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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 hypothesized that closed-circuit television images could be stored with improved resolution by using enhanced deep residual (EDSR) networks.

In this study, the authors tested the ability and accuracy of a neural net to identify patterns in complex number matrices.

In this study, the authors use existing mathematical models to how high school athletes pace 800 m, 1600 m, and 3200 m distance track events compared to elite athletes.

The authors found that SARIMAX-GARCH is more accurate than SARIMAX for load forecasting with respect to energy consumption.

COVID-19 has impacted the way many people go about their daily lives, but what are the main factors driving the changes in the housing market, particular house prices?

In this study, the authors explored whether students' test scores were significantly higher on online exams during the COVID-19 school lockdown when compared to those of the in-person exams before the lockdown.

In this study, the authors assess the factors that allow some speedcubers to solve Rubik's Cubes faster than others.

In this article, the authors investigate whether stock selection across various sectors is efficient enough to outperform an overall market. Stocks from 2006 to 2020 were selected across sectors to calculate beta values using the Capital Asset Pricing Model.

The purpose of the study was to determine whether graph-based machine learning techniques, which have increased prevalence in the last few years, can accurately classify data into one of many clusters, while requiring less labeled training data and parameter tuning as opposed to traditional machine learning algorithms. The results determined that the accuracy of graph-based and traditional classification algorithms depends directly upon the number of features of each dataset, the number of classes in each dataset, and the amount of labeled training data used.