Its well known that understanding human facial expressions is a key component in understanding emotions and finds broad applications in the field of human-computer interaction (HCI), has been a long-standing issue. In this paper, we shed light on the utilisation of a deep convolutional neural network (DCNN) for facial emotion recognition from videos using the TensorFlow machine-learning library from Google. This work was applied to ten emotions from the Amsterdam Dynamic Facial Expression Set-Bath Intensity Variations (ADFES-BIV) dataset and tested using two datasets.

This work was conducted to study the extraction of eucalyptus oil from natural plants (Eucalyptus camaldulensis leaves) using water distillation method by Clevenger apparatus. The effects of main operating parameters were studied: time to reach equilibrium, temperature (70 to100°C), solvent to solid ratio (4:1 to 8:1 (v/w)), agitation speed (0 to 900 rpm), and particle size (0.5 to 2.5 cm) of the fresh leaves, to find the best processing conditions for achieving maximum oil yield. The results showed that the agitation speed of 900 rpm, temperature 100° C, with solvent to solid ratio 5:1 (v/w) of particle size 0.5 cm for 160 minute give the highest percentage of oil (46.25 wt.%). The extracted oil was examined by HPLC.

Selective recovery of atropine from Datura innoxia seeds was studied. Applying pertraction in a rotating film contactor (RFC) the alkaloid was successfully recovered from native aqueous extracts obtained from the plant seeds. Decane as a liquid membrane and sulfuric acid as a stripping agent were used. Pertraction from native liquid extracts provided also a good atropine refinement, since the most of co-extracted from the plant species remained in the feed or membrane solution. Solid–liquid extraction of atropine from Datura innoxia seeds was coupled with RF-pertraction in order to purify simultaneously the extract obtained from the plant. Applying the integrated process, proposed in this study, a product containing 92.6% atropine was

Water scarcity is one of the most important problems facing humanity in various fields such as economics, industry, agriculture, and tourism. This may push people to use low-quality water like industrial-wastewater. The application of some chemical compounds to get rid of heavy metals such as cadmium is an environmentally harmful approach. It is well-known that heavy metals as cadmium may induce harmful problems when present in water and invade to soil, plants and food chain of a human being. In this case, man will be forced to use the low quality water in irrigation. Application of natural materials instead of chemicals to remove cadmium from polluted water is an environmental friendly approach. Attention was drawn in this research wor

In this research, the effect of multi-walled carbon nanotubes (MWCNTs) on the alumina/chromia (Al₂O₃/Cr₂O₃) nanocomposites has been investigated. Al₂O₃/Cr₂O₃-MWCNTs nanocomposites with variable contents of Cr₂O₃ and MWCNTs were fabricated using coprecipitation process and followed by spark plasma sintering. XRD analysis revealed a good crystallinity of sintered nanocomposites samples and there was only one phase presence of Al₂O₃-Cr₂O₃ solid solution. Density, Vickers microhardness, fracture toughness and fracture strength have been measured in the sintered samples. The results show tha

Surfaces quality is one of the most specified customer requirements for machine parts. The major indication of surfaces quality on machined parts is surface roughness. The research aim is to study the cutting conditions and their effects on the surface roughness. This paper utilizes regression models to predict surface roughness over the machining time for variety of cutting conditions in turning. In the experimental part for turning, different types of materials (Aluminum alloy, Copper alloy, and Gray cast iron) were considered with different cutting speed ( ) and feed rate ( ). A mathematical Model depending on statistical-mathematical method between surface roughness (Rz ) and cutting condition ( , ) were derived, for the three materials

A study in the treatment and reuse of oily wastewater generated from the process of fuel oil treatment of gas turbine power plant was performed. The feasibility of using hollow fiber ultrafiltration (UF) membrane and nanofiltration (NF) membrane type polyamide thin-film composite in a pilot plant was investigated. Three different variables: pressure (0.5, 1, 1.5 and 2 bars), oil content (10, 20, 30 and 40 ppm), and temperature (15, 20, 30 and 40 ᵒC) were employed in the UF process while TDS was kept constant at 150 ppm. Four different variables: pressure (2, 3, 4 and 5 bar), oil content (2.5, 5, 7.5 and 10 ppm), total dissolved solids (TDS) (100, 200,300 and 400 ppm), and temperature (15, 20, 30 and 40 ᵒC) were manipulated with the h

Oily carwash wastewater is a high organic and chemical wastewater. This paper targeted to investigate a treatment to decrease the water consumption and contaminants in car-washing stations. Electrocoagulation combined with ultrasonic energy (Sono-Electrocoagulation) was suggested so that the carwash wastewater is treated to be reused. The effect of both the voltage and time of treatment on the removal of COD, turbidity, conductivity, and total dissolved solids (TDS) were studied at constant initial pH 7 and electrode distance 2 cm. The results showed the best results of removal COD, turbidity, TDS, and reduce electrical conductivity is when the voltage was 30 V and a treatment time of 90 minutes.

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