• The KIPS Transactions:PartA
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• v.13A no.6 s.103
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• pp.501-510
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• 2006

The self-organizing super peer ring P2P search scheme improves search performance of the existing unstructured peer-to-peer systems, in which super peers with high capacity constitute a ring structure and all peer in the system utilize the ring for publishing or querying their keys. In this paper, we further improves the performance of the self-organizing ring by adaptively changing its super peer ratio according to the status of the entire system. By using PSO, the optimized super peer ratio can be maintained within the system. Through simulations, we show that our self-organizing super peer ring optimized by PSO outperforms not only the fixed super peer ring but also the self-organizing super ring with fixed ratio in the aspect of query success rate.

• Journal of Korean Library and Information Science Society
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• v.42 no.1
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• pp.325-338
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• 2011

This study aims to investigate characteristics of most clicked documents of Naver's universal search service. In particular, this study analyzed characteristics of most clicked documents such as click ratio, collection distribution, and yearly distribution. Also, clicked documents were evaluated in terms of relevance, credibility, and currency. In conducting this study, query logs and click logs of unified search service were analyzed. The results of this study show that most clicks occurred in blog collection and average click concentration rate reached almost 50%. Also, the relevance and currency of most clicked documents were quite high, but credibility of these documents were on average level. The results of this study can be implemented to the portal's effective development of searching algorithm and interface.

• The Transactions of the Korea Information Processing Society
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• v.3 no.4
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• pp.720-732
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• 1996

Spatial match retrieval methods for iconic image databases recognize an image document as several icon symbols. Therefore the iconic symbols are used as primary keys to index the image document. When a user requires content-based retrieval ofimages, a spatial match retrieval method converts a query image into iconic symbols and then retrieves relevant images by accessing stored images. In order to support content-based image retrieval efficiently, we, in this paper, propose spatial match retrieval methods using signatures for iconic image databases. For this, we design new index representations of two-dimensional iconic images and explain implemented system.. In addition, we compare the conventional 9-DLT and our two-dimensional image retrieval method in terms of retrieval precision and recall ratio. We show that our method is more efficient than the conventional method.

• The KIPS Transactions:PartB
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• v.17B no.2
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• pp.99-106
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• 2010

In this paper, we propose the construction of multi-queries and consistency principle for the user's emotion-based music retrieval system. The features used in the system are MPEG-7 audio descriptors, which are international standards recommended for content-based audio retrievals. In addition we propose the method to determine the weight that represent the importance of each descriptor for each emotion in order to reduce the computation. Also, the proposed retrieval algorithm that uses the relevance feedback based on consistency principal and multi-queries improves the success ratio of musics corresponding to user's emotion.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.5
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• pp.503-510
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• 2016

In this paper I analyzed two decoding algorithms of decentralized LT codes for distributed storage by simulations in small-scale wireless sensor network. From the simulation results we can see that when the decoding ration is above 2.0, the successful decoding probability of OBP decoding is about 99%, while that of BP decoding is below 50% with n=100, and about 70% with n=200. We showed that OBP decoding algorithm is an efficient decoding scheme for decentralized LT codes for distributed storage in small-scale wireless sensor network.

• Journal of the Korean Society for information Management
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• v.23 no.3 s.61
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• pp.147-165
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• 2006

In this study, experiments for selection of association terms were conducted in order to discover the optimum method in selecting additional terms that are related to an initial query term. Association term sets were generated by using support, confidence, and lift measures of the Apriori algorithm, and also by using the similarity measures such as GSS, Jaccard coefficient, cosine coefficient, and Sokal & Sneath 5, and mutual information. In performance evaluation of term selection methods, precision of association terms as well as the overlap ratio of association terms and relevant documents' indexing terms were used. It was found that Apriori algorithm and GSS achieved the highest level of performances.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2004.11a
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• pp.244-249
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• 2004

There have been many attempts to predict the secondary structure content of a protein from its primary sequence, which serves as the first step in a series of bioinformatics processes to gain knowledge of the structure and function of a protein. Most of them assumed that prediction relying on the information of the amino acid composition of a protein can be successful. Several approaches expanded the amount of information by including the pair amino acid composition of two adjacent residues. Recent methods achieved a remarkable improvement in prediction accuracy by using this expanded composition information. The overall average errors of two successful methods were 6.1% and 3.4%. This work was motivated by the observation that evolutionarily related proteins share the similar structure. After manipulating the values of the frequency matrix obtained by running PSI-BLAST, inputs of an artificial neural network were constructed by taking the ratio of the amino acid composition of the evolutionarily related proteins with a query protein to the background probability. Although we did not utilize the expanded composition information of amino acid pairs, we obtained the comparable accuracy, with the overall average error being 3.6%.

• Journal of Korea Society of Industrial Information Systems
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• v.6 no.1
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• pp.33-38
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• 2001

In this paper, we present an image retrieval system using shape features. The preprocessing to gain shape feature includes edge extraction using chain code. The shape features consist of center of mass, standard deviation, ratio of major axis and minor axis length. The similarity is estimated as comparing the features of query image with the features of images in database. Thus, the candidates of images are retrieved according to the order of similarity. The result of an experimentation is dullness for scale, rotation and translation. We evaluate the performance of shape features for image retrieval on a database with over 170 images. The Recall and the Precision is each 0.72 and 0.83 in the result of average experiment. So the proposed method is presented useful method.

• Journal of Communications and Networks
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• v.18 no.3
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• pp.493-501
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• 2016

In-network storage is an effective technique for avoiding network congestion and reducing power consumption in continuous data collection in wireless sensor networks. In recent years, network coding based storage design has been proposed as a means to achieving ubiquitous access that permits any query to be satisfied by a few random (nearby) storage nodes. To maintain data consistency in continuous data collection applications, the readings of a sensor over time must be sent to the same set of storage nodes. In this paper, we present an efficient approach to updating data at storage nodes to maintain data consistency at the storage nodes without decoding out the old data and re-encoding with new data. We studied a transmission strategy that identifies a set of storage nodes for each source sensor that minimizes the transmission cost and achieves ubiquitous access by transmitting sparsely using the sparse matrix theory. We demonstrate that the problem of minimizing the cost of transmission with coding is NP-hard. We present an approximation algorithm based on regarding every storage node with memory size B as B tiny nodes that can store only one packet. We analyzed the approximation ratio of the proposed approximation solution, and compared the performance of the proposed coding approach with other coding schemes presented in the literature. The simulation results confirm that significant performance improvement can be achieved with the proposed transmission strategy.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.2
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• pp.275-282
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• 2015

Since a NAND-flash memory is able to keep data during electricity-off and has small cost to store data per bytes, it is widely used on hand-held devices. It is necessary to use an index in order to process mass data effectively on the flash memory. However, since the flash memory requires high cost for a write operation and does not support an overwrite operation, it is possible to reduce the performance of the index when the disk based index is exploited. In this paper, we implement the fixed grid file index and evaluate the performance of the index on various conditions. To do this, we measure the average processing time by the ratio of query operations and update operations. We also the compare the processing times of the flash memory with those of the magnetic disk.