In this work, functionally graded materials were synthesized by centrifugal technique at different
volume fractions 0.5, 1, 1.5, and 2% Vf with a rotation speed of 1200 rpm and a constant rotation time, T
= 6 min . The mechanical properties were characterized to study the graded and non-graded nanocomposites
and the pure epoxy material. The mechanical tests showed that graded and non-graded added alumina
(Al2O3) nanoparticles enhanced the effect more than pure epoxy. The maximum difference in impact strength
occurred at (FGM), which was loaded from the rich side of the nano-alumina where the maximum value was
at 1% Vf by 133.33% of the sample epoxy side. The flexural strength and Young modulus of the functionally
graded samples were enhanced by 43.69% and 52.74%, respectively, if loaded from the alumina-rich side.
On the other hand, when loading (FGM) from the epoxy side, the amount of decrease in bending resistance
was 122.4% while the improvement in bending modulus was 81.11% compared to pure epoxy. Scanning
electron microscopy (SEM) revealed the fracture surface of the impact samples and the gradient scattering of
nanoparticles in the epoxy matrix. Numerous applications can be used to manufacture the functionally
graded material by centrifugal casting method, including for the manufacture of gears and all bending
applications such as leaf springs.
Nowadays, university education stands in front of both students who feel they are weak and teachers who are addicted to using traditional and dependent teaching. This has led to have negative repercussions on the learner from different aspects, including the mental aspect and the academic achievement process. Therefore, the present research is concerned with finding a new teaching method that adopts the motivation by the fear of failure technique. Thus, the study aims to examine the effect of adopting this method on students’ academic achievement. To achieve this aim, an experimental method was used, and an achievement test was built for the curriculum material of level two students. The pretest test was applied on 17 male and female s
... Show MoreIn the image processing’s field and computer vision it’s important to represent the image by its information. Image information comes from the image’s features that extracted from it using feature detection/extraction techniques and features description. Features in computer vision define informative data. For human eye its perfect to extract information from raw image, but computer cannot recognize image information. This is why various feature extraction techniques have been presented and progressed rapidly. This paper presents a general overview of the feature extraction categories for image.
During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
... Show MoreIn most manufacturing processes, and in spite of statistical control, several process capability indices refer to non conformance of the true mean (µc ) from the target mean ( µT ), and the variation is also high. In this paper, data have been analyzed and studied for a blow molded plastic product (Zahi Bottle) (ZB). WinQSB software was used to facilitate the statistical process control, and process capability analysis and some of capability indices. The relationship between different process capability indices and the true mean of the process were represented, and then with the standard deviation (σ ), of achievement of process capability value that can reduce the standard deviation value and improve production out of theoretical con
... Show MoreBackground : Carpal tunnel syndrome (CTS) is the most common entrapment neuropathy of upper extremities and Open carpal tunnel release is the most frequent surgical procedure and the gold standard for cases that do not respond to conservative treatment. Aims :This study is used to evaluate the functional outcome of limited palmar mini-incision of carpal tunnel release. This study aims to determine the safety and symptomatic and functional efficacy of median nerve decompression with limited incision in carpal tunnel syndrome surgery. Patients and methods:Carpal tunnel release with a 1.5-2 cm limited palmar incision was performed on 20 patients. Patients were evaluated initially at one month after treatment according to symptom severity
... Show MoreBackground: Bacteriocin is a peptidic toxin has many advantages to bacteria in their ecological niche and has strong antibacterial activity. Objective: The aim of this study was to evaluation of bacteriocin using Streptococcus sanguinis isolated from human dental caries.
Subjects and Methods: Thirty five streptococcus isolates were diagnosed and tested for their production of bacteriocin, and then the optimal conditions for production of bacteriocin were determined. After that, the purification of bacteriocin was made partially by ammonium sulfate at 95% saturation levels, followed by and gel filtration chromatography
... Show MoreDuring COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
... Show MoreA comparison between the resistance capacity of a single pile excited by two opposite rotary machines embedded in dry and saturated sandy soil was considered experimentally. A small-scale physical model was manufactured to accomplish the experimental work in the laboratory. The physical model consists of: two small motors supplied with eccentric mass 0·012 kg and eccentric distance 20 mm representing the two opposite rotary machines, an aluminum shaft with 20 mm in diameter as the pile, and a steel plate with dimensions of (160 × 160 × 20 mm) as a pile cap. The experimental work was achieved taking the following parameters into consideration, pile embedment depth ratio (L/d; length to diameter) and operating freq
... Show MoreThe pervaporation using a commercial hydrophilic ceramic membrane supplied from PERVATECH was conducted. The dehydration of ethanol/ water system was used as a model for the pervaporation study. Pervaporation experiments of ethanol/water system were carried out in the temperature range of 303-343K, ethanol concentration in the feed 10-90 vol. % and the feed flow rate in the range of 0.5-10 L/min. In this work, the effect of operation parameters on permeates fluxes as well as permeates separation factors have been studied. The Water flux is strongly dependent on the temperature; it increased with increasing in temperature, which in turn decreased the selectivity of membrane to water molecules.
In addition water flux was decr
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