Tabla de Contenidos: “…-- 2.4 Dual Labour Markets Before and After the Great Recession -- 2.5 Lessons from Spain -- 2.6 Dual Labour Markets and Youth Unemployment -- 2.7 How to Dismantle Dual Employment Protection Legislation -- 2.7.1 Recent EPL Reforms -- 2.7.2 Single/Unified Contracts in Theory -- 2.7.3 Single/Unified Contracts in Practice -- 2.8 Conclusions -- Acknowledgements -- Appendix -- Notes -- References -- 3 Population, Migration, Ageing and Health: A Survey -- 3.1 Introduction -- 3.2 Main Stylized Facts -- 3.3 Migration and Demographic Developments -- 3.3.1 The Selection Hypothesis -- 3.3.2 The Adaptation Hypothesis -- 3.3.3 The Disruption Hypothesis -- 3.4 Permanent versus Temporary Migration -- 3.4.1 Why Do Migrants Return? …”

Tabla de Contenidos: “…Atténuation du changement climatique et adaptation à ses effets -- Graphique 1.6. Les émissions de GES sont découplées de la croissance économique mais ne donnent encore aucun signe de recul -- 3.4. …”

Tabla de Contenidos: “…5.2 Overview of Global Precipitation Products and Data Services -- 5.2.1 TRMM Background -- 5.2.2 TRMM Products -- 5.2.3 TRMM Data Services -- 5.2.4 Global Precipitation Measurement Mission -- 5.3 Big Data Challenges and Solutions -- 5.3.1 Big Data Challenges -- 5.3.2 Solutions -- 5.4 A Prototype -- 5.4.1 Data -- 5.4.2 System Description -- 5.4.3 Examples -- 5.5 Conclusions -- Acknowledgment -- References -- Chapter 6: Algorithmic Design Considerations for Geospatial and/or Temporal Big Data -- 6.1 Motivation -- 6.1.1 Challenges -- 6.1.1.1 Algorithmic Time Complexity -- 6.1.1.2 Algorithmic Space Complexity -- 6.2 Geospatial Big Data Algorithms: The State of the Art -- 6.2.1 Volume Algorithms -- 6.2.2 Velocity Algorithms -- 6.2.3 Variety Algorithms -- 6.3 Analysis of Classical Geospatial and Temporal Algorithms -- 6.4 Approaches to Algorithmic Adaptation for Geospatial Big Data -- 6.4.1 Divide and Conquer -- 6.4.2 Subsampling -- 6.4.3 Aggregation -- 6.4.4 Filtering -- 6.4.5 Online Algorithms -- 6.4.6 Streaming Algorithms -- 6.4.7 Iterative Algorithms -- 6.4.8 Relaxation -- 6.4.9 Convergent Algorithms -- 6.4.10 Stochastic Algorithms -- 6.4.11 Batch versus Online Algorithms -- 6.4.12 Dimensionality Reduction -- 6.4.13 Example -- 6.5 Open Challenges -- 6.6 Summary -- References -- Chapter 7: Machine Learning on Geospatial Big Data -- 7.1 Motivation -- 7.1.1 Supervised, Unsupervised, and Feature Learning -- 7.1.1.1 Supervised Learning -- 7.1.1.2 Unsupervised Learning -- 7.1.1.3 Feature Learning -- 7.1.2 Big Data Challenges -- 7.1.3 Three Vs -- 7.1.3.1 Volume -- 7.1.3.2 Velocity -- 7.1.3.3 Variety -- 7.2 Geospatial Big Data Feature Learning -- 7.2.1 Approaches to Big Data Feature Learning -- 7.3 Reducing Dimensionality of Geospatial Big Data, Making Machine Learning Tractable -- 7.3.1 Feature Construction -- 7.3.1.1 Windowing in Raster Data…”

Tabla de Contenidos: “…8.4 Modeling Interacting Oscillators of a Bacillaria Colony -- 8.4.1 Observation of the Movement Activity at Uncovered Rhaphes -- 8.4.2 Interaction of Neighboring Diatoms -- 8.4.3 Coupled Oscillators -- 8.5 Kuramoto Model -- 8.5.1 Adaptation of the Kuramoto Model for a Bacillaria Colony -- 8.5.2 Analyses and Approximations -- 8.5.3 Critical Coupling -- 8.5.3.1 Uncoupled Oscillators -- 8.5.3.2 Two Oscillators -- 8.5.3.3 Chains without Retardation -- 8.5.3.4 Identical Oscillator Frequencies and Sufficiently Small Delay -- 8.5.3.5 Remarks on the General Case -- 8.5.4 Statistical Considerations and Monte Carlo Simulations -- 8.5.4.1 Expected Value and Standard Deviation -- 8.5.4.2 Distribution of Critical Coupling -- 8.5.5 Simulation of Non-Synchronous States -- 8.5.5.1 Numerical Integration -- 8.5.5.2 Visualization of the Transient -- 8.5.5.3 Discrete Fourier Transform -- 8.5.6 Coupling to a Periodic Light Source -- 8.6 Discussion -- Acknowledgment -- References -- Chapter 9 The Psychophysical World of the Motile Diatom Bacillaria paradoxa -- Abbreviations -- 9.1 Introduction -- 9.1.1 Aneural Architecture of Bacillaria -- 9.1.2 Aneural Cognition in a Broader Context -- 9.1.3 Psychophysics as Diatom Information Processing -- 9.1.4 Information Processing and Aneural Cognition -- 9.1.5 Hebbian Intelligence and Predictive Processing -- 9.2 Measurement Techniques -- 9.2.1 Weber-Fechner Law -- 9.2.2 Connectionist Network -- 9.2.3 Algorithmic Information -- 9.2.4 Collective Pattern Generator -- 9.2.5 Dynamical States of the CoPG -- 9.3 CPGs vs. …”

Tabla de Contenidos: “…7.4 Quantum logic with quantum variables -- 7.4.1 Syntax -- 7.4.2 Semantics -- 7.4.3 Proof system -- 7.5 Quantum logic as an assertion logic -- 7.5.1 Reformulating syntax and semantics of quantum programs -- 7.5.2 Quantum Hoare logic combined with quantum logic -- 7.5.3 Adaptation rules for quantum programs -- 7.6 An effect calculus as assertion logic -- 7.6.1 A calculus of quantum effects -- 7.6.2 Quantum Hoare logic combined with effect calculus -- 7.7 Discussion -- 7.8 Bibliographic remarks and further readings -- 8 Analysis of quantum programs -- 8.1 Control flows of quantum programs -- 8.1.1 Superoperator-valued transition systems -- 8.1.2 Quantum programs as transition systems -- 8.2 Invariants and their generation -- 8.2.1 Basic definitions -- 8.2.2 Partial correctness -- 8.2.3 Inductive assertion maps -- 8.2.4 Generation of inductive invariants -- 8.2.5 An illustrative example -- 8.3 Termination analysis - ranking functions -- 8.3.1 Termination problems -- 8.3.2 Ranking functions and termination theorems -- 8.3.3 Realisability and synthesis of ranking functions -- 8.4 Termination analysis - reachability -- 8.4.1 Termination of quantum while-loops -- 8.4.2 Quantum graph theory -- 8.4.3 Decomposition of the state Hilbert space -- 8.4.4 Reachability analysis of quantum Markov chains -- 8.5 Quantum abstract interpretation -- 8.5.1 Basics of abstract interpretation -- 8.5.2 Restriction and extension of projections -- 8.5.3 Abstraction of quantum states -- 8.5.4 Abstraction of quantum operations -- 8.6 Bibliographic remarks and further readings -- IV Parallel and distributed quantum programs -- 9 Parallel quantum programs -- 9.1 Syntax of disjoint parallel quantum programs -- 9.2 Semantics of disjoint parallel quantum programs -- 9.2.1 Operational semantics -- 9.2.2 Denotational semantics -- 9.3 Proof system for disjoint parallel quantum programs…”

Tabla de Contenidos: “…Molisch / /5.1 Introduction 109 / /5.2 Femtocaching 111 / /5.2.1 System Model 111 / /5.2.2 Adaptive Streaming from Helper Stations 114 / /5.3 User-Caching 115 / /5.3.1 Cluster-Based Caching and D2D Communications 115 / /5.3.2 IT LinQ-Based Caching and Communications 118 / /5.3.3 Coded Multicast 126 / /5.4 Conclusions and Outlook 130 / /References 131 / /6 Wireless Video Fog: Collaborative Live Streaming with Error Recovery 133 /Bo Zhang, Zhi Liu, and S.…”

Tabla de Contenidos: “…3.10.3 Assessment of Controls -- 3.11 Risk Evaluation -- 3.12 Risk Treatment -- 3.13 Communication -- 3.14 Documentation -- 3.15 Monitoring and Continuous Improvement -- 3.16 Summary -- Review Questions -- References -- Chapter 4 Defining Risk Assessment Criteria -- 4.1 Introduction -- 4.2 Defining Risk Criteria -- 4.3 Risk Scoring Systems -- 4.4 Risk Assessment Matrices -- 4.5 Defining Risk Values -- 4.6 Risk Factors -- 4.7 Risk Levels -- 4.8 Risk Scoring -- 4.9 Severity of Consequence -- 4.10 Likelihood of Occurrence -- 4.11 Exposure -- 4.12 Risk Reduction and the Hierarchy of Controls -- 4.12.1 Using a Protection Factor -- 4.13 Acceptable and Unacceptable Risk Levels -- 4.14 Documenting Risk -- 4.15 Communicating Risk Criteria -- 4.16 Summary -- Review Questions -- References -- Appendix A A. Risk Matrix (adapted/modified from ANSI Z10) -- Chapter 5 Fundamental Techniques -- 5.1 Introduction to Fundamental Hazard Analysis and Risk Assessment -- 5.2 Assessments Within an Operational Risk Management System -- 5.3 Hazard Analysis vs. …”

Tabla de Contenidos:

Tabla de Contenidos: “…Vulnérabilités macrofinancières potentielles -- Adaptation des régions à la dégradation des termes de l'échange et mesures visant à faciliter la réorientation sectorielle -- Graphique 6. …”

Tabla de Contenidos: “…L'EMPLOYABILITÉ DES TRAVAILLEURS ÂGÉS ADAPTER LE LIEU DE TRAVAIL À TOUS LES ÂGES ? -- Résumé et principaux résultats -- La situation actuelle -- Les enjeux et les mesures prises à l'échelon national -- Orientations des réformes -- Maintenir les travailleurs âgés dans l'emploi -- Aider les travailleurs âgés à trouver un nouvel emploi -- Promouvoir l'activité à tout âge -- Encadré 2.1. …”

Tabla de Contenidos: “…. -- La libéralisation du secteur de la distribution du gaz a été accélérée -- Malgré de récents progrès, des réformes sont nécessaires dans le secteur des transports -- Autres secteurs -- Réformes du marché financier -- Le système bancaire s'adapte à la désintermédiation financière -- Tableau 13. …”

Tabla de Contenidos: “…Intro -- Avant-propos -- Remerciements -- Abréviations et acronymes -- Éditorial -- Résumé -- « Repenser le développement » -- Les stratégies de développement doivent s'adapter au nouvel ordre mondial -- Les stratégies de développement ne peuvent pas partir du principe que la croissance économique se traduira automatiquement par une amélioration du bien-être -- Les stratégies de développement doivent faire face à de nouvelles tendances et de nouveaux défis -- Quelles stratégies de développement pour le XXIe siècle ? …”

Tabla de Contenidos: “…Directive de conception pour les escaliers -- Taxis accessibles ou adaptés -- Figure 5.3. La transformation d'un monospace en un véhicule à plancher... -- Figure 5.4. …”

Tabla de Contenidos: “…11.5 Economic performance and adaptability analysis…”

Tabla de Contenidos: “…4.2.2.2 ICA Method -- 4.2.2.3 DVA Method -- 4.3 Model‐Based Methods -- 4.3.1 Adaptive State Estimation Methods -- 4.3.2 Data‐Driven Methods -- 4.3.2.1 Empirical and Fitting Methods -- 4.3.2.2 Response Surface‐Based Optimization Algorithms -- 4.3.2.3 Sample Entropy Methods -- 4.4 Joint Estimation Method -- 4.4.1 Relationship Between SOC and Capacity -- 4.4.2 Case Study -- 4.5 Dual Estimation Method -- 4.5.1 Implementation with the AEKF Algorithm -- 4.5.2 SOC-SOH Estimation -- 4.5.3 Case Study -- 4.6 Summary -- References -- Chapter 5 Battery State of Power Estimation -- 5.1 Background -- 5.2 Instantaneous SOP Estimation Methods -- 5.2.1 HPPC Method -- 5.2.2 SOC‐Limited Method -- 5.2.3 Voltage‐Limited Method -- 5.2.4 MCD Method -- 5.2.5 Case Study -- 5.3 Continuous SOP Estimation Method -- 5.3.1 Continuous Peak Current Estimation -- 5.3.2 Continuous SOP Estimation -- 5.3.3 Influences of Battery States and Parameters on SOP Estimation -- 5.3.3.1 Uncertainty of SOC -- 5.3.3.2 Case Study -- 5.3.3.3 Uncertainty of Model Parameters -- 5.3.3.4 Case Study -- 5.3.3.5 Uncertainty of SOH -- 5.4 Summary -- References -- Chapter 6 Battery Charging -- 6.1 Background -- 6.2 Basic Terms for Evaluating Charging Performances -- 6.2.1 Cell and Pack -- 6.2.2 Nominal Ampere‐Hour Capacity -- 6.2.3 C‐rate -- 6.2.4 Cut‐off Voltage for Discharge or Charge -- 6.2.5 Cut‐off Current -- 6.2.6 State of Charge -- 6.2.7 State of Health -- 6.2.8 Cycle Life -- 6.2.9 Charge Acceptance -- 6.2.10 Ampere‐Hour Efficiency -- 6.2.11 Ampere‐Hour Charging Factor -- 6.2.12 Energy Efficiency -- 6.2.13 Watt‐Hour Charging Factor -- 6.2.14 Trickle Charging -- 6.3 Charging Algorithms for Li‐Ion Batteries -- 6.3.1 Constant Current and Constant Voltage Charging -- 6.3.2 Multistep Constant Current Charging -- 6.3.3 Two‐Step Constant Current Constant Voltage Charging…”

Tabla de Contenidos: “…Le salaire minimum n'est pas adapté à la situation locale du marché du travail -- Rehausser le niveau général des compétences de base et renforcer l'égalité des chances -- Graphique 17. …”

Tabla de Contenidos: “…-- Preface xxi / /Acknowledgments xxv / /Summary of Notations xxvii / /About the Cover xxix / /About the Companion Website xxxi / /1 Mathematical Background and Analysis Techniques 1 / /1.1 Introduction 1 / /1.2 The Fourier Transform and Fourier Series 5 / /1.3 Pulse Distortion with Ideal Filter Models 16 / /1.4 Correlation Processing 19 / /1.5 Random Variables and Probability 20 / /1.6 Random Processes 41 / /1.7 The Matched Filter 44 / /1.8 The Likelihood and Log-Likelihood Ratios 46 / /1.9 Parameter Estimation 47 / /1.10 Modem Configurations and Automatic Repeat Request 55 / /1.11 Windows 57 / /1.12 Matrices Vectors and Related Operations 66 / /1.13 Often Used Mathematical Procedures 70 / /1.14 Often Used Mathematical Relationships 71 / /2 Digital Signal Processing and Modem Design Considerations 81 / /2.1 Introduction 81 / /2.2 Discrete Amplitude Sampling 81 / /2.3 Discrete-Time Sampling 87 / /2.4 Signal Reconstruction Following Discrete-Time Sampling 91 / /2.5 Baseband Sampling 92 / /2.6 Bandpass Sampling 92 / /2.7 Corrections for Nonideal Modulators and Demodulators 99 / /2.8 Multirate Signal Processing and Interpolation 106 / /Appendix 2A Amplitude Quantization Function Subprogram 121 / /Appendix 2B Hilbert Transform Parameters 122 / /Appendix 2C Derivation of Parabolic Interpolation Error 126 / /3 Digital Communications 133 / /3.1 Introduction 133 / /3.2 Digital Data Modulation and Optimum Demodulation Criteria 135 / /3.3 Information and Channel Capacity 139 / /3.4 Bit-Error Probability Bound on Memoryless Channel 148 / /3.5 Probability Integral and the Error Function 150 / /4 Phase Shift Keying (PSK) Modulation Demodulation and Performance 153 / /4.1 Introduction 153 / /4.2 Constant Envelope Phase-Modulated Waveforms 154 / /4.3 Non-Constant Envelope Phase-Modulated Waveforms 175 / /4.4 Phase-Modulated Waveform Spectrums and Performance 178 / /5 Frequency Shift Keying (FSK) Modulation Demodulation and Performance 207 / /5.1 Introduction 207 / /5.2 Coherent Detection of BFSK - Known Frequency and Phase 207 / /5.3 Noncoherent Detection of BFSK - Known Frequency and Unknown Phase 210 / /5.4 Case Studies: Coherent and Noncoherent BFSK Performance Simulation 211 / /5.5 Noncoherent Detection of BFSK - Unknown Frequency and Phase 214 / /5.6 BFSK Spectral Density with Arbitrary Modulation Index 219 / /6 Amplitude Shift Keying Modulation Demodulation and Performance 227 / /6.1 Introduction 227 / /6.2 Amplitude Shift Keying (ASK) 227 / /6.3 Quadrature Amplitude Modulation (QAM) 234 / /6.4 Alternate QAM Waveform Constellations 236 / /6.5 Case Study: 16-ary QAM Performance Evaluation 236 / /6.6 Partial Response Modulation 237 / /7 M-ary Coded Modulation 251 / /7.1 Introduction 251 / /7.2 Coherent Detection of Orthogonal Coded Waveforms 252 / /7.3 Noncoherent Detection of M-ary Orthogonal Waveforms 253 / /7.4 Coherent Detection of M-ary Biorthogonal Waveforms 256 / /8 Coding for Improved Communications 261 / /8.1 Introduction 261 / /8.2 Pulse Code Modulation 261 / /8.3 Gray Coding 268 / /8.4 Differential Coding 269 / /8.5 Pseudo-Random Noise Sequences 270 / /8.6 Binary Cyclic Codes 273 / /8.7 Cyclic Redundancy Check Codes 274 / /8.8 Data Randomizing Codes 276 / /8.9 Data Interleaving 277 / /8.10 Wagner Coding and Decoding 279 / /8.11 Convolutional Codes 283 / /8.12 Turbo and Turbo-Like Codes 299 / /8.13 LDPC Code and TPC 313 / /8.14 Bose-Chaudhuri-Hocquenghem Codes 315 / /Appendix 8A 328 / /Appendix 8B 329 / /9 Forward Error Correction Coding Without Bandwidth Expansion 339 / /9.1 Introduction 339 / /9.2 Multi-h M-ary CPM 340 / /9.3 Case Study: 2-h 4-ary 1REC CPM 350 / /9.4 Multiphase Shift Keying Trellis-Coded Modulation 362 / /9.5 Case Study: Four-State 8PSK-TCM Performance Over Satellite Repeater 367 / /10 Carrier Acquisition and Tracking 375 / /10.1 Introduction 375 / /10.2 Bandpass Limiter 377 / /10.3 Baseband Phaselock Loop Implementation 378 / /10.4 Phase-Error Generation 378 / /10.5 First-Order Phaselock Loop 380 / /10.6 Second-Order Phaselock Loop 380 / /10.7 Third-Order Phaselock Loop 390 / /10.8 Optimum Phase Tracking Algorithms 396 / /10.9 Squaring Loss Evaluation 406 / /10.10 Case Study: BPSK and QPSK Phaselock Loop Performance 408 / /10.11 Case Study: BPSK Phase Tracking Performance of a Disadvantaged Transmit Terminal 410 / /11 Waveform Acquisition 413 / /11.1 Introduction 413 / /11.2 CW Preamble Segment Signal Processing 416 / /11.3 Symbol Synchronization Preamble Segment 432 / /11.4 Start-of-Message (SOM) Preamble segment 452 / /11.5 Signal-to-Noise Ratio Estimation 452 / /12 Adaptive Systems 463 / /12.1 Introduction 463 / /12.2 Optimum Filtering - Wiener's Solution 464 / /12.3 Finite Impulse Response-Adaptive Filter Estimation 465 / /12.4 Intersymbol Interference and Multipath Equalization 469 / /12.5 Interference and Noise Cancellation 472 / /12.6 Recursive Least Square (RLS) Equalizer 473 / /12.7 Case Study: LMS Linear Feedforward Equalization 474 / /12.8 Case Study: Narrowband Interference Cancellation 474 / /12.9 Case Study: Recursive Least Squares Processing 480 / /13 Spread-Spectrum Communications 485 / /13.1 Introduction 485 / /13.2 Spread-Spectrum Waveforms and Spectrums 487 / /13.3 Jammer and Interceptor Encounters 499 / /13.4 Communication Interceptors 502 / /13.5 Bit-Error Performance of DSSS Waveforms with Jamming 504 / /13.6 Performance of MFSK with Partial-Band Noise Jamming 512 / /13.7 Performance of DCMPSK with Partial-Band Noise Jamming 514 / /13.8 FHSS Waveforms with Multitone Jamming 515 / /13.9 Approximate Performance with Jammer Threats 521 / /13.10 Case Study: Terrestrial Jammer Encounter and Link-Standoff Ratio 522 / /14 Modem Testing Modeling and Simulation 531 / /14.1 Introduction 531 / /14.2 Statistical Sampling 532 / /14.3 Computer Generation of Random Variables 539 / /14.4 Baseband Waveform Description 545 / /14.5 Sampled Waveform Characterization 547 / /14.6 Case Study: BPSK Monte Carlo Simulation 548 / /14.7 System Performance Evaluation Using Quadrature Integration 550 / /14.8 Case Study: BPSK Bit-Error Evaluation with PLL Tracking 551 / /14.9 Case Study: QPSK Bit-Error Evaluation with PLL Tracking 553 / /15 Communication Range Equation and Link Analysis 557 / /15.1 Introduction 557 / /15.2 Receiver and System Noise Figures and Temperatures 560 / /15.3 Antenna Gain and Patterns 568 / /15.4 Rain Loss 571 / /15.5 Electric Field Wave Polarization 573 / /15.6 Phase-Noise Loss 578 / /15.7 Scintillation Loss 583 / /15.8 Multipath Loss 583 / /15.9 Interface Mismatch Loss 584 / /15.10 Miscellaneous System Losses 585 / /15.11 Nonlinear Power Amplifier Analysis and Simulation 585 / /15.12 Computer Modeling of TWTA and SSPA Nonlinearities 588 / /15.13 Establishing Signal Levels for Simulation Modeling 590 / /15.14 Case Study: Performance Simulation of SRRC-QPSK with SSPA Nonlinearity 592 / /15.15 Link Budget Analysis 596 / /16 Satellite Orbits 603 / /16.1 Introduction 603 / /16.2 Satellite Orbits 606 / /16.3 Earth Stations 607 / /16.4 Path Loss Doppler and Doppler-rate 609 / /16.5 Satellite Viewing 609 / /16.6 Satellite Orbit Selection 610 / /16.7 Satellite Orbit Position Estimation From Parameter Measurements 611 / /16.8 Case Study: Example Satellite Encounters 612 / /17 Communications Through Bandlimited Time-Invariant Linear Channels 617 / /17.1 Introduction 617 / /17.2 Inphase and Quadrature Channel Response 618 / /17.3 Inphase and Quadrature Channel Response to Arbitrary Signal 619 / /17.4 Pulse Modulated Carrier Signal Characteristics 621 / /17.5 Channel Response to a Pulsed Modulated Waveform 622 / /17.6 Example Performance Simulations 623 / /17.7 Example of Channel Amplitude and Phase Responses 624 / /17.8 Example Channel Amplitude Phase and Delay Functions 627 / /18 Communications in Fading Environments 633 / /18.1 Introduction 633 / /18.2 Ricean Fading Channels 634 / /18.3 Ricean Cumulative Distribution 635 / /18.4 Application of Ricean Channel Model 635 / /18.5 Performance of Several Binary Modulation…”

Tabla de Contenidos: “…5.16.2 Advocacy for victims' rights -- 5.17 Conclusion -- 5.17.1 Developing comprehensive policies and legal frameworks -- 5.17.2 Continuous technological vigilance and adaptive detection mechanisms -- 5.17.3 Global collaboration, standards, and cooperation -- 5.17.4 Public awareness, education, and evolving educational programmes -- 5.17.5 Ethical considerations in AI development -- 5.17.6 Proactive approach to emerging threats and evolving tactics -- References -- 6 Trust and risk: psybersecurity in the AI era -- 6.1 Introduction -- 6.1.1 The emerging importance of securing mental health in the digital age -- 6.2 Trust and risk in AI -- 6.2.1 Psychological foundations of trust -- 6.2.2 Context and significance of trust and risk in the AI era -- 6.2.3 Benefits of trust in AI -- 6.3 Risks stemming from trust in AI -- 6.3.1 Over-trust in AI products: abuse and misuse -- 6.3.2 Under-trust in AI products: disuse -- 6.4 Psybersecurity risk framework -- 6.4.1 Mass impact -- 6.4.2 Direct AI impact -- 6.4.3 Malicious use of AI -- 6.5 Discussion -- 6.5.1 Awareness training -- 6.5.2 Transparency in AI -- 6.5.3 Industry regulations -- 6.5.4 Legal frameworks -- 6.6 Conclusion -- References -- 7 Security through influence over mandate -- 7.1 Introduction -- 7.1.1 Make security tangible, not another compliance slideshow -- 7.1.2 Ease, not pain, should be synonymous with security -- 7.1.3 Resistance is necessary and good -- 7.1.4 Security is achieved through continuous, small steps -- 7.1.5 Security is enablement, not gatekeeping -- 7.2 Pattern 1: make security tangible, not another compliance slideshow -- 7.2.1 Adding to the cultural fabric -- 7.2.2 Accelerating the spread of knowledge -- 7.2.3 The difference between reading and knowing the incident response plan -- 7.2.4 The discipline of security chaos engineering -- 7.2.5 Summary…”

Tabla de Contenidos: “…Image Enhancement -- 5.1 Introduction -- 5.2 Pixel Transformation -- 5.3 Image Inverse -- 5.4 Power Law Transformation -- 5.5 Log Transformation -- 5.6 Histogram Equalization -- 5.7 Contrast Limited Adaptive Histogram Equalization (CLAHE) -- 5.8 Contrast Stretching -- 5.9 Sigmoid Correction -- 5.10 Local Contrast Normalization -- 5.11 Summary -- 5.12 Exercises -- 6. …”

Tabla de Contenidos: “…Training efficiently with adaptive gradients -- 7.5.1. Decay and momentum in SGD -- 7.5.2. …”