Note: Title -- Preface -- Organization -- Table of Contents -- Keynote -- An Outline of a Theory of Three-Way Decisions -- Introduction -- A Description of Three-Way Decisions -- Evaluation-Based Three-Way Decisions -- Three-Way Decisions with a Pair of Poset-Based Evaluations -- Three-Way Decisions with One Poset-Based Evaluation -- Three-Way Decisions with an Evaluation Using a Totally Ordered Set -- Comments on Evaluations and Designated Values -- Models of Three-Way Decisions -- Interval Sets and Three-Valued Logic -- Pawlak Rough Sets -- Decision-Theoretic Rough Sets -- Three-Valued Approximations in Many-Valued Logic and Fuzzy Sets -- Shadowed Sets -- Conclusions -- References -- Part I: Rough Sets and Its Applications -- A Multi-granulation Model under Dominance-Based Rough Set Approach -- Introduction -- Preliminaries -- A Multi-granulation Model Based on DRSA -- A Numerical Example -- Conclusions -- References -- A Refined Rough k-Means Clustering with Hybrid Threshold -- Introduction -- Rough c-Means Clustering Algorithm -- The Lingras Rough c-Means Clustering -- The Peters Rough C-Means Clustering -- The Selection of Parameters -- The Proposed Rough c-Means Clustering -- The Adaptive Weights Based on Approximation Accuracy -- The Hybrid Threshold -- Experiments -- Conclusions -- References -- An Incremental Approach for Updating Approximations of Rough Fuzzy Sets under the Variation of the Object Set -- Introduction -- Preliminaries -- Incremental Methods for Updating Approximations of Rough Fuzzy Sets under the Variation of Objects -- The Immigration of a New Object -- The Emigration of One Object -- Illustrations -- Conclusions -- References -- How Good Are Probabilistic Approximations for Rule Induction from Data with Missing Attribute Values? -- Introduction -- Incomplete Data Sets -- Probabilistic Approximations -- Experiments. , Conclusions -- References -- Induction of Ordinal Classification Rules from Incomplete Data -- Introduction -- Different Ways of Handling Missing Values in DRSA -- Basics of DRSA -- Extensions of DRSA to Handle Missing Values -- Induction and Application of Decision Rules -- Results of Computational Experiment and Discussion -- References -- Interval Valued Fuzzy Rough Set Model on Two Different Universes and Its Application -- Introduction -- Preliminaries -- Interval Valued Fuzzy Sets -- Rough Sets -- Interval Valued Fuzzy Rough Set Model on Two Different Universes -- The Application of the Interval Valued Fuzzy Rough Set Model on Two Different Universes -- References -- Maximal Characteristic Sets and Neighborhoods Approach to Incomplete Information Systems -- Introduction -- Related Concepts -- Similarity Relations, Similarity Classes, and Maximal Consistent Blocks -- Binary Neighborhood Systems, Maximal Consistent Block Neighborhoods -- Characteristic Relations and Characteristic Sets -- Neighborhood Systems of Maximal Characteristic Sets -- Maximal Characteristic Sets and Neighborhoods -- Approximations Based on Maximal Characteristic Neighborhoods -- Conclusions -- References -- Probabilistic Fuzzy Rough Set Model over Two Universes -- Introduction -- Preliminaries -- Fuzzy Relation and Fuzzy Compatibility Relation -- Rough Set Models over Two Universes -- Probabilistic Fuzzy Rough Set Model over Two Universes -- Properties for Probabilistic Fuzzy Rough Set over Two Universes -- Conclusions -- References -- Rough Optimizations of Complex Expressions in Infobright's RDBMS -- Introduction -- Infobright's Architecture -- New Implementation of Complex Expressions -- Conclusions -- References -- Rough Sets Based Inequality Rule Learner for Knowledge Discovery -- Introduction -- Compensatory Model for Expressing Inequality Relations. , An Inequality Rule Learner -- Experiment -- Conclusion -- References -- Part II: Current Trends in Computing -- A Computer Aided Diagnosis System for Breast Cancer Using Support Vector Machine -- Introduction -- The Proposed Computer Aided Diagnosis System for Breast Cancer -- Preprocessing Phase -- Segmentation Phase: Seeded-Threshold Growing Region Algorithm -- Feature Extraction Phase: Moment Algorithm -- Classification Phase: Support Vector Machine -- Experimental Results and Discussions -- Conclusions and Further Research -- References -- A New Method of the Accurate Eye Corner Location -- Introduction -- Face Detection -- Accurate Eye Corner Location -- Rough Eye Location -- Extraction Eye Contour Based on Ellipse Fitting -- Corner Detection and Eye Corner Location -- Experiments and Discussion -- Comparative Experiment on Accuracy -- Case Study -- Conclusion -- References -- A Hybrid Approach of Verbal Decision Analysis and Machine Learning -- Introduction -- ZAPROS III-i Method -- Decision Trees -- The Diagnosis of the Alzheimer's Disease -- A Hybrid Model to Determine the Main Characteristics to Diagnose the Alzheimer's Disease -- Conclusions, Future Works and Acknowledgments -- References -- An Efficient Data Integrity Verification Method Supporting Multi-granular Operation with Commutative Hash -- Introduction -- Granular Computing -- Design Goals -- Proposed Scheme -- Notation and Preliminaries -- File Decomposition and Aggregation -- Verification Protocol -- Dynamic Operation -- Data Modification -- Data Insertion -- Security Analysis -- Performance Analysis -- Conclusion -- References -- Density-Based Method for Clustering and Visualization of Complex Data -- Introduction -- Approaches Used to Cluster Large Volumes of Data -- Comparison of OPTICS and DBSCAN -- OPTICS as a Visualization Method -- Summary -- References. , Inference Processes Using Incomplete Knowledge in Decision Support Systems - Chosen Aspects -- Introduction -- Search Using Hierarchy Structure -- Computational Experiments -- The Most Promising Path -- The Conclusions -- References -- Interactive Document Indexing Method Based on Explicit Semantic Analysis -- Introduction -- Semantic Indexing and Searching Using ESA -- Learning Model -- Experiments -- Conclusions and Future Work -- References -- Microblog Topic Detection Based on LDA Model and Single-Pass Clustering -- Introduction -- Related Work -- The Method of Microblog Text Modeling -- Latent Dirichlet Allocation -- Topic Detection by Single-Pass Clustering -- Experiment and Results -- Evaluation Criteria -- Dataset -- Results -- Conclusion -- References -- Named Entity Matching in Publication Databases A Case Study of PubMed in SONCA -- Introduction -- SYNAT Platform and SONCA System -- SONCA Analytic Data Warehouse -- Matching of PubMed Papers in SONCA Database -- Conclusions and Further Work -- References -- On the Homogeneous Ensembling with Balanced Random Sets and Boosting -- Introduction -- Data Pre-processing -- Textual data -- Synthetic Features -- On the Comparison between Different Cost-Variables -- Homogeneous Ensembling with Balances Random Sets -- On the Boosting Principles Applied to the Selection of the Balanced Subsets -- Some Other Ways to Construct Secondary Training Datasets -- The Best Single Model -- Blending of the Different Databases with Neural Nets -- Principle of Invariance -- Concluding Remarks -- References -- On Cost and Uncertainty of Decision Trees -- Introduction -- Basic Notions -- Decision Tables and Decision Trees -- Representation of Sets of Decision Trees -- Cost Functions -- Relationship between Cost and Uncertainty -- Computing the Function F,T -- Experimental Results -- Conclusion -- References. , Optimization of Quadtree Representation and Compression -- Introduction -- CORN Algorithm -- Quadtree Approximation Methods -- Algorithm Design and Empirical Results -- Conclusion and Future Research -- References -- Outlier Mining in Rule-Based Knowledge Bases -- Introduction -- Outliers in Rule Knowledge Bases -- Why to Mine the Outliers in Rules ? -- Methods for Mining Outliers -- Distribution-Based Method -- Distance Based Methods -- Density Based Methods -- Clustering Based Methods -- The Experiments -- Summary -- References -- Relationships between Number of Nodes and Number of Misclassifications for Decision Trees -- Introduction -- Basic Notions -- Representation of Sets of Decision Trees -- Relationships -- Computing Gfi -- Experimental Results -- Conclusions -- References -- Study on Feature Trajectory for Web Video Event Mining -- Introduction -- Related Work -- Topic Detection and Tracking -- Feature Trajectory -- Textual vs. Visual Feature Trajectory -- Studies on Textual Feature Trajectory -- Studies on Visual Feature Trajectory -- Web Video Event Mining by Fusion of Feature Trajectories -- Experiment -- Dataset -- Performance Evaluation -- Conclusion -- References -- The Triangle Inequality versus Projection onto a Dimension in Determining Cosine Similarity Neighborhoods of Non-negative Vectors -- Introduction -- The Euclidean Distance and the Cosine Similarity -- Euclidean Distance Neighborhood and Cosine Similarity Neighborhood -- The Triangle Inequality in Determining Euclidean Distance Neighborhoods -- Vector Projection onto a Dimension in Determining Euclidean Distance Neighborhoods -- The Triangle Inequality versus Projection onto a Dimension for Non-negative Normalized Vectors -- Summary -- References -- The Way of Improving PSO Performance: Medical Imaging Watermarking Case Study -- Introduction -- Preliminaries. , Genetic Algorithm.

Note: Intro -- Preface -- LNCS Transactions on Rough Sets -- Managing Editor -- Technical Editor -- Editorial Board -- Contents -- On the Intuitionistic Fuzzy Topological Structures of Rough Intuitionistic Fuzzy Sets -- 1 Introduction -- 2 Basic Notions of Intuitionistic Fuzzy Sets -- 3 Rough Intuitionistic Fuzzy Sets -- 3.1 Rough Fuzzy Approximation Operators -- 3.2 Rough Intuitionistic Fuzzy Approximation Operators -- 4 Basic Concepts of Intuitionistic Fuzzy Topological Spaces -- 5 Topological Structures of Rough Intuitionistic Fuzzy Sets -- 6 The Conditions of an Intuitionistic Fuzzy Topological Spaces Induced from a Crisp Approximation Space -- 7 Conclusion -- References -- Feature Selection with Positive Region Constraint for Test-Cost-Sensitive Data -- 1 Introduction -- 2 Preliminaries -- 2.1 Test-Cost-Independent Decision Systems -- 2.2 Positive Region -- 2.3 Feature Selection with Positive Region Constraint Problem -- 3 The Algorithm -- 4 Experiments -- 4.1 Experiments Settings -- 4.2 Experiments Results -- 5 Conclusions -- References -- A Rough Neurocomputing Approach for Illumination Invariant Face Recognition System -- 1 Introduction -- 2 Overview of Rough Set Theory -- 3 Proposed RNR System -- 3.1 Pre-processing -- 3.2 Feature Extraction -- 3.3 ADNN-Based Recognition -- 3.4 Approximation Neuron -- 3.5 Decider Neuron -- 4 Simulation Results -- 5 Conclusion -- References -- Variable Precision Multigranulation Rough Set and Attributes Reduction -- 1 Introduction -- 2 VPRS and MGRS -- 2.1 Variable Precision Rough Set -- 2.2 Multigranulation Rough Set -- 3 Variable Precision Multigranulation Rough Set -- 3.1 Variable Precision Optimistic Multigranulation Rough Set -- 3.2 Variable Precision Pessimistic Multigranulation Rough Set -- 3.3 Approximation Quality -- 4 Relationships Among Several Models -- 5 Attribute Reduction in VPMGRS. , 5.1 Experimental Results -- 6 Conclusions -- References -- Three-Way Decisions Versus Two-Way Decisions on Filtering Spam Email -- 1 Introduction -- 2 Decision-Theoretic Rough Set Model -- 3 Three-Way Decisions and Two-Way Decisions Solutions on Spam Filtering -- 3.1 Three-Way Decisions Solution -- 3.2 Two-Way Decisions Solution -- 3.3 Evaluation Measures -- 4 Experiments -- 4.1 Experiment 1 with Measure Group 1 -- 4.2 Experiment 2 with Measure Group 2 -- 5 Conclusions -- A Experimental Result Tables -- References -- A Three-Way Decisions Approach to Density-Based Overlapping Clustering -- 1 Introduction -- 2 Preliminaries -- 3 Formulation of Clustering -- 3.1 Extend DTRS for Clustering -- 3.2 Re-formulation of Clustering Using Interval Sets -- 4 Clustering Algorithm Using Three-way Decisions -- 4.1 Basic Concepts -- 4.2 Initial Clustering Processing -- 4.3 Three-Way Decisions Clustering Processing -- 5 Experimental Results -- 5.1 Overlapping Clustering Analysis -- 5.2 Arbitrary Shape Clustering Analysis -- 6 Conclusion -- References -- Three-Way Decisions in Stochastic Decision-Theoretic Rough Sets 敳敲癥搠䁤 㴀 ⨀䁬整䁴潫敮 ⴀ㘀瀀 -- 1 Introduction -- 2 Preliminaries -- 2.1 Stochastic Model and Confidence Interval -- 2.2 Decision-Theoretic Rough Sets -- 3 Extension of Decision-Theoretic Rough Set Models -- 3.1 Stochastic Decision-Theoretic Rough Sets -- 3.2 Stochastic Decision-Theoretic Rough Sets with Statistical Distributions -- 4 An Illustration -- 5 Conclusions -- References -- Correction to: Transactions on Rough Sets XVIII -- Correction to: J. F. Peters et al. (Eds.): Transactions on Rough Sets XVIII, LNCS 8449, https://doi.org/10.1007/978-3-662-44680-5 -- Author Index.

Note: Intro -- Supervisors' Foreword -- Foreword I -- Foreword II -- Preface -- Contents -- Acronyms -- 1 Introduction -- 1.1 Plasma Turbulence -- 1.2 An Overview of Approaches -- 1.3 Incompressible MHD Turbulence -- 1.3.1 Energy Cascade and Spectra -- 1.3.2 Intermittency -- 1.3.3 Localness of Energy Transfer -- 1.4 Compressible MHD Turbulence -- 1.4.1 MHD Shock Waves -- 1.4.2 Numerical Simulation -- 1.4.3 Possible Effects of Compressibility and Shocks -- 1.5 Plasma Turbulence at Kinetic Scales -- 1.5.1 Energy Spectra at Kinetic Scales -- 1.5.2 Kinetic Dissipation -- References -- 2 Theoretical Modelling -- 2.1 The Electromagnetic Field Equations -- 2.2 Charged Particle Motion -- 2.3 Kinetic Theory -- 2.4 Two-Fluid Theory -- 2.5 Single-Fluid Theory -- 2.5.1 The Reduced Form of Electrodynamic Equations for MHD -- 2.5.2 Magnetic Induction Equation -- 2.5.3 The Full Equations of MHD -- References -- 3 Hybrid Scheme for Compressible MHD Turbulence -- 3.1 Governing Equations -- 3.1.1 Ideal MHD Equations -- 3.1.2 Dimensionless MHD Equations -- 3.2 Numerical Method -- 3.2.1 The Hybrid Compact-WENO Scheme -- 3.2.2 Pentadiagonal Filter -- 3.2.3 Divergence-Free Constraint of the Magnetic Field -- 3.3 Numerical Results -- 3.3.1 Accuracy Analysis of the Hybrid Scheme -- 3.3.2 1D and 2D Numerical Tests -- 3.3.3 Isotropic MHD Turbulence -- 3.4 Concluding Remarks -- References -- 4 Energy Cascade in Compressible MHD Turbulence -- 4.1 Simulation Setup -- 4.1.1 Large-Scale Forcing Mechanism -- 4.1.2 Simulation Details -- 4.2 Filtered Energy Equations -- 4.3 Effect of Forcing Mechanisms -- 4.3.1 Statistical Quantities -- 4.3.2 Turbulent Structures -- 4.3.3 Energy Transfer -- 4.4 Compressibility Effect on Scaling Laws -- 4.4.1 Four-Thirds Law -- 4.4.2 Density Structure Functions -- 4.5 Compressibility Effect on the Localness of Energy Transfer -- 4.6 Concluding Remarks. , References -- 5 Energy Transfer and Dissipation in Collisionless Plasma Turbulence -- 5.1 Energy Balance -- 5.2 PIC Simulation Details -- 5.3 Role of Pressure Tensor -- 5.3.1 Intermittency of Pressure-Strain Interaction -- 5.3.2 Coherent Structures in Plasma Turbulence -- 5.3.3 Correlation Between Energy Transfer and Coherent Structures -- 5.4 Energy Transfer Channels -- 5.4.1 Correlation Between Pressure-Stress Interaction and Electromagnetic Work -- 5.4.2 Filtered Fluid Kinetic Energy Equation -- 5.4.3 Energy Transfer Across Scales and Between Different Forms -- 5.5 Concluding Remarks -- References -- 6 Conclusions and Discussion -- 6.1 Conclusions -- 6.2 Perspectives -- A Fifth-Order WENO Scheme -- B Eigen-System in MHD -- B.1 1D MHD System -- B.2 Extension to 2D and 3D -- C A Parallel Algorithm for Pentadiagonal Systems -- D Filtered Electromagnetic Energy Equation -- Index -- Blank Page -- Blank Page -- Blank Page -- Blank Page -- Blank Page -- Blank Page -- Blank Page -- Blank Page.