Mixed-effects conditional logistic regression is evidently more effective in the study of qualitative differences in longitudinal pollution data as well as their implications on heterogeneous subgroups. This study seeks that conditional logistic regression is a robust evaluation method for environmental studies, thru the analysis of environment pollution as a function of oil production and environmental factors. Consequently, it has been established theoretically that the primary objective of model selection in this research is to identify the candidate model that is optimal for the conditional design. The candidate model should achieve generalizability, goodness-of-fit, parsimony and establish equilibrium between bias and variab

Urban land uses are in a dynamic state that varies over time, the city of Karbala in Iraq has experienced functional changes over the past 100 years, as the city is characterized by the presence of significant tourist and socio-economic activity represented by religious tourism, and it occur due to various reasons such as urbanization. The purpose of this study is to apply a Markov model to analyze and predict the behavior of transforming the use of land in Karbala city over time. This can include the conversion of agricultural land, or other areas into residential, commercial, industrial land uses. The process of urbanization is typically driven by population growth, economic development, based on a set of probabilities and transitions bet

The issue of auditing contracts according to the related services is one of the important topics It has also become necessary to develop traditional procedures and auditing according to international standards to improve the profession of accounting and auditing. From this standpoint, the research aims to indicate the reflection of the contracting audit in accordance with the related services on the auditor's report. in line with the new directions regarding the need to adopt international standards in the Iraqi environment as the research problem focused on the non-comprehensiveness of the audit programs that deal with auditing contracts according to assurance commitments to contribute obtaining Governing evidence, The research

Many of the dynamic processes in different sciences are described by models of differential equations. These models explain the change in the behavior of the studied process over time by linking the behavior of the process under study with its derivatives. These models often contain constant and time-varying parameters that vary according to the nature of the process under study in this We will estimate the constant and time-varying parameters in a sequential method in several stages. In the first stage, the state variables and their derivatives are estimated in the method of penalized splines(p- splines) . In the second stage we use pseudo lest square to estimate constant parameters, For the third stage, the rem

The Purpose of this research is a comparison between two types of multivariate GARCH models BEKK and DVECH to forecast using financial time series which are the series of daily Iraqi dinar exchange rate with dollar, the global daily of Oil price with dollar and the global daily of gold price with dollar for the period from 01/01/2014 till 01/01/2016.The estimation, testing and forecasting process has been computed through the program RATS. Three time series have been transferred to the three asset returns to get the Stationarity, some tests were conducted including Ljung- Box, Multivariate Q and Multivariate ARCH to Returns Series and Residuals Series for both models with comparison between the estimation and for

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

Objective(s): To evaluate the family physicians' practices and to measure its impact upon the quality of family
medicine health care in Baghdad City model primary health care centers.
Methodology: A descriptive study, using the evaluation approach, has evaluated the impact of family physicians'
practices upon quality of healthcare in Baghdad's Model Primary Health Care Centers of Family Medicine. It is
carried out during 15th of May – 20th of August 2017. The study is conducted at five model primary health care
centers of family medicine from two districts; AL-Rusafa and AL-Kurkh. Sample size is calculated to be (76)
family physicians. Convenient sample of (124) patients who are attending these primary health care cen

Research Summary

In The Name of Allah Most Gracious Most Merciful

The word injustice and its derivatives were repeated in the Holy Qur’an in several places, approximately (154) times. This is due to the severity of its danger, and that the most dangerous thing that our Islamic nation suffers from in our time is; It is injustice in all its forms and types, so we should all have an honest review of the sincere change in the right direction, and uncover cases of injustice and explain their causes and causes, and work to treat them and rid the wrongdoers of their injustice, and help them to correct their condition. To reveal their grievances and explain their causes and causes, and work to remedy them, and support them and mi

High vehicular mobility causes frequent changes in the density of vehicles, discontinuity in inter-vehicle communication, and constraints for routing protocols in vehicular ad hoc networks (VANETs). The routing must avoid forwarding packets through segments with low network density and high scale of network disconnections that may result in packet loss, delays, and increased communication overhead in route recovery. Therefore, both traffic and segment status must be considered. This paper presents real-time intersection-based segment aware routing (RTISAR), an intersection-based segment aware algorithm for geographic routing in VANETs. This routing algorithm provides an optimal route for forwarding the data packets toward their destination