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Solving the Hotdog Problem by Using the Joint Zero-order Finite Hankel - Elzaki Transform
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This paper is concerned with combining two different transforms to present a new joint transform FHET and its inverse transform IFHET. Also, the most important property of FHET was concluded and proved, which is called the finite Hankel – Elzaki transforms of the Bessel differential operator property, this property was discussed for two different boundary conditions, Dirichlet and Robin. Where the importance of this property is shown by solving axisymmetric partial differential equations and transitioning to an algebraic equation directly. Also, the joint Finite Hankel-Elzaki transform method was applied in solving a mathematical-physical problem, which is the Hotdog Problem. A steady state which does not depend on time was discussed for each obtained general solution, i.e. in the boiling and cooling states. To clarify the idea of temperature rise and fall over the time domain given in the problem, some figures were drawn manually using Microsoft PowerPoint. The obtained results confirm that the proposed transform technique is efficient, accurate, and fast in solving axisymmetric partial differential equations.

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Publication Date
Sun Apr 02 2017
Journal Name
Journal Of Educational And Psychological Researches
Self -affirmation and its relation of tendency toward perfection and the awareness of creativity among fine arts institutions students
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The study aimed to identify self –affirmation degree, tendency degree toward perfection, awareness degree of creativity among fine arts institutions students, and the significant correlation between self -affirmation and its tendency toward perfection, and the awareness of creativity among fine arts institutions students. To achieve these objectives, the author had constructed two scales: one to measure self –affirmation among the sample based on “Lang& Jakobowski theory” (Lang& Jakobowski, 1973) that consisted of (54) item divided into two parts: qualitative and situational. The other scale is to measure the tendency toward perfection depend on (flett & Hewitt, 1991) that composed of (46) item divided into two sectio

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Publication Date
Sat Jun 01 2019
Journal Name
2019 International Engineering Conference (iec)
Assessment of Specific Absorption Rate and Temperature in the Tumor Tissue Subjected to Plasmonic Bow-Tie Optical Nano-Antenna
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Publication Date
Mon Jan 01 2018
Journal Name
Journal Of Wildlife Diseases
MENINGEAL WORM (PARELAPHOSTRONGYLUS TENUIS) AS A CAUSE OF MORTALITY IN THE RESTORED ELK (CERVUS CANADENSIS) POPULATION IN MISSOURI, USA
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Publication Date
Sun Apr 01 2018
Journal Name
Journal Of Educational And Psychological Researches
The effect of teaching design in accordance with cluster thinking strategies on First-grade-intermediate students’ achievement in science
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The current study aims to develop a teaching design in accordance with cluster thinking strategies and explore the effect of this teaching design on students’ achievement in science. To this end, the null hypothesis was adopted: there is no statistically significant difference at the level of (0, 05) between experimental group who adopted the teaching design in learning science and control group who follow the traditional method in learning the same subject. To test the null hypothesis, total of (74) students from Al-Alaama Hussain Mahfooth intermediate school were selected intentionally for the academic year 2016-2017. The sample divided into two equal groups when all the variables (age, prior achievement of science,

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Publication Date
Fri Oct 30 2020
Journal Name
International Journal Of Agronomy
Molybdenum Induces Growth, Yield, and Defence System Mechanisms of the Mung Bean (Vigna radiata L.) under Water Stress Conditions
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Water stress has a negative impact on the yield and growth of crops worldwide and consequently has a global impact on food security. Many biochemical changes occur in plants as a response to water stress, such as activation of antioxidant systems. Molybdenum (Mo) plays an important part in activating the expression of many enzymes, such as CAT, POD, and SOD, as well as increasing the proline content. Mo therefore supports the defence system in plants and plays an important role in the defence system of mung bean plants growing under water stress conditions. Four concentrations of Mo (0, 15, 30, and 45 mg·L−1) were applied to plants, using two approaches: (a) seed soaking and (b) foliar application. Mung bean plants were subject

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Publication Date
Sun Mar 05 2017
Journal Name
Baghdad Science Journal
Screening of Epiphytic Algae on the Aquatic Plant Phragmites australis inhabiting Tigris River in Al-Jadria Site, Baghdad, Iraq
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The present work included qualitative study of epiphytic algae on dead and living stems, leaves of the aquatic plant Phragmitesaustralis Trin ex Stand, in Tigris River in AL- Jadria Site in Baghdad during Autumn 2014, Winter 2015, Spring 2015, and Summer 2015. The physical and chemical parameters of River’s water were studied (water temperature, pH, electric conductivity, Salinity, TSS, TDS, turbidity, light intensity, dissolve oxygen, BOD5, alkalinity, total hardness, calcium, magnesium and plant nutrient). A total of 142 isolates of epiphytic algae were identified. Diatoms were dominant by 117 isolates followed by Cyanobacteria (13isolates), Chlorophyta (11 isolates) and Rhodophyta (1 isolate), Variations in the isolates number were rec

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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Deep Learning Techniques in the Cancer-Related Medical Domain: A Transfer Deep Learning Ensemble Model for Lung Cancer Prediction
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Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

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Publication Date
Wed Aug 30 2023
Journal Name
Baghdad Science Journal
Deep Learning-based Predictive Model of mRNA Vaccine Deterioration: An Analysis of the Stanford COVID-19 mRNA Vaccine Dataset
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The emergence of SARS-CoV-2, the virus responsible for the COVID-19 pandemic, has resulted in a global health crisis leading to widespread illness, death, and daily life disruptions. Having a vaccine for COVID-19 is crucial to controlling the spread of the virus which will help to end the pandemic and restore normalcy to society. Messenger RNA (mRNA) molecules vaccine has led the way as the swift vaccine candidate for COVID-19, but it faces key probable restrictions including spontaneous deterioration. To address mRNA degradation issues, Stanford University academics and the Eterna community sponsored a Kaggle competition.This study aims to build a deep learning (DL) model which will predict deterioration rates at each base of the mRNA

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Publication Date
Wed Jun 01 2022
Journal Name
Applied Energy
Novel mathematical modeling, performance analysis, and design charts for the typical hybrid photovoltaic/phase-change material (PV/PCM) system
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Publication Date
Sun Mar 01 2015
Journal Name
Spectrochimica Acta Part A: Molecular And Biomolecular Spectroscopy
Effect of solvents on the extraction of natural pigments and adsorption onto TiO2 for dye-sensitized solar cell applications
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