• The Korean Journal of Ecology
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• v.28 no.1
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• pp.15-23
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• 2005

The black locust (Robinia pseudoacacia L.) forests were studied by a phytosociological approach. Particular attention was given to characterize the vegetation classification, distribution pattern, and ecological flora of the syntaxa classified. A total of 38 releves were analyzed by using Correlation coefficient, UPGMA as the clustering method, and Principal Coordinates Analysis for ordination. Ecological flora analyzed by plant character sets such as scrambler, annual and biennial plants, forest elements, and actual urbanization index. The analyzed data are based on site-releve matrix with relative net contribution degree (r-NCD) of species. A total of 77 families, 193 genera and 323 species of vascular plants are recorded. Camellino-Robinietum pseudoacaciae ass. nov. and Phragmites-Robinia pseudoacacia community were described. Main cluster and ordination could be separated: 1) urban type, 2) rural type, 3) riparian type, and 4) combined type. It is defined that the Robinietum is a representative unit on the black locust afforestation, Phragmites-Robinia community on the lentic zone in the river ecosystem, and Cameliino-Robinietum ailanthetosum altissimae as an urban forest type. The Robinietum was considered as a perpetual community.

• Journal of Korea Water Resources Association
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• v.54 no.2
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• pp.121-133
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• 2021

Suspended Solids (SS) generated in rivers are mainly introduced from non-point pollutants or appear naturally in the water body, and are an important water quality factor that may cause long-term water pollution by being deposited. However, the conventional method of measuring the concentration of suspended solids is labor-intensive, and it is difficult to obtain a vast amount of data via point measurement. Therefore, in this study, a model for measuring the concentration of suspended solids based on remote sensing in the Nakdong River was developed using Sentinel-2 data that provides high-resolution multi-spectral satellite images. The proposed model considers the spectral bands and band ratios of various wavelength bands using a machine learning model, Support Vector Regression (SVR), to overcome the limitation of the existing remote sensing-based regression equations. The optimal combination of variables was derived using the Recursive Feature Elimination (RFE) and weight coefficients for each variable of SVR. The results show that the 705nm band belonging to the red-edge wavelength band was estimated as the most important spectral band, and the proposed SVR model produced the most accurate measurement compared with the previous regression equations. By using the RFE, the SVR model developed in this study reduces the variable dependence compared to the existing regression equations based on the single spectral band or band ratio and provides more accurate prediction of spatial distribution of suspended solids concentration.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6A
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• pp.835-842
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• 2008

The response surface method (RSM) is widely adopted for the structural reliability analysis because of its numerical efficiency. However, the RSM is still time consuming for large-scale applications and sometimes shows large errors in the calculation of sensitivity of reliability index with respect to random variables. Therefore, this study proposes a new RSM in which moving least squares (MLS) approximation is applied. Least squares approximation generally used in the common RSM gives equal weight to the coefficients of the response surface function (RSF). On the other hand, The MLS approximation gives higher weight to the experimental points closer to the design point, which yields the RSF more similar to the limit state at the design point. In the procedure of the proposed method, a linear RSF is constructed initially and then a quadratic RSF is formed using the axial experimental points selected from the reduced region where the design point is likely to exist. The RSF is updated successively by adding one more experimental point to the previously sampled experimental points. In order to demonstrate the effectiveness of the proposed method, mathematical problems and ten-bar truss are considered as numerical examples. As a result, the proposed method shows better accuracy and computational efficiency than the common RSM.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5B
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• pp.489-499
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• 2006

The Potential Flood Damage (PFD) is widely used for representing the degree of potential of flood damage. However, this cannot be related with the design frequency of river basin and so we have difficulty in the use of water resources field. Therefore, in this study, the concept of Potential Risk for Flood Damage Occurrence (PRFD) was introduced and estimated, which can be related to the design frequency. The PRFD has three important elements of hazard, exposure, and vulnerability. The hazard means a probability of occurrence of flood event, the exposure represents the degree that the property is exposed in the flood hazard, and the vulnerability represents the degree of weakness of the measures for flood prevention. Those elements were devided into some sub-elements. The hazard is explained by the frequency based rainfall, the exposure has two sub-elements which are population density and official land price, and the vulnerability has two sub-elements which are undevelopedness index and ability of flood defence. Each sub-elements are estimated and the estimated values are rearranged in the range of 0 to 100. The Analytic Hierarchy Process (AHP) is also applied to determine weighting coefficients in the equation of PRFD. The PRFD for the Anyang river basin and the design frequency are estimated by using the maximum rainfall. The existing design frequency for Anyang river basin is in the range of 50 to 200. And the design frequency estimation result of PRFD of this study is in the range of 110 to 130. Therefore, the developed method for the estimation of PRFD and the design frequency for the administrative districts are used and the method for the watershed and the river channel are to be applied in the future study.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.2
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• pp.63-77
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• 2022

Our aim was to reduce estimation errors of a wind velocity model used as an early warning system for weather risk management in the agricultural sector. The Rural Development Administration (RDA) agricultural weather observation network's wind velocity data and its corresponding estimated data from January to December 2020 were used to calculate linear regression equations (Y = aX + b). In each linear regression, the wind estimation error at 87 points and eight time slots per day (00:00, 03:00, 06:00, 09.00, 12.00, 15.00, 18.00, and 21:00) is the dependent variable (Y), while the estimated wind velocity is the independent variable (X). When the correlation coefficient exceeded 0.5, the regression equation was used as the wind velocity correction equation. In contrast, when the correlation coefficient was less than 0.5, the mean error (ME) at the corresponding points and time slots was substituted as the correction value instead of the regression equation. To enable the use of wind velocity model at a national scale, a distribution map with a grid resolution of 250 m was created. This objective was achieved b y performing a spatial interpolation with an inverse distance weighted (IDW) technique using the regression coefficients (a and b), the correlation coefficient (R), and the ME values for the 87 points and eight time slots. Interpolated grid values for 13 weather observation points in rural areas were then extracted. The wind velocity estimation errors for 13 points from January to December 2019 were corrected and compared with the system's values. After correction, the mean ME of the wind velocities reduced from 0.68 m/s to 0.45 m/s, while the mean RMSE reduced from 1.30 m/s to 1.05 m/s. In conclusion, the system's wind velocities were overestimated across all time slots; however, after the correction model was applied, the overestimation reduced in all time slots, except for 15:00. The ME and RMSE improved b y 33% and 19.2%, respectively. In our system, the warning for wind damage risk to crops is driven by the daily maximum wind speed derived from the daily mean wind speed obtained eight times per day. This approach is expected to reduce false alarms within the context of strong wind risk, by reducing the overestimation of wind velocities.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.5
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• pp.705-715
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• 2010

The adoption of carbon foot print system is being activated mostly in the developed countries as one of the long-term response towards tightened up regulations and standards on carbon emission in the agricultural sector. The Korean Ministry of Environment excluded the primary agricultural products from the carbon foot print system due to lack of LCI (life cycle inventory) database in agriculture. Therefore, the research on and establishment of LCI database in the agriculture for adoption of carbon foot print system is urgent. Development of LCA (life cycle assessment) methodology for application of LCA to agricultural environment in Korea is also very important. Application of LCA methodology to agricultural environment in Korea is an early stage. Therefore, this study was carried out to find out the effect of lettuce cultivation on agricultural environment by establishing LCA methodology. Data collection of agricultural input and output for establishing LCI was carried out by collecting statistical data and documents on income from agro and livestock products prepared by RDA. LCA methodology for agriculture was reviewed by investigating LCA methodology and LCA applications of foreign countries. Results based on 1 kg of lettuce production showed that inputs including N, P, organic fertilizers, compound fertilizers and crop protectants were the main sources of major emission factor during lettuce cropping process. The amount of inputs considering the amount of active ingredients was required to estimate the actual quantity of the inputs used. Major emissions due to agricultural activities were $N_2O$ (emission to air) and ${NO_3}^-$/${PO_4}^-$ (emission to water) from fertilizers, organic compounds from pesticides and air pollutants from fossil fuel combustion in using agricultural machines. The softwares for LCIA (life cycle impact assessment) and LCA used in Korea are 'PASS' and 'TOTAL' which have been developed by the Ministry of Knowledge Economy and the Ministry of Environment. However, the models used for the softwares are the ones developed in foreign countries. In the future, development of models and optimization of factors for characterization, normalization and weighting suitable to Korean agricultural environment need to be done for more precise LCA analysis in the agricultural area.

• The Korean Journal of Financial Studies
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• v.9 no.1
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• pp.245-268
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• 2003

전통적인 방법에 의한 PER는 단순히 그 지표의 일반적인 높고 낮음에 따라 소위 '저평가 종목'이라는 이름으로 투자자들에게 추천되고 있다. 그러나 이런 방법은 개별기업의 구체적 내용을 정확하고 종합적으로 고려하지 못하고 있다. 본 연구는 전통적인 방법으로 사용되는 PER지표의 문제점을 개선코자 배당평가 모형으로부터 도출한 PER지표의 구성요소들을 독립변수로 활용 회귀분석을 했다. 그리고 이를 근거로 이론 지표를 만든 후, 그 이론 지표를 투자의사결정에 적용하였을 때의 유효성을 검증했다. PER지표를 구성하는 독립변수는 Kisor & Whitbeck(1963), Malkiel & Cragg(1970), A. Damodaran(1996)에 의해 연구된 것을 원용, PER지표의 구성요소들로 기업의 배당성향, 이익 성장을, 그리고 위험변수로서의 베타계수를 선정했다. 투자성과는 포트폴리오 투자가 일반적인 현실을 감안해 가치가중수익률을 사용한 포트폴리오의 투자성과를 측정했고, 표본은 국내 거래소 시장에 1991년부터 2001년까지 계속 상장된 금융업종을 제외한 전종목을 대상으로 했다. 실증분석에 사용된 기간은 1997년부터 2001년까지 5년 동안의 자료이며, 투자성과를 검증하기 위한 검증모형으로 위험 프리미엄 모형을 사용했다. 먼저 동 분석기간 중 전통적인 방법에 의한 PER효과는 나타나지 않았고, 아울러 기업규모 효과도 찾을 수 없었다. 그러나 회귀분석을 통해 구해진 이론 지표를 활용할 경우, 이론 지표에 비해 시장 지표가 과소 평가된 그룹이 과대 평가된 그룹과 비교할 때 투자성과가 더 우수한 것으로 나타났다. 또한 이론 지표를 통해 PER수준이 낮아짐에 따라 투자성과가 더 높아지는 PER효과도 발견됐다. 이와 같이 이론 지표에 의해 나타나는 PER효과는 기업규모 효과와는 독립적인 것으로 보인다. 외환위기 이후 우리시장에 나타난 차별화 장세 속에 아직도 PER효과나 기업규모 효과와 같은 시장이례 현상이 존재하는지는 관심의 대상이 됐다고 본다. 본 연구에 의하면 기업규모 효과와는 별개의 PER효과가 여전히 존재하며, 다만 이 PER 효과는 전통적 의미의 일반적으로 낮은 PER종목이 초과수익률을 내는 것이 아니라, 기업규모가 크더라도 그 기업의 개별특성을 고려했을 때 이와 비교해 상대적으로 PER가 낮은 종목에 투자하면 초과수익을 낼 수 있음을 의미한다.

• The Korean Journal of Applied Statistics
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• v.28 no.6
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• pp.1217-1225
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• 2015

Survey research, data is commonly collected through a sample design with complex design features that allow the relative efficiency on the precision of an estimator to be measured using the concept of the design effect compared to simple random sampling as a reference design. This concept is most useful when the design effect can be expressed as a function of various design features. We propose a design effect formula suitable under a stratified multistage sampling by generalizing Gabler et al. (1999, 2006)'s approaches for multistage sampling. Its use can either guide improvement in the design efficiency when in design stage or enable the evaluation of the adopted design features afterwards.

• Transactions of the Korean Society of Automotive Engineers
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• v.17 no.4
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• pp.1-9
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• 2009

A simplified model of seat-human body is presented to analyze vibrations of human body on a seat of vehicle. The theoretical model having seven degrees-of-freedom is composed of the inter-connected masses, springs and dampers. Until now, evaluation of ride comfort has been usually performed only through vehicle tests. This study aims to complement shortcomings of conventional vehicle tests in evaluation of ride comfort by using the theoretical model. The acceleration values of the human body are obtained from frequency response functions of the theoretical model. Thereafter, Ride and SEAT indexes are acquired by considering response characteristics of the human body for the 12 axes that are presented in BS 6841. A vehicle test is carried out to measure the acceleration values for the three parts of the human body such as upper body, hip and foot. Ride and SEAT indexes of the vehicle test are also obtained by considering the response characteristics of the human body, of which results are compared with the values from the theoretical model. It is found that the theoretical results are in good agreement with the experimental results.

• Proceedings of the KAIS Fall Conference
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• 2007.05a
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• pp.116-118
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• 2007

비강우시와 강우시 학장천의 수질은 BOD, COD, T-N, T-P, SS에 대해 각각 $11.0{\sim}31.3mg/L$, $15.6{\sim}31.4mg/L$, $5.762{\sim}15.937mg/L$, $0.918{\sim}1.291mg/L$, $18.1{\sim}31.41mg/L$와 $27.2{\sim}65.11mg/L$, $32.1{\sim}73.2rng/L$, $13.409{\sim}18.051mg/L$, $1.263{\sim}2.282mg/L$, $66.0{\sim}417.9mg/L$로 나타나 학장천은 전형적인 생활하수의 특성을 지녔으며, 강우시 발생되는 초기월류수에 다량의 비점오염물질이 포함됨을 알 수 있었다. 강우시 발생된 월류수의 유량을 측정한 결과 학장천의 유출계수는 $0.61{\sim}0.83$의 범위였고, 초기세척효과는 SS>T-N>COD>BOD>T-P>1 의 순서로 그 정도가 크게 나타났다. 학장천 초기월류수의 유량가중평균농도를 산정한 결과 대부분의 항목에서 청천시의 수질농도보다 높게 나타나 강우에 의한 월류수의 비점오염물질의 유출이 심각함을 알 수 있다.