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Academic stress and its sources among university students
Stress has become part of students' academic life due to the various internal and external expectations placed upon their shoulders. Adolescents are particularly vulnerable to the problems associated with academic stress as transitions occur at an individual and social level. It therefore, becomes imperative to understand the sources and impact of academic stress in order to derive adequate and efficient intervention strategies. The study employed a quantitative research design where participants were screened using Academic Stress Scale (Rajendran& Kaliappan,1991 from four streams namely, commerce, management, humanities, and basic sciences. The five dimensions of sources such as personal inadequacy, fear of failure, interpersonal difficulties with teachers, teacher pupil relationship and inadequate study facilities were further analysed and gender differences were also obtained. Understanding the sources of stress would facilitate the development of effective counselling modules and intervention strategies by school psychologists and counsellors in order to help students alleviate stress. Published by Oriental Scientific Publishing Company 2018. -
Child Mental Health in the Milieu of Online Education
The aim of this chapter is to examine the impact of online education on mental health of children, and explore methods to improve the same. With the advent of COVID-19 pandemic, major overhauls were made in day-to-day life including work, home, and education. Shift to online mode of instruction became the primary, if not the only, channel of education. This drastic shift has led to issues like limited social interaction, learning gaps due to insufficient in-person interaction, excessive screen time on devices, and decreased physical activity, which can impact mental health of children. This chapter will explore the impact of online learning on the mental health of children from both mental ill-health and well-being perspectives, the role of parents, teachers, and educational systems, and challenges and opportunities presented by the situation. Further to this, the ways to safeguard and improve mental health of children in the milieu of online education will be discussed. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022. -
Contextual Recommendation System: A Revolutionary Approach Using Hadoop, Spark, NLP and LLMs
This study presents a novel framework for contextual recommendations on platforms like Wikipedia, integrating Hadoop, Spark, NLP, and LLMs. Leveraging these technologies, the framework aims to enhance user experiences by delivering personalized article suggestions aligned with their current interests. Through scalable data processing, advanced NLP techniques, and LLM-powered semantic understanding, the framework offers a transformative approach to recommendation systems, promising to revolutionize knowledge exploration on digital platforms. 2024 IEEE. -
One-pot hydrothermal synthesis of 3D garland BiOI, spherical ZnO, and CNFs onto Ni foam: Supercapacitor performance with enhanced electrochemical properties
This study reported one-pot hydrothermal synthesis of 3D garland BiOI, spherical ZnO, and carbon nanofibers (CNFs) onto Ni foam substrate with improved supercapacitor performance and enhanced electrochemical properties. The synthesized nanocomposites exhibited high specific capacitance (SC) of 1073 g?1 at a current density of 1 A/g and excellent cycling stability with 88.6% retention of original capacity after 5000 cycles in 2M KOH aqueous solution. The findings highlight the potential of 3D materials for use as electrode materials in advanced supercapacitor applications due to their high energy storage capabilities. 2024 Elsevier Ltd -
Ethnic Food: The Food Way Forward
In the context of food security, two things are significant. To ensure availability, affordability and accessibility of adequate food to people throughout the country. Also, to promote entrepreneurship for sustainable food production and supply. This paper highlights differences between food security and food insecurity. The global population in 2050 is predicted at 9 billion in which case the output must double considering the dwindling and degrading resources. This may be a challenge for agronomists and policy-makers. Considering that food security must be achieved at individual, household, district, national and global levels, India may need an Integrated Farming System (IFS) to take agriculture further. There are numerous challenges besides the environment that must be considered for this. It is important to ensure that the dignity of the farmer is not compromised while strategizing food security. Currently, private-public partnerships are being introduced in some places as a potential model. However, all stakeholders in food security have their task cut out (1). This paper is a review of existing literature to understand the level of information we have documented. It tries to highlight ways in which consumption of ethnic food could be a way forward in terms of food security and sustainability. The Electrochemical Society -
Image and signal processing in the underwater environment
To handle submerged action recognition, researchers must first understand the fundamental principles of photonic crystals mostly in the liquid phase. Deterioration effects are produced by the mediums physical attributes, which are not present in typical pictures captured in the air because light is increasingly reduced as it passes through water, submarine pictures are characterized by low readability. As a consequence, the sceneries are poorly contrasting and murky. Its vision capability is limited to approximately twenty meters in clear blue water and five meters or less in muddy water due to light dispersion. Absorbing (the removal of incident light) and dispersion are the two factors that produce light degradation. So the actual quality of submersible digital imaging is influenced by the destructive interference processes of light in water. Longitudinal scattered (haphazardly diverted light traveling from objects to the cameras) causes picture details to be blurred. 2021, SciTechnol, All Rights Reserved. -
Did the Economic Reforms Change the Macroeconomic Drivers of the Indian Economy in the Post-Reform Era? An ARDL Bounds Test Approach
Purpose: The purpose of this study is to investigate the macroeconomic forces that have been driving the Indian economy during both the pre-reform and post-reform eras, that is, from 1950-1951 to 1990-1991 and from 1991-1992 to 2022-2023 respectively. Problem: The Indian economy underwent significant economic and financial sector reforms in 1991-92, with the goal of reviving its stagnant growth. These reforms are intended to spur the economic growth of India. What were the main forces behind the Indian economy before and after the reforms? Is the research question. The goal of the current study is to determine if the economic reforms shifted or maintained the pre-reform eras driving forces for the Indian economy in the post-reform era. Design/Methodology/Approach: The gross domestic product (GDP), the gross domestic savings (GDS), the private consumption expenditure (PFCE), the government final consumption expenditure (GFCE), the inflation rate, the exchange rate, the exports, the imports, the internal and external borrowings of the government, personal remittances, foreign direct investment (FDI), and foreign portfolio investments (FPI) are all taken into consideration in order to fill the research gap that has been identified as a result of the comprehensive review of the literature. Following an analysis of the selected variables' fundamental characteristics, an econometric model is developed using the Autoregressive Distributed Lag (ARDL) Bounds Test Model. Findings: There is no evidence of long-run causation and association between the variables, but the findings of the ARDL Bounds Test showed that in the pre-reform period, PFCE is the major driver of the GDP in the short-run, with strong support from imports. However, since the reform, PFCE, GDS, and Exports are the primary short-and long-term contributors to GDP. Practical Implication: These findings indicate that India's macroeconomic system is shifting. The Indian economy has undergone a dramatic shift, moving away from a reliance on imports and toward one that is consumer-driven and export-driven. As savings and consumer expenditures are the main drivers of the Indian economys growth in the post-reform era, policies should be designed to increase savings and consumption as well as increase exports. 2023, ASERS Publishing House. All rights reserved. -
Integration of blockchain to IoT: Possibilities and pitfalls
[No abstract available] -
Preventing Data Leakage and Traffic Optimization in Software-Defined Programmable Networks
The first widely used communication infrastructure was the telephone network, often known as a connection-oriented or circuit-switched network. While making a phone call, these networks will first set up a connection, and then tear it down after the call has ended. The connection made during the call would not be used again. Thus, connectionless or packet-switched networks have been introduced, with an aim to send voice signals as data packets. When compared to conventional network architecture, SDN's separation of the data plane and control plane of networking devices makes the management of these devices directly programmable via a centralised controller. It uses a MAS-based distributed architecture to categorise network flows, and it's called the Traffic Classification Module. Each host or server's high-priority application traffic is isolated via Deep Packet Inspection (DPI). The time consumed for a packet to travel from one endpoint to another is referred to as the average packet delay, whereas the controller's reaction time is twice the average packet delay. Few works existed that utilised routing strategies to decrease the typical packet delay in SDN. To reduce the controller's response time, Software-Defined Networks (SDNs) need a routing algorithm that reduces the average packet delay. Each of the proposed modules and the whole combined SDN-MASTE framework were put through their paces in a series of experiments and emulation-based tests to see how well they performed. 2023 IEEE. -
Study of Kpers?Lortz Instability in a Weakly Electrically Conducting Couple-Stress Fluid
The study aims to investigate the Kpers?Lortz instability in rotating RayleighBard convection of a weakly electrically conducting couple-stress fluid. A novel aspect of this study is the incorporation of weakly electrically conducting couple-stress fluid in a rotating RayleighBard setup to analyze Kpers?Lortz instability and examine heat transfer in both primary and secondary regimes. The main goal is to understand how the combined effects of the couple-stress, rotation, and magnetic field alter stability thresholds and impact the heat transfer. KpersLortz instability (KLI) means the roll systems obtained during the regular convection get deformed and form an angle with each other, making the system unstable. The critical Rayleigh number for regular convection is obtained using linear stability analysis. A ninth-order Lorenz model is obtained using truncated Fourier expansions to study secondary instability. A weak magnetic field (Hartmann number) and couple-stress parameter hinders the onset-of-regular convection. We also obtain the critical values at which the KLI manifests. The critical values are found at a marginal steady state. The Hartmann number and couple-stress parameters hinder the onset-of-secondary instability. Further, the Nusselt number expression is derived, and it is observed that an increase in the couple-stress parameter and Hartmann number diminishes the heat transfer. Additionally, the Nusselt number is obtained for primary and secondary regimes, showing the impact of the parameters on the efficiency of heat transfer in each regime. To validate the results on secondary instability, the study compares its findings with existing literature in the absence of a weak magnetic field and couple-stress effects. A reasonably good agreement is observed, confirming the reliability of the results. 2025 Wiley Periodicals LLC. -
Study of heat transfer in a rotating weakly electrically conducting Newtonian fluid: Primary and Kpers-Lortz regimes
In this paper, we study the primary and secondary (Kpers-Lortz) instabilities of rotating RayleighBard convection for a weakly electrically conducting Newtonian fluid with idealistic boundaries. The critical Rayleigh number is obtained for each instability. Fourth-order and ninth-order Lorenz model are derived using the truncated Fourier-Galerkin expansion and the onset of primary and secondary instabilities is studied. Using a non-linear analysis, we derive the expression for the Nusselt number for both primary and secondary instabilities. The analysis reveals that the heat transfer in the case of primary instability is an over-prediction when compared with that of the secondary instability. An increase in the strength of the magnetic field is to delay the onset of primary and secondary instabilities and decrease the heat transfer. These insights advance the understanding of magnetohydrodynamic stability in rotating convective systems and have implications for geophysical and astrophysical fluid dynamics. 2025 Elsevier Masson SAS -
Sentiment and emotion analysis using machine learning techniques
Sentiment analysis and text emotion identification have grown in prominence due to their wide range of applications in fields such as psychology, artificial intelligence, human-computer interaction, and so on. There are numerous Machine Learning approaches available for emotion recognition and sentiment analysis. The chapter also delves into the key procedures of data collecting, preprocessing, and emphasising the necessity of good data in training effective models. Real-world applications from a variety of disciplines, including business, healthcare, and entertainment, are investigated to demonstrate the practical utility of these strategies. The chapter also covers the issues of ambiguity, context-awareness, and cross-linguistic disparities, as well as providing suggestions for future study paths. This chapter provides a detailed exploration of machine learning approaches to sentiment and emotion analysis, making it a valuable resource for researchers, practitioners, and students interested in using machine learning to understand and interpret emotional content in textual data. 2025, IGI Global Scientific Publishing. All rights reserved. -
Indian catholic priests' identity, relational autonomy and attachment to god: A narrative analysis
A thematic narrative analysis was carried to explore the 28 South Indian Roman Catholic religious priests’ identity, relational autonomy and attachment to God. Fourteen participants were selected from the structured priestly ministry settings namely education ministry and, another 14 participants from the semi-structured priestly ministry settings namely parish and priestly formation ministry settings. The qualitative data collected through the interviews were analyzed through the narrative thematic analysis method. The thematic narrative analysis found five major themes, influence on the priestly identity, value-oriented life, purpose in life, priestly celibacy and challenges in the priestly ministry and 46 subthemes for the participants’ priestly identity narratives. For relational autonomy, the study found five major themes, impactful childhood, the influence of priestly formation, interpersonal relationships, relationship with the person in authority and decision making and 42 subthemes. For attachment God, it found six major themes, God as an attachment figure, seeking and maintaining proximity to God, God as a haven of safety, God as a secure base, perceiving God as stronger and wiser, and individual differences in attachment to God, and 24 sub-themes. The study results revealed strong support for the correspondence pathway, as the majority of the participants had narratives of correspondence between the attachment to their parents and their attachment to God. It also found evidence for the theme of compensation in three participants’ narratives. -
Indian catholic priests' identity, relational autonomy and attachment to god : A Narrative analysis
A thematic narrative analysis was carried to explore the 28 South Indian Roman Catholic religious priests identity, relational autonomy and attachment to God. Fourteen participants were selected from the structured priestly ministry settings newlinenamely education ministry and, another 14 participants from the semi-structured newlinepriestly ministry settings namely parish and priestly formation ministry settings. The newlinequalitative data collected through the interviews were analyzed through the narrative thematic analysis method. The thematic narrative analysis found five major themes, influence on the priestly identity, value-oriented life, purpose in life, priestly celibacy and challenges in the priestly ministry and 46 subthemes for the participants priestly identity narratives. For relational autonomy, the study found five major themes, impactful childhood, the influence of priestly formation, nterpersonal relationships, relationship with the person in authority and decision making and 42 subthemes. For attachment God, it found six major themes, God as an attachment figure, seeking and maintaining proximity to God, God as a haven of safety, God as a secure base, newlineperceiving God as stronger and wiser, and individual differences in attachment to newlineGod, and 24 sub-themes. The study results revealed strong support for the newlinecorrespondence pathway, as the majority of the participants had narratives of newlinecorrespondence between the attachment to their parents and their attachment to God. newlineIt also found evidence for the theme of compensation in three participants narratives. The qualitative comparison between the groups found that for 19 sub-themes for priestly identity, 20 sub-themes for relational autonomy and 13 sub-themes for newlineattachment to God, the priests from the structured ministry settings differed from the priests from the semi-structured ministry settings. -
IoT Behavioural Analytics for Retail Engagement
The modern-day retailing world is struggling to provide real-time and hyper-personalised customer interaction in the context of fragmented behavioural data, sluggish analytics, and in-store interventions that are generic. Current Internet of Things (IoT) retail systems are mainly focused on inventory and transactional insights and do not capture more in-depth behavioural and emotional indicators that affect purchase intent and satisfaction. In this context, this paper will suggest an Internet of Things (IoT)-Based Behavioural Analytics Platform to Hyper-Personalised Consumer Engagement in Retail Management (IBAPS-RM). The framework incorporates multimodal Internet of Things (IoT) sensing, edge computing, and cloud intelligence in creating Multimedia Behavioural Digital Twins (Behavioural Digital Twin (BDT) that dynamically change in response to contextual, environmental, and Interaction-driven information. One of the most notable novelties is the Behavioural Fusion Neural Unit (BFNU) (Behavioural Fusion Neural Unit (BFNU)), that conducts real-time sensor fusion between gaze movement, dwell time, gestures, proximity, and purchase latency to determine behavioural intent and launch micro-personalised interventions in the form of adaptive light, context sensitive offers and personalised digital content. Reinforcement learning also enhances engagement policies through continuous optimisation based on feedback. Experimental analysis shows that IBAPS-RM has better engagement intelligence, with over 93% of personalisation accuracy, 73% shorter decision latency, and 64% higher conversion rate than traditional Internet of Things (IoT) retail systems. The suggested solution improves responsiveness, consumer experience, and operational effectiveness, and promotes privacy-conscious behavioural modelling. In general, IBAPS-RM creates a dynamic, proactive retail intelligence paradigm that dedicates behavioural inference to real-time engagement delivery. 2025, International Academic Institute for Science and Technology. All rights reserved. -
Machine-Learning Based Sleep Pattern Analysis Using Linear Regression Algorithm
This article is investigating the connection between sleep patterns and concentration spans among university students while exploring the potential influence of MyersBriggs Type Indicator (MBTI) personality types on these aspects. The primary objective is to understand how sleep duration affects students ability to maintain focus and how their personality traits might interact with this relationship. Data was collected from university students aged 1619 using a multiple-choice form. The key variables analyzed were age, MBTI personality types, sleep duration, concentration span, and effective study ranking. Pearson's correlation was employed to examine these relationships. Additionally, a linear regression model was developed to predict concentration span based on sleep hours. The findings revealed a strong positive correlation 0.758 between sleep duration and concentration span, suggesting that increased sleep is associated with longer concentration spans. A moderate positive relationship 0.249 was also observed between concentration span and effective study ranking. However, the analysis showed a negligible relationship ? 0.008 between MBTI personality types and concentration span, indicating that within the context of this study, personality type does not significantly influence concentration span. This research emphasizes the critical role of sleep in academic settings and challenges the assumption that personality types significantly impact concentration span and sleep patterns. The linear regression model developed provides a predictive tool for understanding the impact of sleep on concentration, underscoring the importance of adequate sleep for academic success. This research is contributing to the broader understanding of factors influencing student performance and offers practical insights for optimizing study habits and educational strategies. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
Analysis of magnetohydrodynamic casson fluid flow with chemical reaction in a vertical channel: thermal and mass transfer effects
This study investigates Casson fluid flow in a vertical channel within a magnetohydrodynamic (MHD) region, incorporating chemical reaction effects. The channel consists of two regions: one filled with an electrically conducting fluid and the other with a Casson fluid. The nonlinear coupled governing equations are solved using the perturbation method with a small perturbation parameter. The results are presented graphically to analyze the flow characteristics. This systematic analysis yields the velocity and temperature distributions, governed by key parameters such as the Grashof number (Gr), Hartmann number (M), Casson parameter (?), and chemical reaction rate, all of which critically influence the hydrodynamic and thermal behavior of the system. It is observed that the larger the values of the viscosity ratio, width ratio, and the conductivity ratio, the larger the flow field. The findings reveal that the presence of Casson fluid enhances the thermal and mass Grashof numbers, attributed to buoyancy forces. Conversely, the chemical reaction parameter and Hartmann number exhibit a suppressive effect on the flow. The Author(s) under exclusive license to Universitdegli Studi di Ferrara 2026. -
AI-SECURED VISITOR MANAGEMENT SYSTEM
In general, there are so many organizations using the conventional paper log book to record the access of the visitors. This conventional method takes longer time if the number of visitors exceeds the limit. Meanwhile, security issue should be a main concern if there is an increase in the number of visi tors. This is mainly due to the operators who take a long time to verify the identification of each and every visitor when there is huge number of visi tors entering the premises. Moreover, paper log is inadequate to efficiently retrieve and archive the data after several years. This report mainly discusses about the design and implementation of Visitor Management System using Internet of Things (IoT) and Artificial Intelligence (AI). Visitor management system is a security system which is used to track visitors activities in an organization or public building. ESP32 AI Thinker is used to collect the live stream video. Face detection and identification of visitors can be achieved through Artificial Intelligence (AI). With the help of IoT, we can remote access the system for visitor monitoring. The visitors information gets stored into a cloud server which helps the user to view the visitors details on mobile phone at any time. With the help of an API, the user can control the access of a visitor into the premises through notification alerts. A website has been created in order to store the details of visitors such as photograph, arrival time with the help of dijango web application frame work and bootstrap for user interface. DigitalOcean is the cloud server which is used to store the database. To get the notifications on mobile phone, a Telegram BoT API has been created in Telegram app. This BoT also saves the arrival time and photo of the visitor. With the help of this, the user will also be notified whenever a suspicious activity occurs in the premises. This IoT networked contact less security system offers improved security. AI secured Visitor Management System is the best solution to overcome the problems existing in the conventional method as it is the easy way to identify and record the information of a visitor. 2026 by Apple Academic Press, Inc. -
AI-SECURED VISITOR MANAGEMENT SYSTEM
In general, there are so many organizations using the conventional paper log book to record the access of the visitors. This conventional method takes longer time if the number of visitors exceeds the limit. Meanwhile, security issue should be a main concern if there is an increase in the number of visi tors. This is mainly due to the operators who take a long time to verify the identification of each and every visitor when there is huge number of visi tors entering the premises. Moreover, paper log is inadequate to efficiently retrieve and archive the data after several years. This report mainly discusses about the design and implementation of Visitor Management System using Internet of Things (IoT) and Artificial Intelligence (AI). Visitor management system is a security system which is used to track visitors activities in an organization or public building. ESP32 AI Thinker is used to collect the live stream video. Face detection and identification of visitors can be achieved through Artificial Intelligence (AI). With the help of IoT, we can remote access the system for visitor monitoring. The visitors information gets stored into a cloud server which helps the user to view the visitors details on mobile phone at any time. With the help of an API, the user can control the access of a visitor into the premises through notification alerts. A website has been created in order to store the details of visitors such as photograph, arrival time with the help of dijango web application frame work and bootstrap for user interface. DigitalOcean is the cloud server which is used to store the database. To get the notifications on mobile phone, a Telegram BoT API has been created in Telegram app. This BoT also saves the arrival time and photo of the visitor. With the help of this, the user will also be notified whenever a suspicious activity occurs in the premises. This IoT networked contact less security system offers improved security. AI secured Visitor Management System is the best solution to overcome the problems existing in the conventional method as it is the easy way to identify and record the information of a visitor. 2026 by Apple Academic Press, Inc. -
