• The Journal of the Korea Contents Association
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• v.13 no.2
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• pp.32-43
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• 2013

These days, there are more and more IT research institutions which foresee cloud services as the predominant IT service in the near future and there, in fact, are actual cloud services provided by some IT leading vendors. Regardless of physical location of the service and environment of the system, cloud service can provide users with storage services, usage of data and software. On the other hand, cloud service has challenges as well. Even though cloud service has its edge in terms of the extent to which the IT resource can be freely utilized regardless of the confinement of hardware, the availability is another problem to be solved. Hence, this paper is dedicated to tackle the aforementioned issues; prerequisites of cloud computing for distributed file system, open source based Hadoop distributed file system, in-memory database technology and high availability database system. Also the author tries to body out the high availability mass distributed data management architecture in cloud service's perspective using currently used distributed file system in cloud computing market.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.1 s.307
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• pp.53-66
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• 2006

This paper proposes the combined image retrieval system that gives the same relevance as exhaustive search method while its performance can be considerably improved. This system is combined with two different retrieval methods and each gives the same results that full exhaustive search method does. Both of them are two-stage method. One uses condensation of feature vectors, and the other uses binary-tree clustering. These two methods extract the candidate images that always include correct answers at the first stage, and then filter out the incorrect images at the second stage. Inasmuch as these methods use equal algorithm, they can get the same result as full exhaustive search. The first method condenses the dimension of feature vectors, and it uses these condensed feature vectors to compute similarity of query and images in database. It can be found that there is an optimal condensation ratio which minimizes the overall retrieval time. The optimal ratio is applied to first stage of this method. Binary-tree clustering method, searching with recursive 2-means clustering, classifies each cluster dynamically with the same radius. For preserving relevance, its range of query has to be compensated at first stage. After candidate clusters were selected, final results are retrieved by computing similarities again at second stage. The proposed method is combined with above two methods. Because they are not dependent on each other, combined retrieval system can make a remarkable progress in performance.

• The Journal of the Korea Contents Association
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• v.12 no.2
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• pp.30-39
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• 2012

In these day, some of IT venders already were going to cloud computing market, as well they are going to expand their territory for the cloud computing market through that based on their hardware and software technology, making collaboration between hardware and software vender. Distributed file system is very mainly technology for the cloud computing that must be protect performance and safety for high levels service requests as well data store. This paper introduced distributed file system for cloud computing and how to use this theory such as memory database, Hadoop file system, high availability database system. now In the market, this paper define a very large distributed processing architect as a reference by kind of distributed file systems through using technology in cloud computing market.

• Journal of Biomedical Engineering Research
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• v.25 no.6
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• pp.617-621
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• 2004

In recent, researchers in the field of Bioinformatics need to analyze thousands of genome sequences efficiently according to introduce of new analysis methods and technologies such as genome expression microchip. This rapid growth in the field of bio-engineering needs computing resources to analyze rapidly for genome sequences, but it does not introduce the computing resources due to an enormous investment expense. The core factor of this study is integrated environment based PC-Cluster system & high speed access rate up to 155Mbps, continuous collection system for bio-information at home and abroad. The results of the study are establishment & stabilization of information and communication infrastructure, establishment & stabilization of high performance computer network up to 155Mbps, development of PC-Cluster system with 32 nodes, a parallel BLAST on Cluster system, which can provides scalable speedup in terms of response time, and development of collection & search system for bio-information.

• Journal of the Korea Society of Computer and Information
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• v.19 no.12
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• pp.11-19
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• 2014

In this paper, we design an intelligent agent system with the data mining module and information fusion module as the core components of the system and investigate the possibility for the medical expert system. In the data mining module, fuzzy neural network, OFUN-NET analyzes multi-view data and produces fuzzy cluster knowledge base. In the information fusion module and application module, they serve the diagnosis result with possibility degree and useful information for diagnosis, such as uncertainty decision status or detection of asymmetry. We also present the experiment results on the BI-RADS-based feature data set selected form DDSM benchmark database. They show higher classification accuracy than conventional methods and the feasibility of the system as a computer aided diagnosis system.

• The KIPS Transactions:PartD
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• v.16D no.6
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• pp.845-850
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• 2009

Use of XML data has been increased with growth of Web 2.0 environment. XML is recognized its advantages by using based technology of RSS or ATOM for transferring information from blogs and news feed. Bitmap clustering is a method to keep index in main memory based on Relational DBMS, and which performed better than the other XML indexing methods during the evaluation. Existing method generates too many clusters, and it causes deterioration of result of searching quality. This paper proposes k-Bitmap clustering method that can generate user defined k clusters to solve above-mentioned problem. The proposed method also keeps additional inverted index for searching excluded terms from representative bits of k-Bitmap. We performed evaluation and the result shows that the users can control the number of clusters. Also our method has high recall value in single term search, and it guarantees the searching result includes all related documents for its query with keeping two indices.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2007.11a
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• pp.892-898
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• 2007

This study aims to implement an efficient process management system for small and medium sized(local) construction companies and a performance management system for the Korean construction industry. The process management system by Lean Construction is Web 2.0 platform-based and creates clusters with numerous general contractors and sub-contractors, which will enable mutually organic process management. Plus, this system will enable them to compare project performance management by analyzing it during or after a project by collecting and accumulating lots of data occurring in pursuit of a project. These performance management cases will be of help in process planning during similar upcoming projects. This study is expected to somewhat reduce the burden of implementing a complicated process management protocol and system that Korean small and medium sized (local) construction companies experience with their web-based process management, and is supposed to realize accurate performance management with highly reliable data which are significantly accumulated within the database.

• The Journal of the Korea Contents Association
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• v.11 no.3
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• pp.26-35
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• 2011

In these days, internet environment are very quickly development as well on-line service have been using a online for the mission critical business around the world. As the amount of information to be processed by computers has recently been increased there has been cluster computing systems developed by connecting workstations server using high speed networks for high availability. but cluster computing technology are limited for a lot of IT resources. So, grid computing is an expanded technology of distributed computing technology to use low-cost and high-performance computing power in various fields. Although the purpose of Grid computing focuses on large-scale resource sharing, innovative applications, and in some case, high-performance orientation, it has been used as conventional distributed computing environment like clustered computer until now because grid middleware does not have common sharable information system. In order to use grid computing environment efficiently which consists of various grid middleware, it is necessary to have application-independent information system which can share information description and services, and expand them easily. This paper proposed new database architecture and load balancing for high availability through Grid technology.

• Journal of the Korea Society of Computer and Information
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• v.16 no.3
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• pp.89-97
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• 2011

In semantic web information system like ontology that access distributed information from network, efficient query processing requires an advanced caching mechanism to reduce the query response time. P2P network system have become an important infra structure in web environment. In P2P network system, when the query is initiated, reducing the demand of data transformation to source peer is important aspect of efficient query processing. Caching of query and query result takes a particular advantage by adding or removing a query term. Many of the answers may already be cached and can be delivered to the user right away. In web environment, semantic caching method has been proposed which manages the cache as a collection of semantic regions. In this paper, we propose the semantic caching technique in cluster environment of peers. Especially, using schema data filtering technique and schema similarity cache replacement method, we enhanced the query processing efficiency.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.491-493
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• 2017

본 논문에서는 PCM 알고리즘을 적용하여 한국인 고유의 신체적 특성에 맞는 한의학 기반의 한방 자가 진단 시스템을 제안한다. 제안된 방법은 사용자로부터 입력받은 각 증상들에 가중치를 설정한다. 입력받은 증상의 개수가 많아질 경우에는 해당되지 않는 질병이 도출되기 때문에 각 증상 클러스터의 가중치를 낮게 설정하여 적은 입출력 변화에도 전체 결과의 신뢰도에 영향을 주지 않도록 한다. 입력 데이터와 가중치를 기반으로 하여 이미 학습된 질병의 증상과 비교한 후, 유사도가 높은 상위 5개의 질병을 도출한다. 도출된 상위 5개의 질병과 도출된 질병의 원인과 민간요법을 제공한다. 질병과 증상에 대한 데이터베이스는 여러 한의학 서적을 통해 구축한 후, 한의학 전문의의 검증을 거쳐 구현하였다. 제안된 한방 자가 진단 시스템은 진료 기록을 바탕으로 증상을 학습함으로써 기존의 질병 진단 시스템 보다 다양한 증상에 대한 질병 정보를 제공할 수 있는 것으로 확인되었다.