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RISS 인기검색어
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- 저자 : 김동균(Kim, Donggiun) (검색결과 596 건)
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김동균,이승진,정종평,Kim, Dong-Kyun,Lee, Seung-Jin,Chung, Chong-Pyoung 대한치주과학회 1995 Journal of Periodontal & Implant Science Vol.25 No.2
The purpose of this study was to evaluate drug-loaded biodegradable membranes for guided tissue regeneration(GTR). The membranes were made by coating mesh of polyglycolic acid(PGA) with polylactic acid(PLA) containing 10% flurbiprofen or tetracycline. The thickness of membrane was $150{\pm}30{\mu}m$, and the pore size of surface was about $8{\mu}m$ in diameter. The release of drugs from the membrane was measured in vitro. Cytotoxity test for the membrane was performed by gingival fibroblast cell culture, and the tissue response was observed after implant of membrane into the dorsal skin of the rat for 8 wks. Ability to guided tissue regeneration of membranes were tested by measuring new bone in the calvarial defects(5mm in diameter) of the rat for 5 weeks. The amount of flurbiprofen and tetracycline released from membrane were about 30-60% during 7 days. Minimal cytotoxity was observed in the membrane except 20% drug containing membrane. In histologic finding of rat dorsal skin, many inflammatory cells were observed around e-PTFE, polyglactin 910 and PLAPGA membrane after 1 or 2 weeks. PLA-PGA membrane was perforated by connective tissue after 4 or 6 weeks, and divided as a segment at 8 weeks. In bone regeneration guiding potential test, tetracycline loaded membrane was most effective (p<O.O5). In histologic finding of rat calvaria, new bone formation was greater in defects covered by membrane than in defects uncovered. Tetracycline loaded membrane might be a useful barrier for GTR in periodontal treatment.
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수종의 성분해성 차폐막의 생체분해도 및 조직 재생유도 능력에 관한 연구
김동균,구영,이용무,정종평,Kim, Dong-Kyun,Ku, Young,Lee, Young-Moo,Chung, Chong-Pyoung 대한치주과학회 1997 Journal of Periodontal & Implant Science Vol.27 No.1
The purpose of this study was to evaluate on the biodegradability, biocompatibility and tissue regenerative capacity of synthetic biodegradable $mernbranes-Resolut^{(R)}$, $Guidor^{(R)}$ and $Biomesh^{(R)}$. To evaluate the cell attachment on the membranes, in vitro, the number of gingival fibroblasts attached to each membrane was counted by hemocytometer. Cytotoxicity test for the membranes was performed by MTT test with gingival fibroblast For evaluation of guided- bone regenerative potential, the amount of new bone formation in the rat calvarial defects(5mm in diameter) beneath the membranes was observed for two weeks and examined of the specimens by Massons trichrome staining. Biodegradability was observed for 2, 4, 8 and 12 weeks after implantation of each materials under the skin of rats and examined the specimens with H & E staining. The number of cell attachment were the greatest in $Biomesh^{(R)}$ and followed by $Resolut^{(R)}$. Cell viability of three membranes was almost similar levels. Biodegradability of $Resolut^{(R)}$ was the highest among three membrane and the potential of guided bone regeneration was the greatest in the $Biomesh^{(R)}$ and $Resolut^{(R)}$ was followed. These results suggested that commercially available biodegradable membranes were non-toxic and highly potential to guided bone regeneration.
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김동균,최정석,Kim, Donggyun,Choi, Jung-Suk 해양환경안전학회 2021 해양환경안전학회지 Vol.27 No.5
해운 시황을 예측하는 것은 중요한 문제이다. 투자 방식의 결정, 선대 편성 방법, 운임 등을 결정하기 위한 판단 근거가 되며 이는 기업의 이익과 생존에 큰 영향을 미치기 때문이다. 이를 위해 본 연구에서는 기계학습 모델인 장단기 메모리 및 간소화된 장단기 메모리 구조의 Gated Recurrent Units를 활용하여 컨테이너선의 해상운임 예측 모델을 제안한다. 운임 예측 대상은 중국 컨테이너 운임지수(CCFI)이며, 2003년 3월부터 2020년 5월까지의 CCFI 데이터를 학습에 사용하였다. 각 모델에 따라 2020년 6월 이후의 CCFI를 예측한 후 실제 CCFI와 비교, 분석하였다. 실험 모델은 하이퍼 파라메터의 설정에 따라 총 6개의 모델을 설계하였다. 또한 전통적인 분석 방법과의 성능을 비교하기 위해 ARIMA 모델도 실험에 추가하였다. 최적 모델은 두 가지 방법에 따라 선정하였다. 첫 번째 방법으로 각 모델을 10회 반복 실험하여 얻은 RMSE의 평균값이 가장 작은 모델을 선정하는 것이다. 두 번째 방법으로는 모든 실험에서 가장 낮은 RMSE를 기록한 모델을 선정하는 것이다. 실험 결과 전통적 시계열 예측모델인 ARIMA 모델과 비교하여 딥러닝 모델의 정확도를 입증하였으며, 정확한 예측모델을 통해 운임 변동의 위험관리 능력을 제고시키는데 기여했다. 반면 코로나19와 같은 외부 효과에 따른 운임의 급격한 변화상황이 발생한 경우, 예측모델의 정확도가 감소하는 한계점을 나타냈다. 제안된 모델 중 GRU1 모델이 두 가지 평가 방법 모두에서 가장 낮은 RMSE(69.55, 49.35)를 기록하며 최적 모델로 선정되었다. Predicting shipping markets is an important issue. Such predictions form the basis for decisions on investment methods, fleet formation methods, freight rates, etc., which greatly affect the profits and survival of a company. To this end, in this study, we propose a shipping freight rate prediction model for container ships using gated recurrent units (GRUs) and long short-term memory structure. The target of our freight rate prediction is the China Container Freight Index (CCFI), and CCFI data from March 2003 to May 2020 were used for training. The CCFI after June 2020 was first predicted according to each model and then compared and analyzed with the actual CCFI. For the experimental model, a total of six models were designed according to the hyperparameter settings. Additionally, the ARIMA model was included in the experiment for performance comparison with the traditional analysis method. The optimal model was selected based on two evaluation methods. The first evaluation method selects the model with the smallest average value of the root mean square error (RMSE) obtained by repeating each model 10 times. The second method selects the model with the lowest RMSE in all experiments. The experimental results revealed not only the improved accuracy of the deep learning model compared to the traditional time series prediction model, ARIMA, but also the contribution in enhancing the risk management ability of freight fluctuations through deep learning models. On the contrary, in the event of sudden changes in freight owing to the effects of external factors such as the Covid-19 pandemic, the accuracy of the forecasting model reduced. The GRU1 model recorded the lowest RMSE (69.55, 49.35) in both evaluation methods, and it was selected as the optimal model.
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극한수문사상의 모의를 위한 포아송 클러스터 강우생성모형의 적용성 평가
김동균,권현한,황석환,김태웅,Kim, Dong-Kyun,Kwon, Hyun-Han,Hwang, Seok Hwan,Kim, Tae-Woong 대한토목학회 2014 대한토목학회논문집 Vol.34 No.3
This study evaluated the applicability of the Modified Bartlett-Lewis Rectangular Pulse (MBLRP) rainfall generation model for modeling extreme rainfalls and floods in Korean Peninsula. Firstly, using the ISPSO (Isolated Species Particle Swarm Optimization) method, the parameters of the MBLRP model were estimated at the 61 ASOS (Automatic Surface Observation System) rain gauges located across Korean Peninsula. Then, the synthetic rainfall time series with the length of 100 years were generated using the MBLRP model for each of the rain gauges. Finally, design rainfalls and design floods with various recurrence intervals were estimated based on the generated synthetic rainfall time series, which were compared to the values based on the observed rainfall time series. The results of the comparison indicate that the design rainfalls based on the synthetic rainfall time series were smaller than the ones based on the observation by 20% to 42%. The amount of underestimation increased with the increase of return period. In case of the design floods, the degree of underestimation was 31% to 50%, which increases along with the return period of flood and the curve number of basin. 본 연구는 우리나라의 극한강우와 극한홍수를 모의하기 위한 MBLRP 포아송 클러스터 강우생성모형의 적용성을 평가하였다. 국내 61개의 기상청 지상기상관측시스템의 강우량 관측지점에 대하여 고립입자 군집화 최적화(ISPSO) 기법을 적용하여 모형의 매개변수를 추정하고, 추정된 매개변수를 바탕으로 각 강우관측지점에서 100년치의 가상 강우시계열을 생성하였다. 생성된 강우시계열을 이용하여 확률강우량 및 확률홍수량을 산정하고 이 값들을 관측치에 근거하여 산정된 값들과 비교하였다. 비교 결과, 모형에 의한 확률강우량은 관측치보다 평균적으로 20~42% 작았으며, 강우의 재현기간이 증가할수록 과소산정되는 정도가 증가하였다. 확률홍수량의 경우, 모형에 의한 값이 관측치에 근거한 값보다 31%에서 50% 작았으며, 이 과소산정량은 홍수의 재현기간의 증가 및 유역의 불투수도의 증가와 함께 증가하였다.
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신용카드사의 가맹점 서비스품질 결정요인에 관한 탐색적 연구
김동균,Kim Dong-Gyoon 대한경영정보학회 1998 경영과 정보연구 Vol.2 No.-
This exploratory study examines critical quality factors of store that can give access to credit card. The procedures of developing instrument is followed by recommendations on the developing measures of marketing constructs. The results shows that service quality of store available for credit card is divided four dimensions(personal service, payment-approving service, information-providing service, problem responsiveness service). These dimensions and scales are verified through the assessment of reliability and validity. Finally, the importance of personal service is showed to be different across types of industry.
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