Authors: Mridulaxika, Gurpreet Singh, Varuna Tyagi

Abstract: Student dropout is a persistent challenge in higher education, leading to academic, financial, and institutional losses. Accurate early prediction of at-risk students can significantly improve retention through timely interventions. This paper presents a comparative analysis of three ensemble-based machine learning models AdaBoost, Gradient Boosting Machine (GBM), and a proposed Advanced Extreme Gradient Boosting (ADVXGBoost) algorithm for predicting student dropout risk. The models were evaluated using a dataset of 5,000 student records containing demographic, academic, and behavioral attributes. Performance was assessed using 10-fold stratified cross-validation in the WEKA Explorer environment. Experimental results demonstrate that ADVXGBoost outperforms AdaBoost and GBM, achieving the highest accuracy of 90.76%, the lowest error rates, and balanced class-wise prediction. The findings confirm the effectiveness of enhanced boosting techniques for reliable student dropout prediction and decision-support systems in educational institutions.

Published by: vikaspatanker

Authors: Dr. Arati Basumatary

Abstract: Social media has become a special part of society. In the present age, social media is considered the best medium for communication across the world. The availability of the internet has made social media popular with the facility of instant exchange. Especially platforms like Facebook, WhatsApp, Instagram, YouTube etc. have facilitated communication, photo-video sharing from anywhere. From the new generation to the older generation, people are now attracted to and experienced with the use of such social media. It can be said that social media is a suitable platform not only for entertainment but also for education, business etc. The widespread use and popularity of social media is also observed in Assamese culture. Assamese songs-dances, food etc, the original cultural elements have been able to be presented on the world stage through social media. However, in this context, it can be assumed that the authenticity and values of Assamese traditional culture are somewhat hindered. This proposed research paper will also discuss the impact of social media on Assamese culture, including both positive and some negative impacts.

Published by: vikaspatanker

Authors: Manuela christy dany S

Abstract: Wastewater stabilization is one of the primary methods of environmental engineering that can protect public health and preserve aquatic ecosystems. In this regard, increasing wastewater generation due to urbanization, industrialization, and population growth has increased the need for cost-effective, sustainable, and efficient treatment technologies. Wastewater stabilization techniques undertake the reduction of organic matter, nutrients, pathogens, and toxic substances through biological, chemical, and physical processes. Among these technologies, WSPs, sludge stabilization methods, and integrated hybrid systems have shown high efficiency, especially in developing countries and rural regions. This review paper covers a critical and comprehensive synthesis of recent studies on the various technologies of wastewater stabilization. Major topics that will be covered in this review include fundamental aspects of stabilization, design and operational issues of WSPs, stabilization techniques of sludge, hybrid and decentralized systems, and more recent studies on modeling optimization, and AI applications. Much emphasis is placed on the environmental, economical, and public health impacts, along with the shortcoming of the existing systems. Also, resource recovery, energy-neutral treatment, and climate-resilient design are some of the emerging trends pointed out in this review. This paper intends to provide an in-depth understanding among students, researchers, and practitioners regarding the different stabilization technologies of wastewaters and their future research directions towards sustainable wastewater management.

DOI: https://doi.org/10.5281/zenodo.17935085

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Authors: Salihu Aliyu Lawan, Shuaibu Garba Ngulde, Babagana Ibrahim Bukar

Abstract: In this paper, we study some action of S6 on A6. With Particular cases for n 2, 3, …,. and provide new combinatorial and structural insight into direct product actions of symmetric groups. Groups, Algorithms and Programming software (GAP) have been used to compute the elements of stabilizer S6. Orbit-stabiliser theorem and Cauchy-Frobenius lemma were applied to determine the number of S6(x)-orbits and their corresponding length respectively. We established that the action is transitive, faithful and imprimitive for n ≥ 2. Further results include explicit descriptions of point stabilizers, computation of orbit sizes using the Orbit–Stabilizer Theorem. We also established kernel of the action S6 on A6, and the construction of associated suborbitalni graphs and Upper bounds for the diameter of the resulting graphs are obtained, we the generalized the action (Sn)k for any n ≥ 2 on Cartesian products of k sets.

DOI: https://doi.org/10.5281/zenodo.17937347

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Authors: Rutuja Toggi, Akanksha Kawade, Shraddha Deshmukh, Ulka Nikalje, Vaishnavi Hippargi, Professor N.J.Shaikh

Abstract: Digital technologies such as cloud platforms, online video streaming, internet browsing, and IoT devices significantly contribute to global carbon emissions, yet traditional carbon calculators often ignore these digital footprint s. This project introduces an AI-driven Carbon Emission Monitoring Security System that tracks carbon output from digital activities while ensuring cybersecurity. The system leverages Flutter, Spring Boot, MySQL, Python ML, and a React.js dashboard to monitor activities, detect anomalies, score threats, and generate explainable AI reports. Security features include JWT authentication, MFA, refresh tokens, and RBAC. The AI models automatically retrain with new feedback, providing real-time alerts, analytics dashboards, and secure file scanning.

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Published by: vikaspatanker

Authors: Nivashini N

Abstract: Groundwater serves as a primary source of drinking and irrigation water across the world, particularly in developing regions where surface water is scarce. However, increasing anthropogenic activities, geogenic influences, and climatic variability have resulted in deteriorating groundwater quality. This review synthesizes findings from ten recent peer-reviewed studies from Africa, Asia, and the Middle East. The selected studies evaluate heavy metal contamination, hydrochemical processes, water quality index (WQI), multivariate statistical assessments, GIS-based mapping, spatiotemporal variability, and human health risks. Results reveal widespread contamination by arsenic, lead, cadmium, nitrate, fluoride, and other ions, with significant non-carcinogenic and carcinogenic health impacts. Hydrochemical analyses indicate that water–rock interactions, ion exchange, and anthropogenic pollution play dominant roles. This review emphasizes the need for integrated groundwater monitoring, sustainable management approaches, and advanced spatial–temporal tools to ensure groundwater safety.

DOI: https://doi.org/10.5281/zenodo.17934323

 

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Authors: Sujay Dey, Shrey Jaiswal, E Hemasabari

Abstract: The rapid growth of social media platforms has transformed digital communication, content sharing, and online collaboration. This project presents the development of a full-stack social media application using Spring Boot for the backend, React.js for the frontend, and Cloudinary for cloud-based media storage and management. The system is designed to provide core social networking features such as user authentication, profile management, post creation, image and video uploads, likes, comments, and real-time interaction. Spring Boot is utilized to build secure and scalable RESTful APIs, ensuring efficient handling of business logic and database operations. React.js enables the creation of a responsive and dynamic user interface, enhancing user experience through component-based architecture and state management. Cloudinary is integrated to handle media uploads, storage, and optimization, reducing server load and improving performance. Security mechanisms such as JWT-based authentication and role-based access control are implemented to protect user data and ensure authorized access. The proposed application demonstrates how modern full-stack technologies can be effectively integrated to build a scalable, secure, and user-friendly social media platform. This project highlights practical implementation strategies and serves as a foundation for further enhancements such as real-time notifications, chat functionality, and advanced analytics.

Published by: vikaspatanker

Authors: Abhinay Gour, Prof. Geeta Santosh

Abstract: In the evolving landscape of digital communication, ensuring the authenticity and reliability of email addresses and domains is critical for maintaining security, optimizing deliverability, and mitigating fraud. This paper presents an integrated architecture for an AI-driven email verification and domain intelligence system, combining real-time validation, domain reputation assessment, and a dynamic risk scoring engine. The proposed system leverages machine learning algorithms to detect syntactic anomalies, validate domain existence, and assess historical engagement patterns, while incorporating threat intelligence to evaluate potential risks such as phishing, spam, and disposable addresses. By unifying these components, the architecture not only enhances email deliverability but also provides actionable insights for cybersecurity and marketing strategies. Experimental results demonstrate that the AI-enhanced approach significantly outperforms traditional rule-based verification methods in accuracy, response time, and risk detection, offering a scalable solution for organizations requiring robust email and domain trustworthiness assessment.

 

Published by: vikaspatanker

Authors: Hachimenum Nyebuchi Amadi, Happy Prince Nwokoegi, Richeal Chinaeche Ijeoma

Abstract: Distribution efficiency in developing power systems is often undermined by excessive reactive power demand, poor voltage regulation, and high technical losses. The Port Harcourt mainstream 33 kV distribution network in Nigeria, a critical urban supply corridor, is particularly vulnerable to these inefficiencies due to its radial structure, overloaded transformers, and weak reactive power support. Such conditions result in low power factor, under voltage problems, and distribution losses that exceed international performance standards, thereby threatening supply reliability and quality of service. In this study, the Port Harcourt 33 kV distribution network was modeled in MATLAB/Simulink to evaluate its operational performance and investigate the effectiveness of advanced power factor correction (PFC) using a Distribution Static Synchronous Compensator (D-STATCOM). Baseline simulations revealed progressive voltage deterioration along the feeder, with the weakest bus falling to 0.910 p.u., well below the operational limit of 0.95 p.u. Furthermore, the system recorded active power losses of 1.604 MW, equivalent to 9.5% of peak demand, substantially higher than the 2–6% technical loss benchmark recommended by IEEE for efficient distribution systems. Following the integration of D-STATCOM into the network, remarkable improvements were observed. All bus voltages were restored within 0.989-0.999 p.u., with the weakest bus improved from 0.910 p.u. to 0.989 p.u., thereby ensuring compliance with the 0.95-1.05 p.u. standard. In addition, total technical losses decreased sharply to 0.283 MW, equivalent to 2.0% of peak demand, placing the network well within international best-practice thresholds. The findings confirm D-STATCOM as an effective and sustainable solution for improving voltage stability, minimizing technical losses, and enhancing reliability in urban distribution networks.

DOI: https://doi.org/10.5281/zenodo.17918646

Published by: vikaspatanker

Authors: Aakib Beg, Prof. Geeta Santhosh HOD

Abstract: The rapid digital transformation of the automobile service industry has highlighted the inefficiencies of traditional workshop management methods, especially in multi-brand environments. Manual billing, fragmented inventory tracking, and inconsistent labor pricing frequently lead to revenue losses and customer dissatisfaction. Motor Car Hub is developed as a comprehensive Enterprise Resource Planning (ERP) system built on the MERN stack—MongoDB, Express.js, React.js, and Node.js—to address these challenges. Untitled document (2)This study expands on the original system architecture, presenting a deeper analysis of module interactions, database workflows, performance benchmarks, and the measurable operational improvements achieved in real-world simulations. The enhanced paper discusses MERN-driven scalability, the significance of schema flexibility, automated GST-compliant billing, technician performance tracking, inventory forecasting, and role-based access governance. The system shows an 80% reduction in invoice processing time, complete elimination of manual billing discrepancies, and substantial gains in accountability. These expanded insights provide strong evidence that MERN-based ERP solutions can revolutionize automotive workshop management, making operations more transparent, accurate, and data-driven.

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Published by: vikaspatanker