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Study the Effects of Microwave Furnace Heat on The Mechanical Properties and Estimated Fatigue life of AA2024-T3
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This research aims to study the effect of microwave furnace heat on the mechanical properties and fatigue life of aluminum alloy (AA 2024-T3). Four conditions were used inside microwave furnace (specimens subjected to heat as dry for 30 and 60min. and specimens subjected to heat as wet (water) for 30 and 60 min.), and compared all results with original alloy (AA 2024-T3). Tensile, fatigue, hardness and surface roughness tests were used in this investigation. It is found that hardness of dry conditions is higher than wet conditions and it increases with increasing of time duration inside microwave furnace for dry and wet conditions. Also, tensile strength has the same behavior of hardness, but it increases with decreasing of time. Dry condition for 60 min. shows the higher fatigue strength than other conditions. Surface roughness parameter (Ra) of dry conditions is higher than wet conditions and it decreases with increasing of duration of time.

 

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Publication Date
Thu Jun 30 2011
Journal Name
Al-khwarizmi Engineering Journal
Performance Improvement of Neural Network Based RLS Channel Estimators in MIMO-OFDM Systems
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The objective of this study was tointroduce a recursive least squares (RLS) parameter estimatorenhanced by using a neural network (NN) to facilitate the computing of a bit error rate (BER) (error reduction) during channels estimation of a multiple input-multiple output orthogonal frequency division multiplexing (MIMO-OFDM) system over a Rayleigh multipath fading channel.Recursive least square is an efficient approach to neural network training:first, the neural network estimator learns to adapt to the channel variations then it estimates the channel frequency response. Simulation results show that the proposed method has better performance compared to the conventional methods least square (LS) and the original RLS and it is more robust a

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Publication Date
Sat Jul 20 2024
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Polyacrylonitrile Nanofiber Composites as Efficient Removal of Pollutants for Wastewater: A Review Article
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Polyacrylonitrile nanofiber (PANFS), a well-known polymers, has been extensively employed in the manufacturing of carbon nanofibers (CNFS), which have recently gained substantial attention due to their excellent features, such as spinnability, environmental friendliness, and commercial feasibility. Because of their high carbon yield and versatility in tailoring the final CNFS structure, In addition to the simple formation of ladder structures through nitrile polymerization to yield stable products, CNFS and PAN have been the focus of extensive research as potential production precursors. For instance, the development of biomedical and high-performance composites has now become achievable. PAN homopolymer or PAN-based precursor copolymer can

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Publication Date
Wed Dec 04 2013
Journal Name
Proceedings Of Nuclei Of Seyfert Galaxies And Qsos - Central Engine & Conditions Of Star Formation — Pos(seyfert 2012)
Are Narrow Line Seyfert 1 galaxies a special class of Active Galactic Nuclei?
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No. Due to their apparently extreme optical to X-ray properties, Narrow Line Seyfert 1s (NLSy1s) have been considered a special class of active galactic nuclei (AGN). Here, we summarize observational results from different groups to conclude that none of the characteristics that are typically used to define the NLSy1s as a distinct group – from the, nowadays called, Broad Line Seyfert 1s (BLSy1s) – is unique, nor ubiquitous of these particular sources, but shared by the whole Type 1 AGN. Historically, the NLSy1s have been distinguished from the BLSy1s by the narrow width of the broad Hb emission line. The upper limit on the full width at half maximum of this line is 2000kms−1 for NLSy1s, while in BLSy1s it can be of several thousands

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Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Classification of COVID-19 from CT chest images using Convolutional Wavelet Neural Network
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<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

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Publication Date
Mon Apr 15 2019
Journal Name
Proceedings Of The International Conference On Information And Communication Technology
Optimal control of compliant planar robot for safe impact using steepest descent technique
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Publication Date
Wed Oct 09 2019
Journal Name
Engineering, Technology &amp; Applied Science Research
Numerical Analysis of Segmental Post Tensioned Concrete Beams Exposed to High Fire Temperature
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The main objective of this study is to characterize the main factors which may affect the behavior of segmental prestressed concrete beams comprised of multi segments. The 3-D finite element program ABAQUS was utilized. The experimental work was conducted on twelve simply supported segmental prestressed concrete beams divided into three groups depending on the precast segments number. They all had an identical total length of 3150mm, but each had different segment numbers (9, 7, and 5 segments), in other words, different segment lengths. To simulate the genuine fire disasters, nine beams were exposed to high-temperature flame for one hour, the selected temperatures were 300°C (572°F), 500°C (932°F) and 700°C (1292°F) as recomm

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Publication Date
Tue Sep 11 2018
Journal Name
Iraqi Journal Of Physics
Estimation of kidney tumor volume in CT images using medical image segmentation techniques
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Kidney tumors are of different types having different characteristics and also remain challenging in the field of biomedicine. It becomes very important to detect the tumor and classify it at the early stage so that appropriate treatment can be planned. Accurate estimation of kidney tumor volume is essential for clinical diagnoses and therapeutic decisions related to renal diseases. The main objective of this research is to use the Computer-Aided Diagnosis (CAD) algorithms to help the early detection of kidney tumors that addresses the challenges of accurate kidney tumor volume estimation caused by extensive variations in kidney shape, size and orientation across subjects.
In this paper, have tried to implement an automated segmentati

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Publication Date
Sun Apr 01 2018
Journal Name
Journal Of Educational And Psychological Researches
Measurement of emotional disorders in young people Who suffer from unemployment in Iraq?
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Generally, there are many problems that people run into; unemployment is one of these common diseases which usually hits the whole communities leaving crucial effects (economic, social, and psychological) that are difficult to handle them. The current study aims to identify the level of emotional disorders among Iraqi unemployed alumni for the academic years (2013-2016). To this end, the researchers have prepared a questionnaire to measure (anxiety, depression, and anger): these criteria distributed over (30) item. As for sample, it limited to (50) male and female student. The findings of study have revealed that the whole sample showed a high level of emotional disorders, and anger disorder showed higher level than the level of (depress

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Publication Date
Tue Dec 03 2013
Journal Name
Ibn Al-haitham Journal For Pure And Applied Science
New adaptive satellite image classification technique for al Habbinya region west of Iraq
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Publication Date
Thu Feb 01 2018
Journal Name
Journal Of Engineering
Tuning of PID Controllers for Quadcopter System using Cultural Exchange Imperialist Competitive Algorithm
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Quadrotors are coming up as an attractive platform for unmanned aerial vehicle (UAV) research, due to the simplicity of their structure and maintenance, their ability to hover, and their vertical take-off and landing (VTOL) capability. With the vast advancements in small-size sensors, actuators, and processors, researchers are now focusing on developing mini UAV’s to be used in both research and commercial applications. This work presents a detailed mathematical nonlinear dynamic model of the quadrotor which is formulated using the Newton-Euler method. Although the quadrotor is a 6 DOF under-actuated system, the derived rotational subsystem is fully actuated, while the translational subsystem is under-actuated. The der

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