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A Study on Bivariate Inverse Topp-Leone Model to Counter Heterogeneous Data: Properties, Dependence Studies, Classical and Bayesian Estimation
In probability and statistics, reliable modeling of bivariate continuous characteristics remains a real insurmountable consideration. During the analysis of bivariate data, we have to deal with heterogeneity that is present in data. Therefore, for dealing with such a scenario, we investigate a novel technique based on a Farlie-Gumbel-Morgenstern (FGM) copula and the inverse Topp-Leone (ITL) model in this study. The idea is to use the oscillating functionalities of the FGM copula and the flexibility of the ITL model to propose a serious bivariate solution for the modeling of bivariate lifetime phenomena to counter the heterogeneity present in data. Both theory and practice are developed. In particular, we determine the main functions related to the model, like the cumulative model function, probability density function, and various useful dependence measures for bivariate modeling. The model parameters are estimated using the maximum likelihood method and Bayesian framework of the Markov Chain Monte Carlo (MCMC) methodology. Following that, model comparison methods are used to compare models. To explain the findings and show that better models are recommended, the famous Drought and Burr data sets are used. 2025, Thai Statistical Association. All rights reserved. -
An educational animation intervention to enhance HPV awareness and practices among transgender individuals associated with NGOs in North India: Preliminary findings
Background: Transgender individuals in India face an elevated risk of Human Papillomavirus (HPV) infection due to limited knowledge, awareness, and access to preventive care. However, targeted research and interventions for this population are scarce. Addressing this gap is critical for improving HPV-related health outcomes among transgender individuals. Aim: This pilot study aimed to develop and evaluate the effectiveness of an animation-based intervention designed to enhance knowledge, attitudes, and practices (KAP) related to HPV among transgender individuals in India. Methods: The study was conducted in four phases among sixteen participants from different NGOs in North India. Phase 1 involved a needs analysis through a focus group discussion (FGD) with ten transgender participants, which led to co-designing the intervention. Phase 2 focused on developing the animation intervention based on the identified needs and existing literature. Phase 3 tested the intervention with six participants using a pre-post assessment with the Knowledge, Attitude, and Practice (KAP) Questionnaires and Human Papillomavirus Knowledge Questionnaire (HPV-KQ) questionnaires. Phase 4 finalized the module by incorporating feedback from the transgender community, with minor modifications made following validation. Results: Preliminary analysis showed significant improvement in KAP scores (Knowledge: 0.167 to 1.000, p = 0.073; Attitude: 0.583 to 0.833, p = 0.132; Practice: 0.250 to 0.500, p = 0.200) post-intervention. Participants demonstrated increased knowledge and more positive attitudes toward HPV prevention. Feedback highlighted the animations effectiveness in simplifying complex health information. Conclusion: The animation-based intervention effectively improved HPV-related knowledge, attitudes, and practices among transgender individuals, demonstrating the potential of culturally sensitive, visual interventions to enhance public health outcomes in underserved populations. 2025 Taylor & Francis Group, LLC. -
The impact of the COVID-19 pandemic on fast commerce
Quick commerce, or q-commerce, has quickly become a groundbreaking new model in today's retail, focused on rapid delivery (generally in 30 to 60 minutes). The emergence of q-commerce is framed around the Changing Point Model that lays out the main shifts in the industry; from the pre-pandemic experimentation early-stage through the crisis-induced adoption phase and the current market consolidation and optimization phase. While the consumer preferences keep revolving around convenience vs. cost, companies are left to battle with serious operational and logistical concerns like sustainability, gig economy drivers, and prohibitive/ impossible infrastructure. In a bid to remain competitive, companies are betting on green logistics, electric transport, and artificial intelligence personalization to enhance efficiencies and reduce environmental harms.Q-commerce will further evolve through drone deliveries, decentralized supply chains, and autonomous technology, reshaping last mile logistics. 2026, IGI Global Scientific Publishing. All rights reserved. -
Psychology of Confinement and Intersections of Imposter Syndrome: Identity Reconstruction and Human Rights in Prisons
The imposter syndrome behind bars is the feeling many prisoners have that they do not deserve personal development, educational achievements or rehabilitative accomplishments while incarcerated. In the context of jail and prison, there are many have layers of profound internalized self-doubt as a result of societys bias against criminalized identity and the resolutely stratified nature of life behind bars. When prisoners accomplish something going to school, teaching other prisoners or taking part in therapy programs, as they can feel internally conflicted as to whether it has been real, if it is only them performing. This chapter emphasizes on that how prisoners dissonance slips into the personal stories of society portraying them as what they did, denying their humanity and truthfulness. The also supporting environments and help much in affirming positive identity rebuilding. 2026 by IGI Global Scientific Publishing. All rights reserved. -
Artificial Intelligence-Enabled Digital Twin for Smart Manufacturing
An essential book on the applications of AI and digital twin technology in the smart manufacturing sector. In the rapidly evolving landscape of modern manufacturing, the integration of cutting-edge technologies has become imperative for businesses to remain competitive and adaptive. Among these technologies, Artificial Intelligence (AI) stands out as a transformative force, revolutionizing traditional manufacturing processes and making the way for the era of smart manufacturing. At the heart of this technological revolution lies the concept of the Digital Twin-an innovative approach that bridges the physical and digital realms of manufacturing. By creating a virtual representation of physical assets, processes, and systems, organizations can gain unprecedented insights, optimize operations, and enhance decision-making capabilities. This timely book explores the convergence of AI and Digital Twin technologies to empower smart manufacturing initiatives. Through a comprehensive examination of principles, methodologies, and practical applications, it explains the transformative potential of AI-enabled Digital Twins across various facets of the manufacturing lifecycle. From design and prototyping to production and maintenance, AI-enabled Digital Twins offer multifaceted advantages that redefine traditional paradigms. By leveraging AI algorithms for data analysis, predictive modeling, and autonomous optimization, manufacturers can achieve unparalleled levels of efficiency, quality, and agility. This book explains how AI enhances the capabilities of Digital Twins by creating a powerful tool that can optimize production processes, improve product quality, and streamline operations. Note that the Digital Twin in this context is a virtual representation of a physical manufacturing system, including machines, processes, and products. It continuously collects real-time data from sensors and other sources, allowing it to mirror the physical systems behavior and performance. What sets this Digital Twin apart is the incorporation of AI algorithms and machine learning techniques that enable it to analyze and predict outcomes, recommend improvements, and autonomously make adjustments to enhance manufacturing efficiency. This book outlines essential elements, like real-time monitoring of machines, predictive analytics of machines and data, optimization of the resources, quality control of the product, resource management, decision support (timely or quickly accurate decisions). Moreover, this book elucidates the symbiotic relationship between AI and Digital Twins, highlighting how AI augments the capabilities of Digital Twins by infusing them with intelligence, adaptability, and autonomy. Hence, this book promises to enhance competitiveness, reduce operational costs, and facilitate innovation in the manufacturing industry. By harnessing AIs capabilities in conjunction with Digital Twins, manufacturers can achieve a more agile and responsive production environment, ultimately driving the evolution of smart factories and Industry 4.0/5.0. Audience: This book has a wide audience in computer science, artificial intelligence, and manufacturing engineering, as well as engineers in a variety of industrial manufacturing industries. It will also appeal to economists and policymakers working on the circular economy, clean tech investors, industrial decision-makers, and environmental professionals. 2024 Scrivener Publishing LLC. -
Blockchain for Enhancing Security and Privacy in the Smart Healthcare
The rapid digitalization of healthcare systems and the growing integration of smart technologies have made robust security and patient privacy protection critical concerns. Traditional healthcare systems struggle with maintaining the confidentiality, integrity, and accessibility of sensitive patient data. This section explores how blockchain technology can serve as a transformative solution to address these challenges and elevate security and privacy standards in smart healthcare environments. Blockchain, a decentralized and tamper-resistant distributed ledger technology, offers a novel approach to secure data sharing and storage. In the realm of smart healthcare, blockchain can establish a transparent and immutable record of patient information, medical history, and treatment plans, ensuring data integrity by thwarting unauthorized modifications and tampering. The cryptographic features inherent in blockchain provide a strong basis for safeguarding patient privacy. Smart contracts, which are programmable and self-executing scripts on the blockchain, enable precise access control, permitting only authorized entities to access specific patient data. Additionally, the utilization of decentralized identifiers (DIDs) and verifiable credentials enhances patient identity management, mitigating the risks of identity theft and unauthorized access. This section also delves into case studies and ongoing initiatives leveraging blockchain in smart healthcare applications. From electronic health records (EHRs) and interoperability to medical supply chain management, the adoption of blockchain technology showcases promising outcomes in enhancing security, transparency, and privacy. Various challenges and potential drawbacks of implementing blockchain in healthcare are also explored in this section. In conclusion, the integration of blockchain technology in smart healthcare holds significant potential for transforming data security and privacy practices. As the healthcare sector embraces digital evolution, understanding the implications and advantages of blockchain becomes crucial for constructing resilient and patient-centric healthcare ecosystems. 2024 Scrivener Publishing LLC. -
Emerging Era of Artificial Intelligence Based Chatbots: Is It Really Required to Today Generation?
The advent of AI-powered chatbots has brought about a significant wave of technological advancement, influencing different aspects of our everyday existence. This study rigorously investigates the necessity of AI-powered chatbots in the present-day generation. Although chatbots provide the possibility for increased convenience, efficiency, and accessibility, their extensive use prompts inquiries on their necessity, ethical issues, and the possible impact on human interaction and creativity. This study attempts to provide a thorough analysis of the benefits and limitations of AI chatbots, highlighting their importance and relevance in the present period. It emphasizes the necessity of a balanced approach towards integrating these digital companions. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
A study on comparisons of additive regression frailty models to counter heterogeneity: Bayesian strategies and case study
Historically, the primary goal of conventional survival study methods has been to reduce the frequency of failures over time. If the associated observed and unobserved variables are not known when studying such events, this can have detrimental effects. Frailty models offer a tempting solution for investigating the impact of unknown variables in such a case. In this article, we assume that frailty affects the hazard rate. We find that the weighted Lindley frailty models, which use general versions of the Weibull and log-logistic type II distributions as the baseline distributions, are a reliable method for ensuring the influence of endogenous variability. The parameters involved are estimated according to different loss functions using the Bayesian structure as the basis of Markov Chain Monte Carlo. Bayesian evaluation strategies are then implemented to evaluate the models. The results are demonstrated on known data of kidney infections. It is shown that the novel models outperform those based on the inverse Gaussian and gamma frailty distributions. 2024 Taylor & Francis Group, LLC. -
Theory and practice of a bivariate trigonometric Burr XII distribution
The precise modeling of bivariate continuous characteristics remains an actual challenge in probability and statistics. In this paper, we explore a new strategy based on the combination of a simple polynomial-sine copula and the Burr XII distribution. The idea is to use the oscillating functionalities of the polynomial-sine copula and the flexibility of the Burr XII distribution to propose a serious bivariate solution for the modelling of bivariate lifetime phenomena. Both theory and practice are developed. In particular, we determine the main functions related to the distribution, like the cumulative distribution function, probability density function, conditional density function, and hazard rate function, and perform a moment analysis, including various useful measures for bivariate modeling. On the practical plan, we derive the maximum likelihood and Bayes estimates for the unknown parameters. Also, the bootstrap confidence interval and the highest posterior density interval are obtained. The performance of the proposed bivariate distributions is examined using a simulation study. Finally, one data set is considered to illustrate its flexibility for real-life applications. 2023, African Mathematical Union and Springer-Verlag GmbH Deutschland, ein Teil von Springer Nature. -
On bivariate Teissier model using Copula: dependence properties, and case studies
To precisely represent bivariate continuous variables, this work presents an innovative approach that emphasizes the interdependencies between the variables. The technique is based on the Teissier model and the Farlie-Gumbel-Morgenstern (FGM) copula and seeks to create a complete framework that captures every aspect of associated occurrences. The work addresses data variability by utilizing the oscillatory properties of the FGM copula and the flexibility of the Teissier model. Both theoretical formulation and empirical realization are included in the evolution, which explains the joint cumulative distribution function F(z1,z2), the marginals F(z1) and F(z2), and the probability density function (PDF) f(z1,z2). The novel modeling of bivariate lifetime phenomena that combines the adaptive properties of the Teissier model with the oscillatory characteristics of the FGM copula represents the contribution. The study emphasizes the effectiveness of the strategy in controlling interdependencies while advancing academic knowledge and practical application in bivariate modelling. In parameter estimation, maximum likelihood and Bayesian paradigms are employed through the use of the Markov Chain Monte Carlo (MCMC). Theorized models are examined closely using rigorous model comparison techniques. The relevance of modern model paradigms is demonstrated by empirical findings from the Burr dataset. The Author(s) under exclusive licence to The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden 2024. -
A Study on Bivariate Inverse Topp-Leone Model to Counter Heterogeneous Data: Properties, Dependence Studies, Classical and Bayesian Estimation
In probability and statistics, reliable modeling of bivariate continuous characteristics remains a real insurmountable consideration. During the analysis of bivariate data, we have to deal with heterogeneity that is present in data. Therefore, for dealing with such a scenario, we investigate a novel technique based on a Farlie-Gumbel-Morgenstern (FGM) copula and the inverse Topp-Leone (ITL) model in this study. The idea is to use the oscillating functionalities of the FGM copula and the flexibility of the ITL model to propose a serious bivariate solution for the modeling of bivariate lifetime phenomena to counter the heterogeneity present in data. Both theory and practice are developed. In particular, we determine the main functions related to the model, like the cumulative model function, probability density function, and various useful dependence measures for bivariate modeling. The model parameters are estimated using the maximum likelihood method and Bayesian framework of the Markov Chain Monte Carlo (MCMC) methodology. Following that, model comparison methods are used to compare models. To explain the findings and show that better models are recommended, the famous Drought and Burr data sets are used. 2025, Thai Statistical Association. All rights reserved. -
Multiple Safety Equipment's Detection at Active Construction sites Using Effective Deep Learning Techniques
The safety of human labour is the most important thing in this era no matter where the labour force works. Governments and various NGOs focus on ensuring the delivery of the top safety to the labor class of the country. One such example is the working of the labour force at huge construction sites. For them a lot of work includes a huge amount of risks hence following full safety is the need of the hour for the workers working at construction sites. In order to deal with proper monitoring of the safety being followed at Construction sites. In order to make use of the latest technologies in this field also some of the good object detection models can be used for detecting the safety equipment of the workers which include things like Hard Hats, Masks, Vest, Boots. A lot of research is going on in improving the detection speed and accuracy of objects using state-of-the-art techniques in Computer Vision and this could lead to providing better results. Based on the available research and compute resources future work can be done to improve the results in this specific domain also. 2022 IEEE. -
Reinventing Coffee: Pandemic Lessons from Sleepy Owl Coffee
[No abstract available] -
Theorizing the Phenomenon of Women Empowerment in a Course to Discover the Purpose of Life for Marginalized Women in IndiaEvidence from Phool
The present study attempts to theorize the phenomenon of empowerment of marginalized women in the context of social enterprises involved in sustainable business practices. To extract the deeper meaning of empowerment of such women, an inductive process using Gioias method was employed by interviewing 13 marginalized women working in the social enterprise Phool. The venture is involved in recycling sacred floral waste into incense sticks, organic fertilizers, and other sustainable packaging solutions. The findings of the study were built on the Social Identity Theory, which emphasizes the fundamental need to be a part of social groups. Our findings suggest that for marginalized women, empowerment manifests in dignity and honour, economic sovereignty and social admittance and embracement. The study contributes to the extant literature on womens empowerment by intersecting with the phenomenon of marginalization in the context of social enterprise and explains how marginalized women experience empowerment at work. 2023 Birla Institute of Management Technology. -
Frustration Tolerance among Indian Youth: Exploring its relationship with Gratitude and Self Awareness
Introduction: For any person, adulthood is a difficult era of life filled with uncontrollable frustrations. The move from adolescence to young adulthood has reverberation as it marks a shift from adolescent's dependency to the chores and independence of young adulthood (Boll, 2017). Upon review, it was found that many researchers have established the effects of frustration, however, there is little research and evidence-based practice utilizing positive psychology interventions to target low frustration tolerance in youth. A vast body of research have established the positive consequences of gratitude and self awareness in one's life. The present study aims to explore the relationship between gratitude, self awareness and frustration tolerance among young adults. Methodology: Participants were selected through purposive sampling method. Data were collected from 167 young Indian adults (Females-94, Males-73) aged 19-35 years. Participants completed the three inventories measuring the variables of interest using the online survey forms. Data were analyzed by the SPSS software using descriptive analysis, correlation coefficients, and linear regression. Results: Findings show no significant relationship between gratitude and frustration tolerance (r=-0.071). However, there is a significant positive correlation of self awareness with frustration tolerance (r=0.271). The regression model showed that 7.3% of variance in frustration tolerance can be predicted by self awareness. Conclusion: Thus, self-awareness can be viewed as one of the important factors that impact frustration tolerance. The findings are consistent with previous research that has shown that self-awareness has important effects on performance, and emotions. Future implications are discussed. 2022 RESTORATIVE JUSTICE FOR ALL. -
Artificial Intelligence-Enabled Digital Twin for Smart Manufacturing
An essential book on the applications of AI and digital twin technology in the smart manufacturing sector. In the rapidly evolving landscape of modern manufacturing, the integration of cutting-edge technologies has become imperative for businesses to remain competitive and adaptive. Among these technologies, Artificial Intelligence (AI) stands out as a transformative force, revolutionizing traditional manufacturing processes and making the way for the era of smart manufacturing. At the heart of this technological revolution lies the concept of the Digital Twin-an innovative approach that bridges the physical and digital realms of manufacturing. By creating a virtual representation of physical assets, processes, and systems, organizations can gain unprecedented insights, optimize operations, and enhance decision-making capabilities. This timely book explores the convergence of AI and Digital Twin technologies to empower smart manufacturing initiatives. Through a comprehensive examination of principles, methodologies, and practical applications, it explains the transformative potential of AI-enabled Digital Twins across various facets of the manufacturing lifecycle. From design and prototyping to production and maintenance, AI-enabled Digital Twins offer multifaceted advantages that redefine traditional paradigms. By leveraging AI algorithms for data analysis, predictive modeling, and autonomous optimization, manufacturers can achieve unparalleled levels of efficiency, quality, and agility. This book explains how AI enhances the capabilities of Digital Twins by creating a powerful tool that can optimize production processes, improve product quality, and streamline operations. Note that the Digital Twin in this context is a virtual representation of a physical manufacturing system, including machines, processes, and products. It continuously collects real-time data from sensors and other sources, allowing it to mirror the physical systems behavior and performance. What sets this Digital Twin apart is the incorporation of AI algorithms and machine learning techniques that enable it to analyze and predict outcomes, recommend improvements, and autonomously make adjustments to enhance manufacturing efficiency. This book outlines essential elements, like real-time monitoring of machines, predictive analytics of machines and data, optimization of the resources, quality control of the product, resource management, decision support (timely or quickly accurate decisions). Moreover, this book elucidates the symbiotic relationship between AI and Digital Twins, highlighting how AI augments the capabilities of Digital Twins by infusing them with intelligence, adaptability, and autonomy. Hence, this book promises to enhance competitiveness, reduce operational costs, and facilitate innovation in the manufacturing industry. By harnessing AIs capabilities in conjunction with Digital Twins, manufacturers can achieve a more agile and responsive production environment, ultimately driving the evolution of smart factories and Industry 4.0/5.0. Audience: This book has a wide audience in computer science, artificial intelligence, and manufacturing engineering, as well as engineers in a variety of industrial manufacturing industries. It will also appeal to economists and policymakers working on the circular economy, clean tech investors, industrial decision-makers, and environmental professionals. 2024 Scrivener Publishing LLC. -
Blockchain for Enhancing Security and Privacy in the Smart Healthcare
The rapid digitalization of healthcare systems and the growing integration of smart technologies have made robust security and patient privacy protection critical concerns. Traditional healthcare systems struggle with maintaining the confidentiality, integrity, and accessibility of sensitive patient data. This section explores how blockchain technology can serve as a transformative solution to address these challenges and elevate security and privacy standards in smart healthcare environments. Blockchain, a decentralized and tamper-resistant distributed ledger technology, offers a novel approach to secure data sharing and storage. In the realm of smart healthcare, blockchain can establish a transparent and immutable record of patient information, medical history, and treatment plans, ensuring data integrity by thwarting unauthorized modifications and tampering. The cryptographic features inherent in blockchain provide a strong basis for safeguarding patient privacy. Smart contracts, which are programmable and self-executing scripts on the blockchain, enable precise access control, permitting only authorized entities to access specific patient data. Additionally, the utilization of decentralized identifiers (DIDs) and verifiable credentials enhances patient identity management, mitigating the risks of identity theft and unauthorized access. This section also delves into case studies and ongoing initiatives leveraging blockchain in smart healthcare applications. From electronic health records (EHRs) and interoperability to medical supply chain management, the adoption of blockchain technology showcases promising outcomes in enhancing security, transparency, and privacy. Various challenges and potential drawbacks of implementing blockchain in healthcare are also explored in this section. In conclusion, the integration of blockchain technology in smart healthcare holds significant potential for transforming data security and privacy practices. As the healthcare sector embraces digital evolution, understanding the implications and advantages of blockchain becomes crucial for constructing resilient and patient-centric healthcare ecosystems. 2024 Scrivener Publishing LLC. -
Engineering applications of blockchain in this smart era
The advent of blockchain technology has revolutionized various industries, offering novel solutions to age-old problems. In this smart era, characterized by interconnected devices and burgeoning digital ecosystems, blockchain stands out as a transformative force. This chapter explores the emerging applications of blockchain technology in this paradigm shift towards smart systems. One prominent application of blockchain lies in the domain of decentralized finance (DeFi). Blockchain facilitates peer-to-peer transactions, eliminating the need for intermediaries like banks. Smart contracts, powered by blockchain, automate and execute agreements, enabling programmable finance, lending, and asset management. Moreover, blockchain's transparency and immutability enhance trust in financial transactions, fostering financial inclusion and security. In the realm of SCM, blockchain offers unprecedented transparency and traceability. By recording every transaction on an immutable ledger, blockchain enables users to track the journey of products from raw materials to end consumers. 2024, IGI Global. All rights reserved.