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ijp-778
Influence of grounded electrode area on breakdown current in RF capcitively coupled plasma
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The influence of the grounded electrode area on the ignition voltage in capcitively coupled radio frequency discharge at 13.56 MHz in argon gas is studied experimentally. The results indicate a systematic decrease of the breakdown voltage with increasing grounded electrode area for the same pd value. Results show that the secondary ionization coefficient γ increases with the increase of grounded electrode area. Furthermore, results also the discharge current at the breakdown voltage increases almost linearly with the increase of electrode area suggesting an almost constant current density.

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Publication Date
Wed Jan 01 2025
Journal Name
Aip Conference Proceedings
Synthesis and evaluation of chalcone derivatives for antimicrobial and antioxidant activities using microwave-assisted methodology
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Publication Date
Mon Oct 01 2012
Journal Name
Computers & Mathematics With Applications
Boundary element formulations for the numerical solution of two-dimensional diffusion problems with variable coefficients
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Publication Date
Thu Aug 20 2020
Journal Name
Arab World English Journal
Investigating the Effectiveness of YouTube as a Learning Tool among EFL Students at Baghdad University
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YouTube is not just a platform that individuals share, upload, comment on videos; teachers and educators can utilize it to the best maximum so that students can have benefits. This study aims at investigating how active and influential YouTube can be in the educational process and how it is beneficial for language teachers to enhance the skills of students. The study demonstrates different theoretical frameworks that tackle the employment of technology to enhance the learning/teaching process. It relies on the strategies of Berk (2009) for using multimedia media, video clips in particular to develop the abilities of teachers for using technology in classrooms. To achieve the objective of the study, the researchers develop a questionnair

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Publication Date
Mon Jan 01 2018
Journal Name
Aip Conference Proceedings
Fabricated and investigated the structure and super conductivity properties of Bi2Sr2Can-1CunO2n+4+δ compound
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Publication Date
Sat Apr 01 2023
Journal Name
Chemical Methodologies
A Novel Design for Gas Sensor of Zinc Oxide Nanostructure Prepared by Hydrothermal Annealing Technique
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Publication Date
Mon Jan 01 2024
Journal Name
Fusion: Practice And Applications
Proposed Framework for Semantic Segmentation of Aerial Hyperspectral Images Using Deep Learning and SVM Approach
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Publication Date
Sat Feb 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
An open cloud-based platform for the creation and delivery of smart applications and services
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Abstract<p>With the increasing integration of computers and smartphones into our daily lives, in addition to the numerous benefits it offers over traditional paper-based methods of conducting affairs, it has become necessary to incorporate one of the most essential facilities into this integration; namely: colleges. The traditional approach for conducting affairs in colleges is mostly paper-based, which only increases time and workload and is relatively decentralized. This project provides educational and management services for the university environment, targeting the staff, the student body, and the lecturers, on two of the most used platforms: smartphones and reliable web applications by clo</p> ... Show More
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Publication Date
Tue Dec 08 2020
Journal Name
Acs Infectious Diseases
Antileishmanial Chemotherapy through Clemastine Fumarate Mediated Inhibition of the <i>Leishmania</i> Inositol Phosphorylceramide Synthase
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Publication Date
Fri Mar 29 2024
Journal Name
Iraqi Journal Of Science
Evaluating the Performance and Behavior of CNN, LSTM, and GRU for Classification and Prediction Tasks
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     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

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Publication Date
Fri Oct 24 2014
Journal Name
Journal Of Religion And Health
Cross-Cultural Validation and Psychometric Properties of the Arabic Brief Religious Coping Scale (A-BRCS)
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