• Asia pacific journal of information systems
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• v.11 no.2
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• pp.181-203
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• 2001

As the Internet is used extensively, multimedia information becomes more prevailing and accessible. However, legacy decision support systems rarely mention how to put such multimedia contents into practical use for decision making and support. In particular, no proposals have yet been made on how to integrate the decision technologies and multimedia databases in model management systems. Hence, the aim of this paper is to propose a new model management method to integrating decision technologies and an image database management system to create a multimedia decision support. For this purpose, extended ARG and structured modeling techniques are adopted, to represent image contents and mathematical models respectively. A web-based prototype system is presented to illustrate the feasibility and usability of the methodology.

• Journal of the Korean Society of Systems Engineering
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• v.15 no.2
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• pp.17-30
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• 2019

Due to difficulties in tracking design information of existing document-based configuration management, the research on the development of plant SysML model was started to apply the model-based system engineering methodology to comprehensively manage various design information. However, until now, in order to create the SysML model, the engineers are checking the design information and inputting it to the SysML model. This process requires a lot of time and manpower, it is required to minimize it. Therefore, this study has recognized the problem, a plug-in that extracts the plant design information in the design document and automatically converts the SysML plant model from it. Specifically, the development was performed in the following order. First, the extraction file was selected as the most commonly used Excel file as the plant design document. Next, the design information in the document was analyzed, and extracted information including tag number, name, and the capacity were selected. Finally, the plant SysML model conversion module was implemented. The developed plug-in is confirmed that the task load of the engineers by the SysML model conversion can be minimized and the model can be generated more quickly and accurately.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.613-616
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• 2008

This study presents an IFC-based information model for standardized and integrated information management system of tunnel monitoring. Information items of tunnel monitoring were extracted from the Tunnel Design Standard of Ministry of Construction and Transportation. Then, the information items were compared with components of IFC 2x Edition3 model. Two main entities are added into the IFC model for generic representing of monitoring devices and data. IfcMonitoringElement which is composed of IfcMonitoringLogger and IfcMonitorinSensor is proposed to represent physical information of data loggers and sensors, and relationship between data logger and sensors. Besides, as an additional resource of IFC model, IfcMonitoringData is provided to express measured data from sensors and warning histories.

• Journal of the Korea Safety Management & Science
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• v.5 no.3
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• pp.45-55
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• 2003

Construction Management(CM) system, which was introduced some years ago to large national construction projects, such as the construction of Incheon New Airport, construction of high-speed railroad and World Cup stadiums, is considered to be still in its early stage and safety at each step of CM is very poorly controlled. In an attempt to improve such inferior safety control of domestic CM, this study analyzed safety control operation system in CM home and abroad and suggested a model for the construction of safety control management information system suitable to the conditions of Korea.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1999.04a
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• pp.477-477
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• 1999

• Asia pacific journal of information systems
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• v.27 no.1
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• pp.38-53
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• 2017

As sensor technologies and image processing technologies make collecting information on users' behavior easy, many researchers have examined automatic emotion recognition based on facial expressions, body expressions, and tone of voice, among others. Specifically, many studies have used normal cameras in the multimodal case using facial and body expressions. Thus, previous studies used a limited number of information because normal cameras generally produce only two-dimensional images. In the present research, we propose an artificial neural network-based model using a high-definition webcam and Kinect to recognize users' emotions from facial and bodily expressions when watching a movie trailer. We validate the proposed model in a naturally occurring field environment rather than in an artificially controlled laboratory environment. The result of this research will be helpful in the wide use of emotion recognition models in advertisements, exhibitions, and interactive shows.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.100-103
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• 1996

Presented in this study is an algorithmic procedure to obtain polyhedral model from a compound surface. The compound surface in this study denotes a collection of trimmed surfaces without topological relations. The procedure consists of two main modules: CAD data interface, and surface conversion to polyhedral model. The interface module gets geometric information from CAD databases, and makes topological information by scanning the geometric information. We are investigating CATIA system as a data source system. In the surface conversion module, a shell(compound surface with topological information) is approximated to a triangular-faceted polyhedral surface model through node sampling and triangulation steps. The obtained polyhedral model should obey the vertex-to-vertex rule and meet tolerance requirements. Since the polyhedral model has a simple data structure and geometry processing for it is very efficient and robust, the polyhedral model can be used in various applications, such as surface rendering in computer graphics, FEM model for engineering analysis, CAPP for surface machining, data generation for SLA, and NC tool path generation.

• Journal of Information Technology Applications and Management
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• v.28 no.4
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• pp.33-43
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• 2021

While youth unemployment has recorded the lowest level since the global COVID-19 pandemic, SMEs(small and medium sized enterprises) are still struggling to fill vacancies. It is difficult for SMEs to find good candidates as well as for job seekers to find appropriate job offers due to information mismatch. To overcome information mismatch, this study proposes the fine-turning model for bidirectional HR matching based on a pre-learning language model called BERT(Bidirectional Encoder Representations from Transformers). The proposed model is capable to recommend job openings suitable for the applicant, or applicants appropriate for the job through sufficient pre-learning of terms including technical jargons. The results of the experiment demonstrate the superior performance of our model in terms of precision, recall, and f1-score compared to the existing content-based metric learning model. This study provides insights for developing practical models for job recommendations and offers suggestions for future research.

• Journal of the Korean Operations Research and Management Science Society
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• v.24 no.4
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• pp.1-12
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• 1999

This paper presents a DEA-AHP hybrid model to evaluate and select R&D projects. AHP collects and processes information on the weights of evaluation criteria. The processed information is used as an input for DEA/AR model. Only desirable number of projects are selected by the hybrid model. The model is examined by an example generated from a real data set.

• Journal of the Korean Society for information Management
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• v.40 no.2
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• pp.243-262
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• 2023

In the rapidly developing information technology environment, information management organizations need to effectively evaluate their digital maturity and clarify the direction of improvement to effectively respond to rapidly changing environments. This study derived weights for the digital curation maturity model developed by KISTI from the perspective of digital transformation to facilitate effective evaluation and direction setting of information management organizations. Relative importance was derived as a weight in the major and middle categories of the model through the AHP technique. Summarizing the results, when the major categories of the entire model are measured on the basis of 100 points, technology is 27 points, data is 24 points, strategy is 19 points, organization (manpower) is 16 points, and (social) influence is calculated as 14 points. In addition, weights for each subcategory were presented for each major classification based on a perfect score of 100 points. It is expected that a more objective and reasonable evaluation will be possible by applying the weights for each area derived from this study to the digital transformation maturity evaluation model.