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Blockchain application with specific reference to smart contracts in the insurance sector
The term blockchain was coined in 2008 by Satoshi Nakamoto. Initially, it was used for carrying out decentralised transactions to solve the problem of fake transactions. In the past few years, this was explored extensively for cryptocurrency only, but, over some time, its potential has been explored in many areas. The major reason for the growing interest in this particular technology is that it provides a secure, reliable, and trusted platform to perform digital activities. This is executed without the involvement of any third party. Once the data is entered into the nodes, it is impossible to tamper it. Though blockchain is costly, it provides better solutions to many research problems in real time. In recent times, researchers have explored blockchain in deep and used it in many applications such as building smart contracts, supply chain management, digital identity providers, voting systems, banking, and finance applications, P2P learning, and insurance sectors. Through this chapter, the readers will get a systematic and detailed study of blockchain in the insurance sector and smart contracts and its current applications in the insurance sector. This chapter will also provide a fair idea of blockchain technology in the insurance sector and additionally its usage in specific applications. In the end, a relevant set of further reading references will be provided. 2023 River Publishers. All rights reserved. -
Bromelain enhances digestibility of Spirulina-based fish feed
Microalgae like Spirulina (Arthrospira platensis) are protein rich and can be alternative protein sources to fishmeal and soybean meal in fish feed formulation. The present study aims to improve the protein bioavailability of Spirulina by cost-effective protein extraction followed by protease supplementation in fish feed, using in vitro studies. Different extraction procedures such as microwave-assisted, high pressure, and temperature-mediated extraction, boiling and an isoelectric precipitation were employed to study the protein yield from Spirulina powder, and this was compared with the conventional soybean meal and fishmeal conditioning during feed manufacture. Bromelain is a potent protease that has not been widely used as a feed additive with Spirulina. To study the comparative efficiency of bromelain and other proteases like papain and trypsin on Spirulina and conventional feed substrates, a protease assay was performed at different temperatures and enzyme concentrations. The digestibility of these substrates was also studied in vitro, using gut extracts from the fingerlings of Mozambique tilapia (Oreochromis mossambicus). Unlike an in vivo feeding trial, a novel method was used to study the effect of protease supplementation on the inherent digestibility of the gut with an in vitro method. Bromelain showed the highest activity on all the substrates at both the temperatures. Bromelain supplementation improved the in vitro digestibility of the Spirulina that were subjected to protein extraction, more than the un-extracted one. The results of the present in vitro study suggest that Spirulina could serve as an alternative protein source, and bromelain-based supplementation could improve the digestibility of Spirulina-based fish diets. 2021, Springer Nature B.V. -
Impact of the COVID-19 outbreak on the currency exchanges of selected countries
The paper aims to analyse the impact of the COVID outbreak on the currency market. The study considers spot rates of seven major currencies (i.e., EUR/USD, USD/JPY, GBP/USD, AUD/USD, USD/CAD, USD/CHF, and CHF/JPY). To capture the impact of the outbreak on returns and the volatility of returns of seven currencies during pandemic, the study has segregated in two window periods (i.e., pre- [1st Jan 2019 to 31st Dec, 2019] and post-outbreak of COVID-19 [1st Jan, 2020 to 22nd Dec, 2020]). The study has applied various methods and models (i.e., econometric-based compounded annual growth rate [CAGR], dummy variable regression, and generalized autoregressive conditional heteroskedasticity [GARCH]). The result of the study captures the negative impact of the COVID-19 pandemic on three currencies-USD/JPY, AUD/USD, and USD/CHF-and positive significant impact on EUR/USD, GBP/USD, USD/CAD, and CHF/JPY. Investors can take short position in these while having long position in other currencies. The inferences drawn from the analysis are providing insight to investors and hedgers. Copyright 2022, IGI Global. -
Social, Medical, and Educational Applications of IoT to Assist Visually Impaired People
General daily tasks have always been a problem for visually impaired people. Identification of daily objects becomes a hectic task. Traditional methods such as a walking stick and a guide dog have been helpful to the visually impaired for basic navigation. Such, methods have a lot of limitations and often fail under varied situations. Technologies such as Computer Vision and Pattern Recognition (CVPR), Image Processing (IP) Internet of Things (IoT), etc. have made a major contribution to overcoming the limitations. IoT brings a lot of technical and automated solutions to assist the visually impaired people. Data science and analytics are a major part of the process. Data accumulated via various sensors can be processed and used to identify obstacles and enhance basic navigation using haptic and voice feedback. Raw data goes through a series of analysis and refinement. This is then processed into a form which is understandable to the system and can be directly interpreted to perform various components of an application. These applications involve education, navigation, entertainment, security, consumer, etc. These applications are across various verticals of technologies differing in terms of hardware, software, and protocols. Various economically feasible and accurate solutions are now available. While, optimization remains an issue. These devices have generally been very helpful to ease the lives of visually impaired people. The main aim of this article is to provide essential details related to real-world applications of IoT in the field of education, healthcare, entertainment, security, navigation, and solutions to address the daily challenges faced by visually impaired people. The structure of the article includes introduction to IoT, applications of IoT in modern era is dealt in detail in Sect.10.1. Followed by hardware device and communication technologies in Sect.10.2. Section10.3 deals with state of art which focus majorly on research contributions related to applications of IoT and smart devices benefiting the lives of visually impaired. Section10.4 incorporates the future scope and concludes with a summary in Sect.10.5. The article covers more than 30 research contributions in the pastten years which includes journal papers, conference papers and patents which provide a detailed and clear view on the research being carried out in the field of IoT to help the visually impaired. 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Role of Triguna Personality Towards Emotional Expression in Relation to Emotional Regulation
With the changing times, people are more aware of their emotions regarding how to express and regulate them. The present generation is more active and expressive than the previous generation as they understand the significance of emotions in ones life. The body of literature claims that a person with better emotional understanding and expression is expected to have meaningful emotional regulation irrespective of the generation they represent. Traditional Indian Philosophy defines three essential characteristics, Sattva (purity, harmony), Rajas (activity, passion), and Tamas (resistance, darkness), that influence human behavior and experience. The degree to which one of the gunas predominates in an individual, to that extent, we characterize that person with that guna. The complicated interactions between Trigunas personality, emotional expression, and emotional regulation are examined. Considering the available facts, the present research focuses on exploring the association between emotional expression and emotion regulation strategies and the effect of the triguna personality in it, across two generations within the family. To accomplish this, a cross-sectional research design will be used to explore the generational difference, followed by a correlational research design to study the associations among variables for participants within each group. Participants would include the parents (mothers, 45 to 50 years) and their children (siblings, 18 to 24 years). The data was collected from 30 families. 2024 selection and editorial matter, Dr. Sundeep Katevarapu, Dr. Anand Pratap Singh, Dr. Priyanka Tiwari, Ms. Akriti Varshney, Ms. Priya Lanka, Ms. Aankur Pradhan, Dr. Neeraj Panwar, Dr. Kumud Sapru Wangnue; individual chapters, the contributors. -
IoT based car accident detection and notification algorithm for general road accidents
With an increase in population, there is an increase in the number of accidents that happen every minute. These road accidents are unpredictable. There are situations where most of the accidents could not be reported properly to nearby ambulances on time. In most of the cases, there is the unavailability of emergency services which lack in providing the first aid and timely service which can lead to loss of life by some minutes. Hence, there is a need to develop a system that caters to all these problems and can effectively function to overcome the delay time caused by the medical vehicles. The purpose of this paper is to introduce a framework using IoT, which helps in detecting car accidents and notifying them immediately. This can be achieved by integrating smart sensors with a microcontroller within the car that can trigger at the time of an accident. The other modules like GPS and GSM are integrated with the system to obtain the location coordinates of the accidents and sending it to registered numbers and nearby ambulance to notify them about the accident to obtain immediate help at the location. 2019 Insitute of Advanced Engineeering and Science. All rights reserved. -
Linking the Path to Zero Hunger: Analysing Sustainable Development Goals Within the Context of Global Sustainability
A global framework, the Sustainable Development Goals of the United Nations, are designed to tackle the most urgent global issues. SDG 2, which stands for Zero Hunger, demonstrates a robust interconnection with the remaining seventeen goals since achieving food security and improved nutrition requires an all-encompassing approach that addresses the interconnected challenges presented by poverty, health, education, gender equality, climate change, and sustainable resource management. Within this framework, the research endeavors to ascertain the interrelationships among SDG 2 and other goals and analyze the critical goals that drive the achievement of SDG 2. Furthermore, the study provides an exhaustive analysis of the positions adopted by different nations concerning SDG 2. The results indicate that the SDGs are interconnected; while SDG 2 is closely linked to several other SDGs, their respective impacts differ. Furthermore, it has been determined that policies are crucial to attaining the SDGs. Without a transformation in agri-food systems that enhances resilience and facilitates the provision of affordable, nutritious foods and healthy diets, the current state of affairs will persist. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
Hybrid HOG-SVM encrypted face detection and recognition model
Security plays a major role in an individuals life to win this world with highly secure and authentic lifestyle with the digital equipments. The paper proposed an encryption based secure face detection and recognition model which can be implemented in daily life to generate a more robust and efficient security bubble around the world. The most crucial problem encountered during face recognition is due to the variation in face direction of an individual, the model solves the mentioned pose variation problem. The proposed model takes the help of face recognition library to recognize the face and use HOG (Histogram of Oriented Gradients) & SVM for checking the face authentication by performing an image match, the model also applies the concept of HOG to generate the encoded features from the image. The system is divided into two modules first is to detect a face and then match the detected face from the authentic persons dataset available. The system uses the concept of OpenCV library for giving a support system for the real time image. For data encryption, proposed model used the concept of DES3 and RSA algorithm. The proposed model gets 83.33% accuracy while tested for three different image types and states that the RSA algorithm performs encryption in less computational time. 2022 Taru Publications. -
Assessment of Enablers for Adoption of Blockchain Technology in the Indian Hospitality Industry
Purpose The chapter attempts to analyse various enablers for implementing blockchain technology in the Indian hospitality sector and examine the appropriate set of facilitators through the causal interactions among the enablers. Design/methodology/approach To analyse the enablers for the adoption of blockchain, the tool used is the decision-making trial and evaluation laboratory (DEMATEL), which captures the judgements provided by the experts in the field for the cause-and-effect enablers and the interaction effect among these enablers. Findings The literature suggests fifteen enablers classified into cause-and-effect enabler groups and interactions (i.e., enabling and enabled) among each blockchain adoption practice. The study reveals a reduction in cost and transparency as the most significant cause enablers and the effect variables as trust and database security. Research limitations/implications The results generate various enablers that can be focused upon for bringing out various significant interventions in the field. The study, however, provides an understanding of the enablers for this specific industry in the Indian context. Practical implications The results may be useful for devising policies and managerial implications related to adopting blockchain technology in the hospitality sector. Originality/value Very few researchers have integrated the role of grey DEMATEL techniques in the hospitality industry. 2024 selection and editorial matter, Park Thaichon, Pushan Kumar Dutta, Pethuru Raj Chelliah and Sachin Gupta; individual chapters, the contributors. -
Federated Learning and Blockchain: A Cross-Domain Convergence
Gaining significant attention within decentralized contexts, Federated Learning (FL) has been positioned as a highly desirable method for machine learning. By enabling multiple entities to train a shared model cooperatively, data privacy and security are preserved by Federated Learning. Harnessing inherent transparency and accountability of blockchain technology to trace and authenticate updates effectively in federated learning has transpired as an up-and-coming avenue to tackle data challenges related to confidentiality, protection, and reliability. This study examines the viability of federated learning and blockchain integration across multiple dimensions. The technological components of this integration., including incentive systems, consensus mechanisms, data validation, and smart contracts, are delved into. In the study, a novel proposed model for federated learning integrated with blockchain is designed and implemented. It is observed that the mean cypher size is 100 bytes for varying values of gradients. The average throughput recorded is 1.7 bytes per second, while the mean accuracy is 87.1% for 50 epochs. 2023 IEEE. -
HTLML: Hybrid AI Based Model for Detection of Alzheimers Disease
Alzheimers disease (AD) is a degenerative condition of the brain that affects the memory and reasoning abilities of patients. Memory is steadily wiped out by this condition, which gradually affects the brains ability to think, recall, and form intentions. In order to properly identify this disease, a variety of manual imaging modalities including CT, MRI, PET, etc. are being used. These methods, however, are time-consuming and troublesome in the context of early diagnostics. This is why deep learning models have been devised that are less time-intensive, require less high-tech hardware or human interaction, continue to improve in performance, and are useful for the prediction of AD, which can also be verified by experimental results obtained by doctors in medical institutions or health care facilities. In this paper, we propose a hybrid-based AI-based model that includes the combination of both transfer learning (TL) and permutation-based machine learning (ML) voting classifier in terms of two basic phases. In the first phase of implementation, it comprises two TL-based models: namely, DenseNet-121 and Densenet-201 for features extraction, whereas in the second phase of implementation, it carries out three different ML classifiers like SVM, Nae base and XGBoost for classification purposes. The final classifier outcomes are evaluated by means of permutations of the voting mechanism. The proposed model achieved accuracy of 91.75%, specificity of 96.5%, and an F1-score of 90.25. The dataset used for training was obtained from Kaggle and contains 6200 photos, including 896 images classified as mildly demented, 64 images classified as moderately demented, 3200 images classified as non-demented, and 1966 images classified as extremely mildly demented. The results show that the suggested model outperforms current state-of-the-art models. These models could be used to generate therapeutically viable methods for detecting AD in MRI images based on these results for clinical prospective. 2022 by the authors. -
A Study of Factors Affecting the Adoption of Digital Currencies
Digital currency has taken into the world slowly but steadily, rising in the leads of trades and commercialization, which can create a huge impact on the economic wellbeing. Digital currencies can be further classified into Cryptocurrencies, Virtual currencies and Central bank digital currencies. In this research we study thefactors of adopting digital currencies. Primary data has been collected using structured questionnaire. A total of 140 responses are used for the purpose of analysis. We have used correlation and heatmap foranalysing the impact of the identified factors such as Technological, Economical and Social. 2024 IEEE. -
Digital Platforms and Techniques for Marketing in the Era of Information Technology
Digital marketing is the promotion of a product or service through at least one form of electronic media. This form of marketing is distinct from traditional marketing, but it uses some of the ideologies of traditional marketing. This research article examines the various technologies and platforms used in digital marketing that allow any organization or business to do this form of marketing and study what works for them and what does not. The article also explores the recent advancements in digital marketing due to the increase in users and the vast amount of data collected from these users. The two main advancements analyzed and discussed in this paper are machine learning (ML) and artificial intelligence (AI) tools. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Beyond the Stats: How Investment Decisions Are Influenced by Non-Accounting Data
Making investment decisions is a complex process that is influenced by data from non-accounting and accounting sources. In order to better understand the importance of financial reports in comparison to non-accounting data [1], this article examines this complexity. The study is guided by three main objectives: determining the relative importance of financial reports against non-accounting sources; determining the effect of non-accounting information on investment decisions [2]; and investigating the role of demographic factors on this effect. The study finds that, when making investment decisions, shareholders more frequently turn to non-accounting sources through thorough analysis and statistical testing. Notably, credit rating agencies, stock indices, and brokers all have a big say in how decisions are made, highlighting their significance. This work improves our knowledge of how accounting and non-accounting data interact to influence investment decision-making. It emphasizes how crucial it is to take into account a variety of information sources in order to make wise financial decisions [3]. When navigating the ever-changing market landscape of today, investors, financial analysts, and politicians can benefit greatly from these ideas. 2024 IEEE. -
Broad-band mHz QPOs and spectral study of LMC X-4 with AstroSat
We report the results of broad-band timing and spectral analysis of data from an AstroSat observation of the high-mass X-ray binary LMC X-4. The Large Area X-ray Proportional Counter (LAXPC) and Soft X-ray Telescope (SXT) instruments onboard the AstroSat observed the source in 2016 August. A complete X-ray eclipse was detected with the LAXPC. The 340 keV power density spectrum showed the presence of coherent pulsations along with a ?26 mHz quasi-periodic oscillation feature. The spectral properties of LMC X-4 were derived from a joint analysis of the SXT and LAXPC spectral data. The 0.525 keV persistent spectrum comprised of an absorbed high-energy cut-off power law with photon index of ? ? 0.8 and cut-off at ?16 keV, a soft thermal component with kTBB ? 0.14 keV, and Gaussian components corresponding to Fe K?, Ne IX, and Ne X emission lines. Assuming a source distance of 50 kpc, we determined 0.525 keV luminosity to be ?2 1038 erg s?1 2022 The Author(s) Published by Oxford University Press on behalf of Royal Astronomical Society. -
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Hydrogen Sulfide: A new warrior in assisting seed germination during adverse environmental conditions
Seed, being a truly static period of the plant's existence, is exposed to a variety of biotic and abiotic shocks during dormancy that causes many cellular alterations. To improve its germination and vigor, the seed industry employs a variety of invigoration techniques, which are commonly referred to as seed priming procedures. The treatment with an exogenous H2S donor such as sodium hydrosulfide (NaHS) has been proven to improve seed germination. The H2S molecule is not only a key contributor to the signal transduction pathway meant for the sensation of seed exposure to various biotic and abiotic stresses but also contribute toward the alleviation of different abiotic stress. Although it was initially recognized as a toxic molecule, later its identification as a third gaseous transmitter molecule unveiled its potential role in seed germination, root development, and opening of stomata. Its involvement in cross talks with several other molecules, including plant hormones, also guides numerous physiological responses in the seeds, such as regulation of gene expression and enzymatic activities, which contribute to reliving various biological and non-biological stresses. However, the other metabolic pathways that could be implicated in the dynamics of the germination process when H2S is used are unclear. These pathways possibly may contribute to the seed germinability process with improved performance and stress tolerance. The present review briefly addresses the signaling and physiological impact of H2S in improving seed germination on exposure to various stresses. Graphical abstract: [Figure not available: see fulltext.] 2022, The Author(s), under exclusive licence to Springer Nature B.V. -
The rise of digital currency: A bibliometric evaluation and future research prospect
This study aims to get an insight into the intellectual structure, current research themes, and future research directions on digital currency, cryptocurrency, and blockchain. Bibliometric analysis coupled with performance analysis and cluster analysis has been conducted on the digital currency articles, published between the years 2011 and 2023, filtered using PRISMA protocol, and extracted from the Web of Science and Scopus databases. Network analysis was carried out in the Biblioshiny package of R software and VOSviewer. The study highlights that the research of digital currency is classified into four broad categories: "emerging technology", "cryptocurrencies portfolios", "cryptocurrencies as a medium of exchange and an asset class", and "cryptocurrencies and financial risk". The chapter presents an innovative model focusing on productive avenues for future research by synthesizing the latest research articles extracted from the databases, related to digital currency through bibliometric analysis. 2024 by IGI Global. All rights reserved.