Daily Archives: October 15, 2025

Authors: Swati V, Ms. S. Madhu Sangeetha, Dr. B. Lalitha

Abstract: Automatic Teller Machine (ATM) are widely available for users and procedure the ability to carry-out financial transactions and Banking functions in continuous time basis at any time. It made banking transactions effortless for customers current ATM’s have access card and pin authentication for unique information. This explains ATMs to lot of financial theft like card theft, pin theft and stealing account holders’ information. So this project will make the multilevel high end security to find the authorized user in the ATM machine and make secured and more safety transaction and withdrawal money in ATM. High level security mechanism is provided by the consecutive actions after proceeding with pin number such as initially system use Open CV library to analyze the person authorized identification by capturing the human face initially it begins with the entering the pin number if the entered pin is correct then the process continues with the face recognition. If the entered pin is wrong then it sends OTP to the registered Outlook mail. If the entered OTP is correct then the process continues or else the transaction is declined. If the person is authorized it continues if the person is unauthorized, it sends the alert mail and alert SMS to the registered user by using the fast2sms messaging platform. After the completion of transaction, it provides persons image which was captured at the Time of withdrawal in the ATM has to be sent to the registered user mail.

Published by: vikaspatanker

Authors: Ese Lawrence Ekanem, Ogbede Oritsematosan Marian, Okorocha Cyrilgentle Ugochukwu, Odejobi Babajide Michael, Oluwadamisi Tayo-Ladega , Erienu Obruche Kennedy

Abstract: The research examined how health issues affect the eating habits of older adults in both rural and urban households, focusing on Badagry L.G.A in Lagos State. Four research questions were formulated to guide the study, along with one hypothesis that was tested at a significance level of 0.05. A correlational ex-post facto research design was employed for this investigation. According to the 2006 census, Badagry L.G.A had a population of 241,093. The study used a descriptive survey design with 100 participants. A stratified random sampling method, including simple random sampling, was applied to select the sample for this research. Data was gathered through a questionnaire titled "Influence of Health Challenges on Nutritional Lifestyle of the Elderly in Rural and Urban Households of Badagry L.G.A, Lagos State (IHCNLERUH)." The validity of the instruments was assessed for face, content, and construct. The reliability of the instruments was also checked, yielding an internal consistency reliability coefficient of 0.96. The collected data were analyzed using basic correlation and regression at a significance level of 0.05. Frequency, percentage, mean, and standard deviation were utilized to address the research questions, while Pearson coefficient correlation was employed to test the hypothesis. The findings indicated that the eating habits of older adults significantly influence their healthy lifestyle. Health challenges have a notable impact on the nutritional lifestyle of the elderly in both rural and urban settings. High alcohol consumption adversely affects the nutritional status of older individuals. Various factors hinder the nutritional lifestyle and health behaviors of the elderly in these areas. The study suggested that the government and other stakeholders should regularly monitor the health of older adults to identify those at risk, enabling timely interventions, and establish a social security system to support the income and welfare of the elderly people in the study area

DOI: http://doi.org/10.5281/zenodo.17366239

Published by: vikaspatanker

Authors: Kailash Kumar Mahto

Abstract: Recent advancements in power electronics have provided a strong platform for the development of various multilevel inverter (MLI) topologies. These MLI configurations offer several notable advantages, such as high-quality staircase sinusoidal output voltage, a reduced number of power switches, and the elimination of external filters. In this paper, a symmetrical sourced base multilevel inverter topology to generate 11-level of output is proposed to minimize the number of inverter components while achieving an enhanced voltage-step generation. The proposed structure is capable of producing a high-step, staircase-type of 11-level voltage output waveform that closely approximates a sinusoidal voltage without increasing the number of power semiconductor switches. A Carrier-Based Sinusoidal Pulse Width Modulation (CB-PWM) technique is implemented at a switching frequency of 3 kHz to control the inverter operation. The simulation is carried out using MATLAB/Simulink R2019b environment. The working principle of the proposed multilevel inverter (MLI) is explained in detail. This research focuses on the design of a novel single-phase multilevel inverter with a reduced component count. The proposed MLI configuration is structured to generate the maximum possible number of voltage levels in the output AC waveform while utilizing fewer power electronic devices. Furthermore, the output characteristics of the proposed inverter are analyzed for modulation index 1 for an RL load to examine its dynamic behavior and voltage-step generation capability.

DOI: https://doi.org/10.5281/zenodo.18846772

Published by: vikaspatanker

Authors: Samruddhi Ande, Professor S. V. Raut

Abstract: Millions of individuals worldwide suffer with diabetes, a dangerous medical condition. Serious problems can be avoided with early diabetes prediction. In this study, we predict diabetes in individuals based on a variety of health factors using machine learning approaches. Age, blood pressure, glucose level, BMI, and other medical characteristics are among the data in the dataset. To increase prediction accuracy, data preprocessing techniques such as normalization and handling missing values were used. A number of machine learning models were tested, such as Support Vector Machine, Random Forest, and Decision Tree. The accuracy, precision, recall, and F1-score of these models were used to compare their performances. The Random Forest model demonstrated its suitability for diabetes prediction by achieving the best accuracy. The findings show that machine learning may reliably support early diagnosis, assisting physicians and patients in making better health-related decisions. The significance of technology in healthcare and the potential for AI-based solutions to enhance patient outcomes are highlighted in this study.

Published by: vikaspatanker

Authors: Mr. Harshkrushna D. Khawale, Prof. S. V. Athawale, Prof. S. V. Raut

Abstract: The Metaverse is a persistent, 3D network of virtual spaces and the culmination of interaction technologies. This systematic review synthesizes its architecture and critically assesses inherent governance deficits. While enabled by XR, AI, and Blockchain, existing architectural models lack dedicated layers for governance and interoperability. Sustained user adoption is contingent on trust and privacy protection. The emerging neurosociological paradigm, utilizing implicit interbrain synchrony, introduces severe ethical risks to cognitive liberty. This demands urgent regulatory focus and the establishment of Neurorights legislation. This paper proposes a socio-technical architectural model and a roadmap for preemptive neuro-adaptive governance.

Published by: vikaspatanker

Authors: Mohammed Swaleh Mohammed

Abstract: This study presents a qualitative thematic analysis of student feedback on the usability of Learning Analytics (LA) feature within an e-learning platform. Drawing from 399 open-ended responses, the analysis identifies key themes reflecting user satisfaction, challenges, and self-assessment practices. The findings reveal that ease of use, flexibility, and efficiency are highly valued, while internet connectivity, system performance, and content limitations pose significant barriers. Additionally, students employ grades tracking, progress monitoring, and feedback utilization to evaluate their academic strengths and weaknesses. The study offers insights into enhancing LA tools to better support learner engagement and outcomes

DOI: http://doi.org/10.5281/zenodo.17356211

Published by: vikaspatanker