• Journal of Korea Water Resources Association
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• v.53 no.2
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• pp.121-129
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• 2020

The increase of impervious surface and development along the river due to urbanization not only causes an increase in the number of associated flood risk factors but also exacerbates flood damage, leading to difficulties in flood management. Flood control measures should be prioritized based on various geographical information in urban areas. In this study, a probabilistic flood hazard assessment was applied to flood-prone areas near an urban river. Flood hazard maps were alternatively considered and used to describe the expected inundation areas for a given set of predictors such as elevation, slope, runoff curve number, and distance to river. This study proposes a Bayesian logistic regression-based flood risk model that aims to provide a probabilistic risk metric such as population-at-risk (PAR). Finally, the logistic regression model demonstrates the probabilistic flood hazard maps for the entire area.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.26 no.4
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• pp.207-216
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• 2014

Total organic carbon (TOC) is an important indicator used as an direct biological index in the research field of the marine carbon cycle. It is possible to produce the sufficient TOC estimation data by using the Chemical Oxygen Demand(COD) data because the available TOC data is relatively poor than the COD data. The outlier detection and treatment (removal) should be carried out reasonably and objectively because the equation for a COD-TOC conversion is directly affected the TOC estimation. In this study, it aims to suggest the optimal regression model using the available salinity, COD, and TOC data observed in the Korean coastal zone. The optimal regression model is selected by the comparison and analysis on the changes of data numbers before and after removal, variation coefficients and root mean square (RMS) error of the diverse detection methods of the outlier and influential observations. According to research result, it is shown that a diagnostic case combining SIQR (Semi - Inter-Quartile Range) boxplot and Cook's distance method is most suitable for the outlier detection. The optimal regression function is estimated as the TOC(mg/L) = $0.44{\cdot}COD(mg/L)+1.53$, then determination coefficient is showed a value of 0.47 and RMS error is 0.85 mg/L. The RMS error and the variation coefficients of the leverage values are greatly reduced to the 31% and 80% of the value before the outlier removal condition. The method suggested in this study can provide more appropriate regression curve because the excessive impacts of the outlier frequently included in the COD and TOC monitoring data is removed.

• Journal of the Korea institute for structural maintenance and inspection
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• v.17 no.2
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• pp.10-20
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• 2013

To evaluate the safety of a beam structure, strains are measured as an indicator of structural states. However, unless strain sensors are installed exactly on where maximum or other representative strains occur, the techniques by which rational assessment through measured strains is accomplished are required. Thus, this study suggests a process to estimate strain distribution on the steel beam from discrete strains measured by sensors. In the presented technique, the targeted beam is regarded to be subjected to unknown loads so that applicability is enhanced. Final strain distribution is given as form of a function after regression analysis. To verify the performance of estimation, a bending test for steel beam on which distributed and concentrated loads simultaneously act is conducted. From the comparison between estimated and directly measured strains in the test, the curve of strain distribution and the strain at arbitrary location could be predicted within maximum relative error 3.32% and maximum absolute error of $2.32{\mu}{\varepsilon}$, respectively. Thus reliable and practical monitoring is expected to apply effectively for the steel beam structure.

• Journal of Technology Innovation
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• v.23 no.1
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• pp.87-105
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• 2015

This research confirms a non-linear relationship between R&D investment and performance of small and medium-sized enterprises and measures the adequate level as threshold value. Although previous studies did not consider the time lag and estimated indirectly the level using the R&D investment squared term, this study assumes 2 years time lag and uses the threshold estimation model to measure directly. We find that there is the S-curve relationship between the profit rate as R&D output and R&D intensity and the ratio of researchers to employees as R&D input. Also, we estimate the adequate levels of R&D investment, 6.4% for R&D intensity and 13% for the ratio of researchers to employees. This relationship and measurement of the level can offer basic facts and implications about R&D policy and strategy.

• Journal of the Korean Society of Hazard Mitigation
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• v.9 no.1
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• pp.135-144
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• 2009

The objective of this study is to examine the effect of hydrological factors on critical durations, and to analyze the relationship between the watershed characteristics and the critical duration of design rainfall in the medium sized catchments. Hydrological factors are used to return period, probable intensity formula, hydrograph method, effective rainfall and temporal pattern of design rainfall. Hydrologic analysis has done over the 44 medium sized catchments with $50{\sim}5,000{\beta}{\yen}$. Watershed characteristics such as catchment area, channel length, channel slope, catchment slope, time to peak, concentration of time and curve number were used to simulate correlation analysis. All of hydrological factors except return period influence to the critical duration of design rainfall. Also, it is revealed that critical duration is influenced by the watershed characteristics such as area, channel length, channel slope and catchment slope. Multiple regression analysis using watershed characteristics is carried out for the estimation of relationship among these. And the 7 type equations are proposed by the multiple regression using watershed characteristics and critical duration of design rainfall. The determination coefficient of multiple regression equations shows $0.96{\sim}0.97$.

• Journal of Animal Science and Technology
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• v.54 no.6
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• pp.395-400
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• 2012

This study was conducted to estimate the growth curve parameters for the body weight (BW) and body length (BL) of miniature pigs in Korea. Growth curve parameters were estimated through a nonlinear regression model using Gompertz, Logistic, and von Bertalanffy methods. A total of 25 piglets were measured monthly from birth up to 15 months of age to estimate both body weight and length. Results showed that the estimated average values for the body weight (body length) were 31.83 kg (58.77 cm) for the mature weight (A), 3.06 (1.74) for the growth ratio (${\beta}$), and 0.28 (0.52) for the maturing rate (${\kappa}$). Average inflection points showing maximum growth rate estimated each month for body weight were 3.97 kg and 11.70 cm, while for the body length were 1.06 kg and 21.61 cm. Moreover, the estimated maturation rates of the body weight and length for the group of Sire 1 were 0.22 and 0.40 respectively, whereas for the group of Sire 2 these values were 0.34 and 0.39. On the other hand, for the groups of Dam 1, Dam 2, and Dam 3, maturation rates for their body weights were 0.26, 0.28 and 0.33 respectively, while for their body lengths these values were 0.43, 0.37, and 0.38, respectively. The study also indicated a negative relationship between the values of mature weight and maturity rate for the body weight will result to a higher inflection point which is in contrast for the body length where results show that a positive relationship between the values of mature length and the maturity rate will result to a higher inflection point. Furthermore, the growth performance of miniature pig varies across stages but using these estimated growth curve parameters could improve the genetic traits of miniature pig.

• Journal of Animal Science and Technology
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• v.46 no.4
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• pp.503-508
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• 2004

This study was conducted to estimate the growth curve parameters of crossbreds between Korean native boars and Landrace sows and their relationships with meat qualities. The data used were weight-age data and carcass data from 131 males and 122 females raised at N.L.R.I in Korea. Growth curve parameters were estimated from nonlinear regression using Gompertz model individually. Average mature weight(A), average maturing rate(k), and average inflection point(u) showing maximum growth rate estimated were 179.54${\pm}$6.06kg, 0.3154${\pm}$0.0059, and 5.50${\pm}$0.11 months in females, and 179.84${\pm}$6.33kg, 0.3049${\pm}$0.0061, and 5.24${\pm}$0.13 months in males, respectively. For the growth curve parameters and derived statistics, the phenotypic correlations of maturing rate with gain rate at inflection, mature weight, and inflection point were - .30, - .77, and - .93 in male, and - .31, - .78 and - .94 in female, respectively. Matrure weight was positively correlated to the inflection point as + .89 in both male and female, indicating that late maturing pigs with lower k had longer maturing period with increasing gain rate and reached point of inflection later than early maturing pigs with higher k, and grew to larger mature weight. Backfat thickness and erode fat contents were correlated with mature weight positively in male and negatively in female, and correlated with gain rate at inflection point positively in both male and female, of which coefficients were as high as .42 and .50 in male, respectively.

• Journal of Korea Water Resources Association
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• v.35 no.6
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• pp.715-727
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• 2002

The travel time of a flood through a river reach can be estimated by dividing the river length by the mean velocity with which the flood passes downstream. It is closely related to storage constant for the watershed routing of a flood. There are so many empirical formulas available for the estimation of travel time but the results computed generally show great different depending on individual formulas. In the present study, the mean velocity data computed in the process of water surface profile computation for a probability flood through more than 100 different river reaches were collected along with the mean river bed slope of each river reach. And then, a regression analysis is made between the mean river bed slope and the mean velocity, which showed a wide scatter along the mean regression curve, which appears to be due to the different in the magnitude of probability rainfall and size of watershed area. Therefore, methods have been developed to remove the effect of these factors and generalized empirical equation is proposed to relate the mean velocity to mean river bed slope of a reach. Hence, if the mean river bed slope of a river reach is estimated from the longitudinal river profile, the mean velocity can be computed by the generalized equation along with the probability rainfall and watershed area of the river reach under consideration, which leads to the estimation of travel time through a river reach.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.5
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• pp.273-278
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• 2019

In this study, a new simple method for the estimation of hyperelastic material properties by indentation tests is proposed. Among hyperelastic material models, the Yeoh model with three material properties ($C_{10}$, $C_{20}$, $C_{30}$) is adopted to describe the strain energy density in terms of strain invariants. Finite element simulations of the spherical indentation of hyperelastic materials of the Yeoh model with different material properties are performed to establish a database of indentation force-displacement curves. The indentation force-displacement curves are fitted by cubic polynomials, which are approximated as a product of third-order polynomials of ($C_{10}$, $C_{20}$, $C_{30}$). A regression analysis is conducted to determine the coefficients of the equations for the indentation force-displacement curve approximations. A regression equation is used to estimate the hyperelastic material properties. The present method is verified by comparing the estimated material properties with true values.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.829-833
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• 2006

갈수량(low flow)은 과거 자연상태 하천에서 갈수기에 흘렀던 유량으로서 자연과 사람이 공유할 수 있는 최소한의 유량이며, 이수측면에서 하천수의 공급능력을 평가하여 취수량을 설정하는 기준 유량이다. 일본과 국내에서는 지금까지 일유량의 유황곡선(flow duration curve)을 분석하여 평균갈수량, 기준갈수량 등을 결정하고 이를 갈수량의 지표로 이용하여 왔다. 그러나 미국과 영국 등에서는 7일 동안의 유량을 통계분석하여 만든 10년빈도 7일 최저유량$(7Q_{10})$을 갈수량 지표로 사용하고 있다. 본 연구에서는 위의 두 지표를 실험을 통해 비교하여 서로의 장단점을 우선 고찰하여 보았다. 갈수량 산정을 위해서는 과거의 관측 유량자료가 필요하나 국내에는 수위 관측시설이 한정되어 있을 뿐 아니라 홍수기에 비해 갈수기 자료가 턱없이 부족하여 갈수량 산정에 많은 어려움을 겪고 있다. 국내에서는 대부분 유역면적을 이용한 비유량법으로 계측유역으로부 터 미계측유역의 갈수량을 산정하고 있다. 본 연구에서는 미계측유역(ungauged basin)의 갈수량을 산정하기 위한 방법으로 지역회귀기법(regional regression method)을 국내에 적용하여 보았다. 이를 위해 9개 수위관측소 유역과 7개 댐 유역의 과거 유량자료를 이용하였으며, 교차검증(cross validation)을 통해 갈수량 산정결과의 정확도 검증을 실시하였다.