Search Results - (((((((ant OR wants) OR semantic) OR mind) OR cantor) OR anne) OR plane) OR hints) algorithms.

Ranking the Liveability of the World's Major Cities : the Global Liveable Cities Index (GLCI). by Tan, Khee Giap

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Analytics stories : using data to make good things happen by Winston, Wayne L.

Table of Contents: “…-- Value-Added Assessments of Teacher Effectiveness -- Berkeley, Buses, Cars, and Planes -- Is Carmelo Anthony a Hall of Famer? -- Was Derek Jeter a great fielder? …”
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Fork Algebras in Algebra, Logic and Computer Science. by Frias, Marcelo Fabián

Table of Contents: “…7.5 A Methodology for Program Construction7.6 Examples; 7.6.1 First Example; 7.6.1.1 Finding the Minimum Element in a List; 7.6.1.2 Finding the Minimum Common Ancestor; 7.6.2 Second Example; 7.6.2.1 Finding the Contiguous Sublists of Maximum Sum; 7.6.2.2 Finding the Longest Plateau; 7.7 A D & C Algorithm for MAXSTA; 7.8 Comparison with Previous Work; Bibliography; Index.…”
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FX barrier options : a comprehensive guide for industry quants by Dadachanji, Zareer

Table of Contents: “…Stupid; 4.10 Five things we want from a model; 4.11 Stochastic volatility (SV) models; 4.11.1 SABR model; 4.11.2 Heston model; 4.12 Mixed local/stochastic volatility (lsv) models; 4.12.1 Term structure of volatility of volatility; 4.13 Other models and methods; 4.13.1 Uncertain Volatility (UV) models; 4.13.2 Jump-diffusion models; 4.13.3 Vanna-volga methods; 5 Smile Risk Management; 5.1 Black-Scholes with term structure; 5.2 Local volatility model; 5.3 Spot risk under smile models; 5.4 Theta risk under smile models; 5.5 Mixed local/stochastic volatility models; 5.6 Static hedging; 5.7 Managing risk across businesses; 6 Numerical Methods; 6.1 Finite-difference (FD) methods; 6.1.1 Grid geometry; 6.1.2 Finite-difference schemes; 6.2 Monte Carlo (MC) methods; 6.2.1 Monte Carlo schedules; 6.2.2 Monte Carlo algorithms; 6.2.3 Variance reduction; 6.2.4 The Brownian Bridge; 6.2.5 Early…”
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Practical Strategies in Geriatric Mental Health : Cases and Approaches. by Dunn, Laura B.

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Asymptotic models of fields in dilute and densely packed composites by Movchan, A. B. (Alexander B.)

Table of Contents: “…Motivation; 1.1.2 Asymptotic algorithm involving a boundary layer; 1.1.2.1 Formulation of the problem; 1.1.2.2 The leading-order approximation; 1.1.2.3 Asymptotic formula for the energy; 1.1.3 The dipole matrix; 1.1.3.1 Definition of the dipole matrix; 1.1.3.2 Symmetry of the dipole matrix; 1.1.3.3 The energy asymptotics for a body with a small void; 1.1.4 Dipole matrix for a 2D void in an infinite plane.…”
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Biological computation by Lamm, Ehud

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A Primer on Machine Learning Applications in Civil Engineering by Deka, Paresh Chandra

Table of Contents: “…Cover -- Half Title -- Title Page -- Copyright Page -- Dedication -- Contents -- Preface -- Acknowledgments -- A Primer on Machine Learning Applications in Civil Engineering -- Author -- 1: Introduction -- 1.1 Machine Learning -- 1.2 Learning from Data -- 1.3 Research in Machine Learning: Recent Progress -- 1.4 Artificial Neural Networks -- 1.5 Fuzzy Logic (FL) -- 1.6 Genetic Algorithms -- 1.7 Support Vector Machine (SVM) -- 1.8 Hybrid Approach (HA) -- Bibliography -- 2: Artificial Neural Networks -- 2.1 Introduction to Fundamental Concepts and Terminologies -- 2.2 Evolution of Neural Networks -- 2.3 Models of ANN -- 2.4 McCulloch-Pitts Model -- 2.5 Hebb Network -- 2.6 Summary -- 2.7 Supervised Learning Network -- 2.7.1 Perceptron Network -- 2.7.2 Adaptive Linear Neuron -- 2.7.3 Back-Propagation Network -- 2.7.4 Radial Basis Function Network -- 2.7.5 Generalized Regression Neural Networks -- 2.7.6 Summary -- 2.8 Unsupervised Learning Networks -- 2.8.1 Introduction -- 2.8.2 Kohonen Self-Organizing Feature Maps -- 2.8.3 Counter Propagation Network -- 2.8.4 Adaptive Resonance Theory Network -- 2.8.5 Summary -- 2.9 Special Networks -- 2.9.1 Introduction -- 2.9.2 Gaussian Machine -- 2.9.3 Cauchy Machine -- 2.9.4 Probabilistic Neural Network -- 2.9.5 Cascade Correlation Neural Network -- 2.9.6 Cognitive Network -- 2.9.7 Cellular Neural Network -- 2.9.8 Optical Neural Network -- 2.9.9 Summary -- 2.10 Working Principle of ANN -- 2.10.1 Introduction -- 2.10.2 Types of Activation Function -- 2.10.3 ANN Architecture -- 2.10.4 Learning Process -- 2.10.5 Feed-Forward Back Propagation -- 2.10.6 Strengths of ANN -- 2.10.7 Weaknesses of ANN -- 2.10.8 Working of the Network -- 2.10.9 Summary -- Bibliography -- 3: Fuzzy Logic -- 3.1 Introduction to Classical Sets and Fuzzy Sets -- 3.1.1 Classical Sets -- 3.1.2 Fuzzy Sets -- 3.1.3 Summary.…”
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Artificial intelligence research and development : current challenges, new trends and applications

Table of Contents: “…Step 1: DrugBank -- Unsupervised Systems-Level Learning Mechanism Based on Bayesian-Inference -- Towards a Universal Neural Network Encoder for Time Series -- Determining Classic Versus Modern Style in Fashion -- Data Science, Recommender Systems and Case-Based Reasoning -- Big Data Analytics for Obesity Prediction -- A Method to Integrate Semantic Criteria into a Recommender System Based on ELECTRE Outranking Relations -- A Study on Contextual Influences on Automatic Playlist Continuation.…”
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Power system dynamics by Guruprasada, Rau V.

Table of Contents: “…18.1 Concept of Lyapunov Stability, Asymptotic Stability and Instability -- 18.2 Lyapunov's Asymptotic Stability Theorem -- References -- Chapter 19 Methods of Construction of Lyapunov Functions -- 19.1 Sylvester's Criteria for Definiteness and Semi-Definiteness -- 19.2 Construction of Lyapunov Functions for a Power System -- References -- Chapter 20 Generation of Lyapunov Functions -- 20.1 Energy Metric Algorithm for Generation of Lyapunov Functions -- 20.2 Application to Power System -- 20.3 Evaluation of Region of Asymptotic Stability -- 20.4 Application of Lyapunov Method to Linear System -- References -- Chapter 21 Exercise Problems -- 21.1 Problems with Solutions -- 21.2 Unsolved Problems -- References.…”
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DEEP LEARNING FOR HEALTHCARE DECISION MAKING.

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Microwave and millimeter wave circuits and systems : emerging design, technologies, and applications

Table of Contents: “…1.1.7 MBF Model -- the Memoryless PA Behavioural Model of ChoiceAcknowledgements; References; 2 Artificial Neural Network in Microwave Cavity Filter Tuning; 2.1 Introduction; 2.2 Artificial Neural Networks Filter Tuning; 2.2.1 The Inverse Model of the Filter; 2.2.2 Sequential Method; 2.2.3 Parallel Method; 2.2.4 Discussion on the ANN's Input Data; 2.3 Practical Implementation -- Tuning Experiments; 2.3.1 Sequential Method; 2.3.2 Parallel Method; 2.4 Influence of the Filter Characteristic Domain on Algorithm Efficiency; 2.5 Robots in the Microwave Filter Tuning; 2.6 Conclusions; Acknowledgement…”
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Java Data Mining - Strategy, Standard, and Practice : a Practical Guide for architecture, design, and implementation. by Hornick, Mark F.

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Biomedical image analysis recipes in MATLAB : for life scientists and engineers by Reyes-Aldasoro, Constantino Carlos

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The Big Bang Theory and Philosophy : Rock, Paper, Scissors, Aristotle, Locke

Table of Contents: “…Cover; Contents; Title; Copyright; Acknowledgments; Dedication; Introduction: "Unraveling the Mysteries"; Part One: "It All Began on A Warm Summer's Evening in Greece"; Chapter 1: Aristotle on Sheldon Cooper; The Life of the Mind; The Ancient Greek and the Modern Geek; The Joy of Geekdom; Geeky Fun and the Purpose of Life; Trial of a Nerd; The Aristotle-Cooper Evaluation; Chapter 2: "You're a Sucky, Sucky Friend"; "Do You Have Any Books about Making Friends?"…”
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Advanced Analytics with R and Tableau. by Stirrup, Jen

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Swift 2 design patterns : build robust and scalable iOS and Mac OS X game applications by Lange, Julien

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Multi-dimensional Imaging. by Javidi, Bahram

Table of Contents: “…10.2 Digital Holography 226 -- 10.3 Metal Nanoparticles 227 -- 10.4 Resolution Enhancement in Digital Holography 229 -- 10.5 Field of View Enhancement in Digital Holography 231 -- 10.6 Eliminating the DC Term and the Twin Images 233 -- 10.7 Additional Applications 235 -- Part III MULTI-DIMENSIONAL IMAGING AND DISPLAY -- 11 Three-Dimensional Integral Imaging and Display 243 / Manuel Martƒinez-Corral, Adriǹ Dorado, Anabel LLavador, Genaro Saavedra and Bahram Javidi -- 11.1 Introduction 243 -- 11.2 Basic Theory 245 -- 11.3 The Plenoptic Function 246 -- 11.4 Methods for the Capture of the Plenoptic Field 249 -- 11.5 Walking in Plenoptic Space 255 -- 11.6 Reconstruction of Intensity Distribution in Different Depth Planes 257 -- 11.7 Implementation of the Integral Imaging Display Device 261 -- 11.8 Conclusion 262 -- 12 Image Formats of Various 3-D Displays 267 / Jung-Young Son, Chun-Hea Lee, Wook-Ho Son, Min-Chul Park and Bahram Javidi -- 12.1 Chapter Overview 267 -- 12.2 Introduction 268 -- 12.3 Multiplexing Schemes 269 -- 12.4 Image Formats for 3-D Imaging 271 -- 13 Ray-based and Wavefront-based 3D Representations for Holographic Displays 303 / Masahiro Yamaguchi and Koki Wakunami -- 13.1 Introduction 303 -- 13.2 Ray-based and Wavefront-based 3D Displays 303 -- 13.3 Conversion between Ray-based and Wavefront 3D Representations 307 -- 13.4 Hologram Printer Based on a Full-Parallax Holographic Stereogram 308 -- 13.5 Computational Holography Using a Ray-Sampling Plane 310 -- 13.6 Occlusion Culling for Computational Holography Using the Ray-Sampling Plane 313 -- 13.7 Scanning Vertical Camera Array for Computational Holography 315 -- 13.8 Conclusion and Future Issues 323 -- 14 Rigorous Diffraction Theory for 360 Computer-Generated Holograms 327 / Toyohiko Yatagai, Yusuke Sando and Boaz Jessie Jackin -- 14.1 Introduction 327 -- 14.2 Three-Dimensional Object and Its Diffracted Wavefront 328 -- 14.3 Point-Spread Function Approach for Spherical Holography 333 -- 14.4 Rigorous Point-Spread Function Approach 336.…”
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D Cookbook. by D. Ruppe, Adam

Table of Contents: “…Performing type conversionsFinding the largest files in a directory; Creating a network client and server; Using Base64 to create a data URI; Generating random numbers; Normalizing a string and performing Unicode comparisons; Searching with regular expressions; Writing a digest utility; Using std.zlib compression; Using the std.json module; Chapter 3: Ranges; Introduction; Using ranges when implementing an algorithm; Creating an input range; Creating an output range; Creating a higher-order range; Putting a range interface on a collection; Creating an input range over a tree structure…”
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CCNA Security Study Guide : Exam 210-260. by McMillan, Troy

Table of Contents: “…-- Certification Exam Policies -- Assessment Test -- Answers to Assessment Test -- Chapter 1 Understanding Security Fundamentals -- Goals of Security -- Network Topologies -- Common Network Security Zones -- Summary -- Exam Essentials -- Review Questions -- Chapter 2 Understanding Security Threats -- Common Network Attacks -- Social Engineering -- Malware -- Data Loss and Exfiltration -- Summary -- Exam Essentials -- Review Questions -- Chapter 3 Understanding Cryptography -- Symmetric and Asymmetric Encryption -- Hashing Algorithms -- Key Exchange -- Public Key Infrastructure -- Summary -- Exam Essentials -- Review Questions -- Chapter 4 Securing the Routing Process -- Securing Router Access -- Implementing OSPF Routing Update Authentication -- Securing the Control Plane -- Summary -- Exam Essentials -- Review Questions -- Chapter 5 Understanding Layer 2 Attacks -- Understanding STP Attacks -- Understanding ARP Attacks -- Understanding MAC Attacks -- Understanding CAM Overflows -- Understanding CDP/LLDP Reconnaissance -- Understanding VLAN Hopping -- Understanding DHCP Spoofing -- Summary -- Exam Essentials -- Review Questions -- Chapter 6 Preventing Layer 2 Attacks -- Configuring DHCP Snooping -- Configuring Dynamic ARP Inspection -- Configuring Port Security -- Configuring STP Security Features -- Disabling DTP -- Verifying Mitigations -- Summary -- Exam Essentials -- Review Questions -- Chapter 7 VLAN Security -- Native VLANs -- PVLANs -- ACLs on Switches -- Summary -- Exam Essentials -- Review Questions -- Chapter 8 Securing Management Traffic.…”
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