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In addition to voice connectivity, digital cellular wireless networks such as GSM and its enhancement, GSM-EDGE, can now provide increased data speeds up to a (theoretical) limit of 384ﾠKbps. Third generation mobile networks, such as CDMA2000 and WCDMA or UMTS (Universal Mobile Telecommunications Standards) and TD-SCDMA (China only) are currently being deployed worldwide. These systems offer services such as video streaming, Internet browsing and, by using a technique called High Speed Packet Access (HSPA), they can in theory deliver downlink speeds up to 14,4 Mbps.

An innovatice camera system could in future enhance security in public areas and buildings. Smart Eyes works just like the human eye. The system analyzes the recorded data in real time and then immediately flags up salient features and unusual scenes.  »Goal, goal, goal!« fans in the stadium are absolutely ecstatic, the uproar is enormous. So it‘s hardly surprising that the security personnel fail to spot a brawl going on between a few spectators. Separating jubilant fans from scuffling hooligans is virtually impossible in such a situation. Special surveillance cameras that immediately spot anything untoward and identify anything out of the ordinary could provide a solution. Researchers from the Fraunhofer Institute for Applied Information Technology FIT in Sankt Augustin have now developed such a device as part of the EU project »SEARISE – Smart Eyes: Attending and Recognizing Instances of Salient Events«. The automatic camera system is designed to replicate human-like capabilities in identifying and processing moving images.

When I first heard about compressed sensing, I was skeptical. There were claims that it reduced the amount of data required to represent signals and images by huge factors and then restored the originals exactly. I knew from the Nyquist-Shannon sampling theorem that this is impossible. But after learning more about compressed sensing, I’ve come to realize that, under the right conditions, both the claims and the theorem are true. The Nyquist-Shannon sampling theorem states that to restore a signal exactly and uniquely, you need to have sampled with at least twice its frequency. Of course, this theorem is still valid; if you skip one byte in a signal or image of white noise, you can’t restore the original. But most interesting signals and images are not white noise. When represented in terms of appropriate basis functions, such as trig functions or wavelets, many signals have relatively few non-zero coefficients. In compressed (or compressive) sensing terminology, they are sparse.

A little over a mile from the Wolfram Research Europe Ltd. office, where I work, lies Blenheim Palace, which has a rather nice hedge maze. As I was walking around it on the weekend, I remembered a map solving example by Peter Overmann using new image processing features in an upcoming version of Mathematica. I was excited to apply the idea to this real-world example. Once back at my computer, I started by using Bing Maps to get the aerial photo (data created by Intermap, NAVTEQ, and Getmapping plc).

The goal of Long Term Evolution (LTE) is to achieve higher data rates through more efficient transmission, and thus improving the cellular phone user experience by enabling powerful new devices. The changes required in this technology present new challenges for base station vendors and their suppliers. Supporting 4G systems efficiently requires a number of innovations in DSP design; these innovations are moving the industry toward SoC architectures to support such systems. This paper will explore how TI's new architecture enables the key features in 4G systems.

Microsoft Research who brought us some wonderful technologies such as the incredible Photosynth continue to impress with a much improved web mapping application integrated with the company's new Bing search engine. During the TED 2010 conference, Microsoft engineer Blaise Aguera y Arcas demoed the new Bing augmented reality maps showing real-time registration of video taken with a smart phone and street-view type maps. He showed how the live video can be overlayed over the static images and additional information about the area can be accessed via a Web interface. Much of this is made possible because of the advanced computer vision technology that has been developed in the past decade at Microsoft Research. The Seadragon technology is the back-end that makes it possible to manipulate such vast amounts of data in real-time. Microsoft has also integrated Photosynth and Worldwide telescope into their maps product. You are probably wondering what does this have to do with robotics other than the fact that it is a very impressive application? I can imagine robots using Bing maps to keep localized within a city. One of the most difficult and important problem in robotics is that of Simultaneous Localization and Mapping. Bing maps solve the mapping problem and the new vision techniques (with a bit of help from GPS) can be used to solve the localization problem. The registered video can be used by a robot to localized itself when it goes out to buy your weekly groceries.  You can watch the 10-minute demo below; I bet that it won't be long before Microsoft makes these new features available to us all for free.

For the price of a sports car, you can have a pint of your blood drawn and a month later receive your entire genome—all 6 billion base pairs—encoded in a 1.5-gigabyte data file. That means the price has dropped to 1/50 000 of what it was less than a decade ago (the first genome, after all, cost US $3 billion). Yet the price is expected to fall to 1/1000 of the current price in the next four years. The cultural ramifications of a $100 genome—which is where we’re headed, whether it takes 4 years or 10—are as wide and deep as those of any other recent innovation, including search engines and cellphones.

4 January 2010—Though flexible devices such as roll-up displays have been promised for several years, their commercialization has been stalled by a missing ingredient: a flexible form of flash memory. But researchers at the University of Tokyo have recently developed an organic, floating-gate nonvolatile memory that behaves like flash memory, which may solve that problem. While silicon-based flash memory is fine for the mass data storage found in cellphones, digital music players, and thumb drives, fabricating it requires high processing temperatures, thus ruling out its production on flexible substrates like plastic. Organic semiconductors, however, can be processed at temperatures well below the melting point of most plastics. What's more, "the cost of flash memory is too high to use in applications that require large arrays of memory," says Tsuyoshi Sekitani, an assistant professor in the University of Tokyo's department of electrical and electronic engineering and one of the researchers who developed the new memory. "But we can print our organic memory on flexible substrates and over large areas using inkjet printers. So costs will be low."

On Monday, National Instruments announced one such platform. It's called LabView Robotics. In addition to LabView, the popular data-acquisition application, the package includes a bunch of tools specific to robotics. It can import codes in various formats (C, C++, Matlab, VHDL), offers a library of drivers for a wide variety of sensors and actuators, and has modules for implementation of real-time and embedded hardware. NI says engineers could use the package to both design and run their robotic systems. 

On 10 July, the European Space Agency's Rosetta spacecraft will fly within a few thousand kilometres of 21 Lutetia, a main belt asteroid that orbits the Sun between Mars and Jupiter. Lutetia is an unusual object. It is classified as an M-type asteroid, which are thought to be made mainly of nickel and iron. However, Lutetia's spectrum does not seem to show any evidence of metals. In fact, exactly what Lutetia is made of puzzles astronomers. That's partly why it was chosen for the fly by. So come July, astronomers should know the answer to this conundrum. But in the run up, they're indulging in a little fun. The game they've invented is to see how good a prediction they can make about what Rosetta will find. Today, Irina Belskaya at the Observatoire de Paris and a few friends take a stab. They make several detailed predictions about Lutetia based partly on observations dating back to the 1960s but mostly on data taken since 2004, when interest picked up after the asteroid was chosen as a flyby target. So what do they think Rosetta will find?

Related to the strong demands for virtualization technology, network I/O virtualization has recently become a hot topic and is one of the key topics being discussed at the upcoming Multicore Expo @ ESC. In fact, analyst firm IDC, in a recent white paper titled "Optimizing I/O Virtualization: Preparing the Data Center for Next-Generation Applications", stated that "If I/O is not sufficient, then it could limit all the gains brought about by the virtualization process."

This week, Mercury is emerging from the glare of the sun and making a beeline for Venus. By week's end, the two planets will be just 3o apart, an eye-catching pair in the deep-blue twilight of sunset. The best nights to look are April 3rd and 4th. Go outside at the end of the day and face west. Venus pops out of the twilight first, so bright it actually shines through thin clouds. Mercury follows, just below and to the right: April 3April 4 Venus is an old friend to most sky watchers; Mercury, less so. The first planet from the sun spends most of its time wrapped in painful sunlight. Seeing it so easily, and in the beautiful company of Venus no less, is a rare treat indeed. The next apparition this good won't come until Nov. 2011. By that time, however, we'll have much better view of Mercury all the time. NASA's MESSENGER probe is en route to Mercury now, and in March of 2011 it will become the first spacecraft to orbit the planet. During a year-long science mission, MESSENGER will beam back a stream of high-resolution pictures and data obtained using seven instruments designed to operate in the extreme environment near the Sun. This kind of coverage of planet #1 is unprecedented.

Power and energy are key design considerations across a spectrum of computing solutions, from supercomputers and data centers to handheld phones and other mobile computers. A large body of work focuses on managing power and improving energy efficiency. While prior work is easily summarized in two words—"Avoid waste!"—the challenge is figuring out where and why waste happens and determining how to avoid it. In this article, I discuss how, at a general level, many inefficiencies, or waste, stem from the inherent way system architects address the complex trade-offs in the system-design process. I discuss common design practices that lead to power inefficiencies in typical systems and provide an intuitive categorization of high-level approaches to addressing them. The goal is to provide practitioners—whether in systems, packaging, algorithms, user interfaces, or databases—a set of tools, or "recipes," to systematically reason about and optimize power in their respective domains.

Bruno Oliveira and I are working on a functional pearl called The Monad Zipper (*). You know how dealing with monad transformers can be quite awkward -- especially when developing highly modular programs where every component comes with its own effects?Well, we bring relief in this situation by applying Huet's zipper to a type-level data structure: the monad stack.We're submitting to ICFP on April 2, and would greatly appreciate your feedback on the current draft. Please let us know what you think of the presented approach, the clarity and style of writing, examples of situations where you could have used the monad zipper, ...(*) not to be confused with the zipper monad

A common requirement in digital-dominated mixed-signal verification is the need for purely event-driven models that imitate Spice or AMS blocks at low fidelity but high speed. Resolved record types are commonly used for this modeling style in VHDL-based flows. Unfortunately, SystemVerilog defines only one resolved net type, the logic type. A second, non-standard net type, wreal, has been borrowed from Verilog-AMS and, with proprietary extensions, added to some implementations of SystemVerilog. wreal is a single real value with a small, fixed set of resolution functions. It solves only a subset of the problems commonly encountered in event-driven analog modeling. In contrast, the ADMS_signals approach is completely general and extensible while still conforming strictly to the IEEE SystemVerilog standard. The stored data type can be any type that is legal in SystemVerilog, including arrays and structs (nested to arbitrary depth) and even class instances (objects). The resolution function is a user-supplied SystemVerilog function. Different networks in the same design hierarchy may be given distinct stored type and resolution function.

Today sees the launch of Visual Studio 2010, at five launch events around the world, as announced by Bob Muglia, Jason Zander and S. Somasegar, and presented live today in Las Vegas.   Visual Studio 2010 includes the official version 2.0 of the F# language. As is our custom on the F# team, we also release a matching MSI and ZIP of F# 2.0 (for use with Visual Studio 2008 and as a standalone compiler on a range of platforms)   Today represents the culmination of 7 years of work on the language at Microsoft Research, and, more recently, the Microsoft Developer Division. I am immensely proud of what we’ve achieved. F# brings a productive functional and object-oriented programming language to .NET, extending the platform to new audiences in technical, algorithmic, data-rich, parallel and explorative domains, and its inclusion in Visual Studio 2010 represents a huge milestone for the language.   To help understand what we’re doing with F#, I’ve listed some of the common questions people have about the language below.  We thank everyone who has been involved in the production of F#, especially the many users who have given us feedback on the language!

Let’s face it. Most of the gear you use at work or play has multicore processors in it. Your laptop has them (the CPU itself has two cores, and the dedicated graphics processor has many more). That game console in the living room has still more, and even a high-end smartphone typically has a CPU and graphics core on a single chip. Out of sight but definitely not out of mind–particularly if they cease working–are the servers and high-throughput network routers, all which have numerous multicore processors in them. The multiple cores in these devices work in concert to provide quick responses to user queries or to manage the smooth flow of data throughout the office.