Tabla de Contenidos: “…Evidence from China and Germany -- High-performance computing leadership to enable advances in artificial intelligence and a thriving compute ecosystem -- Artificial intelligence in scientific discovery: Challenges and opportunities -- Artificial intelligence in science: Overview and policy proposals -- Preface -- What can artificial intelligence do for physics? …”

Tabla de Contenidos: “…Front Cover -- Table of contents -- Preface -- Organizing committee -- Boundary control of Boost three-level converters -- Analysis of the three-paralleled-connected switched-inductor boost converter -- Research on chaos characteristic of sound wave interactions in marine medium -- Improvement and simulation of DV-HOP localization algorithm in wireless sensor networks -- Eddy current loss analysis for half-speed large turbine generator -- The design and research of wafer-type tester based on microprocessor -- Design and implementation of SPI flash controller based on Xilinx FPGA -- The current-voltage characteristics of zinc phthalocyanine organic thin film transistor -- Design and implementation of 8-bit MCU based on triple levels pipeline structure -- The operating characteristics measurements and analysis of CuPc thin film transistor -- Research on the technology of static type induction heating -- Analysis of static operating characteristics and potential distribution of the CuPc-OSIT using finite element method -- Design on virtual experiment system for communication principle based on LabVIEW -- Analysis of the working mechanism of organic static induction transistor -- The photoelectric characteristics of vertical organic thin-film transistor -- Design of ZigBee-based athletes pulse detection system -- The design and implementation based on the Android platform of business process management system -- The report based on OFDM power line communications system simulation platform -- Numerical analysis of the electric potential distribution of two dimension in the conductive channel of organic static induction transistor -- The optimization of CAN communication network in automobiles -- Design and implementation of 16-bit high speed fixed-point multiplier based on FPGA -- FPGA implementation of the parallel CRC module in vehicular ad hoc networks -- Optimization design of SDRAM controller based on FPGA in network-processor system -- The numerical analyze the change of gate length for the influence of organic static induction transistor potential distribution inside the conducting channel -- Motion characteristics of water droplet under AC and DC electric field -- A greenhouse seedling control system based on PLC and HMI -- Design of support vector machine recognizer based on single chip microcomputer -- Call identification and interception system based on STC MCU -- Design of fuzzy PID controller based on FPGA -- The affection of different rotor structures on starting and operating performance in U-type single phase permanent magnet synchronous motor…”

Tabla de Contenidos: “…Improved diagnostic tests and performance of LTBI tests in at-risk populations -- 8.4. …”

Tabla de Contenidos: “…Low carbon lining for tunnelling precast segment -- How Dramix® fibre reinforced concrete could facilitate this achievement -- ADVANTEX: Research of innovative tools to support the logistics of the use of excavation materials produced by the Lyon-Turin railway line for the best sustainability and circular economy of the process -- Final design considerations for the major rehabilitation of the Montreal Lafontaine Tunnel -- Carbon footprint emissions of different tunneling construction methods Preliminary design and socio-economic benefits of a road tunnel construction in the Tzoumerka mountainous area -- Managing tunnel infrastructure: A new guideline -- Underground solution for urban resilience: Stormwater management infrastructure -- Advancement of conventional cost benefit for selection of truly sustainable infrastructure alternatives -- Practical countermeasures for road tunnels against collapse of lining caused by earthquake -- Sustainable and resilient city: The case study of a hypogeum stadium in a desert area Autostrade per l'Italia (ASPI) TRS Tunnel Renewal Strategy: The cases of Castello 1 left, San Fermo right and Colle Marino left tunnels -- Resins filling injections of an extensive system of voids behind the final lining of Monte Baldo highway tunnel -- Shafts and spiral tunnels for large heat storages -- an economic study on ideal geometries -- Waterproof sprayed concrete with improved sustainability performance -- Environmental profile of bentonite drilling fluids for civil engineering applications Experimental study on cyclic shear behavior of biopolymer-treated soil as a tunnel backfill material -- Search for potential compressed air energy storage sites in Switzerland -- Mixed use potential of existing road tunnels for conveying water for hydropower generation: A case study of motorway tunnels in Swat, Pakistan -- The new Line 16 São Paulo Metro and best use of zero-carbon technology -- On the mechanical behavior of underground pipeline with separated joints rehabilitated by cured in place pipe…”

Tabla de Contenidos: “…/ What Every Manager Should Know About Machine Learning : A non-technical primer / The Three Types of AI : First, understand which technologies perform which types of tasks / AI Doesn't Have to Be Too Complicated or Expensive for Your Business : Focus on data quality, not quantity / How AI Fits into Your Data Science Team : Get over the cultural hurdles and avoid exaggerated claims / Ramp Up Your Team's Predictive Analytics Skills : Three pitfalls your team needs to avoid / Assembling Your AI Operations Team : A top-notch model is no good if your people can't connect it to your existing systems / How to Spot a Machine Learning Opportunity : What do you want to predict, and do you have the data? …”

Tabla de Contenidos: “…Cover -- Half Title -- Series Page -- Title Page -- Copyright Page -- Table of Contents -- Editors -- Contributors -- Preface -- Chapter 1 Integration of Nature-Inspired Mechanisms to Machine Learning in Real Time Sensors, Controllers, and Actuators for Industrial Automation -- Chapter 2 The Implications of Cloud Computing, IoT, and Wearable Robotics for Smart Healthcare and Agriculture Solutions -- Chapter 3 Role of Human-Robot Interaction in Building Automated Mixed Palletization Based on Industrial Applications -- Chapter 4 Emerging Soft Computing and Machine Learning Techniques Applicable in Industrial and Automated Applications -- Chapter 5 PSO-Based Nature-Inspired Mechanisms for Robots during Smart Decision-Making for Industry 4.0 -- Chapter 6 Application of AI-Based Learning in Automated Applications and Soft Computing Mechanisms Applicable in Industries -- Chapter 7 Investigating Scope and Applications for the Internet of Robotics in Industrial Automation -- Chapter 8 Role of Artificial Intelligence in Making Wearable Robotics Smarter -- Chapter 9 Role of Machine Learning Approaches in Optimization of AI-Based Industry 4.0 Healthcare Management Systems -- Chapter 10 Leveraging Financial Data to Optimize Automation: An Industry 4.0 approach -- Chapter 11 Assessing Cybersecurity Risks in the Age of Robotics and Automation: Frameworks and Strategies for Risk Management -- Chapter 12 The Role of Education in Addressing the Workforce Challenges of Automation: A Global Perspective -- Chapter 13 The Intersection of Human Resource Management and Automation: Opportunities and Challenges for HR Professionals -- Chapter 14 Data-Driven Insights for Agricultural Management: Leveraging Industry 4.0 Technologies for Improved Crop Yields and Resource Optimization -- Chapter 15 Data Analytics and ML for Optimized Performance in Industry 4.0 -- Chapter 16 Business Intelligence in Action: Way of Successful Implementation of Automated Systems -- Chapter 17 A Review of Dielectric Resonator Antennas (DRA)-Based RFID Technology for Industry 4.0 -- Chapter 18 Leveraging Blockchain for Improved Supply Chain Management and Traceability in Industry 4.0 -- Chapter 19 Securing Automated Systems with BT: Opportunities and Challenges -- Chapter 20 Transforming Healthcare with Industry 4.0: The Impact of Social Media on Mental Health -- Chapter 21 Multiband Antenna Design for Internet of Things (IoT) Applications…”

Tabla de Contenidos: “…Skorupski, Joe Fitzpatrick and Karla Egan -- Using Nonlinear Regression to Identify Unusual Performance Level Classification Rates / J. Michael Clark, William P. …”

Tabla de Contenidos: “…Mediating modernity: Theorizing reception in a non-Western society / Arvind Rajagopal ; 21. Performing a dream and its dissolution: A social history of broadcasting in Israel / Tamar Liebes ; 22. …”

Tabla de Contenidos: “…Craig Howes Research Methods for Studying Graphic BiographyCandida Rifkind Working with Family HistoriesAshley Barnwell Tracing Emotional Bonds in Family Letters/ A Pursuit of an Epistolary MelodyLeena Kurvet-Kaossar Life Narrative Methods for Working with DiariesKylie Cardell Autoethnographic Life Writing: Reaching Beyond, Crossing OverSally Ann Murray Telling life stories using creative methods in qualitative interviewsSigne Ravn Performing and broadcasting lives: Auto/biographical testimonies in theatre and radioGunn Gudmundsdottir Big Data and Self-Tracking: Research TrajectoriesJulie Rak FrameworksAnother StoryJeanine Leane Reading Digital Lives GenerouslyLaurie McNeill and John Zuern Reading the Life Narratives of Children and YouthKate Douglas Negotiated Truths and Iterative Practice in Action: The Women In Conflict Expressive Life Writing ProjectMeg Jensen and Siobhan Campbell Researching Online Biographical Media and Death Narratives After the Digital TurnPamela GrahamAn Epistemological Approach to Trans* AutobiographySarah Ray RondatGenetics and Auto/biographyPramod K. …”

Tabla de Contenidos: “…VIRTUAL ACTS: Taking Langer into Performance Art, Christophe Van Eecke (Radboud Nijmegen, the Netherlands) -- 18. …”

Tabla de Contenidos: “…6.2.1 Quadrature Amplitude Modulation Simulator 339 -- 6.2.2 Filtered Noise Method 339 -- 6.2.3 Sum of Sinusoids Method (Jakes Method) 341 -- 6.2.4 Frequency Domain Method 343 -- 6.2.5 Reverberation Chambers (or Mode-Stirred Chambers) 344 -- 6.3 Wideband Stochastic Channel Simulator 346 -- 6.3.1 Time Domain Channel Simulators 346 -- 6.3.2 Frequency Domain Simulators 348 -- 6.4 Frequency Domain Implementation Using Fast Convolution 349 -- 6.5 Channel Block Realization from Measured Data 351 -- 6.6 Theoretical Prediction of System Performance in Additive White Gaussian Noise 353 -- 6.6.1 Matched Filter and Correlation Detector 354 -- 6.6.2 Bit Error Rate of the Matched Filter Detector in AWGN 356 -- 6.6.3 Bit Error Rate with Noncoherent Detectors 357 -- 6.6.4 Comparison of BER of Coherent and Noncoherent Detectors 358 -- 6.6.5 Higher Order Modulation 358 -- 6.7 Prediction of System Performance in Fading Channels 361 -- 6.7.1 Narrowband Signals 361 -- 6.7.2 Wideband Signals 363 -- 6.8 Bit Error Rate Prediction for Wireless Standards 364 -- 6.8.1 IEEE 802.16-d Standard 365 -- 6.8.2 IEEE 802.11-a Standard 371 -- 6.8.3 Third Generation WCDMA Standard 372 -- 6.9 Enhancement of Performance Using Diversity Gain 376 -- 6.9.1 Diversity Combining Methods 377 -- 6.9.2 Diversity Gain Prediction of Rayleigh Fading Channels from Measurements in a Reverberation Chamber 382 -- References 383 -- Appendix 1 385 -- A.1 Probability Distribution Functions 385 -- A.2 The Gaussian (Normal) Distribution 385 -- A.3 The Rayleigh Distribution 387 -- A.4 The Rician Distribution 388 -- A.5 The Nakagami m-Distribution 389 -- A.6 The Weibull Distribution 390 -- A.7 The Log-Normal Distribution 390 -- A.8 The Suzuki Distribution 391 -- A.9 The Chi-Square Distribution 391 -- References 391 -- Appendix 2 393 -- Index 395.…”

Tabla de Contenidos: “…6.5.2 Laplace and Inverse Laplace Transform -- 6.6 Weibull Renewal with Increasing Failure Rate -- 6.6.1 Transient Renewal Function -- 6.6.2 Approximation without Oscillation -- 6.6.3 Approximation with Oscillation -- 6.7 Renewal under Deterministic Fleet Expansion -- 6.7.1 Superimposed Exponential Renewal -- 6.7.2 Superimposed Erlang Renewal -- 6.7.3 Lead‐Time Renewal -- 6.8 Renewal under Stochastic Fleet Expansion -- 6.8.1 Aggregate Exponential Renewal -- 6.8.2 Lead‐Time Renewal -- 6.9 Case Study -- 6.9.1 Installed Base of Wind Turbines in the USA -- 6.9.2 Spare Parts Prediction under Fleet Expansion -- References -- Chapter 7 Performance‐Based Maintenance -- 7.1 Introduction -- 7.2 Corrective Maintenance -- 7.2.1 Classification of Maintenance Policy -- 7.2.2 Corrective Maintenance Management -- 7.3 Preventive Maintenance -- 7.3.1 Block Replacement -- 7.3.2 Age‐Based Replacement -- 7.4 Condition‐Based Maintenance -- 7.4.1 Principle of Condition‐Based Maintenance -- 7.4.2 Proportional Hazard Model -- 7.4.3 Gamma Degradation Process -- 7.4.4 Stationary Gamma Degradation Process -- 7.5 Inverse Gaussian Degradation Process -- 7.5.1 Distribution of Inverse Gaussian Process -- 7.5.2 Probability Density Function of First Passage Time -- 7.6 Non‐Stationary Gaussian Degradation Process -- 7.6.1 The Degradation Model -- 7.6.2 Hypothesis Testing -- 7.6.3 Estimation of Remaining Useful Life -- 7.7 Performance‐Based Maintenance -- 7.7.1 The Rise of Performance‐Driven Service -- 7.7.2 Procedures for PBM Implementation -- 7.7.3 Five Overarching Performance Measures -- 7.7.4 Reliability and MTBF Considering Usage Rate -- 7.7.5 Operational Availability under Corrective Maintenance -- 7.7.6 Operational Availability under Preventive Maintenance -- 7.8 Contracting for Performance‐Based Logistics -- 7.8.1 Incentive Payment Schemes…”

Tabla de Contenidos: “…3.2.2 Die Arbeit in einem separaten Livestudio -- 3.2.3 Kommunikation im Studio -- 3.2.4 Behelfslösungen für das Monitoring in nur einem Raum -- 3.3 Performances mit Comping aufbauen -- 3.3.1 Begrenzen Sie die Zahl der Spuren -- 3.3.2 Arbeiten Sie mit einer Comping-Übersicht -- 3.4 Auf der Suche nach der besten Performance -- 3.4.1 Hinweise für die Performance -- 3.4.2 Tipps fürs Arrangement -- 3.5 Nächster Halt: Mikrofone! …”

Tabla de Contenidos: “…Architectural scenarios and considerations -- 2.1 Architectural scenarios -- 2.1.1 Scenario 1: Single Domino/LEI server -- 2.1.2 Scenario 2: Remote database servers -- 2.1.3 Scenario 3: LEI access to multiple relational back-ends -- 2.1.4 Scenario 4: LEI 6 Advanced Realtime plus Notes replication -- 2.1.5 Scenario 5: Decentralized Advanced RealTime access -- 2.2 Security considerations -- 2.2.1 Generic user ID and password -- 2.2.2 Integrated credentials -- 2.2.3 Fields and public key encryption -- 2.3 Performance considerations -- 2.3.1 LEI considerations -- 2.3.2 Performance spectrum scenarios -- 2.3.3 RDB performance considerations -- 2.3.4 Persistent connections -- Chapter 3. …”

Tabla de Contenidos: “…6.2.2 Wrapper Method -- 6.2.2.1 Procedure -- 6.2.2.2 Advantages and Disadvantages -- 6.2.2.3 Forward Selection Algorithm -- 6.2.2.4 Backward Selection Algorithm -- 6.2.3 Embedded Method -- 6.2.3.1 Least Absolute Shrinkage and Selection Operator -- 6.2.3.2 Advantages -- 6.2.3.3 Disadvantages -- 6.3 Feature Extraction -- 6.3.1 Principal Component Analysis -- 6.3.1.1 Procedure -- 6.3.1.2 Implementation -- 6.3.1.3 Advantages -- 6.3.1.4 Disadvantages -- 6.3.2 Linear Discriminant Analysis -- 6.3.2.1 Concept -- 6.3.2.2 Implementation -- 6.3.2.3 Advantages -- 6.3.2.4 Disadvantages -- 6.4 Feature Learning -- 6.4.1 Supervised Learning -- 6.4.2 Unsupervised Learning -- 6.4.2.1 Procedure -- 6.4.2.2 Advantages -- 6.4.2.3 Disadvantages -- 6.4.3 Deep Learning -- 6.4.3.1 Neural Network Architecture -- 6.4.3.2 Training Process -- 6.4.3.3 Advantages -- 6.4.3.4 Disadvantages -- 6.4.4 Machine Learning and Deep Learning -- 6.5 Future Research and Development -- 6.6 Future Scope -- 6.7 Conclusion -- References -- Chapter 7 Fusion of Phase and Local Features for CBIR -- 7.1 Introduction -- 7.2 Overview of the Proposed System -- 7.3 Proposed Hybrid-Shape Descriptors -- 7.3.1 Global Feature Extraction Using ZMs -- 7.3.1.1 Recurrence Relation for Radial Polynomials Rpq(r) -- 7.3.1.2 Recurrence Relation for Trigonometric Functions -- 7.3.2 Local Feature Extraction Using Hough Transform -- 7.3.3 Features Dimension -- 7.3.4 Effectiveness of the Proposed Descriptors -- 7.4 Similarity Measurement -- 7.5 Experimental Study and Performance Evaluation -- 7.5.1 Precision and Recall (P - R) -- 7.5.2 Database Construction -- 7.5.3 Experimental Study -- 7.5.3.1 Evaluation of Image Retrieval Performance on Subject Databases -- 7.5.3.2 Evaluation of Image Retrieval Performance on Geometric and Photometric Transformed Databases -- 7.5.3.3 Evaluation of Scalability and Time Complexity…”

Tabla de Contenidos: “…-- 13.2.1 Types of Machine Learning -- 13.2.2 Tasks Performed by Machine Learning -- 13.2.3 Depth of Machine Learning -- 13.3 Deep Learning -- 13.3.1 Training of Deep Learning Models -- 13.3.2 Algorithms Used to Train Deep Learning Models -- 13.4 Classification of Images Using a Convolutional Neural Network -- 13.4.1 Classifying Images Using Traditional Methods -- 13.4.2 Image Classification Using CNN -- 13.4.3 Overview of CNN Models Used for Image Classification…”

Tabla de Contenidos: “…Configuring Physics -- Setting shapes -- Physics Object types -- Filtering collisions -- Detecting collisions -- Detecting Trigger events -- Modifying the other Object -- Moving with Physics -- Applying forces -- Tweaking Physics -- Summary -- Chapter 17: Win and Lose Condition -- Creating Object Managers -- Sharing Variables with the Singleton design pattern -- Sharing Variables with Visual Scripting -- Creating Managers -- Creating Game Modes -- Improving our code with events -- Summary -- Chapter 18: Scripting the UI, Sounds, and Graphics -- Scripting the UI -- Showing information in the UI -- Programming the Pause menu -- Scripting feedback -- Scripting visual feedback -- Scripting audio feedback -- Scripting animations -- Summary -- Chapter 19: Implementing Game AI for Building Enemies -- Gathering information with sensors -- Creating Three-Filters sensors with C# -- Creating Three-Filters sensors with Visual Scripting -- Debugging with Gizmos -- Making decisions with FSMs -- Creating the FSM in C# -- Creating transitions -- Creating the FSM in Visual Scripting -- Executing FSM actions -- Calculating our scene's Pathfinding -- Using pathfinding -- Adding the final details -- Summary -- Chapter 20: Scene Performance Optimization -- Optimizing graphics -- Introduction to graphic engines -- Using the Frame Debugger -- Using batching -- Other optimizations -- Optimizing processing -- Detecting CPU- and GPU-bound -- Using the CPU Usage Profiler -- General CPU optimization techniques -- Optimizing memory -- Memory allocation and the garbage collector -- Using the Memory Profiler -- Summary -- Section 4 - Releasing Your Game -- Chapter 21: Building the Project -- Building a project -- Debugging the Build -- Debugging Code -- Profiling performance -- Summary -- Chapter 22: Finishing Touches -- Iterating your game -- Testing and feedback…”

Tabla de Contenidos: “…Advanced Machining Processes -- 15.1 High-Speed Machining -- 15.1.1 Definition of Basic Features of HSM -- 15.1.2 Physical Aspects of HSM -- 15.1.3 HSC Technology and Appliances -- 15.1.4 Basic Applications of HSC Technology -- 15.1.5 Machining of Monolithic Parts -- References -- 15.2 Dry and Semi-Dry Machining -- 15.2.1 The Way to Dry Machining -- 15.2.2 Machine Tools and Equipment for Dry and Quasi-Dry Machining -- 15.2.3 Dry Machining Operations -- 15.2.4 Introduction of Near-Dry Machining -- 15.2.5 MQL Media and Mixture Supplying Systems -- 15.2.6 Machine Tools for Performing NDM Operations -- References -- 15.3 Hard Part Machining -- 15.3.1 Definition of Basic Feature of Hard Part Machining -- 15.3.2 Physical Aspects of Hard Machining -- 15.3.3 Applications of HM Technology -- 15.3.4 Surface Finish Produced by HPM -- References -- 15.4 High-Performance and High-Efficiency Machining -- 15.4.1 Basic Aspects of High-Performance and High-Efficiency Machining -- 15.4.2 Machine Tools and Tooling -- 15.4.3 Simplifying and Improving Machining Operations -- References -- 15.5 Multitasking and One-Pass Machining -- 15.5.1 Background of Multitasking Machining -- 15.5.2 Multitasking Machine Tools and Tooling -- 15.5.3 One-Pass Machining -- References -- 15.6 Ultrasonically and Thermally Assisted Hybrid Machining Processes -- 15.6.1 Ultrasonically Assisted Machining and Ultrasonic Vibration Cutting -- 15.6.2 Laser-Assisted Machining -- 15.6.3 Plasma-Assisted Machining -- References -- 16. …”

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: “…Troubleshooting, hints &amp -- tips -- 5.1 Most common errors -- 5.1.1 Server installation errors -- 5.1.2 Operational errors -- 5.2 Performance tuning (DB and sizing issues) -- 5.2.1 Tivoli Storage Manager tuning options -- Appendix A. …”