Search Results - (((((((ant OR manthe) OR find) OR mantis) OR cantor) OR anne) OR halted) OR grwanting) algorithms.

Artificial intelligence for big data : complete guide to automating big data solutions using artificial intelligence techniques. by Deshpande, Anand

Table of Contents: “…Snowball stemming -- Lancaster stemming -- Lovins stemming -- Dawson stemming -- Lemmatization -- N-grams -- Feature extraction -- One hot encoding -- TF-IDF -- CountVectorizer -- Word2Vec -- CBOW -- Skip-Gram model -- Applying NLP techniques -- Text classification -- Introduction to Naive Bayes' algorithm -- Random Forest -- Naive Bayes' text classification code example -- Implementing sentiment analysis -- Frequently asked questions -- Summary -- Chapter 7: Fuzzy Systems -- Fuzzy logic fundamentals -- Fuzzy sets and membership functions -- Attributes and notations of crisp sets -- Operations on crisp sets -- Properties of crisp sets -- Fuzzification -- Defuzzification -- Defuzzification methods -- Fuzzy inference -- ANFIS network -- Adaptive network -- ANFIS architecture and hybrid learning algorithm -- Fuzzy C-means clustering -- NEFCLASS -- Frequently asked questions -- Summary -- Chapter 8: Genetic Programming -- Genetic algorithms structure -- KEEL framework -- Encog machine learning framework -- Encog development environment setup -- Encog API structure -- Introduction to the Weka framework -- Weka Explorer features -- Preprocess -- Classify -- Attribute search with genetic algorithms in Weka -- Frequently asked questions -- Summary -- Chapter 9: Swarm Intelligence -- Swarm intelligence -- Self-organization -- Stigmergy -- Division of labor -- Advantages of collective intelligent systems -- Design principles for developing SI systems -- The particle swarm optimization model -- PSO implementation considerations -- Ant colony optimization model -- MASON Library -- MASON Layered Architecture -- Opt4J library -- Applications in big data analytics -- Handling dynamical data -- Multi-objective optimization -- Frequently asked questions -- Summary -- Chapter 10: Reinforcement Learning -- Reinforcement learning algorithms concept.…”
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Cognitive foundations of musical pitch by Krumhansl, Carol L.

Table of Contents: “…Statistical analyses of tonal compositions Tonal distributions and tonal hierarchies; Tonal hierarchies, tonal consonance, and tonal distributions; 4. A KEY-FINDING ALGORITHM BASED ON TONAL HIERARCHIES; The key-finding algorithm; Application I: initial segments of preludes of J.S. …”
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Industrial and Applied Mathematics in China. by Li, Tatsien

Table of Contents: “…Mathematical Problems in System-on-Chip Design and ManufactureA New Reconstruction Algorithm for Cone-beam CT with Unilateral Off-centered RT Multi-scan; Bioluminescence Tomography Reconstruction by Radial Basis Function Collocation Method.…”
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Multi-Objective Optimization in Chemical Engineering : Developments and Applications. by Rangaiah, Gade Pandu

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Adaptive phased array thermotherapy for cancer by Fenn, A. J. (Alan Jeffrey), 1953-

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Computational ecology : graphs, networks and agent-based modeling by Zhang, Wenjun

Table of Contents: “…Paton's fundamental circuit finding algorithm; 1.2.2. Chan's circuit matrix algorithm; 1.3. …”
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Apache Spark Machine Learning Blueprints. by Liu, Alex

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Data analytics and big data by Sedkaoui, Soraya

Table of Contents: “…Data analytics and machine learning: the relevance of algorithms -- Machine learning: a method of data analysis that automates analytical model building -- Supervised versus unsupervised algorithms: a guided tour -- Applications and examples.…”
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Graph Partitioning. by Bichot, Charles-Edmond

Table of Contents: “…Hendrickson-Leland coarsening algorithm; 2.3.4. The Heavy Edge Matching (HEM) algorithm; 2.4. …”
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A practical guide to error-control coding using Matlab by Jiang, Yuan

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Hardness of Approximation Between P and NP by Rubinstein, Aviad

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Nonlinear systems and optimization for the chemical engineer : solving numerical problems by Buzzi-Ferraris, G. (Guido), Manenti, Flavio

Table of Contents: “…Nonlinear Systems and Optimization for the Chemical Engineer: Solving Numerical Problems; Contents; Preface; 1 Function Root-Finding; 1.1 Introduction; 1.2 Substitution Algorithms; 1.3 Bolzano's Algorithm; 1.4 Function Approximation; 1.4.1 Newton's Method; 1.4.2 The Secant Method; 1.4.3 Regula Falsi Method; 1.4.4 Muller's Method or Parabolic Interpolation; 1.4.5 Hyperbolic Interpolation Method; 1.4.6 Inverse Polynomial Interpolation Method; 1.4.7 Inverse Rational Interpolation Method; 1.5 Use of a Multiprocessor Machine with a Known Interval of Uncertainty.…”
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Wireless Sensor and Ad Hoc Networks Under Diversified Network Scenarios. by Sarkar, Subir Kumar

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Informatics for Materials Science and Engineering : Data-driven Discovery for Accelerated Experimentation and Application. by Rajan, Krishna

Table of Contents: “…Dimensionality Reduction Methods: Algorithms, Advantages, and Disadvantages; 3.1 Principal Component Analysis (PCA); PCA Algorithm; 3.2 Isomap; Isomap Algorithm; 3.3 Locally Linear Embedding; LLE Algorithm; 3.4 Hessian LLE; hLLE Algorithm; 4. …”
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Mastering SciPy. by Blanco-Silva, Francisco J.

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Tapas in Experimental Mathematics. by Amdeberhan, Tewodros

Table of Contents: “…""Contents""; ""Preface""; ""Two dimensional directed lattice walks with boundaries""; ""Computer-assisted discovery and proof""; ""On the collection of integers that index the fixed points of maps on the space of rational functions""; ""Questionable claims found in Ramanujan's lost notebook""; ""Partition polynomials: Asymptotics and zeros""; ""Hypergeometric functions related to series acceleration formulas""; ""Using integer relations algorithms for finding relationships among functions""; ""Conjecturing the optimal order of the components of the Li/Keiper constants""…”
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Hack proofing your network

Table of Contents: “…</br><br> Looking to the Source Code</br><br> Exploring Diff Tools</br><br> Using File-Comparison Tools</br><br> Working with Hex Editors</br><br> Utilizing File System Monitoring Tools</br><br> Finding Other Tools</br><br> Troubleshooting</br><br> Problems with Checksums and Hashes</br><br> Problems with Compression and Encryption</br><br> Summary</br><br> Solutions Fast Track</br><br> Frequently Asked Questions</br><br>Chapter 6 Cryptography</br><br> Introduction</br><br> Understanding Cryptography Concepts</br><br> History</br><br> Encryption Key Types</br><br> Learning about Standard Cryptographic Algorithms</br><br> Understanding Symmetric Algorithms</br><br> Understanding Asymmetric Algorithms</br><br> Understanding Brute Force</br><br> Brute Force Basics</br><br> Using Brute Force to Obtain Passwords</br><br> Knowing When Real Algorithms Are Being Used Improperly</br><br> Bad Key Exchanges</br><br> Hashing Pieces Separately</br><br> Using a Short Password to Generate a Long Key</br><br> Improperly Stored Private or Secret Keys</br><br> Understanding Amateur Cryptography Attempts</br><br> Classifying the Ciphertext</br><br> Monoalphabetic Ciphers</br><br> Other Ways to Hide Information</br><br> Summary</br><br> Solutions Fast Track</br><br> Frequently Asked Questions</br><br>Chapter 7 Unexpected Input</br><br> Introduction</br><br> Understanding Why Unexpected Data Is Dangerous</br><br> Finding Situations Involving Unexpected Data</br><br> Local Applications and Utilities</br><br> HTTP/HTML</br><br> Unexpected Data in SQL Queries</br><br> Application Authentication</br><br> Disguising the Obvious</br><br> Using Techniques to Find and Eliminate Vulnerabilities</br><br> Black-Box Testing</br><br> Use the Source</br><br> Untaint Data by Filtering It</br><br> Escaping Characters Is Not Always Enough</br><br> Perl</br><br> Cold Fusion/Cold Fusion Markup Language (CFML)</br><br> ASP</br><br> PHP</br><br> Protecting Your SQL Queries</br><br> Silently Removing versus Alerting on Bad Data</br><br> Invalid Input Function</br><br> Token Substitution</br><br> Utilizing the Available Safety Features in Your Programming Language</br><br> Perl</br><br> PHP</br><br> ColdFusion/ColdFusion Markup Language</br><br> ASP</br><br> MySQL</br><br> Using Tools to Handle Unexpected Data</br><br> Web Sleuth</br><br> CGIAudit</br><br> RATS</br><br> Flawfinder</br><br> Retina</br><br> Hailstorm</br><br> Pudding</br><br> Summary</br><br> Solutions Fast Track</br><br> Frequently Asked Questions</br><br>Chapter 8 Buffer Overflow</br><br> Introduction</br><br> Understanding the Stack</br><br> The Stack Dump</br><br> Oddities and the Stack</br><br> Understanding the Stack Frame</br><br> Introduction to the Stack Frame</br><br> Passing Arguments to a Function: A Sample Program</br><br> Stack Frames and Calling Syntaxes</br><br> Learning about Buffer Overflows</br><br> A Simple Uncontrolled Overflow: A Sample Program</br><br> Creating Your First Overflow</br><br> Creating a Program with an Exploitable Overflow</br><br> Performing the Exploit</br><br> Learning Advanced Overflow Techniques </br><br> Stack Based Function Pointer Overwrite</br><br> Heap Overflows</br><br> Advanced Payload Design</br><br> Using What You Already Have</br><br> Summary</br><br> Solutions Fast Track</br><br> Frequently Asked Questions</br><br>Chapter 9 Format Strings</br><br> Introduction</br><br> Understanding Format String Vulnerabilities</br><br> Why and Where Do Format String Vulnerabilities Exist?…”
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Generative design by Agkathidis, Asterios, 1974-

Table of Contents: “…Intro; 1.0 Introduction to Generative Design; 2.0 Continuous Surfaces; 3.0 Modularity and Accumulation; 4.0 Deformation and Subtraction; 5.0 Algorithmic Patterns; 6.0 Triangulation ; 7.0 Conclusion: The Digital Vs Physical Debate ; Bibliography ; Index; Picture Credits; Acknowledgements; 1.1 Design methods in architecture: A brief review; 1.2 Generative form-finding processes; 1.3 The approach of this book; 2.1 Soft mesh; 2.2 Double-curved shells; 2.3 Hyper paraboloids; 3.1 Interlocking units; 3.2 Irregular units; 4.1 Twisted block; 4.2 Porous space; 5.1 Tessellated planes…”
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Advances in time series forecasting. Volume 2

Table of Contents: “…INTRODUCTION -- CLASSICAL TIME SERIES FORECASTING MODELS -- ARTIFICIAL NEURAL NETWORKS FOR FORECASTING TIME SERIES -- A NEW ARTIFICIAL NEURAL NETWORK WITH DETERMINISTIC COMPONENTS -- APPLICATIONS -- CONCLUSION -- CONFLICT OF INTEREST -- ACKNOWLEDGEMENTS -- REFERENCES -- A Fuzzy Time Series Approach Based on Genetic Algorithm with Single Analysis Process -- Ozge Cagcag Yolcu* -- INTRODUCTION -- FUZZY TIME SERIES -- RELATED METHODS -- Genetic Algorithm (GA) -- Single Multiplicative Neuron Model -- PROPOSED METHOD -- APPLICATIONS -- CONCLUSION AND DISCUSSION -- CONFLICT OF INTEREST -- ACKNOWLEDGEMENTS -- REFERENCES -- Forecasting Stock Exchanges with Fuzzy Time Series Approach Based on Markov Chain Transition Matrix -- Cagdas Hakan Aladag1,* and Hilal Guney2 -- INTRODUCTION -- FUZZY TIME SERIES -- TSAUR 'S FUZZY TIME SERIES MARKOV CHAIN MODEL -- THE IMPLEMENTATION -- CONCLUSION -- CONFLICT OF INTEREST -- ACKNOWLEDGEMENTS -- REFERENCES -- A New High Order Multivariate Fuzzy Time Series Forecasting Model -- Ufuk Yolcu* -- INTRODUCTION -- RELATED METHODOLOGY -- The Fuzzy C-Means (FCM) Clustering Method -- Single Multiplicative Neuron Model Artificial Neural Network (SMN-ANN) -- Fuzzy Time Series -- THE PROPOSED METHOD -- APPLICATIONS -- CONCLUSIONS AND DISCUSSION -- CONFLICT OF INTEREST -- ACKNOWLEDGEMENTS -- REFERENCES -- Fuzzy Functions Approach for Time Series Forecasting -- Ali Z. …”
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Lectures in real geometry

Table of Contents: “…Foreword -- Introduction -- Basic algorithms in real algebraic geometry and their complexity: from Sturmâ€?…”
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