Category Archives: Uncategorized

Authors: Dr.M.Sravani, Kalyan Kumar Bethu

Abstract: Stock market volatility makes accurate forecasting vital for informed trading decisions and profit maximization. Over the years, various models have been introduced to enhance the reliability of time series predictions. This study applies the ARIMA model to evaluate data stability and forecast movements in the BSE Index. Model selection was guided by statistical measures including SIGMASQ, Adjusted R², AIC, and BIC, with ARIMA (2,1,2) emerging as the most suitable specification. Using monthly data from January 2021 to January 2025 (49 observations), the model generated forecasts for February 2025 through December 2025, yielding 11 projected values. The results highlight ARIMA’s effectiveness as a short-term forecasting tool, offering actionable insights for informed investment decisions.

DOI: https://doi.org/10.5281/zenodo.17240410

 

Published by: vikaspatanker

Authors: Rutuja Gavai, muniba Ali, zarah Ali, Astha Gulhane, Prof. Sanju D. Garle

Abstract: The effective management of visitors has become a critical aspect of institutional security, smart campus initiatives, and organizational operations. Traditional visitor tracking methods, which rely on manual record-keeping or identity cards, are often prone to errors, delays, and inefficiencies. To address these shortcomings, vehicle plate recognition has emerged as a promising technology for developing intelligent visitor tracking systems. By leveraging the uniqueness of license plates as identifiers, organizations can implement automated, contactless, and reliable mechanisms to verify and monitor visitor entries and exits. This review paper presents a comprehensive survey of existing research on visitor tracking systems that integrate vehicle plate recognition. Key enabling technologies such as image preprocessing, Optical Character Recognition (OCR), fuzzy string matching, and cloud-based services (e.g., Microsoft Azure Cognitive Services) are analyzed for their role in improving accuracy and scalability. The study also discusses the integration of data analytics and reporting frameworks, which transform raw recognition results into actionable insights, such as visitor frequency patterns, identification of unknown vehicles, and predictive analytics for enhanced security planning. In synthesizing current literature, this review identifies major challenges, including image quality variations, diverse license plate formats, and real-time adaptability under unconstrained conditions. It also outlines research gaps in the application of deep learning, edge-based processing, and multimodal verification techniques for intelligent visitor management. The findings highlight that the combination of vehicle plate recognition with intelligent data-driven analysis offers a scalable and efficient pathway toward next-generation visitor tracking systems, particularly in academic institutions, corporate environments, and smart city infrastructures.

 

Published by: vikaspatanker

Authors: Emmadi Uday, Anand Jawdekar, Komati Hema, Lakshmikanth Vuyyuru, Tadikamalla Vinod kumar

Abstract: This paper presents MoviesForYou, a web-based movie booking platform that integrates an AI-powered con- versational chatbot for mood-based movie recommendations, automated seat suggestions, and a data analytics module for theater and revenue insights. The system allows users to describe their mood in natural language; the chatbot leverages language understanding and movie metadata to recommend titles that match the user’s affective state and viewing prefer- ences. The analytics module computes weekly booking trends, genre popularity, theater performance, rating-based summaries, and revenue trend analysis. The platform intentionally supports offline payment workflows (seat-on-hold with time-limited reser- vation) rather than online payment. We describe the system architecture, implementation details (based on the provided project codebase), evaluation methodology, key results, and future directions. The paper includes flowchart and system- architecture placeholders, experimental and analytic outputs, and an APA-style reference list.

DOI: https://doi.org/10.5281/zenodo.17234742

 

Published by: vikaspatanker

Authors: Mr. M. Santhanaraj, S.Dharshini, R.Pooja, B.Devaki

Abstract: This project presents a Blockchain-based University Election System enhanced with biometric authentication and AI-driven anomaly detection to address the challenges of security, transparency, and reliability in student elections. The proposed system verifies voter identity through fingerprint and facial recognition, ensuring that only eligible students participate and eliminating risks of impersonation, duplicate, or proxy voting. Each vote is encrypted and immutably recorded on the blockchain ledger, preventing tampering, deletion, or manipulation while creating a transparent and verifiable audit trail. Smart contracts govern the election process by automating voter eligibility checks, enforcing the one-student-one-vote policy, scheduling the election, and instantly counting and publishing results without human intervention. The integration of AI adds another layer of protection by continuously analyzing voting behaviors, biometric data, and transaction patterns to detect anomalies, suspicious trends, or fraudulent activities in real time. This holistic approach reduces manual errors, enhances accountability, and builds student confidence in the election process through verifiable and tamper-proof outcomes. Additionally, the system is designed to be user-friendly, scalable, and cost-effective, making it adaptable not only for universities but also for larger institutions and government-level elections in the future. By combining blockchain, biometrics, and AI, this project demonstrates a secure, intelligent, and modern framework for conducting elections with integrity and efficiency

DOI: http://doi.org/10.5281/zenodo.17283666

Published by: vikaspatanker

Authors: Lalitha Bhai Jagadeesan

Abstract: – The term Regenerative encompasses a broad and profound area of study, especially when applied within the built environment. Building upon my prior understanding of regenerative design, this research explores the concepts for the healthcare sector—specifically focusing on their potential to reduce energy consumption and enhance the mental well-being of patients, staff, and medical professionals. The study will examine the conceptual design of a hypothetical 100 -bedded hospital and identify regenerative strategies that can be implemented during both the design and execution phases to minimize carbon footprint and operational energy demands. Key areas of investigation will include site selection and planning, energy efficiency strategies, water conservation techniques, indoor air quality improvement, and occupant wellness and comfort. The research will also address biophilic design approaches, smart building technologies, and sustainable healthcare waste management practices. Additionally, the study will incorporate insights from existing green-certified healthcare facilities, evaluating metrics such as staff burnout levels and patient outcomes within regenerative versus conventional hospital environments. A brief comparative analysis of regulatory frameworks and certification systems—such as LEED for Healthcare, WELL Building Standard, the Green Guide for Healthcare (GGHC), and relevant ASHRAE standards—will be used to contextualize and support the proposed strategies. Through this integrated approach, the paper aims to highlight the practical applicability of regenerative design in creating high-performance, healing-centred healthcare spaces.

Published by: vikaspatanker

Authors: Dr. P. Preethi, M. Yuthika, Sadhana Kamaraj, S. Kaviya

Abstract: This web-based system offers five separate login portals designed for students, counsellors, Heads of Departments, Class Advisor and the Principal, ensuring role-specific access and responsibilities. Students can easily submit personal or academic grievances online and monitor their progress. Counsellors manage these grievances by updating their status, adding remarks, and sending email notifications to keep students informed. They also maintain academic records like attendance shortages and disciplinary actions. Unresolved issues are escalated to the HOD for further review and resolution. The Principal oversees the entire system, viewing reports across all departments to ensure transparency and compliance with accreditation standards. The platform is built using Next.js for frontend and backend development, MongoDB for database management, and Tailwind CSS for responsive and modern styling. Email notifications are handled via integration with email services such as EmailJS. This technology stack enables a secure, scalable, and user-friendly system that simplifies communication, enhances accountability, and supports institutional accreditation processes.

DOI: https://doi.org/10.5281/zenodo.17278602

 

Published by: vikaspatanker

Authors: Umudi E.Q, Ekpenyong I.O, Sani M.I, Onwugbuta G C, Ikechukwu S.C, Uzoh R.D, Obruche E.K

Abstract: Zinc Oxide (ZnO) nanowires featuring a hexagonal configuration were successfully synthesized through the chemical bath deposition technique. The characterization of the nanowires was conducted using scanning electron microscopy (SEM), X-ray diffraction (XRD), energy dispersive X-ray analysis (EDX), and a spectrophotometer. The SEM images revealed that the diameters of the ZnO nanowires varied from 170.3 to 481 nm, indicating that a bath solution pH of 8.1 is optimal for the formation of hexagonal ZnO nanowires. The XRD patterns validated that the ZnO nanowires exhibit a hexagonal crystallite structure, with the crystallite size, determined via Scherrer’s equation, increasing with elevated annealing temperatures (0.536 nm, 0.541 nm, and 0.557 nm at 100°C, 150°C, and 200°C, respectively). EDX analysis yielded insights into the elemental composition of the samples, confirming the presence of Zn and O. Results from optical analysis demonstrated that ZnO nanowires possess high absorbance in the ultraviolet and infrared spectra while exhibiting significant transmittance in the visible spectrum. Furthermore, the absorbance of the nanowires was found to increase with higher annealing temperatures. Their notable absorbance in the ultraviolet range indicates potential applications as solar harvesters for capturing solar energy for photovoltaic panels, which can convert sunlight directly into electricity for commercial or industrial use.

DOI: http://doi.org/10.5281/zenodo.17225255

Published by: vikaspatanker

Authors: CEng. Shreekant Patil

Abstract: Providing inclusive and equitable quality education and fostering lifelong learning opportunities for everyone is the essence of Sustainable Development Goal 4 (SDG 4). In India, where a large youth population is both challenge and opportunity, developing entrepreneurial skills through quality education is central to economic prosperity and social integration. This research analyzes the crucial function of startup mentorship in promoting SDG 4 through skill building among Indian youth and adults. Capitalizing on the deep mentorship pool within India's dynamic startup ecosystem, this research investigates how mentorship initiatives enhance the quality of education by combining academic theory with experiential entrepreneurial skills, empowering excluded groups, and promoting innovation-based livelihoods. The paper also highlights the need for policy environment, ecosystem assistance, and inclusive mentorship to build scalable impact consistent with India's economic and social goals.

DOI: http://doi.org/10.5281/zenodo.17225033

Published by: vikaspatanker

Authors: Anushree, Dr. P. Lalitha Associate Professor, Dr. S. Suja Assistant Professor

Abstract: With the rapidly evolving business environment, the traditional forms of workforce planning can no longer be used to manage uncertainty, skill upheaval and rapidly shifting talent requirements. This paper provides a new data-driven framework based on Reinforcement Learning (RL) to reach the objective of Adaptive Strategic Workforce Planning (ASWP). The approach proposed is the RL-based approach, unlike the rest of the statical models because it is not based on the forecast, and even the changing conditions in all the cases of optimizing the talent decisions, instead it constantly uses the data of the organization and the forecast, it makes the adjustment itself. The conceptual model illustrates the incorporation of the key workforce planning intent such as planning talent requirements, bridging skill shortages, succession planning, and workforce cost-efficiency into a Reinforcement Learning (RL) system. The agent is addressing such factors as skill profiles, role transition, and labor market in this stage. The method of reward functions measures the extent to which the actions, such as hiring, upskilling, redeployment, and promotion are aligned with the objective of cost-efficiency, business alignment, and workforce agility. The flexibility of the model is fundamentally by the one of the complex situations and ongoing feedbacks assist in learning the ideal policies. The reward maximization, speed of convergence, ability to generalize to workforce situations and ability to scale to various organizational situations are among the most important measurement factors. Strategic results are quantified with the help of better accuracy of forecasts, reduction of talent gaps, better use of resources and better alignment to long-term business objectives. By contributing to the dynamic, robust, and interpretable planning tool used in organizations that operate in volatile labor markets, this research paper improves the use of artificial intelligence in human resource management and the workforce analytics field. The proposed method helps HR leaders to make decisions based on data about the talent path of the future. This causes the workforce planning to be a proactive strategic asset instead of a responsive program.

Published by: vikaspatanker

Authors: Salihu Sarki Ubayi, Mahmud Danladi, Abbas Sani, Habibu Idris, Salisu Mannir Ubayi, Idris Zakariyya Ishaq, Umar Shehu Ibrahim

Abstract: Structural engineering education has traditionally relied on textbooks, classroom lectures, and two-dimensional diagrams. However, students often struggle to translate these abstract resources into an understanding of real-world structural behavior. This limitation hinders their ability to connect theory with practice. To address this challenge, this paper proposes StructARLearn, a novel software platform derived from Structure + AR (Augmented Reality) + Learning. StructARLearn is an Augmented Reality (AR)-based platform designed to provide immersive, interactive, and experiential learning opportunities in structural engineering. It integrates AR visualizations, real-time finite element simulations, and interactive modules that enable students to apply loads, visualize deformations, and observe structural responses in real-world contexts through mobile devices or AR glasses. By bridging theoretical knowledge with practice, the platform improves comprehension, retention, and engagement. This paper presents the conceptualization and development methodology of StructARLearn, reviews related literature on AR in engineering pedagogy, outlines the framework of the platform, and discusses its anticipated benefits, challenges, and implications for large-scale adoption.

DOI: http://doi.org/10.5281/zenodo.17222735

Published by: vikaspatanker