Deassociate the initial temporal phase deviation provided by photoelastic modulator for stroboscopic illumination polarization modulated ellipsometry

2011 ◽  
Vol 82 (3) ◽  
pp. 035117 ◽  
Author(s):  
Hsiu-Ming Tsai ◽  
Chih-Wei Chen ◽  
Tsung-Han Tsai ◽  
Yu-Faye Chao
Keyword(s):  
Temporal Phase ◽  
Photoelastic Modulator ◽  
Stroboscopic Illumination ◽  
Phase Deviation

scholarly journals Measuring sleep regularity: Theoretical properties and practical usage of existing metrics

SLEEP ◽  
2021 ◽  
Author(s):  
Dorothee Fischer ◽  
Elizabeth B Klerman ◽  
Andrew J K Phillips
Keyword(s):  
Large Scale ◽  
Research Question ◽  
Group Differences ◽  
Regularity Index ◽  
Wake Patterns ◽  
Health Related ◽  
Phase Deviation ◽  
Unbiased Estimates ◽  
Large Scale Simulations ◽  
Larger Sample

Abstract Study Objectives Sleep regularity predicts many health-related outcomes. Currently, however, there is no systematic approach to measuring sleep regularity. Traditionally, metrics have assessed deviations in sleep patterns from an individual’s average. Traditional metrics include intra-individual standard deviation (StDev), Interdaily Stability (IS), and Social Jet Lag (SJL). Two metrics were recently proposed that instead measure variability between consecutive days: Composite Phase Deviation (CPD) and Sleep Regularity Index (SRI). Using large-scale simulations, we investigated the theoretical properties of these five metrics. Methods Multiple sleep-wake patterns were systematically simulated, including variability in daily sleep timing and/or duration. Average estimates and 95% confidence intervals were calculated for six scenarios that affect measurement of sleep regularity: ‘scrambling’ the order of days; daily vs. weekly variation; naps; awakenings; ‘all-nighters’; and length of study. Results SJL measured weekly but not daily changes. Scrambling did not affect StDev or IS, but did affect CPD and SRI; these metrics, therefore, measure sleep regularity on multi-day and day-to-day timescales, respectively. StDev and CPD did not capture sleep fragmentation. IS and SRI behaved similarly in response to naps and awakenings but differed markedly for all-nighters. StDev and IS required over a week of sleep-wake data for unbiased estimates, whereas CPD and SRI required larger sample sizes to detect group differences. Conclusions Deciding which sleep regularity metric is most appropriate for a given study depends on a combination of the type of data gathered, the study length and sample size, and which aspects of sleep regularity are most pertinent to the research question.

scholarly journals High-Q photonic chip-based temporal phase plates for electron microscopy

2021 ◽  
Vol 27 (S1) ◽  
pp. 3132-3133
Author(s):  
Armin Feist ◽  
Arslan Sajid Raja ◽  
Jan-Wilke Henke ◽  
Junqiu Liu ◽  
Germaine Arend ◽  
...  
Keyword(s):  
Electron Microscopy ◽  
High Q ◽  
Temporal Phase ◽  
Phase Plates

scholarly journals High-Quality Pixel Selection Applied for Natural Scenes in GB-SAR Interferometry

2021 ◽  
Vol 13 (9) ◽  
pp. 1617
Author(s):  
Yunkai Deng ◽  
Weiming Tian ◽  
Ting Xiao ◽  
Cheng Hu ◽  
Hong Yang
Keyword(s):  
Phase Measurement ◽  
High Amplitude ◽  
Sar Interferometry ◽  
Spatial Density ◽  
Natural Scenes ◽  
Sar Images ◽  
High Quality ◽  
Temporal Phase ◽  
Permanent Scatterers ◽  
High Phase

Phase analysis based on high-quality pixel (HQP) is crucial to ensure the measurement accuracy of ground-based SAR (GB-SAR). The amplitude dispersion (ADI) criterion has been widely applied to identify pixels with high amplitude stability, i.e., permanent scatterers (PSs), which typically are point-wise scatterers such as stones or man-made structures. However, the PS number in natural scenes is few and limits the GB-SAR applications. This paper proposes an improved method to take HQP selection applied for natural scenes in GB-SAR interferometry. In order to increase the spatial density of HQP for phase measurement, three types of HQPs including PS, quasi-permanent scatter (QPS), and distributed scatter (DS), are selected with different criteria. The ADI method is firstly utilized to take PS selection. To select those pixels with high phase stability but moderate amplitude stability, the temporal phase coherence (TPC) is defined. Those pixels with moderate ADI values and high TPC are selected as QPSs. Then the feasibility of the DS technique is explored. To validate the feasibility of the proposed method, 2370 GB-SAR images of a natural slope are processed. Experimental results prove that the HQP number could be significantly increased while slightly sacrificing phase quality.

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