• Journal of Gastric Cancer
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• v.16 no.4
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• pp.247-253
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• 2016

Purpose: The aim of this study was to establish an anthropometric reference of the stomach for gastric cancer surgery and a modeling formula to predict stomach length. Materials and Methods: Data were retrieved for 851 patients who underwent total gastrectomy at the Seoul National University Hospital between 2008 and 2013. Clinicopathological data and measurements from a formalin-fixed specimen were reviewed. The lengths (cm) of the greater curvature (GC) and lesser curvature (LC) were measured. Anthropometric data of the stomach were compared according to age, body weight, height (cm), and body mass index. To predict stomach length, two multiple regression analyses were performed. Results: The mean lengths of the GC and LC were $22.2{\pm}3.1cm$ and $16.3{\pm}2.6cm$, respectively. The men's GC length was significantly greater than the women's ($22.4{\pm}3.1cm$ vs. $21.2{\pm}2.9cm$, P=0.003). Patients aged >70 years showed significantly longer LC than those aged <50 years ($16.9{\pm}2.9cm$ vs. $15.9{\pm}2.4cm$, P=0.002). Patients with body weights >70 kg showed significantly longer GC than those with body weights <55 kg ($23.0{\pm}2.9cm$ vs. $21.4{\pm}3.2cm$, P<0.001). In the predicted models, 4.11% of the GC was accounted for by age and weight; and 4.94% of the LC, by age, sex, height, and weight. Conclusions: Sex, age, height, and body weight were associated with the length of the LC, while sex and body weight were the only factors that were associated with the length of the GC. However, the prediction model was not sufficiently strong.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.4
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• pp.1861-1864
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• 2016

Although early diagnosis of thyroid nodule type is very important, the diagnostic accuracy of standard tests is a challenging issue. We here aimed to find an optimal combination of factors to improve diagnostic accuracy for distinguishing malignant from benign thyroid nodules before surgery. In a prospective study from 2008 to 2012, 345 patients referred for thyroidectomy were enrolled. The sample size was split into a training set and testing set as a ratio of 7:3. The former was used for estimation and variable selection and obtaining a linear combination of factors. We utilized smoothly clipped absolute deviation (SCAD) logistic regression to achieve the sparse optimal combination of factors. To evaluate the performance of the estimated model in the testing set, a receiver operating characteristic (ROC) curve was utilized. The mean age of the examined patients (66 male and 279 female) was $40.9{\pm}13.4years$ (range 15- 90 years). Some 54.8% of the patients (24.3% male and 75.7% female) had benign and 45.2% (14% male and 86% female) malignant thyroid nodules. In addition to maximum diameters of nodules and lobes, their volumes were considered as related factors for malignancy prediction (a total of 16 factors). However, the SCAD method estimated the coefficients of 8 factors to be zero and eliminated them from the model. Hence a sparse model which combined the effects of 8 factors to distinguish malignant from benign thyroid nodules was generated. An optimal cut off point of the ROC curve for our estimated model was obtained (p=0.44) and the area under the curve (AUC) was equal to 77% (95% CI: 68%-85%). Sensitivity, specificity, positive predictive value and negative predictive values for this model were 70%, 72%, 71% and 76%, respectively. An increase of 10 percent and a greater accuracy rate in early diagnosis of thyroid nodule type by statistical methods (SCAD and ANN methods) compared with the results of FNA testing revealed that the statistical modeling methods are helpful in disease diagnosis. In addition, the factor ranking offered by these methods is valuable in the clinical context.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.12
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• pp.581-588
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• 2017

This study was conducted to determine which factors would predict metabolic syndrome (MetS) perception and exercise by applying a machine learning classifier, or Extreme Gradient Boosting algorithm (XGBoost) from July 2014 to December 2015. Data were obtained from the Korean Community Health Survey (KCHS), representing different community-dwelling Korean adults 19 years and older, from 2009 to 2013. The dataset includes 370,430 adults. Outcomes were categorized as follows based on the perception of MetS and physical activity (PA): Stage 1 (no perception, no PA), Stage 2 (perception, no PA), and Stage 3 (perception, PA). Features common to all questionnaires for the last 5 years were selected for modeling. Overall, there were 161 features, categorical except for age and the visual analogue scale (EQ-VAS). We used the Extreme Boosting algorithm in R programming for a model to predict factors and achieved prediction accuracy in 0.735 submissions. The top 10 predictive factors in Stage 3 were: age, education level, attempt to control weight, EQ mobility, nutrition label checks, private health insurance, EQ-5D usual activities, anti-smoking advertising, EQ-VAS, education in health centers for diabetes, and dental care. In conclusion, the results showed that XGBoost can be used to identify factors influencing disease prevention and management using healthcare bigdata.

• Korean Journal of Agricultural and Forest Meteorology
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• v.10 no.2
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• pp.35-46
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• 2008

Soil moisture is one of the important components in hydrological processes and also controls the subsurface flow mechanism at a hillslope scale. In this study, time series of soil moisture were measured at a hillslope located in Gwangneung National Arboretum, Korea using a multiplex Time Domain Reflectometry(TDR) system measuring soil moisture with bi-hour interval. The Box-Jenkins transfer function and noise model was used to estimate spatial distributions of soil moisture histories between May and September, 2007. Rainfall was used as an input parameter and soil moisture at 10 cm depth was used as an output parameter in the model. The modeling process consisted of a series of procedures(e.g., data pretreatment, model identification, parameter estimation, and diagnostic checking of selected models), and the relationship between soil moisture and rainfall was assessed. The results indicated that the patterns of soil moisture at different locations and slopes along the hillslope were similar with those of rainfall during the measurment period. However, the spatial distribution of soil moisture was not associated with the slope of the monitored location. This implies that the variability of the soil moisture was determined more by rainfall than by the slope of the site. Due to the influence of vegetation activity on soil moisture flow in spring, the soil moisture prediction in spring showed higher variability and complexity than that in early autumn did. This indicates that vegetation activity is an important factor explaining the patterns of soil moisture for an upland forested hillslope.

• Journal of Korean Society on Water Environment
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• v.28 no.3
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• pp.347-358
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• 2012

The SWAT (Soil and Water Assessment Tool) should be calibrated and validated with observed data to secure accuracy of model prediction. Recently, the SWAT-CUP (Calibration and Uncertainty Program for SWAT) software, which can calibrate SWAT using various algorithms, were developed to help SWAT users calibrate model efficiently. In this study, three algorithms (GLUE: Generalized Likelihood Uncertainty Estimation, PARASOL: Parameter solution, SUFI-2: Sequential Uncertainty Fitting ver. 2) in the SWAT-CUP were applied for the Soyang-gang dam watershed to evaluate these algorithms. Simulated total streamflow and 0~75% percentile streamflow were compared with observed data, respectively. The NSE (Nash-Sutcliffe Efficiency) and $R^2$ (Coefficient of Determination) values were the same from three algorithms but the P-factor for confidence of calibration ranged from 0.27 to 0.81 . the PARASOL shows the lowest p-factor (0.27), SUFI-2 gives the greatest P-factor (0.81) among these three algorithms. Based on calibration results, the SUFI-2 was found to be suitable for calibration in Soyang-gang dam watershed. Although the NSE and $R^2$ values were satisfactory for total streamflow estimation, the SWAT simulated values for low flow regime were not satisfactory (negative NSE values) in this study. This is because of limitations in semi-distributed SWAT modeling structure, which cannot simulated effects of spatial locations of HRUs (Hydrologic Response Unit) within subwatersheds in SWAT. To solve this problem, a module capable of simulating groundwater/baseflow should be developed and added to the SWAT system. With this enhancement in SWAT/SWAT-CUP, the SWAT estimated streamflow values could be used in determining standard flow rate in TMDLs (Total Maximum Daily Load) application at a watershed.

• Journal of Korean Society on Water Environment
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• v.28 no.3
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• pp.375-383
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• 2012

Soil erosion has been emphasized as serious environmental problem affecting water quality in the receiving waterbodies. Recently, Best Management Practices (BMPs) have been applied at a field to reduce soil erosion and its effectiveness in soil erosion reduction has been monitored with various methods. Although monitoring at fields/watershed outlets would be accurate way for these ends, it is not possible at some fields/watersheds due to various limitations in direct monitoring. Thus modeling has been suggested as an alternative way to evaluate effects of the BMPs. Most models, which have been used in evaluating hydrology and water quality at a watershed, could not reflect rainfall intensity in runoff generation and soil erosion processes. In addition, source codes of these models are not always public for modification/enhancement. Thus, runoff-sediment evaluation system using hourly rainfall data and vegetated filter strip (VFS) evaluation module at field level were developed using open source MapWindow GIS component in this study. This evaluation system was applied to Bangdongri, Chuncheonsi to evaluate its prediction ability and VFS module in this study. The NSE and $R^2$ values for runoff estimation were 0.86 and 0.91, respectively, and measured and simulated sediment yield were 15.2 kg and 16.5 kg indicating this system, developed in this study, can be used to simulate runoff and sediment yield with acceptable accuracies. Nine VFS scenarios were evaluated for effectiveness of soil erosion reduction. Reduction efficiency of the VFS was high when sediment inflow was small. As shown in this study, this evaluation system can be used for evaluation BMPs with local rainfall intensity and variations considered with ease-of-use GIS interface.

• Ecology and Resilient Infrastructure
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• v.7 no.2
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• pp.114-125
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• 2020

Despite the various artificial neural networks that have been developed, most of the discharge models in previous studies have been developed using deep neural networks. This study aimed to develop a discharge model using a convolution neural network (CNN), which was used to solve classification problems. Furthermore, the applicability of CNN was evaluated. The photographs (pictures or images) for input data to CNN could not clearly show the characteristics of the study area as well as precipitation. Hence, the model employed in this study had to use numerical images. To solve the problem, the CN of NRCS was used to generate images as input data for the model. The generated images showed a good possibility of applicability as input data. Moreover, a new application of CN, which had been used only for discharge prediction, was proposed in this study. As a result of CNN training, the model was trained and generalized stably. Comparison between the actual and predicted values had an R² of 0.79, which was relatively high. The model showed good performance in terms of the Pearson correlation coefficient (0.84), the Nash-Sutcliffe efficiency (NSE) (0.63), and the root mean square error (24.54 ㎥/s).

• KOREAN JOURNAL OF CROP SCIENCE
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• v.33 no.4
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• pp.323-328
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• 1988

The hop alpha-acid content prediction model developed with meteorological elements in Hoeongseong was Y=28.369-0.003X$_1$＋1.558X$_2$-1.953X$_3$-0.335X$_4$-0.003X$\sub$5/-0.119X$\sub$6/, with MSEp of 0.004, Rp$^2$ of 0.9987, Rap$_2$ of 0.9949 and Cp of 7.00. The total sunshine hours (X$_1$), the maximum temperature (X$_3$) and the total precipitation (X$\sub$5/) at flowering stage. the maximum temperature at flower bud differentiation stage (X$_4$) and the maximum temperature at cone ripening stage (X$\sub$6/) influenced on hop alpha .acid content as decrement weather elements. The maximum temperature at cone development stage(X$_2$) effected on ${\alpha}$-acid content as increment weather element.

• Journal of Korean Society for Atmospheric Environment
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• v.26 no.6
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• pp.606-615
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• 2010

This study aims to identify the characteristics of soil in Mongolia, one of the major Asian dust sources that influence the Korean Peninsula. Soil particle size was analyzed and the result shows that sand (57.5~97.3%) was identified prominently in most regions, followed by silt (2.5~34.7%) and clay (0.0~7.8%). Soil pH of the covered regions were in the range 7.1~10.1, either weak alkaline or strong alkaline. Analysis of ion species in the soil samples exhibited that $Na^+$ ($91.9\;mg\;kg^{-1}$), $Cl^-$ ($65.9\;mg\;kg^{-1}$), and $Ca^{2+}$ ($53.5\;mg\;kg^{-1}$) were detected more in the soil than other species such as ${SO_4}^{2-}$ ($19.2\;mg\;kg^{-1}$), ${NO_3}^-$ ($46.6\;mg\;kg^{-1}$), ${NH_4}^+$ ($3.9\;mg\;kg^{-1}$), $K^+$ ($22.0\;mg\;kg^{-1}$), and $Mg^{2+}$ ($10.2\;mg\;kg^{-1}$). As for heavy metal content in the soil, concentrations of soil-borne metals including Fe, Al, Ca, Mg, and K tended to be high, while metals that come from manmade sources Pb, Cd, Cr, V, and Ni were remarkably low. The concentration of organic carbon (OC) was relatively high at $15.9\;{\mu}g\;mg^{-1}$, while elemental carbon (EC), directly released in the process of fossil fuel combustion, was not detected at all or found in very small amounts. The result indicates that pollution from manmade sources scarcely occurred. The analysis results from this study may contribute to improving modeling accuracy by providing input data for Asian dust prediction models, and be used as base data for determining the process of physiochemical transformation of Asian dust during long-range transport.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.17 no.4
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• pp.375-387
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• 2004

A new finite element model will be presented to analyze the nonlinear behavior of RC beams and slabs strengthened by a patch repair. The numerical approach is based on the p-version degenerate shell element including theory of anisotropic laminated composites, theory of materially and geometrically nonlinear plates. In the nonlinear formulation of this model, the total Lagrangian formulation is adopted with large deflections and moderate rotations being accounted for in the sense of von Karman hypothesis. The material model is based on hardening rule, crushing condition, plate-end debonding strength model and so on. The Gauss-Lobatto numerical quadrature is applied to calculate the stresses at the nodal points instead of Gauss points. The validity of the proposed p-version nonlinear finite element model is demonstrated through the load-deflection curves, the ultimate loads, and the failure modes of RC beams or slabs bonded with steel plates or FRP plates compared with available result of experiment and other numerical methods.