http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
이해준,최상묵,정종평,Lee, Hae-Joon,Choi, Sang-Mook,Chung, Chong-Pyoung 대한치주과학회 1993 Journal of Periodontal & Implant Science Vol.23 No.1
Refractory periodontitis manifest progressive attachment loss in a rapid and unrelenting manner regardless of the type or frequency of therapy applied. The purpose of this study was ta evaluate the relation between the level of cytokines in GCF and periodontopathic microflora with disease activity of refractory periodontitis. Selection of patients with refractory periodontitis (7 males, 3 females) were made by long term clinical observation including conventional clinical history and parameters. Teeth that showed pocket depth greater than 6mm were selected as sample teeth. Subjects were examined at baseline and after 3 months. Prior to baseline test, individual acrylic stent was fabricated. Reference grooves were made on each sample tooth site. Pocket depth and attachment loss were measured by Florida Probe. Gingival index was measured at 4 sites each sample teeth. Disease activity was defined as attachment loss of ${\ge}$ 2.1mm, as determined by sequential probing and tolerance method. The pattern and amount of alveolar bone resorption was observed with quantitative digital subtraction image processing radiography. Morphological analysis of subgingival bacteria was taken by phase contrast microscopy. Predominant cultivable bacterial distribution and frequency were compared between disease-active and disease-inactive site using immunofluorescence microscopy and selective microbial culturing. Levels of $interleukin-l{\beta}$, 2, 4, 6 and $TNF-{\alpha}$ in GCF and blood serum sample were quantified by ELISA. In active sites, P. intermedia was significantly increased to compare with inactive site. $IL-1{\beta}$, IL-2, IL-6 and $TNF-{\alpha}$ in GCF were increased in active sites and IL-2 in serum was increased in active patients significantly. Alveolar bone loss in active site was correlated with $IL-1{\beta}$, IL-2 in GCF. And loss of attachment in active site was correlated with IL-2 in GCF. These results demonstrate that IL-2 in serum, $IL-1{\beta}$, IL-2, IL-6 and $TNF-{\alpha}$ in GCF, P, intermedia might be used as possible predictors of disease activity in refractory periodontitis before it is clinically expressed as attachment loss and quantitative alveolar bone change.
이해준,Lee, Hae-Jun 한국정보통신학회 2019 한국정보통신학회논문지 Vol.23 No.5
소형인공위성 전력시스템체계 설계 및 개발방법은 태양풍 자계인 우주환경의 영향에 따라 기술적 제약이 큰 편이다. 이를 극복하기 위해 최근 전력모듈을 융합화와 유닛화 단계별 개발 방식으로 변화 하고 있다. 모듈화 단계에서는 탑재체 전력공급 모듈 요구조건과 함께 유니버설미들웨어를 사용하여 융합하였다. 융합모듈화대상은 탑재체에서 전력분배, 부하관리, 서브유닛의 전원공급체계와 지속성을 고려한 최종모듈 설계 및 개발 단계를 범위로 한다. 본 연구는 위성본체에서 공급되는 전력모듈을 유니버설미들웨어 기반으로 전력모듈의 정밀성과 수요처모듈데이터를 컨텐츠화 하였다. 이 동적시스템과 전력서비스 모듈화는 전력분배모듈과 전원공급모듈간 상호작용으로 Range Control 알고리즘으로 제어된다. 그리하여 전력모듈 설계단계에서 탑재체 전력수요 변수의 변동성에 따른 불확실성을 해소하고 설계의 효율성을 제시하였다. A Small-Sat Power System Design and Development should be depend on space environment such as solar wind with Electromagnetic field by hurdle of techniques. It is surmount solution of trend that will unitize and converge with power module in these days. The level of modularize means that applying Universal Middleware for payload power module requirements. The scope of target system is a main power provider module and operational subunit that can be implemented with the final power module distribution loads to consume for continuous process. A Universal Middleware strengthen to build power module from satellite power system should be accuracy and consuming data. A Power Service Module and dynamic system drive interactive management between power distribution and consumer module by Range Control. Consequently, suggesting evaluation, unexpecting payload system power consumer that makes fine variable resources in the development design process and efficiency.
동적신경망 NARX 기반의 SAR 전력모듈 안전성 연구
이해준,Lee, Hae-Jun 한국정보통신학회 2020 한국정보통신학회논문지 Vol.24 No.6
소형위성 전력분배 및 전송모듈의 설계와 개발과정에서 딥러닝 알고리즘으로 동적 전력자원의 안정성을 평가하였다. 안정성 평가에 따른 요구사항은 소형위성 탑재체인 SAR 레이더의 전력분배모듈과 수요모듈의 전력전송기능을 구성하였다. 전력모듈인 PDM을 구성하는 스위칭 전력부품의 성능확인을 위해 동적신경망을 활용하여 신뢰성을 검증하였다. 신뢰성 검증을 위한 딥러닝 적용대상은 소형위성 본체로부터 공급되는 전력에 대한 탑재체의 전력분배기능이다. 이 기능에 대한 성능확인을 위한 모델링 대상은 출력전압변화추이(Slew Rate Control), 전압오류(Voltage Error), 부하특성(Load Power)이다. 이를 위해 첫째, 모델링으로 Coefficient Structure 영역을 정의하고 PCB모듈을 제작하여 안정성과 신뢰성을 비교 평가하였다. 둘째, 딥러닝 알고리즘으로 Levenberg-Marquare기반의 Two-Way NARX신경망 Sigmoid Transfer를 사용하였다. In the design and development process of Small-Sat power distribution and transmission module, the stability of dynamic resources was evaluated by a deep learning algorithm. The requirements for the stability evaluation consisted of the power distribution function of the power distribution module and demand module to the SAR radar in Small-Sat. To verify the performance of the switching power components constituting the power module PDM, the reliability was verified using a dynamic neural network. The adoption material of deep learning for reliability verification is the power distribution function of the payload to the power supplied from the small satellite main body. Modeling targets for verifying the performance of this function are output voltage (slew rate control), voltage error, and load power characteristics. First, to this end, the Coefficient Structure area was defined by modeling, and PCB modules were fabricated to compare stability and reliability. Second, Levenberg-Marquare based Two-Way NARX neural network Sigmoid Transfer was used as a deep learning algorithm.