Insights into how human brains categorize objects–and their potential for human-computer interfaces as well as neuropsychiatry–have been drawn by members of Carnegie Mellon University’s (CMU’s) Center for Cognitive Brain Imaging using functional magnetic resonance imaging (fMRI) technology. Research from CMU neuroscientists Marcel Just and Vladimir Cherkassky and computer scientists Tom Mitchell and Sandesh Aryal signals that people represent all non-human objects in terms of three dimensions, defined by Just as relating to eating, shelter, and the way the object is employed. With fMRI, the scientists discovered that objects belonging to a specific dimension induced activity in a specific region of the brain. The researchers also learned that they could anticipate which parts of the brain would be triggered by new words and that they could determine how many objects were being thought about. Just says that scientists can “identify the quantity a person is thinking about, as long as [they] instantiate it as an object.” He says the research clears a path for further enhancements in direct communications between the human brain and computers. Additional augmentations to the technology could enable people to communicate with computers by thought.

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The Rugged Software Development Initiative (RSDI) was recently launched by security experts in an effort to ensure that the software writing process includes thinking about security from the very start. RSDI will encourage developers to create resilient software capable of withstanding attacks while performing its normal functions, says The 451 Group’s Joshua Corman, who helped developed the initiative along with OWASP chair Jeff Williams and the Monterey Group’s David Rice. They describe RSDI as a value system for writing secure software, as opposed to a compliance program, and they hope to incorporate the tenets of rugged code development into computer science programs at universities. Unlike other security initiatives, RSDI does not include any new frameworks for secure coding. Instead, Corman says it will serve as an “on-ramp” for secure software development. He envisions the initiative leading to scenarios such as programmers voluntarily pledging to be Rugged software developers or developing an Underwriters Laboratory label for measuring a software’s ruggedness.

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Rutgers University researchers have developed an algorithm to help find open parking spaces, using ultrasonic sensors, global positioning system (GPS) receivers, and cellular data networks. The goal is to create Web-based maps or additions to navigation systems that make parking availability data accessible to those looking for a parking space. The researchers, led by Rutgers professors Marco Gruteser and Wade Trappe, say that data could help alleviate traffic congestion and cut down on energy use. To implement their system, the researchers mounted ultrasonic distance sensors on the passenger-side doors of three cars, which over two months collected parking data in a limited urban area. They then created an algorithm that converted the ultrasonic data into information on available parking spaces. Combining that data with GPS data, the algorithm generated maps that were more than 90 percent accurate. To distinguish parked cars from other objects, such as trees or recycle bins, they measure the length and width of each object using the ultrasonic sensor readings. Gruteser says the parking availability information could be distributed over the Internet and used by drivers to decide whether to park on the street or use a garage.

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Scientists at the Center for Automotive Research at Stanford (CARS) have redesigned an Audi TTS with computers and global positioning system (GPS) receivers so that the car can drive itself. The car will attempt to scale Pikes Peak without a driver at race speeds following a GPS trail from start to finish. “Our first goal is to go up Pikes Peak at speeds resembling race speeds, keep the car stable around corners, and have everything work the way we want it to,” says Stanford’s Chris Gerdes. The car has reached speeds of 130 miles per hour without a driver during test runs at the Bonneville Salt Flats in Utah. It uses differential GPS, which corrects for interference in the atmosphere, and can locate the car’s position on Earth within about two centimeters. The car measures its speed and acceleration with wheel-speed sensors and an accelerometer, and also employs gyroscopes to control equilibrium and direction. “The computer puts all this information together and then compares it to a digital map to figure out how close the car is to the path that we want it to take up Pikes Peak,” Gerdes says.

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