• Journal of Korean Institute of Industrial Engineers
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• v.39 no.1
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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.

• Journal of radiological science and technology
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• v.45 no.1
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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.

• Information Systems Review
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• v.10 no.2
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• pp.269-289
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• 2008

It is very difficult problem to estimate and evaluate the performance of e-government system which scope and size are large and its effectiveness can not be seen shortly but reveals after several years. It is because the previous offline processes can not be transformed to online ones fully and shortly. For such e-transformation cases, the performance evaluation model should be adjusted and modified gradually as time passes. This paper propose new EEM(E-transformation Evaluation Model) model and methodology to evaluate G2B system that is one of large e-government project. EEM model can derive monetary value of e-transformatized business process areas(online areas). It also estimate the expected effect of offline area that is not yet transformed to online. EEM model consists of standard model, verification model and estimation model with some variables such as evaluation year, evaluation area and data type. By using survey data and database data together it can validate the correctness of the model and derive the effect of the system introduction. This paper also propose EEM evaluation methodology consisting of 5 stages and 10 sub processes to evaluate online and offline effect efficiently. To show the usefulness of this study, we evaluate the performance of Korea G2B system named KONEPS which is famous as a successful e-government case in the world by using the proposed model and methodology. The proposed model and methodology can be applied to different similar areas including e-government projects and large scale information system introduction in private sectors. This study can be also used for establishing appropriate policies about e-government project and informatization issues.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.2
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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.

• Journal of the Korean Society of Marine Environment & Safety
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• v.5 no.1
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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.

• The Journal of the Korea Contents Association
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• v.17 no.4
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• pp.541-549
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• 2017

This research investigates the quantitative screening methods for the Grant Funding system and seeks for the efficient evaluation of a number of proposals. We search foreign cases of Grand Funding, but we found no appropriate model for using in Korea. Thus, we had to develope our own model for better screening. First, we analyse the existing evaluation system and find some problems and challenges. Second, we suggest a quantitative screening system for Grant Funding with a numeric model, and operates a tedious simulation by using the previous data and our suggested model. Third, we test the suggested model and find the optimal model by using simulation method The number of data analysed for simulation is larger than 200 thousands. Last, we suggest some brief policy implications based on the results in the paper.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.28 no.6
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• pp.579-588
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• 2015

The data model for structural experiment information formally organizes the information involved in the structural experiments before the data repository using the data model is implemented. The data model is particularly required for the data repositories for the large-scale structural experiment information and the general information for various types of experiments, such as the NEEShub Project Warehouse developed by NEES. This paper proposes criteria for evaluating the organization and the use of design model for structural experiment information. The term of AVE(attribute value existence) indicates the ratio of attributes who values exist in objects, and then used for defining the Attribute AVE for the use of an attribute, the Class AVE for a class, the Class Level AVE for a class including its lower-level classes, the Project AVE for a project including all classes at class levels, and the Data Model AVE for a data model including projects. These criteria are applied to the projects in the NEES data model, and it is successively possible to numerically describe the evaluation of the use of classes and attributes in the data model.

• Proceedings of the ESK Conference
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• 1993.04a
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• pp.10-17
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• 1993

An object-oriented database was developed as a framesork for integrating into ergonomic interface models data for workplace modelling and ergonomic evaluation functions as well as basic anthropometric data required to construct a man model. In order to develop an ergonomic man model representing operators that interact with his working evnironments, not only anthro- pometric data but also efficient handling of such data and accurate representation of the work- space are needed as a prerequistite to proper ergonomic evaluation. Most existing man models are not, however, capable of fully utilizing these data due to the lack of a generallized formalism of data handling, which results in system performance degradation or a potential difficulty when the system is upgraded. In this research, these three sets of data with distinct characteristics were incorporated into a comon integrated database required to manipulate an ergonomic interface model fully coupled with the man model itself. An object- oriented scheme was sued for the database design Specifically, UniSQL/X, an object-oriented database management system and the X-window system on SPARC workstation were used for implementation. The ergonomic man model generated from the object-oriented database is found to possess great flexibility and performance compared to existing ergonomic interface models or ergonomic CAD systems.

• Journal of the Korean Society of Safety
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• v.35 no.2
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• pp.100-110
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• 2020

Recently, the frequency of typhoon and torrential rain due to climate change is increasing. In addition, the upsurge in the complexity of urban sewer network and impervious surfaces area aggravates the inland flooding damage. In response to these worsening situations, the central and local governments are conducting R&D tasks related to predict and mitigate the flood risk. Researches on the analysis of inundation in urban areas have been implemented through various ways, and the common features were to evaluate the accuracy and justification of the model by comparing the model results with the actual inundation data. However, the evaluation procesure using available urban flooding data are not consistent, and if there are no quantitative urban inundation data, verification has to be performed by using press releases, public complaints, or photos of inundation occurring through 'CCTV'. Because theses materials are not quantitative, there is a problem of low reliability. Therefore, this study intends to develop a comparative analysis procedure on the quantitative degree and applicability of the verifiable inundation data, and a systematic framework for the performance assessment of urban flood analysis model was proposed. This would contribute to the standardization of the evaluation and verification procedure for urban flooding modelling.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.32 no.12
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• pp.1063-1071
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• 2008

This paper provides a failure pressure evaluation model for local wall-thinned elbows. In this study, parametric finite element analyses are performed on the elbows containing local wall-thinning defect at their intrados and extrados, and the failure pressures are obtained from the analysis results by applying a local failure criterion that was validated by real-scale pipe tests. An evaluation model including the effects of thinning depth, length, circumferential angle, thinning location, and elbow geometries on the failure pressure is derived based on the evaluated failure pressures. The proposed model agrees well with the results of finite element analyses and reasonably estimates the dependence of failure pressure on the wall-thinning dimensions and elbow geometries. Also, the comparison with experimental data demonstrates that the proposed evaluation model can accurately predict the failure pressure of local wall-thinned elbows.