• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.716-719
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• 2005

We present an algorithm for finding shortest paths in the L$_1$ plane with a transportation network. The transportation network consists of parallel line segments, called highways, through which a movement gets faster. Given a source point s, our algorithm constructs a Shortest Path Map(SPM) such that for any query point t, we can find the length of a shortest path form s to t in O(log n) time. We design a plane sweep-like algorithm computing SPM in O(nlog n) time.

• Journal of Information Technology Services
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• v.16 no.1
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• pp.73-82
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• 2017

Recently in-memory data stream processing has been actively applied to various subjects such as query processing, OLAP, data mining, i.e., frequent item sets, association rules, clustering. However, finding regular periodic patterns of events in an infinite data stream gets less attention. Most researches about finding periods use autocorrelation functions to find certain changes in periodic patterns, not period itself. And they usually find periodic patterns in time-series databases, not in data streams. Literally a period means the length or era of time that some phenomenon recur in a certain time interval. However in real applications a data set indeed evolves with tiny differences as time elapses. This kind of a period is called as a pseudo-period. This paper proposes a new scheme called FPMH (Finding Periods using Multiple Hash functions) algorithm to find such a set of pseudo-periods over a data stream based on multiple hash functions. According to the type of pseudo period, this paper categorizes FPMH into three, FPMH-E, FPMH-PC, FPMH-PP. To maximize the performance of the algorithm in the data stream environment and to keep most recent periodic patterns in memory, we applied decay mechanism to FPMH algorithms. FPMH algorithm minimizes the usage of memory as well as processing time with acceptable accuracy.

• Journal of Broadcast Engineering
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• v.26 no.7
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• pp.838-843
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• 2021

This paper presents an algorithm for effective retrieval of score information to an input score image. The originality of the proposed algorithm is that it is designed to be robust to recognition errors by an OMR (Optical Music Recognition), while existing methods such as pitch histogram requires error induced OMR result be corrected before retrieval process. This approach helps people to retrieve score without training on music score for error correction. OMR takes a score image as input, recognizes musical symbols, and produces structural symbolic notation of the score as output, for example, in MusicXML format. Among the musical symbols on a score, it is observed that filled noteheads are rarely detected with errors with its simple black filled round shape for OMR processing. Barlines that separate measures also strong to OMR errors with its long uniform length vertical line characteristic. The proposed algorithm consists of a descriptor for a score and a similarity measure between a query score and a reference score. The descriptor is based on note-count, the number of filled noteheads in a measure. Each part of a score is represented by a sequence of note-count numbers. The descriptor is an n-gram sequence of the note-count sequence. Simulation results show that the proposed algorithm works successfully to a certain degree in score image-based retrieval for an erroneous OMR output.

• Journal of KIISE:Information Networking
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• v.32 no.1
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• pp.89-99
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• 2005

Advances of Internet and rC accelerate distribution and sharing of information, which make P2P(Peer-to-Peer) computing paradigm appear P2P computing Paradigm is the computing paradigm that shares computing resources and services between users directly. A fundamental problem that confronts Peer-to-Peer applications is the efficient location of the node that stoles a desired item. P2P systems treat the majority of their components as equivalent. This purist philosophy is useful from an academic standpoint, since it simplifies algorithmic analysis. In reality, however, some peers are more equal than others. We propose the P2P protocol considering differences of capabilities of computers, which is ignored in previous researches. And we examine the possibility and applications of the protocol. Simulating the Magic Square, we estimate the performances of the protocol with the number of hop and network round time. Finally, we analyze the performance of the protocol with the numerical formula. We call our p2p protocol the Magic Square. Although the numbers that magic square contains have no meaning, the sum of the numbers in magic square is same in each row, column, and main diagonal. The design goals of our p2p protocol are similar query response time and query path length between request peer and response peer, although the network information stored in each peer is not important.

• Journal of KIISE:Databases
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• v.30 no.5
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• pp.507-520
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• 2003

In this paper, an automatic construction method of theme melody index for large music database and an associative content-based music retrieval mechanism in which the constructed theme melody index is mainly used to improve the users' response time are proposed. First, the system automatically extracted the theme melody from a music file by the graphical clustering algorithm based on the similarities between motifs of the music. To place an extracted theme melody into the metric space of M-tree, we chose the average length variation and the average pitch variation of the theme melody as the major features. Moreover, we added the pitch signature and length signature which summarize the pitch variation pattern and the length variation pattern of a theme melody, respectively, to increase the precision of retrieval results. We also proposed the associative content-based music retrieval mechanism in which the k-nearest neighborhood searching and the range searching algorithms of M-tree are used to select the similar melodies to user's query melody from the theme melody index. To improve the users' satisfaction, the proposed retrieval mechanism includes ranking and user's relevance feedback functions. Also, we implemented the proposed mechanisms as the essential components of content-based music retrieval systems to verify the usefulness.

• The Journal of the Acoustical Society of Korea
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• v.21 no.1
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• pp.82-88
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• 2002

In this paper, we proposed a audio indexing method that is used wavelet transform for audio data retrieval. It is difficult for audio data to make a efficient audio data index because of its own particular properties, such as requirement of large storage, real time to transfer and wide bandwidth. An audio data in del using wavelet transform make it possible to index and retrieval by using the particular wavelet transform properties. Our proposed indexing method doesn't separate data to several blocks. Therefore we use both high-pass and low-pass parts of last level coefficient of wavelet transform. Audio data indexing is made by applying the string matching algorithm to high-pass part and zero-crossing histogram to low-pass part. These are transformed to the continued strings, Through this method, we described a retrieval efficiency. The retrieval method is done by comparing the database index string to the query string and then data of minimum values is chosen to the result. Our simulation decided proper comparative coefficient and made known changing of retrieval efficiency versus audio data length. The results show that the proposed method improves retrieval efficiency compared to conventional method.

• Journal of KIISE:Databases
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• v.30 no.3
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• pp.225-236
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• 2003

MOLAP systems store data in a multidimensional away called a 'cube' and access them using way indexes. When a cube is placed into disk, it can be Partitioned into a set of chunks of the same side length. Such a cube storage scheme is called the chunk-based MOLAP cube storage scheme. It gives data clustering effect so that all the dimensions are guaranteed to get a fair chance in terms of the query processing speed. In order to achieve high space utilization, sparse chunks are further compressed. Due to data compression, the relative position of chunks cannot be obtained in constant time without using indexes. In this paper, we propose a bitmap index for chunk-based MOLAP cubes. The index can be constructed along with the corresponding cube generation. The relative position of chunks is retained in the index so that chunk retrieval can be done in constant time. We placed in an index block as many chunks as possible so that the number of index searches is minimized for OLAP operations such as range queries. We showed the proposed index is efficient by comparing it with multidimensional indexes such as UB-tree and grid file in terms of time and space.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.6
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• pp.2160-2179
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• 2015

In many Radio Frequency Identification (RFID) applications, the reader recognizes the tags within its scope repeatedly. For these applications, some algorithms such as the adaptive query splitting algorithm (AQS) and the novel semi-blocking AQS (SBA) were proposed. In these algorithms, a staying tag retransmits its ID to the reader to be identified, even though the ID of the tag is stored in the reader's memory. When the length of tag ID is long, the reader consumes a long time to identify the staying tags. To overcome this deficiency, we propose a slot allocated blocking anti-collision algorithm (SABA). In SABA, the reader assigns a unique slot to each tag in its range by using a slot allocation mechanism. Based on the allocated slot, each staying tag only replies a short data to the reader in the identification process. As a result, the amount of data transmitted by the staying tags is reduced greatly and the identification rate of the reader is improved effectively. The identification rate and the data amount transmitted by tags of SABA are analyzed theoretically and verified by various simulations. The simulation and analysis results show that the performance of SABA is superior to the existing algorithms significantly.

• Journal of Microbiology
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• v.43 no.5
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• pp.406-410
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• 2005

In contrast to Saccharomyces cerevisiae, little is known about the kinesin-like protein (KLP) in Candida albicans. The motor domain of kinesin, or KLP, contains a subregion, which is well conserved from yeast to humans. A similarity search, with the murine ubiquitous kinesin heavy chain region as a query, revealed 6 contigs that contain putative KLPs in the genome of C. albicans. Of these, the length of an open reading (ORF) of 375 amino acids, temporarily designated CaKAR3, was noticeably short compared with the closely related S. cerevisiae KAR3 (ScKAR3) of 729 amino acids. This finding prompted us to isolate a ${\lambda}$ genomic clone containing the complete CaKAR3 ORF, and here the complete sequence of CaKAR3 is reported. CaKAR3 is a C-terminus motor protein, of 687 amino acids, encoded by a non-disrupting gene. When compared with ScKAR3, the amino terminal region of 112 amino acids was unique, with the middle part of the 306 amino acids exhibiting $25\%$ identity and $44\%$ similarity, while the remaining C-terminal motor domain exhibited $64\%$ identity and $78\%$ similarity, and have been submitted to GeneBank under the accession number AY182242.