돌기해삼 Apostichopus japonicus는 주요 양식 대상 무척추동물로서 우리나라 연안 해역에 서 식하고 있다. 본 연구는 방류 방법에 따른 단기간의 생리학적 스트레스 정도를 평가하기 위하 여 heat shock protein 90 (HSP90) 유전자의 발현 변화를 실시간 정량적 중합효소연쇄반응법 으로 조사하였다. 어린 돌기해삼을 비닐봉지에 산소 포장하여 30분간 수송하거나 방류 해역의 간조기에 1시간 공기 중에 노출된 실험군의 HSP90 유전자 발현은 대조군의 HSP90 유전자 발현에 비하여 통계학적으로 유의미하게 증가하였다(수송 후 실험군 p=0.001; 간조기 실험군 p=0.032). 어린 돌기해삼을 방류 후 6시간까지 분석한 결과, 선상에서 씨뿌림 방식으로 방류된 6시간째의 개체 및 호스를 통과하여 수중으로 방류된 2~6시간째의 HSP90 유전자 발현율은 대 조군에 비하여 약간 감소하는 경향을 보였다(씨뿌림 실험군 p=0.069; 호스 방류군 p=0.093). 한 편, 잠수부에 의해 수중에서 방류된 어린 돌기해삼은 방류 후 시간이 경과할수록 HSP90 유전 자 발현율은 증가하는 패턴이 관찰되었다(p=0.061). 이상의 결과는 방류된 어린 돌기해삼의 단기간 스트레스 반응 연구와 효과적인 방류 방법의 개발에 HSP90 유전자 발현이 유용하게 사용될 수 있음을 시사한다.

Purpose - This work analyzes, in detail, the specification of vector error correction model (VECM) and thus examines the relationships and impact among seven economic variables for USA - balance on current account (BCA), index of stock (STOCK), gross domestic product (GDP), housing price indices (HOUSING), a measure of the money supply that includes total currency as well as large time deposits, institutional money market funds, short-term repurchase agreements and other larger liquid assets (M3), real rate of interest (IR_REAL) and household credits (LOAN). In particular, we search for the main explanatory variables that have an effect on stock and real estate market, respectively and investigate the causal and dynamic associations between them. Research design, data, and methodology – We perform the time series vector error correction model to infer the dynamic relationships among seven variables above. This work employs the conventional augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) unit root techniques to test for stationarity among seven variables under consideration, and Johansen cointegration test to specify the order or the number of cointegration relationship. Granger causality test is exploited to inspect for causal relationship and, at the same time, impulse response function and variance decomposition analysis are checked for both short-run and long-run association among the seven variables by EViews 9.0. The underlying model was analyzed by using 108 realizations from Q1 1990 to Q4 2016 for USA. Results – The results show that all the seven variables for USA have one unit root and they are cointegrated with at most five and three cointegrating equation for USA. The vector error correction model expresses a long-run relationship among variables. Both IR_REAL and M3 may influence real estate market, and GDP does stock market in USA. On the other hand, GDP, IR_REAL, M3, STOCK and LOAN may be considered as causal factors to affect real estate market. Conclusions – The findings indicate that both stock market and real estate market can be modelled as vector error correction specification for USA. In addition, we can detect causal relationships among variables and compare dynamic differences between countries in terms of stock market and real estate market.

Purpose – This paper aims to examine several time series models to predict sales of department stores and discount store markets in South Korea, while other previous trial has performed sales of convenience stores and supermarkets. In addition, optimal predicted values on the underlying model can be got and be applied to distribution industry. Research design, data, and methodology - Two retailing types, under investigation, are homogeneous and comparable in size based on 86 realizations sampled from January 2010 to February in 2017. To accomplish the purpose of this research, both ARIMA model and exponential smoothing methods are, simultaneously, utilized. Furthermore, model-fit measures may be exploited as important tools of the optimal model-building. Results - By applying Holt-Winters’ additive seasonality method to sales of two large-scale retailing types, persisting increasing trend and fluctuation around the constant level with seasonal pattern, respectively, will be predicted from May in 2017 to February in 2018. Conclusions - Considering 2017-2018 forecasts for sales of two large-scale retailing types, it is important to predict future sales magnitude and to produce the useful information for reforming financial conditions and related policies, so that the impacts of any marketing or management scheme can be compared against the do-nothing scenario.

Purpose – In this work, we examined the causal relationship between credit loans from households (CLH), loan collateralized with housing (LCH) and an interest of certificate of deposit (ICD) among others in South Korea. Furthermore, the optimal forecasts on the underlying model will be obtained and have the potential for applications in the economic field. Research design, data, and methodology – A total of 31 realizations sampled from the 4th quarter in 2008 to the 4th quarter in 2016 was chosen for this research. To achieve the purpose of this study, a regression model with correlated errors was exploited. Furthermore, goodness-of-fit measures was used as tools of optimal model-construction. Results – We found that by applying the regression model with errors component ARMA(1,5) to CLH, the steep and lasting rise can be expected over the next year, with moderate increase of LCH and ICD. Conclusions – Based on 2017-2018 forecasts for CLH, the precipitous and lasting increase can be expected over the next two years, with gradual rise of two major explanatory variables. By affording the assumption that the feedback among variables can exist, we can, in the future, consider more generalized models such as vector autoregressive model and structural equation model, to name a few.

Purpose - In this paper, we categorize and segment the 28 national universities in South Korea and measure the degree of dissimilarity (or similarity) between pairs of ones by using dissimilarity distance matrix and cluster analysis, respectively, based on the seven quantitative evaluation of educational conditions (percentage of small-scale courses, percentage of lecture by the faculty, collection of books per student, material purchase per student, percentage of building capacity, percentage of real estate capacity and rate of accommodation) in 2015. In addition, multidimensional scaling (MDS) techniques can obtain visual representation for exploring patterns of proximities among 28 national universities based on seven attributes of educational conditions. Research design, data, and methodology - This work is carried out by the 2015 Announcement of University Information, which is provided by Ministry of Education in South Korea and utilized by multivariate analyses with CLUSTER, PROXIMITIES and ALSCAL modules in IBM SPSS 23.0. Results - We make certain that 28 national universities can be categorized into five clusters which have similar traits by applying two-stage cluster analysis. MDS is utilized to perform positioning of grouped places of cluster and 28 national universities joining every cluster. Conclusions - Both types and traits of each national university can be relatively assessed and practically utilized for each university competitiveness based on underlying results.

Purpose - In this paper, we consider more segmented types of markets than conventional version of ones in South Korea and explore the degree of relations between these markets and the related factors with them. In this case, ten attributes of types of markets mentioned above will be considered. To be more specific, the numerical strength is evaluated and graphical approach is expressed on two-dimensional plane, if the association exists between the considered variables. Research design, data, and methodology - This work is done by the 2013 report on the commercial building lease offered by Small Businessmen Promotion Institute (May/2013~August/2013) and exploited by statistical analyses such as correspondence analysis and a chi-squared test in IBM SPSS 23.0. Results - Findings of this paper indicate that a variable Korean market, including traditional markets, are closely connected with variables administrative district, sales and occupation instead of company, age group and business duration and the detailed associations between variables can be obtained by inspecting results of correspondence analysis. Conclusions - We can understand where the status of the Korean markets stands now through this work and also government authority and local autonomy can take advantage of these findings to enhance the revitalization of Korean markets and other markets.

dissimilarity (or similarity) between pairs of ones by using dissimilarity distance matrix and cluster analysis, respectively, based on the seven quantitative evaluation of educational conditions (percentage of small-scale courses, percentage of lecture by the faculty, collection of books per student, material purchase per student, percentage of building capacity, percentage of real estate capacity and rate of accommodation) in 2015. In addition, multidimensional scaling (MDS) techniques can obtain visual representation for exploring patterns of proximities among 28 national universities based on seven attributes of educational conditions. Research design, data, and methodology - This work is carried out by the 2015 Announcement of University Information, which is provided by Ministry of Education in South Korea and utilized by multivariate analyses with CLUSTER, PROXIMITIES and ALSCAL modules in IBM SPSS 23.0. Results - We make certain that 28 national universities can be categorized into five clusters which have similar traits by applying two-stage cluster analysis. MDS is utilized to perform positioning of grouped places of cluster and 28 national universities joining every cluster. Conclusions - Both types and traits of each national university can be relatively assessed and practically utilized for each university competitiveness based on underlying results.