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Archive for October, 2009

While more older adults than ever are using cell phones and computers, a technology gap still exists that threatens to turn senior citizens into second-class citizens, according to Florida State University researchers.

Neil Charness, the William G. Chase Professor of Psychology, and Walter R. Boot, an assistant professor of psychology, found that both the attitudes and abilities of older adults pose barriers to adopting new forms of technology and urged designers to consider those barriers when developing new products. Charness and Boot will publish a review of the research on the topic in Current Directions in Psychological Science.

“The technology gap is a problem because technology, particularly computer and Internet technology, is becoming ubiquitous, and full participation in society becomes more difficult for those without such access,” said Charness, who along with Boot received a $1.5 million, five-year subcontract from a National Institute of Aging grant to support the Center for Research and Education on Aging and Technology Enhancement (CREATE). Established a decade ago, the center is comprised of researchers at FSU, the University of Miami and the Georgia Institute of Technology, who study ways to increase technology use in order to promote cognition and health in older Americans.

From booking airline tickets to seeking health care information, almost everything is easier, cheaper or faster online. Older adults who may be less mobile in particular stand to benefit from innovations such as online banking. But there is a sharp decline in Internet use after age 65, the researchers said, citing a 2007 Pew Tracking Survey that showed 85 percent of adults in 18-24, 25-34 and 35-44 age groups used the Internet. By contrast, only 39 percent of adults between 65 and 74, and 24 percent of adults between 75 and 84 were Internet users.

Declining cognitive processes, decreased memory capacity and difficulty maintaining attention — all part of the normal aging process — can make it difficult for seniors to learn new skills. In fact, Charness said, it takes older adults roughly twice as long as younger people to learn a new word processor under self-paced learning conditions. That’s true even for older adults who have prior experience with another word processor.

The extra time and effort required to learn a new skill are among the reasons why older adults are generally less motivated than younger people to learn new skills — particularly if they decide that the potential benefits of the new technology are not worth it. In addition, seniors may make a greater number of errors as they interact with technology that was not designed with their capabilities in mind.

Seniors quite literally perceive new technology differently than younger adults do. Changes in acuity, color perception and susceptibility to glare affect the way they see a computer screen. They also have greater difficulty with fine motor control and coordination. However, knowing these constraints, designers can create better products for older adults, the researchers said. Among their suggestions:

* Create cell phones with simplified menus, large fonts and buttons and external noise reduction.
* Design Web sites with high contrast backgrounds and text, larger fonts and minimal scrolling. The sites should provide navigation aids and instructional support.

Computer games — such as Nintendo’s Brain Age — and software packages that have been developed for and marketed to older adults may also help reverse age-related declines in perceptual and cognitive abilities, the researchers said.

“There is limited but encouraging evidence that these so-called brain fitness software packages make a difference in improving some basic skills, but so far there is little evidence that they improve older adults’ quality of life or ability to live independently,” Boot said. “That should be the measure of success in evaluating these programs.”

Although the technology gap between younger and older adults is expected to lessen over time as more adults “grow up” with computers, the problem will not disappear in future generations, the researchers said. That’s because technology will undoubtedly continue to advance rapidly, and age-related declines in cognitive, perceptual and psychomotor skills will make it more difficult for seniors to keep up with the changes.

Don’t believe it? Consider that today’s seniors grew up with telephones, and yet they have been much slower to adapt to using cell phones. Still, those over 65 are more likely to use a cell phone — 46 percent of them do — than use the Internet.

Computer scientists from Nanyang Technological University in Singapore and Autism Society of America are working on the development of an efficient and intelligent facial expression recognition system. The system is capable of locating the face region using derivative-based filtering and recognizing facial expressions using boosting classifier. The portable device is being developed to help autistic children understand the emotions of surrounding people.

A paper detailing the specifics of the device will be published in the journal Intelligent Decision Technologies.

Teik-Toe Teoh, Yok-Yen Nguwi and Siu-Yeung Cho of the Centre for Computational Intelligence of the School of Computer Engineering of Nanyang Technological University state that “emotion is a state of feeling involving thoughts, physiological changes, and an outward expression. In this paper, we propose a system that synergizes the use of derivative filtering and boosting classifier. ”

The portable facial expression recognizer locates the edge of the human face through Gaussian derivatives, Laplacian derivatives and filter out non-face images using Adaboost. Secondly, the feature locator finds crucial fiducial points for subsequent feature extraction and selection processing. Finally, the meaningful features are classified into the corresponding classes.

From the motion sensor to the computer chip, in many products of daily life components are used whose functioning is based on smallest structures of the size of thousandths — or even millionths — of millimetres. These micro and nano structures must be manufactured and assembled with the highest precision so that in the end, the overall system will function smoothly.

Because of this, details are important. Scientists Nursing Los Angeles at the Physikalisch-Technische Bundesanstalt (PTB) have now developed a metrological scanning probe microscope into a micro and nano coordinate measuring instrument. This allows dimensional quantities with nanometer resolution also to be measured on three-dimensional objects in an extraordinarily large measurement range of 25 mm x 25 mm x 5 mm. The new device is already extensively being used at PTB - to a large part for calibration orders from industry and research.

Often, such small dimensions bailwiz can be grasped only when they are transferred to everyday life. If we assume, for example, that someone lost a cube of sugar within an area of 25 square kilometres – the new micro and nano coordinate measuring instrument would not only be able to find it, but it would also be able to determine its exact position and shape. This does not only apply to plane surfaces, but also to three-dimensional landscapes, for example if the cube of sugar were stuck to a steep wall.

As increasingly, hair removal in los angeles components with structures in the micro- and nanometer range are being used in industry, dimensional metrology on such structures is becoming increasingly important. To meet the increasing requirements for 3D measurements of micro and nano structures, 3D measuring probes newly developed at PTB were incorporated in a metrological scanning probe microscope based on a commercial nano-positioning system with integrated laser displacement sensors of the company SIOS Messtechnik GmbH. The new functionalities given by the measuring probe and the software extend the scanning probe microscope to a metrological micro/nano coordinate measuring machine (CMM) which also allows 3D measurements conforming to standards to be performed on micro and nano structures.

International intercomparisons on step-height standards and lattice structures have shown that the measuring system is worldwide one of the most precise of its kind. For step heights, measurement uncertainties in the subnanometer range - and for measurements of the mean structure spacing on extensive lattice standards even in the range of 10 picometers - have been achieved and confirmed in comparison with optical diffraction measurements.

The new measuring instrument is available for dimensional precision measurements with nm resolution on 3D micro and nano structures such as micro gears, micro balls, hardness indenters and nano lattice standards as well as for comparisons of measures; moreover, it serves as a platform for research and development tasks. It is an important link between nano, micro and macro coordinate metrology.

Researchers for autistic spectrum disorder at Carnegie Mellon University and Intel Labs Pittsburgh (ILP) have combined low-power, embedded processors typically used in netbooks with flash memory to create a server architecture that is fast, but far more energy efficient for data-intensive applications than the systems now used by major Internet services.

An experimental computing cluster based on this so-called Fast Array of Wimpy Nodes (FAWN) architecture was able to handle 10 to 100 times as many queries for the same amount of energy as a conventional, disk-based cluster. The FAWN cluster had 21 nodes, each with a low-cost, low-power off-the-shelf processor and a four-gigabyte compact flash card. At peak utilization, the cluster operates on less energy than a 100-watt light bulb.

The research team, led by David Andersen, Carnegie Mellon assistant professor of computer science, and Michael Kaminsky, senior research scientist at ILP, received a best paper award for its report on FAWN at the Association for Computing Machinery’s annual Symposium on Operating Systems Principles Oct. 12 in Big Sky, Mont.

A next-generation FAWN cluster is being built with nodes that include Intel’s Atom processor, which is used in netbooks and other mobile or low-power applications.

Developing energy-efficient server architectures has become a priority for datacenters, where the cost of electricity now equals or surpasses the cost of the computing machines themselves over their typical service life. Datacenters being built today require their own electrical substations and future datacenters may require as much as 200 megawatts of power.

“FAWN systems can’t replace all of the servers in a datacenter, but they work really well for key-value storage systems, which need to access relatively small bits of information quickly,” Andersen said. Key-value storage systems are growing in both size and importance, he added, as ever larger social networks and shopping Web sites keep track of customers’ shopping carts, thumbnail photos of friends and a slew of message postings.

Flash memory is significantly faster than hard disks and far cheaper than dynamic random access memory (DRAM) chips, while consuming less power than either. Though low-power processors aren’t the fastest available, the FAWN architecture can use them efficiently by balancing their performance with input/output bandwidth. In conventional systems, the gap between processor speed and bandwidth has continually grown for decades, resulting in memory bottlenecks that keep fast processors from operating at full capacity even as the processors continue to draw a disproportionate amount of power.

“FAWN will probably never be a good option for challenging real-time applications such as high-end gaming,” Kaminsky said. “But we’ve shown it is a cost-effective, energy efficient approach to designing key-value storage systems and we are now working to extend the approach to applications such as large-scale data analysis.”

The work was supported in part by gifts from Network Appliance, Google and Intel Corp., and by a grant from the National Science Foundation. In addition to Andersen and Kaminsky, the research team included Ph.D. computer science students Jason Franklin, Amar Phanishayee and Vijay Vasudevan, and graduate student Lawrence Tan.