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#### UCoMBrpBYIcIZz9ln9tRzBXw
#### SELECT * FROM DAvidKanal WHERE `Chan` ="UCoMBrpBYIcIZz9ln9tRzBXw"
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:::::::: SELECT * FROM DAvidKanal WHERE Chan="UCoMBrpBYIcIZz9ln9tRzBXw"
#~~~~# SELECT * FROM DAvidKanal WHERE Chan="UCoMBrpBYIcIZz9ln9tRzBXw"

#~~~~# http://chegu.de/Ausgabe.php?URL=https://www.youtube.com/feeds/videos.xml?channel_id=UCoMBrpBYIcIZz9ln9tRzBXw

**15264

**?xml version="1.0" encoding="UTF-8"?> feed xmlns:yt="http://www.youtube.com/xml/schemas/2015" xmlns:media="http://search.yahoo.com/mrss/" xmlns="http://www.w3.org/2005/Atom"> link rel="self" href="http://www.youtube.com/feeds/videos.xml?channel_id=UCoMBrpBYIcIZz9ln9tRzBXw"/> id>yt:channel:oMBrpBYIcIZz9ln9tRzBXw/id> yt:channelId>oMBrpBYIcIZz9ln9tRzBXw/yt:channelId> title>wanderine/title> link rel="alternate" href="https://www.youtube.com/channel/UCoMBrpBYIcIZz9ln9tRzBXw"/> author> name>wanderine/name> uri>https://www.youtube.com/channel/UCoMBrpBYIcIZz9ln9tRzBXw/uri> /author> published>2006-10-07T20:29:06+00:00/published> entry> id>yt:video:yhZQnO92Gk4/id> yt:videoId>yhZQnO92Gk4/yt:videoId> yt:channelId>UCoMBrpBYIcIZz9ln9tRzBXw/yt:channelId> title>First level analysis in BROCCOLI/title> link rel="alternate" href="https://www.youtube.com/watch?v=yhZQnO92Gk4"/> author> name>wanderine/name> uri>https://www.youtube.com/channel/UCoMBrpBYIcIZz9ln9tRzBXw/uri> /author> published>2014-05-27T21:53:21+00:00/published> updated>2024-03-21T11:50:19+00:00/updated> media:group> media:title>First level analysis in BROCCOLI/media:title> media:content url="https://www.youtube.com/v/yhZQnO92Gk4?version=3" type="application/x-shockwave-flash" width="640" height="390"/> media:thumbnail url="https://i2.ytimg.com/vi/yhZQnO92Gk4/hqdefault.jpg" width="480" height="360"/> media:description>This video shows how fast a first level fMRI analysis can be performed using the software package BROCCOLI. BROCCOLI is written in OpenCL (Open Computing Language), making it possible to run it on a large variety of hardware configurations. In the video, BROCCOLI is tested with an Nvidia GPU, an AMD GPU and an Intel CPU. For more information, see http://journal.frontiersin.org/Journal/10.3389/fninf.2014.00024/abstract https://github.com/wanderine/BROCCOLI/media:description> media:community> media:starRating count="2" average="5.00" min="1" max="5"/> media:statistics views="281"/> /media:community> /media:group> /entry> entry> id>yt:video:M1heYPt-6G4/id> yt:videoId>M1heYPt-6G4/yt:videoId> yt:channelId>UCoMBrpBYIcIZz9ln9tRzBXw/yt:channelId> title>Non-parametric permutation tests in BROCCOLI and FSL/title> link rel="alternate" href="https://www.youtube.com/watch?v=M1heYPt-6G4"/> author> name>wanderine/name> uri>https://www.youtube.com/channel/UCoMBrpBYIcIZz9ln9tRzBXw/uri> /author> published>2014-05-27T21:04:18+00:00/published> updated>2024-03-13T13:22:11+00:00/updated> media:group> media:title>Non-parametric permutation tests in BROCCOLI and FSL/media:title> media:content url="https://www.youtube.com/v/M1heYPt-6G4?version=3" type="application/x-shockwave-flash" width="640" height="390"/> media:thumbnail url="https://i2.ytimg.com/vi/M1heYPt-6G4/hqdefault.jpg" width="480" height="360"/> media:description>This video shows non-parametric permutation testing using BROCCOLI and FSL. BROCCOLI is a new software package for fMRI, and is written in OpenCL (Open Computing Language). This makes it possible to use a large variety of hardware configurations. In the first test an Nvidia GPU is used, then an AMD GPU is used and finally an Intel CPU is used. For more information, see http://journal.frontiersin.org/Journal/10.3389/fninf.2014.00024/abstract https://github.com/wanderine/BROCCOLI/media:description> media:community> media:starRating count="3" average="5.00" min="1" max="5"/> media:statistics views="394"/> /media:community> /media:group> /entry> entry> id>yt:video:OxKXFaezMd0/id> yt:videoId>OxKXFaezMd0/yt:videoId> yt:channelId>UCoMBrpBYIcIZz9ln9tRzBXw/yt:channelId> title>Non-linear registration using BROCCOLI, AFNI and FSL/title> link rel="alternate" href="https://www.youtube.com/watch?v=OxKXFaezMd0"/> author> name>wanderine/name> uri>https://www.youtube.com/channel/UCoMBrpBYIcIZz9ln9tRzBXw/uri> /author> published>2014-05-27T20:48:30+00:00/published> updated>2024-03-13T19:00:54+00:00/updated> media:group> media:title>Non-linear registration using BROCCOLI, AFNI and FSL/media:title> media:content url="https://www.youtube.com/v/OxKXFaezMd0?version=3" type="application/x-shockwave-flash" width="640" height="390"/> media:thumbnail url="https://i4.ytimg.com/vi/OxKXFaezMd0/hqdefault.jpg" width="480" height="360"/> media:description>A comparison of non-linear registration using the software packages BROCCOLI, AFNI and FSL. BROCCOLI is a new software package written in OpenCL (Open Computing Language), making it possible to run it on a large variety of hardware configurations. In this video we first see BROCCOLI running on an Nvidia GPU, then an AMD GPU and finally on an Intel CPU. For more information about the BROCCOLI software package, see http://journal.frontiersin.org/Journal/10.3389/fninf.2014.00024/abstract https://github.com/wanderine/BROCCOLI/media:description> media:community> media:starRating count="1" average="5.00" min="1" max="5"/> media:statistics views="689"/> /media:community> /media:group> /entry> entry> id>yt:video:wflbt2sV34M/id> yt:videoId>wflbt2sV34M/yt:videoId> yt:channelId>UCoMBrpBYIcIZz9ln9tRzBXw/yt:channelId> title>True 4D Image Denoising on the GPU/title> link rel="alternate" href="https://www.youtube.com/watch?v=wflbt2sV34M"/> author> name>wanderine/name> uri>https://www.youtube.com/channel/UCoMBrpBYIcIZz9ln9tRzBXw/uri> /author> published>2011-06-22T15:52:05+00:00/published> updated>2024-03-25T07:05:58+00:00/updated> media:group> media:title>True 4D Image Denoising on the GPU/media:title> media:content url="https://www.youtube.com/v/wflbt2sV34M?version=3" type="application/x-shockwave-flash" width="640" height="390"/> media:thumbnail url="https://i4.ytimg.com/vi/wflbt2sV34M/hqdefault.jpg" width="480" height="360"/> media:description>This video shows the result of a 4D image denoising algorithm applied to a computed tomography (CT) heart dataset. To the left is the original data, to the right is the denoised data. To be able to do the 4D image denoising in a reasonable amount of time the algorithm was implemented on the graphics processing unit (GPU) with the CUDA programming language. The visualization is done in Mevislab (www.mevislab.de) by using two volume renderers that are synced in terms of view angle and transfer function. For more information http://www.hindawi.com/journals/ijbi/aip/952819//media:description> media:community> media:starRating count="7" average="5.00" min="1" max="5"/> media:statistics views="2587"/> /media:community> /media:group> /entry> entry> id>yt:video:QIJDGlM3uiE/id> yt:videoId>QIJDGlM3uiE/yt:videoId> yt:channelId>UCoMBrpBYIcIZz9ln9tRzBXw/yt:channelId> title>A Brain Computer Interface for Communication Using Real-Time fMRI/title> link rel="alternate" href="https://www.youtube.com/watch?v=QIJDGlM3uiE"/> author> name>wanderine/name> uri>https://www.youtube.com/channel/UCoMBrpBYIcIZz9ln9tRzBXw/uri> /author> published>2011-04-21T21:09:18+00:00/published> updated>2024-03-15T09:08:15+00:00/updated> media:group> media:title>A Brain Computer Interface for Communication Using Real-Time fMRI/media:title> media:content url="https://www.youtube.com/v/QIJDGlM3uiE?version=3" type="application/x-shockwave-flash" width="640" height="390"/> media:thumbnail url="https://i2.ytimg.com/vi/QIJDGlM3uiE/hqdefault.jpg" width="480" height="360"/> media:description>The video shows how a subject in a MR scanner manages to communicate through a brain computer interface, the technique used is called real-time functional magnetic resonance imaging (fMRI). The subject moves the red cursor to the left by activating the left hand, to the right by activating the right hand, down by activating the left foot and up by activating the right foot. To select a letter the subject simply rests for a number of seconds. In this example the subject tried to write "GUZZI", which is short for the italian motor cycle brand Moto Guzzi. This work was presented at the International Conference on Pattern Recognition (ICPR) in 2010 http://liu.diva-portal.org/smash/get/diva2:297936/FULLTEXT01/media:description> media:community> media:starRating count="1" average="5.00" min="1" max="5"/> media:statistics views="1611"/> /media:community> /media:group> /entry> entry> id>yt:video:7aP2Pjh02ms/id> yt:videoId>7aP2Pjh02ms/yt:videoId> yt:channelId>UCoMBrpBYIcIZz9ln9tRzBXw/yt:channelId> title>Our own videogame console/title> link rel="alternate" href="https://www.youtube.com/watch?v=7aP2Pjh02ms"/> author> name>wanderine/name> uri>https://www.youtube.com/channel/UCoMBrpBYIcIZz9ln9tRzBXw/uri> /author> published>2011-03-29T19:48:13+00:00/published> updated>2024-03-21T18:43:04+00:00/updated> media:group> media:title>Our own videogame console/media:title> media:content url="https://www.youtube.com/v/7aP2Pjh02ms?version=3" type="application/x-shockwave-flash" width="640" height="390"/> media:thumbnail url="https://i4.ytimg.com/vi/7aP2Pjh02ms/hqdefault.jpg" width="480" height="360"/> media:description>The result of a project course in electronics, our own videogame console!/media:description> media:community> media:starRating count="1" average="5.00" min="1" max="5"/> media:statistics views="129"/> /media:community> /media:group> /entry> entry> id>yt:video:wxMqZw0jcOk/id> yt:videoId>wxMqZw0jcOk/yt:videoId> yt:channelId>UCoMBrpBYIcIZz9ln9tRzBXw/yt:channelId> title>Fast random permutation tests for single subject fMRI data using the GPU/title> link rel="alternate" href="https://www.youtube.com/watch?v=wxMqZw0jcOk"/> author> name>wanderine/name> uri>https://www.youtube.com/channel/UCoMBrpBYIcIZz9ln9tRzBXw/uri> /author> published>2011-02-14T09:36:10+00:00/published> updated>2024-03-15T16:35:32+00:00/updated> media:group> media:title>Fast random permutation tests for single subject fMRI data using the GPU/media:title> media:content url="https://www.youtube.com/v/wxMqZw0jcOk?version=3" type="application/x-shockwave-flash" width="640" height="390"/> media:thumbnail url="https://i4.ytimg.com/vi/wxMqZw0jcOk/hqdefault.jpg" width="480" height="360"/> media:description>The video shows a run of a multi-GPU implementation of random permutation tests for analysis of single subject functional magnetic resonance imaging (fMRI) data. The computer is equipped with three Nvidia GTX 480, giving a total of 1440 processor cores. The random permutation test is used in order to estimate the maximum null distribution of the test statistics, in order to calculate a corrected threshold for p = 0.05, 9999 permutations are done in about 57 seconds, with a standard C implementation this would have taken about 16 hours. The statistical analysis applied to the data is canonical correlation analysis (CCA), which finds a higher number of significantly active voxels than the general linear model (GLM). For more information http://www.hindawi.com/journals/ijbi/aip/627947/ http://www.sciencedirect.com/science/article/pii/S0169260711001957/media:description> media:community> media:starRating count="5" average="5.00" min="1" max="5"/> media:statistics views="1261"/> /media:community> /media:group> /entry> entry> id>yt:video:dLB2I5OgkXg/id> yt:videoId>dLB2I5OgkXg/yt:videoId> yt:channelId>UCoMBrpBYIcIZz9ln9tRzBXw/yt:channelId> title>Interactive brain connectivity analysis with GPU (OpenCL)/title> link rel="alternate" href="https://www.youtube.com/watch?v=dLB2I5OgkXg"/> author> name>wanderine/name> uri>https://www.youtube.com/channel/UCoMBrpBYIcIZz9ln9tRzBXw/uri> /author> published>2010-10-26T18:48:09+00:00/published> updated>2024-03-22T21:22:35+00:00/updated> media:group> media:title>Interactive brain connectivity analysis with GPU (OpenCL)/media:title> media:content url="https://www.youtube.com/v/dLB2I5OgkXg?version=3" type="application/x-shockwave-flash" width="640" height="390"/> media:thumbnail url="https://i1.ytimg.com/vi/dLB2I5OgkXg/hqdefault.jpg" width="480" height="360"/> media:description>The video shows an interface for interactive functional connectivity analysis of fMRI data, the yellow voxel is the reference voxel. The interface was implemented with MevisLab (www.mevislab.de) and OpenCL. All the calculations are done on the GPU. http://liu.diva-portal.org/smash/get/diva2:445120/FULLTEXT01 fMRI analysis on the GPU: http://www.sciencedirect.com/science/article/pii/S0169260711001957/media:description> media:community> media:starRating count="2" average="5.00" min="1" max="5"/> media:statistics views="2122"/> /media:community> /media:group> /entry> entry> id>yt:video:HJL7j-uVqxA/id> yt:videoId>HJL7j-uVqxA/yt:videoId> yt:channelId>UCoMBrpBYIcIZz9ln9tRzBXw/yt:channelId> title>Using Real-Time fMRI to Control a Dynamical System by Brain Activity Classification/title> link rel="alternate" href="https://www.youtube.com/watch?v=HJL7j-uVqxA"/> author> name>wanderine/name> uri>https://www.youtube.com/channel/UCoMBrpBYIcIZz9ln9tRzBXw/uri> /author> published>2008-11-13T03:00:21+00:00/published> updated>2024-03-26T00:52:20+00:00/updated> media:group> media:title>Using Real-Time fMRI to Control a Dynamical System by Brain Activity Classification/media:title> media:content url="https://www.youtube.com/v/HJL7j-uVqxA?version=3" type="application/x-shockwave-flash" width="640" height="390"/> media:thumbnail url="https://i1.ytimg.com/vi/HJL7j-uVqxA/hqdefault.jpg" width="480" height="360"/> media:description>The movie clip shows an fMRI based brain computer interface (BCI) realization. The human brain and a computer were here linked by fMRI and worked together as a controller of a dynamical system. The dynamical system was an inverted pendulum. The subject had the ability to induce a force on the pendulum by evoking brain activity in the parts of the motor cortex associated with movements of the left and right hand. A force was applied from the left if the subject was detected to activate the left hand and from the right if the subject was detected to activate the right hand. If the subject was detected to rest no force was applied. A neural network was trained to separate between rest, activity induced by activating the left and right hand. The subject was able to balance the inverted pendulum during a 7 minute test run. This work was presented at the MICCAI conference in 2009, the article can be found at http://liu.diva-portal.org/smash/get/diva2:297924/FULLTEXT01/media:description> media:community> media:starRating count="7" average="5.00" min="1" max="5"/> media:statistics views="2812"/> /media:community> /media:group> /entry> /feed>

wanderine

07.03.2024 · 02:57:42 ···
01.01.1970 · 01:00:00 ···
30.07.2023 · 20:54:05 ··· 5 ··· ··· 9 ···
29.06.2024 · 05:54:38 ···
01.01.1970 · 01:00:00 ···
30.07.2023 · 20:54:05 ··· 5 ··· ··· 9 ···

1:: First level analysis in BROCCOLI

01.01.1970 · 01:00:00 ··· 27.05.2014 · 21:53:21 ··· ···
··· ··· ··· ··· This video shows how fast a first level fMRI analysis can be performed using the software package BROCCOLI. BROCCOLI is written in OpenCL (Open Computing Language), making it possible to run it on a large variety of hardware configurations. In the video, BROCCOLI is tested with an Nvidia GPU, an AMD GPU and an Intel CPU. For more information, see http://journal.frontiersin.org/Journal/10.3389/fninf.2014.00024/abstract https://github.com/wanderine/BROCCOLI

2:: Non-parametric permutation tests in BROCCOLI and FSL

01.01.1970 · 01:00:00 ··· 27.05.2014 · 21:04:18 ··· ···
··· ··· ··· ··· This video shows non-parametric permutation testing using BROCCOLI and FSL. BROCCOLI is a new software package for fMRI, and is written in OpenCL (Open Computing Language). This makes it possible to use a large variety of hardware configurations. In the first test an Nvidia GPU is used, then an AMD GPU is used and finally an Intel CPU is used. For more information, see http://journal.frontiersin.org/Journal/10.3389/fninf.2014.00024/abstract https://github.com/wanderine/BROCCOLI

3:: Non-linear registration using BROCCOLI, AFNI and FSL

01.01.1970 · 01:00:00 ··· 27.05.2014 · 20:48:30 ··· ···
··· ··· ··· ··· A comparison of non-linear registration using the software packages BROCCOLI, AFNI and FSL. BROCCOLI is a new software package written in OpenCL (Open Computing Language), making it possible to run it on a large variety of hardware configurations. In this video we first see BROCCOLI running on an Nvidia GPU, then an AMD GPU and finally on an Intel CPU. For more information about the BROCCOLI software package, see http://journal.frontiersin.org/Journal/10.3389/fninf.2014.00024/abstract https://github.com/wanderine/BROCCOLI

4:: True 4D Image Denoising on the GPU

01.01.1970 · 01:00:00 ··· 22.06.2011 · 15:52:05 ··· ···
··· ··· ··· ··· This video shows the result of a 4D image denoising algorithm applied to a computed tomography (CT) heart dataset. To the left is the original data, to the right is the denoised data. To be able to do the 4D image denoising in a reasonable amount of time the algorithm was implemented on the graphics processing unit (GPU) with the CUDA programming language. The visualization is done in Mevislab (www.mevislab.de) by using two volume renderers that are synced in terms of view angle and transfer function. For more information http://www.hindawi.com/journals/ijbi/aip/952819/

5:: A Brain Computer Interface for Communication Using Real-Time fMRI

01.01.1970 · 01:00:00 ··· 21.04.2011 · 21:09:18 ··· ···
··· ··· ··· ··· The video shows how a subject in a MR scanner manages to communicate through a brain computer interface, the technique used is called real-time functional magnetic resonance imaging (fMRI). The subject moves the red cursor to the left by activating the left hand, to the right by activating the right hand, down by activating the left foot and up by activating the right foot. To select a letter the subject simply rests for a number of seconds. In this example the subject tried to write "GUZZI", which is short for the italian motor cycle brand Moto Guzzi. This work was presented at the International Conference on Pattern Recognition (ICPR) in 2010 http://liu.diva-portal.org/smash/get/diva2:297936/FULLTEXT01

6:: Our own videogame console

01.01.1970 · 01:00:00 ··· 29.03.2011 · 19:48:13 ··· ···
··· ··· ··· ··· The result of a project course in electronics, our own videogame console!

7:: Fast random permutation tests for single subject fMRI data using the GPU

01.01.1970 · 01:00:00 ··· 14.02.2011 · 09:36:10 ··· ···
··· ··· ··· ··· The video shows a run of a multi-GPU implementation of random permutation tests for analysis of single subject functional magnetic resonance imaging (fMRI) data. The computer is equipped with three Nvidia GTX 480, giving a total of 1440 processor cores. The random permutation test is used in order to estimate the maximum null distribution of the test statistics, in order to calculate a corrected threshold for p = 0.05, 9999 permutations are done in about 57 seconds, with a standard C implementation this would have taken about 16 hours. The statistical analysis applied to the data is canonical correlation analysis (CCA), which finds a higher number of significantly active voxels than the general linear model (GLM). For more information http://www.hindawi.com/journals/ijbi/aip/627947/ http://www.sciencedirect.com/science/article/pii/S0169260711001957

8:: Interactive brain connectivity analysis with GPU (OpenCL)

01.01.1970 · 01:00:00 ··· 26.10.2010 · 18:48:09 ··· ···
··· ··· ··· ··· The video shows an interface for interactive functional connectivity analysis of fMRI data, the yellow voxel is the reference voxel. The interface was implemented with MevisLab (www.mevislab.de) and OpenCL. All the calculations are done on the GPU. http://liu.diva-portal.org/smash/get/diva2:445120/FULLTEXT01 fMRI analysis on the GPU: http://www.sciencedirect.com/science/article/pii/S0169260711001957

9:: Using Real-Time fMRI to Control a Dynamical System by Brain Activity Classification

01.01.1970 · 01:00:00 ··· 13.11.2008 · 03:00:21 ··· ···
··· ··· ··· ··· The movie clip shows an fMRI based brain computer interface (BCI) realization. The human brain and a computer were here linked by fMRI and worked together as a controller of a dynamical system. The dynamical system was an inverted pendulum. The subject had the ability to induce a force on the pendulum by evoking brain activity in the parts of the motor cortex associated with movements of the left and right hand. A force was applied from the left if the subject was detected to activate the left hand and from the right if the subject was detected to activate the right hand. If the subject was detected to rest no force was applied. A neural network was trained to separate between rest, activity induced by activating the left and right hand. The subject was able to balance the inverted pendulum during a 7 minute test run. This work was presented at the MICCAI conference in 2009, the article can be found at http://liu.diva-portal.org/smash/get/diva2:297924/FULLTEXT01