Machine Learning and Deep Learning based Stock Market Prediction considering Covid-19 as a Feature

India's capital markets are witnessing intense uncertainty due to global market failures. Since the outbreak of COVID-19, risk asset prices have plummeted sharply. Risk assets declined half or more compared to the losses in 2008 and 2009. The high volatility is likely to continue in the short term;as a result, the Indian markets have declined sharply. In this paper, we have used different algorithms such as Gated Recurrent Unit, Long Short-Term Memory, Support Vector Regressor, Decision Tree, Random Forest, Lasso Regression, Ridge Regression, Bayesian Ridge Regression, Gradient Boost, and Stochastic Gradient Descent Algorithm to predict financial markets based on historical data available along with economic and financial features during this pandemic. According to our findings, deep learning models can accurately estimate financial indexes by utilizing non-linear transaction data. We found that the Gated Recurrent Unit performs better than the existing model. © 2023 IEEE.

Assessing the Impact of COVID-19 on Urban Socio-economic Vulnerability and Wellbeing for Integrated Planning: A Quantitative Enquiry in the Katwa Municipality, West Bengal

The present study focuses on the quantitative investigation of economic vulnerability and assesses the perception survey carried out among 75 residents of Katwa Municipality, an up-growing urban area in Purba Barddhaman District, West Bengal. To estimate the socio-economic vulnerability during the lockdown, standardised factor scores have been calculated in the analysis of principal components and GIS-based mapping has been employed also. Among the total working population of the surveyed household, about 20% have changed their occupation, wages have been reduced by 35 and 35% have lost their occupation during the lockdown period. The highly socio-economic vulnerability has been observed in the wards where households and population are also high. The regression coefficient shows that the increasing trend of marginal other workers has the significantly (p < 0.1) highest marginal effect on the socio-economic vulnerability. The Likert scale measuring perception indicated that the majority of the respondents agreed with their socio-economic vulnerabilities caused by lockdown during the pandemic situation. The significant outcome of the study indicates the initiation of diversified income generation opportunities and deliberates its contribution to the formation of location-specific planning for the socio-economic development and integrative management of the study area. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Exploring the art of medical photography - an otolaryngologist's perspective.

BACKGROUND: Modern day otolaryngology has expanded beyond the ear, nose and throat to include head and neck surgery and aesthetic facial procedures. Photographic documentation is important within this expanded horizon. The spectrum of clinical photography includes photomicrographs, endoscopic photographs, peri-operative photography and medical social photography. METHOD: This article aimed to review the standard guidelines essential to obtain, store and disseminate photographs and looked at setting up a small clinic with minimal gadgets to suit clinical photography requirements. Elaboration of basic photography techniques in otolaryngology was reviewed, with examples of photographs taken in a clinic by a clinician. Advances and innovation in clinical photography, in the form of smartphone photography, artificial intelligence, device editing and newer hardware and software in otorhinolaryngology was reviewed. CONCLUSION: Having a professional photographer to aid a clinician is a luxury. Simple knowledge and regular practice of basic photography guidelines by a clinician is imperative.

Is the pandemic masking waste management?–A review on fallout of the COVID-19 viral contagion

The global outbreak of SARS-CoV-2 has spurred a reassessment of Municipal Solid Waste management strategies and approaches. A significant need for sanitation and hygiene was accentuated for disease prevention and control with the onset of the pandemic. With an alteration of the status quo in waste management system, an unprecedented amount of face masks, protective equipment, and other biological wastes was generated in the form of Municipal Solid Waste. This upsurge of potentially infected wastes originated a risk of transmission amongst frontline workers. Furthermore, the potential contamination of Municipal Solid Waste was rendered as a legitimate threat due to improper collection practices, disposal and handling of solid waste. Several novel waste disposal techniques and waste management policies were also introduced during this period. However, the sanitation-policy making-occupational safety nexus remains inadequately explored under the prevalent COVID-19 scenario. Through the prism of shifting waste composition, this review offers a global assessment of existing solid waste management systems during the COVID-19 pandemic. The physiological and psychological hazards faced by the frontline workers were explored and instances of best-case and worst-case policies on solid waste handling were recorded. Modern methods of waste disposal and latest trends of policymaking were evaluated. A model study of unsupervised learning via Partition Around Medoids cluster analysis was undertaken to reveal underlying patterns of waste management policies. Although, the clusters were formed devoid of any socio-economic parameters, this study strives to indicate proof of concept and can serve as a precursor to advanced clustering studies. © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.