Keynote and Invited Talks -- Interval-Based Models for Decision Problems -- On Choquet Integral Risk Measures -- Computing with Words and Systemic Functional Linguistics: Linguistic Data Summaries and Natural Language Generation -- Managing Granular Information in the Development of Human-Centric Systems -- Dempster-Shafer Reasoning in Large Partially Ordered Sets: Applications in Machine Learning -- Quasi-copulas: A Bridge between Fuzzy Set Theory and Probability Theory -- Fuzzy Measures and Integrals -- A Survey of Fuzzy Integrals: Directions for Extensions -- Choquet Integral on Locally Compact Space: A Survey -- New Conditions for the Egoroff Theorem in Non-additive Measure Theory -- A Study of Riesz Space-Valued Non-additive Measures -- Entropy of Fuzzy Measure -- Representations of Importance and Interaction of Fuzzy Measures, Capacities, Games and Its Extensions: A Survey -- Capacities, Set-Valued Random Variables and Laws of Large Numbers for Capacities -- Integrated Uncertainty and Operations Research -- Symmetries: A General Approach to Integrated Uncertainty Management -- On Interval Probabilities -- Qualitative and Quantitative Data Envelopment Analysis with Interval Data -- Kolmogorov-Smirnov Two Sample Test with Continuous Fuzzy Data -- Hybrid Fuzzy Least-Squares Regression Model for Qualitative Characteristics -- Single-Period Inventory Models with Fuzzy Shortage Costs Dependent on Random Demands -- A Variable-Capacity-Based Fuzzy Random Facility Location Problem with VaR Objective -- Double-Layered Hybrid Neural Network Approach for Solving Mixed Integer Quadratic Bilevel Problems -- Aggregation Operators and Decision Making -- Aggregation of Quasiconcave Functions -- Choquet Integral Models with a Constant -- Fuzzy MCDM and the Sugeno Integral -- Group Decisions in Interval AHP Based on Interval Regression Analysis -- Linguistic Multi-Expert Decision Making Involving Semantic Overlapping -- Constructing Fuzzy Random Goal Constraints for Stochastic Fuzzy Goal Programming -- Logical Approaches to Uncertainty -- Bags, Toll Sets, and Fuzzy Sets -- On a Criterion for Evaluating the Accuracy of Approximation by Variable Precision Rough Sets -- Granularity and Approximation in Sequences, Multisets, and Sets in the Framework of Kripke Semantics -- Uncertainty in Future: A Paraconsistent Approach -- Filters on Commutative Residuated Lattices -- An Algebraic Structure of Fuzzy Logics with Weakly Associative Conjunctors -- Reasoning with Uncertainty -- Reasoning with Uncertainty in Continuous Domains -- Information Cell Mixture Models: The Cognitive Representations of Vague Concepts -- Combination of Uncertain Class Membership Degrees with Probabilistic, Belief, and Possibilistic Measures -- Toward Rough Sets Based Rule Generation from Tables with Uncertain Numerical Values -- Acquiring Knowledge from Decision Tables for Evidential Reasoning -- Data Mining -- Scalable Methods in Rough Sets -- Comparison of Various Evolutionary and Memetic Algorithms -- On the Selection of Parameter m in Fuzzy c-Means: A Computational Approach -- Dissimilarity Based Principal Component Analysis Using Fuzzy Clustering -- Fuzzy and Semi-hard c-Means Clustering with Application to Classifier Design -- Applications -- On the Applications of Aggregation Operators in Data Privacy -- Rough Analysis for Knowledge Discovery in a Simplified Earthquake Database -- User Authentication via Keystroke Dynamics Using Bio-matrix and Fuzzy Neural Network -- How to Activate a Collaboration Network via a Core Employee’s Communication? -- Restructuring of Rough Sets for Fuzzy Random Data of Creative City Evaluation -- A Novel Idea of Real-Time Fuzzy Switching Regression Analysis: A Nuclear Power Plants Case Study -- Consideration on Sensitivity for Correspondence Analysis and Curriculum Comparison.

Solving practical problems often requires the integration of information and knowledge from many different sources, taking into account uncertainty and impreciseness. Typical situations are, for instance, when we need to simultaneously process both measurement data and expert knowledge, where the former may be uncertain and inaccurate due to randomness or error in measurements whilst the latter are often vague and imprecise due to a lack of information or human’s subjective judgements. This gives rise to the demand for methods and techniques of managing and integrating various types of uncertainty within a coherent framework, so as to ultimately improve the solution to any such complex problem in practice. The 2010 International Symposium on Integrated Uncertainty Management and Applications (IUM’2010), which takes place at the Japan Advanced Institute of Science and Technology (JAIST), Ishikawa, Japan, between 9th–11thApril, is therefore conceived as a forum for the discussion and exchange of research results, ideas for and experience of application among researchers and practitioners involved with all aspects of uncertainty modelling and management.