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" Half a world away from the fighting in Iraq and Afghanistan, nestled near the border of Mississippi and Louisiana, a 34-year-old electrical engineer is wielding one of the planet&amp;#039;s most powerful computers to lend a virtual helping hand to American soldiers. Joshua Fairley&amp;#039;s detailed 3D modeling of warzone scenes, based at the U.S. Army Engineer Research and Development Center (ERDC) in Vicksburg, Miss., has vastly improved the effectiveness of airborne sensors in scoping out deadly ground-based threats. Deployed in space or on aircraft--often in UAVs--electro-optical and infrared sensors scan urban and rural terrain for explosive devices. Automatic Target Recognition (ATR) algorithms then digitally decipher the fuzzy images, picking out the mines from the manholes and the bombs from the bushes. At least that&amp;#039;s the hope, with visual clutter triggering regular false alarms. One very time-consuming and expensive way to improve the sensors would be to fly the systems repeatedly, performing case study after case study. Instead, Fairley and his team have used the ERDC&amp;#039;s Cray XT3, the Defense Department&amp;#039;s second most powerful supercomputer, capable of 40 trillion computations per second, to simulate landscapes from combat and do the case studies in a lab on American soil. What makes the work stand out is the level of detail they are achieving: By taking into account soil types, plant distribution, species of plants and even the distinct characteristics of those species, Fairley says his team has processed data &amp;quot;literally down to the weeds.&amp;quot; Soon, the Army Corps researchers hope to model beneath the ground. Why? &amp;quot;Each plant takes up a certain amount of moisture through its roots,&amp;quot; explains Fairley, who once designed sensors for Lockheed Martin. &amp;quot;That moisture could affect localized temperature, which affects the ability to detect a threat.&amp;quot;  Fairley then uses the sensors to scan these &amp;quot;synthetic images&amp;quot; for potential hazards, taking note of how well the sensors function under certain weather conditions, at certain times of year and even different times of day. That way he can write complex new algorithms to &amp;quot;teach&amp;quot; the sensors, some of which take thermal readings, to distinguish harmless objects from threats. In one case study, he cut the false alarm rate by 75 percent. Results like that, he says, &amp;quot;will benefit the well-being and health of our warfighters, which is a reason why I get up in morning and come to work.&amp;quot; PLUS: Houston Cops&amp;#039; Test Drone Flying in Iraq, Developer Confirms PLUS: Boeing&amp;#039;s Laser-Mounted Humvee Blasts IEDs from Afar  Joshua Fairley and his team scan synthetic images (bottom left) from sensors onboard UAVs to evaluate high and low temperatures, then come up with new algorithms to make the Pentagon&amp;#039;s Cray XT3 computer even smarter in the virtual fight against insurgents on two fronts. "^^<http://www.w3.org/2001/XMLSchema#string>
<http://www.popularmechanics.com/military/a2326/4234516/>