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Digital wealth : an automatic way to invest successfully by Moore, Simon, 1978-

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Evolutionary optimization

Table of Contents: “…Cover -- Contents -- Preface -- Contributing Authors -- Part I Introduction -- 1 Conventional Optimization Techniques -- 1 Classifying Optimization Models -- 2 Linear Programming -- 3 Goal Programming -- 4 Integer Programming -- 5 Nonlinear Programming -- 6 Simulation -- 7 Further Reading -- 2 Evolutionary Computation -- 1 What Is Evolutionary Computation -- 2 A Brief Overview of Evolutionary Computation -- 3 Evolutionary Algorithm and Generate-and-Test Search Algorithm -- 4 Search Operators -- 5 Summary -- Part II Single Objective Optimization -- 3 Evolutionary Algorithms and Constrained Optimization -- 1 Introduction -- 2 General considerations -- 3 Numerical optimization -- 4 Final Remarks -- 4 Constrained Evolutionary Optimization -- 1 Introduction -- 2 The Penalty Function Method -- 3 Stochastic Ranking -- 4 Global Competitive Ranking -- 5 How Penalty Methods Work -- 6 Experimental Study -- 7 Conclusion -- Appendix: Test Function Suite -- Part III Multi-Objective Optimization -- 5 Evolutionary Multiobjective Optimization -- 1 Introduction -- 2 Definitions -- 3 Historical Roots -- 4 A Quick Survey of EMOO Approaches -- 5 Current Research -- 6 Future Research Paths -- 7 Summary -- 6 MEA for Engineering Shape Design -- 1 Introduction -- 2 Multi-Objective Optimization and Pareto-Optimality -- 3 Elitist Non-dominated Sorting GA (NSGA-II) -- 4 Hybrid Approach -- 5 Optimal Shape Design -- 6 Simulation Results -- 7 Conclusion -- 7 Assessment Methodologies for MEAs -- 1 Introduction -- 2 Assessment Methodologies -- 3 Discussion -- 4 Comparing Two Algorithms: An Example -- 5 Conclusions and Future Research Paths -- Part IV Hybrid Algorithms -- 8 Hybrid Genetic Algorithms -- 1 Introduction -- 2 Hybridizing GAs with Local Improvement Procedures -- 3 Adaptive Memory GA's -- 4 Summary -- 9 Combining choices of heuristics -- 1 Introduction -- 2 GAs and parameterised algorithms -- 3 Job Shop Scheduling -- 4 Scheduling chicken catching -- 5 Timetabling -- 6 Discussion and future directions -- 10 Nonlinear Constrained Optimization -- 1 Introduction -- 2 Previous Work -- 3 A General Framework to look for SPdn -- 4 Experimental Results -- 5 Conclusions -- Part V Parameter Selection in EAs -- 11 Parameter Selection -- 1 Introduction -- 2 Parameter tuning vs. parameter control -- 3 An example -- 4 Classification of Control Techniques -- 5 Various forms of control -- 6 Discussion -- Part VI Application of EAs to Practical Problems -- 12 Design of Production Facilities -- 1 Introduction -- 2 Design for Material Flow When the Number of I/O Points is Unconstrained -- 3 Design for Material Flow for a Single I/O Point -- 4 Considering Intradepartmental Flow -- 5 Material Handling System Design -- 6 Concluding Remarks -- 13 Virtual Population and Acceleration Techniques -- 1 Introduction -- 2 Concept of Virtual Population -- 3 Solution Acceleration Techniques -- 4 Accelerated GA and Acceleration Sche.…”
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Function Estimates. by Marron, J. S.

Table of Contents: “…Contents -- Preface -- Logspline density estimation -- Statistical encounters with B-splines -- Estimation of a transfer function in a nongaussian context -- Evaluating the performance of an inversion algorithm -- Harmonic splines in geomagnetism -- Problems in estimating the anomalous gravity potential of the earth from discrete data -- What regression model should be chosen when the statistician misspecifies the error distribution? …”
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The silicon jungle : a novel of deception, power, and Internet intrigue by Baluja, Shumeet, 1971-

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Introduction to graph theory by Voloshin, Vitaly I. (Vitaly Ivanovich), 1954-

Table of Contents: “…What Is Mathematical Induction; 7.2. Graph Theory Algorithms and Their Complexity; 7.3. Answers and Hints to Selected Exercises; 7.4. …”
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Artificial Intelligence and Machine Learning Fundamentals : Develop Real-World Applications Powered by the Latest AI Advances. by Nagy, Zsolt

Table of Contents: “…Optimizing the Minmax Algorithm with Alpha-Beta PruningDRYing up the Minmax Algorithm -- The NegaMax Algorithm; Using the EasyAI Library; Activity 4: Connect Four; Summary; Regression; Introduction; Linear Regression with One Variable; What Is Regression?…”
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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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Applied data analytics : principles and applications by Agbinya, Johnson I.

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Comorbidity in migraine

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Slantwise moves : games, literature, and social invention in nineteenth-century America by Guerra, Douglas

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Continuing Kepler's Quest : Assessing Air Force Space Command's Astrodynamics Standards

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Mastering Scala machine learning by Kozlov, Alexander

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CUDA programming : a developer's guide to parallel computing with GPUs by Cook, Shane

Table of Contents: “…ALGORITHMIC ISSUESFINDING AND AVOIDING ERRORS; DEVELOPING FOR FUTURE GPUS; FURTHER RESOURCES; CONCLUSION; References; Index.…”
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Discovering knowledge in data : an introduction to data mining by Larose, Daniel T.

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Numerical Methods for Eigenvalue Problems. by Börm, Steffen

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Eat, cook, grow : mixing human-computer interactions with human-food interactions

Table of Contents: “…"You don't have to be a gardener to do urban agriculture": understanding opportunities for designing interactive technologies to support urban food production / William Odom -- Augmented agriculture, algorithms, aerospace, and alimentary architectures / Jordan Geiger -- The allure of provenance: tracing food through user-generated production information / Ann Light -- Beyond gardening: a new approach to HCI and urban agriculture / Tad Hirsch -- Hungry for data: metabolic interaction from farm to fork to phenotype / Marc Tuters and Denisa Kera -- Food futures: three provocations to challenge HCI interventions / Greg Hearn and David Lindsay Wright -- Bringing technology to the dining table / Charles Spence -- List of recipes.…”
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Literature and encyclopedism in Enlightenment Britain : the pursuit of complete knowledge by Rudy, Seth, 1978-

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Parallel Computing : Advances and Current Issues, Proceedings of the International Conference Parco2001. by Joubert, G. R.

Table of Contents: “…Committees ; Preface ; Invited Papers ; Deploying Parallel Numerical Library Routines to Cluster Computing in a Self Adapting Fashion ; 1 Overview ; 2 Numerical libraries in shared homogeneous distributed environments ; 3 Sample software implementation and results.…”
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Optimization of Observation and Control Processes. by Malyshev, V. V.

Table of Contents: “…Optimization of Informational Noise When Observing a Dynamic Object""; ""4.6. Example of Observing a Maneuvering Object""; ""Chapter 5. …”
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Handbook of operations research in natural resources

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