Microwave heating is caused by the ability of the materials to absorb microwave energy and convert it to heat. The aim of this study is to know the difference that will occur when heat treating the high strength aluminum alloys AA7075-T73 in a microwave furnace within different mediums (dry and acidic solution) at different times (30 and 60) minutes, on mechanical properties and fatigue life. The experimental results of microwave furnace heat energy showed that there were variations in the mechanical properties (ultimate stress, yielding stress, fatigue strength, fatigue life and hardness) with the variation in mediums and duration times when compared with samples without treatment. The ultimate stress, yielding stress and fatigue streng

Background: Therapeutic communication is the basis of interactive relationships among nursing team and their children: that affords opportunities to establish rapport, understand the client’s experience, formulate individualized or client interventions and optimize health care resources.

Objectives: The main aim of the study is to determine the Effectiveness of Education Program on Nurses’ Knowledge about Communication Skills with Children.

Methodology: A quasi-experimental study was conducted in Children Welfare Teaching Hospitals from 7th, October 2018 to the 20th, May 2019. The program and instruments have been constructed by the researcher for the purpose of the study. A non- prob

   In this work, a novel technique to obtain an accurate solutions to nonlinear form by multi-step combination with Laplace-variational approach (MSLVIM) is introduced. Compared with the  traditional approach for variational it overcome all difficulties and enable to provide us more an accurate solutions with extended of the convergence region as well as covering to larger intervals which providing us a continuous representation of approximate analytic solution and it give more better information of the solution over the whole time interval. This technique is more easier for obtaining the general Lagrange multiplier with reduces the time and calculations. It converges rapidly to exact formula with simply computable terms wit

Abstract

The use of modern scientific methods and techniques, is considered important topics to solve many of the problems which face some sector, including industrial, service and health. The researcher always intends to use modern methods characterized by accuracy, clarity and speed to reach the optimal solution and be easy at the same time in terms of understanding and application.

the research presented this comparison between the two methods of solution for linear fractional programming models which are linear transformation for Charnas & Cooper , and denominator function restriction method through applied on the oil heaters and gas cookers plant , where the show after reac

      In this research, the nonparametric technique has been presented to estimate the time-varying coefficients functions for the longitudinal balanced data that characterized by observations obtained through (n) from the independent subjects, each one of them is measured repeatedly by group of  specific time points (m). Although the measurements are independent among the different subjects; they are mostly connected within each subject and the applied techniques is the Local Linear kernel LLPK technique. To avoid the problems of dimensionality, and thick computation, the two-steps method has been used to estimate the coefficients functions by using the two former technique. Since, the two-

المقدمة:

مع مطلع القرن الحادي والعشرين فأن الصراع على امدادات المياه الحيوية هو خطر قائم على الدوام في جميع مناطق العالم حيث يتجاوز الطلب على الماء بشكل كبير العرض القائم ولكون اغلب المصادر الرئيسة للمياه وخاصة في المنطقة العربية يشترك فيها بلدان أو أكثر ولان هذه الدول نادرا ما توافق على الاجراءات التفاوضية الخاصة بأقتسام الامداد المتاح من المياه مما يعني زيادة الخلافات على الوصول الى الم

In this research، a comparison has been made between the robust estimators of (M) for the Cubic Smoothing Splines technique، to avoid the problem of abnormality in data or contamination of error، and the traditional estimation method of Cubic Smoothing Splines technique by using two criteria of differentiation which are (MADE، WASE) for different sample sizes and disparity levels to estimate the chronologically different coefficients functions for the balanced longitudinal data which are characterized by observations obtained through (n) from the independent subjects، each one of them is measured repeatedly by group of  specific time points (m)،since the frequent measurements within the subjects are almost connected an

‎ This research aims to estimate stock returns, according to the ‎Rough Set Theory ‎approach, ‎test ‎its effectiveness and accuracy in predicting stock returns and their potential in the ‎field of ‎financial ‎markets, and rationalize investor decisions. The research sample is totaling (10) ‎companies traded at Iraq Stock Exchange. The results showed a remarkable ‎ ‎Rough Set Theory application in data reduction, contributing to the rationalization of ‎investment ‎decisions. The most prominent conclusions are the capability of rough set theory ‎in ‎dealing with financial data and applying it for forecasting stock ‎returns.‎The ‎research provides those interested in investing stocks in financial

The problem of Bi-level programming is to reduce or maximize the function of the target by having another target function within the constraints. This problem has received a great deal of attention in the programming community due to the proliferation of applications and the use of evolutionary algorithms in addressing this kind of problem. Two non-linear bi-level programming methods are used in this paper. The goal is to achieve the optimal solution through the simulation method using the Monte Carlo method using different small and large sample sizes. The research reached the Branch Bound algorithm was preferred in solving the problem of non-linear two-level programming this is because the results were better.

Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al