Volume 14 | Issue 3 |

 Abstract

This paper presents the design and development of Smart Dustbin System capable to enhance waste management process which is automation and real time monitoring. Over the past few decades, with urbanization growing quickly and population increasing rapidly, there is a strong demand for efficient waste collection systems, while current traditional wise collection systems mainly rely on manual picking inspection and are by fixed schedule. This is where the proposed system plays a role by utilizing sensors and Internet of Things to detect the content level in the bin. A ultrasonic fill level sensor is integrated and a automatic lid gives the possibility of contact less use. When the garbage bin is reached to threshold level, a visual indication displays so while mobile application based wireless telephonic communication is made to related authority. For optimum efficiency a waste compactor is included to maximise bin capacity and minimise the emptying cycle. This anti-dumping autonomous garbage can aims to reduce exposure of humans, and these bins can prevent the excessive contents outflowing to keep smart clean city

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IoT Project

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This project presents the development of a digital Car Wash Time Slot Allocation System designed to optimize scheduling, enhance customer satisfaction, and streamline op- erational management within car wash businesses. The system replaces traditional manual booking methods with a user-friendly web platform that enables customers to view available services, check real-time slot availability, and make instant online reserva- tions. It integrates multiple modules including user management, service listing, appointment booking, secure digital payments, and a customer feedback mechanism. Business administrators can efficiently monitor bookings, manage staff schedules, and generate reports through a centralized dashboard, improving coordination and reducing human error. Incorporating robust non-functional attributes such as security, performance, scala- bility, and reliability, the system ensures encrypted transactions, fast response times, and high availability. Automated notifications and reminders further enhance the user experience by providing timely updates on bookings and service status. Beyond conve- nience, the platform demonstrates how digital transformation can enhance efficiency, transparency, and user engagement in small and medium enterprises. This project highlights practical implementation skills in full-stack web development and database management, while also emphasizing the growing need for technology-driven business automation. Ultimately, it aims to redefine the conventional car wash process by introducing an intelligent, organized, and customer-centric digital ecosystem.

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Time Slot Allocation, Online Appointment Scheduling, Digital Payment Integration, Customer Feedback System, Web-Based Service Au- tomation

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The research paper presents a communication system which uses Ring Learning With Errors (Ring-LWE) lattice cryptography to create secure email encryption that can resist quantum attacks. The security module achieves sub millisecond cryptographic processing on standard hardware through its Number Theoretic Transform (NTT) optimization which produces key generation times of 249 microseconds and encryption times of 468 microseconds and decryption times of 224 microseconds. The stateless cryptographic service is based on polynomial ring with parameters n=1024 and q=12289, which allows efficient computation of NTT. The experiments demonstrate that our method achieves 1.64 times faster performance compared to standard polynomial multiplication methods and the system can process 4,457 decryptions every second.

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post-quantum cryptography, Ring-LWE, lattice based encryption, Number Theoretic Transform, quantum resistant security

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AI is changing the way users communicate with computers. Instead of using traditional graphical software, computers now can be communicated with using natural and conversational methods. However, today's virtual assistants have limited capabilities because basic voice commands are all they can understand, which limits how effective they can be as interactive companions. The current research software combines a speech controlled virtual AI companion system that uses the Whisper speech recognition model for robust speech recognition capabilities and GPT models for high levels of conversational intelligence. The proposed system includes a virtual robotic avatar that enhances embodiment, as well as human interactions with a simulated companion. The proposed system creates simulated conversations via real- time processing of speech input, analysis of users' intent through natural language processing (NLP), and generation of contextually relevant responses through the evolution of conversationally intelligent software. The proposed system is implemented in Python with a LiveKit agent to facilitate real-time communication among users and to support individuals by providing conversational assistance, task reminders, controlling media, and performing basic automated tasks within a simulated environment. Additionally, the proposed system uses noise management techniques and adaptive speech recognition to enhance the performance of the entire system. The experimental analysis involved multiple users and produced a combined average speech recognition accuracy rate of 92% and an average response latency of 2 seconds, indicating that real-time conversations are possible between users and the proposed system. Integration of conversational AI, speech recognition, and virtual embodiment improves upon existing Human Computer Interaction (HCI) methods

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AI Companion, Virtual Human Interaction, Speech Recognition, Natural Language Processing, Whisper, GPT, Conversational AI, LiveKit, Virtual Avatar, Human-Computer Interaction.

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????????? ??? ?????? "?????? ??????????" ?????? ????? ?????? ?? ?? ?????????? ?? ?????????? ???????? ??, ????? ??? ???????? ????? ?? ?? ?????? ?? ??? ??? ????? ??? ??????? ????????????? ???????? ??? ?? ????? ???? ?? ????? ????, ??????? ??????? ??? ?????? ????????? ?? ?? ?????? ???? ???? ???? ??? ??????? ??? ??? ?? ????? ???????, ?????? ????????, ??????? ??? ?????? ???????? ???? ????? ????????? ?? ????? ?? ??? ??, ?? ?? ???????? ?????, ?????? ?? ??????? ?????? ?? ?????? ???? ??? ????? ????? ?? ???? ??? ???????? ??????? ??? ?? ??????? ?? ???????? ??? ???????? ???? ?? ???????? ???? ??? ???? ?? ????? ???? ???, ??????? ?????? ????? ?? ??? ??????? ???, ???? ?????????? ????? ?? ?????? ???? ??? ???

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Artificial Intelligence (AI) has significantly advanced healthcare applications including clinical decision support, medical question answering, diagnostic assistance, and longitudinal patient record analysis. However, standalone Large Language Models (LLMs) frequently suffer from hallucination, factual inconsistency, limited domain grounding, and privacy concerns, making them unreliable for high-stakes medical deployment. Retrieval-Augmented Generation (RAG) has emerged as a robust paradigm that integrates external knowledge retrieval with generative modelling to improve factual accuracy and contextual relevance in healthcare systems. Recent research demonstrates the effectiveness of RAG in secure federated medical diagnosis, clinical decision workflows, privacy-aware telehealth systems, multimodal healthcare question answering, ontology-guided retrieval, hybrid sparse-dense optimization, and automated radiology and pathology report generation. Additionally, studies explore bias mitigation, temporal modelling for longitudinal patient data, cross-hospital transfer learning, explainable risk prediction frameworks, and factual consistency evaluation metrics. Despite these advancements, challenges persist in role-based access control, end-to-end encryption, auditability, regulatory compliance, and real-world hospital deployment.

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Retrieval-Augmented Generation, Medical AI, Large Language Models, Healthcare NLP, Clinical Decision Support

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The growing threat of poaching and habitat destruction has placed immense pressure on wildlife conservation efforts, underscoring the necessity for innovative and real-time surveillance systems. The AI-Powered LoRa Based Wildlife Monitoring and Anti-Poaching System presents an integrated system that uses AI models YOLOv8, for accurate detection of weapons and human intrusion. The system incorporates a Webcam for live image capture, a LoRa communication for long-range, low-power data transmission. Poaching activities are identified using advanced object detection and alerts are triggered for immediate response. Performance testing was carried out to confirm the accuracy of object detection, reliable data transmission, and low energy consumption, achieving real-time performance suitable for remote environments. Advantages include scalability, cost-effectiveness, and continuous monitoring for conservation. Disadvantages include dependency on camera visibility and limited frame rate, which may affect fast-motion detection. Overall, the system offers a practical approach to wildlife protection and proactive anti-poaching measures.

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LoRa, AI, Anti poaching, Wildlife monitoring

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Dvi-daleey raajaneeti banaam teesara vikalp: raajasthaan kee daleey pranaalee kee ek vistrt sameeksha

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Dvi-daleey raajaneeti banaam teesara vikalp: raajasthaan kee daleey pranaalee kee ek vistrt sameeksha

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Elections play a crucial role in the political system of every nation. Elections determine what the future will hold for the nation for the upcoming five years. In India, elections are a crucial part of politics. As technology progresses and increase in globalization necessitate a transformation of the electoral system, since the previous approach has led to significant corruption, Casteism and violence persist; India lacks an adequate management system for conducting elections, which is followed by their consequences. Due to a shortage of staff members, India conducted several elections that demand a significant amount of funding. The Polling Event the Commission of India has periodically implemented numerous reforms in the management of elections throughout the nation. Beginning from paper ballots to electronic voting machines, proxy voting for NRIs and service voters, implementation of limited rights to rejection via NOTA (None of the Above), implementation of Voter Verifiable Paper Audit Trail for strengthening clarity in the election process, Implementation of Voter Photo ID card to prevent impersonation and fraudulent voting, management of elections overseen by ECI and Central Police Forces, along with the establishment of a model code of conduct (MCC) we continue to encounter several issues that necessitate electoral reforms for a democratic India when a qualified Candidate wins the election; we must enforce sections 125A and 126 of the Representation of People Act 1951. Restricted paid news with election connection, restricted government sponsored advertisement, moratorium on exit and opinion polls on news media. We need to add prohibition over antonym donation over political parties and many others. This paper evaluates need, issues and challenges for electoral reforms in India.

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- Elections, electoral reforms, corruption, lack of proper management system, Election Commission of India

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India is widely recognised as one of the most linguistically diverse countries in the world. According to the 2011 census, there are 121 languages, including 22 scheduled languages and 99 non-scheduled languages, as well as numerous other mother tongues spoken throughout the country. To protect this diversity, the Indian Constitution provides safeguards for linguistic minorities through various provisions. Several provisions of the Indian Constitution aim to ensure that linguistic minorities can preserve their languages and culture and have access to educational opportunities in their mother tongue. Despite these guaranteed provisions, the educational experiences of linguistic minorities often reveal a significant gap between constitutional commitment and its practical implementation. Therefore, this study examines the relationship between constitutional guarantees for linguistic minorities and their actual implementation in the educational sector. This study adopts a qualitative research approach to explore and interpret the complexities of language policy, constitutional promises and their practical implications for linguistic minorities in India. This research is primarily based on secondary data sources, drawing on a review of constitutional provisions, language policy, educational policies, government reports and existing scholarly literature on linguistic minorities in India. This approach helps in understanding policy intent and implementation gaps. The study highlights several challenges that hinder the effective implementation of these provisions, including the absence of mother-tongue instruction, the shortage of trained teachers in minority languages, limited availability of textbooks and teaching materials, and, more importantly, the lack of institutional support. The findings suggest that although India has provided a constitutional and policy framework for safeguarding linguistic minorities. But the lack of effective implementation mechanisms and sufficient resources has resulted in ongoing gaps between policy intentions and educational practice. The study argues that strengthening institutional support, enhancing policy implementation, and broadening mother-tongue-based education are vital for protecting linguistic rights and fostering inclusive education across the country.

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linguistic minorities, Constitutional provisions, language policy, educational practices.

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Creative Commons Attribution 4.0 and The Open Definition