Search Results - (((((((ant OR wants) OR semantic) OR kind) OR cantor) OR anne) OR plane) OR hints) algorithms.

Deep learning for dummies by Mueller, John, 1958-, Massaron, Luca

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Robust and error-free geometric computing by Eberly, Dave

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QoS in integrated 3G networks by Lloyd-Evans, Robert

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Fundamentals of Fluid Power Control. by Watton, John

Table of Contents: “…Control-Volume Flow Continuity -- PRV Flow -- Force Balance at the Spindle -- 5.13.3 Frequency Response from a Linearized Transfer Function Analysis -- 5.14 Servovalve Dynamics -- First-Stage, Armature, and Flapper-Nozzle -- Flapper-Nozzle and Resistance Bridge Flow Characteristic -- Force Balance at the Spool -- 5.15 An Open-Loop Servovalve-Motor Drive with Line Dynamics Modeled by Lumped Approximations -- Servovalve, Dynamics Included, Underlapped Spool -- Lines, Laminar Mean Flow, Two Lump Approximations per Line, Negligible Motor Internal Volume -- Motor Flow and Torque Equations -- 5.16 Transmission Line Dynamics -- 5.16.1 Introduction -- Servovalve-Cylinder with Short Lines and Significant Actuator Volumes -- Servovalve-Motor with Long Lines and Negligible Actuator Volumes -- 5.16.2 Lossless Line Model for Z and Y -- 5.16.3 Average and Distributed Line Friction Models for Z and Y -- 5.16.4 Frequency-Domain Analysis -- 5.16.5 Servovalve-Reflected Linearized Coefficients -- 5.16.6 Modeling Systems with Nonlossless Transmission Lines, the Modal Analysis Method -- 5.16.7 Modal Analysis Applied to a Servovalve-Motor Open-Loop Drive -- 5.17 The State-Space Method for Linear Systems Modeling -- 5.17.1 Modeling Principles -- 5.17.2 Some Further Aspects of the Time-Domain Solution -- 5.17.3 The Transfer Function Concept in State Space -- 5.18 Data-Based Dynamic Modeling -- 5.18.1 Introduction -- 5.18.2 Time-Series Modeling -- 5.18.3 The Group Method of Data Handling (GMDH) Algorithm -- 5.18.4 Artificial Neural Networks -- 5.18.5 A Comparison of Time-Series, GMDH, and ANN Modeling of a Second-Order Dynamic System -- 5.18.6 Time-Series Modeling of a Position Control System -- 5.18.7 Time-Series Modeling for Fault Diagnosis -- 5.18.8 Time-Series Modeling of a Proportional PRV -- 5.18.9 GMDH Modeling of a Nitrogen-Filled Accumulator.…”
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Thermal Management of Electronics : an Experimental Approach Using Phase-Change-Based Materials in Composite Heat Sinks. by Baby, Rajesh

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Acoustic emission and durability of composite materials by Godin, Nathalie, Reynaud, Pascal, Fantozzi, G.

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Nano-Biomedical Engineering 2009 : Proceedings of the Tohoku University Global Centre of Excellence Programme Global Nano-Biomedical Engineering Education and Research Network Cent...

Table of Contents: “…Development of the various kinds of artificial organs and clinical application of the new diagnosis tool / Tomoyuki Yambe. …”
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Hands-On Deep Learning with TensorFlow. by Boxel, Dan Van

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XML for DB2 information integration

Table of Contents: “…-- 3.4 Creating an XML schema from a database schema -- 3.4.1 The algorithm.…”
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Danforth's obstetrics and gynecology.

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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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Artificial intelligence and data mining approaches in security frameworks

Table of Contents: “…87 -- 5.1.2 Purpose of Spamming 88 -- 5.1.3 Spam Filters Inputs and Outputs 88 -- 5.2 Content-Based Spam Filtering Techniques 89 -- 5.2.1 Previous Likeness–Based Filters 89 -- 5.2.2 Case-Based Reasoning Filters 89 -- 5.2.3 Ontology-Based E-Mail Filters 90 -- 5.2.4 Machine-Learning Models 90 -- 5.2.4.1 Supervised Learning 90 -- 5.2.4.2 Unsupervised Learning 90 -- 5.2.4.3 Reinforcement Learning 91 -- 5.3 Machine Learning–Based Filtering 91 -- 5.3.1 Linear Classifiers 91 -- 5.3.2 Naïve Bayes Filtering 92 -- 5.3.3 Support Vector Machines 94 -- 5.3.4 Neural Networks and Fuzzy Logics–Based Filtering 94 -- 5.4 Performance Analysis 97 -- 5.5 Conclusion 97 -- References 98 -- 6 Artificial Intelligence in the Cyber Security Environment 101 Jaya Jain -- 6.1 Introduction 102 -- 6.2 Digital Protection and Security Correspondences Arrangements 104 -- 6.2.1 Operation Safety and Event Response 105 -- 6.2.2 AI2 105 -- 6.2.2.1 CylanceProtect 105 -- 6.3 Black Tracking 106 -- 6.3.1 Web Security 107 -- 6.3.1.1 Amazon Macie 108 -- 6.4 Spark Cognition Deep Military 110 -- 6.5 The Process of Detecting Threats 111 -- 6.6 Vectra Cognito Networks 112 -- 6.7 Conclusion 115 -- References 115 -- 7 Privacy in Multi-Tenancy Frameworks Using AI 119 Shweta Solanki -- 7.1 Introduction 119 -- 7.2 Framework of Multi-Tenancy 120 -- 7.3 Privacy and Security in Multi-Tenant Base System Using AI 122 -- 7.4 Related Work 125 -- 7.5 Conclusion 125 -- References 126 -- 8 Biometric Facial Detection and Recognition Based on ILPB and SVM 129 Shubhi Srivastava, Ankit Kumar and Shiv Prakash -- 8.1 Introduction 129 -- 8.1.1 Biometric 131 -- 8.1.2 Categories of Biometric 131 -- 8.1.2.1 Advantages of Biometric 132 -- 8.1.3 Significance and Scope 132 -- 8.1.4 Biometric Face Recognition 132 -- 8.1.5 Related Work 136 -- 8.1.6 Main Contribution 136 -- 8.1.7 Novelty Discussion 137 -- 8.2 The Proposed Methodolgy 139 -- 8.2.1 Face Detection Using Haar Algorithm 139 -- 8.2.2 Feature Extraction Using ILBP 141 -- 8.2.3 Dataset 143 -- 8.2.4 Classification Using SVM 143 -- 8.3 Experimental Results 145 -- 8.3.1 Face Detection 146 -- 8.3.2 Feature Extraction 146 -- 8.3.3 Recognize Face Image 147 -- 8.4 Conclusion 151 -- References 152 -- 9 Intelligent Robot for Automatic Detection of Defects in Pre-Stressed Multi-Strand Wires and Medical Gas Pipe Line System Using ANN and IoT 155 S K Rajesh Kanna, O. …”
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Android Sensor Programming By Example. by Nagpal, Varun

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Liquid surfaces and interfaces : synchrotron X-ray methods by Pershan, Peter S., 1934-

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Machine learning with R quick start guide : a beginner's guide to implementing machine learning techniques from scratch using R 3.5 by Pastor Sanz, Iván

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Introduction to Infrared and Electro-Optical Systems by Driggers, Ronald G.

Table of Contents: “…7.9 Resolution -- 7.10 Aperture Stop, Pupils, and Rays -- 7.11 f-Number and Numerical Aperture -- 7.12 Telescopes and Angular Magnification -- 7.13 MTF -- 7.14 Aberrations -- 7.15 Optical Materials -- 7.16 Cold Stop and Cold Shield -- 7.17 A Typical Optical System -- 7.18 Diffraction Blur -- References -- Chapter 8 Detectors -- 8.1 Types of Detectors -- 8.1.1 Photon Detectors -- 8.1.2 Photoconductors -- 8.1.3 Photovoltaic -- 8.1.4 Photoemissive -- 8.1.5 Thermal Detectors -- 8.1.6 Bolometers -- 8.1.7 Pyroelectric Detectors -- 8.2 CCD and ROIC -- 8.2.1 CCD -- 8.2.2 Multiplexed Analog Readout -- 8.2.3 Column ADC ROIC or D-ROIC -- 8.3 Detector Sensitivity Analysis -- 8.3.1 Quantum Efficiency -- 8.3.2 Responsivity -- 8.3.3 Sensitivity -- 8.3.4 Detector Angular Subtense -- 8.3.5 FPA and Detector Noise (Including Detector 1/f Noise) -- 8.3.6 Dark Current and Rule'07 -- 8.3.7 1/f Noise -- 8.3.8 Photon Shot Noise -- 8.3.9 FPA and ROIC Noise (Including Fixed Pattern Noise) in Staring Systems -- 8.3.10 BLIP -- 8.4 EO Systems: Staring and Scanning Configurations -- 8.4.1 Raster Scan Systems -- 8.4.2 Linear Scan and TDI -- 8.4.3 Staring Systems: Focal Plane Arrays -- 8.5 Detector Transfer Functions -- 8.6 EO Detectors: Materials and Technology -- 8.6.1 MWIR and LWIR Photon Detectors -- 8.6.2 Far Infrared: VLWIR -- 8.6.3 Uncooled Bolometer -- 8.6.4 Visible and NIR -- 8.7 New and Emerging Infrared Detector Technology -- 8.7.1 Ultra-Large-Format Arrays and Small Pitch -- 8.7.2 Dual-Band Detectors (Third Generation) -- 8.7.2 Dual-Band Detectors (Third Generation) -- 8.7.3 Direct Bond Hybridization -- 8.7.4 Advanced ROIC Technology and Digital Pixel -- 8.7.5 Next Generation Imagers -- 8.7.6 Avalanche Photodiodes, Laser Range Gating, and Active and PassiveDetectors -- References -- Chapter 9 Electronics -- 9.1 Detector Circuits.…”
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Creating E-Learning Games with Unity. by Horachek, David

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C# 7 and .NET Core 2.0 High Performance : Build highly performant, multi-threaded, and concurrent applications using C# 7 and .NET Core 2.0. by Mehboob Ahmed Khan, Ovais

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Haecceities. by Strayer, Jeffrey

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