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A Class of Harmonic Multivalent Functions for Higher Derivatives Associated with General Linear Operator
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    The main goal of this paper is to introduce the higher derivatives multivalent harmonic function class, which is defined by the general linear operator. As a result, geometric properties such as coefficient estimation, convex combination, extreme point, distortion theorem and convolution property are obtained. Finally, we show that this class is invariant under the Bernandi-Libera-Livingston integral for harmonic functions.

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
AlexNet Convolutional Neural Network Architecture with Cosine and Hamming Similarity/Distance Measures for Fingerprint Biometric Matching
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In information security, fingerprint verification is one of the most common recent approaches for verifying human identity through a distinctive pattern. The verification process works by comparing a pair of fingerprint templates and identifying the similarity/matching among them. Several research studies have utilized different techniques for the matching process such as fuzzy vault and image filtering approaches. Yet, these approaches are still suffering from the imprecise articulation of the biometrics’ interesting patterns. The emergence of deep learning architectures such as the Convolutional Neural Network (CNN) has been extensively used for image processing and object detection tasks and showed an outstanding performance compare

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Publication Date
Tue Mar 01 2022
Journal Name
International Journal Of Nonlinear Analysis And Applications
Semi-parametric regression function estimation for environmental pollution with measurement error using artificial flower pollination algorithm
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Artificial Intelligence Algorithms have been used in recent years in many scientific fields. We suggest employing flower pollination algorithm in the environmental field to find the best estimate of the semi-parametric regression function with measurement errors in the explanatory variables and the dependent variable, where measurement errors appear frequently in fields such as chemistry, biological sciences, medicine, and epidemiological studies, rather than an exact measurement. We estimate the regression function of the semi-parametric model by estimating the parametric model and estimating the non-parametric model, the parametric model is estimated by using an instrumental variables method (Wald method, Bartlett’s method, and Durbin

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Publication Date
Mon Apr 30 2018
Journal Name
Journal Of Theoretical And Applied Information Technology
An efficient artificial fish swarm algorithm with harmony search for scheduling in flexible job-shop problem
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Flexible job-shop scheduling problem (FJSP) is one of the instances in flexible manufacturing systems. It is considered as a very complex to control. Hence generating a control system for this problem domain is difficult. FJSP inherits the job-shop scheduling problem characteristics. It has an additional decision level to the sequencing one which allows the operations to be processed on any machine among a set of available machines at a facility. In this article, we present Artificial Fish Swarm Algorithm with Harmony Search for solving the flexible job shop scheduling problem. It is based on the new harmony improvised from results obtained by artificial fish swarm algorithm. This improvised solution is sent to comparison to an overall best

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Publication Date
Sun Sep 01 2019
Journal Name
Gazi University Journal Of Science
Reliable Iterative Methods for Solving Convective Straight and Radial Fins with Temperature-Dependent Thermal Conductivity Problems
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In our article, three iterative methods are performed to solve the nonlinear differential equations that represent the straight and radial fins affected by thermal conductivity. The iterative methods are the Daftardar-Jafari method namely (DJM), Temimi-Ansari method namely (TAM) and Banach contraction method namely (BCM) to get the approximate solutions. For comparison purposes, the numerical solutions were further achieved by using the fourth Runge-Kutta (RK4) method, Euler method and previous analytical methods that available in the literature. Moreover, the convergence of the proposed methods was discussed and proved. In addition, the maximum error remainder values are also evaluated which indicates that the propo

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Publication Date
Wed Dec 01 2021
Journal Name
Baghdad Science Journal
Analytical Solutions for Advanced Functional Differential Equations with Discontinuous Forcing Terms and Studying Their Dynamical Properties
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This paper aims to find new analytical closed-forms to the  solutions of the nonhomogeneous functional differential equations of the nth order with finite and constants delays and various initial delay conditions in terms of elementary functions using Laplace transform method. As well as, the definition of dynamical systems for ordinary differential equations is used to introduce the definition of dynamical systems for delay differential equations which contain multiple delays with a discussion of their dynamical properties: The exponential stability and strong stability

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Publication Date
Mon Jan 11 2021
Journal Name
2nd International Conference In Physical Science & Advanced Materials
Comparing the optical parameters for thin CAZTSe films prepared with various Ag ratios and annealing temperatures
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􀀑􀀃Pure Cu (CZTSe) and Ag dopant CZTSe (CAZTSe) thin films with Ag content of 0.1 and 0.2 were fabricated on coring glass substrate at R.T with thickness of 800nm by thermal evaporation method. Comparison between the optical characteristics of pure Cu and Ag alloying thin films was done by measuring and analyzing the absorbance and transmittance spectra in the range of (400-1100)nm. Also, the effect of annealing temperature at 373K and 473K on these characteristics was studied. The results indicated that all films had high absorbance and low transmittance in visible region, and the direct bang gap of films decreases with increasing Ag content and annealing temperature. Optical parameters like extinction coefficientrefractive index, and

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Publication Date
Wed Dec 03 2025
Journal Name
Journal Of Taibah University For Science
Effective computational methods for solving the hyperbolic one-dimensional wave equation with nonlocal mixed boundary conditions
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This paper considers approximate solution of the hyperbolic one-dimensional wave equation with nonlocal mixed boundary conditions by improved methods based on the assumption that the solution is a double power series based on orthogonal polynomials, such as Bernstein, Legendre, and Chebyshev. The solution is ultimately compared with the original method that is based on standard polynomials by calculating the absolute error to verify the validity and accuracy of the performance.

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Publication Date
Sun Jun 30 2024
Journal Name
Iraqi Journal Of Science
Efficient Computational Methods for Solving the One-Dimensional Parabolic Equation with Nonlocal Initial and Boundary Conditions
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     The primary objective of the current paper is to suggest and implement effective computational methods (DECMs) to calculate analytic and approximate solutions to the nonlocal one-dimensional parabolic equation which is utilized to model specific real-world applications. The powerful and elegant methods that are used orthogonal basis functions to describe the solution as a double power series have been developed, namely the Bernstein, Legendre, Chebyshev, Hermite, and Bernoulli polynomials. Hence, a specified partial differential equation is reduced to a system of linear algebraic equations that can be solved by using Mathematica®12. The techniques of effective computational methods (DECMs) have been applied to solve some s

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Publication Date
Sat Jun 01 2019
Journal Name
2019 International Symposium On Networks, Computers And Communications (isncc)
An Interference Mitigation Scheme for Millimetre Wave Heterogeneous Cloud Radio Access Network with Dynamic RRH Clustering
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Publication Date
Fri Mar 29 2024
Journal Name
Iraqi Journal Of Science
Finding the Best Route for Connecting Citizens with Service Centers in Baghdad Based on NN Technology
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     A geographic information system (GIS) is a very effective management and analysis tool. Geographic locations rely on data. The use of artificial neural networks (ANNs) for the interpretation of natural resource data has been shown to be beneficial. Back-propagation neural networks are one of the most widespread and prevalent designs. The combination of geographic information systems with artificial neural networks provides a method for decreasing the cost of landscape change studies by shortening the time required to evaluate data. Numerous designs and kinds of ANNs have been created; the majority of them are PC-based service domains. Using the ArcGIS Network Analyst add-on, you can locate service regions around any network

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