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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 Apr 03 2023
Journal Name
Journal Of Educational And Psychological Researches
Fitting Scoring Rubrics for Electronic Portfolio to Partial Credit Model According to the Number of Assumed Dimensions
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Abstract

 

The current research aims to reveal the extent to which all scoring rubrics data for the electronic work file conform to the partial estimation model according to the number of assumed dimensions. The study sample consisted of (356) female students. The study concluded that the list with the one-dimensional assumption is more appropriate than the multi-dimensional assumption, The current research recommends preparing unified correction rules for the different methods of performance evaluation in the basic courses. It also suggests the importance of conducting studies aimed at examining the appropriateness of different evaluation methods for models of response theory to the

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Publication Date
Tue May 16 2023
Journal Name
Journal Of Engineering
FREE VIBRATION ANALYSIS OF COMPOSITE LAMINATED PLATES USING HOST 12
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This paper presents an application of a Higher Order Shear Deformation Theory (HOST 12) to problem
of free vibration of simply supported symmetric and antisymmetric angle-ply composite laminated plates.
The theoretical model HOST12 presented incorporates laminate deformations which account for the effects
of transverse shear deformation, transverse normal strain/stress and a nonlinear variation of in-plane
displacements with respect to the thickness coordinate – thus modeling the warping of transverse crosssections more accurately and eliminating the need for shear correction coefficients. Solutions are obtained in
closed-form using Navier’s technique by solving the eigenvalue equation. Plates with varying number of

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Crossref
Publication Date
Thu Jun 20 2019
Journal Name
Baghdad Science Journal
Teen-Computer Interaction: Building a Conceptual Model with Thoughts- Emotion-Behaviour
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Teen-Computer Interaction (TeenCI) stands in an infant phase and emerging in positive path. Compared to Human-Computer Interaction (generally dedicated to adult) and Child-Computer Interaction, TeenCI gets less interest in terms of research efforts and publications. This has revealed extensive prospects for researchers to explore and contribute in the region of computer design and evaluation for teen, in specific. As a subclass of HCI and a complementary for CCI, TeenCI that tolerates teen group, should be taken significant concern in the sense of its context, nature, development, characteristics and architecture. This paper tends to discover teen’s emotion contribution as the first attempt towards building a conceptual model for TeenC

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Publication Date
Mon Sep 25 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Comparison of the Suggested loss Function with Generalized Loss Function for One Parameter Inverse Rayleigh Distribution
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The experiences in the life are considered important for many fields, such as industry, medical and others. In literature, researchers are focused on flexible lifetime distribution.

In this paper, some Bayesian estimators for the unknown scale parameter  of Inverse Rayleigh Distribution have been obtained, of different two loss functions, represented by Suggested and Generalized loss function based on Non-Informative prior using Jeffery's and informative prior represented by Exponential distribution. The performance of   estimators is compared empirically with Maximum Likelihood estimator, Using Monte Carlo Simulation depending on the Mean Square Error (MSE). Generally, the preference of Bayesian method of Suggeste

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Publication Date
Sat Mar 04 2023
Journal Name
Baghdad Science Journal
Generalised Henstock - Kurzweil Integral with Multiple Point
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This paper deals with a new Henstock-Kurzweil integral in Banach Space with Bilinear triple n-tuple and integrator function Ψ which depends on multiple points in partition. Finally, exhibit standard results of Generalized Henstock - Kurzweil integral in the theory of integration.

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Scopus Clarivate Crossref
Publication Date
Sun Aug 01 2021
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Weighted Residual Method for the System of Nonlinear Volterra Integral Equations of the Second Kind Using an Exponential Function
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The numerical resolve nonlinear system of Volterra integral equation of the second kind (NLSVIEK2) has been considered. The exponential function is used as the base function of the collocation method to approximate the resolve of the problem. Arithmetic epitome are performed which have already been solved by weighted residual manner,  Taylor manner and block- by- block(2, 3, 5).

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Crossref
Publication Date
Wed Oct 09 2024
Journal Name
Engineering, Technology & Applied Science Research
Improving Pre-trained CNN-LSTM Models for Image Captioning with Hyper-Parameter Optimization
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The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of

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Scopus Crossref
Publication Date
Sun Mar 06 2016
Journal Name
Baghdad Science Journal
A Note on the Perturbation of arithmetic expressions
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In this paper we present the theoretical foundation of forward error analysis of numerical algorithms under;• Approximations in "built-in" functions.• Rounding errors in arithmetic floating-point operations.• Perturbations of data.The error analysis is based on linearization method. The fundamental tools of the forward error analysis are system of linear absolute and relative a prior and a posteriori error equations and associated condition numbers constituting optimal of possible cumulative round – off errors. The condition numbers enable simple general, quantitative bounds definitions of numerical stability. The theoretical results have been applied a Gaussian elimination, and have proved to be very effective means of both a prior

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Crossref
Publication Date
Sat Jan 01 2022
Journal Name
International Journal Of Agricultural And Statistical Sciences
ON ERROR DISTRIBUTION WITH SINGLE INDEX MODEL
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In this paper, the error distribution function is estimated for the single index model by the empirical distribution function and the kernel distribution function. Refined minimum average variance estimation (RMAVE) method is used for estimating single index model. We use simulation experiments to compare the two estimation methods for error distribution function with different sample sizes, the results show that the kernel distribution function is better than the empirical distribution function.

Scopus
Publication Date
Mon Sep 23 2019
Journal Name
Baghdad Science Journal
Hazard Rate Estimation Using Varying Kernel Function for Censored Data Type I
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     In this research, several estimators concerning the estimation are introduced. These estimators are closely related to the hazard function by using one of the nonparametric methods namely the kernel function for censored data type with varying bandwidth and kernel boundary. Two types of bandwidth are used:  local bandwidth and global bandwidth. Moreover, four types of boundary kernel are used namely: Rectangle, Epanechnikov, Biquadratic and Triquadratic and the proposed function was employed with all kernel functions. Two different simulation techniques are also used for two experiments to compare these estimators. In most of the cases, the results have proved that the local bandwidth is the best for all the

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