Phase separation, when molecules part like oil and water, works alongside oxygen diffusion to help memristors—electrical components that store information using electrical resistance—retain information even after the power is shut off, according to a University of Michigan led study recently published in Matter.Phase separation, when molecules part like oil and water, works alongside oxygen diffusion to help memristors—electrical components that store information using electrical resistance—retain information even after the power is shut off, according to a University of Michigan led study recently published in Matter.[#item_full_content]

A research team has identified key visual perceptual factors that enhance the viewing experience of 3D displays.A research team has identified key visual perceptual factors that enhance the viewing experience of 3D displays.[#item_full_content]

Deep learning (DL) has significantly transformed the field of computational imaging, offering powerful solutions to enhance performance and address a variety of challenges. Traditional methods often rely on discrete pixel representations, which limit resolution and fail to capture the continuous and multiscale nature of physical objects. Recent research from Boston University (BU) presents a novel approach to overcome these limitations.Deep learning (DL) has significantly transformed the field of computational imaging, offering powerful solutions to enhance performance and address a variety of challenges. Traditional methods often rely on discrete pixel representations, which limit resolution and fail to capture the continuous and multiscale nature of physical objects. Recent research from Boston University (BU) presents a novel approach to overcome these limitations.[#item_full_content]

In recent years, the Massively Parallel Computation (MPC) model has gained significant attention. However, most distributed and parallel graph algorithms in the MPC model are designed for static graphs. Dynamic graph algorithms can deal with graph changes more efficiently than the corresponding static graph algorithms. Moreover, a few parallel dynamic graph algorithms (such as the graph connectivity) in the MPC model have been proposed and shown superiority over their parallel static counterparts. However, there are no existing dynamic all-pairs shortest paths (APSP) algorithms working in the MPC model.In recent years, the Massively Parallel Computation (MPC) model has gained significant attention. However, most distributed and parallel graph algorithms in the MPC model are designed for static graphs. Dynamic graph algorithms can deal with graph changes more efficiently than the corresponding static graph algorithms. Moreover, a few parallel dynamic graph algorithms (such as the graph connectivity) in the MPC model have been proposed and shown superiority over their parallel static counterparts. However, there are no existing dynamic all-pairs shortest paths (APSP) algorithms working in the MPC model.[#item_full_content]

Analyzing and simulating fluid flow is a challenging mathematical problem that impacts various scenarios, including video game engines, ocean current modeling and hurricane forecasting. The core of this challenge lies in solving the Navier–Stokes equations, a set of classical equations that describe fluid dynamics.Analyzing and simulating fluid flow is a challenging mathematical problem that impacts various scenarios, including video game engines, ocean current modeling and hurricane forecasting. The core of this challenge lies in solving the Navier–Stokes equations, a set of classical equations that describe fluid dynamics.[#item_full_content]

When you ask a rideshare app to find you a car, the company’s computers get to work. They know you want to reach your destination quickly. They know you’re not the only user who needs a ride. And they know drivers want to minimize idle time by picking up someone nearby. The computer’s job, says Cold Spring Harbor Laboratory Associate Professor Saket Navlakha, is to pair drivers with riders in a way that maximizes everyone’s happiness.When you ask a rideshare app to find you a car, the company’s computers get to work. They know you want to reach your destination quickly. They know you’re not the only user who needs a ride. And they know drivers want to minimize idle time by picking up someone nearby. The computer’s job, says Cold Spring Harbor Laboratory Associate Professor Saket Navlakha, is to pair drivers with riders in a way that maximizes everyone’s happiness.[#item_full_content]

A new study has found that intelligence, in the form of general cognitive abilities such as perception, thinking and remembering, is more important than hitherto thought at predicting a person’s ability to complete common tasks with a PC. The study was published in the International Journal of Human-Computer Studies in August 2024.A new study has found that intelligence, in the form of general cognitive abilities such as perception, thinking and remembering, is more important than hitherto thought at predicting a person’s ability to complete common tasks with a PC. The study was published in the International Journal of Human-Computer Studies in August 2024.[#item_full_content]

Reasoning, the process through which human beings mentally process information to draw specific conclusions or solve problems, can be divided into two main categories. The first type of reasoning, known as deductive reasoning, entails starting from a general rule or premise and then using this rule to draw conclusions about specific cases.Reasoning, the process through which human beings mentally process information to draw specific conclusions or solve problems, can be divided into two main categories. The first type of reasoning, known as deductive reasoning, entails starting from a general rule or premise and then using this rule to draw conclusions about specific cases.[#item_full_content]

A team of Alberta Machine Intelligence Institute (Amii) researchers has revealed more about a mysterious problem in machine learning—a discovery that might be a major step towards building advanced AI that can function effectively in the real world.A team of Alberta Machine Intelligence Institute (Amii) researchers has revealed more about a mysterious problem in machine learning—a discovery that might be a major step towards building advanced AI that can function effectively in the real world.[#item_full_content]

Researchers at the University of Toronto have found that using virtual and augmented reality (VR and AR) can temporarily change the way people perceive and interact with the real world—with potential implications for the growing number of industries that use these technologies for training purposes.Researchers at the University of Toronto have found that using virtual and augmented reality (VR and AR) can temporarily change the way people perceive and interact with the real world—with potential implications for the growing number of industries that use these technologies for training purposes.[#item_full_content]