A mobile data acquisition system

A mobile data aquisition (MobiDAQ) was developed for the ATLAS central hadronic calorimeter (TileCal). MobiDAQ has been designed in order to test the functionalities of the TileCal front-end electronics and to acquire calibration data before the final back-end electronics were built and tested. MobiDAQ was also used to record the first cosmic ray events acquired by an ATLAS subdetector in the underground experimental area

FIREBALL: Detector, data acquisition and reduction

The Faint Intergalactic Redshifted Emission Balloon (FIREBALL) had its first scientific flight in June 2009. The instrument combines microchannel plate detector technology with fiber-fed integral field spectroscopy on an unstable stratospheric balloon gondola platform. This unique combination poses a series of calibration and data reduction challenges that must be addressed and resolved to allow for accurate data analysis. We discuss our approach and some of the methods we are employing to accomplish this task

Optimal Data Acquisition for Statistical Estimation

We consider a data analyst's problem of purchasing data from strategic agents to compute an unbiased estimate of a statistic of interest. Agents incur private costs to reveal their data and the costs can be arbitrarily correlated with their data. Once revealed, data are verifiable. This paper focuses on linear unbiased estimators. We design an individually rational and incentive compatible mechanism that optimizes the worst-case mean-squared error of the estimation, where the worst-case is over the unknown correlation between costs and data, subject to a budget constraint in expectation. We characterize the form of the optimal mechanism in closed-form. We further extend our results to acquiring data for estimating a parameter in regression analysis, where private costs can correlate with the values of the dependent variable but not with the values of the independent variables

Trigger and data acquisition

The lectures address some of the issues of triggering and data acquisition in large high-energy physics experiments. Emphasis is placed on hadron-collider experiments that present a particularly challenging environment for event selection and data collection. However, the lectures also explain how T/DAQ systems have evolved over the years to meet new challenges. Some examples are given from early experience with LHC T/DAQ systems during the 2008 single-beam operations.Comment: 32 pages, Lectures given at the 5th CERN-Latin-American School of High-Energy Physics, Recinto Quirama, Colombia, 15 - 28 Mar 200

Automatic probabilistic knowledge acquisition from data

A computer program for extracting significant correlations of attributes from masses of data is outlined. This information can then be used to develop a knowledge base for a probabilistic expert system. The method determines the best estimate of joint probabilities of attributes from data put into contingency table form. A major output from the program is a general formula for calculating any probability relation associated with the data. These probability relations can be utilized to form IF-THEN rules with associated probability, useful for expert systems

New data acquisition system records bearing measurements directly

Digital data acquisition system records steady state and dynamic data of bearing and shaft displacement. Elliptical orbits formed can be reconstructed and the data reduced automatically. System also reads pressures, temperatures, flows, and torque during any one data scan