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Medical Image Segmentation using Modified Interactive Thresholding Technique
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Medical image segmentation is one of the most actively studied fields in the past few decades, as the development of modern imaging modalities such as magnetic resonance imaging (MRI) and computed tomography (CT), physicians and technicians nowadays have to process the increasing number and size of medical images. Therefore, efficient and accurate computational segmentation algorithms become necessary to extract the desired information from these large data sets. Moreover, sophisticated segmentation algorithms can help the physicians delineate better the anatomical structures presented in the input images, enhance the accuracy of medical diagnosis and facilitate the best treatment planning. Many of the proposed algorithms could perform well in certain medical image applications.The aim of this paper is to change the medical image into something that is more meaningful and easier to analyze and recognize features that helps the doctors to diagnoses the diseases .This paper views selected medical image and segmentation method that have been proposed, which are suitable for processing medical images by use the modification of the traditional interactive threshold technique. This method gave good results,and these results are testedaccordingto the measure of quality (PSNR).

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Publication Date
Wed Nov 30 2022
Journal Name
Iraqi Journal Of Science
Breast Cancer Detection using Decision Tree and K-Nearest Neighbour Classifiers
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      Data mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the  most effective parameter, particularly when Age<49.5. Whereas  Ki67  appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimu

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Publication Date
Mon Jun 05 2023
Journal Name
Journal Of Engineering
Nonlinear Analysis on Torsional Strengthening Of Rc Beams Using Cfrp Laminates
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This research is devoted to investigate the behavior and performance of reinforced concrete beams strengthened with externally bonded Carbon Fiber Reinforced Polymer (CFRP) laminates under the effect of torsion. In this study a theoretical analysis has been conducted using finite element code ANSYS. Six previously tested beams are used to investigate reinforced concrete beams behavior
under torsion, two of them are solid and the rest are box-section beams. Also, two beams are without CFRP reinforcement, which are used as control beams for the strengthened one, and the other four beams are strengthened with CFRP laminates with different number of layers and spacing. Numerical investigation is conducted on these beams, and comparisons b

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Publication Date
Mon Sep 01 2014
Journal Name
Journal Of Baghdad College Of Dentistry
Apexification and Periapical Healing of Immature Teeth Using Mineral Trioxide Aggregate
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Publication Date
Sat Apr 01 2023
Journal Name
Journal Of Engineering
Manufacture of Load Bearing Concrete Masonry Units Using Waste Demolishing Material
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The presence of construction wastes such as clay bricks, glass, wood, plastic, and others in large quantities causes serious environmental problems in the world. Where these wastes can be used to preserve the natural resources used in construction and reduce the impact of this problem on the environment, it also works to reduce the problem of high loads of concrete blocks. Clay bricks aggregate (AB) can be recycled as coarse aggregate and replaced with volumetric proportions of coarse aggregate by ( 5% and 10%), as well as the use of clay brick powder (PB) by replacing its weight of cement (5% and 10%) and reduced in the manufacture of concrete blocks (blocks). Four mixtures will be prepared and tested to learn how to re

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Publication Date
Sun Dec 01 2024
Journal Name
Nordic Concrete Research
Evaluating Concrete Strength Under Various Curing Conditions Using Artificial Neural Networks
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Abstract<p>This study examines the impact of different curing methods on the compressive strength of concrete. It investigates techniques such as air curing, periodic water spraying, full water submersion, and polyethylene encasement. Artificial neural network models were employed to evaluate the compressive strength under each curing condition. A model for calculating compressive strength that considers surrounding conditions was created using an artificial neural network. The current study’s figures were generated using this model. The research thoroughly examined the impact of curing environments and concrete mix components on strength properties, taking into account factors such as tempera</p> ... Show More
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Publication Date
Fri Jan 01 2021
Journal Name
Annals Of Tropical Medicine & Public Health
Assessment of Left Ventricular Function in Body builders using conventional echocardiography
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Background: Powerlifters and bodybuilders use anabolic androgenic steroids (AAS) especially – as many as 55 percent of elite powerlifters admitted using these agents. In contrast to numerous documented toxic and hormonal effects of AAS their impact on the structure and function of the left ventricular (LV) was not yet fully understood.

Publication Date
Fri Oct 03 2025
Journal Name
Mesopotamian Journal Of Computer Science
Enhanced TEA Algorithm Performance using Affine Transformation and Chaotic Arnold Map
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In digital images, protecting sensitive visual information against unauthorized access is considered a critical issue; robust encryption methods are the best solution to preserve such information. This paper introduces a model designed to enhance the performance of the Tiny Encryption Algorithm (TEA) in encrypting images. Two approaches have been suggested for the image cipher process as a preprocessing step before applying the Tiny Encryption Algorithm (TEA). The step mentioned earlier aims to de-correlate and weaken adjacent pixel values as a preparation process before the encryption process. The first approach suggests an Affine transformation for image encryption at two layers, utilizing two different key sets for each layer. Th

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Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Revolution In Science And Humanity
Nonparametric Estimation of Failure Periods for Log Normal Distribution Using Bootstra
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A non-parametric kernel method with Bootstrap technology was used to estimate the confidence intervals of the system failure function of the log-normal distribution trace data. These are the times of failure of the machines of the spinning department of the weaving company in Wasit Governorate. Estimating the failure function in a parametric way represented by the method of the maximum likelihood estimator (MLE). The comparison between the parametric and non-parametric methods was done by using the average of Squares Error (MES) criterion. It has been noted the efficiency of the nonparametric methods based on Bootstrap compared to the parametric method. It was also noted that the curve estimation is more realistic and appropriate for the re

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Publication Date
Fri Nov 13 2020
Journal Name
Mechanics Of Advanced Materials And Structures
Enhancing the strength of reinforced concrete columns using steel embedded tubes
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This paper demonstrates an experimental and numerical study on the behavior of reinforced concrete (RC) columns with longitudinal steel embedded tubes positioned at the center of the column cross-section. A total of 12 pin-ended square sectional columns of 150 × 150 mm having a total height of 1400 mm were investigated. The considered variables were the steel tube diameters of 29, 58, and 76 mm and the load eccentricity (0, 50, and 150) mm. Accordingly, these columns were divided into three groups (four columns in each group) depending on the load eccentricity (e) to column depth (h) ratio (e/h = 0, 1/3, and 1). For each group, one column was solid (reference), and the other three columns contained steel tubes with hollow rat

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Publication Date
Sat Feb 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
A comparison of the Semiparametric Estimators model smoothing methods different using
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In this paper, we made comparison among different parametric ,nonparametric and semiparametric estimators for partial linear regression model users parametric represented by ols and nonparametric methods represented by cubic smoothing spline estimator and Nadaraya-Watson estimator, we study three nonparametric regression models and samples sizes  n=40,60,100,variances used σ2=0.5,1,1.5 the results  for the first model show that N.W estimator for partial linear regression model(PLM) is the best followed the cubic smoothing spline estimator for (PLM),and the results of the second and the third model show that the best estimator is C.S.S.followed by N.W estimator for (PLM) ,the

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