BACKGROUND: Strict strategies including lockdowns and working from home were adopted worldwide during the coronavirus (COVID-19) pandemic. University professors suddenly shifted to work from home adopting distance teaching. OBJECTIVES: This study aimed to investigate Health-Related Quality of Life (HRQoL) and its associated occupational and health factors during COVID-19 among university professors. METHODS: A cross-sectional design targeted university professors of all majors in Jordan. The study self-administered survey included demographics and lifestyle data, 12-item Short Form health survey (SF-12), Depression Anxiety Stress Scale (DASS 21), professor’ evaluation of distance teaching, Neck Disability Index (NDI), and International Physical Activity Questionnaire (IPAQ). Descriptive analyses were conducted to demonstrate primary outcome measures data. Factors associated with HRQoL were determined using a multiple variable linear regression analysis. RESULTS: A total of 299 university professors successfully completed the study. Participants’ SF-12 physical health component score was 74.08 (±18.5) and 65.74 (±21.4) for mental health component. Higher depression, stress, neck disability, and weight change were significantly associated with lower HRQoL level. While higher satisfaction with distance teaching, health self-evaluation, and work load change were significantly associated with higher HRQoL level. The regression model explained 66.7%of the variance in professors’ HRQoL (r2 = 0.667, F = 82.83, P < 0.001). CONCLUSIONS: Jordanian university professors demonstrated good HRQoL and mental health levels during COVID-19 lockdown. Factors associated with professors’ HRQoL should be considered by academic institutions in determining the best occupational setup of teaching activities in future pandemics.

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Traffic management in roads is one of the major challenges faced in developing efficient intelligent transportation systems. Recently, wireless networks have received significant attention for tackling this challenge. However, wireless technologies face the well-known spectrum scarcity problem due to the explosive demand for radio resources. To overcome this challenge, this study presents a novel intelligent traffic control system, utilising the unused spectrum. Unlike existing works, the spectrum owners in this study hire free spectrum to drivers. The hired spectrum is deployed to build a short-range cost-effective wireless communication for monitoring traffic and enabling drivers to exchange warning messages, and thus enhancing road safety. Our objectives include minimizing crash probability, utilizing unused spectrum, and enabling spectrum owners to generate extra revenue. Numerical analysis demonstrates the capability of our approach to minimize the crash probability among vehicles under different operating road conditions.

In Wireless Sensor Network (WSN) applications it is critical to accurately determine the location of the distributed sensor nodes in order to report the data that is geographically meaningful. Since localization and tracking algorithms have been attracting research and development attention recently, a wide range of existing approaches regarding this topic have emerged. Tracking and localization algorithms have been proposed for different WSN applications including civilian, industrial and safety applications. A few research studies focused on tracking Threats through military applications, such as detecting and tracking Threats through border security area. Therefore this paper studies and investigates the existing WSN based tracking and localization algorithms and summarizes the potential requirements for localizing and tracking Threats through military applications. The existing systems are categorized and discussed. A critical analysis is found in this paper, in order to guide the developer to design and implement a WSN-based tracking system for military applications.