scholarly journals THE GWAC DATA PROCESSING AND MANAGEMENT SYSTEM

Author(s):  
Y. Xu ◽  
L. P. Xin ◽  
X. H. Han ◽  
H. B. Cai ◽  
L. Huang ◽  
...  

GWAC will have been built an integrated FOV of 5,000 degree2 and have already built 1,800 square degree2. The limit magnitude of a 10-second exposure image in the moonless night is 16R. In each observation night, GWAC produces about 0.7TB of raw data, and the data processing pipeline generates millions of single frame alerts. We describe the GWAC Data Processing and Management System (GPMS), including hardware architecture, database, detection-filtering-validation of transient candidates, data archiving, and user interfaces for the check of transient and the monitor of the system. GPMS combines general technology and software in astronomy and computer field, and use some advanced technologies such as deep learning. Practical results show that GPMS can fully meet the scientific data processing requirement of GWAC. It can online accomplish the detection, filtering and validation of millions of transient candidates, and feedback the final results to the astronomer in real-time. During the observation from October of 2018 to December of 2019, we have already found 102 transients.

2018 ◽  
Vol 4 (1) ◽  
pp. 87-96
Author(s):  
Yanni Suherman

Research conducted at the Office of Archives and Library of Padang Pariaman Regency aims to find out the data processing system library and data archiving. All data processing is done is still very manual by using the document in writing and there is also a stacking of archives on the service. By utilizing library information systems and archives that will be applied to the Office of Archives and Library of Padang Pariaman Regency can improve the quality of service that has not been optimal. This research was made by using System Development Life Cycle (SDLC) which is better known as waterfall method. The first step taken on this method is to go directly to the field by conducting interviews and discussions. This information system will be able to assist the work of officers in terms of data processing libraries and facilitate in search data archives by presenting reports more accurate, effective and efficient.


2012 ◽  
Vol 396 (3) ◽  
pp. 032121 ◽  
Author(s):  
S Zimmer ◽  
L Arrabito ◽  
T Glanzman ◽  
T Johnson ◽  
C Lavalley ◽  
...  

2020 ◽  
Author(s):  
Grigory Sharov ◽  
Dustin R. Morado ◽  
Marta Carroni ◽  
José Miguel de la Rosa-Trevín

Scipion is a modular image processing framework integrating several software packages under a unified interface while taking care of file formats and conversions. Here new developments and capabilities of the Scipion plugin for the Relion software are presented and illustrated with the image processing pipeline of published data. The user interfaces of Scipion and Relion are compared and the key differences highlighted, allowing this manuscript to be used as a guide for both new and experienced users of these software. Different streaming image processing options are also discussed demonstrating the flexibility of the Scipion framework.SynopsisAn overview of the Scipion plugin for the Relion software is presented and various capabilities of image processing within Scipion framework are discussed.


2018 ◽  
Vol 10 (3) ◽  
pp. 76-90
Author(s):  
Ye Tao ◽  
Xiaodong Wang ◽  
Xiaowei Xu

This article describes how rapidly growing data volumes require systems that have the ability to handle massive heterogeneous unstructured data sets. However, most existing mature transaction processing systems are built upon relational databases with structured data. In this article, the authors design a hybrid development framework, to offer greater scalability and flexibility of data analysis and reporting, while keeping maximum compatibility and links to the legacy platforms on which transaction business logics run. Data, service and user interfaces are implemented as a toolset stack, for developing applications with functionalities of information retrieval, data processing, analyzing and visualizing. A use case of healthcare data integration is presented as an example, where information is collected and aggregated from diverse sources. The workflow and simulation of data processing and visualization are also discussed, to validate the effectiveness of the proposed framework.


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