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bsj-6782
Breast Cancer MRI Classification Based on Fractional Entropy Image Enhancement and Deep Feature Extraction
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Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature extraction step to enhance and preserve the fine details of the breast MRI scans boundaries by using fractional integral entropy FIE algorithm, to reduce the effects of the intensity variations between MRI slices, and finally to separate the right and left breast regions by exploiting the symmetry information. The obtained features are classified using a long short-term memory (LSTM) neural network classifier. Subsequently, all extracted features significantly improves the performance of the LSTM network to precisely discriminate between pathological and healthy cases. The maximum achieved accuracy for classifying the collected dataset comprising 326 T2W-TSE images and 326 STIR images is 98.77%. The experimental results demonstrate that FIE enhancement method improve the performance of CNN in classifying breast MRI scans. The proposed model appears to be efficient and might represent a useful diagnostic tool in the evaluation of MRI breast scans.

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Publication Date
Mon Mar 11 2019
Journal Name
Baghdad Science Journal
Solving Mixed Volterra - Fredholm Integral Equation (MVFIE) by Designing Neural Network
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       In this paper, we focus on designing feed forward neural network (FFNN) for solving Mixed Volterra – Fredholm Integral Equations (MVFIEs) of second kind in 2–dimensions. in our method, we present a multi – layers model consisting of a hidden layer which has five hidden units (neurons) and one linear output unit. Transfer function (Log – sigmoid) and training algorithm (Levenberg – Marquardt) are used as a sigmoid activation of each unit. A comparison between the results of numerical experiment and the analytic solution of some examples has been carried out in order to justify the efficiency and the accuracy of our method.

         

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Publication Date
Thu Jun 20 2019
Journal Name
Baghdad Science Journal
Using Backpropagation to Predict Drought Factor in Keetch-Byram Drought Index
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Forest fires continue to rise during the dry season and they are difficult to stop. In this case, high temperatures in the dry season can cause an increase in drought index that could potentially burn the forest every time. Thus, the government should conduct surveillance throughout the dry season. Continuous surveillance without the focus on a particular time becomes ineffective and inefficient because of preventive measures carried out without the knowledge of potential fire risk. Based on the Keetch-Byram Drought Index (KBDI), formulation of Drought Factor is used just for calculating the drought today based on current weather conditions, and yesterday's drought index. However, to find out the factors of drought a day after, the data

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Publication Date
Thu Nov 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
The Quality of University Education at the Middle Technical University in The Light of the Application of National Ranking project for the Quality of Iraqi Universities
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The research aims to identify ways of upgrading the quality level of university education at the Middle Technical University in light of its application for the National Ranking project for the quality of Iraqi universities in order to obtain advanced grades among the Iraqi universities , Which is qualified to enter the Ranking of universities worldwide, through displaying the mechanism of the Application of  National Ranking project for the quality of Iraqi universities in the Middle Technical University and its formations consisting of (5) technical colleges and (11) technical institute.

        The results of the application showed several observations: The most

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Publication Date
Fri Dec 09 2022
Journal Name
Molecules
Palm Raceme as a Promising Biomass Precursor for Activated Carbon to Promote Lipase Activity with the Aid of Eutectic Solvents
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This study concerns the role of activated carbon (AC) from palm raceme as a support material for the enhancement of lipase-catalyzed reactions in an aqueous solution, with deep eutectic solvent (DES) as a co-solvent. The effects of carbonization temperature, impregnation ratio, and carbonization time on lipase activity were studied. The activities of Amano lipase from Burkholderia cepacia (AML) and lipase from the porcine pancreas (PPL) were used to investigate the optimum conditions for AC preparation. The results showed that AC has more interaction with PPL and effectively provides greater enzymatic activity compared with AML. The optimum treatment conditions of AC samples that yield the highest enzymatic activity were 0.5 (NaOH (

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Publication Date
Mon Jan 01 2024
Journal Name
Tropical Journal Of Natural Product Research
Cytotoxic Potential of Neem (Azadirachta indica A. Juss) Oil
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An increasing interest is emerging in identifying natural products to overcome drug resistance in cancer patients. In this context, the present study was conducted to investigate the cytotoxic effects of neem plant (Azadirachta indica) oil in three different biological models (breast cancer cell lines, Allium cepa root tip, and mice vital organs). The cytotoxic potential of the neem oil was evaluated with two human cell lines (MCF7 and MDA-MB231) and an Allum cepa root tip bioassay. Histopathological analysis was conducted on the neem oil-treated and untreated control mice. The results revealed an anti-proliferative effect for neem oil on both estrogen receptor-positive (MCF7) and estrogen receptor-negative (MDA-MB231) breast cancer cell li

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Publication Date
Sun Dec 31 2023
Journal Name
Tropical Journal Of Natural Product Research
Cytotoxic Potential of Neem (Azadirachta indica A. Juss) Oil
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Publication Date
Wed Jan 11 2017
Journal Name
Journal: Ibn Al-haitham Journal For Pure And Applied Sciences
Synthesis and Characterization of some Metal Complexes with (3Z ,5Z, 8Z)-2-azido-8-[azido(3Z,5Z)-2-azido-2,6- bis(azidocarbonyl)-8,9-dihydro-2H-1,7-dioxa-3,4,5- triazonine-9-yl]methyl]-9-[(1-azido-1-hydroxy)methyl]-2H1,7-dioxa-3,4,5-triazonine – 2,6 – dicarbonylazide(L-AZ) .
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The reaction of LAs-Cl8 : [ (2,2- (1-(3,4-bis(carboxylicdichloromethoxy)-5-oxo-2,5- dihydrofuran-2-yl)ethane – 1,2-diyl)bis(2,2-dichloroacetic acid)]with sodium azide in ethanol with drops of distilled water has been investigated . The new product L-AZ :(3Z ,5Z,8Z)-2- azido-8-[azido(3Z,5Z)-2-azido-2,6-bis(azidocarbonyl)-8,9-dihydro-2H-1,7-dioxa-3,4,5- triazonine-9-yl]methyl]-9-[(1-azido-1-hydroxy)methyl]-2H-1,7-dioxa-3,4,5-triazonine – 2,6 – dicarbonylazide was isolated and characterized by elemental analysis (C.H.N) , 1H-NMR , Mass spectrum and Fourier transform infrared spectrophotometer (FT-IR) . The reaction of the L-AZ withM+n: [ ( VO(II) , Cr(III) ,Mn(II) , Co(II) , Ni(II) , Cu(II) , Zn(II) , Cd(II) and Hg(II)] has been i

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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Generative Adversarial Network for Imitation Learning from Single Demonstration
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Imitation learning is an effective method for training an autonomous agent to accomplish a task by imitating expert behaviors in their demonstrations. However, traditional imitation learning methods require a large number of expert demonstrations in order to learn a complex behavior. Such a disadvantage has limited the potential of imitation learning in complex tasks where the expert demonstrations are not sufficient. In order to address the problem, we propose a Generative Adversarial Network-based model which is designed to learn optimal policies using only a single demonstration. The proposed model is evaluated on two simulated tasks in comparison with other methods. The results show that our proposed model is capable of completing co

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Human Pose Estimation Algorithm Using Optimized Symmetric Spatial Transformation Network
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Human posture estimation is a crucial topic in the computer vision field and has become a hotspot for research in many human behaviors related work. Human pose estimation can be understood as the human key point recognition and connection problem. The paper presents an optimized symmetric spatial transformation network designed to connect with single-person pose estimation network to propose high-quality human target frames from inaccurate human bounding boxes, and introduces parametric pose non-maximal suppression to eliminate redundant pose estimation, and applies an elimination rule to eliminate similar pose to obtain unique human pose estimation results. The exploratory outcomes demonstrate the way that the proposed technique can pre

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Publication Date
Sat Jun 08 2024
Journal Name
Karbala International Journal Of Modern Science
Designing of Human Serum Albumin Nanoparticles for Drug Delivery: a Potential Use of Anticancer Treatment
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Human serum albumin (HSA) nanoparticles have been widely used as versatile drug delivery systems for improving the efficiency and pharmaceutical properties of drugs. The present study aimed to design HSA nanoparticle encapsulated with the hydrophobic anticancer pyridine derivative (2-((2-([1,1'-biphenyl]-4-yl)imidazo[1,2-a]pyrimidin-3-yl)methylene)hydrazine-1-carbothioamide (BIPHC)). The synthesis of HSA-BIPHC nanoparticles was achieved using a desolvation process. Atomic force microscopy (AFM) analysis showed the average size of HSA-BIPHC nanoparticles was 80.21 nm. The percentages of entrapment efficacy, loading capacity and production yield were 98.11%, 9.77% and 91.29%, respectively. An In vitro release study revealed that HSA-BIPHC nan

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