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Neural Networks (NNs), particularly in their deep learning variants, have revolutionized pattern recognition and function approximation in high-dimensional spaces. They have emerged as powerful too...

The objective of the thesis is to compare the power of the programming languages R and Python with regard to the implementation of selected advanced statistical analysis methods. Naturally, such a ...

To improve the performance of R programs, it is essential to optimize runtime and / or memory usage. In this study, the following performance optimization methods are focused on: oVectorization oUs...

When simulating random numbers from correspondingly parameterized statistical probability distributions, the pertaining statistical moments (if they exist and are finite) can be determined numerica...

When simulating random numbers from correspondingly parameterized statistical probability distributions, the pertaining statistical moments (if they exist and are finite) can be determined numerica...

Risk perception significantly influences individual and societal decision-making. While accurate risk assessment is critical for rational behavior and policy formulation, risks are often overestima...

While much research has focused on the overestimation of risk, the underestimation of risk can be equally, if not more, consequential in both personal and societal contexts. This paper explores the...

This dissertation explores how frontline idea generation in healthcare organizations is shaped by middle management behavior and the experience of prior ideation success. Drawing on qualitative and...

The summation of random variables is central in probability theory and statistical modeling. Understanding how the sum of independent univariate distributions results in another known distribution ...

In probability theory and statistics, functions of random variables play a central role in modeling, simulation, and inference. While the addition and multiplication of random variables are often w...

Understanding how random variables transform under arithmetic operations is a foundational problem in probability theory. Of particular interest is the difference operation, where for two independe...

The behavior of random variables under multiplicative combination is a topic of significance in diverse fields such as signal processing, finance, hydrology, wireless communications, Bayesian stati...

The increasing dominance of Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning in data-driven disciplines has raised critical questions about the continuing relevance of traditio...

Numerical simulations are a cornerstone of modern scientific inquiry and technological development. They enable researchers to analyze complex systems that are analytically intractable or experimen...

Mathematical modeling constitutes a central pillar of modern science, providing indispensable tools for analyzing, predicting and optimizing complex real-world systems across a wide array of discip...