• Korean Journal of Culture and Social Issue
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• v.16 no.4
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• pp.447-468
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• 2010

The purpose of this study was to attain a clearer understanding of the reciprocal effects of deviant self-concept and delinquent behaviors by applying a latent state-trait autoregressive modeling approach. Although traditional autoregressive cross-lagged (ARCL) modeling has been widely applied to test the longitudinal reciprocal relationship between the two constructs, it could produce misspecified findings if there were trait-like processes involved in this relationship. The latent state-trait autoregressive(LST-AR) modeling was applied to control trait effects of deviant self-concept and to examine the reciprocal causal relations between the two constructs. Data were taken from a sample of 3,449 eighth graders who were followed annually for 5 years from the Korea Youth Panel Study. The combining LST-AR model with ARCL model substantiated the reciprocal effects of deviant self-concept and delinquent behaviors, even after the stable trait component of deviant self-concept was taken into account. The present findings shed lights on the reciprocal effects of behaviors (i.e., delinquency) and self concepts (i.e., deviant self-concept). Not only did behaviors change corresponding self-concept, but the ways adolescents perceived themselves influenced their behaviors.

• Korean Journal of Social Welfare Studies
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• v.43 no.1
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• pp.5-29
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• 2012

The present study was to explore what makes adolescents think of themselves as troublemakers even without conduct problems. It was expected that the failure to attain socio-developmental milestones(e.g., healthy relationships with others, academic achievement) would lead to form trait aspect of deviant self-concept. A latent state-trait autoregressive modeling was used to analyze five annual waves of data from 3,449 adolescents taken from the Korean Youth Panel Study. We decomposed trait and state aspect of deviant self-concept and identified significant predictors of trait-like deviant self-concept, while additionally testing for gender differences. Our results showed that conduct problems had greater effect on deviant self-concept among girls compared with boys. Conduct problem was most predictive of deviant self-concept, and yet both poor peer-relations and school failures predisposed adolescents to have deviant self-concept. Low academic achievement conferred risk for trait aspects of deviant self-concept with no gender difference, whereas poor peer relation was more predictive among girls. It highlights the cultural value system underlying self-concept and how and why adolescents think of themselves as troublemakers.

• The Transactions of the Korea Information Processing Society
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• v.7 no.8
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• pp.2555-2564
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• 2000

In this paper, a new unsupervised image segmentation algorithm is proposed. To model the contextual information presented in images, the characteristics of the Markov random fields (MRF) are utilized. Textured images are modeled as realizations of the stationary Gaussian MRF on a two-dimensional square lattice using the conditional autoregressive (CAR) equations with a second-order noncausal neighborhood. To detect boundaries, hypothesis tests over two masked areas are performed. Under the hypothesis, masked areas are assumed to belong to the same class of textures and CAR equation parameters are estimated in a minimum-mean-square-error (MMSE) sense. If the hypothesis is rejected, a measure of dissimilarity between two areas is accumulated on the rejected area. This approach produces potential edge maps. Using these maps, boundary detection can be performed, which resulting no micro edges. The performance of the proposed algorithm is evaluated by some experiments using real images as weB as synthetic ones. The experiments demonstrate that the proposed algorithm can produce satisfactorY segmentation without any a priori information.