Estimation the unknown parameters of a two-dimensional sinusoidal signal model is an important and a difficult problem , The importance of this model  in modeling Symmetric gray- scale texture image . In this paper, we propose employment Deferential Evaluation algorithm and the use of Sequential approach to estimate the unknown frequencies and amplitudes of the 2-D sinusoidal components when the signal is affected by noise. Numerical simulation are performed for different sample size, and various level of standard deviation to observe the performance of this method in estimate the parameters of 2-D sinusoidal signal model , This model was used for modeling  the Symmetric gray scale texture image and estimating by using

The use of Bayesian approach has the promise of features indicative of regression analysis model classification tree to take advantage of the above information by, and ensemble trees for explanatory variables are all together and at every stage on the other. In addition to obtaining the subsequent information at each node in the construction of these classification tree. Although bayesian estimates is generally accurate, but it seems that the logistic model is still a good competitor in the field of binary responses through its flexibility and mathematical representation. So is the use of three research methods data processing is carried out, namely: logistic model, and model classification regression tree, and bayesian regression tree mode

تعد لعبة كرة القدم ولا زالت من الألعاب التي تحظى بمتابعة الكثير من شرائح المجتمع، وهناك عناصر أساسية لها ( الملعب، الأدوات، اللاعبين، الحكام ) والحكام يشكلون العنصر الرئيس لهذه اللعبة إذ تدار كل مباراة بواسطة طاقم تحكيمي يشمل حكم ساحة بالتعاون مع حكمين مساعدين وحكم رابع ، ومن خلال خبرة الباحثان كونهما يعملان في مجال التحكيم وجدا إن هناك ضعفا في هذا المجال للموسم الكروي (2008 – 2009)، وهذا ما أشارت أليه العديد من وس

Two new nonsymmetrical mesogenic homologous series of terminal substituent ether (series [Vn]) and carboxy (series [VIn]) incorporating azobenzene and 1,3,4-oxadiazole group were synthesized. Both series have been All compounds thus isolated were purified and characterized by elemental analysis, Fourier Transform Infrared Spectroscopy, 1H NMR, along with thermal analysis and texture observation using Differential Scanning Calorimetry (DSC) and Polarizing Optical Microscopy (POM), respectively. All compounds of the first series exhibited liquid crystalline properties. The homologues [V1]-[V3] display a nematic mesophase, the compounds [V4]-[V7] exhibit a dimorphism behavior, nematic (N) and smectic A (SmA) mesophases, the compounds [V8] and

          New nitrone and selenonitrone compounds were synthesized. The condensation method between N-(2-hydroxyethyl) hydroxylamine and substituted carbonyl compounds such as [benzil, 4, 4́-dichlorobenzil and  2,2́ -dinitrobenzil] afforded a variety of new nitrone compounds while the condensation between N-benzylhydroxylamine and substituted selenocarbonyl compounds such as [di(4-fluorobenzoyl) diselenide and (4-chlorobenzoyl selenonitrile] obtained selenonitrone compounds. The condensation of N-4-chlorophenylhydroxylamine with dibenzoyl diselenide obtained another type of selenonitrone compounds. The structures of the synthesized compounds were assigned based on spectroscopic data (FT-IR,

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