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 classifiers. A hybrid supervised learning system that takes advantage of rich intermediate features extracted from deep learning compared to traditional feature extraction to boost classification accuracy and parameters is suggested. They provide the same set of characteristics to discover and verify which classifier yields the best classification with our new proposed approach of “hybrid learning.” To achieve this, the performance of classifiers was assessed depending on a genuine dataset that was taken by our camera system. The simulation results show that the support vector machine (SVM) has a mean square error of 0.011, a total accuracy ratio of 98.80%, and an F1 score of 0.99. Moreover, the results show that the LR classifier has a mean square error of 0.035 and a total ratio of 96.42%, and an F1 score of 0.96 comes in the second place. The ANN classifier has a mean square error of 0.047 and a total ratio of 95.23%, and an F1 score of 0.94 comes in the third place. Furthermore, RF, WKNN, DT, and NB with a mean square error and an F1 score advance to the next stage with accuracy ratios of 91.66%, 90.47%, 79.76%, and 75%, respectively. As a result, the main contribution is the enhancement of the classification performance parameters with images of varying brightness and clarity using the proposed hybrid learning approach.
Chaotic features of nuclear energy spectrum in 68Ge nucleus are investigated by nuclear shell model. The energies are calculated through doing shell model calculations employing the OXBASH computer code with effective interaction of F5PVH. The 68Ge nucleus is supposed to have an inert core of 56Ni with 12 nucleons (4 protons and 8 neutrons) move in the f5p-model space ( and ). The nuclear level density of considered classes of states is seen to have a Gaussian form, which is in accord with the prediction of other theoretical studies. The statistical fluctuations of the energy spectrum (the level spacing P(s) and the Dyson-Mehta (or statistics) are well described by the Gaussian orthogonal ens
... Show MoreTin oxide: titanium oxide: bismuth oxide (SnO2 )1–x(TiO 2 :Bi 2O3 ) x composites with different loading ratios (0, 0.1, 0.15, 0.2, 0.25 and 0.3) have numerous new application in microelectronics, sensors, and capacitors. This work concerned with the synthesis of (SnO 2 )1–x(TiO 2 :Bi 2O3 ) xcomposites as well as, thin films which were deposited on glass substrates as well as, silicon wafers by using pulsed laser deposition. The diffraction pattern confirms the anatase teteragonal phase of undoped tin oxide. It was observed some peaks related with titanium and bismuth oxides appeared at high loading ratios. Upon the transmission-spectra analysis, the undoped samples declared transmittance 60–67% in a visible spectrum, and the energy ga
... Show MoreThe gas material balance equation (MBE) has been widely used as a practical as well as a simple tool to estimate gas initially in place (GIIP), and the ultimate recovery (UR) factor of a gas reservoir. The classical form of the gas material balance equation is developed by considering the reservoir as a simple tank model, in which the relationship between the pressure/gas compressibility factor (p/z) and cumulative gas production (Gp) is generally appeared to be linear. This linear plot is usually extrapolated to estimate GIIP at zero pressure, and UR factor for a given abandonment pressure. While this assumption is reasonable to some extent for conventional reservoirs, this may incur
The purpose of the study is to synthesize and characterize a new polytriazole derivative from polyacryloyl chloried, first reaction of polyacryloyl chloride with hydrazine hydrate in the presence of DMF as a solvent to obtained acid hydrazide (1) than reacted with different amide to give poly 1,2,4-triazole derivatives(1a-1c). Newly synthesized compounds were characterized by spectral methods [13C-NMR, 1H-NMR, and FTIR] and calculated some of its physical properties. Also, we worked theoretical study involving calculated the geometric configurations, total energy, dipole moment etc..,. In addition, the inhibition effect of the synthesized compounds (1a-1c) on corrosion of stainless steel in 1M HCl were studied by method of weight lo
... Show MoreBackground: Colorectal cancer (CRC) is one of the top ten most common cancers worldwide. There are multiple risk factors for CRC, one of which is aging. However, in recent years, CRC has been reported in children. Objective: To describe the main characteristics and symptoms of CRC as well as highlight pathologic data for early-onset CRC. Methods: 79 CRC patients were recruited from the Oncology Teaching Hospital in the period February–December 2022. A questionnaire was used to collect demographic and clinical data. Results: 25 (31.6%) of patients were below 50 years of age. 52 (65.8%) patients had tumors in the colon. The most common symptom is bleeding per rectum in both age groups. There was no significant difference in patholog
... Show MoreAutomated detection of Dubas palm infestation by image processing techniques has practical significance as it can improve agricultural efficiency, increase crop yield and quality, protect the environment, and provide data-driven insights. It also reduces the human effort required for pest control and enhances sustainability. In this study, we aimed to automate the detection of Dubas bug infestation in palm trees using deep learning with transfer learning residual neural networks. Based on four models: InceptionResNetV2, ResNet18, ResNet50, and ResNet101, the data used in this study were obtained by drone photography, many images were taken, and then the infected area was extracted. Using two types of data, 185 infected images and 185 health
... Show MoreThe present study attempts to determine the effect of freezing for different periods on preserved bodies of fish in the laboratory to keep for the research and diagnosis of taxonomic studies and not for consumption. It also endeavors to identify the effect of freezing on some morphometric features of the preserved bodies of fishes. Planiliza abu fish were used to conduct the present study. Fish were frozen by regular freezing in the home refrigerator freezer with temperatures reaching four degrees centigrade below zero. Freezing time is distributed over four months; biometric measurements of frozen fish have been taken in these periods represented by body total length, Standard length, and Head length in centimeters using a ruler ve
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The Quranic discourse focused on a lot of vocabularies that carry goals that help man to acquire good, according to a methodology relies on adopting lofty ideas and values. The individual towards society, and the responsibility of society towards the individual. In our present age, the Muslim individual lives in a state of confrontation with deviant ideas, which unfortunately possess the means that make their impact great on society. The study concluded that the Holy Quran contains indicators and determinants of misguided and deviant thought, Which must be avoided because of the seriousness of its effects. Religion, in its general sense, represents a culture that transcends the limits of human ins
... Show MoreFractal geometry is receiving increase attention as a quantitative and qualitative model for natural phenomena description, which can establish an active classification technique when applied on satellite images. In this paper, a satellite image is used which was taken by Quick Bird that contains different visible classes. After pre-processing, this image passes through two stages: segmentation and classification. The segmentation carried out by hybrid two methods used to produce effective results; the two methods are Quadtree method that operated inside Horizontal-Vertical method. The hybrid method is segmented the image into two rectangular blocks, either horizontally or vertically depending on spectral uniformity crit
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