Because the Coronavirus epidemic spread in Iraq, the COVID-19 epidemic of people quarantined due to infection is our application in this work. The numerical simulation methods used in this research are more suitable than other analytical and numerical methods because they solve random systems. Since the Covid-19 epidemic system has random variables coefficients, these methods are used. Suitable numerical simulation methods have been applied to solve the COVID-19 epidemic model in Iraq. The analytical results of the Variation iteration method (VIM) are executed to compare the results. One numerical method which is the Finite difference method (FD) has been used to solve the Coronavirus model and for comparison purposes. The numerical simulation methods which are Mean Monte Carlo Finite difference (MMC_FD) and Mean Latin Hypercube Finite difference (MLH_FD), are also used to solve the proposed epidemic model under study. The obtained results are discussed, tabulated, and represented graphically. Finally, the absolute error is the tool used to compare the numerical simulation solutions from 2020 to 2024 years. The behavior of the Coronavirus in Iraq has been expected for 4 years from 2020 to 2024 using the proposed numerical simulation methods.
Ping message focused on highlighting the fact commodity trading in Iraq, and increased exposure to world merchandise trade imbalance, which dominate Iraq's foreign trade major commodity is oil, and therefore the inability of Iraq to control financial revenue as a result of the fluctuations in the international market, the shortage of commodity products will lead inevitably to the weakness in the ability of the local market to meet the internal demand and due to the lack of flexible production machine For agricultural, industrial and economic sectors are responding to changes in the domestic or external demand which will open the door to merchandise imports to invade these markets, since the adoption of the Iraq oil exports,
... Show MoreThis paper deals with the problem of the mechanics of the operation of cinematography in the development of museum exhibition halls. In the first chapter, the researcher dealt with the problem and presented it to reach the goals and purpose of the research, which was represented in using and developing the methods and mechanisms of the presentation to keep pace with what is happening in the world of technology and access to the presented model to new formula and vision declares aesthetical and cognitive measure, thus the search constitutes an importance in absorbing Scenography dimensions in the theater and moved to the idea of the museum and the development of the display models and using them in drawing and representation of perception
... Show MoreA total of 589 fishes, belonging to 23 species were collected from eight different localities
in north and mid Iraq during 1993. The parasitological inspection of such fishes revealed the
presence of 59 parasite species and two fungi. Among such parasites, five monogenetic
trematodes were recorded on the gills of some fishes for the first time in Iraq. These
included:- Ancyrocephalus vanbenedenii on Liza abu from Tigris river at Al-Zaafaraniya,
south of Baghdad; Dactylogyrus anchoratus on Cyprinus carpio from Tigris river at Al –
Zaafaranya D. minutus on C. carpio from both Tigris river at Al-Zaafaraniya and Euphrates
river at Al-Qadisiya dam lake; Discocotyle sagittata on L. abu from both the drainage system
at
This paper study two stratified quantile regression models of the marginal and the conditional varieties. We estimate the quantile functions of these models by using two nonparametric methods of smoothing spline (B-spline) and kernel regression (Nadaraya-Watson). The estimates can be obtained by solve nonparametric quantile regression problem which means minimizing the quantile regression objective functions and using the approach of varying coefficient models. The main goal is discussing the comparison between the estimators of the two nonparametric methods and adopting the best one between them
Multilocus haplotype analysis of candidate variants with genome wide association studies (GWAS) data may provide evidence of association with disease, even when the individual loci themselves do not. Unfortunately, when a large number of candidate variants are investigated, identifying risk haplotypes can be very difficult. To meet the challenge, a number of approaches have been put forward in recent years. However, most of them are not directly linked to the disease-penetrances of haplotypes and thus may not be efficient. To fill this gap, we propose a mixture model-based approach for detecting risk haplotypes. Under the mixture model, haplotypes are clustered directly according to their estimated d