Louisiana State University (LSU) professors Supratik Mukhopadhyay and S.S. Iyengar have developed software that can monitor systems and use the data it collects to make decisions on what to do next. The software can sift through massive amounts of data to detect a complex event or pattern. Iyengar says a complex event might involve multiple events that take place over time, with the software comparing the current circumstances to events in the past. Each time the network takes an action, it reevaluates the situation to make the next decision. Iyengar says the software learns quickly, which makes the system as efficient as possible. The researchers’ goal is to embed the software in a computer chip so that customers can take the chip and develop their own interface. They say the system could be adapted for use in many applications, such as military procedures, golf course sprinkler systems, and the electrical power grid.
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Clear and simple visualizations of biomechanical data could improve rehabilitation after a stroke, accelerate the recovery from joint replacements, and prevent older people from falling, according to United Kingdom researchers. University of Strathclyde professor Philip Rowe is leading an initiative to develop bespoke software for capturing biomechanical data and presenting it in a way that would assist health care professionals in their effort to communicate movement information to patients. Currently, movement information is only available in graphical, tabular, or numerical form. The software would work with Strathclyde’s specialist motion analysis system and portable motion sensors. “By using animation, we can enable patients to visualize a movement, and how it affects their body,” Rowe says.
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Tomorrow’s Internet-connected cars could be vulnerable to hackers in the way computers are today, warn researchers at the University of Washington (UW) and the University of California, San Diego (UCSD). During a recent test, the researchers were able to remotely control a car’s braking and other functions. “We demonstrate the ability to adversarially control a wide range of automotive functions and completely ignore driver input–including disabling the brakes, selectively braking individual wheels on demand, stopping the engine, and so on,” the researchers write. The researchers were also able to insert malicious software into the car and then erase any evidence of tampering. “Taken together, ubiquitous computer control, distributed internal connectivity, and telematics interfaces increasingly combine to provide an application software platform for external network access,” write the researchers.
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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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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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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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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 Perception-on-Purpose (POP) project is an effort by European researchers to develop technology enabling a robot to integrate visual and audio data to facilitate purposeful perception. “It is not that easy to decide what is foreground and what is background using sound alone, but by combining the two modalities–sound and vision–it becomes much easier,” says project coordinator Radu Horaud. “If you are able to locate 10 sound sources in 10 different directions, but if in one of these directions you see a face, then you can much more easily concentrate on that sound and throw out the other ones.” The researchers followed this strategy in their development of algorithms that allowed their robot, Popeye, to reliably identify speakers. “Most often, sound research is conducted in specialized labs, with arrays of microphones and a very controlled acoustic environment,” Horaud says. “But we integrated our two microphones and two cameras onto the head of our Popeye. The idea is to have an agent-centered cognitive system.” Horaud believes there is a link between multi-sensory perception and cognition, and that some modern artificial intelligence applications are constrained by their inability to learn from their environment.

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Defcon founder and organizer Jeff Moss, who was named to the U.S. Homeland Security Advisory Council in June, notes that there is a desire in the U.S. Department of Homeland Security (DHS) and other agencies to augment the cybersecurity alert system as well as adopt Web 2.0 technologies. “It goes back to this theme I keep hearing from people there that they need to fully engage in the cyber area with distributing information,” he says. “They want to be more transparent and they want to communicate information faster to broader audiences in different ways. The hang-up seems to be, what are the best ways to do it?” Moss says that DHS has been authorized to hire as many as 1,000 cybersecurity employees over the next three years, but he does not think that specialists are available in such numbers. Moss says agencies’ fierce protection of their bureaucratic fiefdoms plays a part in the U.S. government’s inability to respond adequately to a cyberattack. He acknowledges that the position of cybersecurity czar has been marked by a lot of turnover, and he presents a theory that “the longer you go without a czar the more they realize that maybe they don’t need one, that what they envision what a czar doing, the role is changing.” Moss argues that the position should be one tasked with coordinating intelligence, civilians, and the military. “So it’s probably more important to get the right person and explain the position so they don’t end up with one of these ‘all the responsibilities and none of the authority’ situations, which is what it sounded like, [a] multiple reporting structure with little budget and little staff and no real authority,” he says.

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Massachusetts Institute of Technology’s (MIT’s) Alexey Radul is developing a conceptual framework for computing that could impact artificial intelligence research, parallel computing, and the design of computer hardware. In Radul’s system, multiple logic circuits and memory cells are arranged in a large network. Any logic circuit can exchange data with different memory cells, and any memory cell can exchange data with different logic circuits. However, contradictory data could confuse memory cells, leading to the overwriting of both sets of data. Radul solved this problem by developing memory cells that gradually accumulate information about data instead of just storing it. A programmer using Radul’s system can decide what kinds of information about data the memory cells will store. The cells can track where data comes from, a capability that could be useful in many applications, according to Radul. The system could determine the source of an error in the data, backtrack to that source, and correct all the resulting errors. A more developed version of Radul’s system would enable programmers to specify computational problems in a way that automatically takes advantage of parallelism.