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Diabetic Retinopathy Detection Using Various Machine Learning Algorithms
The advances in technologies have paved the way to generate huge amounts of data in a variety of forms. Machine learning techniques, accompanied by Artificial Intelligence with its challenging nature help in extracting meaningful information from such data. This will have a great impact on many sectors, such as social media analytics, construction and healthcare, etc. Computer-aided clinical decision-making plays a vital role in todays medical field. Hence, a high degree of accuracy with which machine learning algorithms can detect diabetic retinopathy is really in demand. Convolutional neural networks, a deep learning technique, have been used to recognize pathological lesions from images. Image processing and analytics methods are used and have been trained to recognize the significant complications of diabetes, which cause damage to the retina, diabetic retinopathy (DR). Though this condition does not show any symptoms in its early stages, it has to be screened, diagnosed and treated at the earliest or it may lead to blindness. Deep neural networks have proved successful in screening DR from retinal images and handling the risks that may arise due to the disease. This chapter focuses on detecting diabetic retinopathy in retinal images by using efficient image processing and deep learning techniques. It also attempts to investigate the requirements of image pre-processing techniques for diabetic retinopathy. Experiments are carried out by taking a set of retinal images and predicting the level of diabetic retinopathy on a scale of 0 to 4. Deep learning techniques like CNN and DenseNet are applied and tested. 2024 Taylor & Francis Group, LLC. -
A stakeholder theory approach to analysing strategies for improving pandemic vaccine supply chain performance
This study aims to formulate strategies that impact the vaccine supply chain (VSC). This study measures the VSC performance using the proposed strategy concerning stakeholders theory. From the literature review and experts consent, the strategies are classified into six broad strategies as-VSC traceability, VSC visibility, VSC velocity, digitalising VSC, localising VSC, and vaccine inventory. A questionnaire is developed for surveying healthcare organisations and hospitals. All six proposed hypotheses got accepted. The developed model satisfies all the model fit parameters. Strategies like VSC traceability, VSC visibility, VSC velocity, digitalising VSC, localising VSC, and vaccine inventory have positively impacted vaccine supply chain performance. This research will be helpful for healthcare professionals and organisations for the faster delivery of the vaccine. This research will also help policymakers in improving the performance of VSC. This study is also the first to use the stakeholder theory approach for measuring VSC performance. Copyright 2024 Inderscience Enterprises Ltd. -
Implementation of vendor-managed inventory in hospitals: an empirical investigation
This research aims to determine critical success components for implementing the vendor-managed inventory (VMI) and test their influence on the inventory in Indian hospitals. The independent and dependent components of the research are identified from the extensive literature review. The independent variables are top management commitment, supply chain strategy, business process integration, continuous improvement, resource sharing, and information technologies adoption. The dependent variable identified is the adoption of vendor-managed inventory. The study results suggest that the proposed latent variables significantly impact the VMI and significantly contribute to VMIs implementation and sustainability. The study highlights the importance of VMI in Indian hospitals, and therefore, it will help the management focus on the VMI for enhanced operational efficiency. Previous studies have not empirically tested the impact of the suggested practices for VMI in Indian hospitals. The analysis would help evaluate VMI adoption in Indian hospitals. Copyright 2024 Inderscience Enterprises Ltd. -
Analysis of factors impacting firm performance of MSMEs: lessons learnt from COVID-19
Purpose: The micro, small and medium scale enterprises (MSMEs) faced various challenges in the ongoing COVID-19 pandemic, making it challenging to remain competitive and survive in the market. This research develops a model for MSMEs to cope with the current pandemic's operational and supply chain disruptions and similar circumstances. Design/methodology/approach: The exhaustive literature review helped in identifying the constructs, their items and five hypotheses are developed. The responses were collected from the experts working in MSMEs. Total 311 valid responses were received, and the structural equation modeling (SEM) approach was used for testing and validating the proposed model. Findings: Critical constructs identified for the study are-flexibility (FLE), collaboration (COL), risk management culture (RMC) and digitalization (DIG). The statistical analysis indicated that the four latent variables, flexibility, digitalization, risk management culture and collaboration, contribute significantly to the firm performance of MSMEs. Organizational resilience (ORS) mediates the effects of all the four latent variables on firm performance (FP) of MSMEs. Practical implications: The current study's findings will be fruitful for the manufacturing MSMEs and other firms in developing countries. It will enable them to identify the practices that significantly help in achieving the firm performance. Originality/value: The previous researches have not considered the effect of organizational resilience on the firm performance of MSMEs. This study attempts to fill this gap. 2022, Emerald Publishing Limited. -
Psychometric Properties of the Interpersonal Emotion Regulation Questionnaire Among Couples in India
The aim of the present study was to translate the Interpersonal Emotion Regulation Questionnaire (IERQ) into the Tamil language and examine its psychometric properties in the Indian cultural context. Data were collected from a dyadic sample of 340 married heterosexual couples (N = 680) currently residing in India. The mean age of husbands was 39.57 (SD = 6.10; 26 ? range ? 58), and the wives was 35.33 (SD = 5.72; 23 ? range ? 54). Descriptive results indicated that husbands and wives reported similar levels of interpersonal emotion regulation. Confirmatory factor analysis showed a 20-item model with four factorsenhancing positive affect, perspective-taking, soothing and social modeling, similar to the original version, fits the data well. Furthermore, the multiple-group analysis indicated robust measurement invariance across gender (husbands vs. wives), family type ( joint vs. nuclear) and marriage type (arranged vs. love), indicating that the Tamil version of the IERQ operates similarly across these groups. Besides, the Tamil version of the IERQ showed good convergent and discriminant validity with measures of dyadic coping and relationship satisfaction. Implications for research and couples therapy in the Indian cultural context are discussed. 2022, PsychOpen. All rights reserved. -
Investor behaviour, market efficiency, and regulatory challenges in digital currency investments: A comprehensive literature review
The rapid proliferation of digital currencies has ignited significant interest in understanding investor behaviour and the regulatory challenges within this evolving financial landscape. The study seeks to elucidate the factors that influence investor behaviour in the cryptocurrency/digital currency market and explore the regulatory implications associated with digital currency investments. A systematic approach was adopted to identify, review, and analyze relevant scholarly articles from reputable databases. The selected articles span various dimensions of the cryptocurrency/digital currency ecosystem, including investor behaviour, market efficiency, technological innovation, and regulatory measures. It reveals that investor behaviour in the digital currency market is influenced by a complex interplay of emotions, market sentiment, and information asymmetry. Additionally, market efficiency theories are being reconsidered in light of the highly volatile nature of cryptocurrencies. Regulatory challenges encompass issues related to fraud, pump-and-dump schemes, and legal ambiguity. 2024, IGI Global. All rights reserved. -
Initial coin offerings as a form of alternative financing for start-ups: A systematic literature review and bibliometric analysis
This chapter aims to provide a comprehensive overview of the field of initial coin offerings ICOs as a form of alternative financing for start-ups. Through a systematic literature review and bibliometric analysis, the study explores the current understanding of ICOs, the potential uses of fractional ownership of digital assets, and the opportunities and challenges associated with this form of fundraising. The study also highlights the importance of study, which provided the first comprehensive explanation of ICOs and their characteristics. The findings of the research suggest that ICOs have the potential to revolutionize the way start-ups raise funds, but they also present significant challenges and risks. The study encourages further research to continue exploring the opportunities and challenges presented by ICOs, as well as the potential impact of regulatory and legal frameworks on the ICO market. Overall, this chapter provides valuable insights into the complex and evolving topic of ICOs and their implications for start-ups, investors, and the broader economy. 2024, IGI Global. All rights reserved. -
A study of mediating factors influencing student motivation and behaviour: A literature review
This study aims to examine the mediating factors of learning environment, technology, good behaviour, and effective communication, sports, media, problem-based case study, and psychological influence on student motivation and behaviour. The study employs secondary data based on peer-reviewed articles, conference papers, and books collected from a variety of sources such as Scopus, WoS, J-Store, EBSCO, ProQuest, etc. between 1982 and 2022. The 103 articles have been selected based on the keywords which related to study. The results evidenced that the mediating factors have a significant positive impact on student motivation and behaviour. This study contributes to the existing literature by providing a com- prehensive understanding of the relationship between the mediating factors and student motivation and behaviour. The findings of this study have implications for educational institutions, policy makers, and educators in creating effective learning environments that can enhance student motivation and behaviour. 2023, IGI Global. All rights reserved. -
Driving sustainable development through climate finance in India: A case study of the National Clean Energy Fund (NCEF)
This case study examines the national clean energy fund (NCEF) as a climate finance policy in India. The NCEF was established with the objective of promoting renewable energy projects and sustainable development in the country. The study explores the background and context of climate finance, providing an overview of the NCEF's goals and implementation. The case study analyzes the impact of the NCEF by examining its funding allocations and utilization over the years. It highlights the challenges faced in effectively utilizing the funds, such as administrative hurdles, limited capacity, policy uncertainties, project development barriers, financial constraints, and governance issues. Furthermore, the case study discusses the socio-economic impacts of the NCEF, including job creation, clean energy adoption, and environmental benefits. It also explores the lessons learned from the NCEF implementation, identifying areas for improvement and providing recommendations for enhancing climate finance mechanisms in India. This chapter creates a contribution to renewable energy development in India. 2023, IGI Global. All rights reserved. -
Accounting fraud and bankruptcy: The case of wirecard AG
This chapter examines the scandal at Wirecard AG, a German payment processing and financial services company, that became one of the most valuable companies on the German stock exchange in the 2010s. From 2010 to 2018, Wirecard reported consistent revenue growth and profitability. In 2019, the company reported revenues of 2.8 billion ($3.2 billion). As of September 2018, its market capitalization was over 24 billion ($27 billion). In late 2019, the Wirecard scandal was discovered through investigative reports by the Financial Times, which raised questions about Wirecard's accounting practices. The company faced a major scandal in 2020 when it was revealed that 1.9 billion ($2.1 billion) was missing from its balance sheet. Subsequent investigations revealed a massive accounting fraud that had been going on for years. Subsequently, the company filed for bankruptcy. Multiple Wirecard executives, including its CEO, were charged with fraud and market manipulation. German regulators and auditors were criticized for failing to detect and prevent the fraud. 2023, IGI Global. -
Exploring the influence of emotional intelligence on decision-making across diverse domains: A systematic literature review
Emotional intelligence (EI) is increasingly recognized as a crucial factor in decisionmaking across various professional domains. This systematic literature review, covering the period from 2017 to 2023, explores the intricate relationship between EI and decision-making in healthcare, business, education, ethics, and the realms of neuroscience and artificial intelligence (AI). Employing a qualitative research design, the study systematically analyzes articles retrieved from renowned databases including Scopus, ProQuest, EBSCO, J Gate, and Google Scholar. The findings reveal that elevated EI levels among healthcare professionals lead to improved clinical decision-making, characterized by enhanced patient-centered care and ethical considerations. In business and legal contexts, EI competencies are associated with ethical decision-making, effective leadership, and strong client relationships. In education, emotionally intelligent educators create supportive learning environments conducive to better pedagogical decisions and student emotional well-being. 2024, IGI Global. All rights reserved. -
A case study on a beacon of hope transition: India's renewable energy integration and the Ujwal DISCOM assurance Yojana (UDAY)
This case study examines the transformative impact of the Ujwal DISCOM Assurance Yojana (UDAY) on India's energy landscape, focusing on its role in facilitating renewable energy integration. India's energy sector faced daunting challenges, including financially distressed power distribution companies (DISCOMs) and high aggregate technical and commercial (AT&C) losses. UDAY's financial restructuring and operational efficiency improvements led to remarkable reductions in DISCOMs' debt burdens and AT&C losses, respectively. The policy aligned with India's renewable energy goals, driving DISCOMs to procure renewable energy sources. Consequently, India witnessed significant growth in its renewable energy capacity, environmental benefits through reduced emissions, and economic growth via job creation. This case study offers insights into the challenges faced, technological advancements incentivized, and the long-term sustainability of these reforms. Moreover, it presents broader lessons for energy sector reform and renewable energy integration, both within India and globally. 2024, IGI Global. All rights reserved. -
Mapping the AI landscape in healthcare quality: A bibliometrics analysis
This study explores the application of Artificial Intelligence (AI) in healthcare quality improvement through a bibliometric analysis of 222 documents retrieved from the Scopus database using the keywords "healthcare," "quality," and "AI." By examining bibliographic coupling, citations, co-citations, author keywords, and co-occurrence networks, the research unveils the key themes, prominent authors, and emerging trends in this field. The analysis reveals a focus on areas like machine learning for disease prediction, clinical decision support systems, and patient safety improvement. Leading authors and research groups are identified, and promising future directions such as explainable AI and integration with electronic health records are highlighted. This study contributes to understanding the current landscape of AI in healthcare quality improvement and guiding future research for maximizing its impact. 2024, IGI Global. All rights reserved. -
Predicting cryptocurrency prices model using a stacked sparse autoencoder and Bayesian optimization
In recent years, digital currencies, also known as cybercash, digital money, and electronic money, have gained significant attention from researchers and investors alike. Cryptocurrency has emerged as a result of advancements in financial technology and has presented a unique opening for research in the field. However, predicting the prices of cryptocurrencies is a challenging task due to their dynamic and volatile nature. This study aims to address this challenge by introducing a new prediction model called Bayesian optimization with stacked sparse autoencoder-based cryptocurrency price prediction (BOSSAE-CPP). The main objective of this model is to effectively predict the prices of cryptocurrencies. To achieve this goal, the BOSSAE-CPP model employs a stacked sparse autoencoder (SSAE) for the prediction process and resulting in improved predictive outcomes. The results were compared to other models, and it was found that the BOSSAE-CPP model performed significantly better. 2023, IGI Global. -
Prediction and analysis of financial crises using machine learning
This study presents a comparative analysis of various machine learning algorithms for credit risk assessment. The algorithms were tested on two credit datasets: German Credit Dataset and Australian Credit Dataset. The performance of the algorithms was evaluated based on several metrics, including sensitivity, specificity, accuracy, F-score, and Kappa. The results showed that the FCPFS-QDNN algorithm outperformed other algorithms in both datasets, achieving high accuracy, sensitivity, specificity, and F-score. On the other hand, the ACO Algorithm and Multilayer Perceptron algorithms were found to perform poorly in both datasets. The findings of this study have significant implications for credit risk assessment in banking and financial institutions. The study recommends the use of the FCPFS-QDNN algorithm for credit risk assessment due to its superior performance compared to other algorithms. 2023, IGI Global. All rights reserved. -
Dynamic strategies and evolutionary trajectories: A comprehensive review of experiential marketing in the soft drink industry
This comprehensive review explores the evolution of experiential marketing in the soft drink industry from 2005 to 2024. It uses analysis from a diverse set of 62 scholarly articles, Google books, Google Scholar, SSRN, Fig share, and various publishers such as Taylor & Francis, IGI Global, and Springer. The study traces the industry's trajectory from traditional marketing approaches to a digital-centric paradigm. The research captures pivotal moments in the development of experiential marketing strategies, emphasizing the integration of technology, sustainability, and community engagement. Key findings highlight the industry's adaptability to changing consumer preferences, the strategic use of data-driven insights, and the importance of inclusivity in crafting compelling brand narratives. The study identifies overarching trends, challenges, and opportunities that shaped the experiential marketing landscape in the soft drink industry over the past two decades. 2024, IGI Global. All rights reserved. -
Does gamification affect customer brand engagement and brand value co-creation?
The study examines the relationship between gamification and customer brand engagement, focusing on its impact on brand value co-creation. It analyzes various studies published between 2013 and 2023, revealing that gamification positively influences brand engagement by fostering active participation, emotional connections, and increased motivation. It also facilitates brand value co-creation by encouraging consumers to actively contribute to brand development, innovation, and advocacy. Design considerations like game mechanics, aesthetics, and personalized experiences are crucial for maximizing gamification's impact on customer engagement and brand value co-creation. The review identifies potential moderating factors, such as consumer characteristics, cultural differences, and industry-specific dynamics, which may influence the effectiveness of gamification strategies. 2023, IGI Global. All rights reserved. -
Social media and economics education: Addressing challenges and leveraging tools for K-12 educators
This case study focuses on the challenges and opportunities associated with integrating social media into the K-12 economics curriculum. Ms. Smith, a high school economics teacher, faced a number of challenges when implementing social media into her teaching practices, including issues related to student engagement, cyberbullying, and privacy concerns. However, she also recognized the potential benefits of using social media in the classroom, including increased student engagement, improved collaboration and communication, and enhanced access to information and resources. To address these challenges, Ms. Smith implemented a number ofremedies and measurements, including providing professional development for teachers, establishing clear guidelines for social media use, providing technical support, encouraging parent involvement, and regularly assessing the impact of social media on student learning. Through her approach, Ms. Smith was able to effectively integrate social media into her economics curriculum and enhance student learning and engagement. 2024, IGI Global. All rights reserved. -
The role of social media in empowering digital financial literacy
This systematic review examined the role of social media in enhancing financial literacy among individuals by collecting and reviewing 60 articles published from 2021 to 2023. The findings revealed that social media has a positive impact on financial literacy through the dissemination of financial education, promotion of financial awareness, and sharing of financial experiences. The review also identified digital financial literacy, entrepreneurial learning, and financial knowledge as significant determinants of financial literacy, while demographic characteristics, social media usage behavior, risk attitude, and overconfidence played a role in determining financial literacy. The study recommends that financial institutions, policymakers, and educators leverage social media for promoting financial literacy, and social media usage skills to improve financial literacy among individuals. Overall, the study suggests that the use of social media can democratize financial literacy and enable individuals from diverse backgrounds to access financial education and information. Copyright 2023, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. 2023 by IGI Global. All rights reserved. -
Bibliographic Analysis of Soft Computing Components from 1999 2018 in India
The core component of the Soft Computing (SC) domain gives outstanding performances for solving problems compared to other problems solving techniques. In order to solve difficult problems, the majority of researchers are concentrating on the soft computing field. The sub-domains of the soft computing field include Genetic Algorithms, Fuzzy Logic, Machine Learning, Neural Networks, and others. In this paper, we aimed to investigate the contributions made by Indian organizations and authors on the topic of soft computing and its applications for the years 1999 to 2018 for the Scopus database. The study confirmed that the most number of papers published in the neural network with a count of 2127 and the most productive author was M.ChintamaniDeo, with 22 papers with the highest h-index and the Indian Institute of Technology, The most productive institution in the subject of Soft Computing is Roorkee, which has contributed 109 publications overall, garnered 355 citations, and has an h-index of 9. This led us to the conclusion that, in comparison to other sub-domains in the field of Soft Computing and its Applications, Indian Institutions and Indian Authors have produced the majority of publications in Neural Networks and Artificial Intelligence. 2024, Ismail Saritas. All rights reserved.