• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.599-599
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• 2015

최근 지구온난화로 인한 기후변화로 자연재해의 형태는 점차 대형화, 다양화 되고 있는 추세이다. 이와 같이 기후변화에 의한 강도 높은 국지성 집중호우의 영향으로 막대한 인명 및 재산 피해를 주고 있으며, 이를 최소화하기 위한 대안을 마련하기 위해서는 정확한 홍수량 산정과 홍수방지 시설물들이 필요하다. 본 연구에서는 탐진강 하구부의 홍수방어계획 수립을 위해 가상의 분수로 설치 유무에 따른 수리특성을 비교 분석하고자 HEC-RAS모형과 RMA-2모형을 적용하여 모델링을 수행하였다. 먼저 1차원 수리모형인 HEC-RAS모형을 이용하여 탐진강 본류의 홍수위 저하 효과를 검토한 결과 현 상태와 비교했을 때 분수로 설치 시 홍수위가 최대 0.35m저하 되는 것으로 분석되었다. 2차원 수리모형인 RMA-2모형을 적용하기 위해 유한요소망을 구축하고 탐진강 본류 및 분수로의 흐름특성을 분석하였다. 그 결과 분수로 분류 후 탐진강 본류의 유속 및 수위가 저하되는 것으로 나타났으며, 분수로의 유속은 대체적으로 3.0m/s이하로 분석되었다. 분수로 설치 시 탐진강 본류의 홍수량이 일부 감소하나 유사이송능력도 함께 감소하여, 탐진강 하구부 하상퇴적이 예상됨으로 향후 추가적인 연구를 통해 합리적인 홍수방어계획을 제시할 예정이다.

• The Korean Journal of Applied Statistics
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• v.17 no.3
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• pp.535-545
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• 2004

The clustering method suggested in this paper produces clusters based on the 'rules of variables' by merging the 'training' and the identically structured reference data and then by filtering it to obtain the clusters of the 'training data' through the use of the 'tree classification model'. The reference dataset is generated by spatially contrasting it to the 'training data' through the 'reverse arcing' algorithm to effectively identify the clusters. The strength of this method is that it can be applied even to the mixture of continuous and discrete types of 'training data' and the performance of this algorithm is illustrated by applying it to the simulated data as well as to the actual data.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.332-332
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• 2012

강우의 시간적 분포 추정 방법에는 여러 가지가 있으나, 현재 우리나라 실무에서는 거의 Huff 4분위법을 사용하고 있다. 수공구조물 설계과정에서 시간적 분포 추정은 최대홍수량 결정을 위한 임계지속시간 산정의 선행과정으로 사용되고 있으며, 이로 인해 본래 Huff 이론과는 다르게 해석되어 사용되고 있다. 본래, Huff분포는 강우지속기간이 1일(24시간)인 경우에 적용되는 방법이었다. 물론 실제 강우의 시간분포 양상을 적절히 표현할 수만 있다면 윈래 적용되던 지속기간에만 국한시킬 것이 아니라 다른 지속기간의 시간분포에도 이용하는 것은 타당하다. 모든 호우사상을 하나의 시간분포에 맞춰 놓고 어떤 지속기간이더라도 이 시간분포 양상을 따를 것이라고 보장할 수는 없다. 4가지 분위로 분류하고 중호우와 경호우를 나누는 정도의 지엽적인 구별로 해결될 수 있는 문제가 아니다. 서로 다른 지속기간의 강우사상의 시간분포가 동일한 양상을 나타낸다고 기대하기는 어렵다. 설계강우의 지속기간 결정시 임계지속기간을 고려하는 것을 고려하면 임계지속 기간에 결정적인 영향을 미치는 강우의 시간분포에 대한 정확성의 요구는 더욱 더 커진다. 최대홍수량 산정을 위한 설계과정에서는 모든 강우지속시간을 무차원하거나 최빈분위 사용 등의 Huff 4분위법은 오히려 우리나라의 설계개념과는 맞지 않을 수 있다. 이에 본 연구에서는 우리나라 설계과정에서의 Huff 4분위법 사용의 문제점을 분석하고 그 개선방안을 제시하고자 한다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.04a
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• pp.167-170
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• 2007

동일한 집단에 속하는 개체를 다른 집단에 속하는 개체로부터 구별할 수 있는 염기의 특징을 해당 집단의 시그너쳐라고 한다. 학습 데이터는 두 집단에 속하는 염기서열들이고, 염기서열에 대한 시그너쳐는 개체를 다른 집단과 구별할 수 있는 위치의 염기들로 구성된 서열이다. 제안한 방법에서는 각 집단에 대해서 위치별로 염기의 발생빈도를 계산하고, 가장 발생빈도가 높은 염기를 결정한 다음, 다른 집단의 대응 위치에서 해당 염기의 빈도를 계산하여, 빈도차이가 지정한 분류임계값 이상이면, 해당 위치의 염기를 시그너쳐를 구성하는 특징으로 간주한다. 시그너쳐를 대한 임의의 염기서열에 대한 부합정도는 시그너쳐에 속하는 염기의 학습집단에서의 상대빈도값을 가중치로 하여 계산한다. 임의의 염기서열이 특정 집단에 속하는지 판단하기 위해서는 해당 집단의 시그너쳐에 대한 부합정도를 계산하게 되는데, 부합정도가 얼마이상이 되어야 해당 집단에 속하는 것으로 간주할지 기준이 되는 임계값을 엄밀도 임계값이라고 한다. 엄밀도 임계값은 학습 데이터 집합에 대해서 주어진 시그너쳐에 대한 엄밀도 임계값이 민감도와 특이도를 최대로 하는 것을 선택한다. 제안한 방법을 구현한 바이오인포매틱스 도구를 개발하여, 한국형 HIV-1 바이러스 시그너쳐 추출에 적용하여 분류특성이 우수한 시그너쳐를 추출할 수 있음을 확인하였다.

• Tunnel and Underground Space
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• v.18 no.4
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• pp.243-251
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• 2008

Recently, the mining methods are changing from surface mining to underground mining because of the increment of the environmental issues and legal regulations. Therefore, the stability of underground openings is a major concern for the safety and productivity of mining operations. In this paper, a survey of structural geology and discontinuities were carried out at a limestone mine. The relevant mechanical properties of rocks were determined by the laboratory tests and rock mass classifications (RMR and Q-system) for the mine design and input data for the stability analysis. The dimensions of unsupported span for underground openings and pillar were decided based on the RMR values of rock mass classifications. The stability analysis for the suggested mine design was examined through the empirical methods (stability graph method and critical span curve) and 3-D numerical analysis (Visual-FEA).

• Journal of the Korean Association of Geographic Information Studies
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• v.6 no.2
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• pp.80-91
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• 2003

In this research, re-using band ratio data was proposed and examined as a method of raising the accuracy in landcover classification which is using satellite data.In order to determine the band which is used to calculation in the classified item, the six bands except the band 6 were combined with the band in which combination is possible and the landcover classification by MLC of supervised classification was carried out. In the result of landcover classification which is combined with forty nine combination, Two bands which were mostly used by band combination in the accuracy belonged inside the 10th place of a higher rank were selected and also calculated. landcover classification were performed again after the calculation result had been recombinated from the research. In addition, the new landcover classification result was compared and examined with the landcover classification using the old data. From the result of which was compared and examined the new landcover classification data recombinated calculation result with landcover classification using the original data, The classification accuracy of the new landcover classification data recombinated calculation result became low in ground but became improved in the all class. Specially The accuracy to urban area is very improved. therefore, it determined that reusing band ratio data is very useful when we need to analyze landcover classification and land information to urban area after that.

• Korean Journal of Remote Sensing
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• v.30 no.1
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• pp.25-36
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• 2014

Multispectral image classification of individual tree species is often difficult because of the spectral similarity among species. In this study, we attempted to analyze the suitability of hyperspectral image to classify coniferous tree species. Several image sets and classification methods were applied and the classification results were compared with the ones from multispectral image. Two airborne hyperspectral images (AISA, CASI) were obtained over the study area in the Gwangneung National Forest. For the comparison, ETM+ multispectral image was simulated using hyperspectral images as to have lower spectral resolution. We also used the transformed hyperspectral data to reduce the data volume for the classification. Three supervised classification schemes (SAM, SVM, MLC) were applied to thirteen image sets. In overall, hyperspectral image provides higher accuracies than multispectral image to discriminate coniferous species. AISA-dual image, which include additional SWIR spectral bands, shows the best result as compared with other hyperspectral images that include only visible and NIR bands. Furthermore, MNF transformed hyperspectral image provided higher classification accuracies than the full-band and other band reduced data. Among three classifiers, MLC showed higher classification accuracy than SAM and SVM classifiers.

• Korean Journal of Remote Sensing
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• v.13 no.1
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• pp.47-56
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• 1997

In this paper, remote sensing is used to estimate trophic state which is primary concern in a lake. In using remote sensing, this study estimated trophic state not with conventional method such as regression equations but with classification methods. As europhication is caused by the extraodinary proliferation of the algae, chlorophyll a and transparency are applied to remote sensing data.. Maximum Likelihood Classification and Minimum Distance Classification which are kinds of classification methods enabled trophic state to be confirmed in a lake. These are obtained as the result of applying remote sensing to classify trophic state in a lake. Firest, when we evaluate tropic state in a large area of water body, the application of remote sensing data can obtain more than 70% accuracies just in using basic classification methods. Second, in the aspect of classification, the accuracy of Minimum Distance Classification is usually better than that of Maximum Likelihood Classification. This result is caused that samples have normal distribution, but their numbers are a few to apply statistical method. Therefore, classification method is required such as artificial neural networks which are not influenced by statistical distribution. Third, this study enables the trophic state of water body to be analyzed and evaluated rapidly, periodically and visibly. Also, this study is good for forming proper countermeasure accompanying with trophic state progress extent in a lake and is useful for basic-data.

• The korean journal of orthodontics
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• v.37 no.1 s.120
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• pp.29-43
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• 2007

Objective: To establish proper diagnosis and treatment plan for skeletal Class II malocclusions, some important factors to consider are the patient's skeletal morphology, prognosis as well as the treatment effects. Therefore, the present study analyzed the effects of activator treatment on different skeletal patterns in growing Class II malocclusion patients. Methods: A total of 116 patients (53 boys & 63 girls) in the experimental group were treated with the activator appliance. The experimental group was classified into either hyperdivergent or hypodivergent groups according to articular and genial angles. Results: Patients with hypodivergent growth patterns showed good effects of activator treatment. Conclusion: It seems conceivable that through classifying adolescent Class II malocclusion patients into different skeletal patterns, activator treatment effects may be predicted during the diagnosis and treatment planning stage.

• Korean Journal of Soil Science and Fertilizer
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• v.34 no.5
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• pp.342-349
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• 2001

This study was carried out to classify and evaluate the land cover map using Landsat TM data in Pyeongtaeg City. DGPS data, aerial photography, topographical map were used for selection the training sets and accuracy assessment. The overall accuracy and Kappa coefficient of the land cover classification map(using supervised classification with 13 classes) with Landsat TM data(16 June. 1997) were respectively, 86.8%, 85.4%, but the user's accuracy of urban/village and vinyl-house was below 60%, and the producer's accuracy of read and vinyl-house below 70%. Maybe it was caused the spectral reflectance characteristics, heterogeneity and small distribution area on the artificial things such as urban/village, vinyl_house and road, etc. And then, the agricultural land cover classification system using remote sensing data in Korea was to classify level I and II. Level I consisted of 5 classes such as agricultural land, forest land, water, barren land, urban and built-up land.