Browse Articles

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.

The authors used a particle-in-cell simulation to determine the effects on extensive and intensive metrics. They found that preliminary simulations could be run quickly with much lower particle counts before more technically demanding and comprehensive simulations are performed.

The authors looked at how pharmacokinetics changed depending on the use of an in vitro or an in vivo model.

The authors developed a quantum inspired model for stock market fluctuations.

Here the authors present an autonomous drone air filtration system that uses a novel algorithm, the gradient ascent ML particle filter (GA/MLPF), to efficiently locate and mitigate outdoor air pollution. They demonstrate that their GA/MLPF algorithm is significantly more efficient than the conventional gradient ascent algorithm, reducing both the time and number of waypoints needed to find the source of pollution.

Investigation of the largest rigid shape that can be moved through a circular hallway of unit width with an arbitrary turn angle

The authors looked at the correlation between being able to speak more than one language (multilingualism) and visual imagery. They found multilingual individuals had higher visual imagery as measured by the VVIQ.

In this study the authors looked at the ability of the Discrete Fourier Transform (DFT) to analyze different musical elements. They found that DFT is a powerful method to analyze recorded music.

This study explores how to predict and minimize distortion in 3D printed parts, particularly when using affordable PLA filament. The researchers developed a model using a gradient boosting regressor trained on 3D printing data, aiming to predict the necessary CAD dimensions to counteract print distortion.

The authors investigate the relationship between self-esteem, social desirability, and emotion regulation in children and adolescents.