Face recognition is a crucial biometric technology used in various security and identification applications. Ensuring accuracy and reliability in facial recognition systems requires robust feature extraction and secure processing methods. This study presents an accurate facial recognition model using a feature extraction approach within a cloud environment. First, the facial images undergo preprocessing, including grayscale conversion, histogram equalization, Viola-Jones face detection, and resizing. Then, features are extracted using a hybrid approach that combines Linear Discriminant Analysis (LDA) and Gray-Level Co-occurrence Matrix (GLCM). The extracted features are encrypted using the Data Encryption Standard (DES) for security

Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med

A new and hybrid deep learning-based approach for diagnosing faults in electric vehicle (EV) drive motors is proposed in this article. This article presents a new and hybrid deep learning-based method of diagnosing faults in the drive motors of electric vehicles (EV). In contrast to standard CNNLSTM approaches that depend on SoftMax classification, the introduced framework combines a Random Forest (RF) classifier to enhance the generalization, interpretability, and robustness of fault prediction. Furthermore meant for use on edge computing equipment with IoT integration, the design allows for real-time monitoring in resource-limited settings. The introduced algorithm utilizes a Random Forest (RF) classifier for accurate fault classification

White and black chia seeds were used in some food products, such us gluten –free biscuits processing by using rice flour and chia seeds (white and black) with these amonths 112.5, 74.25, 56.25, 27.5 g with 27.5g of quinoa seeds for treatments 1, 2, 3 and 4 respectively, and comparison sensitively with the control treatment which has no additions including the appearance and homogenization of the product, surface cracks, softness, taste and flavor, core color and the specific volume, some microbiological tests were performed for biscuit product after storage for 4 months at 30 and 50°C including bacterial total count and fungal and yeast count, results showed that there weren’t any observation of bacteria or yeast or fungal growth at

An investigation was conducted to suggest relations for estimating yield and properties of the improved light lubricating oil fraction produced from furfural extraction process by using specified regression.

Mass transfer in mixer-settler has been studied. Mass transfer coefficient of continuous phase, mass transfer coefficient of dispersed phase and the overall mass transfer coefficient extraction of light lubes oil distillate fraction by furfural are calculated in addition to all physical properties of individual components and the extraction mixtures.

The effect of extraction variables were studied such as extraction temperature which ranges from 70 to 110°C and solvent to oil ratio which ranges from 1:1 to 4:1 (wt/wt

This 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

Synthesis three organic inhibitors for carbon steel corrosion: 2-(propylthio)-1H-benzo[d]imidazole (PTBI), 2-(allylthio)- 1H-benzo[d]imidazole (ATBI) and 2-(prop-2-ynylthio)-1H-benzo[d]imidazole (YTBI) were prepared from reaction of 2-mercapto benzimidazole with different alkyl halide. The melting point and TLC were used to confirm the purity of the inhibitors as well as using the [FTIR, 1H-NMR and 13C-NMR] for the identify structures. The synthesized inhibitors were examined by potentiostatic polarization measurement as corrosion inhibitors of carbon steel in acidic media [1M H2SO4 ].The polarization measurement results showed that the mixed type inhibitors. In addition, the efficiency of inhibitors (YTBI) were studied at different con