单项选择题

Technology Transfer in Germany

When it comes to translating basic research into industrial success, few nations can match Germany. Since the 1940s, the nation’s vast industrial base has been fed with a constant stream of new ideas and expertise from science. And though German prosperity (繁荣) has faltered (衰退) over the past decade because of the huge cost of unifying east and west as well as the global economic decline, it still has an enviable (令人羡慕的) record for turning ideas into profit.
Much of the reason for that success is the Fraunhofer Society, a network of research institutes that exists solely to solve industrial problems and create sought-after technologies. But today the Fraunhofer institutes have competition. Universities are taking an ever larger role in technology transfer, and technology parks are springing up all over. These efforts are being complemented by the federal programmes for pumping money into start-up companies.
Such a strategy may sound like a recipe for economic success, but it is not without its critics. These people worry that favouring applied research will mean neglecting basic science, eventually starving industry of fresh ideas. If every scientist starts thinking like an entrepreneur (企业家), the argument goes, then the traditional principles of university research being curiosity-driven, free and widely available will suffer. Others claim that many of the programmes to promote technology transfer are a waste of money because half the small businesses that are promoted are bound to go bankrupt within a few years.
While this debate continues, new ideas flow at a steady rate from Germany’s research networks, which bear famous names such as Helmholtz, Max Planck and Leibniz. Yet it is the fourth network, the Fraunhofer Society, that plays the greatest role in technology transfer.
Founded in 1949, the Fraunhofer Society is now Europe’s largest organisation for applied technology, and has 59 institutes employing 12,000 people. It continues to grow. Last year, it swallowed up the Heinrich Hertz Institute for Communication Technology in Berlin. Today, there are even Fraunhofers in the U.S. and Asia.
When was the Fraunhofer Society founded

A.In 1940.
B.Last year.
C.After the unification.
D.In 1949.
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单项选择题
The computer performed better than people in the study because A.the computer worked harder. B.the computer was not busy. C.people tended to be biased. D.people were not good at statistics.
A bunch of behavior sensors (传感器) and a clever piece of software could do just that, by analyzing your behavior to determine if it’s a good time to interrupt you. If built into a phone, the system may decide you’re too busy and ask the caller to leave a message or ring back later.
James Fogarty and Scott Hudson at Camegie Mellon University in Pennsylvania based their system on tiny microphones, cameras and touch sensors that reveal body language and activity. First they had to study different behaviors to find out which ones strongly predict whether your mind is interrupted.
The potential "busyness" signals they focused on included whether the office doors were left open or closed, the time of day, if other people were with the person in question, how close they were to each other, and whether or not the computer was in use.
The sensors monitored these and many other factors while four subjects were at work. At random intervals, the subjects rated how interruptible they were on a scale ranging from "highly interruptible" to "highly not-interruptible". Their ratings were then correlated with the various behaviors. "It is a shotgun (随意的) approach, we used all the indicators we could think of and then let statistics find out which were important," says Hudson.
The model showed that using the keyboard, and talking on a landline or to someone else in the office correlated most strongly with how interruptible the subjects judged themselves to be.
Interestingly, the computer was actually better than people at predicting when someone was too busy to be interrupted. The computer got it right 82 percent of the time, humans 77 percent. Fogarty speculates that this might be because people doing the interrupting are inevitably biased towards delivering their message, whereas computers don’t care.
The first application for Hudson and Fogarty’s system is likely to be in an instant messaging system, followed by office phones and cellphones. "There is no technological roadblock (障碍) to it being deployed in a couple of years," says Hudson.