COVID-19: Emergence of Mental Health Upheaval and Transition in Human Future Perspectives: A Qualitative Study

The outbreak of COVID-19 pandemic is constantly posing warning and creating mental health crisis among people without any discrimination. Therefore, the current study purpose is to explore mental health upheaval and transition in future perspectives due to COVID-19. Using exploratory study design, semi structure interviews were conducted. Interviews were recorded, transcribed and analyzed by using Thematic Content Analysis. The major themes which were identified showed that COVID-19 is constantly eliciting panic and mental health issues such as anxiety, stress, and depression, fears of death, xenophobia, OCD and uncertainty about future among general population. Results also indicated the major transition in public future perspectives and perception. Concern related to adjustability in life after pandemic is major emerging future concern among Pakistani People. During pandemic outbreak, people are becoming vulnerable to different mental health problems. To overcome these issues successfully, role of mental health professionals cannot be denied. There is strong need to devise activities and strategies which help people to increase resilience and build strong relationships during the period of social distancing. This paper gives a deep insight into mental health problems among general population due to COVID-19 and it also implicates need of psychological services to overcome these issues

PACA-ITS: A Multi-Agent System for Intelligent Virtual Laboratory Courses

This paper describes an intensive design leading to the implementation of an intelligent lab companion (ILC) agent for an intelligent virtual laboratory (IVL) platform. An IVL enables virtual labs (VL) to be used as online research laboratories, thereby facilitating and improving the analytical skills of students using agent technology. A multi-agent system enhances the capability of the learning system and solves students’ problems automatically. To ensure an exhaustive Agent Unified Modeling Language (AUML) design, identification of the agents’ types and responsibilities on well-organized AUML strategies is carried out. This work also traces the design challenge of IVL modeling and the ILC agent functionality of six basic agents: the practical coaching agent (PCA), practical dispatcher agent (PDA), practical interaction and coordination agent (PICA), practical expert agent (PEA), practical knowledge management agent (PKMA), and practical inspection agent (PIA). Furthermore, this modeling technique is compatible with ontology mapping based on an enabling technology using the Java Agent Development Framework (JADE), Cognitive Tutor Authoring Tools (CTAT), and Protégé platform integration. The potential Java Expert System Shell (Jess) programming implements the cognitive model algorithm criteria that are applied to measure progress through the CTAT for C++ programming concept task on IVL and successfully deployed on the TutorShop web server for evaluation. The results are estimated through the learning curve to assess the preceding knowledge, error rate, and performance profiler to engage cognitive Jess agent efficiency as well as practicable and active decisions to improve student learning