• Journal of the Korean Institute of Gas
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• v.18 no.1
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• pp.8-16
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• 2014

In this study, the number of gas accidents prediction model was suggested by analyzing the gas accidents occurred in Korea. In order to predict the number of gas accidents, simple moving average method (3, 4, 5 period), weighted average method and exponential smoothing method were applied. Study results of the sum of mean-square error acquired by the models of moving average method for 4 periods and weighted moving average method showed the highest value of 44.4 and 43 respectively. By developing the number of gas accidents prediction model, it could be actively utilized for gas accident prevention activities.

• The Korean Journal of Applied Statistics
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• v.30 no.1
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• pp.1-12
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• 2017

Many stochastic processes satisfy the Markov property exactly or at least approximately. An interested property in the Markov process is the first passage time. Since the sequential analysis by Wald, the approximation of the first passage time has been studied extensively. The Statistical computing technique due to the development of high-speed computers made it possible to calculate the values of the properties close to the true ones. This article introduces an exponentially weighted moving average (EWMA) control chart as an example of the Markov process, and studied how to calculate the average run length with problematic issues that should be cautioned for correct calculation. The results derived for approximation of the first passage time in this research can be applied to any of the Markov processes. Especially the approximation of the continuous time Markov process to the discrete time Markov chain is useful for the studies of the properties of the stochastic process and makes computational approaches easy.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.156-156
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• 2023

본 연구는 SWAT(Soil and Water Assessment Tool)과 PHABSIM(Physical Habitat Simulation System)을 활용하여 남강댐유역(2,983.0 km²)을 대상으로 유역환경변화에 따른 환경생태유량 확보량을 산정하였다. 유역환경변화를 고려하기 위해 유역환경변화 요인(토지이용, 지하수 이용, 산림생장, 도로개발, 토양깊이)를 1980s(1976~1985), 2010s(2006~2019)로 구분하여 보정된 SWAT에 적용하였다. 유역환경변화 분석결과 토지이용은 1980s 대비 2010s에서 도시와 농업지역은 증가하였으나, 산림과 수역은 감소하였다. 지하수 이용은 1980s 대비 2010s에서 +18.9 백만 m³/년 증가한 평균 31.5 백만 m³/년으로 분석되었고, 산림높이는 1980s 대비 2010s에서 +0.6 m 증가한 평균 12.4 m의 수고를 가지는 것으로 분석되었다. 토양깊이와 도로망의 경우 각각 1980s 대비 2010s에서 -0.2 cm, +29.2 km 증가한 61.3 cm, 51.5 km로 나타났다. 유역환경변화 요인을 SWAT에 적용한 결과, 남강댐유역의 평균 유량은 1980s 대비 2010s에서 -9.5 m³/sec 감소한 77.3 m³/sec로 분석되었다. 남강댐유역의 환경생태유량을 산정하기 위해 하류에 위치한 정암교가 위치한 하천에 대해 PHABSIM을 구축하였고, 대표어종인 피라미에 대한 서식처적합도지수를 적용하여 환경생태유량을 산정하였다. 최적 환경생태유량은 21.0 m³/sec로 나타났고, 가중가용면적-유량 관계를 활용하여 가중가용면적 비율별(100%~25%) 환경생태유량을 산정하였다. 2010s에서 환경생태유량을 만족하지 못하는 73일(Q293~Q365)에 대하여 각 유황과 환경생태유량과의 차이를 일별로 계산한 후 10일 간격의 차이의 총합을 확보량으로 정의하여 산정하였다. 100% 환경생태유량 기준일 때 평균 확보량과 확보기간은 각각 5.36 m³/sec, 73일로 나타났고, 80% 기준일 때 평균 확보량과 확보기간은 각각 2.75 m³/sec, 20일로 나타났다.

• Journal of KIISE:Computer Systems and Theory
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• v.26 no.1
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• pp.64-71
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• 1999

본 논문에서는 공중 광역 ATM망 환경에서 비연결형 서비스 제공에 사용되는 CLS에 적용될 수 있는 홉 카운터를 이용한 우선 순위 제어 알고리즘(Priority Control Algorithm using Hop-Count : HC-PC)의 망 자원 손실 비용을 분석하였다. 분석을 통해 우선 순위가 없을 경우 (No Priority Controls Algorithm: NO-Pc) 의 평균 셀 손실률이 HC-PC 의 평균 셀 손실률의 가중 평균보다 크거나 같은 경우 항상 NO-PC 이 평균 망 자원 손실 비용이 HC-PC 의 평균 망 자원 손실 비용에 비해 크다는 사실을 보였다. 시뮬레이션 결과는 분석에 의해 찾아진 조건이 만족됨을 보여주며 HC-PC가 NO-PC에 비해 어떠한 환경에서든지 항상 낮은 평균 망 자원 손실 비용을 가짐을 보여 준다.

• Journal of the Korean Data and Information Science Society
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• v.22 no.2
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• pp.189-196
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• 2011

In this study, we perform a simulation study to compare frequently used standardization methods for interview scores based on trimmed mean, rank mean, and z-score mean. In this simulation study we assume that interviewer's score is influenced by a weighted average of true interviewee's true score and independent noise whose weight is determined by the professionality of the interviewer. In other words, as interviewer's professionality increases, the observed score becomes closer to the true score and if interviewer's professionality decreases, the observed score becomes closer to the noise instead of the true score. By adding interviewer's tendency bias to the weighed average, final interviewee's score is assumed to be observed. In this simulation, the interviewers's cores for each method are computed and then the method is considered best whose rank correlation between the method's scores and the true scores is highest. Simulation results show that when the true score is from normal distributions, z-score mean is best in general and when the true score is from Laplace distributions, z-score mean is better than rank mean in full interview system, where all interviewers meet all interviewees, and rank mean is better than z-score mean in half split interview system, where the interviewers meet only half of the interviewees. Trimmed mean is worst in general.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.4
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• pp.182-193
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• 2011

In order to compare the spatio-temporal variation pattern of sea surface temperature (SST) in Korea's Southern areas of the sea according to a regional scale, this study has selected the winter and summer seasons for 31 years (1980~2010) in a period aspect and selected three areas of the sea such as the Western areas of the sea (region B) and Eastern areas of the sea (region C) around Jeju Island in addition to overall Southern areas of the sea (region A) in regional aspect. The regression analysis was applied to find out a temporal variation pattern of SST, and the weighted mean center (WMC) of SST as well as analysis of a standard deviational ellipse (SDE) was respectively applied. As a result of regression analysis of SST, it showed a rising long-term trend for all two seasons in three regions. However, though the average SST for 31 years was all similar in three regions in the summer season, the region C appeared more highly than region B in the winter season. The spatial variation pattern of SST for two seasons showed that it is respectively different from each other in three regions. The spatial variation pattern of SST appeared as E-W direction in region A, SE-NW direction in region B and SW-NE direction in region C. In addition, the relationship between the location of the WMC of SST and the average SST showed correlation in regions A and B in the winter season, whereas it appeared that there is no correlation in region C. Accordingly, it can be known that the regional scale should be considered in case of analysis of spatio-temporal variation patterns of SST.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.779-784
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• 2008

환경부에서 추진하고 있는 토지피복 중분류별 비점오염부하원단위를 산정하기 위한 사업 중 나지로 분류되는 채광지역의 비점오염부하를 측정하였다. 비점오염부하는 강원도 삼척시 도계읍의 도계 작업장(석탄)과 태백시 장성동의 태백 저탄소 등 2곳의 채광지역에서 2007년 9월부터 12월까지 2회의 강우유출사상을 대상으로 측정하였다. 2회 강우사상 동안 총강수량은 도계 작업장에서 149 mm이었으며 태백 저탄소에서 201 mm이었다. 유출량은 수위계와 유량계로 5분 단위로 측정하였으며, 수질시료는 자동채수기로 2시간 간격으로 채취하였다. 수질시료는 환경부의 공정시험법에 따라 SS, BOD, CODcr, T-N, T-P, 그리고 TOC 농도를 분석하였다. 그리고 일부의 시료에 대해서는 Zn, Cb, Cu, 그리고 Pb의 농도를 분석하였다. 도계 작업장의 유량가중평균농도는 갱내수의 수질에 많은 영향을 받는 것으로 나타났다. 도계작업장의 일평균유량가중평균농도는 SS $86.3{\sim}94.9\;mg/{\ell}$, BOD $3.8{\sim}7.6\;mg/{\ell}$, COD $26.9{\sim}51.6\;mg/{\ell}$, T-N $1.5{\sim}2.1\;mg/{\ell}$, T-P $0.2\;mg/{\ell}$ 그리고 TOC $1.8{\sim}2.3\;mg/{\ell}$로 나타났다. 태백 저탄소의 일평균유량가중평균농도는 SS $16.5{\sim}66.6\;mg/{\ell}$, BOD $7.4{\sim}9.8\;mg/{\ell}$, COD $41.1{\sim}66.7\;mg/{\ell}$, T-N $0.7{\sim}1.1\;mg/{\ell}$, T-P $0.2\;mg/{\ell}$ 그리고 TOC $1.7{\sim}2.6\;mg/{\ell}$로 나타났다. 중금속의 농도는 모든 시료에서 환경부의 배출허용기준농도보다 낮게 나타나거나 검출되지 않았다. 도계 작업장의 일오염부하는 SS $1,368.8{\sim}1,984.1\;kg/day$, BOD $56.6{\sim}128.9\;kg/day$, COD $385.7{\sim}933.7\;kg/day$, T-N $23.4{\sim}44.5\;kg/day$, T-P $2.1{\sim}4.8\;kg/day$ 그리고 TOC $24.3{\sim}39.3\;kg/day$이었다. 태백 저탄소의 일오염부하는 SS $8.2{\sim}162.1\;kg/day$, BOD $2.6{\sim}15.3\;kg/day$, COD $13.8{\sim}83.6\;kg/day$, T-N $0.2{\sim}3.1\;kg/day$, T-P $0.1{\sim}0.6\;kg/day$ 그리고 TOC $0.7{\sim}4.4\;kg/day$로 나타났다. 본 연구는 2회의 강우유출사상에 대하여 측정한 자료이므로 연평균농도나 연평균오염부하로 활용하기는 어렵다. 그러나 석탄광산지역의 비점오염부하를 이해하는데 활용할 수 있으며 또한 장기적인 연구자료로 활용하여 석탄광산지역의 비점오염원단위의 산정에 유용한 자료로 활용할 수 있다.

• Korean Journal of Agricultural and Forest Meteorology
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• v.5 no.1
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• pp.1-5
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• 2003

This study was carried out to investigate the chemical properties of rainwater in the Suwon area. Rainwater was collected from April to October in 1999 and 2000, and its chemical composition was analyzed. The pH of rainwater in April was higher than that of the months after June. Occurrence frequency of rain above pH 5.6 was 45.1%, which showed the highest ratio from rainwater samples during the investigation periods. Those of pH 5.0∼5.6 and 4.5∼4.9 range were 31.4 and 19.6%, respectively. The major cations in rainwater were $Ca^{2+}$ and N $H_{4}$$^{+}$, and S $O_{4}$$^{2-}$ made up more than 50% of total anion composition. Monthly variation of neutralization capacity of rainwater acidity by $Ca^{2+}$ and N $H_{4}$$^{+}$ decreased during the rainy season. The ratio of non-sea salt sulfate to nitrate (nss-S $O_{4}$$^{2-}$/N $O_{3}$$^{[-10]}$ ) was 2.1, which means anthropogenic S $O_{4}$$^{2-}$ contributed to acidity of rainwater two times more than N $O_{3}$$^{[-10]}$ . .

• Korean Journal of Agricultural and Forest Meteorology
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• v.2 no.4
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• pp.175-182
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• 2000

Spatial interpolation of daily temperature forecasts and observations issued by public weather services is frequently required to make them applicable to agricultural activities and modeling tasks. In contrast to the long term averages like monthly normals, terrain effects are not considered in most spatial interpolations for short term temperatures. This may cause erroneous results in mountainous regions where the observation network hardly covers full features of the complicated terrain. We developed a spatial interpolation model for daily minimum temperature which combines inverse distance squared weighting and elevation difference correction. This model uses a time dependent function for 'mountain slope lapse rate', which can be derived from regression analyses of the station observations with respect to the geographical and topographical features of the surroundings including the station elevation. We applied this model to interpolation of daily minimum temperature over the mountainous Korean Peninsula using 63 standard weather station data. For the first step, a primitive temperature surface was interpolated by inverse distance squared weighting of the 63 point data. Next, a virtual elevation surface was reconstructed by spatially interpolating the 63 station elevation data and subtracted from the elevation surface of a digital elevation model with 1 km grid spacing to obtain the elevation difference at each grid cell. Final estimates of daily minimum temperature at all the grid cells were obtained by applying the calculated daily lapse rate to the elevation difference and adjusting the inverse distance weighted estimates. Independent, measured data sets from 267 automated weather station locations were used to calculate the estimation errors on 12 dates, randomly selected one for each month in 1999. Analysis of 3 terms of estimation errors (mean error, mean absolute error, and root mean squared error) indicates a substantial improvement over the inverse distance squared weighting.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.10
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• pp.373-380
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• 2022

This paper presents a deep learning based group synchronization that supports networked immersive interactions between remote users. The goal of group synchronization is to enable all participants to synchronously interact with others for increasing user presence Most previous methods focus on NTP-based clock synchronization to enhance time accuracy. Moving average filters are used to control media playout time on the synchronization server. As an example, the exponentially weighted moving average(EWMA) would be able to track and estimate accurate playout time if the changes in input data are not significant. However it needs more time to be stable for any given change over time due to codec and system loads or fluctuations in network status. To tackle this problem, this work proposes the Deep Group Synchronization(DeepGroupSync), a group synchronization based on deep learning that models important features from the data. This model consists of two Gated Recurrent Unit(GRU) layers and one fully-connected layer, which predicts an optimal playout time by utilizing the sequential playout delays. The experiments are conducted with an existing method that uses the EWMA and the proposed method that uses the DeepGroupSync. The results show that the proposed method are more robust against unpredictable or rapid network condition changes than the existing method.