Detecting dry eye from ocular surface videos based on deep learning
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The majority of the environmental outputs from gas refineries are oily wastewater. This research reveals a novel combination of response surface methodology and artificial neural network to optimize and model oil content concentration in the oily wastewater. Response surface methodology based on central composite design shows a highly significant linear model with P value <0.0001 and determination coefficient R2 equal to 0.747, R adjusted was 0.706, and R predicted 0.643. In addition from analysis of variance flow highly effective parameters from other and optimization results verification revealed minimum oily content with 8.5 ± 0.7 ppm when initial oil content 991 ppm, tempe
Investigating gender differences based on emotional changes becomes essential to understand various human behaviors in our daily life. Ten students from the University of Vienna have been recruited by recording the electroencephalogram (EEG) dataset while watching four short emotional video clips (anger, happiness, sadness, and neutral) of audiovisual stimuli. In this study, conventional filter and wavelet (WT) denoising techniques were applied as a preprocessing stage and Hurst exponent
Objective: Evaluation of the poly ether keton keton polymer (PEKK) coating material on the commercial pure titanium disks (CP Ti) with or without laser surface structuring. Design: In vitro experimental study of PEKK polymer coated material on the CP Ti disks with or without laser surface structuring. Materials and methods: coating the surface of the commercial pure titanium (CP Ti) disks with PEKK polymer was performed via using frictional mode CO2 laser, then the samples disks analyzed by using FESEM. Results: the FESEM reveal good adherence and distribution of the PEKK coated material over the CP Ti substrate by using the frictional mode CO2 laser at 2 watt and 6 ms pulse duration. Conclusion: the frictional mode CO2 laser considered an
... Show MoreThe aim of this study is to investigate the antibacterial capabilities of different coating durations of three nanoparticle (NP) coatings: molybdenum (Mo), tantalum (Ta), and zinc oxide (ZnO), and their effects on the surface characteristics of 316L stainless steel (SS). The coated substrates underwent characterization utilizing field emission scanning electron microscopy (FE-SEM), energy dispersive X-ray spectrometry (EDX), and X-ray diffractometer (XRD) techniques. The antibacterial efficacy of NPs was evaluated using the agar diffusion method. The FE-SEM and EDX images confirmed the presence of nano-sized particles of Mo, Ta, and ZnO on the surface of the substrates with perfectly symmetrical spheres and a uniform distribution of
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