In fourth grade, my best friend and I developed our own sign language so we could communicate across the room and no one would know what we were saying. Unfortunately, our teacher didn't appreciate our "silent" technique. We may have gotten into a lot less trouble if we knew about the reversible data hiding technique developed by Mehmet U. Celik and A. Murat Tekalp of the University of Rochester and Gaurav Sharma and Eli Saber of Xerox. These scientists invented a method for hiding and extracting information within an ordinary digital image. Commonly-used techniques for embedding messages such as digital watermarking irreversibly change the image, resulting in distortions or information loss. "With our new data embedding algorithm, authorized recipients not only can extract the embedded message but also can recover the original image intact," says Sharma. "The technique offers a significantly higher capacity for embedding data and a lower-distortion than any of the alternatives." The technique will be widely applicable to situations requiring authentication of images such as in forensics. It can also be used to encode information about the image itself, such as who took the picture, when, or with what camera. For more information, contact: Ahmet Tekalp at (585) 275-3774 or e-mail: email@example.com.
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.