Results 291 to 300 of about 2,103,579 (337)
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Child factor in measurement dependability
American Journal of Human Biology, 2001AbstractA primary consideration in longitudinal growth studies is the identification of growth from error components. While previous research has considered matters of measurement accuracy and reproducibility in detail, few reports have investigated the errors of measurement due to aspects of the physiology and cooperation of the child.
M, Lampl +4 more
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Novel dependence measure for dependent component analysis
2012 IEEE 11th International Conference on Signal Processing, 2012The purpose of this paper is to develop nonparametric blind signal separation (BSS) algorithm for linear dependent source signals, which is proposed under the framework of contrast method as in independent component analysis (ICA). The contrast function is derived from the Schweizer-Wolff measure of pairwise dependence between the variables. Simulation
Shaoquan Yu +3 more
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Measurement of Analog Sequential Dependencies
Human Factors: The Journal of the Human Factors and Ergonomics Society, 1964A statistic sensitive to sequential dependencies existing between responses was proposed. Two studies were undertaken to determine the validity and practicality of this measure. In the first study, results included: (1) the distribution of this measure (λ) is sufficiently normal to permit parametric analyses; (2) λ sensitively reflects both individual
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2009
Rather than geometrical weighting functions as in Chapter 2, it is preferable to obtain spatial dependence function from a set of measurements points. Prior to such a functional derivation, it is necessary to examine the isotropy and homogeneity of the spatial data directionally and the point-wise features of the regionalized variable (ReV). The basics
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Rather than geometrical weighting functions as in Chapter 2, it is preferable to obtain spatial dependence function from a set of measurements points. Prior to such a functional derivation, it is necessary to examine the isotropy and homogeneity of the spatial data directionally and the point-wise features of the regionalized variable (ReV). The basics
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Dependency clustering across measurement scales
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining, 2012How to automatically spot the major trends in large amounts of heterogeneous data? Clustering can help. However, most existing techniques suffer from one or more of the following drawbacks: 1) Many techniques support only one particular data type, most commonly numerical attributes.
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2013
In the following the validation of the time-dependent CP violation measurements prior to the unblinding of the data distributions is described. The validation comprises the measurements of lifetimes of simulated signal decays, linearity tests, the measurements on large Monte Carlo simulation samples of inclusive decays and ensemble tests.
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In the following the validation of the time-dependent CP violation measurements prior to the unblinding of the data distributions is described. The validation comprises the measurements of lifetimes of simulated signal decays, linearity tests, the measurements on large Monte Carlo simulation samples of inclusive decays and ensemble tests.
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Polarization dependent electrostrictive grating measurements
The Journal of Chemical Physics, 2007The laser induced grating spectroscopy experiments were performed with different polarizations of 1064nm laser pump beams. Thermal and electrostrictive gratings were observed in the mixture of nitrogen at high pressure with methanol vapor. Suppression of gratings by a continuous change of pump beam polarizations was verified both theoretically and ...
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Training-dependent Measurement
1994Neural networks have been applied to many fields with more successes [1]~[7]. But one feels awkward to some specious output of a trained net, such as 0.45 or 0.55. How to distinguish genuine from sham is important to the correct reasoning. In fact, the training provides us two important results.
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2000
The previous chapter has considered how dependence is generated. The next problem is to assess or quantify the dependence in a sensible way. In normal distribution models, we are familiar with using the ordinary product moment correlation (Pearson correlation) for measuring the dependence between the various coordinates.
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The previous chapter has considered how dependence is generated. The next problem is to assess or quantify the dependence in a sensible way. In normal distribution models, we are familiar with using the ordinary product moment correlation (Pearson correlation) for measuring the dependence between the various coordinates.
openaire +1 more source