Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

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

Background: Difficulties arise when attempting to imagine the interpupillary line and comparing it with the Fox plane guide and not more difficult than holding any instrument over the movable pupils just to demonstrate the interpupillary line. The aim of this study was to introduce ear lobes as alternative landmarks for the interpupillary line during orientation of the occlusal plane. Also, the other aim was to compare the ear lobes with the pupils of the eyes to verify that they were indifferent as anatomical landmarks. Materials & methods: The alternative landmarks, ear lobes, were presented and the method for orienting the occlusal plane with these landmarks was introduced. Digital pictures of 30 subjects, who participated in the study,

Copper indium disulphide, CuInS2, is a promising absorber material for thin film photovoltaic which has recently attracted considerable attention due to its suitability to reach high efficiency solar cells by using low cost techniques. In this work CuInS2 thin films have been deposited by chemical spray pyrolysis onto glass substrates at ambient atmosphere, using different [Cu]/[In] ratio in the aqueous solutions at substrate temperature 3000C
and different annealing temperatures . Structural and optical properties of CIS films were analyzed by X-ray diffraction, and optical spectroscopy. Sprayed CIS films are polycrystalline with a chalcopyrite structure with a preferential orientation along the 112 direction and no remains of oxides

Polyaniline organic Semiconductor polymer thin films have been prepared by oxidative polymerization at room temperature, this polymer was deposited on glass substrate with thickness 900nm, FTIR spectra was tested , the structural,optical and electrical properties were studied through XRD ,UV-Vis ,IR measurements ,the results was appeared that polymer thin film sensing to NH3 gas.

The research aims to explore the difficulties that encounter teaching geography of cities as perceived by female students. A total of (113) third stage female students / Geography Dept / college of education for women were chosen as a sample for the study. To collect the required data, a questionnaire was used as an instrument; it consisted of six parts represent teaching difficulties. It was a three-point Likert scale instrument with 1 signifying ‘main difficulty, 2 ‘sub-difficulty, and 3 ‘no difficult'. The difficulties organized in descend order, to analyze data, SPSS tool was used. The results revealed that the difficulties of content ranged (2.15-1.18), difficulties of education techniques ranged (2.47-2.04), difficulties of t

A sensitive and accurate colorimetric method was developed for the determination of the Sitagliptin phosphate monohydrate, here and after will be named Sitagliptin, in its pure and pharmaceutical form. The suggested approach is based on boosting the sensitivity of the traditional spectrometric methods by derivatizing Sitagliptin into a colored product that absorbs the visible spectrum at 573 nm. The proposed method has effectively improved the sensitivity and the limit of detection for the analysis of Sitagliptin. A linear calibration curve was obtained over the concentration range of 0.1-10 μg/ml with a correlation coefficient of 0.9983. The calculated recovery was within the range of 98.98–100.11%. While the limit of detection LOD and