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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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How Ya Doin'? with COVID-19

Kung et al. | Dec 02, 2021

How Ya Doin'? with COVID-19

In this study, the authors survey students and adults about how the COVID-19 pandemic has impacted their sleep patterns, eating habits, mood, physical activity, and screen time.

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Influence of Infill Parameters on the Tensile Mechanical Properties of 3D Printed Parts

Guan et al. | Jul 17, 2020

Influence of Infill Parameters on the Tensile Mechanical Properties of 3D Printed Parts

Manufacturers that produce products using fused filament fabrication (FFF) 3D printing technologies have control of numerous build parameters. This includes the number of solid layers on the exterior of the product, the percentage of material filling the interior volume, and the many different types of infill patterns used to fill their interior.This study investigates the hypothesis that as the density of the part increases, the mechanical properties will improve at the expense of build time and the amount of material required.

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The Effect of Varying Training on Neural Network Weights and Visualizations

Fountain et al. | Dec 04, 2019

The Effect of Varying Training on Neural Network Weights and Visualizations

Neural networks are used throughout modern society to solve many problems commonly thought of as impossible for computers. Fountain and Rasmus designed a convolutional neural network and ran it with varying levels of training to see if consistent, accurate, and precise changes or patterns could be observed. They found that training introduced and strengthened patterns in the weights and visualizations, the patterns observed may not be consistent between all neural networks.

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Ribosome distribution affects stalling in amino-acid starved cancer cells

Deng et al. | Jan 07, 2022

Ribosome distribution affects stalling in amino-acid starved cancer cells

In this article, the authors analyzed ribosome profiling data from amino acid-starved pancreatic cancer cells to explore whether the pattern of ribosome distribution along transcripts under normal conditions can predict the degree of ribosome stalling under stress. The authors found that ribosomes in amino acid-deprived cells stalled more along elongation-limited transcripts. By contrast, they observed no relationship between read density near start and stop and disparities between mRNA sequencing reads and ribosome profiling reads. This research identifies an important relationship between read distribution and propensity for ribosomes to stall, although more work is needed to fully understand the patterns of ribosome distribution along transcripts in ribosome profiling data.

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Using data science along with machine learning to determine the ARIMA model’s ability to adjust to irregularities in the dataset

Choudhary et al. | Jul 26, 2021

Using data science along with machine learning to determine the ARIMA model’s ability to adjust to irregularities in the dataset

Auto-Regressive Integrated Moving Average (ARIMA) models are known for their influence and application on time series data. This statistical analysis model uses time series data to depict future trends or values: a key contributor to crime mapping algorithms. However, the models may not function to their true potential when analyzing data with many different patterns. In order to determine the potential of ARIMA models, our research will test the model on irregularities in the data. Our team hypothesizes that the ARIMA model will be able to adapt to the different irregularities in the data that do not correspond to a certain trend or pattern. Using crime theft data and an ARIMA model, we determined the results of the ARIMA model’s forecast and how the accuracy differed on different days with irregularities in crime.

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Carbonated liquids and carbonation level

Irina et al. | Jan 21, 2024

Carbonated liquids and carbonation level

In our work we followed the formation of gas bubbles on the surface of the vessel walls in different carbonated liquids, over different time intervals, at different temperatures and in vessels made of different materials. Our results made it possible to identify patterns affecting the process of formation and disappearance of carbon dioxide bubbles.

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Machine Learning Algorithm Using Logistic Regression and an Artificial Neural Network (ANN) for Early Stage Detection of Parkinson’s Disease

Kar et al. | Oct 10, 2020

Machine Learning Algorithm Using Logistic Regression and an Artificial Neural Network (ANN) for Early Stage Detection of Parkinson’s Disease

Despite the prevalence of PD, diagnosing PD is expensive, requires specialized testing, and is often inaccurate. Moreover, diagnosis is often made late in the disease course when treatments are less effective. Using existing voice data from patients with PD and healthy controls, the authors created and trained two different algorithms: one using logistic regression and another employing an artificial neural network (ANN).

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