Predicting benchmarked US state employment data in real time

Predicting Maximum Data Staleness in Real-Time Warehouses

This paper presents an analysis technique for estimating maximum data staleness in a data warehouse that collects “near-real-time” data streams. Data is pushed to the warehouse from a variety of external sources with a wide range of inter-arrival times (e.g., once a minute to once a day). In prior work, ad hoc heuristic algorithms have been proposed for scheduling warehouse updates. In this pap...

Improvement of the Analytical Queries Response Time in Real-Time Data Warehouse using Materialized Views Concatenation

A real-time data warehouse is a collection of recent and hierarchical data that is used for managers’ decision-making by creating online analytical queries. The volume of data collected from data sources and entered into the real-time data warehouse is constantly increasing. Moreover, as the volume of input data to the real time data warehouse increases, the interference between online loading ...

Predicting Bus Arrivals Using One Bus Away Real-Time Data

6 Providing real-time bus arrival times can enhance the experience of riders using 7 public transit, but errors in the predictions can cause a decrease in ridership. 8 Using data collected from a local transit agency, we created models to predict 9 arrival times using K-Nearest Neighbors and Kernel Regression and seven sets 10 of features. The best feature set had a RMSE of 34 seconds, a large ...

Predicting point-light actions in real-time.

There is convincing evidence for a mirror system in humans which simulates actions of conspecifics. One possible purpose of such a simulation system is to support action prediction in real-time. Our goal was to study whether the prediction of actions involves a real-time simulation process. We motion-captured a number of human actions and rendered them as point-light action sequences. Observers...

Real - Time State Machines