In this paper Heun method has been used to find numerical solution for first order nonlinear functional differential equation. Moreover, this method has been modified in order to treat system of nonlinear functional differential equations .two numerical examples are given for conciliated the results of this method.

Introduction to Medical Physics for Pharmacy Students and Medical Groups - ISBNiraq.org

This investigation aimed to explain the mechanism of MFCA by applying this method on air-cooled engine factory which was suffering from high production cost. The results of this study revealed that MFCA is a useful tool to identify losses and inefficiencies of the production process. It is found that the factory is suffering from high losses due to material energy and system losses. In conclusion, it is calculated that system losses are the highest among all the losses due to inefficient use of available production capacity.

In this paper has been building a statistical model of the Saudi financial market using GARCH models that take into account Volatility in prices during periods of circulation, were also study the effect of the type of random error distribution of the time series on the accuracy of the statistical model, as it were studied two types of statistical distributions are normal distribution and the T distribution. and found by application of a measured data that the best model for the Saudi market is GARCH (1,1) model when the random error distributed t. student's .

Abstract

The current research aims to identify the role of family upbringing methods in shaping adolescent gender identity disorder, to identify the causes, components, and disorders of the gender identity of adolescents, and to develop practical visions and suggestions to reduce and stop gender identity disorder completely. Due to the sensitivity of the topic, a questionnaire of five open-ended questions was posted on Facebook to collect the needed data, where (20) respondents answered these questions. The researcher took these (20) respondents as the study sample. The results revealed that excessive emancipation within the family, failure to employ family protection laws, and failure to monitor and follow up on

Background: Gastro oesophageal reflux disease (GERD) is characterized by diverse symptoms. There is an evidence for a genetic component to Gastro oesophageal reflux disease as supported by familial aggregation of this disease. Aim of the study was to investigate whether certain human leucocyte antigen genes HLA-DRB1 are associated with (GERD).Methods: Patients and controls were prospectively recruited from GIT center at Al-Kindy Teaching Hospital (Baghdad-Iraq) between January 2014 and July 2016. Sixty Iraqi Arab Muslim patients with a history of heartburn and dyspepsia were compared with 100 Iraqi Arab Muslims controls. All study patients and control groups underwent upper gastrointestinal endoscopic examinations and their serums were anal

The utilization of sugarcane molasses (SCM), a byproduct of sugar refining, offers a promising bio-based alternative to conventional chemical admixtures in cementitious systems. This study investigates the effects of SCM at five dosage levels, 0.25%, 0.50%, 0.75%, 1.00%, and 1.25% by weight of cement, on cement mortar performance across fresh, mechanical, thermal, durability, and density criteria. A comprehensive experimental methodology was employed, including flow table testing, compressive strength (7, 14, and 28 days) and flexural strength measurements, embedded thermal sensors for real-time hydration monitoring, water absorption and chloride ion penetration tests, as well as 28-day density determination. Results revealed clear

Self-driving automobiles are prominent in science and technology, which affect social and economic development. Deep learning (DL) is the most common area of study in artificial intelligence (AI). In recent years, deep learning-based solutions have been presented in the field of self-driving cars and have achieved outstanding results. Different studies investigated a variety of significant technologies for autonomous vehicles, including car navigation systems, path planning, environmental perception, as well as car control. End-to-end learning control directly converts sensory data into control commands in autonomous driving. This research aims to identify the most accurate pre-trained Deep Neural Network (DNN) for predicting the steerin