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A PSO-optimized type-2 fuzzy logic controller for navigation of multiple mobile robots
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Publication Date
Fri Jan 01 2021
Journal Name
Brazilian Dental Science
Assessing the level and diagnostic accuracy of osteopontin and oral health status in periodontitis patients with/without Type-2 Diabetes Mellitus
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Publication Date
Wed Jan 02 2019
Journal Name
Indian Journal Of Public Health Research & Development
Correlation of Protein Tyrosine Kinase with Thyroid Hormones in Type 2 Diabetes Mellitus Patients and those with Diabetic Nephropathy Iraqi Patients.
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Diabetes mellitus is a metabolic disorder categorized hyperglycemia resulting from defects in insulin secretion, insulin action or both. Protein tyrosine kinase (PTK) is an enzyme that catalyzes the transfer of phosphate groups from ATP to the tyrosine residues of many important proteins resulting in proteins phosphorylation. The aim of current study was to evaluate serum levels of protein tyrosine kinase enzyme and thyroid hormone (T3, T4and TSH) and to find the correlation between them in type 2 diabetes mellitus and diabetic nephropathy Iraqi patients. Methods: This study was conducted at The National Diabetes Center, Al-Mustansiriya University, Baghdad, Iraq and included 150 patients divided into three groups the first group included 50

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Publication Date
Fri Jan 01 2021
Journal Name
Brazilian Dental Science
Assessing the level and diagnostic accuracy of osteopontin and oral health status in periodontitis patients with/without Type-2 Diabetes Mellitus
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Publication Date
Wed Jan 01 2020
Journal Name
Medeniyet Medical Journal
SARS-CoV-2: A Piece of Bad News
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A shocking third species emerged from a family of coronaviruses (CoV) in late 2019 following viruses causing SARS (Severe Acute Respiratory Syndrome-CoV) in 2003 and MERS (Middle East Respiratory Syndrome-CoV) in 2012; it’s a novel coronavirus now called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2; formerly called 2019-nCoV). First emerging in China, it has spread rapidly across the globe, giving rise to significant social and economic costs and imposing severe strain on healthcare systems. Since many attempts to control viral spread has been futile, the only old practice of containment including city lockdown and social distancing are working to some extent. Unfortunately, specific antiviral drugs and vaccines remain u

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Publication Date
Sat Apr 01 2023
Journal Name
Digital Communications And Networks
Dynamic channel estimation-aware routing protocol in mobile cognitive radio networks for smart IIoT applications
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Publication Date
Tue Dec 31 2013
Journal Name
Al-khwarizmi Engineering Journal
Design of an Adaptive PID Neural Controller for Continuous Stirred Tank Reactor based on Particle Swarm Optimization
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 A particle swarm optimization algorithm and neural network like self-tuning PID controller for CSTR system is presented. The scheme of the discrete-time PID control structure is based on neural network and tuned the parameters of the PID controller by using a particle swarm optimization PSO technique as a simple and fast training algorithm. The proposed method has advantage that it is not necessary to use a combined structure of identification and decision because it used PSO. Simulation results show the effectiveness of the proposed adaptive PID neural control algorithm in terms of minimum tracking error and smoothness control signal obtained for non-linear dynamical CSTR system.

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Publication Date
Sun Jun 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
Estimation the reliability function of multi state system by using Direct Partial Logic Derivative
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In this research is estimated the function of reliability dynamic of multi state systems  and their compounds and for three types of systems (serial, parallel, 2-out-of-3) and about two states (Failure and repair) depending on calculating the structur function allow to describing the behavior of

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Publication Date
Tue Feb 01 2022
Journal Name
Baghdad Science Journal
An Efficient Algorithm for Fuzzy Linear Fractional Programming Problems via Ranking Function
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In many applications such as production, planning, the decision maker is important in optimizing an objective function that has fuzzy ratio two functions which can be handed using fuzzy fractional programming problem technique. A special class of optimization technique named fuzzy fractional programming problem is considered in this work when the coefficients of objective function are fuzzy. New ranking function is proposed and used to convert the data of the fuzzy fractional programming problem from fuzzy number to crisp number so that the shortcoming when treating the original fuzzy problem can be avoided. Here a novel ranking function approach of ordinary fuzzy numbers is adopted for ranking of triangular fuzzy numbers with simpler an

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Publication Date
Mon Feb 21 2022
Journal Name
Iraqi Journal For Computer Science And Mathematics
Fuzzy C means Based Evaluation Algorithms For Cancer Gene Expression Data Clustering
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The influx of data in bioinformatics is primarily in the form of DNA, RNA, and protein sequences. This condition places a significant burden on scientists and computers. Some genomics studies depend on clustering techniques to group similarly expressed genes into one cluster. Clustering is a type of unsupervised learning that can be used to divide unknown cluster data into clusters. The k-means and fuzzy c-means (FCM) algorithms are examples of algorithms that can be used for clustering. Consequently, clustering is a common approach that divides an input space into several homogeneous zones; it can be achieved using a variety of algorithms. This study used three models to cluster a brain tumor dataset. The first model uses FCM, whic

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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
The classification of fetus gender based on fuzzy C-mean using a hybrid filter
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This paper proposes a new approach, of Clustering Ultrasound images using the Hybrid Filter (CUHF) to determine the gender of the fetus in the early stages. The possible advantage of CUHF, a better result can be achieved when fuzzy c-mean FCM returns incorrect clusters. The proposed approach is conducted in two steps. Firstly, a preprocessing step to decrease the noise presented in ultrasound images by applying the filters: Local Binary Pattern (LBP), median, median and discrete wavelet (DWT),(median, DWT & LBP) and (median & Laplacian) ML. Secondly, implementing Fuzzy C-Mean (FCM) for clustering the resulted images from the first step. Amongst those filters, Median & Laplace has recorded a better accuracy. Our experimental evaluation on re

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