• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.79-94
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• 2013

Recently, the high value added business is steadily growing in the culture and art area. To generated high value from a performance, the satisfaction of audience is necessary. The flow in a critical factor for satisfaction, and it should be induced from audience and measures. To evaluate interest and emotion of audience on contents, producers or investors need a kind of index for the measurement of the flow. But it is neither easy to define the flow quantitatively, nor to collect audience's reaction immediately. The previous studies of the group flow were evaluated by the sum of the average value of each person's reaction. The flow or "good feeling" from each audience was extracted from his face, especially, the change of his (or her) expression and body movement. But it was not easy to handle the large amount of real-time data from each sensor signals. And also it was difficult to set experimental devices, in terms of economic and environmental problems. Because, all participants should have their own personal sensor to check their physical signal. Also each camera should be located in front of their head to catch their looks. Therefore we need more simple system to analyze group flow. This study provides the method for measurement of audiences flow with group synchronization at same time and place. To measure the synchronization, we made real-time processing system using the Differential Image and Group Emotion Analysis (GEA) system. Differential Image was obtained from camera and by the previous frame was subtracted from present frame. So the movement variation on audience's reaction was obtained. And then we developed a program, GEX(Group Emotion Analysis), for flow judgment model. After the measurement of the audience's reaction, the synchronization is divided as Dynamic State Synchronization and Static State Synchronization. The Dynamic State Synchronization accompanies audience's active reaction, while the Static State Synchronization means to movement of audience. The Dynamic State Synchronization can be caused by the audience's surprise action such as scary, creepy or reversal scene. And the Static State Synchronization was triggered by impressed or sad scene. Therefore we showed them several short movies containing various scenes mentioned previously. And these kind of scenes made them sad, clap, and creepy, etc. To check the movement of audience, we defined the critical point, ${\alpha}$and ${\beta}$. Dynamic State Synchronization was meaningful when the movement value was over critical point ${\beta}$, while Static State Synchronization was effective under critical point ${\alpha}$. ${\beta}$ is made by audience' clapping movement of 10 teams in stead of using average number of movement. After checking the reactive movement of audience, the percentage(%) ratio was calculated from the division of "people having reaction" by "total people". Total 37 teams were made in "2012 Seoul DMC Culture Open" and they involved the experiments. First, they followed induction to clap by staff. Second, basic scene for neutralize emotion of audience. Third, flow scene was displayed to audience. Forth, the reversal scene was introduced. And then 24 teams of them were provided with amuse and creepy scenes. And the other 10 teams were exposed with the sad scene. There were clapping and laughing action of audience on the amuse scene with shaking their head or hid with closing eyes. And also the sad or touching scene made them silent. If the results were over about 80%, the group could be judged as the synchronization and the flow were achieved. As a result, the audience showed similar reactions about similar stimulation at same time and place. Once we get an additional normalization and experiment, we can obtain find the flow factor through the synchronization on a much bigger group and this should be useful for planning contents.

• Korean Journal of Breeding Science
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• v.41 no.1
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• pp.16-24
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• 2009

Although leaf characters are important in soybean [Glycin max (L.) Merr.] breeding and development of cultural methods, very little information has been reported. The objectives of this study were to evaluate and analyze the relationships among leaf characters and suggest possible classification criteria for cultivating and wild (Glycin soja Sieb. & Zucc.) soybeans. Total of 94 cultivating and 91 wild soybean accessions from the Soybean Germplasm Laboratory of Chungbuk National University were used for this study. Central leaflet of the second leaf from the top of the plant was selected to measure leaf characters. Average leaf length, leaf width, leaf area, leaf shape index (LSI) of cultivating and wild soybeans were 12.3$\pm$1.25 cm and 6.6$\pm$1.35 cm, 6.8$\pm$1.241 cm and 2.9$\pm$0.92 cm, 55.6$\pm$15.75 $cm^2$ and 14.3$\pm$7.83 $cm^2$, and 1.9$\pm$0.38 and 2.4$\pm$0.53, respectively. Based on LSI, three categories of leaf shape, i.e., oval, ovate and lanceolate, were defined as LIS$\leq$2.0, LSI 2.1~3.0 and 3.1$\leq$LSI, respectively. Percentage of oval, ovate and lanceolate leaf types among cultivating and wild soybean accessions were 78.7%, 17.0% and 4.3 %, and 40%, 15.4% and 4.4%, respectively. Based on leaf length, three categories for cultivating, i.e. short leaf ($\leq$11.0 cm), intermediate (11.1~13.0 cm), and long (13.1 cm$\leq$), and four categories, i.e. short ($\leq$5.0 cm), intermediate (5.1~7.0 cm), long (7.0~9.0 cm), and very long (9.1 cm$\leq$) for wild soybeans were defined. Short, intermediate and long leaf types were about 1/3, 1/2 and 1/6, respectively, in cultivating soybeans, and 15.4%, 40.7% and 39.5%, plus 4.4% of very long leaf type in wild soybean. Cultivating and wild soybeans had leaf thickness, leaf area ratio (LAR), angle and petiol length of 0.25$\pm$0.054 mm and 0.14$\pm$0.032 mm, 40.1$\pm$8.22 and 53.7$\pm$12.02, $37.6{\pm}5.89^{\circ}$ and $54.6{\pm}10.77^{\circ}$, and 23.9$\pm$5.89 cm and 5.9$\pm$2.33 cm, respectively. There were highly significant positive correlations between leaf length and leaf width, and negative correlation between LSI and leaf width both in cultivating and wild soybeans. Although leaf area showed significant correlations with leaf length, leaf width and LIS in cultivating soybeans, wild soybeans showed no significant relationships among these characters. In general, soybeans with oval, ovate and lanceolate leaves were significantly different in leaf width and thickness. Cultivating soybean with oval leaf had greater leaf area, while wild soybeans with oval or ovate leaf had longer petiol than with lanceolate leaf.

• Korean Journal of Soil Science and Fertilizer
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• v.9 no.4
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• pp.235-244
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• 1976

Following results are obtained by re-evaluating N. P. K. and soil improvement trials conducted from 1964 to 1969 in valley paddy soils in rolling lands (Jisan-series, imperfectly drained and Yongji-series, moderately well drained). 1. Average grain yield of rice in no fertilizer plots and the highest yield plots for Yongji-series (31 experiments) were 319 and 507kg/10a respectively, and that of Jisan-series (15 experiments) were 396 and 567kg/10a respectively. The fertility difference between two series may have been a result of the cultivation history. Jisan-series is a mature soil which has a long cultivation history and Yongji-series is sub-mature soil 2. Soil chemical characteristics for Jisan-series are charaterized by 12.8meq/100g in CEC, 6.5meq/100g in exchangeable Ca, 3.9% in OM, and 64 ppm in available $P_2O_5$ For Yongji-series they were 10.4meq/100g in CEC, 4.7meq/100g in exchangeable Ca, 3.2% in OM and 103ppm in available $P_2O_5$. 3. Deep plowing and application of organic matter and lime are expected to be effective in increasing fertility level of soils of Yongji-series. The same will be effective in some soils of Jisan series where the fertility level is low. 4. Jisan-series shows high response to nitrogen, while Yongji series shows sharp decrease in rice yield at the high levels of nitrogen. Both series, however, showed high response to nitrogen only when the OM level was higher than 3%. 5. The optimum level of nitrogen was 8~9kg for Jisan-series, and 10~11kg/10a for Yongji-series. The yield increase per kg of applied nitrogen was 12kg for Jisan-series and 13kg for Yongji series. 6. The optimum level of phosphorus at the optimum level of nitrogen was 6kg/10a for Yongji-series and 3kg/10a for Jisan-series. The optimum level of phosphorus, however, was different depending upon the nitrogen level. It was assumed that Yongji-series required more fertilizer (available $P_2O_5$ was 110ppm) than Jisan-series (available $P_2O_5$ was 64ppm) because the availability of P was higher in Jisan-series than Yongji-series due to the severe reduction of Jisan-series. 7. The response of potassium was also depending upon the nitrogen level. In Yongji-series the potassium response at 8kg/10a nitrogen level decreased with increasing levels of potassium, but the higher level of introgen, potassium response was also higher. In Jisan-series potassium response was recognized at all nitrogen levels. The optimum level of potassium at the optimum level of nitrogen was 8kg/10a in both serieses. 8. The reasonable ratio of NPK fertilizer seems to be 1:0.6:0.6:for Yongji-series and 1:0.4:1 for Jisan-series as N:$P_2O_5$:K.

• Korean Journal of Environmental Agriculture
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• v.37 no.4
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• pp.291-301
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• 2018

BACKGROUND: Rice is one of the main sources for inorganic arsenic among the consumed crops in the world population's diet. Arsenic is classified into Group 1 as it is carcinogenic for humans, according to the IARC. This study was carried out to assess dietary exposure risk of inorganic arsenic in husked rice and polished rice to the Korean population health. METHODS AND RESULTS: Total arsenic was determined using microwave device and ICP-MS. Inorganic arsenic was determined by ICP-MS coupled with HPLC system. The HPLC-ICP-MS analysis was optimized based on the limit of detection, limit of quantitation, and recovery ratio to be $0.73-1.24{\mu}g/kg$, $2.41-4.09{\mu}g/kg$, and 96.5-98.9%, respectively. The inorganic arsenic concentrations of daily exposure (included in body weight) were $4.97{\times}10^{-3}$ (${\geq}20$ years old) $-1.36{\times}10^{-2}$ (${\leq}2$ years old) ${\mu}g/kg\;b.w./day$ (PTWI 0.23-0.63%) by the husked rice, and $1.39{\times}10^{-1}$ (${\geq}20$ years old) $-3.21{\times}10^{-1}$ (${\leq}2$ years old) ${\mu}g/kg\;b.w./day$ (PTWI 6.47-15.00%) by the polished rice. CONCLUSION: The levels of overall exposure to total and inorganic arsenic by the husked and polished rice were far lower than the recommended levels of The Joint FAO/WHO Expert Committee on Food Additives (JECFA), indicating of little possibility of risk.

• 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.

• Korean Journal of Heritage: History & Science
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• v.43 no.1
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• pp.160-189
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• 2010

This study has been designed to grasp the present situation, shapes and meaning of the standing stones and rock pillars in the whole area of Noseong Mountain Fortress in Nonsan City which have never been academically reported yet. Accordingly, the research was carried out to grasp the spatial identity of Noseong Mt. and Noseong Mountain Fortress and the dispersion of standing stones scattered around inside and outside Noseong Mountain Fortress, while the shapes and structural characteristics of stones were investigated and analyzed focusing on Chongsuk Temple, which was considered to have the highest density of standing stones and greatest values for preservation as a cultural property. In consideration of the reference to the 'Top Sa' (tower temple) at the 'Bul Woo Jo' (Article about Buddhism Houses) of 'Shinjoong Dongguk Yeoji Seungram', theoretical existence of the temple according to surveying investigation, and the excavation records of roof tile pieces with the name of 'Gwan Eum Temple', it is presumed that there had been a Buddhist sanctum inside the fortress and it could be connected to the carved letters, 'Chongsuk Temple'. According the observation survey, the 6th place of standing stones among many other places inside the fortress shows that Chongsuk Temple appears to have the strong characteristics of artificially constructed space in consideration of the size of trees and stones, the composite trend of tree and stone composition, and trace of the adjacent well and strand and the construction of stairway leading to the stone gate. Along with the constellation of the Big Dipper carved on a rock at the same space, the stones, on which the letters of 'Shinseonam', 'Chilseongam' and 'Daejangam' were carved, including 'Chongsuksa', and the carved statue of Buddha, which was assumed to be Avalokitesvara Guan Yin, have offered clue which make it possible to infer that the space was a space for Chilseong and Mountain god(Folk Belief) that had originated from the combination of Buddhism, Taoism and folk religion. According to the actual measurement of standing stones at Chonsuk Temple, it was identified that there were big differences in height among 24 stones in total, ranging from 402~29cm and the averaged distance between each stone appeared to be 23.6cm. And the shape of stones appeared to be standing or flat, and various stones such as mountain-like stones and Buddha-like stones were placed in a special arrangement or assorted arrangement, but the direction of the stones had a consistency pointing to the west. And comparing to the trace of construction of ZEN Landscape Garden well known in the country, the three flat stones except for the standing and shaped stones appeared to have the shape of meditation statue, which is the typical formational factors of a ZEN Landscape Garden, on the basis of formational technique of stones. Among them, the flat stone facing the Buddhist saint statue, was formed by way of symbolization of three-mountain stone, which was assumed to be an offering stone for sacrificial food rather than carrying out ZEN Meditation. In consideration of the formation of standing stones at Chong-suk Temple, which was carried out in the composite stoning method based using the scalene triangle with ratio of 3:5:7 in order to seek the in-depth beauty based on the stone statues of three Buddhas where the three factors such as heaven, earth and humans are embodied in the elevated or flat formation, the stones at Chongsuk Temple and the space seemed to the trace of contracted garden construction that was formed with stones for a temple, so that could be used for ZEN meditation.