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Prediction of Creep-Fatigue Interaction Damage for Polyamide 6,6 Composites
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    This paper aims to study the damage generated due to creep-fatigue interaction behaviors in solid polyamide 6,6 and its composites that include 1%wt of carbon nanotubes or 30% wt short carbon fiber prepared by an injection technique. The investigation also includes studying the influence of applied temperatures higher than the glass transition temperatures on mechanical properties. The obtained results showed that the addition of reinforcement materials increased all the mechanical properties, while the increase in test temperature reduced all mechanical properties, especially for polyamide 6,6. The creep-fatigue interaction resistance also improved due to the addition of reinforcement materials by increasing the theoretical damage value by 50% approximately, and the failure always happened through the rotating part of the creep-fatigue interaction test program. Using the Manson-Halford damage equation to estimate the damage generated in polyamide 6,6 and its composites gives unsafe design conditions.    

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Publication Date
Sat Jan 01 2022
Journal Name
Proceedings Of International Conference On Computing And Communication Networks
Automatic Health Speech Prediction System Using Support Vector Machine
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Publication Date
Fri May 01 2020
Journal Name
Journal Of Electrical And Electronics Engineering
HF Wave Propagation Prediction Based On Passive Oblique Ionosonde
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High frequency (HF) communications have an important role in long distances wireless communications. This frequency band is more important than VHF and UHF, as HF frequencies can cut longer distance with a single hopping. It has a low operation cost because it offers over-the-horizon communications without repeaters, therefore it can be used as a backup for satellite communications in emergency conditions. One of the main problems in HF communications is the prediction of the propagation direction and the frequency of optimum transmission (FOT) that must be used at a certain time. This paper introduces a new technique based on Oblique Ionosonde Station (OIS) to overcome this problem with a low cost and an easier way. This technique uses the

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Publication Date
Sat Aug 01 2015
Journal Name
International Journal Of Computer Science And Mobile Computing
Image Compression based on Non-Linear Polynomial Prediction Model
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Publication Date
Mon Mar 09 2020
Journal Name
Agrosystems, Geosciences & Environment
In-season potato yield prediction with active optical sensors
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Crop yield prediction is a critical measurement, especially in the time when parts of the world are suffering from farming issues. Yield forecasting gives an alert regarding economic trading, food production monitoring, and global food security. This research was conducted to investigate whether active optical sensors could be utilized for potato (Solanum tuberosum L.) yield prediction at the mid.le of the growing season. Three potato cultivars (Russet Burbank, Superior, and Shepody) were planted and six rates of N (0, 56, 112, 168, 224, and 280 kg ha−1), ammonium sulfate, which was replaced by ammonium nitrate in the 2nd year, were applied on 11 sites in a randomized complete block design, with four replications. Normalized difference ve

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Publication Date
Thu May 31 2012
Journal Name
Al-khwarizmi Engineering Journal
Channel Estimation and Prediction Based Adaptive Wireless Communication Systems
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Wireless channels are typically much more noisy than wired links and subjected to fading due to multipath  propagation which result in ISI and hence high error rate. Adaptive modulation is a powerful technique to improve the tradeoff between spectral efficiency and Bit Error Rate (BER). In order to adjust the transmission rate, channel state information (CSI) is required at the transmitter side.

In this paper the performance enhancement of using linear prediction along with channel estimation to track the channel variations and adaptive modulation were examined. The simulation results shows that the channel estimation is sufficient for low Doppler frequency shifts (<30 Hz), while channel prediction is much more suited at

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Publication Date
Mon Sep 30 2024
Journal Name
Iraqi Journal Of Science
Attention-Deficit Hyperactivity Disorder Prediction by Artificial Intelligence Techniques
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Attention-Deficit Hyperactivity Disorder (ADHD), a neurodevelopmental disorder affecting millions of people globally, is defined by symptoms of hyperactivity, impulsivity, and inattention that can significantly affect an individual's daily life. The diagnostic process for ADHD is complex, requiring a combination of clinical assessments and subjective evaluations. However, recent advances in artificial intelligence (AI) techniques have shown promise in predicting ADHD and providing an early diagnosis. In this study, we will explore the application of two AI techniques, K-Nearest Neighbors (KNN) and Adaptive Boosting (AdaBoost), in predicting ADHD using the Python programming language. The classification accuracies obtained w

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Publication Date
Fri Oct 01 2010
Journal Name
Iraqi Journal Of Physics
Effect of Carbon Black and Water Absorption on Dielectric behavior of EP-modified SiO2 composites
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Epoxy (EP) – Silica (SiO2) composites are well known composites used in microelectronic industry . So it is important to study their dielectric behavior under different conditions such as
the presence carbon black (UV absorber) and immersion in the water for 30 days .
Dielectric properties were calculated over the frequency range 102 – 106 Hz for epoxy composites with different weight % of micrometer 1.5μm SiO2 particles (60%, 65% and 70wt%) modified with 0.5wt% silane coupling agent to improve adhesion between EP and SiO2 phases .

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Publication Date
Tue Jan 01 2019
Journal Name
Energy Procedia
Manufacturing and improving the characteristics of the isolation of concrete composites by additive Styrofoam particulate
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Publication Date
Sun Dec 07 2014
Journal Name
Baghdad Science Journal
The effect of temperature and chemical solutions on the Compressive strength of particulate hybrid composites
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In this work a hybrid composite materials were prepared containing matrix of polymer (polyethylene PE) reinforced by different reinforcing materials (Alumina powder + Carbon black powder CB + Silica powder). The hybrid composite materials prepared are: • H1 = PE + Al2O3 + CB • H2 = PE + CB + SiO2 • H3 = PE + Al2O3 + CB + SiO2 All samples related to electrical tests were prepared by injection molding process. Mechanical tests include compression with different temperatures and different chemical solutions at different immersion times The mechanical experimentations results were in favour of the samples (H3) with an obvious weakness of the samples (H1) and a decrease of these properties with a rise in temperature and the increasing

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Publication Date
Sun Dec 06 2015
Journal Name
Baghdad Science Journal
The Effect of Fillers on the Chemical, Mechanical and Dielectric Properties of Polyvinyl Chloride Composites
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The compounding of polyvinyl chloride (PVC) with two types of fillers and some additives were studied for the manufacturing of acid resistant tile. Various concentrations of two types of fillers namely; calcium carbonate and recycled glass powder were used along with different additives generally categorized as plasticizers, stabilizers, and lubricants were mixed in the standard concentration unit parts per hundred resins (phr) with the PVC as base polymer. The effects of filler materials on acid resistant towered different acids like sulphuric, nitric and hydrochloric at different concentration were studied. Samples which passed the test were further checked for dielectric strength and mechanical properties. It was found that the recycl

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