Technology Trends

In the 1990s, credit card companies incurred heavy losses because of many credit card users defaulted on their payments. Thus, credit card companies had to come up with a new way to collect debts. It was during this period that credit card companies began offering secured credit cards and prepaid debit cards. Today, most credit card companies such as Visa, Mastercard and American Express issue prepaid debit cards.

The Prepaid Debit Card Concept

A prepaid debit card works similar to a prepaid phone card. You purchase a prepaid debit card by paying the amount you want as your limit. You can add funds to your prepaid debit card at a retail location or an online bank. You use the prepaid debit card like you would use a credit card. The only difference is that the transaction amount is deducted automatically from your prepaid debit card. You can keep using the prepaid debit card until the balance reaches zero.

Benefits of Prepaid Debit Cards

You can enjoy many benefits by owning a prepaid debit card.

* You won’t need to carry a lot of cash with you every time you go out.

* If you travel frequently, you can use your prepaid debit card in countries where your card’s issuing company provides this service. Mastercard, American Express and Visa all issue prepaid debit cards that you can use in many countries. Banks have also started issuing prepad debit cards to their clients.

* With a prepaid debit card, you won’t have to worry about monthly credit card bills and missing credit card payments each month. If you are 18 years old or older, you can apply for a prepaid debit card and use it, irrespective of your credit history. Even if you have a not-so-good credit history, you can still avail of a prepaid debit card since this type of card requires funding.

* You can easily reload or add funds to your prepaid debit card. You can do this by calling the issuing company and authorizing them to transfer funds to your prepaid credit card or getting online and doing the transfer yourself. This feature of a prepaid debit card makes it very convenient for you to transfer funds, particularly when you are traveling or on vacation.

The Downside of Prepaid Debit Cards

Like other cards, the charges levied on prepaid debit cards can be high. There are fees for applying for a prepaid debit card, adding funds to it, exceeding its limit as well as cashing out and cancelling the card. So before you sign up for prepaid debit card, compare the fees offered by the issuing companies. Go with the one that has the lowest fees and the best terms. It costs about $5 to reload a prepaid debit card so make sure that you put an initial funding that is high enough. And when you need to reload your prepaid debit card, add enough funds so that you don’t find yourself reloading frequently.

Keeping Your Prepaid Debit Card Safe

To access funds from your prepaid debit card, you will need to have a PIN. Keep your prepaid debit card safe from unauthorized use by changing your PIN every so often. You should also never reveal your PIN to anyone. It’s also a good thing to ask your bank or issuing company to set a daily spending limit on your prepaid debit card in case you lose your card or someone finds out what your PIN is.

Even though prepaid debit cards have some disadvantages, their benefits outweigh them. Prepaid debit cards are especially a good solution for people who are unable to get approved for a credit card because of a poor credit history.

If you get a prepaid debit card, you should use it carefully and responsibly, much in the same way you would wisely use a credit card. Because it is very easy to reload a prepaid credit card, you may fall into the trap of using it too often and too much. Remember that you can only use it as long as you have funds in it and as long as you have funds to add to it. Keep track of your transactions so you never run out of funds.

Computer scientists from Carnegie Mellon University (CMU) are developing and using online games to train computers to better see according to the Pittsburgh Post-Gazette. One of these games is Peekaboom, used online for free by teams of two players. The first one, designated as “Peek,” sees on his screen an image — initially empty — and a word that describes the image or one element of the image. The second one, named “Boom,” gradually reveals the image or gives hints to “Peek” until he correctly guesses the word associated to the image. And this use of “segmented” images might improve “computer vision” by “teaching” them how to identify objects. But read more before playing…

Below is a simplified trial run of Peekaboom, where “Boom” is the Revealer and “Peek” the guesser (Credit: Peekaboom.org).

You’ll find a larger version of this image — along with other details — on page 15 of this presentation named “Peekaboom: A Game for Locating Objects in Images” (Powerpoint format, 23 pages, 809 KB).

The images and words used in Peekaboom, created by Luis von Ahn, have been taken from a previous CMU online game, the ESP Game, in which participants generate descriptive labels for images.

Now, let’s read some short excerpts from the Pittsburgh Post-Gazette article, starting with the game itself.

In the game, which graduate student Roy Liu has been programming since September, one player is given an image and a word that describes the image or one element of the image. The object of the game is for the first player, designated as Boom, to get the other player, designated as Peek, to correctly guess the word.

Peek initially sees only a blank screen, but as play proceeds Boom reveals the image, little by little, by moving his cursor over the image.

When the word is correctly guessed, or when the players agree to pass on an image, the players switch roles and play resumes. The players receive scores based on the number of correct guesses they can make in four minutes.

But how can this game improve computer vision?

In the early days of machine vision research, it was assumed that computers could learn to identify an object, such as a car, or a spoon, or a face, if it was given the rough geometry of the object, said Alexei Efros, a computer vision researcher at Carnegie Mellon. But that wasn’t a successful approach.

A better approach to teaching a computer how to identify an object, such as a car, is to show it lots of images of cars, of various makes and colors, taken from a variety of angles and distances and under a variety of lighting conditions, he said.

For more information, you can check how Peekaboom works by reading this introduction (PDF format, 1 page, 461 KB).

But for fun, just play with Peekaboom!!!

Sources: Byron Spice, Pittsburgh Post-Gazette, August 1, 2005; and various web sites

Related stories can be found in the following categories.

• AI
  
  
• Computers
  
  
• Games
  
  
• Software
  
  
• Vision and Visualization Apps
  

And remember that comments are no longer accepted here. If you want to tell me something about this post, please go to the bottom right of this page and send me an e-mail.

Penn State researchers have developed software agents which can help human teams to react more accurately and quickly in time-stressed situations than human teams acting alone. According to this news release, the software was tested in a military command-and-control simulation. “When time pressures were normal, the human teams functioned well, sharing information and making correct decisions about the potential threat.” But when the pressure increased, the human teams made errors who would have cost lives in real situations. The decisions taken by agent-supported human teams were much better. Now, it remains to be seen if this software can be used in other stressful situations, such as for emergency management operations. Read more…

Here is a description of the simulation experiment.

In the simulation, team members had to protect an airbase and supply route which were under attack by enemy aircraft. The scenarios were configured with different patterns of attack and at different tempos. The situation was complicated because team members had to determine at first if the aircraft were neutral or hostile. Furthermore, two team members were dependent on the third whose role was to gather information and communicate it to them.

“When the teams don’t know if the incoming aircraft is the enemy, the defense team can’t attack, and the supply team takes action to avoid the incoming threat which causes a delay in delivery,” said Shuang Sun[, one of the researchers.] “These decisions lower the performance of the whole team.”

When the information gatherer was supported by the researchers’ R-CAST software system, the information was gathered and shared more quickly. As a result, the human-agent teams were better able to defend themselves from enemy attack and deliver supplies without delay, Sun said.

The illustration below shows the structure of the two teams used for testing, with human teams on the left, and agent-supported human teams on the right (Credit: Penn State).

And the diagram below shows how these different teams were able to destroy enemies when stress increased (Credit: Penn State).

It seems pretty obvious that software agents helped humans to better react in this stressful situation.

The researchers, Xiaocong Fan, Shuang Sun, John Yen, and Michael McNeese, have presented the results of their experiments at the Fourth International Joint Conference on Autonomous Agents and Multi-Agent Systems, which was held in Amsterdam on July 25-29, 2005 (AAMAS 2005).

Here is a link to their full paper named “Extending the Recognition-Primed Decision Model to Support Human-Agent Collaboration” (PDF format, 8 pages, 413 KB). Here are some selected excerpts from the introduction.

The aim of this research is to support human decision making teams using cognitive agents empowered by a collaborative Recognition-Primed Decision (RPD) model. In this paper, we ¯rst describe an RPD-enabled agent architecture (R-CAST), in which we have implemented an internal mechanism of decision-making adaptation based on collaborative expectancy monitoring, and an information exchange mechanism driven by relevant cue analysis.

We have evaluated R-CAST agents in a real-time simulation environment, feeding teams with frequent decision-making tasks under different tempo situations. While the result conforms to psychological findings that human team members are extremely sensitive to their workload in high-tempo situations, it clearly indicates that human teams, when supported by R-CAST agents, can perform better in the sense that they can maintain team performance at acceptable levels in high time pressure situations.

The illustrations above come from this pretty interesting paper.

And if you still need more information about this project, you can check this page from the Laboratory for Intelligent Agents at Penn State.

Sources: Penn State news release, July 29, 2005; and various web sites

Related stories can be found in the following categories.

• AI
  
  
• Military Applications
  
  
• Psychology
  
  
• Software
  

And remember that comments are no longer accepted here. If you want to tell me something about this post, please go to the bottom right of this page and send me an e-mail.

What a week in the robotic world! All the media wrote about the robots used as camel riders in Qatar, but other exotic machines were also announced, such as robo-matadors in Spain or the future Picasso, the ART Painter in Hartford, Connecticut. In the medical area, robo-masseurs are helping U.S. golfers, tiny needle-driving robots are developed in Israel while future mobile ‘trauma pods’ studied in California are still 10 years away. Elsewhere, a robot that could think for itself and solve real-world problems was unveiled in Wales. But my preferred robot this week is TerraMax, a self-navigating robotic truck built in Oshkosh, Wisconsin, and which might participate in the second DARPA Grand Challenge in October 2005. Read more…

Below is a photograph of the TerraMax robotic truck in action (Credit: Oshkosh Truck Corporation). You’ll find other high-definition pictures of the TerraMax in this photo gallery.

Here are some facts taken from the press release mentioned above.

Oshkosh Truck Corporation announced [on April 12, 2005] that the Defense Advanced Research Projects Agency (DARPA) has chosen the company’s TerraMaxTM robotic vehicle for evaluation for the DARPA Grand Challenge 2005 — a 175-mile, off-road race in the Mojave Desert for completely autonomous vehicles. Of 195 teams originally submitting race entries, DARPA, a part of the Department of Defense, chose 118 for further review based on vehicle designs and capabilities.

DARPA Grand Challenge 2005 is a field test of autonomous (driverless) ground vehicles to promote the advance of autonomous vehicle technology. Teams vying to compete in the Grand Challenge develop their vehicles without government funding. By 2015, the Pentagon hopes that using autonomous military vehicles such as TerraMax will help save the lives of military personnel.

For more information about this robotic race, please visit the official DARPA Grand Challenge website. Below are quick facts about the race.

The 2005 DARPA Grand Challenge will be held on October 8, 2005 in the desert Southwest. The team that develops an autonomous ground vehicle that finishes the designated route most quickly within 10 hours will receive $2 million. The route will be no more than 175 miles over desert terrain featuring natural and man-made obstacles. The exact route will not be revealed until two hours before the event begins.

And don’t forget to check the TerraMax home page, which gives some details about the origins of the truck.

The TerraMax vehicle is based on Oshkosh’s Medium Tactical Vehicle Replacement (MTVR) defense truck platform. The MTVR was designed for the US Marine Corps with a 70% off-road mission profile.

All-wheel drive, TAK-4™ independent suspension, and central tire inflation make rocks, dips, holes and crevasses easier to handle. And the truck can handle 60% grades and 30% side slopes. A 425-hp Cat C-12 engine powers the truck.

But the site doesn’t give any details about the computer systems which will control its path. I guess these details will be available after the race, around the end of the year. Anyway, good luck, TerraMax!

Sources: Various websites

Related stories can be found in the following categories.

• AI
  
  
• Innovation
  
  
• Medicine
  
  
• Robotics
  
  
• Transportation
  

Researchers at the University of Buffalo (UB) are producing immersive virtual reality (VR) dramas in which the users are given some goals at the beginning and are interacting with ’self-aware’ computational agents. The UB Reporter writes that they are putting a new face on ‘user-friendly’ VR environments. They already created a psychodrama called “The Trial The Trail” in which “the user is given two companions named Filopat and Patofil and told that at the end of her experience she will get her heart’s desire.” And because the software agents are continuously improving and ‘improvising’ around human users, the show is different every time. I don’t know if this will lead to some mainstream application, but I’m sure that the researchers had lots of fun in their CAVEs-like systems.

Here is the introduction from the UB Reporter.

A virtual-reality drama by UB researchers — aimed at transforming the movie-going experience — is driving the development of increasingly “self-aware” computational agents that are able to improvise responses to the spontaneous actions of human users.

These improvisational computer agents are expected to influence the development of electronic devices of tomorrow, making them much more user-friendly because they will be able to respond to the idiosyncratic needs of each user.

Here are more explanations.

By necessity, said professor Stuart C. Shapiro, those characters are computational agents that must be capable of behaving in sophisticated and very human-like ways, attributes that also can help take “user-friendliness” for computers and other electronic devices to new heights.

“This is a step in the design and implementation of computer agents that are aware of themselves and their actions, as well as the environment they are in,” he explained, “so this work is relevant to any application in which people interact with a device or system.”

You also can see a video clip of “The Trial The Trail” project (54.7 MB, so be cautious).

And here are some of the reasons why this project is pretty unusual.

While other computer scientists are exploring multiple agent systems, he continued, this project is more demanding because the agents in the drama must be able to “perceive” themselves and then respond to the user.

So, as the human user proceeds through the drama, his or her actions are being recorded computationally over the Internet, interpreted psychologically and used to prompt the responses by the virtual characters.

Because of this, the drama is different every time, a factor that the researchers say is both a more challenging and exciting type of entertainment, while also more computationally demanding.

For more technical information, you can read this technical paper published in 2004 under the title “Psycho-Drama in VR” (PDF format, 12 pages, 220 KB). The above illustrations were extracted from this paper.

Will this research effort lead to something useful? I’ve no idea, but I’m sure I would have like to be involved in this project if my hometown was Buffalo instead of Paris.

Source: Ellen Goldbaum, The University of Buffalo Reporter, March 3, 2005, Volume 36, Number 24

Related stories can be found in the following categories.

• AI
  
  
• Displays
  
  
• Movies
  
  
• Virtual Reality
  
  
• Vision and Visualization
  

‘ArtGarden’ is a new search engine developed by British Telecom (BT) and tested by Tate Online. In “Smart search lets art fans browse,” BBC News reports it allows you to browse the Tate’s collection depending on what you like or not. Instead of typing an artist’s name, you will be shown an initial selection of pictures of paintings or sculptures. When you click on one image, the artificial intelligence component of ‘ArtGarden’ will choose the next set of pictures to show you. This choice will be partially based on keywords associated with each work of art, but unknown to you, partially on your previous preferences, and finally on plain luck. This technology should soon become available online. With ‘ArtGarden,’ it will be like jumping randomly from one aisle of the museum to another. Neat…

Here is a general description of the technology.

The technology uses a system dubbed smart serendipity, which is a combination of artificial intelligence and random selection. It ‘chooses’ a selection of pictures, by scoring paintings based on a selection of keywords associated with them.

So, for instance a Whistler painting of a bridge may have the obvious keywords such as bridge and Whistler associated to it but will also widen the search net with terms such as aesthetic movement, 19th century and water. A variety of paintings will then be shown to the user, based partly on the keywords and partly on luck.

Like many other technologies, this one has a very personal origin.

For Richard Tateson, [a BT's computing expert] who worked on the ArtGarden project, the need for a new way to search grew out of personal frustration. “I went to an online clothes store to find something to buy my wife for Christmas but I didn’t have a clue what I wanted,” he said.

The text-based search was restricted to looking either by type of garment or designer, neither of which he found helpful. He ended up doing his present shopping on the high street instead.

[Note: Yes, Tateson is his real name.]

BT gives additional details on the project in “Get what you want with ‘ArtGarden’,” starting with a description of the concept.

‘ArtGarden’ is designed for those of us who might not know the name of, say, every Dutch artist painting at the same time as Vermeer, but like his style and would like to see others in a similar vein. In other words, it’s designed for those times when you know what you like, would recognise it if you saw it, but can’t exactly describe it in words. ArtGarden takes advantage of broadband to show a range of art-works on screen, the choice of which may be quickly refined by the user.

You’ll find some more tidbits about the technology.

Behind the scenes ArtGarden uses artificial intelligence to keep track of each viewer’s preferences across a range of criteria. These ’scores’ are used to bias the random selector, which then picks the next item to display.

This way of browsing increases the pleasure of online art viewing because it strikes a balance between focusing browsing towards specific personal ‘likes’ and introducing some serendipity — lucky finds that a more blinkered approach might miss. It’s also simple to use — all you have to do is indicate your preferences using your mouse.

Finally, BT explains why the project is named ‘ArtGarden.’

The ArtGarden demonstration system allows online visitors to view a ‘garden’ or selection of art works, which are linked to others through a series of roots defined by the online curators or managers of collections. New items of interest are positively biased to bloom on the visitors’ screens as they select art according to their preference. Old or disliked items wither away from those displayed. After a few minutes’ browsing, the garden will be very different from the initial random selection.

Before ‘ArtGarden’ becomes available, you can search the Tate Collection with more traditional search engines, for example by searching by subject.

Sources: BBC News Online, January 28, 2005; and various websites

Related stories can be found in the following categories.

• AI
  


• Arts
  


• Search
  


• Software
  


• Vision and Visualization
  

Robotics news are dominated these days by the $100 Robosapien toy or by the latest version of Honda’s ASIMO, that you will never been able to buy, even if you put a cool US$1 million on the table. But other recent news are worth mentioning. In Florida, according to the Miami Herald (free subscription), a small company is developing a robotic arm for surgeons which could save the healthcare industry $15 billion a year. And did you know that solar-powered autonomous underwater robots are now monitoring the waters of Lake George, N.Y.? On the other coast, PARC’s pliable ‘polybots’ will reconfigure themselves to act independently on earthquake scenes or in space. And in New Zealand, robot experts are creating servants of the future able to serve us the drink we want. Elsewhere, in Korea, the government wants to deploy two-legged networked robots in post offices later this year. In a long interview to the Korea Times, Carnegie Mellon University (CMU) professor Raj Reddy says the network-based robot is a great idea. Read more…

Please read all the articles linked above for more informatio. Below are only essential excerpts and pictures.

Let’s start with the robotic arm from Z-KAT.

The new firm is using technology licensed from Massachusetts Institute of Technology’s Artificial Intelligence Lab. ”This is what they call haptic robotics,” says Ferre. ”It is a human interactive tool,” so that the surgeon holding the arm has the touch and feel just as if her own fingers were holding the instrument.

The key is that the small arm can do a knee replacement with an inch-long incision, compared with cuts of 7 to 12 inches for traditional surgery.

The arm, trademarked as Tactical Guidance System, must be approved by the Food and Drug Administration, which Ferre expects to happen fairly quickly because the FDA has already given approval to a more basic version of the arm.

Now, let’s look at what Rensselaer researchers are doing with solar underwater robots.

A collaborative group of researchers are conducting experiments with underwater robots at Rensselaer’s Darrin Fresh Water Institute (DFWI) on Lake George, N.Y., as part of the RiverNet project, an NSF-funded initiative. The group is working to develop a network of distributed sensing devices and water-monitoring robots, including solar-powered autonomous underwater vehicles (SAUVs), for detection of chemical and biological trends that may guide the management and improvement of water quality.

[Additional note: you'll find all the details about the experiments done between October 17 and 22, 2004 here.]

PARC’s modular reconfigurable robots, or polybots are an entirely different story. Sometimes, they’re called morphing or mutating robots, but why would you use these reconfigurable robots?

“The problem with a conventional robot is you spend a lot of money building this one robot that does one task very well,” says Craig Eldershaw, [a research engineer at PARC (Palo Alto Research Center).] “A modular robot can change its shape to adapt to a particular job. To wash dishes, it needs small delicate arms and fingers. For gardening, it could have a couple big strong arms to hold a shovel and big treads to move through mud.”

That kind of robotic domestic help is as much as three decades away, he acknowledges. But experimental search-and-rescue bots could be deployed in earthquake- or bomb-racked buildings within the next few years, he says.

Morphing robots also could become space explorers.

PARC recently took on a long-term NASA contract to develop a robotic arm that could move around the outside of a next-generation space shuttle freely and convert itself into several arms or a claw if the need arises. “Think in-space construction or assembly,” Mr. Eldershaw says. “Any time you can prevent someone having to go out into space in a suit you’ve won a lot of friends at NASA.”

Mark Yim, a researcher at the University of Pennsylvania who set up the modular robotics research group at PARC after completing his doctorate at Stanford, is leading a team that has taken on a NASA contract to build a morphing Mars explorer. To demonstrate the robot’s ability to assist with human life support, the experimental robot will be given the task of growing and nurturing a small plant inside a sealed environmental chamber.

It’s time to move to another continent, and to robots willing to serve us our favorite cocktails — maybe not this year — but in a foreseenable future.

“(In) 15 years’ time, I’d estimate something like this would serve drinks,” says Australian Tribotix robotics and electronics company engineering manager Steve Mitchell, putting a humanoid-shaped robot through its paces, literally. They’ll be that common.”

He remote-controls the 30cm-tallrobot and fascinated conference-goers cluster, watching it walk, bend forward and backward and move its arms, legs, torso and head independently. It can also slide skiing-style and perform acrobatics such as headstands.

Meanwhile, Korea is introducing a competitor with Honda’s Asimo. The 1.2-meter-tall KHR-3, which weighs roughly 55 kilograms, can walk by using 41 built-in motors and numerous joints and can also shake hands or lift objects with its five-fingered hands.

Korea’s officials also think they’re fast catching Japanese in robotics.

“In order to understand the humanoid development, we must split two facets of the mechanics and intelligence. Mechanically, we lag behind Japan 2-3 years, but we are almost on par with the country in intelligence,” a project manager said.

These robots will be introduced next year in five different projects, three for home usage and two for post offices.

To conclude this long post, I just want to say I was disappointed by the Korea Times’s interview of Raj Reddy, a person I really respect. His interview looks like a press release, very different from what you can read in a recent effort he made for promoting $250 computing devices for developing countries.

Sources: John Dorschner, The Miami Herald, December 6, 2004; Rensselaer Polytechnic Institute, December 6, 2004; Janet Rae-Dupree, Silicon Valley/San Jose Business Journal, December 10, 2004; Lee Matthews, Manawatu Standard, New Zealand, December 10, 2004; Kim Tae-gyu, The Korea Times, November 23 and December 19, 2004; Byron Spice, Pittsburgh Post-Gazette, September 20, 2004

Related stories can be found in the following categories.

• AI
  


• Environment
  


• Medicine
  


• Robotics