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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
Wed Jan 01 2020
Journal Name
Plant Archives
Study of the environmental parameters on cephalexin degradation by anodic oxidation with biological indication
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Publication Date
Sun Nov 01 2020
Journal Name
Journal Of Physics: Conference Series
Synthesis, characterization and biological evaluation of thiazolyl azo ligand complexes with some metal ions.
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(E)-2-(benzo[d]thiazol-2-yliazenyl)-4-methoxyaniline was synthesized by reaction the diazonium salt of 2-aminobenzothiazole with 4-methoxyaniline. Identified of the ligand by spectral techniques (UV-Vis, FTIR,1HNMR and LC-Mass) and microelemental analysis (C.H.N.S.O) are used to produce of the azo ligand. Complexes of (Co2+, Ni2+, Cu2+ and Zn2+) were synthesized and identified using atomic absorption of flame, elemental analysis, infrared and UV-Vis spectral process as well conductivity and magnetic quantifications. Nature of compounds produced have been studied followed the mole ratio and continuous contrast methods, Beer's law followed during a concentration scope (1×10-4-3×10-4 mole/L). height molar absorptivity of compound solutions h

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Publication Date
Sat Dec 10 2016
Journal Name
International Journal Of Current Microbiology And Applied Sciences
Synthesis, Characterization and Biological Evaluation of Penicillin Derivatives Complexes with Some Transition Metal Ions
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Publication Date
Sun Jun 19 2016
Journal Name
Kufa Journal For Veterinary Medical Sciences
Pre and postnatal morphological developments for the skull bones in guinea pig (Cavia cutleri)
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Publication Date
Tue Jan 01 2019
Journal Name
Sci.int.(lahore)
SOME NEW TYPES OF PERFECT MAPPINGS
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In this work, we introduce a new kind of perfect mappings, namely j-perfect mappings and j-ω-perfect mappings. Furthermore we devoted to study the relationship between j-perfect mappings and j-ω-perfect mappings. Finally, certain theorems and characterization concerning these concepts are studied; j = , δ, α, pre, b, β

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Publication Date
Sun Feb 09 2025
Journal Name
Al-rafidain University College For Sciences
Uncertainty types and theories of treatment
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In this research the researcher had the concept of uncertainty in terms of types and theories of treatment and measurement as it was taken up are three types of indeterminacy and volatility and inconsistency

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Publication Date
Sun Apr 30 2023
Journal Name
Iraqi Journal Of Science
Certain Types of Weakly Closed Function
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The purpose of this paper is to give the condition under which every weakly closed
function is closed and to give the condition under which the concepts of weaklysemi
closed function and weakly pre-closed function are equivalent. Moreover,
characterizations and properties of weakly semi closed functions and weakly preclosed
function was given.

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Publication Date
Sun Feb 09 2025
Journal Name
Journal Mustansiriyah Of Sports Science
The effect of using Daniel's model for people with two types of brain control (left and right) to learn the skill of the Cartwheel in artistic gymnastics for second-stage students
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The research problem focused through the researcher's experience in the gymnastics game and the lack of use of educational models that give the student an important role in the educational process, so it became necessary to identify the type of prevailing style for students, and the need for diversity in the use of educational models based on scientific theories, including the Daniel Document model. Based on three theories of learning, which are structural, behavioral, and meaningful learning. The research aimed to identify the effect of using the Daniel model for people with two types of brain control (left and right) to learn the skill of the Cartwheel in artistic gymnastics for students of the second stage. The researcher used the experi

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Publication Date
Thu Nov 30 2023
Journal Name
Iraqi Journal Of Science
Effect of Genetic Algorithm as a Feature Selection for Image Classification
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     Analysis of image content is important in the classification of images, identification, retrieval, and recognition processes. The medical image datasets for content-based medical image retrieval (  are large datasets that are limited by high computational costs and poor performance. The aim of the proposed method is to enhance this image retrieval and classification by using a genetic algorithm (GA) to choose the reduced features and dimensionality. This process was created in three stages. In the first stage, two algorithms are applied to extract the important features; the first algorithm is the Contrast Enhancement method and the second is a Discrete Cosine Transform algorithm. In the next stage, we used datasets of the medi

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Publication Date
Sat Jun 06 2020
Journal Name
Journal Of The College Of Education For Women
Image classification with Deep Convolutional Neural Network Using Tensorflow and Transfer of Learning
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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 Conv

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