Search Results - (((((((kant OR want) OR semantic) OR when) OR cantor) OR anne) OR blaney) OR hints) algorithms.

From text to political positions : text analysis across disciplines

Table of Contents: “…Conditional probabilities and associative framing ; Semantic network analysis.…”
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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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Challenges in information technology management

Table of Contents: “…Improved data mining algorithms for frequent patterns with composite items / Ke Wang, James N.K. …”
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Meeting security challenges through data analytics and decision support

Table of Contents: “…Counter Terrorism: Methodology and Applications; Arguing About Uncertain Heterogeneous Information for Threat Assessment; Intelligence Analysis: Needs and Solutions; Building Agile Human/Machine Teams with Controlled Natural Language; Military Usages of Speech and Language Technologies: A Review; Comparative Studies on Using Semantic Filtering for Open Relation Identification; Towards an Integration of Fusion of Information and Analytics Technologies (FIAT) to Improve Dependability and Security in Complex Systems; Data Fusion and Response Management.…”
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Fuzzy systems and data mining II : proceedings of FSDM 2016

Table of Contents: “…Adaptive Fuzzy Sliding-Mode Control of Robot and SimulationHesitant Bipolar Fuzzy Set and Its Application in Decision Making; Chance Constrained Twin Support Vector Machine for Uncertain Pattern Classification; Set-Theoretic Kripke-Style Semantics for Monoidal T-Norm (Based) Logics; Data Mining; Dynamic Itemset Mining Under Multiple Support Thresholds; Deep Learning with Large Scale Dataset for Credit Card Data Analysis; Probabilistic Frequent Itemset Mining Algorithm over Uncertain Databases with Sampling; Priority Guaranteed and Energy Efficient Routing in Data Center Networks.…”
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Helping Children Learn Mathematics.

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Bladder Cancer : diagnosis and clinical management

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OpenCV Android Programming By Example. by Muhammad, Amgad

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Apache Spark for Data Science Cookbook. by Chitturi, Padma Priya

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Two-degree-of-freedom control systems : the Youla Parameterization approach by Keviczky, László, Bányász, Csilla

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MATLAB for Machine Learning. by Ciaburro, Giuseppe

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Statistical learning from a regression perspective by Berk, Richard A.

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Computing the homology of the lambda algebra by Tangora, Martin C.

Table of Contents: “…Corollaries to the structure formulas""; ""2.6. Tri-grading when p is odd""; ""2.7. The endomorphism Î?""; ""2.8. …”
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Cystic Tumors of the Pancreas : Diagnosis and Treatment

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Atlas of AI : power, politics, and the planetary costs of artificial intelligence by Crawford, Kate, 1976-

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Foundations of decision-making agents : logic, probability and modality by Das, Subrata Kumar

Table of Contents: “…Complexity of inference algorithms. 6.9. Acquisition of probabilities. 6.10. …”
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Database technology for life sciences and medicine

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Graph drawing and applications for software and knowledge engineers by Sugiyama, Kozo, 1945-

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Data analysis with R : load, wrangle, and analyze your data using the world's most powerful statistical programming language by Fischetti, Tony

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Artificial Neural Network Applications for Software Reliability Prediction. by Bisi, Manjubala

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