This paper proposes a novel meta-heuristic optimization algorithm called the fine-tuning meta-heuristic algorithm (FTMA) for solving global optimization problems. In this algorithm, the solutions are fine-tuned using the fundamental steps in meta-heuristic optimization, namely, exploration, exploitation, and randomization, in such a way that if one step improves the solution, then it is unnecessary to execute the remaining steps. The performance of the proposed FTMA has been compared with that of five other optimization algorithms over ten benchmark test functions. Nine of them are well-known and already exist in the literature, while the tenth one is proposed by the authors and introduced in this article. One test trial was shown t

The Machine learning methods, which are one of the most important branches of promising artificial intelligence, have great importance in all sciences such as engineering, medical, and also recently involved widely in statistical sciences and its various branches, including analysis of survival, as it can be considered a new branch used to estimate the survival and was parallel with parametric, nonparametric and semi-parametric methods that are widely used to estimate survival in statistical research. In this paper, the estimate of survival based on medical images of patients with breast cancer who receive their treatment in Iraqi hospitals was discussed. Three algorithms for feature extraction were explained: The first principal compone

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The concept of joint integration of important concepts in macroeconomic application, the idea of ​​cointegration is due to the Granger (1981), and he explained it in detail in Granger and Engle in Econometrica (1987). The introduction of the joint analysis of integration in econometrics in the mid-eighties of the last century, is one of the most important developments in the experimental method for modeling, and the advantage is simply the account and use it only needs to familiarize them selves with ordinary least squares.

Cointegration seen relations equilibrium time series in the long run, even if it contained all the sequences on t

In this work, a joint quadrature for numerical solution of the double integral is presented. This method is based on combining two rules of the same precision level to form a higher level of precision. Numerical results of the present method with a lower level of precision are presented and compared with those performed by the existing high-precision Gauss-Legendre five-point rule in two variables, which has the same functional evaluation. The efficiency of the proposed method is justified with numerical examples. From an application point of view, the determination of the center of gravity is a special consideration for the present scheme. Convergence analysis is demonstrated to validate the current method.

In our research, we seek to shed a light on one of the most important and sensitive issues, namely, the Sufi influence in the Iraqi novel through the lame maqam of the novelist Jumaa Al-Lami, the Sufi discourse contains many semantic paradoxes between the text's apparent pronunciation and its interpretation of the format and the context that produced these patterns, and incited them, which concludes different results from the prevailing provisions and fixed ideas from the narrative text.The Arabic and Iraqi novel in particular became inspired by the power of Sufi discourse by talking about several Sufi figures by referring to it openly, or implicitly inspired by unauthorized concealment, in employing some of the ideas, or summoning

Obesity is an escalating health problem in developing countries. One to ten children worldwide are overweight in a report showed by the International Obesity Task Force. Ghrelin, orexigenic peptide, has 28 amino acids, it is considered the greatest remarkable promotion in the last two decades for understanding the physiological changes of action regu­lating food intake and hunger. Obestatin is a 23-amino acid peptide nearly connected to ghrelin that secures from substitutio