AS Muhsen, International Journal of Psychosocial Rehabilitation (1475-7192), 2020 - Cited by 1

In this research Bi2S3 thin films have been prepared on glass substrates using chemical spray pyrolysis method at substrate temperature (300oC) and molarity (0.015) mol. Structural and optical properties of the thin films above have been studied; XRD analysis demonstrated that the Bi2S3 films are polycrystalline with (031) orientation and with Orthorhombic structure. The optical properties were studied using the spectral of the absorbance and transmission of films in wavelength ranging (300-1100) nm. The study showed that the films have high transmission within the range of the visible spectrum. Also absorption coefficient, extinction coefficient and the optical energy gap (Eg) was calculated, found that the film have direct ener

The degree of the woman’s satisfaction on clothing depends, to a large extent, on the body measurements. If clothing is very wide, it shows her enormous and if it is too tight it may draw attention to the defects of the body. It may also lead to the compatibility or incompatibility of clothing with fashion. Whatever the quality of the garment in terms of sewing and design, the costume which is not suitable for body size may affect the physical style negatively and may give the wearer an improper look. Clothing was carried out without measurements and did not use models (templates). The method of preparation affected the overall appearance because it often did not fit the shape of the body completely. Therefore, people thought in many w

The - M ultiple mixing ratios of -transitions from levels of 56Fe populated in 56 56 Fe n n Fe ( , )  reactions are calculated by using const. S.T.M. This method has been used in other works [3,7] but with pure transition or with transitions that can be considered as pure transitions، in our work we used This method for mixed  - transitions in addition to pure  - transitions. The experimental angular distribution coefficients a2 was used from previous works [1] in order to calculet - values. It is clear from the results that the - values are in good agreement or consistent, within associated errors, with those reported previously [1]. The discrepancies that occur are due to inaccuracies existing in the expe

Samarium ions (Sm +3), a rare-earth element, have a significant optical emission within the visible spectrum. PMMA samples, mixed with different ratios of SmCl3.6H2O, were prepared via the casting method. The composite was tested using UV-visible, photoluminescence and thermogravimetric analysis (TGA). The FTIR spectrometry of PMMA samples showed some changes, including variation in band intensity, location, and width. Mixed with samarium decreases the intensity of the CO and CH2 stretching bands and band position. A new band appeared corresponding to ionic bonds between samarium cations with negative branches in the polymer. These variations indicate complex links between the Sm +3 ion and oxygen in the ether group. The optical absorption

Free Radical Copolymerization of Styrene/ Methyl Methacrylate were prepared chemically under Nitrogen ,which was investigated, in the present of Benzoyl Peroxide as Initiator at concentration of 2 × 10-3 molar at 70 °C, which was carried out in Benzene as solvent to a certain low conversion . FT-IR spectra were used for determining of the monomer reactivity ratios ,which was obtained by employing the conventional linearization method of Fineman-Ross (F-R) and Kelen-Tüdos (K- T). The experimental results showed the average value for the Styrene r1 / Methyl Methacrylate r2 system, Sty r1 = 0.45 , MMA r2 = 0.38 in the (F–R) Method and r1 = 0.49 , r2 = 0.35 in the (K–T) Method, The Results of this indicated show the random distri

The 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