scholarly journals Search and graphical display of hazardous blocks in underground roadway roofs

Author(s):  
Qingfa Chen ◽  
Shikang Qin ◽  
Tingchang Yin ◽  
Wenshi Zhen
1988 ◽  
Vol 102 ◽  
pp. 107-110
Author(s):  
A. Burgess ◽  
H.E. Mason ◽  
J.A. Tully

AbstractA new way of critically assessing and compacting data for electron impact excitation of positive ions is proposed. This method allows one (i) to detect possible printing and computational errors in the published tables, (ii) to interpolate and extrapolate the existing data as a function of energy or temperature, and (iii) to simplify considerably the storage and transfer of data without significant loss of information. Theoretical or experimental collision strengths Ω(E) are scaled and then plotted as functions of the colliding electron energy, the entire range of which is conveniently mapped onto the interval (0,1). For a given transition the scaled Ω can be accurately represented - usually to within a fraction of a percent - by a 5 point least squares spline. Further details are given in (2). Similar techniques enable thermally averaged collision strengths upsilon (T) to be obtained at arbitrary temperatures in the interval 0 < T < ∞. Application of the method is possible by means of an interactive program with graphical display (2). To illustrate this practical procedure we use the program to treat Ω for the optically allowed transition 2s → 2p in ArXVI.


2020 ◽  
Vol 228 (1) ◽  
pp. 43-49 ◽  
Author(s):  
Michael Kossmeier ◽  
Ulrich S. Tran ◽  
Martin Voracek

Abstract. Currently, dedicated graphical displays to depict study-level statistical power in the context of meta-analysis are unavailable. Here, we introduce the sunset (power-enhanced) funnel plot to visualize this relevant information for assessing the credibility, or evidential value, of a set of studies. The sunset funnel plot highlights the statistical power of primary studies to detect an underlying true effect of interest in the well-known funnel display with color-coded power regions and a second power axis. This graphical display allows meta-analysts to incorporate power considerations into classic funnel plot assessments of small-study effects. Nominally significant, but low-powered, studies might be seen as less credible and as more likely being affected by selective reporting. We exemplify the application of the sunset funnel plot with two published meta-analyses from medicine and psychology. Software to create this variation of the funnel plot is provided via a tailored R function. In conclusion, the sunset (power-enhanced) funnel plot is a novel and useful graphical display to critically examine and to present study-level power in the context of meta-analysis.


2021 ◽  
pp. 109467052110124
Author(s):  
Sarah Köcher ◽  
Sören Köcher

In this article, the authors demonstrate a tendency among consumers to use the arithmetic mode as a heuristic basis when drawing inferences from graphical displays of online rating distributions in such a way that service evaluations inferred from rating distributions systematically vary by the location of the mode. The rationale underlying this phenomenon is that the mode (i.e., the most frequent rating which is represented by the tallest bar in a graphical display) attracts consumers’ attention because of its visual salience and is thus disproportionately weighted when they draw conclusions. Across a series of eight studies, the authors provide strong empirical evidence for the existence of the mode heuristic, shed light on this phenomenon at the process level, and demonstrate how consumers’ inferences based on the mode heuristic depend on the visual salience of the mode. Together, the findings of these studies contribute to a better understanding of how service customers process and interpret graphical illustrations of online rating distributions and provide companies with a new key figure that—aside from rating volume, average ratings, and rating dispersion—should be incorporated in the monitoring, analyzing, and evaluating of review data.


1997 ◽  
Vol 31 (SI) ◽  
pp. 236-245 ◽  
Author(s):  
Aravindan Veerasamy ◽  
Russell Heikes
Keyword(s):  

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