• Proceedings of the Korea Society for Industrial Systems Conference
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• 2007.02a
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• pp.163-167
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• 2007

We propose an XML document storage system, called XDMS (XML Document Management System), by using an object-relational DBMS. XDMS generates object database schema from XML Schema and stores the XML documents in an object-relational database. SAX parser is used for understanding the structure of the XML documents, and XDMS transforms the documents into objects in the database. Experiment shows that object-relational databases provide more efficient storage and query model compared with relational databases.

• Journal of the Korean Operations Research and Management Science Society
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• v.20 no.2
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• pp.139-158
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• 1995

A temporal database systems provides timing information and maintains history of data compared to the conventional database system. In this paper, we present a temporal relational database which use an interval-stamping method for instant-based events and for interval-based states. A set of temporal algebraic operators are developed on an instance of time and interval of time so that we can manipulate events and states at a same time. The set of operation is the basis for creating a relational algebra that is closed for temporal relations. And temporal SQL is also suggested as a temporal query relational language for our algebraic operations on temporal relations.

• Journal of the Korean Operations Research and Management Science Society
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• v.21 no.3
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• pp.197-214
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• 1996

Financial analysis of stock data usually involves extensive computation of large amount of time series data sets. To handle the large size of the data sets and complexity of the analyses, database management systems have been increasingly adaopted for efficient management of stock data. Specially, relational database management system is employed more widely due to its simplistic data management approach. However, the normalized two-dimensional tables and the structured query language of the relational system turn out to be less effective than expected in accommodating time series stock data as well as the various computational operations. This paper explores a new data management approach to stock data management on the basis of an object-oriented database management system (ODBMS), and proposes a data model supporting times series data storage and incorporating a set of financial analysis functions. In terms of functional stock data analysis, it specially focuses on a primitive set of operations such as variance of stock data. In accomplishing this, we first point out the problems of a relational approach to the management of stock data and show the strength of the ODBMS. We secondly propose an object model delineating the structural relationships among objects used in the stock data management and behavioral operations involved in the financial analysis. A prototype system is developed using a commercial ODBMS.

• Journal of the Korean Operations Research and Management Science Society
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• v.13 no.2
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• pp.73-73
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• 1988

Knapsack problems represent many business application such as cargo loading, project selection, and capital budgeting. In this research we developed a knapsack problem solver based on Martello-Toth algorithm using a relational database management system on the PC platform. The solver used the menu-driven user interface. The solver can be easily integrated with the database of decision support system because the solver can access the database to retrieve the data for the model and to store the result directly.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.5
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• pp.257-265
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• 2004

The complex documentation involved in power system analysis software require a well-defined and friendly database system. We have developed an object-oriented database management system for power system analysis, and have described load flow analysis and transient stability analysis using object-oriented database(OODB). Database management systems are widely used and achieve high reliability of data management in the engineering fields. However relational database system have shortcomings in application to power system analysis. ill relational database, the data model is too simple for modeling complex data and database languages are very different from programming languages. Object-oriented techniques are sufficiently powerful to support data-modeling requirements of GUI applications. The GUI is implemented using C++ on a MS windows platform. The OODB supports data modeling requirements of GUI applications and the performance is well acceptable for Gill applications.

• Korean Management Science Review
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• v.13 no.2
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• pp.73-94
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• 1996

Knapsack problems represent many business application such as cargo loading, project selection, and capital budgeting. In this research we developed a knapsack problem solver based on Martello-Toth algorithm using a relational database management system on the PC platform. The solver used the menu-driven user interface. The solver can be easily integrated with the database of decision support system because the solver can access the database to retrieve the data for the model and to store the result directly.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1998.10a
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• pp.395-400
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• 1998

This paper presents a geotechnical information system(HGIS) developed for Korea Highway Corporation. To make a database for boring information, characterization study of boring data is carried out. Based on tile study, the HGIS database is developed as a relational database. The HGIS database consists of 23 tables including 13 reference tables. For an effective database management, a boring log program called GEOLOG is developed. GEOLOG can print boring log and store those data to tile HGIS database.

• Journal of the Korea Society for Simulation
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• v.11 no.2
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• pp.55-66
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• 2002

VHDL has been. widely used in modeling and simulation of hardware designs. However, complex relationship between components of the designs makes the VHDL modeling problem very difficult. Furthermore, after the initial creation of VHDL models, they evolve into many versions over their lifetime. To cope with such difficulties, this paper proposes a new methodology for the management of VHDL models supporting versions. Its conceptual bases are system entity structure and relational database. Within the methodology, a family of hierarchical structures of a design is organized in the form of VHDL model structure. It is, in turn, represented in the form of relational tables. Once the model structure is built in such a way, a specific simulation model which meets design objective is pruned from the model structure. The details of VHDL codes are systematically synthesized by combining it with the primitive models in a model base. These algorithms are also defined in terms of relational algebraic operations.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.3
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• pp.469-476
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• 2016

Relational Database Management Systems have become de facto database model among most developers and users since the inception of Data Science. From IoT devices, sensors, social media and other sources, data is generated in structured, semi-structured and unstructured formats, in huge volumes, thereby the difficulty of data management greatly increases. Organizations that collect large amounts of data are increasingly turning to non relational databases - NoSQL databases. In this paper, through experiments with real field data, we demonstrate that MongoDB, a document-based NoSQL database, is a better alternative for building a Telco Subscriber Data Management System which hitherto is mainly built with Relational Database Management Systems. We compare the existing system in various phases of data flow with our proposed system powered by MongoDB. We show how various workloads at some phases of the existing system were either completely removed or significantly simplified on the new system. Based on experiment results, using MongoDB for managing telco subscriber data turned out to offer performance better than the existing system built with MSSQL Server.

• Water Engineering Research
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• v.5 no.4
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• pp.157-176
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• 2004

This research presents a prototype development and implementation of Decision Support System (DSS) for integrated river basin water management for the flood control. The DSS consists of Relational Database Management System, Hydrologic Data Monitoring System, Spatial Analysis Module, Spatial and Temporal Analysis for Rainfall Event Tool, Flood Forecasting Module, Real-Time Operation of Multi Reservoir System, and Dialog Module with Graphical User Interface and Graphic Display Systems. The developed DSS provides an automated process of alternative evaluation and selection within a flexible, fully integrated, interactive, centered relational database management system in a user-friendly computer environment. The river basin decision-maker for the flood control should expect that she or he could manage the flood events more effectively by fully grasping the hydrologic situation throughout the basin.