• 한국치위생학회지
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• 제13권3호
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• pp.475-480
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• 2013

Objectives : The aim of this study was to analyze self-perceived oral malodor symptoms and associated factors among adults in metropolitan area. Methods : This research was based on self-perceived oral malodor symptoms survey in 413 adults from March 5 to May 7, 2012. Data were analyzed with chi-square test, and stepwise multiple regression analysis using SPSS WIN 12.0 program and significance level was set at p<0.05. Results : The prevalence rate of self-perceived oral malodor symptoms was 62.7%. The most influencing factors of self-perceived oral malodor symptoms was age. The other factors were self-perception stress level, exercise, and periodontitis in the order. Conclusions : In order to reduce self-perceived oral malodor symptoms, it is necessary to maintain mental and physical soundness basically.

• 한국철도학회:학술대회논문집
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• 한국철도학회 1998년도 추계학술대회 논문집
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• pp.379-387
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• 1998

HVAC systems are used to maintain comfort conditions in occupied spaces. Like rolling noise and aerodynamic noise, noise from the HVAC system of train increases interior noise level. For an appropriate interior noise level, it is necessary not to find noise sources and their propagation paths. Noise emission from the sources and propagation through the propagation paths should be regulated in order to reduce their effect to the interior noise level. In general, the main noise source in the HVAC system is blower which operates at high static pressure. This noise propagates through ducts which are directly connected to the residential area. Since the blower noise can be reduced only to some degree, it is necessary for the propagation paths to have enough noise attenuation. Acoustic properties of ducts are usually found by experimental methods but it is rather difficult and expensive to set up such test equipments. In this thesis, the design and the noise characteristics of TGV-K HVAC system are studied. Finite element method in accordance with experimental method is used to study the acoustic properties of TGV-K duct system.

• 한국안전학회지
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• 제35권2호
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• pp.28-33
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• 2020

Recently, the overseas construction market has been actively promoted for about 10 years, and overseas dam construction has been continuously performed. For the economic and safe construction of the dam, it is important to prepare the main dam construction plan considering the design frequency of the diversion tunnel and the cofferdam. In this respect, the prediction of river level during the rainy season is significant. Since most of the overseas dam construction sites are located in areas with poor infrastructure, the most efficient and economic method to predict the water level in dam construction is to use the upstream water level. In this study, a linear regression model, which is one of the simplest statistical methods, was proposed and examined to predict the downstream level from the upstream level. The Pyeongchang River basin, which has the characteristics of the upper stream (mountain stream), was selected as the target site and the observed water level in Pyeongchang and Panwoon gaging station were used. A regression equation was developed using the water level data set from August 22th to 27th, 2017, and its applicability was tested using the water level data set from August 28th to September 1st, 2018. The dependent variable was selected as the "level difference between two stations," and the independent variable was selected as "the level of water level in Pyeongchang station two hours ago" and the "water level change rate in Pyeongchang station (m/hr)". In addition, the accuracy of the developed equation was checked by using the regression statistics of Root Mean Square Error (RMSE), Adjusted Coefficient of Determination (ACD), and Nach Sutcliffe efficiency Coefficient (NSEC). As a result, the statistical value of the linear regression model was very high, so the downstream water level prediction using the upstream water level was examined in a highly reliable way. In addition, the results of the application of the water level change rate (m/hr) to the regression equation show that although the increase of the statistical value is not large, it is effective to reduce the water level error in the rapid level rise section. Accordingly, this is a significant advantage in estimating the evacuation water level during main dam construction to secure safety in construction site.

• Asian Pacific Journal of Cancer Prevention
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• 제17권2호
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• pp.835-838
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• 2016

Background: Lung cancer remains one of the most common cancers in the world, both in terms of new cases (about 13% of total per year) and deaths (nearly one cancer death in five), because of the high case fatality. Errors in lung cancer type or malignant growth determination lead to degraded treatment efficacy, because anticancer strategy depends on tumor morphology. Materials and Methods: We have made an attempt to evaluate effectiveness of machine learning algorithms in the task of lung cancer classification based on gene expression levels. We processed four publicly available data sets. The Dana-Farber Cancer Institute data set contains 203 samples and the task was to classify four cancer types and sound tissue samples. With the University of Michigan data set of 96 samples, the task was to execute a binary classification of adenocarcinoma and non-neoplastic tissues. The University of Toronto data set contains 39 samples and the task was to detect recurrence, while with the Brigham and Women's Hospital data set of 181 samples it was to make a binary classification of malignant pleural mesothelioma and adenocarcinoma. We used the k-nearest neighbor algorithm (k=1, k=5, k=10), naive Bayes classifier with assumption of both a normal distribution of attributes and a distribution through histograms, support vector machine and C4.5 decision tree. Effectiveness of machine learning algorithms was evaluated with the Matthews correlation coefficient. Results: The support vector machine method showed best results among data sets from the Dana-Farber Cancer Institute and Brigham and Women's Hospital. All algorithms with the exception of the C4.5 decision tree showed maximum potential effectiveness in the University of Michigan data set. However, the C4.5 decision tree showed best results for the University of Toronto data set. Conclusions: Machine learning algorithms can be used for lung cancer morphology classification and similar tasks based on gene expression level evaluation.

• 한국안전학회지
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• 제24권5호
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• pp.34-42
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• 2009

There are many accident causes related to even an accident. As well four(4) stepped causes of one accident at construction sites are analyzed in the study. First, eleven(11) cause factors are set up at each step such as policy level, management, indirect, direct level which are discussed and determined by field experts with 15year experience or more. Therefore, one direct cause occurred in construction site can be connected to the previous cause than in direct and management, and policy problem of previous management. These questionnaires results are analyzed with three different methods such as weighing level by Delphi technique, correlation analysis, critical pass method. Three different methods show their characteristic to see which subcontract work is more dangerous or not. Subcontract or at a construction site can be use the above three different cases as they need at their site in order to make more effective countermeasures.

• 대한전자공학회논문지SD
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• 제48권9호
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• pp.50-57
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• 2011

전형적인 버스 시스템 아키텍처는 마스터, 아비터, 디코더, 슬레이브와 같은 성분으로 구성되어 있다. 아비터는 여러 마스터가 동시에 버스를 사용하지 못하므로 선택된 버스중재 방식에 따라 버스를 중재하는 역할을 한다. 고성능을 위해 사용되는 일반적인 우선순위 방법에는 고정 우선순위, 라운드 로빈, TDMA, 로터리 방식 등이 있다. 일반적인 버스 중재 알고리즘은 버스 점유율을 고려하지 않고, 버스중재를 실시한다. 본 연구에서는 각각의 마스터 블록에서 버스 점유율을 계산한 버스 중재방식에 대해 제안하고 있다. TLM 성능분석 방식을 통해 제안하는 방식과 기존의 다른 버스 중재방식의 성능을 분석하였다. 성능검증 결과에서 일반적인 고정우선순위와 라운드로빈 방식은 버스점유율을 설정할 수 없었으며, TDMA와 로터리 중재방법은 100,000 cycle의 시뮬레이션에서 각각 50%와 70%의 버스점유율 오차가 발생하였다. 그러나, 제안하는 점유율 고려방식에서는 1,000cycle이상에서부터 99%이상 정확도를 보였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.1302-1306
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• 2004

This paper proposes a model for information filtering (IF) on the Web. The user information need is described into two levels in this model: profiles on category level, and Boolean queries on document level. To efficiently estimate the relevance between the user information need and documents by fuzzy, the user information need is treated as a rough set on the space of documents. The rough set decision theory is used to classify the new documents according to the user information need. In return for this, the new documents are divided into three parts: positive region, boundary region, and negative region. We modified user profile by the user's relevance feedback and discerning words in the documents. In experimental we compared the results of three methods, firstly is to search documents that are not passed the filtering system. Second, search documents that passed the filtering system. Lastly, search documents after modified user profile. The result from using these techniques can obtain higher precision.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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• pp.610-614
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• 2006

In this paper the advanced method of geodesic active contours was developed for the task of building detection from aerial and satellite images. Automatic extraction of man-made structures including buildings, building blocks or roads from remote sensing data is useful for land use mapping, scene understanding, robotic navigation, image retrieval, surveillance, emergency management procedures, cadastral etc. A level set method based on a region-driven segmentation model was implemented with which building boundaries were detected, through this curve propagation technique. The essence of this approach is to optimize the position and the geometric form of the curve by measuring information along that curve, and within the regions that compose the image partition. To this end, one can consider uniform intensities inside objects and the background. Thus, given an initial position of the curve, one can determine global, region-driven functions and provide a statistical description of the inside and outside object area. The calculus of variations and a gradient descent method was used to optimize the variational functional by an iterative steady state process. Experimental results demonstrate the potential of the proposed processing scheme.

• Communications for Statistical Applications and Methods
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• 제16권5호
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• pp.781-790
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• 2009

본 논문에서는 퍼지수를 포함한 모수적 회귀모형을 추정하기 위하여 분포무관추정량으로 알려진 순위 변환방법과 Theil 방법을 소개한다. 순위 변환방법은 퍼지수의 ${\alpha}$-수준집합의 중심과 폭에 대한 순위를 이용하고 Theil 방법은 ${\alpha}$-수준집합의 중심과 폭에 대한 추정한 값들의 중위수를 이용한다. 예제를 이용하여 분포무관추정량으로 추정된 퍼지회귀모형의 효율성을 최소자승법과 여러 가지 방법으로 추정된 퍼지회귀모형과 비교한다.

• 한국항공우주학회지
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• 제44권7호
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• pp.593-602
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• 2016

본 연구에서는 근접연계방식의 초음속기체 금속분말 미립화장치에 대한 수치해석을 수행하였다. 액체금속의 미립화 과정에서 발생하는 1, 2차 액적분열을 모사하기 위해서 난류 모델을 선정하고 VOF(Volume of Fluid), DPM(Discrete Phase Model) 해석을 차례대로 수행하였다. 해석결과, Level-Set function 분포도를 통해 1차 분열액적의 직경을 계산할 수 있었으며 이 데이터를 DPM 해석에 반영해 도메인 출구에서 수집된 입자들의 최종직경분포를 확인할 수 있었다.