The typical holder of a Ph.D in engineering was paid $70,000 in 1995--more than the median salary for doctorates in major science categories. So finds a report by the National Research Council. The study profiles demographic and employment trends of doctorate-level engineers and scientists in the U.S. The median salary for all science and engineering Ph.Ds was $60,200. The top non-engineering categories were chemistry and physics/astronomy, both at $68,000. Doctorate holders working in the private for-profit sector had the highest median annual salary at $75,000. The figure for those working in educational institutions was $52,000. Engineers did well, too, in patent applications, a measure of productivity. A fourth of the engineering Ph.Ds had applied for patents; 72% got them. The application mark was surpassed only by the 31% submitted by chemistry Ph.Ds. You can find out more about the "1995 Survey of Doctorate Recipients" by e-mailing Peter Henderson at firstname.lastname@example.org.
Truchard will be presented the award at the 2014 Golden Mousetrap Awards ceremony during the co-located events Pacific Design & Manufacturing, MD&M West, WestPack, PLASTEC West, Electronics West, ATX West, and AeroCon.
Robots that walk have come a long way from simple barebones walking machines or pairs of legs without an upper body and head. Much of the research these days focuses on making more humanoid robots. But they are not all created equal.
The IEEE Computer Society has named the top 10 trends for 2014. You can expect the convergence of cloud computing and mobile devices, advances in health care data and devices, as well as privacy issues in social media to make the headlines. And 3D printing came out of nowhere to make a big splash.
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.