Tabla de Contenidos: “…Cover -- Title -- Copyright -- Dedication -- Contents -- Acknowledgments -- Preface -- Chapter 1: Crossover Basics -- What a Crossover Does -- Why a Crossover Is Necessary -- Beaming and Lobing -- Passive Crossovers -- Active Crossover Applications -- Bi-Amping and Bi-Wiring -- Loudspeaker Cables -- The Advantages and Disadvantages of Active Crossovers -- The Advantages of Active Crossovers -- Some Illusory Advantages of Active Crossovers -- The Disadvantages of Active Crossovers -- The Next Step in Hi-Fi -- Active Crossover Systems -- Matching Crossovers and Loudspeakers -- A Modest Proposal: Popularising Active Crossovers -- Multi-Way Connectors -- Subjectivism -- Chapter 2: How Loudspeakers Work -- Sealed-Box Loudspeakers -- Reflex (Ported) Loudspeakers -- Auxiliary Bass Radiator (ABR) Loudspeakers -- Transmission Line Loudspeakers -- Horn Loudspeakers -- Electrostatic Loudspeakers -- Ribbon Loudspeakers -- Electromagnetic Planar Loudspeakers -- Air-Motion Transformers -- Plasma Arc Loudspeakers -- The Rotary Woofer -- MTM Tweeter-Mid Configurations (d'Appolito) -- Vertical Line Arrays -- Line Array Amplitude Tapering -- Line Array Frequency Tapering -- CBT Line Arrays -- Diffraction -- Sound Absorption in Air -- Modulation Distortion -- Drive Unit Distortion -- Doppler Distortion -- Further Reading on Loudspeaker Design -- Chapter 3: Crossover Requirements -- General Crossover Requirements -- 1 Adequate Flatness of Summed Amplitude/Frequency Response On-Axis -- 2 Sufficiently Steep Roll-Off Slopes Between the Filter Outputs -- 3 Acceptable Polar Response -- 4 Acceptable Phase Response -- 5 Acceptable Group Delay Behaviour -- Further Requirements for Active Crossovers -- 1 Negligible Extra Noise -- 2 Negligible Impairment of System Headroom -- 3 Negligible Extra Distortion -- 4 Negligible Impairment of Frequency Response…”

Tabla de Contenidos: “…BASED OPTICAL FIBER SENSING TECHNOLOGY; 6.1 Optical Fiber Sensor Based on Fiber Tip Micro-Michelson Interferometer; 6.2 Optical Fiber Sensor Based on Angled Fiber End; 6.3 Optical Fiber Sensor Based on In-Line Interferometer; ; CHAPTER 7 SURFACE-PLASMON-RESONANCE-BASED OPTICAL FIBER SENSING TECHNOLOGY; 7.1 Coating of Optical Fiber; 7.2 Theoretical Modeling Multimode Optical Fiber Sensor Based on SPR; 7.3 EMD-Based Filtering Algorithm; ; CHAPTER 8 SAGNAC-INTERFEROMETER-BASED OPTICAL FIBER SENSING TECHNOLOGY; 8.1 Principle of Sagnac Interferometer; 8.2 Optical Fiber Gyroscope; 8.3 The Optical Fiber Coil Quality Inspection Method; 8.3.1 Group Birefringence Thermal Coefficient of Polarization-Maintaining Fibers; 8.3.2 Optical Fiber Coil Winding Method; 8.3.3 Polarization Crosstalk Measurement; 8.3.4 Transient Characteristics Measurement with Temperature Stimulation; 8.4 Optical Fiber Current Sensing; ; CHAPTER 9 MODE-INTERFERENCE-BASED OPTICAL FIBER SENSING TECHNOLOGY; 9.1 Mode Interference Theory of Singlemode-Multimode-Singlemode; 9.2 Optical Fiber Refractive Index Sensor Based on SMS; 9.2.1 Sensor Design and Fabrication; 9.2.2 Self-Temperature-Compensation Sensing; 9.2.3 Simultaneous Refractive Index and Temperature Sensing; 9.3 Optical Fiber Magnetic Field Sensor Based on SMS; 9.3.1 Magnetic Fluid; 9.3.2 Sensor Design and Fabrication; 9.3.3 Simultaneous Magnetic Field and Temperature Sensing; ; CHAPTER 10 WHISPER-GALLERY-MODE-BASED OPTICAL FIBER SENSING TECHNOLOGY; 10.1 Whisper-Gallery-Mode Theory; 10.2 Process of Micro Capillary With Inner Pressure Air; 10.2.1 Drawing System and Drawing Model; 10.2.2 Fabrication of Microtube; 10.2.3 Fabrication of Hollow Microsphere; 10.3 Optical Fiber Magnetic Field Sensor Based on Microtube WGM; 10.3.1 Magnetic Nanoparticle Assembly; 10.3.2 Sensor Fabrication and Measurement; 10.4 Optical Fiber Dual Parameters Sensor Based on Hollow Microsphere WGM; 10.5 Ultraprecise Resonance Wavelength Determination Method; ; CHAPTER 11 OPTICAL FIBER INTRA-CAVITY LASER GAS SENSING TECHNOLOGY; 11.1 Theory of Optical Fiber Intra-Cavity Laser Gas Sensing; 11.1.1 Principle of Optical Fiber Laser; 11.1.2 Sensitivity Enhancement of Gas Sensing by Direct Absorption; 11.1.3 Optical Fiber Intra-Cavity Laser Gas Sensing by Wavelength Modulation; 11.1.4 Effect of Temperature on Performance of Gas Sensing; 11.2 Optical Fiber Intra-Cavity Laser Gas Sensing System Design; 11.3 Spectrum Signal Process; 11.3.1 De-Noise with EMD; 11.3.2 Baseline Extraction; 11.3.3 Spectrum Separation; 11.3.4 Concentration Demodulation; 11.4 Wavelength Calibration Analysis and Gas Recognition; ; CHAPTER 12 OPTICAL FIBER BASED OPTICAL COHERENCE TOMOGRAPHY; 12.1 Optical Fiber Coherence Tomography Theory; 12.1.1 Time-Domain Optical Fiber Based Optical Coherence Tomography; 12.1.2 Frequency-Domain Optical Fiber Based Optical Coherence Tomography; 12.2 Functional Optical Fiber Based Optical Coherence Tomography; 12.2.1 Doppler Optical Coherence Tomography; 12.2.2 Polarization Sensitive Optical Coherence Tomography; 12.3 Biomedical Applications; 12.3.1 Dentistry; 12.3.2 Cardiovasology; 12.3.3 Neurology; ; CHAPTER 13 DISCRETE OPTICAL FIBER SENSING NETWORK TECHNOLOGY; 13.1 Topology of Optical Fiber Sensing Network; 13.2 Robustness Evaluation of Optical Fiber Sensing Network; 13.2.1 Robustness Evaluation Model; 13.2.2 Robustness Affection Factor; 13.2.3 Optimization Arrangement; ; CHAPTER 14 DISTRIBUTED VIBRATION SENSING BASED ON DUAL MACH-ZEHNDER INTERFEROMETER; 14.1 Theory of Distributed Vibration Sensing Based on Dual Mach-Zehnder Interferometer; 14.1.1 Principle of System; 14.1.2 Performance Affection Factor; 14.2 Polarization Control Method; 14.2.1 Polarization-Induced Phase Shift and Polarization-Induced Fading; 14.2.2 Chaotic Particle Swarm Optimization Algorithm; 14.2.3 Genetic Algorithm; 14.2.4 Annealing Algorithm; 14.3 Interferometer Based Distributed Vibration Sensing Instrument Design; 14.4 Signal Process Algorithm and Instrument; 14.3.1 Endpoint Detection; 14.3.2 Position Determination; 14.3.3 Intrusion Pattern Recognition; ; CHAPTER 15 REGIONAL STYLE INTELLIGENT PERIMETER SECURITY TECHNIQUE BASE ON MICHELSON INTERFEROMETER; 15.1 Principle of System; 15.2 Instrument Design; 15.3 Perimeter Security Application; ; CHAPTER 16 DISTRIBUTED TEMPERATURE SENSING BASED ON RAMAN SCATTERING; 16.1 Raman Scattering Theory; 16.2 Principle of System; 16.3 Systemn Design; 16.4 De-Noising Algorithm Based on EEMD; 16.5 Applicaion on Electric Power Industry; ; CHAPTER 17 DISTRIBUTED ACOUSTIC SENSING BASED ON OPTICAL TIME DOMAIN REFLECTOMETRY; 17.1 Theory of Optical Time Domain Reflectometry; 17.1.1 Direct-Detection-Based Phase Optical Time Domain Reflectometry; 17.1.2 Coherent-Detection-Based Phase Optical Time Domain Reflectometry; 17.2 Pulse Modulation Method; 17.3 Acoustic Sensitivity Enhance Method of Optical Fiber; 17.4 Dual-Pulse Coherent Phase Optical Time Domain Reflectometry; 17.5 Chirp-Pulse Phase Optical Time Domain Reflectometry; ; CHAPTER 18 DISTRIBUTED SENSING BASED ON OPTICAL FREQUENCY DOMAIN REFLECTOMETRY; 18.1 Principle of Optical Frequency Domain Reflectometry; 18.2 Measurement Range OFDR Beyond Laser Coherence Length; 18.3 Laser Frequency Tuning Nonlinearity and Compensation; 18.3.1 Laser Frequency Tuning Nonlinearity; 18.3.2 Compensation Using Non-Uniform Fast Fourier Transform; 18.3.3 Compensation Using Deskew Filter; 18.4 Distributed Sensing System and Application; 18.4.1 Distributed Vibration Sensing Base on Correlation Analysis; 18.4.2 Distributed Strain and Temperature Measurement; 18.4.3 Distributed Magnetic Field and Current Sensor Bas…”

Tabla de Contenidos: “…Experiments conducted using Hydar -- 5.1 Experiment-The first -- 5.2 Experiment-Observe what is expected -- 5.3 Experiment-Different forward models -- 5.4 Experiment-Higher embedding orders -- 5.5 Experiment-Colored noise -- 5.6 Experiment-White noise -- 5.7 Plotting 4D probabilistic atlas maps -- 5.8 Plotting a statistical map -- 5.9 Glass brain visualization -- 6. …”

Tabla de Contenidos: “…-- Preparing for the paradigm shift -- Summary -- Further reading -- Part 4 - Mastering the Craft: Advancing Your Journey as a Network Architect -- Chapter 10: Preparing for Certifications and Cracking the Job Interview -- Network architects' certification path -- Foundational certifications -- Professional certifications -- Expert certifications -- Design expert certifications -- Miscellaneous certifications and others -- Continued education -- Preparing for certifications -- Create an environment only used for studying -- Remove distractions -- Schedule your studying time -- Use earplugs, white/brown noise, or focus sounds -- Cone of Knowledge -- Use a timer -- Take breaks -- Training and study material -- Supplements and rest -- How to crack interview questions -- Sample questions -- Questions -- Summary -- Chapter 11: The Skills to Become a Better Network Architect and Overcome Daily Challenges…”

Tabla de Contenidos: “…Getting started with Responsible AI in your organization -- Regulatory compliance in Azure Policy for Azure Machine Learning -- Azure Security Benchmark -- Federal Risk and Authorization Management Program -- New Zealand Information Security Manual (restricted) -- NIST SP 800-53 Rev. 5 -- Reserve Bank of India IT Framework for Banks v2016 -- Compliance auditing and reporting -- Azure portal -- Azure Resource Graph Explorer -- Compliance automation in Azure -- Azure Blueprints -- IaC -- Summary -- Part 2: Securing Your Data -- Chapter 4: Data Protection and Governance -- Working with data governance in Azure -- Identifying challenges -- Exploring benefits -- Getting started using cloud data best practices -- Exploring Azure tools and resources -- Storing and retrieving data in Azure Machine Learning -- Connecting datastores -- Adding data assets -- Encrypting and securing data -- Encryption at rest -- Encryption in transit -- Exploring backup and recovery -- Reviewing backup options for your datastores -- Recovering your workspace -- Summary -- Chapter 5: Data Privacy and Responsible AI Best Practices -- Technical requirements -- Working with Python -- Running a notebook in Azure Machine Learning -- Installing the SmartNoise SDK -- Installing Fairlearn -- Discovering and protecting sensitive data -- Identifying sensitive data -- Exploring data anonymization -- Introducing differential privacy -- Mitigating fairness -- Fairlearn -- Working with model interpretability -- Exploring the Responsible AI dashboard -- Exploring FL and secure multi-party computation -- FL with Azure Machine Learning -- Summary -- Further reading -- Part 3: Securing and Monitoring Your AI Environment -- Chapter 6: Managing and Securing Access -- Working with the PoLP -- Authenticating with Microsoft Entra ID -- Implementing RBAC -- Working with built-in roles…”

Tabla de Contenidos: “…Front Cover -- Bio-inspired Algorithms for Engineering -- Copyright -- Contents -- Preface -- Acknowledgments -- 1 Bio-inspired Algorithms -- 1.1 Introduction -- 1.1.1 Bio-inspired and evolutionary algorithms -- 1.2 Particle Swarm Optimization -- 1.3 Arti cial Bee Colony Algorithm -- 1.4 Micro Arti cial Bee Colony Algorithm -- 1.5 Differential Evolution -- 1.6 Bacterial Foraging Optimization Algorithm -- References -- 2 Data Classi cation Using Support Vector Machines Trained with Evolutionary Algorithms Employing Kernel Adatron -- 2.1 Introduction -- 2.2 Support Vector Machines -- 2.3 Evolutionary algorithms -- 2.4 The Kernel Adatron algorithm -- 2.5 Kernel Adatron trained with evolutionary algorithms -- 2.6 Results using benchmark repository datasets -- 2.7 Application to classify electromyographic signals -- 2.8 Conclusions -- References -- 3 Reconstruction of 3D Surfaces Using RBF Adjusted with PSO -- 3.1 Introduction -- 3.2 Radial basis functions -- 3.3 Interpolation of surfaces with RBF and PSO -- 3.3.1 Ellipsoid of covariance -- 3.3.2 RBF-PSO and ellipsoid of covariance to interpolate 3D point-clouds -- 3.3.3 Experimental results -- 3.4 Conclusion -- References -- 4 Soft Computing Applications in Robot Vision -- 4.1 Introduction -- 4.2 Image tracking -- 4.2.1 Normalized cross correlation -- 4.2.2 Continuous plane to image plane conversion -- 4.2.3 Algorithm implementation -- 4.2.4 Experiments -- 4.3 Plane detection -- 4.3.1 Description of the method -- 4.3.2 Simulations results -- 4.3.2.1 Outliers test -- 4.3.3 Noise test -- 4.3.4 Experiments -- 4.4 Conclusion -- References -- 5 Soft Computing Applications in Mobile Robotics -- 5.1 Introduction to mobile robotics -- 5.2 Nonholonomic mobile robot navigation -- 5.2.1 2D projective geometry -- 5.2.1.1 Representation of points -- 5.2.1.2 Representation of lines -- 5.2.1.3 Point line distance…”

Tabla de Contenidos: “…Number of Comparable Firms -- Basis for Selecting Comparable Firms -- Geography and Clientele -- Sector and Industry Characteristics -- Technology and Intraindustry Diversity -- Bimodal and Multimodal Patterns -- Choice of Valuation Multiples -- Choice of Numerator: Market Cap versus Firm Value -- Industry-Specific Multiples -- HYPOTHETICAL EXAMPLE -- Analysis of the Hypothetical Example -- Other Potential Issues -- KEY POINTS -- NOTES -- REFERENCES -- Equity Analysis in a Complex Market -- AN INTEGRATED APPROACH TO A SEGMENTED MARKET -- A Coherent Framework -- DISENTANGLING -- Noise Reduction -- Return Revelation -- Predictive Power -- Additional Complexities -- CONSTRUCTING, TRADING, AND EVALUATING PORTFOLIOS -- PROFITING FROM COMPLEXITY -- KEY POINTS -- NOTES -- REFERENCES -- Equity Portfolio Selection Models in Practice -- PORTFOLIO CONSTRAINTS COMMONLY USED IN PRACTICE -- Long-Only (No-Short-Selling) Constraints -- Holding Constraints -- Turnover Constraints -- Risk Factor Constraints -- Cardinality Constraints -- Minimum Holding and Transaction Size Constraints -- Round Lot Constraints -- BENCHMARK EXPOSURE AND TRACKING ERROR MINIMIZATION -- Standard Definition of Tracking Error -- Alternative Ways of Defining Tracking Error -- Actual Versus Predicted Tracking Error -- INCORPORATING TRANSACTION COSTS -- Linear Transaction Costs -- Piecewise-Linear Transaction Costs -- Quadratic Transaction Costs -- Fixed Transaction Costs -- INCORPORATING TAXES -- MULTIACCOUNT OPTIMIZATION -- ROBUST PARAMETER ESTIMATION -- PORTFOLIO RESAMPLING -- ROBUST PORTFOLIO OPTIMIZATION -- KEY POINTS -- NOTES -- REFERENCES -- Basics of Quantitative Equity Investing -- EQUITY INVESTING -- FUNDAMENTAL VS. …”

Tabla de Contenidos: “…Cover -- Half Title -- Title Page -- Copyright Page -- Table of Contents -- Organizing Committee -- Acknowledgements -- Preface -- Foreword -- About the Editors -- Chapter 01 ▪ Design of One Adaptive Controller for a Dynamic Framework with Non-linear Parameterisation -- 1.1 Introduction -- 1.2 Non-Linear Parameterized Framework -- 1.3 Controller Design -- 1.2.1 Lyapunov Stability Analysis -- 1.4 Results -- 1.5 Conclusion -- References -- Chapter 02 ▪ A Comparative Study of Phasor Estimation Techniques -- 2.1 Introduction -- 2.2 Phasor Estimation Techniques -- 2.2.1 Discrete Fourier Transform Based Phasor Estimation -- 2.2.2 Discrete Wavelet Transform Based Phasor Estimation -- 2.2.3 Least Square Method Based Phasor Estimation -- 2.3 Results and Discussion -- 2.3.1 Signal Reconstruction -- 2.3.2 Total Vector Error -- 2.3.3 Transient Monitor -- 2.3.4 Effect of Noise -- 2.3.5 Effect of Harmonics -- 2.3.6 Effect of Sampling Frequency -- 2.4 Conclusion -- Reference -- Chapter 03 ▪ Adaptive Fuzzy PID Controller for a Current Controlled Multilevel Inverter Fed Matrix Converter -- 3.1 Introduction -- 3.2 Multilevel Inverter -- 3.3 System Modelling -- 3.4 Matrix Converter -- 3.5 Differential Evolution Algorithim (Dea) -- 3.6 Proposed Controller -- 3.7 System Block Diagram -- 3.8 Result and Discussion -- 3.9 Result Analysis -- 3.10 Conclusion -- Appendix -- References -- Chapter 04 ▪ Multi-Objective Optimization for Enhanced Surface Roughness and Microhardness of AA 6063/TiO2 Cast Aluminium Metal Matrix Nanocomposites Fabricated by Friction Stir Processing -- 4.1 Introduction -- 4.2 Experimentation -- 4.3 Results and Discussions -- 4.4 Conclusion -- References -- Chapter 05 ▪ Self-Adaptive Multivariate q-Gaussian-based Capacitor Placement for Reactive Power Compensation in Distribution Feeders -- 5.1 Introduction -- 5.2 Problem Formulation…”

Tabla de Contenidos: “…Settings of Eevee -- Rendering with Cycles -- Setting of Cycles -- Introducing the Freestyle Render -- Using Freestyle -- The Freestyle Panel -- The Freestyle Line Set Panel -- The Strokes, Color, and Alpha Panels -- The Thickness, Geometry, and Texture Panels -- The Freestyle Modifiers -- Along Stroke -- Calligraphy -- Crease Angle -- Curvature 3D -- Distance from Camera -- Distance from Object -- Material -- Noise -- Tangent -- More on Freestyle -- Compositing -- The Compositor Workspace -- Setting the Compositor -- The Denoise Node -- Compositing Nodes -- Input Nodes -- Bokeh Image Node -- Image Node -- Mask Node -- Movie Clip Node -- Render Layers Node -- RGB Node -- Texture Node -- Time Curve Node -- Track Position Node -- Value Node -- Output Nodes -- Composite Node -- File Output Node -- Split Viewer Node -- Viewer Node -- Color Nodes -- Alpha Over Node -- Bright/Contrast Node -- Color Balance Node -- Color Correction Node -- Hue Correct Node -- Hue Saturation Value Node -- Invert Node -- Mix Node -- RGB Curves Node -- Tone Map Node -- Z Combine Node -- Converter Nodes -- Alpha Convert Node -- Color Ramp Node -- Combine and Separate Nodes -- Math Node -- RGB to BW Node -- Set Alpha Node -- Switch View Node -- Filter Nodes -- Bilateral Blur Node -- Blur Node -- Defocus Node -- Denoise Node -- Glare Node -- Pixelate Node -- Vector Blur Node -- Vector Nodes -- Map Value Node -- Normal Node -- Normalize Node -- Matte Nodes -- Channel Key Node -- Chroma Key Node -- Color Key Node -- Color Spill Node -- Cryptomatte -- Luminance Key Node -- Distort Nodes -- Crop Node -- Displace Node -- Flip Node -- Lens Distortion Node -- Rotate Node -- Scale Node -- Translate Node -- Transform Node -- Node Groups -- Make Group -- Edit Group -- Ungroup -- Appending Node Groups -- Layout Nodes -- Frame Node -- Reroute Node -- Switch Node -- Editing Videos…”

Tabla de Contenidos: “…-- Keeping it visual -- What's that noise? -- Someone call a doctor! -- Circular health bar -- Lives counter -- On point! …”

Tabla de Contenidos: “…. -- See also -- Making noise with HTML5 browsers -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- An extreme view for reception areas -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Chapter 10: Processes that Improve Quality -- Culture and collaboration -- Fail early or fail faster -- Data-driven testing -- Learning from history -- Considering test automation as a software project -- Visualize, visualize, and visualize! …”

Tabla de Contenidos: “…. -- Cross-validation with the noise parameter -- There's more... -- Using SGD for regression -- Getting ready -- How to do it... -- How it works... -- Chapter 3: Dimensionality Reduction -- Introduction -- Reducing dimensionality with PCA -- Getting ready -- How to do it... -- How it works... -- There's more... -- Using factor analysis for decomposition -- Getting ready -- How to do it... -- How it works... -- Using kernel PCA for nonlinear dimensionality reduction -- Getting ready -- How to do it... -- How it works... -- Using truncated SVD to reduce dimensionality -- Getting ready -- How to do it... -- How it works... -- There's more... -- Sign flipping -- Sparse matrices -- Using decomposition to classify with DictionaryLearning -- Getting ready -- How to do it... -- How it works... -- Doing dimensionality reduction with manifolds - t-SNE -- Getting ready -- How to do it... -- How it works... -- Testing methods to reduce dimensionality with pipelines -- Getting ready -- How to do it... -- How it works... -- Chapter 4: Linear Models with scikit-learn -- Introduction -- Fitting a line through data -- Getting ready -- How to do it... -- How it works... -- There's more... -- Fitting a line through data with machine learning…”

Tabla de Contenidos:

Tabla de Contenidos: “…Classification error rate comparison using sufficient training data with label noise -- 9.4. Conclusion -- 9.5. References -- Chapter 10. …”

Tabla de Contenidos: “…-- Apply What You Just Learned -- Strategy Without Tactics Is the Slowest Route to Victory -- Nostalgia Marketing and What We Can Learn From John Lewis Ads -- Apply What You Just Learned -- Tactics Without Strategy Is the Noise Before Defeat -- How Is Marketing Going to Help Deliver on Your Business Strategy? …”

Tabla de Contenidos: “…Defining a molecular problem in Qiskit -- Using VQE with Hamiltonians -- Finding excited states with Qiskit -- Using VQE with molecular problems -- Simulations with noise -- Running VQE on quantum computers -- The shape of things to come: the future of Qiskit -- Using VQE with PennyLane -- Defining a molecular problem in PennyLane -- Implementing and running VQE -- Running VQE on real quantum devices -- Summary -- Part 3: A Match Made in Heaven: Quantum Machine Learning -- Chapter 8: What Is Quantum Machine Learning? …”

Tabla de Contenidos: “…Keras advanced activation layers -- Keras normalization layers -- Keras noise layers -- Adding Layers to the Keras Model -- Sequential API to add layers to the Keras model -- Functional API to add layers to the Keras Model -- Compiling the Keras model -- Training the Keras model -- Predicting with the Keras model -- Additional modules in Keras -- Keras sequential model example for MNIST dataset -- Summary -- Chapter 4: Classical Machine Learning with TensorFlow -- Simple linear regression -- Data preparation -- Building a simple regression model -- Defining the inputs, parameters, and other variables -- Defining the model -- Defining the loss function -- Defining the optimizer function -- Training the model -- Using the trained model to predict -- Multi-regression -- Regularized regression -- Lasso regularization -- Ridge regularization -- ElasticNet regularization -- Classification using logistic regression -- Logistic regression for binary classification -- Logistic regression for multiclass classification -- Binary classification -- Multiclass classification -- Summary -- Chapter 5: Neural Networks and MLP with TensorFlow and Keras -- The perceptron -- MultiLayer Perceptron -- MLP for image classification -- TensorFlow-based MLP for MNIST classification -- Keras-based MLP for MNIST classification -- TFLearn-based MLP for MNIST classification -- Summary of MLP with TensorFlow, Keras, and TFLearn -- MLP for time series regression -- Summary -- Chapter 6: RNN with TensorFlow and Keras -- Simple Recurrent Neural Network -- RNN variants -- LSTM network -- GRU network -- TensorFlow for RNN -- TensorFlow RNN Cell Classes -- TensorFlow RNN Model Construction Classes -- TensorFlow RNN Cell Wrapper Classes -- Keras for RNN -- Application areas of RNNs -- RNN in Keras for MNIST data -- Summary -- Chapter 7: RNN for Time Series Data with TensorFlow and Keras…”

Tabla de Contenidos: “…Cover -- Contents -- 1 Introduction to the Linux Kernel -- History of Unix -- Along Came Linus: Introduction to Linux -- Overview of Operating Systems and Kernels -- Linux Versus Classic Unix Kernels -- Linux Kernel Versions -- The Linux Kernel Development Community -- Before We Begin -- 2 Getting Started with the Kernel -- Obtaining the Kernel Source -- Using Git -- Installing the Kernel Source -- Using Patches -- The Kernel Source Tree -- Building the Kernel -- Configuring the Kernel -- Minimizing Build Noise -- Spawning Multiple Build Jobs -- Installing the New Kernel -- A Beast of a Different Nature -- No libc or Standard Headers -- GNU C -- No Memory Protection -- No (Easy) Use of Floating Point -- Small, Fixed-Size Stack -- Synchronization and Concurrency -- Importance of Portability -- Conclusion -- 3 Process Management -- The Process -- Process Descriptor and the Task Structure -- Allocating the Process Descriptor -- Storing the Process Descriptor -- Process State -- Manipulating the Current Process State -- Process Context -- The Process Family Tree -- Process Creation -- Copy-on-Write -- Forking -- vfork() -- The Linux Implementation of Threads -- Creating Threads -- Kernel Threads -- Process Termination -- Removing the Process Descriptor -- The Dilemma of the Parentless Task -- Conclusion -- 4 Process Scheduling -- Multitasking -- Linux's Process Scheduler -- Policy -- I/O-Bound Versus Processor-Bound Processes -- Process Priority -- Timeslice -- The Scheduling Policy in Action -- The Linux Scheduling Algorithm -- Scheduler Classes -- Process Scheduling in Unix Systems -- Fair Scheduling -- The Linux Scheduling Implementation -- Time Accounting -- Process Selection -- The Scheduler Entry Point -- Sleeping and Waking Up -- Preemption and Context Switching -- User Preemption -- Kernel Preemption -- Real-Time Scheduling Policies…”

“…Leverage Raspberry Pi 3 and different JavaScript platforms to build exciting Robotics projects Key Features Build robots that light up and make noise Learn to work with Raspberry Pi 3 and JavaScript Connect your Johnny-Five projects to external APIs and create your own IoT Book Description There has been a rapid increase in the use of JavaScript in hardware and embedded device programming. …”

“…Opto-mechanical FOS's offer unique advantages, including immunity to electromagnetic interference, high fidelity and signal-to-noise ratio, low-loss remote sensing and small size. …”