Direct Cross-correlation Research Articles

Background-Oriented Schlieren (BOS) for Scramjet Inlet-isolator Investigation

Background-oriented Schlieren (BOS) technique is a recently invented non-intrusive flow diagnostic method which has yet to be fully explored in its capabilities. In this paper, BOS technique has been applied for investigating the general flow field characteristics inside a generic scramjet inlet-isolator with Mach 5 flow. The difficulty in finding the delicate balance between measurement sensitivity and measurement area image focusing has been demonstrated. The differences between direct cross-correlation (DCC) and Fast Fourier Transform (FFT) raw data processing algorithm have also been demonstrated. As an exploratory study of BOS capability, this paper found that BOS is simple yet robust enough to be used to visualize complex flow in a scramjet inlet in hypersonic flow. However, in this case its quantitative data can be strongly affected by 3-dimensionality thus obscuring the density value with significant errors.

Image analysis for velocity profile estimation in A-SOFT hybrid rocket combustor

Altering-intensity Swirling-Oxidizer-Flow-Type (A-SOFT) hybrid rocket engine (HRE) was proposed as a technique to solve problems of current hybrid rockets. It uses axial and tangential oxidizer injections and their mass flow rates are manipulated independently to control the thrust and O/F. The visualization experiment of combustion of gaseous oxygen (GOX) and polymethyl methacrylate (PMMA) of A-SOFT HRE is carried out under combustion pressure of 1 bar. Combustion gas flow in the combustor is captured by high speed cameras whose fps is 30000. In order to capture the nature of the flow field quantitatively, obtaining velocity profiles by image analysis applied to its visualization images is effective. Basic image analysis method is Direct Cross Correlation method and, for high precision and spatial resolution, Correlation Based Correction is applied recursively. Averaged velocity profiles are obtained by averaging the calculation results of 10000 images corresponding to the actual time duration of 0.3 s. Flames with strong white light emission are characteristic of hybrid rockets and regarded as traceable markers for the image analysis. These luminous flames are considered to flow in the boundary layer and velocity of flames in the boundary layer is important to capture the characteristics of combustion flow field. Axial velocity of the luminous flame is proportional to the total mixed mass flow rate for each location x. Tangential velocity is proportional to angular momentum given by tangential GOX injection and inversely proportional to the total mixed mass flow rate for each location x. And how much GOX injected in axial and tangential directions are mixed is speculated by velocity profiles. It is found that mixing of GOX injected in axial and tangential directions occurs at almost the same constant rate regardless of the ratio of GOX mass flow rate injected in axial and tangential directions.

Semblance of Heterogeneity in Collective Cell Migration

Cell population heterogeneity is increasingly a focus of inquiry in biological research. For example, cell migration studies have investigated the heterogeneity of invasiveness and taxis in development, wound healing, and cancer. However, relatively little effort has been devoted to exploring when heterogeneity is mechanistically relevant and how to reliably measure it. Statistical methods from the animal movement literature offer the potential to analyze heterogeneity in collections of cell tracking data. A popular measure of heterogeneity, which we use here as an example, is the distribution of delays in directional cross-correlation. Employing a suitably generic, yet minimal, model of collective cell movement in three dimensions, we show how using such measures to quantify heterogeneity in tracking data can result in the inference of heterogeneity where there is none. Our study highlights a potential pitfall in the statistical analysis of cell population heterogeneity, and we argue that this can be mitigated by the appropriate choice of null models.

Constraining multiplicative bias in CFHTLenS weak lensing shear data

Several recent cosmological analyses have found tension between constraints derived from the Canada-France-Hawaii Telescope Lensing Survey (CFHTLenS) data and those derived from other data sets, such as the Planck cosmic microwave background (CMB) temperature anisotropies. Similarly, a direct cross-correlation of the CFHTLenS data with Planck CMB lensing data yielded an anomalously low amplitude compared to expectations based on Planck or WMAP-derived cosmological parameters (Liu & Hill 2015). One potential explanation for these results is a multiplicative bias afflicting the CFHTLenS galaxy shape measurements, from which shears are inferred. Simulations are used in the CFHTLenS pipeline to calibrate such biases, but no data-driven constraints have been presented to date. In this paper, we cross-correlate CFHTLenS galaxy density maps with CFHTLenS shear maps and Planck CMB lensing maps to calibrate an additional multiplicative shear bias (m) in CFHTLenS (beyond the multiplicative correction that has already been applied to the CFHTLenS galaxy shears), following methods suggested by Vallinotto (2012) and Das et al. (2013). We analyze three magnitude-limited galaxy samples, finding 2-4sigma evidence for m<1 using the deepest sample (i<24), while the others are consistent with m=1 (no bias). This matches the expectation that the shapes of faint galaxies are the most prone to measurement biases. Our results for m are essentially independent of the assumed cosmology, and only weakly sensitive to assumptions about the galaxy bias. We consider three galaxy bias models, finding in all cases that the best-fit multiplicative shear bias is less than unity. A value of m~0.9 would suffice to reconcile the amplitude of density fluctuations inferred from the CFHTLenS shear two-point statistics with that inferred from Planck CMB temperature data. This scenario is consistent with our results.

Natural gas pipeline leak aperture identification and location based on local mean decomposition analysis

When a gas pipeline leaks, the leak aperture and its position cannot be easily identified. This paper proposed a leak aperture recognition and location method based on root mean square (RMS) entropy of local mean deposition (LMD) and Wigner–Ville time-frequency analysis. Firstly, wavelet packet energy analysis is employed to remove noise and extract the primary energy leak bands to reconstruct. The reconstructed signal is then decomposed using LMD, and the RMS entropy of PF components is calculated. The RMS entropies of multiple groups are used to build the feature vector, and it is then input into support vector machines (SVMs) to achieve the aperture recognition. An adaptive method based on mutual information is proposed to select the sensitive product function (PF) components, and the time-frequency parameters of the sensitive PF components are then calculated using Wigner–Ville distribution (WVD) method. The time delays are obtained by analyzing the time-frequency parameters. Finally the leak location was achieved by combining time delay with leak signal propagation velocity. The experimental results show that the proposed method can effectively identify different leak apertures, and the leak location accuracy is better than that of the direct cross-correlation method.

An improved cross-correlation method based on wavelet transform and energy feature extraction for pipeline leak detection

Early detection and precise location of leakage is of great importance for life-cycle maintenance and management of municipal pipeline system. In the past few years, acoustic emission (AE) techniques have demonstrated to be an excellent tool for on-line leakage detection. Regarding the multi-mode and frequency dispersion characteristics of AE signals propagating along a pipeline, the direct cross-correlation technique that assumes the constant AE propagation velocity does not perform well in practice for acoustic leak location. This paper presents an improved cross-correlation method based on wavelet transform, with due consideration of the frequency dispersion characteristics of AE wave and the contribution of different mode. Laboratory experiments conducted to simulate pipeline gas leakage and investigate the frequency spectrum signatures of AE leak signals. By comparing with the other methods for leak location identification, the feasibility and superiority of the proposed method are verified.

Comparison Study of Multivariate Statistics Based Key Performance Indicator Monitoring Approaches

In this paper, multivariate statistical process monitoring approaches for key performance indicator (KPI) related static processes are reviewed under a unified framework. Based on their key nature in extracting KPI-related information from process variable space for performance monitoring, those approaches are analyzed and sorted into three categories: direct cross-correlation based decomposition method, modified least square regression based approaches, partial least square based approaches. In addition, their numerical properties and monitoring performance are compared in details. Finally the well-accepted TE benchmark process is utilized to demonstrate the theoretical comparison results and their monitoring performance from industrial viewpoint.

Real-Time Debonding Monitoring of Composite Repaired Materials via Electrical, Acoustic, and Thermographic Methods

The electrical properties of composite materials have been thoroughly investigated recently for the detection and monitoring of damage in carbon fiber-reinforced polymers (CFRPs) under mechanical loading. Carbon nanotubes are incorporated in the polymer matrix of CFRPs for the enhancement of their electrical properties. The electrical properties have shown to be sensitive to the damage state of the material and hence their monitoring provides the profile of their structural deterioration. The aim of the paper is the cross-validation and benchmarking of an electrical potential change monitoring (EPCM) technique against acoustic emission (AE) and lock-in thermography (LT). All techniques successfully identified damage and its propagation. Thermography was more efficient in quantifying damage and describing dynamically the debond topology, as it provided full 2D imaging of the debond in real time. EPCM was successful in providing quantitative information on debond propagation and its directionality. AE provided consistent information on damage propagation. All techniques identified three stages in the fatigue life of the interrogated coupons. The representation of the fatigue behavior as a function of life fraction, the correlation of AE data with EPCM and LT data, and most importantly the consistent behavior of all tested coupons allowed for both the direct and indirect cross-correlation of all employed methodologies, which consistently identified all aforementioned fatigue life stages.

Experimental cross-correlation nitrogen Q-branch CARS thermometry in a spark ignition engine

A purely experimental technique was employed to derive temperatures from nitrogen Q-branch Coherent Anti-Stokes Raman Scattering (CARS) spectra, obtained in a high pressure, high temperature environment (spark ignition Otto engine). This was in order to obviate any errors arising from deficiencies in the spectral scaling laws which are commonly used to represent nitrogen Q-branch CARS spectra at high pressure. The spectra obtained in the engine were compared with spectra obtained in a calibrated high pressure, high temperature cell, using direct cross-correlation in place of the minimisation of sums of squares of residuals.The technique is demonstrated through the measurement of air temperature as a function of crankshaft angle inside the cylinder of a motored single-cylinder Ricardo E6 research engine, followed by the measurement of fuel–air mixture temperatures obtained during the compression stroke in a knocking Ricardo E6 engine. A standard CARS programme (SANDIA's CARSFIT) was employed to calibrate the altered non-resonant background contribution to the CARS spectra that was caused by the alteration to the mole fraction of nitrogen in the unburned fuel–air mixture. The compression temperature profiles were extrapolated in order to predict the auto-ignition temperatures.

F-2-1 Dynamic OpticaI Coherence Straingraphy を用いた皮膚摸擬試料における粘弾性特性断層画像法の基礎的検討(生体治療・医療,バイオ操作・検査(2),口頭発表)

The superficial skin tissue makes up of complicated layers and micro-structures,associated with water content,which should determine micro mechanical properties resulting in viscoelastic behaviors.Recently,OCT has been being developed as a cross-sectional imaging tool with 1 to 10 micrometer resolution.Authors have developed Dynamic OCSA,which can provide time- and space-dependent distribution of tissue deformation by means of direct cross-correlation technique.In this study,the proposed method was applied to skin phantom "BioSkin",in order to confirm the detection of internal viscoelastic information.As a result,Dynamic OCSA can identify statistical significance of viscoelastic properties,i.e.creep recovery time.It is,therefore,concluded that Dynamic OCSA could employ as a "Micro Mechanical Skin Biopsy".

Short-term feed intake is regulated by macronutrient oxidation in lactating Holstein cows

In addition to plasma metabolites and hormones participating as humoral signals in the control of feed intake, oxidative metabolic processes in peripheral organs also generate signals to terminate feeding. Although the degree of oxidation over longer periods is relatively constant, recent work suggests that the periprandial pattern of fuel oxidation is involved in regulating feeding behavior in the bovine. However, the association between periprandial oxidative metabolism and feed intake of dairy cows has not yet been studied. Therefore, the aim of this study was to elucidate possible associations existing between single feed intake events and whole-body net fat and net carbohydrate oxidation as well as their relation to plasma metabolite concentrations. To this end, 4 late-lactating cows equipped with jugular catheters were kept in respiratory chambers with continuous and simultaneous recording of gas exchange and feed intake. Animals were fed ad libitum (AL) for 24h and then feed restricted (RE) to 50% of the previous AL intake for a further 24h. Blood samples were collected hourly to analyze β-hydroxybutyrate (BHBA), glucose, nonesterified fatty acids (NEFA), insulin, and acylated ghrelin concentrations. Cross-correlation analysis revealed an offset ranging between 30 and 42min between the maximum of a feed intake event and the lowest level of postprandial net fat oxidation (FOXnet) and the maximum level of postprandial net carbohydrate oxidation (COXnet), respectively. During the AL period, FOXnet did not increase above −0.2g/min, whereas COXnet did not decrease below 6g/min before the start of the next feed intake event. A strong inverse cross-correlation was obtained between COXnet and plasma glucose concentration. Direct cross-correlations were observed between COXnet and insulin, between heat production and BHBA, between insulin and glucose, and between BHBA and ghrelin. We found no cross-correlation between FOXnet and NEFA. During RE, FOXnet increased with an exponential slope, exceeded the threshold of −0.2g/min as indicated by increasing plasma NEFA concentrations, and approached a maximum rate of 0.1g/min, whereas COXnet decayed in an exponential manner, approaching a minimal COXnet rate of about 2.5g/min in all cows. Our novel findings suggest that, in late-lactating cows, postprandial increases in metabolic oxidative processes seem to signal suppression of feed intake, whereas preprandially an accelerated FOXnet rate and a decelerated COXnet rate initiate feed intake.

Fast 3D PIV with direct sparse cross-correlations

The extension of the well-assessed high-accuracy algorithms for two-dimensional-two components particle image velocimetry (PIV) to the case of three-dimensional (3D) data involves a considerable increase of the computational cost. Tomographic PIV is strongly affected by this issue, relying on 3D cross-correlation to estimate the velocity field. In this study, a number of solutions are presented, enabling a more efficient calculation of the velocity field without any significant loss of accuracy. A quick estimation of the predictor displacement field is proposed, based on voxels binning in the first steps of the process. The corrector displacement field is efficiently computed by restricting the search area of the correlation peak. In the initial part of the process, the calculation of a reduced cross-correlation map by using Fast Fourier Transform on blocks is suggested, in order to accelerate the processing by avoiding redundant calculations in case of overlapping interrogations windows. Eventually, direct cross-correlations with a search radius of only 1 pixel in the neighborhood of the estimated peak are employed; the final iterations are consistently faster, since direct correlations can better enjoy the sparsity of the distributions, reducing the number of operations to be performed. Furthermore, three different approaches to reduce the number of redundant calculations for overlapping windows are presented, based on pre-calculations of the contributions to the cross-correlations coefficients along segments, planes or blocks. The algorithms are tested both on synthetic and real images, showing that a potential speed-up of up to 800 times can be obtained, depending on the complexity of the flow field to be analyzed. The challenging application on a real swirling jet results in a speed-up of an order of magnitude.

Three-dimensional PIV measurement of flow around an arbitrarily moving body

A three-dimensional (3D) particle image velocimetry measurement technique capable of simultaneously monitoring 3D fluid flows and the structure of an arbitrarily moving surface embedded in the flow was proposed with a heavy emphasis on image processing methods. The costs associated with the experimental apparatus were reduced by recording the surface and the trace particles at one image plane without the use of additional cameras or illumination devices. An optimal exposure time for surface and particle imaging was identified using red fluorescent tracer particles in conjunction with a long-pass glass filter. The particle image and surface image were then separated using an image separation process that relied on the feature scaling differences between the particles and the surface texture. A feature detection process and a matching process facilitated estimation of the 3D surface points, and the 3D surface structure was modeled by Delaunay triangulation. The particle volume reconstruction algorithm constrained the voxels inside the surface structure to zero values to minimize ghost particle generation. Volume self-calibration was employed to improve the reconstruction quality and the triangulation accuracy. To conserve computing resources in the presence of numerous zero voxels, the MLOS-SMART reconstruction and the direct non-zero voxel cross-correlation method were applied. Three-dimensional experiments that modeled the flows around an eccentric rotating cylinder and a flapping flag were conducted to validate the present technique.

Theoretical analysis of direct and phase-filtered cross-correlation response to a sinusoidal displacement for PIV image processing

The response of PIV image processing routines adopting cross-correlation is commonly categorized as that of a moving average (MA) filter. This paper addresses the intrinsic response of the statistical operator to a sinusoidal displacement from a theoretical perspective. Evaluation of the derived analytical expressions for the correlation indicates the response not to behave as that of an MA filter contrary to the generally adopted simplification. Instead the inherent signal modulation is non-linear and is determined by the ratio between displacement amplitude and particle image diameter. This finding is expected to be of importance and have considerable implications for recursive image processing routines. In addition, readily available spectral filtering techniques are assessed in terms of effectiveness in minimization of correlation deterioration due to pixelization and displacement filtering inherent to particle image self-correlation. It is shown that the best possible correlation response in digital PIV is dictated by the convolution between particle image self-correlation and displacement distribution function, inevitably retaining particle image inherent amplitude modulation.

The development of direct multicolour fluorescence cross-correlation spectroscopy: Towards a new tool for tracking complex biomolecular events in real-time

Direct three-colour fluorescence cross-correlation spectroscopy can reveal interactions between three fluorescently labelled biomolecules, giving insight toward the complex events that constitute signal transduction pathways. Here we provide the optical and theoretical basis for this technology and demonstrate its ability to detect specific biological associations between nanoparticle-labelled DNA molecules.

Template matching for improved accuracy in molecular tagging velocimetry

In 2D molecular tagging velocimetry (MTV), tags are written into a fluid flow with a laser grid and imaged at discrete times. These images are analyzed to calculate Lagrangian displacement vectors, often by direct cross correlation. The cross correlation method is inherited from particle imaging velocimetry, where the correlated images contain a random pattern of particles. A template matching method is presented here which takes advantage of the known geometry of laser written tag grids in MTV to achieve better accuracy. Grid intersections are explicitly located in each image by correlation with a template with several linear and rotational degrees of freedom. The template is a continuous mathematical function, so the correlation may be optimized at arbitrary sub-pixel resolution. The template is smooth at the spatial scale of the image noise, so random error is substantially suppressed. Under typical experimental conditions at low imaging resolution, displacement uncertainty is reduced by a factor of 5 compared to the direct cross correlation method. Due to the rotational degrees of freedom, displacement uncertainty is insensitive to highly deformed grids, thus permitting longer delay times and increasing the relative accuracy and dynamic range of the measurement. In addition, measured rotational displacements yield velocity gradients which improve the fidelity of interpolated velocity maps.

1H NMR and UPLC-MSE Statistical Heterospectroscopy: Characterization of Drug Metabolites (Xenometabolome) in Epidemiological Studies

Statistical HeterospectroscopY (SHY) is a statistical strategy for the coanalysis of multiple spectroscopic data sets acquired in parallel on the same samples. This method operates through the analysis of the intrinsic covariance between signal intensities in the same and related molecular fingerprints measured by multiple spectroscopic techniques across cohorts of samples. Here, the method is applied to 600-MHz (1)H NMR and UPLC-TOF-MS (E) data obtained from human urine samples ( n = 86) from a subset of an epidemiological population unselected for any relevant phenotype or disease factor. We show that direct cross-correlation of spectral parameters, viz. chemical shifts from NMR and m/ z data from MS, together with fragment analysis from MS (E) scans, leads not only to the detection of numerous endogenous urinary metabolites but also the identification of drug metabolites that are part of the latent use of drugs by the population. We show previously unreported positive mode ions of ibuprofen metabolites with their NMR correlates and suggest the detection of new metabolites of disopyramide in the population samples. This approach is of great potential value in the description of population xenometabolomes and in population pharmacology studies, and indeed for drug metabolism studies in general.

Automatic detection of ultrasonic Doppler signal episodes resulting from fetal breathing movements

A method for automatic detection of fetal breathing movements has been proposed, based on the time-frequency structure of the corresponding continuous wave ultrasonic Doppler signals. The method uses spectral analysis of the envelope of the directional Doppler signal and cross-correlation analysis of both directional envelopes. Detection rule comprises the following criteria: presence of the peak in the envelope spectrum and of the adequate signal level in the frequency range corresponding to the fetal breathing rhythm, the peak value and the position limits of the peak of the cross-correlation coefficient of the both directional envelopes. The effect of the criteria setting on the rule performance and the tradeoff between the specificity and sensitivity was investigated. The rule is most sensitive to the threshold value of the cross-correlation coefficient of the envelopes. The limits of the position of this peak are crucial for the distinction between the breathing episodes and hiccups. The optimal settings of the criteria, resulting in average sensitivity and specificity exceeding, respectively, 0.70 and 0.80, are proposed.

Research on Auto-detection for Remainder Particles of Aerospace Relay Based on Wavelet Analysis

AbstractAerospace relay is one kind of electronic components which is used widely in national defense system and aerospace system. The existence of remainder particles induces the reliability declining, which has become a severe problem in the development of aerospace relay. Traditional particle impact noise detection (PIND) method for remainder detection is ineffective for small particles, due to its low precision and involvement of subjective factors. An auto-detection method for PIND output signals is proposed in this paper, which is based on direct wavelet de-noising (DWD), cross-correlation analysis (CCA) and homo-filtering (HF), the method enhances the affectivity of PIND test about the small particles. In the end, some practical PIND output signals are analysed, and the validity of this new method is proved.

COSMOGRAIL: the COSmological MOnitoring of GRAvItational Lenses

Aims: Our aim is to measure the time delay between the two gravitationally lensed images of the z = 1.547 quasar SDSS J1650+4251, in order to estimate the Hubble constant H_0. Methods: Our measurement is based on R-band light curves with 57 epochs obtained at Maidanak Observatory, in Uzbekistan, from May 2004 to September 2005. The photometry is performed using simultaneous deconvolution of the data, which provides the individual light curves of the otherwise blended quasar images. The time delay is determined from the light curves using two very different numerical techniques, i.e., polynomial fitting and direct cross-correlation. The time delay is converted into H_0 following analytical modeling of the potential well. Results: Our best estimate of the time delay is Dt = 49.5 +/- 1.9 days, i.e., we reach a 3.8% accuracy. The R-band flux ratio between the quasar images, corrected for the time delay and for slow microlensing, is F_A /F_B = 6.2 +/- 5%. Conclusions: The accuracy reached on the time delay allows us to discriminate well between families of lens models. As for most other multiply imaged quasars, only models of the lensing galaxy that have a de Vaucouleurs mass profile plus external shear give a Hubble constant compatible with the current most popular value (H_0 = 72 +/- 8 km s-1 Mpc-1). A more realistic singular isothermal sphere model plus external shear gives H_0 = 51.7 +4.0 -3.0 km s-1 Mpc-1.