Tubificine worms are segmented worms that are capable of forming entangled blobs that behave as a single organism to adapt to extreme environmental conditions or migrate more efficiently. Individual worms are capable of elongating, entwining an uneven area of terrain and dragging the collective worm ball through a narrow passageway in laboratory experiments.Tubificine worms are segmented worms that are capable of forming entangled blobs that behave as a single organism to adapt to extreme environmental conditions or migrate more efficiently. Individual worms are capable of elongating, entwining an uneven area of terrain and dragging the collective worm ball through a narrow passageway in laboratory experiments.[#item_full_content]

Unmanned aerial vehicles (UAVs), commonly known as drones, are already used in countless settings to tackle real-world problems. These flying robotic systems can, among other things, help to monitor natural environments, detect fires or other environmental hazards, monitor cities and find survivors of natural disasters.Unmanned aerial vehicles (UAVs), commonly known as drones, are already used in countless settings to tackle real-world problems. These flying robotic systems can, among other things, help to monitor natural environments, detect fires or other environmental hazards, monitor cities and find survivors of natural disasters.[#item_full_content]

Unmanned aerial vehicles (UAVs), commonly known as drones, are already used in countless settings to tackle real-world problems. These flying robotic systems can, among other things, help to monitor natural environments, detect fires or other environmental hazards, monitor cities and find survivors of natural disasters.Unmanned aerial vehicles (UAVs), commonly known as drones, are already used in countless settings to tackle real-world problems. These flying robotic systems can, among other things, help to monitor natural environments, detect fires or other environmental hazards, monitor cities and find survivors of natural disasters.[#item_full_content]

A robot moves a toy package of butter around a table in the Intelligent Robotics and Vision Lab at The University of Texas at Dallas. With every push, the robot is learning to recognize the object through a new system developed by a team of UT Dallas computer scientists.A robot moves a toy package of butter around a table in the Intelligent Robotics and Vision Lab at The University of Texas at Dallas. With every push, the robot is learning to recognize the object through a new system developed by a team of UT Dallas computer scientists.Robotics[#item_full_content]

Automated vehicles (AV) will need updates on driving conditions. Past studies envision roadside infrastructure transmitting such updates via beams of concentrated, millimeter radio waves. However, challenges remain, such as accurately determining the location of a rapidly moving AV so as to track it with a beam, and forming the optimum beam within a short time slot that will reliably transmit data at high rates and low latency.Automated vehicles (AV) will need updates on driving conditions. Past studies envision roadside infrastructure transmitting such updates via beams of concentrated, millimeter radio waves. However, challenges remain, such as accurately determining the location of a rapidly moving AV so as to track it with a beam, and forming the optimum beam within a short time slot that will reliably transmit data at high rates and low latency.Automotive[#item_full_content]

A main crux of neuroscience is learning how our senses translate light into sight, sound into hearing, food into taste, and texture into touch. Smell is where these sensory relationships get more complex and perplexing.A main crux of neuroscience is learning how our senses translate light into sight, sound into hearing, food into taste, and texture into touch. Smell is where these sensory relationships get more complex and perplexing.Machine learning & AI[#item_full_content]

An artificial intelligence with the ability to look inward and fine tune its own neural network performs better when it chooses diversity over lack of diversity, a new study finds. The resulting diverse neural networks were particularly effective at solving complex tasks.An artificial intelligence with the ability to look inward and fine tune its own neural network performs better when it chooses diversity over lack of diversity, a new study finds. The resulting diverse neural networks were particularly effective at solving complex tasks.[#item_full_content]

An artificial intelligence with the ability to look inward and fine tune its own neural network performs better when it chooses diversity over lack of diversity, a new study finds. The resulting diverse neural networks were particularly effective at solving complex tasks.An artificial intelligence with the ability to look inward and fine tune its own neural network performs better when it chooses diversity over lack of diversity, a new study finds. The resulting diverse neural networks were particularly effective at solving complex tasks.Computer Sciences[#item_full_content]

Hirebucket

FREE
VIEW