The solution casting method was used to prepare a polyvinylpyrrolidone (PVP)/Multi-walled carbon nanotubes (MWCNTs) nanocomposite with Graphene (Gr). Field Effect Scanning Electron Microscope (FESEM) and Fourier Transformer Infrared (FTIR) were used to characterize the surface morphology and optical properties of samples. FESEM images revealed a uniform distribution of graphene within the PVP-MWCNT nanocomposite. The FTIR spectra confirmed the nanocomposite information is successful with apperaring the presence of primary distinct peaks belonging to vibration groups that describe the prepared samples.. Furthermore, found that the DC electrical conductivity of the prepared nanocomposites increases with increasing MWCNT concentration which is due to hopping conduction
The ceramic compound Mg1-xSixAl2O4 (x= 0, 0.1, 0.2, 0.3, 0.4) was prepared from nano powder of Al2O3 and MgO doped with Nano powder of SiO2 at different molar ratios. The specimens were prepared by standard chemical solid reaction technique and sintered at 1450 oC. Structure of the specimens was analyzed by using X-ray diffraction (XRD). The X-ray patterns of the specimens showed the formation of pure simple cubic spinel structure MgAl2O4 phase with space group of ̅ . The average grain size and surface topology were studied by atomic force microscopy. The results showed that the average grain size was about 73-90 nm. The DC electrical properties of the specimen were measured. The apparent density was found to increase and the porosity a
... Show MoreMulti-point forming (MPF) is an advanced flexible manufacture technology, and the technology results from the idea that the whole die is separated into small punches that can be adjusted height. This idea is applied to the traditional rigid blank-holder, so flexible blank-holder (FBH) idea can be obtained. In this work, the performance of a multi-point die is investigated with pins in square matrix and suitable blank holder. Each pin in the punch holder can be a significant moved according to the die high and at different load that applied with spring with respect to spring stiffness. The results shows the reduction in setting time with respect to traditional single point incremental forming process that lead to (90%). and also show duri
... Show MoreIn this study four species from Solanaceae family was conducted. These four species belong to four different genera (Solanum L. ? Physalis L. ?Withania Pauq. ? Lycium L.) The study included morphological characters of sex organs and their pollen grains for these Iraqi wild plants.The results showed that the position of epipetalous stamens , the shape of anther, their dimensions ,and the length of filaments are important taxonomical characters .On the others hand the shape of their ovaries and stigmas are also important characters in distinguish between these four species .Pollen grains are similar in their general shapes and polarities, they have three germinal furrows and germinal apertures, so they are minor in distinguish between these f
... Show MoreLeuciscidae species are the abundant and widely distributed fish species in Iraq's inland waters. They are complex species, and morphology makes them difficult to identify. Molecular analysis achieved and confirmed the morphological characters. Twenty specimens of Acanthobrama marmid were collected from two localities at Tigris River, in the middle of Iraq; 15 specimens from the Al-Zubaydia sub-district and five specimens from Al-Tharthar Lake. We used the mitochondrial DNA cytochrome b (cytb) gene to sequence the DNA of A. marmid. The following analysis are compared the sequences with those of other fish genera and species found in the Gene Bank. The barcoding result (DNA sequencing) in fishes found in the same family (Leuciscidae) showed
... Show MoreThe field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet
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