Search Results - (((((((kent OR wanting) OR cantee) OR arts) OR cantor) OR anne) OR warte) OR mantis) algorithms.

Data Science : The Executive Summary - a Technical Book for Non-Technical Professionals. by Cady, Field

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New Techniques in Digital Holography

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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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Cloud computing and virtualization

Table of Contents: “…5.1 Detecting and Preventing Data Migrations to the Cloud5.2 Protecting Data Moving to the Cloud; 5.3 Application Security; 5.4 Virtualization; 5.5 Virtual Machine Guest Hardening; 5.6 Security as a Service; 5.7 Conclusion; References; Chapter 6: Dynamic Load Balancing Based on Live Migration; 6.1 Introduction; 6.2 Classification of Load Balancing Techniques; 6.3 Policy Engine; 6.4 Load Balancing Algorithm; 6.5 Resource Load Balancing; 6.6 Load Balancers in Virtual Infrastructure Management Software; 6.7 VMware Distributed Resource Scheduler; 6.8 Conclusion; References.…”
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Yttrium : compounds, production and applications

Table of Contents: “…Spot Size ; 4.4. Fluence ; 4.5. Algorithm ; 5. DEFINITION OF VASCULAR PATHOLOGY ; 6. …”
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The structure of amorphous materials using molecular dynamics by Massobrio, C. (Carlo)

Table of Contents: “…4.2.4 The beauty of the Verlet algorithm -- 4.3 Creating a computer glass via MD: the initial conditions -- 4.4 Production of trajectories and the setup of a thermal cycle -- 4.4.1 An essential summary before hitting the road -- 4.4.2 Starting to run carefully and cautiously: a mini guide -- 4.4.3 Handling adiabaticity: the gap issue -- 4.4.4 Some instructions to be effective when moving to high temperatures -- 4.4.5 Quenching down to the glassy state -- 4.5 Dealing with FPMD odds and ends (including non-adiabaticity): the case of SiN -- 4.5.1 State of the art and calculations…”
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Coder to developer : tools and strategies for delivering your software by Gunderloy, Mike

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RFID systems : research trends and challenges

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Iaeng transactions on electrical engineering. Vol. 1, Special issue of the International Multiconference of Engineers and Computer Scientists 2012

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Pancreatology : a clinical casebook

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Linearization and efficiency enhancement techniques for silicon power amplifiers : from RF to mmW by Kerhervé, Eric, Belot, Didier

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Scala Machine Learning Projects : Build real-world machine learning and deep learning projects with Scala. by Karim, Md. Rezaul

Table of Contents: “…-- Project structure -- Running the Scala Play web app -- Summary -- Chapter 4: Population-Scale Clustering and Ethnicity Prediction -- Population scale clustering and geographic ethnicity -- Machine learning for genetic variants -- 1000 Genomes Projects dataset description -- Algorithms, tools, and techniques -- H2O and Sparkling water -- ADAM for large-scale genomics data processing -- Unsupervised machine learning -- Population genomics and clustering -- How does K-means work? …”
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Handbook of safety principles

Table of Contents: “…Success or Failure / Ann Enander -- 30.8. Relations to Other Safety Principles / Ann Enander -- References / Ann Enander -- Further Reading / Ann Enander -- 31. …”
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Memory Allocation Problems in Embedded Systems : Optimization Methods. by Soto, Maria

Table of Contents: “…Memory management for decreasing power consumption; 1.3. State of the art in optimization techniques for memory management and data assignment; 1.3.1. …”
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A Polygeneration Process Concept for Hybrid Solar and Biomass Power Plant : Simulation, Modeling, and Optimization. by Sahoo, Umakanta

Table of Contents: “…Cover; Title Page; Copyright Page; Contents; Foreword; Preface; 1 Introduction; 1.1 Global Scenario on Renewable Energy; 1.2 Indian Scenario on Renewable Energy; Exercise; References; 2 State-of-the-Art Concentrated Solar Thermal Technologies for End Use Applications; 2.1 Solar Thermal Technologies for Low Grade Heat Applications; 2.1.1 Flat Plate Collector System; 2.1.2 Built-In Storage Solar Water Heating System; 2.1.3 Evacuated Tubular Collector System; ETC Water Heating System Specification; 2.1.4 Cumulative Growth of SWHS Installation Capacity; 2.1.5 Performance Evaluation of SWHs.…”
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Medical and Care Compunetics 2 : Medical and Care Compunetics 2. by Bos, L.

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Adaptive processing of brain signals by Sanei, Saeid

Table of Contents: “…262 -- 11.8 Emotion-Related Brain Signal Processing 263 -- 11.9 Other Neuroimaging Modalities Used for Emotion Study 264 -- 11.10 Applications 267 -- 11.11 Conclusions 268 -- References 268 -- 12 Sleep and Sleep Apnoea 274 -- 12.1 Introduction 274 -- 12.2 Stages of Sleep 275 -- 12.2.1 NREM Sleep 275 -- 12.2.2 REM Sleep 277 -- 12.3 The Influence of Circadian Rhythms 278 -- 12.4 Sleep Deprivation 279 -- 12.5 Psychological Effects 280 -- 12.6 Detection and Monitoring of Brain Abnormalities During Sleep by EEG Analysis 281 -- 12.6.1 Analysis of Sleep Apnoea 281 -- 12.6.2 Detection of the Rhythmic Waveforms and Spindles Employing Blind Source Separation 282 -- 12.6.3 Application of Matching Pursuit 282 -- 12.6.4 Detection of Normal Rhythms and Spindles Using Higher Order Statistics 285 -- 12.6.5 Application of Neural Networks 287 -- 12.6.6 Model-Based Analysis 288 -- 12.6.7 Hybrid Methods 290 -- 12.7 EEG and Fibromyalgia Syndrome 290 -- 12.8 Sleep Disorders of Neonates 291 -- 12.9 Dreams and Nightmares 291 -- 12.10 Conclusions 292 -- References 292 -- 13 Brain-Computer Interfacing 295 -- 13.1 Introduction 295 -- 13.2 State of the Art in BCI 296 -- 13.3 BCI-Related EEG Features 300 -- 13.3.1 Readiness Potential and Its Detection 300 -- 13.3.2 ERD and ERS 300 -- 13.3.3 Transient Beta Activity after the Movement 302 -- 13.3.4 Gamma Band Oscillations 302 -- 13.3.5 Long Delta Activity 303 -- 13.4 Major Problems in BCI 303 -- 13.4.1 Pre-Processing of the EEGs 304 -- 13.5 Multidimensional EEG Decomposition 306 -- 13.5.1 Space-Time-Frequency Method 308 -- 13.5.2 Parallel Factor Analysis 309 -- 13.6 Detection and Separation of ERP Signals 310 -- 13.7 Estimation of Cortical Connectivity 311 -- 13.8 Application of Common Spatial Patterns 314 -- 13.9 Multiclass Brain-Computer Interfacing 316 -- 13.10 Cell-Cultured BCI 318 -- 13.11 Conclusions 319 -- References 320 -- 14 EEG and MEG Source Localization 325 -- 14.1 Introduction 325 -- 14.2 General Approaches to Source Localization 326 -- 14.2.1 Dipole Assumption 327 -- 14.3 Most Popular Brain Source Localization Approaches 329 -- 14.3.1 ICA Method 329 -- 14.3.2 MUSIC Algorithm 329 -- 14.3.3 LORETA Algorithm 333 -- 14.3.4 FOCUSS Algorithm 335 -- 14.3.5 Standardised LORETA 335 -- 14.3.6 Other Weighted Minimum Norm Solutions 336 -- 14.3.7 Evaluation Indices 338 -- 14.3.8 Joint ICA-LORETA Approach 338 -- 14.3.9 Partially Constrained BSS Method 340 -- 14.3.10 Constrained Least-Squares Method for Localization of P3a and P3b 341 -- 14.3.11 Spatial Notch Filtering Approach 342 -- 14.3.12 Deflation Beamforming Approach for EEG/MEG Multiple Source Localization 347 -- 14.3.13 Hybrid Beamforming -- Particle Filtering 351 -- 14.4 Determination of the Number of Sources from the EEG/MEG Signals 353 -- 14.5 Conclusions 355 -- References 356 -- 15 Seizure and Epilepsy 360 -- 15.1 Introduction 360 -- 15.2 Types of Epilepsy 362 -- 15.3 Seizure Detection 365 -- 15.3.1 Adult Seizure Detection 365 -- 15.3.2 Detection of Neonate Seizure 371 -- 15.4 Chaotic Behaviour of EEG Sources 376 -- 15.5 Predictability of Seizure from the EEGs 378 -- 15.6 Fusion of EEG -- fMRI Data for Seizure Detection and Prediction 391 -- 15.7 Conclusions 391 -- References 392 -- 16 Joint Analysis of EEG and fMRI 397 -- 16.1 Fundamental Concepts 397 -- 16.1.1 Blood Oxygenation Level Dependent 399 -- 16.1.2 Popular fMRI Data Formats 400 -- 16.1.3 Preprocessing of fMRI Data 401 -- 16.1.4 Relation between EEG and fMRI 401 -- 16.2 Model-Based Method for BOLD Detection 403 -- 16.3 Simultaneous EEG-fMRI Recording: Artefact Removal from EEG 405 -- 16.3.1 Gradient Artefact Removal 405 -- 16.3.2 Ballistocardiogram Artefact Removal 406 -- 16.4 BOLD Detection in fMRI 413 -- 16.4.1 Implementation of Different NMF Algorithms for BOLD Detection 414 -- 16.4.2 BOLD Detection Experiments 416 -- 16.5 Fusion of EEG and fMRI 419 -- 16.5.1 Extraction of fMRI Time-Course from EEG 419 -- 16.5.2 Fusion of EEG and fMRI, Blind Approach 241 -- 16.5.3 Fusion of EEG and fMRI, Model-Based Approach 425 -- 16.6 Application to Seizure Detection 425 -- 16.7 Conclusions 427 -- References 427.…”
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Handbook of constraint programming

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