• Journal of Korean Society of Rural Planning
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• v.19 no.4
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• pp.319-327
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• 2013

The objective of this research was to develop a relational database management system(RDBMS) to collect, manage and analyze data on agricultural non-point source(NPS) pollution. The system consists of the relational database for agricultural NPS data and data process modules. The data process modules were composed of four sub-modules for data input, management, analysis, and output. The data collected from the watershed of the upper Cheongmi stream and Geunsam-Ri were used in this study. The database was constructed using Apache Derby with meteorological, hydrological, water quality, and soil characteristics. Agricultural NPS-Data Management System(ANPS-DMS) was developed using Oracle Java. The system developed in this study can deal with a variety of agricultural NPS data and is expected to provide an appropriate data management tool for agricultural NPS studies.

• 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.

• Journal of the Korea Society of Computer and Information
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• v.17 no.12
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• pp.169-177
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• 2012

In the development process of application systems, the most important works are analysis and design. Most of the application systems are implemented on database system. So, database design is important. Also, IT System are confronted with more and more attacks by an increase interconnections between IT systems. Therefore security-related processes belong to a very important process. Security is a complex non-functional requirement that can interaction of many parts in the system. But Security is considered in the final stages of development. Therefore, Their increases the potential for the final product to contain vulnerabilities. Accordingly, Early in development related to security analysis and design process is very important. J2EE gives a solution based on RBAC((Role Based Access Control) for security and object-relational database also has RBAC for security. But there is not a object-oriented analysis and design methodology using RBAC of J2EE and object-relational database for security. In this paper, the unified object-oriented analysis and design methodology is developed for security-critical web application systems based on J2EE and object-relational database. We used UMLsec and RBAC of object-relational database and J2EE for this methodology.

• Journal of Korean Society of Steel Construction
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• v.10 no.1 s.34
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• pp.37-45
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• 1998

The relational database system on fatigue strength was constructed, and the properties of fatigue life distribution were examined to analyze reliability and safety of metallic materials. Data manipulations were efficiently performed in relational fatigue strength database system using dependency diagram. Regardless of the distribution of fatigue strength, the proposed method, the Robust method and the complementary error function method using probability distribution, successfully estimated parameters of the 3-parameter Weibull distribution. The proposed criterion for estimating non-failure probability showed good results regardless of censoring time. The fatigue life distribution function described as a function of parameters of the Weibull distribution and applied stress ratio produced P-S-N characteristics reasonably.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.384-387
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• 2003

Most of the real world phenomena change over time. The ability to represent and to reason geographic data becomes crucial. A large amount of non-standard applications are dealing with data characterized by spatial, temporal and/or uncertainty features. Non-standard data like spatial and temporal data have an inner complex structure requiring sophisticated data representation, and their operations necessitate sophisticated and efficient algorithms. Current GIS technology is inefficient to model and to handle complex geographic phenomena, which involve space, time and uncertainty dimensions. This paper concentrates on developing a fuzzy spatio-temporal data model based on fuzzy set theory and relational data models. Fuzzy spatio-temporal operators are also provided to support dynamic query.

• Journal of the Korean Association of Geographic Information Studies
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• v.4 no.4
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• pp.21-28
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• 2001

In this study, GNLP(GIS linked non-linear network analysis program) for pipeline system analysis has been developed. This GNLP gets the input data for pipeline analysis from existing GIS(geographic information system) data automatically, and has GUI(graphic user interface) for user. Non-Linear Method was used for hydraulic analysis of pipe network based on Hazen-Williams equation, and Microsoft Access of relational database management system(RDBMS) was used for the framework of database applied program. GNLP system environment program was improved so that a pipe network designer can input information data for hydraulic analysis of pipeline system more easily than that of existing models. Furthermore this model generate output such as pressure and water quantities in the form of a table and a chart, and also produces output data in Excel file. This model is also able to display data effectively for analysed data confirmation and query function which is the core of GIS program.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.11a
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• pp.325-327
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• 2008

In electrical industry, classification methodology has been an important issue for analyzing power consumption patterns. It has many applications including decisions on energy purchasing, load switching as well as helping in infrastructure development. Our aim in this work is to classify the electrical section and find potentially non-safe electrical sections. For this purpose, we use Emerging Patterns based classification. The classification method uses the aggregate score of emerging patterns to build classifier. The proposed methodology was applied to a set of electrical section data of the Korea power. The test data and relational electricity information and knowledge are supported by Korea Electric Power Research Institute (KEPRI).

• Journal of the Korean Institute of Intelligent Systems
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• v.3 no.1
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• pp.65-75
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• 1993

Fuzzy data is a phenomenon often occurring in real life. There is the inherent vagueness of classification terms referring to a continuous scale, the uncertainty of linguistic terms such as "I almost agree" or the vagueness of terms and concepts due to the statistical variability in communication [20] and many more. Previously, such fuzzy data was approximated by non-fuzzy (crisp) data, which obviously did not lead to a correct and precise representation of the real world. Fuzzy set theory has been developed to represent and manipulate fuzzy data [18]. Explicitly managing the degree of fuzziness in databases allows the system to distinguish between what is known, what is not known and what is partially known. Systems in the literature whose specific objective is to handle imprecision in databases present various approaches. This paper is concerned with the different ways uncertainty and imprecision are handled in database design. It outlines the major areas of fuzzification in (relational) database systems.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.04a
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• pp.153-156
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• 2005

In this paper, a framework for implementing UFIS (Unified Fuzzy rule-based knowledge Inference System) is presented. First, fuzzy clustering and fuzzy rules deal with the presence of the knowledge in DB (DataBase) and its value is presented with a value between 0 and 1. Second, RDB (Relational DB) and SQL queries provide more flexible functionality fur knowledge management than the conventional non-fuzzy knowledge management systems. Therefore, the obtained fuzzy rules offer the user additional information to be added to the query with the purpose of guiding the search and improving the retrieval in knowledge base and/ or rule base. The framework can be used as DM (Data Mining) and ES (Expert Systems) development and easily integrated with conventional KMS (Knowledge Management Systems) and ES.

• Journal of the Korea Society of Computer and Information
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• v.4 no.4
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• pp.47-56
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• 1999

We design and implement an ORDBMS-based geographic information system for sightseeing information of Chungbuk to verify the performance and applicability of GEUS/XTM ORDBMS. We Acquire the positional coordinates of the boundaries of administrative districts , roads, and railroads, determine the various kinds of information such as the locations of sightseeing sites, lodgings, and so on, design an object-relational schema using OMT, and implement the geographic information system including a database system. Through the examination of selective accessibility on the sightseeing inform ation database by the various queries, we conclude that the ORDBMS is more applicable than other DBMSs in modeling, storing, referring, and managing of non-fixed complex data such as sightseeing information. Therefore, ORDBMSs provide efficient and extensible implementations of databases and information services from various sources for the increasing demand on geographic information service on internet.