R N Bailey
Assessing the predictive ability of the test-positive findings of an elementary school vision screening
Optometry and vision science : official publication of the American Academy of Optometry
study introduces machine learning mlassisted image segmentation method automatic bubble identification gassolid quasi2d fluidized beds offering enhanced accuracy bubble recognition binary images segmented ml method inhouse lagrangian tracking technique developed track bubble evolution mlassisted segmentation method requires training data achieves accuracy 9875 allows filtering common sources uncertainty hydrodynamics varying illumination conditions outoffocus regions thus providing efficient tool study bubbling standard consistent repeatable manner work mlassisted methodology tested particularly challenging case structured oscillating fluidized beds spatial time evolution bubble position velocity shape characteristics nucleationpropagationrupture cycle new method validated across various operational conditions particle sizes demonstrating versatility effectiveness shows ability capture challenging bubbling dynamics subtle changes velocity size distributions observed beds varying particle size new characteristic features oscillating beds identified including effect frequency particle size bubble morphology aspect shape factors relationship stability flow quantified rate coalescence splitting events type combination classic analysis application ml assisted techniques provides powerful tool improve standardization address reproducibility hydrodynamic studies potential extended gassolid fluidization multiphase flow systems