• The Journal of Information Technology and Database
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• v.8 no.2
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• pp.137-159
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• 2001

This study provides a thorough methodology for IT Investment evaluation. A software tool to support the evaluation process was introduced along with a case study. The software supports the methodology that consists of 7 phases : Target analysis, ldentifying IT measures, Measuring IT impact, Assessing business value, Analyzing the decree of realization, Cost-benefit analysis, and Reporting. The case study showed that the software (CAFA) was a very useful tool supporting both decision-making and post-implementation reviews of IT investment.

• Environmental Engineering Research
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• v.14 no.2
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• pp.111-119
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• 2009

A prototype GIS-based decision support system (DSS) was developed by using a database management system (DBMS), a model management system (MMS), a knowledge-based system (KBS), a graphical user interface (GUI), and a geographical information system (GIS). The method of selecting a dispersion model or a modeling scheme, originally devised by Park and Seok, was developed using our GIS-based DSS. The performances of candidate models or modeling schemes were evaluated by using a single index(statistical score) derived by applying fuzzy inference to statistical measures between the measured and predicted concentrations. The fumigation dispersion model performed better than the models such as industrial source complex short term model(ISCST) and atmospheric dispersion model system(ADMS) for the prediction of the ground level $SO_2$ (1 hr) concentration in a coastal area. However, its coincidence level between actual and calculated values was poor. The neural network models were found to improve the accuracy of predicted ground level $SO_2$ concentration significantly, compared to the fumigation models. The GIS-based DSS may serve as a useful tool for selecting the best prediction model, even for complex terrains.

• Spatial Information Research
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• v.15 no.3
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• pp.311-322
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• 2007

Geovisual analytics is the new research area that looks fur the way to enable a truly synergetic work of human and visualization tool in analyzing spatio-temporal data. The research challenge for geovisual analytics is developing new geovisualization tools and enhancing human capabilities to analyse, envision, and reason a lot of spatio-temporal changes. With this research area, geovisual analytics is expected to be a new methodology for developing spatial decision support tools. This research is to integrate T scatter plot with computational method to classify the several patterns of the regional fright generation in Korea. The result of this work shows the capabilities provided by geovisual analytics to support spatial decision making.

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.37-53
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• 2023

The AI based intelligent command and control system can automatically analyzes the properties of intricate battlefield information and tactical data. In addition, commanders can receive situation analysis results and battlefield awareness through the system to support decision-making. It is necessary to build a battlefield situation analysis dataset similar to the actual battlefield situation for learning AI in order to provide decision-making support to commanders. In this paper, we explain the next step of the dataset construction method of the existing previous research, 'A Virtual Battlefield Situation Dataset Generation for Battlefield Analysis based on Artificial Intelligence'. We proposed a method to build the dataset required for the final battlefield situation analysis results to support the commander's decision-making and recognize the future battlefield. We developed 'Dataset Generator SW', a software tool to build a learning dataset for battlefield situation analysis, and used the SW tool to perform data labeling. The constructed dataset was input into the Siamese Network model. Then, the output results were inferred to verify the dataset construction method using a post-processing ranking algorithm.

• Korea Journal of Hospital Management
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• v.21 no.4
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• pp.1-12
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• 2016

The purpose of this study are suggest to performance measurement model of Electronic Medical Record(EMR) and Key Performance Index(KPI). For data collection, 665 questionnaires were distributed to medical record administrators and insurance reviewers at 31 hospitals, and 580 questionnaires were collected(collection rate: 87.2%). Regarding methodology, Critical Success Factor(CSF) and index of the information system were derived based on previous studies, and these were set as performance measurement factors of EMR system. The performance measurement factors were constructed by perspective using BSC, and analysis on causal relationship between factors was conducted. A model of causal relationship was established, and performance measurement model of EMR system was proposed through model validation. Analysis on causal relationship between performance management factors revealed that utility cognition of the learning & growth perspective factor had causal relationship with job efficiency(${\beta}=0.20$) and decision support(${\beta}=0.66$) of the internal process perspective factors, and security had causal relationship with system satisfaction(${\beta}=0.31$) of the customer perspective factor. System quality had causal relationship with job efficiency(${\beta}=0.66$) and decision support(${\beta}=0.76$) of the internal process perspective factors, all of which were statistically significant(P<0.01). Job efficiency of the internal process perspective had causal relationship with system satisfaction(${\beta}=0.43$), and decision support had causal relationship with decision support satisfaction(${\beta}=0.91$) and job satisfaction (${\beta}=0.74$), all of which were statistically significant(P<0.01). System satisfaction of the customer perspective had causal relationship with job satisfaction(${\beta}=0.12$), job satisfaction had causal relationship with cost reduction(${\beta}=0.53$) of the financial perspective, and decision support satisfaction had causal relationship with productivity improvement(${\beta}=0.40$)of the financial perspective(P<0.01). Also, cost reduction of the financial perspective had causal relationship with productivity improvement(${\beta}=0.37$), all which were statistically significant(P<0.05). Suitability index verification of the performance measurement model whose causal relationship was found to be statistically significant revealed that $X^2/df=2.875$, RMR=0.036, GFI=0.831, AGFI=0.810, CFI=0.887, NFI=0.838, IFI=0.888, RMSEA=0.057, PNFI=0.781, and PCFI=0.827, all of which were in suitable levels. In conclusion, the performance measurement indices of EMR system include utility cognition, security, and system quality of the learning & growth perspective, decision support and job efficiency of the internal process perspective, system satisfaction, decision support satisfaction, and job satisfaction of the customer perspective, and productivity improvement and cost reduction of the financial perspective. In this study, it is expected that the performance measurement indices and model of EMR system which are suggested by the author, will be a measurement tool available for system performance measurement of EMR system in medical institutions.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.53 no.2
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• pp.161-170
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• 2008

Interest is growing in applying simulation models for the South Texas conditions, to better assess crop water use and production with different crop management practices. The Environmental Policy Integrated Climate (EPIC) model was used to evaluate its application as a decision support tool for irrigation management of com (Zea mays L.) in South Texas of the U.S. We measured actual crop evapotranspiration (ETc) using a weighing lysimeter, soil moisture using a neutron probe, and grain yield by field sampling. The model was then validated using the measured data. Simulated ETc using the Hargreaves-Samani equation was in agreement with the lysimeter measured ETc. Simulated soil moisture generally matched with the measured soil moisture. The EPIC model simulated the variability in grain yield with different irrigation regimes with $r^2$value of 0.69 and root mean square error of $0.5\;ton\;ha^{-1}$. Simulation results with farm data demonstrate that EPIC can be used as a decision support tool for com under irrigated conditions in South Texas. EPIC appears to be effective in making long term and pre-season decisions for irrigation management of crops, while reference ET and phenologically based crop coefficients can be used for inseason irrigation management.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.163-163
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• 2019

The rapidly growing global population increases the awareness of water, energy, and food security worldwide. The concept of Water, Energy, and Food nexus (hereafter, WEF nexus) has been widely introduced as a new resources management concept that integrate the water, energy, and food in a single management framework. Recently, WEF nexus analyzes not only the interconnections among the resources, but also considers the external factors (such as environment, climate change, policy, finance, etc) to enhance the resources sustainability by proper understanding of their relations. A nation-level resources management is quite complex task since multiple regions (e.g., watersheds, cities, and counties) with different characteristics are spatially interconnected and transfer the resources each other. This study proposes a multiple region WEF nexus simulation and transfer model. The model is equipped with three simulation modules, such as local nexus simulation module, regional resources transfer module, and optimal investment planning module. The model intends to determine an optimal capital investment plan (CIP), such as build-up of power plants, water/waste water treatment plants, farmland development and to determine W-E-F import/export decisions among areas. The objective is to maximize overall resources sustainability while minimize financial cost. For demonstration, the proposed model is applied to a semi-hypothetical study area with three different characterized cities. It is expected the model can be used as a decision support tool for a long-term resources management planning process.

• Journal of Biomedical Engineering Research
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• v.43 no.2
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• pp.102-108
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• 2022

Purpose: To propose a deep learning-based clinical decision support technique for laryngeal disease on epiglottis, tongue and vocal cords. Materials and Methods: A total of 873 laryngeal endoscopic images were acquired from the PACS database of Pusan N ational University Yangsan Hospital. and VGG16 model was applied with transfer learning and fine-tuning. Results: The values of precision, recall, accuracy and F1-score for test dataset were 0.94, 0.97, 0.95 and 0.95 for epiglottis images, 0.91, 1.00, 0.95 and 0.95 for tongue images, and 0.90, 0.64, 0.73 and 0.75 for vocal cord images, respectively. Conclusion: Experimental results demonstrated that the proposed model have a potential as a tool for decision-supporting of otolaryngologist during manual inspection of laryngeal endoscopic images.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.47-51
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• 2013

Existing buildings now represent the greatest opportunity to improve building energy efficiency. Building performance analysis is becoming increasingly important because decision makers can have a better visualization of their building's performance and quickly make the solution for improving building energy efficiency and reducing environmental impacts. Nowadays, building information models (BIMs) have been widely created during the design phase of new buildings, and it can be easily imported to third party software to conduct various analyses. However, a BIM is not always available for all existing buildings. Even if a BIM is available during the design and construction phases, it is very challenging to keep updating it while a building is aged. A manual process to create or update a BIM is very time consuming and labor intensive. A laser scanning technology has been a popular tool to create as-is BIM. However it still needs labor-intensive manual processes to create a BIM out of point clouds. This paper introduces automatic as-is simplified BIM creation from point clouds for energy simulations. A framework of decision support system that can assist decision makers on retrofits for existing buildings is introduced as well. A case study on a residential house was tested in this study to validate the proposed framework, and the technical feasibility of the developed system was positively demonstrated.

• East Asian Journal of Business Economics (EAJBE)
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• v.12 no.1
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• pp.35-42
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• 2024

Purpose: A railroad project is a complex system with large construction costs in the initial stage and ongoing operating costs over its lifecycle. Current railroad projects tend to be based on construction options, which leads to huge deficiencies in operating costs. This phenomenon results from a lack of appropriate tools to accurately estimate a railroad project's lifecycle costs. This study attempts to analyze the major components of railroad operating costs and to propose a decision-making system for analyzing the long-term lifecycle costs of railroad projects. Research design, data and methodology: We review the literature and analyze the current status of railroad operating costs in Korea and overseas. Based on previous projects, a framework for project options and operating costs is proposed. The framework is applied to actual railroad projects to demonstrate the validity of the model. Results: Case analysis shows that our framework is comprehensive in analyzing the primary aspects of railroad operating costs and plays an effective role in choosing various railroad project options. This study points out that the railway project operates inefficiently because estimating long-term costs without reflecting specific project options causes many errors. Conclusions: A major contribution of this study is the development of an improved framework for accurately estimating operating costs and providing policymakers and engineering firms with a holistic decision support system. Detailed components in estimating operating costs of the railroad business are discussed. And we present a decision-making tool that policymakers and private businesses can use in planning the railroad business.