Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep learning model was utilized to resize images and feature extraction. Finally, different ML classifiers have been tested for recognition based on the extracted features. The effectiveness of each classifier was assessed using various performance metrics. The results show that the proposed system works well, and all the methods achieved good results; however, the best results obtained were for the Support Vector Machine (SVM) with a linear kernel.
This study deals with the subject of art criticism by using Erwin Panofsky's theory to analyze a few Saudi artists' works. The study aims to identify Panofsky's theory and provide criticism of some Saudi artworks using it. The importance of the study is that it enriches the field of art criticism in the Kingdom of Saudi Arabia and helps critics and artists in using Panofsky’s theory to analyze artworks.
The study sample consists of six artworks produced in 2021 by six contemporary Saudi artists. In the theoretical section, the study dealt with several topics; first, is art criticism, the second part presents Panofsky’s theory with its three stages, the final part deals with the beginning of Saudi art until present time and its
Al-Rustamiyah plant is the oldest and biggest sewage treatment plant in Iraq; it locates in the south of Baghdad city. The plant suffers from serious problems associated with overflow and low capacity. The present work aims to upgrade the heart of biological treatment process through suggesting the use of membrane bioreactor; (MBR). In this work, fouling of membrane during sewage treatment has been analyzed experimentally and theoretically by fouling mechanisms. Aeration has been applied in order to control fouling through producing effective diameters of air bubbles close to the membrane walls. Effect of air flow rate on flux decline was investigated. Hermia's models were used to investigate the fouling mechanisms. The results showed th
... Show MoreChemical bath deposition was used to synthesize ZnO nanorods (NRs) on glass and fluorine_doped tin oxide (FTO) substrates. X-ray diffraction was performed to examine the crystallinity of ZnO nanorod. Results showed that ZnO NRs had a wurtzite crystal structure. Field emission scanning electron microscopy images showed that glass sample had rod-like structure distribution with (50 nm) diameter and average length of approximately (700 nm), whereas the FTO-coated glass sample had 25 nm diameter and average length of approximately 950 nm. The direct optical transition band gaps of the glass and FTO_coated glass samples were( 4 and 4.43 eV), respectively. The structural and optical properties of the synthesized ZnO p
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Analyzing the size of the interrelationships between the main economic sectors in the Iraqi economy is an important necessity to know the impact of each sector on other economic sectors on the basis of the interrelationships and reciprocity between them, and what these relationships have achieved in terms of enhancing development and increasing the gross domestic product. To achieve the objectives of the study, we relied on mathematical (quantitative) analysis using user-product tables. Issued by the Ministry of Planning / Central Bureau of Statistics and Research (Directorate of National Accounts) for the economic sectors that make up the Iraqi economy. The study conc
... Show MoreThe two-dimensional transient heat conduction through a thermal insulation of temperature dependent thermal properties is investigated numerically using the FVM. It is assumed that this insulating material is initially at a uniform temperature. Then, it is suddenly subjected at its inner surface with a step change in temperature and subjected at its outer surface with a natural convection boundary condition associated with a periodic change in ambient temperature and heat flux of solar radiation. Two thermal insulation materials were selected. The fully implicit time scheme is selected to represent the time discretization. The arithmetic mean thermal conductivity is chosen to be the value of the approximated thermal conductivity at the i
... Show MoreDuring the last two decades, nanomaterial application has gained a significant attraction into asphalt technology due to their effect in enhancing asphalt binder improving the asphaltic mixture. This study will modify the asphalt binder with two different nano types, nano SiO2 and CaCO3, at levels ranging from 1% to 7%. The resulting optimum nano-modified Asphalt will be subject to a series of rheological tests, including dynamic shear rheometer (DSR), Viscosity, and bending beam rheometer (BBR) to determine asphalt binder sensitivity towards low-medium-high temperature range. Results indicate that both nano types improved the physical characteristics of Asphalt, and 5% by weight of Asphalt was suggested as a reasonable dosage of nano-SiO2
... Show MoreOn Saturday, May 13, 2023, a glorious day was engraved in the history of Al-Kindy College Medical Journal as it is the day of indexing the journal in the Scopus Database Journals. The journal has paced a strenuous journey to make that achievement.
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
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