Search Results - (((((((ant OR wants) OR semantic) OR wind) OR cantor) OR anne) OR plans) OR hints) algorithms.

Implant aesthetics : keys to diagnosis and treatment

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Aerospace Sensors. by Nebylov, Alexander

Table of Contents: “…Principles and examples of sensor integration -- 9.1 Sensor systems -- 9.1.1 The sensor system concept -- 9.1.2 Joint processing of readings from identical sensors -- 9.1.3 Joint processing of readings from cognate sensors with different measurement ranges -- 9.1.4 Joint processing of diverse sensors readings -- 9.1.5 Linear and nonlinear sensor integration algorithms -- 9.2 Fundamentals of integrated measuring system synthesis -- 9.2.1 Synthesis problem statement -- 9.2.2 Classes of dynamic system realization -- 9.2.3 Measurement accuracy indices -- 9.2.4 Excitation properties -- 9.2.5 Objective functions for robust system optimisation -- 9.2.6 Methods of dynamic system accuracy index analysis under excitation with given numerical characteristics of derivatives -- 9.2.6.1 Estimation of error variance -- 9.2.6.2 Example of error variance analysis -- 9.2.6.3 Use of equivalent harmonic excitation -- 9.2.6.4 Estimation of error maximal value -- 9.2.7 System optimization under maximum accuracy criteria -- 9.2.8 Procedures for the dimensional reduction of a measuring system -- 9.2.8.1 Determination of an optimal set of sensors -- 9.2.8.2 Analysis of the advantages of invariant system construction -- 9.2.8.3 Advantages of the zeroing of several system parameters -- 9.2.9 Realization and simulation of integration algorithms -- 9.3 Examples of two-component integrated navigation systems -- 9.3.1 Noninvariant robust integrated speed meter -- 9.3.2 Integrated radio-inertial measurement -- 9.3.3 Airborne gravimeter integration -- 9.3.4 The orbital verticant -- References…”
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Probability, Random Processes, and Statistical Analysis : Applications to Communications, Signal Processing, Queueing Theory and Mathematical Finance. by Kobayashi, Hisashi

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Understanding smart sensors by Frank, Randy

Table of Contents: “…ZigBee-Like Wireless -- 8.3.3. ANT+ -- 8.3.4.6LoWPAN -- 8.3.5. Near Field Communication (NFC) -- 8.3.6.Z-Wave -- 8.3.7. …”
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Power system monitoring and control by Bevrani, Hassan

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Uncommon sense : investment wisdom since the stock market's dawn by Kemp, Michael E.

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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: “…Prakasam and Madheswaran Muthusamy -- Rapid prototyping substitute material preparation and applications in casting process / Changming Zhang and Hui Zhang -- A novel fast motion estimation method based on clonal particle swarm optimization / Ranganadham D, Pavankumar Gorpuni and Ganapati Panda -- Two level encryption -- a new algorithm for information security / Subhashis Maitra -- Physical modeling of high rib and thin web aerocraft frame part with different cross-section during isotherm condition / Hui Zhang -- Semi-automatic manufacturing feature recognition for feature interaction problem in process planning / Deepali Tatkar and Venkatesh Kamat -- Multi-resolution segmentation of retinal vessels using optimal thresholding method / M.C. …”
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Handbook of Stochastic Models and Analysis of Manufacturing System Operations. by Smith, J. M. (J. MacGregor)

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Insight into fuzzy modeling by Novák, Vilém, 1951-, Perfilieva, Irina, 1953-, Dvořák, Antonín (Mathematician)

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Networks-on-chip : from implementations to programming paradigms by Ma, Sheng, Huang, Libo, 1976-, Lai, Mingche, Shi, Wei

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Millimeter-wave digitally intensive frequency generation in CMOS by Wu, Wanghua, Staszewski, Robert Bogdan, 1965-, Long, John R. (John Robert), 1958-

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Listed Volatility and Variance Derivatives : a Python-based Guide. by Hilpisch, Yves

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The Dictionary of Critical Social Sciences. by Young, T. R.

Table of Contents: “…Cover -- Half Title -- Title -- Copyright -- Dedication -- Preface -- Authors' Note -- Acknowledgments -- A -- AARP -- Abduction -- Abolitionism -- Abortion -- Abuse, Child -- Abuse, Spousal -- Accenting the Sign -- Act -- Act, Philosophy of -- Acton, Lord (1834-1902) -- Actor -- Adolescence -- Adorno, Theodor (1903-1969) -- Adventist Religious Groups -- Advertising -- Aesthetics -- Aesthetics (Socialist) -- Affect -- Age -- Aged, Immiseration of -- Age Grades -- Agency, Human -- Agitation -- Agnosticism -- Agrarian Society -- Agriculture -- Agriculture, Hydraulic Societies -- Agrippa -- Ahistoricism -- Algorithm -- Alienation -- Alienation, Assumptions of -- Alienation, Psychological -- Allegory -- Analogy -- Analysis -- Anarchy -- Androcentricism -- Animal Functions -- Anomia -- Anomie -- Anthropocentrism -- Anthropology -- Anthropomorphism -- Anti-Foundationalism -- Anti-Semitism -- Apathy -- Apollonian -- Apology -- Apple, and Temptation to Knowledge -- Appropriation -- Appropriation, Mechanisms of -- Aquinas, Thomas, St. (1225-1274) -- Archaeology -- Archetype -- Aristocracy -- Aristotle (384-322 B.C.E.) -- Art -- Artificial Intelligence -- Artificial Stupidity -- Asceticism -- Ascribed Status -- Ashby's Law of Requisite Variety -- Assimilation -- Atheism -- Attitude -- Attractor -- Attractor, Strange -- Augustine, St. (354-430) -- Author -- Authoritarianism -- Authoritarian Personality -- Authority -- Automation -- Autonomy -- Away(s) -- Axiology -- Axiom -- B -- Back Stage -- Bacon, Francis (1561-1626) -- Bakunin, Mikhail (1814-1876) -- Balance of Payments -- Balance of Trade -- Banditry, Social -- Barbarism -- Barthes, Roland (1915-1980) -- Base -- Baseball -- Base Communities -- Bastard -- Baudrillard, Jean (1929- ) -- Beauvoir, Simone de (1908-1986) -- Behavior -- Behaviorism -- Behavior Modification -- Belief.…”
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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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Le Fabuleux Chantier : Rendre l'intelligence Artificielle Robustement Bénéfique. by HOANG, Lê Nguyên

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Digital image interpolation in Matlab by Kok, Chi-Wah, Tam, Wing-Shan

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

Table of Contents: “…6.3.1 Hardware Emulation of CT-Ms on an FPGA 257 -- 6.3.2 GPU-accelerated Computing of CT-Ms 258 -- 6.4 Using Multi-objective Evolutionary Algorithms to Optimize Ms 259 -- 6.4.1 Combining MOEA with SIMSIDES 261 -- 6.4.2 Applying MOEA and SIMSIDES to the Synthesis of CT-Ms 262 -- 6.5 Summary 269 -- References 269 -- 7 Electrical Design of ??…”
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Industrial automation technologies by Dey, Chanchal, Sen, Sunit Kumar

Table of Contents: “…Digital PID Control Algorithm -- Positional and Velocity Forms -- 3.3.4. …”
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