If you were thinking of buying a new Apple computer, you probably won’t find a better time than now, especially if you are interested in the 24-inch iMac with the M1 chip. Unfortunately, Apple does not make discounts on the price of its products, but MediaMarkt does, so pay attention to the offer that we tell you about in this post because it will surely interest you.
When buying an Apple computer, the investment that the user has to make is always high, and it doesn’t matter if there is a discount or not, no matter how much discount the device has, you will surely always have to invest more than 900 euros. Now, it is not the same to go from having to pay almost 1,500 euros for the iMac to being able to buy the same product for 1,300, right? Well, that is exactly what we want to tell you about in this post, since MediaMarkt has a piece of sale on the 24-inch iMac M1. We leave them to you below.
- iMac M1 8 GB of RAM 256 GB SSD with 8 CPU cores and 7 GPU cores: 1,299 euros, that is, a discount of 150 euros.
- iMac M1 8 GB of RAM 256 GB SSD with 8 CPU cores and 8 GPU cores: 1489 euros, that is, a reduction of 180 euros.
- iMac M1 8 GB of RAM 512 GB SSD with 8 CPU cores and 8 GPU cores: 1722 euros, that is, a discount of 177 euros.
Is the 24-inch iMac worth it?
As we told you, despite the fact that the discount you have available is considerable, the investment you have to make is still quite high, and that makes many potential buyers who are in doubt wonder, is this device really worth it? Well, everything will depend, as always, on the needs that the user has.
The iMac, par excellence, is a device that has always been characterized by three factors, the least important being its designand the two primordial ones, the great performance that it offers and also the durability of the team, which is capable of performing like a charm for many years. However, when buying a computer you have to take into account what you are going to do with it.
The 24-inch iMac It is not intended for an ultra-professional audience, but for ordinary users who need a computer that gives them the reliability and power they need to carry out their daily tasks. These tasks are browsing the internet, making video calls, working on text documents, excel, presentations, and also occasional video editing, as well as photo editing. In the end you have to take into account that they have 8 GB of RAM, and that’s what it gives, so if you want something more focused on moving actions that require a lot of power, you would have to look at other options with more RAM. However, this audience is not the most common, so the vast majority of users will have more than enough with this iMac, which now has a very interesting discount for Black Friday.


From discussions all over the internet, I understand that in a 512 sample point fft, only the first 256 contain relevant information provided that my signal is real. The other half contains complex conjugates of the first half. I base my question on this discussion at stack exchange.
I'm trying to plot the fft of a wav file. I used 2 files - one wav file containing some music and another that was generated by scrip to play at 440Hz. The fft plot of the 2nd (440hz signal) showed 2 peaks - one at 440hz and another at the other end of the plot. This was expected. However, plot of the music wav file was asymmetric. How can that be?
I used the file onclassical_demo_elysium_anonymous-elysium_the-young-false-man_small-version_live-and_restored found here. Scipy did not parse it properly first and I had to strip the meta tags using audacity before I could get it working.
I used print and I got this for the 440hz tone :
[ 203395.00000000 +0.j 203395.08226712 -57.78564066j 203395.32901382-115.57039787j ..., 203395.74007235+173.35334037j 203395.32901385+115.57039784j 203395.08226713 +57.78564063j]
For the music file, I got this :
[[ 2.+0.j -4.+0.j] [-1.+0.j -7.+0.j] [ 0.+0.j -2.+0.j] ..., [ 0.+0.j -6.+0.j] [ 0.+0.j -2.+0.j] [ 1.+0.j -1.+0.j]]
I don't think any of them are symmetrical! Or else the first and last values should coincide at least in the real part right?
And just for the sake of it, the 440hz signal plot :
I tried plotting abs(fft) - still asymmetrical. Also, why is the plot having both blue and green colors - real and complex parts?


WiFi File Transfer Pro
Size: 2.59 MB | Version: 1.0.9 | File Type: APK | System: Android 2.1 or higher
Description : WiFi File Transfer Pro is a light-weight web server that lets you upload and download files to/from your phone or tablet over a wireless connection. Transfer files without a USB cable.
Features of WiFi File Transfer Pro apps : • Upload or download multiple files at once • Upload entire folder structures (Google Chrome only) • Delete, rename, copy, zip or unzip files • Compatible with all modern operating systems that provide a web browser (Windows, Mac OS, Linux etc.) • Password authentication (optional) • Shortcuts to photo, video and music directories • Runs as a background service • View photos directly in your web browser • Autostart service when connected to home network (optional) • Provides access to external SD cards and USB storage devices • Works while the device is in hotspot mode
Features of WiFi File Transfer Pro mod : • Free
Install Instructions :
* You visited this site on mobile ? 1. Download the Apk file on mobile. 2. Install and run it. 3. That’s it,Enjoy! * You visited this site on desktop or laptop ? 1. Download the Apk file on Pc. 2. Transfer Apk file from PC to your Android Phone (Via USB , Bluetooth , Wi-Fi). 3. Install and run it. 4. That’s it,Enjoy!


Originally Posted by JasonPC
Oh are you another hardcore red alert fan whiner geez.
There are glaring plot holes and issues with the storyline. But I still think it's a really well done game that's very fun. Not sure what's people's problems.
Im hot a hardcore fan but please a cannon that fires soldiers? you can fit like 5 units on the screencant see ****
no more harvesting..... and a ****load of other redicilous units and all kinds of bull****
Gameplay is basicly spam build whatever unit, point at greenthing on minimap, win.
Peoples problems are that its not C&C
they should have called it something else


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Solar energy is an increasingly popular method to reduce the standard household dependency on coal and other non-renewable sources of power. Advancements in solar technology are estimated to not only increase the amount of power that can be produced through solar energy but make affording the technology more accessible to homeowners. These breakthroughs make it an exciting time to invest in the solar energy markets and reap the returns some investors have known about for years. Here are just a few of the most recent technology changes that are taking the industry by storm.
Wider Light Spectrum
The sun produces a broad range of light types, many of which are not visible to the naked eye. Solar panel manufacturers are now rethinking light absorption and are designing panels that can access nonvisible wavelengths and convert them into usable energy. This will allow a single board to be smaller in design while enabling it to absorb the greatest amount of light possible. This technology is still in testing phases but promises to redefine the idea of renewable energy.
As energy is converted, it is typically stored in batteries to be used later. While this is effective, the transfer of the power from the solar panel to battery storage can lead to as much as 25% waste in the form of heat loss. New advancements in cold energy storage reduce the level of waste to as low as 3% without affecting the longevity of the storage devices. This increased efficiency cuts down on solar waste and ensures a home always has the power it needs.
Reduced Installation Fees
One of the most common barriers preventing a homeowner from installing solar panels is the cost. The cost of the panels is minimal when compared to the fees associated with standard installation. These new technology advancements now make it more affordable, as there is less labor required to fit a home with an adequate number of solar panels.
Investors around the world are diversifying their portfolios by choosing to invest in the renewable energy market. The experts at Oil and Energy Investors can be found online here and provide in-depth information on the upcoming trends and how they can help create astounding returns. Check out their blog and learn more about future clean energy investments.


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It's official; CEDIA 2016 is almost here. Our first clue was the news that Amazon would present the Friday morning keynote on September 16. And now CEDIA has announced its Best New Product Award finalists for 2016.
Each year, winning products are selected by a panel of home technology professional judges for their innovation and value to both the integrator's business and the end user.
Winners will be revealed at a press conference on Thursday, September 15 at 3:00 p.m. in the CEDIA booth (#4710). Winners will also be recognized that Thursday evening at the CEDIA Celebration, hosted at Gilley's Club in Dallas.
The CEDIA Celebration is open to all CEDIA 2016 attendees. It will recognize the award-winning work of CEDIA members and provide a venue for all attendees to enjoy a true Lone star experience with cocktails, BBQ, live music and a mechanical bull.
More details on each product can be found on CEDIA's website.
The 2016 Best New Product Award finalists are:
In this piece, “Amazon Echo at CES 2016 and Beyond: The Next Big Driver for Home Automation,” we noted that the biggest detractors of voice control are the folks who have never tried Echo.
Nano Backpack P5
The P5 was announced last year at CEDIA as the “world's smallest 5.1 system.” It included the emerging wireless WiSA standard for wireless surround, but the company decided not to include WiSA in the first shipping product. At Essential Install Live in England last month, the company says it will ship a WiSA surround product with companion wireless subwoofer later.
eSeries Mirage Audio System MAS-4-2e
Autonomic eSeries MMS-1e Music Streamer
The eSeries is Autonomic's new line of more affordable media streamers. The product has been shown at a handful of tradeshows over the past year but will make its formal debut at CEDIA 2016.
Control4 EA Series Controllers
Control4 set a new standard in home automation products by including high-resolutional audio and built-in Ethernet switches in its new EA line of controllers, starting at $600.
Best known in the commercial world, Dataset entered the residential business a couple years ago with the RS20i preamplifier/processor. Reviewer Bob Archer wrote back then, “Datasat has redefined home theater performance for me.”
The massive Hopper 3 takes satellite to new heights with 16 tuners, a split-screen sports bar model, super-fast processor, 2 TB hard drive and new amenities like the Hopper Voice Remote and HopperGo hard drive for taking shows on the road.
Domotz has sophisticated IP device discovery technology for its remote network monitoring solution. New services for integrators provide better access and insights into their customers' home systems. Domotz's recent acquisition of Fing adds further intelligence to the cloud-based platform.
CinemaOne Home Theater Audio Ensemble
According to the manufacturer, these powered speakers from an icon in home-theater design are the “most refined high SPL loudspeaker package available in the industry to day.” Principal Anthony Grimani told CE Pro back in 2014 that the self-contained design of the speaker/amp/DSP boosts stability and reliability.
ALLie Home 360×360-Degree Lifestyle Video Camera
Using dual cameras and sophisticated software for de-warping and stitching, IC Realtime packs complete 360-degree views into ALLie. Because processing takes place in the camera itself — and not the cloud — it enables real-time streaming. ALLie is the first 360-degree camera to live-stream to YouTube.
The iPort Surface holds an iPad and features IP-addressable hard buttons. Compatible with major home-control systems, the mount allows direct access to automation features, without having to wake up the tablet.
Sivoia QS Triathlon WIDR Shades
Lutron Lutron's GIANT battery-operated Sivoia QS WIDR maxes out at 12×12 square feet. The company says the product line features the smallest roll-up diameter for any roller shades of this size, with a maximum roll-up of 3 inches for a 144-square-inch shade. The new “Battery Boost” option gives users up to an 80% increase in battery life for a system that can last up to 6 years on batteries.
Lutron Connect Bridge and App
Lutron brought Web connectivity first to the consumer market via Caseta and the Smart Bridge. The new Connect Bridge and App now brings effortless connectivity to HomeWorks and RadioRa 2 for pros.
Middle Atlantic Products
DC Power Distribution
Middle Atlantic calls this solution “the only universal DC power solution in the AV industry that removes messy, space consuming, and unreliable wall warts and other power clutter.” Color-coded screw terminal connectors and polarity labeling, ensures reliability with multi-level protection on both AC input and DC outputs.
Nexus 21 Concealment Systems
CL-65 TV Flip-Down
“We started from scratch and have a built-in-the-USA unit that is faster and quieter than any other flip-down solution on the market,” says Cory Lovett, president, Nexus 21. “The cost of the CL-65 to dealers is about half of what is being paid for older technology, which opens up many more opportunities to spec the product.”
Pakedge by Control4
Pakedge NK-1 Controller (pdf)
The NK-1 suite from Pakedge includes the Wireless Controller and Network Patroller, simplifying device set-up, optimizing wireless networking and providing remote management via the company's cloud-based BakPak service.
RoseWater Energy Group
Residential Energy Management Hub
After a couple of years demonstrating its energy-storage solutions, RoseWater is finding traction among custom integrators. Boca Theater and Automation recently installed a system in its new showroom.
Savant Pro Remote
Home automation company Savant released its first new remote in a long time — the Savant Pro, featuring voice control and a streamlined design.
This motorized video projection screen, which appears to float in mid-air, won the Home Theater category for CE Pro's Top New Technology awards at ISE 2016.
When you must have an 84-inch 4K TV in the direct sunlight, Seura delivers.
SnapAV has been building out its ecosystem of OvrC-enabled remote monitoring and control systems, now compatible with the company's power-management, networking and surveillance lines. Stay tuned for more announcements at CEDIA Expo.
As we wrote about Sonos's second-gen Play: 5 last year, “New Sonos Trueplay Software is EQ for Dummies.”
XBR-75X940D 4K HDR Ultra HD TV
Here's what Sony product technology manager Phil Jones says about this 4K TV line: “There's better upscaling, less noise when you look at content that's film based. Not only can we detect what resolution you're looking at, we can detect what type of source you're looking at, and based on that we triage the patient differently. A 4K Blu-ray looks very different than 4K you shot on your cellphone; the TV knows that and uses different processing based on each one.”
VPL-VW5000ES 4K SXRD Home Cinema Projector
Integrator Dallas Dingle of Supercalibrations says this new laser projector provides the “best images we have ever seen.” And that was before he calibrated unit.
STR-ZA5000ES – 9.2 Channel 4K AV Receiver
This is the next flagship receiver in Sony's vaunted ES line, offering both Dolby Atmos and DTS:X, as well as full 4K/60p resolution and support for HDR and HDCP 2.2.
Wilson says its 4000R solution is the “industry's first rack-mounted signal booster,” for cell phones, with coverage up to 100,000 square feet.
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Surveon Launches New Generation HD Cameras with Advanced Image Functionality
Surveon, the complete megapixel solutions provider, today announced a new generation of HD cameras. Powered by the individual advanced ISP, the new HD cameras provide enhanced image functionality, including 3D Noise Reduction, Edge Enhancement, High Light Compensation, D-WDR, Defog, and Low Shutter Speed Control. The series comes with different models, from the standard box CAM2311, the vandal-proof dome CAM4361, to the IP66 bullet CAM3361. All of them follow Surveon’s high quality standards, with industrial-grade components, in-house production, and 3 year warranty.
“With the vast growth of megapixel projects in the market, the HD resolution has become the basic requirement,” said Casper Wu, product manager of Surveon. “Customers are looking for advanced functions to further improve image quality.” While 2D-Denoise is still commonly used in the industry, Surveon’s new HD cameras have adapted the advanced 3DNR technology. The Defog function can facilitate outdoor installations, and combined with High Light Compensation, makes the new cameras the ideal solutions for traffic monitoring and city surveillance. These advanced features, plus Edge Enhancement, D-WDR, and Low Shutter Speed Control, provide our partners competitive edges to handle megapixel projects.
Surveon’s new HD cameras support the ONVIF standards and are fully compatible with Surveon VMS and the 3rd party CMS, giving customers a broad range of solution selections for their projects. The new cameras can be used in combination with Surveon's industrial megapixel RAID NVR series to create highly integrated and reliable solutions that reduce the integration effort for project installers.
For more information, please visit www.surveon.com
- About Surveon Technology Inc.
Surveon Technology offers end-to-end network video surveillance solutions that showcase our expertise in professional camera design, hardware RAID NVR, high-availability video storage, embedded firmware and video management software. All Surveon products are designed in-house and manufactured on our ISO 9001 and ISO 14001 certified production site to ensure the highest quality for our partners. For more information about Surveon, please visit our website at www.surveon.com.
- Inquiry contact
Surveon Technology, Inc.


Minecraft Cartoon Texture Pack 145 votes, minecraft Cartoon Texture Pack.5.2 Preview How to Install Minecraft Cartoon Texture Pack.
Everything from the vegetation to the mobs is candy-coated.
Soartex Fanver is a texture pack for Minecraft.5.2.Related searches minecraft texture pack editor.8 at UpdateStar minecraft texture pack editor.8 search results, descriptions containing minecraft texture pack editor.8, additional titles containing minecraft texture pack editor.8.What is Faithful Texture Pack?Soartex Fanver Texture Pack 43 votes, what is Soartex Fanver Resource (Texture) Pack?Download, mCPatcher HD, download and install, editor Texture Pack.Next, Run the game normally, select Mods and Texture Packs, just, Open Texture packs folder.From this menu you can see the terrain surface such as a surface for your blog unique.PixelCinema Texture Pack 107 votes, about PixelCinema Texture Pack.5.2 This Texture Pack will let you to make Faithful Texture Pack 79 votes.About BoxCraft Texture Pack.5.2 This is BoxCraft!This pack might make your teeth ache just looking.Faithful Texture Pack for Minecraft.5.2 brings lightweight textures.Modern HD Texture Pack 116 votes, about Modern HD Texture Pack Modern HD Resource Pack.5.2 is a texture pack that every terrain texture.Atherys Ascended Texture Pack 20 votes, about Atherys Ascended Texture Pack Atherys Ascended Texture Pack is one of the most popular.The End Is Extremely Night Texture Pack 12 votes, the End Is Extremely Night Texture Pack.5.2 is a detailed mod!This tool also allows players to compare the two side texture pack or copy all the tiles from a texture pack to another.Minecraft / texturepacks folder texture pack is different from the ordinary.Semi-Realistic Texture Pack 62 votes, semi-Realistic Texture Pack.5.2 Preview How to Install Semi-Realistic Texture Pack for Minecraft.Flows HD Texture Pack 185 votes, flows HD Texture Pack.5.2 Preview See more pictures corel photo paint portable here Show Content » How to Install Flows.BoxCraft Texture Pack 36 votes.Instead of an array of different files, folders pack the meat into large square surfaces.
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More storage with a 2nd laptop hard drive Thanks to HDD Caddy it is now easy to add more storage space to your laptop or Macbook Pro! With HDD Caddy you can add a second internal hard disk drive (HDD) or solid state drive (SSD) to your laptop. No need to carry external USB hard drives or USB sticks anymore! It is easy to install. First insert your own HDD or SSD in the HDD Caddy and then replace your optical drive (DVD or BluRay drive) with the HDD Caddy. HDD Caddy is an ideal solution if you need more storage space or if you want to use a fast SSD with an extra HDD. Enjoy the flexibility of having more storage space.
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USB 2.0 External Sound Card Channel 7.1 3.5mm Adapter Microphone Headphone Audio InterfaceComputer & Laptop Accessories
USB 2.0 External Sound Card Channel 7.1 3.5mm Adapter Microphone Headphone Audio Interface0 out of 5(0)Key Features:Size: 57 x 25 x 12mmLED indicators: Microphone-Mute Status, ActivityUSB2.0 Full-Speed ( 12Mbps ) SpecificationUSB HID Class Specification 1.1USB Audio Device Class Specification 1.0. USB bus-powered, no external power required.This is USB 2.0 External 7.1-Channel Audio Sound Card Adapter. It can work with either desktop or laptop. it extends your stereo speaker or earphone to 7.1 channel environment, giving you high quality sound enjoyment.Connectors: USB Type A, Stereo output jack, mono microphone input jackFunctions keys: Microphone-Mute, Speaker-Mute, Volume-Up and Volume-DownPlug and Play. No drivers required for Windows 2000 / XP / Server 2003 / Vista, Linux, Mac OSCompact, portable, convenient to carrySKU: 059010
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How to Charge iPhone and iPad Batteries Faster
iPad Repair Jakarta - Charging iPads and iPhones can often be a tedious process, due to their long duration or the time it takes to fully charge 100%. But there are lots of tricks, unknown to many Apple fans, to increase the charging speed of phones and tablets. Here are some of them.
Simple Tricks to Charge Battery Faster
With the simple tips we'll give you below, you're sure to make your device load time much shorter and your phone or tablet available for use in less time than usual. This is a very simple trick to do and surprisingly as it looks, it will work. We will list four tricks to charge iPad and iPhone faster or more efficiently.
Choose the right charger
The technical specifications of the charger or power adapter have different charging speeds. Not all chargers are the same and some are much faster than others, because they have more power. But that's not the only thing that affects speed. There are three different types of chargers, one with a USB socket, an iPhone adapter, and an iPad adapter. Each of them has different characteristics, which make it more or less efficient:
- USB computer : 5 volts, 0.5 amps, 2.5 watts of power.
- iPhone charger: 5 volts, 1 amp, 5 watts of power.
- iPad Air charger: 5.1 volts, 2.1 amps, 10 watts of power.
As you can see, the numbers are not the same for everyone and while they may seem confusing at first, the numbers determine the speed of power transfer. So with a more powerful charger, charging the battery can be completed faster. And we say it can, because it also depends on other factors that can limit loading speed.
The charger is not a power adapter, the latter is in the device and is the adapter that regulates or manages charging. Even if you buy a charger with a higher power, it doesn't mean the charging speed is faster. But in the end charging the device via USB is the slowest way.
Remove the cover or case
Have you noticed how the device heats up while charging its battery? This may be due to the case or shield it was wearing at the time, causing the temperature to rise, or it could also be because you left apps open and draining power.
It is best to remove the case when charging this device from Apple, as heating the battery can reduce it and make charging slower or not charging satisfactorily.
If charging via USB, do so on a Mac
We've already mentioned that charging via a USB cable is the slowest way, but if you do it via a Mac with one of the high-power USB ports that some models have, it'll be quicker. On the one hand this is just a rumour, but it is true that some USB ports on Macs have different power ratings. You have to make sure that you have connected the device to the port that charges the battery, not all ports can do this, and keep the computer on for it to work properly.
We all know, that any technology will not last forever. In other words, various electronic objects can be damaged even if we take good care of them. And when your Apple product is damaged, you can take it to our service experts at Dr Gadget iPad repair Jakarta.
Dr. Gadget presents the best service in the world of repair or service of Apple products, be it iPhone, iPad or MacBook iMac. This Jakarta iPad repair place can repair your gadgets right in front of your eyes. Have repair experts who are very reliable and can diagnose damage to your gadget accurately.
Dr Gadget will also provide a warranty of up to 30 days to 90 days after the repair is carried out. No less interesting than they are very experts on IC and Motherboard problems, you also get a money back guarantee if your device can't be repaired. How, don't hesitate anymore, contact us now to get your favorite device you can use again. Or you can also go directly to the Dr Gadget service center closest to your location.
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SANTA CLARA, CA — DataDirect Networks (DDN) has announced the winners of the 2015 Pioneer User Awards. The awards recognize and celebrate visionary individuals, organizations and/or multiple people who are embracing leading-edge high performance computing technologies to shatter long-standing technical limits and to accelerate business results and scientific insights. The recipients of the DDN 2015 Pioneer Awards are Dr. Alf Wachsmann, CIO at Max Delbrück Center for Molecular Medicine, Steve Furmedge, Director of Security Services at Public Transport Authority, and the HudsonAlpha Institute for Biotechnology.
“Innovation is driven by brilliant minds combining ingenuity and technology to solve problems faster and more accurately than previously conceived possible,” said Molly Rector CMO, executive vice president product management and worldwide marketing, DDN. “DDN’s innovation in high performance storage and data management solutions is driven by the demands of the science and the business needs of the most data-intensive organizations on the globe. We are thrilled to recognize and celebrate the achievements of the 2015 DDN Pioneer Award recipients who are embracing advanced technologies and innovation to accelerate business results and vital scientific insights while pushing the boundaries of discovery.”
Dr. Alf Wachsmann, CIO, Max Delbrück Center for Molecular Medicine
As the CIO of Germany-based Max Delbrück Center for Molecular Medicine (MDC), which investigates basic biological concepts to understand disease mechanisms and to close the gap between basic biomedical and clinical research, Dr. Alf Wachsmann and his team were the first to test a SAP HANA cluster. Based on the requirements of life sciences researchers at the center, he and his team used their experience in integrating existing decentralized computing resources to form a federated in-memory database system. This approach combined advantages of cloud computing, such as efficient use of hardware resources and provisioning of managed software, with the security of storing and processing sensitive data on local hardware only.
Dr. Wachsmann’s experience includes systems design and management at the German Electron Synchrotron Lab (DESY) Stanford Linear Accelerator Center (SLAC; now SLAC National Accelerator Lab), and the Okinawa Institute of Science and Technology Graduate University (OIST). He has used DDN storage systems in the United States, Japan and Germany.
Steve Furmedge, Director of Security Services at the Public Transport Authority
A 30-year law enforcement professional and recognized expert on counter terrorism and security strategies for mass and public transit, Steve Furmedge leads security for the Public Transport Authority (PTA), which is the government agency that oversees Western Australia’s public transit infrastructure. Chartered with serving more than two million people in the Perth metropolitan area, as well as more than 240 towns across the state, the PTA connects people and places safely and securely.
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The HudsonAlpha Institute for Biotechnology
Genomics is the language of life and HudsonAlpha scientists decipher its code. Propelled by game-changing technology and a drive for innovation, the expertise of HudsonAlpha researchers impacts the quality of human, plant and animal life around the world. HudsonAlpha is helping to save lives by accelerating genomic data analysis in order to solve some of the most pressing challenges in cancer, childhood genetic disorders, neuropsychiatric disorders and immune-mediated disease. To meet these challenges, HudsonAlpha leverages a unified architecture to meet its end-to-end data lifecycle needs, including the management of 4 PB of annually-generated data from its Illumina XTEN sequencer and downstream analysis using the Edico Genome DRAGEN card.
Pioneers Jim Hudson and Lonnie McMillian developed the concept for HudsonAlpha in the early 2000s to develop, maintain and apply cutting-edge genomic technology across a wide spectrum of biology and biomedical research. Other innovators include Dr. Richard Myers who leads the institute, Dr. Shawn Levy who pioneered cutting-edge genomics processing, and Kevin Behn, the lead storage architect who continues to innovate new approaches for its expanding data requirements. In addition, Dr. Howard Jacob recently joined HudsonAlpha to pioneer the integration of genomic research into clinical settings.
The Pioneer Award winners were selected by a DDN panel of judges consisting of a Chief Scientist, Customer Advocate, HPC Market Expert and Commercial Market Expert. These awards recognize the use of DDN storage and data management innovation in high performance computing and big data environments.
The Pioneer awards acknowledge thought leaders across the globe who strive to accelerate discovery, insights and results within data-intensive HPC and enterprise big data markets by embracing leading-edge technology and innovation. Recognized annually, Pioneer award nominations will open August 1, 2016, for the 2016 Pioneer awards, and winners will be announced next November at the 2016 International Conference for High Performance Computing, Networking, Storage and Analysis (SC16).
- Click here for more information on the awards.
DataDirect Networks (DDN) is a big data storage supplier to data-intensive, global organizations. For more than 15 years, DDN has designed, developed, deployed and optimized systems, software and solutions that enable enterprises, service providers, universities and government agencies to generate more value and to accelerate time to insight from their data and information, on premise and in the cloud. Organizations leverage the power of DDN technology and the deep technical expertise of its team to capture, store, process, analyze, collaborate and distribute data, information and content at largest scale in the most efficient, reliable and cost effective manner.


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ORIGINAL RESEARCH article
Spelling is just a click away – a user-centered brain–computer interface including auto-calibration and predictive text entry
- Department for Psychology I, Institute for Psychology, University of Würzburg, Würzburg, Germany
Brain–computer interfaces (BCI) based on event-related potentials (ERP) allow for selection of characters from a visually presented character-matrix and thus provide a communication channel for users with neurodegenerative disease. Although they have been topic of research for more than 20 years and were multiply proven to be a reliable communication method, BCIs are almost exclusively used in experimental settings, handled by qualified experts. This study investigates if ERP–BCIs can be handled independently by laymen without expert support, which is inevitable for establishing BCIs in end-user’s daily life situations. Furthermore we compared the classic character-by-character text entry against a predictive text entry (PTE) that directly incorporates predictive text into the character-matrix. N = 19 BCI novices handled a user-centered ERP–BCI application on their own without expert support. The software individually adjusted classifier weights and control parameters in the background, invisible to the user (auto-calibration). All participants were able to operate the software on their own and to twice correctly spell a sentence with the auto-calibrated classifier (once with PTE, once without). Our PTE increased spelling speed and, importantly, did not reduce accuracy. In sum, this study demonstrates feasibility of auto-calibrating ERP–BCI use, independently by laymen and the strong benefit of integrating predictive text directly into the character-matrix.
Event-related potentials (ERP) are brain signals in the human electroencephalogram (EEG) that occur in response to stimuli, e.g., visual stimuli (for review, see Polich, 2007). Farwell and Donchin (1988) suggested to utilize these potentials for brain–computer interface (BCI) based communication, particularly dedicated to patients with impaired motor control due to neurodegenerative disease (e.g., patients suffering from amyotrophic lateral sclerosis, ALS). Such ERP–BCI is often referred to as P300-BCI due to its usual dependence on the P300, a prominent positive ERP approximately 200–400 ms post-stimulus (Picton, 1992; Polich et al., 1997). It is elicited in an oddball-paradigm, in which participants focus their attention on a rare stimulus (the odd stimulus) among many frequent but irrelevant stimuli. In the visual ERP–BCI this oddball is typically realized by presenting letters and numbers of the alphabet on a computer screen and flashing these characters randomly. Users are then asked to focus their attention on flashings of the character they intend to spell while ignoring all other characters (e.g., counting the target flashes). After a certain number of character flashings, a classification algorithm detects ERPs in the recorded signal and thereof determines the intended character. Hence, healthy as well as severely impaired users can communicate words on a character-by-character basis (e.g., Nijboer et al., 2008).
Today, visual ERP–BCIs are most commonly used systems for BCI-based communication (for a review, see Kleih et al., 2011). It has been shown that they are reliably accurate (in healthy participants, e.g., Guger et al., 2009; Kleih et al., 2010; in patients, e.g., Sellers et al., 2006, 2010; Townsend et al., 2010) and robust for long-term use (Nijboer et al., 2008; Sellers et al., 2010). However, when considering daily use of a visual ERP–BCI system at current status of technology, some main barriers in terms of practicability and usability can be identified:
First, preparation effort for EEG acquisition with commonly used wet electrodes and herewith originating inconvenience (e.g., electrode gel, washing hair) were reported as being highly discomforting for patients using BCIs (Zickler et al., 2011). This issue is currently addressed by several manufacturers, e.g., by investigating dry electrodes. First prototypes have been tested for use in BCI (e.g., Grozea et al., 2011; Zander et al., 2011, for a review see Mak et al., 2011).
Second, since its first description in 1988, numerous modifications to the ERP–BCI have been well studied and led to many improvements e.g., in signal processing and classification (e.g., Krusienski et al., 2006, 2008; Blankertz et al., 2011, for reviews see Lotte et al., 2007; Kleih et al., 2011) and on the stimulus presentation side (e.g., Sellers et al., 2006; Guger et al., 2009; Salvaris and Sepulveda, 2009; Takano et al., 2009; Jin et al., 2010b; Townsend et al., 2010; Frye et al., 2011; Kaufmann et al., 2011; McFarland et al., 2011). Many of these modifications have been incorporated into today’s BCI software systems and led to implementation of a plethora of parameters that allow for individual adjustment. However, being comprehensive and flexible for research purpose inevitably entails complexity and effort in user handling. Therefore, this constitutes a major problem when bringing BCI technology toward end-users (Zickler et al., 2009), as they and their care-givers may not be educated in handling of complex software as well as analysis and interpretation of acquired EEG data for calibrating the BCI system.
Third, communication speed and accuracy are low compared to existing solutions from the field of assistive technology (AT; Zickler et al., 2011). In parts this issue may be improved with further investigation of new signal processing methods and/or modifications of the paradigm. For example Kaufmann et al. (2011) recently investigated new stimuli, i.e., flashing characters with famous faces, which clearly outperformed classic character flashing in terms of communication speed and accuracy. Consequently, choice of appropriate stimuli may enhance bit rate. However, independent of all possible improvements, the commonly used ERP–BCI paradigm is necessarily limited to spelling on a character-by-character basis. Therefore, another attempt to foster bit rate is to integrate a predictive text entry (PTE) system into the BCI paradigm (Wolpaw et al., 2002). Besides the classic character-by-character text entry, Ryan et al. (2011) presented users with a separate window of numbered text suggestions, determined by a predictive text system. Users were provided with the possibility to select these numbered text predictions by focusing on their associated number in the matrix. For example, after spelling an “y,” a first suggestion “your” would appear with number “1” among other suggestions in the separate window and by focusing on “1” in the character-matrix, users would in fact spell “your.” We therefore further refer to this paradigm as “indirect paradigm.” The authors reported that integration of such PTE system into the BCI effectively decreased the time needed to spell a sentence. A likewise indirect approach was proposed by Jin et al. (2010a) who adapted a Chinese cell-phone input system for BCI use to enable communication for languages that comprise too many characters for classic character-by-character text entry (e.g., Chinese, Japanese). In their system, seven word suggestions were presented that could be chosen indirectly by focusing on the numbers 1–7 in the matrix. Unfortunately, Ryan et al. (2011) reported that overall spelling accuracy was significantly decreased when using such indirect PTE paradigms, which was explained with higher workload and task demands (dual task interference). However, it remains unclear if this negative side effect is generalizable for all paradigms using predictive text system or if the higher workload is evoked by the indirect paradigm used in this study, i.e., selecting predictive text by focusing on its related number in the main matrix.
We addressed the latter two barriers by developing and evaluating a software solution, further referred to as optimized communication interface (OCI). It was specifically designed for use by laymen and thus reduces handling of the whole BCI application to a minimum of several button presses, thereby automatically controlling all other necessary steps in the background. Its core feature lies in an auto-calibration of the classifier that – with one button press – individually adjusts classifier weights to the user’s brain signals. The system assesses quality of the signal recorded during a calibration session and decides if further calibration data is needed. Furthermore a PTE system was integrated as optional choice. Instead of numbering text suggestions and requiring the user to indirectly focus on the appropriate numbers (Ryan et al., 2011), we integrated predictive text directly into the matrix. This could decrease workload and task demand as users directly focus on the suggested word and its selection would be similar to selections of any other character in the matrix.
The herein presented study evaluated use of OCI by investigating (1) if auto-calibrating BCI systems can be used independently by laymen and (2) if predictive text incorporated into the speller matrix may better serve the goal of fast but highly accurate BCI-based communication than the classic character-by-character selection.
Materials and Methods
Optimized Communication Interface (OCI) Software
Implementation of OCI was based on the core modules of BCI2000 (Schalk et al., 2004, Version 3, http://bci2000.org) and compiled with Microsoft Visual Studio 2008 compiler. It can be grouped into three work stages: (1) modification of the graphical user interface, (2) implementation of an auto-calibration and (3) implementation of a stimulus presentation paradigm including a PTE system.
Graphical user interface
BCI2000’s graphical user interface was modified using Qt Designer 4.7. Handling of the whole BCI application was reduced to one button and an optional check mark for switching on the PTE system (see Figure 1). When starting OCI, the button acts as a start button for the calibration session. With one button press, all parameters are automatically set in the background and the classic character-matrix appears. After a predefined calibration word was spelled, the matrix disappears and auto-calibration is performed in the background without user intervention. In case of successful calibration, the button automatically turns into a start button for the online, free-spelling mode. Otherwise it would act as a start button for recalibration of the system.
Figure 1. Graphical user interface of OCI. The application is controlled with one button only. When starting OCI, the button displays “Kalibrieren” (German for “calibrate”). During the calibration phase it acts as a stop button, whereas after successful calibration it turns into a start button for the online mode. Optionally, a predictive text entry system is switched on by selecting the “Bibliothek” check mark (German for “library”).
Auto-calibration was performed by automatically transferring the acquired data to MATLAB (The Mathworks, USA; version 2010b) using the MATLAB Component Runtime 4.14 to bridge between C++ and MATLAB code. A stepwise linear discriminant analysis (intervals of 800 ms post-stimulus, no spatial filtering) was performed based on data from all 12 EEG electrodes and thereof classifier weights were computed for the online sessions. Also, the number of sequences (NoS; a sequence consists of all rows and columns flashed once) used for flashing the characters in the online sessions was computed. Accuracy and stability of offline classification determined the outcome of the calibration session: (1) If accuracy was below 75% with 15 sequences, calibration session had to be performed again. (2) NoS used for online sessions was adjusted based on the stability of the classifier output, i.e., maximum accuracy remained stable after a given amount of data segments. In this case, NoS was defined as the minimum number of sequences to reach a stable offline accuracy maximum plus two sequences. E.g., if stable 100% accuracy were reached offline with seven sequences, NoS would have been nine during online sessions. (3) If no plateau was reached but classification accuracy was above 75%, NoS was set to 15. (4) The minimum NoS was restricted to eight to prevent from high error rates in long spelling sessions.
Note that auto-calibration was performed invisible to the user and all parameters for the online sessions were automatically adjusted without expert or user intervention.
Predictive text and stimulus presentation paradigm
First, we wrote an application that screened several prominent German internet pages (e.g., news pages) for words and counted their amount of occurrence. The word list was then sorted with decreasing occurrence and manually checked for non-sense words or words with internet specific content, e.g., name of the webpage holder. The final list comprised 82.616 words. This number includes various grammatical variations of the same word, e.g., plural forms.
Suggestion of predictive text and stimulus presentation matrix was implemented in Python 2.5 and connected to BCI2000 via user datagram protocol. After each letter selection, the application screened the list downwards to update the six most likely words that were than presented in the first column of the speller matrix. If less than six words matched the previously entered letters, fewer up to none text suggestions were presented. At the beginning of new words, i.e., after selection of space, word deletion or after selection of a predictive word, the six most frequent words were presented (first six words of the list).
For the control condition, i.e., a matrix without PTE, an identical Python based stimulus presentation paradigm was used. Only it did not contain the PTE. Figure 2 provides examples of both stimulus presentation matrices. All matrices were of size 6 × 6 and displayed on a computer screen approximately 70 cm distant from the participant (size: 22′′; refresh rate: 60 Hz; resolution: 1680 × 1050; size of matrix: 40 × 25 cm2).
Figure 2. Two paradigms were tested. (A) The classic character matrix consisting of single characters. Furthermore the matrix contains functions for deletion (delete character), space, and escape (finish writing). (B) Our new predictive text entry paradigm with predictive text included into the first column of the matrix to allow for direct selection of words. Also, the matrix contains functions for deletion (delete character, delete word), space, and escape.
As predictive text was directly integrated into the matrix it could be flashed in a similar manner than usually done in ERP-BCIs, i.e., in both conditions (PTE and character-by-character entry) the full 6 × 6 matrix was flashed row/column wise. Thus, selection of predictive text was also performed by counting each highlighting of the intended word to spell. The BCI system always chose the cell in the matrix with highest probability, which could be a selection of predictive text, single characters or commands (delete, space, escape) depending on the content of the chosen matrix cell (see Figure 2).
Electrodes were mounted by the experimenter. Thereafter, all participants handled the software fully on their own without expert support. Handling of OCI was explained in a condensed user manual (paper hardcopy) and with two short videos.
First, participants were required to start OCI and to start a calibration session where they had to spell the word “BRAINPOWER.” Each character was highlighted 30 times per letter to spell [NoS = 15; stimulus duration of 31.25 ms; inter-stimulus interval (ISI) of 125 ms]. This resulted in a final data set of 30 × 10 target and 150 × 10 non-target stimuli. From this data set, classifier weights were automatically computed in the background, invisible to the user.
Thereafter, participants twice spelled a German sentence comprising of 45 characters (nine words) using the automatically adjusted classifier weights and automatically determined NoS. Errors had to be corrected immediately such that the finalized sentence was 100% accurate. Then, spelling had to be terminated by selecting twice the “escape” function from the matrix, which brought them back to the main application window (necessary double selection constituted a safety mechanism of the “escape” function, to prevent unintended program termination due to selection error, i.e., selecting “escape” only once had no consequence). The inter-trial interval was 5 s to provide participants with enough time to perceive feedback on the spelled character/word and to screen all predictive text suggestions before the next stimulus sequence began. The same sentence was spelled once with PTE and once without, but both times with equal classifier weights and equal NoS to ensure comparability (within-subject design; calibration had to be performed only once). The order was randomized across participants.
After finalization of the spelling sessions, participants were asked to fill out questionnaires on handling of OCI and the PTE.
N = 20 healthy university students with normal or corrected to normal vision participated in the study. All participants were native German speakers and BCI novices. Due to equipment failure, data acquisition for N = 1 participant was aborted. The final sample comprised N = 19 participants (10 male, mean age 23.9 years, SD = 3.7, range 20–35). The experiment was conducted in accordance with standard ethical guidelines as defined by the Declaration of Helsinki (World Medical Association) and the European Council’s Convention for the Protection of Human Rights and Dignity of the Human Being with regard to the Application of Biology and Medicine (Convention on Human Rights and Biomedicine). All participants gave signed informed consent prior to the experiment and received 8 € per hour for taking part in the study.
Electroencephalogram was acquired from 12 passive Ag/AgCl electrodes that were placed according to the guidelines of the American Electroencephalographic Society at positions Fz, FC1, FC2, C3, Cz, C4, P3, Pz, P4, O1, Oz, and O2. Furthermore an electrooculogram (EOG) was obtained from two horizontal (hEOG) and two vertical (vEOG) sintered Ag/AgCl electrodes. Both, EEG and EOG were recorded at a sampling rate of 256 Hz and amplified with a 16-channel g.USBamp amplifier (g.tec Medical Engineering GmbH, Austria).
The study aimed at investigating two independent aspects, i.e., feasibility of auto-calibrated BCI use and benefit of a new PTE paradigm.
Besides computation of bit rate (as described e.g., in Wolpaw et al., 2000; Wolpaw et al., 2002; Serby et al., 2005) we computed a bit rate measure incorporating the information transferred with selections of whole words. PTE systems enhance bit rate in that with one selection many characters are communicated at once. Thus true bit rate is not only depending on the number of accurate selections made but also on the information transferred with each selection. Certainly such measure heavily depends on the length of the selected words. For example true bit rate would be five times higher when selecting a 10-character word instead of a two-character word, although bit rate in terms of selections/minute would be identical. Therefore true bit rate has to be interpreted with caution and is only provided to display the potential of PTE systems.
For offline analysis of ERPs, EEG data were filtered with 0.1 Hz high and 30 Hz low pass and corrected for ocular artifacts (Gratton et al., 1983). To avoid influence of overlapping ERPs due to the short ISI used in this study (ISI = 125 ms), only target stimuli with a minimum time distance of 469 ms (i.e., at least two non-target stimuli in between) were taken into account for ERP analysis. For statistical comparison, P300 peak amplitudes were obtained as maximum potentials between 200 and 300 ms at electrode Cz for both conditions.
Apart from ocular artifact correction with Brain Vision Analyser (Brain Products GmbH, Germany), all data analysis was performed using Matlab (The Mathworks, USA; version 2010b), and SPSS statistics (IBM, USA). Statistical comparison was performed using analysis of variance (ANOVA), except for not normally distributed data for which Wilcoxon-Test was used.
All participants were able to handle OCI on their own without expert support and to twice spell the predefined sentence correctly using the auto-calibrated classifier. In a forced-choice questionnaire all participants reported, that handling of the software was straightforward (average score: 3.84, with 1 = “not at all,” 2 = “not really,” 3 = “mostly,” 4 = “completely”), that they would be able to manage the BCI application on their own in the future (3.84) and to explain it to others (3.74).
For all participants, classifier weights were adjusted automatically after one calibration session and no repetitions were needed. In the consecutively scheduled online spelling sessions participants achieved overall good performance levels with regards to the length of the spelled sentence (average performance with classic character-by-character paradigm: 91.2%, SD = 7.8, range: 76–100% accuracy).
As auto-calibration may lead to classification of ocular artifacts, classifier accuracy of the auto-calibration as well as achieved stable NoS (see Auto-Calibration) were compared to accuracy and NoS after ocular artifact detection. No significant difference was found for the automatically selected NoS [F(1, 18) = 0.156, p = .697, η2partial = 0.009]. Also, offline classification accuracy did not differ before and after correction [With minimal NoS possible (NoS = 1): F(1, 18) = 0.518, p = .481, η2partial=0.028; with minimal NoS used online (NoS = 8): Z = −1.0, p = .317]. Furthermore, we checked how many NoS were necessary to achieve a stable classifier accuracy of 100%. Difference was not significant before and after ocular artifact correction [F(1, 18) = 0.010, p = .920, η2partial = 0.001].
Predictive Text Entry
Figure 3 summarizes the overall time needed to finish each sentence correctly. In line with Ryan et al. (2011), PTE significantly decreased spelling time [F(1, 18) = 95.74, p < .001, η2partial = 0.84]. Average time needed to finish the task was reduced by factor 1.8 (12.4 min as compared to 22.3 min without PTE).
Figure 3. Overall time needed to copy spell the sentence (including error correction and escape of spelling mode after finalization of 100% accurate sentence): within-subject comparison between classic character-by-character text entry and predictive text entry paradigm.
However, in contrast to the indirect paradigm by Ryan et al. (2011), accuracy did not decrease with our PTE paradigm [F(1, 18) = 1.64, p = .216, η2partial = 0.084]. Performance ranged from 100% accuracy to 76% (classic character-by-character condition) and to 74% respectively (PTE condition), see Figure 4. Bit rate (in terms of selections per minute) was comparably high for both conditions (character-by-character: M = 15.1 characters/min, SD = 5.6; PTE: M = 15.7 characters/min, SD = 5.7). Figure 5 displays bit rate as well as true bit rate. True bit rate was higher for all participants, when using the PTE paradigm. For those participants that made many errors with this paradigm (P08, P17) benefit in terms of true bit rate was small. On the other hand, participants with high accuracy also show a high benefit. Average true bit rate for the sentence was M = 12.0 characters/min (SD = 2.7) with character-by-character text entry and M = 20.6 characters/min (SD = 5.3) with PTE. Please note that true bit rate heavily depends on the length of the selected words (see Analysis) and thus needs to be interpreted with caution. In this experiment, word length of the selected words was M = 4.1 characters on average (SD = 1.9; range: 2–8 characters).
Figure 4. Average number of errors per selected item: within-subject comparison between classic character-by-character text entry and predictive text entry paradigm. As the number of items selected to finish the sentence varied between participants and conditions (e.g., due to error correction or selection of predictive text) no absolute amount of errors is presented but instead the amount of errors per selected item.
Figure 5. Bit rate (in terms of selections per time unit) and true bit rate (in terms of communicated characters per time unit): within-subject comparison between classic character-by-character text entry and predictive text entry paradigm.
Figure 6 displays the grand average ERPs for both conditions with most prominent P300 amplitude at electrode Cz around 246.5 ms (SD = 23.2; character-by-character text entry) and 250.0 ms (SD = 24.3; PTE). Grand average P300 amplitude was 3.55 μV (SD = 1.19) for character-by-character text entry and 3.44 μV (SD = 1.40) for PTE. No within-subject difference was found for P300 amplitudes between the conditions [F(1, 18) = 0.72, p = .410, η2partial = 0.038].
Figure 6. Grand average event-related potentials: within-subject comparison between classic character-by-character text entry and predictive text entry paradigm.
We further compared the amount of errors made when selecting a character against the amount of errors made when selecting a word or command. When using the classic character-by-character text entry, participants made M = 2.2 errors (SD = 2.2) on average for selecting a single character and M = 4.2 errors (SD = 4.8) for selecting a command. Error rates in the PTE condition were slightly lower (single character selection: M = 1.3, SD = 1.6; selection of command or word: M = 1.6, SD = 2.5). To write the sentence without any error, 10 commands (8× space, 2× escape) and 37 characters were necessary in the character-by-character text entry condition, whereas 11 commands and words and 16 characters were necessary in the PTE condition.
Evaluation of questionnaires revealed that all participants would prefer to use the PTE paradigm instead of character-by-character spelling, when exposed to BCI-based spelling in the future. Only one participant (participant 9) reported higher effort in selecting complete words as compared to single characters, which however was not reflected in his performance.
This study provides evidence, that current BCI technology can be automatized and operated by BCI novices through a user-centered, easy-to-use graphical user interface. This is inevitable when bringing BCIs out of the laboratory environment to end-user’s homes. Zickler et al. (2009) assessed user needs and requirements from N = 77 AT users and reported “functionality,” “possibility of independent use,” and “easiness of use” as most important requirements. The latter was one of the main reasons for dissatisfaction with current AT solutions. Importantly, our results from handling of OCI indicate high satisfaction with both, “easiness of use” and “possibility of independent use.” Furthermore, “functionality” was high as none of the auto-calibration sessions had to be performed twice and all participants were able to correctly spell the sentences. Overall spelling accuracy was high and none of the participants performed with lower than 70% accuracy – an accuracy level previously described as minimum level for communication (Kübler et al., 2001).
When considering adoption of a new AT solution, “functionality/effectiveness” was identified as the major critical factor for potential end-users (Zickler et al., 2009). This study suggested integration of predictive text directly into the matrix and proofed high benefit in terms of spelling speed (effectiveness) without loss of accuracy (functionality). As can be particularly seen from the true bit rate of participants with lower accuracy in the PTE paradigm, a high performance level is inevitable to clearly benefit from a PTE system. The unaffected P300 amplitudes in our study show that when integrating predictive text directly into the matrix workload may remain low, as predictive text is selected in a similar manner than single characters. The drop in performance reported by Ryan et al. (2011) may thus indeed be attributed to higher workload and dual task interference in the indirect PTE paradigm. The remaining performance level in our study, as well as the heavily decreased time needed to spell a sentence may well explain why none of the participants reported to prefer the character-by-character over the PTE paradigm. Advantageously, daily life application with such PTE system could easily be equipped with algorithms for grammar recognition and learning of new words.
Limitations and Future Experimentation
To reduce the amount of errors during spelling of long sentences, we restricted the automatically adjusted NoS to a minimum of eight sequences. This limit was set on basis of previous experience. Apparently, there is a trade-off, as low NoS increases the probability of errors due to a low number of trials to average, whereas high NoS may entail errors due to increased duration of spelling time. We speculate that for some participants NoS could be further reduced. This could also be realized with recently introduced dynamic stopping methods. (e.g., Lenhardt et al., 2008; Höhne et al., 2010; Liu et al., 2010; Schreuder et al., 2011b; for comparison of methods see Schreuder et al., 2011a). Instead of flashing characters with a fixed NoS, dynamic stopping algorithms adjust the NoS in every trial, i.e., stimulus presentation stops as soon as probability of correct target classification reaches a certain level.
This study aimed at investigating if spelling at high accuracy level is possible using an auto-calibrated classifier. Comparison to manually calibrated classifier performance needs separate investigation. Manual calibration may still be valuable for some cases (e.g., for exclusion of bad channels or detection of equipment failure). Auto-calibration may also be further equipped with mechanisms for detecting such cases. Our results are promising in that high accuracy could be achieved in all participants using auto-calibration and none of the participants needed recalibration of the system.
We assume that our validation results from healthy users may well transfer to end-users as we cautiously addressed their major concerns (Zickler et al., 2009). However, Zickler et al. (2010) found differences between end-users and care-givers with regards to their expectations of new AT solutions – differences which may certainly also exist in our healthy sample. Thus, it is inevitable to develop and validate new BCI technology in close discussion with them. Future experimentation therefore needs to validate our results in an end-user sample.
In sum, this study specifically addressed critical aspects of ERP–BCI-based communication reported by end-users, i.e., “functionality/effectiveness,” “easiness of use,” and “possibility of independent use.” Our results proofed feasibility of expert independent BCI-based communication using auto-calibration and underlined the strong benefit of predictive text directly integrated into the spelling matrix.
Conflict of Interest Statement
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
We thank Ruben Real for his support. This work is supported by the European ICT Programme Project FP7-224631. This paper only reflects the authors’ views and funding agencies are not liable for any use that may be made of the information contained herein. Open access publication was funded by the German Research Foundation (DFG) and the University of Würzburg in the funding programme Open Access Publishing.”
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Keywords: brain–computer interface, user-centered, auto-calibration, predictive text entry, event-related potentials, assisitve technology, P300-Speller, ERP-BCI
Citation: Kaufmann T, Völker S, Gunesch L and Kübler A (2012) Spelling is Just a Click Away – A User-Centered Brain–Computer Interface Including Auto-Calibration and Predictive Text Entry. Front. Neurosci. 6:72. doi: 10.3389/fnins.2012.00072
Received: 14 February 2012; Accepted: 30 April 2012;
Published online: 23 May 2012.
Edited by:Emanuel Donchin, University of South Florida, USA
Copyright: © 2012 Kaufmann, Völker, Gunesch and Kübler. This is an open-access article distributed under the terms of the Creative Commons Attribution Non Commercial License, which permits non-commercial use, distribution, and reproduction in other forums, provided the original authors and source are credited.
*Correspondence: Tobias Kaufmann, Department for Psychology I, University of Würzburg, Marcusstr. 9-11, 97070 Würzburg, Germany. e-mail: firstname.lastname@example.org


SAN JOSE, Calif. A group of eleven companies and two U.S. national laboratories is forming a consortium to define a standard Linux implementation of the Infiniband interconnect.
The Open Infiniband Alliance expects its first-generation set of standard Infiniband software drivers will be available later this year will be used primarily in high-end technical computing applications. A follow-on in about 18 months is targeted at large commercial database clusters.
"This is one of the most significant things to happen with Infiniband since its inception," said Jim Pappas, director of initiatives market for Intel Corp.'s server group, and a member of OpenIB. "We are going to choose not to differentiate products with proprietary software stacks but have a common open software approach," he added.
The group includes major computer and storage makers Dell, Engenio Inc. (formerly LSI Logic's RAID systems group), IBM, Network Appliance and Sun Microsystems as well as Infiniband chip and systems makers Infinicon, Mellanox, Topspin and Voltaire. Lawrence Livermore and Sandia National Labs, big users of Infiniband clusters, are also participating.
OpenIB will complement the work of the Infiniband Trade Association that oversees the development of the core Infiniband spec but is forbidden by its charter from developing Infiniband software or application programming interfaces. OpenIB will announce its schedule for delivering the software before October, Pappas said.


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Crysis 1 multiplayer is working on Openspy.net master server emulator and has been working for some time now. The original game directed players to the Gamespy master server which is no longer working. So to fix this, you will need to direct your connection for multiplayer to the openspy.net master emulator. How can this be done? Simple. (1) You will need to down load the zip file Crynetwork.dll from this site: (2) You will need to open the game and find the path or location of the original crynetwork.dll. Mine is located here: D:\Program Files (x86)\Electronic Arts\Crytek\Crysis\Bin32. (3) Find the Crynetwork.dll and replace it with the one that you just downloaded from Moddb.com. This will redirect your game from the old Gamespy server to the new Openspy master server. (4) So now you can launch the game, create an openspy game account just like back in day when Gamespy was working. On DvD version it works.
Only registered members can share their thoughts. So come on! Join the community today (totally free - or sign in with your social account on the right) and join in the conversation.
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