• 한국데이타베이스학회:학술대회논문집
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• 한국데이타베이스학회 2008년도 연합학회학술대회
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• pp.379-388
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• 2008

초기 사업자들에 의해 일방적으로 정보가 제공되던 인터넷 GIS 사이트는 Web 2.0의 패러다임과 함께 사용자들에 의해서 정보가 생산되고, 평가되는 형태로 변화하였다. 기존의 일반적인 웹사이트의 평가모델과 GIS 사이트 평가 모델에 대해서 살펴보고, Web 2.0을 고려하여 보완된 GIS 사이트 평가모델의 기준점을 을 제시하고자 한다. 본 연구를 통해 제안된 평가 모델의 기준점은 사용자 참여 정도를 고려한 평가 기준점으로써 이를 발전시켜 GIS 2.0 에 대한 평가모델을 제안할 수 있을 것이다.

• 동력기계공학회지
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• 제4권3호
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• pp.72-80
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• 2000

In order to design a stable robust controller, nominal model, and the upper bound about the uncertainty which is the error of the model are needed. The problem to estimate the nominal model of controlled system and the upper bound of uncertainty at the same time is called robust identification. When the nominal model of controlled system and the upper bound of uncertainty in relation to robust identification are given, the evaluation of the validity of the model and the upper bound makes it possible to distinguish whether there is a model which explains observation data including disturbance among the model set. This paper suggests a method to identity the uncertainty which removes disturbance and expounds observation data by giving a probable postulation and plural data set to disturbance. It also examines the suggested method through a numerical computation simulation and validates its effectiveness.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 D
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• pp.2690-2692
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• 2000

In order to design a stable robust controller, nominal model, and the upper bound about the uncertainty which is the error of the model are needed. The problem to estimate the nominal model of controlled system and the upper bound of uncertainty at the same time is called robust identifcation. When the nominal model of controlled system and the upper bound of uncertainty in relation to robust identifcation are given, the evaluation of the validity of the model and the upper bound makes it possible to distinguish whether there is a model which explains observation data including disturbance among the model set. This paper suggests a method to identify the uncertainty which removes disturbance and expounds observation data by giving a probable postulation and plural data set to disturbance. It also examines the suggested method through a numerical computation simulation and validates its effectiveness.

• 대한산업공학회지
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• 제39권1호
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• pp.1-9
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• 2013

The current manufacturers have generated tremendous amount of digitized product data to efficiently share and exchange it with other stakeholders or various software systems for product development. The digitized product data is a valuable asset for manufacturers, and has a potential to support high level strategic decision makings needed at many stages in product development. However, the lack of studies on extraction of key performance indicators(KPIs) from product data management(PDM) databases has prohibited manufacturers to use the product data to support the decision makings. Therefore this paper examines a possibility of an architecture that supports KPIs for evaluation of product development performances, by applying multidimensional product data model and on-line analytic processing(OLAP) to operational databases of product data management. To validate the architecture, the paper provides a prototype product data management system and OLAP applications that implement the multidimensional product data model and analytic processing.

• 대한방사선기술학회지:방사선기술과학
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• 제45권1호
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• pp.41-47
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• 2022

The purpose of this study is to apply a deep learning model that can distinguish lung perfusion and lung ventilation images in nuclear medicine, and to evaluate the image classification ability. Image data pre-processing was performed in the following order: image matrix size adjustment, min-max normalization, image center position adjustment, train/validation/test data set classification, and data augmentation. The convolutional neural network(CNN) structures of VGG-16, ResNet-18, Inception-ResNet-v2, and SE-ResNeXt-101 were used. For classification model evaluation, performance evaluation index of classification model, class activation map(CAM), and statistical image evaluation method were applied. As for the performance evaluation index of the classification model, SE-ResNeXt-101 and Inception-ResNet-v2 showed the highest performance with the same results. As a result of CAM, cardiac and right lung regions were highly activated in lung perfusion, and upper lung and neck regions were highly activated in lung ventilation. Statistical image evaluation showed a meaningful difference between SE-ResNeXt-101 and Inception-ResNet-v2. As a result of the study, the applicability of the CNN model for lung scintigraphy classification was confirmed. In the future, it is expected that it will be used as basic data for research on new artificial intelligence models and will help stable image management in clinical practice.

• 경영정보학연구
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• 제10권2호
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• pp.269-289
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• 2008

전자정부 정보화 사업과 같은 규모와 그 범위가 거대하며, 한번에 모든 기존의 오프라인 프로세스가 온라인화 되지 않고 수년간에 걸쳐 그 효과가 나타나는 시스템의 파급효과에 대한 예측은 무척 난해한 문제이다. 이러한 e-transformation이 이루어지는 경우에는 지속적으로 모델의 수정 및 보완작업이 함께 이루어져야 한다. 이에 본 연구에서는 전자정부 정보화사업 중 하나인 G2B 시스템의 효과평가를 위해 EEM (E-transformation Evaluation Model)으로 명명한 새로운 모델과 평가방법론을 제시하고자한다. EEM 모델은 G2B 시스템으로 인해 e-transformation화된 업무프로세스 영역(온라인 영역)의 효과를 화폐가치로 산출하는 정량평가 모델이다. 또한 아직 G2B 시스템이 적응되지 않은 업무프로세스 영역(오프라인 영역)을 정보화시켰을 때 예상되는 효과를 함께 추정할 수 있도록 해준다. EEM 모델에서는 기준모델, 검증모델, 예측모델을 설정하고, 평가년도, 측정영역, 데이터종류에 따라 설문데이터와 DB 데이터를 함께 활용하여 모델을 검증하며 효과를 예측한다. 본 연구에서는 온라인과 오프라인 효과를 효과적으로 평가하기 위해 5단계와 10개의 세부절차로 구성된 EEM평가방법론을 제시하였다. 또한 제시된 방법론을 활용하여 대한민국 전자조달 G2B 시스템에 대해서 평가분석을 실시하였다. 본 연구에서 제시된 EEM 모델과 평가방볍론은 평가대상에 따라 다각적인 적응이 가능하므로 향후 전자정부 정보화사업의 효과평가와 정책수립에 도움이 될 것으로 기대된다. 뿐만 아니라 민간기업의 대형시스템 도입 효과평가에도 도움이 될 것으로 사료된다.

• 한국측량학회지
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• 제38권2호
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• pp.153-163
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• 2020

After launching the GOCE (Gravity Field and Steady-State Ocean Circulation Explorer) which obtains high-frequency gravity signal using a gravity gradiometer, many research institutes are concentrating on the development of GGM (Global Geopotential Model) based on GOCE data and evaluating its precision. The precision of some GGMs was also evaluated in Korea. However, some studies dealt with GGMs constructed based on initial GOCE data or others applied a part of GNSS (Global Navigation Satellite System) / Leveling data on UCPs (Unified Control Points) for the precision evaluation. Now, GGMs which have a higher degree than EGM2008 (Earth Gravitational Model 2008) are available and UCPs were fully established at the end of 2019. Thus, EIGEN-6C4 (European Improved Gravity Field of the Earth by New techniques - 6C4), GECO (GOCE and EGM2008 Combined model), XGM2016 (Experimental Gravity Field Model 2016), SGG-UGM-1, XGM2019e_2159 were collected with EGM2008, and their precisions were assessed based on the GNSS/Leveling data on UCPs. Among GGMs, it was found that XGM2019e_2159 showed the minimum difference compared to a total of 5,313 points of GNSS/Leveling data. It is about a 1.5cm and 0.6cm level of improvement compare to EGM2008 and EIGEN-6C4. Especially, the local biases in the northern part of Gyeonggi-do, Jeju island shown in the EGM2008 was removed, so that both mean and standard deviation of the difference of XGM2019e_2159 to the GNSS/Leveling are homogeneous regardless of region (mountainous or plain area). NGA (National Geospatial-Intelligence Agency) is currently in progress in developing EGM2020 and XGM2019e_2159 is the experimentally published model of EGM2020. Therefore, it is expected that the improved GGM will be available shortly so that it is necessary to verify the precision of new GGMs consistently.

• 해양환경안전학회지
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• 제5권1호
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• pp.9-18
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• 1999

To predict the oil spill dispersion phenomena in the ocean, the oil spill response model, which can be used for strategic purpose on the oil spill site, based on Lagrangian particle-tracking method was formulated and applied to the neighboring area with Pusan port where the oil spill incident occurred when the tanker ship No.1 Youil struck on a small rock near the Namhyungjeto on September 21, 1995. The real-time tidal currents to be required as input data of the oil spill model were obtained by the two-dimensional hydrodynamic model and the tide prediction model. Evaluation of tidal currents using observation data was successful. For wind data, other input data of oil spill model, observed data on the spot were used. To verify the oil spill model, the oil spill modelling results were compared with the field data obtained from the spill site. Compared the modelling results with the observation data, there exist some discrepancies but the general pattern of modelling results was similar to that of field observation. The modelling results on 7 days after spill occurred showed that the 40% of spilled oil is in floating, 36% in evaporated, 23% at shore, and 1% in out of boundary, respectively. According to the evaluation of weighting curves of effective components to the dispersion of oil, the winds make a 37% of contribution to the dispersion of oil, turbulent diffusion 39.5%, and tidal currents 23.5%, respectively. Provided the more accurate wind data are supported, more favorable results might be obtained.

• 한국콘텐츠학회논문지
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• 제17권4호
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• pp.541-549
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• 2017

본 연구에서는 정액연구 지원방식에 대한 정량평가 방법을 연구하고, 효율적인 평가방법을 확립하기 위한 모델을 만들었다. 첫째, 기존의 평가 시스템을 분석하여 몇 가지 문제점과 과제를 발견했다. 둘째, 정액연구 지원방식에 대한 정량평가 방법을 제안하고, 20만개 이상의 데이터와 모델을 이용하여 시뮬레이션하였다. 셋째, 제안된 모델을 시험하여 최적의 모델을 찾았다. 그리고 이러한 결과에 따라 몇 가지 정책적 시사점을 제시하였다.

• 한국전산구조공학회논문집
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• 제28권6호
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• pp.579-588
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• 2015

구조실험을 위한 데이터 모델은 구조실험에 관련된 실험정보를 정형화하여 표현하므로 데이터 저장소를 개발하는데 이용할 수 있다. 데이터 모델은 특히 대규모의 구조실험정보 또는 일반적인 다양한 실험정보를 위한 데이터 저장소에 효과적인데 예를 들면 NEES에서 개발한 NEEShub Project Warehouse가 있다. 본 논문은 데이터 모델의 구성과 사용을 평가하기 위한 평가요소를 제안하고 있다. 클래스의 속성이 값을 갖는지를 의미하는 AVE(attribute value existence)란 용어를 도입하여 속성의 사용성에 대한 Attribute AVE, 클래스의 사용성에 대한 Class AVE, 하위레벨에 있는 클래스를 포함하는 Class Level AVE, 하나의 프로젝트의 모든 클래스를 포함하는 Project AVE, 모든 프로젝트를 포함하는 데이터 모델에 대한 Data Model AVE를 정의하였다. 이러한 평가요소들을 NEES 데이터 모델의 프로젝트들에 적용하였는데 데이터 모델내의 클래스와 객체에 대한 사용성을 수치적으로 기술하여 평가하는 것이 가능하였다.