• Journal of the Korea institute for structural maintenance and inspection
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• v.16 no.5
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• pp.29-39
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• 2012

The main objective is to predict the future degradation and maintenance budget for a suspension bridge system. Bayesian inference is applied to find the posterior probability density function of the source parameters (damage indices and serviceability), given ten years of maintenance data. The posterior distribution of the parameters is sampled using a Markov chain Monte Carlo method. The simulated risk prediction for decreased serviceability conditions are posterior distributions based on prior distribution and likelihood of data updated from annual maintenance tasks. Compared with conventional linear prediction model, the proposed quadratic model provides highly improved convergence and closeness to measured data in terms of serviceability, risky factors, and maintenance budget for bridge components, which allows forecasting a future performance and financial management of complex infrastructures based on the proposed quadratic stochastic regression model.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.11
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• pp.1191-1198
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• 2015

In this paper, we develop simplified finite element (FE) models for butt-, lap- and T-welded joints by performing numerical and experimental experiments. Three-point bending tests of butt- and lap-welded specimens are performed to obtain the stiffness of the specimens and the strains at points near the welding beads. Similarly the stiffness and strains of T-welded specimen are measured by applying a point load at the end of the specimen. To develop simplified FE models, we consider the shape parameters of width, thickness and the angle of weld elements in the numerical simulations. The shape parameters of the simplified FE models are determined by building linear regression models for the experimental data sets.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.102-102
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• 2015

최근 중소규모 하천은 하천수 및 하천변 지하수 이용의 증가와 토지이용변화 등 유역 내 수문인자의 특성 변화로 인해 하천의 건천화가 점증하고 있어 하천 환경이 악화되고 있는 실정이다. 본 연구에서는 격자기반의 분포형 장기수문 모델(PGA-CC)을 이용하여 과거 수십년동안 토지이용변화에 따른 하천 건천화 영향을 평가하였다. 실제 건천화가 진행되고 있는 삽교천 상류유역($358.8km^2$)을 선정하였고 토지이용변화분석을 위해 과거 1975년 토지이용도(Past), 현재 2008년 토지이용도(Present)를 구축하였다. 각각의 토지이용 항목 중 변화율이 가장 높은 도시비율은 과거 토지이용도에서는 2.6 %였으며 현재 토지이용도에서는 11.3 %로 8.7 %가 증가하였다. 모델 검보정은 최근 7년(2005-2011)동안 최종유역출구지점에서 유출 검보정을 실시하였다. 그 결과 NSE (Nash-Sutcliffe model efficiency)은 평균 0.71로 유출량의 모의값과 실측값이 유효한 것으로 나타났다. 건천화를 평가하기 위해 시험유역에서의 5 WPs (Watching Points)를 선정하여 과거 및 현재 토지이용조건을 모의하고 유황분석을 통한 갈수 변화량 분석을 실시하였다. 건천화 빈도분석을 위해 GEV (Generalized Extreme Value) 갈수빈도분석을 실시하여 과거 토지이용 모의결과 산정된 평균 갈수량($m^3/s$) 이하로 낮아지는 유출량 일수를 계산하였다. 최종유역출구에서 과거 및 현재 토지이용도에서 모의된 평균갈수량은 각각 $3.27m^3/s$ 및 $3.11m^3/s$로 나타났다. GEV 갈수빈도분석결과 과거 토지이용조건에서의 평균갈수량은 $3.20m^3/s$(재현기간 2.33년)으로 나타났다. 도시증가에 따른 인구증가는 지하수 사용량에 증가를 가져온다. 이는, 건천화에 영향을 미치며 본 연구에서는 지하수이용량 자료(1998-2011)를 이용하여 도시면적과 지하수이용량의 선형회귀분석을 실시하여 과거 22년 지하수 사용량을 예측하였다. 그 결과 지하수사용량 증가는 토지이용변화와 복합적으로 상류유역에 하천의 변화를 가속시키는 것으로 나타냈다.

• Journal of the Korea Society of Computer and Information
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• v.28 no.7
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• pp.57-65
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• 2023

Various studies to enhance the accuracy of rice production forecasting are focused on improving the accuracy of the models. In contrast, there is a relative lack of research regarding the data itself, which the prediction models are applied to. When applying the same dependent variable and prediction model to two different sets of rice production data composed of distinct features, discrepancies in results can occur. It is challenging to determine which dataset yields superior results under such circumstances. To address this issue, by identifying potential influential features within the data before applying the prediction model and centering the modeling around these, it is possible to achieve stable prediction results regardless of the composition of the data. In this study, we propose a method to adjust the composition of the data's features in order to select optimal base variables, aiding in achieving stable and consistent predictions for rice production. This method makes use of the Korea Meteorological Administration's ASOS data. The findings of this study are expected to make a substantial contribution towards enhancing the utility of performance evaluations in future research endeavors.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.350-350
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• 2022

R은 통계 및 빅데이터 분석에 널리 사용되는 오픈 소스 프로그래밍 언어로, 통계와 그래픽스에 관련된 기능을 확정할 수 있어 다양한 분야에 활용되고 있다. 특히, 수자원 분야의 연구에서 그 활용이 늘어나고 있으며, 최근 들어 다양한 수자원 관련 R 패키지가 발표되고 있다. 이중, 미국 지질조사국(U.S. Geological Survey, USGS)이 개발한 EGRET은 수질 및 유출량 자료의 장기 추세 변화 분석을 위한 패키지로 R 프로그래밍 언어를 기반으로 구동되며, 분석·처리한 데이터에 대하여 광범위한 그래픽 프리젠테이션을 제공하여 탐색적 자료 분석에 매우 효과적인 도구이다. 특히, EGRET 패키지는 농도와 유출 사이의 관계 특성, 수집된 자료의 계절성 존재 및 특성, 점진적 또는 급격한 경향의 존재를 검토할 수 있는 그래픽 결과를 제시하며, 가중 회귀(Weighted Regressions on Time, Discharge, and Season, 이하 WRTDS) 모델을 적용하여 농도와 부하의 상태와 경향을 특성화한다. 시간, 유량 및 계절에 대한 WRTDS 모델은 농도 및 부하의 상태와 경향을 특성화하는 데 사용할 수 있는 수질 데이터 세트의 분석 방법으로, 근본적으로 탐색적 데이터 분석 방법으로 다양한 유형의 트렌드 시나리오에 민감하도록 설계되었으며 선형 또는 2차 함수형에 맞지 않을 수 있는 시간적 추세를 탐지하여 설명할 수 있고, 불규칙한 간격의 자료를 사용하기에 적합한 장점이 있다. 본 연구에서는 북한강 상류의 지속적인 흙탕물 발생으로 문제가 되고 있는 자운지구의 자운천을 대상으로 흙탕물 발생 현황을 분석하기 R을 이용하여 탐색적 자료 분석을 실시하였다. 자료 분석은 EGRET 패키지를 사용하여 수집된 자료(2016년 4월 - 2021년 7월까지 수집된 191개의 SS 자료와 인근 유량측정망의 유량자료)의 유량과 SS 농도 간의 관계, 시간에 따른 SS 농도 분포, SS 농도의 월별 특성 분석 및 유황별 SS 농도 변화 등을 검토하였으며, WRTDS 모델로 SS와 부하량을 예측하고 검토하여 자운천 유역의 흙탕물 부하 특성을 검토하였다.

• Korean Journal of Soil Science and Fertilizer
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• v.32 no.2
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• pp.95-108
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• 1999

Field experiments were conducted in the 101 tobacco fields(51 fields in 1985 and 50 fields in 1986) of chief tobacco producing counties of Chungbuk province(Jincheon, Eumseong, Goesan, and Joongweon counties), Chungnam province(Cheonweon county), and Kyongbuk province (Cheongdo, Seongju, and Andong counties) for two years from 1985 to 1986 in order to evaluate soil fertility using chemical properties and soil map database. Pot experiments also on the same soils were conducted and the results were compared to those of field experiments. The yield of tobacco in the plots of no fertilization was considered as a basic factor representing the soil fertility and was evaluated by nineteen independent variables, that was 9 chemical properties and 10 soil map databases. These independent variables were classified into two groups, 11 quantitative indexes and 9 qualitative indexes, and were analyzed by multiple linear regression(MLR) of SAS by REG and GLM models. The yield of tobacco in the plot of no fertilization showed high variations, e.g. the difference between minimum and maximum yields was about 5.0-5.5 times in the pot experiment and 8.2-14.9 times in the field experiment. The indexes indicating close link between yield of tobacco and soil chemical indexes, was selected but it was not well matched by the years or between pot and field experiments. Also, the standardized partial regression coefficients of quantitative indexes for the yield of field were less than 1.0, suggesting that it is difficult to develop an available single index for the evaluation of soil fertility. Evaluation for the soil fertility of field by MLR was better than that of single regression and it was gradually improved by adding chemical properties, quantitative indexes, and qualitative indexes of soil map. For example, the coefficient of determination ($R^2$) of MLR for the yield of 1985 was increased to 0.422 with chemical indexes, 0.503 by addition of quantitative indexes, and 0.633 by the additional adding of qualitative indexes of soil map, compared to 0.244 of single index, $NO_3-N$ content of soil. Consequently, it is assumed that this approach by MLR with quantitative and qualitative indexes including chemical properties and soil map databases was available as an evaluation model of soil fertility for tobacco field.

• Food Science of Animal Resources
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• v.33 no.6
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• pp.796-805
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• 2013

This study was conducted to investigate the relationship between quality factors and freshness or palatability of Hanwoo beef according to storage condition. The drip loss, cooking loss, volatile basic nitrogen (VBN), thiobarbituric acid reactive substance (TBARS), total viable counts (TVC) and sensorial characteristics of Hanwoo beef (raw and cooked) were investigated during storage for 36 d at 0 and $10^{\circ}C$. The drip loss, cooking loss, VBN, and TBARS were increased during storage period. The correlation between these factors and freshness was shown to be highly significant at both $10^{\circ}C$ than $0^{\circ}C$. Especially, correlation of between the cooking loss and freshness of Hanwoo beef showed high significance (p<0.01) at higher storage temperature. The correlation coefficient between factors such as VBN, cooking loss, and TVC and palatability were decreased with increased storage temperature. As a statistical analysis result, a multiple regression equation of $Y_1=10.768-0.706X_1$ (Drip loss) with $R^2=0.87$ was obtained for freshness evaluation of Hanwoo beef. Also, multiple regression with drip loss ($X_1$) and TVC ($X_5$) increased the coefficient of determination for sensorial palatability ($Y_2$) to $R^2=0.95$ with a regression equation of $Y_2=9.702-0.438X_1(Drip\;loss)-0.232X_5(TVC)$.

• Spatial Information Research
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• v.18 no.4
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• pp.1-11
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• 2010

Unlike the previous studies which have focused on 2-dimensional urban characteristics, this paper presents statistical models explaining urban heat island(UHI) effect by 3-dimensional urban morphologic information and addresses its policy implications. 3~dimensional informations of Columbus, Ohio arc captured from LiDAR data and building boundary informations are extracted from a building digital map, Finally NDV[ and temperature data are calculated by manipulating band 3, band 4, and thermal hand of LandSat images. Through complicated data processing, 6 independent variables(building surface area, building volume, height to width ratio, porosity, plan surface area) are introduced in simple and multiple linear regression models. The regression models are specified by Box-Tidwell method, finding the power to which the independent variable needs to raised to be in a linearity. Porosity, NDVI, and building surface area are carefully chosen as explanatory variables in the final multiple regression model, which explaining about 57% of the variability in temperatures. On reducing UHI, various implications of the results give guidelines to policy-making in open space, roof garden, and vertical garden management.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.127-146
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• 2022

Recently, as word embedding has shown excellent performance in various tasks of deep learning-based natural language processing, researches on the advancement and application of word, sentence, and document embedding are being actively conducted. Among them, cross-language transfer, which enables semantic exchange between different languages, is growing simultaneously with the development of embedding models. Academia's interests in vector alignment are growing with the expectation that it can be applied to various embedding-based analysis. In particular, vector alignment is expected to be applied to mapping between specialized domains and generalized domains. In other words, it is expected that it will be possible to map the vocabulary of specialized fields such as R&D, medicine, and law into the space of the pre-trained language model learned with huge volume of general-purpose documents, or provide a clue for mapping vocabulary between mutually different specialized fields. However, since linear-based vector alignment which has been mainly studied in academia basically assumes statistical linearity, it tends to simplify the vector space. This essentially assumes that different types of vector spaces are geometrically similar, which yields a limitation that it causes inevitable distortion in the alignment process. To overcome this limitation, we propose a deep learning-based vector alignment methodology that effectively learns the nonlinearity of data. The proposed methodology consists of sequential learning of a skip-connected autoencoder and a regression model to align the specialized word embedding expressed in each space to the general embedding space. Finally, through the inference of the two trained models, the specialized vocabulary can be aligned in the general space. To verify the performance of the proposed methodology, an experiment was performed on a total of 77,578 documents in the field of 'health care' among national R&D tasks performed from 2011 to 2020. As a result, it was confirmed that the proposed methodology showed superior performance in terms of cosine similarity compared to the existing linear vector alignment.

• Korean Journal of Plant Resources
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• v.25 no.1
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• pp.132-141
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• 2012

This study was carried out to test seed germination responses to temperatures and pre-treatments in Hippophae rhamnoides, which has many abilities in antioxidant activity, soil improvement and erosion control. H. rhamnoides seeds were placed at 10, 15, 20, 25, 30 and $35^{\circ}C$ under light condition. As the results, germination percentage (GP) was the highest at 15 and $20^{\circ}C$, and mean germination time (MGT), germination rate (GR) and germination value (GV) were the highest at $25^{\circ}C$. Quadratic and linear regression model were used to determine the cardinal temperatures such as base ($T_b$), maximum ($T_m$) and optimum ($T_o$) temperature for germination. In quadratic regression model using PG, $T_b$, $T_m$ and $T_o$ was estimated as 0.6, 36.4 and $18.5^{\circ}C$, respectively, and temperature range for germination was $35.8^{\circ}C$. In linear regression model using GR, $T_b$, $T_m$ and $T_o$ was estimated as 8.3, 35.4 and $25.3^{\circ}C$, respectively, and temperature range for germination was $27.2^{\circ}C$. Germination properties were investigated after H. rhamnoides seeds were treated by prechilling (1, 2, 4, 6 and 8 weeks), stratification (2, 4, 6 and 8 weeks), solid matrix priming (seed : carrier : water = 5 : 1 : 7, 8, 9 and 10), osmo-priming (-0.25, -0.5, -1.0 and -1.5 MPa) and calcium chloride ($CaCl_2$) -priming (100, 200, 300 and 400 mM). The highest GP was observed in $CaCl_2$ 300 and 400 mM treatments, and MGT was the shortest in stratification 6 and 8 weeks treatments. GR and GV were the highest and GP was the second highest when seeds were prechilled for 1 and 2 weeks. Consequently, prechilling 1 or 2 weeks treatment was considered as the appropriate method when we contemplate qualitative and quantitative effects in seedling production.