In this study, polymeric composites were prepared from unsaturated polyester as a base material with glass powder (fluorescent) in different weight ratios (4, 6, 8, 10,and 11%) as a support material and after comparison before and after reinforcement of the prepared composites, an increase was found. In the values ​​of mechanical properties (hardness, compressive strength), the shock resistance values ​​decreased, but an increase in temperature leads to an increase in the values ​​of shock resistance, as well as the values ​​of compressive strength And it reduces the hardness value.

Haruki Murakami (1949-present) is a contemporary Japanese writer whose works have been translated into fifty languages and won him plenty of Japanese and international awards. His short stories are well constructed in a weird realistic manner and are mixed with elements of surrealism. His novels and short stories fall under the genre of magical realism. One of the major revolving themes that Murakami wrote about was the haunting feeling of emptiness and disconnectedness in a world which seems to care much for materialism and self-interests.

    The paper explores two of Murakami’s short stories in his book After the Quake (2000) and the relevance of their themes and characters to Iraq after the q

Encryption of data is translating data to another shape or symbol which enables people only with an access to the secret key or a password that can read it. The data which are encrypted are generally referred to as cipher text, while data which are unencrypted are known plain text. Entropy can be used as a measure which gives the number of bits that are needed for coding the data of an image. As the values of pixel within an image are dispensed through further gray-levels, the entropy increases. The aim of this research is to compare between CAST-128 with proposed adaptive key and RSA encryption methods for video frames to determine the more accurate method with highest entropy. The first method is achieved by applying the "CAST-128" and

Coagulation is the most important process in drinking water treatment. Alum coagulant increases the aluminum residuals, which have been linked in many studies to Alzheimer's disease. Therefore, it is very important to use it with the very optimal dose. In this paper, four sets of experiments were done to determine the relationship between raw water characteristics: turbidity, pH, alkalinity, temperature, and optimum doses of alum [   .14 O] to form a mathematical equation that could replace the need for jar test experiments. The experiments were performed under different conditions and under different seasonal circumstances. The optimal dose in every set was determined, and used to build a gene expression model (GEP). The models were co

Linear discriminant analysis and logistic regression are the most widely used in multivariate statistical methods for analysis of data with categorical outcome variables .Both of them are appropriate for the development of linear  classification models .linear discriminant analysis has been that the data of explanatory variables must be distributed multivariate normal distribution. While logistic regression no assumptions on the distribution of the explanatory data. Hence ,It is assumed that logistic regression is the more flexible and more robust method in case of violations of these assumptions.

In this paper we have been focus for the comparison between three forms for classification data belongs

The proposal of nonlinear models is one of the most important methods in time series analysis, which has a wide potential for predicting various phenomena, including physical, engineering and economic, by studying the characteristics of random disturbances in order to arrive at accurate predictions.

In this, the autoregressive model with exogenous variable was built using a threshold as the first method, using two proposed approaches that were used to determine the best cutting point of [the predictability forward (forecasting) and the predictability in the time series (prediction), through the threshold point indicator]. B-J seasonal models are used as a second method based on the principle of the two proposed approaches in dete

Currently, one of the topical areas of application of machine learning methods is the prediction of material characteristics. The aim of this work is to develop machine learning models for determining the rheological properties of polymers from experimental stress relaxation curves. The paper presents an overview of the main directions of metaheuristic approaches (local search, evolutionary algorithms) to solving combinatorial optimization problems. Metaheuristic algorithms for solving some important combinatorial optimization problems are described, with special emphasis on the construction of decision trees. A comparative analysis of algorithms for solving the regression problem in CatBoost Regressor has been carried out. The object of

Background: Machine learning relies on a hybrid of analytics, including regression analyses. There have been no attempts to deploy a sinusoidal transformation of data to enhance linear regression models.
Objectives: We aim to optimize linear models by implementing sinusoidal transformation to minimize the sum of squared error.
Methods: We implemented non-Bayesian statistics using SPSS and MatLab. We used Excel to generate 30 trials of linear regression models, and each has 1,000 observations. We utilized SPSS linear regression, Wilcoxon signed-rank test, and Cronbach’s alpha statistics to evaluate the performance of the optimization model. Results: The sinusoidal

The banks mobilize savings and channel them to the economy, whether commercial or Islamic banks and thus both contribute to increasing financial depth, the objective of this paper is to measure the contribution of the Islamic banks in increase financial depth in Iraq, and compared the role played by private commercial banks in contributing to increasing financial depth in Iraq. The paper has been applying the most used indicators of financial depth that used widely in the literatures, especially those applicable with the Iraqi economy.

The paper found via using the Autoregressive Distributed Lag Model (ARDL) that Islamic banks did not contribute to increasing financial depth in Iraq, as well as for the p

The analysis of survival and reliability considered of topics and methods of vital statistics at the present time because of their importance in the various demographical, medical, industrial and engineering fields. This research focused generate random data for samples from the probability distribution Generalized Gamma: GG, known as: "Inverse Transformation" Method: ITM, which includes the distribution cycle integration function incomplete Gamma integration making it more difficult classical estimation so will be the need to illustration to the method of numerical approximation and then appreciation of the function of survival function. It was estimated survival function by simulation the way "Monte Carlo". The Entropy method used for the