DCA-IoMT: Knowledge-Graph-Embedding-Enhanced Deep Collaborative Alert Recommendation Against COVID-19

Filtration to optimal exactness is mandatory since the options inundate the online world. Knowledge graph embedding is extraordinarily contributing to the recommendations, but the existing knowledge graph (KG)-based recommendation methods only exploit the correlations among the preferences and stand-alone entities, without bonding the cocurricular features and tendencies of the context. Additionally, the integration of the location-based current data of coronavirus disease 2019 (COVID-19) into the KG is necessary for the recommendation of region-aware precautionary alerts to the concerned people-an essential application of the current and future Internet of Medical Things. Therefore, in this article, we propose a novel deep collaborative alert recommendation (DCA) approach to cope with the situation. Particularly, DCA collects current online data about COVID-19, purifies, and transforms them to the KG. Furthermore, it independently encapsulates the cocurricular features and tendencies of the context in the embedding space and encodes them to the independent hidden factors via a graph neural network. The bi-end hidden factors are computed via matrix factorization to infer the potential connections. Moreover, a relevance estimator and a cross transistor are configured to enhance the generalization capability of the model. Experiments on two real-world datasets are performed to evaluate the effectiveness of DCA. Results and analysis show that the proposed approach has outperformed the baseline methods with fine improvements in providing the required recommendations.

COMPARISON OF EMOTIONAL STATUS AND QUALITY OF LIFE IN WOMEN WITH DIFFERENT PHYSICAL ACTIVITY LEVELS DURING COVID-19 PANDEMIC

Purpose: It was aimed to compare the effects of the coronavirus disease 19 (COVID-19) pandemic process on physically active and inactive women under general quarantine conditions. And second aim was to compare physical activity and general well-being in women who were employees and non-employees in a non-governmental organization. Methods: A total of 286 women were included in this study. The research was conducted online via the Google Forms web survey platform. The demographic information of the participants and non-governmental organization volunteering were asked before the questionnaires. Individuals' levels of physical activity were assessed by International Physical Activity Questionnaire-Short form (IPAQ), stress level was assessed The Distress Thermometer index, anxiety levels were assessed with Generalized Anxiety Disorder-7 (GAD-7), quality of life was evaluated with the World Health Organization Quality of Life-Bref questionnaire (WHOQOL-Bref). Results: It was found that physically inactive women had significantly higher anxiety and stress levels and lower quality of life (p<0.05). And women who were employees in a non-governmental organization had significantly higher physically activity level and lower anxiety and stress levels and better quality of life (p<0.05). Conclusion: Physical activity has an intensely positive effect on anxiety, stress, and quality of life during COVID-19 pandemic under general quarantine conditions.