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Revisiting Television in India: Mapping the Portrayal of Women in Soap Operas
This article attempts to map the portrayal of women in popular soap operas on television in India. It begins with the discourses around portrayal of women on Doordarshan in the pre-liberalisation era and goes on to analyse a few soap operas in the past one decade. With substantive review of visual texts, it aims to disprove the claim that there is a paradigm shift especially with respect to the portrayal of women in the contemporary and so-called progressive soap operas. It concludes by comparing all the phases of development of television in India with respect to construction of women and stating how very little and inconsequential change has occurred in this regard in spite of all the efforts from the state and the intellectual community. 2018 Indian Sociological Society. -
Revisiting television in India: Mapping the portrayal of women in soap operas /
Sociological Bulletin, Vol.67, Issue 2, pp. 204-219. -
Revisiting the efficacy of policies in the Indian primary healthcare sector: Interventions and approaches during the COVID-19 pandemic
The COVID-19 pandemic has wracked even the most modern healthcare systems worldwide and has influenced Indias healthcare sector and vastly affected the governments and corporate stakeholders healthcare reform plans; hence, this chapter is intended to unfold the paradigm shift in Indias primary healthcare industry due to the pandemic in the last one and half years. This chapter described Indias experience with the coronavirus during the first and second waves and tried examining the public health difficulties in the COVID era. It provides a timeline of significant events of the pandemics growth in India and worldwide and how India responded to the situations through their economic and healthcare policies. We also go through some of the pandemics impacts and Indias recovery approach and strategies for its revival. All possibly available secondary data like Scopus, Web of Science, Medline/PubMed, and Google Scholar search engines, newspapers, government websites, etc., were excavated to meet this purpose; secondary sources were used to analyze the data. This chapter also examined the effect of COVID-19 on healthcare workers in India. This chapter critically examined the primary healthcares role during this pandemic and the governments policies and processes to deal with COVID-19 and any other unforeseen situations which the country may encounter in the future. 2022 Elsevier Inc. All rights reserved. -
Revisiting the Nexus Between Suicides and Economic Indicators: An Empirical Investigation
In India, as of 2021, there was a 7.2% increase in suicides. With the economic burden inflicted by the pandemic and increasing suicides, a systematic investigation needs to be done. This empirical investigation uses the Autoregressive Distributed Lag (ARDL) model to obtain long and short-term estimates for the relationship between suicides and prominent economic indicators. The findings suggest that economic indicators like GDP per capita growth, age dependency ratio, and unemployment rate have a significant dynamic relationship with suicides. In this regard, preventive measures can be formulated and implemented in such a way that focuses on improving the countrys economic scenario which will in turn reduce suicides. Organizations and governments can plan training and mental health care programs for farmers, workers, and students. Mental health care services require attention from the government so that at a macro level the problem of increasing suicides can be handled. The Author(s), under exclusive license to Springer Nature Switzerland AG. 2024. -
Revisiting the PushPull Tourist Motivation Model: A Theoretical and Empirical Justification for a ReflectiveFormative Structure
This study introduces a novel reflectiveformative hierarchical model specification for the classic pushpull tourist motivation construct, aligning its measurement with the theoretical distinction between intrinsic push drives and external pull attributes. Unlike the traditional reflective-reflective structuring of tourist motivation we defied the higher order factors (novelty, knowledge and facilities as formative. Using partial least squares structural equation modeling (PLS-SEM) on a purposive sample of 319 international tourists, we empirically validate the reflectiveformative (reflective first-order, formative second-order) model. The reflectiveformative model showed a superior fit and predictive power: it explained substantially more variance in key outcome constructs (social motives (R2 = 53.60) and self-actualization (R2 = 23.10)) than the traditional reflectivereflective specification (social motives (R2 = 49.30) and self-actualization (R2 = 21.70)), which is consistent with best-practice guidelines for theoretically grounded models. In contrast, the incorrectly specified reflectivereflective model showed stronger effects between unrelated constructs, supporting concerns that choosing the wrong type of measurement model can lead to incorrect conclusions. By reconciling the pushpull theory with measurement design, this works main contributions are a theoretically justified reflectiveformative model for tourist motivation, and evidence of its empirical benefits. These findings highlight a methodological innovation in motivation modeling and underscore that modeling pushpull motives formatively yields more accurate insights for theory and practice. 2025 by the authors. -
Revisiting the trade opennessunemployment nexus: anapplication of the novel JKS panel causality test with static anddynamic panel models
Purpose: This paper documents a robust empirical regularity: higher trade openness is associated with a lower unemployment rate. This paper also examines whether or not the effects of trade liberalisation depend on countries' income levels. Further, the dynamic causation between trade openness and unemployment is also examined. Design/methodology/approach: In order to obtain insight into the opennessunemployment nexus, following empirical methods were utilised - static panel models, dynamic panel models and a novel panel Granger causality approach proposed by Juodis etal. (2021). Findings: Results suggest that openness negatively affects unemployment; the extent to which trade liberalisation affects unemployment depends on the income level of each country. The Juodis, Karavias, and Sarafidis (JKS) test confirmed that the past values of trade openness, inflation, foreign direct investment and gross domestic product per capita contain information that helps to predict unemployment in a more robust manner. To simply put, opening upto trade may eventually become a requirement for creating more job opportunities, but this alone may not be enough. The extent to which nations benefit from trade liberalisation is largely dependent on the overall economic conditions and their capability to move up the income scale. Originality/value: A major difference between this study and those performed previously is that this study does not only examine the impact of trade openness on unemployment, but also investigates whether the unemployment effect of liberalisation is affected by countries' income levels an issue that has received little attention in the past. Additionally, the unique panel non-causality approach put forth by Juodis etal. (2021) is used in the first instance to look into the causal link between trade openness and unemployment. This method has advantages in that the method enables capturing Granger-causality in homogeneous or heterogeneous panels amongst multiple variables. 2023, Emerald Publishing Limited. -
Revisiting wideband pulsar timing measurements
In the wideband paradigm of pulsar timing, the time of arrival of a pulsar pulse is measured simultaneously with the corresponding dispersion measure from a frequency-resolved integrated pulse profile. We present a new method for performing wideband measurements that rigorously accounts for measurement noise. We demonstrate this method using observations of PSR J2124?3358 made as part of the Indian Pulsar Timing Array experiment using the upgraded Giant Metre-wave Radio Telescope, and show that our method produces more realistic measurement uncertainty estimates compared to the existing wideband measurement method. The Author(s) 2026. Published by Oxford University Press on behalf of Royal Astronomical Society. -
Revitalizing education: A roadmap for school transformation
Educational equity, school transformation, and policy and practice alignment are crucial in the evolution of educational systems. It requires an all-encompassing comprehension that transcends historical contexts, technological impacts, and conceptual frameworks to address students' varied requirements and eliminate inequalities. Acknowledging educational equity as a moral imperative underscores the ethical obligation of stakeholders. School transformation necessitates the presence of forward-thinking administrators, the active involvement of stakeholders, and a comprehensive reassessment. A cohesive approach to equity requires the utilization of robust frameworks, ongoing professional development, and continuous assessment to align policy and practice. Overcoming obstacles requires confronting opposition, capitalizing on technological advancements, deriving lessons from past failures, and establishing the foundation for a future characterized by greater inclusivity. 2024, IGI Global. All rights reserved. -
Revitalizing language acquisition journey: A multidisciplinary approach to combat burnout
This chapter presents an all-encompassing strategy for combating digital fatigue in second language acquisition (SLA). It examines digital exhaustion's symptoms, causes, and psychological effects, emphasizing the need for healthy digital practices. Excessive use of technology, such as language applications and social media, can exacerbate exhaustion and necessitate self-care and stress management. Learners should prioritize their well-being by engaging in self-reflection, relaxation, and non-language activities, including mindfulness and meditation. Instructors are essential for fostering supportive environments incorporating feedback and a development mindset. Peer participation fosters community and reduces fatigue. This comprehensive strategy engages learners, instructors, parents, and peers to ensure a successful SLA journey in the digital age, with well-being at its core. 2023, IGI Global. -
Revocable and Secure Multi-Authority Attribute-Encryption Scheme
Security is an important factor as nowadays many systems generates and process huge amount of data. This also leads many of us to rely on a third-party service provider for storing sensitive and confidential data. Providing outsourcing means the data owner will encrypt and store the data in a third-party storage system. In this paper, we are proving solutions for two main problems. The first issue is what if the attribute authority itself can access the data because the attributes and secret keys are known by attribute. This issue is called the key escrow problem. For solving it we are proposing a multi-authority system with Elliptic Curve Cryptography. The second issue that we addressed in this paper is the revocation problem, which means when someone leaves the system should be prohibited from accessing subsequent data this is called forward security and as a second case when someone joins the system should be prevented from accessing previous shared date this is called backward security. In this paper, we address both forward and backward security. For solving this problem we are using the concept of the Lagrange interpolation technique for generating and verifying secret keys. Based on this technique secret key will be dynamically altered and used for encryption and due to this can achieve greater security. 2023, Ismail Saritas. All rights reserved. -
Revolution of the Indian Agricultural Landscape using Machine Learning and Big Data Techniques: A Systematic Review
The world of Big Data has been rapidly expanding into the domains of Engineering and Machine Learning. The biggest challenge in the Big Data landscape is the incompetence of processing vast amounts of data in a time-efficient manner. The agriculture domain has so long only relied on traditional method for yield prediction. This can be bettered by using novel Machine Learning techniques and innovative thinking. The study provides the review of most of the techniques already implemented in the ML, Big Data and Agriculture domain- traditional and modern- while focusing on highlighting the difference in accuracy between the traditional methods and the more advanced methods. 2022 IEEE. -
Revolutionising Tumour Diagnosis: How Clinical Application of Artificial Intelligence and Machine Learning Enhances Accuracy and Efficiency
This research paper examines the transformative influence of Artificial Intelligence (AI) and Machine Learning (ML) on tumour diagnosis within clinical settings. The advent of AI and ML technologies has revolutionised the field of oncology, offering the unprecedented potential for more accurate, timely, and personalised cancer detection. By leveraging vast datasets of medical images, genomic information, and patient records, these intelligent systems enable the early identification of tumours, classification of cancer types, and prediction of patient outcomes with remarkable precision. This paper delves into the mechanisms through which AI and ML algorithms analyse complex data, highlighting their ability to detect subtle patterns and anomalies that may escape human perception. Moreover, we examine the successful integration of these technologies into clinical workflows, their potential to reduce diagnostic errors, and the implications for patient care and outcomes. As AI and ML continue to emerge, the synergy between technology and clinical expertise promises to enhance tumour diagnosis, ultimately contributing to more effective and personalised cancer treatments. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Revolutionizing Arrhythmia Classification: Unleashing the Power of Machine Learning and Data Amplification for Precision Healthcare
This paper presents a comprehensive exploration of arrhythmia classification using machine learning techniques applied to electrocardiogram (ECG) signals. The study delves into the development and evaluation of diverse models, including K-Nearest Neighbors, Logistic Regression, Decision Tree Classifier, Linear and Kernelized Support Vector Machines, and Random Forest. The models undergo rigorous analysis, emphasizing precision and recall due to the categorical nature of the dependent variable. To enhance model robustness and address class imbalances, Principal Component Analysis (PCA) and Random Oversampling are employed. The results highlight the effectiveness of the Kernelized SVM with PCA, achieving a remarkable accuracy of 99.52%. Additionally, the paper discusses the positive impact of feature reduction and oversampling on model performance. The study concludes with insights into the significance of PCA and Random Oversampling in refining arrhythmia classification models, offering potential avenues for future research in healthcare analytics. 2024 IEEE. -
Revolutionizing Biodegradable and Sustainable Materials: Exploring the Synergy of Polylactic Acid Blends with Sea Shells
This study explores the mechanical properties of a novel composite material, blending polylactic acid (PLA) with sea shells, through a comprehensive tensile test analysis. The tensile test results offer valuable insights into the materials behavior under axial loading, shedding light on its strength, stiffness, and deformation characteristics. The results suggest that the incorporation of sea shells decrease the tensile strength of 14.55% and increase the modulus of 27.44% for 15 wt% SSP (sea shell powder) into PLA, emphasizing the reinforcing potential of the mineral-rich sea shell particles. However, a potential trade-off between decreased strength and reduced ductility is noted, highlighting the need for a delicate balance in material composition. The study underscores the importance of uniform sea shell particle distribution within the PLA matrix for consistent mechanical performance. These results offer a basis for additional PLA-sea shell blend optimization, directing future efforts to balance strength, flexibility, and other critical attributes for a range of applications, including biomedical devices and sustainable packaging. This investigation opens the door to more sustainable and mechanically strong materials in the field of additive manufacturing by demonstrating the positive synergy between nature-inspired materials and cutting-edge testing techniques. 2024 The Authors. -
Revolutionizing Circular Business Practices with Waste Reduction and Resource Optimization
The concept of the circular economy (CE) offers a transformative solution to pressing global challenges such as resource depletion, waste generation, and environmental degradation. By shifting from the traditional linear take-make-dispose model to a closed-loop system, the CE principles aim to enhance resource efficiency and sustainability. This paper proposes a Waste Reduction and Resource Optimization (WRRO)-oriented circular business model, offering a comprehensive theoretical framework to guide businesses in optimizing resource utilization and reducing waste. Through the exploration of academic literature and a practical case study, the paper illustrates how businesses can effectively transition to circular business models. It also addresses the challenges businesses face during implementation, providing actionable insights for both theory and practice. The papers key contribution lies in integrating circular economy principles with resource efficiency strategies, offering a novel approach that supports both environmental sustainability and economic performance. 2025 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Revolutionizing education with AI: ChatGPT as a personalized virtual tutor for E-learning platforms
It integrates AI into learning environments, which is transforming the conventional and online learning environment by coming up with something groundbreaking in the way of a personalized virtual tutor known as ChatGPT. The chapter looks into how ChatGPT uses the sophisticated natural language processing to present tailormade learning experiences to suit the different preferences, paces, and requirements of individual students. The instant explanations, feedback, and support on diverse subjects increase the engagement, motivation, and ultimate educational success of the students. The chapter also presents practical insights on technical integration, data security, and ethical considerations to ensure accountable use. It emphasizes the importance of combining AI with human oversight in creating balanced educational solutions. Through many examples and case studies, it demonstrates how ChatGPT is capable of connecting old learning methods with modern e- learning, thereby encouraging stakeholders to consider AI for greater personalization and transformation in education. 2026 by IGI Global Scientific Publishing. All rights reserved. -
Revolutionizing Education: Evaluating the Impact of AI and Ed Tech Tools on Learning Outcomes
The rapid evolution of artificial intelligence (AI) and educational technology (EdTech) tools is significantly transforming teaching and learning processes across the globe. This chapter seeks to critically examine the impact of Al-driven platforms and digi-tal learning tools on educational outcomes, learner engagement, and pedagogicalpractices. By exploring empirical evidence, theoretical frameworks, and real-world implementations, this chapter aims to provide a comprehensive understanding of how Al and EdTech tools are reshaping personalized learning, assessment, student support, and teacher facilitation. Particular emphasis will be given to the effectiveness of these tools in diverse educational contexts, including challenges related to accessibility, ethical considerations, and the digital divide. The chapter will also present recommendations for integrating Al and EdTech in ways that are pedagog-ically sound, inclusive, and outcome-focused. 2026 by IGI Global Scientific Publishing. All rights reserved. -
Revolutionizing healthcare telemedicine's global technological integration
The pursuit of universal and high-quality healthcare services is a fundamental obligation of any responsible state, yet India faces persistent challenges in achieving this goal despite governmental efforts and policies. Notably, the 65th World Health Assembly emphasized universal health coverage (UHC) as pivotal for global public health advancement. Addressing this, a 2010 high-level expert group identified impediments in UHC implementation, highlighting issues such as health financing, infrastructure, skilled human resources, and access to medicines. This study focuses on exploring telemedicine's potential to mitigate these challenges and become instrumental in realizing universal health coverage in India. It aims to scrutinize government plans, critically assess policies on telemedicine implementation, and propose effective integration models, particularly in rural areas, to facilitate UHC. Additionally, the research aims to examine the role of AI, ML, deep learning, and neutral networks within telemedicine, envisaging their contribution to augmenting telemedicine's efficacy towards achieving universal health coverage in India. 2024, IGI Global. All rights reserved.