NASA/DOD Aerospace Knowledge Diffusion Research Project. Report 13: Source selection and information use by US aerospace engineers and scientists: Results of a telephone survey

A telephone survey of U.S. aerospace engineers and scientists belonging to the Society of Automotive Engineers (SAE) was conducted between December 4, 1991 and January 5, 1992. The survey was undertaken to (1) validate the telephone survey as an appropriate technique for collecting data from U.S. aerospace engineers and scientists; (2) collect information about how the results of NASA/DoD aerospace research are used in the R&D process; (3) identify those selection criteria which affect the use of federally-funded aerospace R&D; and (4) obtain information that could be used to develop a self-administered mail questionnaire for use with the same population. The average rating of importance of U.S. government technical reports was 2.5 (on a 4-point scale); The mean/median number of times U.S. government technical reports were used per 6 months was 8/2. Factors scoring highest for U.S. government technical reports were technical accuracy (2.9), reliable data and technical information (2.8), and contains comprehensive data and information (2.7) on a 4-point system. The factors scoring highest for influencing the use of U.S. government technical reports were relevance (3.1), technical accuracy (3.06), and reliable data/information (3.02). Ease of use, familiarity, technical accuracy, and relevance correlated with use of U.S. government technical reports. Survey demographics, survey questionnaire, and the NASA/DoD Aerospace Knowledge Diffusion Research Project publications list are included

Resolving Technological Controversies in Regulatory Agencies

Professor Shapiro notes that, e.g., advisory committees may increase technical accuracy at the price of delaying already slow rule making and urges Congress and the courts to provide agencies with broad procedural discretion

Accurate Sky Continuum Subtraction with Fibre-fed Spectrographs

Fibre-fed spectrographs now have throughputs equivalent to slit spectrographs. However, the sky subtraction accuracy that can be reached has often been pinpointed as one of the major issues associated with the use of fibres. Using technical time observations with FLAMES-GIRAFFE, two observing techniques, namely dual staring and cross beam-switching, were tested and the resulting sky subtraction accuracy reached in both cases was quantified. Results indicate that an accuracy of 0.6% on sky subtraction can be reached, provided that the cross beam-switching mode is used. This is very encouraging with regard to the detection of very faint sources with future fibre-fed spectrographs, such as VLT/MOONS or E-ELT/MOSAIC.Comment: to appear in ESO Messenger, March 201

Does priming really put the gloss on performance?

Priming has recently emerged in the literature as offering advantages in the preparation for skilled performance. Accordingly, the current study tested the efficacy of imagery against a priming paradigm as a means of enhancing motor performance: in essence, contrasting a preparation technique primarily under the conscious control of the performer to an unconscious technique promoting automaticity. The imagery intervention was guided by the PETTLEP model, while the priming intervention took the form of a scrambled sentence task. Eighteen skilled field-hockey players performed a dribbling task under imagery, priming, skill-focus, and control conditions. Results revealed a significant improvement in speed and technical accuracy for the imagery condition as opposed to the skill-focus, control, and priming conditions. In addition, there were no significant differences in performance times or technical accuracy between the priming and control conditions. The study provides further support for the efficacy of imagery to elicit enhanced motor skill performance but questions the emerging emphasis on priming as an effective tool in preparation for physical tasks

Estimating Farm Efficiency in the Presence of Double Heteroscedasticity Using Panel Data

The accuracy of technical efficiency measures is important given the interest in such measures in policy discussions. In recent years the use of stochastic frontiers has become popular for estimating technical inefficiency, but estimated inefficiencies are sensitive to specification errors. One source of such errors is heteroscedasticity. This paper addresses this issue by extending the Hadri (1999) correction for heteroscedasticity to stochastic production frontiers and to panel data. It is argued that heteroscedasticity within an estimation can have a significant effect on results, and that correcting for heteroscedasticity yields more accurate measures of technical inefficiency. Using panel data on cereal farms, it is found that the usual technical efficiency measures used in stochastic production frontiers are significantly sensitive to the extended correction for heteroscedasticity.stochastic frontier production, heteroscedasticity, technical efficiency, panel data

Inventory of available data elements for the San Bernardino, California region

Elements of data sets that are available to be integrated for the San Bernardino vertical data integration project are given. Each of the data sets has specified for it the ownership, validity, accuracy and technical requirements for integration

Feedback of information in the empathic accuracy of sport coaches

Objective The purpose of this study was to investigate changes in the empathic accuracy of sport coaches in relation to feedback of information. Coaches' experience and qualification level were also considered. Method Sixty badminton coaches were randomly assigned to either an experimental or a control group. All coaches watched a video of an athlete's technical training session with her coach. At designated segments of the video all coaches were asked to make inferences about what the athlete's thoughts and feelings had been. Only the coaches in the experimental group were given corrective feedback on the athlete's thoughts and feelings following their inference. Empathic accuracy was estimated by comparing these inferences with the athlete's own self-reported thoughts and feelings. Results It was shown that both groups' empathic accuracy improved over the course of watching the video; however, the experimental group improved significantly more. It was found that coaches' experience was significantly associated with empathic accuracy for the control group only. Conclusions The results suggest that continued exposure to an athlete increases a coach's empathic accuracy and that this can be significantly improved with accurate feedback about that athlete

Evaluation of the Performance of the Markov Blanket Bayesian Classifier Algorithm

The Markov Blanket Bayesian Classifier is a recently-proposed algorithm for construction of probabilistic classifiers. This paper presents an empirical comparison of the MBBC algorithm with three other Bayesian classifiers: Naive Bayes, Tree-Augmented Naive Bayes and a general Bayesian network. All of these are implemented using the K2 framework of Cooper and Herskovits. The classifiers are compared in terms of their performance (using simple accuracy measures and ROC curves) and speed, on a range of standard benchmark data sets. It is concluded that MBBC is competitive in terms of speed and accuracy with the other algorithms considered.Comment: 9 pages: Technical Report No. NUIG-IT-011002, Department of Information Technology, National University of Ireland, Galway (2002

Impact of variance components on reliability of absolute quantification using digital PCR

Background: Digital polymerase chain reaction (dPCR) is an increasingly popular technology for detecting and quantifying target nucleic acids. Its advertised strength is high precision absolute quantification without needing reference curves. The standard data analytic approach follows a seemingly straightforward theoretical framework but ignores sources of variation in the data generating process. These stem from both technical and biological factors, where we distinguish features that are 1) hard-wired in the equipment, 2) user-dependent and 3) provided by manufacturers but may be adapted by the user. The impact of the corresponding variance components on the accuracy and precision of target concentration estimators presented in the literature is studied through simulation. Results: We reveal how system-specific technical factors influence accuracy as well as precision of concentration estimates. We find that a well-chosen sample dilution level and modifiable settings such as the fluorescence cut-off for target copy detection have a substantial impact on reliability and can be adapted to the sample analysed in ways that matter. User-dependent technical variation, including pipette inaccuracy and specific sources of sample heterogeneity, leads to a steep increase in uncertainty of estimated concentrations. Users can discover this through replicate experiments and derived variance estimation. Finally, the detection performance can be improved by optimizing the fluorescence intensity cut point as suboptimal thresholds reduce the accuracy of concentration estimates considerably. Conclusions: Like any other technology, dPCR is subject to variation induced by natural perturbations, systematic settings as well as user-dependent protocols. Corresponding uncertainty may be controlled with an adapted experimental design. Our findings point to modifiable key sources of uncertainty that form an important starting point for the development of guidelines on dPCR design and data analysis with correct precision bounds. Besides clever choices of sample dilution levels, experiment-specific tuning of machine settings can greatly improve results. Well-chosen data-driven fluorescence intensity thresholds in particular result in major improvements in target presence detection. We call on manufacturers to provide sufficiently detailed output data that allows users to maximize the potential of the method in their setting and obtain high precision and accuracy for their experiments