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61
Handbook of performability engineering
Published 2008Table of Contents: “…Tampered Failure Rate Load-Sharing Systems: Status and Perspectives /…”
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62
Market liquidity : theory, evidence, and policy
Published 2013Table of Contents: “…Risk-sharing Effects…”
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63
Modeling Reality : How Computers Mirror Life.
Published 2004Table of Contents: “…Contents; 1 From building blocks to computers: Models and modeling; 2 The game of life: A legendary cellular automaton; 3 Heads or tails: Probability of an event; 4 Galton's board: Probability and statistics; 5 Twenty questions: Probability and information; 6 Snowflakes: The evolution of dynamical systems; 7 The Lorenz butterfly: Deterministic chaos; 8 From Cantor to Mandelbrot: Self-similarity and fractals; 9 Typing monkeys: Statistical linguistics; 10 The bridges of Königsberg: Graph theory; 11 Prisoner's dilemma: Game theory; 12 Let the best man win: Genetic algorithms.…”
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64
Media technologies : essays on communication, materiality, and society
Published 2014Table of Contents: “…Bowker -- "What Do We Want?" "Materiality!" "When Do We Want It?" "Now!" …”
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65
Open innovation : new product development essentials from the PDMA
Published 2014Table of Contents: “…Pricing Algorithm --…”
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67
Data clustering in C++ : an object-oriented approach
Published 2011Full text (MFA users only)
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68
Pattern discovery in biomolecular data : tools, techniques, and applications
Published 1999Table of Contents: “…Discovering patterns in DNA sequences by the algorithmic significance method / Aleksandar Milosavljevic -- Assembling blocks / Jorja G. …”
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69
Artificial neural systems : principle and practice
Published 2015Table of Contents: “…INTRODUCTIONDENSITY BASED ALGORITHMS: CLUSTERING ALGORITHMS; NATURE-BASED ALGORITHMS; Evolutionary Algorithm and Programming ; Genetic Algorithm; GA Operators; APPLICATIONS OF GENETIC ALGORITHM; NETWORK METHOD: EDGES AND NODES; MULTI-LAYERED PERCEPTRON; REAL-TIME APPLICATIONS OF STATE-OF-THE-ART ANN SYSTEMS; DEFINITION OF ARTIFICIAL NEURAL NETWORKS (ANN); Intelligence; An Artificial Neural Network (ANN) system; PERFORMANCE MEASURES; Receiver's Operating Characteristics (ROC); Hypothesis Testing; Chi-squared (Goodness-of-fit) Test; CONFLICT OF INTEREST; ACKNOWLEDGEMENTS; REFERENCES…”
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70
Ivor Horton's beginning Visual C++ 2012
Published 2012Table of Contents: “…Using shared_ptr Objects --…”
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72
Methods for Network Optimization and Parallel Derivative-free Optimization.
Published 2014Table of Contents: “…Intro -- Abstract -- Populärvetenskaplig sammanfattning -- Acknowledgements -- Thesis Introduction -- Contents -- Part I Contributions to Network Optimization -- 1 Introduction -- 2 Related Work -- 3 The Relay Positioning Problems -- 4 Environment Representation and Discretization -- 5 Relay Positioning Algorithms for Single Target Problems -- 6 Relay Positioning for Multiple Targets -- 7 Implementation and Experimental Results -- 8 Discussion -- Bibliography -- Part II Contributions to Derivative-free Optimization -- 9 Introduction -- 10 Setting And Problem Description -- 11 Direct Search Algorithms -- 12 Model Building Algorithms -- 13 Existing Model Building Algorithms -- 14 Radial Basis Functions -- 15 Parallelism in Algorithms for Derivative-Free Optimization -- 16 Information Sharing -- 17 Control of Optimization Algorithms -- 18 Implementation Details -- 19 Testing on Synthetic Test Cases -- 20 Testing On Industrial Test Cases -- 21 Future Work -- 22 Conclusions -- A Terms -- Bibliography.…”
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73
Navigation signal processing for GNSS software receivers
Published 2010Full text (MFA users only)
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74
Machine learning : a Bayesian and optimization perspective
Published 2015Table of Contents: “…Probability and stochastic processes -- Learning in parametric modeling: basic concepts and directions -- Mean-square error linear estimation -- Stochastic gradient descent: the LMS algorithm -- The least-squares family -- Classification: a tour of the classics -- Parameter learning: a convex analytic path -- Sparsity-aware learning: concepts and theoretical foundations -- Sparcity-aware learning: algorithms and applications -- Learning in reproducing Kernel Hilbert spaces -- Bayesian learning: inference and the EM alogrithm -- Bayesian learning: approximate inference and nonparametric models -- Monte Carlo methods -- Probabilistic graphical models: Part I -- Probabilistic graphical models: Part II -- Particle filtering -- Neural networks and deep learning -- Dimensionality reduction -- Appendix A LInear algebra -- Appendix B Probability theory and statistics -- Appendix C Hints on constrained optimization.…”
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75
Learning Boost C++ libraries : solve practical programming problems using powerful, portable, and expressive libraries from Boost
Published 2015Table of Contents: “…Shared ownership semanticsboost::shared_ptr and std::shared_ptr; Intrusive smart pointers -- boost::intrusive_ptr; shared_array; Managing non-memory resources using smart pointers; Self-test questions; Summary; References; Chapter 4: Working with Strings; Text processing with Boost String Algorithms library; Using Boost String Algorithms; Find algorithms; Case-conversion and trimming algorithms; The replace and erase algorithms; The split and join algorithms; Splitting text using the Boost Tokenizer library; Tokenizing based on separators…”
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76
Autonomous mobile robots and multi-robot systems : motion-planning, communication, and swarming
Published 2020Full text (MFA users only)
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77
Visible Business : Uncover the Blindspots and Engage the World's Female Economy.
Published 2017Table of Contents: “…Blind Spots; Contents; Foreword; About the Author; Acknowledgements; To my community; To my village; Preface; Introduction; Chapter 1 From history to herstory; The birth of business marketing; Things have changed -- or have they?; Women want more; The wo-man algorithm; Become conscious of the bias; From reject to results; Chapter 2 Are you blind?…”
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78
Analytical modeling of wireless communication systems
Published 2016Table of Contents: “…Safety Message Broadcasting -- Modeling Information Sharing -- Cellular Networks. Multi-RAT Algorithms.…”
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79
Introduction to graph and hypergraph theory
Published 2009Full text (MFA users only)
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80
Advanced Analytics with R and Tableau.
Published 2016Table of Contents: “…; Understanding the performance of the result; Next steps; Sharing our data analysis using Tableau; Interpreting the results; Summary; Chapter 5: Classifying Data with Tableau; Business understanding; Understanding the data; Data preparation; Describing the data; Data exploration; Modeling in R; Analyzing the results of the decision tree; Model deployment; Decision trees in Tableau using R; Bayesian methods; Graphs; Terminology and representations; Graph implementations; Summary.…”
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