• Journal of KIISE:Databases
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• v.37 no.3
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• pp.127-136
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• 2010

With rapid growth of information and computer communication technologies, the numbers of digital documents including multimedia data have been recently exploded. In particular, news video database and news video mining have became the subject of extensive research, to develop effective and efficient tools for manipulation and analysis of news videos, because of their information richness. However, many research focus on browsing, retrieval and summarization of news videos. Up to date, it is a relatively early state to discover and to analyse the plentiful latent semantic knowledge from news videos. In this paper, we propose the news video mining system based on multi-modal approach and text mining, which uses the visual-textual information of news video clips and their scripts. The proposed system systematically constructs a taxonomy of news video stories in automatic manner with hierarchical clustering algorithm which is one of text mining methods. Then, it multilaterally analyzes the topics of news video stories by means of time-cluster trend graph, weighted cluster growth index, and network analysis. To clarify the validity of our approach, we analyzed the news videos on "The Second Summit of South and North Korea in 2007".

• Journal of KIISE:Databases
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• v.32 no.1
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• pp.56-70
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• 2005

The results of location-dependent queries(LDQ) generally depend on the current locations of query issuers. Many mechanisms, e.g. broadcast scheme, hoarding, or racking policy, have been developed to improve the system peformance and provide better services, which are specialized for LDQs. Considering geographical adjacency of data and characteristics oi target area, caching policy and broadcast scheme affect the overall performance in LDQ. For this reason, we propose both the caching policy and broadcast scheme, which these features are reflected in. Based on the adjacency of data in LDQ, our broadcast scheme use Hilbert curve to cluster data. Moreover, in order to develop the caching policy suitable for LDQ on urban area, we apply the moving distance of a MH(Mobile Host) to our caching policy We evaluate the performance of the caching policy measuring the workload of MHs and the correctness of LDQ results and the performance of the broadcast scheme measuring the average setup-time of MHs in our experiments. Finally, we expect that our caching policy Provides more correct answers when executing LDQ in focal cache and leads significant improvement of the performance of MHs. It also seems quite probable that our broadcast scheme leads improvement of battery life of the MH.

• Journal of KIISE:Databases
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• v.31 no.3
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• pp.261-273
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• 2004

Advances in information and communication technologies have been creating new classes of applications in the area of databases. For example, in moving object databases, which track positions of a lot of objects, or stream databases, which process data streams from a lot of sensors, data Processed in such database systems are usually changed very rapidly and continuously. However, traditional database systems have a problem in processing these rapidly and continuously changing data because they suppose that a data item stored in the database remains constant until It is explicitly modified. The problem becomes more serious in the R-tree, which is a typical index structure for multidimensional data, because modifying data in the R-tree can generate cascading node splits or merges. To process frequent updates more efficiently, we propose a novel update technique for the R-tree, which we call the leaf-update technique. If a new value of a data item lies within the leaf MBR that the data item belongs, the leaf-update technique changes the leaf node only, not whole of the tree. Using this leaf-update manner and the leaf-access hash table for direct access to leaf nodes, the proposed technique can reduce update cost greatly. In addition, the leaf-update technique can be adopted in diverse variants of the R-tree and various applications that use the R-tree since it is based on the R-tree and it guarantees the correctness of the R-tree. In this paper, we prove the effectiveness of the leaf-update techniques theoretically and present experimental results that show that our technique outperforms traditional one.

• Korean Journal of Remote Sensing
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• v.31 no.6
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• pp.561-570
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• 2015

Till now, applications of many kinds of satellite images have been accentuated in the datacentric scientific studies, researches regarding system development and concerned technologies for them are on the un-matured stage. Especially, satellite image processing requires large volume data handling and specific analysis functionalities, so that practical necessity of base study for system development is emphasized on. In the view of information system, various edged trends such as web standards, cloud computing, or web framework are utilized owing to their application benefits proven and business needs. Considered these aspects, a testing implementation was carried out using OpenStack cloud computing environment and e-government framework. As for the processing functions, WPS in GeoServer, as one of OGC web standards, was applied to perform interoperable data processing scheme between two or more remote servers. Working with the server implemented, client-side was also developed using several open sources such as HTML 5, jQuery, and OpenLayers. If it is that completed further experiments onsite applications with actual multi-data sets and extension of on-demand functionalities with the result of this study, it will be referred as an example case model for complicated and complex system design and implementation which needs cloud computing, geo-spatial web standards and web framework.

• Horticultural Science & Technology
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• v.34 no.1
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• pp.102-111
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• 2016

The goal of this study was to characterize the BrDSR (Drought Stress Resistance in B. rapa) gene and to identify the expression network of drought-inducible genes in Chinese cabbage under drought stress. Agrobacterium-mediated transformation was conducted using a B. rapa inbred line ('CT001') and the pSL100 vector containing the BrDSR full length CDS (438 bp open reading frame). Four transgenic plants were selected by PCR and the expression level of BrDSR was approximately 1.9-3.4-fold greater than that in the wild-type control under drought stress. Phenotypic characteristics showed that BrDSR over-expressing plants were resistant to drought stress and showed normal growth habit. To construct a co-expression network of drought-responsive genes, B. rapa 135K cDNA microarray data was analyzed to identify genes associated with BrDSR. BrDSR was directly linked to DARK INDUCIBLE 2 (DIN2, AT3G60140) and AUTOPHAGY 8H (ATG8H, AT3G06420) previously reported to be leaf senescence and autophagy-related genes in plants. Taken together, the results of this study indicated that BrDSR plays a significant role in enhancement of tolerance to drought conditions.

• Journal of KIISE:Software and Applications
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• v.26 no.11
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• pp.1314-1323
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• 1999

컴퓨터의 사용이 일반화됨에 따라 데이타를 생성하고 수집하는 것이 용이해졌다. 이에 따라 데이타로부터 자동적으로 유용한 지식을 얻는 기술이 필요하게 되었다. 데이타 마이닝에서 얻어진 지식은 정확성과 이해성을 충족해야 한다. 본 논문에서는 데이타 마이닝을 위하여 퍼지 결정트리에 기반한 효율적인 퍼지 규칙을 생성하는 알고리즘을 제안한다. 퍼지 결정트리는 ID3와 C4.5의 이해성과 퍼지이론의 추론과 표현력을 결합한 방법이다. 특히, 퍼지 규칙은 속성 축에 평행하게 판단 경계선을 결정하는 방법으로는 어려운 속성 축에 평행하지 않는 경계선을 갖는 패턴을 효율적으로 분류한다. 제안된 알고리즘은 첫째, 각 속성 데이타의 히스토그램 분석을 통해 적절한 소속함수를 생성한다. 둘째, 주어진 소속함수를 바탕으로 ID3와 C4.5와 유사한 방법으로 퍼지 결정트리를 생성한다. 또한, 유전자 알고리즘을 이용하여 소속함수를 조율한다. IRIS 데이타, Wisconsin breast cancer 데이타, credit screening 데이타 등 벤치마크 데이타들에 대한 실험 결과 제안된 방법이 C4.5 방법을 포함한 다른 방법보다 성능과 규칙의 이해성에서 보다 효율적임을 보인다.Abstract With an extended use of computers, we can easily generate and collect data. There is a need to acquire useful knowledge from data automatically. In data mining the acquired knowledge needs to be both accurate and comprehensible. In this paper, we propose an efficient fuzzy rule generation algorithm based on fuzzy decision tree for data mining. We combine the comprehensibility of rules generated based on decision tree such as ID3 and C4.5 and the expressive power of fuzzy sets. Particularly, fuzzy rules allow us to effectively classify patterns of non-axis-parallel decision boundaries, which are difficult to do using attribute-based classification methods.In our algorithm we first determine an appropriate set of membership functions for each attribute of data using histogram analysis. Given a set of membership functions then we construct a fuzzy decision tree in a similar way to that of ID3 and C4.5. We also apply genetic algorithm to tune the initial set of membership functions. We have experimented our algorithm with several benchmark data sets including the IRIS data, the Wisconsin breast cancer data, and the credit screening data. The experiment results show that our method is more efficient in performance and comprehensibility of rules compared with other methods including C4.5.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.4
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• pp.284-288
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• 2009

With explosively growing PPI databases, the computational approach for a prediction and configuration of PPI network has been a big stream in the bioinformatics area. Recent researches gradually consider physicochemical properties of proteins and support high resolution results with integration of experimental results. With regard to current research trend, it is very close future to complete a PPI network configuration of each organism. However, direct applying the PPI network to real field is complicated problem because PPI network is only a set of co-expressive proteins or gene products, and its network link means simple physical binding rather than in-depth knowledge of biological process. In this paper, we suggest a protein functional flow model which is a directed network based on a protein functions' relation of signaling transduction pathway. The vertex of the suggested model is a molecular function annotated by gene ontology, and the relations among the vertex are considered as edges. Thus, it is easy to trace a specific function's transition, and it can be a constraint to extract a meaningful sub-path from whole PPI network. To evaluate the model, 11 functional flow models of Homo sapiens were built from KEGG, and Cronbach's alpha values were measured (alpha=0.67). Among 1023 functional flows, 765 functional flows showed 0.6 or higher alpha values.

• Journal of KIISE:Software and Applications
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• v.29 no.7
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• pp.476-486
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• 2002

CBD(Component Based Development) has become the best strategical method for the business application. Because CBD is a new development paradigm which makes it possible to assemble the software components for application, it copes with the rapid challenge of business process and meets the increasing requirements for productivity. Since the business process is rapidly changing, CBD technology is the promising way to solve the productivity. Especially, the repository is the most important part for the development, distribution and reuse of components. In component repository, we can store and manage the related work-products produced at each step of component development as well as component itself. In this paper, we suggested a practical approach for repository construction to support and realize the CBD process and developed the CRMS(Component Repository Management System) as implementation product of the proposed techniques. CRMS can manage a variety of component products based on component architecture, and help software developers to search a candidate component for their project and to understand a variety of information for the component. In the paper, a practical approach for component repository was suggested, and a supporting environment was constructed to make CBD to be working efficiently. We expect this work wall be valuable research for component repository and the entire supporting Component Based Development Process.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.4
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• pp.244-254
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• 2009

This paper describes a remote system to monitor the circadian behavioral patterns of elders who live alone. The proposed system was designed and implemented to provide more conveniently and reliably the required functionalities of a remote monitoring system for elders based on the development of first phase prototype[2]. The developed system is composed of an in-house sensing system and a server system. The in-house sensing system is a set of wireless sensor nodes which have pyroelectric infrared (PIR) sensor to detect a motion of elder. Each sensing node sends its detection signal to a home gateway via wireless link. The home gateway stores the received signals into a remote database. The server system is composed of a database server and a web server, which provides web-based monitoring system to caregivers (friends, family and social workers) for more cost effective intelligent care service. The improved second phase system can provide 'automatic diagnosis', 'going out detection', and enhanced user interface functionalities. We have evaluated the first and second phase monitoring systems from real field experiments of 3/4 months continuous operation with installation of 9/15 elders' houses, respectively. The experimental results show the promising possibilities to estimate the behavioral patterns and the current status of elder even though the simplicity of sensing capability.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.9
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• pp.819-831
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• 2019

The types of properties traded in modern times are rapidly increasing due to changes in consumption patterns. However, as the type of properties traded increases, estimation about the value of properties may become inaccurate. There is a problem that it is difficult for consumers to estimate the right value and the variety of trading forms makes it difficult to guarantee the reliability of value estimation As access to a variety of properties has expanded, these shortcomings are considered to be a factor that hinders the stability of the shared economic market. In this paper, to resolve this issue, we present a blockchain-based property contract service through a trusted broker. The developed service registers trusted brokers into smart contracts on the Ethereum blockchain and use them for the evaluation and contract process of properties. In addition, registered contents, proposals and contracts of properties are stored in the blockchain to ensure the reliability of the contract process. Every step of the contract process is stored in the smart contract, recorded in the transaction history of the blockchain, ensuring the reliability of the stored data. In addition, the entire process of registration, proposal, and contract is driven by smart contracts designed by state machine technology, enabling users to more securely control the contract process.