Popcorn Hour
The Popcorn Hour A-110 Media Think Tank is an enhanced version of the popular A-100 model. It adds support for 2.5"/3.5" SATA HDD and USB Slave functionality to improve connectivity and transfer rates. HDMI has been updated to the 1.3a spec, allowing full support of HD Audio pass-through for DTS HD-HR, DTS HD-MA, Dolby Digital Plus and Dolby TrueHD. The ports on the device have also been reconfigured, with a USB port moved to the rear panel, optical S/PDIF replacing the co-axial S/PDIF and a hardware reset button to allow for easier use of the device.
Popcorn Hour A-110 allows you to pull in digital video, audio and photos from various sources for your enjoyment on your HDTV or Home Theater setup. You can stream or playback your digital media content from a variety of sources, such as your PC, NAS, digital camera, USB mass storage devices (Flash drive, HDD, DVD drive), internal SATA HDD and even directly from the Internet via the Media Service Portal. It also serves as a NAS and a BitTorrent peer-to-peer downloader to eliminate the need to switch on a PC or other device for this purpose.
The Popcorn Hour A-110 supports the latest high bitrate video formats (MPEG2 MP@HL, H.264 HP@L4.1, VC-1 AP@L3 in TS of at least 40Mbps) to give you up to 1080p high-definition videos. In recognition of advances in Internet TV, the A-110 supports peer-to-peer Internet TV streaming technology from SayaTV, as well as popular unicast internet TV such as YouTube, Revision 3 and Vuze via the Media Service Portal. The A-110 firmware is upgradeable to support future media containers, codecs and features.
One randomly drawn winner will receive today's prize.
Realizing the promise of Apache® Hadoop® requires the effective deployment of compute, memory, storage and networking to achieve optimal results. With its flexibility and multitude of options, it is easy to over or under provision the server infrastructure, resulting in poor performance and high TCO. Join us for an in depth, technical discussion with industry experts from leading Hadoop and server companies who will provide insights into the key considerations for designing and deploying an optimal Hadoop cluster.
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Built-in forensics, incident response, and security with Red Hat Enterprise Linux 6
Every security policy provides guidance and requirements for ensuring adequate protection of information and data, as well as high-level technical and administrative security requirements for a system in a given environment. Traditionally, providing security for a system focuses on the confidentiality of the information on it. However, protecting the data integrity and system and data availability is just as important. For example, when processing United States intelligence information, there are three attributes that require protection: confidentiality, integrity, and availability.
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Enter to Win an Adafruit Pi Cobbler Breakout Kit for Raspberry Pi

It's Raspberry Pi month at Linux Journal. Each week in May, Adafruit will be giving away a Pi-related prize to a lucky, randomly drawn LJ reader. Winners will be announced weekly.
Fill out the fields below to enter to win this week's prize-- a Pi Cobbler Breakout Kit for Raspberry Pi.
Congratulations to our winners so far:
- 5-8-13, Pi Starter Pack: Jack Davis
- 5-15-13, Pi Model B 512MB RAM: Patrick Dunn
- 5-21-13, Prototyping Pi Plate Kit: Philip Kirby
- Next winner announced on 5-27-13!
Free Webinar: Hadoop
How to Build an Optimal Hadoop Cluster to Store and Maintain Unlimited Amounts of Data Using Microservers
Realizing the promise of Apache® Hadoop® requires the effective deployment of compute, memory, storage and networking to achieve optimal results. With its flexibility and multitude of options, it is easy to over or under provision the server infrastructure, resulting in poor performance and high TCO. Join us for an in depth, technical discussion with industry experts from leading Hadoop and server companies who will provide insights into the key considerations for designing and deploying an optimal Hadoop cluster.
Some of key questions to be discussed are:
- What is the “typical” Hadoop cluster and what should be installed on the different machine types?
- Why should you consider the typical workload patterns when making your hardware decisions?
- Are all microservers created equal for Hadoop deployments?
- How do I plan for expansion if I require more compute, memory, storage or networking?



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