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현호색 추출액을 이용한 직물의 천연염색 - 모직물의 염색성과 기능성 -
김관영,이문수,Kim, Kwan-Young,Lee, Mun-Soo 한국의류산업학회 2017 한국의류산업학회지 Vol.19 No.5
In this study, the dyeing conditions(temperature, time, concentration) are changed from various conditions on wool fabrics by using corydalis tuber extract in order to develop new natural dyes. The purpose of this study is to improve the dyeability, color fastness, and functionality and to derive optimal dyeing conditions by comparing and analyzing the changes of K/S values and surface color by dyeing pH changes, mordant method, and mordant type. As a result of the experiment, the optimum dyeing condition of the wool fabrics is shown dyeing temperature:$80^{\circ}C$, dyeing time:90min, dyeing concentration:100%. The dyeability by pH variants of corydalis tuber extract indicates that K/S values is higher alkaline than acidic. The mordant method of corydalis tuber extract showed pre-mordant has high K/S values. In terms of color fastness, marked improvement has not been shown despite of mordant treatment on wool fabrics. In particular, color change of color fastness to washing, color fastness to light indicates the low fastness. In addition, the functionality such as antibacterial activities and deodorization can be given at dyeing with corydalis tuber extract thus it is expected to be applied to underwear or apparel products for the elderly and infirm and children with weak skin that required high functionality.
건설투자(建設投資)의 단기예측모형(短期豫測模型) 비교(比較)
김관영,이창수,Kim, Kwan-young,Lee, Chang-soo 한국개발연구원 1992 韓國 開發 硏究 Vol.14 No.1
본고(本稿)에서는 현재의 경제상황을 잘 반영하는 건설투자활동(建設投資活動)의 단기예측모형(短期豫測模型)을 정립하고자 먼저 관련 시계열자료의 안정성(安定性) 여부(與否)와 순환성(循環性), 계절성(季節性)의 특성을 살펴본 후 여러 단기모형의 예측력(豫測力), 정합성(整合性), 설명력(說明力)을 비교 검토했다. 단위근(單位根) 검정(檢定)과 자기상관계수(自己相關係數) 스펙트랄 밀도함수 분석의 결과, 건설관련 시계열자료들이 대체로 단위근(單位根)을 갖지 않음으로써 안정적이고 주기적인 순환변동을 하고 있으며, 시차변수의 설명력이 높은 특성을 나타내었다. 또한 건설투자자료의 특성이 선행지표(先行指標)인 건축허가연면적(建築許可延面積) 및 건설수주액(建設受注額)과 아주 유사하여 건설투자 단기예측에 있어서 두 지표 사이의 시차관계(時差關係) 파악이 중요함을 알 수 있었다. 제(第)III장(章)에서는 단변량(單變量) 시계열모형(時系列模型)으로 ARIMA모형(模型)과 승법선형추세예측모형(乘法線型趨勢豫測模型)을, 다변량(多變量) 시계열모형(時系列模型)으로는 첫째, 선행지표(先行指標)를 이용한 1차자기회귀모형(次自己回歸模型), VAR모형(模型), 둘째 GNP자료를 이용한 거시경제모형의 단순한 축약형모형(縮約型模型)과 VAR모형(模型)을 제시하고 이들을 비교 평가하였다. 이에 따르면 단변량 시계열모형보다는 다변량 시계열모형이 시간이 경과할수록 예측오차(豫測誤差)가 커지지 않는다는 점에서 우수한 것으로 나타났으며, 다변량모형 중에서도 벡터자기회귀모형이 여타 모형보다 절대예측오차평균(絶對豫測誤差平均), 평균자승근(平均自乘根) 퍼센트 오차(誤差), 결정계수(決定係數) 등 모든 면에서 우수한 것으로 평가되었다. 이는 최근 건설투자가 추세에서 벗어난 급증세를 지속하고 있음을 고려할 때 타당한 결론이라 생각된다. This paper examines characteristics of time series data related to the construction investment(stationarity and time series components such as secular trend, cyclical fluctuation, seasonal variation, and random change) and surveys predictibility, fitness, and explicability of independent variables of various models to build a short-term construction investment forecasting model suitable for current economic circumstances. Unit root test, autocorrelation coefficient and spectral density function analysis show that related time series data do not have unit roots, fluctuate cyclically, and are largely explicated by lagged variables. Moreover it is very important for the short-term construction investment forecasting to grasp time lag relation between construction investment series and leading indicators such as building construction permits and value of construction orders received. In chapter 3, we explicate 7 forecasting models; Univariate time series model (ARIMA and multiplicative linear trend model), multivariate time series model using leading indicators (1st order autoregressive model, vector autoregressive model and error correction model) and multivariate time series model using National Accounts data (simple reduced form model disconnected from simultaneous macroeconomic model and VAR model). These models are examined by 4 statistical tools that are average absolute error, root mean square error, adjusted coefficient of determination, and Durbin-Watson statistic. This analysis proves two facts. First, multivariate models are more suitable than univariate models in the point that forecasting error of multivariate models tend to decrease in contrast to the case of latter. Second, VAR model is superior than any other multivariate models; average absolute prediction error and root mean square error of VAR model are quitely low and adjusted coefficient of determination is higher. This conclusion is reasonable when we consider current construction investment has sustained overheating growth more than secular trend.
김관영(Kwan Young Kim),주만수(Man Soo Joo) 한국지역학회 1998 지역연구 Vol.14 No.1
In this paper, the authors studied a comprehensive study of national physical distribution costs in Korea. A method to calculate national physical distribution costs used here was originally developed by J L. Heskett(1962) and modified in Korean context by Oh-Kyung Kwon(1997). Using this method the authors calculated national physical distribution costs in Korea from 1984 to 1996. Unlike the major industrialized countries, national physical distribution costs in Korea showed continuous increasing trend in every senses. Using this time series data on physical distribution costs, we analyzed the inefficiencies in the physical distribution and figured out the sources of these inefficiencies. The major sources of increasing physical distribution costs in Korea were (1) increasing traffic congestion measured by number of automobiles per road-kilometer, (2) increasing real wages, and (3) high interest rates. Especially, alternatives adopted by firms facing increasing traffic congestion were buying more vehicles, which in turn caused more serious congestion ever. This inefficient cycle in physical distribution area should be cut somehow in order to restore national competitiveness of Korean firms by reducing physical distribution costs.
混合物實驗에서 反應表面의 기울기推定에 適合한 實驗計劃法에 關한 硏究
김관영(Kwan- Young Kim),김정일(Jung-Il Kim) 강원대학교 기초과학연구소 1988 기초과학연구 Vol.5 No.-
혼합물실험에서 반응표면의 기울기추정에 적합한 최적성기준을 기울기회전성개념을 사용하여 제안하고, 그에 의하여 얻어지는 최적실험계획법이 기존에 사용되고 있는 선형최적성기준에 부합됨을 보였다. Designs for estimating the slope of second order Scheffe polynomial response surfaces for mixture experiments are considered. The variance of the estimated slope at a point is a function of the direction of the slope and the design. If the variance is averaged, it is only a function of the design. Minimization of the integration of the averaged variance on the space of predictor variables is taken as the optimal criterion. The resulting designs belong to a more general class of L-optimal designs.