• Korea journal of population studies
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• v.26 no.1
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• pp.1-30
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• 2003

This paper attempts to explore the effects of ecological and socioeconomic factors on the level of mortality and the changing trends of such effects during the period of 1990∼2000. For this purpose the population census data and micro-data from the vital statistics for years 1990, 1995 and 2000 were used. As indicators of mortality, the crude death rate(CDR), the standardized death rate(SDR) and the longevity rate were calculated for 170 'Si' s and 'Gun's. Using GIS, this paper first presents the mortality and longevity maps for years 1990, 1995 and 2000. Then ANOVA and regression analyses are carried out in an effort to generalize the effects of ecological and socioeconomic factors on the CDR, the SDR and the longevity rate. When the mortality and longevity maps are examined, three indices of mortality are found to be markedly high in the southwest coastal regions of Cholla-Nam-Do. By contrast, Seoul and Pusan metropolitan areas show substantially low level of mortality and longevity in these indices. It is also found that the regional differentials in the SDR and the longevity rate show a trend of becoming smaller after 1990. The research, however, does not find any linear relationship between the SDR and the longevity rate. The causal mechanisms of the two indices are found to be different. The results of the ANOVA and the regression analysis reveal that the locational factors of both mountainous and farming regions tend to increase the CDR and SDR while both coastal and farming regions disclose a tendency of increasing the longevity rate. The level of statistical significance of these analytical results is found to be weaker when socioeconomic factors such as education, income, marital status, availability of medical care, and sanitary conditions of the region are taken into account. The regional differentials in the mortality level seem to have a clear relationship not only with the socioeconomic factors but also with the age structure influenced by the age selectivity of migration during the past 40 years.

• Journal of Bio-Environment Control
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• v.27 no.1
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• pp.34-39
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• 2018

This research was conducted to estimate moisture content in cucurbitaceae seedlings, such as cucumber and watermelon, using hyperspectral imagery. Using a hyperspectral image acquisition system, the reflectance of leaf area of cucumber and watermelon seedlings was calculated after providing water stress. Then, moisture content in each seedling was measured by using a dry oven. Finally, using reflectance and moisture content, the moisture content estimation models were developed by PLSR analysis. After developing the estimation models, performance of the cucumber showed 0.73 of $R^2$, 1.45% of RMSE, and 1.58% of RE. Performance of the watermelon showed 0.66 of $R^2$, 1.06% of RMSE, and 1.14% of RE. The model performed slightly better after removing one sample from cucumber seedlings as outlier and unnecessary. Hence, the performance of new model for cucumber seedlings showed 0.79 of $R^2$, 1.10% of RMSE, and 1.20% of RE. The model performance combined with all samples showed 0.67 of $R^2$, 1.26% of RMSE, and 1.36% of RE. The model of cucumber showed better performance than the model of watermelon. This is because variables of cucumber are consisted of widely distributed variation, and it affected the performance. Further, accuracy and precision of the cucumber model were increased when an insignificant sample was eliminated from the dataset. Finally, it is considered that both models can be significantly used to estimate moisture content, as gradients of trend line are almost same and intersected. It is considered that the accuracy and precision of the estimating models possibly can be improved, if the models are constructed by using variables with widely distributed variation. The improved models will be utilized as the basis for developing low-priced sensors.