This study examines how socioeconomic status (SES) influences student mathematics achievement across countries by conducting multiple regression analyses to the Trends in International Mathematics and Science Study (TIMSS) 2019 dataset.
Read More...Comparative data analysis on the effect of socioeconomic factors on math proficiency
This study examines how socioeconomic status (SES) influences student mathematics achievement across countries by conducting multiple regression analyses to the Trends in International Mathematics and Science Study (TIMSS) 2019 dataset.
Read More...Vineyard vigilance: Harnessing deep learning for grapevine disease detection
Globally, the cultivation of 77.8 million tons of grapes each year underscores their significance in both diets and agriculture. However, grapevines face mounting threats from diseases such as black rot, Esca, and leaf blight. Traditional detection methods often lag, leading to reduced yields and poor fruit quality. To address this, authors used machine learning, specifically deep learning with Convolutional Neural Networks (CNNs), to enhance disease detection.
Read More...Comparative life cycle analysis: Solvent recycling and improved dewatering scenarios in PHB plastic production
The authors looked at alternative production processes for PHB plastic in an effort to reduce environmental impact. They found that no alternative process was able to significantly decrease the environmental impact of PHB production, but that optimizing dewatering steps during production could lead to the largest improvement on environmental impact.
Read More...An analysis of the distribution of microplastics along the South Shore of Long Island, NY
This study is focused on the distribution of microplastics in Long Island, NY. Microplastics are plastic particles that measure less than 5 mm in length and pose an environmental risk due to their size, composition, and ubiquitous location in the marine environment. Focusing on the South Shore of Long Island, the authors investigated the locations and concentrations of microplastics at four locations along the shore line. While they did not find significant differences in the number of microplastics per location, there were microplastics at all four locations. This finding is important to drive future research and environmental policy as well.
Read More...Exponential regression analysis of the Canadian Zero Emission Vehicle market’s effects on climate emissions in 2030
Here, the authors explored how the sale and use of electric vehicles could reduce emissions from the transport industry in Canada. By fitting the sale of total of electric vehicles with an exponential model, the authors predicted the number of electric vehicle sales through 2030 and related that to the average emission for such vehicles. Ultimately, they found that the sale and use of electric vehicles alone would likely not meet the 45% reduction in emissions from the transport industry suggested by the Canadian government
Read More...Culturally Adapted Assessment Tool for Autism Spectrum Disorder and its Clinical Significance
Diagnosing of Autism Spectrum Disorder (ASD) using tools developed in the West is challenging in the Indian setting due to a huge diversity in sociocultural and economic backgrounds. Here, the authors developed a home-based, audiovisual game app (Autest) suitable for ASD risk assessment in Indian children under 10 years of age. Ratings suggested that the tool is effective and can reduce social inhibition and facilitate assessment. Further usage and development of Autest can improve risk assessment and early intervention measures for children with ASD in India.
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...Student work preferences: Typing or handwriting in the digital era
The authors survey high school students regarding preferences for taking notes by hand versus typing.
Read More...Predicting and explaining illicit financial flows in developing countries: A machine learning approach
The authors looked at the ability of different machine learning algorithms to predict the level of financial corruption in different countries.
Read More...Transfer Learning with Convolutional Neural Network-Based Models for Skin Cancer Classification
Skin cancer is a common and potentially deadly form of cancer. This study’s purpose was to develop an automated approach for early detection for skin cancer. We hypothesized that convolutional neural network-based models using transfer learning could accurately differentiate between benign and malignant moles using natural images of human skin.
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