• Journal of information and communication convergence engineering
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• 제20권1호
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• pp.31-40
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• 2022

Coronary heart disease (CHD) is a comorbidity of COVID-19; therefore, routine early diagnosis is crucial. A large number of examination attributes in the context of diagnosing CHD is a distinct obstacle during the pandemic when the number of health service users is significant. The development of a precise machine learning model for diagnosis with a minimum number of examination attributes can allow examinations and healthcare actions to be undertaken quickly. This study proposes a CHD diagnosis model based on feature selection, data balancing, and ensemble-based classification methods. In the feature selection stage, a hybrid SVM-GA combined with fast correlation-based filter (FCBF) is used. The proposed system achieved an accuracy of 94.60% and area under the curve (AUC) of 97.5% when tested on the z-Alizadeh Sani dataset and used only 8 of 54 inspection attributes. In terms of performance, the proposed model can be placed in the very good category.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2021년도 춘계학술발표대회
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• pp.323-325
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• 2021

In this article, we have improved the prediction of hypertension detection using the feature selection method for the Korean national health data named by the KNHANES database. The study identified a variety of risk factors associated with chronic hypertension. The paper is divided into two modules. The first of these is a data pre-processing step that uses a factor analysis (FA) based feature selection method from the dataset. The next module applies a predictive analysis step to detect and predict hypertension risk prediction. In this study, we compare the mean standard error (MSE), F1-score, and area under the ROC curve (AUC) for each classification model. The test results show that the proposed FIFA-OE-NB algorithm has an MSE, F1-score, and AUC outcomes 0.259, 0.460, and 64.70%, respectively. These results demonstrate that the proposed FIFA-OE method outperforms other models for hypertension risk predictions.

• 문화기술의 융합
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• 제5권4호
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• pp.413-420
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• 2019

본 연구의 목적은 기존의 body fat mass 변수와 고콜레스테롤혈증의 연관성연구를 벗어나, 머신러닝기법을 기반으로 body fat mass 변수들의 조합을 이용하여 고콜레스테롤혈증 예측 모델을 개발하는 것이다. 이러한 연구를 위하여 국민건강영양조사 데이터를 기반으로 두 가지 variable selection 메소드와 머신러닝 알고리즘을 이용하여 총 6개의 모델을 생성하였고 질병 예측력을 비교분석하였다. 여러 body fat mass 관련 변수들 중에서 몸통지방량 변수가 고콜레스테롤혈증 예측력이 가장 우수한 변수인 것을 밝혀내었고, 머신러닝 기반 예측모델들 중에서 correlation-based feature subset selection 기반 naive Bayes 알고리즘을 이용한 모델이 0.739의 the area under the receiver operating characteristic curve 값과 0.36의 Matthews correlation coefficient 값을 얻었다. 이러한 연구의 결과는 향후 국내외 대규모 스크리닝 및 대중보건 연구에서 질병예측분야의 중요정보로 활용될 것으로 예상한다.

• 대한방사선협회지
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• 제25권1호
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• pp.46.2-47
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• 1999

• 대한기계학회논문집
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• 제16권4호
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• pp.696-706
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• 1992

본 연구에서는 공구선정 작업의 자동화를 목표로 하였다.공구선정을 완전 자동으로 행하기 위해 해결해야 할 문제는, 현재 공구대(turret)에 장착되어 있는 공 구중에서 어떤 공구를 얼마칸큼 직선, 회전 이동시키면 판재 경계와 정확하게 일치하 는가 하는 문제와, 복잡한 형상의 펀칭을 위해선 효과적인 공구조합은 어떻게 해야하 나 하는 문제로 귀결되므로 이 두가지 문제의 해결방안을 기술한다.

• 수산해양기술연구
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• 제53권4호
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• pp.317-326
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• 2017

Comparative fishing experiments were conducted in the eastern coastal waters near Uljin, Korea from 2002 to 2004, using the experimental trammel nets to estimate the selectivity for spinyhead sculpin Dasycottus setiger. The inner panels of the nets were made of nylon monofilament with four mesh sizes (82.2, 89.4, 104.8, and 120.2 mm) while its two outer panels were made of twisted nylon multifilament with a mesh size of 510 mm. The SELECT (Share Each Length's Catch Total) procedure with maximum likelihood method was applied to obtain a master selection curve. The different functional models (normal, lognormal, bi-normal, and logistic model) were fitted to the catch data. The lognormal model with the fixed relative fishing intensity was chosen as the best-fitted selection curve through comparison of model deviance and AIC (Akaike's Information Criterion). The optimum relative length (the ratio of fish total length to mesh size) with the maximum relative efficiency was obtained as 2.492.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 1998년도 지반조사위원회 봄 학술세미나
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• pp.37-46
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• 1998

Several researchers have developed a number of theoretical time factors to determine the coefficient of consolidation by biezocone excess pore water dissipation test in soft clay deposits. However, depending on the assumptions and analytical techniques, the estimated coefficient of consolidation could be in a considerably wide range even for a specific degree of consolidation. These solutions are obtained from an initial excess porewater pressure distribution which can be determined from. either the cavity expansion theory or the strain path method. The 야ssipation of the initial excess porelvater pressure has been usally simulated by means of linear-uncoupled consolidation analysis and then the dissipation curve is normalized by the initial excess porewater pressure for easy use. However. since there is no guidelines or rules on which method gives the best solution for obtaining the coefficient of consolidation from the dissipation curve, the final selection was only based on engineer's extrience and Judgements. Thus, such an arbitrary selection might be inappropriate for a specific site to characterize the consolidation behavior. In this paper, we reviewed various theoretical time factors and, based on this consideration, we mentioned needs for researches in selecting a specific solution that is compatible for Korean clays. Also we listed some source of errors that can be encountered in the procedure of dissipation analysis.

• 융합보안논문지
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• 제12권3호
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• pp.115-121
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• 2012

소프트웨어 고장 시간은 테스팅 시간과 관계없이 일정하거나. 단조증가 혹은 단조 감소 추세를 가지고 있다. 이러한 소프트웨어 신뢰모형들을 분석하기 위한 자료척도로 자료에 대한 추세 검정이 개발되어 있다. 추세 분석에는 산술평균 검정과 라플라스 추세 검정 등이 있다. 추세분석들은 전체적인 자료의 개요의 정보만 제공한다. 본 논문에서는 고장시간을 측정하다가 시간 절단이 될 경우에 미래의 고장 시간 예측에 관하여 연구 하였다. 곡선회귀모형에 이용되는 S곡선모형과 성장모형, 로지스틱을 이용하여 미래고장 시간을 예측하여 비교 하였다. 제안된 예측방법에서는 고장시간 자료를 이용하여 모형들에 대한 예측 값을 결정계수 와 평균제곱오차를 이용하여 비교 하고 효율적 모형을 선택 하였다.

• International Journal of Control, Automation, and Systems
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• 제2권1호
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• pp.107-117
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• 2004

A new algorithm for planning a collision-free path based on an algebraic curve as well as the concept of path space is developed. Robot path planning has so far been concerned with generating a single collision-free path connecting two specified points in a given robot workspace with appropriate constraints. In this paper, a novel concept of path space (PS) is introduced. A PS is a set of points that represent a connection between two points in Euclidean metric space. A geometry mapping (GM) for the systematic construction of path space is also developed. A GM based on the 2$^{nd}$ order base curve, specifically Bezier curve of order two is investigated for the construction of PS and for collision-free path planning. The Bezier curve of order two consists of three vertices that are the start, S, the goal, G, and the middle vertex. The middle vertex is used to control the shape of the curve, and the origin of the local coordinate (p, $\theta$) is set at the centre of S and G. The extreme locus of the base curve should cover the entire area of actual workspace (AWS). The area defined by the extreme locus of the path is defined as quadratic workspace (QWS). The interference of the path with obstacles creates images in the PS. The clear areas of the PS that are not mapped by obstacle images identify collision-free paths. Hence, the PS approach converts path planning in Euclidean space into a point selection problem in path space. This also makes it possible to impose additional constraints such as determining the shortest path or the safest path in the search of the collision-free path. The QWS GM algorithm is implemented on various computer systems. Simulations are carried out to measure performance of the algorithm and show the execution time in the range of 0.0008 ~ 0.0014 sec.

• 한국수자원학회논문집
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• 제32권2호
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• pp.163-176
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• 1999

GIS기법을 이용하여 추출되는 수문지형정보는 기존 주제도의 선정, 사용된 알고리즘 등에 따라 달라질 수 있다. 따라서 본 연구에서는 토양도 및 토지이용도의 선정에 따른 유출수문곡선번호의 변화를 분석하여 미계측 유역의 강우유출모의에 효과적인 GIS의 활용방안을 제시하고자 한다. 이를 위해 미계측 유역에서의 유효강우량 산정에 필요한 GIS 공간자료(개략토양도, 정밀토양도, 토지이용계획도,위성영상)를 구축하였다. 미국 토양보존국(SCS)의 유출곡선번호(runoff curve number; CN)방법의 적용을 위한 수문학적 속성의 입력과정에서 발생할 수 있는 문제점을 분석하였다. 또한 SCS CN값 산정을 위한 GIS 공간자료의 선정에 따른 유출응답특성을 검토하였다. 실측 수문곡선과의 검증을 통해 미계측 유역에서의 강우유출모의에서 GIS의 적용성을 확인할 수 있었다. SCS CN값을 산정하기 위한 GIS 공간자료로서는 정밀토양도와 위성영상자료를 이용하는 것이 적합한 것으로 나타났다.