• Journal of the Korea Society of Computer and Information
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• v.16 no.7
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• pp.95-103
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• 2011

The actual utilization of Semantic Web technology which aims to provide more intelligent and automated service for information retrieval over the Web becomes gradually reality. RDF is widely used as the one of standard formats to present and manage the voluminous data on the Web. Efficient query processing on RDF data, therefore, is one of the ongoing research topics. Retrieving resources having a specific association from a given resource is the typical query processing type and several researches for this have done. However the most of previous researches have not fully considered discovering the complex relationship among resources such as returning the association between resources as the query processing result. This paper introduces the indexing and query processing for ${\rho}$-intersect operation which is one of the semantic association retrieval types. It includes an indexing scheme using suffix array and optimal processing approaches for handling ${\rho}$-intersect operation. The experimental evaluations shows that the average execution times for the proposed approach is 3~7 times faster than the previous approach.

• The Journal of the Convergence on Culture Technology
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• v.1 no.1
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• pp.79-85
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• 2015

According to the growing use of the personal GPS in the mobile device recently, the LBS (Local bases service), which processes and refines the GPS information, such as a position-tracking service, a public safety service, a local based information service, has increased steadily. Due to the refraction or reflection of GPS, however, it is impossible to use GPS around or in buildings. Therefore, it is necessary to correct the errors of GPS. We propose the method which corrects the errors of GPS and creates the refined trajectory using intersection region indexing. After analyzing the trajectory, receiving trajectories from many people and identifying the similarity between of trajectories, we will recommend the favorite route and useful information such as restaurant, convenience store, bus station and emergency call service.

• The Journal of the Acoustical Society of Korea
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• v.20 no.2
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• pp.10-15
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• 2001

In this paper, we describe the comparison between the combination of features using a speech and music discrimination, which is classifying between speech and music on audio signals. Audio signals are classified into 3classes (speech, music, speech and music) and 2classes (speech, music). Experiments carried out on three types of feature, Mel-cepstrum, energy, zero-crossings, and try to find a best combination between features to speech and music discrimination. We using a Gaussian Mixture Model (GMM) for discrimination algorithm and combine different features into a single vector prior to modeling the data with a GMM. In 3classes, the best result is achieved using Mel-cepstrum, energy and zero-crossings in a single feature vector (speech: 95.1％, music: 61.9％, speech & music: 55.5％). In 2classes, the best result is achieved using Mel-cepstrum, energy and Mel-cepstrum, energy, zero-crossings in a single feature vector (speech: 98.9％, music: 100％).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.11A
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• pp.870-881
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• 2009

The rapid development of healthcare information management for 3D medical digital library, 3D PACS and 3D medical diagnosis has addressed security issues with medical IT technology. This paper presents multiple 3D medical image data for protection, authentication, indexing and diagnosis information hiding applied to healthcare information management. The proposed scheme based on POCS watermarking embeds the robust watermark for doctor's digital signature and information retrieval indexing key to the distribution of vertex curvedness and embeds the fragile watermark for diagnosis information and authentication reference message to the distance difference of vertex. The multiple embedding process designs three convex sets for robustness, fragileness and invisibility and projects 3D medical image data onto three convex sets alternatively and iteratively. Experimental results confirmed that the proposed scheme has the robustness and fragileness to various 3D geometric and mesh modifiers at once.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.1
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• pp.1-8
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• 2016

In this paper, several problems functioning as the obstacles against software reuse were summarized. Among them, the issues dealt with in this paper include the effective method for constructing the library, the proper structure of the library, and the efficient retrieval technique. The knowledge-based approach and the information retrieval approach were integrated to construct and manage the library. The former is on the object- oriented model. Basically the object-oriented library is based on the classes and organized by inheritance. Because inheritance hierarchy is based on syntactical information, it dose not present the relationship of functionality. Using the information retrieval approach, the index file which characterizes the component and similarity among the components can be analyzed. Especially, we focused on the reusable library for the object-oriented programming environments.

• Journal of KIISE:Databases
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• v.29 no.5
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• pp.381-392
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• 2002

This paper deals with the problem of shape-based retrieval in time-series databases. The shape-based retrieval is defined as the operation that searches for the (sub)sequences whose shapes are similar to that of a given query sequence regardless of their actual element values. In this paper, we propose an effective and efficient approach for shape-based retrieval of subsequences. We first introduce a new similarity model for shape-based retrieval that supports various combinations of transformations such as shifting, scaling, moving average, and time warping. For efficient processing of the shape-based retrieval based on the similarity model, we also propose the indexing and query processing methods. To verify the superiority of our approach, we perform extensive experiments with the real-world S&P 500 stock data. The results reveal that our approach successfully finds all the subsequences that have the shapes similar to that of the query sequence, and also achieves significant speedup up to around 66 times compared with the sequential scan method.

• The KIPS Transactions:PartD
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• v.15D no.1
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• pp.31-40
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• 2008

We generally use lower-dimensional transformations to convert high-dimensional sequences into low-dimensional points in similar sequence matching. These traditional transformations, however, show different characteristics in indexing performance by the type of time-series data. It means that the selection of lower-dimensional transformations makes a significant influence on the indexing performance in similar sequence matching. To solve this problem, in this paper we propose a hybrid approach that integrates multiple transformations and uses them in a single multidimensional index. We first propose a new notion of hybrid lower-dimensional transformation that exploits different lower-dimensional transformations for a sequence. We next define the hybrid distance to compute the distance between the transformed sequences. We then formally prove that the hybrid approach performs the similar sequence matching correctly. We also present the index building and the similar sequence matching algorithms that use the hybrid approach. Experimental results for various time-series data sets show that our hybrid approach outperforms the single transformation-based approach. These results indicate that the hybrid approach can be widely used for various time-series data with different characteristics.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.12
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• pp.673-681
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• 2004

As the use of digital videos is getting popular, there is an increasing demand for efficient browsing and retrieval of video. To support such operations, effective video indexing should be incorporated. One of the most fundamental steps in video indexing is to parse video stream into shots and scenes. Generally, it takes long time to parse a video due to the huge amount of computation in a traditional single computing environment. Previous studies had widely used Round Robin scheduling which basically allocates tasks to each slave for a time interval of one quantum. This scheduling is difficult to adapt in a heterogeneous environment. In this paper, we propose two different parallel parsing algorithms which are Size-Adaptive Round Robin and Dynamic Size-Adaptive Round Robin for the heterogeneous distributed computing environments. In order to show their performance, we perform several experiments and show some of the results.

• Journal of KIISE:Databases
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• v.30 no.4
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• pp.362-371
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• 2003

In this paper, we propose an optimal interest point extraction method to support shape-base image classification and indexing for image database by applying a dynamic threshold that reflects the characteristics of the shape contour. The threshold is determined dynamically by comparing the contour length ratio of the original shape and the approximated polygon while the algorithm is running. Because our algorithm considers the characteristics of the shape contour, it can minimize the number of interest points. For n points of the contour, the proposed algorithm has O(nlogn) computational cost on an average to extract the number of m optimal interest points. Experiments were performed on the 70 synthetic shapes of 7 different contour types and 1100 fish shapes. It shows the average optimization ratio up to 0.92 and has 14% improvement, compared to the fixed threshold method. The shape features extracted from our proposed method can be used for shape-based image classification, indexing, and similarity search via normalization.

• Journal of KIISE:Databases
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• v.31 no.6
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• pp.650-663
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• 2004

In molecular biology, DNA sequence searching is one of the most crucial operations. Since DNA databases contain a huge volume of sequences, a fast indexing mechanism is essential for efficient processing of DNA sequence searches. In this paper, we first identify the problems of the suffix tree in aspects of the storage overhead, search performance, and integration with DBMSs. Then, we propose a new index structure that solves those problems. The proposed index consists of two parts: the primary part represents the trie as bit strings without any pointers, and the secondary part helps fast accesses of the leaf nodes of the trio that need to be accessed for post processing. We also suggest an efficient algorithm based on that index for DNA sequence searching. To verify the superiority of the proposed approach, we conducted a performance evaluation via a series of experiments. The results revealed that the proposed approach, which requires smaller storage space, achieves 13 to 29 times performance improvement over the suffix tree.