• Journal of KIISE:Software and Applications
• /
• v.30 no.7_8
• /
• pp.610-617
• /
• 2003

Similarity matching in video database is of growing importance in many new applications such as video clustering and digital video libraries. In order to provide efficient access to relevant data in large databases, there have been many research efforts in video indexing with diverse spatial and temporal features. however, most of the previous works relied on sequential matching methods or memory-based inverted file techniques, thus making them unsuitable for a large volume of video databases. In order to resolve this problem, this paper proposes an effective and scalable indexing technique using a trie, originally proposed for string matching, as an index structure. For building an index, we convert each frame into a symbol sequence using a window order heuristic and build a disk-resident trie from a set of symbol sequences. For query processing, we perform a depth-first search on the trie and execute a temporal segmentation. To verify the superiority of our approach, we perform several experiments with real and synthetic data sets. The results reveal that our approach consistently outperforms the sequential scan method, and the performance gain is maintained even with a large volume of video databases.

• Journal of Korea Multimedia Society
• /
• v.8 no.11
• /
• pp.1556-1564
• /
• 2005

Various optimization techniques are deployed in the compilation process of a source program for improving the program's execution speed and reducing the size of the source code. Of the optimization pattern matching techniques, the string pattern matching technique involves finding an optimal pattern that corresponds to the intermediate code. However, it is deemed inefficient due to excessive time required for optimized pattern search. The tree matching pattern technique can result in many redundant comparisons for pattern determination, and there is also the disadvantage of high cost involved in constructing a code tree. The objective of this paper is to propose a table-driven code optimizer using the DFA(Deterministic Finite Automata) optimization table to overcome the shortcomings of existing optimization techniques. Unlike other techniques, this is an efficient method of implementing an optimizer that is constructed with the deterministic automata, which determines the final pattern, refuting the pattern selection cost and expediting the pattern search process.

• Journal of the Institute of Electronics Engineers of Korea SD
• /
• v.38 no.2
• /
• pp.103-113
• /
• 2001

This paper described a design and implementation of a single-chip encoder/decoder using the LZSS algorithm and entropy coding in 0.6${\mu}{\textrm}{m}$ CMOS technology. Dictionary storage for the dictionary search processor(DISP) used a 2K$\times$8bit on-chip memory with 50MHz clock speed. It performs compression on byte-oriented input data at a data rate of one byte per clock cycle except when one out of every 33 cycles is used to update the string window of dictionary. In result, the average compression ratio is 46% by applied entropy coding of the LZSS codeword output. This is to improved on the compression performance of 7% much more then LZSS.

• Genomics & Informatics
• /
• v.6 no.3
• /
• pp.153-156
• /
• 2008

Complex diseases such as stroke and cancer have two or more genetic loci and are affected by environmental factors that contribute to the diseases. Due to the complex characteristics of these diseases, identifying candidate genes requires a system-level analysis of the following: gene ontology, pathway, and interactions. A database and user interface, termed StrokeBase, was developed; StrokeBase provides queries that search for pathways, candidate genes, candidate SNPs, and gene networks. The database was developed by using in silico data mining of HGNC, ENSEMBL, STRING, RefSeq, UCSC, GO, HPRD, KEGG, GAD, and OMIM. Forty candidate genes that are associated with cerebrovascular disease were selected by human experts and public databases. The networked cerebrovascular disease gene maps also were developed; these maps describe genegene interactions and biological pathways. We identified 1127 genes, related indirectly to cerebrovascular disease but directly to the etiology of cerebrovascular disease. We found that a protein-protein interaction (PPI) network that was associated with cerebrovascular disease follows the power-law degree distribution that is evident in other biological networks. Not only was in silico data mining utilized, but also 250K Affymetrix SNP chips were utilized in the 320 control/disease association study to generate associated markers that were pertinent to the cerebrovascular disease as a genome-wide search. The associated genes and the genes that were retrieved from the in silico data mining system were compared and analyzed. We developed a well-curated cerebrovascular disease-associated gene network and provided bioinformatic resources to cerebrovascular disease researchers. This cerebrovascular disease network can be used as a frame of systematic genomic research, applicable to other complex diseases. Therefore, the ongoing database efficiently supports medical and genetic research in order to overcome cerebrovascular disease.

• Microbiology and Biotechnology Letters
• /
• v.24 no.3
• /
• pp.371-375
• /
• 1996

TFD is a transcription factor database which consists of short functional DNA sequences called as signals and their references. SIGNAL SCAN, developed by Dan S. Prestridge, is used to determine what signals of TFD may exist in a DNA sequence. This program searches TFD database by using a simple algorithm for character string comparison. We developed TFSCAN that aims at searching for signals in an input DNA sequence more efficently than SIGNAL SCAN. Our algorithms consist of two parts, one constructs an automata by scanning sequences of rFD, the other searches for signals through this automata. Searching for signal-related references is radically improved in time by using an indexing method. Usage of TFSCAN is very simple and its output is obvious. We developed and installed a TFSCAN input form and a CGI program in GINet Web server, to use TFSCAN. The algorithm applying automata showed drastical results in improvement of computing time. This approach may apply to recognizing several biological patterns. We have been developing our algorithm to optimize the automata and to search more sensitively for signals.

• Journal of KIISE:Software and Applications
• /
• v.37 no.11
• /
• pp.826-836
• /
• 2010

This paper proposes a hybrid machine translation system which integrates SMT, RBMT, and PBMT in serial manner. SMT in our project has been implemented as a Quasi-syntax-based system where monotone search is done, given a preprocessed string of foreign language. Preprocessing includes rule-based reordering, NE recognition, clausal splitting, and attaching pattern translation information at the end of the input text. For lengthy & complex sentences, clausal splitting turned out to generate better translation than normal input.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.2 no.1
• /
• pp.53-58
• /
• 2002

In the construction of successful fuzzy models for nonlinear systems, the identification of an optimal fuzzy model system is an important and difficult problem. Traditionally, sGA(simple genetic algorithm) has been used to identify structures and parameters of fuzzy model because it has the ability to search the optimal solution somewhat globally. But SGA optimization process may be the reason of the premature local convergence when the appearance of the superior individual at the population evolution. Therefore, in this paper we propose a new method that can yield a successful fuzzy model using VmGA(virus messy genetic algorithms). The proposed method not only can be the countermeasure of premature convergence through the local information changed in population, but also has more effective and adaptive structure with respect to using changeable length string. In order to demonstrate the superiority and generality of the fuzzy modeling using VmGA, we finally applied the proposed fuzzy modeling methodof a complex nonlinear system.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.4 no.5
• /
• pp.968-988
• /
• 2010

Anonymous hierarchical identity based encryption (HIBE) is an extension of identity based encryption (IBE) that can use an arbitrary string like an e-mail address for a public key, and it additionally provide the anonymity of identity in ciphertexts. Using the anonymous HIBE schemes, it is possible to construct anonymous communication systems and public key encryption with keyword search. This paper presents an anonymous HIBE scheme with constant size ciphertexts under prime order symmetric bilinear groups, and shows that it is secure under the selective security model. Previous anonymous HIBE schemes were constructed to have linear size ciphertexts, to use composite order bilinear groups, or to use asymmetric bilinear groups that is a special type of bilinear groups. Our construction is the first efficient anonymous HIBE scheme that has constant size ciphertexts and that uses prime order symmetric bilinear groups. Compared to the previous scheme of composite order bilinear groups, ours is ten times faster. To achieve our construction, we first devise a novel cancelable random blinding technique. The random blinding property of our technique provides the anonymity of our construction, and the cancellation property of our technique enables decryption.

• Proceedings of the Korea Institute of Convergence Signal Processing
• /
• 2000.12a
• /
• pp.57-60
• /
• 2000

Even if the video data is utilized for a lot of field, its very difficult to reuse and search easily because of its atypical(unfixed form) and complicated structure. In this study, we presented the video retrieval system which is based on the synchronized closed caption and video, SMIL and SAMI languages which are described to structured and systematic form like multimedia data These have next structure; At first, a key word is inputted by user, then time stamp would be sampling from the string which has a key word in the caption file. To the result, the screen shows an appropriate video frame.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.8 no.5
• /
• pp.1135-1140
• /
• 2007

This paper proposes an edge-based text region detection algorithm using the adaptive character-edge maps which are independent of the size of characters and the orientation of character string in natural images. First, labeled images are obtained from edge images and in order to search for characters, adaptive character-edge maps by way grammar are applied to labeled images. Next, selected label images are clustered as for distance of its neighbors. And then, text region candidates are obtained. Finally, text region candidates are verified by using the empirical rules and horizontal/vertical projection profiles based on the orientation of text region. As the results of experiments, a text region detection algorithm turned out to be robust in the matter of various character size, orientation, and the complexity of the background.