Phase Correlation Processing for DPIV Measurements: Part I — Spatial Domain Analysis

Volume 1: Symposia, Parts A and B ◽

10.1115/fedsm2007-37286 ◽

2007 ◽

Author(s):

Adric C. Eckstein ◽

John J. Charonko ◽

Pavlos P. Vlachos

Keyword(s):

Nonlinear Filtering ◽

Cross Correlation ◽

Correlation Method ◽

Spatial Filter ◽

Phase Correlation ◽

Image Correlation ◽

Superior Performance ◽

Spatial Filters ◽

Cross Correlation Analysis ◽

Improve Measurement

A novel Digital Particle Image Velocimetry (DPIV) correlation method is presented using nonlinear filtering techniques coupled with a phase-only filter (POF) generalized cross-correlation (GCC). Error analysis demonstrates the deficiency of the GCC alone to successfully improve measurement accuracy, as shown from a decrease in valid vector detection as well as an increase in bias and RMS errors. The use of spatial filters is commonly argued to be disadvantageous for standard Fourier based cross-correlation analysis [1]. However, here we demonstrate that appropriate spatial filters applied to the GCC provide vastly superior performance. The zeropadding method as well as a new spatial filter derived from the Blackman window is introduced, both of which are able to enhance the vector detection capabilities of the GCC processor. In addition, a Gaussian transform filtering technique is introduced which dramatically increases the subpixel resolution of the GCC processor, alleviating apparent effects of peak-locking. The use of these filters with the GCC is able to provide striking improvements in DPIV image correlation.

Download Full-text

Multi-color fluorescence fluctuation spectroscopy in living cells via spectral detection

10.1101/2020.12.18.423407 ◽

2020 ◽

Author(s):

Valentin Dunsing ◽

Annett Petrich ◽

Salvatore Chiantia

Keyword(s):

Correlation Analysis ◽

Influenza A ◽

Cross Correlation ◽

Matrix Protein ◽

Living Cells ◽

Correlation Spectroscopy ◽

Image Correlation ◽

Fluorescence Fluctuation Spectroscopy ◽

Diffusion Dynamics ◽

Cross Correlation Analysis

AbstractFluorescence fluctuation spectroscopy provides a powerful toolbox to quantify transport dynamics and interactions between biomolecules in living cells. For example, cross-correlation analysis of spectrally separated fluctuations allows the investigation of inter-molecular interactions. This analysis is conventionally limited to two fluorophore species that are excited with a single or two different laser lines and detected in two non-overlapping spectral channels. However, signaling pathways in biological systems often involve interactions between multiple biomolecules, e.g. formation of ternary or quaternary protein complexes. Here, we present a methodology to investigate such interactions at the plasma membrane (PM) of cells, as encountered for example in viral assembly or receptor-ligand interactions. To this aim, we introduce scanning fluorescence spectral correlation spectroscopy (SFSCS), a combination of scanning fluorescence correlation spectroscopy with spectrally resolved detection and decomposition. We first demonstrate that SFSCS allows cross-talk-free cross-correlation analysis of PM-associated proteins labeled with strongly overlapping fluorescent proteins (FPs), such as mEGFP and mEYFP, excited with a single excitation line. We then verify the applicability of SFSCS for quantifying diffusion dynamics and protein oligomerization (based on molecular brightness analysis) of two protein species tagged with spectrally overlapping FPs. Adding a second laser line, we demonstrate the possibility of three- and four-species (cross-) correlation analysis using mApple and mCherry2, as examples of strongly overlapping FP tags in the red spectral region. Next, we apply this scheme to investigate the interactions of influenza A virus (IAV) matrix protein 2 (M2) with two cellular host factors simultaneously. Using the same set of fluorophores, we furthermore extend the recently presented raster spectral image correlation spectroscopy (RSICS) approach to four species analysis, successfully demonstrating multiplexed RSICS measurements of protein interactions in the cell cytoplasm. Finally, we apply RSICS to investigate the assembly of the ternary IAV polymerase complex and report a 2:2:2 stoichiometry of these protein assemblies in the nucleus of living cells.

Download Full-text

Feature Analysis of Degradation Signal of Rolling Stock Lateral Damper

Information ◽

10.3390/info11060298 ◽

2020 ◽

Vol 11 (6) ◽

pp. 298

Author(s):

Zhiyan Zhao ◽

Bin Wu ◽

Ting Zhou

Keyword(s):

Cross Correlation ◽

Wavelet Packet ◽

Reference Signal ◽

Correlation Method ◽

Health Condition ◽

Wavelet Packet Transform ◽

Rolling Stock ◽

Health State ◽

Vibration Signals ◽

Cross Correlation Analysis

The lateral damper is one of the key components of rolling stock. Establishing the relationship between the degraded signal and the health state of the lateral damper is important in order to perform timely performance detection and fault diagnosis. This paper proposes a wavelet packet cross-correlation method (WPCC) that is based on wavelet packet transform (WPT) and cross-correlation analysis (CCA). First, the vibration signals under different running speeds, different running conditions, and different track excitations were collected and analyzed. Second, the wavelet packet transform was used to select larger energy band signals for reconstruction. Subsequently, the WPCC coefficient was calculated between the reference signal and the signal to be measured. The proposed method was applied to analysis of vibration signals of the lateral damper performance degradation. The lateral damper health condition was divided into four intervals, and the average accuracy calculated under different running speeds, different running conditions, and different track excitation was 95%.

Download Full-text

Wavelet Cross-Correlation Analysis of the Unsteady Signals of the Flow in the Open Sump

Volume 1 ◽

10.1115/ht-fed2004-56207 ◽

2004 ◽

Author(s):

Mansa Kante ◽

Yulin Wu ◽

Yong Li ◽

Shuhong Liu ◽

Daqing Zhou

Keyword(s):

Cross Correlation ◽

Correlation Method ◽

Vibration Signal ◽

Structural Similarity ◽

Signal Distribution ◽

Cross Correlation Analysis ◽

Correlation Scale ◽

Pump Sump ◽

The Relationship ◽

Signal Analysis Method

The wavelet cross-correlation method was used to analyze the unsteady signals of the flow of the model open pump sump, which include pressure signal, vibration signal and acoustic signal. The continuous wavelet transform was done first to find the signal distribution at various periods and at any time, then the wavelet cross-correlation was used to find the relationship between the signals taken two a two. Through comparing the result of wavelet cross-correlation and the result of classic cross-correlation, one can find the correlation scale of any two unsteady signals (pressure-vibration, pressure-noise, and vibration-noise). The signal on the correlation scale was reconstruct and its characteristics were obtained using classical signal analysis method same as the structural similarity of a arbitrary two signals.

Download Full-text

Fluctuation Characteristics of Water Level and Water Temperature of Huize Well Based on MF-DCCA

International Journal of Heat and Technology ◽

10.18280/ijht.390316 ◽

2021 ◽

Vol 39 (3) ◽

pp. 825-832

Author(s):

Jian Yu ◽

Lili Sui ◽

Yirong Xu ◽

Baoming Chi

Keyword(s):

Time Series ◽

Water Temperature ◽

Water Level ◽

Cross Correlation ◽

Correlation Method ◽

Multifractal Spectrum ◽

Earthquake Precursor ◽

Observation Data ◽

Cross Correlation Analysis ◽

Abnormal Increase

In recent decades, the network of seismic subsurface fluid observatories is developing constantly, the observation data of subsurface fluids are enriched accordingly, which provides a favorable condition for the research on the formation, occurrence, and development of earthquakes. In the observation data of subsurface fluids, water level and water temperature changes are very important observation indicators, and their fluctuation sequences are quite complicated. Therefore, this paper employed a non-linear cross-correlation method to study the relationship between the water level and water temperature of Huize Well from 2004 to 2006, and found that there’s a significant cross-correlation between the time series of water level and water temperature; then, this study adopted DCCA (detrended cross-correlation analysis) to calculate the cross-correlation coefficient under different scales and explore the continuous changes of water level and water temperature; at last, this paper used the MF-DCCA (Multifractal-DCCA) method to prove that there’s multifractal cross-correlation between the time series of water level and water temperature. Before the M5.1 earthquake in Huize area, there’s an abnormal increase in the width of the multifractal spectrum of the water level and water temperature drawn with a sliding window of 500-hour, and this is a possible earthquake precursor.

Download Full-text

A qualitative study of the seismo-ionospheric precursors prior to the 6 April 2009 earthquake in L'Aquila, Italy

Natural Hazards and Earth System Science ◽

10.5194/nhess-10-133-2010 ◽

2010 ◽

Vol 10 (1) ◽

pp. 133-137 ◽

Cited By ~ 20

Author(s):

G. S. Tsolis ◽

T. D. Xenos

Keyword(s):

Correlation Coefficient ◽

Cross Correlation ◽

Seismic Event ◽

Correlation Method ◽

L’Aquila Earthquake ◽

Earthquake Preparation ◽

Mode Decomposition ◽

Cross Correlation Analysis ◽

Correlation Analysis Method ◽

The Cross

Abstract. In this paper we use the Cross Correlation analysis method in conjunction with the Empirical Mode Decomposition to analyze foF2 signals collected from Rome, Athens and San Vito ionospheric stations, in order to verify the existence of seismo-ionospheric precursors prior to M=6.3 L'Aquila earthquake in Italy. The adaptive nature of EMD allows for removing the geophysical noise from the foF2 signals, and then to calculate the correlation coefficient between them. According to the cross correlation coefficient theory, we expect the stations which located inside the earthquake preparation area, as evaluated using Dobrovolsky equation, to capture the ionospheric disturbances generated by the seismic event. On the other hand the stations outside of this area are expected to remain unaffected. The results of our study are in accordance with the theoretical model, evidencing ionospheric modification prior to L'Aquila earthquake in a certain area around the epicenter. However, it was found that the selection of stations at the limits of the theoretically estimated earthquake preparation area is not the best choice when the cross correlation method is applied, since the modification of the ionosphere over these stations may not be enough for the ionospheric precursors to appear. Our experimental results also show that when a seismic event constitutes the main shock after a series of pre-seismic activity, precursors may appear as early as 22 days prior to the event.

Download Full-text

Application of an Improved Correlation Method in Electrostatic Gait Recognition of Hemiparetic Patients

Sensors ◽

10.3390/s19112529 ◽

2019 ◽

Vol 19 (11) ◽

pp. 2529 ◽

Cited By ~ 1

Author(s):

Shanshan Tian ◽

Mengxuan Li ◽

Yifei Wang ◽

Xi Chen

Keyword(s):

Correlation Analysis ◽

Correlation Coefficient ◽

Cross Correlation ◽

Correlation Method ◽

Disease Diagnosis ◽

Characteristic Analysis ◽

Cross Correlation Analysis ◽

Gait Characteristic ◽

Scaling Index ◽

Coefficient Method

Hemiparesis is one of the common sequelae of neurological diseases such as strokes, which can significantly change the gait behavior of patients and restrict their activities in daily life. The results of gait characteristic analysis can provide a reference for disease diagnosis and rehabilitation; however, gait correlation as a gait characteristic is less utilized currently. In this study, a new non-contact electrostatic field sensing method was used to obtain the electrostatic gait signals of hemiplegic patients and healthy control subjects, and an improved Detrended Cross-Correlation Analysis cross-correlation coefficient method was proposed to analyze the obtained electrostatic gait signals. The results show that the improved method can better obtain the dynamic changes of the scaling index under the multi-scale structure, which makes up for the shortcomings of the traditional Detrended Cross-Correlation Analysis cross-correlation coefficient method when calculating the electrostatic gait signal of the same kind of subjects, such as random and incomplete similarity in the trend of the scaling index spectrum change. At the same time, it can effectively quantify the correlation of electrostatic gait signals in subjects. The proposed method has the potential to be a powerful tool for extracting the gait correlation features and identifying the electrostatic gait of hemiplegic patients.

Download Full-text

Multi-color fluorescence fluctuation spectroscopy in living cells via spectral detection

eLife ◽

10.7554/elife.69687 ◽

2021 ◽

Vol 10 ◽

Author(s):

Valentin Dunsing ◽

Annett Petrich ◽

Salvatore Chiantia

Keyword(s):

Influenza A ◽

Cross Correlation ◽

Matrix Protein ◽

Living Cells ◽

Correlation Spectroscopy ◽

Image Correlation ◽

Protein Species ◽

Fluorescence Fluctuation Spectroscopy ◽

Spectral Correlation ◽

Cross Correlation Analysis

Signaling pathways in biological systems rely on specific interactions between multiple biomolecules. Fluorescence fluctuation spectroscopy provides a powerful toolbox to quantify such interactions directly in living cells. Cross-correlation analysis of spectrally separated fluctuations provides information about inter-molecular interactions but is usually limited to two fluorophore species. Here, we present scanning fluorescence spectral correlation spectroscopy (SFSCS), a versatile approach that can be implemented on commercial confocal microscopes, allowing the investigation of interactions between multiple protein species at the plasma membrane. We demonstrate that SFSCS enables cross-talk-free cross-correlation, diffusion and oligomerization analysis of up to four protein species labeled with strongly overlapping fluorophores. As an example, we investigate the interactions of influenza A virus (IAV) matrix protein 2 with two cellular host factors simultaneously. We furthermore apply raster spectral image correlation spectroscopy for the simultaneous analysis of up to four species and determine the stoichiometry of ternary IAV polymerase complexes in the cell nucleus.

Download Full-text

Comparison of Deterministic and Linear Cosine Spatial Filtering of Transmission Electron Micrographs

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100096230 ◽

1972 ◽

Vol 30 ◽

pp. 596-597

Author(s):

David A. Ansley

Keyword(s):

Spherical Aberration ◽

Focal Length ◽

Chromatic Aberration ◽

Spatial Filter ◽

Operating Conditions ◽

Objective Lens ◽

List Type ◽

Spatial Filters ◽

Transmission Electron ◽

Wide Range

The coherence of the electron flux of a transmission electron microscope (TEM) limits the direct application of deconvolution techniques which have been used successfully on unmanned spacecraft programs. The theory assumes noncoherent illumination. Deconvolution of a TEM micrograph will, therefore, in general produce spurious detail rather than improved resolution.A primary goal of our research is to study the performance of several types of linear spatial filters as a function of specimen contrast, phase, and coherence. We have, therefore, developed a one-dimensional analysis and plotting program to simulate a wide 'range of operating conditions of the TEM, including adjustment of the:(1) Specimen amplitude, phase, and separation(2) Illumination wavelength, half-angle, and tilt(3) Objective lens focal length and aperture width(4) Spherical aberration, defocus, and chromatic aberration focus shift(5) Detector gamma, additive, and multiplicative noise constants(6) Type of spatial filter: linear cosine, linear sine, or deterministic

Download Full-text

Application of cross correlation to HREM images of surfaces

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100128080 ◽

1987 ◽

Vol 45 ◽

pp. 754-755

Author(s):

D. E. Luzzi ◽

L. D. Marks ◽

M. I. Buckett

Keyword(s):

Cross Correlation ◽

A Priori ◽

Matrix Material ◽

Correlation Method ◽

Accurate Knowledge ◽

Complex Image ◽

Fourier Filtering ◽

The Matrix ◽

Low Pass ◽

Data Reduction Technique

As the HREM becomes increasingly used for the study of dynamic localized phenomena, the development of techniques to recover the desired information from a real image is important. Often, the important features are not strongly scattering in comparison to the matrix material in addition to being masked by statistical and amorphous noise. The desired information will usually involve the accurate knowledge of the position and intensity of the contrast. In order to decipher the desired information from a complex image, cross-correlation (xcf) techniques can be utilized. Unlike other image processing methods which rely on data massaging (e.g. high/low pass filtering or Fourier filtering), the cross-correlation method is a rigorous data reduction technique with no a priori assumptions.We have examined basic cross-correlation procedures using images of discrete gaussian peaks and have developed an iterative procedure to greatly enhance the capabilities of these techniques when the contrast from the peaks overlap.

Download Full-text