Repository logo
    Info Pages
    Content PolicyCopyright & Access InfoDepositing to MRODeposit LicenseDeposit License SummaryFile FormatsTheses FAQDoctoral Thesis Deposit
    Communities & Collections
    All of MRO
  • English
  • العربية
  • বাংলা
  • Català
  • Čeština
  • Deutsch
  • Ελληνικά
  • Español
  • Suomi
  • Français
  • Gàidhlig
  • हिंदी
  • Magyar
  • Italiano
  • Қазақ
  • Latviešu
  • Nederlands
  • Polski
  • Português
  • Português do Brasil
  • Srpski (lat)
  • Српски
  • Svenska
  • Türkçe
  • Yкраї́нська
  • Tiếng Việt
Log In
New user? Click here to register using a personal email and password.Have you forgotten your password?
  1. Home
  2. Browse by Author

Browsing by Author "Xu, Huawei"

Filter results by typing the first few letters
Now showing 1 - 1 of 1
  • Results Per Page
  • Sort Options
  • Loading...
    Thumbnail Image
    Item
    A database with enterprise application for mining astronomical data obtained by MOA : a thesis submitted in partial fulfilment of the requirements for the degree of the Master of Information Science in Computer Science, Massey University at Albany, Auckland, New Zealand
    (Massey University, 2007) Xu, Huawei
    The MOA (Microlensing Observations in Astrophysics) Project is one of a new generation of modern astronomy endeavours that generates huge volumes of data. These have enormous scientific data mining potential. However, it is common for astronomers to deal with millions and even billions of records. The challenge of how to manage these large data sets is an important case for researchers. A good database management system is vital for the research. With the modern observation equipments used, MOA suffers from the growing volume of the data and a database management solution is needed. This study analyzed the modern technology for database and enterprise application. After analysing the data mining requirements of MOA, a prototype data management system based on MVC pattern was developed. Furthermore, the application supports sharing MOA findings and scientific data on the Internet. It was tested on a 7GB subset of achieved MOA data set. After testing, it was found that the application could query data in an efficient time and support data mining.

Copyright © Massey University  |  DSpace software copyright © 2002-2025 LYRASIS

  • Contact Us
  • Copyright Take Down Request
  • Massey University Privacy Statement
  • Cookie settings
Repository logo COAR Notify