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

To date, comprehensive reviews and discussions of the strengths and limitations of Remote Sensing (RS) standalone and combination approaches, and Deep Learning (DL)-based RS datasets in archaeology have been limited. The objective of this paper is, therefore, to review and critically discuss existing studies that have applied these advanced approaches in archaeology, with a specific focus on digital preservation and object detection. RS standalone approaches including range-based and image-based modelling (e.g., laser scanning and SfM photogrammetry) have several disadvantages in terms of spatial resolution, penetrations, textures, colours, and accuracy. These limitations have led some archaeological studies to fuse/integrate multip

Objective: The aim of this study is to detect the effect of continuous exposure to Sodium Nitrite on 8-oxoguanine
DNA glycosylase (OGG1) gene which responsible on DNA repairs. DNA repair play a major role in maintaining
genomic stability when DNA exposure to damage. Genomic stability is very important for keeping body cells
healthy and to prevent many types of tumor development. Many genes are responsible for this job; one of them is
OGG1 gene.
Methodology: In current study two groups of mice were chronically exposed to sodium nitrite for six months and
eighteen months while third group was used as a control. Then sizes of OGG1 were estimated.
Results: The results exhibited in the unexposed (control) mice had two dif

Aim: surface modification of titanium using fiber laser 1064 nm to enhance the bond strength to resin cement. Material and Methods: thirty titanium discs of 0.6 cm x 0.3 cm (diameter and thickness respectively) were categorized after preparation into three groups (n=10) as follows: control group with no surface treatment and two test groups were treated with fiber laser after estimation the appropriate parameters in the pilot study which are 81 ns pulse duration, 30,000 Hz frequency, 50 µm spot size and 10,000 mm/s scanning speed and different average power values (10 W and 20 W) depending on the tested group. Titanium discs surface characterization was performed by scanning electron microscope (SEM), a

The numerical analysis was conducted to studying the influence of length to diameter ratio (L/D) on the behavior of the soil treated with sand columns treated with 8% sodium silicate for both floating and end bearing type by using finite element method (Plaxis 3D Foundation ) for isolated foundation of real dimensions. The analysis’s study indicate that in the floating type the best improvement ratio was achieved at (L/D=8) when using columns with a diameter of (0.5, 0.7), but when using columns with a diameter of 0.3 m, it was noticed that the bearing improvement ratio increases with increasing (L/d). While the results of the analysis for end bearing type show that the higher improvement ratio was achieved at (L/D=4) when using columns w

DeepFake is a concern for celebrities and everyone because it is simple to create. DeepFake images, especially high-quality ones, are difficult to detect using people, local descriptors, and current approaches. On the other hand, video manipulation detection is more accessible than an image, which many state-of-the-art systems offer. Moreover, the detection of video manipulation depends entirely on its detection through images. Many worked on DeepFake detection in images, but they had complex mathematical calculations in preprocessing steps, and many limitations, including that the face must be in front, the eyes have to be open, and the mouth should be open with the appearance of teeth, etc. Also, the accuracy of their counterfeit detectio

The purpose of this research is to identify
the effect of the translation of poetic poem into an artistic picture in the achievement of retention among fifth grade students.
In order to verify the research goal, the first two hypotheses were determined. There are no statistically significant differences between the average scores of the experimental group who study (according to the technical picture) ) And the control group (according to the traditional method of art education) at the level of significance (0,05). The second is that there are no statistically significant differences between the average of the experimental group who study (according to the technical picture) and the control group who study (On According to the trad

This study is due to insufficient development of the issues of initial training in tennis at youthful (student) age. Objective: development of a methodological and scientific-methodological base of students' tennis with current trends in tennis. Summing up the best practices of modern tennis, we came to the conclusion that the formation of the art of reflection backhands in teaching beginner students of sports specialization to achieve future success. In modern conditions in the development of Russian tennis student opens the possibility of using new technologies and programs. Using these approaches, we have developed a training program and tested students' tennis in the pedagogical experiment, which resulted in its effectiveness.

Statistical learning theory serves as the foundational bedrock of Machine learning (ML), which in turn represents the backbone of artificial intelligence, ushering in innovative solutions for real-world challenges. Its origins can be linked to the point where statistics and the field of computing meet, evolving into a distinct scientific discipline. Machine learning can be distinguished by its fundamental branches, encompassing supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning. Within this tapestry, supervised learning takes center stage, divided in two fundamental forms: classification and regression. Regression is tailored for continuous outcomes, while classification specializes in c