Bilgisayar Mühendisliği Bölümü Yayın Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/253
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Article Citation - WoS: 19Citation - Scopus: 27Software Professionals During the Covid-19 Pandemic in Turkey: Factors Affecting Their Mental Well-Being and Work Engagement in the Home-Based Work Setting(Elsevier Science inc, 2022) Tokdemir, GulWith the COVID-19 pandemic, strict measures have been taken to slow down the spread of the virus, and consequently, software professionals have been forced to work from home. However, home based working entails many challenges, as the home environment is shared by the whole family simultaneously under pandemic conditions. The aim of this study is to explore software professionals' mental well-being and work engagement and the relationships of these variables with job strain and resource-related factors in the forced home-based work setting during the COVID-19 pandemic. An online cross-sectional survey based on primarily well-known, validated scales was conducted with software professionals in Turkey. The analysis of the results was performed through hierarchical multivariate regression. The results suggest that despite the negative effect of job strain, the resource related protective factors, namely, sleep quality, decision latitude, work-life balance, exercise predict mental well-being. Additionally, work engagement is predicted by job strain, sleep quality, and decision latitude. The results of the study will provide valuable insights to management of the software companies and professionals about the precautions that can be taken to have a better home-based working experience such as allowing greater autonomy and enhancing the quality of sleep and hence mitigating the negative effects of pandemic emergency situations on software professionals' mental well-being and work engagement. (C)& nbsp;2022 Elsevier Inc. All rights reserved.Article Citation - WoS: 2The Effect of Population and Tourism Factors on Covid-19 Cases in Italy: Visual Data Analysis and Forecasting Approach(Wiley, 2022) Ozyer, Baris; Ozyer, Gulsah Tumuklu; Tokdemir, Gul; Uguz, Sezer; Yaganoglu, MeteAt the beginning of 2020, the new coronavirus disease (Covid-19), a deadly viral illness, is declared as a public health emergency situation by WHO. Consequently, it is accepted as pandemic that affected millions of people worldwide. Italy is one of the most affected countries by Covid-19 disease among the world. In this article, our main goal is to investigate the effect of intensity of Covid-19 cases based on the population size and tourism factors in certain regions of Italy by visual data analysis. The regions of Lombardia, Veneto, Campania, Emilia-Romagna, Piemonte are the top five regions covering 58.50% of the total Covid-19 cases diagnosed in Italy. It has been shown by visual data analysis that population and tourism factors play an important role in the spread of Covid-19 cases in these five regions. In addition, a prediction model was created using Bi-LSTM and ARIMA algorithms to forecast the number of Covid-19 cases occurring in these five regions in order to take early action. We can conclude that these northern regions have been affected mostly by Covid-19 and the distribution of the resident population and tourist flow factors affected the number of Covid-19 cases in Italy.Conference Object Investigating the Factors That Impact E-Learning Systems in Oil and Gas Industry(American Institute of Physics Inc., 2022) AlRawi, L.N.; AlBella, A.H.; Ashour, O.I.The use of digital media such as audio and video as a teaching media helps to achieve teaching goals better than following traditional teaching. It improves the engagement with the lecture and helps to deliver the education by lower cost and shorter time. Many companies use electronic Learning (e-learning) as an effective way to improve the knowledge, skills, and performance of their employees. For that, it became essential to investigate the factors that affect the usage of these systems. Many researches have performed on the factors affecting e-learning systems in different sectors, but studies into e-learning systems for Oil and Gas industry is limited. In this study, the Oil and Gas sector is targeted since we have found the use of distance training and learning is projected to increase in this industry especially with current unprecedented circumstances and the lockdown that are associated with Coronavirus 2019 Disease (COVID-19). Human factors that influence e-learning systems for Oil and Gas companies are targeted and investigated. An investigation had conducted in order to gain insights into human factors. Questionnaires were collected from 76 employees from the field. The findings show that learner’s education, system interface, computer literacy, organization support, and teaching methods were identified as factors affecting e-learning systems. This research will play an essential role in helping oil and gas companies to develop and improve the use of their e-learning systems. © 2022 American Institute of Physics Inc.. All rights reserved.
