• Journal of Radiation Protection and Research
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• v.17 no.1
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• pp.57-70
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• 1992

An excess risk of lung cancer mortality among Koreans, attributable to indoor $^{222}Rn$ daughters exposure, were quantitatively evaluated by applying a stochastic health risk projection model on the radiation exposure. The lung cancer rate in Korean males and females, based on the 1989 demographic data, were estimated to be $22.4/10^5-y\;and\;9.5/10^5-y$, respectively The lifetime baseline lung cancer risks, deduced from these rates, appeared to be 0.047 and 0.019 for males and females, respectively, and were lower than the corresponding 1984 values of 0.067 and 0.025 in the U.S.A. The excess risk coefficients, derived by modified relative risk projection model of the BEIR-IV Committee under the US National Academy of Science, per annual 1.0 WLM of exposure to indoor radon daughters were estimated to be 0.022/WLM for males, 0.009/WLM for females, and 0.017/WLM for both sexes. The resulting annual frequency of excess lung cancer mortality for the life expectancy in the Korean population appeared to be 230/10^6-WLM, which was an approximate median of $120{\sim}450/10^6-WLM$ reported so far in the world.

• Korean Journal of Clinical Laboratory Science
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• v.50 no.4
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• pp.511-524
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• 2018

The purpose of this study is to provide policy recommendations for manpower planning by forecasting the supply and demand of Medical Technologists. Supply was estimated using an in-and-out movement method with a demographic method based on a baseline projection model. Demand was projected according to a demand-based method using the number of clinico-pathologic examinations taken for Medical Technologists. Over- or undersupply of Medical Technologists will depend on the productivity scenario and assumptions and ultimately on governmental policy direction. In other words, whether the production of Medical Technologists is higher or lower than the current level depends on the government policy to consider insurance finances. In this study, we assessed 'productivity scenario 3' based on the productivity as of 2012, when the government's policy direction was not considered. Based on the demand scenario using the ARIMA model, the supply of Medical Technologists is expected to be excessive. This oversupply accounts for less than 10% of the total and therefore should not be a big problem. However, given that the employment rate of Medical Technologists is 60%, it is necessary to consider policies to utilize the unemployed. These measures should expand the employment opportunities for the unemployed. To this end, it is necessary to strengthen the functions of laboratories in the public health center, to increase the quota of Medical Technologists, to assure their status, to establish a permanent inspection system for outpatient patients, and to expand the export of Medical Technologists overseas.

• 한국노년학
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• v.40 no.1
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• pp.147-161
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• 2020

The purpose of this research is to investigates 10-year trajectories of cognitive functions among older adults in their 70s to understand changes in cognitive functions as a continuum until very late life. This study also examines differences in trajectories of cognitive functions by gender and by changes in marital status, especially widowhood. Among participants of the Korean Longitudinal Study of Ageing(KLoSA), the sample of this study includes 800 older adults in their 70s during the first study wave (2006) and those who reported their cognitive functions for six consecutive study waves (2006, 2008, 2010, 2012, 2014, and 2016). The analyses were conducted in two steps. First, we conducted Latent Class Growth Analyses(LCGA) to investigated heterogeneous trajectories of cognitive functions in 10 years. Then, we performed multinomial logistic regression. Three heterogeneous trajectories of cognitive functions were identified. One group of 48.7% of older adults showed high cognitive function at baseline and maintained it over 10 years. Second group of 14.7% of older adults reported low cognitive function scores at baseline and showed continuous decline over time. Third group of 36.6% were showed mid-level cognitive functions and maintained their functions over time. We also found significant gender differences but not significant differences in marital status when we consider both in our model; however, the we found significant differences in changes in marital status when we did not consider gender in the model. The results suggest that the importance of considering dynamics of gender and changes in marital status to understand changes in cognitive functions in later life.

• Korean Journal of Radiology
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• v.23 no.6
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• pp.664-673
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• 2022

Objective: To evaluate the performance of baseline clinical characteristics and pretherapeutic histogram parameters derived from T2 mapping of the extraocular muscles (EOMs) in the prediction of treatment response to intravenous glucocorticoid (IVGC) therapy for active and moderate-to-severe thyroid-associated ophthalmopathy (TAO) and to investigate the effect of fat-suppression (FS) in T2 mapping in this prediction. Materials and Methods: A total of 79 patients clinically diagnosed with active, moderate-to-severe TAO (47 female, 32 male; mean age ± standard deviation, 46.1 ± 10 years), including 43 patients with a total of 86 orbits in the responsive group and 36 patients with a total of 72 orbits in the unresponsive group, were enrolled. Baseline clinical characteristics and pretherapeutic histogram parameters derived from T2 mapping with FS (i.e., FS T2 mapping) or without FS (i.e., conventional T2 mapping) of EOMs were compared between the two groups. Independent predictors of treatment response to IVGC were identified using multivariable analysis. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the predictive performance of the prediction models. Differences between the models were examined using the DeLong test. Results: Compared to the unresponsive group, the responsive group had a shorter disease duration, lower kurtosis (FS-kurtosis), lower standard deviation, larger 75th, 90th, and 95th (FS-95th) T2 relaxation times in FS mapping and lower kurtosis in conventional T2 mapping. Multivariable analysis revealed that disease duration, FS-95th percentile, and FS-kurtosis were independent predictors of treatment response. The combined model, integrating all identified predictors, had an optimized area under the ROC curve of 0.797, 88.4% sensitivity, and 62.5% specificity, which were significantly superior to those of the imaging model (p = 0.013). Conclusion: An integrated combination of disease duration, FS-95th percentile, and FS-kurtosis was a potential predictor of treatment response to IVGC in patients with active and moderate-to-severe TAO. FS T2 mapping was superior to conventional T2 mapping in terms of prediction.

• Geophysics and Geophysical Exploration
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• v.1 no.1
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• pp.25-30
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• 1998

Time-lapse crosswell seismic data, recorded before and after the cavity filling, showed that the filling increased the velocity at a known cavity zone in an old mine site in Inchon area. The seismic response depicted on the tomogram and in conjunction with the geologic data from drillings imply that the size of the cavity may be either small or filled by debris. In this study, I attempted to evaluate the filling effect by analyzing velocity measured from the time-lapse tomograms. The data acquired by a downhole airgun and 24-channel hydrophone system revealed that there exists measurable amounts of source statics. I presented a methodology to estimate the source statics. The procedure for this method is: 1) examine the source firing-time for each source, and remove the effect of irregular firing time, and 2) estimate the residual statics caused by inaccurate source positioning. This proposed multi-step inversion may reduce high frequency numerical noise and enhance the resolution at the zone of interest. The multi-step inversion with different starting models successfully shows the subtle velocity changes at the small cavity zone. The inversion procedure is: 1) conduct an inversion using regular sized cells, and generate an image of gross velocity structure by applying a 2-D median filter on the resulting tomogram, and 2) construct the starting velocity model by modifying the final velocity model from the first phase. The model was modified so that the zone of interest consists of small-sized grids. The final velocity model developed from the baseline survey was as a starting velocity model on the monitor inversion. Since we expected a velocity change only in the cavity zone, in the monitor inversion, we can significantly reduce the number of model parameters by fixing the model out-side the cavity zone equal to the baseline model.

• KDI Journal of Economic Policy
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• v.14 no.4
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• pp.3-26
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• 1992

The pupose of this paper is to construct a price determination model of the Korean economy and to find out the propogation mechanism of monetary and fiscal policies. The model is a small-size macroeconometric model consisted of ten core equations : consumption, investment, exports, imports, consumer price index, wage rate, corporate bond rate, potential GNP, capital stock, and GNP identity. The model is a Keynesian model : consumer price index is determined by markup over costs, and wage rate is expressed by Phillipse curve ralation. Two features of the model, however, distinguish this model from other macroeconometric models of the Korean economy. First of all, the estimation of potential GNP and the capital stock is endogenized as suggested by Haque, Lahiri, and Montiel (1990). This allows us to calculate the level of excess demand, which is defined as the difference between the actual GNP and the potential GNP. Second, interest rate, inflation and wages are all estimated as endogenous variables. Moreover, all quantity variables include price variables as important determinants. For instance, interest rate is an important determinant of consumption and investment. Exports and imports are determined by the real effective exchange rate. These two features make the interactions between excess demand and prices the driving forces of this model. In the model, any shock which affects quantity variable(s) affects excess demand, which in turn affects prices. This strong interaction between prices and quantities makes the model look like a classical model over the long run. That is, increases in money supply, government expenditures, and exchange rate (the price of the U.S. dollar in terms of Korean won) all have expansionery effects on the real GNP in the short run, but prices, wage, and interest rate all increase as a result. Over the long run, higher prices have dampenning effects on output. Therefore the level of real GNP turns out to be not much different from the baseline level ; on the other hand, the rates of inflation, wage and interest rate remain at higher levels.

• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.73-95
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• 2021

This study uses Node2vec graph embedding method and Light GBM link prediction to explore undeveloped export candidate countries in Korea's food and beverage industry. Node2vec is the method that improves the limit of the structural equivalence representation of the network, which is known to be relatively weak compared to the existing link prediction method based on the number of common neighbors of the network. Therefore, the method is known to show excellent performance in both community detection and structural equivalence of the network. The vector value obtained by embedding the network in this way operates under the condition of a constant length from an arbitrarily designated starting point node. Therefore, it has the advantage that it is easy to apply the sequence of nodes as an input value to the model for downstream tasks such as Logistic Regression, Support Vector Machine, and Random Forest. Based on these features of the Node2vec graph embedding method, this study applied the above method to the international trade information of the Korean food and beverage industry. Through this, we intend to contribute to creating the effect of extensive margin diversification in Korea in the global value chain relationship of the industry. The optimal predictive model derived from the results of this study recorded a precision of 0.95 and a recall of 0.79, and an F1 score of 0.86, showing excellent performance. This performance was shown to be superior to that of the binary classifier based on Logistic Regression set as the baseline model. In the baseline model, a precision of 0.95 and a recall of 0.73 were recorded, and an F1 score of 0.83 was recorded. In addition, the light GBM-based optimal prediction model derived from this study showed superior performance than the link prediction model of previous studies, which is set as a benchmarking model in this study. The predictive model of the previous study recorded only a recall rate of 0.75, but the proposed model of this study showed better performance which recall rate is 0.79. The difference in the performance of the prediction results between benchmarking model and this study model is due to the model learning strategy. In this study, groups were classified by the trade value scale, and prediction models were trained differently for these groups. Specific methods are (1) a method of randomly masking and learning a model for all trades without setting specific conditions for trade value, (2) arbitrarily masking a part of the trades with an average trade value or higher and using the model method, and (3) a method of arbitrarily masking some of the trades with the top 25% or higher trade value and learning the model. As a result of the experiment, it was confirmed that the performance of the model trained by randomly masking some of the trades with the above-average trade value in this method was the best and appeared stably. It was found that most of the results of potential export candidates for Korea derived through the above model appeared appropriate through additional investigation. Combining the above, this study could suggest the practical utility of the link prediction method applying Node2vec and Light GBM. In addition, useful implications could be derived for weight update strategies that can perform better link prediction while training the model. On the other hand, this study also has policy utility because it is applied to trade transactions that have not been performed much in the research related to link prediction based on graph embedding. The results of this study support a rapid response to changes in the global value chain such as the recent US-China trade conflict or Japan's export regulations, and I think that it has sufficient usefulness as a tool for policy decision-making.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.27-40
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• 2023

With the increase in the spread of smart devices and the impact of COVID-19, the consumption of media contents through smart devices has significantly increased. Along with this trend, the amount of media contents viewed through OTT platforms is increasing, that makes contents recommendations on these platforms more important. Previous contents-based recommendation researches have mostly utilized metadata that describes the characteristics of the contents, with a shortage of researches that utilize the contents' own descriptive metadata. In this paper, various text data including titles and synopses that describe the contents were used to recommend similar contents. KLUE-RoBERTa-large, a Korean language model with excellent performance, was used to train the model on the text data. A dataset of over 20,000 contents metadata including titles, synopses, composite genres, directors, actors, and hash tags information was used as training data. To enter the various text features into the language model, the features were concatenated using special tokens that indicate each feature. The test set was designed to promote the relative and objective nature of the model's similarity classification ability by using the three contents comparison method and applying multiple inspections to label the test set. Genres classification and hash tag classification prediction tasks were used to fine-tune the embeddings for the contents meta text data. As a result, the hash tag classification model showed an accuracy of over 90% based on the similarity test set, which was more than 9% better than the baseline language model. Through hash tag classification training, it was found that the language model's ability to classify similar contents was improved, which demonstrated the value of using a language model for the contents-based filtering.

• The Korean Journal of Applied Statistics
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• v.27 no.2
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• pp.317-330
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• 2014

Bipolar disorder is a psychopathy characterized by manic and major depressive episodes. It is important to determine the degree of depression when treating patients with bipolar disorder because 810% of bipolar patients commit suicide during the periods in which they experience major depressive episodes. The Hamilton depression rating scale is most commonly used to estimate the degree of depression in a patient. This paper proposes using the Hamilton depression rating scale to estimate the effectiveness of patient treatment based on the linear mixed effects model and the transition model. Study subjects were recruited from the Seoul National University Bundang Hospital who scored 8 points or above in the Hamilton depression rating scale on their first medical examination. The linear mixed effects model and the transition model were fitted using the Hamilton depression rating scales measured at the baseline, six month, and twelve month follow-ups. Then, Hamilton depression rating scale at the twenty-four month follow-up was predicted using these models. The prediction models were then evaluated by comparing the observed and predicted Hamilton depression rating scales on the twenty-four month follow-up.

• Journal of Broadcast Engineering
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• v.19 no.5
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• pp.677-686
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• 2014

This paper analyzes the 3D accuracy of stereo images captured from a mobile phone. For 3D accuracy evaluation, we have compared the accuracy result according to the amount of the convergence angle. In order to calculate the 3D model space coordinate of control points, we perform inner orientation, distortion correction and image geometry estimation. And the quantitative 3D accuracy was evaluated by transforming the 3D model space coordinate into the 3D object space coordinate. The result showed that relatively precise 3D information is generated in more than $17^{\circ}$ convergence angle. Consequently, it is necessary to set up stereo model structure consisting adequate convergence angle as an measurement distance and a baseline distance for accurate 3D information generation. It is expected that the result would be used to stereoscopic 3D contents and 3D reconstruction from images captured by a mobile phone camera.