Plane‐Wave Tube for Low‐Audio‐Frequency and Infrasonic Acoustic Measurements

1970 ◽  
Vol 47 (5A) ◽  
pp. 1145-1149
Author(s):  
Austin J. Brouns
2017 ◽  
Vol 141 (5) ◽  
pp. 3677-3677 ◽  
Author(s):  
Tung Shen Chew ◽  
Arthur Zhao ◽  
Robert Littrell

2017 ◽  
Author(s):  
Daxton Hawks ◽  
Tracianne B. Neilsen ◽  
Kent L. Gee ◽  
Scott D. Sommerfeldt

Author(s):  
J. M. Pankratz

It is often desirable in transmission electron microscopy to know the vertical spacing of points of interest within a specimen. However, in order to measure a stereo effect, one must have two pictures of the same area taken from different angles, and one must have also a formula for converting measured differences between corresponding points (parallax) into a height differential.Assume (a) that the impinging beam of electrons can be considered as a plane wave and (b) that the magnification is the same at the top and bottom of the specimen. The first assumption is good when the illuminating system is overfocused. The second assumption (the so-called “perspective error”) is good when the focal length is large (3 x 107Å) in relation to foil thickness (∼103 Å).


2020 ◽  
Vol 63 (12) ◽  
pp. 3991-3999
Author(s):  
Benjamin van der Woerd ◽  
Min Wu ◽  
Vijay Parsa ◽  
Philip C. Doyle ◽  
Kevin Fung

Objectives This study aimed to evaluate the fidelity and accuracy of a smartphone microphone and recording environment on acoustic measurements of voice. Method A prospective cohort proof-of-concept study. Two sets of prerecorded samples (a) sustained vowels (/a/) and (b) Rainbow Passage sentence were played for recording via the internal iPhone microphone and the Blue Yeti USB microphone in two recording environments: a sound-treated booth and quiet office setting. Recordings were presented using a calibrated mannequin speaker with a fixed signal intensity (69 dBA), at a fixed distance (15 in.). Each set of recordings (iPhone—audio booth, Blue Yeti—audio booth, iPhone—office, and Blue Yeti—office), was time-windowed to ensure the same signal was evaluated for each condition. Acoustic measures of voice including fundamental frequency ( f o ), jitter, shimmer, harmonic-to-noise ratio (HNR), and cepstral peak prominence (CPP), were generated using a widely used analysis program (Praat Version 6.0.50). The data gathered were compared using a repeated measures analysis of variance. Two separate data sets were used. The set of vowel samples included both pathologic ( n = 10) and normal ( n = 10), male ( n = 5) and female ( n = 15) speakers. The set of sentence stimuli ranged in perceived voice quality from normal to severely disordered with an equal number of male ( n = 12) and female ( n = 12) speakers evaluated. Results The vowel analyses indicated that the jitter, shimmer, HNR, and CPP were significantly different based on microphone choice and shimmer, HNR, and CPP were significantly different based on the recording environment. Analysis of sentences revealed a statistically significant impact of recording environment and microphone type on HNR and CPP. While statistically significant, the differences across the experimental conditions for a subset of the acoustic measures (viz., jitter and CPP) have shown differences that fell within their respective normative ranges. Conclusions Both microphone and recording setting resulted in significant differences across several acoustic measurements. However, a subset of the acoustic measures that were statistically significant across the recording conditions showed small overall differences that are unlikely to have clinical significance in interpretation. For these acoustic measures, the present data suggest that, although a sound-treated setting is ideal for voice sample collection, a smartphone microphone can capture acceptable recordings for acoustic signal analysis.


1997 ◽  
Vol 92 (3) ◽  
pp. 477-487 ◽  
Author(s):  
GERALD LIPPERT ◽  
JuRG HUTTER ◽  
MICHELE PARRINELLO

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