• 한국멀티미디어학회논문지
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• 제17권3호
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• pp.277-286
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• 2014

본 논문에서는 Gabor 특징과 MDLC 특징, 그리고 co-occurrence 특징의 융합에 의한 질감 특징 기반언어 인식 방법을 제안한다. 제안된 방법에서는 먼저 시험 영상에 Gabor 변환에 이은 크기 연산자를 적용하여 Gabor 크기 영상을 얻고 그 통계치를 계산하여 결과를 벡터화한다. 이어서 MDLC 연산자를 이용하여 MDLC 영상을 얻고 역시 그 통계치를 계산하여 벡터화한다. 다음으로 시험 영상으로부터 GLCM을 계산하고 이를 이용하여 co-occurrence 특징을 계산한 다음 벡터화한다. 이들 Gabor, MDLC, co-occurrence 특징에 의한 벡터들은 벡터 융합에 의하여 특징 벡터로 사용된다. 분류 단계에서는 얼굴 인식에 주로 사용되는 WPCA를 분류기로 하여 시험 특징 벡터와 가장 유사한 학습 특징 벡터를 찾는다. 제안된 방법의 성능은 15개국 언어의 문서를 스캔하여 얻은 시험 문서 영상 DB에 대한 평균 인식률을 조사하여 알아본다. 실험 결과 제안된 방법은 시험 DB에 대하여 비교적 낮은 특징 벡터 차원으로 매우 우수한 언어 인식 성능을 보여준다.

• Mass Spectrometry Letters
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• 제5권4호
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• pp.95-103
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• 2014

Characterization and studies of proteome are challenging because biological samples are complex, with a wide dynamic range of abundance. At present the proteins are identified by digestion into peptides, with subsequent identification of the peptides by mass spectrometry (MS). MS is a powerful technique for the purpose, but it cannot identify every peptide in such complex mixtures simultaneously. For accurate analysis and quantification it is important to separate the peptides first by chromatography into fractions of a size that MS can handle. With these less complex fractions, the probability is increased of identifying peptides of low abundance that would otherwise experience ion suppression effects due to the presence of peptides of high abundance. Enrichment for peptides with certain post-translational modifications helps to increase their detection rates as well. Electrostatic repulsion-hydrophilic interaction chromatography (ERLIC) is a mixed-mode chromatographic technique which combines the use of electrostatic repulsion and hydrophilic interaction. This review provides an overview of ERLIC and its various proteomics applications. ERLIC has been demonstrated to have good orthogonality to reverse phase liquid chromatography (RPLC), making it useful as a first dimension in multidimensional liquid chromatography (MDLC) and fractionation of digests in general. Peptides elute in order of their isoelectric points and polarity. ERLIC has also been successfully utilized for the enrichment for phosphopeptides and glycopeptides, facilitating their identification. In addition, it is promising for the study of peptide deamidation. ERLIC performs comparably well or better than established methods for these various applications, and serves as a viable and efficient workflow alternative.