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Characterization Performance of Monocrystalline Silicon Photovoltaic Module Using Experimentally Measured Data
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Solar photovoltaic (PV) system has emerged as one of the most promising technology to generate clean energy. In this work, the performance of monocrystalline silicon photovoltaic module is studied through observing the effect of necessary parameters: solar irradiation and ambient temperature. The single diode model with series resistors is selected to find the characterization of current-voltage (I-V) and power-voltage (P-V) curves by determining the values of five parameters ( ). This model shows a high accuracy in modeling the solar PV module under various weather conditions. The modeling is simulated via using MATLAB/Simulink software. The performance of the selected solar PV module is tested experimentally for different weather data (solar irradiance and ambient temperature) that is gathered from October 2017 to April 2018 in the city of Baghdad. The collected data is recorded for the entire months during the time which is limited between 8:00 AM and 1:00 PM. This work demonstrates that the change in a cell temperature is directly proportional with the PV module current, while it is inversely proportional with the PV module voltage. Additionally, the output power of a PV module increases with decreasing the solar module temperature. Furthermore, the Simulink block diagram is used to evaluate the influence of weather factors on the PV module temperature by connecting to the MATLAB code. The best value from the results of this work was in March when the solar irradiance was equal to 1000 W/m2 and the results were:

Isc,exp=3.015, Isc,mod=3.25 , RE=7.79 and Voc,exp=19.67 ,Voc,mod=19.9 ,RE=1.1

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Publication Date
Tue Oct 01 2013
Journal Name
Proceedings Of The International Astronomical Union
The infrared <i>K</i>-band identification of the DSO/G2 source from VLT and Keck data
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Abstract<p>A fast moving infrared excess source (G2) which is widely interpreted as a core-less gas and dust cloud approaches Sagittarius A* (Sgr A*) on a presumably elliptical orbit. VLT <italic>K<sub>s</sub></italic>-band and Keck <italic>K</italic>′-band data result in clear continuum identifications and proper motions of this ∼19<sup><italic>m</italic></sup> Dusty S-cluster Object (DSO). In 2002-2007 it is confused with the star S63, but free of confusion again since 2007. Its near-infrared (NIR) colors and a comparison to other sources in the field speak in favor of the DSO being an IR excess star with photospheric continuum emission at 2 microns than a</p> ... Show More
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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Exploring the Challenges of Diagnosing Thyroid Disease with Imbalanced Data and Machine Learning: A Systematic Literature Review
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Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise

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Publication Date
Wed Dec 01 2021
Journal Name
Journal Of Physics: Conference Series
The effect of left ventricle ischemia severity on cardiac performance appeared on ejection fraction using radioactive TC <sup>99m</sup> MIBI in comparison with echocardiography
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Abstract<p>Ischemic heart disease is a major causes of heart failure. Heart failure patients have predominantly left ventricular dysfunction (systolic or diastolic dysfunction, or both). Acute heart failure is most commonly caused by reduced myocardial contractility, and increased LV stiffness. We performed echocardiography and gated SPECT with Tc<sup>99m</sup> MIBI within 263 patients and 166 normal individuals. Left ventricular end systolic volume (LVESV), left ventricular end diastolic volume (LVEDV), and left ventricular ejection fraction (LVEF) were measured. For all degrees of ischemia, there was a significant difference between ejection fraction values measured by SPECT and echo</p> ... Show More
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Publication Date
Sat Dec 28 2024
Journal Name
Journal Of Physical Education
The Effect of Competitive Exercises Using Physical Performance Tracking Technology (GPS Playertek Plus and Polar H9) on Developing Speed in Iraqi Premier League Football Players
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Football is one of the most important team sports, practiced by men and women, young and old, across various age groups. The physical development in this sport can be attributed to athletic training and modern technology, which have contributed significantly to advancing the sports field in general. Outstanding performance in football requires precise and quick physical abilities, closely tied to the competitive nature of the game. Speed is fundamental in football, making the use of technologies such as GPS tracking devices and heart rate monitors essential in both training and matches. This study aims to develop the speed of Al-Talaba SC players in Baghdad using a scientifically-based approach to improve their performance. The impo

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Publication Date
Mon Jul 29 2019
Journal Name
International Journal Of Energy Research
Performance of the dye‐sensitized solar cells fabricated using natural dyes from <i>Ixora coccinea</i> flowers and <i>Cymbopogon schoenanthus</i> leaves as sensitizers
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Publication Date
Tue Aug 01 2017
Journal Name
Journal Of Natural Gas Science And Engineering
Recovery of mono-ethylene glycol by distillation and the impact of dissolved salts evaluated through simulation of field data
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Publication Date
Wed Jul 01 2020
Journal Name
Proceedings Of The Institution Of Mechanical Engineers, Part H: Journal Of Engineering In Medicine
Comparison study of classification methods of intramuscular electromyography data for non-human primate model of traumatic spinal cord injury
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Traumatic spinal cord injury is a serious neurological disorder. Patients experience a plethora of symptoms that can be attributed to the nerve fiber tracts that are compromised. This includes limb weakness, sensory impairment, and truncal instability, as well as a variety of autonomic abnormalities. This article will discuss how machine learning classification can be used to characterize the initial impairment and subsequent recovery of electromyography signals in an non-human primate model of traumatic spinal cord injury. The ultimate objective is to identify potential treatments for traumatic spinal cord injury. This work focuses specifically on finding a suitable classifier that differentiates between two distinct experimental

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Publication Date
Thu Jan 10 2019
Journal Name
Applied Physics A
Characterization and nanocrystalline growth of a-Ge:In/c-GaAs
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Publication Date
Mon Jan 01 2024
Journal Name
Aip Conference Proceedings
Gamma irradiation effect on characterization of MoO3 nanostructures films
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Publication Date
Sun Apr 14 2019
Journal Name
Political Sciences Journal
Characterization of terrorist methods and how to address them
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توصيف الاساليب الارهابية وسبل مواجهتها

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