With the popularity of location-based social networks, location prediction has become an important task and has gained significant attention in recent years. However, how to use massive trajectory data and spatial-temporal context information effectively to mine the user’s mobility pattern and predict the users’ next location is still unresolved. In this paper, we propose a novel network named STSAN, which can integrate spatial-temporal information with the self-attention for location prediction. In STSAN, we design a trajectory attention module to learn users’ (...) dynamic trajectory representation, which includes three modules: location attention, which captures the location sequential transitions with self-attention; spatial attention, which captures user’s preference for geographic location; and temporal attention, which captures the user temporal activity preference. Finally, extensive experiments on four real-world check-ins datasets are designed to verify the effectiveness of our proposed method. Experimental results show that spatial-temporal information can effectively improve the performance of the model. Our method STSAN gains about 39.8% Acc@1 and 4.4% APR improvements against the strongest baseline on New York City dataset. (shrink)

This paper analyzes the impact of the COVID-19 pandemic on the mental health of the teachers, specifically the techno stress arising in them as a result of issues faced by them in the use of technology when they conduct the online academic activities. It aims to assess the major factors related to the online teaching that specifically adds to techno stress on the teachers during the COVID-19 outbreak. Finally, the study aims to provide suggestions to the policymakers and the management (...) of the universities so that the effect of the COVID-19's on teachers' mental health and the related techno stress can be reduced. This paper is a literature review of the articles on the notion of techno stress on teachers and their mental health by searching the related articles with these terminologies using the renowned search engines of Google Scholar and Web of Science. A combination of the terms such as Coronavirus, COVID-19, mental health, psychological distress, techno stress, and online teaching were used in the article search for the review. The literature has suggested that the COVID-19 outbreak has significantly affected the mental health of the employees in general and specifically, the teachers who are engaged in online academic activities and teaching in the universities. The paper has identified a few factors that are the cause of the techno stress and provides recommendations for the university management and the policy makers for minimizing their negative impact on the teachers, in terms of the techno stress and their mental health. Coronavirus is a new strain of the viruses that has badly engulfed the entire population of the world. It is even now badly rising and causing deaths while this article is in the writing phase. The article has addressed the mental health concerns of the university teachers as they are now working from home using ICT for delivering the lectures and conducting the online teaching and learning activities for the students at their universities. This is a matter of grave importance now and requires immediate attention. Hence, this article broadens the scope of the research on the corona virus and its impact on the university teachers. (shrink)