• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.2
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• pp.87-96
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• 2004

When watershed spatial database is constructed from DEM, hydrological geographic characteristics of watershed can be easily extracted. And the characteristics can be assigned and managed as the attribute of spatial database. In this study the scheme of constructing framework spatial database which is basic information for managing watershed information is examined. We established framework spatial data and defined the relationship of the data. And framework spatial database of test site was constructed. In this study, HyGIS(Hydrological Geographic Information System) which is developed by domestic technology for making hydrological spatial data and developing water resources system is used. Hydrological geographic characteristics and spatial data is extracted by HyGIS. And the data from HyGIS is used for constructing framework spatial database of test site. Finally, this study suggests the strategy of constructing framework spatial database for developing watershed management system based on river network.

• Korean Journal of Computational Design and Engineering
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• v.17 no.4
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• pp.234-245
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• 2012

This paper proposes a multi-level product modeling framework for long-term lifecycle products. The framework can help engineers to define product models and relate them to physical instances. The framework is defined in three levels; data, design model, modeling language. The data level represents real-world products, The model level describes design models of real-world products. The modeling language level defines concepts and relationships to describe product design models. The concepts and relationships in the modeling language level enable engineers to express the semantics of product models in an engineering-friendly way. The interactions between these three levels are explained to show how the framework can manage long-term lifecycle product information. A prototype system is provided for further understanding of the framework.

• ETRI Journal
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• v.39 no.2
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• pp.202-212
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• 2017

With the advent of the Internet-of-Things paradigm, the amount of data production has grown exponentially and the user demand for responsive consumption of data has increased significantly. Herein, we present DART, a fast and lightweight stream processing framework for the IoT environment. Because the DART framework targets a geospatially distributed environment of heterogeneous devices, the framework provides (1) an end-user tool for device registration and application authoring, (2) automatic worker node monitoring and task allocations, and (3) runtime management of user applications with fault tolerance. To maximize performance, the DART framework adopts an actor model in which applications are segmented into microtasks and assigned to an actor following a single responsibility. To prove the feasibility of the proposed framework, we implemented the DART system. We also conducted experiments to show that the system can significantly reduce computing burdens and alleviate network load by utilizing the idle resources of intermediate edge devices.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.1329-1333
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• 2006

This paper proposes a framework for product development including hardware and software components. The framework provides separation of the hardware dependent software, an integrated product development process, and integration of software components with product configurations and product structures. In order to separates the hardware dependent software, the framework considers product configuration modules and engineering changes of associated hardware and software components. The proposed product development process integrates development of the hardware dependent software into the existing product development process. In order to integrates the hardware dependent software with product configurations and product structures, the framework represents software components by existing product data models in Product Data Management (PDM). The framework is applied to development of a robot system including hardware and software components in order to show its effectiveness.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.5
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• pp.173-178
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• 2014

Smart devices linked to high speed networks enable us to obtain location dependent data at anywhere and anytime. In this environment, a wireless data broadcast system can deal with enormous data request from a great number of clients effectively. In order to set up an efficient wireless data broadcast system, various data scheduling and indexing schemes have been proposed. However, a simulation framework to evaluate the schemes is not reported yet. In this paper, we design and develop a simulation framework for a wireless data broadcast system. The developed simulation framework can evaluate quickly a wireless data broadcast system and has scalability to adopt various data scheduling and indexing schemes for wireless data broadcasting.

• Ocean Systems Engineering
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• v.9 no.1
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• pp.79-95
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• 2019

The material analysis of an offshore structure is generally conducted in the contract design phase for the price quotation of a new offshore project. This analysis is conducted manually by an engineer, which is time-consuming and can lead to inaccurate results, because the data size from previous projects is too large, and there are so many materials to consider. In this study, the piping materials in an offshore structure are analyzed for contract design using a big data framework. The big data technologies used include HDFS (Hadoop Distributed File System) for data saving, Hive and HBase for the database to handle the saved data, Spark and Kylin for data processing, and Zeppelin for user interface and visualization. The analyzed results show that the proposed big data framework can reduce the efforts put toward contract design in the estimation of the piping material cost.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.1
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• pp.31-44
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• 2008

The 1st phase framework data implementation of National Geographic Information Systems (NGIS) used 1:5,000 digital map with 5 years updating period which is lacking in the latest information. This is a significant factor which hinders the use of framework data. This study proposed the efficient technical method of a location based object data management and system implementation for updating framework data. First, we did an object-oriented data modeling and database design using a location based features identifier(UFID: Unique Feature IDentifier). The second, we developed the system with various functions such as a location based UFID creation, input and output, a spatial and attribute data editing, an object based data processing using UML(Unified Modeling Language). Finally, we applied the system to the study area and got high quality data of 99% accuracy and 35% benefit effect of personnel expenses compare to the previous method. We expect that this study can contribute to the maintenance of national framework data as well as the revitalization of various GIS markets by providing user the latest framework data and that we can develop the methods of a feature-change modeling and monitoring using an object based data management.

• The Journal of Bigdata
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• v.1 no.2
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• pp.1-8
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• 2016

User activity log includes lots of hidden information, however it is not structured and too massive to process data, so there are lots of parts uncovered yet. Especially, it includes time series data. We can reveal lots of parts using it. But we cannot use log data directly to analyze users' behaviors. In order to analyze user activity model, it needs transformation process through extra framework. Due to these things, we need to figure out user activity model analysis framework first and access to data. In this paper, we suggest a novel framework model in order to analyze user activity model effectively. This model includes MapReduce process for analyzing massive data quickly in the distributed environment and data architecture design for analyzing user activity model. Also we explained data model in detail based on real online service log design. Through this process, we describe which analysis model is fit for specific data model. It raises understanding of processing massive log and designing analysis model.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.4
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• pp.147-154
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• 2023

With the recent popularity of smartphones, many games are being developed on mobile-based platforms. As a result, it has brought about many changes in the way mobile game is developed. Especially mobile platforms, which are divided into Android and IOS, can now be applied to each platform without additional development through cross-platform. This means that it is necessary to move away from the method of developing each using separate development tools and implement the development process through cross-platform unique features. In this paper, we studied various methods to increase the productivity and quality of game development for the development of mobile games, and a formal framework considering the development process was developed. The framework consists of process, development domain, and platform support parts, each playing its own role. Items of the detailed framework must be reflected so that detailed response data for efficient application of game development can be established in actual mobile game development. The framework was developed by approaching it from two domains, the need for a framework and the framework implementation of key item response data.

• Journal of Computing Science and Engineering
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• v.2 no.3
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• pp.221-248
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• 2008

Data provenance is the background knowledge that enables a piece of data to be interpreted and used correctly within context. The importance of tracking provenance is widely recognized, as witnessed by significant research in various areas including e-science, homeland security, and data warehousing and business intelligence. In order to further advance the research on data provenance, however, one must first understand the research that has been conducted to date and identify specific topics that merit further investigation. In this work, we develop a framework based on semiotics theory to assist in analyzing and comparing existing provenance research at the conceptual level. We provide a detailed review of data provenance research and compare and contrast the research based on d semiotics framework. We conclude with an identification of challenges that will drive future research in this field.