• Journal of the Korea Society of Computer and Information
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• v.23 no.1
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• pp.85-90
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• 2018

The new information service has been demanded due to the recent mobile internet activation, and the government is promoting the activation of the private use of the public data by putting up the Government 3.0. According to government policy, many public sectors provide public data, but the railway sector is inferior to other public sector. In the case of national railway corporation, urban railway is now operated by 14 corporations such as Seoul Metro through the nation and high-speed railway is now operated by Korea Railroad Corporation and Supreme Railways. It is very difficult to standardize and integrate data due to mutual interests of national railway corporation. This paper describes a way to standardize and integrate rail passengers information collected through research project.

• Electronics and Telecommunications Trends
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• v.34 no.1
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• pp.13-22
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• 2019

Various hyper-intelligent and ultra-realistic data-driven services are being increasingly developed with the goal of achieving a hyper-connected intelligent society. To sustain this trend, our research focuses on the integration and optimization of data-driven applications from several aspects such as delivery, storage, execution, and sharing of data and software, beyond the limitations of the existing network infrastructure. In this paper, we present important research issues of data-centric hyper-distributed autonomous infrastructure technologies.

• Annual Conference of KIPS
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• 2013.05a
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• pp.474-475
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• 2013

In healthcare systems, the accuracy of a classifier for classifying medical diseases depends on a reduced dataset. Key to achieve true classification results is the reduction of data to a set of optimal number of significant features. The initial step towards data reduction is the integration of heterogeneous data sources to a unified reduced dataset which is further reduced by considering the range of values of all the attributes and then finally filtering and dropping out the least significant features from the dataset. This paper proposes a three step data reduction model which plays a vital role in the classification process.

• Annual Conference of KIPS
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• 2009.04a
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• pp.846-848
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• 2009

The interest in the access and integration of distributed massive data resources has increased recently. This paper presents the Advanced Collection Manager(CM) service with OGSA-DAI component which can access and integrate the distributed data resources. The Advanced CM service supports the data resource of various types. And it can provide the query, updating, transforming and delivering data via cooperating with other services in Grid Information Retrieval(Grid-IR or GIR) System. As a result, it can access and manage the data resource more flexible and efficient.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.503-508
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• 2005

In the modern, distributed and dynamic construction environment it is important to exchange information from different sources and in different data formats in order to improve the processes supported by these systems. Previous research has demonstrated that (i) a significant percentage of construction data is stored in semi-structured or unstructured data formats (ii) locating and identifying such data that are needed for the important decision making processes is a very hard and time-consuming task. In this paper, an automated methodology for the classification and retrieval of construction images in AEC/FM model based systems will be presented. Specifically, a combination of techniques from the areas of image processing, computer vision, and content-based image retrieval have been deployed to develop a method that can retrieve related construction site image data from components of a project model.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.672-679
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• 2024

This study introduces a novel system for the 4D simulation of Building Information Modeling (BIM) objects in mixed reality (MR) environments, addressing challenges of file format compatibility and data management. By developing a system that effectively partitions and manages BIM data, specifically utilizing the OBJ format, the study enables precise simulation of construction project changes over time. This advancement enhances visualization and decision-making in construction project planning and execution. The study highlights the integration of BIM and MR technologies, facilitating enhanced project management and operational workflows. Future work will focus on expanding compatibility with various BIM data formats and MR devices, and integrating AI-based data analysis for more accurate and efficient construction simulations.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.8
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• pp.1463-1472
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• 2008

We propose Framework that (should) have data interoperability between Legacy DataBases using Proxy DataBases based on XMDR(eXtended Meta-Data Registry) Data Hub in this papers. It may occur some problems among data structure, semantics and other heterogeneous problems between interoperability of legacy DB on cooperation environment. Also, It is hard to keep consistency of Data that changes on realtime, regardless of data variety and type. In this paper, Using XMDR data hub, we solve the problem that was occurred by data integration and interoperability between legacy DB. We suggest the framework which are compatible with any class and type of interoperability-data and offer accurate information with consistency in real-time using proxy database.

• Korean Journal of Computational Design and Engineering
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• v.13 no.2
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• pp.89-97
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• 2008

Today's manufacturing environment is becoming a distributed manufacturing process in which a unique and specialized technological background is required in specific domains rather than having a single company execute all the manufacturing processes. This phenomenon is especially true in the automotive industry, where the sharing of product data between companies is rampant; however, this kind of interoperability causes many problems. When each company has its own method of managing product data, the sharing of product data in a distributed environment is a major problem. A data translator module or a data mapping module had to be developed for the exchange of data in heterogeneous systems of product data management (PDM); moreover, this type of module must be continually changed and improved due to the fact that PDM systems change for many reasons. In addition, the growth in corporate partnerships deepens the burden of developing and maintaining this module and creates further data exchange problems due to the increasing complexity of the system. This paper introduces a way of exchanging product data among heterogeneous PDM systems through the use of OpenPDM, which is a kind of virtual data warehouse. The implementation of a PDM integrating system is also discussed with respect to the requirement for a logical integration of product data which are physically distributed.

• Korean Journal of Computational Design and Engineering
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• v.18 no.3
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• pp.200-210
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• 2013

It has become important to manage plant data effectively and to share these data among different organizations that are located in different places and participate in a variety of lifecycle phases. ISO 15926 is an international standard for integration of lifecycle data for process plants including oil and gas facilities. This standard consists of several parts providing a generic data model, reference data, and implementation methods. iRINGTools is a tool developed for the exchange of plant design data. This tool supports the implementation methods specified in ISO 15926. In this paper, the exchange of plant design data using iRINGTools is investigated. For this, sample P&ID data was modeled and data exchange experiment was performed. From the experiment, a data exchange procedure based on ISO 15926 is established and design data types that can be practically exchanged using ISO 15926 were identified.

• Journal of Information Technology Services
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• v.23 no.3
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• pp.39-54
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• 2024

This study explores the barriers to using health and medical data in research and development (R&D) within the healthcare industry and suggests ways to enhance data utilization. As artificial intelligence technology drives transformative changes across industries, there is an increased demand for robust health and medical data, highlighting its critical economic value and utility in fostering innovation. Using qualitative analysis through Grounded Theory, the study involves ten R&D professionals from healthcare industry, including both medical centers and corporations, using surveys and in-depth interviews to gather diverse experiences and perspectives on the challenges and opportunities in health and medical data use. Key findings point to legislative, regulatory, and data quality and integration issues, as well as complexities in patient data access and usage. Technological limitations and inadequate data governance frameworks also emerge as significant obstacles. Recommendations focus on improving regulatory frameworks, enhancing data standardization and quality, and fostering stronger partnerships between data custodians and users. The study concludes that overcoming these obstacles requires a comprehensive strategy involving legislative changes, improved technological infrastructure, and increased stakeholder collaboration. Implementing these recommendations could greatly enhance health and medical data utilization in R&D, significantly advancing medical science and patient care services.