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How Computer Modelers Took On the Ebola Outbreak

Did real-time epidemic modeling save lives in West Africa?

12 min read
A photo of a Liberian child sitting in an Ebola isolation ward
At The Epidemic’s Epicenter: A Liberian child sits in an Ebola isolation ward housing people who might have contracted the contagious disease.
Photo: John Moore/Getty Images

Here’s what we know for sure. On the afternoon of Friday, 3 October 2014, Pyrros A. Telionis got a telephone call from the U.S. government’s Defense Threat Reduction Agency (DTRA). He was sitting in a featureless cubicle in Blacksburg, Va., that would have made the cartoon office drudge Dilbert feel right at home. The voice on the phone was brisk and professional. And highly specific. Could Telionis provide, by 8 o’clock Monday morning, a list of the best places to build Ebola treatment centers in Liberia’s six southernmost counties?

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Deep Learning Gets a Boost From New Reconfigurable Processor

The ReAAP processor allows AI to be faster, more efficient

2 min read
different colored beams of light shooting up
iStock

This article is part of our exclusive IEEE Journal Watch series in partnership with IEEE Xplore.

Deep learning is a critical computing approach that is pushing the boundaries of technology – crunching immense amounts of data and uncovering subtle patterns that humans could never discern on their own. But for optimal performance, deep learning algorithms need to be supported with the right software compiler and hardware combinations. In particular, reconfigurable processors, which allow for flexible use of hardware resources for computing as needed, are key.

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Rory Cooper’s Wheelchair Tech Makes the World More Accessible

He has introduced customized controls and builds wheelchairs for rough terrain

6 min read
portrait of a man in a navy blue polo with greenery in the background
Abigail Albright

For more than 25 years, Rory Cooper has been developing technology to improve the lives of people with disabilities.

Cooper began his work after a spinal cord injury in 1980 left him paralyzed from the waist down. First he modified the back brace he was required to wear. He then turned to building a better wheelchair and came up with an electric-powered version that helped its user stand up. He eventually discovered biomedical engineering and was inspired to focus his career on developing assistive technology. His inventions have helped countless wheelchair users get around with more ease and comfort.

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Learn How Global Configuration Management and IBM CLM Work Together

In this presentation we will build the case for component-based requirements management

2 min read

This is a sponsored article brought to you by 321 Gang.

To fully support Requirements Management (RM) best practices, a tool needs to support traceability, versioning, reuse, and Product Line Engineering (PLE). This is especially true when designing large complex systems or systems that follow standards and regulations. Most modern requirement tools do a decent job of capturing requirements and related metadata. Some tools also support rudimentary mechanisms for baselining and traceability capabilities (“linking” requirements). The earlier versions of IBM DOORS Next supported a rich configurable traceability and even a rudimentary form of reuse. DOORS Next became a complete solution for managing requirements a few years ago when IBM invented and implemented Global Configuration Management (GCM) as part of its Engineering Lifecycle Management (ELM, formerly known as Collaborative Lifecycle Management or simply CLM) suite of integrated tools. On the surface, it seems that GCM just provides versioning capability, but it is so much more than that. GCM arms product/system development organizations with support for advanced requirement reuse, traceability that supports versioning, release management and variant management. It is also possible to manage collections of related Application Lifecycle Management (ALM) and Systems Engineering artifacts in a single configuration.

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