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The explosion of the COVID-19 pandemic shows the limitations of the existing healthcare system in handling health emergencies. Innovative technologies like artificial intelligence and mathematical modelling can play an essential role in effective planning operations for fighting coronavirus pandemic. In this paper, a comparison between the mathematical model performance and three data-driven models (Feed-forward neural network, Stacked LSTM and Bidirectional LSTM) was performed. These methods (data-driven methods) are applied to model the percentage of positive cases out of the total qPCR tests in Jordan to provide more insight on the appropriate model that can be utilized for COVID-19 disease-spreading analysis. The performance metrics were: mean absolute error (MAE), mean square error (MSE) and coefficient of determination (R2). Our findings show that both mathematical and data-driven models can assess disease-spreading research. However, with the appearance of the new virus variant, Omicron, the mathematical model failed to forecast the pandemic while data-driven approaches are robust and successfully captured the sudden change in the number of positive cases in Jordan. However, much work is still needed to capture more factors in the modelling process and provide a reliable solution for stopping this pandemic.

Die Vorzuge alternativer Antriebe sind allgemein bekannt, und dennoch bergen Fahrzeuge mit zum Beispiel Batterie- oder Wasserstoffantrieb etliche Herausforderungen, unter anderem fur die Strukturintegritat und -sicherheit. So muss bei Unfallszenarien, wie beim seitlichen Pfahlaufprall, sichergestellt sein, dass die Energiespeicher besonders geschutzt sind. Hierbei gilt es, den wenigen Platz im Seitenbereich fur Energieabsorption unter Berucksichtigung der allgemeinen Crashanforderungen optimal zu nutzen.

This paper deals with assessing the impact of socio-economic factors on students’ English language performance in EFL classrooms in Dubai public secondary schools by exploiting a mixed methods research. By doing in depth case study analysis and by using some statistical tools followed by interviews the assessment on Students’ being studied. The impact of this study reveals that the factors involved by students’ points as well by the parent side being considered. The various factors by both sides have an impact on the learning attitude and performance in EFL class rooms which affects in class room phenomenon. The significance of this study using correlation analysis being carried out and the impact is registered accordingly for future analysis.

The improvement of clinical engineering activities has become an issue of increasing concern within the health care services over recent years. This manuscript describes the tools and programs used by the Quality Assurance and Quality Control (QA&QC) department to monitor, control and evaluate activities carried out by the Directorate of Biomedical Engineering (DBE) at Jordanian Ministry of health (MOH) (30 hospital, 712 medical centers). The implemented QA&QC programs and procedures include measurement and monitoring of several performance indicators for services provided by DBE. The local designed Computerized Clinical Engineering Management System (CCEMS) is used to implement QA&QC procedures to monitor, analysis and evaluate different CE activates within DBE. The results of the implemented QA&QC tools and programs prove significant improvement of DBE activities for last three years.