• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.6
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• pp.22-27
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• 2011

This paper presents an efficient technique to reduce PN code acquisition time considerably by adjusting threshold values in direct sequence spread spectrum (DS-SS) systems. The proposed algorithm employs a pre-dump mode prior to a search mode, and the pre-dump mode determines threshold values of both search and verification modes depending on its correlation energy, which can improve not only the rejection performance of false code phases in the search mode but also that in the verification mode. The proposed method can reduce the mean code acquisition time by about 40% without increase of hardware costs compared with the conventional technique.

• Journal of Computing Science and Engineering
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• v.9 no.1
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• pp.1-8
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• 2015

Accessing and searching in a sequence of numbers are fundamental operations in computing that are encountered in a wide range of applications. One of the applications of the problem is cryptanalytic time-memory tradeoff which is aimed at a one-way function. A rainbow table, which is a common method for the time-memory tradeoff, contains elements from an input domain of a hash function that are normally sorted integers. In this paper, we present a practical indexing method for a monotonically increasing static sequence of numbers where the access and search queries can be addressed efficiently in terms of both time and space complexity. For a sequence of n numbers from a universe $U=\{0,{\ldots},m-1\}$, our data structure requires n lg(m/n) + O(n) bits with constant average running time for both access and search queries. We also give an analysis of the time and space complexities of the data structure, supported by experiments with rainbow tables.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.4
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• pp.121-128
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• 2018

A Korean morphological analyzer adopts sequence-to-sequence (seq2seq) model, which can generate an output sequence of different length from an input. In general, a seq2seq based Korean morphological analyzer takes a syllable-unit based sequence as an input, and output a syllable-unit based sequence. Syllable-based morphological analysis has the advantage that unknown words can be easily handled, but has the disadvantages that morpheme-based information is ignored. In this paper, we propose a reranking model as a post-processor of seq2seq model that can improve the accuracy of morphological analysis. The seq2seq based morphological analyzer can generate K results by using a beam-search method. The reranking model exploits morpheme-unit embedding information as well as n-gram of morphemes in order to reorder K results. The experimental results show that the reranking model can improve 1.17% F1 score comparing with the original seq2seq model.

• Genomics & Informatics
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• v.9 no.4
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• pp.189-193
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• 2011

Simple sequence repeats (SSRs) are ubiquitous short tandem duplications found within eukaryotic genomes. Their length variability and abundance throughout the genome has led them to be widely used as molecular markers for crop-breeding programs, facilitating the use of marker-assisted selection as well as estimation of genetic population structure. Here, we report a software application, "SSR-Primer Generator " for SSR discovery, SSR-primer design, and homology-based search of in silico amplicons from a DNA sequence dataset. On submission of multiple FASTA-format DNA sequences, those analyses are batch processed in a Java runtime environment (JRE) platform, in a pipeline, and the resulting data are visualized in HTML tabular format. This application will be a useful tool for reducing the time and costs associated with the development and application of SSR markers.

• Bioinformatics and Biosystems
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• v.1 no.2
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• pp.99-102
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• 2006

The Basic Local Alignment Search Tool (BLAST) is one of the most established software in bioinformatics research and it compares a query sequence against the libraries of known sequences in order to investigate sequence similarity. Expressed Sequence Tags (ESTs) are single-pass sequence reads from mRNA (or cDNA) and represent the expression for a given cDNA library and the snapshot of genes expressed in a given tissue and/or at a given developmental stage. Therefore, ESTs can be very valuable information for functional genomics and bioinformatics researches. Although major bio database (DB) websites including NCBI are providing BLAST services and EST data, local DB and search system is demanding for better performance and security issue. Here we present animal EST DBs and local BLAST search system. The animal ESTs DB in NCBI Genbank were divided by animal species using the Perl script we developed. and we also built the new extended DB search systems fur the new data (Local Animal BLAST Search System: http://bioinfo.kohost.net), which was constructed on the high-capacity PC Cluster system fur the best performance. The new local DB contains 650,046 sequences for Bos taurus(cattle), 368,120 sequences for Sus scrofa (pig), 693,005 sequences for Gallus gallus (fowl), respectively.

• Journal of the Korea Society of Computer and Information
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• v.11 no.6 s.44
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• pp.69-78
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• 2006

In the field of the bioinformatics, it plays an important role in predicting functional information or structure information to search similar sequence in biological DB. Biolrgical sequences have been increased dramatically since Human Genome Project. At this point, because the searching speed for the similar sequence is highly regarded as the important factor for predicting function or structure, the SMP(Sysmmetric Multi-Processors) computer or cluster is being used in order to improve the performance of searching time. As the method to improve the searching time of BLAST(Basic Local Alighment Search Tool) being used for the similarity sequence search, We suggest the nBLAST algorithm performing on the cluster environment in this paper. As the nBLAST uses the MPI(Message Passing Interface), the parallel library without modifying the existing BLAST source code, to distribute the query to each node and make it performed in parallel, it is possible to easily make BLAST parallel without complicated procedures such as the configuration. In addition, with the experiment performing the nBLAST in the 28 nodes of LINUX cluster, the enhanced performance according to the increase in the number of the nodes has been confirmed.

• Journal of KIISE:Databases
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• v.34 no.2
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• pp.119-132
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• 2007

In molecular biology, approximate subsequence search is one of the most important operations. In this paper, we propose an accurate and efficient method for approximate subsequence search in large DNA databases. The proposed method basically adopts a binary trie as its primary structure and stores all the window subsequences extracted from a DNA sequence. For approximate subsequence search, it traverses the binary trie in a breadth-first fashion and retrieves all the matched subsequences from the traversed path within the trie by a dynamic programming technique. However, the proposed method stores only window subsequences of the pre-determined length, and thus suffers from large post-processing time in case of long query sequences. To overcome this problem, we divide a query sequence into shorter pieces, perform searching for those subsequences, and then merge their results. To verify the superiority of the proposed method, we conducted performance evaluation via a series of experiments. The results reveal that the proposed method, which requires smaller storage space, achieves 4 to 17 times improvement in performance over the suffix tree based method. Even when the length of a query sequence is large, our method is more than an order of magnitude faster than the suffix tree based method and the Smith-Waterman algorithm.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.2
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• pp.51-62
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• 2018

High utility sequential pattern (HUSP) mining has been considered as an important research topic in data mining. Although some algorithms have been proposed for this topic, they incur the problem of producing a large search space for HUSPs. The tighter utility upper bound of a sequence can prune more unpromising patterns early in the search space. In this paper, we propose a sequence expected utility (SEU) as a new utility upper bound of each sequence, which is the maximum expected utility of a sequence and all its descendant sequences. A sequence utility list for each pattern is used as a new data structure to maintain essential information for mining HUSPs. We devise an algorithm, high sequence utility list-span (HSUL-Span), to identify HUSPs by employing SEU. Experimental results on both synthetic and real datasets from different domains show that HSUL-Span generates considerably less candidate patterns and outperforms other algorithms in terms of execution time.

• Journal of KIISE:Computing Practices and Letters
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• v.10 no.3
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• pp.273-281
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• 2004

There is the temporal correlation of the video sequence between the motion vector of current block and the motion vector of previous block. In this paper, we propose the prediction search algorithm for block matching using the temporal correlation of the video 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 PSNR(Peak-to-Signal Noise Ratio) values are improved up to the 1.06㏈ as depend on the video sequences and improved about 0.19∼0.46㏈ on an average except the full search(FS) algorithm.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.6
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• pp.724-729
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• 2011

Information retrieval is a method to search the needed data by users. Generally, when a user searches some data in the large scale data set like the internet, ranking-based search is widely used because it is not easy to find the exactly needed data at once. In this paper, we propose a novel ranking-based search method based on sequence and adjacency relationship of user query by the help of TF-IDF and n-gram. As a result, it was possible to find the needed data more accurately with 73% accuracy in more than 19,000 data set.