Search Results - (((((((kant OR wkant) OR mantis) OR wien) OR cantor) OR anne) OR shape) OR hints) algorithms.

Danforth's obstetrics and gynecology.

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Decision Intelligence for Dummies by Baker, Pamela

Table of Contents: “…Preventing Wrong Influences from Affecting Decisions -- Bad influences in AI and analytics -- The blame game -- Ugly politics and happy influencers -- Risk Factors in Decision Intelligence -- DI and Hyperautomation -- Part 5 The Part of Tens -- Chapter 17 Ten Steps to Setting Up a Smart Decision -- Check Your Data Source -- Track Your Data Lineage -- Know Your Tools -- Use Automated Visualizations -- Impact = Decision -- Do Reality Checks -- Limit Your Assumptions -- Think Like a Science Teacher -- Solve for Missing Data -- Partial versus incomplete data -- Clues and missing answers -- Take Two Perspectives and Call Me in the Morning -- Chapter 18 Bias In, Bias Out (and Other Pitfalls) -- A Pitfalls Overview -- Relying on Racist Algorithms -- Following a Flawed Model for Repeat Offenders -- Using A Sexist Hiring Algorithm -- Redlining Loans -- Leaning on Irrelevant Information -- Falling Victim to Framing Foibles -- Being Overconfident -- Lulled by Percentages -- Dismissing with Prejudice -- Index -- EULA.…”
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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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Nonlinear science and complexity

Table of Contents: “…Bruzón -- Applying a new algorithm to derive nonclassical symmetries / M.S. …”
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Evolutionary Robust Control. by Feyel, Philippe

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Stirling Cycle Engines : Inner Workings and Design. by Organ, Allan J.

Table of Contents: “…-- 3.6 The way forward -- 4 Equivalence conditions for volume variations -- 4.1 Kinematic configuration -- 4.2 'Additional' dead space -- 4.3 Net swept volume -- 5 The optimum versus optimization -- 5.1 An engine from Turkey rocks the boat -- 5.2 ... and an engine from Duxford -- 5.3 Schmidt on Schmidt -- 5.3.1 Volumetric compression ratio rv -- 5.3.2 Indicator diagram shape -- 5.3.3 More from the re-worked Schmidt analysis -- 5.4 Crank-slider mechanism again -- 5.5 Implications for engine design in general -- 6 Steady-flow heat transfer correlations -- 6.1 Turbulent -- or turbulent? …”
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Mechanical and Electronics Engineering : proceedings of the International Conference on ICMEE 2009, Chennai, India, 24-26 July 2009

Table of Contents: “…Shafie -- The investigation of input shaping with different polarities for anti-sway control of a gantry crane system / Mohd. …”
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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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Flood hazard identification and mitigation in semi- and arid environments

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Sigma-Delta Converters. by De la Rosa, José M.

Table of Contents: “…4.5.2 Effect of Finite Slew Rate on CT-Ms 133 -- 4.6 Sources of Distortion in CT-Ms 134 -- 4.6.1 Nonlinearities in the Front-end Integrator 134 -- 4.6.2 Intersymbol Interference in the Feedback DAC 136 -- 4.7 Circuit Noise in CT-Ms 137 -- 4.7.1 Noise Analysis Considering NRZ Feedback DACs 137 -- 4.7.2 Noise Analysis Considering SC Feedback DACs 139 -- 4.8 Clock Jitter in CT-Ms 140 -- 4.8.1 Jitter in Return-to-zero DACs 141 -- 4.8.2 Jitter in Non-return-to-zero DACs 142 -- 4.8.3 Jitter in Switched-capacitor DACs 144 -- 4.8.4 Lingering Effect of Clock Jitter Error 145 -- 4.8.5 Reducing the Effect of Clock Jitter with FIR and Sine-shaped DACs 147 -- 4.9 Excess Loop Delay in CT-Ms 149 -- 4.9.1 Intuitive Analysis of ELD 149 -- 4.9.2 Analysis of ELD based on Impulse-invariant DT-CT Transformation 151 -- 4.9.3 Alternative ELD Compensation Techniques 154 -- 4.10 Quantizer Metastability in CT-Ms 155 -- 4.11 Summary 159 -- References 160 -- 5 Behavioral Modeling and High-level Simulation 165 -- 5.1 Systematic Design Methodology of Modulators 165 -- 5.1.1 System Partitioning and Abstraction Levels 167 -- 5.1.2 Sizing Process 167 -- 5.2 Simulation Approaches for the High-level Evaluation of Ms 169 -- 5.2.1 Alternatives to Transistor-level Simulation 169 -- 5.2.2 Event-driven Behavioral Simulation Technique 171 -- 5.2.3 Programming Languages and Behavioral Modeling Platforms 172 -- 5.3 Implementing M Behavioral Models 173 -- 5.3.1 From Circuit Analysis to Computational Algorithms 173 -- 5.3.2 Time-domain versus Frequency-domain Behavioral Models 175 -- 5.3.3 Implementing Time-domain Behavioral Models in MATLAB 178 -- 5.3.4 Building Time-domain Behavioral Models as SIMULINK C-MEX S-functions 182 -- 5.4 Efficient Behavioral Modeling of M Building Blocks using C-MEX S-functions 188 -- 5.4.1 Modeling of SC Integrators using S-functions 188 -- 5.4.1.1 Capacitor Mismatch and Nonlinearity 190.…”
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Computational fluid-structure interaction : methods and applications by Bazilevs, Yuri

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Polymer extrusion

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Visual Inspection Technology in the Hard Disc Drive Industry. by Muneesawang, Paisarn

Table of Contents: “…Introduction / Suchart Yammen / Paisarn Muneesawang -- 1.2. Algorithm for corrosion detection / Suchart Yammen / Paisarn Muneesawang -- 1.2.1. …”
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Public safety networks from LTE to 5G by Yarali, Abdulrahman

Table of Contents: “…9.2.5 Flexibility 164 -- 9.3 Starting Public Safety Implementation Versus Waiting for 5G 165 -- 9.4 5GVersus 4G Public Safety Services 166 -- 9.4.1 Video Surveillance 167 -- 9.4.2 Computer-Driven Augmented Reality (AR) Helmet 167 -- 9.5 How 5GWill Shape Emergency Services 167 -- 9.6 4G LTE Defined Public Safety Content in 5G 168 -- 9.7 The Linkage Between 4G-5G Evolution and the Spectrum for Public Safety 168 -- 9.8 Conclusion 168 -- References 168 -- 10 Fifth Generation (5G) Cellular Technology 171 -- 10.1 Introduction 171 -- 10.2 Background Information on Cellular Network Generations 172 -- 10.2.1 Evolution of Mobile Technologies 172 -- 10.2.1.1 First Generation (1G) 172 -- 10.2.1.2 Second Generation (2G) Mobile Network 172 -- 10.2.1.3 Third Generation (3G) Mobile Network 172 -- 10.2.1.4 Fourth Generation (4G) Mobile Network 173 -- 10.2.1.5 Fifth Generation (5G) 173 -- 10.3 Fifth Generation (5G) and the Network of Tomorrow 174 -- 10.3.1 5G Network Architecture 176 -- 10.3.2 Wireless Communication Technologies for 5G 177 -- 10.3.2.1 Massive MIMO 177 -- 10.3.2.2 Spatial Modulation 179 -- 10.3.2.3 Machine to Machine Communication (M2M) 179 -- 10.3.2.4 Visible Light Communication (VLC) 180 -- 10.3.2.5 Green Communications 180 -- 10.3.3 5G System Environment 180 -- 10.3.4 Devices Used in 5G Technology 181 -- 10.3.5 Market Standardization and Adoption of 5G Technology 181 -- 10.3.6 Security Standardization of Cloud Applications 183 -- 10.3.7 The Global ICT Standardization Forum for India (GISFI) 184 -- 10.3.8 Energy Efficiency Enhancements 184 -- 10.3.9 Virtualization in the 5G Cellular Network 185 -- 10.3.10 Key Issues in the Development Process 185 -- 10.3.10.1 Challenges of Heterogeneous Networks 186 -- 10.3.10.2 Challenges Caused by Massive MIMO Technology 186 -- 10.3.10.3 Big Data Problem 186 -- 10.3.10.4 Shared Spectrum 186 -- 10.4 Conclusion 187 -- References 187 -- 11 Issues and Challenges of 4G and 5G for PS 189 -- 11.1 Introduction 189 -- 11.2 4G and 5GWireless Connections 190.…”
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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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Queer Data Studies. by Keilty, Patrick

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Pink 2.0 : encoding queer cinema on the internet by Tsika, Noah, 1983-

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Primary surplus behavior and risks to fiscal sustainability in emerging market countries : a "fan-chart" approach by Celasun, Oya, Debrun, Xavier, Ostry, Jonathan D. (Jonathan David), 1962-

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Power system monitoring and control by Bevrani, Hassan

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