Search Results - (((((((want OR wantsa) OR semantic) OR when) OR cantor) OR anne) OR blaney) OR hints) algorithms.

Techniques and key points for endoscopic cranial base reconstruction by Pinheiro-Neto, Carlos, Peris-Celda, Maria

Table of Contents: “…Techniques and Key Points for Endoscopic Cranial Base Reconstruction -- MedOne Access Information -- Tittle Page -- Copyright -- Dedication -- Contents -- Videos -- Foreword -- Preface -- Acknowledgments -- Contributors -- Section I Introduction -- 1 Principles of Endoscopic Cranial Base Reconstruction -- 1.1 Introduction -- 1.2 Fundamentals of Endonasal Reconstruction -- 1.3 Repair Options -- 1.4 Vascularized Reconstruction -- 1.5 Reconstruction Decalogue -- 2 Operative Planning and Treatment Algorithm -- 2.1 Introduction -- 2.2 Preoperative Planning -- 2.3 Perioperative and Intraoperative Considerations -- 2.4 Treatment Algorithm -- 2.5 Postoperative Considerations -- 2.5.1 Inpatient Care -- 2.5.2 Outpatient Care -- Section II Nasoseptal Flap and Variations -- 3 Standard Nasoseptal Flap -- 3.1 Anatomy -- 3.2 Fundamentals -- 3.3 Indications -- 3.4 Limitations -- 3.5 Surgical Technique -- 3.5.1 Harvest -- 3.5.2 Reconstruction -- 3.6 Postoperative Care -- 3.7 Managing Complications -- 4 Rescue Nasoseptal Flap -- 4.1 Fundamentals -- 4.2 Indications -- 4.3 Limitations -- 4.4 Surgical Technique -- 4.5 Postoperative Care -- 4.6 Complications -- 5 Extended Nasoseptal Flap -- 5.1 Fundamentals -- 5.2 Indications -- 5.3 Limitations -- 5.4 Surgical Technique -- 5.4.1 Harvest -- 5.4.2 Reconstruction -- 5.5 Postoperative Care -- 5.5.1 One-Week Postoperative Visit -- 5.5.2 One-Month Postoperative Visit -- 5.5.3 Four-Month Postoperative Visit -- 5.6 Complications -- 6 Nasoseptal Flap Pedicle Release -- 6.1 Anatomy -- 6.2 Fundamentals -- 6.3 Indications -- 6.4 Limitations -- 6.5 Surgical Technique -- 6.5.1 360-Degree Bone Removal around the SPA Foramen (Osseous Release) -- 6.5.2 Ipsilateral Transpterygoid Approach -- 6.5.3 360-Degree Circumferential Incision in the Periosteum of the PPF around the SPA (Periosteal Release) -- 6.6 Postoperative Care.…”
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RSSDI Diabetes update 2018

Table of Contents: “…-- Chapter 42: Etiopathogenesis and Management of Diabetic Heart Failure -- Chapter 43: Diabetes and Stroke -- Chapter 44: Cellular Mechanism of Atherosclerosis in Diabetes Mellitus -- Chapter 45: Nondiabetic Ocular Complications in Diabetes -- Chapter 46: Nondiabetic Kidney Disease in Patients with Type 2 Diabetes Mellitus: When to Suspect?.…”
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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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IBM TotalStorage : SAN product, design, and optimization guide

Table of Contents: “…-- 3.7.6 What happens when there is more than one shortest path? -- 3.7.7 Can FSPF cause any problems? …”
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Big Data Analytics with R. by Walkowiak, Simon

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Credit securitizations and derivatives : challenges for the global markets

Table of Contents: “…Market Credit Risk Pricing -- Regulation -- Developments in Structured Finance Markets -- Impairments of Asset-Backed Securities and Outstanding Ratings -- Issuance of Asset-backed Securities and Outstanding Volume -- Global CDO Issuance and Outstanding Volume -- PART II CREDIT PORTFOLIO RISK MEASUREMENT -- Mortgage Credit Risk -- Five C's of Credit and Mortgage Credit Risk -- Determinants of Mortgage Default, Loss Given Default and Exposure at Default -- Determinants of Mortgage Default -- Determinants of Mortgage LGD -- Determinants of Mortgage EAD -- Modeling Methods for Default, LGD and EAD -- Model Risk Management -- Credit Portfolio Correlations and Uncertainty -- Introduction -- Gaussian and Semi-Gaussian Single Risk Factor Model -- Individual and Simultaneous Confidence Bounds and Intervals -- Confidence Intervals for Asset Correlations -- Confidence Intervals for Default and Survival Time Correlations -- Confidence Intervals for Default Correlations -- Confidence Intervals for Survival Time Correlations -- Credit Portfolio Correlations with Dynamic Leverage Ratios -- The Hui et al. (2007) Model -- The Method of Images for Constant Coefficients -- The Method of Images for Time-Varying Coefficients -- Modelling Default Correlations in a Two-Firm Model -- Default Correlations -- A Two-Firm Model with Dynamic Leverage Ratios -- Method of Images for Constant Coefficients -- Method of Images for Time-Varying Coefficients -- Alternative Methodologies for General Values -- Numerical Results -- Accuracy -- The Impact of Correlation between Two Firms -- The Impact of Different Credit Quality Paired Firms -- The Impact of Volatilities -- The Impact of Drift Levels -- The Impact of Initial Value of Leverage Ratio Levels -- Impact of Correlation between Firms and Interest Rates -- The Price of Credit-Linked Notes -- A Hierarchical Model of Tail-Dependent Asset Returns -- The Variance Compound Gamma Model -- Multivariate Process for Logarithmic Asset Returns -- Dependence Structure -- Sampling -- Copula Properties -- An Application Example -- Portfolio Setup -- Test Portfolios -- Parameter Setup -- Simulation Results -- Importance Sampling Algorithm -- Conclusions -- Appendix A: The VCG Probability Distribution Function Appendix B: HAC Representation for the VCG Framework -- Monte Carlo Methods for Portfolio Credit Risk -- Modeling Credit Portfolio Losses -- Risk Measures -- Modeling Dependency -- Estimating Risk Measures via Monte Carlo -- Crude Monte Carlo Estimators -- Importance Sampling -- Specific Models -- The Bernoulli Mixture Model -- Factor Models -- Copula Models -- Intensity Models -- An Example Point Process Model -- Appendix A: A Primer on Rare-event Simulation -- Efficiency -- Importance Sampling -- The Choice of g -- Adaptive Importance Sampling -- Importance Sampling for Stochastic Processes -- Credit Portfolio Risk and Diversification -- Introduction -- Model Setup -- Independent Asset Values -- Correlated Asset Values -- Large Portfolio Limit -- Correlated Diffusion -- Correlated GARCH Process -- Applications of the Structural Recovery Rate -- Conclusions -- PART III CREDIT PORTFOLIO RISK SECURITIZATION AND TRANCHING -- Differences in Tranching Methods: Some Results and Implications -- Defining a Tranche -- The Mathematics of Tranching -- PD-based Tranching -- EL-based Tranching -- The EL of a Tranche Necessarily Increases When Either the Attachment Point or the Detachment Point is Decreased -- Upper Bound on Tranche Expected LGD (LGDt) Assumption Given EL-based Tranches -- Skipping of Some Tranches in the EL-based Approach -- Global Structured Finance Rating -- Asset-Backed Securities -- The ABS Structure for the Experiment -- Cash Flow Modeling -- Modeling and Simulating Defaults -- Expected Loss Rating -- Global Sensitivity Analysis -- Elementary Effects -- Variance-based Method -- Global Sensitivity Analysis Results -- Uncertainty Analysis -- Sensitivity Analysis -- Global Rating -- PART IV CREDIT DERIVATIVES -- Analytic Dynamic Factor Copula Model -- Pricing Equations -- One-factor Copula Model -- Multi-period Factor Copula Models -- Calibration -- Dynamic Modeling of Credit Derivatives -- General Model Choice -- Modeling Option Prices -- Modeling Credit Risk -- Portfolio Credit Derivatives -- Modeling Asset Dynamics -- The Market Model -- The Asset-value Model -- Empirical Analysis -- Elementary Data -- Implied Dividends -- Market Dynamics -- Asset Value Model -- Tranche Pricing -- Out-of-time Application -- Pricing and Calibration in Market Models -- Basic notions -- The model -- Modeling Assumptions -- Absence of Arbitrage -- An affine specification -- Pricing -- Calibration -- Calibration Procedure -- Calibration Results -- Appendix A: Computations -- Counterparty Credit Risk and Clearing of Derivatives -- From the Perspective of an Industrial Corporate with a Focus on Commodity Markets -- Credit exposures in commodity business -- Settlement Exposure -- Performance Exposure -- Example of Fixed Price Deal with Performance Exposure -- Example of a Floating Price Deal with Performance Exposure -- General Remarks on Credit Exposure Concepts -- Ex Ante exposure-reducing techniques -- Payment Terms -- Material Adverse Change Clauses -- Master Agreements -- Netting -- Margining -- Close Out Exposure and Threshold -- Ex Ante risk-reducing techniques -- Credit Enhancements in General -- Parent Company Guarantees -- Letters of Credit -- Credit Insurance -- Clearing via a Central Counterparty -- Ex Post risk-reducing techniques -- Factoring -- Novation -- Risk-reducing Trades -- Hedging with CDS -- Hedging with Contingent-CDS -- Hedging with Puts on Equity -- Ex Post work out considerations -- Practical credit risk management and pricing Peculiarities of commodity markets -- Peculiarities of commodity related credit portfolios -- Credit Risk Capital for a commodity related portfolio measured with an extension of CreditMetrics -- CreditRisk+ study: applied to a commodity related credit portfolio -- CDS Industrial Sector Indices, Credit and Liquidity Risk -- The Data -- Methodology and Results -- Preliminary Analysis -- Common Factor Analysis -- Stability of Relations -- Risk Transfer and Pricing of Illiquid Assets with Loan CDS -- Shipping Market -- Loan Credit Default Swaps -- LCDS Pricing -- Modeling LCDS Under the Intensity-based Model -- Valuation Framework for LCDS -- The Structural Approach -- Credit Risk in Shipping Loans -- Valuation of LCDS on Shipping Loans -- Simulation Model -- Numerical Results -- Appendix A: Monte Carlo Parameterization PART V REGULATION -- Regulatory Capital Requirements for Securitizations -- Regulatory Approaches for Securitizations -- Ratings Based Approach (RBA) -- Supervisory Formula Approach (SFA) -- Standardized Approach (SA) -- Post-crisis Revisions to the Basel Framework -- Regulating OTC Derivatives -- The Wall Street Transparency and Accountability Part of the Dodd-Frank Act of 2010 -- Which Derivatives Will Be Affected? …”
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Insight into fuzzy modeling by Novák, Vilém, 1951-, Perfilieva, Irina, 1953-, Dvořák, Antonín (Mathematician)

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Statistics for business by Mariappan, Perumal

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Big data : concepts, technology and architecture by Balusamy, Balamurugan, R, Nandhini Abirami, Kadry, Seifedine, 1977-, Gandomi, Amir Hossein

Table of Contents: “…143</p> <p>5.2.3HDFS Architecture. 143</p> <p>5.2.4HDFS Read/Write Operation. 146</p> <p>5.2.5Rack Awareness. 148</p> <p>5.2.6Features of HDFS. 149</p> <p>5.2.6.1Cost-effective. 149</p> <p>5.2.6.2Distributed storage. 149</p> <p>5.2.6.3Data Replication. 149</p> <p>5.3 Hadoop Computation. 149</p> <p>5.3.1MapReduce. 149</p> <p>5.3.1.1Mapper. 151</p> <p>5.3.1.2Combiner. 151</p> <p>5.3.1.3 Reducer. 152</p> <p>5.3.1.4 JobTracker and TaskTracker. 153</p> <p>5.3.2 MapReduce Input Formats. 154</p> <p>5.3.3 MapReduce Example. 156</p> <p>5.3.4 MapReduce Processing. 157</p> <p>5.3.5 MapReduce Algorithm.. 160</p> <p>5.3.6 Limitations of MapReduce. 161</p> <p>5.4Hadoop 2.0. 161</p> <p>5.4.1Hadoop 1.0 limitations. 162</p> <p>5.4.2 Features of Hadoop 2.0. 163</p> <p>5.4.3 Yet Another Resource Negotiator (YARN). 164</p> <p>5.4.3 Core components of YARN.. 165</p> <p>5.4.3.1 ResourceManager. 165</p> <p>5.4.3.2 NodeManager. 166</p> <p>5.4.4 YARN Scheduler. 169</p> <p>5.4.4.1 <i>FIFO scheduler</i>. 169</p> <p>5.4.4.2 <i>Capacity Scheduler</i>. 170</p> <p>5.4.4.3 <i>Fair Scheduler</i>. 170</p> <p>5.4.5 Failures in YARN.. 171</p> <p>5.4.5.1ResourceManager failure. 171</p> <p>5.4.5.2 ApplicationMaster failure. 172</p> <p>5.4.5.3 NodeManagerFailure. 172</p> <p>5.4.5.4 Container Failure. 172</p> <p>5.3 HBASE. 173</p> <p>5.4 Apache Cassandra. 176</p> <p>5.5 SQOOP. 177</p> <p>5.6 Flume. 179</p> <p>5.6.1 Flume Architecture. 179</p> <p>5.6.1.1 Event. 180</p> <p>5.6.1.2 Agent. 180</p> <p>5.7 Apache Avro. 181</p> <p>5.8 Apache Pig. 182</p> <p>5.9 Apache Mahout. 183</p> <p>5.10 Apache Oozie. 183</p> <p>5.10.1 Oozie Workflow.. 184</p> <p>5.10.2 Oozie Coordinators. 186</p> <p>5.10.3 Oozie Bundles. 187</p> <p>5.11 Apache Hive. 187</p> <p>5.11 Apache Hive. 187</p> <p>Hive Architecture. 189</p> <p>Hadoop Distributions. 190</p> <p>Chapter 5refresher. 191</p> <p>Conceptual short questions with answers. 194</p> <p>Frequently asked Interview Questions. 199</p> <p>Chapter Objective. 200</p> <p>6.1 Terminologies of Big Data Analytics. 201</p> <p><i>Data Warehouse</i>. 201</p> <p><i>Business Intelligence</i>. 201</p> <p><i>Analytics</i>. 202</p> <p>6.2 Big Data Analytics. 202</p> <p>6.2.1 Descriptive Analytics. 204</p> <p>6.2.2 Diagnostic Analytics. 205</p> <p>6.2.3 Predictive Analytics. 205</p> <p>6.2.4 Prescriptive Analytics. 205</p> <p>6.3 Data Analytics Lifecycle. 207</p> <p>6.3.1 Business case evaluation and Identify the source data. 208</p> <p>6.3.2 Data preparation. 209</p> <p>6.3.3 Data Extraction and Transformation. 210</p> <p>6.3.4 Data Analysis and visualization. 211</p> <p>6.3.5 Analytics application. 212</p> <p>6.4 Big Data Analytics Techniques. 212</p> <p>6.4.1 Quantitative Analysis. 212</p> <p>6.4.3 Statistical analysis. 214</p> <p>6.4.3.1 A/B testing. 214</p> <p>6.4.3.2 Correlation. 215</p> <p>6.4.3.3 Regression. 218</p> <p>6.5 Semantic Analysis. 220</p> <p>6.5.1 Natural Language Processing. 220</p> <p>6.5.2 Text Analytics. 221</p> <p>6.7 Big Data Business Intelligence. 222</p> <p>6.7.1 Online Transaction Processing (OLTP). 223</p> <p>6.7.2 Online Analytical Processing (OLAP). 223</p> <p>6.7.3 Real-Time Analytics Platform (RTAP). 224</p> <p>6.6Big Data Real Time Analytics Processing. 225</p> <p>6.7 Enterprise Data Warehouse. 227</p> <p>Chapter 6 Refresher. 228</p> <p>Concept…”
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Disobedient Aesthetics : Surveillance, Bodies, Control by Stagliano, Anthony, 1973-

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Qualitative computing : a computational journey into nonlinearity by Chaitin-Chatelin, Françoise

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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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Formal languages, automata and numeration systems. 1, Introduction to combinatorics on words by Rigo, Michel

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Spread spectrum systems for GNSS and wireless communications by Holmes, Jack K. (Jack Kenneth), 1936-

Table of Contents: “…4.3.1 Convolutional Code Encoder Characterization -- 4.3.2 The Transfer Function of a Convolutional Code and the Free Distance -- 4.3.3 Decoding of Convolutional Codes -- 4.3.4 The Viterbi Algorithm -- 4.3.5 Error Probabilities for Viterbi Decoding of Convolutional Codes -- 4.3.6 Sequential Decoding of Convolutional Codes -- 4.3.7 Threshold Decoding of Convolutional Codes -- 4.3.8 Nonbinary Convolutional Codes -- 4.4 ITERATIVELY DECODED CODES -- 4.4.1 Turbo Codes -- 4.4.2 A Serial Concatenated Convolutional Code -- 4.4.3 Serial Concatenated Block Codes -- 4.4.4 Parallel Concatenated Block Codes -- 4.4.5 Low-Density Parity Check Codes -- 4.5 SELECTED RESULTS FOR SOME ERROR CORRECTION CODES -- 4.5.1 Bose, Chaudhuri, and Hocquenghem Codes -- 4.5.2 Reed-Solomon Codes -- 4.5.3 Convolutional Codes with Maximum Free Distance -- 4.5.4 Hard- and Soft-Decision FFH/MFSK with Repeat Coding BER Performance -- 4.6 SHANNON'S CAPACITY THEOREM, THE CHANNEL CODING THEOREM, AND BANDWIDTH EFFICIENCY -- 4.6.1 Shannon's Capacity Theorem -- 4.6.2 Channel Coding Theorem -- 4.6.3 Bandwidth Efficiency -- 4.7 APPLICATIONS OF ERROR CONTROL CODING -- 4.8 SUMMARY -- References -- Selected Bibliography -- Problems -- CHAPTER 5 Carrier Tracking Loops and Frequency Synthesizers -- 5.0 INTRODUCTION -- 5.1 TRACKING OF RESIDUAL CARRIER SIGNALS -- 5.2 PLL FOR TRACKING A RESIDUAL CARRIER COMPONENT -- 5.2.1 The Likelihood Function for Phase Estimation -- 5.2.2 The Maximum-Likelihood Estimation of Carrier Phase -- 5.2.3 Long Loops and Short Loops -- 5.2.4 The Stochastic Differential Equation of Operation -- 5.2.5 The Linear Model of the PLL with Noise -- 5.2.6 The Various Loop Filter Types -- 5.2.7 Transient Response of a Second-Order Loop -- 5.2.8 Steady State Tracking Error When the Phase Error Is Small -- 5.2.9 The Variance of the Linearized PLL Phase Error Due to Thermal Noise.…”
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Liquid surfaces and interfaces : synchrotron X-ray methods by Pershan, Peter S., 1934-

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Optimal learning by Powell, Warren B., 1955-

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Engineering autonomous vehicles and robots : the DragonFly modular-based approach by Liu, Shaoshan

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Power system monitoring and control by Bevrani, Hassan

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