• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.4
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• pp.1-25
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• 2021

In order to respond and prevent underground safety accidents, the Korean government has been preparing a submitting completion drawing web system project for converting the current manual-based 3D Underground Geospatial Map construction and its update system to an automation-based 3D underground information construction. However, research on standard drawings required for the automatic update of 3D underground structures is insufficient, so detailed research is needed. In this research paper, a standard map-based 3D underground structure construction plan was presented for the six types of underground structures constituting the 3D Underground Geospatial Map, enabling rapid and accurate drawing data creation and systematically 3D underground structure drawing data could be managed. In addition, we developed a 3D construction drawing tool that can be used in underground information practice so that ordinary CAD program users can easily produce processing drawings. The results derived from this paper are expected to be major reference materials for the establishment of standard frameworks and practical application guidelines for the construction of 3D underground structures in the future.

• The Journal of Society for e-Business Studies
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• v.26 no.4
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• pp.133-154
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• 2021

Today smart phone is the most common media with a vehicle called 'application'. In order to understand how media users select applications and build their repertoire, this study conducted two-step approach using big data from smart phone log for 4 weeks in November 2019, and finally classified 8 media repertoire groups. Each of the eight media repertoire groups showed differences in time spent of mobile application category compared to other groups, and also showed differences between groups in demographic distribution. In addition to the academic contribution of identifying the mobile application repertoire with large scale behavioral data, this study also has significance in proposing a two-step approach that overcomes 'outlier issue' in behavioral data by extracting prototype vectors using SOM (Sefl-Organized Map) and applying it to k-means clustering for optimization of the classification. The study is also meaningful in that it categorizes customers using e-commerce services, identifies customer structure based on behavioral data, and provides practical guides to e-commerce communities that execute appropriate services or marketing decisions for each customer group.

• Korean Journal of Construction Engineering and Management
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• v.21 no.6
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• pp.113-124
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• 2020

Social movements to improve the performance of buildings through remodeling of aging apartment houses are being captured. To this end, the remodeling construction cost analysis, structural analysis, and political institutional review have been conducted to suggest ways to activate the remodeling. However, although the method of analyzing construction cost for remodeling apartment houses is currently being proposed for research purposes, there are limitations in practical application possibilities. Specifically, In order to be used practically, it is applicable to cases that have already been completed or in progress, but cases that will occur in the future are also used for construction cost analysis, so the sustainability of the analysis method is lacking. For the purpose of this, we would like to suggest an automated estimating method. For the sustainability of construction cost estimates, Deep-Learning was introduced in the estimating procedure. Specifically, a method for automatically finding the relationship between design elements, work types, and cost increase factors that can occur in apartment remodeling was presented. In addition, Monte Carlo Simulation was included in the estimation procedure to compensate for the lack of uncertainty, which is the inherent limitation of the Deep Learning-based estimation. In order to present higher accuracy as cases are accumulated, a method of calculating higher accuracy by comparing the estimate result with the existing accumulated data was also suggested. In order to validate the sustainability of the automated estimates proposed in this study, 13 cases of learning procedures and an additional 2 cases of cumulative procedures were performed. As a result, a new construction cost estimating procedure was automatically presented that reflects the characteristics of the two additional projects. In this study, the method of estimate estimate was used using 15 cases, If the cases are accumulated and reflected, the effect of this study is expected to increase.

• Journal of the Korean Data and Information Science Society
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• v.27 no.1
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• pp.203-215
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• 2016

This study was performed in order to investigate the effect of breast milk on pain relief in newborn during heel lancing. Nonequivalent control group pretest-posttest design by double blinded experiment was used. 50 neonates were randomized to receive breast milk (experimental group, n=25) or no treatment (control group, n=25) before undergoing heel lancing. Informed consent was obtained from parents of 50 neonates. Neonatal infant pain scale (NIPS), respiration rate, heart rate, oxygen saturation, and crying duration were used to assess subjects' pain reaction. Data were analyzed using SPSS 18.0. The experimental and control group showed a statistically significant differences in NIPS score (F=28.89, p<.001), heart rate (F=14.03, p<.001), respiration rate (F=4.79, p=.001), oxygen saturation (F=2.69, p=.027), and crying duration (t=-8.78, p <.001) at each time points (during heel lancing, right after heel lancing, 1, 2, 3 minutes after heel lancing). The result suggest that oral administration of expressed breast milk is safe and natural agents for reducing procedural pain of neonates. Another clinical trial study with more samples is recommended.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.6
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• pp.10-23
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• 2016

With requiring circumspections using big data, this study attempts to develop and apply the search method for audit issues relating to the ITS policy or program. For the foregoing, the auditing process of the board of audit and inspection was converged with the theoretical frame of boundary analysis proposed by William Dunn as an analysis tool for audit issues. Moreover, we apply the text mining technique in order to computerize the analysis tool, which is similar to the boundary analysis in the concept of approaching meta-problems. For the text mining analysis, specific model we applied the antisymmetry-symmetry compound lexeme-based LDA model based on the Latent Dirichlet Allocation(LDA) methodologies proposed by David Blei. The several prime issues were founded through a case analysis as follows: lack of collection of traffic information by the urban traffic information system, which is operated by the National Police Agency, the overlapping problems between the Ministry of Land, Infrastructure and Transport and the Advanced Traffic Management System and fabrication of the mileage on digital tachograph.

• Journal of Korean Library and Information Science Society
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• v.51 no.1
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• pp.115-143
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• 2020

With the era of the 4th Industrial Revolution, the number of data-centric integrated researches increases. The integrated researches make information identification and linkage more important, so it is necessary to seek a method to efficiently manage and share academic-information for supporting the researches. Therefore, this study aims to analyze identification system and linkable information types of 12 major academic search engines and bibliographic databases(ASEBDs) in Korea and abroad and to propose a method to identify and link academic-information. The analysis was conducted 2 times, and academic-information types, searchable fields, linkable information types, used identification system were investigated. As a result, the ASEBDs link directly or/and indirectly 3~4 information types based on their own identifiers with persistent identifiers. In addition, they identify academic-information semi-automatically based on machine learning methodology and collect and manage the related data. Finally, the method for academic-information linkage was proposed in terms of practice and society: linkage based on persistent identifiers and linkage based on collaborative network of institutions.

• Journal of Korean Society for Geospatial Information Science
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• v.16 no.3
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• pp.95-103
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• 2008

Spatial information is essential for administrative affairs. So many Administrative Information System(AIS)s and Geographic Information System(GIS)s have been implemented at local government to support administrative affairs. AIS deals with document based information, and is not designed to use map information. Also, various information is not matched, because address systems for AIS and coordinate system for GIS are different. Therefore, existing AIS and GIS are not suitable for linking administrative affairs and spatial information. This paper deals with the enterprise architecture for local government to support the linkage of administrative affairs and spatial information. Enterprise architecture in this paper is composed of business architecture, data architecture, application architecture, and technical architecture. Each architecture is designed up to planner's and owner's level. Detail structures of each architecture follow the practical guidance for applying e-government enterprise architecture in Korea. Business and data architecture are applied to transportation administrative affairs.

• International Area Studies Review
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• v.20 no.4
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• pp.163-184
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• 2016

Recently, many companies consider various methods for hiring employees. Hiring talent employee has made influences on the future of the company. Therefore, companies spend a lot of money for developing many tools on hiring employee. But most of companies don't try to review the comparison between the assessment system of hire and performance. There is few research on the performance results from the assessment scores of hiring. Only, the companies focus on hiring good employee who have good ability. Sometimes, HR managers are satisfied only with low quit rate. The paper analyzes what kind of relevance between the hire assessment and performance assessment for the same people. It uses the actual data for A company. This is very useful data for research on the relevance between hire and perform assessment. We can consider what the important things are for hiring and managing employee.

• Journal of the Korean Society for information Management
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• v.40 no.3
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• pp.143-162
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• 2023

This study analyzed the Beopmaru, Supreme Court Library of Korea, circulation data to identify user lending patterns and proposed a plan to reflect the analysis results in future user services. In 2022, Beopmaru's collection of books was 212,608, with law books accounting for 73%. However, general books accounted for 83% of actual circulation. Looking at the usage coefficient by topic, the literature field was the most actively used at 5.85, and the law field was the least used at 0.23. In the case of interlibrary loan, both KERIS member institutions and the Korean Bar Association had the highest loan ratios in the legal field, civil law field, and judicial litigation procedure field, in that order. However, member institutions affiliated with KERIS, a legal academic community, were lending law books on a wider range of subject areas than the Korean Bar Association, a practical organization. To improve access to legal information, the Beopmaru public service was implemented, but in reality, the use of reading space was high, and the proportion of general books loaned was much higher. In order to improve this, it seems necessary to strengthen the promotion of Beopmaru loan services, provide personalized services, improve book lending regulations, strengthen online services, and establish a cooperative network.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.2
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• pp.167-175
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• 2024

Due to the Fourth Industrial Revolution, ICT(Information and Communication Technology) industry is becoming more important and sophisticated than ever. In B2B based ICT industry demand forecasting by analyzing the previous customer data is so important. RFM, one of customer relationship management models is a marketing technique that evaluates Recency, Frequency and Monetary value to predict customers behavior. RFM model has been studied focusing on the B2C based industry. On the other hand there is a lack of research on B2B based technology industry. Therefore this study applied it to B2B based high technology industry and considered T(technology collaboration) value, which are identified as important factors in the technology industry. To present an improved model for market performance in B2B technology industry, an empirical study was conducted on comparing the accuracy of the traditional RFM model and the improved RFM-T model. The objective of this study is to contribute to market performance by presenting an improved model in B2B based high technology industry.