• International Journal of Industrial Entomology and Biomaterials
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• v.14 no.1
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• pp.23-32
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• 2007

The nature of genetic variation and diversity among the 65 multivoltine silkworm genotypes was evaluated for 16 post cocoon characters. The components of genetic variation revealed higher PCV (60.487%) and GCV (44.56%) for evenness (variation 1) followed by cohesion (PCV=55.38%, GCV=40.36%) and non-broken filament length (PCV=32.05%, GCV=31.28%). The higher heritability ($h^2$ in broad sense) was observed for boil-off loss (95.6%) followed by non-broken filament length (95.22%). The both genotypic and phenotypic correlation indicated significant positive correlation of filament length with non-broken filament length, silk recovery, raw silk, neatness, and low neatness; and negative correlation with denier, renditta and silk waste. The principal component analysis (PCA) revealed 75.381 % of total variance from the five principal components extracted. On the basis of Mahalonobis' $D^2$ values (Ward's minimum variance), the sixty-five multivoltine silkworm genotypes were classified in to 9 clusters with substantial inter and intra cluster distances. Number of genotypes included in different clusters varied from 3 to 17. The results indicated that the optimum distance obtained in cluster VII (15.059) along with higher cluster mean values especially for filament length, non broken filament length, renditta, silk recovery, silk waste, and raw silk emphasized the utilization of these genotypes in the conventional silkworm breeding programme for improvement of multivoltine silk fibre quality. The possibility of exploiting genetic variation in post cocoon traits for efficient breeding programme is discussed.

• Journal of Korea Multimedia Society
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• v.21 no.7
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• pp.745-754
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• 2018

Language is an essential tool for verbal and emotional communication among human beings, enabling them to engage in social interactions. Although a majority of hearing-impaired people can speak; however, they are unable to receive feedback on their pronunciation most of them can speak. However, they do not receive feedback on their pronunciation. This results in impaired communication owing to incorrect pronunciation, which causes difficulties in their social interactions. If hearing-impaired people could receive continuous feedback on their pronunciation and phonation through lip-reading training, they could communicate more effectively with people without hearing disabilities, anytime and anywhere, without the use of sign language. In this study, the mouth area is detected from videos of learners speaking monosyllabic words. The grayscale information of the detected mouth area is used to estimate a velocity vector using Optical Flow. This information is then quantified as feature values to classify vowels. Subsequently, a system is proposed that classifies monosyllables by algebraic computation of geometric feature values of lips using the characteristics of articulatory phonation. Additionally, the system provides feedback by evaluating the comparison between the information which is obtained from the sample categories and experimental results.