B Saleem, H Alwan, L Khalid, Journal of Engineering, 2011 - Cited by 2

The covid-19 pandemic sweeping the world and has rendered a large proportion of the workforce as they are unable to commute to work. This has resulted in employees and employers seeking alternative work arrangements, including the software industry. Then comes the need for the global market and international presence of many companies to implement the global virtual teams (GVTs). GVTs members are gradually engaged in globalized business environments across space, time and organizational boundaries via information and communication technologies. Despite the advancement of technology, the project managers are still facing many challenges in communication. Hense, to become a successful project manager still a big challenge for them. This study

This study aims to analyze the messages of a number of global news outlets on Twitter. In order to clarify the news outlets tactics of reporting, the subjects and focus during the crisis related to the spread of the Covid-19 virus. The study sample was chosen in a deliberate manner to provide descriptive results. Three news sites were selected: two of the most followed, professional and famous international news sites: New York Times and the Guardian, and one Arab news site: Al-Arabiya channel.

A total of 18,085 tweets were analyzed for the three accounts during the period from (1/3/2020) to (8/4/2020). A content analysis form was used to analyze the content of the news coverage.   The results indicate an increase in th

The aim of this study was to compare the effect of conventional implant site preparation technique and a combination of conventional/piezosurgery preparation on implant stability measured at different time intervals, insertion torque, and preparation time. A randomized controlled study was designed, it included 26 patients who received 54 dental implants randomly assigned to 2 groups; in the control group, implants were installed after conventional preparation with drills whereas the study group received implants after mixed conventional/piezosurgery preparation. The outcome variables included: implant stability measured immediately after implant insertion, at 8 weeks and 16 weeks postoperatively, insertion torque and preparation time. All

Coronavirus diseases 2021 (COVID-19) on going situation in Iraq is characterized in this paper. The pandemic handling by the government and the difficulties of public health measures enforcement in Iraq. Estimation of the COVID-19 data set was performed. Iraq is endangered to the pandemic, like the rest of the world besides sharing borders with hotspot neighbouring country Iran. The government of Iraq launched proactive measures in an attempt to prevent the viral spread. Nevertheless, reports of new cases keep escalating leaving the public health officials racing to take more firm constriction to face the pandemic. The paper bring forth the current COVID-19 scenario in Iraq, the government measures towards the public health challenges, and

The covid-19 global pandemic has influenced the day-to-day lives of people across the world. One consequence of this has been significant distortion to the subjective speed at which people feel like time is passing. To date, temporal distortions during covid-19 have mainly been studied in Europe. The current study therefore sought to explore experiences of the passage of time in Iraq. An online questionnaire was used to explore the passage of time during the day, week and the 11 months since the first period of covid-19 restrictions were imposed in Iraq. The questionnaire also measured affective and demographic factors, and task-load. The results showed that distortions to the passage of time were widespread in Iraq. Participants co

After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings