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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. Model-Based Signal Processing: Correlation Detection With Synthetic Seismograms

    SciTech Connect

    Rodgers, A; Harris, D; Pasyanos, M; Blair, S; Matt, R

    2006-08-30

    Recent applications of correlation methods to seismological problems illustrate the power of coherent signal processing applied to seismic waveforms. Examples of these applications include detection of low amplitude signals buried in ambient noise and cross-correlation of sets of waveforms to form event clusters and accurately measure delay times for event relocation and/or earth structure. These methods rely on the exploitation of the similarity of individual waveforms and have been successfully applied to large sets of empirical observations. However, in cases with little or no empirical event data, such as aseismic regions or exotic event types, correlation methods with observed seismograms will not be possible due to the lack of previously observed similar waveforms. This study uses model-based signals computed for three-dimensional (3D) Earth models to form the basis for correlation detection. Synthetic seismograms are computed for fully 3D models estimated from the Markov Chain Monte-Carlo (MCMC) method. MCMC uses stochastic sampling to fit multiple seismological data sets. Rather than estimate a single ''optimal'' model, MCMC results in a suite of models that sample the model space and incorporates uncertainty through variability of the models. The variability reflects our ignorance of Earth structure, due to limited resolution, data and modeling errors, and produces variability in the seismic waveform response. Model-based signals are combined using a subspace method where the synthetic signals are decomposed into an orthogonal basis by singular-value decomposition (SVD) and the observed waveforms are represented with a linear combination of a sub-set of eigenvectors (signals) associated with the most significant eigenvalues. We have demonstrated the method by modeling long-period (80-10 seconds) regional seismograms for a moderate (M{approx}5) earthquake near the China-North Korea border. Synthetic seismograms are computed with the Spectral Element Method

  4. 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.

  5. Enhanced video-based target detection using multi-frame correlation filtering

    SciTech Connect

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

    2009-01-01

    Most existing video-based target detection systems employ state-space models to keep track of an explicit number of individual targets. We introduce a framework for enhancing target detection in video by applying probabilistic models to the soft information in correlation outputs before thresholding. We show how to efficiently compute arrays of posterior target probabilities for every position in the scene conditioned on all current and past frames of a video sequence. These arrays can then be thresholded in the typical manner to yield more reliable target detections. Because the framework avoids the formation of explicit tracks, it is well suited for handling scenes with unknown numbers of targets at unknown positions. Simulation results on forward-looking infrared (FLIR) video sequences show that our proposed framework can significantly reduce the false-alarm rate of a bank of correlation filters while requiring only a marginal increase in computation.

  6. Correlation enhanced modularity-based belief propagation method for community detection in networks

    NASA Astrophysics Data System (ADS)

    Lai, Darong; Shu, Xin; Nardini, Christine

    2016-05-01

    Community structure is an important feature of networks, and the correct detection of communities is a fundamental problem in network analysis. Statistical inference has recently been proposed for successful detection, provided the number of communities can be appropriately estimated a priori. In the absence of such information, model selection by determination of the number of communities remains an issue. We show here that correlation between communities from a highly parceled partition can be used to estimate a narrow range of variation for the real number of communities. This range, further elaborated by modularity-based belief propagation, correctly identifies communities. Testing on synthetic networks generated by a stochastic block model and a set of real-world networks shows that our method can alleviate the effects of modularity fluctuations well and enhance the ability of community detection of the bare modularity-based belief propagation method.

  7. Correlation Detection Based on the Reconstructed Excitation Signal of Electromagnetic Seismic Vibrator

    NASA Astrophysics Data System (ADS)

    Yang, Z.; Jiang, T.; Xu, X.; Jia, H.

    2014-12-01

    Correlation detection method is generally used to detect seismic data of electromagnetic seismic vibrator, which is widely applicated for shallow mineral prospecting. By analyzing field seismic data from electromagnetic and hydraulic seismic vibrators in mining area, we find when media underground is complex or the base-plate of vibrator is coupled poorly with ground, there is a 9.30 m positioning precision error and false multiple waves in the electromagnetic vibrator data reference to hydraulic vibrator data. The paper analyzes the theoretical reason of above problems by studying how the signal of electromagnetic vibrator is excited, then proposes a new method of correlation detection based on the reconstructed excitation signal (CDBRES). CDBRES includes following steps. First, it extracts the direct wave signal from seismometer near base-plate of electromagnetic vibrator. Next, it reconstructs the excitation signal according to the extracted direct wave. Then, it detects the seismic data using cross-correlation with the reconstructed excitation signal as a reference. Finally, it uses spectrum whitening to improve detection quality. We simulate with ray-tracing method, and simulation results show that the reconstructed excitation signal is extremely consistence with the ideal excitation signal, the correlation coefficient between them is up to 0.9869. And the signal of electromagnetic vibrator is detected correctly with CDBRES method. Then a field comparison experiment between hydraulic vibrator MiniVib T15000 and electromagnetic vibrator PHVS 500 was carried out near a copper and nickel deposit area. Their output force are 30000N and 300N, respectively. Though there is a great output force difference, the detection result of PHVS 500 using CDBRES method is still consistent with MiniVib T15000. Reference to the MiniVib T15000, the positioning error of PHVS 500 is only 0.93m in relatively stronger noise level. In addition, false multiple waves are invisible. In

  8. Study on an auto-correlation-function-based damage index: Sensitivity analysis and structural damage detection

    NASA Astrophysics Data System (ADS)

    Zhang, Muyu; Schmidt, Rüdiger

    2015-12-01

    The damage index based on the auto correlation function to detect the damage of the structure under white noise excitation is studied in detail in this paper. The maximum values of the auto correlation function of the vibration response signals (displacement, velocity and acceleration) from different measurement points of the structure are collected and formulated as a vector called Auto Correlation Function at Maximum Point Value Vector (AMV), which is expressed as a weighted combination of the Hadamard product of two mode shapes. AMV is normalized by its root mean square value so that the influence of the excitation can be eliminated. Sensitivity analysis for the different parts of the normalized AMV shows that the sensitivity of the normalized AMV to the local stiffness is dependent most on the sensitivity of the Hadamard product of the two lower order mode shapes to the local stiffness, which has a sudden change of the value around the local stiffness change position. The sensitivity of the normalized AMV has the similar shape and same trend that shows it is a very good damage indicator even for the very small damage. The relative change of the normalized AMV before and after damage occurs in the structure is adopted as the damage index to show the damage location. Several examples of the stiffness reduction detection of a 12-story shear frame structure are utilized to validate the results in sensitivity analysis, illustrate the effectiveness and anti-noise ability of the AMV-based damage detection method and compare the effect of the response type on the detectability of the normalized AMV.

  9. Thresholding Based on Maximum Weighted Object Correlation for Rail Defect Detection

    NASA Astrophysics Data System (ADS)

    Li, Qingyong; Huang, Yaping; Liang, Zhengping; Luo, Siwei

    Automatic thresholding is an important technique for rail defect detection, but traditional methods are not competent enough to fit the characteristics of this application. This paper proposes the Maximum Weighted Object Correlation (MWOC) thresholding method, fitting the features that rail images are unimodal and defect proportion is small. MWOC selects a threshold by optimizing the product of object correlation and the weight term that expresses the proportion of thresholded defects. Our experimental results demonstrate that MWOC achieves misclassification error of 0.85%, and outperforms the other well-established thresholding methods, including Otsu, maximum correlation thresholding, maximum entropy thresholding and valley-emphasis method, for the application of rail defect detection.

  10. [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. PMID:24822407

  11. 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.

  12. 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

  13. 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.

  14. Sensitivity analysis of an auto-correlation-function-based damage index and its application in structural damage detection

    NASA Astrophysics Data System (ADS)

    Zhang, Muyu; Schmidt, Rüdiger

    2014-12-01

    Structural damage detection using time domain vibration responses has advantages such as simplicity in calculation and no requirement of a finite element model, which attracts more and more researchers in recent years. In present paper, a new approach to detect the damage based on the auto correlation function is proposed. The maximum values of the auto correlation function of the vibration response signals from different measurement points are formulated as a vector called Auto Correlation Function at Maximum Point Value Vector, AMV for short. The relative change of the normalized AMV before and after damage is used as the damage index to locate the damage. Sensitivity analysis of the normalized AMV with respect to the local stiffness shows that the normalized AMV has a sharp change around the local stiffness change location, which means the normalized AMV is a good indicator to detect the damage even when the damage is very small. Stiffness reduction detection of a 12-story frame structure is provided to illustrate the validity, effectiveness and the anti-noise ability of the proposed method. Comparison of the normalized AMV and the other correlation-function-based damage detection method shows the normalized AMV has a better detectability.

  15. Evaluation of sensitivity of fluorescence-based asbestos detection by correlative microscopy.

    PubMed

    Ishida, Takenori; Alexandrov, Maxym; Nishimura, Tomoki; Minakawa, Kenji; Hirota, Ryuichi; Sekiguchi, Kiyoshi; Kohyama, Norihiko; Kuroda, Akio

    2012-01-01

    Fluorescence microscopy (FM) has recently been applied to the detection of airborne asbestos fibers that can cause asbestosis, mesothelioma and lung cancer. In our previous studies, we discovered that the E. coli protein DksA specifically binds to the most commonly used type of asbestos, chrysotile. We also demonstrated that fluorescent-labeled DksA enabled far more specific and sensitive detection of airborne asbestos fibers than conventional phase contrast microscopy (PCM). However, the actual diameter of the thinnest asbestos fibers visualized under the FM platform was unclear, as their dimensions were below the resolution of optical microscopy. Here, we used correlative microscopy (scanning electron microscopy [SEM] in combination with FM) to measure the actual diameters of asbestos fibers visualized under the FM platform with fluorescent-labeled DksA as a probe. Our analysis revealed that FM offers sufficient sensitivity to detect chrysotile fibrils as thin as 30-35 nm. We therefore conclude that as an analytical method, FM has the potential to detect all countable asbestos fibers in air samples, thus approaching the sensitivity of SEM. By visualizing thin asbestos fibers at approximately tenfold lower magnifications, FM enables markedly more rapid counting of fibers than SEM. Thus, fluorescence microscopy represents an advanced analytical tool for asbestos detection and monitoring. PMID:21932006

  16. Selecting Valid Correlation Areas for Automated Bullet Identification System Based on Striation Detection

    PubMed Central

    Chu, Wei; Song, John; Vorburger, Theodore V.; Thompson, Robert; Silver, Richard

    2011-01-01

    Some automated bullet identification systems calculate a correlation score between two land impressions to measure their similarity. When extracting a compressed profile from the land impression of a fired bullet, inclusion of areas that do not contain valid individual striation information may lead to sub-optimal extraction and therefore may deteriorate the correlation result. In this paper, an edge detection algorithm and selection process are used together to locate the edge points of all tool-mark features and filter out those not corresponding to striation marks. Edge points of the resulting striation marks are reserved and expanded to generate a mask image. By imposing the mask image on the topography image, the weakly striated area(s) are removed from the expressed profile extraction. Using this method, 48 bullets fired from 12 gun barrels of six manufacturers resulted in a higher matching rate than previous studies. PMID:26989589

  17. Minimax distance transform correlation filter-based target detection in FLIR imagery

    NASA Astrophysics Data System (ADS)

    Khan, J. F.; Alam, M. S.; Adhami, R. R.; Bhuiyan, S. M. A.

    2005-08-01

    This paper proposes a method to detect objects of arbitrary poses and sizes from a complex forward looking infrared (FLIR) image scene exploiting image correlation technique along with the preprocessing of the scene using a class of morphological operators. This presented automatic target recognition (ATR) algorithm consists of two steps. In the first step, the image is preprocessed, by employing morphological reconstruction operators, to remove the background as well as clutter and to intensify the presence of both low or high contrast targets. This step also involves in finding the possible candidate target regions or region of interests (ROIs) and passing those ROIs to the second step for classification. The second step exploits template-matching technique such as minimax distance transform correlation filter (MDTCF) to identify the true target from the false alarms in the pre-selected ROIs after classification. The MDTCF minimizes the average squared distance from the filtered true-class training images to a filtered reference image while maximizing the mean squared distance of the filtered false-class training images to this filtered reference image. This approach increases the separation between the false-class correlation outputs and the true-class correlation outputs. Classification is performed using the squared distance of a filtered test image to the chosen filtered reference image. The proposed technique has been tested with real life FLIR image sequences supplied by the Army Missile Command (AMCOM). Experimental results, obtained with these real FLIR image sequences, illustrating a wide variety of target and clutter variability, demonstrate the effectiveness and robustness of the proposed method.

  18. 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. PMID:27368774

  19. 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.

  20. 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.

  1. Neural correlates of face detection.

    PubMed

    Xu, Xiaokun; Biederman, Irving

    2014-06-01

    Although face detection likely played an essential adaptive role in our evolutionary past and in contemporary social interactions, there have been few rigorous studies investigating its neural correlates. MJH, a prosopagnosic with bilateral lesions to the ventral temporal-occipital cortices encompassing the posterior face areas (fusiform and occipital face areas), expresses no subjective difficulty in face detection, suggesting that these posterior face areas do not mediate face detection exclusively. Despite his normal contrast sensitivity and visual acuity in foveal vision, the present study nevertheless revealed significant face detection deficits in MJH. Compared with controls, MJH showed a lower tolerance to noise in the phase spectrum for faces (vs. cars), reflected in his higher detection threshold for faces. MJH's lesions in bilateral occipito-temporal cortices thus appear to have produced a deficit not only in face individuation, but also in face detection. PMID:23365211

  2. 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.

  3. 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

  4. 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

  5. WCEDS: A waveform correlation event detection system

    SciTech Connect

    Young, C.J.; Beiriger, J.I.; Trujillo, J.R.; Withers, M.M.; Aster, R.C.; Astiz, L.; Shearer, P.M.

    1995-08-01

    We have developed a working prototype of a grid-based global event detection system based on waveform correlation. The algorithm comes from a long-period detector but we have recast it in a full matrix formulation which can reduce the number of multiplications needed by better than two orders of magnitude for realistic monitoring scenarios. The reduction is made possible by eliminating redundant multiplications in the original formulation. All unique correlations for a given origin time are stored in a correlation matrix (C) which is formed by a full matrix product of a Master Image matrix (M) and a data matrix (D). The detector value at each grid point is calculated by following a different summation path through the correlation matrix. Master Images can be derived either empirically or synthetically. Our testing has used synthetic Master Images because their influence on the detector is easier to understand. We tested the system using the matrix formulation with continuous data from the IRIS (Incorporate Research Institutes for Seismology) broadband global network to monitor a 2 degree evenly spaced surface grid with a time discretization of 1 sps; we successfully detected the largest event in a two hour segment from October 1993. The output at the correct gridpoint was at least 33% larger than at adjacent grid points, and the output at the correct gridpoint at the correct origin time was more than 500% larger than the output at the same gridpoint immediately before or after. Analysis of the C matrix for the origin time of the event demonstrates that there are many significant ``false`` correlations of observed phases with incorrect predicted phases. These false correlations dull the sensitivity of the detector and so must be dealt with if our system is to attain detection thresholds consistent with a Comprehensive Test Ban Treaty (CTBT).

  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.; 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

  7. 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.

  8. Cross correlation anomaly detection system

    NASA Technical Reports Server (NTRS)

    Micka, E. Z. (Inventor)

    1975-01-01

    This invention provides a method for automatically inspecting the surface of an object, such as an integrated circuit chip, whereby the data obtained by the light reflected from the surface, caused by a scanning light beam, is automatically compared with data representing acceptable values for each unique surface. A signal output provided indicated of acceptance or rejection of the chip. Acceptance is based on predetermined statistical confidence intervals calculated from known good regions of the object being tested, or their representative values. The method can utilize a known good chip, a photographic mask from which the I.C. was fabricated, or a computer stored replica of each pattern being tested.

  9. 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.

  10. Exploring underwater target detection by imaging polarimetry and correlation techniques.

    PubMed

    Dubreuil, M; Delrot, P; Leonard, I; Alfalou, A; Brosseau, C; Dogariu, A

    2013-02-10

    Underwater target detection is investigated by combining active polarization imaging and optical correlation-based approaches. Experiments were conducted in a glass tank filled with tap water with diluted milk or seawater and containing targets of arbitrary polarimetric responses. We found that target estimation obtained by imaging with two orthogonal polarization states always improves detection performances when correlation is used as detection criterion. This experimental study illustrates the potential of polarization imaging for underwater target detection and opens interesting perspectives for the development of underwater imaging systems. PMID:23400061

  11. Change Point Detection in Correlation Networks

    PubMed Central

    Barnett, Ian; Onnela, Jukka-Pekka

    2016-01-01

    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. PMID:26739105

  12. Neonatal seizure detection using blind distributed detection with correlated decisions.

    PubMed

    Li, Huaying; Jeremíc, Aleksandar

    2011-01-01

    Seizure is the result of excessive electrical discharges of neurons, which usually develops synchronously and happens suddenly in the central nervous system. Clinically, it is difficult for physician to identify neonatal seizures visually, while EEG seizures can be recognized by the trained experts. By extending our previous results on multichannel information fusion, we propose an automated distributed detection system consisting of the existing detectors and a fusion centre to detect the seizure activities in the newborn EEG assuming that the decisions of local detectors are correlated. The advantage of this proposed technique is that it accounts for correlated decisions of the local detectors. It has been shown that correlation between local detectors can lead to severe performance degradation if not modelled properly. Therefore our proposed technique can potentially improve the performance of existing single and multichannel neonatal seizure detection algorithms. PMID:22255847

  13. Correlation between ELISA and pseudovirion-based neutralisation assay for detecting antibodies against human papillomavirus acquired by natural infection or by vaccination

    PubMed Central

    Zhao, Hui; Lin, Zhi-Jie; Huang, Shou-Jie; Li, Juan; Liu, Xiao-Hui; Guo, Meng; Zhang, Jun; Xia, Ning-Shao; Pan, Hui-Rong; Wu, Ting; Li, Chang-Gui

    2014-01-01

    A pseudovirion-based neutralisation assay (PBNA) has been considered the gold standard for measuring specific antibody responses against human papillomavirus (HPV). However, this assay is labor intensive and therefore very difficult to implement in large-scale studies. Previous studies have evaluated the agreement between virus-like particle (VLP)-based ELISA and PBNA for measuring HPV vaccine-induced antibodies. However, the concordance of these assays to detect antibodies induced by natural infection has not yet been fully elucidated. In this study, the results of an Escherichia coli (E. coli)-expressed VLP-based ELISA were found to be highly concordant with those of a baculovirus-expressed VLP-based ELISA (r = 0.96 and 0.97 for HPV-16 and HPV-18) when detecing HPV vaccine induced antibodies and the concordance was medium (r = 0.68 and 0.68 for HPV-16 and HPV-18) when assessing natural infection induced antibodies. The results of the E. coli expressed VLP-based ELISA correlated well with those of the PBNA when testing 1020 post-vaccination human sera collected at one month after vaccination with the E. coli expressed VLP-based bivalent HPV vaccine (r = 0.83 and 0.81 for HPV-16 and HPV-18). The agreement and correlation were moderate (kappa < 0.3 for both HPV types 16 and 18, r = 0.59 and 0.68 for HPV-16 and HPV-18, respectively) when assessing 1600 serum samples from unvaccinated women of age 18–25 years. In conclusion, the VLP-based ELISA is an acceptable surrogate for the neutralizing antibody assay in measuring vaccine responses. However, the use of the VLP-based ELISA in epidemiological studies should be carefully considered. PMID:24384608

  14. 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.

  15. Uncovering Quantum Correlations with Time-Multiplexed Click Detection.

    PubMed

    Sperling, J; Bohmann, M; Vogel, W; Harder, G; Brecht, B; Ansari, V; Silberhorn, C

    2015-07-10

    We report on the implementation of a time-multiplexed click detection scheme to probe quantum correlations between different spatial optical modes. We demonstrate that such measurement setups can uncover nonclassical correlations in multimode light fields even if the single mode reductions are purely classical. The nonclassical character of correlated photon pairs, generated by a parametric down-conversion, is immediately measurable employing the theory of click counting instead of low-intensity approximations with photoelectric detection models. The analysis is based on second- and higher-order moments, which are directly retrieved from the measured click statistics, for relatively high mean photon numbers. No data postprocessing is required to demonstrate the effects of interest with high significance, despite low efficiencies and experimental imperfections. Our approach shows that such novel detection schemes are a reliable and robust way to characterize quantum-correlated light fields for practical applications in quantum communications. PMID:26207467

  16. Uncovering Quantum Correlations with Time-Multiplexed Click Detection

    NASA Astrophysics Data System (ADS)

    Sperling, J.; Bohmann, M.; Vogel, W.; Harder, G.; Brecht, B.; Ansari, V.; Silberhorn, C.

    2015-07-01

    We report on the implementation of a time-multiplexed click detection scheme to probe quantum correlations between different spatial optical modes. We demonstrate that such measurement setups can uncover nonclassical correlations in multimode light fields even if the single mode reductions are purely classical. The nonclassical character of correlated photon pairs, generated by a parametric down-conversion, is immediately measurable employing the theory of click counting instead of low-intensity approximations with photoelectric detection models. The analysis is based on second- and higher-order moments, which are directly retrieved from the measured click statistics, for relatively high mean photon numbers. No data postprocessing is required to demonstrate the effects of interest with high significance, despite low efficiencies and experimental imperfections. Our approach shows that such novel detection schemes are a reliable and robust way to characterize quantum-correlated light fields for practical applications in quantum communications.

  17. 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.

  18. 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

  19. 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).

  20. 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.

  1. 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.

  2. 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

  3. Reveal quantum correlation in complementary bases

    PubMed Central

    Wu, Shengjun; Ma, Zhihao; Chen, Zhihua; Yu, Sixia

    2014-01-01

    An essential feature of genuine quantum correlation is the simultaneous existence of correlation in complementary bases. We reveal this feature of quantum correlation by defining measures based on invariance under a basis change. For a bipartite quantum state, the classical correlation is the maximal correlation present in a certain optimum basis, while the quantum correlation is characterized as a series of residual correlations in the mutually unbiased bases. Compared with other approaches to quantify quantum correlation, our approach gives information-theoretical measures that directly reflect the essential feature of quantum correlation. PMID:24503595

  4. 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

  5. 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.

  6. 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.

  7. Detecting correlations among functional-sequence motifs.

    PubMed

    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. PMID:23005179

  8. 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

  9. 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.

  10. 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

  11. Signal processing in photoacoustic detection of phase transitions by means of the autospectra correlation-based method: Evaluation with ceramic BaTiO3

    NASA Astrophysics Data System (ADS)

    Mejía-Uriarte, E. V.; Navarrete, M.; Villagrán-Muniz, M.

    2004-09-01

    This work describes a simple numerical procedure which, when applied to digitally recorded photoacoustic (PA) signals, allows the construction of thermal profiles (rS,drS/dT) to determine: the transition order, the phase transition temperature (Tc), and the phase transformation temperature range (ΔT), on samples, which undergo low-high transitions. During continuous heating of the sample, the ultrasonic signal was generated using a pulsed laser beam incident on a surface and detected on the opposite surface of the sample using a long quartz bar attached to a piezoelectric sensor. The thermal profile, rS, is built from a sequence of the ordinary correlation coefficients ri associated with an interval of temperature. The ri coefficients are calculated from amplitude spectra pairs. The amplitude spectra are obtained via fast Fourier transforms from original PA records. This procedure is applied on samples of bulk ceramic BaTiO3 to obtain their thermal behavior. The PA signal and temperature sample were registered every 0.2°. The samples were heated from room temperature to 137 °C at a rate of 0.1 °C min-1. The thermal profile rS shows the entire thermal history including the structural phase transition from tetragonal to cubic (T-C), which appears as a jump on the graph within an uncertainty of 2%. The drS/dT profile shows that the T-C phase transformation occurs over a range of temperatures. The results are in agreement with those reported in the literature.

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

    DOE PAGESBeta

    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

  13. Improving detection range via correlation of long PN codes

    NASA Astrophysics Data System (ADS)

    Subedi, Saurav; Wang, Zhonghai; Zheng, Y. Rosa

    2012-06-01

    This paper proposes a correlation method for detecting super-regenerative RF receivers via stimulation. Long PN sequences are used as to stimulate the unintended emissions from the RF receivers. High correlation between known PN sequence and stimulated unintended emissions from RF receivers helps improving the detection range compared to passive detection and power detection methods. Although RF receivers generate unintended emissions from their nonlinear devices, without stimulation, the power of these unintended emission is usually lower than --70dBm, as per the FCC regulations. Direct detection (passive detection) of these emissions is a challenging task specially in noisy conditions. When a stimulation signal is transmitted from distance, superregenerative receivers generate unintended emissions that contain the stimulation signal and its harmonics. Excellent correlation property of PN sequence enables us to improve the range and accuracy of detecting the super-regenerative receivers through stimulation method even in noisy conditions. The experiment involves detection of wireless doorbell, a commercially available super-regenerative receiver. USRP is used for transmitting the stimulant signal and receiving unintended stimulated emissions from the doorbell. Experiments show that the detection range of the proposed method with long PN sequences is much larger than passive detection and power detection methods.

  14. 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

  15. 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.

  16. Diffraction-based optical correlator

    NASA Technical Reports Server (NTRS)

    Spremo, Stevan M. (Inventor); Fuhr, Peter L. (Inventor); Schipper, John F. (Inventor)

    2005-01-01

    Method and system for wavelength-based processing of a light beam. A light beam, produced at a chemical or physical reaction site and having at least first and second wavelengths, ?1 and ?2, is received and diffracted at a first diffraction grating to provide first and second diffracted beams, which are received and analyzed in terms of wavelength and/or time at two spaced apart light detectors. In a second embodiment, light from first and second sources is diffracted and compared in terms of wavelength and/or time to determine if the two beams arise from the same source. In a third embodiment, a light beam is split and diffracted and passed through first and second environments to study differential effects. In a fourth embodiment, diffracted light beam components, having first and second wavelengths, are received sequentially at a reaction site to determine whether a specified reaction is promoted, based on order of receipt of the beams. In a fifth embodiment, a cylindrically shaped diffraction grating (uniform or chirped) is rotated and translated to provide a sequence of diffracted beams with different wavelengths. In a sixth embodiment, incident light, representing one or more symbols, is successively diffracted from first and second diffraction gratings and is received at different light detectors, depending upon the wavelengths present in the incident light.

  17. 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.

  18. 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

  19. 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.

  20. 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

  1. Norm-based measurement of quantum correlation

    SciTech Connect

    Wu Yuchun; Guo Guangcan

    2011-06-15

    In this paper we derived a necessary and sufficient condition for classical correlated states and proposed a norm-based measurement Q of quantum correlation. Using the max norm of operators, we gave the expression of the quantum correlation measurement Q and investigated the dynamics of Q in Markovian and non-Markovian cases, respectively. Q decays exponentially and vanishes only asymptotically in the Markovian case and causes periodical death and rebirth in the non-Markovian case. In the pure state, the quantum correlation Q is always larger than the entanglement, which was different from other known measurements. In addition, we showed that locally broadcastable and broadcastable are equivalent and reproved the density of quantum correlated states.

  2. 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

  3. 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

  4. Across-frequency envelope correlation discrimination and masked signal detection

    PubMed Central

    Grose, John H.; Buss, Emily; Porter, Heather L.; Hall, Joseph W.

    2013-01-01

    This study compared the dependence of comodulation masking release (CMR) and monaural envelope correlation perception (MECP) on the degree of envelope correlation for the same narrowband noise stimuli. Envelope correlation across noise bands was systematically varied by mixing independent bands with a base set of comodulated bands. The magnitude of CMR fell monotonically with reductions in envelope correlation, and CMR varied over a range of envelope correlations that were not discriminable from each other in the MECP paradigm. For complexes of 100-Hz-wide noise bands, discrimination thresholds in the MECP task were similar whether the standard was a comodulated set of noise bands or a completely independent set of noise bands. This was not the case for 25-Hz-wide noise bands. Although the data demonstrate that CMR and MECP exhibit different dependencies on the degree of envelope correlation, some commonality across the two phenomena was observed. Specifically, for 25-Hz-wide bands of noise, there was a robust relationship between individual listeners' sensitivity to decorrelation from an otherwise comodulated set of noise bands and the magnitude of CMR measured for those same comodulated noise bands. PMID:23927119

  5. 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.

  6. 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

  7. 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

  8. On detecting and modeling periodic correlation in financial data

    NASA Astrophysics Data System (ADS)

    Broszkiewicz-Suwaj, E.; Makagon, A.; Weron, R.; Wyłomańska, A.

    2004-05-01

    For many economic problems standard statistical analysis, based on the notion of stationarity, is not adequate. These include modeling seasonal decisions of consumers, forecasting business cycles and-as we show in the present article-modeling wholesale power market prices. We apply standard methods and a novel spectral domain technique to conclude that electricity price returns exhibit periodic correlation with daily and weekly periods. As such they should be modeled with periodically correlated processes. We propose to apply periodic autoregression models which are closely related to the standard instruments in econometric analysis-vector autoregression models.

  9. 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.

  10. Motion detection based on recurrent network dynamics

    PubMed Central

    Joukes, Jeroen; Hartmann, Till S.; Krekelberg, Bart

    2014-01-01

    The detection of visual motion requires temporal delays to compare current with earlier visual input. Models of motion detection assume that these delays reside in separate classes of slow and fast thalamic cells, or slow and fast synaptic transmission. We used a data-driven modeling approach to generate a model that instead uses recurrent network dynamics with a single, fixed temporal integration window to implement the velocity computation. This model successfully reproduced the temporal response dynamics of a population of motion sensitive neurons in macaque middle temporal area (MT) and its constituent parts matched many of the properties found in the motion processing pathway (e.g., Gabor-like receptive fields (RFs), simple and complex cells, spatially asymmetric excitation and inhibition). Reverse correlation analysis revealed that a simplified network based on first and second order space-time correlations of the recurrent model behaved much like a feedforward motion energy (ME) model. The feedforward model, however, failed to capture the full speed tuning and direction selectivity properties based on higher than second order space-time correlations typically found in MT. These findings support the idea that recurrent network connectivity can create temporal delays to compute velocity. Moreover, the model explains why the motion detection system often behaves like a feedforward ME network, even though the anatomical evidence strongly suggests that this network should be dominated by recurrent feedback. PMID:25565992

  11. Correlative Analysis of GRBs detected by Swift, Konus and HETE

    NASA Technical Reports Server (NTRS)

    Krimm, Hans A.; Barthelmy, S. D.; Gehrels, N.; Hullinger, D.; Sakamoto, T.; Donaghy, T.; Lamb, D. Q.; Pal'shin, V.; Golenetskii, S.; Ricker, G. R.

    2005-01-01

    Swift has now detected a large enough sample of gamma-ray bursts (GRBs) to allow correlation studies of burst parameters. Such studies of earlier data sets have yielded important results leading to further understanding of burst parameters and classifications. This work focuses on seventeen Swift bursts that have also been detected either by Konus-Wind or HETE-II, providing high energy spectra and fits to E(sub peak). Eight of these bursts have spectroscopic redshifts and for others we can estimate redshifts using the variability/luminosity relationship. We can also compare E(sub peak) with E(sub iso), and for those bursts for which a jet break was observed in the afterglow we can derive E(sub g) and test the relationship between E(peak) and E(sub gamma). For all bursts we can derive durations and hardness ratios from the prompt emission.

  12. 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.

  13. 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…

  14. 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.

  15. 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.

  16. 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

  17. Adaptive, Model-Based Monitoring and Threat Detection

    NASA Astrophysics Data System (ADS)

    Valdes, Alfonso; Skinner, Keith

    2002-09-01

    We explore the suitability of model-based probabilistic techniques, such as Bayes networks, to the field of intrusion detection and alert report correlation. We describe a network intrusion detection system (IDS) using Bayes inference, wherein the knowledge base is encoded not as rules but as conditional probability relations between observables and hypotheses of normal and malicious usage. The same high-performance Bayes inference library was employed in a component of the Mission-Based Correlation effort, using an initial knowledge base that adaptively learns the security administrator's preference for alert priority and rank. Another major effort demonstrated probabilistic techniques in heterogeneous sensor correlation. We provide results for simulated attack data, live traffic, and the CyberPanel Grand Challenge Problem. Our results establish that model-based probabilistic techniques are an important complementary capability to signature-based methods in detection and correlation.

  18. The waveform correlation event detection system project: Issues in system refinement, tuning, and operation

    SciTech Connect

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

    1996-08-01

    The goal of the Waveform Correlation Event Detection System (WCEDS) Project at Sandia Labs has been to develop a prototype of a full-waveform correlation based seismic event detection system which could be used to assess potential usefulness for CTBT monitoring. The current seismic event detection system in use at the IDC is very sophisticated and provides good results but there is still significant room for improvement, particularly in reducing the number of false events (currently being nearly equal to the number of real events). Our first prototype was developed last year and since then we have used it for extensive testing from which we have gained considerable insight. The original prototype was based on a long-period detector designed by Shearer (1994), but it has been heavily modified to address problems encountered in application to a data set from the Incorporated Research Institutes for Seismology (IRIS) broadband global network. Important modifications include capabilities for event masking and iterative event detection, continuous near-real time execution, improved Master Image creation, and individualized station pre-processing. All have been shown to improve bulletin quality. In some cases the system has detected marginal events which may not be detectable by traditional detection systems, but definitive conclusions cannot be made without direct comparisons. For this reason future work will focus on using the system to process GSETT3 data for comparison with current event detection systems at the IDC.

  19. Neural correlates of auditory sensory memory and automatic change detection.

    PubMed

    Sabri, Merav; Kareken, David A; Dzemidzic, Mario; Lowe, Mark J; Melara, Robert D

    2004-01-01

    An auditory event-related potential component, the mismatch negativity (MMN), reflects automatic change detection and its prerequisite, sensory memory. This study examined the neural correlates of automatic change detection using BOLD fMRI and two rates of presentation previously shown to induce either a large or no MMN. A boxcar block design was employed in two functional scans, each performed twice. A block consisting of 1000-Hz standards (S) alternated with one consisting of 1000-Hz standards and 2000-Hz infrequent deviants (S + D). Presentation rate was either 150 or 2400 ms. Fourteen participants were instructed to ignore all auditory stimulation and concentrate on a film (no audio) by reading subtitles. Data analysis used SPM99 and random effects approach. Cluster statistics (P < 0.05, corrected) were employed at a height threshold of P < 0.001. At the short ISI, there was a significant BOLD response in the right superior temporal gyrus (STG), the left insula, and the left STG (including parts of primary auditory cortex). There were no suprathreshold clusters at the long rate, with S + D blocks inducing no greater activity than S blocks. These results support the hypothesis that the automatic detection of auditory change occurs in the STG bilaterally and relies on the maintenance of sensory memory traces. PMID:14741643

  20. Theoretical NMR correlations based Structure Discussion

    PubMed Central

    2011-01-01

    The constitutional assignment of natural products by NMR spectroscopy is usually based on 2D NMR experiments like COSY, HSQC, and HMBC. The actual difficulty of the structure elucidation problem depends more on the type of the investigated molecule than on its size. The moment HMBC data is involved in the process or a large number of heteroatoms is present, a possibility of multiple solutions fitting the same data set exists. A structure elucidation software can be used to find such alternative constitutional assignments and help in the discussion in order to find the correct solution. But this is rarely done. This article describes the use of theoretical NMR correlation data in the structure elucidation process with WEBCOCON, not for the initial constitutional assignments, but to define how well a suggested molecule could have been described by NMR correlation data. The results of this analysis can be used to decide on further steps needed to assure the correctness of the structural assignment. As first step the analysis of the deviation of carbon chemical shifts is performed, comparing chemical shifts predicted for each possible solution with the experimental data. The application of this technique to three well known compounds is shown. Using NMR correlation data alone for the description of the constitutions is not always enough, even when including 13C chemical shift prediction. PMID:21797997

  1. Detecting correlated errors in state-preparation-and-measurement tomography

    NASA Astrophysics Data System (ADS)

    Jackson, Christopher; van Enk, S. J.

    2015-10-01

    Whereas in standard quantum-state tomography one estimates an unknown state by performing various measurements with known devices, and whereas in detector tomography one estimates the positive-operator-valued-measurement elements of a measurement device by subjecting to it various known states, we consider here the case of SPAM (state preparation and measurement) tomography where neither the states nor the measurement device are assumed known. For d -dimensional systems measured by d -outcome detectors, we find there are at most d2(d2-1 ) "gauge" parameters that can never be determined by any such experiment, irrespective of the number of unknown states and unknown devices. For the case d =2 we find gauge-invariant quantities that can be accessed directly experimentally and that can be used to detect and describe SPAM errors. In particular, we identify conditions whose violations detect the presence of correlations between SPAM errors. From the perspective of SPAM tomography, standard quantum-state tomography and detector tomography are protocols that fix the gauge parameters through the assumption that some set of fiducial measurements is known or that some set of fiducial states is known, respectively.

  2. 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.

  3. 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.

  4. 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.

  5. HEALPix Based Cross-Correlation in Astronomy

    NASA Astrophysics Data System (ADS)

    Fernique, P.; Durand, D.; Boch, T.; Oberto, A.; Pineau, F.

    2013-10-01

    We are presenting our work on a cross correlation system based on HEALPix cells indexing. The system allows users to answer scientific questions like “please find all HST images on which there is an observation of a radio quiet quasar” in a single query. The baseline of this system is the creation of the HEALPix indexes grouped hierarchically and organized in a special format file called MOC (see http://ivoa.net/Documents/Notes/MOC) developed by the CDS. Using the MOC files, the cross correlation between images and or catalogues is reduced to searches only in meaningful areas. Under the condition that the survey database also internally uses a HEALPix positional index, the search result comes back almost immediately (typically a few seconds). We have started building the index for some surveys, catalogues (VizieR catalogues, Simbad, etc.) and some pointed mode archives (like HST at CADC) and are developing an elementary library to support basic operations on any input MOC files. The usage of the MOC files is starting to be used throughout the VO community as a general indexing method and tools such as Aladin and TOPCAT are starting to make use of them.

  6. Detection of Antiferromagnetic Correlations in the Fermi-Hubbard Model

    NASA Astrophysics Data System (ADS)

    Hulet, Randall

    2014-05-01

    The Hubbard model, consisting of a cubic lattice with on-site interactions and kinetic energy arising from tunneling to nearest neighbors is a ``standard model'' of strongly correlated many-body physics, and it may also contain the essential ingredients of high-temperature superconductivity. While the Hamiltonian has only two terms it cannot be numerically solved for arbitrary density of spin-1/2 fermions due to exponential growth in the basis size. At a density of one spin-1/2 particle per site, however, the Hubbard model is known to exhibit antiferromagnetism at temperatures below the Néel temperature TN, a property shared by most of the undoped parent compounds of high-Tc superconductors. The realization of antiferromagnetism in a 3D optical lattice with atomic fermions has been impeded by the inability to attain sufficiently low temperatures. We have developed a method to perform evaporative cooling in a 3D cubic lattice by compensating the confinement envelope of the infrared optical lattice beams with blue-detuned laser beams. Evaporation can be controlled by the intensity of these non-retroreflected compensating beams. We observe significantly lower temperatures of a two-spin component gas of 6Li atoms in the lattice using this method. The cooling enables us to detect the development of short-range antiferromagnetic correlations using spin-sensitive Bragg scattering of light. Comparison with quantum Monte Carlo constrains the temperature in the lattice to 2-3 TN. We will discuss the prospects of attaining even lower temperatures with this method. Supported by DARPA/ARO, ONR, and NSF.

  7. 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

  8. Trends in correlation-based pattern recognition and tracking in forward-looking infrared imagery.

    PubMed

    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

  9. 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

  10. A random motility assay based on image correlation spectroscopy.

    PubMed

    Prummer, Michael; Kling, Dorothee; Trefzer, Vanessa; Enderle, Thilo; Zoffmann, Sannah; Prunotto, Marco

    2013-06-01

    We demonstrate the random motility (RAMOT) assay based on image correlation spectroscopy for the automated, label-free, high-throughput characterization of random cell migration. The approach is complementary to traditional migration assays, which determine only the collective net motility in a particular direction. The RAMOT assay is less demanding on image quality compared to single-cell tracking, does not require cell identification or trajectory reconstruction, and performs well on live-cell, time-lapse, phase contrast video microscopy of hundreds of cells in parallel. Effective diffusion coefficients derived from the RAMOT analysis are in quantitative agreement with Monte Carlo simulations and allowed for the detection of pharmacological effects on macrophage-like cells migrating on a planar collagen matrix. These results expand the application range of image correlation spectroscopy to multicellular systems and demonstrate a novel, to our knowledge, migration assay with little preparative effort. PMID:23746508

  11. Visible light communication based motion detection.

    PubMed

    Sewaiwar, Atul; Tiwari, Samrat Vikramaditya; Chung, Yeon-Ho

    2015-07-13

    In this paper, a unique and novel visible light communication based motion detection is presented. The proposed motion detection is performed based on white light LEDs and an array of photodetectors from existing visible light communication (VLC) links, thus providing VLC with three functionalities of illumination, communication and motion detection. The motion is detected by observing the pattern created by intentional obstruction of the VLC link. Experimental and simulation results demonstrate the validity of the proposed VLC based motion detection technique. The VLC based motion detection can benefit smart devices control in VLC based smart home environments. PMID:26191937

  12. Study on correlation methods for damage detection: Simulation and experimental validation

    NASA Astrophysics Data System (ADS)

    Dall'Acqua, D.; Di Maio, D.

    2014-05-01

    In the current days there is an increment of interest in damage detection methods, aimed to assure the operating status of existing structures or for intensifier quality control on production line. These are only some of the applications whereby damage detection methods have been dev eloped. In the past several researches have been addressed towards damage detection using vibration analysis, especially through mode shape and natural frequencies changes. In the preset study correlation methods based on ODSs have been developed. The structure was taken under consideration is steel plate. The correlation methods presented are based on the comparison of the ODSs generated by two FEM models of the plate, one defined as pristine and the other as damaged. The latter has been modelled adding a single node mass element to the model surface. This mass element was chosen to simulate a magnet attached to the surface plate in the experimental case. Several simulations have been performed using combinations of mass and positions, for a total of 16 cases. Studying the correlations between a ODSs pair, given by the same excitation frequency and position, is possible to identify the presence of damage in the structure. The experimental model validation has been performed using the best excitation condition obtained by simulation, which can point out large differences between the damaged ODS and undamaged ODS.

  13. 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.

  14. 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.

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

    PubMed

    Kwapień, Jarosław; Oświęcimka, Paweł; Drożdż, Stanisław

    2015-11-01

    The detrended cross-correlation coefficient ρ(DCCA) 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 ρ(DCCA) 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 ρ(DCCA) that exploits the multifractal versions of DFA and DCCA: multifractal detrended fluctuation analysis and multifractal detrended cross-correlation analysis, respectively. The resulting new coefficient ρ(q) 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 ρ(q) 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. PMID:26651752

  16. 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.

  17. 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.

  18. 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

  19. Full-field detection of surface defects using real-time holography and optical correlation techniques

    NASA Astrophysics Data System (ADS)

    Blackshire, James L.; Duncan, Bradley D.

    1999-02-01

    Innovative optical NDE techniques are being developed for the full-field detection and evaluation of surface defects and defect precursors in titanium and aluminum based alloys. The techniques are based on frequency-translated holography and optical correlation principles, and use bacteriohodopsin (bR) holographic films and temporal correlation techniques for real-time storage and retrieval of Surface Acoustic Waves (SAW) features and embedded surface defect information. The SAW waves induced on the material surface being studied are made to interfere with optical light waves, and fringes are produced that are a function of optical Doppler shifts induced by phonon-photon interaction on the surface of the materials. Visualization of these SAW patterns allow for NDE characterization of features on and near the surface of the materials, including defect and defect precursor sites. Preliminary results are provided for real-time bR holographic recordings of acoustic patterns induced on Al2024-T3 material surfaces.

  20. 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.

  1. Detecting temporal and spatial correlations in pseudoperiodic time series

    NASA Astrophysics Data System (ADS)

    Zhang, Jie; Luo, Xiaodong; Nakamura, Tomomichi; Sun, Junfeng; Small, Michael

    2007-01-01

    Recently there has been much attention devoted to exploring the complicated possibly chaotic dynamics in pseudoperiodic time series. Two methods [Zhang , Phys. Rev. E 73, 016216 (2006); Zhang and Small, Phys. Rev. Lett. 96, 238701 (2006)] have been forwarded to reveal the chaotic temporal and spatial correlations, respectively, among the cycles in the time series. Both these methods treat the cycle as the basic unit and design specific statistics that indicate the presence of chaotic dynamics. In this paper, we verify the validity of these statistics to capture the chaotic correlation among cycles by using the surrogate data method. In particular, the statistics computed for the original time series are compared with those from its surrogates. The surrogate data we generate is pseudoperiodic type (PPS), which preserves the inherent periodic components while destroying the subtle nonlinear (chaotic) structure. Since the inherent chaotic correlations among cycles, either spatial or temporal (which are suitably characterized by the proposed statistics), are eliminated through the surrogate generation process, we expect the statistics from the surrogate to take significantly different values than those from the original time series. Hence the ability of the statistics to capture the chaotic correlation in the time series can be validated. Application of this procedure to both chaotic time series and real world data clearly demonstrates the effectiveness of the statistics. We have found clear evidence of chaotic correlations among cycles in human electrocardiogram and vowel time series. Furthermore, we show that this framework is more sensitive to examine the subtle changes in the dynamics of the time series due to the match between PPS surrogate and the statistics adopted. It offers a more reliable tool to reveal the possible correlations among cycles intrinsic to the chaotic nature of the pseudoperiodic time series.

  2. 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.

  3. A SAR ATR algorithm based on coherent change detection

    SciTech Connect

    Harmony, D.W.

    2000-12-01

    This report discusses an automatic target recognition (ATR) algorithm for synthetic aperture radar (SAR) imagery that is based on coherent change detection techniques. The algorithm relies on templates created from training data to identify targets. Objects are identified or rejected as targets by comparing their SAR signatures with templates using the same complex correlation scheme developed for coherent change detection. Preliminary results are presented in addition to future recommendations.

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

    DOE PAGESBeta

    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

  5. 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.

  6. Flow detection of propagating waves with temporospatial correlation of activity

    PubMed Central

    Takagaki, Kentaroh; Zhang, Chuan; Wu, Jian-Young; Ohl, Frank W.

    2011-01-01

    Voltage-sensitive dye imaging (VSDI) allows population patterns of cortical activity to be recorded with high temporal resolution, and recent findings ascribe potential significance to their spatial propagation patterns—both for normal cortical processing and in pathologies such as epilepsy. However, analysis of these spatiotemporal patterns has been mostly qualitative to date. In this report, we describe an algorithm to quantify fast local flow patterns of cortical population activation, as measured with VSDI. The algorithm uses correlation of temporal features across space, and therefore differs from conventional optical flow algorithms which use correlation of spatial features over time. This alternative approach allows us to take advantage of the characteristics of fast optical imaging data, which have very high temporal resolution but less spatial resolution. We verify the method both on artificial and biological data, and demonstrate its use. PMID:21664934

  7. Canonical Correlation Analysis for Gene-Based Pleiotropy Discovery

    PubMed Central

    Seoane, Jose A.; Campbell, Colin; Day, Ian N. M.; Casas, Juan P.; Gaunt, Tom R.

    2014-01-01

    Genome-wide association studies have identified a wealth of genetic variants involved in complex traits and multifactorial diseases. There is now considerable interest in testing variants for association with multiple phenotypes (pleiotropy) and for testing multiple variants for association with a single phenotype (gene-based association tests). Such approaches can increase statistical power by combining evidence for association over multiple phenotypes or genetic variants respectively. Canonical Correlation Analysis (CCA) measures the correlation between two sets of multidimensional variables, and thus offers the potential to combine these two approaches. To apply CCA, we must restrict the number of attributes relative to the number of samples. Hence we consider modules of genetic variation that can comprise a gene, a pathway or another biologically relevant grouping, and/or a set of phenotypes. In order to do this, we use an attribute selection strategy based on a binary genetic algorithm. Applied to a UK-based prospective cohort study of 4286 women (the British Women's Heart and Health Study), we find improved statistical power in the detection of previously reported genetic associations, and identify a number of novel pleiotropic associations between genetic variants and phenotypes. New discoveries include gene-based association of NSF with triglyceride levels and several genes (ACSM3, ERI2, IL18RAP, IL23RAP and NRG1) with left ventricular hypertrophy phenotypes. In multiple-phenotype analyses we find association of NRG1 with left ventricular hypertrophy phenotypes, fibrinogen and urea and pleiotropic relationships of F7 and F10 with Factor VII, Factor IX and cholesterol levels. PMID:25329069

  8. Canonical correlation analysis for gene-based pleiotropy discovery.

    PubMed

    Seoane, Jose A; Campbell, Colin; Day, Ian N M; Casas, Juan P; Gaunt, Tom R

    2014-10-01

    Genome-wide association studies have identified a wealth of genetic variants involved in complex traits and multifactorial diseases. There is now considerable interest in testing variants for association with multiple phenotypes (pleiotropy) and for testing multiple variants for association with a single phenotype (gene-based association tests). Such approaches can increase statistical power by combining evidence for association over multiple phenotypes or genetic variants respectively. Canonical Correlation Analysis (CCA) measures the correlation between two sets of multidimensional variables, and thus offers the potential to combine these two approaches. To apply CCA, we must restrict the number of attributes relative to the number of samples. Hence we consider modules of genetic variation that can comprise a gene, a pathway or another biologically relevant grouping, and/or a set of phenotypes. In order to do this, we use an attribute selection strategy based on a binary genetic algorithm. Applied to a UK-based prospective cohort study of 4286 women (the British Women's Heart and Health Study), we find improved statistical power in the detection of previously reported genetic associations, and identify a number of novel pleiotropic associations between genetic variants and phenotypes. New discoveries include gene-based association of NSF with triglyceride levels and several genes (ACSM3, ERI2, IL18RAP, IL23RAP and NRG1) with left ventricular hypertrophy phenotypes. In multiple-phenotype analyses we find association of NRG1 with left ventricular hypertrophy phenotypes, fibrinogen and urea and pleiotropic relationships of F7 and F10 with Factor VII, Factor IX and cholesterol levels. PMID:25329069

  9. 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

  10. Large‐Scale Test of Dynamic Correlation Processors: Implications for Correlation‐Based Seismic Pipelines

    DOE PAGESBeta

    Dodge, Douglas A.; Harris, David 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

  11. Shifting-and-Scaling Correlation Based Biclustering Algorithm.

    PubMed

    Ahmed, Hasin Afzal; Mahanta, Priyakshi; Bhattacharyya, Dhruba Kumar; Kalita, Jugal Kumar

    2014-01-01

    The existence of various types of correlations among the expressions of a group of biologically significant genes poses challenges in developing effective methods of gene expression data analysis. The initial focus of computational biologists was to work with only absolute and shifting correlations. However, researchers have found that the ability to handle shifting-and-scaling correlation enables them to extract more biologically relevant and interesting patterns from gene microarray data. In this paper, we introduce an effective shifting-and-scaling correlation measure named Shifting and Scaling Similarity (SSSim), which can detect highly correlated gene pairs in any gene expression data. We also introduce a technique named Intensive Correlation Search (ICS) biclustering algorithm, which uses SSSim to extract biologically significant biclusters from a gene expression data set. The technique performs satisfactorily with a number of benchmarked gene expression data sets when evaluated in terms of functional categories in Gene Ontology database. PMID:26357059

  12. Ghost imaging based on Pearson correlation coefficients

    NASA Astrophysics Data System (ADS)

    Yu, Wen-Kai; Yao, Xu-Ri; Liu, Xue-Feng; Li, Long-Zhen; Zhai, Guang-Jie

    2015-05-01

    Correspondence imaging is a new modality of ghost imaging, which can retrieve a positive/negative image by simple conditional averaging of the reference frames that correspond to relatively large/small values of the total intensity measured at the bucket detector. Here we propose and experimentally demonstrate a more rigorous and general approach in which a ghost image is retrieved by calculating a Pearson correlation coefficient between the bucket detector intensity and the brightness at a given pixel of the reference frames, and at the next pixel, and so on. Furthermore, we theoretically provide a statistical interpretation of these two imaging phenomena, and explain how the error depends on the sample size and what kind of distribution the error obeys. According to our analysis, the image signal-to-noise ratio can be greatly improved and the sampling number reduced by means of our new method. Project supported by the National Key Scientific Instrument and Equipment Development Project of China (Grant No. 2013YQ030595) and the National High Technology Research and Development Program of China (Grant No. 2013AA122902).

  13. 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

  14. 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.

  15. Correlation-based aberration correction in the presence of inoperable elements.

    PubMed

    O'Donnell, M; Engeler, W E

    1992-01-01

    Estimation of phase aberrations using correlation processing between neighboring elements in a phased array is explored in the presence of inoperable elements. Using a CORDIC-based implementation of a complex baseband correlator, inactive elements can be identified simultaneous with correlation processing. Following detection of inoperable elements, a simple rerouting of the adaptive beam former is used to eliminate these elements from correlation analysis. Experimental results on a 3.33-MHz, 64-element array system with four contiguous, inactive elements demonstrate the robustness of the simple rerouting method for accurate phase aberration estimation. PMID:18267685

  16. 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.

  17. 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

  18. 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%.

  19. 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.

  20. 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.

  1. 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.

  2. 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

  3. Correlation Based Hierarchical Clustering in Financial Time Series

    NASA Astrophysics Data System (ADS)

    Micciche', S.; Lillo, F.; Mantegna, R. N.

    2005-09-01

    We review a correlation based clustering procedure applied to a portfolio of assets synchronously traded in a financial market. The portfolio considered consists of the set of 500 highly capitalized stocks traded at the New York Stock Exchange during the time period 1987-1998. We show that meaningful economic information can be extracted from correlation matrices.

  4. Quantum Encryption Protocol Based on Continuous Variable EPR Correlations

    NASA Astrophysics Data System (ADS)

    He, Guang-Qiang; Zeng, Gui-Hua

    2006-07-01

    A quantum encryption protocol based on Gaussian-modulated continuous variable EPR correlations is proposed. The security is guaranteed by continuous variable EPR entanglement correlations produced by nondegenerate optical parametric amplifier (NOPA). For general beam splitter eavesdropping strategy, the mutual information I(α,epsilon) between Alice and Eve is calculated by employing Shannon information theory. Finally the security analysis is presented.

  5. 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.

  6. 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.

  7. Identification of Traceability Barcode Based on Phase Correlation Algorithm

    NASA Astrophysics Data System (ADS)

    Lang, Liying; Zhang, Xiaofang

    In the paper phase correlation algorithm based on Fourier transform is applied to the traceability barcode identification, which is a widely used method of image registration. And there is the rotation-invariant phase correlation algorithm which combines polar coordinate transform with phase correlation, that they can recognize the barcode with partly destroyed and rotated. The paper provides the analysis and simulation for the algorithm using Matlab, the results show that the algorithm has the advantages of good real-time and high performance. And it improves the matching precision and reduces the calculation by optimizing the rotation-invariant phase correlation.

  8. Retinal recognition using compression-based joint transform correlator

    NASA Astrophysics Data System (ADS)

    Suripon, Ubon; Widjaja, Joewono

    2013-06-01

    Retinal recognition by using compression-based joint transform correlator (JTC) is proposed. Recognition performance is quantitatively measured by taking into account effect of imbalanced illuminations and noise presence. The simulation results show that the compression-based JTC has reliable recognition performance for high-contrast retina target. Besides acceleration of image transfer time, the compression of the noise-corrupted retina target images can improve the correlator robustness to noise.

  9. 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

  10. 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

  11. Edge detection based on gradient ghost imaging.

    PubMed

    Liu, Xue-Feng; Yao, Xu-Ri; Lan, Ruo-Ming; Wang, Chao; Zhai, Guang-Jie

    2015-12-28

    We present an experimental demonstration of edge detection based on ghost imaging (GI) in the gradient domain. Through modification of a random light field, gradient GI (GGI) can directly give the edge of an object without needing the original image. As edges of real objects are usually sparser than the original objects, the signal-to-noise ratio (SNR) of the edge detection result will be dramatically enhanced, especially for large-area, high-transmittance objects. In this study, we experimentally perform one- and two-dimensional edge detection with a double-slit based on GI and GGI. The use of GGI improves the SNR significantly in both cases. Gray-scale objects are also studied by the use of simulation. The special advantages of GI will make the edge detection based on GGI be valuable in real applications. PMID:26832041

  12. 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.

  13. 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.

  14. 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.

  15. 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

  16. ENZYME-BASED DETECTION OF CHLORINATED HYDROCARBONS

    EPA Science Inventory

    Recent advances in immobilized enzyme-based analytical methods, e.g., the cholinesterase-based water monitor 'CAM' (cholinesterase antagonsist monitor), have proved useful in the detection of organophosphate and carbamate pesticides. This work has now been extended to the detecti...

  17. Correlating nuclear frequencies by two-dimensional ELDOR-detected NMR spectroscopy

    NASA Astrophysics Data System (ADS)

    Kaminker, Ilia; Wilson, Tiffany D.; Savelieff, Masha G.; Hovav, Yonatan; Zimmermann, Herbert; Lu, Yi; Goldfarb, Daniella

    2014-03-01

    ELDOR (Electron Double Resonance)-detected NMR (EDNMR) is a pulse EPR experiment that is used to measure the transition frequencies of nuclear spins coupled to electron spins. These frequencies are further used to determine hyperfine and quadrupolar couplings, which are signatures of the electronic and spatial structures of paramagnetic centers. In recent years, EDNMR has been shown to be particularly useful at high fields/high frequencies, such as W-band (∼95 GHz, ∼3.5 T), for low γ quadrupolar nuclei. Although at high fields the nuclear Larmor frequencies are usually well resolved, the limited resolution of EDNMR still remains a major concern. In this work we introduce a two dimensional, triple resonance, correlation experiment based on the EDNMR pulse sequence, which we term 2D-EDNMR. This experiment allows circumventing the resolution limitation by spreading the signals in two dimensions and the observed correlations help in the assignment of the signals. First we demonstrate the utility of the 2D-EDNMR experiment on a nitroxide spin label, where we observe correlations between 14N nuclear frequencies. Negative cross-peaks appear between lines belonging to different MS electron spin manifolds. We resolved two independent correlation patterns for nuclear frequencies arising from the EPR transitions corresponding to the 14N mI = 0 and mI = -1 nuclear spin states, which severely overlap in the one dimensional EDNMR spectrum. The observed correlations could be accounted for by considering changes in the populations of energy levels that S = 1/2, I = 1 spin systems undergo during the pulse sequence. In addition to these negative cross-peaks, positive cross-peaks appear as well. We present a theoretical model based on the Liouville equation and use it to calculate the time evolution of populations of the various energy levels during the 2D-EDNMR experiment and generated simulated 2D-EDMR spectra. These calculations show that the positive cross-peaks appear due

  18. Correlating nuclear frequencies by two-dimensional ELDOR-detected NMR spectroscopy.

    PubMed

    Kaminker, Ilia; Wilson, Tiffany D; Savelieff, Masha G; Hovav, Yonatan; Zimmermann, Herbert; Lu, Yi; Goldfarb, Daniella

    2014-03-01

    ELDOR (Electron Double Resonance)-detected NMR (EDNMR) is a pulse EPR experiment that is used to measure the transition frequencies of nuclear spins coupled to electron spins. These frequencies are further used to determine hyperfine and quadrupolar couplings, which are signatures of the electronic and spatial structures of paramagnetic centers. In recent years, EDNMR has been shown to be particularly useful at high fields/high frequencies, such as W-band (∼95 GHz, ∼3.5 T), for low γ quadrupolar nuclei. Although at high fields the nuclear Larmor frequencies are usually well resolved, the limited resolution of EDNMR still remains a major concern. In this work we introduce a two dimensional, triple resonance, correlation experiment based on the EDNMR pulse sequence, which we term 2D-EDNMR. This experiment allows circumventing the resolution limitation by spreading the signals in two dimensions and the observed correlations help in the assignment of the signals. First we demonstrate the utility of the 2D-EDNMR experiment on a nitroxide spin label, where we observe correlations between (14)N nuclear frequencies. Negative cross-peaks appear between lines belonging to different MS electron spin manifolds. We resolved two independent correlation patterns for nuclear frequencies arising from the EPR transitions corresponding to the (14)N mI=0 and mI=-1 nuclear spin states, which severely overlap in the one dimensional EDNMR spectrum. The observed correlations could be accounted for by considering changes in the populations of energy levels that S=1/2, I=1 spin systems undergo during the pulse sequence. In addition to these negative cross-peaks, positive cross-peaks appear as well. We present a theoretical model based on the Liouville equation and use it to calculate the time evolution of populations of the various energy levels during the 2D-EDNMR experiment and generated simulated 2D-EDMR spectra. These calculations show that the positive cross-peaks appear due to

  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. Driver fatigue detection system based on DSP

    NASA Astrophysics Data System (ADS)

    Wang, Qian; Yu, Fu liang; Song, Lixin

    2012-01-01

    To detect driver fatigue states effectively and in real time, a driver fatigue detection system was built, which take ICETEK-DM6347 module as system core, near-infrared LED as light source, and CCD camera as picture gathering device. An improved PER-NORFACE detection method combined several simple and efficient image processing algorithms was proposed, which based on principle of PERCLOS method and take the human face location as the main detection target. To ensure the ability of real-time processing, the algorithms on the DM6437 DaVinci processor were optimized. Experiments show that the system could complete the driver fatigue states detection accurately and in real time.

  1. Automatic tremor detection with a combined cross-correlation and neural network approach

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

    Low-amplitude, long-duration, and ambiguous phase arrivals associated with crustal tremor make automatic detection difficult. We present a new detection method that combines cross-correlation with a neural network clustering algorithm. The approach is independent of any a priori assumptions regarding tremor event duration; instead, it examines frequency content, amplitude, and motion products of continuous data to distinguish tremor from earthquakes and background noise in an automated fashion. Because no assumptions regarding event duration are required, the clustering algorithm is therefore able to detect short, burst-like events which may be missed by many current methods. We detect roughly 130 seismic events occurring over 100 minutes, including earthquakes and tremor, in a three-week long test data set of waveforms recorded near Cholame, California. The detection has a success rate of over 90% when compared to visually selected events. We use continuous broadband data from 13 STS-2 seismometers deployed from May 2010 to July 2011 along the Cholame segment of the San Andreas Fault, as well as stations from the HRSN network. The large volume of waveforms requires first reducing the amount of data before applying the neural network algorithm. First, we filter the data between 2 Hz and 8 Hz, calculate envelopes, and decimate them to 0.2 Hz. We cross-correlate signals at each station with two master stations using a moving 520-second time window with a 5-sec time step. We calculate a mean cross-correlation coefficient value between all station pairs for each time window and each master station, and select the master station with the highest mean value. Time windows with mean coefficients exceeding 0.3 are used in the neural network approach, and windows separated by less than 300 seconds are grouped together. In the second step, we apply the neural network algorithm, i.e., Self Organized Map (SOM), to classify the reduced data set. We first calculate feature

  2. Correlated digital back propagation based on perturbation theory.

    PubMed

    Liang, Xiaojun; Kumar, Shiva

    2015-06-01

    We studied a simplified digital back propagation (DBP) scheme by including the correlation between neighboring signal samples. An analytical expression for calculating the correlation coefficients is derived based on a perturbation theory. In each propagation step, nonlinear distortion due to phase-dependent terms in the perturbative expansion are ignored which enhances the computational efficiency. The performance of the correlated DBP is evaluated by simulating a single-channel single-polarization fiber-optic system operating at 28 Gbaud, 32-quadrature amplitude modulation (32-QAM), and 40 × 80 km transmission distance. As compared to standard DBP, correlated DBP reduces the total number of propagation steps by a factor of 10 without performance penalty. Correlated DBP with only 2 steps per link provides about one dB improvement in Q-factor over linear compensation. PMID:26072825

  3. 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.

  4. 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.

  5. [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

  6. 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.

  7. Optical-Correlator Neural Network Based On Neocognitron

    NASA Technical Reports Server (NTRS)

    Chao, Tien-Hsin; Stoner, William W.

    1994-01-01

    Multichannel optical correlator implements shift-invariant, high-discrimination pattern-recognizing neural network based on paradigm of neocognitron. Selected as basic building block of this neural network because invariance under shifts is inherent advantage of Fourier optics included in optical correlators in general. Neocognitron is conceptual electronic neural-network model for recognition of visual patterns. Multilayer processing achieved by iteratively feeding back output of feature correlator to input spatial light modulator and updating Fourier filters. Neural network trained by use of characteristic features extracted from target images. Multichannel implementation enables parallel processing of large number of selected features.

  8. 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.

  9. On event-based optical flow detection

    PubMed Central

    Brosch, Tobias; Tschechne, Stephan; Neumann, Heiko

    2015-01-01

    Event-based sensing, i.e., the asynchronous detection of luminance changes, promises low-energy, high dynamic range, and sparse sensing. This stands in contrast to whole image frame-wise acquisition by standard cameras. Here, we systematically investigate the implications of event-based sensing in the context of visual motion, or flow, estimation. Starting from a common theoretical foundation, we discuss different principal approaches for optical flow detection ranging from gradient-based methods over plane-fitting to filter based methods and identify strengths and weaknesses of each class. Gradient-based methods for local motion integration are shown to suffer from the sparse encoding in address-event representations (AER). Approaches exploiting the local plane like structure of the event cloud, on the other hand, are shown to be well suited. Within this class, filter based approaches are shown to define a proper detection scheme which can also deal with the problem of representing multiple motions at a single location (motion transparency). A novel biologically inspired efficient motion detector is proposed, analyzed and experimentally validated. Furthermore, a stage of surround normalization is incorporated. Together with the filtering this defines a canonical circuit for motion feature detection. The theoretical analysis shows that such an integrated circuit reduces motion ambiguity in addition to decorrelating the representation of motion related activations. PMID:25941470

  10. Vector correlation technique for pixel-wise detection of collagen fiber realignment during injurious tensile loading.

    PubMed

    Quinn, Kyle P; Winkelstein, Beth A

    2009-01-01

    Excessive soft tissue loading can produce adverse structural and physiological changes in the absence of any visible tissue rupture. However, image-based analysis techniques to assess microstructural changes during loading without any visible rupture remain undeveloped. Quantitative polarized light imaging (QPLI) can generate spatial maps of collagen fiber alignment during loading with high temporal resolution and can provide a useful technique to measure microstructural responses. While collagen fibers normally realign in the direction that tissue is loaded, rapid, atypical fiber realignment during loading may be associated with the response of a local collagenous network to fiber failure. A vector correlation technique was developed to detect this atypical fiber realignment using QPLI and mechanical data collected from human facet capsular ligaments (n=16) loaded until visible rupture. Initial detection of anomalous realignment coincided with a measurable decrease in the tissue stiffness in every specimen and occurred at significantly lower strains than those at visible rupture (p<0.004), suggesting this technique may be sensitive to a loss of microstructural integrity. The spatial location of anomalous realignment was significantly associated with regions where visible rupture developed (p<0.001). This analysis technique provides a foundation to identify regional differences in soft tissue injury tolerances and relevant mechanical thresholds. PMID:19895112

  11. 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.

  12. 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

  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. The role of envelope statistics in detecting changes in interaural correlation

    PubMed Central

    Goupell, Matthew J.

    2012-01-01

    The role of envelope statistics in binaural masking-level differences (BMLDs) and correlation change detection was investigated in normal-hearing listeners. Thresholds and just-noticeable differences (JNDs) were measured for different bandwidths and center frequencies (500, 2000, 4000, and 8000 Hz) using Gaussian noises (GNs) and low-fluctuation noises (LFNs). At a 500-Hz center frequency, GN NoSo thresholds were higher than, NoSπ thresholds were lower than, and correlation change detection JNDs were the same as LFN thresholds and JNDs. At higher center frequencies, GN NoSπ thresholds were the same or higher than LFN thresholds and GN correlation change detection JNDs were much smaller than LFN JNDs. Using a pulsed sine vocoder, a second experiment was performed to investigate if binaural adaptation might contribute to the difference in GN and LFN detection. There was no effect of pulse rate, thus providing no clear evidence that binaural adaptation plays a role in these tasks. Both a cross-correlation model and a model that utilized the fluctuations in the interaural differences could explain a majority of the variance in the LFN correlation change JNDs. PMID:22978885

  15. 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.

  16. 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.

  17. 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.

  18. 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

  19. Detecting Distributed Network Traffic Anomaly with Network-Wide Correlation Analysis

    NASA Astrophysics Data System (ADS)

    Zonglin, Li; Guangmin, Hu; Xingmiao, Yao; Dan, Yang

    2008-12-01

    Distributed network traffic anomaly refers to a traffic abnormal behavior involving many links of a network and caused by the same source (e.g., DDoS attack, worm propagation). The anomaly transiting in a single link might be unnoticeable and hard to detect, while the anomalous aggregation from many links can be prevailing, and does more harm to the networks. Aiming at the similar features of distributed traffic anomaly on many links, this paper proposes a network-wide detection method by performing anomalous correlation analysis of traffic signals' instantaneous parameters. In our method, traffic signals' instantaneous parameters are firstly computed, and their network-wide anomalous space is then extracted via traffic prediction. Finally, an anomaly is detected by a global correlation coefficient of anomalous space. Our evaluation using Abilene traffic traces demonstrates the excellent performance of this approach for distributed traffic anomaly detection.

  20. Low-cost microprocessor-based photon correlator

    NASA Astrophysics Data System (ADS)

    Murthy, N. S.; Choudhary, D. M.

    1983-04-01

    A simple cost-effective microprocessor-based correlator is described which can be used for Gaussian as well as non-Gaussian light sources. Error calculations are presented to show that there is no significant improvement in accuracy by adopting 4-bit word length in preference to 3-bit word length. The instrument can also be used in Raman and Raleigh scattering experiments. A few experimental results are presented bringing out the importance of correlation averaging in S/N enhancement. Some autocorrelograms for fluctuations in the scattered light from polystyrene spheres suspended in water are also presented. The instrument can sample 1500 points and calculate 85 correlations in each scan. All the parameters such as number of samples, number of correlations, number of scans, and the sampling time are user programmable.

  1. 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.

  2. 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.

  3. Predictive classification of correlated targets with application to detection of metastatic cancer using functional CT imaging.

    PubMed

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

    2015-09-01

    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 article, 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. Augmentative communication based on realtime vocal cord vibration detection.

    PubMed

    Falk, Tiago H; Chan, Julie; Duez, Pierre; Teachman, Gail; Chau, Tom

    2010-04-01

    A binary switch based on the detection of periodic vocal cord vibrations is proposed for individuals with multiple and severe disabilities. The system offers three major advantages over existing speech-based access technologies, namely, insensitivity to environment noise, increased robustness against user-generated artifacts such as coughs, and reduced exertion during prolonged usage periods. The proposed system makes use of a dual-axis accelerometer placed noninvasively in proximity of the vocal cords by means of a neckband. Periodic vocal cord vibrations are detected using the normalized cross-correlation function computed from anterior-posterior and superior-inferior accelerometry signals. Experiments with a participant with hypotonic cerebral palsy show the proposed system outperforming a popular commercial sound-based system in terms of sensitivity, task time, and user-perceived exertion. PMID:20071275

  5. [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. PMID:26415436

  6. 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.

  7. 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.

  8. 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.

  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. 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. 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. 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

  13. 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).

  14. 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.

  15. A Web Based Cardiovascular Disease Detection System.

    PubMed

    Alshraideh, Hussam; Otoom, Mwaffaq; Al-Araida, Aseel; Bawaneh, Haneen; Bravo, José

    2015-10-01

    Cardiovascular Disease (CVD) is one of the most catastrophic and life threatening health issue nowadays. Early detection of CVD is an important solution to reduce its devastating effects on health. In this paper, an efficient CVD detection algorithm is identified. The algorithm uses patient demographic data as inputs, along with several ECG signal features extracted automatically through signal processing techniques. Cross-validation results show a 98.29 % accuracy for the decision tree classification algorithm. The algorithm has been integrated into a web based system that can be used at anytime by patients to check their heart health status. At one end of the system is the ECG sensor attached to the patient's body, while at the other end is the detection algorithm. Communication between the two ends is done through an Android application. PMID:26293754

  16. 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.

  17. Regional principal color based saliency detection.

    PubMed

    Lou, Jing; Ren, Mingwu; Wang, Huan

    2014-01-01

    Saliency detection is widely used in many visual applications like image segmentation, object recognition and classification. In this paper, we will introduce a new method to detect salient objects in natural images. The approach is based on a regional principal color contrast modal, which incorporates low-level and medium-level visual cues. The method allows a simple computation of color features and two categories of spatial relationships to a saliency map, achieving higher F-measure rates. At the same time, we present an interpolation approach to evaluate resulting curves, and analyze parameters selection. Our method enables the effective computation of arbitrary resolution images. Experimental results on a saliency database show that our approach produces high quality saliency maps and performs favorably against ten saliency detection algorithms. PMID:25379960

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. SERS-based detection of biomolecules

    NASA Astrophysics Data System (ADS)

    Cialla, Dana; Pollok, Sibyll; Steinbrücker, Carolin; Weber, Karina; Popp, Jürgen

    2014-12-01

    In order to detect biomolecules, different approaches using for instance biological, spectroscopic or imaging techniques are established. Due to the broad variety of these methods, this review is focused on surface enhanced Raman spectroscopy (SERS) as an analytical tool in biomolecule detection. Here, the molecular specificity of Raman spectroscopy is combined with metallic nanoparticles as sensor platform, which enhances the signal intensity by several orders of magnitude. Within this article, the characterization of diverse biomolecules by means of SERS is explained and moreover current application fields are presented. The SERS intensity and as a consequence thereof the reliable detection of the biomolecule of interest is effected by distance, orientation and affinity of the molecule towards the metal surface. Furthermore, the great capability of the SERS technique for cutting-edge applications like pathogen detection and cancer diagnosis is highlighted. We wish to motivate by this comprehensive and critical summary researchers from various scientific background to create their own ideas and schemes for a SERS-based detection and analysis of biomolecules.

  3. 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.

  4. 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

  5. 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. PMID:26245835

  6. 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.

  7. Space target detection in star image based on motion information

    NASA Astrophysics Data System (ADS)

    Zhang, Jian; Ren, Jian-cun; Cheng, Shao-cheng

    2013-08-01

    In order to precisely locate and track space targets, construct targets' kinematic trajectories, a space target detection algorithm in star image based on motion information is researched in this paper. Firstly, Target's SNR is increased based on spatial energy accumulation, and the faint targets can be easily segmented from the background. Then, according to the invariance of stars' relative position in neighboring 2 frames, the control points of star images are extracted. And the global motion parameters can be calculated with the control points in succession. Then, according to the relative position between star points and the control points, stars and potential targets are classified. And then, targets are grossly detected utilizing 3-frames nearest neighboring correlation method, and false targets are filtered with multi-frame back and forth searching method. In the end, all targets in star image sequence are numbered, and targets' trajectories are constructed. Experimental results about 4 groups of real photographed star images are as follows: All targets' trajectories are constructed. The least average SNR detected is 2.99. The least mean motion velocity is 2.47 pixel /frame. The most mean motion velocity is 12.72pixel /frame. The algorithm in this paper can satisfy the space target detection requirements, which include high detection probability, few false alarms and high trajectory locating accuracy, etc..

  8. 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

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. Normalized gradient fields cross-correlation for automated detection of prostate in magnetic resonance images

    NASA Astrophysics Data System (ADS)

    Fotin, Sergei V.; Yin, Yin; Periaswamy, Senthil; Kunz, Justin; Haldankar, Hrishikesh; Muradyan, Naira; Cornud, François; Turkbey, Baris; Choyke, Peter L.

    2012-02-01

    Fully automated prostate segmentation helps to address several problems in prostate cancer diagnosis and treatment: it can assist in objective evaluation of multiparametric MR imagery, provides a prostate contour for MR-ultrasound (or CT) image fusion for computer-assisted image-guided biopsy or therapy planning, may facilitate reporting and enables direct prostate volume calculation. Among the challenges in automated analysis of MR images of the prostate are the variations of overall image intensities across scanners, the presence of nonuniform multiplicative bias field within scans and differences in acquisition setup. Furthermore, images acquired with the presence of an endorectal coil suffer from localized high-intensity artifacts at the posterior part of the prostate. In this work, a three-dimensional method for fast automated prostate detection based on normalized gradient fields cross-correlation, insensitive to intensity variations and coil-induced artifacts, is presented and evaluated. The components of the method, offline template learning and the localization algorithm, are described in detail. The method was validated on a dataset of 522 T2-weighted MR images acquired at the National Cancer Institute, USA that was split in two halves for development and testing. In addition, second dataset of 29 MR exams from Centre d'Imagerie Médicale Tourville, France were used to test the algorithm. The 95% confidence intervals for the mean Euclidean distance between automatically and manually identified prostate centroids were 4.06 +/- 0.33 mm and 3.10 +/- 0.43 mm for the first and second test datasets respectively. Moreover, the algorithm provided the centroid within the true prostate volume in 100% of images from both datasets. Obtained results demonstrate high utility of the detection method for a fully automated prostate segmentation.

  15. Biotoxin detection using cell-based sensors.

    PubMed

    Banerjee, Pratik; Kintzios, Spyridon; Prabhakarpandian, Balabhaskar

    2013-12-01

    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

  16. 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

  17. Modeling of Time-correlated Detection of Fast Neutrons Emitted in Induced SNM Fission

    NASA Astrophysics Data System (ADS)

    Guckes, Amber; Barzilov, Alexander; Richardson, Norman

    Neutron multiplicity methods are widely used in the assay of fissile materials. Fission reactions release multiple neutrons simultaneously. Time-correlated detection of neutrons provides a coincidence signature that is unique to fission,which enables distinguishing it from other events. In general, fission neutrons are fast. Thermal neutron sensors require the moderation of neutrons prior to a detection event; therefore, the neutron's energy and the event's timing information may be distorted, resulting in the wide time windows in the correlation analysis. Fastneutron sensing using scintillators allows shortening the time correlation window. In this study, four EJ-299-33A plastic scintillator detectors with neutron/photon pulse shape discrimination properties were modeled usingthe MCNP6 code. This sensor array was studied for time-correlated detection of fast neutrons emitted inthe induced fission of 239Pu and (α,n) neutron sources. This paper presents the results of computational modeling of arrays of these plastic scintillator sensors as well as3He detectors equipped with a moderator.

  18. Assessing the performance of a motion tracking system based on optical joint transform correlation

    NASA Astrophysics Data System (ADS)

    Elbouz, M.; Alfalou, A.; Brosseau, C.; Ben Haj Yahia, N.; Alam, M. S.

    2015-08-01

    We present an optimized system specially designed for the tracking and recognition of moving subjects in a confined environment (such as an elderly remaining at home). In the first step of our study, we use a VanderLugt correlator (VLC) with an adapted pre-processing treatment of the input plane and a postprocessing of the correlation plane via a nonlinear function allowing us to make a robust decision. The second step is based on an optical joint transform correlation (JTC)-based system (NZ-NL-correlation JTC) for achieving improved detection and tracking of moving persons in a confined space. The proposed system has been found to have significantly superior discrimination and robustness capabilities allowing to detect an unknown target in an input scene and to determine the target's trajectory when this target is in motion. This system offers robust tracking performance of a moving target in several scenarios, such as rotational variation of input faces. Test results obtained using various real life video sequences show that the proposed system is particularly suitable for real-time detection and tracking of moving objects.

  19. Automated image based prominent nucleoli detection

    PubMed Central

    Yap, Choon K.; Kalaw, Emarene M.; Singh, Malay; Chong, Kian T.; Giron, Danilo M.; Huang, Chao-Hui; Cheng, Li; Law, Yan N.; Lee, Hwee Kuan

    2015-01-01

    Introduction: Nucleolar changes in cancer cells are one of the cytologic features important to the tumor pathologist in cancer assessments of tissue biopsies. However, inter-observer variability and the manual approach to this work hamper the accuracy of the assessment by pathologists. In this paper, we propose a computational method for prominent nucleoli pattern detection. Materials and Methods: Thirty-five hematoxylin and eosin stained images were acquired from prostate cancer, breast cancer, renal clear cell cancer and renal papillary cell cancer tissues. Prostate cancer images were used for the development of a computer-based automated prominent nucleoli pattern detector built on a cascade farm. An ensemble of approximately 1000 cascades was constructed by permuting different combinations of classifiers such as support vector machines, eXclusive component analysis, boosting, and logistic regression. The output of cascades was then combined using the RankBoost algorithm. The output of our prominent nucleoli pattern detector is a ranked set of detected image patches of patterns of prominent nucleoli. Results: The mean number of detected prominent nucleoli patterns in the top 100 ranked detected objects was 58 in the prostate cancer dataset, 68 in the breast cancer dataset, 86 in the renal clear cell cancer dataset, and 76 in the renal papillary cell cancer dataset. The proposed cascade farm performs twice as good as the use of a single cascade proposed in the seminal paper by Viola and Jones. For comparison, a naive algorithm that randomly chooses a pixel as a nucleoli pattern would detect five correct patterns in the first 100 ranked objects. Conclusions: Detection of sparse nucleoli patterns in a large background of highly variable tissue patterns is a difficult challenge our method has overcome. This study developed an accurate prominent nucleoli pattern detector with the potential to be used in the clinical settings. PMID:26167383

  20. On the cross correlation function amplitude vector and its application to structural damage detection

    NASA Astrophysics Data System (ADS)

    Yang, Zhichun; Yu, Zhefeng; Sun, Hao

    2007-10-01

    A new approach to detecting structure damage using the cross correlation function amplitude vector (CorV) of the measured vibration responses is proposed. It is verified that under a steady random excitation with specific frequency spectrum, the CorV of a structure only depends on the frequency response function matrix of the structure, and it is also found that the normalized CorV has a specific shape. Thus the damage can be detected and located with the correlation and the relative difference between the CorVs obtained from intact and damaged structures. The Cross Correlation Function Amplitude Vector Assurance Criterion (CVAC) is then defined and can be used to quantify the variation of CorV. It is found that the CVAC decreases monotonously with the increasing of damage factor, which indicates the change of CorV is related to the damage severity. The methods of damage locating with CorV are then proposed and demonstrated by the experiments. Finally, the experiment on detection in the fasteners loosing of an aircraft panel model are presented to illustrate the application of the CorV. The feature of this approach lies in that the CorV is obtained from the time domain vibration responses of the structure under steady random excitation, and it has the advantages of simplicity in calculation and the damage detection, so it is possible that the presented approach applies to the structural health monitoring (SHM) with steady ambient excitations.

  1. PreImplantation factor (PIF) detection in maternal circulation in early pregnancy correlates with live birth (bovine model)

    PubMed Central

    2013-01-01

    Background Early identification of viable pregnancy is paramount for successful reproduction. Detection of specific signals from pre-implantation viable embryos in normal pregnancy circulation would indicate initiation of embryo-maternal interaction and create a continuum to accurately reflect embryo/fetal well-being post-implantation. Viable mammalian embryos secrete PreImplantation Factor (PIF), a biomarker which plays key, multi-targeted roles to promote implantation, trophoblast invasion and modulate maternal innate and adaptive immunity toward acceptance. Anti-PIF monoclonal antibody (mAb-based chemiluminescent ELISA) accurately detects PIF in singly cultured embryos media and its increased levels correlate with embryo development up to the blastocyst stage. Herein reported that PIF levels (ELISA) in early maternal serum correlate with pregnancy outcome. Methods Artificially inseminated (AI) blind-coded Angus cattle (N = 21-23) serum samples (day10,15 & 20 post-AI) with known calf birth were blindly tested, using both non-pregnant heifers (N = 30) and steer serum as negative controls. Assay properties and anti-PIF monoclonal antibody specificity were determined by examining linearity, spike and recovery experiments and testing the antibody against 234 different circulating proteins by microarray. Endogenous PIF was detected using <3 kDa filter separation followed by anti-PIF mAb-based affinity chromatography and confirmed by ELISA and HPLC. PIF expression was established in placenta using anti-PIF mAb-based IHC. Results PIF detects viable pregnancy at day 10 post-AI with 91.3% sensitivity, reaching 100% by day 20 and correlating with live calf birth. All non-pregnant samples were PIF negative. PIF level in pregnant samples was a stringent 3 + SD higher as compared to heifers and steer sera. Assay is linear and spike and recovery data demonstrates lack of serum interference. Anti-PIF mAb is specific and does not interact with circulating proteins

  2. 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.

  3. Advances in neutron based bulk explosive detection

    NASA Astrophysics Data System (ADS)

    Gozani, Tsahi; Strellis, Dan

    2007-08-01

    Neutron based explosive inspection systems can detect a wide variety of national security threats. The inspection is founded on the detection of characteristic gamma rays emitted as the result of neutron interactions with materials. Generally these are gamma rays resulting from thermal neutron capture and inelastic scattering reactions in most materials and fast and thermal neutron fission in fissile (e.g.235U and 239Pu) and fertile (e.g.238U) materials. Cars or trucks laden with explosives, drugs, chemical agents and hazardous materials can be detected. Cargo material classification via its main elements and nuclear materials detection can also be accomplished with such neutron based platforms, when appropriate neutron sources, gamma ray spectroscopy, neutron detectors and suitable decision algorithms are employed. Neutron based techniques can be used in a variety of scenarios and operational modes. They can be used as stand alones for complete scan of objects such as vehicles, or for spot-checks to clear (or validate) alarms indicated by another inspection system such as X-ray radiography. The technologies developed over the last two decades are now being implemented with good results. Further advances have been made over the last few years that increase the sensitivity, applicability and robustness of these systems. The advances range from the synchronous inspection of two sides of vehicles, increasing throughput and sensitivity and reducing imparted dose to the inspected object and its occupants (if any), to taking advantage of the neutron kinetic behavior of cargo to remove systematic errors, reducing background effects and improving fast neutron signals.

  4. 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.

  5. 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.

  6. Temporal correlation measurements of pulsed dual CO2 lidar returns. [for atmospheric pollution detection

    NASA Technical Reports Server (NTRS)

    Menyuk, N.; Killinger, D. K.

    1981-01-01

    A pulsed dual-laser direct-detection differential-absorption lidar DIAL system, operating near 10.6 microns, is used to measure the temporal correlation and statistical properties of backscattered returns from specular and diffuse topographic targets. Results show that atmospheric-turbulence fluctuations can effectively be frozen for pulse separation times on the order of 1-3 msec or less. The diffuse target returns, however, yielded a much lower correlation than that obtained with the specular targets; this being due to uncorrelated system noise effects and different statistics for the two types of target returns.

  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. QRS detection based ECG quality assessment.

    PubMed

    Hayn, Dieter; Jammerbund, Bernhard; Schreier, Günter

    2012-09-01

    Although immediate feedback concerning ECG signal quality during recording is useful, up to now not much literature describing quality measures is available. We have implemented and evaluated four ECG quality measures. Empty lead criterion (A), spike detection criterion (B) and lead crossing point criterion (C) were calculated from basic signal properties. Measure D quantified the robustness of QRS detection when applied to the signal. An advanced Matlab-based algorithm combining all four measures and a simplified algorithm for Android platforms, excluding measure D, were developed. Both algorithms were evaluated by taking part in the Computing in Cardiology Challenge 2011. Each measure's accuracy and computing time was evaluated separately. During the challenge, the advanced algorithm correctly classified 93.3% of the ECGs in the training-set and 91.6 % in the test-set. Scores for the simplified algorithm were 0.834 in event 2 and 0.873 in event 3. Computing time for measure D was almost five times higher than for other measures. Required accuracy levels depend on the application and are related to computing time. While our simplified algorithm may be accurate for real-time feedback during ECG self-recordings, QRS detection based measures can further increase the performance if sufficient computing power is available. PMID:22902864

  9. The technology of forest fire detection based on infrared image

    NASA Astrophysics Data System (ADS)

    Wu, Zhi-guo; Liu, Guo-juan; Wang, Ming-jia; Wang, Suo-jian

    2013-09-01

    According to infrared imaging features of forest fire, we use image processing technology which is conducive to early detection and prevention of forest fires. We use image processing technology based on infrared imaging features of forest fire which is conducive to early detection and prevention of forest fires. In order to the timeliness and accuracy of fire detection, this paper proposes a forest fire detection method based on infrared image technology. We take gray histogram analysis to collected Cruising image. The image which will be detected is segmented by the adaptive dynamic threshold. Then the suspected ignitions are extracted in the image after segmentation. The ignition of forest fire which form image in the infrared image is almost circular. We use the circular degree of suspected ignition as the decision basis of the fire in the infrared image. Through the analysis of position correlation which is the same suspected ignition between adjacent frames, we judge whether there is a fire in the image. In order to verify the effectiveness of the method, we adopt image sequences of forest fire to do experiment. The experimental results show that the proposed algorithm under the conditions of different light conditions and complex backgrounds, which can effectively eliminate distractions and extract the fire target. The accuracy fire detection rate is above 95 percent. All fire can be detected. The method can quickly identify fire flame and high-risk points of early fire. The structure of method is clear and efficient which processing speed is less than 25 frames per second. So it meets the application requirement of real-time processing.

  10. 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.

  11. 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.

  12. 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.

  13. Detecting particle dark matter signatures by cross-correlating γ-ray anisotropies with weak lensing

    NASA Astrophysics Data System (ADS)

    Camera, S.; Fornasa, M.; Fornengo, N.; Regis, M.

    2016-05-01

    The underlying nature of dark matter still represents one of the fundamental questions in contemporary cosmology. Although observations well agree with its description in terms of a new fundamental particle, neither direct nor indirect signatures of its particle nature have been detected so far, despite a strong experimental effort. Similarly, particle accelerators have hitherto failed at producing dark matter particles in collider physics experiments. Here, we illustrate how the cross-correlation between anisotropies in the diffuse γ-ray background and weak gravitational lensing effects represents a novel promising way in the quest of detecting particle dark matter signatures.

  14. 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

  15. Reset tree-based optical fault detection.

    PubMed

    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

  16. [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

  17. Detecting nonuniformity in small welds and solder seams using optical correlation and electronic processing.

    PubMed

    Wagner, J W

    1981-10-15

    Using holographic matched filtering and electronic processing, small variations in surface displacement along the seam of a hermetic microcircuit package can be detected when the seam is stressed. Destructive analysis of a solder-sealed package reveals a strong correlation between optical signal variations and nonuniformity of solder adhesion and wetting along the seam. The technique promises potential application as a means of nondestructively inspecting for flaws in small welded or soldered seams. PMID:20372226

  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

    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.

  20. 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.

  1. 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).

  2. 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.

  3. Analysis on correlation imaging based on fractal interpolation

    NASA Astrophysics Data System (ADS)

    Li, Bailing; Zhang, Wenwen; Chen, Qian; Gu, Guohua

    2015-10-01

    One fractal interpolation algorithm has been discussed in detail and the statistical self-similarity characteristics of light field have been analized in correlated experiment. For the correlation imaging experiment in condition of low sampling frequent, an image analysis approach based on fractal interpolation algorithm is proposed. This approach aims to improve the resolution of original image which contains a fewer number of pixels and highlight the image contour feature which is fuzzy. By using this method, a new model for the light field has been established. For the case of different moments of the intensity in the receiving plane, the local field division also has been established and then the iterated function system based on the experimental data set can be obtained by choosing the appropriate compression ratio under a scientific error estimate. On the basis of the iterative function, an explicit fractal interpolation function expression is given out in this paper. The simulation results show that the correlation image reconstructed by fractal interpolation has good approximations to the original image. The number of pixels of image after interpolation is significantly increased. This method will effectively solve the difficulty of image pixel deficiency and significantly improved the outline of objects in the image. The rate of deviation as the parameter has been adopted in the paper in order to evaluate objectively the effect of the algorithm. To sum up, fractal interpolation method proposed in this paper not only keeps the overall image but also increases the local information of the original image.

  4. Mobile Recommendation Based on Link Community Detection

    PubMed Central

    Zhang, Jianpei; Yang, Jing

    2014-01-01

    Since traditional mobile recommendation systems have difficulty in acquiring complete and accurate user information in mobile networks, the accuracy of recommendation is not high. In order to solve this problem, this paper proposes a novel mobile recommendation algorithm based on link community detection (MRLD). MRLD executes link label diffusion algorithm and maximal extended modularity (EQ) of greedy search to obtain the link community structure, and overlapping nodes belonging analysis (ONBA) is adopted to adjust the overlapping nodes in order to get the more accurate community structure. MRLD is tested on both synthetic and real-world networks, and the experimental results show that our approach is valid and feasible. PMID:25243204

  5. 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.

  6. 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.

  7. Laser-diode-based joint transform correlator for fingerprint identification

    NASA Astrophysics Data System (ADS)

    Lal, Amit K.; Zang, De Yu; Millerd, James E.

    1999-01-01

    A laser-diode-based joint transform correlator (JTC) is reported here for the identification and discrimination of fingerprints. The system employs compact and inexpensive laser diodes as the light sources and a bacteriorhodopsin (BR) film in the Fourier plane, which can record the joint power spectrum without the need for expensive spatial light modulators or CCD cameras. The BR film also introduces nonlinearities in the Fourier plane which can improve JTC performance. In addition, real-time, all-optical programmable spatial filtering is demonstrated to improve the discrimination of the system. We present computer modeling and experimental results of this optical correlator, which shows excellent potential for the identification and discrimination of fingerprints.

  8. 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

  9. 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.

  10. 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

  11. 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.

  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. 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.

  14. Correlation of geophysical factors with results of gravity wave detection experiments

    SciTech Connect

    Sazeeva, N.N.

    1986-04-01

    The possible influence of variations in the daily-average sunspot number (W) and geomagnetic-wave amplitude (Ap) on the detections of gravitational-radiation events (GREs) reported by Brown et al. (1982) for a 440-d period in 1979-1981 is investigated statistically. An era-superposition technique is applied to compare 18 GRE periods and 20 non-GRE periods of 7 d each. Both Ap and W are found to be correlated with the GRE signals (the Ap peaking on the day of the GRE), and a bias toward daylight hours for GRE detection (62 percent of GREs in daylight and 43 percent of those between 10 AM and 2 PM local time) is noted. It is inferred that shielded gravitational-wave antennas may be subject to atmospheric EM noise too weak to be detected with available magnetometers. 10 references.

  15. 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.

  16. Extraction of texture regions using region-based local correlation

    NASA Astrophysics Data System (ADS)

    Seo, Sang Yong; Lim, Chae Whan; Chun, Young Deok; Kim, Nam Chul

    2000-12-01

    We present an efficient algorithm using a region-based texture feature for the extraction of texture regions. The key idea of this algorithm is based on the fact that most of the variations of local correlation coefficients (LCCs) according to different orientations are clearly larger in texture regions than in shade regions. An object image is first segmented into homogeneous regions. The variations of LCCs are next averaged in each segmented region. Based on the averaged variations of LCCs, each region is then classified as a texture or shade region. The threshold for classification is found automatically by an iterative threshold selection technique. In order to evaluate the performance of the proposed algorithm, we use six test images (Lena, Woman, Tank, Jet, Face and Tree) of 256 X 256 8-bit pixels. Experimental results show that the proposed feature suitably extracts the regions that appear visually as texture regions.

  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

    2009-01-01

    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 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. PMID:19956680

  18. 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

  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 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.

  1. 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.

  2. 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.

  3. Mitigating ground-based sensor failures with video motion detection

    NASA Astrophysics Data System (ADS)

    Macior, Robert E.; Knauth, Jonathan P.; Walter, Sharon M.; Evans, Richard

    2008-10-01

    Unattended Ground Sensor (UGS) systems typically employ distributed sensor nodes utilizing seismic, magnetic or passive IR sensing modalities to alarm if activity is present. The use of an imaging component to verify sensor events is beneficial to create actionable intelligence. Integration of the ground-based images with other ISR data requires that the images contain valid activity and are appropriately formatted, such as prescribed by Standard NATO Agreement (STANAG) 4545 or the National Imagery Transmission Format, version 2.1 (NITF 2.1). Ground activity sensors suffer from false alarms due to meteorological or biological activity. The addition of imaging allows the analyst to differentiate valid threats from nuisance alarms. Images are prescreened based on target size and temperature difference relative to the background. The combination of video motion detection based on thermal imaging with seismic, magnetic or passive IR sensing modalities improves data quality through multi-phenomenon combinatorial logic. The ground-based images having a nominally vertical aspect are transformed to the horizontal geospatial domain for exploitation and correlation of UGS imagery with other ISR data and for efficient archive and retrieval purposes. The description of an UGS system utilized and solutions that were developed and implemented during an experiment to correlate and fuse IR still imagery with ground moving target information, forming real-time, actionable, coalition intelligence, are presented.

  4. Track infrared point targets based on projection coefficient templates and non-linear correlation combined with Kalman prediction

    NASA Astrophysics Data System (ADS)

    Liu, Ruiming; Li, Xuelong; Han, Lei; Meng, Jiao

    2013-03-01

    For a long time, tracking IR point targets is a great challenge task. We propose a tracking framework based on template matching combined with Kalman prediction. Firstly, a novel template matching method for detecting infrared point targets is presented. Different from the classic template matching, the projection coefficients obtained from principal component analysis are used as templates and the non-linear correlation coefficient is used to measure the matching degree. The non-linear correlation can capture the higher-order statistics. So the detection performance is improved greatly. Secondly, a framework of tracking point targets, based on the proposed detection method and Kalman prediction, is developed. Kalman prediction reduces the searching region for the detection method and, in turn, the detection method provides the more precise measurement for Kalman prediction. They bring out the best in each other. Results of experiments show that this framework is competent to track infrared point targets.

  5. 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. PMID:26192503

  6. 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

  7. 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...

  8. Multiphoton excitation fluorescence correlation spectroscopy of fluorescent DNA base analogs

    NASA Astrophysics Data System (ADS)

    Katilius, Evaldas; Woodbury, Neal W.

    2004-06-01

    Two- and three-photon excitation was used to investigate the properties of two fluorescent DNA base analogs: 2-aminopurine and 6-methylisoxanthopterin. 2-aminopurine is a widely used fluorescent analog of the DNA base adenine. Three-photon excitation of 2-aminopurine is achievable by using intense femtosecond laser pulses in 850-950 nm spectral region. Interestingly, the three-photon excitation spectrum is blue-shifted relative to the three-times-wavelength single-photon excitation spectrum. The maximum of the absorbance band in the UV is at 305 nm, while the three-photon excitation spectrum has a maximum at around 880 nm. Fluorescence correlation measurements were attempted to evaluate the feasibility of using three-photon excitation of 2-aminopurine for DNA-protein interaction studies. However, due to relatively small three-photon absorption cross-section, a good signal-to-noise fluorescence correlation curves take very long time to obtain. Fluorescence properties of 6-methylisoxanthopterin, the fluorescent analog of guanine, were investigated using two-photon excitation. This molecule has the lowest energy absorption band centered around 350 nm, thus, two-photon excitation is attainable using 700 to 760 nm output of Ti-sapphire laser. The excitation spectrum of this molecule in the infrared well matches the doubled-wavelength single-photon excitation spectrum in the UV. The high fluorescence quantum yield of 6-methylisoxanthopterin allows efficient fluorescence correlation measurements and makes this molecule a very good candidate for using in in vitro DNA-protein interaction studies.

  9. 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

  10. 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