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Fuzzy-Based Ensemble Feature Selection for Automated Estimation of Speaker Height and Age Using Vocal Characteristics

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Publication Date
Sun Feb 01 2015
Journal Name
Journal Of Economics And Administrative Sciences
Reliability Estimation Of Fuzzy Failure Times Of Free Distribution And It Use To Estimate The Fuzzy Reliability Of Mosul Dam

The way used to estimate the fuzzy reliability differs according to the nature of the information of failure time which has been dealt in this research.The information of failure times has no probable distribution to explain it , in addition it has fuzzy quality.The research includes fuzzy reliability estimation of three periods ,the first one from 1986 to 2013,the second one from 2013 to 2033 while the third one from 2033 to 2066 .Four failure time have been chosen to identify the membership function of fuzzy trapezoid represented in the pervious years after taking in consideration the estimation of most researchers, proffional    geologists and the technician who is incharge of maintaining of Mosul Dam project. B

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Publication Date
Mon Feb 25 2019
Journal Name
Iraqi Journal Of Physics
Nuclear level density with proton resonance using Gaussian orthogonal ensemble theory

The Gaussian orthogonal ensemble (GOE) version of the random matrix theory (RMT) has been used to study the level density following up the proton interaction with 44Ca, 48Ti and 56Fe.

A promising analysis method has been implemented based on the available data of the resonance spacing, where widths are associated with Porter Thomas distribution. The calculated level density for the compound nuclei 45Sc,49Vand 57Co shows a parity and spin dependence, where for Sc a discrepancy in level density distinguished from this analysis probably due to the spin  misassignment .The present results show an acceptable agreement with the combinatorial method of level density.

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Publication Date
Tue Oct 12 2021
Journal Name
Engineering, Technology And Applied Science Research
Automated Pavement Distress Detection Using Image Processing Techniques

Pavement crack and pothole identification are important tasks in transportation maintenance and road safety. This study offers a novel technique for automatic asphalt pavement crack and pothole detection which is based on image processing. Different types of cracks (transverse, longitudinal, alligator-type, and potholes) can be identified with such techniques. The goal of this research is to evaluate road surface damage by extracting cracks and potholes, categorizing them from images and videos, and comparing the manual and the automated methods. The proposed method was tested on 50 images. The results obtained from image processing showed that the proposed method can detect cracks and potholes and identify their severity levels wit

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Publication Date
Tue Nov 03 2015
Journal Name
Journal Of Natural Sciences Research
Publication Date
Sun Oct 01 2006
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Modified Automated Scoring system for Immunohistochemical staining using commercially available low cost software for image analysis

Background: During the past several years, there has been a rapidly escalating clinical need to perform IHC stains that require quantitative interpretation. Automated Cellular
Imaging System is used to analyze immunohistochemically stained slides, primarily for cancer-related diagnostics. Studies have shown that the device offers accuracy,
precision, and reproducibility of immunostained slide analysis exceeding that possible with manual evaluation, which was the prevailing method.
Aim of the study In this article we will demonstrate that meaningful image analysis of immunohistochemical staining studies can be performed using inexpensive, widely distributed
graphics software (Adobe Photoshop) on a personal

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Publication Date
Tue Sep 29 2020
Journal Name
Iraqi Journal Of Science
An Automated Classification of Mammals and Reptiles Animal Classes Using Deep Learning

Detection and classification of animals is a major challenge that is facing the researchers. There are five classes of vertebrate animals, namely the Mammals, Amphibians, Reptiles, Birds, and Fish, and each type includes many thousands of different animals. In this paper, we propose a new model based on the training of deep convolutional neural networks (CNN) to detect and classify two classes of vertebrate animals (Mammals and Reptiles). Deep CNNs are the state of the art in image recognition and are known for their high learning capacity, accuracy, and robustness to typical object recognition challenges. The dataset of this system contains 6000 images, including 4800 images for training. The proposed algorithm was tested by using 1200

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Publication Date
Thu Dec 02 2021
Journal Name
Iraqi Journal Of Science
Automated Methods to Segment Kidneys and Detect Tumors Using CT Images

Kidney tumors are of different types having different characteristics and also remain challenging in the field of biomedicine. It becomes very important to detect the tumor and classify it at the early stage so that appropriate treatment can be planned. The main objective of this research is to use the Computer-Aided Diagnosis (CAD) algorithms to help the early detection of kidney tumors. In this paper, tried to implement an automated segmentation methods of gray level CT images is used to provide information such as anatomical structure and identifying the Region of Interest (ROI) i.e. locate tumor, lesion and other in kidney.
A CT image has inhomogeneity, noise which affects the continuity and accuracy of the images segmentation. In

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Publication Date
Mon Jan 02 2012
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Estimation of the seminal fluid of subfertile patients of different age groups.

Background: Among different lifestyle factors, aging process can adversely affect male semen parameters and hence male fertility in this study, semen parameters and productive hormonal profiles of subfertile young men were compared with subfertile middle and old age men.

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Publication Date
Sun Oct 30 2022
Journal Name
Iraqi Journal Of Science
Automated Methodology for Volume Fraction Measurement of Three Phase Steel Micrograph Using Image Processing Techniques

     A quantitative description of microstructure governs the characteristics of the material. Various heat and excellent treatments reveal micro-structures when the material is prepared. Depending on the microstructure, mechanical properties like hardness, ductility, strength, toughness, corrosion resistance, etc., also vary. Microstructures are characterized by morphological features like volume fraction of different phases, particle size, etc. Relative volume fractions of the phases must be known to correlate with the mechanical properties. In this work, using image processing techniques, an automated scheme was presented to calculate relative volume fractions of the phases, namely Ferrite, Martensite, and Bainite, present in the

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Publication Date
Mon Jan 25 2021
Journal Name
Engineering And Technology Journal
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