Oak Ridge, TN —Designers of medical equipment and diagnostic systems should check out progress on the Virtual Human project being lead by the Oak Ridge National Laboratory (ORNL; www.ornl. gov/virtualhuman). This collection of assets on the Internet is aimed at modeling organs and their behavior on the systems level. The project looks to establish servers with resources, including: libraries of physiological models and anatomical data (for developing equivalent physical "phantom" models of various organs that can be made for device testing); actual patient data (such as EKG and EEG traces); and databases of metabolic and bioprocesses. These would all be linked by a "client" user interface.
For designing seat belts or airbags, for example, designers could use the Virtual Human to study how the organs in the chest would respond to and be affected by a blunt-object or accident trauma. Organ exposure to toxins, such as mercury vapor inhalation, and treatment could also be modeled. With precise models of "well" and "problem" physiological characteristics, designers of safety, medical-imaging, and diagnostic systems will be able to evaluate effectiveness of products earlier in the design cycle.
In an age of globalization and rapid changes through scientific progress, two of our societies' (and economies') main concerns are to satisfy the needs and wishes of the individual and to save precious resources. Cloud computing caters to both of these.
For industrial control applications, or even a simple assembly line, that machine can go almost 24/7 without a break. But what happens when the task is a little more complex? That’s where the “smart” machine would come in. The smart machine is one that has some simple (or complex in some cases) processing capability to be able to adapt to changing conditions. Such machines are suited for a host of applications, including automotive, aerospace, defense, medical, computers and electronics, telecommunications, consumer goods, and so on. This discussion will examine what’s possible with smart machines, and what tradeoffs need to be made to implement such a solution.