Shirley M Moore, Vilailert Komton, Clara Adegbite-Adeniyi, Mary A Dolansky, Heather K Hardin, Elaine A Borawski
Development of the Systems Thinking Scale for Adolescent Behavior Change
Western journal of nursing research
starch alcohol serve pivotal indicators assessing quality lees fermentation paper two hyperspectral imaging hsi techniques visiblenearinfrared visnir nir utilized acquire separate hsi data fused analyzed toforecast starch alcohol contents fermentation lees five preprocessing methods first used preprocess visnir nir fused visnir nir data partial least squares regression models established determine best preprocessing method following competitive adaptive reweighted sampling successive projection algorithm principal component analysis algorithms used extract characteristic wavelengths accurately predict starch alcohol levels finally support vector machine svmadaboost xgboost models built based lowlevel fusion llf intermediatelevel fusion ilf single visnir nir well fused data results showed svmadaboost model built using llf data afterpreprocessing standard normalized variable accurate predicting starch content rp2 rp2 09976 root mean square error prediction rmsep 00992 xgboost model built using ilf data accurate predicting alcohol content rp2rp2 09969 rmsep 00605 conclusion analysis fused data distinct hsi technologies facilitates rapid precise determination starch alcohol contents fermented grains