ABSTRACT
Neurofeedback (NF) is a scientific method that alters the brain states to improve mental disorders. Neurofeedback can perform through Brain-Computer Interface (BCI) which involves hardware, and software to communicate with the outside environment using the brain's thoughts. Coronavirus disease (COVID-19) has shown a substantial influence on mental health symptoms because individuals are working from home (WFH). However, A brain condition known as Mental Fatigue (MF) is induced by continuous cognitive work and lowers mental attentiveness as well as negatively affects performance. There are different approaches to address different mental states and Neurofeedback strategies to change mental states. Thus, Neurofeedback can be an Intervention technique to reduce mental fatigue and improve cognitive task performance. Furthermore, it is proven by researchers that Machine Learning Technique can successfully detect Mental Fatigue through electroencephalography (EEG). Currently, there is no BCI that integrated Mental Fatigue detection and applies Neurofeedback strategies to reduce Mental Fatigue. This review identified a neurofeedback process that includes signal acquisition, signal pre-processing, feature extraction, classification and generation of feedback signals. This review aims to develop a general architecture of mental fatigue intervention through BCI. © 2022 IEEE.
ABSTRACT
Since the beginning of the Covid-19 pandemic, big data analytics (BDA) remains a signatory medium in the battle against it. Governments and policymakers alike are yet to leverage on this scalable technology in an attempt to curb the economic effects of Covid-19. The primary objective of this study is to leverage on BDA to identify economic shocks, and propose a strategic solution for economic recovery in ASEAN member states (AMS). The findings of this study suggest that BDA techniques, frameworks, and architectures are effective tools in predicting and tracking economic shocks, as well as in designing and implementing an effective economic recovery plan. This study proposes a guideline to governments and policymakers scrambling for resources and considering different options to start an economic recovery process. Our findings draw a roadmap for complex AMS economies struggling to explore options for economic recovery in the response of Covid-19. This study has extended and confirmed the knowledge and perception about harnessing BDA as a tool as well as proposed a scientific approach to design economic policies. The findings outlined in this study contribute to the pipeline of BDA's theoretical frameworks which is expected to strengthen its novelty in data science.
ABSTRACT
The outbreak of Covid-19 is the second most devastating event over a century. The pandemic, alongside deep health crises, has ushered the largest economic shocks, which require governments’ attention to ameliorate to avoid an economic downturn. The aim of this study is to measure the economic impacts of Covid-19 in Brunei by estimating the exposure, vulnerability, and resilience of the economy. This study deployed the United Nations Disaster Risk Reduction framework to examine the economic impact empirically. The data related to variables of gross domestic product, oil prices, international merchandise trade, tourism, unemployment, consumer price index, money supply, and national accounts were collected from September 2019 to July 2020 and analyzed through the fixed effects panel regression technique. The findings show that the news of the Covid-19 outbreak has exposed the weaknesses in energy sectors by having a significant negative impact. Additionally, analysis discloses that the energy and tourism sectors are vulnerable to the shocks of Covid-19. During the peak of the pandemic outbreak, unemployment in Brunei has also escalated. Additionally, the energy and tourism sectors are less resilient to pandemic shocks. The findings indicated that the consumer price index has significantly escalated during the economic recovery process. The findings elucidate that the overall GDP growth rate, international merchandise trade, and the financial sector continue exhibiting better performance amid Covid-19. The findings of this study contribute to developing policy implications for the emerging economies concerned with the economic recovery process during the pandemic. © Hakimah Yaacob, Qaisar Ali, Nur Anissa Sarbini, Abdul Nasir Rani, Zaki Zaini, 2021