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Traditional finance vs. web 3: A comparative analysis of key features and characteristics for better readability purposes
Web3 is a ground-breaking invention that has the ability to address the shortcomings of web1 and web2. The industry witnessing its major impact is the finance sector. A wave of innovation in traditional finance has been inspired by the introduction of Web3. It is also referred to as the decentralised web and is a developing movement that is upending conventional finance by providing a more open, safe, and decentralised substitute. Traditional banking should work to adopt the features that Web3 offers, including stability, scalability, interoperability, security, performance, extensibility, management, and openness. In order for TradFi to maintain its relevance and expertise in the face of the widespread adoption of digital financial modes, it is now necessary to embrace several Web3 capabilities. Keeping into consideration the relevance and importance of Web3 in finance, this chapter will basically focus on analysing the key features and characteristics of Web3 in comparison to traditional finance. 2023 by IGI Global. All rights reserved. -
Leveraging transparency and privacy through blockchain technology
Blockchain is a conveyed record innovation that can be utilized to keep exchanges in a safe and straightforward way. This makes it a promising innovation for various applications, for example inventory network the executives, monetary administrations, and medical services. One of the vital advantages of blockchain is its capacity to guarantee information consistency. This is on the grounds that all information on the blockchain is put away in a disseminated way, and every hub in the organization has a duplicate of the record. This makes it truly challenging for any one party to mess with the information. One more key advantage of blockchain is its straightforwardness. All exchanges on the blockchain are public, and anybody can see them. This can assist with building trust and straightforwardness among partners. Blockchain can likewise present difficulties regarding information security. This is on the grounds that all information on the blockchain is put away in a public record. This implies that anybody with admittance to the blockchain can see the information, including delicate data, for example individual recognizable proof numbers (PII). There are various ways of tending to the difficulties of information protection in blockchain. One methodology is to utilize encryption to safeguard delicate information. Another 2024, IGI Global. All rights reserved. -
Model Selection Procedure in Alleviating Drawbacks of the Electronic Whiteboard
Deep learning has paved the way for critical and revolutionary applications in almost every field of life in general. Ranging from engineering to healthcare, machine learning and deep learning has left its mark as the state-of-the-art technology application which holds the epitome of a reasonable high benchmarked solution. Incorporating neural network architectures into applications has become a common part of any software development process. In this paper, we perform a comparative analysis on the different transfer learning approaches in the domain of hand-written digit recognition. We use two performance measures, loss and accuracy. We later visualize the different results for the training and validation datasets and reach to a unison conclusion. This paper aims to target the drawbacks of the electronic whiteboard with simultaneous focus on the suitable model selection procedure for the digit recognition problem. 2021 IEEE. -
A post covid machine learning approach in teaching and learning methodology to alleviate drawbacks of the e-whiteboards
Deep learning has paved the way for critical and revolutionary applications in almost every field of life in general. Ranging from engineering to healthcare, machine learning and deep learning has left its mark as the state-of-the-art technology application which holds the epitome of a reasonable high benchmarked solution. Incorporating neural network architectures into applications has become a common part of any software development process. In this paper, we perform a comparative analysis on the different transfer learning approaches in the domain of hand-written digit recognition. We use two performance measures, loss and accuracy. We later visualize the different results for the training and validation datasets and reach to a unison conclusion. This paper aims to target the drawbacks of the electronic whiteboard with simultaneous focus on the suitable model selection procedure for the digit recognition problem. 2021 Tamkang University. All Rights Reserved. -
Secured and Provisioned Access Authentication using Subscribed User Identity in Federated Clouds
Cloud computing has become an essential source for modern trade or market environments by abled frameworks. The exponential growth of cloud computing services in the last few years has resulted in extensive use, especially in storing and sharing the data on various cloud servers. The current trend in the cloud shows that the cloud owners use relative functions and target areas in such a way that cloud customers access or store their data either in the same servers or related servers. Simultaneously, from the security point of view, the lack of confidence about the customer's data on the cloud server is still questionable. The hour's need is to provide the cloud service in a single port way by forming the joint management policy to increase customer satisfaction and profitability. In addition to this, the authentication steps also need to be improvised. This paper discusses issues on the security authentication and access provisioning of the cloud service consumers in federated clouds using subscribed user identity. This work proposes the user identity verification module (UidVM) in the cloud service consumer's authentication process to serve as a cloud broker to minimize the work overloads on the central cloud federation management system, thus enhancing the cloud security. 2021. All Rights Reserved. -
Blockchain-Enabled Smart Contracts in Agriculture: Enhancing Trust and Efficiency
This study explores the important role of blockchain technology in the transformation of agriculture and presents a new way to integrate chatbots and smart contracts to solve the problem of persistence. Leverage the decentralized structure and security of the blockchain to increase traceability, transparency and fairness in agricultural product prices. A user-friendly chatbot built in Python using Tkinter that acts as a bridge between farmers and the Ethereum-based blockchain pricing algorithm. Smart contracts used in Solidity dynamically adjust crop prices based on the weather in real time, making it possible for prices to react and adjust. Simulations and tests in Ganache validate the proposed method, confirming its economic value and effectiveness in many agricultural cultures. This study delves into analytics, including latency and production time, to demonstrate the benefits of the blockchain model in creating transparent, farmer-centric and region-specific crop prices. The importance of this research is to support continuous change in agricultural technology, paving the way for the introduction of appropriate and fair prices. According to the amendment, the integration of advanced machine learning, further integration and collaboration with agricultural stakeholders should be developed in the future. This work sets a good path for agriculture, promoting transparency, fairness and quick access to the best crop prices, thus ensuring security and agricultural technology. 2024 IEEE. -
Integrated IoT-Based Secure and Efficient Key Management Framework Using Hashgraphs for Autonomous Vehicles to Ensure Road Safety
Autonomous vehicles offer various advantages to both vehicle owners and automobile companies. However, despite the advantages, there are various risks associated with these vehicles. These vehicles interact with each other by forming a vehicular network, also known as VANET, in a centralized manner. This centralized network is vulnerable to cyber-attacks which can cause data loss, resulting in road accidents. Thus, to prevent the vehicular network from being attacked and to prevent the privacy of the data, key management is used. However, key management alone over a centralized network is not effective in ensuring data integrity in a vehicular network. To resolve this issue, various studies have introduced a blockchain-based approach and enabled key management over a decentralized network. This technique is also found effective in ensuring the privacy of all the stakeholders involved in a vehicular network. Furthermore, a blockchain-based key management system can also help in storing a large amount of data over a distributed network, which can encourage a faster exchange of information between vehicles in a network. However, there are certain limitations of blockchain technology that may affect the efficient working of autonomous vehicles. Most of the existing blockchain-based systems are implemented over Ethereum or Bitcoin. The transaction-processing capability of these blockchains is in the range of 5 to 20 transactions per second, whereas hashgraphs are capable of processing thousands of transactions per second as the data are processed exponentially. Furthermore, a hashgraph prevents the user from altering the order of the transactions being processed, and they do not need high computational powers to operate, which may help in reducing the overall cost of the system. Due to the advantages offered by a hashgraph, an advanced key management framework based on a hashgraph for secure communication between the vehicles is suggested in this paper. The framework is developed using the concept of Leaving of Vehicles based on a Logical Key Hierarchy (LKH) and Batch Rekeying. The system is tested and compared with other closely related systems on the basis of the transaction compilation time and change in traffic rates. 2022 by the authors. Licensee MDPI, Basel, Switzerland. -
An Introduction to Business Intelligence
The quality of managerial decisions impacts the performance of any business, and this decision mainly depends on the reliability, inclusiveness, correctness, and trustworthiness of the data used for this purpose. Nowadays, business intelligence (BI) has become a key buzzword. BI supports better business decision-making by transforming data into actionable insights. The digitalization or digitization of business is accommodating and embracing the new BI to endure and stand for consistency and competitiveness for business development toward technological or digital transformation. In this digital or computer era, only those businesses will be profitable and successful that are well furnished to digitally (or binary) shift their practices in the technological or information age. In the new technological age, high powered by data analytics capabilities, meaningful and systematic data assimilation has become a new challenge for an organization to transfer data into BI. BI is a technology-driven process for analyzing data into information; information into knowledge; and knowledge into plans that manage and regulate the organization. BI presents actionable information to help corporate executives; business managers, and other end-users and makes more informed business decisions. BI software systems provide historical, current, and predictive views of business operations. Dashboards; Forecasting; Graphical Reporting; Graphical Online Analytical Processing (OLAP); and Key Performance Indicators (KPIs) are the modules of BI. BI helps in organizing teams, keeping them mindful and aware of KPIs. The awareness of KPIs through dashboards and reports keeps teams aligned and more focused on their goals. The optimal aim of BI is to enable a business to make informed decisions. BI helps business managers or leaders utilize data in a way that is coherent and dynamic. The key elements of BI involved are Advanced Analytics or Corporate Performance Management; BI; Data Sources; Data Warehousing and OLAP. With the latest technology and innovations, there are countless BI applications available for varied types of data analysis. BI software or technologies can deal with multiple structured and unstructured data to identify, develop, and create new strategies business opportunities. Its purpose is to enable clear and accessible interpretation of the huge data, to identify new opportunities and execute effective strategies. Strategic BI (SBI) is always associated with reporting from an analytical data source or data warehouse. Essentially, SBI improves the business process by analyzing a predetermined set of data pertinent to that process and provides the historical background of that data. SBI assembles on four crucial and necessary criteria or frameworks, namely collection and storage of data; Optimization of data for analysis; Identification of important business drivers through past data records; and seeking answers to key business questions. Hence, BI provides procedures and technologies, and tools for current business leaders to alter and modify dynamically and effectively lead their companies with correct data decisions. This research paper is qualitative and based on secondary data. This chapter aims to provide insights into BI and highlights the recent innovations and future of BI. 2023 selection and editorial matter, Deepmala Singh, Anurag Singh, Amizan Omar & S.B Goyal. -
Patents and Innovations for Digital Sustainability
With technology growing at a rapid pace, a major issue which is being faced is the problem of effective energy usage and sustainability such that the future generation does not have to bear the brunt of our actions. Through the course of the chapter, the various innovations and patents in the field of digital sustainability are explored which are vital for the preservation of the planet. Patents play a crucial role in promoting innovations and development, as well as protecting the rights of inventors. The varied recent developments in the field of energy sustainability and explaining their work while assessing their contribution to the field are the focus of this chapter. The chapter also provides a comprehensive overview of the relationship between patents and innovations in digital sustainability, offering insights and guidance for researchers, practitioners, and policymakers working in this field. 2024 selection and editorial matter, Vandana Sharma, Balamurugan Balusamy, Munish Sabharwal, and Mariya Ouaissa. -
Application of Sensory and Neuromarketing to Sustain in Emerging Economies
Neuromarketing involves the application of neuroscience in developing suitable marketing campaigns or messages (Morin, 2011). Neuromarketing involves understanding the schema of associations in the consumer's mind, through which a brand can subconsciously stimulate brand recall and drive purchase behavior (Briesemeister & Selmer, 2022). Use of neuromarketing tools can help build associations based on existing knowledge/ semantic memory or through past experiences/episodic memory (Tulving, 1972). Furthermore, sensory marketing can also create subconscious cues to episodic memory (Krishna, 2012) as sensory cues such as touch, taste, and smell are already encoded in a consumer's long- term memory. In the customer journey driven by traditional marketing messages, decision making is driven by reasoning of known facts, but sensory marketing messages can drive implicit decision making based on impulses (Friese et al., 2006). 2026, IGI Global Scientific Publishing. All rights reserved. -
Blockchain Technology: Proof of Work vs Proof of Stake Consensus Mechanism
The purpose of blockchain technology is to record transactions after they have been confirmed. Blockchain?s ability to guarantee decentralized, transparent transactions with solid security has increased the appeal of new virtual currencies. The consensus mechanism, one of the key components of a blockchain network?s operation, plays a crucial role in a decentralized system. The debate surrounding an adequate consensus method has attracted significant attention, particularly in comparing Proof of Work (PoW) and Proof of Stake (PoS). This chapter comprehensively examines the Proof of Work (PoW) and Proof of Stake (PoS) algorithms and compares other consensus algorithms utilized in contemporary blockchain systems. 2026 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies. -
Unlocking India's growth: UPI's digital impact on GDP
Unified Payments Interface (UPI) has emerged as a pivotal driver of economic growth. By offering a seamless and efficient platform for digital transactions, UPI has significantly expanded financial inclusion, allowing even those without access to traditional banking services to participate in the formal economy. Utilizing secondary data the study examines the long-term relationships between UPI's digital impact (measured by UPI transaction volume, CPI, number of banks participating live on UPI), and GDP growth. 2025 by IGI Global Scientific Publishing. All rights reserved. -
A Smartphone Based Robust Model for Intelligent Prediction of Thyroid Disease
The thyroid is an integral organ that exerts vital functionality in regulating the bodys functionality in many different ways. Intelligent thyroid disease prediction is very crucial. Through this paper we will describe a smartphone model for predicting whether a patient has thyroid disease based on certain attributes whose values are given by the user. Here, a profound machine learning algorithm named Random Forest will help us predict thyroid disease. By exercising Random Forest within a mobile application, the users can learn about any potential thyroid disease disorder and thus seek medical help in time. This will help improve both the patients and the medical providers quality of care and the help received. With the integration of the Random Forest algorithm along with the mobile application it will prove to be a vital tool which will help everyone in the healthcare fraternity because of its availability and accessibility. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
Characterizing Context-Dependent Biochar Effects: An ANOVA-Based Study on Soil Properties and Microbial Diversity
Contemporary intensive agriculture has improved food security, but is a detriment to soil health, biodiversity, and long-term sustainability. Biochar is an exciting product derived from the pyrolysis of biomass that possesses great potential to be a soil amendment that can improve soil chemical, physical and biological properties and sequester carbon. This paper summarizes recent international studies (2024-2025) and contains experimental analyses showing how biochar had an effect on soil systems. Considering soil pH, hydrophobicity, porosity, and particle size were emphasized. Our findings indicate that biochar improves soil structure, water retention, nutrient retention, and diversity in microbes, all of which increase crop resilience under abiotic stress conditions. However, there is a context-sensitivity to the utilization of biochar - often changing with soil types, feedstock, pyrolysis, and application rates. By using standardized and characterizing methods in soil characteristics and ANOVA based statistical analysis, this study presents the rationale and insights, opportunities and limitations of biochar as a sustainable soil conditioner. Further, the findings suggest to tailor "designer biochars". It seems plausible that these could be optimized for targeted soil and crop systems, and be a vital tool in developing climate-resilient and sustainable. 2026 IEEE. -
Dynamics of Socio-economic Factors in Shaping Fertility Rates in Manipur: A Robust Poisson Regression Framework Using NFHS-5 Data
This study utilizes Poisson regression to examine the total number of children ever born for all the surveyed women in Manipur, using data from the NFHS-5. Poisson regression is well-suited for modeling count data, such as fertility outcomes, due to its ability to handle discrete, non-negative variables. The model incorporates robust standard errors to deal with violations of the assumptions typically associated with Poisson models, such as under or over dispersion and heteroscedasticity in the residuals. Findings indicate that lower levels of education, age at first child, and limited health literacy are some of the significant predictors of higher birth rates. Furthermore, women from specific religious communities and economically disadvantaged backgrounds are likely to have more children, probably due to restricted access to family planning resources and healthcare services. These findings highlight the value for targeted policy interventions that prioritize improving womens educational opportunities and health literacy. Such strategies are essential for effectively managing fertility rates in Manipur and are in line with national sustainable development goals focused on health and education improvements. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
The Convergence of Artificial Intelligence and Sustainable Finance: Transforming the Financial Landscape
This chapter examines the transformative impact of Artificial Intelligence (AI) on sustainable finance by emphasizing environmental, social, and governance (ESG) investment choices. This chapter utilized the literature review method to analyse diverse AI models, such as machine learning, natural language processing, and predictive analytics, concerning data analysis, risk modelling, and sustainable product development in the financial industry. Additionally, the study presents a use case of the AI-implemented model in the ESG ratings, which assesses environmental consequences and evaluates investment sustainability. The research also recognized possible challenges and ethical issues in the application of AI in the sustainable investing domain. These challenges highlight the necessity for a comprehensive governance framework and the appropriate implementation of AI. The study contributes to the literature by providing insights into technology advancements and proposing solutions to address sustainable finance requirements. 2025 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
A Theoretical Article: Exploring the Evolutionary Dynamics of Couples and Family Therapy
This article provides a comprehensive review of how the field of family therapy has evolved, tracing its roots from early practices influenced by eugenics to its current diverse theoretical frameworks, which are ever-expanding. In the mid-20th century, family therapy expanded beyond its eugenic roots, embracing diverse theoretical frameworks and giving rise to various therapeutic modalities like behavioral and emotionally focused family and couples therapy. However, due to cultural disparities, these concepts and models cannot holistically capture the essence of family therapy in India. They do not compute the central role of the intergenerational subsystem or understand hierarchical dynamics. What is deemed okay in the Western context does not hold true in the Indian context. Postmodern approaches show a marked improvement in dealing with these problems in cultural adaptations of family and couples therapy by integrating diverse therapeutic practices, technological advances, and cultural and diversity-sensitive practices. However, despite these advancements, the adapted modalities have a scope for improvement, posing a pressing need for research that bridges this gap. Moving forward research should focus on family change mechanisms, symptom improvement factors, and prioritizing culturally sensitive approaches to meet the unique needs of Indian families. The Author(s) 2024. -
Empowering Local Action: Strategies for ClimateResponsive Governance
Governance explores the pivotal role of local governance in addressing the urgent challenges posed by climate change. As the effects of climate disruption become increasingly localized, cities, towns, and communities are on the front lines, facing the immediate impacts while also offering innovative solutions. This chapter examines the strategies that enable local governments to integrate climate resilience into their policies, governance structures, and day-to-day decision-making processes. It discusses the importance of building local capacity, fostering collaboration among stakeholders, and utilizing data-driven approaches for adaptive management. Through case studies and real-world examples, the chapter highlights how local leadership can empower citizens, engage in sustainable urban planning, and implement climate-mitigation practices. By enhancing the capacity for climate-responsive governance, this work underscores the need for a bottom-up approach in achieving global climate goals and creating resilient communities. 2026 by IGI Global Scientific Publishing. All rights reserved. -
Biosynthesis of silver nanoparticles using Vitex negundo: Pesticidal efficacy against Spodoptera litura and Helicoverpa armigera with a safety assessment
Plant-based metallic nanoparticles hold promise for agricultural applications. This study investigated the biosynthesis of silver nanoparticles (AgNPs) using Vitex negundo leaf extract. It assessed their pesticidal properties and safety. AgNPs were synthesized via aqueous extract and characterized by UVVis spectroscopy, dynamic light scattering (DLS), Scanning electron microscopy (SEM), X-ray diffraction (XRD), and Fourier-transform infrared spectroscopy (FTIR) Characterization revealed a surface plasmon resonance (SPR) peak at 435 nm, an average particle size of 236.4 nm, and a stable zeta potential. SEM confirmed spherical morphology, XRD indicated a face-centred cubic (fcc) structure, and FTIR confirmed biomolecule-mediated capping and stabilization. Larvicidal bioassays showed that 5 mg/L AgNPs caused 78-89% mortality in Spodoptera litura and 83-100% in Helicoverpa armigera. In both pests, oxidative stress was triggered. Catalase (CAT) activity increased by over 80% in S.litura and moderately in H. armigera. Glutathione-S-transferase (GST) activity declined post-treatment, from 9.4 to 5.0 mM/ min/mg protein in H. armigera and from 1.0 to 0.7 mM/min/mg protein in S. litura, indicating impaired detoxification. In Oreo-chromis urolepis, AgNPs (5, 10, and 25 mg/L) induced oxidative stress without mortality. CAT activity decreased within 24 hours (72.4% at 5 mg/L) and remained suppressed by day 5 (36.7% at 25 mg/L). Superoxide dismutase (SOD) activity increased at 5 mg/L (19.8%) and 25 mg/L (54.8%), while GST initially declined but rebounded at higher concentrations. Reduced glutathione (GSH) levels increased by 24.3% at 25 mg/L, indicating adaptation. This study highlights that V. negundo-derived AgNPs are effective, eco-friendly biopesticides with minimal non-target toxicity. Author (s). -
Smartphone-integrated quantitative determination of bilirubin using luminescent carbon nanoparticles
Herein, using a green, cost-effective, and sustainable biomass precursor, luminescent carbon nanoparticles (CNP) are synthesized for selective bilirubin quantification. From high-resolution transmission electron microscopy (HRTEM) image, the prepared CNP exhibited spherical morphology and the crystallite size ranges from 8 to 16 nm. X-ray photoelectron spectroscopy (XPS) analysis confirmed the presence of both sp2 and sp3 hybridized carbon bonds within the carbon nanoparticles (CNP). Furthermore, Dynamic Light Scattering (DLS) analysis was performed to determine the hydrodynamic diameter of the CNP and the average particle size was found to be approximately 12.94 0.19 nm. Under ultraviolet (UV) radiation of 350 nm wavelength, the CNP displayed excitation dependent emission characteristics, having an average lifetime of 4.4 ns. The fluorescence intensity of carbon nanoparticles reduced considerably in the presence of Fe3+ ions and fluorescence turn ON was achieved upon the addition of different concentrations of bilirubin. The probe displayed remarkable selectivity towards bilirubin over other potential interferences. Using a sensing platform based on a mobile phone application, the fluorescent probe exhibited a limit of detection (LOD) of 32 nM. Moreover, the fluorescent probe was efficiently employed for the detection of bilirubin in human serum and urine specimens. This cost-effective carbon-based turn-off-on fluorescent sensor makes it easy to detect bilirubin, through visual inspection under ultraviolet light, thereby enabling prompt diagnosis. 2025 Elsevier B.V.