Authors: Nupur Pradip Panchal, Sakshi Sanjay Shinde

Abstract: This research report presents the development and evaluation of a deep learning-based system for the automated detection of plant diseases through leaf image analysis. Aimed at addressing the significant economic impact of crop diseases in agriculture, the project leverages a Convolutional Neural Network (CNN) model trained on the publicly available Plant Village dataset. The implemented system processes leaf images through stages of pre-processing, augmentation, and feature extraction to classify diseases in crops such as tomato, potato, and maize. The model achieved a high classification accuracy of 96.5%, with supporting precision, recall, and F1-scores all above 95%. The study successfully demonstrates the technical feasibility of using image processing and deep learning for accurate, rapid disease identification. A key innovation proposed is the deployment of this model on a mobile application, which would provide farmers with an accessible tool for early disease detection and improved crop management, thereby enhancing agricultural productivity. The report also discusses the current limitations and potential future integrations with IoT and advanced imaging technologies for broader field application.

DOI: https://doi.org/10.5281/zenodo.19567125

Published by: vikaspatanker

Authors: Saif Chaudhary, Faizan Bari, Arbab Ansari, Fahim Shaikh, Prof. Anuja Kamat

Abstract: The rapid evolution of technology and the expanding digital economy have created significant complexity in career decision-making for students and fresh graduates. Traditional career counselling approaches are static, generalized, and fail to account for individual skill profiles, evolving industry demands, and personalized learning trajectories. This paper presents ElevateX, an AI-powered career guidance platform that leverages large language models (LLMs) and natural language processing (NLP) to deliver personalized career recommendations, skill gap analysis, dynamic learning roadmaps, project suggestions, resume insights, and mock interview simulations. ElevateX engages users through an intelligent questionnaire that assesses their skills, interests, and aspirations, and subsequently generates actionable guidance tailored to their profile. Experimental evaluations demonstrate high user satisfaction, improved career clarity, and measurable gains in skill awareness among participants. The platform addresses a critical gap in accessible, personalized, and data-driven career counselling for the student community.

DOI: https://doi.org/10.5281/zenodo.19566697

Published by: vikaspatanker

Authors: Ch. Saiharsha, D. Sathvika, J. Siddhi Haarika, P. Yuktha Laasya

Abstract: Braille literacy is very vital in facilitation of independent reading, education and communication among the visually impaired. Availability of affordable Braille learning and display systems is however low especially in environments with limited resources whereby commercial refreshable Braille displays are prohibitively expensive. In this paper, a low-cost assistive platform that is intended to aid in the learning of the Braille, visualization, and prototype of a system is presented. The offered system makes Grade-1 patterns of Braille represented in real-time, which lets the user comprehend the character mapping and sequencing. The design is focused on affordability, modularity and implementation ease, which fits the educational institutions and assistive technology development. The system has been proven to be reliable in converting textual input into relative Braille patterns. Even though the existing implementation offers a non-tactile representation, it is an effective training/validation tool of students, educators, and researchers. The suggested solution demonstrates the possibility of creating scalable and cost-efficient assistive solutions.

Published by: vikaspatanker

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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Published by: vikaspatanker

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