• Journal of Korean Society of Transportation
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• v.30 no.3
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• pp.57-70
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• 2012

Variable speed limit(VSL) is a useful speed management tool for alleviating traffic congestion and enhancing traffic safety. The purpose of this study is to identify promising freeway segments for safety enhancement through VSL operations. An ordered probit model was adopted to capture factors affecting freeway crash severity that can be used to support decision making for selecting the promising segments. Pseudo elasticity and marginal effects, which are outcomes of the ordered probit analysis, were used to determine priority of promising segments for traffic safety. The results of this study would be useful in installing VSL systems and developing traffic control and operations strategies in practice.

• Journal of Korean Society on Water Environment
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• v.29 no.5
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• pp.681-690
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• 2013

Watershed models have been increasingly used to support an integrated management of land and water, non-point source pollutants, and implement total daily maximum load policy. However, these models demand a great amount of input data, process parameters, a proper calibration, and sometimes result in significant uncertainty in the simulation results. For this reason, uncertainty analysis is necessary to minimize the risk in the use of the models for an important decision making. The objectives of this study were to evaluate three different uncertainty analysis algorithms (SUFI-2: Sequential Uncertainty Fitting-Ver.2, GLUE: Generalized Likelihood Uncertainty Estimation, ParaSol: Parameter Solution) that used to analyze the sensitivity of the SWAT(Soil and Water Assessment Tool) parameters and auto-calibration in a watershed, evaluate the uncertainties on the simulations of runoff and sediment load, and suggest alternatives to reduce the uncertainty. The results confirmed that the parameters which are most sensitive to runoff and sediment simulations were consistent in three algorithms although the order of importance is slightly different. In addition, there was no significant difference in the performance of auto-calibration results for runoff simulations. On the other hand, sediment calibration results showed less modeling efficiency compared to runoff simulations, which is probably due to the lack of measurement data. It is obvious that the parameter uncertainty in the sediment simulation is much grater than that in the runoff simulation. To decrease the uncertainty of SWAT simulations, it is recommended to estimate feasible ranges of model parameters, and obtain sufficient and reliable measurement data for the study site.

• Journal of Korean Society of Rural Planning
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• v.13 no.1 s.34
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• pp.73-84
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• 2007

The first theme of this study is to preserve and manage rural multi-functionality resource Information. This study is to suggest the method that can irradiate rural multi-functionality resource Information efficiently and constructively. GIS uses PDA and Tablet PC as an investigation tool and verifies the outcome of the development in the investigation system. This study enhanced the mobility function of PDA by installing recording system and camera to the PDA. Also, Using GPS has been ensured scientific precision and realism to the investigation. Direct input on spot can save time, cost and minimize human error by simplifying the investigation process. Database is composed of characters like scale, form, location, distance, resident's opinion and image of 37 resources. The survey system was applied in 170 villages and got a total of 12,270 resources data. Management system should be easy to input and output the surveyed information and to get reports in any kind of form ( i.e. final result can be produced as a map). By utilizing of the Rural Resource information system, the study made a simulation to compare the target areas before and after. Also, digitalized investigation system, minimized re-input and reprocessing of data and enabled to simplify and standardize the process than memorandum investigation. Data collected through digital system could offer people useful information by Web-GIS. It was need to specify practical way in decision-making and a way to measure the value of resources to align with the regional plan. Also, need to keep on developing statistical data and application program that can connect us to present the best solution to support regional planning. Therefore, quality of data is very important. Finally, it is very important to develop various programs to analyze space md rural resource by monitoring rural environment.

• The Journal of the Korea Contents Association
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• v.11 no.5
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• pp.104-116
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• 2011

A recommender system is a personalized decision support tool to suggest suitable products in proper manners for the benefits of both suppliers and consumers, with the assumption of full understating of consumers' needs and preferences. However, a substantial number of studies have focused on making recommender systems more accurate and efficient. Whereas, there have been a few studies on consumers' needs and preferences under their own contexts to accept recommender systems. To this end, this study attempted to find out the impact of personal sentiments and contexts on the willingness to accept music recommender systems based on the simplified "Technology Acceptance Model" and some verified variables from the precedent studies. For the study, we conducted an empirical study using surveys and High-Order Structural Equation Model (SEM). The outcomes of the research was affirmative to the research hypothesis that the personal sentiments and contexts positively affect the acceptance of the music recommender systems.

• Korean Institute of Interior Design Journal
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• v.24 no.5
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• pp.117-127
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• 2015

This paper depicts a case study of the BIM (Building Information Modeling)-enabled evaluation of design alternatives for an actual remodeling project in Yeongwol, Korea. The increase of urban population and income followed by the growth of economy has derived massive supply of grand scale housing project in Korea since 1970s. Consequently, building remodeling became one of the feasible resolutions for renovating such old housings in these days. This paper aims to introduce a technical approach to such remodeling projects based on BIM-enabled applications focusing on quantitative analysis of design alternatives. Among the technical issues of such building remodeling projects, this paper focuses on the BIM-enabled area analysis and comparison between design alternatives to support decision-making even in early phase of remodeling design process. BIM and its variety of applications have broadly influenced the domain of AEC-FM (Architecture, Engineering, Construction, and Facility Management) within the lifecycle of buildings. As one of the applications facilitated by BIM, the automated area calculation and scenario-based comparison between alternatives can play an important role in the early phase of remodeling project. We modeled three design alternatives (buildings) and three housing modules (units) based on the actual case in Yeongwol city, Korea using a BIM design authoring tool. Nine combinatorial BIM models were demonstrated for the BIM-enabled review process described in this paper. To determine the most optimal design scenario among nine alternatives, this paper demonstrates a result of the conducted spatial program review. The main subject includes specific spatial program issues on; 1) the number of unit spaces; and 2) area of individual/grouped and private/shared spaces.

• Journal of Soil and Groundwater Environment
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• v.27 no.spc
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• pp.64-74
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• 2022

The conceptual site model (CSM) is used as a key tool to support decision making in risk based management of contaminated sites. In this work, CSM was applied in Jeonju Industrial Complex where site investigation for groundwater contamination was conducted. Site background information including facility types, physical conditions, contaminants spill history, receptor exposure, and ecological information were collected and cross-checked with tabulated checklist necessary for CSM application. The CSM for contaminants migration utilized DNAPL transport model and narrative CSMs were constructed for source to receptor pathway, ecological exposure route, and contaminants fate and transport in the form of a diagram or flowchart. The component and uncertainty of preliminary CSM were reviewed using the data gap analysis while taking into account the purpose of the survey and the site management stage at the time of the survey. Through this approach, the potential utility of CSM was demonstrated in the site management process, such as assessing site conditions and planning follow-up survey work.

• Land and Housing Review
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• v.13 no.2
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• pp.125-139
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• 2022

For construction companies to become competitive innovative, cost management as well as process improvement are required. Activity-based costing (ABC), which uses cost information to support long-term decision-making, is a tool that enhances a company's competitiveness. In this study, we compare and analyze tradition-based costing (TBC) and ABC to confirm the adequacy of performance-based costing. In addition, we will empirically examine the relationship between the impact of the reward system using ABC on employee satisfaction and involvement. In research results, the influence of the reward system on employee involvement appeared in the order of intrinsic reward (𝛽 = 0.338) and extrinsic reward (𝛽 = 0.308). In addition, the reward system showed positive (+) effects on employee satisfaction, with influence appearing in the order of intrinsic reward (𝛽 = 0.360) and extrinsic reward (𝛽 = 0.337). And employee satisfaction (𝛽 = 0.225) had a positive effect on involvement. We were able to confirm that it is necessary to build a reward system consisting of intrinsic and extrinsic rewards to increase employee satisfaction and involvement.

• Informatization Policy
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• v.29 no.3
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• pp.61-81
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• 2022

This paper explores how the provided information from Enterprise Architecture (EA) affects the activities to for performing IT projects. The IT projects analyzed in this paper are projects to for developing and maintaining Korea Customs' UNI-PASS. This research was conducted based on surveys to demonstrate the effects of the information from EA on activities for IT projects. Information from EA is categorized into propriety, sufficiency and consistency. Activities for IT projects are defined as management, participation, communication, requirement management and human resource. Correlational analysis is used to measure the effects of the inf ormation on the defined activities. The analysis, which verifies the provided information by EA, does not have meaningful correlation with project management nor human resource. For public officials in charge, Sufficiency of the information produces a positive effect on decision making. For operation company, consistency of the information encourages utilization of the resources required for the project. This research suggests that strategies for performing IT projects with EA information that can support the verification of characteristic environments of each project and performance of vital activities required by the participants' roles will ensure the success of government IT projects.

• Nuclear Engineering and Technology
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• v.55 no.9
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• pp.3423-3440
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• 2023

In this work, a multivariate time-series machine learning meta-model is developed to predict the transient response of a typical nuclear power plant (NPP) undergoing a steam generator tube rupture (SGTR). The model employs Recurrent Neural Networks (RNNs), including the Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and a hybrid CNN-LSTM model. To address the uncertainty inherent in such predictions, a Bayesian Neural Network (BNN) was implemented. The models were trained using a database generated by the Best Estimate Plus Uncertainty (BEPU) methodology; coupling the thermal hydraulics code, RELAP5/SCDAP/MOD3.4 to the statistical tool, DAKOTA, to predict the variation in system response under various operational and phenomenological uncertainties. The RNN models successfully captures the underlying characteristics of the data with reasonable accuracy, and the BNN-LSTM approach offers an additional layer of insight into the level of uncertainty associated with the predictions. The results demonstrate that LSTM outperforms GRU, while the hybrid CNN-LSTM model is computationally the most efficient. This study aims to gain a better understanding of the capabilities and limitations of machine learning models in the context of nuclear safety. By expanding the application of ML models to more severe accident scenarios, where operators are under extreme stress and prone to errors, ML models can provide valuable support and act as expert systems to assist in decision-making while minimizing the chances of human error.

• Earthquakes and Structures
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• v.22 no.5
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• pp.503-515
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• 2022

This paper presents the development of seismic fragility curves for a precast reinforced concrete bridge instrumented with a structural health monitoring (SHM) system. The bridge is located near an active seismic fault in the Dominican Republic (DR) and provides the only access to several local communities in the aftermath of a potential damaging earthquake; moreover, the sample bridge was designed with outdated building codes and uses structural detailing not adequate for structures in seismic regions. The bridge was instrumented with an SHM system to extract information about its state of structural integrity and estimate its seismic performance. The data obtained from the SHM system is integrated with structural models to develop a set of fragility curves to be used as a quantitative measure of the expected damage; the fragility curves provide an estimate of the probability that the structure will exceed different damage limit states as a function of an earthquake intensity measure. To obtain the fragility curves a digital twin of the bridge is developed combining a computational finite element model and the information extracted from the SHM system. The digital twin is used as a response prediction tool that minimizes modeling uncertainty, significantly improving the predicting capability of the model and the accuracy of the fragility curves. The digital twin was used to perform a nonlinear incremental dynamic analysis (IDA) with selected ground motions that are consistent with the seismic fault and site characteristics. The fragility curves show that for the maximum expected acceleration (with a 2% probability of exceedance in 50 years) the structure has a 62% probability of undergoing extensive damage. This is the first study presenting fragility curves for civil infrastructure in the DR and the proposed methodology can be extended to other structures to support disaster mitigation and post-disaster decision-making strategies.