Complex network theory has become a key analytical framework in modern physics for studying structure, dynamics, and emergent behaviour in complex systems.

Machine learning-driven carrier risk modeling enables supply chains to predict and prevent pickup defects, reducing costs and improving on-time performance.

Three LangChain flaws enable data theft across LLM apps, affecting millions of deployments, exposing secrets and files.

Abstract: This article investigates the nonlinear model predictive control (NMPC) for electric bus operations (EBOs) under dynamic environments, based on the generalized disjunctive programming (GDP) ...

Nonlinear relationships are common in applied research, especially in education, health, and economics. While Python provides statsmodels for mixed-effects models and patsy for spline construction, ...

audio/ includes all sound examples for the datasets used in the paper. Some of these sound examples are presented on the accompanying web-page. cfg/ includes configuration files for experiments. src/ ...

If you've been planning to step up your data science game for the new year, the 2026 NPTEL course lineup from India's top IITs is honestly a goldmine. These courses cover the backbone of modern ...

Escola de Química, EPQB, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Rio de Janeiro 21941-909, Brazil Programa de Engenharia Química, PEQ/COPPE, Universidade Federal do Rio de Janeiro, Rio ...

ABSTRACT: In order to better extract the displacement fault signals inside bearings based on the vibration characteristics of rolling bearings after failure, a two-degree-of-freedom model simplifying ...

Abstract: This paper presents a novel approach to practical nonlinear model predictive control (PNMPC) using Kolmogorov–Arnold networks (KANs) as prediction models. KANs are based on the ...