Factors Affecting the Risk Perceptions of Cryptocurrency Investors
Blockchain technology; Conceptual clarity; Cryptocurrency; Investment education; Risk perception
This study explores risk perceptions in cryptocurrency investments among Indian investors. It employs a multistage random sampling survey of 228 investors. Four key factors influence this perception: conceptual clarity, investment education, awareness of investment options, and fear-induced psychological factors. The overall risk perception of crypto investors is high. Based on our findings, we suggest that the Indian government should organize an awareness campaign to create awareness and educate investors about cryptocurrency. Policymakers and investment managers should focus on transforming high-risk investors into lower-risk investors through education and support, fostering a more favorable investment environment. 2024 The Institute of Behavioral Finance.
Bhattacharjee J.; Pandey L.; Singh R.; Baker H.K.
Bhattacharjee J., School of Business and Management, Christ (Deemed to be University), India; Pandey L., Indian Institute of Information Technology Allahabad, India; Singh R., Indian Institute of Information Technology Allahabad, India; Baker H.K., American University, Kogod School of Business, United States
Buffer zones in Wayanad: A social constructivist exploration into farmers mental health
Buffer zone; mental health of farmers; stressors faced by farmers of Wayanad
Buffer zones are regions set aside to border protected areas to preserve biodiversity, control interactions between people and wildlife, and foster sustainable development. The majority of research on buffer zones focuses on ecological issues, and little is known about how they affect local communities mental health. This study explores buffer zones potential consequences on farmers mental health in Wayanad. Through purposive sampling, eleven participants residing in Wayanad were recruited for the study. The socio-demographics of participants were collected through printed translated questionnaires. The qualitative exploration of their lived experiences, perceptions, and coping strategies was conducted using semi-structured, in-depth interviews. Thematic analysis by Braun and Clarke was used to gain a clearer understanding of the data collected. Through in-depth analysis of the data, it was identified that Mental Health Factors, Communication Factors, Financial Impact, Operational Stress, Interference of Judiciary and Legislature, and Seclusion of the Tribal Community were the issues the farmers faced in Wayanad. The results will contribute to the expanding mental health field and give policymakers, conservationists, and mental health professionals information about the potential psychological effects of buffer zones and guide them in creating suitable interventions and support systems to improve mental health. The Author(s) 2024.
Menon R.R., Department of Psychology, Christ (Deemed to be University), Bangalore, India; Warrier M.G., Department of Psychology, Christ (Deemed to be University), Bangalore, India
Peristaltic mechanism of Ellis fluid with viscous dissipation and thermal radiation induced by cilia wave
cilia wave; Ellis fluid; heat transfer; peristaltic flow; thermal radiation
Bioheat transfer analysis in tissue has attracted the attention of numerous researchers due to its widespread potential applications in the medical field, mainly in thermotherapy and the human thermoregulation system. Also, temperature regulation of the human body primarily occurs through bioheat transfer. Due to the widespread biomedical applications of bio-heat transfer, we aim to investigate the movement of biofluid and bioheat in human organs with the influences of thermal radiation and ciliary waves. The mathematical model for Ellis fluid flow through a tube includes the metachronal wave of cilia motion and convective conditions. The governing equations are created based on mass, momentum conservation, and energy. The current problem is displayed and exact solutions are managed under long wavelength (? < 1) and low Reynolds number (Re < 1) approximations. An analytical approach is employed to derive expressions for longitudinal velocity, temperature, pressure gradient, and stream function as a function of the parameters of the problem. The physical behavior of the peristaltic motion of the Ellis fluid is explained in detail and illustrated graphically for various parameter values. The results of the current study provide potential information for advancement in the biomedical industry, particularly in the development of biomedical devices and processes. World Scientific Publishing Europe Ltd.
Channakote M.M.; Siddabasappa C.; Tripathi D.
International Journal of Computational Materials Science and Engineering
Channakote M.M., Department of Mathematics and Statistics, M. S. Ramaiah University of Applied Sciences, Bangalore, India; Siddabasappa C., Department of Sciences and Humanities CHRIST (Deemed to be University), Bangalore, India; Tripathi D., Department of Mathematics, National Institute of Technology Uttarakhand, (Garhwal), Uttarakhand, Srinagar, 246174, India
Through the Lenses of Sexual Minorities in the Indian LGBTQ + Community: Perception of Social Equality and Community Support
asexual; Bisexual; LGBTQ + community; pansexual; perceived social equality; perceived social support
Whether in the form of same-sex attraction or love, the history of same-sex relationships has been well documented in every culture across the globe. In India, evidence of the same can be found on the monolithic sculptures of the Vishvanath Temple in Khajuraho and texts like Mahabharata and Sushrata Samahita. The acceptance and openness enjoyed by the non-hetero-normative and non-cis-gender individuals in ancient India, changed after the nations colonization. In current times, mainstream society holds heterosexual intercourse as the norm while considering same-sex relationships as deviations. Same sex relationships are a highly stigmatized and garner objections from several religious and political sects. This social stigma and erasure becomes harsher when directed toward individuals with polysexual or asexual orientations. The lack of awareness and representations garners bisexuals, pansexuals and asexuals the status of sexual minorities within the LGBTQ + community. This study makes use of three focus group discussions to explore the perception of each sexual minority regarding social equality within the Indian LGBTQ + community and outside it, alongside trying to understand the community support received by the sexual minorities in the Indian LGBTQ + community. The study uses inductive thematic analysis to draw out themes. The results indicate a predominant feeling of being misunderstood, exploited, fetishized and alienated even within the LGBTQ + community while finding solace in their own sub-communities and the online community. The results also reveal feelings expectations held by individuals from each sexual minority in terms of their desired place in society. 2024 Taylor & Francis Group, LLC.
Journal of Bisexuality, Vol-24, No. 3, pp. 411-444.
Ghosh O., Department of Psychology, CHRIST (Deemed to be University), NCR, Delhi, India
A characterization of star-perfect graphs
Perfect graph; star-imperfect graph; star-perfect graph
Motivated by Berge perfect graphs, we define star-perfect graphs and characterize them. For a finite simple graph G(V, E), let (Formula presented.) denote the minimum number of induced stars contained in G such that the union of their vertex sets is V(G), and let (Formula presented.) denote the maximum number of vertices in G such that no two of them are contained in the same induced star of G. We call a graph G star-perfect if (Formula presented.), for every induced subgraph H of G. A graph G is star-perfect if and only if G is (Formula presented.) -free, for every (Formula presented.). A bipartite graph G is star-perfect if and only if every induced cycle in G is of length (Formula presented.). The minimum parameter (Formula presented.) and the maximum parameter (Formula presented.) have been extensively studied in various contexts. 2024 The Author(s). Published with license by Taylor & Francis Group, LLC.
Ravindra G.; Ghosh S.; Kureethara J.V.; Abraham V.M.
AKCE International Journal of Graphs and Combinatorics, Vol-21, No. 2, pp. 189-197.
Ravindra G., Department of Mathematics, CHRIST(Deemed to be University), Bengaluru, India; Ghosh S., Department of Mathematics, CHRIST(Deemed to be University), Bengaluru, India; Kureethara J.V., Department of Mathematics, CHRIST(Deemed to be University), Bengaluru, India; Abraham V.M., Department of Mathematics, CHRIST(Deemed to be University), Bengaluru, India
Creating a sustainable future: insights into brand marketing in the luxury fashion industry
attitude; Brand Management; branding; Consumer Behaviour; fashion industry; luxury; Marketing; purchase intention; Relationship Marketing; Sales; Sharma Nitika, International Management InstituteNew Delhi, India; Sustainability; Sustainability; sustainability challenges; sustainable luxury fashion
This paper aims to develop a conceptual framework that elucidates the factors that impact sustainable luxury brand marketing, specifically focusing on the luxury fashion industry. The framework aims to highlight the role played by the industry in promoting economic, social, and environmental sustainability. By examining these factors, the study seeks to contribute to a better understanding of how luxury fashion brands can effectively incorporate sustainability into their marketing strategies, thereby fostering a more sustainable and responsible approach to luxury consumption. Applying the theoretical framework derived from the literature review and systematic mapping approach, we examine its relevance in the luxury fashion market. This exploration allows us to assess its practical applicability and gather empirical evidence regarding sustainable brand marketing in this context. This research will give an in-depth analysis of the major elements influencing the consumption of sustainable luxury goods. The findings expand our understanding of the sustainable practices adopted by luxury fashion brands, providing valuable insights for academia and the industry. This studys implications are profound: luxury brand managers can enhance brand value through insights on sustainable fashion consumption drivers, while sustainable brands gain strategies for audience engagement and loyalty. 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
Kaur H.; Choudhary S.; Manoj A.; Tyagi M.
Cogent Business and Management, Vol-11, No. 1
Kaur H., School of Commerce, Finance and Accountancy, CHRIST (Deemed to be University), Delhi, India; Choudhary S., School of Commerce, Finance and Accountancy, CHRIST (Deemed to be University), Delhi, India; Manoj A., School of Commerce, Finance and Accountancy, CHRIST (Deemed to be University), Delhi, India; Tyagi M., School of Commerce, Finance and Accountancy, CHRIST (Deemed to be University), Delhi, India
Emotional Inhibition and Personality as Predictors of Anxiety and Depression in Young Adults
Anxiety; Depression; Emotional Inhibition; introversion-extroversion; Personality
Purpose: Anxiety and depression have been major contributors to the global burden of disease, and the impact has been exacerbated following the COVID-19 pandemic. Therefore, the aim of this study was to understand the association between emotional suppression and the introverted-extraverted dimension of personality in young people and anxiety and depression. Method: Participants were 152 Indian females between the age group of 18-25 years who provided basic demographic details and completed three questionnaires via a google form. Findings: Results described a significant negative correlation of anxiety r (152) = .500, p <0.01and depression r(152)=.471, p <0.01 with emotional inhibition. There was also a significant positive correlation of anxiety r (152) = .288,p < 0.01 and depression r(152)= .288, p <0.01 with personality. While Emotional inhibition emerged as a significant negative predictor of anxiety (R2= .250) as well as of depression (R2=.222), personality (R2=.243) emerged as a significant predictor of depression. Conclusion/Value: Contrary to popular belief, the results of this study suggest that anxiety and depression are inversely related to emotional inhibition. It restores the complexity of emotions and the need to investigate their role in various pathologies. These findings provide an initial basis for further investigation into the role of emotional expression and suppression in the Indian population. 2024 RJ4All.
Dhar A., Christ Deemed to be University, Delhi-NCR, India; Kaur H., Panjab University, India
Lightweight Model for Occlusion Removal from Face Images
Dynamic Quantization; Generative adversarial network (GAN); Occlusion; Pix2pix
In the realm of deep learning, the prevalence of models with large number of parameters poses a significant challenge for low computation device. Critical influence of model size, primarily governed by weight parameters in shaping the computational demands of the occlusion removal process. Recognizing the computational burdens associated with existing occlusion removal algorithms, characterized by their propensity for substantial computational resources and large model sizes, we advocate for a paradigm shift towards solutions conducive to low-computation environments. Existing occlusion riddance techniques typically demand substantial computational resources and storage capacity. To support real-time applications, it's imperative to deploy trained models on resource-constrained devices like handheld devices and internet of things (IoT) devices possess limited memory and computational capabilities. There arises a critical need to compress and accelerate these models for deployment on resource-constrained devices, without compromising significantly on model accuracy. Our study introduces a significant contribution in the form of a compressed model designed specifically for addressing occlusion in face images for low computation devices. We perform dynamic quantization technique by reducing the weights of the Pix2pix generator model. The trained model is then compressed, which significantly reduces its size and execution time. The proposed model, is lightweight, due to storage space requirement reduced drastically with significant improvement in the execution time. The performance of the proposed method has been compared with other state of the art methods in terms of PSNR and SSIM. Hence the proposed lightweight model is more suitable for the real time applications with less computational cost. 2024 by the author(s).
Annals of Emerging Technologies in Computing, Vol-8, No. 2, pp. 1-14.
International Association for Educators and Researchers (IAER)
https://doi.org/10.33166/AETiC.2024.02.001 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85190413826&doi=10.33166%2fAETiC.2024.02.001&partnerID=40&md5=ff179998cf4cf9c790ce04656ddfd0a5
John S., Department of Computer Science and Engineering, Christ University, India; Danti A., Department of Computer Science and Engineering, Christ University, India
Relationships between Ultrasonographic Placental Thickness in the Third Trimester and Foetal Outcomes
Gestational diabetes; Gestational Diabetes Mellitus; Oligohydramnios; Preeclampsia; Ultrasonographic
Poor neonatal outcomes, including low birth weight (LBW), poor APGAR scores, more NICU hospitalizations, and a higher chance to develop Pre-Eclampsia, IUGR, and Oligo Hydramnios, are all linked to thin placental thickness. While both thin and thick placentae are connected to a greater prevalence of C-sections, thick placentae are linked with a greater possibility of developing GDM and an increase in NICU hospitalizations. Objective of this research was to investigate the association between placental thickness as measured by ultrasonography in the third trimester and foetal outcome, including the relationship between placental histopathology and placental thickness. investigate the link among placental thickness, foetal outcome, and placental histology. Most newborns had fibrinoid necrosis and calcifications. Babies with Macrosomia and IUGR, respectively, were more likely to develop Syncytial knots and thickening of the vessel wall. Patients with normal placenta thickness at 36 weeks' gestation experienced fewer difficulties than those with thin or thick placentas at the same time. The study emphasizes the value of evaluating placental thickness using ultrasound in the third trimester to detect high-risk pregnancies. The study also shows that aberrant foetal and neonatal events are linked to certain placental histological characteristics, like artery wall thickening and infarctions. RJPT All right reserved.
Kadam D.; Patil Y.; Patange R.P.; Patil S.; Sebastian S.; Jarag R.
Research Journal of Pharmacy and Technology, Vol-17, No. 2, pp. 746-750.
Research Journal of Pharmacy and Technology
Kadam D., Department of Gynecology, Krishna Institute of Medical Sciences, Krishna Vishwa Vidyapeeth Deemed to be University, Maharashtra, Karad, India; Patil Y., Department of Gynecology, Krishna Institute of Medical Sciences, Krishna Vishwa Vidyapeeth Deemed to be University, Maharashtra, Karad, India; Patange R.P., Department of Gynecology, Krishna Institute of Medical Sciences, Krishna Vishwa Vidyapeeth Deemed to be University, Maharashtra, Karad, India; Patil S., Department of Gynecology, Krishna Institute of Medical Sciences, Krishna Vishwa Vidyapeeth Deemed to be University, Maharashtra, Karad, India; Sebastian S., Christ (Deemed to be University), India; Jarag R., Bharati Vidyapeeth College of Pharmacy, Maharashtra, Kolhapur, India
Machine Learning Classifiers for Credit Risk Analysis
Credit risk; Decision tree; K-Nearest Neighbour; Machine learning; Naive Bayes classifier
The modern world is a place of global commerce. Since globalization became popular, entrepreneurs of small and medium enterprises to large ones have looked up to banks, which have existed in various forms since antiquity, as their pillars of support. The risk of granting loans in various forms has significantly increased as a consequence of this, the businesses face financing difficulties. Credit Risk Analysis is a major aspect of approving the loan application that is done by analyzing different types of data. The goal is to minimize the risk of approving the loan for the Individuals or businesses who might not pay back on time. This research paper addresses this challenge by applying various machine learning classifiers to the German credit risk dataset. By evaluating and comparing the accuracy of these models to identify the most effective classifier for credit risk analysis. Furthermore, it proposes a contributory approach that combines the strengths of multiple classifiers to enhance the decision-making process for loan approvals. By leveraging ensemble learning techniques, such as the Voting Ensemble model, the aim is to improve the accuracy and reliability of credit risk analysis. Additionally, it explores tailored feature engineering techniques that focus on selecting and engineering informative features specific to credit risk analysis. 2024 Sudiksha et al., licensed to EAI.
EAI Endorsed Transactions on Internet of Things, Vol-10
https://doi.org/10.4108/eetiot.5376 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85187884959&doi=10.4108%2feetiot.5376&partnerID=40&md5=b342327412a0caadb68881e3df17b106
Sudiksha, Department of Data Science, Christ University, Pune Lavasa Campus, India; Nanjundan P., Department of Data Science, Christ University, Pune Lavasa Campus, India; George J.P., Department of Data Science, Christ University, Pune Lavasa Campus, India
Looking at psychological well-being through the lens of identity among adolescent girls: An exploration
Adolescent; Identity processes; Psychological Well-being
Purpose: This research endeavours to delve into the intricate dimensions of adolescent girls' psychological well-being and identity, aiming to shed light on their interplay and identify key predictors of psychological well-being. The study, conducted with a sample of adolescent girls, seeks to enrich our understanding of the multifaceted nature of their developmental experiences. Psychological well-being is attained by achieving a state of balance affected by both challenging and rewarding life events and a stable sense of identity. Approach: The present research is an ex-post facto research falling in the area of quantitative research design. Data has been collected on 348 adolescents, purposely recruited from different schools of Delhi NCR. The age range of the respondents was 15 to 17 years. Findings: The results reveal that psychological well-being is being predicted by identity processes among adolescent females. The different dimensions of identity processes are found to be explaining almost 19% variance in the regression model. Commitment has been found to have a ? value of 0.197 (t= 3.511; p<.01), in-depth exploration has a ?= 0.161 (t= 2.867; p<.01), and reconsideration of commitment has a ?= 0.314 (t= 6.294; p<.01). Value: By addressing the objectives of this research, valuable insights may be received by educators, mental health professionals, and policymakers to better support and enhance the well-being of adolescent girls through having a stable sense of identity. 2024 RESTORATIVE JUSTICE FOR ALL.
Ahirwar S., CHRIST (Deemed to be University), India; Shukla R., The University of New South Wales, Australia
Can we improve the outcome of pregnancies with low serum PAPP-A in the first trimester?
first-trimester screening; micronized vaginal progesterone; PAPP-A; Pregnancy; preterm birth
Low birth weight is associated with various complications, and recent findings rely on the fact that micronized progesterone supplementation leads to improved birth weight, which is crucial for addressing concerns related to fetal growth. Objective: This study aimed to assess the impact of micronized progesterone (VMP4) supplementation on pregnancies with low serum pregnancy-associated plasma protein-A (PAPP-A) multiples of the median (MoM) values during first-trimester screening. Methods: Out of 8933 patients evaluated, 116 pregnant women with low PAPP-A concentrations in their blood and no fetal chromosomal anomalies (CAs) were included. Three groups were formed: group 1 received VMP4 from 11 to 16weeks (29 women, 25%), group 2 received VMP4 from 11 to 36weeks (25 women, 21.5%), and group 3 (62 women, 53.5%) served as controls without receiving progesterone. Results: Results indicated that group 3 had higher rates of complications, including miscarriages (16.37%), preterm delivery (17.8%), and fetal developmental abnormalities (19.4%). Birthweight variations were elevated in pregnancies without progesterone, contrasting with lower variations in VMP4 groups. Group 2, receiving VMP4 until 36weeks, reported the lowest incidence of abortion and preterm birth (PB), along with the highest mean birth weight. Conclusions: The conclusion suggests that 200 mg per day of VMP4 up to 36weeks of supplementation led to fewer placental-related complications in women with very low PAPP-A at first-trimester screening (0.399 MoM). By reporting lower rates of miscarriages, PBs, and fetal developmental abnormalities in the micronized progesterone-treated groups, the study suggests a potential reduction in complications. 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
Tsibizova V.; Al-Sannan B.; Fedorova A.; Govorov I.; Meyyazhagan A.; Di Renzo G.C.
Journal of Maternal-Fetal and Neonatal Medicine, Vol-37, No. 1
All Open Access; Hybrid Gold Open Access
ISSN: 14767058; PubMed ID: 38503546; CODEN: JMNMA
Tsibizova V., Almazov National Medical Research Centre, Saint Petersburg, Russian Federation, PREIS International School, Firenze, Italy; Al-Sannan B., Obstetrics and Gynecology Department, Faculty of Medicine, University of Kuwait, Kuwait City, Kuwait; Fedorova A., Leningrad Region Hospital, Saint Petersburg, Russian Federation; Govorov I., Almazov National Medical Research Centre, Saint Petersburg, Russian Federation; Meyyazhagan A., PREIS International School, Firenze, Italy, Department of Life Sciences, CHRIST (Deemed to be University), Bengaluru, India, Centre of Perinatal and Reproductive Medicine, University of Perugia, Perugia, Italy; Di Renzo G.C., PREIS International School, Firenze, Italy, Centre of Perinatal and Reproductive Medicine, University of Perugia, Perugia, Italy, Department of Obstetrics, Gynecology and Perinatal Medicine, First Moscow Medical University, Sechenov University, Moscow, Russian Federation
Optimal procurement policy for growing items under permissible delay in payment
delay in payment; deteriorating items; growing items; inventory management; mortality
In the last decade, growing item industries have shown an increasing trend in production and it is expected that such industries will maintain this increasing pace in the future. Existing challenges of these industries, like mortality in the production phase and deterioration in the consumption phase, make procurement decisions more complex. In this article, we established an inventory model with mortality, deterioration, and price-dependent demand. To increase the sales volume and profit, a delay in payment policy is considered. A numerical example is presented to explain the solution procedure. The concavity of the profit function is discussed analytically for decision variables. It has been observed through sensitivity analysis that selling price is the most sensitive among decision variables and parameters. 2024 Inderscience Enterprises Ltd.
International Journal of Services and Operations Management, Vol-47, No. 3, pp. 354-365.
https://doi.org/10.1504/IJSOM.2024.137318 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85187993567&doi=10.1504%2fIJSOM.2024.137318&partnerID=40&md5=abbe177f8f3ca2f6f3add917bd54f839
Saraswat A.K., Department of Mathematics, Institute of Applied Sciences and Humanities, GLA University, NH-2, Mathura, 281406, India, School of Sciences, CHRIST (Deemed to be University), Delhi- NCR, Ghaziabad, 201003, India; Sharma A., Department of Mathematics, Institute of Applied Sciences and Humanities, GLA University, NH-2, Mathura, 281406, India, School of Sciences, CHRIST (Deemed to be University), Delhi- NCR, Ghaziabad, 201003, India
Unveiling metaverse sentiments using machine learning approaches
Behavior; Information technology; Neural nets; Qualitative research
Purpose: The metaverse, which is now revolutionizing how brands strategize their business needs, necessitates understanding individual opinions. Sentiment analysis deciphers emotions and uncovers a deeper understanding of user opinions and trends within this digital realm. Further, sentiments signify the underlying factor that triggers ones intent to use technology like the metaverse. Positive sentiments often correlate with positive user experiences, while negative sentiments may signify issues or frustrations. Brands may consider these sentiments and implement them on their metaverse platforms for a seamless user experience. Design/methodology/approach: The current study adopts machine learning sentiment analysis techniques using Support Vector Machine, Doc2Vec, RNN, and CNN to explore the sentiment of individuals toward metaverse in a user-generated context. The topics were discovered using the topic modeling method, and sentiment analysis was performed subsequently. Findings: The results revealed that the users had a positive notion about the experience and orientation of the metaverse while having a negative attitude towards the economy, data, and cyber security. The accuracy of each model has been analyzed, and it has been concluded that CNN provides better accuracy on an average of 89% compared to the other models. Research limitations/implications: Analyzing sentiment can reveal how the general public perceives the metaverse. Positive sentiment may suggest enthusiasm and readiness for adoption, while negative sentiment might indicate skepticism or concerns. Given the positive user notions about the metaverses experience and orientation, developers should continue to focus on creating innovative and immersive virtual environments. At the same time, users' concerns about data, cybersecurity and the economy are critical. The negative attitude toward the metaverses economy suggests a need for innovation in economic models within the metaverse. Also, developers and platform operators should prioritize robust data security measures. Implementing strong encryption and two-factor authentication and educating users about cybersecurity best practices can address these concerns and enhance user trust. Social implications: In terms of societal dynamics, the metaverse could revolutionize communication and relationships by altering traditional notions of proximity and the presence of its users. Further, virtual economies might emerge, with virtual assets having real-world value, presenting both opportunities and challenges for industries and regulators. Originality/value: The current study contributes to research as it is the first of its kind to explore the sentiments of individuals toward the metaverse using deep learning techniques and evaluate the accuracy of these models. 2024, Emerald Publishing Limited.
Natarajan T.; Pragha P.; Dhalmahapatra K.; Veera Raghavan D.R.
https://doi.org/10.1108/K-11-2023-2268 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85188192750&doi=10.1108%2fK-11-2023-2268&partnerID=40&md5=214cdd4eeb7dcd452f9391b2d9870084
Natarajan T., Department of Management Studies, National Institute of Technology Tiruchirappalli, Tiruchirappalli, India; Pragha P., Department of Management Studies, National Institute of Technology Tiruchirappalli, Tiruchirappalli, India; Dhalmahapatra K., Operations and Quantitative Techniques, IIM Shillong, Shillong, India; Veera Raghavan D.R., School of Business and Management, CHRIST (Deemed to be) University, Bangalore, India
AN OPTIMIZATION AND PREDICTIVE MODELING TO ENHANCE THE WEAR AND MECHANICAL PERFORMANCE OF Al 5054 ALLOY FOR DEFENSE APPLICATIONS WITH TiO2 NANOPARTICLES
Artificial Neural Network; impact; Taguchi design of experiments; tensile; wear test
This study examines the effects of 2%, 4%, and 6% additions of TiO2 nanoparticles on the wear and mechanical characteristics of Al 5054 alloy reinforcement. The results demonstrate that the addition of TiO2 nanoparticles considerably increases the alloys tensile and impact strengths. Tensile strength reaches a peak of 221 MPa at 6% reinforcement and it rises gradually as the percentage of TiO2 reinforcement increases. Similarly, impact strength rises with time and, with TiO2 reinforcement, it reaches a maximum of 63 Joules at 6%. Wear analysis using Taguchi-based design determines the optimal combination of composition, disc rotation speed, load, and sliding distance to minimize a given wear rate and friction force. The SEM analysis validates that the composites exhibit enhanced wear resistance due to the uniform distribution of TiO2 nanoparticles. An Artificial Neural Network (ANN) model is also developed to predict the responses, and it achieves an overall accuracy of 83.549%. The mechanical properties and wear resistance of TiO2-reinforced Al 5054 composites can be enhanced, as it is demonstrated by these results. This information is crucial for material design and optimization across a range of engineering applications. 2024, Scibulcom Ltd.. All rights reserved.
Sahu S.K.; Bansod P.J.; Mohanasundaram S.; Vetrivel K.P.; Pandian P.P.; Rajendiran M.
Journal of the Balkan Tribological Association, Vol-30, No. 1, pp. 67-80.
Sahu S.K., Department of Mechanical Engineering, Veer Surendra Sai University of Technology, Odisha, Burla, India; Bansod P.J., Department of Mechanical Engineering, G H Raisoni College of Engineering & Management Wagholi, Maharashtra, Pune, India; Mohanasundaram S., Department of Mechanical Engineering, Karunya Institute of Technology and Sciences, Tamil Nadu, Coimbatore, India; Vetrivel K.P., Department of Mechanical Engineering, M. P. Nachimuthu M. Jaganathan Engineering College, Tamil Nadu, Erode, India; Pandian P.P., Department of Mechanical Engineering, School of Engineering and Technology, Christ University (Deemed to be University), Karnataka, Bangalore, India; Rajendiran M., Department of Computer Science and Engineering, Panimalar Engineering College, Poonamallee, Tamil Nadu, Chennai, India
An efficient deep learning approach for identifying interstitial lung diseases using HRCT images
deep learning; DL; high-resolution computed tomography; HRCT; ILD; interstitial lung disease; multi-label classification; transfer learning
Interstitial lung disease (ILD) encompasses over 200 fatal lung disorders affecting the interstitium, leading to significant mortality rates. We propose an AI-driven approach to diagnose and classify ILD from high-resolution computed tomography (HRCT) images. The research utilises a dataset of 3,045 HRCT images and employs a two-tier ensemble method that combines various machine learning (ML) models, convolutional neural networks (CNNs), and transfer learning. Initially, ML models achieve high accuracy, with the J48 model at 93.08% accuracy, mainly highlighting the importance of diagonal-wise standard deviation. Deep learning techniques are then applied, with three CNN models achieving test accuracies of 94.08%, 92.04%, and 93.72%. Transfer learning models also show promise, with InceptionV3 at 92.48% accuracy. Ensembling these models further boosts accuracy, with the ensemble of three CNN models reaching 97.42%. This research has the potential to advance ILD diagnosis, offering a robust computational framework that enhances accuracy and ultimately improves patient outcomes. Copyright 2024 Inderscience Enterprises Ltd.
International Journal of Computational Science and Engineering, Vol-27, No. 3, pp. 286-301.
https://doi.org/10.1504/IJCSE.2024.138427 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85192870037&doi=10.1504%2fIJCSE.2024.138427&partnerID=40&md5=b3c6ded0e2833e6e04cba94656d8187a
Raju N., Department of Computer Science, CHRIST (Deemed to be University), Bangalore, India; Augustine D.P., Department of Computer Science, CHRIST (Deemed to be University), Bangalore, India
Getting Rid of Organizational Complacency in a Dynamic Environment
career planning; Change management; diagnostic process; human resource interventions; planned change; six-box Weisbord
This case investigates the external consultants organizational diagnosis aimed at understanding the imperative for change within Infotics Solutions. It explores various concepts, including the nature of planned change and the resistance exhibited by employees. Emphasis is placed on the necessity of a comprehensive organizational diagnosis before embarking on the change process, highlighting the pitfalls of relying solely on a leaders intuition and experience to initiate change. Furthermore, the case underlines the implementation of human resource management interventions and their significance from both employee and organizational standpoints. It addresses the protagonists recognition of the need for external consultants expertise to grasp the problem and devise a strategic change process. The consultants methodical approach to planning change across different themes to achieve organizational objectives is elucidated, featuring the importance of employing the right diagnosis technique in situations where the problem is unclear. The case also showcases the consultants analytical approach to problem-solving, offering specific solutions tailored to the organizations needs. Ultimately, it illustrates the challenges faced by organizations that lean heavily on past successes and struggle to adapt to evolving environmental demands. Lastly, the case highlights the importance of analysing survey results and implementing theme-based interventions to address the issues confronting the organization and its employees at Infotics Solutions. 2024 Lahore University of Management Sciences.
Aranha R.; Dsouza A.; Saldanha A.; Balasundaram S.; Basavaraj S.
Aranha R., School of Business and Management, Christ (Deemed to be University), Karnataka, Bangalore, India; Dsouza A., School of Business and Management, Christ (Deemed to be University), Karnataka, Bangalore, India; Saldanha A., St Josephs Institute of Management, Karnataka, Bengaluru, India; Balasundaram S., School of Business and Management, Christ (Deemed to be University), Karnataka, Bangalore, India; Basavaraj S., School of Business and Management, Christ (Deemed to be University), Karnataka, Bangalore, India
A Pilot Study of the DREAMS Program: A Community Collaborative Intervention for the Psychosocial Development of Middle School Students
after school program; DREAMS intervention; psychosocial development; school-community partnership
The purpose of this study was to pilot the DREAMS (Desire, Readiness, Empowerment, Action, and Mastery for Success) program, a community-collaborative, after-school intervention program designed specifically to address the holistic developmental needs of students at school. The author originally developed and implemented the program in Kerala, India, and later redesigned it for American school students. Combining the theories of Vygotsky and Erikson, the DREAMS model emphasizes the impact of the community on the development of children. This study evaluates the effects of a summer camp, the primary intervention of a three-year program, on the self-worth, self-esteem, and self-concept of 20 middle school students in Northeast Louisiana. After students attended the week-long program, the most significant improvements were observed in self-esteem and self-worth. Further longitudinal or comparative experimental research on the complete design would provide stronger evidence to draw more substantive conclusions. (2024), (California State University). All rights reserved.
Journal of School Administration Research and Development, Vol-9, No. 1, pp. 46-55.
https://doi.org/10.32674/jsard.v9i1.5670 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85191393081&doi=10.32674%2fjsard.v9i1.5670&partnerID=40&md5=7b08fac6ad4a4366fab66a2126e8d787
NDC Pebbling Number for Some Class of Graphs
Cover pebbling number; NDC pebbling number; Non-split dominating set
Let G be a connected graph. A pebbling move is defined as taking two pebbles from one vertex and the placing one pebble to an adjacent vertex and throwing away the another pebble. A dominating set D of a graph G = (V, E) is a non-split dominating set if the induced graph < V ? D > is connected. The Non-split Domination Cover(NDC) pebbling number, ?ns(G), of a graph G is the minimum of pebbles that must be placed on V(G) such that after a sequence of pebbling moves, the set of vertices with a pebble forms a non-split dominating set of G, regardless of the initial configuration of pebbles. We discuss some basic results and determine ?ns for some families of standard graphs. 2024 the Author(s), licensee Combinatorial Press.
Lourdusamy A.; Dhivviyanandam I.; Mathew L.
Journal of Combinatorial Mathematics and Combinatorial Computing, Vol-119, pp. 121-128.
https://doi.org/10.61091/jcmcc119-13 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85192672126&doi=10.61091%2fjcmcc119-13&partnerID=40&md5=cb9b767211b83765ce93c1a35256c14f
Lourdusamy A., Department of Mathematics, St. Xaviers College (Autonomous), Palayamkottai, India; Dhivviyanandam I., St. Xaviers College (Autonomous), Palayamkottai Affiliated to Manonmaniam Sundaranar University, Tamil Nadu, Abisekapatti, 627012, India; Mathew L., Department of Mathematics CHRIST(Deemed to be university), Pune- Lavasa Campus, India
ACCIDENT PREVENTION AND MANAGEMENT SYSTEM IN URBAN VANETS FOR IMPROVING SLIPPERY ROADS RIDE AFTER RAIN
rainfall; safer driving; timely warnings; urban environments; Vehicular Ad-hoc Networks
Urban Vehicular Ad-hoc Networks (VANETs) face challenges in managing accidents and enhancing safety, particularly on slippery roads post rainfall. This study addresses this issue by proposing an Accident Prevention and Management System tailored for improving ride safety in such conditions. The problem statement identifies the increased risk of accidents and decreased road grip due to rain-induced slippery surfaces in urban areas. The proposed method integrates real-time data collection from vehicles and road infrastructure to predict and detect slippery road segments. Utilising this information, the system dynamically disseminates warnings to nearby vehicles, enabling them to adapt their driving behaviour and avoid potential accidents. The flow of the proposed system involves a multi-step process: (1) Real-time data collection using sensors installed in vehicles and roadside infrastructure, (2) Data analysis and prediction algorithms to identify slippery road segments, (3) Communication protocols for disseminating warnings to vehicles in the neighbourhood, and (4) Driver assistance mechanisms to aid in adapting to the road conditions. Results from simulations and real-world experiments demonstrate the efficacy of the system in significantly reducing the likelihood of accidents on slippery roads after rainfall. By leveraging VANET technology and real-time data analysis, this system enhances safety by providing timely warnings and promoting safer driving practices, ultimately mitigating the risks associated with adverse weather conditions in urban environments. 2024, Scibulcom Ltd.. All rights reserved.
Leena B.; Vimal V.R.; Labhade-Kumar N.; Acharjee P.B.; Raha S.; Ponnusamy M.; Rajaram A.
Journal of Environmental Protection and Ecology, Vol-25, No. 2, pp. 586-599.
Leena B., Department of ECE, KGISL Institute of Technology, Coimbatore, India; Vimal V.R., Institute of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Thandalam, Chennai, India; Labhade-Kumar N., Computer Department, Shree Ramchandra College of Engineering, Maharashtra, Pune, India; Acharjee P.B., CHRIST University, Lavasa Campus, Pune, India; Raha S., Department of Geography, Bhairab Ganguly College, Belgharia, WestBengal, Kolkata, India; Ponnusamy M., Indian Institute of Information Technology, WestBengal, Kalyani, India; Rajaram A., Department of Electronics and Communication Engineering, E.G.S Pillay Engineering College, Tamil Nadu, Nagapattinam, 611 002, India