• Health Policy and Management
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• v.18 no.1
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• pp.1-20
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• 2008

How health care providers compete and how competition among them affects their behavior are crucial questions in theory and health policy. In ordinary markets, competition improves social welfare, However in health care markets facing uncertainty and information asymmetry, competition can take the form of wasteful quality competition and result in cost increase. The purpose of this study is to examine the characteristics of hospital service markets and examine the impact of hospital competition on hospital behavior, more specifically hospital cost and the size of personnel. Based on patient discharge data of 2002 by the Ministry of Health and Welfare and Korea Institute for Health and Social Affairs, and health insurance EDI claims data of 2002, this study measures the degree of competition in the inpatient service market of hospitals, using variable radius method and Herfindahl index. The result of the study shows that the hospital service market consists of on average 3.13 government administrative units(shi, gun, or gu). Compared with hospitals, general or general specialized hospitals cover larger markets and operate in more competitive markets. Nearly 60% of patients use hospitals, which are not located in their government administrative units, meaning that market definition based on variable radius is better than the conventional method of market definition based on government administrative units. The results of multivariate analysis show that competition is not associated with high cost index of hospitals. But hospitals in more competitive markets employ larger(more intensive) input of personnel per 100 beds, implying that hospital competition in Korea can have the form of quality and cost-increasing competition.

• Korean Journal of Applied Biomechanics
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• v.23 no.1
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• pp.37-43
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• 2013

The purpose of this study was to analyze the 12-week horse riding exercise effect on the locomotion of a body and bilateral balance and flexion/extension of trunk during the sit-to-stand(STS) in elementary and middle school students. One-hundred eleven participants were divided into three groups. Each group was subject to a different horse riding exercise: control group(n = 36), 1 time/week group(n=37), and 3 times/week group(n=38). Two-way repeated ANOVA was used to compare weight transfer time(WTT), trunk flexion velocity(TFV), trunk extension velocity(TEV), mean rising index(MRI), mean weight asymmetry( MWA) among the groups, and STS changes in before and after 12 weeks. There was a group interaction in WTT, TFV, TEV, MRI, and MWA with different responses to horse riding exercise participation. There was a significant increase in 1 time/week group and 3 times/week group of WTT, TFV, TEV, and MRI. Additionally, MWA(an index of a capacity for bilateral balance) in lower extremity was decreased in 3 times/week group. It seems that horse riding exercise positively affected musculoskeletal function of the trunk and lower extremity by accelerating locomotion and bilateral balance.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.5
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• pp.3579-3586
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• 2015

In this study, EEG, HRV, and Vibra image were compared and analyzed in the environmental test room due to stimulation of aroma and color temperature. The condition of the environmental test room was in temperature $25[^{\circ}C]$, relative humidity 50[RH%], air current speed 0.02[m/s] and illuminance 1000[lux] with setting up different sensory stimulation condition which are before exposure, single-sensory stimulation of Jasmine scent, single-sensory stimulation of RED color lighting, and multi-sensory stimulation of Jasmine scent and RED color lighting. The result of this study, at multi-sensory stimulation of Jasmine scent and RED color lighting, relative $S{\alpha}$ wave, SEF50, $SMR/{\theta}$ and SDNN were revitalized, and both sides ${\alpha}$ wave asymmetry index, stress index, fatigue degree, and HRT were decreased. Also, Viba image of tension/anxiety and stress were declined. Therefore multi-sensory stimulation of Jasmine scent and RED color lighting effects to increase the Neuro-energy like amenity, productivity of work efficiency, and concentration.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.1
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• pp.418-425
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• 2013

In this study, the three scents effects on subjects due to EEG type, and it researched to find optimal scent to increase their amenity and productivity. EEG and HRV were compared and analyzed in the environmental test room by classifying subjects into two type: A and B. The condition of the environmental test room was in temperature 31[$^{\circ}C$], relative humidity 50[RH%], air current speed 0.02[m/s] and illuminance 1000[lux] with setting up three different scents which are Rosemary, Jasmine and Hazelnut. The result of this study, at Jasmine scent for A and B type, relative ${\alpha}$ wave, SEF50, $\frac{SMR}{\theta}$ and SDNN were revitalized, and ${\alpha}$ wave asymmetry index, HRT, stress index and fatigue degree were decreased. It was found that favorite scent of A and B type is same as Jasmine scent, but A type was more sensitive than B type about scent. Therefore Jasmine scent is very effective to increase amenity, productivity and concentration, and to decrease stress and fatigue degree.

• The Korean Journal of Applied Statistics
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• v.36 no.2
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• pp.129-139
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• 2023

Forecasting volatility is essential to avoiding the risk caused by the uncertainties of an financial asset. Complicated financial volatility features such as ambiguity between non-stationarity and stationarity, asymmetry, long-memory, sudden fairly large values like outliers bring great challenges to volatility forecasts. In order to address such complicated features implicity, we consider machine leaning models such as LSTM (1997) and GRU (2014), which are known to be suitable for existing time series forecasting. However, there are the problems of vanishing gradients, of enormous amount of computation, and of a huge memory. To solve these problems, a causal temporal convolutional network (TCN) model, an advanced form of 1D CNN, is also applied. It is confirmed that the overall forecasting power of TCN model is higher than that of the RNN models in forecasting VIX, VXD, and VXN, the daily volatility indices of S&P 500, DJIA, Nasdaq, respectively.

• Journal of Biomedical Engineering Research
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• v.29 no.4
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• pp.286-294
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• 2008

This work investigates the characteristics of brain interactions of experienced Zen-Buddhist practitioners by obtaining multichannel EEG (electroencephalogram) data. Brain interactions were compared among three phases-40-minute meditation (M), 5-minute Chakra-focusing practice (Z) and rest with closed eyes (R). The similarity index S, developed in nonlinear dynamical system theory, was employed to measure the degree of possibly asymmetric coupling. Meditators exhibited, overall, stronger interactions among multiple cortical areas in meditation stages M and Z than in the R state. This enhancement was greater in the M stage when the meditator was accompanied by a thought-free and fully consciousness state. In the high-frequency band (>13Hz), the interdependence was also higher in both meditation stages than at baseline rest. However, the interaction strength, especially in the posterior regions, was greatest in the Z stage, which involved internal attention. Few electrode pairs were observed with significant pair-wise asymmetry in the Z state. The similarity is a possible characteristic of dense reciprocal and strong mutual interactions between multiple cortical areas during meditation - especially in the Z state in the high-frequency band. These results demonstrate that profound Zen meditation induces various dynamic states in different phases of meditation, possibly reflected by nonlinear interdependence measure.

• The Journal of Asian Finance, Economics and Business
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• v.3 no.4
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• pp.17-24
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• 2016

The purpose of this paper is to understand the underlying dynamics for the share market bubbles in China during the most recent decade. By using the behavioral finance theory and the Shanghai Composite index prices during the periods from 2005 to 2008 and from 2014 to 2015 as the study samples, we find that the large volatilities in the Chinese share market are closely related to information blockage, which impedes share prices to timely respond to economic conditions as well as external shocks and increases (decreases) the demand of shares when the supply is difficult to adjust. Although the Chinese government has introduced a series of programs designed to increase more reliable information to the public, the share market still tends to confront issues of information asymmetry. The potential reason is that the reforms did not change the long-stand situation in China, where individuals or groups related to government bureaucracy who play a dominant role in the society are given priority to gain access and obtain information that benefits. By identifying the main reasons for the large volatilities in the market, policy makers are given advice as to which areas they may need to focus on to improve future market performance.

• The Journal of Information Systems
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• v.29 no.3
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• pp.119-144
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• 2020

Purpose Real estate usually takes charge of the highest proportion of physical properties which individual, organizations, and government hold and instability of real estate market affects the economic condition seriously for each economic subject. Consequently, practices for predicting the real estate market have attention for various reasons, such as financial investment, administrative convenience, and wealth management. Additionally, development of machine learning algorithms and computing hardware enhances the expectation for more precise and useful prediction models in real estate market. Design/methodology/approach In response to the demand, this paper aims to provide a framework for forecasting the real estate market with machine learning algorithms. The framework consists of demonstrating the prediction efficiency of each machine learning algorithm, interpreting the interior feature effects of prediction model with a state-of-art algorithm, LIME(Local Interpretable Model-agnostic Explanation), and comparing the results in different cities. Findings This research could not only enhance the academic base for information system and real estate fields, but also resolve information asymmetry on real estate market among economic subjects. This research revealed that macroeconomic indicators, real estate-related indicators, and Google Trends search indexes can predict real-estate prices quite well.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.38 no.9
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• pp.643-651
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• 2001

Fused vertical directional coupler switches (FVCSs) with switching operation induced section (SOIS) and extinction ratio enhanced section (ERES) are proposed. In these FVCSs, switching operation is achieved by changing the refractive indices of both cores in SOIS and improvement of extinction ratios larger than 30dB for both cross and bar states is achieved by controlling the asymmetry of refractive indices between both cores in ERES. In addition, the design guidelines to have high extinction ratios larger than 30dB with large tolerances of the refractive index of cores are presented.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.9
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• pp.39-49
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• 2020

This study empirically examines herd behavior for fast moving consumer goods (FMCG) sector stocks under varied market return conditions and the period during the global financial crisis and its aftermath. We examine the sample of stocks trading on the Nifty FMCG Index of the Indian equity market from January 2008 up to December 2018 using the dispersion measure of cross sectional absolute deviation and examine its relationship with the market return to explore herd phenomenon. Quantile regression estimate is used and the results of the study validate rational asset pricing models as the sector does not display herding. In contrast, anti-herd behavior at lower and median quantile values is observed. A possible reason can be the non-cyclical nature of the industry where investors rely more on the fundamentals rather than crowd chasing. We also findthe absence of herd phenomenon during the market asymmetries of bull and bear phases, extreme movements, the period of the global financial crisis, and afterward. We further examine herding under the impact of the information technology (IT) industry and conclude that significant return movements in IT sector impact dispersions in the FMCG industry. Also, there is a co-varying risk between the two sectors confirming the spillover in an integrated market.