The authors looked at ways to provide better forecasting on website traffic. They found that deep learning models performed better than statistical models.
Read More...Deep sequential models versus statistical models for web traffic forecasting
The authors looked at ways to provide better forecasting on website traffic. They found that deep learning models performed better than statistical models.
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...Sector Dynamics: Equity and fixed-income performance across market cycles
The authors examined the relationships between S&P 500 Technology and Financials equity sectors and their corresponding investment-grade fixed-income markets from 1995 to 2025.
Read More...How to improve at chess: Uncovering insights using regression analysis
The authors looked at how different factors related to practicing and playing chess would impact a player's rating.
Read More...A comparative analysis of machine learning approaches for prediction of breast cancer
Machine learning and deep learning techniques can be used to predict the early onset of breast cancer. The main objective of this analysis was to determine whether machine learning algorithms can be used to predict the onset of breast cancer with more than 90% accuracy. Based on research with supervised machine learning algorithms, Gaussian Naïve Bayes, K Nearest Algorithm, Random Forest, and Logistic Regression were considered because they offer a wide variety of classification methods and also provide high accuracy and performance. We hypothesized that all these algorithms would provide accurate results, and Random Forest and Logistic Regression would provide better accuracy and performance than Naïve Bayes and K Nearest Neighbor.
Read More...The Effect of Various Preparation Methods on the Spoilage Rate of Roma Tomatoes (Solanum lycopersicum)
As levels of food waste continue to rise, it is essential to find improved techniques of prolonging the shelf life of produce. The authors aimed to find a simple, yet effective, method of slowing down spoilage in tomatoes. Linear regression analysis revealed that the tomatoes soaked salt water and not dried displayed the lowest correlation between time and spoilage, confirming that this preparation was the most effective.
Read More...Understanding the battleground of identity fraud
The authors looked at variables associated with identity fraud in the US. They found that national unemployment rate and online banking usage are among significant variables that explain identity fraud.
Read More...Determining the relationship between unemployment and minimum wage in Turkey
The authors looked at the relationship between unemployment and minimum wage in Turkey (Türkiye). They found that there is a positive correlation between minimum wage and unemployment.
Read More...Too hot to work? Heat waves, household income, and labor adaptation in India
Paper found that heat waves in India are linked to lower household income, agricultural income, and consumption, with agriculture being affected the most. It also suggests farm workers may adapt to extreme heat over time by increasing labor inputs despite rising temperatures.
Read More...Is the NFL Combine predictive of a defensive lineman’s NFL career?
The authors looked at which measurements from the NFL combine were the most predictive of success for defensemen in the NFL.
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