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Does the cryptocurrency index provide diversification opportunities with MSCI world index and MSCI emerging markets index? Cryptocurrency and portfolio diversificaiton
The study is extending the ongoing discussion on Bitcoin as a diversification asset with the stock market. Some studies analysed cryptocurrencies as a diversification asset, and few challenged the same. During times of turbulence, it is crucial to gauge further diversification opportunities. Henceforth, the study revisits the opportunities of hedging and diversification with the crypto market from a broader perspective. Markets Index to Bitwise 10 Crypto Index Fund (BITW). The study has contributed methodologically to the existing literature by applying DY with symmetric and asymmetric dynamic conditional volatility models. The results provide in-depth shreds of evidence that BITW is insulated, neither taking volatilities from other countries nor contributing to the volatilities of other countries. The study provides insight to policymakers and investors.The study captures the spillover from MSCI World Index and MSCI Emerging Markets Index to Bitwise 10 Crypto Index Fund (BITW). The study has contributed methodologically to the existing literature by applying DY with symmetric and asymmetric dynamic conditional volatility models. The results provide in-depth shreds of evidence that BITW is insulated, neither taking volatilities from other countries nor contributing to the volatilities of other countries. The study provides insight to policymakers and investors. 2023, IGI Global. All rights reserved. -
Driving profitable business growth through economical optimization, energy management, and industrial 5.0 innovations
The chapter emphasizes the significance of economic optimization, energy efficiency, and Industrial 5.0 innovations in driving sustainable growth and profitability in today's business landscape. It highlights the strategic allocation of resources to maximize efficiency and minimize costs, using lean management principles, automation, and data analytics. Energy management is crucial for reducing operational costs and mitigating environmental impact, using renewable energy sources and smart technologies. Industrial 5.0, a new era of industrial transformation, combines automation, connectivity, and data exchange, with technologies like artificial intelligence, IoT, and blockchain. 2024, IGI Global. -
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. -
Drones for Crop Monitoring and Analysis
Drones are becoming a vital tool for crop monitoring and analysis in contemporary agriculture. With the use of sophisticated sensors, these unmanned aerial vehicles (UAVs) can gather high-resolution pictures and data, giving farmers real-time insights into the growth and health of their crops. Thanks to technological advancements, drones can now more reliably and effectively collect a variety of data points than previous techniques, including plant health, moisture levels, and insect infestations. Drones are a useful tool for crop monitoring because they enable farmers to identify problems early on, such as nutrient deficits, water stress, and disease outbreaks, and take prompt action to optimize yields and avoid losses. Drones can also swiftly and affordably cover vast tracts of agriculture, giving a thorough picture of crop conditions. Farmers may use the information that drones gather to make educated decisions by choices about fertilization plans, pest control techniques, and irrigation schedules, eventually enhancing crop sustainability and output. Drone technology is projected to play an increasingly bigger role in agriculture as it develops, completely changing how farmers monitor and assess their crops. (Publisher name) (publishing year) all right reserved. -
Dynamic Channel Allocation in Wireless Personal Area Networks for Industrial IoT Applications
Industrial wireless networks gain a substantial growth in size in the global market. In the congested scenarios of the industrial IoT application instances of wireless personal area networks, it should have a medium access strategy that is efficient and works autonomously to provide a reliable channel by reducing packet collisions. Medium access protocols must consider properties of the links between devices before a node is allowed to access the shared medium. Characteristic metrics of the channel like link quality indicator, received signal strength indicator, and path loss distance have to be considered in the contention resolution process between the nodes. A fuzzy-based channel allocation algorithm is proposed with dynamic adaptation of contention window in channel access strategy of the MAC layer standard. As per the simulation results, the algorithm proposed showed better results in terms of network throughput and packet delivery rate. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
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. -
Dynamics of motivation in online education: Theories,techniques, and mediating factors
Online education is a process where learners encompass various subject areas, disciplines, and degree programs via an internet connection rather than in person. Online learning has become an essential part of delivering flexibility in education. The objective of the book chapter is to create and improve the motivational environment during online classes. It guides students who lack the motivation to achieve their degrees and educational objectives through online education. Students often need more motivation to succeed in the online and face-to-face teaching process. This chapter will focus on identifying the motivational factors, including intrinsic and extrinsic, that are essential for improving students' participation in online education which enables them to understand the importance and necessity of motivation for achieving their goals and desired degrees in any mode of instruction. This chapter will provide them techniques and technology that researchers have proved to be effective and improve the self-motivation factor for students to succeed in all modalities. 2023, IGI Global. All rights reserved. -
Dynamics of Sustainable Economic Growth in Emerging Middle Power Economies: Does Institutional Quality Matter?
The present study investigates the relevance of Institutional structures quality as a determinant of the GDP of the Emerging Middle Power Economies (MIKTA) which constitute predominantly middle-income countries, namely Mexico, South Korea, Indonesia, Turkey, and Australia over the timeframe of 19852016. In addition to institutional variables such as Government Stability, Bureaucratic Quality and Socioeconomic Conditions, the study uses productive factors (per worker capital, human capital) and a macroeconomic indicator (inflation) to show the GDP of the above-mentioned countries. The impact that institutional variables taken have on Efficient Environmental resources, Sustainability and their management has shown to have an impact on the rate of growth of the middle-income economies. To estimate a long-run relation, the study employs the Autoregressive Distributed Lag model, also known as the ARDL model, bringing in controls for cointegration, nonstationary, heterogeneity and cross-sectional dependency and accounts for a mixed order of integration of variables. The model indicates that capital per worker, socio-economic conditions, bureaucratic quality, human capital and inflation have a long-run effect on the GDP of a country. The paper concludes with a positive impact of institutional variables during both, the short-run and the long-run, for the de-pendent variable. The Author(s), under exclusive license to Springer Nature Switzerland AG. 2024. -
Dynamics of the Dadras-Momeni System in the Frame of the Caputo-Fabrizio Fractional Derivative
Investigation of chaos in dynamical systems is one of the most fascinating issues that has received a lot of attention across a variety of scientific domains. One such dynamical system which generates two, three, and four-scroll chaotic attractors with a single parameter change, is the novel Dadras-Momeni system. In this study, we have analyzed the Dadras-Momeni system in the frame of the Caputo-Fabrizio fractional derivative. Theoretical aspects such as boundedness, existence, and uniqueness of solutions are presented. A detailed analysis is presented regarding the stability of points of equilibrium. To regulate chaos in this fractional-order system with unpredictable dynamics, a sliding mode controller is developed and the global stability of the system with control law is established. Later, we introduced uncertainties and external disturbances to the controlled system, and the condition of global stability is derived. To perform numerical simulation we have identified certain values of the parameters where the system exhibits chaotic behavior. Then the theoretical claims about the influence of the controller on the system are established with the help of numerical simulations. 2023 Taylor & Francis Group, LLC. -
E-Commerce data analytics using web scraping
Some companies, like Twitter and others, provide an application programming interface (API) to fetch the information. If the API is not available, we will have to search other websites to get the data in a structured format. The primary way to get data from a web page is through web scraping. The basic idea of web scraping is to pull data from a website and convert it into a format that can be used for analysis. In this paper, we will discuss the simple explanation of how we can use Beautiful Soup to scratch data into Python and later save the extracted data in an Excel spreadsheet and do the spreadsheet analysis later. We will pull data from the Flipkart website to know the cell phone name, cell phone price, cell phone rating, and cell phone specification. 2023 Scrivener Publishing LLC. -
E-learning During COVID-19Challenges and Opportunities of the Education Institutions
As part of the COVID-19 lockdown, educational institutions were closed and adopted e-learning to keep the learning process going. Due to the COVID-19 pandemic, e-learning has become a required component of all educational institutions such as schools, colleges, and universities worldwide. This pandemic has thrown the offline teaching process into chaos. This chapter discusses the concept and role of e-learning during the pandemic and various challenges and opportunities of e-learning encountered by educational institutions. Three broad challenges identified in e-learning are inaccessibility, self-inefficacy, and technical incompetency. E-learning opportunities are no geographic barriers, flexibility, creativity, and critical learning incorporation increased utilization of online resources and reinforced distance learning. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Early stage detection of osteoarthritis of the joints (hip and knee) using machine learning
This study explores the developing relationship between health care and technology, with a special emphasis on the use of machine learning (ML) algorithms to detect early stage osteoarthritis (OA) in the hip and knee joints. OA, a substantial worldwide health problem, requires improved diagnosis techniques. In this analysis, we illuminate the limitations of traditional methods, emphasizing the inherent subjectivity of clinical assessments and the delay in detection using routine imaging techniques. The research investigates the potential of ML to bring about significant changes. It focuses on combining various algorithms with extensive datasets and highlights the need to select relevant features and prepare the data to improve the accuracy of the models. The use of ML is closely connected to ethical issues, which include the protection of data privacy and the capacity to comprehend the models used. To bridge the gap between theory and practice, the chapter presents concrete examples of ML's practical use in detecting OA, opening possibilities for customized therapy and enhanced patient results. The chapter also highlights potential areas for future study, emphasizing the urgent requirement for additional progress in ML-based early detection techniques to alleviate the worldwide impact of OA. 2025 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies. -
Ecofriendly Approaches for Ameliorating the Adverse Effects of Cadmium in Plants by Regulating Physiological and Defense Responses: An Overview
Mitigating cadmium stress in agricultural plants becomes extremely critical in order to assure food sufficiency in the scenario of a rapidly growing population. An extensive review of environmentally friendly methods for reducing cadmium toxicity in plants is provided in this chapter, with special attention to a variety of tactics like phytohormones, polyamines, melatonin, mineral ions, nanoparticles, and transgenic techniques. Nanoparticles are capable of changing the distribution of cadmium, activating antioxidant defense mechanisms, and boosting physiological processes that are crucial for plant resilience and growth. Microorganisms greatly increase plant resistance to cadmium stress by modifying phytohormones and regulating defense-related proteins. Phytohormones can increase a plants adaptability to cadmium stress through a number of mechanisms, such as the regulation of gene expression and physiological processes. Melatonin and polyamines provide protection against oxidative stress and heavy metal toxicity, while mineral ions such as silicon, calcium, zinc, iron, and selenium increase plant resistance to cadmium, minimizing pollution-related harm. Transgenic plants that are tolerant to cadmium exhibit enhanced detoxification processes and reduced metal accumulation. These findings provide important insights for long-term plant cadmium mitigation and highlight the significance of interdisciplinary approaches in managing heavy metal stress in agricultural systems. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Economic Analysis, Environmental Impact, Future Prospects and Mechanistic Understandings of Nanosensors and Nanocatalysis
It is crucial to understand the economic importance of sensors and catalysis. Economy always plays a major role in the field of nanotechnology. The ever-growing industrial revolution raises many concerns to understand the phenomena and to develop inexpensive devices for sensing applications. However, manufacturing such devices have caused a severe impact on environment. Thus, it is a requirement to understand the mechanistic aspects and also future prospects of nanosensors and catalysis to achieve sustainable technologies for the future. 2023 selection and editorial matter, Anitha Varghese and Gurumurthy Hegde; individual chapters, the contributors. -
Economic aspects of marine biopolymers
The usage of synthetic polymers such as plastic is a much-debated topic across the globe for a reason; it is not recyclable and harms the environment. However, todays consumers have shifted their preferences to eco-friendly products over harmful products. The biopolymers market globally accounted for about $13.7 billion in 2021, and by 2030, its projected to reach over $35.2 billion, growing at 11.07% [compound annual growth rate (CAGR)]. By 2026, the marine biotechnology sector will be worth $5 billion worldwide. Despite the manufacturing cost of marine biopolymers being higher than that of standard polymers, the market is growing faster because of its benefits across various industries and mainly for stakeholders. The biopolymer industry has evolved due to the depletion of petroleum reservoirs. Key players from countries such as the United States, Brazil, Germany, Netherlands, Italy, United Kingdom, Japan, Germany, and Australia are in the biopolymers market. Different classes of marine biopolymers and their industrial applications prove the precious value of ocean resources to society. 2025 Elsevier Ltd. All rights reserved. -
Economic Sustainability, Mindfulness, and Diversity in the Age of Artificial Intelligence and Machine Learning
The sustainability of artificial intelligence (Al) and machine learning (ML) requires human diversity and mindfulness. This chapter discusses the various ways in which AI and ML can interact with humans to improve society, e.g., in filing copyrights or design patents or increasing mindfulness. AI and ML could educate weavers and farmers about their legal rights, cultivation methods, banking processes, and the harmful effects of tobacco consumption and other health-related issues. AI and ML could help teach mindfulness. ML can measure additional biofeedback. Music, mathematics, and art may benefit from AI and machine learning. Human-technology relations and the blue-green deployment model can be used to maintain two independent infrastructures or duplicate feature stores. It is possible to cultivate mindfulness and an awareness of diversity and communal harmony through AI and machine learning, as AI and machine learning can infer the emotional and cognitive states of the people with whom they interact. By leveraging the entire process of visualization, reading, and listening with AI, machine learning, and beyond, the digital future has the potential to incorporate real-time emotions and feelings. This would entail emotional responses on both ends and a variety of other technologies and users. 2024 Taylor & Francis Group, LLC. -
Ecotourism a Sustainable Development Approach: A Case Study of Bandipur Forest
Bandipur Tiger Reserve is geographically speaking, it is an ecological confluence since the Western and Eastern Ghats intersect here, making this region unique and exceptional in terms of its flora and fauna. The community land areas of all the border settlements as well as the nearby notified and unnotified forests have been included in the buffer of this tiger reserve. The scrub jungle along the park's eastern boundaries is made up of stunted trees, scattered bushes, and open grassland patches. The Eco-tourism activity is run in the two Ranges of Bandipur (54 km2) and GS Betta (28 km2), covering a total area of 82.00 km2, or around 9.40% of the Reserve's total size. From the above analysis, it could be concluded that the government should provide that there are administrative facilities, halting facilities, etc. just next to National Highway 67, which cuts through the eco-tourism region. Additionally, the village community people agree that the regions where some Private Tourist Resorts have situated border the Kundu Range's Eco-tourism area. The Reserve benefits from having almost year-round operations. The usual methods of stopping poaching, such as arresting and prosecuting offenders, have obviously failed; conservation education aiming at altering local attitudes will greatly reduce the ongoing threats to the integrity of biological systems in the Bandipur forest. Operationalizing sustainable ecotourism within protected areas ultimately relies on management and operations that maximize the industry's potential positive advantages while minimizing its negative ones. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Edge computing for smart disease prediction treatment therapy
Healthcare systems are increasingly seeking to match patients' pace of life and be personalized, as they are demanding more advanced products and services. The only solution for collecting and analyzing health data in realtime is an edge computing (EC) environment, coupled with 5G speeds and modern computing techniques. The technology in healthcare is currently being used to develop smart systems that can expedite the diagnosis of disease and provide precise and timely treatment. The automated hospital monitoring system and medical diagnosis system enable doctors to monitor and diagnose patients from a variety of locations, including hospitals, workplaces, and homes and provide transportation options. As a result, overall doctor visits are reduced as well as patient care is improved. More than 162 billion healthcare IoT devices are expected to be used worldwide by 2021 thanks to the internet of things (IoT) sensors and applications for general healthcare. With edge intelligence (EI), wearable devices with sensors, like smartwatches or smartphones, and gateway devices, such as microcontrollers, can form edge nodes: smart devices with sensors, as well as gateway devices with sensors, can act as edge nodes. Smart sensor devices are typically installed at a greater distance from personal computers (PCs) and servers, which can be utilized in fog computing (FC). In healthcare, EC and FC are used to deliver reliable, low-latency, and location-aware healthcare services by utilizing sensors located within users' reach. Recently, many researchers have proposed using hierarchical computing for the distribution and allocation of inference-based tasks among edge devices and fog nodes, which could lead to an increase in computing power and compute capability of edge devices. For disease prediction, this chapter discusses a variety of EC techniques. 2024 Apple Academic Press, Inc. All rights reserved. -
Edge Computing in Aerial Imaging A Research Perspective
Internet of Drones (IoD) is a field that has a vast scope for improvement due to its high adaptability and complex problem statements. Aerial vehicles have been employed in various applications such as rescue operations, agriculture, crop productivity analysis, disaster management, etc. As computing and storage power have increased, satellite imaging and drone imaging have become possible, with vast datasets available for study and experiments. The recent work lies in the edge computing sector, where the captured aerial images are processed at the edge. Our paper focuses on the algorithms and technologies that easily facilitate aerial image processing. The applications and their architectures are focused on which can efficiently function using aerial processing. The various research perspectives in aerial imaging are concentrated on paving the way for further research. 2024 Scrivener Publishing LLC. All rights reserved. -
Edge intelligence to smart management and control of epidemic
The effects of COVID-19 vary from person to person. A pandemic is devastating economically and socially. Thousands of enterprises face the possibility of collapse. More than half of the world's 3.3 billion workers may lose their livelihoods if the current crisis continues. The world's healthcare services are facing an unprecedented situation due to the recent outbreak of a novel coronavirus (COVID-19). Community and government health are adversely affected by the COVID-19 pandemic. COVID-19 has continued to spread, and mortalities have risen steadily. The spread of this disease can therefore be controlled utilizing nonpharmacological methods, such as quarantine, isolation, and public health education. Recent breakthroughs in deep learning (DL) have led to an explosion in applications and services relating to artificial intelligence (AI). The rapid advancements in mobile computing and AI have enabled zillions of Bytes of data to be generated at the network edge from thousands of mobile devices and internet of things (IoT) devices connected to the Internet. As a result of the success of IoT and AI technologies, it is of utmost importance that we expand the AI frontiers to the network edge in order for big data to be fully tapped. Edge computing (EC) can help overcome this trend because it allows computation-intensive AI applications to run on edge hardware. The topic of discussion in this chapter is edge intelligence (EI) technology's application in limiting virus spread during pandemics. 2024 Apple Academic Press, Inc. All rights reserved.