• 한국석유지질학회:학술대회논문집
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• 한국석유지질학회 1998년도 제5차 학술발표회 발표논문집
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• pp.10-14
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• 1998

A systematic methodology is developed for the electrofacies determination from wireline log data using multivariate statistical analysis. To consider corresponding contribution of each log and reduce the computational dimension, multivariate logs are transformed into a single variable through principal components analysis. Resultant principal components logs are segmented using the statistical zonation method to enhance the efficiency and quality of the interpreted results. Hierarchical cluster analysis is then used to group the segments into electrofacies. Optimal number of groups is determined on the basis of the ratio of within-group variance to total variance and core data. This technique is applied to the wells in the Korea Continental Shelf. The results of field application demonstrate that the prediction of lithology based on the electrofacies classification matches well to the core and the cutting data with high reliability This methodology for electrofacies classification can be used to define the reservoir characteristics which are helpful to the reservoir management.

• 한국대기환경학회지
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• 제18권1호
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• pp.25-37
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• 2002

The purpose of the study was to survey the distribution patterns of inorganic elements of PM-10 in the various indoor environments and analyze the pollution patterns of aerosol in various places of indoor environment using a pattern recognition method based on cluster analysis and disjoint principal component analysis. A total of 40 samples in the indoor had been collected using mini-vol portable samplers. These samples were analyzed for their 19 bulk inorganic compounds such as B, Na, Mg, Al, K, Ca, Ti, V, Cr, Fe, Ni, Cu, Zn, As, Se, Cd, Ba, Ce, and Pb by using an ICP-MS. By applying a disjoint principal component analysis, four patterns of the indoor air pollutions were distinguished. The first pattern was identified as a group with high concentrations of PM-10, Na, Mg, and Ca. The second pattern was identified as a group with high concentrations B, Mg, At, Ca, Fe, Cu, and Ba. The third pattern was a group of sites with high concentrations of K, Zn. Cd. The fourth pattern was a group with low concentrations PM-10 and all inorganic elements. This methodology was found to be helpful enough to set the criteria standard of indoor air quality, corresponding pollutants, and classification of indoor environment categories when making an indoor air quality law.

• 한국자원식물학회지
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• 제19권1호
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• pp.105-111
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• 2006

대추나무에 관한 연구 및 2008년부터 시행될 산림수종의 품종보호제도에 대비하여 대추나무의 특성조사요령검정지침서(TG : Test guidelines) 작성 등에 활용할 수 있는 기초자료를 제공하고자 우리나라에서 가장 많이 재배되고 있는 대추나무 복조 등 5품종을 대상으로 과실과 엽의 형태적 특성들을 조사, 주성분분석 및 군집분석 등과 같은 다변량 분석법을 이용하여 분석 고찰한 결과, 인(仁)과 관련된 특성에서는 유의성이 인정되지 않아 대추나무의 품종간 유연관계를 고찰하는 특성으로는 부적절 한 것으로 판단된다. 과실중량을 비롯한 모든 특성들에서 보은대추 품종이 복조를 비롯한 다른 4품종과는 형태적 특성에서 명확하게 구분되는 것으로 나타났다. 주성분분석 결과, 제1주성분의 고유값은 10.45로 전체 분산에 대하여 65.3%의 기여도가 있는 것으로 분석되었으며, 고유 값이 1이상인 제3주성분까지의 전체 분산에 대한 기여도는 96.5%로 매우 높은 것으로 나타났다. 특히, 과실종경을 비롯하여 엽장과 엽병장 및 정엽장과 정엽폭, 과형지수와 핵형지수 및 정엽형지수와 같은 형태적 특성들이 대추나무 품종의 유연관계를 구명하는데 높은 기여도를 나타내는 것으로 분석되었다. 군집분석 결과, 거리수준 3.3을 기준으로 보은대추를 제외한 무등과 월출 및 금성과 복조품종이 포함된 I group과 보은대추 품종만이 포함된 II group등 크게 2개의 group으로 구분할 수 있었으며 I group은 무등과 월출 및 복조품종이 포함된 sub group과 금성 품종 등 2개의 sub group으로 다시 구분할 수 있었다.

• 한국통신학회논문지
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• 제38B권4호
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• pp.291-297
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• 2013

최근 월드 와이드 웹(World Wide Web)의 사용이 폭발적으로 증가함에 따라 다양한 정보를 포함하고 있는 웹 페이지들의 양도 엄청나게 증가 하였다. 따라서 웹상에 존재 하고 있는 웹페이지들에 대한 접근을 용이하게 하고, 그룹화를 통한 검색을 가능하게 하기 위해 웹 페이지 분류의 필요성이 대두 되고 있다. 웹 페이지 분류는 기존의 웹 상에 산재 되어 있는 웹페이지들을 비슷한 문서 유형 또는 같은 키워드를 사용하는 문서들의 묶음으로 구분하는 작업을 의미하며, 웹 페이지 분류 기술은 웹페이지 검색, 그룹 검색, 메일 필터링 등의 분야에 응용될 수 있는 기술이다. 하지만 웹상에 존재하는 웹페이지들을 사람이 수동적으로 분류하는 방법으로는 현재 월드 와이드 웹에 존재하는 엄청난 양의 웹페이지들을 처리할 수 없으며, 자동적인 분류 방법 역시 서로 다른 형태로 작성된 웹페이지들을 정확하게 분류할 수 없다는 문제로 인해 한계를 보이고 있다. 본 논문에서는 서로 다른 형태로 작성된 웹 문서들에 대한 부정확한 분류 문제를 해결하기위해 웹페이지에 존재하는 메타 정보를 획득하여 자동적으로 분류하는 메타 태그기반의 자동화된 웹페이지 분류 시스템을 제안하였다.

• Progress in Superconductivity
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• 제7권1호
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• pp.41-45
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• 2005

The diagnostic management of patients with chest pain remains a clinical challenge. Magnetocardiography (MCG) has been proposed as a new non-invasive method for detection of myocardial ischemia. To date, however, MCG technique is not intensively introduced for clinical use. One of the main reasons might be the absence of statistically valid and diagnostically clean criteria, which can determine the presence of certain heart disease. In this work, we suggested a new method to classify the diagnostic value of MCG for the detection of coronary artery disease (CAD) in patients with chest pain. MCG was recorded for three groups (healthy subjects and patients without and with CAD) by means of the 64 channel SQUID gradiometer system installed at a hospital. Using four parameters, which were found to be significantly different between groups, we evaluated a probability, in which parameters can be classified into each group based on the distribution function of the parameter in each group. For all parameters, sum of probabilities was compared between groups to determine the presence of CAD. Our classification method shows that the MCG can be a useful tool to predict the presence of CAD with sensitivity and specificity of higher than $80\%$ each.

• 한국산림과학회지
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• 제86권2호
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• pp.214-222
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• 1997

본 연구는 우리 나라 낙엽 활엽수림의 대표적인 수종인 신갈나무림을 분류하기 위하여 강원도 오대산, 점봉산 및 중왕산의 자연 식생 중에서 100개소를 조사하였으며, 식물사회학적 방법과 TWINSPAN에 의하여 군락을 분류하였다. 1. 신갈나무림을 식물사회학적 방법으로 분류하면 신갈나무-당단풍 군락군의 신갈나무-까치박달나무군락, 신갈나무-당단풍 전형 군락, 신갈나무-생강나무 군락 및 신갈나무-분비나무 군락으로 구분되었으며, 신갈나무-까치박달나무 군락은 다시 복장나무 하위 군락 및 전형 하위 군락으로 구분되었다. 2. TWINSPAN에 의하여 분류하면 신갈나무-복장나무 군락, 신갈나무-까치박달나무 군곽, 신갈나무-당단풍 군락, 신갈나무-생강나무 군락, 신갈나무-분비나무 군락으로 구분되었다. 3. 식물사회학적 방법과 TWINSPAN에 의한 군락 분류는 일치성을 보이고 있어 두 방법에 의한 군락 분류 방법은 상호 보완될 수 있다고 사료된다.

• 한국과학교육학회지
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• 제32권3호
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• pp.524-531
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• 2012

Categorization is an important human function used to process different stimuli. It is also one of the most important factors affecting measurement of a person's classification ability. Explicit categorization, the representative system by which categorization ability is measured, can verbally describe the categorization rule. The purpose of this study was to develop a prediction model for categorization ability as it relates to the classification process of living organisms using fMRI. Fifty-five participants were divided into two groups: a model generation group, comprised of twenty-seven subjects, and a model verification group, made up of twenty-eight subjects. During prediction model generation, functional connectivity was used to analyze temporal correlations between brain activation regions. A classification ability quotient (CQ) was calculated to identify the verbal categorization ability distribution of each subject. Additionally, the connectivity coefficient (CC) was calculated to quantify the functional connectivity for each subject. Hence, it was possible to generate a prediction model through regression analysis based on participants' CQ and CC values. The resultant categorization ability regression model predictor was statistically significant; however, researchers proceeded to verify its predictive ability power. In order to verify the predictive power of the developed regression model, researchers used the regression model and subjects' CC values to predict CQ values for twenty-eight subjects. Correlation between the predicted CQ values and the observed CQ values was confirmed. Results of this study suggested that explicit categorization ability differs at the brain network level of individuals. Also, the finding suggested that differences in functional connectivity between individuals reflect differences in categorization ability. Last, researchers have provided a new method for predicting an individual's categorization ability by measuring brain activation.

• Clinical Endoscopy
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• 제57권3호
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• pp.364-374
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• 2024

Background/Aims: Endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) using a 19-gauge needle is an efficient sampling method for the diagnosis of lymphadenopathy. This study compared 19-gauge conventional and Franseen needles for the diagnosis of lymphadenopathy and classification of malignant lymphoma (ML). Methods: Patient characteristics, number of needle passes, puncture route, sensitivity, specificity, and accuracy of cytology/histology for lymphadenopathy were analyzed in patients diagnosed with lymphadenopathy by EUS-FNA using conventional or Franseen needles. Results: Between 2012 and 2022, 146 patients met the inclusion criteria (conventional [n=70] and Franseen [n=76]). The median number of needle passes was significantly lower in the conventional group than in the Franseen group (3 [1-6] vs. 4 [1-6], p=0.023). There were no significant differences in cytological/ histological diagnoses between the two groups. For ML, the immunohistochemical evaluation rate, sensitivity of flow cytometry, and cytogenetic assessment were not significantly different in either group. Bleeding as adverse events (AEs) were observed in three patients in the Franseen group. Conclusions: Both the 19-gauge conventional and Franseen needles showed high accuracy in lymphadenopathy and ML classification. Considering sufficient tissue collection and the avoidance of AEs, the use of 19-gauge conventional needles seems to be a good option for the diagnosis of lymphadenopathy.

• 대한산업공학회지
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• 제39권5호
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• pp.393-402
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• 2013

The Mahalanobis-Taguchi System (MTS) is a diagnostic and predictive method for multivariate data. In the MTS, the Mahalanobis space (MS) of reference group is obtained using the standardized variables of normal data. The Mahalanobis space can be used for multi-class classification. Once this MS is established, the useful set of variables is identified to assist in the model analysis or diagnosis using orthogonal arrays and signal-to-noise ratios. And other several techniques have already been used for classification, such as linear discriminant analysis and logistic regression, decision trees, neural networks, etc. The goal of this case study is to compare the ability of the Mahalanobis-Taguchi System and logistic regression using a data set.

• 한국컴퓨터정보학회논문지
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• 제22권3호
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• pp.81-88
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• 2017

In this paper, we classified the weaknesses of C/C++ programs listed in CWE based on the diagnostic information produced at each stage of program compilation. Our classification identifies which stages should be responsible for analyzing the weaknesses. We also present algorithmic frameworks for detecting typical weaknesses belonging to the classes to demonstrate validness of our scheme. For the weaknesses that cannot be analyzed by using the diagnostic information, we separated them as a group that are often detectable by the analyses that simulate program execution, for instance, symbolic execution and abstract interpretation. We expect that classification of weaknesses, and diagnostic information accordingly, would contribute to systematic development of static analyzers that minimizes false positives and negatives.