Search Results - (((((((want OR alter) OR wind) OR semantic) OR cantor) OR anne) OR halted) OR wwanting) algorithms.

Computer and network security essentials

Table of Contents: “…SECURITY APPLICATIONS -- Chapter 25. Generic Semantics Specification and Processing for Inter-System Information Flow Tracking -- Chapter 26. …”
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Nuclear Medicine Imaging: An Encyclopedic Dictionary by Thie, Joseph A.

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The bitcoin big bang : how alternative currencies are about to change the world by Kelly, Brian, 1971-

Table of Contents: “…; What Is Cryptography?; Still Want to Be a Miner?; Do We Need Another Bitcoin?; 7 Nautiluscoin-0 to 1 Million in 60 Days; Creating the Coin; Did It Work?…”
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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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Atlas of minimally invasive surgery for lung and esophageal cancer

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Fork Algebras in Algebra, Logic and Computer Science. by Frias, Marcelo Fabián

Table of Contents: “…7.5 A Methodology for Program Construction7.6 Examples; 7.6.1 First Example; 7.6.1.1 Finding the Minimum Element in a List; 7.6.1.2 Finding the Minimum Common Ancestor; 7.6.2 Second Example; 7.6.2.1 Finding the Contiguous Sublists of Maximum Sum; 7.6.2.2 Finding the Longest Plateau; 7.7 A D & C Algorithm for MAXSTA; 7.8 Comparison with Previous Work; Bibliography; Index.…”
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Negative binomial regression by Hilbe, Joseph M., 1944-

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A Primer on Machine Learning Applications in Civil Engineering by Deka, Paresh Chandra

Table of Contents: “…Cover -- Half Title -- Title Page -- Copyright Page -- Dedication -- Contents -- Preface -- Acknowledgments -- A Primer on Machine Learning Applications in Civil Engineering -- Author -- 1: Introduction -- 1.1 Machine Learning -- 1.2 Learning from Data -- 1.3 Research in Machine Learning: Recent Progress -- 1.4 Artificial Neural Networks -- 1.5 Fuzzy Logic (FL) -- 1.6 Genetic Algorithms -- 1.7 Support Vector Machine (SVM) -- 1.8 Hybrid Approach (HA) -- Bibliography -- 2: Artificial Neural Networks -- 2.1 Introduction to Fundamental Concepts and Terminologies -- 2.2 Evolution of Neural Networks -- 2.3 Models of ANN -- 2.4 McCulloch-Pitts Model -- 2.5 Hebb Network -- 2.6 Summary -- 2.7 Supervised Learning Network -- 2.7.1 Perceptron Network -- 2.7.2 Adaptive Linear Neuron -- 2.7.3 Back-Propagation Network -- 2.7.4 Radial Basis Function Network -- 2.7.5 Generalized Regression Neural Networks -- 2.7.6 Summary -- 2.8 Unsupervised Learning Networks -- 2.8.1 Introduction -- 2.8.2 Kohonen Self-Organizing Feature Maps -- 2.8.3 Counter Propagation Network -- 2.8.4 Adaptive Resonance Theory Network -- 2.8.5 Summary -- 2.9 Special Networks -- 2.9.1 Introduction -- 2.9.2 Gaussian Machine -- 2.9.3 Cauchy Machine -- 2.9.4 Probabilistic Neural Network -- 2.9.5 Cascade Correlation Neural Network -- 2.9.6 Cognitive Network -- 2.9.7 Cellular Neural Network -- 2.9.8 Optical Neural Network -- 2.9.9 Summary -- 2.10 Working Principle of ANN -- 2.10.1 Introduction -- 2.10.2 Types of Activation Function -- 2.10.3 ANN Architecture -- 2.10.4 Learning Process -- 2.10.5 Feed-Forward Back Propagation -- 2.10.6 Strengths of ANN -- 2.10.7 Weaknesses of ANN -- 2.10.8 Working of the Network -- 2.10.9 Summary -- Bibliography -- 3: Fuzzy Logic -- 3.1 Introduction to Classical Sets and Fuzzy Sets -- 3.1.1 Classical Sets -- 3.1.2 Fuzzy Sets -- 3.1.3 Summary.…”
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Poetry and Mind : Tractatus Poetico-Philosophicus by Dubreuil, Laurent

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Lung cancer and imaging

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Artificial Intelligence in Wireless Communications. by Rondeau, Thomas W.

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DEEP LEARNING FOR HEALTHCARE DECISION MAKING.

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Microwave and millimeter wave circuits and systems : emerging design, technologies, and applications

Table of Contents: “…1.1.7 MBF Model -- the Memoryless PA Behavioural Model of ChoiceAcknowledgements; References; 2 Artificial Neural Network in Microwave Cavity Filter Tuning; 2.1 Introduction; 2.2 Artificial Neural Networks Filter Tuning; 2.2.1 The Inverse Model of the Filter; 2.2.2 Sequential Method; 2.2.3 Parallel Method; 2.2.4 Discussion on the ANN's Input Data; 2.3 Practical Implementation -- Tuning Experiments; 2.3.1 Sequential Method; 2.3.2 Parallel Method; 2.4 Influence of the Filter Characteristic Domain on Algorithm Efficiency; 2.5 Robots in the Microwave Filter Tuning; 2.6 Conclusions; Acknowledgement…”
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Biomedical image analysis recipes in MATLAB : for life scientists and engineers by Reyes-Aldasoro, Constantino Carlos

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D Cookbook. by D. Ruppe, Adam

Table of Contents: “…Performing type conversionsFinding the largest files in a directory; Creating a network client and server; Using Base64 to create a data URI; Generating random numbers; Normalizing a string and performing Unicode comparisons; Searching with regular expressions; Writing a digest utility; Using std.zlib compression; Using the std.json module; Chapter 3: Ranges; Introduction; Using ranges when implementing an algorithm; Creating an input range; Creating an output range; Creating a higher-order range; Putting a range interface on a collection; Creating an input range over a tree structure…”
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Towards Cognitive Autonomous Networks : Network Management Automation for 5G and Beyond. by Mwanje, Stephen S.

Table of Contents: “…Cover -- Title Page -- Copyright -- Contents -- List of Contributors -- Foreword I -- Foreword II -- Preface -- Chapter 1 The Need for Cognitive Autonomy in Communication Networks -- 1.1 Complexity in Communication Networks -- 1.1.1 The Network as a Graph -- 1.1.2 Planes, Layers, and Cross-Functional Design -- 1.1.3 New Network Technology -- 5G -- 1.1.4 Processes, Algorithms, and Automation -- 1.1.5 Network State Changes and Transitions -- 1.1.6 Multi-RAT Deployments -- 1.2 Cognition in Network Management Automation -- 1.2.1 Business, Service and Network Management Systems…”
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Contemporary Ergonomics 1998. by Hanson, Margaret A.

Table of Contents: “…Development of a questionnaire to measure attitudes towards virtual reality -- Orientation of blind users on the World Wide Web -- F̃lash, splash and crash:̃ Human factors and the implementation of innovative Web technologies -- Determining ergonomic factors in stress from work demands of nurses -- A risk assessment and control cycle approach to managing workplace stress -- Teleworking: Assessing the risks -- Evaluating teleworking -- case study -- Team organisational mental models: an integrative framework for research -- The impact of ITT on virtual team working in the European automotive industry -- The effect of communication processes upon workers and job efficiency -- A case study of job design in a steel plant -- The effects of age and habitual physical activity on the adjustment to nocturnal shiftwork -- Job design for university technicians: work activity and allocation of function -- Allocation of functions and manufacturing job design based on knowledge requirements -- The need to specify cognition within system requirements -- Analysis of complex communication tasks -- Health and safety as the basis for specifying information systems design requirements -- Cognitive algorithms -- Rapid prototyping in foam of 3D anthropometric computer models in functional postures -- The use of high and low level prototyping methods for product user interfaces -- Creative collaboration in engineering design teams -- Pleasure and product semantics -- A survey of usability practice and needs in Europe -- Cultural influence in usability assessment -- Interface display designs based on operator knowledge requirements -- Understanding what makes icons effective: how subjective ratings can inform design -- Representing uncertainty in decision support systems: the state of the art.…”
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Pediatric incontinence : evaluation and clinical management

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Discovering knowledge in data : an introduction to data mining by Larose, Daniel T.

Table of Contents: “…DISCOVERING KNOWLEDGE IN DATA -- Contents -- Preface -- 1 An Introduction to Data Mining -- 1.1 What is Data Mining? -- 1.2 Wanted: Data Miners -- 1.3 The Need for Human Direction of Data Mining -- 1.4 The Cross-Industry Standard Practice for Data Mining -- 1.4.1 Crisp-DM: The Six Phases -- 1.5 Fallacies of Data Mining -- 1.6 What Tasks Can Data Mining Accomplish? …”
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Clinical simulation : operations, engineering and management

Table of Contents: “…; 3.5 The Systems Approach to Training; 3.6 Defining the Performance Requirement; 3.7 Cost Versus Value Added; 3.8 Operations Cost; 3.9 Standardization: What is it, and who Wants it?; 3.10 Patients as Training Conditions; 3.11 Equipment as Training Conditions; 3.12 Increase in Training System Cost; 3.13 You as the Leader-Manager; 3.14 Conclusion; Endnotes; Topic II What's In It For Me.…”
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