The Digital Future: Is XRP Quietly Laying the Infrastructure for Tomorrow's Financial System?
Web-Based Smart Mental Health Assistant using NLP for Sentiment Analysis, Emotion Detection, and Crisis Support
A Novel Approach for Decentralized Hospital Record and Account Management by Blockchain
Real-Time Facial Attendance Monitoring System using CNN and Blockchain Technology
Information Security Enhancement in Agriculture using Blockchain Technology
Transforming VLSI Design with AI: Pioneering the Future of Chip Technology
Robust Phishing URL Detection using Hybrid Deep Learning Models
An Overview of Hacking as a Service (HaaS) in Africa
E-Tendering System using Blockchain
A Wristwatch-Based Real-Time Monitoring, Tracking, and Emergency Response System for Fishermen by Integrating Sensor Technologies and Dual Signal Communications
Real-Time Facial Attendance Monitoring System using CNN and Blockchain Technology
Information Security Enhancement in Agriculture using Blockchain Technology
A Novel Approach for Decentralized Hospital Record and Account Management by Blockchain
The Digital Future: Is XRP Quietly Laying the Infrastructure for Tomorrow's Financial System?
Robust Phishing URL Detection using Hybrid Deep Learning Models
This research paper investigates the potential of XRP, the digital currency developed by Ripple Labs, as a foundational element for the financial systems of tomorrow. Utilizing a qualitative case study methodology, the paper systematically analyses XRP's technological framework, including its consensus mechanism and transaction efficiency, while exploring its strategic partnerships with financial institutions and central banks. The findings reveal that XRP possesses significant advantages over traditional cross-border payment systems, particularly in terms of speed and cost reduction, thereby positioning itself as a central player among emerging digital assets. Notably, the study uncovers that XRP's role as a bridge currency for Central Bank Digital Currencies (CBDCs) could significantly enhance financial interoperability and promote greater financial inclusion. However, the landscape is troubled with challenges, as expanding competition from other cryptocurrencies and increasing regulatory scrutiny present formidable hurdles for XRP's broader adoption. Considering these findings, this research offers future suggestions, which include the development of a cohesive regulatory framework that can adapt to the evolving digital asset landscape, as well as the necessity for proactive engagement from stakeholders to fully leverage the transformative potential of XRP. Overall, this study underscores XRP's position at the forefront of the digital asset revolution, illustrating both the opportunities and complexities associated with integrating blockchain technology into existing financial frameworks.
The global burden of mental health challenges, particularly among students and young adults, necessitates innovative digital solutions that are both accessible and effective. This paper proposes the design of a web-based Smart Mental Health Assistant to address critical gaps in current digital support tools. The core innovation of the proposed system lies in its integrated architecture, which leverages a fine-tuned Natural Language Processing (NLP) engine for nuanced sentiment analysis and multi-label emotion detection. A key feature is a novel hybrid crisis detection model that combines rule-based filters with contextual machine learning to identify high-risk user communications with high sensitivity. The proposed platform is designed to offer a comprehensive suite of features through a unified web interface, including an empathetic chatbot for real-time interaction, a mood tracking and visualization dashboard, a personalized recommendation engine for coping strategies, and an emergency response module. The design methodology follows an iterative, user-centered approach to ensure usability and engagement. While formal results are pending implementation, the proposed system is designed to surpass existing solutions by integrating advanced NLP capabilities with proactive safety mechanisms, aiming to provide a more holistic, responsive, and secure form of AI- powered mental health support.
The fragmented nature of healthcare systems typically leads to inefficiencies in patient care coordination, particularly when individuals transition between providers. This paper proposes a blockchain-based framework to address the challenge of decentralized medical record and billing management. By assigning patients a unique blockchain public address, health-care providers can securely access historical treatment data, prescriptions, and billing information through a tamper-proof, patient-authorized ledger. The system employs smart contracts to automate access permissions, ensuring only verified providers retrieve encrypted records after obtaining patient consent. Cryptographic techniques, such as asymmetric encryption, safeguard sensitive data while enabling interoperability across disparate healthcare networks. A hybrid architecture combines on-chain metadata (e.g., transaction hashes, timestamps) with off-chain storage of encrypted records through distributed file systems, balancing scalability and security. The solution minimizes administrative redundancies, reduces billing disputes, and mitigates risks of incomplete medical histories. Case study simulations demonstrate a 40% reduction in duplicate diagnostic tests and a 30% improvement in billing accuracy compared to traditional electronic health record (EHR) systems. By prioritizing patient-centric data ownership and regulatory compliance, such as HIPAA and GDPR, this framework enhances care continuity, fosters trust among stakeholders, and establishes a scalable model for secure health information exchange.
In today's digital era, efficient and secure attendance monitoring is crucial for organizations, educational institutions, and workplaces. Traditional attendance systems, such as manual registers and RFID-based methods, are prone to fraud, manipulation, and inefficiencies. The system employs a CNN-based deep learning model to detect and recognize faces in real time, ensuring high accuracy and robustness against spoofing. The attendance records are then stored in a blockchain ledger, which guarantees tamper-proof, decentralized, and transparent record-keeping. By integrating smart contracts, the system ensures automated and immutable attendance tracking, reducing administrative overhead and eliminating proxy attendance. This approach enhances security, scalability, and efficiency, making it suitable for academic institutions, corporate environments, and government offices. Experimental results demonstrate that our proposed system achieves high accuracy in facial recognition while maintaining data integrity and security through blockchain implementation.
The agricultural sector faces numerous challenges regarding data integrity, supply chain transparency, and information security. Conventional systems for managing agricultural records, transactions, and logistics are vulnerable to data tampering, fraud, and inefficiencies. Blockchain technology, with its decentralized, immutable, and secure architecture, presents a transformative solution. This paper explores the application of blockchain in enhancing information security in agriculture. A framework is proposed to integrate blockchain with agricultural data management, ensuring confidentiality, authenticity, and accountability in the supply chain. Experimental analysis and case studies demonstrate blockchain's potential to mitigate cyber risks, build trust among stakeholders, and improve efficiency.
