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Sample records for based correlation detection

  1. Is Host-Based Anomaly Detection + Temporal Correlation = Worm Causality

    DTIC Science & Technology

    2007-03-06

    combination of host-based anomaly detection and temporal correlation of network events. The contribution of this paper is a systematic exploration of this...suggest that it is feasible to establish attack causality accurately using anomaly detection and temporal event correlation in enterprise network environments with tens of thousands of hosts.

  2. Structural Plasticity Controlled by Calcium Based Correlation Detection

    PubMed Central

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

    2008-01-01

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

  3. Correlation based efficient face recognition and color change detection

    NASA Astrophysics Data System (ADS)

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

    2013-01-01

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

  4. Stochastic quantum Zeno-based detection of noise correlations

    NASA Astrophysics Data System (ADS)

    Müller, Matthias M.; Gherardini, Stefano; Caruso, Filippo

    2016-12-01

    A system under constant observation is practically freezed to the measurement subspace. If the system driving is a random classical field, the survival probability of the system in the subspace becomes a random variable described by the Stochastic Quantum Zeno Dynamics (SQZD) formalism. Here, we study the time and ensemble average of this random survival probability and demonstrate how time correlations in the noisy environment determine whether the two averages do coincide or not. These environment time correlations can potentially generate non-Markovian dynamics of the quantum system depending on the structure and energy scale of the system Hamiltonian. We thus propose a way to detect time correlations of the environment by coupling a quantum probe system to it and observing the survival probability of the quantum probe in a measurement subspace. This will further contribute to the development of new schemes for quantum sensing technologies, where nanodevices may be exploited to image external structures or biological molecules via the surface field they generate.

  5. Stochastic quantum Zeno-based detection of noise correlations

    PubMed Central

    Müller, Matthias M.; Gherardini, Stefano; Caruso, Filippo

    2016-01-01

    A system under constant observation is practically freezed to the measurement subspace. If the system driving is a random classical field, the survival probability of the system in the subspace becomes a random variable described by the Stochastic Quantum Zeno Dynamics (SQZD) formalism. Here, we study the time and ensemble average of this random survival probability and demonstrate how time correlations in the noisy environment determine whether the two averages do coincide or not. These environment time correlations can potentially generate non-Markovian dynamics of the quantum system depending on the structure and energy scale of the system Hamiltonian. We thus propose a way to detect time correlations of the environment by coupling a quantum probe system to it and observing the survival probability of the quantum probe in a measurement subspace. This will further contribute to the development of new schemes for quantum sensing technologies, where nanodevices may be exploited to image external structures or biological molecules via the surface field they generate. PMID:27941889

  6. Optical correlator based target detection, recognition, classification, and tracking.

    PubMed

    Manzur, Tariq; Zeller, John; Serati, Steve

    2012-07-20

    A dedicated automatic target recognition and tracking optical correlator (OC) system using advanced processing technology has been developed. Rapidly cycling data-cubes with size, shape, and orientation are employed with software algorithms to isolate correlation peaks and enable tracking of targets in maritime environments with future track prediction. The method has been found superior to employing maximum average correlation height filters for which the correlation peak intensity drops off in proportion to the number of training images. The physical dimensions of the OC system may be reduced to as small as 2 in. × 2 in. × 3 in. (51 mm × 51 mm × 76 mm) by modifying and minimizing the OC components.

  7. A correlation based fault detection method for short circuits in battery packs

    NASA Astrophysics Data System (ADS)

    Xia, Bing; Shang, Yunlong; Nguyen, Truong; Mi, Chris

    2017-01-01

    This paper presents a fault detection method for short circuits based on the correlation coefficient of voltage curves. The proposed method utilizes the direct voltage measurements from the battery cells, and does not require any additional hardware or effort in modeling during fault detection. Moreover, the inherent mathematical properties of the correlation coefficient ensure the robustness of this method as the battery pack ages or is imbalanced in real applications. In order to apply this method online, the recursive moving window correlation coefficient calculation is adopted to maintain the detection sensitivity to faults during operation. An additive square wave is designed to prevent false positive detections when the batteries are at rest. The fault isolation can be achieved by identifying the overlapped cell in the correlation coefficients with fault flags. Simulation and experimental results validated the feasibility and demonstrated the advantages of this method.

  8. Enhancing unsupervised canonical correlation analysis-based frequency detection of SSVEPs by incorporating background EEG.

    PubMed

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

    2014-01-01

    Steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs) have potential to provide a fast communication channel between human brain and external devices. In SSVEP-based BCIs, Canonical Correlation Analysis (CCA) has been widely used to detect frequency-coded SSVEPs due to its high efficiency and robustness. However, the detectability of SSVEPs differs among frequencies due to a power-law distribution of the power spectra of spontaneous electroencephalogram (EEG) signals. This study proposed a new method based on the fact that changes of canonical correlation coefficients for SSVEPs and background EEG signals follow the same trend along frequency. The proposed method defined a normalized canonical correlation coefficient, the ratio of the canonical correlation coefficient for SSVEPs to the mean of the canonical correlation coefficients for background EEG signals, to enhance the frequency detection of SSVEPs. An SSVEP dataset from 13 subjects was used for comparing classification performance between the proposed method and the standard CCA method. Classification accuracy and simulated information transfer rates (ITR) suggest that, in an unsupervised way, the proposed method could considerably improve the frequency detection accuracy of SSVEPs with little computational effort.

  9. Detecting the DPRK nuclear test explosion on 25 May 2009 using array-based waveform correlation

    NASA Astrophysics Data System (ADS)

    Gibbons, Steven J.; Ringdal, Frode

    2010-05-01

    The Democratic People's Republic of Korea (DPRK) announced on 25 May 2009 that it had conducted its second nuclear test, the first one having taken place on 9 October 2006. As was the case with the first test, the second test was detected and reported by the IDC. We have carried out an experiment taking the 9 October 2006 test as a starting point and running a continuous waveform correlation scheme in order to a) assess the potential for automatically detecting the second nuclear test and b) monitoring the false alarm rate associated with such a detection scheme. Using only data from the Matsushiro array (MJAR), and applying the array-based procedure developed by Gibbons and Ringdal (2006) with a waveform template from the first nuclear test, we found that the second test was readily detected without a single false alarm during the entire three year period. Moreover, by a scaling procedure, we argue that an explosion many times smaller than the second test would have been detected automatically, with no false alarms, had it taken place at the same site as the second test. We note that this remarkable performance is achieved even though the MJAR array is known to be difficult to process using conventional methods, because of signal incoherency. An important element of the detection procedure for the automatic elimination of false alarms is a post-processing system which performs slowness analysis on the single-channel cross-correlation traces. It is well known that successful correlation detection requires the two sources to be closely spaced (i.e. the detector has a narrow "footprint"), but there is evidence that array-based correlation covers a larger footprint than the 1/4 wavelength estimated by Geller and Mueller (1980) for single-station correlation. This could be important for a more general application of the method described here, and needs further study.

  10. Spatial correlation based artifact detection for automatic seizure detection in EEG.

    PubMed

    Skupch, Ana M; Dollfuß, Peter; Fürbaß, Franz; Gritsch, Gerhard; Hartmann, Manfred M; Perko, Hannes; Pataraia, Ekaterina; Lindinger, Gerald; Kluge, Tilmann

    2013-01-01

    Automatic EEG-processing systems such as seizure detection systems are more and more in use to cope with the large amount of data that arises from long-term EEG-monitorings. Since artifacts occur very often during the recordings and disturb the EEG-processing, it is crucial for these systems to have a good automatic artifact detection. We present a novel, computationally inexpensive automatic artifact detection system that uses the spatial distribution of the EEG-signal and the location of the electrodes to detect artifacts on electrodes. The algorithm was evaluated by including it into the automatic seizure detection system EpiScan and applying it to a very large amount of data including a large variety of EEGs and artifacts.

  11. Output-Based Structural Damage Detection by Using Correlation Analysis Together with Transmissibility

    PubMed Central

    Cao, Hongyou; Liu, Quanmin; Wahab, Magd Abdel

    2017-01-01

    Output-based structural damage detection is becoming increasingly appealing due to its potential in real engineering applications without any restriction regarding excitation measurements. A new transmissibility-based damage detection approach is presented in this study by combining transmissibility with correlation analysis in order to strengthen its performance in discriminating damaged from undamaged scenarios. From this perspective, damage detection strategies are hereafter established by constructing damage-sensitive indicators from a derived transmissibility. A cantilever beam is numerically analyzed to verify the feasibility of the proposed damage detection procedure, and an ASCE (American Society of Civil Engineers) benchmark is henceforth used in the validation for its application in engineering structures. The results of both studies reveal a good performance of the proposed methodology in identifying damaged states from intact states. The comparison between the proposed indicator and the existing indicator also affirms its applicability in damage detection, which might be adopted in further structural health monitoring systems as a discrimination criterion. This study contributed an alternative criterion for transmissibility-based damage detection in addition to the conventional ones. PMID:28773218

  12. Image region duplication detection based on circular window expansion and phase correlation.

    PubMed

    Shao, Hong; Yu, Tianshu; Xu, Mengjia; Cui, Wencheng

    2012-10-10

    Region duplication forgery is one of the tampering techniques that are frequently used, where a part of an image is copied and pasted into another part of the same image. In this paper, a phase correlation method based on polar expansion and adaptive band limitation is proposed for region duplication forgery detection. Our method starts by calculating the Fourier transform of the polar expansion on overlapping windows pair, and then an adaptive band limitation procedure is implemented to obtain a correlation matrix in which the peak is effectively enhanced. After estimating the rotation angle of the forgery region, a searching algorithm in the sense of seed filling is executed to display the whole duplicated region. Experimental results show that the proposed approach can detect duplicated region with high accuracy and robustness to rotation, illumination adjustment, blur and JPEG compression while rotation angle is estimated precisely for further calculation.

  13. 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.

  14. Non-invasive Imaging based Detection and Mapping of Brain Oxidative Stress and its Correlation with Cognitive Functions

    DTIC Science & Technology

    2017-05-14

    AFRL-AFOSR-JP-TR-2017-0052 Non-invasive Imaging based Detection and Mapping of Brain Oxidative Stress and its Correlation with Cognative Functions...Pravat Mandal National Brain Research Centre Final Report 05/14/2017 DISTRIBUTION A: Distribution approved for public release. AF Office Of Scientific...invasive Imaging based Detection and Mapping of Brain Oxidative Stress and its Correlation with Cognative Functions 5a.  CONTRACT NUMBER 5b.  GRANT

  15. A urinary biomarker-based risk score correlates with multiparametric MRI for prostate cancer detection.

    PubMed

    Hendriks, Rianne J; van der Leest, Marloes M G; Dijkstra, Siebren; Barentsz, Jelle O; Van Criekinge, Wim; Hulsbergen-van de Kaa, Christina A; Schalken, Jack A; Mulders, Peter F A; van Oort, Inge M

    2017-10-01

    Prostate cancer (PCa) diagnostics would greatly benefit from more accurate, non-invasive techniques for the detection of clinically significant disease, leading to a reduction of over-diagnosis and over-treatment. The aim of this study was to determine the association between a novel urinary biomarker-based risk score (SelectMDx), multiparametric MRI (mpMRI) outcomes, and biopsy results for PCa detection. This retrospective observational study used data from the validation study of the SelectMDx score, in which urine was collected after digital rectal examination from men undergoing prostate biopsies. A subset of these patients also underwent a mpMRI scan of the prostate. The indications for performing mpMRI were based on persistent clinical suspicion of PCa or local staging after PCa was found upon biopsy. All mpMRI images were centrally reviewed in 2016 by an experienced radiologist blinded for the urine test results and biopsy outcome. The PI-RADS version 2 was used. In total, 172 patients were included for analysis. Hundred (58%) patients had PCa detected upon prostate biopsy, of which 52 (52%) had high-grade disease correlated with a significantly higher SelectMDx score (P < 0.01). The median SelectMDx score was significantly higher in patients with a suspicious significant lesion on mpMRI compared to no suspicion of significant PCa (P < 0.01). For the prediction of mpMRI outcome, the area-under-the-curve of SelectMDx was 0.83 compared to 0.66 for PSA and 0.65 for PCA3. There was a positive association between SelectMDx score and the final PI-RADS grade. There was a statistically significant difference in SelectMDx score between PI-RADS 3 and 4 (P < 0.01) and between PI-RADS 4 and 5 (P < 0.01). The novel urinary biomarker-based SelectMDx score is a promising tool in PCa detection. This study showed promising results regarding the correlation between the SelectMDx score and mpMRI outcomes, outperforming PCA3. Our results suggest that this risk

  16. Correlation between human detection accuracy and observer model-based image quality metrics in computed tomography

    PubMed Central

    Solomon, Justin; Samei, Ehsan

    2016-01-01

    Abstract. The purpose of this study was to compare computed tomography (CT) low-contrast detectability from human readers with observer model-based surrogates of image quality. A phantom with a range of low-contrast signals (five contrasts, three sizes) was imaged on a state-of-the-art CT scanner (Siemens’ force). Images were reconstructed using filtered back projection and advanced modeled iterative reconstruction and were assessed by 11 readers using a two alternative forced choice method. Concurrently, contrast-to-noise ratio (CNR), area-weighted CNR (CNRA), and observer model-based metrics were estimated, including nonprewhitening (NPW) matched filter, NPW with eye filter (NPWE), NPW with internal noise, NPW with an eye filter and internal noise (NPWEi), channelized Hotelling observer (CHO), and CHO with internal noise (CHOi). The correlation coefficients (Pearson and Spearman), linear discriminator error, E, and magnitude of confidence intervals, |CI95%|, were used to determine correlation, proper characterization of the reconstruction algorithms, and model precision, respectively. Pearson (Spearman) correlation was 0.36 (0.33), 0.83 (0.84), 0.84 (0.86), 0.86 (0.88), 0.86 (0.91), 0.88 (0.90), 0.85 (0.89), and 0.87 (0.84), E was 0.25, 0.15, 0.2, 0.25, 0.3, 0.25, 0.4, and 0.45, and |CI95%| was 2.84×10−3, 5.29×10−3, 4.91×10−3, 4.55×10−3, 2.16×10−3, 1.24×10−3, 4.58×10−2, and 7.95×10−2 for CNR, CNRA, NPW, NPWE, NPWi, NPWEi, CHO, and CHOi, respectively. PMID:27704032

  17. [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.

  18. Automatic detection of noisy channels in fNIRS signal based on correlation analysis.

    PubMed

    Guerrero-Mosquera, Carlos; Borragán, Guillermo; Peigneux, Philippe

    2016-09-15

    fNIRS signals can be contaminated by distinct sources of noise. While most of the noise can be corrected using digital filters, optimized experimental paradigms or pre-processing methods, few approaches focus on the automatic detection of noisy channels. In the present study, we propose a new method that detect automatically noisy fNIRS channels by combining the global correlations of the signal obtained from sliding windows (Cui et al., 2010) with correlation coefficients extracted experimental conditions defined by triggers. The validity of the method was evaluated on test data from 17 participants, for a total of 16 NIRS channels per subject, positioned over frontal, dorsolateral prefrontal, parietal and occipital areas. Additionally, the detection of noisy channels was tested in the context of different levels of cognitive requirement in a working memory N-back paradigm. Bad channels detection accuracy, defined as the proportion of bad NIRS channels correctly detected among the total number of channels examined, was close to 91%. Under different cognitive conditions the area under the Receiver Operating Curve (AUC) increased from 60.5% (global correlations) to 91.2% (local correlations). Our results show that global correlations are insufficient for detecting potentially noisy channels when the whole data signal is included in the analysis. In contrast, adding specific local information inherent to the experimental paradigm (e.g., cognitive conditions in a block or event-related design), improved detection performance for noisy channels. Also, we show that automated fNIRS channel detection can be achieved with high accuracy at low computational cost. Copyright © 2016 Elsevier B.V. All rights reserved.

  19. 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.

  20. Baseline-free fatigue crack detection based on spectral correlation and nonlinear wave modulation

    NASA Astrophysics Data System (ADS)

    Liu, Peipei; Sohn, Hoon; Yang, Suyoung; Lim, Hyung Jin

    2016-12-01

    By generating ultrasonic waves at two different frequencies onto a cracked structure, modulations due to crack-induced nonlinearity can be observed in the corresponding ultrasonic response. This nonlinear wave modulation phenomenon has been widely studied and proven capable of detecting a fatigue crack at a very early stage. However, under field conditions, other exogenous vibrations exist and the modulation components can be buried under ambient noises, making it difficult to extract the modulation components simply by using a spectral density function. In this study, the nonlinear modulation components in the ultrasonic response were extracted using a spectral correlation function (the double Fourier transform) with respect to time and time lag of a signal’s autocorrelation. Using spectral correlation, noise or interference, which is spectrally overlapped with the nonlinear modulation components in the ultrasonic response, can be effectively removed or reduced. Only the nonlinear modulation components are accentuated at specific coordinates of the spectral correlation plot. A damage feature is defined by comparing the spectral correlation value between nonlinear modulation components with other spectral correlation values among randomly selected frequencies. Then, by analyzing the statistical characteristics of the multiple damage feature values obtained from different input frequency combinations, fatigue cracks can be detected without relying on baseline data obtained from the pristine condition of the target structure. In the end, an experimental test was conducted on aluminum plates with a real fatigue crack and the test signals were contaminated by simulated noises with varying signal-to-noise ratios. The results validated the proposed technique.

  1. 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.

  2. Impact of correlated magnetic noise on the detection of stochastic gravitational waves: Estimation based on a simple analytical model

    NASA Astrophysics Data System (ADS)

    Himemoto, Yoshiaki; Taruya, Atsushi

    2017-07-01

    After the first direct detection of gravitational waves (GW), detection of the stochastic background of GWs is an important next step, and the first GW event suggests that it is within the reach of the second-generation ground-based GW detectors. Such a GW signal is typically tiny and can be detected by cross-correlating the data from two spatially separated detectors if the detector noise is uncorrelated. It has been advocated, however, that the global magnetic fields in the Earth-ionosphere cavity produce the environmental disturbances at low-frequency bands, known as Schumann resonances, which potentially couple with GW detectors. In this paper, we present a simple analytical model to estimate its impact on the detection of stochastic GWs. The model crucially depends on the geometry of the detector pair through the directional coupling, and we investigate the basic properties of the correlated magnetic noise based on the analytic expressions. The model reproduces the major trend of the recently measured global correlation between the GW detectors via magnetometer. The estimated values of the impact of correlated noise also match those obtained from the measurement. Finally, we give an implication to the detection of stochastic GWs including upcoming detectors, KAGRA and LIGO India. The model suggests that LIGO Hanford-Virgo and Virgo-KAGRA pairs are possibly less sensitive to the correlated noise and can achieve a better sensitivity to the stochastic GW signal in the most pessimistic case.

  3. Correlation-based target detection for the Navy's SHARP sensor suite

    NASA Astrophysics Data System (ADS)

    Topiwala, Pankaj N.; Casasent, David P.

    2004-09-01

    High resolution, high data rate sensor streams acquired from the Navy Shared Reconnaissance Pod (SHARP), encompassing unsurpassed resolution EO and IR sensors, covering large tactical areas with detailed surveillance information, will overwhelm current signal processing and communications capabilities. However, the value and utility of these data streams is dependent on their subsequent exploitation and timely dissemination to appropriate commanders. This situation renders real-time surveillance infeasible without significant advances in each of these areas: signal processing, communications, and interpretation. Data compression, encryption, and other related technologies play a vital role here. Here we focus on the target recognition problem from an ultra-high resolution SHARP sensor suite, specifically on the detection in the EO domain. The theory of correlation filters (MACH, MACE, etc.), developed by Casasent and company at CMU has been typically used for classification purposes in the past. Herein we develop innovative low-complexity Correlation Eigen-Filters (CEFs), which have the unique advantage of offering detection capability for one or multiple objects, over a wide range of aspect angles (up to full 360 degrees), using as few as a single filter. In the paper, we develop a theoretical analysis of the CEF filter design, and provide some application examples. Figure 1 illustrates a case in point: various military aircraft are detected with perfect performance (Pd = 1.0, Pfa = 0) by training CEF filters on examples aircraft in other imagery, and testing on sequestered data. We not only diverge from traditional correlation-filter methods in that we use the correlation filter as a detector, but also to develop a novel feature space in which to do discrimination analysis, figure 1c.

  4. 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.

  5. Multifractal detrended fluctuation analysis based on fractal fitting: The long-range correlation detection method for highway volume data

    NASA Astrophysics Data System (ADS)

    Dai, Meifeng; Hou, Jie; Ye, Dandan

    2016-02-01

    In this paper, we investigate the traffic time series for volume data observed on the Guangshen highway. We introduce a multifractal detrended fluctuation analysis based on fractal fitting (MFDFA-FF), which is one of the most effective methods to detect long-range correlations of time series. Through effective detecting of long-range correlations, highway volume can be predicted more accurately. In order to get a better detrend effect, we use fractal fitting to replace polynomial fitting in detrend process, the result shows that fractal fitting can get a better detrend effect than polynomial fitting and the MFDFA-FF method can achieve a more accurate research result. Then we introduce the Legendre spectrum to detect the multifractal property characterized by the long-range correlation and multifractality of Guangshen highway volume data.

  6. Neural correlates of tactile detection: a combined magnetoencephalography and biophysically based computational modeling study.

    PubMed

    Jones, Stephanie R; Pritchett, Dominique L; Stufflebeam, Steven M; Hämäläinen, Matti; Moore, Christopher I

    2007-10-03

    Previous reports conflict as to the role of primary somatosensory neocortex (SI) in tactile detection. We addressed this question in normal human subjects using whole-head magnetoencephalography (MEG) recording. We found that the evoked signal (0-175 ms) showed a prominent equivalent current dipole that localized to the anterior bank of the postcentral gyrus, area 3b of SI. The magnitude and timing of peaks in the SI waveform were stimulus amplitude dependent and predicted perception beginning at approximately 70 ms after stimulus. To make a direct and principled connection between the SI waveform and underlying neural dynamics, we developed a biophysically realistic computational SI model that contained excitatory and inhibitory neurons in supragranular and infragranular layers. The SI evoked response was successfully reproduced from the intracellular currents in pyramidal neurons driven by a sequence of lamina-specific excitatory input, consisting of output from the granular layer (approximately 25 ms), exogenous input to the supragranular layers (approximately 70 ms), and a second wave of granular output (approximately 135 ms). The model also predicted that SI correlates of perception reflect stronger and shorter-latency supragranular and late granular drive during perceived trials. These findings strongly support the view that signatures of tactile detection are present in human SI and are mediated by local neural dynamics induced by lamina-specific synaptic drive. Furthermore, our model provides a biophysically realistic solution to the MEG signal and can predict the electrophysiological correlates of human perception.

  7. Neural Correlates of Tactile Detection: A Combined Magnetoencephalography and Biophysically Based Computational Modeling Study

    PubMed Central

    Jones, Stephanie R.; Pritchett, Dominique L.; Stufflebeam, Steven M.; Hämäläinen, Matti; Moore, Christopher I.

    2010-01-01

    Previous reports conflict as to the role of primary somatosensory neocortex (SI) in tactile detection. We addressed this question in normal human subjects using whole-head magnetoencephalography (MEG) recording. We found that the evoked signal (0 –175 ms) showed a prominent equivalent current dipole that localized to the anterior bank of the postcentral gyrus, area 3b of SI. The magnitude and timing of peaks in the SI waveform were stimulus amplitude dependent and predicted perception beginning at ~70 ms after stimulus. To make a direct and principled connection between the SI waveform and underlying neural dynamics, we developed a biophysically realistic computational SI model that contained excitatory and inhibitory neurons in supragranular and infragranular layers. The SI evoked response was successfully reproduced from the intracellular currents in pyramidal neurons driven by a sequence of lamina-specific excitatory input, consisting of output from the granular layer (~25 ms), exogenous input to the supragranular layers (~70 ms), and a second wave of granular output (~135 ms). The model also predicted that SI correlates of perception reflect stronger and shorter-latency supragranular and late granular drive during perceived trials. These findings strongly support the view that signatures of tactile detection are present in human SI and are mediated by local neural dynamics induced by lamina-specific synaptic drive. Furthermore, our model provides a biophysically realistic solution to the MEG signal and can predict the electrophysiological correlates of human perception. PMID:17913909

  8. Spatial correlation coefficient images for ultrasonic detection.

    PubMed

    Cepel, Raina; Ho, K C; Rinker, Brett A; Palmer, Donald D; Lerch, Terrence P; Neal, Steven P

    2007-09-01

    In ultrasonics, image formation and detection are generally based on signal amplitude. In this paper, we introduce correlation coefficient images as a signal-amplitude independent approach for image formation. The correlation coefficients are calculated between A-scans digitized at adjacent measurement positions. In these images, defects are revealed as regions of high or low correlation relative to the background correlations associated with noise. Correlation coefficient and C-scan images are shown to demonstrate flat-bottom-hole detection in a stainless steel annular ring and crack detection in an aluminum aircraft structure.

  9. Ultrasonic Detection Using Correlation Images (Preprint)

    DTIC Science & Technology

    2006-08-01

    for imaging and detection based on the similarity of adjacent signals, quantified by the correlation coefficient calculated between A-scans... Correlation coefficient images are introduced and shown with C-scan images to demonstrate flat-bottom-hole and crack detection in experimental data and planar

  10. Microevent Detection Based on Waveform Cross-correlation in the Dogye Mining Area, Korea

    NASA Astrophysics Data System (ADS)

    Son, M.; Shin, J. S.; Kim, G.

    2015-12-01

    We have studied induced seismicity associated with Dogye coal mine located in the eastern part of Korea. From May 2009 to March 2014, 222 events that occurred at the mining area were reported in our catalog with local magnitudes ranging from 0.6 to 2.4. For 67 events we can observe that the epicenters relocated by the double difference technique with Lg waveform cross-correlation image location of the six clusters classified according to waveform similarity. On May 2014 a broadband seismometer is installed in the mine office to understand seismicity of the mining area. We cross-correlate continuous data of the installed station recorded from May 2014 to April 2015 with a comb-like waveform observed regularly. The comb-like waveform with length of 30 to 60 minutes is a signal train composed of a blast every 30 seconds. We consider the comb-like signal related directly to mining activity from the fact that the signal train appears averagely four times a day on weekdays with its monotonic amplitude. Besides the comb-like signal, events with an irregular occurrence time and amplitude is detected from the one-year continuous record of the installed station. We suggests that most of the undefined events are formed from fracturing in response to stress-perturbation on an active mining face or represent slip in existing shear zones such as a fault or dike.

  11. Hotspot detection using image pattern recognition based on higher-order local auto-correlation

    NASA Astrophysics Data System (ADS)

    Maeda, Shimon; Matsunawa, Tetsuaki; Ogawa, Ryuji; Ichikawa, Hirotaka; Takahata, Kazuhiro; Miyairi, Masahiro; Kotani, Toshiya; Nojima, Shigeki; Tanaka, Satoshi; Nakagawa, Kei; Saito, Tamaki; Mimotogi, Shoji; Inoue, Soichi; Nosato, Hirokazu; Sakanashi, Hidenori; Kobayashi, Takumi; Murakawa, Masahiro; Higuchi, Tetsuya; Takahashi, Eiichi; Otsu, Nobuyuki

    2011-04-01

    Below 40nm design node, systematic variation due to lithography must be taken into consideration during the early stage of design. So far, litho-aware design using lithography simulation models has been widely applied to assure that designs are printed on silicon without any error. However, the lithography simulation approach is very time consuming, and under time-to-market pressure, repetitive redesign by this approach may result in the missing of the market window. This paper proposes a fast hotspot detection support method by flexible and intelligent vision system image pattern recognition based on Higher-Order Local Autocorrelation. Our method learns the geometrical properties of the given design data without any defects as normal patterns, and automatically detects the design patterns with hotspots from the test data as abnormal patterns. The Higher-Order Local Autocorrelation method can extract features from the graphic image of design pattern, and computational cost of the extraction is constant regardless of the number of design pattern polygons. This approach can reduce turnaround time (TAT) dramatically only on 1CPU, compared with the conventional simulation-based approach, and by distributed processing, this has proven to deliver linear scalability with each additional CPU.

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

    PubMed

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

    2015-01-01

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

  13. Harmful intrusion detection algorithm of optical fiber pre-warning system based on correlation of orthogonal polarization signals

    NASA Astrophysics Data System (ADS)

    Bi, Fukun; Feng, Chong; Qu, Hongquan; Zheng, Tong; Wang, Chonglei

    2017-09-01

    At present, advanced researches of optical fiber intrusion measurement are based on the constant false alarm rate (CFAR) algorithm. Although these conventional methods overcome the interference of non-stationary random signals, there are still a large number of false alarms in practical applications. This is because there is no specific study on orthogonal polarization signals of false alarm and intrusion. In order to further reduce false alarms, we analyze the correlation of optical fiber signals using birefringence of single-mode fiber. This paper proposes the harmful intrusion detection algorithm based on the correlation of two orthogonal polarization signals. The proposed method uses correlation coefficient to distinguish false alarms and intrusions, which can decrease false alarms. Experiments on real data, which are collected from the practical environment, demonstrate that the difference in correlation is a robust feature. Furthermore, the results show that the proposed algorithm can reduce the false alarms and ensure the detection performance when it is used in optical fiber pre-warning system (OFPS).

  14. 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.

  15. 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.

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

    PubMed

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

    2013-03-01

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

  17. 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.

  18. Urban vehicle detection in high-resolution aerial images via superpixel segmentation and correlation-based sequential dictionary learning

    NASA Astrophysics Data System (ADS)

    Zhang, Xunxun; Xu, Hongke; Fang, Jianwu; Sheng, Gang

    2017-04-01

    Vehicle detection in high-resolution aerial images has received widespread interests when it comes to providing the required information for traffic management and urban planning. It is challenging due to the relatively small size of the vehicles and the complex background. Furthermore, it is particularly challenging if the higher detection efficiency is required. Therefore, an urban vehicle detection algorithm is proposed via improved entropy rate clustering (IERC) and correlation-based sequential dictionary learning (CSDL). First, to enhance the detection accuracy, IERC is designed to generate more regular superpixels. It aims to avoid the situation that one superpixel sometimes straddles multiple vehicles. The generated superpixels are then treated as the seeds for the training sample selection. Then, CSDL is constructed to achieve a fast sequential training and updating of the dictionary. In CSDL, only the atoms correlated with the sparse representation of the new training data are inferred. Finally, comprehensive analyses and comparisons on two data sets demonstrate that the proposed method generates satisfactory and competitive results.

  19. Electrophysiological correlates of change detection.

    PubMed

    Eimer, Martin; Mazza, Veronica

    2005-05-01

    To identify electrophysiological correlates of change detection, event-related brain potentials (ERPs) were recorded while participants monitored displays containing four faces in order to detect a face identity change across successive displays. Successful change detection was mirrored by an N2pc component at posterior electrodes contralateral to the side of a change, suggesting close links between conscious change detection and attention. ERPs on undetected-change trials differed from detected-change and no-change trials. We suggest that short-latency ERP differences between these trial types reflect trial-by-trial fluctuations in advance task preparation, whereas differences in the P3 time range are due to variations in the duration of perceptual and decision-related processing. Overall, these findings demonstrate that ERPs are a useful tool for dissociating processes underlying change blindness and change detection.

  20. Detection and Identification of Multiple Stationary Human Targets Via Bio-Radar Based on the Cross-Correlation Method

    PubMed Central

    Zhang, Yang; Chen, Fuming; Xue, Huijun; Li, Zhao; An, Qiang; Wang, Jianqi; Zhang, Yang

    2016-01-01

    Ultra-wideband (UWB) radar has been widely used for detecting human physiological signals (respiration, movement, etc.) in the fields of rescue, security, and medicine owing to its high penetrability and range resolution. In these applications, especially in rescue after disaster (earthquake, collapse, mine accident, etc.), the presence, number, and location of the trapped victims to be detected and rescued are the key issues of concern. Ample research has been done on the first issue, whereas the identification and localization of multi-targets remains a challenge. False positive and negative identification results are two common problems associated with the detection of multiple stationary human targets. This is mainly because the energy of the signal reflected from the target close to the receiving antenna is considerably stronger than those of the targets at further range, often leading to missing or false recognition if the identification method is based on the energy of the respiratory signal. Therefore, a novel method based on cross-correlation is proposed in this paper that is based on the relativity and periodicity of the signals, rather than on the energy. The validity of this method is confirmed through experiments using different scenarios; the results indicate a discernible improvement in the detection precision and identification of the multiple stationary targets. PMID:27801795

  1. Detection and Identification of Multiple Stationary Human Targets Via Bio-Radar Based on the Cross-Correlation Method.

    PubMed

    Zhang, Yang; Chen, Fuming; Xue, Huijun; Li, Zhao; An, Qiang; Wang, Jianqi; Zhang, Yang

    2016-10-27

    Ultra-wideband (UWB) radar has been widely used for detecting human physiological signals (respiration, movement, etc.) in the fields of rescue, security, and medicine owing to its high penetrability and range resolution. In these applications, especially in rescue after disaster (earthquake, collapse, mine accident, etc.), the presence, number, and location of the trapped victims to be detected and rescued are the key issues of concern. Ample research has been done on the first issue, whereas the identification and localization of multi-targets remains a challenge. False positive and negative identification results are two common problems associated with the detection of multiple stationary human targets. This is mainly because the energy of the signal reflected from the target close to the receiving antenna is considerably stronger than those of the targets at further range, often leading to missing or false recognition if the identification method is based on the energy of the respiratory signal. Therefore, a novel method based on cross-correlation is proposed in this paper that is based on the relativity and periodicity of the signals, rather than on the energy. The validity of this method is confirmed through experiments using different scenarios; the results indicate a discernible improvement in the detection precision and identification of the multiple stationary targets.

  2. A Dynamically Configurable Log-based Distributed Security Event Detection Methodology using Simple Event Correlator

    DTIC Science & Technology

    2010-06-01

    from SANS Whitepaper - "... Detecting Attacks on Web Applications from Log Files" #look for image tags type=Single continue=TakeNext ptype=RegExp...shellcmd /home/user/sec -2.5.3/ common/syslogclient "... Synthetic : " "$2|$1|xss detected in image tag: $3" #send the raw log type=Single ptype=RegExp...Expressions taken from SANS Whitepaper - "... Detecting Attacks on Web Applications from Log Files" #look for image tags type=Single continue=TakeNext

  3. Algorithms For Detection Of Correlation Spots

    NASA Technical Reports Server (NTRS)

    Scholl, Marija S.; Udomkesmalee, Suraphol

    1993-01-01

    Three algorithms provide for improved postprocessing of outputs of optical correlators based on binary phase-only filters. Detect correlation spots. Function in presence of noise and executed rapidly. First algorithm starts processing correlation-image data while data fed out of video camera and digitized for subsequent analysis. Second involves convolution of correlation image with small-window two-dimensional impulse-response function followed by threshold operation in which negative values of convolution integral set to zero. Third affects generation as well as postprocessing of correlation image.

  4. Real-time phase correlation based integrated system for seizure detection

    NASA Astrophysics Data System (ADS)

    Romaine, James B.; Delgado-Restituto, Manuel; Leñero-Bardallo, Juan A.; Rodríguez-Vázquez, Ángel

    2017-05-01

    This paper reports a low area, low power, integer-based digital processor for the calculation of phase synchronization between two neural signals. The processor calculates the phase-frequency content of a signal by identifying the specific time periods associated with two consecutive minima. The simplicity of this phase-frequency content identifier allows for the digital processor to utilize only basic digital blocks, such as registers, counters, adders and subtractors, without incorporating any complex multiplication and or division algorithms. In fact, the processor, fabricated in a 0.18μm CMOS process, only occupies an area of 0.0625μm2 and consumes 12.5nW from a 1.2V supply voltage when operated at 128kHz. These low-area, low-power features make the proposed processor a valuable computing element in closed loop neural prosthesis for the treatment of neural diseases, such as epilepsy, or for extracting functional connectivity maps between different recording sites in the brain.

  5. Correlation between adenoma detection rate in colonoscopy- and fecal immunochemical testing-based colorectal cancer screening programs.

    PubMed

    Cubiella, Joaquín; Castells, Antoni; Andreu, Montserrat; Bujanda, Luis; Carballo, Fernando; Jover, Rodrigo; Lanas, Ángel; Morillas, Juan Diego; Salas, Dolores; Quintero, Enrique

    2017-03-01

    The adenoma detection rate (ADR) is the main quality indicator of colonoscopy. The ADR recommended in fecal immunochemical testing (FIT)-based colorectal cancer screening programs is unknown. Using the COLONPREV (NCT00906997) study dataset, we performed a post-hoc analysis to determine if there was a correlation between the ADR in primary and work-up colonoscopy, and the equivalent figure to the minimal 20% ADR recommended. Colonoscopy was performed in 5722 individuals: 5059 as primary strategy and 663 after a positive FIT result (OC-Sensor™; cut-off level 15 µg/g of feces). We developed a predictive model based on a multivariable lineal regression analysis including confounding variables. The median ADR was 31% (range, 14%-51%) in the colonoscopy group and 55% (range, 21%-83%) in the FIT group. There was a positive correlation in the ADR between primary and work-up colonoscopy (Pearson's coefficient 0.716; p < 0.001). ADR in the FIT group was independently related to ADR in the colonoscopy group: regression coefficient for colonoscopy ADR, 0.71 (p = 0.009); sex, 0.09 (p = 0.09); age, 0.3 (p = 0.5); and region 0.00 (p = 0.9). The equivalent figure to the 20% ADR was 45% (95% confidence interval, 35%-56%). ADR in primary and work-up colonoscopy of a FIT-positive result are positively and significantly correlated.

  6. Correlation between adenoma detection rate in colonoscopy- and fecal immunochemical testing-based colorectal cancer screening programs

    PubMed Central

    Castells, Antoni; Andreu, Montserrat; Bujanda, Luis; Carballo, Fernando; Jover, Rodrigo; Lanas, Ángel; Morillas, Juan Diego; Salas, Dolores; Quintero, Enrique

    2016-01-01

    Background The adenoma detection rate (ADR) is the main quality indicator of colonoscopy. The ADR recommended in fecal immunochemical testing (FIT)-based colorectal cancer screening programs is unknown. Methods Using the COLONPREV (NCT00906997) study dataset, we performed a post-hoc analysis to determine if there was a correlation between the ADR in primary and work-up colonoscopy, and the equivalent figure to the minimal 20% ADR recommended. Colonoscopy was performed in 5722 individuals: 5059 as primary strategy and 663 after a positive FIT result (OC-Sensor™; cut-off level 15 µg/g of feces). We developed a predictive model based on a multivariable lineal regression analysis including confounding variables. Results The median ADR was 31% (range, 14%–51%) in the colonoscopy group and 55% (range, 21%–83%) in the FIT group. There was a positive correlation in the ADR between primary and work-up colonoscopy (Pearson’s coefficient 0.716; p < 0.001). ADR in the FIT group was independently related to ADR in the colonoscopy group: regression coefficient for colonoscopy ADR, 0.71 (p = 0.009); sex, 0.09 (p = 0.09); age, 0.3 (p = 0.5); and region 0.00 (p = 0.9). The equivalent figure to the 20% ADR was 45% (95% confidence interval, 35%–56%). Conclusions ADR in primary and work-up colonoscopy of a FIT-positive result are positively and significantly correlated. PMID:28344793

  7. 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.

  8. 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

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

    PubMed Central

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

    2013-01-01

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

  10. 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

  11. Sequence detection analysis based on canonical correlation for steady-state visual evoked potential brain computer interfaces.

    PubMed

    Cao, Lei; Ju, Zhengyu; Li, Jie; Jian, Rongjun; Jiang, Changjun

    2015-09-30

    Steady-state visual evoked potential (SSVEP) has been widely applied to develop brain computer interface (BCI) systems. The essence of SSVEP recognition is to recognize the frequency component of target stimulus focused by a subject significantly present in EEG spectrum. In this paper, a novel statistical approach based on sequence detection (SD) is proposed for improving the performance of SSVEP recognition. This method uses canonical correlation analysis (CCA) coefficients to observe SSVEP signal sequence. And then, a threshold strategy is utilized for SSVEP recognition. The result showed the classification performance with the longer duration of time window achieved the higher accuracy for most subjects. And the average time costing per trial was lower than the predefined recognition time. It was implicated that our approach could improve the speed of BCI system in contrast to other methods. Comparison with existing method(s): In comparison with other resultful algorithms, experimental accuracy of SD approach was better than those using a widely used CCA-based method and two newly proposed algorithms, least absolute shrinkage and selection operator (LASSO) recognition model as well as multivariate synchronization index (MSI) method. Furthermore, the information transfer rate (ITR) obtained by SD approach was higher than those using other three methods for most participants. These conclusions demonstrated that our proposed method was promising for a high-speed online BCI. Copyright © 2015 Elsevier B.V. All rights reserved.

  12. A Small Leak Detection Method Based on VMD Adaptive De-Noising and Ambiguity Correlation Classification Intended for Natural Gas Pipelines

    PubMed Central

    Xiao, Qiyang; Li, Jian; Bai, Zhiliang; Sun, Jiedi; Zhou, Nan; Zeng, Zhoumo

    2016-01-01

    In this study, a small leak detection method based on variational mode decomposition (VMD) and ambiguity correlation classification (ACC) is proposed. The signals acquired from sensors were decomposed using the VMD, and numerous components were obtained. According to the probability density function (PDF), an adaptive de-noising algorithm based on VMD is proposed for noise component processing and de-noised components reconstruction. Furthermore, the ambiguity function image was employed for analysis of the reconstructed signals. Based on the correlation coefficient, ACC is proposed to detect the small leak of pipeline. The analysis of pipeline leakage signals, using 1 mm and 2 mm leaks, has shown that proposed detection method can detect a small leak accurately and effectively. Moreover, the experimental results have shown that the proposed method achieved better performances than support vector machine (SVM) and back propagation neural network (BP) methods. PMID:27983577

  13. A Small Leak Detection Method Based on VMD Adaptive De-Noising and Ambiguity Correlation Classification Intended for Natural Gas Pipelines.

    PubMed

    Xiao, Qiyang; Li, Jian; Bai, Zhiliang; Sun, Jiedi; Zhou, Nan; Zeng, Zhoumo

    2016-12-13

    In this study, a small leak detection method based on variational mode decomposition (VMD) and ambiguity correlation classification (ACC) is proposed. The signals acquired from sensors were decomposed using the VMD, and numerous components were obtained. According to the probability density function (PDF), an adaptive de-noising algorithm based on VMD is proposed for noise component processing and de-noised components reconstruction. Furthermore, the ambiguity function image was employed for analysis of the reconstructed signals. Based on the correlation coefficient, ACC is proposed to detect the small leak of pipeline. The analysis of pipeline leakage signals, using 1 mm and 2 mm leaks, has shown that proposed detection method can detect a small leak accurately and effectively. Moreover, the experimental results have shown that the proposed method achieved better performances than support vector machine (SVM) and back propagation neural network (BP) methods.

  14. 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).

  15. Detecting protein atom correlations using correlation of probability of recurrence.

    PubMed

    Fataftah, Hiba; Karain, Wael

    2014-09-01

    The dynamic cross-correlation Map(DCCM) technique has been used extensively to study protein dynamics. In this work, we introduce the use of the method of correlation of probability of recurrence (CPR) as a complementary method to detect correlations between protein residue atoms. Time series of the distances of the Cα atoms of the β-lactamase inhibitory protein (BLIP) from a reference position are analyzed using CPR and mutual information (MI). The results are compared to those provided by DCCM. In comparison to MI, CPR is found to detect more of the correlations present in DCCM. It is also able to detect a small number of significant correlations between distant residues that are not detected by DCCM. © 2014 Wiley Periodicals, Inc.

  16. 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

  17. Progress of a cross-correlation based optical strain measurement technique for detecting radial growth on a rotating disk

    NASA Astrophysics Data System (ADS)

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

    2014-04-01

    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

  18. Detection of diluted contaminants on chicken carcasses using a two-dimensional scatter plot based on a two-dimensional hyperspectral correlation spectrum.

    PubMed

    Wu, Wei; Chen, Gui-Yun; Wu, Ming-Qing; Yu, Zhen-Wei; Chen, Kun-Jie

    2017-03-20

    A two-dimensional (2D) scatter plot method based on the 2D hyperspectral correlation spectrum is proposed to detect diluted blood, bile, and feces from the cecum and duodenum on chicken carcasses. First, from the collected hyperspectral data, a set of uncontaminated regions of interest (ROIs) and four sets of contaminated ROIs were selected, whose average spectra were treated as the original spectrum and influenced spectra, respectively. Then, the difference spectra were obtained and used to conduct correlation analysis, from which the 2D hyperspectral correlation spectrum was constructed using the analogy method of 2D IR correlation spectroscopy. Two maximum auto-peaks and a pair of cross peaks appeared at 656 and 474 nm. Therefore, 656 and 474 nm were selected as the characteristic bands because they were most sensitive to the spectral change induced by the contaminants. The 2D scatter plots of the contaminants, clean skin, and background in the 474- and 656-nm space were used to distinguish the contaminants from the clean skin and background. The threshold values of the 474- and 656-nm bands were determined by receiver operating characteristic (ROC) analysis. According to the ROC results, a pixel whose relative reflectance at 656 nm was greater than 0.5 and relative reflectance at 474 nm was lower than 0.3 was judged as a contaminated pixel. A region with more than 50 pixels identified was marked in the detection graph. This detection method achieved a recognition rate of up to 95.03% at the region level and 31.84% at the pixel level. The false-positive rate was only 0.82% at the pixel level. The results of this study confirm that the 2D scatter plot method based on the 2D hyperspectral correlation spectrum is an effective method for detecting diluted contaminants on chicken carcasses.

  19. 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.

  20. Spatial Correlation Coefficient Images for Ultrasonic Detection (Preprint)

    DTIC Science & Technology

    2006-07-01

    for image formation and detection based on the similarity of adjacent signals. Signal similarity is quantified in terms of the correlation coefficient calculated...between A-scans digitized at adjacent measurement positions. Correlation coefficient images are introduced for visualizing the similarity...beam field with the defect. Correlation coefficient and C-scan images are shown to demonstrate flat-bottom-hole detection in a stainless steel annular

  1. Multi-point hydrogen detection system using hetero-core structured optical fiber hydrogen tip sensor based on surface plasmon resonance and pseudorandom noise code correlation reflectometry

    NASA Astrophysics Data System (ADS)

    Hosoki, Ai; Nishiyama, Michiko; Igawa, Hirotaka; Seki, Atsushi; Watanabe, Kazuhiro

    2015-07-01

    In this paper, the multi-point hydrogen detection system using the hetero-core optical fiber hydrogen tip sensor based on surface plasmon resonance (SPR) and Pseudorandom Noise code correlation reflectometry (PNCR) has been proposed. This method makes use of the correlation between a launched pseudorandom noise code signal and its reflection, can obtain a high signal to noise ration. We demonstrated the 4 sensors characteristics to 4% hydrogen. It was observed from experimental results that all sensors induced a response time of 15 s for 4% hydrogen for the 25-nm Au / 60-nm Ta2O5 / 5-nm Pd multi-layers film. In addition, all sensors were detected the hydrogen concentration with sufficient sensitivities.

  2. Gas correlation lidar for methane detection

    NASA Technical Reports Server (NTRS)

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

    1986-01-01

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

  3. 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.

  4. High Accuracy Verification of a Correlated-Photon-Based Method for Determining Photon-Counting Detection Efficiency

    DTIC Science & Technology

    2007-01-01

    with Correlated Visible Photons: Technique Verification and Measurement Uncertainty,” Metrologia 32, 479–483 (1995/6). 13. G. Brida , S. Castelletto...2007 (C) 2007 OSA 19 February 2007 / Vol. 15, No. 4 / OPTICS EXPRESS 1390 14. G. Brida , S. Castelletto, I. P. Degiovanni, M. Genovese, C. Novero

  5. [Detection of human papilloma virus (HPV) in liquid-based cervical samples. Correlation with protein p16INK4a expression].

    PubMed

    Toro de Méndez, Morelva; Ferrández Izquierdo, Antonio

    2011-03-01

    The liquid-based cervical cytology improves the quality of the sample and the residual sample could be used efficiently to carry out complementary tests, such as the detection of HPV DNA and the immunocytochemical biomarkers study. The purpose of this study was to correlate the presence of HPV and immunoexpression of p16INK4a in liquid-based cervical samples to examine the utility of these new tools in the detection of cervical cancer. The included patients (n = 67) presented an abnormal cytology or previous cervical pathology. The HPV detection and genotyping were carried out with PCR-SPF10/LiPA (INNOLiPA Extra Amp) and for p16INK4a immunodetection was used antibody clone E6H4. The conventional cytology provided the same cytologic interpretations that those of liquid-based cytology. The overall HPV prevalence was 43.3% (29/67). HPV16 was the most frequent viral type (31.03%) and 48.3% of the cases were infected with multiple HPV types. p16INK4a immunoexpression was observed in 35.8% of liquid-based cytological samples and this was significantly (p < 0.020) associated to the HPV presence. These results support the evidence that the implementation of new technologies in the daily routine of the laboratory, contribute significantly in the early detection of cervical cancer and provide important data to help in the patient's efficient management. The combined use of HPV detection and p16INK4a expression could be used for evaluation of patients with more risk to develop significant cervical lesions.

  6. 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.

  7. Multiparametric 3T Prostate MR Imaging to Detect Cancer: Histopathologic Correlation Using Prostatectomy Specimens Processed in Customized MRI-Based Molds

    PubMed Central

    Turkbey, Baris; Mani, Haresh; Shah, Vijay; Rastinehad, Ardeshir R.; Bernardo, Marcelino; Pohida, Thomas; Pang, Yuxi; Daar Dagane, R.T.; Benjamin, Compton; McKinney, Yolanda L.; Trivedi, Hari; Chua, Celene; Bratslavsky, Gennady; Shih, Joanna H.; Linehan, William M.; Merino, Maria J.; Choyke, Peter L.; Pinto, Peter A.

    2017-01-01

    Purpose To determine the prostate cancer detection rate of multi-parametric (MP) MRI at 3T. Precise one to one histopathologic correlation with MRI was possible using prostate MRI based custom-printed specimen molds following radical prostatectomy. Materials and methods This IRB approved prospective study included forty-five patients (mean age 60.2 years, range 49–75 years) with a mean PSA of 6.37ng/mL (range 2.3–23.7ng/mL), who had biopsy proven prostate cancer (mean Gleason score of 6.7; range 6 to 9). Prior to prostatectomy, all patients underwent prostate MRI on a 3T scanner which included tri-plane T2 weighted MRI, apparent diffusion coefficient maps of diffusion weighted MRI, dynamic contrast enhanced MRI, and spectroscopy.. The prostate specimen was whole mount sectioned in the mold allowing geometric alignment to MRI. Tumors were mapped on MRI and histopathology.. Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of MRI for cancer detection were calculated. Additionally, the effects of tumor size and Gleason score on sensitivity of MP-MRI were evaluated. Results PPV of MP-MRI to detect prostate cancer was 98%, 98%, and 100% in overall prostate, peripheral zone, and central gland, respectively. Sensitivities of MRI sequences were higher for tumors >5mm in diameter, as well as for tumors with higher Gleason scores (>7) (p<0.05). Conclusion Prostate MRI at 3T allows for the detection of prostate cancer. A multi-parametric approach increases the predictive power of MRI for diagnosis. In this study, accurate correlation between MP-MRI and histopathology was obtained by the patient specific MRI-based mold technique. PMID:21944089

  8. Change Point Detection in Correlation Networks

    NASA Astrophysics Data System (ADS)

    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.

  9. 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

  10. Fatigue Crack Detection Using Digital Image Correlation

    NASA Astrophysics Data System (ADS)

    Cawley, P.; Hutt, T. D.

    2009-03-01

    At present, detecting structural defects such as cracking and corrosion before they become critical is largely achieved by time consuming techniques such as eddy current and ultrasonic testing. These techniques require point-by-point scanning over the area to be tested. Digital Image Correlation could provide a cheaper and quicker testing technique. It works by correlating images of the structure surface in unloaded and loaded states taken with a standard digital camera, giving the displacement and strain fields. The specific case of a crack at a hole in an aluminium plate was investigated. It was found that the strain concentration around the crack tip is too localised to detect; however the displacement jump across the crack could be seen. This technique allows the cracks to be detected and would allow rapid testing of a structure if it can easily be loaded.

  11. 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.

  12. Correlation Based Geomagnetic Field Modeling

    NASA Astrophysics Data System (ADS)

    Holschneider, M.; Mauerberger, S.; Lesur, V.; Baerenzung, J.

    2015-12-01

    We present a new method for determining geomagnetic field models. It is based on the construction of an a priori correlation structure derived from our knowledge about characteristic length scales and sources of the geomagnetic field. The magnetic field measurements are then seen as correlated random variables too and the inversion process amounts to compute the a posteriori correlation structure using Bayes theorem. We show how this technique allows the statistical separation of the various field contributions and the assessment of their uncertainties.

  13. Quadratic Gabor correlation filters for object detection

    NASA Astrophysics Data System (ADS)

    Weber, David; Casasent, David P.

    1996-10-01

    We present a new class of quadratic filters that are capable of creating spherical, elliptical, hyperbolic and linear decision surfaces which result in better detection and classification capabilities than the linear decision surfaces obtained from correlation filters. Each filter comprises of a number of separately designed linear basis filters. These filters are linearly combined into several macro filters; the output from these macro filters are passed through a magnitude square operation and are then linearly combined using real weights to achieve the quadratic decision surface. This nonlinear fusion algorithm is called the extended piecewise quadratic neural network (E-PQNN). For detection, the creation of macro filters allows for a substantial computational saving by reducing the number of correlation operations required. In this work, we consider the use of Gabor basis filters; the Gabor filter parameters are separately optimized; the fusion parameters to combine the Gabor filter outputs are optimized using the conjugate gradient method; they and the nonlinear combination of filter outputs are included in our E-PQNN algorithm. We demonstrate methods for selecting the number of macro Gabor filters, the filter parameters and the linear and nonlinear combination coefficients. We prove that our simple E-PQNN architecture is able to generate arbitrary piecewise quadratic decision surfaces. We present preliminary results obtained for an IR vehicle detection problem.

  14. Quadratic Gabor correlation filters for object detection

    NASA Astrophysics Data System (ADS)

    Weber, David; Casasent, David P.

    1997-04-01

    We present a new class of quadratic filters that are capable of creating spherical, elliptical, hyperbolic and linear decision surfaces which result in better detection and classification capabilities than the linear decision surfaces obtained from correlation filters. Each filter comprises of a number of separately designed linear basis filters. These filters are linearly combined into several macro filters; the output from these macro filters are passed through a magnitude square operation and are then linearly combined using real weights to achieve the quadratic decision surface. This non-linear fusion algorithm is called the extended piecewise quadratic neural network (E-PQNN). For detection, the creation of macro filters allows for a substantial computational saving by reducing the number of correlation operations required. In this work, we consider the use of Gabor basis filters; the Gabor filter parameters are separately optimized; the fusion parameters to combine the Gabor filter outputs are optimized using the conjugate gradient method; they and the non-linear combination of filter outputs are included in our E-PQNN algorithm. We demonstrate methods for selecting the number of macro Gabor filters, the filter parameters and the linear and non-linear combination coefficients. We prove that our simple E-PQNN architecture is able to generate arbitrary piecewise quadratic decision surfaces. We present preliminary results obtained for an IR vehicle detection problem.

  15. Neuroanatomical correlates of biological motion detection

    PubMed Central

    Gilaie-Dotan, Sharon; Kanai, Ryota; Bahrami, Bahador; Rees, Geraint; Saygin, Ayse P.

    2013-01-01

    Biological motion detection is both commonplace and important, but there is great inter-individual variability in this ability, the neural basis of which is currently unknown. Here we examined whether the behavioral variability in biological motion detection is reflected in brain anatomy. Perceptual thresholds for detection of biological motion and control conditions (non-biological object motion detection and motion coherence) were determined in a group of healthy human adults (n=31) together with structural magnetic resonance images of the brain. Voxel based morphometry analyzes revealed that gray matter volumes of left posterior superior temporal sulcus (pSTS) and left ventral premotor cortex (vPMC) significantly predicted individual differences in biological motion detection, but showed no significant relationship with performance on the control tasks. Our study reveals a neural basis associated with the inter-individual variability in biological motion detection, reliably linking the neuroanatomical structure of left pSTS and vPMC with biological motion detection performance. PMID:23211992

  16. Correlation fluorescence method of amine detection

    NASA Astrophysics Data System (ADS)

    Myslitsky, Valentin F.; Tkachuk, Svetlana S.; Rudeichuk, Volodimir M.; Strinadko, Miroslav T.; Slyotov, Mikhail M.; Strinadko, Marina M.

    1997-12-01

    The amines fluorescence spectra stimulated by UV laser radiation are investigated in this paper. The fluorescence is stimulated by the coherent laser beam with the wavelength 0.337 micrometers . At the sufficient energy of laser stimulation the narrow peaks of the fluorescence spectra are detected besides the wide maximum. The relationship between the fluorescence intensity and the concentration of amines solutions are investigated. The fluorescence intensity temporal dependence on wavelength 0.363 micrometers of the norepinephrine solution preliminarily radiated by UV laser with wavelength 0.337 micrometers was found. The computer stimulated and experimental investigations of adrenaline and norepinephrine mixtures fluorescence spectra were done. The correlation fluorescent method of amines detection is proposed.

  17. 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).

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

    SciTech Connect

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

    2016-07-15

    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{sup 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).

  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. Improving Broadband Displacement Detection with Quantum Correlations

    NASA Astrophysics Data System (ADS)

    Kampel, N. S.; Peterson, R. W.; Fischer, R.; Yu, P.-L.; Cicak, K.; Simmonds, R. W.; Lehnert, K. W.; Regal, C. A.

    2017-04-01

    Interferometers enable ultrasensitive measurement in a wide array of applications from gravitational wave searches to force microscopes. The role of quantum mechanics in the metrological limits of interferometers has a rich history, and a large number of techniques to surpass conventional limits have been proposed. In a typical measurement configuration, the trade-off between the probe's shot noise (imprecision) and its quantum backaction results in what is known as the standard quantum limit (SQL). In this work, we investigate how quantum correlations accessed by modifying the readout of the interferometer can access physics beyond the SQL and improve displacement sensitivity. Specifically, we use an optical cavity to probe the motion of a silicon nitride membrane off mechanical resonance, as one would do in a broadband displacement or force measurement, and observe sensitivity better than the SQL dictates for our quantum efficiency. Our measurement illustrates the core idea behind a technique known as variational readout, in which the optical readout quadrature is changed as a function of frequency to improve broadband displacement detection. And, more generally, our result is a salient example of how correlations can aid sensing in the presence of backaction.

  1. Papanicolaou test in the detection of high-grade cervical lesions: a re-evaluation based on cytohistologic non-correlation rates in 356 concurrently obtained samples.

    PubMed

    Carns, Bhavini; Fadare, Oluwole

    2008-01-01

    Studies evaluating the routine Papanicolaou (Pap) test have traditionally used as the reference gold standard, the diagnoses on the follow-up histologic samples. Since the latter are typically obtained days to weeks after the Pap test, the accuracy of the resultant comparison may be affected by interim factors, such as regression of human papillomavirus, new lesion acquisitions or colposcopy-associated variability. A subset of our clinicians have routinely obtained cervical cytology samples immediately prior to their colposcopic procedures, which presented a unique opportunity to re-evaluate the test performance of liquid-based cervical cytology in detecting the most clinically significant lesions (i.e. cervical intraepithelial neoplasia 2 or worse: CIN2+), using as gold standard, diagnoses on cervical biopsies that were essentially obtained simultaneously. For each patient, cytohistologic non-correlation between the Pap test and biopsy was considered to be present when either modality displayed a high-grade squamous intraepithelial lesion (HGSIL)/CIN2+ while the other displayed a less severe lesion. Therefore, HGSIL/CIN2+ was present in both the Pap test and biopsy in true positives, and absent in both modalities in true negatives. In false positives, the Pap test showed HGSIL while the biopsy showed less than a CIN2+. In false negatives, Pap tests displaying less than a HGSIL were associated with biopsies displaying CIN2+. Combinations associated with "atypical" interpretations were excluded. A cytohistologic non-correlation was present in 17 (4.8%) of the 356 combinations reviewed. The non-correlation was attributed, by virtue of having the less severe interpretation, to the Pap test in all 17 cases. There were 17, 322, 0, and 17 true positives, true negatives, false positives and false negatives respectively. The sensitivity, specificity, positive predictive value and negative predictive value of the Pap test, at a diagnostic threshold of HGSIL, in identifying

  2. 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.

  3. 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.

  4. Joint Transform Correlation for face tracking: elderly fall detection application

    NASA Astrophysics Data System (ADS)

    Katz, Philippe; Aron, Michael; Alfalou, Ayman

    2013-03-01

    In this paper, an iterative tracking algorithm based on a non-linear JTC (Joint Transform Correlator) architecture and enhanced by a digital image processing method is proposed and validated. This algorithm is based on the computation of a correlation plane where the reference image is updated at each frame. For that purpose, we use the JTC technique in real time to track a patient (target image) in a room fitted with a video camera. The correlation plane is used to localize the target image in the current video frame (frame i). Then, the reference image to be exploited in the next frame (frame i+1) is updated according to the previous one (frame i). In an effort to validate our algorithm, our work is divided into two parts: (i) a large study based on different sequences with several situations and different JTC parameters is achieved in order to quantify their effects on the tracking performances (decimation, non-linearity coefficient, size of the correlation plane, size of the region of interest...). (ii) the tracking algorithm is integrated into an application of elderly fall detection. The first reference image is a face detected by means of Haar descriptors, and then localized into the new video image thanks to our tracking method. In order to avoid a bad update of the reference frame, a method based on a comparison of image intensity histograms is proposed and integrated in our algorithm. This step ensures a robust tracking of the reference frame. This article focuses on face tracking step optimisation and evalutation. A supplementary step of fall detection, based on vertical acceleration and position, will be added and studied in further work.

  5. 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

  6. More Voodoo correlations: when average-based measures inflate correlations.

    PubMed

    Brand, Andrew; Bradley, Michael T

    2012-01-01

    A Monte-Carlo simulation was conducted to assess the extent that a correlation estimate can be inflated when an average-based measure is used in a commonly employed correlational design. The results from the simulation reveal that the inflation of the correlation estimate can be substantial, up to 76%. Additionally, data was re-analyzed from two previously published studies to determine the extent that the correlation estimate was inflated due to the use of an averaged based measure. The re-analyses reveal that correlation estimates had been inflated by just over 50% in both studies. Although these findings are disconcerting, we are somewhat comforted by the fact that there is a simple and easy analysis that can be employed to prevent the inflation of the correlation estimate that we have simulated and observed.

  7. Detection Performance of the Circular Correlation Coefficient Receiver,

    DTIC Science & Technology

    of the squared modulus of the circular serial correlation coefficient is found when no signal is present, allowing computation of the detection...threshold. For small data records, as is typical in radar applications, the performance of the correlation coefficient detector is compared to a standard... Correlation Coefficient , Autoregressive, CFAR, Autocorrelation Estimation, Radar Receiver, and Digital Signal Processing.

  8. 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.

  9. Cross-correlation-based detection and characterisation of microseismicity adjacent to the locked, late-interseismic Alpine Fault, South Westland, New Zealand

    NASA Astrophysics Data System (ADS)

    Chamberlain, Calum J.; Boese, Carolin M.; Townend, John

    2017-01-01

    The Alpine Fault is inferred on paleoseismological grounds to produce magnitude 8 earthquakes approximately every 330 yrs and to have last ruptured almost 300 yrs ago in 1717 AD. Despite approximately 90% of its typical interseismic period having elapsed since the last major earthquake, the Alpine Fault exhibits little present-day microseismicity and no geodetic evidence for shallow creep. Determining the mechanical state of the fault ahead of a future earthquake is a key objective of several studies, including the Deep Fault Drilling Project (DFDP). Here we use a network of borehole seismometers installed in conjunction with DFDP to detect and characterise low-magnitude seismicity adjacent to the central section of the Alpine Fault. We employ matched-filter detection techniques, automated cross-correlation phase picking, and singular value decomposition-derived magnitude estimation to construct a high-precision catalogue of 283 earthquakes within 5 km of the fault trace in an otherwise seismically quiet zone. The newly recognised seismicity occurs in non-repeating, spatially and temporally limited sequences, similar to sequences previously documented using standard methods but at significantly lower magnitudes of ML < 1.8. These earthquakes are not clustered on a single distinctive structure, and we infer that they are distributed throughout a highly fractured zone surrounding the Alpine Fault. Focal mechanisms computed for 13 earthquakes using manual polarity picks exhibit predominantly strike-slip faulting, consistent with focal mechanisms observed further from the fault. We conclude that the Alpine Fault is locked and accumulating strain throughout the seismogenic zone at this location.

  10. 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

  11. Brain correlates of automatic visual change detection.

    PubMed

    Cléry, H; Andersson, F; Fonlupt, P; Gomot, M

    2013-07-15

    A number of studies support the presence of visual automatic detection of change, but little is known about the brain generators involved in such processing and about the modulation of brain activity according to the salience of the stimulus. The study presented here was designed to locate the brain activity elicited by unattended visual deviant and novel stimuli using fMRI. Seventeen adult participants were presented with a passive visual oddball sequence while performing a concurrent visual task. Variations in BOLD signal were observed in the modality-specific sensory cortex, but also in non-specific areas involved in preattentional processing of changing events. A degree-of-deviance effect was observed, since novel stimuli elicited more activity in the sensory occipital regions and at the medial frontal site than small changes. These findings could be compared to those obtained in the auditory modality and might suggest a "general" change detection process operating in several sensory modalities. Copyright © 2013 Elsevier Inc. All rights reserved.

  12. 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.

  13. Detection and location of small aftershocks using waveform cross correlation

    NASA Astrophysics Data System (ADS)

    Kitov, Ivan; Sanina, Irina; Sergeev, Sergey

    2017-04-01

    Aftershock sequences of earthquakes with magnitudes 5.0 and lower are difficult to detect and locate by sparse regional networks. Signals from aftershocks with magnitudes 2 to 3 are usually below detection thresholds of standard 3-C seismic stations at near regional distances. For seismic events close in space, the method waveform cross correlation (WCC) allows to reduce detection threshold by at least a unit of magnitude and to improve location precision to a few kilometers. Therefore, the WCC method is directly applicable to weak aftershock sequences. Here, we recover seismic activity after the earthquake near the town of Mariupol (Ukraine) occurred on August 7, 2016. The main shock was detected by many stations of the International monitoring system (IMS), including the closest primary IMS array stations AKASG (6.62 deg.) and BRTR (7.81), as well as 3-C station KBZ (5.00). The International data centre located this event (47.0013N, 37.5427E), estimated its origin time (08:15:4.1 UTC), magnitude (mb=4.5), and depth (6.8 km). This event was also detected by two array stations of the Institute for Dynamics of Geospheres (IDG) of the Russian Academy of Sciences: portable 3-C array RDON (3.28), which is the closest station, and MHVAR (7.96). Using signals from the main shock at five stations as waveform templates, we calculated continuous traces of cross correlation coefficient (CC) from the 7th to the 11th of August. We found that the best templates should include all regional phases, and thus, have the length from 80 s to 180 s. For detection, we used standard STA/LTA method with threshold depending on station. The accuracy of onset time estimation by the STA/LTA detector based on CC-traces is close to one sample, which varies from 0.05 s at BRTR to 0.005 s for RDON and MHVAR. Arrival times of all detected signals were reduced to origin times using the observed travel times from the main shock. Clusters of origin times are considered as event hypotheses in the

  14. 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

    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

    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. 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 > = 7 mmol/L). 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. 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.

  15. 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

  16. Correlation studies on surface particle detection methods

    NASA Technical Reports Server (NTRS)

    Peterson, Ronald V.; White, James C.

    1988-01-01

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

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

    SciTech Connect

    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 correlation 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.

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

    DOE PAGES

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

    2016-03-15

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

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

    PubMed

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

    2014-01-01

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

  20. 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

  1. Canonical Correlation Analysis for Feature-Based Fusion of Biomedical Imaging Modalities and Its Application to Detection of Associative Networks in Schizophrenia.

    PubMed

    Correa, Nicolle M; Li, Yi-Ou; Adalı, Tülay; Calhoun, Vince D

    2008-12-01

    Typically data acquired through imaging techniques such as functional magnetic resonance imaging (fMRI), structural MRI (sMRI), and electroencephalography (EEG) are analyzed separately. However, fusing information from such complementary modalities promises to provide additional insight into connectivity across brain networks and changes due to disease. We propose a data fusion scheme at the feature level using canonical correlation analysis (CCA) to determine inter-subject covariations across modalities. As we show both with simulation results and application to real data, multimodal CCA (mCCA) proves to be a flexible and powerful method for discovering associations among various data types. We demonstrate the versatility of the method with application to two datasets, an fMRI and EEG, and an fMRI and sMRI dataset, both collected from patients diagnosed with schizophrenia and healthy controls. CCA results for fMRI and EEG data collected for an auditory oddball task reveal associations of the temporal and motor areas with the N2 and P3 peaks. For the application to fMRI and sMRI data collected for an auditory sensorimotor task, CCA results show an interesting joint relationship between fMRI and gray matter, with patients with schizophrenia showing more functional activity in motor areas and less activity in temporal areas associated with less gray matter as compared to healthy controls. Additionally, we compare our scheme with an independent component analysis based fusion method, joint-ICA that has proven useful for such a study and note that the two methods provide complementary perspectives on data fusion.

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

    PubMed

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

    2016-06-02

    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.

  3. 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.

  4. EMCCD-based spectrally resolved fluorescence correlation spectroscopy.

    PubMed

    Bestvater, Felix; Seghiri, Zahir; Kang, Moon Sik; Gröner, Nadine; Lee, Ji Young; Im, Kang-Bin; Wachsmuth, Malte

    2010-11-08

    We present an implementation of fluorescence correlation spectroscopy with spectrally resolved detection based on a combined commercial confocal laser scanning/fluorescence correlation spectroscopy microscope. We have replaced the conventional detection scheme by a prism-based spectrometer and an electron-multiplying charge-coupled device camera used to record the photons. This allows us to read out more than 80,000 full spectra per second with a signal-to-noise ratio and a quantum efficiency high enough to allow single photon counting. We can identify up to four spectrally different quantum dots in vitro and demonstrate that spectrally resolved detection can be used to characterize photophysical properties of fluorophores by measuring the spectral dependence of quantum dot fluorescence emission intermittence. Moreover, we can confirm intracellular cross-correlation results as acquired with a conventional setup and show that spectral flexibility can help to optimize the choice of the detection windows.

  5. A method for detecting complex correlation in time series

    NASA Astrophysics Data System (ADS)

    Alfi, V.; Petri, A.; Pietronero, L.

    2007-06-01

    We propose a new method for detecting complex correlations in time series of limited size. The method is derived by the Spitzer's identity and proves to work successfully on different model processes, including the ARCH process, in which pairs of variables are uncorrelated, but the three point correlation function is non zero. The application to financial data allows to discriminate among dependent and independent stock price returns where standard statistical analysis fails.

  6. 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.

  7. 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

  8. Correlation filter fusion for detection: morphological, wavelet, and Gabor methods

    NASA Astrophysics Data System (ADS)

    Casasent, David P.; Smokelin, John S.; Ye, Anqi; Schaefer, Roland H.

    1993-11-01

    We consider the detection of candidate objects (regions of interest) in a scene containing high clutter, multiple objects in different classes, independent of aspect view, with hot/cold/bimodal/partial object variations, and with low contrast targets. We use three different filters with each designed to produce high probability of detection (PD). We fuse the results from different outputs to reduce false alarms (PFA). All filters are realizable on a correlator.

  9. Interevent Correlations from Avalanches Hiding Below the Detection Threshold.

    PubMed

    Janićević, Sanja; Laurson, Lasse; Måløy, Knut Jørgen; Santucci, Stéphane; Alava, Mikko J

    2016-12-02

    Numerous systems ranging from deformation of materials to earthquakes exhibit bursty dynamics, which consist of a sequence of events with a broad event size distribution. Very often these events are observed to be temporally correlated or clustered, evidenced by power-law-distributed waiting times separating two consecutive activity bursts. We show how such interevent correlations arise simply because of a finite detection threshold, created by the limited sensitivity of the measurement apparatus, or used to subtract background activity or noise from the activity signal. Data from crack-propagation experiments and numerical simulations of a nonequilibrium crack-line model demonstrate how thresholding leads to correlated bursts of activity by separating the avalanche events into subavalanches. The resulting temporal subavalanche correlations are well described by our general scaling description of thresholding-induced correlations in crackling noise.

  10. Interevent Correlations from Avalanches Hiding Below the Detection Threshold

    NASA Astrophysics Data System (ADS)

    Janićević, Sanja; Laurson, Lasse; Mâløy, Knut Jørgen; Santucci, Stéphane; Alava, Mikko J.

    2016-12-01

    Numerous systems ranging from deformation of materials to earthquakes exhibit bursty dynamics, which consist of a sequence of events with a broad event size distribution. Very often these events are observed to be temporally correlated or clustered, evidenced by power-law-distributed waiting times separating two consecutive activity bursts. We show how such interevent correlations arise simply because of a finite detection threshold, created by the limited sensitivity of the measurement apparatus, or used to subtract background activity or noise from the activity signal. Data from crack-propagation experiments and numerical simulations of a nonequilibrium crack-line model demonstrate how thresholding leads to correlated bursts of activity by separating the avalanche events into subavalanches. The resulting temporal subavalanche correlations are well described by our general scaling description of thresholding-induced correlations in crackling noise.

  11. Nonlinear spectral correlation for fatigue crack detection under noisy environments

    NASA Astrophysics Data System (ADS)

    Liu, Peipei; Sohn, Hoon; Jeon, Ikgeun

    2017-07-01

    When ultrasonic waves at two distinct frequencies are applied to a structure with a fatigue crack, crack-induced nonlinearity creates nonlinear ultrasonic modulations at the sum and difference of the two input frequencies. The amplitude of the nonlinear modulation components is typically one or two orders of magnitude smaller than that of the primary linear components. Therefore, the modulation components can be easily buried under noise levels and it becomes difficult to extract the nonlinear modulation components under noisy environments using a conventional spectral density function. In this study, nonlinear spectral correlation, which calculates the spectral correlation between nonlinear modulation components, is proposed to isolate the nonlinear modulation components from noisy environments and used for fatigue crack detection. The proposed nonlinear spectral correlation offers the following benefits: (1) Stationary noises have little effect on nonlinear spectral correlation; (2) By using a wideband high-frequency input and a single low-frequency input, the contrast of nonlinear spectral correlation between damage and intact conditions can be enhanced; and (3) The test efficiency can be also improved via reducing the data collection time. Validation tests are performed on aluminum plates and scaled steel shafts with real fatigue cracks. The experimental results demonstrate that the proposed nonlinear spectral correlation owns a higher sensitivity to fatigue crack than the classical nonlinear coefficient estimated from the spectral density function, and the usage of nonlinear spectral correlation allows the detection of fatigue crack even using noncontact air-coupled transducers with a low signal-to-noise ratio.

  12. 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.

  13. Unzipping of DNA with correlated base sequence.

    PubMed

    Allahverdyan, A E; Gevorkian, Zh S; Hu, Chin-Kun; Wu, Ming-Chya

    2004-06-01

    We consider force-induced unzipping transition for a heterogeneous DNA model with a correlated base sequence. Both finite-range and long-range correlated situations are considered. It is shown that finite-range correlations increase stability of DNA with respect to the external unzipping force. Due to long-range correlations the number of unzipped base pairs displays two widely different scenarios depending on the details of the base sequence: either there is no unzipping phase transition at all, or the transition is realized via a sequence of jumps with magnitude comparable to the size of the system. Both scenarios are different from the behavior of the average number of unzipped base pairs (non-self-averaging). The results can be relevant for explaining the biological purpose of correlated structures in DNA.

  14. Intrinsic Correlations for Flaring Blazars Detected by Fermi

    NASA Astrophysics Data System (ADS)

    Fan, J. H.; Yang, J. H.; Xiao, H. B.; Lin, C.; Constantin, D.; Luo, G. Y.; Pei, Z. Y.; Hao, J. M.; Mao, Y. W.

    2017-02-01

    Blazars are an extreme subclass of active galactic nuclei. Their rapid variability, luminous brightness, superluminal motion, and high and variable polarization are probably due to a beaming effect. However, this beaming factor (or Doppler factor) is very difficult to measure. Currently, a good way to estimate it is to use the timescale of their radio flares. In this Letter, we use multiwavelength data and Doppler factors reported in the literature for a sample of 86 flaring blazars detected by Fermi to compute their intrinsic multiwavelength data and intrinsic spectral energy distributions and investigate the correlations among observed and intrinsic data. Quite interestingly, intrinsic data show a positive correlation between luminosity and peak frequency, in contrast with the behavior of observed data, and a tighter correlation between γ-ray luminosity and the lower-energy ones. For flaring blazars detected by Fermi, we conclude that (1) observed emissions are strongly beamed; (2) the anti-correlation between luminosity and peak frequency from the observed data is an apparent result, the correlation between intrinsic data being positive; and (3) intrinsic γ-ray luminosity is strongly correlated with other intrinsic luminosities.

  15. Facial landmark detection in real-time with correlation filtering

    NASA Astrophysics Data System (ADS)

    Contreras, Viridiana; Díaz-Ramírez, Víctor H.

    2016-09-01

    An algorithm for facial landmark detection based on template matched filtering is presented. The algorithm is able to detect and estimate the position of a set of prespecified landmarks by employing a bank of linear filters. Each filter in the bank is trained to detect a single landmark that is located in a small region of the input face image. The filter bank is implemented in parallel on a graphics processing unit to perform facial landmark detection in real-time. Computer simulation results obtained with the proposed algorithm are presented and discussed in terms of detection rate, accuracy of landmark location estimation, and real-time efficiency.

  16. Speckle correlation method used to detect an object's surface slope

    SciTech Connect

    Smid, Petr; Horvath, Pavel; Hrabovsky, Miroslav

    2006-09-20

    We present a technique employing a speckle pattern correlation method for detection of the slope of an object's surface. Controlled translation of an object under investigation and numerical correlation of speckle patterns recorded during its motion give information used to evaluate the tilt of the object. The proposed optical setup uses a symmetrical arrangement of detection planes in the image field and enables one to detect the tilt of an object's surface within the interval(10 deg. -30 deg. ). Simulation analysis shows how to control the measuring range. The presented theory, simulation analysis, and setup are verified through an experiment by measurement of the slope of a surface of a cube made out of steel.

  17. Speckle correlation method used to detect an object's surface slope.

    PubMed

    Smíd, Petr; Horváth, Pavel; Hrabovský, Miroslav

    2006-09-20

    We present a technique employing a speckle pattern correlation method for detection of the slope of an object's surface. Controlled translation of an object under investigation and numerical correlation of speckle patterns recorded during its motion give information used to evaluate the tilt of the object. The proposed optical setup uses a symmetrical arrangement of detection planes in the image field and enables one to detect the tilt of an object's surface within the interval (10 degrees-30 degrees). Simulation analysis shows how to control the measuring range. The presented theory, simulation analysis, and setup are verified through an experiment by measurement of the slope of a surface of a cube made out of steel.

  18. 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.

  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.

  20. 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

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

    DTIC Science & Technology

    2010-09-01

    Boulder Abstract Object correlation and maneuver detection are persistent problems in space surveillance and space object catalog maintenance. This paper ...Documentation Page Form ApprovedOMB No. 0704-0188 Public reporting burden for the collection of information is estimated to average 1 hour per response...reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including

  2. 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.

  3. Detection of fluctuating targets in correlated K-distributed clutter

    NASA Astrophysics Data System (ADS)

    Conte, E.; Longo, M.; Lops, M.; Ricci, G.

    This paper deals with the detection of coherent pulse trains, with scan-to-scan amplitude and phase fluctuation, in correlated K-distributed clutter. A coherent adaptive structure, designed according to a generalized Neyman-Pearson strategy, is considered. A relevant feature of the proposed approach is that the detector is canonical, namely its structure does not depend on the fluctuation laws of the target amplitude and phase. In addition, the receiver in the presence of correlated clutter is the same as for uncorrelated observations, but for the presence of a whitening filter. The performance assessment shows that the proposed scheme outperforms the conventional detector under the most common models of scan-to-scan fluctuation. Moreover, the performance in correlated observations can be read off the curves corresponding to white noise, provided that the abscissas are interpreted as the signal-to-noise ratio at the output of the whitening filter.

  4. Analog Correlator Based on One Bit Digital Correlator

    NASA Technical Reports Server (NTRS)

    Prokop, Norman (Inventor); Krasowski, Michael (Inventor)

    2017-01-01

    A two input time domain correlator may perform analog correlation. In order to achieve high throughput rates with reduced or minimal computational overhead, the input data streams may be hard limited through adaptive thresholding to yield two binary bit streams. Correlation may be achieved through the use of a Hamming distance calculation, where the distance between the two bit streams approximates the time delay that separates them. The resulting Hamming distance approximates the correlation time delay with high accuracy.

  5. Low-cost gas correlation detection of methane

    NASA Astrophysics Data System (ADS)

    Chapman, O. M.; Hilton, M.

    2006-04-01

    Two instruments have been designed for airborne remote sensing of landfill methane emissions using the infrared absorption of reflected sunlight. A gas correlation filter wheel and a length modulated cell have been produced to discriminate between methane and other interfering species and the performance of the two systems discussed. The two systems have been interfaced with an Indium Gallium Arsenide (InGaAs) 2D detector array and an Indium Antimonide (InSb) point detector. The InGaAs array detector response rate was found to be too slow so experiments were done using the InSb detector. The gas correlation filter wheel has been shown to detect levels of methane equivalent to 200ppmv with a 30m pathlength at the 3.3μm methane band with the InSb point detector. It has been predicted that it should be possible to detect levels equivalent to 20ppmv over a 30m pathlength at the 1.65μm band with the gas correlation filter wheel and a fast response InGaAs detector. The length modulated device was found to have far less sensitivity in comparison to the filter wheel system, but could have enhanced performance with improved design.

  6. 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.

  7. Exploiting large-scale correlations to detect continuous gravitational waves.

    PubMed

    Pletsch, Holger J; Allen, Bruce

    2009-10-30

    Fully coherent searches (over realistic ranges of parameter space and year-long observation times) for unknown sources of continuous gravitational waves are computationally prohibitive. Less expensive hierarchical searches divide the data into shorter segments which are analyzed coherently, then detection statistics from different segments are combined incoherently. The novel method presented here solves the long-standing problem of how best to do the incoherent combination. The optimal solution exploits large-scale parameter-space correlations in the coherent detection statistic. Application to simulated data shows dramatic sensitivity improvements compared with previously available (ad hoc) methods, increasing the spatial volume probed by more than 2 orders of magnitude at lower computational cost.

  8. 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.

  9. 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.

  10. Detecting correlation functions of ultracold atoms through fourier sampling of time-of-flight images.

    PubMed

    Duan, L-M

    2006-03-17

    We propose a detection method for ultracold atoms which allows reconstruction of the full one-particle and two-particle correlation functions from the measurements. The method is based on Fourier sampling of the time-of-flight images through two consecutive impulsive Raman pulses. For applications of this method, we discuss a few examples, including detection of phase separation between superfluid and Mott insulators, various types of spin or superfluid orders, entanglement, exotic or fluctuating orders.

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

    SciTech Connect

    Oberer, Richard B.

    2002-10-01

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

  12. A local correlation based visual saliency model

    NASA Astrophysics Data System (ADS)

    Li, Yang; Mou, Xuanqin

    2016-09-01

    We propose a novel local correlation based saliency model that is friendly to application of video coding. The proposed model is developed in YCbCr color space. We extract feature maps with local mean and local contrast of each channel image and its Gaussian blurred image, and produce rarity maps by calculating the correlation between the feature maps of the original and blurred channels. The proposed saliency map is produced by a combination of the local mean rarity maps and the local contrast rarity maps across all the channels. Experiments validate that the proposed model works with excellent performance.

  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. 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

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

    PubMed

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

    2014-04-29

    Behavioral studies have shown that emotional facial expressions are detected more rapidly and accurately than are neutral expressions. However, the neural mechanism underlying this efficient detection has remained unclear. To investigate this mechanism, we measured event-related potentials (ERPs) during a visual search task in which participants detected the normal emotional facial expressions of anger and happiness or their control stimuli, termed "anti-expressions," within crowds of neutral expressions. The anti-expressions, which were created using a morphing technique that produced changes equivalent to those in the normal emotional facial expressions compared with the neutral facial expressions, were most frequently recognized as emotionally neutral. Behaviorally, normal expressions were detected faster and more accurately and were rated as more emotionally arousing than were the anti-expressions. Regarding ERPs, the normal expressions elicited larger early posterior negativity (EPN) at 200-400ms compared with anti-expressions. Furthermore, larger EPN was related to faster and more accurate detection and higher emotional arousal. These data suggest that the efficient detection of emotional facial expressions is implemented via enhanced activation of the posterior visual cortices at 200-400ms based on their emotional significance. Copyright © 2014 Elsevier B.V. All rights reserved.

  16. A new approach for SSVEP detection using PARAFAC and canonical correlation analysis.

    PubMed

    Tello, Richard; Pouryazdian, Saeed; Ferreira, Andre; Beheshti, Soosan; Krishnan, Sridhar; Bastos, Teodiano

    2015-01-01

    This paper presents a new way for automatic detection of SSVEPs through correlation analysis between tensor models. 3-way EEG tensor of channel × frequency × time is decomposed into constituting factor matrices using PARAFAC model. PARAFAC analysis of EEG tensor enables us to decompose multichannel EEG into constituting temporal, spectral and spatial signatures. SSVEPs characterized with localized spectral and spatial signatures are then detected exploiting a correlation analysis between extracted signatures of the EEG tensor and the corresponding simulated signatures of all target SSVEP signals. The SSVEP that has the highest correlation is selected as the intended target. Two flickers blinking at 8 and 13 Hz were used as visual stimuli and the detection was performed based on data packets of 1 second without overlapping. Five subjects participated in the experiments and the highest classification rate of 83.34% was achieved, leading to the Information Transfer Rate (ITR) of 21.01 bits/min.

  17. 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.

  18. FPGA design of correlation-based pattern recognition

    NASA Astrophysics Data System (ADS)

    Jridi, Maher; Alfalou, Ayman

    2017-05-01

    Optical/Digital pattern recognition and tracking based on optical/digital correlation are a well-known techniques to detect, identify and localize a target object in a scene. Despite the limited number of treatments required by the correlation scheme, computational time and resources are relatively high. The most computational intensive treatment required by the correlation is the transformation from spatial to spectral domain and then from spectral to spatial domain. Furthermore, these transformations are used on optical/digital encryption schemes like the double random phase encryption (DRPE). In this paper, we present a VLSI architecture for the correlation scheme based on the fast Fourier transform (FFT). One interesting feature of the proposed scheme is its ability to stream image processing in order to perform correlation for video sequences. A trade-off between the hardware consumption and the robustness of the correlation can be made in order to understand the limitations of the correlation implementation in reconfigurable and portable platforms. Experimental results obtained from HDL simulations and FPGA prototype have demonstrated the advantages of the proposed scheme.

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

    NASA Astrophysics Data System (ADS)

    Miśkiewicz, Janusz; Ausloos, Marcel

    2008-11-01

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

  20. Prospects of Frequency-Time Correlation Analysis for Detecting Pipeline Leaks by Acoustic Emission Method

    NASA Astrophysics Data System (ADS)

    Faerman, V. A.; Cheremnov, A. G.; Avramchuk, V. V.; Luneva, E. E.

    2014-08-01

    In the current work the relevance of nondestructive test method development applied for pipeline leak detection is considered. It was shown that acoustic emission testing is currently one of the most widely spread leak detection methods. The main disadvantage of this method is that it cannot be applied in monitoring long pipeline sections, which in its turn complicates and slows down the inspection of the line pipe sections of main pipelines. The prospects of developing alternative techniques and methods based on the use of the spectral analysis of signals were considered and their possible application in leak detection on the basis of the correlation method was outlined. As an alternative, the time-frequency correlation function calculation is proposed. This function represents the correlation between the spectral components of the analyzed signals. In this work, the technique of time-frequency correlation function calculation is described. The experimental data that demonstrate obvious advantage of the time-frequency correlation function compared to the simple correlation function are presented. The application of the time-frequency correlation function is more effective in suppressing the noise components in the frequency range of the useful signal, which makes maximum of the function more pronounced. The main drawback of application of the time- frequency correlation function analysis in solving leak detection problems is a great number of calculations that may result in a further increase in pipeline time inspection. However, this drawback can be partially reduced by the development and implementation of efficient algorithms (including parallel) of computing the fast Fourier transform using computer central processing unit and graphic processing unit.

  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. Long-term visual tracking based on correlation filters

    NASA Astrophysics Data System (ADS)

    Wei, Quanlu; Lao, Songyang; Bai, Liang

    2017-03-01

    In order to accomplish the long term visual tracking task in complex scenes, solve problems of scale variation, appearance variation and tracking failure, a long term tracking algorithm is given based on the framework of collaborative correlation tracking. Firstly, we integrate several powerful features to boost the represent ability based on the kernel correlation filter, and extend the filter by embedding a scale factor into the kernelized matrix to handle the scale variation. Then, we use the Peak-Sidelobe Ratio to decide whether the object is tracked successfully, and a CUR filter for re-detection the object in case of tracking failure is learnt with random sampling. Corresponding experiment is performed on 17 challenging benchmark video sequences. Compared with the 8 existing state-of-the-art algorithms based on discriminative learning method, the results show that the proposed algorithm improves the tracking performance on several indexes, and is robust to complex scenes for long term visual tracking.

  3. Automatic seizure detection using correlation integral with nonlinear adaptive denoising and Kalman filter.

    PubMed

    Hongda Wang; Chiu-Sing Choy

    2016-08-01

    The ability of correlation integral for automatic seizure detection using scalp EEG data has been re-examined in this paper. To facilitate the detection performance and overcome the shortcoming of correlation integral, nonlinear adaptive denoising and Kalman filter have been adopted for pre-processing and post-processing. The three-stage algorithm has achieved 84.6% sensitivity and 0.087/h false detection rate, which are comparable to many machine learning based methods, but at much lower computational cost. Since this algorithm is tested with long-term scalp EEG, it has the potential to achieve higher performance with intracranial EEG. The clinical value of this algorithm includes providing a pre-judgement to assist the doctor's diagnosis procedure and acting as a reliable warning system in a wearable device for epilepsy patients.

  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. 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.

  6. Detection of Impaired Cerebral Autoregulation Using Selected Correlation Analysis: A Validation Study

    PubMed Central

    Brawanski, Alexander

    2017-01-01

    Multimodal brain monitoring has been utilized to optimize treatment of patients with critical neurological diseases. However, the amount of data requires an integrative tool set to unmask pathological events in a timely fashion. Recently we have introduced a mathematical model allowing the simulation of pathophysiological conditions such as reduced intracranial compliance and impaired autoregulation. Utilizing a mathematical tool set called selected correlation analysis (sca), correlation patterns, which indicate impaired autoregulation, can be detected in patient data sets (scp). In this study we compared the results of the sca with the pressure reactivity index (PRx), an established marker for impaired autoregulation. Mean PRx values were significantly higher in time segments identified as scp compared to segments showing no selected correlations (nsc). The sca based approach predicted cerebral autoregulation failure with a sensitivity of 78.8% and a specificity of 62.6%. Autoregulation failure, as detected by the results of both analysis methods, was significantly correlated with poor outcome. Sca of brain monitoring data detects impaired autoregulation with high sensitivity and sufficient specificity. Since the sca approach allows the simultaneous detection of both major pathological conditions, disturbed autoregulation and reduced compliance, it may become a useful analysis tool for brain multimodal monitoring data. PMID:28255331

  7. Bacteriophage-Based Pathogen Detection

    NASA Astrophysics Data System (ADS)

    Ripp, Steven

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

  8. Spectral Correlation of Multicarrier Modulated Signals and Its Application for Signal Detection

    NASA Astrophysics Data System (ADS)

    Zhang, Haijian; Le Ruyet (Eurasipmember), Didier; Terré, Michel

    2009-12-01

    Spectral correlation theory for cyclostationary time-series signals has been studied for decades. Explicit formulas of spectral correlation function for various types of analog-modulated and digital-modulated signals are already derived. In this paper, we investigate and exploit the cyclostationarity characteristics for two kinds of multicarrier modulated (MCM) signals: conventional OFDM and filter bank based multicarrier (FBMC) signals. The spectral correlation characterization of MCM signal can be described by a special linear periodic time-variant (LPTV) system. Using this LPTV description, we have derived the explicit theoretical formulas of nonconjugate and conjugate cyclic autocorrelation function (CAF) and spectral correlation function (SCF) for OFDM and FBMC signals. According to theoretical spectral analysis, Cyclostationary Signatures (CS) are artificially embedded into MCM signal and a low-complexity signature detector is, therefore, presented for detecting MCM signal. Theoretical analysis and simulation results demonstrate the efficiency and robustness of this CS detector compared to traditionary energy detector.

  9. Correlation Between Ceres' Water Vapor Detections and Energetic Solar Proton Events

    NASA Astrophysics Data System (ADS)

    Villarreal, Michaela N.; Russell, Christopher T.; Luhmann, Janet G.; Thompson, William T.; Prettyman, Thomas H.; A'Hearn, Michael; Kueppers, Michael; O'Rourke, Laurence

    2017-04-01

    Ceres was expected to be, and Dawn has confirmed, an ice-rich body. Prior to the Dawn mission, several attempts were made to detect exospheric water using terrestrial spacecraft around closest approach of Earth and Ceres. These attempts show the exosphere to be time varying. While it has been proposed that sublimation controls the presence of the exosphere, there is not a correlation between Ceres' heliocentric distance and the positive detections or the magnitude of the signal. Recently, Dawn indirectly twice sensed the presence of an exosphere through the presence of energetic electrons reflected at Ceres' bow shock surface; a shock which is created through the exosphere's interaction with the solar wind. Both these events were preceded by large solar proton events. This is important because water ice can be sputtered by these very energetic protons, the flux of which are highly variable. A solar proton event could produce a transient atmosphere that would last on the order of a week before it disappeared. We analyze the correlation between the observed production rates and the energetic proton flux preceding each observation using space-based measurements near 1 AU. We conclude that solar proton events occurred in conjunction with positive detections, and were absent during negative detections. Since Dawn has seen the same correlation and has not detected evidence for active plumes, optically or thermally, we conclude that the variability of solar energetic protons explains the transient behavior of the Ceres water exosphere.

  10. Using Amino Acid Correlation and Community Detection Algorithms to Identify Functional Determinants in Protein Families

    PubMed Central

    Bleicher, Lucas; Lemke, Ney; Garratt, Richard Charles

    2011-01-01

    Correlated mutation analysis has a long history of interesting applications, mostly in the detection of contact pairs in protein structures. Based on previous observations that, if properly assessed, amino acid correlation data can also provide insights about functional sub-classes in a protein family, we provide a complete framework devoted to this purpose. An amino acid specific correlation measure is proposed, which can be used to build networks summarizing all correlation and anti-correlation patterns in a protein family. These networks can be submitted to community structure detection algorithms, resulting in subsets of correlated amino acids which can be further assessed by specific parameters and procedures that provide insight into the relationship between different communities, the individual importance of community members and the adherence of a given amino acid sequence to a given community. By applying this framework to three protein families with contrasting characteristics (the Fe/Mn-superoxide dismutases, the peroxidase-catalase family and the C-type lysozyme/α-lactalbumin family), we show how our method and the proposed parameters and procedures are related to biological characteristics observed in these protein families, highlighting their potential use in protein characterization and gene annotation. PMID:22205928

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

    NASA Astrophysics Data System (ADS)

    He, Hai-Tao; Marguet, Didier

    2011-05-01

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

  12. 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.

  13. Detection system for neutron β decay correlations in the UCNB and Nab experiments

    NASA Astrophysics Data System (ADS)

    Broussard, L. J.; Zeck, B. A.; Adamek, E. R.; Baeßler, S.; Birge, N.; Blatnik, M.; Bowman, J. D.; Brandt, A. E.; Brown, M.; Burkhart, J.; Callahan, N. B.; Clayton, S. M.; Crawford, C.; Cude-Woods, C.; Currie, S.; Dees, E. B.; Ding, X.; Fomin, N.; Frlez, E.; Fry, J.; Gray, F. E.; Hasan, S.; Hickerson, K. P.; Hoagland, J.; Holley, A. T.; Ito, T. M.; Klein, A.; Li, H.; Liu, C.-Y.; Makela, M. F.; McGaughey, P. L.; Mirabal-Martinez, J.; Morris, C. L.; Ortiz, J. D.; Pattie, R. W.; Penttilä, S. I.; Plaster, B.; Počanić, D.; Ramsey, J. C.; Salas-Bacci, A.; Salvat, D. J.; Saunders, A.; Seestrom, S. J.; Sjue, S. K. L.; Sprow, A. P.; Tang, Z.; Vogelaar, R. B.; Vorndick, B.; Wang, Z.; Wei, W.; Wexler, J.; Wilburn, W. S.; Womack, T. L.; Young, A. R.

    2017-03-01

    We describe a detection system designed for precise measurements of angular correlations in neutron β decay. The system is based on thick, large area, highly segmented silicon detectors developed in collaboration with Micron Semiconductor, Ltd. The prototype system meets specifications for β electron detection with energy thresholds below 10 keV, energy resolution of ∼3 keV FWHM, and rise time of ∼50 ns with 19 of the 127 detector pixels instrumented. Using ultracold neutrons at the Los Alamos Neutron Science Center, we have demonstrated the coincident detection of β particles and recoil protons from neutron β decay. The fully instrumented detection system will be implemented in the UCNB and Nab experiments to determine the neutron β decay parameters B, a, and b.

  14. Domain similarity based orthology detection.

    PubMed

    Bitard-Feildel, Tristan; Kemena, Carsten; Greenwood, Jenny M; Bornberg-Bauer, Erich

    2015-05-13

    Orthologous protein detection software mostly uses pairwise comparisons of amino-acid sequences to assert whether two proteins are orthologous or not. Accordingly, when the number of sequences for comparison increases, the number of comparisons to compute grows in a quadratic order. A current challenge of bioinformatic research, especially when taking into account the increasing number of sequenced organisms available, is to make this ever-growing number of comparisons computationally feasible in a reasonable amount of time. We propose to speed up the detection of orthologous proteins by using strings of domains to characterize the proteins. We present two new protein similarity measures, a cosine and a maximal weight matching score based on domain content similarity, and new software, named porthoDom. The qualities of the cosine and the maximal weight matching similarity measures are compared against curated datasets. The measures show that domain content similarities are able to correctly group proteins into their families. Accordingly, the cosine similarity measure is used inside porthoDom, the wrapper developed for proteinortho. porthoDom makes use of domain content similarity measures to group proteins together before searching for orthologs. By using domains instead of amino acid sequences, the reduction of the search space decreases the computational complexity of an all-against-all sequence comparison. We demonstrate that representing and comparing proteins as strings of discrete domains, i.e. as a concatenation of their unique identifiers, allows a drastic simplification of search space. porthoDom has the advantage of speeding up orthology detection while maintaining a degree of accuracy similar to proteinortho. The implementation of porthoDom is released using python and C++ languages and is available under the GNU GPL licence 3 at http://www.bornberglab.org/pages/porthoda .

  15. 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.

  16. Correlation between quantitative traits and correlation between corresponding LOD scores: detection of pleiotropic effects.

    PubMed

    Ulgen, Ayse; Han, Zhihua; Li, Wentian

    2003-12-31

    We address the question of whether statistical correlations among quantitative traits lead to correlation of linkage results of these traits. Five measured quantitative traits (total cholesterol, fasting glucose, HDL cholesterol, blood pressure, and triglycerides), and one derived quantitative trait (total cholesterol divided by the HDL cholesterol) are used for phenotype correlation studies. Four of them are used for linkage analysis. We show that although correlation among phenotypes partially reflects the correlation among linkage analysis results, the LOD-score correlations are on average low. The most significant peaks found by using different traits do not often overlap. Studying covariances at specific locations in LOD scores may provide clues for further bivariate linkage analyses.

  17. Coincidence detection of spatially correlated photon pairs with a monolithic time-resolving detector array.

    PubMed

    Unternährer, Manuel; Bessire, Bänz; Gasparini, Leonardo; Stoppa, David; Stefanov, André

    2016-12-12

    We demonstrate coincidence measurements of spatially entangled photons by means of a multi-pixel based detection array. The sensor, originally developed for positron emission tomography applications, is a fully digital 8×16 silicon photomultiplier array allowing not only photon counting but also per-pixel time stamping of the arrived photons with an effective resolution of 265 ps. Together with a frame rate of 500 kfps, this property exceeds the capabilities of conventional charge-coupled device cameras which have become of growing interest for the detection of transversely correlated photon pairs. The sensor is used to measure a second-order correlation function for various non-collinear configurations of entangled photons generated by spontaneous parametric down-conversion. The experimental results are compared to theory.

  18. Trace gas detection and monitoring with the Digital Array Gas-correlation Radiometer (DAGR)

    NASA Astrophysics Data System (ADS)

    Gordley, Larry L.; Hervig, Mark E.; Fish, Chad; McHugh, Martin J.

    2011-05-01

    We present the first results from a Digital Array Gas-correlation Radiometer (DAGR) prototype sensor, and discuss applications in remote sensing of trace gases. The sensor concept is based on traditional and reliable Gas Filter Correlation Radiometry (GFCR), but overcomes the limitations in solar backscatter applications. The DAGR sensor design can be scaled to the size of a digital camera and is ideal for downlooking detection of gases in the boundary layer, where solar backscatter measurements are needed to overcome the lack of thermal contrast in the IR. Ground-based portable DAGR sensors can monitor carbon sequestration sites or industrial facilities. Aircraft or UAV deployment can quickly survey large areas and are particularly well suited for gas leak detection or carbon monitoring. From space-based platforms, Doppler modulation can be exploited to produce an extremely fine spectral resolution with effective resolving power exceeding 100,000. Such space-based DAGR observations could provide near-global sensing of climatically important species such as such as CO2, CO, CH4, O3 and N2O. Planetary science applications include detection and mapping of biomarkers in the Martian atmosphere.

  19. A Random Motility Assay Based on Image Correlation Spectroscopy

    PubMed Central

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

    2013-01-01

    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

  20. 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

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

    NASA Astrophysics Data System (ADS)

    Ikuta, Akira; Orimoto, Hisako; Ogawa, Hitoshi

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

  2. 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.

  3. Early Detection of Breast Cancer via Multiplane Correlation Breast Imaging

    DTIC Science & Technology

    2007-04-01

    superior diagnostic information. Towards this end, a LG CHO mathematical observer model was constructed to assess the detectability of a simulated mass...on mathematical observer model was developed to assess the detectability of the mass. Detectability was measured in terms of Receiver Operating...This task has been accomplished. The goal of this task was to develop an observer model which could be used to quantify the performance of MCI in

  4. 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.

  5. 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.

  6. An autonomous surface discontinuity detection and quantification method by digital image correlation and phase congruency

    NASA Astrophysics Data System (ADS)

    Cinar, A. F.; Barhli, S. M.; Hollis, D.; Flansbjer, M.; Tomlinson, R. A.; Marrow, T. J.; Mostafavi, M.

    2017-09-01

    Digital image correlation has been routinely used to measure full-field displacements in many areas of solid mechanics, including fracture mechanics. Accurate segmentation of the crack path is needed to study its interaction with the microstructure and stress fields, and studies of crack behaviour, such as the effect of closure or residual stress in fatigue, require data on its opening displacement. Such information can be obtained from any digital image correlation analysis of cracked components, but it collection by manual methods is quite onerous, particularly for massive amounts of data. We introduce the novel application of Phase Congruency to detect and quantify cracks and their opening. Unlike other crack detection techniques, Phase Congruency does not rely on adjustable threshold values that require user interaction, and so allows large datasets to be treated autonomously. The accuracy of the Phase Congruency based algorithm in detecting cracks is evaluated and compared with conventional methods such as Heaviside function fitting. As Phase Congruency is a displacement-based method, it does not suffer from the noise intensification to which gradient-based methods (e.g. strain thresholding) are susceptible. Its application is demonstrated to experimental data for cracks in quasi-brittle (Granitic rock) and ductile (Aluminium alloy) materials.

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

    NASA Astrophysics Data System (ADS)

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

    2009-02-01

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

  8. Detection system for neutron β decay correlations in the UCNB and Nab experiments

    SciTech Connect

    Broussard, L. J.; Zeck, B. A.; Adamek, E. R.; Baeßler, S.; Birge, N.; Blatnik, M.; Bowman, J. D.; Brandt, A. E.; Brown, M.; Burkhart, J.; Callahan, N. B.; Clayton, S. M.; Crawford, C.; Cude-Woods, C.; Currie, S.; Dees, E. B.; Ding, X.; Fomin, N.; Frlez, E.; Fry, J.; Gray, F. E.; Hasan, S.; Hickerson, K. P.; Hoagland, J.; Holley, A. T.; Ito, T. M.; Klein, A.; Li, H.; Liu, C. -Y.; Makela, M. F.; McGaughey, P. L.; Mirabal-Martinez, J.; Morris, C. L.; Ortiz, J. D.; Pattie, R. W.; Penttilä, S. I.; Plaster, B.; Počanić, D.; Ramsey, J. C.; Salas-Bacci, A.; Salvat, D. J.; Saunders, A.; Seestrom, S. J.; Sjue, S. K. L.; Sprow, A. P.; Tang, Z.; Vogelaar, R. B.; Vorndick, B.; Wang, Z.; Wei, W.; Wexler, J.; Wilburn, W. S.; Womack, T. L.; Young, A. R.

    2016-12-19

    Here, we describe a detection system designed to precisely measure multiple correlations in neutron β decay. Furthermore, the system is based on thick, large area, highly segmented silicon detectors developed in collaboration with Micron Semiconductor, Ltd. The prototype system meets specifications of energy thresholds below 10 keV, energy resolution of ~3 keV FWHM, and rise time of ~50 ns with 19 of the 127 detector pixels instrumented. We have demonstrated the coincident detection of β particles and recoil protons from neutron β decay, using ultracold neutrons at the Los Alamos Neutron Science Center, . The fully instrumented detection system will be implemented in the UCNB and Nab experiments, to determine the neutron β decay parameters B, a, and b.

  9. Detection system for neutron β decay correlations in the UCNB and Nab experiments

    DOE PAGES

    Broussard, L. J.; Oak Ridge National Lab.; Zeck, B. A.; ...

    2016-12-19

    Here, we describe a detection system designed to precisely measure multiple correlations in neutron β decay. Furthermore, the system is based on thick, large area, highly segmented silicon detectors developed in collaboration with Micron Semiconductor, Ltd. The prototype system meets specifications of energy thresholds below 10 keV, energy resolution of ~3 keV FWHM, and rise time of ~50 ns with 19 of the 127 detector pixels instrumented. We have demonstrated the coincident detection of β particles and recoil protons from neutron β decay, using ultracold neutrons at the Los Alamos Neutron Science Center, . The fully instrumented detection system willmore » be implemented in the UCNB and Nab experiments, to determine the neutron β decay parameters B, a, and b.« less

  10. Correlation between quantitative traits and correlation between corresponding LOD scores: detection of pleiotropic effects

    PubMed Central

    Ulgen, Ayse; Han, Zhihua; Li, Wentian

    2003-01-01

    Background We address the question of whether statistical correlations among quantitative traits lead to correlation of linkage results of these traits. Five measured quantitative traits (total cholesterol, fasting glucose, HDL cholesterol, blood pressure, and triglycerides), and one derived quantitative trait (total cholesterol divided by the HDL cholesterol) are used for phenotype correlation studies. Four of them are used for linkage analysis. Results We show that although correlation among phenotypes partially reflects the correlation among linkage analysis results, the LOD-score correlations are on average low. The most significant peaks found by using different traits do not often overlap. Conclusion Studying covariances at specific locations in LOD scores may provide clues for further bivariate linkage analyses. PMID:14975128

  11. 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.

  12. A Correlated Microwave-Acoustic Imaging method for early-stage cancer detection.

    PubMed

    Gao, Fei; Zheng, Yuanjin

    2012-01-01

    Microwave-based imaging technique shows large potential in detecting early-stage cancer due to significant dielectric contrast between tumor and surrounding healthy tissue. In this paper, we present a new way named Correlated Microwave-Acoustic Imaging (CMAI) of combining two microwave-based imaging modalities: confocal microwave imaging(CMI) by detecting scattered microwave signal, and microwave-induced thermo-acoustic imaging (TAI) by detecting induced acoustic signal arising from microwave energy absorption and thermal expansion. Necessity of combining CMI and TAI is analyzed theoretically, and by applying simple algorithm to CMI and TAI separately, we propose an image correlation approach merging CMI and TAI together to achieve better performance in terms of resolution and contrast. Preliminary numerical simulation shows promising results in case of low contrast and large variation scenarios. A UWB transmitter is designed and tested for future complete system implementation. This preliminary study inspires us to develop a new medical imaging modality CMAI to achieve real-time, high resolution and high contrast simultaneously.

  13. Damage detection of structures with detrended fluctuation and detrended cross-correlation analyses

    NASA Astrophysics Data System (ADS)

    Lin, Tzu-Kang; Fajri, Haikal

    2017-03-01

    Recently, fractal analysis has shown its potential for damage detection and assessment in fields such as biomedical and mechanical engineering. For its practicability in interpreting irregular, complex, and disordered phenomena, a structural health monitoring (SHM) system based on detrended fluctuation analysis (DFA) and detrended cross-correlation analysis (DCCA) is proposed. First, damage conditions can be swiftly detected by evaluating ambient vibration signals measured from a structure through DFA. Damage locations can then be determined by analyzing the cross correlation of signals of different floors by applying DCCA. A damage index is also proposed based on multi-scale DCCA curves to improve the damage location accuracy. To verify the performance of the proposed SHM system, a four-story numerical model was used to simulate various damage conditions with different noise levels. Furthermore, an experimental verification was conducted on a seven-story benchmark structure to assess the potential damage. The results revealed that the DFA method could detect the damage conditions satisfactorily, and damage locations can be identified through the DCCA method with an accuracy of 75%. Moreover, damage locations can be correctly assessed by the damage index method with an improved accuracy of 87.5%. The proposed SHM system has promising application in practical implementations.

  14. 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

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

    DOE PAGES

    Arrowsmith, Stephen John; Young, Christopher J.; Ballard, Sanford; ...

    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

  16. 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.

  17. 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.

  18. Correlating video meteors with GRAVES radio detections from the UK

    NASA Astrophysics Data System (ADS)

    Fleet, R.

    2015-01-01

    The area of meteor ablation layer illuminated by the GRAVES radar is low on the horizon from southern UK. A number of simultaneous video meteor and radio detections suggested that it was possible to record common events despite the unfavorable relative positions. This was investigated further to see what the constraints are and whether there is any prospect of obtaining useful data.

  19. How reliable is routine lumbar spine MRI for detection of renal cysts? Correlation with abdominal CT.

    PubMed

    Cho, Hee Woo; Lee, Young Han; Chung, Soo Yoon; Park, Jin-Oh; Suh, Jin-Suck

    2016-04-01

    Incidental renal cysts are a very common finding in routine lumbar spine magnetic resonance imaging (MRI). However, there is no report of the renal cyst detection rate on routine lumbar spine MRI. To determine the renal cyst detection rate in routine lumbar spine MRI based on findings of abdominal computed tomography (CT), and to investigate if the largest renal cyst seen by abdominal CT could be also detected by routine lumbar spine MRI. A retrospective study was conducted of 70 patients who underwent both routine lumbar spine MRI and abdominal CT between December 2011 and January 2014. The detection rate of all renal cysts>5 mm as well as the largest renal cyst seen by abdominal CT were assessed in routine lumbar spine MRI. On routine lumbar spine MRI, the detection rate of renal cysts was 46.5% (73/157) for>5-mm renal cysts and 68.0% (34/50) for>10-mm renal cysts, correlating with abdominal CT. The detection rate of the largest renal cyst seen by abdominal CT was 60.0% (27/45). Non-detection of the largest renal cyst could be caused by upper positioning (n = 7), lateral positioning (n = 6), or relatively small cyst size (n = 5). Approximately half of renal cysts>5 mm and two-thirds of renal cysts>10 mm were detected on routine lumbar spine MRI. However, radiologists should be aware that kidney lesions may not be included in the scan coverage of routine lumbar spine MRI. © The Foundation Acta Radiologica 2015.

  20. 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.

  1. Detection of correlated sources in EEG using combination of beamforming and surface Laplacian methods.

    PubMed

    Murzin, Vyacheslav; Fuchs, Armin; Scott Kelso, J A

    2013-08-15

    Beamforming offers a way to estimate the solution to the inverse problem in EEG and MEG but is also known to perform poorly in the presence of highly correlated sources, e.g. during binaural auditory stimulation, when both left and right primary auditory cortices are activated simultaneously. Surface Laplacian, or the second spatial derivative calculated from the electric potential, allows for deblurring of EEG potential recordings reducing the effects of low skull conductivity and is independent of the reference electrode location. We show that anatomically constrained beamforming in conjunction with the surface Laplacian allows for detection of both locations and dynamics of temporally correlated sources in EEG. Whole-head 122 channel binaural stimulus EEG data were simulated using a boundary element method (BEM) and realistic geometry forward model. We demonstrate that in contrast to conventional potential-based EEG beamforming, Laplacian beamforming allows to determine locations of correlated source dipoles without any a priori assumption about the number of sources. We also show (by providing simulations of auditory evoked potentials) that the dynamics at the detected source locations can be derived from subsets of electrodes. Deblurring auditory evoked potential maps subdivides EEG signals from each hemisphere and allows for the beamformer to be applied separately for left and right hemispheres.

  2. Correlates of rediscovery and the detectability of extinction in mammals

    PubMed Central

    Fisher, Diana O.; Blomberg, Simon P.

    2011-01-01

    Extinction is difficult to detect, even in well-known taxa such as mammals. Species with long gaps in their sighting records, which might be considered possibly extinct, are often rediscovered. We used data on rediscovery rates of missing mammals to test whether extinction from different causes is equally detectable and to find which traits affect the probability of rediscovery. We find that species affected by habitat loss were much more likely to be misclassified as extinct or to remain missing than those affected by introduced predators and diseases, or overkill, unless they had very restricted distributions. We conclude that extinctions owing to habitat loss are most difficult to detect; hence, impacts of habitat loss on extinction have probably been overestimated, especially relative to introduced species. It is most likely that the highest rates of rediscovery will come from searching for species that have gone missing during the 20th century and have relatively large ranges threatened by habitat loss, rather than from additional effort focused on charismatic missing species. PMID:20880890

  3. Structural damage detection using auto correlation functions of vibration response under sinusoidal excitation

    NASA Astrophysics Data System (ADS)

    Zhang, Muyu; Schmidt, Rüdiger; Markert, Bernd

    2015-07-01

    Structural damage detection using time domain vibration responses has attracted more and more researchers in recent years because of its simplicity in calculation and no requirement of a finite element model. This paper proposes a new approach to locate the damage using the auto correlation function of vibration response signals under sinusoidal excitation from different measurement points of the structure, based on which a vector named Auto Correlation Function at Maximum Point Value Vector (AMV) is formulated. A sensitivity analysis of the normalized AMV with respect to the local stiffness shows that under several specific frequency excitations, the normalized AMV has a sharp change around the local stiffness change location, which means that even when the damage is very small, the normalized AMV is a good indicator for the damage. In order to locate the damage, a damage index is defined as the relative change of the normalized AMV before and after damage. Several example cases in stiffness reduction detection of a frame structure valid the results of the sensitivity analysis, demonstrate the efficiency of the normalized AMV in damage localization and the effect of the excitation frequency on its detectability.

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

    NASA Astrophysics Data System (ADS)

    alinne solano, ericka; Hjorleifsdottir, Vala

    2016-04-01

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

  5. Experimental Techniques for Detecting Correlated Motion of Brownian Particles

    NASA Astrophysics Data System (ADS)

    Franck, Carl; Durand, Richard V.

    1998-03-01

    We, as well as other workers, have noticed using light microscopy that particles undergoing Brownian motion can appear to linger around each other for long periods of time. The question arises as to whether this lingering is a product of interparticle interactions, or is an artifact due to random thermal motion. By way of answering this question, we developed techniques for dealing with the random nature of the particle motion. We present an algorithm to track individual Brownian particles which can handle the disappearance of a particle due to its temporary movement outside of the field of view. We used the tracking data to create randomized particle trajectories which were subsequently compared with the actual trajectories. This backgrounding technique allowed us to extract information about correlated motion in the midst of Brownian noise. We found(R.V. Durand and C. Franck, Phys. Rev. E 56), 1998 (1997). that the aforementioned apparent correlated motion could have been due to observer misperception. Financial support was provided by the National Science Foundation through grant DMR-9320910 and through MRL Central Facilities at the Materials Science Center at Cornell University (DMR-9121654).

  6. LOCI: Fast Outlier Detection Using the Local Correlation Integral

    DTIC Science & Technology

    2002-11-01

    Density-based approach. This was proposed by M. Breunig , et al. [BKNS00]. It relies on the local outlier factor (LOF) of each object, which depends...VLDB, pages 299–310, 1995. [BKNS00] M.M. Breunig , H.P. Kriegel, R.T. Ng, and J. Sander. Lof: Identifying density-based local outliers. In Proc

  7. Knowledge-based pitch detection

    NASA Astrophysics Data System (ADS)

    Dove, W. P.

    1986-06-01

    Many problems in signal processing involve a mixture of numerical and symbolic knowledge. Examples of problems of this sort include the recognition of speech and the analysis of images. This thesis focuses on the problem of employing a mixture of symbolic and numerical knowledge within a single system, through the development of a system directed at a modified pitch detection problem. For this thesis, the conventional pitch detection problem was modified by providing a phonetic transcript and sex/age information as input to the system, in addition to the acoustic waveform. The Pitch Detector's Assistant (PDA) system that was developed is an interactive facility for evaluating ways of approaching this problem. The PDA system allows the user to interrupt processing at any point, change either input data, derived data, or problem knowledge and continue execution.

  8. Knuckle based hand correlation for user authentication

    NASA Astrophysics Data System (ADS)

    Sricharan, K. Kumar; Reddy, A. Aneesh; Ramakrishnan, A. G.

    2006-04-01

    Different hand-derived biometric traits have been used for user authentication in many commercial systems. In this paper we have investigated the possibility of using a new biometric trait, the knuckle, for user authentication. Knuckle regions are extracted from the hand images and correlation methods are used for the purpose of verification. Experimental results on a data set of 125 people show that the knuckle is a viable biometric trait, which can be used as an alternative to finger and palm prints or in conjunction with them.

  9. Correlation based rotation-invariant corner detector

    NASA Astrophysics Data System (ADS)

    Mazzaferri, Javier; Ledesma, Silvia

    2008-04-01

    In this work we introduce a new approach for corner extraction. The method that allows the corner extraction with rotation invariance is composed by a spiral phase function and a binary amplitude. The designed function can be easily implemented as a filter for a Vander Lugt-like optical correlator. A final image obtained with the detector presents intensity peaks in each corner location. Numerical simulation has been performed on a set of synthetic scenes, modulated either in amplitude or phase. Results that show the very good performance of the method are shown.

  10. Mapping frontal-limbic correlates of orienting to change detection.

    PubMed

    Williams, Leanne M; Felmingham, Kim; Kemp, Andrew H; Rennie, Chris; Brown, Kerri J; Bryant, Richard A; Gordon, Evian

    2007-02-12

    Orienting responses are elicited by salient stimuli, and may be indexed by skin conductance responses. Concurrent functional magnetic resonance imaging and skin conductance response recording was used to identify neural correlates of orienting to abrupt sensory change (infrequent high pitch oddball 'target' tones embedded in frequent lower pitch 'standard' tones) in 16 healthy participants. 'With skin conductance response' responses to targets were distinguished by preferentially greater activity in the amygdala and ventral medial and lateral frontal cortical regions. By contrast, 'without skin conductance response' responses elicited distinctive activity in the dorsal lateral frontal cortex and supramarginal gyrus. These findings suggest that orienting to unexpected sensory change elicits a network for appraising salience and novelty, whereas, in the absence of orienting, a parallel network for sensory and context evaluation is preferentially engaged.

  11. An attempt to determine the effect of increase of observation correlations on detectability and identifiability of a single gross error

    NASA Astrophysics Data System (ADS)

    Prószyński, Witold; Kwaśniak, Mieczysław

    2016-12-01

    The paper presents the results of investigating the effect of increase of observation correlations on detectability and identifiability of a single gross error, the outlier test sensitivity and also the response-based measures of internal reliability of networks. To reduce in a research a practically incomputable number of possible test options when considering all the non-diagonal elements of the correlation matrix as variables, its simplest representation was used being a matrix with all non-diagonal elements of equal values, termed uniform correlation. By raising the common correlation value incrementally, a sequence of matrix configurations could be obtained corresponding to the increasing level of observation correlations. For each of the measures characterizing the above mentioned features of network reliability the effect is presented in a diagram form as a function of the increasing level of observation correlations. The influence of observation correlations on sensitivity of the w-test for correlated observations (Förstner 1983, Teunissen 2006) is investigated in comparison with the original Baarda's w-test designated for uncorrelated observations, to determine the character of expected sensitivity degradation of the latter when used for correlated observations. The correlation effects obtained for different reliability measures exhibit mutual consistency in a satisfactory extent. As a by-product of the analyses, a simple formula valid for any arbitrary correlation matrix is proposed for transforming the Baarda's w-test statistics into the w-test statistics for correlated observations.

  12. Exploring the Limits of Waveform Correlation Event Detection as Applied to Three Earthquake Aftershock Sequences

    NASA Astrophysics Data System (ADS)

    Young, C. J.; Carr, D.; Resor, M.; Duffey, S.

    2009-12-01

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

  13. Nonlocality in many-body quantum systems detected with two-body correlators

    SciTech Connect

    Tura, J.; Augusiak, R.; Sainz, A.B.; Lücke, B.; Klempt, C.; Lewenstein, M.; Acín, A.

    2015-11-15

    Contemporary understanding of correlations in quantum many-body systems and in quantum phase transitions is based to a large extent on the recent intensive studies of entanglement in many-body systems. In contrast, much less is known about the role of quantum nonlocality in these systems, mostly because the available multipartite Bell inequalities involve high-order correlations among many particles, which are hard to access theoretically, and even harder experimentally. Standard, “theorist- and experimentalist-friendly” many-body observables involve correlations among only few (one, two, rarely three...) particles. Typically, there is no multipartite Bell inequality for this scenario based on such low-order correlations. Recently, however, we have succeeded in constructing multipartite Bell inequalities that involve two- and one-body correlations only, and showed how they revealed the nonlocality in many-body systems relevant for nuclear and atomic physics [Tura et al., Science 344 (2014) 1256]. With the present contribution we continue our work on this problem. On the one hand, we present a detailed derivation of the above Bell inequalities, pertaining to permutation symmetry among the involved parties. On the other hand, we present a couple of new results concerning such Bell inequalities. First, we characterize their tightness. We then discuss maximal quantum violations of these inequalities in the general case, and their scaling with the number of parties. Moreover, we provide new classes of two-body Bell inequalities which reveal nonlocality of the Dicke states—ground states of physically relevant and experimentally realizable Hamiltonians. Finally, we shortly discuss various scenarios for nonlocality detection in mesoscopic systems of trapped ions or atoms, and by atoms trapped in the vicinity of designed nanostructures.

  14. Detecting PM2.5's Correlations between Neighboring Cities Using a Time-Lagged Cross-Correlation Coefficient.

    PubMed

    Wang, Fang; Wang, Lin; Chen, Yuming

    2017-08-31

    In order to investigate the time-dependent cross-correlations of fine particulate (PM2.5) series among neighboring cities in Northern China, in this paper, we propose a new cross-correlation coefficient, the time-lagged q-L dependent height crosscorrelation coefficient (denoted by p q (τ, L)), which incorporates the time-lag factor and the fluctuation amplitude information into the analogous height cross-correlation analysis coefficient. Numerical tests are performed to illustrate that the newly proposed coefficient ρ q (τ, L) can be used to detect cross-correlations between two series with time lags and to identify different range of fluctuations at which two series possess cross-correlations. Applying the new coefficient to analyze the time-dependent cross-correlations of PM2.5 series between Beijing and the three neighboring cities of Tianjin, Zhangjiakou, and Baoding, we find that time lags between the PM2.5 series with larger fluctuations are longer than those between PM2.5 series withsmaller fluctuations. Our analysis also shows that cross-correlations between the PM2.5 series of two neighboring cities are significant and the time lags between two PM2.5 series of neighboring cities are significantly non-zero. These findings providenew scientific support on the view that air pollution in neighboring cities can affect one another not simultaneously but with a time lag.

  15. Clusters of suicides and suicide attempts: detection, proximity and correlates.

    PubMed

    Too, L S; Pirkis, J; Milner, A; Spittal, M J

    2017-10-01

    A suicide cluster is defined as a higher number of observed cases occurring in space and/or time than would typically be expected. Previous research has largely focused on identifying clusters of suicides, while there has been comparatively limited research on clusters of suicide attempts. We sought to identify clusters of both types of behaviour, and having done that, identify the factors that distinguish suicide attempts inside a cluster from those that were outside a cluster. We used data from Western Australia from 2000 to 2011. We defined suicide attempts as admissions to hospital for deliberate self-harm and suicides as deaths due to deliberate self-harm. Using an analytic strategy that accounted for the repetition of attempted suicide within a cluster, we performed spatial-temporal analysis using Poisson discrete scan statistics to detect clusters of suicide attempts and clusters of suicides. Logistic regression was then used to compare clustered attempts with non-clustered attempts to identify risk factors for an attempt being in a cluster. We detected 350 (1%) suicide attempts occurring within seven spatial-temporal clusters and 12 (0.6%) suicides occurring within two spatial-temporal clusters. Both of the suicide clusters were located within a larger but later suicide attempt cluster. In multivariate analysis, suicide attempts by individuals who lived in areas of low socioeconomic status had higher odds of being in a cluster than those living in areas of high socioeconomic status [odds ratio (OR) = 29.1, 95% confidence interval (CI) = 6.3-135.5]. A one percentage-point increase in the proportion of people who had changed address in the last year was associated with a 60% increase in the odds of the attempt being within a cluster (OR = 1.60, 95% CI = 1.29-1.98) and a one percentage-point increase in the proportion of Indigenous people in the area was associated with a 7% increase in the suicide being within a cluster (OR = 1.07, 95% CI = 1.00-1.13). Age

  16. Optical flow based finger stroke detection

    NASA Astrophysics Data System (ADS)

    Zhu, Zhongdi; Li, Bin; Wang, Kongqiao

    2010-07-01

    Finger stroke detection is an important topic in hand based Human Computer Interaction (HCI) system. Few research studies have carried out effective solutions to this problem. In this paper, we present a novel approach for stroke detection based on mono vision. Via analyzing the optical flow field within the finger area, our method is able to detect finger stroke under various camera position and visual angles. We present a thorough evaluation for each component of the algorithm, and show its efficiency and effectiveness on solving difficult stroke detection problems.

  17. 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.

  18. Automatic microseismic event detection by band-limited phase-only correlation

    NASA Astrophysics Data System (ADS)

    Wu, Shaojiang; Wang, Yibo; Zhan, Yi; Chang, Xu

    2016-12-01

    Identification and detection of microseismic events is a significant issue in source locations and source mechanism analysis. The number of the records is notably large, especially in the case of some real-time monitoring, and while the majority of microseismic events are highly weak and sparse, automatic algorithms are indispensable. In this study, we introduce an effective method for the identification and detection of microseismic events by judging whether the P-wave phase exists in a local segment from a single three-component microseismic records. The new judging algorithm consists primarily of the following key steps: 1) transform the waveform time series into time-varying spectral representations using the S-transform; 2) calculate the similarity of the frequency content in the time-frequency domain using the phase-only correlation function; and 3) identify the P-phase by the combination analysis between any two components. The proposed algorithm is compared to a similar approach using the cross-correlation in the time domain between any two components and later tested with synthetic microseismic datasets and real field-recorded datasets. The results indicate that the proposed algorithm is able to distinguish similar and dissimilar waveforms, even for low signal noise ratio and emergent events, which is important for accurate and rapid selection of microseismic events from a large number of records. This method can be applied to other geophysical analyses based on the waveform data.

  19. 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.

  20. 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.

  1. 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.

  2. The application of the multifractal cross-correlation analysis methods in radar target detection within sea clutter

    NASA Astrophysics Data System (ADS)

    Xi, Caiping; Zhang, Shuning; Xiong, Gang; Zhao, Huichang; Yang, Yonghong

    2017-02-01

    Many complex systems generate multifractal time series which are long-range cross-correlated. This paper introduces three multifractal cross-correlation analysis methods, such as multifractal cross-correlation analysis based on the partition function approach (MFXPF), multifractal detrended cross-correlation analysis (MFDCCA) methods based on detrended fluctuation analysis (MFXDFA) and detrended moving average analysis (MFXDMA), which only consider one moment order. We do comparative analysis of the artificial time series (binomial multiplicative cascades and Cantor sets with different probabilities) by these methods. Then we do a feasibility test of the fixed threshold target detection within sea clutter by applying the multifractal cross-correlation analysis methods to the IPIX radar sea clutter data. The results show that it is feasible to use the method of the fixed threshold based on the multifractal feature parameter Δf(α) by the MFXPF and MFXDFA-1 methods. At last, we give the main conclusions and provide a valuable reference on how to choose the multifractal algorithms, the detection parameters and the target detection methods within sea clutter in practice.

  3. Contour detection based on wavelet differentiation

    NASA Astrophysics Data System (ADS)

    Bezuglov, D.; Kuzin, A.; Voronin, V.

    2016-05-01

    This work proposes a novel algorithm for contour detection based on high-performance algorithm of wavelet analysis for multimedia applications. To solve the noise effect on the result of peaking in this paper we consider the direct and inverse wavelet differentiation. Extensive experimental evaluation on noisy images demonstrates that our contour detection method significantly outperform competing algorithms. The proposed algorithm provides a means of coupling our system to recognition application such as detection and identification of vehicle number plate.

  4. Sociolect-Based Community Detection

    SciTech Connect

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

    2013-06-06

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

  5. 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.

  6. TENTATIVE DETECTION OF QUASAR FEEDBACK FROM WMAP AND SDSS CROSS-CORRELATION

    SciTech Connect

    Chatterjee, Suchetana; Newman, Jeffrey A.; Kosowsky, Arthur; Ho, Shirley

    2010-09-01

    We perform a cross-correlation analysis of microwave data from the Wilkinson Microwave Anisotropy Probe and photometric quasars from the Sloan Digital Sky Survey, testing for the Sunyaev-Zeldovich (SZ) effect from quasars. A statistically significant (2.5{sigma}) temperature decrement exists in the 41 GHz microwave band. A two-component fit to the cross-correlation spectrum incorporating both dust emission and SZ yields a best-fit y parameter of (7.0 {+-} 3.4) x 10{sup -7}. A similar cross-correlation analysis with the luminous red galaxy sample from Sloan gives a best-fit y parameter of (5.3 {+-} 2.5) x 10{sup -7}. We discuss the possible physical origin of these signals, which is likely a combination of SZ effects from quasars and galaxy clusters. Both the Planck Surveyor satellite and the current ground-based arcminute-resolution microwave experiments will detect this signal with a higher statistical significance.

  7. Smartphone-based colorimetric detection of glutathione.

    PubMed

    Vobornikova, Irena; Pohanka, Miroslav

    2016-12-18

    Glutathione belongs to the family of small-molecular weight antioxidants like ascorbic acid, cysteine, α-tocopherol, uric acid, etc. These molecules play important role in the neutralization of free radicals and reactive oxygen species (ROS). Oxidative stress may lead to ageing and the development of large scale of pathological states of organism. This low molecular weight antioxidant´s level can alter under pathological conditions from reduced (GSH, thiols) to oxidized (oxidized glutathione -GSSG, disulfides) form. A GSSG-to-GSH ratio is indicative marker of oxidative stress. There is a large scale of methods how to determine this biomarker. The trend of the analysis is to minimalize the instrument equipment, sample application volume and analysis cost. Reduced glutathione (GSH) solutions were prepared in water in the concentration 0-16 mmol/L. Other small-molecular weight antioxidants like 0.25 mmol/L ascorbic acid, 0.15 mmol/L TROLOX and 0.02 mmol/L N-acetyl-cysteine (NAcCys) were studied as possible interferents. The samples were mixed with 5,5´-dithiobis-(2-nitrobenzoic) acid (DTNB) resulting in yellow colored drops forming. Coloration was assayed using camera integrated in a smartphone and color channels analysis. The total volume of 10 µl of sample was applied for one analysis. The smartphone-based data were compared with the reference Ellman assay. The calibration of glutathione was evaluated. The blue channel intensity data were decreasing according to the increasing glutathione concentration. Red and green channel intensities were stagnating during the whole concentration scale of glutathione. Limits of detection were 0.4 mmol/l for glutathione. Addition of 0.25 mmol/L of ascorbic acid, 0.15 mmol/L of TROLOX and 0.02mmol/L of N-acetylcysteine to GSH in final concentration 0-16 mmol/L had minimal influence on the assay. The results from smartphone-based analysis correlate with the standard Ellman method. The detection limit for GSH was 0.03 mmol

  8. Time-correlated Raman and fluorescence spectroscopy based on a silicon photomultiplier and time-correlated single photon counting technique.

    PubMed

    Zhang, Chunling; Zhang, Liying; Yang, Ru; Liang, Kun; Han, Dejun

    2013-02-01

    We report a time-correlated Raman spectroscopy technique based on a silicon photomultiplier (SiPM) and a time-correlated single photon counting (TCSPC) technique to exploit the natural temporal separation between Raman and fluorescence phenomena to alleviate the high fluorescence background with conventional Raman detection. The TCSPC technique employed can greatly reduce the effect of high dark count rate (DCR) and crosstalk of SiPM that seriously hinder its application in low light level detection. The operating principle and performance of the 400 ps time resolution system are discussed along with the improvement of the peak-to-background ratio (PBR) for bulk trinitrotoluene (TNT) Raman spectrum relative to a commercial Raman spectrometer with charge coupled device (CCD). The fluorescence lifetime for solid TNT and Surface Enhanced Raman Scattering (SERS) spectrum for 10(-6) mol/L trace TNT have also been obtained by this system, showing excellent versatility and convenience in spectroscopy measurement.

  9. Noise Correlation Effect on Detection: Signals in Equicorrelated or Autoregressive(1) Gaussian.

    PubMed

    Kasasbeh, Hadi; Viswanathan, Ramanarayanan; Cao, Lei

    2017-07-01

    In this letter, we consider the effect of noise correlation on the error performance of binary hypothesis signal detection, when one of two deterministic signals is received in correlated Gaussian noise. For the likelihood ratio detection scheme, analytical performance results are derived for equicorrelated and autoregressive order one models. Although it is known previously that the best signal lies in the direction of eigenvector corresponding to the minimum eigenvalue of the noise covariance matrix, our investigation of the variation of mean signal-to-noise power ratio as a function of correlation parameter (i) shows how correlation leads to increased probability of error up to a point, beyond which monotonic decrease in error probability with increasing correlation is possible and (ii) provides a max-min signal design solution for the unknown correlation parameter case. Numerical results are also included for some specific signals.

  10. 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.

  11. Collaborative Regression-based Anatomical Landmark Detection

    PubMed Central

    Gao, Yaozong; Shen, Dinggang

    2015-01-01

    Anatomical landmark detection plays an important role in medical image analysis, e.g., for registration, segmentation and quantitative analysis. Among various existing methods for landmark detection, regression-based methods recently have drawn much attention due to robustness and efficiency. In such methods, landmarks are localized through voting from all image voxels, which is completely different from classification-based methods that use voxel-wise classification to detect landmarks. Despite robustness, the accuracy of regression-based landmark detection methods is often limited due to 1) inclusion of uninformative image voxels in the voting procedure, and 2) 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 localize landmarks by gradually excluding uninformative votes from faraway voxels. Moreover, for the informative voxels near the landmark, a spherical sampling strategy is also designed in 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 (CT) images, and also dental landmarks in cone beam computed tomography (CBCT) 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. PMID:26579736

  12. A correlation consistency based multivariate alarm thresholds optimization approach.

    PubMed

    Gao, Huihui; Liu, Feifei; Zhu, Qunxiong

    2016-11-01

    Different alarm thresholds could generate different alarm data, resulting in different correlations. A new multivariate alarm thresholds optimization methodology based on the correlation consistency between process data and alarm data is proposed in this paper. The interpretative structural modeling is adopted to select the key variables. For the key variables, the correlation coefficients of process data are calculated by the Pearson correlation analysis, while the correlation coefficients of alarm data are calculated by kernel density estimation. To ensure the correlation consistency, the objective function is established as the sum of the absolute differences between these two types of correlations. The optimal thresholds are obtained using particle swarm optimization algorithm. Case study of Tennessee Eastman process is given to demonstrate the effectiveness of proposed method.

  13. 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

  14. 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

  15. Experimental results for correlation-based wavefront sensing

    SciTech Connect

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

    2005-07-01

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

  16. Quantifying the momentum correlation between two light beams by detecting one

    NASA Astrophysics Data System (ADS)

    Hochrainer, Armin; Lahiri, Mayukh; Lapkiewicz, Radek; Barreto Lemos, Gabriela; Zeilinger, Anton

    2017-02-01

    We report a measurement of the transverse momentum correlation between two photons by detecting only one of them. Our method uses two identical sources in an arrangement in which the phenomenon of induced coherence without induced emission is observed. In this way, we produce an interference pattern in the superposition of one beam from each source. We quantify the transverse momentum correlation by analyzing the visibility of this pattern. Our approach might be useful for the characterization of correlated photon pair sources and may lead to an experimental measure of continuous variable entanglement, which relies on the detection of only one of two entangled particles.

  17. Quantifying the momentum correlation between two light beams by detecting one.

    PubMed

    Hochrainer, Armin; Lahiri, Mayukh; Lapkiewicz, Radek; Lemos, Gabriela Barreto; Zeilinger, Anton

    2017-02-14

    We report a measurement of the transverse momentum correlation between two photons by detecting only one of them. Our method uses two identical sources in an arrangement in which the phenomenon of induced coherence without induced emission is observed. In this way, we produce an interference pattern in the superposition of one beam from each source. We quantify the transverse momentum correlation by analyzing the visibility of this pattern. Our approach might be useful for the characterization of correlated photon pair sources and may lead to an experimental measure of continuous variable entanglement, which relies on the detection of only one of two entangled particles.

  18. Quantifying the momentum correlation between two light beams by detecting one

    PubMed Central

    Hochrainer, Armin; Lahiri, Mayukh; Lapkiewicz, Radek; Lemos, Gabriela Barreto; Zeilinger, Anton

    2017-01-01

    We report a measurement of the transverse momentum correlation between two photons by detecting only one of them. Our method uses two identical sources in an arrangement in which the phenomenon of induced coherence without induced emission is observed. In this way, we produce an interference pattern in the superposition of one beam from each source. We quantify the transverse momentum correlation by analyzing the visibility of this pattern. Our approach might be useful for the characterization of correlated photon pair sources and may lead to an experimental measure of continuous variable entanglement, which relies on the detection of only one of two entangled particles. PMID:28143940

  19. 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.

  20. Optical correlation based on the fractional Fourier transform.

    PubMed

    Granieri, S; Arizaga, R; Sicre, E E

    1997-09-10

    Some properties of optical correlation based on the fractional Fourier transform are analyzed. For a particular set of fractional orders, a filter is obtained that becomes insensitive to scale variations of the object. An optical configuration is also proposed to carry out the fractional correlation in a flexible way, and some experimental results are shown.

  1. Vision Based Obstacle Detection in Uav Imaging

    NASA Astrophysics Data System (ADS)

    Badrloo, S.; Varshosaz, M.

    2017-08-01

    Detecting and preventing incidence with obstacles is crucial in UAV navigation and control. Most of the common obstacle detection techniques are currently sensor-based. Small UAVs are not able to carry obstacle detection sensors such as radar; therefore, vision-based methods are considered, which can be divided into stereo-based and mono-based techniques. Mono-based methods are classified into two groups: Foreground-background separation, and brain-inspired methods. Brain-inspired methods are highly efficient in obstacle detection; hence, this research aims to detect obstacles using brain-inspired techniques, which try to enlarge the obstacle by approaching it. A recent research in this field, has concentrated on matching the SIFT points along with, SIFT size-ratio factor and area-ratio of convex hulls in two consecutive frames to detect obstacles. This method is not able to distinguish between near and far obstacles or the obstacles in complex environment, and is sensitive to wrong matched points. In order to solve the above mentioned problems, this research calculates the dist-ratio of matched points. Then, each and every point is investigated for Distinguishing between far and close obstacles. The results demonstrated the high efficiency of the proposed method in complex environments.

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

    NASA Astrophysics Data System (ADS)

    Carr, Richard; Whitney, James

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

  3. Detecting correlation changes in multivariate time series: A comparison of four non-parametric change point detection methods.

    PubMed

    Cabrieto, Jedelyn; Tuerlinckx, Francis; Kuppens, Peter; Grassmann, Mariel; Ceulemans, Eva

    2017-06-01

    Change point detection in multivariate time series is a complex task since next to the mean, the correlation structure of the monitored variables may also alter when change occurs. DeCon was recently developed to detect such changes in mean and\\or correlation by combining a moving windows approach and robust PCA. However, in the literature, several other methods have been proposed that employ other non-parametric tools: E-divisive, Multirank, and KCP. Since these methods use different statistical approaches, two issues need to be tackled. First, applied researchers may find it hard to appraise the differences between the methods. Second, a direct comparison of the relative performance of all these methods for capturing change points signaling correlation changes is still lacking. Therefore, we present the basic principles behind DeCon, E-divisive, Multirank, and KCP and the corresponding algorithms, to make them more accessible to readers. We further compared their performance through extensive simulations using the settings of Bulteel et al. (Biological Psychology, 98 (1), 29-42, 2014) implying changes in mean and in correlation structure and those of Matteson and James (Journal of the American Statistical Association, 109 (505), 334-345, 2014) implying different numbers of (noise) variables. KCP emerged as the best method in almost all settings. However, in case of more than two noise variables, only DeCon performed adequately in detecting correlation changes.

  4. Modeling Travel-Time Correlations Based on Sensitivity Kernels and Correlated Velocity Anomalies

    DTIC Science & Technology

    2008-09-01

    MODELING TRAVEL -TIME CORRELATIONS BASED ON SENSITIVITY KERNELS AND CORRELATED VELOCITY ANOMALIES William L. Rodi1 and Stephen C. Myers2 Massachusetts...05NA266031 and DE-AC52-07NA273442 Proposal No. BAA05-14 ABSTRACT This project concerns the errors in predicted regional and teleseismic travel times...resulting from velocity heterogeneity in the real Earth not represented in the reference Earth model used for travel -time calculation. We are developing

  5. 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

  6. 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.

  7. 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.

  8. Pedestrian detection based on redundant wavelet transform

    NASA Astrophysics Data System (ADS)

    Huang, Lin; Ji, Liping; Hu, Ping; Yang, Tiejun

    2016-10-01

    Intelligent video surveillance is to analysis video or image sequences captured by a fixed or mobile surveillance camera, including moving object detection, segmentation and recognition. By using it, we can be notified immediately in an abnormal situation. Pedestrian detection plays an important role in an intelligent video surveillance system, and it is also a key technology in the field of intelligent vehicle. So pedestrian detection has very vital significance in traffic management optimization, security early warn and abnormal behavior detection. Generally, pedestrian detection can be summarized as: first to estimate moving areas; then to extract features of region of interest; finally to classify using a classifier. Redundant wavelet transform (RWT) overcomes the deficiency of shift variant of discrete wavelet transform, and it has better performance in motion estimation when compared to discrete wavelet transform. Addressing the problem of the detection of multi-pedestrian with different speed, we present an algorithm of pedestrian detection based on motion estimation using RWT, combining histogram of oriented gradients (HOG) and support vector machine (SVM). Firstly, three intensities of movement (IoM) are estimated using RWT and the corresponding areas are segmented. According to the different IoM, a region proposal (RP) is generated. Then, the features of a RP is extracted using HOG. Finally, the features are fed into a SVM trained by pedestrian databases and the final detection results are gained. Experiments show that the proposed algorithm can detect pedestrians accurately and efficiently.

  9. Extracting Coherent Information from Noise Based Correlation Processing

    DTIC Science & Technology

    2015-09-30

    1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Extracting Coherent Information from Noise Based...LONG-TERM GOALS The goal of this research is to establish methodologies to utilize ambient noise in the ocean and to determine what scenarios...are best suited for applying these methods. OBJECTIVES Because noise -based correlation processing is based on equilibrium related stationary

  10. Relating quantum coherence and correlations with entropy-based measures.

    PubMed

    Wang, Xiao-Li; Yue, Qiu-Ling; Yu, Chao-Hua; Gao, Fei; Qin, Su-Juan

    2017-09-21

    Quantum coherence and quantum correlations are important quantum resources for quantum computation and quantum information. In this paper, using entropy-based measures, we investigate the relationships between quantum correlated coherence, which is the coherence between subsystems, and two main kinds of quantum correlations as defined by quantum discord as well as quantum entanglement. In particular, we show that quantum discord and quantum entanglement can be well characterized by quantum correlated coherence. Moreover, we prove that the entanglement measure formulated by quantum correlated coherence is lower and upper bounded by the relative entropy of entanglement and the entanglement of formation, respectively, and equal to the relative entropy of entanglement for all the maximally correlated states.

  11. 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

  12. 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

  13. 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

  14. 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.

  15. 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.

  16. Quantum Endpoint Detection Based on QRDA

    NASA Astrophysics Data System (ADS)

    Wang, Jian; Wang, Han; Song, Yan

    2017-10-01

    Speech recognition technology is widely used in many applications for man - machine interaction. To face more and more speech data, the computation of speech processing needs new approaches. The quantum computation is one of emerging computation technology and has been seen as useful computation model. So we focus on the basic operation of speech recognition processing, the voice activity detection, to present quantum endpoint detection algorithm. In order to achieve this algorithm, the n-bits quantum comparator circuit is given firstly. Then based on QRDA(Quantum Representation of Digital Audio), a quantum endpoint detection algorithm is presented. These quantum circuits could efficient process the audio data in quantum computer.

  17. Quantum Endpoint Detection Based on QRDA

    NASA Astrophysics Data System (ADS)

    Wang, Jian; Wang, Han; Song, Yan

    2017-08-01

    Speech recognition technology is widely used in many applications for man - machine interaction. To face more and more speech data, the computation of speech processing needs new approaches. The quantum computation is one of emerging computation technology and has been seen as useful computation model. So we focus on the basic operation of speech recognition processing, the voice activity detection, to present quantum endpoint detection algorithm. In order to achieve this algorithm, the n-bits quantum comparator circuit is given firstly. Then based on QRDA(Quantum Representation of Digital Audio), a quantum endpoint detection algorithm is presented. These quantum circuits could efficient process the audio data in quantum computer.

  18. 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.

  19. 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.

  20. Direct connections assist neurons to detect correlation in small amplitude noises

    PubMed Central

    Bolhasani, E.; Azizi, Y.; Valizadeh, A.

    2013-01-01

    We address a question on the effect of common stochastic inputs on the correlation of the spike trains of two neurons when they are coupled through direct connections. We show that the change in the correlation of small amplitude stochastic inputs can be better detected when the neurons are connected by direct excitatory couplings. Depending on whether intrinsic firing rate of the neurons is identical or slightly different, symmetric or asymmetric connections can increase the sensitivity of the system to the input correlation by changing the mean slope of the correlation transfer function over a given range of input correlation. In either case, there is also an optimum value for synaptic strength which maximizes the sensitivity of the system to the changes in input correlation. PMID:23966940

  1. 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

  2. A robust fringe-adjusted joint transform correlator for efficient object detection

    NASA Astrophysics Data System (ADS)

    Sidike, Paheding; Asari, Vijayan K.; Alam, Mohammad S.

    2015-03-01

    The fringe-adjusted joint transform correlation (FJTC) technique has been widely used for real-time optical pattern recognition applications. However, the classical FJTC technique suffers from target distortions due to noise, scale, rotation and illumination variations of the targets in input scenes. Several improvements of the FJTC have been proposed in the literature to accommodate these problems. Some popular techniques such as synthetic discriminant function (SDF) based FJTC was designed to alleviate the problems of scale and rotation variations of the target, whereas wavelet based FJTC has been found to yield better performance for noisy targets in the input scenes. While these techniques integrated with specific features to improve performance of the FJTC, a unified and synergistic approach to equip the FJTC with robust features is yet to be done. Thus, in this paper, a robust FJTC technique based on sequential filtering approach is proposed. The proposed method is developed in such a way that it is insensitive to rotation, scale, noise and illumination variations of the targets. Specifically, local phase (LP) features from monogenic signal is utilized to reduce the effect of background illumination thereby achieving illumination invariance. The SDF is implemented to achieve rotation and scale invariance, whereas the logarithmic fringe-adjusted filter (LFAF) is employed to reduce the noise effect. The proposed technique can be used as a real-time region-of-interest detector in wide-area surveillance for automatic object detection. The feasibility of the proposed technique has been tested on aerial imagery and has observed promising performance in detection accuracy.

  3. 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

  4. [Metagenomics-based detection of swine viruses].

    PubMed

    Han, Wen; Luo, Yuzi; Zhao, Bibo; Sun, Yuan; Li, Su; Qiu, Huaji

    2013-02-04

    Extreme varieties of viruses exist in the environment and animals, some of which are unknown. However, many unknown viruses are barely detected by means of conventional virus isolation and PCR assay. To develop a technology platform for detecting unknown viruses. We established the technology based on viral metagenomics in combination with novel molecular diagnostics. The technology is consisted of removal of host nucleic acid, random PCR amplification, large-scale sequencing, and bioinformatics. The technology was applied to detect classical swine fever virus (CSFV)-infected cells and a tissue sample of a pig infected with porcine circovirus type 2 (PCV2). We amplified 13.7% sequences of CSFV genome and 47.2% those of PCV2 genome, respectively. Moreover, we amplified 16.4% sequences of the simian parainfluenza virus type 5 genome from an unknown virus cell culture using the developed method. In addition, using the developed method combined with the high-throughput sequencing, we detected 1.1% virus sequences, including CSFV, PCV2, torque teno sus virus (TTSuV), porcine bocavirus (PBoV) and human adenovirus type 6 (Ad6) from 7 clinical swine samples of unknown causative agents. The developed metagenomics-based method showed good sensitivity for detection of both DNA and RNA viruses from diverse swine samples, and has potential for universal detection of known and unknown viruses. It might facilitate the diagnosis of emerging viral diseases.

  5. 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

  6. Energy detection based on undecimated discrete wavelet transform and its application in magnetic anomaly detection.

    PubMed

    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.

  7. Perseveration effects in detection tasks with correlated decision intervals. [applied to pilot collision avoidance

    NASA Technical Reports Server (NTRS)

    Gai, E. G.; Curry, R. E.

    1978-01-01

    An investigation of the behavior of the human decisionmaker is described for a task related to the problem of a pilot using a traffic situation display to avoid collisions. This sequential signal detection task is characterized by highly correlated signals with time varying strength. Experimental results are presented and the behavior of the observers is analyzed using the theory of Markov processes and classical signal detection theory. Mathematical models are developed which describe the main result of the experiment: that correlation in sequential signals induced perseveration in the observer response and a strong tendency to repeat their previous decision, even when they were wrong.

  8. Pipeline Processing with an Iterative, Context-Based Detection Model

    DTIC Science & Technology

    2016-01-22

    15. SUBJECT TERMS aftershock sequences, repeating explosions, detection framework, pattern detectors, correlation detectors, subspace detectors...49 Figure 23: The two cases where a signal failed to be detected by correlation detectors because of the presence of a strong...Cancellers assume that a separate recording of an interference source time history is available and that this time history is correlated with

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

    PubMed

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

    2015-01-01

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

  10. 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.

  11. 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.

  12. [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.

  13. 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.

  14. Mine detection training based on expert skill

    NASA Astrophysics Data System (ADS)

    Staszewski, James J.; Davison, Alan

    2000-08-01

    Studies show that soldiers' mine detection capabilities with the PSS-12 hand-held detector are substandard and that their probabilities of detecting (PD) low-metal mines are dangerously low. Highly experienced PSS-12 operators, however, achieve PDS over 0.90 on high- and low-metal anti- tank (AT) and anti-personnel (AP) mines. Significantly, experts' detection techniques differ from conventional military PSS-12 operating procedures. We report three studies investigating whether instruction based on expert skill could bridge the observed performance gap. Basic research on human expertise has shown that instruction based on detailed scientific analyses of experts' behaviors and thought processes boosts skill acquisition dramatically. These studies tested the effects of an experimental detection training program based on knowledge and techniques learned from analysis of PSS-12 expertise. In Study I soldiers who had completed standard mine detection training participated as operators/trainees. This experiment used a pretest-posttest design. Mine simulants served as targets in testing gand training. Targets simulate d5 different mines and represented high- and low-metal AT and AP mine types. Pretest performance failed to distinguish the treatment and control groups. Both achieved very low PDs on low metal mines. Treatment-group soldiers then received approximately 15 hours of experimental, hands-on training. Posttest results showed that the treatment groups PD on minimal metal targets was more than 6 times that of the control group. Study 2 tested a subset of the treated soldiers in the same setting, now wearing body armor. Results replicated those of Study 1. Study 3 tested treatment group soldiers on real mine targets. Several mines from each mine type were used. The surface of the test lanes was expected to increase detection difficulty. Soldiers nonetheless achieved an aggregate PD of 0.97 and showed significant improvement in detecting low-metal mines.

  15. 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.

  16. 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.

  17. GaAs-based photorefractive time-integrating correlator

    NASA Technical Reports Server (NTRS)

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

    1992-01-01

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

  18. 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.

  19. Light Scattering based detection of food pathogens

    USDA-ARS?s Scientific Manuscript database

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

  20. Combined zero-quantum and spin-diffusion mixing for efficient homonuclear correlation spectroscopy under fast MAS: broadband recoupling and detection of long-range correlations.

    PubMed

    Lu, Xingyu; Guo, Changmiao; Hou, Guangjin; Polenova, Tatyana

    2015-01-01

    Fast magic angle spinning (MAS) NMR spectroscopy is emerging as an essential analytical and structural biology technique. Large resolution and sensitivity enhancements observed under fast MAS conditions enable structural and dynamics analysis of challenging systems, such as large macromolecular assemblies and isotopically dilute samples, using only a fraction of material required for conventional experiments. Homonuclear dipolar-based correlation spectroscopy constitutes a centerpiece in the MAS NMR methodological toolbox, and is used essentially in every biological and organic system for deriving resonance assignments and distance restraints information necessary for structural analysis. Under fast MAS conditions (rotation frequencies above 35-40 kHz), dipolar-based techniques that yield multi-bond correlations and non-trivial distance information are ineffective and suffer from low polarization transfer efficiency. To overcome this limitation, we have developed a family of experiments, CORD-RFDR. These experiments exploit the advantages of both zero-quantum RFDR and spin-diffusion based CORD methods, and exhibit highly efficient and broadband dipolar recoupling across the entire spectrum, for both short-range and long-range correlations. We have verified the performance of the CORD-RFDR sequences experimentally on a U-(13)C,(15)N-MLF tripeptide and by numerical simulations. We demonstrate applications of 2D CORD-RFDR correlation spectroscopy in dynein light chain LC8 and HIV-1 CA tubular assemblies. In the CORD-RFDR spectra of LC8 acquired at the MAS frequency of 40 kHz, many new intra- and inter-residue correlations are detected, which were not observed with conventional dipolar recoupling sequences. At a moderate MAS frequency of 14 kHz, the CORD-RFDR experiment exhibits excellent performance as well, as demonstrated in the HIV-1 CA tubular assemblies. Taken together, the results indicate that CORD-RFDR experiment is beneficial in a broad range of conditions

  1. Effective information spreading based on local information in correlated networks

    NASA Astrophysics Data System (ADS)

    Gao, Lei; Wang, Wei; Pan, Liming; Tang, Ming; Zhang, Hai-Feng

    2016-12-01

    Using network-based information to facilitate information spreading is an essential task for spreading dynamics in complex networks. Focusing on degree correlated networks, we propose a preferential contact strategy based on the local network structure and local informed density to promote the information spreading. During the spreading process, an informed node will preferentially select a contact target among its neighbors, basing on their degrees or local informed densities. By extensively implementing numerical simulations in synthetic and empirical networks, we find that when only consider the local structure information, the convergence time of information spreading will be remarkably reduced if low-degree neighbors are favored as contact targets. Meanwhile, the minimum convergence time depends non-monotonically on degree-degree correlation, and a moderate correlation coefficient results in the most efficient information spreading. Incorporating the local informed density information into contact strategy, the convergence time of information spreading can be further reduced, and be minimized by an moderately preferential selection.

  2. 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.

  3. 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.

  4. Correlation-based tracking using tunable training and Kalman prediction

    NASA Astrophysics Data System (ADS)

    Ontiveros-Gallardo, Sergio E.; Kober, Vitaly

    2016-09-01

    Tracking solves the problem of detecting and estimating the future target state in an input video sequence. In this work, an adaptive tracking algorithm by means of multiple object detections in reduced frame areas with a tunable bank of correlation filters is proposed. Prediction of the target state is carried out with the Kalman filtering. It helps us to estimate the target state, to reduce the search area in the next frame, and to solve the occlusion problem. The bank of composite filters is updated frame by frame with tolerance to different recent viewpoint and scale changes of the target. The performance of the proposed algorithm with the help of computer simulation is evaluated in terms of detection and location errors.

  5. Correlation coefficient mapping in fluorescence spectroscopy: tissue classification for cancer detection.

    PubMed

    Crowell, Ed; Wang, Gufeng; Cox, Jason; Platz, Charles P; Geng, Lei

    2005-03-01

    Correlation coefficient mapping has been applied to intrinsic fluorescence spectra of colonic tissue for the purpose of cancer diagnosis. Fluorescence emission spectra were collected of 57 colonic tissue sites in a range of 4 physiological conditions: normal (29), hyperplastic (2), adenomatous (5), and cancerous tissues (21). The sample-sample correlation was used to examine the ability of correlation coefficient mapping to determine tissue disease state. The correlation coefficient map indicates two main categories of samples. These categories were found to relate to disease states of the tissue. Sensitivity, selectivity, predictive value positive, and predictive value negative for differentiation between normal tissue and all other categories were all above 92%. This was found to be similar to, or higher than, tissue classification using existing methods of data reduction. Wavelength-wavelength correlation among the samples highlights areas of importance for tissue classification. The two-dimensional correlation map reveals absorption by NADH and hemoglobin in the samples as negative correlation, an effect not obvious from the one-dimensional fluorescence spectra alone. The integrity of tissue was examined in a time series of spectra of a single tissue sample taken after tissue resection. The wavelength-wavelength correlation coefficient map shows the areas of significance for each fluorophore and their relation to each other. NADH displays negative correlation to collagen and FAD, from the absorption of emission or fluorescence resonance energy transfer. The wavelength-wavelength correlation map for the decay set also clearly shows that there are only three fluorophores of importance in the samples, by the well-defined pattern of the map. The sample-sample correlation coefficient map reveals the changes over time and their impact on tissue classification. Correlation coefficient mapping proves to be an effective method for sample classification and cancer

  6. Angular velocity-based structural damage detection

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  7. Microchip-based flow cytometry for effective detection and count

    NASA Astrophysics Data System (ADS)

    Mu, Canjun; Zhang, Zhiyi; Lin, Min; Cao, Xudong; Zhang, Feiling

    2009-06-01

    High-throughput detection and identification of foodborne pathogens are in increasing demand for rapid bacteria detections in food safety and quality monitoring. As an effective method, microchip-based flow cytometry (microcytometery) has a potential to be less expensive and high throughout, and requires less bulky instrumentation than conventional methods. In this work, a low-cost and robust microcytometer with a simple optical setup was developed for demonstrating the high-throughput identification of foodborne bacterial pathogens that integrate sample flow focusing and detection into one testing procedure. High performance identification capability was achieved through simultaneously detecting the fluorescence and scatter light emitted from micro-fabricated channel, after designing and optimizing the laser shaping optical system and the micro-channel structure to improve the excitation light intensity as well as the detection sensitivity. In our configuration, the simple testing configuration with the collection angle of 42° in the orthogonal plane to micro chip presents the best SNR for both signals through simulation and systematic measurements. As a result, the maximum throughput of 83particles/s for the fluorescence-labelled bead with diameter of 1.013μm was obtained as well as the high detection efficiency (above 99%) and the correlation percentage (above 99.5%). Apart from the high detection sensitivity and identification power, this microcytometer also has the advantages of simple optical structure, compactness and ease in building.

  8. 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. © 2011 Society for Applied Spectroscopy

  9. The matched-lag filter: detecting broadband multipath signals with auto- and cross-correlation functions.

    PubMed

    Spiesberger, J L

    2001-05-01

    Signal detection is considered for uncertain noise variance and a broadband source of unknown waveform and emission time. The signal travels to the receivers along paths with unknown delays. Using a new "matched-lag filter," the presence or absence of the signal is estimated from the auto- and cross-correlation functions of the receptions. Like a matched filter, correlation functions provide the first stage of gain in signal-to-noise ratio because the paths are assumed to be partially coherent. The second stage achieves additional gain by searching only over physically possible arrangements of signals in the auto- and cross-correlation functions while excluding forbidden arrangements. These stages enable the matched-lag filter to behave like a matched filter within a matched filter. In an ideal case, simulations of the matched-lag filter yield probabilities of detection that are, with one and two receivers, 4.1 and 366 times, respectively, that obtained from the conventional energy detector at a false-alarm probability of 0.001. The matched-lag filter has applications to wireless communications and the detection of acoustic signals from animals, vehicles, ships, and nuclear blasts. The matched-lag filter more completely describes signal structure than stochastic detection and communication theories whose specified auto-correlation function does not prohibit forbidden arrangements.

  10. On the Power of Multivariate Latent Growth Curve Models to Detect Correlated Change

    ERIC Educational Resources Information Center

    Hertzog, Christopher; Lindenberger, Ulman; Ghisletta, Paolo; Oertzen, Timo von

    2006-01-01

    We evaluated the statistical power of single-indicator latent growth curve models (LGCMs) to detect correlated change between two variables (covariance of slopes) as a function of sample size, number of longitudinal measurement occasions, and reliability (measurement error variance). Power approximations following the method of Satorra and Saris…

  11. The Multivariate Reality of Educational Research: Detecting Interaction Effects Using Canonical Correlation Analysis.

    ERIC Educational Resources Information Center

    Kirby, Peggy C.; Abernathy, Mari W.

    Canonical correlation analysis is the best technique to employ when the research problem has multiple predictor and multiple criterion (outcome) variables, which is usually the case in the "real" world of education. A hypothetical data set is presented to illustrate how this particular multivariate method can be used to detect effects of…

  12. Mutation detection in plasmid-based biopharmaceuticals.

    PubMed

    Oliveira, Pedro H; Prather, Kristala L J; Prazeres, Duarte M F; Monteiro, Gabriel A

    2011-04-01

    As the number of applications involving therapeutic plasmid DNA (pDNA) increases worldwide, there is a growing concern over maintaining rigorous quality control through a panel of high-quality assays. For this reason, efficient, cost-effective and sensitive technologies enabling the identification of genetic variants and unwanted side products are needed to successfully establish the identity and stability of a plasmid-based biopharmaceutical. This review highlights several bioinformatic tools for ab initio detection of potentially unstable DNA regions, as well as techniques used for mutation detection in nucleic acids, with particular emphasis on pDNA.

  13. Head tracker based on a compact optical correlator

    NASA Astrophysics Data System (ADS)

    Wilkinson, Tim D.; New, Nicholas J.

    2001-08-01

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

  14. 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.

  15. Anti-correlations in the degree distribution increase stimulus detection performance in noisy spiking neural networks.

    PubMed

    Martens, Marijn B; Houweling, Arthur R; E Tiesinga, Paul H

    2017-02-01

    Neuronal circuits in the rodent barrel cortex are characterized by stable low firing rates. However, recent experiments show that short spike trains elicited by electrical stimulation in single neurons can induce behavioral responses. Hence, the underlying neural networks provide stability against internal fluctuations in the firing rate, while simultaneously making the circuits sensitive to small external perturbations. Here we studied whether stability and sensitivity are affected by the connectivity structure in recurrently connected spiking networks. We found that anti-correlation between the number of afferent (in-degree) and efferent (out-degree) synaptic connections of neurons increases stability against pathological bursting, relative to networks where the degrees were either positively correlated or uncorrelated. In the stable network state, stimulation of a few cells could lead to a detectable change in the firing rate. To quantify the ability of networks to detect the stimulation, we used a receiver operating characteristic (ROC) analysis. For a given level of background noise, networks with anti-correlated degrees displayed the lowest false positive rates, and consequently had the highest stimulus detection performance. We propose that anti-correlation in the degree distribution may be a computational strategy employed by sensory cortices to increase the detectability of external stimuli. We show that networks with anti-correlated degrees can in principle be formed by applying learning rules comprised of a combination of spike-timing dependent plasticity, homeostatic plasticity and pruning to networks with uncorrelated degrees. To test our prediction we suggest a novel experimental method to estimate correlations in the degree distribution.

  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.

  17. Regional Principal Color Based Saliency Detection

    PubMed Central

    Lou, Jing; Ren, Mingwu; Wang, Huan

    2014-01-01

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

  18. 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.

  19. Optimized PCR-based detection of mycoplasma.

    PubMed

    Dobrovolny, Paige L; Bess, Dan

    2011-06-20

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

  20. Skeleton-Based Abnormal Gait Detection.

    PubMed

    Nguyen, Trong-Nguyen; Huynh, Huu-Hung; Meunier, Jean

    2016-10-26

    Human gait analysis plays an important role in musculoskeletal disorder diagnosis. Detecting anomalies in human walking, such as shuffling gait, stiff leg or unsteady gait, can be difficult if the prior knowledge of such a gait pattern is not available. We propose an approach for detecting abnormal human gait based on a normal gait model. Instead of employing the color image, silhouette, or spatio-temporal volume, our model is created based on human joint positions (skeleton) in time series. We decompose each sequence of normal gait images into gait cycles. Each human instant posture is represented by a feature vector which describes relationships between pairs of bone joints located in the lower body. Such vectors are then converted into codewords using a clustering technique. The normal human gait model is created based on multiple sequences of codewords corresponding to different gait cycles. In the detection stage, a gait cycle with normality likelihood below a threshold, which is determined automatically in the training step, is assumed as an anomaly. The experimental results on both marker-based mocap data and Kinect skeleton show that our method is very promising in distinguishing normal and abnormal gaits with an overall accuracy of 90.12%.

  1. Skeleton-Based Abnormal Gait Detection

    PubMed Central

    Nguyen, Trong-Nguyen; Huynh, Huu-Hung; Meunier, Jean

    2016-01-01

    Human gait analysis plays an important role in musculoskeletal disorder diagnosis. Detecting anomalies in human walking, such as shuffling gait, stiff leg or unsteady gait, can be difficult if the prior knowledge of such a gait pattern is not available. We propose an approach for detecting abnormal human gait based on a normal gait model. Instead of employing the color image, silhouette, or spatio-temporal volume, our model is created based on human joint positions (skeleton) in time series. We decompose each sequence of normal gait images into gait cycles. Each human instant posture is represented by a feature vector which describes relationships between pairs of bone joints located in the lower body. Such vectors are then converted into codewords using a clustering technique. The normal human gait model is created based on multiple sequences of codewords corresponding to different gait cycles. In the detection stage, a gait cycle with normality likelihood below a threshold, which is determined automatically in the training step, is assumed as an anomaly. The experimental results on both marker-based mocap data and Kinect skeleton show that our method is very promising in distinguishing normal and abnormal gaits with an overall accuracy of 90.12%. PMID:27792181

  2. 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.

  3. 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

  4. 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).

  5. 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.

  6. 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.

  7. Tests of Fit Based on the Correlation Coefficient

    DTIC Science & Technology

    1990-10-04

    is, the worse the fit. Sarkadi [1975] and more recently Gerlach [1979]have shown consistency for correlation tests based on R(.X,m), or equivalently Z...the distribution of quadratic forms in normal variables. Biometrika, 48, 419-426. 4. Sarkadi , K., (1975). The consistency of the Shapiro-Francia test

  8. Electrophysiological Correlates of Change Detection during Delayed Matching Task: A Comparison of Different References.

    PubMed

    Liang, Tengfei; Hu, Zhonghua; Li, Yuchen; Ye, Chaoxiong; Liu, Qiang

    2017-01-01

    Detecting the changed information between memory representation and incoming sensory inputs is a fundamental cognitive ability. By offering the promise of excellent temporal resolution, event-related potential (ERP) technique has served as a primary tool for studying this process with reference of the linked mastoid (LM). However, given that LM may distort the ERP signals, it is still undetermined whether LM is the best reference choice. The goal of the current study was to systematically compare LM, reference electrode standardization technique (REST) and average reference (AR) for assessing the ERP correlates of change detection during a delayed matching task. Colored shapes were adopted as materials while both the task-relevant shape feature and -irrelevant color feature could be changed. The results of the ERP amplitude showed that both of the task-relevant and -conjunction feature changes elicited significantly more positive posterior P2 in REST and AR, but not in LM. Besides, significantly increased N270 was observed in task-relevant and -conjunction feature changes in both the REST and LM, but in the conjunction feature change in AR. Only the REST-obtained N270 revealed a significant increment in task-irrelevant feature change, which was compatible with the delayed behavioral performance. Statistical parametric scalp mapping (SPSM) results showed a left posterior distribution for AR, an anterior distribution for LM, and both the anterior and left posterior distributions for REST. These results indicate that different types of references may provide distinct cognitive interpretations. Interestingly, only the SPSM of REST was consistent with previous fMRI findings. Combined with the evidence of simulation studies and the current observations, we take the REST-based results as the objective one, and recommend using REST technology in the future ERP data analysis.

  9. Detecting Communities Based on Network Topology

    NASA Astrophysics Data System (ADS)

    Liu, Wei; Pellegrini, Matteo; Wang, Xiaofan

    2014-07-01

    Network methods have had profound influence in many domains and disciplines in the past decade. Community structure is a very important property of complex networks, but the accurate definition of a community remains an open problem. Here we defined community based on three properties, and then propose a simple and novel framework to detect communities based on network topology. We analyzed 16 different types of networks, and compared our partitions with Infomap, LPA, Fastgreedy and Walktrap, which are popular algorithms for community detection. Most of the partitions generated using our approach compare favorably to those generated by these other algorithms. Furthermore, we define overlapping nodes that combine community structure with shortest paths. We also analyzed the E. Coli. transcriptional regulatory network in detail, and identified modules with strong functional coherence.

  10. 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.

  11. Hyperspectral materials detection/identification/quantification using the residual correlation method

    NASA Astrophysics Data System (ADS)

    Hudgins, Lonnie H.; Hayashi, Joan; Blake, Pamela L.; Tran, Luong V.; Kilday, Elizabeth

    2001-08-01

    Remote detection, identification, and quantification of materials is an important problem in earth resource assessment. Satellite-based hyperspectral imaging sensors currently being developed by government and industry partnerships (e.g. the Coastal Ocean Imaging Spectrometer aboard the Naval EarthMap Observer) appear to be uniquely qualified for this purpose. Obtaining accurate estimates of material abundance on a pixel-by-pixel basis poses many challenging algorithmic and computational difficulties. A significant issue that must be addressed is how to efficiently select endmembers from a library when that library is spectrally redundant. In this paper, we demonstrate how an improved version of the Residual Correlation Method (RCM+) can provide a flexible solution to this problem. The RCM+ offers a robust treatment for selecting endmembers from spectrally redundant libraries in a one-at-a-time fashion. We discuss alternative methods such as two-at-a-time, or more generally, N-at-a-time methods within a unified mathematical framework for analysis. Certain theorems apply to all such methods, and help to define a trade space for endmember selection methods in general. We demonstrate our results using synthetic test cases, and discuss how all endmember selection methods may be affected by redundancy within the library as well as specific properties of the data.

  12. 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

  13. 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.

  14. 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..

  15. Fast dual graph-based hotspot detection

    NASA Astrophysics Data System (ADS)

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

    2006-10-01

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

  16. Cross-correlation analysis of mechanomyographic signals detected in two axes.

    PubMed

    Beck, Travis W; Dillon, Michael A; DeFreitas, Jason M; Stock, Matt S

    2009-12-01

    The purpose of this study was to use laser displacement sensors to examine the cross-correlation of surface mechanomyographic (MMG) signals detected from the rectus femoris muscle in perpendicular and transverse axes during isometric muscle actions of the leg extensors. Ten healthy men (mean +/- SD age = 22.1 +/- 1.6 years) and ten healthy women (age = 24.4 +/- 2.8 years) volunteered to perform submaximal to maximal isometric muscle actions of the dominant leg extensors. During each muscle action, two separate MMG signals were detected from the rectus femoris with laser displacement sensors. One MMG sensor was oriented in an axis that was perpendicular (PERP) to the muscle surface, and the second sensor was oriented in an axis that was transverse (TRAN) to the muscle surface. For each subject and force level, the MMG signals from the PERP and TRAN sensors were cross-correlated. The results showed maximum cross-correlation coefficients that ranged from R(x)(,y) = 0.273 to 0.989, but all subjects demonstrated at least one coefficient greater than 0.89. These findings showed a high level of association between the MMG signals detected in the perpendicular and transverse axes. Thus, it may not be necessary to detect MMG signals in multiple axes.

  17. 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

  18. Fatigue crack detection by nonlinear spectral correlation with a wideband input

    NASA Astrophysics Data System (ADS)

    Liu, Peipei; Sohn, Hoon

    2017-04-01

    Due to crack-induced nonlinearity, ultrasonic wave can distort, create accompanying harmonics, multiply waves of different frequencies, and, under resonance conditions, change resonance frequencies as a function of driving amplitude. All these nonlinear ultrasonic features have been widely studied and proved capable of detecting fatigue crack at its very early stage. However, in noisy environment, the nonlinear features might be drown in the noise, therefore it is difficult to extract those features using a conventional spectral density function. In this study, nonlinear spectral correlation is defined as a new nonlinear feature, which considers not only nonlinear modulations in ultrasonic waves but also spectral correlation between the nonlinear modulations. The proposed nonlinear feature is associated with the following two advantages: (1) stationary noise in the ultrasonic waves has little effect on nonlinear spectral correlation; and (2) the contrast of nonlinear spectral correlation between damage and intact conditions can be enhanced simply by using a wideband input. To validate the proposed nonlinear feature, micro fatigue cracks are introduced to aluminum plates by repeated tensile loading, and the experiment is conducted using surface-mounted piezoelectric transducers for ultrasonic wave generation and measurement. The experimental results confirm that the nonlinear spectral correlation can successfully detect fatigue crack with a higher sensitivity than the classical nonlinear coefficient.

  19. Correlation-based pointwise processing of dynamic speckle patterns.

    PubMed

    Stoykova, Elena; Ivanov, Branimir; Nikova, Tania

    2014-01-01

    Correlation-based pointwise processing of dynamic speckle patterns is proposed for spatial characterization of activity in a sample. The result is a set of 2D activity maps of the estimates of temporal correlation, or structure functions, at increasing time lags. Pointwise computation provides spatial resolution, limited by the pixel period of the optical sensor used for acquisition of the speckle patterns. Pointwise normalization of the estimates solves the problem with the nonuniform illumination and varying reflectivity across the sample. The high contrast detailed activity maps obtained from processing of synthetic and experimental speckle patterns confirms efficiency of the proposed approach.

  20. An iterative detection method of MIMO over spatial correlated frequency selective channel: using list sphere decoding for simplification

    NASA Astrophysics Data System (ADS)

    Shi, Zhiping; Yan, Bing

    2010-08-01

    In multiple-input multiple-output(MIMO) wireless systems, combining good channel codes(e.g., Non-binary Repeat Accumulate codes) with adaptive turbo equalization is a good option to get better performance and lower complexity under Spatial Correlated Frequency Selective(SCFS) Channel. The key of this method is after joint antennas MMSE detection (JAD/MMSE) based on interruption cancelling using soft information, considering the detection result as an output of a Gaussian equivalent flat fading channel, and performing maximum likelihood detection(ML) to get more correct estimated result. But the using of ML brings great complexity increase, which is not allowed. In this paper, a low complexity method called list sphere decoding is introduced and applied to replace the ML in order to simplify the adaptive iterative turbo equalization system.

  1. 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.

  2. 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.

  3. Deformation of inherent structures to detect long-range correlations in supercooled liquids

    NASA Astrophysics Data System (ADS)

    Mosayebi, Majid; Del Gado, Emanuela; Ilg, Patrick; Öttinger, Hans Christian

    2012-07-01

    We propose deformations of inherent structures as a suitable tool for detecting structural changes underlying the onset of cooperativity in supercooled liquids. The non-affine displacement (NAD) field resulting from the applied deformation shows characteristic differences between the high temperature liquid and supercooled state, which are typically observed in dynamic quantities. The average magnitude of the NAD is very sensitive to temperature changes in the supercooled regime and is found to be strongly correlated with the inherent structure energy. In addition, the NAD field is characterized by a correlation length that increases upon lowering the temperature towards the supercooled regime.

  4. 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.

  5. Stereo vision-based pedestrian detection using dense disparity map-based detection and segmentation

    NASA Astrophysics Data System (ADS)

    Lee, Chung-Hee; Kim, Dongyoung

    2015-03-01

    In this paper, we propose a stereo vision-based pedestrian detection method using a dense disparity map-based detection and segmentation algorithm. To enhance a pedestrian detection performance, we use a dense disparity map extracted from a global stereo matching algorithm. First, we extract a road feature information from the dense disparity map, which is a decision basis of presence or absence of obstacles on the road. It is very important to extract the road feature from the disparity for detecting obstacles robustly regardless of external traffic situations. The obstacle detection is performed with the road feature information to detect only obstacles from entire image. In other words, pedestrian candidates including various upright objects are detected in the obstacle detection stage. Each obstacle area tends to include multiple objects. Thus, a disparity map-based segmentation is performed to separate the obstacle area into each obstacle accurately. And then, accurate pedestrian areas are extracted from segmented obstacle areas using road contact and pedestrian height information. This stage enables to reduce false alarms and to enhance computing speed. To recognize pedestrians, classifier is performed in each verified pedestrian candidate. Finally, we perform a verification stage to examine the recognized pedestrian in detail. Our algorithms are verified by conducting experiments using ETH database.

  6. Rapid and Robust Cross-Correlation-Based Seismic Phase Identification Using an Approximate Nearest Neighbor Method

    NASA Astrophysics Data System (ADS)

    Tibi, R.; Young, C. J.; Gonzales, A.; Ballard, S.; Encarnacao, A. V.

    2016-12-01

    The matched filtering technique involving the cross-correlation of a waveform of interest with archived signals from a template library has proven to be a powerful tool for detecting events in regions with repeating seismicity. However, waveform correlation is computationally expensive, and therefore impractical for large template sets unless dedicated distributed computing hardware and software are used. In this study, we introduce an Approximate Nearest Neighbor (ANN) approach that enables the use of very large template libraries for waveform correlation without requiring a complex distributed computing system. Our method begins with a projection into a reduced dimensionality space based on correlation with a randomized subset of the full template archive. Searching for a specified number of nearest neighbors is accomplished by using randomized K-dimensional trees. We used the approach to search for matches to each of 2700 analyst-reviewed signal detections reported for May 2010 for the IMS station MKAR. The template library in this case consists of a dataset of more than 200,000 analyst-reviewed signal detections for the same station from 2002-2014 (excluding May 2010). Of these signal detections, 60% are teleseismic first P, and 15% regional phases (Pn, Pg, Sn, and Lg). The analyses performed on a standard desktop computer shows that the proposed approach performs the search of the large template libraries about 20 times faster than the standard full linear search, while achieving recall rates greater than 80%, with the recall rate increasing for higher correlation values. To decide whether to confirm a match, we use a hybrid method involving a cluster approach for queries with two or more matches, and correlation score for single matches. Of the signal detections that passed our confirmation process, 52% were teleseismic first P, and 30% were regional phases.

  7. 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.

  8. Detection research on low light level target with joint transform correlator

    NASA Astrophysics Data System (ADS)

    Zhang, Su; Shang, Jiyang; Chen, Chi; Wang, Wensheng

    2011-08-01

    Low light level target detection has received more attentions in varieties of domains in recent years. In this paper we use hybrid optoelectronic joint transform correlator(HOJTC) for detecting and recognizing low light level target. It is thought to be one of the most effective methods in target detection. But because of the cluttered backgrounds and strong noises of the low light level target, it always can not be detected successfully. In order to solve this problem efficiently, firstly we choose sym4 wavelet function to achieve the purpose of wavelet de-noising. After that edge extraction processing is used to distinguish the useful target from the cluttered backgrounds with Sobel operator. At last processed targets can be put into HOJTC to obtain a pair of correlation peaks clearly. To prove this method, many experiments of low light level targets have been implemented with computer simulation method and optical experiment method. As an example a low light level image "deer" is presented. The results show that the low light level target can be detected from the cluttered backgrounds and strong noises with wavelet de-noising and Sobel operator successfully.

  9. 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.

  10. NO2 Detection Using Microcantilever Based Potentiometry

    PubMed Central

    Qazi, Muhammad; Koley, Goutam

    2008-01-01

    A highly sensitive and novel sensor platform for gases and volatile chemicals using microcantilever based potentiometry is reported. A resonant cantilever is used to detect the changes in surface work functions of functionalized substrates caused by adsorption of target gas molecules. Surface work function (SWF) changes were measured for different functionalization layers made of transition metal oxide thin films with the flow of NO2. The rate of change in SWF for In2O3 and SnO2 were found to be ∼80 and ∼100 μV/sec, respectively, for 70 ppm NO2. A sensitivity of 64 μV/sec for SWF change was also found for 70 ppm NO2 concentration for isolated clusters of ZnO nanowires, indicating that this technique is applicable even for nano-clusters of sensing materials where amperometric detection is impossible due to material discontinuity. NO2 detection as low as 400 ppb was possible using highly insulating In2O3 and SnO2 thin films (resistivity > 1 TΩ/□. Two different forms of nano scale graphite were compared with the transition oxide based functionalization layer for sensing sub-ppm NO2 sensing. It was observed that nanostructured graphite (NG) shows much higher sensitivity and lower response time than transition metal oxides. PMID:27873919

  11. NO₂ Detection Using Microcantilever Based Potentiometry.

    PubMed

    Qazi, Muhammad; Koley, Goutam

    2008-11-12

    A highly sensitive and novel sensor platform for gases and volatile chemicals using microcantilever based potentiometry is reported. A resonant cantilever is used to detect the changes in surface work functions of functionalized substrates caused by adsorption of target gas molecules. Surface work function (SWF) changes were measured for different functionalization layers made of transition metal oxide thin films with the flow of NO₂. The rate of change in SWF for In₂O₃ and SnO₂ were found to be ~80 and ~100 μV/sec, respectively, for 70 ppm NO₂. A sensitivity of 64 μV/sec for SWF change was also found for 70 ppm NO₂ concentration for isolated clusters of ZnO nanowires, indicating that this technique is applicable even for nano-clusters of sensing materials where amperometric detection is impossible due to material discontinuity. NO₂ detection as low as 400 ppb was possible using highly insulating In₂O₃ and SnO₂ thin films (resistivity > 1 TΩ/⎕). Two different forms of nano scale graphite were compared with the transition oxide based functionalization layer for sensing sub-ppm NO₂ sensing. It was observed that nanostructured graphite (NG) shows much higher sensitivity and lower response time than transition metal oxides.

  12. 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.

  13. 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.

  14. 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.

  15. Hip Prosthesis Detection based on Complex Natural Resonances.

    PubMed

    Lui, Hoi-Shun; Shuley, Nicholas; Crozier, Stuart

    2005-01-01

    Resonance based radar target detection has been applied to Ground Penetrating Radar (GPR) applications for the detection and recognition of landmines. Target detection is achieved by searching for certain target dependent Complex Natural Resonances (CNRs), which could be considered as a feature set for identification. In this paper, detection of a hip prosthesis under human tissues using resonance based target detection technique is investigated.

  16. 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.

  17. 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

  18. Contour based object detection using part bundles

    PubMed Central

    Lu, ChengEn; Adluru, Nagesh; Ling, Haibin; Zhu, Guangxi; Latecki, Longin Jan

    2016-01-01

    In this paper we propose a novel framework for contour based object detection from cluttered environments. Given a contour model for a class of objects, it is first decomposed into fragments hierarchically. Then, we group these fragments into part bundles, where a part bundle can contain overlapping fragments. Given a new image with set of edge fragments we develop an efficient voting method using local shape similarity between part bundles and edge fragments that generates high quality candidate part configurations. We then use global shape similarity between the part configurations and the model contour to find optimal configuration. Furthermore, we show that appearance information can be used for improving detection for objects with distinctive texture when model contour does not sufficiently capture deformation of the objects.

  19. [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.

  20. An SPR based sensor for allergens detection.

    PubMed

    Ashley, J; Piekarska, M; Segers, C; Trinh, L; Rodgers, T; Willey, R; Tothill, I E

    2017-02-15

    A simple, sensitive and label-free optical sensor method was developed for allergens analysis using α-casein as the biomarker for cow's milk detection, to be used directly in final rinse samples of cleaning in place systems (CIP) of food manufacturers. A Surface Plasmon Resonance (SPR) sensor chip consisting of four sensing arrays enabling the measurement of samples and control binding events simultaneously on the sensor surface was employed in this work. SPR offers several advantages in terms of label free detection, real time measurements and superior sensitivity when compared to ELISA based techniques. The gold sensor chip was used to immobilise α-casein-polyclonal antibody using EDC/NHS coupling procedure. The performance of the assay and the sensor was first optimised and characterised in pure buffer conditions giving a detection limit of 58ngmL(-1) as a direct binding assay. The assay sensitivity can be further improved by using sandwich assay format and amplified with nanoparticles. However, at this stage this is not required as the detection limit achieved exceeded the required allergens detection levels of 2µgmL(-1) for α-S1-casein. The sensor demonstrated good selectivity towards the α-casein as the target analyte and adequate recoveries from CIP final rinse wash samples. The sensor would be useful tool for monitoring allergen levels after cleaning procedures, providing additional data that may better inform upon wider food allergen risk management decision(s) that are made by food manufacturer. In particular, this sensor could potentially help validate or optimise cleaning practices for a given food manufacturing process.

  1. Energy based correlation criteria in the mid-frequency range

    NASA Astrophysics Data System (ADS)

    Biedermann, J.; Winter, R.; Wandel, M.; Böswald, M.

    2017-07-01

    Aircraft structures are characterized by their lightweight design. As such, they are prone to vibrations. Numerical models based on the Finite Element Method often show significant deviations when the mid-frequency range is considered, where strong interaction between vibrations and acoustics is present. Model validation based on experimental modal data is often not possible due to the high modal density that aircraft fuselage structures exhibit in this frequency range. Classical correlation criteria like the Modal Assurance Criterion require mode shapes and can therefore not be applied. Other correlation criteria using frequency response data, such as the Frequency Domain Assurance Criterion, are highly sensitive to even small structural modifications and fail to indicated the correlation between test and analysis data in the mid-frequency range. Nevertheless, validated numerical models for the mid- to high-frequency ranges are a prerequisite for acoustic comfort predictions of aircraft cabin. This paper presents a new method for the correlation of response data from test and analysis in the mid-frequency range to support model validation in the mid-frequency range and to enable the usage of finite element models in this frequency range. The method is validated on a stiffened cylindrical shell structure, which represents a scale-model of an aircraft fuselage. The correlation criterion presented here is inspired by Statistical Energy Analysis and is based on kinetic energies integrated over frequency bands and spatially integrated over surface areas of the structure. The objective is to indicate frequency bands where the finite element model needs to be adjusted to better match with experimental observations and to locate the areas where these adjustments should be applied.

  2. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2008-10-01

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

  4. 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.

  5. Incidentally detected breast lesions on chest CT with US correlation: a pictorial essay

    PubMed Central

    Son, Jung Hee; Jung, Hyun Kyung; Song, Jong Woon; Baek, Hye Jin; Doo, Kyung Won; Kim, Woogyeong; Kim, Yeon Mee; Kim, Woon Won; Lee, Jung Sun; Cho, Een Young

    2016-01-01

    With the increasing use of computed tomography (CT), incidental breast lesions are detected more frequently. When interpreting chest CT findings, it is important for radiologists to carefully review the breast to recognize any abnormal findings that could affect patient management. The purpose of this study is to discuss incidental breast lesions on chest CT with ultrasonography correlation that may be encountered in routine clinical practice. PMID:27707680

  6. 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.

  7. Search for time-correlated optical flashes of GRO-detected gamma-ray bursts

    NASA Technical Reports Server (NTRS)

    Greiner, J.; Wenzel, W.; Hudec, R.; Moskalenko, E. I.; Fishman, G. J.; Kouveliotou, C.; Meegan, C. A.; Paciesas, W. S.; Wilson, R. B.

    1992-01-01

    This status report presents some details on the project 'Search for time-correlated optical counterparts of gamma-ray bursters'. The photographic sky patrol of the three observatories Sonneberg (FRG), Ondrejov (CSFR), and Odessa (USSR) is used to look for patrol plates which have been exposed simultaneously with a gamma-ray burst detected by GRO. Our expectations and the very first results are presented.

  8. Time correlation measurements from extensive air showers detected by the EEE telescopes

    NASA Astrophysics Data System (ADS)

    Abbrescia, M.; Agocs, A.; Aiola, S.; Antolini, R.; Avanzini, C.; Baldini Ferroli, R.; Bencivenni, G.; Bossini, E.; Bressan, E.; Chiavassa, A.; Cicalò, C.; Cifarelli, L.; Coccia, E.; De Gruttola, D.; De Pasquale, S.; Di Giovanni, A.; D'Incecco, M.; Dreucci, M.; Fabbri, F. L.; Frolov, V.; Garbini, M.; Gemme, G.; Gnesi, I.; Gustavino, C.; Hatzifotiadou, D.; La Rocca, P.; Li, S.; Librizzi, F.; Maggiora, A.; Massai, M.; Miozzi, S.; Panareo, M.; Paoletti, R.; Perasso, L.; Pilo, F.; Piragino, G.; Regano, A.; Riggi, F.; Righini, G. C.; Sartorelli, G.; Scapparone, E.; Scribano, A.; Selvi, M.; Serci, S.; Siddi, E.; Spandre, G.; Squarcia, S.; Taiuti, M.; Tosello, F.; Votano, L.; Williams, M. C. S.; Yanez, G.; Zichichi, A.; Zouyevski, R.

    2013-12-01

    Time correlated events due to cosmic muons from extensive air showers have been detected by means of telescope pairs of the EEE (Extreme Energy Events) Project array. The coincidence rate, properly normalized for detector acceptance, efficiency and altitude location, has been extracted as a function of the relative distance between the telescopes. The results have been also compared with additional measurements carried out by small scintillator detectors at various distances.

  9. 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.

  10. 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.

  11. Step detection in single-molecule real time trajectories embedded in correlated noise.

    PubMed

    Arunajadai, Srikesh G; Cheng, Wei

    2013-01-01

    Single-molecule real time trajectories are embedded in high noise. To extract kinetic or dynamic information of the molecules from these trajectories often requires idealization of the data in steps and dwells. One major premise behind the existing single-molecule data analysis algorithms is the gaussian 'white' noise, which displays no correlation in time and whose amplitude is independent on data sampling frequency. This so-called 'white' noise is widely assumed but its validity has not been critically evaluated. We show that correlated noise exists in single-molecule real time trajectories collected from optical tweezers. The assumption of white noise during analysis of these data can lead to serious over- or underestimation of the number of steps depending on the algorithms employed. We present a statistical method that quantitatively evaluates the structure of the underlying noise, takes the noise structure into account, and identifies steps and dwells in a single-molecule trajectory. Unlike existing data analysis algorithms, this method uses Generalized Least Squares (GLS) to detect steps and dwells. Under the GLS framework, the optimal number of steps is chosen using model selection criteria such as Bayesian Information Criterion (BIC). Comparison with existing step detection algorithms showed that this GLS method can detect step locations with highest accuracy in the presence of correlated noise. Because this method is automated, and directly works with high bandwidth data without pre-filtering or assumption of gaussian noise, it may be broadly useful for analysis of single-molecule real time trajectories.

  12. Spectral fringe-adjusted joint transform correlation based efficient object classification in hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Sidike, Paheding; Alam, Mohammad S.

    2013-03-01

    The spectral fringe-adjusted joint transform correlation (SFJTC) has been used effectively for performing deterministic target detection in hyperspectral imagery. However, experiments show decreased performance when noise-corrupted spectral variability is present in the target signatures. In this paper, we propose to use a modified spectral fringe-adjusted joint transform correlation based target detection algorithm, which employs a new real-valued filter called the logarithmic fringe-adjusted filter (LFAF). Furthermore, the maximum noise fraction (MNF) technique is used for preprocessing the hyperspectral imagery, which makes the SFJTC technique more insensitive to spectral variability in noisy environment. Test results using real life oil spill based hyperspectral image datasets show that the proposed scheme yields better performance compared to alternate techniques.

  13. 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.

  14. Design and implementation of random noise radar with spectral-domain correlation for moving target detection

    NASA Astrophysics Data System (ADS)

    Kim, Jeong Phill; Jeong, Chi Hyun; Kim, Cheol Hoo

    2011-06-01

    A correlation processing algorithm in the spectral domain is proposed for detecting moving targets with random noise radar. AD converted reference and Rx signals are passed through FFT block, and they are multiplied after the reference signal is complex conjugated. Now inverse FFT yields the sub-correlation results, and range and velocity information can be accurately extracted by an additional FFT processing. In this design procedure, specific considerations have to be made for correlation length, averaging number, and number of sub-correlation data for Doppler processing. The proposed algorithm was verified by Simulink (Mathworks) simulation, and its logic was implemented with Xilinx FPGA device (Vertex5 series) by System Generator block sets (Xilinx) in the Simulink environment. A CW X-band random-FM noise radar prototype with an instantaneous bandwidth of 100 MHz was designed and implemented, and laboratory and field tests were conducted to detect moving targets, and the observed results showed the validity of the proposed algorithm and the operation of implemented FPGA logics.

  15. 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.

  16. Correlated EEG Signals Simulation Based on Artificial Neural Networks.

    PubMed

    Tomasevic, Nikola M; Neskovic, Aleksandar M; Neskovic, Natasa J

    2016-09-30

    In recent years, simulation of the human electroencephalogram (EEG) data found its important role in medical domain and neuropsychology. In this paper, a novel approach to simulation of two cross-correlated EEG signals is proposed. The proposed method is based on the principles of artificial neural networks (ANN). Contrary to the existing EEG data simulators, the ANN-based approach was leveraged solely on the experimentally acquired EEG data. More precisely, measured EEG data were utilized to optimize the simulator which consisted of two ANN models (each model responsible for generation of one EEG sequence). In order to acquire the EEG recordings, the measurement campaign was carried out on a healthy awake adult having no cognitive, physical or mental load. For the evaluation of the proposed approach, comprehensive quantitative and qualitative statistical analysis was performed considering probability distribution, correlation properties and spectral characteristics of generated EEG processes. The obtained results clearly indicated the satisfactory agreement with the measurement data.

  17. Unified picture for magnetic correlations in iron-based superconductors.

    PubMed

    Yin, Wei-Guo; Lee, Chi-Cheng; Ku, Wei

    2010-09-03

    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.

  18. Detecting millisecond-range coupling delays between brainwaves in terms of power correlations by magnetoencephalography.

    PubMed

    Dabek, Juhani; Nikulin, Vadim V; Ilmoniemi, Risto J

    2014-09-30

    The spatiotemporal coupling of brainwaves is commonly quantified using the amplitude or phase of signals measured by electro- or magnetoencephalography (EEG/MEG). To enhance the temporal resolution for coupling delays down to millisecond level, a new power correlation (PC) method is proposed and tested. The cross-correlations of any two brainwave powers at two locations are calculated sequentially through a measurement using the convolution theorem. For noise suppression, the cross-correlation series is moving-average filtered, preserving the millisecond resolution in the cross-correlations, but with reduced noise. The coupling delays are determined from the delays of the cross-correlation peaks. Simulations showed that the new method detects reliably power cross-correlations with millisecond accuracy. Moreover, in MEG measurements on three healthy volunteers, the method showed average alpha-alpha coupling delays of around 0-20 ms between the occipital areas of two hemispheres. Lower-frequency brainwaves vs. alpha waves tended to have a larger lag; higher-frequency waves vs. alpha waves showed delays with large deviations. The use of signal power instead of its square root (amplitude) in the cross-correlations improves noise cancellation. Compared to signal phase, the signal power analysis time delays do not have periodic ambiguity. In addition, the novel method allows fast calculation of cross-correlations. The PC method conveys novel information about brainwave dynamics. The method may be extended from sensor-space to source-space analysis, and can be applied also for electroencephalography (EEG) and local field potentials (LFP). Copyright © 2014 Elsevier B.V. All rights reserved.

  19. Aging effects on detection of spectral changes induced by a break in sound correlation.

    PubMed

    Qu, Tianshu; Cao, Shuyang; Chen, Xun; Huang, Ying; Li, Liang; Wu, Xihong; Schneider, Bruce A

    2013-01-01

    Previous studies have shown that both younger adults and older adults with clinically normal hearing are able to detect a break in correlation (BIC) between interaurally correlated sounds presented over headphones. This ability to detect a BIC improved when the correlated sounds were presented over left and right loudspeakers rather than over left and right headphones, suggesting that additional spectral cues provided by comb filtering (caused by interference between the two channels) facilitate detection of the BIC. However, older adults receive significantly less benefit than younger adults from a switch to loudspeaker presentation. It is hypothesized that this is a result of an age-related reduction in the sensitivity to the monaural spectral cues provided by comb filtering. Two experiments were conducted in this study. Correlated white noises with a BIC in the temporal middle were presented from two spatially separated loudspeakers (positioned at ±45-degree azimuth) and recorded at the right ear of a Knowles Electronic Manikin for Acoustic Research (KEMAR). In Experiment 1, the waveforms recorded at the KEMAR's right ear were presented to the participant's right ear over a headphone in 14 younger adults and 24 older adults with clinically normal hearing. In Experiment 2, 8 of the 14 younger participants participated. Under the monaurally cueing condition, the waveforms recorded at the KEMAR's right ear were presented to the participant's right ear as Experiment 1. Under the binaurally cueing condition, waveforms delivered from the left loudspeaker and those from the right loudspeaker were recorded at the KEMAR's left and right ear, respectively, thereby eliminating the spectral ripple cue, and were presented to the participant's left and right ears, respectively. For each of the two experiments, the break duration threshold for detecting the BIC was examined when the interloudspeaker interval (delay) (ILI) was 0, 1, 2, or 4 msec (left loudspeaker leading). In

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

    PubMed

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

    2013-11-01

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

  1. Bhattacharyya distance based video scene change detection

    NASA Astrophysics Data System (ADS)

    Shen, Bichuan; Chen, C. H.

    2009-10-01

    This paper studies statistics based scene change detection in the video streaming scenario, and three scene feature metrics including histogram distance, chi-square distance, and Bhattacharyya distance have been investigated. With the unique characteristics of triangular inequality and non-singularity, Bhattacharyya distance has been proposed as a viable scene change metrics. It outperforms much better than the other two in that it calculates and maximizes the feature vector distance between multi-modal clusters in a hyper-sphere space. The experiments are conducted and the precision recall statistics are compared, and the results support our analysis.

  2. Covariance based outlier detection with feature selection.

    PubMed

    Zwilling, Chris E; Wang, Michelle Y

    2016-08-01

    The present covariance based outlier detection algorithm selects from a candidate set of feature vectors that are best at identifying outliers. Features extracted from biomedical and health informatics data can be more informative in disease assessment and there are no restrictions on the nature and number of features that can be tested. But an important challenge for an algorithm operating on a set of features is for it to winnow the effective features from the ineffective ones. The powerful algorithm described in this paper leverages covariance information from the time series data to identify features with the highest sensitivity for outlier identification. Empirical results demonstrate the efficacy of the method.

  3. Effective information spreading based on local information in correlated networks

    PubMed Central

    Gao, Lei; Wang, Wei; Pan, Liming; Tang, Ming; Zhang, Hai-Feng

    2016-01-01

    Using network-based information to facilitate information spreading is an essential task for spreading dynamics in complex networks. Focusing on degree correlated networks, we propose a preferential contact strategy based on the local network structure and local informed density to promote the information spreading. During the spreading process, an informed node will preferentially select a contact target among its neighbors, basing on their degrees or local informed densities. By extensively implementing numerical simulations in synthetic and empirical networks, we find that when only consider the local structure information, the convergence time of information spreading will be remarkably reduced if low-degree neighbors are favored as contact targets. Meanwhile, the minimum convergence time depends non-monotonically on degree-degree correlation, and a moderate correlation coefficient results in the most efficient information spreading. Incorporating the local informed density information into contact strategy, the convergence time of information spreading can be further reduced, and be minimized by an moderately preferential selection. PMID:27910882

  4. Theory and practical recommendations for autocorrelation-based image correlation spectroscopy

    PubMed Central

    George, Steven C.

    2012-01-01

    Abstract. Image correlation spectroscopy (ICS) is a powerful technique for detecting arrangement of fluorophores in images. This tutorial gives background into the mathematical underpinnings of ICS, specifically image autocorrelation. The effects of various artifacts and image processing steps, including background subtraction, noise, and image morphology were examined analytically and their effects on ICS analysis modeled. A series of recommendations was built based on this analysis. PMID:23224160

  5. 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.

  6. 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.

  7. Cluster-based co-saliency detection.

    PubMed

    Fu, Huazhu; Cao, Xiaochun; Tu, Zhuowen

    2013-10-01

    Co-saliency is used to discover the common saliency on the multiple images, which is a relatively underexplored area. In this paper, we introduce a new cluster-based algorithm for co-saliency detection. Global correspondence between the multiple images is implicitly learned during the clustering process. Three visual attention cues: contrast, spatial, and corresponding, are devised to effectively measure the cluster saliency. The final co-saliency maps are generated by fusing the single image saliency and multiimage saliency. The advantage of our method is mostly bottom-up without heavy learning, and has the property of being simple, general, efficient, and effective. Quantitative and qualitative experiments result in a variety of benchmark datasets demonstrating the advantages of the proposed method over the competing co-saliency methods. Our method on single image also outperforms most the state-of-the-art saliency detection methods. Furthermore, we apply the co-saliency method on four vision applications: co-segmentation, robust image distance, weakly supervised learning, and video foreground detection, which demonstrate the potential usages of the co-saliency map.

  8. 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

  9. Waveguide-based biosensors for pathogen detection.

    PubMed

    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.

  10. Cluster-based Co-saliency Detection

    PubMed Central

    Fu, Huazhu; Cao, Xiaochun; Tu, Zhuowen

    2013-01-01

    Co-saliency is used to discover the common saliency on the multiple images, which is a relatively under-explored area. In this paper, we introduce a new cluster-based algorithm for co-saliency detection. Global correspondence between the multiple images is implicitly learned during the clustering process. Three visual attention cues: contrast, spatial, and corresponding, are devised to effectively measure the cluster saliency. The final co-saliency maps are generated by fusing the single image saliency and multi-image saliency. The advantage of our method is mostly bottom-up without heavy learning, and has the property of being simple, general, efficient, and effective. Quantitative and qualitative experimental results on a variety of benchmark datasets demonstrate the advantages of the proposed method over the competing co-saliency methods, and our method on single image also outperforms most the state-of-the-art saliency detection methods. Furthermore, we apply the co-saliency method on four vision applications: co-segmentation, robust image distance, weakly supervised learning, and video foreground detection, which demonstrate the potential usages of the co-saliency map. PMID:23629857

  11. 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

  12. Laser-Based Pulsed Photoacoustic Ammonia Detection

    NASA Astrophysics Data System (ADS)

    Vallespi, Arturo; Slezak, Verónica; Peuriot, Alejandro; Santiago, Guillermo

    2013-09-01

    Detecting ammonia traces is relevant in health, manufacturing, and security areas, among others. As ammonia presents a strong absorption band (the mode) around 10 m, some of the physical properties which may influence its detection by means of pulsed photoacoustic (PA) spectroscopy with a TEA laser have been studied. The characteristics of the ammonia molecule and the laser intensity may result in a nonlinear dependence of the PA signal amplitude on the laser fluence. Ammonia absorption can be described as a simple two-level system with power broadening. As is a polar molecule, it strongly undergoes adsorption phenomena in contact with different surfaces. Therefore, physical adsorption-desorption at the cell’s wall is studied. A theoretical model, based on Langmuir’s assumptions, fits well to the experimental results with stainless steel. Related to these studies, measurements led to the conclusion that, at the used fluenced values, dissociation by multiphotonic absorption at the 10P(32) laser line may be discarded. A calibration of the system was performed, and a detection limit around 190 ppb (at 224 ) was achieved.

  13. [Time-correlated measurement of autofluorescence. A method to detect metabolic changes in the fundus].

    PubMed

    Schweitzer, D; Kolb, A; Hammer, M; Anders, R

    2002-10-01

    The detection of metabolic changes opens the possibility for intervention of reversible pathological alterations. Measurements of oxygen saturation are limited to the blood vessel system. Detection of alterations in oxygen concentrations are up to 3 orders of magnitude more sensitive by autofluorescence of coenzymes than by measurement of oxygen saturation. Because of limited transmission of the ocular media no specific excitation of endogenous fluorophores can be realised. For this reason it was investigated if the fluorescence lifetime after pulse excitation can be detected at the human fundus. Applying a laser scanner ophthalmoscope and mode-locked Ar(+) laser as well as time-correlated single photon counting, lifetime images of the living fundus were obtained. In mono-exponential approximation, a mean lifetime of 5 ns was detected from the optic disc and large vessels whereas about 1.5 ns were detected in the parapapillary area. By evaluating the frequency of lifetimes, lipofuscin, free FAD, and collagen are probably detectable. Comparative measurements were performed in fundus specimens and on free FAD.

  14. The modified correlation mass method for detecting neutrino mass from astrophysical neutrino bursts

    NASA Technical Reports Server (NTRS)

    Chan, Kwing L.; Chiu, Hong-Yee; Kondo, Yoji

    1989-01-01

    A modified correlation mass method for calculating the value of a possible neutrino mass from neutrino bursts of astrophysical origin is proposed which can more sensitively detect small neutrino masses than previous methods. Application of the method to the neutrinos detected from SN 1987 A yields a value of 3.6 + or - 0.3 eV for the neutrino mass energy with a confidence level of 97 percent. Assuming a neutrino mass of 3.6 eV, and transforming all of the detected neutrino events back to the point of emission, it is shown that bursts are composed of a short initial pulse (which lasts for about 0.1 sec and contains 30-40 percent of the total neutrinos) and an extended emission lasting for about 10 sec.

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

    SciTech Connect

    Paglieroni, David W.

    2016-06-07

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

  16. Artifact Free and Detection Profile Independent Higher Order Fluorescence Correlation Spectroscopy for Microsecond Resolved Kinetics. 2. Mixtures and Reactions.

    PubMed

    Abdollah-Nia, Farshad; Gelfand, Martin P; Van Orden, Alan K

    2017-02-09

    Fluorescence correlation spectroscopy (FCS) is a primary tool in the time-resolved analysis of non-reacting or reacting molecules in solution, based on fluorescence intensity fluctuations. However, conventional FCS alone is insufficient for complete determination of reaction or mixture parameters. In an accompanying article, a technique for computation of artifact-free higher-order correlations with microsecond time resolution was described. Here, we demonstrate applications of the technique to analyze systems of fast and slow reactions. As an example of slow- or non-reacting systems, the technique is applied to resolve two-component mixtures of labeled oligonucleotides. Next, the protonation reaction of fluorescein isothiocyanate (FITC) in phosphate buffer is analyzed as an example of fast reactions (relaxation time <1 μs ). By reference to an (apparent) non-reacting system, the simple factorized form of cumulant-based higher-order correlations is exploited to remove the dependence on the molecular detection function (MDF). Therefore, there is no need to model and characterize the experimental MDF, and the precision and the accuracy of the technique are enhanced. It is verified that higher-order correlation analysis enables complete and simultaneous determination of number and brightness parameters of mixing or reacting molecules, the reaction relaxation time, and forward and reverse reaction rates.

  17. 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.

  18. Edge detection in potential filed using the correlation coefficients between the average and standard deviation of vertical derivatives

    NASA Astrophysics Data System (ADS)

    Du, Wei; Wu, Yangang; Guan, Yanwu; Hao, Mengcheng

    2017-08-01

    Edge detection is an essential task in the interpretation of potential field data. Many existing edge detection methods are the functions composed by the horizontal derivative and vertical derivative of potential field data. The edges recognized by those methods are bigger than the true edges and when the depths of the geological bodies are different, the edges will be detected fuzzy and difficult to identify the edges accurately. In this paper, we present a new method to delineate the edges of the sources, which is based on the correlation coefficients between the average and standard deviation of vertical derivatives in a sliding window. The algorithm of this method is very simple. The zero value of the correlation coefficients is used to delineate the geological edges. It's clear to see the edges with the zero contours which will lead to continuous and clear detected edges and the method shows the edges more precisely. Moreover, the anomalies in different depths can be detected in the same degree and are insensitive to noise. The measure is initially applied on the synthetic gravity and magnetic data. The tests of theoretical models indicate that the new method could detect the edges of models in different depths and the position is in good accordance with the models' edges. Finally, this method is applied to gravity data from a portion of Vientiane Basin, Laos. As a result, the method is helpful in recognizing geologic fractures clearly. Moreover, it shows more geologic details with smaller window size and gives superior results with higher quality data.

  19. Correlation-coefficient-based fast template matching through partial elimination.

    PubMed

    Mahmood, Arif; Khan, Sohaib

    2012-04-01

    Partial computation elimination techniques are often used for fast template matching. At a particular search location, computations are prematurely terminated as soon as it is found that this location cannot compete with an already known best match location. Due to the nonmonotonic growth pattern of the correlation-based similarity measures, partial computation elimination techniques have been traditionally considered inapplicable to speed up these measures. In this paper, we show that partial elimination techniques may be applied to a correlation coefficient by using a monotonic formulation, and we propose basic-mode and extended-mode partial correlation elimination algorithms for fast template matching. The basic-mode algorithm is more efficient on small template sizes, whereas the extended mode is faster on medium and larger templates. We also propose a strategy to decide which algorithm to use for a given data set. To achieve a high speedup, elimination algorithms require an initial guess of the peak correlation value. We propose two initialization schemes including a coarse-to-fine scheme for larger templates and a two-stage technique for small- and medium-sized templates. Our proposed algorithms are exact, i.e., having exhaustive equivalent accuracy, and are compared with the existing fast techniques using real image data sets on a wide variety of template sizes. While the actual speedups are data dependent, in most cases, our proposed algorithms have been found to be significantly faster than the other algorithms.

  20. 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

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

    PubMed

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

    2009-11-26

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

  2. Correlation Between Bowel Preparation and the Adenoma Detection Rate in Screening Colonoscopy.

    PubMed

    Park, Jung Hun; Kim, Sang Jin; Hyun, Jong Hee; Han, Kyung Su; Kim, Byung Chang; Hong, Chang Won; Lee, Sang-Jeon; Sohn, Dae Kyung

    2017-06-01

    The adenoma detection rate is commonly used as a measure of the quality of colonoscopy. This study assessed both the association between the adenoma detection rate and the quality of bowel preparation and the risk factors associated with the adenoma detection rate in screening colonoscopy. This retrospective analysis involved 1,079 individuals who underwent screening colonoscopy at the National Cancer Center between December 2012 and April 2014. Bowel preparation was classified by using the Aronchick scale. Individuals with inadequate bowel preparations (n = 47, 4.4%) were excluded because additional bowel preparation was needed. The results of 1,032 colonoscopies were included in the analysis. The subjects' mean age was 53.1 years, and 657 subjects (63.7%) were men. The mean cecal intubation time was 6.7 minutes, and the mean withdrawal time was 8.7 minutes. The adenoma and polyp detection rates were 28.1% and 41.8%, respectively. The polyp, adenoma, and advanced adenoma detection rates did not correlate with the quality of bowel preparation. The multivariate analysis showed age ≥ 60 years (hazard ratio [HR], 1.42; 95% confidence interval [CI], 1.02-1.97; P = 0.040), body mass index ≥ 25 kg/m(2) (HR, 1.56; 95% CI, 1.17-2.08; P = 0.002) and current smoking (HR, 1.44; 95% CI, 1.01-2.06; P = 0.014) to be independent risk factors for adenoma detection. The adenoma detection rate was unrelated to the quality of bowel preparation for screening colonoscopy. Older age, obesity, and smoking were independent risk factors for adenoma detection.

  3. Feature Selection Using Information Gain for Improved Structural-Based Alert Correlation.

    PubMed

    Alhaj, Taqwa Ahmed; Siraj, Maheyzah Md; Zainal, Anazida; Elshoush, Huwaida Tagelsir; Elhaj, Fatin

    2016-01-01

    Grouping and clustering alerts for intrusion detection based on the similarity of features is referred to as structurally base alert correlation and can discover a list of attack steps. Previous researchers selected different features and data sources manually based on their knowledge and experience, which lead to the less accurate identification of attack steps and inconsistent performance of clustering accuracy. Furthermore, the existing alert correlation systems deal with a huge amount of data that contains null values, incomplete information, and irrelevant features causing the analysis of the alerts to be tedious, time-consuming and error-prone. Therefore, this paper focuses on selecting accurate and significant features of alerts that are appropriate to represent the attack steps, thus, enhancing the structural-based alert correlation model. A two-tier feature selection method is proposed to obtain the significant features. The first tier aims at ranking the subset of features based on high information gain entropy in decreasing order. The‏ second tier extends additional features with a better discriminative ability than the initially ranked features. Performance analysis results show the significance of the selected features in terms of the clustering accuracy using 2000 DARPA intrusion detection scenario-specific dataset.

  4. Feature Selection Using Information Gain for Improved Structural-Based Alert Correlation

    PubMed Central

    Siraj, Maheyzah Md; Zainal, Anazida; Elshoush, Huwaida Tagelsir; Elhaj, Fatin

    2016-01-01

    Grouping and clustering alerts for intrusion detection based on the similarity of features is referred to as structurally base alert correlation and can discover a list of attack steps. Previous researchers selected different features and data sources manually based on their knowledge and experience, which lead to the less accurate identification of attack steps and inconsistent performance of clustering accuracy. Furthermore, the existing alert correlation systems deal with a huge amount of data that contains null values, incomplete information, and irrelevant features causing the analysis of the alerts to be tedious, time-consuming and error-prone. Therefore, this paper focuses on selecting accurate and significant features of alerts that are appropriate to represent the attack steps, thus, enhancing the structural-based alert correlation model. A two-tier feature selection method is proposed to obtain the significant features. The first tier aims at ranking the subset of features based on high information gain entropy in decreasing order. The‏ second tier extends additional features with a better discriminative ability than the initially ranked features. Performance analysis results show the significance of the selected features in terms of the clustering accuracy using 2000 DARPA intrusion detection scenario-specific dataset. PMID:27893821

  5. 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.

  6. 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.

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

    SciTech Connect

    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.

  8. Cross correlation calculations and neutron scattering analysis for a portable solid state neutron detection system

    NASA Astrophysics Data System (ADS)

    Saltos, Andrea

    In efforts to perform accurate dosimetry, Oakes et al. [Nucl. Intrum. Mehods. (2013)] introduced a new portable solid state neutron rem meter based on an adaptation of the Bonner sphere and the position sensitive long counter. The system utilizes high thermal efficiency neutron detectors to generate a linear combination of measurement signals that are used to estimate the incident neutron spectra. The inversion problem associated to deduce dose from the counts in individual detector elements is addressed by applying a cross-correlation method which allows estimation of dose with average errors less than 15%. In this work, an evaluation of the performance of this system was extended to take into account new correlation techniques and neutron scattering contribution. To test the effectiveness of correlations, the Distance correlation, Pearson Product-Moment correlation, and their weighted versions were performed between measured spatial detector responses obtained from nine different test spectra, and the spatial response of Library functions generated by MCNPX. Results indicate that there is no advantage of using the Distance Correlation over the Pearson Correlation, and that weighted versions of these correlations do not increase their performance in evaluating dose. Both correlations were proven to work well even at low integrated doses measured for short periods of time. To evaluate the contribution produced by room-return neutrons on the dosimeter response, MCNPX was used to simulate dosimeter responses for five isotropic neutron sources placed inside different sizes of rectangular concrete rooms. Results show that the contribution of scattered neutrons to the response of the dosimeter can be significant, so that for most cases the dose is over predicted with errors as large as 500%. A possible method to correct for the contribution of room-return neutrons is also assessed and can be used as a good initial estimate on how to approach the problem.

  9. 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.

  10. Ground-Based Correlates of Solar Irradiance Variation

    NASA Technical Reports Server (NTRS)

    Jones, Harrison P.

    2001-01-01

    Ground-based instruments cannot directly measure solar irradiance variability at the 0.1% level at which it occurs because of the earth's atmosphere. However, many forms of ground-based solar observations correlate well with solar irradiance variations, and this fact has been used to construct facular-sunspot models which can explain about 90% of the variance of total solar irradiance as observed by spacecraft radiometers. It is not yet clear whether remaining discrepancies are observational or require additional sources in the model. This paper is a selective review of the current status of the use of ground-based data to understand spacecraft observations of solar irradiance and to apply this understanding to periods before space-based measurements were available. New results from the extension of the histogram analysis of NASA/NSO spectromagnetograph observations (Jones et al., 2000, ApJ529, 1070) to the period from Nov. 1992 to Sep. 2000 are reported which confirm that strong mixed polarity magnetic regions (quiet network) are not significantly correlated with total solar irradiance and which show an unexplained linear trend in the residuals of a multiple regression.

  11. Compact-optical-correlator-based helmet tracking system

    NASA Astrophysics Data System (ADS)

    New, Nicholas J.; Wilkinson, Tim D.

    2001-03-01

    We present a high-speed compact Binary Phase Joint Transform Correlator system based on a single liquid crystal over silicon spatial light modulator. The system is capable of processing images of 320*120 pixel resolution at frame rates currently limited to around 40 frames per second by the choice of camera within the system. The system is presented in the context of an image comparator system in a fighter aircraft cockpit, which is used to track the view of the pilot. This is achieved by using a helmet-mounted camera to provide the input scenes and some of the inherent properties of the Joint Transform Correlator. Results from an experimental prototype are presented.

  12. Quantum Image Encryption Algorithm Based on Image Correlation Decomposition

    NASA Astrophysics Data System (ADS)

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

    2015-02-01

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

  13. Optimization of integer wavelet transforms based on difference correlation structures.

    PubMed

    Li, Hongliang; Liu, Guizhong; Zhang, Zhongwei

    2005-11-01

    In this paper, a novel lifting integer wavelet transform based on difference correlation structure (DCCS-LIWT) is proposed. First, we establish a relationship between the performance of a linear predictor and the difference correlations of an image. The obtained results provide a theoretical foundation for the following construction of the optimal lifting filters. Then, the optimal prediction lifting coefficients in the sense of least-square prediction error are derived. DCCS-LIWT puts heavy emphasis on image inherent dependence. A distinct feature of this method is the use of the variance-normalized autocorrelation function of the difference image to construct a linear predictor and adapt the predictor to varying image sources. The proposed scheme also allows respective calculations of the lifting filters for the horizontal and vertical orientations. Experimental evaluation shows that the proposed method produces better results than the other well-known integer transforms for the lossless image compression.

  14. CuBIC: cumulant based inference of higher-order correlations in massively parallel spike trains

    PubMed Central

    Rotter, Stefan; Grün, Sonja

    2009-01-01

    Recent developments in electrophysiological and optical recording techniques enable the simultaneous observation of large numbers of neurons. A meaningful interpretation of the resulting multivariate data, however, presents a serious challenge. In particular, the estimation of higher-order correlations that characterize the cooperative dynamics of groups of neurons is impeded by the combinatorial explosion of the parameter space. The resulting requirements with respect to sample size and recording time has rendered the detection of coordinated neuronal groups exceedingly difficult. Here we describe a novel approach to infer higher-order correlations in massively parallel spike trains that is less susceptible to these problems. Based on the superimposed activity of all recorded neurons, the cumulant-based inference of higher-order correlations (CuBIC) presented here exploits the fact that the absence of higher-order correlations imposes also strong constraints on correlations of lower order. Thus, estimates of only few lower-order cumulants suffice to infer higher-order correlations in the population. As a consequence, CuBIC is much better compatible with the constraints of in vivo recordings than previous approaches, which is shown by a systematic analysis of its parameter dependence. PMID:19862611

  15. Time-Based Indicators of Emotional Complexity: Interrelations and Correlates

    PubMed Central

    Grühn, Daniel; Lumley, Mark A.; Diehl, Manfred; Labouvie-Vief, Gisela

    2012-01-01

    Emotional complexity has been regarded as one correlate of adaptive emotion regulation in adulthood. One novel and potentially valuable approach to operationalizing emotional complexity is to use reports of emotions obtained repeatedly in real time, which can generate a number of potential time-based indicators of emotional complexity. It is not known, however, how these indicators relate to each other, to other measures of affective complexity, such as those derived from a cognitive-developmental view of emotional complexity, or to measures of adaptive functioning, such as well-being. A sample of 109 adults, aged 23 to 90 years, participated in an experience-sampling study and reported their negative and positive affect five times a day for one week. Based on these reports, we calculated nine different time-based indicators potentially reflecting emotional complexity. Analyses showed three major findings: First, the indicators showed a diverse pattern of interrelations suggestive of four distinct components of emotional complexity. Second, age was generally not related to time-based indicators of emotional complexity; however, older adults showed overall low variability in negative affect. Third, time-based indicators of emotional complexity were either unrelated or inversely related to measures of adaptive functioning; that is, these measures tended to predict a less adaptive profile, such as lower subjective and psychological well-being. In sum, time-based indicators of emotional complexity displayed a more complex and less beneficial picture than originally thought. In particular, variability in negative affect seems to indicate suboptimal adjustments. Future research would benefit from collecting empirical data for the interrelations and correlates of time-based indicators of emotional complexity in different contexts. PMID:23163712

  16. Mitochondrial correlation microscopy and nanolaser spectroscopy - new tools for biophotonic detection of cancer in single cells.

    PubMed

    Gourley, Paul L; Hendricks, Judy K; McDonald, Anthony E; Copeland, R Guild; Barrett, Keith E; Gourley, Cheryl R; Singh, Keshav K; Naviaux, Robert K

    2005-12-01

    Currently, pathologists rely on labor-intensive microscopic examination of tumor cells using century-old staining methods that can give false readings. Emerging BioMicroNano-technologies have the potential to provide accurate, realtime, high-throughput screening of tumor cells without the need for time-consuming sample preparation. These rapid, nano-optical techniques may play an important role in advancing early detection, diagnosis, and treatment of disease. In this report, we show that laser scanning confocal microscopy can be used to identify a previously unknown property of certain cancer cells that distinguishes them, with single-cell resolution, from closely related normal cells. This property is the correlation of light scattering and the spatial organization of mitochondria. In normal liver cells, mitochondria are highly organized within the cytoplasm and highly scattering, yielding a highly correlated signal. In cancer cells, mitochondria are more chaotically organized and poorly scattering. These differences correlate with important bioenergetic disturbances that are hallmarks of many types of cancer. In addition, we review recent work that exploits the new technology of nanolaser spectroscopy using the biocavity laser to characterize the unique spectral signatures of normal and transformed cells. These optical methods represent powerful new tools that hold promise for detecting cancer at an early stage and may help to limit delays in diagnosis and treatment.

  17. 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

  18. 3D shape measurement with phase correlation based fringe projection

    NASA Astrophysics Data System (ADS)

    Kühmstedt, Peter; Munckelt, Christoph; Heinze, Matthias; Bräuer-Burchardt, Christian; Notni, Gunther

    2007-06-01

    Here we propose a method for 3D shape measurement by means of phase correlation based fringe projection in a stereo arrangement. The novelty in the approach is characterized by following features. Correlation between phase values of the images of two cameras is used for the co-ordinate calculation. This work stands in contrast to the sole usage of phase values (phasogrammetry) or classical triangulation (phase values and image co-ordinates - camera raster values) for the determination of the co-ordinates. The method's main advantage is the insensitivity of the 3D-coordinates from the absolute phase values. Thus it prevents errors in the determination of the co-ordinates and improves robustness in areas with interreflections artefacts and inhomogeneous regions of intensity. A technical advantage is the fact that the accuracy of the 3D co-ordinates does not depend on the projection resolution. Thus the achievable quality of the 3D co-ordinates can be selectively improved by the use of high quality camera lenses and can participate in improvements in modern camera technologies. The presented new solution of the stereo based fringe projection with phase correlation makes a flexible, errortolerant realization of measuring systems within different applications like quality control, rapid prototyping, design and CAD/CAM possible. In the paper the phase correlation method will be described in detail. Furthermore, different realizations will be shown, i.e. a mobile system for the measurement of large objects and an endoscopic like system for CAD/CAM in dental industry.

  19. 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

  20. Oil spill detection in ocean environment via ultrasonic imaging and spectral fringe-adjusted joint transform correlation

    NASA Astrophysics Data System (ADS)

    Chowdhury, Nizam U.; Sakla, Adel A.; Alam, Mohammad S.

    2013-08-01

    A novel technique for oil spill detection in an ocean environment from ultrasonic hyperspectral imagery (UHI) using spectral fringe-adjusted joint transform correlation (SFJTC) is presented. Since UHI is a new concept and such data are not available, for this work an UHI dataset is created from pure target (oil) and background (sea water) signatures using a linear mixing model. A new SFJTC-based technique for oil spill detection in ocean environment has been developed and tested by using the UHI dataset. To evaluate the performance of the proposed technique, we used the receiver operating characteristics (ROC) curves and the area under the ROC. Test results confirm that the proposed technique shows excellent results even in the presence of a large amount of noise in the UHI data.

  1. Detection of non-uniform multi-body motion in image time-series using saccades-enhanced phase correlation

    NASA Astrophysics Data System (ADS)

    Gladilin, Evgeny; Eils, Roland

    2009-02-01

    Unsupervised analysis of time-series of live-cell images is one of the important tools of quantitative biology. Due to permanent cell motility or displacements of subcellular structures, microscopic images exhibit intrinsic non-uniform motion. In this article, we present a novel approach for detection of non-uniform multi-body motion which is based on combination of the Fourier-phase correlation with iterative probing target and background image regions similar to the strategy known from saccadic eye movements. We derive theoretical expressions that yield plausible explanation why this strategy turns out to be advantageous for tracking particular image pattern. Our experiments with synthetic and live-cell images demonstrate that the proposed approach is capable of accurately detecting non-uniform motion in synthetic and live-cell images.

  2. 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

  3. 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.

  4. Direct identification of base-paired RNA nucleotides by correlated chemical probing.

    PubMed

    Krokhotin, Andrey; Mustoe, Anthony M; Weeks, Kevin M; Dokholyan, Nikolay V

    2017-01-01

    Many RNA molecules fold into complex secondary and tertiary structures that play critical roles in biological function. Among the best-established methods for examining RNA structure are chemical probing experiments, which can report on local nucleotide structure in a concise and extensible manner. While probing data are highly useful for inferring overall RNA secondary structure, these data do not directly measure through-space base-pairing interactions. We recently introduced an approach for single-molecule correlated chemical probing with dimethyl sulfate (DMS) that measures RNA interaction groups by mutational profiling (RING-MaP). RING-MaP experiments reveal diverse through-space interactions corresponding to both secondary and tertiary structure. Here we develop a framework for using RING-MaP data to directly and robustly identify canonical base pairs in RNA. When applied to three representative RNAs, this framework identified 20%-50% of accepted base pairs with a <10% false discovery rate, allowing detection of 88% of duplexes containing four or more base pairs, including pseudoknotted pairs. We further show that base pairs determined from RING-MaP analysis significantly improve secondary structure modeling. RING-MaP-based correlated chemical probing represents a direct, experimentally concise, and accurate approach for detection of individual base pairs and helices and should greatly facilitate structure modeling for complex RNAs. © 2016 Krokhotin et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

  5. The Neural Correlates of Similarity- and Rule-based Generalization.

    PubMed

    Milton, Fraser; Bealing, Pippa; Carpenter, Kathryn L; Bennattayallah, Abdelmalek; Wills, Andy J

    2017-01-01

    The idea that there are multiple learning systems has become increasingly influential in recent years, with many studies providing evidence that there is both a quick, similarity-based or feature-based system and a more effortful rule-based system. A smaller number of imaging studies have also examined whether neurally dissociable learning systems are detectable. We further investigate this by employing for the first time in an imaging study a combined positive and negative patterning procedure originally developed by Shanks and Darby [Shanks, D. R., & Darby, R. J. Feature- and rule-based generalization in human associative learning. Journal of Experimental Psychology: Animal Behavior Processes, 24, 405-415, 1998]. Unlike previous related studies employing other procedures, rule generalization in the Shanks-Darby task is beyond any simple non-rule-based (e.g., associative) account. We found that rule- and similarity-based generalization evoked common activation in diverse regions including the pFC and the bilateral parietal and occipital lobes indicating that both strategies likely share a range of common processes. No differences between strategies were identified in whole-brain comparisons, but exploratory analyses indicated that rule-based generalization led to greater activation in the right middle frontal cortex than similarity-based generalization. Conversely, the similarity group activated the anterior medial frontal lobe and right inferior parietal lobes more than the rule group did. The implications of these results are discussed.

  6. The correlation-based law of effect1

    PubMed Central

    Baum, William M.

    1973-01-01

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

  7. Matrix-based concordance correlation coefficient for repeated measures.

    PubMed

    Hiriote, Sasiprapa; Chinchilli, Vernon M

    2011-09-01

    In many clinical studies, Lin's concordance correlation coefficient (CCC) is a common tool to assess the agreement of a continuous response measured by two raters or methods. However, the need for measures of agreement may arise for more complex situations, such as when the responses are measured on more than one occasion by each rater or method. In this work, we propose a new CCC in the presence of repeated measurements, called the matrix-based concordance correlation coefficient (MCCC) based on a matrix norm that possesses the properties needed to characterize the level of agreement between two p× 1 vectors of random variables. It can be shown that the MCCC reduces to Lin's CCC when p= 1. For inference, we propose an estimator for the MCCC based on U-statistics. Furthermore, we derive the asymptotic distribution of the estimator of the MCCC, which is proven to be normal. The simulation studies confirm that overall in terms of accuracy, precision, and coverage probability, the estimator of the MCCC works very well in general cases especially when n is greater than 40. Finally, we use real data from an Asthma Clinical Research Network (ACRN) study and the Penn State Young Women's Health Study for demonstration.

  8. Correlation-based imaging technique for fatigue monitoring of riveted lap-joint structure

    NASA Astrophysics Data System (ADS)

    Quaegebeur, N.; Ostiguy, P. C.; Masson, P.

    2014-05-01

    In the present study, a correlation-based imaging technique called Excitelet is assessed to monitor fatigue crack propagation in a riveted aluminum lap-joint, representative of an aircraft component. For this purpose, a micro-machined piezoceramic array is used to generate guided waves into the structure and measure the reflections induced by potential damage. The method uses a propagation model to correlate measured signals with a bank of signals and imaging is performed using a round-robin procedure (full-matrix capture). This allows taking into account the transducer dynamics and finite dimensions, multi-modal and dispersive characteristics of the guided wave propagation and complex interaction between with damage. Experimental validation has been conducted on an aluminum lap-joint instrumented with a compact linear piezoceramic array of 8 circular elements of 3 mm diameter each. The imaging technique is applied to detect crack propagation after fatigue cycling. Imaging results obtained using A0 mode at 300 and 450 kHz are presented for different crack sizes. It is demonstrated that crack detection and localization can be achieved, while the correlation level indicates the level of reflected energy, and thus damage severity. An accuracy below 5 mm on damage location can be achieved, demonstrating the potential of the correlation-based imaging technique for damage monitoring of complex aerospace structures.

  9. 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).''

  10. 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.

  11. Smell Detection Agent Based Optimization Algorithm

    NASA Astrophysics Data System (ADS)

    Vinod Chandra, S. S.

    2016-09-01

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

  12. 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.

  13. Aptamer Based Microsphere Biosensor for Thrombin Detection

    PubMed Central

    Zhu, Hongying; Suter, Jonathan D.; White, Ian M.; Fan, Xudong

    2006-01-01

    We have developed an optical microsphere resonator biosensor using aptamer as receptor for the measurement of the important biomolecule thrombin. The sphere surface is modified with anti-thrombin aptamer, which has excellent binding affinity and selectivity for thrombin. Binding of the thrombin at the sphere surface is monitored by the spectral position of the microsphere's whispering gallery mode resonances. A detection limit on the order of 1 NIH Unit/mL is demonstrated. Control experiments with non-aptamer oligonucleotide and BSA are also carried out to confirm the specific binding between aptamer and thrombin. We expect that this demonstration will lead to the development of highly sensitive biomarker sensors based on aptamer with lower cost and higher throughput than current technology.

  14. Controlling and detecting spin correlations of ultracold atoms in optical lattices.

    PubMed

    Trotzky, Stefan; Chen, Yu-Ao; Schnorrberger, Ute; Cheinet, Patrick; Bloch, Immanuel

    2010-12-31

    We report on the controlled creation of a valence bond state of delocalized effective-spin singlet and triplet dimers by means of a bichromatic optical superlattice. We demonstrate a coherent coupling between the singlet and triplet states and show how the superlattice can be employed to measure the singlet-fraction employing a spin-blockade effect. Our method provides a reliable way to detect and control nearest-neighbor spin correlations in many-body systems of ultracold atoms. Being able to measure these correlations is an important ingredient in studying quantum magnetism in optical lattices. We furthermore employ a SWAP operation between atoms which are part of different triplets, thus effectively increasing their bond-length. Such a SWAP operation provides an important step towards the massively parallel creation of a multiparticle entangled state in the lattice.

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

    NASA Astrophysics Data System (ADS)

    Sun, W.; Fu, L.

    2012-12-01

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

  16. Rapid and Robust Cross-Correlation-Based Seismic Signal Identification Using an Approximate Nearest Neighbor Method

    DOE PAGES

    Tibi, Rigobert; Young, Christopher; Gonzales, Antonio; ...

    2017-07-04

    The matched filtering technique that uses the cross correlation of a waveform of interest with archived signals from a template library has proven to be a powerful tool for detecting events in regions with repeating seismicity. However, waveform correlation is computationally expensive and therefore impractical for large template sets unless dedicated distributed computing hardware and software are used. In this paper, we introduce an approximate nearest neighbor (ANN) approach that enables the use of very large template libraries for waveform correlation. Our method begins with a projection into a reduced dimensionality space, based on correlation with a randomized subset ofmore » the full template archive. Searching for a specified number of nearest neighbors for a query waveform is accomplished by iteratively comparing it with the neighbors of its immediate neighbors. We used the approach to search for matches to each of ~2300 analyst-reviewed signal detections reported in May 2010 for the International Monitoring System station MKAR. The template library in this case consists of a data set of more than 200,000 analyst-reviewed signal detections for the same station from February 2002 to July 2016 (excluding May 2010). Of these signal detections, 73% are teleseismic first P and 17% regional phases (Pn, Pg, Sn, and Lg). Finally, the analyses performed on a standard desktop computer show that the proposed ANN approach performs a search of the large template libraries about 25 times faster than the standard full linear search and achieves recall rates greater than 80%, with the recall rate increasing for higher correlation thresholds.« less

  17. Phase-image-correlation-based high sensitive optical nanoscope

    NASA Astrophysics Data System (ADS)

    Kim, Daesuk; Baek, Byung Joon; Zvyagin, Andrei V.; Lee, Hyungchul; Cho, Yong Jai

    2010-12-01

    We describe a novel real time optical 3D nanoscope scheme that can be applied for both metrology and inspection in various semiconductor fields. Since the proposed off-axis scheme based on a matched filter correlation method basically measure the phase information of a nano object, the proposed scheme has some benefits in terms of sensitivity in both 3D geometry measurement and defect inspection capability. In this study, the feasibility of the proposed scheme has been evaluated by combining the conical diffraction and wave propagation simulation codes.

  18. A calculable and correlation-based magnetic field fluctuation thermometer

    NASA Astrophysics Data System (ADS)

    Kirste, A.; Regin, M.; Engert, J.; Drung, D.; Schurig, T.

    2014-12-01

    We have developed a new Magnetic Field Fluctuation Thermometer (MFFT) specifically designed for operation in primary mode, which requires the determination of the relation between thermal flux noise density and thermodynamic temperature. The noise thermometer combines a correlation-based SQUID readout and an integrated conductivity measurement on the metallic temperature sensor with an in situ flux calibration. The operation of the MFFT is modelled theoretically. First temperature measurements in secondary mode between 9 mK and 4.2 K showed excellent agreement with a copy of the PLTS-2000 within 0.5%.

  19. Correlations in infrared spectra of nanostructures based on mixed oxides

    NASA Astrophysics Data System (ADS)

    Averin, I. A.; Karmanov, A. A.; Moshnikov, V. A.; Pronin, I. A.; Igoshina, S. E.; Sigaev, A. P.; Terukov, E. I.

    2015-12-01

    This paper has presented experimental data on the infrared spectroscopic investigation of nanostructures based on mixed oxides. Nanostructures in the form of porous thin films deposited on oxidized single- crystal silicon substrates have been synthesized by the sol-gel method. The qualitative composition of film-forming sols and the related nanostructures has been examined. Correlations relating the coefficient of transmission of infrared radiation through the materials under investigation and their quantitative composition have been established. The processes occurring during the annealing of the nanostructures in the temperature range from 100 to 600°C have been analyzed.

  20. Path integral based calculations of symmetrized time correlation functions. II.

    PubMed

    Bonella, S; Monteferrante, M; Pierleoni, C; Ciccotti, G

    2010-10-28

    Schofield's form of quantum time correlation functions is used as the starting point to derive a computable expression for these quantities. The time composition property of the propagators in complex time is exploited to approximate Schofield's function in terms of a sequence of short time classical propagations interspersed with path integrals that, combined, represent the thermal density of the system. The approximation amounts to linearization of the real time propagators and it becomes exact with increasing number of propagation legs. Within this scheme, the correlation function is interpreted as an expectation value over a probability density defined on the thermal and real path space and calculated by a Monte Carlo algorithm. The performance of the algorithm is tested on a set of benchmark problems. Although the numerical effort required is considerable, we show that the algorithm converges systematically to the exact answer with increasing number of iterations and that it is stable for times longer than those accessible via a brute force, path integral based, calculation of the correlation function. Scaling of the algorithm with dimensionality is also examined and, when the method is combined with commonly used filtering schemes, found to be comparable to that of alternative semiclassical methods.

  1. Detecting suspicious behaviour using speech: acoustic correlates of deceptive speech -- an exploratory investigation.

    PubMed

    Kirchhübel, Christin; Howard, David M

    2013-09-01

    The current work intended to enhance our knowledge of changes or lack of changes in the speech signal when people were being deceptive. In particular, the study attempted to investigate the appropriateness of using speech cues in detecting deception. Truthful, deceptive and control speech were elicited from ten speakers in an interview setting. The data were subjected to acoustic analysis and results are presented on a range of speech parameters including fundamental frequency (f0), overall amplitude and mean vowel formants F1, F2 and F3. A significant correlation could not be established between deceptiveness/truthfulness and any of the acoustic features examined. Directions for future work are highlighted.

  2. Detection of Target ssDNA Using a Microfabricated Hall Magnetometer with Correlated Optical Readout

    PubMed Central

    Hira, Steven M.; Aledealat, Khaled; Chen, Kan-Sheng; Field, Mark; Sullivan, Gerard J.; Chase, P. Bryant; Xiong, Peng; von Molnár, Stephan; Strouse, Geoffrey F.

    2012-01-01

    Sensing biological agents at the genomic level, while enhancing the response time for biodetection over commonly used, optics-based techniques such as nucleic acid microarrays or enzyme-linked immunosorbent assays (ELISAs), is an important criterion for new biosensors. Here, we describe the successful detection of a 35-base, single-strand nucleic acid target by Hall-based magnetic transduction as a mimic for pathogenic DNA target detection. The detection platform has low background, large signal amplification following target binding and can discriminate a single, 350 nm superparamagnetic bead labeled with DNA. Detection of the target sequence was demonstrated at 364 pM (<2 target DNA strands per bead) target DNA in the presence of 36 μM nontarget (noncomplementary) DNA (<10 ppm target DNA) using optical microscopy detection on a GaAs Hall mimic. The use of Hall magnetometers as magnetic transduction biosensors holds promise for multiplexing applications that can greatly improve point-of-care (POC) diagnostics and subsequent medical care. PMID:22496610

  3. A method for detection of abrupt changes in the financial market combining wavelet decomposition and correlation graphs

    NASA Astrophysics Data System (ADS)

    Caetano, Marco Antonio Leonel; Yoneyama, Takashi

    2012-10-01

    The objective of this work is to propose a new methodology to detect the imminence of abrupt changes in the stock market by combining a numerical indicator based on the wavelet decomposition technique with a measure of the interdependency of the markets using graph theory. While the indicator based on wavelet decomposition is based on a single time series, an approach based on network representation can provide information on the interdependency of the various markets. More specifically, the stock market indices are associated with nodes of a network and the correlation between pairs of nodes with links. Results from the theory of graphs can then be used to indicate numerically the connectivity of this network. Experimentations with a variety of financial time series shows that the connectivity varies as trends of the financial time series varies. Combining the indicator based on the wavelet decomposition with the proposed measure of the connectivity of the network, it was possible to refine the authors previous results in terms of detecting abrupt changes in the stock market. In order to illustrate the methodology a case study involving twelve stock market indices was presented.

  4. Value of a complete sonographic survey in detecting fetal abnormalities: correlation with perinatal autopsy.

    PubMed

    Yeo, Lami; Guzman, Edwin R; Shen-Schwarz, Susan; Walters, Christine; Vintzileos, Anthony M

    2002-05-01

    To determine the sensitivity of using a complete anatomic sonographic survey in detecting fetal abnormalities via correlation with perinatal autopsy results. All perinatal autopsies (1994-2001) with positive findings for at least 1 fetal abnormality and performed by a single perinatal pathologist at our institution were retrospectively reviewed. From these cases, singleton fetuses who received prenatal sonography solely in our unit were identified. The sensitivity of sonography in detecting anomalous fetuses as well as fetal abnormalities and abnormalities by organ system was determined. Abnormalities were classified as major or minor In addition, findings from sonography and autopsy were compared, and their correlation was assigned to 1 of 3 categories. Of 88 fetuses identified, 85 had 1 or more abnormal structural sonographic findings (sensitivity for fetuses with anomalies, 97%). A total of 372 separate abnormalities were found on autopsy; of the 299 major and 73 minor abnormalities, prenatal sonography showed 224 (75%) and 13 (18%), respectively. There was either complete agreement or only minor differences between sonographic and autopsy findings in 57 (65%) of 88. The sensitivity of sonography in identifying abnormalities was greater than 70% in these systems: central nervous system, cardiac system, urinary system, extremities, genitalia, ribs, and hydrops. In experienced hands, sonography has 97% sensitivity in detecting anomalous fetuses when compared with perinatal autopsy results. Although the sensitivity of sonography in detecting major fetal abnormalities is 75%, the sensitivity for minor abnormalities is poor, even when using a complete anatomic sonographic survey. Although it has limitations, this type of survey is invaluable for both patients and physicians in diagnosing fetal abnormalities.

  5. A Correlation-Based Joint CFAR Detector Using Adaptively-Truncated Statistics in SAR Imagery

    PubMed Central

    Ai, Jiaqiu; Yang, Xuezhi; Zhou, Fang; Dong, Zhangyu; Jia, Lu; Yan, He

    2017-01-01

    Traditional constant false alarm rate (CFAR) detectors only use the contrast information between ship targets and clutter, and they suffer probability of detection (PD) degradation in multiple target situations. This paper proposes a correlation-based joint CFAR detector using adaptively-truncated statistics (hereafter called TS-2DLNCFAR) in SAR images. The proposed joint CFAR detector exploits the gray intensity correlation characteristics by building a two-dimensional (2D) joint log-normal model as the joint distribution (JPDF) of the clutter, so joint CFAR detection is realized. Inspired by the CFAR detection methodology, we design an adaptive threshold-based clutter truncation method to eliminate the high-intensity outliers, such as interfering ship targets, side-lobes, and ghosts in the background window, whereas the real clutter samples are preserved to the largest degree. A 2D joint log-normal model is accurately built using the adaptively-truncated clutter through simple parameter estimation, so the joint CFAR detection performance is greatly improved. Compared with traditional CFAR detectors, the proposed TS-2DLNCFAR detector achieves a high PD and a low false alarm rate (FAR) in multiple target situations. The superiority of the proposed TS-2DLNCFAR detector is validated on the multi-look Envisat-ASAR and TerraSAR-X data. PMID:28346395

  6. A Correlation-Based Joint CFAR Detector Using Adaptively-Truncated Statistics in SAR Imagery.

    PubMed

    Ai, Jiaqiu; Yang, Xuezhi; Zhou, Fang; Dong, Zhangyu; Jia, Lu; Yan, He

    2017-03-27

    Traditional constant false alarm rate (CFAR) detectors only use the contrast information between ship targets and clutter, and they suffer probability of detection (PD) degradation in multiple target situations. This paper proposes a correlation-based joint CFAR detector using adaptively-truncated statistics (hereafter called TS-2DLNCFAR) in SAR images. The proposed joint CFAR detector exploits the gray intensity correlation characteristics by building a two-dimensional (2D) joint log-normal model as the joint distribution (JPDF) of the clutter, so joint CFAR detection is realized. Inspired by the CFAR detection methodology, we design an adaptive threshold-based clutter truncation method to eliminate the high-intensity outliers, such as interfering ship targets, side-lobes, and ghosts in the background window, whereas the real clutter samples are preserved to the largest degree. A 2D joint log-normal model is accurately built using the adaptively-truncated clutter through simple parameter estimation, so the joint CFAR detection performance is greatly improved. Compared with traditional CFAR detectors, the proposed TS-2DLNCFAR detector achieves a high PD and a low false alarm rate (FAR) in multiple target situations. The superiority of the proposed TS-2DLNCFAR detector is validated on the multi-look Envisat-ASAR and TerraSAR-X data.

  7. Detection of the Wenchuan aftershock sequence using waveform correlation with a composite regional network

    SciTech Connect

    Slinkard, Megan; Heck, Stephen; Schaff, David; Bonal, Nedra; Daily, David; Young, Christopher; Richards, Paul

    2016-06-28

    Using template waveforms from aftershocks of the Wenchuan earthquake (12 May 2008, Ms 8.0) listed in a global bulletin and continuous data from eight regional stations, we detected more than 6000 additional events in the mainshock source region from 1 May to 12 August 2008. These new detections obey Omori’s law, extend the magnitude of completeness downward by 1.1 magnitude units, and lead to a more than fivefold increase in number of known aftershocks compared with the global bulletins published by the International Data Centre and the Inter national Seismological Centre. Moreover, we detected more M > 2 events than were listed by the Sichuan Seismograph Network. Several clusters of these detections were then relocated using the double-difference method, yielding locations that reduced travel-time residuals by a factor of 32 compared with the initial bulletin locations. Finally, our results suggest that using waveform correlation on a few regional stations can find aftershock events very effectively and locate them with precision.

  8. Detection of the Wenchuan aftershock sequence using waveform correlation with a composite regional network

    DOE PAGES

    Slinkard, Megan; Heck, Stephen; Schaff, David; ...

    2016-06-28

    Using template waveforms from aftershocks of the Wenchuan earthquake (12 May 2008, Ms 8.0) listed in a global bulletin and continuous data from eight regional stations, we detected more than 6000 additional events in the mainshock source region from 1 May to 12 August 2008. These new detections obey Omori’s law, extend the magnitude of completeness downward by 1.1 magnitude units, and lead to a more than fivefold increase in number of known aftershocks compared with the global bulletins published by the International Data Centre and the Inter national Seismological Centre. Moreover, we detected more M > 2 events thanmore » were listed by the Sichuan Seismograph Network. Several clusters of these detections were then relocated using the double-difference method, yielding locations that reduced travel-time residuals by a factor of 32 compared with the initial bulletin locations. Finally, our results suggest that using waveform correlation on a few regional stations can find aftershock events very effectively and locate them with precision.« less

  9. Age mitigates the correlation between cognitive processing speed and audio-visual asynchrony detection in speech.

    PubMed

    Alm, Magnus; Behne, Dawn

    2014-11-01

    Cognitive processing speed, hearing acuity, and audio-visual (AV) experience have been suggested to influence AV asynchrony detection. Whereas the influence of hearing acuity and AV experience have been explored to some extent, the influence of cognitive processing speed on perceived AV asynchrony has not been directly tested. Therefore, the current study investigates the relationship between cognitive processing speed and AV asynchrony detection in speech and, with hearing acuity controlled, assesses whether age-related AV experience mitigates the strength of this relationship. The cognitive processing speed and AV asynchrony detection by 20 young adults (20-30 years) and 20 middle-aged adults (50-60 years) were measured using auditory, visual and AV recognition reaction time tasks, and an AV synchrony judgment task. Strong correlations between audio, visual, and AV reaction times and AV synchrony window size were found for young adults, but not for middle-aged adults. These findings suggest that although cognitive processing speed influences AV asynchrony detection in speech, the strength of the relationship is seemingly reduced by AV experience.

  10. Detection of the Wenchuan aftershock sequence using waveform correlation with a composite regional network

    SciTech Connect

    Slinkard, Megan; Heck, Stephen; Schaff, David; Bonal, Nedra; Daily, David; Young, Christopher; Richards, Paul

    2016-06-28

    Using template waveforms from aftershocks of the Wenchuan earthquake (12 May 2008, Ms 8.0) listed in a global bulletin and continuous data from eight regional stations, we detected more than 6000 additional events in the mainshock source region from 1 May to 12 August 2008. These new detections obey Omori’s law, extend the magnitude of completeness downward by 1.1 magnitude units, and lead to a more than fivefold increase in number of known aftershocks compared with the global bulletins published by the International Data Centre and the Inter national Seismological Centre. Moreover, we detected more M > 2 events than were listed by the Sichuan Seismograph Network. Several clusters of these detections were then relocated using the double-difference method, yielding locations that reduced travel-time residuals by a factor of 32 compared with the initial bulletin locations. Finally, our results suggest that using waveform correlation on a few regional stations can find aftershock events very effectively and locate them with precision.

  11. 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.

  12. Libman-Sacks Endocarditis: Detection, Characterization, and Clinical Correlates by Three-Dimensional Transesophageal Echocardiography.

    PubMed

    Roldan, Carlos A; Tolstrup, Kirsten; Macias, Leonardo; Qualls, Clifford R; Maynard, Diana; Charlton, Gerald; Sibbitt, Wilmer L

    2015-07-01

    Libman-Sacks endocarditis, characterized by Libman-Sacks vegetations, is common in patients with systemic lupus erythematosus and is commonly complicated with embolic cerebrovascular disease. Thus, accurate detection of Libman-Sacks vegetations may lead to early therapy and prevention of their associated complications. Although two-dimensional (2D) transesophageal echocardiography (TEE) has high diagnostic value for detection of Libman-Sacks vegetations, three-dimensional (3D) TEE may allow improved detection, characterization, and clinical correlations of Libman-Sacks vegetations. Twenty-nine patients with systemic lupus erythematosus (27 women; mean age, 34 ± 12 years) prospectively underwent 40 paired 3D and 2D transesophageal echocardiographic studies and assessment of cerebrovascular disease manifested as acute clinical neurologic syndromes, neurocognitive dysfunction, or focal brain injury on magnetic resonance imaging. Initial and repeat studies in patients were intermixed in a blinded manner with paired studies from healthy controls, deidentified, coded, and independently interpreted by experienced observers unaware of patients' clinical and imaging data. The results of 3D TEE compared with 2D TEE were more often positive for mitral or aortic valve vegetations, and 3D TEE detected more vegetations per study and determined larger sizes of vegetations (P ≤ .03 for all). Also, 3D TEE detected more vegetations on the anterior mitral leaflet, anterolateral and posteromedial scallops, and ventricular side or both atrial and ventricular sides of the leaflets (P < .05 for all). In addition, 3D TEE detected more vegetations on the aortic valve left and noncoronary cusps, coronary cusps' tips and margins, and aortic side or both aortic and ventricular sides of the cusps (P ≤ .01 for all). Furthermore, 3D TEE more often detected associated mitral or aortic valve commissural fusion (P = .002). Finally, 3D TEE detected more vegetations in patients with

  13. Divisive Correlation Clustering Algorithm (DCCA) for grouping of genes: detecting varying patterns in expression profiles.

    PubMed

    Bhattacharya, Anindya; De, Rajat K

    2008-06-01

    Cluster analysis (of gene-expression data) is a useful tool for identifying biologically relevant groups of genes that show similar expression patterns under multiple experimental conditions. Various methods have been proposed for clustering gene-expression data. However most of these algorithms have several shortcomings for gene-expression data clustering. In the present article, we focus on several shortcomings of conventional clustering algorithms and propose a new one that is able to produce better clustering solution than that produced by some others. We present the Divisive Correlation Clustering Algorithm (DCCA) that is suitable for finding a group of genes having similar pattern of variation in their expression values. To detect clusters with high correlation and biological significance, we use the correlation clustering concept introduced by Bansal et al. Our proposed algorithm DCCA produces a clustering solution without taking number of clusters to be created as an input. DCCA uses the correlation matrix in such a way that all genes in a cluster have highest average correlation with genes in that cluster. To test the performance of the DCCA, we have applied DCCA and some well-known conventional methods to an artificial dataset, and nine gene-expression datasets, and compared the performance of the algorithms. The clustering results of the DCCA are found to be more significantly relevant to the biological annotations than those of the other methods. All these facts show the superiority of the DCCA over some others for the clustering of gene-expression data. The software has been developed using C and Visual Basic languages, and can be executed on the Microsoft Windows platforms. The software may be downloaded as a zip file from http://www.isical.ac.in/~rajat. Then it needs to be installed. Two word files (included in the zip file) need to be consulted before installation and execution of the software.

  14. 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

  15. Inter-lead correlation analysis for automated detection of cable reversals in 12/16-lead ECG.

    PubMed

    Jekova, Irena; Krasteva, Vessela; Leber, Remo; Schmid, Ramun; Twerenbold, Raphael; Müller, Christian; Reichlin, Tobias; Abächerli, Roger

    2016-10-01

    A crucial factor for proper electrocardiogram (ECG) interpretation is the correct electrode placement in standard 12-lead ECG and extended 16-lead ECG for accurate diagnosis of acute myocardial infarctions. In the context of optimal patient care, we present and evaluate a new method for automated detection of reversals in peripheral and precordial (standard, right and posterior) leads, based on simple rules with inter-lead correlation dependencies. The algorithm for analysis of cable reversals relies on scoring of inter-lead correlations estimated over 4s snapshots with time-coherent data from multiple ECG leads. Peripheral cable reversals are detected by assessment of nine correlation coefficients, comparing V6 to limb leads: (I, II, III, -I, -II, -III, -aVR, -aVL, -aVF). Precordial lead reversals are detected by analysis of the ECG pattern cross-correlation progression within lead sets (V1-V6), (V4R, V3R, V3, V4), and (V4, V5, V6, V8, V9). Disturbed progression identifies the swapped leads. A test-set, including 2239 ECGs from three independent sources-public 12-lead (PTB, CSE) and proprietary 16-lead (Basel University Hospital) databases-is used for algorithm validation, reporting specificity (Sp) and sensitivity (Se) as true negative and true positive detection of simulated lead swaps. Reversals of limb leads are detected with Se = 95.5-96.9% and 100% when right leg is involved in the reversal. Among all 15 possible pairwise reversals in standard precordial leads, adjacent lead reversals are detected with Se = 93.8% (V5-V6), 95.6% (V2-V3), 95.9% (V3-V4), 97.1% (V1-V2), and 97.8% (V4-V5), increasing to 97.8-99.8% for reversals of anatomically more distant electrodes. The pairwise reversals in the four extra precordial leads are detected with Se = 74.7% (right-sided V4R-V3R), 91.4% (posterior V8-V9), 93.7% (V4R-V9), and 97.7% (V4R-V8, V3R-V9, V3R-V8). Higher true negative rate is achieved with Sp > 99% (standard 12-lead ECG), 81.9% (V4R-V3R), 91

  16. Probabilistic fluorescence-based synapse detection.

    PubMed

    Simhal, Anish K; Aguerrebere, Cecilia; Collman, Forrest; Vogelstein, Joshua T; Micheva, Kristina D; Weinberg, Richard J; Smith, Stephen J; Sapiro, Guillermo

    2017-04-01

    Deeper exploration of the brain's vast synaptic networks will require new tools for high-throughput structural and molecular profiling of the diverse populations of synapses that compose those networks. Fluorescence microscopy (FM) and electron microscopy (EM) offer complementary advantages and disadvantages for single-synapse analysis. FM combines exquisite molecular discrimination capacities with high speed and low cost, but rigorous discrimination between synaptic and non-synaptic fluorescence signals is challenging. In contrast, EM remains the gold standard for reliable identification of a synapse, but offers only limited molecular discrimination and is slow and costly. To develop and test single-synapse image analysis methods, we have used datasets from conjugate array tomography (cAT), which provides voxel-conjugate FM and EM (annotated) images of the same individual synapses. We report a novel unsupervised probabilistic method for detection of synapses from multiplex FM (muxFM) image data, and evaluate this method both by comparison to EM gold standard annotated data and by examining its capacity to reproduce known important features of cortical synapse distributions. The proposed probabilistic model-based synapse detector accepts molecular-morphological synapse models as user queries, and delivers a volumetric map of the probability that each voxel represents part of a synapse. Taking human annotation of cAT EM data as ground truth, we show that our algorithm detects synapses from muxFM data alone as successfully as human annotators seeing only the muxFM data, and accurately reproduces known architectural features of cortical synapse distributions. This approach opens the door to data-driven discovery of new synapse types and their density. We suggest that our probabilistic synapse detector will also be useful for analysis of standard confocal and super-resolution FM images, where EM cross-validation is not practical.

  17. Probabilistic fluorescence-based synapse detection

    PubMed Central

    Aguerrebere, Cecilia; Collman, Forrest; Vogelstein, Joshua T.; Micheva, Kristina D.; Weinberg, Richard J.; Smith, Stephen J.; Sapiro, Guillermo

    2017-01-01

    Deeper exploration of the brain’s vast synaptic networks will require new tools for high-throughput structural and molecular profiling of the diverse populations of synapses that compose those networks. Fluorescence microscopy (FM) and electron microscopy (EM) offer complementary advantages and disadvantages for single-synapse analysis. FM combines exquisite molecular discrimination capacities with high speed and low cost, but rigorous discrimination between synaptic and non-synaptic fluorescence signals is challenging. In contrast, EM remains the gold standard for reliable identification of a synapse, but offers only limited molecular discrimination and is slow and costly. To develop and test single-synapse image analysis methods, we have used datasets from conjugate array tomography (cAT), which provides voxel-conjugate FM and EM (annotated) images of the same individual synapses. We report a novel unsupervised probabilistic method for detection of synapses from multiplex FM (muxFM) image data, and evaluate this method both by comparison to EM gold standard annotated data and by examining its capacity to reproduce known important features of cortical synapse distributions. The proposed probabilistic model-based synapse detector accepts molecular-morphological synapse models as user queries, and delivers a volumetric map of the probability that each voxel represents part of a synapse. Taking human annotation of cAT EM data as ground truth, we show that our algorithm detects synapses from muxFM data alone as successfully as human annotators seeing only the muxFM data, and accurately reproduces known architectural features of cortical synapse distributions. This approach opens the door to data-driven discovery of new synapse types and their density. We suggest that our probabilistic synapse detector will also be useful for analysis of standard confocal and super-resolution FM images, where EM cross-validation is not practical. PMID:28414801

  18. Correlation coefficient based supervised locally linear embedding for pulmonary nodule recognition.

    PubMed

    Wu, Panpan; Xia, Kewen; Yu, Hengyong

    2016-11-01

    Dimensionality reduction techniques are developed to suppress the negative effects of high dimensional feature space of lung CT images on classification performance in computer aided detection (CAD) systems for pulmonary nodule detection. An improved supervised locally linear embedding (SLLE) algorithm is proposed based on the concept of correlation coefficient. The Spearman's rank correlation coefficient is introduced to adjust the distance metric in the SLLE algorithm to ensure that more suitable neighborhood points could be identified, and thus to enhance the discriminating power of embedded data. The proposed Spearman's rank correlation coefficient based SLLE (SC(2)SLLE) is implemented and validated in our pilot CAD system using a clinical dataset collected from the publicly available lung image database consortium and image database resource initiative (LICD-IDRI). Particularly, a representative CAD system for solitary pulmonary nodule detection is designed and implemented. After a sequential medical image processing steps, 64 nodules and 140 non-nodules are extracted, and 34 representative features are calculated. The SC(2)SLLE, as well as SLLE and LLE algorithm, are applied to reduce the dimensionality. Several quantitative measurements are also used to evaluate and compare the performances. Using a 5-fold cross-validation methodology, the proposed algorithm achieves 87.65% accuracy, 79.23% sensitivity, 91.43% specificity, and 8.57% false positive rate, on average. Experimental results indicate that the proposed algorithm outperforms the original locally linear embedding and SLLE coupled with the support vector machine (SVM) classifier. Based on the preliminary results from a limited number of nodules in our dataset, this study demonstrates the great potential to improve the performance of a CAD system for nodule detection using the proposed SC(2)SLLE. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  19. Transient Directed Motions of GABAA Receptors in Growth Cones Detected by a Speed Correlation Index

    PubMed Central

    Bouzigues, Cédric; Dahan, Maxime

    2007-01-01

    Single-molecule tracking of membrane proteins has become an important tool for investigating dynamic processes in live cells, such as cell signaling, membrane compartmentation or trafficking. The extraction of relevant parameters, such as interaction times between molecular partners or confinement-zone sizes, from the trajectories of single molecules requires appropriate statistical methods. Here we report a new tool, the speed correlation index, designed to detect transient periods of directed motion within trajectories of diffusing molecules. The ability to detect such events in a wide range of biologically relevant parameter values (speed, diffusion coefficient, and durations of the directed period) was first established on simulated data. The method was next applied to analyze the trajectories of quantum-dot-labeled GABAA receptors in nerve growth cones. The use of the speed correlation index revealed that the receptors had a “conveyor belt” type of motion due to temporary interactions (∼4.0 s) between the receptors and the microtubules, leading to an average directed motion (velocity ∼0.3 μm s−1) in the growth-cone membrane. Our observations point to the possibility of a cytoskeleton-dependent redistribution of the sensing molecules in the membrane, which could play a role in the modulation of the cell response to external signals. PMID:17071660

  20. Detecting Differential and Correlated Protein Expression in Label-Free Shotgun Proteomics

    SciTech Connect

    Zhang, Bing; Verberkmoes, Nathan C; Langston, Michael A; Uberbacher, Edward C; Hettich, Robert {Bob} L; Samatova, Nagiza F

    2006-01-01

    Recent studies have revealed a relationship between protein abundance and sampling statistics, such as sequence coverage, peptide count, and spectral count, in label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS) shotgun proteomics. The use of sampling statistics offers a promising method of measuring relative protein abundance and detecting differentially expressed or coexpressed proteins. We performed a systematic analysis of various approaches to quantifying differential protein expression in eukaryotic Saccharomycescerevisiaeand prokaryotic Rhodopseudomonaspalustrislabel free LC-MS/MS data. First, we showed that, among three sampling statistics, the spectral count has the highest technical reproducibility, followed by the less-reproducible peptide count and relatively nonreproducible sequence coverage. Second, we used spectral count statistics to measure differential protein expression in pairwise experiments using five statistical tests: Fisher's exact test, G-test, AC test, t-test, and LPE test. Given the S.cerevisiaedata set with spiked proteins as a benchmark and the false positive rate as a metric, our evaluation suggested that the Fisher's exact test, G-test, and AC test can be used when the number of replications is limited (one or two), whereas the t-test is useful with three or more replicates available. Third, we generalized the G-test to increase the sensitivity of detecting differential protein expression under multiple experimental conditions. Out of 1622 identified R.palustris proteins in the LC-MS/MS experiment, the generalized G-test detected 1119 differentially expressed proteins under six growth conditions. Finally, we studied correlated expression of these 1119 proteins by analyzing pairwise expression correlations and by delineating protein clusters according to expression patterns. Through pairwise expression correlation analysis, we demonstrated that proteins co-located in the same operon were much more strongly coexpressed

  1. Laser-detected lateral muscle displacement is correlated with force fluctuations during voluntary contractions in humans.

    PubMed

    Yoshitake, Yasuhide; Masani, Kei; Shinohara, Minoru

    2008-08-30

    Fluctuations in muscle force during steady voluntary contractions result from the summation of twitch forces produced by asynchronous activation of multiple motor units. We hypothesized that oscillatory lateral muscle displacement, measured with a non-contact high-resolution laser displacement sensor, is correlated with force fluctuations during steady, voluntary contractions with a human muscle. Eight healthy young adults (20-33 yrs) performed steady isometric contractions with the first dorsal interosseus muscle. Contraction intensity ranged from 2.5% to 60% of the maximal voluntary contraction force. Oscillatory lateral displacement of the muscle surface was measured with a high-resolution laser displacement sensor (0.5 microm resolution), concurrently with abduction force of the index finger. In the time-domain analysis, there was a significant positive peak in the cross-correlation function between lateral muscle displacement and force fluctuations. In addition, the amplitude increased linearly with contraction intensity in both signals. In the frequency-domain analysis, frequency content was similar in both signals, and there was significant coherence between signals for the major frequency range of the signals (<5 Hz). In conclusion, laser-detected lateral displacement of a hand muscle is correlated with force fluctuations across a wide range of contraction intensity during steady voluntary contractions in humans.

  2. Correlation and comparison of magnetic and electric detection of small intestinal electrical activity.

    PubMed

    Bradshaw, L A; Allos, S H; Wikswo, J P; Richards, W O

    1997-05-01

    The small intestinal basic electrical rhythm (BER) was detected simultaneously with serosal electrodes and a transabdominal superconducting quantum interference device (SQUID) magnetometer in anesthetized rabbits. We induced mesenteric ischemia to correlate serosal electrode recording of changes in BER with the SQUID magnetometer. The BER frequency was obtained by spectral analysis of the data using Fourier and autoregressive techniques. There was a high degree of correlation (r = 0.96) between the BER frequency determined using the serosal electrodes and the BER frequency ascertained from SQUID data. Additionally, the effects of an electrical insulator on the external electric and magnetic fields were studied in the rabbit model. The presence of an insulator profoundly attenuates external electric potentials recorded by cutaneous electrodes but does not significantly affect external magnetic fields or serosal potentials. We conclude that SQUID magnetometers could noninvasively record small intestinal BER that was highly correlated with the activity recorded by invasive serosal electrodes. The advantages of magnetic field measurements have encouraged us to investigate clinical applications.

  3. 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.

  4. 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.

  5. Optical correlation recognition of infrared target based on wavelet multi-scale product

    NASA Astrophysics Data System (ADS)

    Chen, Fang-han; Wang, Wen-sheng

    2011-06-01

    As one of the most successful optical correlation recognizers, hybrid optoelectronic joint transform correlator (HOJTC) has received more and more attraction than the purely electronic way in the field of target detection and recognition. It primarily because that HOJTC has the advantages of optics as well as those of electronics. This kind of combination determines that the performance of HOJTC is closely related to optical configuration of system and digital image processing technology. For the stability of optical part, a lot of efforts concerning image processing methods have been made in recent years for improving the power of recognition of HOJTC. Edge contours play a decisive role in target detection. In order to obtain adequate contour feature of target, the solution of edge extraction based on wavelet multi-scale product is proposed. Normalized maximum and argument of each point could be defined utilizing wavelet coefficient of image. Both of them contain the relation of coefficient product between each scale. Edge points synthesized the information of multi-scale are extracted by searching local maxima along the direction of gradient. The way adopted fully exploited the character of multi-resolution of wavelet. Simulation experiments and optical experiments indicate that the energy of correlation peaks is obviously enhanced after the original image is processed by wavelet multi-scale product, and it successfully realizes detection and recognition of infrared target.

  6. 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.

  7. 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.

  8. HHT based cardiopulmonary coupling analysis for sleep apnea detection.

    PubMed

    Liu, Dongdong; Yang, Xiaochen; Wang, Guangfa; Ma, Jing; Liu, Yanhui; Peng, Chung-Kang; Zhang, Jue; Fang, Jing

    2012-05-01

    To validate the feasibility of the Hilbert-Huang transform (HHT) based cardiopulmonary coupling (CPC) technique in respiratory events detection and estimation of the severity of apnea/hypopnea. The HHT-CPC sleep spectrogram technique was applied to a total of 69 single-lead ECG signals downloaded from the Physionet Sleep Apnea Database. Sleep spectrograms generated by both the original and the improved CPC method were compared on the structure distribution and time-frequency resolution. The performance of respiratory events detection by using the power of low frequency coupling (pLFC) in the new method was estimated by receiver operating characteristic analysis. Furthermore, correlation between HHT-CPC index (temporal Variability of Dominant Frequency, TVDF) and conventional OSAHS scoring was computed. The HHT-CPC spectrum provides much finer temporal resolution and frequency resolution (8 s and 0.001 Hz) compared with the original CPC (8.5 min and 0.004 Hz). The area under the ROC curve of pLFC was 0.79 in distinguishing respiratory events from normal breathing. Significant differences were found in TVDF among groups with different severities of OSAHS (normal, mild, moderate, and severe, p<0.001). TVDF has a strong negative correlation with the apnea/hypopnea index (AHI, correlation coefficient -0.71). The HHT-CPC spectrum could exhibit more detailed temporal-frequency information about cardiopulmonary coupling during sleep. As two spectrographic markers, pLFC and TVDF can be used to identify respiratory events and represent the disruption extent of sleep architecture in patients with sleep apnea/hypopnea, respectively. The proposed technique might serve as a complementary approach to enhance diagnostic efforts. Copyright © 2012 Elsevier B.V. All rights reserved.

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

    PubMed

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

    2012-12-17

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

  10. Force measurement-based discontinuity detection during friction stir welding

    DOE PAGES

    Shrivastava, Amber; Zinn, Michael; Duffie, Neil A.; ...

    2017-02-23

    Here, the objective of this work is to develop a method for detecting the creation of discontinuities (i.e., voids, volume defects) during friction stir welding. Friction stir welding is inherently cost effective, however, the need for significant weld inspection can make the process cost prohibitive. A new approach to weld inspection is required in which an in situ characterization of weld quality can be obtained, reducing the need for postprocess inspection. To this end, friction stir welds with subsurface voids and without voids were created. The subsurface voids were generated by reducing the friction stir tool rotation frequency and increasingmore » the tool traverse speed in order to create “colder” welds. Process forces were measured during welding, and the void sizes were measured postprocess by computerized tomography (i.e., 3D X-ray imaging). Two parameters, based on frequency domain content and time-domain average of the force signals, were found to be correlated with void size. Criteria for subsurface void detection and size prediction were developed and shown to be in good agreement with experimental observations. Furthermore, with the proper choice of data acquisition system and frequency analyzer the occurrence of subsurface voids can be detected in real time.« less

  11. fREDUCE: Detection of degenerate regulatory elements using correlation with expression

    PubMed Central

    Wu, Randy Z; Chaivorapol, Christina; Zheng, Jiashun; Li, Hao; Liang, Shoudan

    2007-01-01

    Background The precision of transcriptional regulation is made possible by the specificity of physical interactions between transcription factors and their cognate binding sites on DNA. A major challenge is to decipher transcription factor binding sites from sequence and functional genomic data using computational means. While current methods can detect strong binding sites, they are less sensitive to degenerate motifs. Results We present fREDUCE, a computational method specialized for the detection of weak or degenerate binding motifs from gene expression or ChIP-chip data. fREDUCE is built upon the widely applied program REDUCE, which elicits motifs by global statistical correlation of motif counts with expression data. fREDUCE introduces several algorithmic refinements that allow efficient exhaustive searches of oligonucleotides with a specified number of degenerate IUPAC symbols. On yeast ChIP-chip benchmarks, fREDUCE correctly identified motifs and their degeneracies with accuracies greater than its predecessor REDUCE as well as other known motif-finding programs. We have also used fREDUCE to make novel motif predictions for transcription factors with poorly characterized binding sites. Conclusion We demonstrate that fREDUCE is a valuable tool for the prediction of degenerate transcription factor binding sites, especially from array datasets with weak signals that may elude other motif detection methods. PMID:17941998

  12. Information content in fluorescence correlation spectroscopy: binary mixtures and detection volume distortion.

    PubMed

    Lam, Jonathan D; Culbertson, Michael J; Skinner, Nathan P; Barton, Zachary J; Burden, Daniel L

    2011-07-01

    When properly implemented, fluorescence correlation spectroscopy (FCS) reveals numerous static and dynamic properties of molecules in solution. However, complications arise whenever the measurement scenario is complex. Specific limitations occur when the detection region does not match the ideal Gaussian geometry ubiquitously assumed by FCS theory, or when properties of multiple fluorescent species are assessed simultaneously. A simple binary solution of diffusers, where both mole fraction and diffusion constants are sought, can face interpretive difficulty. In order to better understand the limits of FCS, this study systematically explores the relationship between detection-volume distortion, diffusion constants, species mole fraction, and fitting methodology in analyses that utilize a two-component autocorrelation model. FCS measurements from solution mixtures of dye-labeled protein and free dye are compared to simulations, which predict the performance of FCS under a variety of experimental circumstances. The results reveal a range of conditions necessary for performing accurate measurements and describe experimental scenarios that should be avoided. The findings also provide guidelines for obtaining meaningful measurements when grossly distorted detection volumes are utilized and generally assess the latent information contained in FCS datasets.

  13. New Opportunities for Fracture Healing Detection: Impedance Spectroscopy Measurements Correlate to Tissue Composition in Fractures.

    PubMed

    Lin, Monica C; Yang, Frank; Herfat, Safa T; Bahney, Chelsea S; Marmor, Meir; Maharbiz, Michel M

    2017-04-06

    Accurate evaluation of fracture healing is important for clinical decisions on when to begin weight-bearing and when early intervention is necessary in cases of fracture nonunion. While the stages of healing involving hematoma, cartilage, trabecular bone, and cortical bone have been well characterized histologically, physicians typically track fracture healing by using subjective physical examinations and radiographic techniques that are only able to detect mineralized stages of bone healing. This exposes the need for a quantitative, reliable technique to monitor fracture healing, and particularly to track healing progression during the early stages of repair. The goal of this study was to validate the use of impedance spectroscopy to monitor fracture healing and perform comprehensive evaluation comparing measurements with histological evidence. Here we show that impedance spectroscopy not only can distinguish between cadaver tissues involved throughout fracture repair, but also correlates to fracture callus composition over the middle stages of healing in wild-type C57BL/6 mice. Specifically, impedance magnitude has a positive relationship with % trabecular bone and a negative relationship with % cartilage, and the opposite relationships are found when comparing phase angle to these same volume fractions of tissues. With this information, we can quantitatively evaluate how far a fracture has progressed through the healing stages. Our results demonstrate the feasibility of impedance spectroscopy for detection of fracture callus composition and reveals its potential as a method for early detection of bone healing and fracture nonunion. This article is protected by copyright. All rights reserved.

  14. Detection of pepsin in mouth swab: correlation with clinical gastroesophageal reflux in preterm infants.

    PubMed

    Farhath, Sabeena; He, Zhaoping; Saslow, Judy; Soundar, Sam; Amendolia, Barbara; Bhat, Vishwanath; Pyon, Kee; Stahl, Gary; Mehta, Dev; Aghai, Zubair H

    2013-05-01

    To study the relationship between pepsinogen/pepsin in a mouth swab and clinical gastroesophageal reflux (GER) in preterm infants. Preterm infants (birth weight ≤ 2000 g) on full enteral feeds were enrolled. Mouth swabs from cheek and below the tongue were collected one, two and three hours after feeding. An enzymatic assay with substrate fluorescein isothiocyanate-casein was used to detect pepsin A and C activities with further confirmation by western blot. Blinded investigators reviewed the infant's medical record to clinically diagnose GER. A total of 101 premature infants were enrolled. Pepsinogen/pepsin was detected in 45/101 (44.5%) infants in at least one sample. A clinical diagnosis of GER was made in 36/101 (35.6%) infants. Mouth swabs were positive in 26/36 (72%) infants with clinical GER and only 19/65 (29%) infants without GER (p < 0.001). Similarly, the levels of pepsinogen/pepsin A and C were higher in the mouth swabs of infants with clinical GER. The detection of pepsinogen/pepsin in a mouth swab correlates with clinical GER in premature infants.

  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. 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.

  17. 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.

  18. 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.

  19. 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

  20. 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

    2015-10-06

    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.

  1. Ground-Based Detection of Exoatmospheric Calcium

    NASA Astrophysics Data System (ADS)

    Rojo, Patricio M.; Astudillo-Defru, Nicola

    2014-11-01

    Data acquired with HDS@Subaru for HD209458b is re-analyzed. A new pipeline performs an automated search for the exoatmospheric presence of several elements without any a-priori assumptions on its existence or strength. We analyzed thousands of lines in the full spectral range of this optical echelle spectrograph using a robust method to correct for the telluric contamination. We recover previous detections of Sodium and Halpha, and present the first strong detection of Calcium in an Extrasolar Atmosphere as well as the tentative detection of other elements. The Calcium detection is in disagreement with theoretical thermal-equilibrium models.

  2. Structural neural correlates of multitasking: A voxel-based morphometry study.

    PubMed

    Zhang, Rui-Ting; Yang, Tian-Xiao; Wang, Yi; Sui, Yuxiu; Yao, Jingjing; Zhang, Chen-Yuan; Cheung, Eric F C; Chan, Raymond C K

    2016-12-01

    Multitasking refers to the ability to organize assorted tasks efficiently in a short period of time, which plays an important role in daily life. However, the structural neural correlates of multitasking performance remain unclear. The present study aimed at exploring the brain regions associated with multitasking performance using global correlation analysis. Twenty-six healthy participants first underwent structural brain scans and then performed the modified Six Element Test, which required participants to attempt six subtasks in 10 min while obeying a specific rule. Voxel-based morphometry of the whole brain was used to detect the structural correlates of multitasking ability. Grey matter volume of the anterior cingulate cortex (ACC) was positively correlated with the overall performance and time monitoring in multitasking. In addition, white matter volume of the anterior thalamic radiation (ATR) was also positively correlated with time monitoring during multitasking. Other related brain regions associated with multitasking included the superior frontal gyrus, the inferior occipital gyrus, the lingual gyrus, and the inferior longitudinal fasciculus. No significant correlation was found between grey matter volume of the prefrontal cortex (Brodmann Area 10) and multitasking performance. Using a global correlation analysis to examine various aspects of multitasking performance, this study provided new insights into the structural neural correlates of multitasking ability. In particular, the ACC was identified as an important brain region that played both a general and a specific time-monitoring role in multitasking, extending the role of the ACC from lesioned populations to healthy populations. The present findings also support the view that the ATR may influence multitasking performance by affecting time-monitoring abilities.

  3. Transient modeling and parameter identification based on wavelet and correlation filtering for rotating machine fault diagnosis

    NASA Astrophysics Data System (ADS)

    Wang, Shibin; Huang, Weiguo; Zhu, Z. K.

    2011-05-01

    At constant rotating speed, localized faults in rotating machine tend to result in periodic shocks and thus arouse periodic transients in the vibration signal. The transient feature analysis has always been a crucial problem for localized fault detection, and the key aim for transient feature analysis is to identify the model and its parameters (frequency, damping ratio and time index) of the transient, and the time interval, i.e. period, between transients. Based on wavelet and correlation filtering, a technique incorporating transient modeling and parameter identification is proposed for rotating machine fault feature detection. With the proposed method, both parameters of a single transient and the period between transients can be identified from the vibration signal, and localized faults can be detected based on the parameters, especially the period. First, a simulation signal is used to test the performance of the proposed method. Then the method is applied to the vibration signals of different types of bearings with localized faults in the outer race, the inner race and the rolling element, respectively, and all the results show that the period between transients, representing the localized fault characteristic, is successfully detected. The method is also utilized in gearbox fault diagnosis and the effectiveness is verified through identifying the parameters of the transient model and the period. Moreover, it can be drawn that for bearing fault detection, the single-side wavelet model is more suitable than double-side one, while the double-side model for gearbox fault detection. This research proposed an effective method of localized fault detection for rotating machine fault diagnosis through transient modeling and parameter detection.

  4. Correlation-based OTDR for in-service monitoring of 64-split TDM PON.

    PubMed

    Shim, H K; Cho, K Y; Takushima, Y; Chung, Y C

    2012-02-27

    We demonstrate that the correlation-based optical time domain reflectometer (OTDR) can be used for the in-service monitoring of the 64-split time-division-multiplexed passive optical network (TDM PON). To achieve this objective, we superimpose a pseudo noise (PN) sequence having a modulation depth of ~40% to the downstream signal and utilize it for the correlation detection. However, the use of such a large PN sequence can seriously deteriorate the performance of the downstream receiver. Thus, we apply 8B/10B encoding to the downstream signal, and then filter out the PN sequence at the downstream receiver by using a high-pass filter. As a result, the power penalty caused by the use of a large PN sequence is reduced to an acceptable level (<3 dB), while the dynamic range of this correlation-based OTDR is increased to ~30 dB. We then evaluate the performance of the proposed OTDR in the fiber link similar to the optical distribution network of the 64-split TDM PON. The results show that this OTDR can detect both the reflective and non-reflective events occurred in the feeder fiber as well as the reflective events in the drop fibers even in the 64-split TDM PON.

  5. Perceptual image hashing based on virtual watermark detection.

    PubMed

    Khelifi, Fouad; Jiang, Jianmin

    2010-04-01

    This paper proposes a new robust and secure perceptual image hashing technique based on virtual watermark detection. The idea is justified by the fact that the watermark detector responds similarly to perceptually close images using a non embedded watermark. The hash values are extracted in binary form with a perfect control over the probability distribution of the hash bits. Moreover, a key is used to generate pseudo-random noise whose real values contribute to the randomness of the feature vector with a significantly increased uncertainty of the adversary, measured by mutual information, in comparison with linear correlation. Experimentally, the proposed technique has been shown to outperform related state-of-the art techniques recently proposed in the literature in terms of robustness with respect to image processing manipulations and geometric attacks.

  6. 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

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

    PubMed

    Wang, Yue; Wu, Xintao

    2013-08-01

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

  8. 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

  9. A Method for Vibration-Based Structural Interrogation and Health Monitoring Based on Signal Cross-Correlation

    NASA Astrophysics Data System (ADS)

    Trendafilova, I.

    2011-07-01

    Vibration-based structural interrogation and health monitoring is a field which is concerned with the estimation of the current state of a structure or a component from its vibration response with regards to its ability to perform its intended function appropriately. One way to approach this problem is through damage features extracted from the measured structural vibration response. This paper suggests to use a new concept for the purposes of vibration-based health monitoring. The correlation between two signals, an input and an output, measured on the structure is used to develop a damage indicator. The paper investigates the applicability of the signal cross-correlation and a nonlinear alternative, the average mutual information between the two signals, for the purposes of structural health monitoring and damage assessment. The suggested methodology is applied and demonstrated for delamination detection in a composite beam.

  10. Two lightning flashes correlated with detected terrestrial gamma-ray flashes: The UPC Colombia TGF Campaign

    NASA Astrophysics Data System (ADS)

    Fabró, Ferran; Montanyà, Joan; van der Velde, Oscar; Marisaldi, Martino; Betz, Hans-Dieter

    2013-04-01

    TGFs are intense bursts of gamma rays originated in Earth observed from space. These emissions have been correlated with lightning and thunderstorms (e.g. Cummer et al. 2005). Moreover, there is a clear correlation between lightning and TGF activity being both greater in the tropics, probably the occurrence of TGF in these areas can be related to the tropopause height (Smith et al. 2010). The AGILE satellite of the Italian Space Agency (ASI) have detected TGFs events up to 100 MeV (Tavani et al. 2011), confirming that this is the most energetic radiation on Earth. This satellite operates in the +-2.5 latitude belt over Equator. One of the interesting results (Fuschino et al. 2011) is that the TGFs/lightning occurrence ratio is different depending on the Earth region, being greater over South America. In the framework of the future ASIM mission a campaign is conducted in the south of Colombia in order to measure VLF magnetic fields related with TGF parent lightning. A single LINET sensor was installed in October 2012 in the region of coverage of AGILE. Additional lightning data information is provided by the existing LINET network in Colombia. Since the setup of the sensor, two AGILE TGFs events have occurred near the LINET sensor. The first one occurred in November 23rd 2012. The sub-satellite point was located 1400 km away from the LINET sensor. A VLF signal was detected within ˜2.5 ms, which is in agreement with other publications. The second TGF event occurred in November 19th where the sub-satellite point was 260 km away from the LINET sensor. Although this event was very close to the sensor the VLF signal detected occurred ˜170 ms delayed from the TGF. Because of the time differences between the TGF and VLF lightning signals, the first case appears related to the return stroke whereas the second would be related to a leader process. By using VLF signals from the double loop antenna, the direction of the received signal can be retrieved. Correlating this

  11. Research on Fault Detection System of Power Equipment Based on UV and Infrared Image

    NASA Astrophysics Data System (ADS)

    Lu, Qiyu; Ding, Kun

    2017-09-01

    UV corona on power system can reflect the location of the fault and the severity of the fault, the traditional UV and infrared detection equipment can only use the band and the visible light band image of the power system fault detection. In this paper, a power system fault detection system based on ultraviolet and infrared dual-band images is designed. The principle of UV imaging detection and image fusion are introduced respectively. The software of the host computer is written by MFC. The software can acquire both ultraviolet and infrared, the two images are fused using the image fusion algorithm based on edge detection and cross correlation and the highest point temperature is plotted. Experiments show that the system can detect the failure of power equipment in time, and has a certain practical value, which puts forward a new idea for fault detection of power equipment.

  12. 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

  13. 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

  14. Dependence-Based Anomaly Detection Methodologies

    DTIC Science & Technology

    2012-08-16

    tricks the user to enter their Netflix login. Detecting it is out of our scope and requires site authentication (i.e., certification verification... Netflix login. Detecting it is out of our scope and requires site authentication (i.e., certification verification) and user education. The preliminary

  15. 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.

  16. Signal Detection Theory-Based Information Processing for the Detection of Breast Cancer at Microwave Frequencies

    DTIC Science & Technology

    2002-08-01

    the measurement noise, as well as the physical model of the forward scattered electric field. The Bayesian algorithms for the Uncertain Permittivity...received at multiple sensors. In this research project a tissue- model -based signal-detection theory approach for the detection of mammary tumors in the...oriented information processors. In this research project a tissue- model - based signal detection theory approach for the detection of mammary tumors in the

  17. Immunostaining Detection of Cytomegalovirus in Gastrointestinal Biopsies: Clinicopathological Correlation at a Large Academic Health System

    PubMed Central

    Liao, Xiaoyan; Reed, Sharon L.; Lin, Grace Y.

    2016-01-01

    Background Cytomegalovirus (CMV) infection can be asymptomatic in healthy individuals but may cause serious complications in immunocompromised patients. We investigated the clinicopathological correlation of CMV in gastrointestinal (GI) biopsies at our institute between January 1, 2013 and December 31, 2015. Methods A total of 105 non-neoplastic GI biopsies tested positive for CMV by immunohistochemistry (IHC). The IHC results were stratified as “true positive” if > 2 cells stained, or “rare positive” if only 1 - 2 cells stained. Clinical information including comorbidities, serum CMV viral loads, and treatment was reviewed and correlated. Results Overall 1% of all GI biopsies were positive for CMV by immunostaining. The most frequently involved organ was colon, followed by esophagus, stomach, ileum and duodenum. When > 2 cells were stained positive, serum CMV viral loads were positive in 52.2%, negative in 17.2%, and not tested in 27.6% of cases. When only 1 - 2 cells stained positive, CMV viral loads were positive in 23.4%, negative in 25.5%, and not tested in 51.1% of cases. We further showed that clinical management of CMV differs based on both pathological findings and underlying diseases. Conclusions The role of CMV in GI biopsies remains controversial. We propose an algorithm of performing CMV immunostaining based on clinicopathological correlation. PMID:28058077

  18. 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.

  19. 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

  20. Spin correlation and entanglement detection in Cooper pair splitters by current measurements using magnetic detectors

    NASA Astrophysics Data System (ADS)

    Busz, Piotr; Tomaszewski, Damian; Martinek, Jan

    2017-08-01

    We analyze a model of a double quantum dot Cooper pair splitter coupled to two ferromagnetic detectors and demonstrate the possibility of determination of spin correlation by current measurements. We use perturbation theory, taking account of the exchange interaction with the detectors, which leads to complex spin dynamics in the dots. This affects the measured spin and restricts the use of ferromagnetic detectors to the nonlinear current-voltage characteristic regime at the current plateau, where the relevant spin projection is conserved, in contrast to the linear current-voltage characteristic regime, in which the spin information is distorted. Moreover, we show that for separable states the spin correlation can only be determined in a limited parameter regime, much more restricted than in the case of entangled states. We propose an entanglement test based on the Bell inequality.

  1. Lesion area detection using source image correlation coefficient for CT perfusion imaging.

    PubMed

    Fan Zhu; Rodriguez Gonzalez, David; Carpenter, Trevor; Atkinson, Malcolm; Wardlaw, Joanna

    2013-09-01

    Computer tomography (CT) perfusion imaging is widely used to calculate brain hemodynamic quantities such as cerebral blood flow, cerebral blood volume, and mean transit time that aid the diagnosis of acute stroke. Since perfusion source images contain more information than hemodynamic maps, good utilization of the source images can lead to better understanding than the hemodynamic maps alone. Correlation-coefficient tests are used in our approach to measure the similarity between healthy tissue time-concentration curves and unknown curves. This information is then used to differentiate penumbra and dead tissues from healthy tissues. The goal of the segmentation is to fully utilize information in the perfusion source images. Our method directly identifies suspected abnormal areas from perfusion source images and then delivers a suggested segmentation of healthy, penumbra, and dead tissue. This approach is designed to handle CT perfusion images, but it can also be used to detect lesion areas in magnetic resonance perfusion images.

  2. High correlation of double Debye model parameters in skin cancer detection.

    PubMed

    Truong, Bao C Q; Tuan, H D; Fitzgerald, Anthony J; Wallace, Vincent P; Nguyen, H T

    2014-01-01

    The double Debye model can be used to capture the dielectric response of human skin in terahertz regime due to high water content in the tissue. The increased water proportion is widely considered as a biomarker of carcinogenesis, which gives rise of using this model in skin cancer detection. Therefore, the goal of this paper is to provide a specific analysis of the double Debye parameters in terms of non-melanoma skin cancer classification. Pearson correlation is applied to investigate the sensitivity of these parameters and their combinations to the variation in tumor percentage of skin samples. The most sensitive parameters are then assessed by using the receiver operating characteristic (ROC) plot to confirm their potential of classifying tumor from normal skin. Our positive outcomes support further steps to clinical application of terahertz imaging in skin cancer delineation.

  3. 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.

  4. Automated EEG detection algorithms and clinical semiology in epilepsy: importance of correlations.

    PubMed

    Hogan, R Edward

    2011-12-01

    With advances in technological innovation, electroencephalography has remained the gold standard for classification and localization of epileptic seizures. Like other diagnostic modalities, technological advances have opened new avenues for assessment of data, and hold great promise to improve interpretive capabilities. However, proper overall interpretation and application of electroencephalographic findings relies on valid correlations of associated clinical semiology. This article addresses interpretation of clinical signs and symptoms in the context of the diagnostic predictive value of electroencephalographic, clinical, and electrographic definitions of seizures, and upcoming challenges of interpreting intracranial high-frequency electroencephalographic data. This article is part of a Supplemental Special Issue entitled The Future of Automated Seizure Detection and Prediction. Copyright © 2011 Elsevier Inc. All rights reserved.

  5. Correlation of radiographic measurements of structures of the equine foot with lesions detected on magnetic resonance imaging.

    PubMed

    de Zani, D; Polidori, C; di Giancamillo, M; Zani, D D

    2016-03-01

    There are few studies on the correlations between radiographic measurements of the foot and abnormalities of specific structures found with magnetic resonance imaging (MRI). To document the relationship between radiographic measurements of the equine foot and the presence of lesions in the foot on MRI. We hypothesised that different radiographic measurements would be associated with specific lesions detected by MRI. Retrospective analysis of radiographs and MRI studies. Seventy-four feet from 52 lame horses were included. Twenty parameters were measured on radiographs, whereas the signal intensity, homogeneity and size of each structure in the foot were evaluated on magnetic resonance images. The data were analysed using simple linear correlation analysis and classification and regression trees (CARTs). Linear correlations were found between the navicular bone compacta thickness and injuries of the deep digital flexor tendon, collateral sesamoidean ligament, navicular spongiosa and navicular bone proximal border. Long-toed horses had a high incidence of lesions involving the spongiosa and proximal border of the navicular bone. Elongation of the navicular bone was associated with proximal and distal border injuries. A reduced palmar angle and increased angle between the middle and distal phalanx were observed in horses with alterations of collateral ligaments of the distal interphalangeal joint and navicular bone spongiosa, respectively. For each structure under investigation, CARTs predicting the presence of MRI pathology based on radiographic measurements had excellent performance, with >80% correct classification of cases, when using one of 3 data sources. This study demonstrated a relationship between radiographic measurements of the foot and the presence of lesions detected on MRI, while CARTs illustrated that different radiographic measurements were associated with different MRI lesions. © 2015 EVJ Ltd.

  6. Digital image correlation based on a fast convolution strategy

    NASA Astrophysics Data System (ADS)

    Yuan, Yuan; Zhan, Qin; Xiong, Chunyang; Huang, Jianyong

    2017-10-01

    In recent years, the efficiency of digital image correlation (DIC) methods has attracted increasing attention because of its increasing importance for many engineering applications. Based on the classical affine optical flow (AOF) algorithm and the well-established inverse compositional Gauss-Newton algorithm, which is essentially a natural extension of the AOF algorithm under a nonlinear iterative framework, this paper develops a set of fast convolution-based DIC algorithms for high-efficiency subpixel image registration. Using a well-developed fast convolution technique, the set of algorithms establishes a series of global data tables (GDTs) over the digital images, which allows the reduction of the computational complexity of DIC significantly. Using the pre-calculated GDTs, the subpixel registration calculations can be implemented efficiently in a look-up-table fashion. Both numerical simulation and experimental verification indicate that the set of algorithms significantly enhances the computational efficiency of DIC, especially in the case of a dense data sampling for the digital images. Because the GDTs need to be computed only once, the algorithms are also suitable for efficiently coping with image sequences that record the time-varying dynamics of specimen deformations.

  7. The algorithm of malicious code detection based on data mining

    NASA Astrophysics Data System (ADS)

    Yang, Yubo; Zhao, Yang; Liu, Xiabi

    2017-08-01

    Traditional technology of malicious code detection has low accuracy and it has insufficient detection capability for new variants. In terms of malicious code detection technology which is based on the data mining, its indicators are not accurate enough, and its classification detection efficiency is relatively low. This paper proposed the information gain ratio indicator based on the N-gram to choose signature, this indicator can accurately reflect the detection weight of the signature, and helped by C4.5 decision tree to elevate the algorithm of classification detection.

  8. Generating correlation matrices based on the boundaries of their coefficients.

    PubMed

    Numpacharoen, Kawee; Atsawarungruangkit, Amporn

    2012-01-01

    Correlation coefficients among multiple variables are commonly described in the form of matrices. Applications of such correlation matrices can be found in many fields, such as finance, engineering, statistics, and medicine. This article proposes an efficient way to sequentially obtain the theoretical bounds of correlation coefficients together with an algorithm to generate n × n correlation matrices using any bounded random variables. Interestingly, the correlation matrices generated by this method using uniform random variables as an example produce more extreme relationships among the variables than other methods, which might be useful for modeling complex biological systems where rare cases are very important.

  9. 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.

  10. 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.

  11. [The correlation analysis of coagulation detection and blood routine parameters of sudden hearing loss].

    PubMed

    Bao, Fengxiang; Zhang, Shujia; Zhang, Yanping; Zhu, Xuetao; Liu, Weiwei

    2015-01-01

    Through the analysis of coagulation convention and blood routine parameters of sudden hearing loss (SHL) patients, further prove the correlation of sudden deafness and the the inner ear microcirculation, to guide clinical diagnosis and treatment. Select 424 patients (448 ears) with sudden deafness in our department to SHL group. According to hearing curve is classified into low intermediate frequency descent group, high frequency drop and full frequency group, and drawing 244 cases in the same period of hospitalization deviated septum, vocal cord polyp patients as control group. All patients' coagulation detection, D-dimer, blood leukocytes, neutrophils and platelet count percentages were analyzed. Then a meaningful factor multivariate Logistic regression analysis was made. There was a statistically significant difference between the two groups' prothrombin time, international normalized ratio, activated partial thromboplastin time, thrombin time measurement, fibrinogen, D-dimer, platelet count, white blood cell, neutrophil ratio(P<0.05); Logistic regression analysis showed that the prothrombin, thrombin time measurement, fibrinogen, D-dimer, neutrophil incidence of sudden hearing loss associated risk factors. SHL in patients with coagulation dysfunction may be involved in the occurrence of SHL development mechanism, and there is a correlation of the SHL and the dysfunction of inner ear microcirculation.

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

    PubMed

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

    2016-03-01

    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. 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. 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. 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. Canonical correlation analysis can be used as a useful tool for management and preparing of medical data for discovering of knowledge hidden in them.

  13. 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

  14. Ground-based Detection of Exoatmospheric Calcium

    NASA Astrophysics Data System (ADS)

    Rojo, P.; Astudillo-Defru, N.

    2014-03-01

    Data acquired with HDS@Subaru for HD209458b is re-analyzed. A new pipeline performs an automated search for the exoatmospheric presence of several elements without any a-priori assumptions on its existence or strength. We analyzed thousands of lines in the full spectral range of this optical echelle spectrograph using a robust method to correct for the telluric contamination. We recover previous detections of Sodium and Halpha, and present the first strong detection of Calcium in an Extrasolar Atmosphere as well as the tentative detection of other elements. The Calcium detection is in disagreement with theoretical thermal-equilibrium models. Results published in Astudillo-Defru and Rojo (2013, A&A 557, 56)

  15. 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.

  16. Detection of long-range electrostatic interactions between charged molecules by means of fluorescence correlation spectroscopy

    NASA Astrophysics Data System (ADS)

    Nardecchia, Ilaria; Lechelon, Mathias; Gori, Matteo; Donato, Irene; Preto, Jordane; Floriani, Elena; Jaeger, Sebastien; Mailfert, Sebastien; Marguet, Didier; Ferrier, Pierre; Pettini, Marco

    2017-08-01

    In the present paper, an experimental feasibility study on the detection of long-range intermolecular interactions through three-dimensional molecular diffusion in solution is performed. This follows recent theoretical and numerical analyses reporting that long-range electrodynamic forces between biomolecules could be identified through deviations from Brownian diffusion. The suggested experimental technique was fluorescence correlation spectroscopy (FCS). By considering two oppositely charged molecular species in aqueous solution, namely, lysozymes and fluorescent dye molecules (Alexa488), the diffusion coefficient of the dyes has been measured for different values of the concentration of lysozyme, that is, for different average distances between the oppositely charged molecules. For our model, long-range interactions are of electrostatic origin, suggesting that their action radius can be varied by changing the ionic strength of the solution. The experimental outcomes clearly prove the detectability of long-range intermolecular interactions by means of the FCS technique. Molecular dynamics simulations provide a clear and unambiguous interpretation of the experimental results.

  17. Motion detection and pattern tracking in microscopical images using phase correlation approach

    NASA Astrophysics Data System (ADS)

    Gladilin, Evgeny; Kappel, Constantin; Eils, Roland

    2007-03-01

    High-throughput live-cell imaging is one of the important tools for the investigation of cellular structure and functions in modern experimental biology. Automatic processing of time series of microscopic images is hampered by a number of technical and natural factors such as permanent movements of cells in the optical field, alteration of optical cell appearance and high level of noise. Detection and compensation of global motion of groups of cells or relocation of a single cell within a dynamical multi-cell environment is the first indispensable step in the image analysis chain. This article presents an approach for detection of global image motion and single cell tracking in time series of confocal laser scanning microscopy images using an extended Fourier-phase correlation technique, which allows for analysis of non-uniform multi-body motion in partially-similar images. Our experimental results have shown that the developed approach is capable to perform cell tracking and registration in dynamical and noisy scenes, and provides a robust tool for fully-automatic registration of time-series of microscopic images.

  18. 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.

  19. 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.

  20. Repeated measures dose-finding design with time-trend detection in the presence of correlated toxicity data.

    PubMed

    Yin, Jun; Paoletti, Xavier; Sargent, Daniel J; Mandrekar, Sumithra J

    2017-08-01

    Phase I trials are designed to determine the safety, tolerability, and recommended phase 2 dose of therapeutic agents for subsequent testing. The dose-finding paradigm has thus traditionally focused on identifying the maximum tolerable dose of an agent or combination therapy under the assumption that there is a non-decreasing relationship between dose-toxicity and dose-efficacy. The dose is typically determined based on the probability of severe toxicity observed during the first treatment cycle. A novel endpoint, the total toxicity profile, was previously developed to account for the multiple toxicity types and grades experienced in the first cycle. More recently, this was extended to a repeated measures design based on the total toxicity profile to account for longitudinal toxicities over multiple treatment cycles in the absence of within-patient correlation. In this work, we propose to extend the design in the presence of within-patient correlation. Furthermore, we provide a framework to detect a toxicity time trend (toxicity increasing, decreasing, or stable) over multiple treatment cycles. We utilize a linear mixed model in the Bayesian framework, with the addition of Bayesian risk functions for decision-making in dose assignment. The performance of this design was evaluated using simulation studies and real data from a phase I trial. We demonstrated that using available toxicity data from all cycles of treatment improves the accuracy of maximum tolerated dose identification and allows for the detection of a time trend. The performance is consistent regardless of the strength of the within-patient correlation. In addition, the use of a quasi-continuous total toxicity profile score significantly increased the power to detect time trends compared to when binary data only were used. The increased interest in molecularly targeted agents and immunotherapies in oncology necessitates innovative phase I study designs. Our proposed framework provides a tool to tackle

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

    DOEpatents

    Craig, William W [Pittsburg, CA; Labov, Simon E [Berkeley, CA

    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.

  2. 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.

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

    PubMed

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

    2008-06-01

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

  4. Vibration measurement based on the optical cross-correlation technique with femtosecond pulsed laser

    NASA Astrophysics Data System (ADS)

    Han, Jibo; Wu, Tengfei; Zhao, Chunbo; Li, Shuyi

    2016-10-01

    Two vibration measurement methods with femtosecond pulsed laser based on the optical cross-correlation technique are presented independently in this paper. The balanced optical cross-correlation technique can reflect the time jitter between the reference pluses and measurement pluses by detecting second harmonic signals using type II phase-matched nonlinear crystal and balanced amplified photo-detectors. In the first method, with the purpose of attaining the vibration displacement, the time difference of the reference pulses relative to the measurement pluses can be measured using single femtosecond pulsed laser. In the second method, there are a couple of femtosecond pulsed lasers with high pulse repetition frequency. Vibration displacement associated with cavity length can be calculated by means of precisely measuring the pulse repetition frequency. The results show that the range of measurement attains ±150μm for a 500fs pulse. These methods will be suited for vibration displacement measurement, including laboratory use, field testing and industrial application.

  5. A cross-correlation based fiber optic white-light interferometry with wavelet transform denoising

    NASA Astrophysics Data System (ADS)

    Wang, Zhen; Jiang, Yi; Ding, Wenhui; Gao, Ran

    2013-09-01

    A fiber optic white-light interferometry based on cross-