Key-frame selection plays an important role in facial expression recognition systems. It helps in selecting the most representative frames that capture the different poses of the face. The effect of the number of selected keyframes has been studied in this paper to find its impact on the final accuracy of the emotion recognition system. Dynamic and static information is employed to select the most effective key-frames of the facial video with a short response time. Firstly, the absolute difference between the successive frames is used to reduce the number of frames and select the candidate ones which then contribute to the clustering process. The static-based information of the reduced sets of frames is then given to the fuzzy C-Means algorithm to select the best C-frames. The selected keyframes are then fed to a graph mining-based facial emotion recognition system to select the most effective sub-graphs in the given set of keyframes. Different experiments have been conducted using Surrey Audio-Visual Expressed Emotion (SAVEE) database and the results show that the proposed method can effectively capture the keyframes that give the best accuracy with a mean response time equals to 2.89.
Background In recent years, there has been a notable increase in the level of attention devoted to exploring capabilities of nanoparticles, specifically gold nanoparticles AuNPs, within context of modern times. AuNPs possess distinct biophysical properties, as a novel avenue as an antibacterial agent targeting Streptococcus Mutans and Candida Albicans. The aim of this study to create a nano-platform that has the potential to be environmentally sustainable, in addition to exhibiting exceptional antimicrobial properties against Streptococcus Mutans as well as Candida Albicans. Methods this study involved utilization of
In this study, manganese dioxide (MnO₂) nanoparticles (NPs) were synthesized via the hydrothermal method and utilized for the adsorption of Janus green dye (JG) from aqueous solutions. The effects of MnO₂ NPs on kinetics and diffusion were also analyzed. The synthesized NPs were characterized by scanning electron microscopy (SEM), X-ray diffraction (XRD), energy-dispersive X-ray analysis (EDX), and Fourier-transform infrared spectroscopy (FT-IR), with XRD confirming the nanoparticle size of 6.23 nm. The adsorption kinetics were investigated using three models: pseudo-first-order (PFO), pseudo-second-order (PSO), and the intraparticle diffusion model. The PSO model provided the best fit (R² = 0.999), indicating that the adsorpti
... Show MoreA simple, environmental friendly and selective sample preparation technique employing porous membrane protected micro-solid phase extraction (μ-SPE) loaded with molecularly imprinted polymer (MIP) for the determination of ochratoxin A (OTA) is described. After the extraction, the analyte was desorbed using ultrasonication and was analyzed using high performance liquid chromatography. Under the optimized conditions, the detection limits of OTA for coffee, grape juice and urine were 0.06 ng g−1, 0.02 and 0.02 ng mL−1, respectively while the quantification limits were 0.19 ng g−1, 0.06 and 0.08 ng mL−1, respectively. The recoveries of OTA from coffee spiked at 1, 25 and 50 ng g−1, grape juice and urine samples at 1, 25 and 50 ng mL
... Show MoreA chemometric method, partial least squares regression (PLS) was applied for the simultaneous determination of piroxicam (PIR), naproxen (NAP), diclofenac sodium (DIC), and mefenamic acid (MEF) in synthetic mixtures and commercial formulations. The proposed method is based on the use of spectrophotometric data coupled with PLS multivariate calibration. The Spectra of drugs were recorded at concentrations in the linear range of 1.0 - 10 μg mL-1 for NAP and from 1.0 - 20 μg mL-1 for PIR, DIC, and MEF. 34 sets of mixtures were used for calibration and 10 sets of mixtures were used for validation in the wavelength range of 200 to 400 nm with the wavelength interval λ = 1 nm in methanol. This method has been used successfully to quant
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