The U.K. e-science grid is being used to run simulations of transistors smaller than 30 nanometers, which will help designers manage the physical constraints that come into effect when working on such a small scale. Hundreds of thousands of tiny transistors have already been simulated, using about 20 years worth of processing time. The researchers hope to understand how such small components function and determine the best way to produce future generations of nanoscale chips. “What we do in these simulations is try to predict the behavior of these devices in the presence of atomic-scale effects,” says the University of Glasgow’s Asen Asenov, who is leading the NanoCMOS simulation project. The current generation of chips features transistors about 32 nanometers in size, but manufacturers want to move to transistors with even smaller components. “What’s happening at such dimensions is that the atomic structure of the transistor cannot be precisely controlled,” Asenov says. “In order to make them work we have to put in impurities to define different regions.” The researchers are learning how to best deploy materials so transistors provide reliable and dependable performance at the nanoscale.

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Accurate, large-scale three-dimensional (3D) computer maps could soon revolutionize how people manage and relate to urban environments. “Everyone is now familiar with 3D maps, we’re trying to take them beyond simple visualization,” says Glen Hart, the head of research at Ordnance Survey, the United Kingdom’s mapping agency. In a project to demonstrate the potential of 3D mapping, researchers used Lidar technology to capture the height of buildings, trees, and other features in Bournemouth, a coastal resort town in south England. Combining the Lidar scans with information from aerial photos and traditional surveys produces a full-color 3D map, built from more than 700 million points and accurate to 4 centimeters in x, y, and z. In comparison, the 3D structures in Google Earth are accurate to about 15 meters. Other efforts to advance 3D mapping include transferring the overlaying techniques already used on detailed digital two-dimensional maps to large-scale 3D maps, including information such as the layout of electric cables or data on air pollution. “Now it’s not just buildings, but floors within the building that could be annotated,” Hart says. The newest generation of maps can capture information such as mailboxes and lamp posts, which are too small to appear on existing city-scale virtual maps. They also can be used to simulate how a proposed building would affect available light in neighboring buildings, for example, or predict wind corridors or dead spots in cell coverage.

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Once primarily a place for outsourcing call centers and repetitive software development, Bangalore is now home to a thriving research and development (R&D) industry that is driving advances in chip and software design and innovative healthcare products, writes Saritha Rai. Google’s Map Maker, Intel’s Xeon processor, Microsoft’s Bing search engine, and Hewlett-Packard’s Dynamic Smart Cool Technology were all designed, at least in part, in Bangalore. Bangalore’s evolution into a mature global R&D center has taken place in only a few years, largely due to an ecosystem of inexpensive talent, maturing skills, and innovative ideas for new products and services. “There is a defined shift post-2007,” says Zinnov Management Consulting’s Praveen Bhadada, author of a recently released study titled “India R&D Talent Pool.” Companies are not just shifting research and development to India, they are also shifting R&D management to India. “By giving core R&D responsibilities to their India heads, companies like Cisco, General Electric, and IBM have pioneered a new global innovation model,” says Navi Radjou, executive director of the University of Cambridge’s Center for India & Global Business. Costs in Bangalore are similar to other global R&D centers such as Shanghai, the Ukraine, and Russia, according to Zinnov’s analysis. Bangalore does have some challenges, particularly a weak infrastructure. However, Radjou says that using Bangalore or Shanghai to shape Western businesses’ global identities is a smart strategy given that emerging markets will account for much of their future economic growth.

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Advanced computer modeling has enabled British Petroleum (BP) to determine the best design and operating conditions for its oil refinery in Kwinana. BP teamed up with the Curtin University of Technology and the University of Newcastle to develop a computational fluid dynamics (CFD) model for the refinery’s catalyst strippers, which use steam to separate hydrocarbons from the process that breaks up heavy crude oil into smaller molecular parts. A team led by Curtin’s Center of Process Systems Computations (CPSC) used the CFD model to evaluate the internal structure that impacts the interactions between gases and solids, and to determine the optimal mix of steam, catalyst, and hydrocarbons inside the stripper. CPSC director Vishnu Pareek says simulating a few seconds of real-time interaction in the catalyst stripper used to take weeks. “This project used innovative techniques to achieve realistic flow predictions with the least amount of computational effort required,” he says. BP says the CFD model will help save hundreds of thousands of dollars annually on steam usage.
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Indiana University and Oak Ridge National Laboratory researchers have developed a method for finding where malicious systems originate. The researchers performed a statistical analysis of Internet Protocol (IP) addresses from blacklists to identify Internet service providers, hosting services, or other autonomous systems with high levels of blacklisted IP addresses. “We wanted to be able to say if a particular network is doing a good job of cleaning up its machines,” says Oak Ridge researcher Craig Shue. The researchers found that some autonomous systems have more than 80 percent of their IP addresses blacklisted. Three U.S.-based hosting providers accounted for more than six percent of one of the blacklists, a disproportionately large percentage for the size of the systems. “This indicates that some [autonomous systems] have either too lax a security policy or may be intentionally harboring cybercrime,” the researchers say. The next step is to evaluate the quality of the blacklist data.
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