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김익환,김창용,김경희,허준영,옥수민,정성희,안용우,고명연,Kim, Ik-Hwan,Kim, Chang-Yong,Kim, Kyung-Hee,Huh, Joon-Young,Ok, Soo-Min,Jeong, Sung-Hee,Ahn, Yong-Woo,Ko, Myung-Yun 대한안면통증구강내과학회 2011 Journal of Oral Medicine and Pain Vol.36 No.4
Personal characteristics of female lichen planus patients were analyzed psychologically using the SCL-90-R. The subjects were 51 female lichen planus patients who visited Orofacial pain clinic of the Department of Oral Medicine, Pusan National University Yangsan Dental Hospital from 2009 to 2010. The female control group were collected from Pusan Kyungnam area. 45 female burning mouth syndrome patients, 36 female temporomandibular joint disorder patients, 23 female trigeminal neuralgia patients were subjected at Orofacial pain clinic of the Department of Oral Medicine, Pusan National University Hospital from 1998 to 2010. 1. Lichen planus patients group, burning mouth syndrome patient group, temporomandibular joint disorder patients group, trigeminal neuralgia patients group and the control group were within normal range. 2. The T-Scores of O-C, IS, DEP, ANX, HOS, PHOB in lichen planus patients group were significantly higher than in the control group. 3. The T-Scores of O-C, IS, DEP, ANX, PAR, PSY in chronic group was significantly higher than in acute group. 4. The T-Scores of SOM, O-C, DEP, ANX, in burning mouth syndrome patients group was significantly higher than in lichen planus patient group. 5. There was no significant T-score difference between lichen planus group and temporomandibular joint disorder patient group. 6. There was no significant T-score difference between lichen planus group and trigeminal neuralgia patient group.
안드로이드 플랫폼에서 유연한 응용프로그램 권한관리 기법 설계 및 구현
김익환,김태현,Kim, Ik-Hwan,Kim, Tae-Hyoun 한국정보처리학회 2011 정보처리학회논문지 C : 정보통신,정보보안 Vol.18 No.3
대표적인 스마트폰 플랫폼의 하나인 구글 안드로이드는 응용프로그램 권한기반 보안모델을 채택하고 있다. 이는 응용프로그램의 시스템 자원에 대한 부적절한 접근을 제한하여 보안위협을 줄이기 위한 방법이지만 권한의 선택적 허용이 불가능한 점, 한번 권한이 부여된 경우 이를 되돌릴 수 없는 점, 사용자 ID 공유에 따른 권한의 공유를 사용자가 알 수 없는 점 등 문제점이 존재한다. 본 연구에서는 기존 안드로이드 보안 모델의 한계점을 개선하기 위해 사용자가 응용프로그램이 요구하는 권한을 유연하게 설정할 수 있는 기법을 설계, 구현하였다. 본 연구에서 제안한 기법의 설계목표는 기존 보안모델의 수정을 최소화하면서 보안성과 사용자 편의성을 향상하는 것이며, 구현된 기법의 동작 검증은 안드로이드 에뮬레이터 상에서 실제 응용프로그램 수행을 통해 이루어졌다. Google Android, which is one of the popular smart phone platforms, employs a security model based on application permissions. This model intends to reduce security threats by protecting inappropriate accesses to system resources from applications, but this model has a few problems. First, permission requested by an application cannot be granted selectively. Second, once the permission has been granted it is maintained until the application is uninstalled. Third, applications may acquire powerful permissions through user ID sharing without any notice to users. In order to overcome these limitations, we designed and implemented a flexible application permission management scheme. The goal of our scheme is to enhance security and user convenience while keeping compatibility to original platform. We also verified the operation of our scheme with real applications on Android emulator.
인공지능을 활용한 액적 이미지 경계특성에 따른 접촉각 예측 정확도 분석
김익환(Ik Hwan Kim),강현욱(Hyun Wook Kang) 대한기계학회 2022 대한기계학회 춘추학술대회 Vol.2022 No.11
In various industries, wettability analysis of a solid surface is essential to determine the surface energy. A contact angle is a tangential angle for a liquid interface at the intersection of droplets on a solid surface in the environment. General methods for measuring contact angle at the contact point have been developed to accurately use a goniometer and image processing software to find the border of the sessile droplet on aligned and fixed lighting with a camera system. However, extracting the exact three-phase contact point is difficult due to the light scattering on droplets and an out-of-focused images by human error. To overcome these errors, we suggest a convolutional neural network model predict contact angle from the preprocessed sessile droplet images. The trained model analyzes the experimental droplet images depending on the contact angle and defines the three-phase contact point through pixel distribution. The developed model performance shows 2.67% of the mean absolute percentage error at the contact angle range of 20° to 160°.
인공지능을 활용한 액적 이미지 경계특성에 따른 접촉각 예측 정확도 분석
김익환(Ik Hwan Kim),강현욱(Hyun Wook Kang) 대한기계학회 2022 대한기계학회 춘추학술대회 Vol.2022 No.11
In various industries, wettability analysis of a solid surface is essential to determine the surface energy. A contact angle is a tangential angle for a liquid interface at the intersection of droplets on a solid surface in the environment. General methods for measuring contact angle at the contact point have been developed to accurately use a goniometer and image processing software to find the border of the sessile droplet on aligned and fixed lighting with a camera system. However, extracting the exact three-phase contact point is difficult due to the light scattering on droplets and an out-of-focused images by human error. To overcome these errors, we suggest a convolutional neural network model predict contact angle from the preprocessed sessile droplet images. The trained model analyzes the experimental droplet images depending on the contact angle and defines the three-phase contact point through pixel distribution. The developed model performance shows 2.67% of the mean absolute percentage error at the contact angle range of 20° to 160°.