• Journal of Korea Water Resources Association
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• v.46 no.9
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• pp.885-896
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• 2013

SEMMA (Soil Erosion Model for Mountain Areas) should be revised to apply on mountain watershed of large scale. In this study, the basic structure of original SEMMA and methods to calculate main parameters are reviewed and the revised parameters are presented to expand a range of application. SEMMA-Ic is new model revised by a rate of vegetation cover which is substituted for index of vegetation structure to use specially NDVI for large scale areas. The correlation coefficient and the Nash-Sutcliffe simulation efficiency for the revised model decreased rather than those of original model. However the evaluation of the revised model on watershed showed the approximate simulation with measured sediment yield and the underestimated simulation when sediment yield is large. The additional research for channel erosion is needed so that soil erosion model for hillslopes is used to estimate sediment yield from a watershed.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.3B
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• pp.221-232
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• 2011

Applicability of three soil erosion models for burnt hillslopes was evaluated. The models were estimated with the data from plots established after tremendous wildfire occurred in the east coastal region. Soil erosion and surface runoff were simulated by the Water Erosion Prediction Project (WEPP) and the Revised Universal Soil Loss Equation (RUSLE) of application mode for disturbed forest areas and the Soil Erosion Model for Mountain Areas (SEMMA) developed for burnt hillslopes. Simulated sediment yield and surface runoff were compared with the measured those. In maximum value of sediment yield, three models was under-predicted and RUSLE and WEPP had difference of over two times. SEMMA showed the best model response coefficient, determination coefficient and the model efficiency. In application of models to the soil erosion according to the elapsed year after wildfire, all models were underestimated in initial stage disturbed by wildfire. Evaluation of models in this burnt hillslopes was shown the tends to under-predict soil erosion for larger measured values. Although a lot of sediment can be generated in small rainfall event as fine-grained soil of the high water repellency was exposed excessively right after wildfire, this under-prediction was shown that those models have a limit to estimate the weighted factors by wildfire.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.1556-1560
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• 2006

유역 전체의 토양침식량에 대한 토사유출량의 비로 정의되는 토사유출률은 유역의 크기가 커지면 토사가 유출되는 과정에서 퇴적되거나, 저류될 수 있는 지형적인 요인이 많아지게 되어 상대적으로 감소한다. 우리나라 산불지역의 유역에 대량의 토사유출을 제어하기 위해 설치된 여러개의 사방댐을 활용하여 강우사상별 댐 저류지에 퇴적되는 토사량 측정하였다. 실측된 토사유출량과 산지사면을 대상으로 개발된 토양침식 모형인 SEMMA에 의해 예측된 토양침식량과를 비교하여 유역크기에 따른 토사유출률의 관계를 분석하였다. SEMMA는 강우에 의한 토양입자의 분리현상과 지표유출에 의한 세류와 세류간 침식에 의해 발생하는 토양침식량을 산정하지만, 구곡이나, 유역의 수로에서의 침식은 고려하지 않는다. 보편적으로 토사유출률은 1.0을 넘지 않으나, 본 연구에서는 토사유출률이 대부분 1.0을 넘는 결과를 보여 산불 지역의 유역에서는 수로발달과 수로확장에 의한 침식이 심각했다. 토사유출률이 산지 유역이 커짐에 따라 감소하는 경향은 세계의 다른 유역에서의 조사된 결과와 비슷한 결과를 보였으나, 수치적인 차이가 큼을 알 수 있었다. 또한 토사유출률은 강우사상의 크기에도 상관성이 있음이 확인되었다.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.608-612
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• 2006

산지사면에서의 토양침식량은 실제 유역을 빠져나가는 토사유출량과 같지 않다. 이는 토사가 이동하는 과정에서 지형적인 요인 등에 의해 퇴적되거나, 가중되는 유수에 의해 더 많은 토양이 침식될 수 있기 때문이다. 토사유출률(SDR)은 유역의 크기뿐만 아니라 지형, 기후, 토양, 식생피복, 토지이용도 등에 관계된다. 본 연구에서는 기후 특성인 강우크기에 따른 토사유출률의 변화를 분석하고자 하였다. 산불 이후 5년 동안 산지 소유역의 시험유역을 운영하여 유출 및 토사유출량을 실측하여 자료를 구축하였고, 이 유역에 산지지역의 토양침식 모형인 SEMMA을 적용하여 토양침식량을 산정하고 유역출구로 이송한 실제 토사유출량과 비교하였다. 5년 동안 SDR은 전반적으로 감소하고, 강우량, 강우강도, 강우에너지와 같은 강우사상의 크기에 따라 증가한다. SDR은 2001년에서 2002년까지 대부분 1.0 이상이고, 2005년에는 1.0을 초과하지 않으며, 강우특성 뿐만 아니라 식생피복, 산불시간경과 등의 인자에 의존한다.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10c
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• pp.155-158
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• 2007

현재 전자상거래는 우리의 생활과 밀접히 연관되어 있다. 최근 인터넷을 기반으로 전자조달, 수출입 브로커 등과 같은 유형의 B2B 전자상거래가 활발히 이루어지고 있으며, 소비자를 대상으로 하는 전자상거래 또한 점차 확산되는 시장을 형성하고 있다. 국제적으로도 전자상거래 시장 규모가 급속도로 증가할 것이라는 전망은 자명한 사실이다. 전자상거래에 대한 의존도가 높아지면서 관리해야 하는 데이터의 양 또한 급속도로 증가하고 있다. 본 논문에서는 실시간으로 유입되는 데이터를 효율적으로 활용하기 위챈 실시간 데이터 마이닝 활용 모델을 제안한다. 이 실시간 데이터 마이닝 모델은 지속적으로 유입되는 데이터의 규칙화를 통해 저장 공간의 효율성을 극대화하고 중요도 분석을 통한 총체적인 접근 방법을 시도함으로써 전자상거래 상에서 유용하게 쓰일 수 있는 활용 모델이다. 이 실시간 데이터 마이닝 모델의 바탕은 데이터 마이닝의 기법인 SEMMA를 따르며, 그 특징에 따라 규칙 추출과 의사 결정 나무 기법을 이용하여 전자상거래 상에서 유용하게 사용될 수 있는 모델을 제시하고자 한다.

• Bulletin of the Korean Chemical Society
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• v.30 no.4
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• pp.781-782
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• 2009

• Journal of Digital Convergence
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• v.18 no.8
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• pp.225-230
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• 2020

The KBO League is held over a long period of time due to the large number of games. Also, Korea has a diverse and distinct climate. Therefore, this study analyzed the relationship between the daily average temperature and the record of batting power such as home runs, triples, doubles, number of bases, batting percentage, and net batting percentage, and a third baseball record was defined. For this study, the correlation between the daily average temperature data and the batter who entered the standard at-bat in the KBO League in 2019 was analyzed through the SEMMA method. From the results of this study, it was found that the average daily temperature had an effect on a batter's hitting power. In particular, it was found that a batter's hitting power decreased on the day of temperatures recorded between 20.0 degrees and 24.9 degrees, and it was discussed that this may have been related to the physical condition of the pitcher the batter was facing. Therefore, it can be expected that players, coaching staff, and the front desk can use them in the game through conditions outside the game. In addition, it is expected that it will be a more useful analysis model by analyzing the records of pitching, base running, and defense as well as subsequent batting records.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1343-1346
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• 2005

In the cold rolling mill, coil breakage that generated in rolling process makes the various types of troubles such as the degradation of productivity and the damage of equipment. Recent researches were done by the mechanical analysis such as the analysis of roll chattering or strip inclining and the prevention of breakage that detects the crack of coil. But they could cover some kind of breakages. The prediction of Coil breakage was very complicated and occurred rarely. We propose to build effective prediction modes for coil breakage in rolling process, based on data mining model. We proposed three prediction models for coil breakage: (1) decision tree based model, (2) regression based model and (3) neural network based model. To reduce model parameters, we selected important variables related to the occurrence of coil breakage from the attributes of coil setup by using the methods such as decision tree, variable selection and the choice of domain experts. We developed these prediction models and chose the best model among them using SEMMA process that proposed in SAS E-miner environment. We estimated model accuracy by scoring the prediction model with the posterior probability. We also have developed a software tool to analyze the data and generate the proposed prediction models either automatically and in a user-driven manner. It also has an effective visualization feature that is based on PCA (Principle Component Analysis).

• Journal of Preventive Medicine and Public Health
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• v.39 no.5
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• pp.433-437
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• 2006

Objectives: The aim of this study is to develop a methodology for estimating a nationwide statistic for hernia operations with using the claim database of the Korea Health Insurance Cooperation (KHIC). Methods: According to the insurance claim procedures, the claim database was divided into the electronic data interchange database (EDI_DB) and the sheet database (Paper_DB). Although the EDI_DB has operation and management codes showing the facts and kinds of operations, the Paper_DB doesn't. Using the hernia matched management code in the EDI_DB, the cases of hernia surgery were extracted. For drawing the potential cases from the Paper_DB, which doesn't have the code, the predictive model was developed using the data mining technique called SEMMA. The claim sheets of the cases that showed a predictive probability of an operation over the threshold, as was decided by the ROC curve, were identified in order to get the positive predictive value as an index of usefulness for the predictive model. Results: Of the claim databases in 2004, 14,386 cases had hernia related management codes with using the EDI system. For fitting the models with applying the data mining technique, logistic regression was chosen rather than the neural network method or the decision tree method. From the Paper_DB, 1,019 cases were extracted as potential cases. Direct review of the sheets of the extracted cases showed that the positive predictive value was 95.3%. Conclusions: The results suggested that applying the data mining technique to the claim database in the KHIC for estimating the nationwide surgical statistics would be useful from the aspect of execution and cost-effectiveness.