Browse Items (1422 total)
Sort by:
-
Impact of climate adaption and resilience on mental and social wellbeing
According to United Nations Climate Change, adaptation refers to adjustments in ecological, social, or economic systems in response to actual or expected climatic stimuli and their effects. In contrast, resilience is all about being able to cope with unexpected or difficult circumstances and being able to persevere in the face of challenges, overcoming barriers and bouncing back after setbacks. While adaptability involves changing to manage under new conditions, resilience, through bouncing back, implies the ability to revert to a previous, more positive state after experiencing some difficulty or challenge. Marianne Hrabok (2020) The pathways through which extreme climate events affect mental health are numerous and include direct (e.g., exposure to trauma) and indirect (social, economic disruptions) routes (Ramadan and Ataallah, 2021). Climate-related catastrophes have significant impacts on the mental well-being of the populations involved, causing surges in cases of depression, anxiety, and posttraumatic stress disorder (PTSD) primarily (Gina Martin, 2022). Studies suggest that the mental well-being impacts and negative emotions that stem from climate change awareness may be shared among child populations (Doherty & Clayton, 2011). In addition to direct and indirect psychological impacts, climate change is likely to impact social and community relationships. Some of these impacts may result directly from changes in climate, but most are likely to be indirect results of shifts in how people use and occupy territory. The response to climatic change by any living organism or system is to adapt or be resilient. This chapter discusses the different types of adaptation and resilience strategies theoretically and successfully adopted by various countries in the world. These strategies have a remarkable impact on the mental and social well-being of its stakeholders. With the discussion on the impacts, this chapter will also suggest strategies to be adopted at an individual level to either adapt or resilience toward climatic change to enhance mental and social well-being at the same time. 2025 Elsevier Inc. All rights are reserved including those for text and data mining AI training and similar technologies. -
Healthcare cloud services in image processing
Technology has been fundamental in defining, advancing, and reinventing medicalpractises, equipment, and drugs during the last century. Although cloud computing is quite a newer concept, it is now one of the most often discussed issues in academic and therapeutic contexts. Many academics and healthcare persons are focused in providing vast, conveniently obtainable, and reconstruct assets like virtual frameworks, platforms, and implementations having lesser business expenditures. As they need enough assets to operate, store, share, and utilise huge quantity of healthcare data, specialists in the field of medicine are transferring their operations in the cloud. Major issues about the application of cutting-edge cloud computing in medical imaging are covered in this chapter. The research also takes into account the ethical and security concerns related to cloud computing. 2023, IGI Global. All rights reserved. -
Analysis of the spread of infectious diseases with the effects of consciousness programs by media using three fractional operators
In this chapter, the mathematical model spread of infectious diseases exemplifying the effects of awareness programs by media is studied with the help of newly proposed fractional operators. The solution for the system of equations exemplifying the model is obtained with the help of the q-homotopy analysis transform technique (q-HATT). The projected method is an elegant amalgamation of the q-homotopy analysis scheme and the Laplace transform. Three fractional operators are employed in this study to show their essence in generalizing the models associated with power-law distribution: kernel singular, nonlocal, and nonsingular. The fixed-point theorem employed to present the existence and uniqueness for the hired arbitrary-order model and converges for the solution is derived with Banach space. The projected scheme springs the series solution rapidly convergent, and it can guarantee the convergence associated with the homotopy parameter. Moreover, for diverse fractional-order, the physical nature has been captured in plots. 2022 Elsevier Inc. All rights reserved. -
Harmonizing financial systems for a greener future: Exploring sustainable finance strategies in India
Sustainable finance represents the next biggest transformation in the financial sector to aid the process of sustainable development. Sustainable finance comprises traditional investment which provides financial profits as well as financing the projects or investments that have social, economic and governance impact. The transition from traditional investment to sustainable finance is underway in different markets at different capacities. This study seeks to examine the performance of sustainability indices representing sustainable finance in the Indian and global markets by analysing returns. It was found that sustainable finance gained significant appreciation in the Indian market. In comparing the performance of sustainability indices in developing and developed markets, there was no development divide identified. In this path towards widespread adoption of sustainable finance, data science as a field also provides promising applications for facilitating this transformation. 2024, IGI Global. All rights reserved. -
Educational technology at pivotal crossroads
Educational technology startups, commonly referred to as EdTech, combine education and innovative technology to transform school environments and improve student learning outcomes. Set against the backdrop of primary and secondary schools, this exploratory study uncovers the most important factors affecting the growth of EdTech startups in Bengaluru, India. Drawing on Isenberg's Entrepreneurship Ecosystem Model (2010, 2011) this exploratory, qualitative study concludes that "lack of conducive culture, infrastructure support, and finance as well as inadequacies in entrepreneurial approach and value addition" affect the growth of startups in EdTech Entrepreneurial landscape. The Author(s), under exclusive license to Springer Nature Switzerland AG 2021. All rights reserved. -
Optimal Charging Strategy for Spatially Distributed Electric Vehicles in Power System by Remote Analyser
The burden on the consumer for the price of fuel for classic vehicles is the root cause for the emergence of the fast growing trend in the power driven vehicles or electric vehicles. Less acceptance of electric vehicles by the customers and the hesitancy to replace traditional fuel powered vehicles by considering the economic factor is a major concern that existing in the current scenario. Therefore, for the proper balancing of the load with respect to the power available among different neighbouring charging stations in a given area, a load scheduling algorithm is used. The optimal route planner for the electric vehicles reaching the charging station is identified and then the power carried by each feeder is calculated by cumulative power of all the charging stations. The identification of the possible route is performed by the spatial network analysis which will be executing at remote analyzer. The location, state of charge, and other details of the electric vehicle through telemetry is used to find the best charging station for the particular vehicle in view of the cost, distance and the time. The performance of the technique is evaluated with and without optimization by considering the logical constraints; and the results are presented. Springer Nature Switzerland AG 2020. -
Internet of Things Based Autonomous Borewell Management System
Water is a basic need for all living beings. At present, due to a large population, water level is getting depleted at an alarming rate particularly in urban region. During summer season, there is no continuous flow of water or availability of water. In electrical contingency situations, bore-wells are prone to damages. The utilization of power at dry run condition affects the economy of the consumers. Despite having no water in the bore-well, if the motor runs, the motor windings may burdened and gives rise to unnecessary power loss. In the present scenario, conservation of energy is a major concern. The conservation of energy as a whole will take place when an individual take an active part by using autonomous and effective methodologies or controllers. The issue is solved by managing the borewell using Internet of Things (IoT) as a platform to automate and manage. The IoT based borewell management system is designed to provision scheduling, manual operation, avoidance of borewell motor running at dry run condition and also nullifies energy loss. The automated borewell operations can be executed from a remote control and measurement unit by the measurement of electrical parameters and analytics. The proposed system minimizes man power, saves time and conserve energy loss. The paper presents operating the conventional borewell by deployment of smart controller which handles the information and communication technology at client and base units. Springer Nature Switzerland AG 2020. -
Development of Internet of Things Platform and Its Application in Remote Monitoring and Control of Transformer Operation
Internet of Things platforms deployed on the system will exhibit numerous benefits such as real time monitoring, faster operation and cost effectiveness. A system oriented IoT platform is developed which features database connotation, web services, setup portal, cloud hosting, drivers or listener for programming languages and hardware devices. The functional parameters of transformer in electrical power system vary around the limit and beyond, which is observed by the IoT platform for remote analysis and to report deformation in the winding. The frequency response measurement from the transformer terminal unit is send to cloud database which is then fetched to remote application through IoT client. At remote monitoring tool, the diagnostic algorithm is executed to estimate the location and extent of deformation. IoT based frequency response analyzer and transformer diagnostic tools developed reports the status of the transformer health condition. Depending upon the extent of deformation, the transformer is isolated from power system. Springer Nature Switzerland AG 2020. -
Assessment of male millennial digital purchase intent with regard to online fashion
There has been a tremendous growth in the number of people opting for online purchases in recent years especially among the tech savvy millennials not just in tier 1 city by also in tier 2 and 3 cities of Karnataka, Reasons for such a massive growth can be a result of several benefits offered by online shopping such as convenience, time-saving, reduces time and cost of travelling and avoiding traffic chaos in metro cities and so on. Also, we can observe from previous studies that online shopping is widely preferred by females when compared to males in India and also male millennials are reluctant to opt for online purchases (Chaudhary et al.2022). Thus, there exists a need to find out the factors affecting digital purchase intent among male millennials with regard to online fashion Purchases. This study aims to assess the validity and reliability of the measurement instrument, assess the issues and challenges faced by male millennials and mediating effect of e-satisfaction and e-experience. 2024, IGI Global. All rights reserved. -
Developing a Model of Content Marketing in Creative Economy Marketing Strategies to Influence Consumer Purchase Intentions
The creative economy, which is a cluster of industries encompassing arts and crafts, audio and video, visual arts, architecture, performing arts, fashion, design, and so on, building on human creativity, knowledge, and technology, is to be given more precedence in the Indian economy. This work aims at building a model that can act as a foundation to promote the creative economys performance by keeping marketing function as the key component to success. The model contemplates what factors of content marketing activities have to be prioritized so as to help a creative business unit increase its visibility and impact the attention of consumers. This study classifies the model into two components. Component 1: creative business unit model and Component 2 of the content marketing strategy model. As the model is a working model and is not proven empirically, it can be further used by researchers and marketers for advanced research and development. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Research Potentials and Future Trends of Digital Sustainability
A once-in-a-century pandemic has left scars on countries already roiled by the increasingly erratic weather patterns induced by the climate crisis, wreaking havoc on sectors as diverse as food security, industrial production, and defence. Countries are torn between ameliorating COVID-19's devastating impact on education, health, and livelihoods of citizens, and finding their footing in a new global order. But from this ferment are emerging technologies, ideas, and solutions that will drive the world of the future; innovation and big ideas are building a vision that is bold and transformative. As the digital technologies evolve, its comprehensive impact on the environment needs to be considered to harness its full potential. Technology is transforming our world, but at the same time it brings new opportunities as well as challenges for sustainability. The unintended negative environmental impacts emerging from technologies are likely to be outweighed by potential of technology to solving it. Advances in technology, coupled with artificial intelligence, innovation in analytics, and data generation, is likely to have positive sustainability impacts. This chapter highlights the research potential and future trends of digital technologies for sustainability purposes. We intend to evaluate the implications of digital technology such as cloud computing, blockchain, Internet of Things, big data analytics, and artificial intelligence on pollution reduction, sustainable farming practices, conservation of biodiversity, and natural disaster management. Using real-life cases, we will investigate how digital technologies can be both an obstacle and enabler to global sustainability, which will enable devising appropriate digitalization strategies geared towards the achievement of sustainability. 2024 selection and editorial matter, Vandana Sharma, Balamurugan Balusamy, Munish Sabharwal, and Mariya Ouaissa. -
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. -
Comparing Strategies for Post-Hoc Explanations in Machine Learning Models
Most of the machine learning models act as black boxes, and hence, the need for interpreting them is rising. There are multiple approaches to understand the outcomes of a model. But in order to be able to trust the interpretations, there is a need to have a closer look at these approaches. This project compared three such frameworksELI5, LIME and SHAP. ELI5 and LIME follow the same approach toward interpreting the outcomes of machine learning algorithms by building an explainable model in the vicinity of the datapoint that needs to be explained, whereas SHAP works with Shapley values, a game theory approach toward assigning feature attribution. LIME outputs an R-squared value along with its feature attribution reports which help in quantifying the trust one must have in those interpretations. The R-squared value for surrogate models within different machine learning models varies. SHAP trades-off accuracy with time (theoretically). Assigning SHAP values to features is a time and computationally consuming task, and hence, it might require sampling beforehand. SHAP triumphs over LIME with respect to optimization of different kinds of machine learning models as it has explainers for different types of machine learning models, and LIME has one generic explainer for all model types. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Exploring the synergy of IIoT, AI, and data analytics in Industry 6.0
This chapter delves into the transformative intersection of artificial intelligence (AI), Industrial Internet of Things (IIoT), and data analytics within the context of emerging Industry 6.0. As industries continue to emerge towards greater connectivity and automation, the chapter delivers a comprehensive analysis of the convergence of these cutting-edge technologies in reshaping the industrial landscape. It explores the synergistic relationships among IIoT, AI, and data analytics, examining their collaborative potential to enhance efficiency, productivity, and decision-making processes. The chapter begins by offering an in-depth overview of Industry 6.0, highlighting the technological advancements and paradigm shifts that characterize this era. Subsequently, it dissects the role of IIoT as a pivotal enabler, connecting physical devices and systems to facilitate real-time data exchange. The incorporation of artificial intelligence is explored as a premeditated augmentation, empowering machines to learn, adapt, and optimize operations autonomously. Simultaneously, the chapter investigates the significance of advanced data analytics techniques in extracting actionable insights from big data, fueling informed decision-making and predictive maintenance strategies. Furthermore, the chapter delves into practical applications and case studies showcasing successful implementations of this triad in diverse industrial sectors. 2025 selection and editorial matter, C Kishor Kumar Reddy, Srinath Doss, Lavanya Pamulaparty, Kari Lippert and Ruchi Doshi; individual chapters, the contributors. -
Functionalities and Approaches of Multi-cloud Environment
Cloud computing is a paradigm that envisions fast access to any resources from anywhere at any time with the most significant advantages of enabling an intuitive environment that offers plethora of services to mankind. The exponential increase in technological advances has been an advantage for the growth of cloud computing. The advancement in technology has enabled the shift in organizations from using a single cloud toward multi-cloud strategy. Multi-cloud uses multiple services from various cloud vendors which has been advantageous in several ways. Multi-cloud strategy has been designed to enable a hybrid mode for the organizations with ample security and savings in cost. This chapter gives an overview of multi-cloud computing and the security issues with respect to cloud computing. 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
Internet of Things: Immersive Healthcare Technologies
Internet of Things (IoT) can be defined as a system that consists of a group of things where information is exchanged with the help of the internet, sensors, and devices. The boom of IoT is mainly because of the factor that it does not require human influence and can take place independently in utilizing digital information from physical devices. The main concern is how the integration of these technologies creates unique applications for the ease of human life. This chapter discusses various technologies of IoT in healthcare and their numerous applications in medical field. It also introduces the involvement of augmented reality that is acquiring a new dimension in the Internet of Things. 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
Wearable Sensors for Pervasive and Personalized Health Care
Healthcare systems are designed to provide commendable services to cater health needs of individuals with minimum expenditure and limited use of human resources. Pervasive health care can be considered as a major development in the healthcare system which aims to treat patients with minimal human resources. This provides a solution to several existing healthcare problems which might change the future of the healthcare systems in a positive way. Pervasive health care is defined as a system which is available to anyone at any point of time and at any place without any location constraints. At a broader definition, it helps in monitoring the health-related issues at a home-based environment by medical stakeholders which is very beneficial in case of emergency situations. This chapter elaborates architecture of IoT, how wearable sensors can be used to help people to get personalized and pervasive healthcare systems, and it also gives a detailed working of different types of IoT-enabled wearable devices for pervasive health care. 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Elevating medical imaging: AI-driven computer vision for brain tumor analysis
Artificial Intelligence (AI) applications in the realm of computer vision have witnessed remarkable advancements, reshaping various industries and solving complex problems. In this context, this research focuses on the use of convolutional neural networks (CNNs) for classifying brain tumors - a crucial domain within medical imaging. Leveraging the power of CNNs, this research aimed to accurately classify brain tumor images into "No Tumor" and "Tumor" categories. The achieved test loss of 0.4554 and test accuracy of 75.89% exemplify the potential of AI-powered computer vision in healthcare. These results signify the significance of AI-driven image analysis in assisting healthcare professionals with early tumor detection and improved diagnostics, underlining the need for continuous refinement and validation to ensure its clinical effectiveness. This research adds to the expanding research and applications that harness AI and computer vision to enhance healthcare decisionmaking processes. 2024, IGI Global. All rights reserved. -
Farming Futures: Leveraging Machine Language for Potato Leaf Disease Forecasting and Yield Optimization
Crop yield prediction is of paramount importance in modern agriculture. It serves as a linchpin for ensuring food security, efficient resource management, risk mitigation, environmental sustainability, and socioeconomic development. Accurate predictions enable us to maintain a stable food supply, optimize resource allocation, and manage the uncertainties associated with climate and market fluctuations. By fostering sustainable farming practices, crop yield prediction also plays a crucial role in reducing environmental impact and promoting rural development. Integrating artificial intelligence (AI) and machine learning (ML) in modern agricultural practices offers the potential to revolutionize the way we produce food, making it more sustainable, efficient, and resilient. This study has demonstrated the effectiveness of convolutional neural networks (CNNs) in the classification of potato leaf disease, achieving remarkable results with a test loss of 0.0757 and a test accuracy of 0.9741. 2024 Taylor & Francis Group, LLC. -
Sentimental analysis on Amazon book reviews: A deep learning approach
[No abstract available]