Parametric analysis of correlation functions

The increasing radio frequency interference (RFI) is a well-recognized problem in radio astronomy research. Pulsars and Fast Radio Bursts (FRBs) are high-priority science targets of the ongoing Commercial Radio Astronomy FAST Survey (CRAFTS). To improve the quality of RFI removal in searches of pulsars and FRBs based on CRAFTS multi-beam data, we here propose an intuitive but powerful RFI mitigation pipeline (CCF-ST). The “CCF-ST” is a spatial filter constructed by signal cross-correlation function (CCF) and Sum-Threshold (ST) algorithm. The RFI marking result is saved in a “mask” file, a binary format for RFI masks in PRESTO. Three known pulsars, PSR B0525-21, PSR B0621-04, and PSR J0943 + 2252 from CRAFTS L-band 19 beams data are used for evaluation of the performance of CCF-ST in comparison with other methods, such as PRESTO’s “rfifind”, ArPLS-ST and ArPLS-SF. The result shows that CCF-ST can reduce effective data loss rate and improves the detected signal-to-noise ratio of the pulsations by ∼26% and ∼18% respectively compared with PRESTO’s “rfifind” and ArPLS-ST. The CCF-ST also has the advantage of low computational cost, e.g., reducing the time consumption by ∼40% and memory consumption by ∼90% compared with ArPLS-SF. We expect that the new RFI mitigation and analysis toolkit (CCF-ST) demonstrated in this paper can be applied to CRAFTS and other multi-beam telescope observations to improve the data quality and efficiency of pulsar and FRB searches.

A method and hardware for ultrasonic control of an inhomogeneous gaseous medium are presented. An algorithm based on digital phase modulation of pulse signals and their correlation processing is used to increase the resolution of an ultrasonic device. The algorithm allows high-resolution measurements of the time delay between the ultrasound pulses that arrive at a receiver along different propagation paths in an inhomogeneous medium. It is shown that it is possible to measure small values of time delays by analyzing the asymmetry of the cross correlation functions of signals. Laboratory experimental measurements carried out under scattering of ultrasound in an inhomogeneous airflow are described. The possibility of measuring relative time delays of 3–5 μs of pulses at the 40-kHz carrier frequency of ultrasound is shown.

The detection and localization of a possible leak on a pipe network is a problem under heavy scrutiny by the process engineering departments of the oil and gas treating corporations due to the significant accompanying implications in terms of environmental and financial impact, health hazards etc. As a result, a series of solutions has been proposed spanning from early research derived proposals to final commercial products. Among the methods proposed or adopted over the years, the techniques based on the Time Difference of Arrival (TDOA) estimation for ascertaining the existence and location of a fault signal with non or less intrusive means have attracted significant interest due to their simplicity in terms of formulation and their promising results, especially in the case of the Cross-Correlation (CC) based approaches. In this paper an account of a testing and measuring campaign is presented, regarding the vibration analysis of a typical pipe installation carrying fluids (water in this case) attempting the extraction of the propagation characteristics and analysis of the vibration signals in metallic pipelines, in the presence of a leak signal.

The investigation of the static and dynamic structural properties of colloidal systems relies on techniques capable of atomic resolution in real space and femtosecond resolution in time. Recently, the cross-correlation function (CCF) analysis of both X-rays and electron diffraction patterns from dilute and dense aggregates has demonstrated the ability to retrieve information on the sample’s local order and symmetry. Open questions remain regarding the role of the beam coherence in the formation of the diffraction pattern and the properties of the CCF, especially in dense systems. Here, we simulate the diffraction patterns of dense two-dimensional monodisperse systems of different symmetries, varying the transverse coherence of the probing wave, and analyze their CCF. We study samples with different symmetries at different size scale, as for example, pentamers arranged into a four-fold lattice where each pentamer is surrounded by triangular lattices, both ordered and disordered. In such systems, different symmetry modulations are arising in the CCF at specific scattering vectors. We demonstrate that the amplitude of the CCF is a fingerprint of the degree of the ordering in the sample and that at partial transverse coherence, the CCF of a dense sample corresponds to that of an individual scattering object.

Wideband (WB) and ultrawideband (UWB) systems combined with multiple-input multiple-output (MIMO) technology increase both the systems performances and the complexity of the channel models required to evaluate their capabilities. Because in real scenarios waves propagate nonisotropically, the accuracy of the channel model is increased if nonisotropic propagation is considered. The channel bandwidth is the key term in the evaluation process of these systems because large bandwidths introduce frequency selectivity, a unique phenomenon of WB and UWB systems with more complexity in the latter case. This is due to the fact that, unlike WB technology in which the propagating signal is the only affected parameter by the frequency selectivity, in the UWB case, this phenomenon also affects the antenna propagation pattern (APP). In this paper, we developed a novel channel model based on the statistical analysis of two-dimensional cross correlation functions (CCFs) of WB/UWB MIMO nonisotropic channels. A mathematical solution to assess the frequency selective behavior of the UWB APP is also presented. The CCF reveals how the power spectral density (PSD) of the channel is influenced by bandwidth, nonisotropic propagation, and APP.

Continuous recordings of ambient seismic noise across large seismic arrays allows a new type of processing using the cross‐correlation technique on broadband data. We propose to apply double beamforming (DBF) to cross correlations to extract a particular wave component of the reconstructed signals. We focus here on the extraction of the surface waves to measure phase velocity variations with great accuracy. DBF acts as a spatial filter between two distant subarrays after cross correlation of the wavefield between each single receiver pair. During the DBF process, horizontal slowness and azimuth are used to select the wavefront on both subarray sides. DBF increases the signal‐to‐noise ratio, which improves the extraction of the dispersive wave packets. This combination of cross correlation and DBF is used on the Transportable Array (USArray), for the central U.S. region. A standard model of surface wave propagation is constructed from a combination of the DBF and cross correlations at different offsets and for different frequency bands. The perturbation (phase shift) between each beam and the standard model is inverted. High‐resolution maps of the phase velocity of Rayleigh and Love waves are then constructed. Finally, the addition of azimuthal information provided by DBF is discussed, to construct curved rays that replace the classical great‐circle path assumption.

Because pipeline has large pipe diameter, large throughout and high pressure, once pipeline leakage accident happens, the damage is quite serious. In addition, pipeline leakage accident caused by man-made drilling oil stolen every year results in huge economic losses on oilfield. Therefore, a real-time and accurate pipeline leak detection and location system not only can effectively decrease leakage loss and reduce the waste of manpower and material resources in patrolling work, but also is conductive to the management of oil pipeline and improvement of economic efficiency of enterprise. The paper determines leak detection and location project giving priority to negative pressure wave and supplemented by flow parameter analysis. The method not only can judge the accidence of leakage timely and accurately, but also can effectively avoid leakage false alarm caused by start or stop pumps in pipeline. Negative pressure wave method is the method which is used widely on pipeline leakage detection and location internationally at present. It is based on signal processing. And the method doesn't need to establish hydraulic and mathematical model of pipeline, and most only use pressure signal. So the method adapts to the application of pipeline in China(1). Because oil pipeline has the function of guiding wave, the negative pressure wave caused by leakage can transmit more than tens of kilometers along the pipeline. Its propagation velocity is equal to the propagation velocity of sound wave transferring fluid in pipeline. And the propagation velocity of negative pressure wave in the original oil pipeline is between 1000meters and 1200 meters. As negative pressure wave has the characteristics of remote transmission, pressure transducer installed at the end and first of the pipeline can be used to capture negative pressure wave containing leakage information and to detect the leakage. After identifying leakage happens, leakage location can be made according to time difference of negative pressure wave caused by leakage transmitting to the head and end of the pipeline and negative pressure wave velocity(2).

Leak detection and location in a gas distribution network are significant issues. The acoustic emission (AE) technique can be used to locate a pipeline leak. The time delay between two sensor signals can be determined by the cross-correlation function (CCF), which is a measure of the similarity of two signals as a function of the time delay between them. Due to the energy attenuation, dispersion effect and reverberation of the leakage-induced signals in the pipelines, the CCF location method performs poorly. To improve the leakage location accuracy, this paper proposes a modified leakage location method based on the AE signal, and combines the modified generalized cross-correlation location method and the attenuation-based location method using multilayer perceptron neural networks (MLPNN). In addition, the wave speed was estimated more accurately by the peak frequency of the leakage-induced AE signal in combination with the group speed dispersive curve of the fundamental flexural mode. To verify the reliability of the proposed location method, many tests were performed over a range of leak-sensor distances. The location results show that compared to using the CCF location method, the MLPNN locator reduces the average of the relative location errors by 14%, therefore, this proposed method is better than the CCF method for locating a gas pipe leak.

The research about online monitoring and leakage automatic location of water distribution networks (WDN) has a wide range of applications that include water resource protection, monitoring, and allocation. Variational mode decomposition (VMD) and cross-correlation (CC) based leakage location is a popular and effective method in WDN. However, the value of K intrinsic mode functions (IMFs) based on VMD decomposition needs to be determined artificially, which affects the separation effect of signal frequency band characteristics directly. Hence, this work proposes an adaptive method to determine the parameter K of leakage vibration signal’s IMFs, which will be applied to automatic leakage location in WDN. Firstly, the number of saddle points in the frequency domain envelope of the sampled signal in different step sizes is calculated. The parameter K is determined according to the curvature change of the number of saddle points and the sampled signal. Finally, the selective IMFs are reconstituted into a new signal, which can determine a leak position using CC based time-delay estimation (TDE). To verify the effectiveness of the proposed algorithm, the different methods based on EMD and Fast ICA are compared. The experimental results demonstrate that the proposed parameter K value adaptive VMD (KVA-VMD) decomposition method is more suitable for leakage location in WDN.

In Kleine-Levin Syndrome (KLS), new episodes of hypersomnia are often preceded by an acute flu-like syndrome or upper airway infection 3 to 5 days before onset. This study investigated the relationship between the occurrence of mild upper respiratory tract infections (URIs) in the general population and the occurrence and seasonality and hypersomnic episodes in KLS patients. This investigation was a longitudinal clinical study. Based on data obtained from the National Health Research Institutes between 2006 and 2007, the timing of hypersomnic episodes in 30 KLS patients were compared with calendar reports of URI events, and the results compared with age-matched general Taiwanese population. Clinical symptoms, physical examination, polysomnographic recording, SPECT study, and laboratory tests affirming KLS during both periods of hypersomnic attack and non-attack were collected. Every symptomatic episode was then followed up. The cross-correlation function (CCF) and bivariate correlations analysis were performed to see the relationship between KLS and URIs. A positive finding of CCF analysis and significant bivariate correlations were found between KLS episodes and URI in the general population (r = 0.456*). In onset of hypersomnia, significant correlations existed among "acute upper respiratory infections" (r = 0.446*), "acute bronchitis and bronchiolitis" (r = 0.462*), and "pharyngitis and nasopharyngitis" (r = 0.548*) subtypes of infections. A positive correlation between higher reports of symptomatic hypersomnia and URI also existed in a given season. A positive nonsignificant trend for "allergic rhinitis" (r = 0.400) was also found. The agent behind URI or its consequence (such as fever) is associated with increased incidence of KLS episodes and may explain periodic symptomatic recurrences.

Binaural sound source localization based on weighted template matching

Owing to the principle of least commitment, near-field beamformers can produce passive acoustic source localizations which are robust to noise and interference. The power output of a traditional Bartlett near-field beamformer may be formulated in terms of the pairwise cross correlation functions of the sensor signals. We present a modified Bartlett processor wherein the ordinary cross correlation is replaced by generalized cross correlation, generalized in both time and frequency. As an example of the utility of the technique, we present results from a six element pentagonal marine array with a baseline of approximately 15 km deployed off the coast of Virginia. Localization of synthetic FM sweeps from known source locations within the array yield deviations from the true source location as measured by GPS of less than 100 meters. Localization of actual North Atlantic Right Whale calls provide good alignment of the unknown channel arrivals and acceptably small error ellipses.

Ultra-Wide Band radio positioning systems are maturing very quickly and now represent a good candidate for indoor positioning. The aim of this study was to undertake a quality assessment on the use of a commercial Ultra-Wide Band positioning system for the tracking of athletes during indoor wheelchair court sports. Several aspects have been investigated including system set-up, calibration, sensor positioning, determination of sport performance indicators and quality assessment of the output. With a simple set-up procedure, it has been demonstrated that athletes tracking can be achieved with an average horizontal positioning error of 0.37 m (σ = ± 0.24 m). The distance covered can be computed after data processing with an error below 0.5% of the course length. It has also been demonstrated that the tag update rate and the number of wheelchairs on the court do not affect significantly the positioning quality; however, for highly dynamic movement tracking, higher rates are recommended for a finer dynamic recording.

Novel hearable technology is securely and comfortably positioned within the ear canal minimizing inaccuracies caused by accessory movements during activities. Despite extensive research on hearable technologies within the outer ear, there is a lack of research in the field of vascular imaging and quantitative analysis in the outer ear in vivo, which is one of the crucial factors to select the appropriate sensor position. Therefore, in this paper, we introduced optical coherence tomography angiography (OCTA)-based qualitative and quantitative analyses to visualize the inner vasculature of the outer ear to acquire vascular maps for microvascular assessments in vivo. By generating maximum amplitude projection images from three-dimensional blood vascular volume, we identified variations of blood vessel signal caused by the different biological characteristics and curvature of the ear among individuals. The performance of micro-vascular mapping using the proposed method was validated through the comparison and analysis of individual vascular parameters using extracted 20 vascular-related variables. In addition, we extracted pulsatile blood flow signals, demonstrating its potential to provide photoplethysmographic signals and ear blood maps simultaneously. Therefore, our proposed OCTA-based method for ear vascular mapping successfully provides quantitative information about ear vasculature, which is potentially used for determining the position of system-on-chip sensors for health monitoring in hearable devices.

BackgroundInfluenza remains a significant public health challenge, characterized by substantial seasonal variation and considerable socioeconomic burden. Although meteorological factors are known to influence influenza transmission, their specific effects within subtropical monsoon climates, such as that of Quanzhou, remain inadequately characterized.MethodsWe analyzed weekly influenza-like illness (ILI%) data from sentinel hospitals in Quanzhou between 2016 and 2024. Descriptive statistics, distributed lag nonlinear models (DLNM), cross-correlation function (CCF) analysis, and ARIMAX modeling were employed to examine the lagged and nonlinear associations between meteorological variables and ILI%.ResultsThe overall ILI% during the surveillance period was 2.32%, with significant temporal trends: a pronounced decline from 2016 to 2020 (APC = −22.693, p = 0.001) was followed by a significant increase from 2020 to 2024 (APC = 21.555, p = 0.003). Children under 15 years of age were the most affected demographic. A consistent bimodal seasonal pattern was observed, with a primary peak in winter (weeks 50–14) and a secondary peak in summer (weeks 20–29). DLNM analysis indicated that low atmospheric pressure (<997 hPa) at lag 0–0.5 weeks was associated with increased ILI risk, while higher pressure (≥1,010 hPa) had a protective effect (relative risk [RR] = 0.85, 95% CI: 0.73–0.99). Precipitation of 4–16 mm elevated ILI risk (RR = 1.10, 95% CI: 1.02–1.18), whereas precipitation >21 mm was protective. Wind speed demonstrated an N-shaped association with ILI%, though this was not statistically significant. The optimal forecasting model incorporated precipitation at a 2-week lag as an exogenous variable (ARIMA(1,1,1)(1,1,1)52 + WAP(lag2)) and yielded the highest predictive accuracy for 2024 ILI%, improving RMSE by 2.9% and MAE by 1.3% compared to the baseline model.ConclusionIncorporating meteorological factors significantly improves the accuracy of influenza forecasting models. These findings support the development of climate-informed early warning systems and targeted public health interventions in subtropical regions.