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Author

S. K. Sahani

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Open access Sep 2026

Regularization of Divergent Series via Classical Summability Methods with Applications to Reliability and Engineering Systems

Accurate estimation of remaining useful life (RUL) from noisy and oscillatory degradation data remains a fundamental challenge in prognostics and health management (PHM), especially in safety-critical and resource-constrained settings. While modern data-driven methods achieve high predictive accuracy, they often requir...

S. K. Sahani, Kameshwar Sahani, Aashiq Mahato et al. · 0 citations
Sep 2026

Mathematical Modeling and Deep Learning for Early Prediction of Fluid Hazards in Mountain Communities

Mountain communities are increasingly exposed to rapidly evolving fluid hazards, including flash floods, rainfall-triggered debris flows, glacial lake outburst floods (GLOFs), and flood–landslide cascades. Their short response times, complex terrain, sparse observational networks, and changing hydro-climatic conditions...

Aman Gupta, S. K. Sahani · 0 citations
Review Open access Aug 2026

Trust and Acceptance in Human–Robot Interaction: Psychological Foundations for Industry 5.0

A human‐centered approach for strong and calibrated trust for Industry 5.0 is proposed, which includes the integration of transparent XAI, human state monitoring, cultural adaptation, proactive interaction, and adaptive trust models.

Salony Sah, Aashiq Mahato, Rishav Jha et al. · 0 citations
Open access Jul 2026

Hybrid Analytical Numerical and Machine Learning Frameworks for Solving Deterministic and Stochastic Differential Equations with Stability, Convergence, and Uncertainty Quantification

This work introduces a unified hybrid analytical–numerical–ML framework for deterministic and stochastic differential equations that provides a principled pathway toward physically consistent, scalable, and uncertainty-aware solvers for complex dynamical systems.

S. K. Sahani · 2 citations
Review Open access May 2026

Data-Driven Identification of Stochastic Dynamical Systems

Identifying stochastic dynamical systems from observational data remains a major challenge in applied mathematics and engineering, particularly when complex systems are influenced by random perturbations and incomplete empirical information. This comprehensive review aims to examine state-of-the-art data-driven methods...

Rishav Jha, Kameshwar Sahani, S. K. Sahani et al. · 0 citations

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