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281
Computational ecology : graphs, networks and agent-based modeling
Published 2012Table of Contents: “…Paton's fundamental circuit finding algorithm; 1.2.2. Chan's circuit matrix algorithm; 1.3. …”
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282
Apache Spark Machine Learning Blueprints.
Published 2016Full text (MFA users only)
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283
Data analytics and big data
Published 2018Table 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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284
Graph Partitioning.
Published 2013Table of Contents: “…Hendrickson-Leland coarsening algorithm; 2.3.4. The Heavy Edge Matching (HEM) algorithm; 2.4. …”
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285
Emerging engineering approaches and applications : selected, peer reviewed papers from the 2011 International Conference on Information Engineering for Mechanics and Materials, Aug...
Published 2011Table of Contents: “…A Hierarchical Structure of Service-Oriented Manufacturing ModeStudy of Combination Algorithm in Partitioning Manufacture Technology; The Machinability of MAR-M247 Superalloy; Chapter 3: Computational Methods for Engineering; The BP Network Classification Leafminer-Infected Leaves Based on the Fractal Dimension; An Evaluation Survey of Score Normalization in Multibiometric Systems; Non-Line-of-Sight Error Mitigation in Wireless Communication Systems; Information Delay Protocol Using Non-Orthogonal Quantum States; A New Algorithm of Image Encryption Based on 3D Arnold Cat…”
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286
A practical guide to error-control coding using Matlab
Published 2010Full text (MFA users only)
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287
Hardness of Approximation Between P and NP
Published 2019Full text (MFA users only)
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288
Nonlinear systems and optimization for the chemical engineer : solving numerical problems
Published 2013Table 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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289
Wireless Sensor and Ad Hoc Networks Under Diversified Network Scenarios.
Published 2012Full text (MFA users only)
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290
Informatics for Materials Science and Engineering : Data-driven Discovery for Accelerated Experimentation and Application.
Published 2013Table 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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291
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292
Hack proofing your network
Published 2002Table 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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293
Tapas in Experimental Mathematics.
Published 2008Table 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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294
Generative design
Published 2015Table 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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295
Advances in time series forecasting. Volume 2
Published 2017Table 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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296
Automatic Text Summarization
Published 2014Table of Contents: “…State-of-the-art approaches; 3.4. Latent semantic analysis; 3.5. Graph-based approaches; 3.6. …”
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297
Lectures in real geometry
Published 1996Table of Contents: “…Foreword -- Introduction -- Basic algorithms in real algebraic geometry and their complexity: from Sturmâ€?…”
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298
Infectious diseases in pediatric otolaryngology : a practical guide
Published 2016Full text (MFA users only)
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299
Atlas of multiparametric prostate MRI : with PI-RADS approach and anatomic-MRI-pathological correlation
Published 2018Full text (MFA users only)
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300
PRINCIPLES OF QUANTUM ARTIFICIAL INTELLIGENCE.
Published 2013Table of Contents: “…Computation; 2.1 Entscheidungsproblem; 2.1.1 Cantor's diagonal argument; 2.1.2 Reductio ad absurdum; 2.2 Complexity Theory; 2.2.1 Decision problems; 2.2.2 P and NP; 2.3 Church-Turing Thesis; 2.3.1 Church-Turing-Deutsch principle; 2.4 Computers; 2.4.1 Analog computers; 2.4.2 Digital computers; 2.4.3 Von Neumann architecture; 3. …”
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