This article investigates the study methodologies, learning strategies, and motives of spelling bee participants. The authors identify several important educational implications of this work.
Read More...Spelling Bee: A Study on the Motivation and Learning Strategies Among Elementary and Junior-High Student Competitors
This article investigates the study methodologies, learning strategies, and motives of spelling bee participants. The authors identify several important educational implications of this work.
Read More...Drought prediction in the Midwestern United States using deep learning
The authors studied the ability of deep learning models to predict droughts in the midwestern United States.
Read More...Impact of length of audio on music classification with deep learning
The authors looked at how the length of an audio clip used of a song impacted the ability to properly classify it by musical genre.
Read More...Explainable AI tools provide meaningful insight into rationale for prediction in machine learning models
The authors compare current machine learning algorithms with a new Explainable AI algorithm that produces a human-comprehensible decision tree alongside predictions.
Read More...Applying machine learning to breast cancer diagnosis: A high school student’s exploration using R
The authors combine fine needle aspiration biopsy and machine learning algorithms to develop a breast cancer detection method suitable for resource-constrained regions that lack access to mammograms.
Read More...Deep dive into predicting insurance premiums using machine learning
The authors looked at different factors, such as age, pre-existing conditions, and geographic region, and their ability to predict what an individual's health insurance premium would be.
Read More...Using advanced machine learning and voice analysis features for Parkinson’s disease progression prediction
The authors looked at the ability to use audio clips to analyze the progression of Parkinson's disease.
Read More...Using two-step machine learning to predict harmful algal bloom risk
Using machine learning to predict the risk of algae bloom
Read More...Relationship between p62 and learning behavior in male and female mice deficient in hippocampal folliculin
Here the authors hypothesized that reducing folliculin (FLCN) might affect p62 protein levels in the dorsal hippocampus of mice, given their potential functional connection and p62's role in neurodegenerative diseases. Their study, using western blots and a two-way ANOVA on young wild-type mice, found that p62 levels correlated with FLCN expression, but ultimately concluded there's no evidence of a functional connection between FLCN and p62 in this specific model.
Read More...Analyzing market dynamics and optimizing sales performance with machine learning
This study uses interpretable machine learning models, lasso and ridge regression with Shapley analysis, to identify key sales drivers for Corporación Favorita, Ecuador’s largest grocery chain. The results show that macroeconomic factors, especially labor force size, have the greatest impact on sales, though geographic and seasonal variables like city altitude and holiday proximity also play important roles. These insights can help businesses focus on the most influential market conditions to enhance competitiveness and profitability.
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