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  This study is concerned with the estimation of constant  and time-varying parameters in non-linear ordinary differential equations, which do not have analytical solutions. The estimation is done in a multi-stage method where constant and time-varying parameters are estimated in a straight sequential way from several stages. In the first stage, the model of the differential equations is converted to a regression model that includes the state variables with their derivatives and then the estimation of the state variables and their derivatives in a penalized splines method and compensating the estimations in the regression model. In the second stage, the pseudo- least squares method was used to es

The process of transformation from the central economy to a free economy requires restructuring the economy according to a new economic philosophy that relies on activating the role of private economic activity in which private and medium-sized institutions occupy an essential axis for their active role in the economies of all countries, especially those countries that have directed towards the market mechanism and sector leadership. The special process of economic development and the role that commercial banks can play in advancing the financing of these projects by establishing specialized business incubators for financing.

What encouraged countries to pay attention to these institutions is the ease of

The paper presents an overview of theoretical aspects of small radio telescope antenna parameters. The basic parameters include antenna beamwidth, antenna gain, aperture efficiency, and antenna temperature. These parameters should be carefully studied since they have vital effects on astronomical radio observations. The simulations of antenna parameters were carried out to assess the capability and the efficiency of small radio telescopes to observe a point source at a specific frequency. Two-dimensional numerical simulations of a uniform circular aperture antenna are implemented at different radii. The small diameter values are chosen to be varied between (1-10) m. This study focuses on a small radio telescope with a diameter of 3 m sin

The - mixing ratios of -transitions from levels in populated in the reactions are calculated in present work using - ratio, constant statisticalTensor and least squares fitting methods The results obtained are in general, in good agreement or consistent, within the associated uncertainties, with these reported in Ref.[9],the discrepancies that occurs are due to inaccuracy existing in the experimental data The results obtained in the present work confirm the –method for mixed transitions better than that for pure transition because this method depends only on the experimental data where the second method depends on the pure or those considered to be pure -transitions, the same results occur in – method

The absurdity of Orientalist thought and its deviation in interpretation
Quranic text
View and critique

The Artificial Neural Network methodology is a very important & new subjects that build's the models for Analyzing, Data Evaluation, Forecasting & Controlling without depending on an old model or classic statistic method that describe the behavior of statistic phenomenon, the methodology works by simulating the data to reach a robust optimum model that represent the statistic phenomenon & we can use the model in any time & states, we used the Box-Jenkins (ARMAX) approach for comparing, in this paper depends on the received power to build a robust model for forecasting, analyzing & controlling in the sod power, the received power come from

This paper includes a comparison between denoising techniques by using statistical approach, principal component analysis with local pixel grouping (PCA-LPG), this procedure is iterated second time to further improve the denoising performance, and other enhancement filters were used. Like adaptive Wiener low pass-filter to a grayscale image that has been degraded by constant power additive noise, based on statistics estimated from a local neighborhood of each pixel. Performs Median filter of the input noisy image, each output pixel contains the Median value in the M-by-N neighborhood around the corresponding pixel in the input image, Gaussian low pass-filter and Order-statistic filter also be used. Experimental results shows LPG-PCA method

This paper includes a comparison between denoising techniques by using statistical approach, principal component analysis with local pixel grouping (PCA-LPG), this procedure is iterated second time to further improve the denoising performance, and other enhancement filters were used. Like adaptive Wiener low pass-filter to a grayscale image that has been degraded by constant power additive noise, based on statistics estimated from a local neighborhood of each pixel. Performs Median filter of the input noisy image, each output pixel contains the Median value in the M-by-N neighborhood around the corresponding pixel in the input image, Gaussian low pass-filter and Order-statistic filter also be used.

Experimental results shows LPG-

Background: Temporomandibular joint disorder (TMD) is a general term that describe a wide variety of conditions that include myogenic pain, internalderangement, arthritic problem, ankylosis of the joint and growth disorders. The aims of study was to evaluate the value of 3 Tesla magnetic resonance imaging in assessment of articular disc position and configuration in patients with temporomandibular joint disorders and to evaluate the correlations of these MRI findings with the clinical signs and symptoms. Materials and methods: A total forty six (30 study and 16 control) participants aged between18 and 49 years, were examined according to Helkimo anamnestic index (questionnaire for anamnesis) and clinical dysfunction index scoring criteria