Search Results - (((((((ant OR antii) OR semantic) OR arts) OR cantor) OR anne) OR maarten) OR mantis) algorithms.

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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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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Network and system security

Table of Contents: “…Statistical Analysis -- 24. Signature Algorithms -- 25. Local Area Network Security Countermeasures Implementation Checklist -- 26. …”
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Mastering mobile learning

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Big data and differential privacy : analysis strategies for railway track engineering by Attoh-Okine, Nii O.

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Grey systems : theory and applications by Chen, Mian-Yun

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Danforth's obstetrics and gynecology.

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Fuzzy intelligent systems : methodologies, techniques, and applications

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Nuclear Magnetic Resonance Spectroscopy Of Liquid Crystals.

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An introduction to statistical computing : a simulation-based approach by Voss, Jochen

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Stochastic simulation optimization for discrete event systems : perturbation analysis, ordinal optimization, and beyond

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Catalytic Reactors

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Stochastic dynamics of structures by El Hami, Abdelkhalak, Radi, Bouchaïb

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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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3D face modeling, analysis and recognition by Daoudi, Mohamed, Ph. D., Srivastava, Anuj, Veltkamp, Remco C., 1963-

Table of Contents: “…4 3D Morphable Models for Face Surface Analysis and Recognition4.1 Introduction; 4.2 Data Sets; 4.3 Face Model Fitting; 4.3.1 Distance Measure; 4.3.2 Iterative Face Fitting; 4.3.3 Coarse Fitting; 4.3.4 Fine Fitting; 4.3.5 Multiple Components; 4.3.6 Results; 4.4 Dynamic Model Expansion; 4.4.1 Bootstrapping Algorithm; 4.4.2 Results; 4.5 Face Matching; 4.5.1 Comparison; 4.5.2 Results; 4.6 Concluding Remarks; Exercises; References; 5 Applications; 5.1 Introduction; 5.2 3D Face Databases; 5.3 3D Face Recognition; 5.3.1 Challenges of 3D Face Recognition; 5.3.2 3D Face Recognition: State of the Art.…”
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Qualitative computing : a computational journey into nonlinearity by Chaitin-Chatelin, Françoise

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Hacking digital ethics by Krieger, David J.

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Recent advances in computational sciences : selected papers from the International Workshop on Computational Sciences and its Education, Beijing, China, 29-31 August 2005

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