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

Published by: vikaspatanker

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

Published by: vikaspatanker

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

Published by: vikaspatanker

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/

Published by: vikaspatanker

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

Published by: vikaspatanker

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

 

Published by: vikaspatanker

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

Authors: Ranjith Durgunala, Harshith Manchikkanti, Rahul Perugu, Sunadh Rithvik Ponnuru

Abstract: Therapid increase in sedentary lifestyles and unhealthy dietary habits has raised serious concerns regarding physical fitness and overall well-being. This project presents an AI Framework for Personalized Fitness & Diet Recommendation System designed to provide intelligent and customized health guidance. The system gathers essential user information including age, gender, height, weight, activity level, medical conditions, dietary preference, and fitness goals. Using this data, Body Mass Index (BMI) is calculated to assess the user’s health status. Machine learning algorithms analyze user profiles to generate personalized workout routines and diet plans tailored for fat loss, muscle gain, weight gain, or general fitness. A progress tracking module records daily weight, workout completion, and calorie intake to evaluate improvement. In addition, predictive models estimate expected fitness outcomes over 30, 60, and 90 days. The proposed framework enhances decision-making through data-driven insights, improves user engagement, and promotes sustainable lifestyle changes using artificial intelligence and machine learning techniques.

Published by: vikaspatanker

Authors: Gudimella Akhilesh, Peruri Karthik Sai, Kunburu Manikanta Reddy, Dr. Atul Kumar Ramotra

Abstract: Career decision-making among engineering students is often influenced by trends rather than a proper evaluation of individual skill sets, leading to skill–career mismatch. This project presents CareerLens, an explainable skill-based career recommendation system designed to guide students in selecting suitable academic streams and job roles. The system analyzes user-provided technical skills along with proficiency levels, maps them to predefined career requirements, and computes readiness scores to generate personalized recommendations. Additionally, it identifies skill gaps and suggests improvements to enhance career readiness. By emphasizing transparency, interpretability, and skill-driven guidance, CareerLens aims to bridge the gap between student capabilities and evolving industry demands.

DOI: https://doi.org/10.5281/zenodo.19550142

 

Published by: vikaspatanker