Abstract: We propose an explainable topic modeling method that tracks user interests to elucidate their association with social events while ensuring high reliability and low computational cost.
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, ...
Learn how to model 1D motion in Python using loops! šāļø This step-by-step tutorial shows you how to simulate position, velocity, and acceleration over time with easy-to-follow Python code. Perfect ...
Explore advanced physics with **āModeling Sliding Bead On Tilting Wire Using Python | Lagrangian Explained.ā** In this tutorial, we demonstrate how to simulate the motion of a bead sliding on a ...
ABSTRACT: Accurate prediction of water travel time in drip irrigation systems is essential for efficient water and nutrient delivery. This study develops a predictive model for travel time by ...
ABSTRACT: This study investigates projectile motion under quadratic air drag, focusing on mass-dependent dynamics using the Runge-Kutta (RK4) method implemented in FreeMat. Quadratic drag, predominant ...
Atrial fibrillation (AF) is the most common arrhythmia worldwide, and patient perceptions significantly influence shared treatment decisions. Artificial intelligenceādriven analysis of social media ...
Volatility forecasting is a key component of modern finance, used in asset allocation, risk management, and options pricing. Investors and traders rely on precise volatility models to optimize ...
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