• Environmental Sciences Bulletin of The Korean Environmental Sciences Society
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• 제4권1호
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• pp.11-23
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• 2000

Photochemical air quality models are essential tools in predicting future air quality and assessing air pollution control strategies. To evaluate air quality using a photochemical air quality model, emission inventories are important inputs to these models. Since most emission inventories are provided at a county-level, these emission inventories need to be geographically allocated to the computational grid cells of the model prior to running the model. The conventional method for the spatial allocation of these emissions uses "spatial surrogate indicators", such as population for mobile source emissions and county area for biogenic source emissions. In order to examine the applicability of such approximations, more detailed spatial surrogate indicators were developed using Geographic Information System(GIS) tools to improve the spatial allocation of mobile and boigenic source emissions, The proposed spatial surrogate indicators appear to be more appropriate than conventional spatial surrogate indicators in allocating mobile and biogenic source emissions. However, they did not provide a substantial improvement in predicting ground-level ozone(O3) concentrations. As for the carbon monoxide(CO) concentration predictions, certain differences between the conventional and new spatial allocation methods were found, yet a detailed model performance evaluation was prevented due to a lack of sufficient observed data. The use of the developed spatial surrogate indicators led to higher O3 and CO concentration estimates in the biogenic source emission allocation than in the mobile source emission allocation.llocation.

• Environmental Sciences Bulletin of The Korean Environmental Sciences Society
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• 제3권3호
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• pp.151-158
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• 1999

Biogenic source emissions refer to naturally occuring emissions from vegetation, microbial activities in soil, lightening, and so on. Vegetation is especially known to emit a considerable amout of volatile organic compounds into the atmosphere. Therefore, biogenic source emissions are an important input to photochemical air quality models. since most biogenic source emissions are calculated at the county-level, they should be geographically allocated to the computational grid cells of a photochemical air quality model prior to running the model. The traditional method for the spatial allocation for biogenic source emissions has been to use a "spatial surrogate indicator" such as a county area. In order to examine the applicability of such approximations, this study developed more detailed surrogate indicators to improve the spatial allocation method for biogenic source emissions. Due to the spatially variable nature of biogenic source emissions, Geographic Information Systems(GIS) were introduced as new tools to develop more detailed spatial surrogate indicators. Use of these newly developed spatial surrogate indicators for biogenic source emission allocation provides a better resolution than the standard spatial surrogate indicator.indicator.

• Environmental Sciences Bulletin of The Korean Environmental Sciences Society
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• 제3권3호
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• pp.143-150
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• 1999

Mobile source emissions are important inputs to photochemical air quality models. Since most mobile source emissions are calculated at the county-level, these emission should be geographically allocated to the computational grid cells of a photochemical air quality model prior to running the model. The traditional method for the spatial allocation of these emissions has been to use a "spatial surrogate indicator" such as population, since grid-specific emission calculations are very labor-intensive and expensive, plus the necessary data are often not available for such grid resolutions. Accordingly, new spatial surrogate indicators for mobile source emissions(specifically for highway emissions) were developed using Geographic Information Systems(GIS) tools due to the spatially variable nature of mobile source emissions. These newly developed spatial surrogate indicators appear to be more appropriate for the allocation of highway emissions than the population surrogate indicator. It was also revealed that the conventional spatial allocation method underestimates the maximum levels of air pollutant emmissions.mmissions.

• 한국정보과학회논문지:데이타베이스
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• 제30권4호
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• pp.397-407
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• 2003

이동 클라이언트를 이용한 공간 데이타의 변경 트랜잭션은 서버와 통신을 단절한 상태에서 사용자와의 상호 연산을 통하여 수정하는 긴 트랜잭션이다. 따라서 트랜잭션의 동시성 제어를 위해 잠금을 이용한 비관적 기법을 사용하면 이동 클라이언트가 잠금을 획득하기 위해 오랜 시간동안 대기해야 하므로 일반적으로 검증 작업을 이용한 낙관적 기법이 적합하다. 본 논문에서는 이동 클라이언트를 이용해 공간 데이타를 변경하는데 적합한 S-S-M(서버-대리 PC-이동 클라이언트) 구조를 위한 대리 트랜잭션 모델을 제안하고 모델에 따른 관리자클 구현한다. 서버와 이동 클라이언트가 대리 PC를 통해 통신하는 이 구조에서 대리 트랜잭션의 동시성 제어를 위해 공간 객체간의 위상 관계인 공간 관련성을 고려하며 기존의 검증 조건을 확장한다. 또한, 충돌이 발생한 트랜잭션의 완료 비용을 최소화하기 위해 대리 PC에서 충돌이 발생한 객체에 대하여 조정 작업을 수행하며 이를 지원하기 위한 확장된 완료 프로토콜을 제시한다.

• International Journal of Fluid Machinery and Systems
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• 제10권3호
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• pp.240-253
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• 2017

Latin hypercube sampling is widely used design-of-experiment technique to select design points for simulation which are then used to construct a surrogate model. The exploration/exploitation properties of surrogate models depend on the size and distribution of design points in the chosen design space. The present study aimed at evaluating the performance characteristics of various surrogate models depending on the Latin hypercube sampling (LHS) procedure (sample size and spatial distribution) for a diverse set of optimization problems. The analysis was carried out for two types of problems: (1) thermal-fluid design problems (optimizations of convergent-divergent micromixer coupled with pulsatile flow and boot-shaped ribs), and (2) analytical test functions (six-hump camel back, Branin-Hoo, Hartman 3, and Hartman 6 functions). The three surrogate models, namely, response surface approximation, Kriging, and radial basis neural networks were tested. The important findings are illustrated using Box-plots. The surrogate models were analyzed in terms of global exploration (accuracy over the domain space) and local exploitation (ease of finding the global optimum point). Radial basis neural networks showed the best overall performance in global exploration characteristics as well as tendency to find the approximate optimal solution for the majority of tested problems. To build a surrogate model, it is recommended to use an initial sample size equal to 15 times the number of design variables. The study will provide useful guidelines on the effect of initial sample size and distribution on surrogate construction and subsequent optimization using LHS sampling plan.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2001년도 가을 학술발표논문집 Vol.28 No.2 (1)
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• pp.208-210
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• 2001

S-S-M(Server-Surrogate PC-Mobile Client)과 같은 3-계층 구조에서 이동 클라이언트를 이용한 공간 데이터 변경을 위해 대리트랜잭션 모델이 소개되었다. 이 모델에서는 이동 클라이언트의 공간 데이터변경을 위한 트랜잭션간의 동시성 제어를 위하여 전통적인 낙관적 병행 기법인 확인 기법을 확장하였다. 분산 환경에서는 참여자가 완료를 요청하면 조정자는 데이터를 공유하는 모든 참여자에게 완료 또는 취소 여부를 물어 최종 완료를 수행하였으나S-S-M 환경에서는 이동 클라이언트가 서버와의 접속을 해제하고 데이터를 변경한다. 따라서, 본 논문은 이동 클라이언트의 변경 완료 요청을 대리 PC를 통해 서버로 전달하고, 서버는 해당 트랜잭션의 충돌 여부를 검증하여 완료 또는 취소하는 완료 규약을 제시하고 이를 검증하기 위해 설계 및 구현한다.

• 한국수자원학회논문집
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• 제54권3호
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• pp.167-179
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• 2021

하천 합류부는 두 하천이 만나 형성되는 지역으로 합류부 구간의 혼합 매커니즘을 이해하기 위해서는 지류의 다양한 유입조건에 따른 본류와의 수체혼합의 공간적인 패턴을 분석하는 것이 중요하다. 그러나, 대부분의 합류부 연구들은 실측을 통한 현장데이터를 획득하기 어렵기 때문에 수리 및 수질 수치모형을 통한 연구가 주로 수행되어 왔다. 본 연구에서는 지류와 본류의 합류의 혼합 현상을 규명하는 인자로 유속과 수심 등 기본적인 수리학적 인자들 외에 최근 하천 유사측정을 위해 부유사농도의 지표로 연구되고 있는 ADCP의 초음파산란도를 활용하여 합류부에서 상이한 유사특성을 가진 두 수체가 혼합되는 양상을 측정하여 합류부의 혼합 특성을 해석하고자 하였다. 초음파산란도는 부유사와 관련되는 인자로 SonTek ADCP 이동식으로 측정된 초음파산란도(SNR)자료를 빔퍼짐에 대한 보정, 물에 의한 흡수를 고려하여 보정한 후 3차원 혼합거동의 공간적인 분포를 도출하였다. 그리고 측정기간 중 드론(UAV), LISST를 이용하여 합류부의 혼합양상을 모니터링하여 초음파산란도를 이용한 분석결과와 비교하였다. 분석결과, ADCP로부터 제공되는 초음파산란도를 보정한 결과 합류부의 3차원적인 유사 혼합의 공간적 특성을 규명하는 데 적합한 인자라고 할 수 있었고, 상이한 본류와 지류의 유입을 고려하였을 때 다양한 혼합 거동을 분석하는데 지표로 사용이 가능함을 확인할 수 있었다. 따라서 본 연구에서는 남강과 낙동강의 합류부에 대해 초음파산란도를 활용하여 합류부의 혼합 특성을 분석하였다.

• 한국환경과학회지
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• 제20권1호
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• pp.107-118
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• 2011

While the assessment of mean flow field is very important to characterize the hydrodynamic aspect of the flow regime in river, the conventional methodologies have required very time-consuming efforts and cost to obtain the mean flow field. The paper provides an efficient technique to quickly assess mean flow field by developing and applying spatial averaging method utilizing repeatedly surveyed acoustic Doppler current profiler(ADCP)'s cross-sectional measurements. ADCP has been widely used in measuring the detailed velocity and discharge in the last two decades. In order to validate the proposed spatial averaging method, the averaged velocity filed using the spatial averaging was compared with the bench-mark data computed by the time-averaging of the consistent fix-point ADCP measurement, which has been known as a valid but a bit inefficient way to obtain mean velocity field. The comparison showed a good agreement between two methods, which indicates that the spatial averaging method is able to be used as a surrogate way to assess the mean flow field. Bed shear stress distribution, which is a derived hydrodynamic quantity from the mean velocity field, was additionally computed by using both spatial and time-averaging methods, and they were compared each other so as to validate the spatial averaging method. This comparison also gave a good agreement. Therefore, such comparisons proved the validity of the spatial averaging to quickly assess mean flow field. The mean velocity field and its derived riverine quantities can be actively used for characterizing the flow dynamics as well as potentially applicable for validating numerical simulations.

• 대한원격탐사학회지
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• 제37권1호
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• pp.169-176
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• 2021

The Global Space-based Inter-Calibration System (GSICS) is an international partnership sponsored by World Meteorological Organization (WMO) to continue and improve climate monitoring and to ensure consistent accuracy between observation data from meteorological satellites operating around the world. The objective for GSICS is to inter-calibration from pairs of satellites observations, which includes direct comparison of collocated Geostationary Earth Orbit (GEO)-Low Earth Orbit (LEO) observations. One of the GSICS inter-calibration methods, the Ray-matching technique, is a surrogate approach that uses matched, co-angled and co-located pixels to transfer the calibration from a well calibrated satellite sensor to another sensor. In Korea, the first GEO satellite, Communication Ocean and Meteorological Satellite (COMS), is used to participate in the GSICS program. The National Meteorological Satellite Center (NMSC), which operated COMS/MI, calculated the Radiative Transfer Model (RTM)-based GSICS coefficient coefficients. The L1P reproduced through GSICS correction coefficient showed lower RMSE and Bias than L1B without GSICS correction coefficient applied. The calculation cycles of the GSICS correction coefficients for COMS/MI visible channel are provided annual and diurnal (2, 5, 10, 14-day), but long-term evaluation according to these cycles was not performed. The purpose of this paper is to perform evaluation depending on the annual/diurnal cycles of COMS/MI GSICS correction coefficients based on the ray-matching technique using Suomi-NPP/Visible Infrared Imaging Radiometer Suite (VIIRS) data as reference data. As a result of evaluation, the diurnal cycle had a higher coincidence rate with the reference data than the annual cycle, and the 14-day diurnal cycle was the most suitable for use as the GSICS correction coefficient.

• Journal of Biosystems Engineering
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• 제31권1호
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• pp.24-32
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• 2006

Compaction is becoming a greater concern in crop production and the environment because it can have deleterious effects on growing conditions that are difficult to remediate. Because compaction can vary considerably from point to point within a field, and also from depth to depth within the soil profile, it is important to consider quantification and management of the spatial and vertical variability in soil compaction when developing an overall site-specific crop management plan. In this paper, the importance of soil compaction, techniques for quantification of its variability, and the concept of site-specific tillage are examined. Methods and systems to detect within-field variation in soil strength as a surrogate measure of soil compaction and related soil properties are also compared and discussed. Quantification of variability in soil compaction and site-specific compaction management was motivated recently, and sensors and control systems are still under development. Future study will need to address a number of issues related to understanding and applying the sensor measurements.