In this paper the nuclear structure of some of Si-isotopes namely, 28,32,36,40Si have been studied by calculating the static ground state properties of these isotopes such as charge, proton, neutron and mass densities together with their associated rms radii, neutron skin thicknesses, binding energies, and charge form factors. In performing these investigations, the Skyrme-Hartree-Fock method has been used with different parameterizations; SkM*, S1, S3, SkM, and SkX. The effects of these different parameterizations on the above mentioned properties of the selected isotopes have also been studied so as to specify which of these parameterizations achieves the best agreement between calculated and experimental data. It can be deduced from this study that it is SkX parameterization that achieves such agreement. Furthermore, comparison between the theoretical and experimental results of charge form factors has been performed.
The influence of an aortic aneurysm on blood flow waveforms is well established, but how to exploit this link for diagnostic purposes still remains challenging. This work uses a combination of experimental and computational modelling to study how aneurysms of various size affect the waveforms. Experimental studies are carried out on fusiform-type aneurysm models, and a comparison of results with those from a one-dimensional fluid–structure interaction model shows close agreement. Further mathematical analysis of these results allows the definition of several indicators that characterize the impact of an aneurysm on waveforms. These indicators are then further studied in a computational model of a systemic blood flow network. This demonstr
... Show MoreThe green method was chosen for the preparation of nano iron oxide due to its simplicity, ease of preparation, and purity, compared to other methods. Nano iron oxide was made using a substance that causes precipitation and a coating from the alcoholic extract of orange leaves from Iraq. It was examined structurally and spectrally using several techniques, including X-ray diffraction, Fourier transform infrared spectroscopy, field-emission scanning microscopy (FESEM), energy-dispersive X-ray spectroscopy, and UV-Vis spectroscopy. The diagnosis proved that the nano iron oxide was successfully prepared in a spherical form and with an average size of 71.1 nm. The nano iron oxide particles were tested for their ability to remove crystal
... Show MoreEffect of [Cu/In] ratio on the optical properties of CuInS2 thin films prepared by chemical spray pyrolysis on glass slides at 300oC was studied. The optical characteristics of the prepared thin films have been investigated using UV-VIS spectrophotometer in the wavelength range (300-1100 nm). The films have a direct allow electronic transition with optical energy gap (Eg) decreased from 1.51 eV to 1.30 eV with increasing of [Cu/In] ratio and as well as we notice that films have different behavior when annealed the films in the temperature 100oC (1h,2h), 200oC (1h,2h) for [Cu/In]=1.4 . Also the extinction coefficient (k), refractive index (n) and the real and imaginary dielectric constants (ε1, ε2) have been investigated
This paper proposed a new method to study functional non-parametric regression data analysis with conditional expectation in the case that the covariates are functional and the Principal Component Analysis was utilized to de-correlate the multivariate response variables. It utilized the formula of the Nadaraya Watson estimator (K-Nearest Neighbour (KNN)) for prediction with different types of the semi-metrics, (which are based on Second Derivative and Functional Principal Component Analysis (FPCA)) for measureing the closeness between curves. Root Mean Square Errors is used for the implementation of this model which is then compared to the independent response method. R program is used for analysing data. Then, when the cov
... Show MoreWe propose a new method for detecting the abnormality in cerebral tissues present within Magnetic Resonance Images (MRI). Present classifier is comprised of cerebral tissue extraction, image division into angular and distance span vectors, acquirement of four features for each portion and classification to ascertain the abnormality location. The threshold value and region of interest are discerned using operator input and Otsu algorithm. Novel brain slices image division is introduced via angular and distance span vectors of sizes 24˚ with 15 pixels. Rotation invariance of the angular span vector is determined. An automatic image categorization into normal and abnormal brain tissues is performed using Support Vector Machine (SVM). St
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