• Journal of The Korean Association For Science Education
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• v.34 no.8
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• pp.755-765
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• 2014

The convergence and consilience in education (hereafter, interdisciplinary education) is receiving great attention from societies. This study aims to investigate the works of scientists and artists who have intended to combine science with the arts in the modern era, to take into account the socio-philosophical setbacks during the period, and to suggest pedagogical implications of science education as interdisciplinary education. The concept of interdisciplinary education stems from Plato's thought, idea, as a comprehensive and invariant truth. The renaissance, full of enrichment about scientific achievement, was based on Neo-Platonism pursuing holistic-synthetic approach. During the time, scientists presented in this study tried to find comprehensive principles and borrow useful method from the arts. In such a context, scientists not only made use of the arts for expression of scientific knowledge, but also drew conclusion by analogical reasoning between science and the arts. Artists, as well, relied upon anatomy and optics especially, to elaborate linear perspective and even developed their own scientific knowledge through personal experience. Hence, contemporary science education should encourage students to hold a holistic viewpoint about science and the arts, articulate explicit goals and outcomes as interdisciplinary education, implement meta-disciplinary instruction about science and the arts, and develop assessment framework for collaborative learning. There may be good examples for inter-disciplinary education as listed: illustrating scientific ideas through the arts and vice versa, organizing collaborative works and evaluations criteria for them, and stressing problem solving on a daily basis.

• Korean Journal of Environmental Agriculture
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• v.26 no.1
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• pp.69-76
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• 2007

The accumulation curves of phenol in the flesh of apples were measured at $5^{\circ}C$, $25^{\circ}C$ and $40^{\circ}C$ when they were exposed to phenol vapor, The effective diffusivities of phenol at the rind and flesh were determined by comparing its experimentally obtained accumulation curves with simulated ones. The simulation was carried out by the non-steady state diffusion rate equation. The diffusion model assumed the consecutive diffusion of phenol at the rind and flesh of apples. The detection time of phenol in the flesh of apples was shortened with increasing temperature, and it accumulated amount also increased rapidly. The estimated effective diffusivity of phenol at the rind of apples increased with temperature as like $1.1{\times}10^{-13}\;m^2/s$ at $5^{\circ}C$, $1.4{\times}10^{-13}\;m^2/s$ at $25^{\circ}C$ and $2.2{\times}10^{-13}\;m^2/s$ at $40^{\circ}C$, but those at the flesh of apples were invariant as $1.5{\times}10^{-10}\;m^2/s$ at this temperature range. The effect of temperature on the diffusivity of phenol was small, but the increase of the vapor pressure of phenol with temperature accelerated the penetration of phenol at the rind, resulting in the rapid accumulation at the flesh of apple.

• The Korean Journal of Zoology
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• v.28 no.3
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• pp.125-136
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• 1985

The present study has been undertaken to elucidate whether there are developmentally regulated proteins in chick myogenesis by observing cellular and plasma membrane glycoproteins by use of labelled-Con A staining. At least three classes and five classes of glycoproteins can be identified in terms of their occurrence and their change in levels, respectively. As to the former, there are glycoproteins which are specific to cellular fraction are eight, those which are specific to plasma membrane are four, and those which occur in both fraction are nine. Likewise, as to the latter, there are glycoproteins which are invariant, those which increase in level, those which decrease, those which increase and subsequently decrease, and those which decrease and subsequently increase. The present experiment reveals that the level of fibronectin does decrease after the fusion and that the apparent conflicting results so far reported may be due to the difference in time point setting during fusion and myotube stages. It is thought to be a general tendency that glycoproteins of high-molecular-weight decrease and those of low-molecular-weight increase in relative levels as the fusion proceeds. These results are suggestive of the fact that a major structural reorganization of glycoproteins does occur in association with myoblast fusion.

• The Transactions of the Korea Information Processing Society
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• v.4 no.10
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• pp.2461-2469
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• 1997

Target detection and recognition problems, in which neural networks are widely used, require translation invariant and real-time processing in addition to the requirements that general pattern recognition problems need. This paper presents a novel architecture that meets the requirements and explains effective methodology to train the network. The proposed neural network is an architectural extension of the shared-weight neural network that is composed of the feature extraction stage followed by the pattern recognition stage. Its feature extraction stage performs correlational operation on the input with a weight kernel, and the entire neural network can be considered a nonlinear correlation filter. Therefore, the output of the proposed neural network is correlational plane with peak values at the location of the target. The architecture of this neural network is suitable for implementing with parallel or distributed computers, and this fact allows the application to the problems which require realtime processing. Net training methodology to overcome the problem caused by unbalance of the number of targets and non-targets is also introduced. To verify the performance, the proposed network is applied to detection and recognition problem of a specific automobile driving around in a parking lot. The results show no false alarms and fast processing enough to track a target that moves as fast as about 190 km per hour.

• The Journal of the Acoustical Society of Korea
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• v.42 no.1
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• pp.25-31
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• 2023

In order to estimate the radial speed of an underwater object so-called target with active sonar, Continuous Wave (CW) pulse is generally used, but if a target is slow and at near distance, it is not easy to estimate the radial velocity of the target due to acoustic reverberation in the ocean. In 2017, Wang et al. utilized broadband signal of two Hyperbolic Frequency Modulation (HFM) pulses, which is known as a doppler-invariant pulse, with equal frequency band and in opposite sweep directions to overcome this problem and successfully estimate the radial speed of slow-moving nearby target. They demonstrated the estimation of the radial velocity with computer simulation using the parameters of two HFM starting time differences and receiving times. However, for it uses two HFM pulses with equal frequency, cross-correlation between the two pulses negatively affect the detection performance. To mitigate this cross-correlation effect, we suggest using two different band HFM with the opposite sweep directions. In this paper, a method of radial velocity estimation is derived and simulated using two HFM pulses with the pulse length of 1 second and bandwidth of 400 Hz. Applying the suggested method, the radial velocity was estimated with approximately 6 % of relative error in the simulation.

• 한국노년학
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• v.38 no.4
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• pp.1035-1055
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• 2018

The purpose of this study is to investigate the relationship between public care and family care. Public care for older adults began in 2008 with the implementation of the Long-Term Care insurance in South Korea. Although the expansion of public care has the purpose of reducing the care burden for the family, it is not easy to say whether the developments of public care system reduce the amount of family care for older family members. Theoretically, public care and family care are expected to have various relationships depending on the degree of the role and function(substitution, hierarchical compensatory, task specific, supplementation, complementarity). And literatures have showed inconsistent results depending on the country, data, and methods. In this study, we analyzed the relationship between two care types focusing on home care services for older persons. Analyses were based on data from the second(2008) to sixth(2016) waves of Korean Longitudinal Study of Ageing(KLoSA). To investigate elderly care dynamics in the households, we pooled the data for four changes between two periods(2008-2010, 2010-2012, 2012-2014, and 2014-2016). This study used an analytic sample of 262 older adults, who are aged 55 over and experienced public care at least one point of time. We used Fixed-Effects(FE) model to analyze the differences within the same individuals under the condition that time-invariant unobserved factors are controlled. This study distinguished the cases of entry into public care and other cases of exiting public care. The results showed that older people who are dependent on public care are less dependent on family care than before. In both entry and exit groups, negative relations were maintained, but in the entering stage of public care, the degree of negative relations was relatively small, whereas in the stage of maintaining or departing from public care, relatively negative relations were strong. At the beginning periods, even though public care increased, family care did not decrease significantly. On the other hand, at the time of ending public care and relying on family care, family care increased significantly. The results of this study show that the relationship between public care and family care is close to hierarchical compensatory model and varies according to the stage of caring transition. Also, it was found that the cases of transition from public care to family care have the biggest burden of elderly care than other groups.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.3
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• pp.157-165
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• 2006

The change of external/internal factors of the cell rquires specific biological functions to maintain life. Such functions encourage particular genes to jnteract/regulate each other in multiple ways. Accordingly, we applied a linear decomposition model IFSA, which derives hidden variables, called the 'expression mode' that corresponds to the functions. To interpret gene interaction/regulation, we used a cross-correlation method given an expression mode. Linear decomposition models such as principal component analysis (PCA) and independent component analysis (ICA) were shown to be useful in analyzing high dimensional DNA microarray data, compared to clustering methods. These methods assume that gene expression is controlled by a linear combination of uncorrelated/indepdendent latent variables. However these methods have some difficulty in grouping similar patterns which are slightly time-delayed or asymmetric since only exactly matched Patterns are considered. In order to overcome this, we employ the (IFSA) method of [1] to locate phase- and shut-invariant features. Membership scoring functions play an important role to classify genes since linear decomposition models basically aim at data reduction not but at grouping data. We address a new function essential to the IFSA method. In this paper we stress that IFSA is useful in grouping functionally-related genes in the presence of time-shift and expression phase variance. Ultimately, we propose a new approach to investigate the multiple interaction information of genes.

• KDI Journal of Economic Policy
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• v.30 no.1
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• pp.71-130
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• 2008

Using data from the Korean Labor & Income Panel Study (KLIPS), this study investigates private income transfers in Korea, where adult children have undertaken the most responsibility of supporting their elderly parents without well-established social safety net for the elderly. According to the KLIPS data, three out of five households provided some type of support for their aged parents and two out of five households of the elderly received financial support from their adult children on a regular base. However, the private income transfers in Korea are not enough to alleviate the impact of the fall in the earned income of those who retired and are approaching an age of needing financial assistance from external source. The monthly income of those at least the age of 75, even with the earning of their spouses, is below the staggering amount of 450,000 won, which indicates that the elderly in Korea are at high risk of poverty. In order to analyze microeconomic factors affecting the private income transfers to the elderly parents, the following three samples extracted from the KLIPS data are used: a sample of respondents of age 50 or older with detailed information on their financial status; a five-year household panel sample in which their unobserved family-specific and time-invariant characteristics can be controlled by the fixed-effects model; and a sample of the younger split-off household in which characteristics of both the elderly household and their adult children household can be controlled simultaneously. The results of estimating private income transfer models using these samples can be summarized as follows. First, the dominant motive lies on the children-to-parent altruistic relationship. Additionally, another is based on exchange motive, which is paid to the elderly parents who take care of their grandchildren. Second, the amount of private income transfers has negative correlation with the income of the elderly parents, while being positively correlated with the income of the adult children. However, its income elasticity is not that high. Third, the amount of private income transfers shows a pattern of reaching the highest level when the elderly parents are in the age of 75 years old, following a decreasing pattern thereafter. Fourth, public assistance, such as the National Basic Livelihood Security benefit, appears to crowd out private transfers. Private transfers have fared better than public transfers in alleviating elderly poverty, but the role of public transfers has been increasing rapidly since the welfare expansion after the financial crisis in the late 1990s, so that one of four elderly people depends on public transfers as their main income source in 2003. As of the same year, however, there existed and occupied 12% of the elderly households those who seemed eligible for the National Basic Livelihood benefit but did not receive any public assistance. To remove elderly poverty, government may need to improve welfare delivery system as well as to increase welfare budget for the poor. In the face of persistent elderly poverty and increasing demand for public support for the elderly, which will lead to increasing government debt, welfare policy needs targeting toward the neediest rather than expanding universal benefits that have less effect of income redistribution and heavier cost. Identifying every disadvantaged elderly in dire need for economic support and providing them with the basic livelihood security would be the most important and imminent responsibility that we all should assume to prepare for the growing aged population, and this also should accompany measures to utilize the elderly workforce with enough capability and strong will to work.

• Asia pacific journal of information systems
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• v.20 no.3
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• pp.115-137
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• 2010

Information technology (IT) outsourcing, the use of a third-party vendor to provide IT services, started in the late 1980s and early 1990s in Korea, and has increased rapidly since 2000. Recently, firms have increased their efforts to capture greater value from IT outsourcing. To date, there have been a large number of studies on IT outsourcing. Most prior studies on IT outsourcing have focused on outsourcing practices and decisions, and little attention has been paid to objectively measuring the value of IT outsourcing. In addition, studies that examined the performance of IT outsourcing have mainly relied on anecdotal evidence or practitioners' perceptions. Our study examines the contribution of IT outsourcing to economic growth in Korean industries over the 1990 to 2007 period, using a production function framework and a panel data set for 54 industries constructed from input-output tables, fixed-capital formation tables, and employment tables. Based on the framework and estimation procedures that Han, Kauffman and Nault (2010) used to examine the economic impact of IT outsourcing in U.S. industries, we evaluate the impact of IT outsourcing on output and productivity in Korean industries. Because IT outsourcing started to grow at a significantly more rapid pace in 2000, we compare the impact of IT outsourcing in pre- and post-2000 periods. Our industry-level panel data cover a large proportion of Korean economy-54 out of 58 Korean industries. This allows us greater opportunity to assess the impacts of IT outsourcing on objective performance measures, such as output and productivity. Using IT outsourcing and IT capital as our primary independent variables, we employ an extended Cobb-Douglas production function in which both variables are treated as factor inputs. We also derive and estimate a labor productivity equation to assess the impact of our IT variables on labor productivity. We use data from seven years (1990, 1993, 2000, 2003, 2005, 2006, and 2007) for which both input-output tables and fixed-capital formation tables are available. Combining the input-output tables and fixed-capital formation tables resulted in 54 industries. IT outsourcing is measured as the value of computer-related services purchased by each industry in a given year. All the variables have been converted to 2000 Korean Won using GDP deflators. To calculate labor hours, we use the average work hours for each sector provided by the OECD. To effectively control for heteroskedasticity and autocorrelation present in our dataset, we use the feasible generalized least squares (FGLS) procedures. Because the AR1 process may be industry-specific (i.e., panel-specific), we consider both common AR1 and panel-specific AR1 (PSAR1) processes in our estimations. We also include year dummies to control for year-specific effects common across industries, and sector dummies (as defined in the GDP deflator) to control for time-invariant sector-specific effects. Based on the full sample of 378 observations, we find that a 1% increase in IT outsourcing is associated with a 0.012~0.014% increase in gross output and a 1% increase in IT capital is associated with a 0.024~0.027% increase in gross output. To compare the contribution of IT outsourcing relative to that of IT capital, we examined gross marginal product (GMP). The average GMP of IT outsourcing was 6.423, which is substantially greater than that of IT capital at 2.093. This indicates that on average if an industry invests KRW 1 millon, it can increase its output by KRW 6.4 million. In terms of the contribution to labor productivity, we find that a 1% increase in IT outsourcing is associated with a 0.009~0.01% increase in labor productivity while a 1% increase in IT capital is associated with a 0.024~0.025% increase in labor productivity. Overall, our results indicate that IT outsourcing has made positive and economically meaningful contributions to output and productivity in Korean industries over the 1990 to 2007 period. The average GMP of IT outsourcing we report about Korean industries is 1.44 times greater than that in U.S. industries reported in Han et al. (2010). Further, we find that the contribution of IT outsourcing has been significantly greater in the 2000~2007 period during which the growth of IT outsourcing accelerated. Our study provides implication for policymakers and managers. First, our results suggest that Korean industries can capture further benefits by increasing investments in IT outsourcing. Second, our analyses and results provide a basis for managers to assess the impact of investments in IT outsourcing and IT capital in an objective and quantitative manner. Building on our study, future research should examine the impact of IT outsourcing at a more detailed industry level and the firm level.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.107-122
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• 2017

Volatility in the stock market returns is a measure of investment risk. It plays a central role in portfolio optimization, asset pricing and risk management as well as most theoretical financial models. Engle(1982) presented a pioneering paper on the stock market volatility that explains the time-variant characteristics embedded in the stock market return volatility. His model, Autoregressive Conditional Heteroscedasticity (ARCH), was generalized by Bollerslev(1986) as GARCH models. Empirical studies have shown that GARCH models describes well the fat-tailed return distributions and volatility clustering phenomenon appearing in stock prices. The parameters of the GARCH models are generally estimated by the maximum likelihood estimation (MLE) based on the standard normal density. But, since 1987 Black Monday, the stock market prices have become very complex and shown a lot of noisy terms. Recent studies start to apply artificial intelligent approach in estimating the GARCH parameters as a substitute for the MLE. The paper presents SVR-based GARCH process and compares with MLE-based GARCH process to estimate the parameters of GARCH models which are known to well forecast stock market volatility. Kernel functions used in SVR estimation process are linear, polynomial and radial. We analyzed the suggested models with KOSPI 200 Index. This index is constituted by 200 blue chip stocks listed in the Korea Exchange. We sampled KOSPI 200 daily closing values from 2010 to 2015. Sample observations are 1487 days. We used 1187 days to train the suggested GARCH models and the remaining 300 days were used as testing data. First, symmetric and asymmetric GARCH models are estimated by MLE. We forecasted KOSPI 200 Index return volatility and the statistical metric MSE shows better results for the asymmetric GARCH models such as E-GARCH or GJR-GARCH. This is consistent with the documented non-normal return distribution characteristics with fat-tail and leptokurtosis. Compared with MLE estimation process, SVR-based GARCH models outperform the MLE methodology in KOSPI 200 Index return volatility forecasting. Polynomial kernel function shows exceptionally lower forecasting accuracy. We suggested Intelligent Volatility Trading System (IVTS) that utilizes the forecasted volatility results. IVTS entry rules are as follows. If forecasted tomorrow volatility will increase then buy volatility today. If forecasted tomorrow volatility will decrease then sell volatility today. If forecasted volatility direction does not change we hold the existing buy or sell positions. IVTS is assumed to buy and sell historical volatility values. This is somewhat unreal because we cannot trade historical volatility values themselves. But our simulation results are meaningful since the Korea Exchange introduced volatility futures contract that traders can trade since November 2014. The trading systems with SVR-based GARCH models show higher returns than MLE-based GARCH in the testing period. And trading profitable percentages of MLE-based GARCH IVTS models range from 47.5% to 50.0%, trading profitable percentages of SVR-based GARCH IVTS models range from 51.8% to 59.7%. MLE-based symmetric S-GARCH shows +150.2% return and SVR-based symmetric S-GARCH shows +526.4% return. MLE-based asymmetric E-GARCH shows -72% return and SVR-based asymmetric E-GARCH shows +245.6% return. MLE-based asymmetric GJR-GARCH shows -98.7% return and SVR-based asymmetric GJR-GARCH shows +126.3% return. Linear kernel function shows higher trading returns than radial kernel function. Best performance of SVR-based IVTS is +526.4% and that of MLE-based IVTS is +150.2%. SVR-based GARCH IVTS shows higher trading frequency. This study has some limitations. Our models are solely based on SVR. Other artificial intelligence models are needed to search for better performance. We do not consider costs incurred in the trading process including brokerage commissions and slippage costs. IVTS trading performance is unreal since we use historical volatility values as trading objects. The exact forecasting of stock market volatility is essential in the real trading as well as asset pricing models. Further studies on other machine learning-based GARCH models can give better information for the stock market investors.