Browse Articles

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.

This manuscript describes a new method of on-the-go passwords using typing characteristics. The authors developed a keyboard and keystroke recording setup and tested it with 30 participants. The results indicated the five chosen parameters are distinct across participants yet consistent across time for each participant, making it a plausible candidate for a behavior-based password system.

This study examined whether eye color affects photophobia and vision in elementary school students and staff, finding no significant relationship between eye color, light sensitivity, or visual acuity. However, photophobia was common across age groups, highlighting the need for greater awareness of light sensitivity in learning environments.

The authors used a particle-in-cell simulation to determine the effects on extensive and intensive metrics. They found that preliminary simulations could be run quickly with much lower particle counts before more technically demanding and comprehensive simulations are performed.

The authors looked at the difference in investing in stock vs. mutual funds.

The authors studied the ability of deep learning models to predict droughts in the midwestern United States.

The authors looked at ways that seizures in patients with glioblastoma could be treated using C. elegans as a model system.

The authors looked the ability of sound sensors to predict clogged pipes when the sound intensity data is run through a machine learning algorithm.

Determination of Penalty Kick Success in Soccer

The authors design and test an easy-to-use and cost-effective mobile app-based alert system to help senior citizens rapidly communicate with caregivers in emergencies or when in need of assistance.