Autocorrelation Technique Research Articles

WEAK SIGNAL DETECTION BASED ON MULTIPLE AUTO-CORRELATION TECHNIQUES

This study presents the performance of the auto-correlation methods for detecting weak signals, where the signal level is much less than the noise level. Double and triple auto-correlation techniques are used to improve the detection performance compared with the single autocorrelation. Simulation results obtained by MATLAB programs show that the multiple correlation techniques outperform the single correlation in terms of probability of detection and probability of false alarm versus signal to noise ratio SNR.

Mapping risk zones of potential erosion in the upper Nazas River basin, Mexico through spatial autocorrelation techniques

Mapping risk zones of potential erosion in the upper Nazas River basin, Mexico through spatial autocorrelation techniques

Analysing Spatio-Temporal Voting Patterns in Brazilian Elections Through a Simple Data Science Pipeline

Since 1989, the first year of the democratic presidential election after a long period of a dictatorship regime, Brazil conducted eight presidential elections. Short and long-term shifts of power and two impeachment processes marked such a period. This instability is a research case in electoral studies, mainly regarding the understanding of citizens' voting behavior. Comprehending patterns in the population behavior can give us insight into phenomena and processes that affect democratic political decisions. In light of this, our paper analyses Brazilian electoral data at the municipal level from 1998 to 2018 using a simple data science pipeline, which consists of five steps: (i) data selection; (ii) data preprocessing; (iii) identification of spatial patterns, in which we seek to understand the role of space in the election results employing spatial auto-correlation techniques; (iv) identification of temporal patterns, where we investigate similar trends of votes over the years applying a hierarchical clustering method; and (v) evaluation of results. We study the presidential elections focusing on the right and left-wing parties most relevant for the period: the Brazilian Social Democracy Party~(PSDB) and the Workers' Party~(PT). We also analyse the congressman election data regarding parties ideologically to the right and left in the political spectrum. Through the obtained results, we found the existence of spatial dependence in every electoral year investigated. Moreover, despite the changes in the political-economic context over the years, neighboring cities seem to present similar voting behavior trends.

Measurements of visual binaries with PISCO2 at the Nice 76‐cm refractor in 2011–2012

AbstractWe present relative astrometric and photometric measurements of visual binaries made in 2011–2012, with PISCO2 installed at the 76‐cm refractor of Côte d'Azur Observatory in Nice (France). Our observing list contains orbital couples as well as binaries whose motion is still uncertain. Three different techniques have been used for obtaining those measurements: Lucky imaging, speckle interferometry, and the direct vector autocorrelation method. From our observations of 3,136 multiple stars, we obtained 3,568 new measurements with angular separations in the range of 0″.1–10″ and an average accuracy of 0″.016. The mean error on the position angles is 1°.7. Most of the position angles were determined without the usual 180° ambiguity with the application of the direct vector autocorrelation technique and/or by inspection of the Lucky images or the long integration files. We managed to routinely monitor faint systems (mV ≈ 9–11) with large magnitude difference (up to ΔmV ≈ 5). We have thus been able to measure many systems containing red dwarf stars that had been poorly monitored since their discovery. We also measured the magnitude difference of the two components of 326 binaries with an estimated error of 0.2 mag. Except for a few objects that have been discussed, our measurements are in a good agreement with the ephemerides computed with published orbital elements, even for the binaries closer than the diffraction limit. Thanks to good seeing images and with the use of high‐contrast numerical filters, we have also been able to obtain 196 measurements with an angular separation smaller than the diffraction limit of our instrumentation, and consistent with those obtained with larger telescopes. We also obtained new measurements of the 15th magnitude multiple system CON37, and discovered a faint new double star in its vicinity. Finally, we report 47 measurements of 28 new binaries found during our observations.

Characterization of vacuum and deep ultraviolet pulses via two-photon autocorrelation signals.

Characterization of ultrashort vacuum and deep ultraviolet pulses is important in view of applications of those pulses for spectroscopic and dynamical imaging of atoms, molecules, and materials. We present an extension of the autocorrelation technique, applied for measurement of the pulse duration via a single Gaussian function. Analytic solutions for two-photon ionization of atoms by Gaussian pulses are used along with an expansion of the pulse to be characterized using multiple Gaussians at multi-color central frequencies. This approach allows one to use two-photon autocorrelation signals to characterize isolated ultrashort pulses and pulse trains, i.e., the time-dependent amplitude and phase variation of the electric field. The potential of the method is demonstrated using vacuum and deep ultraviolet pulses and pulse trains obtained from numerical simulations of macroscopic high harmonic spectra.

Radial differential rotation of solar corona using radio emissions

ABSTRACT The present work is an effort to investigate possible radial variations in the solar coronal rotation by analysing the solar radio emission data at 15 different frequencies (275–1755 MHz) for the period starting from 1994 July to 1999 May. We used a time series of disc-integrated radio flux recorded daily at these frequencies through radio telescopes situated at the Astronomical Observatory of the Jagellonian University in Cracow. The different frequency radiation originates from different heights in the solar corona. Existing models indicate its origin at the height range from nearly ∼12 000 km (for emission at 275 MHz), below up to ∼2400 km (for emission at 1755 MHz). There are some data gaps in the time series used for the study, so we used statistical analysis using the Lomb–Scargle periodogram (LSP). This method has successfully estimated the periodicity present in time series even with such data gaps. The rotation period estimated through LSP shows variation in the rotation period, which is compared with the earlier reported estimate using auto correlation technique. This study indicates some similarity as well as a contradiction with studies reported earlier. The radial and temporal variation in the solar rotation period are presented and discussed for the whole period analysed.

A Spatial panel Analysis of Carbon Emission and Food security

This study examines the influence of co2emission on food security proxied by food supply by spatial econometrics models from 2000 to 2014 globally. We also comprised the socio-economic variables in the model for the bias of variables. The global Moran's I and local spatial autocorrelation technique used for spatial dependence, and they suggested the spatial dependence exist in the cross-sectional units. Therefore, we used the spatial panel model to check the spatial spillover effect of co2emisson on food supply. The chosen spatial panel Durbin model outcomes showed that the co2emission, population growth, and unemployment rate have negatively decreased the given country's food supply level and its neighbour countries. Simultaneously, the GDP and arable land are beneficial for the given country and its adjacent countries. Moreover, the real coefficients, direct, indirect (spillover), and the total effects of the carbon emission indicated that the carbon emissions decrease food security levels in both of this country and its nearest neighbouring countries. Therefore, the carbon emissions level needs to be reduced to improve food production (in quality and quantity) and increase the food supply level.

Spatio-temporal analysis of COVID-19 in India – a geostatistical approach

Coronavirus (Covid) is a severe acute respiratory syndrome infectious disease, spreads primarily between human beings during close contact, most often through the coughing, sneezing, and speaking small droplets. A retrospective surveillance research is conducted in India during 30th January–21st March 2020 to gain insight into Covid’s epidemiology and spatial distribution. Voronoi statistics is used to draw attention of the affected states from a series of polygons. Spatial patterns of disease clustering are analyzed using global spatial autocorrelation techniques. Local spatial autocorrelation has also been observed using statistical methods from Getis-Ord Gi*. The findings showed that disease clusters existed in the area of research. Most of the clusters are concentrated in the central and western states of India, while the north-eastern countries are still predominantly low-rate of clusters. This simulation technique helps public health professionals to identify risk areas for disease and take decisions in real time to control this viral disease.

FPGA based Identification of Frequency and Phase Modulated Signals by Time Domain Digital Techniques for ELINT Systems

In this paper, a decision tree algorithm based on time-domain digital technique is developed for the identification and classification of diverse radar intra-pulse modulated signals for the electronic intelligence system in real-time. This includes linear frequency modulation, non-linear frequency modulation, stepped frequency modulation and bi-phase modulation. The received signal is digitised and the instantaneous phase and high accuracy instantaneous frequency are estimated. The instantaneous amplitude is also estimated to get the start and stop of the pulse. Instantaneous parameters are estimated using a moving autocorrelation technique. The proposed algorithm is employed on the instantaneous frequency and the modulation is identified. The modulation type and modulation parameter are important for unique radar identification when similar radars are operating in a dense environment. Simulations are carried out at various SNR conditions and results are presented. The model for algorithm is developed using a system generator and implemented in FPGA. These results are compared when the proposed algorithm is used with the existing digital in-phase and quadrature-phase (DIQ) technique of instantaneous frequency and amplitude estimation.

Association of peripheral artery disease and chronic limb-threatening ischemia with socioeconomic deprivation in people with diabetes: A population data-linkage and geospatial analysis.

The association between the prevalence and geographical distribution of peripheral artery disease (PAD) and chronic limb-threatening ischemia (CLTI) in patients with diabetes in the context of socioeconomic deprivation is not well understood. We undertook a retrospective cohort study of 76,307 people with diabetes admitted as a hospital inpatient in a large Scottish health administrative area. Utilising linked health records, we identified diagnoses of PAD and/or CLTI and their distribution using small area cartography techniques according to multiple deprivation maps. Spatial autocorrelation techniques were applied to examine PAD and CLTI patterning. Association between crude inpatient prevalence-adjusted outcome rates and exposure to social deprivation were determined. We found crude prevalence-adjusted rates of 8.05% for PAD and 1.10% for CLTI with a five- to sevenfold difference from the least to most deprived regions. Statistically significant hot spots were found for PAD (p < 0.001) and CLTI (p < 0.001) in the most deprived areas, and cold spots for PAD (p < 0.001) but not CLTI (p = 0.72) in the least deprived areas. Major health disparities in PAD/CLTI diagnoses in people with diabetes is driven by socioeconomic deprivation.

The HIV epidemic in Colombia: spatial and temporal trends analysis

BackgroundColombia has the fourth highest incidence rate of HIV/AIDS among all Latin American countries and it has been increasing since the 1980s. However, the number of studies that addresses this trend is limited. Here, we employed spatial and temporal trend analyses to study the behaviour of the epidemic in the Colombian territory.MethodsOur sample included 72,994 cases of HIV/AIDS and 21,898 AIDS-related deaths reported to the National Ministry of Health between 2008 and 2016. We employed the joinpoint regression model to analyse the annual HIV/AIDS incidence and AIDS mortality rates. In the spatial analysis, we used univariate autocorrelation techniques and the Kernel density estimator.ResultsWhile the HIV/AIDS incidence had an increasing trend in Colombia, the AIDS mortality rate was stable. HIV/AIDS incidence and AIDS mortality showed a downward trend in the 0–14 age group. An upward trend was observed for HIV/AIDS incidence in people older than 15 years and with the highest trend in the 65 years and above group. AIDS mortality showed an increasing trend among people aged 65 years or older. The comparison between the sexes showed an upward trend of HIV/AIDS incidence in all age groups and AIDS-mortality rates in 65 years and above in men, while in women, the incidence was upward among those aged 45 years and above, and concerning the AIDS-mortality rate in the 45–64 group. The high–high clusters of HIV/AIDS incidence and AIDS mortality were located in the Andean and Caribbean regions.ConclusionOur study found an upward trend in HIV/AIDS incidence and a stable trend in the AIDS mortality rate in Colombia. The downward trend in HIV/AIDS incidence and AIDS mortality rate in the 0–14 age group reflects the downwards mother-to-child HIV transmission. The upward trend in HIV/AIDS incidence in older women and AIDS mortality in younger women rates, compared with men, may be due to late diagnosis and treatment. The Caribbean and the ‘coffee belt’ regions were the most impacted by the HIV epidemic, most likely due to sexual tourism. Our results provide crucial information that may help Colombian health authorities fight HIV transmission.

Insights into Mechanical Properties of the 1980 Irpinia Fault System from the Analysis of a Seismic Sequence

Seismic sequences are a powerful tool to locally infer geometrical and mechanical properties of faults and fault systems. In this study, we provided detailed location and characterization of events of the 3–7 July 2020 Irpinia sequence (southern Italy) that occurred at the northern tip of the main segment that ruptured during the 1980 Irpinia earthquake. Using an autocorrelation technique, we detected more than 340 events within the sequence, with local magnitude ranging between −0.5 and 3.0. We thus provided double difference locations, source parameter estimation, and focal mechanisms determination for the largest quality events. We found that the sequence ruptured an asperity with a size of about 800 m, along a fault structure having a strike compatible with the one of the main segments of the 1980 Irpinia earthquake, and a dip of 50–55° at depth of 10.5–12 km and 60–65° at shallower depths (7.5–9 km). Low stress drop release (average of 0.64 MPa) indicates a fluid-driven initiation mechanism of the sequence. We also evaluated the performance of the earthquake early warning systems running in real-time during the sequence, retrieving a minimum size for the blind zone in the area of about 15 km.

Width Estimation of Non-Gaussian Doppler Velocity Spectra of Meteorological Formations

The paper considers features of the Doppler velocity spectrum width of meteorological formations obtained on the basis of the pulse-pair method when a velocity Doppler spectrum differs from the Gaussian shape. Since the autoregressive models of various orders are widely used in practice for approximating the echo signals from meteorological formations and taking into account their spectrum shape, we have analyzed the measurement errors while using the pulse-pair method. It is shown that neglecting the information on the shape of Doppler velocity spectrum may lead to unacceptable large measurement errors and distort the true level of danger of meteorological formations. The possible methods of determining the autoregressive model orders are discussed, and the benefits of the method based on threshold processing of α-parameters of adaptive lattice filters are shown. The distribution densities of these parameters are determined for the calculation of recognition threshold of autoregressive model order. The statistical characteristics of recognition obtained by the known and proposed methods are compared. The proposed method in terms of the accuracy of order recognition actually is not inferior to the known methods, but can be implemented directly in the process of measuring the width of Doppler velocity spectrum that sets it apart from the others.

On The Efficiency of P‐Wave Coda Autocorrelation in Recovering Crustal Structure: Examples From Dense Arrays in the Eastern United States

AbstractDue to a sharp contrast in elastic properties across the basement rocks of sedimentary basins (SBs), strong reverberations are generated during the passage of seismic waves. Traditional receiver function methods become inadequate for imaging crustal structure due to the existence of these strong reverberations. We investigate the feasibility of an autocorrelation technique to extract vertical component receiver functions from teleseismic earthquake data and the efficiency of the method to image the crustal architecture in presence of a SB. The method involves spectral whitening followed by autocorrelation and stacking in the depth domain. We show promising results when using temporary seismic networks in the eastern United States. Using synthetic and field‐data examples, we demonstrate that vertical autocorrelations are more efficient than classical radial receiver functions for interpretation purposes in an SB context. We also perform a joint analysis of the amplitudes on radial and vertical receiver functions for characterizing the thickness of the Mohorovičić discontinuity (Moho). We find that the Moho in the eastern United States is a transitional layer (up to 5‐km thick) instead of a sharp boundary. Further, we point out that it is challenging to unambiguously pick and interpret reflected phases on autocorrelations because of the effects of reverberations, cross‐mode contaminations, and a narrow frequency band limiting the resolution of velocity gradients. We therefore send a message of caution for future interpretations based on this technique.

Array and spectral ratio techniques applied to seismic noise to investigate the Campi Flegrei (Italy) subsoil structure at different scales

Abstract. The purpose of this work is to study the subsoil structure of the Campi Flegrei area using both spectral ratios and array techniques applied to seismic noise. We have estimated the dispersion curves of Rayleigh waves by applying the Frequency–Wavenumber (f–k hereinafter) and Modified Spatial Autocorrelation (MSPAC) techniques to the seismic noise recorded by the underground short period seismic Array “ARF”, by the broadband stations of the UNREST experiment and by the broadband stations of the seismic monitoring network of INGV – Osservatorio Vesuviano. We have performed the inversion of a dispersion curve (obtained averaging the f–k and MSPAC dispersion curves of seismic noise and single phase velocity values of coherent transient signals) jointly with the H∕V spectral ratio of the broadband station CELG, to obtain a shear wave velocity model up to 2000 m depth. The best-fit model obtained is in a good agreement with the stratigraphic information available in the area coming from shallow boreholes and deep wells drilled for geothermal exploration. In active volcanic areas, such as Campi Flegrei, the definition of the velocity model is a crucial issue to characterize the physical parameters of the medium. Generally, a high quality characterization of the medium properties helps to separate the contributions of the volcanic source, path and site in the geophysical observables. Therefore, monitoring possible variations in time of such properties in general can help to recognize anomalies due to the volcano dynamics, i.e. fluid migration connected to the volcanic activity.

Identification of Axial and Radial Impacts for Pneumatic Artificial Muscles in Static and Dynamic Processes Based on Autocorrelations of Differential Pressure Signals

Since the pneumatic artificial muscle is usually employed to actuate the robot, it is inevitable that it will collide with obstacles and/or other objects such that there will be impacts. The typical impacts include the axial and radial ones. This paper detects these two kinds of impact by a designed differential pressure measurement system, and achieves the goal of identifying them by the autocorrelations of their differential pressure signals in both static and dynamic processes, which are the two main work processes of the pneumatic artificial muscle. In detail, first we design an experiment scheme by connecting the pneumatic artificial muscle to the differential pressure sensor through two pressure tubes; then the axial and radial impact signals are acquired via the impact experiments under different work conditions (impact strength, internal pressure, load, and impact position); finally, the identification of the axial and radial impact signals are achieved based on the autocorrelation technique with a well-selected threshold. The experiments illustrate the effectiveness of the whole method.

Examining transport needs in the global south using a screening framework

Despite the increasing emphasis on the social aspects of transport externalities in the global agenda of public policies (UN, 2016), transport appraisals (ex-ante) are still strongly driven by economic and environmental analysis only (Geurs et al. 2009; Jones and Lucas 2012). In this context, the goals targeting poverty reduction and social well-being promotion become fundamentally undermined when the social impacts are overlooked in the decision-making process of transport development (Vasconcellos 2003; World Bank 2006; Jones and Lucas 2012; Jones et al. 2013).Hence, in a context where the transport-related needs have been either disregarded, not fully captured, or addressed by subjective approaches, the proposition of an objective and well-grounded screening framework of transport needs can play a pivotal role in making transport planning more socially inclusive. The framework that is proposed applies the Analytic Hierarchy Process (AHP) and spatial autocorrelation techniques to provide tools and evidence-based guidelines that can guide transport interventions in Northeast Brazil to become more effective in reducing poverty. While the socially driven framework that is outlined here focuses on the transport needs of Northeast Brazil, it can also be replicated in other developing countries facing similar socio-economic and transport challenges. The results show that different regions of Northeast Brazil suffer differently from externalities and that sub-regional analysis is needed.

Impact of frequency-dependent spherical aberration in the focusing of ultrashort pulses.

In this paper, the temporal and spatial intensity pulse distributions are calculated around the focal region of an optical system using a combination of ray tracing and a wave propagation method. We analyze how to measure the width of the intensity pulse distributions to estimate pulse duration and spot size in order to study the impact of the variation of spherical aberration with frequency in a pulse on the intensity distributions. Two experimental techniques used in the laboratory are also modeled: the knife-edge test to measure spatial distribution and the intensity autocorrelation technique to measure the temporal distribution. We use two measuring criteria, the full-width half-maximum (FWHM) and standard deviation (σ), to compare the spatial and temporal intensity distributions of the calculated diffraction patterns and those obtained from the simulated experimental techniques. We show that the FWHM is not a good criterion, since it gives different results in the measured intensity distributions in time and space when they are measured directly from the theoretical modeling and when they are measured from the modeled experimental techniques used in the laboratory. The standard deviation, however, is a consistent criterion, giving the same results for the calculated intensity distributions and the modeled experiments.

Intelligent System for the Predictive Analysis of an Industrial Wastewater Treatment Process

Considering the exponential growth of today’s industry and the wastewater results of its processes, it needs to have an optimal treatment system for such effluent waters to mitigate the environmental impact generated by its discharges and comply with the environmental regulatory standards that are progressively increasing their demand. This leads to the need to innovate in the control and management information systems of the systems responsible to treat these residual waters in search of improvement. This paper proposes the development of an intelligent system that uses the data from the process and makes a prediction of its behavior to provide support in decision making related to the operation of the wastewater treatment plant (WWTP). To carry out the development of this system, a multilayer perceptron neural network with 2 hidden layers and 22 neurons each is implemented, together with process variable analysis, time-series decomposition, correlation and autocorrelation techniques; it is possible to predict the chemical oxygen demand (COD) at the input of the bioreactor with a one-day window and a mean absolute percentage error (MAPE) of 10.8%, which places this work between the adequate ranges proposed in the literature.

Analysis and spatial distribution of schistosomiasis mansoni in a historically endemic area of northeastern Brazil.

To perform a descriptive analysis of the activities of the Schistosomiasis Control Program, as well as the spatial distribution of the condition in the state of Alagoas, Brazil, for the period from 2007 to 2016. Descriptive ecological study. Data from positive human cases and operational data were collected in the Information System of the Schistosomiasis Control Program, and data for spatial analysis were collected on the website of the Brazilian Institute of Geography and Statistics. An analysis of spatial autocorrelation (Moran statistics) was performed, where a spatial pattern was established, which showed the Q1 and Q2 patterns to be the most important, and Q3 and Q4 representing transition areas. In the years under study, at least 85% (n=60/70) of the municipalities carried out the activities recommended by the PCE (Schistosomiasis Control Program). Alagoas presented an average positivity rate of 7.1%, which is very high compared to the prevalence of 3.3% at the last national schistosomiasis survey conducted between 2010 and 2015. Moran's statistics showed 22/70 municipalities forming a Q1 cluster, of high/high pattern, and 32/70 municipalities forming a Q2 cluster, of low/low pattern, with the others in a transition area. Moran Map data, however, showed only 7/70 municipalities in the endemic area with a spatial autocorrelation, with these municipalities having the Mundau River as a common element. Schistosomiasis mansoni is of great importance for public health in Alagoas and that the use of spatial analysis can identify priority areas for preventive and control measures against schistosomiasis mansoni.