The research aimed to shed light on the impact of international Accounting Standard No (21) on tax obstacles represented by (tax evasion, double taxation) The financial statements of a group of banks operating in the private sector were relied upon to know the impact of the standard on tax obstacles, as well as knowing the amount of amounts, The researcher relied on the method of financial analysis of that data, which was obtained from the website of the Securities Commission, and conducted personal interviews with a number of university professors, chartered accountants, financial experts, banks, and the General Authority for Taxes to benefit from their

The research involves using phenol – formaldehyde (Novolak) resin as matrix for making composite material, while glass fiber type (E) was used as reinforcing materials. The specimen of the composite material is reinforced with (60%) ratio of glass fiber.

      The impregnation method is used in test sample preparation, using molding by pressure presses.

      All samples were exposure to (Co⁶⁰) gamma rays of an average energy (2.5)Mev. The total doses were (208, 312 and 728) KGy.

      The mechanical tests (bending, bending strength, shear force, impact strength and surface indentation) were performed on un irradiated and irrad

     The current issues in spam email detection systems are directly related to spam email classification's low accuracy and feature selection's high dimensionality. However, in machine learning (ML), feature selection (FS) as a global optimization strategy reduces data redundancy and produces a collection of precise and acceptable outcomes. A black hole algorithm-based FS algorithm is suggested in this paper for reducing the dimensionality of features and improving the accuracy of spam email classification. Each star's features are represented in binary form, with the features being transformed to binary using a sigmoid function. The proposed Binary Black Hole Algorithm (BBH) searches the feature space for the best feature subsets,

Nonlinear time series analysis is one of the most complex problems ; especially the nonlinear autoregressive with exogenous variable (NARX) .Then ; the problem of model identification and the correct orders determination considered the most important problem in the analysis of time series . In this paper , we proposed splines  estimation method for model identification , then we used three criterions for the correct orders determination. Where ; proposed method used to estimate the additive splines for model identification , And the rank determination depends on the additive property  to avoid the problem of curse dimensionally . The proposed method is one of the nonparametric methods , and the simulation results give a