A new review published in Artificial Intelligence and Autonomous Systems（AIAS） highlights how artificial intelligence can tackle the pervasive problem of missing traffic data in intelligent transportation systems. The study categorizes and compares leading data imputation methods, offering a clear roadmap for researchers and city planners to improve traffic management and smart city operations.

New research warns of declining access to safe, reliable and affordable water in the U.S., urging for better water tracking tools and immediate policy reforms.

Using a cutting-edge adaptive optics system developed at the University of Arizona's Steward Observatory, a growing planet outside our solar system has been discovered to inhabit a gap in a disk of dust and gas. The images provide a glimpse of what our solar system likely looked like during its infancy.

Recently, defect detection systems using artificial intelligence (AI) sensor data have been installed in smart factory manufacturing sites. However, when the manufacturing process changes due to machine replacement or variations in temperature, pressure, or speed, existing AI models fail to properly understand the new situation and their performance drops sharply. KAIST researchers have developed AI technology that can accurately detect defects even in such situations without retraining, achieving performance improvements up to 9.42%. This achievement is expected to contribute to reducing AI operating costs and expanding applicability in various fields such as smart factories, healthcare devices, and smart cities.

Research published in Proceedings of the National Academy of Sciences confirms that fossilized marine invertebrates serve as a powerful tool for understanding long-term ecological change and informing modern conservation efforts.

Faculty members from the Department of Electrical Engineering and Computer Science at University of Tennessee are involved in two collaborative National Science Foundation grants that aim to address health disparities research and enhance the performance and productivity of AI science.