Kyc through Blockchain
Authors:Prince Mohobia, Dr. P.M. Chaudhari, Harsh Sakhare, Najim Sheikh, Ramin Singh, Devanshu Bhajbhuje

Abstract- Know Your Customer (KYC) process plays a critical role in helping every bank verify the identity of its customers. Banks must conduct KYC checks to prevent criminals using them to commit crimes such as drug trafficking and terrorism. Current manual KYC processes are insecure, slow, and outdated. E-KYC allows users to quickly complete the recruitment process without leaving their homes. Using blockchain-based KYC verification, these limitations can be eliminated as blockchain provides features such as decentralization, transferability, and security. Governments around the world are using electronic KYC systems to make this task easier and more transparent. Governments around the world are rapidly implementing electronic KYC systems to expedite and improve transparency in this critical activity. This document provides access to unique trust based on a self-governing model that enhances customer privacy, has regulatory authority,and helps banks improve the reliability and accuracy of customer data. Presents a management system. Reduce customer acquisition costs. This article aims to offer a solution to this problem. Our solution uses blockchain to perform one-time KYC verification and eliminate multiple checks to ensure database security. Financial institutions on the blockchain network can access a user’s KYC information only with the user’s permission.

DOI: 10.61137/ijsret.vol.10.issue1.132

Published by: vikaspatanker

Impact of Social Media Advertising on Consumer Buying Behaviour
Authors:Saloni kumari, Hardik shiyani, Umashankar pandey, Rajneesh Yadav

Abstract-The ubiquity of digital communication technologies has led to widespread adoption of social media platforms, shaping consumer behavior and marketing strategies. This study aims to investigate consumer responses to online advertisements and their influence on purchasing habits. Key objectives include assessing social media usage for product purchases, analyzing the effectiveness of different advertisement strategies, evaluating online product information reliability, and understanding the impact of social media advertising on consumer behavior. Through empirical analysis, this research seeks to provide valuable insights for firms and consumers in navigating the digital marketing landscape.

DOI: 10.61137/ijsret.vol.10.issue1.131

Published by: vikaspatanker

Factors Influencing Purchasing Behaviour of Consumers towards E-Vehicles
Authors:Saubhagya Bhowmick, Saptarshi Ray, Kaustave Roy, Yogesh Patil

Abstract-The objective of this study project is to examine the factors that influence consumers’ decisions to buy electric vehicles (EVs). The need to transition to sustainable energy sources and lower greenhouse gas emissions has increased interest in electric vehicles (EVs). However, a number of issues, including expensive initial expenses, a short driving range, and a lack luster infrastructure for charging EVs, have contributed to the delayed consumer acceptance of EVs. As such, it is vital to ascertain the pivotal elements that impact consumer inclination towards electric vehicle purchases. To better understand and predict consumers’ intention to buy electric vehicles, the study aims to operationalize and assess the extended Technological Acceptance Model (TAM) with perceived risk and financial incentives policy based on the integrative approach of “Beliefs-attitude-intention” (EVs). Using structural equation modelling (SEM), it is possible to determine how adoption intention for EVs is influenced both directly and indirectly by the predictor variables attitude, perceived utility, perceived ease of use, and perceived danger, with the policy of financial incentives acting as a moderator. The study also reveals that consumer education, awareness, and understanding are critical determinants of EV adoption. The main factors influencing consumers’ purchases of electric vehicles not only apply to the design and development of vehicles that better satisfy consumer demands, but they also provide a theoretical framework for the popularization of electric vehicles and act as a guide for consumers’ purchasing decisions. Expanding the public awareness of electric vehicles and offering more attractive battery and charging plans are two strategies that the government and relevant manufacturers should consider in order to attract consumers and support the auto industry’s sustainable growth. Globalization and technology have brought about significant advances in human civilization, but they have also had a negative impact on the planet’s biological ecology. As a result, many are thinking deeply about sustainable development and the environment. Vehicles powered by new energy are one way to address environmental problems.

DOI: 10.61137/ijsret.vol.10.issue1.130

Published by: vikaspatanker

“Transforming Financial Services: The Impact of AI on JP Morgan Chase’s Operational Efficiency and Decision-Making”
Authors-K Tulsi, Arpan Dutta, Navneet Singh, Deepansh Jain

Abstract-The purpose of this study is to investigate how artificial intelligence (AI) is transforming the operating environment of JP Morgan Chase, a significant global financial firm. The research looks into how JP Morgan Chase has used AI technology to boost operational efficiency, enhance working procedures, and empower decision-making across many business domains. The report examines the influence of these technical breakthroughs on JP Morgan Chase’s overall performance by assessing the individual AI applications implemented by the corporation, such as fraud detection, risk management, and trading algorithms. This study offers light on the advantages, obstacles, and potential hazards connected with integrating AI into the company’s day-to-day operations using a combination of qualitative and quantitative data. Finally, the research intends to give significant insights on the effective deployment of AI in the financial sector, as well as the implications for other industry participants.

DOI: 10.61137/ijsret.vol.10.issue1.129

Published by: vikaspatanker

Floating Dual Axis Sun Tracker Solar Panel
Authors:Nitesh Singh, Dr. D Shakina Deiv

Abstract- Floating sun tracker solar panel is a solar panel that is mounted on a floating platform and incorporates a sun tracking mechanism. The floating panel allow advantages such as reduced land requirements and minimized water evaporation. The sun tracker mechanism adjusts the orientation of the solar panel to follow the sun’s path, maximizing energy generation. This technology offers increased energy production compared to fixed solar installations and can benefit from the cooling effect of water. However, challenges exist in system design, mechanical and electrical issues, and ensuring stability in water environments. Further research is needed to optimize these systems and assess their economic viability.

DOI: 10.61137/ijsret.vol.10.issue1.128

Published by: vikaspatanker

Tokenization for Text Analysis
Authors:Sowmik Sekhar

Abstract-The Seminar “TOKENIZATION FOR TEXT ANALYSIS” is an advanced tokenization technique that is a revolutionizing text analysis, enabling researchers to glean profound insights from vast textual data. This study explores diverse tokenization approaches, encompassing word-based, subword-based, character-level, and language-agnostic methods, with a particular emphasis on BERT integration for capturing language nuances. Striking a balance between granularity and computational efficiency is paramount for practical applications in sentiment analysis, information retrieval, and natural language processing, where processing massive datasets while preserving language intricacies is essential. The study addresses challenges posed by social media content with informal language and unconventional writing styles, unsegmented languages lacking defined word boundaries, and multilingual datasets demanding language-independent tokenization strategies. For large-scale text analysis, optimizing tokenization to minimize processing time while maintaining analysis performance is critical, making tokenization a viable approach for real-world applications. This research provides valuable insights into aligning tokenization methods with text data characteristics and analysis goals, ensuring granularity matches task requirements. Furthermore, the study envisions seamless integration of advanced tokenization techniques with emerging NLP technologies, enhancing text analysis efficacy across domains for knowledge discovery and informed decision-making. Subword-based tokenization approaches, such as Byte Pair Encoding (BPE) and Sentence Piece, effectively capture language nuances and improve the performance of NLP tasks on social media data and other text datasets with informal language and unconventional writing styles. These methods break down words into smaller units, enabling a more granular representation of language. For multilingual datasets and unsegmented languages with undefined word boundaries, language-agnostic tokenization methods, such as those based on characters or word embeddings, prove to be valuable tools. These methods overcome the limitations of language-specific tokenization approaches and effectively handle diverse linguistic structures, making them well-suited for cross-lingual applications.

DOI: 10.61137/ijsret.vol.10.issue1.127

Published by: vikaspatanker

Architectural Review of Client-Server Models
Authors:Mr. Geofrey Mwamba Nyabuto, Mr. Victor Mony, Professor Samuel Mbugua

Abstract-Client-server architecture is a distributed systems architecture where one or more client computers request resources from a server computer over a network. The client computers provide user-friendly interfaces through which users request resources from the server. In turn, the server receives one or more requests, processes them, and returns a response to the requesting client. The birth of this architecture led to the birth of many models and applications including the Internet, banking systems, and mobile cellular networks among others. This model enables multiple users to simultaneously access and use the same resource. This study used a systematic approach to review types of client-server architecture, comparing these types by pointing out their characteristics, advantages, and disadvantages. Through the Google search engine, articles were retrieved, reviewed, and analyzed. The study was able to note that each of the types of client-server architecture has its advantages and disadvantages as per implementation needs. Two-tier architecture works well in a small set-up where not many resources are available, and the implementation is not resource intensive. On the other end, n-tier architecture is suitable where a lot of resources are needed, and high processing speed is required.

DOI: 10.61137/ijsret.vol.10.issue1.126

Published by: vikaspatanker

Authors: Research Scholar Thumane Anil, Professor Dr.Uttam Chand Gupta

Abstract: Freshwater systems surely play a key role in keeping nature balanced and supporting different living things. Moreover, these water bodies help meet important human needs like drinking water, farming, and fishing. Zooplankton work as main consumers in these systems and further connect phytoplankton to higher food levels. This connection itself helps maintain the food chain balance. As per their sensitivity to environmental changes, they work as good bioindicators regarding water quality. This study shows a complete review of research papers regarding zooplankton changes, seasonal differences, and water quality factors that affect freshwater systems. The focus is on how zooplankton helps in checking the health of water bodies as per ecological studies. As per the review, zooplankton groups like Rotifera, Cladocera, Copepoda, and Ostracoda show major seasonal changes regarding temperature, rainfall, nutrients, and water quality factors such as pH and dissolved oxygen. Summer seasons show higher zooplankton numbers due to increased nutrients and phytoplankton growth, whereas monsoon conditions further reduce these populations due to water dilution and turbidity itself. Winter seasons surely provide stable conditions that support moderate diversity. Moreover, these conditions remain relatively consistent throughout the season Moreover, physical and chemical factors of water surely control where zooplankton live and how many different types are found. Moreover, these parameters are considered the main drivers of zooplankton community patterns. Basically, changes in temperature, oxygen, and nutrients directly affect how these organisms survive, reproduce, and form the same community structures. The review actually shows that zooplankton are definitely good indicators for checking pollution and ecological problems in freshwater bodies. These small water animals can reliably tell us about environmental changes. Basically, the study found major research gaps – there are no region-specific studies, no combined biological and chemical analysis, and the same lack of long-term monitoring in freshwater reservoirs like Sathnala project in Telangana. The results definitely show that water quality management actually needs to include zooplankton studies for better conservation work. This review surely gives a complete picture of how zooplankton changes, seasonal patterns, and water quality are connected. Moreover, it shows why these connections are important for managing freshwater ecosystems in a sustainable way.

DOI: https://zenodo.org/records/20049071

Published by: vikaspatanker

Authors: Research Scholar Preetham Narote, Professor Dr.Pankaj Khairnar

Abstract: Emotion recognition has surely become an important field in artificial intelligence. Moreover, it helps make better communication between humans and computers through emotional computing. As per research findings, human emotions show through face expressions, voice, and written text, so single-method systems are not enough for correct recognition. Regarding emotion detection, multiple ways are needed for better accuracy. Further, as per the progress in deep learning, multimodal emotion recognition is getting much attention regarding its ability to combine different data sources. This study reviews the development of emotion recognition methods as per traditional approaches, machine learning, deep learning, and multimodal systems. The review covers different techniques regarding how emotions can be identified and recognized. The system actually focuses on attention-based fusion methods and adaptive learning that definitely improve performance. Basically, the review shows the same big problems like mixed data

DOI: https://zenodo.org/records/20049316

Published by: vikaspatanker

Prevention of URL Attacks by Analyzing Browser Extension
Authors:-Amit Choudhary, Anusha. M. R, Devika. L.R, Manushree M, A.M. Prasad

Abstract- Rapid growth of internet usage has led to cyber-attacks. Malicious cyber criminals exploit vulnerabilities in a browser to initiate cyber-attacks which affects user data, privacy and system integrity. Nowadays many technical solutions on URL attacks were developed, but these approaches were either unsuccessful or unable to identify URL attacks and detect malicious code efficiently. One of the draw-back is due to poor detection strategy and less adaptability to new URL attacks. This work outlines research initiative focused on the prevention of URL attacks through the analyses of browser extension. Thus, the main objective of our project is to design and develop a python-based web browser extension that focuses on identifying URL attacks by extracting features from URL and integrating with various anti-virus tools. The extension combines rule-based analyses of feature extraction technique with external anti-virus services and tools to enhance the accuracy of URL attacks identification.

DOI: 10.61137/ijsret.vol.9.issue6.123

Published by: vikaspatanker