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Impact of financial literacy on savings behavior: the moderation role of risk aversion and financial confidence
This research examines the impact of financial literacy on the savings behavior of investors residing in the Gulf Cooperation Council (GCC) region. It also investigates the moderating impact of financial confidence and risk aversion in the relationship between financial literacy and savings behavior. The primary data were collected from 357 respondents through a structured questionnaire using the snowball sampling method. The findings of this study suggest that financial literacy has a positive impact on investors' savings behavior. Further, the study also found that risk aversion significantly moderates the relationship between financial literacy and savings behavior. The three-way interaction between financial literacy, risk aversion, and financial confidence significantly affects the investors savings behavior. The study suggests that policymakers should emphasize training programs for investors on financial literacy, financial confidence, and risk aversion. The Author(s), under exclusive licence to Springer Nature Limited 2024. -
An IoT-Based Model for Pothole Detection
Maintenance of the good roads plays a very important role in the growth of the country. Poorly maintained roads can lead to potholes which causes severe accidents. To overcome the damage caused by poor roads, the pothole detection model has been proposed in this paper. In recent days, the Internet of Things (IoT)-embedded models are developed in different applications. The main objective of the proposed work is to design the IoT prototype to collect data which can be used to detect potholes and humps. This prototype is embedded with three sensors, namely accelerometer, ultrasonic sensor, and GPS. The data from these sensors is collected by the controller and transmitted by Wi-Fi module to store in the cloud. The collected data can be downloaded as a spreadsheet from the cloud and can be used for different data analysis applications like pothole notifier application. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
The DarcyForechhiemer multilayer model of Casson nanofluid squeezed by Newtonian nanofluid under asymmetric slip conditions
Sandwiched model of non-Newtonian and Newtonian fluid flow in the presence of a magnetic field is analyzed in this paper. Porous medium is considered in all three regions, and the system is modeled by using the DarcyForchheimer model. Furthermore, the homogeneous and heterogeneous reactions are analyzed using quartic catalysis. An asymmetric slip condition (i.e., the slip effect is present in the right and the left wall) for velocity and temperature jump (i.e., jump condition is considered in the right wall, whereas temperature is assumed to be constant in the left wall) is examined in the boundaries of the channel. Additionally, the base fluids are considered to be immiscible which causes the fluids to form an interfacial layer between each other thereby resulting in the formation of three regions in the channel. The mathematical model is explained in the form of governing equations and is solved by the RKF method. The results are explained in the form of graphs, and the physical quantities of interest like skin friction and Nusselt number are interpreted in detail with the help of tabulated numerical values. It is observed from the analysis that in the single-layer model, the viscosity of the fluid decreases the fluid motion, but in the case of the multilayer model, the velocity is improved by the increasing viscosity ratio. Correspondingly, the presence of a magnetic field reduces the temperature. 2022, The Author(s), under exclusive licence to SocietItaliana di Fisica and Springer-Verlag GmbH Germany, part of Springer Nature. -
Thermal optimisation through multilayer convective flow of CuO- MWCNT hybrid nanofluid in a composite porous annulus
The present article deals with the analysis of the three-layer convective flow of immiscible nanofluids in a composite porous annulus. Water and kerosene are chosen as base fluids due to their immiscible property that leads to the formation of a non-physical boundary separation and thus forming a multi-layer flow. In this model, the hybrid nanofluid is formed by suspending copper oxide (CuO) and multi walled carbon nanotubes (MWCNTs) in water which is sandwiched between layers of nanofluid formed by suspending CuO in kerosene leading to two boundary separations that give rise to the interface regions. Such a flow finds applications in the field of solar reactors, electronic cooling, etc. The model based on the above assumptions is in the form of a system of ordinary differential equations that are solved using the differential transformation method. The solutions are found to be in agreement with the existing literature and the results of this study are interpreted graphically. It is to be noted that the interfacial region in the multilayer nanofluid flow helps in maintaining the system at an optimum temperature which helps to cool down the systems. Further, the increase in the Eckert number increases the heat conduction of the nanofluid and pressure enhances the flow speed of the nanofluid. 2022 Informa UK Limited, trading as Taylor & Francis Group. -
Exploration of Thermophoresis and Brownian motion effect on the bio-convective flow of Newtonian fluid conveying tiny particles: Aspects of multi-layer model
This research deals with the analysis of bioconvection caused by the movement of gyrotactic microorganisms. The multi-layer immiscible Newtonian fluid flowing through the vertical channel conveying tiny particles is accounted. The immiscible fluids are arranged in the form of a sandwich where the middle layer has a different base fluid that does not mix with the base fluid of the adjacent fluid layer. This separation of the fluid layers gives rise to the interface boundary conditions. Such flows have found applications in electronic cooling and solar reactors processes. Buongiornos model has been incorporated to design the mathematical model that describes the three-layer flows of Newtonian fluid conveying tiny (metal/oxide) particles under thermophoretic force and Brownian motion. The model thus formed is in the form of the ordinary differential system of equations that are solved using the DTM-Pade approximant after non-dimensionalization. The limited results have an excellent comparison with the existing literature results. The results are discussed through graphs and tables. It is seen that thermophoresis enhances the temperature and particle concentration of the fluid whereas, the Brownian motion is found to enhance the temperature and decrease the concentration. The presence of bioconvection helps in achieving enhanced energy and mass transportation. Moreover, the heat transfer occurring between the different base fluids helps to maintain the optimum temperature in the systems. IMechE 2022. -
Heat amd Mass Transfer Analyses of Nanofluid in a Multilayer Model
The study offers an in-depth exploration into the dynamics and properties of multilayered nanofluids and hybrid nanofluid flow in newlinedifferent geometries. The in-vestigation ranges from sinusoidal channels with micropolar hybrid nanoliquids to concentric cylinders that exhibit electrokinetic effects and rotating disks. Also, the DarcyForchheimer model is introduced to assess non-Newtonian and Newtonian fluid interplay, emphasizing the role of asymmetric slip conditions which reduces the fluid flow. Moreover, the study on bioconvection obtained newlineby addition of gyrotac-tic microorganisms which enhances mass and heat transfer in multilayer Newtonian fluid channels. Studies explain the importance of interfacial regions in achieving optimal system temperature. The subsequent study examines the two-layer hybrid nanofluid (HNF) with magnetohydrodynamic properties between two newlineidentical ro-tating disks. The governing equations of the mathematical models are explained using PDE and solutions are attained using numerical and semi-analytical methods such as the DTM and Range Kutta method. Further, the obtained results have been explained with the help of tables and graphs. The study reveals that the immisci-bility of the base fluids forms an interfacial layer, revealing that the addition of two different fluids restricts the fluid motion nearer to the interfacial region, maintaining an optimum temperature in the system. Collectively, these findings pave the way for advanced applications in industries like solar, nuclear, biomedical, and electronic cooling, promising enhanced newlineperformance and efficiency. -
FINNET: A Hierarchical Graph Learning Framework for Adaptive Cross-Market Financial Risk Prediction
Systemic financial risk emerges from complex multi-scale interactions among entities, sectors, and markets. We introduce FINNET, a hierarchical graph neural network framework that models these vertical dependencies through volatility-aware adaptive pooling. Our approach features: (1) a tri-scale graph structure capturing entity, sector, and market dynamics; (2) dynamic embeddings combining static features with time-varying signals; (3) transfer learning for emerging markets; and (4) transparent risk decomposition for regulatory compliance. Validated on 58,432 financial entities across three continents, FINNET achieves 0.891 AUC with only 3.8% performance degradation during crises, while providing early warnings 15 days before failures. 2026 IEEE. -
Building an Industry Standard Novel Language Model Using Named Entities
In every Industry, there is a significant amount of text used in their specific domains. As these are less prevalent in the testing set, anticipating entity names in a language model is a problem faced by the entire industry. In this research a unique and very effective strategy for creating exclusionary classification models that could map entity names based on entity type information is provided. A group of benchmark datasets based on Mortgage is presented, which we used to test the below-presented model. According to experimental findings, our model achieves a perplexity level that is 64% higher than that of the most advanced language models. 2022 IEEE. -
Strategic Innovation and Sustainable Customer-Centric Growth
Strategic innovation and sustainable customer-centric growth drive long-term success in today's evolving business landscape. Organizations that prioritize innovation adapt to changing market demands while ensuring they stay ahead. By placing the customer at the core of their strategies, businesses can create lasting value, build brand loyalty, and drive meaningful growth that balances profitability with long-term sustainability. This approach requires a continuous alignment of innovative efforts with customer needs, emerging technologies, and environmental and social responsibility. The convergence of strategy, innovation, and a customer-centric mindset may build resilient and future-ready organizations. Strategic Innovation and Sustainable Customer-Centric Growth explores how organizations can leverage strategic innovation to develop sustainable, customer-centric business models that drive long-term growth. It examines the integration of customer insights, technological advancements, and sustainability practices into core strategies to create competitive advantage and lasting value. This book covers topics such as business strategy, circular economics, and digital marketing, and is a useful resource for business owners, academicians, researchers, and scientists. 2026 by IGI Global Scientific Publishing. All rights reserved. -
New Business Development Strategies for Achieving Sustainable Growth
In an increasingly competitive and fast-paced global economy, sustainable business success hinges on the ability to innovate, adapt, and execute well-informed strategies. The modern entrepreneur or business leader must navigate complex challenges, from securing funding and managing teams to leveraging technology and aligning operations with long-term goals. Strategic frameworks that integrate both foundational business principles and emerging trends are essential for building resilient, scalable enterprises. By promoting agility, innovation, and sustainability, this topic directly supports economic development and empowers a new generation of leaders to create lasting, positive impact across industries and communities. New Business Development Strategies for Achieving Sustainable Growth provides a comprehensive road map to build, grow, and sustain successful businesses in an ever-changing global market. It bridges the gap between theoretical knowledge and practical application, equipping readers with actionable strategies to navigate challenges, leverage opportunities, and achieve long-term business success. Covering topics such as adaptive business, digitalization, and property management, this book is an excellent resource for entrepreneurs, business owners, managers, executives, students, consultants, educators, researchers, academicians, and more. 2026 by IGI Global Scientific Publishing. All rights reserved. -
An Empirical Evaluation of the Relationship Between Economic Growth, Population and Solid Waste Generation in India
Municipal solid waste (MSW) poses a hazard to the environment, human health and well-being and economic growth, if not managed correctly.It is essential to study the determinants of municipal solid waste generation for efficient waste management planning and achieving sustainable growth.The main objective of this paper is to establish a relationship between economic growth, population and MSW generation.Secondly, it aims to verify whether the environmental Kuznets curve (EKC) hypothesis is valid in the Indian context with MSW generation as the proxy variable for environmental degradation.Panel regression has been run using statewise data of MSW generation, state net domestic product (SNDP) per capita and population for the years 2000-2019.The results show a significant positive relationship between the selected variables.Least square regression was applied to verify the validity of the environmental Kuznets curve (EKC) hypothesis in India using nationwide data for MSW generation and GDP per capita for the years mentioned above.The results depicted inverted U-shaped curve with MSW as the dependent variable and GDP per capita as the independent variable and confirmed the validity of the EKC hypothesis. 2022 Scientific Publishers. All rights reserved. -
Sign Language Diversity and its Impact on Global Communication: Towards a Unified Framework
Sign language is a visually expressive language conveyed through hand gestures and other visual expressions rather than spoken words. Primarily used by individuals with auditory impairments, it is also practiced by many hearing individuals to bridge the gap between the hearing-impaired and hard-of-hearing communities, fostering inclusivity in society. Currently, there are more than 300 different types of sign languages in use, practiced by over 72 million people worldwide. These languages lack a standardized framework, leading to communication, education, and professional integration challenges. This study aims to provide an extensive review of linguistic diversity in sign languages and their impact on communication. It also proposes AI-driven solutions to address these challenges, enabling policymakers, stakeholders, and educators to create an inclusive global community by working toward standardizing sign languages. 2025 IEEE. -
Structure-based virtual screening, pharmacokinetic prediction, molecular dynamics studies for the identification of novel EGFR inhibitors in breast cancer
Breast cancer is one of the most prevalent malignancy cancer types especially affecting women globally. EGFR is a proto onco gene as well as the first identified tyrosine kinase receptor. It plays a dynamic role in many biological tasks such as apoptosis, cell cycle progression, differentiation, development and transcription. Somatic mutation in the EGFR kinase domain derails the normal kinase activity and over expression leads to the progression of cancer especially breast cancer. EGFR is one of the well-known therapeutic targets for breast cancer. In this scenario, we attempt to identify novel potent inhibitors of EGFR. Initially, we performed structure-based virtual screening and identified four potential compounds effective against EGFR. Further, the compounds were subjected to ADME prediction as part of evaluation of the druggability and all the four compounds found to fall under satisfactory range with predicted pharmacokinetic properties. Eventually, the conformational stability of proteinligand complex was analyzed at different time scale by using Gromacs software. Molecular dynamics simulation run of 20 ns is carried out and results were analyzed using root mean square deviation (RMSD), root mean square fluctuation (RMSF) to signify the stability of proteinigand complex. The stability of the proteinligand complex is more stable throughout entire simulation. From the results obtained from in silico studies, we propose that these compounds are exceptionally useful for further lead optimization and drug development. Communicated by Ramaswamy H. Sarma. 2020 Informa UK Limited, trading as Taylor & Francis Group. -
An efficient nonlinear access policy based on quadratic residue for ciphertext policy attribute based encryption
Ciphertext Policy Attribute Based Encryption (CP-ABE) is an efficient encryption scheme as data owner is making decision about the attributes that can access his data and adding that attributes to access structure while encrypting that message. Most existing CP-ABE scheme are based traditional access structure such as linear secret sharing scheme which incur large ciphertext size and linearly increases according to the number of attributes. And those schemes have more computational overhead for calculating share for each attribute and when recalculating secret in data user side. In this paper, we propose a different secret sharing scheme that can be used in access policy for CP-ABE which will reduce the size of ciphertext and there by communication overhead. Furthermore, the proposed scheme reduced computational overhead of secret sharing scheme and improved overall efficiency of the scheme. 2021 Little Lion Scientific -
Machine Learning Techniques for Resource-Constrained Devices in IoT Applications with CP-ABE Scheme
Ciphertext-policy attribute-based encryption (CP-ABE) is one of the promising schemes which provides security and fine-grain access control for outsourced data. The emergence of cloud computing allows many organizations to store their data, even sensitive data, in cloud storage. This raises the concern of security and access control of stored data in a third-party service provider. To solve this problem, CP-ABE can be used. CP-ABE cannot only be used in cloud computing but can also be used in other areas such as machine learning (ML) and the Internet of things (IoT). In this paper, the main focus is discussing the use of the CP-ABE scheme in different areas mainly ML and IoT. In ML, data sets are trained, and they can be used for decision-making in the CP-ABE scheme in several scenarios. IoT devices are mostly resource-constrained and has to process huge amounts of data so these kinds of resource-constrained devices cannot use the CP-ABE scheme. So, some solutions for these problems are discussed in this paper. Two security schemes used in resource-constrained devices are discussed. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
AN EFFICIENT ACCESS POLICY WITH MULTI-LINEAR SECRET-SHARING SCHEME IN CIPHERTEXT-POLICY ATTRIBUTE-BASED ENCRYPTION
Ciphertext-Policy Attribute-Based Encryption (CP-ABE) is a system in which attribute are used for user's identity and data owner determine the access policy to the data to be encrypt. Here access policy are attached with the ciphertext. In the form of a monotone Boolean formula monotone access structure, an access policy can be interpreted and a linear secret-sharing scheme (LSSS) can be implemented. In recent CP-ABE schemes, LSSS is a matrix whose row represent attributes and there exist a general algorithm which is proposed by Lewko and Waters it transforms a Boolean formula into corresponding LSSS matrix. But we may want to transform the monotone Boolean formula to an analogous but compressed formula first before applying the algorithm. This is a very complex procedure and require efficient optimization algorithm for obtaining equivalent but smaller size Boolean formula. So in this paper we are introducing an extended LSSS called multi-linear secret-sharing scheme where we can eliminate above optimization algorithm and directly convert any Boolean formula to multi-linear secret-sharing scheme. 2022 Little Lion Scientific. All rights reserved. -
A Revocable Multi-Authority Attribute Based Encryption Scheme Based On Nonlinear Access Policy
Due to the tremendous increase of data, currently individuals and organizations are increasingly opting to store their data with third-party providers as a solution to their storage issues. Ciphertext Policy Attribute Based Encryption facilitates data outsourcing by encrypting the data at the source and uploading it to a third-party storage provider with some restricted access which is mentioned using access policy. In classical Identity-based Encryption (IBE), when a data owner needs to transmit a message to a data user, they would send it together with the data user's specific identity, such as their email address. This ensures that only the intended recipient can access and read the message. The primary issue is that the data owner must possess knowledge of the identity of each user. Other than the traditional IBE, a data owner can utilize attribute-based encryption to deliver a message to a group of individuals who have the same attributes. Here, the data owner does not need to be aware of every user's identity; instead, he can send messages using the attributes and access policies that have been provided, such as which users can access this message. This research work primarily focuses on three CP-ABE aspects: access policy, number of attribute authority, and revocation. The current access policies are insecure due to their linear character, as they always calculate shares using the same linear equation. For this particular issue in this work, a non-linear secret sharing model that enhances the security of the model is proposed. For addressing the key escrow problem, a solution using multiauthority systems were introduced. These systems involve multiple attribute authorities, each responsible for holding a specific subset of attributes for each user. And access policy will be based on non-linear secret sharing scheme. In the third aspect related to revocation, this work has addressed both user and attribute revocation so that it will make this model a perfect implementation model in terms of improved security. Some of the existing approach for revocation are re-encryption, periodic updating of ciphertext instead this work used a polynomial called Lagrange polynomial which helps to address this problem in less complex and more efficient way. These features will make the proposed scheme a real model that is secure and can be implement in any organization. -
A Machine Learning Model for Augmenting the Media Accessibility for the Disabled People
In an era characterized by the proliferation of digital media, the need to efficiently use multimedia content has become paramount. This article discusses an innovative technique called 'Fast Captioning (FC)' to improve media accessibility, especially for people with disabilities and others with time restrictions. Modern Machine Learning (ML) algorithms are incorporated into the framework, which speeds up video consumption while maintaining content coherence. The procedure includes extracting complex features like Word2Vec embeddings, part-of-speech tags, named entities, and syntactic relationships. Using annotated data, a ML model is trained to forecast semantic similarity scores between words and frames. The predicted scores seamlessly integrate into equations that calculate similarity, thus enhancing content comprehension. Through this all-encompassing approach, the article offers a comprehensive solution that balances the requirements of contemporary media with the accessibility requirements of people with disabilities, producing a more inclusive digital environment. Machine Learning-based Media Augmentation (ML-MA) has achieved the highest accuracy of 96%, and the captioning is accurate. 2023 IEEE. -
Innovative paths to energy efficiency and CO2 reduction in supply chains
The undercurrents of the model provide innovative pathways to energy efficiency and collaboration strategies to reduce CO2 emissions throughout the sustainable supply chain. It highlights the importance of multi- stakeholder engagement in catalyzing transformative change to global systems. By implementing new technologies, enhancing efficiencies, and leveraging renewables, organizations can improve their sustainability performance. Overcoming the barriers to collaboration in this chapter, the challenges and potential solutions of cooperation are discussed, including supportive policy frameworks and collaborative training programs. Ultimately, it sees a better future, one where the capacity for innovation and stakeholder engagement enables a resilient, low- carbon supply chain network that is made even more resilient as we work to align economic outcomes with environmental needs in the age of climate change. 2025, IGI Global Scientific Publishing. All rights reserved.