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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

    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.

  19. 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

  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.

    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

  20. 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.

  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 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

  7. 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

  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

    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.

  4. 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.

  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. 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

  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. 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

  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. 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

  2. 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.

  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

    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

  10. 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

  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. 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.

  6. [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

  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. 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.

  10. 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.

  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. 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.

  14. 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.

  15. 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.

  16. 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

  17. 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

  18. Future enhancements to ground-based microburst detection

    NASA Technical Reports Server (NTRS)

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

    1994-01-01

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

  19. 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. 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

  5. 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

  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. 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.

  10. 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.

  11. 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.

  12. 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.

  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. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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

  15. 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

  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. 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.

  7. 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.

  8. 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.

  9. 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

  10. 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

  11. Scene change detection based on multimodal integration

    NASA Astrophysics Data System (ADS)

    Zhu, Yingying; Zhou, Dongru

    2003-09-01

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

  12. 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

  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 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

  10. 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

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

    SciTech Connect

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

    2014-02-01

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

  12. Brain structure correlates of emotion-based rash impulsivity

    PubMed Central

    Muhlert, N.; Lawrence, A.D.

    2015-01-01

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

  13. Quantitative evaluation of the sensitivity of library-based Raman spectral correlation methods.

    PubMed

    Rodriguez, Jason D; Westenberger, Benjamin J; Buhse, Lucinda F; Kauffman, John F

    2011-06-01

    Library-based Raman spectral correlation methods are widely used in surveillance applications in multiple areas including the pharmaceutical industry, where Raman spectroscopy is commonly used in verification screening of incoming raw materials. While these spectral correlation methods are rapid and require little or no sample preparation, their sensitivity to the presence of contaminants has not been adequately evaluated. This is particularly important when dealing with pharmaceutical excipients, which are susceptible to economically motivated adulteration by substances having similar physical/chemical/spectroscopic properties. We report a novel approach to evaluating the sensitivity of library-based Raman spectral correlation methods to contaminants in binary systems using a hit-quality index model. We examine three excipient/contaminant systems, glycerin/diethylene glycol, propylene glycol/diethylene glycol, and lactose/melamine and find that the sensitivity to contaminant for each system is 18%, 32%, and 4%, respectively. These levels are well-correlated to the minimum contaminant composition that can be detected by both verification and identification methods. Our studies indicate that the most important factor that determines the sensitivity of a spectral correlation measurement to the presence of contaminant is the relative Raman scattering cross section of the contaminant. PMID:21548558

  14. On exploiting interbeat correlation in compressive sensing-based ECG compression

    NASA Astrophysics Data System (ADS)

    Polania, Luisa F.; Carrillo, Rafael E.; Blanco-Velasco, Manuel; Barner, Kenneth E.

    2012-06-01

    Compressive Sensing (CS) is an emerging data acquisition scheme with the potential to reduce the number of measurements required by the Nyquist sampling theorem to acquire sparse signals. We recently used the interbeat correlation to find the common support between jointly sparse adjacent heartbeats. In this paper, we fully exploit this correlation to find the magnitude, in addition to the support of the significant coefficients in the sparse domain. The approach used for this purpose is based on sparse Bayesian learning algorithms due to its superior performance compared to other reconstruction algorithms and the fact that being a probabilistic approach facilitates the incorporation of correlation information. The reconstruction includes, in the first place, the detection of the R peaks and the length normalization of ECG cycles to take advantage of the quasi-periodic structure. Since the common support reduces as the number of heartbeats increases, we propose the use of a sliding window where the support maintains approximately constant across cycles. The sparse Bayesian algorithm adaptively learns and exploits the high correlation between the heartbeats in the constructed window. Experimental results show that the proposed method reduces significantly the number of measurements required to achieve good reconstruction quality, validating the potential of using correlation information in compressed sensing-based ECG compression.

  15. Comic image understanding based on polygon detection

    NASA Astrophysics Data System (ADS)

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

    2013-01-01

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

  16. Texture-Based Polyp Detection in Colonoscopy

    NASA Astrophysics Data System (ADS)

    Ameling, Stefan; Wirth, Stephan; Paulus, Dietrich; Lacey, Gerard; Vilarino, Fernando

    Colonoscopy is one of the best methods for screening colon cancer. A variety of research groups have proposed methods for automatic detection of polyps in colonoscopic images to support the doctors during examination. However, the problem can still not be assumed as solved. The major drawback of many approaches is the amount and quality of images used for classifier training and evaluation. Our database consists of more than four hours of high resolution video from colonoscopies which were examined and labeled by medical experts. We applied four methods of texture feature extraction based on Grey-Level-Co-occurence and Local-Binary-Patterns. Using this data, we achieved classification results with an area under the ROC-curve of up to 0.96.

  17. Low complexity pixel-based halftone detection

    NASA Astrophysics Data System (ADS)

    Ok, Jiheon; Han, Seong Wook; Jarno, Mielikainen; Lee, Chulhee

    2011-10-01

    With the rapid advances of the internet and other multimedia technologies, the digital document market has been growing steadily. Since most digital images use halftone technologies, quality degradation occurs when one tries to scan and reprint them. Therefore, it is necessary to extract the halftone areas to produce high quality printing. In this paper, we propose a low complexity pixel-based halftone detection algorithm. For each pixel, we considered a surrounding block. If the block contained any flat background regions, text, thin lines, or continuous or non-homogeneous regions, the pixel was classified as a non-halftone pixel. After excluding those non-halftone pixels, the remaining pixels were considered to be halftone pixels. Finally, documents were classified as pictures or photo documents by calculating the halftone pixel ratio. The proposed algorithm proved to be memory-efficient and required low computation costs. The proposed algorithm was easily implemented using GPU.

  18. Detecting Soft Errors in Stencil based Computations

    SciTech Connect

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

    2015-05-06

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

  19. Detecting different correlation regimes in a 1D Bose gas using in-situ absorption imaging

    NASA Astrophysics Data System (ADS)

    Salces-Carcoba, Francisco; Sugawa, Seiji; Yue, Yuchen; Putra, Andika; Spielman, Ian

    2016-05-01

    We present the realization of a single 1D Bose gas (1DBG) using a tightly focused Laguerre-Gauss beam as a waveguide for a 87Rb cloud. Axial confinement is provided by a weak trap that also sets the final density profile. A homogeneous 1DBG at T = 0 can be fully described by the dimensionless interaction parameter γ ~ 1/n, where n is the linear density; at sufficiently low densities the system becomes strongly interacting. An inhomogeneous (trapped) system can enter this description within the local density approximation (LDA) where the interaction parameter becomes position dependent γ(x) ~ 1/n(x). The system then displays different correlation regimes over its extension which can be detected by measuring its equation of state (EoS) or the density density correlations in real space using in-situ absorption imaging.

  20. Synchronization-based approach for detecting functional activation of brain

    NASA Astrophysics Data System (ADS)

    Hong, Lei; Cai, Shi-Min; Zhang, Jie; Zhuo, Zhao; Fu, Zhong-Qian; Zhou, Pei-Ling

    2012-09-01

    In this paper, we investigate a synchronization-based, data-driven clustering approach for the analysis of functional magnetic resonance imaging (fMRI) data, and specifically for detecting functional activation from fMRI data. We first define a new measure of similarity between all pairs of data points (i.e., time series of voxels) integrating both complete phase synchronization and amplitude correlation. These pairwise similarities are taken as the coupling between a set of Kuramoto oscillators, which in turn evolve according to a nearest-neighbor rule. As the network evolves, similar data points naturally synchronize with each other, and distinct clusters will emerge. The clustering behavior of the interaction network of the coupled oscillators, therefore, mirrors the clustering property of the original multiple time series. The clustered regions whose cross-correlation coefficients are much greater than other regions are considered as the functionally activated brain regions. The analysis of fMRI data in auditory and visual areas shows that the recognized brain functional activations are in complete correspondence with those from the general linear model of statistical parametric mapping, but with a significantly lower time complexity. We further compare our results with those from traditional K-means approach, and find that our new clustering approach can distinguish between different response patterns more accurately and efficiently than the K-means approach, and therefore more suitable in detecting functional activation from event-related experimental fMRI data.

  1. Case-Based Multi-Sensor Intrusion Detection

    NASA Astrophysics Data System (ADS)

    Schwartz, Daniel G.; Long, Jidong

    2009-08-01

    Multi-sensor intrusion detection systems (IDSs) combine the alerts raised by individual IDSs and possibly other kinds of devices such as firewalls and antivirus software. A critical issue in building a multi-sensor IDS is alert-correlation, i.e., determining which alerts are caused by the same attack. This paper explores a novel approach to alert correlation using case-based reasoning (CBR). Each case in the CBR system's library contains a pattern of alerts raised by some known attack type, together with the identity of the attack. Then during run time, the alert streams gleaned from the sensors are compared with the patterns in the cases, and a match indicates that the attack described by that case has occurred. For this purpose the design of a fast and accurate matching algorithm is imperative. Two such algorithms were explored: (i) the well-known Hungarian algorithm, and (ii) an order-preserving matching of our own device. Tests were conducted using the DARPA Grand Challenge Problem attack simulator. These showed that the both matching algorithms are effective in detecting attacks; but the Hungarian algorithm is inefficient; whereas the order-preserving one is very efficient, in fact runs in linear time.

  2. The effects of finite element grid density on model correlation and damage detection of a bridge

    SciTech Connect

    Simmermacher, T.; Mayes, R.L.; Reese, G.M.; James, G.H.; Zimmerman, D.C.

    1995-12-31

    Variation of model size as determined by grid density is studied for both model refinement and damage detection. In model refinement 3 it is found that a large model with a fine grid is preferable in order to achieve a reasonable correlation between the experimental response and the finite element model. A smaller model falls victim to the inaccuracies of the finite element method. As the grid become increasing finer, the FE method approaches an accurate representation. In damage detection the FE method is only a starting point. The model is refined with a matrix method which doesn`t retain the FE approximation, therefore a smaller model that captures most of the dynamics of the structure can be used and is preferable.

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

    PubMed

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

    2007-10-01

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

  4. Digital image correlation-based optical coherence elastography

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  5. Digital image correlation-based optical coherence elastography.

    PubMed

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

    2013-12-01

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

  6. Application of chaos-based signal processing in the laser underwater target detection system

    SciTech Connect

    Luo, Z.; Lu, Y.; Chen, W.

    1996-12-31

    In this paper, the authors first demonstrate that the signal received from the laser underwater target detection system may be chaotic through phase space reconstruction, correlation dimension analysis and Lyapunov exponent calculation. Then the result of the correlation dimension analysis is used to construct a neural network predictor which is considered as an approximation of the basic dynamics of the received signal. Finally they introduce a chaos-based detection method and apply it to detect the underwater target. The performance of this new method is superior to that of the conventional method.

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

    NASA Astrophysics Data System (ADS)

    Chen, Min; He, Junhua; Chen, Liangyi

    2006-06-01

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

  8. Holographic security system based on image domain joint transform correlator

    NASA Astrophysics Data System (ADS)

    Borisov, Michael; Odinokov, Sergey B.; Bondarev, Leonid A.; Kurakin, Sergey V.; Matveyev, Sergey V.; Belyaev, V. S.

    2002-04-01

    We describe holographic security system providing machine reading of the holographic information and matching it with the reference one by optical means. The security holographic mark includes several test holograms and should be applied to a carrier: ID-card, paper seal etc. Each of the holograms stores a part of entire image, stored in the reference hologram. Image domain JTC is used to match the images retrieved from the holograms. Being recorded and retrieved, the images provides correlation peaks with special positions, with a strict dependence on the tested and reference holograms mutual shifts. The system proposed works like usual JTC with a few useful differences. The image domain recognizing is a result of Fresnel holographic technique of the images recording. It provides more effective usage of the light addressed SLM (LASLM) work pupil and resolution in more simple and compact device. Few correlation peaks enhances the device recognizing probability. We describe the real-time experimental arrangement based on LASLM. The experimental results are in a good correspondence with computer simulations. We also show in practice that good results may be obtained while using the image domain JTC technique in despite of the low LASLM resolution and the device compact size.

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

    PubMed

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

    2015-10-01

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

  10. Color image encryption based on joint fractional Fourier transform correlator

    NASA Astrophysics Data System (ADS)

    Lu, Ding; Jin, Weimin

    2011-06-01

    In this paper, an optical color image encryption/decryption technology based on joint fractional Fourier transform correlator and double random phase encoding (DRPE) is developed. In this method, the joint fractional power spectrum of the image to be encrypted and the key codes is recorded as the encrypted data. Different from the case with classical DRPE, the same key code was used both in the encryption and decryption. The security of the system is enhanced because of the fractional order as a new added key. This method takes full advantage of the parallel processing features of the optical system, and could optically realize single-channel color image encryption. The experimental results indicate that the new method is feasible.

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

    PubMed Central

    Wang, Yue; Wu, Xintao

    2014-01-01

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

  12. Methods of estrus detection and correlates of the reproductive cycle in the sun bear (Helarctos malayanus).

    PubMed

    Frederick, Cheryl; Kyes, Randall; Hunt, Kathleen; Collins, Darin; Durrant, Barbara; Wasser, Samuel K

    2010-10-15

    The objective was to explore multiple methods for detecting and characterizing the reproductive cycle of the sun bear (Helarctos malayanus). Thirteen H. m. euryspilus females, loaned from the Malaysian government to US zoos, were used. Fecal metabolite concentrations of estrogen and progesterone were compared to vaginal cytology, changes in genital appearance, and behavior (videotapes and zookeeper observations). Cytology and video behavior were characterized during five hormonally defined states: high, low, and baseline progesterone, estrus, and high estrogen. Among states, there were significant differences in cytology and behavior. Sexual, affiliative, and stereotypic behaviors were highest during estrus, whereas affiliative and social behaviors were lowest during high progesterone. In this captive breeding population, 30.8% of females cycled two or three times a year, 30.8% cycled once a year, and 38.5% did not cycle during this study. Inter-estrus intervals were (mean ± SEM) 115.7 ± 6.3 d (range, 101-131). Spearman rank correlations were significant between both ordinal sexual and affiliative behaviors and vulva swelling and color. Sexual behavior was significantly positively correlated with superficial and keratinized cells, but negatively correlated with parabasal and basophilic cells in cycling females (opposite pattern for appetitive behavior). In conclusion, data for cytology, vulva changes and behavior were consistent with, and complementary to, hormonal data; collectively, they delineated estrus and identified specific reproductive types. PMID:20688366

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

    NASA Astrophysics Data System (ADS)

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

    2010-02-01

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

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

    SciTech Connect

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

    1998-04-01

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

  15. Intelligent-based Structural Damage Detection Model

    SciTech Connect

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

    2010-05-21

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

  16. Biomimetic visual detection based on insect neurobiology

    NASA Astrophysics Data System (ADS)

    O'Carroll, David C.

    2001-11-01

    With a visual system that accounts for as much as 30% of the lifted mass, flying insects such as dragonflies and hoverflies invest more in vision than any other animal. Impressive visual performance is subserved by a surprisingly simple visual system. In a typical insect eye, between 2,000 and 30,000 pixels in the image are analyzed by fewer than 200,000 neurons in underlying neural circuits. The combination of sophisticated visual processing with an approachable level of complexity has made the insect visual system a leading model for biomimetic approaches to computer vision. Much neurobiological research has focused on neural circuits used for detection of moving patterns (e.g. optical flow during flight) and moving targets (e.g. prey). Research from several labs has led to great advances in our understanding of the neural mechanisms involved, and has spawned neuromorphic hardware based on key processes identified in neurobiological experiments. Despite its attractions, the highly non-linear nature of several key stages in insect visual processing presents a challenge to understanding. I will describe examples of adaptive elements of neural circuits in the fly visual system which analyze the direction and velocity of wide-field optical flow patterns and the result of experiments that suggest that these non-linearities may contribute to robust responses to natural image motion.

  17. Lagrangian based methods for coherent structure detection

    SciTech Connect

    Allshouse, Michael R.; Peacock, Thomas

    2015-09-15

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

  18. Lagrangian based methods for coherent structure detection.

    PubMed

    Allshouse, Michael R; Peacock, Thomas

    2015-09-01

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

  19. GIS-based detection of grain boundaries

    NASA Astrophysics Data System (ADS)

    Li, Yingkui; Onasch, Charles M.; Guo, Yonggui

    2008-04-01

    The recognition of grain boundaries in deformed rocks from images of thin-sections or polished slabs is an essential step in describing and quantifying various fabric elements and strain. However, many of the methods in use today require labor-intensive manual digitization of grain boundary information. Here, we propose an automated, GIS-based method to detect grain boundaries and construct a grain boundary database in which the shape, orientation, and spatial distribution of grains can be quantified and analyzed in a reproducible manner. The proposed method includes a series of operations and functions to identify grain boundaries and construct the grain boundary database. These processes are integrated into a GIS model using ArcGIS ModelBuilder; thus, little or no operator intervention is required to perform the entire analysis. The method was evaluated using thin section images taken from three sandstone samples. The results indicate that the proposed method can correctly identify >70% of grains recognized manually without any intervention and is especially suitable for analyses where large numbers of grains are required.

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

    NASA Astrophysics Data System (ADS)

    Kitov, Ivan; Sanina, Irina

    2016-04-01

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

  1. Attribute-Based Time Series Cross-Correlation Measures

    NASA Astrophysics Data System (ADS)

    Cooper, G. R. J.

    2016-05-01

    Datasets are usually compared using cross-correlation, often using a moving window to calculate the correlation as a function of time or space. However, signals can be considered as being composed of sinusoids which possess amplitudes, frequencies and phases. All these three attributes can be computed at each point in time, and then used as the basis of a cross-correlation method. By using all the three measures of correlation together, their individual disadvantages can be minimised. By combining these measures with the continuous wavelet transform, information on the correlation as a function of wavelength can be obtained.

  2. Prevalence, Detection and Correlates of PTSD in the Primary Care Setting: A Systematic Review.

    PubMed

    Greene, Talya; Neria, Yuval; Gross, Raz

    2016-06-01

    Research suggests that posttraumatic stress disorder (PTSD) is common, debilitating and frequently associated with comorbid health conditions, including poor functioning, and increased health care utilization. This article systematically reviewed the empirical literature on PTSD in primary care settings, focusing on prevalence, detection and correlates. Twenty-seven studies were identified for inclusion. Current PTSD prevalence in primary care patients ranged widely between 2 % to 39 %, with significant heterogeneity in estimates explained by samples with different levels of trauma exposure. Six studies found detection of PTSD by primary care physicians (PCPs) ranged from 0 % to 52 %. Studies examining associations between PTSD and sociodemographic variables yielded equivocal results. High comorbidity was reported between PTSD and other psychiatric disorders including depression and anxiety, and PTSD was associated with functional impairment or disability. Exposure to multiple types of trauma also raised the risk of PTSD. While some studies indicated that primary care patients with PTSD report higher levels of substance and alcohol abuse, somatic symptoms, pain, health complaints, and healthcare utilization, other studies did not find these associations. This review proposes that primary care settings are important for the early detection of PTSD, which can be improved through indicated screening and PCP education. PMID:26868222

  3. Detection of Satellite Attitude Jitter Based on Image Processing

    NASA Astrophysics Data System (ADS)

    Liu, S.; Tong, X.; Ye, Z.; Tang, X.; Xu, Y.; Li, L.; Wang, F.; Xie, H.; Xie, J.; Li, T.

    2014-12-01

    High-resolution satellite imageries (HRSIs) always suffer from mechanical vibration during scan, resulting in attitude jitter and non-ignorable errors in geo-positioning and mapping. Therefore, it is critical to detect and estimate the attitude jitter for further possible compensation to explore the full geometric potential of HRSI. We bring up with a solution to detect the attitude jitter effect based on image processing using images recorded by a sensor system with parallax observation. Three methods of attitude jitter detection are investigated. The first one is based on analysis of the co-registration errors between images with very small parallax observation (e.g. different bands of multispectral image). The second one is based on stereo images using sensor imaging models to investigate the geometric inconsistance in image space. The third one is based on analysis of the co-registration errors of two DOM products from the images. Phase correlation, geometric constraint cross correlation and least squares matching are used in our methods correspondingly for high accuracy image matching, and the RANSAC algorithm is adopted to remove mismatched points and outliers. Finally, the image disparities from each method are used to investigate the effect and characteristic of satellite attitude jitter. We applied our methods on different satellites to investigate their attitude jitter characteristics. Results of experiment with multispectral images obtained by the ASTER camera equipped on Terra satellite showed that there exist more than one frequency with amplitude up to 0.3 pixel. Experimental results with panchromatic image strips captured by LROC revealed that there exist at least two attitude jitter frequencies with amplitude up to 0.6 pixel. Three methods were all used to investigate the attitude jitter of Chinese ZY-3 satellite and the results from different methods showed good consistency, and a distinct periodic attitude fluctuation with frequency around 0.65Hz

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

    PubMed

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

    2015-10-01

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

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed Central

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

    2011-01-01

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

  7. Correlation of dual colour single particle trajectories for improved detection and analysis of interactions in living cells.

    PubMed

    Deschout, Hendrik; Martens, Thomas; Vercauteren, Dries; Remaut, Katrien; Demeester, Jo; De Smedt, Stefaan C; Neyts, Kristiaan; Braeckmans, Kevin

    2013-01-01

    Interactions between objects inside living cells are often investigated by looking for colocalization between fluorescence microscopy images that are recorded in separate colours corresponding to the fluorescent label of each object. The fundamental limitation of this approach in the case of dynamic objects is that coincidental colocalization cannot be distinguished from true interaction. Instead, correlation between motion trajectories obtained by dual colour single particle tracking provides a much stronger indication of interaction. However, frequently occurring phenomena in living cells, such as immobile phases or transient interactions, can limit the correlation to small parts of the trajectories. The method presented here, developed for the detection of interaction, is based on the correlation inside a window that is scanned along the trajectories, covering different subsets of the positions. This scanning window method was validated by simulations and, as an experimental proof of concept, it was applied to the investigation of the intracellular trafficking of polymeric gene complexes by endosomes in living retinal pigment epithelium cells, which is of interest to ocular gene therapy. PMID:23965965

  8. Nuclear based techniques for detection of contraband

    SciTech Connect

    Gozani, T.

    1993-12-31

    The detection of contraband such as explosives and drugs concealed in luggage or other container can be quite difficult. Nuclear techniques offer capabilities which are essential to having effective detection devices. This report describes the features of various nuclear techniques and instrumentation.

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2012-01-01

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

  11. Laser-based Sensors for Chemical Detection

    SciTech Connect

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

    2010-05-10

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

  12. Network Anomaly Detection Based on Wavelet Analysis

    NASA Astrophysics Data System (ADS)

    Lu, Wei; Ghorbani, Ali A.

    2008-12-01

    Signal processing techniques have been applied recently for analyzing and detecting network anomalies due to their potential to find novel or unknown intrusions. In this paper, we propose a new network signal modelling technique for detecting network anomalies, combining the wavelet approximation and system identification theory. In order to characterize network traffic behaviors, we present fifteen features and use them as the input signals in our system. We then evaluate our approach with the 1999 DARPA intrusion detection dataset and conduct a comprehensive analysis of the intrusions in the dataset. Evaluation results show that the approach achieves high-detection rates in terms of both attack instances and attack types. Furthermore, we conduct a full day's evaluation in a real large-scale WiFi ISP network where five attack types are successfully detected from over 30 millions flows.

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

    PubMed Central

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

    2016-01-01

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

  14. Testing the waveform correlation event detection system: Teleseismic, regional, and local distances

    SciTech Connect

    Young, C.J.; Beiriger, J.I.; Harris, J.M.

    1997-08-01

    Waveform Correlation Event Detection System (WCEDS) prototypes have now been developed for both global and regional networks and the authors have extensively tested them to assess the potential usefulness of this technology for CTBT (Comprehensive Test Ban Treaty) monitoring. In this paper they present the results of tests on data sets from the IDC (International Data Center) Primary Network and the New Mexico Tech Seismic Network. The data sets span a variety of event types and noise conditions. The results are encouraging at both scales but show particular promise for regional networks. The global system was developed at Sandia Labs and has been tested on data from the IDC Primary Network. The authors have found that for this network the system does not perform at acceptable levels for either detection or location unless directional information (azimuth and slowness) is used. By incorporating directional information, however, both areas can be improved substantially suggesting that WCEDS may be able to offer a global detection capability which could complement that provided by the GA (Global Association) system in use at the IDC and USNDC (United States National Data Center). The local version of WCEDS (LWCEDS) has been developed and tested at New Mexico Tech using data from the New Mexico Tech Seismic Network (NMTSN). Results indicate that the WCEDS technology works well at this scale, despite the fact that the present implementation of LWCEDS does not use directional information. The NMTSN data set is a good test bed for the development of LWCEDS because of a typically large number of observed local phases and near network-wide recording of most local and regional events. Detection levels approach those of trained analysts, and locations are within 3 km of manually determined locations for local events.

  15. Improving seroreactivity-based detection of glioma.

    PubMed

    Ludwig, Nicole; Keller, Andreas; Heisel, Sabrina; Leidinger, Petra; Klein, Veronika; Rheinheimer, Stefanie; Andres, Claudia U; Stephan, Bernhard; Steudel, Wolf-Ingo; Graf, Norbert M; Burgeth, Bernhard; Weickert, Joachim; Lenhof, Hans-Peter; Meese, Eckart

    2009-12-01

    Seroreactivity profiling emerges as valuable technique for minimal invasive cancer detection. Recently, we provided first evidence for the applicability of serum profiling of glioma using a limited number of immunogenic antigens. Here, we screened 57 glioma and 60 healthy sera for autoantibodies against 1827 Escherichia coli expressed clones, including 509 in-frame peptide sequences. By a linear support vector machine approach, we calculated mean specificity, sensitivity, and accuracy of 100 repetitive classifications. We were able to differentiate glioma sera from sera of the healthy controls with a specificity of 90.28%, a sensitivity of 87.31% and an accuracy of 88.84%. We were also able to differentiate World Health Organization grade IV glioma sera from healthy sera with a specificity of 98.45%, a sensitivity of 80.93%, and an accuracy of 92.88%. To rank the antigens according to their information content, we computed the area under the receiver operator characteristic curve value for each clone. Altogether, we found 46 immunogenic clones including 16 in-frame clones that were informative for the classification of glioma sera versus healthy sera. For the separation of glioblastoma versus healthy sera, we found 91 informative clones including 26 in-frame clones. The best-suited in-frame clone for the classification glioma sera versus healthy sera corresponded to the vimentin gene (VIM) that was previously associated with glioma. In the future, autoantibody signatures in glioma not only may prove useful for diagnosis but also offer the prospect for a personalized immune-based therapy. PMID:20019846

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

    NASA Astrophysics Data System (ADS)

    Schulze-Hartung, Tim

    2012-08-01

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

  17. TCSPC based approaches for multiparameter detection in living cells

    NASA Astrophysics Data System (ADS)

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

    2014-03-01

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

  18. Comparison of a Waveform Cross Correlation Detection Method to a Traditional STA/LTA Picker: Application to the Crooked Lake Sequence Near Fox Creek, Alberta

    NASA Astrophysics Data System (ADS)

    Greig, D. W.; Spriggs, N.

    2014-12-01

    based on the probability density function. Finally, we discuss the practicality of implementing waveform cross correlation detection methods to monitor induced seismicity.

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

    NASA Astrophysics Data System (ADS)

    Bhattacharjee, Sudipta; Deb, Debasis

    2016-07-01

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

  20. A non-spectrogram-correlation method of automatically detecting minke whale boings.

    PubMed

    Ou, Hui; Au, Whitlow W L; Oswald, Julie N

    2012-10-01

    This letter introduces an algorithm for automatic detection of minke whale boing sounds. This method searches for frequency features of boings without calculating the continuous spectrogram of the data, thereby reducing computational time. The detector has been tested on 8 h of acoustic data recorded at the Station ALOHA Cabled Observatory in March 2007. This dataset was previously analyzed using the cross-correlation detector of XBAT and was verified by a human listener, as reported in Oswald et al. [(2011). J. Acoust. Soc. Am. 129, 3353-3360]. A comparison of results indicates that the detector introduced here generates fewer false alarms, and it recognizes low-SNR calls that are missed by XBAT. PMID:23039571

  1. Biopolymer-based material used in optical image correlation

    NASA Astrophysics Data System (ADS)

    Mysliwiec, Jaroslaw; Kochalska, Anna; Miniewicz, Andrzej

    2008-04-01

    We investigate the possible application of a modified deoxyribonucleic acid (DNA)-dye system for dynamic processing of optical information, e.g., optical correlation. The system consists of a biopolymeric matrix made of DNA substituted with the cationic surfactant molecule cetyltrimethyl-ammonium chloride (CTMA) and doped with a photochromic Disperse Red 1 dye. Fast dynamics (millisecond range of rise and fall times) of output correlation signal formation was measured in a joint Fourier transform optical correlator experimental setup. Full reversibility of the correlation signal and reproducibility were observed even after long-time exposures.

  2. Optical cross-correlator based on supercontinuum generation

    SciTech Connect

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

    2006-03-20

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

  3. Orbital correlation of space objects based on orbital elements

    NASA Astrophysics Data System (ADS)

    Wang, Xiu-Hong; Li, Jun-Feng; Du, Xin-Peng; Zhang, Xuan

    2016-03-01

    Orbital correlation of space objects is one of the most important elements in space object identification. Using the orbital elements, we provide correlation criteria to determine if objects are coplanar, co-orbital or the same. We analyze the prediction error of the correlation parameters for different orbital types and propose an orbital correlation method for space objects. The method is validated using two line elements and multisatellite launching data. The experimental results show that the proposed method is effective, especially for space objects in near-circular orbits.

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

    NASA Astrophysics Data System (ADS)

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

    2016-07-01

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

  5. CFHTLenS and RCSLenS Cross-Correlation with Planck Lensing Detected in Fourier and Configuration Space

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

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

    PubMed Central

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

    2015-01-01

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

  7. STOCK Market Differences in Correlation-Based Weighted Network

    NASA Astrophysics Data System (ADS)

    Youn, Janghyuk; Lee, Junghoon; Chang, Woojin

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

  8. Application of Canonical Correlation Analysis for Detecting Risk Factors Leading to Recurrence of Breast Cancer

    PubMed Central

    Sadoughi, Farahnaz; Lotfnezhad Afshar, Hadi; Olfatbakhsh, Asiie; Mehrdad, Neda

    2016-01-01

    Background: Advances in treatment options of breast cancer and development of cancer research centers have necessitated the collection of many variables about breast cancer patients. Detection of important variables as predictors and outcomes among them, without applying an appropriate statistical method is a very challenging task. Because of recurrent nature of breast cancer occurring in different time intervals, there are usually more than one variable in the outcome set. For the prevention of this problem that causes multicollinearity, a statistical method named canonical correlation analysis (CCA) is a good solution. Objectives: The purpose of this study was to analyze the data related to breast cancer recurrence of Iranian females using the CCA method to determine important risk factors. Patients and Methods: In this cross-sectional study, data of 584 female patients (mean age of 45.9 years) referred to Breast Cancer Research Center (Tehran, Iran) were analyzed anonymously. SPSS and NORM softwares (2.03) were used for data transformation, running and interpretation of CCA and replacing missing values, respectively. Data were obtained from Breast Cancer Research Center, Tehran, Iran. Results: Analysis showed seven important predictors resulting in breast cancer recurrence in different time periods. Family history and loco-regional recurrence more than 5 years after diagnosis were the most important variables among predictors and outcomes sets, respectively. Conclusions: Canonical correlation analysis can be used as a useful tool for management and preparing of medical data for discovering of knowledge hidden in them. PMID:27231580

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

    DOEpatents

    Craig, William W.; Labov, Simon E.

    2009-06-09

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

  10. 3D Detection, Quantification and Correlation of Slope Failures with Geologic Structure in the Mont Blanc massif

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-03-01

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

  12. A Correlation method for detection short-period perturbations in the ionosphere, from a large network of GPS receivers.

    NASA Astrophysics Data System (ADS)

    Lee, S.; Garrison, J. L.; Haase, J.; Calais, E.

    2006-12-01

    A technique has been developed for detecting small, short period, traveling perturbations in the ionosphere and estimating their propagation speed and direction from ground-based GPS data. These perturbations can result from atmosphere-ionosphere coupling following an earthquake, tsunami, or large human induced disturbances, such as rocket launches or nuclear weapons tests. These disturbances are often, however, observed at times in which no such source can be identified. The correlation method increases the signal to noise ratio of small amplitude signals, allowing the detection of weaker disturbances. Time series of the Integral Electron Content (IEC), generated from many ground-based dual-frequency GPS receivers, are passed through a filter with a pass band of (typically) 3-10 minutes. Cross-correlations between every pair of IEC time-series, from the same GPS satellite, viewed at multiple ground stations, are used to test for the presence of a disturbance, and measure the propagation delay between the two sub-ionosphere points (SIP's) corresponding to each pair of receivers. A two-dimensional plane wave model is fit to the set of delay measurements from all of the time series having correlation powers above a threshold. A change of variables is shown to convert this model to a linear one, allowing the use of linear least squares estimation methods. The inversion of the linear model is found to be very fast, numerically, allowing it to be used to process large data sets efficiently. It could, thus, be applied autonomously to process large GPS datasets efficiently, for statistical studies of the occurrence of these disturbances. A technique is developed to remove the effects of the time-varying satellite motion and to reconstruct the waveform of the disturbance that would have been observed at a fixed station in the ionosphere. Several post-processing tests are derived to test the velocity estimate accuracy and validity. Two weeks of data, one in the summer (5

  13. Vision-based vehicle detection and tracking algorithm design

    NASA Astrophysics Data System (ADS)

    Hwang, Junyeon; Huh, Kunsoo; Lee, Donghwi

    2009-12-01

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

  14. The electrophysiological correlate of saliency: evidence from a figure-detection task.

    PubMed

    Straube, Sirko; Fahle, Manfred

    2010-01-11

    Although figure-ground segregation in a natural environment usually relies on multiple cues, we experience a coherent figure without usually noticing the individual single cues. It is still unclear how various cues interact to achieve this unified percept and whether this interaction depends on task demands. Studies investigating the effect of cue combination on the human EEG are still lacking. In the present study, we combined psychophysics, ERP and time-frequency analysis to investigate the interaction of orientation and spatial frequency as visual cues in a figure detection task. The figure was embedded in a matrix of Gabor elements, and we systematically varied figure saliency by changing the underlying cue configuration. We found a strong correlation between the posterior P2 amplitude and the perceived saliency of the figure: the P2 amplitude decreased with increasing saliency. Analogously, the power of the theta-band decreased for more salient figures. At longer latencies, the posterior P3 component was modulated in amplitude and latency, possibly reflecting increased decision confidence at higher saliencies. In conclusion, when the cue composition (e.g. one or two cues) or cue strength is changed in a figure detection task, first differences in the electrophysiological response reflect the perceived saliency and not directly the underlying cue configuration. PMID:19854163

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

    SciTech Connect

    Pack, Chan-Gi; Ahn, Sang-Gun

    2015-07-31

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

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

    NASA Technical Reports Server (NTRS)

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

    2001-01-01

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

  17. The imprecision of heterozygosity-fitness correlations hinders the detection of inbreeding and inbreeding depression in a threatened species.

    PubMed

    Grueber, Catherine E; Waters, Jonathan M; Jamieson, Ian G

    2011-01-01

    In nonpedigreed wild populations, inbreeding depression is often quantified through the use of heterozygosity-fitness correlations (HFCs), based on molecular estimates of relatedness. Although such correlations are typically interpreted as evidence of inbreeding depression, by assuming that the marker heterozygosity is a proxy for genome-wide heterozygosity, theory predicts that these relationships should be difficult to detect. Until now, the vast majority of empirical research in this area has been performed on generally outbred, nonbottlenecked populations, but differences in population genetic processes may limit extrapolation of results to threatened populations. Here, we present an analysis of HFCs, and their implications for the interpretation of inbreeding, in a free-ranging pedigreed population of a bottlenecked species: the endangered takahe (Porphyrio hochstetteri). Pedigree-based inbreeding depression has already been detected in this species. Using 23 microsatellite loci, we observed only weak evidence of the expected relationship between multilocus heterozygosity and fitness at individual life-history stages (such as survival to hatching and fledging), and parameter estimates were imprecise (had high error). Furthermore, our molecular data set could not accurately predict the inbreeding status of individuals (as 'inbred' or 'outbred', determined from pedigrees), nor could we show that the observed HFCs were the result of genome-wide identity disequilibrium. These results may be attributed to high variance in heterozygosity within inbreeding classes. This study is an empirical example from a free-ranging endangered species, suggesting that even relatively large numbers (>20) of microsatellites may give poor precision for estimating individual genome-wide heterozygosity. We argue that pedigree methods remain the most effective method of quantifying inbreeding in wild populations, particularly those that have gone through severe bottlenecks. PMID

  18. Nanopore-Based Target Sequence Detection

    PubMed Central

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

    2016-01-01

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

  19. Human vision based color edge detection

    NASA Astrophysics Data System (ADS)

    Kim, Ari; Kim, Hong-suk; Park, Seung-ok

    2011-01-01

    Edge detection can be of great importance to image processing in various digital imaging applications such as digital television and camera. Therefore, extracting more accurate edge properties are significantly demanded for achieving a better image understanding. In vector gradient edge detection, absolute difference of RGB values between a center pixel value, and its neighborhood values are usually used, although such a device-dependent color space does not account for human visual characteristics well. The goal of this study is to test a variety of color difference equations and propose the most effective model that can be used for the purpose of color edge detection. Three of synthetic images generated using perceptibility threshold of the human visual system were used for objectively evaluate to 5 color difference equations studied in this paper. A set of 6 complex color images was also used to testing the 5 color difference equations psychophysically. The equations include ΔRGB, ΔE* ab, ΔECMC, CIEDE2000 (ΔE00) and CIECAM02-UCS delta E (ΔECAM-UCS). Consequently, there were not significant performance variations observed between those 5 color difference equations for the purpose of edge detection. However, ΔE00 and ΔECAM-UCS showed slightly higher mean opinion score (MOS) in detected edge information.

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

    SciTech Connect

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

    2013-07-01

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

  1. Biosensor based on Butyrylcholinesterase for Detection of Carbofuran

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  2. Adaptive skin detection based on online training

    NASA Astrophysics Data System (ADS)

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

    2007-11-01

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

  3. Targeted cell detection based on microchannel gating.

    PubMed

    Javanmard, Mehdi; Talasaz, Amirali H; Nemat-Gorgani, Mohsen; Pease, Fabian; Ronaghi, Mostafa; Davis, Ronald W

    2007-01-01

    Currently, microbiological techniques such as culture enrichment and various plating techniques are used for detection of pathogens. These expensive and time consuming methods can take several days. Described below is the design, fabrication, and testing of a rapid and inexpensive sensor, involving the use of microelectrodes in a microchannel, which can be used to detect single bacterial cells electrically (label-free format) in real time. As a proof of principle, we have successfully demonstrated real-time detection of target yeast cells by measuring instantaneous changes in ionic impedance. We have also demonstrated the selectivity of our sensors in responding to target cells while remaining irresponsive to nontarget cells. Using this technique, it can be possible to multiplex an array of these sensors onto a chip and probe a complex mixture for various types of bacterial cells. PMID:19693402

  4. Antibody-based biological toxin detection

    SciTech Connect

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

    1995-12-01

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

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

    SciTech Connect

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

    1993-11-01

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

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

    PubMed

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

    2015-10-15

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

  7. An improved intrusion detection model based on paraconsistent logic

    NASA Astrophysics Data System (ADS)

    Yan, Fei; Zhang, Huanguo; Wang, Lina; Yang, Min

    2005-02-01

    A major difficulty of current intrusion detection model is the attack set cannot be separated from normal set thoroughly. On the basis of paraconsistent logic, an improved intrusion detection model is proposed to solve this problem. We give a proof that the detection model is trivial and discuss the reason of false alerts. A parallel paraconsistent detection algorithm is presented to develop the detection technology based on our model. An experiment using network connection data, which is usually used to evaluate the intrusion detection methods, is given to illustrate the performance of this model. We use one-class supported vector machine (SVM) to train our profiles and use supported vector-clustering (SVC) algorithm to update our detection profiles. Results of the experiment indicate that the detection system based on our model can deal with the uncertain events and reduce the false alerts.

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

    PubMed

    Kleinberg, Bennett; Verschuere, Bruno

    2015-01-01

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

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

    PubMed Central

    Kleinberg, Bennett; Verschuere, Bruno

    2015-01-01

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

  10. Correlation-based Transition Modeling for External Aerodynamic Flows

    NASA Astrophysics Data System (ADS)

    Medida, Shivaji

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

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

    PubMed Central

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

    2014-01-01

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

  12. Eggshell defects detection based on color processing

    NASA Astrophysics Data System (ADS)

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

    2000-03-01

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

  13. Daytime Water Detection Based on Color Variation

    NASA Technical Reports Server (NTRS)

    Rankin, Arturo L.; Matthies, Larry H.

    2010-01-01

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

  14. Vibration-Based Damage Detection in Rotating Machinery

    SciTech Connect

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

    1999-06-28

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

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

    PubMed Central

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

    2014-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

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

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

    PubMed

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

    2016-03-14

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

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

    NASA Astrophysics Data System (ADS)

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

    2007-11-01

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

  19. Neutron Detection with Water Cerenkov Based Detectors

    SciTech Connect

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

    2009-05-13

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

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

    NASA Astrophysics Data System (ADS)

    Chen, Xiaomei; Koenders, Ludger

    2014-04-01

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

  1. A high resolution laser ranging system based on time-correlated single-photon counting technology

    NASA Astrophysics Data System (ADS)

    Yang, Yixin; Wang, Huanqin; Huang, Zhe; Cao, Yangyang; Gui, Huaqiao

    2014-12-01

    Laser ranging has become an important method for both distance measurements and acquisition of threedimensional (3D) images. In this paper, a laser ranging system based on Time-Correlated Single-Photon Counting technology (TCSPC) is developed. A Geiger-mode avalanche photodiode (G-APD), which has the ability of detecting single-photon events, is used to capture the weak light scattered from the long-range target. In order to improve the ranging resolution of TCSPC based measurement system, a high repetition frequency of subnanosecond narrow pulse generator circuit based on the avalanche effect of RF-BJT is designed and applied as the light source. Moreover, some optimized optical light designs have been done to improve the system signal to noise rate (SNR), including using a special aspherical lens as projecting lens, adopting a telephoto camera lens with small view angle and short depth of field before detector. Experimental tests for evaluation of the laser raging system performance are described. As a means of echo signal analysis, three different algorithms have been introduced, in which the cross-correlation algorithm was demonstrated to be the most effective algorithm to determining the round trip time to a target, even based on histograms with a significant amount of background noise photons. It was found that centimeter ranging resolution can be achieved thanks to the use of Time-to-Digital Converter (TDC) with picosecond resolution and the Cross-Correlation algorithm. The proposed laser ranging system has advantages of high range resolution, short response time and simple structure, which was potential applications for 3D object recognition, computer vision, reverse engineering and virtual reality.

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

    NASA Astrophysics Data System (ADS)

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

    2016-08-01

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

  3. Mapping sources of correlation in resting state FMRI, with artifact detection and removal.

    PubMed

    Jo, Hang Joon; Saad, Ziad S; Simmons, W Kyle; Milbury, Lydia A; Cox, Robert W

    2010-08-15

    Many components of resting-state (RS) FMRI show non-random structure that has little to do with neural connectivity but can covary over multiple brain structures. Some of these signals originate in physiology and others are hardware-related. One artifact discussed herein may be caused by defects in the receive coil array or the RF amplifiers powering it. During a scan, this artifact results in small image intensity shifts in parts of the brain imaged by the affected array components. These shifts introduce artifactual correlations in RS time series on the spatial scale of the coil's sensitivity profile, and can markedly bias RS connectivity results. We show that such a transient artifact can be substantially removed from RS time series by using locally formed regressors from white matter tissue. This is particularly important in arrays with larger numbers of coils, which may generate smaller artifact zones. In such a case, brain-wide average noise estimates would fail to capture the artifact. We also examine the anatomical structure of artifactual variance in RS FMRI time series, by identifying sources that contribute to these signals and where in the brain are they manifested. We consider current methods for reducing confounding sources (or noises) and their effects on connectivity maps, and offer an improved approach (ANATICOR) that can also reduce hardware artifacts. The methods described herein are currently available with AFNI, in addition to tools for rapid, interactive generation of seed-based correlation maps at single-subject and group levels. PMID:20420926

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

    PubMed

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

    2009-11-01

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

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

    NASA Astrophysics Data System (ADS)

    Hassebrook, Laurence G.

    2009-04-01

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

  6. Neural Correlates of Familiarity-Based Associative Retrieval

    ERIC Educational Resources Information Center

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

    2010-01-01

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

  7. Clustering and information in correlation based financial networks

    NASA Astrophysics Data System (ADS)

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

    2004-03-01

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

  8. A vehicle detection algorithm based on deep belief network.

    PubMed

    Wang, Hai; Cai, Yingfeng; Chen, Long

    2014-01-01

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

  9. MPEG recompression detection based on block artifacts

    NASA Astrophysics Data System (ADS)

    Luo, Weiqi; Wu, Min; Huang, Jiwu

    2008-02-01

    With sophisticated video editing technologies, it is becoming increasingly easy to tamper digital video without leaving visual clues. One of the common tampering operations on video is to remove some frames and then re-encode the resulting video. In this paper, we propose a new method for detecting this type of tampering by exploring the temporal patterns of the block artifacts in video sequences. We show that MPEG compression introduces different block artifacts into various types of frames and that the strength of the block artifacts as a function over time has a regular pattern for a given group of pictures (GOP) structure. When some frames are removed from an MPEG video file and the file is then recompressed, the block artifacts introduced by the previous compression would remain and affect the average of block artifact strength of the recompressed one in such a way that depends on the number of deleted frames and the type of GOP used previously. We propose a feature curve to reveal the compression history of an MPEG video file with a given GOP structure, and use it as evidence to detect tampering. Experimental results evaluated on common video benchmark clips demonstrate the effectiveness of the proposed method.

  10. Wireless Falling Detection System Based on Community.

    PubMed

    Xia, Yun; Wu, Yanqi; Zhang, Bobo; Li, Zhiyang; He, Nongyue; Li, Song

    2015-06-01

    The elderly are more likely to suffer the aches or pains from the accidental falls, and both the physiology and psychology of patients would subject to a long-term disturbance, especially when the emergency treatment was not given timely and properly. Although many methods and devices have been developed creatively and shown their efficiency in experiments, few of them are suitable for commercial applications routinely. Here, we design a wearable falling detector as a mobile terminal, and utilize the wireless technology to transfer and monitor the activity data of the host in a relatively small community. With the help of the accelerometer sensor and the Google Mapping service, information of the location and the activity data will be send to the remote server for the downstream processing. The experimental result has shown that SA (Sum-vector of all axes) value of 2.5 g is the threshold value to distinguish the falling from other activities. A three-stage detection algorithm was adopted to increase the accuracy of the real alarm, and the accuracy rate of our system was more than 95%. With the further improvement, the falling detecting device which is low-cost, accurate and user-friendly would become more and more common in everyday life. PMID:26369050

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

    USGS Publications Warehouse

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

    2012-01-01

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

  12. A bio-aerosol detection technique based on tryptophan intrinsic fluorescence measurement

    NASA Astrophysics Data System (ADS)

    Cai, Shuyao; Zhang, Pei; Zhu, Linglin; Zhao, Yongkai; Huang, Huijie

    2011-12-01

    Based on the measurement of intrinsic fluorescence, a set of bio-aerosol including virus aerosols detection instrument is developed, with which a method of calibration is proposed using tryptophan as the target. The experimental results show a good linear relationship between the fluorescence voltage of the instrument and the concentration of the tryptophan aerosol. An excellent correlation (R2>=0.99) with the sensitivity of 4000PPL is obtained. The research demonstrates the reliability of the bio-aerosol detection by measuring the content of tryptophan. Further more the feasibility of prejudgment to the species of bio-aerosol particles with the multi-channel fluorescence detection technology is discussed.

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

    NASA Astrophysics Data System (ADS)

    Liu, Shuyang; Zhou, Tao; Jia, Xiaodong

    2014-11-01

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

  14. Sequential Bayesian Detection: A Model-Based Approach

    SciTech Connect

    Sullivan, E J; Candy, J V

    2007-08-13

    Sequential detection theory has been known for a long time evolving in the late 1940's by Wald and followed by Middleton's classic exposition in the 1960's coupled with the concurrent enabling technology of digital computer systems and the development of sequential processors. Its development, when coupled to modern sequential model-based processors, offers a reasonable way to attack physics-based problems. In this chapter, the fundamentals of the sequential detection are reviewed from the Neyman-Pearson theoretical perspective and formulated for both linear and nonlinear (approximate) Gauss-Markov, state-space representations. We review the development of modern sequential detectors and incorporate the sequential model-based processors as an integral part of their solution. Motivated by a wealth of physics-based detection problems, we show how both linear and nonlinear processors can seamlessly be embedded into the sequential detection framework to provide a powerful approach to solving non-stationary detection problems.

  15. Sequential Bayesian Detection: A Model-Based Approach

    SciTech Connect

    Candy, J V

    2008-12-08

    Sequential detection theory has been known for a long time evolving in the late 1940's by Wald and followed by Middleton's classic exposition in the 1960's coupled with the concurrent enabling technology of digital computer systems and the development of sequential processors. Its development, when coupled to modern sequential model-based processors, offers a reasonable way to attack physics-based problems. In this chapter, the fundamentals of the sequential detection are reviewed from the Neyman-Pearson theoretical perspective and formulated for both linear and nonlinear (approximate) Gauss-Markov, state-space representations. We review the development of modern sequential detectors and incorporate the sequential model-based processors as an integral part of their solution. Motivated by a wealth of physics-based detection problems, we show how both linear and nonlinear processors can seamlessly be embedded into the sequential detection framework to provide a powerful approach to solving non-stationary detection problems.

  16. A fast and accurate FPGA based QRS detection system.

    PubMed

    Shukla, Ashish; Macchiarulo, Luca

    2008-01-01

    An accurate Field Programmable Gate Array (FPGA) based ECG Analysis system is described in this paper. The design, based on a popular software based QRS detection algorithm, calculates the threshold value for the next peak detection cycle, from the median of eight previously detected peaks. The hardware design has accuracy in excess of 96% in detecting the beats correctly when tested with a subset of five 30 minute data records obtained from the MIT-BIH Arrhythmia database. The design, implemented using a proprietary design tool (System Generator), is an extension of our previous work and uses 76% resources available in a small-sized FPGA device (Xilinx Spartan xc3s500), has a higher detection accuracy as compared to our previous design and takes almost half the analysis time in comparison to software based approach. PMID:19163797

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

    NASA Astrophysics Data System (ADS)

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

    2009-07-01

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

  18. Laser Spot Detection Based on Reaction Diffusion

    PubMed Central

    Vázquez-Otero, Alejandro; Khikhlukha, Danila; Solano-Altamirano, J. M.; Dormido, Raquel; Duro, Natividad

    2016-01-01

    Center-location of a laser spot is a problem of interest when the laser is used for processing and performing measurements. Measurement quality depends on correctly determining the location of the laser spot. Hence, improving and proposing algorithms for the correct location of the spots are fundamental issues in laser-based measurements. In this paper we introduce a Reaction Diffusion (RD) system as the main computational framework for robustly finding laser spot centers. The method presented is compared with a conventional approach for locating laser spots, and the experimental results indicate that RD-based computation generates reliable and precise solutions. These results confirm the flexibility of the new computational paradigm based on RD systems for addressing problems that can be reduced to a set of geometric operations. PMID:26938537

  19. Laser Spot Detection Based on Reaction Diffusion.

    PubMed

    Vázquez-Otero, Alejandro; Khikhlukha, Danila; Solano-Altamirano, J M; Dormido, Raquel; Duro, Natividad

    2016-01-01

    Center-location of a laser spot is a problem of interest when the laser is used for processing and performing measurements. Measurement quality depends on correctly determining the location of the laser spot. Hence, improving and proposing algorithms for the correct location of the spots are fundamental issues in laser-based measurements. In this paper we introduce a Reaction Diffusion (RD) system as the main computational framework for robustly finding laser spot centers. The method presented is compared with a conventional approach for locating laser spots, and the experimental results indicate that RD-based computation generates reliable and precise solutions. These results confirm the flexibility of the new computational paradigm based on RD systems for addressing problems that can be reduced to a set of geometric operations. PMID:26938537

  20. Research on moving object detection based on frog's eyes

    NASA Astrophysics Data System (ADS)

    Fu, Hongwei; Li, Dongguang; Zhang, Xinyuan

    2008-12-01

    On the basis of object's information processing mechanism with frog's eyes, this paper discussed a bionic detection technology which suitable for object's information processing based on frog's vision. First, the bionics detection theory by imitating frog vision is established, it is an parallel processing mechanism which including pick-up and pretreatment of object's information, parallel separating of digital image, parallel processing, and information synthesis. The computer vision detection system is described to detect moving objects which has special color, special shape, the experiment indicates that it can scheme out the detecting result in the certain interfered background can be detected. A moving objects detection electro-model by imitating biologic vision based on frog's eyes is established, the video simulative signal is digital firstly in this system, then the digital signal is parallel separated by FPGA. IN the parallel processing, the video information can be caught, processed and displayed in the same time, the information fusion is taken by DSP HPI ports, in order to transmit the data which processed by DSP. This system can watch the bigger visual field and get higher image resolution than ordinary monitor systems. In summary, simulative experiments for edge detection of moving object with canny algorithm based on this system indicate that this system can detect the edge of moving objects in real time, the feasibility of bionic model was fully demonstrated in the engineering system, and it laid a solid foundation for the future study of detection technology by imitating biologic vision.

  1. Real-Time Optical Correlator Based On GaAs

    NASA Technical Reports Server (NTRS)

    Liu, Tsuen-Hsi; Cheng, Li-Jen

    1992-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-09-01

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

  3. Special Nuclear Material Detection with a Water Cherenkov based Detector

    SciTech Connect

    Sweany, M; Bernstein, A; Bowden, N; Dazeley, S; Svoboda, R

    2008-11-10

    Fission events from Special Nuclear Material (SNM), such as highly enriched uranium or plutonium, produce a number of neutrons and high energy gamma-rays. Assuming the neutron multiplicity is approximately Poissonian with an average of 2 to 3, the observation of time correlations between these particles from a cargo container would constitute a robust signature of the presence of SNM inside. However, in order to be sensitive to the multiplicity, one would require a high total efficiency. There are two approaches to maximize the total efficiency; maximizing the detector efficiency or maximizing the detector solid angle coverage. The advanced detector group at LLNL is investigating one way to maximize the detector size. We are designing and building a water Cerenkov based gamma and neutron detector for the purpose of developing an efficient and cost effective way to deploy a large solid angle car wash style detector. We report on our progress in constructing a larger detector and also present preliminary results from our prototype detector that indicates detection of neutrons.

  4. Experiments on Adaptive Techniques for Host-Based Intrusion Detection

    SciTech Connect

    DRAELOS, TIMOTHY J.; COLLINS, MICHAEL J.; DUGGAN, DAVID P.; THOMAS, EDWARD V.; WUNSCH, DONALD

    2001-09-01

    This research explores four experiments of adaptive host-based intrusion detection (ID) techniques in an attempt to develop systems that can detect novel exploits. The technique considered to have the most potential is adaptive critic designs (ACDs) because of their utilization of reinforcement learning, which allows learning exploits that are difficult to pinpoint in sensor data. Preliminary results of ID using an ACD, an Elman recurrent neural network, and a statistical anomaly detection technique demonstrate an ability to learn to distinguish between clean and exploit data. We used the Solaris Basic Security Module (BSM) as a data source and performed considerable preprocessing on the raw data. A detection approach called generalized signature-based ID is recommended as a middle ground between signature-based ID, which has an inability to detect novel exploits, and anomaly detection, which detects too many events including events that are not exploits. The primary results of the ID experiments demonstrate the use of custom data for generalized signature-based intrusion detection and the ability of neural network-based systems to learn in this application environment.

  5. The detection and location of low magnitude earthquakes in northern Norway using multi-channel waveform correlation at regional distances

    NASA Astrophysics Data System (ADS)

    Gibbons, Steven J.; Bøttger Sørensen, Mathilde; Harris, David B.; Ringdal, Frode

    2007-03-01

    A fortuitous sequence of closely spaced earthquakes in the Rana region of northern Norway, during 2005, has provided an ideal natural laboratory for investigating event detectability using waveform correlation over networks and arrays at regional distances. A small number of events between magnitude 2.0 and 3.5 were recorded with a high SNR by the Fennoscandian IMS seismic arrays at distances over 600 km and three of these events, including the largest on 24 June, displayed remarkable waveform similarity even at relatively high frequencies. In an effort to detect occurrences of smaller earthquakes in the immediate geographical vicinity of the 24 June event, a multi-channel correlation detector for the NORSAR array was run for the whole calender year 2005 using the signal from the master event as a template. A total of 32 detections were made and all but 2 of these coincided with independent correlation detections using the other Nordic IMS array stations; very few correspond to signals detectable using traditional energy detectors. Permanent and temporary stations of the Norwegian National Seismic Network (NNSN) at far closer epicentral distances have confirmed that all but one of the correlation detections at NORSAR in fact correspond to real events. The closest stations at distances of approximately 10 km can confirm that the smallest of these events have magnitudes down to 0.5 which represents a detection threshold reduction of over 1.5 for the large-aperture NORSAR array and over 1.0 for the almost equidistant regional ARCES array. The incompleteness of the local network recordings precludes a comprehensive double-difference location for the full set of events. However, stable double-difference relative locations can be obtained for eight of the events using only the Lg phase recorded at the array stations. All events appear to be separated by less than 0.5 km. Clear peaks were observed in the NORSAR correlation coefficient traces during the coda of some of the

  6. Accelerator based techniques for contraband detection

    NASA Astrophysics Data System (ADS)

    Vourvopoulos, George

    1994-05-01

    It has been shown that narcotics, explosives, and other contraband materials, contain various chemical elements such as H, C, N, O, P, S, and Cl in quantities and ratios that differentiate them from each other and from other innocuous substances. Neutrons and γ-rays have the ability to penetrate through various materials at large depths. They are thus able, in a non-intrusive way, to interrogate volumes ranging from suitcases to Sea-Land containers, and have the ability to image the object with an appreciable degree of reliability. Neutron induced reactions such as (n, γ), (n, n') (n, p) or proton induced γ-resonance absorption are some of the reactions currently investigated for the identification of the chemical elements mentioned above. Various DC and pulsed techniques are discussed and their advantages, characteristics, and current progress are shown. Areas where use of these methods is currently under evaluation are detection of hidden explosives, illicit drug interdiction, chemical war agents identification, nuclear waste assay, nuclear weapons destruction and others.

  7. Dynamic based damage detection in composite structures

    NASA Astrophysics Data System (ADS)

    Banerjee, Sauvik; Ricci, Fabrizio; Baid, Harsh; Mal, Ajit K.

    2009-03-01

    Advanced composites are being used increasingly in state-of-the-art aircraft and aerospace structures. In spite of their many advantages, composite materials are highly susceptible to hidden flaws that may occur at any time during the life cycle of a structure, and if undetected, may cause sudden and catastrophic failure of the entire structure. This paper is concerned with the detection and characterization of hidden defects in composite structures before they grow to a critical size. A methodology for automatic damage identification and localization is developed using a combination of vibration and wave propagation data. The structure is assumed to be instrumented with an array of actuators and sensors to excite and record its dynamic response, including vibration and wave propagation effects. A damage index, calculated from the measured dynamical response of the structure in a previous (reference) state and the current state, is introduced as a determinant of structural damage. The indices are used to identify low velocity impact damages in increasingly complex composite structural components. The potential application of the approach in developing health monitoring systems in defects-critical structures is indicated.

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

    PubMed Central

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

    1996-01-01

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

  9. Host-Based Data Exfiltration Detection via System Call Sequences

    SciTech Connect

    Beaver, Justin M; Jewell, Brian C

    2011-01-01

    The host-based detection of malicious data exfiltration activities is currently a sparse area of research and mostly limited to methods that analyze network traffic or signature based detection methods that target specific processes. In this paper we explore an alternative method to host-based detection that exploits sequences of system calls and new collection methods that allow us to catch these activities in real time. We show that system calls sequences can be found to reach a steady state across processes and users, and explore the viability of new methods as heuristics for profiling user behaviors.

  10. Feature-based alert correlation in security systems using self organizing maps

    NASA Astrophysics Data System (ADS)

    Kumar, Munesh; Siddique, Shoaib; Noor, Humera

    2009-04-01

    The security of the networks has been an important concern for any organization. This is especially important for the defense sector as to get unauthorized access to the sensitive information of an organization has been the prime desire for cyber criminals. Many network security techniques like Firewall, VPN Concentrator etc. are deployed at the perimeter of network to deal with attack(s) that occur(s) from exterior of network. But any vulnerability that causes to penetrate the network's perimeter of defense, can exploit the entire network. To deal with such vulnerabilities a system has been evolved with the purpose of generating an alert for any malicious activity triggered against the network and its resources, termed as Intrusion Detection System (IDS). The traditional IDS have still some deficiencies like generating large number of alerts, containing both true and false one etc. By automatically classifying (correlating) various alerts, the high-level analysis of the security status of network can be identified and the job of network security administrator becomes much easier. In this paper we propose to utilize Self Organizing Maps (SOM); an Artificial Neural Network for correlating large amount of logged intrusion alerts based on generic features such as Source/Destination IP Addresses, Port No, Signature ID etc. The different ways in which alerts can be correlated by Artificial Intelligence techniques are also discussed. . We've shown that the strategy described in the paper improves the efficiency of IDS by better correlating the alerts, leading to reduced false positives and increased competence of network administrator.

  11. Minimum variance imaging based on correlation analysis of Lamb wave signals.

    PubMed

    Hua, Jiadong; Lin, Jing; Zeng, Liang; Luo, Zhi

    2016-08-01

    In Lamb wave imaging, MVDR (minimum variance distortionless response) is a promising approach for the detection and monitoring of large areas with sparse transducer network. Previous studies in MVDR use signal amplitude as the input damage feature, and the imaging performance is closely related to the evaluation accuracy of the scattering characteristic. However, scattering characteristic is highly dependent on damage parameters (e.g. type, orientation and size), which are unknown beforehand. The evaluation error can degrade imaging performance severely. In this study, a more reliable damage feature, LSCC (local signal correlation coefficient), is established to replace signal amplitude. In comparison with signal amplitude, one attractive feature of LSCC is its independence of damage parameters. Therefore, LSCC model in the transducer network could be accurately evaluated, the imaging performance is improved subsequently. Both theoretical analysis and experimental investigation are given to validate the effectiveness of the LSCC-based MVDR algorithm in improving imaging performance. PMID:27155349

  12. Research about Memory Detection Based on the Embedded Platform

    NASA Astrophysics Data System (ADS)

    Sun, Hao; Chu, Jian

    As is known to us all, the resources of memory detection of the embedded systems are very limited. Taking the Linux-based embedded arm as platform, this article puts forward two efficient memory detection technologies according to the characteristics of the embedded software. Especially for the programs which need specific libraries, the article puts forwards portable memory detection methods to help program designers to reduce human errors,improve programming quality and therefore make better use of the valuable embedded memory resource.

  13. Saliency-based artificial object detection for satellite images

    NASA Astrophysics Data System (ADS)

    Ke, Shidong; Ding, Xiaoying; Yang, Daiqin; Chen, Zhenzhong; Fang, Yuming

    2015-03-01

    In this paper, we introduce a computational model of top-down saliency based on multiscale orientation information for artificial object detection for satellite images. Further more, the top-down saliency is integrated with bottom-up saliency to obtain the saliency map in satellite images. We compare our method to several state-of-the-art saliency detection models and demonstrate the superior performance in artificial object detection for satellite images.

  14. Change detection of built-up land: A framework of combining pixel-based detection and object-based recognition

    NASA Astrophysics Data System (ADS)

    Xiao, Pengfeng; Zhang, Xueliang; Wang, Dongguang; Yuan, Min; Feng, Xuezhi; Kelly, Maggi

    2016-09-01

    This study proposed a new framework that combines pixel-level change detection and object-level recognition to detect changes of built-up land from high-spatial resolution remote sensing images. First, an adaptive differencing method was designed to detect changes at the pixel level based on both spectral and textural features. Next, the changed pixels were subjected to a set of morphological operations to improve the completeness and to generate changed objects, achieving the transition of change detection from the pixel level to the object level. The changed objects were further recognised through the difference of morphological building index in two phases to indicate changed objects on built-up land. The transformation from changed pixels to changed objects makes the proposed framework distinct with both the pixel-based and the object-based change detection methods. Compared with the pixel-based methods, the proposed framework can improve the change detection capability through the transformation and successive recognition of objects. Compared with the object-based method, the proposed framework avoids the issue of multitemporal segmentation and can generate changed objects directly from changed pixels. The experimental results show the effectiveness of the transformation from changed pixels to changed objects and the successive object-based recognition on improving the detection accuracy, which justify the application potential of the proposed change detection framework.

  15. SVD principle analysis and fault diagnosis for bearings based on the correlation coefficient

    NASA Astrophysics Data System (ADS)

    Qiao, Zijian; Pan, Zhengrong

    2015-08-01

    Aiming at solving the existing sharp problems by using singular value decomposition (SVD) in the fault diagnosis of rolling bearings, such as the determination of the delay step k for creating the Hankel matrix and selection of effective singular values, the present study proposes a novel adaptive SVD method for fault feature detection based on the correlation coefficient by analyzing the principles of the SVD method. This proposed method achieves not only the optimal determination of the delay step k by means of the absolute value {{r}k} of the autocorrelation function sequence of the collected vibration signal, but also the adaptive selection of effective singular values using the index ρ corresponding to useful component signals including weak fault information to detect weak fault signals for rolling bearings, especially weak impulse signals. The effectiveness of this method has been verified by contrastive results between the proposed method and traditional SVD, even using the wavelet-based method through simulated experiments. Finally, the proposed method has been applied to fault diagnosis for a deep-groove ball bearing in which a single point fault located on either the inner or outer race of rolling bearings is obtained successfully. Therefore, it can be stated that the proposed method is of great practical value in engineering applications.

  16. Local-hybrid functional based on the correlation length

    SciTech Connect

    Johnson, Erin R.

    2014-09-28

    Local-hybrid functionals involve position-dependent mixing of Hartree-Fock and density-functional exchange, which should allow improved performance relative to conventional hybrids by reducing the inherent delocalization error and improving the long-range behaviour. Herein, the same-spin correlation length, obtained from the Fermi-hole radius, is used as the mixing parameter. The performance of the resulting local-hybrid functional is assessed for standard thermochemical and kinetics benchmarks. The local hybrid is shown to perform significantly better than the corresponding global hybrid in almost all cases.

  17. SCREEN photometric property detection system based on area CCD

    NASA Astrophysics Data System (ADS)

    Yan, Fu-cai; Ye, Wei; Xu, Yu; Wang, Chao; Zhang, Yu-wei

    2011-08-01

    The photometric property detection of screen display is crucial for screen display quality test. Traditional photometry detection technologies were based on photoelectric sensors such as silicon photocell, photo-electric multiplier and CdS, which can detect only some isolated points. To break the limitation of randomness, incompleteness and detection accuracy in current technologies, we designed a screen photometric detection system based on area CCD. The system consists of photometric image sensor, photometric image acquisition hardware and photometric image analyzing software. The photometric image sensor, which adopts optical lens, optical filters and area CCD, adapts its spectrum response property to fit the spectrum luminous efficiency curve V (λ) by adjusting the thickness and quantity of appropriate optical filters. photometric image acquisition hardware adopts the DSP as a core processor to drive the area CCD, to sample, acquire , process and save the image from image sensor, to transmit the image to computer. For real-time performance of transmitting, the hardware system adopts the transmission protocol of USB2.0. The uploaded image will be processed by photometric image analyzing software, and then displayed in real time with detection results. The screen photometric detection technology based on area CCD can detect specifications of the whole screen such as luminance, contrast, onoff ratio and uniformity, breaks the limitation of randomness and incompleteness in current detection technology, exactly and fully reflects the integrated display quality of the whole screen. According to the test results, the accuracy of this system has reached the accuracy level one in China.

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2016-01-01

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

  1. Flow cytometry-based apoptosis detection

    PubMed Central

    Wlodkowic, Donald; Skommer, Joanna; Darzynkiewicz, Zbigniew

    2013-01-01

    An apoptosing cell demonstrates multitude of characteristic morphological and biochemical features, which vary depending on the stimuli and cell type. The gross majority of classical apoptotic hallmarks can be rapidly examined by flow and image cytometry. Cytometry thus became a technology of choice in diverse studies of cellular demise. A large variety of cytometric methods designed to identify apoptotic cells and probe mechanisms associated with this mode of cell demise have been developed during the past two decades. In the present chapter we outline a handful of commonly used methods that are based on the assessment of: mitochondrial transmembrane potential, activation of caspases, plasma membrane alterations and DNA fragmentation. PMID:19609746

  2. Video-Based Affect Detection in Noninteractive Learning Environments

    ERIC Educational Resources Information Center

    Chen, Yuxuan; Bosch, Nigel; D'Mello, Sidney

    2015-01-01

    The current paper explores possible solutions to the problem of detecting affective states from facial expressions during text/diagram comprehension, a context devoid of interactive events that can be used to infer affect. These data present an interesting challenge for face-based affect detection because likely locations of affective facial…

  3. CINCH (confocal incoherent correlation holography) super resolution fluorescence microscopy based upon FINCH (Fresnel incoherent correlation holography)

    PubMed Central

    Siegel, Nisan; Storrie, Brian; Bruce, Marc

    2016-01-01

    FINCH holographic fluorescence microscopy creates high resolution super-resolved images with enhanced depth of focus. The simple addition of a real-time Nipkow disk confocal image scanner in a conjugate plane of this incoherent holographic system is shown to reduce the depth of focus, and the combination of both techniques provides a simple way to enhance the axial resolution of FINCH in a combined method called “CINCH”. An important feature of the combined system allows for the simultaneous real-time image capture of widefield and holographic images or confocal and confocal holographic images for ready comparison of each method on the exact same field of view. Additional GPU based complex deconvolution processing of the images further enhances resolution. PMID:26839443

  4. Raman spectroscopy-based detection of chemical contaminants in food powders

    NASA Astrophysics Data System (ADS)

    Chao, Kuanglin; Dhakal, Sagar; Qin, Jianwei; Kim, Moon; Bae, Abigail

    2016-05-01

    Raman spectroscopy technique has proven to be a reliable method for qualitative detection of chemical contaminants in food ingredients and products. For quantitative imaging-based detection, each contaminant particle in a food sample must be detected and it is important to determine the necessary spatial resolution needed to effectively detect the contaminant particles. This study examined the effective spatial resolution required for detection of maleic acid in tapioca starch and benzoyl peroxide in wheat flour. Each chemical contaminant was mixed into its corresponding food powder at a concentration of 1% (w/w). Raman spectral images were collected for each sample, leveled across a 45 mm x 45 mm area, using different spatial resolutions. Based on analysis of these images, a spatial resolution of 0.5mm was selected as effective spatial resolution for detection of maleic acid in starch and benzoyl peroxide in flour. An experiment was then conducted using the 0.5mm spatial resolution to demonstrate Raman imaging-based quantitative detection of these contaminants for samples prepared at 0.1%, 0.3%, and 0.5% (w/w) concentrations. The results showed a linear correlation between the detected numbers of contaminant pixels and the actual concentrations of contaminant.

  5. A Versatile Microparticle-Based Immunoaggregation Assay for Macromolecular Biomarker Detection and Quantification

    PubMed Central

    Wu, Haiyan; Han, Yu; Yang, Xi; Chase, George G.; Tang, Qiong; Lee, Chen-Jung; Cao, Bin; Zhe, Jiang; Cheng, Gang

    2015-01-01

    The rapid, sensitive and low-cost detection of macromolecular biomarkers is critical in clinical diagnostics, environmental monitoring, research, etc. Conventional assay methods usually require bulky, expensive and designated instruments and relative long assay time. For hospitals and laboratories that lack immediate access to analytical instruments, fast and low-cost assay methods for the detection of macromolecular biomarkers are urgently needed. In this work, we developed a versatile microparticle (MP)-based immunoaggregation method for the detection and quantification of macromolecular biomarkers. Antibodies (Abs) were firstly conjugated to MP through streptavidin-biotin interaction; the addition of macromolecular biomarkers caused the aggregation of Ab-MPs, which were subsequently detected by an optical microscope or optical particle sizer. The invisible nanometer-scale macromolecular biomarkers caused detectable change of micrometer-scale particle size distributions. Goat anti-rabbit immunoglobulin and human ferritin were used as model biomarkers to demonstrate MP-based immunoaggregation assay in PBS and 10% FBS to mimic real biomarker assay in the complex medium. It was found that both the number ratio and the volume ratio of Ab-MP aggregates caused by biomarker to all particles were directly correlated to the biomarker concentration. In addition, we found that the detection range could be tuned by adjusting the Ab-MP concentration. We envision that this novel MP-based immunoaggregation assay can be combined with multiple detection methods to detect and quantify macromolecular biomarkers at the nanogram per milliliter level. PMID:25658837

  6. Electrophysiological Correlates of Automatic Visual Change Detection in School-Age Children

    ERIC Educational Resources Information Center

    Clery, Helen; Roux, Sylvie; Besle, Julien; Giard, Marie-Helene; Bruneau, Nicole; Gomot, Marie

    2012-01-01

    Automatic stimulus-change detection is usually investigated in the auditory modality by studying Mismatch Negativity (MMN). Although the change-detection process occurs in all sensory modalities, little is known about visual deviance detection, particularly regarding the development of this brain function throughout childhood. The aim of the…

  7. Vibration Based Sun Gear Damage Detection

    NASA Technical Reports Server (NTRS)

    Hood, Adrian; LaBerge, Kelsen; Lewicki, David; Pines, Darryll

    2013-01-01

    Seeded fault experiments were conducted on the planetary stage of an OH-58C helicopter transmission. Two vibration based methods are discussed that isolate the dynamics of the sun gear from that of the planet gears, bearings, input spiral bevel stage, and other components in and around the gearbox. Three damaged sun gears: two spalled and one cracked, serve as the focus of this current work. A non-sequential vibration separation algorithm was developed and the resulting signals analyzed. The second method uses only the time synchronously averaged data but takes advantage of the signal/source mapping required for vibration separation. Both algorithms were successful in identifying the spall damage. Sun gear damage was confirmed by the presence of sun mesh groups. The sun tooth crack condition was inconclusive.

  8. Saliency detection based on multi-instance images learning

    NASA Astrophysics Data System (ADS)

    Wan, Shouhong; Jin, Peiquan; Yue, Lihua; Huang, Qian

    2015-07-01

    Existing visual saliency detection methods are usually based on single image, however, without priori knowledge, the contents of single image are ambiguous, so visual saliency detection based on single image can't extract region of interest. To solve it, we propose a novel saliency detection based on multi-instance images. Our method considers human's visual psychological factors and measures visual saliency based on global contrast, local contrast and sparsity. It firstly uses multi-instance learning to get the center of clustering, and then computes feature relative dispersion. By fusing different weighted feature saliency map, the final synthesize saliency map is generated. Comparing with other saliency detection methods, our method increases the rate of hit.

  9. Semiconducting Metal Oxide Based Sensors for Selective Gas Pollutant Detection

    PubMed Central

    Kanan, Sofian M.; El-Kadri, Oussama M.; Abu-Yousef, Imad A.; Kanan, Marsha C.

    2009-01-01

    A review of some papers published in the last fifty years that focus on the semiconducting metal oxide (SMO) based sensors for the selective and sensitive detection of various environmental pollutants is presented. PMID:22408500

  10. ENZYME-BASED DETECTION OF CHLORINATED HYDROCARBONS IN WATER

    EPA Science Inventory

    An enzyme-based approach for detecting hazardous levels of high molecular weight chlorinated hydrocarbons in natural waters has been explored. An extensive review of the literature indicated that the enzymes, lactate dehydrogenase, carbonic anhydrase, hexokinase, phosphorylase an...

  11. Functional MRI-based lie detection: scientific and societal challenges.

    PubMed

    Farah, Martha J; Hutchinson, J Benjamin; Phelps, Elizabeth A; Wagner, Anthony D

    2014-02-01

    Functional MRI (fMRI)-based lie detection has been marketed as a tool for enhancing personnel selection, strengthening national security and protecting personal reputations, and at least three US courts have been asked to admit the results of lie detection scans as evidence during trials. How well does fMRI-based lie detection perform, and how should the courts, and society more generally, respond? Here, we address various questions — some of which are based on a meta-analysis of published studies — concerning the scientific state of the art in fMRI-based lie detection and its legal status, and discuss broader ethical and societal implications. We close with three general policy recommendations. PMID:24588019

  12. Pilot study of automated bullet signature identification based on topography measurements and correlations.

    PubMed

    Chu, Wei; Song, John; Vorburger, Theodore; Yen, James; Ballou, Susan; Bachrach, Benjamin

    2010-03-01

    A procedure for automated bullet signature identification is described based on topography measurements using confocal microscopy and correlation calculation. Automated search and retrieval systems are widely used for comparison of firearms evidence. In this study, 48 bullets fired from six different barrel manufacturers are classified into different groups based on the width class characteristic for each land engraved area of the bullets. Then the cross-correlation function is applied both for automatic selection of the effective correlation area, and for the extraction of a 2D bullet profile signature. Based on the cross-correlation maximum values, a list of top ranking candidates against a ballistics signature database of bullets fired from the same model firearm is developed. The correlation results show a 9.3% higher accuracy rate compared with a currently used commercial system based on optical reflection. This suggests that correlation results can be improved using the sequence of methods described here. PMID:20102451

  13. An optimized, universal hardware-based adaptive correlation receiver architecture

    NASA Astrophysics Data System (ADS)

    Zhu, Zaidi; Suarez, Hernan; Zhang, Yan; Wang, Shang

    2014-05-01

    The traditional radar RF transceivers, similar to communication transceivers, have the basic elements such as baseband waveform processing, IF/RF up-down conversion, transmitter power circuits, receiver front-ends, and antennas, which are shown in the upper half of Figure 1. For modern radars with diversified and sophisticated waveforms, we can frequently observe that the transceiver behaviors, especially nonlinear behaviors, are depending on the waveform amplitudes, frequency contents and instantaneous phases. Usually, it is a troublesome process to tune an RF transceiver to optimum when different waveforms are used. Another issue arises from the interference caused by the waveforms - for example, the range side-lobe (RSL) caused by the waveforms, once the signals pass through the entire transceiver chain, may be further increased due to distortions. This study is inspired by the two existing solutions from commercial communication industry, digital pre-distortion (DPD) and adaptive channel estimation and Interference Mitigation (AIM), while combining these technologies into a single chip or board that can be inserted into the existing transceiver system. This device is then named RF Transceiver Optimizer (RTO). The lower half of Figure 1 shows the basic element of RTO. With RTO, the digital baseband processing does not need to take into account the transceiver performance with diversified waveforms, such as the transmitter efficiency and chain distortion (and the intermodulation products caused by distortions). Neither does it need to concern the pulse compression (or correlation receiver) process and the related mitigation. The focus is simply the information about the ground truth carried by the main peak of correlation receiver outputs. RTO can be considered as an extension of the existing calibration process, while it has the benefits of automatic, adaptive and universal. Currently, the main techniques to implement the RTO are the digital pre- or -post

  14. Detection of smoke plume for a land-based early forest fire detection system

    NASA Astrophysics Data System (ADS)

    Saghri, John; Jacobs, John; Davenport, Tim; Garges, David

    2015-09-01

    A promising daytime smoke plume detection for a land-based early forest fire detection system is proposed. The visible video imagery from a land-based monitoring camera is processed to detect the smoke which likely rises in an early stage of a forest fire. Unlike the fire core and its surrounding heat which are detected via day/night infrared imaging, the relatively cold smoke plume can only be captured in the visible spectrum of light. The smoke plume is detected via exploitation of its temporal signature. This is accomplished via Principal Component Transformation (PCT) operations on consecutive sequences of visible video frames followed by spatial filtering of one of the resulting low-order Principal Component (PC) images. It is shown that the blue channel of the Red, Green, Blue (RGB) color camera is most effective in detecting the smoke plume. Smoke plume is clearly detected and isolated via simple blurring, thresholding, and median filtering of one of the resulting low-order principle component (PC) images. The robustness of this PCA-based method relative to simple temporal frame differencing and use of color, i.e., visible spectral signature of smoke, are discussed. Various parameters of the system including the required observation time and number of frames to retain for PCT, selection of which low-order PC to use, and types and sizes of the filters applied to the selected PC image to detect and isolate the smoke plume, are discussed.

  15. Using Morphlet-Based Image Representation for Object Detection

    NASA Astrophysics Data System (ADS)

    Gorbatsevich, V. S.; Vizilter, Yu. V.

    2016-06-01

    In this paper, we propose an original method for objects detection based on a special tree-structured image representation - the trees of morphlets. The method provides robust detection of various types of objects in an image without employing a machine learning procedure. Along with a bounding box creation on a detection step, the method makes pre-segmentation, which can be further used for recognition purposes. Another important feature of the proposed approach is that there are no needs to use a running window as well as a features pyramid in order to detect the objects of different sizes.

  16. Foreign fiber detecting system based on multispectral technique

    NASA Astrophysics Data System (ADS)

    Li, Qi; Han, Shaokun; Wang, Ping; Wang, Liang; Xia, Wenze

    2015-08-01

    This paper presents a foreign fiber detecting system based on multi-spectral technique. The absorption rate and the reflectivity of foreign fibers differently under different wavelengths of light so that the characteristics of the image has difference in the different light irradiation. Contrast pyramid image fusion algorithm and adaptive enhancement is improved to extracted the foreign fiber from the cotton background. The experimental results show that the single light source can detect 6 kinds of foreign fiber in cotton and multi-spectral detection can detect eight kinds.

  17. Vehicle Detection Based on Probability Hypothesis Density Filter

    PubMed Central

    Zhang, Feihu; Knoll, Alois

    2016-01-01

    In the past decade, the developments of vehicle detection have been significantly improved. By utilizing cameras, vehicles can be detected in the Regions of Interest (ROI) in complex environments. However, vision techniques often suffer from false positives and limited field of view. In this paper, a LiDAR based vehicle detection approach is proposed by using the Probability Hypothesis Density (PHD) filter. The proposed approach consists of two phases: the hypothesis generation phase to detect potential objects and the hypothesis verification phase to classify objects. The performance of the proposed approach is evaluated in complex scenarios, compared with the state-of-the-art. PMID:27070621

  18. Vehicle Detection Based on Probability Hypothesis Density Filter.

    PubMed

    Zhang, Feihu; Knoll, Alois

    2016-01-01

    In the past decade, the developments of vehicle detection have been significantly improved. By utilizing cameras, vehicles can be detected in the Regions of Interest (ROI) in complex environments. However, vision techniques often suffer from false positives and limited field of view. In this paper, a LiDAR based vehicle detection approach is proposed by using the Probability Hypothesis Density (PHD) filter. The proposed approach consists of two phases: the hypothesis generation phase to detect potential objects and the hypothesis verification phase to classify objects. The performance of the proposed approach is evaluated in complex scenarios, compared with the state-of-the-art. PMID:27070621

  19. Correlation Analysis of Automobile Crash Responses Based on Wavelet Decompositions

    NASA Astrophysics Data System (ADS)

    Cheng, Z. Q.; Pellettiere, J. A.

    2003-11-01

    Wavelets are used to analyse automobile crash responses. Crash signals are decomposed into a wavelet or wavelet packet basis, which provide an intuitive vision of impact behaviour of the vehicle structure and occupants. The decomposed signals are further divided into segments that represent vibrations occurring in certain time spans. A correlation analysis is then performed on the decomposed and segmented signals in order to determine the dynamic relationship between different parts of the structure or different segments of the body. The structural responses and the occupant responses in a full frontal impact test are analysed. It is shown that when the gross motions of the structural components are superimposed with significant short time vibrations, the occupant forward motion is basically a rigid body motion. Published by Elsevier Science Ltd.

  20. Theoretical detection ranges for acoustic based manatee avoidance technology.

    PubMed

    Phillips, Richard; Niezrecki, Christopher; Beusse, Diedrich O

    2006-07-01

    The West Indian manatee (Trichechus manatus latirostris) has become endangered partly because of watercraft collisions in Florida's coastal waterways. To reduce the number of collisions, warning systems based upon detecting manatee vocalizations have been proposed. One aspect of the feasibility of an acoustically based warning system relies upon the distance at which a manatee vocalization is detectable. Assuming a mixed spreading model, this paper presents a theoretical analysis of the system detection capabilities operating within various background and watercraft noise conditions. This study combines measured source levels of manatee vocalizations with the modeled acoustic properties of manatee habitats to develop a method for determining the detection range and hydrophone spacing requirements for acoustic based manatee avoidance technologies. In quiet environments (background noise approximately 70 dB) it was estimated that manatee vocalizations are detectable at approximately 250 m, with a 6 dB detection threshold, In louder environments (background noise approximately 100dB) the detection range drops to 2.5 m. In a habitat with 90 dB of background noise, a passing boat with a maximum noise floor of 120 dB would be the limiting factor when it is within approximately 100 m of a hydrophone. The detection range was also found to be strongly dependent on the manatee vocalization source level. PMID:16875213

  1. Image-based target detection with multispectral UWB OFDM radar

    NASA Astrophysics Data System (ADS)

    Bufler, Travis D.; Garmatyuk, Dmitriy S.

    2012-06-01

    This paper proposes an image-based automatic target detection algorithm to be used in clutter and sparse target environments. We intend to apply the algorithm to an ultra-wideband multispectral radar concept by means of employing multi-carrier waveforms based upon Orthogonal Frequency Division Multiplexing (OFDM) modulation. Individual sub-bands of an OFDM waveform can be processed separately to yield range and cross-range reconstruction of a target scene containing both targets and clutter. Target detection in resulting images will be performed and contrasted with the detection performance of a traditional fixed-waveform Synthetic Aperture Radar system. The target detection algorithm is implemented through the use of scalar and vector field operations performed on the images from the reconstructed target scene. We hypothesize that the use of vector operations and field analysis will allow for an adaptive approach to the detection of targets within clutter.

  2. Transistor-based particle detection systems and methods

    DOEpatents

    Jain, Ankit; Nair, Pradeep R.; Alam, Muhammad Ashraful

    2015-06-09

    Transistor-based particle detection systems and methods may be configured to detect charged and non-charged particles. Such systems may include a supporting structure contacting a gate of a transistor and separating the gate from a dielectric of the transistor, and the transistor may have a near pull-in bias and a sub-threshold region bias to facilitate particle detection. The transistor may be configured to change current flow through the transistor in response to a change in stiffness of the gate caused by securing of a particle to the gate, and the transistor-based particle detection system may configured to detect the non-charged particle at least from the change in current flow.

  3. Gold Nanoparticles-Based Barcode Analysis for Detection of Norepinephrine.

    PubMed

    An, Jeung Hee; Lee, Kwon-Jai; Choi, Jeong-Woo

    2016-02-01

    Nanotechnology-based bio-barcode amplification analysis offers an innovative approach for detecting neurotransmitters. We evaluated the efficacy of this method for detecting norepinephrine in normal and oxidative-stress damaged dopaminergic cells. Our approach use a combination of DNA barcodes and bead-based immunoassays for detecting neurotransmitters with surface-enhanced Raman spectroscopy (SERS), and provides polymerase chain reaction (PCR)-like sensitivity. This method relies on magnetic Dynabeads containing antibodies and nanoparticles that are loaded both with DNA barcords and with antibodies that can sandwich the target protein captured by the Dynabead-bound antibodies. The aggregate sandwich structures are magnetically separated from the solution and treated to remove the conjugated barcode DNA. The DNA barcodes are then identified by SERS and PCR analysis. The concentration of norepinephrine in dopaminergic cells can be readily detected using the bio-barcode assay, which is a rapid, high-throughput screening tool for detecting neurotransmitters. PMID:27305769

  4. Infrared small target detection based on Danger Theory

    NASA Astrophysics Data System (ADS)

    Lan, Jinhui; Yang, Xiao

    2009-11-01

    To solve the problem that traditional method can't detect the small objects whose local SNR is less than 2 in IR images, a Danger Theory-based model to detect infrared small target is presented in this paper. First, on the analog with immunology, the definition is given, in this paper, to such terms as dangerous signal, antigens, APC, antibodies. Besides, matching rule between antigen and antibody is improved. Prior to training the detection model and detecting the targets, the IR images are processed utilizing adaptive smooth filter to decrease the stochastic noise. Then at the training process, deleting rule, generating rule, crossover rule and the mutation rule are established after a large number of experiments in order to realize immediate convergence and obtain good antibodies. The Danger Theory-based model is built after the training process, and this model can detect the target whose local SNR is only 1.5.

  5. Flow-Based Detection of Bar Coded Particles

    SciTech Connect

    Rose, K A; Dougherty, G M; Santiago, J G

    2005-06-24

    We have developed methods for flow control, electric field alignment, and readout of colloidal Nanobarcodes{copyright}. Our flow-based detection scheme leverages microfluidics and alternate current (AC) electric fields to align and image particles in a well-defined image plane. Using analytical models of the particle rotation in electric fields we can optimize the field strength and frequency necessary to align the particles. This detection platform alleviates loss of information in solution-based assays due to particle clumping during detection.

  6. DDoS Attack Detection Algorithms Based on Entropy Computing

    NASA Astrophysics Data System (ADS)

    Li, Liying; Zhou, Jianying; Xiao, Ning

    Distributed Denial of Service (DDoS) attack poses a severe threat to the Internet. It is difficult to find the exact signature of attacking. Moreover, it is hard to distinguish the difference of an unusual high volume of traffic which is caused by the attack or occurs when a huge number of users occasionally access the target machine at the same time. The entropy detection method is an effective method to detect the DDoS attack. It is mainly used to calculate the distribution randomness of some attributes in the network packets' headers. In this paper, we focus on the detection technology of DDoS attack. We improve the previous entropy detection algorithm, and propose two enhanced detection methods based on cumulative entropy and time, respectively. Experiment results show that these methods could lead to more accurate and effective DDoS detection.

  7. Laser-based instrumentation for the detection of chemical agents

    SciTech Connect

    Hartford, A. Jr.; Sander, R.K.; Quigley, G.P.; Radziemski, L.J.; Cremers, D.A.

    1982-01-01

    Several laser-based techniques are being evaluated for the remote, point, and surface detection of chemical agents. Among the methods under investigation are optoacoustic spectroscopy, laser-induced breakdown spectroscopy (LIBS), and synchronous detection of laser-induced fluorescence (SDLIF). Optoacoustic detection has already been shown to be capable of extremely sensitive point detection. Its application to remote sensing of chemical agents is currently being evaluated. Atomic emission from the region of a laser-generated plasma has been used to identify the characteristic elements contained in nerve (P and F) and blister (S and Cl) agents. Employing this LIBS approach, detection of chemical agent simulants dispersed in air and adsorbed on a variety of surfaces has been achieved. Synchronous detection of laser-induced fluorescence provides an attractive alternative to conventional LIF, in that an artificial narrowing of the fluorescence emission is obtained. The application of this technique to chemical agent simulants has been successfully demonstrated. 19 figures.

  8. Region Duplication Forgery Detection Technique Based on SURF and HAC

    PubMed Central

    Mishra, Parul; Sharma, Sanjeev; Patel, Ravindra

    2013-01-01

    Region duplication forgery detection is a special type of forgery detection approach and widely used research topic under digital image forensics. In copy move forgery, a specific area is copied and then pasted into any other region of the image. Due to the availability of sophisticated image processing tools, it becomes very hard to detect forgery with naked eyes. From the forged region of an image no visual clues are often detected. For making the tampering more robust, various transformations like scaling, rotation, illumination changes, JPEG compression, noise addition, gamma correction, and blurring are applied. So there is a need for a method which performs efficiently in the presence of all such attacks. This paper presents a detection method based on speeded up robust features (SURF) and hierarchical agglomerative clustering (HAC). SURF detects the keypoints and their corresponding features. From these sets of keypoints, grouping is performed on the matched keypoints by HAC that shows copied and pasted regions. PMID:24311972

  9. Research on object detection based on circular polarization property

    NASA Astrophysics Data System (ADS)

    Wu, Yun-zhi; Zeng, Xian-fang; Yin, Cheng-liang; Luo, Xiao-lin

    2013-09-01

    It is an important subject in information scout, battlefield surveillance and automatic target recognition to detect interesting objects from complicated background. Compared with intensity detection, polarization detection has its advantage in identifying some camouflage targets. Usually, in the studies of target polarization detection, circular polarization property is usually neglected because of its small value. But in particular conditions, the circular polarization property of target will be used to accomplish object detection with their obviously different value. In this study, a single reflectance model of Mueller matrix is established, and based on Fresnel's law, circular polarization property of object is analyzed which is obvious while linear polarization property is obscure in particular condition. It is available to use the circular polarization component to detect target.

  10. Revisiting node-based SIR models in complex networks with degree correlations

    NASA Astrophysics Data System (ADS)

    Wang, Yi; Cao, Jinde; Alofi, Abdulaziz; AL-Mazrooei, Abdullah; Elaiw, Ahmed

    2015-11-01

    In this paper, we consider two growing networks which will lead to the degree-degree correlations between two nearest neighbors in the network. When the network grows to some certain size, we introduce an SIR-like disease such as pandemic influenza H1N1/09 to the population. Due to its rapid spread, the population size changes slowly, and thus the disease spreads on correlated networks with approximately fixed size. To predict the disease evolution on correlated networks, we first review two node-based SIR models incorporating degree correlations and an edge-based SIR model without considering degree correlation, and then compare the predictions of these models with stochastic SIR simulations, respectively. We find that the edge-based model, even without considering degree correlations, agrees much better than the node-based models incorporating degree correlations with stochastic SIR simulations in many respects. Moreover, simulation results show that for networks with positive correlation, the edge-based model provides a better upper bound of the cumulative incidence than the node-based SIR models, whereas for networks with negative correlation, it provides a lower bound of the cumulative incidence.

  11. Noise-benefit forbidden-interval theorems for threshold signal detectors based on cross correlations.

    PubMed

    Mitaim, Sanya; Kosko, Bart

    2014-11-01

    We show that the main forbidden interval theorems of stochastic resonance hold for a correlation performance measure. Earlier theorems held only for performance measures based on mutual information or the probability of error detection. Forbidden interval theorems ensure that a threshold signal detector benefits from deliberately added noise if the average noise does not lie in an interval that depends on the threshold value. We first show that this result holds for correlation for all finite-variance noise and for all forms of infinite-variance stable noise. A second forbidden-interval theorem gives necessary and sufficient conditions for a local noise benefit in a bipolar signal system when the noise comes from a location-scale family. A third theorem gives a general condition for a local noise benefit for arbitrary signals with finite second moments and for location-scale noise. This result also extends forbidden intervals to forbidden bands of parameters. A fourth theorem gives necessary and sufficient conditions for a local noise benefit when both the independent signal and noise are normal. A final theorem derives necessary and sufficient conditions for forbidden bands when using arrays of threshold detectors for arbitrary signals and location-scale noise. PMID:25493756

  12. Design and implementation of photon correlator based on C8051F

    NASA Astrophysics Data System (ADS)

    Shen, Jin; Li, Yuming; Liu, Wei; Yang, Yan; Cheng, Yanting

    2008-02-01

    Correlation techniques are widely used to extract spectral information from light scattering and other stochastic processes. Within the photon correlation system, the correlating operation must work at a high speed. In this paper, a photon correlator based on microcontroller C8051F was developed. In the photon correlator, the work of counting and scratch is completed by the two 4-bits binary adder 74F161, which is connected to form an 8-bits adder., and the correlation operation of every channel is carried out by the software of C8051F. By probably choosing high speed devices counting of 10ns in width pulses can be counted. The correlation operations including multiplying and addition operation of 56 channels with the circulation program within 3μs were made in interrupt service routine of the C8051F. The work in this paper can be applied in the ultra-fine particle sizing with photon correlation spectroscopy.

  13. REIONIZATION ON LARGE SCALES. II. DETECTING PATCHY REIONIZATION THROUGH CROSS-CORRELATION OF THE COSMIC MICROWAVE BACKGROUND

    SciTech Connect

    Natarajan, A.; Battaglia, N.; Trac, H.; Pen, U.-L.; Loeb, A.

    2013-10-20

    We investigate the effect of patchy reionization on the cosmic microwave background (CMB) temperature. An anisotropic optical depth τ( n-hat ) alters the TT power spectrum on small scales l > 2000. We make use of the correlation between the matter density and the reionization redshift fields to construct full sky maps of τ( n-hat ). Patchy reionization transfers CMB power from large scales to small scales, resulting in a non-zero cross correlation between large and small angular scales. We show that the patchy τ correlator is sensitive to small root mean square (rms) values τ{sub rms} ∼ 0.003 seen in our maps. We include frequency-independent secondaries such as CMB lensing and kinetic Sunyaev-Zel'dovich (kSZ) terms, and show that patchy τ may still be detected at high significance. Reionization models that predict different values of τ{sub rms} may be distinguished even for the same mean value (τ). It is more difficult to detect patchy τ in the presence of larger secondaries such as the thermal Sunyaev-Zel'dovich, radio background, and the cosmic infrared background. In this case, we show that patchy τ may be detected if these frequency-dependent secondaries are minimized to ∼< 5 μK (rms) by means of a multi-frequency analysis. We show that the patchy τ correlator provides information that is complementary to what may be obtained from the polarization and the kSZ power spectra.

  14. Signalprint-Based Intrusion Detection in Wireless Networks

    NASA Astrophysics Data System (ADS)

    Mitchell, Rob; Chen, Ing-Ray; Eltoweissy, Mohamed

    Wireless networks are a critical part of global communication for which intrusion detection techniques should be applied to secure network access, or the cost associated with successful attacks will overshadow the benefits that wireless networks offer. In this paper we investigate a new scheme called Nodeprints to extend the existing centralized Signalprints design for authentication to a distributed voting-based design for intrusion detection. We analyze the effect of voting-based intrusion detection designs, the probability of an individual node voting incorrectly, the ratio of mobile nodes to base stations, and the rate at which nodes are compromised, on the system performance measured by the probability that the intrusion detection system yields a false result. We develop a performance model for evaluating our Nodeprints design and identify conditions under which Nodeprints outperforms the existing Signalprints design.

  15. Detection of heavy metal by paper-based microfluidics.

    PubMed

    Lin, Yang; Gritsenko, Dmitry; Feng, Shaolong; Teh, Yi Chen; Lu, Xiaonan; Xu, Jie

    2016-09-15

    Heavy metal pollution has shown great threat to the environment and public health worldwide. Current methods for the detection of heavy metals require expensive instrumentation and laborious operation, which can only be accomplished in centralized laboratories. Various microfluidic paper-based analytical devices have been developed recently as simple, cheap and disposable alternatives to conventional ones for on-site detection of heavy metals. In this review, we first summarize current development of paper-based analytical devices and discuss the selection of paper substrates, methods of device fabrication, and relevant theories in these devices. We then compare and categorize recent reports on detection of heavy metals using paper-based microfluidic devices on the basis of various detection mechanisms, such as colorimetric, fluorescent, and electrochemical methods. To finalize, the future development and trend in this field are discussed. PMID:27131999

  16. Detecting entanglement of continuous variables with three mutually unbiased bases

    NASA Astrophysics Data System (ADS)

    Paul, E. C.; Tasca, D. S.; Rudnicki, Łukasz; Walborn, S. P.

    2016-07-01

    An uncertainty relation is introduced for a symmetric arrangement of three mutually unbiased bases in continuous-variable phase space, and then used to derive a bipartite entanglement criterion based on the variance of global operators composed of these three phase-space variables. We test this criterion using spatial variables of photon pairs and show that the entangled photons are correlated in three pairs of bases.

  17. DSP design for real-time hyperspectral target detection based on spatial-spectral information extraction

    NASA Astrophysics Data System (ADS)

    Yang, Wei; Zhang, Bing; Gao, Lianru; Wu, Yuanfeng

    2012-06-01

    Military target detection is an important application of hyperspectral remote sensing. It highly demands real-time or near real-time processing. However, the massive amount of hyperspectral image data seriously limits the processing speed. Real-time image processing based on hardware platform, such as digital signal processor (DSP), is one of recent developments in hyperspectral target detection. In hyperspectral target detection algorithms, correlation matrix or covariance matrix calculation is always used to whiten data, which is a very time-consuming process. In this paper, a strategy named spatial-spectral information extraction (SSIE) is presented to accelerate the speed of hyperspectral image processing. The strategy is composed of bands selection and sample covariance matrix estimation. Bands selection fully utilizes the high-spectral correlation in spectral image, while sample covariance matrix estimation fully utilizes the high-spatial correlation in remote sensing image. Meanwhile, this strategy is implemented on the hardware platform of DSP. The hardware implementation of constrained energy minimization (CEM) algorithm is composed of hardware architecture and software architecture. The hardware architecture contains chips and peripheral interfaces, and software architecture establishes a data transferring model to accomplish the communication between DSP and PC. In experiments, the performance on software of ENVI with that on hardware of DSP is compared. Results show that the processing speed and recognition result on DSP are better than those on ENVI. Detection results demonstrate that the strategy implemented by DSP is sufficient to enable near real-time supervised target detection.

  18. [Medical image processing based on wavelet characteristics and edge blur detection].

    PubMed

    Zhu, Baihui; Wan, Zhiping

    2014-06-01

    To solve the problems of noise interference and edge signal weakness for the existing medical image, we used two-dimensional wavelet transform to process medical images. Combined the directivity of the image edges and the correlation of the wavelet coefficients, we proposed a medical image processing algorithm based on wavelet characteristics and edge blur detection. This algorithm improved noise reduction capabilities and the edge effect due to wavelet transformation and edge blur detection. The experimental results showed that directional correlation improved edge based on wavelet transform fuzzy algorithm could effectively reduce the noise signal in the medical image and save the image edge signal. It has the advantage of the high-definition and de-noising ability. PMID:25219221

  19. Correlating multidimensional fetal heart rate variability analysis with acid-base balance at birth.

    PubMed

    Frasch, Martin G; Xu, Yawen; Stampalija, Tamara; Durosier, Lucien D; Herry, Christophe; Wang, Xiaogang; Casati, Daniela; Seely, Andrew Je; Alfirevic, Zarko; Gao, Xin; Ferrazzi, Enrico

    2014-12-01

    Fetal monitoring during labour currently fails to accurately detect acidemia. We developed a method to assess the multidimensional properties of fetal heart rate variability (fHRV) from trans-abdominal fetal electrocardiogram (fECG) during labour. We aimed to assess this novel bioinformatics approach for correlation between fHRV and neonatal pH or base excess (BE) at birth.We enrolled a prospective pilot cohort of uncomplicated singleton pregnancies at 38-42 weeks' gestation in Milan, Italy, and Liverpool, UK. Fetal monitoring was performed by standard cardiotocography. Simultaneously, with fECG (high sampling frequency) was recorded. To ensure clinician blinding, fECG information was not displayed. Data from the last 60 min preceding onset of second-stage labour were analyzed using clinically validated continuous individualized multiorgan variability analysis (CIMVA) software in 5 min overlapping windows. CIMVA allows simultaneous calculation of 101 fHRV measures across five fHRV signal analysis domains. We validated our mathematical prediction model internally with 80:20 cross-validation split, comparing results to cord pH and BE at birth.The cohort consisted of 60 women with neonatal pH values at birth ranging from 7.44 to 6.99 and BE from -0.3 to -18.7 mmol L(-1). Our model predicted pH from 30 fHRV measures (R(2) = 0.90, P < 0.001) and BE from 21 fHRV measures (R(2) = 0.77, P < 0.001).Novel bioinformatics approach (CIMVA) applied to fHRV derived from trans-abdominal fECG during labor correlated well with acid-base balance at birth. Further refinement and validation in larger cohorts are needed. These new measurements of fHRV might offer a new opportunity to predict fetal acid-base balance at birth. PMID:25407948

  20. Fiber Bragg grating sensor fatigue crack real-time monitoring based on spectrum cross-correlation analysis

    NASA Astrophysics Data System (ADS)

    Bao, Pengyu; Yuan, Mei; Dong, Shaopeng; Song, Hao; Xue, Jingfeng

    2013-01-01

    As one of the most critical tasks in structural damage monitoring, real-time fatigue crack monitoring plays an important role in improving the durability of a structure. In this paper, an online fatigue crack detection method is investigated based on the fiber Bragg grating (FBG) crack monitoring test bed (FBG-CMTB). Aiming at detecting ultrasonic spread in the structure when the crack is growing, the spectrum cross-correlation analysis algorithm and the cross-correlation function sequence are two methods that we will investigate in detail. Considering the singularity characteristic of the crack detecting signals when crack initiates, the wavelet packet analysis method is applied for feature extraction and two damage factors, crack initiation factor (CIF) and crack propagation factor (CPF), are constructed for damage initiation and propagation degree identification. To analyze the efficiency of this method, this paper presents the comparison tests based on different sensors array, FBG and acoustic emission (AE). Experimental results shows a satisfactory performance of the proposed spectrum cross-correlation analysis (SCCA) and damage feature factors on the fatigue crack online monitoring.

  1. Fuzzy logic and optical correlation-based face recognition method for patient monitoring application in home video surveillance

    NASA Astrophysics Data System (ADS)

    Elbouz, Marwa; Alfalou, Ayman; Brosseau, Christian

    2011-06-01

    Home automation is being implemented into more and more domiciles of the elderly and disabled in order to maintain their independence and safety. For that purpose, we propose and validate a surveillance video system, which detects various posture-based events. One of the novel points of this system is to use adapted Vander-Lugt correlator (VLC) and joint-transfer correlator (JTC) techniques to make decisions on the identity of a patient and his three-dimensional (3-D) positions in order to overcome the problem of crowd environment. We propose a fuzzy logic technique to get decisions on the subject's behavior. Our system is focused on the goals of accuracy, convenience, and cost, which in addition does not require any devices attached to the subject. The system permits one to study and model subject responses to behavioral change intervention because several levels of alarm can be incorporated according different situations considered. Our algorithm performs a fast 3-D recovery of the subject's head position by locating eyes within the face image and involves a model-based prediction and optical correlation techniques to guide the tracking procedure. The object detection is based on (hue, saturation, value) color space. The system also involves an adapted fuzzy logic control algorithm to make a decision based on information given to the system. Furthermore, the principles described here are applicable to a very wide range of situations and robust enough to be implementable in ongoing experiments.

  2. IUE's View of Callisto: Detection of an SO2 Absorption Correlated to Possible Torus Neutral Wind Alterations

    NASA Technical Reports Server (NTRS)

    Lane, Arthur L.; Domingue, Deborah L.

    1997-01-01

    Observations taken with the International Ultraviolet Explorer (IUE) detected a 0.28 micron absorption feature on Callisto's leading and Jupiter-facing hemispheres. This feature is similar to Europa's 0.28 micron feature, however it shows no correlation with magnetospheric ion bombardment. The strongest 0.28 micron signature is seen in the region containing the Valhalla impact. This absorption feature also shows some spatial correlation to possible neutral wind interactions, suggestive of S implantation (rather than S(sub x)) into Callisto's water ice surface, Indications of possible temporal variations (on the 10% level) are seen at other wavelengths between the 1984-1986 and the 1996 observations.

  3. How to detect Edgar Allan Poe's 'purloined letter,' or cross-correlation algorithms in digitized video images for object identification, movement evaluation, and deformation analysis

    NASA Astrophysics Data System (ADS)

    Dost, Michael; Vogel, Dietmar; Winkler, Thomas; Vogel, Juergen; Erb, Rolf; Kieselstein, Eva; Michel, Bernd

    2003-07-01

    Cross correlation analysis of digitised grey scale patterns is based on - at least - two images which are compared one to each other. Comparison is performed by means of a two-dimensional cross correlation algorithm applied to a set of local intensity submatrices taken from the pattern matrices of the reference and the comparison images in the surrounding of predefined points of interest. Established as an outstanding NDE tool for 2D and 3D deformation field analysis with a focus on micro- and nanoscale applications (microDAC and nanoDAC), the method exhibits an additional potential for far wider applications, that could be used for advancing homeland security. Cause the cross correlation algorithm in some kind seems to imitate some of the "smart" properties of human vision, this "field-of-surface-related" method can provide alternative solutions to some object and process recognition problems that are difficult to solve with more classic "object-related" image processing methods. Detecting differences between two or more images using cross correlation techniques can open new and unusual applications in identification and detection of hidden objects or objects with unknown origin, in movement or displacement field analysis and in some aspects of biometric analysis, that could be of special interest for homeland security.

  4. Multicriteria Similarity-Based Anomaly Detection Using Pareto Depth Analysis.

    PubMed

    Hsiao, Ko-Jen; Xu, Kevin S; Calder, Jeff; Hero, Alfred O

    2016-06-01

    We consider the problem of identifying patterns in a data set that exhibits anomalous behavior, often referred to as anomaly detection. Similarity-based anomaly detection algorithms detect abnormally large amounts of similarity or dissimilarity, e.g., as measured by the nearest neighbor Euclidean distances between a test sample and the training samples. In many application domains, there may not exist a single dissimilarity measure that captures all possible anomalous patterns. In such cases, multiple dissimilarity measures can be defined, including nonmetric measures, and one can test for anomalies by scalarizing using a nonnegative linear combination of them. If the relative importance of the different dissimilarity measures are not known in advance, as in many anomaly detection applications, the anomaly detection algorithm may need to be executed multiple times with different choices of weights in the linear combination. In this paper, we propose a method for similarity-based anomaly detection using a novel multicriteria dissimilarity measure, the Pareto depth. The proposed Pareto depth analysis (PDA) anomaly detection algorithm uses the concept of Pareto optimality to detect anomalies under multiple criteria without having to run an algorithm multiple times with different choices of weights. The proposed PDA approach is provably better than using linear combinations of the criteria, and shows superior performance on experiments with synthetic and real data sets. PMID:26336154

  5. Detecting Causality In Space Plasmas With Entropy Based Measures

    NASA Astrophysics Data System (ADS)

    Johnson, J. R.; Wing, S.

    2008-12-01

    Understanding causal relationships in space plasmas is a key ingredient of modeling, but can often be difficult to establish. Frequently, causality is investigated by looking at the cross-correlation and checking for a shift in the peak as a function of lag time or by examining differences in the forward and backwards directions. Some of the shortcomings of this method can be illustrated by cross-correlations that exhibit multiple peaks that are large in the non-causal direction and causal systems that do not exhibit asymmetries in the cross-correlation. Furthermore, cross-correlations only reveal linear dependency and may not be as useful for a nonlinear storage and release dynamics (such as might be expected for the magnetospheric response to the solar wind). An alternative choice for studying causality is the one-sided transfer entropy which is highly directional and accounts for static internal correlations so that it is possible to examine whether two variables are driven by a common driver or whether they are causally connected. We apply the transfer entropy to several test systems to illustrate its utility for detecting causality and to space data to illustrate causality in space systems with examples from solar wind-magnetosphere coupling.

  6. Autoregressive model based algorithm for correcting motion and serially correlated errors in fNIRS

    PubMed Central

    Barker, Jeffrey W.; Aarabi, Ardalan; Huppert, Theodore J.

    2013-01-01

    Systemic physiology and motion-induced artifacts represent two major sources of confounding noise in functional near infrared spectroscopy (fNIRS) imaging that can reduce the performance of analyses and inflate false positive rates (i.e., type I errors) of detecting evoked hemodynamic responses. In this work, we demonstrated a general algorithm for solving the general linear model (GLM) for both deconvolution (finite impulse response) and canonical regression models based on designing optimal pre-whitening filters using autoregressive models and employing iteratively reweighted least squares. We evaluated the performance of the new method by performing receiver operating characteristic (ROC) analyses using synthetic data, in which serial correlations, motion artifacts, and evoked responses were controlled via simulations, as well as using experimental data from children (3–5 years old) as a source baseline physiological noise and motion artifacts. The new method outperformed ordinary least squares (OLS) with no motion correction, wavelet based motion correction, or spline interpolation based motion correction in the presence of physiological and motion related noise. In the experimental data, false positive rates were as high as 37% when the estimated p-value was 0.05 for the OLS methods. The false positive rate was reduced to 5–9% with the proposed method. Overall, the method improves control of type I errors and increases performance when motion artifacts are present. PMID:24009999

  7. Detection of hydrogen attack in base metal and weld HAZ

    SciTech Connect

    Birring, A.S.; Elliot, J.; Hsiao, C.P.

    1995-12-01

    Hydrogen attack is known to occur in C-1/2Mo steels operating at high temperature and pressure in the hydrogen environment. The attack occurs in the base metal as well as in the weld heat affected zone (HAZ) of vessels and pipes. Hydrogen attack reduces the strength and toughness of steel and, if left undetected, can lead to component failure. Failures can be avoided by timely application of reliable and sensitive nondestructive techniques. Ultrasonic techniques were developed and applied to detect hydrogen attack in both the base metal and weld HAZ attack. Ultrasonic backscatter and velocity ratio techniques were applied for detection of base metal attack. These techniques are, however, not suitable for detection of HAZ attack. Conventional shear wave examination is currently used for HAZ inspection. This method can detect large cracks but is not sensitive to detect microcracks produced by hydrogen attack. A combination of two techniques was developed for detection of HAZ attack. These techniques are: contact focused angle beam S-wave and pitch-catch L-wave. The first technique focuses the beam using an acoustic lens while the second technique uses the intersection point of the two pitch-catch beam axes to illuminate the HAZ zone. Both the focused and pitch-catch techniques were applied on samples with simulated HAZ attack. The techniques were successful in detecting simulated attack.

  8. Hierarchical clustering of EMD based interest points for road sign detection

    NASA Astrophysics Data System (ADS)

    Khan, Jesmin; Bhuiyan, Sharif; Adhami, Reza

    2014-04-01

    This paper presents an automatic road traffic signs detection and recognition system based on hierarchical clustering of interest points and joint transform correlation. The proposed algorithm consists of the three following stages: interest points detection, clustering of those points and similarity search. At the first stage, good discriminative, rotation and scale invariant interest points are selected from the image edges based on the 1-D empirical mode decomposition (EMD). We propose a two-step unsupervised clustering technique, which is adaptive and based on two criterion. In this context, the detected points are initially clustered based on the stable local features related to the brightness and color, which are extracted using Gabor filter. Then points belonging to each partition are reclustered depending on the dispersion of the points in the initial cluster using position feature. This two-step hierarchical clustering yields the possible candidate road signs or the region of interests (ROIs). Finally, a fringe-adjusted joint transform correlation (JTC) technique is used for matching the unknown signs with the existing known reference road signs stored in the database. The presented framework provides a novel way to detect a road sign from the natural scenes and the results demonstrate the efficacy of the proposed technique, which yields a very low false hit rate.

  9. Detection and correction of blinking bias in image correlation transport measurements of quantum dot tagged macromolecules.

    PubMed

    Durisic, Nela; Bachir, Alexia I; Kolin, David L; Hebert, Benedict; Lagerholm, B Christoffer; Grutter, Peter; Wiseman, Paul W

    2007-08-15

    Semiconductor nanocrystals or quantum dots (QDs) are becoming widely used as fluorescent labels for biological applications. Here we demonstrate that fluorescence fluctuation analysis of their diffusional mobility using temporal image correlation spectroscopy is highly susceptible to systematic errors caused by fluorescence blinking of the nanoparticles. Temporal correlation analysis of fluorescence microscopy image time series of streptavidin-functionalized (CdSe)ZnS QDs freely diffusing in two dimensions shows that the correlation functions are fit well to a commonly used diffusion decay model, but the transport coefficients can have significant systematic errors in the measurements due to blinking. Image correlation measurements of the diffusing QD samples measured at different laser excitation powers and analysis of computer simulated image time series verified that the effect we observe is caused by fluorescence intermittency. We show that reciprocal space image correlation analysis can be used for mobility measurements in the presence of blinking emission because it separates the contributions of fluctuations due to photophysics from those due to transport. We also demonstrate application of the image correlation methods for measurement of the diffusion coefficient of glycosyl phosphatidylinositol-anchored proteins tagged with QDs as imaged on living fibroblasts. PMID:17526586

  10. SENNA: device for explosives' detection based on nanosecond neutron analysis

    NASA Astrophysics Data System (ADS)

    Kuznetsov, Andrey; Evsenin, Alexey; Osetrov, Oleg; Vakhtin, Dmitry; Gorshkov, Igor

    2006-05-01

    Portable device for explosives' detection (SENNA) based on Nanosecond Neutron Analysis (NNA) / Associated Particles Technique (APT) has been created and tested. SENNA is a single suitcase weighting 35 kg; it is remotely controlled from any PC-compatible computer. Inside is an APT neutron generator with a 3×3 matrix of semiconductor detectors of associated alpha-particles, two BGO-based detectors of gamma-rays, fully-digital data acquisition electronics, data analysis and decision-making software, and batteries. Detection technology is based on determining chemical composition of the concealed substance by analyzing secondary gamma-rays from interaction of tagged fast neutrons with its material. A combination of position-sensitive alpha-detector and time-of-flight analysis allows one to determine the location of the detected material within the inspected volume and its approximate mass. Fully digital data acquisition electronics is capable of performing alpha-gamma coincidence analysis at very high counting rates, which leads to reduction of the detection time down to dozens of seconds. SENNA's scenario-driven automatic decisionmaking algorithm based of "fuzzy logic" mechanism allows one to detect not only standard military or industrial explosives, but also improvised explosives (including those containing no nitrogen), even if their chemical composition differs from that of standard explosives. SENNA can also be "trained" to detect other hazardous materials, such as chemical/toxic materials, if their chemical composition is in any way different from that of the surrounding materials.

  11. Noise-immune complex correlation for optical coherence angiography based on standard and Jones matrix optical coherence tomography

    PubMed Central

    Makita, Shuichi; Kurokawa, Kazuhiro; Hong, Young-Joo; Miura, Masahiro; Yasuno, Yoshiaki

    2016-01-01

    This paper describes a complex correlation mapping algorithm for optical coherence angiography (cmOCA). The proposed algorithm avoids the signal-to-noise ratio dependence and exhibits low noise in vasculature imaging. The complex correlation coefficient of the signals, rather than that of the measured data are estimated, and two-step averaging is introduced. Algorithms of motion artifact removal based on non perfusing tissue detection using correlation are developed. The algorithms are implemented with Jones-matrix OCT. Simultaneous imaging of pigmented tissue and vasculature is also achieved using degree of polarization uniformity imaging with cmOCA. An application of cmOCA to in vivo posterior human eyes is presented to demonstrate that high-contrast images of patients’ eyes can be obtained. PMID:27446673

  12. Fluorescence detection of single molecules using pulsed near-field optical excitation and time correlated photon counting

    SciTech Connect

    Ambrose, W.P.; Goodwin, P.M.; Martin, J.C.; Keller, R.A.

    1994-03-01

    Pulsed excitation, time correlated single photon counting and time gated detection are used in near-field optical microscopy to enhance fluorescence images and measure the fluorescence lifetimes of single molecules of Rhodamine 6G on silica surfaces. Time gated detection is used to reject prompt scattered background and to improve the image signal to noise ratio. The excited state lifetime of a single Rhodamine 6G molecule is found to depend on the position of the near-field probe. We attribute the lifetime variations to spontaneous emission rate alterations by the fluorescence reflected from and quenching by the aluminum coated probe.

  13. A determinant-based criterion for working correlation structure selection in generalized estimating equations.

    PubMed

    Jaman, Ajmery; Latif, Mahbub A H M; Bari, Wasimul; Wahed, Abdus S

    2016-05-20

    In generalized estimating equations (GEE), the correlation between the repeated observations on a subject is specified with a working correlation matrix. Correct specification of the working correlation structure ensures efficient estimators of the regression coefficients. Among the criteria used, in practice, for selecting working correlation structure, Rotnitzky-Jewell, Quasi Information Criterion (QIC) and Correlation Information Criterion (CIC) are based on the fact that if the assumed working correlation structure is correct then the model-based (naive) and the sandwich (robust) covariance estimators of the regression coefficient estimators should be close to each other. The sandwich covariance estimator, used in defining the Rotnitzky-Jewell, QIC and CIC criteria, is biased downward and has a larger variability than the corresponding model-based covariance estimator. Motivated by this fact, a new criterion is proposed in this paper based on the bias-corrected sandwich covariance estimator for selecting an appropriate working correlation structure in GEE. A comparison of the proposed and the competing criteria is shown using simulation studies with correlated binary responses. The results revealed that the proposed criterion generally performs better than the competing criteria. An example of selecting the appropriate working correlation structure has also been shown using the data from Madras Schizophrenia Study. Copyright © 2015 John Wiley & Sons, Ltd. PMID:26626276

  14. Highly sensitive fluorescence resonance energy transfer (FRET)-based nanosensor for rapid detection of clenbuterol

    NASA Astrophysics Data System (ADS)

    Nghia Nguyen, Duc; Ngo, Trinh Tung; Liem Nguyen, Quang

    2012-09-01

    In this study we investigate the fabrication of a fluorescence resonance energy transfer (FRET)-based nanosensor for the detection of clenbuterol. The nanosensor consists of CdTe quantum dots coated by clenbuterol recognizable agent naphthol and diazotized clenbuterol. Changes in maximal photoluminescent intensities of the nanosensor were utilized to measure clenbuterol concentrations. The maximal photoluminescent intensities of the nanosensor were found to decrease with increasing clenbuterol concentrations, following a linear correlation. We have successfully fabricated a nanosensor for detection of clenbuterol with sensitivity up to 10 pg ml‑1.

  15. Graph-based pigment network detection in skin images

    NASA Astrophysics Data System (ADS)

    Sadeghi, M.; Razmara, M.; Ester, M.; Lee, T. K.; Atkins, M. S.

    2010-03-01

    Detecting pigmented network is a crucial step for melanoma diagnosis. In this paper, we present a novel graphbased pigment network detection method that can find and visualize round structures belonging to the pigment network. After finding sharp changes of the luminance image by an edge detection function, the resulting binary image is converted to a graph, and then all cyclic sub-graphs are detected. Theses cycles represent meshes that belong to the pigment network. Then, we create a new graph of the cyclic structures based on their distance. According to the density ratio of the new graph of the pigment network, the image is classified as "Absent" or "Present". Being Present means that a pigment network is detected in the skin lesion. Using this approach, we achieved an accuracy of 92.6% on five hundred unseen images.

  16. Nanomaterial-Based Biosensors for Detection of Pesticides and Explosives

    SciTech Connect

    Wang, Jun; Lin, Yuehe

    2009-01-01

    In this chapter, we describe nanomaterial-based biosensors for detecting OP pesticides and explosives. CNTs and functionalized silica nanoparticles have been chosen for this study. The biosensors were combined with the flow-injection system, providing great advantages for onsite, real-time, and continuous detection of environmental pollutants such as OPs and TNT. The sensors take advantage of the electrocatalytic properties of CNTs, which makes it feasible to achieve a sensitive electrochemical detection of the products from enzymatic reactions at low potential. This approach uses a large aspect ratio of silica nanoparticles, which can be used as a carrier for loading a large amount of electroactive species, such as poly(guanine), for amplified detection of explosives. These methods offer a new environmental monitoring tool for rapid, inexpensive, and highly sensitive detection of OPs or TNT compounds.

  17. Edge detection of noisy images based on cellular neural networks

    NASA Astrophysics Data System (ADS)

    Li, Huaqing; Liao, Xiaofeng; Li, Chuandong; Huang, Hongyu; Li, Chaojie

    2011-09-01

    This paper studies a technique employing both cellular neural networks (CNNs) and linear matrix inequality (LMI) for edge detection of noisy images. Our main work focuses on training templates of noise reduction and edge detection CNNs. Based on the Lyapunov stability theorem, we derive a criterion for global asymptotical stability of a unique equilibrium of the noise reduction CNN. Then we design an approach to train edge detection templates, and this approach can detect the edge precisely and efficiently, i.e., by only one iteration. Finally, we illustrate performance of the proposed methodology from the aspect of peak signal to noise ratio (PSNR) through computer simulations. Moreover, some comparisons are also given to prove that our method outperforms classical operators in gray image edge detection.

  18. Detecting circular and rectangular particles based on geometric feature detection in electron micrographs.

    PubMed

    Yu, Zeyun; Bajaj, Chandrajit

    2004-01-01

    Accurate and automatic particle detection from cryo-electron microscopy (cryo-EM images) is very important for high-resolution reconstruction of large macromolecular structures. In this paper, we present a method for particle picking based on shape feature detection. Two fundamental concepts of computational geometry, namely, the distance transform and the Voronoi diagram, are used for detection of critical features as well as for accurate location of particles from the images or micrographs. Unlike the conventional template-matching methods, our approach detects the particles based on their boundary features instead of intensities. The geometric features derived from the boundaries provide an efficient way for locating particles quickly and accurately, which avoids a brute-force searching for the best position/orientation. Our approach is fully automatic and has been successfully applied to detect particles with approximately circular or rectangular shapes (e.g., KLH particles). Particle detection can be enhanced by multiple sets of parameters used in edge detection and/or by anisotropic filtering. We also discuss the extension of this approach to other types of particles with certain geometric features. PMID:15065684

  19. Detecting a stochastic background of gravitational waves in the presence of non-Gaussian noise: A performance of generalized cross-correlation statistic

    SciTech Connect

    Himemoto, Yoshiaki; Hiramatsu, Takashi; Taruya, Atsushi; Kudoh, Hideaki

    2007-01-15

    We discuss a robust data analysis method to detect a stochastic background of gravitational waves in the presence of non-Gaussian noise. In contrast to the standard cross-correlation (SCC) statistic frequently used in the stochastic background searches, we consider a generalized cross-correlation (GCC) statistic, which is nearly optimal even in the presence of non-Gaussian noise. The detection efficiency of the GCC statistic is investigated analytically, particularly focusing on the statistical relation between the false-alarm and the false-dismissal probabilities, and the minimum detectable amplitude of gravitational-wave signals. We derive simple analytic formulas for these statistical quantities. The robustness of the GCC statistic is clarified based on these formulas, and one finds that the detection efficiency of the GCC statistic roughly corresponds to the one of the SCC statistic neglecting the contribution of non-Gaussian tails. This remarkable property is checked by performing the Monte Carlo simulations and successful agreement between analytic and simulation results was found.

  20. Stratification-Based Outlier Detection over the Deep Web

    PubMed Central

    Xian, Xuefeng; Zhao, Pengpeng; Sheng, Victor S.; Fang, Ligang; Gu, Caidong; Yang, Yuanfeng; Cui, Zhiming

    2016-01-01

    For many applications, finding rare instances or outliers can be more interesting than finding common patterns. Existing work in outlier detection never considers the context of deep web. In this paper, we argue that, for many scenarios, it is more meaningful to detect outliers over deep web. In the context of deep web, users must submit queries through a query interface to retrieve corresponding data. Therefore, traditional data mining methods cannot be directly applied. The primary contribution of this paper is to develop a new data mining method for outlier detection over deep web. In our approach, the query space of a deep web data source is stratified based on a pilot sample. Neighborhood sampling and uncertainty sampling are developed in this paper with the goal of improving recall and precision based on stratification. Finally, a careful performance evaluation of our algorithm confirms that our approach can effectively detect outliers in deep web. PMID:27313603

  1. Enhancing Community Detection By Affinity-based Edge Weighting Scheme

    SciTech Connect

    Yoo, Andy; Sanders, Geoffrey; Henson, Van; Vassilevski, Panayot

    2015-10-05

    Community detection refers to an important graph analytics problem of finding a set of densely-connected subgraphs in a graph and has gained a great deal of interest recently. The performance of current community detection algorithms is limited by an inherent constraint of unweighted graphs that offer very little information on their internal community structures. In this paper, we propose a new scheme to address this issue that weights the edges in a given graph based on recently proposed vertex affinity. The vertex affinity quantifies the proximity between two vertices in terms of their clustering strength, and therefore, it is ideal for graph analytics applications such as community detection. We also demonstrate that the affinity-based edge weighting scheme can improve the performance of community detection algorithms significantly.

  2. a Uav-Based ROE Deer Fawn Detection System

    NASA Astrophysics Data System (ADS)

    Israel, M.

    2011-09-01

    This paper presents a UAV based remote sensing system for the detection of fawns in the meadows. There is a high demand because during pasture mowing many wild animals, especially roe deer fawns are killed by mowing machines. The system was tested in several real situations especially with differing weather and iluminating conditions. Its primary sensor is a lightweight thermal infrared camera. The images are captured onboard of the flight system and also transmitted as analog video stream to the ground station, where the user can follow the camera live stream on a monitor for manual animal detection. Beside a high detection rate a fast workflow is another very important objective for this application. Therefore a waypoint planning software was developed that accelerates the workflow. At adequate illuminating and weather conditions the presented UAV-based fawn detection via thermal imaging is a comfortable, fast and reliable method.

  3. The Unknown Computer Viruses Detection Based on Similarity

    NASA Astrophysics Data System (ADS)

    Liu, Zhongda; Nakaya, Naoshi; Koui, Yuuji

    New computer viruses are continually being generated and they cause damage all over the world. In general, current anti-virus software detects viruses by matching a pattern based on the signature; thus, unknown viruses without any signature cannot be detected. Although there are some static analysis technologies that do not depend on signatures, virus writers often use code obfuscation techniques, which make it difficult to execute a code analysis. As is generally known, unknown viruses and known viruses share a common feature. In this paper we propose a new static analysis technology that can circumvent code obfuscation to extract the common feature and detect unknown viruses based on similarity. The results of evaluation experiments demonstrated that this technique is able to detect unknown viruses without false positives.

  4. A dynamic bead-based microarray for parallel DNA detection

    NASA Astrophysics Data System (ADS)

    Sochol, R. D.; Casavant, B. P.; Dueck, M. E.; Lee, L. P.; Lin, L.

    2011-05-01

    A microfluidic system has been designed and constructed by means of micromachining processes to integrate both microfluidic mixing of mobile microbeads and hydrodynamic microbead arraying capabilities on a single chip to simultaneously detect multiple bio-molecules. The prototype system has four parallel reaction chambers, which include microchannels of 18 × 50 µm2 cross-sectional area and a microfluidic mixing section of 22 cm length. Parallel detection of multiple DNA oligonucleotide sequences was achieved via molecular beacon probes immobilized on polystyrene microbeads of 16 µm diameter. Experimental results show quantitative detection of three distinct DNA oligonucleotide sequences from the Hepatitis C viral (HCV) genome with single base-pair mismatch specificity. Our dynamic bead-based microarray offers an effective microfluidic platform to increase parallelization of reactions and improve microbead handling for various biological applications, including bio-molecule detection, medical diagnostics and drug screening.

  5. Stratification-Based Outlier Detection over the Deep Web.

    PubMed

    Xian, Xuefeng; Zhao, Pengpeng; Sheng, Victor S; Fang, Ligang; Gu, Caidong; Yang, Yuanfeng; Cui, Zhiming

    2016-01-01

    For many applications, finding rare instances or outliers can be more interesting than finding common patterns. Existing work in outlier detection never considers the context of deep web. In this paper, we argue that, for many scenarios, it is more meaningful to detect outliers over deep web. In the context of deep web, users must submit queries through a query interface to retrieve corresponding data. Therefore, traditional data mining methods cannot be directly applied. The primary contribution of this paper is to develop a new data mining method for outlier detection over deep web. In our approach, the query space of a deep web data source is stratified based on a pilot sample. Neighborhood sampling and uncertainty sampling are developed in this paper with the goal of improving recall and precision based on stratification. Finally, a careful performance evaluation of our algorithm confirms that our approach can effectively detect outliers in deep web. PMID:27313603

  6. Knowledge-based architecture for airborne mine and minefield detection

    NASA Astrophysics Data System (ADS)

    Agarwal, Sanjeev; Menon, Deepak; Swonger, C. W.

    2004-09-01

    One of the primary lessons learned from airborne mid-wave infrared (MWIR) based mine and minefield detection research and development over the last few years has been the fact that no single algorithm or static detection architecture is able to meet mine and minefield detection performance specifications. This is true not only because of the highly varied environmental and operational conditions under which an airborne sensor is expected to perform but also due to the highly data dependent nature of sensors and algorithms employed for detection. Attempts to make the algorithms themselves more robust to varying operating conditions have only been partially successful. In this paper, we present a knowledge-based architecture to tackle this challenging problem. The detailed algorithm architecture is discussed for such a mine/minefield detection system, with a description of each functional block and data interface. This dynamic and knowledge-driven architecture will provide more robust mine and minefield detection for a highly multi-modal operating environment. The acquisition of the knowledge for this system is predominantly data driven, incorporating not only the analysis of historical airborne mine and minefield imagery data collection, but also other "all source data" that may be available such as terrain information and time of day. This "all source data" is extremely important and embodies causal information that drives the detection performance. This information is not being used by current detection architectures. Data analysis for knowledge acquisition will facilitate better understanding of the factors that affect the detection performance and will provide insight into areas for improvement for both sensors and algorithms. Important aspects of this knowledge-based architecture, its motivations and the potential gains from its implementation are discussed, and some preliminary results are presented.

  7. Application of spatial cross correlation to detection of migration of submarine sand dunes

    NASA Astrophysics Data System (ADS)

    Duffy, Garret P.; Hughes-Clarke, John E.

    2005-12-01

    Knowledge of migration rates of bedforms provides an indirect indication of the behavior of tidally averaged bottom currents, enables optimization of hydrographic survey frequency and may enable calculation of bedload transport rate. To measure bedform migration rate, we test the use of spatial correlation as a measurement method, which quantifies and locates a region of maximum similarity between two spatial variables. For the latter, we use consecutive eight-bit images of spatial gradient, derived from bathymetric digital terrain models, carrying out the correlation over this representation of the shape of the seabed rather than the bathymetric surface. The digital terrain models were compiled from six repeat multibeam surveys of a headland-associated bank near Saint John, New Brunswick, with a roughly 30-day interval. Vectors are drawn depicting the movement of a sand dune at time t0 toward a point in the spatial correlation array at a later time, t1. A number of different techniques of picking the end of the migration vector were used. The sinuosity of the dune crest at the scale of the correlation window has an impact on which migration vector is the better pick. Averaging of migration vectors from consecutive epochs diminishes random errors in the correlation picks using any single pair of images and creates a more accurate picture of the migration field. Migration rates and crest-relative migration directions vary substantially across the sand bank, reflecting the high gradients in bottom shear stress around the headland.

  8. Spectral evolution of gamma-ray bursts detected by the SIGNE experiment. 1: Correlation between intensity and spectral hardness

    NASA Technical Reports Server (NTRS)

    Kargatis, Vincent E.; Liang, Edison P.; Hurley, Kevin C.; Barat, C.; Eveno, E.; Niel, M.

    1994-01-01

    We study the continuum spectral evolution of 16 gamma-ray bursts detected by the Franco-Soviet SIGNE experiment in 1981-1982 by fitting time resolved (0.5 s) spectra in count space with simple thermal bremsstrahlung and synchrotron models. We find that there is no single characteristic of spectral evolution: we see hard-to-soft, soft-to-hard, luminosity-hardness tracking, and chaotic evolution. We perform correlation studies between instantaneous burst intensity and spectral temperature for seven bursts. While we basically confirm the existence of a correlation between these variables as originally claimed by Golenetskii et al. (1983) we find higher values and a broader range of correlation indices.

  9. Sonoclot(®)-based method to detect iron enhanced coagulation.

    PubMed

    Nielsen, Vance G; Henderson, Jon

    2016-07-01

    Thrombelastographic methods have been recently introduced to detect iron mediated hypercoagulability in settings such as sickle cell disease, hemodialysis, mechanical circulatory support, and neuroinflammation. However, these inflammatory situations may have heme oxygenase-derived, coexistent carbon monoxide present, which also enhances coagulation as assessed by the same thrombelastographic variables that are affected by iron. This brief report presents a novel, Sonoclot-based method to detect iron enhanced coagulation that is independent of carbon monoxide influence. Future investigation will be required to assess the sensitivity of this new method to detect iron mediated hypercoagulability in clinical settings compared to results obtained with thrombelastographic techniques. PMID:26497986

  10. Fiber-Optic Based Compact Gas Leak Detection System

    NASA Technical Reports Server (NTRS)

    deGroot, Wim A.

    1995-01-01

    A propellant leak detection system based on Raman scattering principles is introduced. The proposed system is flexible and versatile as the result of the use of optical fibers. It is shown that multiple species can be monitored simultaneously. In this paper oxygen, nitrogen, carbon monoxide, and hydrogen are detected and monitored. The current detection sensitivity for both hydrogen and carbon monoxide is 1% partial pressure at ambient conditions. The sensitivity for oxygen and nitrogen is 0.5% partial pressure. The response time to changes in species concentration is three minutes. This system can be used to monitor multiple species at several locations.

  11. Estimation and inference on correlations between biomarkers with repeated measures and left-censoring due to minimum detection levels

    PubMed Central

    Xie, Xianhong; Xue, Xiaonan; Gange, Stephen J.; Strickler, Howard D.; Kim, Mimi Y.

    2013-01-01

    Statistical approaches for estimating and drawing inference on the correlation between two biomarkers which are repeatedly assessed over time and subject to left-censoring due to minimum detection levels are lacking. We propose a linear mixed-effects model and estimate the parameters with the Monte Carlo Expectation Maximization (MCEM) method. Inferences regarding the model parameters and the correlation between the biomarkers are performed by applying Louis’s method and the delta method. Simulation studies were conducted to compare the proposed MCEM method with existing methods including the MLE method, the multiple imputation (MI) method, and two widely used ad hoc approaches: replacing the censored values with the detection limit (DL) or with half of the detection limit (HDL). The results show that the performance of the MCEM with respect to relative bias and coverage probability for the 95% confidence interval is superior to the DL and HDL approaches and exceeds that of the MI method at medium to high levels of censoring, and the standard error estimates from the MCEM method are close to ideal. The MLE method can estimate the parameters accurately; however, a non-positive definite information matrix can occur so that the variances are not estimable. These five methods are illustrated with data from a longitudinal HIV study to estimate and draw inference on the correlation between HIV RNA levels measured in plasma and in cervical secretions at multiple time points. PMID:22714546

  12. Joint transform correlator based on CIELAB model with encoding technique for color pattern recognition

    NASA Astrophysics Data System (ADS)

    Lin, Tiengsheng; Chen, Chulung; Liu, Chengyu; Chen, Yuming

    2010-10-01

    The CIELAB standard color vision model instead of the traditional RGB color model is utilized for polychromatic pattern recognition. The image encoding technique is introduced. The joint transform correlator is set to be the optical configuration. To achieve the distortion invariance in discrimination processes, we have used the minimum average correlation energy approach to yield sharp correlation peak. From the numerical results, it is found that the recognition ability based on CIELAB color specification system is accepted.

  13. Modified friction factor correlation for CICC's based on a porous media analogy

    NASA Astrophysics Data System (ADS)

    Lewandowska, Monika; Bagnasco, Maurizio

    2011-09-01

    A modified correlation for the bundle friction factor in CICC's based on a porous media analogy is presented. The correlation is obtained by the analysis of the collected pressure drop data measured for 23 CICC's. The friction factors predicted by the proposed correlation are compared with those resulting from the pressure drop data for two CICC's measured recently using cryogenic helium in the SULTAN test facility at EPFL-CRPP.

  14. Vision-Based People Detection System for Heavy Machine Applications

    PubMed Central

    Fremont, Vincent; Bui, Manh Tuan; Boukerroui, Djamal; Letort, Pierrick

    2016-01-01

    This paper presents a vision-based people detection system for improving safety in heavy machines. We propose a perception system composed of a monocular fisheye camera and a LiDAR. Fisheye cameras have the advantage of a wide field-of-view, but the strong distortions that they create must be handled at the detection stage. Since people detection in fisheye images has not been well studied, we focus on investigating and quantifying the impact that strong radial distortions have on the appearance of people, and we propose approaches for handling this specificity, adapted from state-of-the-art people detection approaches. These adaptive approaches nevertheless have the drawback of high computational cost and complexity. Consequently, we also present a framework for harnessing the LiDAR modality in order to enhance the detection algorithm for different camera positions. A sequential LiDAR-based fusion architecture is used, which addresses directly the problem of reducing false detections and computational cost in an exclusively vision-based system. A heavy machine dataset was built, and different experiments were carried out to evaluate the performance of the system. The results are promising, in terms of both processing speed and performance. PMID:26805838

  15. Automatic food intake detection based on swallowing sounds

    PubMed Central

    Makeyev, Oleksandr; Lopez-Meyer, Paulo; Schuckers, Stephanie; Besio, Walter; Sazonov, Edward

    2012-01-01

    This paper presents a novel fully automatic food intake detection methodology, an important step toward objective monitoring of ingestive behavior. The aim of such monitoring is to improve our understanding of eating behaviors associated with obesity and eating disorders. The proposed methodology consists of two stages. First, acoustic detection of swallowing instances based on mel-scale Fourier spectrum features and classification using support vector machines is performed. Principal component analysis and a smoothing algorithm are used to improve swallowing detection accuracy. Second, the frequency of swallowing is used as a predictor for detection of food intake episodes. The proposed methodology was tested on data collected from 12 subjects with various degrees of adiposity. Average accuracies of >80% and >75% were obtained for intra-subject and inter-subject models correspondingly with a temporal resolution of 30s. Results obtained on 44.1 hours of data with a total of 7305 swallows show that detection accuracies are comparable for obese and lean subjects. They also suggest feasibility of food intake detection based on swallowing sounds and potential of the proposed methodology for automatic monitoring of ingestive behavior. Based on a wearable non-invasive acoustic sensor the proposed methodology may potentially be used in free-living conditions. PMID:23125873

  16. Deceiving entropy-based DoS detection

    NASA Astrophysics Data System (ADS)

    Özçelik, Ä.°lker; Brooks, Richard R.

    2014-06-01

    Denial of Service (DoS) attacks disable network services for legitimate users. A McAfee report shows that eight out of ten Critical Infrastructure Providers (CIPs) surveyed had a significant Distributed DoS (DDoS) attack in 2010.1 Researchers proposed many approaches for detecting these attacks in the past decade. Anomaly based DoS detection is the most common. In this approach, the detector uses statistical features; such as the entropy of incoming packet header fields like source IP addresses or protocol type. It calculates the observed statistical feature and triggers an alarm if an extreme deviation occurs. However, intrusion detection systems (IDS) using entropy based detection can be fooled by spoofing. An attacker can sniff the network to collect header field data of network packets coming from distributed nodes on the Internet and fuses them to calculate the entropy of normal background traffic. Then s/he can spoof attack packets to keep the entropy value in the expected range during the attack. In this study, we present a proof of concept entropy spoofing attack that deceives entropy based detection approaches. Our preliminary results show that spoofing attacks cause significant detection performance degradation.

  17. Vision-Based People Detection System for Heavy Machine Applications.

    PubMed

    Fremont, Vincent; Bui, Manh Tuan; Boukerroui, Djamal; Letort, Pierrick

    2016-01-01

    This paper presents a vision-based people detection system for improving safety in heavy machines. We propose a perception system composed of a monocular fisheye camera and a LiDAR. Fisheye cameras have the advantage of a wide field-of-view, but the strong distortions that they create must be handled at the detection stage. Since people detection in fisheye images has not been well studied, we focus on investigating and quantifying the impact that strong radial distortions have on the appearance of people, and we propose approaches for handling this specificity, adapted from state-of-the-art people detection approaches. These adaptive approaches nevertheless have the drawback of high computational cost and complexity. Consequently, we also present a framework for harnessing the LiDAR modality in order to enhance the detection algorithm for different camera positions. A sequential LiDAR-based fusion architecture is used, which addresses directly the problem of reducing false detections and computational cost in an exclusively vision-based system. A heavy machine dataset was built, and different experiments were carried out to evaluate the performance of the system. The results are promising, in terms of both processing speed and performance. PMID:26805838

  18. Detection of polyomaviral DNA in clinical samples from immunocompromised patients: correlation with clinical disease.

    PubMed

    Perrons, C J; Fox, J D; Lucas, S B; Brink, N S; Tedder, R S; Miller, R F

    1996-05-01

    Clinical samples from immunocompromised patients were screened for polyomaviral sequences by nested polymerase chain reaction (PCR) to evaluate the association of these viral infections with progressive multifocal leukoencephalopathy (PML). JC virus (JCV) DNA was detected in 19 of 23 CSF samples and all four brain samples from patients with PML. Neither BK virus (BKV) nor simian virus 40 (SV40) DNA were detected in these samples. No evidence was found to support the hypothesis that polyomaviral DNA is present in the central nervous system of immunosuppressed patients without PML (CSF n = 67, brain n = 19). JCV DNA was not detected in any peripheral blood sample included in this study. JCV DNA was detected in urine from three of eight patients with PML, but was also amplified from three of 29 urine samples from patients without PML, JCV, and not SV40 or BKV, was associated with PML in this study. PMID:8793709

  19. Sensitive giant magnetoresistive-based immunoassay for multiplex mycotoxin detection.

    PubMed

    Mak, Andy C; Osterfeld, Sebastian J; Yu, Heng; Wang, Shan X; Davis, Ronald W; Jejelowo, Olufisayo A; Pourmand, Nader

    2010-03-15

    Rapid and multiplexed measurement is vital in the detection of food-borne pathogens. While highly specific and sensitive, traditional immunochemical assays such as enzyme-linked immunosorbent assays (ELISAs) often require expensive read-out equipment (e.g. fluorescent labels) and lack the capability of multiplex detection. By combining the superior specificity of immunoassays with the sensitivity and simplicity of magnetic detection, we have developed a novel multiplex magnetic nanotag-based detection platform for mycotoxins that functions on a sub-picomolar concentration level. Unlike fluorescent labels, magnetic nanotags (MNTs) can be detected with inexpensive giant magnetoresistive (GMR) sensors such as spin-valve sensors. In the system presented here, each spin-valve sensor has an active area of 90 microm x 90 microm, arranged in an 8 x 8 array. Sample is added to the antibody-immobilized sensor array prior to the addition of the biotinylated detection antibody. The sensor response is recorded in real time upon the addition of streptavidin-linked MNTs on the chip. Here we demonstrate the simultaneous detection of multiple mycotoxins (aflatoxins B(1), zearalenone and HT-2) and show that a detection limit of 50 pg/mL can be achieved. PMID:20047828

  20. Broad base biological assay using liquid based detection assays

    SciTech Connect

    Milanovich, F; Albala, J; Colston, B; Langlois, R; Venkateswaren, K

    2000-10-31

    The release of a biological agent by terrorists represents a serious threat to the safety of US citizens. At present there are over 50 pathogens and toxins on various agency threat lists. Most of these pathogens are rarely seen by public health personnel so the ability to rapidly identify their infection is limited. Since many pathogenic infections have symptomatic delays as long as several days, effective treatment is often compromised. This translates into two major deficiencies in our ability to counter biological terrorism (1) the lack of any credible technology to rapidly detect and identify all the pathogens or toxins on current threat lists and (2) the lack of a credible means to rapidly diagnose thousands of potential victims. In this SI we are developing a rapid, flexible, inexpensive, high throughput, and deeply multiplex-capable biological assay technology. The technology, which we call the Liquid Array (LA), utilizes optical encoding of small diameter beads which serve as the templates for biological capture assays. Once exposed to a fluid sample these beads can be identified and probed for target pathogens at rates of several thousand beads per second. Since each bead can be separately identified, one can perform parallel assays by assigning a different assay to each bead in the encoded set. The goal for this development is a detection technology capable of simultaneously identifying 100s of different bioagents and/or of rapidly diagnosing several thousand individuals. We are pursuing this research in three thrusts. In the first we are exploring the fundamental interactions of the beads with proteins and nucleic acids in complex mixtures. This will provide us with a complete understanding of the limits of the technology with respect to throughput and complex environment. A major spin-off of this activity is in the rapidly emerging field of proteomics where we may be able to rapidly assess the interactions responsible for cell metabolism, structural

  1. Ion Beam Analysis Of Silicon-Based Surfaces And Correlation With Surface Energy Measurements

    NASA Astrophysics Data System (ADS)

    Xing, Qian; Herbots, N.; Hart, M.; Bradley, J. D.; Wilkens, B. J.; Sell, D. A.; Sell, Clive H.; Kwong, Henry Mark; Culbertson, R. J.; Whaley, S. D.

    2011-06-01

    The water affinity of Si-based surfaces is quantified by contact angle measurement and surface free energy to explain hydrophobic or hydrophilic behavior of silicone, silicates, and silicon surfaces. Surface defects such as dangling bonds, surface free energy including Lewis acid-base and Lifshitz-van der Waals components are discussed. Water nucleation and condensation is further explained by surface topography. Tapping mode atomic force microscopy (TMAFM) provides statistical analysis of the topography of these Si-based surfaces. The correlation of the above two characteristics describes the behavior of water condensation at Si-based surfaces. Surface root mean square roughness increasing from several Å to several nm is found to provide nucleation sites that expedite water condensation visibly for silica and silicone. Hydrophilic surfaces have a condensation pattern that forms puddles of water while hydrophobic surfaces form water beads. Polymer adsorption on these surfaces alters the water affinity as well as the surface topography, and therefore controls condensation on Si-based surfaces including silicone intraocular lens (IOL). The polymer film is characterized by Rutherford backscattering spectrometry (RBS) in conjunction with 4.265 MeV 12C(α, α)12C, 3.045 MeV 16O(α,α)16O nuclear resonance scattering (NRS), and 2.8 MeV elastic recoil detection (ERD) of hydrogen for high resolution composition and areal density measurements. The areal density of hydroxypropyl methylcellulose (HPMC) film ranges from 1018 atom/cm2 to 1019 atom/cm2 gives the silica or silicone surface a roughness of several Å and a wavelength of 0.16±0.02 μm, and prevents fogging by forming a complete wetting layer during water condensation.

  2. Ion Beam Analysis Of Silicon-Based Surfaces And Correlation With Surface Energy Measurements

    SciTech Connect

    Xing Qian; Herbots, N.; Hart, M.; Bradley, J. D.; Wilkens, B. J.; Sell, D. A.; Culbertson, R. J.; Whaley, S. D.; Sell, Clive H.; Kwong, Henry Mark Jr.

    2011-06-01

    The water affinity of Si-based surfaces is quantified by contact angle measurement and surface free energy to explain hydrophobic or hydrophilic behavior of silicone, silicates, and silicon surfaces. Surface defects such as dangling bonds, surface free energy including Lewis acid-base and Lifshitz-van der Waals components are discussed. Water nucleation and condensation is further explained by surface topography. Tapping mode atomic force microscopy (TMAFM) provides statistical analysis of the topography of these Si-based surfaces. The correlation of the above two characteristics describes the behavior of water condensation at Si-based surfaces. Surface root mean square roughness increasing from several A ring to several nm is found to provide nucleation sites that expedite water condensation visibly for silica and silicone. Hydrophilic surfaces have a condensation pattern that forms puddles of water while hydrophobic surfaces form water beads. Polymer adsorption on these surfaces alters the water affinity as well as the surface topography, and therefore controls condensation on Si-based surfaces including silicone intraocular lens (IOL). The polymer film is characterized by Rutherford backscattering spectrometry (RBS) in conjunction with 4.265 MeV {sup 12}C({alpha}, {alpha}){sup 12}C, 3.045 MeV {sup 16}O({alpha},{alpha}){sup 16}O nuclear resonance scattering (NRS), and 2.8 MeV elastic recoil detection (ERD) of hydrogen for high resolution composition and areal density measurements. The areal density of hydroxypropyl methylcellulose (HPMC) film ranges from 10{sup 18} atom/cm{sup 2} to 10{sup 19} atom/cm{sup 2} gives the silica or silicone surface a roughness of several A ring and a wavelength of 0.16{+-}0.02 {mu}m, and prevents fogging by forming a complete wetting layer during water condensation.

  3. [A Hyperspectral Imagery Anomaly Detection Algorithm Based on Gauss-Markov Model].

    PubMed

    Gao, Kun; Liu, Ying; Wang, Li-jing; Zhu, Zhen-yu; Cheng, Hao-bo

    2015-10-01

    With the development of spectral imaging technology, hyperspectral anomaly detection is getting more and more widely used in remote sensing imagery processing. The traditional RX anomaly detection algorithm neglects spatial correlation of images. Besides, it does not validly reduce the data dimension, which costs too much processing time and shows low validity on hyperspectral data. The hyperspectral images follow Gauss-Markov Random Field (GMRF) in space and spectral dimensions. The inverse matrix of covariance matrix is able to be directly calculated by building the Gauss-Markov parameters, which avoids the huge calculation of hyperspectral data. This paper proposes an improved RX anomaly detection algorithm based on three-dimensional GMRF. The hyperspectral imagery data is simulated with GMRF model, and the GMRF parameters are estimated with the Approximated Maximum Likelihood method. The detection operator is constructed with GMRF estimation parameters. The detecting pixel is considered as the centre in a local optimization window, which calls GMRF detecting window. The abnormal degree is calculated with mean vector and covariance inverse matrix, and the mean vector and covariance inverse matrix are calculated within the window. The image is detected pixel by pixel with the moving of GMRF window. The traditional RX detection algorithm, the regional hypothesis detection algorithm based on GMRF and the algorithm proposed in this paper are simulated with AVIRIS hyperspectral data. Simulation results show that the proposed anomaly detection method is able to improve the detection efficiency and reduce false alarm rate. We get the operation time statistics of the three algorithms in the same computer environment. The results show that the proposed algorithm improves the operation time by 45.2%, which shows good computing efficiency. PMID:26904830

  4. Analysis of Vehicle Detection with WSN-Based Ultrasonic Sensors

    PubMed Central

    Jo, Youngtae.; Jung, Inbum.

    2014-01-01

    Existing traffic information acquisition systems suffer from high cost and low scalability. To address these problems, the application of wireless sensor networks (WSNs) has been studied, as WSN-based systems are highly scalable and have a low cost of installing and replacing the systems. Magnetic, acoustic and accelerometer sensors have been considered for WSN-based traffic surveillance, but the use of ultrasonic sensors has not been studied. The limitations of WSN-based systems make it necessary to employ power saving methods and vehicle detection algorithms with low computational complexity. In this paper, we model and analyze optimal power saving methodologies for an ultrasonic sensor and present a computationally-efficient vehicle detection algorithm using ultrasonic data. The proposed methodologies are implemented and evaluated with a tiny microprocessor on real roads. The evaluation results show that the low computational complexity of our algorithm does not compromise the accuracy of vehicle detection. PMID:25093342

  5. Aptamer-based microcantilever biosensor for ultrasensitive detection of tumor marker nucleolin.

    PubMed

    Li, Huiyan; Bai, Xiaojing; Wang, Nan; Chen, Xuejuan; Li, Jing; Zhang, Zhe; Tang, Jilin

    2016-01-01

    We present an aptamer-based microcantilever biosensor for label-free detection of nucleolin. The sensor cantilevers in the microcantilever array were functionalized with nucleolin aptamer (AS1411) while the reference cantilevers were modified by 6-mercapto-1-hexanol (MCH) to eliminate environmental disturbances. The interaction between nucleolin and AS1411 induced surface stress changes, resulting in a differential deflection between sensor and reference cantilevers. The amplitude of differential cantilever deflection had a good linear relationship with the nucleolin concentration ranging from 10 nM to 250 nM with a correlation coefficient of 0.999. The detection limit was about 1.0 nM, at a signal-to-noise ratio of 3. The aptamer-based microcantilever sensor demonstrated good selectivity and was facile, rapid, and reagentless. Our results show the potential for the application of microcantilever biosensor system as a powerful tool to detect tumor markers with high sensitivity and specificity. PMID:26695322

  6. M3D: a kernel-based test for spatially correlated changes in methylation profiles

    PubMed Central

    Mayo, Tom R.; Schweikert, Gabriele; Sanguinetti, Guido

    2015-01-01

    Motivation: DNA methylation is an intensely studied epigenetic mark implicated in many biological processes of direct clinical relevance. Although sequencing-based technologies are increasingly allowing high-resolution measurements of DNA methylation, statistical modelling of such data is still challenging. In particular, statistical identification of differentially methylated regions across different conditions poses unresolved challenges in accounting for spatial correlations within the statistical testing procedure. Results: We propose a non-parametric, kernel-based method, M3D, to detect higher order changes in methylation profiles, such as shape, across pre-defined regions. The test statistic explicitly accounts for differences in coverage levels between samples, thus handling in a principled way a major confounder in the analysis of methylation data. Empirical tests on real and simulated datasets show an increased power compared to established methods, as well as considerable robustness with respect to coverage and replication levels. Availability and implementation: R/Bioconductor package M3D. Contact: G.Sanguinetti@ed.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25398611

  7. The detection of bulk explosives using nuclear-based techniques

    SciTech Connect

    Morgado, R.E.; Gozani, T.; Seher, C.C.

    1988-01-01

    In 1986 we presented a rationale for the detection of bulk explosives based on nuclear techniques that addressed the requirements of civil aviation security in the airport environment. Since then, efforts have intensified to implement a system based on thermal neutron activation (TNA), with new work developing in fast neutron and energetic photon reactions. In this paper we will describe these techniques and present new results from laboratory and airport testing. Based on preliminary results, we contended in our earlier paper that nuclear-based techniques did provide sufficiently penetrating probes and distinguishable detectable reaction products to achieve the FAA operational goals; new data have supported this contention. The status of nuclear-based techniques for the detection of bulk explosives presently under investigation by the US Federal Aviation Administration (FAA) is reviewed. These include thermal neutron activation (TNA), fast neutron activation (FNA), the associated particle technique, nuclear resonance absorption, and photoneutron activation. The results of comprehensive airport testing of the TNA system performed during 1987-88 are summarized. From a technical point of view, nuclear-based techniques now represent the most comprehensive and feasible approach for meeting the operational criteria of detection, false alarms, and throughput. 9 refs., 5 figs., 2 tabs.

  8. DNA methylation detection based on difference of base content

    NASA Astrophysics Data System (ADS)

    Sato, Shinobu; Ohtsuka, Keiichi; Honda, Satoshi; Sato, Yusuke; Takenaka, Shigeori

    2016-04-01

    Methylation frequently occurs in cytosines of CpG sites to regulate gene expression. The identification of aberrant methylation of certain genes is important for cancer marker analysis. The aim of this study was to determine the methylation frequency in DNA samples of unknown length and/or concentration. Unmethylated cytosine is known to be converted to thymine following bisulfite treatment and subsequent PCR. For this reason, the AT content in DNA increases with an increasing number of methylation sites. In this study, the fluorescein-carrying bis-acridinyl peptide (FKA) molecule was used for the detection of methylation frequency. FKA contains fluorescein and two acridine moieties, which together allow for the determination of the AT content of double-stranded DNA fragments. Methylated and unmethylated human genomes were subjected to bisulfide treatment and subsequent PCR using primers specific for the CFTR, CDH4, DBC1, and NPY genes. The AT content in the resulting PCR products was estimated by FKA, and AT content estimations were found to be in good agreement with those determined by DNA sequencing. This newly developed method may be useful for determining methylation frequencies of many PCR products by measuring the fluorescence in samples excited at two different wavelengths.

  9. Land-based infrared imagery for marine mammal detection

    NASA Astrophysics Data System (ADS)

    Graber, Joseph; Thomson, Jim; Polagye, Brian; Jessup, Andrew

    2011-09-01

    A land-based infrared (IR) camera is used to detect endangered Southern Resident killer whales in Puget Sound, Washington, USA. The observations are motivated by a proposed tidal energy pilot project, which will be required to monitor for environmental effects. Potential monitoring methods also include visual observation, passive acoustics, and active acoustics. The effectiveness of observations in the infrared spectrum is compared to observations in the visible spectrum to assess the viability of infrared imagery for cetacean detection and classification. Imagery was obtained at Lime Kiln Park, Washington from 7/6/10-7/9/10 using a FLIR Thermovision A40M infrared camera (7.5-14μm, 37°HFOV, 320x240 pixels) under ideal atmospheric conditions (clear skies, calm seas, and wind speed 0-4 m/s). Whales were detected during both day (9 detections) and night (75 detections) at distances ranging from 42 to 162 m. The temperature contrast between dorsal fins and the sea surface ranged from 0.5 to 4.6 °C. Differences in emissivity from sea surface to dorsal fin are shown to aid detection at high incidence angles (near grazing). A comparison to theory is presented, and observed deviations from theory are investigated. A guide for infrared camera selection based on site geometry and desired target size is presented, with specific considerations regarding marine mammal detection. Atmospheric conditions required to use visible and infrared cameras for marine mammal detection are established and compared with 2008 meteorological data for the proposed tidal energy site. Using conservative assumptions, infrared observations are predicted to provide a 74% increase in hours of possible detection, compared with visual observations.

  10. Analysis of quantitative phase detection based on optical information processing

    NASA Astrophysics Data System (ADS)

    Tao, Wang; Tu, Jiang-Chen; Chun, Kuang-Tao; Yu, Han-Wang; Xin, Du

    2009-07-01

    Phase object exists widely in nature, such as biological cells, optical components, atmospheric flow field and so on. The phase detection of objects has great significance in the basic research, nondestructive testing, aerospace, military weapons and other areas. The usual methods of phase object detection include interference method, grating method, schlieren method, and phase-contrast method etc. These methods have their own advantages, but they also have some disadvantages on detecting precision, environmental requirements, cost, detection rate, detection range, detection linearity in various applications, even the most sophisticated method-phase contrast method mainly used in microscopic structure, lacks quantitative analysis of the size of the phase of the object and the relationship between the image contrast and the optical system. In this paper, various phase detection means and the characteristics of different applications are analyzed based on the optical information processing, and a phase detection system based on optical filtering is formed. Firstly the frequency spectrum of the phase object is achieved by Fourier transform lens in the system, then the frequency spectrum is changed reasonably by the filter, at last the image which can represent the phase distribution through light intensity is achieved by the inverse Fourier transform. The advantages and disadvantages of the common used filters such as 1/4 wavelength phase filter, high-pass filter and edge filter are analyzed, and their phase resolution is analyzed in the same optical information processing system, and the factors impacting phase resolution are pointed out. The paper draws a conclusion that there exists an optimal filter which makes the detect accuracy best for any application. At last, we discussed how to design an optimal filter through which the ability of the phase testing of optical information processing system can be improved most.

  11. Evaluating the Quality of Evidence from Correlational Research for Evidence-Based Practice

    ERIC Educational Resources Information Center

    Thompson, Bruce; Diamond, Karen E.; McWilliam, Robin; Snyder, Patricia; Snyder, Scott W.

    2005-01-01

    Only true experiments offer definitive evidence for causal inferences, but not all educational interventions are readily amenable to experiments. Correlational evidence can at least tentatively inform evidence-based practice when sophisticated causal modeling or exclusion methods are employed. Correlational evidence is most informative when…

  12. Phase demodulation from a single fringe pattern based on a correlation technique.

    PubMed

    Robin, Eric; Valle, Valéry

    2004-08-01

    We present a method for determining the demodulated phase from a single fringe pattern. This method, based on a correlation technique, searches in a zone of interest for the degree of similarity between a real fringe pattern and a mathematical model. This method, named modulated phase correlation, is tested with different examples. PMID:15298408

  13. Effective and Efficient Correlation Analysis with Application to Market Basket Analysis and Network Community Detection

    ERIC Educational Resources Information Center

    Duan, Lian

    2012-01-01

    Finding the most interesting correlations among items is essential for problems in many commercial, medical, and scientific domains. For example, what kinds of items should be recommended with regard to what has been purchased by a customer? How to arrange the store shelf in order to increase sales? How to partition the whole social network into…

  14. Machine learning algorithms for damage detection: Kernel-based approaches

    NASA Astrophysics Data System (ADS)

    Santos, Adam; Figueiredo, Eloi; Silva, M. F. M.; Sales, C. S.; Costa, J. C. W. A.

    2016-02-01

    This paper presents four kernel-based algorithms for damage detection under varying operational and environmental conditions, namely based on one-class support vector machine, support vector data description, kernel principal component analysis and greedy kernel principal component analysis. Acceleration time-series from an array of accelerometers were obtained from a laboratory structure and used for performance comparison. The main contribution of this study is the applicability of the proposed algorithms for damage detection as well as the comparison of the classification performance between these algorithms and other four ones already considered as reliable approaches in the literature. All proposed algorithms revealed to have better classification performance than the previous ones.

  15. Contour detection based on brightness and contour completion

    NASA Astrophysics Data System (ADS)

    Zou, Lamei; Wan, Min; Jin, Liujia; Gao, Yahong; Yang, Weidong

    2015-12-01

    The further research of visual processing mechanism provides a new idea for contour detection. On the primary visual cortex, the non-classical receptive field of the neurons has the orientation selectivity exerts suppression effect on the response of classical receptive field, which influences edge or line perception. Based on the suppression property of non-classical receptive field and contour completion, this paper proposed a contour detection method based on brightness and contour completion. The experiment shows that the proposed method can not only effectively eliminate clutter information, but also connect the broken contour points by taking advantage of contour completion.

  16. A Cyber-Attack Detection Model Based on Multivariate Analyses

    NASA Astrophysics Data System (ADS)

    Sakai, Yuto; Rinsaka, Koichiro; Dohi, Tadashi

    In the present paper, we propose a novel cyber-attack detection model based on two multivariate-analysis methods to the audit data observed on a host machine. The statistical techniques used here are the well-known Hayashi's quantification method IV and cluster analysis method. We quantify the observed qualitative audit event sequence via the quantification method IV, and collect similar audit event sequence in the same groups based on the cluster analysis. It is shown in simulation experiments that our model can improve the cyber-attack detection accuracy in some realistic cases where both normal and attack activities are intermingled.

  17. Mass spectrometric detection of protein-based toxins.

    PubMed

    Tevell Åberg, Annica; Björnstad, Kristian; Hedeland, Mikael

    2013-09-01

    This review focuses on mass spectrometric detection of protein-based toxins, which are among the most toxic substances known. Special emphasis is given to the bacterial toxins botulinum neurotoxin from Clostridium botulinum and anthrax toxins from Bacillus anthracis as well as the plant toxin ricin produced by Ricinus communis. A common feature, apart from their extreme toxicity, is that they are composed of 2 polypeptide chains, one of which is responsible for cell uptake and another that has enzymatic function with the ability to destroy basic cellular functions. These toxins pose a threat, both regarding natural spread and from a terrorism perspective. In order for public health and emergency response officials to take appropriate action in case of an outbreak, whether natural or intentional, there is a need for fast and reliable detection methods. Traditionally, large molecules like proteins have been detected using immunological techniques. Although sensitive, these methods suffer from some drawbacks, such as the risk of false-positives due to cross-reactions and detection of inactive toxin. This article describes recently developed instrumental methods based on mass spectrometry for the reliable detection of botulinum neurotoxins, anthrax toxins, and ricin. Unequivocal identification of a protein toxin can be carried out by mass spectrometry-based amino acid sequencing. Furthermore, in combination with antibody affinity preconcentration and biochemical tests with mass spectrometric detection demonstrating the toxin's enzymatic activity, very powerful analytical methods have been described. In conclusion, the advent of sensitive, easily operated mass spectrometers provides new possibilities for the detection of protein-based toxins. PMID:23971809

  18. A CORRELATION BETWEEN THE HIGHEST ENERGY COSMIC RAYS AND NEARBY ACTIVE GALACTIC NUCLEI DETECTED BY FERMI

    SciTech Connect

    Nemmen, Rodrigo S.; Bonatto, Charles; Storchi-Bergmann, Thaisa

    2010-10-10

    We analyze the correlation of the positions of {gamma}-ray sources in the Fermi Large Area Telescope (LAT) First Source Catalog (1FGL) and the First LAT Active Galactic Nuclei (AGNs) Catalog (1LAC) with the arrival directions of ultra-high-energy cosmic rays (UHECRs) observed with the Pierre Auger Observatory, in order to investigate the origin of UHECRs. We find that Galactic sources and blazars identified in the 1FGL are not significantly correlated with UHECRs, while the 1LAC sources display a mild correlation (2.6{sigma} level) on an {approx}2.{sup 0}4 angular scale. When selecting only the 1LAC AGNs closer than 200 Mpc, we find a strong association (5.4{sigma}) between their positions and the directions of UHECRs on an {approx}17{sup 0} angular scale; the probability of the observed configuration being due to an isotropic flux of cosmic rays is 5 x 10{sup -8}. There is also a 5{sigma} correlation with nearby 1LAC sources on a 6.{sup 0}5 scale. We identify seven '{gamma}-ray loud' AGNs which are associated with UHECRs within {approx}17{sup 0} and are likely candidates for the production sites of UHECRs: Centaurus A, NGC 4945, ESO 323-G77, 4C+04.77, NGC 1218, RX J0008.0+1450, and NGC 253. We interpret these results as providing additional support to the hypothesis of the origin of UHECRs in nearby extragalactic objects. As the angular scales of the correlations are large, we discuss the possibility that intervening magnetic fields might be considerably deflecting the trajectories of the particles on their way to Earth.

  19. VoIP attacks detection engine based on neural network

    NASA Astrophysics Data System (ADS)

    Safarik, Jakub; Slachta, Jiri

    2015-05-01

    The security is crucial for any system nowadays, especially communications. One of the most successful protocols in the field of communication over IP networks is Session Initiation Protocol. It is an open-source project used by different kinds of applications, both open-source and proprietary. High penetration and text-based principle made SIP number one target in IP telephony infrastructure, so security of SIP server is essential. To keep up with hackers and to detect potential malicious attacks, security administrator needs to monitor and evaluate SIP traffic in the network. But monitoring and following evaluation could easily overwhelm the security administrator in networks, typically in networks with a number of SIP servers, users and logically or geographically separated networks. The proposed solution lies in automatic attack detection systems. The article covers detection of VoIP attacks through a distributed network of nodes. Then the gathered data analyze aggregation server with artificial neural network. Artificial neural network means multilayer perceptron network trained with a set of collected attacks. Attack data could also be preprocessed and verified with a self-organizing map. The source data is detected by distributed network of detection nodes. Each node contains a honeypot application and traffic monitoring mechanism. Aggregation of data from each node creates an input for neural networks. The automatic classification on a centralized server with low false positive detection reduce the cost of attack detection resources. The detection system uses modular design for easy deployment in final infrastructure. The centralized server collects and process detected traffic. It also maintains all detection nodes.

  20. Detecting weak seismicity in urban areas using waveform stacking and cross correlation: Application to a stimulation experiment

    NASA Astrophysics Data System (ADS)

    Plenkers, K.; Ritter, J.; Schindler, M.

    2012-04-01

    Urban noise often prevents the detection of microseismicity (ML < 2). The problem is well known from many geotechnical production sites, where the need to perform reliable hazard assessment has increased the interest in small seismic events. We study the microseismicity (ML < 2) in the region of Landau, SW Germany. Here, due to thick sediments ( approx. 3 km) and high cultural seismic noise, the signal-to-noise ratio is in general very low for small earthquakes. To gain new insights into the occurrence of very small seismic events we developed a 3-step detection approach and are thus able to identify 207 formerly unknown microseismic events (-1 < ML < 1) with signal-to-noise ratios smaller than three. We use the recordings from a unfavourable broadband network installed for a teleseismic study with station distances of approximately 10 km. First, we apply a short term average to long term average detection algorithm for data reduction. The detection algorithm is affected severely by transient noise signals that do not differ in frequency content, duration and amplitude from the microseismic events searched for. Therefore, the most promising detections, selected by coinciding triggers and high amplitude measures, are reviewed manually. In this way we are able to identify 13 seismic events. Finally, we conduct a cross correlation analysis. As master template we use the stacked waveforms of five manually detected seismic events with a repeating waveform. This search reveals additional 194 events with a cross correlation coefficient exceeding 0.65 which ensures a stable identification. Our analysis shows that the repeating events occurred during the stimulation of a geothermal reservoir within a source region of only about (0.5 km)3.

  1. Background updating and shadow detection based on spatial, color, and texture information of detected objects

    NASA Astrophysics Data System (ADS)

    Hamad, Ahmed Mahmoud; Tsumura, Norimichi

    2012-05-01

    Background model updating is a vital process for any background subtraction technique. This paper presents an updating mechanism that can be applied efficiently to any background subtraction technique. This updating mechanism exploits the color and spatial features to characterize each detected object. Spatial and color features are used to classify each detected object as a moving background object, a ghost, or a real moving object. The starting position of each detected object is the cue for updating background images. In addition, this paper presents a hybrid scheme to detect and remove cast shadows based on texture and color features. The robustness of the proposed method and its effectiveness in overcoming challenging problems such as gradual and sudden illumination changes, ghost appearance, non-stationary background objects, the stability of moving objects most of the time, and cast shadows are verified quantitatively and qualitatively.

  2. Analog Signal Correlating Using an Analog-Based Signal Conditioning Front End

    NASA Technical Reports Server (NTRS)

    Prokop, Norman; Krasowski, Michael

    2013-01-01

    This innovation is capable of correlating two analog signals by using an analog-based signal conditioning front end to hard-limit the analog signals through adaptive thresholding into a binary bit stream, then performing the correlation using a Hamming "similarity" calculator function embedded in a one-bit digital correlator (OBDC). By converting the analog signal into a bit stream, the calculation of the correlation function is simplified, and less hardware resources are needed. This binary representation allows the hardware to move from a DSP where instructions are performed serially, into digital logic where calculations can be performed in parallel, greatly speeding up calculations.

  3. Analysis of Android Device-Based Solutions for Fall Detection

    PubMed Central

    Casilari, Eduardo; Luque, Rafael; Morón, María-José

    2015-01-01

    Falls are a major cause of health and psychological problems as well as hospitalization costs among older adults. Thus, the investigation on automatic Fall Detection Systems (FDSs) has received special attention from the research community during the last decade. In this area, the widespread popularity, decreasing price, computing capabilities, built-in sensors and multiplicity of wireless interfaces of Android-based devices (especially smartphones) have fostered the adoption of this technology to deploy wearable and inexpensive architectures for fall detection. This paper presents a critical and thorough analysis of those existing fall detection systems that are based on Android devices. The review systematically classifies and compares the proposals of the literature taking into account different criteria such as the system architecture, the employed sensors, the detection algorithm or the response in case of a fall alarms. The study emphasizes the analysis of the evaluation methods that are employed to assess the effectiveness of the detection process. The review reveals the complete lack of a reference framework to validate and compare the proposals. In addition, the study also shows that most research works do not evaluate the actual applicability of the Android devices (with limited battery and computing resources) to fall detection solutions. PMID:26213928

  4. Analysis of Android Device-Based Solutions for Fall Detection.

    PubMed

    Casilari, Eduardo; Luque, Rafael; Morón, María-José

    2015-01-01

    Falls are a major cause of health and psychological problems as well as hospitalization costs among older adults. Thus, the investigation on automatic Fall Detection Systems (FDSs) has received special attention from the research community during the last decade. In this area, the widespread popularity, decreasing price, computing capabilities, built-in sensors and multiplicity of wireless interfaces of Android-based devices (especially smartphones) have fostered the adoption of this technology to deploy wearable and inexpensive architectures for fall detection. This paper presents a critical and thorough analysis of those existing fall detection systems that are based on Android devices. The review systematically classifies and compares the proposals of the literature taking into account different criteria such as the system architecture, the employed sensors, the detection algorithm or the response in case of a fall alarms. The study emphasizes the analysis of the evaluation methods that are employed to assess the effectiveness of the detection process. The review reveals the complete lack of a reference framework to validate and compare the proposals. In addition, the study also shows that most research works do not evaluate the actual applicability of the Android devices (with limited battery and computing resources) to fall detection solutions. PMID:26213928

  5. Multispectral face liveness detection method based on gradient features

    NASA Astrophysics Data System (ADS)

    Hou, Ya-Li; Hao, Xiaoli; Wang, Yueyang; Guo, Changqing

    2013-11-01

    Face liveness detection aims to distinguish genuine faces from disguised faces. Most previous works under visible light focus on classification of genuine faces and planar photos or videos. To handle the three-dimensional (3-D) disguised faces, liveness detection based on multispectral images has been shown to be an effective choice. In this paper, a gradient-based multispectral method has been proposed for face liveness detection. Three feature vectors are developed to reduce the influence of varying illuminations. The reflectance-based feature achieves the best performance, which has a true positive rate of 98.3% and a true negative rate of 98.7%. The developed methods are also tested on individual bands to provide a clue for band selection in the imaging system. Preliminary results on different face orientations are also shown. The contributions of this paper are threefold. First, a gradient-based multispectral method has been proposed for liveness detection, which considers the reflectance properties of all the distinctive regions in a face. Second, three illumination-robust features are studied based on a dataset with two-dimensional planar photos, 3-D mannequins, and masks. Finally, the performance of the method on different spectral bands and face orientations is also shown in the evaluations.

  6. An EEG-Based Fatigue Detection and Mitigation System.

    PubMed

    Huang, Kuan-Chih; Huang, Teng-Yi; Chuang, Chun-Hsiang; King, Jung-Tai; Wang, Yu-Kai; Lin, Chin-Teng; Jung, Tzyy-Ping

    2016-06-01

    Research has indicated that fatigue is a critical factor in cognitive lapses because it negatively affects an individual's internal state, which is then manifested physiologically. This study explores neurophysiological changes, measured by electroencephalogram (EEG), due to fatigue. This study further demonstrates the feasibility of an online closed-loop EEG-based fatigue detection and mitigation system that detects physiological change and can thereby prevent fatigue-related cognitive lapses. More importantly, this work compares the efficacy of fatigue detection and mitigation between the EEG-based and a nonEEG-based random method. Twelve healthy subjects participated in a sustained-attention driving experiment. Each participant's EEG signal was monitored continuously and a warning was delivered in real-time to participants once the EEG signature of fatigue was detected. Study results indicate suppression of the alpha- and theta-power of an occipital component and improved behavioral performance following a warning signal; these findings are in line with those in previous studies. However, study results also showed reduced warning efficacy (i.e. increased response times (RTs) to lane deviations) accompanied by increased alpha-power due to the fluctuation of warnings over time. Furthermore, a comparison of EEG-based and nonEEG-based random approaches clearly demonstrated the necessity of adaptive fatigue-mitigation systems, based on a subject's cognitive level, to deliver warnings. Analytical results clearly demonstrate and validate the efficacy of this online closed-loop EEG-based fatigue detection and mitigation mechanism to identify cognitive lapses that may lead to catastrophic incidents in countless operational environments. PMID:27121994

  7. Current-based detection of nonlocal spin transport in graphene for spin-based logic applications

    NASA Astrophysics Data System (ADS)

    Wen, Hua; Zhu, Tiancong; Luo, Yunqiu Kelly; Amamou, Walid; Kawakami, Roland K.

    2014-05-01

    Graphene has been proposed for novel spintronic devices due to its robust and efficient spin transport properties at room temperature. Some of the most promising proposals require current-based readout for integration purposes, but the current-based detection of spin accumulation has not yet been developed. In this work, we demonstrate current-based detection of spin transport in graphene using a modified nonlocal geometry. By adding a variable shunt resistor in parallel to the nonlocal voltmeter, we are able to systematically cross over from the conventional voltage-based detection to current-based detection. As the shunt resistor is reduced, the output current from the spin accumulation increases as the shunt resistance drops below a characteristic value R*. We analyze this behavior using a one-dimensional drift-diffusion model, which accounts well for the observed behavior. These results provide the experimental and theoretical foundation for current-based detection of nonlocal spin transport.

  8. A stereo vision-based obstacle detection system in vehicles

    NASA Astrophysics Data System (ADS)

    Huh, Kunsoo; Park, Jaehak; Hwang, Junyeon; Hong, Daegun

    2008-02-01

    Obstacle detection is a crucial issue for driver assistance systems as well as for autonomous vehicle guidance function and it has to be performed with high reliability to avoid any potential collision with the front vehicle. The vision-based obstacle detection systems are regarded promising for this purpose because they require little infrastructure on a highway. However, the feasibility of these systems in passenger car requires accurate and robust sensing performance. In this paper, an obstacle detection system using stereo vision sensors is developed. This system utilizes feature matching, epipoplar constraint and feature aggregation in order to robustly detect the initial corresponding pairs. After the initial detection, the system executes the tracking algorithm for the obstacles. The proposed system can detect a front obstacle, a leading vehicle and a vehicle cutting into the lane. Then, the position parameters of the obstacles and leading vehicles can be obtained. The proposed obstacle detection system is implemented on a passenger car and its performance is verified experimentally.

  9. R-peaks detection based on stationary wavelet transform.

    PubMed

    Merah, M; Abdelmalik, T A; Larbi, B H

    2015-10-01

    Automatic detection of the QRS complexes/R-peaks in an electrocardiogram (ECG) signal is the most important step preceding any kind of ECG processing and analysis. The performance of these systems heavily relies on the accuracy of the QRS detector. The objective of present work is to drive a new robust method based on stationary wavelet transform (SWT) for R-peaks detection. The decimation of the coefficients at each level of the transformation algorithm is omitted, more samples in the coefficient sequences are available and hence a better outlier detection can be performed. Using the information of local maxima, minima and zero crossings of the fourth SWT coefficient detail, the proposed algorithm identifies the significant points for detection and delineation of the QRS complexes, as well as detection and identification of the QRS individual waves peaks of the pre-processed ECG signal. Various experimental results show that the proposed algorithm exhibits reliable QRS detection as well as accurate ECG delineation, achieving excellent performance on different databases, on the MIT-BIH database (Se=99.84%, P=99.88%), on the QT Database (Se=99.94%, P=99.89%) and on MIT-BIH Noise Stress Test Database, (Se=95.30%, P=93.98%). Reliability and accuracy are close to the highest among the ones obtained in other studies. Experiments results being satisfactory, the SWT may represent a novel QRS detection tool, for a robust ECG signal analysis. PMID:26105724

  10. PCA-HOG symmetrical feature based diseased cell detection

    NASA Astrophysics Data System (ADS)

    Wan, Min-jie

    2016-04-01

    A histogram of oriented gradient (HOG) feature is applied to the field of diseased cell detection, which can detect diseased cells in high resolution tissue images rapidly, accurately and efficiently. Firstly, motivated by symmetrical cellular forms, a new HOG symmetrical feature based on the traditional HOG feature is proposed to meet the condition of cell detection. Secondly, considering the high feature dimension of traditional HOG feature leads to plenty of memory resources and long runtime in practical applications, a classical dimension reduction method called principal component analysis (PCA) is used to reduce the dimension of high-dimensional HOG descriptor. Because of that, computational speed is increased greatly, and the accuracy of detection can be controlled in a proper range at the same time. Thirdly, support vector machine (SVM) classifier is trained with PCA-HOG symmetrical features proposed above. At last, practical tissue images is detected and analyzed by SVM classifier. In order to verify the effectiveness of this new algorithm, it is practically applied to conduct diseased cell detection which takes 200 pieces of H&E (hematoxylin & eosin) high resolution staining histopathological images collected from 20 breast cancer patients as a sample. The experiment shows that the average processing rate can be 25 frames per second and the detection accuracy can be 92.1%.

  11. An FPGA-based rapid wheezing detection system.

    PubMed

    Lin, Bor-Shing; Yen, Tian-Shiue

    2014-02-01

    Wheezing is often treated as a crucial indicator in the diagnosis of obstructive pulmonary diseases. A rapid wheezing detection system may help physicians to monitor patients over the long-term. In this study, a portable wheezing detection system based on a field-programmable gate array (FPGA) is proposed. This system accelerates wheezing detection, and can be used as either a single-process system, or as an integrated part of another biomedical signal detection system. The system segments sound signals into 2-second units. A short-time Fourier transform was used to determine the relationship between the time and frequency components of wheezing sound data. A spectrogram was processed using 2D bilateral filtering, edge detection, multithreshold image segmentation, morphological image processing, and image labeling, to extract wheezing features according to computerized respiratory sound analysis (CORSA) standards. These features were then used to train the support vector machine (SVM) and build the classification models. The trained model was used to analyze sound data to detect wheezing. The system runs on a Xilinx Virtex-6 FPGA ML605 platform. The experimental results revealed that the system offered excellent wheezing recognition performance (0.912). The detection process can be used with a clock frequency of 51.97 MHz, and is able to perform rapid wheezing classification. PMID:24481034

  12. Analytical assays based on detecting conformational changes of single molecules.

    PubMed

    Zocchi, Giovanni

    2006-03-13

    One common strategy for the detection of biomolecules is labeling either the target itself or an antibody that binds to it. Herein, a different approach, based on detecting the conformational change of a probe molecule induced by binding of the target is discussed. That is, what is being detected is not the presence of the target or the probe, but the conformational change of the probe. Recently, a single-molecule sensor has been developed that exploits this mechanism to detect hybridization of a single DNA oligomer to a DNA probe, as well as specific binding of a single protein to a DNA probe. Biomolecular recognition often involves large conformational changes of the molecules involved, and therefore this strategy may be applicable to other assays. PMID:16514690

  13. Vegetation change detection based on image fusion technique

    NASA Astrophysics Data System (ADS)

    Jia, Yonghong; Liu, Yueyan; Yu, Hui; Li, Deren

    2005-10-01

    The change detection of land use and land cover has always been the focus of remotely sensed study and application. Based on techniques of image fusion, a new approach of detecting vegetation change according to vector of brightness index (BI) and perpendicular vegetation index (PVI) extracted from multi-temporal remotely sensed imagery is proposed. The procedure is introduced. Firstly, the Landsat eTM+ imagery is geometrically corrected and registered. Secondly, band 2,3,4 and panchromatic images of Landsat eTM+ are fused by a trous wavelet fusion, and bands 1,2,3 of SPOT are registered to the fused images. Thirdly, brightness index and perpendicular vegetation index are respectively extracted from SPOT images and fused images. Finally, change vectors are obtained and used to detect vegetation change. The testing results show that the approach of detecting vegetation change is very efficient.

  14. Violence detection based on histogram of optical flow orientation

    NASA Astrophysics Data System (ADS)

    Yang, Zhijie; Zhang, Tao; Yang, Jie; Wu, Qiang; Bai, Li; Yao, Lixiu

    2013-12-01

    In this paper, we propose a novel approach for violence detection and localization in a public scene. Currently, violence detection is considerably under-researched compared with the common action recognition. Although existing methods can detect the presence of violence in a video, they cannot precisely locate the regions in the scene where violence is happening. This paper will tackle the challenge and propose a novel method to locate the violence location in the scene, which is important for public surveillance. The Gaussian Mixed Model is extended into the optical flow domain in order to detect candidate violence regions. In each region, a new descriptor, Histogram of Optical Flow Orientation (HOFO), is proposed to measure the spatial-temporal features. A linear SVM is trained based on the descriptor. The performance of the method is demonstrated on the publicly available data sets, BEHAVE and CAVIAR.

  15. Contributed Review: Quantum cascade laser based photoacoustic detection of explosives

    SciTech Connect

    Li, J. S. Yu, B.; Fischer, H.; Chen, W.; Yalin, A. P.

    2015-03-15

    Detecting trace explosives and explosive-related compounds has recently become a topic of utmost importance for increasing public security around the world. A wide variety of detection methods and an even wider range of physical chemistry issues are involved in this very challenging area. Optical sensing methods, in particular mid-infrared spectrometry techniques, have a great potential to become a more desirable tools for the detection of explosives. The small size, simplicity, high output power, long-term reliability make external cavity quantum cascade lasers (EC-QCLs) the promising spectroscopic sources for developing analytical instrumentation. This work reviews the current technical progress in EC-QCL-based photoacoustic spectroscopy for explosives detection. The potential for both close-contact and standoff configurations using this technique is completely presented over the course of approximately the last one decade.

  16. Feature-based eye corner detection from static images

    NASA Astrophysics Data System (ADS)

    Xia, Haiying; Yan, Guoping; You, Chao

    2009-10-01

    Eye corner detection is important for eye extraction, face normalization, other facial landmark extraction and so on. We present a feature-based method for eye corner detection from static images in this paper. This method is capable of locating eye corners automatically. The process of eye corner detection is divided into two stages: classifier training and classifier application. For training, two classifiers trained by AdaBoost with Haar-like features, are skillfully designed to detect inner eye corners and outer eye corners. Then, two classifiers are applied to input images to search targets. Eye corners are finally located according to two eye models from targets. Experimental results tested on BioID face database and our own database demonstrate that our method obtains a high accuracy under clutter conditions.

  17. Photofission-Based, Nuclear Material Detection: Technology Demonstration

    SciTech Connect

    Jones, James Litton; Yoon, Woo Yong; Haskell, Kevin James; Norman, Daren Reeve; Moss, C. E.; Goulding, C. A.; Hollas, C. L.; Myers, W. L.; Franco, Ed

    2002-12-01

    The Idaho National Engineering and Environmental Laboratory (INEEL), the Los Alamos National Laboratory (LANL), and the Advanced Research and Applications Corporation (ARACOR) [Sunnyvale, California] performed a photonuclear technology demonstration for shielded nuclear material detection during August 21–22, 2002, at the LANL TA-18 facility. The demonstration used the Pulsed Photonuclear Assessment Technique (PPAT) that focused on the application of a photofission-based, nuclear material detection method as a viable complement to the ARACOR Eagle inspection platform. The Eagle is a mobile and fully operational truck and cargo inspection system that uses a 6-MeV electron accelerator to perform real-time radiography. This imaging is performed using an approved “radiation-safe” or “cabinet safe” operation relative to the operators, inspectors, and any stowaways within the inspected vehicles. While the PPAT has been primarily developed for active interrogation, its neutron detection system also maintains a complete and effective passive detection capability.

  18. Detecting medication errors: analysis based on a hospital's incident reports.

    PubMed

    Härkänen, Marja; Turunen, Hannele; Saano, Susanna; Vehviläinen-Julkunen, Katri

    2015-04-01

    The aim of this paper is to analyse how medication incidents are detected in different phases of the medication process. The study design is a retrospective register study. The material was collected from one university hospital's web-based incident reporting database in Finland. In 2010, 1617 incident reports were made, 671 of those were medication incidents and analysed in this study. Statistical methods were used to analyse the material. Results were reported using frequencies and percentages. Twenty-one percent of all medication incidents were detected during documenting or reading the documents. One-sixth of medication incidents were detected during medicating the patients, and approximately one-tenth were detected during verifying of the medicines. It is important to learn how to break the chain of medication errors as early as possible. Findings showed that for nurses, the ability to concentrate on documenting and medicating the patient is essential. PMID:24256158

  19. Microcontroller-based real-time QRS detection.

    PubMed

    Sun, Y; Suppappola, S; Wrublewski, T A

    1992-01-01

    The authors describe the design of a system for real-time detection of QRS complexes in the electrocardiogram based on a single-chip microcontroller (Motorola 68HC811). A systematic analysis of the instrumentation requirements for QRS detection and of the various design techniques is also given. Detection algorithms using different nonlinear transforms for the enhancement of QRS complexes are evaluated by using the ECG database of the American Heart Association. The results show that the nonlinear transform involving multiplication of three adjacent, sign-consistent differences in the time domain gives a good performance and a quick response. When implemented with an appropriate sampling rate, this algorithm is also capable of rejecting pacemaker spikes. The eight-bit single-chip microcontroller provides sufficient throughput and shows a satisfactory performance. Implementation of multiple detection algorithms in the same system improves flexibility and reliability. The low chip count in the design also favors maintainability and cost-effectiveness. PMID:1450792

  20. Contributed Review: Quantum cascade laser based photoacoustic detection of explosives

    NASA Astrophysics Data System (ADS)

    Li, J. S.; Yu, B.; Fischer, H.; Chen, W.; Yalin, A. P.

    2015-03-01

    Detecting trace explosives and explosive-related compounds has recently become a topic of utmost importance for increasing public security around the world. A wide variety of detection methods and an even wider range of physical chemistry issues are involved in this very challenging area. Optical sensing methods, in particular mid-infrared spectrometry techniques, have a great potential to become a more desirable tools for the detection of explosives. The small size, simplicity, high output power, long-term reliability make external cavity quantum cascade lasers (EC-QCLs) the promising spectroscopic sources for developing analytical instrumentation. This work reviews the current technical progress in EC-QCL-based photoacoustic spectroscopy for explosives detection. The potential for both close-contact and standoff configurations using this technique is completely presented over the course of approximately the last one decade.