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Using Fuzzy Clustering to Detect the Tumor Area in Stomach Medical Images
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Although the number of stomach tumor patients reduced obviously during last decades in western countries, but this illness is still one of the main causes of death in developing countries. The aim of this research is to detect the area of a tumor in a stomach images based on fuzzy clustering. The proposed methodology consists of three stages. The stomach images are divided into four quarters and then features elicited from each quarter in the first stage by utilizing seven moments invariant. Fuzzy C-Mean clustering (FCM) was employed in the second stage for each quarter to collect the features of each quarter into clusters. Manhattan distance was calculated in the third stage among all clusters' centers in all quarters to disclosure of the quarter that contains a tumor based on the centroid value of the cluster in this quarter, which is far from the centers of the remaining quarters. From the calculations conducted on several images' quarters, the experimental outcomes show that the centroid value of the cluster in each quarter was greater than 0.9 if this quarter did not contain a tumor while the value of the centroid value for the cluster containing a tumor was less than 0.4.For examples, in a quarter no.1 for STOMACH_1 medical image, the centroid value of the cluster was 0.973 while the value of the cluster centroid in quarter no.3 was 0.280. For this reason the tumor area was found in quarter no.(3) of the medical image STOMACH_1. Also, the centroid value of the cluster in a quarter no.2 was 0.948 for STOMACH_2 while, the value of the cluster centroid in quarter no.4 was 0.397. For this reason the tumor area was found in a quarter no.4 of the medical image STOMACH_2.

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Publication Date
Mon Jul 01 2019
Journal Name
Iop Conference Series: Materials Science And Engineering
Fuzzy orbit topological spaces
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Abstract<p>The concept of fuzzy orbit open sets under the mapping <italic>f</italic>:<italic>X</italic> → <italic>X</italic> in a fuzzy topological space (<italic>X</italic>,<italic>τ</italic>) was introduced by Malathi and Uma (2017). In this paper, we introduce some conditions on the mapping <italic>f</italic>, to obtain some properties of these sets. Then we employ these properties to show that the family of all fuzzy orbit open sets construct a new fuzzy topology, which we denoted by <italic>τ</italic> <sub> <italic>F0</italic> </sub> coarser </p> ... Show More
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Publication Date
Tue Jun 30 2020
Journal Name
Journal Of New Theory
Fuzzy Orbit Irresolute Mappings
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Fuzzy orbit topological space is a new structure very recently given by [1]. This new space is based on the notion of open fuzzy orbit sets. The aim of this paper is to provide applications of open fuzzy orbit sets. We introduce the notions of fuzzy orbit irresolute mappings and fuzzy orbit open (resp. irresolute open) mappings and studied some of their properties. .

Publication Date
Mon Aug 01 2022
Journal Name
Journal Of Physics: Conference Series
Fibrewise Fuzzy Separation Axioms
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Abstract<p>Within that research, we introduce fibrewise fuzzy types of the most important separation axioms in ordinary fuzz topology, namely fibrewise fuzzy (T 0 spaces, T 1 spaces, R 0 spaces, Hausdorff spaces, functionally Hausdorff spaces, regular spaces, completely regular spaces, normal spaces, and normal spaces). Too we add numerous outcomes about it.</p>
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Publication Date
Sat Jun 15 2019
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Fuzzy Internal Direct Product
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The purpose of this research is to show a constructive method
for using known fuzzy groups as building blocks to form more fuzzy
subgroups. As we shall describe employing this procedure with the
fuzzy generating subgroups give us a large class of fuzzy
subgroup of abelian groups which include all fuzzy subgroup of
abelian groups of finite order.

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Publication Date
Tue Jul 09 2024
Journal Name
Diagnostics
A Novel Hybrid Machine Learning-Based System Using Deep Learning Techniques and Meta-Heuristic Algorithms for Various Medical Datatypes Classification
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Medicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep lea

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Publication Date
Sat Oct 01 2022
Journal Name
Lark Journal
The role of metaphor in the embodiment of female images (In the novel by Ludmila Ulitskaya "Sincerely Yours Shurik" as model)
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The research deals with metaphors as being one of the primary means used by Lyudmila Ulitskaya when writing the novel " Sincerely Yours Shurik ", to form diverse and multifaceted collective female images of representatives of the classic psychological patterns presented in the work. This research reflects the results of the study related to the work of Lyudmila Yevkinevna Ulitskaya, an actress of modern Russian prose. The novel "The Sincerely to You Shorek" is one of Ludmila Ulitskaya's creations (the year of writing - 2003), which, like her other works, is distinguished by a unique presentation style, rich vocabulary, lexical and semantic diversity, and a special style of writing. writer. The main objective of the research is to look at th

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Publication Date
Thu Feb 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Using the Balanced Performance Approach to Increase the Effectiveness of Strategic Planning in order to Maximize the Job Satisfaction Rates at the Faculties of Bisha University
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Purpose: To use the balanced measurement approach as a strategic link for increasing the effectiveness of strategic planning in the direction of achieving satisfaction rates at Bisha University in Saudi Arabia

Design / methodology / approach –The questionnaire survey was used to collect the data of the study from the faculty members at University of Bisha.

Findings –Prove the assumption that the use of the balanced measurement approach - as a strategic planning tool - leads to maximize the satisfaction rates among faculty members at the University of Bisha.

Research limitations/implications-  adopt effective strategic planning in order to achieve

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Publication Date
Sat Jun 26 2021
Journal Name
Asian Journal Of Civil Engineering
Using AHP to prioritize the corruption risk practices in the Iraqi construction sector
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Publication Date
Wed Dec 30 2020
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Petrophysical Properties of Khasib Formation in East Baghdad Oil Field Southern Area
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Petrophysical properties evaluation from well log analysis has always been crucial for the identification and assessment of hydrocarbon bearing zones. East Baghdad field is located 10 km east of Baghdad city, where the southern area includes the two southern portions of the field, Khasib formation is the main reservoir of East Baghdad oil field.

In this paper, well log data of nine wells have been environmentally corrected, where the corrected data used to determine lithology, shale volume, porosity, and water saturation. Lithology identified by two methods; neutron-density and M-N matrix plots, while the shale volume estimated by single shale indicator and dual shale indicator, The porosity is calculated from the three common po

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Publication Date
Fri Dec 01 2023
Journal Name
Bulletin Of Electrical Engineering And Informatics
A comparative study of Gaussian mixture algorithm and K-means algorithm for efficient energy clustering in MWSN
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Wireless sensor networks (WSNs) represent one of the key technologies in internet of things (IoTs) networks. Since WSNs have finite energy sources, there is ongoing research work to develop new strategies for minimizing power consumption or enhancing traditional techniques. In this paper, a novel Gaussian mixture models (GMMs) algorithm is proposed for mobile wireless sensor networks (MWSNs) for energy saving. Performance evaluation of the clustering process with the GMM algorithm shows a remarkable energy saving in the network of up to 92%. In addition, a comparison with another clustering strategy that uses the K-means algorithm has been made, and the developed method has outperformed K-means with superior performance, saving ener

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