The impact of COVID-19 pandemic on education models was mainly through the expansion of technology use in the different educational programs. Earlier impact of COVID-19 was manifested in the complete and sudden transition to distance education regardless of institution preparedness status. Gradually, many institutions are moving back to on-campus face-to-face education. However, others including all higher education institutions in Iraq are adopting the hybrid education model. This report presents part of the end of semester evaluation survey conducted at the University of Baghdad College of Pharmacy for the Spring 2021 semester. The survey aims to address points of strength and weakness associated with the hybrid education model and spe

Artificial intelligence (AI) offers significant benefits to biomedical research and academic writing. Nevertheless, using AI-powered writing aid tools has prompted worries about excessive dependence on these tools and their possible influence on writing proficiency. The current study aimed to explore the academic staff’s perspectives on the impact of AI on academic writing. This qualitative study incorporated in-person interviews with academic faculty members. The interviews were conducted in a semi-structured manner, using a predetermined interview guide consisting of open-ended questions. The interviews were done in person with the participants from May to November 2023. The data was analyzed using thematic analysis. Ten academics aged

AI in teaching English is reshaping language learning. While interest in AI-supported education is growing worldwide, research in this area is still emerging in Iraq. This review synthesizes empirical AI-based intervention studies to enhance English language learning in Iraqi higher education, and the perceptions of stakeholders regarding AI tools in language instruction. The reviewed intervention studies, comprising studies employed different AI platforms to support grammar instruction, speaking fluency, writing feedback, and pragmatic competence. These interventions yielded improvements in learners’ performance, motivation, and communicative confidence. In parallel, perception-focused studies revealed positive attitudes toward A

This research examines the relationship between dinar deposits and U.S. dollar payments at the Central Bank of Iraq using monthly data for the period 2016–2025. The ARDL model, the GRU neural network, and a hybrid ARDL–GRU model are applied. The results show that dollar payments are stationary at level, while dinar deposits become stationary after first differencing, with a significant positive long-run cointegrating relationship. The linear ARDL model has limited ability to capture sudden shocks, whereas the hybrid ARDL–GRU model achieves superior forecasting performance both in-sample and out-of-sample. The findings confirm the Central Bank of Iraq’s efficiency in managing domestic and foreign liquidity and maintaining market stab

Estimation of trip attraction and analyzing its main influencing factors are powerful for offering different classifications for business districts and presenting recommendations for improving attractiveness in long term. This is beneficial for designing transportation facilities and infrastructures. The paper presents the prediction of trip attraction using an artificial intelligence technology due to the profits that the technology can possess in shortening time, lowering expenses and saving effort. The new model has utilized six input parameters that have not been considered previously within the area of Nasiriyah city including; age and educational level of the passengers, mode of transport that the passengers use, purpose of the trip,

Abstract This research adopted a novel mixed-method approach combining quantitative analysis and geospatial statistics with artificial intelligence (AI) techniques to evaluate U5MR in the Middle Euphrates provinces of Iraq in 2022. We investigated spatial patterns, socioeconomic determinants and health system factors related to child mortality, Using data from the Iraqi Ministry of Health in 2022. We uncovered significant disparities across the regions, where the highest death rate in Al Diwaniyah province was 33.1 per 1000 and dropped to 16.6 per 1000 live births in al-Muthanna province. An exhaustive statistical analysis brought to the fore the main factors that accounted for such a variation, that is to say population density in rural a

Diyala River is one of the important rivers that provide water for the Governorate of Diyala. In this research, the morphology and sediment transport of this river were studied using HEC-Ras software. The selected length of the river in the present study is 193 km and extended from Diyala Weir to the confluence of Tigris River and Diyala River. The fieldwork period extended from June 2020 till August 2020, where suspended-load and bed-load samples were collected and surveyed some cross-sections. The one-dimensional sediment transport model has been calibrated for five years, from 2014 to 2019. The results were compared with the measured cross-sections in 2019,  and the suitable value of (maximum depth

In this research an Artificial Neural Network (ANN) technique was applied for the prediction of Ryznar Index (RI) of the flowing water from WTPs in Al-Karakh side (left side) in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3) have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad) including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI) with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respe

The ring modulator described in part I of this paper is designed here for two operating wavelengths 1550nm and 1310nm. For each wavelength, three structures are designed corresponding to three values of polymer slot widths (40, 50 and 60nm). The performance of these modulators are simulated using COMSOL software (version 4.3b) and the results are discussed and compared with theoretical predictions. The performance of intensity modulation/direct detection short range and long rang optical communication systems incorporating the designed modulators is simulated for 40 and 100Gb/s data rates using Optisystem software (version 12). The results reveal that an average energy per bit as low as 0.05fJ can be obtained when the 1550nm modulator is d

This paper presents comprehensive analysis and investigation for 1550nm and 1310nm ring optical modulators employing an electro-optic polymer infiltrated silicon-plasmonic hybrid phase shifter. The paper falls into two parts which introduce a theoretical modeling framework and performance assessment of these advanced modulators, respectively. In this part, analytical expressions are derived to characterize the coupling effect in the hybrid phase shifter, transmission function of the modulator, and modulator performance parameters. The results can be used as a guideline to design compact and wideband optical modulators using plasmonic technology