“…The approach is practical and the use of mathematics is kept to a minimum and information is supplied in graphical and tabular form. …”

Tabla de Contenidos: “…A REVIEW OF DATA REPRESENTATION AND THE MATHEMATICS OF COMPUTING -- Binary Information and Representation: Bits, Bytes, Nibbles, Octets, and Characters -- Binary Information -- Binary Information Representation and Groups -- Byte Versus Octet -- Decimal, Binary, Octal, and Hexadecimal Numbers -- Binary Numbers and Their Decimal Equivalents -- Making Binary Numbers Easier to Use by Grouping Bits -- Octal Numbers -- Hexadecimal Numbers -- Decimal, Binary, Octal, and Hexadecimal Number Conversion -- Binary, Octal, and Hexadecimal Conversions -- Conversion from Binary, Octal, or Hexadecimal to Decimal -- Conversion from Decimal to Binary, Octal, or Hexadecimal -- Conversion from Decimal to Binary -- Conversion from Decimal to Octal or Hexadecimal -- Binary, Octal, and Hexadecimal Arithmetic -- Binary Arithmetic -- Octal and Hexadecimal Arithmetic -- Boolean Logic and Logical Functions -- Boolean Logical Functions -- NOT -- AND and OR -- Exclusive-OR (XOR or EOR) -- Combining Boolean Expressions -- Bit Masking (Setting, Clearing, and Inverting) Using Boolean Logical Functions -- Setting Groups of Bits with OR -- Clearing Bits with AND -- Inverting Bits with XOR…”

“…Key topics are addressed in depth including the mathematical definition of novel graph classes, i.e. generalized trees and directed universal hierarchical graphs, and the application areas in which to apply graph classes to practical problems in computational biology, computer science, mathematics, mathematical psychology, etc"--…”

“…Poised among intuition, actual events, and financial mathematics, this book can be used to solve problems in risk management, taxation, regulation, and above all, pric…”

Tabla de Contenidos: “…Cover -- About the Author -- Title Page -- Copyright Page -- Dedication -- Contents -- Foreword -- Acknowledgments -- 1 Introduction -- Why You Should Read This Book -- The Book Subject: Photonic Signals and Systems -- Applications -- The Concluded Learning Experience -- 2 Nature of Light -- Light Propagation -- Nature of Light from Its Early Beginnings -- Negative Refractive Index -- Photon: The Light Particle and Its Application-Photonics -- Mechanical Motion of Matter with Light -- Optoelectronics: Photons and Electrons -- The Laser -- The Fundamental Forces of Matter and Photonics -- Problems -- Additional Reading -- 3 Electromagnetic Waves, Light, and Polarization -- Electromagnetic Waves and Polarization -- Mathematical Formalization of Traveling Waves -- EM Radiation, Media, and Polarization -- Maxwell's Equations for Traveling Waves and Polarization -- Real- and Complex-Wave Representations -- Complex Index of Refraction and Evanescent (Surface) Waves -- Total Internal Reflection and the Evanescent Wave -- Group Velocity and Dispersion -- Polarization Representations -- Problems -- Additional Reading -- 4 Interference, Coherence, and Diffraction -- Interference -- Interference in the RF Regime of the EM Spectrum -- Interference in the Optical Regime of the EM Spectrum -- Interference of Two Optical Beams -- Visualizing Coherence of a Wave -- Plane-Wave Interference via the Plane-Wave Function -- Heterodyne Interferometry-RF Generation via Photo-Detection -- Diffraction -- Problems -- 5 Optical Building Blocks: Components -- Acousto-Optic Devices -- Liquid Crystal Devices -- Mechanical Devices -- Fiber-Optic Devices -- Planar-Optics and Integrated-Optic (Waveguide) Devices -- Problems -- 6 Photonic Systems Using Optical Micro-Electro-Mechanical Systems Devices…”

Tabla de Contenidos: “…-- The Performance Measurement Process -- The Purpose of This Book -- The Role of Performance Analysts -- Book Structure -- 2 The Asset Management Industry -- Asset Classes -- Public Equities -- Bonds (or Fixed Income) -- Cash (and near cash) -- Private Assets -- Real estate -- Private equity -- Private debt -- Infrastructure -- Natural resources -- Commodities -- Derivatives -- Futures -- Forwards -- Swaps -- Options -- Option price sensitivity (the Greeks) -- Warrants -- Convertible bonds -- Contracts for difference (CFDs) -- Overlay strategies -- Currency -- Hedge Funds -- Asset Allocation -- Strategic asset allocation -- Tactical asset allocation -- 3 The Mathematics of Portfolio Return -- Simple Return -- Continuously Compounded (or Logarithmic) Returns -- Money‐weighted Returns (MWRs) -- Internal rate of return (IRR) -- Ex‐ante internal rate of return -- Simple internal rate of return -- Ex‐post internal rate of return -- Simple Dietz -- ICAA method -- Modified Dietz -- Time‐weighted Returns (TWRs) -- True time‐weighted -- Unit price method -- Unit price method with distributions -- Time‐weighted versus Money‐weighted Rates of Return -- Approximations to the Time‐weighted Return -- Index substitution -- Regression method (or β method) -- Analyst's test -- Hybrid Methodologies -- Linked modified Dietz -- BAI method (or linked IRR) -- Which Method to Use? …”

Tabla de Contenidos: “…Cover -- Half-title -- Title page -- Copyright information -- Contents -- Preface -- 1 Introduction -- 1.1 Petroleum Recovery -- 1.2 Reservoir Simulation -- 1.3 Outline of the Book -- 1.4 The First Encounter with MRST -- Part I Geological Models and Grids -- 2 Modeling Reservoir Rocks -- 2.1 Formation of Sedimentary Rocks -- 2.2 Creation of Crude Oil and Natural Gas -- 2.3 Multiscale Modeling of Permeable Rocks -- 2.3.1 Geological Characterization -- 2.3.2 Representative Elementary Volumes -- 2.3.3 Microscopic Models: The Pore Scale -- 2.3.4 Mesoscopic Models -- 2.4 Modeling Rock Properties -- 2.4.1 Porosity -- 2.4.2 Permeability -- 2.4.3 Other Parameters -- 2.5 Property Modeling in MRST -- 2.5.1 Homogeneous Models -- 2.5.2 Random and Lognormal Models -- 2.5.3 The 10th SPE Comparative Solution Project: Model 2 -- 2.5.4 The Johansen Formation -- 2.5.5 SAIGUP: Shallow-Marine Reservoirs -- 3 Grids in Subsurface Modeling -- 3.1 Structured Grids -- 3.2 Unstructured Grids -- 3.2.1 Delaunay Tessellation -- 3.2.2 Voronoi Diagrams -- 3.2.3 General Tessellations -- 3.2.4 Using an External Mesh Generator -- 3.3 Stratigraphic Grids -- 3.3.1 Corner-Point Grids -- 3.3.2 2.5D Unstructured Grids -- 3.4 Grid Structure in MRST -- 3.5 Examples of More Complex Grids -- 3.5.1 SAIGUP: Model of a Shallow-Marine Reservoir -- 3.5.2 Composite Grids -- 3.5.3 Control-Point and Boundary Conformal Grids -- 3.5.4 Multiblock Grids -- Part II Single-Phase Flow -- 4 Mathematical Models for Single-Phase Flow -- 4.1 Fundamental Concept: Darcy's Law -- 4.2 General Flow Equations for Single-Phase Flow -- 4.3 Auxiliary Conditions and Equations -- 4.3.1 Boundary and Initial Conditions -- 4.3.2 Injection and Production Wells -- 4.3.3 Field Lines and Time-of-Flight -- 4.3.4 Tracers and Volume Partitions -- 4.4 Basic Finite-Volume Discretizations -- 4.4.1 Two-Point Flux-Approximation…”

Tabla de Contenidos: “…. -- 5.6 Exercises -- Part II: All the Fundamentals Applied to Inferring a Binomial Probability -- Chapter 6: Inferring a Binomial Probability via Exact Mathematical Analysis -- 6.1 The Likelihood Function: Bernoulli Distribution -- 6.2 A Description of Credibilities: The Beta Distribution -- 6.2.1 Specifying a beta prior -- 6.3 The Posterior Beta -- 6.3.1 Posterior is compromise of prior and likelihood -- 6.4 Examples -- 6.4.1 Prior knowledge expressed as a beta distribution -- 6.4.2 Prior knowledge that cannot be expressed as a beta distribution -- 6.5 Summary -- 6.6 Appendix: R Code for Figure 6.4 -- 6.7 Exercises -- Chapter 7: Markov Chain Monte Carlo -- 7.1 Approximating a Distribution with a Large Sample -- 7.2 A Simple Case of the Metropolis Algorithm -- 7.2.1 A politician stumbles upon the Metropolis algorithm -- 7.2.2 A random walk -- 7.2.3 General properties of a random walk -- 7.2.4 Why we care -- 7.2.5 Why it works -- 7.3 The Metropolis Algorithm More Generally -- 7.3.1 Metropolis algorithm applied to Bernoulli likelihood and beta prior -- 7.3.2 Summary of Metropolis algorithm -- 7.4 Toward Gibbs Sampling: Estimating Two Coin Biases -- 7.4.1 Prior, likelihood and posterior for two biases -- 7.4.2 The posterior via exact formal analysis -- 7.4.3 The posterior via the Metropolis algorithm -- 7.4.4 Gibbs sampling -- 7.4.5 Is there a difference between biases? …”

Tabla de Contenidos: “…12.3.1.5 Spying -- 12.3.2 Active Attacks -- 12.3.2.1 Denial of Service -- 12.3.2.2 Distributed Denial of Service (DDOS) -- 12.3.2.3 Message Modification -- 12.3.2.4 Masquerade -- 12.3.2.5 Trojans -- 12.3.2.6 Replay Attacks -- 12.3.3 Programming Weapons for the Attackers -- 12.3.3.1 Dormant Phase -- 12.3.3.2 Propagation Phase -- 12.3.3.3 Triggering Phase -- 12.3.3.4 Execution Phase -- 12.4 Recent Cyber Attacks -- 12.5 Drawbacks of Traditional Cryptography -- 12.5.1 Cost and Time Delay -- 12.5.2 Disclosure of Mathematical Computation -- 12.5.3 Unsalted Hashing -- 12.5.4 Attacks -- 12.6 Need of Quantum Cryptography -- 12.6.1 Quantum Mechanics -- 12.7 Evolution of Quantum Cryptography -- 12.8 Conclusion and Future Work -- References -- Chapter 13 Identification of Bacterial Diseases in Plants Using Re-Trained Transfer Learning in Quantum Computing Environment -- 13.1 Introduction -- 13.2 Literature Review -- 13.3 Proposed Methodology -- 13.3.1 SVM Classifier -- 13.3.2 Random Forest to Classify the Rice Leaf -- 13.3.2.1 Image Pre-Processing -- 13.3.2.2 Feature Extraction -- 13.3.2.3 Classification -- 13.4 Experiment Results -- Conclusion -- References -- Chapter 14 Quantum Cryptography -- 14.1 Fundamentals of Cryptography -- 14.2 Principle of Quantum Cryptography -- 14.2.1 Quantum vs. …”

Tabla de Contenidos: “…7.4.3 Ropelength -- 7.4.4 Distortion -- 7.4.5 Final Remarks -- Bibliography -- Polygonal approximation of unknots by quadrisecants -- 8.1 Introduction -- 8.2 Quadrisecant approximation of knots -- 8.3 Quadrisecants of Polygonal Unknots -- 8.4 Quadrisecants of Smooth Unknots -- 8.5 Finding Quadrisecants -- 8.6 Test for Good Approximations -- Bibliography -- Open knotting -- 9.1 Introduction -- 9.2 Defining open knotting -- 9.2.1 Single closure techniques -- 9.2.2 Stochastic techniques -- 9.2.3 Other closure techniques -- 9.2.4 Topology of knotted arcs -- 9.3 Visualizing knotting in open chains using the knotting fingerprint -- 9.4 Features of knotting fingerprints, knotted cores, and crossing changes -- 9.5 Conclusions -- Bibliography -- The Knot Spectrum of Random Knot Spaces -- 10.1 Introduction -- 10.2 Basic mathematical background in knot theory -- 10.3 Spaces of random knots, knot sampling and knot identification -- 10.4 An analysis of the behavior of PK with respect to length and radius -- 10.4.1 PK(L,R) as a function of length L for fixed R -- 10.4.2 PK(L,R) as a function of confinement radius R for fixed L -- 10.4.3 Modeling PK as a function of length and radius. -- 10.5 Numerical results -- 10.5.1 The numerical analysis of PK(L,R) based on the old data -- 10.5.2 The numerical analysis of PK(L,R) based on the new data -- 10.5.3 The location of local maxima of PK(L,R) -- 10.6 The influence of the confinement radius on the distributions of knot types -- 10.6.1 3-, 4-, and 5-crossing knots -- 10.6.2 6-crossing knots -- 10.6.3 7-crossing knots -- 10.6.4 8-crossing knots -- 10.6.5 9-crossing knots -- 10.6.6 10-crossing knots -- 10.7 The influence of polygon length on the distributions of knot types in the presence of confinement -- 10.7.1 3-, 4-, and 5-crossing knots -- 10.7.2 6-crossing knots -- 10.7.3 7-crossing knots -- 10.7.4 8-crossing knots…”

Tabla de Contenidos: “…Setting the figure resolution -- Jupyter support -- Interactive navigation toolbar -- Configuring Matplotlib -- Configuring within Python code -- Reverting to default settings -- Global setting via configuration rc file -- Finding the rc configuration file -- Editing the rc configuration file -- Summary -- Chapter 3: Decorating Graphs with Plot Styles and Types -- Controlling the colors -- Default color cycle -- Single-lettered abbreviations for basic colors -- Standard HTML color names -- RGB or RGBA color code -- Hexadecimal color code -- Depth of grayscale -- Colormaps -- Creating custom colormaps -- Line and marker styles -- Marker styles -- Choosing the shape of markers -- Using custom characters as markers -- Adjusting marker sizes and colors -- Fine-tuning marker styles with keyword arguments -- Line styles -- Color -- Line thickness -- Dash patterns -- Designing a custom dash style -- Cap styles -- Spines -- More native Matplotlib plot types -- Choosing the right plot -- Histogram -- Bar plot -- Setting bar plot properties -- Drawing bar plots with error bars using multivariate data -- Mean-and-error plots -- Pie chart -- Polar chart -- Controlling radial and angular grids -- Text and annotations -- Adding text annotations -- Font -- Mathematical notations -- Mathtext -- LaTeX support -- External text renderer -- Arrows -- Using style sheets -- Applying a style sheet -- Creating own style sheet -- Resetting to default styles -- Aesthetics and readability considerations in styling -- Suitable font styles -- Effective use of colors -- Keeping it simple -- Summary -- Chapter 4: Advanced Matplotlib -- Drawing Subplots -- Initiating a figure with plt.figure() -- Initiating subplots as axes with plt.subplot() -- Adding subplots with plt.figure.add_subplot() -- Initiating an array of subplots with plt.subplots() -- Shared axes…”

Tabla de Contenidos: “…Introduction -- 17.2. Mathematical model -- 17.3. Asymptotic average characteristics -- 17.4. …”

Tabla de Contenidos: “…Visualizing the goodness of fit -- Computing MSE and median absolute error -- Evaluating clusters with the mean silhouette coefficient -- Comparing results with a dummy classifier -- Determining MAPE and MPE -- Comparing with a dummy regressor -- Calculating the mean absolute error and the residual sum of squares -- Examining the kappa of classification -- Taking a look at the Matthews correlation coefficient -- Chapter 11: Analyzing Images -- Introduction -- Setting up OpenCV -- Applying Scale-Invariant Feature Transform (SIFT) -- Detecting features with SURF -- Quantizing colors -- Denoising images -- Extracting patches from an image -- Detecting faces with Haar cascades -- Searching for bright stars -- Extracting metadata from images -- Extracting texture features from images -- Applying hierarchical clustering on images -- Segmenting images with spectral clustering -- Chapter 12: Parallelism and Performance -- Introduction -- Just-in-time compiling with Numba -- Speeding up numerical expressions with Numexpr -- Running multiple threads with the threading module -- Launching multiple tasks with the concurrent.futures module -- Accessing resources asynchronously with the asyncio module -- Distributed processing with execnet -- Profiling memory usage -- Calculating the mean, variance, skewness, and kurtosis on the fly -- Caching with a least recently used cache -- Caching HTTP requests -- Streaming counting with the Count-min sketch -- Harnessing the power of the GPU with OpenCL -- Appendix A: Glossary -- Appendix B: Function Reference -- IPython -- Matplotlib -- NumPy -- pandas -- Scikit-learn -- SciPy -- Seaborn -- Statsmodels -- Appendix C: Online Resources -- IPython notebooks and open data -- Mathematics and statistics -- Appendix D: Tips and Tricks for Command-Line and Miscellaneous Tools -- IPython notebooks -- Command-line tools…”

Tabla de Contenidos: “…Cover -- Title Page -- Copyright and Credits -- Dedication -- Packt Upsell -- Contributors -- Table of Contents -- Preface -- Chapter 1: Getting Started with Robot Operating System -- Technical requirements -- Introduction to ROS -- ROS concepts -- The ROS filesystem -- The ROS Computation Graph -- The ROS community level -- Installing ROS on Ubuntu -- Introducing catkin -- Creating a ROS package -- Hello_world_publisher.py -- Hello_world_subscriber.py -- Introducing Gazebo -- Installing Gazebo -- Testing Gazebo with the ROS interface -- Summary -- Questions -- Chapter 2: Understanding the Basics of Differential Robots -- Mathematical modeling of the robot -- Introduction to the differential drive system and robot kinematics -- Forward kinematics of a differential robot -- Explanations of the forward kinematics equation -- Inverse kinematics -- Summary -- Questions -- Further information -- Chapter 3 : Modeling the Differential Drive Robot -- Technical requirements -- Requirements of a service robot -- Robot drive mechanism -- Selection of motors and wheels -- Calculation of RPM of motors -- Calculation of motor torque -- The design summary -- The robot chassis design -- Installing LibreCAD, Blender, and MeshLab -- Installing LibreCAD -- Installing Blender -- Installing MeshLab -- Creating 2D CAD drawing of a robot using LibreCAD -- The base plate designs -- Base plate pole design -- Wheel, motor, and motor clamp design -- Caster wheel design -- Middle plate design -- Top plate design -- Working with a 3D model of the robot using Blender -- Python scripting in Blender -- Introduction to Blender Python APIs -- Python script of the robot model -- Creating a URDF model of the robot -- Creating a Chefbot description ROS package -- Summary -- Questions -- Further reading -- Chapter 4: Simulating a Differential Drive Robot Using ROS…”

Tabla de Contenidos: “…-- Understanding the building blocks of logic programming -- Solving problems using logic programming -- Installing Python packages -- Matching mathematical expressions -- Validating primes -- Parsing a family tree -- Analyzing geography -- Building a puzzle solver -- Summary -- Chapter 7: Heuristic Search Techniques -- What is heuristic search? …”

Tabla de Contenidos: “…. -- Chapter 8: Creating New Features -- Technical requirements -- Combining features with mathematical functions -- Getting ready -- How to do it... -- How it works... -- See also -- Comparing features to reference variables -- How to do it... -- How it works... -- See also -- Performing polynomial expansion -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Combining features with decision trees -- Getting ready -- How to do it... -- How it works... -- Creating periodic features from cyclical variables -- Getting ready -- How to do it... -- How it works... -- See also -- Creating spline features -- Getting ready -- How to do it... -- How it works... -- See also -- Chapter 9: Extracting Features from Relational Data with Featuretools -- Technical requirements -- Setting up an entity set and creating features automatically…”

Tabla de Contenidos: “…Anticipation of Potential Problems: P-Diagrams and DFMEA -- Target and Spec Limits -- Measurement System Analysis -- Capability Analysis -- Flow-Down or Decomposition -- Procedure for Critical Parameter Flow-Down or Decomposition -- Flow-Down Examples -- Initial Tolerance Allocation -- Summary -- Chapter 11 Software DFSS and Agile -- Measuring the Agile Design -- Data Collection Plan for ViewHome Prototype -- Summary -- Chapter 12 Software Architecture Decisions -- Software Architecture Decision-Making Process -- Using Design Heuristics to Make Decisions -- Common Design Heuristics and Principles -- Using Architecture Tactics to Make Decisions -- Using DFSS Design Trade-Off Analysis to Make Decisions -- Using Design Patterns, Simulation, Modeling, and Prototyping for Decisions -- Summary -- Chapter 13 Predictive Engineering: Continuous and Discrete Transfer Functions -- Discrete versus Continuous Critical Parameters -- Methods for Deriving a Transfer Function for a Discrete Critical Parameter -- Logistic Regression for Discrete Parameters -- Methods for Deriving a Transfer Function for a Continuous or Ordinal Critical Parameter -- Existing or Derived Equation (First Principles Modeling) -- Modeling within a Spreadsheet, Mathematical Modeling Software, or Simulation Software -- Empirical Modeling using Historical Data: Regression Analysis and General Linear Model -- Empirical Modeling using Design of Experiments -- Empirical Modeling using Response Surface Methods -- DOE with Simulators: Design and Analysis of Computer Experiments (DACE) -- Summary -- Chapter 14 Predictive Engineering: Optimization and Critical Parameter Flow-Up -- Critical Parameter Flow-Up: Monte Carlo Simulation -- Critical Parameter Flow-Up: Generation of System Moments (Root Sum of Squares) -- Critical Parameter Scorecard -- Selecting Critical Parameters for Optimization…”

“…Dive deeper into neural networks and get your models trained, optimized with this quick reference guide About This Book A quick reference to all important deep learning concepts and their implementations Essential tips, tricks, and hacks to train a variety of deep learning models such as CNNs, RNNs, LSTMs, and more Supplemented with essential mathematics and theory, every chapter provides best practices and safe choices for training and fine-tuning your models in Keras and Tensorflow. …”

“…It is assumed that as a reader you have a good understanding of mathematics. Working knowledge of R is expected. What You Will Learn Get equipped with a deeper understanding of how to apply machine-learning techniques Implement each of the advanced machine-learning techniques Solve real-life problems that are encountered in order to make your applications produce improved results Gain hands-on experience in problem solving for your machine-learning systems Understand the methods of collecting data, preparing data for usage, training the model, evaluating the model's performance, and improving the model's performance In Detail Machine learning has become the new black. …”

Tabla de Contenidos: “…Intro -- Preface -- Organization -- Invited Talks -- How to Solve Math Problems Without Talent -- Bridging Formal Mathematics and Software Verification -- The Art of SMT Solving -- Contents - Part I -- Contents - Part II -- Contents - Part III -- Decision Procedures -- Split Gröbner Bases for Satisfiability Modulo Finite Fields -- 1 Introduction -- 1.1 Related Work -- 2 Background -- 3 Motivating Example -- 3.1 Verifying the Determinism of Num2Bits -- 3.2 The Challenge of Bit-Splitting -- 3.3 Cooperative Reasoning: A Path Forward -- 4 Approach -- 4.1 Split Gröbner bases -- 4.2 Abstract Procedure: Split -- 4.3 Concrete Procedure: BitSplit -- 5 Experiments -- 5.1 Benchmarks -- 5.2 Comparison to Prior Solvers -- 5.3 Comparison to Variants -- 6 Application -- 6.1 Background on Verifiable Field-Blasting -- 6.2 A New Strategy for Verifying Operator Rules -- 7 Conclusion -- A Additional Background -- B Computing Bitsum Usage in Real World Projects -- C Proof of Theorem 1 -- D Proof of Theorems 2 and 3 -- E Proof of Lemma 1 -- F The Seq Benchmark Family -- G Proof of Theorem 4 -- References -- Arithmetic Solving in Z3 -- 1 Introduction -- 2 Design Goals and Implementation Choices -- 3 Linear Real Arithmetic -- 3.1 Linear Solving -- 3.2 Finding Equal Variables - Cheaply -- 3.3 Bounds Propagation -- 4 Integer Linear Arithmetic -- 4.1 Patching -- 4.2 Cubes -- 4.3 GCD Consistency -- 4.4 Branching -- 4.5 Cuts -- 5 Non-linear Arithmetic -- 5.1 Patch Monomials -- 5.2 Bounds Propagation -- 5.3 Adding Bounds -- 5.4 Gröbner reduction -- 5.5 Incremental Linearization -- 5.6 NLSat -- 6 Shared Equalities -- 7 Evaluation -- 8 Summary and Discussion -- References -- Algebraic Reasoning Meets Automata in Solving Linear Integer Arithmetic -- 1 Introduction -- 2 Preliminaries -- 3 Classical Automata-Based Decision Procedure for LIA…”