جامعة الكوت - University of kut - Research Hosam kamel lssa

	2025	2nd International Conference on Emerging Trends and Applications in Artificial Intelligence (ICETAI 2024)
The Triple Modular Redundancy (TMR) system is a powerful technique that works to reduce errors and failures that occur in the system because it works to increase the reliability of the systems, these systems consist of three components. These components are exposed to higher stress than the stress they face under the normal conditions. Some mathematical properties of the system distribution were derived, such as the probability density function (PDF), the Cumulative Density Function (CDF), the reliability of the system and the risk function. This study focuses on the comparison between two prediction methods (maximum likelihood and least squares) for the “TMR” system under the (partial life test) with gradual stress, which follows the (Frechete distribution). The comparison standard was the modified mean square error, and a simulation utilizing the (Monte Carlo) method in the (R) program was studied. This study aims to find out the most efficient method for this tripartite standard system. One of the most important conclusions of this study, the maximum likelihood method is better in prediction for the parameters and is more efficient because of the least mean square error rate compared to the other method, which reduces the risk of unexpected failure and economic losses.

	2025	2nd International Conference on Emerging Trends and Applications in Artificial Intelligence (ICETAI 2024)
In this study, a new distribution was presented, called Marshall-Olkin truncated exponential distribution based on a generalization formula, which is one of the statistical distributions to describe the continuous variables for many real life and physical experiments. The proposed distribution is consists of three parameters (α, θ, λ) and the it derivation of some important statistical properties of the Marshall-Olkin exponential distribution such as the cumulative distribution function (CDF), the probability density function (PDF), the survival function, and the risk function, as well as the derivation of some of mathematical properties such as the mean, variance, flatness, skewness, and the use of an estimation method for the parameters of the Marshall-Olkin distribution, which is (the method of moments and the method of proportions). Monte Carlo simulation method was utilized and three sample sizes (10, 50, 100) were taken to compare the parameters of the proposed distribution by using the comparison criterion of the mean square error (MSE). The results are the method of moment is superiority over the other method because it had the least mean square error

	2025	مجلة جامعة الكوت
This study aims to analyze the impact of economic variables, specifically the average crude oil prices as the dependent variable, on the exchange rate of the Iraqi dinar against the US dollar during the period from 2000 to 2024. The analysis was conducted using statistical tools and methods. Annual data for the two studied variables were collected and subjected to normality tests (Kolmogorov-Smirnov and Shapiro-Wilk). In addition, Pearson correlation and simple linear regression analyses were performed to determine the extent of the impact of oil prices on the exchange rate.The results showed that the exchange rate data of the Iraqi dinar follow a normal distribution. The correlation analysis revealed an inverse relationship between the two variables, with a correlation coefficient of -0.283 and a p-value of 0.170, which is higher than the commonly accepted significance level of 0.05.The study recommends the use of non- parametric statistical methods in future analyses of such variables, emphasizing the importance of developing predictive models, such as ARIMA, to analyze future trends in exchange rates and enhance the ability to make data-driven economic and financial decisions.

	2025	مجلة جامعة الكوت
This research aims to construct an econometric model to measure inflation in Iraq and assess its stability over the period from 1971 to 2013. The study focuses on the relationship between money supply as a quantitative indicator and inflation behavior, considering Iraq’s unstable economic conditions including wars, oil price fluctuations, and shifting fiscal policies.Using linear regression analysis via SPSS, along with the Chow test to examine model stability across different time periods, the findings show relative stability during 1971–2003. However, the 2013–2003 period reflects a weakening relationship, indicating a shift in inflation dynamics and model instability in recent years.The study recommends updating economic models used in fiscal and monetary policy, incorporating a broader set of indicators to measure inflation, and enhancing economic stability to ensure more accurate future estimations.