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Comparison of Various Gradient Types for Biological Image with Morphological Operations
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Biological image edge detection preserving the important structural properties in an image. Detecting accurate edges are very important for analyzing the basic properties associated with a biological image. Gradient operator plays very important role in edge detection. In this paper the images had been using are color biological images taken from microbiology laboratory at the biological department college of science Al-MustansiriyhUniversity and the effect of gradient operation have applied on around 10 different biological color images but view only two. In our proposed approach comparative of various gradient of biological image include (gradient of image, gradient of image using first order derivative edge detection (Soble,Prewitt,Roberts)and gradient image using morphological operation and The comparative output images using quality assessment include (MSR, PNSR, l2rat, maxerr, entropy). The software tool that has been used is MATLAB 7.0 from the results we found that morphological and Robert gradient edge detection algorithm better performs than the others and are important with extraction features of biologic images.

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Publication Date
Sat Sep 30 2023
Journal Name
Iraqi Journal Of Science
Comparing the Random Forest vs. Extreme Gradient Boosting using Cuckoo Search Optimizer for Detecting Arabic Cyberbullying
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   Cyberbullying is one of the major electronic problems, and it is not a new phenomenon. It was present in the traditional form before the emergence of social networks, and cyberbullying has many consequences, including emotional and physiological states such as depression and anxiety. Given the prevalence of this phenomenon and the importance of the topic in society and its negative impact on all age groups, especially adolescents, this work aims to build a model that detects cyberbullying in the comments on social media (Twitter) written in the Arabic language using Extreme Gradient Boosting (XGBoost) and Random Forest methods in building the models. After a series of pre-processing, we found that the accuracy of classification of t

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Publication Date
Thu Sep 30 2021
Journal Name
Iraqi Journal Of Science
The Dynamics of Biological Models with Optimal Harvesting
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      This paper aims to introduce a concept of an equilibrium point of a dynamical system which will call it almost global asymptotically stable. We also propose and analyze a prey-predator model with a suggested  function growth in prey species. Firstly the existence and local stability of all its equilibria are studied. After that the model is extended to an optimal control problem to obtain an optimal harvesting strategy. The discrete time version of Pontryagin's maximum principle is applied to solve the optimality problem. The characterization of the optimal harvesting variable and the adjoint variables are derived. Finally these theoretical results are demonstrated with numerical simulations.

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Various Extracts of Some Medicinal Plants as Inhibitors for Beta-lactamase Activity
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The inhibitory effect of acetone, ethanol, and aqueous extracts of ten medicinal plants on β-lactamase from Staphylococcus sciuri and Klebsiella pneumoniae was investigated in vitro by starch-iodine agar plate method. The results revealed the success of starch-iodine method for the detection of the inhibition of β-lactamase activity by the various extracts of each individual plant. The acetone extracts of Catharanthus roseus, Eucalyptus camaldulensis, and Schinus terebinthifolius induced an inhibitory effect on β-lactamase from Staphylococcus sciuri. On the other hand, acetone extracts from only Eucalyptus camaldulensis, and Schinus

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Publication Date
Thu Aug 30 2018
Journal Name
Journal Of Engineering
Accuracy Assessment of Various Resolutions Digital Cameras For Close Range Photogrammetry Applications
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Due to the great evolution in digital commercial cameras, several studies have addressed the using of such cameras in different civil and close-range applications such as 3D models generation. However, previous studies have not discussed a precise relationship between a camera resolution and the accuracy of the models generated based on images of this camera. Therefore the current study aims to evaluate the accuracy of the derived 3D buildings models captured by different resolution cameras. The digital photogrammetric methods were devoted to derive 3D models using the data of various resolution cameras and analyze their accuracies. This investigation involves selecting three different resolution cameras (low, medium and

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Publication Date
Tue Jan 30 2024
Journal Name
Iraqi Journal Of Science
Boundary Exponential Gradient Reduced Order Detectability in Neumann Conditions
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     This work, aims to study and examine the description f the gradient reduced order-strategic sensors of type boundary exponential (-strategic sensors) for completion gradient  order-detectability of type boundary exponential (-detectability). Thus, this concept is linked to an estimator in distributed parameter systems (DPSS) in Neumann problem. So,we present numerous consequences regarding to diverse kinds of information, region  and conditions of boundary region to allow existence of -detectable systems. In addition,we have estimated at the junction interface that the interior solution isharmonizedwith the exterior solution for -detectable and, we give the relationship between this concept and sensors structures. F

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Publication Date
Thu Sep 01 2022
Journal Name
Iraqi Journal Of Physics
Structural and Morphological Characterization of MEH-PPV Nanocomposite Doped with FeCl3
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Poly [2-methoxy-5-(2-ethylhexyloxy)-1, 4-phenylenevinyl] (MEH-PPV) thin films were created in this study using both spin coating and drop casting processes. MEH-PPV thin films generated by Ferric Chloride (FeCl3) doping (0.03, 0.06, 0.09, and 0.12 wt%) were studied for some physical features using Fourier-Transform Infrared Spectroscopy (FTIR), Field Emission Scanning Electron Microscopy (FE-SEM), and Energy Dispersive X-ray Spectroscopy (EDX). An FTIR test showed that there was no chemical reaction that occurred between Ferric Chloride (FeCl3) and MEH-PPV, but rather a physical one, that is, an organic material composite occurred. As for FE-SEM, the pure sample MEH-PPV formed uniformly, but when FeCl3 was added by weight, we have differ

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Publication Date
Mon Oct 30 2023
Journal Name
Iraqi Journal Of Science
Machine Learning Approach for Facial Image Detection System
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     Face detection systems are based on the assumption that each individual has a unique face structure and that computerized face matching is possible using facial symmetry. Face recognition technology has been employed for security purposes in many organizations and businesses throughout the world. This research examines the classifications in machine learning approaches using feature extraction for the facial image detection system. Due to its high level of accuracy and speed, the Viola-Jones method is utilized for facial detection using the MUCT database. The LDA feature extraction method is applied as an input to three algorithms of machine learning approaches, which are the J48, OneR, and JRip classifiers.  The experiment’s

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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 Mar 09 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Images Segmentation Based on Fast Otsu Method Implementing on Various Edge Detection Operators
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The present work aims to study the effect of using an automatic thresholding technique to convert the features edges of the images to binary images in order to split the object from its background, where the features edges of the sampled images obtained from first-order edge detection operators (Roberts, Prewitt and Sobel) and second-order edge detection operators (Laplacian operators). The optimum automatic threshold are calculated using fast Otsu method. The study is applied on a personal image (Roben) and a satellite image to study the compatibility of this procedure with two different kinds of images. The obtained results are discussed.

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Publication Date
Sun Dec 01 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Measurement and disclosure of losses resulting from terrorist operations
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The aim of the research is to identify the losses resulting from the terrorist operations and then find a proposed accounting treatment for the losses resulting from the terrorist operations and to indicate their impact on disclosure in the financial statements by reviewing the international standards and local rules and the unified accounting system and not dealing with these losses, Of the financial statements and therefore adversely affect the accounting disclosure as well as the weak commitment of economic units to apply the requirements of accounting measurement and disclosure of losses of terrorist operations in a manner consistent with local and international standards to achieve the Reliability in the financial statement.

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