This study examines the transformation of political slogans, clichés, and stereotypes in Russia and Iraq during periods of political regime change in the late 20th and early 21st centuries. The main objective of the work is to identify and comparatively analyze the linguistic and cultural changes that accompanied political transformations in both countries. The research is based on theoretical concepts of political myth, framing, and critical discourse analysis. The research methodology includes content analysis of political texts, comparative analysis of linguistic transformations, and analysis of statistical data on cultural consumption. The main hypothesis is that, despite the presence of common trends in linguistic and cultural

Conversation analysis has long been the concern of many linguists who work in the field of discourse analysis. In spite of the fact that there are many researches have been done in the field of short stories but up to the researcher knowledge the investigation of the selected short stories has not been studied yet. Hence, this paper aims at answering the following questions: what are the features of children’s short stories language and the differences between short stories of four years old and those of six years old.  Hence, the devices used by the story tellers in reciting the short stories should be observed. Thus, the researcher has consulted the models presented by Johnson and Fillmore (2010) to show tenses and sentence str

This research aims to analyze and simulate biochemical real test data for uncovering the relationships among the tests, and how each of them impacts others. The data were acquired from Iraqi private biochemical laboratory. However, these data have many dimensions with a high rate of null values, and big patient numbers. Then, several experiments have been applied on these data beginning with unsupervised techniques such as hierarchical clustering, and k-means, but the results were not clear. Then the preprocessing step performed, to make the dataset analyzable by supervised techniques such as Linear Discriminant Analysis (LDA), Classification And Regression Tree (CART), Logistic Regression (LR), K-Nearest Neighbor (K-NN), Naïve Bays (NB

 This paper adapted the neural network for the estimating of the direction of arrival (DOA). It uses an unsupervised adaptive neural network with GHA algorithm to extract the principal components that in turn, are used by Capon method to estimate the DOA, where by the PCA neural network we take signal subspace only and use it in Capon (i.e. we will ignore the noise subspace, and take the signal subspace only).

Crocidolomia binotalis (Cb) (Zeller) is one of the main pests of cabbage which is difficult for farmers to control in the Ijen Crater in Indonesia. The demand for cabbage in Indonesia is increasing every year, so intensification efforts are continuously being made. Farmers intensively use synthetic pesticides as the primary control of Cb. The purpose of this study is to examine several control agents that can be used as an alternative to synthetic pesticides. Then, it provides recommendations to Ijen Crater farmers to adapt in reducing the use of synthetic pesticides. The biopesticide used was based on the Nuclear Polyhedrosis Virus strains of Spodoptera litura (SlNPV) and Helicoverpa armigera (HaNPV), botanical pesticides, and

This paper presents a novel idea as it investigates the rescue effect of the prey with fluctuation effect for the first time to propose a modified predator-prey model that forms a non-autonomous model. However, the approximation method is utilized to convert the non-autonomous model to an autonomous one by simplifying the mathematical analysis and following the dynamical behaviors. Some theoretical properties of the proposed autonomous model like the boundedness, stability, and Kolmogorov conditions are studied. This paper's analytical results demonstrate that the dynamic behaviors are globally stable and that the rescue effect improves the likelihood of coexistence compared to when there is no rescue impact. Furthermore, numerical simul

The present study has examined the spatiotemporal varieties of the demographics of the Shatt Al-Arab River fishes and their relation to some ecological components. The aim is to forecast these groups in the unexplored parts of the waterway with an emphasis on environmental indices of diversity. Three sites in the river were selected as an observation and study of these species, which lasted from March 2019 to February 2020, the study dealt with factors affecting fishes, as Water Temperature (WT), Dissolved Oxygen (DO), Potential Hydrogen Ion (pH), Salinity (Sal), and Transparency (Tra). Gill nets, cast nets, hooks, and hand nets were adopted to collecting fish. The results indicated that the fish population comprises 60 species represent

<span>Dust is a common cause of health risks and also a cause of climate change, one of the most threatening problems to humans. In the recent decade, climate change in Iraq, typified by increased droughts and deserts, has generated numerous environmental issues. This study forecasts dust in five central Iraqi districts using machine learning and five regression algorithm supervised learning system framework. It was assessed using an Iraqi meteorological organization and seismology (IMOS) dataset. Simulation results show that the gradient boosting regressor (GBR) has a mean square error of 8.345 and a total accuracy ratio of 91.65%. Moreover, the results show that the decision tree (DT), where the mean square error is 8.965, c

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