Vol. 3 No. 3 (2025): Volume-III, Number-III, 2025
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Error Mitigation Techniques for Robust Quantum Computing in Financial Modeling: Toward Reliable Quantum Advantage in Near-Term Financial Applications
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The acceleration of quantum computing (QC) presents unprecedented opportunities for computational finance, enabling efficient modeling of complex portfolios, derivative pricing, and risk optimization. However, the inherent noise, decoherence, and gate infidelity in near-term quantum devices termed Noisy Intermediate-Scale Quantum (NISQ) systems limit their practical deployment. This pa ... read more
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Human–Robot Collaboration in Elderly Care: Assessing the Impact of Social Robots on Mental Well-being and Adherence
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As populations age globally, socially assistive and companion robots are emerging as promising tools to support older adults’ mental well-being and adherence to health routines (medication, exercise, appointments). This article synthesizes theoretical frameworks, empirical results, and technological approaches to human–robot collaboration (HRC) in eldercare, with a special focus on mental h ... read more
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Hybrid Quantum-Classical Algorithms for Enhanced Fraud Detection in E-commerce Transactions
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E-commerce fraud detection is a critical component of transaction risk management for digital commerce platforms and payment systems. As fraud tactics grow in sophistication and dataset volumes escalate, conventional machine learning (ML) approaches face challenges in scalability, feature complexity, real-time detection and adversarial resilience. Meanwhile, quantum ... read more -
Investigating the Performance of Quantum Support Vector Machines for High-Frequency Trading Strategies
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High-frequency trading (HFT) strategies operate under extreme requirements of latency, high-dimensional data streams, and rapid decision-making. Classical machine learning models, including support vector machines (SVMs), are widely used in algorithmic trading, but they face limitations when confronted with ultra-high dimensionality, non-stationarity, and the need f ... read more -
Quantum Machine Learning for Personalized Insurance Premium Calculation
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Personalized insurance pricing requires robust estimation of conditional loss distributions from high-dimensional, heterogeneous data (demographics, medical records, telematics, claims histories). Classical ML techniques (gradient-boosted trees, deep neural networks, kernel methods) have advanced personalization but face computational and statistical limits when data are extremely high-dimensio ... read more