• The KIPS Transactions:PartD
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• v.11D no.5
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• pp.1143-1148
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• 2004

To develop multi-tier model or distributed architecture based distributed application needs to consider various aspects such as division of role between web-designer and software developer, defining entity and its usage, database connection and transaction processing etc. This paper presents DONSL(Data Server of Non SQL-Query) architecture that provides solution to above aspects through web-tier object modeling. This is the architecture that guarantees the transaction processing and performance between web-tier and DBMS through simplified usage of query logic property. This new conceptual framework also solves enterprise site implementation problems simplifying tier, and removing DAO(Data Access Object) and entity.

• Journal of the Korean Society for Library and Information Science
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• v.32 no.3
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• pp.179-206
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• 1998

The purpose of this study is to discuss the theoretical and practical strategies for the quality management of a union database built in a distributed system. To the end, this study introduces the quality control methods employed for the OCLC union catalog, which has been built in a distributed system and also known as the most typical union DB. The main discussion is about the quality issue of KORDIC's SATURN DB, the most typical union DB in South Korea. The final recommendation includes the management strategies and practical guidelines for the efficient quality control of a union DB built in a distributed system.

• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.135-146
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• 2023

An effective educational program warrants the inclusion of an innovative construction which enhances the higher education efficacy in such a way that accelerates the achievement of desired results and reduces the risk of failures. Educational Decision Support System (EDSS) has currently been a hot topic in educational systems, facilitating the pupil result monitoring and evaluation to be performed during their development. Insufficient information systems encounter trouble and hurdles in making the sufficient advantage from EDSS owing to the deficit of accuracy, incorrect analysis study of the characteristic, and inadequate database. DMTs (Data Mining Techniques) provide helpful tools in finding the models or forms of data and are extremely useful in the decision-making process. Several researchers have participated in the research involving distributed data mining with multi-agent technology. The rapid growth of network technology and IT use has led to the widespread use of distributed databases. This article explains the available data mining technology and the distributed data mining system framework. Distributed Data Mining approach is utilized for this work so that a classifier capable of predicting the success of students in the economic domain can be constructed. This research also discusses the Intelligent Knowledge Base Distributed Data Mining framework to assess the performance of the students through a mid-term exam and final-term exam employing Multi-agent system-based educational mining techniques. Using single and ensemble-based classifiers, this study intends to investigate the factors that influence student performance in higher education and construct a classification model that can predict academic achievement. We also discussed the importance of multi-agent systems and comparative machine learning approaches in EDSS development.

• Journal of Internet Computing and Services
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• v.8 no.3
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• pp.131-143
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• 2007

The current trends in information technology and intelligent systems use data mining techniques to discover patterns and extract rules from distributed databases. In distributed environment, the extracted rules from data mining techniques can be used in dynamic replications, adaptive load balancing and other schemes. However, transmission of large data through the system can cause errors and unreliable results. This paper proposes the intelligent distributed platform based on dynamic group binding using mobile agents which addresses the use of intelligence in distributed environment. The proposed grouping service implements classification scheme of objects. Data compressor agent and data miner agent extracts rules and compresses data, respectively, from the service node databases. The proposed algorithm performs preprocessing where it merges the less frequent dataset using neuro-fuzzy classifier before sending the data. Object group classification, data mining the service node database, data compression method, and rule extraction were simulated. Result of experiments in efficient data compression and reliable rule extraction shows that the proposed algorithm has better performance compared to other methods.

• Journal of the Korea Society of Computer and Information
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• v.13 no.7
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• pp.199-205
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• 2008

The centralized conference model has advantage of conference management and control. however it's scalability has been limited as performance degrades largely with increasing number of conference users. So new distributed conference models which improve scalability of centralized conference model have been suggested recently. In the distributed conference model. as conference users exceed a predefined maximum number, a new conference server is added to the conference dynamically. In this paper, We have proposed a new method which increases efficiency of conference event package processing that primary conference server should charge in the distributed conference environment. The primary conference server exchanges informations with each secondary conference servers and conference users by using conference event package. And from the conference information database it selects SIP(Session Initiation Protocol) UA(User Agent) which will share notification to the conference users, and transfers lists to each conference servers. The conference servers make the selected UAs share processing of conference event package, so loads of SIP signal processing decrease, and improve scalability of distributed conference model. The performance of our proposed model is evaluated by experiments.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.8
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• pp.1111-1115
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• 2014

With the increasing interest of a demand side management using a Smart Grid infrastructure, the demand resources and energy usage data management becomes an important factor in energy industry. In addition, with the help of Advanced Measuring Infrastructure(AMI), energy usage data becomes a Big Data System. Therefore, it becomes difficult to store and manage the demand resources big data using a traditional relational database management system. Furthermore, not many researches have been done to analyze the big energy data collected using AMI. In this paper, we are proposing a Hadoop based Big Data system to manage the demand resources energy data and we will also show how the demand side management systems can be used to improve energy efficiency.

• Journal of Korean Library and Information Science Society
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• v.30 no.3
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• pp.295-322
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• 1999

The purpose of this study is to identify and present the solution to the problems of KORMARC on Disc, which was produced by the National Library of Korea and is being distributed nationwide. Currently, KORMARC on Disc has reached the serious level of duplicates of input record, error on input data and noise of retrieval. Futhermore, input data is not in accordance with KORMARC Rules for Descriptive Cataloging, thus generating many problems. Of all thing, since current MARC system itself is based on manual system, it does not correspond effectively to the online environment. Accordingly, in order to elevate the quality of KORMARC database, current problems must be resolved, at the same time, korea Machine Readable Cataloging must be modified into a format, more suitable to Machine Readable environment. Consequently, the current study analyzes and identifies problems of data in KORMARC on Disc, at the same time, it examines currently used KORMARC Format and Korea machine Readable Cataloging Rules for descriptive Cataloging as to provide easier usage and guidelines for accurate data inputs.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10c
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• pp.191-194
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• 2007

본 논문에서는 분산형 환경에 적합한 새로운 의사결정나무 알고리즘을 제안하고 그 실용성을 확인하기 위해 분산형 데이터마이닝 시스템을 구현하였다. 그리고 본 논문에서 구현한 시스템을 평가하기 위해 데이터의 신뢰성이 높은 방대한 양의 미국의 인구통계 데이터(Census bureau database)를 사용하였다. 본 논문에서 구현한 시스템을 이용하여 신뢰성을 테스트하였고 그 결과가 다른 시스템의 알고리즘과 유사한 신뢰성을 나타내었다.

• The Journal of Information Technology and Database
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• v.8 no.2
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• pp.91-101
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• 2001

Previous research efforts on performance evaluation of multidimensional indexes typically have used synthetic data sets distributed uniformly or normally over multidimensional space. However, recent research research result has shown that these hinds of data sets hardly reflect the characteristics of multimedia database applications. In this paper, we discuss issues on generating high dimensional data and query sets for resolving the problem. We first identify the features of the data and query sets that are appropriate for fairly evaluating performances of multidimensional indexes, and then propose HDDQ_Gen(High-Dimensional Data and Query Generator) that satisfies such features. HDDQ_Gen supports the following features : (1) clustered distributions, (2) various object distributions in each cluster, (3) various cluster distributions, (4) various correlations among different dimensions, (5) query distributions depending on data distributions. Using these features, users are able to control tile distribution characteristics of data and query sets. Our contribution is fairly important in that HDDQ_Gen provides the benchmark environment evaluating multidimensional indexes correctly.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.10a
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• pp.275-278
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• 1996

We propose dynamic file allocation method in distributed database management system with changing access patterns. There are a lot of studies on file allocation problem in D-DBMS, and those studies deal with off-line analysis and optimization. Those works are well for systems with static database access patterns, but are inadequate for systems that have changing access patterns. In these systems, dynamic file allocation along with access pattern is more proper. In advance, Brunstrom et al. studied on this area, but they dealt a extremely simplified model. So, we make more practical models to simulate real system. In these models, many factors that were disregard in the advance study are considered. These models are composed with the non-replication system and the replication system. In addition to, we deal with CPU workload balancing in such system in order to improve performance of systems. Our methodology is very simple and realistic, therefore we think that it will give a lot of improvement in D-DBMS with changing access pattern.