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Now showing items 11-20 of 22
Interpreting natural language processing (NLP) models and lifting their limitations
(2021-07)
There have been many advances in the artificial intelligence field due to the emergence of deep learning and big data. In almost all sub-fields, artificial neural networks have reached or exceeded human-level performance. ...
Analysis of time series forecasting in application to solar energy harvest
(2022-05)
The promised future applications in solar energy harvest have been remarkably recognized. However, the hourly forecasting of normal solar irradiance (NSI) outputs is considered a problem due to the dynamic nature of ...
Application of Raman and infrared microscopy coupled with chemometrics for the forensic examination of automotive clear coats and paint smears
(2022-07)
Modern automotive paints typically use thinner undercoat and color coat layers protected by a thicker clear coat layer. All too often, a clear coat is the only layer of automotive paint left at the crime scene. Current ...
Polynomials with small elliptic Mahler measure via genetic algorithms
(2020-05)
For a minimal polynomial $f$ we denote by $M(f)$ the Mahler measure of the roots of $f$. The classical Lehmer conjecture is concerned with finding a definitive lower bound for $M(f)$. Lehmer's polynomial is known to have ...
Developing Clinical Decision Support Systems for Sepsis Prediction Using Temporal and Non-Temporal Machine Learning Methods
(2019-07)
In healthcare, diagnostic errors represent the biggest challenge to synthesize accurate treatments. In the United States, patient deaths due to misdiagnoses are estimated at 40,000 to 80,000 per year. It was also found ...
Studying employee absenteeism due to health-related factors: A data-science approach
(2022-07)
United States employers are spending approximately $950 billion on healthcare benefits, and these costs are impeding their ability to compete in their respective markets. Furthermore, these costs do not include employee ...
Analyzing Optimal Performance of Evolutionary Search with Restart as Problem Complexity Changes
(Oklahoma State University, 2006-12-01)
This research explores how the complexity of a problem domain affects the performance of an evolutionary search using a performance-based restart policy. Previous research indicates that using a restart policy to avoid ...
Self-tuned, block-coordinate, and incremental mirror descent methods with applications in machine learning and wireless communications
(2020-07)
Uncertainty, high-dimensionality, and matrix structure of the decision variables are among the main challenges that may arise in addressing a wide range of stochastic optimization and equilibrium problems in machine learning ...
Critical assessment of CEO succession on organizational performance through descriptive and predictive research methods
(2021-07)
This research offers a comprehensive analysis of extant CEO succession literature to discover and illuminate previously unanalyzed variable relationships and potential areas for future research. An analysis is performed ...
Modern process planning for additive manufacturing assisted a 356 aluminum casting
(2023-05)
Foundry engineering integrates mechanical design, thermal-fluid dynamics, and material science to cast components of a unique design. This project was intended to apply these concepts to optimize the casting process of an ...