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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.

This study evaluates the potential of natural language processing (NLP) models in an emotion-driven bibliotherapy framework to improve mental health challenges.

The authors assessed the correlation between the stock, commodity, and consumer markets with the housing market.

The authors looked at the feasibility to predict wind speeds that will have less reliance on using historical data.

Advertising platforms like Google Ads use AI to drive the algorithms used to maximize advertisers benefits. This study shows that AI does not adjust it strategy based on auction type and highlights the limitations of AI running without explicit guidance.

Here, seeking to explore new antimicrobial therapies, the authors investigated the antimicrobial activity of Maitake mushroom extract against Staphylococcus epidermidis, a common cause of antibiotic resistant hospital-acquired infections. They found that Maitake extract showed potent antimicrobial activity, with higher concentrations showing inhibition comparable to tetracycline.

Authors emphasize the challenges of manual tumor segmentation and the potential of deep learning models to enhance accuracy by automatically analyzing MRI scans.

The authors compare the predicted versus actual geyser eruption times for the Old Faithful and Beehive Geysers at Yellowstone National Park.

The authors investigate how well AI-detection machine learning models can detect real versus AI-generated art across different art styles.

In this study the authors looked at developing a more efficient particle collision classification method with the goal of being able to more efficiently analyze particle trajectories from large-scale particle collisions without loss of accuracy.