Volume 14 | Issue 5 |

 Abstract

This research paper explores the transformative role of intelligent online examination systems in enhancing digital education and ensuring secure remote assessments through the integration of Computer Vision and Facial Recognition technologies. By analyzing AI-powered examination platforms, automated proctoring systems, and real-time student monitoring solutions, the study highlights how these technologies reduce manual supervision, improve exam integrity, ensure authentication accuracy, and provide efficient online assessment management. The implementation of Computer Vision algorithms and Facial Recognition models enables real-time candidate verification, suspicious activity detection, and scalable remote examination solutions tailored to modern educational needs. The paper concludes that intelligent online examination systems significantly contribute to secure digital learning environments by empowering institutions with automated monitoring, transparency, and improved examination reliability.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

This research paper explores the transformative role of intelligent online examination systems in enhancing digital education and ensuring secure remote assessments through the integration of Computer Vision and Facial Recognition technologies. By analyzing AI-powered examination platforms, automated proctoring systems, and real-time student monitoring solutions, the study highlights how these technologies reduce manual supervision, improve exam integrity, ensure authentication accuracy, and pr

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Bharat Soviet Sangh 20 Varshiya Maitri Sandhi 1971 Ek Aitihasik Vishleshanatmak Adhyayan

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Bharat Soviet Sangh 20 Varshiya Maitri Sandhi 1971 Ek Aitihasik Vishleshanatmak Adhyayan

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Native plant-derived medicinal practices constitute an integral part of traditional healthcare systems in rural India, particularly in biodiversity-rich districts such as Murshidabad, West Bengal. Indigenous communities, traditional healers (Vaidyas, Ojhas), and rural households rely extensively on medicinal plants for treating a wide range of ailments. The present study reviews the traditional ethnomedicinal knowledge associated with native plant species in Murshidabad district and explores their sustainable applications in healthcare and biodiversity conservation. Data from previous ethnobotanical studies indicate that over 50 medicinal plant species belonging to approximately 39 families are commonly used in the district. Frequently utilized plant parts include leaves, roots, bark, fruits, and seeds, addressing ailments such as digestive disorders, skin diseases, fever, diabetes, jaundice, and musculoskeletal problems. Sustainable application of these medicinal resources requires proper documentation, conservation of sacred groves, community participation, cultivation practices, and integration of traditional knowledge with scientific validation. This study highlights the significance of preserving indigenous medicinal knowledge and promoting sustainable utilization for ecological and socio-economic development in Murshidabad.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Ethnomedicine, Medicinal plants, Indigenous knowledge, Sustainability, Murshidabad, West Bengal, Traditional healthcare, Biodiversity conservation

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The urban traffic in cities has gotten so worse as vehicle ownership has grown. Which actually means longer commutes, more fuel burned, and higher emissions. Most of navigation systems handle it the same way they always have: compute a route, react when something slows down. The congestion is already there by the time the system notices. We have built a Dynamic Route Rationalization framework to address this. It combines Graph Convolutional Networks and Long Short-Term Memory models with a modified A* search algorithm. The traffic data comes in through the Google Maps API. The GCN handles spatial structure -- which road segments connect, and how they influence each other. The LSTM handles time -- how patterns shift across the day. The two together makes sure the system forecast congestion a few steps ahead instead of catching up to it. The route selection uses a cost function that weighs distance, travel time, congestion level, incident severity, and predicted conditions. The weights aren't fixed and they shift depending on what's happening. A* then uses that cost to generate routes that avoid congestion before it builds. On urban traffic datasets, the framework reduced travel times, avoided more congestion events, and produced more stable routes during peak hours than baseline approaches.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Urban Traffic Optimization, GCN-LSTM, Dynamic Cost Algorithm, A* Routing, Smart Mobility, Real-Time Traffic Prediction

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The traditional e-learning system allows users to learn new things easily but the problem arises because it fails to consider learning ability of individuals. Some learners have understood the concepts in less time but some takes more time and it does not give importance for increasing critical thinking and gives only limited access to users. This limitation has become the reason to implement new learning system by using artificial intelligence. The main advantage of this work is that it allows learner to give feedback for the quizzes generated by it. Some learners may find the questions easy while others may find them difficult based on this feedback the system automatically adjusts upcoming concepts and question difficulty. It also increases critical thinking of user by analyzing the things in different way rather than just giving importance only for memorizing the things. The system also includes a progress bar in which user can easily see the number of courses they are learning and percentage of each course.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Feedback-Based Learning, Artificial Intelligence, Critical Thinking, Personalized Learning, e-learning System.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Sanskrit Vyakaran evam Nyaya Parampara mein San Pratyay Mithila ke Vishesh Sandarbh mein Ek Darshanik evam Bhashai Vishleshan

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Sanskrit Vyakaran evam Nyaya Parampara mein San Pratyay Mithila ke Vishesh Sandarbh mein Ek Darshanik evam Bhashai Vishleshan

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

ABSTRACT : Ashmari is considered one among the Ashtamahagada described in Ayurveda due to its severe pain, recurrent nature, and difficulty in management1. It is characterized by the formation of stone-like structures in the Mutravaha Srotas due to vitiation of Doshas, mainly Kapha and Pitta 1. Based on the predominance of Doshas, Ashmari is classified into Vataja, Pittaja, Kaphaja, and Shukraja Ashmari. In contemporary science, Ashmari can be correlated with Renal Calculi or Urolithiasis 4, a common urinary tract disorder characterized by the formation of calculi within the kidney or urinary system due to crystallization of urinary salts. Renal calculi are mainly classified into calcium oxalate, uric acid, struvite, and cystine stones. The prevalence of urolithiasis is increasing globally and affects nearly 10-12% of the population, with higher incidence among males and individuals between 20-50 years of age. In India, approximately 5-7 million people are estimated to suffer from renal calculi 5. Major causative factors include inadequate water intake, sedentary lifestyle, altered food habits, excessive intake of spicy and salty foods and suppression of natural urges, metabolic disturbances, and recurrent urinary tract infections 2. Clinically, the condition presents with severe abdominal or flank pain, burning micturation, dysuria, haematuria, nausea, vomiting, and difficulty in urination4. Symptoms are often aggravated by dehydration, dietary indiscretions, and irregular lifestyle, while adequate hydration, proper dietary regimen, and timely treatment provide relief 5. Contemporary management includes analgesics, antibiotics, lithotripsy, and surgical interventions. However, recurrence and associated complications remain common. Among the different types of Ashmari, Pittaja Mutrashmari is characterized by burning micturation, yellowish or reddish discoloration of urine, severe pain, and Pittaja lakshanas due to predominant vitiation of Pitta Dosha along with Kapha 1. The clinical features of Pittaja Mutrashmari show close resemblance with renal calculi associated with inflammation and burning urinary symptoms. Ayurveda offers a holistic approach through Shodhana and Shamana therapies aimed at correcting the underlying Vikruta avasta of Dosha , facilitating disintegration and expulsion of calculi, relieving symptoms, and preventing recurrence. This article highlights the Ayurveda management of Pittaja Mutrashmari with its correlation to renal calculi and demonstrates significant symptomatic relief and reduction in stone size through Ayurveda intervention.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Ashmari, Pittaja Mutrashmari, Renal Calculi, Urolithiasis, Ayurveda, Shodhana, Shamana.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This paper proposes an efficient Wi-Fi-based human activity recognition (HAR) framework integrated with AI-optimized reconfigurable antennas for next-generation 6G communication systems. The approach leverages channel state information (CSI) to enable device-free activity recognition while introducing an adaptive antenna elimination mechanism to enhance energy efficiency and reduce system complexity. The proposed method dynamically deactivates redundant antenna elements based on their contribution to signal quality, achieving optimized hardware utilization without degrading recognition performance. In addition, a lightweight artificial intelligence model is employed to intelligently reconfigure antenna patterns in real time, improving robustness under dynamic environmental conditions. Experimental results demonstrate that the proposed system achieves an activity recognition accuracy of 96.3%, while reducing energy consumption by 28% and computational overhead by 22% compared to conventional multi-antenna HAR systems. The framework shows strong adaptability across diverse indoor scenarios, making it suitable for applications such as smart healthcare, ambient assisted living, and intelligent surveillance. These findings highlight the effectiveness of combining adaptive antenna control with AI-driven optimization for efficient and scalable 6G-enabled sensing systems.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Wi-Fi sensing, human activity recognition (HAR), channel state information (CSI), adaptive antenna elimination, reconfigurable antennas, artificial intelligence, 6G, smart environments.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The Aadhaar Card-Based Complaint Management System (ACBCMS) is a secure digital platform designed to simplify complaint registration, tracking, and resolution for citizens in Municipal Corporations. The system addresses challenges such as identity fraud, duplicate complaints, lack of tracking mechanisms, delayed responses, and administrative inefficiencies by providing a unified web-based environment for managing complaints. It integrates Aadhaar-based authentication through UIDAI to ensure verified user participation and eliminate false or duplicate requests. The platform includes features such as complaint tracking, department-level workflow management, prioritization, and escalation mechanisms to improve efficiency and accountability. Developed with a structured and scalable architecture, ACBCMS ensures secure data handling and smooth coordination between departments. Experimental evaluation indicates reduced complaint duplication by approximately 35-45%, improved resolution efficiency, and enhanced transparency. The proposed system contributes toward strengthening urban governance and improving citizen engagement through a reliable and centralized digital solution.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Aadhaar, UIDAI, Municipal Corporation, Complaint Management System, e-Governance, Digital Identity, Authentication, Transparency, Public Administration

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Customer satisfaction has become one of the most important factors influencing the success and growth of banking institutions in the modern financial environment. Banks are continuously improving their service quality, technological facilities, and customer relationship practices to attract and retain customers. This study focuses on customer satisfaction towards service delivery with special reference to State Bank of India and Union Bank of India. The research aims to analyze the level of satisfaction among customers regarding various banking services offered by these banks. The primary objective of the study is to evaluate customer perceptions about service quality, employee behavior, responsiveness, digital banking facilities, reliability, and overall banking experience. The study also attempts to identify the factors that influence customer satisfaction and compare the service delivery performance of SBI and UBI banks. Both primary and secondary data sources were utilized for the research. Primary data was collected through structured questionnaires distributed to customers of SBI and UBI branches, while secondary data was gathered from journals, websites, reports, and banking publications.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Customer Satisfaction, Service Delivery, Banking Services, SBI, UBI, Digital Banking, Service Quality, Customer Loyalty.

  License

Creative Commons Attribution 4.0 and The Open Definition