• Journal of the Korean Society for information Management
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• v.29 no.2
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• pp.193-204
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• 2012

The characteristics of citation and centrality measures in citation networks can be identified using multiple linear regression analyses. In this study, we examine the relationships between bibliometric indices and centrality measures in an article-level co-citation network to determine whether the linear model is the best fitting model and to suggest the necessity of data transformation in the analysis. 703 highly cited articles in Physics published in 2004 were sampled, and four indicators were developed as variables in this study: citation counts, degree centrality, closeness centrality, and betweenness centrality in the co-citation network. As a result, the relationship pattern between citation counts and degree centrality in a co-citation network fits a non-linear rather than linear model. Also, the relationship between degree and closeness centrality measures, or that between degree and betweenness centrality measures, can be better explained by non-linear models than by a linear model. It may be controversial, however, to choose non-linear models as the best-fitting for the relationship between closeness and betweenness centrality measures, as this result implies that data transformation may be a necessary step for inferential statistics.

• The Korean Journal of Applied Statistics
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• v.11 no.2
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• pp.451-459
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• 1998

The analysis of data from a multiresponse experiment requires careful consideration of the multivariate nature of the data. In a multiresponse sitation, the optimization problem is more complex than in the single response case. The biplot is a graphical tool which make the analyst to understand the correlation of the response variables, the relation of the response variables arid the explanatory variables and the relative importance of the explanatory variables. In case of good fitting of the first order model, we can draw the biplot with the first order experimental design. Otherwise, we can make the biplot with the second order experimental design by adding other experimental points.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.4
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• pp.1-10
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• 2022

Attempts to interpret human perspectives using computer vision have been developed in various fields. In this paper, we propose a method for evaluating the walking environment through semantic segmentation results of images from road images. First, the Kakao Map API was used to collect road images, and four-way images were collected from about 50,000 points in JeonJu. 20% of the collected images build datasets through crowdsourcing-based paired comparisons, and train various regression models using paired comparison data. In order to derive the walkability score of the image data, the ranking score is calculated using the Trueskill algorithm, which is a ranking algorithm, and the walkability and analysis using various regression models are performed using the constructed data. Through this study, it is shown that the walkability of Jeonju can be evaluated and scores can be derived through the correlation between pixel distribution classification information rather than human vision.

• Water for future
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• v.28 no.4
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• pp.195-204
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• 1995

New dispersion coefficient equation which can be used to estimate dispersion coefficient by using only hydraulic data easily obtained in natural streams has been developed. Dimensional analysis was performed to select physically meaningful parameters, One-Step Huber method, which is one of the nonlinear multi-regression method, was applied to derive a regression equation of dispersion coefficient. 59 measured hydraulic data which were collected in 26 streams in the United States and were analyzed in the Part I of this study, were used in developing new dispersion coefficient equation. Among 59 measured data sets, 35 data sets were used in deriving regression equation, and 24 data sets are used for verification. The new dispersion coefficient equation, which has been developed in this study was proven to be superior in explaining dispersion characteristics of natural streams more precisely compared to existing dispersion coefficient equations.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.412-427
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• 2016

댐의 건설은 자연하천에서 퇴적과 침식의 유사 순환과정에 영향을 주고 저수지 퇴사(reservoir sedimentation)를 야기한다. 이러한 현상은 댐의 건설 이후 장기간 축적되면서 이수와 취수에 대한 영향을 가져오기 때문에 댐 관리와 설계를 위해 정확한 추정이 필요하다. 퇴사량을 산정하는 방법에는 실측자료를 방법과 실제 유사량 자료를 이용하는 방법 그리고 경험공식을 이용하는 방법 등이 있으나, 가용한 자료의 부족으로 주로 경험 공식에 의존하고 있다. 이에 본 연구에서는 국내 대규모 다목적댐에 적합한 비퇴사량 산정 경험 공식을 제안하고자 하였다. 이를 위해 먼저 기존의 공식을 조사 및 검토하여 비퇴사량에 영향을 미칠 만한 여러 인자들을 선정하였다. 총 8개 국내 대규모 다목적댐의 비퇴사량 자료와 제원을 이용하여 다중 회귀분석을 실시하여 최종적인 식을 제안하였다. 그 결과, 대규모 다목적댐의 비퇴사량에 영향을 미치는 인자로 연평균 강우량(P, mm),연평균 유입량(I, cms), 유역 평균경사(S, %),저수지 길이(L, km),저수용량/유역면적(C/A, $m^3/km^2$)을 채택하였으며, 제안된 식을 이용하여 산정한 비퇴사량과 실측 비퇴사량의 상관계수와 결정계수는 각각 0.985, 0.970으로 확인되었다. 아울러, 다중 공선성 분석에서도 모두 일반적인 기준치를 범위 안에 존재함을 확인하면서, 선정된 독립변수들이 통계적으로 유의함을 확인하였다. 허나, 가용 자료의 부족과 불확실성으로 인해 여전히 한계점이 존재한다. 충분한 비퇴사량 실측 자료가 구축된다면, 보다 신뢰도 높고 발전된 형태의 경험 공식의 제안이 가능할 것이다.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.19-43
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• 2016

This study examines the causes of the Asian exchange rate crisis and compares it to the European Monetary System crisis. In 1997, emerging countries in Asia experienced financial crises. Previously in 1992, currencies in the European Monetary System had undergone the same experience. This was followed by Mexico in 1994. The objective of this paper lies in the generation of useful insights from these crises. This research presents a comparison of South Korea, United Kingdom and Mexico, and then compares three different models for prediction. Previous studies of economic crisis focused largely on the manual construction of causal models using linear techniques. However, the weakness of such models stems from the prevalence of nonlinear factors in reality. This paper uses a structural equation model to analyze the causes, followed by a neural network model to circumvent the linear model's weaknesses. The models are examined in the context of predicting exchange rates In this paper, data were quarterly ones, and Consumer Price Index, Gross Domestic Product, Interest Rate, Stock Index, Current Account, Foreign Reserves were independent variables for the prediction. However, time periods of each country's data are different. Lisrel is an emerging method and as such requires a fresh approach to financial crisis prediction model design, along with the flexibility to accommodate unexpected change. This paper indicates the neural network model has the greater prediction performance in Korea, Mexico, and United Kingdom. However, in Korea, the multiple regression shows the better performance. In Mexico, the multiple regression is almost indifferent to the Lisrel. Although Lisrel doesn't show the significant performance, the refined model is expected to show the better result. The structural model in this paper should contain the psychological factor and other invisible areas in the future work. The reason of the low hit ratio is that the alternative model in this paper uses only the financial market data. Thus, we cannot consider the other important part. Korea's hit ratio is lower than that of United Kingdom. So, there must be the other construct that affects the financial market. So does Mexico. However, the United Kingdom's financial market is more influenced and explained by the financial factors than Korea and Mexico.

• Journal of the Korean Geotechnical Society
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• v.37 no.6
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• pp.29-37
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• 2021

Since many geotechnical structures are constructed on a weathered granite layer, it is important to evaluate their characteristics. As a seismic design is the more important nowadays, the demands to estimate a shear wave velocity (V_S) based on acceptable methods are increasing. In this study, an empirical equation predicting V_S of the weathered granite layer is suggested based on the nonlinear multiple variable regression analysis whose independent variables are both SPT (Standard penetration test)-N₆₀ and chemical weathering index. It is concluded that the accuracy of the empirical equation estimating V_S of the weathered granite layer increases when it considers the chemical weathering index as an additional independent variable compared to the result of simple regression analysis using only N₆₀.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2020.12a
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• pp.53-53
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• 2020

본 실험은 다양한 생리활성이 보고되어 약용으로 널리 쓰이는 개똥쑥(Artemisia annua L.) 종자의 온도에 따른 발아 특성을 조사하기 위해 진행하였다. 미세온도구배 발아기를 이용하여 낮과 밤의 온도를 각각 5 ~ 35℃ 범위에서 낮과 밤의 시간을 12시간으로 고정하고, 낮 온도가 밤 온도보다 크거나 같은 조건을 설정하여 총 27개의 온도조건으로 개똥쑥 종자의 최종 발아율 및 발아율과의 관계를 분석하였다. 실험결과, 개똥쑥 종자는 실험에 사용한 모든 온도조건에서 발아가 가능한 것으로 나타났으며, 25/10℃(낮/밤) 조건에서 90%로 가장 높게 조사되었다. 또한, 발아율 조사결과를 통해 일평균온도뿐만 아니라 일교차온도도 발아율에 영향을 미치는 것으로 판단되어 일평균온도와 일교차온도로 나누어 발아율과의 관계를 분석하였다. 온도조건과 발아율과의 연속적인 발아특성을 분석하기 위해 다중회귀분석과 비선형 회귀분석을 이용하여 온도 조건과 상대적 발아율의 관계를 수식으로 표현하였다. 일평균온도를 기준으로 발아율과의 관계를 분석한 결과, 5 ~ 35℃의 모든 일평균 온도범위에서 유의성이 나타났으며 5, 7.5, 32.5, 35℃는 상대적인 음의 영향력을, 나머지 조건에서는 상대적인 양의 영향력을 가진 것으로 분석되었다. 일교차온도를 기준으로 발아율과의 관계를 분석한 결과, 0 ~ 25℃의 모든 일교차 온도범위에서 양의 영향력을 가진 것으로 분석되었다. 일평균온도는 19.3℃에 가까울수록, 일교차온도는 14.9℃에 가까울수록 발아에 대한 영향력이 큰 것으로 조사되었다. 각 수식을 통해 도출된 수치화된 온도에 따른 개똥쑥 종자의 일일누적 온도 영향력을 temperature score(TS)로 설정하였다. 본 연구에서 도출된 수식을 통해 누적 TS를 계산한 결과, 14.9 TS가 누적되었을 때 발아율이 85% 이상으로 나타날 것으로 예측되었다.

• Journal of the Korean Chemical Society
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• v.38 no.3
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• pp.221-223
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• 1994

We tried to apply the linear solvation energy comparison method to solute retention in normal phase liquid chromatography. Correlation coefficients of regression of lnk' collected in a fixed eluent against solute polarity indices have proven to be lower than those obtained from reversed phase liquid chromatography data. This event can be attributed to complexity of solute retention process in normal phase liquid chromatography. We concluded from the regression results that each specific polarity of the stationary phase is greater than that of the mobile phase and that the difference in each polarity between the stationary phase and the mobile phase decreases as the volume fraction(${\phi}$) of the more polar solvent in the mobile phase increases. Correlations of lnk' of a single solute against solvent polarity indices have proven to be meaningless owing to covariance among the solvent polarity indices. Instead, a good linear relationship between lnk' and solvent ${\pi}^*$ was observed, and its linearity is better than that between lnk' and ${\phi}$.

• Korean Journal of Soil Science and Fertilizer
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• v.33 no.4
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• pp.221-233
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• 2000

Evaluation method of soil fertility by application of geographic information system (GIS) which includes landscape characteristics and soil map data was investigated from productivities of red pepper and tobacco grown on the fields with no fertilization. Total 131 fields experiments, 64 fields of red pepper and 67 fields of tobacco were conducted from 22 and 23 fields for red pepper and tobacco, respectively, located at Cheangweon and Eumseong counties in 1996, from 20 and 25 fields at Boeun and Goesan counties in 1997, and 22 and 19 fields at Jincheon and Chungju counties in 1998. All the experimental sites were selected on the basis of wide range of distribution in landscape and soil attributes. Dry weights and nutrients (N, P and K) uptakes by red pepper plant and tobacco leaves were considered as basic fertility of the soil (BFS). The BFS was estimated by twenty-five independent variables including 13 chemical properties and 12 GIS data. Twenty-five independent variables were classified by two groups, 15 quantitative variables and 10 qualitative variables, and were analyzed by multiple linear regression (MLR) of REG and GLM models of SAS. Dry weight of red pepper (DWRP) and dry weight of tobacco leaves (DWTL) every year showed high variations by five times in difference plots with minimum yield and maximum yield indicating the diverse soil fertility among the experimental fields. Evaluation for the BFS by the MLR including independent variables was better than that by simple regression showing gradual improvement by adding chemical properties, quantitative variables, and qualitative variables of the GIS. However the evaluation for the BFS by the MLR showed the better result for tobacco than red pepper. For example the variability in the DWTL by MLR was explained 34.2% by only chemical properties, 35.0% by adding quantitative variables, and 72.5% by adding both the quantitative and qualitative variables of the GIS compared with 21.7% by simple regression with $NO_3-N$ content in soil. Consequently, it is assumed that this approach by the MLR including both the quantitative and qualitative variables was available as an evaluation model of soil fertility for upland field.