Browse Articles

The authors look at using publicly available data and machine learning to see if they can develop a criminal activity index for counties within the state of California.

In this study the authors looked at developing a more efficient particle collision classification method with the goal of being able to more efficiently analyze particle trajectories from large-scale particle collisions without loss of accuracy.

This article describes the relationship between socioeconomic factors and the extent of how the COVID-19 Pandemic affected communities. Factors such as infection rate, vaccination rate, and economic status were all evaluated within the context of this article.

A bottleneck in deleting algal blooms is that current data section is manual and is reactionary to an existing algal bloom. These authors made a custom-designed Seek and Destroy Algal Mitigation System (SDAMS) that detects harmful algal blooms at earlier time points with astonishing accuracy, and can instantaneously suppress the pre-bloom algal population.

Here, seeking to develop an understanding of the properties that determine the viability of piezoelectric flexible materials for applications in electro-mechanical sensors, the authors investigated the effects of the inclusion BaTiO₃ nanoparticles in electrospun Polyvinyledene Fluoride. They found the voltage generated had a piecewise linear dependence on the applied force at a few temperatures.

In this study, the authors hypothesized that closed-circuit television images could be stored with improved resolution by using enhanced deep residual (EDSR) networks.

Food spoilage happens when food is not kept in a good storage condition. Qualitatively estimating the shortened shelf life of food could reduce food waste. In this study, we tested the impact of heat on milk shelf life. Our results showed that an exposure at room temperature (25°C) for 3.2 hours will decrease the shelf life of milk by one day.

In this study, the authors developed and assessed the accuracy of a machine learning algorithm to identify skin cancers using images of biopsies.

Here, seeking to better understand the roles of glycans in the receptors of active sites of neuronal cells, the authors used molecular dynamics simulations to to uncover the dynamic nature of N-glycans on membrane proteins. The authors suggest the study of theinteractions of these membrane poreins could provide future potential therapeutic targets to treat mental diseases.

Using a convolution neural network, these authors show machine learning can clinically diagnose breast cancer with high accuracy.