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박병선,한우상,장용이,최진숙,Park, Byoung-Sun,Han, Wou-Sang,Jang, Yong-Lee,Choi, Jin-Sook 대한불안의학회 2008 대한불안의학회지 Vol.4 No.2
Objective : This study investigated the temperament and character traits associated with suicide attempts in patients with mood disorders. Methods : The temperament and character inventory (TCI) was administered to 150 patients who visited psychiatric clinics seeking treatment for mood symptoms. The patients were divided into three groups as follows : non-suicide ideation, suicide ideation and suicide attempt. We also gathered socio-economic data in order to rule out confounding variables. MANOVA was performed to analyze differences in personal temperament and character scores on the TCI between the three groups. Results : The self-directedness and cooperativeness subscales of the TCI are most influenced by the clinical symptoms rated by Beck Suicide Ideation Scale and Hamilton Depression Rating Scale. In the temperament scale, the suicide attempt group scored higher on the novelty seeking and harm avoidance items than the other two groups. The specific temperaments associated with suicidal behavior in patients with depression are impulsivity (NS2) and anticipatory anxiety or pessimism (HA1). Conclusion : In this study, we found that more risky patients who had previously attempted suicide had a temperament of impulsivity or pessimism. This finding suggests that a more cautious approach is needed to assess mood disorder patients with impulsive or pessimistic temperaments in order to prevent suicide attempts.
박병선(Byoung Sun Park),김재협(Jae Hyup Kim) 한국컴퓨터정보학회 2015 韓國컴퓨터情報學會論文誌 Vol.20 No.12
In this paper, we propose the horizontal line detection using the Haar-like features and linear regression in infrared images. In the marine environment horizon image is very useful information on a variety of systems. In the proposed method Haar-like features it was noted that the standard deviation be calculated in real time on a static area. Based on the pixel position, calculating the standard deviation of the around area in real time and, if the reaction is to filter out the largest pixel can get the energy map of the area containing the straight horizontal line. In order to select a horizontal line of pixels from the energy map, we applied the linear regression, calculating a linear fit to the transverse horizontal line across the image to select the candidate optimal horizontal. The proposed method was carried out in a horizontal line detecting real infrared image experiment for day and night, it was confirmed the excellent detection results than the legacy methods.