• The Journal of the Korea Contents Association
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• v.22 no.8
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• pp.33-43
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• 2022

Labeled graphs are used to represent entities, their relationships, and their structures in real data such as knowledge graphs and protein interactions. With the rapid development of IT and the explosive increase in data, there has been a need for a subgraph matching technology to provide information that the user is interested in. In this paper, we propose an approximate Top-k labeled subgraph matching scheme that considers the semantic similarity of labels and the difference in graph structure. The proposed scheme utilizes a learning model using FastText in order to consider the semantic similarity of a label. In addition, the label similarity graph(LSG) is used for approximate subgraph matching by calculating similarity values between labels in advance. Through the LSG, we can resolve the limitations of the existing schemes that subgraph expansion is possible only if the labels match exactly. It supports structural similarity for a query graph by performing searches up to 2-hop. Based on the similarity value, we provide k subgraph matching results. We conduct various performance evaluations in order to show the superiority of the proposed scheme.

• Journal of the Korea Society of Computer and Information
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• v.11 no.2 s.40
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• pp.201-211
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• 2006

The standardization of third Generation Partnership Project(3GPP) has been performed in of order to support interactive multimedia services under mobile environments. In this 3GPP, transmit diversity solutions are applied to increase the available diversity effectively using 2 or more antennas. In this paper, we analyzer the performances on STTD(Space Time Transmit Diversity) technique and its modified techniques such as STTD-OTD, CL-STTD, and 4TX-STTD out of open loop transmit diversities that the standardization of 3GPP has released. We also propose the open loop transmitter and receiver diversities to add the receiver diversity. We analyze and discuss the performance of the proposed techniques and using the Matlab simulation under the flat fading channel environment.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.10
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• pp.421-426
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• 2013

As a greater amount of traffic have been generated on the Internet, it becomes more important to know the size of each flow. Many research studies have been conducted on the traffic measurement, and mostly they have focused on how to increase the measurement accuracy with a limited amount of memory. In this paper, we propose an explicit flow labeling technique that can be used to find out the names of the top flows and to increase the counting upper bound of the existing scheme. The labeling technique is applied to CSM (Counter Sharing Method), the most recent traffic measurement algorithm, and the performance is evaluated using the CAIDA dataset.

• Proceedings of the Korea Institutes of Information Security and Cryptology Conference
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• 1996.11a
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• pp.205-218
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• 1996

World Wide Web(WWW) has a lot of useful charaters. Easiness of use, multi-media data supporting and interactive communication capability are typical reasons why people want to use WWW. But because WWW is based on Internet, it has some security problems which originate in plain format data transmission on physical transmission line. The unique solution fer this problems is data encryption. Since theoritically proved encryption algorithms ensure data confidentiality, a unauthorized user can not know what is transmitted on network. In this paper, we propose a cryptography system which uses public key system. In detail, our public key based web security mechanism is using PGP module. PGP is a e-mail security system implemented by Phil Zimmermann. The basic idea of our propose is data encryption and integrity checking for all data which is transmitted on Web. To implement these facilities, we. use netscape browser extension technology, plug-in. Through these technology, security mechanisms are added on netscape browser.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.4B
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• pp.311-322
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• 2006

Peer-to-peer (P2P) systems have become a popular medium through which to share huge amounts of data. On the basis of network topology, P2P systems are divided into three types: centralized, structured distribution, unstructured distribution. Unstructured P2P systems such as Gnutella are novel in the sense that they are extensible and reliable. However, as the number of nodes increases, unstructured P2P systems would suffer from the high complexity of search operations that have to scan the network to find the required data items. Efficient replication of data items can reduce the complexity, but it introduces another problem of maintaining consistency among replicated data items when each data item could be updated. In this paper, we propose a new update propagation algorithm that propagates an updated data item to all of its replica. The proposed algorithm can reduce the message transfer overhead by adopting the notion of timestamp and hybrid push/pull messaging.

• Journal of Digital Contents Society
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• v.16 no.2
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• pp.299-306
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• 2015

In this paper, we research to secure stability of data storing/searching on NoSQL implemented on Distributed File System. When implementing NoSQL on Distributed File System, we faced that random write on Distributed File System is almost impossible. To solve this problem, a concept of Intermediate-File was employed, and then it has been achieved that our system resist any failure circumstance. Additionally, since we discovered its performance cannot be as fast as general File System, by redefining the file block unit for our NoSQL system, we have prevented a slowdown in system performance. As a result, we are able to develop highly scalable NoSQL as Distributed File System, which fulfills basic conditions of transaction: Atomicity, Consistency, Isolation, and Performance.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.5
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• pp.608-615
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• 2006

This paper proposes a fuzzy model tree consisting of local linear models using fuzzy cluster for data modeling. First, cluster centers are calculated by fuzzy clustering method using all input and output attributes. And then, linear models are constructed at internal nodes with fuzzy membership values between centers and input attributes. The expansion of internal node is determined by comparing errors calculated in parent node with ones in child node, respectively. As a final step, data prediction is performed with a linear model having the highest fuzzy membership value between input attributes and cluster centers in leaf nodes. To show the effectiveness of the proposed method, we have applied our method to various dataset. Under various experiments, our proposed method shows better performance than conventional model tree and artificial neural networks.

• Journal of Advanced Navigation Technology
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• v.28 no.3
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• pp.262-271
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• 2024

In this paper, by applying deep learning, one of the A.I. techniques, through angle information, which is optical observation data generated when observing satellites at observatories, distance information from observatories is learned to predict range data, thereby increasing the precision of satellite's orbit determination. To this end, we generated observational data from GMAT, reduced the learning data error of deep learning through preprocessing of the generated observational data, and conducted deep learning through MATLAB. Based on the predicted distance information from learning, trajectory determination was performed using an extended Kalman filter, one of the filtering techniques for trajectory determination, through GMAT. The reliability of the model was verified by comparing and analyzing the orbital determination with angular information without distance information and the orbital determination result with predicted distance information from the model.

• Journal of Korea Spatial Information System Society
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• v.6 no.1 s.11
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• pp.3-17
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• 2004

With the rapid growth of the Internet geographic information services through the WWW such as a location-based service and so on. Web GISs (Geographic Information Systems) have also come to be a cluster-based architecture like most other information systems. That is, in order to guarntee high quality of geographic information service without regard to the rapid growth of the number of users, web GISs need cluster-based architecture that will be cost-effective and have high availability and scalability. This paper proposes the design of the cluster-based web GIS with high availability and scalability. For this, each node within a cluster-based web GIS consists of main memory spatial databases which accomplish role of caching by using data declustering and the locality of spatial query. Not only simple region queries but also the proposed system processed spatial join queries effectively. Compare to the existing method. Parallel R-tree spatial join for a shared-Nothing architecture, the result of simulation experiments represents that the proposed spatial join method achieves improvement of performance respectively 23% and 30% as data quantity and nodes of cluster become large.

• Journal of Digital Contents Society
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• v.18 no.5
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• pp.811-820
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• 2017

For content-based audio retrieval which is one of main functions in audio service, the techniques for extracting fingerprints from the audio source, storing and indexing them in a database are widely used. However, if the fingerprints of new audio sources are continually inserted into the database, there is a problem that space efficiency as well as audio retrieval performance are gradually deteriorated. Therefore, there is a need for techniques to support efficient expansion of audio database without periodic reorganization of the database that would increase the system operation cost. In this paper, we design a content-based audio retrieval system that solves this problem by using MapReduce and NoSQL database in a cluster computing environment based on the Shazam's fingerprinting algorithm, and evaluate its performance through a detailed set of experiments using real world audio data.