysis layer -- 8.2 Detecting attacks using string signatures -- 8.3 Statistical models for fraud detection -- 8.3.1 Sliding windows and circular buffers -- 8.3.2 Moving averages -- 8.4 Using geographic data to find abuses -- 8.4.1 Geoprofiling users -- 8.4.2 Calculating distances -- 8.4.3 Finding a user's normal connection area -- 8.5 Detecting anomalies in known patterns -- 8.5.1 User-agent signature -- 8.5.2 Anomalous browser -- 8.5.3 Interaction patterns -- 8.6 Raising alerts to operators and end users -- 8.6.1 Escalating security events to operators -- 8.6.2 How and when to notify end users -- Summary -- Chapter 9: Detecting intrusions -- 9.1 The seven phases of an intrusion: the kill chain -- 9.2 What are indicators of compromise? …”

Tabla de Contenidos: “…9.4 Continuity of the Moroccan Merchant Colony -- 9.4.1 Arráez Tuffe (1796-1800) -- 9.4.2 Haslem el Rubio (1797) -- 9.4.3 Absalem el Jedit (1798-1800) -- 9.4.4 Hamet Ford (El Sordo) (1798-1803) -- 9.4.5 Mahamet Chandri (1799) -- 9.4.6 Hamet Bohelen (1799) -- 9.4.7 Ataib (1799) -- 9.4.8 Alhach Malamud Almasaid (1799) -- 9.4.9 Hamet Yngles Salazar (1799-1800) -- 9.4.10 Hach Ali Elfucay (1799-1800) -- 9.4.11 Caddur Ben Gileli (1799-1804) -- 9.4.12 Mohamet Valenciano (1800) -- 9.4.13 Haljach Abdalá (1800) -- 9.4.14 Haljach Candur (1800) -- 9.4.15 Algache Abdarrajaman Acatam (1800) -- 9.4.16 Hamet Bujalel (1800) -- 9.4.17 Abdasalem Buasa (1800) -- 9.4.18 Hach Hamet Absalem (1800-1801) -- 9.4.19 Hach Mekki (1800-1801) -- 9.4.20 Achijamet and Jamet (1800-1801) -- 9.4.21 Ibrahim Lubaris (1801) -- 9.4.22 Mahomed Ben El Fach Ahmed Mogtal El Tarbelsi (1801) -- 9.4.23 Taibe Menaiza and Meliro Açabel (1801) -- 9.4.24 Ali Turqui (1801-1803) -- 9.4.25 Sidi Abdala Carcet (1801-1807) -- 9.4.26 Staibesel (1802) -- 9.4.27 Mahomet Bencherif (1807) -- 9.4.28 Tajar Ben Majamet (1808) -- 9.4.29 Achay Candor Abbo (1810) -- 9.4.30 Majamet Boali (1814-1815) -- 9.5 Algerian, Tunisian, and Tripolitan Captains, Pursers, and Merchants -- 9.5.1 Ben Talb (1786) -- 9.5.2 Youssef el Tripolino (1786) -- 9.5.3 Mahamet Ben Seitun (1790) -- 9.5.4 Aggi Yunis Ben Yunis (1799-1804) -- 9.5.5 Mahamet Arrizzi (1800) -- 9.5.6 Captain Hadgi Zayton (1800) -- 9.5.7 Soliman Ben Yunis (1801) -- 9.5.8 Caddur Ben Massus and Abdalá Karsis (1802) -- 9.5.9 Haggi Hamet Arcandi (1802) -- 9.5.10 Captain Aggi Abdallah (1806) -- 9.5.11 Captain Mahamet Ben Mocessa (1806-1807) -- 9.5.12 Captain Amet Ben Mustafa (1807-1808) -- 9.5.13 Hassan Haltay (1811) -- Epilogue The First Moroccan Agent on Spanish Soil (1798) -- Conclusions -- Bibliography -- Index of Personal and Place Names…”

Tabla de Contenidos: “…-- 6 Conclusions and Future Work -- References -- Second-Order Hyperproperties -- 1 Introduction -- 2 Preliminaries -- 3 Second-Order HyperLTL -- 3.1 Hyper2LTL -- 3.2 Hyper2LTLfp -- 3.3 Common Knowledge in Multi-agent Systems -- 3.4 Hyper2LTL Model Checking -- 4 Expressiveness of Hyper2LTL -- 4.1 Hyper2LTL and LTLK, C -- 4.2 Hyper2LTL and Asynchronous Hyperproperties -- 5 Model-Checking Hyper2LTLfp -- 5.1 Fixpoints in Hyper2LTLfp -- 5.2 Functions as Automata -- 5.3 Model Checking for First-Order Quantification -- 5.4 Bidirectional Model Checking -- 5.5 Computing Under- and Overapproximations -- 6 Implementation and Experiments -- 7 Related Work -- 8 Conclusion -- References -- Neural Networks and Machine Learning -- Certifying the Fairness of KNN in the Presence of Dataset Bias -- 1 Introduction…”

Tabla de Contenidos: “…9.7 A Summary of Neuromorphic Hardware Methodologies -- 9.8 Neuromorphic Computing in Robotics -- 9.8.1 Sensor Processing and Perception -- 9.8.2 Motor Control and Movement -- 9.8.3 Neuromorphic Hardware Advances -- 9.8.4 Brain-Inspired Learning Algorithms -- 9.9 Challenges in Neuromorphic Computing -- 9.9.1 Language Understanding and Interpretation -- 9.9.2 Sentiment Analysis and Emotion Recognition -- 9.9.3 Natural Language Generation -- 9.9.4 Language Translation and Multilingual Processing -- 9.9.5 Dialogue Systems and Conversational Agents -- 9.9.6 Language Modeling and Prediction -- 9.9.7 Text Summarization and Information Extraction -- 9.10 Applications of Neuromorphic Computing -- 9.10.1 Medicines -- 9.10.2 Artificial Intelligence [AI] -- 9.10.3 Imaging -- 9.10.4 Sensor Processing and Perception -- 9.10.5 Motor Control and Movement -- 9.10.6 Autonomous Navigation and Mapping -- 9.10.7 Human-Robot Interaction and Collaboration -- 9.10.8 Adaptive and Learning Capabilities -- 9.10.9 Task Planning and Decision Making -- 9.10.10 Robustness and Fault Tolerance -- 9.10.11 Some More Applications -- 9.11 Conclusion -- References -- Chapter 10 Performance Evaluation of Prototype Microstrip Patch Antenna Fabrication Using Microwave Dielectric Ceramic Nanocomposite Materials for X-Band Applications -- 10.1 Introduction -- 10.2 Materials and Methods -- 10.3 Results and Discussion -- 10.4 Conclusions -- References -- Chapter 11 Build and Deploy a Smart Speaker with Biometric Authentication and Advanced Voice Interaction Capabilities -- 11.1 Introduction -- 11.2 Cybersecurity Risk as Smart Speakers Don't Have an Authentication Process -- 11.3 Related Work -- 11.4 Overview of Biometric Authentication and the Voice Algorithm-Based Smart Speaker -- 11.5 Conclusion and Discussion -- Acknowledgements -- References…”

“…In view of the limited agent-specific information available from epidemiological studies, assessments of these agents relied mainly on carcinogenicity bioassays to reach conclusions as to the carcinogenic hazard to exposed humans…”

“…Developer, data scientist, and expert instructor Phil Tabor guides you from the basics all the way to programming your own constantly-learning AI agents. In this course, he'll break down key concepts like how RL systems learn, how to sense and process environmental data, and how to build and train AI agents. …”

“…British intelligence knew far earlier that Maclean was Moscow's agent and concealed that knowledge in a 1949-1951 counterespionage operation that de-ceived Philby and Burgess. …”

“…C'est en décembre 1997 que l'Allemagne a signé, en compagnie de trente-trois autres pays, la Convention sur la lutte contre la corruption d'agents publics étrangers dans les transactions commerciales internationales (la Convention de l'OCDE). …”

“…"Develop self-learning algorithms and agents using TensorFlow and other Python tools, frameworks, and libraries Key Features Learn, develop, and deploy advanced reinforcement learning algorithms to solve a variety of tasks Understand and develop model-free and model-based algorithms for building self-learning agents Work with advanced Reinforcement Learning concepts and algorithms such as imitation learning and evolution strategies Book Description Reinforcement Learning (RL) is a popular and promising branch of AI that involves making smarter models and agents that can automatically determine ideal behavior based on changing requirements. …”