Science.gov

Sample records for based correlation detection

  1. Spike Detection Based on Normalized Correlation with Automatic Template Generation

    PubMed Central

    Hwang, Wen-Jyi; Wang, Szu-Huai; Hsu, Ya-Tzu

    2014-01-01

    A novel feedback-based spike detection algorithm for noisy spike trains is presented in this paper. It uses the information extracted from the results of spike classification for the enhancement of spike detection. The algorithm performs template matching for spike detection by a normalized correlator. The detected spikes are then sorted by the OSortalgorithm. The mean of spikes of each cluster produced by the OSort algorithm is used as the template of the normalized correlator for subsequent detection. The automatic generation and updating of templates enhance the robustness of the spike detection to input trains with various spike waveforms and noise levels. Experimental results show that the proposed algorithm operating in conjunction with OSort is an efficient design for attaining high detection and classification accuracy for spike sorting. PMID:24960082

  2. Structural Plasticity Controlled by Calcium Based Correlation Detection

    PubMed Central

    Helias, Moritz; Rotter, Stefan; Gewaltig, Marc-Oliver; Diesmann, Markus

    2008-01-01

    Hebbian learning in cortical networks during development and adulthood relies on the presence of a mechanism to detect correlation between the presynaptic and the postsynaptic spiking activity. Recently, the calcium concentration in spines was experimentally shown to be a correlation sensitive signal with the necessary properties: it is confined to the spine volume, it depends on the relative timing of pre- and postsynaptic action potentials, and it is independent of the spine's location along the dendrite. NMDA receptors are a candidate mediator for the correlation dependent calcium signal. Here, we present a quantitative model of correlation detection in synapses based on the calcium influx through NMDA receptors under realistic conditions of irregular pre- and postsynaptic spiking activity with pairwise correlation. Our analytical framework captures the interaction of the learning rule and the correlation dynamics of the neurons. We find that a simple thresholding mechanism can act as a sensitive and reliable correlation detector at physiological firing rates. Furthermore, the mechanism is sensitive to correlation among afferent synapses by cooperation and competition. In our model this mechanism controls synapse formation and elimination. We explain how synapse elimination leads to firing rate homeostasis and show that the connectivity structure is shaped by the correlations between neighboring inputs. PMID:19129936

  3. Correlation based efficient face recognition and color change detection

    NASA Astrophysics Data System (ADS)

    Elbouz, M.; Alfalou, A.; Brosseau, C.; Alam, M. S.; Qasmi, S.

    2013-01-01

    Identifying the human face via correlation is a topic attracting widespread interest. At the heart of this technique lies the comparison of an unknown target image to a known reference database of images. However, the color information in the target image remains notoriously difficult to interpret. In this paper, we report a new technique which: (i) is robust against illumination change, (ii) offers discrimination ability to detect color change between faces having similar shape, and (iii) is specifically designed to detect red colored stains (i.e. facial bleeding). We adopt the Vanderlugt correlator (VLC) architecture with a segmented phase filter and we decompose the color target image using normalized red, green, and blue (RGB), and hue, saturation, and value (HSV) scales. We propose a new strategy to effectively utilize color information in signatures for further increasing the discrimination ability. The proposed algorithm has been found to be very efficient for discriminating face subjects with different skin colors, and those having color stains in different areas of the facial image.

  4. Multiresolution community detection for megascale networks by information-based replica correlations

    NASA Astrophysics Data System (ADS)

    Ronhovde, Peter; Nussinov, Zohar

    2009-07-01

    We use a Potts model community detection algorithm to accurately and quantitatively evaluate the hierarchical or multiresolution structure of a graph. Our multiresolution algorithm calculates correlations among multiple copies (“replicas”) of the same graph over a range of resolutions. Significant multiresolution structures are identified by strongly correlated replicas. The average normalized mutual information, the variation in information, and other measures, in principle, give a quantitative estimate of the “best” resolutions and indicate the relative strength of the structures in the graph. Because the method is based on information comparisons, it can, in principle, be used with any community detection model that can examine multiple resolutions. Our approach may be extended to other optimization problems. As a local measure, our Potts model avoids the “resolution limit” that affects other popular models. With this model, our community detection algorithm has an accuracy that ranks among the best of currently available methods. Using it, we can examine graphs over 40×106 nodes and more than 1×109 edges. We further report that the multiresolution variant of our algorithm can solve systems of at least 200000 nodes and 10×106 edges on a single processor with exceptionally high accuracy. For typical cases, we find a superlinear scaling O(L1.3) for community detection and O(L1.3logN) for the multiresolution algorithm, where L is the number of edges and N is the number of nodes in the system.

  5. [Detection of chlorophyll content in water body based on two-dimensional correlation spectroscopy].

    PubMed

    Zhang, Yao; Zheng, Li-Hua; Sun, Hong; Li, Min-Zan

    2014-02-01

    Twenty five samples were collected from 10 different ponds in Jiangsu Province of China. According to the different water status and surface area of each pond, different numbers of water samples were collected. The present paper aims to detect chlorophyll content in water body based on hyperspectrum. The visible and near infrared spectral transmittance of the water samples was measured by using a Shimadzu UV-2450 spectrograph. At the same time, the chlorophyll content of each sample was measured using hot-ethanol extraction method in the laboratory. Then the spectral characteristics were analyzed for the water samples and the results showed that with chlorophyll concentration increasing, spectral transmittance decreased gradually. There is an apparent transmission valley at 676 nm. And then two dimensional correlation spectrum technology was used to analyze the sensitive absorption band of chlorophyll in water body. Comprehensive observation of the spectral characteristics of water samples can be carried out much accurately by analyzing two-dimensional correlation spectra of synchronous and asynchronous spectrograms. And the effective spectral response bands of the chlorophyll content were found at 488 and 676 nm. Then the NDWCI (normalized difference water chlorophyll index) was established with the transmittance of red band and blue band. Two regression models were built to predict the chlorophyll concentration in water. One is a multiple linear regression model based on the original transmittances at 488 and 676 nm. The other is the linear regression model based on NDWCI. By comparison, the model based on NDWCI was better. The R2 of its training model reached to 0.7712, and the root mean square error of calibration was 45.5099 mg x L(-1). The R2 of prediction model reached to 0.7658, and the root mean square error of prediction was 39.5038 mg x L(-1). It reached to a practical level to predict the chlorophyll content in water body rapidly.

  6. Community Detection for Correlation Matrices

    NASA Astrophysics Data System (ADS)

    MacMahon, Mel; Garlaschelli, Diego

    2015-04-01

    A challenging problem in the study of complex systems is that of resolving, without prior information, the emergent, mesoscopic organization determined by groups of units whose dynamical activity is more strongly correlated internally than with the rest of the system. The existing techniques to filter correlations are not explicitly oriented towards identifying such modules and can suffer from an unavoidable information loss. A promising alternative is that of employing community detection techniques developed in network theory. Unfortunately, this approach has focused predominantly on replacing network data with correlation matrices, a procedure that we show to be intrinsically biased because of its inconsistency with the null hypotheses underlying the existing algorithms. Here, we introduce, via a consistent redefinition of null models based on random matrix theory, the appropriate correlation-based counterparts of the most popular community detection techniques. Our methods can filter out both unit-specific noise and system-wide dependencies, and the resulting communities are internally correlated and mutually anticorrelated. We also implement multiresolution and multifrequency approaches revealing hierarchically nested subcommunities with "hard" cores and "soft" peripheries. We apply our techniques to several financial time series and identify mesoscopic groups of stocks which are irreducible to a standard, sectorial taxonomy; detect "soft stocks" that alternate between communities; and discuss implications for portfolio optimization and risk management.

  7. A canonical correlation analysis based method for contamination event detection in water sources.

    PubMed

    Li, Ruonan; Liu, Shuming; Smith, Kate; Che, Han

    2016-06-15

    In this study, a general framework integrating a data-driven estimation model is employed for contamination event detection in water sources. Sequential canonical correlation coefficients are updated in the model using multivariate water quality time series. The proposed method utilizes canonical correlation analysis for studying the interplay between two sets of water quality parameters. The model is assessed by precision, recall and F-measure. The proposed method is tested using data from a laboratory contaminant injection experiment. The proposed method could detect a contamination event 1 minute after the introduction of 1.600 mg l(-1) acrylamide solution. With optimized parameter values, the proposed method can correctly detect 97.50% of all contamination events with no false alarms. The robustness of the proposed method can be explained using the Bauer-Fike theorem. PMID:27264637

  8. Staff line detection and revision algorithm based on subsection projection and correlation algorithm

    NASA Astrophysics Data System (ADS)

    Yang, Yin-xian; Yang, Ding-li

    2013-03-01

    Staff line detection plays a key role in OMR technology, and is the precon-ditions of subsequent segmentation 1& recognition of music sheets. For the phenomena of horizontal inclination & curvature of staff lines and vertical inclination of image, which often occur in music scores, an improved approach based on subsection projection is put forward to realize the detection of original staff lines and revision in an effect to implement staff line detection more successfully. Experimental results show the presented algorithm can detect and revise staff lines fast and effectively.

  9. Phase space correlation to improve detection accuracy.

    PubMed

    Carroll, T L; Rachford, F J

    2009-09-01

    The standard method used for detecting signals in radar or sonar is cross correlation. The accuracy of the detection with cross correlation is limited by the bandwidth of the signals. We show that by calculating the cross correlation based on points that are nearby in phase space rather than points that are simultaneous in time, the detection accuracy is improved. The phase space correlation technique works for some standard radar signals, but it is especially well suited to chaotic signals because trajectories that are adjacent in phase space move apart from each other at an exponential rate.

  10. A Comparison Study of Canonical Correlation Analysis Based Methods for Detecting Steady-State Visual Evoked Potentials

    PubMed Central

    Nakanishi, Masaki; Wang, Yijun; Wang, Yu-Te; Jung, Tzyy-Ping

    2015-01-01

    Canonical correlation analysis (CCA) has been widely used in the detection of the steady-state visual evoked potentials (SSVEPs) in brain-computer interfaces (BCIs). The standard CCA method, which uses sinusoidal signals as reference signals, was first proposed for SSVEP detection without calibration. However, the detection performance can be deteriorated by the interference from the spontaneous EEG activities. Recently, various extended methods have been developed to incorporate individual EEG calibration data in CCA to improve the detection performance. Although advantages of the extended CCA methods have been demonstrated in separate studies, a comprehensive comparison between these methods is still missing. This study performed a comparison of the existing CCA-based SSVEP detection methods using a 12-class SSVEP dataset recorded from 10 subjects in a simulated online BCI experiment. Classification accuracy and information transfer rate (ITR) were used for performance evaluation. The results suggest that individual calibration data can significantly improve the detection performance. Furthermore, the results showed that the combination method based on the standard CCA and the individual template based CCA (IT-CCA) achieved the highest performance. PMID:26479067

  11. Producing and Detecting Correlated Atoms

    SciTech Connect

    Westbrook, C. I.; Schellekens, M.; Perrin, A.; Krachmalnicoff, V.; Viana Gomes, J.; Trebbia, J.-B.; Esteve, J.; Chang, H.; Bouchoule, I.; Boiron, D.; Aspect, A.; Jeltes, T.; McNamara, J.; Hogervorst, W.; Vassen, W.

    2006-11-07

    We discuss experiments to produce and detect atom correlations in a degenerate or nearly degenerate gas of neutral atoms. First we treat the atomic analog of the celebrated Hanbury Brown Twiss experiment, in which atom correlations result simply from interference effects without any atom interactions. We have performed this experiment for both bosons and fermions. Next we show how atom interactions produce correlated atoms using the atomic analog of spontaneous four-wave mixing. Finally, we briefly mention experiments on a one dimensional gas on an atom chip in which correlation effects due to both interference and interactions have been observed.

  12. A novel coefficient for detecting and quantifying asymmetry of California electricity market based on asymmetric detrended cross-correlation analysis

    NASA Astrophysics Data System (ADS)

    Wang, Fang

    2016-06-01

    In order to detect and quantify asymmetry of two time series, a novel cross-correlation coefficient is proposed based on recent asymmetric detrended cross-correlation analysis (A-DXA), which we called A-DXA coefficient. The A-DXA coefficient, as an important extension of DXA coefficient ρ D X A , contains two directional asymmetric cross-correlated indexes, describing upwards and downwards asymmetric cross-correlations, respectively. By using the information of directional covariance function of two time series and directional variance function of each series itself instead of power-law between the covariance function and time scale, the proposed A-DXA coefficient can well detect asymmetry between the two series no matter whether the cross-correlation is significant or not. By means of the proposed A-DXA coefficient conducted over the asymmetry for California electricity market, we found that the asymmetry between the prices and loads is not significant for daily average data in 1999 yr market (before electricity crisis) but extremely significant for those in 2000 yr market (during the crisis). To further uncover the difference of asymmetry between the years 1999 and 2000, a modified H statistic (MH) and ΔMH statistic are proposed. One of the present contributions is that the high MH values calculated for hourly data exist in majority months in 2000 market. Another important conclusion is that the cross-correlation with downwards dominates over the whole 1999 yr in contrast to the cross-correlation with upwards dominates over the 2000 yr.

  13. A novel coefficient for detecting and quantifying asymmetry of California electricity market based on asymmetric detrended cross-correlation analysis.

    PubMed

    Wang, Fang

    2016-06-01

    In order to detect and quantify asymmetry of two time series, a novel cross-correlation coefficient is proposed based on recent asymmetric detrended cross-correlation analysis (A-DXA), which we called A-DXA coefficient. The A-DXA coefficient, as an important extension of DXA coefficient ρDXA, contains two directional asymmetric cross-correlated indexes, describing upwards and downwards asymmetric cross-correlations, respectively. By using the information of directional covariance function of two time series and directional variance function of each series itself instead of power-law between the covariance function and time scale, the proposed A-DXA coefficient can well detect asymmetry between the two series no matter whether the cross-correlation is significant or not. By means of the proposed A-DXA coefficient conducted over the asymmetry for California electricity market, we found that the asymmetry between the prices and loads is not significant for daily average data in 1999 yr market (before electricity crisis) but extremely significant for those in 2000 yr market (during the crisis). To further uncover the difference of asymmetry between the years 1999 and 2000, a modified H statistic (MH) and ΔMH statistic are proposed. One of the present contributions is that the high MH values calculated for hourly data exist in majority months in 2000 market. Another important conclusion is that the cross-correlation with downwards dominates over the whole 1999 yr in contrast to the cross-correlation with upwards dominates over the 2000 yr.

  14. Cross-correlation detection and analysis for California's electricity market based on analogous multifractal analysis.

    PubMed

    Wang, Fang; Liao, Gui-ping; Li, Jian-hui; Zou, Rui-biao; Shi, Wen

    2013-03-01

    A novel method, which we called the analogous multifractal cross-correlation analysis, is proposed in this paper to study the multifractal behavior in the power-law cross-correlation between price and load in California electricity market. In addition, a statistic ρAMF-XA, which we call the analogous multifractal cross-correlation coefficient, is defined to test whether the cross-correlation between two given signals is genuine or not. Our analysis finds that both the price and load time series in California electricity market express multifractal nature. While, as indicated by the ρAMF-XA statistical test, there is a huge difference in the cross-correlation behavior between the years 1999 and 2000 in California electricity markets.

  15. Cross-correlation detection and analysis for California's electricity market based on analogous multifractal analysis

    NASA Astrophysics Data System (ADS)

    Wang, Fang; Liao, Gui-ping; Li, Jian-hui; Zou, Rui-biao; Shi, Wen

    2013-03-01

    A novel method, which we called the analogous multifractal cross-correlation analysis, is proposed in this paper to study the multifractal behavior in the power-law cross-correlation between price and load in California electricity market. In addition, a statistic ρAMF -XA, which we call the analogous multifractal cross-correlation coefficient, is defined to test whether the cross-correlation between two given signals is genuine or not. Our analysis finds that both the price and load time series in California electricity market express multifractal nature. While, as indicated by the ρAMF -XA statistical test, there is a huge difference in the cross-correlation behavior between the years 1999 and 2000 in California electricity markets.

  16. Defect Detection in Correlated Noise

    NASA Astrophysics Data System (ADS)

    Dogandžić, Aleksandar; Eua-Anant, Nawanat

    2004-02-01

    We present methods for detecting NDE defect signals in correlated noise having unknown covariance. The proposed detectors are derived using the statistical theory of generalized likelihood ratio (GLR) tests and multivariate analysis of variance (MANOVA). We consider both real and complex data models. To allow accurate estimation of the noise covariance, we incorporate secondary data containing only noise into detector design. Probability distributions of the GLR test statistics are derived under the null hypothesis, i.e. assuming that the signal is absent, and used for detector design. We apply the proposed methods to simulated and experimental data and demonstrate their superior performance compared with the detectors that neglect noise correlation.

  17. An automated cross-correlation based event detection technique and its application to surface passive data set

    USGS Publications Warehouse

    Forghani-Arani, Farnoush; Behura, Jyoti; Haines, Seth S.; Batzle, Mike

    2013-01-01

    In studies on heavy oil, shale reservoirs, tight gas and enhanced geothermal systems, the use of surface passive seismic data to monitor induced microseismicity due to the fluid flow in the subsurface is becoming more common. However, in most studies passive seismic records contain days and months of data and manually analysing the data can be expensive and inaccurate. Moreover, in the presence of noise, detecting the arrival of weak microseismic events becomes challenging. Hence, the use of an automated, accurate and computationally fast technique for event detection in passive seismic data is essential. The conventional automatic event identification algorithm computes a running-window energy ratio of the short-term average to the long-term average of the passive seismic data for each trace. We show that for the common case of a low signal-to-noise ratio in surface passive records, the conventional method is not sufficiently effective at event identification. Here, we extend the conventional algorithm by introducing a technique that is based on the cross-correlation of the energy ratios computed by the conventional method. With our technique we can measure the similarities amongst the computed energy ratios at different traces. Our approach is successful at improving the detectability of events with a low signal-to-noise ratio that are not detectable with the conventional algorithm. Also, our algorithm has the advantage to identify if an event is common to all stations (a regional event) or to a limited number of stations (a local event). We provide examples of applying our technique to synthetic data and a field surface passive data set recorded at a geothermal site.

  18. Progress of a Cross-correlation Based Optical Strain Measurement Technique for Detecting Radial Growth on a Rotating Disk

    NASA Technical Reports Server (NTRS)

    Clem, Michelle M.; Woike, Mark; Abdul-Aziz, Ali

    2013-01-01

    The Aeronautical Sciences Project under NASAs Fundamental Aeronautics Program is extremely interested in the development of fault detection technologies, such as optical surface measurements in the internal parts of a flow path, for in situ health monitoring of gas turbine engines. In situ health monitoring has the potential to detect flaws, i.e. cracks in key components, such as engine turbine disks, before the flaws lead to catastrophic failure. In the present study, a cross-correlation imaging technique is investigated in a proof-of-concept study as a possible optical technique to measure the radial growth and strain field on an already cracked sub-scale turbine engine disk under loaded conditions in the NASA Glenn Research Centers High Precision Rotordynamics Laboratory. The optical strain measurement technique under investigation offers potential fault detection using an applied background consisting of a high-contrast random speckle pattern and imaging the background under unloaded and loaded conditions with a CCD camera. Spinning the cracked disk at high speeds induces an external load, resulting in a radial growth of the disk of approximately 50.8-m in the flawed region and hence, a localized strain field. When imaging the cracked disk under static conditions, the disk will appear shifted. The resulting background displacements between the two images will then be measured using the two-dimensional cross-correlation algorithms implemented in standard Particle Image Velocimetry (PIV) software to track the disk growth, which facilitates calculation of the localized strain field. In order to develop and validate this optical strain measurement technique an initial proof-of-concept experiment is carried out in a controlled environment. Using PIV optimization principles and guidelines, three potential backgrounds, for future use on the rotating disk, are developed and investigated in the controlled experiment. A range of known shifts are induced on the

  19. Detection of Cardiac Quiescence from B-Mode Echocardiography Using a Correlation-Based Frame-to-Frame Deviation Measure

    PubMed Central

    Mcclellan, James H.; Ravichandran, Lakshminarayan; Tridandapani, Srini

    2013-01-01

    Two novel methods for detecting cardiac quiescent phases from B-mode echocardiography using a correlation-based frame-to-frame deviation measure were developed. Accurate knowledge of cardiac quiescence is crucial to the performance of many imaging modalities, including computed tomography coronary angiography (CTCA). Synchronous electrocardiography (ECG) and echocardiography data were obtained from 10 healthy human subjects (four male, six female, 23–45 years) and the interventricular septum (IVS) was observed using the apical four-chamber echocardiographic view. The velocity of the IVS was derived from active contour tracking and verified using tissue Doppler imaging echocardiography methods. In turn, the frame-to-frame deviation methods for identifying quiescence of the IVS were verified using active contour tracking. The timing of the diastolic quiescent phase was found to exhibit both inter- and intra-subject variability, suggesting that the current method of CTCA gating based on the ECG is suboptimal and that gating based on signals derived from cardiac motion are likely more accurate in predicting quiescence for cardiac imaging. Two robust and efficient methods for identifying cardiac quiescent phases from B-mode echocardiographic data were developed and verified. The methods presented in this paper will be used to develop new CTCA gating techniques and quantify the resulting potential improvement in CTCA image quality. PMID:26609501

  20. Investigation of a Cross-Correlation Based Optical Strain Measurement Technique for Detecting radial Growth on a Rotating Disk

    NASA Technical Reports Server (NTRS)

    Clem, Michelle M.; Woike, Mark R.

    2013-01-01

    The Aeronautical Sciences Project under NASA`s Fundamental Aeronautics Program is extremely interested in the development of novel measurement technologies, such as optical surface measurements in the internal parts of a flow path, for in situ health monitoring of gas turbine engines. In situ health monitoring has the potential to detect flaws, i.e. cracks in key components, such as engine turbine disks, before the flaws lead to catastrophic failure. In the present study, a cross-correlation imaging technique is investigated in a proof-of-concept study as a possible optical technique to measure the radial growth and strain field on an already cracked sub-scale turbine engine disk under loaded conditions in the NASA Glenn Research Center`s High Precision Rotordynamics Laboratory. The optical strain measurement technique under investigation offers potential fault detection using an applied high-contrast random speckle pattern and imaging the pattern under unloaded and loaded conditions with a CCD camera. Spinning the cracked disk at high speeds induces an external load, resulting in a radial growth of the disk of approximately 50.0-im in the flawed region and hence, a localized strain field. When imaging the cracked disk under static conditions, the disk will be undistorted; however, during rotation the cracked region will grow radially, thus causing the applied particle pattern to be .shifted`. The resulting particle displacements between the two images will then be measured using the two-dimensional cross-correlation algorithms implemented in standard Particle Image Velocimetry (PIV) software to track the disk growth, which facilitates calculation of the localized strain field. In order to develop and validate this optical strain measurement technique an initial proof-of-concept experiment is carried out in a controlled environment. Using PIV optimization principles and guidelines, three potential speckle patterns, for future use on the rotating disk, are developed

  1. Progress of a Cross-Correlation Based Optical Strain Measurement Technique for Detecting Radial Growth on a Rotating Disk

    NASA Technical Reports Server (NTRS)

    Clem, Michelle M.; Woike, Mark R.; Abdul-Aziz, Ali

    2014-01-01

    The Aeronautical Sciences Project under NASA's Fundamental Aeronautics Program is interested in the development of novel measurement technologies, such as optical surface measurements for the in situ health monitoring of critical constituents of the internal flow path. In situ health monitoring has the potential to detect flaws, i.e. cracks in key components, such as engine turbine disks, before the flaws lead to catastrophic failure. The present study, aims to further validate and develop an optical strain measurement technique to measure the radial growth and strain field of an already cracked disk, mimicking the geometry of a sub-scale turbine engine disk, under loaded conditions in the NASA Glenn Research Center's High Precision Rotordynamics Laboratory. The technique offers potential fault detection by imaging an applied high-contrast random speckle pattern under unloaded and loaded conditions with a CCD camera. Spinning the cracked disk at high speeds (loaded conditions) induces an external load, resulting in a radial growth of the disk of approximately 50.0-µm in the flawed region and hence, a localized strain field. When imaging the cracked disk under static conditions, the disk will be undistorted; however, during rotation the cracked region will grow radially, thus causing the applied particle pattern to be 'shifted'. The resulting particle displacements between the two images is measured using the two-dimensional cross-correlation algorithms implemented in standard Particle Image Velocimetry (PIV) software to track the disk growth, which facilitates calculation of the localized strain field. A random particle distribution is adhered onto the surface of the cracked disk and two bench top experiments are carried out to evaluate the technique's ability to measure the induced particle displacements. The disk is shifted manually using a translation stage equipped with a fine micrometer and a hotplate is used to induce thermal growth of the disk, causing the

  2. Efficiency of using correlation function for estimation of probability of substance detection on the base of THz spectral dynamics

    NASA Astrophysics Data System (ADS)

    Trofimov, Vyacheslav A.; Peskov, Nikolay V.; Kirillov, Dmitry A.

    2012-10-01

    One of the problems arising in Time-Domain THz spectroscopy for the problem of security is the developing the criteria for assessment of probability for the detection and identification of the explosive and drugs. We analyze the efficiency of using the correlation function and another functional (more exactly, spectral norm) for this aim. These criteria are applied to spectral lines dynamics. For increasing the reliability of the assessment we subtract the averaged value of THz signal during time of analysis of the signal: it means deleting the constant from this part of the signal. Because of this, we can increase the contrast of assessment. We compare application of the Fourier-Gabor transform with unbounded (for example, Gaussian) window, which slides along the signal, for finding the spectral lines dynamics with application of the Fourier transform in short time interval (FTST), in which the Fourier transform is applied to parts of the signals, for the same aim. These methods are close each to other. Nevertheless, they differ by series of frequencies which they use. It is important for practice that the optimal window shape depends on chosen method for obtaining the spectral dynamics. The probability enhancements if we can find the train of pulses with different frequencies, which follow sequentially. We show that there is possibility to get pure spectral lines dynamics even under the condition of distorted spectrum of the substance response on the action of the THz pulse.

  3. Gas correlation lidar for methane detection

    NASA Technical Reports Server (NTRS)

    Galletti, E.; Zanzottera, E.; Draghi, S.; Garbi, M.; Petroni, R.

    1986-01-01

    A new type of DIAL system for the detection of methane in the atmosphere is being developed. The main feature of this lidar is the use of a gas correlation technique to obtain the reference signal by means of a single laser pulse, instead of two shots at different wavelengths. This fact is useful to make measurements on fast moving platforms. To meet the infrared absorption band of methane an optical parametric oscillator (OPO) was used with a LiNbO3 crystal as active element, and a tuning range between 1.5 divided by 4 microns. As known, the major problem to overcome in parametric oscillators are the pump beam quality and the difficulty in reducing the linewidth. The first requirement is met by using, as a pump, a Nd-YAG laser based on a new type of resonator cavity, named SFUR (Self Filtering Unstable Resonator). The laser emits, with high efficiency, near diffraction limited pulsed beams of about 250 mJ of energy, 20 ns of duration at 10 pps of frequency repetition rate. On the other hand, the gas correlation technique allows the operation with a bandwidth as large as 1/cm, which is obtainable using only a diffraction grating as a dispersive element in the OPO cavity.

  4. Distortion-insensitive correlation constellation detection

    NASA Astrophysics Data System (ADS)

    Casey, Charles; Hassebrook, Laurence G.; Crane, Eli; Davidson, Aaron

    2011-04-01

    There are applications that require detection of multiple features which remain consistent in shape locally, but may change position with respect to one another globally. We refer to these feature sets as multi-feature constellations. We introduce a multi-level correlation filter design which uses composite feature detection filters, which on one level detect local features, and then on the next level detect constellations of these local feature responses. We demonstrate the constellation filter method with sign language recognition and fingerprint matching.

  5. Change Point Detection in Correlation Networks.

    PubMed

    Barnett, Ian; Onnela, Jukka-Pekka

    2016-01-07

    Many systems of interacting elements can be conceptualized as networks, where network nodes represent the elements and network ties represent interactions between the elements. In systems where the underlying network evolves, it is useful to determine the points in time where the network structure changes significantly as these may correspond to functional change points. We propose a method for detecting change points in correlation networks that, unlike previous change point detection methods designed for time series data, requires minimal distributional assumptions. We investigate the difficulty of change point detection near the boundaries of the time series in correlation networks and study the power of our method and competing methods through simulation. We also show the generalizable nature of the method by applying it to stock price data as well as fMRI data.

  6. Progress of a Cross-Correlation Based Optical Strain Measurement Technique for Detecting Radial Growth on a Rotating Disk

    NASA Technical Reports Server (NTRS)

    Clem, Michelle M.; Abdul-Aziz, Ali; Woike, Mark R.; Fralick, Gustave C.

    2015-01-01

    The modern turbine engine operates in a harsh environment at high speeds and is repeatedly exposed to combined high mechanical and thermal loads. The cumulative effects of these external forces lead to high stresses and strains on the engine components, such as the rotating turbine disks, which may eventually lead to a catastrophic failure if left undetected. The operating environment makes it difficult to use conventional strain gauges, therefore, non-contact strain measurement techniques is of interest to NASA and the turbine engine community. This presentation describes one such approach; the use of cross correlation analysis to measure strain experienced by the engine turbine disk with the goal of assessing potential faults and damage.

  7. Cluster identification based on correlations

    NASA Astrophysics Data System (ADS)

    Schulman, L. S.

    2012-04-01

    The problem addressed is the identification of cooperating agents based on correlations created as a result of the joint action of these and other agents. A systematic method for using correlations beyond second moments is developed. The technique is applied to a didactic example, the identification of alphabet letters based on correlations among the pixels used in an image of the letter. As in this example, agents can belong to more than one cluster. Moreover, the identification scheme does not require that the patterns be known ahead of time.

  8. Time-resolved single-photon detection module based on silicon photomultiplier: A novel building block for time-correlated measurement systems.

    PubMed

    Martinenghi, E; Di Sieno, L; Contini, D; Sanzaro, M; Pifferi, A; Dalla Mora, A

    2016-07-01

    We present the design and preliminary characterization of the first detection module based on Silicon Photomultiplier (SiPM) tailored for single-photon timing applications. The aim of this work is to demonstrate, thanks to the design of a suitable module, the possibility to easily exploit SiPM in many applications as an interesting detector featuring large active area, similarly to photomultipliers tubes, but keeping the advantages of solid state detectors (high quantum efficiency, low cost, compactness, robustness, low bias voltage, and insensitiveness to magnetic field). The module integrates a cooled SiPM with a total photosensitive area of 1 mm(2) together with the suitable avalanche signal read-out circuit, the signal conditioning, the biasing electronics, and a Peltier cooler driver for thermal stabilization. It is able to extract the single-photon timing information with resolution better than 100 ps full-width at half maximum. We verified the effective stabilization in response to external thermal perturbations, thus proving the complete insensitivity of the module to environment temperature variations, which represents a fundamental parameter to profitably use the instrument for real-field applications. We also characterized the single-photon timing resolution, the background noise due to both primary dark count generation and afterpulsing, the single-photon detection efficiency, and the instrument response function shape. The proposed module can become a reliable and cost-effective building block for time-correlated single-photon counting instruments in applications requiring high collection capability of isotropic light and detection efficiency (e.g., fluorescence decay measurements or time-domain diffuse optics systems). PMID:27475542

  9. Time-resolved single-photon detection module based on silicon photomultiplier: A novel building block for time-correlated measurement systems

    NASA Astrophysics Data System (ADS)

    Martinenghi, E.; Di Sieno, L.; Contini, D.; Sanzaro, M.; Pifferi, A.; Dalla Mora, A.

    2016-07-01

    We present the design and preliminary characterization of the first detection module based on Silicon Photomultiplier (SiPM) tailored for single-photon timing applications. The aim of this work is to demonstrate, thanks to the design of a suitable module, the possibility to easily exploit SiPM in many applications as an interesting detector featuring large active area, similarly to photomultipliers tubes, but keeping the advantages of solid state detectors (high quantum efficiency, low cost, compactness, robustness, low bias voltage, and insensitiveness to magnetic field). The module integrates a cooled SiPM with a total photosensitive area of 1 mm2 together with the suitable avalanche signal read-out circuit, the signal conditioning, the biasing electronics, and a Peltier cooler driver for thermal stabilization. It is able to extract the single-photon timing information with resolution better than 100 ps full-width at half maximum. We verified the effective stabilization in response to external thermal perturbations, thus proving the complete insensitivity of the module to environment temperature variations, which represents a fundamental parameter to profitably use the instrument for real-field applications. We also characterized the single-photon timing resolution, the background noise due to both primary dark count generation and afterpulsing, the single-photon detection efficiency, and the instrument response function shape. The proposed module can become a reliable and cost-effective building block for time-correlated single-photon counting instruments in applications requiring high collection capability of isotropic light and detection efficiency (e.g., fluorescence decay measurements or time-domain diffuse optics systems).

  10. Edge-based correlation image registration for multispectral imaging

    DOEpatents

    Nandy, Prabal

    2009-11-17

    Registration information for images of a common target obtained from a plurality of different spectral bands can be obtained by combining edge detection and phase correlation. The images are edge-filtered, and pairs of the edge-filtered images are then phase correlated to produce phase correlation images. The registration information can be determined based on these phase correlation images.

  11. The waveform correlation event detection system global prototype software design

    SciTech Connect

    Beiriger, J.I.; Moore, S.G.; Trujillo, J.R.; Young, C.J.

    1997-12-01

    The WCEDS prototype software system was developed to investigate the usefulness of waveform correlation methods for CTBT monitoring. The WCEDS prototype performs global seismic event detection and has been used in numerous experiments. This report documents the software system design, presenting an overview of the system operation, describing the system functions, tracing the information flow through the system, discussing the software structures, and describing the subsystem services and interactions. The effectiveness of the software design in meeting project objectives is considered, as well as opportunities for code refuse and lessons learned from the development process. The report concludes with recommendations for modifications and additions envisioned for regional waveform-correlation-based detector.

  12. Waveform Correlation Based Detection of Aftershocks of the 6 August 2007 4.1 Mw Crandall Canyon Mine Collapse in Central Utah

    NASA Astrophysics Data System (ADS)

    Koper, K. D.; Kubacki, T. M.; McCarter, M. K.; Pankow, K. L.

    2012-12-01

    On 6 August 2007 at 08:48:40 (UTC) a 3.9 ML seismic event occurred about 22 km ESE of the town of Mount Pleasant in the coal mining district of central Utah [Pechmann et al., 2008]. An epicenter of 39.4675°N, 111.2249°W and source depth of 0.5 km were determined by University of Utah Seismograph Stations (UUSS). It quickly became clear that the seismic event was associated with a catastrophic collapse at the Crandall Canyon coal mine in which six miners were killed. Subsequent moment tensor inversion showed that a pure double-couple mechanism did not fit the observed waveforms and instead a mechanism dominated by a closing crack (which incorporates an isotropic component) and a smaller residual double-couple and/or CLVD source was preferred [Ford et al., 2008]. The full moment tensor had a scalar moment corresponding to 4.1 Mw. In the 60 days following the mine collapse UUSS located 42 seismic events in the immediate source region. These events had magnitudes of 0.8-2.5 Mc and were detected using standard network association procedures with data from permanent stations of the Utah Regional Seismic Network (URSN), as well as 5 temporary seismometers that UUSS installed in the source area within 2-3 days of the main event. Simple inspection of continuous data from the nearest station shows evidence for a much larger number of seismic events, especially in the hours immediately following the collapse. These events originally went undetected because they were too small to be recorded at a significant number of the permanent URSN stations. Here we use waveform correlation methods to formally detect and locate these tiny aftershocks. We performed multi-channel cross-correlation [vanDecar and Crosson, 1990] on the 42 catalog events using data recorded at the nearest permanent broadband URSN station, MTPU, which was located about 19 km to the south of the mine. A 15-s long window starting 5 s before the expected P arrival was used on data that had been bandpass filtered

  13. Object detection by optical correlator and intelligence recognition surveillance systems

    NASA Astrophysics Data System (ADS)

    Sheng, Yunlong

    2013-09-01

    We report a recent work on robust object detection in high-resolution aerial imagery in urban environment for Intelligence, Surveillance and Recognition (ISR) missions. Our approaches used the simple linear iterative clustering (SLIC) algorithm, which combines regional and edge information to form the superpixels. The irregularity in size and shape of the superpixels measured with the Hausdorff distance served to determine the salient regions in the very large aerial images. Then, the car detection was performed with both the component-based approach and the featurebased approaches. We merged the superpixels with the statistical region merging (SRM) algorithm. The regions were described by the radiometric, geometrical moments and shape features, and classified using the Support Vector Machine (SVM). The cast shadow were detected and removed by a radiometry based tricolor attenuation model (TAM). Detection of object parts is less sensitive to occlusion, rotation, and changes in scale, view angle and illumination than detection of the object as whole. The object parts were combined to the object according to their unique spatial relations. On the other hand, we used the invariant scale invariant feature transform (SIFT) features to describe superpixels and classed them by the SVM as belong or not to the object. All along our recent work we still trace the brilliant ideas in early days by H. John Caulfield and other pioneers of optical pattern recognition, for improving the discrimination of the matched spatial filter with linear combinations of cross-correlations, which have been inherited transformed and reinvented to achieve tremendous progress.

  14. Neural correlates of humor detection and appreciation.

    PubMed

    Moran, Joseph M; Wig, Gagan S; Adams, Reginald B; Janata, Petr; Kelley, William M

    2004-03-01

    Humor is a uniquely human quality whose neural substrates remain enigmatic. The present report combined dynamic, real-life content and event-related functional magnetic resonance imaging (fMRI) to dissociate humor detection ("getting the joke") from humor appreciation (the affective experience of mirth). During scanning, subjects viewed full-length episodes of the television sitcoms Seinfeld or The Simpsons. Brain activity time-locked to humor detection moments revealed increases in left inferior frontal and posterior temporal cortices, whereas brain activity time-locked to moments of humor appreciation revealed increases in bilateral regions of insular cortex and the amygdala. These findings provide evidence that humor depends critically upon extant neural systems important for resolving incongruities (humor detection) and for the expression of affect (humor appreciation). PMID:15006673

  15. Detection of virus in shrimp using digital color correlation

    NASA Astrophysics Data System (ADS)

    Alvarez-Borrego, Josue; Chavez-Sanchez, Cristina; Bueno-Ibarra, Mario A.

    1999-07-01

    Detection of virus in shrimp tissue using digital color correlation is presented. Phase filters in three channels (red, green and blue) were used in order to detect HPV virus like target. These first results obtained showed that is possible to detect virus in shrimp tissue. More research must be made with color correlation in order to consider natural morphology of the virus, color, scale and rotation and noise in the samples.

  16. Detecting correlations among functional-sequence motifs

    NASA Astrophysics Data System (ADS)

    Pirino, Davide; Rigosa, Jacopo; Ledda, Alice; Ferretti, Luca

    2012-06-01

    Sequence motifs are words of nucleotides in DNA with biological functions, e.g., gene regulation. Identification of such words proceeds through rejection of Markov models on the expected motif frequency along the genome. Additional biological information can be extracted from the correlation structure among patterns of motif occurrences. In this paper a log-linear multivariate intensity Poisson model is estimated via expectation maximization on a set of motifs along the genome of E. coli K12. The proposed approach allows for excitatory as well as inhibitory interactions among motifs and between motifs and other genomic features like gene occurrences. Our findings confirm previous stylized facts about such types of interactions and shed new light on genome-maintenance functions of some particular motifs. We expect these methods to be applicable to a wider set of genomic features.

  17. Endotoxemia: methods of detection and clinical correlates.

    PubMed Central

    Hurley, J C

    1995-01-01

    As an assay for endotoxin, the Limulus amebocyte lysate assay has several desirable properties: sensitivity, specificity, and potential for adaptation to a quantitative format. Several modifications have been developed to enhance its potential for clinical application. The modifications that allow quantitative measurement of endotoxin and also improve its application to blood samples are described in this review. In fluids other than blood, the detection of endotoxin with the Limulus amebocyte lysate assay can be used as an aid to identify the presence of gram-negative bacteria, and the assay has established utility. With blood, however, there are a range of factors that interfere with the detection of endotoxemia and there are disparate views with respect to the diagnostic and prognostic significance of the test results. In general, the clinical significance of the finding of endotoxemia broadly parallels the frequency and importance of gram-negative sepsis in the patient groups studied and a decline in endotoxin levels accompanies clinical improvement. However, with therapies designed to reduce levels of endotoxin, or to antagonize its effects, it is unclear whether clinical improvement occurs as a consequence of changes in the levels of endotoxemia. PMID:7621402

  18. Object Correlation and Maneuver Detection Using Optimal Control Performance Metrics

    NASA Astrophysics Data System (ADS)

    Holzinger, M.; Scheeres, D.

    2010-09-01

    Object correlation and maneuver detection are persistent problems in space surveillance and space object catalog maintenance. This paper demonstrates the utility of using quadratic trajectory control cost, an analog to the trajectory L2-norm in control, as a distance metric with which to both correlate object tracks and detect maneuvers using Uncorrelated Tracks (UCTs), real-time sensor measurement residuals, and prior state uncertainty. State and measurement uncertainty are incorporated into the computation, and distributions of optimal control usage are computed. Both UCT correlation as well as maneuver detection are demonstrated in several scenarios Potential avenues for future research and contributions are summarized.

  19. Target detection from dual disparate sonar platforms using canonical correlations

    NASA Astrophysics Data System (ADS)

    Azimi-Sadjdadi, Mahmood R.; Tucker, J. Derek

    2008-04-01

    In this paper a new coherence-based feature extraction method for sonar imagery generated from two disparate sonar systems is developed. Canonical correlation analysis (CCA) is employed to identify coherent information from co-registered regions of interest (ROI's) that contain target activities, while at the same time extract useful coherent features from both images. The extracted features can be used for simultaneous detection and classification of target and non-target objects in the sonar images. In this study, a side-scan sonar that provides high resolution images with good target definition and a broadband sonar that generates low resolution images, but with reduced background clutter. The optimum Neyman-Pearson detector will be presented and then extended to the dual sensor platform scenarios. Test results of the proposed methods on a dual sonar imagery data set provided by the Naval Surface Warfare Center (NSWC) Panama City, FL will be presented. This database contains co-registered pair of images over the same target field with varying degree of detection difficulty and bottom clutter. The effectiveness of CCA as the optimum detection tool is demonstrated in terms of probability of detection and false alarm rate.

  20. The Prevalence, Correlates, Detection and Control of Diabetes among Older People in Low and Middle Income Countries. A 10/66 Dementia Research Group Population-Based Survey

    PubMed Central

    Salas, Aquiles; Acosta, Daisy; Ferri, Cleusa P.; Guerra, Mariella; Huang, Yueqin; Jacob, K. S.; Jimenez-Velazquez, Ivonne Z.; Llibre Rodriguez, Juan J.; Sosa, Ana L.; Uwakwe, Richard; Williams, Joseph D.; Jotheeswaran, A. T.; Liu, Zhaorui; Lopez Medina, A. M.; Salinas-Contreras, Rosa Maria; Prince, Martin J.

    2016-01-01

    Background Little is known of the epidemiology of diabetes among older people in low and middle income countries. We aimed to study and compare prevalence, social patterning, correlates, detection, treatment and control of diabetes among older people in Latin America, India, China and Nigeria. Methods Cross-sectional surveys in 13 catchment area sites in nine countries. Diagnosed diabetes was assessed in all sites through self-reported diagnosis. Undiagnosed diabetes was assessed in seven Latin American sites through fasting blood samples (glucose > = 7mmol/L). Results Total diabetes prevalence in catchment sites in Cuba (prevalence 24.2%, SMR 116), Puerto Rico (43.4%, 197), and urban (27.0%, 125), and rural Mexico (23.7%, 111) already exceeds that in the USA, while that in Venezuela (20.9%, 100) is similar. Diagnosed diabetes prevalence varied very widely, between low prevalences in sites in rural China (0.9%), rural India (6.6%) and Nigeria (6.0%). and 32.1% in Puerto Rico, explained mainly by access to health services. Treatment coverage varied substantially between sites. Diabetes control (40 to 61% of those diagnosed) was modest in the Latin American sites where this was studied. Diabetes was independently associated with less education, but more assets. Hypertension, central obesity and hypertriglyceridaemia, but not hypercholesterolaemia were consistently associated with total diabetes. Conclusions Diabetes prevalence is already high in most sites. Identifying undiagnosed cases is essential to quantify population burden, particularly in least developed settings where diagnosis is uncommon. Metabolic risk factors and associated lifestyles may play an important part in aetiology, but this requires confirmation with longitudinal data. Given the high prevalence among older people, more population research is indicated to quantify the impact of diabetes, and to monitor the effect of prevention and health system strengthening on prevalence, treatment and control

  1. Correlation studies on surface particle detection methods

    NASA Technical Reports Server (NTRS)

    Peterson, Ronald V.; White, James C.

    1988-01-01

    The accurate determination of dust levels on optical surfaces is necessary to assess sensor system performance. A comparison study was made on several particle measurement methods including those based on direct imaging and light scattering. The effectiveness of removing the particles from the surface prior to determining particle size distributions was also assessed. These studies revealed that some methods, especially those requiring particle removal before analysis, are subject to large systematic errors affecting particle size distributions. Thus, an understanding of the particle measurement methods employed is necessary before any surface cleanliness or obstruction value assignments are accepted as true representations of an optical surface contamination condition.

  2. Automatic particle detection in microscopy using temporal correlations.

    PubMed

    Röding, Magnus; Deschout, Hendrik; Martens, Thomas; Notelaers, Kristof; Hofkens, Johan; Ameloot, Marcel; Braeckmans, Kevin; Särkkä, Aila; Rudemo, Mats

    2013-10-01

    One of the fundamental problems in the analysis of single particle tracking data is the detection of individual particle positions from microscopy images. Distinguishing true particles from noise with a minimum of false positives and false negatives is an important step that will have substantial impact on all further analysis of the data. A common approach is to obtain a plausible set of particles from a larger set of candidate particles by filtering using manually selected threshold values for intensity, size, shape, and other parameters describing a particle. This introduces subjectivity into the analysis and hinders reproducibility. In this paper, we introduce a method for automatic selection of these threshold values based on maximizing temporal correlations in particle count time series. We use Markov Chain Monte Carlo to find the threshold values corresponding to the maximum correlation, and we study several experimental data sets to assess the performance of the method in practice by comparing manually selected threshold values from several independent experts with automatically selected threshold values. We conclude that the method produces useful results, reducing subjectivity and the need for manual intervention, a great benefit being its easy integratability into many already existing particle detection algorithms. PMID:23857566

  3. Large-Scale Test of Dynamic Correlation Processors: Implications for Correlation-Based Seismic Pipelines

    DOE PAGES

    Dodge, D. A.; Harris, D. B.

    2016-03-15

    Correlation detectors are of considerable interest to the seismic monitoring communities because they offer reduced detection thresholds and combine detection, location and identification functions into a single operation. They appear to be ideal for applications requiring screening of frequent repeating events. However, questions remain about how broadly empirical correlation methods are applicable. We describe the effectiveness of banks of correlation detectors in a system that combines traditional power detectors with correlation detectors in terms of efficiency, which we define to be the fraction of events detected by the correlators. This paper elaborates and extends the concept of a dynamic correlationmore » detection framework – a system which autonomously creates correlation detectors from event waveforms detected by power detectors; and reports observed performance on a network of arrays in terms of efficiency. We performed a large scale test of dynamic correlation processors on an 11 terabyte global dataset using 25 arrays in the single frequency band 1-3 Hz. The system found over 3.2 million unique signals and produced 459,747 screened detections. A very satisfying result is that, on average, efficiency grows with time and, after nearly 16 years of operation, exceeds 47% for events observed over all distance ranges and approaches 70% for near regional and 90% for local events. This observation suggests that future pipeline architectures should make extensive use of correlation detectors, principally for decluttering observations of local and near-regional events. Our results also suggest that future operations based on correlation detection will require commodity large-scale computing infrastructure, since the numbers of correlators in an autonomous system can grow into the hundreds of thousands.« less

  4. Application of time-correlated single photon counting and stroboscopic detection methods with an evanescent-wave fibre-optic sensor for fluorescence-lifetime-based pH measurements

    NASA Astrophysics Data System (ADS)

    Henning, Paul E.; Geissinger, Peter

    2012-04-01

    Quasi-distributed optical fibre sensor arrays containing luminescent sensor molecules can be read out spatially resolved utilizing optical time-of-flight detection (OTOFD) methods, which employ pulsed laser interrogation of the luminosensors and time-resolved detection of the sensor signals. In many cases, sensing is based on a change in sensor luminescence intensity; however, sensing based on luminescence lifetime changes is preferable because it reduces the need for field calibration. Because in OTOFD detection is time-resolved, luminescence-lifetime information is already available through the signal pulses, although in practise applications were restricted to sensors with long luminescence lifetimes (hundreds of ns). To implement lifetime-based sensing in crossed-optical-fibre-sensor arrays for sensor molecules with lifetimes less than 10 ns, two time-domain methods, time-correlated single photon counting and stroboscopic detection, were used to record the pH-dependent emission of a fluorescein derivative covalently attached to a highly-porous polymer. A two-term nonexponential decay function yielded both a good fit for experimental lifetime data during reconvolution and a pH response that matches Henderson-Hasselbalch behaviour, yielding a sensor accuracy of 0.02 pH units. Moreover, strong agreement was obtained for the two lifetime determination methods and with intensity-based measurements taken previously.

  5. Detection of PLGA-based nanoparticles at a single-cell level by synchrotron radiation FTIR spectromicroscopy and correlation with X-ray fluorescence microscopy

    PubMed Central

    Pascolo, Lorella; Bortot, Barbara; Benseny-Cases, Nuria; Gianoncelli, Alessandra; Tosi, Giovanni; Ruozi, Barbara; Rizzardi, Clara; De Martino, Eleonora; Vandelli, Maria Angela; Severini, Giovanni Maria

    2014-01-01

    Poly-lactide-co-glycolide (PLGA) is one of the few polymers approved by the US Food and Drug Administration as a carrier for drug administration in humans; therefore, it is one of the most used materials in the formulation of polymeric nanoparticles (NPs) for therapeutic purposes. Because the cellular uptake of polymeric NPs is a hot topic in the nanomedicine field, the development of techniques able to ensure incontrovertible evidence of the presence of NPs in the cells plays a key role in gaining understanding of their therapeutic potential. On the strength of this premise, this article aims to evaluate the application of synchrotron radiation-based Fourier transform infrared spectroscopy (SR-FTIR) spectromicroscopy and SR X-ray fluorescence (SR-XRF) microscopy in the study of the in vitro interaction of PLGA NPs with cells. To reach this goal, we used PLGA NPs, sized around 200 nm and loaded with superparamagnetic iron oxide NPs (PLGA-IO-NPs; Fe3O4; size, 10–15 nm). After exposing human mesothelial (MeT5A) cells to PLGA-IO-NPs (0.1 mg/mL), the cells were analyzed after fixation both by SR-FTIR spectromicroscopy and SR-XRF microscopy setups. SR-FTIR-SM enabled the detection of PLGA NPs at single-cell level, allowing polymer detection inside the biological matrix by the characteristic band in the 1,700–2,000 cm−1 region. The precise PLGA IR-signature (1,750 cm−1 centered pick) also was clearly evident within an area of high amide density. SR-XRF microscopy performed on the same cells investigated under SR-FTIR microscopy allowed us to put in evidence the Fe presence in the cells and to emphasize the intracellular localization of the PLGA-IO-NPs. These findings suggest that SR-FTIR and SR-XRF techniques could be two valuable tools to follow the PLGA NPs’ fate in in vitro studies on cell cultures. PMID:24944512

  6. Detection of PLGA-based nanoparticles at a single-cell level by synchrotron radiation FTIR spectromicroscopy and correlation with X-ray fluorescence microscopy.

    PubMed

    Pascolo, Lorella; Bortot, Barbara; Benseny-Cases, Nuria; Gianoncelli, Alessandra; Tosi, Giovanni; Ruozi, Barbara; Rizzardi, Clara; De Martino, Eleonora; Vandelli, Maria Angela; Severini, Giovanni Maria

    2014-01-01

    Poly-lactide-co-glycolide (PLGA) is one of the few polymers approved by the US Food and Drug Administration as a carrier for drug administration in humans; therefore, it is one of the most used materials in the formulation of polymeric nanoparticles (NPs) for therapeutic purposes. Because the cellular uptake of polymeric NPs is a hot topic in the nanomedicine field, the development of techniques able to ensure incontrovertible evidence of the presence of NPs in the cells plays a key role in gaining understanding of their therapeutic potential. On the strength of this premise, this article aims to evaluate the application of synchrotron radiation-based Fourier transform infrared spectroscopy (SR-FTIR) spectromicroscopy and SR X-ray fluorescence (SR-XRF) microscopy in the study of the in vitro interaction of PLGA NPs with cells. To reach this goal, we used PLGA NPs, sized around 200 nm and loaded with superparamagnetic iron oxide NPs (PLGA-IO-NPs; Fe₃O₄; size, 10-15 nm). After exposing human mesothelial (MeT5A) cells to PLGA-IO-NPs (0.1 mg/mL), the cells were analyzed after fixation both by SR-FTIR spectromicroscopy and SR-XRF microscopy setups. SR-FTIR-SM enabled the detection of PLGA NPs at single-cell level, allowing polymer detection inside the biological matrix by the characteristic band in the 1,700-2,000 cm(-1) region. The precise PLGA IR-signature (1,750 cm(-1) centered pick) also was clearly evident within an area of high amide density. SR-XRF microscopy performed on the same cells investigated under SR-FTIR microscopy allowed us to put in evidence the Fe presence in the cells and to emphasize the intracellular localization of the PLGA-IO-NPs. These findings suggest that SR-FTIR and SR-XRF techniques could be two valuable tools to follow the PLGA NPs' fate in in vitro studies on cell cultures. PMID:24944512

  7. Correlation filter for target detection and noise and clutter rejection

    NASA Astrophysics Data System (ADS)

    Goo, Gee-In

    1996-03-01

    This study was motivated by the infrared search and tracking (IRST) project. The investigation seeks to develop a technique that could detect the presence of a moving target in a cloud cluttered environment. Particularly, the signals, noise and clutters are unknown to the system. Thus, the correlation technique for image processing was developed, demonstrating its ability to detect moving targets of one pixel in size such as missiles and planes. A real-time image processor using this correlation technique was implemented. A Panoramic Imaging System, a 512 by 480 image processor at 30 frames per second was demonstrated. The demonstrated imaging system was operating at 120 mops (million operations per second) using an assembly- line processor architecture. The successful investigation of the correlation technique for image processing led to the developments of a correlation filter and the inspiration to develop the generalized filter. From the investigation, the author found that the Kalman filter, the Weiner filter and the correlation filter are special cases of a generalized filter. These filters can be related through a cost function in the constrained gain matrix of a generalized filter. However, in developing the correlation filter and the real-time imager, the correlation filter was observed to be a very effective noise and clutter rejecter and yet a very powerful detector. The filter was successfully applied to detection of pixel sized targets in noisy and cluttered IR images. Also it has been successfully applied to detection of intruders in cluttered, trees and bushes, video and IR images in security systems. This paper presents the derivation of the correlation filter for detection and estimation of unknown signals in unknown noise. Several noise rejection and cluttered rejection examples are presented.

  8. Robust Statistical Detection of Power-Law Cross-Correlation

    NASA Astrophysics Data System (ADS)

    Blythe, Duncan A. J.; Nikulin, Vadim V.; Müller, Klaus-Robert

    2016-06-01

    We show that widely used approaches in statistical physics incorrectly indicate the existence of power-law cross-correlations between financial stock market fluctuations measured over several years and the neuronal activity of the human brain lasting for only a few minutes. While such cross-correlations are nonsensical, no current methodology allows them to be reliably discarded, leaving researchers at greater risk when the spurious nature of cross-correlations is not clear from the unrelated origin of the time series and rather requires careful statistical estimation. Here we propose a theory and method (PLCC-test) which allows us to rigorously and robustly test for power-law cross-correlations, correctly detecting genuine and discarding spurious cross-correlations, thus establishing meaningful relationships between processes in complex physical systems. Our method reveals for the first time the presence of power-law cross-correlations between amplitudes of the alpha and beta frequency ranges of the human electroencephalogram.

  9. Detecting and quantifying cross-correlations by analogous multifractal height cross-correlation analysis

    NASA Astrophysics Data System (ADS)

    Wang, Fang; Yang, Zhaohui; Wang, Lin

    2016-02-01

    A new algorithm, analogous multifractal height cross-correlation analysis (AMF-HXA), is proposed in this paper. Our novel method takes into consideration of both the fluctuation information and the sign information in the corresponding cross-covariance function. Numerical tests on artificially simulated series and real world series are performed to demonstrate that our method can accurately detect long-range cross-correlations for two simultaneously recorded series. A new cross-correlation coefficient is also defined to quantify the levels of cross-correlation between two series.

  10. Noninvasive deep Raman detection with 2D correlation analysis

    NASA Astrophysics Data System (ADS)

    Kim, Hyung Min; Park, Hyo Sun; Cho, Youngho; Jin, Seung Min; Lee, Kang Taek; Jung, Young Mee; Suh, Yung Doug

    2014-07-01

    The detection of poisonous chemicals enclosed in daily necessaries is prerequisite essential for homeland security with the increasing threat of terrorism. For the detection of toxic chemicals, we combined a sensitive deep Raman spectroscopic method with 2D correlation analysis. We obtained the Raman spectra from concealed chemicals employing spatially offset Raman spectroscopy in which incident line-shaped light experiences multiple scatterings before being delivered to inner component and yielding deep Raman signal. Furthermore, we restored the pure Raman spectrum of each component using 2D correlation spectroscopic analysis with chemical inspection. Using this method, we could elucidate subsurface component under thick powder and packed contents in a bottle.

  11. Fluorescence correlation spectroscopy: Ultrasensitive detection in clear and turbid media

    NASA Astrophysics Data System (ADS)

    Tahari, Abdel Kader

    In this work, I describe the development of a simple, inexpensive, and powerful alternative technique to detect and analyze, without enrichment, extremely low concentrations of cells, bacteria, viruses, and protein aggregates in turbid fluids for clinical and biotechnological applications. The anticipated applications of this technique are many. They range from the determination of the somatic cell count in milk for the dairy industry, to the enumeration and characterization of microorganisms in environmental microbiology and the food industry, and to the fast and ultrasensitive detection of protein aggregates for the diagnosis of Alzheimer's and other neurodegenerative diseases in clinical medicine. A prototype instrument has been built and allowed the detection and quantification of particles down to a few per milliliter in short scanning times. It consists of a small microscope that has a horizontal geometry and a mechanical instrument that holds a cylindrical cuvette (1 cm in diameter) with two motors that provide a rotational and a slower vertical inversion motions. The illumination focus is centered about 200 mum from the wall of the cuvette inside the sample. The total volume that is explored is large (˜1ml/min for bright particles). The data is analyzed with a correlation filter program based on particle passage pattern recognition. I will also describe further work on improving the sensitivity of the technique, expanding it for multiple-species discrimination and enumeration, and testing the prototype device in actual clinical and biotechnological applications. The main clinical application of this project seeks to establish conditions and use this new technique to quantify and size-analyze oligomeric complexes of the Alzheimer's disease beta-peptide in cerebrospinal fluid and other body fluids as a molecular biomarker for persons at risk of Alzheimer's disease dementia. The technology could potentially be extended to the diagnosis and therapeutic

  12. Evolution of worldwide stock markets, correlation structure, and correlation-based graphs.

    PubMed

    Song, Dong-Ming; Tumminello, Michele; Zhou, Wei-Xing; Mantegna, Rosario N

    2011-08-01

    We investigate the daily correlation present among market indices of stock exchanges located all over the world in the time period January 1996 to July 2009. We discover that the correlation among market indices presents both a fast and a slow dynamics. The slow dynamics reflects the development and consolidation of globalization. The fast dynamics is associated with critical events that originate in a specific country or region of the world and rapidly affect the global system. We provide evidence that the short term time scale of correlation among market indices is less than 3 trading months (about 60 trading days). The average values of the nondiagonal elements of the correlation matrix, correlation-based graphs, and the spectral properties of the largest eigenvalues and eigenvectors of the correlation matrix are carrying information about the fast and slow dynamics of the correlation of market indices. We introduce a measure of mutual information based on link co-occurrence in networks in order to detect the fast dynamics of successive changes of correlation-based graphs in a quantitative way.

  13. Evolution of worldwide stock markets, correlation structure, and correlation-based graphs

    NASA Astrophysics Data System (ADS)

    Song, Dong-Ming; Tumminello, Michele; Zhou, Wei-Xing; Mantegna, Rosario N.

    2011-08-01

    We investigate the daily correlation present among market indices of stock exchanges located all over the world in the time period January 1996 to July 2009. We discover that the correlation among market indices presents both a fast and a slow dynamics. The slow dynamics reflects the development and consolidation of globalization. The fast dynamics is associated with critical events that originate in a specific country or region of the world and rapidly affect the global system. We provide evidence that the short term time scale of correlation among market indices is less than 3 trading months (about 60 trading days). The average values of the nondiagonal elements of the correlation matrix, correlation-based graphs, and the spectral properties of the largest eigenvalues and eigenvectors of the correlation matrix are carrying information about the fast and slow dynamics of the correlation of market indices. We introduce a measure of mutual information based on link co-occurrence in networks in order to detect the fast dynamics of successive changes of correlation-based graphs in a quantitative way.

  14. Evolution of worldwide stock markets, correlation structure, and correlation-based graphs.

    PubMed

    Song, Dong-Ming; Tumminello, Michele; Zhou, Wei-Xing; Mantegna, Rosario N

    2011-08-01

    We investigate the daily correlation present among market indices of stock exchanges located all over the world in the time period January 1996 to July 2009. We discover that the correlation among market indices presents both a fast and a slow dynamics. The slow dynamics reflects the development and consolidation of globalization. The fast dynamics is associated with critical events that originate in a specific country or region of the world and rapidly affect the global system. We provide evidence that the short term time scale of correlation among market indices is less than 3 trading months (about 60 trading days). The average values of the nondiagonal elements of the correlation matrix, correlation-based graphs, and the spectral properties of the largest eigenvalues and eigenvectors of the correlation matrix are carrying information about the fast and slow dynamics of the correlation of market indices. We introduce a measure of mutual information based on link co-occurrence in networks in order to detect the fast dynamics of successive changes of correlation-based graphs in a quantitative way. PMID:21929065

  15. Auditory cortical detection and discrimination correlates with communicative significance.

    PubMed

    Liu, Robert C; Schreiner, Christoph E

    2007-07-01

    Plasticity studies suggest that behavioral relevance can change the cortical processing of trained or conditioned sensory stimuli. However, whether this occurs in the context of natural communication, where stimulus significance is acquired through social interaction, has not been well investigated, perhaps because neural responses to species-specific vocalizations can be difficult to interpret within a systematic framework. The ultrasonic communication system between isolated mouse pups and adult females that either do or do not recognize the calls' significance provides an opportunity to explore this issue. We applied an information-based analysis to multi- and single unit data collected from anesthetized mothers and pup-naïve females to quantify how the communicative significance of pup calls affects their encoding in the auditory cortex. The timing and magnitude of information that cortical responses convey (at a 2-ms resolution) for pup call detection and discrimination was significantly improved in mothers compared to naïve females, most likely because of changes in call frequency encoding. This was not the case for a non-natural sound ensemble outside the mouse vocalization repertoire. The results demonstrate that a sensory cortical change in the timing code for communication sounds is correlated with the vocalizations' behavioral relevance, potentially enhancing functional processing by improving its signal to noise ratio. PMID:17564499

  16. Robust Statistical Detection of Power-Law Cross-Correlation

    PubMed Central

    Blythe, Duncan A. J.; Nikulin, Vadim V.; Müller, Klaus-Robert

    2016-01-01

    We show that widely used approaches in statistical physics incorrectly indicate the existence of power-law cross-correlations between financial stock market fluctuations measured over several years and the neuronal activity of the human brain lasting for only a few minutes. While such cross-correlations are nonsensical, no current methodology allows them to be reliably discarded, leaving researchers at greater risk when the spurious nature of cross-correlations is not clear from the unrelated origin of the time series and rather requires careful statistical estimation. Here we propose a theory and method (PLCC-test) which allows us to rigorously and robustly test for power-law cross-correlations, correctly detecting genuine and discarding spurious cross-correlations, thus establishing meaningful relationships between processes in complex physical systems. Our method reveals for the first time the presence of power-law cross-correlations between amplitudes of the alpha and beta frequency ranges of the human electroencephalogram. PMID:27250630

  17. Robust Statistical Detection of Power-Law Cross-Correlation.

    PubMed

    Blythe, Duncan A J; Nikulin, Vadim V; Müller, Klaus-Robert

    2016-01-01

    We show that widely used approaches in statistical physics incorrectly indicate the existence of power-law cross-correlations between financial stock market fluctuations measured over several years and the neuronal activity of the human brain lasting for only a few minutes. While such cross-correlations are nonsensical, no current methodology allows them to be reliably discarded, leaving researchers at greater risk when the spurious nature of cross-correlations is not clear from the unrelated origin of the time series and rather requires careful statistical estimation. Here we propose a theory and method (PLCC-test) which allows us to rigorously and robustly test for power-law cross-correlations, correctly detecting genuine and discarding spurious cross-correlations, thus establishing meaningful relationships between processes in complex physical systems. Our method reveals for the first time the presence of power-law cross-correlations between amplitudes of the alpha and beta frequency ranges of the human electroencephalogram. PMID:27250630

  18. Optical correlation recognition based on LCOS

    NASA Astrophysics Data System (ADS)

    Tang, Mingchuan; Wu, Jianhong

    2013-08-01

    Vander-Lugt correlator[1] plays an important role in optical pattern recognition due to the characteristics of accurate positioning and high signal-to-noise ratio. The ideal Vander-Lugt correlator should have the ability of outputting strong and sharp correlation peak in allusion to the true target, in the existing Spatial Light Modulators[2], Liquid Crystal On Silicon(LCOS) has been the most competitive candidate for the matched filter owing to the continuous phase modulation peculiarity. Allowing for the distortions of the target to be identified including rotations, scaling changes, perspective changes, which can severely impact the correlation recognition results, herein, we present a modified Vander-Lugt correlator based on the LCOS by means of applying an iterative algorithm to the design of the filter so that the correlator can invariant to the distortions while maintaining good performance. The results of numerical simulation demonstrate that the filter could get the similar recognition results for all the training images. And the experiment shows that the modified correlator achieves the 180° rotating tolerance significantly improving the recognition efficiency of the correlator.

  19. Correlation detection as a general mechanism for multisensory integration

    PubMed Central

    Parise, Cesare V.; Ernst, Marc O.

    2016-01-01

    The brain efficiently processes multisensory information by selectively combining related signals across the continuous stream of multisensory inputs. To do so, it needs to detect correlation, lag and synchrony across the senses; optimally integrate related information; and dynamically adapt to spatiotemporal conflicts across the senses. Here we show that all these aspects of multisensory perception can be jointly explained by postulating an elementary processing unit akin to the Hassenstein–Reichardt detector—a model originally developed for visual motion perception. This unit, termed the multisensory correlation detector (MCD), integrates related multisensory signals through a set of temporal filters followed by linear combination. Our model can tightly replicate human perception as measured in a series of empirical studies, both novel and previously published. MCDs provide a unified general theory of multisensory processing, which simultaneously explains a wide spectrum of phenomena with a simple, yet physiologically plausible model. PMID:27265526

  20. Correlation detection as a general mechanism for multisensory integration.

    PubMed

    Parise, Cesare V; Ernst, Marc O

    2016-01-01

    The brain efficiently processes multisensory information by selectively combining related signals across the continuous stream of multisensory inputs. To do so, it needs to detect correlation, lag and synchrony across the senses; optimally integrate related information; and dynamically adapt to spatiotemporal conflicts across the senses. Here we show that all these aspects of multisensory perception can be jointly explained by postulating an elementary processing unit akin to the Hassenstein-Reichardt detector-a model originally developed for visual motion perception. This unit, termed the multisensory correlation detector (MCD), integrates related multisensory signals through a set of temporal filters followed by linear combination. Our model can tightly replicate human perception as measured in a series of empirical studies, both novel and previously published. MCDs provide a unified general theory of multisensory processing, which simultaneously explains a wide spectrum of phenomena with a simple, yet physiologically plausible model. PMID:27265526

  1. The waveform correlation event detection system project, Phase I: Issues in prototype development and testing

    SciTech Connect

    Young, C.; Harris, M.; Beiriger, J.; Moore, S.; Trujillo, J.; Withers, M.; Aster, R.

    1996-08-01

    A study using long-period seismic data showed that seismic events can be detected and located based on correlations of processed waveform profiles with the profile expected for an event. In this technique both time and space are discretized and events are found by forming profiles and calculating correlations for all time-distance points. events are declared at points with large correlations. In the first phase of the Waveform Correlation Event Detection System (WCEDS) Project at Sandia Labs we have developed a prototype automatic event detection system based on Shearer`s work which shows promise for treaty monitoring applications. Many modifications have been made to meet the requirements of the monitoring environment. A new full matrix multiplication has been developed which can reduce the number of computations needed for the data correlation by as much as two orders of magnitude for large grids. New methodology has also been developed to deal with the problems caused by false correlations (sidelobes) generated during the correlation process. When an event has been detected, masking matrices are set up which will mask all correlation sidelobes due to the event, allowing other events with intermingled phases to be found. This process is repeated until a detection threshold is reached. The system was tested on one hour of Incorporated Research Institutions for Seismology (IRIS) broadband data and built all 4 of the events listed in the National Earthquake Information Center (NEIC) Preliminary Determination of Epicenters (PDE) which were observable by the IRIS network. A continuous execution scheme has been developed for the system but has not yet been implemented. Improvements to the efficiency of the code are in various stages of development. Many refinements would have to be made to the system before it could be used as part of an actual monitoring system, but at this stage we know of no clear barriers which would prevent an eventual implementation of the system.

  2. A robust correlation method to detect heterogeneous heart valve symptoms

    NASA Astrophysics Data System (ADS)

    Suboh, Mohd Zubir; Mansor, Muhammad Naufal; Junoh, Ahmad Kadri; Daud, Wan Suhana Wan; Muhamad, Wan Zuki Azman Wan; Idris, Azrini

    2015-05-01

    Heart valve disease affects a large number of patients. During the past decade, major advances have occurred in diagnostic techniques of heart valve disease. In this paper, we present an alternative method in classifying heart valve disease using correlation analysis and neural network classifier based on heart sound signal. The heart sound signals used in this study were taken from heart sound manipulator software. First, the signal was converted into frequency domain. Then, power spectrum of the sample is determined and cross-correlated with a reference sample (also in power spectrum form) to get different pattern of correlation plot. Seven different heart sounds of normal and other abnormal sounds from heart valve disease were classified into their classes. The result shows that 98.70% of the samples had been correctly classified by the system.

  3. Fission Multiplicity Detection with Temporal Gamma-Neutron Discrimination from Higher-Order Time Correlation Statistics

    SciTech Connect

    Oberer, R.B.

    2002-11-12

    The current practice of nondestructive assay (NDA) of fissile materials using neutrons is dominated by the {sup 3}He detector. This has been the case since the mid 1980s when Fission Multiplicity Detection (FMD) was replaced with thermal well counters and neutron multiplicity counting (NMC). The thermal well counters detect neutrons by neutron capture in the {sup 3}He detector subsequent to moderation. The process of detection requires from 30 to 60 {micro}s. As will be explained in Section 3.3 the rate of detecting correlated neutrons (signal) from the same fission are independent of this time but the rate of accidental correlations (noise) are proportional to this time. The well counters are at a distinct disadvantage when there is a large source of uncorrelated neutrons present from ({alpha}, n) reactions for example. Plastic scintillating detectors, as were used in FMD, require only about 20 ns to detect neutrons from fission. One thousandth as many accidental coincidences are therefore accumulated. The major problem with the use of fast-plastic scintillation detectors, however, is that both neutrons and gamma rays are detected. The pulses from the two are indistinguishable in these detectors. For this thesis, a new technique was developed to use higher-order time correlation statistics to distinguish combinations of neutron and gamma ray detections in fast-plastic scintillation detectors. A system of analysis to describe these correlations was developed based on simple physical principles. Other sources of correlations from non-fission events are identified and integrated into the analysis developed for fission events. A number of ratios and metric are identified to determine physical properties of the source from the correlations. It is possible to determine both the quantity being measured and detection efficiency from these ratios from a single measurement without a separate calibration. To account for detector dead-time, an alternative analytical technique

  4. Vehicle Localization by LIDAR Point Correlation Improved by Change Detection

    NASA Astrophysics Data System (ADS)

    Schlichting, A.; Brenner, C.

    2016-06-01

    LiDAR sensors are proven sensors for accurate vehicle localization. Instead of detecting and matching features in the LiDAR data, we want to use the entire information provided by the scanners. As dynamic objects, like cars, pedestrians or even construction sites could lead to wrong localization results, we use a change detection algorithm to detect these objects in the reference data. If an object occurs in a certain number of measurements at the same position, we mark it and every containing point as static. In the next step, we merge the data of the single measurement epochs to one reference dataset, whereby we only use static points. Further, we also use a classification algorithm to detect trees. For the online localization of the vehicle, we use simulated data of a vertical aligned automotive LiDAR sensor. As we only want to use static objects in this case as well, we use a random forest classifier to detect dynamic scan points online. Since the automotive data is derived from the LiDAR Mobile Mapping System, we are able to use the labelled objects from the reference data generation step to create the training data and further to detect dynamic objects online. The localization then can be done by a point to image correlation method using only static objects. We achieved a localization standard deviation of about 5 cm (position) and 0.06° (heading), and were able to successfully localize the vehicle in about 93 % of the cases along a trajectory of 13 km in Hannover, Germany.

  5. Infants' Detection of Correlated Features among Social Stimuli: A Precursor to Stereotyping?

    ERIC Educational Resources Information Center

    Levy, Gary D.; And Others

    This study examined the abilities of 10-month-old infants to detect correlations between objects and persons based on the characteristic of gender. A total of 32 infants were habituated to six stimuli in which a picture of a male or female face was paired with one of six objects such as a football or frying pan. Three objects were associated with…

  6. Upper Subcritical Calculations Based on Correlated Data

    SciTech Connect

    Sobes, Vladimir; Rearden, Bradley T; Mueller, Don; Marshall, William BJ J; Scaglione, John M; Dunn, Michael E

    2015-01-01

    The American National Standards Institute and American Nuclear Society standard for Validation of Neutron Transport Methods for Nuclear Criticality Safety Calculations defines the upper subcritical limit (USL) as “a limit on the calculated k-effective value established to ensure that conditions calculated to be subcritical will actually be subcritical.” Often, USL calculations are based on statistical techniques that infer information about a nuclear system of interest from a set of known/well-characterized similar systems. The work in this paper is part of an active area of research to investigate the way traditional trending analysis is used in the nuclear industry, and in particular, the research is assessing the impact of the underlying assumption that the experimental data being analyzed for USL calculations are statistically independent. In contrast, the multiple experiments typically used for USL calculations can be correlated because they are often performed at the same facilities using the same materials and measurement techniques. This paper addresses this issue by providing a set of statistical inference methods to calculate the bias and bias uncertainty based on the underlying assumption that the experimental data are correlated. Methods to quantify these correlations are the subject of a companion paper and will not be discussed here. The newly proposed USL methodology is based on the assumption that the integral experiments selected for use in the establishment of the USL are sufficiently applicable and that experimental correlations are known. Under the assumption of uncorrelated data, the new methods collapse directly to familiar USL equations currently used. We will demonstrate our proposed methods on real data and compare them to calculations of currently used methods such as USLSTATS and NUREG/CR-6698. Lastly, we will also demonstrate the effect experiment correlations can have on USL calculations.

  7. Vehicle-borne IED detection using the ULTOR correlation processor

    NASA Astrophysics Data System (ADS)

    Burcham, Joel D.; Vachon, Joyce E.

    2006-05-01

    Advanced Optical Systems, Inc. developed the ULTOR(r) system, a real-time correlation processor that looks for improvised explosive devices (IED) by examining imagery of vehicles. The system determines the level of threat an approaching vehicle may represent. The system works on incoming video collected at different wavelengths, including visible, infrared, and synthetic aperture radar. Sensors that attach to ULTOR can be located wherever necessary to improve the safety around a checkpoint. When a suspect vehicle is detected, ULTOR can track the vehicle, alert personnel, check for previous instances of the vehicle, and update other networked systems with the threat information. The ULTOR processing engine focuses on the spatial frequency information available in the image. It correlates the imagery with templates that specify the criteria defining a suspect vehicle. It can perform full field correlations at a rate of 180 Hz or better. Additionally, the spatial frequency information is applied to a trained neural network to identify suspect vehicles. We have performed various laboratory and field experiments to verify the performance of the ULTOR system in a counter IED environment. The experiments cover tracking specific targets in video clips to demonstrating real-time ULTOR system performance. The selected targets in the experiments include various automobiles in both visible and infrared video.

  8. Electrophysiological correlates of the efficient detection of emotional facial expressions.

    PubMed

    Sawada, Reiko; Sato, Wataru; Uono, Shota; Kochiyama, Takanori; Toichi, Motomi

    2014-04-29

    Behavioral studies have shown that emotional facial expressions are detected more rapidly and accurately than are neutral expressions. However, the neural mechanism underlying this efficient detection has remained unclear. To investigate this mechanism, we measured event-related potentials (ERPs) during a visual search task in which participants detected the normal emotional facial expressions of anger and happiness or their control stimuli, termed "anti-expressions," within crowds of neutral expressions. The anti-expressions, which were created using a morphing technique that produced changes equivalent to those in the normal emotional facial expressions compared with the neutral facial expressions, were most frequently recognized as emotionally neutral. Behaviorally, normal expressions were detected faster and more accurately and were rated as more emotionally arousing than were the anti-expressions. Regarding ERPs, the normal expressions elicited larger early posterior negativity (EPN) at 200-400ms compared with anti-expressions. Furthermore, larger EPN was related to faster and more accurate detection and higher emotional arousal. These data suggest that the efficient detection of emotional facial expressions is implemented via enhanced activation of the posterior visual cortices at 200-400ms based on their emotional significance. PMID:24594020

  9. Gait correlation analysis based human identification.

    PubMed

    Chen, Jinyan

    2014-01-01

    Human gait identification aims to identify people by a sequence of walking images. Comparing with fingerprint or iris based identification, the most important advantage of gait identification is that it can be done at a distance. In this paper, silhouette correlation analysis based human identification approach is proposed. By background subtracting algorithm, the moving silhouette figure can be extracted from the walking images sequence. Every pixel in the silhouette has three dimensions: horizontal axis (x), vertical axis (y), and temporal axis (t). By moving every pixel in the silhouette image along these three dimensions, we can get a new silhouette. The correlation result between the original silhouette and the new one can be used as the raw feature of human gait. Discrete Fourier transform is used to extract features from this correlation result. Then, these features are normalized to minimize the affection of noise. Primary component analysis method is used to reduce the features' dimensions. Experiment based on CASIA database shows that this method has an encouraging recognition performance. PMID:24592144

  10. Ladar-based IED detection

    NASA Astrophysics Data System (ADS)

    Engström, Philip; Larsson, Hâkan; Letalick, Dietmar

    2014-05-01

    An improvised explosive device (IED) is a bomb constructed and deployed in a non-standard manor. Improvised means that the bomb maker took whatever he could get his hands on, making it very hard to predict and detect. Nevertheless, the matters in which the IED's are deployed and used, for example as roadside bombs, follow certain patterns. One possible approach for early warning is to record the surroundings when it is safe and use this as reference data for change detection. In this paper a LADAR-based system for IED detection is presented. The idea is to measure the area in front of the vehicle when driving and comparing this to the previously recorded reference data. By detecting new, missing or changed objects the system can make the driver aware of probable threats.

  11. Correlation measure to detect time series distances, whence economy globalization

    NASA Astrophysics Data System (ADS)

    Miśkiewicz, Janusz; Ausloos, Marcel

    2008-11-01

    An instantaneous time series distance is defined through the equal time correlation coefficient. The idea is applied to the Gross Domestic Product (GDP) yearly increments of 21 rich countries between 1950 and 2005 in order to test the process of economic globalisation. Some data discussion is first presented to decide what (EKS, GK, or derived) GDP series should be studied. Distances are then calculated from the correlation coefficient values between pairs of series. The role of time averaging of the distances over finite size windows is discussed. Three network structures are next constructed based on the hierarchy of distances. It is shown that the mean distance between the most developed countries on several networks actually decreases in time, -which we consider as a proof of globalization. An empirical law is found for the evolution after 1990, similar to that found in flux creep. The optimal observation time window size is found ≃15 years.

  12. Correlative Analysis of GRBs Detected by Swift and Suzaku- WAM

    NASA Technical Reports Server (NTRS)

    Krimm, H.A.; Sakamoto, T.; Yamaoka, K.; Sugita, S.; Ohno, M.; Sato, G.; Hara, R.; Ohmori, N.; Tanaka, H.; Yamauchi, M.; Onda, K.; Tashiro, M.

    2009-01-01

    It is now well known that a complete understanding of the energetics of the prompt phase of gamma-ray bursts (GRBs) requires full knowledge of the spectrum, extending at least as high as the peak energy (Epeak) of the vF(v) spectrum. Since most gamma-ray bursts (GRBs) have Epeak above the energy range (15-150 keV) of the Burst Alert Telescope (BAT) on Swift, a full understanding of the prompt emission from Swift GRBs requires spectral fits over as broad an energy range as possible. This can be completed for bursts which are simultaneously detected by Swift BAT and the Suzaku Wide-band All-Sky Monitor (WAM), which covers the energy range from 50-5000 keV. Between the launch of Suzaku in July 2005 and the end of 2008, there were 44 gamma-ray bursts (GRBs) which triggered both Swift and WAM and an additional 41 bursts which triggered Swift and were detected by WAM, but did not trigger. A joint BAT-WAM team has cross-calibrated the two instruments using GRBs, and we are now able to perform joint fits on these bursts to determine spectral parameters including Epeak. The results of broad spectral fits allows us to understand the distribution of Epeak for Swift bursts and to calibrate Epeak estimators when Epeak is within the BAT energy range. For those bursts with spectroscopic redshifts, we can calculate the isotropic energy and study various correlations between Epeak and other global burst parameters. Here we present the results of joint Swift/BAT-Suzaku/WAM spectral fits for 77 of the bursts jointly detected by the two instruments. We show that the distribution of spectral fit parameters is consistent with distributions from earlier missions and confirm that Swift bursts are consistent with earlier reported relationships between Epeak and isotropic energy. We show through time-resolved spectroscopy that individual burst pulses are also consistent with this relationship.

  13. Neural correlates of stimulus spatial frequency-dependent contrast detection

    PubMed Central

    Meng, Jianjun; Liu, Ruilong; Wang, Ke; Hua, Tianmiao; Lu, Zhong-Lin; Xi, Minmin

    2016-01-01

    Psychophysical studies on human and non-human vertebrate species have shown that visual contrast sensitivity function (CSF) peaks at a certain stimulus spatial frequency and declines in both lower and higher spatial frequencies. The underlying neural substrate and mechanisms remain in debate. Here, we investigated the role of primary visual cortex (V1: area 17) in spatial frequency-dependent contrast detection in cats. Perceptual CSFs of three cats were measured using a two-alternative forced choice task. The responses of V1 neurons to their optimal visual stimuli in a range of luminance contrast levels (from 0 to 1.0) were recorded subsequently using in vivo extracellular single-unit recording techniques. The contrast sensitivity of each neuron was determined. The neuronal CSF for each cat was constructed from the mean contrast sensitivity of neurons with different preferred stimulus spatial frequencies. Results (1) The perceptual and neuronal CSFs of each of the three cats exhibited a similar shape with peak amplitude near 0.4 c/deg. (2) The neuronal CSF of each cat was highly correlated with its perceptual CSF. (3) V1 neurons with different preferred stimulus spatial frequencies had different contrast gains. Conclusion (1) Contrast detection of visual stimuli with different spatial frequencies may likely involve population coding of V1 neurons with different preferred stimulus spatial frequencies. (2) Difference in contrast-gain may underlie the observed contrast sensitivity variation of V1 neurons with different preferred stimulus spatial frequencies, possibly from either evolution or postnatal visual experiences. PMID:23314692

  14. Detecting Nanodomains in Living Cell Membrane by Fluorescence Correlation Spectroscopy

    NASA Astrophysics Data System (ADS)

    He, Hai-Tao; Marguet, Didier

    2011-05-01

    Cell membranes actively participate in numerous cellular functions. Inasmuch as bioactivities of cell membranes are known to depend crucially on their lateral organization, much effort has been focused on deciphering this organization on different length scales. Within this context, the concept of lipid rafts has been intensively discussed over recent years. In line with its ability to measure diffusion parameters with great precision, fluorescence correlation spectroscopy (FCS) measurements have been made in association with innovative experimental strategies to monitor modes of molecular lateral diffusion within the plasma membrane of living cells. These investigations have allowed significant progress in the characterization of the cell membrane lateral organization at the suboptical level and have provided compelling evidence for the in vivo existence of raft nanodomains. We review these FCS-based studies and the characteristic structural features of raft nanodomains. We also discuss the findings in regards to the current view of lipid rafts as a general membrane-organizing principle.

  15. Ionizing particle detection based on phononic crystals

    SciTech Connect

    Aly, Arafa H. E-mail: arafa.hussien@science.bsu.edu.eg; Mehaney, Ahmed; Eissa, Mostafa F.

    2015-08-14

    Most conventional radiation detectors are based on electronic or photon collections. In this work, we introduce a new and novel type of ionizing particle detector based on phonon collection. Helium ion radiation treats tumors with better precision. There are nine known isotopes of helium, but only helium-3 and helium-4 are stable. Helium-4 is formed in fusion reactor technology and in enormous quantities during Big Bang nucleo-synthesis. In this study, we introduce a technique for helium-4 ion detection (sensing) based on the innovative properties of the new composite materials known as phononic crystals (PnCs). PnCs can provide an easy and cheap technique for ion detection compared with conventional methods. PnC structures commonly consist of a periodic array of two or more materials with different elastic properties. The two materials are polymethyl-methacrylate and polyethylene polymers. The calculations showed that the energies lost to target phonons are maximized at 1 keV helium-4 ion energy. There is a correlation between the total phonon energies and the transmittance of PnC structures. The maximum transmission for phonons due to the passage of helium-4 ions was found in the case of making polyethylene as a first layer in the PnC structure. Therefore, the concept of ion detection based on PnC structure is achievable.

  16. Ionizing particle detection based on phononic crystals

    NASA Astrophysics Data System (ADS)

    Aly, Arafa H.; Mehaney, Ahmed; Eissa, Mostafa F.

    2015-08-01

    Most conventional radiation detectors are based on electronic or photon collections. In this work, we introduce a new and novel type of ionizing particle detector based on phonon collection. Helium ion radiation treats tumors with better precision. There are nine known isotopes of helium, but only helium-3 and helium-4 are stable. Helium-4 is formed in fusion reactor technology and in enormous quantities during Big Bang nucleo-synthesis. In this study, we introduce a technique for helium-4 ion detection (sensing) based on the innovative properties of the new composite materials known as phononic crystals (PnCs). PnCs can provide an easy and cheap technique for ion detection compared with conventional methods. PnC structures commonly consist of a periodic array of two or more materials with different elastic properties. The two materials are polymethyl-methacrylate and polyethylene polymers. The calculations showed that the energies lost to target phonons are maximized at 1 keV helium-4 ion energy. There is a correlation between the total phonon energies and the transmittance of PnC structures. The maximum transmission for phonons due to the passage of helium-4 ions was found in the case of making polyethylene as a first layer in the PnC structure. Therefore, the concept of ion detection based on PnC structure is achievable.

  17. Bacteriophage-Based Pathogen Detection

    NASA Astrophysics Data System (ADS)

    Ripp, Steven

    Considered the most abundant organism on Earth, at a population approaching 1031, bacteriophage, or phage for short, mediate interactions with myriad bacterial hosts that has for decades been exploited in phage typing schemes for signature identification of clinical, food-borne, and water-borne pathogens. With over 5,000 phage being morphologically characterized and grouped as to susceptible host, there exists an enormous cache of bacterial-specific sensors that has more recently been incorporated into novel bio-recognition assays with heightened sensitivity, specificity, and speed. These assays take many forms, ranging from straightforward visualization of labeled phage as they attach to their specific bacterial hosts to reporter phage that genetically deposit trackable signals within their bacterial hosts to the detection of progeny phage or other uniquely identifiable elements released from infected host cells. A comprehensive review of these and other phage-based detection assays, as directed towards the detection and monitoring of bacterial pathogens, will be provided in this chapter.

  18. Detecting and quantifying temporal correlations in stochastic resonance via information theory measures

    NASA Astrophysics Data System (ADS)

    Rosso, O. A.; Masoller, C.

    2009-05-01

    We show that Information Theory quantifiers are suitable tools for detecting and for quantifying noise-induced temporal correlations in stochastic resonance phenomena. We use the Bandt & Pompe (BP) method [Phys. Rev. Lett. 88, 174102 (2002)] to define a probability distribution, P, that fully characterizes temporal correlations. The BP method is based on a comparison of neighboring values, and here is applied to the temporal sequence of residence-time intervals generated by the paradigmatic model of a Brownian particle in a sinusoidally modulated bistable potential. The probability distribution P generated via the BP method has associated a normalized Shannon entropy, H[P], and a statistical complexity measure, C[P], which is defined as proposed by Rosso et al. [Phys. Rev. Lett. 99, 154102 (2007)]. The statistical complexity quantifies not only randomness but also the presence of correlational structures, the two extreme circumstances of maximum knowledge (“perfect order") and maximum ignorance (“complete randomness") being regarded an “trivial", and in consequence, having complexity C = 0. We show that both, H and C, display resonant features as a function of the noise intensity, i.e., for an optimal level of noise the entropy displays a minimum and the complexity, a maximum. This resonant behavior indicates noise-enhanced temporal correlations in the sequence of residence-time intervals. The methodology proposed here has great potential for the precise detection of subtle signatures of noise-induced temporal correlations in real-world complex signals.

  19. Trends in Correlation-Based Pattern Recognition and Tracking in Forward-Looking Infrared Imagery

    PubMed Central

    Alam, Mohammad S.; Bhuiyan, Sharif M. A.

    2014-01-01

    In this paper, we review the recent trends and advancements on correlation-based pattern recognition and tracking in forward-looking infrared (FLIR) imagery. In particular, we discuss matched filter-based correlation techniques for target detection and tracking which are widely used for various real time applications. We analyze and present test results involving recently reported matched filters such as the maximum average correlation height (MACH) filter and its variants, and distance classifier correlation filter (DCCF) and its variants. Test results are presented for both single/multiple target detection and tracking using various real-life FLIR image sequences. PMID:25061840

  20. Detection of correlated fragments in a sequence of images by superimposed Fourier holograms

    NASA Astrophysics Data System (ADS)

    Pavlov, A. V.

    2016-08-01

    The problem of detecting correlated fragments in a sequence of images recorded by the superimposing holograms within the Fourier holography scheme with angular multiplication of a spatially modulated reference beam is considered. The approach to the solution of this problem is based on the properties of the variance of the image sum. It is shown that this problem can be solved by providing a constant distance between the signal and reference images when recording superimposed holograms and a partial mutual correlatedness of reference images. The detection efficiency is analysed from the point of view of estimated image data capacity, the degree of mutual correlation of reference images, and the hologram recording conditions. The results of a numerical experiment under the most complicated conditions (representation of images by realisations of homogeneous random fields) confirm the theoretical conclusions.

  1. Detection of Failure of Machine by Using the Higher Order Correlation Information between Sound and Vibration

    NASA Astrophysics Data System (ADS)

    Ikuta, Akira; Orimoto, Hisako; Ogawa, Hitoshi

    In this study, a stochastic detection method of failure of machines based on the changing information of not only a linear correlation but also the higher order nonlinear correlation is proposed in a form suitable for on-line signal processing in time domain by using a personal computer, especially in order to find minutely the mutual relationship between sound and vibration emitted from rotational machines. More specifically, a conditional probability hierarchically reflecting various types of correlation information is theoretically derived by introducing an expression on the multi-dimensional probability distribution in orthogonal expansion series form. The effectiveness of the proposed theory is experimentally confirmed by applying it to the observed data emitted from a rotational machine driven by an electric motor.

  2. Detrended fluctuation analysis made flexible to detect range of cross-correlated fluctuations

    NASA Astrophysics Data System (ADS)

    Kwapień, Jarosław; Oświecimka, Paweł; DroŻdŻ, Stanisław

    2015-11-01

    The detrended cross-correlation coefficient ρDCCA has recently been proposed to quantify the strength of cross-correlations on different temporal scales in bivariate, nonstationary time series. It is based on the detrended cross-correlation and detrended fluctuation analyses (DCCA and DFA, respectively) and can be viewed as an analog of the Pearson coefficient in the case of the fluctuation analysis. The coefficient ρDCCA works well in many practical situations but by construction its applicability is limited to detection of whether two signals are generally cross-correlated, without the possibility to obtain information on the amplitude of fluctuations that are responsible for those cross-correlations. In order to introduce some related flexibility, here we propose an extension of ρDCCA that exploits the multifractal versions of DFA and DCCA: multifractal detrended fluctuation analysis and multifractal detrended cross-correlation analysis, respectively. The resulting new coefficient ρq not only is able to quantify the strength of correlations but also allows one to identify the range of detrended fluctuation amplitudes that are correlated in two signals under study. We show how the coefficient ρq works in practical situations by applying it to stochastic time series representing processes with long memory: autoregressive and multiplicative ones. Such processes are often used to model signals recorded from complex systems and complex physical phenomena like turbulence, so we are convinced that this new measure can successfully be applied in time-series analysis. In particular, we present an example of such application to highly complex empirical data from financial markets. The present formulation can straightforwardly be extended to multivariate data in terms of the q -dependent counterpart of the correlation matrices and then to the network representation.

  3. A vehicle threat detection system using correlation analysis and synthesized x-ray images

    NASA Astrophysics Data System (ADS)

    Zheng, Yufeng; Elmaghraby, Adel

    2013-06-01

    The goal of the proposed research is to automate the vehicle threat detection with X-ray images when a vehicle crosses the country border or the gateway of a secured facility (military base). The proposed detection system requires two inputs: probe images (from X-ray machine) and gallery images (from database). For each vehicle, the gallery images include the X-ray images of fully-loaded (with typical cargo) and unloaded (empty) vehicle. The proposed system produces two types of outputs for threat detection: the detected anomalies and the synthesized images (e.g., grayscale fusion, color fusion, and differential images). The anomalies are automatically detected with the block-wise correlation analysis between two temporally aligned images (probe versus gallery). The locations of detected anomalies can be marked with small rectangles on the probe X-ray images. The several side-view images can be combined into one fused image in gray scale and in colors (color fusion) that provides more comprehensive information to the operator. The fused images are suitable for human analysis and decision. We analyzed a set of vehicle X-ray images, which consists of 4 images generated from AS and E OmniView Gantry™. The preliminary results of detected anomalies and synthesized images are very promising; meanwhile the processing speed is very fast.

  4. Hierarchical detection of red lesions in retinal images by multiscale correlation filtering

    NASA Astrophysics Data System (ADS)

    Zhang, Bob; Wu, Xiangqian; You, Jane; Li, Qin; Karray, Fakhri

    2009-02-01

    This paper presents an approach to the computer aided diagnosis (CAD) of diabetic retinopathy (DR) -- a common and severe complication of long-term diabetes which damages the retina and cause blindness. Since red lesions are regarded as the first signs of DR, there has been extensive research on effective detection and localization of these abnormalities in retinal images. In contrast to existing algorithms, a new approach based on Multiscale Correlation Filtering (MSCF) and dynamic thresholding is developed. This consists of two levels, Red Lesion Candidate Detection (coarse level) and True Red Lesion Detection (fine level). The approach was evaluated using data from Retinopathy On-line Challenge (ROC) competition website and we conclude our method to be effective and efficient.

  5. DOM Based XSS Detecting Method Based on Phantomjs

    NASA Astrophysics Data System (ADS)

    Dong, Ri-Zhan; Ling, Jie; Liu, Yi

    Because malicious code does not appear in html source code, DOM based XSS cannot be detected by traditional methods. By analyzing the causes of DOM based XSS, this paper proposes a detection method of DOM based XSS based on phantomjs. This paper uses function hijacking to detect dangerous operation and achieves a prototype system. Comparing with existing tools shows that the system improves the detection rate and the method is effective to detect DOM based XSS.

  6. Improved maximum average correlation height filter with adaptive log base selection for object recognition

    NASA Astrophysics Data System (ADS)

    Tehsin, Sara; Rehman, Saad; Awan, Ahmad B.; Chaudry, Qaiser; Abbas, Muhammad; Young, Rupert; Asif, Afia

    2016-04-01

    Sensitivity to the variations in the reference image is a major concern when recognizing target objects. A combinational framework of correlation filters and logarithmic transformation has been previously reported to resolve this issue alongside catering for scale and rotation changes of the object in the presence of distortion and noise. In this paper, we have extended the work to include the influence of different logarithmic bases on the resultant correlation plane. The meaningful changes in correlation parameters along with contraction/expansion in the correlation plane peak have been identified under different scenarios. Based on our research, we propose some specific log bases to be used in logarithmically transformed correlation filters for achieving suitable tolerance to different variations. The study is based upon testing a range of logarithmic bases for different situations and finding an optimal logarithmic base for each particular set of distortions. Our results show improved correlation and target detection accuracies.

  7. A new technique for the detection of large scale landslides in glacio-lacustrine deposits using image correlation based upon aerial imagery: A case study from the French Alps

    NASA Astrophysics Data System (ADS)

    Fernandez, Paz; Whitworth, Malcolm

    2016-10-01

    Landslide monitoring has benefited from recent advances in the use of image correlation of high resolution optical imagery. However, this approach has typically involved satellite imagery that may not be available for all landslides depending on their time of movement and location. This study has investigated the application of image correlation techniques applied to a sequence of aerial imagery to an active landslide in the French Alps. We apply an indirect landslide monitoring technique (COSI-Corr) based upon the cross-correlation between aerial photographs, to obtain horizontal displacement rates. Results for the 2001-2003 time interval are presented, providing a spatial model of landslide activity and motion across the landslide, which is consistent with previous studies. The study has identified areas of new landslide activity in addition to known areas and through image decorrelation has identified and mapped two new lateral landslides within the main landslide complex. This new approach for landslide monitoring is likely to be of wide applicability to other areas characterised by complex ground displacements.

  8. DSN Beowulf Cluster-Based VLBI Correlator

    NASA Technical Reports Server (NTRS)

    Rogstad, Stephen P.; Jongeling, Andre P.; Finley, Susan G.; White, Leslie A.; Lanyi, Gabor E.; Clark, John E.; Goodhart, Charles E.

    2009-01-01

    The NASA Deep Space Network (DSN) requires a broadband VLBI (very long baseline interferometry) correlator to process data routinely taken as part of the VLBI source Catalogue Maintenance and Enhancement task (CAT M&E) and the Time and Earth Motion Precision Observations task (TEMPO). The data provided by these measurements are a crucial ingredient in the formation of precision deep-space navigation models. In addition, a VLBI correlator is needed to provide support for other VLBI related activities for both internal and external customers. The JPL VLBI Correlator (JVC) was designed, developed, and delivered to the DSN as a successor to the legacy Block II Correlator. The JVC is a full-capability VLBI correlator that uses software processes running on multiple computers to cross-correlate two-antenna broadband noise data. Components of this new system (see Figure 1) consist of Linux PCs integrated into a Beowulf Cluster, an existing Mark5 data storage system, a RAID array, an existing software correlator package (SoftC) originally developed for Delta DOR Navigation processing, and various custom- developed software processes and scripts. Parallel processing on the JVC is achieved by assigning slave nodes of the Beowulf cluster to process separate scans in parallel until all scans have been processed. Due to the single stream sequential playback of the Mark5 data, some ramp-up time is required before all nodes can have access to required scan data. Core functions of each processing step are accomplished using optimized C programs. The coordination and execution of these programs across the cluster is accomplished using Pearl scripts, PostgreSQL commands, and a handful of miscellaneous system utilities. Mark5 data modules are loaded on Mark5 Data systems playback units, one per station. Data processing is started when the operator scans the Mark5 systems and runs a script that reads various configuration files and then creates an experiment-dependent status database

  9. Peak detection in fiber Bragg grating using a fast phase correlation algorithm

    NASA Astrophysics Data System (ADS)

    Lamberti, A.; Vanlanduit, S.; De Pauw, B.; Berghmans, F.

    2014-05-01

    Fiber Bragg grating sensing principle is based on the exact tracking of the peak wavelength location. Several peak detection techniques have already been proposed in literature. Among these, conventional peak detection (CPD) methods such as the maximum detection algorithm (MDA), do not achieve very high precision and accuracy, especially when the Signal to Noise Ratio (SNR) and the wavelength resolution are poor. On the other hand, recently proposed algorithms, like the cross-correlation demodulation algorithm (CCA), are more precise and accurate but require higher computational effort. To overcome these limitations, we developed a novel fast phase correlation algorithm (FPC) which performs as well as the CCA, being at the same time considerably faster. This paper presents the FPC technique and analyzes its performances for different SNR and wavelength resolutions. Using simulations and experiments, we compared the FPC with the MDA and CCA algorithms. The FPC detection capabilities were as precise and accurate as those of the CCA and considerably better than those of the CPD. The FPC computational time was up to 50 times lower than CCA, making the FPC a valid candidate for future implementation in real-time systems.

  10. Multi-lane detection based on multiple vanishing points detection

    NASA Astrophysics Data System (ADS)

    Li, Chuanxiang; Nie, Yiming; Dai, Bin; Wu, Tao

    2015-03-01

    Lane detection plays a significant role in Advanced Driver Assistance Systems (ADAS) for intelligent vehicles. In this paper we present a multi-lane detection method based on multiple vanishing points detection. A new multi-lane model assumes that a single lane, which has two approximately parallel boundaries, may not parallel to others on road plane. Non-parallel lanes associate with different vanishing points. A biological plausibility model is used to detect multiple vanishing points and fit lane model. Experimental results show that the proposed method can detect both parallel lanes and non-parallel lanes.

  11. Lung lesions: correlation between viewing time and detection.

    PubMed

    Oestmann, J W; Greene, R; Kushner, D C; Bourgouin, P M; Linetsky, L; Llewellyn, H J

    1988-02-01

    The influence of viewing time on the detectability of subtle and obvious lung cancers was studied. Frontal chest radiographs of 40 patients with subtle cancers, 40 patients with obvious cancers, and 40 healthy control subjects were shown to four observers for four different viewing times (0.25 second, 1 second, 4 seconds, and unlimited time). Receiver operating characteristic analysis was used to compare the detectability of lesions. Performance was degraded as viewing time decreased. The true-positive fractions for subtle and obvious cancers were 30% and 70% at 0.25 second and 74% and 98% at unlimited viewing time, respectively, for a given false-positive fraction of 20%. Thus, even with unlimited viewing time, the false-negative fraction for subtle cancers was 26%. The difference in detectability between subtle and obvious lung cancers was exaggerated at 1.0 second compared with 4 seconds and unlimited viewing time. The following conclusions were reached: (a) a substantial proportion of subtle lung lesions are missed, even with unlimited viewing time; (b) a large proportion of obvious lung cancers are detected with flash viewing; (c) the detectability of lesions decreases considerably as viewing time becomes less than 4 seconds; and (d) differences in detectability are exaggerated by short viewing times. PMID:3336720

  12. Auditory evoked-potential correlates of decrement detection.

    PubMed

    Boettcher, Flint A; Emery, Mark

    2006-02-01

    Decrement detection is a commonly used psychophysical technique in which a subject is required to detect partially filled gaps in an ongoing sound. The paradigm provides information regarding both temporal resolution and intensity discrimination. The purpose of this project was to determine if an evoked-potential paradigm using decrements in an ongoing noise approximates psychophysical data. If so, the evoked-response paradigm would be useful in estimating decrement detection in laboratory animals, where training time for a psychophysical model of decrement detection might prove prohibitive. In this study, Mongolian gerbils aged 3-10 months were used as subjects. The stimulus was a broadband noise (low-pass filtered at 5 or 30 kHz, overall level of 70 dB SPL), interrupted for durations of 2-32 ms. Within each off period, a second, identically filtered noise at levels of 0-70 dB SPL was presented. In a manner qualitatively similar to previous human and animal psychophysical studies, the ABR threshold decreased as the duration of the decrement was increased. Latency and amplitudes changed as a function of decrement duration when the decrement depth was held constant, but minimal change as a function of decrement depth occurred when the decrement duration was held constant. The results suggest that ABR paradigm for decrement detection is a qualitative alternative to psychophysical techniques, but that amplitude and latency data may not provide more information on temporal and intensity coding than ABR measures of gap detection. PMID:16403610

  13. Pickless event detection and location: The waveform correlation event detection system (WCEDS) revisited

    DOE PAGES

    Arrowsmith, Stephen John; Young, Christopher J.; Ballard, Sanford; Slinkard, Megan Elizabeth

    2016-01-01

    The standard paradigm for seismic event monitoring breaks the event detection problem down into a series of processing stages that can be categorized at the highest level into station-level processing and network-level processing algorithms (e.g., Le Bras and Wuster (2002)). At the station-level, waveforms are typically processed to detect signals and identify phases, which may subsequently be updated based on network processing. At the network-level, phase picks are associated to form events, which are subsequently located. Furthermore, waveforms are typically directly exploited only at the station-level, while network-level operations rely on earth models to associate and locate the events thatmore » generated the phase picks.« less

  14. Pickless event detection and location: The waveform correlation event detection system (WCEDS) revisited

    SciTech Connect

    Arrowsmith, Stephen John; Young, Christopher J.; Ballard, Sanford; Slinkard, Megan Elizabeth

    2016-01-01

    The standard paradigm for seismic event monitoring breaks the event detection problem down into a series of processing stages that can be categorized at the highest level into station-level processing and network-level processing algorithms (e.g., Le Bras and Wuster (2002)). At the station-level, waveforms are typically processed to detect signals and identify phases, which may subsequently be updated based on network processing. At the network-level, phase picks are associated to form events, which are subsequently located. Furthermore, waveforms are typically directly exploited only at the station-level, while network-level operations rely on earth models to associate and locate the events that generated the phase picks.

  15. A novel method to detect proteins evolving at correlated rates: identifying new functional relationships between coevolving proteins.

    PubMed

    Clark, Nathaniel L; Aquadro, Charles F

    2010-05-01

    Interacting proteins evolve at correlated rates, possibly as the result of evolutionary pressures shared by functional groups and/or coevolution between interacting proteins. This evolutionary signature can be exploited to learn more about protein networks and to infer functional relationships between proteins on a genome-wide scale. Multiple methods have been introduced that detect correlated evolution using amino acid distances. One assumption made by these methods is that the neutral rate of nucleotide substitution is uniform over time; however, this is unlikely and such rate heterogeneity would adversely affect amino acid distance methods. We explored alternative methods that detect correlated rates using protein-coding nucleotide sequences in order to better estimate the rate of nonsynonymous substitution at each branch (d(N)) normalized by the underlying synonymous substitution rate (d(S)). Our novel likelihood method, which was robust to realistic simulation parameters, was tested on Drosophila nuclear pore proteins, which form a complex with well-documented physical interactions. The method revealed significantly correlated evolution between nuclear pore proteins, where members of a stable subcomplex showed stronger correlations compared with those proteins that interact transiently. Furthermore, our likelihood approach was better able to detect correlated evolution among closely related species than previous methods. Hence, these sequence-based methods are a complementary approach for detecting correlated evolution and could be applied genome-wide to provide candidate protein-protein interactions and functional group assignments using just coding sequences.

  16. Color balancing based upon gamut and temporal correlations

    NASA Astrophysics Data System (ADS)

    Kim, Sung-Su; Lee, Ho-Young; Kang, Byoung-Ho; Lee, Seong-Deok; Park, Du-Sik; Kim, Chang-Yeong

    2007-02-01

    Image acquisition devices inherently do not have color constancy mechanism like human visual system. Machine color constancy problem can be circumvented using a white balancing technique based upon accurate illumination estimation. Unfortunately, previous study can give satisfactory results for both accuracy and stability under various conditions. To overcome these problems, we suggest a new method: spatial and temporal illumination estimation. This method, an evolution of the Retinex and Color by Correlation method, predicts on initial illuminant point, and estimates scene-illumination between the point and sub-gamuts derived by from luminance levels. The method proposed can raise estimation probability by not only detecting motion of scene reflectance but also by finding valid scenes using different information from sequential scenes. This proposed method outperforms recently developed algorithms.

  17. Molecular detection of rabies encephalitis and correlation with cytokine expression.

    PubMed

    Nuovo, Gerard J; Defaria, Dulcelena L; Chanona-Vilchi, Juan G; Zhang, Yilan

    2005-01-01

    The purposes of this study were to elucidate the role of cytokine upregulation in the pathogenesis of rabies encephalitis and to compare the detection of Negri bodies with that of rabies protein by immunohistochemistry and rabies RNA by reverse transcriptase (RT) in situ PCR for its diagnosis. Negri bodies were evident in 4/7 of the documented rabies cases; viral protein and viral RNA were detected in each case. The average number of rabies-infected cells, determined by counting 150 neurons in serial sections in areas where viral protein was evident, with the three different detection methods was: Negri bodies (<1/150), immunohistochemistry (4/150), and RT in situ PCR (49/150). No rabies protein or RNA was detected in four control brain tissues that were read with the rabies cases in a blinded fashion. The ratio of cells expressing tumor necrosis factor alpha (TNFalpha) or inducible nitric oxide synthetase (iNOS) to 1 SSI-1/SOCS-1 (suppressors of cytokine signaling) expression, which is a novel class of negative feedback regulators of cytokine receptor signaling, was markedly increased only in the areas where many viral infected cells were present. Colabeling experiments showed that most of the cells expressing iNOS or TNFalpha were not virally infected, but rather adjacent to rabies-infected neurons. We conclude that RT in situ PCR for rabies virus is the most accurate test for the determination of viral load in rabies encephalitis. Further, the disease is characterized by massive viral infection of neurons in a markedly focal distribution in conjunction with a concomitant upregulation of cytokine expression in adjacent, noninfected cells that may be due, in part, to SOCS downregulation.

  18. Cellular telephone-based radiation detection instrument

    DOEpatents

    Craig, William W.; Labov, Simon E.

    2011-06-14

    A network of radiation detection instruments, each having a small solid state radiation sensor module integrated into a cellular phone for providing radiation detection data and analysis directly to a user. The sensor module includes a solid-state crystal bonded to an ASIC readout providing a low cost, low power, light weight compact instrument to detect and measure radiation energies in the local ambient radiation field. In particular, the photon energy, time of event, and location of the detection instrument at the time of detection is recorded for real time transmission to a central data collection/analysis system. The collected data from the entire network of radiation detection instruments are combined by intelligent correlation/analysis algorithms which map the background radiation and detect, identify and track radiation anomalies in the region.

  19. Detection and correction of spectral and spatial misregistrations for hyperspectral data using phase correlation method.

    PubMed

    Yokoya, Naoto; Miyamura, Norihide; Iwasaki, Akira

    2010-08-20

    Hyperspectral imaging sensors suffer from spectral and spatial misregistrations due to optical-system aberrations and misalignments. These artifacts distort spectral signatures that are specific to target objects and thus reduce classification accuracy. The main objective of this work is to detect and correct spectral and spatial misregistrations of hyperspectral images. The Hyperion visible near-infrared subsystem is used as an example. An image registration method based on phase correlation demonstrates the accurate detection of the spectral and spatial misregistrations. Cubic spline interpolation using estimated properties makes it possible to modify the spectral signatures. The accuracy of the proposed postlaunch estimation of the Hyperion characteristics is comparable to that of the prelaunch measurements, which enables the accurate onboard calibration of hyperspectral sensors. PMID:20733628

  20. Detection and correction of spectral and spatial misregistrations for hyperspectral data using phase correlation method.

    PubMed

    Yokoya, Naoto; Miyamura, Norihide; Iwasaki, Akira

    2010-08-20

    Hyperspectral imaging sensors suffer from spectral and spatial misregistrations due to optical-system aberrations and misalignments. These artifacts distort spectral signatures that are specific to target objects and thus reduce classification accuracy. The main objective of this work is to detect and correct spectral and spatial misregistrations of hyperspectral images. The Hyperion visible near-infrared subsystem is used as an example. An image registration method based on phase correlation demonstrates the accurate detection of the spectral and spatial misregistrations. Cubic spline interpolation using estimated properties makes it possible to modify the spectral signatures. The accuracy of the proposed postlaunch estimation of the Hyperion characteristics is comparable to that of the prelaunch measurements, which enables the accurate onboard calibration of hyperspectral sensors.

  1. Searching non-impulsive earthquakes using a full-waveform, cross-correlation detection method.

    NASA Astrophysics Data System (ADS)

    alinne solano, ericka; Hjorleifsdottir, Vala

    2016-04-01

    Some seismic events, which have low P-wave amplitude, pass undetected by regional or global networks. A subset of these events occur due to fast mass movement as in the case of rapid glacial movements (Ekström, et al., 2003; Ekström, et al., 2006) or landslides (Ekstrom and Stark, 2013). Some other events depleted in high frequencies are related to volcanic activity (e.g. Schuler and Ekstrom, 2009) or to non-volcanic tremors (Obara, 2002). Furthermore, non-impulsive earthquakes have been located on oceanic transform faults (OTF) (Abercrombie and Ekstrom, 2001). A suite of methods can be used to detect these non-impulsive events. Correlation, matched filter, or template event methods (e.g. Schaff and Waldhauser 2010; Rubinstein & Beroza 2007) are very efficient for detecting smaller events occurring in a similar place and with the same mechanism as a larger template event. One such method (Ekström, 2006), that is applied on the scale of the globe, routinely detects events with magnitudes around Mw 5 and larger. In this work we want to lower the detection threshold by using shorter period records registered by regional networks together with a full-waveform detection method based on time reversal schemes (Solano, et al., in prep.). The method uses continuous observed seismograms, together with moment tensor responses calculated for a 3D structure. Looking for events on the East Pacific Rise (EPR) around 9 N in one month of data from the National Seismological broadband Network (Servicio Sismologico Nacional, SSN), we found one new event. However, we also had 435 false detections due to high noise levels at several stations, gaps in the data or detection of teleseismic phases. To manually discard these events is a time consuming task that should be automated. We are working on several strategies, including weighting the input traces by their signal to noise ratio, correlation of a template peak associated to the detection function and the coincidence in time of the

  2. Exploring the limits of waveform correlation event detection as applied to three earthquake aftershock sequences.

    SciTech Connect

    Resor, Megan E.; Carr, Dorthe Bame; Young, Christopher John

    2010-05-01

    Swarms of earthquakes and/or aftershock sequences can dramatically increase the level of seismicity in a region for a period of time lasting from days to months, depending on the swarm or sequence. Such occurrences can provide a large amount of useful information to seismologists. For those who monitor seismic events for possible nuclear explosions, however, these swarms/sequences are a nuisance. In an explosion monitoring system, each event must be treated as a possible nuclear test until it can be proven, to a high degree of confidence, not to be. Seismic events recorded by the same station with highly correlated waveforms almost certainly have a similar location and source type, so clusters of events within a swarm can quickly be identified as earthquakes. We have developed a number of tools that can be used to exploit the high degree of waveform similarity expected to be associated with swarms/sequences. Dendro Tool measures correlations between known events. The Waveform Correlation Detector is intended to act as a detector, finding events in raw data which correlate with known events. The Self Scanner is used to find all correlated segments within a raw data steam and does not require an event library. All three techniques together provide an opportunity to study the similarities of events in an aftershock sequence in different ways. To comprehensively characterize the benefits and limits of waveform correlation techniques, we studied 3 aftershock sequences, using our 3 tools, at multiple stations. We explored the effects of station distance and event magnitudes on correlation results. Lastly, we show the reduction in detection threshold and analyst workload offered by waveform correlation techniques compared to STA/LTA based detection. We analyzed 4 days of data from each aftershock sequence using all three methods. Most known events clustered in a similar manner across the toolsets. Up to 25% of catalogued events were found to be a member of a cluster. In

  3. Improving the resolution in proton-detected through-space heteronuclear multiple quantum correlation NMR spectroscopy

    NASA Astrophysics Data System (ADS)

    Shen, Ming; Trébosc, J.; Lafon, O.; Pourpoint, F.; Hu, Bingwen; Chen, Qun; Amoureux, J.-P.

    2014-08-01

    Connectivities and proximities between protons and low-gamma nuclei can be probed in solid-state NMR spectroscopy using two-dimensional (2D) proton-detected heteronuclear correlation, through Heteronuclear Multiple Quantum Correlation (HMQC) pulse sequence. The indirect detection via protons dramatically enhances the sensitivity. However, the spectra are often broadened along the indirect F1 dimension by the decay of heteronuclear multiple-quantum coherences under the strong 1H-1H dipolar couplings. This work presents a systematic comparison of the performances of various decoupling schemes during the indirect t1 evolution period of dipolar-mediated HMQC (D-HMQC) experiment. We demonstrate that 1H-1H dipolar decoupling sequences during t1, such as symmetry-based schemes, phase-modulated Lee-Goldburg (PMLG) and Decoupling Using Mind-Boggling Optimization (DUMBO), provide better resolution than continuous wave 1H irradiation. We also report that high resolution requires the preservation of 1H isotropic chemical shifts during the decoupling sequences. When observing indirectly broad spectra presenting numerous spinning sidebands, the D-HMQC sequence must be fully rotor-synchronized owing to the rotor-synchronized indirect sampling and dipolar recoupling sequence employed. In this case, we propose a solution to reduce artefact sidebands caused by the modulation of window delays before and after the decoupling application during the t1 period. Moreover, we show that 1H-1H dipolar decoupling sequence using Smooth Amplitude Modulation (SAM) minimizes the t1-noise. The performances of the various decoupling schemes are assessed via numerical simulations and compared to 2D 1H-{13C} D-HMQC experiments on [U-13C]-L-histidineṡHClṡH2O at various magnetic fields and Magic Angle spinning (MAS) frequencies. Great resolution and sensitivity enhancements resulting from decoupling during t1 period enable the detection of heteronuclear correlation between aliphatic protons and

  4. Experimental detection of nonclassical correlations in mixed-state quantum computation

    SciTech Connect

    Passante, G.; Moussa, O.; Trottier, D. A.; Laflamme, R.

    2011-10-15

    We report on an experiment to detect nonclassical correlations in a highly mixed state. The correlations are characterized by the quantum discord and are observed using four qubits in a liquid-state nuclear magnetic resonance quantum information processor. The state analyzed is the output of a DQC1 computation, whose input is a single quantum bit accompanied by n maximally mixed qubits. This model of computation outperforms the best known classical algorithms and, although it contains vanishing entanglement, it is known to have quantum correlations characterized by the quantum discord. This experiment detects nonvanishing quantum discord, ensuring the existence of nonclassical correlations as measured by the quantum discord.

  5. Identification of Protein-Protein Interactions by Detecting Correlated Mutation at the Interface.

    PubMed

    Guo, Fei; Ding, Yijie; Li, Zhao; Tang, Jijun

    2015-09-28

    Protein-protein interactions play key roles in a multitude of biological processes, such as de novo drug design, immune response, and enzymatic activity. It is of great interest to understand how proteins in a complex interact with each other. Here, we present a novel method for identifying protein-protein interactions, based on typical co-evolutionary information. Correlated mutation analysis can be used to predict interface residues. In this paper, we propose a non-redundant database to detect correlated mutation at the interface. First, we construct structure alignments for one input protein, based on all aligned proteins in the database. Evolutionary distance matrices, one for each input protein, can be calculated through geometric similarity and evolutionary information. Then, we use evolutionary distance matrices to estimate correlation coefficient between each pair of fragments from two input proteins. Finally, we extract interacting residues with high values of correlation coefficient, which can be grouped as interacting patches. Experiments illustrate that our method achieves better results than some existing co-evolution-based methods. Applied to SK/RR interaction between sensor kinase and response regulator proteins, our method has accuracy and coverage values of 53% and 45%, which improves upon accuracy and coverage values of 50% and 30% for DCA method. We evaluate interface prediction on four protein families, and our method has overall accuracy and coverage values of 34% and 30%, which improves upon overall accuracy and coverage values of 27% and 21% for PIFPAM. Our method has overall accuracy and coverage values of 59% and 63% on Benchmark v4.0, and 50% and 49% on CAPRI targets. Comparing to existing methods, our method improves overall accuracy value by at least 2%. PMID:26284382

  6. Optics based biohashing using joint transform correlator

    NASA Astrophysics Data System (ADS)

    Saini, Nirmala; Sinha, Aloka

    2010-03-01

    Most authentication process uses password and personal identification numbers (PIN) for security purposes. In order to remove the problem of hacking or stealing of the password and PIN numbers, there has been an increased interest in the utilization of specific biometric feature of the user. Recently, biohashing systems have been introduced for automatic biometric recognition. In a biohashing system, biohash codes are generated using the feature of the biometric. A basic biohashing system involves two steps. First is the extraction of the feature from the input biometric image and second is the discretisation of the obtained feature vector by using ortho-normalized random numbers. In this paper, a new biohashing system has been proposed in which joint transform correlator (JTC) has been used for extraction of the specific feature of the biometric. In the enrolment process, a biohash code has been generated by using a single face image and then stored. In the verification process, this biohash code is matched with the verification codes for recognition purpose. The main advantage of the proposed biohashing method is the possibility of the optical implementation of the feature extraction of the face image. Experimental as well as simulation results have been given to validate the proposed technique. Normalized Hamming distance has been calculated to discriminate the genuine and impostor face images. By varying the dimension of the feature matrix, the study of the variation of the normalized Hamming distance with the density of the population has been undertaken. For the performance evaluation of the proposed technique the false rejection ratio (FRR) and false acceptance ratio (FAR) have also been calculated.

  7. NEURAL CORRELATES OF HUMOR DETECTION AND APPRECIATION IN CHILDREN

    PubMed Central

    Neely, Michelle N.; Walter, Elizabeth; Black, Jessica M.; Reiss, Allan L.

    2012-01-01

    Humor is a vital component of human well-being. Neuroimaging studies conducted with adults indicate that humor activates specific brain regions including the temporo-occipito-parietal junction (TOPJ), involved in incongruity resolution, and mesolimbic regions, involved in reward processing. However, no study to date has used neuroimaging to examine humor in typically developing children. Here we illuminate the neural network involved in the detection and appreciation of humor in childhood. Fifteen typically developing children ages 6–12 were invited to watch and respond to video clips while neural activity was imaged with a 3T GE Discovery MR750 scanner. Prior to presentation during functional imaging, the clips were evaluated by age-matched controls and were representative of three categories: Funny, Positive (enjoyable but not funny), and Neutral (not intended to evoke any emotional response). We found TOPJ and mesolimbic activation in children’s response to humor, suggesting these regions may form a humor-essential neural network already present in childhood. Furthermore, in a novel comparison of Funny stimuli to Positive stimuli, we found that bilateral TOPJ activation may be specific to humor processing and not part of a general constellation of neural activity in response to reward. Finally, we observed greater activation in the inferior frontal gyrus and NAcc in younger participants, indicating humor activation intensity changes during development. By providing a crucial link in studying the neurodevelopment of humor processing across the lifespan, our findings contribute valuable information about the evolution of how children understand their world. PMID:22302817

  8. Neural correlates of gap detection in auditory nerve fibers of the chinchilla.

    PubMed

    Zhang, W; Salvi, R J; Saunders, S S

    1990-07-01

    The neural correlates of gap detection were examined in a population of single auditory nerve fibers in the chinchilla. Acoustic stimuli consisted of 120 ms noise bursts (30-80 dB SPL) which contained silent intervals (gaps: 1, 2, 3, 4,5, 6 and 10 ms) at the midpoint. The neural response to the gap was quantified by the modulation index, (MAX-MIN)/AVE, which accounts for the steady state discharge rate before the gap (AVE), the minimum firing rate during the gap (MIN), and the maximum firing rate after the gap (MAX). In general, the modulation index increased as a function of gap width and stimulus level. Furthermore, there was a positive correlation between the modulation index and the characteristic frequency of the fiber. To estimate how detection could be based on the neuronal response, a criterion-free measure, analogous to d'. was calculated using z-scores obtained from the distributions of modulation index values collected before and during the gap and used to predict percent correct values for chinchilla psychophysical studies. The values increased with gap duration in a sigmoidal manner much like the psychometric functions in the chinchilla. In general, the neural gap thresholds obtained approximated those obtained psychophysically, although they were less affected by stimulus level. PMID:2394632

  9. Biplane correlation imaging for lung nodule detection: initial human subject results

    NASA Astrophysics Data System (ADS)

    Majdi Nasab, Nariman; Samei, Ehsan; Dobbins, James T., III

    2006-03-01

    In this paper, we present performance of biplane correlation imaging (BCI) on set of chest x-ray projections of human data. BCI significantly minimizes the number of false positives (FPs) when used in conjunction with computer aided detection (CAD) by eliminating non-correlated nodule candidates. Sixty-one low exposure posterior projections were acquired from more than 20 human subjects with small angular separations (0.32 degree) over a range of 20 degrees along the vertical axis. All patients were previously diagnosed for the presence of lung nodules based on computed tomography (CT) examination. Images were processed following two steps. First, all images were analyzed using our CAD routine for chest radiography. This process proceeded with a BCI processing in which the results of CAD on each single projection were examined in terms of their geometrical correlation with those found in the other 60 projections based on the predetermined shift of possible nodule locations in each projection. The suspect entities with a geometrical correlation that coincided with the known location of the lesions were selected as nodules; otherwise they were ignored. An expert radiologist with reference to the associated CT dataset determined the truth regarding nodule location and sizes, which were then used to determine if the found nodules are true positive or false positive. The preliminary results indicated that the best performance was obtained when the angular separation of the projection pair was greater than about 6.7 degrees. Within the range of optimum angular separation, the number of FPs per image was 0-1 without impacting the number of true positives (TPs), averaged around 92%.

  10. Detecting Eve in communication with continuous-variable Einstein-Podolsky-Rosen correlations

    SciTech Connect

    Messikh, A.

    2007-03-15

    We study the validity of the entanglement parameter introduced in a recent publication by Guangqiang et al. [Phys. Rev. A 73, 012314 (2006)] for detecting Eve, the eavesdropper. We have found that Eve can be detected using this parameter only if Alice establishes a quantum correlation between the Einstein-Podolsky-Rosen (EPR) pair. This quantum correlation is related to the possibility of an apparent violation of the Heisenberg inequality for the quadrature components of the EPR pair.

  11. Visualizing confusion matrices for multidimensional signal detection correlational methods

    NASA Astrophysics Data System (ADS)

    Zhou, Yue; Wischgoll, Thomas; Blaha, Leslie M.; Smith, Ross; Vickery, Rhonda J.

    2013-12-01

    Advances in modeling and simulation for General Recognition Theory have produced more data than can be easily visualized using traditional techniques. In this area of psychological modeling, domain experts are struggling to find effective ways to compare large-scale simulation results. This paper describes methods that adapt the web-based D3 visualization framework combined with pre-processing tools to enable domain specialists to more easily interpret their data. The D3 framework utilizes Javascript and scalable vector graphics (SVG) to generate visualizations that can run readily within the web browser for domain specialists. Parallel coordinate plots and heat maps were developed for identification-confusion matrix data, and the results were shown to a GRT expert for an informal evaluation of their utility. There is a clear benefit to model interpretation from these visualizations when researchers need to interpret larger amounts of simulated data.

  12. Miniaturized Hollow-Waveguide Gas Correlation Radiometer (GCR) for Trace Gas Detection in the Martian Atmosphere

    NASA Technical Reports Server (NTRS)

    Wilson, Emily L.; Georgieva, E. M.; Melroy, H. R.

    2012-01-01

    Gas correlation radiometry (GCR) has been shown to be a sensitive and versatile method for detecting trace gases in Earth's atmosphere. Here, we present a miniaturized and simplified version of this instrument capable of mapping multiple trace gases and identifying active regions on the Mars surface. Reduction of the size and mass of the GCR instrument has been achieved by implementing a lightweight, 1 mm inner diameter hollow-core optical fiber (hollow waveguide) for the gas correlation cell. Based on a comparison with an Earth orbiting CO2 gas correlation instrument, replacement of the 10 meter mUltipass cell with hollow waveguide of equivalent pathlength reduces the cell mass from approx 150 kg to approx 0.5 kg, and reduces the volume from 1.9 m x 1.3 m x 0.86 m to a small bundle of fiber coils approximately I meter in diameter by 0.05 m in height (mass and volume reductions of >99%). This modular instrument technique can be expanded to include measurements of additional species of interest including nitrous oxide (N2O), hydrogen sulfide (H2S), methanol (CH3OH), and sulfur dioxide (SO2), as well as carbon dioxide (CO2) for a simultaneous measure of mass balance.

  13. Fearful Face Detection Sensitivity in Healthy Adults Correlates with Anxiety-Related Traits

    PubMed Central

    Doty, Tracy J.; Japee, Shruti; Ingvar, Martin; Ungerleider, Leslie G.

    2014-01-01

    Threatening faces have a privileged status in the brain, which can be reflected in a processing advantage. However, this effect varies among individuals, even healthy adults. For example, one recent study showed that fearful face detection sensitivity correlated with trait anxiety in healthy adults (Japee, Crocker, Carver, Pessoa, & Ungerleider, 2009). Here, we expanded upon those findings by investigating whether intersubject variability in fearful face detection is also associated with state anxiety, as well as more broadly with other traits related to anxiety. To measure fearful face detection sensitivity, we employed a masked face paradigm where the target face was presented for only 33 ms and was immediately followed by a neutral face mask. Subjects then rated their confidence in detecting either fear or no fear in the target face. Fearful face detection sensitivity was calculated for each subject using signal detection theory. Replicating previous results, we found a significant positive correlation between trait anxiety and fearful face detection sensitivity. However, this behavioral advantage did not correlate with state anxiety. We also found that fearful face detection sensitivity correlated with other personality measures, including neuroticism and harm avoidance. Our data suggest that fearful face detection sensitivity varies parametrically across the healthy population, is associated broadly with personality traits related to anxiety, but remains largely unaffected by situational fluctuations in anxiety. These results underscore the important contribution of anxiety-related personality traits to threat processing in healthy adults. PMID:23398584

  14. Experimental results for correlation-based wavefront sensing

    SciTech Connect

    Poyneer, L A; Palmer, D W; LaFortune, K N; Bauman, B

    2005-07-01

    Correlation wave-front sensing can improve Adaptive Optics (AO) system performance in two keys areas. For point-source-based AO systems, Correlation is more accurate, more robust to changing conditions and provides lower noise than a centroiding algorithm. Experimental results from the Lick AO system and the SSHCL laser AO system confirm this. For remote imaging, Correlation enables the use of extended objects for wave-front sensing. Results from short horizontal-path experiments will show algorithm properties and requirements.

  15. Neural correlates of object-based attention.

    PubMed

    Pei, Francesca; Pettet, Mark W; Norcia, Anthony M

    2002-01-01

    Much research has been directed toward disentangling the "units" of attention: Is attention directed to locations in space, visual objects, or to individual features of an object? Moreover, there is considerable interest in whether attention increases the gain of neural mechanisms (signal enhancement) or acts by other means, such as reducing noise or narrowing channel tuning. To address these questions, we used a direct measure of signal strength: the amplitude of visual evoked potentials and a task in which selection could be based on a depth order cue but not on location. Attended and nonattended stimuli were presented at different temporal frequencies, and, thus, responses to the two stimuli could be analyzed separately even though they were presented simultaneously. Attention increased the amplitude of the second harmonic component of the response, but not the fourth harmonic. In addition, responses measured at the second harmonic, but not at the fourth harmonic, were larger for stimuli seen as behind. The results are consistent with the fourth harmonic being generated at a stage of processing that is not accessible to attention and where depth order has not been extracted. The second harmonic, on the other hand, is modifiable by attention and shows evidence for differential encoding of depth order.

  16. Detection of microcalcifications by characteristic magnetic susceptibility effects using MR phase image cross-correlation analysis

    SciTech Connect

    Baheza, Richard A.; Welch, E. Brian; Gochberg, Daniel F.; Sanders, Melinda; Harvey, Sara; Gore, John C.; Yankeelov, Thomas E.

    2015-03-15

    Purpose: To develop and evaluate a new method for detecting calcium deposits using their characteristic magnetic susceptibility effects on magnetic resonance (MR) images at high fields and demonstrate its potential in practice for detecting breast microcalcifications. Methods: Characteristic dipole signatures of calcium deposits were detected in magnetic resonance phase images by computing the cross-correlation between the acquired data and a library of templates containing simulated phase patterns of spherical deposits. The influence of signal-to-noise ratio and various other MR parameters on the results were assessed using simulations and validated experimentally. The method was tested experimentally for detection of calcium fragments within gel phantoms and calcium-like inhomogeneities within chicken tissue at 7 T with optimized MR acquisition parameters. The method was also evaluated for detection of simulated microcalcifications, modeled from biopsy samples of malignant breast cancer, inserted in silico into breast magnetic resonance imaging (MRIs) of healthy subjects at 7 T. For both assessments of calcium fragments in phantoms and biopsy-based simulated microcalcifications in breast MRIs, receiver operator characteristic curve analyses were performed to determine the cross-correlation index cutoff, for achieving optimal sensitivity and specificity, and the area under the curve (AUC), for measuring the method’s performance. Results: The method detected calcium fragments with sizes of 0.14–0.79 mm, 1 mm calcium-like deposits, and simulated microcalcifications with sizes of 0.4–1.0 mm in images with voxel sizes between (0.2 mm){sup 3} and (0.6 mm){sup 3}. In images acquired at 7 T with voxel sizes of (0.2 mm){sup 3}–(0.4 mm){sup 3}, calcium fragments (size 0.3–0.4 mm) were detected with a sensitivity, specificity, and AUC of 78%–90%, 51%–68%, and 0.77%–0.88%, respectively. In images acquired with a human 7 T scanner, acquisition times below 12

  17. Detection of microcalcifications by characteristic magnetic susceptibility effects using MR phase image cross-correlation analysis

    PubMed Central

    Baheza, Richard A.; Welch, E. Brian; Gochberg, Daniel F.; Sanders, Melinda; Harvey, Sara; Gore, John C.; Yankeelov, Thomas E.

    2015-01-01

    Purpose: To develop and evaluate a new method for detecting calcium deposits using their characteristic magnetic susceptibility effects on magnetic resonance (MR) images at high fields and demonstrate its potential in practice for detecting breast microcalcifications. Methods: Characteristic dipole signatures of calcium deposits were detected in magnetic resonance phase images by computing the cross-correlation between the acquired data and a library of templates containing simulated phase patterns of spherical deposits. The influence of signal-to-noise ratio and various other MR parameters on the results were assessed using simulations and validated experimentally. The method was tested experimentally for detection of calcium fragments within gel phantoms and calcium-like inhomogeneities within chicken tissue at 7 T with optimized MR acquisition parameters. The method was also evaluated for detection of simulated microcalcifications, modeled from biopsy samples of malignant breast cancer, inserted in silico into breast magnetic resonance imaging (MRIs) of healthy subjects at 7 T. For both assessments of calcium fragments in phantoms and biopsy-based simulated microcalcifications in breast MRIs, receiver operator characteristic curve analyses were performed to determine the cross-correlation index cutoff, for achieving optimal sensitivity and specificity, and the area under the curve (AUC), for measuring the method’s performance. Results: The method detected calcium fragments with sizes of 0.14–0.79 mm, 1 mm calcium-like deposits, and simulated microcalcifications with sizes of 0.4–1.0 mm in images with voxel sizes between (0.2 mm)3 and (0.6 mm)3. In images acquired at 7 T with voxel sizes of (0.2 mm)3–(0.4 mm)3, calcium fragments (size 0.3–0.4 mm) were detected with a sensitivity, specificity, and AUC of 78%–90%, 51%–68%, and 0.77%–0.88%, respectively. In images acquired with a human 7 T scanner, acquisition times below 12 min, and voxel sizes of

  18. Daytime Water Detection Based on Sky Reflections

    NASA Technical Reports Server (NTRS)

    Rankin, Arturo; Matthies, Larry; Bellutta, Paolo

    2011-01-01

    A water body s surface can be modeled as a horizontal mirror. Water detection based on sky reflections and color variation are complementary. A reflection coefficient model suggests sky reflections dominate the color of water at ranges > 12 meters. Water detection based on sky reflections: (1) geometrically locates the pixel in the sky that is reflecting on a candidate water pixel on the ground (2) predicts if the ground pixel is water based on color similarity and local terrain features. Water detection has been integrated on XUVs.

  19. An Intrusion Detection Algorithm Based On NFPA

    NASA Astrophysics Data System (ADS)

    Anming, Zhong

    A process oriented intrusion detection algorithm based on Probabilistic Automaton with No Final probabilities (NFPA) is introduced, system call sequence of process is used as the source data. By using information in system call sequence of normal process and system call sequence of anomaly process, the anomaly detection and the misuse detection are efficiently combined. Experiments show better performance of our algorithm compared to the classical algorithm in this field.

  20. Assessment of absolute added correlative coding in optical intensity modulation and direct detection channels

    NASA Astrophysics Data System (ADS)

    Dong-Nhat, Nguyen; Elsherif, Mohamed A.; Malekmohammadi, Amin

    2016-06-01

    The performance of absolute added correlative coding (AACC) modulation format with direct detection has been numerically and analytically reported, targeting metro data center interconnects. Hereby, the focus lies on the performance of the bit error rate, noise contributions, spectral efficiency, and chromatic dispersion tolerance. The signal space model of AACC, where the average electrical and optical power expressions are derived for the first time, is also delineated. The proposed modulation format was also compared to other well-known signaling, such as on-off-keying (OOK) and four-level pulse-amplitude modulation, at the same bit rate in a directly modulated vertical-cavity surface-emitting laser-based transmission system. The comparison results show a clear advantage of AACC in achieving longer fiber delivery distance due to the higher dispersion tolerance.

  1. Comparison of cyclic correlation and the wavelet method for symbol rate detection

    NASA Astrophysics Data System (ADS)

    Carr, Richard; Whitney, James

    Software defined radio (SDR) is a relatively new technology that holds a great deal of promise in the communication field in general, and, in particular the area of space communications. Tra-ditional communication systems are comprised of a transmitter and a receiver, where through prior planning and scheduling, the transmitter and receiver are pre-configured for a particu-lar communication modality. For any particular modality the radio circuitry is configured to transmit, receive, and resolve one type of modulation at a certain data rate. Traditional radio's are limited by the fact that the circuitry is fixed. Software defined radios on the other hand do not suffer from this limitation. SDR's are comprised mainly of software modules which allow them to be flexible, in that they can resolve various types of modulation types that occur at different data rates. This ability is of very high importance in space where parameters of the communications link may need to be changed due to channel fading, reduced power, or other unforeseen events. In these cases the ability to autonomously change aspects of the radio's con-figuration becomes an absolute necessity in order to maintain communications. In order for the technology to work the receiver has to be able to determine the modulation type and the data rate of the signal. The data rate of the signal is one of the first parameters to be resolved, as it is needed to find the other signal parameters such as modulation type and the signal-to-noise ratio. There are a number of algorithms that have been developed to detect or estimate the data rate of a signal. This paper will investigate two of these algorithms, namely, the cyclic correlation algorithm and a wavelet-based detection algorithm. Both of these algorithms are feature-based algorithms, meaning that they make their estimations based on certain inherent features of the signals to which they are applied. The cyclic correlation algorithm takes advan-tage of the

  2. Design of fire detection equipment based on ultraviolet detection technology

    NASA Astrophysics Data System (ADS)

    Liu, Zhenji; Liu, Jin; Chu, Sheng; Ping, Chao; Yuan, Xiaobing

    2015-03-01

    Utilized the feature of wide bandgap semiconductor of MgZnO, researched and developed a kind of Mid-Ultraviolet-Band(MUV) ultraviolet detector which has passed the simulation experiment in the sun circumstance. Based on the ultraviolet detector, it gives out a design scheme of gun-shot detection device, which is composed of twelve ultraviolet detectors, signal amplifier, processor, annunciator , azimuth indicator and the bracket. Through Analysing the feature of solar blind, ultraviolet responsivity, fire feature of gunshots and detection distance, the feasibility of this design scheme is proved.

  3. Parameter-space correlations of the optimal statistic for continuous gravitational-wave detection

    SciTech Connect

    Pletsch, Holger J.

    2008-11-15

    The phase parameters of matched-filtering searches for continuous gravitational-wave signals are sky position, frequency, and frequency time-derivatives. The space of these parameters features strong global correlations in the optimal detection statistic. For observation times smaller than 1 yr, the orbital motion of the Earth leads to a family of global-correlation equations which describes the 'global maximum structure' of the detection statistic. The solution to each of these equations is a different hypersurface in parameter space. The expected detection statistic is maximal at the intersection of these hypersurfaces. The global maximum structure of the detection statistic from stationary instrumental-noise artifacts is also described by the global-correlation equations. This permits the construction of a veto method which excludes false candidate events.

  4. Sociolect-Based Community Detection

    SciTech Connect

    Reynolds, William N.; Salter, William J.; Farber, Robert M.; Corley, Courtney D.; Dowling, Chase P.; Beeman, William O.; Smith-Lovin, Lynn; Choi, Joon Nak

    2013-06-06

    "Sociolects" are specialized vocabularies used by social subgroups defined by common interests or origins. We applied methods to retrieve large quantities of Twitter data based on expert-identified sociolects and then applied and developed network-analysis methods to relate sociolect use to network (sub-) structure. We show that novel methods including consideration of node populations, as well as edge counts, provide substantially enhanced performance compared to standard assortativity. We explain these methods, show their utility in analyzing large corpora of social media data, and discuss their further extensions and potential applications.

  5. Continuous detection of weak sensory signals in afferent spike trains: the role of anti-correlated interspike intervals in detection performance.

    PubMed

    Goense, J B M; Ratnam, R

    2003-10-01

    An important problem in sensory processing is deciding whether fluctuating neural activity encodes a stimulus or is due to variability in baseline activity. Neurons that subserve detection must examine incoming spike trains continuously, and quickly and reliably differentiate signals from baseline activity. Here we demonstrate that a neural integrator can perform continuous signal detection, with performance exceeding that of trial-based procedures, where spike counts in signal- and baseline windows are compared. The procedure was applied to data from electrosensory afferents of weakly electric fish (Apteronotus leptorhynchus), where weak perturbations generated by small prey add approximately 1 spike to a baseline of approximately 300 spikes s(-1). The hypothetical postsynaptic neuron, modeling an electrosensory lateral line lobe cell, could detect an added spike within 10-15 ms, achieving near ideal detection performance (80-95%) at false alarm rates of 1-2 Hz, while trial-based testing resulted in only 30-35% correct detections at that false alarm rate. The performance improvement was due to anti-correlations in the afferent spike train, which reduced both the amplitude and duration of fluctuations in postsynaptic membrane activity, and so decreased the number of false alarms. Anti-correlations can be exploited to improve detection performance only if there is memory of prior decisions.

  6. Detection of Prostate Cancer: Quantitative Multiparametric MR Imaging Models Developed Using Registered Correlative Histopathology.

    PubMed

    Metzger, Gregory J; Kalavagunta, Chaitanya; Spilseth, Benjamin; Bolan, Patrick J; Li, Xiufeng; Hutter, Diane; Nam, Jung W; Johnson, Andrew D; Henriksen, Jonathan C; Moench, Laura; Konety, Badrinath; Warlick, Christopher A; Schmechel, Stephen C; Koopmeiners, Joseph S

    2016-06-01

    Purpose To develop multiparametric magnetic resonance (MR) imaging models to generate a quantitative, user-independent, voxel-wise composite biomarker score (CBS) for detection of prostate cancer by using coregistered correlative histopathologic results, and to compare performance of CBS-based detection with that of single quantitative MR imaging parameters. Materials and Methods Institutional review board approval and informed consent were obtained. Patients with a diagnosis of prostate cancer underwent multiparametric MR imaging before surgery for treatment. All MR imaging voxels in the prostate were classified as cancer or noncancer on the basis of coregistered histopathologic data. Predictive models were developed by using more than one quantitative MR imaging parameter to generate CBS maps. Model development and evaluation of quantitative MR imaging parameters and CBS were performed separately for the peripheral zone and the whole gland. Model accuracy was evaluated by using the area under the receiver operating characteristic curve (AUC), and confidence intervals were calculated with the bootstrap procedure. The improvement in classification accuracy was evaluated by comparing the AUC for the multiparametric model and the single best-performing quantitative MR imaging parameter at the individual level and in aggregate. Results Quantitative T2, apparent diffusion coefficient (ADC), volume transfer constant (K(trans)), reflux rate constant (kep), and area under the gadolinium concentration curve at 90 seconds (AUGC90) were significantly different between cancer and noncancer voxels (P < .001), with ADC showing the best accuracy (peripheral zone AUC, 0.82; whole gland AUC, 0.74). Four-parameter models demonstrated the best performance in both the peripheral zone (AUC, 0.85; P = .010 vs ADC alone) and whole gland (AUC, 0.77; P = .043 vs ADC alone). Individual-level analysis showed statistically significant improvement in AUC in 82% (23 of 28) and 71% (24 of 34

  7. Collaborative regression-based anatomical landmark detection

    NASA Astrophysics Data System (ADS)

    Gao, Yaozong; Shen, Dinggang

    2015-12-01

    Anatomical landmark detection plays an important role in medical image analysis, e.g. for registration, segmentation and quantitative analysis. Among the various existing methods for landmark detection, regression-based methods have recently attracted much attention due to their robustness and efficiency. In these methods, landmarks are localised through voting from all image voxels, which is completely different from the classification-based methods that use voxel-wise classification to detect landmarks. Despite their robustness, the accuracy of regression-based landmark detection methods is often limited due to (1) the inclusion of uninformative image voxels in the voting procedure, and (2) the lack of effective ways to incorporate inter-landmark spatial dependency into the detection step. In this paper, we propose a collaborative landmark detection framework to address these limitations. The concept of collaboration is reflected in two aspects. (1) Multi-resolution collaboration. A multi-resolution strategy is proposed to hierarchically localise landmarks by gradually excluding uninformative votes from faraway voxels. Moreover, for informative voxels near the landmark, a spherical sampling strategy is also designed at the training stage to improve their prediction accuracy. (2) Inter-landmark collaboration. A confidence-based landmark detection strategy is proposed to improve the detection accuracy of ‘difficult-to-detect’ landmarks by using spatial guidance from ‘easy-to-detect’ landmarks. To evaluate our method, we conducted experiments extensively on three datasets for detecting prostate landmarks and head & neck landmarks in computed tomography images, and also dental landmarks in cone beam computed tomography images. The results show the effectiveness of our collaborative landmark detection framework in improving landmark detection accuracy, compared to other state-of-the-art methods.

  8. Correlation-Based Image Reconstruction Methods for Magnetic Particle Imaging

    NASA Astrophysics Data System (ADS)

    Ishihara, Yasutoshi; Kuwabara, Tsuyoshi; Honma, Takumi; Nakagawa, Yohei

    Magnetic particle imaging (MPI), in which the nonlinear interaction between internally administered magnetic nanoparticles (MNPs) and electromagnetic waves irradiated from outside of the body is utilized, has attracted attention for its potential to achieve early diagnosis of diseases such as cancer. In MPI, the local magnetic field distribution is scanned, and the magnetization signal from MNPs within a selected region is detected. However, the signal sensitivity and image resolution are degraded by interference from magnetization signals generated by MNPs outside of the selected region, mainly because of imperfections (limited gradients) in the local magnetic field distribution. Here, we propose new methods based on correlation information between the observed signal and the system function—defined as the interaction between the magnetic field distribution and the magnetizing properties of MNPs. We performed numerical analyses and found that, although the images were somewhat blurred, image artifacts could be significantly reduced and accurate images could be reconstructed without the inverse-matrix operation used in conventional image reconstruction methods.

  9. Cartridge case image matching using effective correlation area based method.

    PubMed

    Yammen, S; Muneesawang, P

    2013-06-10

    A firearm leaves a unique impression on fired cartridge cases. The cross-correlation function plays an important role in matching the characteristic features on the cartridge case found at the crime scene with a specific firearm, for accurate firearm identification. This paper proposes that the computational forensic techniques of alignment and effective correlation area-based approaches to image matching are essential to firearm identification. Specifically, the reference and the corresponding cartridge cases are aligned according to the phase-correlation criterion on the transform domain. The informative segments of the breech face marks are identified by a cross-covariance coefficient using the coefficient value in a window located locally in the image space. The segments are then passed to the measurement of edge density for computing effective correlation areas. Experimental results on a new dataset show that the correlation system can make use of the best properties of alignment and effective correlation area-based approaches, and can attain significant improvement of image-correlation results, compared with the traditional image-matching methods for firearm identification, which employ cartridge-case samples. An analysis of image-alignment score matrices suggests that all translation and scaling parameters are estimated correctly, and contribute to the successful extraction of effective correlation areas. It was found that the proposed method has a high discriminant power, compared with the conventional correlator. This paper advocates that this method will enable forensic science to compile a large-scale image database to perform correlation of cartridge case bases, in order to identify firearms that involve pairwise alignments and comparisons.

  10. Bioaerosol standoff detection and correlation assessment with concentration and viability point sensors

    NASA Astrophysics Data System (ADS)

    Buteau, Sylvie; Simard, Jean-Robert; Rowsell, Susan; Roy, Gilles

    2010-10-01

    A standoff bioaerosol sensor based on intensified range-gated spectrometric detection of Laser Induced Fluorescence was used to spectrally characterize bioaerosol simulants during in-chamber and open-air releases at Suffield, Canada, in August 2008 from a standoff position. In total, 42 in-chamber Bacillus atrophaeus (formerly Bacillus subtilis var globigii; BG) cloud and 27 open-air releases of either BG, Pantoea agglomerans (formerly Erwinia herbicola; EH), MS2 and ovalbumin (OV) were generated. The clouds were refereed by different point sensors including Aerodynamic Particle Sizer (APS) and slit or impingers samplers. The APS monitored the particle size distribution and concentration and the samplers characterized the viable portion of the cloud. The extracted spectral signatures show robustness to different degree. The correlation assessment showed good results in most cases where the LIF signal to noise ratio was significant. The sensor 4σ sensitivity was evaluated to 1 300, 600, 100 and 30 ppl for BG, OV, MS2 and EH respectively. Correlation results are presented by plotting the SINBAHD metric versus the corresponding particle concentration, in which case, the obtained slope is proportional to the material fluorescence cross-section. The different acquired signal is hence compared in terms of their fluorescence cross-section additionally to their spectral characteristics.

  11. [Electroencephalogram Feature Selection Based on Correlation Coefficient Analysis].

    PubMed

    Zhou, Jinzhi; Tang, Xiaofang

    2015-08-01

    In order to improve the accuracy of classification with small amount of motor imagery training data on the development of brain-computer interface (BCD systems, we proposed an analyzing method to automatically select the characteristic parameters based on correlation coefficient analysis. Throughout the five sample data of dataset IV a from 2005 BCI Competition, we utilized short-time Fourier transform (STFT) and correlation coefficient calculation to reduce the number of primitive electroencephalogram dimension, then introduced feature extraction based on common spatial pattern (CSP) and classified by linear discriminant analysis (LDA). Simulation results showed that the average rate of classification accuracy could be improved by using correlation coefficient feature selection method than those without using this algorithm. Comparing with support vector machine (SVM) optimization features algorithm, the correlation coefficient analysis can lead better selection parameters to improve the accuracy of classification. PMID:26710441

  12. Correlation-based methods in calibrating an FBG sensor with strain field non-uniformity

    NASA Astrophysics Data System (ADS)

    Cieszczyk, S.

    2015-12-01

    Fibre Bragg gratings have many sensing applications, mainly for measuring strain and temperature. The physical quantity that influences grating uniformly along its length causes a related shift of the Bragg wavelength. Many peak detection algorithms have been proposed, among which the most popular are the detection of maximum intensity, the centroid detection, the least square method, the cross-correlation, auto-correlation and fast phase correlation. Nonuniform gratings elongation is a cause of spectrum deformation. The introduction of non-uniformity can be intentional or appear as an unintended effect of placing sensing elements in the tested structure. Heterogeneous impacts on grating may result in additional errors and the difficulty in tracking the Bragg wavelength based on a distorted spectrum. This paper presents the application of correlation methods of peak wavelength shifts estimation for non-uniform Bragg grating elongation. The autocorrelation, cross-correlation and fast phase correlation algorithms are considered and experimental spectra measured for axisymmetric strain field along the Bragg grating are analyzed. The strain profile consists of constant and variable components. The results of this study indicate the properties of correlation algorithms applied to moderately non-uniform elongation of an FBG sensor.

  13. Daytime Water Detection Based on Sky Reflections

    NASA Technical Reports Server (NTRS)

    Rankin, Arturo L.; Matthies, Larry H.; Bellutta, Paolo

    2011-01-01

    Robust water detection is a critical perception requirement for unmanned ground vehicle (UGV) autonomous navigation. This is particularly true in wide-open areas where water can collect in naturally occurring terrain depressions during periods of heavy precipitation and form large water bodies. One of the properties of water useful for detecting it is that its surface acts as a horizontal mirror at large incidence angles. Water bodies can be indirectly detected by detecting reflections of the sky below the horizon in color imagery. The Jet Propulsion Laboratory (JPL) has implemented a water detector based on sky reflections that geometrically locates the pixel in the sky that is reflecting on a candidate water pixel on the ground and predicts if the ground pixel is water based on color similarity and local terrain features. This software detects water bodies in wide-open areas on cross-country terrain at mid- to far-range using imagery acquired from a forward-looking stereo pair of color cameras mounted on a terrestrial UGV. In three test sequences approaching a pond under a clear, overcast, and cloudy sky, the true positive detection rate was 100% when the UGV was beyond 7 meters of the water's leading edge and the largest false positive detection rate was 0.58%. The sky reflection based water detector has been integrated on an experimental unmanned vehicle and field tested at Ft. Indiantown Gap, PA, USA.

  14. GaAs-based photorefractive time-integrating correlator

    NASA Technical Reports Server (NTRS)

    Liu, Duncan T. H.; Luke, Keung L.; Cheng, Li-Jen

    1992-01-01

    A potential application of the photorefractive time-integrating correlator is the real-time radar jamming interference rejection system, using the adaptive filter method; a fast photorefractive crystal is needed for adapting a rapidly changing jamming signal. An effort is presently made to demonstrate and characterize a GaAs-based photorefractive time-integrating correlator, since GaAs crystals are 2-3 orders of magnitude faster than most other alternatives.

  15. Fearful face detection sensitivity in healthy adults correlates with anxiety-related traits.

    PubMed

    Doty, Tracy J; Japee, Shruti; Ingvar, Martin; Ungerleider, Leslie G

    2013-04-01

    Threatening faces have a privileged status in the brain, which can be reflected in a processing advantage. However, this effect varies among individuals, even healthy adults. For example, one recent study showed that fearful face detection sensitivity correlated with trait anxiety in healthy adults (S. Japee, L. Crocker, F. Carver, L. Pessoa, & L. G. Ungerleider, 2009. Individual differences in valence modulation of face-selective M170 response. Emotion, 9, 59-69). Here, we expanded on those findings by investigating whether intersubject variability in fearful face detection is also associated with state anxiety, as well as more broadly with other traits related to anxiety. To measure fearful face detection sensitivity, we used a masked face paradigm where the target face was presented for only 33 ms and was immediately followed by a neutral face mask. Subjects then rated their confidence in detecting either fear or no fear in the target face. Fearful face detection sensitivity was calculated for each subject using signal detection theory. Replicating previous results, we found a significant positive correlation between trait anxiety and fearful face detection sensitivity. However, this behavioral advantage did not correlate with state anxiety. We also found that fearful face detection sensitivity correlated with other personality measures, including neuroticism and harm avoidance. Our data suggest that fearful face detection sensitivity varies parametrically across the healthy population, is associated broadly with personality traits related to anxiety, but remains largely unaffected by situational fluctuations in anxiety. These results underscore the important contribution of anxiety-related personality traits to threat processing in healthy adults.

  16. A rule-based system for well log correlation

    SciTech Connect

    Startzman, R.A.; Kuo, T.B.

    1987-09-01

    Computer-assisted approaches to well log correlation are of interest to engineers and geologists for two reasons. In large field studies, a computer can be used simply to reduce the time required to correlate zones of interest. It is also possible that computer-assisted correlations may suggest zonal matches of interest and originality that might not have been considered. This paper presents a new approach to the computer-assisted log correlation. Geologic horizons are correlated between wells by use of an artificial intelligence rule-based technique. Using the symbol-manipulation capabilities of a computer language called List Processing (LISP), the author developed a prototype rule-bases system that has symbolic representation of log data, recognizes log shapes from traces, identifies geologic zones from a sequence of shapes in a log, characterizes the zones, correlates zones from well to well with a set of ''if/then'' type of rules, and uses a forward-chaining inference scheme to execute the rule base. The purpose of this paper is to describe the use of the LISP language and the methodology involved in the development of this system.

  17. Similar Impacts of the Interaural Delay and Interaural Correlation on Binaural Gap Detection

    PubMed Central

    Kong, Lingzhi; Xie, Zilong; Lu, Lingxi; Qu, Tianshu; Wu, Xihong; Yan, Jun; Li, Liang

    2015-01-01

    The subjective representation of the sounds delivered to the two ears of a human listener is closely associated with the interaural delay and correlation of these two-ear sounds. When the two-ear sounds, e.g., arbitrary noises, arrive simultaneously, the single auditory image of the binaurally identical noises becomes increasingly diffuse, and eventually separates into two auditory images as the interaural correlation decreases. When the interaural delay increases from zero to several milliseconds, the auditory image of the binaurally identical noises also changes from a single image to two distinct images. However, measuring the effect of these two factors on an identical group of participants has not been investigated. This study examined the impacts of interaural correlation and delay on detecting a binaurally uncorrelated fragment (interaural correlation = 0) embedded in the binaurally correlated noises (i.e., binaural gap or break in interaural correlation). We found that the minimum duration of the binaural gap for its detection (i.e., duration threshold) increased exponentially as the interaural delay between the binaurally identical noises increased linearly from 0 to 8 ms. When no interaural delay was introduced, the duration threshold also increased exponentially as the interaural correlation of the binaurally correlated noises decreased linearly from 1 to 0.4. A linear relationship between the effect of interaural delay and that of interaural correlation was described for listeners participating in this study: a 1 ms increase in interaural delay appeared to correspond to a 0.07 decrease in interaural correlation specific to raising the duration threshold. Our results imply that a tradeoff may exist between the impacts of interaural correlation and interaural delay on the subjective representation of sounds delivered to two human ears. PMID:26125970

  18. Detection of Unexpected High Correlations between Balance Calibration Loads and Load Residuals

    NASA Technical Reports Server (NTRS)

    Ulbrich, N.; Volden, T.

    2014-01-01

    An algorithm was developed for the assessment of strain-gage balance calibration data that makes it possible to systematically investigate potential sources of unexpected high correlations between calibration load residuals and applied calibration loads. The algorithm investigates correlations on a load series by load series basis. The linear correlation coefficient is used to quantify the correlations. It is computed for all possible pairs of calibration load residuals and applied calibration loads that can be constructed for the given balance calibration data set. An unexpected high correlation between a load residual and a load is detected if three conditions are met: (i) the absolute value of the correlation coefficient of a residual/load pair exceeds 0.95; (ii) the maximum of the absolute values of the residuals of a load series exceeds 0.25 % of the load capacity; (iii) the load component of the load series is intentionally applied. Data from a baseline calibration of a six-component force balance is used to illustrate the application of the detection algorithm to a real-world data set. This analysis also showed that the detection algorithm can identify load alignment errors as long as repeat load series are contained in the balance calibration data set that do not suffer from load alignment problems.

  19. Recent advances in biosensor based endotoxin detection.

    PubMed

    Das, A P; Kumar, P S; Swain, S

    2014-01-15

    Endotoxins also referred to as pyrogens are chemically lipopolysaccharides habitually found in food, environment and clinical products of bacterial origin and are unavoidable ubiquitous microbiological contaminants. Pernicious issues of its contamination result in high mortality and severe morbidities. Standard traditional techniques are slow and cumbersome, highlighting the pressing need for evoking agile endotoxin detection system. The early and prompt detection of endotoxin assumes prime importance in health care, pharmacological and biomedical sectors. The unparalleled recognition abilities of LAL biosensors perched with remarkable sensitivity, high stability and reproducibility have bestowed it with persistent reliability and their possible fabrication for commercial applicability. This review paper entails an overview of various trends in current techniques available and other possible alternatives in biosensor based endotoxin detection together with its classification, epidemiological aspects, thrust areas demanding endotoxin control, commercially available detection sensors and a revolutionary unprecedented approach narrating the influence of omics for endotoxin detection. PMID:23934306

  20. Recent advances in biosensor based endotoxin detection.

    PubMed

    Das, A P; Kumar, P S; Swain, S

    2014-01-15

    Endotoxins also referred to as pyrogens are chemically lipopolysaccharides habitually found in food, environment and clinical products of bacterial origin and are unavoidable ubiquitous microbiological contaminants. Pernicious issues of its contamination result in high mortality and severe morbidities. Standard traditional techniques are slow and cumbersome, highlighting the pressing need for evoking agile endotoxin detection system. The early and prompt detection of endotoxin assumes prime importance in health care, pharmacological and biomedical sectors. The unparalleled recognition abilities of LAL biosensors perched with remarkable sensitivity, high stability and reproducibility have bestowed it with persistent reliability and their possible fabrication for commercial applicability. This review paper entails an overview of various trends in current techniques available and other possible alternatives in biosensor based endotoxin detection together with its classification, epidemiological aspects, thrust areas demanding endotoxin control, commercially available detection sensors and a revolutionary unprecedented approach narrating the influence of omics for endotoxin detection.

  1. Correlation theory-based signal processing method for CMF signals

    NASA Astrophysics Data System (ADS)

    Shen, Yan-lin; Tu, Ya-qing

    2016-06-01

    Signal processing precision of Coriolis mass flowmeter (CMF) signals affects measurement accuracy of Coriolis mass flowmeters directly. To improve the measurement accuracy of CMFs, a correlation theory-based signal processing method for CMF signals is proposed, which is comprised of the correlation theory-based frequency estimation method and phase difference estimation method. Theoretical analysis shows that the proposed method eliminates the effect of non-integral period sampling signals on frequency and phase difference estimation. The results of simulations and field experiments demonstrate that the proposed method improves the anti-interference performance of frequency and phase difference estimation and has better estimation performance than the adaptive notch filter, discrete Fourier transform and autocorrelation methods in terms of frequency estimation and the data extension-based correlation, Hilbert transform, quadrature delay estimator and discrete Fourier transform methods in terms of phase difference estimation, which contributes to improving the measurement accuracy of Coriolis mass flowmeters.

  2. Immunity-Based Aircraft Fault Detection System

    NASA Technical Reports Server (NTRS)

    Dasgupta, D.; KrishnaKumar, K.; Wong, D.; Berry, M.

    2004-01-01

    In the study reported in this paper, we have developed and applied an Artificial Immune System (AIS) algorithm for aircraft fault detection, as an extension to a previous work on intelligent flight control (IFC). Though the prior studies had established the benefits of IFC, one area of weakness that needed to be strengthened was the control dead band induced by commanding a failed surface. Since the IFC approach uses fault accommodation with no detection, the dead band, although it reduces over time due to learning, is present and causes degradation in handling qualities. If the failure can be identified, this dead band can be further A ed to ensure rapid fault accommodation and better handling qualities. The paper describes the application of an immunity-based approach that can detect a broad spectrum of known and unforeseen failures. The approach incorporates the knowledge of the normal operational behavior of the aircraft from sensory data, and probabilistically generates a set of pattern detectors that can detect any abnormalities (including faults) in the behavior pattern indicating unsafe in-flight operation. We developed a tool called MILD (Multi-level Immune Learning Detection) based on a real-valued negative selection algorithm that can generate a small number of specialized detectors (as signatures of known failure conditions) and a larger set of generalized detectors for unknown (or possible) fault conditions. Once the fault is detected and identified, an adaptive control system would use this detection information to stabilize the aircraft by utilizing available resources (control surfaces). We experimented with data sets collected under normal and various simulated failure conditions using a piloted motion-base simulation facility. The reported results are from a collection of test cases that reflect the performance of the proposed immunity-based fault detection algorithm.

  3. Predictive Classification of Correlated Targets with Application to Detection of Metastatic Cancer using Functional CT Imaging

    PubMed Central

    Wang, Yuan; Hobbs, Brian P.; Hu, Jianhua; Ng, Chaan S.; Do, Kim-Anh

    2015-01-01

    Summary Perfusion computed tomography (CTp) is an emerging functional imaging modality that uses physiological models to quantify characteristics pertaining to the passage of fluid through blood vessels. Perfusion characteristics provide physiological correlates for neovascularization induced by tumor angiogenesis. Thus CTp offers promise as a non-invasive quantitative functional imaging tool for cancer detection, prognostication, and treatment monitoring. In this paper, we develop a Bayesian probabilistic framework for simultaneous supervised classification of multivariate correlated objects using separable covariance. The classification approach is applied to discriminate between regions of liver that contain pathologically verified metastases from normal liver tissue using five perfusion characteristics. The hepatic regions tend to be highly correlated due to common vasculature. We demonstrate that simultaneous Bayesian classification yields dramatic improvements in performance in the presence of strong correlation among intra-subject units, yet remains competitive with classical methods in the presence of weak or no correlation. PMID:25851056

  4. Laser-based detection of chemical contraband

    NASA Astrophysics Data System (ADS)

    Clemmer, Robert G.; Kelly, James F.; Martin, Steven W.; Mong, Gary M.; Sharpe, Steven W.

    1997-02-01

    The goal of our work is tow fold; 1) develop a portable and rapid laser based air sampler for detection of specific chemical contraband and 2) compile a spectral data base in both the near- and mid-IR of sufficiently high quality to be useful for gas phase spectroscopic identification of chemical contraband. During the synthesis or 'cooking' of many illicit chemical substances, relatively high concentrations of volatile solvents, chemical precursors and byproducts are unavoidably released to the atmosphere. In some instances, the final product may have sufficient vapor pressure to be detectable in the surrounding air. The detection of a single high-value effluent or the simultaneous detection of two or more low-value effluents can be used as reliable indicators of a nearby clandestine cooking operation. The designation of high- versus low-value effluent reflects both the commercial availability and legitimate usage of a specific chemical. This paper will describe PNNL's progress and efforts towards the development of a portable laser based air sampling system for the detection of clandestine manufacturing of methamphetamine. Although our current efforts ar focused on methamphetamine, we see no fundamental limitations on detection of other forms of chemical contraband manufacturing. This also includes the synthesis of certain classes of chemical weapons that have recently been deployed by terrorist groups.

  5. Damage detection of metro tunnel structure through transmissibility function and cross correlation analysis using local excitation and measurement

    NASA Astrophysics Data System (ADS)

    Feng, Lei; Yi, Xiaohua; Zhu, Dapeng; Xie, Xiongyao; Wang, Yang

    2015-08-01

    In a modern metropolis, metro rail systems have become a dominant mode for mass transportation. The structural health of a metro tunnel is closely related to public safety. Many vibration-based techniques for detecting and locating structural damage have been developed in the past several decades. However, most damage detection techniques and validation tests are focused on bridge and building structures; very few studies have been reported on tunnel structures. Among these techniques, transmissibility function and cross correlation analysis are two well-known diagnostic approaches. The former operates in frequency domain and the latter in time domain. Both approaches can be applied to detect and locate damage through acceleration data obtained from sensor arrays. Furthermore, the two approaches can directly utilize structural response data without requiring excitation measurement, which offers advantages in field testing on a large structure. In this research, a numerical finite element model of a metro tunnel is built and different types of structural defects are introduced at multiple locations of the tunnel. Transmissibility function and cross correlation analysis are applied to perform structural damage detection and localization, based on simulated structural vibration data. Numerical results demonstrate that the introduced defects can be successfully identified and located. The sensitivity and feasibility of the two approaches have been verified when sufficient distribution of measurement locations is available. Damage detection results of the two different approaches are compared and discussed.

  6. Repeat Sequences and Base Correlations in Human Y Chromosome Palindromes

    NASA Astrophysics Data System (ADS)

    Jin, Neng-zhi; Liu, Zi-xian; Qi, Yan-jiao; Qiu, Wen-yuan

    2009-06-01

    On the basis of information theory and statistical methods, we use mutual information, n-tuple entropy and conditional entropy, combined with biological characteristics, to analyze the long range correlation and short range correlation in human Y chromosome palindromes. The magnitude distribution of the long range correlation which can be reflected by the mutual information is P5>P5a>P5b (P5a and P5b are the sequences that replace solely Alu repeats and all interspersed repeats with random uncorrelated sequences in human Y chromosome palindrome 5, respectively); and the magnitude distribution of the short range correlation which can be reflected by the n-tuple entropy and the conditional entropy is P5>P5a>P5b>random uncorrelated sequence. In other words, when the Alu repeats and all interspersed repeats replace with random uncorrelated sequence, the long range and short range correlation decrease gradually. However, the random uncorrelated sequence has no correlation. This research indicates that more repeat sequences result in stronger correlation between bases in human Y chromosome. The analyses may be helpful to understand the special structures of human Y chromosome palindromes profoundly.

  7. Sella size and jaw bases - Is there a correlation???

    PubMed Central

    Neha; Mogra, Subraya; Shetty, Vorvady Surendra; Shetty, Siddarth

    2016-01-01

    Introduction: Sella turcica is an important cephalometric structure and attempts have been made in the past to correlate its dimensions to the malocclusion. However, no study has so far compared the size of sella to the jaw bases that determine the type of malocclusion. The present study was undertaken to find out any such correlation if it exists. Materials and Methods: Lateral cephalograms of 110 adults consisting of 40 Class I, 40 Class II, and 30 Class III patients were assessed for the measurement of sella length, width, height, and area. The maxillary length, mandibular ramus height, and body length were also measured. The sella dimensions were compared among three malocclusion types by one-way ANOVA. Pearson correlation was calculated between the jaw size and sella dimensions. Furthermore, the ratio of jaw base lengths and sella area were calculated. Results and Conclusion: Mean sella length, width and area were found to be greatest in Class III, followed by Class I and least in Class II though the results were not statistically significant. 3 out of 4 measured dimensions of sella, correlated significantly with mandibular ramus and body length each. However, only one dimension of sella showed significant correlation with maxilla. The mandibular ramus and body length show a nearly constant ratio to sella area (0.83–0.85, 0.64–0.65, respectively) in all the three malocclusions. Thus, mandible has a definite and better correlation to the size of sella turcica. PMID:27041903

  8. Head tracker based on a compact optical correlator

    NASA Astrophysics Data System (ADS)

    Wilkinson, Tim D.; New, Nicholas J.

    2001-08-01

    This paper presents a new application for optical correlation in the form of a head tracking system intended for use in a modern fighter aircraft, where knowing the direction of the pilot's field of view is very important. A video camera, mounted on the pilot's helmet is used to produce a sequence of views of the aircraft cockpit. This view will change from frame to frame as the pilot's head moves and we can use a joint transform optical correlator to track this motion from one frame to the next. In this system, a binary phase joint transform correlator is used to track the frame to frame motion, which can be converted into a change in angle of the pilot's view of the aircraft cockpit. Results from an experimental prototype optical correlation based head tracking system are presented.

  9. Energy Detection Based on Undecimated Discrete Wavelet Transform and Its Application in Magnetic Anomaly Detection

    PubMed Central

    Nie, Xinhua; Pan, Zhongming; Zhang, Dasha; Zhou, Han; Chen, Min; Zhang, Wenna

    2014-01-01

    Magnetic anomaly detection (MAD) is a passive approach for detection of a ferromagnetic target, and its performance is often limited by external noises. In consideration of one major noise source is the fractal noise (or called 1/f noise) with a power spectral density of 1/fa (0correlation. Meanwhile the orthonormal wavelet decomposition can play the role of a Karhunen-Loève-type expansion to the 1/f-type signal by its decorrelation abilities, an effective energy detection method based on undecimated discrete wavelet transform (UDWT) is proposed in this paper. Firstly, the foundations of magnetic anomaly detection and UDWT are introduced in brief, while a possible detection system based on giant magneto-impedance (GMI) magnetic sensor is also given out. Then our proposed energy detection based on UDWT is described in detail, and the probabilities of false alarm and detection for given the detection threshold in theory are presented. It is noticeable that no a priori assumptions regarding the ferromagnetic target or the magnetic noise probability are necessary for our method, and different from the discrete wavelet transform (DWT), the UDWT is shift invariant. Finally, some simulations are performed and the results show that the detection performance of our proposed detector is better than that of the conventional energy detector even utilized in the Gaussian white noise, especially when the spectral parameter α is less than 1.0. In addition, a real-world experiment was done to demonstrate the advantages of the proposed method. PMID:25343484

  10. Brillouin optical correlation domain reflectometry with lock-in detection scheme

    NASA Astrophysics Data System (ADS)

    Yao, Yuguo; Kishi, Masato; Hotate, Kazuo

    2016-07-01

    We propose a Brillouin optical correlation domain reflectometry (BOCDR) technique with a lock-in detection scheme in this paper. By designing a new system using the lock-in detection scheme and amplifying a small spontaneous Brillouin signal with a lock-in amplifier, a Brillouin scattering spectrum with a stable shape is obtained. By further introducing a periodical on/off phase modulation for chopping for lock-in detection, the undesired optical background spectrum is effectively reduced, and a 20 cm section with 7,000 µε strain is clearly measured.

  11. Two-dimensional correlation analysis and waterfall plots for detecting positional fluctuations of spectral changes.

    PubMed

    Ryu, Soo Ryeon; Noda, Isao; Lee, Chang-Hee; Lee, Phil Ho; Hwang, Hyonseok; Jung, Young Mee

    2011-04-01

    In this study, we demonstrate the potentials and pitfalls of using various waterfall plots, such as conventional waterfall plots, two-dimensional (2D) gradient maps, moving window two-dimensional analysis (MW2D), perturbation-correlation moving window two-dimensional analysis (PCMW2D), and moving window principal component analysis two-dimensional correlation analysis (MWPCA2D), in the detection of the existence of band position shifts. Waterfall plots of the simulated spectral datasets are compared with conventional 2D correlation spectra. Different waterfall plots give different features in differentiating the behaviors of frequency shift versus two overlapped bands. Two-dimensional correlation spectra clearly show the very characteristic cluster pattern for both band position shifts and two overlapped bands. The vivid pattern differences are readily detectable in various waterfalls plots. Various types of waterfall plots of temperature-dependent infrared (IR) spectra of ethylene glycol, which does not have the actual band shift but only two overlapped bands, and of Fourier transform infrared (FT-IR) spectra of 2 wt% acetone in a mixed solvent of CHCl(3)/CCl(4) demonstrate that waterfall plots are not able to unambiguously detect the difference between real band shift and two overlapped bands. Thus, the presence or lack of the asynchronous 2D butterfly pattern seems like the most effective diagnostic tool for band shift detection. PMID:21396181

  12. Two-dimensional correlation analysis and waterfall plots for detecting positional fluctuations of spectral changes.

    PubMed

    Ryu, Soo Ryeon; Noda, Isao; Lee, Chang-Hee; Lee, Phil Ho; Hwang, Hyonseok; Jung, Young Mee

    2011-04-01

    In this study, we demonstrate the potentials and pitfalls of using various waterfall plots, such as conventional waterfall plots, two-dimensional (2D) gradient maps, moving window two-dimensional analysis (MW2D), perturbation-correlation moving window two-dimensional analysis (PCMW2D), and moving window principal component analysis two-dimensional correlation analysis (MWPCA2D), in the detection of the existence of band position shifts. Waterfall plots of the simulated spectral datasets are compared with conventional 2D correlation spectra. Different waterfall plots give different features in differentiating the behaviors of frequency shift versus two overlapped bands. Two-dimensional correlation spectra clearly show the very characteristic cluster pattern for both band position shifts and two overlapped bands. The vivid pattern differences are readily detectable in various waterfalls plots. Various types of waterfall plots of temperature-dependent infrared (IR) spectra of ethylene glycol, which does not have the actual band shift but only two overlapped bands, and of Fourier transform infrared (FT-IR) spectra of 2 wt% acetone in a mixed solvent of CHCl(3)/CCl(4) demonstrate that waterfall plots are not able to unambiguously detect the difference between real band shift and two overlapped bands. Thus, the presence or lack of the asynchronous 2D butterfly pattern seems like the most effective diagnostic tool for band shift detection.

  13. Water Detection Based on Sky Reflections

    NASA Technical Reports Server (NTRS)

    Rankin, Arturo L.; Matthies, Larry H.

    2010-01-01

    This software has been designed to detect water bodies that are out in the open on cross-country terrain at mid- to far-range (approximately 20 100 meters), using imagery acquired from a stereo pair of color cameras mounted on a terrestrial, unmanned ground vehicle (UGV). Non-traversable water bodies, such as large puddles, ponds, and lakes, are indirectly detected by detecting reflections of the sky below the horizon in color imagery. The appearance of water bodies in color imagery largely depends on the ratio of light reflected off the water surface to the light coming out of the water body. When a water body is far away, the angle of incidence is large, and the light reflected off the water surface dominates. We have exploited this behavior to detect water bodies out in the open at mid- to far-range. When a water body is detected at far range, a UGV s path planner can begin to look for alternate routes to the goal position sooner, rather than later. As a result, detecting water hazards at far range generally reduces the time required to reach a goal position during autonomous navigation. This software implements a new water detector based on sky reflections that geometrically locates the exact pixel in the sky that is reflecting on a candidate water pixel on the ground, and predicts if the ground pixel is water based on color similarity and local terrain features

  14. Simple road detection based on vanishing point

    NASA Astrophysics Data System (ADS)

    Ziyu, Chen; Zhen, He

    2014-05-01

    Vision-based road detection is one of the key techniques of autonomous driving, intelligent vehicles, and visual navigation. At present, methods based on vanishing point perform best with general roads. However, it is difficult for them to meet the needs of a real-time system due to high time consumption. This paper presents a fast detection method, namely simple road detection, which achieves high efficiency by employing sky segmentation and two new optimization schemes-sample convolution and fast voting. The optimizations are based on lookup tables, sample computing, and computing simplification. The interval sampling in sample convolution makes the proposed method flexible to meet various efficiency and accuracy demands by different sample-step values. Mean filter and vote orientation limitation are also proposed to help improve detection accuracy. Experiments have been conducted with a large number of road images under different environmental conditions, and the results demonstrate that our proposed method is efficient and effective in detecting both structured and unstructured roads.

  15. Detectability of trace gases in the Martian atmosphere using gas correlation filter radiometry

    NASA Astrophysics Data System (ADS)

    Sinclair, J.; Irwin, P. G. J.; Wilson, E.; Calcutt, S.

    2015-10-01

    We present the results of radiative transfer simulations of a gas correlation filter radiometer (GCFR) in the detection of trace species in the Martian atmosphere. We investigated two scenarios: 1) nadir and/or limb sounding from a Mars orbiter in the thermal infrared, 2) solar occultation measurements in the near-infrared from the Martian surface. In both scenarios, a GCFR would allow detection of trace gases at a lower concentration than that detectable by a conventional filter radiometer. In nadir/limb sounding, we find that CH4, SO2, N2O, C2H2 and CH3OH are detectable at concentrations lower than previously-derived upper limits. From solar occultation measurements, we find that CH4, SO2, C2H2, C2H6 are detectable at concentrations lower than previously-derived upper limits but only in low dust conditions.

  16. Multiple target detection in video using quadratic multi-frame correlation filtering

    SciTech Connect

    Kerekes, Ryan A; Kumar, B. V. K. Vijaya

    2008-01-01

    Most integrated target detection and tracking systems employ state-space models to keep track of an explicit number o findividual targets. Recently, a non-state-space framework was developed for enhancing target detection in video by applying probabilistic motion models to the soft information in correlation outputs before thresholding. This framework has been referred to as multi-frame correlation ltering (MFCF), and because it avoids the use of state-space models and the formation of explicit tracks, the framework is well-suited for handling scenes with unknown numbers of targets at unknown positions. In this paper, we propose to use quadratic correlation lters(QCFs)in the MFCF framework for robust target detection. We test our detection algorithm on real and synthe sized single-target and multi-target video sequences. Simulation results show that MFCF can signi cantly reduce (to zero in the best case) the false alarm rates of QCFs at detection rates above 95%in the presence of large amounts of uncorrelated noise. We also show that MFCF is more adept at rejecting those false peaks due to uncorrelated noise rather than those due to clutter and compression noise; consequently, we show that lters used in the framework should be made to favor clutter rejection over noise tolerance.

  17. Tornado Detection Based on Seismic Signal.

    NASA Astrophysics Data System (ADS)

    Tatom, Frank B.; Knupp, Kevin R.; Vitton, Stanley J.

    1995-02-01

    At the present time the only generally accepted method for detecting when a tornado is on the ground is human observation. Based on theoretical considerations combined with eyewitness testimony, there is strong reason to believe that a tornado in contact with the ground transfers a significant amount of energy into the ground. The amount of energy transferred depends upon the intensity of the tornado and the characteristics of the surface. Some portion of this energy takes the form of seismic waves, both body and surface waves. Surface waves (Rayleigh and possibly Love) represent the most likely type of seismic signal to be detected. Based on the existence of such a signal, a seismic tornado detector appears conceptually possible. The major concerns for designing such a detector are range of detection and discrimination between the tornadic signal and other types of surface waves generated by ground transportation equipment, high winds, or other nontornadic sources.

  18. Light Scattering based detection of food pathogens

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The current methods for detecting foodborne pathogens are mostly destructive (i.e., samples need to be pretreated), and require time, personnel, and laboratories for analyses. Optical methods including light scattering based techniques have gained a lot of attention recently due to its their rapid a...

  19. Indirectly detected chemical shift correlation NMR spectroscopy in solids under fast magic angle spinning

    SciTech Connect

    Mao, Kanmi

    2011-01-01

    The development of fast magic angle spinning (MAS) opened up an opportunity for the indirect detection of insensitive low-γ nuclei (e.g., 13C and 15N) via the sensitive high-{gamma} nuclei (e.g., 1H and 19F) in solid-state NMR, with advanced sensitivity and resolution. In this thesis, new methodology utilizing fast MAS is presented, including through-bond indirectly detected heteronuclear correlation (HETCOR) spectroscopy, which is assisted by multiple RF pulse sequences for 1H-1H homonuclear decoupling. Also presented is a simple new strategy for optimization of 1H-1H homonuclear decoupling. As applications, various classes of materials, such as catalytic nanoscale materials, biomolecules, and organic complexes, are studied by combining indirect detection and other one-dimensional (1D) and two-dimensional (2D) NMR techniques. Indirectly detected through-bond HETCOR spectroscopy utilizing refocused INEPT (INEPTR) mixing was developed under fast MAS (Chapter 2). The time performance of this approach in 1H detected 2D 1H{l_brace}13C{r_brace} spectra was significantly improved, by a factor of almost 10, compared to the traditional 13C detected experiments, as demonstrated by measuring naturally abundant organic-inorganic mesoporous hybrid materials. The through-bond scheme was demonstrated as a new analytical tool, which provides complementary structural information in solid-state systems in addition to through-space correlation. To further benefit the sensitivity of the INEPT transfer in rigid solids, the combined rotation and multiple-pulse spectroscopy (CRAMPS) was implemented for homonuclear 1H decoupling under fast MAS (Chapter 3). Several decoupling schemes (PMLG5m$\\bar{x}$, PMLG5mm$\\bar{x}$x and SAM3) were analyzed to maximize the performance of through-bond transfer based

  20. Distinct frontal and amygdala correlates of change detection for facial identity and expression

    PubMed Central

    Achaibou, Amal; Loth, Eva

    2016-01-01

    Recruitment of ‘top-down’ frontal attentional mechanisms is held to support detection of changes in task-relevant stimuli. Fluctuations in intrinsic frontal activity have been shown to impact task performance more generally. Meanwhile, the amygdala has been implicated in ‘bottom-up’ attentional capture by threat. Here, 22 adult human participants took part in a functional magnetic resonance change detection study aimed at investigating the correlates of successful (vs failed) detection of changes in facial identity vs expression. For identity changes, we expected prefrontal recruitment to differentiate ‘hit’ from ‘miss’ trials, in line with previous reports. Meanwhile, we postulated that a different mechanism would support detection of emotionally salient changes. Specifically, elevated amygdala activation was predicted to be associated with successful detection of threat-related changes in expression, over-riding the influence of fluctuations in top-down attention. Our findings revealed that fusiform activity tracked change detection across conditions. Ventrolateral prefrontal cortical activity was uniquely linked to detection of changes in identity not expression, and amygdala activity to detection of changes from neutral to fearful expressions. These results are consistent with distinct mechanisms supporting detection of changes in face identity vs expression, the former potentially reflecting top-down attention, the latter bottom-up attentional capture by stimulus emotional salience. PMID:26245835

  1. Distinct frontal and amygdala correlates of change detection for facial identity and expression.

    PubMed

    Achaibou, Amal; Loth, Eva; Bishop, Sonia J

    2016-02-01

    Recruitment of 'top-down' frontal attentional mechanisms is held to support detection of changes in task-relevant stimuli. Fluctuations in intrinsic frontal activity have been shown to impact task performance more generally. Meanwhile, the amygdala has been implicated in 'bottom-up' attentional capture by threat. Here, 22 adult human participants took part in a functional magnetic resonance change detection study aimed at investigating the correlates of successful (vs failed) detection of changes in facial identity vs expression. For identity changes, we expected prefrontal recruitment to differentiate 'hit' from 'miss' trials, in line with previous reports. Meanwhile, we postulated that a different mechanism would support detection of emotionally salient changes. Specifically, elevated amygdala activation was predicted to be associated with successful detection of threat-related changes in expression, over-riding the influence of fluctuations in top-down attention. Our findings revealed that fusiform activity tracked change detection across conditions. Ventrolateral prefrontal cortical activity was uniquely linked to detection of changes in identity not expression, and amygdala activity to detection of changes from neutral to fearful expressions. These results are consistent with distinct mechanisms supporting detection of changes in face identity vs expression, the former potentially reflecting top-down attention, the latter bottom-up attentional capture by stimulus emotional salience.

  2. On the detectability of trace chemical species in the martian atmosphere using gas correlation filter radiometry

    NASA Astrophysics Data System (ADS)

    Sinclair, J. A.; Irwin, P. G. J.; Calcutt, S. B.; Wilson, E. L.

    2015-11-01

    The martian atmosphere is host to many trace gases including water (H2O) and its isotopologues, methane (CH4) and potentially sulphur dioxide (SO2), nitrous oxide (N2O) and further organic compounds, which would serve as indirect tracers of geological, chemical and biological processes on Mars. With exception of the recent detection of CH4 by Curiosity, previous detections of these species have been unsuccessful or considered tentative due to the low concentrations of these species in the atmosphere (∼10-9 partial pressures), limited spectral resolving power and/or signal-to-noise and the challenge of discriminating between telluric and martian features when observing from the Earth. In this study, we present radiative transfer simulations of an alternative method for detection of trace gas species - the gas correlation radiometry method. Two potential observing scenarios were explored where a gas correlation filter radiometer (GCFR) instrument: (1) performs nadir and/or limb sounding of the martian atmosphere in the thermal infrared (200-2000 cm-1 from an orbiting spacecraft or (2) performs solar occultation measurements in the near-infrared (2000-5000 cm-1) from a lander on the martian surface. In both scenarios, simulations of a narrowband filter radiometer (without gas correlation) were also generated to serve as a comparison. From a spacecraft, we find that a gas correlation filter radiometer, in comparison to a filter radiometer (FR), offers a greater discrimination between temperature and dust, a greater discrimination between H2O and HDO, and would allow detection of N2O and CH3OH at concentrations of ∼10 ppbv and ∼2 ppbv, respectively, which are lower than previously-derived upper limits. However, the lowest retrievable concentration of SO2 (approximately 2 ppbv) is comparable with previous upper limits and CH4 is only detectable at concentrations of approximately 10 ppbv, which is an order of magnitude higher than the concentration recently measured

  3. [Quantitative Detection of Chinese Cabbage Clubroot Based on FTIR Spectroscopy].

    PubMed

    Wang, Wei-ping; Chai, A-li; Shi, Yan-xia; Xie, Xue-wen; Li, Bao-ju

    2015-05-01

    Clubroot, caused by Plasmodiophora brassicae, is considered the most devastating soilborne disease in Brassica crops. It has emerged as a serious disease threatening the cruciferous crop production industry in China. Nowadays, the detection techniques for P. brassicae are laborious, time-consuming and low sensitivity. Rapid and effective detection methods are needed. The objective of this study is to develop a Fourier transform infrared spectrometer (FTIR) technique for detection of P. brassicae effectively and accurately. FTIR and Real-time PCR techniques were applied in quantitative detection of P. brassicae. Chinese cabbages were inoculated with P. brassicae. By analyzing the FTIR spectra of P. brassicae, infected clubroots and healthy roots, three specific bands 1 105, 1 145 and 1 228 cm-1 were selected. According to the correlation between the peak areas at these sensitive bands and Real-time PCR Ct value, quantitative evaluation model of P. brassicae was established based on FTIR y=34. 17 +12. 24x - 9. 81x2 - 6. 05x3, r=0. 98 (p<0. 05). To validate accuracy of the model, 10 clubroot samples were selected randomly from field, and detected by FTIR spectrum model, the results showed that the average error is 1. 60%. This demonstrated that the FTIR technology is an available one for the quantitative detection of P. brassicae in clubroot, and it provides a new method for quantitative and quickly detection of Chinese cabbage clubroot.

  4. Water Detection Based on Object Reflections

    NASA Technical Reports Server (NTRS)

    Rankin, Arturo L.; Matthies, Larry H.

    2012-01-01

    Water bodies are challenging terrain hazards for terrestrial unmanned ground vehicles (UGVs) for several reasons. Traversing through deep water bodies could cause costly damage to the electronics of UGVs. Additionally, a UGV that is either broken down due to water damage or becomes stuck in a water body during an autonomous operation will require rescue, potentially drawing critical resources away from the primary operation and increasing the operation cost. Thus, robust water detection is a critical perception requirement for UGV autonomous navigation. One of the properties useful for detecting still water bodies is that their surface acts as a horizontal mirror at high incidence angles. Still water bodies in wide-open areas can be detected by geometrically locating the exact pixels in the sky that are reflecting on candidate water pixels on the ground, predicting if ground pixels are water based on color similarity to the sky and local terrain features. But in cluttered areas where reflections of objects in the background dominate the appearance of the surface of still water bodies, detection based on sky reflections is of marginal value. Specifically, this software attempts to solve the problem of detecting still water bodies on cross-country terrain in cluttered areas at low cost.

  5. Utilizing digital breast tomosynthesis projection views correlation for microcalcification enhancement for detection purposes

    NASA Astrophysics Data System (ADS)

    Baddar, Wissam J.; Kim, Eun Joon; Kim, Dae Hoe; Ro, Yong Man

    2015-03-01

    This paper presents a novel method for enhancing the contrast of microcalcifications in digital breast tomosynthesis projection views for detection purposes. The proposed method relies on the correlation between the projection views in order to reduce the effect of noise, due to the low-dose exposure, and increase the contrast of the microcalcification particles for microcalcification cluster detection purposes. The method performs a series of multi-shift operations to capture the microcalcification particle movement information and compensate it in order to enhance microcalcification particles contrast. Furthermore, the proposed approach utilizes the projection view correlation in order to reduce the falsely detected regions of interest, and improve the classification of the detected regions into false positives or actual microcalcification clusters. Comparative experiments have been performed to quantitatively measure the contrast enhancement of microcalcification particles and its effect on the MC cluster detection. To that end, the contrast to noise ratio have been calculated and compared with some with previous methods. Furthermore, the free response receiver operating characteristic (FROC) curve have been used to measure the effect of the proposed enhancement on the microcalcification cluster detectability.

  6. Community detection based on network communicability

    NASA Astrophysics Data System (ADS)

    Estrada, Ernesto

    2011-03-01

    We propose a new method for detecting communities based on the concept of communicability between nodes in a complex network. This method, designated as N-ComBa K-means, uses a normalized version of the adjacency matrix to build the communicability matrix and then applies K-means clustering to find the communities in a graph. We analyze how this method performs for some pathological cases found in the analysis of the detection limit of communities and propose some possible solutions on the basis of the analysis of the ratio of local to global densities in graphs. We use four different quality criteria for detecting the best clustering and compare the new approach with the Girvan-Newman algorithm for the analysis of two "classical" networks: karate club and bottlenose dolphins. Finally, we analyze the more challenging case of homogeneous networks with community structure, for which the Girvan-Newman completely fails in detecting any clustering. The N-ComBa K-means approach performs very well in these situations and we applied it to detect the community structure in an international trade network of miscellaneous manufactures of metal having these characteristics. Some final remarks about the general philosophy of community detection are also discussed.

  7. Wafer weak point detection based on aerial images or WLCD

    NASA Astrophysics Data System (ADS)

    Ning, Guoxiang; Philipp, Peter; Litt, Lloyd C.; Ackmann, Paul; Crell, Christian; Chen, Norman

    2015-10-01

    Aerial image measurement is a key technique for model based optical proximity correction (OPC) verification. Actual aerial images obtained by AIMS (aerial image measurement system) or WLCD (wafer level critical dimension) can detect printed wafer weak point structures in advance of wafer exposure and defect inspection. Normally, the potential wafer weak points are determined based on optical rule check (ORC) simulation in advance. However, the correlation to real wafer weak points is often not perfect due to the contribution of mask three dimension (M3D) effects, actual mask errors, and scanner lens effects. If the design weak points can accurately be detected in advance, it will reduce the wafer fab cost and improve cycle time. WLCD or AIMS tools are able to measure the aerial images CD and bossung curve through focus window. However, it is difficult to detect the wafer weak point in advance without defining selection criteria. In this study, wafer weak points sensitive to mask mean-to-nominal values are characterized for a process with very high MEEF (normally more than 4). Aerial image CD uses fixed threshold to detect the wafer weak points. By using WLCD through threshold and focus window, the efficiency of wafer weak point detection is also demonstrated. A novel method using contrast range evaluation is shown in the paper. Use of the slope of aerial images for more accurate detection of the wafer weak points using WLCD is also discussed. The contrast range can also be used to detect the wafer weak points in advance. Further, since the mean to nominal of the reticle contributes to the effective contrast range in a high MEEF area this work shows that control of the mask error is critical for high MEEF layers such as poly, active and metal layers. Wafer process based weak points that cannot be detected by wafer lithography CD or WLCD will be discussed.

  8. Using Cross-Correlation to Detect Upper Mantle Phases beneath Spain and Morocco

    NASA Astrophysics Data System (ADS)

    Bonatto, L.; Schimmel, M.; Gallart, J.; Morales, J.

    2012-04-01

    A novel technique is implemented to search for weak amplitude upper mantle phases that arrive in the P-wave coda. Cross-correlation and stacking techniques are applied in order to detect waveform similarity and eliminate the source influence from the vertical and radial component of records from single stations. A pilot wave is selected from the vertical component, this wavelet contains the P-wave and part of its coda. Phase cross-correlation (PCC) and geometrically normalized cross-correlation (CCGN) are performed between this pilot and the vertical, and the radial component of each event. It is expected that this procedure detects P to s conversions, and reflections at different mantle discontinuities (such as 410-km and 660-km depth discontinuities). Stacking is used to enhance signals which arrive consistently (near receiver conversions and reflections) and attenuate isolated depth phases and also spurious arrivals. Besides the source equalization, PCC and CCGN provide relative travel times with respect to the P phase through their correlation maxima. The data set used in the real data example is obtained from more than 40 stations selected from the first phase of the IberArray seismic network deployment (TopoIberia project) in south Spain and north Morocco. P-wave reflections and P to s conversions at 410-km and 660-km upper mantle discontinuities were detected beneath the studied region. Both discontinuities are on average within the expected depth range from global studies.

  9. Microwave-Based Biosensor for Glucose Detection

    NASA Astrophysics Data System (ADS)

    Salim, N. S. M.; Khalid, K.; Yusof, N. A.

    2010-07-01

    In this project, microwave-based biosensor for glucose detection has been studied. The study is based on the dielectric properties changes at microwave frequency for glucose-enzyme reaction. Glucose interaction with glucose oxidase (GOD) produced gluconic acid and hydrogen peroxide. The reaction of the glucose solutions with an enzyme was carried out in 1:3 of glucose and enzyme respectively. The measurements were done using the Open Ended Coaxial Probe (OECP) coupled with computer controlled software automated network analyzer (ANA) with frequency range from 200MHz to 20GHz at room temperature (25 °C). The differences of enzyme and glucose-enzyme reaction were calculated and plotted. In the microwave interaction with the glucose-enzyme reaction, ionic conduction and dipole molecules was detected at 0.99GHz and 16.44GHz respectively based on changes of dielectric loss factor.

  10. Angular velocity-based structural damage detection

    NASA Astrophysics Data System (ADS)

    Liao, Yizheng; Kiremidjian, Anne S.; Rajagopal, Ram; Loh, Chin-Hsiung

    2016-04-01

    Damage detection is an important application of structural health monitoring. With the recent development of sensing technology, additional information about structures, angular velocity, has become available. In this paper, the angular velocity signals obtained from gyroscopes are modeled as an autoregressive (AR) model. The damage sensitive features (DSFs) are defined as a function of the AR coefficients. It is found that the mean values of the DSF for the damaged and undamaged signals are different. Also, we show that the angular velocity- based AR model has a linear relationship with the acceleration-based AR model. To test the proposed damage detection method, the algorithm has been tested with the experimental data from a recent shake table test where the damage is introduced systemically. The results indicate that the change of DSF means is statistically significant, and the angular velocity-based DSFs are sensitive to damage.

  11. Differential Search Algorithm Based Edge Detection

    NASA Astrophysics Data System (ADS)

    Gunen, M. A.; Civicioglu, P.; Beşdok, E.

    2016-06-01

    In this paper, a new method has been presented for the extraction of edge information by using Differential Search Optimization Algorithm. The proposed method is based on using a new heuristic image thresholding method for edge detection. The success of the proposed method has been examined on fusion of two remote sensed images. The applicability of the proposed method on edge detection and image fusion problems have been analysed in detail and the empirical results exposed that the proposed method is useful for solving the mentioned problems.

  12. GPU Based Software Correlators - Perspectives for VLBI2010

    NASA Technical Reports Server (NTRS)

    Hobiger, Thomas; Kimura, Moritaka; Takefuji, Kazuhiro; Oyama, Tomoaki; Koyama, Yasuhiro; Kondo, Tetsuro; Gotoh, Tadahiro; Amagai, Jun

    2010-01-01

    Caused by historical separation and driven by the requirements of the PC gaming industry, Graphics Processing Units (GPUs) have evolved to massive parallel processing systems which entered the area of non-graphic related applications. Although a single processing core on the GPU is much slower and provides less functionality than its counterpart on the CPU, the huge number of these small processing entities outperforms the classical processors when the application can be parallelized. Thus, in recent years various radio astronomical projects have started to make use of this technology either to realize the correlator on this platform or to establish the post-processing pipeline with GPUs. Therefore, the feasibility of GPUs as a choice for a VLBI correlator is being investigated, including pros and cons of this technology. Additionally, a GPU based software correlator will be reviewed with respect to energy consumption/GFlop/sec and cost/GFlop/sec.

  13. Ultrasound thermal change detection based on steerable filters.

    PubMed

    Sahba, Nima; Tavakoli, Vahid; Nambakhsh, MohamadSaleh

    2008-01-01

    Growing tendency toward utilization of Laser and RF knives has opened a new port for thermal control applications in which ultrasound thermal detection is crucial. Ultrasound velocity is dependent on the thermal properties of the environment. In this paper we focus on tissue temperature detection using multiresolution steerable filter-based motion estimation. The proposed technique was evaluated on simulated and real in-vivo cases during surgical occlusion and reopening of renal segmental artery and demonstrated promising results for observation of internal organ temperature changes using only digital ultrasound systems for diagnosis and therapy. It is proved that being oriented in space and time, steerable filters can achieve more accurate results. Performing thermal detection methods on synthetic phantoms demonstrated good correlation between speckle shifts and the ground truth temperature. For the simulated images average thermal error was 0.68 degrees Celsius with a standard deviation of 0.79.

  14. Detecting repeated seismicity int he Tohoku-Oki Earthquake using Waveform Correlation

    NASA Astrophysics Data System (ADS)

    Carr, D.; Slinkard, M.; Heck, S.; Young, C. J.

    2011-12-01

    The Tohoku-Oki earthquake generated a tremendous number of aftershocks. Fortunately, the high degree of waveform similarity expected within aftershock sequences offers a way to process these events more quickly and robustly than is possible using traditional methods (e.g. STA/LTA detection). Previously we have discussed our Waveform Correlation Detector which detects and clusters similar events during an aftershock sequence. Our system compares incoming waveform data at one station to a continuously updating library of waveforms from known events. Incoming waveform data that correlates above a specified threshold with a library event is marked as a repeating event and assigned to a family of similar waveforms. Using our detector on other large earthquake sequences (Northridge, Kashmir, Wenchuan), we have shown that 47% - 92% of the events in the sequence can be recognized as repeating events. We will demonstrate the results of applying our Waveform Correlation Detector on the Tohuku-Oki aftershocks. We will discuss the number of events detected as repeated events, and the characteristics of the family groups. Results will be analyzed in terms of location along the fault, rate of activity of families in time, and improved efficiency in detection.

  15. Correlates of gender and achievement in introductory algebra based physics

    NASA Astrophysics Data System (ADS)

    Smith, Rachel Clara

    The field of physics is heavily male dominated in America. Thus, half of the population of our country is underrepresented and underserved. The identification of factors that contribute to gender disparity in physics is necessary for educators to address the individual needs of students, and, in particular, the separate and specific needs of female students. In an effort to determine if any correlations could be established or strengthened between sex, gender identity, social network, algebra skill, scientific reasoning ability, and/or student attitude, a study was performed on a group of 82 students in an introductory algebra based physics course. The subjects each filled out a survey at the beginning of the semester of their first semester of algebra based physics. They filled out another survey at the end of that same semester. These surveys included physics content pretests and posttests, as well as questions about the students' habits, attitudes, and social networks. Correlates of posttest score were identified, in order of significance, as pretest score, emphasis on conceptual learning, preference for male friends, number of siblings (negatively correlated), motivation in physics, algebra score, and parents' combined education level. Number of siblings was also found to negatively correlate with, in order of significance, gender identity, preference for male friends, emphasis on conceptual learning, and motivation in physics. Preference for male friends was found to correlate with, in order of significance, emphasis on conceptual learning, gender identity, and algebra score. Also, gender identity was found to correlate with emphasis on conceptual learning, the strongest predictor of posttest score other than pretest score.

  16. Detection of rheumatoid arthritis by evaluation of normalized variances of fluorescence time correlation functions

    NASA Astrophysics Data System (ADS)

    Dziekan, Thomas; Weissbach, Carmen; Voigt, Jan; Ebert, Bernd; MacDonald, Rainer; Bahner, Malte L.; Mahler, Marianne; Schirner, Michael; Berliner, Michael; Berliner, Birgitt; Osel, Jens; Osel, Ilka

    2011-07-01

    Fluorescence imaging using the dye indocyanine green as a contrast agent was investigated in a prospective clinical study for the detection of rheumatoid arthritis. Normalized variances of correlated time series of fluorescence intensities describing the bolus kinetics of the contrast agent in certain regions of interest were analyzed to differentiate healthy from inflamed finger joints. These values are determined using a robust, parameter-free algorithm. We found that the normalized variance of correlation functions improves the differentiation between healthy joints of volunteers and joints with rheumatoid arthritis of patients by about 10% compared to, e.g., ratios of areas under the curves of raw data.

  17. An experimental correlation study between field-target overlap and sensitivity of surface plasmon resonance biosensors based on sandwiched immunoassays

    NASA Astrophysics Data System (ADS)

    Ryu, Yeonsoo; Moon, Seyoung; Oh, Youngjin; Kim, Yonghwi; Kim, Donghyun

    2012-10-01

    In this report, we have studied the effectiveness of field-target overlap to evaluate detection sensitivity of surface plasmon resonance (SPR) biosensors. The investigation used theoretical analysis based on the transfer matrix method, which was experimentally confirmed by thin film-based detection in sandwich and reverse sandwich immunoglobulin G (IgG) assays. Both theoretical and experimental results show that strong correlation exists between the overlap and the sensitivity with the coefficient of correlation higher than 95% in all the cases that we have considered. We have also confirmed the correlation in diffraction grating-based SPR measurement of IgG/anti-IgG interactions. The correlation elucidates the mechanism behind the far-field detection sensitivity of SPR biosensors and can lead to the enhancement of SPR biosensing with molecular scale sensitivity.

  18. Future enhancements to ground-based microburst detection

    NASA Technical Reports Server (NTRS)

    Campbell, Steven D.; Matthews, Michael P.; Dasey, Timothy J.

    1994-01-01

    This set of viewgraphs presents the results of the Cockpit Weather Information (CWI) program at M.I.T. Lincoln Laboratory. The CWI program has been funded through NaSA Langley Research Center by the joint NASA/FAA Integrated Airborne Wind Shear Program for the past four years. During this time, over 120 microburst penetrations by research aircraft have been conducted under Terminal Doppler Weather Radar (TDWR) testbed radar surveillance at Orlando, FL. The results of these in-situ measurements have been compared with ground-based detection methods. Several valuable insights were gained from this research activity. First, it was found that the current TDWR microburst shapes do not permit accurate characterization of microburst hazard in terms of the F factor hazard index, because they are based on loss value rather than shear. Second, it was found that the horizontal component of the F factor can be accurately estimated from shear, provided compensation is made for the dependence of outflow strength on altitude. Third, it was found that a simple continuity assumption for estimating the vertical component of the F factor yielded poor results. However, further research has shown that downdraft strength is correlated with features aloft detected by the TDWR radar scan strategy. The outcome of the CWI program is to move from the loss-based wind shear detection algorithm used in the TDWR to a shear-based detection scheme as proposed in the Integrated Terminal Weather System (ITWS).

  19. Nanomaterials based biosensors for cancer biomarker detection

    NASA Astrophysics Data System (ADS)

    Malhotra, Bansi D.; Kumar, Saurabh; Mouli Pandey, Chandra

    2016-04-01

    Biosensors have enormous potential to contribute to the evolution of new molecular diagnostic techniques for patients suffering with cancerous diseases. A major obstacle preventing faster development of biosensors pertains to the fact that cancer is a highly complex set of diseases. The oncologists currently rely on a few biomarkers and histological characterization of tumors. Some of the signatures include epigenetic and genetic markers, protein profiles, changes in gene expression, and post-translational modifications of proteins. These molecular signatures offer new opportunities for development of biosensors for cancer detection. In this context, conducting paper has recently been found to play an important role towards the fabrication of a biosensor for cancer biomarker detection. In this paper we will focus on results of some of the recent studies obtained in our laboratories relating to fabrication and application of nanomaterial modified paper based biosensors for cancer biomarker detection.

  20. Spectral methods and cluster structure in correlation-based networks

    NASA Astrophysics Data System (ADS)

    Heimo, Tapio; Tibély, Gergely; Saramäki, Jari; Kaski, Kimmo; Kertész, János

    2008-10-01

    We investigate how in complex systems the eigenpairs of the matrices derived from the correlations of multichannel observations reflect the cluster structure of the underlying networks. For this we use daily return data from the NYSE and focus specifically on the spectral properties of weight W=|-δ and diffusion matrices D=W/sj-δ, where C is the correlation matrix and si=∑jW the strength of node j. The eigenvalues (and corresponding eigenvectors) of the weight matrix are ranked in descending order. As in the earlier observations, the first eigenvector stands for a measure of the market correlations. Its components are, to first approximation, equal to the strengths of the nodes and there is a second order, roughly linear, correction. The high ranking eigenvectors, excluding the highest ranking one, are usually assigned to market sectors and industrial branches. Our study shows that both for weight and diffusion matrices the eigenpair analysis is not capable of easily deducing the cluster structure of the network without a priori knowledge. In addition we have studied the clustering of stocks using the asset graph approach with and without spectrum based noise filtering. It turns out that asset graphs are quite insensitive to noise and there is no sharp percolation transition as a function of the ratio of bonds included, thus no natural threshold value for that ratio seems to exist. We suggest that these observations can be of use for other correlation based networks as well.

  1. Optimized PCR-based detection of mycoplasma.

    PubMed

    Dobrovolny, Paige L; Bess, Dan

    2011-06-20

    The maintenance of contamination-free cell lines is essential to cell-based research. Among the biggest contaminant concerns are mycoplasma contamination. Although mycoplasma do not usually kill contaminated cells, they are difficult to detect and can cause a variety of effects on cultured cells, including altered metabolism, slowed proliferation and chromosomal aberrations. In short, mycoplasma contamination compromises the value of those cell lines in providing accurate data for life science research. The sources of mycoplasma contamination in the laboratory are very challenging to completely control. As certain mycoplasma species are found on human skin, they can be introduced through poor aseptic technique. Additionally, they can come from contaminated supplements such as fetal bovine serum, and most importantly from other contaminated cell cultures. Once mycoplasma contaminates a culture, it can quickly spread to contaminate other areas of the lab. Strict adherence to good laboratory practices such as good aseptic technique are key, and routine testing for mycoplasma is highly recommended for successful control of mycoplasma contamination. PCR-based detection of mycoplasma has become a very popular method for routine cell line maintenance. PCR-based detection methods are highly sensitive and can provide rapid results, which allows researchers to respond quickly to isolate and eliminate contamination once it is detected in comparison to the time required using microbiological techniques. The LookOut Mycoplasma PCR Detection Kit is highly sensitive, with a detection limit of only 2 genomes per μl. Taking advantage of the highly specific JumpStart Taq DNA Polymerase and a proprietary primer design, false positives are greatly reduced. The convenient 8-tube format, strips pre-coated with dNTPs, and associated primers helps increase the throughput to meet the needs of customers with larger collections of cell lines. Given the extreme sensitivity of the kit, great

  2. Hydrocarbon microseepage mapping using signature based target detection techniques

    NASA Astrophysics Data System (ADS)

    Soydan, Hilal; Koz, Alper; Şebnem Düzgün, H.; Aydin Alatan, A.

    2015-10-01

    In this paper, we compare the conventional methods in hydrocarbon seepage anomalies with the signature based detection algorithms. The Crosta technique [1] is selected as a basement in the experimental comparisons for the conventional approach. The Crosta technique utilizes the characteristic bands of the searched target for principal component transformation in order to determine the components characterizing the target in interest. Desired Target Detection and Classification Algorithm (DTDCA), Spectral Matched Filter (SMF), and Normalized Correlation (NC) are employed for signature based target detection. Signature based target detection algorithms are applied to the whole spectrum benefiting from the information stored in all spectral bands. The selected methods are applied to a multispectral Advanced SpaceBorne Thermal Emission and Radiometer (ASTER) image of the study region, with an atmospheric correction prior to the realization of the algorithms. ASTER provides multispectral bands covering visible, short wave, and thermal infrared region, which serves as a useful tool for the interpretation of the areas with hydrocarbon anomalies. The exploration area is selected as Gemrik Anticline which is located in South East Anatolia, Adıyaman, Bozova Oil Field, where microseeps can be observed with almost no vegetation cover. The spectral signatures collected with Analytical Spectral Devices Inc. (ASD) spectrometer from the reference valley [2] have been utilized as an input to the signature based detection algorithms. The experiments have indicated that DTDCA and MF outperforms the Crosta technique by locating the microseepage patterns along the mitigation pathways with a better contrast. On the other hand, NC has not been able to map the searched target with a visible distinction. It is concluded that the signature based algorithms can be more effective than the conventional methods for the detection of microseepage induced anomalies.

  3. Shearlet-based detection of flame fronts

    NASA Astrophysics Data System (ADS)

    Reisenhofer, Rafael; Kiefer, Johannes; King, Emily J.

    2016-03-01

    Identifying and characterizing flame fronts is the most common task in the computer-assisted analysis of data obtained from imaging techniques such as planar laser-induced fluorescence (PLIF), laser Rayleigh scattering (LRS), or particle imaging velocimetry (PIV). We present Complex Shearlet-Based Ridge and Edge Measure (CoShREM), a novel edge and ridge (line) detection algorithm based on complex-valued wavelet-like analyzing functions—so-called complex shearlets—displaying several traits useful for the extraction of flame fronts. In addition to providing a unified approach to the detection of edges and ridges, our method inherently yields estimates of local tangent orientations and local curvatures. To examine the applicability for high-frequency recordings of combustion processes, the algorithm is applied to mock images distorted with varying degrees of noise and real-world PLIF images of both OH and CH radicals. Furthermore, we compare the performance of the newly proposed complex shearlet-based measure to well-established edge and ridge detection techniques such as the Canny edge detector, another shearlet-based edge detector, and the phase congruency measure.

  4. Water Detection Based on Color Variation

    NASA Technical Reports Server (NTRS)

    Rankin, Arturo L.

    2012-01-01

    This software has been designed to detect water bodies that are out in the open on cross-country terrain at close range (out to 30 meters), using imagery acquired from a stereo pair of color cameras mounted on a terrestrial, unmanned ground vehicle (UGV). This detector exploits the fact that the color variation across water bodies is generally larger and more uniform than that of other naturally occurring types of terrain, such as soil and vegetation. Non-traversable water bodies, such as large puddles, ponds, and lakes, are detected based on color variation, image intensity variance, image intensity gradient, size, and shape. At ranges beyond 20 meters, water bodies out in the open can be indirectly detected by detecting reflections of the sky below the horizon in color imagery. But at closer range, the color coming out of a water body dominates sky reflections, and the water cue from sky reflections is of marginal use. Since there may be times during UGV autonomous navigation when a water body does not come into a perception system s field of view until it is at close range, the ability to detect water bodies at close range is critical. Factors that influence the perceived color of a water body at close range are the amount and type of sediment in the water, the water s depth, and the angle of incidence to the water body. Developing a single model of the mixture ratio of light reflected off the water surface (to the camera) to light coming out of the water body (to the camera) for all water bodies would be fairly difficult. Instead, this software detects close water bodies based on local terrain features and the natural, uniform change in color that occurs across the surface from the leading edge to the trailing edge.

  5. Wavelet based detection of manatee vocalizations

    NASA Astrophysics Data System (ADS)

    Gur, Berke M.; Niezrecki, Christopher

    2005-04-01

    The West Indian manatee (Trichechus manatus latirostris) has become endangered partly because of watercraft collisions in Florida's coastal waterways. Several boater warning systems, based upon manatee vocalizations, have been proposed to reduce the number of collisions. Three detection methods based on the Fourier transform (threshold, harmonic content and autocorrelation methods) were previously suggested and tested. In the last decade, the wavelet transform has emerged as an alternative to the Fourier transform and has been successfully applied in various fields of science and engineering including the acoustic detection of dolphin vocalizations. As of yet, no prior research has been conducted in analyzing manatee vocalizations using the wavelet transform. Within this study, the wavelet transform is used as an alternative to the Fourier transform in detecting manatee vocalizations. The wavelet coefficients are analyzed and tested against a specified criterion to determine the existence of a manatee call. The performance of the method presented is tested on the same data previously used in the prior studies, and the results are compared. Preliminary results indicate that using the wavelet transform as a signal processing technique to detect manatee vocalizations shows great promise.

  6. Pollution detection by digital correlation of multispectral, stero-image pairs.

    NASA Technical Reports Server (NTRS)

    Krause, F. R.; Betz, H. T.; Lysobey, D. H.

    1971-01-01

    Remote detection of air pollution circulation patterns is proposed to eventually predict the accumulation of hazardous surface concentrations in time for preventive emission control operations. Earth observations from space platforms will contain information on the height, mean velocity and lateral mixing scales of inversion layers and pollution plumes. Although this information is often not visible on photographs, it could conceivably be retrieved through a digital cross-correlation of multispectral stereo image pairs. Laboratory and field test results are used to illustrate the detection of non-visual inversion layers, the reduction of dominant signal interference, and the spectroscopic identification of combustion products.

  7. Detecting gravitational waves from inspiraling binaries with a network of detectors: Coherent strategies for correlated detectors

    SciTech Connect

    Tagoshi, Hideyuki; Mukhopadhyay, Himan; Dhurandhar, Sanjeev; Sago, Norichika; Takahashi, Hirotaka; Kanda, Nobuyuki

    2007-04-15

    We discuss the coherent search strategy to detect gravitational waves from inspiraling compact binaries by a network of correlated laser interferometric detectors. From the maximum likelihood ratio statistic, we obtain a coherent statistic which is slightly different from and generally better than what we obtained in our previous work. In the special case when the cross spectrum of two detectors normalized by the power spectrum density is constant, the new statistic agrees with the old one. The quantitative difference of the detection probability for a given false alarm rate is also evaluated in a simple case.

  8. Correlation Study Of Diffenrential Skin Temperatures (DST) For Ovulation Detection Using Infra-Red Thermography

    NASA Astrophysics Data System (ADS)

    Rao, K. H. S.; Shah, A. v.; Ruedi, B.

    1982-11-01

    The importance of ovulation time detection in the Practice of Natural Birth Control (NBC) as a contraceptive tool, and for natural/artificial insemination among women having the problem of in-fertility, is well known. The simple Basal Body Temperature (BBT) method of ovulation detection is so far unreliable. A newly proposed Differential Skin Temperature (DST) method may help minimize disturbing physiological effects and improve reliability. This paper explains preliminary results of a detailed correlative study on the DST method, using Infra-Red Thermography (IRT) imaging, and computer analysis techniques. Results obtained with five healthy, normally menstruating women volunteers will be given.

  9. Correlation between self-reported and clinically based diagnoses of bruxism in temporomandibular disorders patients.

    PubMed

    Paesani, D A; Lobbezoo, F; Gelos, C; Guarda-Nardini, L; Ahlberg, J; Manfredini, D

    2013-11-01

    The present investigation was performed in a population of patients with temporomandibular disorders (TMD), and it was designed to assess the correlation between self-reported questionnaire-based bruxism diagnosis and a diagnosis based on history taking plus clinical examination. One-hundred-fifty-nine patients with TMD underwent an assessment including a questionnaire investigating five bruxism-related items (i.e. sleep grinding, sleep grinding referral by bed partner, sleep clenching, awake clenching, awake grinding) and an interview (i.e. oral history taking with specific focus on bruxism habits) plus a clinical examination to evaluate bruxism signs and symptoms. The correlation between findings of the questionnaire, viz., patients' report, and findings of the interview/oral history taking plus clinical examination, viz., clinicians' diagnosis, was assessed by means of φ coefficient. The highest correlations were achieved for the sleep grinding referral item (φ = 0·932) and for the awake clenching item (φ = 0·811), whilst lower correlation values were found for the other items (φ values ranging from 0·363 to 0·641). The percentage of disagreement between the two diagnostic approaches ranged between 1·8% and 18·2%. Within the limits of the present investigation, it can be suggested that a strong positive correlation between a self-reported and a clinically based approach to bruxism diagnosis can be achieved as for awake clenching, whilst lower levels of correlation were detected for sleep-time activities.

  10. Unified Picture for Magnetic Correlations in Iron-Based Superconductors

    SciTech Connect

    Yin, W.G.; Lee, E.-C.; Ku, W.

    2010-09-02

    The varying metallic antiferromagnetic correlations observed in iron-based superconductors are unified in a model consisting of both itinerant electrons and localized spins. The decisive factor is found to be the sensitive competition between the superexchange antiferromagnetism and the orbital-degenerate double-exchange ferromagnetism. Our results reveal the crucial role of Hund's rule coupling for the strongly correlated nature of the system and suggest that the iron-based superconductors are closer kin to manganites than cuprates in terms of their diverse magnetism and incoherent normal-state electron transport. This unified picture would be instrumental for exploring other exotic properties and the mechanism of superconductivity in this new class of superconductors.

  11. Patterns of trading profiles at the Nordic Stock Exchange. A correlation-based approach.

    NASA Astrophysics Data System (ADS)

    Musciotto, Federico; Marotta, Luca; Miccichè, Salvatore; Piilo, Jyrki; Mantegna, Rosario N.

    2016-07-01

    We investigate the trading behavior of Finnish individual investors trading the stocks selected to compute the OMXH25 index in 2003 by tracking the individual daily investment decisions. We verify that the set of investors is a highly heterogeneous system under many aspects. We introduce a correlation based method that is able to detect a hierarchical structure of the trading profiles of heterogeneous individual investors. We verify that the detected hierarchical structure is highly overlapping with the cluster structure obtained with the approach of statistically validated networks when an appropriate threshold of the hierarchical trees is used. We also show that the combination of the correlation based method and of the statistically validated method provides a way to expand the information about the clusters of investors with similar trading profiles in a robust and reliable way.

  12. [Progress in Application of Two-Dimensional Correlation Spectroscopy for Detection of Food Quality].

    PubMed

    Yang, Ren-jie; Yang, Yan-rong; Liu, Hai-xue; Dong, Gui-mei; Du, Yan-hong; Shan, Hui-yong; Zhang, Wei-yu

    2015-08-01

    In recent years, the food safety and quality has always been a serious issue. Therefore, it is urgent to develop a rapid and widely available method to determine the quality of food. Due to high spectral resolution, good spectral selectivity and good ability of spectrogram analysis, the technology of two-dimensional (2D) correlation spectroscopy is an effective method for solving three major problems encountered by the conventional one-dimensional (1D) spectrum: low selectivity of the spectra, difficulty in extracting the information of the spectral feature and difficulty in spectrogram analysis. Therefore, 2D correlation spectroscopy, which is suited to distinguish similar samples hardly distinguished by the conventional 1D spectroscopy, has been successfully applied in many complex biological systems. The developmental process, the experimental way to obtain spectrum, the fundamental mathematical principle and the properties of 2D correlation spectroscopy were introduced in this paper. At the same time, it is pointed out that the origin of weak characteristic bands of substance can be verified in terms of the positive or negative corss peaks in synchronous 2D correlation spectrum combined with the existence or inexistence of corss peaks in asynchronous 2D correlation spectrum. The application of 2D near-infrared, mid-infrared, fluorescence, and raman correlation spectroscopy in the detection of food quality and adulteration, concentrated specifically on diary product, wine, oil, meat, honey, and rice were reviewed. Finally, the limitations and future development prospects were pointed out.

  13. [Progress in Application of Two-Dimensional Correlation Spectroscopy for Detection of Food Quality].

    PubMed

    Yang, Ren-jie; Yang, Yan-rong; Liu, Hai-xue; Dong, Gui-mei; Du, Yan-hong; Shan, Hui-yong; Zhang, Wei-yu

    2015-08-01

    In recent years, the food safety and quality has always been a serious issue. Therefore, it is urgent to develop a rapid and widely available method to determine the quality of food. Due to high spectral resolution, good spectral selectivity and good ability of spectrogram analysis, the technology of two-dimensional (2D) correlation spectroscopy is an effective method for solving three major problems encountered by the conventional one-dimensional (1D) spectrum: low selectivity of the spectra, difficulty in extracting the information of the spectral feature and difficulty in spectrogram analysis. Therefore, 2D correlation spectroscopy, which is suited to distinguish similar samples hardly distinguished by the conventional 1D spectroscopy, has been successfully applied in many complex biological systems. The developmental process, the experimental way to obtain spectrum, the fundamental mathematical principle and the properties of 2D correlation spectroscopy were introduced in this paper. At the same time, it is pointed out that the origin of weak characteristic bands of substance can be verified in terms of the positive or negative corss peaks in synchronous 2D correlation spectrum combined with the existence or inexistence of corss peaks in asynchronous 2D correlation spectrum. The application of 2D near-infrared, mid-infrared, fluorescence, and raman correlation spectroscopy in the detection of food quality and adulteration, concentrated specifically on diary product, wine, oil, meat, honey, and rice were reviewed. Finally, the limitations and future development prospects were pointed out. PMID:26672279

  14. Capacity limitations and the detection of correlations: comment on Kareev (2000).

    PubMed

    Juslin, Peter; Olsson, Henrik

    2005-01-01

    Y. Kareev (2000) argued that the limited capacity of working memory may be an adaptive advantage for the early detection of useful correlations. His analysis indeed suggests that the optimal sample size is close to G. A. Miller's (1956) "magical number 7 +/- 2." The authors point out logical and statistical limitations of Y. Kareev's (2000) analysis, including that it neglects that the adaptive value is not determined by the hit rate but by the posterior probability of hit and that only signal trials are considered. The authors' analysis demonstrates that when these limitations are corrected for, the alleged benefit for small samples does not occur, and larger samples imply considerable improvement in the detection of correlations. PMID:15631597

  15. General SIC measurement-based entanglement detection

    NASA Astrophysics Data System (ADS)

    Chen, Bin; Li, Tao; Fei, Shao-Ming

    2015-06-01

    We study the quantum separability problem by using general symmetric informationally complete measurements and present separability criteria for both -dimensional bipartite and multipartite systems. The criterion for bipartite quantum states is effective in detecting several well-known classes of quantum states. For isotropic states, it becomes both necessary and sufficient. Furthermore, our criteria can be experimentally implemented, and the criterion for two-qudit states requires less local measurements than the one based on mutually unbiased measurements.

  16. Raman LIDAR Detection of Cloud Base

    NASA Technical Reports Server (NTRS)

    Demoz, Belay; Starr, David; Whiteman, David; Evans, Keith; Hlavka, Dennis; Peravali, Ravindra

    1999-01-01

    Advantages introduced by Raman lidar systems for cloud base determination during precipitating periods are explored using two case studies of light rain and virga conditions. A combination of the Raman lidar derived profiles of water vapor mixing ratio and aerosol scattering ratio, together with the Raman scattered signals from liquid drops, can minimize or even eliminate some of the problems associated with cloud boundary detection using elastic backscatter lidars.

  17. Biotoxin Detection Using Cell-Based Sensors

    PubMed Central

    Banerjee, Pratik; Kintzios, Spyridon; Prabhakarpandian, Balabhaskar

    2013-01-01

    Cell-based biosensors (CBBs) utilize the principles of cell-based assays (CBAs) by employing living cells for detection of different analytes from environment, food, clinical, or other sources. For toxin detection, CBBs are emerging as unique alternatives to other analytical methods. The main advantage of using CBBs for probing biotoxins and toxic agents is that CBBs respond to the toxic exposures in the manner related to actual physiologic responses of the vulnerable subjects. The results obtained from CBBs are based on the toxin-cell interactions, and therefore, reveal functional information (such as mode of action, toxic potency, bioavailability, target tissue or organ, etc.) about the toxin. CBBs incorporate both prokaryotic (bacteria) and eukaryotic (yeast, invertebrate and vertebrate) cells. To create CBB devices, living cells are directly integrated onto the biosensor platform. The sensors report the cellular responses upon exposures to toxins and the resulting cellular signals are transduced by secondary transducers generating optical or electrical signals outputs followed by appropriate read-outs. Examples of the layout and operation of cellular biosensors for detection of selected biotoxins are summarized. PMID:24335754

  18. Correlation detection strategies in microbial data sets vary widely in sensitivity and precision.

    PubMed

    Weiss, Sophie; Van Treuren, Will; Lozupone, Catherine; Faust, Karoline; Friedman, Jonathan; Deng, Ye; Xia, Li Charlie; Xu, Zhenjiang Zech; Ursell, Luke; Alm, Eric J; Birmingham, Amanda; Cram, Jacob A; Fuhrman, Jed A; Raes, Jeroen; Sun, Fengzhu; Zhou, Jizhong; Knight, Rob

    2016-07-01

    Disruption of healthy microbial communities has been linked to numerous diseases, yet microbial interactions are little understood. This is due in part to the large number of bacteria, and the much larger number of interactions (easily in the millions), making experimental investigation very difficult at best and necessitating the nascent field of computational exploration through microbial correlation networks. We benchmark the performance of eight correlation techniques on simulated and real data in response to challenges specific to microbiome studies: fractional sampling of ribosomal RNA sequences, uneven sampling depths, rare microbes and a high proportion of zero counts. Also tested is the ability to distinguish signals from noise, and detect a range of ecological and time-series relationships. Finally, we provide specific recommendations for correlation technique usage. Although some methods perform better than others, there is still considerable need for improvement in current techniques. PMID:26905627

  19. Semiautomated tremor detection using a combined cross-correlation and neural network approach

    NASA Astrophysics Data System (ADS)

    Horstmann, T.; Harrington, R. M.; Cochran, E. S.

    2013-09-01

    Despite observations of tectonic tremor in many locations around the globe, the emergent phase arrivals, low-amplitude waveforms, and variable event durations make automatic detection a nontrivial task. In this study, we employ a new method to identify tremor in large data sets using a semiautomated technique. The method first reduces the data volume with an envelope cross-correlation technique, followed by a Self-Organizing Map (SOM) algorithm to identify and classify event types. The method detects tremor in an automated fashion after calibrating for a specific data set, hence we refer to it as being "semiautomated". We apply the semiautomated detection algorithm to a newly acquired data set of waveforms from a temporary deployment of 13 seismometers near Cholame, California, from May 2010 to July 2011. We manually identify tremor events in a 3 week long test data set and compare to the SOM output and find a detection accuracy of 79.5%. Detection accuracy improves with increasing signal-to-noise ratios and number of available stations. We find detection completeness of 96% for tremor events with signal-to-noise ratios above 3 and optimal results when data from at least 10 stations are available. We compare the SOM algorithm to the envelope correlation method of Wech and Creager and find the SOM performs significantly better, at least for the data set examined here. Using the SOM algorithm, we detect 2606 tremor events with a cumulative signal duration of nearly 55 h during the 13 month deployment. Overall, the SOM algorithm is shown to be a flexible new method that utilizes characteristics of the waveforms to identify tremor from noise or other seismic signals.

  20. Semiautomated tremor detection using a combined cross-correlation and neural network approach

    USGS Publications Warehouse

    Horstmann, Tobias; Harrington, Rebecca M.; Cochran, Elizabeth S.

    2013-01-01

    Despite observations of tectonic tremor in many locations around the globe, the emergent phase arrivals, low‒amplitude waveforms, and variable event durations make automatic detection a nontrivial task. In this study, we employ a new method to identify tremor in large data sets using a semiautomated technique. The method first reduces the data volume with an envelope cross‒correlation technique, followed by a Self‒Organizing Map (SOM) algorithm to identify and classify event types. The method detects tremor in an automated fashion after calibrating for a specific data set, hence we refer to it as being “semiautomated”. We apply the semiautomated detection algorithm to a newly acquired data set of waveforms from a temporary deployment of 13 seismometers near Cholame, California, from May 2010 to July 2011. We manually identify tremor events in a 3 week long test data set and compare to the SOM output and find a detection accuracy of 79.5%. Detection accuracy improves with increasing signal‒to‒noise ratios and number of available stations. We find detection completeness of 96% for tremor events with signal‒to‒noise ratios above 3 and optimal results when data from at least 10 stations are available. We compare the SOM algorithm to the envelope correlation method of Wech and Creager and find the SOM performs significantly better, at least for the data set examined here. Using the SOM algorithm, we detect 2606 tremor events with a cumulative signal duration of nearly 55 h during the 13 month deployment. Overall, the SOM algorithm is shown to be a flexible new method that utilizes characteristics of the waveforms to identify tremor from noise or other seismic signals.

  1. Fast dual graph-based hotspot detection

    NASA Astrophysics Data System (ADS)

    Kahng, Andrew B.; Park, Chul-Hong; Xu, Xu

    2006-10-01

    As advanced technologies in wafer manufacturing push patterning processes toward lower-k I subwavelength printing, lithography for mass production potentially suffers from decreased patterning fidelity. This results in generation of many hotspots, which are actual device patterns with relatively large CD and image errors with respect to on-wafer targets. Hotspots can be formed under a variety of conditions such as the original design being unfriendly to the RET that is applied, unanticipated pattern combinations in rule-based OPC, or inaccuracies in model-based OPC. When these hotspots fall on locations that are critical to the electrical performance of a device, device performance and parametric yield can be significantly degraded. Previous rule-based hotspot detection methods suffer from long runtimes for complicated patterns. Also, the model generation process that captures process variation within simulation-based approaches brings significant overheads in terms of validation, measurement and parameter calibration. In this paper, we first describe a novel detection algorithm for hotspots induced by lithographic uncertainty. Our goal is to rapidly detect all lithographic hotspots without significant accuracy degradation. In other words, we propose a filtering method: as long as there are no "false negatives", i.e., we successfully have a superset of actual hotspots, then our method can dramatically reduce the layout area for golden hotspot analysis. The first step of our hotspot detection algorithm is to build a layout graph which reflects pattern-related CD variation. Given a layout L, the layout graph G = (V, E c union E p) consists of nodes V, corner edges E c and proximity edges E p. A face in the layout graph includes several close features and the edges between them. Edge weight can be calculated from a traditional 2-D model or a lookup table. We then apply a three-level hotspot detection: (1) edge-level detection finds the hotspot caused by two close

  2. The impact of angular separation on the performance of biplane correlation imaging for lung nodule detection

    NASA Astrophysics Data System (ADS)

    Nasab, Nariman Majdi; Samei, Ehsan

    2006-03-01

    In this paper, we evaluate the performance of biplane correlation imaging (BCI) using a set of off-angle projections acquired from an anthropomorphic chest phantom. BCI reduces the effect of anatomical noise, which would otherwise impact the detection subtle lesions in planar images. BCI also minimizes the number of false positives (FPs) when used in conjunction with computer aided diagnosis (CAD) applied to a set of coronal chest x-ray projections by eliminating non-correlated nodule candidates. In BCI, two digital images of the chest are acquired within a short time interval from two slightly different posterior projections. The image data are then incorporated into the CAD algorithm in which nodules are detected by examining the geometrical correlation of the detected signals in the two views, thus largely "canceling" the impact of anatomical noise. Seventy-one low exposure posterior projections were acquired of an anthropomorphic chest phantom containing tissue equivalent lesions with small angular separations (0.32 degree) over a range of 20 degrees, [-10°, +10°], along the vertical axis. The data were analyzed to determine the accuracy of the technique as a function of angular separation. The results indicated that the best performance was obtained when the angular separation of the projection pair was greater than 6 degrees. Within the range of optimum angular separation, the number of FPs per image, FPpI, was ~1.1 with average sensitivity around 75% (supported by a grant from the NIH R01CA109074).

  3. Wenchuan Event Detection And Localization Using Waveform Correlation Coupled With Double Difference

    NASA Astrophysics Data System (ADS)

    Slinkard, M.; Heck, S.; Schaff, D. P.; Young, C. J.; Richards, P. G.

    2014-12-01

    The well-studied Wenchuan aftershock sequence triggered by the May 12, 2008, Ms 8.0, mainshock offers an ideal test case for evaluating the effectiveness of using waveform correlation coupled with double difference relocation to detect and locate events in a large aftershock sequence. We use Sandia's SeisCorr detector to process 3 months of data recorded by permanent IRIS and temporary ASCENT stations using templates from events listed in a global catalog to find similar events in the raw data stream. Then we take the detections and relocate them using the double difference method. We explore both the performance that can be expected with using just a small number of stations, and, the benefits of reprocessing a well-studied sequence such as this one using waveform correlation to find even more events. We benchmark our results against previously published results describing relocations of regional catalog data. Before starting this project, we had examples where with just a few stations at far-regional distances, waveform correlation combined with double difference did and impressive job of detection and location events with precision at the few hundred and even tens of meters level.

  4. Correlation of DNA fragment sizes within loci in the presence of non-detectable alleles.

    PubMed

    Chakraborty, R; Li, Z

    1995-01-01

    At present most forensic databases of DNA profiling of individuals consist of DNA fragment sizes measured from Southern blot restriction fragment length polymorphism (RFLP) analysis. Statistical studies of these databases have revealed that, when fragment sizes are measured from RFLP analysis, some of the single-band patterns of individuals may actually be due to heterozygosity of alleles in which fragment size resulting from one allele remains undetected. In this work, we evaluate the effect of such allelic non-detectability on correlation of fragment sizes within individuals at a locus, and its impact on the inference of independence of fragment sizes within loci. We show that when non-detectable alleles are present in a population at a locus, positive correlations of fragment sizes are expected, which increase with the proportion of non-detectable alleles at the locus. Therefore, a non-zero positive correlation is not a proof of allelic dependence within individuals. Applications of this theory to the current forensic RFLP databases within the US show that there is virtually no evidence of significant allelic dependence within any of the loci. Therefore, the assumption that DNA fragment sizes within loci are independent is valid, and hence, the population genetic principles of computing DNA profile frequencies by multiplying binned frequencies of fragment sizes are most likely to be appropriate for forensic applications of DNA typing data.

  5. Application of interferential correlation of spectrum to the detection of atmospheric pollutants

    NASA Technical Reports Server (NTRS)

    Fortunato, G.

    1979-01-01

    The general correlation principles for spectra and spectra derivatives are studied by using the Fourier transform of the spectral distribution of energy from a source illuminating a double beam interferometer with transverse splitting by dividing luminance. In this correlation technique, the use of such an interferometer has the advantage of greater luminosity as compared with a slit spectrometer. However, the correlation example indicates that it is necessary to adapt the correlator to the particular case considered, in order to obtain the best gain in the signal to noise ratio. In the case of sulfur dioxide detection, a very simple mounting which could be used in some interesting industrial applications was developed. This mounting can be used each time that the substance to be analyzed has a quasi-periodic absorption spectrum: in particular this is often the case with absorption spectra of gases, and a mounting identical to the one described for sulfur dioxide proved to be effective in the detection of nitrogen oxides.

  6. A New Intrusion Detection Method Based on Antibody Concentration

    NASA Astrophysics Data System (ADS)

    Zeng, Jie; Li, Tao; Li, Guiyang; Li, Haibo

    Antibody is one kind of protein that fights against the harmful antigen in human immune system. In modern medical examination, the health status of a human body can be diagnosed by detecting the intrusion intensity of a specific antigen and the concentration indicator of corresponding antibody from human body’s serum. In this paper, inspired by the principle of antigen-antibody reactions, we present a New Intrusion Detection Method Based on Antibody Concentration (NIDMBAC) to reduce false alarm rate without affecting detection rate. In our proposed method, the basic definitions of self, nonself, antigen and detector in the intrusion detection domain are given. Then, according to the antigen intrusion intensity, the change of antibody number is recorded from the process of clone proliferation for detectors based on the antigen classified recognition. Finally, building upon the above works, a probabilistic calculation method for the intrusion alarm production, which is based on the correlation between the antigen intrusion intensity and the antibody concen-tration, is proposed. Our theoretical analysis and experimental results show that our proposed method has a better performance than traditional methods.

  7. Global Contrast Based Salient Region Detection.

    PubMed

    Cheng, Ming-Ming; Mitra, Niloy J; Huang, Xiaolei; Torr, Philip H S; Hu, Shi-Min

    2015-03-01

    Automatic estimation of salient object regions across images, without any prior assumption or knowledge of the contents of the corresponding scenes, enhances many computer vision and computer graphics applications. We introduce a regional contrast based salient object detection algorithm, which simultaneously evaluates global contrast differences and spatial weighted coherence scores. The proposed algorithm is simple, efficient, naturally multi-scale, and produces full-resolution, high-quality saliency maps. These saliency maps are further used to initialize a novel iterative version of GrabCut, namely SaliencyCut, for high quality unsupervised salient object segmentation. We extensively evaluated our algorithm using traditional salient object detection datasets, as well as a more challenging Internet image dataset. Our experimental results demonstrate that our algorithm consistently outperforms 15 existing salient object detection and segmentation methods, yielding higher precision and better recall rates. We also show that our algorithm can be used to efficiently extract salient object masks from Internet images, enabling effective sketch-based image retrieval (SBIR) via simple shape comparisons. Despite such noisy internet images, where the saliency regions are ambiguous, our saliency guided image retrieval achieves a superior retrieval rate compared with state-of-the-art SBIR methods, and additionally provides important target object region information. PMID:26353262

  8. Bacteriophage based probes for pathogen detection.

    PubMed

    Singh, Amit; Arutyunov, Denis; Szymanski, Christine M; Evoy, Stephane

    2012-08-01

    Rapid and specific detection of pathogenic bacteria is important for the proper treatment, containment and prevention of human, animal and plant diseases. Identifying unique biological probes to achieve a high degree of specificity and minimize false positives has therefore garnered much interest in recent years. Bacteriophages are obligate intracellular parasites that subvert bacterial cell resources for their own multiplication and production of disseminative new virions, which repeat the cycle by binding specifically to the host surface receptors and injecting genetic material into the bacterial cells. The precision of host recognition in phages is imparted by the receptor binding proteins (RBPs) that are often located in the tail-spike or tail fiber protein assemblies of the virions. Phage host recognition specificity has been traditionally exploited for bacterial typing using laborious and time consuming bacterial growth assays. At the same time this feature makes phage virions or RBPs an excellent choice for the development of probes capable of selectively capturing bacteria on solid surfaces with subsequent quick and automatic detection of the binding event. This review focuses on the description of pathogen detection approaches based on immobilized phage virions as well as pure recombinant RBPs. Specific advantages of RBP-based molecular probes are also discussed.

  9. Ultrasensitive detection of genetically modified plants by fluorescence cross-correlation spectroscopy

    NASA Astrophysics Data System (ADS)

    Li, Junfeng; Xing, Da; Chen, Tongsheng; Liu, Jinfeng

    2006-09-01

    In this study, a novel method for the direct detection of GMP without amplified by the general method of PCR is firstly presented and proved by experiments. In our method, fluorescence correlation spectroscopy, cleaving nucleic acid by restriction endonuclease and two nucleic acid probe hybridization techniques are combined to distinguish the caulifiower mosaic virus (CaMV) 35S promoter and determine whether samples contain genetically modified components. The detection principle is as follows: firstly two restriction endonucleases FOKI and BsrDlare used to cleave the genomic DNA and the 169bp fragments of CaMV 35S promoter are retrieved; secondly, two nucleic acid probes labeled by Rhodamine Green and y5 dyes respectively hybridize with cleaved 169bp fragments of CaMV 35S promoter; thirdly, the hybridization products simultaneously with two dye-labeled probes are detected by fluorescence cross-correlation spectroscopy and GMP is distinguished. As the detection and analysis by FCS can be performed at the level of single molecule, there is no need for any type of amplification. Genetically modified tobaccos are measured by this method. The results indicate this method can detect CaMV 35S promoter of GMP exactly and the sensitivity can be down to 3.47X10 -10M. Because no any type of amplification is involved, this method can avoid the non-specffic amplification and false-positive problems of PCR, Due to its high-sensitivity, simplicity, reliability and little need for sample amounts, this method promises to be a highly effective detection method for GMP.

  10. Cellular Phone Face Recognition System Based on Optical Phase Correlation

    NASA Astrophysics Data System (ADS)

    Watanabe, Eriko; Ishikawa, Sayuri; Ohta, Maiko; Kodate, Kashiko

    We propose a high security facial recognition system using a cellular phone on the mobile network. This system is composed of a face recognition engine based on optical phase correlation which uses phase information with emphasis on a Fourier domain, a control sever and the cellular phone with a compact camera for taking pictures, as a portable terminal. Compared with various correlation methods, our face recognition engine revealed the most accurate EER of less than 1%. By using the JAVA interface on this system, we implemented the stable system taking pictures, providing functions to prevent spoofing while transferring images. This recognition system was tested on 300 women students and the results proved this system effective.

  11. Quantum Image Encryption Algorithm Based on Image Correlation Decomposition

    NASA Astrophysics Data System (ADS)

    Hua, Tianxiang; Chen, Jiamin; Pei, Dongju; Zhang, Wenquan; Zhou, Nanrun

    2015-02-01

    A novel quantum gray-level image encryption and decryption algorithm based on image correlation decomposition is proposed. The correlation among image pixels is established by utilizing the superposition and measurement principle of quantum states. And a whole quantum image is divided into a series of sub-images. These sub-images are stored into a complete binary tree array constructed previously and then randomly performed by one of the operations of quantum random-phase gate, quantum revolving gate and Hadamard transform. The encrypted image can be obtained by superimposing the resulting sub-images with the superposition principle of quantum states. For the encryption algorithm, the keys are the parameters of random phase gate, rotation angle, binary sequence and orthonormal basis states. The security and the computational complexity of the proposed algorithm are analyzed. The proposed encryption algorithm can resist brute force attack due to its very large key space and has lower computational complexity than its classical counterparts.

  12. Correlation dynamics and enhanced signals for the identification of serial biomolecules and DNA bases

    NASA Astrophysics Data System (ADS)

    Ahmed, Towfiq; Haraldsen, Jason T.; Rehr, John J.; Di Ventra, Massimiliano; Schuller, Ivan; Balatsky, Alexander V.

    2014-03-01

    Nanopore-based sequencing has demonstrated a significant potential for the development of fast, accurate, and cost-efficient fingerprinting techniques for next generation molecular detection and sequencing. We propose a specific multilayered graphene-based nanopore device architecture for the recognition of single biomolecules. Molecular detection and analysis can be accomplished through the detection of transverse currents as the molecule or DNA base translocates through the nanopore. To increase the overall signal-to-noise ratio and the accuracy, we implement a new ‘multi-point cross-correlation’ technique for identification of DNA bases or other molecules on the single molecular level. We demonstrate that the cross-correlations between each nanopore will greatly enhance the transverse current signal for each molecule. We implement first-principles transport calculations for DNA bases surveyed across a multilayered graphene nanopore system to illustrate the advantages of the proposed geometry. A time-series analysis of the cross-correlation functions illustrates the potential of this method for enhancing the signal-to-noise ratio. This work constitutes a significant step forward in facilitating fingerprinting of single biomolecules using solid state technology.

  13. Reset Tree-Based Optical Fault Detection

    PubMed Central

    Lee, Dong-Geon; Choi, Dooho; Seo, Jungtaek; Kim, Howon

    2013-01-01

    In this paper, we present a new reset tree-based scheme to protect cryptographic hardware against optical fault injection attacks. As one of the most powerful invasive attacks on cryptographic hardware, optical fault attacks cause semiconductors to misbehave by injecting high-energy light into a decapped integrated circuit. The contaminated result from the affected chip is then used to reveal secret information, such as a key, from the cryptographic hardware. Since the advent of such attacks, various countermeasures have been proposed. Although most of these countermeasures are strong, there is still the possibility of attack. In this paper, we present a novel optical fault detection scheme that utilizes the buffers on a circuit's reset signal tree as a fault detection sensor. To evaluate our proposal, we model radiation-induced currents into circuit components and perform a SPICE simulation. The proposed scheme is expected to be used as a supplemental security tool. PMID:23698267

  14. The Correlation Function of Galaxy Clusters and Detection of Baryon Acoustic Oscillations

    NASA Astrophysics Data System (ADS)

    Hong, T.; Han, J. L.; Wen, Z. L.; Sun, L.; Zhan, H.

    2012-04-01

    We calculate the correlation function of 13,904 galaxy clusters of z <= 0.4 selected from the cluster catalog of Wen et al. The correlation function can be fitted with a power-law model ξ(r) = (r/R 0)-γ on the scales of 10 h -1 Mpc <= r <= 50 h -1 Mpc, with a larger correlation length of R 0 = 18.84 ± 0.27 h -1 Mpc for clusters with a richness of R >= 15 and a smaller length of R 0 = 16.15 ± 0.13 h -1 Mpc for clusters with a richness of R >= 5. The power-law index of γ = 2.1 is found to be almost the same for all cluster subsamples. A pronounced baryon acoustic oscillations (BAO) peak is detected at r ~ 110 h -1 Mpc with a significance of ~1.9σ. By analyzing the correlation function in the range of 20 h -1 Mpc <= r <= 200 h -1 Mpc, we find that the constraints on distance parameters are Dv (zm = 0.276) = 1077 ± 55(1σ) Mpc and h = 0.73 ± 0.039(1σ), which are consistent with the cosmology derived from Wilkinson Microwave Anisotropy Probe (WMAP) seven-year data. However, the BAO signal from the cluster sample is stronger than expected and leads to a rather low matter density Ω m h 2 = 0.093 ± 0.0077(1σ), which deviates from the WMAP7 result by more than 3σ. The correlation function of the GMBCG cluster sample is also calculated and our detection of the BAO feature is confirmed.

  15. THE CORRELATION FUNCTION OF GALAXY CLUSTERS AND DETECTION OF BARYON ACOUSTIC OSCILLATIONS

    SciTech Connect

    Hong, T.; Han, J. L.; Wen, Z. L.; Sun, L.; Zhan, H.

    2012-04-10

    We calculate the correlation function of 13,904 galaxy clusters of z {<=} 0.4 selected from the cluster catalog of Wen et al. The correlation function can be fitted with a power-law model {xi}(r) = (r/R{sub 0}){sup -{gamma}} on the scales of 10 h{sup -1} Mpc {<=} r {<=} 50 h{sup -1} Mpc, with a larger correlation length of R{sub 0} = 18.84 {+-} 0.27 h{sup -1} Mpc for clusters with a richness of R {>=} 15 and a smaller length of R{sub 0} = 16.15 {+-} 0.13 h{sup -1} Mpc for clusters with a richness of R {>=} 5. The power-law index of {gamma} = 2.1 is found to be almost the same for all cluster subsamples. A pronounced baryon acoustic oscillations (BAO) peak is detected at r {approx} 110 h{sup -1} Mpc with a significance of {approx}1.9{sigma}. By analyzing the correlation function in the range of 20 h{sup -1} Mpc {<=} r {<=} 200 h{sup -1} Mpc, we find that the constraints on distance parameters are D{sub v} (z{sub m} = 0.276) = 1077 {+-} 55(1{sigma}) Mpc and h = 0.73 {+-} 0.039(1{sigma}), which are consistent with the cosmology derived from Wilkinson Microwave Anisotropy Probe (WMAP) seven-year data. However, the BAO signal from the cluster sample is stronger than expected and leads to a rather low matter density {Omega}{sub m} h{sup 2} = 0.093 {+-} 0.0077(1{sigma}), which deviates from the WMAP7 result by more than 3{sigma}. The correlation function of the GMBCG cluster sample is also calculated and our detection of the BAO feature is confirmed.

  16. PCR-Free Detection of Genetically Modified Organisms Using Magnetic Capture Technology and Fluorescence Cross-Correlation Spectroscopy

    PubMed Central

    Zhou, Xiaoming; Xing, Da; Tang, Yonghong; Chen, Wei R.

    2009-01-01

    The safety of genetically modified organisms (GMOs) has attracted much attention recently. Polymerase chain reaction (PCR) amplification is a common method used in the identification of GMOs. However, a major disadvantage of PCR is the potential amplification of non-target DNA, causing false-positive identification. Thus, there remains a need for a simple, reliable and ultrasensitive method to identify and quantify GMO in crops. This report is to introduce a magnetic bead-based PCR-free method for rapid detection of GMOs using dual-color fluorescence cross-correlation spectroscopy (FCCS). The cauliflower mosaic virus 35S (CaMV35S) promoter commonly used in transgenic products was targeted. CaMV35S target was captured by a biotin-labeled nucleic acid probe and then purified using streptavidin-coated magnetic beads through biotin-streptavidin linkage. The purified target DNA fragment was hybridized with two nucleic acid probes labeled respectively by Rhodamine Green and Cy5 dyes. Finally, FCCS was used to detect and quantify the target DNA fragment through simultaneously detecting the fluorescence emissions from the two dyes. In our study, GMOs in genetically engineered soybeans and tomatoes were detected, using the magnetic bead-based PCR-free FCCS method. A detection limit of 50 pM GMOs target was achieved and PCR-free detection of GMOs from 5 µg genomic DNA with magnetic capture technology was accomplished. Also, the accuracy of GMO determination by the FCCS method is verified by spectrophotometry at 260 nm using PCR amplified target DNA fragment from GM tomato. The new method is rapid and effective as demonstrated in our experiments and can be easily extended to high-throughput and automatic screening format. We believe that the new magnetic bead-assisted FCCS detection technique will be a useful tool for PCR-free GMOs identification and other specific nucleic acids. PMID:19956680

  17. PCR-free detection of genetically modified organisms using magnetic capture technology and fluorescence cross-correlation spectroscopy.

    PubMed

    Zhou, Xiaoming; Xing, Da; Tang, Yonghong; Chen, Wei R

    2009-11-26

    The safety of genetically modified organisms (GMOs) has attracted much attention recently. Polymerase chain reaction (PCR) amplification is a common method used in the identification of GMOs. However, a major disadvantage of PCR is the potential amplification of non-target DNA, causing false-positive identification. Thus, there remains a need for a simple, reliable and ultrasensitive method to identify and quantify GMO in crops. This report is to introduce a magnetic bead-based PCR-free method for rapid detection of GMOs using dual-color fluorescence cross-correlation spectroscopy (FCCS). The cauliflower mosaic virus 35S (CaMV35S) promoter commonly used in transgenic products was targeted. CaMV35S target was captured by a biotin-labeled nucleic acid probe and then purified using streptavidin-coated magnetic beads through biotin-streptavidin linkage. The purified target DNA fragment was hybridized with two nucleic acid probes labeled respectively by Rhodamine Green and Cy5 dyes. Finally, FCCS was used to detect and quantify the target DNA fragment through simultaneously detecting the fluorescence emissions from the two dyes. In our study, GMOs in genetically engineered soybeans and tomatoes were detected, using the magnetic bead-based PCR-free FCCS method. A detection limit of 50 pM GMOs target was achieved and PCR-free detection of GMOs from 5 microg genomic DNA with magnetic capture technology was accomplished. Also, the accuracy of GMO determination by the FCCS method is verified by spectrophotometry at 260 nm using PCR amplified target DNA fragment from GM tomato. The new method is rapid and effective as demonstrated in our experiments and can be easily extended to high-throughput and automatic screening format. We believe that the new magnetic bead-assisted FCCS detection technique will be a useful tool for PCR-free GMOs identification and other specific nucleic acids.

  18. Enhanced detectability of small objects in correlated clutter using an improved 2-D adaptive lattice algorithm.

    PubMed

    Ffrench, P A; Zeidler, J H; Ku, W H

    1997-01-01

    Two-dimensional (2-D) adaptive filtering is a technique that can be applied to many image processing applications. This paper will focus on the development of an improved 2-D adaptive lattice algorithm (2-D AL) and its application to the removal of correlated clutter to enhance the detectability of small objects in images. The two improvements proposed here are increased flexibility in the calculation of the reflection coefficients and a 2-D method to update the correlations used in the 2-D AL algorithm. The 2-D AL algorithm is shown to predict correlated clutter in image data and the resulting filter is compared with an ideal Wiener-Hopf filter. The results of the clutter removal will be compared to previously published ones for a 2-D least mean square (LMS) algorithm. 2-D AL is better able to predict spatially varying clutter than the 2-D LMS algorithm, since it converges faster to new image properties. Examples of these improvements are shown for a spatially varying 2-D sinusoid in white noise and simulated clouds. The 2-D LMS and 2-D AL algorithms are also shown to enhance a mammogram image for the detection of small microcalcifications and stellate lesions.

  19. Phase transition transistors based on strongly-correlated materials

    NASA Astrophysics Data System (ADS)

    Nakano, Masaki

    2013-03-01

    The field-effect transistor (FET) provides electrical switching functions through linear control of the number of charges at a channel surface by external voltage. Controlling electronic phases of condensed matters in a FET geometry has long been a central issue of physical science. In particular, FET based on a strongly correlated material, namely ``Mott transistor,'' has attracted considerable interest, because it potentially provides gigantic and diverse electronic responses due to a strong interplay between charge, spin, orbital and lattice. We have investigated electric-field effects on such materials aiming at novel physical phenomena and electronic functions originating from strong correlation effects. Here we demonstrate electrical switching of bulk state of matter over the first-order metal-insulator transition. We fabricated FETs based on VO2 with use of a recently developed electric-double-layer transistor technique, and found that the electrostatically induced carriers at a channel surface drive all preexisting localized carriers of 1022 cm-3 even inside a bulk to motion, leading to bulk carrier delocalization beyond the electrostatic screening length. This non-local switching of bulk phases is achieved with just around 1 V, and moreover, a novel non-volatile memory like character emerges in a voltage-sweep measurement. These observations are apparently distinct from those of conventional FETs based on band insulators, capturing the essential feature of collective interactions in strongly correlated materials. This work was done in collaboration with K. Shibuya, D. Okuyama, T. Hatano, S. Ono, M. Kawasaki, Y. Iwasa, and Y. Tokura. This work was supported by the Japan Society for the Promotion of Science (JSAP) through its ``Funding Program for World-Leading Innovative R&D on Science and Technology (FIRST Program).''

  20. The correlation-based law of effect1

    PubMed Central

    Baum, William M.

    1973-01-01

    It is commonly understood that the interactions between an organism and its environment constitute a feedback system. This implies that instrumental behavior should be viewed as a continuous exchange between the organism and the environment. It follows that orderly relations between behavior and environment should emerge at the level of aggregate flow in time, rather than momentary events. These notions require a simple, but fundamental, change in the law of effect: from a law based on contiguity of events to a law based on correlation between events. Much recent research and argument favors such a change. If the correlation-based law of effect is accepted, it favors measures and units of analysis that transcend momentary events, extending through time. One can measure all consequences on a common scale, called value. One can define a unit of analysis called the behavioral situation, which circumscribes a set of values. These concepts allow redefinition of reinforcement and punishment, and clarification of their relation to discriminative stimuli. PMID:16811687

  1. CORRELATION ANALYSIS OF HYPERSPECTRAL IMAGERY FOR MULTISPECTRAL WAVELENGTH SELECTION FOR DETECTION OF DEFECTS ON APPLES

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Visible/near-infrared reflectance spectra extracted from hyperspectral images of apples were used to determine wavelength pairs that can be used to distinguish defect regions from normal regions on the apple surface. The optimal wavelengths were selected based on correlation analysis between the wa...

  2. Mouse V1 population correlates of visual detection rely on heterogeneity within neuronal response patterns

    PubMed Central

    Montijn, Jorrit S; Goltstein, Pieter M; Pennartz, Cyriel MA

    2015-01-01

    Previous studies have demonstrated the importance of the primary sensory cortex for the detection, discrimination, and awareness of visual stimuli, but it is unknown how neuronal populations in this area process detected and undetected stimuli differently. Critical differences may reside in the mean strength of responses to visual stimuli, as reflected in bulk signals detectable in functional magnetic resonance imaging, electro-encephalogram, or magnetoencephalography studies, or may be more subtly composed of differentiated activity of individual sensory neurons. Quantifying single-cell Ca2+ responses to visual stimuli recorded with in vivo two-photon imaging, we found that visual detection correlates more strongly with population response heterogeneity rather than overall response strength. Moreover, neuronal populations showed consistencies in activation patterns across temporally spaced trials in association with hit responses, but not during nondetections. Contrary to models relying on temporally stable networks or bulk signaling, these results suggest that detection depends on transient differentiation in neuronal activity within cortical populations. DOI: http://dx.doi.org/10.7554/eLife.10163.001 PMID:26646184

  3. Preliminary study of digital image correlation based optical coherence elastography

    NASA Astrophysics Data System (ADS)

    Sun, Cuiru; Vuong, Barry; Wen, Xiao-Yan; Yang, Victor

    2013-06-01

    Optical coherence elastography (OCE) provides deformation or material properties mapping of soft tissue, which is important for morphological and pathological studies of the tissue. An OCE technique is developed based on digital image correlation. System calibration and measurement error evaluation are performed. The displacement measurement of 0.6 μm to over 100 μm was obtained through a phantom experiment. The capability of this OCE technique for differentiation of stiffness was evaluated by imaging a two-components phantom. OCE imaging of an aneurysm sample shows promising results for characterization of composites of aneurismal wall in the future.

  4. Correlation-based smoothing model for optical polishing.

    PubMed

    Shu, Yong; Kim, Dae Wook; Martin, Hubert M; Burge, James H

    2013-11-18

    A generalized model is developed to quantitatively describe the smoothing effects from different polishing tools used for optical surfaces. The smoothing effect naturally corrects mid-to-high spatial frequency errors that have features small compared to the size of the polishing lap. The original parametric smoothing model provided a convenient way to compare smoothing efficiency of different polishing tools for the case of sinusoidal surface irregularity, providing the ratio of surface improvement via smoothing to the bulk material removal. A new correlation-based smoothing model expands the capability to quantify smoothing using general surface data with complex irregularity. For this case, we define smoothing as a band-limited correlated component of the change in the surface and original surface. Various concepts and methods, such as correlation screening, have been developed and verified to manipulate the data for the calculation of smoothing factor. Data from two actual polishing runs from the Giant Magellan Telescope off-axis segment and the Large Synoptic Survey Telescope monolithic primary-tertiary mirror were processed, and a quantitative evaluation for the smoothing efficiency of a large pitch lap and a conformal lap with polishing pads is provided.

  5. Dramatyping: a generic algorithm for detecting reasonable temporal correlations between drug administration and lab value alterations

    PubMed Central

    2016-01-01

    According to the World Health Organization, one of the criteria for the standardized assessment of case causality in adverse drug reactions is the temporal relationship between the intake of a drug and the occurrence of a reaction or a laboratory test abnormality. This article presents and describes an algorithm for the detection of a reasonable temporal correlation between the administration of a drug and the alteration of a laboratory value course. The algorithm is designed to process normalized lab values and is therefore universally applicable. It has a sensitivity of 0.932 for the detection of lab value courses that show changes in temporal correlation with the administration of a drug and it has a specificity of 0.967 for the detection of lab value courses that show no changes. Therefore, the algorithm is appropriate to screen the data of electronic health records and to support human experts in revealing adverse drug reactions. A reference implementation in Python programming language is available. PMID:27042396

  6. Dramatyping: a generic algorithm for detecting reasonable temporal correlations between drug administration and lab value alterations.

    PubMed

    Newe, Axel

    2016-01-01

    According to the World Health Organization, one of the criteria for the standardized assessment of case causality in adverse drug reactions is the temporal relationship between the intake of a drug and the occurrence of a reaction or a laboratory test abnormality. This article presents and describes an algorithm for the detection of a reasonable temporal correlation between the administration of a drug and the alteration of a laboratory value course. The algorithm is designed to process normalized lab values and is therefore universally applicable. It has a sensitivity of 0.932 for the detection of lab value courses that show changes in temporal correlation with the administration of a drug and it has a specificity of 0.967 for the detection of lab value courses that show no changes. Therefore, the algorithm is appropriate to screen the data of electronic health records and to support human experts in revealing adverse drug reactions. A reference implementation in Python programming language is available. PMID:27042396

  7. Dramatyping: a generic algorithm for detecting reasonable temporal correlations between drug administration and lab value alterations.

    PubMed

    Newe, Axel

    2016-01-01

    According to the World Health Organization, one of the criteria for the standardized assessment of case causality in adverse drug reactions is the temporal relationship between the intake of a drug and the occurrence of a reaction or a laboratory test abnormality. This article presents and describes an algorithm for the detection of a reasonable temporal correlation between the administration of a drug and the alteration of a laboratory value course. The algorithm is designed to process normalized lab values and is therefore universally applicable. It has a sensitivity of 0.932 for the detection of lab value courses that show changes in temporal correlation with the administration of a drug and it has a specificity of 0.967 for the detection of lab value courses that show no changes. Therefore, the algorithm is appropriate to screen the data of electronic health records and to support human experts in revealing adverse drug reactions. A reference implementation in Python programming language is available.

  8. Waveguide-Based Biosensors for Pathogen Detection

    PubMed Central

    Mukundan, Harshini; Anderson, Aaron S.; Grace, W. Kevin; Grace, Karen M.; Hartman, Nile; Martinez, Jennifer S.; Swanson, Basil I.

    2009-01-01

    Optical phenomena such as fluorescence, phosphorescence, polarization, interference and non-linearity have been extensively used for biosensing applications. Optical waveguides (both planar and fiber-optic) are comprised of a material with high permittivity/high refractive index surrounded on all sides by materials with lower refractive indices, such as a substrate and the media to be sensed. This arrangement allows coupled light to propagate through the high refractive index waveguide by total internal reflection and generates an electromagnetic wave—the evanescent field—whose amplitude decreases exponentially as the distance from the surface increases. Excitation of fluorophores within the evanescent wave allows for sensitive detection while minimizing background fluorescence from complex, “dirty” biological samples. In this review, we will describe the basic principles, advantages and disadvantages of planar optical waveguide-based biodetection technologies. This discussion will include already commercialized technologies (e.g., Corning’s EPIC® Ô, SRU Biosystems’ BIND™, Zeptosense®, etc.) and new technologies that are under research and development. We will also review differing assay approaches for the detection of various biomolecules, as well as the thin-film coatings that are often required for waveguide functionalization and effective detection. Finally, we will discuss reverse-symmetry waveguides, resonant waveguide grating sensors and metal-clad leaky waveguides as alternative signal transducers in optical biosensing. PMID:22346727

  9. Overlapping Community Detection based on Network Decomposition.

    PubMed

    Ding, Zhuanlian; Zhang, Xingyi; Sun, Dengdi; Luo, Bin

    2016-01-01

    Community detection in complex network has become a vital step to understand the structure and dynamics of networks in various fields. However, traditional node clustering and relatively new proposed link clustering methods have inherent drawbacks to discover overlapping communities. Node clustering is inadequate to capture the pervasive overlaps, while link clustering is often criticized due to the high computational cost and ambiguous definition of communities. So, overlapping community detection is still a formidable challenge. In this work, we propose a new overlapping community detection algorithm based on network decomposition, called NDOCD. Specifically, NDOCD iteratively splits the network by removing all links in derived link communities, which are identified by utilizing node clustering technique. The network decomposition contributes to reducing the computation time and noise link elimination conduces to improving the quality of obtained communities. Besides, we employ node clustering technique rather than link similarity measure to discover link communities, thus NDOCD avoids an ambiguous definition of community and becomes less time-consuming. We test our approach on both synthetic and real-world networks. Results demonstrate the superior performance of our approach both in computation time and accuracy compared to state-of-the-art algorithms. PMID:27066904

  10. Overlapping Community Detection based on Network Decomposition

    NASA Astrophysics Data System (ADS)

    Ding, Zhuanlian; Zhang, Xingyi; Sun, Dengdi; Luo, Bin

    2016-04-01

    Community detection in complex network has become a vital step to understand the structure and dynamics of networks in various fields. However, traditional node clustering and relatively new proposed link clustering methods have inherent drawbacks to discover overlapping communities. Node clustering is inadequate to capture the pervasive overlaps, while link clustering is often criticized due to the high computational cost and ambiguous definition of communities. So, overlapping community detection is still a formidable challenge. In this work, we propose a new overlapping community detection algorithm based on network decomposition, called NDOCD. Specifically, NDOCD iteratively splits the network by removing all links in derived link communities, which are identified by utilizing node clustering technique. The network decomposition contributes to reducing the computation time and noise link elimination conduces to improving the quality of obtained communities. Besides, we employ node clustering technique rather than link similarity measure to discover link communities, thus NDOCD avoids an ambiguous definition of community and becomes less time-consuming. We test our approach on both synthetic and real-world networks. Results demonstrate the superior performance of our approach both in computation time and accuracy compared to state-of-the-art algorithms.

  11. Scene change detection based on multimodal integration

    NASA Astrophysics Data System (ADS)

    Zhu, Yingying; Zhou, Dongru

    2003-09-01

    Scene change detection is an essential step to automatic and content-based video indexing, retrieval and browsing. In this paper, a robust scene change detection and classification approach is presented, which analyzes audio, visual and textual sources and accounts for their inter-relations and coincidence to semantically identify and classify video scenes. Audio analysis focuses on the segmentation of audio stream into four types of semantic data such as silence, speech, music and environmental sound. Further processing on speech segments aims at locating speaker changes. Video analysis partitions visual stream into shots. Text analysis can provide a supplemental source of clues for scene classification and indexing information. We integrate the video and audio analysis results to identify video scenes and use the text information detected by the video OCR technology or derived from transcripts available to refine scene classification. Results from single source segmentation are in some cases suboptimal. By combining visual, aural features adn the accessorial text information, the scence extraction accuracy is enhanced, and more semantic segmentations are developed. Experimental results are proven to rather promising.

  12. Overlapping Community Detection based on Network Decomposition

    PubMed Central

    Ding, Zhuanlian; Zhang, Xingyi; Sun, Dengdi; Luo, Bin

    2016-01-01

    Community detection in complex network has become a vital step to understand the structure and dynamics of networks in various fields. However, traditional node clustering and relatively new proposed link clustering methods have inherent drawbacks to discover overlapping communities. Node clustering is inadequate to capture the pervasive overlaps, while link clustering is often criticized due to the high computational cost and ambiguous definition of communities. So, overlapping community detection is still a formidable challenge. In this work, we propose a new overlapping community detection algorithm based on network decomposition, called NDOCD. Specifically, NDOCD iteratively splits the network by removing all links in derived link communities, which are identified by utilizing node clustering technique. The network decomposition contributes to reducing the computation time and noise link elimination conduces to improving the quality of obtained communities. Besides, we employ node clustering technique rather than link similarity measure to discover link communities, thus NDOCD avoids an ambiguous definition of community and becomes less time-consuming. We test our approach on both synthetic and real-world networks. Results demonstrate the superior performance of our approach both in computation time and accuracy compared to state-of-the-art algorithms. PMID:27066904

  13. Real-time quantitative PCR detection of WT1 gene expression in children with AML: prognostic significance, correlation with disease status and residual disease detection by flow cytometry.

    PubMed

    Trka, J; Kalinová, M; Hrusák, O; Zuna, J; Krejcí, O; Madzo, J; Sedlácek, P; Vávra, V; Michalová, K; Jarosová, M; Starý, J

    2002-07-01

    The clinical significance of WT1 gene expression at diagnosis and during therapy of AML has not yet been resolved. We analysed WT1 expression at presentation in an unselected group of 47 childhood AML patients using real-time quantitative reverse-transcription PCR. We also showed that within the first 30 h following aspiration RQ-RT-PCR results were not influenced by transportation time. We observed lower levels of WT1 transcript in AML M5 (P = 0.0015); no association was found between expression levels and sex, initial leukocyte count and karyotype-based prognostic groups. There was significant correlation between very low WT1 expression at presentation and excellent outcome (EFS P = 0.0014). Combined analysis of WT1 levels, three-colour flow cytometry residual disease detection and the course of the disease in 222 samples from 28 children with AML showed remarkable correlation. Fourteen patients expressed high WT1 levels at presentation. In eight of them, who suffered relapse or did not reach complete remission, dynamics of WT1 levels clearly correlated with the disease status and residual disease by flow cytometry. We conclude that very low WT1 levels at presentation represent a good prognostic factor and that RQ-RT-PCR-based analysis of WT1 expression is a promising and rapid approach for monitoring of MRD in approximately half of paediatric AML patients.

  14. Detection of thermal SZ-CMB lensing cross-correlation in Planck nominal mission data

    SciTech Connect

    Hill, J. Colin; Spergel, David N. E-mail: dns@astro.princeton.edu

    2014-02-01

    The nominal mission maps from the Planck satellite contain a wealth of information about secondary anisotropies in the cosmic microwave background (CMB), including those induced by the thermal Sunyaev-Zel'dovich (tSZ) effect and gravitational lensing. As both the tSZ and CMB lensing signals trace the large-scale matter density field, the anisotropies sourced by these processes are expected to be correlated. We report the first detection of this cross-correlation signal, which we measure at 6.2σ significance using the Planck data. We take advantage of Planck's multifrequency coverage to construct a tSZ map using internal linear combination techniques, which we subsequently cross-correlate with the publicly-released Planck CMB lensing potential map. The cross-correlation is subject to contamination from the cosmic infrared background (CIB), which is known to correlate strongly with CMB lensing. We correct for this contamination via cross-correlating our tSZ map with the Planck 857 GHz map and confirm the robustness of our measurement using several null tests. We interpret the signal using halo model calculations, which indicate that the tSZ-CMB lensing cross-correlation is a unique probe of the physics of intracluster gas in high-redshift, low-mass groups and clusters. Our results are consistent with extrapolations of existing gas physics models to this previously unexplored regime and show clear evidence for contributions from both the one- and two-halo terms, but no statistically significant evidence for contributions from diffuse, unbound gas outside of collapsed halos. We also show that the amplitude of the signal depends rather sensitively on the amplitude of fluctuations (σ{sub 8}) and the matter density (Ω{sub m}), scaling as σ{sub 8}{sup 6.1}Ω{sub m}{sup 1.5} at ℓ = 1000. We constrain the degenerate combination σ{sub 8}(Ω{sub m}/0.282){sup 0.26} = 0.824±0.029, a result that is in less tension with primordial CMB constraints than some recent t

  15. Point pattern match-based change detection in a constellation of previously detected objects

    DOEpatents

    Paglieroni, David W.

    2016-06-07

    A method and system is provided that applies attribute- and topology-based change detection to objects that were detected on previous scans of a medium. The attributes capture properties or characteristics of the previously detected objects, such as location, time of detection, detection strength, size, elongation, orientation, etc. The locations define a three-dimensional network topology forming a constellation of previously detected objects. The change detection system stores attributes of the previously detected objects in a constellation database. The change detection system detects changes by comparing the attributes and topological consistency of newly detected objects encountered during a new scan of the medium to previously detected objects in the constellation database. The change detection system may receive the attributes of the newly detected objects as the objects are detected by an object detection system in real time.

  16. Detecting small scale heterogeneities in the crust from ambient noise cross-correlation

    NASA Astrophysics Data System (ADS)

    Sun, W.; Fu, L.

    2012-12-01

    Ambient noise cross-correlation is extensively applied to obtain the surface wave dispersion, and further to study the structures of the crust and the upper mantle. In recent years, many applications of the ambient noise tomography are reported in many locations, e.g., California, Europe, New Zealand, Tibet, and even in the Antarctica. The scale is regional or even continental. However, the applications of the method in detecting small scale heterogeneities are paid little attention. Small scale heterogeneities may be important to monitor/predict activities of volcano. This is concluded from the fact activities of volcano will result in stress variations. Correspondingly, the velocity distribution, i.e., heterogeneities, will change. Here, we will try to extend the ambient noise cross-correlation method to study small heterogeneities in the crust.

  17. Automatic detection of LUCC based on SIFT

    NASA Astrophysics Data System (ADS)

    Ammala, Keonuchan; Liu, YaoLin; Tai, Ji Rong

    2009-10-01

    Land use cover change (LUCC) provide important information for environmental management and planning. It is one of the most prominent characteristics in globe environment change, and not only limited by natural factor, but also affected by the factor of social, economics, technique and histories. Traditionally, field surveys of land cover and land use are time consuming and costly and provide tabular statistics with out geographic location information. Remote sensing and GIS are the most modern technologies which have been widely used in the field of natural resource management and monitoring. Change detection in land use and updating information on the distribution and dynamics of land use have long term significance in policy making and scientific research. In this paper, we use multistpectral images of Spot period two different of time 2002 and 2007 for detection on LUCC base on Scale Invariant Feature Transform (SIFT) method. An automatic image matching technique based on SIFT was proposed by using the rotation and scale invariant property of SIFT. Keypoints are first extracted by searching over all scales and image locations, then the descriptors defined on the keypoint neighborhood are computed. The proposed algorithm is robust to translation, rotation, noise and scaling. Experimental results, urban is the most part of Huangpi area which have been changed.

  18. Brain structure correlates of emotion-based rash impulsivity

    PubMed Central

    Muhlert, N.; Lawrence, A.D.

    2015-01-01

    Negative urgency (the tendency to engage in rash, ill-considered action in response to intense negative emotions), is a personality trait that has been linked to problematic involvement in several risky and impulsive behaviours, and to various forms of disinhibitory psychopathology, but its neurobiological correlates are poorly understood. Here, we explored whether inter-individual variation in levels of trait negative urgency was associated with inter-individual variation in regional grey matter volumes. Using voxel-based morphometry (VBM) in a sample (n = 152) of healthy participants, we found that smaller volumes of the dorsomedial prefrontal cortex and right temporal pole, regions previously linked to emotion appraisal, emotion regulation and emotion-based decision-making, were associated with higher levels of trait negative urgency. When controlling for other impulsivity linked personality traits (sensation seeking, lack of planning/perseverance) and negative emotionality per se (neuroticism), these associations remained, and an additional relationship was found between higher levels of trait negative urgency and smaller volumes of the left ventral striatum. This latter finding mirrors recent VBM findings in an animal model of impulsivity. Our findings offer novel insight into the brain structure correlates of one key source of inter-individual differences in impulsivity. PMID:25957991

  19. Attribute and topology based change detection in a constellation of previously detected objects

    DOEpatents

    Paglieroni, David W.; Beer, Reginald N.

    2016-01-19

    A system that applies attribute and topology based change detection to networks of objects that were detected on previous scans of a structure, roadway, or area of interest. The attributes capture properties or characteristics of the previously detected objects, such as location, time of detection, size, elongation, orientation, etc. The topology of the network of previously detected objects is maintained in a constellation database that stores attributes of previously detected objects and implicitly captures the geometrical structure of the network. A change detection system detects change by comparing the attributes and topology of new objects detected on the latest scan to the constellation database of previously detected objects.

  20. Multifocal multiphoton excitation and time correlated single photon counting detection for 3-D fluorescence lifetime imaging.

    PubMed

    Kumar, S; Dunsby, C; De Beule, P A A; Owen, D M; Anand, U; Lanigan, P M P; Benninger, R K P; Davis, D M; Neil, M A A; Anand, P; Benham, C; Naylor, A; French, P M W

    2007-10-01

    We report a multifocal multiphoton time-correlated single photon counting (TCSPC) fluorescence lifetime imaging (FLIM) microscope system that uses a 16 channel multi-anode PMT detector. Multiphoton excitation minimizes out-of-focus photobleaching, multifocal excitation reduces non-linear in-plane photobleaching effects and TCSPC electronics provide photon-efficient detection of the fluorescence decay profile. TCSPC detection is less prone to bleaching- and movement-induced artefacts compared to wide-field time-gated or frequency-domain FLIM. This microscope is therefore capable of acquiring 3-D FLIM images at significantly increased speeds compared to single beam multiphoton microscopy and we demonstrate this with live cells expressing a GFP tagged protein. We also apply this system to time-lapse FLIM of NAD(P)H autofluorescence in single live cells and report measurements on the change in the fluorescence decay profile following the application of a known metabolic inhibitor. PMID:19550524

  1. Texture orientation-based algorithm for detecting infrared maritime targets.

    PubMed

    Wang, Bin; Dong, Lili; Zhao, Ming; Wu, Houde; Xu, Wenhai

    2015-05-20

    Infrared maritime target detection is a key technology for maritime target searching systems. However, in infrared maritime images (IMIs) taken under complicated sea conditions, background clutters, such as ocean waves, clouds or sea fog, usually have high intensity that can easily overwhelm the brightness of real targets, which is difficult for traditional target detection algorithms to deal with. To mitigate this problem, this paper proposes a novel target detection algorithm based on texture orientation. This algorithm first extracts suspected targets by analyzing the intersubband correlation between horizontal and vertical wavelet subbands of the original IMI on the first scale. Then the self-adaptive wavelet threshold denoising and local singularity analysis of the original IMI is combined to remove false alarms further. Experiments show that compared with traditional algorithms, this algorithm can suppress background clutter much better and realize better single-frame detection for infrared maritime targets. Besides, in order to guarantee accurate target extraction further, the pipeline-filtering algorithm is adopted to eliminate residual false alarms. The high practical value and applicability of this proposed strategy is backed strongly by experimental data acquired under different environmental conditions.

  2. Digital image correlation-based optical coherence elastography

    NASA Astrophysics Data System (ADS)

    Sun, Cuiru; Standish, Beau; Vuong, Barry; Wen, Xiao-Yan; Yang, Victor

    2013-12-01

    Optical coherence elastography (OCE) provides deformation or material properties, mapping of soft tissue. We aim to develop a robust speckle tracking OCE technique with improved resolution and accuracy. A digital image correlation (DIC)-based OCE technique was developed by combining an advanced DIC algorithm with optical coherence tomography (OCT). System calibration and measurement error evaluation demonstrated that this DIC-based OCE technique had a resolution of ˜0.6 μm displacement and <0.5% strain measurement in the axial scan direction. The measured displacement ranged from 0.6 to 150 μm, obtained via phantom imaging. The capability of the DIC-based OCE technique, for differentiation of stiffness, was evaluated by imaging a candle gel phantom with an irregularly shaped stiff inclusion. OCE imaging of a chicken breast sample differentiated the fat, membrane, and muscle layers. Strain elastograms of an aneurysm sample showed heterogeneity of the tissue and clear contrast between the adventitia and media. These promising results demonstrated the capability of the DIC-based OCE for the characterization of the various components of the tissue sample. Further improvement of the system will be conducted to make this OCE technique a practical tool for measuring and differentiating material properties of soft tissue.

  3. Digital image correlation-based optical coherence elastography.

    PubMed

    Sun, Cuiru; Standish, Beau; Vuong, Barry; Wen, Xiao-Yan; Yang, Victor

    2013-12-01

    Optical coherence elastography (OCE) provides deformation or material properties, mapping of soft tissue. We aim to develop a robust speckle tracking OCE technique with improved resolution and accuracy. A digital image correlation (DIC)-based OCE technique was developed by combining an advanced DIC algorithm with optical coherence tomography (OCT). System calibration and measurement error evaluation demonstrated that this DIC-based OCE technique had a resolution of ~0.6 μm displacement and <0.5% strain measurement in the axial scan direction. The measured displacement ranged from 0.6 to 150 μm, obtained via phantom imaging. The capability of the DIC-based OCE technique, for differentiation of stiffness, was evaluated by imaging a candle gel phantom with an irregularly shaped stiff inclusion. OCE imaging of a chicken breast sample differentiated the fat, membrane, and muscle layers. Strain elastograms of an aneurysm sample showed heterogeneity of the tissue and clear contrast between the adventitia and media. These promising results demonstrated the capability of the DIC-based OCE for the characterization of the various components of the tissue sample. Further improvement of the system will be conducted to make this OCE technique a practical tool for measuring and differentiating material properties of soft tissue. PMID:24346855

  4. Long-range vibration sensor based on correlation analysis of optical frequency-domain reflectometry signals.

    PubMed

    Ding, Zhenyang; Yao, X Steve; Liu, Tiegen; Du, Yang; Liu, Kun; Han, Qun; Meng, Zhuo; Chen, Hongxin

    2012-12-17

    We present a novel method to achieve a space-resolved long- range vibration detection system based on the correlation analysis of the optical frequency-domain reflectometry (OFDR) signals. By performing two separate measurements of the vibrated and non-vibrated states on a test fiber, the vibration frequency and position of a vibration event can be obtained by analyzing the cross-correlation between beat signals of the vibrated and non-vibrated states in a spatial domain, where the beat signals are generated from interferences between local Rayleigh backscattering signals of the test fiber and local light oscillator. Using the proposed technique, we constructed a standard single-mode fiber based vibration sensor that can have a dynamic range of 12 km and a measurable vibration frequency up to 2 kHz with a spatial resolution of 5 m. Moreover, preliminarily investigation results of two vibration events located at different positions along the test fiber are also reported.

  5. Estimation of viscosity based on transverse momentum correlations

    NASA Astrophysics Data System (ADS)

    Sharma, Monika

    2010-02-01

    The heavy ion program at RHIC created a paradigm shift in the exploration of strongly interacting hot and dense matter. An important milestone achieved is the discovery of the formation of strongly interacting matter which seemingly flows like a perfect liquid at temperatures on the scale of T ˜ 2 x10^12 K [1]. As a next step, we consider measurements of transport coefficients such as kinematic, shear or bulk viscosity? Many calculations based on event anisotropy measurements indicate that the shear viscosity to the entropy density ratio (η/s) of the fluid formed at RHIC is significantly below that of all known fluids including the superfluid ^4He [2]. Precise determination of η/s ratio is currently a subject of extensive study. We present an alternative technique for the determination of medium viscosity proposed by Gavin and Aziz [3]. Preliminary results of measurements of the evolution of the transverse momentum correlation function with collision centrality of Au + Au interactions at √sNN = 200 GeV will be shown. We present results on differential version of the correlation measure and describe its use for the experimental determination of η/s.[4pt] [1] J. Adams et al., [STAR Collaboration], Nucl. Phys. A 757 (2005) 102.[0pt] [2] R. A. Lacey et al., Phys. Rev. Lett. 98 (2007) 092301.[0pt] [3] S. Gavin and M. Abdel-Aziz, Phys. Rev. Lett. 97 (2006) 162302. )

  6. Detecting Soft Errors in Stencil based Computations

    SciTech Connect

    Sharma, V.; Gopalkrishnan, G.; Bronevetsky, G.

    2015-05-06

    Given the growing emphasis on system resilience, it is important to develop software-level error detectors that help trap hardware-level faults with reasonable accuracy while minimizing false alarms as well as the performance overhead introduced. We present a technique that approaches this idea by taking stencil computations as our target, and synthesizing detectors based on machine learning. In particular, we employ linear regression to generate computationally inexpensive models which form the basis for error detection. Our technique has been incorporated into a new open-source library called SORREL. In addition to reporting encouraging experimental results, we demonstrate techniques that help reduce the size of training data. We also discuss the efficacy of various detectors synthesized, as well as our future plans.

  7. Comic image understanding based on polygon detection

    NASA Astrophysics Data System (ADS)

    Li, Luyuan; Wang, Yongtao; Tang, Zhi; Liu, Dong

    2013-01-01

    Comic image understanding aims to automatically decompose scanned comic page images into storyboards and then identify the reading order of them, which is the key technique to produce digital comic documents that are suitable for reading on mobile devices. In this paper, we propose a novel comic image understanding method based on polygon detection. First, we segment a comic page images into storyboards by finding the polygonal enclosing box of each storyboard. Then, each storyboard can be represented by a polygon, and the reading order of them is determined by analyzing the relative geometric relationship between each pair of polygons. The proposed method is tested on 2000 comic images from ten printed comic series, and the experimental results demonstrate that it works well on different types of comic images.

  8. Smell Detection Agent Based Optimization Algorithm

    NASA Astrophysics Data System (ADS)

    Vinod Chandra, S. S.

    2016-09-01

    In this paper, a novel nature-inspired optimization algorithm has been employed and the trained behaviour of dogs in detecting smell trails is adapted into computational agents for problem solving. The algorithm involves creation of a surface with smell trails and subsequent iteration of the agents in resolving a path. This algorithm can be applied in different computational constraints that incorporate path-based problems. Implementation of the algorithm can be treated as a shortest path problem for a variety of datasets. The simulated agents have been used to evolve the shortest path between two nodes in a graph. This algorithm is useful to solve NP-hard problems that are related to path discovery. This algorithm is also useful to solve many practical optimization problems. The extensive derivation of the algorithm can be enabled to solve shortest path problems.

  9. Research on the measurement of bubble velocity based on cross-correlation algorithm

    NASA Astrophysics Data System (ADS)

    Chen, Min; He, Junhua; Chen, Liangyi

    2006-06-01

    Cross-correlation algorithm is based on information theory and stochastic process theory. It has been widely used in many research fields, such as, medical ultrasound, ocean engineering, signal detection, modal parameters under ambient excitation, etc., but its applications in research of bubble curtains are seldom seen in domestic released periodicals, so our work is attempting to use cross-correlation algorithm. Through computing the velocity vector of bubble curtains, the bubble movement character can be known, i.e. the details of the bubble curtains can also be known. After comparing the differences between it and Doppler method, the cross-correlation algorithm has been applied to the measurement of bubble curtains parameters from a new aspect. The He-Ne laser and high-speed CCD camera are used to acquire the images of dancing bubbles, the velocities of bubbles are computed from image post-processed. Through improving conventional cross-correlation algorithm commonly used for analysis of flow field, the Fast Fourier Transform (FFT) has been used to implement the cross-correlation algorithm rapidly. In order to enhance the computing accuracy, Gaussian curve fitting is used to modify the correlation peak location and the fitting equations are listed, so the bubbles displacement with subpixel accuracy is obtained. Noises are stochastically added from hardware when acquiring images and the cross-correlation algorithm may also introduce errors. The character of velocity vectors result can be entirely wrong with ambient vectors, so they must be corrected. In order to calibrate the cross-correlation algorithm, images with universal displacement are used to validate its feasibility and reliability. The algorithm is applied to the computation of parameters in bubble curtains, yielding the vector graph of bubble motion. The algorithm is expected to be a valuable tool in acquiring the real-time velocity information in bubble curtains.

  10. Adulteration detection in milk using infrared spectroscopy combined with two-dimensional correlation analysis

    NASA Astrophysics Data System (ADS)

    He, Bin; Liu, Rong; Yang, Renjie; Xu, Kexin

    2010-02-01

    Adulteration of milk and dairy products has brought serious threats to human health as well as enormous economic losses to the food industry. Considering the diversity of adulterants possibly mixed in milk, such as melamine, urea, tetracycline, sugar/salt and so forth, a rapid, widely available, high-throughput, cost-effective method is needed for detecting each of the components in milk at once. In this paper, a method using Fourier Transform Infrared spectroscopy (FTIR) combined with two-dimensional (2D) correlation spectroscopy is established for the discriminative analysis of adulteration in milk. Firstly, the characteristic peaks of the raw milk are found in the 4000-400 cm-1 region by its original spectra. Secondly, the adulterant samples are respectively detected with the same method to establish a spectral database for subsequent comparison. Then, 2D correlation spectra of the samples are obtained which have high time resolution and can provide information about concentration-dependent intensity changes not readily accessible from one-dimensional spectra. And the characteristic peaks in the synchronous 2D correlation spectra of the suspected samples are compared with those of raw milk. The differences among their synchronous spectra imply that the suspected milk sample must contain some kinds of adulterants. Melamine, urea, tetracycline and glucose adulterants in milk are identified respectively. This nondestructive method can be used for a correct discrimination on whether the milk and dairy products are adulterated with deleterious substances and it provides a new simple and cost-effective alternative to test the components of milk.

  11. The Waveform Correlation Event Detection System project, Phase II: Testing with the IDC primary network

    SciTech Connect

    Young, C.J.; Beiriger, J.I.; Moore, S.G.

    1998-04-01

    Further improvements to the Waveform Correlation Event Detection System (WCEDS) developed by Sandia Laboratory have made it possible to test the system on the accepted Comprehensive Test Ban Treaty (CTBT) seismic monitoring network. For our test interval we selected a 24-hour period from December 1996, and chose to use the Reviewed Event Bulletin (REB) produced by the Prototype International Data Center (PIDC) as ground truth for evaluating the results. The network is heterogeneous, consisting of array and three-component sites, and as a result requires more flexible waveform processing algorithms than were available in the first version of the system. For simplicity and superior performance, we opted to use the spatial coherency algorithm of Wagner and Owens (1996) for both types of sites. Preliminary tests indicated that the existing version of WCEDS, which ignored directional information, could not achieve satisfactory detection or location performance for many of the smaller events in the REB, particularly those in the south Pacific where the network coverage is unusually sparse. To achieve an acceptable level of performance, we made modifications to include directional consistency checks for the correlations, making the regions of high correlation much less ambiguous. These checks require the production of continuous azimuth and slowness streams for each station, which is accomplished by means of FK processing for the arrays and power polarization processing for the three-component sites. In addition, we added the capability to use multiple frequency-banded data streams for each site to increase sensitivity to phases whose frequency content changes as a function of distance.

  12. Voxel-based analysis in neuroferritinopathy expands the phenotype and determines radiological correlates of disease severity.

    PubMed

    Keogh, M J; Aribisala, B S; He, J; Tulip, E; Butteriss, D; Morris, C; Gorman, G; Horvath, R; Chinnery, P F; Blamire, Andrew M

    2015-10-01

    Neuroferritinopathy is an autosomal dominant adult-onset movement disorder which occurs due to mutations in the ferritin light chain gene (FTL). Extensive iron deposition and cavitation are observed post-mortem in the basal ganglia, but whether more widespread pathological changes occur, and whether they correlate with disease severity is unknown. 3D-T1w and quantitative T2 whole brain MRI scans were performed in 10 clinically symptomatic patients with the 460InsA FTL mutation and 10 age-matched controls. Voxel-based morphometry (VBM) and voxel-based relaxometry (VBR) were subsequently performed. Clinical assessment using the Unified Dystonia Rating Scale (UDRS) and Unified Huntington's Disease Rating Scale (UHDRS) was undertaken in all patients. VBM detected significant tissue changes within the substantia nigra, midbrain and dentate together with significant cerebellar atrophy in patients (FWE, p < 0.05). Iron deposition in the caudate head and cavitation in the lateral globus pallidus correlated with UDRS score (p < 0.001). There were no differences between groups with VBR. Our data show that progressive iron accumulation in the caudate nucleus, and cavitation of the globus pallidus correlate with disease severity in neuroferritinopathy. We also confirm sub-clinical cerebellar atrophy as a feature of the disease. We suggest that VBM is an effective technique to detect regions of iron deposition and cavitation, with potential wider utility to determine radiological markers of disease severity for all NBIA disorders. PMID:26142024

  13. Preserving Differential Privacy in Degree-Correlation based Graph Generation

    PubMed Central

    Wang, Yue; Wu, Xintao

    2014-01-01

    Enabling accurate analysis of social network data while preserving differential privacy has been challenging since graph features such as cluster coefficient often have high sensitivity, which is different from traditional aggregate functions (e.g., count and sum) on tabular data. In this paper, we study the problem of enforcing edge differential privacy in graph generation. The idea is to enforce differential privacy on graph model parameters learned from the original network and then generate the graphs for releasing using the graph model with the private parameters. In particular, we develop a differential privacy preserving graph generator based on the dK-graph generation model. We first derive from the original graph various parameters (i.e., degree correlations) used in the dK-graph model, then enforce edge differential privacy on the learned parameters, and finally use the dK-graph model with the perturbed parameters to generate graphs. For the 2K-graph model, we enforce the edge differential privacy by calibrating noise based on the smooth sensitivity, rather than the global sensitivity. By doing this, we achieve the strict differential privacy guarantee with smaller magnitude noise. We conduct experiments on four real networks and compare the performance of our private dK-graph models with the stochastic Kronecker graph generation model in terms of utility and privacy tradeoff. Empirical evaluations show the developed private dK-graph generation models significantly outperform the approach based on the stochastic Kronecker generation model. PMID:24723987

  14. Preserving Differential Privacy in Degree-Correlation based Graph Generation.

    PubMed

    Wang, Yue; Wu, Xintao

    2013-08-01

    Enabling accurate analysis of social network data while preserving differential privacy has been challenging since graph features such as cluster coefficient often have high sensitivity, which is different from traditional aggregate functions (e.g., count and sum) on tabular data. In this paper, we study the problem of enforcing edge differential privacy in graph generation. The idea is to enforce differential privacy on graph model parameters learned from the original network and then generate the graphs for releasing using the graph model with the private parameters. In particular, we develop a differential privacy preserving graph generator based on the dK-graph generation model. We first derive from the original graph various parameters (i.e., degree correlations) used in the dK-graph model, then enforce edge differential privacy on the learned parameters, and finally use the dK-graph model with the perturbed parameters to generate graphs. For the 2K-graph model, we enforce the edge differential privacy by calibrating noise based on the smooth sensitivity, rather than the global sensitivity. By doing this, we achieve the strict differential privacy guarantee with smaller magnitude noise. We conduct experiments on four real networks and compare the performance of our private dK-graph models with the stochastic Kronecker graph generation model in terms of utility and privacy tradeoff. Empirical evaluations show the developed private dK-graph generation models significantly outperform the approach based on the stochastic Kronecker generation model.

  15. The use of waveform cross correlation at a three-component seismic array for detection, location, and magnitude estimation

    NASA Astrophysics Data System (ADS)

    Kitov, Ivan; Sanina, Irina

    2016-04-01

    Using the waveform cross-correlation technique, we have re-estimated relative locations and magnitudes of 200 events detected by an array consisting of seven 3-C sensors. All these events were quarry blasts conducted at several local/regional mines, which were detected and identified in the course of regional seismotectonic monitoring. From all detected signals we selected those having the highest quality and created a set of three-component templates for further cross correlation study. By changing the length of correlation window and the frequency band of the templates we selected optimal parameters for robust estimates of cross correlation coefficients and relative amplitudes/magnitudes of all signals. The relative locations and magnitude estimates obtained by cross correlation are compared to those in the catalog created in standard interactive analysis.

  16. Dual channel detection of ultra low concentration of bacteria in real time by scanning fluorescence correlation spectroscopy

    NASA Astrophysics Data System (ADS)

    Altamore, Ilaria; Lanzano, Luca; Gratton, Enrico

    2013-06-01

    We describe a novel method to detect very low concentrations of bacteria in water. Our device consists of a portable horizontal geometry small confocal microscope with large pinhole and a holder for cylindrical cuvettes containing the sample. Two motors provide fast rotational and slow vertical motion of the cuvette so the device looks like a simplified flow cytometer without flow. To achieve high sensitivity, the design has two detection channels. Bacteria are stained by two different nucleic acid dyes and excited with two different lasers. Data are analyzed with a correlation filter based on particle passage pattern recognition. The passage of a particle through the illumination volume is compared with a Gaussian pattern in both channels. The width of the Gaussian correlates with the time of passage of the particle so one particle is counted when the algorithm finds a match with a Gaussian in both channels. The concentration of particles in the sample is deduced from the total number of coincident hits and the total volume scanned. This portable setup provides higher sensitivity, low-cost advantage, and it can have a wide use ranging from clinical applications to pollution monitors and water and air quality control.

  17. Preliminary evaluation of biplane correlation (BCI) stereographic imaging for lung nodule detection.

    PubMed

    Boyce, Sarah J; McAdams, H Page; Ravin, Carl E; Patz, Edward F; Washington, Lacey; Martinez, Santiago; Koweek, Lynne; Samei, Ehsan

    2013-02-01

    A biplane correlation (BCI) imaging system obtains images that can be viewed in stereo, thereby minimizing overlapping structures. This study investigated whether using stereoscopic visualization provides superior lung nodule detection compared to standard postero-anterior (PA) image display. Images were acquired at two oblique views of ±3° as well as at a standard PA position from 60 patients. Images were processed using optimal parameters and displayed on a stereoscopic display. The PA image was viewed in the standard format, while the oblique views were paired to provide a stereoscopic view of the subject. A preliminary observer study was performed with four radiologists who viewed and scored the PA image then viewed and scored the BCI stereoscopic image. The BCI stereoscopic viewing of lung nodules resulted in 71 % sensitivity and 0.31 positive predictive value (PPV) index compared to PA results of 86 % sensitivity and 0.26 PPV index. The sensitivity for lung nodule detection with the BCI stereoscopic system was reduced by 15 %; however, the total number of false positives reported was reduced by 35 % resulting in an improved PPV index of 20 %. The preliminary results indicate observer dependency in terms of relative advantage of either system in the detection of lung nodules, but overall equivalency of the two methods with promising potential for BCI as an adjunct diagnostic technique.

  18. Lightweight Raman spectroscope using time-correlated photon-counting detection.

    PubMed

    Meng, Zhaokai; Petrov, Georgi I; Cheng, Shuna; Jo, Javier A; Lehmann, Kevin K; Yakovlev, Vladislav V; Scully, Marlan O

    2015-10-01

    Raman spectroscopy is an important tool in understanding chemical components of various materials. However, the excessive weight and energy consumption of a conventional CCD-based Raman spectrometer forbids its applications under extreme conditions, including unmanned aircraft vehicles (UAVs) and Mars/Moon rovers. In this article, we present a highly sensitive, shot-noise-limited, and ruggedized Raman signal acquisition using a time-correlated photon-counting system. Compared with conventional Raman spectrometers, over 95% weight, 65% energy consumption, and 70% cost could be removed through this design. This technique allows space- and UAV-based Raman spectrometers to robustly perform hyperspectral Raman acquisitions without excessive energy consumption.

  19. Lightweight Raman spectroscope using time-correlated photon-counting detection.

    PubMed

    Meng, Zhaokai; Petrov, Georgi I; Cheng, Shuna; Jo, Javier A; Lehmann, Kevin K; Yakovlev, Vladislav V; Scully, Marlan O

    2015-10-01

    Raman spectroscopy is an important tool in understanding chemical components of various materials. However, the excessive weight and energy consumption of a conventional CCD-based Raman spectrometer forbids its applications under extreme conditions, including unmanned aircraft vehicles (UAVs) and Mars/Moon rovers. In this article, we present a highly sensitive, shot-noise-limited, and ruggedized Raman signal acquisition using a time-correlated photon-counting system. Compared with conventional Raman spectrometers, over 95% weight, 65% energy consumption, and 70% cost could be removed through this design. This technique allows space- and UAV-based Raman spectrometers to robustly perform hyperspectral Raman acquisitions without excessive energy consumption. PMID:26392538

  20. Lightweight Raman spectroscope using time-correlated photon-counting detection

    PubMed Central

    Meng, Zhaokai; Petrov, Georgi I.; Cheng, Shuna; Jo, Javier A.; Lehmann, Kevin K.; Yakovlev, Vladislav V.; Scully, Marlan O.

    2015-01-01

    Raman spectroscopy is an important tool in understanding chemical components of various materials. However, the excessive weight and energy consumption of a conventional CCD-based Raman spectrometer forbids its applications under extreme conditions, including unmanned aircraft vehicles (UAVs) and Mars/Moon rovers. In this article, we present a highly sensitive, shot-noise–limited, and ruggedized Raman signal acquisition using a time-correlated photon-counting system. Compared with conventional Raman spectrometers, over 95% weight, 65% energy consumption, and 70% cost could be removed through this design. This technique allows space- and UAV-based Raman spectrometers to robustly perform hyperspectral Raman acquisitions without excessive energy consumption. PMID:26392538

  1. Miniaturized Gas Correlation Radiometer for the Detection of Trace Gases in the Martian Atmosphere

    NASA Astrophysics Data System (ADS)

    Melroy, H.; Wilson, E. L.; Georgieva, E.

    2012-12-01

    We present a miniaturized and simplified version of a gas correlation radiometer (GCR) capable of simultaneously mapping multiple trace gases and identifying active regions on the Mars surface. Gas correlation radiometry (GCR) has been shown to be a sensitive and versatile method for detecting trace gases in Earth's atmosphere. Reduction of the size and mass of the GCR was achieved by implementing compact, light-weight 1 mm inner diameter hollow-core optical fibers (hollow waveguides) as the gas correlation cells. In a comparison with an Earth orbiting CO2 GCR instrument, exchanging the 10 m multipass cells with hollow waveguide gas correlation cells of equivalent pathlength reduces the mass from ~150 kg to ~0.5 kg, and reduces the volume from 1.9 m x 1.3 m x 0.86 m to a small bundle of fiber coils approximately 1 meter in diameter by 0.05 m in height (mass and volume reductions of >99%). A unique feature of this instrument is its stackable module design, with a single module for each trace gas. Each of the modules is self-contained, and fundamentally identical; differing by the bandpass filter wavelength range and gas mixtures inside the hollow-waveguide absorption cells. The current configuration contains four stacked modules for simultaneous measurements of methane (CH4), formaldehyde (H2CO), water vapor (H2O), and deuterated water vapor (HDO) but could easily be expanded to include measurements of additional species of interest including nitrous oxide (N2O), hydrogen sulfide (H2S), methanol (CH3OH), and sulfur dioxide (SO2), as well as carbon dioxide (CO2) for a simultaneous measure of mass balance. Preliminary results indicate that a 1 ppb detection limit is possible for both formaldehyde and methane with one second of averaging. Using non-optimized components, we have demonstrated an instrument sensitivity equivalent to ~30 ppb for formaldehyde, and ~500 ppb for methane. We expect custom bandpass filters and 6 m long waveguides to significantly improve these

  2. Miniaturized Gas Correlation Radiometer for the Detection of Trace Gases in the Martian Atmosphere

    NASA Technical Reports Server (NTRS)

    Melroy, Hilary R.; Wilson, Emily L.; Georgieva, Elena

    2012-01-01

    We present a miniaturized and simplified version of a gas correlation radiometer (GCR) capable of simultaneously mapping multiple trace gases and identifying active regions on the Mars surface. Gas correlation radiometry (GCR) has been shown to be a sensitive and versatile method for detecting trace gases in Earth's atmosphere. Reduction of the size and mass of the GCR was achieved by implementing compact, light-weight 1 mm inner diameter hollow-core optical fibers (hollow waveguides) as the gas correlation cells. In a comparison with an Earth orbiting CO2 GCR instrument, exchanging the 10 m multipass cells with hollow waveguide gas correlation cells of equivalent path length reduces the mass from approximately 150 kg to approximately 0.5 kg, and reduces the volume from 1.9 m x 1.3 m x 0.86 m to a small bundle of fiber coils approximately 1 meter in diameter by 0.05 m in height (mass and volume reductions of greater than 99%). A unique feature of this instrument is its stackable module design, with a single module for each trace gas. Each of the modules is self-contained, and fundamentally identical; differing by the bandpass filter wavelength range and gas mixtures inside the hollow-waveguide absorption cells. The current configuration contains four stacked modules for simultaneous measurements of methane (CH4), formaldehyde (H2CO), water vapor (H2O), and deuterated water vapor (HDO) but could easily be expanded to include measurements of additional species of interest including nitrous oxide (N2O), hydrogen sulfide (H2S), methanol (CH3OH), and sulfur dioxide (SO2), as well as carbon dioxide (CO2) for a simultaneous measure of mass balance. Preliminary results indicate that a 1 ppb detection limit is possible for both formaldehyde and methane with one second of averaging. Using non-optimized components, we have demonstrated an instrument sensitivity equivalent to approximately 30 ppb for formaldehyde, and approximately 500 ppb for methane. We expect custom

  3. Correlation of expertise with error detection skills of force application during spinal manipulation learning*

    PubMed Central

    Loranger, Michel; Treboz, Julien; Boucher, Jean-Alexandre; Nougarou, François; Dugas, Claude; Descarreaux, Martin

    2016-01-01

    Objective: Most studies on spinal manipulation learning demonstrate the relevance of including motor learning strategies in chiropractic curricula. Two outcomes of practice are the production of movement in an efficient manner and the improved capability of learners to evaluate their own motor performance. The goals of this study were to evaluate if expertise is associated with increased spinal manipulation proficiency and if error detection skills of force application during a high-velocity low-amplitude spinal manipulation are related to expertise. Methods: Three groups of students and 1 group of expert chiropractors completed 10 thoracic spine manipulations on an instrumented device with the specific goal of reaching a maximum peak force of 300 N after a brief period of practice. After each trial, participants were asked to give an estimate of their maximal peak force. Force-time profiles were analyzed to determine the biomechanical parameters of each participant and the participant's capacity to estimate his or her own performance. Results: Significant between-group differences were found for each biomechanical parameter. No significant difference was found between groups for the error detection variables (p > .05). The lack of significant effects related to the error detection capabilities with expertise could be related to the specificity of the task and how the training process was structured. Conclusion: This study confirms that improvements in biomechanical parameters of spinal manipulation are related to expertise. Feedback based on error detection could be implemented in chiropractic curricula to improve trainee abilities in detecting motor execution errors. PMID:26270897

  4. Fourier-based interpolation bias prediction in digital image correlation.

    PubMed

    Su, Yong; Zhang, Qingchuan; Gao, Zeren; Xu, Xiaohai; Wu, Xiaoping

    2015-07-27

    Based on the Fourier method, this paper deduces analytic formulae for interpolation bias in digital image correlation, explains the well-known sinusoidal-shaped curves of interpolation bias, and introduces the concept of interpolation bias kernel, which characterizes the frequency response of the interpolation bias and thus provides a measure of the subset matching quality of the interpolation algorithm. The interpolation bias kernel attributes the interpolation bias to aliasing effect of interpolation and indicates that high-frequency components are the major source of interpolation bias. Based on our theoretical results, a simple and effective interpolation bias prediction approach, which exploits the speckle spectrum and the interpolation transfer function, is proposed. Significant acceleration is attained, the effect of subset size is analyzed, and both numerical simulations and experimental results are found to agree with theoretical predictions. During the experiment, a novel experimental translation technique was developed that implements subpixel translation of a captured image through integer pixel translation on a computer screen. Owing to this remarkable technique, the influences of mechanical error and out-of-plane motion are eliminated, and complete interpolation bias curves as accurate as 0.01 pixel are attained by subpixel translation experiments.

  5. A low-cost digital image correlation based constitutive sensor

    NASA Astrophysics Data System (ADS)

    Yun, Gun-Jin; Shang, Shen; Kunchum, Shilpa; Carletta, Joan; Nam, Si-Byung

    2010-03-01

    In this paper, a low-cost digital image correlation-based constitutive sensor with a novel identification algorithm that is deployable and scalable in the field is proposed. The term 'constitutive sensor' is coined herein to describe a sensor that is capable of determining the target material constitutive parameters. The proposed method is different from existing identification methods in that it does not need to solve boundary value problems of the target materials using updated parameters. Since the development of the digital image correlation (DIC) technique in the 1980s, the DIC technique has been broadly evaluated and improved for measuring full-field displacements of test specimens, mainly in laboratory settings. Although its potential in damage and mechanical identification is immense, the high cost of current commercial DIC systems makes it difficult to apply the DIC technique to in-field health monitoring of structures. To realize a first ever application of DIC in the field, a prototypical low-cost sensing unit consisting of a high performance embedded microprocessor board, a low-cost web camera, and a communication module is suggested. In the proposed constitutive sensor, DIC displacement fields considered as true values are used in computing stress fields satisfying the equilibrium condition and strain fields using finite element concepts. The unknown constitutive law is initially assumed to be fully anisotropic and linear elastic. A steady state genetic algorithm is utilized to search for the material parameters by minimizing a cost function that measures energy residuals. The main features that allow the sensor to be deployable in the field are introduced, and a validation of the proposed constitutive sensor concept using synthetic data is presented.

  6. Detection of the baryon acoustic peak in the large-scale correlation function of SDSS luminous red galaxies

    SciTech Connect

    Eisenstein, Daniel J.; Zehavi, Idit; Hogg, David W.; Scoccimarro, Roman; Blanton, Michael R.; Nichol, Robert C.; Scranton, Ryan; Seo, Hee-Jong; Tegmark, Max; Zheng, Zheng; Anderson, Scott F.; Annis, Jim; Bahcall, Neta; Brinkmann, Jon; Burles, Scott; Castander, Francisco J.; Connolly, Andrew; Csabai, Istvan; Doi, Mamoru; Fukugita, Masataka; Frieman, Joshua A.; /Arizona U., Astron. Dept. - Steward Observ. /CCPP, New York /Portsmouth U., ICG /Pittsburgh U. /Pennsylvania U. /MIT /Princeton, Inst. Advanced Study /Washington U., Seattle, Astron. Dept. /Fermilab /Princeton U. Observ. /Apache Point Observ. /Barcelona, IEEC /Eotvos U. /Tokyo U., Inst. Astron. /Tokyo U., ICRR /Chicago U., Astron. Astrophys. Ctr. /Johns Hopkins U. /Naval Observ., Flagstaff /Colorado U., CASA /Baltimore, Space Telescope Sci. /Michigan U.

    2005-01-01

    We present the large-scale correlation function measured from a spectroscopic sample of 46,748 luminous red galaxies from the Sloan Digital Sky Survey. The survey region covers 0.72h{sup -3} Gpc{sup 3} over 3816 square degrees and 0.16 < z < 0.47, making it the best sample yet for the study of large-scale structure. We find a well-detected peak in the correlation function at 100h{sup -1} Mpc separation that is an excellent match to the predicted shape and location of the imprint of the recombination-epoch acoustic oscillations on the low-redshift clustering of matter. This detection demonstrates the linear growth of structure by gravitational instability between z {approx} 1000 and the present and confirms a firm prediction of the standard cosmological theory. The acoustic peak provides a standard ruler by which we can measure the ratio of the distances to z = 0.35 and z = 1089 to 4% fractional accuracy and the absolute distance to z = 0.35 to 5% accuracy. From the overall shape of the correlation function, we measure the matter density {Omega}{sub m}h{sup 2} to 8% and find agreement with the value from cosmic microwave background (CMB) anisotropies. Independent of the constraints provided by the CMB acoustic scale, we find {Omega}{sub m} = 0.273 {+-} 0.025 + 0.123(1 + w{sub 0}) + 0.137{Omega}{sub K}. Including the CMB acoustic scale, we find that the spatial curvature is {Omega}{sub K} = -0.010 {+-} 0.009 if the dark energy is a cosmological constant. More generally, our results provide a measurement of cosmological distance, and hence an argument for dark energy, based on a geometric method with the same simple physics as the microwave background anisotropies. The standard cosmological model convincingly passes these new and robust tests of its fundamental properties.

  7. Automatic detection and classification of damage zone(s) for incorporating in digital image correlation technique

    NASA Astrophysics Data System (ADS)

    Bhattacharjee, Sudipta; Deb, Debasis

    2016-07-01

    Digital image correlation (DIC) is a technique developed for monitoring surface deformation/displacement of an object under loading conditions. This method is further refined to make it capable of handling discontinuities on the surface of the sample. A damage zone is referred to a surface area fractured and opened in due course of loading. In this study, an algorithm is presented to automatically detect multiple damage zones in deformed image. The algorithm identifies the pixels located inside these zones and eliminate them from FEM-DIC processes. The proposed algorithm is successfully implemented on several damaged samples to estimate displacement fields of an object under loading conditions. This study shows that displacement fields represent the damage conditions reasonably well as compared to regular FEM-DIC technique without considering the damage zones.

  8. CFHTLenS and RCSLenS cross-correlation with Planck lensing detected in fourier and configuration space

    NASA Astrophysics Data System (ADS)

    Harnois-Déraps, Joachim; Tröster, Tilman; Hojjati, Alireza; van Waerbeke, Ludovic; Asgari, Marika; Choi, Ami; Erben, Thomas; Heymans, Catherine; Hildebrandt, Hendrik; Kitching, Thomas D.; Miller, Lance; Nakajima, Reiko; Viola, Massimo; Arnouts, Stéphane; Coupon, Jean; Moutard, Thibaud

    2016-07-01

    We measure the cross-correlation signature between the Planck cosmic microwave background (CMB) lensing map and the weak lensing observations from both the Red-sequence Cluster Lensing Survey and the Canada-France-Hawaii Telescope Lensing Survey. In addition to a Fourier analysis, we include the first configuration-space detection, based on the estimators <κCMBκgal> and <κCMBγt>. Combining 747.2 deg2 from both surveys, we find a detection significance that exceeds 4.2σ in both Fourier- and configuration-space analyses. Scaling the predictions by a free parameter A, we obtain A^Planck_CFHT= 0.68± 0.31 and A^Planck_RCS= 1.31± 0.33. In preparation for the next generation of measurements similar to these, we quantify the impact of different analysis choices on these results. First, since none of these estimators probes the exact same dynamical range, we improve our detection by combining them. Secondly, we carry out a detailed investigation on the effect of apodization, zero-padding and mask multiplication, validated on a suite of high-resolution simulations, and find that the latter produces the largest systematic bias in the cosmological interpretation. Finally, we show that residual contamination from intrinsic alignment and the effect of photometric redshift error are both largely degenerate with the characteristic signal from massive neutrinos, however the signature of baryon feedback might be easier to distinguish. The three lensing data sets are publicly available.

  9. Endogenous brain-machine interface based on the correlation of EEG maps.

    PubMed

    Ubeda, Andrés; Iáñez, Eduardo; Azorín, José M; Perez-Vidal, Carlos

    2013-11-01

    In this paper, a non-invasive endogenous brain-machine interface (BMI) based on the correlation of EEG maps has been developed to work in real-time applications. The classifier is able to detect two mental tasks related to motor imagery with good success rates and stability. The BMI has been tested with four able-bodied volunteers. First, the users performed a training with visual feedback to adjust the classifier. Afterwards, the users carried out several trajectories in a visual interface controlling the cursor position with the BMI. In these tests, score and accuracy were measured. The results showed that the participants were able to follow the targets during the performed trajectory, proving that the EEG mapping correlation classifier is ready to work in more complex real-time applications aimed at helping people with a severe disability in their daily life.

  10. Intelligent-based Structural Damage Detection Model

    SciTech Connect

    Lee, Eric Wai Ming; Yu, K.F.

    2010-05-21

    This paper presents the application of a novel Artificial Neural Network (ANN) model for the diagnosis of structural damage. The ANN model, denoted as the GRNNFA, is a hybrid model combining the General Regression Neural Network Model (GRNN) and the Fuzzy ART (FA) model. It not only retains the important features of the GRNN and FA models (i.e. fast and stable network training and incremental growth of network structure) but also facilitates the removal of the noise embedded in the training samples. Structural damage alters the stiffness distribution of the structure and so as to change the natural frequencies and mode shapes of the system. The measured modal parameter changes due to a particular damage are treated as patterns for that damage. The proposed GRNNFA model was trained to learn those patterns in order to detect the possible damage location of the structure. Simulated data is employed to verify and illustrate the procedures of the proposed ANN-based damage diagnosis methodology. The results of this study have demonstrated the feasibility of applying the GRNNFA model to structural damage diagnosis even when the training samples were noise contaminated.

  11. Lagrangian based methods for coherent structure detection.

    PubMed

    Allshouse, Michael R; Peacock, Thomas

    2015-09-01

    There has been a proliferation in the development of Lagrangian analytical methods for detecting coherent structures in fluid flow transport, yielding a variety of qualitatively different approaches. We present a review of four approaches and demonstrate the utility of these methods via their application to the same sample analytic model, the canonical double-gyre flow, highlighting the pros and cons of each approach. Two of the methods, the geometric and probabilistic approaches, are well established and require velocity field data over the time interval of interest to identify particularly important material lines and surfaces, and influential regions, respectively. The other two approaches, implementing tools from cluster and braid theory, seek coherent structures based on limited trajectory data, attempting to partition the flow transport into distinct regions. All four of these approaches share the common trait that they are objective methods, meaning that their results do not depend on the frame of reference used. For each method, we also present a number of example applications ranging from blood flow and chemical reactions to ocean and atmospheric flows. PMID:26428570

  12. Lagrangian based methods for coherent structure detection

    SciTech Connect

    Allshouse, Michael R.; Peacock, Thomas

    2015-09-15

    There has been a proliferation in the development of Lagrangian analytical methods for detecting coherent structures in fluid flow transport, yielding a variety of qualitatively different approaches. We present a review of four approaches and demonstrate the utility of these methods via their application to the same sample analytic model, the canonical double-gyre flow, highlighting the pros and cons of each approach. Two of the methods, the geometric and probabilistic approaches, are well established and require velocity field data over the time interval of interest to identify particularly important material lines and surfaces, and influential regions, respectively. The other two approaches, implementing tools from cluster and braid theory, seek coherent structures based on limited trajectory data, attempting to partition the flow transport into distinct regions. All four of these approaches share the common trait that they are objective methods, meaning that their results do not depend on the frame of reference used. For each method, we also present a number of example applications ranging from blood flow and chemical reactions to ocean and atmospheric flows.

  13. Intelligent-based Structural Damage Detection Model

    NASA Astrophysics Data System (ADS)

    Lee, Eric Wai Ming; Yu, Kin Fung

    2010-05-01

    This paper presents the application of a novel Artificial Neural Network (ANN) model for the diagnosis of structural damage. The ANN model, denoted as the GRNNFA, is a hybrid model combining the General Regression Neural Network Model (GRNN) and the Fuzzy ART (FA) model. It not only retains the important features of the GRNN and FA models (i.e. fast and stable network training and incremental growth of network structure) but also facilitates the removal of the noise embedded in the training samples. Structural damage alters the stiffness distribution of the structure and so as to change the natural frequencies and mode shapes of the system. The measured modal parameter changes due to a particular damage are treated as patterns for that damage. The proposed GRNNFA model was trained to learn those patterns in order to detect the possible damage location of the structure. Simulated data is employed to verify and illustrate the procedures of the proposed ANN-based damage diagnosis methodology. The results of this study have demonstrated the feasibility of applying the GRNNFA model to structural damage diagnosis even when the training samples were noise contaminated.

  14. 3D Detection, Quantification and Correlation of Slope Failures with Geologic Structure in the Mont Blanc massif

    NASA Astrophysics Data System (ADS)

    Allan, Mark; Dunning, Stuart; Lim, Michael; Woodward, John

    2016-04-01

    A thorough understanding of supply from landslides and knowledge of their spatial distribution is of fundamental importance to high-mountain sediment budgets. Advances in 3D data acquisition techniques are heralding new opportunities to create high-resolution topographic models to aid our understanding of landscape change through time. In this study, we use a Structure-from-Motion Multi-View Stereo (SfM-MVS) approach to detect and quantify slope failures at selected sites in the Mont Blanc massif. Past and present glaciations along with its topographical characteristics have resulted in a high rate of geomorphological activity within the range. Data for SfM-MVS processing were captured across variable temporal scales to examine short-term (daily), seasonal and annual change from terrestrial, Unmanned Aerial Vehicle (UAV) and helicopter perspectives. Variable spatial scales were also examined ranging from small focussed slopes (~0.01 km2) to large valley-scale surveys (~3 km2). Alignment and registration were conducted using a series of Ground Control Points (GCPs) across the surveyed slope at various heights and slope aspects. GCPs were also used to optimise data and reduce non-linear distortions. 3D differencing was performed using a multiscale model-to-model comparison algorithm (M3C2) which uses variable thresholding across each slope based on local surface roughness and model alignment quality. Detected change was correlated with local slope structure and 3D discontinuity analysis was undertaken using a plane-detection and clustering approach (DSE). Computation of joint spacing was performed using the classified data and normal distances. Structural analysis allowed us to assign a Slope Mass Rating (SMR) and assess the stability of each slope relative to the detected change and determine likely failure modes. We demonstrate an entirely 3D workflow which preserves the complexity of alpine slope topography to compute volumetric loss using a variable threshold. A

  15. Is comprehension necessary for error detection? A conflict-based account of monitoring in speech production

    PubMed Central

    Nozari, Nazbanou; Dell, Gary S.; Schwartz, Myrna F.

    2011-01-01

    Despite the existence of speech errors, verbal communication is successful because speakers can detect (and correct) their errors. The standard theory of speech-error detection, the perceptual-loop account, posits that the comprehension system monitors production output for errors. Such a comprehension-based monitor, however, cannot explain the double dissociation between comprehension and error-detection ability observed in the aphasic patients. We propose a new theory of speech-error detection which is instead based on the production process itself. The theory borrows from studies of forced-choice-response tasks the notion that error detection is accomplished by monitoring response conflict via a frontal brain structure, such as the anterior cingulate cortex. We adapt this idea to the two-step model of word production, and test the model-derived predictions on a sample of aphasic patients. Our results show a strong correlation between patients’ error-detection ability and the model’s characterization of their production skills, and no significant correlation between error detection and comprehension measures, thus supporting a production-based monitor, generally, and the implemented conflict-based monitor in particular. The successful application of the conflict-based theory to error-detection in linguistic, as well as non-linguistic domains points to a domain-general monitoring system. PMID:21652015

  16. Optical cross-correlator based on supercontinuum generation

    SciTech Connect

    Filip, Catalin V.; Toth, Csaba; Leemans, Wim P.

    2006-03-20

    A novel cross-correlator that can be used for temporal characterization of femtosecond laser pulses has been developed. The correlation trace is obtained by ''sampling'' the structure of the laser pulse with a single, high-contrast pulse produced through femtosecond white-light generation in a line focus. This correlator has, therefore, fewer ''ghosts'' than a conventional third-order cross-correlator and it can be used with laser pulses that span across a wide wavelength range. Both scanning and single-shot experimental arrangements are described.

  17. Heat shock-induced interactions among nuclear HSFs detected by fluorescence cross-correlation spectroscopy

    SciTech Connect

    Pack, Chan-Gi; Ahn, Sang-Gun

    2015-07-31

    The cellular response to stress is primarily controlled in cells via transcriptional activation by heat shock factor 1 (HSF1). HSF1 is well-known to form homotrimers for activation upon heat shock and subsequently bind to target DNAs, such as heat-shock elements, by forming stress granules. A previous study demonstrated that nuclear HSF1 and HSF2 molecules in live cells interacted with target DNAs on the stress granules. However, the process underlying the binding interactions of HSF family in cells upon heat shock remains unclear. This study demonstrate for the first time that the interaction kinetics among nuclear HSF1, HSF2, and HSF4 upon heat shock can be detected directly in live cells using dual color fluorescence cross-correlation spectroscopy (FCCS). FCCS analyses indicated that the binding between HSFs was dramatically changed by heat shock. Interestingly, the recovery kinetics of interaction between HSF1 molecules after heat shock could be represented by changes in the relative interaction amplitude and mobility. - Highlights: • The binding interactions among nuclear HSFs were successfully detected. • The binding kinetics between HSF1s during recovery was quantified. • HSF2 and HSF4 strongly formed hetero-complex, even before heat shock. • Nuclear HSF2 and HSF4 bound to HSF1 only after heat shock.

  18. Development of an Early Warning Fire Detection System using Correlation Spectroscopy

    NASA Technical Reports Server (NTRS)

    Goswami, K.; Voevodkin, G.; Rubstov, V.; Lieberman, R.; Piltch, N.

    2001-01-01

    Combustion byproducts are numerous. A few examples of the gaseous byproducts include carbon dioxide, carbon monoxide, hydrogen chloride, hydrogen cyanide and ammonia. For detecting these chemical species, classic absorption spectroscopy has been used for many decades, but the sensitivity of steady-state methods is often unsuitable for the detection of trace compounds at the low levels (parts per million to parts per billion) appropriate for scientific purposes. This is particularly so for monitoring equipment, which must be compact and cost-effective, and which is often subjected to shock, vibration, and other environmental effects that can severely degrade the performance of high-sensitivity spectrometers in an aircraft. Steady-state techniques also suffer from a lack of specificity; the deconvolution of the spectra of complex mixtures is a laborious and error prone process. These problems are exacerbated in remote fiber-optic monitoring where, for practical reasons, the fundamental absorbance region of the spectrum (often between 3 and 8 microns) is inaccessible, and the low-strength, closely spaced, near-infrared overtone absorbance bands must be used. We circumvented these challenges by employing correlation spectroscopy, a variation of modulation spectroscopy.

  19. STOCK Market Differences in Correlation-Based Weighted Network

    NASA Astrophysics Data System (ADS)

    Youn, Janghyuk; Lee, Junghoon; Chang, Woojin

    We examined the sector dynamics of Korean stock market in relation to the market volatility. The daily price data of 360 stocks for 5019 trading days (from January, 1990 to August, 2008) in Korean stock market are used. We performed the weighted network analysis and employed four measures: the average, the variance, the intensity, and the coherence of network weights (absolute values of stock return correlations) to investigate the network structure of Korean stock market. We performed regression analysis using the four measures in the seven major industry sectors and the market (seven sectors combined). We found that the average, the intensity, and the coherence of sector (subnetwork) weights increase as market becomes volatile. Except for the "Financials" sector, the variance of sector weights also grows as market volatility increases. Based on the four measures, we can categorize "Financials," "Information Technology" and "Industrials" sectors into one group, and "Materials" and "Consumer Discretionary" sectors into another group. We investigated the distributions of intrasector and intersector weights for each sector and found the differences in "Financials" sector are most distinct.

  20. Atlas-based diffusion tensor imaging correlates of executive function

    PubMed Central

    Nowrangi, Milap A.; Okonkwo, Ozioma; Lyketsos, Constantine; Oishi, Kenichi; Mori, Susumu; Albert, Marilyn; Mielke, Michelle M.

    2015-01-01

    Impairment in executive function (EF) is commonly found in Alzheimer’s Dementia (AD) and Mild Cognitive Impairment (MCI). Atlas-based Diffusion Tensor Imaging (DTI) methods may be useful in relating regional integrity to EF measures in MCI and AD. 66 participants (25 NC, 22 MCI, and 19 AD) received DTI scans and clinical evaluation. DTI scans were applied to a pre-segmented atlas and fractional anisotropy (FA) and mean diffusivity (MD) were calculated. ANOVA was used to assess group differences in frontal, parietal, and cerebellar regions. For regions differing between groups (p<0.01), linear regression examined the relationship between EF scores and regional FA and MD. Anisotropy and diffusivity in frontal and parietal lobe white matter (WM) structures were associated with EF scores in MCI and only frontal lobe structures in AD. EF was more strongly associated with FA than MD. The relationship between EF and anisotropy and diffusivity was strongest in MCI. These results suggest that regional WM integrity is compromised in MCI and AD and that FA may be a better correlate of EF than MD. PMID:25318544

  1. Laser-based Sensors for Chemical Detection

    SciTech Connect

    Myers, Tanya L.; Phillips, Mark C.; Taubman, Matthew S.; Bernacki, Bruce E.; Schiffern, John T.; Cannon, Bret D.

    2010-05-10

    Stand-off detection of hazardous materials ensures that the responder is located at a safe distance from the suspected source. Remote detection and identification of hazardous materials can be accomplished using a highly sensitive and portable device, at significant distances downwind from the source or the threat. Optical sensing methods, in particular infrared absorption spectroscopy combined with quantum cascade lasers (QCLs), are highly suited for the detection of chemical substances since they enable rapid detection and are amenable for autonomous operation in a compact and rugged package. This talk will discuss the sensor systems developed at Pacific Northwest National Laboratory and will discuss the progress to reduce the size and power while maintaining sensitivity to enable stand-off detection of multiple chemicals.

  2. A Case Study Correlating Innovative Gamma Ray Scanning Detection Systems Data to Surface Soil Gamma Spectrometry Results - 13580

    SciTech Connect

    Thompson, Shannon; Rodriguez, Rene; Billock, Paul; Lit, Peter

    2013-07-01

    HydroGeoLogic (HGL), Inc. completed a United States Environmental Protection Agency (USEPA) study to characterize radiological contamination at a site near Canoga Park, California. The characterized area contained 470 acres including the site of a prototype commercial nuclear reactor and other nuclear design, testing, and support operations from the 1950's until 1988 [1]. The site history included radiological releases during operation followed by D and D activities. The characterization was conducted under an accelerated schedule and the results will support the project remediation. The project has a rigorous cleanup to background agenda and does not allow for comparison to risk-based guidelines. To target soil sample locations, multiple lines of evidence were evaluated including a gamma radiation survey, geophysical surveys, historical site assessment, aerial photographs, and former worker interviews. Due to the time since production and decay, the primary gamma emitting radionuclide remaining is cesium-137 (Cs-137). The gamma ray survey covered diverse, rugged terrain using custom designed sodium iodide thallium-activated (NaI(Tl)) scintillation detection systems. The survey goals included attaining 100% ground surface coverage and detecting gamma radiation as sensitively as possible. The effectiveness of innovative gamma ray detection systems was tested by correlating field Cs-137 static count ratios to Cs-137 laboratory gamma spectrometry results. As a case study, the area encompassing the former location of the first nuclear power station in the U. S. was scanned, and second by second global positioning system (GPS)-linked gamma spectral data were evaluated by examining total count rate and nuclide-specific regions of interest. To compensate for Compton scattering from higher energy naturally occurring radionuclides (U-238, Th-232 and their progeny, and K-40), count rate ratios of anthropogenic nuclide-specific regions of interest to the total count rate were

  3. Determination of melamine of milk based on two-dimensional correlation infrared spectroscopy

    NASA Astrophysics Data System (ADS)

    Yang, Ren-jie; Liu, Rong; Xu, Kexin

    2012-03-01

    The adulteration of milk with harmful substances is a threat to public health and beyond question a serious crime. In order to develop a rapid, cost-effective, high-throughput analysis method for detecting of adulterants in milk, the discriminative analysis of melamine is established in milk based on the two-dimensional (2D) correlation infrared spectroscopy in present paper. Pure milk samples and adulterated milk samples with different content of melamine were prepared. Then the Fourier Transform Infrared spectra of all samples were measured at room temperature. The characteristics of pure milk and adulterated milk were studied by one-dimensional spectra. The 2D NIR and 2D IR correlation spectroscopy were calculated under the perturbation of adulteration concentration. In the range from 1400 to 1800 cm-1, two strong autopeaks were aroused by melamine in milk at 1464 cm-1 and 1560 cm-1 in synchronous spectrum. At the same time, the 1560 cm-1 band does not share cross peak with the 1464 cm-1 band, which further confirm that the two bands have the same origin. Also in the range from 4200 to 4800 cm-1, the autopeak was shown at 4648 cm-1 in synchronous spectrum of melamine in milk. 2D NIR-IR hetero-spectral correlation analysis confirmed that the bands at 1464, 1560 and 4648 cm-1 had the same origin. The results demonstrated that the adulterant can be discriminated correctly by 2D correlation infrared spectroscopy.

  4. BASE: Bayesian Astrometric and Spectroscopic Exoplanet Detection and Characterization Tool

    NASA Astrophysics Data System (ADS)

    Schulze-Hartung, Tim

    2012-08-01

    BASE is a novel program for the combined or separate Bayesian analysis of astrometric and radial-velocity measurements of potential exoplanet hosts and binary stars. The tool fulfills two major tasks of exoplanet science, namely the detection of exoplanets and the characterization of their orbits. BASE was developed to provide the possibility of an integrated Bayesian analysis of stellar astrometric and Doppler-spectroscopic measurements with respect to their binary or planetary companions’ signals, correctly treating the astrometric measurement uncertainties and allowing to explore the whole parameter space without the need for informative prior constraints. The tool automatically diagnoses convergence of its Markov chain Monte Carlo (MCMC[2]) sampler to the posterior and regularly outputs status information. For orbit characterization, BASE delivers important results such as the probability densities and correlations of model parameters and derived quantities. BASE is a highly configurable command-line tool developed in Fortran 2008 and compiled with GFortran. Options can be used to control the program’s behaviour and supply information such as the stellar mass or prior information. Any option can be supplied in a configuration file and/or on the command line.

  5. TCSPC based approaches for multiparameter detection in living cells

    NASA Astrophysics Data System (ADS)

    Jahn, Karolina; Buschmann, Volker; Koberling, Felix; Hille, Carsten

    2014-03-01

    In living cells a manifold of processes take place simultaneously. This implies a precise regulation of intracellular ion homeostasis. In order to understand their spatio-temporal pattern comprehensively, the development of multiplexing concepts is essential. Due to the multidimensional characteristics of fluorescence dyes (absorption and emission spectra, decay time, anisotropy), the highly sensitive and non-invasive fluorescence microscopy is a versatile tool for realising multiplexing concepts. A prerequisite are analyte-specific fluorescence dyes with low cross-sensitivity to other dyes and analytes, respectively. Here, two approaches for multiparameter detection in living cells are presented. Insect salivary glands are well characterised secretory active tissues which were used as model systems to evaluate multiplexing concepts. Salivary glands secrete a KCl-rich or NaCl-rich fluid upon stimulation which is mainly regulated by intracellular Ca2+ as second messenger. Thus, pairwise detection of intracellular Na+, Cl- and Ca2+ with the fluorescent dyes ANG2, MQAE and ACR were tested. Therefore, the dyes were excited simultaneously (2-photon excitation) and their corresponding fluorescence decay times were recorded within two spectral ranges using time-correlated singlephoton counting (TCSPC). A second approach presented here is based on a new TCSPC-platform covering decay time detection from picoseconds to milliseconds. Thereby, nanosecond decaying cellular fluorescence and microsecond decaying phosphorescence of Ruthenium-complexes, which is quenched by oxygen, were recorded simultaneously. In both cases changes in luminescence decay times can be linked to changes in analyte concentrations. In consequence of simultaneous excitation as well as detection, it is possible to get a deeper insight into spatio-temporal pattern in living tissues.

  6. Cross Psi(B)-energy operator-based signal detection.

    PubMed

    Boudraa, Abdel-Ouahab; Cexus, Jean-Christophe; Abed-Meraim, Karim

    2008-06-01

    In this paper, two methods for signal detection and time-delay estimation based on the cross Psi(B)-energy operator are proposed. These methods are well suited for mono-component AM-FM signals. The Psi(B) energy operator measures how much one signal is present in another one. The peak of the Psi(B) operator corresponds to the maximum of interaction between the two signals. Compared to the cross-correlation function, the Psi(B) operator includes temporal information and relative changes of the signal which are reflected in its first and second derivatives. The discrete version of the continuous-time form of the Psi(B) operator, which is used in its implementation, is presented. The methods are illustrated on synthetic and real signals and the results compared to those of the matched filter and the cross correlation. The real signals correspond to impulse responses of buried objects obtained by active sonar in iso-speed single path environments. PMID:18537379

  7. Cross Psi(B)-energy operator-based signal detection.

    PubMed

    Boudraa, Abdel-Ouahab; Cexus, Jean-Christophe; Abed-Meraim, Karim

    2008-06-01

    In this paper, two methods for signal detection and time-delay estimation based on the cross Psi(B)-energy operator are proposed. These methods are well suited for mono-component AM-FM signals. The Psi(B) energy operator measures how much one signal is present in another one. The peak of the Psi(B) operator corresponds to the maximum of interaction between the two signals. Compared to the cross-correlation function, the Psi(B) operator includes temporal information and relative changes of the signal which are reflected in its first and second derivatives. The discrete version of the continuous-time form of the Psi(B) operator, which is used in its implementation, is presented. The methods are illustrated on synthetic and real signals and the results compared to those of the matched filter and the cross correlation. The real signals correspond to impulse responses of buried objects obtained by active sonar in iso-speed single path environments.

  8. Cellular telephone-based wide-area radiation detection network

    DOEpatents

    Craig, William W.; Labov, Simon E.

    2009-06-09

    A network of radiation detection instruments, each having a small solid state radiation sensor module integrated into a cellular phone for providing radiation detection data and analysis directly to a user. The sensor module includes a solid-state crystal bonded to an ASIC readout providing a low cost, low power, light weight compact instrument to detect and measure radiation energies in the local ambient radiation field. In particular, the photon energy, time of event, and location of the detection instrument at the time of detection is recorded for real time transmission to a central data collection/analysis system. The collected data from the entire network of radiation detection instruments are combined by intelligent correlation/analysis algorithms which map the background radiation and detect, identify and track radiation anomalies in the region.

  9. Estimating individual contribution from group-based structural correlation networks.

    PubMed

    Saggar, Manish; Hosseini, S M Hadi; Bruno, Jennifer L; Quintin, Eve-Marie; Raman, Mira M; Kesler, Shelli R; Reiss, Allan L

    2015-10-15

    Coordinated variations in brain morphology (e.g., cortical thickness) across individuals have been widely used to infer large-scale population brain networks. These structural correlation networks (SCNs) have been shown to reflect synchronized maturational changes in connected brain regions. Further, evidence suggests that SCNs, to some extent, reflect both anatomical and functional connectivity and hence provide a complementary measure of brain connectivity in addition to diffusion weighted networks and resting-state functional networks. Although widely used to study between-group differences in network properties, SCNs are inferred only at the group-level using brain morphology data from a set of participants, thereby not providing any knowledge regarding how the observed differences in SCNs are associated with individual behavioral, cognitive and disorder states. In the present study, we introduce two novel distance-based approaches to extract information regarding individual differences from the group-level SCNs. We applied the proposed approaches to a moderately large dataset (n=100) consisting of individuals with fragile X syndrome (FXS; n=50) and age-matched typically developing individuals (TD; n=50). We tested the stability of proposed approaches using permutation analysis. Lastly, to test the efficacy of our method, individual contributions extracted from the group-level SCNs were examined for associations with intelligence scores and genetic data. The extracted individual contributions were stable and were significantly related to both genetic and intelligence estimates, in both typically developing individuals and participants with FXS. We anticipate that the approaches developed in this work could be used as a putative biomarker for altered connectivity in individuals with neurodevelopmental disorders. PMID:26162553

  10. Effect of the degree of phase-correlation of laser sources on the transmission and optical coherent detection in radio-over-fibre systems

    NASA Astrophysics Data System (ADS)

    Maldonado-Basilio, Ramón; Li, Ran; Abdul-Majid, Sawsan; Nikkhah, Hamdam; Leong, Kin-Wai; Hall, Trevor J.

    2013-01-01

    The deployment of high capacity Radio-over-Fiber (RoF) systems rely, among many aspects, on the capability to efficiently generate, transport, and detect millimeter-wave carriers modulated at high data rates. Photonic approaches based on the heterodyne beating of two free-running laser sources have been proposed as an alternative to generate multi-Gbps quadrature phase modulated signals imposed on millimeter wave carriers. Implementing photonic approaches in the down-link avoids the need for electronic generation of high frequency carriers and decreases the requirements at the base band electronics. In addition, implementing complex modulation formats overcomes some of the typical issues found in intensity modulation direct detection approaches such as non­ linearity, receiver sensitivity and dynamic range. In this work, the performance improvement of a coherent RoF system carrying 10 Gbps QPSK signals is numerically analyzed in terms of both the frequency linewidth and the degree of phase correlation between the lasers utilised at the down-link (for the optical heterodyne beating) and at the up-link (for the optical coherent detection). Relative to phase correlated lasers featuring linewidths of 5 MHz, the peak power of the 60 G Hz carrier generated at the down-link is reduced by 8 dB for un-correlated lasers. In addition, the error vector magnitude of the received signal at the up-link is improved from over 20% (for un-correlated lasers and linewidths of 5 MHz) to around 15% (for correlated lasers) at an optical received power of -30 dBm. The results obtained reinforce the idea of using coherent comb laser sources with phase correlated modes located at the Central Office. It also motivates the eventual deployment of techniques to control the degree of phase correlation between the lasers used as signal and local oscillator at the optical coherent receivers.

  11. A review and development of correlations for base pressure and base heating in supersonic flow

    SciTech Connect

    Lamb, J.P.; Oberkampf, W.L.

    1993-11-01

    A comprehensive review of experimental base pressure and base heating data related to supersonic and hypersonic flight vehicles has been completed. Particular attention was paid to free-flight data as well as wind tunnel data for models without rear sting support. Using theoretically based correlation parameters, a series of internally consistent, empirical prediction equations has been developed for planar and axisymmetric geometries (wedges, cones, and cylinders). These equations encompass the speed range from low supersonic to hypersonic flow and laminar and turbulent forebody boundary layers. A wide range of cone and wedge angles and cone bluntness ratios was included in the data base used to develop the correlations. The present investigation also included preliminary studies of the effect of angle of attack and specific-heat ratio of the gas.

  12. Vision-based vehicle detection and tracking algorithm design

    NASA Astrophysics Data System (ADS)

    Hwang, Junyeon; Huh, Kunsoo; Lee, Donghwi

    2009-12-01

    The vision-based vehicle detection in front of an ego-vehicle is regarded as promising for driver assistance as well as for autonomous vehicle guidance. The feasibility of vehicle detection in a passenger car requires accurate and robust sensing performance. A multivehicle detection system based on stereo vision has been developed for better accuracy and robustness. This system utilizes morphological filter, feature detector, template matching, and epipolar constraint techniques in order to detect the corresponding pairs of vehicles. After the initial detection, the system executes the tracking algorithm for the vehicles. The proposed system can detect front vehicles such as the leading vehicle and side-lane vehicles. The position parameters of the vehicles located in front are obtained based on the detection information. The proposed vehicle detection system is implemented on a passenger car, and its performance is verified experimentally.

  13. Aerobic plate counts and ATP levels correlate with Listeria monocytogenes detection in retail delis.

    PubMed

    Hammons, Susan R; Stasiewicz, Matthew J; Roof, Sherry; Oliver, Haley F

    2015-04-01

    Listeria monocytogenes is a foodborne pathogen that causes an estimated 1,591 cases of illness and 255 deaths annually in the United States, the majority of which are attributed to ready-to-eat deli meats processed in retail delis. Because retail delis distribute product directly to consumers, rapid methods to validate cleaning and sanitation are needed to improve retail food safety. This study investigated the relationships among ATP levels, standard aerobic plate count (APC), and L. monocytogenes presence in fully operational delis. Fifteen full-service delis were concurrently sampled for ATP, APC, and L. monocytogenes during preoperational hours once monthly for 3 months. Fifteen additional delis were recruited for 6 months of operational sampling (n = 30). A 1-log increase in APC was equivalent to a 3.3-fold increase in the odds of detecting L. monocytogenes (P < 0.001) and a 1.9-log increase in L monocytogenes population (P = 0.03). An ATP level increase of 1 log relative light unit correlated to a 0.22-log increase in APC (P < 0.001). A preoperational ATP level mean increase by 1 log relative light unit increased the odds of detecting L. monocytogenes concurrently fourfold. A 0.5-log increase in mean ATP level during preoperational sampling corresponded to a 2% increase in the predicted L. monocytogenes prevalence during operation (P < 0.01). Additionally, 10 statistically representative sites were identified and recommended for use in sanitation monitoring programs. Our data support the use of ATP as a rapid method to validate effective cleaning and sanitation to reduce L. monocytogenes in retail delis.

  14. Neural Correlates of Own Name and Own Face Detection in Autism Spectrum Disorder

    PubMed Central

    Cygan, Hanna B.; Tacikowski, Pawel; Ostaszewski, Pawel; Chojnicka, Izabela; Nowicka, Anna

    2014-01-01

    Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental condition clinically characterized by social interaction and communication difficulties. To date, the majority of research efforts have focused on brain mechanisms underlying the deficits in interpersonal social cognition associated with ASD. Recent empirical and theoretical work has begun to reveal evidence for a reduced or even absent self-preference effect in patients with ASD. One may hypothesize that this is related to the impaired attentional processing of self-referential stimuli. The aim of our study was to test this hypothesis. We investigated the neural correlates of face and name detection in ASD. Four categories of face/name stimuli were used: own, close-other, famous, and unknown. Event-related potentials were recorded from 62 electrodes in 23 subjects with ASD and 23 matched control subjects. P100, N170, and P300 components were analyzed. The control group clearly showed a significant self-preference effect: higher P300 amplitude to the presentation of own face and own name than to the close-other, famous, and unknown categories, indicating preferential attentional engagement in processing of self-related information. In contrast, detection of both own and close-other's face and name in the ASD group was associated with enhanced P300, suggesting similar attention allocation for self and close-other related information. These findings suggest that attention allocation in the ASD group is modulated by the personal significance factor, and that the self-preference effect is absent if self is compared to close-other. These effects are similar for physical and non-physical aspects of the autistic self. In addition, lateralization of face and name processing is attenuated in ASD, suggesting atypical brain organization. PMID:24465847

  15. Neural correlates of own name and own face detection in autism spectrum disorder.

    PubMed

    Cygan, Hanna B; Tacikowski, Pawel; Ostaszewski, Pawel; Chojnicka, Izabela; Nowicka, Anna

    2014-01-01

    Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental condition clinically characterized by social interaction and communication difficulties. To date, the majority of research efforts have focused on brain mechanisms underlying the deficits in interpersonal social cognition associated with ASD. Recent empirical and theoretical work has begun to reveal evidence for a reduced or even absent self-preference effect in patients with ASD. One may hypothesize that this is related to the impaired attentional processing of self-referential stimuli. The aim of our study was to test this hypothesis. We investigated the neural correlates of face and name detection in ASD. Four categories of face/name stimuli were used: own, close-other, famous, and unknown. Event-related potentials were recorded from 62 electrodes in 23 subjects with ASD and 23 matched control subjects. P100, N170, and P300 components were analyzed. The control group clearly showed a significant self-preference effect: higher P300 amplitude to the presentation of own face and own name than to the close-other, famous, and unknown categories, indicating preferential attentional engagement in processing of self-related information. In contrast, detection of both own and close-other's face and name in the ASD group was associated with enhanced P300, suggesting similar attention allocation for self and close-other related information. These findings suggest that attention allocation in the ASD group is modulated by the personal significance factor, and that the self-preference effect is absent if self is compared to close-other. These effects are similar for physical and non-physical aspects of the autistic self. In addition, lateralization of face and name processing is attenuated in ASD, suggesting atypical brain organization.

  16. Nanopore-Based Target Sequence Detection

    PubMed Central

    Morin, Trevor J.; Shropshire, Tyler; Liu, Xu; Briggs, Kyle; Huynh, Cindy; Tabard-Cossa, Vincent; Wang, Hongyun; Dunbar, William B.

    2016-01-01

    The promise of portable diagnostic devices relies on three basic requirements: comparable sensitivity to established platforms, inexpensive manufacturing and cost of operations, and the ability to survive rugged field conditions. Solid state nanopores can meet all these requirements, but to achieve high manufacturing yields at low costs, assays must be tolerant to fabrication imperfections and to nanopore enlargement during operation. This paper presents a model for molecular engineering techniques that meets these goals with the aim of detecting target sequences within DNA. In contrast to methods that require precise geometries, we demonstrate detection using a range of pore geometries. As a result, our assay model tolerates any pore-forming method and in-situ pore enlargement. Using peptide nucleic acid (PNA) probes modified for conjugation with synthetic bulk-adding molecules, pores ranging 15-50 nm in diameter are shown to detect individual PNA-bound DNA. Detection of the CFTRΔF508 gene mutation, a codon deletion responsible for ∼66% of all cystic fibrosis chromosomes, is demonstrated with a 26-36 nm pore size range by using a size-enhanced PNA probe. A mathematical framework for assessing the statistical significance of detection is also presented. PMID:27149679

  17. Correlation-based Transition Modeling for External Aerodynamic Flows

    NASA Astrophysics Data System (ADS)

    Medida, Shivaji

    Conventional turbulence models calibrated for fully turbulent boundary layers often over-predict drag and heat transfer on aerodynamic surfaces with partially laminar boundary layers. A robust correlation-based model is developed for use in Reynolds-Averaged Navier-Stokes simulations to predict laminar-to-turbulent transition onset of boundary layers on external aerodynamic surfaces. The new model is derived from an existing transition model for the two-equation k-omega Shear Stress Transport (SST) turbulence model, and is coupled with the one-equation Spalart-Allmaras (SA) turbulence model. The transition model solves two transport equations for intermittency and transition momentum thickness Reynolds number. Experimental correlations and local mean flow quantities are used in the model to account for effects of freestream turbulence level and pressure gradients on transition onset location. Transition onset is triggered by activating intermittency production using a vorticity Reynolds number criterion. In the new model, production and destruction terms of the intermittency equation are modified to improve consistency in the fully turbulent boundary layer post-transition onset, as well as ensure insensitivity to freestream eddy viscosity value specified in the SA model. In the original model, intermittency was used to control production and destruction of turbulent kinetic energy. Whereas, in the new model, only the production of eddy viscosity in SA model is controlled, and the destruction term is not altered. Unlike the original model, the new model does not use an additional correction to intermittency for separation-induced transition. Accuracy of drag predictions are improved significantly with the use of the transition model for several two-dimensional single- and multi-element airfoil cases over a wide range of Reynolds numbers. The new model is able to predict the formation of stable and long laminar separation bubbles on low-Reynolds number airfoils that

  18. Biosensor based on Butyrylcholinesterase for Detection of Carbofuran

    NASA Astrophysics Data System (ADS)

    Dey, Mousumi; Bhuvanagayathri, R.; Daniel, David K.

    2015-04-01

    Esterase enzymes play an important role in biology because they are responsible for the hydrolysis of choline esters. In their absence, the original state of the post synaptic membranes cannot be reestablished. Therefore, the aim of the work is to study the inhibiting action exerted by the group of compounds on these enzymes. Among these class of inhibiting compounds, pesticides are important because of the potential danger as a result of their large scale use in agriculture. Pesticides are generally determined using liquid or gas chromatography methods with various detection techniques. These methods are very sensitive and discriminating, however they require sample pretreatment such as extraction, preconcentration and clean up, which are skilled techniques and high cost treatment and also time consuming. In this study, acetyl cholinesterase and butyrylcholinesterase based biosensors have emerged as a promising tool for the detection and characterization of pesticides which are inhibitors of these enzymes. Although the physiological function of butyrylcholinesterase in comparison with acetyl cholinesterase is ambiguous, it has larger substrate specificity towards choline esters. Therefore, the development of a more selective electrode against choline, can lead to more sensitive determination of the inhibitor being investigated. Hence in the present work, a method based on inhibition of butyrylcholinesterase was attempted for quantification of carbofuran on the basis of cholinesterase inhibition. Butyrylcholinesterase with an activity of 10.2 units/mg was immobilized on a solid surface by cross linking with glutaraldehyde. The immobilized system was calibrated by correlating the inhibition of the butyrylcholinesterase activity with varying concentrations of the butyryl choline chloride and carbofuran. The sensing mechanism was investigated for its response to carbofuran concentrations ranging from 125 to 1,000 ppm. The effects of butyryl choline chloride

  19. Adaptive skin detection based on online training

    NASA Astrophysics Data System (ADS)

    Zhang, Ming; Tang, Liang; Zhou, Jie; Rong, Gang

    2007-11-01

    Skin is a widely used cue for porn image classification. Most conventional methods are off-line training schemes. They usually use a fixed boundary to segment skin regions in the images and are effective only in restricted conditions: e.g. good lightness and unique human race. This paper presents an adaptive online training scheme for skin detection which can handle these tough cases. In our approach, skin detection is considered as a classification problem on Gaussian mixture model. For each image, human face is detected and the face color is used to establish a primary estimation of skin color distribution. Then an adaptive online training algorithm is used to find the real boundary between skin color and background color in current image. Experimental results on 450 images showed that the proposed method is more robust in general situations than the conventional ones.

  20. Antibody-based biological toxin detection

    SciTech Connect

    Menking, D.E.; Goode, M.T.

    1995-12-01

    Fiber optic evanescent fluorosensors are under investigation in our laboratory for the study of drug-receptor interactions for detection of threat agents and antibody-antigen interactions for detection of biological toxins. In a direct competition assay, antibodies against Cholera toxin, Staphylococcus Enterotoxin B or ricin were noncovalently immobilized on quartz fibers and probed with fluorescein isothiocyanate (FITC) - labeled toxins. In the indirect competition assay, Cholera toxin or Botulinum toxoid A was immobilized onto the fiber, followed by incubation in an antiserum or partially purified anti-toxin IgG. These were then probed with FITC-anti-IgG antibodies. Unlabeled toxins competed with labeled toxins or anti-toxin IgG in a dose dependent manner and the detection of the toxins was in the nanomolar range.

  1. A Novel Detection Scheme for High-Resolution Two-Dimensional Spin-Echo Correlated Spectra in Inhomogeneous Fields

    PubMed Central

    Huang, Yuqing; Zhang, Zhiyong; Cai, Shuhui; Chen, Zhong

    2014-01-01

    Background Two-dimensional (2D) nuclear magnetic resonance (NMR) spectroscopy is a powerful and non-invasive tool for the analysis of molecular structures, conformations, and dynamics. However, the inhomogeneity of magnetic fields experienced by samples will destroy spectral information and hinder spectral analysis. In this study, a new pulse sequence is proposed based on the modulation of distant dipolar field to recover high-resolution 2D spin-echo correlated spectroscopy (SECSY) from inhomogeneous fields. Method and Material By using the new sequence, the correlation information between coupled spins and the J coupled information with straightforward multiplet patterns can be obtained free from inhomogeneous line broadening. In addition, the new sequence is also suitable for non-J coupled spin systems. Although three-dimensional acquisition is needed, the evolution of indirect detection dimensions is carefully designed and the ultrafast acquisition scheme is utilized to improve the acquisition efficiency. A chemical solution of butyl methacrylate (C8H14O2) in DMSO (C2H6SO) in a deshimmed magnetic field was tested to demonstrate the implementation details of the new sequence. The performance of the new sequence relative to the conventional SECSY sequence was shown by using an aqueous solution of main brain metabolites in a deshimmed magnetic field. Conclusion The results reveal that the new sequence provides an attractive way to eliminate the inhomogeneous spectral line broadening for the spin-echo correlated spectrum and is a promising tool for the study of metabolites in metabonomics, even for the applications on in vivo and in situ high-resolution 2D NMR spectroscopy. PMID:24392105

  2. Detecting wrong notes in advance: neuronal correlates of error monitoring in pianists.

    PubMed

    Ruiz, María Herrojo; Jabusch, Hans-Christian; Altenmüller, Eckart

    2009-11-01

    Music performance is an extremely rapid process with low incidence of errors even at the fast rates of production required. This is possible only due to the fast functioning of the self-monitoring system. Surprisingly, no specific data about error monitoring have been published in the music domain. Consequently, the present study investigated the electrophysiological correlates of executive control mechanisms, in particular error detection, during piano performance. Our target was to extend the previous research efforts on understanding of the human action-monitoring system by selecting a highly skilled multimodal task. Pianists had to retrieve memorized music pieces at a fast tempo in the presence or absence of auditory feedback. Our main interest was to study the interplay between auditory and sensorimotor information in the processes triggered by an erroneous action, considering only wrong pitches as errors. We found that around 70 ms prior to errors a negative component is elicited in the event-related potentials and is generated by the anterior cingulate cortex. Interestingly, this component was independent of the auditory feedback. However, the auditory information did modulate the processing of the errors after their execution, as reflected in a larger error positivity (Pe). Our data are interpreted within the context of feedforward models and the auditory-motor coupling. PMID:19276327

  3. A versatile software package for inter-subject correlation based analyses of fMRI

    PubMed Central

    Kauppi, Jukka-Pekka; Pajula, Juha; Tohka, Jussi

    2014-01-01

    In the inter-subject correlation (ISC) based analysis of the functional magnetic resonance imaging (fMRI) data, the extent of shared processing across subjects during the experiment is determined by calculating correlation coefficients between the fMRI time series of the subjects in the corresponding brain locations. This implies that ISC can be used to analyze fMRI data without explicitly modeling the stimulus and thus ISC is a potential method to analyze fMRI data acquired under complex naturalistic stimuli. Despite of the suitability of ISC based approach to analyze complex fMRI data, no generic software tools have been made available for this purpose, limiting a widespread use of ISC based analysis techniques among neuroimaging community. In this paper, we present a graphical user interface (GUI) based software package, ISC Toolbox, implemented in Matlab for computing various ISC based analyses. Many advanced computations such as comparison of ISCs between different stimuli, time window ISC, and inter-subject phase synchronization are supported by the toolbox. The analyses are coupled with re-sampling based statistical inference. The ISC based analyses are data and computation intensive and the ISC toolbox is equipped with mechanisms to execute the parallel computations in a cluster environment automatically and with an automatic detection of the cluster environment in use. Currently, SGE-based (Oracle Grid Engine, Son of a Grid Engine, or Open Grid Scheduler) and Slurm environments are supported. In this paper, we present a detailed account on the methods behind the ISC Toolbox, the implementation of the toolbox and demonstrate the possible use of the toolbox by summarizing selected example applications. We also report the computation time experiments both using a single desktop computer and two grid environments demonstrating that parallelization effectively reduces the computing time. The ISC Toolbox is available in https

  4. A versatile software package for inter-subject correlation based analyses of fMRI.

    PubMed

    Kauppi, Jukka-Pekka; Pajula, Juha; Tohka, Jussi

    2014-01-01

    In the inter-subject correlation (ISC) based analysis of the functional magnetic resonance imaging (fMRI) data, the extent of shared processing across subjects during the experiment is determined by calculating correlation coefficients between the fMRI time series of the subjects in the corresponding brain locations. This implies that ISC can be used to analyze fMRI data without explicitly modeling the stimulus and thus ISC is a potential method to analyze fMRI data acquired under complex naturalistic stimuli. Despite of the suitability of ISC based approach to analyze complex fMRI data, no generic software tools have been made available for this purpose, limiting a widespread use of ISC based analysis techniques among neuroimaging community. In this paper, we present a graphical user interface (GUI) based software package, ISC Toolbox, implemented in Matlab for computing various ISC based analyses. Many advanced computations such as comparison of ISCs between different stimuli, time window ISC, and inter-subject phase synchronization are supported by the toolbox. The analyses are coupled with re-sampling based statistical inference. The ISC based analyses are data and computation intensive and the ISC toolbox is equipped with mechanisms to execute the parallel computations in a cluster environment automatically and with an automatic detection of the cluster environment in use. Currently, SGE-based (Oracle Grid Engine, Son of a Grid Engine, or Open Grid Scheduler) and Slurm environments are supported. In this paper, we present a detailed account on the methods behind the ISC Toolbox, the implementation of the toolbox and demonstrate the possible use of the toolbox by summarizing selected example applications. We also report the computation time experiments both using a single desktop computer and two grid environments demonstrating that parallelization effectively reduces the computing time. The ISC Toolbox is available in https://code.google.com/p/isc-toolbox/

  5. Coupled-cluster based basis sets for valence correlation calculations

    NASA Astrophysics Data System (ADS)

    Claudino, Daniel; Gargano, Ricardo; Bartlett, Rodney J.

    2016-03-01

    Novel basis sets are generated that target the description of valence correlation in atoms H through Ar. The new contraction coefficients are obtained according to the Atomic Natural Orbital (ANO) procedure from CCSD(T) (coupled-cluster singles and doubles with perturbative triples correction) density matrices starting from the primitive functions of Dunning et al. [J. Chem. Phys. 90, 1007 (1989); ibid. 98, 1358 (1993); ibid. 100, 2975 (1993)] (correlation consistent polarized valence X-tuple zeta, cc-pVXZ). The exponents of the primitive Gaussian functions are subject to uniform scaling in order to ensure satisfaction of the virial theorem for the corresponding atoms. These new sets, named ANO-VT-XZ (Atomic Natural Orbital Virial Theorem X-tuple Zeta), have the same number of contracted functions as their cc-pVXZ counterparts in each subshell. The performance of these basis sets is assessed by the evaluation of the contraction errors in four distinct computations: correlation energies in atoms, probing the density in different regions of space via (-3 ≤ n ≤ 3) in atoms, correlation energies in diatomic molecules, and the quality of fitting potential energy curves as measured by spectroscopic constants. All energy calculations with ANO-VT-QZ have contraction errors within "chemical accuracy" of 1 kcal/mol, which is not true for cc-pVQZ, suggesting some improvement compared to the correlation consistent series of Dunning and co-workers.

  6. Coupled-cluster based basis sets for valence correlation calculations.

    PubMed

    Claudino, Daniel; Gargano, Ricardo; Bartlett, Rodney J

    2016-03-14

    Novel basis sets are generated that target the description of valence correlation in atoms H through Ar. The new contraction coefficients are obtained according to the Atomic Natural Orbital (ANO) procedure from CCSD(T) (coupled-cluster singles and doubles with perturbative triples correction) density matrices starting from the primitive functions of Dunning et al. [J. Chem. Phys. 90, 1007 (1989); ibid. 98, 1358 (1993); ibid. 100, 2975 (1993)] (correlation consistent polarized valence X-tuple zeta, cc-pVXZ). The exponents of the primitive Gaussian functions are subject to uniform scaling in order to ensure satisfaction of the virial theorem for the corresponding atoms. These new sets, named ANO-VT-XZ (Atomic Natural Orbital Virial Theorem X-tuple Zeta), have the same number of contracted functions as their cc-pVXZ counterparts in each subshell. The performance of these basis sets is assessed by the evaluation of the contraction errors in four distinct computations: correlation energies in atoms, probing the density in different regions of space via ⟨r(n)⟩ (-3 ≤ n ≤ 3) in atoms, correlation energies in diatomic molecules, and the quality of fitting potential energy curves as measured by spectroscopic constants. All energy calculations with ANO-VT-QZ have contraction errors within "chemical accuracy" of 1 kcal/mol, which is not true for cc-pVQZ, suggesting some improvement compared to the correlation consistent series of Dunning and co-workers.

  7. Coupled-cluster based basis sets for valence correlation calculations.

    PubMed

    Claudino, Daniel; Gargano, Ricardo; Bartlett, Rodney J

    2016-03-14

    Novel basis sets are generated that target the description of valence correlation in atoms H through Ar. The new contraction coefficients are obtained according to the Atomic Natural Orbital (ANO) procedure from CCSD(T) (coupled-cluster singles and doubles with perturbative triples correction) density matrices starting from the primitive functions of Dunning et al. [J. Chem. Phys. 90, 1007 (1989); ibid. 98, 1358 (1993); ibid. 100, 2975 (1993)] (correlation consistent polarized valence X-tuple zeta, cc-pVXZ). The exponents of the primitive Gaussian functions are subject to uniform scaling in order to ensure satisfaction of the virial theorem for the corresponding atoms. These new sets, named ANO-VT-XZ (Atomic Natural Orbital Virial Theorem X-tuple Zeta), have the same number of contracted functions as their cc-pVXZ counterparts in each subshell. The performance of these basis sets is assessed by the evaluation of the contraction errors in four distinct computations: correlation energies in atoms, probing the density in different regions of space via ⟨r(n)⟩ (-3 ≤ n ≤ 3) in atoms, correlation energies in diatomic molecules, and the quality of fitting potential energy curves as measured by spectroscopic constants. All energy calculations with ANO-VT-QZ have contraction errors within "chemical accuracy" of 1 kcal/mol, which is not true for cc-pVQZ, suggesting some improvement compared to the correlation consistent series of Dunning and co-workers. PMID:26979680

  8. A Multiscale Modeling Demonstration Based on the Pair Correlation Function

    SciTech Connect

    Gao, Carrie Y; Nicholson, Don M; Keffer, David; Edwards, Brian J

    2008-01-01

    For systems with interatomic interactions that are well described by pair-wise potentials, the pair correlation function provides a vehicle for passing information from the molecular level to the macroscopic level of description. In this work, we present a complete demonstration of the use of the pair correlation function to simulate a fluid at the molecular and macroscopic levels. At the molecular level, we describe a monatomic fluid using the Ornstein-Zernike integral equation theory closed with the Percus-Yevick approximation. We show that all of the required thermodynamic properties can be evaluated knowing the pair correlation function. At the macroscopic level, we perform a multiscale simulation with macroscopic evolution equations for the mass, momentum, temperature, and pair correlation function, using molecular-level simulation to provide the boundary conditions. We perform a self-consistency check by comparing the pair correlation function that evolved from the multiscale simulation with the one evaluated at the molecular-level; excellent agreement is achieved.

  9. Composite correlation filter for O-ring detection in stationary colored noise

    NASA Astrophysics Data System (ADS)

    Hassebrook, Laurence G.

    2009-04-01

    O-rings are regularly replaced in aircraft and if they are not replaced or if they are installed improperly, they can result in catastrophic failure of the aircraft. It is critical that the o-rings be packaged correctly to avoid mistakes made by technicians during routine maintenance. For this reason, fines may be imposed on the o-ring manufacturer if the o-rings are packaged incorrectly. That is, a single o-ring must be packaged and labeled properly. No o-rings or more than one o-ring per package is not acceptable. We present an industrial inspection system based on real-time composite correlation filtering that has successfully solved this problem in spite of opaque paper o-ring packages. We present the system design including the composite filter design.

  10. Estimation of shear viscosity based on transverse momentum correlations

    NASA Astrophysics Data System (ADS)

    STAR Collaboration; Sharma, Monika; STAR Collaboration

    2009-11-01

    Event anisotropy measurements at RHIC suggest the strongly interacting matter created in heavy ion collisions flows with very little shear viscosity. Precise determination of “shear viscosity-to-entropy” ratio is currently a subject of extensive study [S. Gavin and M. Abdel-Aziz, Phys. Rev. Lett. 97 (2006) 162302]. We present preliminary results of measurements of the evolution of transverse momentum correlation function with collision centrality of Au+Au interactions at s=200 GeV. We compare two differential correlation functions, namely inclusive [J. Adams et al. (STAR Collaboration), Phys. Rev. C 72 (2005) 044902] and a differential version of the correlation measure C˜ introduced by Gavin et al. [S. Gavin and M. Abdel-Aziz, Phys. Rev. Lett. 97 (2006) 162302; M. Sharma and C. A. Pruneau, Phys. Rev. C 79 (2009) 024905.]. These observables can be used for the experimental study of the shear viscosity per unit entropy.

  11. Memory detection 2.0: the first web-based memory detection test.

    PubMed

    Kleinberg, Bennett; Verschuere, Bruno

    2015-01-01

    There is accumulating evidence that reaction times (RTs) can be used to detect recognition of critical (e.g., crime) information. A limitation of this research base is its reliance upon small samples (average n = 24), and indications of publication bias. To advance RT-based memory detection, we report upon the development of the first web-based memory detection test. Participants in this research (Study1: n = 255; Study2: n = 262) tried to hide 2 high salient (birthday, country of origin) and 2 low salient (favourite colour, favourite animal) autobiographical details. RTs allowed to detect concealed autobiographical information, and this, as predicted, more successfully so than error rates, and for high salient than for low salient items. While much remains to be learned, memory detection 2.0 seems to offer an interesting new platform to efficiently and validly conduct RT-based memory detection research.

  12. Memory detection 2.0: the first web-based memory detection test.

    PubMed

    Kleinberg, Bennett; Verschuere, Bruno

    2015-01-01

    There is accumulating evidence that reaction times (RTs) can be used to detect recognition of critical (e.g., crime) information. A limitation of this research base is its reliance upon small samples (average n = 24), and indications of publication bias. To advance RT-based memory detection, we report upon the development of the first web-based memory detection test. Participants in this research (Study1: n = 255; Study2: n = 262) tried to hide 2 high salient (birthday, country of origin) and 2 low salient (favourite colour, favourite animal) autobiographical details. RTs allowed to detect concealed autobiographical information, and this, as predicted, more successfully so than error rates, and for high salient than for low salient items. While much remains to be learned, memory detection 2.0 seems to offer an interesting new platform to efficiently and validly conduct RT-based memory detection research. PMID:25874966

  13. Memory Detection 2.0: The First Web-Based Memory Detection Test

    PubMed Central

    Kleinberg, Bennett; Verschuere, Bruno

    2015-01-01

    There is accumulating evidence that reaction times (RTs) can be used to detect recognition of critical (e.g., crime) information. A limitation of this research base is its reliance upon small samples (average n = 24), and indications of publication bias. To advance RT-based memory detection, we report upon the development of the first web-based memory detection test. Participants in this research (Study1: n = 255; Study2: n = 262) tried to hide 2 high salient (birthday, country of origin) and 2 low salient (favourite colour, favourite animal) autobiographical details. RTs allowed to detect concealed autobiographical information, and this, as predicted, more successfully so than error rates, and for high salient than for low salient items. While much remains to be learned, memory detection 2.0 seems to offer an interesting new platform to efficiently and validly conduct RT-based memory detection research. PMID:25874966

  14. Sampling of general correlators in worm-algorithm based simulations

    NASA Astrophysics Data System (ADS)

    Rindlisbacher, Tobias; Åkerlund, Oscar; de Forcrand, Philippe

    2016-08-01

    Using the complex ϕ4-model as a prototype for a system which is simulated by a worm algorithm, we show that not only the charged correlator <ϕ* (x) ϕ (y) >, but also more general correlators such as < | ϕ (x) | | ϕ (y) | > or < arg ⁡ (ϕ (x)) arg ⁡ (ϕ (y)) >, as well as condensates like < | ϕ | >, can be measured at every step of the Monte Carlo evolution of the worm instead of on closed-worm configurations only. The method generalizes straightforwardly to other systems simulated by worms, such as spin or sigma models.

  15. A novel pitch evaluation of one-dimensional gratings based on a cross-correlation filter

    NASA Astrophysics Data System (ADS)

    Chen, Xiaomei; Koenders, Ludger

    2014-04-01

    If one-dimensional (1D), p-period and arbitrarily structured grating position-related topographical signals coexist with noise, it is difficult to evaluate the pitch practically using the center-of-gravity (CG) method. The Fourier-transform-based (FT) method is the most precise to evaluate pitches; nevertheless, it cannot give the uniformity of pitches. If a cross-correlation filter—a half period of sinusoidal waveform sequence (pT period), cross-correlates with the signals, the noise can be eliminated if pT ≈ p. After cross-correlation filtering, the distance between any two adjacent waveform peaks along the direction perpendicular to 1D grating lines is one pitch value. The pitch evaluation based on the cross-correlation filtering together with the detection of the peak's position is described as the peak detection (PD) method in this paper. The pitch average and uniformity can be calculated by using the PD method. The computer simulation has indicated that the average of pitch deviations from the true pitch and the pitch variations are less than 0.2% and 0.2% for the sinusoidal and rectangular waveform signals with up to 50% uniform white noise, less than 0.1% and 1% for the sinusoidal and rectangular waveform signals and 0.6% and 2.5% for the triangular waveform signal if three waveform signals are mixed with Gaussian white, binomial and Bernoulli noise up to 50% in standard deviation, one probability and trial probability, respectively. As examples, a highly oriented pyrolytic graphite (HOPG) with a 0.246 nm distance between second nearest neighbour atoms and a 1D grating with 3000 nm nominal pitch are measured by a ultra-high vacuum scanning tunneling microscope (UHV STM) and a metrological atomic force microscope (AFM), respectively. After the position-related topographical signals are cross-correlation filtered, the 0.240 and 3004.11 nm pitches calculated by using the PD method are very close to the 0.240 and 3003.34 nm results evaluated by the FT

  16. An Immunity-Based Anomaly Detection System with Sensor Agents

    PubMed Central

    Okamoto, Takeshi; Ishida, Yoshiteru

    2009-01-01

    This paper proposes an immunity-based anomaly detection system with sensor agents based on the specificity and diversity of the immune system. Each agent is specialized to react to the behavior of a specific user. Multiple diverse agents decide whether the behavior is normal or abnormal. Conventional systems have used only a single sensor to detect anomalies, while the immunity-based system makes use of multiple sensors, which leads to improvements in detection accuracy. In addition, we propose an evaluation framework for the anomaly detection system, which is capable of evaluating the differences in detection accuracy between internal and external anomalies. This paper focuses on anomaly detection in user's command sequences on UNIX-like systems. In experiments, the immunity-based system outperformed some of the best conventional systems. PMID:22291560

  17. Fire flame detection based on GICA and target tracking

    NASA Astrophysics Data System (ADS)

    Rong, Jianzhong; Zhou, Dechuang; Yao, Wei; Gao, Wei; Chen, Juan; Wang, Jian

    2013-04-01

    To improve the video fire detection rate, a robust fire detection algorithm based on the color, motion and pattern characteristics of fire targets was proposed, which proved a satisfactory fire detection rate for different fire scenes. In this fire detection algorithm: (a) a rule-based generic color model was developed based on analysis on a large quantity of flame pixels; (b) from the traditional GICA (Geometrical Independent Component Analysis) model, a Cumulative Geometrical Independent Component Analysis (C-GICA) model was developed for motion detection without static background and (c) a BP neural network fire recognition model based on multi-features of the fire pattern was developed. Fire detection tests on benchmark fire video clips of different scenes have shown the robustness, accuracy and fast-response of the algorithm.

  18. Clustering and information in correlation based financial networks

    NASA Astrophysics Data System (ADS)

    Onnela, J.-P.; Kaski, K.; Kertész, J.

    2004-03-01

    Networks of companies can be constructed by using return correlations. A crucial issue in this approach is to select the relevant correlations from the correlation matrix. In order to study this problem, we start from an empty graph with no edges where the vertices correspond to stocks. Then, one by one, we insert edges between the vertices according to the rank of their correlation strength, resulting in a network called asset graph. We study its properties, such as topologically different growth types, number and size of clusters and clustering coefficient. These properties, calculated from empirical data, are compared against those of a random graph. The growth of the graph can be classified according to the topological role of the newly inserted edge. We find that the type of growth which is responsible for creating cycles in the graph sets in much earlier for the empirical asset graph than for the random graph, and thus reflects the high degree of networking present in the market. We also find the number of clusters in the random graph to be one order of magnitude higher than for the asset graph. At a critical threshold, the random graph undergoes a radical change in topology related to percolation transition and forms a single giant cluster, a phenomenon which is not observed for the asset graph. Differences in mean clustering coefficient lead us to conclude that most information is contained roughly within 10% of the edges.

  19. Neural Correlates of Familiarity-Based Associative Retrieval

    ERIC Educational Resources Information Center

    Ford, Jaclyn Hennessey; Verfaellie, Mieke; Giovanello, Kelly S.

    2010-01-01

    The current study compared the neural correlates of associative retrieval of compound (unitized) stimuli and unrelated (non-unitized) stimuli. Although associative recognition was nearly identical for compounds and unrelated pairs, accurate recognition of these different pair types was associated with activation in distinct regions within the…

  20. Automatic background updating for video-based vehicle detection

    NASA Astrophysics Data System (ADS)

    Hu, Chunhai; Li, Dongmei; Liu, Jichuan

    2008-03-01

    Video-based vehicle detection is one of the most valuable techniques for the Intelligent Transportation System (ITS). The widely used video-based vehicle detection technique is the background subtraction method. The key problem of this method is how to subtract and update the background effectively. In this paper an efficient background updating scheme based on Zone-Distribution for vehicle detection is proposed to resolve the problems caused by sudden camera perturbation, sudden or gradual illumination change and the sleeping person problem. The proposed scheme is robust and fast enough to satisfy the real-time constraints of vehicle detection.

  1. Eggshell defects detection based on color processing

    NASA Astrophysics Data System (ADS)

    Garcia-Alegre, Maria C.; Ribeiro, Angela; Guinea, Domingo; Cristobal, Gabriel

    2000-03-01

    The automatic classification of defective eggs constitutes a fundamental issue at the poultry industry for both economical and sanitary reasons. The early separation of eggs with spots and cracks is a relevant task as the stains can leak while progressing on the conveyor-belts, degrading all the mechanical parts. Present work is focused on the implementation of an artificial vision system for detecting in real time defective eggs at the poultry farm. First step of the algorithmic process is devoted to the detection of the egg shape to fix the region of interest. A color processing is then performed only on the eggshell to obtain an image segmentation that allows the discrimination of defective eggs from clean ones in critic time. The results are presented to demonstrate the validity of the proposed visual process on a wide sample of both defective and non-defective eggs.

  2. Daytime Water Detection Based on Color Variation

    NASA Technical Reports Server (NTRS)

    Rankin, Arturo L.; Matthies, Larry H.

    2010-01-01

    Robust water detection is a critical perception requirement for unmanned ground vehicle (UGV) autonomous navigation. This is particularly true in wide open areas where water can collect in naturally occurring terrain depressions during periods of heavy precipitation and form large water bodies (such as ponds). At far range, reflections of the sky provide a strong cue for water. But at close range, the color coming out of a water body dominates sky reflections and the water cue from sky reflections is of marginal use. We model this behavior by using water body intensity data from multiple frames of RGB imagery to estimate the total reflection coefficient contribution from surface reflections and the combination of all other factors. Then we describe an algorithm that uses one of the color cameras in a forward- looking, UGV-mounted stereo-vision perception system to detect water bodies in wide open areas. This detector exploits the knowledge that the change in saturation-to-brightness ratio across a water body from the leading to trailing edge is uniform and distinct from other terrain types. In test sequences approaching a pond under clear, overcast, and cloudy sky conditions, the true positive and false negative water detection rates were (95.76%, 96.71%, 98.77%) and (0.45%, 0.60%, 0.62%), respectively. This software has been integrated on an experimental unmanned vehicle and field tested at Ft. Indiantown Gap, PA.

  3. Vibration-Based Damage Detection in Rotating Machinery

    SciTech Connect

    Farrar, C.R.; Duffey, T.A.

    1999-06-28

    Damage detection as determined from changes in the vibration characteristics of a system has been a popular research topic for the last thirty years. Numerous damage identification algorithms have been proposed for detecting and locating damage in structural and mechanical systems. To date, these damage-detection methods have shown mixed results. A particular application of vibration-based damage detection that has perhaps enjoyed the greatest success is that of damage detection in rotating machinery. This paper summarizes the state of technology in vibration-based damage detection applied to rotating machinery. The review interprets the damage detection process in terms of a statistical pattern recognition paradigm that encompasses all vibration-based damage detection methods and applications. The motivation for the study reported herein is to identify the reasons that vibration-based damage detection has been successfully applied to rotating machinery, but has yet to show robust applications to civil engineering infrastructure. The paper concludes by comparing and contrasting the vibration-based damage detection applied to rotating machinery with large civil engineering infrastructure applications.

  4. Automatic hearing loss detection system based on auditory brainstem response

    NASA Astrophysics Data System (ADS)

    Aldonate, J.; Mercuri, C.; Reta, J.; Biurrun, J.; Bonell, C.; Gentiletti, G.; Escobar, S.; Acevedo, R.

    2007-11-01

    Hearing loss is one of the pathologies with the highest prevalence in newborns. If it is not detected in time, it can affect the nervous system and cause problems in speech, language and cognitive development. The recommended methods for early detection are based on otoacoustic emissions (OAE) and/or auditory brainstem response (ABR). In this work, the design and implementation of an automated system based on ABR to detect hearing loss in newborns is presented. Preliminary evaluation in adults was satisfactory.

  5. Experimental damage detection in a wind turbine blade model using principal components of response correlation functions

    NASA Astrophysics Data System (ADS)

    Hoell, S.; Omenzetter, P.

    2015-07-01

    The utilization of vibration signals for structural damage detection (SDD) is appealing due to the strong theoretical foundation of such approaches, ease of data acquisition and processing efficiency. Different methods are available for defining damage sensitive features (DSFs) based on vibrations, such as modal analysis or time series methods. The present paper proposes the use of partial autocorrelation coefficients of acceleration responses as DSFs. Principal component (PC) analysis is used to transform the initial DSFs to scores. The resulting scores from the healthy and damaged states are used to select the PCs which are most sensitive to damage. These are then used for making decisions about the structural state by means of statistical hypothesis testing conducted on the scores. The approach is applied to experiments with a laboratory scale wind turbine blade (WTB) made of glass-fibre reinforced epoxy composite. Damage is non-destructively simulated by attaching small masses and the WTB is excited with the help of an electrodynamic shaker using band-limited white noise. The SDD results for the selected subsets of PCs show a clear improvement of the detectability of early damages compared to other DSF selections.

  6. Hypervelocity dust impacts on the Wind spacecraft: Correlations between Ulysses and Wind interstellar dust detections

    NASA Astrophysics Data System (ADS)

    Wood, S. R.; Malaspina, David M.; Andersson, Laila; Horanyi, Mihaly

    2015-09-01

    The Wind spacecraft is positioned just sunward of Earth at the first Lagrange point, while the Ulysses spacecraft orbits above and below the ecliptic plane crossing the ecliptic as far from the Sun as the orbit of Jupiter (˜5 AU). While Wind does not carry a dedicated dust detector, we demonstrate the ability of Wind electric field measurements to detect hypervelocity dust impacts through their impact plasma signatures. Interstellar dust (ISD) and interplanetary dust particles are differentiated based on a yearly modulation of the ISD flux. Measurements of ISD flux variation by Wind are found to be in good agreement with ISD flux variation measured by Ulysses. While measurements of the ISD flow direction through the Solar System determined by Wind could not be directly compared to those from Ulysses, strong variation in ISD flow direction was observed during similar time periods by both spacecraft.

  7. Biclustering of Gene Expression Data by Correlation-Based Scatter Search

    PubMed Central

    2011-01-01

    Background The analysis of data generated by microarray technology is very useful to understand how the genetic information becomes functional gene products. Biclustering algorithms can determine a group of genes which are co-expressed under a set of experimental conditions. Recently, new biclustering methods based on metaheuristics have been proposed. Most of them use the Mean Squared Residue as merit function but interesting and relevant patterns from a biological point of view such as shifting and scaling patterns may not be detected using this measure. However, it is important to discover this type of patterns since commonly the genes can present a similar behavior although their expression levels vary in different ranges or magnitudes. Methods Scatter Search is an evolutionary technique that is based on the evolution of a small set of solutions which are chosen according to quality and diversity criteria. This paper presents a Scatter Search with the aim of finding biclusters from gene expression data. In this algorithm the proposed fitness function is based on the linear correlation among genes to detect shifting and scaling patterns from genes and an improvement method is included in order to select just positively correlated genes. Results The proposed algorithm has been tested with three real data sets such as Yeast Cell Cycle dataset, human B-cells lymphoma dataset and Yeast Stress dataset, finding a remarkable number of biclusters with shifting and scaling patterns. In addition, the performance of the proposed method and fitness function are compared to that of CC, OPSM, ISA, BiMax, xMotifs and Samba using Gene the Ontology Database. PMID:21261986

  8. Neutron Detection with Water Cerenkov Based Detectors

    SciTech Connect

    Dazeley, S; Bernstein, A; Bowden, N; Carr, D; Ouedraogo, S; Svoboda, R; Sweany, M; Tripathi, M

    2009-05-13

    Legitimate cross border trade involves the transport of an enormous number of cargo containers. Especially following the September 11 attacks, it has become an international priority to verify that these containers are not transporting Special Nuclear Material (SNM) without impeding legitimate trade. Fission events from SNM produce a number of neutrons and MeV-scale gammas correlated in time. The observation of consistent time correlations between neutrons and gammas emitted from a cargo container could, therefore, constitute a robust signature for SNM, since this time coincident signature stands out strongly against the higher rate of uncorrelated gamma-ray backgrounds from the local environment. We are developing a cost effective way to build very large neutron detectors for this purpose. We have recently completed the construction of two new water Cherenkov detectors, a 250 liter prototype and a new 4 ton detector. We present both the results from our prototype detector and an update on the newly commissioned large detector. We will also present pictures from the construction and outline our future detector development plans.

  9. Preliminary measurement results of biotinylated BSA detection of a low cost optical cavity based biosensor using differential detection

    NASA Astrophysics Data System (ADS)

    Cowles, Peter; Joy, Cody; Bujana, Antonio; Rho, DongGee; Kim, Seunghyun

    2016-03-01

    We report an optical cavity based biosensor using a novel differential detection method for point-of-care applications. Two laser diodes allow for multiplexing capability along with the ability to enhance the responsivity using differential detection. The laser wavelengths are chosen so that the optical intensities of two lasers change monotonically with opposite slopes upon the adsorption of desired biomarkers. The cavity width, PMMA thickness, and silver thickness have been optimized to achieve a large change in scaled differential value. We chose biotinylated BSA detection with Avidin as a receptor molecule to demonstrate the proposed design. Avidin is attached directly to the PMMA layer by physisorption. Then, biotinylated BSA is introduced to the sample and the intensities of the laser diodes are measured by a sCMOS camera. A change in the scaled differential value will correlate to the binding of biotinylated BSA. In this presentation, we will discuss simulation results, fabrication procedures, and preliminary measurement results.

  10. Sensitive and bidirectional detection of urine telomerase based on the four detection-color states of difunctional gold nanoparticle probe.

    PubMed

    Duan, Ruixue; Wang, Boya; Zhang, Tianchi; Zhang, Zhenyu; Xu, Shaofang; Chen, Zhifei; Lou, Xiaoding; Xia, Fan

    2014-10-01

    Telomerase, a valuable biomarker, is highly correlated with the development of most of human cancers. Here, we develop a bidirectional strategy for telomerase activity detection and bladder cancer diagnosis based on four detection-color states of difunctional gold nanoparticle (GNP) probes such as blue, purple, red, and precipitate. Specifically, we define the red GNP probe as origin, which represents urine extracts with inactive telomerase and implies normal individuals. The forward direction is corresponding to the detection of a relatively high concentration of active telomerase, in which system GNP probes assemble obviously and precipitate, predicting bladder cancer samples. The negative direction is corresponding to extracts with a relatively low concentration (purple) and without any telomerase (blue), which can be differentiated by naked eyes or UV-vis spectrum, indicating bladder cancer and normal individuals, respectively. More importantly, this noninvasive strategy shows great sensitivity and selectivity when tested by 18 urine specimens from bladder cancer patients, inflammation, and normal individuals.

  11. Laser-scanning Doppler photoacoustic microscopy based on temporal correlation

    PubMed Central

    Song, Wei; Liu, Wenzhong; Zhang, Hao F.

    2013-01-01

    We present a methodology to measure absolute flow velocity using laser-scanning photoacoustic microscopy. To obtain the Doppler angle, the angle between ultrasonic detection axis and flow direction, we extracted the distances between the transducer and three adjacent scanning points along the flow and repeatedly applied the law of cosines. To measure flow velocity along the ultrasonic detection axis, we calculated the time shift between two consecutive photoacoustic waves at the same scanning point, then converted the time shift to velocity according to the sound velocity and time interval between two laser illuminations. We verified our method by imaging flow phantoms. PMID:23825803

  12. Immunohistochemical detection of p53 in Wilms' tumors correlates with unfavorable outcome.

    PubMed Central

    Lahoti, C.; Thorner, P.; Malkin, D.; Yeger, H.

    1996-01-01

    The role of p53 in the pathogenesis and progression of Wilms' tumors is only partly understood. Although p53 mutations were initially reported only in anaplastic Wilms' tumors, we had reported that, of two of twenty-one cases that had a p53 mutation, one tumor showed no evidence of anaplasia. To determine the significance of p53 expression in all clinical stages of Wilms' tumor, twenty-eight cases were analyzed for p53 immunoreactivity. Paraffin sections were immunolabeled with two different monoclonal antibodies, recognizing both mutant and wild-type p53. Fifteen of sixteen tumors in the recurrent/metastatic group and three of twelve tumors in the nonmetastatic/nonrecurrent group showed p53 immunopositivity. Only one of three positive tumors in the latter group showed moderate to strong positivity, whereas twelve of sixteen metastatic/recurrent tumors revealed a similar degree of p53 positivity. The positivity was stronger in the metastasis/recurrences as compared with the corresponding primary tumor. Western blot analysis revealed p53 expression in all of the Wilms' tumors tested, suggesting its involvement in the development of Wilms' tumors. Single-strand conformation polymorphism analysis performed on twenty-three of these tumors revealed p53 mutations in four of fourteen recurrent/metastatic tumors and none in the nonmetastatic/nonrecurrent group. Our results show that, whereas 60% of cases were immunopositive for p53 protein, mutations were detected in only 16% of tumors, indicating that wild-type p53 protein is retained in the other tumors. We conclude that p53 immunopositivity strongly correlates with recurrence/metastasis in Wilms' tumors. Furthermore, the accumulation of p53 in these tumors is not only due to mutations but may also involve stabilization of normal p53 with other proteins. Images Figure 1 Figure 2 Figure 3 PMID:8623926

  13. Color night vision method based on the correlation between natural color and dual band night image

    NASA Astrophysics Data System (ADS)

    Zhang, Yi; Bai, Lian-fa; Zhang, Chuang; Chen, Qian; Gu, Guo-hua

    2009-07-01

    Color night vision technology can effectively improve the detection and identification probability. Current color night vision method based on gray scale modulation fusion, spectrum field fusion, special component fusion and world famous NRL method, TNO method will bring about serious color distortion, and the observers will be visual tired after long time observation. Alexander Toet of TNO Human Factors presents a method to fuse multiband night image a natural day time color appearance, but it need the true color image of the scene to be observed. In this paper we put forward a color night vision method based on the correlation between natural color image and dual band night image. Color display is attained through dual-band low light level images and their fusion image. Actual color image of the similar scene is needed to obtain color night vision image, the actual color image is decomposed to three gray-scale images of RGB color module, and the short wave LLL image, long wave LLL image and their fusion image are compared to them through gray-scale spatial correlation method, and the color space mapping scheme is confirmed by correlation. Gray-scale LLL images and their fusion image are adjusted through the variation of HSI color space coefficient, and the coefficient matrix is built. Color display coefficient matrix of LLL night vision system is obtained by multiplying the above coefficient matrix and RGB color space mapping matrix. Emulation experiments on general scene dual-band color night vision indicate that the color display effect is approving. This method was experimented on dual channel dual spectrum LLL color night vision experimental apparatus based on Texas Instruments digital video processing device DM642.

  14. Familial correlations of HDL subclasses based on gradient gel electrophoresis.

    PubMed

    Williams, P T; Vranizan, K M; Austin, M A; Krauss, R M

    1992-12-01

    We used nondenaturing polyacrylamide gradient gel electrophoresis to examine the familial correlations of high density lipoprotein (HDL) subclasses for 150 offspring in 47 nuclear families. The absorbance of protein stain was used as an index of mass concentrations at intervals of 0.01 nm within five HDL subclasses: HDL3c (7.2-7.8 nm), HDL3b (7.8-8.2 nm), HDL3a (8.2-8.8 nm), HDL2a (8.8-9.7 nm), and HDL2b (9.7-12 nm). Parent-offspring correlations were computed for two different characterizations of the parents: 1) by sex (i.e., mother versus father) and 2) by their relative values (highest versus lowest HDL). Sibling resemblance was assessed by using the intraclass correlations coefficient. Family members were significantly related for the following subclasses: HDL3c (sibling and father-offspring), HDL3b (sibling), HDL3a (sibling and mother-offspring), HDL2a (mother-offspring), and HDL2b (sibling, father-offspring, and mother-offspring). The offsprings' HDL3c and HDL2b values were more strongly related to their fathers' than to their mothers' values, whereas their HDL2a levels were more strongly related to their mothers' than their fathers' values. In addition, fathers' HDL2b levels were inversely correlated with the offsprings' HDL3b. The parents' HDL subclass levels were more strongly related to subclass levels of their younger (< or = 20 years) than their older offspring. Among all subclasses, HDL2b showed the strongest parent-offspring relation, with the parents' HDL values accounting for over 30% of the variance in offsprings' HDL2b.(ABSTRACT TRUNCATED AT 250 WORDS)

  15. Real-Time Optical Correlator Based On GaAs

    NASA Technical Reports Server (NTRS)

    Liu, Tsuen-Hsi; Cheng, Li-Jen

    1992-01-01

    Apparatus performs correlation between input image and reference image in real time by means of degenerate four-wave mixing in photorefractive crystal, which serves as real-time holographic medium. Gallium arsenide chosen to be photorefractive material in this application because at frame rate and level of illumination used in experiments, offers adequate diffraction efficiency. Frame rates as high as 1,000 s to negative 1st power achievable.

  16. A spatial-correlation analysis of the cubic 3-torus topology based on the Planck 2013 data

    NASA Astrophysics Data System (ADS)

    Aurich, R.

    2015-09-01

    Spatial correlations of the cubic 3-torus topology are analysed using the Planck 2013 data. The spatial-correlation method for detecting multiply connected spaces is based on the fact that positions on the cosmic microwave background (CMB) sky, that are separated by large angular distances, can be spatially much nearer according to a hypothesized topology. The comparison of the correlations computed with and without the assumed topology can reveal whether a promising topological candidate is found. The level of the expected correlations is estimated by CMB simulations of the cubic 3-torus topology and compared to those obtained from the Planck data. An interesting 3-torus configuration is discovered which possesses topological correlations of the magnitude found in the CMB simulations based on a toroidal universe. Although the spatial-correlation method has a high false-positive rate, it is striking that there exists an orientation of a cubic 3-torus cell, where correlations between points that are separated by large angular distances, mimic those of closely separated points.

  17. Correlation-timing-based erythrocyte velocity measurement using CCD imagery

    NASA Astrophysics Data System (ADS)

    O'Reilly, William J.; Hudetz, Anthony

    2001-05-01

    An automated correlation method is introduced to estimate erythrocyte velocity component of erythrocyte flux within the cerebral capillary network. Erythrocyte flux, defined as the number of red blood cells passing through a plane orthogonal to the axis of erythrocyte flow in a vessel per unit time, is considered to be the closest index of capillary flow. Introduced previously is the two-point cross-correlation method, a method whereby a video photometric analyzer captures the voltage produced from two electronic windows placed over a vessel of interest. In our new method, instead of using electronic windows, we use a CCD array, focused on a two- dimensional projection of the three-dimensional capillary structure. Simulations of this method yields accurate velocity measurements at a measured cell intensity of .2 standard deviations above mean noise values or cell counts fewer than 30 cells per minute for image sequences of 180 frames captured over a time interval of three seconds. We conclude that with proper reduction in the measured standard deviation of noise and by increasing the percentage of fluorscently labeled erythrocytes injected into the rat, the correlation timing method of estimating erythrocyte velocity is an accurate substitute for hand-measured velocity calculation.

  18. Accelerometry-based home monitoring for detection of nocturnal hypermotor seizures based on novelty detection.

    PubMed

    Cuppens, Kris; Karsmakers, Peter; Van de Vel, Anouk; Bonroy, Bert; Milosevic, Milica; Luca, Stijn; Croonenborghs, Tom; Ceulemans, Berten; Lagae, Lieven; Van Huffel, Sabine; Vanrumste, Bart

    2014-05-01

    Nocturnal home monitoring of epileptic children is often not feasible due to the cumbersome manner of seizure monitoring with the standard method of video/EEG-monitoring. We propose a method for hypermotor seizure detection based on accelerometers attached to the extremities. From the acceleration signals, multiple temporal, frequency, and wavelet-based features are extracted. After determining the features with the highest discriminative power, we classify movement events in epileptic and nonepileptic movements. This classification is only based on a nonparametric estimate of the probability density function of normal movements. Such approach allows us to build patient-specific models to classify movement data without the need for seizure data that are rarely available. If, in the test phase, the probability of a data point (event) is lower than a threshold, this event is considered to be an epileptic seizure; otherwise, it is considered as a normal nocturnal movement event. The mean performance over seven patients gives a sensitivity of 95.24% and a positive predictive value of 60.04%. However, there is a noticeable interpatient difference. PMID:24122607

  19. A Vehicle Detection Algorithm Based on Deep Belief Network

    PubMed Central

    Cai, Yingfeng; Chen, Long

    2014-01-01

    Vision based vehicle detection is a critical technology that plays an important role in not only vehicle active safety but also road video surveillance application. Traditional shallow model based vehicle detection algorithm still cannot meet the requirement of accurate vehicle detection in these applications. In this work, a novel deep learning based vehicle detection algorithm with 2D deep belief network (2D-DBN) is proposed. In the algorithm, the proposed 2D-DBN architecture uses second-order planes instead of first-order vector as input and uses bilinear projection for retaining discriminative information so as to determine the size of the deep architecture which enhances the success rate of vehicle detection. On-road experimental results demonstrate that the algorithm performs better than state-of-the-art vehicle detection algorithm in testing data sets. PMID:24959617

  20. A novel way to detect correlations on multi-time scales, with temporal evolution and for multi-variables

    PubMed Central

    Yuan, Naiming; Xoplaki, Elena; Zhu, Congwen; Luterbacher, Juerg

    2016-01-01

    In this paper, two new methods, Temporal evolution of Detrended Cross-Correlation Analysis (TDCCA) and Temporal evolution of Detrended Partial-Cross-Correlation Analysis (TDPCCA), are proposed by generalizing DCCA and DPCCA. Applying TDCCA/TDPCCA, it is possible to study correlations on multi-time scales and over different periods. To illustrate their properties, we used two climatological examples: i) Global Sea Level (GSL) versus North Atlantic Oscillation (NAO); and ii) Summer Rainfall over Yangtze River (SRYR) versus previous winter Pacific Decadal Oscillation (PDO). We find significant correlations between GSL and NAO on time scales of 60 to 140 years, but the correlations are non-significant between 1865–1875. As for SRYR and PDO, significant correlations are found on time scales of 30 to 35 years, but the correlations are more pronounced during the recent 30 years. By combining TDCCA/TDPCCA and DCCA/DPCCA, we proposed a new correlation-detection system, which compared to traditional methods, can objectively show how two time series are related (on which time scale, during which time period). These are important not only for diagnosis of complex system, but also for better designs of prediction models. Therefore, the new methods offer new opportunities for applications in natural sciences, such as ecology, economy, sociology and other research fields. PMID:27293028

  1. A novel way to detect correlations on multi-time scales, with temporal evolution and for multi-variables

    NASA Astrophysics Data System (ADS)

    Yuan, Naiming; Xoplaki, Elena; Zhu, Congwen; Luterbacher, Juerg

    2016-06-01

    In this paper, two new methods, Temporal evolution of Detrended Cross-Correlation Analysis (TDCCA) and Temporal evolution of Detrended Partial-Cross-Correlation Analysis (TDPCCA), are proposed by generalizing DCCA and DPCCA. Applying TDCCA/TDPCCA, it is possible to study correlations on multi-time scales and over different periods. To illustrate their properties, we used two climatological examples: i) Global Sea Level (GSL) versus North Atlantic Oscillation (NAO); and ii) Summer Rainfall over Yangtze River (SRYR) versus previous winter Pacific Decadal Oscillation (PDO). We find significant correlations between GSL and NAO on time scales of 60 to 140 years, but the correlations are non-significant between 1865–1875. As for SRYR and PDO, significant correlations are found on time scales of 30 to 35 years, but the correlations are more pronounced during the recent 30 years. By combining TDCCA/TDPCCA and DCCA/DPCCA, we proposed a new correlation-detection system, which compared to traditional methods, can objectively show how two time series are related (on which time scale, during which time period). These are important not only for diagnosis of complex system, but also for better designs of prediction models. Therefore, the new methods offer new opportunities for applications in natural sciences, such as ecology, economy, sociology and other research fields.

  2. Combining satellite-based fire observations and ground-based lightning detections to identify lightning fires across the conterminous USA

    USGS Publications Warehouse

    Bar-Massada, A.; Hawbaker, T.J.; Stewart, S.I.; Radeloff, V.C.

    2012-01-01

    Lightning fires are a common natural disturbance in North America, and account for the largest proportion of the area burned by wildfires each year. Yet, the spatiotemporal patterns of lightning fires in the conterminous US are not well understood due to limitations of existing fire databases. Our goal here was to develop and test an algorithm that combined MODIS fire detections with lightning detections from the National Lightning Detection Network to identify lightning fires across the conterminous US from 2000 to 2008. The algorithm searches for spatiotemporal conjunctions of MODIS fire clusters and NLDN detected lightning strikes, given a spatiotemporal lag between lightning strike and fire ignition. The algorithm revealed distinctive spatial patterns of lightning fires in the conterminous US While a sensitivity analysis revealed that the algorithm is highly sensitive to the two thresholds that are used to determine conjunction, the density of fires it detected was moderately correlated with ground based fire records. When only fires larger than 0.4 km2 were considered, correlations were higher and the root-mean-square error between datasets was less than five fires per 625 km2 for the entire study period. Our algorithm is thus suitable for detecting broad scale spatial patterns of lightning fire occurrence, and especially lightning fire hotspots, but has limited detection capability of smaller fires because these cannot be consistently detected by MODIS. These results may enhance our understanding of large scale patterns of lightning fire activity, and can be used to identify the broad scale factors controlling fire occurrence.

  3. Nanoparticle-based detection and quantification of DNA with single nucleotide polymorphism (SNP) discrimination selectivity

    PubMed Central

    Qin, Wei Jie; Yung, Lin Yue Lanry

    2007-01-01

    Sequence-specific DNA detection is important in various biomedical applications such as gene expression profiling, disease diagnosis and treatment, drug discovery and forensic analysis. Here we report a gold nanoparticle-based method that allows DNA detection and quantification and is capable of single nucleotide polymorphism (SNP) discrimination. The precise quantification of single-stranded DNA is due to the formation of defined nanoparticle-DNA conjugate groupings in the presence of target/linker DNA. Conjugate groupings were characterized and quantified by gel electrophoresis. A linear correlation between the amount of target DNA and conjugate groupings was found. For SNP detection, single base mismatch discrimination was achieved for both the end- and center-base mismatch. The method described here may be useful for the development of a simple and quantitative DNA detection assay. PMID:17720714

  4. Towards aerial natural gas leak detection system based on TDLAS

    NASA Astrophysics Data System (ADS)

    Liu, Shuyang; Zhou, Tao; Jia, Xiaodong

    2014-11-01

    Pipeline leakage is a complex scenario for sensing system due to the traditional high cost, low efficient and labor intensive detection scheme. TDLAS has been widely accepted as industrial trace gas detection method and, thanks to its high accuracy and reasonable size, it has the potential to meet pipeline gas leakage detection requirements if it combines with the aerial platform. Based on literature study, this paper discussed the possibility of applying aerial TDLAS principle in pipeline gas leak detection and the key technical foundation of implementing it. Such system is able to result in a high efficiency and accuracy measurement which will provide sufficient data in time for the pipeline leakage detection.

  5. Defects' geometric feature recognition based on infrared image edge detection

    NASA Astrophysics Data System (ADS)

    Junyan, Liu; Qingju, Tang; Yang, Wang; Yumei, Lu; Zhiping, Zhang

    2014-11-01

    Edge detection is an important technology in image segmentation, feature extraction and other digital image processing areas. Boundary contains a wealth of information in the image, so to extract defects' edges in infrared images effectively enables the identification of defects' geometric features. This paper analyzed the detection effect of classic edge detection operators, and proposed fuzzy C-means (FCM) clustering-Canny operator algorithm to achieve defects' edges in the infrared images. Results show that the proposed algorithm has better effect than the classic edge detection operators, which can identify the defects' geometric feature much more completely and clearly. The defects' diameters have been calculated based on the image edge detection results.

  6. Proton-detected heteronuclear single quantum correlation NMR spectroscopy in rigid solids with ultra-fast MAS

    PubMed Central

    Holland, Gregory P.; Cherry, Brian R.; Jenkins, Janelle E.; Yarger, Jeffery L.

    2009-01-01

    In this article, we show the potential for utilizing proton-detected heteronuclear single quantum correlation (HSQC) NMR in rigid solids under ultra-fast magic angle spinning (MAS) conditions. The indirect detection of carbon-13 from coupled neighboring hydrogen nuclei provides a sensitivity enhancement of 3 - 4 fold in crystalline amino acids over direct-detected versions. Furthermore, the sensitivity enhancement is shown to be significantly larger for disordered solids that display inhomogeneously broadened carbon-13 spectra. Latrodectus hesperus (Black Widow) dragline silk is given as an example where the sample is mass-limited and the sensitivity enhancement for the proton-detected experiment is 8 - 13 fold. The ultra-fast MAS proton-detected HSQC solid-state NMR technique has the added advantage that no proton homonuclear decoupling is applied during the experiment. Further, well-resolved, indirectly observed carbon-13 spectra can be obtained in some cases without heteronuclear proton decoupling. PMID:19857977

  7. Large range rotation distortion measurement for remote sensing images based on volume holographic optical correlator

    NASA Astrophysics Data System (ADS)

    Zheng, Tianxiang; Cao, Liangcai; Zhao, Tian; He, Qingsheng; Jin, Guofan

    2012-10-01

    Volume holographic optical correlator can compute the correlation results between images at a super-high speed. In the application of remote imaging processing such as scene matching, 6,000 template images have been angularly multiplexed in the photorefractive crystal and the 6,000 parallel processing channels are achieved. In order to detect the correlation pattern of images precisely and distinguishingly, an on-off pixel inverted technology of images is proposed. It can fully use the CCD's linear range for detection and expand the normalized correlation value differences as the target image rotates. Due to the natural characteristics of the remote sensing images, the statistical formulas between the rotation distortions and the correlation results can be estimated. The rotation distortion components can be estimated by curve fitting method with the data of correlation results. The intensities of the correlation spots are related to the distortion between the two images. The rotation distortion could be derived from the intensities in the post processing procedure. With 18 rotations of the input image and sending them into the volume holographic system, the detection of the rotation variation in the range of 180° can be fulfilled. So the large range rotation distortion detection is firstly realized. It offers a fast, large range rotation measurement method for image distortions.

  8. Feature-based alert correlation in security systems using self organizing maps

    NASA Astrophysics Data System (ADS)

    Kumar, Munesh; Siddique, Shoaib; Noor, Humera

    2009-04-01

    The security of the networks has been an important concern for any organization. This is especially important for the defense sector as to get unauthorized access to the sensitive information of an organization has been the prime desire for cyber criminals. Many network security techniques like Firewall, VPN Concentrator etc. are deployed at the perimeter of network to deal with attack(s) that occur(s) from exterior of network. But any vulnerability that causes to penetrate the network's perimeter of defense, can exploit the entire network. To deal with such vulnerabilities a system has been evolved with the purpose of generating an alert for any malicious activity triggered against the network and its resources, termed as Intrusion Detection System (IDS). The traditional IDS have still some deficiencies like generating large number of alerts, containing both true and false one etc. By automatically classifying (correlating) various alerts, the high-level analysis of the security status of network can be identified and the job of network security administrator becomes much easier. In this paper we propose to utilize Self Organizing Maps (SOM); an Artificial Neural Network for correlating large amount of logged intrusion alerts based on generic features such as Source/Destination IP Addresses, Port No, Signature ID etc. The different ways in which alerts can be correlated by Artificial Intelligence techniques are also discussed. . We've shown that the strategy described in the paper improves the efficiency of IDS by better correlating the alerts, leading to reduced false positives and increased competence of network administrator.

  9. Sequential Bayesian Detection: A Model-Based Approach

    SciTech Connect

    Sullivan, E J; Candy, J V

    2007-08-13

    Sequential detection theory has been known for a long time evolving in the late 1940's by Wald and followed by Middleton's classic exposition in the 1960's coupled with the concurrent enabling technology of digital computer systems and the development of sequential processors. Its development, when coupled to modern sequential model-based processors, offers a reasonable way to attack physics-based problems. In this chapter, the fundamentals of the sequential detection are reviewed from the Neyman-Pearson theoretical perspective and formulated for both linear and nonlinear (approximate) Gauss-Markov, state-space representations. We review the development of modern sequential detectors and incorporate the sequential model-based processors as an integral part of their solution. Motivated by a wealth of physics-based detection problems, we show how both linear and nonlinear processors can seamlessly be embedded into the sequential detection framework to provide a powerful approach to solving non-stationary detection problems.

  10. Sequential Bayesian Detection: A Model-Based Approach

    SciTech Connect

    Candy, J V

    2008-12-08

    Sequential detection theory has been known for a long time evolving in the late 1940's by Wald and followed by Middleton's classic exposition in the 1960's coupled with the concurrent enabling technology of digital computer systems and the development of sequential processors. Its development, when coupled to modern sequential model-based processors, offers a reasonable way to attack physics-based problems. In this chapter, the fundamentals of the sequential detection are reviewed from the Neyman-Pearson theoretical perspective and formulated for both linear and nonlinear (approximate) Gauss-Markov, state-space representations. We review the development of modern sequential detectors and incorporate the sequential model-based processors as an integral part of their solution. Motivated by a wealth of physics-based detection problems, we show how both linear and nonlinear processors can seamlessly be embedded into the sequential detection framework to provide a powerful approach to solving non-stationary detection problems.

  11. Electrophysiological Correlates of Automatic Visual Change Detection in School-Age Children

    ERIC Educational Resources Information Center

    Clery, Helen; Roux, Sylvie; Besle, Julien; Giard, Marie-Helene; Bruneau, Nicole; Gomot, Marie

    2012-01-01

    Automatic stimulus-change detection is usually investigated in the auditory modality by studying Mismatch Negativity (MMN). Although the change-detection process occurs in all sensory modalities, little is known about visual deviance detection, particularly regarding the development of this brain function throughout childhood. The aim of the…

  12. Local-hybrid functional based on the correlation length

    SciTech Connect

    Johnson, Erin R.

    2014-09-28

    Local-hybrid functionals involve position-dependent mixing of Hartree-Fock and density-functional exchange, which should allow improved performance relative to conventional hybrids by reducing the inherent delocalization error and improving the long-range behaviour. Herein, the same-spin correlation length, obtained from the Fermi-hole radius, is used as the mixing parameter. The performance of the resulting local-hybrid functional is assessed for standard thermochemical and kinetics benchmarks. The local hybrid is shown to perform significantly better than the corresponding global hybrid in almost all cases.

  13. Wavelet transform modulus maxima based fractal correlation analysis

    NASA Astrophysics Data System (ADS)

    Lin, D. C.; Sharif, A.

    2007-12-01

    The wavelet transform modulus maxima (WTMM) used in the singularity analysis of one fractal function is extended to study the fractal correlation of two multifractal functions. The technique is developed in the framework of joint partition function analysis (JPFA) proposed by Meneveau et al. [C. Meneveau, K.R. Sreenivasan, Phys. Rev. A 41, 894 (1990)] and is shown to be equally effective. In addition, we show that another leading approach developed for the same purpose, namely, relative multifractal analysis, can be considered as a special case of JPFA at a particular parameter setting.

  14. CINCH (confocal incoherent correlation holography) super resolution fluorescence microscopy based upon FINCH (Fresnel incoherent correlation holography)

    PubMed Central

    Siegel, Nisan; Storrie, Brian; Bruce, Marc

    2016-01-01

    FINCH holographic fluorescence microscopy creates high resolution super-resolved images with enhanced depth of focus. The simple addition of a real-time Nipkow disk confocal image scanner in a conjugate plane of this incoherent holographic system is shown to reduce the depth of focus, and the combination of both techniques provides a simple way to enhance the axial resolution of FINCH in a combined method called “CINCH”. An important feature of the combined system allows for the simultaneous real-time image capture of widefield and holographic images or confocal and confocal holographic images for ready comparison of each method on the exact same field of view. Additional GPU based complex deconvolution processing of the images further enhances resolution. PMID:26839443

  15. Aptamer-Based Technologies in Foodborne Pathogen Detection

    PubMed Central

    Teng, Jun; Yuan, Fang; Ye, Yingwang; Zheng, Lei; Yao, Li; Xue, Feng; Chen, Wei; Li, Baoguang

    2016-01-01

    Aptamers are single stranded DNA or RNA ligands, which can be selected by a method called systematic evolution of ligands by exponential enrichment (SELEX); and they can specifically recognize and bind to their targets. These unique characteristics of aptamers offer great potentials in applications such as pathogen detection and biomolecular screening. Pathogen detection is the critical means in detecting and identifying the problems related to public health and food safety; and only the rapid, sensitive and efficient detection technologies can enable the users to make the accurate assessments on the risks of infections (humans and animals) or contaminations (foods and other commodities) caused by various pathogens. This article reviews the development in the field of the aptamer-based approaches for pathogen detection, including whole-cell SELEX and Genomic SELEX. Nowadays, a variety of aptamer-based biosensors have been developed for pathogen detection. Thus, in this review, we also cover the development in aptamer-based biosensors including optical biosensors for multiple pathogen detection by multiple-labeling or label-free models such as fluorescence detection and surface plasmon resonance, electrochemical biosensors and lateral chromatography test strips, and their applications in pathogen detection and biomolecular screening. While notable progress has been made in the field in the last decade, challenges or drawbacks in their applications such as pathogen detection and biomolecular screening remain to be overcome.

  16. Aptamer-Based Technologies in Foodborne Pathogen Detection.

    PubMed

    Teng, Jun; Yuan, Fang; Ye, Yingwang; Zheng, Lei; Yao, Li; Xue, Feng; Chen, Wei; Li, Baoguang

    2016-01-01

    Aptamers are single stranded DNA or RNA ligands, which can be selected by a method called systematic evolution of ligands by exponential enrichment (SELEX); and they can specifically recognize and bind to their targets. These unique characteristics of aptamers offer great potentials in applications such as pathogen detection and biomolecular screening. Pathogen detection is the critical means in detecting and identifying the problems related to public health and food safety; and only the rapid, sensitive and efficient detection technologies can enable the users to make the accurate assessments on the risks of infections (humans and animals) or contaminations (foods and other commodities) caused by various pathogens. This article reviews the development in the field of the aptamer-based approaches for pathogen detection, including whole-cell SELEX and Genomic SELEX. Nowadays, a variety of aptamer-based biosensors have been developed for pathogen detection. Thus, in this review, we also cover the development in aptamer-based biosensors including optical biosensors for multiple pathogen detection by multiple-labeling or label-free models such as fluorescence detection and surface plasmon resonance, electrochemical biosensors and lateral chromatography test strips, and their applications in pathogen detection and biomolecular screening. While notable progress has been made in the field in the last decade, challenges or drawbacks in their applications such as pathogen detection and biomolecular screening remain to be overcome.

  17. Aptamer-Based Technologies in Foodborne Pathogen Detection

    PubMed Central

    Teng, Jun; Yuan, Fang; Ye, Yingwang; Zheng, Lei; Yao, Li; Xue, Feng; Chen, Wei; Li, Baoguang

    2016-01-01

    Aptamers are single stranded DNA or RNA ligands, which can be selected by a method called systematic evolution of ligands by exponential enrichment (SELEX); and they can specifically recognize and bind to their targets. These unique characteristics of aptamers offer great potentials in applications such as pathogen detection and biomolecular screening. Pathogen detection is the critical means in detecting and identifying the problems related to public health and food safety; and only the rapid, sensitive and efficient detection technologies can enable the users to make the accurate assessments on the risks of infections (humans and animals) or contaminations (foods and other commodities) caused by various pathogens. This article reviews the development in the field of the aptamer-based approaches for pathogen detection, including whole-cell SELEX and Genomic SELEX. Nowadays, a variety of aptamer-based biosensors have been developed for pathogen detection. Thus, in this review, we also cover the development in aptamer-based biosensors including optical biosensors for multiple pathogen detection by multiple-labeling or label-free models such as fluorescence detection and surface plasmon resonance, electrochemical biosensors and lateral chromatography test strips, and their applications in pathogen detection and biomolecular screening. While notable progress has been made in the field in the last decade, challenges or drawbacks in their applications such as pathogen detection and biomolecular screening remain to be overcome. PMID:27672383

  18. Aptamer-Based Technologies in Foodborne Pathogen Detection.

    PubMed

    Teng, Jun; Yuan, Fang; Ye, Yingwang; Zheng, Lei; Yao, Li; Xue, Feng; Chen, Wei; Li, Baoguang

    2016-01-01

    Aptamers are single stranded DNA or RNA ligands, which can be selected by a method called systematic evolution of ligands by exponential enrichment (SELEX); and they can specifically recognize and bind to their targets. These unique characteristics of aptamers offer great potentials in applications such as pathogen detection and biomolecular screening. Pathogen detection is the critical means in detecting and identifying the problems related to public health and food safety; and only the rapid, sensitive and efficient detection technologies can enable the users to make the accurate assessments on the risks of infections (humans and animals) or contaminations (foods and other commodities) caused by various pathogens. This article reviews the development in the field of the aptamer-based approaches for pathogen detection, including whole-cell SELEX and Genomic SELEX. Nowadays, a variety of aptamer-based biosensors have been developed for pathogen detection. Thus, in this review, we also cover the development in aptamer-based biosensors including optical biosensors for multiple pathogen detection by multiple-labeling or label-free models such as fluorescence detection and surface plasmon resonance, electrochemical biosensors and lateral chromatography test strips, and their applications in pathogen detection and biomolecular screening. While notable progress has been made in the field in the last decade, challenges or drawbacks in their applications such as pathogen detection and biomolecular screening remain to be overcome. PMID:27672383

  19. Laser Spot Detection Based on Reaction Diffusion

    PubMed Central

    Vázquez-Otero, Alejandro; Khikhlukha, Danila; Solano-Altamirano, J. M.; Dormido, Raquel; Duro, Natividad

    2016-01-01

    Center-location of a laser spot is a problem of interest when the laser is used for processing and performing measurements. Measurement quality depends on correctly determining the location of the laser spot. Hence, improving and proposing algorithms for the correct location of the spots are fundamental issues in laser-based measurements. In this paper we introduce a Reaction Diffusion (RD) system as the main computational framework for robustly finding laser spot centers. The method presented is compared with a conventional approach for locating laser spots, and the experimental results indicate that RD-based computation generates reliable and precise solutions. These results confirm the flexibility of the new computational paradigm based on RD systems for addressing problems that can be reduced to a set of geometric operations. PMID:26938537

  20. Laser Spot Detection Based on Reaction Diffusion.

    PubMed

    Vázquez-Otero, Alejandro; Khikhlukha, Danila; Solano-Altamirano, J M; Dormido, Raquel; Duro, Natividad

    2016-03-01

    Center-location of a laser spot is a problem of interest when the laser is used for processing and performing measurements. Measurement quality depends on correctly determining the location of the laser spot. Hence, improving and proposing algorithms for the correct location of the spots are fundamental issues in laser-based measurements. In this paper we introduce a Reaction Diffusion (RD) system as the main computational framework for robustly finding laser spot centers. The method presented is compared with a conventional approach for locating laser spots, and the experimental results indicate that RD-based computation generates reliable and precise solutions. These results confirm the flexibility of the new computational paradigm based on RD systems for addressing problems that can be reduced to a set of geometric operations.

  1. Coherent-based method for detection of underwater objects from sonar imagery

    NASA Astrophysics Data System (ADS)

    Tucker, James D.; Azimi-Sadjadi, Mahmood R.; Dobeck, Gerry J.

    2007-04-01

    Detection and classification of underwater objects in sonar imagery are challenging problems. In this paper, a new coherent-based method for detecting potential targets in high-resolution sonar imagery is developed using canonical correlation analysis (CCA). Canonical coordinate decomposition allows us to quantify the changes between the returns from the bottom and any target activity in sonar images and at the same time extract useful features for subsequent classification without the need to perform separate detection and feature extraction. Moreover, in situations where any visual analysis or verification by human operators is required, the detected/classified objects can be reconstructed from the coherent features. In this paper, underwater target detection using the canonical correlations extracted from regions of interest within the sonar image is considered. Test results of the proposed method on underwater side-scan sonar images provided by the Naval Surface Warfare Center (NSWC) in Panama City, FL is presented. This database contains synthesized targets in real background varying in degree of difficulty and bottom clutter. Results illustrating the effectiveness of the CCA based detection method are presented in terms of probability of detection, and false alarm rates for various densities of background clutter.

  2. Special Nuclear Material Detection with a Water Cherenkov based Detector

    SciTech Connect

    Sweany, M; Bernstein, A; Bowden, N; Dazeley, S; Svoboda, R

    2008-11-10

    Fission events from Special Nuclear Material (SNM), such as highly enriched uranium or plutonium, produce a number of neutrons and high energy gamma-rays. Assuming the neutron multiplicity is approximately Poissonian with an average of 2 to 3, the observation of time correlations between these particles from a cargo container would constitute a robust signature of the presence of SNM inside. However, in order to be sensitive to the multiplicity, one would require a high total efficiency. There are two approaches to maximize the total efficiency; maximizing the detector efficiency or maximizing the detector solid angle coverage. The advanced detector group at LLNL is investigating one way to maximize the detector size. We are designing and building a water Cerenkov based gamma and neutron detector for the purpose of developing an efficient and cost effective way to deploy a large solid angle car wash style detector. We report on our progress in constructing a larger detector and also present preliminary results from our prototype detector that indicates detection of neutrons.

  3. Experiments on Adaptive Techniques for Host-Based Intrusion Detection

    SciTech Connect

    DRAELOS, TIMOTHY J.; COLLINS, MICHAEL J.; DUGGAN, DAVID P.; THOMAS, EDWARD V.; WUNSCH, DONALD

    2001-09-01

    This research explores four experiments of adaptive host-based intrusion detection (ID) techniques in an attempt to develop systems that can detect novel exploits. The technique considered to have the most potential is adaptive critic designs (ACDs) because of their utilization of reinforcement learning, which allows learning exploits that are difficult to pinpoint in sensor data. Preliminary results of ID using an ACD, an Elman recurrent neural network, and a statistical anomaly detection technique demonstrate an ability to learn to distinguish between clean and exploit data. We used the Solaris Basic Security Module (BSM) as a data source and performed considerable preprocessing on the raw data. A detection approach called generalized signature-based ID is recommended as a middle ground between signature-based ID, which has an inability to detect novel exploits, and anomaly detection, which detects too many events including events that are not exploits. The primary results of the ID experiments demonstrate the use of custom data for generalized signature-based intrusion detection and the ability of neural network-based systems to learn in this application environment.

  4. Accelerator based techniques for contraband detection

    NASA Astrophysics Data System (ADS)

    Vourvopoulos, George

    1994-05-01

    It has been shown that narcotics, explosives, and other contraband materials, contain various chemical elements such as H, C, N, O, P, S, and Cl in quantities and ratios that differentiate them from each other and from other innocuous substances. Neutrons and γ-rays have the ability to penetrate through various materials at large depths. They are thus able, in a non-intrusive way, to interrogate volumes ranging from suitcases to Sea-Land containers, and have the ability to image the object with an appreciable degree of reliability. Neutron induced reactions such as (n, γ), (n, n') (n, p) or proton induced γ-resonance absorption are some of the reactions currently investigated for the identification of the chemical elements mentioned above. Various DC and pulsed techniques are discussed and their advantages, characteristics, and current progress are shown. Areas where use of these methods is currently under evaluation are detection of hidden explosives, illicit drug interdiction, chemical war agents identification, nuclear waste assay, nuclear weapons destruction and others.

  5. Dynamic based damage detection in composite structures

    NASA Astrophysics Data System (ADS)

    Banerjee, Sauvik; Ricci, Fabrizio; Baid, Harsh; Mal, Ajit K.

    2009-03-01

    Advanced composites are being used increasingly in state-of-the-art aircraft and aerospace structures. In spite of their many advantages, composite materials are highly susceptible to hidden flaws that may occur at any time during the life cycle of a structure, and if undetected, may cause sudden and catastrophic failure of the entire structure. This paper is concerned with the detection and characterization of hidden defects in composite structures before they grow to a critical size. A methodology for automatic damage identification and localization is developed using a combination of vibration and wave propagation data. The structure is assumed to be instrumented with an array of actuators and sensors to excite and record its dynamic response, including vibration and wave propagation effects. A damage index, calculated from the measured dynamical response of the structure in a previous (reference) state and the current state, is introduced as a determinant of structural damage. The indices are used to identify low velocity impact damages in increasingly complex composite structural components. The potential application of the approach in developing health monitoring systems in defects-critical structures is indicated.

  6. Host-Based Data Exfiltration Detection via System Call Sequences

    SciTech Connect

    Beaver, Justin M; Jewell, Brian C

    2011-01-01

    The host-based detection of malicious data exfiltration activities is currently a sparse area of research and mostly limited to methods that analyze network traffic or signature based detection methods that target specific processes. In this paper we explore an alternative method to host-based detection that exploits sequences of system calls and new collection methods that allow us to catch these activities in real time. We show that system calls sequences can be found to reach a steady state across processes and users, and explore the viability of new methods as heuristics for profiling user behaviors.

  7. Change detection of built-up land: A framework of combining pixel-based detection and object-based recognition

    NASA Astrophysics Data System (ADS)

    Xiao, Pengfeng; Zhang, Xueliang; Wang, Dongguang; Yuan, Min; Feng, Xuezhi; Kelly, Maggi

    2016-09-01

    This study proposed a new framework that combines pixel-level change detection and object-level recognition to detect changes of built-up land from high-spatial resolution remote sensing images. First, an adaptive differencing method was designed to detect changes at the pixel level based on both spectral and textural features. Next, the changed pixels were subjected to a set of morphological operations to improve the completeness and to generate changed objects, achieving the transition of change detection from the pixel level to the object level. The changed objects were further recognised through the difference of morphological building index in two phases to indicate changed objects on built-up land. The transformation from changed pixels to changed objects makes the proposed framework distinct with both the pixel-based and the object-based change detection methods. Compared with the pixel-based methods, the proposed framework can improve the change detection capability through the transformation and successive recognition of objects. Compared with the object-based method, the proposed framework avoids the issue of multitemporal segmentation and can generate changed objects directly from changed pixels. The experimental results show the effectiveness of the transformation from changed pixels to changed objects and the successive object-based recognition on improving the detection accuracy, which justify the application potential of the proposed change detection framework.

  8. Research about Memory Detection Based on the Embedded Platform

    NASA Astrophysics Data System (ADS)

    Sun, Hao; Chu, Jian

    As is known to us all, the resources of memory detection of the embedded systems are very limited. Taking the Linux-based embedded arm as platform, this article puts forward two efficient memory detection technologies according to the characteristics of the embedded software. Especially for the programs which need specific libraries, the article puts forwards portable memory detection methods to help program designers to reduce human errors,improve programming quality and therefore make better use of the valuable embedded memory resource.

  9. Frequency analysis and data correlation for beam displacement measurements based on the ISTIMES campaign in Montagnole

    NASA Astrophysics Data System (ADS)

    Nordebo, S.; Gustafsson, M.; Dumoulin, J.; Perrone, A.; Pignatti, S.; Soldovieri, F.

    2012-04-01

    Time-frequency analysis is an interdisciplinary subject, which originates from mathematics, signal analysis and physics (Grochenig, 2001). From a signal theoretical and mathematical point of view the primary purpose has been to understand how signals, operators and other mathematical objects can be understood simultaneously in the time and frequency variables, which correspond to the phase space variables in physics (Grochenig, 2001; Claasen, 1980). Perhaps the most popular time-frequency representations are the short-time Fourier transform (STFT) and the Wigner distribution (Grochenig, 2001). Their common feature is to localize a function before taking the Fourier transform, thereby obtaining a time-frequency representation. Here, we employ the classical Kaiser window (Kaiser and Schafer, 1980) which is well known in spectrum analysis, since it provides a flexible approach to control the frequency resolution as well as the amplitude dynamics (sidelobe rejection) for a given measurement interval (or resolution) in time. In this contribution, we employ frequency analysis and data correlation for beam displacement measurements based on the ISTIMES campaign (Proto et al., 2010) conducted at the rock fall test center in Montagnole, France, on October 14, 2010. Several test cases are considered based on direct and indirect impact from a steel sphere dropped on a reinforced concrete beam. Several measurement technologies were used to measure the deformation of the beam based on IRT (InfraRed Thermography), GBSAR (Ground Based Synthetic Aperture Radar), and ODM (Optical Diode Measurements). A time-frequency analysis was used to analyze the evolution of the resonance frequencies of the beam. A short-time cross-correlation followed by Fourier transformation was used to integrate data based on two different signal sources (sensor technologies). The results were compared to a frequency analysis based on video data and image processing to yield a high-accuracy reference

  10. REIONIZATION ON LARGE SCALES. II. DETECTING PATCHY REIONIZATION THROUGH CROSS-CORRELATION OF THE COSMIC MICROWAVE BACKGROUND

    SciTech Connect

    Natarajan, A.; Battaglia, N.; Trac, H.; Pen, U.-L.; Loeb, A.

    2013-10-20

    We investigate the effect of patchy reionization on the cosmic microwave background (CMB) temperature. An anisotropic optical depth τ( n-hat ) alters the TT power spectrum on small scales l > 2000. We make use of the correlation between the matter density and the reionization redshift fields to construct full sky maps of τ( n-hat ). Patchy reionization transfers CMB power from large scales to small scales, resulting in a non-zero cross correlation between large and small angular scales. We show that the patchy τ correlator is sensitive to small root mean square (rms) values τ{sub rms} ∼ 0.003 seen in our maps. We include frequency-independent secondaries such as CMB lensing and kinetic Sunyaev-Zel'dovich (kSZ) terms, and show that patchy τ may still be detected at high significance. Reionization models that predict different values of τ{sub rms} may be distinguished even for the same mean value (τ). It is more difficult to detect patchy τ in the presence of larger secondaries such as the thermal Sunyaev-Zel'dovich, radio background, and the cosmic infrared background. In this case, we show that patchy τ may be detected if these frequency-dependent secondaries are minimized to ∼< 5 μK (rms) by means of a multi-frequency analysis. We show that the patchy τ correlator provides information that is complementary to what may be obtained from the polarization and the kSZ power spectra.

  11. ERP correlates of pitch error detection in complex tone and voice auditory feedback with missing fundamental.

    PubMed

    Behroozmand, Roozbeh; Korzyukov, Oleg; Larson, Charles R

    2012-04-11

    Previous studies have shown that the pitch of a sound is perceived in the absence of its fundamental frequency (F0), suggesting that a distinct mechanism may resolve pitch based on a pattern that exists between harmonic frequencies. The present study investigated whether such a mechanism is active during voice pitch control. ERPs were recorded in response to +200 cents pitch shifts in the auditory feedback of self-vocalizations and complex tones with and without the F0. The absence of the fundamental induced no difference in ERP latencies. However, a right-hemisphere difference was found in the N1 amplitudes with larger responses to complex tones that included the fundamental compared to when it was missing. The P1 and N1 latencies were shorter in the left hemisphere, and the N1 and P2 amplitudes were larger bilaterally for pitch shifts in voice and complex tones compared with pure tones. These findings suggest hemispheric differences in neural encoding of pitch in sounds with missing fundamental. Data from the present study suggest that the right cortical auditory areas, thought to be specialized for spectral processing, may utilize different mechanisms to resolve pitch in sounds with missing fundamental. The left hemisphere seems to perform faster processing to resolve pitch based on the rate of temporal variations in complex sounds compared with pure tones. These effects indicate that the differential neural processing of pitch in the left and right hemispheres may enable the audio-vocal system to detect temporal and spectral variations in the auditory feedback for vocal pitch control.

  12. Validating spectral spatial detection based on MMPP formulation

    NASA Astrophysics Data System (ADS)

    Trang, Anh; Agarwal, Sanjeev; Broach, Thomas; Smith, Thomas

    2011-06-01

    Spectral, shape or texture features of the detected targets are used to model the likelihood of the targets to be potential mines in a minefield. However, some potential mines can be false alarms due to the similarity of the mine signatures with natural and other manmade clutter signatures. Therefore, in addition to the target features, spatial distribution of the detected targets can be used to improve the minefield detection performance. In our recently published SPIE paper, we evaluated minefield detection performance for both patterned and unpatterned minefields in highly cluttered environments, simultaneously using both target features and target spatial distributions that define Markov Marked Point Process (MMPP). The results have suggested that proper exploitation of spectral/shape features and spatial distributions can indeed contribute improved performance of patterned and unpatterned minefield detection. Also, the ability of the algorithm to detect the minefields in highly cluttered environments shows the robustness of the developed minefield detection algorithm based on MMPP formulation. Moreover, the results show that the MMPP minefield detection algorithm performs significantly better than the baseline algorithm employing spatial point process with false alarm mitigation. Since these results were based on the simulated data, it is not clear that the MMPP detection algorithm has fully achieved its best performance. To validate its performance, an analytical solution for the minefield detection problem will be developed, and its performance will be compared with the performance of the simulated solution. The analytical solution for the complete minefield detection problem is intractable due to a large number of detections and the variation of the number of detected mines in the minefield process. Therefore, an analytical solution for a simplified detection problem will be derived, and its minefield performance will be compared with the minefield

  13. SCREEN photometric property detection system based on area CCD

    NASA Astrophysics Data System (ADS)

    Yan, Fu-cai; Ye, Wei; Xu, Yu; Wang, Chao; Zhang, Yu-wei

    2011-08-01

    The photometric property detection of screen display is crucial for screen display quality test. Traditional photometry detection technologies were based on photoelectric sensors such as silicon photocell, photo-electric multiplier and CdS, which can detect only some isolated points. To break the limitation of randomness, incompleteness and detection accuracy in current technologies, we designed a screen photometric detection system based on area CCD. The system consists of photometric image sensor, photometric image acquisition hardware and photometric image analyzing software. The photometric image sensor, which adopts optical lens, optical filters and area CCD, adapts its spectrum response property to fit the spectrum luminous efficiency curve V (λ) by adjusting the thickness and quantity of appropriate optical filters. photometric image acquisition hardware adopts the DSP as a core processor to drive the area CCD, to sample, acquire , process and save the image from image sensor, to transmit the image to computer. For real-time performance of transmitting, the hardware system adopts the transmission protocol of USB2.0. The uploaded image will be processed by photometric image analyzing software, and then displayed in real time with detection results. The screen photometric detection technology based on area CCD can detect specifications of the whole screen such as luminance, contrast, onoff ratio and uniformity, breaks the limitation of randomness and incompleteness in current detection technology, exactly and fully reflects the integrated display quality of the whole screen. According to the test results, the accuracy of this system has reached the accuracy level one in China.

  14. Inequivalence of correlation-based measures of non-Markovianity

    NASA Astrophysics Data System (ADS)

    Neto, Alaor Cervati; Karpat, Göktuǧ; Fanchini, Felipe Fernandes

    2016-09-01

    We conclusively show that the entanglement- and the mutual-information-based measures of quantum non-Markovianity are inequivalent. To this aim, we first analytically solve the optimization problem in the definition of the entanglement-based measure for a two-level system. We demonstrate that the optimal initial bipartite state of the open system and the ancillary is always given by one of the Bell states for any one-qubit dynamics. On top of this result, we present an explicit example dynamics where memory effects emerge according to the mutual-information-based measure, even though the time evolution remains memoryless with respect to the entanglement-based measure. Finally, we explain this disagreement between the two measures in terms of the information dynamics of the open system, exploring the accessible and inaccessible parts of information.

  15. Polypyrrole based gas sensor for ammonia detection

    NASA Astrophysics Data System (ADS)

    Dunst, K. J.; Cysewska, K.; Kalinowski, P.; Jasiński, P.

    2016-01-01

    The nature of polypyrrole response to toxic gases does not allow using the sensor in a conventional way. The main aim of this study is to acquire the information about the concentration using different approaches: a linear approximation, a non-linear approximation and a tangent method. In this paper a two-steps procedure for sensor response measurements has been utilized. Polypyrrole films were electrochemically synthesized on the interdigitated electrodes. Gas sensing measurements of polypyrrole based sensor were carried out at room temperature. The influence of the flow rate on the sensing performance to NH3 were investigated. The preliminary studies of aging of the sensor were also explored.

  16. Video-Based Affect Detection in Noninteractive Learning Environments

    ERIC Educational Resources Information Center

    Chen, Yuxuan; Bosch, Nigel; D'Mello, Sidney

    2015-01-01

    The current paper explores possible solutions to the problem of detecting affective states from facial expressions during text/diagram comprehension, a context devoid of interactive events that can be used to infer affect. These data present an interesting challenge for face-based affect detection because likely locations of affective facial…

  17. Revisiting node-based SIR models in complex networks with degree correlations

    NASA Astrophysics Data System (ADS)

    Wang, Yi; Cao, Jinde; Alofi, Abdulaziz; AL-Mazrooei, Abdullah; Elaiw, Ahmed

    2015-11-01

    In this paper, we consider two growing networks which will lead to the degree-degree correlations between two nearest neighbors in the network. When the network grows to some certain size, we introduce an SIR-like disease such as pandemic influenza H1N1/09 to the population. Due to its rapid spread, the population size changes slowly, and thus the disease spreads on correlated networks with approximately fixed size. To predict the disease evolution on correlated networks, we first review two node-based SIR models incorporating degree correlations and an edge-based SIR model without considering degree correlation, and then compare the predictions of these models with stochastic SIR simulations, respectively. We find that the edge-based model, even without considering degree correlations, agrees much better than the node-based models incorporating degree correlations with stochastic SIR simulations in many respects. Moreover, simulation results show that for networks with positive correlation, the edge-based model provides a better upper bound of the cumulative incidence than the node-based SIR models, whereas for networks with negative correlation, it provides a lower bound of the cumulative incidence.

  18. Corn tassel detection based on image processing

    NASA Astrophysics Data System (ADS)

    Tang, Wenbing; Zhang, Yane; Zhang, Dongxing; Yang, Wei; Li, Minzan

    2012-01-01

    Machine vision has been widely applied in facility agriculture, and played an important role in obtaining environment information. In this paper, it is studied that application of image processing to recognize and locate corn tassel for corn detasseling machine. The corn tassel identification and location method was studied based on image processing and automated technology guidance information was provided for the actual production of corn emasculation operation. The system is the application of image processing to recognize and locate corn tassel for corn detasseling machine. According to the color characteristic of corn tassel, image processing techniques was applied to identify corn tassel of the images under HSI color space and Image segmentation was applied to extract the part of corn tassel, the feature of corn tassel was analyzed and extracted. Firstly, a series of preprocessing procedures were done. Then, an image segmentation algorithm based on HSI color space was develop to extract corn tassel from background and region growing method was proposed to recognize the corn tassel. The results show that this method could be effective for extracting corn tassel parts from the collected picture and can be used for corn tassel location information; this result could provide theoretical basis guidance for corn intelligent detasseling machine.

  19. Raman spectroscopy-based detection of chemical contaminants in food powders

    NASA Astrophysics Data System (ADS)

    Chao, Kuanglin; Dhakal, Sagar; Qin, Jianwei; Kim, Moon; Bae, Abigail

    2016-05-01

    Raman spectroscopy technique has proven to be a reliable method for qualitative detection of chemical contaminants in food ingredients and products. For quantitative imaging-based detection, each contaminant particle in a food sample must be detected and it is important to determine the necessary spatial resolution needed to effectively detect the contaminant particles. This study examined the effective spatial resolution required for detection of maleic acid in tapioca starch and benzoyl peroxide in wheat flour. Each chemical contaminant was mixed into its corresponding food powder at a concentration of 1% (w/w). Raman spectral images were collected for each sample, leveled across a 45 mm x 45 mm area, using different spatial resolutions. Based on analysis of these images, a spatial resolution of 0.5mm was selected as effective spatial resolution for detection of maleic acid in starch and benzoyl peroxide in flour. An experiment was then conducted using the 0.5mm spatial resolution to demonstrate Raman imaging-based quantitative detection of these contaminants for samples prepared at 0.1%, 0.3%, and 0.5% (w/w) concentrations. The results showed a linear correlation between the detected numbers of contaminant pixels and the actual concentrations of contaminant.

  20. IUE's View of Callisto: Detection of an SO2 Absorption Correlated to Possible Torus Neutral Wind Alterations

    NASA Technical Reports Server (NTRS)

    Lane, Arthur L.; Domingue, Deborah L.

    1997-01-01

    Observations taken with the International Ultraviolet Explorer (IUE) detected a 0.28 micron absorption feature on Callisto's leading and Jupiter-facing hemispheres. This feature is similar to Europa's 0.28 micron feature, however it shows no correlation with magnetospheric ion bombardment. The strongest 0.28 micron signature is seen in the region containing the Valhalla impact. This absorption feature also shows some spatial correlation to possible neutral wind interactions, suggestive of S implantation (rather than S(sub x)) into Callisto's water ice surface, Indications of possible temporal variations (on the 10% level) are seen at other wavelengths between the 1984-1986 and the 1996 observations.

  1. Design and implementation of photon correlator based on C8051F

    NASA Astrophysics Data System (ADS)

    Shen, Jin; Li, Yuming; Liu, Wei; Yang, Yan; Cheng, Yanting

    2008-02-01

    Correlation techniques are widely used to extract spectral information from light scattering and other stochastic processes. Within the photon correlation system, the correlating operation must work at a high speed. In this paper, a photon correlator based on microcontroller C8051F was developed. In the photon correlator, the work of counting and scratch is completed by the two 4-bits binary adder 74F161, which is connected to form an 8-bits adder., and the correlation operation of every channel is carried out by the software of C8051F. By probably choosing high speed devices counting of 10ns in width pulses can be counted. The correlation operations including multiplying and addition operation of 56 channels with the circulation program within 3μs were made in interrupt service routine of the C8051F. The work in this paper can be applied in the ultra-fine particle sizing with photon correlation spectroscopy.

  2. Noise-benefit forbidden-interval theorems for threshold signal detectors based on cross correlations.

    PubMed

    Mitaim, Sanya; Kosko, Bart

    2014-11-01

    We show that the main forbidden interval theorems of stochastic resonance hold for a correlation performance measure. Earlier theorems held only for performance measures based on mutual information or the probability of error detection. Forbidden interval theorems ensure that a threshold signal detector benefits from deliberately added noise if the average noise does not lie in an interval that depends on the threshold value. We first show that this result holds for correlation for all finite-variance noise and for all forms of infinite-variance stable noise. A second forbidden-interval theorem gives necessary and sufficient conditions for a local noise benefit in a bipolar signal system when the noise comes from a location-scale family. A third theorem gives a general condition for a local noise benefit for arbitrary signals with finite second moments and for location-scale noise. This result also extends forbidden intervals to forbidden bands of parameters. A fourth theorem gives necessary and sufficient conditions for a local noise benefit when both the independent signal and noise are normal. A final theorem derives necessary and sufficient conditions for forbidden bands when using arrays of threshold detectors for arbitrary signals and location-scale noise. PMID:25493756

  3. Functional MRI-based lie detection: scientific and societal challenges.

    PubMed

    Farah, Martha J; Hutchinson, J Benjamin; Phelps, Elizabeth A; Wagner, Anthony D

    2014-02-01

    Functional MRI (fMRI)-based lie detection has been marketed as a tool for enhancing personnel selection, strengthening national security and protecting personal reputations, and at least three US courts have been asked to admit the results of lie detection scans as evidence during trials. How well does fMRI-based lie detection perform, and how should the courts, and society more generally, respond? Here, we address various questions — some of which are based on a meta-analysis of published studies — concerning the scientific state of the art in fMRI-based lie detection and its legal status, and discuss broader ethical and societal implications. We close with three general policy recommendations.

  4. Functional MRI-based lie detection: scientific and societal challenges.

    PubMed

    Farah, Martha J; Hutchinson, J Benjamin; Phelps, Elizabeth A; Wagner, Anthony D

    2014-02-01

    Functional MRI (fMRI)-based lie detection has been marketed as a tool for enhancing personnel selection, strengthening national security and protecting personal reputations, and at least three US courts have been asked to admit the results of lie detection scans as evidence during trials. How well does fMRI-based lie detection perform, and how should the courts, and society more generally, respond? Here, we address various questions — some of which are based on a meta-analysis of published studies — concerning the scientific state of the art in fMRI-based lie detection and its legal status, and discuss broader ethical and societal implications. We close with three general policy recommendations. PMID:24588019

  5. Semiconducting Metal Oxide Based Sensors for Selective Gas Pollutant Detection

    PubMed Central

    Kanan, Sofian M.; El-Kadri, Oussama M.; Abu-Yousef, Imad A.; Kanan, Marsha C.

    2009-01-01

    A review of some papers published in the last fifty years that focus on the semiconducting metal oxide (SMO) based sensors for the selective and sensitive detection of various environmental pollutants is presented. PMID:22408500

  6. Saliency detection based on multi-instance images learning

    NASA Astrophysics Data System (ADS)

    Wan, Shouhong; Jin, Peiquan; Yue, Lihua; Huang, Qian

    2015-07-01

    Existing visual saliency detection methods are usually based on single image, however, without priori knowledge, the contents of single image are ambiguous, so visual saliency detection based on single image can't extract region of interest. To solve it, we propose a novel saliency detection based on multi-instance images. Our method considers human's visual psychological factors and measures visual saliency based on global contrast, local contrast and sparsity. It firstly uses multi-instance learning to get the center of clustering, and then computes feature relative dispersion. By fusing different weighted feature saliency map, the final synthesize saliency map is generated. Comparing with other saliency detection methods, our method increases the rate of hit.

  7. Detection of smoke plume for a land-based early forest fire detection system

    NASA Astrophysics Data System (ADS)

    Saghri, John; Jacobs, John; Davenport, Tim; Garges, David

    2015-09-01

    A promising daytime smoke plume detection for a land-based early forest fire detection system is proposed. The visible video imagery from a land-based monitoring camera is processed to detect the smoke which likely rises in an early stage of a forest fire. Unlike the fire core and its surrounding heat which are detected via day/night infrared imaging, the relatively cold smoke plume can only be captured in the visible spectrum of light. The smoke plume is detected via exploitation of its temporal signature. This is accomplished via Principal Component Transformation (PCT) operations on consecutive sequences of visible video frames followed by spatial filtering of one of the resulting low-order Principal Component (PC) images. It is shown that the blue channel of the Red, Green, Blue (RGB) color camera is most effective in detecting the smoke plume. Smoke plume is clearly detected and isolated via simple blurring, thresholding, and median filtering of one of the resulting low-order principle component (PC) images. The robustness of this PCA-based method relative to simple temporal frame differencing and use of color, i.e., visible spectral signature of smoke, are discussed. Various parameters of the system including the required observation time and number of frames to retain for PCT, selection of which low-order PC to use, and types and sizes of the filters applied to the selected PC image to detect and isolate the smoke plume, are discussed.

  8. Vibration Based Sun Gear Damage Detection

    NASA Technical Reports Server (NTRS)

    Hood, Adrian; LaBerge, Kelsen; Lewicki, David; Pines, Darryll

    2013-01-01

    Seeded fault experiments were conducted on the planetary stage of an OH-58C helicopter transmission. Two vibration based methods are discussed that isolate the dynamics of the sun gear from that of the planet gears, bearings, input spiral bevel stage, and other components in and around the gearbox. Three damaged sun gears: two spalled and one cracked, serve as the focus of this current work. A non-sequential vibration separation algorithm was developed and the resulting signals analyzed. The second method uses only the time synchronously averaged data but takes advantage of the signal/source mapping required for vibration separation. Both algorithms were successful in identifying the spall damage. Sun gear damage was confirmed by the presence of sun mesh groups. The sun tooth crack condition was inconclusive.

  9. How to detect Edgar Allan Poe's 'purloined letter,' or cross-correlation algorithms in digitized video images for object identification, movement evaluation, and deformation analysis

    NASA Astrophysics Data System (ADS)

    Dost, Michael; Vogel, Dietmar; Winkler, Thomas; Vogel, Juergen; Erb, Rolf; Kieselstein, Eva; Michel, Bernd

    2003-07-01

    Cross correlation analysis of digitised grey scale patterns is based on - at least - two images which are compared one to each other. Comparison is performed by means of a two-dimensional cross correlation algorithm applied to a set of local intensity submatrices taken from the pattern matrices of the reference and the comparison images in the surrounding of predefined points of interest. Established as an outstanding NDE tool for 2D and 3D deformation field analysis with a focus on micro- and nanoscale applications (microDAC and nanoDAC), the method exhibits an additional potential for far wider applications, that could be used for advancing homeland security. Cause the cross correlation algorithm in some kind seems to imitate some of the "smart" properties of human vision, this "field-of-surface-related" method can provide alternative solutions to some object and process recognition problems that are difficult to solve with more classic "object-related" image processing methods. Detecting differences between two or more images using cross correlation techniques can open new and unusual applications in identification and detection of hidden objects or objects with unknown origin, in movement or displacement field analysis and in some aspects of biometric analysis, that could be of special interest for homeland security.

  10. Detection and correction of blinking bias in image correlation transport measurements of quantum dot tagged macromolecules.

    PubMed

    Durisic, Nela; Bachir, Alexia I; Kolin, David L; Hebert, Benedict; Lagerholm, B Christoffer; Grutter, Peter; Wiseman, Paul W

    2007-08-15

    Semiconductor nanocrystals or quantum dots (QDs) are becoming widely used as fluorescent labels for biological applications. Here we demonstrate that fluorescence fluctuation analysis of their diffusional mobility using temporal image correlation spectroscopy is highly susceptible to systematic errors caused by fluorescence blinking of the nanoparticles. Temporal correlation analysis of fluorescence microscopy image time series of streptavidin-functionalized (CdSe)ZnS QDs freely diffusing in two dimensions shows that the correlation functions are fit well to a commonly used diffusion decay model, but the transport coefficients can have significant systematic errors in the measurements due to blinking. Image correlation measurements of the diffusing QD samples measured at different laser excitation powers and analysis of computer simulated image time series verified that the effect we observe is caused by fluorescence intermittency. We show that reciprocal space image correlation analysis can be used for mobility measurements in the presence of blinking emission because it separates the contributions of fluctuations due to photophysics from those due to transport. We also demonstrate application of the image correlation methods for measurement of the diffusion coefficient of glycosyl phosphatidylinositol-anchored proteins tagged with QDs as imaged on living fibroblasts.

  11. Fluorescence-based multiplex protein detection using optically encoded microbeads.

    PubMed

    Jun, Bong-Hyun; Kang, Homan; Lee, Yoon-Sik; Jeong, Dae Hong

    2012-01-01

    Potential utilization of proteins for early detection and diagnosis of various diseases has drawn considerable interest in the development of protein-based multiplex detection techniques. Among the various techniques for high-throughput protein screening, optically-encoded beads combined with fluorescence-based target monitoring have great advantages over the planar array-based multiplexing assays. This review discusses recent developments of analytical methods of screening protein molecules on microbead-based platforms. These include various strategies such as barcoded microbeads, molecular beacon-based techniques, and surface-enhanced Raman scattering-based techniques. Their applications for label-free protein detection are also addressed. Especially, the optically-encoded beads such as multilayer fluorescence beads and SERS-encoded beads are successful for generating a large number of coding.

  12. Foreign fiber detecting system based on multispectral technique

    NASA Astrophysics Data System (ADS)

    Li, Qi; Han, Shaokun; Wang, Ping; Wang, Liang; Xia, Wenze

    2015-08-01

    This paper presents a foreign fiber detecting system based on multi-spectral technique. The absorption rate and the reflectivity of foreign fibers differently under different wavelengths of light so that the characteristics of the image has difference in the different light irradiation. Contrast pyramid image fusion algorithm and adaptive enhancement is improved to extracted the foreign fiber from the cotton background. The experimental results show that the single light source can detect 6 kinds of foreign fiber in cotton and multi-spectral detection can detect eight kinds.

  13. Vehicle Detection Based on Probability Hypothesis Density Filter

    PubMed Central

    Zhang, Feihu; Knoll, Alois

    2016-01-01

    In the past decade, the developments of vehicle detection have been significantly improved. By utilizing cameras, vehicles can be detected in the Regions of Interest (ROI) in complex environments. However, vision techniques often suffer from false positives and limited field of view. In this paper, a LiDAR based vehicle detection approach is proposed by using the Probability Hypothesis Density (PHD) filter. The proposed approach consists of two phases: the hypothesis generation phase to detect potential objects and the hypothesis verification phase to classify objects. The performance of the proposed approach is evaluated in complex scenarios, compared with the state-of-the-art. PMID:27070621

  14. Using Morphlet-Based Image Representation for Object Detection

    NASA Astrophysics Data System (ADS)

    Gorbatsevich, V. S.; Vizilter, Yu. V.

    2016-06-01

    In this paper, we propose an original method for objects detection based on a special tree-structured image representation - the trees of morphlets. The method provides robust detection of various types of objects in an image without employing a machine learning procedure. Along with a bounding box creation on a detection step, the method makes pre-segmentation, which can be further used for recognition purposes. Another important feature of the proposed approach is that there are no needs to use a running window as well as a features pyramid in order to detect the objects of different sizes.

  15. Vehicle Detection Based on Probability Hypothesis Density Filter.

    PubMed

    Zhang, Feihu; Knoll, Alois

    2016-01-01

    In the past decade, the developments of vehicle detection have been significantly improved. By utilizing cameras, vehicles can be detected in the Regions of Interest (ROI) in complex environments. However, vision techniques often suffer from false positives and limited field of view. In this paper, a LiDAR based vehicle detection approach is proposed by using the Probability Hypothesis Density (PHD) filter. The proposed approach consists of two phases: the hypothesis generation phase to detect potential objects and the hypothesis verification phase to classify objects. The performance of the proposed approach is evaluated in complex scenarios, compared with the state-of-the-art. PMID:27070621

  16. Correlating multidimensional fetal heart rate variability analysis with acid-base balance at birth.

    PubMed

    Frasch, Martin G; Xu, Yawen; Stampalija, Tamara; Durosier, Lucien D; Herry, Christophe; Wang, Xiaogang; Casati, Daniela; Seely, Andrew Je; Alfirevic, Zarko; Gao, Xin; Ferrazzi, Enrico

    2014-12-01

    Fetal monitoring during labour currently fails to accurately detect acidemia. We developed a method to assess the multidimensional properties of fetal heart rate variability (fHRV) from trans-abdominal fetal electrocardiogram (fECG) during labour. We aimed to assess this novel bioinformatics approach for correlation between fHRV and neonatal pH or base excess (BE) at birth.We enrolled a prospective pilot cohort of uncomplicated singleton pregnancies at 38-42 weeks' gestation in Milan, Italy, and Liverpool, UK. Fetal monitoring was performed by standard cardiotocography. Simultaneously, with fECG (high sampling frequency) was recorded. To ensure clinician blinding, fECG information was not displayed. Data from the last 60 min preceding onset of second-stage labour were analyzed using clinically validated continuous individualized multiorgan variability analysis (CIMVA) software in 5 min overlapping windows. CIMVA allows simultaneous calculation of 101 fHRV measures across five fHRV signal analysis domains. We validated our mathematical prediction model internally with 80:20 cross-validation split, comparing results to cord pH and BE at birth.The cohort consisted of 60 women with neonatal pH values at birth ranging from 7.44 to 6.99 and BE from -0.3 to -18.7 mmol L(-1). Our model predicted pH from 30 fHRV measures (R(2) = 0.90, P < 0.001) and BE from 21 fHRV measures (R(2) = 0.77, P < 0.001).Novel bioinformatics approach (CIMVA) applied to fHRV derived from trans-abdominal fECG during labor correlated well with acid-base balance at birth. Further refinement and validation in larger cohorts are needed. These new measurements of fHRV might offer a new opportunity to predict fetal acid-base balance at birth. PMID:25407948

  17. Fluorescence detection of single molecules using pulsed near-field optical excitation and time correlated photon counting

    SciTech Connect

    Ambrose, W.P.; Goodwin, P.M.; Martin, J.C.; Keller, R.A.

    1994-03-01

    Pulsed excitation, time correlated single photon counting and time gated detection are used in near-field optical microscopy to enhance fluorescence images and measure the fluorescence lifetimes of single molecules of Rhodamine 6G on silica surfaces. Time gated detection is used to reject prompt scattered background and to improve the image signal to noise ratio. The excited state lifetime of a single Rhodamine 6G molecule is found to depend on the position of the near-field probe. We attribute the lifetime variations to spontaneous emission rate alterations by the fluorescence reflected from and quenching by the aluminum coated probe.

  18. Fuzzy logic and optical correlation-based face recognition method for patient monitoring application in home video surveillance

    NASA Astrophysics Data System (ADS)

    Elbouz, Marwa; Alfalou, Ayman; Brosseau, Christian

    2011-06-01

    Home automation is being implemented into more and more domiciles of the elderly and disabled in order to maintain their independence and safety. For that purpose, we propose and validate a surveillance video system, which detects various posture-based events. One of the novel points of this system is to use adapted Vander-Lugt correlator (VLC) and joint-transfer correlator (JTC) techniques to make decisions on the identity of a patient and his three-dimensional (3-D) positions in order to overcome the problem of crowd environment. We propose a fuzzy logic technique to get decisions on the subject's behavior. Our system is focused on the goals of accuracy, convenience, and cost, which in addition does not require any devices attached to the subject. The system permits one to study and model subject responses to behavioral change intervention because several levels of alarm can be incorporated according different situations considered. Our algorithm performs a fast 3-D recovery of the subject's head position by locating eyes within the face image and involves a model-based prediction and optical correlation techniques to guide the tracking procedure. The object detection is based on (hue, saturation, value) color space. The system also involves an adapted fuzzy logic control algorithm to make a decision based on information given to the system. Furthermore, the principles described here are applicable to a very wide range of situations and robust enough to be implementable in ongoing experiments.

  19. Theoretical detection ranges for acoustic based manatee avoidance technology.

    PubMed

    Phillips, Richard; Niezrecki, Christopher; Beusse, Diedrich O

    2006-07-01

    The West Indian manatee (Trichechus manatus latirostris) has become endangered partly because of watercraft collisions in Florida's coastal waterways. To reduce the number of collisions, warning systems based upon detecting manatee vocalizations have been proposed. One aspect of the feasibility of an acoustically based warning system relies upon the distance at which a manatee vocalization is detectable. Assuming a mixed spreading model, this paper presents a theoretical analysis of the system detection capabilities operating within various background and watercraft noise conditions. This study combines measured source levels of manatee vocalizations with the modeled acoustic properties of manatee habitats to develop a method for determining the detection range and hydrophone spacing requirements for acoustic based manatee avoidance technologies. In quiet environments (background noise approximately 70 dB) it was estimated that manatee vocalizations are detectable at approximately 250 m, with a 6 dB detection threshold, In louder environments (background noise approximately 100dB) the detection range drops to 2.5 m. In a habitat with 90 dB of background noise, a passing boat with a maximum noise floor of 120 dB would be the limiting factor when it is within approximately 100 m of a hydrophone. The detection range was also found to be strongly dependent on the manatee vocalization source level.

  20. Theoretical detection ranges for acoustic based manatee avoidance technology.

    PubMed

    Phillips, Richard; Niezrecki, Christopher; Beusse, Diedrich O

    2006-07-01

    The West Indian manatee (Trichechus manatus latirostris) has become endangered partly because of watercraft collisions in Florida's coastal waterways. To reduce the number of collisions, warning systems based upon detecting manatee vocalizations have been proposed. One aspect of the feasibility of an acoustically based warning system relies upon the distance at which a manatee vocalization is detectable. Assuming a mixed spreading model, this paper presents a theoretical analysis of the system detection capabilities operating within various background and watercraft noise conditions. This study combines measured source levels of manatee vocalizations with the modeled acoustic properties of manatee habitats to develop a method for determining the detection range and hydrophone spacing requirements for acoustic based manatee avoidance technologies. In quiet environments (background noise approximately 70 dB) it was estimated that manatee vocalizations are detectable at approximately 250 m, with a 6 dB detection threshold, In louder environments (background noise approximately 100dB) the detection range drops to 2.5 m. In a habitat with 90 dB of background noise, a passing boat with a maximum noise floor of 120 dB would be the limiting factor when it is within approximately 100 m of a hydrophone. The detection range was also found to be strongly dependent on the manatee vocalization source level. PMID:16875213

  1. Structure-property correlation of Zr-base alloys

    NASA Astrophysics Data System (ADS)

    Wadekar, S. L.; Raman, V. V.; Banerjee, S.; Asundi, M. K.

    1988-01-01

    Zirconium alloys, because of their unique combination of high strength, good corrosion resistance in water and low capture cross-section for thermal neutrons, have become attractive for use as structural materials in the nuclear industry. Presently, Zircaloy-2 and Zircaloy-4 find wide application as fuel and pressure tube materials for water cooled power reactors. In order to understand how the various alloying elements of Zircaloy, namely Sn, Fe, Cr and Ni, affect the mechanical properties, a programme has been initiated to evolve a correlation between chemistry, microstructure and mechanical properties of Zr-alloy containing various amounts of Sn, Fe and Cr. In the present investigation, mechanical properties of Zr-alloys with various addition of Sn, Fe and Cr have been determined at 300 K and 573 K in various metallurgical conditions such as recrystallised annealed, β-quenched, tempered and α-annealed conditions. The study revealed that the reduced tin content dit not affect the mechanical properties as the reduced tin leads to formation of fine precipitates. The mechanical properties were also not altered drastically with the low level of iron and chromium concentrations studied. Cold work and α-annealing after β-quenching resulted in the growth and redistribution of second phase particles. Metallographie studies showed that particle distribution was not uniform. A TEM investigation of the alloys has also been undertaken to study the details of microstructure developed during various heat-treated conditions. It has been found that the β-quenched samples exhibit the most uniform microstructure consisting of acicular alpha phase with lath boundary enriched by solute element and fine intermetallic particle formation. The observed microstructural features together with the mechanical properties data have been compared with the available mechanical properties cum microstructure of Zircaloy.

  2. Transistor-based particle detection systems and methods

    DOEpatents

    Jain, Ankit; Nair, Pradeep R.; Alam, Muhammad Ashraful

    2015-06-09

    Transistor-based particle detection systems and methods may be configured to detect charged and non-charged particles. Such systems may include a supporting structure contacting a gate of a transistor and separating the gate from a dielectric of the transistor, and the transistor may have a near pull-in bias and a sub-threshold region bias to facilitate particle detection. The transistor may be configured to change current flow through the transistor in response to a change in stiffness of the gate caused by securing of a particle to the gate, and the transistor-based particle detection system may configured to detect the non-charged particle at least from the change in current flow.

  3. Gold Nanoparticles-Based Barcode Analysis for Detection of Norepinephrine.

    PubMed

    An, Jeung Hee; Lee, Kwon-Jai; Choi, Jeong-Woo

    2016-02-01

    Nanotechnology-based bio-barcode amplification analysis offers an innovative approach for detecting neurotransmitters. We evaluated the efficacy of this method for detecting norepinephrine in normal and oxidative-stress damaged dopaminergic cells. Our approach use a combination of DNA barcodes and bead-based immunoassays for detecting neurotransmitters with surface-enhanced Raman spectroscopy (SERS), and provides polymerase chain reaction (PCR)-like sensitivity. This method relies on magnetic Dynabeads containing antibodies and nanoparticles that are loaded both with DNA barcords and with antibodies that can sandwich the target protein captured by the Dynabead-bound antibodies. The aggregate sandwich structures are magnetically separated from the solution and treated to remove the conjugated barcode DNA. The DNA barcodes are then identified by SERS and PCR analysis. The concentration of norepinephrine in dopaminergic cells can be readily detected using the bio-barcode assay, which is a rapid, high-throughput screening tool for detecting neurotransmitters. PMID:27305769

  4. Infrared small target detection based on Danger Theory

    NASA Astrophysics Data System (ADS)

    Lan, Jinhui; Yang, Xiao

    2009-11-01

    To solve the problem that traditional method can't detect the small objects whose local SNR is less than 2 in IR images, a Danger Theory-based model to detect infrared small target is presented in this paper. First, on the analog with immunology, the definition is given, in this paper, to such terms as dangerous signal, antigens, APC, antibodies. Besides, matching rule between antigen and antibody is improved. Prior to training the detection model and detecting the targets, the IR images are processed utilizing adaptive smooth filter to decrease the stochastic noise. Then at the training process, deleting rule, generating rule, crossover rule and the mutation rule are established after a large number of experiments in order to realize immediate convergence and obtain good antibodies. The Danger Theory-based model is built after the training process, and this model can detect the target whose local SNR is only 1.5.

  5. Robust human motion detection via fuzzy set based image understanding

    NASA Astrophysics Data System (ADS)

    Li, Qin; You, Jane

    2006-02-01

    This paper presents an image understanding approach to monitor human movement and identify the abnormal circumstance by robust motion detection for the care of the elderly in a home-based environment. In contrast to the conventional approaches which apply either a single feature extraction scheme or a fixed object model for motion detection and tracking, we introduce a multiple feature extraction scheme for robust motion detection. The proposed algorithms include 1) multiple image feature extraction including the fuzzy compactness based detection of interesting points and fuzzy blobs, 2) adaptive image segmentation via multiple features, 3) Hierarchical motion detection, 4) a flexible model of human motion adapted in both rigid and non-rigid conditions, and 5) Fuzzy decision making via multiple features.

  6. Caption detection from video sequence based on fuzzy neural networks

    NASA Astrophysics Data System (ADS)

    Gao, Xinbo; Xin, Hong; Li, Jie

    2001-09-01

    Caption graphically superimposed in video frames can provide important indexing information. The automatic detection and recognition of video captions can be of great help in querying topics of interest in digital news library. To detect the caption from video sequence, we present algorithms based on fuzzy clustering neural networks. Since neural networks have the capabilities of learning and self-organizing and parallel computing mechanism, with the great increasing of digital images and video databases, neural networks based techniques become more efficient and popular tools for multimedia processing. Experimental results show that our caption detection scheme is effective and robust.

  7. Detecting a stochastic background of gravitational waves in the presence of non-Gaussian noise: A performance of generalized cross-correlation statistic

    SciTech Connect

    Himemoto, Yoshiaki; Hiramatsu, Takashi; Taruya, Atsushi; Kudoh, Hideaki

    2007-01-15

    We discuss a robust data analysis method to detect a stochastic background of gravitational waves in the presence of non-Gaussian noise. In contrast to the standard cross-correlation (SCC) statistic frequently used in the stochastic background searches, we consider a generalized cross-correlation (GCC) statistic, which is nearly optimal even in the presence of non-Gaussian noise. The detection efficiency of the GCC statistic is investigated analytically, particularly focusing on the statistical relation between the false-alarm and the false-dismissal probabilities, and the minimum detectable amplitude of gravitational-wave signals. We derive simple analytic formulas for these statistical quantities. The robustness of the GCC statistic is clarified based on these formulas, and one finds that the detection efficiency of the GCC statistic roughly corresponds to the one of the SCC statistic neglecting the contribution of non-Gaussian tails. This remarkable property is checked by performing the Monte Carlo simulations and successful agreement between analytic and simulation results was found.

  8. Spectral evolution of gamma-ray bursts detected by the SIGNE experiment. 1: Correlation between intensity and spectral hardness

    NASA Technical Reports Server (NTRS)

    Kargatis, Vincent E.; Liang, Edison P.; Hurley, Kevin C.; Barat, C.; Eveno, E.; Niel, M.

    1994-01-01

    We study the continuum spectral evolution of 16 gamma-ray bursts detected by the Franco-Soviet SIGNE experiment in 1981-1982 by fitting time resolved (0.5 s) spectra in count space with simple thermal bremsstrahlung and synchrotron models. We find that there is no single characteristic of spectral evolution: we see hard-to-soft, soft-to-hard, luminosity-hardness tracking, and chaotic evolution. We perform correlation studies between instantaneous burst intensity and spectral temperature for seven bursts. While we basically confirm the existence of a correlation between these variables as originally claimed by Golenetskii et al. (1983) we find higher values and a broader range of correlation indices.

  9. Detection of heavy metal by paper-based microfluidics.

    PubMed

    Lin, Yang; Gritsenko, Dmitry; Feng, Shaolong; Teh, Yi Chen; Lu, Xiaonan; Xu, Jie

    2016-09-15

    Heavy metal pollution has shown great threat to the environment and public health worldwide. Current methods for the detection of heavy metals require expensive instrumentation and laborious operation, which can only be accomplished in centralized laboratories. Various microfluidic paper-based analytical devices have been developed recently as simple, cheap and disposable alternatives to conventional ones for on-site detection of heavy metals. In this review, we first summarize current development of paper-based analytical devices and discuss the selection of paper substrates, methods of device fabrication, and relevant theories in these devices. We then compare and categorize recent reports on detection of heavy metals using paper-based microfluidic devices on the basis of various detection mechanisms, such as colorimetric, fluorescent, and electrochemical methods. To finalize, the future development and trend in this field are discussed. PMID:27131999

  10. Detection of heavy metal by paper-based microfluidics.

    PubMed

    Lin, Yang; Gritsenko, Dmitry; Feng, Shaolong; Teh, Yi Chen; Lu, Xiaonan; Xu, Jie

    2016-09-15

    Heavy metal pollution has shown great threat to the environment and public health worldwide. Current methods for the detection of heavy metals require expensive instrumentation and laborious operation, which can only be accomplished in centralized laboratories. Various microfluidic paper-based analytical devices have been developed recently as simple, cheap and disposable alternatives to conventional ones for on-site detection of heavy metals. In this review, we first summarize current development of paper-based analytical devices and discuss the selection of paper substrates, methods of device fabrication, and relevant theories in these devices. We then compare and categorize recent reports on detection of heavy metals using paper-based microfluidic devices on the basis of various detection mechanisms, such as colorimetric, fluorescent, and electrochemical methods. To finalize, the future development and trend in this field are discussed.

  11. Noise-immune complex correlation for optical coherence angiography based on standard and Jones matrix optical coherence tomography

    PubMed Central

    Makita, Shuichi; Kurokawa, Kazuhiro; Hong, Young-Joo; Miura, Masahiro; Yasuno, Yoshiaki

    2016-01-01

    This paper describes a complex correlation mapping algorithm for optical coherence angiography (cmOCA). The proposed algorithm avoids the signal-to-noise ratio dependence and exhibits low noise in vasculature imaging. The complex correlation coefficient of the signals, rather than that of the measured data are estimated, and two-step averaging is introduced. Algorithms of motion artifact removal based on non perfusing tissue detection using correlation are developed. The algorithms are implemented with Jones-matrix OCT. Simultaneous imaging of pigmented tissue and vasculature is also achieved using degree of polarization uniformity imaging with cmOCA. An application of cmOCA to in vivo posterior human eyes is presented to demonstrate that high-contrast images of patients’ eyes can be obtained. PMID:27446673

  12. Screen-detected breast carcinoma with macroscopic dystrophic calcification: A pictorial essay with radiolological pathological correlation.

    PubMed

    Ebrahim, Lamya; Dissanayake, Deepthi; Metcalf, Cecily; Wylie, Elizabeth

    2016-04-01

    Breast calcifications are among the most common abnormal radiographic findings detected at screening mammography. This essay illustrates the clinico-pathological features of nine screen-detected breast carcinomas, which had benign-appearing macrocalcifications, as a radiographically dominant presenting feature. We aimed to demonstrate that benign-appearing calcifications within a breast lesion are not diagnostic of a benign process if the other imaging characteristics of the lesion are suspicious of malignancy.

  13. [Mutual information-based correlation analysis of herbs against insomnia].

    PubMed

    Tian, Jin; Liu, Ren-quan

    2015-10-01

    This paper aims to analyze Professor Guo Rongjuan's medication experience on insomnia therapy based on the Traditional Chinese Medicine (TCM) Inheritance Support Plat. First, TCM formulae prescribed by Professor Guo for insomnia therapy were collected from the TCM Inheritance Support Plat. Next, unsupervised data mining algorithms, including apriori, modified mutual-information, and entropy clustering of complex system were applied to obtain the frequencies for different herbs and identify the association rules among the herbs. Accordingly, we can gain new insights into Professor Guo's medication experience on insomnia therapy. Based on analysis of 3 084 formulae, we determined the frequencies for herbs in the formulae and identified the association rules among these herbs. At last, 41 core combinations and 7 new formulae were obtained. The identified medication experience conform with Professor Guo's views on the etiology and pathogenesis of insomnia: "pathogenic fire derived from stagnation of liver-QI (Gan Yu Hua Huo)" is the core pathogenesis of insomnia; "liver stagnation and spleen deficiency" and "chronic illness transferred to kidney" are the main features for insomnia. The TCM Inheritance Support Plat is of great practical value for mining clinical experience of famous TCM doctors.

  14. A feature-based model of symmetry detection.

    PubMed Central

    Scognamillo, Renata; Rhodes, Gillian; Morrone, Concetta; Burr, David

    2003-01-01

    Symmetry detection is important for many biological visual systems, including those of mammals, insects and birds. We constructed a symmetry-detection algorithm with two stages: location of the visually salient features of the image, then evaluating the symmetry of these features over a long range, by means of a simple Gaussian filter. The algorithm detects the axis of maximum symmetry for human faces (or any arbitrary image) and calculates the magnitude of the asymmetry. We have evaluated the algorithm on the dataset of Rhodes et al. (1998 Psychonom. Bull. Rev. 5, 659-669) and found that the algorithm is able to discriminate small variations of symmetry created by computer-manipulating the symmetry levels in individual faces, and that the values measured by the algorithm correlate well with human psycho-physical symmetry ratings. PMID:12965001

  15. Multicriteria Similarity-Based Anomaly Detection Using Pareto Depth Analysis.

    PubMed

    Hsiao, Ko-Jen; Xu, Kevin S; Calder, Jeff; Hero, Alfred O

    2016-06-01

    We consider the problem of identifying patterns in a data set that exhibits anomalous behavior, often referred to as anomaly detection. Similarity-based anomaly detection algorithms detect abnormally large amounts of similarity or dissimilarity, e.g., as measured by the nearest neighbor Euclidean distances between a test sample and the training samples. In many application domains, there may not exist a single dissimilarity measure that captures all possible anomalous patterns. In such cases, multiple dissimilarity measures can be defined, including nonmetric measures, and one can test for anomalies by scalarizing using a nonnegative linear combination of them. If the relative importance of the different dissimilarity measures are not known in advance, as in many anomaly detection applications, the anomaly detection algorithm may need to be executed multiple times with different choices of weights in the linear combination. In this paper, we propose a method for similarity-based anomaly detection using a novel multicriteria dissimilarity measure, the Pareto depth. The proposed Pareto depth analysis (PDA) anomaly detection algorithm uses the concept of Pareto optimality to detect anomalies under multiple criteria without having to run an algorithm multiple times with different choices of weights. The proposed PDA approach is provably better than using linear combinations of the criteria, and shows superior performance on experiments with synthetic and real data sets.

  16. Hierarchical clustering of EMD based interest points for road sign detection

    NASA Astrophysics Data System (ADS)

    Khan, Jesmin; Bhuiyan, Sharif; Adhami, Reza

    2014-04-01

    This paper presents an automatic road traffic signs detection and recognition system based on hierarchical clustering of interest points and joint transform correlation. The proposed algorithm consists of the three following stages: interest points detection, clustering of those points and similarity search. At the first stage, good discriminative, rotation and scale invariant interest points are selected from the image edges based on the 1-D empirical mode decomposition (EMD). We propose a two-step unsupervised clustering technique, which is adaptive and based on two criterion. In this context, the detected points are initially clustered based on the stable local features related to the brightness and color, which are extracted using Gabor filter. Then points belonging to each partition are reclustered depending on the dispersion of the points in the initial cluster using position feature. This two-step hierarchical clustering yields the possible candidate road signs or the region of interests (ROIs). Finally, a fringe-adjusted joint transform correlation (JTC) technique is used for matching the unknown signs with the existing known reference road signs stored in the database. The presented framework provides a novel way to detect a road sign from the natural scenes and the results demonstrate the efficacy of the proposed technique, which yields a very low false hit rate.

  17. Effective and Efficient Correlation Analysis with Application to Market Basket Analysis and Network Community Detection

    ERIC Educational Resources Information Center

    Duan, Lian

    2012-01-01

    Finding the most interesting correlations among items is essential for problems in many commercial, medical, and scientific domains. For example, what kinds of items should be recommended with regard to what has been purchased by a customer? How to arrange the store shelf in order to increase sales? How to partition the whole social network into…

  18. Modified friction factor correlation for CICC's based on a porous media analogy

    NASA Astrophysics Data System (ADS)

    Lewandowska, Monika; Bagnasco, Maurizio

    2011-09-01

    A modified correlation for the bundle friction factor in CICC's based on a porous media analogy is presented. The correlation is obtained by the analysis of the collected pressure drop data measured for 23 CICC's. The friction factors predicted by the proposed correlation are compared with those resulting from the pressure drop data for two CICC's measured recently using cryogenic helium in the SULTAN test facility at EPFL-CRPP.

  19. Adaptive Rule Based Fetal QRS Complex Detection Using Hilbert Transform

    PubMed Central

    Ulusar, Umit D.; Govindan, R.B.; Wilson, James D.; Lowery, Curtis L.; Preissl, Hubert; Eswaran, Hari

    2010-01-01

    In this paper we introduce an adaptive rule based QRS detection algorithm using the Hilbert transform (adHQRS) for fetal magnetocardiography processing. Hilbert transform is used to combine multiple channel measurements and the adaptive rule based decision process is used to eliminate spurious beats. The algorithm has been tested with a large number of datasets and promising results were obtained. PMID:19964648

  20. Ion Beam Analysis Of Silicon-Based Surfaces And Correlation With Surface Energy Measurements

    NASA Astrophysics Data System (ADS)

    Xing, Qian; Herbots, N.; Hart, M.; Bradley, J. D.; Wilkens, B. J.; Sell, D. A.; Sell, Clive H.; Kwong, Henry Mark; Culbertson, R. J.; Whaley, S. D.

    2011-06-01

    The water affinity of Si-based surfaces is quantified by contact angle measurement and surface free energy to explain hydrophobic or hydrophilic behavior of silicone, silicates, and silicon surfaces. Surface defects such as dangling bonds, surface free energy including Lewis acid-base and Lifshitz-van der Waals components are discussed. Water nucleation and condensation is further explained by surface topography. Tapping mode atomic force microscopy (TMAFM) provides statistical analysis of the topography of these Si-based surfaces. The correlation of the above two characteristics describes the behavior of water condensation at Si-based surfaces. Surface root mean square roughness increasing from several Å to several nm is found to provide nucleation sites that expedite water condensation visibly for silica and silicone. Hydrophilic surfaces have a condensation pattern that forms puddles of water while hydrophobic surfaces form water beads. Polymer adsorption on these surfaces alters the water affinity as well as the surface topography, and therefore controls condensation on Si-based surfaces including silicone intraocular lens (IOL). The polymer film is characterized by Rutherford backscattering spectrometry (RBS) in conjunction with 4.265 MeV 12C(α, α)12C, 3.045 MeV 16O(α,α)16O nuclear resonance scattering (NRS), and 2.8 MeV elastic recoil detection (ERD) of hydrogen for high resolution composition and areal density measurements. The areal density of hydroxypropyl methylcellulose (HPMC) film ranges from 1018 atom/cm2 to 1019 atom/cm2 gives the silica or silicone surface a roughness of several Å and a wavelength of 0.16±0.02 μm, and prevents fogging by forming a complete wetting layer during water condensation.

  1. Ion Beam Analysis Of Silicon-Based Surfaces And Correlation With Surface Energy Measurements

    SciTech Connect

    Xing Qian; Herbots, N.; Hart, M.; Bradley, J. D.; Wilkens, B. J.; Sell, D. A.; Culbertson, R. J.; Whaley, S. D.; Sell, Clive H.; Kwong, Henry Mark Jr.

    2011-06-01

    The water affinity of Si-based surfaces is quantified by contact angle measurement and surface free energy to explain hydrophobic or hydrophilic behavior of silicone, silicates, and silicon surfaces. Surface defects such as dangling bonds, surface free energy including Lewis acid-base and Lifshitz-van der Waals components are discussed. Water nucleation and condensation is further explained by surface topography. Tapping mode atomic force microscopy (TMAFM) provides statistical analysis of the topography of these Si-based surfaces. The correlation of the above two characteristics describes the behavior of water condensation at Si-based surfaces. Surface root mean square roughness increasing from several A ring to several nm is found to provide nucleation sites that expedite water condensation visibly for silica and silicone. Hydrophilic surfaces have a condensation pattern that forms puddles of water while hydrophobic surfaces form water beads. Polymer adsorption on these surfaces alters the water affinity as well as the surface topography, and therefore controls condensation on Si-based surfaces including silicone intraocular lens (IOL). The polymer film is characterized by Rutherford backscattering spectrometry (RBS) in conjunction with 4.265 MeV {sup 12}C({alpha}, {alpha}){sup 12}C, 3.045 MeV {sup 16}O({alpha},{alpha}){sup 16}O nuclear resonance scattering (NRS), and 2.8 MeV elastic recoil detection (ERD) of hydrogen for high resolution composition and areal density measurements. The areal density of hydroxypropyl methylcellulose (HPMC) film ranges from 10{sup 18} atom/cm{sup 2} to 10{sup 19} atom/cm{sup 2} gives the silica or silicone surface a roughness of several A ring and a wavelength of 0.16{+-}0.02 {mu}m, and prevents fogging by forming a complete wetting layer during water condensation.

  2. Cavity enhanced detection methods for probing the dynamics of spin correlated radical pairs in solution

    NASA Astrophysics Data System (ADS)

    Neil, Simon R. T.; Maeda, Kiminori; Henbest, Kevin B.; Goez, Martin; Hemmens, Robert; Timmel, Christiane R.; Mackenzie, Stuart R.

    2010-04-01

    Cavity enhanced absorption spectroscopy (CEAS) combined with phase-sensitive detection is employed to study the effects of static magnetic fields on radical recombination reactions. The chemical system comprises the photochemically generated thionine semiquinone radical and a 1,4-diazabicyclo[2.2.2]octane (DABCO) cationic radical in a micellar solution of sodium dodecyl sulphate. Data obtained using the modulated CEAS technique, describing the magnetic field effect (MFE) on reaction yields, are shown to be superior to those obtained using conventional transient absorption (TA) flash photolysis methods typically employed for these measurements. The high sensitivity afforded by modulated CEAS detection is discussed in terms of the new possibilities it offers such as the measurement of magnetic field effects in real biological systems which have hitherto been largely beyond the detection capabilities of existing techniques.

  3. Weighted ensemble based automatic detection of exudates in fundus photographs.

    PubMed

    Prentasic, Pavle; Loncaric, Sven

    2014-01-01

    Diabetic retinopathy (DR) is a visual complication of diabetes, which has become one of the leading causes of preventable blindness in the world. Exudate detection is an important problem in automatic screening systems for detection of diabetic retinopathy using color fundus photographs. In this paper, we present a method for detection of exudates in color fundus photographs, which combines several preprocessing and candidate extraction algorithms to increase the exudate detection accuracy. The first stage of the method consists of an ensemble of several exudate candidate extraction algorithms. In the learning phase, simulated annealing is used to determine weights for combining the results of the ensemble candidate extraction algorithms. The second stage of the method uses a machine learning-based classification for detection of exudate regions. The experimental validation was performed using the DRiDB color fundus image set. The validation has demonstrated that the proposed method achieved higher accuracy in comparison to state-of-the art methods.

  4. Distributed intrusion detection system based on fuzzy rules

    NASA Astrophysics Data System (ADS)

    Qiao, Peili; Su, Jie; Liu, Yahui

    2006-04-01

    Computational Intelligence is the theory and method solving problems by simulating the intelligence of human using computer and it is the development of Artificial Intelligence. Fuzzy Technique is one of the most important theories of computational Intelligence. Genetic Fuzzy Technique and Neuro-Fuzzy Technique are the combination of Fuzzy Technique and novel techniques. This paper gives a distributed intrusion detection system based on fuzzy rules that has the characters of distributed parallel processing, self-organization, self-learning and self-adaptation by the using of Neuro-Fuzzy Technique and Genetic Fuzzy Technique. Specially, fuzzy decision technique can be used to reduce false detection. The results of the simulation experiment show that this intrusion detection system model has the characteristics of distributed, error tolerance, dynamic learning, and adaptation. It solves the problem of low identifying rate to new attacks and hidden attacks. The false detection rate is low. This approach is efficient to the distributed intrusion detection.

  5. Nanomaterial-Based Biosensors for Detection of Pesticides and Explosives

    SciTech Connect

    Wang, Jun; Lin, Yuehe

    2009-01-01

    In this chapter, we describe nanomaterial-based biosensors for detecting OP pesticides and explosives. CNTs and functionalized silica nanoparticles have been chosen for this study. The biosensors were combined with the flow-injection system, providing great advantages for onsite, real-time, and continuous detection of environmental pollutants such as OPs and TNT. The sensors take advantage of the electrocatalytic properties of CNTs, which makes it feasible to achieve a sensitive electrochemical detection of the products from enzymatic reactions at low potential. This approach uses a large aspect ratio of silica nanoparticles, which can be used as a carrier for loading a large amount of electroactive species, such as poly(guanine), for amplified detection of explosives. These methods offer a new environmental monitoring tool for rapid, inexpensive, and highly sensitive detection of OPs or TNT compounds.

  6. Phase demodulation from a single fringe pattern based on a correlation technique.

    PubMed

    Robin, Eric; Valle, Valéry

    2004-08-01

    We present a method for determining the demodulated phase from a single fringe pattern. This method, based on a correlation technique, searches in a zone of interest for the degree of similarity between a real fringe pattern and a mathematical model. This method, named modulated phase correlation, is tested with different examples. PMID:15298408

  7. Research of Reticle Detection System Based on Mobile Platform

    NASA Astrophysics Data System (ADS)

    Ding, Haiyang; Wang, Mingfei

    This paper indicates a reticle detection system base on mobile platform. We establish a detection system base on mobile platform, and the goal of this system is detection of the centers of reticles. After capturing the image of reticles, the system gets four reticle images for Y, M, C, K purity color through image segmentation. In this paper, the system mainly to solve the detection for rotational reticles, and the system uses the approach that two points determine a straight line, and two straight lines determine an intersection, and the intersection is the center position of one reticle. At last, through comparing the center positions of four reticles, the system can obtain the conclusion whether four-color printing overprint accurately, and if they don't overprint accurately, the system can calculate the relative deviation between different color printings.

  8. Stratification-Based Outlier Detection over the Deep Web

    PubMed Central

    Xian, Xuefeng; Zhao, Pengpeng; Sheng, Victor S.; Fang, Ligang; Gu, Caidong; Yang, Yuanfeng; Cui, Zhiming

    2016-01-01

    For many applications, finding rare instances or outliers can be more interesting than finding common patterns. Existing work in outlier detection never considers the context of deep web. In this paper, we argue that, for many scenarios, it is more meaningful to detect outliers over deep web. In the context of deep web, users must submit queries through a query interface to retrieve corresponding data. Therefore, traditional data mining methods cannot be directly applied. The primary contribution of this paper is to develop a new data mining method for outlier detection over deep web. In our approach, the query space of a deep web data source is stratified based on a pilot sample. Neighborhood sampling and uncertainty sampling are developed in this paper with the goal of improving recall and precision based on stratification. Finally, a careful performance evaluation of our algorithm confirms that our approach can effectively detect outliers in deep web. PMID:27313603

  9. Stratification-Based Outlier Detection over the Deep Web.

    PubMed

    Xian, Xuefeng; Zhao, Pengpeng; Sheng, Victor S; Fang, Ligang; Gu, Caidong; Yang, Yuanfeng; Cui, Zhiming

    2016-01-01

    For many applications, finding rare instances or outliers can be more interesting than finding common patterns. Existing work in outlier detection never considers the context of deep web. In this paper, we argue that, for many scenarios, it is more meaningful to detect outliers over deep web. In the context of deep web, users must submit queries through a query interface to retrieve corresponding data. Therefore, traditional data mining methods cannot be directly applied. The primary contribution of this paper is to develop a new data mining method for outlier detection over deep web. In our approach, the query space of a deep web data source is stratified based on a pilot sample. Neighborhood sampling and uncertainty sampling are developed in this paper with the goal of improving recall and precision based on stratification. Finally, a careful performance evaluation of our algorithm confirms that our approach can effectively detect outliers in deep web.

  10. Enhancing Community Detection By Affinity-based Edge Weighting Scheme

    SciTech Connect

    Yoo, Andy; Sanders, Geoffrey; Henson, Van; Vassilevski, Panayot

    2015-10-05

    Community detection refers to an important graph analytics problem of finding a set of densely-connected subgraphs in a graph and has gained a great deal of interest recently. The performance of current community detection algorithms is limited by an inherent constraint of unweighted graphs that offer very little information on their internal community structures. In this paper, we propose a new scheme to address this issue that weights the edges in a given graph based on recently proposed vertex affinity. The vertex affinity quantifies the proximity between two vertices in terms of their clustering strength, and therefore, it is ideal for graph analytics applications such as community detection. We also demonstrate that the affinity-based edge weighting scheme can improve the performance of community detection algorithms significantly.

  11. Efficient method of image edge detection based on FSVM

    NASA Astrophysics Data System (ADS)

    Cai, Aiping; Xiong, Xiaomei

    2013-07-01

    For efficient object cover edge detection in digital images, this paper studied traditional methods and algorithm based on SVM. It analyzed Canny edge detection algorithm existed some pseudo-edge and poor anti-noise capability. In order to provide a reliable edge extraction method, propose a new detection algorithm based on FSVM. Which contains several steps: first, trains classify sample and gives the different membership function to different samples. Then, a new training sample is formed by increase the punishment some wrong sub-sample, and use the new FSVM classification model for train and test them. Finally the edges are extracted of the object image by using the model. Experimental result shows that good edge detection image will be obtained and adding noise experiments results show that this method has good anti-noise.

  12. A dynamic bead-based microarray for parallel DNA detection

    NASA Astrophysics Data System (ADS)

    Sochol, R. D.; Casavant, B. P.; Dueck, M. E.; Lee, L. P.; Lin, L.

    2011-05-01

    A microfluidic system has been designed and constructed by means of micromachining processes to integrate both microfluidic mixing of mobile microbeads and hydrodynamic microbead arraying capabilities on a single chip to simultaneously detect multiple bio-molecules. The prototype system has four parallel reaction chambers, which include microchannels of 18 × 50 µm2 cross-sectional area and a microfluidic mixing section of 22 cm length. Parallel detection of multiple DNA oligonucleotide sequences was achieved via molecular beacon probes immobilized on polystyrene microbeads of 16 µm diameter. Experimental results show quantitative detection of three distinct DNA oligonucleotide sequences from the Hepatitis C viral (HCV) genome with single base-pair mismatch specificity. Our dynamic bead-based microarray offers an effective microfluidic platform to increase parallelization of reactions and improve microbead handling for various biological applications, including bio-molecule detection, medical diagnostics and drug screening.

  13. The Unknown Computer Viruses Detection Based on Similarity

    NASA Astrophysics Data System (ADS)

    Liu, Zhongda; Nakaya, Naoshi; Koui, Yuuji

    New computer viruses are continually being generated and they cause damage all over the world. In general, current anti-virus software detects viruses by matching a pattern based on the signature; thus, unknown viruses without any signature cannot be detected. Although there are some static analysis technologies that do not depend on signatures, virus writers often use code obfuscation techniques, which make it difficult to execute a code analysis. As is generally known, unknown viruses and known viruses share a common feature. In this paper we propose a new static analysis technology that can circumvent code obfuscation to extract the common feature and detect unknown viruses based on similarity. The results of evaluation experiments demonstrated that this technique is able to detect unknown viruses without false positives.

  14. Stratification-Based Outlier Detection over the Deep Web.

    PubMed

    Xian, Xuefeng; Zhao, Pengpeng; Sheng, Victor S; Fang, Ligang; Gu, Caidong; Yang, Yuanfeng; Cui, Zhiming

    2016-01-01

    For many applications, finding rare instances or outliers can be more interesting than finding common patterns. Existing work in outlier detection never considers the context of deep web. In this paper, we argue that, for many scenarios, it is more meaningful to detect outliers over deep web. In the context of deep web, users must submit queries through a query interface to retrieve corresponding data. Therefore, traditional data mining methods cannot be directly applied. The primary contribution of this paper is to develop a new data mining method for outlier detection over deep web. In our approach, the query space of a deep web data source is stratified based on a pilot sample. Neighborhood sampling and uncertainty sampling are developed in this paper with the goal of improving recall and precision based on stratification. Finally, a careful performance evaluation of our algorithm confirms that our approach can effectively detect outliers in deep web. PMID:27313603

  15. a Uav-Based ROE Deer Fawn Detection System

    NASA Astrophysics Data System (ADS)

    Israel, M.

    2011-09-01

    This paper presents a UAV based remote sensing system for the detection of fawns in the meadows. There is a high demand because during pasture mowing many wild animals, especially roe deer fawns are killed by mowing machines. The system was tested in several real situations especially with differing weather and iluminating conditions. Its primary sensor is a lightweight thermal infrared camera. The images are captured onboard of the flight system and also transmitted as analog video stream to the ground station, where the user can follow the camera live stream on a monitor for manual animal detection. Beside a high detection rate a fast workflow is another very important objective for this application. Therefore a waypoint planning software was developed that accelerates the workflow. At adequate illuminating and weather conditions the presented UAV-based fawn detection via thermal imaging is a comfortable, fast and reliable method.

  16. Serum Creatinine Detection by a Conducting Polymer Based Electrochemical Sensor to Identify Allograft Dysfunction

    PubMed Central

    Wei, Fang; Cheng, Scott; Korin, Yael; Reed, Elaine F.; Gjertson, David; Ho, Chih-ming; Gritsch, H. Albin; Veale, Jeffrey

    2015-01-01

    Kidney transplant recipients who have abnormally high creatinine levels in their blood often have allograft dysfunction secondary to rejection. Creatinine has become the preferred marker for renal dysfunction and is readily available in hospital clinical settings. We developed a rapid and accurate polymer-based electrochemical point-of-care (POC) assay for creatinine detection from whole blood to identify allograft dysfunction. The creatinine concentrations of 19 blood samples from transplant recipients were measured directly from clinical serum samples by the conducting polymer based electrochemical (EC) sensor arrays. These measurements were compared to the traditional clinical laboratory assay. The time required for detection was less than 5 minutes from sample loading. Sensitivity of the detection was found to be 0.46 mg/dL of creatinine with only 40 μL sample in the creatinine concentration range of 0 mg/dL to 11.33 mg/dL. Signal levels that were detected electrochemically correlated closely with the creatinine blood concentration detected by the UCLA Ronald Reagan Medical Center traditional clinical laboratory assay (correlation coefficient 0.94). This work is encouraging for the development of a rapid and accurate POCT device for measuring creatinine levels in whole blood. PMID:22881369

  17. Knowledge-based architecture for airborne mine and minefield detection

    NASA Astrophysics Data System (ADS)

    Agarwal, Sanjeev; Menon, Deepak; Swonger, C. W.

    2004-09-01

    One of the primary lessons learned from airborne mid-wave infrared (MWIR) based mine and minefield detection research and development over the last few years has been the fact that no single algorithm or static detection architecture is able to meet mine and minefield detection performance specifications. This is true not only because of the highly varied environmental and operational conditions under which an airborne sensor is expected to perform but also due to the highly data dependent nature of sensors and algorithms employed for detection. Attempts to make the algorithms themselves more robust to varying operating conditions have only been partially successful. In this paper, we present a knowledge-based architecture to tackle this challenging problem. The detailed algorithm architecture is discussed for such a mine/minefield detection system, with a description of each functional block and data interface. This dynamic and knowledge-driven architecture will provide more robust mine and minefield detection for a highly multi-modal operating environment. The acquisition of the knowledge for this system is predominantly data driven, incorporating not only the analysis of historical airborne mine and minefield imagery data collection, but also other "all source data" that may be available such as terrain information and time of day. This "all source data" is extremely important and embodies causal information that drives the detection performance. This information is not being used by current detection architectures. Data analysis for knowledge acquisition will facilitate better understanding of the factors that affect the detection performance and will provide insight into areas for improvement for both sensors and algorithms. Important aspects of this knowledge-based architecture, its motivations and the potential gains from its implementation are discussed, and some preliminary results are presented.

  18. Detecting Nonlinear Associations, Plus Comments on Testing Hypotheses about the Correlation Coefficient.

    ERIC Educational Resources Information Center

    Wilcox, Rand R.

    2001-01-01

    Discusses problems in detecting nonlinear associations and investigates the use of two statistics for this purpose. Simulation results suggest that the Cramer-von Mises form of the test statistic is generally better than the Kolmogorov-Smirnov form. Discusses the power of this method. (SLD)

  19. Detection of material property errors in handbooks and databases using artificial neural networks with hidden correlations

    NASA Astrophysics Data System (ADS)

    Zhang, Y. M.; Evans, J. R. G.; Yang, S. F.

    2010-11-01

    The authors have discovered a systematic, intelligent and potentially automatic method to detect errors in handbooks and stop their transmission using unrecognised relationships between materials properties. The scientific community relies on the veracity of scientific data in handbooks and databases, some of which have a long pedigree covering several decades. Although various outlier-detection procedures are employed to detect and, where appropriate, remove contaminated data, errors, which had not been discovered by established methods, were easily detected by our artificial neural network in tables of properties of the elements. We started using neural networks to discover unrecognised relationships between materials properties and quickly found that they were very good at finding inconsistencies in groups of data. They reveal variations from 10 to 900% in tables of property data for the elements and point out those that are most probably correct. Compared with the statistical method adopted by Ashby and co-workers [Proc. R. Soc. Lond. Ser. A 454 (1998) p. 1301, 1323], this method locates more inconsistencies and could be embedded in database software for automatic self-checking. We anticipate that our suggestion will be a starting point to deal with this basic problem that affects researchers in every field. The authors believe it may eventually moderate the current expectation that data field error rates will persist at between 1 and 5%.

  20. Tomosynthesis-detected Architectural Distortion: Management Algorithm with Radiologic-Pathologic Correlation.

    PubMed

    Durand, Melissa A; Wang, Steven; Hooley, Regina J; Raghu, Madhavi; Philpotts, Liane E

    2016-01-01

    As use of digital breast tomosynthesis becomes increasingly widespread, new management challenges are inevitable because tomosynthesis may reveal suspicious lesions not visible at conventional two-dimensional (2D) full-field digital mammography. Architectural distortion is a mammographic finding associated with a high positive predictive value for malignancy. It is detected more frequently at tomosynthesis than at 2D digital mammography and may even be occult at conventional 2D imaging. Few studies have focused on tomosynthesis-detected architectural distortions to date, and optimal management of these distortions has yet to be well defined. Since implementing tomosynthesis at our institution in 2011, we have learned some practical ways to assess architectural distortion. Because distortions may be subtle, tomosynthesis localization tools plus improved visualization of adjacent landmarks are crucial elements in guiding mammographic identification of elusive distortions. These same tools can guide more focused ultrasonography (US) of the breast, which facilitates detection and permits US-guided tissue sampling. Some distortions may be sonographically occult, in which case magnetic resonance imaging may be a reasonable option, both to increase diagnostic confidence and to provide a means for image-guided biopsy. As an alternative, tomosynthesis-guided biopsy, conventional stereotactic biopsy (when possible), or tomosynthesis-guided needle localization may be used to achieve tissue diagnosis. Practical uses for tomosynthesis in evaluation of architectural distortion are highlighted, potential complications are identified, and a working algorithm for management of tomosynthesis-detected architectural distortion is proposed. PMID:26963448

  1. Algorithm for detecting human faces based on convex-hull

    NASA Astrophysics Data System (ADS)

    Park, Minsick; Park, Chang-Woo; Park, Mignon; Lee, Chang-Hoon

    2002-03-01

    In this paper, we proposed a new method to detect faces in color based on the convex-hull. We detect two kinds of regions that are skin and hair likeness region. After preprocessing, we apply the convex-hull to their regions and can find a face from their intersection relationship. The proposed algorithm can accomplish face detection in an image involving rotated and turned faces as well as several faces. To validity the effectiveness of the proposed method, we make experiment with various cases.

  2. Moving target detection algorithm based on Gaussian mixture model

    NASA Astrophysics Data System (ADS)

    Wang, Zhihua; Kai, Du; Zhang, Xiandong

    2013-07-01

    In real-time video surveillance system, background noise and disturbance for the detection of moving objects will have a significant impact. The traditional Gaussian mixture model;GMM&;has strong adaptive various complex background ability, but slow convergence speed and vulnerable to illumination change influence. the paper proposes an improved moving target detection algorithm based on Gaussian mixture model which increase the convergence rate of foreground to the background model transformation and introducing the concept of the changing factors, through the three frame differential method solved light mutation problem. The results show that this algorithm can improve the accuracy of the moving object detection, and has good stability and real-time.

  3. Fiber-Optic Based Compact Gas Leak Detection System

    NASA Technical Reports Server (NTRS)

    deGroot, Wim A.

    1995-01-01

    A propellant leak detection system based on Raman scattering principles is introduced. The proposed system is flexible and versatile as the result of the use of optical fibers. It is shown that multiple species can be monitored simultaneously. In this paper oxygen, nitrogen, carbon monoxide, and hydrogen are detected and monitored. The current detection sensitivity for both hydrogen and carbon monoxide is 1% partial pressure at ambient conditions. The sensitivity for oxygen and nitrogen is 0.5% partial pressure. The response time to changes in species concentration is three minutes. This system can be used to monitor multiple species at several locations.

  4. Nuclear-based explosives detection in an airport environment

    SciTech Connect

    Bell, C.J.

    1994-12-31

    Beginning in the 1970`s The FAA has been developing techniques for detection of explosives in airline passenger luggage and/or air cargo. One general class of techniques of interest are those based on nuclear phenomena. Any system to be deployed in an airport must detect high explosives in sub-kilogram quantities while processing 600 bags/hour. Systems must meet the standards of regulatory agencies such as the FDA and/or NRC. In addition, installation of explosives detection systems at airports should neither require major alteration of facilities nor significantly disrupt normal operations.

  5. Deceiving entropy-based DoS detection

    NASA Astrophysics Data System (ADS)

    Özçelik, Ä.°lker; Brooks, Richard R.

    2014-06-01

    Denial of Service (DoS) attacks disable network services for legitimate users. A McAfee report shows that eight out of ten Critical Infrastructure Providers (CIPs) surveyed had a significant Distributed DoS (DDoS) attack in 2010.1 Researchers proposed many approaches for detecting these attacks in the past decade. Anomaly based DoS detection is the most common. In this approach, the detector uses statistical features; such as the entropy of incoming packet header fields like source IP addresses or protocol type. It calculates the observed statistical feature and triggers an alarm if an extreme deviation occurs. However, intrusion detection systems (IDS) using entropy based detection can be fooled by spoofing. An attacker can sniff the network to collect header field data of network packets coming from distributed nodes on the Internet and fuses them to calculate the entropy of normal background traffic. Then s/he can spoof attack packets to keep the entropy value in the expected range during the attack. In this study, we present a proof of concept entropy spoofing attack that deceives entropy based detection approaches. Our preliminary results show that spoofing attacks cause significant detection performance degradation.

  6. Automatic food intake detection based on swallowing sounds

    PubMed Central

    Makeyev, Oleksandr; Lopez-Meyer, Paulo; Schuckers, Stephanie; Besio, Walter; Sazonov, Edward

    2012-01-01

    This paper presents a novel fully automatic food intake detection methodology, an important step toward objective monitoring of ingestive behavior. The aim of such monitoring is to improve our understanding of eating behaviors associated with obesity and eating disorders. The proposed methodology consists of two stages. First, acoustic detection of swallowing instances based on mel-scale Fourier spectrum features and classification using support vector machines is performed. Principal component analysis and a smoothing algorithm are used to improve swallowing detection accuracy. Second, the frequency of swallowing is used as a predictor for detection of food intake episodes. The proposed methodology was tested on data collected from 12 subjects with various degrees of adiposity. Average accuracies of >80% and >75% were obtained for intra-subject and inter-subject models correspondingly with a temporal resolution of 30s. Results obtained on 44.1 hours of data with a total of 7305 swallows show that detection accuracies are comparable for obese and lean subjects. They also suggest feasibility of food intake detection based on swallowing sounds and potential of the proposed methodology for automatic monitoring of ingestive behavior. Based on a wearable non-invasive acoustic sensor the proposed methodology may potentially be used in free-living conditions. PMID:23125873

  7. Vision-Based People Detection System for Heavy Machine Applications

    PubMed Central

    Fremont, Vincent; Bui, Manh Tuan; Boukerroui, Djamal; Letort, Pierrick

    2016-01-01

    This paper presents a vision-based people detection system for improving safety in heavy machines. We propose a perception system composed of a monocular fisheye camera and a LiDAR. Fisheye cameras have the advantage of a wide field-of-view, but the strong distortions that they create must be handled at the detection stage. Since people detection in fisheye images has not been well studied, we focus on investigating and quantifying the impact that strong radial distortions have on the appearance of people, and we propose approaches for handling this specificity, adapted from state-of-the-art people detection approaches. These adaptive approaches nevertheless have the drawback of high computational cost and complexity. Consequently, we also present a framework for harnessing the LiDAR modality in order to enhance the detection algorithm for different camera positions. A sequential LiDAR-based fusion architecture is used, which addresses directly the problem of reducing false detections and computational cost in an exclusively vision-based system. A heavy machine dataset was built, and different experiments were carried out to evaluate the performance of the system. The results are promising, in terms of both processing speed and performance. PMID:26805838

  8. Vision-Based People Detection System for Heavy Machine Applications.

    PubMed

    Fremont, Vincent; Bui, Manh Tuan; Boukerroui, Djamal; Letort, Pierrick

    2016-01-01

    This paper presents a vision-based people detection system for improving safety in heavy machines. We propose a perception system composed of a monocular fisheye camera and a LiDAR. Fisheye cameras have the advantage of a wide field-of-view, but the strong distortions that they create must be handled at the detection stage. Since people detection in fisheye images has not been well studied, we focus on investigating and quantifying the impact that strong radial distortions have on the appearance of people, and we propose approaches for handling this specificity, adapted from state-of-the-art people detection approaches. These adaptive approaches nevertheless have the drawback of high computational cost and complexity. Consequently, we also present a framework for harnessing the LiDAR modality in order to enhance the detection algorithm for different camera positions. A sequential LiDAR-based fusion architecture is used, which addresses directly the problem of reducing false detections and computational cost in an exclusively vision-based system. A heavy machine dataset was built, and different experiments were carried out to evaluate the performance of the system. The results are promising, in terms of both processing speed and performance. PMID:26805838

  9. [A Hyperspectral Imagery Anomaly Detection Algorithm Based on Gauss-Markov Model].

    PubMed

    Gao, Kun; Liu, Ying; Wang, Li-jing; Zhu, Zhen-yu; Cheng, Hao-bo

    2015-10-01

    With the development of spectral imaging technology, hyperspectral anomaly detection is getting more and more widely used in remote sensing imagery processing. The traditional RX anomaly detection algorithm neglects spatial correlation of images. Besides, it does not validly reduce the data dimension, which costs too much processing time and shows low validity on hyperspectral data. The hyperspectral images follow Gauss-Markov Random Field (GMRF) in space and spectral dimensions. The inverse matrix of covariance matrix is able to be directly calculated by building the Gauss-Markov parameters, which avoids the huge calculation of hyperspectral data. This paper proposes an improved RX anomaly detection algorithm based on three-dimensional GMRF. The hyperspectral imagery data is simulated with GMRF model, and the GMRF parameters are estimated with the Approximated Maximum Likelihood method. The detection operator is constructed with GMRF estimation parameters. The detecting pixel is considered as the centre in a local optimization window, which calls GMRF detecting window. The abnormal degree is calculated with mean vector and covariance inverse matrix, and the mean vector and covariance inverse matrix are calculated within the window. The image is detected pixel by pixel with the moving of GMRF window. The traditional RX detection algorithm, the regional hypothesis detection algorithm based on GMRF and the algorithm proposed in this paper are simulated with AVIRIS hyperspectral data. Simulation results show that the proposed anomaly detection method is able to improve the detection efficiency and reduce false alarm rate. We get the operation time statistics of the three algorithms in the same computer environment. The results show that the proposed algorithm improves the operation time by 45.2%, which shows good computing efficiency.

  10. [A Hyperspectral Imagery Anomaly Detection Algorithm Based on Gauss-Markov Model].

    PubMed

    Gao, Kun; Liu, Ying; Wang, Li-jing; Zhu, Zhen-yu; Cheng, Hao-bo

    2015-10-01

    With the development of spectral imaging technology, hyperspectral anomaly detection is getting more and more widely used in remote sensing imagery processing. The traditional RX anomaly detection algorithm neglects spatial correlation of images. Besides, it does not validly reduce the data dimension, which costs too much processing time and shows low validity on hyperspectral data. The hyperspectral images follow Gauss-Markov Random Field (GMRF) in space and spectral dimensions. The inverse matrix of covariance matrix is able to be directly calculated by building the Gauss-Markov parameters, which avoids the huge calculation of hyperspectral data. This paper proposes an improved RX anomaly detection algorithm based on three-dimensional GMRF. The hyperspectral imagery data is simulated with GMRF model, and the GMRF parameters are estimated with the Approximated Maximum Likelihood method. The detection operator is constructed with GMRF estimation parameters. The detecting pixel is considered as the centre in a local optimization window, which calls GMRF detecting window. The abnormal degree is calculated with mean vector and covariance inverse matrix, and the mean vector and covariance inverse matrix are calculated within the window. The image is detected pixel by pixel with the moving of GMRF window. The traditional RX detection algorithm, the regional hypothesis detection algorithm based on GMRF and the algorithm proposed in this paper are simulated with AVIRIS hyperspectral data. Simulation results show that the proposed anomaly detection method is able to improve the detection efficiency and reduce false alarm rate. We get the operation time statistics of the three algorithms in the same computer environment. The results show that the proposed algorithm improves the operation time by 45.2%, which shows good computing efficiency. PMID:26904830

  11. Vision-based Lane-Vehicle Detection and Tracking

    NASA Astrophysics Data System (ADS)

    Lim, King Hann; Seng, Kah Phooi; Ang, Li-Minn; Chin, Siew Wen

    2009-10-01

    This chapter presents a vision-based lane-vehicle detection and tracking system comprising of (i) enhanced lane boundary detection, (ii) linear-parabolic lane region tracking, and (iii) vehicle detection with a proposed possible vehicle region verification. First, a road image is partitioned into sky and road region. Lane boundaries are then extracted from the road region using line model estimation without applying Hough Transform. These detected boundaries are tracked in consecutive video frames with possible edges scanning and linear-parabolic modeling. An approximate lane region is subsequently constructed with the predicted model parameters. By integrating the knowledge of lane region with vehicle detection, vehicle searching region is restricted to the road area so as to detect the shadow underneath a vehicle continuously with less interference to the road environment and non-vehicle structures. A self-adjusting bounding box is used to extract likely vehicle region for further verification. Besides horizontal symmetry detection, a vertical asymmetry measurement is presented to validate the extracted region and to obtain the center of frontal vehicle. Simulation results have revealed good performance of lane-vehicle detection and tracking system.

  12. Analysis of Vehicle Detection with WSN-Based Ultrasonic Sensors

    PubMed Central

    Jo, Youngtae.; Jung, Inbum.

    2014-01-01

    Existing traffic information acquisition systems suffer from high cost and low scalability. To address these problems, the application of wireless sensor networks (WSNs) has been studied, as WSN-based systems are highly scalable and have a low cost of installing and replacing the systems. Magnetic, acoustic and accelerometer sensors have been considered for WSN-based traffic surveillance, but the use of ultrasonic sensors has not been studied. The limitations of WSN-based systems make it necessary to employ power saving methods and vehicle detection algorithms with low computational complexity. In this paper, we model and analyze optimal power saving methodologies for an ultrasonic sensor and present a computationally-efficient vehicle detection algorithm using ultrasonic data. The proposed methodologies are implemented and evaluated with a tiny microprocessor on real roads. The evaluation results show that the low computational complexity of our algorithm does not compromise the accuracy of vehicle detection. PMID:25093342

  13. Analysis of vehicle detection with WSN-based ultrasonic sensors.

    PubMed

    Jo, Youngtae; Jung, Inbum

    2014-08-04

    Existing traffic information acquisition systems suffer from high cost and low scalability. To address these problems, the application of wireless sensor networks (WSNs) has been studied, as WSN-based systems are highly scalable and have a low cost of installing and replacing the systems. Magnetic, acoustic and accelerometer sensors have been considered for WSN-based traffic surveillance, but the use of ultrasonic sensors has not been studied. The limitations of WSN-based systems make it necessary to employ power saving methods and vehicle detection algorithms with low computational complexity. In this paper, we model and analyze optimal power saving methodologies for an ultrasonic sensor and present a computationally-efficient vehicle detection algorithm using ultrasonic data. The proposed methodologies are implemented and evaluated with a tiny microprocessor on real roads. The evaluation results show that the low computational complexity of our algorithm does not compromise the accuracy of vehicle detection.

  14. The detection of bulk explosives using nuclear-based techniques

    SciTech Connect

    Morgado, R.E.; Gozani, T.; Seher, C.C.

    1988-01-01

    In 1986 we presented a rationale for the detection of bulk explosives based on nuclear techniques that addressed the requirements of civil aviation security in the airport environment. Since then, efforts have intensified to implement a system based on thermal neutron activation (TNA), with new work developing in fast neutron and energetic photon reactions. In this paper we will describe these techniques and present new results from laboratory and airport testing. Based on preliminary results, we contended in our earlier paper that nuclear-based techniques did provide sufficiently penetrating probes and distinguishable detectable reaction products to achieve the FAA operational goals; new data have supported this contention. The status of nuclear-based techniques for the detection of bulk explosives presently under investigation by the US Federal Aviation Administration (FAA) is reviewed. These include thermal neutron activation (TNA), fast neutron activation (FNA), the associated particle technique, nuclear resonance absorption, and photoneutron activation. The results of comprehensive airport testing of the TNA system performed during 1987-88 are summarized. From a technical point of view, nuclear-based techniques now represent the most comprehensive and feasible approach for meeting the operational criteria of detection, false alarms, and throughput. 9 refs., 5 figs., 2 tabs.

  15. Broad base biological assay using liquid based detection assays

    SciTech Connect

    Milanovich, F; Albala, J; Colston, B; Langlois, R; Venkateswaren, K

    2000-10-31

    The release of a biological agent by terrorists represents a serious threat to the safety of US citizens. At present there are over 50 pathogens and toxins on various agency threat lists. Most of these pathogens are rarely seen by public health personnel so the ability to rapidly identify their infection is limited. Since many pathogenic infections have symptomatic delays as long as several days, effective treatment is often compromised. This translates into two major deficiencies in our ability to counter biological terrorism (1) the lack of any credible technology to rapidly detect and identify all the pathogens or toxins on current threat lists and (2) the lack of a credible means to rapidly diagnose thousands of potential victims. In this SI we are developing a rapid, flexible, inexpensive, high throughput, and deeply multiplex-capable biological assay technology. The technology, which we call the Liquid Array (LA), utilizes optical encoding of small diameter beads which serve as the templates for biological capture assays. Once exposed to a fluid sample these beads can be identified and probed for target pathogens at rates of several thousand beads per second. Since each bead can be separately identified, one can perform parallel assays by assigning a different assay to each bead in the encoded set. The goal for this development is a detection technology capable of simultaneously identifying 100s of different bioagents and/or of rapidly diagnosing several thousand individuals. We are pursuing this research in three thrusts. In the first we are exploring the fundamental interactions of the beads with proteins and nucleic acids in complex mixtures. This will provide us with a complete understanding of the limits of the technology with respect to throughput and complex environment. A major spin-off of this activity is in the rapidly emerging field of proteomics where we may be able to rapidly assess the interactions responsible for cell metabolism, structural

  16. Noise-based Detection and Segmentation of Nebulous Objects

    NASA Astrophysics Data System (ADS)

    Akhlaghi, Mohammad; Ichikawa, Takashi

    2015-09-01

    A noise-based non-parametric technique for detecting nebulous objects, for example, irregular or clumpy galaxies, and their structure in noise is introduced. “Noise-based” and “non-parametric” imply that this technique imposes negligible constraints on the properties of the targets and that it employs no regression analysis or fittings. The sub-sky detection threshold is defined and initial detections are found independently of the sky value. False detections are then estimated and removed using the ambient noise as a reference. This results in a purity level of 0.88 for the final detections as compared to 0.29 for SExtractor when a completeness of 1 is desired for a sample of extremely faint and diffuse mock galaxy profiles. The difference in the mean of the undetected pixels with the known background of mock images is decreased by 4.6 times depending on the diffuseness of the test profiles, quantifying the success in their detection. A non-parametric approach to defining substructure over a detected region is also introduced. NoiseChisel is our software implementation of this new technique. Contrary to the existing signal-based approach to detection, in its various implementations, signal-related parameters such as the image point-spread function or known object shapes and models are irrelevant here. Such features make this technique very useful in astrophysical applications such as detection, photometry, or morphological analysis of nebulous objects buried in noise, for example, galaxies that do not generically have a known shape when imaged.

  17. Land-based infrared imagery for marine mammal detection

    NASA Astrophysics Data System (ADS)

    Graber, Joseph; Thomson, Jim; Polagye, Brian; Jessup, Andrew

    2011-09-01

    A land-based infrared (IR) camera is used to detect endangered Southern Resident killer whales in Puget Sound, Washington, USA. The observations are motivated by a proposed tidal energy pilot project, which will be required to monitor for environmental effects. Potential monitoring methods also include visual observation, passive acoustics, and active acoustics. The effectiveness of observations in the infrared spectrum is compared to observations in the visible spectrum to assess the viability of infrared imagery for cetacean detection and classification. Imagery was obtained at Lime Kiln Park, Washington from 7/6/10-7/9/10 using a FLIR Thermovision A40M infrared camera (7.5-14μm, 37°HFOV, 320x240 pixels) under ideal atmospheric conditions (clear skies, calm seas, and wind speed 0-4 m/s). Whales were detected during both day (9 detections) and night (75 detections) at distances ranging from 42 to 162 m. The temperature contrast between dorsal fins and the sea surface ranged from 0.5 to 4.6 °C. Differences in emissivity from sea surface to dorsal fin are shown to aid detection at high incidence angles (near grazing). A comparison to theory is presented, and observed deviations from theory are investigated. A guide for infrared camera selection based on site geometry and desired target size is presented, with specific considerations regarding marine mammal detection. Atmospheric conditions required to use visible and infrared cameras for marine mammal detection are established and compared with 2008 meteorological data for the proposed tidal energy site. Using conservative assumptions, infrared observations are predicted to provide a 74% increase in hours of possible detection, compared with visual observations.

  18. Hair cortisol detection in dairy cattle by using EIA: protocol validation and correlation with faecal cortisol metabolites.

    PubMed

    Tallo-Parra, O; Manteca, X; Sabes-Alsina, M; Carbajal, A; Lopez-Bejar, M

    2015-06-01

    Hair may be a useful matrix to detect cumulative cortisol concentrations in studies of animal welfare and chronic stress. The aim of this study was to validate a protocol for cortisol detection in hair from dairy cattle by enzyme immunoassay (EIA). Seventeen adult Holstein-Friesian dairy cows were used during the milking period. Hair cortisol concentration was assessed in 25-day-old hair samples taken from the frontal region of the head, analysing black and white coloured hair separately. Concentrations of cortisol metabolites were determined in faeces collected twice a week during the same period of time. There was a high correlation between cortisol values in faeces and cortisol in white colour hair samples but such correlation was not significant with the black colour hair samples. The intra- and inter-assay coefficients of variation were 4.9% and 10.6%, respectively. The linearity showed R 2=0.98 and mean percentage error of -10.8 ± 1.55%. The extraction efficiency was 89.0 ± 23.52% and the parallelism test showed similar slopes. Cortisol detection in hair by using EIA seems to be a valid method to represent long-term circulating cortisol levels in dairy cattle.

  19. Integrator or Coincidence Detector: A Novel Measure Based on the Discrete Reverse Correlation to Determine a Neuron's Operational Mode.

    PubMed

    Kanev, Jacob; Koutsou, Achilleas; Christodoulou, Chris; Obermayer, Klaus

    2016-10-01

    In this letter, we propose a definition of the operational mode of a neuron, that is, whether a neuron integrates over its input or detects coincidences. We complete the range of possible operational modes by a new mode we call gap detection, which means that a neuron responds to gaps in its stimulus. We propose a measure consisting of two scalar values, both ranging from -1 to +1: the neural drive, which indicates whether its stimulus excites the neuron, serves as background noise, or inhibits it; the neural mode, which indicates whether the neuron's response is the result of integration over its input, of coincidence detection, or of gap detection; with all three modes possible for all neural drive values. This is a pure spike-based measure and can be applied to measure the influence of either all or subset of a neuron's stimulus. We derive the measure by decomposing the reverse correlation, test it in several artificial and biological settings, and compare it to other measures, finding little or no correlation between them. We relate the results of the measure to neural parameters and investigate the effect of time delay during spike generation. Our results suggest that a neuron can use several different modes simultaneously on different subsets of its stimulus to enable it to respond to its stimulus in a complex manner. PMID:27557103

  20. Sensitive measurement of radiation trapping in cold-atom clouds by intensity correlation detection.

    PubMed

    Stites, Ronald; Beeler, Matthew; Feeney, Laura; Kim, Soo; Bali, Samir

    2004-12-01

    We present experimental evidence that the intensity correlations of light scattered from a cold-atom cloud are sensitive to the presence of small amounts of radiation trapping in an atomic sample of density 6 x 10(8)/cm3, with an optical depth (for a resonant light beam) of 0.4. This density and optical depth are approximately an order of magnitude less than the density and on-resonance optical depth at which effects of multiple scattering in cold-atom clouds have been previously observed [Phys. Rev. Lett. 64, 408 (1990)].

  1. Perceptual detection as a dynamical bistability phenomenon: A neurocomputational correlate of sensation

    PubMed Central

    Deco, Gustavo; Pérez-Sanagustín, Mar; de Lafuente, Victor; Romo, Ranulfo

    2007-01-01

    Recent studies that combined psychophysical/neurophysiological experiments [de Lafuente V, Romo R (2005) Nat Neurosci 8:1698–1703] analyzed the responses from single neurons, recorded in several cortical areas of parietal and frontal lobes, while trained monkeys reported the presence or absence of a mechanical vibration of varying amplitude applied to skin of one fingertip. The analysis showed that the activity of primary somatosensory cortex neurons covaried with the stimulus strength but did not covary with the animal's perceptual reports. In contrast, the activity of medial premotor cortex (MPC) neurons did not covary with the stimulus strength but did covary with the animal's perceptual reports. Here, we address the question of how perceptual detection is computed in MPC. In particular, we regard perceptual detection as a bistable neurodynamical phenomenon reflected in the activity of MPC. We show that the activity of MPC is consistent with a decision-making-like scenario of fluctuation-driven computation that causes a probabilistic transition between two bistable states, one corresponding to the case in which the monkey detects the sensory input, the other corresponding to the case in which the monkey does not. Moreover, the high variability activity of MPC neurons both within and between trials reflects stochastic fluctuations that may play a crucial role in the monkey's probabilistic perceptual reports. PMID:18077434

  2. Salamander locomotion-induced head movement and retinal motion sensitivity in a correlation-based motion detector model.

    PubMed

    Begley, Jeffrey R; Arbib, Michael A

    2007-06-01

    We report on a computational model of retinal motion sensitivity based on correlation-based motion detectors. We simulate object motion detection in the presence of retinal slip caused by the salamander's head movements during locomotion. Our study offers new insights into object motion sensitive ganglion cells in the salamander retina. A sigmoidal transformation of the spatially and temporally filtered retinal image substantially improves the sensitivity of the system in detecting a small target moving in place against a static natural background in the presence of comparatively large, fast simulated eye movements, but is detrimental to the direction-selectivity of the motion detector. The sigmoid has insignificant effects on detector performance in simulations of slow, high contrast laboratory stimuli. These results suggest that the sigmoid reduces the system's noise sensitivity.

  3. DNA methylation detection based on difference of base content

    NASA Astrophysics Data System (ADS)

    Sato, Shinobu; Ohtsuka, Keiichi; Honda, Satoshi; Sato, Yusuke; Takenaka, Shigeori

    2016-04-01

    Methylation frequently occurs in cytosines of CpG sites to regulate gene expression. The identification of aberrant methylation of certain genes is important for cancer marker analysis. The aim of this study was to determine the methylation frequency in DNA samples of unknown length and/or concentration. Unmethylated cytosine is known to be converted to thymine following bisulfite treatment and subsequent PCR. For this reason, the AT content in DNA increases with an increasing number of methylation sites. In this study, the fluorescein-carrying bis-acridinyl peptide (FKA) molecule was used for the detection of methylation frequency. FKA contains fluorescein and two acridine moieties, which together allow for the determination of the AT content of double-stranded DNA fragments. Methylated and unmethylated human genomes were subjected to bisulfide treatment and subsequent PCR using primers specific for the CFTR, CDH4, DBC1, and NPY genes. The AT content in the resulting PCR products was estimated by FKA, and AT content estimations were found to be in good agreement with those determined by DNA sequencing. This newly developed method may be useful for determining methylation frequencies of many PCR products by measuring the fluorescence in samples excited at two different wavelengths.

  4. Unsupervised malaria parasite detection based on phase spectrum.

    PubMed

    Fang, Yuming; Xiong, Wei; Lin, Weisi; Chen, Zhenzhong

    2011-01-01

    In this paper, we propose a novel method for malaria parasite detection based on phase spectrum. The method first obtains the amplitude spectrum and phase spectrum for blood smear images through Quaternion Fourier Transform (QFT). Then it gets the reconstructed image based on Inverse Quaternion Fourier transform (IQFT) on a constant amplitude spectrum and the original phase spectrum. The malaria parasite areas can be detected easily from the reconstructed blood smear images. Extensive experiments have demonstrated the effectiveness of this novel method. PMID:22256196

  5. Detection of polyaromatic compounds using antibody-based fiberoptics fluoroimmunosensors

    SciTech Connect

    Vo-Dinh, T.; Tromberg, B.J.; Griffin, G.D.; Ambrose, K.R.; Sepaniak, M.J.; Alarie, J.P.

    1987-01-01

    In this work we have investigated the performance of an antibody-based fiberoptics sensor for the detection of the carcinogen benzo(a)pyrene and its DNA-adduct product BP-tetrol. The excellent sensitivity of this device - femtomole limits of detection for BP - illustrates that it has considerable potential to perform analyses of chemical and biological samples at trace levels in complex matrices. The results indicate that fiberoptics-based fluoroimmunosensors can be useful in a wide spectrum of biochemical and clinical analyses. 17 refs., 4 figs., 1 tab.

  6. A Cyber-Attack Detection Model Based on Multivariate Analyses

    NASA Astrophysics Data System (ADS)

    Sakai, Yuto; Rinsaka, Koichiro; Dohi, Tadashi

    In the present paper, we propose a novel cyber-attack detection model based on two multivariate-analysis methods to the audit data observed on a host machine. The statistical techniques used here are the well-known Hayashi's quantification method IV and cluster analysis method. We quantify the observed qualitative audit event sequence via the quantification method IV, and collect similar audit event sequence in the same groups based on the cluster analysis. It is shown in simulation experiments that our model can improve the cyber-attack detection accuracy in some realistic cases where both normal and attack activities are intermingled.

  7. VoIP attacks detection engine based on neural network

    NASA Astrophysics Data System (ADS)

    Safarik, Jakub; Slachta, Jiri

    2015-05-01

    The security is crucial for any system nowadays, especially communications. One of the most successful protocols in the field of communication over IP networks is Session Initiation Protocol. It is an open-source project used by different kinds of applications, both open-source and proprietary. High penetration and text-based principle made SIP number one target in IP telephony infrastructure, so security of SIP server is essential. To keep up with hackers and to detect potential malicious attacks, security administrator needs to monitor and evaluate SIP traffic in the network. But monitoring and following evaluation could easily overwhelm the security administrator in networks, typically in networks with a number of SIP servers, users and logically or geographically separated networks. The proposed solution lies in automatic attack detection systems. The article covers detection of VoIP attacks through a distributed network of nodes. Then the gathered data analyze aggregation server with artificial neural network. Artificial neural network means multilayer perceptron network trained with a set of collected attacks. Attack data could also be preprocessed and verified with a self-organizing map. The source data is detected by distributed network of detection nodes. Each node contains a honeypot application and traffic monitoring mechanism. Aggregation of data from each node creates an input for neural networks. The automatic classification on a centralized server with low false positive detection reduce the cost of attack detection resources. The detection system uses modular design for easy deployment in final infrastructure. The centralized server collects and process detected traffic. It also maintains all detection nodes.

  8. Analysis of Android Device-Based Solutions for Fall Detection.

    PubMed

    Casilari, Eduardo; Luque, Rafael; Morón, María-José

    2015-07-23

    Falls are a major cause of health and psychological problems as well as hospitalization costs among older adults. Thus, the investigation on automatic Fall Detection Systems (FDSs) has received special attention from the research community during the last decade. In this area, the widespread popularity, decreasing price, computing capabilities, built-in sensors and multiplicity of wireless interfaces of Android-based devices (especially smartphones) have fostered the adoption of this technology to deploy wearable and inexpensive architectures for fall detection. This paper presents a critical and thorough analysis of those existing fall detection systems that are based on Android devices. The review systematically classifies and compares the proposals of the literature taking into account different criteria such as the system architecture, the employed sensors, the detection algorithm or the response in case of a fall alarms. The study emphasizes the analysis of the evaluation methods that are employed to assess the effectiveness of the detection process. The review reveals the complete lack of a reference framework to validate and compare the proposals. In addition, the study also shows that most research works do not evaluate the actual applicability of the Android devices (with limited battery and computing resources) to fall detection solutions.

  9. Analysis of Android Device-Based Solutions for Fall Detection

    PubMed Central

    Casilari, Eduardo; Luque, Rafael; Morón, María-José

    2015-01-01

    Falls are a major cause of health and psychological problems as well as hospitalization costs among older adults. Thus, the investigation on automatic Fall Detection Systems (FDSs) has received special attention from the research community during the last decade. In this area, the widespread popularity, decreasing price, computing capabilities, built-in sensors and multiplicity of wireless interfaces of Android-based devices (especially smartphones) have fostered the adoption of this technology to deploy wearable and inexpensive architectures for fall detection. This paper presents a critical and thorough analysis of those existing fall detection systems that are based on Android devices. The review systematically classifies and compares the proposals of the literature taking into account different criteria such as the system architecture, the employed sensors, the detection algorithm or the response in case of a fall alarms. The study emphasizes the analysis of the evaluation methods that are employed to assess the effectiveness of the detection process. The review reveals the complete lack of a reference framework to validate and compare the proposals. In addition, the study also shows that most research works do not evaluate the actual applicability of the Android devices (with limited battery and computing resources) to fall detection solutions. PMID:26213928

  10. Analysis of Android Device-Based Solutions for Fall Detection.

    PubMed

    Casilari, Eduardo; Luque, Rafael; Morón, María-José

    2015-01-01

    Falls are a major cause of health and psychological problems as well as hospitalization costs among older adults. Thus, the investigation on automatic Fall Detection Systems (FDSs) has received special attention from the research community during the last decade. In this area, the widespread popularity, decreasing price, computing capabilities, built-in sensors and multiplicity of wireless interfaces of Android-based devices (especially smartphones) have fostered the adoption of this technology to deploy wearable and inexpensive architectures for fall detection. This paper presents a critical and thorough analysis of those existing fall detection systems that are based on Android devices. The review systematically classifies and compares the proposals of the literature taking into account different criteria such as the system architecture, the employed sensors, the detection algorithm or the response in case of a fall alarms. The study emphasizes the analysis of the evaluation methods that are employed to assess the effectiveness of the detection process. The review reveals the complete lack of a reference framework to validate and compare the proposals. In addition, the study also shows that most research works do not evaluate the actual applicability of the Android devices (with limited battery and computing resources) to fall detection solutions. PMID:26213928

  11. Forward vehicle detection using cluster-based AdaBoost

    NASA Astrophysics Data System (ADS)

    Baek, Yeul-Min; Kim, Whoi-Yul

    2014-10-01

    A camera-based forward vehicle detection method with range estimation for forward collision warning system (FCWS) is presented. Previous vehicle detection methods that use conventional classifiers are not robust in a real driving environment because they lack the effectiveness of classifying vehicle samples with high intraclass variation and noise. Therefore, an improved AdaBoost, named cluster-based AdaBoost (C-AdaBoost), for classifying noisy samples along with a forward vehicle detection method are presented in this manuscript. The experiments performed consist of two parts: performance evaluations of C-AdaBoost and forward vehicle detection. The proposed C-AdaBoost shows better performance than conventional classification algorithms on the synthetic as well as various real-world datasets. In particular, when the dataset has more noisy samples, C-AdaBoost outperforms conventional classification algorithms. The proposed method is also tested with an experimental vehicle on a proving ground and on public roads, ˜62 km in length. The proposed method shows a 97% average detection rate and requires only 9.7 ms per frame. The results show the reliability of the proposed method FCWS in terms of both detection rate and processing time.

  12. An EEG-Based Fatigue Detection and Mitigation System.

    PubMed

    Huang, Kuan-Chih; Huang, Teng-Yi; Chuang, Chun-Hsiang; King, Jung-Tai; Wang, Yu-Kai; Lin, Chin-Teng; Jung, Tzyy-Ping

    2016-06-01

    Research has indicated that fatigue is a critical factor in cognitive lapses because it negatively affects an individual's internal state, which is then manifested physiologically. This study explores neurophysiological changes, measured by electroencephalogram (EEG), due to fatigue. This study further demonstrates the feasibility of an online closed-loop EEG-based fatigue detection and mitigation system that detects physiological change and can thereby prevent fatigue-related cognitive lapses. More importantly, this work compares the efficacy of fatigue detection and mitigation between the EEG-based and a nonEEG-based random method. Twelve healthy subjects participated in a sustained-attention driving experiment. Each participant's EEG signal was monitored continuously and a warning was delivered in real-time to participants once the EEG signature of fatigue was detected. Study results indicate suppression of the alpha- and theta-power of an occipital component and improved behavioral performance following a warning signal; these findings are in line with those in previous studies. However, study results also showed reduced warning efficacy (i.e. increased response times (RTs) to lane deviations) accompanied by increased alpha-power due to the fluctuation of warnings over time. Furthermore, a comparison of EEG-based and nonEEG-based random approaches clearly demonstrated the necessity of adaptive fatigue-mitigation systems, based on a subject's cognitive level, to deliver warnings. Analytical results clearly demonstrate and validate the efficacy of this online closed-loop EEG-based fatigue detection and mitigation mechanism to identify cognitive lapses that may lead to catastrophic incidents in countless operational environments.

  13. R-peaks detection based on stationary wavelet transform.

    PubMed

    Merah, M; Abdelmalik, T A; Larbi, B H

    2015-10-01

    Automatic detection of the QRS complexes/R-peaks in an electrocardiogram (ECG) signal is the most important step preceding any kind of ECG processing and analysis. The performance of these systems heavily relies on the accuracy of the QRS detector. The objective of present work is to drive a new robust method based on stationary wavelet transform (SWT) for R-peaks detection. The decimation of the coefficients at each level of the transformation algorithm is omitted, more samples in the coefficient sequences are available and hence a better outlier detection can be performed. Using the information of local maxima, minima and zero crossings of the fourth SWT coefficient detail, the proposed algorithm identifies the significant points for detection and delineation of the QRS complexes, as well as detection and identification of the QRS individual waves peaks of the pre-processed ECG signal. Various experimental results show that the proposed algorithm exhibits reliable QRS detection as well as accurate ECG delineation, achieving excellent performance on different databases, on the MIT-BIH database (Se=99.84%, P=99.88%), on the QT Database (Se=99.94%, P=99.89%) and on MIT-BIH Noise Stress Test Database, (Se=95.30%, P=93.98%). Reliability and accuracy are close to the highest among the ones obtained in other studies. Experiments results being satisfactory, the SWT may represent a novel QRS detection tool, for a robust ECG signal analysis. PMID:26105724

  14. An FPGA-based rapid wheezing detection system.

    PubMed

    Lin, Bor-Shing; Yen, Tian-Shiue

    2014-02-01

    Wheezing is often treated as a crucial indicator in the diagnosis of obstructive pulmonary diseases. A rapid wheezing detection system may help physicians to monitor patients over the long-term. In this study, a portable wheezing detection system based on a field-programmable gate array (FPGA) is proposed. This system accelerates wheezing detection, and can be used as either a single-process system, or as an integrated part of another biomedical signal detection system. The system segments sound signals into 2-second units. A short-time Fourier transform was used to determine the relationship between the time and frequency components of wheezing sound data. A spectrogram was processed using 2D bilateral filtering, edge detection, multithreshold image segmentation, morphological image processing, and image labeling, to extract wheezing features according to computerized respiratory sound analysis (CORSA) standards. These features were then used to train the support vector machine (SVM) and build the classification models. The trained model was used to analyze sound data to detect wheezing. The system runs on a Xilinx Virtex-6 FPGA ML605 platform. The experimental results revealed that the system offered excellent wheezing recognition performance (0.912). The detection process can be used with a clock frequency of 51.97 MHz, and is able to perform rapid wheezing classification.

  15. A stereo vision-based obstacle detection system in vehicles

    NASA Astrophysics Data System (ADS)

    Huh, Kunsoo; Park, Jaehak; Hwang, Junyeon; Hong, Daegun

    2008-02-01

    Obstacle detection is a crucial issue for driver assistance systems as well as for autonomous vehicle guidance function and it has to be performed with high reliability to avoid any potential collision with the front vehicle. The vision-based obstacle detection systems are regarded promising for this purpose because they require little infrastructure on a highway. However, the feasibility of these systems in passenger car requires accurate and robust sensing performance. In this paper, an obstacle detection system using stereo vision sensors is developed. This system utilizes feature matching, epipoplar constraint and feature aggregation in order to robustly detect the initial corresponding pairs. After the initial detection, the system executes the tracking algorithm for the obstacles. The proposed system can detect a front obstacle, a leading vehicle and a vehicle cutting into the lane. Then, the position parameters of the obstacles and leading vehicles can be obtained. The proposed obstacle detection system is implemented on a passenger car and its performance is verified experimentally.

  16. An FPGA-Based Rapid Wheezing Detection System

    PubMed Central

    Lin, Bor-Shing; Yen, Tian-Shiue

    2014-01-01

    Wheezing is often treated as a crucial indicator in the diagnosis of obstructive pulmonary diseases. A rapid wheezing detection system may help physicians to monitor patients over the long-term. In this study, a portable wheezing detection system based on a field-programmable gate array (FPGA) is proposed. This system accelerates wheezing detection, and can be used as either a single-process system, or as an integrated part of another biomedical signal detection system. The system segments sound signals into 2-second units. A short-time Fourier transform was used to determine the relationship between the time and frequency components of wheezing sound data. A spectrogram was processed using 2D bilateral filtering, edge detection, multithreshold image segmentation, morphological image processing, and image labeling, to extract wheezing features according to computerized respiratory sound analysis (CORSA) standards. These features were then used to train the support vector machine (SVM) and build the classification models. The trained model was used to analyze sound data to detect wheezing. The system runs on a Xilinx Virtex-6 FPGA ML605 platform. The experimental results revealed that the system offered excellent wheezing recognition performance (0.912). The detection process can be used with a clock frequency of 51.97 MHz, and is able to perform rapid wheezing classification. PMID:24481034

  17. PCA-HOG symmetrical feature based diseased cell detection

    NASA Astrophysics Data System (ADS)

    Wan, Min-jie

    2016-04-01

    A histogram of oriented gradient (HOG) feature is applied to the field of diseased cell detection, which can detect diseased cells in high resolution tissue images rapidly, accurately and efficiently. Firstly, motivated by symmetrical cellular forms, a new HOG symmetrical feature based on the traditional HOG feature is proposed to meet the condition of cell detection. Secondly, considering the high feature dimension of traditional HOG feature leads to plenty of memory resources and long runtime in practical applications, a classical dimension reduction method called principal component analysis (PCA) is used to reduce the dimension of high-dimensional HOG descriptor. Because of that, computational speed is increased greatly, and the accuracy of detection can be controlled in a proper range at the same time. Thirdly, support vector machine (SVM) classifier is trained with PCA-HOG symmetrical features proposed above. At last, practical tissue images is detected and analyzed by SVM classifier. In order to verify the effectiveness of this new algorithm, it is practically applied to conduct diseased cell detection which takes 200 pieces of H&E (hematoxylin & eosin) high resolution staining histopathological images collected from 20 breast cancer patients as a sample. The experiment shows that the average processing rate can be 25 frames per second and the detection accuracy can be 92.1%.

  18. R-peaks detection based on stationary wavelet transform.

    PubMed

    Merah, M; Abdelmalik, T A; Larbi, B H

    2015-10-01

    Automatic detection of the QRS complexes/R-peaks in an electrocardiogram (ECG) signal is the most important step preceding any kind of ECG processing and analysis. The performance of these systems heavily relies on the accuracy of the QRS detector. The objective of present work is to drive a new robust method based on stationary wavelet transform (SWT) for R-peaks detection. The decimation of the coefficients at each level of the transformation algorithm is omitted, more samples in the coefficient sequences are available and hence a better outlier detection can be performed. Using the information of local maxima, minima and zero crossings of the fourth SWT coefficient detail, the proposed algorithm identifies the significant points for detection and delineation of the QRS complexes, as well as detection and identification of the QRS individual waves peaks of the pre-processed ECG signal. Various experimental results show that the proposed algorithm exhibits reliable QRS detection as well as accurate ECG delineation, achieving excellent performance on different databases, on the MIT-BIH database (Se=99.84%, P=99.88%), on the QT Database (Se=99.94%, P=99.89%) and on MIT-BIH Noise Stress Test Database, (Se=95.30%, P=93.98%). Reliability and accuracy are close to the highest among the ones obtained in other studies. Experiments results being satisfactory, the SWT may represent a novel QRS detection tool, for a robust ECG signal analysis.

  19. Correlation of Transcranial Color Doppler to N20 Somatosensory Evoked Potential Detects Ischemic Penumbra in Subarachnoid Hemorrhage

    PubMed Central

    Di Pasquale, Piero; Zanatta, Paolo; Morghen, Ilaria; Bosco, Enrico; Forini, Elena

    2011-01-01

    Background: Normal subjects present interhemispheric symmetry of middle cerebral artery (MCA) mean flow velocity and N20 cortical somatosensory evoked potential (SSEP). Subarachnoid haemorrhage (SAH) can modify this pattern, since high regional brain vascular resistances increase blood flow velocity, and impaired regional brain perfusion reduces N20 amplitude. The aim of the study is to investigate the variability of MCA resistances and N20 amplitude between hemispheres in SAH. Methods: Measurements of MCA blood flow velocity (vMCA) by transcranial color-Doppler and median nerve SSEP were bilaterally performed in sixteen patients. MCA vascular changes on the compromised hemisphere were calculated as a ratio of the reciprocal of mean flow velocity (1/vMCA) to contralateral value and correlated to the simultaneous variations of interhemispheric ratio of N20 amplitude, within each subject. Data were analysed with respect to neuroimaging of MCA supplied areas. Results: Both interhemispheric ratios of 1/vMCA and N20 amplitude were detected >0.65 (p <0,01) in patients without neuroimages of injury. Both ratios became <0.65 (p <0.01) when patients showed unilateral images of ischemic penumbra and returned >0.65 if penumbra disappeared. The two ratios no longer correlated after structural lesion developed, as N20 detected in the damaged side remained pathological (ratio <0.65), whereas 1/vMCA reverted to symmetric interhemispheric state (ratio >0.65), suggesting a luxury perfusion. Conclusion: Variations of interhemispheric ratios of MCA resistance and cortical N20 amplitude correlate closely in SAH and allow identification of the reversible ischemic penumbra threshold, when both ratios become <0.65. The correlation is lost when structural damage develops. PMID:21660110

  20. A Correlation-Based Transition Model using Local Variables. Part 1; Model Formation

    NASA Technical Reports Server (NTRS)

    Menter, F. R.; Langtry, R. B.; Likki, S. R.; Suzen, Y. B.; Huang, P. G.; Volker, S.

    2006-01-01

    A new correlation-based transition model has been developed, which is based strictly on local variables. As a result, the transition model is compatible with modern computational fluid dynamics (CFD) approaches, such as unstructured grids and massive parallel execution. The model is based on two transport equations, one for intermittency and one for the transition onset criteria in terms of momentum thickness Reynolds number. The proposed transport equations do not attempt to model the physics of the transition process (unlike, e.g., turbulence models) but from a framework for the implementation of correlation-based models into general-purpose CFD methods.

  1. Polymer-based sensor array for phytochemical detection

    NASA Astrophysics Data System (ADS)

    Weerakoon, Kanchana A.; Hiremath, Nitilaksha; Chin, Bryan A.

    2012-05-01

    Monitoring for the appearance of volatile organic compounds emitted by plants which correspond to time of first insect attack can be used to detect the early stages of insect infestation. This paper reports a chemical sensor array consisting of polymer based chemiresistor sensors that could detect insect infestation effectively. The sensor array consists of sensors with micro electronically fabricated interdigitated electrodes, and twelve different types of electro active polymer layers. The sensor array was cheap, easy to fabricate, and could be used easily in agricultural fields. The polymer array was found to be sensitive to a variety of volatile organic compounds emitted by plants including γ-terpinene α-pinene, pcymene, farnesene, limonene and cis-hexenyl acetate. The sensor array was not only able to detect but also distinguish between these compounds. The twelve sensors produced a resistance change for each of the analytes detected, and each of these responses together produced a unique fingerprint, enabling to distinguish among these chemicals.

  2. Contributed Review: Quantum cascade laser based photoacoustic detection of explosives

    SciTech Connect

    Li, J. S. Yu, B.; Fischer, H.; Chen, W.; Yalin, A. P.

    2015-03-15

    Detecting trace explosives and explosive-related compounds has recently become a topic of utmost importance for increasing public security around the world. A wide variety of detection methods and an even wider range of physical chemistry issues are involved in this very challenging area. Optical sensing methods, in particular mid-infrared spectrometry techniques, have a great potential to become a more desirable tools for the detection of explosives. The small size, simplicity, high output power, long-term reliability make external cavity quantum cascade lasers (EC-QCLs) the promising spectroscopic sources for developing analytical instrumentation. This work reviews the current technical progress in EC-QCL-based photoacoustic spectroscopy for explosives detection. The potential for both close-contact and standoff configurations using this technique is completely presented over the course of approximately the last one decade.

  3. Contributed review: quantum cascade laser based photoacoustic detection of explosives.

    PubMed

    Li, J S; Yu, B; Fischer, H; Chen, W; Yalin, A P

    2015-03-01

    Detecting trace explosives and explosive-related compounds has recently become a topic of utmost importance for increasing public security around the world. A wide variety of detection methods and an even wider range of physical chemistry issues are involved in this very challenging area. Optical sensing methods, in particular mid-infrared spectrometry techniques, have a great potential to become a more desirable tools for the detection of explosives. The small size, simplicity, high output power, long-term reliability make external cavity quantum cascade lasers (EC-QCLs) the promising spectroscopic sources for developing analytical instrumentation. This work reviews the current technical progress in EC-QCL-based photoacoustic spectroscopy for explosives detection. The potential for both close-contact and standoff configurations using this technique is completely presented over the course of approximately the last one decade.

  4. Sparsity-based algorithm for detecting faults in rotating machines

    NASA Astrophysics Data System (ADS)

    He, Wangpeng; Ding, Yin; Zi, Yanyang; Selesnick, Ivan W.

    2016-05-01

    This paper addresses the detection of periodic transients in vibration signals so as to detect faults in rotating machines. For this purpose, we present a method to estimate periodic-group-sparse signals in noise. The method is based on the formulation of a convex optimization problem. A fast iterative algorithm is given for its solution. A simulated signal is formulated to verify the performance of the proposed approach for periodic feature extraction. The detection performance of comparative methods is compared with that of the proposed approach via RMSE values and receiver operating characteristic (ROC) curves. Finally, the proposed approach is applied to single fault diagnosis of a locomotive bearing and compound faults diagnosis of motor bearings. The processed results show that the proposed approach can effectively detect and extract the useful features of bearing outer race and inner race defect.

  5. An ellipse detection algorithm based on edge classification

    NASA Astrophysics Data System (ADS)

    Yu, Liu; Chen, Feng; Huang, Jianming; Wei, Xiangquan

    2015-12-01

    In order to enhance the speed and accuracy of ellipse detection, an ellipse detection algorithm based on edge classification is proposed. Too many edge points are removed by making edge into point in serialized form and the distance constraint between the edge points. It achieves effective classification by the criteria of the angle between the edge points. And it makes the probability of randomly selecting the edge points falling on the same ellipse greatly increased. Ellipse fitting accuracy is significantly improved by the optimization of the RED algorithm. It uses Euclidean distance to measure the distance from the edge point to the elliptical boundary. Experimental results show that: it can detect ellipse well in case of edge with interference or edges blocking each other. It has higher detecting precision and less time consuming than the RED algorithm.

  6. Based on spatial-temporal multiframe association infrared target detection

    NASA Astrophysics Data System (ADS)

    Wang, Zhonghua; Wang, Chao; Huang, Faliang; Liu, Jianguo

    2015-12-01

    Infrared small target detection is difficult due to several aspects, including the low signal-to-clutter ratio of the infrared image, and the small size, lack of shape and texture information of the target. a novel method, which is based on spatial-temporal association, is presented for infrared target detection. The algorithm consists of the three steps: Firstly, 2-dimensional histogram of entropy flow field is computed to estimate the background motion. Secondly, the difference image through background motion compensation is obtained. Finally, the targets are detected by spatial-temporal filter. The experiment results demonstrate that the proposed algorithm is robust to noise, and also fit to detect small targets under moving backgrounds in infrared image sequences.

  7. Colour based fire detection method with temporal intensity variation filtration

    NASA Astrophysics Data System (ADS)

    Trambitckii, K.; Anding, K.; Musalimov, V.; Linß, G.

    2015-02-01

    Development of video, computing technologies and computer vision gives a possibility of automatic fire detection on video information. Under that project different algorithms was implemented to find more efficient way of fire detection. In that article colour based fire detection algorithm is described. But it is not enough to use only colour information to detect fire properly. The main reason of this is that in the shooting conditions may be a lot of things having colour similar to fire. A temporary intensity variation of pixels is used to separate them from the fire. These variations are averaged over the series of several frames. This algorithm shows robust work and was realised as a computer program by using of the OpenCV library.

  8. Measurements-based Moving Target Detection in Quantum Video

    NASA Astrophysics Data System (ADS)

    Yan, Fei; Iliyasu, Abdullah M.; Khan, Asif R.; Yang, Huamin

    2016-04-01

    A method to detect a moving target in multi-channel quantum video is proposed based on multiple measurements on the video strip. The proposed method is capable of detecting the location of the moving target in each frame of the quantum video thereby ensuring that the motion trail of the object is easily and efficiently retrieved. Three experiments, i.e. moving target detection (MTD) of a pixel, MTD of an object in complex shape, and MTD of a pixel whose color is conterminous with that of its background, are implemented to demonstrate the feasibility of the proposal. This study presents a modest attempt to focus on the moving target detection and its applications in quantum video.

  9. Feature-based eye corner detection from static images

    NASA Astrophysics Data System (ADS)

    Xia, Haiying; Yan, Guoping; You, Chao

    2009-10-01

    Eye corner detection is important for eye extraction, face normalization, other facial landmark extraction and so on. We present a feature-based method for eye corner detection from static images in this paper. This method is capable of locating eye corners automatically. The process of eye corner detection is divided into two stages: classifier training and classifier application. For training, two classifiers trained by AdaBoost with Haar-like features, are skillfully designed to detect inner eye corners and outer eye corners. Then, two classifiers are applied to input images to search targets. Eye corners are finally located according to two eye models from targets. Experimental results tested on BioID face database and our own database demonstrate that our method obtains a high accuracy under clutter conditions.

  10. Auto Correlation Analysis of Coda Waves from Local Earthquakes for Detecting Temporal Changes in Shallow Subsurface Structures: the 2011 Tohoku-Oki, Japan Earthquake

    NASA Astrophysics Data System (ADS)

    Nakahara, Hisashi

    2015-02-01

    For monitoring temporal changes in subsurface structures I propose to use auto correlation functions of coda waves from local earthquakes recorded at surface receivers, which probably contain more body waves than surface waves. Use of coda waves requires earthquakes resulting in decreased time resolution for monitoring. Nonetheless, it may be possible to monitor subsurface structures in sufficient time resolutions in regions with high seismicity. In studying the 2011 Tohoku-Oki, Japan earthquake (Mw 9.0), for which velocity changes have been previously reported, I try to validate the method. KiK-net stations in northern Honshu are used in this analysis. For each moderate earthquake normalized auto correlation functions of surface records are stacked with respect to time windows in the S-wave coda. Aligning the stacked, normalized auto correlation functions with time, I search for changes in phases arrival times. The phases at lag times of <1 s are studied because changes at shallow depths are focused. Temporal variations in the arrival times are measured at the stations based on the stretching method. Clear phase delays are found to be associated with the mainshock and to gradually recover with time. The amounts of the phase delays are 10 % on average with the maximum of about 50 % at some stations. The deconvolution analysis using surface and subsurface records at the same stations is conducted for validation. The results show the phase delays from the deconvolution analysis are slightly smaller than those from the auto correlation analysis, which implies that the phases on the auto correlations are caused by larger velocity changes at shallower depths. The auto correlation analysis seems to have an accuracy of about several percent, which is much larger than methods using earthquake doublets and borehole array data. So this analysis might be applicable in detecting larger changes. In spite of these disadvantages, this analysis is still attractive because it can

  11. Cortical dynamics of visual change detection based on sensory memory.

    PubMed

    Urakawa, Tomokazu; Inui, Koji; Yamashiro, Koya; Tanaka, Emi; Kakigi, Ryusuke

    2010-08-01

    Detecting a visual change was suggested to relate closely to the visual sensory memory formed by visual stimuli before the occurrence of the change, because change detection involves identifying a difference between ongoing and preceding sensory conditions. Previous neuroimaging studies showed that an abrupt visual change activates the middle occipital gyrus (MOG). However, it still remains to be elucidated whether the MOG is related to visual change detection based on sensory memory. Here we tried to settle this issue using a new method of stimulation with blue and red LEDs to emphasize a memory-based change detection process. There were two stimuli, a standard trial stimulus and a deviant trial stimulus. The former was a red light lasting 500 ms, and the latter was a red light lasting 250 ms immediately followed by a blue light lasting 250 ms. Effects of the trial-trial interval, 250 approximately 2000 ms, were investigated to know how cortical responses to the abrupt change (from red to blue) were affected by preceding conditions. The brain response to the deviant trial stimulus was recorded by magnetoencephalography. Results of a multi-dipole analysis showed that the activity in the MOG, peaking at around 150 ms after the change onset, decreased in amplitude as the interval increased, but the earlier activity in BA 17/18 was not affected by the interval. These results suggested that the MOG is an important cortical area relating to the sensory memory-based visual change-detecting system.

  12. Current-based detection of nonlocal spin transport in graphene for spin-based logic applications

    SciTech Connect

    Wen, Hua; Amamou, Walid; Zhu, Tiancong; Luo, Yunqiu; Kawakami, Roland K.

    2014-05-07

    Graphene has been proposed for novel spintronic devices due to its robust and efficient spin transport properties at room temperature. Some of the most promising proposals require current-based readout for integration purposes, but the current-based detection of spin accumulation has not yet been developed. In this work, we demonstrate current-based detection of spin transport in graphene using a modified nonlocal geometry. By adding a variable shunt resistor in parallel to the nonlocal voltmeter, we are able to systematically cross over from the conventional voltage-based detection to current-based detection. As the shunt resistor is reduced, the output current from the spin accumulation increases as the shunt resistance drops below a characteristic value R*. We analyze this behavior using a one-dimensional drift-diffusion model, which accounts well for the observed behavior. These results provide the experimental and theoretical foundation for current-based detection of nonlocal spin transport.

  13. Capacitance-based damage detection sensing for aerospace structural composites

    NASA Astrophysics Data System (ADS)

    Bahrami, P.; Yamamoto, N.; Chen, Y.; Manohara, H.

    2014-04-01

    Damage detection technology needs improvement for aerospace engineering application because detection within complex composite structures is difficult yet critical to avoid catastrophic failure. Damage detection is challenging in aerospace structures because not all the damage detection technology can cover the various defect types (delamination, fiber fracture, matrix crack etc.), or conditions (visibility, crack length size, etc.). These defect states are expected to become even more complex with future introduction of novel composites including nano-/microparticle reinforcement. Currently, non-destructive evaluation (NDE) methods with X-ray, ultrasound, or eddy current have good resolutions (< 0.1 mm), but their detection capabilities is limited by defect locations and orientations and require massive inspection devices. System health monitoring (SHM) methods are often paired with NDE technologies to signal out sensed damage, but their data collection and analysis currently requires excessive wiring and complex signal analysis. Here, we present a capacitance sensor-based, structural defect detection technology with improved sensing capability. Thin dielectric polymer layer is integrated as part of the structure; the defect in the structure directly alters the sensing layer's capacitance, allowing full-coverage sensing capability independent of defect size, orientation or location. In this work, capacitance-based sensing capability was experimentally demonstrated with a 2D sensing layer consisting of a dielectric layer sandwiched by electrodes. These sensing layers were applied on substrate surfaces. Surface indentation damage (~1mm diameter) and its location were detected through measured capacitance changes: 1 to 250 % depending on the substrates. The damage detection sensors are light weight, and they can be conformably coated and can be part of the composite structure. Therefore it is suitable for aerospace structures such as cryogenic tanks and rocket

  14. TACT: A Set of MSC/PATRAN- and MSC/NASTRAN- based Modal Correlation Tools

    NASA Technical Reports Server (NTRS)

    Marlowe, Jill M.; Dixon, Genevieve D.

    1998-01-01

    This paper describes the functionality and demonstrates the utility of the Test Analysis Correlation Tools (TACT), a suite of MSC/PATRAN Command Language (PCL) tools which automate the process of correlating finite element models to modal survey test data. The initial release of TACT provides a basic yet complete set of tools for performing correlation totally inside the PATRAN/NASTRAN environment. Features include a step-by-step menu structure, pre-test accelerometer set evaluation and selection, analysis and test result export/import in Universal File Format, calculation of frequency percent difference and cross-orthogonality correlation results using NASTRAN, creation and manipulation of mode pairs, and five different ways of viewing synchronized animations of analysis and test modal results. For the PATRAN-based analyst, TACT eliminates the repetitive, time-consuming and error-prone steps associated with transferring finite element data to a third-party modal correlation package, which allows the analyst to spend more time on the more challenging task of model updating. The usefulness of this software is presented using a case history, the correlation for a NASA Langley Research Center (LaRC) low aspect ratio research wind tunnel model. To demonstrate the improvements that TACT offers the MSC/PATRAN- and MSC/DIASTRAN- based structural analysis community, a comparison of the modal correlation process using TACT within PATRAN versus external third-party modal correlation packages is presented.

  15. In situ detection of warfarin using time-correlated single-photon counting

    SciTech Connect

    Rosengren, Annika M.; Karlsson, Bjoern C.G.; Naeslund, Inga; Andersson, Per Ola; Nicholls, Ian A.

    2011-04-01

    Highlights: {yields} Direct in situ measurement of specific isomeric forms of the anticoagulant warfarin. {yields} TCSPC spectroscopy in conjunction with synthetic Sudlow I binding site receptors. {yields} Development of sensor principle for use in clinical and environmental monitoring. -- Abstract: Here we report on a novel method for the direct in situ measurement of specific isomeric forms of the anticoagulant warfarin using time correlated single-photon counting (TCSPC) spectroscopy in conjunction with synthetic Sudlow I binding site receptors. The method is highly robust over the clinically significant concentration range, and demonstrates the potential of the binding site mimics in conjunction with the spectroscopic strategy employed here for the determination of this important pharmaceutical in clinical or even environmental samples.

  16. Single gold nanoparticles to enhance the detection of single fluorescent molecules at micromolar concentration using fluorescence correlation spectroscopy

    NASA Astrophysics Data System (ADS)

    Punj, Deep; Rigneault, Hervé; Wenger, Jérôme

    2014-05-01

    Single nanoparticles made of noble metals are strongly appealing to develop practical applications to detect fluorescent molecules in solution. Here, we detail the use of a single gold nanoparticle of 100 nm diameter to enhance the detection of single Alex Fluor 647 fluorescent molecules at high concentrations of several micromolar. We discuss the implementation of fluorescence correlation spectroscopy, and provide a new method to reliably extract the enhanced fluorescence signal stemming from the nanoparticle near-field from the background generated in the confocal volume. The applicability of our method is checked by reporting the invariance of the single molecule results as function of the molecular concentration, and the experimental data is found in good agreement with numerical simulations.

  17. Electrochemiluminescence detection in microfluidic cloth-based analytical devices.

    PubMed

    Guan, Wenrong; Liu, Min; Zhang, Chunsun

    2016-01-15

    This work describes the first approach at combining microfluidic cloth-based analytical devices (μCADs) with electrochemiluminescence (ECL) detection. Wax screen-printing is employed to make cloth-based microfluidic chambers which are patterned with carbon screen-printed electrodes (SPEs) to create truly disposable, simple, inexpensive sensors which can be read with a low-cost, portable charge coupled device (CCD) imaging sensing system. And, the two most commonly used ECL systems of tris(2,2'-bipyridyl)ruthenium(II)/tri-n-propylamine (Ru(bpy)3(2+)/TPA) and 3-aminophthalhydrazide/hydrogen peroxide (luminol/H2O2) are applied to demonstrate the quantitative ability of the ECL μCADs. In this study, the proposed devices have successfully fulfilled the determination of TPA with a linear range from 2.5 to 2500μM with a detection limit of 1.265μM. In addition, the detection of H2O2 can be performed in the linear range of 0.05-2.0mM, with a detection limit of 0.027mM. It has been shown that the ECL emission on the wax-patterned cloth device has an acceptable sensitivity, stability and reproducibility. Finally, the applicability of cloth-based ECL is demonstrated for determination of glucose in phosphate buffer solution (PBS) and artificial urine (AU) samples, with the detection limits of 0.032mM and 0.038mM, respectively. It can be foreseen, therefore, that μCADs with ECL detection could provide a new sensing platform for point-of-care testing, public health, food safety detection and environmental monitoring in remote regions, developing or developed countries. PMID:26319168

  18. Identifying Threats Using Graph-based Anomaly Detection

    NASA Astrophysics Data System (ADS)

    Eberle, William; Holder, Lawrence; Cook, Diane

    Much of the data collected during the monitoring of cyber and other infrastructures is structural in nature, consisting of various types of entities and relationships between them. The detection of threatening anomalies in such data is crucial to protecting these infrastructures. We present an approach to detecting anomalies in a graph-based representation of such data that explicitly represents these entities and relationships. The approach consists of first finding normative patterns in the data using graph-based data mining and then searching for small, unexpected deviations to these normative patterns, assuming illicit behavior tries to mimic legitimate, normative behavior. The approach is evaluated using several synthetic and real-world datasets. Results show that the approach has high truepositive rates, low false-positive rates, and is capable of detecting complex structural anomalies in real-world domains including email communications, cellphone calls and network traffic.

  19. Nanoparticles based DNA conjugates for detection of pathogenic microorganisms

    NASA Astrophysics Data System (ADS)

    Jamdagni, Pragati; Khatri, Poonam; Rana, J. S.

    2016-01-01

    Infectious diseases have been on rise in the recent past. Early diagnosis plays a role as important as proper treatment and prophylaxis. The current practices of detection are time consuming which may result in unnecessary delays in treatment. Advances in nanodiagnostic approaches have been in focus lately. The rising interest and better understanding of nanoparticles have led to opening up of new frontiers in the concerned area. Optical properties of nanoparticles are being exploited to design detection systems that can provide fast, one-step and reliable results. Based on conserved DNA sequences unique to the target organism, the results offer accuracy comparable to conventional tests. Further, visual or spectrophotometric analysis omits the need of costly apparatus for result interpretation. The present review aims at putting together the information on nanoparticles based DNA conjugate systems for detection of pathogenic microorganisms.

  20. Neurotransmitter imaging in living cells based on native fluorescence detection

    SciTech Connect

    Tan, W.; Yeung, E.S. |; Parpura, V.; Haydon, P.G.

    1995-08-01

    A UV laser-based optical microscope and CCD detection system with high sensitivity has been developed to image neurotransmitters in living cells. We demonstrate the detection of serotonin that has been taken up into individual living glial cells (astrocytes) based on its native fluorescence. We found that the fluorescence intensity of astrocytes increased by up to 10 times after serotonin uptake. The temporal resolution of this detection system at 10{sup -4} M serotonin is as fast as 50 ms, and the spatial resolution is diffraction limited. This UV laser microscope imaging system shows promise for studies of spatial-temporal dynamics of neurotransmitter levels in living neurons and glia. 19 refs., 5 figs., 1 tab.