• The KIPS Transactions:PartD
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• v.10D no.3
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• pp.501-512
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• 2003

This paper proposes an indexing technique for fast retrieval of similar image subsequences using the multi-dimensional time warping distance. The time warping distance is a more suitable similarity measure than Lp distance in many applications where sequences may be of different lengths and/or different sampling rates. Our indexing scheme employs a disk-based suffix tree as an index structure and uses a lower-bound distance function to filter out dissimilar subsequences without false dismissals. It applies the normaliration for an easier control of relative weighting of feature dimensions and the discretization to compress the index tree. Experiments on medical and synthetic image sequences verify that the proposed method significantly outperforms the naive method and scales well in a large volume of image sequence databases.

• Journal of the Korea Computer Industry Society
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• v.9 no.4
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• pp.149-156
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• 2008

There is the temporal correlation of a animation sequence between the motion vector of current block and the motion vector of previous block. In this paper, we propose the scene change detection algorithm for block matching using the temporal correlation of the animation sequence and the center-biased property of motion vectors. The proposed algorithm determines the location of a better starting point for the search of an exact motion vector using the point of the smallest SAD(sum of absolute difference) value by the predicted motion vector from the same block of the previous frame and the predictor candidate point on each search region. Simulation results show that the proposed algorithm has better detection performance, such as recall rate, then the existing method. The algorithm has the advantage of speed, simplicity and accuracy. In addition, it requires less amount of storage.

• Journal of Mushroom
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• v.2 no.3
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• pp.145-148
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• 2004

This study was carried out to screen the fruiting body formation-specific genes from the medicinal mushroom Cordyceps militaris. A cDNA synthesized using total RNA from 4 stages of mushroom development, mycelium, primordium, immature fruiting body and mature fruiting body. Differential expression gene screening was performed by DD-PCR(Differential Display Arbitrary Primer PCR) with cDNA, we sequenced partial 6 genes using pGEM cloning vector. The DNA Sequence of the six DD-PCR products derived from differentially expressed genes was compared to that in the GenBank database by using the NCBI BLAST search to identify similarities to known sequences. Sequence analysis showed that six of DD-PCR products have unknown sequence.

• Korean Journal of Microbiology
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• v.44 no.4
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• pp.333-338
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• 2008

Computational analysis of partial rpoB gene sequence (777 bp) was done in this study to identify B. anthracis and its closely related species B. cereus and B. thuringiensis. Sequence data including 17 B. anthracis strains, 9 B. cereus strains, and 7 B. thuringiensis strains were obtained by searching databases. Those sequences were aligned and used for other computational analysis. B. anthracis strains were identificated by in silico restriction enzyme digestion. B. cereus and B. thuringiensis were not segregated by this method. Those sequencing and BLAST search were required to distinguish the two. In actual identification tests, B. anthracis strains could be identified by PCR-RFLP, and B. cereus and B. thuringiensis strains were distinguished by BLAST search with reliable e-value. In this study fast and accurate method for identifying three Bacillus species, and flow chart of identification were developed.

• Journal of the Korea Computer Industry Society
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• v.10 no.5
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• pp.227-234
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• 2009

The Paper introduces a new technique for block matching motion estimation. since the temporal correlation of a animation sequence between the motion vector of current block and the motion vector of previous block. In this paper, we propose the scene change detection algorithm for block matching using the temporal correlation of the animation sequence and the center-biased property of motion vectors. The proposed algorithm determines the location of a better starting point for the search of an exact motion vector using the point of the smallest SAD(sum of absolute difference) value by the predicted motion vector from the same block of the previous frame and the predictor candidate point on each search region. Simulation results show that the PSNR values are improved as high as 9~32% in terms of average number of search point per motion vector estimation and improved about 0.06~0.21dB on an average except the FS(full search) algorithm.

• Journal of Digital Contents Society
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• v.19 no.2
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• pp.301-307
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• 2018

Generally, search engine summarizes the main contents of the search results so that user can click the site providing the information of the contents to search first. In this study, we demonstrated whether the user clicks on the search results based on the summary content provided by the search engine or on the order of the search result placement through empirical studies through the presentation of search results. By using the API provided by the search engine company, a search site that presents the search results in a regular and inverse order is created, and the click action of each user's search result is displayed in the order of actual click order, click position, and the user's search type such as the route of movement. As a result of the analysis, most users account for more than 60% of users who click on the first and second exposed search results regardless of the search results. It is confirmed that the search priority of users is determined according to the order of search results regardless of the summary of search results.

• The Journal of Korean Society of Virology
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• v.29 no.1
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• pp.23-31
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• 1999

Hantavirus is a genus of the Bunyaviridae family causing two serious diseases, hemorrhagic fever with renal syndrome (HFRS) and hantavirus pulmonary syndrome (HPS). Puumala virus is a member of hantavirus originally found in Europe, and its natural reservoir is Clethrionomys glareolus. It is also associated with the human disease nephropathia epidemica, a milder form of HFRS. To identify the hantaviruses in bats, bats were collected from Jeong-Sun, Won-Joo, Chung-Ju and Hwa-Cheon area in Korea, and nested RT-PCR was performed with serotype specific primer from M segment. Interestingly, Puumala virus was detected in bats (Rhinolophus ferrum-equinum) only from Won-Joo. The 327 bp nested RT-PCR product, was sequenced. The sequence database search indicates that the sequence is homologous to the published sequence of Puumala viruses. The sequence similarities were ranged from 71% to 97%. The highest sequence similarity was 97% with Puumala virus Vranicam strain, and the lowest was 71% with Puumala virus K27 isolate. Puumala virus Vranicam strain was isolated from a bank vole (Clethrionomys glareolus) in Bosnia-Hercegovina. Puumala virus K27 was isolated from human in Russia. This analysis confirms that bats (Rhinolophus ferrum-equinum) in Korea are natural reservoir of Puumala virus.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.4
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• pp.28-36
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• 2009

Sequence-Pair(SP) model represents the topological relation between modules. In general, SP model based floorplanners search solutions using Simulated-Annealing(SA) algorithm. Several SA based floorplanning techniques using SP model have been published. To improve the performance of those techniques they tried to improve the speed for evaluation function for SP model, to find better scheduling methods and perturb functions for SA. In this paper we propose a two phase SA based algorithm. In the first phase, white space between modules is reduced by applying compaction technique to the floorplan obtained by an SP. From the compacted floorplan, the corresponding SP is determined. Solution space has been searched by changing the SP in the SA framework. When solutions converge to some threshold value, the first phase of the SA based search stops. Then using the typical SA based algorithm, ie, without using the compaction technique, the second phase of our algorithm continues to find optimal solutions. Experimental results with MCNC benchmark circuits show that how the proposed technique affects to the procedure for SA based floorplainning algorithm and that the results obtained by our technique is better than those obtained by existing SA-based algorithms.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.11
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• pp.507-520
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• 2017

The set-based similar sequence matching method measures similarity not for an individual data item but for a set grouping multiple data items. In the method, the similarity of two sets is represented as the size of intersection between them. However, there is a critical performances issue for the method in twofold: 1) calculating intersection size is a time consuming process, and 2) the number of set pairs that should be calculated the intersection size is quite large. In this paper, we propose an index-based search method for improving performance of set-based similar sequence matching in order to solve these performance issues. Our method consists of two parts. In the first part, we convert the set similarity problem into the intersection size comparison problem, and then, provide an index structure that accelerates the intersection size calculation. Second, we propose an efficient set-based similar sequence matching method which exploits the proposed index structure. Through experiments, we show that the proposed method reduces the execution time by 30 to 50 times then the existing methods. We also show that the proposed method has scalability since the performance gap becomes larger as the number of data sequences increases.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.1
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• pp.26-32
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• 2018

The protein secondary structures are important information for studying the evolution, structure and function of proteins. Recently, deep learning methods have been actively applied to predict the secondary structure of proteins using only protein sequence information. In these methods, widely used input features are protein profiles transformed from protein sequences. In this paper, to obtain an effective protein profiles, protein profiles were constructed using protein sequence search methods such as PSI-BLAST and HHblits. We adjust the similarity threshold for determining the homologous protein sequence used in constructing the protein profile and the number of iterations of the profile construction using the homologous sequence information. We used the protein profiles as inputs to convolutional neural networks and recurrent neural networks to predict the secondary structures. The protein profile that was created by adding evolutionary information only once was effective.