In this article, the authors identify the characteristics that make a book a best-seller. Knowing what, besides content, predicts the success of a book can help publishers maximize the success of their print products.
Read More...A Novel Model to Predict a Book's Success in the New York Times Best Sellers List
In this article, the authors identify the characteristics that make a book a best-seller. Knowing what, besides content, predicts the success of a book can help publishers maximize the success of their print products.
Read More...Simulations of Cheetah Roaming Demonstrate the Effect of Safety Corridors on Genetic Diversity and Human-Cheetah Conflict
Ecological corridors are geographic features designated to allow the movement of wildlife populations between habitats that have been fragmented by human landscapes. Corridors can be a pivotal aspect in wildlife conservation because they preserve a suitable habitat for isolated populations to live and intermingle. Here, two students simulate the effect of introducing a safety corridor for cheetahs, based on real tracking data on cheetahs in Namibia.
Read More...Weather-based power outage prediction in New York City: An ensemble machine learning approach
This study contributes to our understanding of how urban energy systems respond to climate variability and inform strategies for enhancing power grid resilience. The findings can help inform urban planners and infrastructure developers by identifying the factors that make regions within a power grid more vulnerable.
Read More...Predicting the spread speed of red imported fire ants under different temperature conditions in China
The authors looked at non-natural factors that influenced the spread rate of fire ants in multiple cities in China.
Read More...Predicting voting and union support in certification elections: Evidence from Starbucks workers, 2021-2024
The authors looked at unionization petitions from Starbucks workers between August 2021 and July 2024 to determine what factors influence votes for or against unionization.
Read More...Stock price prediction: Long short-term memory vs. Autoformer and time series foundation model
The authors looked the ability to predict future stock prices using various machine learning models.
Read More...Optimizing an eDNA assay and field deployment to detect decapod species in Oʻahu streams
This study explored the use of environmental DNA (eDNA) methods to detect native Hawaiian decapod species (‘opae), which are difficult to observe manually due to their low density.
Read More...Minimizing distortion with additive manufacturing parts using Machine Learning
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.
Read More...Gender disparities in tennis media
The authors analyze differences in sports commentary between men's matches and women's matches during the 2023 US Open.
Read More...Creating a drought prediction model using convolutional neural networks
Droughts kill over 45,000 people yearly and affect the livelihoods of 55 million others worldwide, with climate change likely to worsen these effects. However, unlike other natural disasters (hurricanes, etc.), there is no early detection system that can predict droughts far enough in advance to be useful. Bora, Caulkins, and Joycutty tackle this issue by creating a drought prediction model.
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