• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.363-371
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• 2021

The goal of this study was to investigate the influence of exercise training with or without blood flow restriction (BFR) on physical performance and balance in elderly females. Participants (N = 43) were randomly divided into combined exercise with BFR group (n = 14, EX-BFR), only combine exercise group (n =14, EX) or a non-exercise control group (n = 15, CON). Both EX-BFR and EX groups had completed exercise training for 12 weeks. During the training period, the CON group maintained their normal lives. After baseline tests, two-way repeated measures ANOVA with contrast testing was conducted using SPSS 22.0. Study results found that physical performance and balance in both EX-BFR and EX groups were significantly improved, and fall index in both EX-BFR and EX groups were significantly decreased. There were no changes in the CON group. In addition, the % change and effect size of all variables in the EX-BFR group were larger than the EX group. So, the results showed that the EX-BFR group had performed more intense exercise caused by restricted blood flow during the training period compared to the EX group. Thus, exercise with BFR training may additionally influence physical performance and balance in elderly females.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.27 no.2
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• pp.49-70
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• 2022

Sea Surface Temperature (SST), one of the ocean features, has a significant impact on climate, marine ecosystem and human activities. Therefore, SST prediction has been always an important issue. Recently, deep learning has drawn much attentions, since it can predict SST by training past SST patterns. Compared to the numerical simulations, deep learning model is highly efficient, since it can estimate nonlinear relationships between input data. With the recent development of Graphics Processing Unit (GPU) in computer, large amounts of data can be calculated repeatedly and rapidly. In this study, Short-term SST will be predicted through Convolutional Neural Network (CNN)-based U-Net that can handle spatiotemporal data concurrently and overcome the drawbacks of previously existing deep learning-based models. The SST prediction performance depends on the seasonal and interannual SST variabilities around the southern coast of Korea. The predicted SST has a wide range of variance during spring and summer, while it has small range of variance during fall and winter. A wide range of variance also has a significant correlation with the change of the Pacific Decadal Oscillation (PDO) index. These results are found to be affected by the intensity of the seasonal and PDO-related interannual SST fronts and their intensity variations along the southern Korean seas. This study implies that the SST prediction performance using the developed deep learning model can be significantly varied by seasonal and interannual variabilities in SST.

• Journal of Korea Trade
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• v.24 no.4
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• pp.71-94
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• 2020

Purpose - Multi-National Enterprises (MNEs) tend to face a high level of institutional pressures in regions with high institutional development level. When complying with institutional pressures, firms try to make decisions to maximize profit while minimizing the risks to them. The purpose of this study is to investigate the influence of the institutional development level on institutional compliance timing by MNEs and the relationship between compliance speed and corporate performance. Design/methodology - The research focuses on three main variables, which are the institutional development level (as a determination of the institutional pressure level), the firm's compliance speed (as a determination of the compliance timing), and the firm's financial performance (as a determination of the corporate performance). We collected 19,869 firm-level data from CSMAR (the China Stock Market and Accounting Research), 6,922 CSR data from RKS (the Rankins CSR Ratings), and province and city-level data from the NERIM (National Economic Research Institute Index of Marketization) and NBSC (National Bureau of Statistics of China). The firms in China were chosen for analysis, and the analysis period was from 2008 to 2017. Random Effects GLS Regression was used to test the relationships among the variables. Findings - This study examined the effect of the institutional development level on the firm's compliance speed, together with the effect of compliance speed on the firm's financial performance of the MNEs in China. We found that the institutional development level positively influenced firms' financial performances, which means the firms' financial performances are better in the region with a high institutional development level. The compliance speed of institutional practice by firms was faster in the higher level of institutional development. However, the firm's delayed compliance led to better financial performance. Originality/value - Studies in the resource dependence view of Institutional Theory often fall short in understanding the theory by overlooking the firm's active decision-making. Thus, the findings do not present a full scope of corporate performance in this regard. This study not only found a way to test the role of a firm's independent decision-making (i.e., compliance timing) when facing the institutional pressure but also prove the significant role of the compliance timing on corporate performance. Also, we were able to test the effect of institutional development level, controlling location-specific variables because we used CSR performance data for MNEs operating in China. Lastly, by doing the above, the findings of this study suggest practical implications to the industry practitioners in MNEs.

• Korean Journal of Agricultural and Forest Meteorology
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• v.12 no.2
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• pp.95-106
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• 2010

The performance of Community Land Model version 3.5 - Dynamic Global Vegetation Model (CLM-DGVM) was evaluated through a comparison with the observation over temperate deciduous forest in Gwangneung, Korea. Influence of plant phenology, composition of plant functional type, and climate variability on carbon exchanges was also examined through sensitivity test. To get equilibrium carbon storage, the model was run for 400 years driven by the observed atmospheric data at the deciduous forest of the year 2006. We run the model for 2006 with the equilibrium carbon storage at Gwangneung forest and compared the model output with the observation. A comparison of leaf area index (LAI) between the model and observation indicated that the simulated phenology poorly represented the timing of budburst, leaf-fall, and evolution of LAI. Senescence of the phenology was delayed about four weeks and the simulated maximum LAI (of 5.8 $m^2$ $m^{-2}$) was greater than the observed value (of 4.5 $m^2$ $m^{-2}$). The overestimated LAI contributed to overestimation of both gross primary productivity (GPP) and ecosystem respiration $(R_e)$ through increased photosynthesis and foliar autotropic respiration $(R_a)$, respectively. Despite the discrepancy between the simulated and observed LAI, the simulated tree carbon storage amounts were comparable with the reported values at the site. Change in plant phenology from the simulated to the observed reduced more than six weeks of the plant growth period, resulting in the decreased amount of GPP and $R_e$. These values, however, were still higher (~10% of GPP and 40% of $R_e$) than the observed values. The effect of change in plant functional type composition (from dominant temperate deciduous forest to the coexistence of temperate deciduous and needle leaf forests) on the estimated amount of GPP and $R_e$ was marginal. The influence of climate variability on carbon storage amounts was not significant. The simulated inter-annual variation of GPP and $R_e$ from 1994 to 2003 depended on annual mean air temperature and total radiation but not on precipitation. Other deficiencies of CLM3.5-DGVM have been discussed.

• 한국노년학
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• v.29 no.4
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• pp.1247-1259
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• 2009

Muscle mass is reduced by aging. There seems to be no direct relationship between sarcopenia(muscle loss) and medical cost in the elderly, but lowering muscle mass results in increase risk of fall and decrease of strength, fitness, physical activity, and independent life. This is coupled with physical trouble and chronic degenerative disease such as diabetes, obesity, hyperlipidemia, and hypertension. Thus, sarcopenia is potential risk factor increasing mortality. The purpose of this study was to investigate the effects of elastic band exercise and detraining on sarcopenia prevention related variables, body composition and fitness. The subject of this study was 60~70 aged 14 seniors who participated in exercise program in J-welfare senior center at J-gu in S-city. Elastic band exercise was performed twice per week for 12 weeks. The body composition and fitness variables were measured before 12 weeks of control, after control(before exercise), after 12 weeks of exercise(before detraining), and after 12 weeks of detraining. There was no significant difference in body composition and fitness variables before and after 12 weeks of control, but elastic band exercise before and after 12 weeks has effect on body composition variables such as weight (t=2.978, p=0.001), body mass index (t=3.502, p=0.004), percent body fat (t=2.216, p=0.045), muscle mass (t=-3.837, p=0.002), visceral fat area (t=5.186, p<0.001), and waist-hip ratio (t=3.045, p=0.009) and on fitness variables such as 2-minutes step (t=-6.891 p<0.001), arm curl (t=-4.702, p<0.001), chair stand (t=-4.860, p<0.001), chair sit and reach (t=-5.910, p<0.001), back scratch (t=-3.835, p=0.002), and 8-ft up and go (t=7.560, p<0.001). This exercise effect was continued after 12 weeks of detraining on body composition variables such as weight (t=2.323, p=0.037), body mass index (t=2.503, p=0.026), muscle mass (t=-3.137, p=0.008) and on fitness variables such as 2-minutes step (t=-6.489 p<0.001), chair stand (t=-4.694, p<0.001), chair sit and reach (t=-3.690, p=0.003), and 8-ft up and go (t=7.539, p<0.001). It was found that the elastic band exercise has positive effect on body composition and fitness in the elderly and the effect was maintained over 12 weeks of detraining.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.8 no.2
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• pp.47-60
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• 1975

For the calculation of population parameter and estimation of recruitment of a fish population, an application of multiple regression method was used with some statistical inferences. Then, the differences between the calculated values and the true parameters were discussed. In addition, this method criticized by applying it to the statistical data of a population of bigeye tuna, Thunnus obesus of the Indian Ocean. The method was also applied to the available data of a population of Pacific saury, Cololabis saira, to estimate its recuitments. A stock at t year and t+1 year is, $N_{0,\;t+1}=N_{0,\;t}(1-m_t)-C_t+R_{t+1}$ where $N_0$ is the initial number of fish in a given year; C, number o: fish caught; R, number of recruitment; and M, rate of natural mortality. The foregoing equation is $$\phi_{t+1}=\frac{(1-\varrho^{-z}{t+1})Z_t}{(1-\varrho^{-z}t)Z_{t+1}}-\frac{1-\varrho^{-z}t+1}{Z_{t+1}}\phi_t-a'\frac{1-\varrho^{-z}t+1}{Z_{t+1}}C_t+a'\frac{1-\varrho^{-z}t+1}{Z_{t+1}}R_{t+1}......(1)$$ where $\phi$ is CPUE; a', CPUE $(\phi)$ to average stock $(\bar{N})$ in number; Z, total mortality coefficient; and M, natural mortality coefficient. In the equation (1) , the term $(1-\varrho^{-z}t+1)/Z_{t+1}$s almost constant to the variation of effort (X) there fore coefficients $\phi$ and $C_t$, can be calculated, when R is a constant, by applying the method of multiple regression, where $\phi_{t+1}$ is a dependent variable; $\phi_t$ and $C_t$ are independent variables. The values of Mand a' are calculated from the coefficients of $\phi_t$ and $C_t$; and total mortality coefficient (Z), where Z is a'X+M. By substituting M, a', $Z_t$, and $Z_{t+1}$ to the equation (1) recruitment $(R_{t+1})$ can be calculated. In this precess $\phi$ can be substituted by index of stock in number (N'). This operational procedures of the method of multiple regression can be applicable to the data which satisfy the above assumptions, even though the data were collected from any chosen year with similar recruitments, though it were not collected from the consecutive years. Under the condition of varying effort the data with such variation can be treated effectively by this method. The calculated values of M and a' include some deviation from the population parameters. Therefore, the estimated recruitment (R) is a relative value instead of all absolute one. This method of multiple regression is also applicable to the stock density and yield in weight instead of in number. For the data of the bigeye tuna of the Indian Ocean, the values of estimated recruitment (R) calculated from the parameter which is obtained by the present multiple regression method is proportional with an identical fluctuation pattern to the values of those derived from the parameters M and a', which were calculated by Suda (1970) for the same data. Estimated recruitments of Pacific saury of the eastern coast of Korea were calculated by the present multiple regression method. Not only spring recruitment $(1965\~1974)$ but also fall recruitment $(1964\~1973)$ was found to fluctuate in accordance with the fluctuations of stock densities (CPUE) of the same spring and fall, respectively.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.77-97
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• 2010

Market timing is an investment strategy which is used for obtaining excessive return from financial market. In general, detection of market timing means determining when to buy and sell to get excess return from trading. In many market timing systems, trading rules have been used as an engine to generate signals for trade. On the other hand, some researchers proposed the rough set analysis as a proper tool for market timing because it does not generate a signal for trade when the pattern of the market is uncertain by using the control function. The data for the rough set analysis should be discretized of numeric value because the rough set only accepts categorical data for analysis. Discretization searches for proper "cuts" for numeric data that determine intervals. All values that lie within each interval are transformed into same value. In general, there are four methods for data discretization in rough set analysis including equal frequency scaling, expert's knowledge-based discretization, minimum entropy scaling, and na$\ddot{i}$ve and Boolean reasoning-based discretization. Equal frequency scaling fixes a number of intervals and examines the histogram of each variable, then determines cuts so that approximately the same number of samples fall into each of the intervals. Expert's knowledge-based discretization determines cuts according to knowledge of domain experts through literature review or interview with experts. Minimum entropy scaling implements the algorithm based on recursively partitioning the value set of each variable so that a local measure of entropy is optimized. Na$\ddot{i}$ve and Booleanreasoning-based discretization searches categorical values by using Na$\ddot{i}$ve scaling the data, then finds the optimized dicretization thresholds through Boolean reasoning. Although the rough set analysis is promising for market timing, there is little research on the impact of the various data discretization methods on performance from trading using the rough set analysis. In this study, we compare stock market timing models using rough set analysis with various data discretization methods. The research data used in this study are the KOSPI 200 from May 1996 to October 1998. KOSPI 200 is the underlying index of the KOSPI 200 futures which is the first derivative instrument in the Korean stock market. The KOSPI 200 is a market value weighted index which consists of 200 stocks selected by criteria on liquidity and their status in corresponding industry including manufacturing, construction, communication, electricity and gas, distribution and services, and financing. The total number of samples is 660 trading days. In addition, this study uses popular technical indicators as independent variables. The experimental results show that the most profitable method for the training sample is the na$\ddot{i}$ve and Boolean reasoning but the expert's knowledge-based discretization is the most profitable method for the validation sample. In addition, the expert's knowledge-based discretization produced robust performance for both of training and validation sample. We also compared rough set analysis and decision tree. This study experimented C4.5 for the comparison purpose. The results show that rough set analysis with expert's knowledge-based discretization produced more profitable rules than C4.5.

• Journal of Korea Water Resources Association
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• v.45 no.3
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• pp.301-316
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• 2012

Two models, TANK and SWAT (Soil and Water Assessment Tool) were compared for simulating natural flows in the Paldang Dam upstream areas of the Han River basin in order to understand the limitations of TANK and to review the applicability and capability of SWAT. For comparison, simulation results from the previous research work were used. In the results for the calibrated watersheds (Chungju Dam and Soyanggang Dam), two models provided promising results for forecasting of daily flows with the Nash-Sutcliffe model efficiency of around 0.8. TANK simulated observations during some peak flood seasons better than SWAT, while it showed poor results during dry seasons, especially its simulations did not fall down under a certain value. It can be explained that TANK was calibrated for relatively larger flows than smaller ones. SWAT results showed a relatively good agreement with observed flows except some flood flows, and simulated inflows at the Paldang Dam considering discharges from upper dams coincided with observations with the model efficiency of around 0.9. This accounts for SWAT applicability with higher accuracy in predicting natural flows without dam operation or artificial water uses, and in assessing flow variations before and after dam development. Also, two model results were compared for other watersheds such as Pyeongchang-A, Dalcheon-B, Seomgang-B, Inbuk-A, Hangang-D, and Hongcheon-A to which calibrated TANK parameters were applied. The results were similar to the case of calibrated watersheds, that TANK simulated poor smaller flows except some flood flows and had same problem of keeping on over a certain value in dry seasons. This indicates that TANK application may have fatal uncertainties in estimating low flows used as an important index in water resources planning and management. Therefore, in order to reflect actually complex and complicated physical characteristics of Korean watersheds, and to manage efficiently water resources according to the land use and water use changes with urbanization or climate change in the future, it is necessary to utilize a physically based watershed model like SWAT rather than an existing conceptual lumped model like TANK.

• Korean Journal of Environment and Ecology
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• v.27 no.2
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• pp.219-229
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• 2013

This research is performed in order to suggest seasonal effective research time that is applied to wild birds research which lives in a forest. The subject area of this research is Mulgun-ri village forest in Samdong-Myeon, Namhe-gun. To investigate suitability of the project, existing land-use, existing vegetation, vegetational structure, and etc. of the subject and whole area are figured out. To suggest adequate research time, based on seasonal sun rise and set time for 3days, repetitive research is performed at hourly intervals. The subject area is connected with a forest and is possible for forest wild birds to flows in and provides various habitats and feeding areas. And also the subject area is a appropriate area for wild birds research and is like a natural forest in that a layer structure development of the forest itself, a distribution of Zelkova serrata and Aphananthe aspera and so on. 105 species which is observed in subject area are categorized and mountain birds are classified. After time-based peak value is selected in each season, hourly species richness, diversity, and index of similarity are analyzed as compared with the appearing number of species and individual bird. As a result, 7~11 hour is the most effective time in spring, and 8~9 hour is the best time. In summer, 6~9 hour is the most appropriate time when whole appearing species are similar to species structure. In fall, 7~11(30~60 minutes after sun rise) when wild birds movements are vigorous is analyzed easy to observe and 8~9 hour is the most appropriate research time because each analysis shows the best values. In winter, 7~12 hour is the most effective time although 10~11 hour is the best time but it is decided that similar results are drawn because hourly deviation is not so big except 1 hour before sun rise. In every four season, it is decided that 30~60 minutes after sun rise is appropriate to research a group of wild birds in the subject area.

• Journal of Korean Academy of Nursing
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• v.11 no.2
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• pp.105-123
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• 1981

This study was carried out during the month of September 1976 to analyse and compare the health complaints of two groups of the university women, those who lived at home and those who lived in the university dormitory. The purpose of the study was to provide basic data required by the university health program for planning related to the health need of women students. The study sample consisted of 434 students living in the dormitory and 381 students living at home enrolled for the fall semester 1976 in a womens university in Seoul. The instrument used for the collection of data was an abridged version of a modified Cornell Medical Index. The questionarre included 35 items related to physical health complaint and 22 items related to mental health complaints. The data was treated by a computer (SPSS) using one way analysis, the Fishers' ratio and Chi-Square test at the 5％ level were used for the test for statistical significance. The interpretation of this study is limited due to the sample which was restricted to one university and not randomly selected. To guide the direction of the study, it was hypothesized that the rate of expressed health problems of students living in the dormitory would be Venter than that of students living at home. The hypothesis was tested and rejected. The following is a summary of the findings; 1. Total health (physical and mental) complaints a. There was no statistically significant difference between the home and dormitory groups with regard to total health complaints expressed. b. The rate of total complaints expressed by the home group significantly higher than dormitory group only among third year students. c. There was no statistically significant between the home and dormitory groups in their satisfaction with their economic situation. d. The home group showed a significantly higher rate of complaints related to the Nervous System compared to that of the dormitory group. 2. Physical health complaints a. Students living at home showed a significantly higher rate of physical complaints than the dormitory group. b. When the year variable was controlled, the third year was the only group which showed a different rate between home and dormitory groups; the home group presented a higher rate. c. Since the year variable seemed to affect the physical complaints those data were further analysed to see whether the specific system areas were operating as variables in each year. The results were as follow: Among the home group, First year students showed a higher rate in Family History of Disease, while the third year students more Nervous System and Cardiovascular System complaints. Among the dormitory group, only fourth year students showed a higher rate in the Skeletal-Muscular System. This was the only area the dormitory group though only for the fourth year students supported the hypothesis. d. When the economic satisfaction variable was controlled, the satisfied group was the only group which showed a different rate between home and dormitory groups; the home group presented higher rate. e. Since the economic satisfaction variable seemed to affect the physical complaints those data were further analyzed to see whether the specific system areas were operating as variables in each economic satisfaction level, but there was no statistically significant difference between home and dormitory groups. 3. Mental health complaints a. There was no significantly difference between home and dormitory groups with regard to mental health complaints expressed. b. When the year variable was controlled the third year group was the only group which showed a different rate between home and dormitory groups; the home group presented a higher rate. c. Since the year variable seemed to affect the mental complaints, those data were further analyzed to see whether the specific system areas were operatings variables in each economic satisfaction level. The result were as follows: Among the home group, the third year students showed higher rates in Inadequacy and Anxiety. d. When the economic satisfaction variable was controlled, the very satisfied group was the only group which showed a different rate between home and dormitory groups: the home group presented a higher rate. Since the economic satisfaction variable seemed to affect the mental complaints, those data were further analysed to see whether the specific system areas were operating as variables in each economic satisfaction level, but there was no statistical significant difference between the home and dormitory groups. Although the social environment of dormitory life differs from family life, there was no difference in the rate of total health problem complaints between the home and dormitory groups but the home group showed a higher rate of physical health complaints than the dormitory group. Possible positive factors influencing dormitory life and negative factors influencing family life affecting health complaints must be explored in order to relate to the health needs of the university health program. This study could not define the causes for the fewer physical complaints of dormitory students living at home. Further study of such causal factors recommended in order to provide the data needed to contribute to a more effective health program.