Category Archives: Uncategorized

Authors: Himani Atul Khamkar, Riddhika Dattaram Zolage, Prof. Sanjay Eknath Gawli

Abstract: Social media platforms such as Instagram are widely used for communication, networking, and content sharing. How- ever, the rapid growth of these platforms has also led to a signifi- cant increase in fraudulent or fake accounts. These accounts are often involved in activities such as spamming, phishing, spreading misinformation, and manipulating engagement metrics. Due to the large number of users and the dynamic behavior of social media platforms, manual identification of fake accounts becomes difficult and inefficient. This research proposes a machine learning-based approach to detect fake Instagram accounts using profile-based features. Various attributes such as follower-following ratio, number of posts, engagement behavior, profile completeness, and other pro- file characteristics are analyzed. The Random Forest classification algorithm is used to distinguish between real and fake accounts. The performance of the model is evaluated using metrics such as accuracy, precision, recall, and F1-score. The experimental results demonstrate that the proposed approach can effectively identify fake accounts and contribute to improving the reliability and security of social media platforms.

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Published by: vikaspatanker

Authors: Atharva Deshmukh, Anirudh Madiwal, Shruti Ayare, Purva Devrukhkar

Abstract: The rapid growth of the food and beverage industry has increased the need for efficient and automated management systems. Traditional café management methods often rely on manual processes, leading to inefficiencies, errors, and reduced customer satisfaction. This research paper presents the design and development of the Lumière Café Management System, a full-stack web-based application aimed at streamlining café operations including order processing, inventory tracking, staff management, and reporting. The system leverages modern web technologies such as React for the frontend, Node.js with Express for backend services, and SQL-based databases for persistent data storage. The application provides role-based access for administrators and staff, enabling efficient task allocation and monitoring. The results demonstrate improved operational efficiency, reduced human errors, and enhanced decision-making capabilities through real-time data insights.

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Authors: Khushi V. Kayande, Kishor B. Charhate, Kiran. B. Nagre, Krushna S. Bhutekar, Dr. Prafulla R Tathe, Kishor B. Charhate

Abstract: Insulin pump therapy, clinically known as Continuous Subcutaneous Insulin Infusion (CSII), represents a sophisticated shift in diabetes management from conventional multiple daily injections (MDI). By delivering a continuous supply of rapid-acting insulin through a subcutaneous cannula, the therapy more closely mimics the physiological insulin secretion of a healthy pancreas. The current data indicate there are over 1 million people with diabetes on insulin pump therapy worldwide3 and 350,000 to 515,000 in the United States4. Insulin pump therapy offers increased lifestyle flexibility and improved glucose management. The goal of this paper is to outline the topics that should be covered by diabetes care and education specialists when teaching people with diabetes (PWD) and their families or significant others. It focuses on insulin pump therapy and the importance of maintaining a high level of expertise in this subspecialty of diabetes education if choosing to include pump and sensor training in the individual specialist’s practice.

DOI: https://doi.org/10.5281/zenodo.19554544

Published by: vikaspatanker

Authors: Dr. B. Mohan Kumar, Dr. Y.S.S. Patro, Ms. J. Lavanya

Abstract: Digital Human Resource Transformation (HRDT) is a key driver of workforce performance in the digital era. This study analyzes the impact of digital HR practices on employee productivity and work engagement using data from 140 respondents. Statistical techniques such as correlation and regression were applied. The results show a significant positive relationship between HRDT, work engagement, and productivity, with engagement partially mediating this relationship. The study highlights the importance of technology-enabled HR systems in enhancing employee outcomes and organizational effectiveness.

DOI: https://doi.org/10.5281/zenodo.19554455

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Authors: H. M. Pawar, Ajay Athare, Sujal Bagdane, Damini Barde, Rutika Vadaje

Abstract: In Recent Years, The Rapid Growth Of Wireless Communication Technologies Has Led To Congestion In The Radio Frequency (Rf) Spectrum. Technologies Such As Wi-Fi, Bluetooth, And Cellular Communication Rely Heavily On Rf Waves, Which Suffer From Limitations Like Limited Bandwidth, Interference, Security Issues, And Restricted Usage In Sensitive Environments Such As Hospitals And Aircraft. To Overcome These Challenges, Light Fidelity (Li-Fi) Has Emerged As A Promising Alternative Wireless Communication Technology.

DOI: https://doi.org/10.5281/zenodo.19554367

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Authors: Ekaterina Nikiforova

Abstract: This paper conducts an in-depth exploration of the mythological motifs in The Master and Mar-garita, focusing on the novel's multilayered character system. It examines how Mikhail Bulgakov integrates mythology, religion, and literary traditions to construct a narrative rich in intertextuali-ty and symbolic meaning. The analysis centers on the characters of the Master, Margarita, Woland, and his retinue, revealing their deep intertextual connections with classic texts such as the Bible and Faust. It argues that these mythological motifs play a crucial role in shaping the characters, advancing the plot, and expressing philosophical themes. Through close textual read-ing and cultural comparison, this study shows that The Master and Margarita is not merely a work of fantasy but a literary masterpiece that reflects Bulgakov’s profound contemplation on good and evil, faith, freedom, and Soviet reality. This research aims to deepen the understanding of the relationship between mythology and character construction in Bulgakov’s work and to provide new interpretive perspectives on its literary and cultural significance.

DOI: https://doi.org/10.5281/zenodo.19554233

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Authors: Assistant Professor K.Karthick, R.Mounish, M.Sanjay, M.Vallarasu

Abstract: A Web-Based Smart City Complaint Monitoring and Resolution System is an integrated digital solution developed to enhance the efficiency of urban service management. The system provides a user-friendly web interface that enables citizens to register complaints related to public services such as infrastructure, sanitation, water supply, electricity, and traffic management. Each complaint is automatically classified, assigned a unique identification number, and routed to the appropriate municipal authority for prompt action. The proposed system incorporates real-time tracking, allowing users to monitor complaint status throughout its lifecycle. Administrative modules support prioritization based on severity, geographic location, and impact, thereby improving response time and service delivery. A centralized database facilitates data storage, analysis, and reporting, enabling authorities to identify recurring issues and support data-driven decision-making for smart city development. Furthermore, features such as automated notifications, feedback mechanisms, and performance dashboards ensure transparency, accountability, and improved citizen engagement. The implementation of web-based technologies minimizes manual intervention and enhances communication between stakeholders. Overall, the system promotes efficient governance and contributes to the development of sustainable and citizen-centric smart cities.

DOI: http://doi.org/

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Authors: Aashutosh Kushwaha, Tapas Kumar Nandi

Abstract: The advancement ofi human civilization into the solar system is fiundamentally constrained by the energy density limitations ofi chemical propulsion. Nuclear propulsion, encompassing thermal, electric, and pulse architectures, ofifiers a transfiormative leap in specifiic impulse and payload capacity by leveraging the high energy density ofi nuclear fiission. This report provides a technically rigorous examination ofi the evolution, physics, and design ofi nuclear rocket systems. It begins with a detailed historical reconstruction ofi the United States' Project Rover and NERVA programs, alongsidg thg Sovigt Union’s RD-0410 development, highlighting the achievement ofi specifiic impulses exceeding 840 seconds. The fiundamental physics ofi neutron kinetics and heat transfier in extreme environments are derived, fiocusing on the McCarthy- Wolfi and Taylor correlations fior supercritical hydrogen. A comparative analysis ofi propellants—liquid hydrogen, ammonia, and methane—reveals the critical trade-ofifis between mass efifiiciency and storage density. Advanced concepts, including gas-core reactors, nuclear light bulbs, and the pulse propulsion ofi Project Orion, are evaluated fior their potential to achieve interstellar velocities. The report concludes with an analysis ofi the current DARPA/NASA DRACO mission and the shifit toward High-Assay Low-Enriched Uranium (HALEU) fiuels, outlining a path fior the next generation ofi deep-space transportation.

DOI: https://doi.org/10.5281/zenodo.19553037

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Authors: Gayathri Kodipaka, Kompalli Sri Divya Muktha, Sowmya Manukonda

Abstract: Polycystic Ovary Syndrome (PCOS) and Anemia are among the most prevalent yet underdiagnosed health conditions affecting women in India, largely due to delayed symptom recognition, lack of awareness, and limited access to preventive healthcare. This project presents an AI-based early risk detection system designed to provide non-diagnostic risk assessment and health awareness support. The system analyzes user-provided inputs such as lifestyle habits, menstrual irregularities, fatigue levels, dietary patterns, and basic lab values like hemoglobin range to estimate a personalized risk probability for PCOS and Anemia. Machine learning models including Logistic Regression and XGBoost are employed to identify patterns associated with elevated risk levels. The application is developed using Python for model implementation, Streamlit for an interactive and accessible user interface, and SQLite for lightweight data storage. Unlike conventional period-tracking applications, this solution focuses on preventive risk scoring tailored to Indian women, aiming to encourage early medical consultation and improve health outcomes across both rural and urban populations.

DOI: https://doi.org/10.5281/zenodo.19552421

 

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Authors: Md Ali Bashar Alam, Uzma Fathima, Dr.A. Kannagi

Abstract: The rapid adoption of artificial intelligence (AI) has created significant opportunities for innovation, efficiency, and competitive growth among small-scale businesses. However, limited resources, lack of technical expertise, and growing ethical concerns make it challenging for small enterprises to implement AI responsibly. This research paper explores the design and development of responsible AI tools tailored specifically for small-scale business environments, focusing on transparency, fairness, accountability, data privacy, and regulatory compliance. By analysing existing global AI ethics frameworks and governance principles, the study proposes a practical model that integrates ethical guidelines into scalable and cost-effective AI solutions. The research highlights key challenges such as algorithmic bias, data protection risks, limited infrastructure, and information asymmetry faced by small businesses, while presenting strategies to mitigate these issues through explainable AI, lightweight governance mechanisms, and certification-based approaches. Furthermore, the paper discusses how responsible AI adoption can enhance customer trust, reduce reputational risk, and support sustainable digital transformation. The findings aim to bridge the gap between high-level ethical principles and real-world implementation by offering a structured framework that enables small-scale enterprises to deploy AI systems safely, ethically, and efficiently. Ultimately, this study contributes to the advancement of inclusive and trustworthy AI ecosystems by empowering small businesses to adopt responsible innovation practices without compromising operational feasibility or economic growth.

Published by: vikaspatanker