• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.39-39
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• 2012

Data assimilation techniques have received growing attention due to their capability to improve prediction in various areas. Despite of their potentials, applicable software frameworks to probabilistic approaches and data assimilation are still limited because the most of hydrologic modelling software are based on a deterministic approach. In this study, we developed a hydrological modelling framework for sequential data assimilation, namely MPI-OHyMoS. MPI-OHyMoS allows user to develop his/her own element models and to easily build a total simulation system model for hydrological simulations. Unlike process-based modelling framework, this software framework benefits from its object-oriented feature to flexibly represent hydrological processes without any change of the main library. In this software framework, sequential data assimilation based on the particle filters is available for any hydrologic models considering various sources of uncertainty originated from input forcing, parameters and observations. The particle filters are a Bayesian learning process in which the propagation of all uncertainties is carried out by a suitable selection of randomly generated particles without any assumptions about the nature of the distributions. In MPI-OHyMoS, ensemble simulations are parallelized, which can take advantage of high performance computing (HPC) system. We applied this software framework for several catchments in Japan using a distributed hydrologic model. Uncertainty of model parameters and radar rainfall estimates is assessed simultaneously in sequential data assimilation.

• Journal of Information Science Theory and Practice
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• v.12 no.3
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• pp.49-62
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• 2024

Strategy monitoring is essential for business management and for administrators, including managers and executives, to build a data-driven organization. Having a tool that is able to visualize strategic data is significant for business intelligence. Unfortunately, there are gaps between business users and information technology departments or business intelligence experts that need to be filled to meet user requirements. For example, business users want to be self-reliant when using business intelligence systems, but they are too inexperienced to deal with the technical difficulties of the business intelligence systems. This research aims to create an automatic matching framework between the key performance indicators (KPI) formula and the data in database systems, based on ontology concepts, in the case study of Prince of Songkla University. The mapping data schema with ontology (MapDSOnto) framework is created through knowledge adaptation from the literature review and is evaluated using sample data from the case study. String similarity methods are compared to find the best fit for this framework. The research results reveal that the "fuzz.token_set_ratio" method is suitable for this study, with a 91.50 similarity score. The two main algorithms, database schema mapping and domain schema mapping, present the process of the MapDS-Onto framework using the "fuzz.token_set_ratio" method and database structure ontology to match the correct data of each factor in the KPI formula. The MapDS-Onto framework contributes to increasing self-reliance by reducing the amount of database knowledge that business users need to use semantic business intelligence.

• 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.

• Nuclear Engineering and Technology
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• v.56 no.11
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• pp.4578-4586
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• 2024

Human reliability analysis (HRA) of nuclear research reactors often encounters a lack of human performance data, a challenge that is also faced by the TRIGA reactor of Thailand having no specific full method or human error database for HRA. To overcome this challenge, in 2023, HRA teams from the Korea Atomic Energy Research Institute (KAERI) and the Thailand Institute of Nuclear Technology (TINT) jointly developed an HRA framework for the TRIGA reactor. In the HRA framework development, the HRA practitioners applied KAERI's three main HRA tools, namely 1) the EMpirical data-Based crew Reliability Assessment and Cognitive Error analysis (EMBRACE) method, 2) the Human Reliability data EXtraction (HuREX) database, and 3) the TAsk COMplexity (TACOM) method. The HRA framework covers the overall process including the classification of documents and human error types as well as nominal human error extraction for estimating nominal human error probabilities. According to the results of the first use of the HRA framework on the TRIGA reactor in Thailand, the HRA framework provided an effective way to improve the procedures and systematically identify nominal human errors of actions in the emergency procedures.