This study investigates the phonological adaptation of diphthongs within English loanwords in Iraqi Arabic (IA). In contrast to earlier small-scale descriptive studies, this study used quantitative content analysis to analyse 346 established loanwords collected through document review and direct observation to determine the diphthong adaptation patterns involved in the nativisation of English loanwords by native speakers of IA. Content analysis results revealed that most GB diphthong adaptations in English loanwords in IA occur in systematic patterns and thus may be ascribed to particular aspects in both L1 and L2 phonological systems. More specifically, the results indicate that the IA output forms tend to maintain the features of the GB i

Nowadays, the ideas of integrating the concepts of the environment and saving it are being famous. These ideas are widely seen in many fields of study, and language education is one of them. Thus, the identity of English Language teachers (ELT) is a step toward transferring this concept in EFL materials in ELT departments. The EFL teacher's identity takes different meanings. Sometimes, it only means the teacher who teaches the English language, and other times, it means, the cultural and social aspects that the teacher and students interact during the study course. These cultural and social aspects represent the environment in teacher’s identity. This study aims to explore the environmental identity within EFL teacher identity. The sam

Solar collectors, in general, are utilized to convert the solar energy into heat energy, where it is employed to generate electricity. The non-concentrating solar collector with a circular shape was adopted in the present study. Ambient air is heated under a translucent roof where buoyant air is drawn from outside periphery towards the collector center (tower base). The present study is aimed to predict and visualize the thermal-hydrodynamic behavior for airflow under inclined roof of the solar air collector, SAC. Three-dimensional of the SAC model using the re-normalization group, RNG, k−ε turbulence viscus model is simulated. The simulation was carried out by using ANSYS-FLUENT 14.5. The simulation

The main source of water supply in Iraq is the surface water, especially Tigris and Euphrates Rivers and their tributaries. In the recent years there was a great drop in the water levels of Tigris River within Baghdad City which had affected the operation of twelve water supply projects located on the banks of Tigris River in Baghdad City, due to significant climate changes, and the expansion of hydraulic construction (dams) and implementation of new irrigation projects in Turkey, these factors have greatly reduced the water flowrates of river by about 46%. In the present study the flow characteristics of Tigris River within Baghdad City was studied, the reach involved was about 49km in which it represents the urban zone

In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc

. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a

This paper is specifically a detailed review of the Spatial Quantile Autoregressive (SARQR) model that refers to the incorporation of quantile regression models into spatial autoregressive models to facilitate an improved analysis of the characteristics of spatially dependent data. The relevance of SARQR is emphasized in most applications, including but not limited to the fields that might need the study of spatial variation and dependencies. In particular, it looks at literature dated from 1971 and 2024 and shows the extent to which SARQR had already been applied previously in other disciplines such as economics, real estate, environmental science, and epidemiology. Accordingly, evidence indicates SARQR has numerous benefits compar

This paper is specifically a detailed review of the Spatial Quantile Autoregressive (SARQR) model that refers to the incorporation of quantile regression models into spatial autoregressive models to facilitate an improved analysis of the characteristics of spatially dependent data. The relevance of SARQR is emphasized in most applications, including but not limited to the fields that might need the study of spatial variation and dependencies. In particular, it looks at literature dated from 1971 and 2024 and shows the extent to which SARQR had already been applied previously in other disciplines such as economics, real estate, environmental science, and epidemiology. Accordingly, evidence indicates SARQR has numerous benefits compar