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The purpose of this study was to determine the necessity of previous non-algorithmic attacks (Adversarial Training) in light of algorithmic defense methods (Gradient Masking and Defensive Distillation) against FGSM attacks. We found a significant increase in image classification accuracy from defense methods with the non-algorithmic defense method compared to ones without. By analyzing the significance with a McNemar test, we determined that the inclusion of non-algorithmic defense methods is still necessary in light of new algorithmic defense methods.

The authors studied the impact of AI face-tracking technology on the immersiveness of videogames as an alternative to virtual reality gaming.

About 25% of the food grown never reaches consumers due to spoilage, and 11.5 billion pounds of produce from gardens are wasted every year. Current solutions involve farmers manually looking for and treating diseased crops. These methods of tending crops are neither time-efficient nor feasible. I used a convolutional neural network to identify signs of plant disease on leaves for garden owners and farmers.

Here, seeking to understand the effects of emotion on memory recall, the authors used a study of 30 teenagers, comparing their ability to recall details from information or narrative writing. They found improved recall of narrative writing, suggesting emotional response can contribute to improved memory recall.

The authors investigated adoption rates of solar photovoltaic power at K-12 schools in California.

The main goal of this study is to determine what demographics are related to tuberculosis incidence in the United States populations, particularly if changing demographics are related to differences in tuberculosis risk over two discrete time periods. The major finding is that in the two studied time periods, tuberculosis risk factors were somewhat consistent and may be influenced by things such as immigration, healthcare access, and race or ethnicity, although the top predictor did change.

The authors looked at how vocabulary is impacted in Alzheimer's disease and whether it could be used a predictor of disease onset.

The authors employ computational protein design to identify a mini-protein with the potential to enhance binding of the tight junction protein, claudin-5, at the blood-blood barrier with therapeutic potential for neurodegenerative diseases.

The authors looked at the correlation between being able to speak more than one language (multilingualism) and visual imagery. They found multilingual individuals had higher visual imagery as measured by the VVIQ.

Authors examine the effectiveness of Large Language Models (LLMs) like BERT, MathBERT, and OpenAI GPT-3.5 in assisting middle school students with math word problems, particularly following the decline in math performance post-COVID-19.