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The R programming language was featured about a year ago in a New York Times article (http://bit.ly/iaqQ). I've been an R user since 2000, so I've collected some resources for people who want to get started with R.   The first place to start is the R Project web site at http://www.r-project.org/. Next, you'll actually want to install R itself. There are several options, depending on your environment.

Last week Wim Jongman bloged about the Nebula Oscilloscope widget. It’s just an awesome widget for monitoring activity. See Wim’s post to form an opinion yourself. So, for me as a RAP developer, the first question I always ask myself when seeing such a cool thing is: “Will it run on RAP?”. I followed the steps Wim described to get the Oscilloscope running, changed the target to RAP, commented out one line of code and started the application. You can see the result in the screencast below.

The Robotics Developer Studio (RDS) Simulator is a key feature of the package that allows you to get started without buying expensive robots. It is a great tool for use in education. The add-ons outlined below help you to create your own simulation environments and get started on learning about robotics.

You can think of the Distributed Flight Array as a combination between vertical take-off and landing vehicles, and modular reconfigurable robots. It is a flying platform consisting of multiple, autonomous, single-propeller vehicles, and these single propeller vehicles - or modules - are able to generate enough thrust to lift themselves into the air, but are completely unstable in flight, kind of like a helicopter without a tail rotor.

In short, Joe argues, "Throughout, it became abundantly clear that TM, much like generics, was a systemic and platform-wide technology shift. It didn’t require type theory, but the road ahead sure wasn’t going to be easy." The whole blog post deals with how many implementation challenges platform-wide support for STM would be in .NET, including what options were considered. He does not mention Maurice Herlihy's SXM library approach, but refers to Tim Harris's work several times.

First, right off the top here: Scala has true blue Java-like null; any reference may be null. Its presence muddies the water quite a bit. But since Beust's article explicitly talks about Haskell he's clearly not talking about that aspect of Scala because Haskell doesn't have null. I'll get back to Scala's null at the end but for now pretend it doesn't exist.Second, just to set the record straight: "Option" has roots in programming languages as far back as ML. Both Haskell's "Maybe" and Scala's "Option" (and F#'s "Option" and others) trace their ancestry to it.

platform :   Linux   Windows   MacOSX Intel type :   diskmag release date : august 2010 release party : Evoke 2010

Scientists from Bielefeld University have come up with a plastic-head robot called Flobi that can express a number of different emotions, and can have it’s appearance reassembled from male to female (or vice-versa) in a couple of minutes.

The MATLAB team at MathWorks tested performance scaling of the backslash ("\") matrix division operator to solve for x in the equation A*x = b. In their testing, matrix A occupies far more memory (290 GB) than is available in a single high-end desktop machine—typically a quad core processor with 4-8 GB of RAM, supplying approximately 20 Gigaflops. Therefore, they spread the calculation across machines. In order to solve linear systems of equations they need to be able to access all of the elements of the array even when the array is spread across multiple machines. This problem requires significant amounts of network communication, memory access, and CPU power. They scaled up to a cluster in EC2, giving them the ability to work with larger arrays and to perform calculations at up to 1.3 Teraflops, a 60X improvement. They were able to do this without making any changes to the application code. Here's a graph showing the near-linear scalability of an EC2 cluster across a range of matrix sizes with corresponding increases in cluster size for MATLAB's parallel backslash operator:

In this session, Don McCrady discusses how C++ programmers can fully utilize multicore in their applications using the Concurrency Runtime (ConcRT), the Parallel Pattern Library (PPL), and the Asynchronous Agents Library that ship with Visual Studio 2010.

Because telecommunication systems require by essence to conform to a common standard that covers static and dynamic interfaces, telecommunication standardization bodies as well as telecommunication equipment manufacturer have been using advanced modeling technologies such as MSC, ASN.1, SDL, and TTCN for years. In fact these technologies cover the whole development cycle from requirements, specification, design, and test. That is why it should definitely be considered when developing communicating systems.   

When a data (typically a variable) can be accessed by several threads, you must synchronize the access to the data to ensure visibility and correctness.

If you need a quick reference guide for the UML notation, check one of the following, IMHO, gret UML cheat sheets (in no particular order):

Dave Megginson (who drove the development of the SAX API that will be familiar to many XML developers who use Java) recently wrote Java is dead. Java stood out as a programming language (though not as a platform) in that Sun had refused to standardize it through an independent and reputable standards organization (a lot of the hard work had been done in one attempt to put it through ECMA and one to put it through ISO, both times Sun pulled out and eventually made their highly unsatisfactory JCP Java Community Process system.) Without the ability to alter Java significantly in ways that might go against their druthers, Java suffered two major forks (Microsoft's J++ then its C#, and IBM's SWT) where significant players disagreed with a major component (the graphics library). Java succeeded in middleware, and but failed to take advantage of the rise of browsers on the deskop: their HTML parser was great for the middle 1990s but was deliberately neglected to the point of being unusable: it is hard not to see this as a deliberate attempt by Sun to leave the browser market to its friends and enemies. I really liked Java, and bet my company on it (in a sense): I would not do that today.

As many long time readers know, I am an enthusiast of the F# programming language.  I make no apologies for the fact that, if you are developing software on the .NET platform, F# is one of the better choices you can make for numerous reasons.  It is one of the reasons I proudly contributed as a co-author to the book, Professional F# 2.0, which is being published by Wrox in October. Some of the oft cited benefits of F# are that, to distill them quickly, it is good at doing intensely mathematical operations, it is built for parallelism, and it is good at helping define domain specific languages.  Those benefits are so often cited by speakers on the F# speaker circuit that they pretty much seem cliche to me at this point (note, yours truly is proud to call himself a member of said circuit, and often gives this talk!)  As great as these features are, there are a couple features, that in my more mundane F# experiences, seem to stand out as things that “save my ass”, for lack of a better phrase, more often than not.

The latest episode of the Robots Podcast looks at the following scenario: Imagine being able to throw a hand-full of smart matter in a tank full of liquid and then pulling out a ready-to-use wrench once the matter has assembled. This is the vision of this episode's guests Michael Tolley and Jonas Neubert from the Computational Synthesis Laboratory run by Hod Lipson at Cornell University, NY. Tolley and Neubert give an introduction into Programmable Matter and then present their research on stochastic assembly of matter in fluid, including both simulation (see video above) and real-world implementation. Read on or tune in!

Japan’s National Institute of Advanced Industrial Science and Technology (AIST) has detailed the software used to make their robot dance (see some nice photos over at Pink Tentacle) in a recent press release.  The software, dubbed Choreonoid (Choreography and Humanoid), is similar to conventional computer animation software.  Users create key poses and the software automatically interpolates the motion between them.  What makes the software unique is that it also corrects the poses if they are mechanically unstable, such as modifying the position of the feet and waist, allowing anyone to create motions compatible with the ZMP balancing method.  This is especially important for robots like the HRP-4C, where complicated motions could easily cause it to fall over.

WebP is a method of lossy compression that can be used on photographic images. WebP offers compression that has shown 39.8% more byte-size efficiency than JPEG for the same quality in a large scale study of 900,000 images on the Web. The degree of compression is adjustable so a user can choose the trade-off between file size and image quality.

Researchers at CMU and Intel are attempting to map and understand human brain activity well enough that individual words can be detected. Currently, giant MRI machines are being used but the future holds smaller devices that can be worn like a helmet according to Dean Pomerleau, senior researcher at Intel. The efficiency and productivity of word detection will be superior to existing technology that allows an operator to simply control a cursor. This technology will no doubt make its way into robotic telepresence applications including remote surgery and construction in dangerous environments such as the ocean and space.