Intelligent Data Management System and Performance Joint Blockchain Model for Commercial Bank Management Accounting

A patient-oriented data management system is described. The environment was cardiology with a heavy emphasis on research and the MEDIC system was designed to meet the day to day program needs. The data are organized in speciality files with dynamic patient records composed of subrecords of different types. The schema is described by a data definition language. Application packages include data quality control, medical reporting and general inquiry.After five years of extensive use in various clinical applications, its utility has been assessed as well as its low cost. The disadvantages, the main being the multifile structure, can now be stated as its advantages, like data independence and performance increase. Although the system is now partially outdated, the experience acquired with its use becomes very helpful in the selection process of the future database management system.

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Design and Performance Evaluation of Mobile Personal Big Data Management System based on ICN

Internet Technology Letters ◽

10.1002/itl2.237 ◽

2020 ◽

Author(s):

Lijun Chen ◽

Luca Sciullo ◽

Angelo Trotta

Keyword(s):

Big Data ◽

Performance Evaluation ◽

Data Management ◽

Management System ◽

Data Management System ◽

And Performance

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The Belle II Raw Data Management System

EPJ Web of Conferences ◽

10.1051/epjconf/202024504005 ◽

2020 ◽

Vol 245 ◽

pp. 04005 ◽

Cited By ~ 1

Author(s):

Michel Hernández Villanueva ◽

Ikuo Ueda

Keyword(s):

Data Management ◽

Management System ◽

Computing System ◽

Data Management System ◽

Current Status ◽

Distributed Data ◽

Data Set ◽

Raw Data ◽

Belle Ii ◽

And Performance

The Belle II experiment, a major upgrade of the previous e+e− asymmetric collider experiment Belle, is expected to produce tens of petabytes of data per year due to the luminosity increase from the upgraded SuperKEKB accelerator. The distributed computing system of the Belle II experiment plays a key role, storing and distributing data in a reliable way to be easily accessed and analyzed by more than 1000 collaborators. In particular, the Belle II Raw Data Management system has been developed with an aim to upload output files onto grid storage, register them into the file and metadata catalogs, and make two replicas of the full raw data set using the Belle II Distributed Data Management system. It has been implemented as an extension of DIRAC (Distributed Infrastructure with Remote Agent Control) and consists of a database, services, client and monitoring tools, and several agents that treat the data automatically. The first year of data taken with the Belle II full detector has been managed by the Belle II Raw Data Management system successfully. The design, current status, and performance are presented. Prospects for improvements towards the full luminosity data taking are also reviewed.

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Development of the JUNO Conditions Data Management System

EPJ Web of Conferences ◽

10.1051/epjconf/202024504030 ◽

2020 ◽

Vol 245 ◽

pp. 04030

Author(s):

Xingtao Huang

Keyword(s):

Data Management ◽

Management System ◽

Liquid Scintillator ◽

Data Management System ◽

Mass Hierarchy ◽

Neutrino Mass Hierarchy ◽

Web Interfaces ◽

The Status ◽

And Performance ◽

Treat All

The Jiangmen Underground Neutrino Observatory (JUNO) experiment is designed to determine the neutrino mass hierarchy and precisely measure oscillation parameters with an unprecedented energy resolution of 3% at 1 MeV. It is composed of a 20 kton liquid scintillator central detector equipped with 18000 20-inch PMTs and 25000 3-inch PMTs, a water pool with 2000 20-inch PMTs, and a top tracker. Conditions data, coming from calibration and detector monitoring, are heterogeneous, different type of conditions data has different write rates, data format and data volume. JUNO conditions data management system (JCDMS) is developed to homogeneously treat all these heterogeneous conditions data in order to provide easy management and convenient access with both Restful API and web interfaces, support good scalability and maintenance for long time running. The paper describes the status and development of JCDMS including the data model, workflows, interfaces, data caching and performance of the system.

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Structured Big Data Management System Supported Cross-Domain Query

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.631-632.1033 ◽

2014 ◽

Vol 631-632 ◽

pp. 1033-1038 ◽

Cited By ~ 1

Author(s):

Tao Xu ◽

Ge Fu ◽

Huai Yuan Tan ◽

Hong Zhang ◽

Xin Ran Liu

Keyword(s):

Big Data ◽

Data Management ◽

Management System ◽

Large Scale ◽

Parallel Execution ◽

Data Management System ◽

Cross Domain ◽

Software And Hardware ◽

And Performance ◽

Massive Parallel Processing

We design a structured big data management system which can deal with large-scale structured datasets and supports the cross-domain collaborative query. The system employs the HDFS as the storage layer. And it realizes a scheduling engine in reference with the splitting technology of the massive parallel processing (MPP) database. Using this engine, tasks can be split and distributed to different sub-nodes for parallel execution. Through cross-domain querymodule, users can execute SQL commands on the datasets of different datacenters or network domains. Meanwhile, the system supports the distributed deployment, so as to reduce the construction cost by making full use of existing software and hardware resources and equipments. We test the system functions and performance on a 80 nodes cluster, and compares with Hive. The result suggested that system performance is improved by 2-3 times than Hive and the function designed can be performed correctly.

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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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