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MR Brain Image Segmentation Using Spatial Fuzzy C- Means Clustering Algorithm
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conventional FCM algorithm does not fully utilize the spatial information in the image. In this research, we use a FCM algorithm that incorporates spatial information into the membership function for clustering. The spatial function is the summation of the membership functions in the neighborhood of each pixel under consideration. The advantages of the method are that it is less
sensitive to noise than other techniques, and it yields regions more homogeneous than those of other methods. This technique is a powerful method for noisy image segmentation. 

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Publication Date
Fri Oct 23 2020
Journal Name
Biomed Research International
A Computational Model of the Brain Cortex and Its Synchronization
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Obtaining the computational models for the functioning of the brain gives us a chance to understand the brain functionality thoroughly. This would help the development of better treatments for neurological illnesses and disorders. We created a cortical model using Python language using the Brian simulator. The Brian simulator is specialized in simulating the neuronal connections and synaptic interconnections. The dynamic connection model has multiple parameters in order to ensure an accurate simulation (Bowman, 2016). We concentrated on the connection weights and studied their effect on the interactivity and connectivity of the cortical neurons in the same cortical layer and across multiple layers. As synchronization helps us to mea

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Publication Date
Tue May 01 2012
Journal Name
Iraqi Journal Of Physics
Early detection of breast cancer mass lesions by mammogram segmentation images based on texture features
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Mammography is at present one of the available method for early detection of masses or abnormalities which is related to breast cancer. The most common abnormalities that may indicate breast cancer are masses and calcifications. The challenge lies in early and accurate detection to overcome the development of breast cancer that affects more and more women throughout the world. Breast cancer is diagnosed at advanced stages with the help of the digital mammogram images. Masses appear in a mammogram as fine, granular clusters, which are often difficult to identify in a raw mammogram. The incidence of breast cancer in women has increased significantly in recent years.
This paper proposes a computer aided diagnostic system for the extracti

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Publication Date
Fri Nov 08 2024
Journal Name
International Journal Of Language Testing
Validation of C-Test among Iraqi EFL University Students
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Publication Date
Mon Apr 01 2013
Journal Name
مجلة كلية بغداد للعلوم الاقتصادية الجامعة العدد الخاص بمؤتمر الكلية
A propose method for hiding image into image
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Publication Date
Thu Dec 01 2011
Journal Name
Swarm And Evolutionary Computation
Energy-aware evolutionary routing protocol for dynamic clustering of wireless sensor networks
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Publication Date
Tue Jul 19 2022
Journal Name
Handbook Of Moth-flame Optimization Algorithm
Moth-Flame Optimization Algorithm, Arithmetic Optimization Algorithm, Aquila Optimizer, Gray Wolf Optimizer, and Sine Cosine Algorithm
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Publication Date
Wed Sep 11 2024
Journal Name
Lecture Notes In Civil Engineering
An Image Processing Algorithm to Address the Problem of Stains Merge on Water Sensitive Papers and Its Impact on the Evaluation of Spray Quality Indicators
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There are many techniques that can be used to estimate the spray quality traits such as the spray coverage, droplet density, droplet count, and droplet diameter. One of the most common techniques is to use water sensitive papers (WSP) as a spray collector on field conditions and analyzing them using several software. However, possible merger of some droplets could occur after they deposit on WSP, and this could affect the accuracy of the results. In this research, image processing technique was used for better estimation of the spray traits, and to overcome the problem of droplet merger. The droplets were classified as non-merged and merged droplets based on their roundness, then the merged droplets were separated based on the average non-m

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Publication Date
Mon Jun 05 2023
Journal Name
Journal Of Economics And Administrative Sciences
Fuzzy Bridge Regression Model Estimating via Simulation
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      The main problem when dealing with fuzzy data variables is that it cannot be formed by a model that represents the data through the method of Fuzzy Least Squares Estimator (FLSE) which gives false estimates of the invalidity of the method in the case of the existence of the problem of multicollinearity. To overcome this problem, the Fuzzy Bridge Regression Estimator (FBRE) Method was relied upon to estimate a fuzzy linear regression model by triangular fuzzy numbers. Moreover, the detection of the problem of multicollinearity in the fuzzy data can be done by using Variance Inflation Factor when the inputs variable of the model crisp, output variable, and parameters are fuzzed. The results were compared usin

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Publication Date
Fri Jan 01 2016
Journal Name
Aip Conference Proceedings
Analysis of performance measures with single channel fuzzy queues under two class by using ranking method
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Publication Date
Tue Oct 30 2018
Journal Name
Journal Of Engineering
Evaluation of the Project Overhead Costs in Iraqi Construction Industry using Fuzzy Analytic Hierarchy Process (FAHP)
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This research investigated the importance and priorities of the project overhead costs in Iraq via a questionnaire using the fuzzy analytic hierarchy process technique (FAHP). Using this technique is very important in the uncertain circumstances as in our country. The researcher reached to frame an equation through the results of the priorities of weights include the percentages of each of the main items of the project overhead costs. The researcher tested this equation by applying it to one of the completed projects and the results showed suitability for the application. The percentages of the (salaries, grants, and incentives) and (fieldwork requirements) in equation represent approximately two-thirds of project overhe

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