Using machine learning to predict the risk of algae bloom
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...The effect of COVID-19 on the USA house market
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?
Read More...Comparative study of machine learning models for water potability prediction
The global issue of water quality has led to the use of machine learning models, like ANN and SVM, to predict water potability. However, these models can be complex and resource-intensive. This research aimed to find a simpler, more efficient model for water quality prediction.
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...Who controls U.S. politics? An analysis of major political endorsements in U.S. midterm elections
The authors analyze political endorsement patterns and impacts from the 2018 and 2020 midterm elections and find that such endorsements may be predictable based on the ideological and demographic factors of the endorser.
Read More...Global trends in total cholesterol by gender (1980-2018)
This study explores global trends in average total cholesterol levels among adults from 1980 to 2018, finding a significant decline in both men and women, with a sharper decrease among men. While these improvements likely reflect advances in public health and medical treatment, the persistent gender gap highlights the need for more targeted approaches to cardiovascular disease prevention.
Read More...Uncovering the hidden trafficking trade with geographic data and natural language processing
The authors use machine learning to develop an evidence-based detection tool for identifying human trafficking.
Read More...Social and psychosocial factors associated with mood states among adolescents: A questionnaire-based study
The authors assess the relationship between supportive family environments and internalized stigma in adolescents.
Read More...Distributional effects of residential energy tax credits: A machine learning approach
Tax incentives for sustainable technology are a key part of the push for a greener future. However, these incentives may not reach all income strata equally. Using a machine learning approach, this study analyzed the distributional effects of residential energy tax credits across different income levels in the United States.
Read More...Demographic trends of alcohol and marijuana co-use: examining age, gender, and race/ethnicity trends
This study aims to examine the demographic factors that predict patterns of co-use of alcohol and marijuana in the United States. Significant findings were identified using data from the National Survey on Drug Use and Health (2012-2022), showing that there were significant differences in the prevalence of substance use among demographic groups, with young adults showing the highest co-use of alcohol and marijuana.
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