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E-learning During COVID-19Challenges and Opportunities of the Education Institutions
As part of the COVID-19 lockdown, educational institutions were closed and adopted e-learning to keep the learning process going. Due to the COVID-19 pandemic, e-learning has become a required component of all educational institutions such as schools, colleges, and universities worldwide. This pandemic has thrown the offline teaching process into chaos. This chapter discusses the concept and role of e-learning during the pandemic and various challenges and opportunities of e-learning encountered by educational institutions. Three broad challenges identified in e-learning are inaccessibility, self-inefficacy, and technical incompetency. E-learning opportunities are no geographic barriers, flexibility, creativity, and critical learning incorporation increased utilization of online resources and reinforced distance learning. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Identification of new classical Ae stars in the Galaxy using LAMOST DR5
We report the first systematic study to identify and characterize a sample of classical Ae stars in the Galaxy. The spectra of these stars were retrieved from the A-star catalogue using the Large sky Area Multi-Object fibre Spectroscopic Telescope (LAMOST) survey. We identified the emission-line stars in this catalogue from which 159 are confirmed as classical Ae stars. This increases the sample of known classical Ae stars by about nine times from the previously identified 21 stars. The evolutionary phase of classical Ae stars in this study is confirmed from the relatively small mid- and far-infrared excess and from their location in the optical colour-magnitude diagram. We estimated the spectral type using MILES spectral templates and identified classical Ae stars beyond A3, for the first time. The prominent emission lines in the spectra within the wavelength range 3700-9000 are identified and compared with the features present in classical Be stars. The H ? emission strength of the stars in our sample show a steady decrease from late-B type to Ae stars, suggesting that the disc size may be dependent on the spectral type. Interestingly, we noticed emission lines of Fe ii, O i, and Paschen series in the spectrum of some classical Ae stars. These lines are supposed to fade out by late B-type and should not be present in Ae stars. Further studies, including spectra with better resolution, is needed to correlate these results with the rotation rates of classical Ae stars. 2021 2020 The Author(s) Published by Oxford University Press on behalf of Royal Astronomical Society. -
COVID-19 Pandemic: Review on Emerging Technology Involvement with Cloud Computing
Cloud computing is the latest technology that has a significant influence on everyones life. During the COVID-19 crisis, cloud computing aids cooperation, communication, and vital Internet services. The pandemic situation made the people switch to online mode. The technology helped to bridge the gap between the work space and personal space. A quick evaluation of cloud computing services to health care is conducted through this study in COVID situation. A short overview on how cloud computing technologies are critical for addressing the current predicament has been held. The paper also discusses distant working of cloud computing in health care. Moreover, cloud infrastructure provides a way to connect with different aid personnel. The patient data can be transferred to the cloud for monitoring, surveillance, and diagnosis. Thus, health care is provided instantaneously to all the individuals. Additionally, the study addresses the privacy and security-related issues with appropriate solutions. The paper also briefs on the different kind of services are provided by different CSPs that are cloud service providers to confront this epidemic. This article primarily focuses on cloud computing technology involvement in COVID, and secondary focus is on other technology like blockchain, drones, machine learning and Internet of things in COVID-19. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Analytical Methods of Machine Learning Model for E-Commerce Sales Analysis and Prediction
In the commercial market, E-commerce sales show a significant trend and have attracted many consumers. Ecommerce sales forecasting has a significant role in an organization's growth and aids in improved operation. Many studies have been conducted in the past using statistical, fundamental, and data mining techniques for better analysis and prediction of sales. However, the current scenario calls for a better study that combines the available information to propose different machine-learning techniques. The sole motive of the study is to analyze and determine different machine learning models to predict accurate results. The research observed that the Extreme Gradient Boosting model outperformed all other models and brought a good result. It produced an RMSE value of 0.0004 and Explained Variance score of 0.99. Decision Tree algorithm also shows an exemplary result. 2023 IEEE. -
An Efficient Machine Learning Framework for Flood Forecasting
Floods, a significant natural disaster which has an impact on the whole world present major risks to ecosystems and humans, particularly in semi-arid areas with variable rainfall patterns. With the help of ICRISATs historical meteorological data and machine learning algorithms, this study has developed a customized flood prediction model for use. After evaluating and contrasting various models, including the proposed model Stacked Gradient Boosting with Random Forest (SGB-RAF), KNN, Decision Tree, Random Forest, and Linear Regression, it shows that SGB-RAF has the highest R2 score and lowest RMSE comparatively to other models. While other enhancements such as Ridge Regression and polynomial feature creation were studied, SGB-RAF remained effective. Overall, this study highlights how machine learning may improve flood prediction accuracy, which is important for disaster management and for improving the semi-arid regions adaptability to climatic variability. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
Maximum Decision Support Regression-Based Advance Secure Data Encrypt Transmission for Healthcare Data Sharing in the Cloud Computing
The recent growth of cloud computing has led to most companies storing their data in the cloud and sharing it efficiently with authorized users. Health care is one of the initiatives to adopt cloud computing for services. Both patients and healthcare providers need to have access to patient health information. Healthcare data must be shared and maintained more securely. While transmitting health data from sender to receiver through intermediate nodes, intruders can create falsified data at intermediate nodes. Therefore, security is a primary concern when sharing sensitive medical data. It is thus challenging to share sensitive data in the cloud because of limitations in resource availability and concerns about data privacy. Healthcare records struggle to meet the needs of security, privacy, and other regulatory constraints. To address these difficulties, this novel proposes a machine learning-based Maximum Decision Support Regression (MDSR)-based Advanced Secure Data Encrypt Transmission (ASDET) approach for efficient data communication in cloud storage. Initially, the proposed method analyzed the node's trust, energy, delay, and mobility using Node Efficiency Hit Rate (NEHR) method. Then identify the efficient route using an Efficient Spider Optimization Scheme (ESOS) for healthcare data sharing. After that, MDSR analyzes the malicious node for efficient data transmission in the cloud. The proposed Advanced Secure Data Encrypt Transmission (ASDET) algorithm is used to encrypt the data. ASDET achieved 92% in security performance. The proposed simulation result produces better performance compared with PPDT and FAHP methods. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Analysis of nonlinear convection and diffusion in viscoelastic fluid flow with variable thermal conductivity and thermal radiations
The study offers a thorough evaluation of the complex fluid dynamics and heat transfer phenomena in Williamson viscoelastic fluid flow, taking into account thermal radiations and variable thermal conductivity. The paper extends its analysis to include heat transfer effects, which are critical in several engineering and industrial applications, and digs into the complexity of non-Newtonian fluid behavior, with a special focus on thermal radiation, heat production, diffusion and viscous dissipation. The study makes use of mathematical models and numerical method RK4 to clarify the nonlinear interactions between convection and diffusion processes in this viscoelastic fluid. The energy and concentration equations are simulated in the presence of the modified Fourier and Fick laws. Moreover, the predicted heat flow is based on the Cattaneo-Christov theory. This research also sheds light on the interaction between rheological properties and thermal characteristics, providing important new knowledge to the broader field of fluid dynamics and heat transfer. 2024 World Scientific Publishing Company. -
Clay-based cementitious nanofluid flow subjected to Newtonian heating
In recent years, a novel technique for producing robust cementitious materials, called nanocomposites, has emerged. These materials are comprised of clay minerals and polymers. As a result, a vertical flat plate has been used to evaluate a clay-based cementitious nanofluid in this research. The impacts of first-order chemical reactions, heat generation/heat absorption, and the Jeffrey fluid model are taken into account for the study of flow. Newtonian heating and the conditions for slippage velocity have also been considered. The mathematical problem for the flow analysis has been established in relations of partially coupled partial differential equations and the model has been generalized using constant proportional Caputo (CPC) fractional derivative. The problem is solved using the Laplace transform technique to provide precise analytical solutions. On the concentration, temperature, and velocity fields, the physics of a number of crucial flow parameters have been examined graphically. The acquired results have been condensed to a very well-known published work to verify the validity of the current work. It is important to note here that the rate of heat transfer in the fluid decreases by 10.17% by adding clay nanoparticles, while the rate of mass transfer decrease by 1.31% when the value of ? reaches 0.04. 2023 World Scientific Publishing Company. -
MHD nanofluid flow through Darcy medium with thermal radiation and heat source
In this analysis, we have considered heat transmission in two-dimensional steady laminar nanouid ow past a wedge. Magnetohydrodynamic (MHD), Brownian motion, viscous dissipation and thermophoresis eects are considered over the porous surface. Similarity transformations have been used to change the governing partial dierential equations (PDEs) into nonlinear higher-order ordinary dierential equations (ODEs). Governing ODEs with boundary conditions are then converted to the system of first-order initial value problem. After that the modeled system is solved numerically by RK4 technique. Impact of the magnetic number, Eckert number, Prandtl number, Lewis number, Brownian motion, thermophoresis and permeability parameters on the ow domain is analyzed graphically as well as in tabular form. It is noted that magnitude of Nusselt number for the ow regime increases with the increase of nondimensional parameter Pr; Nb; Nt while opposite behavior is observed in case of R. World Scientific Publishing Company. -
Heat Convection in a Viscoelastic Nanofluid Flow: A Memory DescriptiveModel
Modeling of physical phenomena with fractional differential equations is as old as modeling with ordinary differential equations. There are two stages in modeling of a memory process. One of them is short with persistent impact and other is usually governed by fractional mathematical model. It is established that fractional models fit the experimental data for the memory phenomena in better way when compared with the ordinary models, particularly in mechanics, psychology and in biology. Fractional model of viscoelastic nanofluid flow through permeable medium is studied in this communication. Convection parameters in the flow domain are used to account for buoyancy forces. The governing flow equations are computed using a numerical algorithm that combines finite difference and finite element techniques. The governing models friction coefficient, Sherwood numbers, and Nusselt numbers are calculated. Change in noninteger numbers behave similarly in concentration, temperature, and velocity fields, according to simulations. It is also noted that heat flux, ?1 and mass flux, ?2 numbers have contradictory effects on friction coefficient. Various flow patterns, particularly in the polymer industry and electrospinning for nanofiber manufacture, can be addressed in a similar manner 2023 L&H Scientific Publishing, LLC. All rights reserved -
A clinical study of hepatitis B
The spread of Hepatitis B, which is a severe and enduring disease that origins from its virus is a vital universal issue. It is assessed that about 70 crore people around the globe are enduring HBV transporters. The medical range of HBV virus series starting with subclinical to severe suggestive hepatitis or, hardly, hazardous hepatitis during the severe point and from the quiet hepatitis B external antigen (HBsAg) transporter state, enduring hepatitis of numerous grades of histologic sternness to cirrhosis and its difficulties during the enduring point. In this research paper, we witness medication, signs, and consequence of Hepatitis B. 2019 by Advance Scientific Research. -
Cloud security based attack detection using transductive learning integrated with Hidden Markov Model
In recent years, organizations and enterprises put huge attention on their network security. The attackers were able to influence vulnerabilities for the configuration of the network through the network. Zero-day (0-day) is defined as vulnerable software or application that is either defined by the vendor or not patched by any vendor of organization. When zero-day attack is identified within the network there is no proper mechanism when observed. To mitigate challenges related to the zero-day attack, this paper presented HMM_TDL, a deep learning model for detection and prevention of attack in the cloud platform. The presented model is carried out in three phases like at first, Hidden Markov Model (HMM) is incorporated for the detection of attacks. With the derived HMM model, hyper alerts are transmitted to the database for attack prevention. In the second stage, a transductive deep learning model with k-medoids clustering is adopted for attack identification. With k-medoids clustering, soft labels are assigned for attack and data and update to the database. In the last phase, with computed HMM_TDL database is updated with computed trust value for attack prevention within the cloud. 2022 -
STRATEGIC PARTNERSHIPS AND REGIONAL RESILIENCE: Exploring the Evolving Landscape of India-Southeast Asia Relations
India and Southeast Asia share an elusive sphere of influence, yet face formidable challenges in realising ambitious goals set for the region. Over the years, Indias foreign policy has progressed from being principled to goal driven and objective oriented. Based on analysis of secondary sources of literature, this chapter traces through the relationship between India and Southeast Asia, highlighting a shared landscape of experiences, weaving socio-cultural practices and further boosting economic and international relations. These historical references have found avenues for remodelling in contemporary times in the form of diplomatic success in varied dimensions of engagements. Drawing from these developments and taking the transformations in the geopolitics of Indo-Pacific region into cognizance, this chapter envisions the future prospects for India and Southeast Asia through the lens of building community resilience, promoting its potential to guide regional development and explore the sustainability of social, economic and environmental systems to manage change. This renewed line of thought supports a new analytic of governance which advocates that the local define the configurations and prospects for sustainability of policy frameworks and agreements in the global system. Thus, in the background of the rising traditional and non-traditional challenges, this chapter contributes to a better understanding of change and complexity through a revitalised scope for coordination, cooperation and pragmatism in partnership between the countries. 2024 Taylor & Francis. -
Understanding the social identity of adolescents in the Indigenous Kodava Community of India
The social identity development of adolescents in marginalized communities across the globe holds paramount significance in determining the overall well-being of its future population. Focusing on one such community, the Kodavas, an Indigenous community in South India, this study aims to understand the shifting configurations of social identity based on the changing sociocultural structure and its implications on identity perception among the adolescents belonging to the Kodava community in Kodagu district in Karnataka, India. This study used a qualitative research design to develop an analytical framework of social identity formation and its transitions in the context of the Kodavas. Data were collected from 188 adolescents (47% boys, 53% girls) between 13 and 17 years (M age = 15 years), in the form of essay writing. The findings based on thematic analysis highlight the core traditional elements of Kodava identity, factors influencing the transition in identity, and its reflection in the contemporary period. 2024 Society for Research on Adolescence. -
Rumination, existential anxiety and professional quality of life among palliative care professionals in India
Objective: Palliative care enhances the quality of life for individuals with life-limiting illnesses, but frequent exposure to death and suffering poses emotional challenges for professionals. This study examines ruminations role in the relationship between existential anxiety (EA) and professional quality of life (ProQOL) among palliative care professionals in India. Methods: A mixed-method research design was employed. Quantitative data were collected from 500 palliative care professionals using the Event-Related Rumination Inventory, EA Questionnaire and ProQOL scale. In-depth interviews were conducted with 27 professionals with high rumination scores. Correlation and regression analyses were used for quantitative data, while thematic analysis was applied to qualitative data. Results: Persistent rumination heightened mortality awareness, exacerbated EA and negatively impacted ProQOL. Rumination partially mediated the relationship between EA and ProQOL. Four key themes emerged: (1) brooding rumination, (2) reflective rumination, (3) impact of rumination on ProQOL and (4) impact of rumination on EA. Individual differences in ruminations intensity and duration were notable. Conclusions: Findings highlight cultural and contextual challenges faced by Indian palliative care professionals, underscoring the need for targeted mental health interventions. This study supports Sustainable Development Goals 3, 8 and 4 by advocating for healthcare worker well-being, job satisfaction and improved mental health training. Author(s) (or their employer(s)) 2026. No commercial re-use. See rights and permissions. Published by BMJ Group. -
Early life adversity: Impact on the neuroimmune network and long-term health outcomes
A life that begins in a healthy environment is a precursor to the evolution of a beautiful narrative. In its course, adversities can manifest in various forms ranging from psychosocial factors to environmental toxins. The current understanding of these adverse events is largely limited to a unidimensional perspective. However, it is to be noted that the nature of the impact is not isolated, but interconnected, also emphasizing the neurobehavioral effects caused by the combination of different types of adversities in varied contexts and time frames. Hence, this chapter investigates the cumulative/interactive effect of early life adversity on the neuroimmune network and its long-term consequences to health. It proposes that by fostering environments where children are more likely to develop in healthy, supportive settings, we can create a foundation for social change, leading to physically, psychologically and socially healthier communities. Such a development would contribute to individual well-being, with a potential to create healthy and resilient societies. 2025 by IGI Global Scientific Publishing. All rights reserved. -
Understanding the Experiences and Impact of Secondary Trauma and Moral Injury on the Professional Identity of Mental Health Professionals in India
Mental health professionals often encounter emotional and ethical challenges, including exposure to client trauma and complex ethical dilemmas. These situations can lead to secondary trauma and moral injury. This study examines the factors contributing to secondary trauma and moral injury and their impact on the professional identity of mental health professionals in India. A purposeful sample of 30 professionals, composed of psychiatrists, clinical psychologists, and psychiatric social workers, participated in semi-structured interviews. Qualitative thematic analysis identified four key themes: vulnerabilities and emotional exposure, ethical complexities and responsibilities, balancing integrity with emotional strain, and resilience and professional growth. These qualitative themes underscore the significant challenges faced by mental health professionals in India, including emotional strain, systemic barriers, and ethical conflicts, while highlighting strategies such as coping mechanisms, professional development, and support systems to address these issues. This study provides practical recommendations for interventions aimed at addressing secondary trauma and moral injury, fostering resilience, and strengthening the professionals identity and overall well-being of professionals within the Indian context. 2025 Taylor & Francis Group, LLC. -
The behaviour of macro and micro economic variables and the impact on systematic risk of non-banking finance companies
The reforms initiated by the Government of India during 1990s have brought fundamental changes in the structure and functioning of Banking and Non-Banking Institutions, their business models and the products and services offered by them. Global economic developments have altered the macro economic conditions of the respective nations and make the nations and their economies vulnerable to economic shocks in the form of systematic risk associated with their business activities. Macro-economic factors and micro economic factors have had effect on the risk level, assessing risk, measuring and managing risk has become paramount for Non-Banking financial Institutions. Individual influence of factors on the systematic risk as there is weak relationship with Beta but combined effect of factors is very positive on the systematic risk of the companies. Indian Institute of Finance. -
Initial public offerings and performance evaluation: Evidence from the Indian capital market /
International Journal of Economics And Financial Issues, Vol.8, Issue 5, pp.59-63, ISSN No:2146-4138. -
Markov analysis of unmanned cryogenic nitrogen plant with standby system
The unmanned cryogenic nitrogen plants operated by the industrial gas companies globally have their unique set of Reliability, Availability and Maintainability challenges. A generic reliability model of a typical unmanned cryogenic nitrogen plant is presented in this research work along with standby cryogenic storage System. The standby system is analysed for sensing and switching device as well as for load sharing system. The complexities of unmanned cryogenic nitrogen plant under repair with standby system are analysed using Markov method. A Markovian model has been developed for two different configurations: Configuration-1: Cryogenic nitrogen plant with gas and liquid production, nitrogen plant with only gas production and its dependence on the standby cryogenic storage system and to overall system reliability. Configuration-2: Considering cryogenic nitrogen plant is under repair and the standby system with external supply component under operation without failure and the system reliability of the configurations are solved by solving the set of differential equations and the solutions are presented in this paper. 2020 Author(s).