Discover how Monte Carlo analysis helps investors assess risk and make informed decisions. Explore its role in generating ...
Abstract: Simulating multivariate random variables is essential in data analytics as it allows for more accurate modeling, improved decision-making, and a better understanding of complex systems and ...
Objective This study aims to evaluate relationships between self-reported fine motor ability and quality of life (assessed by life satisfaction and life problems) from people with spinal cord injury ...
Background Current diagnosis of antiphospholipid syndrome (APS) relies on antiphospholipid antibodies (aPL) testing, but false-positive aPL results and asymptomatic aPL carriers pose significant ...
Background Teenagers widely use digital devices for information sharing and other daily activities. Their heavy reliance on smartphones and tablets may contribute to repetitive-use injuries of the ...
Cristani, C. and Tessera, D. (2026) A Foundational Protocol for Reproducible Visualization in Multivariate Quantum Data. Open Access Library Journal, 13, 1-13. doi: 10.4236/oalib.1114704 .
Abstract: The past decade has witnessed the success of deep learning-based multivariate time-series forecasting in Internet of Things (IoT) systems. However, dynamic variable correlation remains a ...
If the probability that a randomly selected person will vote in the next election is 0.39, how would we find the probability that more than half of the people in a sample of 1000 will vote? Since the ...
The code is implemented in Python using the PyTorch framework. DACAD is a PyTorch-based framework for unsupervised domain adaptation in multivariate time series anomaly detection that hsa been ...
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