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Sencha , formerly known as "Ext JS", has announced the beta release of Sencha Touch, an HTML5-based mobile application framework. Sencha Touch gives mobile application developers access to HTML5 technologies that can be deployed to both Apple and Android devices, while giving users applications that look and feels like native applications, with no need to download application updates. "HTML5 technologies are here, they're being adopted very quickly, and by the end of the year they'll be running on every mobile device that matters," said Sencha's Abe Elias. "As server and client frameworks continue to fragment, the mobile device industry has consolidated on the HTML5-capable Webkit browser as its default platform."

Complex computer models can involve thousands of variables. But paradoxically, adding more variables can sometimes make them easier to work with.

In mathematics, computer science, and related subjects, an 'algorithm' is an effective method for solving a problem expressed as a finite sequence of instructions. Algorithms are used for calculation, data processing, and many other fields. (In more advanced or abstract settings, the instructions do not necessarily constitute a finite sequence, or even a sequence; see, for example, "nondeterministic algorithm".) Each algorithm is a list of well-defined instructions for completing a task. Starting from an initial state, the instructions describe a computation that proceeds through a well-defined series of successive states, eventually terminating in a final ending state. The transition from one state to the next is not necessarily deterministic; some algorithms, known as randomized algorithms, incorporate randomness. [source = Bing Reference]

I happened to write this code sometime back that took Excel data and converted it to specific xml format. It was a simple Linq statement and here is the code

Just finishing off the chapter on bit syntax and pattern matching over bit strings for our Erlang book. We wanted to put in a realistic example, and chose a TCP segment as described  here. It's amazing how expressive the notation can be, and we get a definition which pretty much mirrors the diagram and explanation in the link above: nothing like doing it for yourself to convince you that it works.

As promised in the previous post, let’s continue with Grails support in  IntelliJ IDEA 8. Today we’ll see how the powerful IntelliJ IDEA‘s code completion applies to the Grails applications.

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.

Erlang allows for massively scalable concurrency, often with millions of lightweight, thread-like components known as actors. Unfortunately, using Erlang requires rewriting all of your legacy code into a rather esoteric language. But there are other options, such as the little known CCR platform that was developed by .NET's robotics department. Actor based languages such as Erlang are able to achieve high degrees of parallelism by using the Actor model. Under this model the fundamental unit of concurrency is not a thread or fiber, but rather something much smaller. Known as a "process" in Erlang, each unit of concurrency has a base overhead of about 1200 bytes on a 32-bit system. By comparison, a thread on the Windows operating system defaults to 1 MB just for the stack, additional space is also needed for bookkeeping and thread local storage. Because they are so lightweight, an application can spawn literally millions of processes simultaneously.

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):

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!

In order to test and run benchmarks on the work I'm doing around creating a managed variant of the JSR-166y ForkJoinPool along with supporting infrastructure for use with Scala Actors, I'm creating a test harness that captures a host of environmental factors about how it was run, and writing sbt actions to make it easy to run the benchmarks and automatically permute the variables.

scala> val ONE_DAY = 24 * 60 * 60 * 1000 ONE_DAY: Int = 86400000 scala> var manyDays: Long = ONE_DAY * 10000 manyDays: Long = 711573504 scala> var manyDays: Long = ONE_DAY * 10000L manyDays: Long = 864000000000 scala> ONE_DAY * 10000 res1: Int = 711573504

Flare is an ActionScript library for creating visualizations that run in the Adobe Flash Player. From basic charts and graphs to complex interactive graphics, the toolkit supports data management, visual encoding, animation, and interaction techniques. Even better, flare features a modular design that lets developers create customized visualization techniques without having to reinvent the wheel. View the demos and sample applications to see a few of the visualizations that flare makes it easy to build. To begin making your own visualizations, download flare and work through the tutorial. You should also get familiar with the API documentation. Need more help? Visit the help forum (you'll need a SourceForge login to post). Flare is open-source software released under a BSD license, meaning it can be freely deployed and modified (and even sold for $$). Flare's design was adapted from its predecessor prefuse, a visualization toolkit for Java

This paper develops a family of multi-pass image resampling algorithms that use one-dimensional filtering stages to achieve high-quality results at low computational cost. Our key insight is to perform a frequency-domain analysis to ensure that very little aliasing occurs at each stage in the multi-pass transform and to insert additional stages where necessary to ensure this. Using one-dimensional resampling enables the use of small resampling kernels, thus producing highly efficient algorithms. We compare our results with other state of the art software and hardware resampling algorithms.

Piotr Zalewa has created a really great playground, jsFiddle, for testing sample code and playing with the Web. With an area for the holy trinity of the Web (HTML, CSS, JS) and an output region, you can get right to hacking. It goes beyond this though. You can also add resources, an Ajax echo backend, and auto load from a slew of JavaScript frameworks. You can also check out the examples and see great stuff such as Processing in action. And the finishing touch, share and embed. Piotr wrote all of this using CodeMirror and MooTools. Nice! Having worked on Bespin, and developed a playground like this (looking forward to show a new mobile one soon!) I appreciate the work!

ScalaModules is an open source project aimed at providing fluent support for OSGi to Scala developers. It takes advantage of Scala's infix operator notation, higher order functions, and implicit conversions. ScalaModules transparently uses the Scala compiler to wrap an OSGi BundleContext with its own RichBundleContext model. This general technique is not unusual for creating DSLs in mainstream languages. Sean McDirmid uses similar tricks for his C# Bling library for WPF, except that Bling must overcome the lack of C# offering comparable extensions to Scala.