Volume 12 | Issue 1 |

 Abstract

The method of credit scoring involves a set of decision models that help in granting consumers loan and credit [1]. Since it involves many decisive statements, we employ machine learning models to predict the credit score of a consumer. The following chapter will investigate into the details of machine learning or ML model usages, such as the understanding of model outputs, structure modification, and constant investigation of work [2]. These understandings intend to cultivate the prognostic abilities, donating implicitly to the dominion of credit score forecast. Credit assessment has an essential part in the monetary business, leading the lending choices and handling the danger. Usually, this evaluation depends on physical approaches and comparatively humble scoring representations [3]. By bridging research gaps in credit scoring methodologies, specifically, model interpretability, fairness, and adaptability this project makes substantial contributions to advancing the comprehension and application of machine learning in the realm of credit risk assessment. The system's design prioritizes simplicity and transparency, fostering reproducibility and accommodating future expansions in credit scoring research and practical implementations.

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 Keywords

Credit Score; K-Nearest Neighbours; Support Vector Classifier; Random Forest; confusion matrix; correlation; Min-Max scaling

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The use of electronic voting in elections for public office is becoming more common around the world. This trend can be attributed to the advantages of these systems, such as remote voting capabilities and rapid vote counting. Additionally, electronic voting machines provide greater privacy and increase protection against fraudulent voting. Blockchain technology increases the power of the voting process through an immutable voting process, thus reducing the threat of vote manipulation and maintaining the legitimacy of the election surge. The technology has been adopted by countries such as Germany, Russia, Estonia and Switzerland for use in electronic voting systems. This study provides an overview of blockchain-based electronic voting systems currently used by countries and companies and suggests academic research. Additionally, this study analyzes the challenges faced by blockchain electronic voting systems and identifies areas for future research to improve the reliability of these systems.

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 Keywords

Electronic Voting, Blockchain Technology, Rapid Vote Counting, Privacy Protection, Fraudulent Voting, Immutable Voting Process, Vote Manipulation, Legitimacy of Elections, Blockchain-based Electronic Voting Systems

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Creative Commons Attribution 4.0 and The Open Definition

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Identity verification plays a pivotal role in the contemporary digital landscape, especially within financial and online services. The adoption of Know Your Customer (KYC) processes has become imperative to ensure secure and reliable interactions. This survey paper explores the integration of Optical Character Recognition (OCR) techniques, with a specific focus on the Convolutional Text Proposal Network (CTPN), as a machine learning approach for enhancing KYC verification. Traditional KYC methods often suffer from inefficiencies in terms of speed, accuracy, and scalability. The manual verification processes inherent in these methods not only consume valuable time but are also susceptible to errors. The advent of OCR technology has revolutionized the KYC landscape by automating the extraction and interpretation of textual information from diverse documents such as passports and driver's licenses. The survey begins by highlighting the limitations of conventional KYC methods, underscoring the need for advanced automated solutions. It provides an extensive overview of OCR, elucidating its significance in extracting text from a variety of documents while addressing challenges related to document formats, languages, and image qualities. Machine learning emerges as a critical enabler for OCR, allowing for continuous improvement in accuracy and adaptability to evolving requirements. A substantial portion of the paper is dedicated to introducing and exploring the capabilities of the Convolutional Text Proposal Network (CTPN) as an innovative machine learning approach tailored for OCR-based KYC verification. CTPN's ability to accurately localize and recognize text within images positions it as a promising solution for improving the precision and efficiency of KYC processes. The survey concludes with an evaluation of the current state of OCR-based KYC verification, identifying areas of success and potential challenges. It serves as a roadmap for future research and development, emphasizing the importance of ongoing advancements in machine learning and OCR technologies to meet the evolving demands of identity verification in the digital age.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Identity Verification, KYC, OCR, CTPN, Machine Learning, Automated Solutions, Document Extraction, Traditional KYC Methods, Efficiency, Challenges

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

As consumer consciousness soars and concerns about environmental degradation deepen, regenerative agriculture emerges as a beacon of hope. This study investigates the potential of this transformative approach in Dakshina Kannada District, India, focusing on consumer willingness to pay (WTP) and market impacts. We aimed to assess consumer interest in regenerative products, identify potential drivers of WTP beyond general environmental concerns, and evaluate the economic feasibility for farmers in the region. We employed a quantitative survey of 100 Dakshina Kannada District residents, encompassing questions on product preferences, WTP for regeneratively produced food, and underlying motivations. Statistical analysis, including regressions, explored the determinants of WTP and its variation across demographics and product categories. A remarkable 87% of respondents indicated WTP more for regeneratively grown products, particularly coffee, fruits, and vegetables. However, general environmental concerns lacked explanatory power in predicting WTP. Our analysis suggests alternative drivers, such as trust in producers, specific environmental benefits, and product certifications, warrant further investigation. Farmers face a promising market for regeneratively produced goods. Focusing on high-demand crops, highlighting specific environmental advantages, and building trust with consumers can unlock premium pricing and economic gains. Policymakers must tailor interventions and policies to address the unique motivations of Dakshina Kannada consumers, including supporting infrastructure development, raising awareness, and establishing robust certification standards.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Regenerative agriculture, Consumer willingness to pay, Environmental sustainability, Dakshina Kannada District

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Creative Commons Attribution 4.0 and The Open Definition

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The sustainable development and inclusive growth of any nation consists in its capacity to inclusively engage every cultural factor and aspect into its comprehensive wholeness. The nation-building process of Canada has been fraught with a series of hostilities in the form of climatic challenges racial dissentions and cultural diversities; but mostly by the fact that the indigenous People such as the First Nations, the Metis and the Inuits are outnumbered by the Euro--American settlers. Consequently the minor aboriginals culturally remained eclipsed and felt a strong sense of alienation from the nation's mainstream modernization. But recognizing the plurality of its cultural artefacts and encouraging a cosy ambience for even the native aboriginals, noticeably for the last few decades, the Canadian statehood has progressively revolutionized itself in strengthening its unified future or hood and solidifying its socio-political strong roots. The greatest testimony to this fact is the recent but rapid rise in the literary output by the native aboriginals who are putting firm feet and looking a lasting corner in the cultural dissemination by profusely writing about their own identity as indigenous.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

native, inclusive, plurality, aboriginals, identity

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Creative Commons Attribution 4.0 and The Open Definition

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The research paper explores India's relation between renewable energy and sustainable development. Despite energy challenges, renewable adoption can curb emissions, enhance security, and foster innovation. Hence, the present article made an attempt to understand the growth of electricity sector and potential of renewable energy sources for driving sustainable development in India through reducing carbon, boosting jobs, and equitable energy. This article deepens understanding of renewable energy's pivotal role in India's journey towards resilience, prosperity, and equity, amid rapid development, energy demand, and environmental concerns.

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Creative Commons Attribution 4.0 and The Open Definition

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Renewable Energy, Sustainable Development, Wind, Bio and Solar Power.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The categorization system of r?gas known as S?uddha-Cha?yalaga-Sanki?rn?a gained prominence in the post-Nat?yas?a?stra era. Initially introduced in Auma?patam by Uma?pati, many subsequent treatise authors credited him for this classification system. While it laid the foundation for the modern Melakarta classification, scholars like Sambamurthy expanded its application to ra?gas such as Ma?nji, A?hiri, Dvija?vanti or Juja?vanti, etc., incorporating aesthetic elements from other ra?gas. This paper aims to illuminate the ra?ga Juja?vanti, believed to have been imported from Hindustani Music into Karnatak Music.

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Creative Commons Attribution 4.0 and The Open Definition

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Sanki?rn?a, Ra?ga, Dvija?vanti, Juja?vanti

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The oral route is considered to most natural, uncomplicated, convenient and safe due to its ease of administration, patient acceptance, and cost-effective production process. Many technological developments have resulted in the creation of controlled drug delivery systems, which have the potential to transform medication distribution and offer a multitude of therapeutic advantages. These systems address the shortcomings of conventional drug delivery methods. among the most popular methods for gastro-retentive drugs delivery. Several approaches are currently being used to prolong the GRT, including gastr-retentive drug delivery systems (GRDDS), also known as hydrodynamically balanced systems (HBS), swelling and expanding systems, high-density systems, and other delayed gastric emptying devices. One dosage form that is showing promise is floating dosage forms. By combining the right ingredients and a gas-generating agent, floating dosage forms can be made into tablets or capsules. This review on gastro-retentive drug delivery systems (GRDDS) was written with the intention of gathering the most recent research, paying particular attention to the main mechanism of floatation to accomplish gastric retention. The current study aims to improve bioavailability by extending the gastrointestinal residence duration by the creation of a gastro retentive floating bilayered tablet. A simple UV spectro photometric method has been employed for the estimation of API at 238 nm with a Beer's range of 0-10?g/ml. Fourier transform Infrared spectroscopy confirmed the absence of any drug/polymer's interactions.

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Creative Commons Attribution 4.0 and The Open Definition

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: Gastro-Retentive drug delivery, Floating drug delivery, Gastric Retention Time, etc.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In the ever-evolving and competitive job market, presenting a compelling resume has become critical for job seekers to secure interviews and land their desired positions. However, manually reviewing and assessing a vast number of resumes can be a time-consuming and laborious task for re- cruiters, often leading to inefficiencies and potential biases in the hiring process. Automatic Resume Quality Assessment (ARQA) systems have emerged as promising solutions to address these challenges, leveraging the power of artificial intelligence (AI) and natural language processing (NLP) techniques to automate the resume evaluation process. This survey paper delves into the fascinating world of ARQA, providing a comprehensive overview of the existing approaches, techniques, challenges, and promising future directions

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Resume , Quality, CV Parser, Resume Parser,

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Illegal fishing is a pervasive and destructive global issue that poses a significant threat to maritime ecosystems and the resilience of fisheries. Illegal, unregulated, and unreported (IUU) fishing leads to extinction of fishing population. Also, fishing businesses facing a major financial problem throughout the globe due to IUU. The effective identification and monitoring of illegal fishing activities are crucial in order to protect maritime resources and the enforcement of international regulations. This review paper explores the use of geographical area modeling as a promising approach to combat illegal fishing in oceans. We discuss various techniques and technologies that have been employed to detect IUU fishing within specific geographical areas, providing insights into their strengths, weaknesses, and future prospects. We will develop machine learning algorithms to analyze the geospatial data and identify patterns associated with illegal fishing activities. The current study attempted to conduct a methodical and critical analysis of around Sixty (60) prior publications that were pertinent and published in academic journals throughout a twenty two-year period (2000 - 2022) in modelling of geographical areas to detect illegal fishing. Specifically :(i) Anomaly detection to identify irregular fishing behaviors, such as fishing in prohibited areas(ii) The application of machine learning techniques and how well they match this domain. (iii) the ideas and elements influencing modelling of geographical areas and the starting point of study, (iv) the pertinent mistake and accuracy metrics. Finally, we summarize the difficulties and prospects for more study in the identification of illicit

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

- Illegal fishing, unreported fishing, unregulated fishing, Geographical areas, Marine resources, Geographical Modelling

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Creative Commons Attribution 4.0 and The Open Definition