|
|
|
MauveDB: Supporting Model-based User Views in Data
|
|
MauveDB: Supporting Model-based User Views in Database Systems Amol Deshpande, University of Maryland Samuel Madden, MIT Motivation Unprecedented, and rapidly increasing, instrumentation of our every-day world Overwhelmingly large raw data volumes generated continuously Data must be processed in real-time The applications have strong acquisitional aspects Data may have to be actively acquired from the environment Typically imprecise, unreliable and incomplete data Inherent measurement noises (e.g. GPS) and low success rates (e.g. RFID) Communication link or sensor node failures (e.g. wireless sensor networks) Spatial and temporal biases because of measurement constraints Traditional data management tools are ill-equipped to handle these challenges
|
|
IT and Computers
-Database
|
|
By
Paull Shocker
|
|
Tags: MauveDB , Supporting Model-based User Views Database Systems , Amol Deshpande , University Maryland , Samuel Madden , MIT , Wireless Sensor Networks
|
|
|
|
|
|
|
|
|
|
|
|
|
|
A Collaborative Code Development Environment for C
|
|
A Collaborative Code Development Environment for Computational Electromagnetics David W. Walker, Oak Ridge National Lab Omer Rana, Matthew Shields, Cardiff University David Golby, BAE SYSTEMS, Sowerby Scientific Computing Prediction : as in traditional computational science. Abstraction : the recognition of patterns and inter-relationships. Visualization for steering, navigation, and immersion. Data mining. Collaboration : brings a wide range of expertise to a problem.
|
|
Undergrad and Grad
-Science
|
|
By
Martin Neon
|
|
Tags: Collaborative Code Development Environment Computational Electromagnetics , David W. Walker , Oak Ridge National Lab , Omer Rana , Matthew Shields , Cardiff University , David Golby , BAE SYSTEMS , Sowerby , Scientific Computing , Prediction , traditional computational science. , Abstraction , recognition patterns and inter-relationships. , Visualization steering , navigation , and immersion. , Data mining. , Collaboration , brings wide range expertise problem.
|
|
|
|
|