Vol. 6, Issue 1 (2025)
Natural settings make it challenging to identify facial expressions since head position, illumination level, and occlusion vary. Thus, developing a more generic model without front-facing images alone is quite crucial. This research proposes a facial expression recognition model based on pre-trained deep convolutional neural networks with transfer learning. The model was trained on several cases to classify face expressions into seven classifications efficiently. The proposed system used the EfficientNetB0 model that has one dense dropout layer. The model first rescales and norms the input dataset in the input layer that takes images of a larger resolution to get better results. After entering 7 blocks sequential
... Show MoreThis investigation presents an experimental and analytical study on the behavior of reinforced concrete deep beams before and after repair. The original beams were first loaded under two points load up to failure, then, repaired by epoxy resin and tested again. Three of the test beams contains shear reinforcement and the other two beams have no shear reinforcement. The main variable in these beams was the percentage of longitudinal steel reinforcement (0, 0.707, 1.061, and 1.414%). The main objective of this research is to investigate the possibility of restoring the full load carrying capacity of the reinforced concrete deep beam with and without shear reinforcement by using epoxy resin as the material of repair. All be
... Show MoreThis research suggests a robust and systematic way for Arabic Sentiment Analysis using a vast dataset of 66,666 text reviews. One of the main advantages of this study is that the dataset was perfectly balanced (33,333 positive samples and 33,333 negative samples). In machine learning, this 50/50 split is important because it eliminates class bias and enables the predictive model to treat both sentiment classes equally. As shown in the values of the metrics — overall accuracy, weighted precision, weighted recall, and F1 score — there is great similarity among them, indicating a stable and reliable assessment of the model's real potential throughout the Arabic dataset. Based on data profile, the average word count per review is 42.3
... Show MoreThe aim of this study is to evaluate the levels of trace elements Magnesium (Mg), Zinc (Zn), Copper (Cu), and Selenium (Se) in blood sera of asthmatic patients by Atomic Absorption Spectrophotometry (AAS). The concentrations of Mg, Cu, and Zn have been determined by Flame Atomic Absorption spectrophotometry (FAAS), and Se with flameless Graphite Furnace Atomic Absorption Spectrophotometry (GFAAS). The study involves (55) asthmatic patients as study group and (28) subjects as control from both genders. Serum levels of Mg, Cu, and Se were significantly higher (p<0.001 for all) in patients when compared with healthy subjects, while Zn level was relatively significant (p<0.05). Our observations confirm the efficacy and applicability of (AAS) in
... Show MoreBackground Cadmium (Cd), one of the most abundant heavy metals, is extremely toxic to both humans and animals. hIt is well known that zinc (Zn) administration reduces Cd-induced toxicity and that metallothioneins can have a protective effect in biological systems to mitigate Cd toxicity. Objective The aim of the current study to determine if Zn administration affected the induction of MT-1 and MT-2 in the liver tissue in mice exposed to Cd. Materials and methods Metallothionein protein (MT) level in the tissue of male mice were detected using the anion -exchang high-performance liquid chromatography coupled (HPLC)assay and immunohistochemical staining. Results Single treatment to zinc or cadmium increase the level of MT in the liver, but zi
... Show MoreThe galvanic corrosion of the (Cu - Fe), (Cu - Zn) and (Fe - Zn) couples have been investigated in 3.5% NaCl solution, 40ºC, different velocities (Re = 5000, 10000 and 15000) and different area ratio’s of cathode to anode (AR= 0.5,1 and 2), by using commercial metal pipe (cylindrical tube).The Zero Resistance Ammeter has been used to measure the galvanic current (Ig) and galvanic potential (Eg) with time. The galvanic current density increases with increasing velocity (Re) and the area ratio (AR). The galvanic potential (Eg) is shifted to less negative with increasing velocity (Re) and the area ratio (AR). A statistical relations for the galvanic current density and galvanic potential as a function of (Re). and the area ratio had been
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