Browse Articles

The authors propose a method to help first responders find the location of a person within a high-rise building in densely populated areas.

In this study, the authors investigate the effects of acetone on the color of copper chloride (CuCl₂) solution, which has important implications for detecting copper in the environment.

In order to determine whether unmarked soybeans in the market were genetically modified crops, the authors developed a polymerase chain reaction (PCR) screen for DNA lectin.

Multi-perspective drone imagery (adding oblique views to top-down shots) raised crop classification accuracy from 35.73% to 52.93% across five species. The improvement scaled with canopy complexity, from +4.2% for simple rice to +38.1% for structurally complex sugarcane.

The authors studied the accuracy of two commonly used explainable AI techniques for detecting pneumonia in chest x-rays.

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.

The authors develop a method for detecting fake AI-generated images from real images.

Determination of Penalty Kick Success in Soccer

In this study, the authors examine how knowledge, lack of knowledge, and deception affect the rate of perceived exertion and actual performance of teenagers in sprint training. Their results suggest that fully informing athletes about workout duration yields the fastest and most consistent speeds.

The authors develop a machine learning method to reduce misclassification of objects in safety-critical applications such as medical diagnosis.