• Journal of Korea Water Resources Association
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• v.43 no.8
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• pp.695-707
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• 2010

The frequency and size of typhoon and local severe rainfall are increasing due to the climate change and the damage also increasing from typhoon and severe rainfall. The flood forecasting and warning system to reduce the damage from typhoon and severe rainfall needs forecasted rainfall using radar data and short-term rainfall forecasting model. For this reason, this study examined the applicability of short-term rainfall forecast using translation model with weather radar data to point out that the utilization of flood forecasting in Korea. This study estimated the radar rainfall using Least-square fitting method and estimated rainfall was used as initial field of translation model. The translation model have verified accuracy of forecasted radar rainfall through the comparison of forecasted radar rainfall and observed rainfall quantitatively and qualitatively. Almost case studies showed that accuracy is over 0.6 within 4 hours leading time and mean of correlation coefficient is over 0.5 within 1 hours leading time in Kwanak and Jindo radar site. And, as the increasing the leading time, the forecast accuracy of precipitation decreased. The results of the calculated Mean Area Precipitation (MAP) showed forecast rainfall tend to be underestimated than observed rainfall but the correlation coefficient more than 0.5. Therefore it showed that translation model could be accurately predicted the rainfall relatively. The present results indicate that possibility of translation model application of Korea just within 2 hours leading forecasted rainfall.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.4
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• pp.772-780
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• 2008

K-means is one of the simplest unsupervised learning algorithms that solve the clustering problem. However K-means suffers the basic shortcoming: the number of clusters k has to be known in advance. In this paper, we propose extensions of X-means, which can estimate the number of clusters using Bayesian information criterion(BIC). We introduce two different versions of algorithm: modified X-means(MX-means) and generalized X-means(GX-means), which employ one full covariance matrix for one cluster and so can estimate the number of clusters efficiently without severe over-fitting which X-means suffers due to its spherical cluster assumption. The algorithms start with one cluster and try to split a cluster iteratively to maximize the BIC score. The former uses K-means algorithm to find a set of optimal clusters with current k, which makes it simple and fast. However it generates wrongly estimated centers when the clusters are overlapped. The latter uses EM algorithm to estimate the parameters and generates more stable clusters even when the clusters are overlapped. Experiments with synthetic data show that the purposed methods can provide a robust estimate of the number of clusters and cluster parameters compared to other existing top-down algorithms.

• Journal of Distribution Science
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• v.14 no.11
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• pp.83-90
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• 2016

Purpose - During the last two years, convenient stores (CS) are emerging as one of the most fast-growing retail trades in Korea. The goal of this work is to forecast and to analyze sales at CS using ARIMA-Intervention model (IM) and exponential smoothing method (ESM), together with sales at supermarkets in South Korea. Considering that two retail trades above are homogeneous and comparable in size and purchasing items on off-line distribution channel, individual behavior and characteristic can be detected and also relative superiority of future growth can be forecasted. In particular, the rapid growth of sales at CS is regarded as an everlasting external event, or step intervention, so that IM with season variation can be examined. At the same time, Winters ESM can be investigated as an alternative to seasonal ARIMA-IM, on the assumption that the underlying series shows exponentially decreasing weights over time. In case of sales at supermarkets, the marked intervention could not be found over the underlying periods, so that only Winters ESM is considered. Research Design, Data, and Methodology - The dataset of this research is obtained from Korean Statistical Information Service (1/2010~7/2016) and Survey of Service Trend of Korea Statistics Administration. This work is exploited time series analyses such as IM, ESM and model-fitting statistics by using TSPLOT, TSMODEL, EXSMOOTH, ARIMA and MODELFIT procedures in SPSS 23.0. Results - By applying seasonal ARIMA-Intervention model to sales at CS, the steep and persisting increase can be expected over the next one year. On the other hand, we expect the rate of sales growth of supermarkets to be lagging and tied up constantly in the next 2016 year. Conclusions - Based on 2017 one-year sales forecasts for CS and supermarkets, we can yield the useful information for the development of CS and also for all retail trades. Future study is needed to analyze sales of popular items individually such as tobacco, banana milk, soju and so on and to get segmented results. Furthermore, we can expand sales forecasts to other retail trades such as department stores, hypermarkets, non-store retailing, so that comprehensive diagnostics can be delivered in the future.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.11
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• pp.455-464
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• 2022

There are two unique characteristics of the datasets from a manufacturing process. They are the severe class imbalance and lots of Out-of-Distribution samples. Some good strategies such as the oversampling over the minority class, and the down-sampling over the majority class, are well known to handle the class imbalance. In addition, SMOTE has been chosen to address the issue recently. But, Out-of-Distribution samples have been studied just with neural networks. It seems to be hardly shown that Out-of-Distribution detection is applied to the predictive model using conventional machine learning algorithms such as SVM, Random Forest and KNN. It is known that conventional machine learning algorithms are much better than neural networks in prediction performance, because neural networks are vulnerable to over-fitting and requires much bigger dataset than conventional machine learning algorithms does. So, we suggests a new approach to utilize Out-of-Distribution detection based on SVM algorithm. In addition to that, bagging technique will be adopted to improve the precision of the model.

• Computers and Concrete
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• v.31 no.4
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• pp.349-358
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• 2023

This paper describes an in-depth analysis on flexural strength of a girder-deck system experiencing a strand debonding damage with various strengthening systems, based on finite element software ABAQUS. A detailed finite element analysis (FEA) model was developed and verified against the relevant experimental data performed by other researchers. The proposed analytical model showed a good agreement with experimental data. Based on the verified FE model, over a hundred girder-deck systems were investigated with the consideration of following variables: 1) debonding level, 2) span-to-depth ratio (L/d), 3) strengthening type, 4) strengthening material thickness. Based on the data above, a new detailed analytical model was developed and proposed for estimating residual flexural strength of the strand-debonding damaged girder-deck system with strengthening systems. It was demonstrated that both finite element model and analysis model could be used to predict flexural behaviors for debonding damaged prestressed girder-deck systems. Since the strands are debonding from surrounding concrete over a certain zone over the length of the beam, the increase of strain in strands can be linked with a ratio ψ, which is L_p/c. The analytical model was proposed and developed regarding the ratio ψ. By conducting procedure of calculating ψ, the ψ value varies from 9.3 to 70.1. Multiple nonlinear regression analysis was performed in Software IBM SPSS Statistics 27.0.1 to derive equation of ψ. ψ equation was curved to be an exponential function, and the independent variable (X) is a linear function in terms of three variables of debonding level (λ), span length (L), and amount of strengthening material (A_s). The coefficient of determinate (R²) for curve fitting in nonlinear regression analysis is 0.8768. The developed analytical model was compared to the ultimate capacities computed by FEA model.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.125-125
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• 2020

European Space Agency's Sentinel-1 has an improved spatial and temporal resolution, as compared to previous satellite data such as Envisat Advanced SAR (ASAR) or Advanced Scatterometer (ASCAT). Thus, the assumption used for low-resolution retrieval algorithms used by ENVISAT ASAR or ASCAT is not applicable to Sentinel-1, because a higher degree of land surface heterogeneity should be considered for retrieval. The assumption of homogeneity over land surface is not valid any more. In this study, considering that soil roughness is one of the key parameters sensitive to soil moisture retrievals, various approaches are discussed. First, soil roughness is spatially inverted from Sentinel-1 backscattering over Yanco sites in Australia. Based upon this, Artificial Neural Networks data (feedforward multiplayer perception, MLP, Levenberg-Marquadt algorithm) are compared with Fractal approach (brownian fractal, Hurst exponent of 0.5). When using ANNs, training data are achieved from theoretical forward scattering models, Integral Equation Model (IEM). and Sentinel-1 measurements. The network is trained by 20 neurons and one hidden layer, and one input layer. On the other hand, fractal surface roughness is generated by fitting 1D power spectrum model with roughness spectra. Fractal roughness profile is produced by a stochastic process describing probability between two points, and Hurst exponent, as well as rms heights (a standard deviation of surface height). Main interest of this study is to estimate a spatial variability of roughness without the need of local measurements. This non-local approach is significant, because we operationally have to be independent from local stations, due to its few spatial coverage at the global level. More fundamentally, SAR roughness is much different from local measurements, Remote sensing data are influenced by incidence angle, large scale topography, or a mixing regime of sensors, although probe deployed in the field indicate point data. Finally, demerit and merit of these approaches will be discussed.

• Journal of Fashion Business
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• v.2 no.3
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• pp.137-156
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• 1998

In this study, the researcher studied the historical background, and the traditional culture about dress and ornament of Yunnan Province of China, The results of the study are as follows. 1. Dress and personal ornaments of the Va peoples vary with the locality. Their traditional dress and adornment is characterized by those in the Ximeng area. Men usually wear black or dark blue collarless jackets and black and dark blue loose and short bagged trousers with folding waist. Women usually wear close-fitting sleeveless pullover blouses with V-shaped necks and straight skirts with patterns of red and black cross stripes. 2. Jingpo men have changed to wear shirts with button down the front and trousers. They also entwine white turbans with red bobbles on both ends, and carry diagonally long knives, firelocks and red woolen figured satchels on their shoulders. Women usually wear black velvet blouses with silver bowl-shaped ornaments and chains around collars and on the fronts. They also wear red straight skirts with overlapped slit on the right, waistbands and waist hoops made of rattan and bamboo. 3. The Naxi nationality has a long history and excellent traditional culture. In modern times, women like to wear red, blue or purple laced blouses, long double-layered pleated skirts, waistbands and embroidered shoes. They wear their hair in buns with either hats or kerchiefs over them. While working or going out, they put on their "seven-star" capes made of sheepskin and embroidered with two big circles and seven small ones, while is a symbol of their frog totem. 4. The dress and adorment of the Jinuo people is simple, elegant and has its own unique characteristics. Men usually wear white buttonless shirts with round necks and an opening on the front, knee-length bagged trousers and legging. They wear cloth turbans, earrings and also put small bamboo or silver pipes in the holes of their earlobes. Women wear short buttonless blouses with round necks and seven coloured stripes and thin tight-fitting or embroidered triangular underwear. 5. The dress and ardorment of the Benglong (De' ang) nationality has its own strong national colour. Most of the men wear jackets with buttons arranged diagonally on the front, loose, short trousers and black or white turbans. Some young men like to wear eardrops and silver necklaces. Women's dress and adornment differs according to various branches. For example, the women of the Bielie and Liang branches have their hair shaved and wear black turbans. They use large square silver tablets as buttons and wear blue or black blouses with buttons down the front. 6. Oai men usually wear trousers, white or blue cloth turbans and round-necked shirts with buttons down the front or arranged diagonally on the front. Women usually wear long straight skirt and blouses. But dress and adornment varies in regions. 7. The Bai nationality dress and adornment has unique national style. The dress fabrics are mainly cotton cloth, silk and velvet. Men usually wear red velvet vests over white shirts with buttons down the front or black velvet vests over light blue shirts. They also wear white of blue turbans and carry satchels with beautiful embroidered designs over their shoulders. Women usually wear red velvet vests over white blouses, or black vests over light-coloured blouses.

• Journal of Korean Ophthalmic Optics Society
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• v.16 no.2
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• pp.123-133
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• 2011

Purpose: The present study was conducted to analyze any difference in the movement of aspheric RGP lens by the amounts of keratometiric astigmatisms using keratometer and corneal topography. Methods: Corneal curvatures in thirty six eyes of males and females of with-the-rule keratometric astigmatisms in their twenties were measured by a keratometer and worn aspheric RGP lenses. Then, lens rotations, vertical and horizontal movements of lens by blinking were measured to compare with lens movements when aspheric RGP lenses were fitted by total keratometric astigmatisms using corneal topography. Results: The case having higher amount of central keratometric astigmatism was 61.1% of subjects, however, 36.1% of subjects showed higher total keratometric astigmatism indicating that central keratometric astigmatism was not always bigger than total keratometric astigmatism. Since over 0.25 diopter difference between total and central keratometric astigmatisms was shown in 19 eyes (52.8% of subjects), the prescription for lens fitting could be changed. Significant difference in horizontal movement was detected with increase of astigmatism when it compared based on the amount of keratometric astigmatism measured by a keratometer. However, there was no significant difference in lens rotation, horizontal and vertical movements by comparison with the amount of total keratometric astigmatism using a corneal topography. When central keratometric astigmatism measured by keratometer was bigger than total keratometric astigmatism estimated by corneal topography, bigger lens rotation was shown compared with opposite case. Also, the tendency of bigger lens rotation was measured with the increase of keratomatric astigmatism in the case of same prescription having same base curves with same amount of keratometric astigmatism but different curvatures. Conclusions: From the present study, we concluded that lens movements on cornea were not totally different when aspheric RGP lens fitted on with-the-rule astigmatism by keratometer and corneal topography. However, there was some difference in certain lens movements. Therefore, we concluded that further study on the relationship between the prescriptions for lens fitting should be conducted for improving the rate of successful lens fitting by keratometer or for the proper application of corneal topography for lens fitting.

• Journal of Korean Ophthalmic Optics Society
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• v.20 no.2
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• pp.141-150
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• 2015

Purpose: In the present study, a difference in tear volume between the cornea and the rigid gas permeable (RGP) lens relative to corneal shape and corneal astigmatism was investigated by the alignment fitting status of spherical and aspherical RGP lenses. Methods: Spherical and aspherical RGP lenses were fitted with alignment in 77 subjects (135 eyes) who were in their 20~30s. Tear volume stained with fluorescein was qualitatively analyzed by dividing cornea into center, mid-peripheral and peripheral parts. Results: For the spherical RGP lens fitting, tear volume differences were found in each part in all corneal types. For the aspherical RGP lens fitting, tear volume differences were in each corneal part in symmetric bow tie- and asymmetric bow tie-type corneas. However, the tear was equally distributed from the center to the peripheral part in round- and oval-type corneas. In the group with corneal astigmatism lower than 1.25 D, tear volume between center and peripheral parts, and mid-peripheral and peripheral parts, was different when a spherical RGP lens was fitted. However, tear volume in each part was not different in the group with corneal astigmatism over 1.50 D. Moreover, the tear volumes of the central and mid-peripheral parts were proportionally increased with increasing corneal astigmatism in both spherical and aspherical RGP lenses. Furthermore, aspherical RGP lenses showed greater increments than spherical RGP lenses. Conclusions: The results revealed that the difference in tear volume between aspherical RGP lens and cornea was less than spherical RGP lens, and the difference in tear volume varied according to corneal shape and astigmatism. In addition, the method of measuring relative tear volume between RGP lens and cornea that was established in the present study can be used to evaluate tear volume between contact lens and cornea.

• Journal of Biomedical Engineering Research
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• v.33 no.1
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• pp.1-7
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• 2012

Hemorrhagic shock is a common cause of death in emergency rooms. Early diagnosis of hemorrhagic shock makes it possible for physicians to treat patients successfully. Therefore, the purpose of this study was to select an optimal survival prediction model using physiological parameters for the two analyzed periods: two and five minutes before and after the bleeding end. We obtained heart rates, mean arterial pressures, respiration rates and temperatures from 45 rats. These physiological parameters were used for the training and testing data sets of survival prediction models using an artificial neural network (ANN) and support vector machine (SVM). We applied a 5-fold cross validation method to avoid over-fitting and to select the optimal survival prediction model. In conclusion, SVM model showed slightly better accuracy than ANN model for survival prediction during the entire analysis period.