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Prediction of whiteness index of cotton using bleaching process variables by fuzzy inference system
Abu Naser Md Ahsanul Haque,Shamima Akter Smriti,Manwar Hussain,Nawshin Farzana,Fahmida Siddiqa,Md. Azharul Islam 한국의류학회 2018 Fashion and Textiles Vol.5 No.1
A fuzzy prediction model has been built based on hydrogen peroxide concentration, temperature and time of bleaching as the input variables and knitted fabric whiteness index as the output variable. The process parameters affecting the whiteness index of cotton knitted fabrics are very non-linear. Fuzzy inference system is a prospective modeling tool as it can map effectively in nonlinear domain with minimum investigational data. Triangular-shaped membership functions were considered for the variables and total 48 rules were created in this study. It was found that the sole effect of the concentration of hydrogen peroxide on whiteness is pretty low, but is affected by temperature noticeably even in a fixed concentration of hydrogen peroxide. The model proposed in the present study has been verified by additional experimental data set. The root mean square, mean absolute error percentage and coefficient of determination (R 2 ) between the predicted and experimental values were found to be 0.536, 0.798 and 0.959 respectively. The results validate that the model can be applied suitably for the prediction of fabric whiteness index in textile industries.
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Urmy Nushrat Jahan,Hossain Md. Mokbul,Shamim Abu Ahmed,Khan Md. Showkat Ali,Hanif Abu Abdullah Mohammad,Hasan Mehedi,Akter Fahmida,Mitra Dipak Kumar,Hossaine Moyazzam,Ullah Mohammad Aman,Sarker Samir 질병관리본부 2020 Osong Public Health and Research Persptectives Vol.11 No.6
Objectives To assess the prevalence of noncommunicable disease (NCD) risk factors and the factors associated with the coexistence of multiple risk factors (≥ 2 risk factors) among adolescent boys and girls in Bangladesh. Methods Data on selected NCD risk factors collected from face to face interviews of 4,907 boys and 4,865 girls in the national Nutrition Surveillance round 2018–2019, was used. Descriptive analysis and multivariable logistic regression were performed. Results The prevalence of insufficient fruit and vegetable intake, inadequate physical activity, tobacco use, and being overweight/obese was 90.72%, 29.03%, 4.57%, and 6.04%, respectively among boys; and 94.32%, 50.33%, 0.43%, and 8.03%, respectively among girls. Multiple risk factors were present among 34.87% of boys and 51.74% of girls. Younger age (p < 0.001), non-slum urban (p < 0.001) and slum residence (p < 0.001), higher paternal education (p = 0.001), and depression (p < 0.001) were associated with the coexistence of multiple risk factors in both boys and girls. Additionally, higher maternal education (p < 0.001) and richest wealth quintile (p = 0.023) were associated with the coexistence of multiple risk factors in girls. Conclusion The government should integrate specific services into the existing health and non-health programs which are aimed at reducing the burden of NCD risk factors.
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