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.

   A microbubble air flotation technique was used to remove chromium ions from simulated wastewater (e.g. water used for electroplating, textiles, paints and pigments, and tanning leather). Experimental parameters were investigated to analyze the flotation process and determine the removal efficiency. These parameters included the location of the sampling port from the bottom of the column, where the diffuser is located to the top of flotation column (30, 60, and 90 cm), the type of surfactant (anionic, SDS, or cationic, CTAB) and its concentration (5, 10, 15, and 20 mg/L), the pH of the initial solution (3, 5, 7, 9, and 11), the initial contaminant concentration (10, 20, 30, and 40 mg/L), the gas flow rate (0.1, 0.2, 0.3, and 0.5 L/mi

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

A mixture of algae biomass (Chrysophyta, Cyanophyta, and Chlorophyte) has been investigated for its possible adsorption removal of cationic dyes (methylene blue, MB). Effect of pH (1-8), biosorbent dosage (0.2-2 g/100ml), agitated speed (100-300), particle size (1304-89μm), temperature (20-40˚C), initial dye concentration (20-300 mg/L), and sorption–desorption were investigated to assess the algal-dye sorption mechanism. Different pre-treatments, alkali, protonation, and CaCl2 have been experienced in order to enhance the adsorption capacity as well as the stability of the algal biomass. Equilibrium isotherm data were analyzed using Langmuir, Freundlich, and Temkin models. The maximum dye-sorption capacity was 26.65 mg/g at pH= 5, 25

In this research project, a tip-tilting angle of a photovoltaic solar cell was developed to increase generated electrical power output. An active, accurate, and simple dual-axis tracking system was designed by using an Arduino Uno microprocessor. The system consisted of two sections: software and apparatus (hardware). It was modified by using a group of light-dependent resistor sensors, and two DC servo motors were utilized to rotate the solar panel to a location with maximum sunlight. These components were arranged in a mechanical configuration with the gearbox. The three locations of the solar cell were chosen according to the tilt angle values, at zero angles, which included an optimal 33-degree angle for the Baghdad location and

Four photosensitizers were used to test inhibitory effect of Helicobacter pylori bacteria using
low power helium: neon red laser radiation. Biopsies were collected from 176 patients and H. pylori were
isolated, identified and bacterial suspension was prepared. Samples of this suspension were mixed with
various low concentrations of the test sensitizer. The mixture samples were exposed to different laser
radiation doses. The samples were then inoculated and the inhibition zones were studied and compared
with their analogues of control samples. The most effective sensitizer with optimum concentration and
irradiation dose was determined. Statistical analysis of results was performed. The sensitizers' toluidine
blue and