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Modeling and Control of Fuel Cell Using Artificial Neural Networks
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This paper includes an experimental study of hydrogen mass flow rate and inlet hydrogen pressure effect on the fuel cell performance. Depending on the experimental results, a model of fuel cell based on artificial neural networks is proposed. A back propagation learning rule with the log-sigmoid activation function is adopted to construct neural networks model. Experimental data resulting from 36 fuel cell tests are used as a learning data. The hydrogen mass flow rate, applied load and inlet hydrogen pressure are inputs to fuel cell model, while the current and voltage are outputs. Proposed model could successfully predict the fuel cell performance in good agreement with actual data. This work is extended to developed fuel cell feedback control system using PID controller to stabilize the fuel cell voltage. Particle swarm optimization technique is used to tune the PID controller gains. The voltage error and hydrogen flow rate are input and the actuator of the PID controller respectively. Simulation results showed that using PID controller with proposed model of fuel cell can successfully improve system performance in tracking output voltage under different operating conditions.

 

 

 

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Publication Date
Wed Sep 14 2016
Journal Name
Journal Of Baghdad College Of Dentistry
Immunohistochemical Expressions of AKT, ATM and Cyclin E in Oral Squamous Cell Carcinoma
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Background: Understanding the pathogenesis and molecular basis of Oral Squamous Cell Carcinoma (OSCC) has increased rapidly over the past few years that is essential to improve patient's prognosis and treatment modalities. The purpose of this study to evaluate the Immunohistochemical expressions of AKT, ATM, AND Cyclin E in oral squamous cell carcinoma Materials and methods: This study was performed on a forty formalin-fixed paraffin-embedded blocks which histopathologically diagnosed as Oral Squamous Cell Carcinoma. All cases were collected from the Histopathological Laboratory from patients treated surgically at Maxillofacial surgery Department at Ramadi Teaching Hospital, Iraq. Results: The immunohistochemical staining of AKT showed pos

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Publication Date
Wed Mar 23 2022
Journal Name
Journal Of Educational And Psychological Researches
Self-control and its relation to the work pressure of educational counselors
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1- The degree of self-control of the educational counselors.

2- The level of work pressures that educational counselors are exposed to from their point of view.

3- The significance of the differences in the degree of self-control and work pressures according to the gender variable (male / female).

4- The relationship between self-control and work stress for the sample as a whole.

The current research was limited to educational counselors of both sexes in Anbar Governorate, Ramadi District, affiliated to the Anbar Education Directorate. The researcher adopted the steps of the relational descriptive approach to achieve the research objectives. The current research community consists of (100) m

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Publication Date
Mon Dec 31 2012
Journal Name
Al-khwarizmi Engineering Journal
Senserless Speed and Position of Direct Field Orientation Control Induction Motor Drive
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Direct field-orientation Control (DFOC) of induction motor drives without mechanical speed sensors at the motor shaft has the attractions of low cost and high reliability. To replace the sensor, information on the rotor speed and position are extracted from measured stator currents and from voltages at motor terminals. In this paper presents direct field-orientation control (DFOC) with two type of kalman filter (complete order and reduced order extended kalman filter) to estimate flux, speed, torque and position. Simulated results show how good performance for reduced order extended kalman filter over that of complete  order extended kalman filter in tracking performance and reduced time of state estimation.

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Publication Date
Wed Feb 21 2024
Journal Name
Al-rafidain Journal Of Medical Sciences ( Issn 2789-3219 )
Perceptions of Senior Pharmacy Students Towards the Impact of Artificial Intelligence on University Education and Scientific Writing: A Qualitative Study
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Background: The roles of AI in the academic community continue to grow, especially in the enhancement of learning outcomes and the improvement of writing quality and efficiency. Objectives: To explore in depth the experience of senior pharmacy students in using artificial intelligence for academic purposes. Methods: This qualitative study included face-to-face individual interviews with senior pharmacy students from March to May 2023 using a pre-planned interview guide of open-ended questions. All interviews were audio-recorded. Thematic analysis was used to analyze the data. Results: The results were obtained from 15 in-depth face-to-face interviews with senior pharmacy students (5th and 4th years). Eight participants were male, an

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Publication Date
Sun Jan 01 2023
Journal Name
Chemical Methodologies
Cytotoxicity and Anticancer Effect of Chitosan-Ag NPs-Doxorubicin-Folic Acid Conjugate on Lungs Cell Line
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This study looked at how the synthetic chitosan-AgNPs-Doxorubicin-folic acid combination affected the A549 cell line in terms of cytotoxicity and anticancer activity. By reducing silver nitrate (AgNO3) and biodegradable chitosan, silver nanoparticles were biosynthesized. The produced conjugate was examined by using FT-IR spectroscopy, atomic force microscopy (AFM), and field emission scanning electron microscopy (FE-SEM). The cytotoxicity assay for the viability of A549 cells revealed that the combination of chitosan, AgNPs, doxorubicin, and folic acid decrease cell viability in a dose-determined by method over 48 hours, which direct to a dependent reduce in the activity of A549 cells. The mechanism analysis of the impacted living cells lea

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Publication Date
Sat Jan 01 2022
Journal Name
Technologies And Materials For Renewable Energy, Environment And Sustainability: Tmrees21gr
Study and preparation of optoelectronic properties of AgAl1-xInxSe2/Si heterojunction solar cell applications
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Publication Date
Sat Oct 01 2022
Journal Name
Inorganic Chemistry Communications
Investigation of performance and efficiency of donor-π-bridge-acceptor based material solar cell
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The novel groups of organic chromophores containing triphenylamine (TPA) (ATP-I to ATP-IV) have been constructed by structural modification of electron donors with substitution biphenyl and bipyridine rings inserting a π-linkage. Density functional theory (DFT) and time-dependent type of it (TD-DFT) have been operated to study results of donating ability of TPA and spacer on absorption, geometrical, photovoltaic, and energetic attributes of these sensitizers. Structural attributes have been revealed that incorporation of TPA, acceptor and π bridge include a perfect coplanar conformation in TPA-III. Based on frequency computations and ground-state optimization, bandgap (Eg) energy, ELUMO, EHOMO have been determined. For enlightening maximu

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Publication Date
Sat Jan 22 2022
Journal Name
Aip Conference Proceedings 2437, 020032
Study and preparation of optoelectronic properties of AgAl1-xInxSe2/Si heterojunction solar cell applications
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􀀤􀁅􀁖􀁗􀁕􀁄􀁆􀁗􀀑􀀃􀀬􀁑􀀃􀁗􀁋􀁌􀁖􀀃􀁕􀁈􀁖􀁈􀁄􀁕􀁆􀁋􀀏􀀃􀀤􀁊􀀤􀁏􀀔􀀐􀁛􀀬􀁑􀁛􀀶􀁈􀀕􀀃􀀋􀀤􀀤􀀬􀀶􀀌􀀃􀁆􀁒􀁐􀁓􀁒􀁘􀁑􀁇􀀃􀁄􀁏􀁏􀁒􀁜􀁖􀀃􀁓􀁕􀁈􀁓􀁄􀁕􀁈􀁇􀀃􀁉􀁒􀁕􀀃􀁇􀁌􀁉􀁉􀁈􀁕􀁈􀁑􀁗􀀃􀁛􀀃􀀋􀀓􀀑􀀖􀀏􀀃􀀓􀀑􀀙􀀃􀁄􀁑􀁇􀀃􀀓􀀑􀀜􀀌􀀃􀁅􀁜􀀃􀁐􀁈􀁏􀁗􀁌􀁑􀁊􀀃 􀁗􀁋􀁈􀁐􀀃 􀁌􀁑􀀃 􀁄􀁑􀀃 􀁈􀁙􀁄􀁆􀁘􀁄􀁗􀁈􀁇􀀃 􀁔􀁘􀁄􀁕􀁗􀁝􀀃 􀁗􀁘􀁅􀁈􀀃 􀀋􀀕􀀑􀀘􀀍􀀔􀀓􀀐􀀖􀀃 􀁗􀁒􀁕􀁕􀀌􀀑􀀃 􀀤􀀤􀀬􀀶􀀃 􀁚􀁌􀁗􀁋􀀃 􀁇􀁌􀁉􀁉

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Publication Date
Wed Jun 28 2023
Journal Name
Al–bahith Al–a'alami
The Future of Television Work in the Light of Artificial Intelligence Challenges an Exploratory Study
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This research examines the future of television work in light of the challenges posed by artificial intelligence (AI). The study aims to explore the impact of AI on the form and content of television messages and identify areas where AI can be employed in television production. This study adopts a future-oriented exploratory approach, utilizing survey methodology. As the research focuses on foresight, the researcher gathers the opinions of AI experts and media specialists through in-depth interviews to obtain data and insights. The researcher selected 30 experts, with 15 experts in AI and 15 experts in media. The study reveals several findings, including the potential use of machine learning, deep learning, and na

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Publication Date
Sat Jun 01 2019
Journal Name
Synthetic Metals
Modeling tunnel currents in organic permeable-base transistors
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