• International conference on construction engineering and project management
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• 2013.01a
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• pp.648-651
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• 2013

The information generated in large-scale and complex construction projects are transferred continuously and transformed into project products on the long span life cycle. Therefore, information flow management is related with the success of project directly. However, certain characteristics of large-scale and complex construction projects make the solving the problem more difficultly. Although several information retrieval systems support the information management system, it is not suitable to grasp information flows. Hence, we developed an information retrieval system specialized with the information flow based on a preceding research. The system consists of a relation-based database and the process information transferring relation inference application module. The system enables project managers to manage the entire project process more efficiently and each project member to work their own task being served the information flow retrieval results.

• Proceedings of the KSR Conference
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• 2008.11b
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• pp.2121-2124
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• 2008

The total length of Korean railway network is about 3,300km. Since it is of great scale in system view point, the systemization of GIS-based information system requires so much cost and time. One of the difficulties is due to the fact that GIS-based information system requires the feature database for GIS, which is generally built manually from many as-built drawing files. In order to build-up the feature database for GIS with ease, this study suggests the automatic data conversion from electronic drawings to make feature database for GIS. The proposed method can be applied to build large-scale railway facility management system at lower cost.

• Proceedings of the Korean Society of Computer Information Conference
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• 2013.01a
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• pp.291-294
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• 2013

연관 규칙 감축 기법은 대규모 데이터를 사용하는 Socially aware computing분야에서 매우 중요한 이슈이다. 본 논문에서는 수집된 각종 데이터들을 각 속성 기준에 따라 이진 변환한 후 가중치를 부여하고 논리식 감축 방법을 이용하여 신뢰성을 보장하는 규칙을 도출하는 새로운 데이터 감축 기법을 제안한다. 이는 컴퓨터 시뮬레이션 결과 기존의 방식들에 비해 지지도, 신뢰도, 규칙 감소율, 연관 규칙 추출 시간에 좋은 성능을 보였으며 이는 빠른 시간 내에 신뢰성 높은 대규모 데이터 처리가 필요한 Socially aware computing분야에 적합하다고 판단한다.

• Journal of the Korea Society of Computer and Information
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• v.23 no.3
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• pp.49-54
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• 2018

A data warehouse is a system that collectively manages and integrates data of a company. And provides the basis for decision making for management strategy. Nowadays, analysis data volumes are reaching critical size challenging traditional data ware housing approaches. Current implemented solutions are mainly based on relational database that are no longer adapted to these data volume. NoSQL solutions allow us to consider new approaches for data warehousing, especially from the multidimensional data management point of view. In this paper, we extend the data warehouse design methodology based on relational database using star schema, and have developed a consistent design methodology from information requirement analysis to data warehouse construction for large scale data warehouse construction based on MongoDB, one of NoSQL.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.6
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• pp.781-788
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• 1999

In this paper, an expert system is proposed, which can be effectively applied to the large-scale systems with the diversity time constraints, the objectives and the unfixed system structure. The inference scheme of the expert system have the integrated structure composed of the intuitive inference module and logical inference module in order to support effectively the operating constraints of system. The intuitive inference module is designed using the pattern matching or pattern recognition method in order to search a same or similar pattern under the fixed system structure. On the other hand, the logical inference module is designed as the structure with the multiple inference mode based on the heuristic search method in order to determine the optimal or near optimal control strategies satisfing the time constraints for system events under the unfixed system structure, and in order to use as knowledge generator. Here, inference mode consists of the best-first, the local-minimum tree, the breadth-iterative, the limited search width/time method. Finally, the application results for large-scale distribution SCADA system proves that the inference scheme of the expert system is very effective for the large-scale system. The expert system is implemented in C language for the dynamic mamory allocation method, database interface, compatability.

• Journal of Information Processing Systems
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• v.18 no.3
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• pp.374-388
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• 2022

Database systems usually have many parameters that must be configured by database administrators and users. RocksDB achieves fast data writing performance using a log-structured merged tree. This database has many parameters associated with write and space amplifications. Write amplification degrades the database performance, and space amplification leads to an increased storage space owing to the storage of unwanted data. Previously, it was proven that significant performance improvements can be achieved by tuning the database parameters. However, tuning the multiple parameters of a database is a laborious task owing to the large number of potential configuration combinations. To address this problem, we selected the important parameters that affect the performance of RocksDB using random forest. We then analyzed the effects of the selected parameters on write and space amplifications using analysis of variance. We used a genetic algorithm to obtain optimized values of the major parameters. The experimental results indicate an insignificant reduction (-5.64%) in the execution time when using these optimized values; however, write amplification, space amplification, and data processing rates improved considerably by 20.65%, 54.50%, and 89.68%, respectively, as compared to the performance when using the default settings.

• The KIPS Transactions:PartD
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• v.10D no.6
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• pp.907-916
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• 2003

Database benchmarks require efficient of large-scale data. This presents the system architecture, control flows, and characteristics of the data generator we have developed. The data generator features generation of large-scale data, column-by-column data generation, a number of data distributions and verification, and real data generation. An extensive conparison with other data generators in terms of function is also presented. Finally, empirical performance experiments between RAID systems and non-RAID one have been conducted to alleviate I/O bottleneck. The test results can serve as guidelines to help confifure system architecture.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05b
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• pp.552-556
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• 2004

This paper surveys the design of the adaptive information filtering agents to retrieve the useful information within a large scale database. As the information retrieval through the Internet is generalized, it is necessary to extract the useful information satisfied the user's request condition to reduce the seeking time. For the first, this module is designed by the Rough reduct to generate the reduced minimal knowledge database considered the users natural query language in a large scale knowledge database, and also it is executed the soft computing by the fuzzy composite processing to operate the uncertain value of the reduced schema domain.

• Journal of KIISE:Databases
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• v.29 no.5
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• pp.347-357
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• 2002

Graphs have provided a powerful methodology to solve a lot of real-world problems, and therefore there have been many proposals on the graph representations and algorithms. But, because most of them considered only memory-based graphs, there are still difficulties to apply them to large-scale problems. To cope with the difficulties, this paper proposes a graph representation and graph algorithms based on the well-developed relational database theory. Graphs are represented in the form of relations which can be visualized as relational tables. Each vertex and edge of a graph is represented as a tuple in the tables. Graph algorithms are also defined in terms of relational algebraic operations such as projection, selection, and join. They can be implemented with the database language such as SQL. We also developed a library of basic graph operations for the management of graphs and the development of graph applications. This database approach provides an efficient methodology to deal with very large- scale graphs, and the graph library supports the development of graph applications. Furthermore, it has many advantages such as the concurrent graph sharing among users by virtue of the capability of database.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2000.05a
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• pp.320-324
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• 2000

In this paper we propose and realize the large scale multimedia security system that one janitor control many rooms in many building on multimedia. We Study the system that one watch janitor lots of rooms and lots of buildings the same time, and store the trespasser's moving cource in Database for understanding his action pattern using computer vision technology, but the relational system cannot solve the problem that the trespasser disjoint the security system on sensing method and the system watch only one room or one building.