• Journal of the Korean earth science society
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• v.40 no.6
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• pp.572-583
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• 2019

In this study, the atmospheric vertical structure (AVS) associated with summertime (June, July, and August) heavy rainfall in Seoul was classified into three patterns (Loaded Gun: L, Inverted V: IV, and Thin Tube: TT) using rawinsonde soundings launched at Osan from 2009 to 2018. The characteristics of classified AVS and precipitation property were analyzed. Occurrence frequencies in each type were 34.7% (TT-type), 20.4% (IV-type), 20.4% (LG-type), and 24.5% (Other-type), respectively. The mean value of Convective Available Potential Energy (1131.1 J kg^-1) for LG-types and Storm Relative Helicity (357.6 ㎡s^-2) for TT-types was about 2 times higher than that of other types, which seems to be the difference in the mechanism of convection at the low level atmosphere. The composited synoptic fields in all cases showed a pattern that warm and humid southwesterly wind flows into the Korean Peninsula. In the cases of TT-type, the low pressure center (at 850 hPa) was followed by the trough in upper-level (at 500 hPa) as the typical pattern of a low pressure deepening. The TT-type was strongly influenced by the low level jet (at 850 hPa), showing a pattern of connecting the upper- and low-level jets. The result of analysis indicated that precipitation was intensified in the first half of all types. IV-type precipitation induced by thermal instability tended to last for a short term period with strong precipitation intensity, while TT-type by mechanical instability showed weak precipitation over a long term period.

• Journal of The Korean Astronomical Society
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• v.50 no.2
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• pp.21-27
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• 2017

The autoregressive method provides a univariate procedure to predict the future sunspot number (SSN) based on past record. The strength of this method lies in the possibility that from past data it yields the SSN in the future as a function of time. On the other hand, its major limitation comes from the intrinsic complexity of solar magnetic activity that may deviate from the linear stationary process assumption that is the basis of the autoregressive model. By analyzing the residual errors produced by the method, we have obtained the following conclusions: (1) the optimal duration of the past time for the forecast is found to be 8.5 years; (2) the standard error increases with prediction horizon and the errors are mostly systematic ones resulting from the incompleteness of the autoregressive model; (3) there is a tendency that the predicted value is underestimated in the activity rising phase, while it is overestimated in the declining phase; (5) the model prediction of a new Solar Cycle is fairly good when it is similar to the previous one, but is bad when the new cycle is much different from the previous one; (6) a reasonably good prediction of a new cycle can be made using the AR model 1.5 years after the start of the cycle. In addition, we predict the next cycle (Solar Cycle 25) will reach the peak in 2024 at the activity level similar to the current cycle.

• KIEAE Journal
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• v.15 no.6
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• pp.63-68
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• 2015

Purpose: Most if buildings need various repair works for preventing or delaying the deterioration which gives rise to affect the living condition or function after constructed. Therefore, a long-term repair schedule should be planned and a repair cost is required. In this paper, it aimed at providing the statistical forecast model for a repair cost in roof water-proofing work and elevator work using statistical approach with three variables such as number of household, management area and a elapsed year. Data are collected in apartment housings which are located in Seoul area and conducted with interview and questionnaire sheet. Each analyzed work is divided into a partly work and fully work. Results of this study are shown that, first, the regression model takes a multiplying type like a Cobb-Douglas function and is changed into the log-linear type to include the three variable simultaneously. Second, the goodness-of-fit of the repair cost forecasting model has a good statistics in determinant's coefficient and Dubin-Watson value. Third, the management area is stronger factor than other the number of household and an elapsed year in roof water-proofing work and elevator work.

• Journal of Korea Game Society
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• v.18 no.2
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• pp.15-26
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• 2018

Virtual Reality(VR) is one of the most remarkable technologies in the current game industry. Nevertheless, it is difficult for the game industry to actively invest in the VR technology because of the technical problems to overcome and the uncertainty about the market possibility. Therefore, this study attempts to estimate the future possibilities of the VR game market in various angles. For the purpose, we explore the domestic game market from the past to the present, and forecast the game industry ecosystem using the Scenario Network Mapping. Based on the result, we propose a short and long term future prospect and suggest the possible strategies for each stakeholder of the VR game market.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.991-995
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• 2009

최근 기후변화 등으로 우리나라의 경우 강수일수는 감소한 반면 집중호우의 발생빈도는 증가하고 있다. 실제 가뭄과홍수와 같은 극치사상의 피해가 증가될 가능성과 이러한 재해로부터 인명 및 재산을 보호하고 효율적인 수자원 활용을 위해서는 장기간 강우-유출과정의 정확한 해석이 필수적이다. 본 연구는 미호천 유역을 대상으로 장기유출을 모의하기 위해 개념적 강우유출모형을 적용하였다. 본 연구의 개념적 강우유출모형은 PDM(Probability Distributed Model)으로 유역을 한 개의 단위구역으로 사용한 집중형(lumped) 모형이고, 분포형 모형에 비하여 간단 (parsimonious)하며 영국의 수자원 및 홍수 관리 목적으로 널리 사용되고 있다. 모형의 검정은 MC(Monte Carlo) 방법과 SCE-UA(Shuffled Complex Evolution-University of Arizona) 방법을 적용하였으며, NSE(Nash Sutcliffe Efficiency) 목적함수를 사용하여 모형의 성능을 검토하였다. 그 결과, MC 방법과 SCE-UA 방법 모두 NSE의 값 0.9 이상으로 만족할 만한 모의성능을 나타내었다. 분포형 모형에 비하여 적은 수문자료 및 검정변수를 갖는 PDM 모형을 수문자료의 취득이 용이하지 않은 중 소규모 유역에 적용하여 모형의 검정 및 유량산정에 있어 우수함을 확인하였다. 이에 우리나라 전역에 걸쳐 다양한 유역을 대상으로 PDM 모형의 검토가 요구되고, 향후 우리나라의 홍수량 산정 및 수자원 관리에 적용될 수 있다고 판단된다.

• Journal of the Korean Institute of Rural Architecture
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• v.4 no.1
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• pp.9-18
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• 2002

Keumsan-gun is the area where there are many mobile populations as the place to be adjacent to Daejon. There is the tendency that the empty houses at Keumsan area are increasing as 1,115 houses every year as of 2001. So, this researcher examined and analyzed the actual state by grasping the present situation of empty houses centering around Keumsan-gun. And, this researcher could obtain the following conclusion as the result that this researcher progressed the study so as to present the application scheme of empty houses. As for Keumsan-gun, farming populations are more than other city and gun at Choongcheong Southern Proince Area as the area formed with mountain groups topographically. Thus, it is forecast that the appearance of empty houses will increase, as the population decrease and the residents to have migration plan will appear higher than other city and gun in the future also. Therefore, as for the superannuated empty houses that use is impossible, to service by removing will be helpful to the image uplifting of village. In addition, as for the empty houses that use is possible, the establishment of system to connect buyers by rebuilding them as garden houses and weekend houses etc. through purchase and sale and long-term lease etc. is necessary.

• Atmosphere
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• v.20 no.4
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• pp.519-530
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• 2010

In this paper we review current research on Atmospheric Brown Clouds (ABCs) with lightweight Unmanned Aerial Vehicles (UAVs) and miniaturized instruments. The UAV technology for in-situ measurements, including aerosol concentration, aerosol size distribution, aerosol absorption, cloud drop size distribution, solar radiation fluxes (visible and broadband), and spectral radiative fluxes, is a leading-edge technology for cost-effective atmospheric sounding, which can fill the gap between the ground measurement and satellite observation. The first experimental observation with UAVs in Korea, Cheju ABC Plume Monsoon Experiment (CAPMEX), conducted during summer 2008 revealed that the Beijing plumes exerted a strong positive influence on the net warming and fossil-fuel-dominated black-carbon plumes were approximately 100% more efficient warming agents than biomass-burning-dominated plumes. Long-term sustainable routine UAV measurements will eventually provide truly three-dimensional data of ABCs, which is necessary for the better understanding of their climate impacts and for the improvement of numerical models for air pollution, weather forecast and climate change.

• Journal of The Korean Society of Agricultural Engineers
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• v.50 no.3
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• pp.71-79
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• 2008

Generally the price of agricultural products has much different characteristics from that of manufacturing products. If products have the limitation of long-term storage and the short period of cultivation, the price of products can be more unstable. Moreover, the price forecasting is very difficult because it doesn't follow any cycle or trend. However price can be regarded as risk instead of uncertainty if we can calculate the probability of price. Reliability analysis techniques are used for forecasting the price change of Chinese cabbage. This study aims to show the usability of reliability analysis for price forecasting. A price-forecasting model was developed based on weather data of the first 10 days of the full cultivating cycle (80 days) 70 days and the average price and standard deviation of wholesale market prices from 1996 to 2001 and applied to forecast the boom price, or the orice which is over the tolerance of market prices, of upland Chinese cabbage in 2002 and 2003. Applied results showed the possibility of boom price forecasting using reliability analysis techniques.

• Journal of the Korean Institute of Rural Architecture
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• v.11 no.4
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• pp.51-58
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• 2009

The senior adults which are a central manpower of economic activity of the nation decreased and the elderly sustenance allowance already went over 10%. And the economic activity participation of the woman which are the supporter of the unpaid the elderly within the family is increasing. This big change is expected to support awareness. To respond to these changes, the improvement of social welfare system for elderly with the job of retirement lifestyles of the elderly, a figure that is needed for the ceremony. The elderly medical treatment facility that began in 2008 the elderly long-term medical treatment law enforcement because of the demand is expected to grow. It is forecast with the fact that the data which is fundamental is most important will become that old person medical treatment facility of the middle-aged layer which is a central role of the protector who decides the facility use of the preliminary consumer of the elderly care facility and currently the very the elderly and manhood ceremony and the preference to plan of the elderly welfare facility. The purpose of this study is to present the fundamental data about the elderly care facility for comparative analysis the awareness & perfernces of the elderly care facilities of the senior adults & the elderly.

• Korean Journal of Agricultural Science
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• v.46 no.4
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• pp.843-856
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• 2019

Real-time flood prediction has an important role in significantly reducing potential damage caused by floods for urban residential areas located downstream of river basins. This paper presents an effective approach for flood forecasting based on the construction of a deep neural network (DNN) model. In addition, this research depends closely on the open-source software library, TensorFlow, which was developed by Google for machine and deep learning applications and research. The proposed model was applied to forecast the flowrate one, two, and three days in advance at the Son Tay hydrological station on the Red River, Vietnam. The input data of the model was a series of discharge data observed at five gauge stations on the Red River system, without requiring rainfall data, water levels and topographic characteristics. The research results indicate that the DNN model achieved a high performance for flood forecasting even though only a modest amount of data is required. When forecasting one and two days in advance, the Nash-Sutcliffe Efficiency (NSE) reached 0.993 and 0.938, respectively. The findings of this study suggest that the DNN model can be used to construct a real-time flood warning system on the Red River and for other river basins in Vietnam.