• The Journal of the Acoustical Society of Korea
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• v.23 no.3E
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• pp.91-97
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• 2004

In this paper, we propose a classification system of TV program scenes based on audio information. The system classifies the video scene into six categories of commercials, basketball games, football games, news reports, weather forecasts and music videos. Two type of audio feature set are extracted from each audio frame-timbral features and coefficient domain features which result in 58-dimensional feature vector. In order to reduce the computational complexity of the system, 58-dimensional feature set is further optimized to yield l0-dimensional features through Sequential Forward Selection (SFS) method. This down-sized feature set is finally used to train and classify the given TV program scenes using κ -NN, Gaussian pattern matching algorithm. The classification result of 91.6% reported here shows the promising performance of the video scene classification based on the audio information. Finally, the system stability problem corresponding to different query length is investigated.

• Journal of Industrial Technology
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• v.21 no.A
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• pp.155-166
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• 2001

This paper deals with the subsequence searching problem under time-warping. Our work is motivated by the observation that subsequence searches slow down quadratically as the average length of data sequences increases. To resolve this problem, the Segment-Based Approach for Subsequence Searches (SBASS) is proposed. The SBASS divides data and query sequences into a series of segments, and retrieves all data subsequences. Our segmentation scheme allows segments to have different lengths; thus we employ the time warping distance as a similarity measure for each segment pair. For efficient retrieval of similar subsequences, we extract feature vectors from all data segments exploiting their monotonically changing properties, and build a spatial index using feature vectors. The effectiveness of our approach is verified through extensive experiments.

• Journal of Information Processing Systems
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• v.11 no.1
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• pp.95-103
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• 2015

This paper presents a memory efficient tree based anti-collision protocol to identify memoryless RFID (Radio Frequency Identification) tags that may be attached to products. The proposed deterministic scheme utilizes two bit arrays instead of stack or queue and requires only ${\Theta}(n)$ space, which is better than the earlier schemes that use at least $O(n^2)$ space, where n is the length of a tag ID in a bit. Also, the size n of each bit array is independent of the number of tags to identify. Our simulation results show that our bit array scheme consumes much less memory space than the earlier schemes utilizing queue or stack.

• Journal of the Korea Society of Computer and Information
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• v.19 no.9
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• pp.45-53
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• 2014

This paper suggests methods to chronicle and track the history of dialogues exchanged among characters to prevent logical errors of a story. As for stories that are long with many characters, especially in full-length novels and co-written stories, cognitive burden is imposed on a writer. If the writer has confused understanding of a character, then a logical error would enter the story. This would compromise completeness and integrity of writing. Against the backdrop, this paper shows how dialogues among characters are chronicled and tracked by using the aforementioned tracking methods through design of a writer support system that relieves a writer's cognitive burden while supporting the writing and through an analysis of existing novels. In addition, we showed the accuracy results of average 68.5% through the performance evaluation of the query used in the dialogue history tracking.

• Journal of Korea Multimedia Society
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• v.12 no.11
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• pp.1581-1592
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• 2009

Recently, we can hear various kinds of music in everywhere and anytime. If a user wants to find the music which was heard before in a street or cafe, but he does not know the title of the music, it is difficult to find it. That is the limitation of previous retrieval system of music data. To overcome these problems, we research a method of content-based retrieval of music data based on the recorded humming, the part of recorded music and the played musical instrument. In this paper, we investigated previous content-based retrieval methods of papers, systems and patents. Based on that, we research a method of content-based retrieval of music data. That is, in case of using the recorded humming and music for query, we extract the frequency information from the recorded humming/music and the stored music data by using FFT. We use a MIDI file in case of query by the played musical instrument. And by using dynamic programming matching, the error caused by the disparity of length between the input source with the stored music data could be reduced.

• Journal of KIISE:Databases
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• v.30 no.1
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• pp.27-40
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• 2003

The inverted index widely used in the existing information retrieval field should be extended for XML documents to support containment queries by XML information retrieval systems. In this paper, we consider that there are two methods in storing the inverted index and processing containment queries for XML documents as the previous work suggested: using a RDBMS or using an inverted lift engine. It has two drawbacks to extend the inverted index in the previous work. One is that using a RDBMS is moth worse in the performance than using an inverted list engine. The other is that when containment queries are processed in a RDBMS, there is an increase in the number of a join operation as the path length of a query increases and a join operation always happens between large fables. In this paper. we extend the inverted index in a different way to solve these problems and show the effectiveness of using a RDBMS.

• Journal of Korea Spatial Information System Society
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• v.12 no.1
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• pp.37-48
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• 2010

In this paper, we analyze the shortcomings of the previous declustering methods, which are based on grid-like partitioning and a mapping function from a cell to a disk number, for high-dimensional space and propose a solution. The problems arise from the fact that the number of splitting is small(for the most part, binary-partitioning is sufficient), and the side length of a range query whose selectivity is small is quite large. To solve this problem, we propose a mathematical model to estimate the performance of a grid-like partitioning method. With the proposed estimation model, we can choose a good grid-like partitioning method among the possible schemes and this results in overall improvement in declustering performance. Several experimental results show that we can improve the performance of a previous declustering method up to 2.7 times.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.7B
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• pp.728-733
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• 2009

An ubiquitous environment has features like peer-to-peer and nomadic environments. Such features can be represented by peer-to-peer systems and mobile ad-hoc networks. P2P systems and MANETs share similar features, appealing for implementing P2P systems in MANET environment. However, if a P2P system designed for wired networks was applied to mobile ad-hoc environment, its performance was not good enough. Subsequently, this paper proposes a P2P system to improve performance using cross-layer design and the goodness of a node as a peer by using routing metric and P2P metric to choose favorable peers to connect. It also utilizes proactive approach for distributing peer information. The simulation results showed that the proposed system produced better performance in query success rate, query response time and energy consumption by reducing the routing path length.

• Journal of KIISE:Databases
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• v.28 no.3
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• pp.344-356
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• 2001

This paper deals with the subsequence searching problem under time-warping in sequence databases. Our work is motivated by the observation that subsequence searches slow down quadratically as the average length of data sequences increases. To resolve this problem, the Segment-Based Approach for Subsequence Searches (SBSS) is proposed. The SBASS divides data and query sequences into a series of segments, and retrieves all data subsequences that satisfy the two conditions: (1) the number of segments is the same as the number of segments in a query sequence, and (2) the distance of every segment pair is less than or equal to a tolerance. Our segmentation scheme allows segments to have different lengths; thus we employ the time warping distance as a similarity measure for each segment pair. For efficient retrieval of similar subsequences, we extract feature vectors from all data segments exploiting their monotonically changing properties, and build a spatial index using feature vectors. Using this index, queries are processed with the four steps: (1) R-tree filtering, (2) feature filtering, (3) successor filtering, and (4) post-processing. The effectiveness of our approach is verified through extensive experiments.

• Journal of Biosystems Engineering
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• v.27 no.2
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• pp.151-160
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• 2002

Cow image processing technique would be useful not only for recognizing an individual but also for establishing the image database and analyzing the shape of cows. A cow (Holstein) has usually the unique speckle pattern. In this study, the individual recognition of cow was carried out using the speckle pattern and the content-based image retrieval technique. Sixty cow images of 16 heads were captured under outdoor illumination, which were complicated images due to shadow, obstacles and walking posture of cow. Sixteen images were selected as the reference image for each cow and 44 query images were used for evaluating the efficiency of individual recognition by matching to each reference image. Run-lengths and positions of runs across speckle area were calculated from 40 horizontal line profiles for ROI (region of interest) in a cow body image after 3 passes of 5$\times$5 median filtering. A similarity measure for recognizing cow individuals was calculated using Euclidean distance of normalized G-frame histogram (GH). normalized speckle run-length (BRL), normalized x and y positions (BRX, BRY) of speckle runs. This study evaluated the efficiency of individual recognition of cow using Recall(Success rate) and AVRR(Average rank of relevant images). Success rate of individual recognition was 100% when GH, BRL, BRX and BRY were used as image query indices. It was concluded that the histogram as global property and the information of speckle runs as local properties were good image features for individual recognition and the developed system of individual recognition was reliable.