The Experts below are selected from a list of 60 Experts worldwide ranked by ideXlab platform
Jacek Becla - One of the best experts on this subject based on the ideXlab platform.
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Qserv: A distributed shared-nothing Database for the LSST Catalog
SC '11: Proceedings of 2011 International Conference for High Performance Computing Networking Storage and Analysis, 2011Co-Authors: Daniel L. Wang, Serge M. Monkewitz, Jacek BeclaAbstract:The LSST project will provide public access to a Database Catalog that, in its final year, is estimated to include 26 billion stars and galaxies in dozens of trillion detections in multiple petabytes. Because we are not aware of an existing open-source Database implementation that has been demonstrated to efficiently satisfy astronomers' spatial self-joining and cross-matching queries at this scale, we have implemented Qserv, a distributed shared-nothing SQL Database query system. To speed development, Qserv relies on two successful open-source software packages: the MySQL RDBMS and the Xrootd distributed file system. We describe Qserv's design, architecture, and ability to scale to LSST's data requirements. We illustrate its potential with test results on a 150-node cluster using 55 billion rows and 30 terabytes of simulated data. These results demonstrate the soundness of Qserv's approach and the scale it achieves on today's hardware.
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SC State of the Practice Reports - Qserv: a distributed shared-nothing Database for the LSST Catalog
State of the Practice Reports on - SC '11, 2011Co-Authors: Daniel L. Wang, Serge M. Monkewitz, Kian-tat Lim, Jacek BeclaAbstract:The LSST project will provide public access to a Database Catalog that, in its final year, is estimated to include 26 billion stars and galaxies in dozens of trillion detections in multiple petabytes. Because we are not aware of an existing open-source Database implementation that has been demonstrated to efficiently satisfy astronomers' spatial self-joining and cross-matching queries at this scale, we have implemented Qserv, a distributed shared-nothing SQL Database query system. To speed development, Qserv relies on two successful open-source software packages: the MySQL RDBMS and the Xrootd distributed file system. We describe Qserv's design, architecture, and ability to scale to LSST's data requirements. We illustrate its potential with test results on a 150-node cluster using 55 billion rows and 30 terabytes of simulated data. These results demonstrate the soundness of Qserv's approach and the scale it achieves on today's hardware.
Daniel L. Wang - One of the best experts on this subject based on the ideXlab platform.
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Qserv: A distributed shared-nothing Database for the LSST Catalog
SC '11: Proceedings of 2011 International Conference for High Performance Computing Networking Storage and Analysis, 2011Co-Authors: Daniel L. Wang, Serge M. Monkewitz, Jacek BeclaAbstract:The LSST project will provide public access to a Database Catalog that, in its final year, is estimated to include 26 billion stars and galaxies in dozens of trillion detections in multiple petabytes. Because we are not aware of an existing open-source Database implementation that has been demonstrated to efficiently satisfy astronomers' spatial self-joining and cross-matching queries at this scale, we have implemented Qserv, a distributed shared-nothing SQL Database query system. To speed development, Qserv relies on two successful open-source software packages: the MySQL RDBMS and the Xrootd distributed file system. We describe Qserv's design, architecture, and ability to scale to LSST's data requirements. We illustrate its potential with test results on a 150-node cluster using 55 billion rows and 30 terabytes of simulated data. These results demonstrate the soundness of Qserv's approach and the scale it achieves on today's hardware.
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SC State of the Practice Reports - Qserv: a distributed shared-nothing Database for the LSST Catalog
State of the Practice Reports on - SC '11, 2011Co-Authors: Daniel L. Wang, Serge M. Monkewitz, Kian-tat Lim, Jacek BeclaAbstract:The LSST project will provide public access to a Database Catalog that, in its final year, is estimated to include 26 billion stars and galaxies in dozens of trillion detections in multiple petabytes. Because we are not aware of an existing open-source Database implementation that has been demonstrated to efficiently satisfy astronomers' spatial self-joining and cross-matching queries at this scale, we have implemented Qserv, a distributed shared-nothing SQL Database query system. To speed development, Qserv relies on two successful open-source software packages: the MySQL RDBMS and the Xrootd distributed file system. We describe Qserv's design, architecture, and ability to scale to LSST's data requirements. We illustrate its potential with test results on a 150-node cluster using 55 billion rows and 30 terabytes of simulated data. These results demonstrate the soundness of Qserv's approach and the scale it achieves on today's hardware.
Serge M. Monkewitz - One of the best experts on this subject based on the ideXlab platform.
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Qserv: A distributed shared-nothing Database for the LSST Catalog
SC '11: Proceedings of 2011 International Conference for High Performance Computing Networking Storage and Analysis, 2011Co-Authors: Daniel L. Wang, Serge M. Monkewitz, Jacek BeclaAbstract:The LSST project will provide public access to a Database Catalog that, in its final year, is estimated to include 26 billion stars and galaxies in dozens of trillion detections in multiple petabytes. Because we are not aware of an existing open-source Database implementation that has been demonstrated to efficiently satisfy astronomers' spatial self-joining and cross-matching queries at this scale, we have implemented Qserv, a distributed shared-nothing SQL Database query system. To speed development, Qserv relies on two successful open-source software packages: the MySQL RDBMS and the Xrootd distributed file system. We describe Qserv's design, architecture, and ability to scale to LSST's data requirements. We illustrate its potential with test results on a 150-node cluster using 55 billion rows and 30 terabytes of simulated data. These results demonstrate the soundness of Qserv's approach and the scale it achieves on today's hardware.
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SC State of the Practice Reports - Qserv: a distributed shared-nothing Database for the LSST Catalog
State of the Practice Reports on - SC '11, 2011Co-Authors: Daniel L. Wang, Serge M. Monkewitz, Kian-tat Lim, Jacek BeclaAbstract:The LSST project will provide public access to a Database Catalog that, in its final year, is estimated to include 26 billion stars and galaxies in dozens of trillion detections in multiple petabytes. Because we are not aware of an existing open-source Database implementation that has been demonstrated to efficiently satisfy astronomers' spatial self-joining and cross-matching queries at this scale, we have implemented Qserv, a distributed shared-nothing SQL Database query system. To speed development, Qserv relies on two successful open-source software packages: the MySQL RDBMS and the Xrootd distributed file system. We describe Qserv's design, architecture, and ability to scale to LSST's data requirements. We illustrate its potential with test results on a 150-node cluster using 55 billion rows and 30 terabytes of simulated data. These results demonstrate the soundness of Qserv's approach and the scale it achieves on today's hardware.
Anita Sindar Rm Sinaga - One of the best experts on this subject based on the ideXlab platform.
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Real Time Database Seleksi Wajah Digital Menggunakan Algoritma CAMshift
'Universitas Darussalam Gontor', 2020Co-Authors: Anita Sindar Rm SinagaAbstract:AbstrakPerkuliahan yang ditempuh 4-5 tahun mempengaruhi perkembangan fisik. Penelitian ini menggunakan data video digital mahasiswa. Hasil rekaman video digunakan untuk data set menentukan ciri tertentu yang dimiliki mahasiswa nantinya tersimpan dalam katalog Database file digital. Dimulai dari konversi video .mp4 menjadi format .AVI. Algoritma CAMShift menggunakan dasar warna HSV untuk pelacakan posisi wajah (tracking) dan mengenal wajah (recognition). Video durasi 1-2 detik menghasilkan 45-200 frame format PNG. Algoritma CamShift melakukan penghitungan nilai Hue data sample. Hasil seleksi area bounding box disimpan dalam Database wajah. Tracking wajah menggunakan Meanshift switching Matlab–OpenGL. Penelitian bertujuan mendokumentasikan profil wajah berbentuk digital berdasarkan warna dominan kulit. Hasil uji pencocokan wajah dilakukan pada beberapa video play, keberhasilan deteksi: 100% terseleksi, 45%-60%, 80-90%, disimpulkan sekitar 50%-100% berhasil. Gerakan wajah akan tertangkap centroid bounding box, bila warna wajah dominan Hue.Kata kunci: Algoritma Camshift; Database Wajah; Real Time; Seleksi Wajah; Warna Hue; Abstract[Real Time for Digital Face Database Selection Using Camshift Algorithm] Education taken 4-5 years affects physical development. This study uses student digital video data. The recording results are used to identify certain characteristics possessed by a student later stored in the digital file Database Catalog. The stages of the study consisted of identification, recognition and matching of faces. It starts from converting .mp4 videos to .AVI format. The CAMShift algorithm uses basic HSV colors for tracking face position (tracking) and faces recognition. 1-2 seconds video produces 45-200 frames PNG file. The research aims to document the digital profile of a face based on the dominant color of the skin. The face matching test results were carried out on several video play, the success of detection: 100% selected, 45%-60%, 80-90%, concluded around 50%-100% successful. Face movements will be caught by the centroid bounding box, if the color of the face is dominant in HueKeywords: Camshift Algorithm, Database Faces Face Selection; Hue Color; Real Tim
B.r. Von Konsky - One of the best experts on this subject based on the ideXlab platform.
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Using image Databases to relate internal anatomy to surface features in human motion and animation
Proceedings of 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 1996Co-Authors: B.r. Von KonskyAbstract:A technique is presented for generating animation sequences relating surface anatomy with internal anatomic structures. The method uses a Database containing digitized images from a human motion video study. Images in the Database Catalog the forearm over a large range of joint configurations spanning the anatomic range. Individual frames are accessed by selecting the frame most closely matching a requested joint configuration and viewing orientation. Frames depicting surface anatomy are synchronized with rendered images of internal anatomy using data from an MRI cadaver study. Database requests are formulated using either interactive kinematic input or a dynamic muscle and limb model. Based on user input, the method enables original animation sequences to be generated which synchronize the motion of internal and external anatomy. Educational applications of the methodology are described.
