• Korean Journal of Microbiology
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• v.42 no.4
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• pp.271-276
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• 2006

Previously we demonstrated that virus-inducible stress protein (VISP) is induced in fish cells by the infection of a fish rhabdovirus. In this paper, we investigated the subcellular localization of the VISP and determined the region of VISP responsible for the subcellular localization. The CHSE-214 cells were stained with monoclonal antibody raised against VISP and observed with confocal microscope to detect the endogenous VISP. The results showed that the VISP localizes to the perinuclear region as spots. A plasmid expressing VISP fused to enhanced green fluorescent protein (EGFP) was constructed. The transient expression of full-length VISP fused to EGFP in CHSE-214 cells confirmed the spot formation of the VISP at perinuclear region. To determine the region responsible for the perinuclear localization of the VISP, we constructed a series of deletion mutants and, by using these deletion mutants, we found that C-terminal region of the VISP (aa 612-710) is essential for the perinuclear distribution of VISP and that this region contained nuclear receptor binding motif (691-TLTSLLL-697). Our results suggest that VISP localizes to the perinuclear region and C-terminal regions are important for this localization. Further studies on the role of the perinuclear localization of VISP in IHNV growth mali reveal the novel mechanism of IHNV pathogenecity.

• The Journal of the Acoustical Society of Korea
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• v.25 no.2
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• pp.96-100
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• 2006

Kim et al. Proposed Normalized Confidence Measure (NCM) [1-2] and it was successfully used for rejecting mis-recognized words in isolated word recognition. However their experiments were performed on the fixed word speech recognition. In this Paper we apply NCM to the domain of vocabulary independent speech recognition (VISP) and shows the rejection Performance of NCM in VISP. Specialty we Propose vector quantization (VQ) based method for overcoming the problem of unseen triphones. It is because NCM uses the statistics of triphone confidence in the case of triphone-based normalization. According to speech recognition experiments Phone-based normalization method shows better results than RLJC[3] and also triphone-based normalization approach. This results are different with those of Kim et al [1-2]. Concludingly the Phone-based normalization shows robust Performance in VISP domain.