Type-2 fuzzy ontology-based semantic knowledge for collision avoidance of autonomous underwater vehicles

In this paper, a novel approach to web-based education that performs individualized instruction on the domain of programming languages is presented. This approach is fully implemented and evaluated in an educational application module, called fuzzy knowledge state definer (FuzKSD). In particular, FuzKSD performs user modeling by dynamically identifying and updating a student's knowledge level of all the concepts of the domain knowledge. The operation of FuzKSD is based on fuzzy cognitive maps (FCMs) that are used to represent the dependences among the domain concepts. FuzKSD uses fuzzy sets to represent a student's knowledge level as a subset of the domain knowledge. Thus, it combines fuzzy theory with the overlay model. Moreover, it employs a novel inference mechanism that dynamically updates user stereotypes using fuzzy sets. It should be noted that the overlay model and stereotypes constitute two widely used methods for user modeling. However, they have not been combined with fuzzy sets thus far in the literature. The gain from this novel combination is significant as a student level of knowledge is represented in a more realistic way by automatically modeling the learning or forgetting process of a student with respect to the FCMs and thus the system can provide individualized adaptive advice. The application of this approach is not limited to adaptive instruction. It can also be used in other systems with changeable user states, such as e-shops, where consumers' preferences change over time and affect one another. Therefore, the particular module constitutes a novel generic fuzzy tool, which offers dynamic adaptation to users' needs and preferences of adaptive systems.

Fuzzy Logic for Adaptive Instruction in an E-learning Environment for Computer Programming

Likelihoods of interval type-2 trapezoidal fuzzy preference relations and their application to multiple criteria decision analysis

An interval type-2 fuzzy model of computing with words

In theory, social integration is considered one of the important aspects of assimilation?often referred to as social assimilation. For Eisenstadt, integration is called \"institutional dispersion\", and it entails the extension of the immigrants' institutional and associational participation in the main spheres of the social system of the receiving society (1954:13). Gordon emphasizes integration at the primary group level and terms it \"structural assimilation\" which entails the entrance of the immigrants into social cliques, clubs, and institutions of the host society (1964:70-71). The extension of the immigrants' relations outside their own group to include members of the receiving society is considered an important feature of the newcomers' adaptation and orientation toward the new country. On the other hand, lack of participation in the institutional activities of the receiving society, on the part of the immigrants, is viewed as indicative of the continuing maintenance of a separate social identity (Eisenstadt, 1954:78, 11-13; Warner and Srole, 1945:149-150). Empirical studies in the field of social assimilation, especially in the United States, have dealt with the integration of immigrants in a variety of spheres of the American life including the ecological and political systems, the socioeconomic system, mass media, religion, family and friendships, to name some (Macisco, 1968; Myers, 1950; Duncan and Lieberson, 1959; Lieberson, 1963; Glick, 1942; Vlachos, 1968; Sengstock, 1969; Kourvetaris, 1971; Drakopoulou, 1974; Rogg, 1974; Hurh and Kim, 1984; Humphrey and Louis, 1973; Yu, 1971). The bulk of studies reviewed, however, are

Differential Social Integration among First Generation Greeks in New York: Participation in Religious Institutions.

This paper proposes a new approach to simulating language evolution, it expands on the original work done by Lee and Zadeh on Fuzzy Grammars and introduces a Type-2 Fuzzy Grammar. Ants in an Ant Colony Optimization algorithm are given the ability of embedding a message on the pheromone using a Type-2 Fuzzy Grammar. These ants are able to gradually adopt a foreign language by adjusting the grades of membership of their grammar. Results that show the effect of uncertainty in a language are given.

Type-2 Fuzzy Grammar in Language Evolution

This paper focuses on the self-stabilizing leader election algorithm of Xu and Srimani [10] that finds a leader in a tree graph. The worst case execution time for this algorithm is O(N4), where N is the number of nodes in the tree. We show that the average execution time for this algorithm, assuming two different scenarios, is much lower than O(N4). In the first scenario, the algorithm assumes an equiprobable daemon and it only privileges a single node at a time. The average execution time for this case is O(N2). For the second case, the algorithm can privilege multiple nodes at a time. We eliminate the daemon from this algorithm by making random choices to avoid interference between neighboring nodes. The execution time for this case is O(N). We also show that for specific tree graphs, these results reduce even more.

Analysis of the average execution time for a self-stabilizing leader election algorithm

This paper proposes a new approach to simulating language evolution; it expands on the original work done by Lee and Zadeh on Fuzzy Grammars and introduces a Type-2 Fuzzy Grammar. Ants in an Ant Colony Optimization algorithm are given the ability of embedding a message on the pheromone using a Type-2 Fuzzy Grammar. These ants are able to gradually adopt a foreign language by adjusting the grades of membership of their grammar. Results that show the effect of uncertainty in a language are given.

Type-2 Fuzzy Logic Grammars in Language Evolution

Many computer simulations try to explain language evolution with socially oriented scenarios in multi-agent systems by applying methods such as genetic algorithms and neural networks. In this paper a new approach based on modifications to the classic Ant Colony Optimization algorithm is proposed. Ants are provided with a Fuzzy Grammar and the ability to embed a message in the pheromone. By fuzzifying the grammar, ants are able to modify the degree of membership of the production rules to gradually adopt a foreign language.

Simulation of language evolution using Fuzzy Grammars

This paper deals with the self-stabilizing leader election algorithm of Xu and Srimani that finds a leader in a tree graph. The worst case execution time for this algorithm is O(N4), where N is the number of nodes in the tree. We show that the average execution time for this algorithm, assuming two different scenarios, is much lower than O(N4). In the first scenario, the algorithm assumes a equiprobable daemon and it only privileges a single node at a time. The average execution time for this case is O(N2). For the second case, the algorithm can privilege multiple nodes at a time. We eliminate the daemon from this algorithm by making random choices to avoid interference between neighbor nodes. The execution time for this case is O(N). We also show that for specific tree graphs, these results reduce even more.

/pdf/average-execution-time-analysis-of-a-self-stabilizing-leader-5brynfhnsk.pdf

Juan Paulo Alvarado-Magaña

Papers

Type-2 Fuzzy Grammar in Language Evolution

Analysis of the average execution time for a self-stabilizing leader election algorithm

Type-2 Fuzzy Logic Grammars in Language Evolution

Simulation of language evolution using Fuzzy Grammars

Average Execution Time Analysis of a Self-stabilizing Leader Election Algorithm