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jih-2938
On the Double of the Emad - Falih Transformation and Its Properties with Applications
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In this paper, we have generalized the concept of one dimensional Emad - Falih integral transform into two dimensional, namely, a double Emad - Falih integral transform. Further, some main properties and theorems related to the double Emad - Falih transform are established. To show the proposed transform's efficiency, high accuracy, and applicability, we have implemented the new integral transform for solving partial differential equations. Many researchers have used double integral transformations in solving partial differential equations and their applications. One of the most important uses of double integral transformations is how to solve partial differential equations and turning them into simple algebraic ones. The most important partial differential equations are Laplace, Poisson, wave, heat, telegraph, and other equations. A new Double Emad -Falih integral transform denoted by the operator , the transform form is as follows:

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Publication Date
Sun Jun 06 2010
Journal Name
Baghdad Science Journal
Using Neural Network with Speaker Applications
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In Automatic Speech Recognition (ASR) the non-linear data projection provided by a one hidden layer Multilayer Perceptron (MLP), trained to recognize phonemes, and has previous experiments to provide feature enhancement substantially increased ASR performance, especially in noise. Previous attempts to apply an analogous approach to speaker identification have not succeeded in improving performance, except by combining MLP processed features with other features. We present test results for the TIMIT database which show that the advantage of MLP preprocessing for open set speaker identification increases with the number of speakers used to train the MLP and that improved identification is obtained as this number increases beyond sixty.

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Publication Date
Tue Jan 29 2019
Journal Name
Journal Of The College Of Education For Women
The Separation Worry and its Correlation with Working Memory of the Primary School Pupils
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The concept of the separation worry is considered one of the common disorders in children. The causes and effects of this worry influence the child mental and cognitive ability and the child ability to communicate with others, has friendship and the ability of adaptive with the environment, peers and teachers and it also influences the child's academic and social performance.
The importance of this study is represented in handling the working memory, one of important subject in cognitive psychology. Many universal studies show that the working memory is very important in several daily functions such as continuous attention, followinstructions, implement instructions of many steps, the moment of information remembering and keep focusin

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Publication Date
Sun Oct 01 2017
Journal Name
Applied Energy
Hourly yield prediction of a double-slope solar still hybrid with rubber scrapers in low-latitude areas based on the particle swarm optimization technique
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Publication Date
Wed May 17 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Dynamics of Double Chaos
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stract         This paper includes studying (dynamic of double chaos) in two steps: First Step:- Applying ordinary differential equation have behaved chaotically such as (Duffing's equation) on (double pendulum) equation system to get new system of ordinary differential equations depend on it next step. Second Step:- We demonstrate existence of a dynamics of double chaos in Duffing's equation by relying on graphical result of Poincare's map from numerical simulation.

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Publication Date
Sat Apr 09 2022
Journal Name
Engineering, Technology & Applied Science Research
Effect of Sustainable Glass Powder on the Properties of Reactive Powder Concrete with Polypropylene Fibers
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Global warming and environmental damage have become major problems. The production of Portland cement releases large quantities of gas, which cause pollution to the atmosphere. This problem can be solved via the use of sustainable materials, such as glass powder. This study investigates the effect of partial replacement of cement with sustainable glass powder at various percentages (0, 15, 20, and 25%) by weight of cement on some mechanical properties (compressive strength, flexural strength, absorption, and dry density) of Reactive Powder Concrete (RPC) containing a percentage of Polypropylene fibers (PRPC) of 1% by weight. Furthermore, steam curing was performed for 5 hours at 90oC after hardening the sample directly. The RPC was

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Publication Date
Tue Oct 01 2024
Journal Name
Journal Of Alloys And Compounds
Conversion of preferred crystalline orientation by annealing and its impacts on the structural, electronic, and optical properties of pulsed laser-deposited CdO thin films
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Publication Date
Wed Sep 30 2015
Journal Name
College Of Islamic Sciences
Break in the bond And its impact on the difference of scholars
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Break in the bond and its impact on the difference of scholars

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Publication Date
Mon Jul 20 2020
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Solving Some Fractional Partial Differential Equations by Invariant Subspace and Double Sumudu Transform Methods
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      In this paper, several types of space-time fractional partial differential equations has been solved by using most of special double linear integral transform ”double  Sumudu ”. Also, we are going to argue the truth of these solutions by another analytically method “invariant subspace method”. All results are illustrative numerically and graphically.

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Publication Date
Thu May 05 2022
Journal Name
5g Impact On Biomedical Engineering
Wireless Techniques and Applications of the Internet of Medical Things
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Publication Date
Fri Apr 14 2023
Journal Name
Journal Of Big Data
A survey on deep learning tools dealing with data scarcity: definitions, challenges, solutions, tips, and applications
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Abstract<p>Data scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for</p> ... Show More
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