Abbas El-Gamal, associate professor of electrical engineering at Stanford University, research associate Boyd Fowler, and graduate student David Yang are designing an advanced imaging sensor. They plan to integrate digitization with the image-capture process by moving it to the pixel level. "Pixel-level processing provides a number of potential advantages," says El-Gamal, including a dynamic range large enough to capture details of objects in bright sunlight and deep shade at the same time; reduction in noise; and pixel-level programmability, which could aid in automatic image recognition. Stanford has taken out four patents on different aspects of pixel-level processing. The device will be made from the same technology used to make low-power computer chips, CMOS. This allows engineers to combine the imaging sensors with computer circuitry, reducing the chip count and cutting production costs. CMOS imaging arrays are also faster than conventional CCD arrays because the pixels are read out in parallel while CCD arrays read out pixels sequentially, say the researchers. Other applications include digital imaging. Canon Inc., Eastman Kodak Co., Hewlett-Packard, Intel, and Interval Research made significant investments in the program. Industry partners will assist in design and prototyping, as well as fabrication of chips for test purposes. FAX: (415) 725-0247; e-mail firstname.lastname@example.org.
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.