• Korean Journal of Heritage: History & Science
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• v.55 no.1
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• pp.305-321
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• 2022

The stone chamber tomb in Eungpyeong-ri, Buyeo, is a joint tomb that contains the bodies of two individuals. This paper investigates the relationship between the buried persons and the characteristics of the stone chamber tomb. Based on the geographical location, relics, and the excavated human bones, it was determined that the tomb was built during the Sabi Period of the Baekje Dynasty and that the buried individuals were most probably residents of high stature or government officials. To study the excavated bones, the remains were carefully collected and conservation was carried out. Before collecting samples from the human bones for the analytical research, the results of near-infrared analysis were used to collect the samples for the isotope analysis and DNA analysis. The most important issue when handling the excavation site was the reinforcing agent and the concentration of the agent used. In situations like this, Paraloid B-72 is the most suitable agent. When the shape of human bones was difficult to distinguish from the soil, conservation was performed using X-ray and CT imaging data. The same chemical used for the reinforcement of the site was used to complete a minimum level of conservation to the surface areas where the conservation treatment of removing foreign substances, the reinforcement areas, and bonded areas were carried out. The collagen yield from the sample obtained at selected position was 3.8% to 6.1%. The results of analyzing the stable isotopes of carbon and nitrogen found in the extracted collagen showed that the stable isotope ratios came out to δ¹³C -18.3‰±0.1‰, -19.0‰±0.1‰ for EBW and δ¹⁵N 10.7‰±0.5‰, 10.6‰±0.1‰ for EBE. It is believed the two individuals consumed small amounts of minor cereals, mainly from C₃ plants, and protein was obtained from eating terrestrial animals. What's more, the deviations in data obtained from the two individuals were so small that it could be inferred that the individuals ate similar foods. Considering the preservation state of the sample, amplifying DNA for the DNA analysis would have been very difficult since the amount of surviving DNA was so deficient. For DNA analysis, it is anticipated that the results could be derived by applying improved extraction methods that will be developed in the future. In this research, any association between scientific analysis(DNA and stable isotope ratio) and near-infrared spectroscopy was difficult to establish. Further research is needed on the utilization of near-infrared analysis for gathering samples from human bones.

• Journal of agricultural medicine and community health
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• v.47 no.3
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• pp.181-188
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• 2022

Objectives: The prevalence of diabetes mellitus was approximately 16% in populations of over age 30 years, and deaths from diabetes mellitus became the sixth most prevalent cause of death by disease. To assess the relationship between HbA1c and heavy metal level in blood and urine, targeted residents were evaluated in a vast steel industrial complex. Methods: We selected 414 subjects for analysis after applying the following exclusion criterion: 18 persons with diabetes mellitus. They took part in a questionnaire survey and underwent blood and urinary assessments. HbA1c and lead (Pb) level were measured in blood and, cadmium (Cd), inorganic arsenic (iAs) and mercury (Hg) were evaluated in urine. Two subgroups were divided by HbA1c 6.5%. Each subgroup was divided by 10th, 20th, 30th, 40th, 50th, 60th, 70th, 80th and 90th percentile levels of biological exposure index of the heavy metals for logistic regression. Results: Odd ratios have a tendency to increase as they go from the 90th to the 10th percentile of cadmium. However, lead, arsenic and mercury did not have significant relationships with HbA1c. In correction of age, region, gender and smoking history, a higher distribution in the subgroup with cadmium above 0.8318 ㎍/g creatinine (30th percentile) was demonstrated in the subgroup with HbA1c levels above the 6.5%, with an odds ratio of 5.26 (95% C.I. ; 1.44~19.17). Conclusion: This study found a significant correlation between urinary levels of cadmium and HbA1c in correction of several factors. It is meaningful that this outcome may be used as a basis for a study to establish the acceptable limit of urinary cadmium in Korea.

• Magazine of the Korean Society of Agricultural Engineers
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• v.16 no.2
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• pp.3361-3394
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• 1974

The purpose of this thesis is to disclose some characteristics of water consumption in relation to the quantities of dry matters through the growing period for two statured varieties of paddy rice which are a tall statured variety and a short one, including the water consumption during seedling period, and to find out the various coefficients of evapotranspiration that are applicable for the water use of an expected yield of the two varieties. PAL-TAL, a tall statured variety, and TONG-lL, a short statured variety were chosen for this investigation. Experiments were performed in two consecutive periods, a seedling period and a paddy field period, In the investigation of seedling period, rectangular galvanized iron evapotranspirometers (91cm${\times}$85cm${\times}$65cm) were set up in a way of two levels (PAL-TAL and TONG-lL varieties) with two replications. A standard fertilization method was applied to all plots. In the experiment of paddy field period, evapotanspiration and evaporation were measured separately. For PAL-TAL variety, the evapotranspiration measurements of 43 plots of rectangular galvanized iron evapotranspirometer (91cm${\times}$85cm${\times}$65cm) and the evaporation measurements of 25 plots of rectangular galvanized iron evaporimeter (91cm${\times}$85cm${\times}$15cm) have been taken for seven years (1966 through 1972), and for TONG-IL variety, the evapotranspiration measurements of 19 plots and the evaporation measurements of 12 plots have been collected for two years (1971 through 1972) with five different fertilization levels. The results obtained from this investigation are summarized as follows: 1. Seedling period 1) The pan evaporation and evapotranspiration during seedling period were proved to have a highly significant correlation to solar radiation, sun shine hours and relative humidity. But they had no significant correlation to average temperature, wind velocity and atmospheric pressure, and were appeared to be negatively correlative to average temperature and wind velocity, and positively correlative to the atmospheric pressure, in a certain period. There was the highest significant correlation between the evapotranspiration and the pan evaporation, beyond all other meteorological factors considered. 2) The evapotranpiration and its coefficient for PAL-TAL variety were 194.5mm and 0.94∼1.21(1.05 in average) respectively, while those for TONG-lL variety were 182.8mm and 0.90∼1.10(0.99 in average) respectively. This indicates that the evapotranspiration for TONG-IL variety was 6.2% less than that for PAL-TAL variety during a seedling period. 3) The evapotranspiration ratio (the ratio of the evapotranspiration to the weight of dry matters) during the seedling period was 599 in average for PAL-TAL variety and 643 for TONG-IL variety. Therefore the ratio for TONG-IL was larger by 44 than that for PAL-TAL variety. 4) The K-values of Blaney and Criddle formula for PAL-TAL variety were 0.78∼1.06 (0.92 in average) and for TONG-lL variety 0.75∼0.97 (0.86 in average). 5) The evapotranspiration coefficient and the K-value of B1aney and Criddle formular for both PAL-TAL and TONG-lL varieties showed a tendency to be increasing, but the evapotranspiration ratio decreasing, with the increase in the weight of dry matters. 2. Paddy field period 1) Correlation between the pan evaporation and the meteorological factors and that between the evapotranspiration and the meteorological factors during paddy field period were almost same as that in case of the seedling period (Ref. to table IV-4 and table IV-5). 2) The plant height, in the same level of the weight of dry matters, for PAL-TAL variety was much larger than that for TONG-IL variety, and also the number of tillers per hill for PAL-TAL variety showed a trend to be larger than that for TONG-IL variety from about 40 days after transplanting. 3) Although there was a tendency that peak of leaf-area-index for TONG-IL variety was a little retarded than that for PAL-TAL variety, it appeared about 60∼80 days after transplanting. The peaks of the evapotranspiration coefficient and the weight of dry matters at each growth stage were overlapped at about the same time and especially in the later stage of growth, the leaf-area-index, the evapotranspiration coefficient and the weight of dry matters for TONG-IL variety showed a tendency to be larger then those for PAL-TAL variety. 4) The evaporation coefficient at each growth stage for TONG-IL and PAL-TALvarieties was decreased and increased with the increase and decrease in the leaf-area-index, and the evaporation coefficient of TONG-IL variety had a little larger value than that of PAL-TAL variety. 5) Meteorological factors (especially pan evaporation) had a considerable influence to the evapotranspiration, the evaporation and the transpiration. Under the same meteorological conditions, the evapotranspiration (ET) showed a increasing logarithmic function of the weight of dry matters (x), while the evaporation (EV) a decreasing logarithmic function of the weight of dry matters; 800kg/10a x 2000kg/10a, ET=al+bl logl0x (bl>0) EV=a2+b2 log10x (a2>0 b2<0) At the base of the weight of total dry matters, the evapotranspiration and the evaporation for TONG-IL variety were larger as much as 0.3∼2.5% and 7.5∼8.3% respectively than those of PAL-TAL variety, while the transpiration for PAL-TAL variety was larger as much as 1.9∼2.4% than that for TONG-IL variety on the contrary. At the base of the weight of rough rices the evapotranspiration and the transpiration for TONG-IL variety were less as much as 3.5% and 8.l∼16.9% respectively than those for PAL-TAL variety and the evaporation for TONG-IL was much larger by 11.6∼14.8% than that for PAL-TAL variety. 6) The evapotranspiration coefficient, the evaporation coefficient and the transpiration coefficient and the transpiration coefficient were affected by the weight of dry matters much more than by the meteorological conditions. The evapotranspiratioa coefficient (ETC) and the evaporation coefficient (EVC) can be related to the weight of dry matters (x) by the following equations: 800kg/10a x 2000kg/10a, ETC=a3+b3 logl0x (b3>0) EVC=a4+b4 log10x (a4>0, b4>0) At the base of the weights of dry matters, 800kg/10a∼2000kg/10a, the evapotranspiration coefficients for TONG-IL variety were 0.968∼1.474 and those for PAL-TAL variety, 0.939∼1.470, the evaporation coefficients for TONG-IL variety were 0.504∼0.331 and those for PAL-TAL variety, 0.469∼0.308, and the transpiration coefficients for TONG-IL variety were 0.464∼1.143 and those for PAL-TAL variety, 0.470∼1.162. 7) The evapotranspiration ratio, the evaporation ratio (the ratio of the evaporation to the weight of dry matters) and the transpiration ratio were highly affected by the meteorological conditions. And under the same meteorological condition, both the evapotranspiration ratio (ETR) and the evaporation ratio (EVR) showed to be a decreasing logarithmic function of the weight of dry matters (x) as follows: 800kg/10a x 2000kg/10a, ETR=a5+b5 logl0x (a5>0, b5<0) EVR=a6+b6 log10x (a6>0 b6<0) In comparison between TONG-IL and PAL-TAL varieties, at the base of the pan evaporation of 343mm and the weight of dry matters of 800∼2000kg/10a, the evapotranspiration ratios for TONG-IL variety were 413∼247, while those for PAL-TAL variety, 404∼250, the evaporation ratios for TONG-IL variety were 197∼38 while those for PAL-TAL variety, 182∼34, and the transpiration ratios for TONG-IL variety were 216∼209 while those for PAL-TAL variety, 222∼216 (Ref. to table IV-23, table IV-25 and table IV-26) 8) The accumulative values of evapotranspiration intensity and transpiration intensity for both PAL-TAL and TONG-IL varieties were almost constant in every climatic year without the affection of the weight of dry matters. Furthermore the evapotranspiration intensity appeared to have more stable at each growth stage. The peaks of the evapotranspiration intensity and transpiration intensity, for both TONG-IL and PAL-TAL varieties, appeared about 60∼70 days after transplanting, and the peak value of the former was 128.8${\pm}$0.7, for TONG-IL variety while that for PAL-TAL variety, 122.8${\pm}$0.3, and the peak value of the latter was 152.2${\pm}$1.0 for TONG-IL variety while that for PAL-TAL variety, 152.7${\pm}$1.9 (Ref.to table IV-27 and table IV-28) 9) The K-value in Blaney & Criddle formula was changed considerably by the meteorological condition (pan evaporation) and related to be a increasing logarithmic function of the weight of dry matters (x) for both PAL-TAL and TONG-L varieties as follows; 800kg/10a x 2000kg/10a, K=a7+b7 logl0x (b7>0) The K-value for TONG-IL variety was a little larger than that for PAL-TAL variety. 10) The peak values of the evapotranspiration coefficient and k-value at each growth stage for both TONG-IL and PAL-TAL varieties showed up about 60∼70 days after transplanting. The peak values of the former at the base of the weights of total dry matters, 800∼2000kg/10a, were 1.14∼1.82 for TONG-IL variety and 1.12∼1.80, for PAL-TAL variety, and at the base of the weights of rough rices, 400∼1000 kg/10a, were 1.11∼1.79 for TONG-IL variety and 1.17∼1.85 for PAL-TAL variety. The peak values of the latter, at the base of the weights of total dry matters, 800∼2000kg/10a, were 0.83∼1.39 for TONG-IL variety and 0.86∼1.36 for PAL-TAL variety and at the base of the weights of rough rices, 400∼1000kg/10a, 0.85∼1.38 for TONG-IL variety and 0.87∼1.40 for PAL-TAL variety (Ref. to table IV-18 and table IV-32) 11) The reasonable and practicable methods that are applicable for calculating the evapotranspiration of paddy rice in our country are to be followed the following priority a) Using the evapotranspiration coefficients based on an expected yield (Ref. to table IV-13 and table IV-18 or Fig. IV-13). b) Making use of the combination method of seasonal evapotranspiration coefficient and evapotranspiration intensity (Ref. to table IV-13 and table IV-27) c) Adopting the combination method of evapotranspiration ratio and evapotranspiration intensity, under the conditions of paddy field having a higher level of expected yield (Ref. to table IV-23 and table IV-27). d) Applying the k-values calculated by Blaney-Criddle formula. only within the limits of the drought year having the pan evaporation of about 450mm during paddy field period as the design year (Ref. to table IV-32 or Fig. IV-22).

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.1-32
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• 2018

In addition to stakeholders including managers, employees, creditors, and investors of bankrupt companies, corporate defaults have a ripple effect on the local and national economy. Before the Asian financial crisis, the Korean government only analyzed SMEs and tried to improve the forecasting power of a default prediction model, rather than developing various corporate default models. As a result, even large corporations called 'chaebol enterprises' become bankrupt. Even after that, the analysis of past corporate defaults has been focused on specific variables, and when the government restructured immediately after the global financial crisis, they only focused on certain main variables such as 'debt ratio'. A multifaceted study of corporate default prediction models is essential to ensure diverse interests, to avoid situations like the 'Lehman Brothers Case' of the global financial crisis, to avoid total collapse in a single moment. The key variables used in corporate defaults vary over time. This is confirmed by Beaver (1967, 1968) and Altman's (1968) analysis that Deakins'(1972) study shows that the major factors affecting corporate failure have changed. In Grice's (2001) study, the importance of predictive variables was also found through Zmijewski's (1984) and Ohlson's (1980) models. However, the studies that have been carried out in the past use static models. Most of them do not consider the changes that occur in the course of time. Therefore, in order to construct consistent prediction models, it is necessary to compensate the time-dependent bias by means of a time series analysis algorithm reflecting dynamic change. Based on the global financial crisis, which has had a significant impact on Korea, this study is conducted using 10 years of annual corporate data from 2000 to 2009. Data are divided into training data, validation data, and test data respectively, and are divided into 7, 2, and 1 years respectively. In order to construct a consistent bankruptcy model in the flow of time change, we first train a time series deep learning algorithm model using the data before the financial crisis (2000~2006). The parameter tuning of the existing model and the deep learning time series algorithm is conducted with validation data including the financial crisis period (2007~2008). As a result, we construct a model that shows similar pattern to the results of the learning data and shows excellent prediction power. After that, each bankruptcy prediction model is restructured by integrating the learning data and validation data again (2000 ~ 2008), applying the optimal parameters as in the previous validation. Finally, each corporate default prediction model is evaluated and compared using test data (2009) based on the trained models over nine years. Then, the usefulness of the corporate default prediction model based on the deep learning time series algorithm is proved. In addition, by adding the Lasso regression analysis to the existing methods (multiple discriminant analysis, logit model) which select the variables, it is proved that the deep learning time series algorithm model based on the three bundles of variables is useful for robust corporate default prediction. The definition of bankruptcy used is the same as that of Lee (2015). Independent variables include financial information such as financial ratios used in previous studies. Multivariate discriminant analysis, logit model, and Lasso regression model are used to select the optimal variable group. The influence of the Multivariate discriminant analysis model proposed by Altman (1968), the Logit model proposed by Ohlson (1980), the non-time series machine learning algorithms, and the deep learning time series algorithms are compared. In the case of corporate data, there are limitations of 'nonlinear variables', 'multi-collinearity' of variables, and 'lack of data'. While the logit model is nonlinear, the Lasso regression model solves the multi-collinearity problem, and the deep learning time series algorithm using the variable data generation method complements the lack of data. Big Data Technology, a leading technology in the future, is moving from simple human analysis, to automated AI analysis, and finally towards future intertwined AI applications. Although the study of the corporate default prediction model using the time series algorithm is still in its early stages, deep learning algorithm is much faster than regression analysis at corporate default prediction modeling. Also, it is more effective on prediction power. Through the Fourth Industrial Revolution, the current government and other overseas governments are working hard to integrate the system in everyday life of their nation and society. Yet the field of deep learning time series research for the financial industry is still insufficient. This is an initial study on deep learning time series algorithm analysis of corporate defaults. Therefore it is hoped that it will be used as a comparative analysis data for non-specialists who start a study combining financial data and deep learning time series algorithm.