CT Intensity Segmentation of Lungs

The early diagnosis and treatment of lung diseases is a very critical procedure and it requires the use of Computed Tomography (CT) imaging for the segmentation of lungs. Segmentation of the lung helps in the analysis of the lesions. The project proposes a CT lung and vessel segmentation model without any labels which is based on medical image processing using Python. This would assist the medical practitioners and scientists who are working in the field of CT intensity segmentation of lungs. It would make the diagnosis process easier and more convenient for patients, especially in pandemic situations like COVID. © 2022 IEEE.

Psychosocial Health, Family Life Satisfaction and Coping with Stress among Emerging Adults

The world at present is faced with Covid-19 pandemic subjecting billions to unprecedented changes, uncertainties and stressful challenges in life, especially among the youth. This study focuses on examining the Psychosocial health, Family life satisfaction and stress coping abilities of Emerging adults. A total of 280 participants in the age group of 18 to 25 years were procured through random sampling. Participants completed Duke Health profile, family life Satisfaction scale and coping with stress scale. Descriptive and inferential statistics were employed to analyze the sample data using SPSS version 26. Results revealed a positive relationship among psychosocial health and family life satisfaction and stress coping. However, family life satisfaction was not found related to stress coping among emerging adults. Gender differences were evident and regression analysis further revealed some crucial findings which are discussed in the main article along with the implications of the study. © The Electrochemical Society

Work and Family Conflict among Work from Home Employees during Covid-19 Pandemic

United Nation's Sustainable Development Goal No.3: Good Health and Wellbeing, ensures healthy lives through the promotion of well-being for all ages. Currently, the world is facing a global health crisis unlike any other due to the Covid-19 pandemic. The Pandemic is escalating human suffering, destabilizing the global economy, and upending the lives of billions of people around the globe. Due to pandemic, work from home is the only option for most of the employees in the Education and IT sectors. Due to this unexpected change in their work and family life, conflicts arise and they struggle to balance their work and family life. In this context, this study has attempted to examine the experience of Work-Family Conflict and the Family-Work Conflict among employees who work from home during the COVID-19 pandemic. An incidental sampling technique was utilized to collect the data using Google Form. Participants (N=223) responded to The Work and Family Conflict Scale (11 items), Wallach's Organizational Culture Index (15 items), Multi-Dimensional Scale of Perceived Social Support (12 items), scales. Results revealed that the work to family conflict factor had a negative relationship with social support and organizational culture as well as family to work conflict also had a negative association with the social support and organizational culture. organizational culture was positively related to social support. Multiple regression analysis revealed that 28% of the variance in organizational culture and social support is influenced by work and family conflict. 31% of the demographic variables was influenced by work and family conflict. The results and implications of this study are discussed in the main article. © The Electrochemical Society

Fuzzy Logic-Based Health Monitoring System for COVID'19 Patients

In several countries, the ageing population contour focuses on high healthcare costs and overloaded health care environments. Pervasive health care monitoring system can be a potential alternative, especially in the COVID-19 pandemic situation to help mitigate such problems by encouraging healthcare to transition from hospital-centred services to self-care, mobile care and home care. In this aspect, we propose a pervasive system to monitor the COVID'19 patient's conditions within the hospital and outside by monitoring their medical and psychological situation. It facilitates better healthcare assistance, especially for COVID'19 patients and quarantined people. It identifies the patient's medical and psychological condition based on the current context and activities using a fuzzy context-aware reasoning engine based model. Fuzzy reasoning engine makes decisions using linguistic rules based on inference mechanisms that support the patient condition identification. Linguistics rules are framed based on the fuzzy set attributes belong to different context types. The fuzzy semantic rules are used to identify the relationship among the attributes, and the reasoning engine is used to ensure precise real-time context interpretation and current evaluation of the situation. Outcomes are measured using a fuzzy logic-based context reasoning system under simulation. The results indicate the usefulness of monitoring the COVID'19 patients based on the current context.