• Journal of KIBIM
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• v.13 no.4
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• pp.54-63
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• 2023

In recent years, the mandatory use of BIM has been actively promoted due to the digital transformation of the construction industry. However, the CDE (Common Data Environment) system, which is an essential element for operating BIM, has not been established in accordance with the domestic situation. To solve this problem, this study analyzed the results of previous studies, including the ISO 19650 standard and domestic CDE system requirements, and developed BIM-based collaboration functions that are suitable for the domestic construction industry through functional analysis of domestic and foreign commercial CDE solutions. And we developed a BIM collaboration framework to provide BIM-based collaboration functions as a service by using cloud technologies such as IaaS, PaaS, and SaaS to provide infrastructure resources flexibly and flexibly. The BIM collaboration framework developed in this study meets most of the CDE requirements of ISO1965, so it can secure competitiveness when bidding for overseas BIM projects. Also, because the BIM collaboration functions can be selectively applied to build a BIM-based collaboration platform, it is expected that the utilization of the BIM collaboration framework will be high, as it can minimize not only the time to build the platform but also the operating costs, and the usability is higher than that of existing commercial BIM CDE solutions.

• The Journal of Information Systems
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• v.29 no.3
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• pp.119-144
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• 2020

Purpose Real estate usually takes charge of the highest proportion of physical properties which individual, organizations, and government hold and instability of real estate market affects the economic condition seriously for each economic subject. Consequently, practices for predicting the real estate market have attention for various reasons, such as financial investment, administrative convenience, and wealth management. Additionally, development of machine learning algorithms and computing hardware enhances the expectation for more precise and useful prediction models in real estate market. Design/methodology/approach In response to the demand, this paper aims to provide a framework for forecasting the real estate market with machine learning algorithms. The framework consists of demonstrating the prediction efficiency of each machine learning algorithm, interpreting the interior feature effects of prediction model with a state-of-art algorithm, LIME(Local Interpretable Model-agnostic Explanation), and comparing the results in different cities. Findings This research could not only enhance the academic base for information system and real estate fields, but also resolve information asymmetry on real estate market among economic subjects. This research revealed that macroeconomic indicators, real estate-related indicators, and Google Trends search indexes can predict real-estate prices quite well.

• Journal of the Korea Society of Computer and Information
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• v.24 no.3
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• pp.49-56
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• 2019

The purpose of this study is to analyze the characteristics and meanings of Instagram hashtags related to the exhibitions as a online communication platform of museums. At the same time, it focuses on efficiency of hashtags as a reference framework of inferring viewing experiences. We collect and visualize Instagram hashtags of exhibitions held in Korea for the past two years including 'Paper Present (2017)', 'YOUTH (2017)', 'Monet, Draw Light Exhibition (2018)', 'Van Gogh Inside (2016)', 'Drawn by the Wind: Shin yun-bok & Jeong Seon'. To sum up, significant data related to viewing experiences are not derived, and hashtags as a reference framework of inferring viewing experiences are turned out to be inefficient. Meanwhile, we conclude that potential for distributing information about the exhibitions is inherent in hashtags. In terms of informational characteristics, we notice that the influence of hashtags related to regional information is presented more than the response toward the viewing experiences. This result shows that Instagram users in the exhibitions are worthy of place making rather than viewing experiences.

• Journal of Korean Society for Quality Management
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• v.38 no.1
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• pp.64-74
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• 2010

Since management of information resources is getting more complicated in the distributed, heterogeneous computing environment, the capability of monitoring and controlling the dispersed information resources is perceived as a critical success factor for the effective enterprise-wide information resource management. Integrated Control Architecture(ICA) provides that capability. Utilizing such architecture, we can manage corporate information resources more efficiently, perform impact analysis for changes in information resources, and alleviate the human effort by automating the monitoring of critical information resources. In this paper, we propose a conceptual framework and metamodel of ICA.

• Journal of the Korean Society of Food Culture
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• v.22 no.2
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• pp.235-245
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• 2007

This study was undertaken to develop web-based nutrition information contents for the older adults. Twenty six domestic web-sites were analyzed and then 12 foreign web-sites and 4 education materials for the elderly of foreign university were benchmarked. Also a lot of literatures on elderly education program were reviewed. A card-sorting task was performed with 8 older adults to ascertain how the target audience organized information about nutrition. The results were as fellows. Among 26 domestic web-sites, 2 sites(7.7%) were only for the elderly. Main topics of information contents for the elderly included 'Importance of Healthy Eating', 'DRI', 'Dietary Guidelines'. Four of twelve foreign web-sites were for the elderly nutrition education. Topics of 'Dietary Guideline', 'Meal Program' were found in 4 sites and 'Importance of Healthy Eating', 'Diet & Disease', 'DRI, 'Food Guide Pyramid', 'Nutrition Fact Labels' were found in 3 sites. Education materials of foreign university dealt with basic information on 'nutrient needs changes related with aging', 'Heart & Bone Healthy Eating Plan', 'Food Guide Pyramid'. Also topics on 'Eating on a budget', 'Eating Out Guideline' were included for practical use for the elderly. Based on card-sorting process, contents framework for web-site was developed and 4 main menus for framework were respectively named as 'Nutrition', 'Meals', 'Foods'. 'Check up Nutritional Health' by panel discussion. Finally we developed nutrition information contents for 4 main menus. We focused on helping older adults recognize the importance of healthy eating and apply the nutrition information to practical use. We expect that the developed framework of contents can be a guideline for indentifying the information needs of older adults in developing effective nutrition intervention program. And we suggest that the survey for target people should be peformed for the web-site to be user-friendly designed and the developed contents be evaluated and revised in the near future.

• The KIPS Transactions:PartC
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• v.13C no.1 s.104
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• pp.129-136
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• 2006

Information Retrieval System aims towards providing fast and accurate information to users. However, current search systems are based on plain svntactic analysis which makes it difficult for the user to find the exact required information. This paper proposes the SW-IRS (Semantic Web-based Information Retrieval System) using an Ontology Server. The proposed system is purposed to maximize efficiency and accuracy of information retrieval of unstructured and semi-structured documents by using an agent-based automatic classification technology and semantic web based information retrieval methods. For interoperability and easy integration, RDF based repository system is supported, and the newly developed ranking algorithm was applied to rank search results and provide more accurate and reliable information. Finally, a new ranking algorithm is suggested to be used to evaluate performance and verify the efficiency and accuracy of the proposed retrieval system.

• The KIPS Transactions:PartC
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• v.17C no.5
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• pp.391-398
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• 2010

Most of digital forensics tools focus on file analysis of allocated area on storage. So, there is a lack of recovery methods for deleted files by suspects or previously used files. To efficiently analyze deleted files, digital forensic tools depend on data recovery tools. These process not appropriate for quick and efficient responses the incident or integrity preservation. This paper suggests the framework for data recovery and analysis tools from digital forensics point of view and presents implementation results.

• Journal of Computing Science and Engineering
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• v.6 no.3
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• pp.219-226
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• 2012

Recently, shape analysis of human organs has achieved much attention, owing to its potential to localize structural abnormalities. For a group-wise shape analysis, it is important to accurately restore the shape of a target structure in each subject and to build the inter-subject shape correspondences. To accomplish this, we propose a shape modeling method based on the Laplacian deformation framework. We deform a template model of a target structure in the segmented images while restoring subject-specific shape features by using Laplacian surface representation. In order to build the inter-subject shape correspondences, we implemented the progressive weighting scheme for adaptively controlling the rigidity parameter of the deformable model. This weighting scheme helps to preserve the relative distance between each point in the template model as much as possible during model deformation. This area-preserving deformation allows each point of the template model to be located at an anatomically consistent position in the target structure. Another advantage of our method is its application to human organs of non-spherical topology. We present the experiments for evaluating the robustness of shape modeling against large variations in shape and size with the synthetic sets of the second cervical vertebrae (C2), which has a complex shape with holes.

• Journal of Information Processing Systems
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• v.3 no.1
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• pp.33-37
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• 2007

Semantic clustering is important to various fields in the modem information society. In this work we applied the Independent Component Analysis method to the extraction of the features of latent concepts. We used verb and object noun information and formulated a concept as a linear combination of verbs. The proposed method is shown to be suitable for our framework and it performs better than a hierarchical clustering in latent semantic space for finding out invisible information from the data.

• Journal of Digital Convergence
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• v.17 no.11
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• pp.233-240
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• 2019

In order to predict and respond to cyber attacks, a number of security companies quickly identify the methods, types and characteristics of attack techniques and are publishing Security Intelligence Reports(SIRs) on them. However, the SIRs distributed by each company are huge and unstructured. In this paper, we propose a framework that uses five analytic techniques to formulate a report and extract key information in order to reduce the time required to extract information on large unstructured SIRs efficiently. Since the SIRs data do not have the correct answer label, we propose four analysis techniques, Keyword Extraction, Topic Modeling, Summarization, and Document Similarity, through Unsupervised Learning. Finally, has built the data to extract threat information from SIRs, analysis applies to the Named Entity Recognition (NER) technology to recognize the words belonging to the IP, Domain/URL, Hash, Malware and determine if the word belongs to which type We propose a framework that applies a total of five analysis techniques, including technology.