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Transfer Learning for Small and Different Datasets: Fine-Tuning A Pre-Trained Model Affects Performance

Gupta et al. | Oct 18, 2020

Transfer Learning for Small and Different Datasets: Fine-Tuning A Pre-Trained Model Affects Performance

In this study, the authors seek to improve a machine learning algorithm used for image classification: identifying male and female images. In addition to fine-tuning the classification model, they investigate how accuracy is affected by their changes (an important task when developing and updating algorithms). To determine accuracy, a set of images is used to train the model and then a separate set of images is used for validation. They found that the validation accuracy was close to the training accuracy. This study contributes to the expanding areas of machine learning and its applications to image identification.

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Sports Are Not Colorblind: The Role of Race and Segregation in NFL Positions

Coleman et al. | Oct 23, 2018

Sports Are Not Colorblind: The Role of Race and Segregation in NFL Positions

In this study, the authors conducted a statistical investigation into the history of position-based racial segregation in the NFL. Specifically, they focused on the cornerback position, which they hypothesized would be occupied disproportionately by black players due to their historical stereotyping as more suitable for positions requiring extreme athletic ability. Using publicly available datasets on the demographics of NFL players over the past several decades, they confirmed their hypothesis that the cornerback position is skewed towards black players. They additionally discovered that, unlike in the quarterback position, this trend has shown no sign of decreasing over time.

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The Feasibility of Mixed Reality Gaming as a Tool for Physical Therapy Following a Spinal Cord Injury

DeBre et al. | Apr 04, 2018

The Feasibility of Mixed Reality Gaming as a Tool for Physical Therapy Following a Spinal Cord Injury

Physical therapy, especially for patients with spinal cord injuries, can be a difficult and tedious experience. This can result in negative health outcomes, such as patients dropping out of physical therapy or developing additional health problems. In this study, the authors develop and test a potential solution to these challenges: a mixed reality game called Skyfarer that replaces a standard physical therapy regimen with an immersive experience that can be shared with their friends and family. The findings of this study suggest that mixed reality games such as Skyfarer could be effective alternatives to conventional physical therapy.

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An Analysis of the Density and Patterns of the Solutions of Diophantine Equations of the Third Power

Grewal et al. | Oct 05, 2020

An Analysis of the Density and Patterns of the Solutions of Diophantine Equations of the Third Power

In this study, the authors sought to find out how many mathematical solutions there were to the Indian mathematician Ramanujan's formula, which is a3 + b3 + c3 = d3, and also quantify the densities its solutions. They wrote their own computer program to do so and kept values of a, b, and c less than 10,000. While conducting the analysis, they were also looking for perfect power taxicab numbers and their frequency. They were able to find solutions and densities for the equation. Additionally, while they found that most perfect cube taxicab numbers had a frequency of 2 or 3, they also found on number with a frequency of 42!

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A novel filtration model for microplastics using natural oils and its application to the environment

Park et al. | Jun 27, 2022

A novel filtration model for microplastics using natural oils and its application to the environment

Recognizing the need for a method to filter microplastics from polluted water the authors sought to use nonpolar solvents, palm oil and palm kernel oil, to filter microplastics out of model seawater. By relying on the separation of polar and nonpolar solvents followed by freezing the nonpolar solvent, they reported that microplastics could be extracted with percentages ranging from 96.2% to 94.2%. They also provided an estimation to use this method as part of container ships to clean the Pacific Ocean of microplastics.

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Risk assessment modeling for childhood stunting using automated machine learning and demographic analysis

Sirohi et al. | Sep 25, 2022

Risk assessment modeling for childhood stunting using automated machine learning and demographic analysis

Over the last few decades, childhood stunting has persisted as a major global challenge. This study hypothesized that TPTO (Tree-based Pipeline Optimization Tool), an AutoML (automated machine learning) tool, would outperform all pre-existing machine learning models and reveal the positive impact of economic prosperity, strong familial traits, and resource attainability on reducing stunting risk. Feature correlation plots revealed that maternal height, wealth indicators, and parental education were universally important features for determining stunting outcomes approximately two years after birth. These results help inform future research by highlighting how demographic, familial, and socio-economic conditions influence stunting and providing medical professionals with a deployable risk assessment tool for predicting childhood stunting.

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