Tiered data management system: Accelerating data processing on HPC systems

In recent years, autonomous solutions in the multidisciplinary field of mining engineering have been an extremely popular applied research topic. This is a result of the increasing demands of society on mineral resources along with the accelerating exploitation of the currently economically viable resources, which lead the mining sector to turn to deeper, more-difficult-to-mine orebodies. An appropriate data management system comprises a crucial aspect of the designing and the engineering of a system that involves autonomous or semiautonomous vehicles. The vast volume of data collected from onboard sensors, as well as from a potential IoT network dispersed around a smart mine, necessitates the development of a reliable data management strategy. Ideally, this strategy will allow for fast and asynchronous access to the data for real-time processing and decision-making purposes as well as for visualization through a corresponding human–machine interface. The proposed system has been developed for autonomous navigation of a coalmine shuttle car and has been implemented on a 1/6th scale shuttle car in a mock mine. It comprises three separate nodes, namely, a data collection node, a data management node, and a data processing and visualization node. This approach was dictated by the large amount of collected data and the need to ensure uninterrupted and fast data management and flow. The implementation of an SQL database server allows for asynchronous, real-time, and reliable data management, including data storage and retrieval. On the other hand, this approach introduces latencies between the data management node and the other two nodes. In general, these latencies include sensor latencies, network latencies, and processing latencies. However, the data processing and visualization module is able to retrieve and process the latest data and make a decision about the next optimal movement of the shuttle car prototype in less than 900 ms. This allows the prototype to navigate efficiently around the pillars without interruptions.

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Current status of the WLCG data management system, the experience from the three years of data taking and future role of Grids for the LHC data processing

10.22323/1.184.0020 ◽

2013 ◽

Cited By ~ 1

Author(s):

Dagmar Adamova

Keyword(s):

Data Processing ◽

Data Management ◽

Management System ◽

Data Management System ◽

Current Status ◽

Future Role

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PERANCANGAN PROGRAM PENGELOLAAN DATA KEUANGAN PASIEN RAWAT JALAN BPJS PADA RUMAH SAKIT GRAHA JUANDA BEKASI

Kilat ◽

10.33322/kilat.v7i1.98 ◽

2018 ◽

Vol 7 (1) ◽

pp. 66-77

Author(s):

Redaksi Tim Jurnal

Keyword(s):

Information Technology ◽

Health Services ◽

Data Processing ◽

Data Management ◽

Management System ◽

Financial Data ◽

Data Management System ◽

Service Business ◽

Search Data ◽

Data Error

In today's era of globalization, information technology is speeding up. The computer is a device that was created to facilitate human work, while achieving good progress in the manufacture of hardware and software. Graha Juanda Hospital is a service business engaged in the field of health services. BPJS outpatient financial system that is done still manually from the calculation, data processing until the making of the report so it is possible at the time penginputan data error occurred in the recording or less accurate in the report made and delays in search data required. by using BPJS outpatient data management system that computerized BPJS outpatient financial data management will be more effective and efficient. In addition, the data stored neatly if at any time needed then the search data will be easier.

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An experience of updated hydrological network data processing using the CUAHSI HIS ODM data management system

Russian Meteorology and Hydrology ◽

10.3103/s1068373913050099 ◽

2013 ◽

Vol 38 (5) ◽

pp. 359-366 ◽

Cited By ~ 7

Author(s):

A. N. Bugaets ◽

B. I. Gartsman ◽

S. A. Krasnopeev ◽

N. D. Bugaets

Keyword(s):

Data Processing ◽

Data Management ◽

Management System ◽

Data Management System ◽

Network Data

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RELIABILITY CENTRAL AUTOMATIC DATA PROCESSING SUBSYSTEM. VOLUME 3. DATA MANAGEMENT SYSTEM SURVEY

10.21236/ad0489668 ◽

1966 ◽

Cited By ~ 1

Author(s):

J. Sable ◽

W. Crowley ◽

M. Rosenthal ◽

S. Forst ◽

P. Harper

Keyword(s):

Data Processing ◽

Data Management ◽

Management System ◽

Automatic Data Processing ◽

Data Management System ◽

Automatic Data ◽

Processing Subsystem

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Risk Management on Information Security in ABC Company

ACMIT Proceedings ◽

10.33555/acmit.v4i1.60 ◽

2017 ◽

Vol 4 (1) ◽

pp. 62-66

Author(s):

Luyen Ha Nam

Keyword(s):

Risk Management ◽

Information Security ◽

Data Management ◽

Management System ◽

Risk Mitigation ◽

Data Management System ◽

Data Centre ◽

Long Time ◽

Mitigation Action ◽

Better Than

From long, long time ago until nowadays information still takes a serious position for all aspect of life, fromindividual to organization. In ABC company information is somewhat very sensitive, very important. But how wekeep our information safe, well we have many ways to do that: in hard drive, removable disc etc. with otherorganizations they even have data centre to save their information. The objective of information security is to keep information safe from unwanted access. We applied Risk Mitigation Action framework on our data management system and after several months we have a result far better than before we use it: information more secure, quickly detect incidents, improve internal and external collaboration etc.

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