Quantum computer components 'coalesce' to 'converse'

ScienceDaily (Oct. 26, 2011) — If quantum computers are ever to be realized, they likely will be made of different types of parts that will need to share information with one another, just like the memory and logic circuits in today's computers do. However, prospects for achieving this kind of communication seemed distant -- until now. A team of physicists working at the National Institute of Standards and Technology (NIST) has shown for the first time how these parts might communicate effectively.

The goal to develop quantum computers -- a long-awaited type of computer that could solve otherwise intractable problems, such as breaking complex encryption codes -- has inspired scientists the world over to invent new devices that could become the brains and memory of these machines. Many of these tiny devices use particles of light, or photons, to carry the bits of information that a quantum computer will use.

But while each of these pieces of hardware can do some jobs well, none are likely to accomplish all of the functions necessary to build a quantum computer. This implies that several different types of quantum devices will need to work together for the computer or network to function. The trouble is that these tiny devices frequently create photons of such different character that they cannot transfer the quantum bits of information between one another. Transmuting two vastly different photons into two similar ones would be a first step toward permitting quantum information components to communicate with one another over large distances, but until now this goal has remained elusive.

However, the team has demonstrated that it is possible to take photons from two disparate sources and render these particles partially indistinguishable. That photons can be made to "coalesce" and become indistinguishable without losing their essential quantum properties suggests in principle that they can connect various types of hardware devices into a single quantum information network. The team's achievement also demonstrates for the first time that a "hybrid" quantum computer might be assembled from different hardware types.

The team connected single photons from a "quantum dot," which could be useful in logic circuits, with a second single-photon source that uses "parametric down conversion," which might be used to connect different parts of the computer. These two sources typically produce photons that differ so dramatically in spectrum that they would be unusable in a quantum network. But with a deft choice of filters and other devices that alter the photons' spectral shapes and other properties, the team was able to make the photons virtually identical.

"We manipulate the photons to be as indistinguishable as possible in terms of spectra, location and polarization -- the details you need to describe a photon. We attribute the remaining distinguishability to properties of the quantum dot," says Glenn Solomon, of NIST's Quantum Measurement Division. "No conceivable measurement can tell indistinguishable photons apart. The results prove in principle that a hybrid quantum network is possible and can be scaled up for use in a quantum network."

The research team includes scientists from the NIST/University of Maryland Joint Quantum Institute (JQI) and Georgetown University. The NSF Physics Frontier Center at JQI provided partial funding.

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The above story is reprinted from materials provided by National Institute of Standards and Technology (NIST).

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Journal Reference:

Sergey Polyakov, Andreas Muller, Edward Flagg, Alex Ling, Natalia Borjemscaia, Edward Van Keuren, Alan Migdall, Glenn Solomon. Coalescence of Single Photons Emitted by Disparate Single-Photon Sources: The Example of InAs Quantum Dots and Parametric Down-Conversion Sources. Physical Review Letters, 2011; 107 (15) DOI: 10.1103/PhysRevLett.107.157402

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Computer scientist cracks mysterious 'Copiale Cipher'

ScienceDaily (Oct. 25, 2011) — The manuscript seems straight out of fiction: a strange, handwritten message in abstract symbols and Roman letters meticulously covering 105 yellowing pages hidden in the depths of an academic archive.

Now, more than three centuries after it was devised, the 75,000-character Copiale Cipher finally has been broken.

The mysterious cryptogram, bound in gold and green brocade paper, reveals the rituals and political leanings of an 18th-century secret society in Germany. The rituals detailed in the document indicate the society had a fascination with eye surgery and ophthalmology, though it seems members of the society were not eye doctors.

"This opens up a window for people who study the history of ideas and the history of secret societies," said computer scientist Kevin Knight of the USC Viterbi School of Engineering, part of the international team that finally cracked the cipher. "Historians believe that secret societies have had a role in revolutions, but all that is yet to be worked out, and a big part of the reason is because so many documents are enciphered."

To break the cipher, Knight and colleagues Beáta Megyesi and Christiane Schaefer of Uppsala University in Sweden tracked down the original manuscript, which was found in the East Berlin Academy after the Cold War and now is in a private collection. They transcribed a machine-readable version of the text, using a computer program created by Knight to help quantify the co-occurrences of certain symbols and other patterns.

"When you get a new code and look at it, the possibilities are nearly infinite," Knight said. "Once you come up with a hypothesis based on your intuition as a human, you can turn over a lot of grunt work to the computer."

With the cipher, the codebreaking team began not even knowing the language of the encrypted document. But because they had a hunch about the Roman and Greek characters distributed throughout the manuscript, they isolated these from the abstract symbols and attacked it as the true code.

"It took quite a long time and resulted in complete failure," Knight said.

After trying 80 languages, the cryptography team realized the Roman characters were "nulls" intended to mislead the reader. It was the abstract symbols that held the message.

The team later tested the hypothesis that abstract symbols with similar shapes represented the same letter or groups of letters. Eventually, the first meaningful words of German emerged: "Ceremonies of Initiation," followed by "Secret Section."

For more information about the method of decipherment, visit http://stp.lingfil.uu.se/%7Ebea/copiale/

Knight now is targeting other coded messages, including ciphers sent by the Zodiac Killer, a serial murderer who sent taunting messages to the press and has never been caught. Knight also is applying his computer-assisted codebreaking software to other famous unsolved codes such as the last section of "Kryptos," an encrypted message carved into a granite sculpture on the grounds of CIA headquarters, and the Voynich Manuscript, a medieval document that has baffled professional cryptographers for decades.

But for Knight, the trickiest language puzzle of all is still everyday speech. A senior research scientist in the Intelligent Systems Division of the USC Information Sciences Institute, Knight is one of the world's leading experts on machine translation -- teaching computers to turn Chinese into English or Arabic into Korean.

"Translation remains a tough challenge for artificial intelligence," said Knight, whose translation software has been adopted by Apple and Intel, among other companies.

With researcher Sujith Ravi, who received a Ph.D. in computer science from USC in 2011, Knight has been approaching translation as a cryptographic problem, which could not only improve human language translation but also could be useful in translating languages that are not currently spoken by humans, including ancient languages and animal communication.

The National Science Foundation funded Knight's cryptography and translation research. The Copiale Cipher work was presented as part of an invited presentation at this year's meeting of The Association for Computational Linguistics.

For a video on Kevin Knight and the Copiale Cipher, visit http://www.youtube.com/watch?v=Eam0Tk-1FyI

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The above story is reprinted from materials provided by University of Southern California. The original article was written by Suzanne Wu.

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Could a computer one day rewire itself? New nanomaterial 'steers' electric currents in multiple dimensions

ScienceDaily (Oct. 16, 2011) — Scientists at Northwestern University have developed a new nanomaterial that can "steer" electrical currents. The development could lead to a computer that can simply reconfigure its internal wiring and become an entirely different device, based on changing needs.

As electronic devices are built smaller and smaller, the materials from which the circuits are constructed begin to lose their properties and begin to be controlled by quantum mechanical phenomena. Reaching this physical barrier, many scientists have begun building circuits into multiple dimensions, such as stacking components on top of one another.

The Northwestern team has taken a fundamentally different approach. They have made reconfigurable electronic materials: materials that can rearrange themselves to meet different computational needs at different times.

"Our new steering technology allows use to direct current flow through a piece of continuous material," said Bartosz A. Grzybowski, who led the research. "Like redirecting a river, streams of electrons can be steered in multiple directions through a block of the material -- even multiple streams flowing in opposing directions at the same time."

Grzybowski is professor of chemical and biological engineering in the McCormick School of Engineering and Applied Science and professor of chemistry in the Weinberg College of Arts and Sciences.

The Northwestern material combines different aspects of silicon- and polymer-based electronics to create a new classification of electronic materials: nanoparticle-based electronics.

The study, in which the authors report making preliminary electronic components with the hybrid material, will be published online Oct. 16 by the journal Nature Nanotechnology. The research also will be published as the cover story in the November print issue of the journal.

"Besides acting as three-dimensional bridges between existing technologies, the reversible nature of this new material could allow a computer to redirect and adapt its own circuitry to what is required at a specific moment in time," said David A. Walker, an author of the study and a graduate student in Grzybowski's research group.

Imagine a single device that reconfigures itself into a resistor, a rectifier, a diode and a transistor based on signals from a computer. The multi-dimensional circuitry could be reconfigured into new electronic circuits using a varied input sequence of electrical pulses.

The hybrid material is composed of electrically conductive particles, each five nanometers in width, coated with a special positively charged chemical. (A nanometer is a billionth of a meter.) The particles are surrounded by a sea of negatively charged atoms that balance out the positive charges fixed on the particles. By applying an electrical charge across the material, the small negative atoms can be moved and reconfigured, but the relatively larger positive particles are not able to move.

By moving this sea of negative atoms around the material, regions of low and high conductance can be modulated; the result is the creation of a directed path that allows electrons to flow through the material. Old paths can be erased and new paths created by pushing and pulling the sea of negative atoms. More complex electrical components, such as diodes and transistors, can be made when multiple types of nanoparticles are used.

The title of the paper is "Dynamic Internal Gradients Control and Direct Electric Currents Within Nanostructured Materials." In addition to Grzybowski and Walker, other authors are Hideyuki Nakanishi, Paul J. Wesson, Yong Yan, Siowling Soh and Sumanth Swaminathan, from Northwestern, and Kyle J. M. Bishop, a former member of the Grzybowski research group, now with Pennsylvania State University.

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The above story is reprinted from materials provided by Northwestern University, via EurekAlert!, a service of AAAS.

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Journal Reference:

Hideyuki Nakanishi, David A. Walker, Kyle J. M. Bishop, Paul J. Wesson, Yong Yan, Siowling Soh, Sumanth Swaminathan, Bartosz A. Grzybowski. Dynamic internal gradients control and direct electric currents within nanostructured materials. Nature Nanotechnology, 2011; DOI: 10.1038/nnano.2011.165

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Intel to Mass-Produce New 3-D Transistors for Faster, More Efficient Computer Chips

3-D Transistor This image shows the vertical fins of Intel’s 22 nanometer microprocessor using 3-D Tri-Gate transistors. Intel
In a move that could remake the microchip industry, Intel announced Wednesday it will start mass-producing the first three-dimensional silicon transistors. The 3-D transistor design, which Intel says will improve efficiency by more than one-third, will be integrated into a 22-nanometer node in an Intel chip called Ivy Bridge.
It’s a major change from the two-dimensional flat transistor structure we all know and love, which has powered every computer chip for the last 50 years. The 3-D switch design and the scale of its production will allow Moore’s Law to advance apace, Intel said.
Moore’s Law holds that the number of transistors that can be placed on a circuit will double every two years, but this places limits on the circuits’ size — a growing problem as engineers cram greater numbers of transistors onto ever-tinier chips. A 3-D switch could allow computer chips to be built like skyscrapers, optimizing space by building upward, and thereby allowing uninhibited transistor growth.
The Tri-Gate transistors consist of a thin 3-D silicon fin that arises vertically from the silicon substrate, Intel explains. Each fin has three gates, one on the top and one on each side, which allows for greater transistor current control. When it’s on, current flow is more efficient, and when the switches are off, the flow of electrons is closer to zero. By contrast, flat transistors have one gate, only on top.
All this leads to greater efficiency, allowing chips to operate at a lower voltage and with lower leakage — Intel claims a whopping 37 percent performance increase over its 2-D chips. Since the fins and their gates are vertical, more transistors can be packed close together. Eventually, designers will be able to make taller fins, aiming for even better performance.
“It will give product designers the flexibility to make current devices smarter and wholly new ones possible,” said Mark Bohr, a senior fellow at Intel.
More than 6 million 22-nm Tri-Gate transistors could fit inside the period at the end of this sentence, according to the company. (If you zoom in, who knows how many could fit!)
The new transistors will be integrated into Ivy Bridge-based Intel Core processors by the end of this year, which consumers will be able to get in 2012, Intel said.
Plenty of other chip designers have been talking about 3-D chips — just last month, we saw a 2-D reprogrammable one designed to behave as if it was a 3-D one. But Intel has taken it a step further by figuring out how to mass-produce them.
It’s technically 3-D because the switches are vertical and horizontal, but the transistors are not stacked, allowing electrons to flow in three dimensions — that’s a holy Grail of microprocessor design. But a new circuit design that allows more transistors on tinier spaces certainly sounds like a major breakthrough.
[IBM via PC Magazine]

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New 'FeTRAM' is promising computer memory technology

ScienceDaily (Sep. 27, 2011) — Researchers are developing a new type of computer memory that could be faster than the existing commercial memory and use far less power than flash memory devices.

The technology combines silicon nanowires with a "ferroelectric" polymer, a material that switches polarity when electric fields are applied, making possible a new type of ferroelectric transistor.

"It's in a very nascent stage," said doctoral student Saptarshi Das, who is working with Joerg Appenzeller, a professor of electrical and computer engineering and scientific director of nanoelectronics at Purdue's Birck Nanotechnology Center.

The ferroelectric transistor's changing polarity is read as 0 or 1, an operation needed for digital circuits to store information in binary code consisting of sequences of ones and zeroes. The new technology is called FeTRAM, for ferroelectric transistor random access memory.

"We've developed the theory and done the experiment and also showed how it works in a circuit," he said. Findings are detailed in a research paper that appeared this month in Nano Letters, published by the American Chemical Society.

The FeTRAM technology has nonvolatile storage, meaning it stays in memory after the computer is turned off. The devices have the potential to use 99 percent less energy than flash memory, a non-volatile computer storage chip and the predominant form of memory in the commercial market.

"However, our present device consumes more power because it is still not properly scaled," Das said. "For future generations of FeTRAM technologies one of the main objectives will be to reduce the power dissipation. They might also be much faster than another form of computer memory called SRAM."

The FeTRAM technology fulfills the three basic functions of computer memory: to write information, read the information and hold it for a long period of time.

"You want to hold memory as long as possible, 10 to 20 years, and you should be able to read and write as many times as possible," Das said. "It should also be low power to keep your laptop from getting too hot. And it needs to scale, meaning you can pack many devices into a very small area. The use of silicon nanowires along with this ferroelectric polymer has been motivated by these requirements."

The new technology also is compatible with industry manufacturing processes for complementary metal oxide semiconductors, or CMOS, used to produce computer chips. It has the potential to replace conventional memory systems.

A patent application has been filed for the concept.

The FeTRAMs are similar to state-of-the-art ferroelectric random access memories, FeRAMs, which are in commercial use but represent a relatively small part of the overall semiconductor market. Both use ferroelectric material to store information in a nonvolatile fashion, but unlike FeRAMS, the new technology allows for nondestructive readout, meaning information can be read without losing it.

This nondestructive readout is possible by storing information using a ferroelectric transistor instead of a capacitor, which is used in conventional FeRAMs.

This work was supported by the Nanotechnology Research Initiative (NRI) through Purdue's Network for Computational Nanotechnology (NCN), which is supported by National Science Foundation.

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The above story is reprinted (with editorial adaptations by ScienceDaily staff) from materials provided by Purdue University. The original article was written by Emil Venere.

Journal Reference:

Saptarshi Das, Joerg Appenzeller. FETRAM. An Organic Ferroelectric Material Based Novel Random Access Memory Cell. Nano Letters, 2011; 11 (9): 4003 DOI: 10.1021/nl2023993

Note: If no author is given, the source is cited instead.

Disclaimer: Views expressed in this article do not necessarily reflect those of ScienceDaily or its staff.

View the original article here

New 'FeTRAM' is promising computer memory technology

ScienceDaily (Sep. 27, 2011) — Researchers are developing a new type of computer memory that could be faster than the existing commercial memory and use far less power than flash memory devices.

The technology combines silicon nanowires with a "ferroelectric" polymer, a material that switches polarity when electric fields are applied, making possible a new type of ferroelectric transistor.

"It's in a very nascent stage," said doctoral student Saptarshi Das, who is working with Joerg Appenzeller, a professor of electrical and computer engineering and scientific director of nanoelectronics at Purdue's Birck Nanotechnology Center.

The ferroelectric transistor's changing polarity is read as 0 or 1, an operation needed for digital circuits to store information in binary code consisting of sequences of ones and zeroes. The new technology is called FeTRAM, for ferroelectric transistor random access memory.

"We've developed the theory and done the experiment and also showed how it works in a circuit," he said. Findings are detailed in a research paper that appeared this month in Nano Letters, published by the American Chemical Society.

The FeTRAM technology has nonvolatile storage, meaning it stays in memory after the computer is turned off. The devices have the potential to use 99 percent less energy than flash memory, a non-volatile computer storage chip and the predominant form of memory in the commercial market.

"However, our present device consumes more power because it is still not properly scaled," Das said. "For future generations of FeTRAM technologies one of the main objectives will be to reduce the power dissipation. They might also be much faster than another form of computer memory called SRAM."

The FeTRAM technology fulfills the three basic functions of computer memory: to write information, read the information and hold it for a long period of time.

"You want to hold memory as long as possible, 10 to 20 years, and you should be able to read and write as many times as possible," Das said. "It should also be low power to keep your laptop from getting too hot. And it needs to scale, meaning you can pack many devices into a very small area. The use of silicon nanowires along with this ferroelectric polymer has been motivated by these requirements."

The new technology also is compatible with industry manufacturing processes for complementary metal oxide semiconductors, or CMOS, used to produce computer chips. It has the potential to replace conventional memory systems.

A patent application has been filed for the concept.

The FeTRAMs are similar to state-of-the-art ferroelectric random access memories, FeRAMs, which are in commercial use but represent a relatively small part of the overall semiconductor market. Both use ferroelectric material to store information in a nonvolatile fashion, but unlike FeRAMS, the new technology allows for nondestructive readout, meaning information can be read without losing it.

This nondestructive readout is possible by storing information using a ferroelectric transistor instead of a capacitor, which is used in conventional FeRAMs.

This work was supported by the Nanotechnology Research Initiative (NRI) through Purdue's Network for Computational Nanotechnology (NCN), which is supported by National Science Foundation.

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Story Source:

The above story is reprinted (with editorial adaptations by ScienceDaily staff) from materials provided by Purdue University. The original article was written by Emil Venere.

Journal Reference:

Saptarshi Das, Joerg Appenzeller. FETRAM. An Organic Ferroelectric Material Based Novel Random Access Memory Cell. Nano Letters, 2011; 11 (9): 4003 DOI: 10.1021/nl2023993

Note: If no author is given, the source is cited instead.

Disclaimer: Views expressed in this article do not necessarily reflect those of ScienceDaily or its staff.

View the original article here

Stretchable electronics: Wireless sensor measures and inputs intense body movements to computer

ScienceDaily (June 17, 2011) — Electronics that can be bent and stretched might sound like science fiction. But Uppsala researcher Zhigang Wu, working with collaborators, has devised a wireless sensor that can stand to be stretched. For example, the sensor can measure intensive body movements and wirelessly send information directly to a computer.

The findings are now being presented in the journal Advanced Functional Materials.

Robots of liquid metal, as in the Terminator movies, are probably the best-known cases of deformable electronic systems. But so far this only exists in our imagination. Twisting, folding, and stretching fragile conventional electronics is not yet possible.

The latest advances in the field of µFSRFE (microfluidic stretchable radio frequency electronics) have shown the possibility of combining established stiff electronics components with channels of elastomers filled with fluid metal. In this way it has been possible to construct systems that after severe mechanical deformation can manage to return to their original form. Such electronics can adapt to nearly any bent and moving surfaces on a human being or a robot and can thus serve as a second layer of smart e-skin for health monitoring or remote control.

The researcher Zhigang Wu from Uppsala University, in collaboration with researchers at the company Laird Technologies, has presented a newly developed and wireless µFSRFE sensor consisting of a multifunctional antenna integrated with a conventional rigid circuit board. The reporting sensor can measure intensive body movements and wirelessly send information directly to a computer. The design enables wireless measurement of repeated bending across a large area or moveable parts.

The sensor they designed will pave the way for myriad new applications that until now have only been seen on the movie screen.

Story Source:

The above story is reprinted (with editorial adaptations by ScienceDaily staff) from materials provided by Uppsala Universitet.

Journal Reference:

Shi Cheng, Zhigang Wu. A Microfluidic, Reversibly Stretchable, Large-Area Wireless Strain Sensor. Advanced Functional Materials, 2011; DOI: 10.1002/adfm.201002508

Note: If no author is given, the source is cited instead.

Disclaimer: Views expressed in this article do not necessarily reflect those of ScienceDaily or its staff.

View the original article here

Faster computer graphics: Digitally mimicking photographic blur caused by moving objects

ScienceDaily (June 13, 2011) — Photographs of moving objects are almost always a little blurry -- or a lot blurry, if the objects are moving rapidly enough. To make their work look as much like conventional film as possible, game and movie animators try to reproduce this blur. But counterintuitively, producing blurry images is actually more computationally complex than producing perfectly sharp ones.

In August, at this year's Siggraph conference -- the premier computer-graphics conference -- researchers from the Computer Graphics Group at MIT's Computer Science and Artificial Intelligence Laboratory will present a pair of papers that describe new techniques for computing blur much more efficiently. The result could be more convincing video games and frames of digital video that take minutes rather than hours to render.

The image sensor in a digital camera, and even the film in a conventional camera, can be thought of as a grid of color detectors, each detector corresponding to one pixel in the final image. If the objects being photographed are stationary, then during a single exposure, each detector registers the color of just one point on an object's surface. But if the objects are moving, light from different points on an object, and even from different objects, will strike a single detector. The detector effectively averages the colors of all the points, and the result is blur.

Digitally rendering a frame of video is a computationally intensive process with several discrete stages. First, the computer has to determine how the objects in the scene are moving. Second, it has to calculate how rays of light from an imagined light source would reflect off the objects. Finally, it determines which rays of light would actually reach an imagined lens. If the objects in the video are moving slowly enough, the computer has to go through that process only once per frame. If the objects are moving rapidly, however, it may have to go through it dozens or even hundreds of times.

Colorfast

Given how difficult blurring is to calculate, you might think that animators would simply ignore it. But that leads to surprisingly unconvincing video. "The motion doesn't look fluid at all," says Jaakko Lehtinen, who worked on both projects as a postdoc in the Computer Graphics Group and is now a senior research scientist with graphics-chip manufacturer Nvidia.

To get a sense of what motion without blur looks like, Lehtinen says, consider the type of clay animation familiar from old movies or Christmas specials such as "Rudolph the Red-Nosed Reindeer." "This doesn't have motion blur, because the scene is actually stationary when you take the picture," Lehtinen says. "It just looks choppy. The motion doesn't look natural."

The MIT researchers took two different approaches to simplifying the computation of blur, corresponding to two different stages in the graphics-rendering pipeline. Graduate student Jonathan Ragan-Kelley is the lead author on one of the Siggraph papers, joined by associate professor Frédo Durand, who leads the Computer Graphics Group; Lehtinen; graduate student Jiawen Chen; and Michael Doggett of Lund University in Sweden. In that paper, the researchers make the simplifying assumption that the way in which light reflects off a moving object doesn't change over the course of a single frame. For each pixel in the final image, their algorithm still averages the colors of multiple points on objects' surfaces, but it calculates those colors only once. The researchers found a way to represent the relationship between the color calculations and the shapes of the associated objects as entries in a table. For each pixel in the final image, the algorithm simply looks up the corresponding values in the table. That drastically simplifies the calculation but has little effect on the final image.

Adopting the researchers' proposal would require modifying the architecture of graphics chips. "You can imagine really just going ahead and building what they suggest," says Henry Moreton, a distinguished engineer at Nvidia. "But I think that the greater value of the paper is that it points at strategies for solving these problems more elegantly, more efficiently, and more practically. Whether they manifest themselves in exactly the fashion that the paper presents is probably not that likely. But what they did is they pointed to a new way of attacking the problem."

Turning the tables

The second of the Computer Graphics Group's Siggraph papers, led by Lehtinen and also featuring Durand, Chen and two of Lehtinen's Nvidia colleagues, reduces the computational burden of determining which rays of light would reach an imagined lens. To produce convincing motion blur, digital animators might ordinarily consider the contributions that more than 100 discrete points on the surfaces of moving objects make to the color value of a single pixel. Lehtinen and his colleagues' algorithm instead looks at a smaller number of points -- maybe 16 or so -- and makes an educated guess about the color values of the points in between. The result: A frame of digital video that would ordinarily take about an hour to render might instead take about 10 minutes.

In fact, both techniques apply not only to motion blur but also to the type of blur that occurs in, say, the background of an image when the camera is focused on an object in the foreground. That, too, is something that animators seek to reproduce. "Where the director and the cinematographer choose to focus the lens, it directs your attention when you're looking at the picture in subtle ways," Lehtinen says. If an animated film has no such lapses in focus, "there's just something wrong with it," Lehtinen says. "It doesn't look like a movie." Indeed, Lehtinen says, even though the paper has yet to be presented, several major special-effects companies have already contacted the researchers about the work.

Story Source:

The above story is reprinted (with editorial adaptations by ScienceDaily staff) from materials provided by Massachusetts Institute of Technology. The original article was written by Larry Hardesty, MIT News Office.

Note: If no author is given, the source is cited instead.

Disclaimer: Views expressed in this article do not necessarily reflect those of ScienceDaily or its staff.

View the original article here

Stretchable electronics: Wireless sensor measures and inputs intense body movements to computer

ScienceDaily (June 17, 2011) — Electronics that can be bent and stretched might sound like science fiction. But Uppsala researcher Zhigang Wu, working with collaborators, has devised a wireless sensor that can stand to be stretched. For example, the sensor can measure intensive body movements and wirelessly send information directly to a computer.

The findings are now being presented in the journal Advanced Functional Materials.

Robots of liquid metal, as in the Terminator movies, are probably the best-known cases of deformable electronic systems. But so far this only exists in our imagination. Twisting, folding, and stretching fragile conventional electronics is not yet possible.

The latest advances in the field of µFSRFE (microfluidic stretchable radio frequency electronics) have shown the possibility of combining established stiff electronics components with channels of elastomers filled with fluid metal. In this way it has been possible to construct systems that after severe mechanical deformation can manage to return to their original form. Such electronics can adapt to nearly any bent and moving surfaces on a human being or a robot and can thus serve as a second layer of smart e-skin for health monitoring or remote control.

The researcher Zhigang Wu from Uppsala University, in collaboration with researchers at the company Laird Technologies, has presented a newly developed and wireless µFSRFE sensor consisting of a multifunctional antenna integrated with a conventional rigid circuit board. The reporting sensor can measure intensive body movements and wirelessly send information directly to a computer. The design enables wireless measurement of repeated bending across a large area or moveable parts.

The sensor they designed will pave the way for myriad new applications that until now have only been seen on the movie screen.

Story Source:

The above story is reprinted (with editorial adaptations by ScienceDaily staff) from materials provided by Uppsala Universitet.

Journal Reference:

Shi Cheng, Zhigang Wu. A Microfluidic, Reversibly Stretchable, Large-Area Wireless Strain Sensor. Advanced Functional Materials, 2011; DOI: 10.1002/adfm.201002508

Note: If no author is given, the source is cited instead.

Disclaimer: Views expressed in this article do not necessarily reflect those of ScienceDaily or its staff.

View the original article here

Faster computer graphics: Digitally mimicking photographic blur caused by moving objects

ScienceDaily (June 13, 2011) — Photographs of moving objects are almost always a little blurry -- or a lot blurry, if the objects are moving rapidly enough. To make their work look as much like conventional film as possible, game and movie animators try to reproduce this blur. But counterintuitively, producing blurry images is actually more computationally complex than producing perfectly sharp ones.

In August, at this year's Siggraph conference -- the premier computer-graphics conference -- researchers from the Computer Graphics Group at MIT's Computer Science and Artificial Intelligence Laboratory will present a pair of papers that describe new techniques for computing blur much more efficiently. The result could be more convincing video games and frames of digital video that take minutes rather than hours to render.

The image sensor in a digital camera, and even the film in a conventional camera, can be thought of as a grid of color detectors, each detector corresponding to one pixel in the final image. If the objects being photographed are stationary, then during a single exposure, each detector registers the color of just one point on an object's surface. But if the objects are moving, light from different points on an object, and even from different objects, will strike a single detector. The detector effectively averages the colors of all the points, and the result is blur.

Digitally rendering a frame of video is a computationally intensive process with several discrete stages. First, the computer has to determine how the objects in the scene are moving. Second, it has to calculate how rays of light from an imagined light source would reflect off the objects. Finally, it determines which rays of light would actually reach an imagined lens. If the objects in the video are moving slowly enough, the computer has to go through that process only once per frame. If the objects are moving rapidly, however, it may have to go through it dozens or even hundreds of times.

Colorfast

Given how difficult blurring is to calculate, you might think that animators would simply ignore it. But that leads to surprisingly unconvincing video. "The motion doesn't look fluid at all," says Jaakko Lehtinen, who worked on both projects as a postdoc in the Computer Graphics Group and is now a senior research scientist with graphics-chip manufacturer Nvidia.

To get a sense of what motion without blur looks like, Lehtinen says, consider the type of clay animation familiar from old movies or Christmas specials such as "Rudolph the Red-Nosed Reindeer." "This doesn't have motion blur, because the scene is actually stationary when you take the picture," Lehtinen says. "It just looks choppy. The motion doesn't look natural."

The MIT researchers took two different approaches to simplifying the computation of blur, corresponding to two different stages in the graphics-rendering pipeline. Graduate student Jonathan Ragan-Kelley is the lead author on one of the Siggraph papers, joined by associate professor Frédo Durand, who leads the Computer Graphics Group; Lehtinen; graduate student Jiawen Chen; and Michael Doggett of Lund University in Sweden. In that paper, the researchers make the simplifying assumption that the way in which light reflects off a moving object doesn't change over the course of a single frame. For each pixel in the final image, their algorithm still averages the colors of multiple points on objects' surfaces, but it calculates those colors only once. The researchers found a way to represent the relationship between the color calculations and the shapes of the associated objects as entries in a table. For each pixel in the final image, the algorithm simply looks up the corresponding values in the table. That drastically simplifies the calculation but has little effect on the final image.

Adopting the researchers' proposal would require modifying the architecture of graphics chips. "You can imagine really just going ahead and building what they suggest," says Henry Moreton, a distinguished engineer at Nvidia. "But I think that the greater value of the paper is that it points at strategies for solving these problems more elegantly, more efficiently, and more practically. Whether they manifest themselves in exactly the fashion that the paper presents is probably not that likely. But what they did is they pointed to a new way of attacking the problem."

Turning the tables

The second of the Computer Graphics Group's Siggraph papers, led by Lehtinen and also featuring Durand, Chen and two of Lehtinen's Nvidia colleagues, reduces the computational burden of determining which rays of light would reach an imagined lens. To produce convincing motion blur, digital animators might ordinarily consider the contributions that more than 100 discrete points on the surfaces of moving objects make to the color value of a single pixel. Lehtinen and his colleagues' algorithm instead looks at a smaller number of points -- maybe 16 or so -- and makes an educated guess about the color values of the points in between. The result: A frame of digital video that would ordinarily take about an hour to render might instead take about 10 minutes.

In fact, both techniques apply not only to motion blur but also to the type of blur that occurs in, say, the background of an image when the camera is focused on an object in the foreground. That, too, is something that animators seek to reproduce. "Where the director and the cinematographer choose to focus the lens, it directs your attention when you're looking at the picture in subtle ways," Lehtinen says. If an animated film has no such lapses in focus, "there's just something wrong with it," Lehtinen says. "It doesn't look like a movie." Indeed, Lehtinen says, even though the paper has yet to be presented, several major special-effects companies have already contacted the researchers about the work.

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The above story is reprinted (with editorial adaptations by ScienceDaily staff) from materials provided by Massachusetts Institute of Technology. The original article was written by Larry Hardesty, MIT News Office.

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Phase change memory-based 'Moneta' system points to the future of computer storage

ScienceDaily (June 3, 2011) — A University of California, San Diego faculty-student team is about to demonstrate a first-of-its kind, phase-change memory solid state storage device that provides performance thousands of times faster than a conventional hard drive and up to seven times faster than current state-of-the-art solid-state drives (SSDs).

The device was developed in the Computer Science and Engineering department at the UC San Diego Jacobs School of Engineering and will be on exhibit June 7-8 at DAC 2011, the world's leading technical conference and trade show on electronic design automation, with the support of several industry partners, including Micron Technology, BEEcube and Xilinx. The storage system, called "Moneta," uses phase-change memory (PCM), an emerging data storage technology that stores data in the crystal structure of a metal alloy called a chalcogenide. PCM is faster and simpler to use than flash memory -- the technology that currently dominates the SSD market.

Moneta marks the latest advancement in solid state drives (SSDs). Unlike conventional hard disk drives, solid state storage drives have no moving parts. Today's SSDs use flash memory and can be found in a wide range of consumer electronics such as iPads and laptops. Although faster than hard disk, flash memory is still too slow to meet modern data storage and analysis demands, particularly in the area of high performance computing where the ability to sift through enormous volumes of data quickly is critical. Examples include storing and analyzing scientific data collected through environmental sensors, or even web searches through Google.

"As a society, we can gather all this data very, very quickly -- much faster than we can analyze it with conventional, disk-based storage systems," said Steven Swanson, professor of Computer Science and Engineering and director of the Non-Volatile Systems Lab (NVSL). "Phase-change memory-based solid state storage devices will allow us to sift through all of this data, make sense of it, and extract useful information much faster. It has the potential to be revolutionary."

PCM Memory Chips

To store data, the PCM memory chips switch the alloy between a crystalline and amorphous state based on the application of heat through an electrical current. To read the data, the chips use a smaller current to determine which state the chalcogenide is in.

Moneta uses Micron Technology's first-generation PCM chips and can read large sections of data at a maximum rate of 1.1 gigabytes per second and write data at up to 371 megabytes per second. For smaller accesses (e.g., 512 B), Moneta can read at 327 megabytes per second and write at 91 megabytes per second , or between two and seven times faster than a state-of-the-art, flash-based SSD. Moneta also provides lower latency for each operation and should reduce energy requirements for data-intensive applications.

A Glimpse at Computers of the Future

Swanson hopes to build the second generation of the Moneta storage device in the next six to nine months and says the technology could be ready for market in just a few years as the underlying phase-change memory technology improves. The development has also revealed a new technology challenge.

"We've found that you can build a much faster storage device, but in order to really make use of it, you have to change the software that manages it as well. Storage systems have evolved over the last 40 years to cater to disks, and disks are very, very slow," said Swanson. "Designing storage systems that can fully leverage technologies like PCM requires rethinking almost every aspect of how a computer system's software manages and accesses storage. Moneta gives us a window into the future of what computer storage systems are going to look like, and gives us the opportunity now to rethink how we design computer systems in response."

In addition to Swanson, the Moneta team includes Computer Science and Engineering Professor and Chair Rajesh Gupta, who is also associate director of UC San Diego's California Institute for Telecommunications and Information Technology. Student team members from the Department of Computer Science and Engineering include Ameen Akel, Adrian Caulfield, Todor Mollov, Arup De, and Joel Coburn.

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The above story is reprinted (with editorial adaptations by ScienceDaily staff) from materials provided by University of California - San Diego, Jacobs School of Engineering.

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Computer vision: Music video by C-Mon & Kypski used for data collection

ScienceDaily (May 17, 2011) — Researchers at New York University's Courant Institute of Mathematical Sciences have adopted an innovative data collection method for their latest work in the area of computer vision -- a music video created by the Dutch progressive-electro band C-Mon & Kypski. Individual frames from the band's recent video for its song "More is Less" served as a unique visual database for the Courant researchers' work to develop computer vision technology.

Computer vision, a developing technology, aims to give eyesight to machines and is currently used in a range of applications. These include Microsoft's Kinect, which detects poses in order for game play to be controlled using only the body, and cell-phone technology that allows users to cash checks by merely snapping a picture.

However, for computer vision to truly mimic the human vision system, it must be able to reliably detect specific objects or individuals under a variety of conditions -- poor lighting, cluttered backgrounds, unusual clothing, and other sources of variation. In building such a system, developers have sought to implement an algorithm to perform "pose estimation" -- computer recognition of individuals or objects based on their positioning. However, in order for a computer to succeed at pose estimation it must draw from a large database of people or objects in a variety of poses -- after detecting a certain pose in its field of vision, it draws on its vast database of images to find a match.

"If we had many examples of people in similar pose, but under differing conditions, we could construct an algorithm that matches based on pose and ignores the distracting information -- lighting, clothing, and background," explained Graham Taylor, a post-doctoral fellow at the Courant Institute and one of the project's researchers. "But how do we collect such data?"

Departing from traditional data-collection methods, the team turned to Dutch progressive-electro band C-Mon & Kypski and, specifically, its video crowd-sourcing project--"One Frame of Fame" (http://oneframeoffame.com/)--which asks fans to replace one frame of the band's music video for the song "More or Less" with a capture from their webcams. In the project, a visitor to the band's website is shown a single frame of the video and asked to perform an imitation in front of the camera. The new contribution is spliced into the video that updates once an hour.

"This turned out to be the perfect data source for developing an algorithm that learns to compute similarity based on pose," explained Taylor, who obtained his doctorate in computer science from the University of Toronto. "Armed with the band's data and a few machine learning tricks up our sleeves, we built a system that is highly effective at matching people in similar pose but under widely different settings."

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The above story is reprinted (with editorial adaptations by ScienceDaily staff) from materials provided by New York University, via EurekAlert!, a service of AAAS.

Note: If no author is given, the source is cited instead.

Disclaimer: Views expressed in this article do not necessarily reflect those of ScienceDaily or its staff.

View the original article here

Hardware encryption developed for new computer memory technology

ScienceDaily (May 18, 2011) — Security concerns are one of the key obstacles to the adoption of new non-volatile main memory (NVMM) technology in next-generation computers, which would improve computer start times and boost memory capacity. But now researchers from North Carolina State University have developed new encryption hardware for use with NVMM to protect personal information and other data.

NVMM technologies, such as phase-change memory, hold great promise to replace conventional dynamic random access memory (DRAM) in the main memory of computers. NVMM would allow computers to start instantly, and can fit more memory into the same amount of space used by existing technologies. However, NVMM poses a security risk.

Conventional DRAM main memory does not store data once the computer is turned off. That means, for example, that it doesn't store your credit card number and password after an online shopping spree. NVMM, on the other hand, retains all user data in main memory even years after the computer is turned off. This feature could give criminals access to your personal information or other data if your laptop or smart phone were stolen. And, because the data in the NVMM is stored in main memory, it cannot be encrypted using software. Software cannot manage main memory functions, because software itself operates in main memory.

NC State researchers have developed a solution using a hardware encryption system called i-NVMM.

"We could use hardware to encrypt everything," explains Dr. Yan Solihin, associate professor of electrical and computer engineering at NC State and co-author of a paper describing i-NVMM, "but then the system would run very slowly -- because it would constantly be encrypting and decrypting data.

"Instead, we developed an algorithm to detect data that is likely not needed by the processor. This allows us to keep 78 percent of main memory encrypted during typical operation, and only slows the system's performance by 3.7 percent."

The i-NVMM tool has two additional benefits as well. First, its algorithm also detects idleness. That means any data not currently in use -- such as your credit card number -- is automatically encrypted. This makes i-NVMM even more secure than DRAM. Second, while 78 percent of the main memory is encrypted when the computer is in use, the remaining 22 percent is encrypted when the computer is powered down.

"Basically, unless someone accesses your computer while you're using it, all of your data is protected," Solihin says.

i-NVMM relies on a self-contained encryption engine that is incorporated into a computer's memory module -- and does not require changes to the computer's processors. That means it can be used with different processors and different systems.

"We're now seeking industry partners who are interested in this technology," Solihin says.

The paper, "i-NVMM: A Secure Non-Volatile Main Memory System with Incremental Encryption," will be presented June 6 at the International Symposium on Computer Architecture (ISCA) in San Jose, Calif. The paper was co-authored by Dr. Siddhartha Chhabra, a former Ph.D. student at NC State. The research was supported, in part, by the National Science Foundation.

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The above story is reprinted (with editorial adaptations by ScienceDaily staff) from materials provided by North Carolina State University.

Note: If no author is given, the source is cited instead.

Disclaimer: Views expressed in this article do not necessarily reflect those of ScienceDaily or its staff.

View the original article here

Hardware encryption developed for new computer memory technology

ScienceDaily (May 18, 2011) — Security concerns are one of the key obstacles to the adoption of new non-volatile main memory (NVMM) technology in next-generation computers, which would improve computer start times and boost memory capacity. But now researchers from North Carolina State University have developed new encryption hardware for use with NVMM to protect personal information and other data.

NVMM technologies, such as phase-change memory, hold great promise to replace conventional dynamic random access memory (DRAM) in the main memory of computers. NVMM would allow computers to start instantly, and can fit more memory into the same amount of space used by existing technologies. However, NVMM poses a security risk.

Conventional DRAM main memory does not store data once the computer is turned off. That means, for example, that it doesn't store your credit card number and password after an online shopping spree. NVMM, on the other hand, retains all user data in main memory even years after the computer is turned off. This feature could give criminals access to your personal information or other data if your laptop or smart phone were stolen. And, because the data in the NVMM is stored in main memory, it cannot be encrypted using software. Software cannot manage main memory functions, because software itself operates in main memory.

NC State researchers have developed a solution using a hardware encryption system called i-NVMM.

"We could use hardware to encrypt everything," explains Dr. Yan Solihin, associate professor of electrical and computer engineering at NC State and co-author of a paper describing i-NVMM, "but then the system would run very slowly -- because it would constantly be encrypting and decrypting data.

"Instead, we developed an algorithm to detect data that is likely not needed by the processor. This allows us to keep 78 percent of main memory encrypted during typical operation, and only slows the system's performance by 3.7 percent."

The i-NVMM tool has two additional benefits as well. First, its algorithm also detects idleness. That means any data not currently in use -- such as your credit card number -- is automatically encrypted. This makes i-NVMM even more secure than DRAM. Second, while 78 percent of the main memory is encrypted when the computer is in use, the remaining 22 percent is encrypted when the computer is powered down.

"Basically, unless someone accesses your computer while you're using it, all of your data is protected," Solihin says.

i-NVMM relies on a self-contained encryption engine that is incorporated into a computer's memory module -- and does not require changes to the computer's processors. That means it can be used with different processors and different systems.

"We're now seeking industry partners who are interested in this technology," Solihin says.

The paper, "i-NVMM: A Secure Non-Volatile Main Memory System with Incremental Encryption," will be presented June 6 at the International Symposium on Computer Architecture (ISCA) in San Jose, Calif. The paper was co-authored by Dr. Siddhartha Chhabra, a former Ph.D. student at NC State. The research was supported, in part, by the National Science Foundation.

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The above story is reprinted (with editorial adaptations by ScienceDaily staff) from materials provided by North Carolina State University.

Note: If no author is given, the source is cited instead.

Disclaimer: Views expressed in this article do not necessarily reflect those of ScienceDaily or its staff.

View the original article here

Computer vision: Music video by C-Mon & Kypski used for data collection

ScienceDaily (May 17, 2011) — Researchers at New York University's Courant Institute of Mathematical Sciences have adopted an innovative data collection method for their latest work in the area of computer vision -- a music video created by the Dutch progressive-electro band C-Mon & Kypski. Individual frames from the band's recent video for its song "More is Less" served as a unique visual database for the Courant researchers' work to develop computer vision technology.

Computer vision, a developing technology, aims to give eyesight to machines and is currently used in a range of applications. These include Microsoft's Kinect, which detects poses in order for game play to be controlled using only the body, and cell-phone technology that allows users to cash checks by merely snapping a picture.

However, for computer vision to truly mimic the human vision system, it must be able to reliably detect specific objects or individuals under a variety of conditions -- poor lighting, cluttered backgrounds, unusual clothing, and other sources of variation. In building such a system, developers have sought to implement an algorithm to perform "pose estimation" -- computer recognition of individuals or objects based on their positioning. However, in order for a computer to succeed at pose estimation it must draw from a large database of people or objects in a variety of poses -- after detecting a certain pose in its field of vision, it draws on its vast database of images to find a match.

"If we had many examples of people in similar pose, but under differing conditions, we could construct an algorithm that matches based on pose and ignores the distracting information -- lighting, clothing, and background," explained Graham Taylor, a post-doctoral fellow at the Courant Institute and one of the project's researchers. "But how do we collect such data?"

Departing from traditional data-collection methods, the team turned to Dutch progressive-electro band C-Mon & Kypski and, specifically, its video crowd-sourcing project--"One Frame of Fame" (http://oneframeoffame.com/)--which asks fans to replace one frame of the band's music video for the song "More or Less" with a capture from their webcams. In the project, a visitor to the band's website is shown a single frame of the video and asked to perform an imitation in front of the camera. The new contribution is spliced into the video that updates once an hour.

"This turned out to be the perfect data source for developing an algorithm that learns to compute similarity based on pose," explained Taylor, who obtained his doctorate in computer science from the University of Toronto. "Armed with the band's data and a few machine learning tricks up our sleeves, we built a system that is highly effective at matching people in similar pose but under widely different settings."

Story Source:

The above story is reprinted (with editorial adaptations by ScienceDaily staff) from materials provided by New York University, via EurekAlert!, a service of AAAS.

Note: If no author is given, the source is cited instead.

Disclaimer: Views expressed in this article do not necessarily reflect those of ScienceDaily or its staff.

View the original article here

Revolutionary new paper computer shows flexible future for smartphones and tablets

ScienceDaily (May 4, 2011) — The world's first interactive paper computer is set to revolutionize the world of interactive computing.

"This is the future. Everything is going to look and feel like this within five years," says creator Roel Vertegaal, the director of Queen's University Human Media Lab. "This computer looks, feels and operates like a small sheet of interactive paper. You interact with it by bending it into a cell phone, flipping the corner to turn pages, or writing on it with a pen."

The smartphone prototype, called PaperPhone is best described as a flexible iPhone -- it does everything a smartphone does, like store books, play music or make phone calls. But its display consists of a 9.5 cm diagonal thin film flexible E Ink display. The flexible form of the display makes it much more portable that any current mobile computer: it will shape with your pocket.

Dr. Vertegaal will unveil his paper computer on May 10 at 2 pm at the Association of Computing Machinery's CHI 2011 (Computer Human Interaction) conference in Vancouver -- the premier international conference of Human-Computer Interaction.

Being able to store and interact with documents on larger versions of these light, flexible computers means offices will no longer require paper or printers.

"The paperless office is here. Everything can be stored digitally and you can place these computers on top of each other just like a stack of paper, or throw them around the desk" says Dr. Vertegaal.

The invention heralds a new generation of computers that are super lightweight, thin-film and flexible. They use no power when nobody is interacting with them. When users are reading, they don't feel like they're holding a sheet of glass or metal.

An article on a study of interactive use of bending with flexible thinfilm computers is to be published at the conference in Vancouver, where the group is also demonstrating a thinfilm wristband computer called Snaplet.

The development team included researchers Byron Lahey and Win Burleson of the Motivational Environments Research Group at Arizona State University (ASU), Audrey Girouard and Aneesh Tarun from the Human Media Lab at Queen's University, Jann Kaminski and Nick Colaneri, director of ASU's Flexible Display Center, and Seth Bishop and Michael McCreary, the VP R&D of E Ink Corporation.

For more information, articles, videos, and high resolution photos, visit http://www.humanmedialab.org/paperphone/ and http://www.youtube.com/watch?v=Rl-qygUEE2c

Story Source:

The above story is reprinted (with editorial adaptations by ScienceDaily staff) from materials provided by Queen's University.

Note: If no author is given, the source is cited instead.

Disclaimer: Views expressed in this article do not necessarily reflect those of ScienceDaily or its staff.

View the original article here

Revolutionary new paper computer shows flexible future for smartphones and tablets

ScienceDaily (May 4, 2011) — The world's first interactive paper computer is set to revolutionize the world of interactive computing.

"This is the future. Everything is going to look and feel like this within five years," says creator Roel Vertegaal, the director of Queen's University Human Media Lab. "This computer looks, feels and operates like a small sheet of interactive paper. You interact with it by bending it into a cell phone, flipping the corner to turn pages, or writing on it with a pen."

The smartphone prototype, called PaperPhone is best described as a flexible iPhone -- it does everything a smartphone does, like store books, play music or make phone calls. But its display consists of a 9.5 cm diagonal thin film flexible E Ink display. The flexible form of the display makes it much more portable that any current mobile computer: it will shape with your pocket.

Dr. Vertegaal will unveil his paper computer on May 10 at 2 pm at the Association of Computing Machinery's CHI 2011 (Computer Human Interaction) conference in Vancouver -- the premier international conference of Human-Computer Interaction.

Being able to store and interact with documents on larger versions of these light, flexible computers means offices will no longer require paper or printers.

"The paperless office is here. Everything can be stored digitally and you can place these computers on top of each other just like a stack of paper, or throw them around the desk" says Dr. Vertegaal.

The invention heralds a new generation of computers that are super lightweight, thin-film and flexible. They use no power when nobody is interacting with them. When users are reading, they don't feel like they're holding a sheet of glass or metal.

An article on a study of interactive use of bending with flexible thinfilm computers is to be published at the conference in Vancouver, where the group is also demonstrating a thinfilm wristband computer called Snaplet.

The development team included researchers Byron Lahey and Win Burleson of the Motivational Environments Research Group at Arizona State University (ASU), Audrey Girouard and Aneesh Tarun from the Human Media Lab at Queen's University, Jann Kaminski and Nick Colaneri, director of ASU's Flexible Display Center, and Seth Bishop and Michael McCreary, the VP R&D of E Ink Corporation.

For more information, articles, videos, and high resolution photos, visit http://www.humanmedialab.org/paperphone/ and http://www.youtube.com/watch?v=Rl-qygUEE2c

Story Source:

The above story is reprinted (with editorial adaptations by ScienceDaily staff) from materials provided by Queen's University.

Note: If no author is given, the source is cited instead.

Disclaimer: Views expressed in this article do not necessarily reflect those of ScienceDaily or its staff.

View the original article here