• The Journal of Engineering Geology
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• v.25 no.3
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• pp.377-385
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• 2015

We constructed a model test apparatus to evaluate the dependence of the saturation velocity (V_s) in soils on rainfall intensity (I_R). The apparatus comprises a soil box, a rainfall simulator, and measuring sensors. The model grounds (60 cm × 50 cm × 15 cm) were formed by Joomunjin standard sand with a relative density of 75%. The rainfall simulator can control the rainfall intensity to reenact the actual rainfall in a soil box. Time Domain Reflectometer (TDR) sensors and tensiometers were installed in the soils to measure changes in the volumetric water content and matric suction due to rainfall infiltration. During the tests, the soil saturation was determined by raising the groundwater table, which was formed at the bottom of the soil box. [Please check that the correct meaning has been maintained.] The wetting front did not form at the ground surface during rainfall because the soil particles were uniform and the coefficient of permeability was relatively high. Our results show that the suction stress of the soils decreased with increasing volumetric water content, and this effect was most pronounced for volumetric water contents of 20%-30%. Based on a regression analysis of the relationship between rainfall intensity and the average saturation velocity, we suggest the following equation for estimating the saturation velocity in soils: V_savg (cm/sec) = 0.068I_R (mm/hr).

• Korean Journal of Agricultural and Forest Meteorology
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• v.7 no.4
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• pp.282-288
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• 2005

This study was carried out to estimate aboveground carbon contents associated with four years of thinning treatment of Quercus acuta stands in Wando Arboretum, Jeonnam. Stand thinning was conducted over four years using stand table projection for each thinning treatment. Ten sample trees were cut in the surveyed area. Estimation of aboveground biomass was made using the equation model $W=aD+bD^2$ where W is oven dry weight and D is DBH in cm. The total aboveground biomass for each intensity treatment area was : control (148.4 ton/ha), light (105.6 ton/ha), moderate (68.7 ton/ha) and heavy (39.1 ton/ha). Aboveground carbon storage for Quercus acuta stands was found by multiplying dry weigh t (ton/ha) by 0.5. Carbon storage and increment after four years was: control (74.2 tonC/ha), light (52.8 tonC/ha), moderate (34.3 tonC/ha) and heavy thinning intensity area (38.2tonC/ha).

• Journal of Korea Water Resources Association
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• v.32 no.4
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• pp.403-415
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• 1999

This study is to derive the rainfall intensity formula based on the representative probability distribution in Korea. The 11 probability distributions which has been widely used in hydrologic frequency analysis are applied to the annual maximum rainfall. The parameters of each probability distribution are estimated by method of moments, maximum likelihood method and method of probability weighted moments. Four tests such as $x^2$-test, Kolmogorv-Smirnov test, difference test and modified difference test are used to determine the goodness of fit of the distributions. The homogeneous tests (Mann-Whitney U test, Kruskal-Wallis one-way analysis of variance of nonparametric test) are applied to find the stations with rainfall homogeneity. The results of homogeneous tests show that there is no representative appropriate distribution for the whole duration in Korea. The whole region could be divided into five zones for 12-durations. The representative probability distribution of each divided zone for 12-durations was determined. The GEV distribution for I,II,V zones and the 3-parameter Weibull distribution for III,IV zones were determined as the representative probability distribution. The rainfall were obtained from representative probability distribution for the selected return periods. Rainfall intensity formula was determined by linearization technique for the rainfall.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.774-778
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• 2010

Upland erosion pollutes surface waters and often causes serious problems when deposition occurs. This study builds a sediment rating curve using the measured sediment yield and the simulated soil erosion by a GIS-embedded empirical model. The coefficient of determination ($R^2$) between the simulated soil erosion and the measurement sediment yields with rainfall amount are 0.427 for Donghyang and 0.667 for Cheonchen, but the values with rainfall intensity are 0.873 and 0.927 respectively. The data are divided into two groups: one for calibration during 2002-2005 (48 months) and the other for estimation during 2006-2008 (36 months). The first data group (2002-2005) was used to derive the SDR with an aid of soil erosion calculated by the USLE and the measured sediment yield. The mean SDR with rainfall amount is 6.273 and 3.353, respectively, while 4.799 and 2.874 for rainfall intensity. But the standard deviation (STD) with rainfall intensity is 0.930 and 0.407, which is much less than that with rainfall amount (3.746 and 2.090) for both sites. The results show the derived SDR provides reasonable accuracy and rainfall intensity gives better performance in calculating soil erosion than rainfall amount.

• Korean Journal of Remote Sensing
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• v.26 no.5
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• pp.511-525
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• 2010

Rainfall intensity was estimated using the MTSAT-1R infrared channels and the microwave satellite precipitation data. Brightness temperature of geostationary satellite is matched temporal and spatial to a variety of microwave satellite(SSM/I, SSMIS, AMSU-B, AMSRE, TRMM) precipitation data. Rainfall intensity was calculated by the look -up table using relationships of MTSAT-1R brightness temperature and microwave precipitation. Estimated rainfall is verified using by precipitation of TRMM satellite(TRMM3B42) and ground rainfall as AWS from Jul. 21 2008 to Jul. 25 2008. The results of rainfall estimated TRMM 2A12(TMI) that validated by AWS and TRMM3B42 precipitation are represented highly 0.38 and 0.61 by correlation coefficient, 5.81 mm/hr and 2.44 mm/hr by RMSE, 0.79 and 0.84 by POD and 0.65 and 0.87 by PC, respectively. Overall, estimated rainfall using by microwave satellite calculated 5 mm/hr or more comparing by AWS and 5 mm/hr or more comparing by TRMM3B42 precipitation, respectively. Validation results of correlation coefficient are shown series of TRMM 2A12, AMSRE, SSM/I, AMSU-B and SSMIS.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.4
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• pp.232-241
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• 2019

This study examines one of the conventional and controversial issues in modern finance. Specifically, this study identifies financial determinants of corporate R&D intensity for firms belonging to Korean Chaebols. Empirical estimation procedures are applied to derive more robust results of each hypothesis test. Static panel data, Tobit regression and stepwise regression models are employed to obtain significant financial factors of R&D expenditures, while logit, probit and complementary log-log regression models are used to detect financial differences between Chaebol firms and their counterparts not classified as Chaebols. Study results found the level of R&D intensity in the prior fiscal year, market-value based leverage ratio and firm size empirically showed their significance to account for corporate R&D intensity in the first hypothesis test, whereas the majority of explanatory variables had important power on a relative basis. Assuming that the current circumstances in the domestic capital market may necessitate gradual changes of Korean Chaebols in terms of their socio-economic function, the results of this study are expected to contribute to identifying financial antecedents that can be beneficial to attain optimal level of corporate R&D expenditures for Chaebol firms on a virtuous cycle.

• Journal of the Economic Geographical Society of Korea
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• v.25 no.4
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• pp.600-616
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• 2022

This study contemplates spatial context of startup in manufacturing, mainly analyzing job creation effects of time lag of startups in manufacturing at different technology levels. Using DID model, we found that each region including capital, non-capital and metropolitan area shows different job creation effects of time lag. In capial region, startup cohort in high R&D intensity manufacturing was found to show short-term job creation effects, but in non-capital region, long-term job creation effects was found with the one in medium-high R&D intensity manufacturing. In case of metropolitan area, we couldn't find much evidence of job creation effects that was statistically significant. The result of analysis implied that, in capital region, startup support policies, targeting at high R&D intensity manufacturing, ought to be focused on scale-up of startups that survived for a certain period. And non-capital area and some of metropolitan areas in non-capital region that have comparatively inferior infrastructure and brain-drain problems as well should focus on fostering startups in medium-high R&D intensity manufacturing in a long-term perspective and utilize their traditional manufacturing base.

• Environmental and Resource Economics Review
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• v.18 no.2
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• pp.279-309
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• 2009

Greenhouse gas emissions should be precisely forecast to reduce the emissions from industrial production processes. This study calculated the direct and indirect $CO_2$ emission intensities of 401 industries using the Input-Output tables 2003 and statistical data on the amount of energy use. This study had some limitations in drawing study findings because overseas data were used given the lack of domestic data. Other limiting factors included the oil distribution problems in the oil refinery sector, re-review of carbon neutral, and insufficient consideration of waste treatment. Nonetheless, this study is very meaningful since the direct and indirect $CO_2$ emission intensities of 401 industries were calculated. Specifically, this study considered from the zero-waste perspective the effects of waste, which attract interest worldwide since coke gas and gas from the steel industry are obtained as byproducts for the first time in Korea. According to the results of the analysis of $CO_2$ emission intensity per industry, typical industries whose indirect $CO_2$ emission intensity is high include crude steel making, Remicon, steel wire rods & track rail, cast iron, and iron reinforcing rods & bar steel. These industries produce products using the raw materials produced in the industrial sector whose $CO_2$ emission intensity is high. The representative industries whose direct $CO_2$ emission intensity is high include cement, pig iron, lime & plaster products, andcoal-based compounds. These industries extract raw ore from nature and refine them into raw materials that are useful in other industries. The findings in this study can be effectively used for the following case: estimation of target $CO_2$ emission reduction level reflecting each industrial sector's characteristics, calculation of potential emission reduction of each policy to reduce $CO_2$ emissions, identification of a firm's $CO_2$ emission level, and setting of the target level of emission reduction. Moreover, the findings in this study can be utilized widely in fields such as System of integrated Environmental and Economic Accounting(SEEA) and Material Flow Analysis(MFA) as the current topic of research in Korea.

• Journal of the HCI Society of Korea
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• v.9 no.1
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• pp.11-21
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• 2014

We present an experimental framework to analyze the physical reactions and causal factors of Visually Induced Motion Sickness (VIMS) using electroencephalography (EEG) signals and vital signs. We studied eleven subjects who are voluntarily participated in the experiments and conducted online and offline surveys. In order to simulate videos including global motions that could cause the motion sickness, we extracted global motions by optical flow estimation method from hand-held captured video recordings containing intense motions. Then, we applied the extracted global motions to our test videos with action movies and texts. Each genre of video includes three levels of different motions depending on its intensity. EEG signal and vital sign that were measured by a portable electrocorticography device and an electronic monometer in real time while the subjects watch the videos including ones with the extracted motions. We perform an analysis of the EEG signals using Distance Map(DM) calculated by correlation among each channel of brain signal. Analysis using the vital signs and the survey results is also performed to obtain relationship between the VIMS and causal factors. As a result, we clustered subjects into three groups based on the analysis of the physical reaction using the DM and the correlation between vital sign and survey results, which shows high relationships between the VIMS and the intensity of motions.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.5
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• pp.469-475
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• 2017

Software reliability is one of the most basic and essential problems in software development. In order to detect the software failure phenomenon, the intensity function, which is the instantaneous failure rate in the non-homogeneous Poisson process, can have the property that it is constant, non-increasing or non-decreasing independently at the failure time. In this study, was compared the reliability performance of the software reliability model using the Landely lifetime distribution with the intensity function decreasing pattern and Erlang lifetime distribution from increasing to decreasing pattern in the software product testing process. In order to identify the software failure phenomenon, the parametric estimation was applied to the maximum likelihood estimation method. Therefore, in this paper, was compared and evaluated software reliability using software failure interval time data. As a result, the reliability of the Landely model is higher than that of the Erlang distribution model. But, in the Erlang distribution model, the higher the shape parameter, the higher the reliability. Through this study, the software design department will be able to help the software design by applying various life distribution and shape parameters, and providing software reliability attributes data and basic knowledge to software reliability model using software failure analysis.