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A deluge of high-energy physics data is headed toward servers in Geneva, Switzerland, later this month. That's because the European Organization for Nuclear Research (CERN) now says it plans to restart its Large Hadron Collider (LHC) soon for a run that could last as long as two years at a collision energy of seven TeV (tera–electron volts, 3.5 TeV per beam). As CERN ramps up the world's most powerful particle accelerator to operate well beyond its previous best performance, the lab's computer systems must likewise be tuned so they can properly capture and analyze all of this new output.

A major hurdle in the ambitious quest to design and construct a radically new kind of quantum computer has been finding a way to manipulate the single electrons that very likely will constitute the new machines' processing components or "qubits."

Willow Garage is organizing a workshop at the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR) 2010 in San Francisco to discuss the intersection of computer vision with human-robot interaction. Willow Garage is the hardware and open source software organization behind the Robot Operating System (ROS) and the PR robot development platform. Here’s a recent video from Willow Garage of work done at the University of Illinois on how robots can be taught to perceive images:

At first glance, D-Wave Systems looks like any other well-appointed office, with an open reception area and conventional cubicles. But one glance at the wall beside the receptionist and you know the average IQ here is intimidatingly high — it’s literally covered in plaques from the U.S. patent office featuring 19th century lettering and incongruously describing patents for superconducting qubit-based microchips.

Researchers at Purdue University have developed two new techniques for computer-vision technology that mimic how humans perceive three-dimensional shapes.The techniques, heat mapping and heat distribution, apply mathematical methods to enable machines to perceive three-dimensional objects by mimicking how humans perceive three-dimensional shapes by instantly recognizing objects no matter how they are twisted or bent, an advance that could help machines see more like people.

“CMS” stands for Compact Muon Solenoid, a general-purpose particle physics detector built on the Large Hadron Collider. The CMS project posted a few comics which provide a nice, simple (if somewhat cheesy) explanation of what the CMS/LHC does. The LHC generates massive amounts of data of all different varieties, which is distributed across a worldwide grid. It sends status messages to some of the computers, job monitoring info to other computers, bookkeeping info still elsewhere, and so on. This means that each location has specialized queries it can do on the data it has, but up until now it’s been very difficult to query across the whole grid. Enter the Data Aggregation System, designed to allow anything to be queried across all of the machines.

Robot motion planning has traditionally been used to avoid collisions when moving a robot arm. Avoiding collisions is important, but many other desirable criteria are often ignored. For example, motions that minimize energy will let the robot extend its battery life. Smoother trajectories may cause less wear on motors and can be more aesthetically appealing. There may be even more useful criteria, like keeping a glass of water upright when moving it around. This summer, Mrinal Kalakrishnan from the Computational Learning and Motor Control Lab at USC worked on a new motion planner called STOMP, which stands for "Stochastic Trajectory Optimization for Motion Planning". This planner can plan paths for high-dimensional robotic systems that are collision-free, smooth, and can simultaneously satisfy task constraints, minimize energy consumption, or optimize other arbitrary criteria. STOMP is derived from gradient-free optimization and path integral reinforcement learning techniques (Policy Improvement with Path Integrals, Theodorou et al, 2010).

CHELMSFORD, MA.  October 7, 2010  Mercury Computer Systems, Inc. (NASDAQ: MRCY, www.mc.com), a trusted ISR subsystems provider, announced the availability of OpenSAL, an open source version of its award-winning Scientific Algorithm Library (SAL) for vector math acceleration. SAL is a high-throughput, low-latency signal processing library containing efficient algorithms with the fewest possible instructions and computing resources. OpenSAL provides a robust API, C code reference design and documentation for over 400 SAL math functions.

PC-compatible industrial computers are increasing in computing power at a rapid rate due to the availability of multi-core microprocessor chips, and Microsoft Windows has become the de-facto software platform for implementing human-machine interfaces (HMIs). PCs are also becoming more reliable. With these trends, the practice of building robotic systems as complex multi-architecture, multi-platform systems is being challenged. It is now becoming possible to integrate all the functions of machine control and HMI into a single platform, without sacrificing performance and reliability of processing. Through new developments in software, we are seeing industrial systems evolving to better integrate Windows with real-time functionality such as machine vision and motion control. Software support to simplify motion control algorithm implementation already exists for the Intel processor architecture.

As I noted last week, US Federal Bureau of Investigation (FBI) Director Robert Mueller told the US House Appropriations Committee’s Subcommittee on Commerce, Justice, Science, and Related Agencies that the follow-on to the notoriously failed $170 million Virtual Case File program called Sentinel would once again slip its schedule and cost targets. The latest cost estimate is in excess of $481 million with a total program slip now of some two years and counting.    Director Mueller told the House Committee that the FBI decided to suspend work on Sentinel in early March to correct some "minor" technical issues and make some design changes. These issues included, according to the New York Times, "slow response times, awkward display pages and screen print that was too small."

Their new research is published in the online edition of the Proceedings of the National Academy of Sciences (PNAS), and will soon be published in the print edition of the journal. The findings may enable new applications for semiconductors --materials that are the foundation of today's information technology. In particular, they may help identify alternative materials to use for building a potential quantum computer.

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

In 1975, future Hall of Famer Roger Staubach had the football but little else in a playoff game against the Minnesota Vikings. Behind by four points at midfield with 24 seconds to go, the Dallas Cowboys quarterback closed his eyes, threw the ball as hard as he could, and said a Hail Mary. (For you soccer fans, this would be like David Beckham taking a shot on goal from midfield late in injury time.)

In 1975, future Hall of Famer Roger Staubach had the football but little else in a playoff game against the Minnesota Vikings. Behind by four points at midfield with 24 seconds to go, the Dallas Cowboys quarterback closed his eyes, threw the ball as hard as he could, and said a Hail Mary. (For you soccer fans, this would be like David Beckham taking a shot on goal from midfield late in injury time.)

Pico Computing has developed a signal processing library which is made up of a set of FPGA firmware components and related tools that speed the development and deployment of advanced video and network analytics for security, defense and aerospace applications.The library, which includes flexible components for signal analysis, feature detection, scale-space generation, correlation and filtering, has been validated and optimized for Pico Computing platforms based on the latest-generation Xilinx Virtex-5 and Virtex-6 FPGA devices.

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.

What made me fall of my chair is the methodology/architecture part of this statement. It’s hard enough (but doable) to use RDF to map philosophically similar APIs. It’s a non-starter to use it to bridge architectural and methodological differences. I have spent a fair amount of time looking at Semantic Web technologies in the context of modeling IT systems (see the “semantic tech” category of this blog). While I think they would be a great foundation I don’t see them ever coming anywhere near what Reuven describes.

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.

RoweBots Research, Inc., a supplier of tiny embedded POSIX RTOS products, today announced the launch and release of UnisonTM Version 5 and the open-source version of Unison Version 4. These two ultra-tiny embedded-Linux and POSIX compatible RTOSs open Renesas Technology Corp.’s SH-2A Microcontroller (MCU) family to Linux and POSIX compatible development for the first time.

A class of molecules whose size, structure and chemical composition have been optimized for photonic use could provide the demanding combination of properties needed to serve as the foundation for low-power, high-speed all-optical signal processing.