Part 1 - Theoretical Foundations.- Interval Type-2 Fuzzy Logic Systems and Perceptual Computers: Their Similarities and Differences.- Continuous Karnik-Mendel Algorithms and Their Generalizations.- Two Differences Between Interval Type-2 and Type-1 Fuzzy Logic Controllers: Adaptiveness and Novelty.- Interval Type-2 Fuzzy Markov Chains.- zSlices Based General Type-2 Fuzzy Sets and Systems.- Geometric Type-2 Fuzzy Sets.- Type-2 Fuzzy Sets and Bichains.- Type-2 Fuzzy Sets and Conceptual Spaces.- Part B- Type-2 Fuzzy Set Membership Function Generation.- Modeling Complex Concepts with Type-2 Fuzzy Sets: The Case of User Satisfaction of Online Services.- Construction of Interval type-2 fuzzy sets from fuzzy sets. Methods and applications.- Interval type-2 fuzzy membership function generation methods for representing sample data.- Part C - Applications.- ype-2 Fuzzy Logic in Image Analysis and Pattern Recognition.- Reliable Tool Life Estimation with Multiple Acoustic Emission Signal Feature Selection and Integration Based on Type-2 Fuzzy Logic.- A Review of Cluster Validation with an Example of Type-2 Fuzzy Application in R.- Type-2 Fuzzy Set and Fuzzy Ontology for Diet Application.