• Journal of information and communication convergence engineering
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• v.20 no.1
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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.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.05a
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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.

• The Journal of the Convergence on Culture Technology
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• v.5 no.4
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• pp.413-420
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• 2019

The purpose of the present study is to develop a model for predicting hypercholesterolemia using an integrated set of body fat mass variables based on machine learning techniques, beyond the study of the association between body fat mass and hypercholesterolemia. For this study, a total of six models were created using two variable subset selection methods and machine learning algorithms based on the Korea National Health and Nutrition Examination Survey (KNHANES) data. Among the various body fat mass variables, we found that trunk fat mass was the best variable for predicting hypercholesterolemia. Furthermore, we obtained the area under the receiver operating characteristic curve value of 0.739 and the Matthews correlation coefficient value of 0.36 in the model using the correlation-based feature subset selection and naive Bayes algorithm. Our findings are expected to be used as important information in the field of disease prediction in large-scale screening and public health research.

• Journal of The Korean Radiological Technologist Association
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• v.25 no.1
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• pp.46.2-47
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• 1999

• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.4
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• pp.696-706
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• 1992

In sheet metal fabrication using NCT(numerically controlled turret), the automatic tool selection for the NCT operation is the major problem to be solved first to improve its production performance. However, the punching tool selection has been done by human experts either manually or semi-automatically. In this paper, we have introduced the shape-index-set to handle the shape of sheet metal parts and developed an algorithm through which one can find easily the successive matching curves between two curve lists, one from the punching tool and the other from the boundaries of the sheet metal part. Based on this algorithm, we have also devised the method that can select automatically the tools to punch out the boundaries of sheet metal parts. The result of several computational experiments shows the successful tool selection without any fail.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.53 no.4
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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.

• Proceedings of the Korean Geotechical Society Conference
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• 1998.04a
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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.

• Convergence Security Journal
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• v.12 no.3
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• pp.115-121
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• 2012

Software failure time presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing. For data analysis of software reliability model, data scale tools of trend analysis are developed. The methods of trend analysis are arithmetic mean test and Laplace trend test. Trend analysis only offers information of outline content. In this paper, we discuss forecasting failure time case of failure time censoring. In this study, we predict the future failure time by using the curve regression analysis where the s-curve, growth, and Logistic model is used. The proposed prediction method analysis used failure time for the prediction of this model. Model selection using the coefficient of determination and the mean square error were presented for effective comparison.

• International Journal of Control, Automation, and Systems
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• v.2 no.1
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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.

• Journal of Korea Water Resources Association
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• v.32 no.2
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• pp.163-176
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• 1999

Hydrology-based topographical informations generated by GIS techniques could be changed according to the selection of base map, algorithm of extraction, and so on. The purpose of this paper is to investigate the variation of SCS CN extracted by GIS technique and to propose the effective strategy for applying GIS to the rainfall-runoff simulation in ungaged basin. For experimental implementation, GIS spatial data, such as reconnaissance soil map, detailed interpretative soil map, landuse planning map and remotely sensed data(Landsat TM), were collected and generated to calculate the amount of effective rainfall in Pyungchang river basin. In applying SCS Runoff Curve Number to the test basin, the hydrological attribute data were analyzed. In addition, the characteristics of runoff responses according to the selection of GIS spatial data for SCS CN were reviewed. This study shows the applicability of GIS techniques to runoff simulation in ungaged basin by comparing with the measured flood hydrograph. It has been found that the detained interpretative soil map and remote sensing data are appropriate for calculating of SCS CN.