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Role of Digital Lending in Serving Financially Excluded Individuals and Small Medium Businesses in India
Financial inclusion has become a national strategy for the achievement of an inclusive economy and inclusive society in emerging countries. Access and continuous usage of formal financial services by the financially excluded people are known as financial inclusion. Financially excluded people are still there across the globe and in India. In India, although there are many supply-side and demand-side constraints for promoting financial inclusion, the vital constraint of financial inclusion is the inability of formal financial institutions to serve the unbanked and underbanked by adopting disruptive technologies for their business models and by developing and delivering innovative and customised financial products and services. Formal financial institutions embrace technologies such as Artificial Intelligence, Machine Learning, and Big Data Analytics for their operations in a gradual pace when compared to FinTech start-ups. But Digital Lending Start-ups make all the efforts to serve the unbanked and underbanked population through AI-powered alternative scoring methodology and customised digital loans. This article focuses on the process in which Digital Lending Start-ups serve the financially excluded individuals and Small and Medium Businesses in India. Further, this article analyses the growth, acceptance, future potential, and limitations of digital lending in India. 2024 selection and editorial matter, Satyajit Chakrabarti, Saikat Chakrabarti, Amit Kumar Bhandari, Dipak Saha and Rabin Mazumder. -
Role of Data Science in the Field of Genomics and Basic Analysis of Raw Genomic Data Using Python
The application of genomics in identifying the nature and cause of diseases has predominantly increased in this decade. This field of study in life sciences combined with new technologies, revealed an outbreak of certain large amounts of genomic sequences. Analysis of such huge data in an appropriate way will ensure accurate prediction of disease which helps to adopt preventive mechanisms which can ultimately improve the human quality of life. In order to achieve this, efficient comprehensive analysis tools and storage mechanisms for handling the enormous genomic data is essential. This research work gives an insight into the application of data science in genomics with a demonstration using Python. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Role of corporate innovation and uncertainty in determining corporate investment of the firm: does financial constraint, executive risk preference and firm risk-taking ability play any role
Purpose: This paper aims to investigate the relationship between corporate innovation and the firms corporate investment. Further, the authors begin with the assertion that the relationship between corporate innovation and corporate investment is impacted by significantly a) uncertain periods, b) financial constraint, c) executives risk preference and d) firm risk-taking ability. Design/methodology/approach: This study has considered non-financial listed companies (774 firms) for the period spanning from 20102022. The authors use a fixed effect regression model within a panel data framework to examine the relationship between corporate innovation and investment. For robustness, the authors use system generalised methods of moments to investigate the relationship between corporate investment and corporate innovation across all the samples. Findings: This study finds a positive relationship between corporate innovation and corporate investment, which means when the firm tries to make some innovation, it will increase its expenditure on fixed assets. However, the positive relationship between corporate innovation and corporate investment reduces with uncertainty. Additionally, financial constraint plays a significant role in determining this relationship. Executives and firms with high risk-taking ability tend to be more inclined to make investments. Originality/value: The study is unique because it determines the impact of corporate innovation on corporate investment. The current literature is focused on corporate innovation and uncertainties. However, no light has been shed on the relationship between corporate innovation and investment. At the same time, the authors have introduced three more variables which play a significant role in determining the corporate innovation-investment relationship. , Emerald Publishing Limited. -
Role of Constructivism Developing Metacognitive Abilities Among Secondary School Students
Research Tracks, Vol-1 (1), pp. 125-128. ISSN-2347-4637 -
Role of charged impurities in thermoelectric transport in molybdenum disulfide monolayers
A theoretical study of the electronic properties, namely, electrical conductivity (EC), electronic thermal conductivity (ETC) and thermoelectric power (TEP) in 2D MoS2 monolayers (MLs), over a wide range of temperatures (10 < T < 300 K), is presented employing Boltzmann transport formalism. Considering the electrons to be scattered by screened charged impurities and the acoustic, optical and remote phonons, the transport equation is solved using Ritz iterative method. Numerical calculations of EC, ETC and TEP presented for supported and free-standing MLs with high electron concentrations, as a function of temperature, bring out the relative importance of the various scattering mechanisms operative. The role of CIs, with regard to both concentration and separation from the substrate-ML interface, in determining the properties of supported MLs is demonstrated for the first time. Validity of Wiedemann-Franz law and Mott formula are examined for supported and free standing MLs. Calculations are in consonance with recent experimental data on mobility and TEP of exfoliated SiO2-supported MoS2 ML samples. In the case of TEP it is found that though the diffusion contribution is dominant the inclusion of the drag component, incorporating contributions from all relevant phonon scattering mechanisms, is needed to obtain good agreement with the data. 2017 IOP Publishing Ltd. -
Role of blockchain technology for user data security in metaverse
The metaverse is generating widespread interest among organizations of various scales, as companies acknowledge its capacity for profound transformation. Prominent organizations are actively adopting the metaverse concept to improve their operations and interact with clients in innovative and captivating manners. This chapter examines the vital function that blockchain plays in bolstering user data security as it explores the urgent problem of data breaches in the metaverse sector. The authors also carefully examine recent data breach cases in the metaverse sector, such as sandbox incursions, deepfake attacks, and digital avatar assaults. By outlining these practical difficulties, they make clear how urgent it is to come up with reliable ways to safeguard user data in the metaverse. The study findings have emphasized the dynamic and evolving nature of the metaverse industry, which is now undergoing substantial development and continuous exploration. They have also focused on significant blockchain technologies that demonstrate potential in ensuring data security. 2024, IGI Global. All rights reserved. -
Role of Blockchain in the Healthcare Sector: Challenges, Opportunities and Its Uses in Covid-19 Pandemic
As the world grapples with the Covid-19 pandemic and major populations are getting vaccinated, increasing realisation processes healthcare industry needs to be augmented. It includes managing supply chains, healthcare records, and patient care. With a scarcity of time and resources, adaptation of blockchain technology will help mitigate the pressures on existing infrastructure. A blockchain distributed ledger helps to exchange health information securely without complex intermediation of trust with secure access. The organisations and persons in the blockchain network can verify and authorise the data, thus protecting patient identity, privacy, medical information system, and reducing transaction costs. The paper examines managing and protecting electronic medical records and personal health records data using blockchain. It also analyses issues in healthcare, blockchain implementation, and its uses in the Covid-19 pandemic. 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
Role of biosynthesized silver nanoparticles in environmental remediation: a review
Nanoscience and nanotechnology have made remarkable advances that have significantly altered the environmental remediation process. Silver nanoparticles (AgNPs) are an essential and remarkable nanomaterial in environmental remediation. The potential of AgNPs in biomedical applications is well explored compared to their environmental applications. This review explores the biosynthesis and application of AgNPs in environmental remediation. The discussion continues with the challenges of using AgNPs for environmental remediation and concludes with the prospects of AgNPs. The review will be beneficial to all researchers and professionals who are starting their journey with AgNP synthesis. 2023, The Author(s), under exclusive licence to Springer Nature Switzerland AG. -
Role of Bioadsorbents in Reducing Toxic Metals
Industrialization and urbanization have led to the release of increasing amounts of heavy metals into the environment. Metal ion contamination of drinking water and waste water is a serious ongoing problem especially with high toxic metals such as lead and cadmium and less toxic metals such as copper and zinc. Several biological materials have attracted many researchers and scientists as they offer both cheap and effective removal of heavy metals from waste water. Therefore it is urgent to study and explore all possible sources of agrobased inexpensive adsorbents for their feasibility in the removal of heavy metals. The objective was to study inexpensive adsorbents like various agricultural wastes such as sugarcane bagasse, rice husk, oil palm shell, coconut shell, and coconut husk in eliminating heavy metals from waste water and their utilization possibilities based on our research and literature survey. It also shows the significance of developing and evaluating new potential biosorbents in the near future with higher adsorption capacity and greater reusable options. 2016 Blessy Baby Mathew et al. -
Role of Bacillus thuringiensis in development of transgenic plants
One of the most significant advancements in plant biotechnology has been the production of genetically engineered plants. Due to the effects of pests damaging the majority of crops, the development of pest immunity was necessary for crop preservation. Plants that have had their gene makeup altered in-utero, such as Bacillus thuringiensis, which has insecticidal properties and helps protect crops from pests, are referred to as "genetically modified plants." Cry proteins, which are poisonous proteins that exist in the state of crystals, are the major genes responsible for the development of transgenic plants. Based on the effect of different pest species, cry proteins are divided into many categories. Since they are extremely specific by nature and only affect the target proteins, they are considered environmentally beneficial pesticides since they have no impact on the physiologically significant soil bacteria or other bacterial flora. These cry proteins stay as dormant crystals, but when a pest consumes plants, the inactive form of the crystals becomes active in the alkaline stomach pH of the microorganism, aiding in the rupture of the gut epithelium and ultimately causing the microorganism to die. These days, transgenic plants have been created, including BT corn, BT rice, sugarcane, brinjal, potato, tomato, and many more, it was also discovered that using these transgenic plants increased crop productivity. Transgenic plants can prevent several ecological issues associated with traditional pesticides, including the emergence of resistance, their toxicity to non-target living things, and the buildup of toxic waste in the environment. 2023 Horizon e-Publishing Group. All rights reserved. -
Role of Artificial Intelligence in Neuroimaging for Cognitive Research
Artificial intelligence (AI)-based solutions are used in most of our daily activities. AI has been adapted and it has found various applications. Cognitive research is one area where AI has been applied to understand the hidden patterns in the data. Neuroimaging techniques investigate the neural basis of cognitive processes like perception, attention, memory, language, reasoning, decision-making, and problem-solving. The irregularities in the cognitive process lead to cognitive disabilities and diseases. Neuroimaging techniques, including magnetic resonance imaging (MRI), functional MRI (fMRI), electroencephalography (EEG), and positron emission tomography (PET), along with other data-gathering techniques, are studied to identify cognitive disorders. The imaging techniques generate large amounts of complex data. AI methods, including machine learning (ML), deep learning (DL), natural language processing (NLP), and computer vision, are applied and used to analyse and interpret the data generated by various imagining techniques. Numerous techniques have been designed, developed, and proposed to handle the neuroimaging data for cognitive research with the help of AI techniques. AI techniques include ML algorithms like decision trees, random forest, support vector machine (SVM), principal component analysis (PCA), and DL algorithms, including convolution neural networks (CNNs), long short-term memory (LSTM), and generative adversarial networks (GANs). Recent advancements in the field of neuroimages use AI techniques to preprocess, process, and analyse the data generated by various neuroimaging modalities. This chapter provides an in-depth analysis and summary of various AI techniques for processing neuroimages for cognitive disorders. 2024 selection and editorial matter, Anitha S. Pillai and Bindu Menon; individual chapters, the contributors. -
Role of Artificial Intelligence in Influencing Impulsive Buying Behaviour
This research paper investigates the influence of Artificial Intelligence (AI) on impulsive buying behaviour in the digital commerce domain. The study explores how AI algorithms, data analysis, and customized marketing approaches influence impulsive buying decisions, reshaping traditional understandings of this phenomenon. The analysis draws from a confluence of psychological principles, technological advancements, and marketing strategies, aiming to shed light on how AI not only forecasts but also incites impulsive buying behaviours. The study identifies research gaps, such as the integration of AI with emotional triggers, the comparative effectiveness of AI vs. human influence, and cross-cultural and demographic variability. The research methodology involves a descriptive study with a questionnaire-based survey, and data analysis tools such as ANOVA and paired t-tests. This research contributes to the broader discussion on digital-age consumer behaviors, underscoring the revolutionary role of AI in transforming retail experiences and beyond. 2024 IEEE. -
Role of Artificial Intelligence and Robotics in Shaping the Students: A Higher Educational Perspective
An unprecedented shift in technology has begun in the modern era. Robotics and artificial intelligence (AI) advancements have created fresh positions while de-skilling or retraining many existing ones. Technical developments at higher education institutions (HEIs) protect students against potential changes in their field of study brought on by A) and prepare them for success in the workplace. This research aims to investigate how, over the past 150 years; globalization has fundamentally changed human civilization. Conventional education confronts enormous challenges as energy, the internet of things, and the cyber-physical systems they oversee diminish. One may argue that energy, the internet of things, and the cyber-physical systems that are under its jurisdiction are the foundations of all future education. The demise of these systems presents a significant threat to traditional schooling. Students' screen time is increased by this action, which has an impact on their mental health. Five-fold cross-validation with 210 students from Delhi NCR and abroad is beneficial for the classification techniques SVM, Naive Bayes, and Random Forest. The study examined the factors that contributed to an increased rate of mental health issues among undergraduate students in Delhi, India, following the introduction of the COVID-19 virus. The results have demonstrated that while technology's practical applications will likely have a positive influence on education in the future, there may be negative effects as well. This is an opportunity for educators and learners to support excellence and remove obstacles that prevent many kids and schools from achieving it. Therefore, in the future, every nation will need to create an education system that is more technologically sophisticated. 2024 IEEE. -
Role of AI in the inventory management of agri-fresh produce at HOPCOMS
Inventory management is vital for maintaining the efficiency of supply chain management. Fruits and vegetables being perishable in nature should involve inventory management to avoid wastage and loss in terms of over stocking and stock out situations. The present study focuses on the role of artificial intelligence (AI)-powered inventory management of fruits and vegetables at HOPCOMS, a cooperative society founded in Bangalore. In the road to satisfy the customers, it is necessary for the society to come up with different strategies to manage the inventories in which a retailer confronts overstock and stock out situation, affecting the profit of the society. Therefore, a study was conducted with the help of structured questionnaire among 122 retailers of HOPCOMS outlets in Bangalore. The results obtained from the study suggest that inventory valuation method positively influences AI-powered demand forecasting and customer order fulfillment, and AI-powered demand forecasting is positively related to customer order fulfillment. 2023, IGI Global. All rights reserved. -
Role of AI in Strengthening ESG Governance: Perspective From Industry Experts
Socially conscious investors, especially Gen Z, value ethics over money. ESG reports are as important as financial reports for them. ESG ratings from various sources can puzzle these Gen Z investors, as there is no standardization in ESG data. Firstly, the chapter focuses on the need to integrate AI into ESG reporting by highlighting the limitations of mere frameworks such as GRI, SASB, and ISSB. Secondly, it emphasizes the difference between traditional reporting and AI-integrated ESG reporting. It also points out the challenges of AI integration and ways to overcome these challenges. Lastly, the chapter also proposes the need for a unified framework, making it easier for investors to compare and make decisions. 2024, IGI Global. All rights reserved. -
Role of AI in Enhancing Customer Experience in Online Shopping
AI-powered tools and applications may provide customers with a positive, effective, and customized purchasing experience. By studying client preferences and behaviours, AI systems can anticipate future customer needs, improving and personalizing the shopping experience. The main aim of this study is to examine the role of artificial intelligence (AI) on enhancing customer experience. The results of this study revealed that there is a positive significant relationship between AI features like perceived convenience, personalization and AI-enabled service quality and Customer experience. A total of 416 responses were analysed using a structured questionnaire. The findings indicate significant role of trust as factor, mediating the effects of independent variables on customer experience. Data was analysed using T-test, ANOVA and regression. 2024 IEEE. -
Rock abrading in South India /
Encyclopedia of Global Archaeology, pp.1-10 -
Robust feature selection using rough set-based ant-lion optimizer for data classification
The selection of an algorithm to tackle a certain problem is a vital undertaking that necessitates both time and knowledge. Non-functional needs, such as the size, quality, and nature of the data, must frequently be taken into account. To develop a generalized machine learning model for any domain, the most relevant features must be chosen because noisy and irrelevant characteristics degrade data mining performance. However, the selection of the dominating features is still dependent on the search technique. When there are a high number of input features, stochastic optimization can be applied to the search space. In this research, the authors investigate the ant lion optimization (ALO), a natureinspired algorithm that mimics the hunting process of ant lions and is further stimulated to identify the smallest reducts. They also investigate rough set-based ant lion optimizer for feature selection. The actual results reveal that the ant lion-based rough set reduct selects a better feature subset and classifies them more accurately. 2022 Information Resources Management Association. All rights reserved. -
Robust Deep Learning Empowered Real Time Object Detection for Unmanned Aerial Vehicles based Surveillance Applications
Surveillance is a major stream of research in the field of Unmanned Aerial Vehicles (UAV), which focuses on the observation of a person, group of people, buildings, infrastructure, etc. With the integration of real time images and video processing approaches such as machine learning, deep learning, and computer vision, the UAV possesses several advantages such as enhanced safety, cheap, rapid response, and effective coverage facility. In this aspect, this study designs robust deep learning based real time object detection (RDL-RTOD) technique for UAV surveillance applications. The proposed RDL-RTOD technique encompasses a two-stage process namely object detection and objects classification. For detecting objects, YOLO-v2 with ResNet-152 technique is used and generates a bounding box for every object. In addition, the classification of detected objects takes place using optimal kernel extreme learning machine (OKELM). In addition, fruit fly optimization (FFO) algorithm is applied for tuning the weight parameter of the KELM model and thereby boosts the classification performance. A series of simulations were carried out on the benchmark dataset and the results are examined under various aspects. The experimental results highlighted the supremacy of the RDL-RTOD technique over the recent approaches in terms of several performance measures. 2022 River Publishers.