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A New Model Design for Combating COVID -19 Pandemic Based on SVM and CNN Approaches
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       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial lung CT-scans into two groups (COVID-19 and NonCOVID-19) had been proposed. A dataset used is 960 slices of CT scan collected from Iraqi patients /Ibn Al-Nafis teaching hospital. The performance metrics are used in this study (accuracy, recall, precision, and F1 scores). The results indicate that the proposed approach generated a high-quality model for the collected dataset, with an overall accuracy of 98.95% and an overall recall of 97 %.

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Publication Date
Thu Jun 01 2023
Journal Name
Iraqi Journal Of Physics
Cytotoxic Activity of CuO NPs Prepared by PLAL Against Liver Cancer (Hep-G2) Cell Line and HdFn Cell Lines
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A simple physical technique was used in this study to create stable and cost-effective copper oxide (CuO) nanoparticles from pure copper metal using the pulsed laser ablation technique. The synthesis of crystalline CuO nanoparticles was confirmed by various analytical techniques such as particle concentration measurement using atomic absorption spectrometry (AAS), field emission scanning electron microscopy (FE-SEM), the energy dispersive X-ray (EDX), and X-ray diffraction (XRD) to determine the crystal size and identify of the crystal structure of the prepared particles. The main characteristic diffraction peaks of the three samples were consistent. The corresponding 2θ is also consistent, and the cytotoxicity of the nanoparticles was

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Publication Date
Wed Oct 09 2024
Journal Name
Engineering, Technology & Applied Science Research
Improving Pre-trained CNN-LSTM Models for Image Captioning with Hyper-Parameter Optimization
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The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of

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Publication Date
Thu Nov 17 2022
Journal Name
Journal Of Discrete Mathematical Sciences And Cryptography
Minimum spanning tree application in Covid-19 network structure analysis in the countries of the Middle East
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Coronavirus disease (Covid-19) has threatened human life, so it has become necessary to study this disease from many aspects. This study aims to identify the nature of the effect of interdependence between these countries and the impact of each other on each other by designating these countries as heads for the proposed graph and measuring the distance between them using the ultrametric spanning tree. In this paper, a network of countries in the Middle East is described using the tools of graph theory.

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Publication Date
Wed Dec 08 2021
Journal Name
J. Inf. Hiding Multim. Signal Process.
Predication of Most Significant Features in Medical Image by Utilized CNN and Heatmap.
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The growth of developments in machine learning, the image processing methods along with availability of the medical imaging data are taking a big increase in the utilization of machine learning strategies in the medical area. The utilization of neural networks, mainly, in recent days, the convolutional neural networks (CNN), have powerful descriptors for computer added diagnosis systems. Even so, there are several issues when work with medical images in which many of medical images possess a low-quality noise-to-signal (NSR) ratio compared to scenes obtained with a digital camera, that generally qualified a confusingly low spatial resolution and tends to make the contrast between different tissues of body are very low and it difficult to co

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Publication Date
Wed Jun 01 2022
Journal Name
Journal Of The College Of Languages (jcl)
Criticism and study of Al-Bandari's Arabic translation of the story Bigan and Manijeh by Shahnameh Ferdowsi: نقد و بررسی ترجمه¬ی عربی بنداری به داستان بیژن و منیژه از شاهنامه¬ی فردوسی
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      Among Persian poets and literary works, Ferdowsi and Shahnameh have a distinctive and prominent place. Since the 5th  C. AH , they took the interest of all Persian language and literature scholars and were one of the first books to be translated into different languages including Arabic by Al Fatih Bin Ali Bin Mohammed Al-Bandari in  the year of (620)AH  .Because it was completed in the early 7th C. AH and in terms of antiquity, there is no older copy than  of Al-Bandari’s version  which holds great value in the analysis of  Shahnameh other different copies.

      To find out the how far analogy goes, the present paper makes a general comparisons of  Bijan and Manijeh in Shahnameh Fer

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Publication Date
Thu Feb 01 2018
Journal Name
Iet Signal Processing
Signal compression and enhancement using a new orthogonal‐polynomial‐based discrete transform
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Publication Date
Mon Dec 05 2022
Journal Name
Baghdad Science Journal
Short Text Semantic Similarity Measurement Approach Based on Semantic Network
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Estimating the semantic similarity between short texts plays an increasingly prominent role in many fields related to text mining and natural language processing applications, especially with the large increase in the volume of textual data that is produced daily. Traditional approaches for calculating the degree of similarity between two texts, based on the words they share, do not perform well with short texts because two similar texts may be written in different terms by employing synonyms. As a result, short texts should be semantically compared. In this paper, a semantic similarity measurement method between texts is presented which combines knowledge-based and corpus-based semantic information to build a semantic network that repre

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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Synthesizing, Structuring, and Characterizing Bioactivities of .Cr(III), La(III), and Ce(III) .Complexes with Nitrogen, Oxygen .and Sulpher donor bidentate Schiff base ligands
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Two Schiff bases, namely, 3-(benzylidene amino) -2-thioxo-6-methyl 2,5-dihydropyrimidine-4(3H)-one (LS])and 3-(benzylidene amino)-6-methyl pyrimidine 4(3H, 5H)-dione(LA)as chelating ligands), were used to prepare some complexes of Cr(III), La(III), and Ce(III)] ions. Standard physico-chemical procedures including metal analysis M%, element microanalysis (C.H.N.S) , magnetic susceptibility, conductometric measurements, FT-IR and UV-visible Spectra were used to identify Metal (III) complexes and  Schiff bases (LS) and (LA). According to findings, a [Cr(III) complex] showed six coordinated octahedral geometry, while [La(III), and Ce(III) complexes]were structured with coordination number seven.  Schiff's bases a

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Publication Date
Wed Aug 21 2019
Journal Name
Al-khwarizmi Engineering Journal
Design and Optimization of a Surface-Mounted Permanent-Magnet Linear Synchronous Motor with Maxwell ANSYS
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Linear motor offers several features in many applications that require linear motion. Nevertheless, the presence of cogging force can deteriorate the thrust of a permanent magnet linear motor. Using several methodologies, a design of synchronous single sided linear iron-core motor was proposed. According to exact formulas with surface-mounted magnets and concentrated winding specification, which are relying on geometrical parameters. Two-dimensional performance analysis of the designed model and its multi-objective optimization were accomplished as a method to reduce the motor cogging force using MAXWELL ANSYS. The optimum model design results showed that the maximum force ripple was approximatrly reduced by 81.24%compared to the origina

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Publication Date
Wed Jan 01 2025
Journal Name
Iv. International Rimar Congress Of Pure, Applied Sciences
A New Intrusion Detection Approach Based on RNA Encoding and K-Means Clustering Algorithm Using KDD-Cup99 Dataset
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Intrusion detection systems (IDS) are useful tools that help security administrators in the developing task to secure the network and alert in any possible harmful event. IDS can be classified either as misuse or anomaly, depending on the detection methodology. Where Misuse IDS can recognize the known attack based on their signatures, the main disadvantage of these systems is that they cannot detect new attacks. At the same time, the anomaly IDS depends on normal behaviour, where the main advantage of this system is its ability to discover new attacks. On the other hand, the main drawback of anomaly IDS is high false alarm rate results. Therefore, a hybrid IDS is a combination of misuse and anomaly and acts as a solution to overcome the dis

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