The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Convolutional Neural Network (CNN) has been chosen as a better option for the training process because it produces a high accuracy. The final accuracy has reached 91.18% in five different classes. The results are discussed in terms of the probability of accuracy for each class in the image classification in percentage. Cats class got 99.6 %, while houses class got 100 %.Other types of classes were with an average score of 90 % and above.
A simple straightforward mathematical method has been developed to cluster grid nodes on a boundary segment of an arbitrary geometry that can be fitted by a relevant polynomial. The method of solution is accomplished in two steps. At the first step, the length of the boundary segment is evaluated by using the mean value theorem, then grids are clustered as desired, using relevant linear clustering functions. At the second step, as the coordinates cell nodes have been computed and the incremental distance between each two nodes has been evaluated, the original coordinate of each node is then computed utilizing the same fitted polynomial with the mean value theorem but reversibly.
The method is utilized to predict
... Show Moreأثر استراتيجية التدريس البصري باستخدام الانـفوجرافيك في التحصيل والتفكير البصري لدى طلاب المرحلة المتوسطة فـي مادة الرياضيات
In this paper, a statistical analysis compared the pattern of distribution of spending on various goods and services and to identify the main factors that control the rates of spending between the survey of social and economic status of families in Iraq for the year (2007) and the survey of Iraq knowledge net work (IKN) for the year (2011), which were carried out by the Central Bureau of Statistics through the use of factor analysis and cluster analysis, using the ready statistical software package ready (SPSS) to gain access to the results.
Abstract
In this work, two algorithms of Metaheuristic algorithms were hybridized. The first is Invasive Weed Optimization algorithm (IWO) it is a numerical stochastic optimization algorithm and the second is Whale Optimization Algorithm (WOA) it is an algorithm based on the intelligence of swarms and community intelligence. Invasive Weed Optimization Algorithm (IWO) is an algorithm inspired by nature and specifically from the colonizing weeds behavior of weeds, first proposed in 2006 by Mehrabian and Lucas. Due to their strength and adaptability, weeds pose a serious threat to cultivated plants, making them a threat to the cultivation process. The behavior of these weeds has been simulated and used in Invas
... Show MoreWith the fast-growing of neural machine translation (NMT), there is still a lack of insight into the performance of these models on semantically and culturally rich texts, especially between linguistically distant languages like Arabic and English. In this paper, we investigate the performance of two state-of-the-art AI translation systems (ChatGPT, DeepSeek) when translating Arabic texts to English in three different genres: journalistic, literary, and technical. The study utilizes a mixed-method evaluation methodology based on a balanced corpus of 60 Arabic source texts from the three genres. Objective measures, including BLEU and TER, and subjective evaluations from human translators were employed to determine the semantic, contextual an
... Show MoreWater is an essential aspect of life and important in evolution. Recently the potable water quality topic has received much attention. The study aims to determine drinking water quality in Al-Najaf City by collecting samples throughout Al-Najaf city and comparing the results with the Iraqi guidelines (IQS 417) and World Health Organization (WHO) guidelines, as well as to calculate the WQI. Samples were tested in the laboratory between December 2021 and June 2022. The results showed that multiple parameters exceeded the allowable limits during both testing periods; during winter months, the results of TDS and turbidity exceeded the upper limits in multiple locations. Total hardness values also
... Show MoreNatural convection heat transfer is experimentally investigated for laminar air flow in a vertical circular tube by using the boundary condition of constant wall heat flux in the ranges of (RaL) from (1.1*109) to (4.7*109). The experimental set-up was designed for determining the effect of different types of restrictions placed at entry of heated tube in bottom position, on the surface temperature distribution and on the local and average heat transfer coefficients. The apparatus was made with an electrically heated cylinder of a length (900mm) and diameter (30mm). The entry restrictions were included a circular tube of same diameter as the heated cylinder but with lengths of (60cm, 120cm), sharp-edge and
... Show MoreThe aim of this paper is to approximate multidimensional functions by using the type of Feedforward neural networks (FFNNs) which is called Greedy radial basis function neural networks (GRBFNNs). Also, we introduce a modification to the greedy algorithm which is used to train the greedy radial basis function neural networks. An error bound are introduced in Sobolev space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result is published in [16]).