Survey on highly imbalanced multi-class data

Machine learning technology has a massive impact on society because it offers solutions to solve many complicated problems like classification, clustering analysis, and predictions, especially during the COVID-19 pandemic. Data distribution in machine learning has been an essential aspect in providing unbiased solutions. From the earliest literatures published on highly imbalanced data until recently, machine learning research has focused mostly on binary classification data problems. Research on highly imbalanced multi-class data is still greatly unexplored when the need for better analysis and predictions in handling Big Data is required. This study focuses on reviews related to the models or techniques in handling highly imbalanced multi-class data, along with their strengths and weaknesses and related domains. Furthermore, the paper uses the statistical method to explore a case study with a severely imbalanced dataset. This article aims to (1) understand the trend of highly imbalanced multi-class data through analysis of related literatures; (2) analyze the previous and current methods of handling highly imbalanced multi-class data; (3) construct a framework of highly imbalanced multi-class data. The chosen highly imbalanced multi-class dataset analysis will also be performed and adapted to the current methods or techniques in machine learning, followed by discussions on open challenges and the future direction of highly imbalanced multi-class data. Finally, for highly imbalanced multi-class data, this paper presents a novel framework. We hope this research can provide insights on the potential development of better methods or techniques to handle and manipulate highly imbalanced multi-class data

Coronaviruses Research in BRICS Countries

SARS-CoV-2 has infected more than 105 million people worldwide. During this pandemic, researchers and clinicians have been working to understand the molecular mechanisms that underpin viral pathogenesis by studying viral–host interactions. Now, with the global rollout of various COVID-19 vaccines—based on the neutralization of the spike protein using different technologies—viral immunology and cell-based immunity are being investigated. Researchers are also studying how various SARS-CoV-2 genetic mutations will impact the efficacy of these COVID-19 vaccines. At the same time, various antiviral drugs have been identified or repurposed that have potential as anti-SARS-CoV-2 treatments. BRICS (Brazil, Russia, India, China, and South Africa) is the acronym used to associate five major emerging national economies. The BRICS countries are known for their significant influence on regional affairs, including being leaders in scientific and clinical research and innovation. This Special Issue includes researchers from BRICS countries, in particular South Africa, involved in the study of SARS-CoV-2 and COVID-19. Original articles, as well as new perspectives or reviews on the matter, were welcomed. Research in the fields of vaccine studies, pathogenesis, genetic mutations, viral immunology, and antiviral drugs were especially encouraged