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Near Rough and Near Exact Subgraphs in Gm-Closure spaces
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The basic concepts of some near open subgraphs, near rough, near exact and near fuzzy graphs are introduced and sufficiently illustrated. The Gm-closure space induced by closure operators is used to generalize the basic rough graph concepts. We introduce the near exactness and near roughness by applying the near concepts to make more accuracy for definability of graphs. We give a new definition for a membership function to find near interior, near boundary and near exterior vertices. Moreover, proved results, examples and counter examples are provided. The Gm-closure structure which suggested in this paper opens up the way for applying rich amount of topological facts and methods in the process of granular computing.

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Publication Date
Mon May 11 2020
Journal Name
Baghdad Science Journal
Strong Subordination for E -valent Functions Involving the Operator Generalized Srivastava-Attiya
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Some relations of inclusion and their properties are investigated for functions of type " -valent that involves the generalized operator of Srivastava-Attiya by using the principle of strong differential subordination.

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Publication Date
Thu Jun 25 2020
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn: 1683 - 3597 , E-issn : 2521 - 3512)
Evaluating the Clinical Outcomes of Three Medication Regimens for Treating a Sample of Iraqi Persistent Asthmatic patients
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Abstract     Asthma is a complex disease defined by chronic airway inflammation and airflow limitation causing variable respiratory symptoms which include shortness of breath (SOB), wheezing, chest tightness and cough. Asthma guidelines advocate adding a second long acting bronchodilator to medium doses of inhaled corticosteroids (ICS) rather using high doses of ICS alone to control moderate to severe persistent asthma. The aim of this study was to evaluate the clinical outcomes of three medication regimens indicated for Iraqi patients suffering from persistent asthma.      This study was interventional randomized clinical study conducted on a sample of adult Iraqi asthmatic patients in Baghdad City. The study com

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Publication Date
Tue Feb 28 2023
Journal Name
Iraqi Journal Of Science
Benchmarking Framework for COVID-19 Classification Machine Learning Method Based on Fuzzy Decision by Opinion Score Method
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     Coronavirus disease (COVID-19), which is caused by SARS-CoV-2, has been announced as a global pandemic by the World Health Organization (WHO), which results in the collapsing of the healthcare systems in several countries around the globe. Machine learning (ML) methods are one of the most utilized approaches in artificial intelligence (AI) to classify COVID-19 images. However, there are many machine-learning methods used to classify COVID-19. The question is: which machine learning method is best over multi-criteria evaluation? Therefore, this research presents benchmarking of COVID-19 machine learning methods, which is recognized as a multi-criteria decision-making (MCDM) problem. In the recent century, the trend of developing

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Publication Date
Tue Jun 01 2021
Journal Name
Int. J. Nonlinear Anal. Appl.
Fibrewise totally perfect mapping
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The main purpose of this paper is to introduce a some concepts in fibrewise totally topological space which are called fibrewise totally mapping, fiberwise totally closed mapping, fibrewise weakly totally closed mapping, fibrewise totlally perfect mapping fibrewise almost totally perfect mapping. Also the concepts as totally adherent point, filter, filter base, totally converges to a subset, totally directed toward a set, totally rigid, totally-H-set, totally Urysohn space, locally totally-QHC totally topological space are introduced and the main concept in this paper is fibrewise totally perfect mapping in totally top

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Publication Date
Sat Apr 01 2023
Journal Name
Baghdad Science Journal
Coincidence of Fixed Points with Mixed Monotone Property
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The purpose of this paper is to introduce and prove some coupled coincidence fixed point theorems for self mappings satisfying -contractive condition with rational expressions on complete partially ordered metric spaces involving altering distance functions with mixed monotone property of the mapping. Our results improve and unify a multitude of coupled fixed point theorems and generalize some recent results in partially ordered metric space. An example is given to show the validity of our main result. 

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Publication Date
Tue Feb 28 2023
Journal Name
Iraqi Journal Of Science
Applications of the Finite Operator〖 〗_3 E_2 (■(q^(-N),a,b@c,d);q,-fθ) for the Polynomials B_n (a,b,c,d,f,x,y|q)
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     In this work,   polynomials  and the finite q-exponential operator  are constructed. The operator  is used to combine an operator proof of the generating function with its extension, Mehler's formula with its extension and Roger's formula for the polynomials . The generating function with its extension,  Mehler's formula with its extension and Rogers formula for Al-Salam-Carlitz polynomials  are deduced by giving special values to polynomials .

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Publication Date
Sun Jan 20 2019
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Bayesian Estimation for Two Parameters of Gamma Distribution Under Precautionary Loss Function
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In the current study, the researchers have been obtained Bayes estimators for the shape and scale parameters of Gamma distribution under the precautionary loss function, assuming the priors, represented by Gamma and Exponential priors for the shape and scale parameters respectively. Moment, Maximum likelihood estimators and Lindley’s approximation have been used effectively in Bayesian estimation.

Based on Monte Carlo simulation method, those estimators are compared depending on the mean squared errors (MSE’s). The results show that, the performance of Bayes estimator under precautionary loss function with Gamma and Exponential priors is better than other estimates in all cases.

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Publication Date
Mon May 15 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
The Effect of Spot Size on the Fractal Optical Modulation
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The present paper analyzes the signal emitting from the Reticle during changing the spot size of laser falling on the disk and shows the optimum frequency and the amount of energy window in different patterns of modulator (Reticle).  All results are obtained by establishing   a special program named “Disk optical modulator version 3" using the language visual basic 6 ahich contains many parameters. All models of optical modulator consist of twenty sectors, ten sectors are opaque and other ten sectors are transmitted for the laser. The number of sectors depends on several factors as chopping frequency, power transparent and modulation transfer function.   It has been demonstrated by simulations, the optimal

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Publication Date
Mon Aug 01 2022
Journal Name
Baghdad Science Journal
Performance Assessment of Solar-Transformer-Consumption System Using Neural Network Approach
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Solar energy is one of the immeasurable renewable energy in power generation for a green, clean and healthier environment. The silicon-layer solar panels absorb sun energy and converts it into electricity by off-grid inverter. Electricity is transferred either from this inverter or from transformer, consumed by consumption unit(s) available for residential or economic purposes. The artificial neural network is the foundation of artificial intelligence and solves many complex problems which are difficult by statistical methods or by humans. In view of this, the purpose of this work is to assess the performance of the Solar - Transformer - Consumption (STC) system. The system may be in complete breakdown situation due to failure of both so

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Publication Date
Wed Oct 20 2021
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Bayesian Estimation for Two Parameters of Weibull Distribution under Generalized Weighted Loss Function
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In this paper, Bayes estimators for the shape and scale parameters of Weibull distribution have been obtained using the generalized weighted loss function, based on Exponential priors. Lindley’s approximation has been used effectively in Bayesian estimation. Based on theMonte Carlo simulation method, those estimators are compared depending on the mean squared errors (MSE’s).

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