Veridicality of self-concept of strengths in male adolescents

Changes in physical self-concept and veridicality (i.e., the appropriateness of one’s self-perceptions to reality) during childhood and adolescence are related to performance in physical fi tness, exercise, and global self-esteem, particularly in male adolescents. This cross-sectional study examined the relation between the self-concept of strength and actual strength in groups of male adolescents ages 12 to 15 years. For this purpose, 889 male adolescents (M age = 13.2 yr., SD = 1.0) were questioned about their self-concept of strength, after which a test of strength was carried out. The results showed that the correlation between self- concept of strength and actual strength was higher in older (14- and 15-year-old) than younger (12- and 13-year-old) adolescents. There was a statistically signifi cant association between age group and veridicality, indicating that realistic self-concept is underrepresented among younger, but overrepresented among older adolescents. No association was found between the adolescents’ physical activity and veridicality. The consequences for further research on the development of veridicality in the physical domain are discussed.

A Concept of Semantics Extraction from Web Data by Induction of Fuzzy Ontologies

Traditionally, ontologies describe knowledge representation in a denotational, formalized, and deductive way. In addition, in this paper, we propose a semiotic, inductive, and approximate approach to ontology creation. We define a conceptual framework, a semantics extraction algorithm, and a first proof of concept applying the algorithm to a small set of Wikipedia documents. Intended as an extension to the prevailing top-down ontologies, we introduce an inductive fuzzy grassroots ontology, which organizes itself organically from existing natural language Web content. Using inductive and approximate reasoning to reflect the natural way in which knowledge is processed, the ontology’s bottom-up build process creates emergent semantics learned from the Web. By this means, the ontology acts as a hub for computing with words described in natural language. For Web users, the structural semantics are visualized as inductive fuzzy cognitive maps, allowing an initial form of intelligence amplification. Eventually, we present an implementation of our inductive fuzzy grassroots ontology Thus,this paper contributes an algorithm for the extraction of fuzzy grassroots ontologies from Web data by inductive fuzzy classification.