Search Results - (((((((ant OR kkantis) OR wants) OR hints) OR cantor) OR anne) OR find) OR wkanting) algorithms.

Java Deep Learning Projects : Implement 10 Real-World Deep Learning Applications Using Deeplearning4j and Open Source APIs. by Karim, Rezaul

Table of Contents: “…; Artificial Neural Networks; Biological neurons; A brief history of ANNs; How does an ANN learn?; ANNs and the backpropagation algorithm; Forward and backward passes; Weights and biases; Weight optimization; Activation functions.…”
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Optimization advances in electric power systems

Table of Contents: “…Unreliability Costs -- 3.5. Proposed Algorithms -- 3.5.1. ES and TS Algorithms -- 3.5.2. …”
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Integrated and collaborative product development environment : technologies and implementations by Li, W. D.

Table of Contents: “…Intelligent Optimisation of Process Planning; 5.1 Intelligent Optimisation Strategies for CAPP Systems; 5.2 Knowledge Representation of Process Plans; 5.2.1 Process plan representation; 5.2.2 Machining cost criteria for process plans; 5.2.3 Precedence constraints; 5.3 A Hybrid GA/SA-based Optimisation Method; 5.3.1 Overview of the algorithm; 5.3.2 Genetic algorithm -- phase 1; 5.3.3 Simulated annealing algorithm -- phase 2; 5.3.4 Constraint handling algorithm.…”
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Datafied society : studying culture through data

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Trading systems and methods by Kaufman, Perry J.

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Bladder Cancer : diagnosis and clinical management

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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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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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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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Mastering machine learning with scikit-learn : learn to implement and evaluate machine learning solutions with scikit-learn by Hackeling, Gavin

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Learning OpenCV 3 Application Development. by Datta, Samyak

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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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