Quantitative Detection and Genotyping of Helicobacter pylori from Stool using Droplet Digital PCR Reveals Variation in Bacterial Loads that Correlates with cagA Virulence Gene Carriage.

PubMed

Talarico, Sarah; Safaeian, Mahboobeh; Gonzalez, Paula; Hildesheim, Allan; Herrero, Rolando; Porras, Carolina; Cortes, Bernal; Larson, Ann; Fang, Ferric C; Salama, Nina R

2016-08-01

Epidemiologic studies of the carcinogenic stomach bacterium Helicobacter pylori have been limited by the lack of noninvasive detection and genotyping methods. We developed a new stool-based method for detection, quantification, and partial genotyping of H. pylori using droplet digital PCR (ddPCR), which allows for increased sensitivity and absolute quantification by PCR partitioning. Stool-based ddPCR assays for H. pylori 16S gene detection and cagA virulence gene typing were tested using a collection of 50 matched stool and serum samples from Costa Rican volunteers and 29 H. pylori stool antigen-tested stool samples collected at a US hospital. The stool-based H. pylori 16S ddPCR assay had a sensitivity of 84% and 100% and a specificity of 100% and 71% compared to serology and stool antigen tests, respectively. The stool-based cagA genotyping assay detected cagA in 22 (88%) of 25 stools from CagA antibody-positive individuals and four (16%) of 25 stools from CagA antibody-negative individuals from Costa Rica. All 26 of these samples had a Western-type cagA allele. Presence of serum CagA antibodies was correlated with a significantly higher load of H. pylori in the stool. The stool-based ddPCR assays are a sensitive, noninvasive method for detection, quantification, and partial genotyping of H. pylori. The quantitative nature of ddPCR-based H. pylori detection revealed significant variation in bacterial load among individuals that correlates with presence of the cagA virulence gene. These stool-based ddPCR assays will facilitate future population-based epidemiologic studies of this important human pathogen. © 2015 John Wiley & Sons Ltd.

Wear Detection of Drill Bit by Image-based Technique

NASA Astrophysics Data System (ADS)

Sukeri, Maziyah; Zulhilmi Paiz Ismadi, Mohd; Rahim Othman, Abdul; Kamaruddin, Shahrul

2018-03-01

Image processing for computer vision function plays an essential aspect in the manufacturing industries for the tool condition monitoring. This study proposes a dependable direct measurement method to measure the tool wear using image-based analysis. Segmentation and thresholding technique were used as the means to filter and convert the colour image to binary datasets. Then, the edge detection method was applied to characterize the edge of the drill bit. By using cross-correlation method, the edges of original and worn drill bits were correlated to each other. Cross-correlation graphs were able to detect the difference of the worn edge despite small difference between the graphs. Future development will focus on quantifying the worn profile as well as enhancing the sensitivity of the technique.

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

Consistently Sampled Correlation Filters with Space Anisotropic Regularization for Visual Tracking

PubMed Central

Shi, Guokai; Xu, Tingfa; Luo, Jiqiang; Li, Yuankun

2017-01-01

Most existing correlation filter-based tracking algorithms, which use fixed patches and cyclic shifts as training and detection measures, assume that the training samples are reliable and ignore the inconsistencies between training samples and detection samples. We propose to construct and study a consistently sampled correlation filter with space anisotropic regularization (CSSAR) to solve these two problems simultaneously. Our approach constructs a spatiotemporally consistent sample strategy to alleviate the redundancies in training samples caused by the cyclical shifts, eliminate the inconsistencies between training samples and detection samples, and introduce space anisotropic regularization to constrain the correlation filter for alleviating drift caused by occlusion. Moreover, an optimization strategy based on the Gauss-Seidel method was developed for obtaining robust and efficient online learning. Both qualitative and quantitative evaluations demonstrate that our tracker outperforms state-of-the-art trackers in object tracking benchmarks (OTBs). PMID:29231876

Tsunami Detection by High Frequency Radar Beyond the Continental Shelf: II. Extension of Time Correlation Algorithm and Validation on Realistic Case Studies

NASA Astrophysics Data System (ADS)

Grilli, Stéphan T.; Guérin, Charles-Antoine; Shelby, Michael; Grilli, Annette R.; Moran, Patrick; Grosdidier, Samuel; Insua, Tania L.

2017-08-01

In past work, tsunami detection algorithms (TDAs) have been proposed, and successfully applied to offline tsunami detection, based on analyzing tsunami currents inverted from high-frequency (HF) radar Doppler spectra. With this method, however, the detection of small and short-lived tsunami currents in the most distant radar ranges is challenging due to conflicting requirements on the Doppler spectra integration time and resolution. To circumvent this issue, in Part I of this work, we proposed an alternative TDA, referred to as time correlation (TC) TDA, that does not require inverting currents, but instead detects changes in patterns of correlations of radar signal time series measured in pairs of cells located along the main directions of tsunami propagation (predicted by geometric optics theory); such correlations can be maximized when one signal is time-shifted by the pre-computed long wave propagation time. We initially validated the TC-TDA based on numerical simulations of idealized tsunamis in a simplified geometry. Here, we further develop, extend, and apply the TC algorithm to more realistic tsunami case studies. These are performed in the area West of Vancouver Island, BC, where Ocean Networks Canada recently deployed a HF radar (in Tofino, BC), to detect tsunamis from far- and near-field sources, up to a 110 km range. Two case studies are considered, both simulated using long wave models (1) a far-field seismic, and (2) a near-field landslide, tsunami. Pending the availability of radar data, a radar signal simulator is parameterized for the Tofino HF radar characteristics, in particular its signal-to-noise ratio with range, and combined with the simulated tsunami currents to produce realistic time series of backscattered radar signal from a dense grid of cells. Numerical experiments show that the arrival of a tsunami causes a clear change in radar signal correlation patterns, even at the most distant ranges beyond the continental shelf, thus making an early tsunami detection possible with the TC-TDA. Based on these results, we discuss how the new algorithm could be combined with standard methods proposed earlier, based on a Doppler analysis, to develop a new tsunami detection system based on HF radar data, that could increase warning time. This will be the object of future work, which will be based on actual, rather than simulated, radar data.

Gas detection by correlation spectroscopy employing a multimode diode laser.

PubMed

Lou, Xiutao; Somesfalean, Gabriel; Zhang, Zhiguo

2008-05-01

A gas sensor based on the gas-correlation technique has been developed using a multimode diode laser (MDL) in a dual-beam detection scheme. Measurement of CO(2) mixed with CO as an interfering gas is successfully demonstrated using a 1570 nm tunable MDL. Despite overlapping absorption spectra and occasional mode hops, the interfering signals can be effectively excluded by a statistical procedure including correlation analysis and outlier identification. The gas concentration is retrieved from several pair-correlated signals by a linear-regression scheme, yielding a reliable and accurate measurement. This demonstrates the utility of the unsophisticated MDLs as novel light sources for gas detection applications.

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.

Correlation Filters for Detection of Cellular Nuclei in Histopathology Images.

PubMed

Ahmad, Asif; Asif, Amina; Rajpoot, Nasir; Arif, Muhammad; Minhas, Fayyaz Ul Amir Afsar

2017-11-21

Nuclei detection in histology images is an essential part of computer aided diagnosis of cancers and tumors. It is a challenging task due to diverse and complicated structures of cells. In this work, we present an automated technique for detection of cellular nuclei in hematoxylin and eosin stained histopathology images. Our proposed approach is based on kernelized correlation filters. Correlation filters have been widely used in object detection and tracking applications but their strength has not been explored in the medical imaging domain up till now. Our experimental results show that the proposed scheme gives state of the art accuracy and can learn complex nuclear morphologies. Like deep learning approaches, the proposed filters do not require engineering of image features as they can operate directly on histopathology images without significant preprocessing. However, unlike deep learning methods, the large-margin correlation filters developed in this work are interpretable, computationally efficient and do not require specialized or expensive computing hardware. A cloud based webserver of the proposed method and its python implementation can be accessed at the following URL: http://faculty.pieas.edu.pk/fayyaz/software.html#corehist .

Thresholding Based on Maximum Weighted Object Correlation for Rail Defect Detection

NASA Astrophysics Data System (ADS)

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

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

Tensor Fukunaga-Koontz transform for small target detection in infrared images

NASA Astrophysics Data System (ADS)

Liu, Ruiming; Wang, Jingzhuo; Yang, Huizhen; Gong, Chenglong; Zhou, Yuanshen; Liu, Lipeng; Zhang, Zhen; Shen, Shuli

2016-09-01

Infrared small targets detection plays a crucial role in warning and tracking systems. Some novel methods based on pattern recognition technology catch much attention from researchers. However, those classic methods must reshape images into vectors with the high dimensionality. Moreover, vectorizing breaks the natural structure and correlations in the image data. Image representation based on tensor treats images as matrices and can hold the natural structure and correlation information. So tensor algorithms have better classification performance than vector algorithms. Fukunaga-Koontz transform is one of classification algorithms and it is a vector version method with the disadvantage of all vector algorithms. In this paper, we first extended the Fukunaga-Koontz transform into its tensor version, tensor Fukunaga-Koontz transform. Then we designed a method based on tensor Fukunaga-Koontz transform for detecting targets and used it to detect small targets in infrared images. The experimental results, comparison through signal-to-clutter, signal-to-clutter gain and background suppression factor, have validated the advantage of the target detection based on the tensor Fukunaga-Koontz transform over that based on the Fukunaga-Koontz transform.

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.

Change Detection via Selective Guided Contrasting Filters

NASA Astrophysics Data System (ADS)

Vizilter, Y. V.; Rubis, A. Y.; Zheltov, S. Y.

2017-05-01

Change detection scheme based on guided contrasting was previously proposed. Guided contrasting filter takes two images (test and sample) as input and forms the output as filtered version of test image. Such filter preserves the similar details and smooths the non-similar details of test image with respect to sample image. Due to this the difference between test image and its filtered version (difference map) could be a basis for robust change detection. Guided contrasting is performed in two steps: at the first step some smoothing operator (SO) is applied for elimination of test image details; at the second step all matched details are restored with local contrast proportional to the value of some local similarity coefficient (LSC). The guided contrasting filter was proposed based on local average smoothing as SO and local linear correlation as LSC. In this paper we propose and implement new set of selective guided contrasting filters based on different combinations of various SO and thresholded LSC. Linear average and Gaussian smoothing, nonlinear median filtering, morphological opening and closing are considered as SO. Local linear correlation coefficient, morphological correlation coefficient (MCC), mutual information, mean square MCC and geometrical correlation coefficients are applied as LSC. Thresholding of LSC allows operating with non-normalized LSC and enhancing the selective properties of guided contrasting filters: details are either totally recovered or not recovered at all after the smoothing. These different guided contrasting filters are tested as a part of previously proposed change detection pipeline, which contains following stages: guided contrasting filtering on image pyramid, calculation of difference map, binarization, extraction of change proposals and testing change proposals using local MCC. Experiments on real and simulated image bases demonstrate the applicability of all proposed selective guided contrasting filters. All implemented filters provide the robustness relative to weak geometrical discrepancy of compared images. Selective guided contrasting based on morphological opening/closing and thresholded morphological correlation demonstrates the best change detection result.

Correlation-based perfusion mapping using time-resolved MR angiography: A feasibility study for patients with suspicions of steno-occlusive craniocervical arteries.

PubMed

Nam, Yoonho; Jang, Jinhee; Park, Sonya Youngju; Choi, Hyun Seok; Jung, So-Lyung; Ahn, Kook-Jin; Kim, Bum-Soo

2018-05-22

To explore the feasibility of using correlation-based time-delay (CTD) maps produced from time-resolved MR angiography (TRMRA) to diagnose perfusion abnormalities in patients suspected to have steno-occlusive lesions in the craniocervical arteries. Twenty-seven patients who were suspected to have steno-occlusive lesions in the craniocervical arteries underwent both TRMRA and brain single-photon emission computed tomography (SPECT). TRMRA was performed on the supra-aortic area after intravenous injection of a 0.03 mmol/kg gadolinium-based contrast agent. Time-to-peak (TTP) maps and CTD maps of the brain were automatically generated from TRMRA data, and their quality was assessed. Detection of perfusion abnormalities was compared between CTD maps and the time-series maximal intensity projection (MIP) images from TRMRA and TTP maps. Correlation coefficients between quantitative changes in SPECT and parametric maps for the abnormal perfusion areas were calculated. The CTD maps were of significantly superior quality than TTP maps (p < 0.01). For perfusion abnormality detection, CTD maps (kappa 0.84, 95% confidence interval [CI] 0.67-1.00) showed better agreement with SPECT than TTP maps (0.66, 0.46-0.85). For perfusion deficit detection, CTD maps showed higher accuracy (85.2%, 95% CI 66.3-95.8) than MIP images (66.7%, 46-83.5), with marginal significance (p = 0.07). In abnormal perfusion areas, correlation coefficients between SPECT and CTD (r = 0.74, 95% CI 0.34-0.91) were higher than those between SPECT and TTP (r = 0.66, 0.20-0.88). CTD maps generated from TRMRA were of high quality and offered good diagnostic performance for detecting perfusion abnormalities associated with steno-occlusive arterial lesions in the craniocervical area. • Generation of perfusion parametric maps from time-resolved MR angiography is clinically useful. • Correlation-based delay maps can be used to detect perfusion abnormalities associated with steno-occlusive craniocervical arteries. • Estimation of correlation-based delay is robust for low signal-to-noise 4D MR data.

Analysis of digital communication signals and extraction of parameters

NASA Astrophysics Data System (ADS)

Al-Jowder, Anwar

1994-12-01

The signal classification performance of four types of electronics support measure (ESM) communications detection systems is compared from the standpoint of the unintended receiver (interceptor). Typical digital communication signals considered include binary phase shift keying (BPSK), quadrature phase shift keying (QPSK), frequency shift keying (FSK), and on-off keying (OOK). The analysis emphasizes the use of available signal processing software. Detection methods compared include broadband energy detection, FFT-based narrowband energy detection, and two correlation methods which employ the fast Fourier transform (FFT). The correlation methods utilize modified time-frequency distributions, where one of these is based on the Wigner-Ville distribution (WVD). Gaussian white noise is added to the signal to simulate various signal-to-noise ratios (SNR's).

Convective-diffusion-based fluorescence correlation spectroscopy for detection of a trace amount of E. coli in water.

PubMed

Qing, De-Kui; Mengüç, M Pinar; Payne, Fred A; Danao, Mary-Grace C

2003-06-01

Fluorescence correlation spectroscopy (FCS) is adapted for a new procedure to detect trace amounts of Escherichia coli in water. The present concept is based on convective diffusion rather than Brownian diffusion and employs confocal microscopy as in traditional FCS. With this system it is possible to detect concentrations as small as 1.5 x 10(5) E. coli per milliliter (2.5 x 10(-16) M). This concentration corresponds to an approximately 1.0-nM level of Rhodamine 6G dyes. A detailed analysis of the optical system is presented, and further improvements for the procedure are discussed.

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

PubMed

Goense, J B M; Ratnam, R

2003-10-01

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

Rayleigh-enhanced attosecond sum-frequency polarization beats via twin color-locking noisy lights

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang Yanpeng; Li Long; Ma Ruiqiong

2005-07-15

Based on color-locking noisy field correlation, a time-delayed method is proposed to suppress the thermal effect, and the ultrafast longitudinal relaxation time can be measured even in an absorbing medium. One interesting feature in field-correlation effects is that Rayleigh-enhanced four-wave mixing (RFWM) with color-locking noisy light exhibits spectral symmetry and temporal asymmetry with no coherence spike at {tau}=0. Due to the interference between the Rayleigh-resonant signal and the nonresonant background, RFWM exhibits hybrid radiation-matter detuning with terahertz damping oscillations. The subtle Markovian high-order correlation effects have been investigated in the homodyne- or heterodyne-detected Rayleigh-enhanced attosecond sum-frequency polarization beats (RASPBs). Analyticmore » closed forms of fourth-order Markovian stochastic correlations are characterized for homodyne (quadratic) and heterodyne (linear) detection, respectively. Based on the polarization interference between two four-wave mixing processes, the phase-sensitive detection of RASPBs has also been used to obtain the real and imaginary parts of the Rayleigh resonance.« less

Development of 19F-NMR chemical shift detection of DNA B-Z equilibrium using 19F-NMR.

PubMed

Nakamura, S; Yang, H; Hirata, C; Kersaudy, F; Fujimoto, K

2017-06-28

Various DNA conformational changes are in correlation with biological events. In particular, DNA B-Z equilibrium showed a high correlation with translation and transcription. In this study, we developed a DNA probe containing 5-trifluoromethylcytidine or 5-trifluoromethylthymidine to detect DNA B-Z equilibrium using 19 F-NMR. Its probe enabled the quantitative detection of B-, Z-, and ss-DNA based on 19 F-NMR chemical shift change.

Multivariate η-μ fading distribution with arbitrary correlation model

NASA Astrophysics Data System (ADS)

Ghareeb, Ibrahim; Atiani, Amani

2018-03-01

An extensive analysis for the multivariate ? distribution with arbitrary correlation is presented, where novel analytical expressions for the multivariate probability density function, cumulative distribution function and moment generating function (MGF) of arbitrarily correlated and not necessarily identically distributed ? power random variables are derived. Also, this paper provides exact-form expression for the MGF of the instantaneous signal-to-noise ratio at the combiner output in a diversity reception system with maximal-ratio combining and post-detection equal-gain combining operating in slow frequency nonselective arbitrarily correlated not necessarily identically distributed ?-fading channels. The average bit error probability of differentially detected quadrature phase shift keying signals with post-detection diversity reception system over arbitrarily correlated and not necessarily identical fading parameters ?-fading channels is determined by using the MGF-based approach. The effect of fading correlation between diversity branches, fading severity parameters and diversity level is studied.

Radiation detector device for rejecting and excluding incomplete charge collection events

DOEpatents

Bolotnikov, Aleksey E.; De Geronimo, Gianluigi; Vernon, Emerson; Yang, Ge; Camarda, Giuseppe; Cui, Yonggang; Hossain, Anwar; Kim, Ki Hyun; James, Ralph B.

2016-05-10

A radiation detector device is provided that is capable of distinguishing between full charge collection (FCC) events and incomplete charge collection (ICC) events based upon a correlation value comparison algorithm that compares correlation values calculated for individually sensed radiation detection events with a calibrated FCC event correlation function. The calibrated FCC event correlation function serves as a reference curve utilized by a correlation value comparison algorithm to determine whether a sensed radiation detection event fits the profile of the FCC event correlation function within the noise tolerances of the radiation detector device. If the radiation detection event is determined to be an ICC event, then the spectrum for the ICC event is rejected and excluded from inclusion in the radiation detector device spectral analyses. The radiation detector device also can calculate a performance factor to determine the efficacy of distinguishing between FCC and ICC events.

Measuring Time-of-Flight in an Ultrasonic LPS System Using Generalized Cross-Correlation

PubMed Central

Villladangos, José Manuel; Ureña, Jesús; García, Juan Jesús; Mazo, Manuel; Hernández, Álvaro; Jiménez, Ana; Ruíz, Daniel; De Marziani, Carlos

2011-01-01

In this article, a time-of-flight detection technique in the frequency domain is described for an ultrasonic Local Positioning System (LPS) based on encoded beacons. Beacon transmissions have been synchronized and become simultaneous by means of the DS-CDMA (Direct-Sequence Code Division Multiple Access) technique. Every beacon has been associated to a 255-bit Kasami code. The detection of signal arrival instant at the receiver, from which the distance to each beacon can be obtained, is based on the application of the Generalized Cross-Correlation (GCC), by using the cross-spectral density between the received signal and the sequence to be detected. Prior filtering to enhance the frequency components around the carrier frequency (40 kHz) has improved estimations when obtaining the correlation function maximum, which implies an improvement in distance measurement precision. Positioning has been achieved by using hyperbolic trilateration, based on the Time Differences of Arrival (TDOA) between a reference beacon and the others. PMID:22346645

Measuring time-of-flight in an ultrasonic LPS system using generalized cross-correlation.

PubMed

Villladangos, José Manuel; Ureña, Jesús; García, Juan Jesús; Mazo, Manuel; Hernández, Alvaro; Jiménez, Ana; Ruíz, Daniel; De Marziani, Carlos

2011-01-01

In this article, a time-of-flight detection technique in the frequency domain is described for an ultrasonic local positioning system (LPS) based on encoded beacons. Beacon transmissions have been synchronized and become simultaneous by means of the DS-CDMA (direct-sequence code Division multiple access) technique. Every beacon has been associated to a 255-bit Kasami code. The detection of signal arrival instant at the receiver, from which the distance to each beacon can be obtained, is based on the application of the generalized cross-correlation (GCC), by using the cross-spectral density between the received signal and the sequence to be detected. Prior filtering to enhance the frequency components around the carrier frequency (40 kHz) has improved estimations when obtaining the correlation function maximum, which implies an improvement in distance measurement precision. Positioning has been achieved by using hyperbolic trilateration, based on the time differences of arrival (TDOA) between a reference beacon and the others.

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.

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

A powerful score-based test statistic for detecting gene-gene co-association.

PubMed

Xu, Jing; Yuan, Zhongshang; Ji, Jiadong; Zhang, Xiaoshuai; Li, Hongkai; Wu, Xuesen; Xue, Fuzhong; Liu, Yanxun

2016-01-29

The genetic variants identified by Genome-wide association study (GWAS) can only account for a small proportion of the total heritability for complex disease. The existence of gene-gene joint effects which contains the main effects and their co-association is one of the possible explanations for the "missing heritability" problems. Gene-gene co-association refers to the extent to which the joint effects of two genes differ from the main effects, not only due to the traditional interaction under nearly independent condition but the correlation between genes. Generally, genes tend to work collaboratively within specific pathway or network contributing to the disease and the specific disease-associated locus will often be highly correlated (e.g. single nucleotide polymorphisms (SNPs) in linkage disequilibrium). Therefore, we proposed a novel score-based statistic (SBS) as a gene-based method for detecting gene-gene co-association. Various simulations illustrate that, under different sample sizes, marginal effects of causal SNPs and co-association levels, the proposed SBS has the better performance than other existed methods including single SNP-based and principle component analysis (PCA)-based logistic regression model, the statistics based on canonical correlations (CCU), kernel canonical correlation analysis (KCCU), partial least squares path modeling (PLSPM) and delta-square (δ (2)) statistic. The real data analysis of rheumatoid arthritis (RA) further confirmed its advantages in practice. SBS is a powerful and efficient gene-based method for detecting gene-gene co-association.

Detecting coupled collective motions in protein by independent subspace analysis

NASA Astrophysics Data System (ADS)

Sakuraba, Shun; Joti, Yasumasa; Kitao, Akio

2010-11-01

Protein dynamics evolves in a high-dimensional space, comprising aharmonic, strongly correlated motional modes. Such correlation often plays an important role in analyzing protein function. In order to identify significantly correlated collective motions, here we employ independent subspace analysis based on the subspace joint approximate diagonalization of eigenmatrices algorithm for the analysis of molecular dynamics (MD) simulation trajectories. From the 100 ns MD simulation of T4 lysozyme, we extract several independent subspaces in each of which collective modes are significantly correlated, and identify the other modes as independent. This method successfully detects the modes along which long-tailed non-Gaussian probability distributions are obtained. Based on the time cross-correlation analysis, we identified a series of events among domain motions and more localized motions in the protein, indicating the connection between the functionally relevant phenomena which have been independently revealed by experiments.

Multi-Station Broad Regional Event Detection Using Waveform Correlation

NASA Astrophysics Data System (ADS)

Slinkard, M.; Stephen, H.; Young, C. J.; Eckert, R.; Schaff, D. P.; Richards, P. G.

2013-12-01

Previous waveform correlation studies have established the occurrence of repeating seismic events in various regions, and the utility of waveform-correlation event-detection on broad regional or even global scales to find events currently not included in traditionally-prepared bulletins. The computational burden, however, is high, limiting previous experiments to relatively modest template libraries and/or processing time periods. We have developed a distributed computing waveform correlation event detection utility that allows us to process years of continuous waveform data with template libraries numbering in the thousands. We have used this system to process several years of waveform data from IRIS stations in East Asia, using libraries of template events taken from global and regional bulletins. Detections at a given station are confirmed by 1) comparison with independent bulletins of seismicity, and 2) consistent detections at other stations. We find that many of the detected events are not in traditional catalogs, hence the multi-station comparison is essential. In addition to detecting the similar events, we also estimate magnitudes very precisely based on comparison with the template events (when magnitudes are available). We have investigated magnitude variation within detected families of similar events, false alarm rates, and the temporal and spatial reach of templates.

Sea Ice Detection Based on an Improved Similarity Measurement Method Using Hyperspectral Data.

PubMed

Han, Yanling; Li, Jue; Zhang, Yun; Hong, Zhonghua; Wang, Jing

2017-05-15

Hyperspectral remote sensing technology can acquire nearly continuous spectrum information and rich sea ice image information, thus providing an important means of sea ice detection. However, the correlation and redundancy among hyperspectral bands reduce the accuracy of traditional sea ice detection methods. Based on the spectral characteristics of sea ice, this study presents an improved similarity measurement method based on linear prediction (ISMLP) to detect sea ice. First, the first original band with a large amount of information is determined based on mutual information theory. Subsequently, a second original band with the least similarity is chosen by the spectral correlation measuring method. Finally, subsequent bands are selected through the linear prediction method, and a support vector machine classifier model is applied to classify sea ice. In experiments performed on images of Baffin Bay and Bohai Bay, comparative analyses were conducted to compare the proposed method and traditional sea ice detection methods. Our proposed ISMLP method achieved the highest classification accuracies (91.18% and 94.22%) in both experiments. From these results the ISMLP method exhibits better performance overall than other methods and can be effectively applied to hyperspectral sea ice detection.

Sea Ice Detection Based on an Improved Similarity Measurement Method Using Hyperspectral Data

PubMed Central

Han, Yanling; Li, Jue; Zhang, Yun; Hong, Zhonghua; Wang, Jing

2017-01-01

Hyperspectral remote sensing technology can acquire nearly continuous spectrum information and rich sea ice image information, thus providing an important means of sea ice detection. However, the correlation and redundancy among hyperspectral bands reduce the accuracy of traditional sea ice detection methods. Based on the spectral characteristics of sea ice, this study presents an improved similarity measurement method based on linear prediction (ISMLP) to detect sea ice. First, the first original band with a large amount of information is determined based on mutual information theory. Subsequently, a second original band with the least similarity is chosen by the spectral correlation measuring method. Finally, subsequent bands are selected through the linear prediction method, and a support vector machine classifier model is applied to classify sea ice. In experiments performed on images of Baffin Bay and Bohai Bay, comparative analyses were conducted to compare the proposed method and traditional sea ice detection methods. Our proposed ISMLP method achieved the highest classification accuracies (91.18% and 94.22%) in both experiments. From these results the ISMLP method exhibits better performance overall than other methods and can be effectively applied to hyperspectral sea ice detection. PMID:28505135

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.

Thin and Slow Smoke Detection by Using Frequency Image

NASA Astrophysics Data System (ADS)

Zheng, Guang; Oe, Shunitiro

In this paper, a new method to detect thin and slow smoke for early fire alarm by using frequency image has been proposed. The correlation coefficient of the frequency image between the current stage and the initial stage are calculated, so are the gray image correlation coefficient of the color image. When the thin smoke close to transparent enters into the camera view, the correlation coefficient of the frequency image becomes small, while the gray image correlation coefficient of the color image hardly change and keep large. When something which is not transparent, like human beings, etc., enters into the camera view, the correlation coefficient of the frequency image becomes small, as well as that of color image. Based on the difference of correlation coefficient between frequency image and color image in different situations, the thin smoke can be detected. Also, considering the movement of the thin smoke, miss detection caused by the illustration change or noise can be avoided. Several experiments in different situations are carried out, and the experimental results show the effect of the proposed method.

Tsunami detection by high-frequency radar in British Columbia: performance assessment of the time-correlation algorithm for synthetic and real events

NASA Astrophysics Data System (ADS)

Guérin, Charles-Antoine; Grilli, Stéphan T.; Moran, Patrick; Grilli, Annette R.; Insua, Tania L.

2018-05-01

The authors recently proposed a new method for detecting tsunamis using high-frequency (HF) radar observations, referred to as "time-correlation algorithm" (TCA; Grilli et al. Pure Appl Geophys 173(12):3895-3934, 2016a, 174(1): 3003-3028, 2017). Unlike standard algorithms that detect surface current patterns, the TCA is based on analyzing space-time correlations of radar signal time series in pairs of radar cells, which does not require inverting radial surface currents. This was done by calculating a contrast function, which quantifies the change in pattern of the mean correlation between pairs of neighboring cells upon tsunami arrival, with respect to a reference correlation computed in the recent past. In earlier work, the TCA was successfully validated based on realistic numerical simulations of both the radar signal and tsunami wave trains. Here, this algorithm is adapted to apply to actual data from a HF radar installed in Tofino, BC, for three test cases: (1) a simulated far-field tsunami generated in the Semidi Subduction Zone in the Aleutian Arc; (2) a simulated near-field tsunami from a submarine mass failure on the continental slope off of Tofino; and (3) an event believed to be a meteotsunami, which occurred on October 14th, 2016, off of the Pacific West Coast and was measured by the radar. In the first two cases, the synthetic tsunami signal is superimposed onto the radar signal by way of a current memory term; in the third case, the tsunami signature is present within the radar data. In light of these test cases, we develop a detection methodology based on the TCA, using a correlation contrast function, and show that in all three cases the algorithm is able to trigger a timely early warning.

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.

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…

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

Detection of Nitrogen Content in Rubber Leaves Using Near-Infrared (NIR) Spectroscopy with Correlation-Based Successive Projections Algorithm (SPA).

PubMed

Tang, Rongnian; Chen, Xupeng; Li, Chuang

2018-05-01

Near-infrared spectroscopy is an efficient, low-cost technology that has potential as an accurate method in detecting the nitrogen content of natural rubber leaves. Successive projections algorithm (SPA) is a widely used variable selection method for multivariate calibration, which uses projection operations to select a variable subset with minimum multi-collinearity. However, due to the fluctuation of correlation between variables, high collinearity may still exist in non-adjacent variables of subset obtained by basic SPA. Based on analysis to the correlation matrix of the spectra data, this paper proposed a correlation-based SPA (CB-SPA) to apply the successive projections algorithm in regions with consistent correlation. The result shows that CB-SPA can select variable subsets with more valuable variables and less multi-collinearity. Meanwhile, models established by the CB-SPA subset outperform basic SPA subsets in predicting nitrogen content in terms of both cross-validation and external prediction. Moreover, CB-SPA is assured to be more efficient, for the time cost in its selection procedure is one-twelfth that of the basic SPA.

Fully invariant wavelet enhanced minimum average correlation energy filter for object recognition in cluttered and occluded environments

NASA Astrophysics Data System (ADS)

Tehsin, Sara; Rehman, Saad; Riaz, Farhan; Saeed, Omer; Hassan, Ali; Khan, Muazzam; Alam, Muhammad S.

2017-05-01

A fully invariant system helps in resolving difficulties in object detection when camera or object orientation and position are unknown. In this paper, the proposed correlation filter based mechanism provides the capability to suppress noise, clutter and occlusion. Minimum Average Correlation Energy (MACE) filter yields sharp correlation peaks while considering the controlled correlation peak value. Difference of Gaussian (DOG) Wavelet has been added at the preprocessing stage in proposed filter design that facilitates target detection in orientation variant cluttered environment. Logarithmic transformation is combined with a DOG composite minimum average correlation energy filter (WMACE), capable of producing sharp correlation peaks despite any kind of geometric distortion of target object. The proposed filter has shown improved performance over some of the other variant correlation filters which are discussed in the result section.

Quantifying Phishing Susceptibility for Detection and Behavior Decisions.

PubMed

Canfield, Casey Inez; Fischhoff, Baruch; Davis, Alex

2016-12-01

We use signal detection theory to measure vulnerability to phishing attacks, including variation in performance across task conditions. Phishing attacks are difficult to prevent with technology alone, as long as technology is operated by people. Those responsible for managing security risks must understand user decision making in order to create and evaluate potential solutions. Using a scenario-based online task, we performed two experiments comparing performance on two tasks: detection, deciding whether an e-mail is phishing, and behavior, deciding what to do with an e-mail. In Experiment 1, we manipulated the order of the tasks and notification of the phishing base rate. In Experiment 2, we varied which task participants performed. In both experiments, despite exhibiting cautious behavior, participants' limited detection ability left them vulnerable to phishing attacks. Greater sensitivity was positively correlated with confidence. Greater willingness to treat e-mails as legitimate was negatively correlated with perceived consequences from their actions and positively correlated with confidence. These patterns were robust across experimental conditions. Phishing-related decisions are sensitive to individuals' detection ability, response bias, confidence, and perception of consequences. Performance differs when people evaluate messages or respond to them but not when their task varies in other ways. Based on these results, potential interventions include providing users with feedback on their abilities and information about the consequences of phishing, perhaps targeting those with the worst performance. Signal detection methods offer system operators quantitative assessments of the impacts of interventions and their residual vulnerability. © 2016, Human Factors and Ergonomics Society.

Dual linear structured support vector machine tracking method via scale correlation filter

NASA Astrophysics Data System (ADS)

Li, Weisheng; Chen, Yanquan; Xiao, Bin; Feng, Chen

2018-01-01

Adaptive tracking-by-detection methods based on structured support vector machine (SVM) performed well on recent visual tracking benchmarks. However, these methods did not adopt an effective strategy of object scale estimation, which limits the overall tracking performance. We present a tracking method based on a dual linear structured support vector machine (DLSSVM) with a discriminative scale correlation filter. The collaborative tracker comprised of a DLSSVM model and a scale correlation filter obtains good results in tracking target position and scale estimation. The fast Fourier transform is applied for detection. Extensive experiments show that our tracking approach outperforms many popular top-ranking trackers. On a benchmark including 100 challenging video sequences, the average precision of the proposed method is 82.8%.

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

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

PubMed

Proescholdt, Martin A; Faltermeier, Rupert; Bele, Sylvia; 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.

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.

Multiscale Anomaly Detection and Image Registration Algorithms for Airborne Landmine Detection

DTIC Science & Technology

2008-05-01

with the sensed image. The two- dimensional correlation coefficient r for two matrices A and B both of size M ×N is given by r = ∑ m ∑ n (Amn...correlation based method by matching features in a high- dimensional feature- space . The current implementation of the SIFT algorithm uses a brute-force...by repeatedly convolving the image with a Guassian kernel. Each plane of the scale

Towards sensitive, high-throughput, biomolecular assays based on fluorescence lifetime

NASA Astrophysics Data System (ADS)

Ioanna Skilitsi, Anastasia; Turko, Timothé; Cianfarani, Damien; Barre, Sophie; Uhring, Wilfried; Hassiepen, Ulrich; Léonard, Jérémie

2017-09-01

Time-resolved fluorescence detection for robust sensing of biomolecular interactions is developed by implementing time-correlated single photon counting in high-throughput conditions. Droplet microfluidics is used as a promising platform for the very fast handling of low-volume samples. We illustrate the potential of this very sensitive and cost-effective technology in the context of an enzymatic activity assay based on fluorescently-labeled biomolecules. Fluorescence lifetime detection by time-correlated single photon counting is shown to enable reliable discrimination between positive and negative control samples at a throughput as high as several hundred samples per second.

Serum creatinine detection by a conducting-polymer-based electrochemical sensor to identify allograft dysfunction.

PubMed

Wei, Fang; Cheng, Scott; Korin, Yael; Reed, Elaine F; Gjertson, David; Ho, Chih-ming; Gritsch, H Albin; Veale, Jeffrey

2012-09-18

Kidney transplant recipients who have abnormally high creatinine levels in their blood often have allograft dysfunction secondary to rejection. Creatinine has become the preferred marker for renal dysfunction and is readily available in hospital clinical settings. We developed a rapid and accurate polymer-based electrochemical point-of-care (POC) assay for creatinine detection from whole blood to identify allograft dysfunction. The creatinine concentrations of 19 blood samples from transplant recipients were measured directly from clinical serum samples by the conducting polymer-based electrochemical (EC) sensor arrays. These measurements were compared to the traditional clinical laboratory assay. The time required for detection was <5 min from sample loading. Sensitivity of the detection was found to be 0.46 mg/dL of creatinine with only 40 μL sample in the creatinine concentration range of 0 mg/dL to 11.33 mg/dL. Signal levels that were detected electrochemically correlated closely with the creatinine blood concentration detected by the UCLA Ronald Reagan Medical Center traditional clinical laboratory assay (correlation coefficient = 0.94). This work is encouraging for the development of a rapid and accurate POC device for measuring creatinine levels in whole blood.

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.

Hierarchical clustering of EMD based interest points for road sign detection

NASA Astrophysics Data System (ADS)

Khan, Jesmin; Bhuiyan, Sharif; Adhami, Reza

2014-04-01

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

Bell Correlations in a Many-Body System with Finite Statistics

NASA Astrophysics Data System (ADS)

Wagner, Sebastian; Schmied, Roman; Fadel, Matteo; Treutlein, Philipp; Sangouard, Nicolas; Bancal, Jean-Daniel

2017-10-01

A recent experiment reported the first violation of a Bell correlation witness in a many-body system [Science 352, 441 (2016)]. Following discussions in this Letter, we address here the question of the statistics required to witness Bell correlated states, i.e., states violating a Bell inequality, in such experiments. We start by deriving multipartite Bell inequalities involving an arbitrary number of measurement settings, two outcomes per party and one- and two-body correlators only. Based on these inequalities, we then build up improved witnesses able to detect Bell correlated states in many-body systems using two collective measurements only. These witnesses can potentially detect Bell correlations in states with an arbitrarily low amount of spin squeezing. We then establish an upper bound on the statistics needed to convincingly conclude that a measured state is Bell correlated.

Bell Correlations in a Many-Body System with Finite Statistics.

PubMed

Wagner, Sebastian; Schmied, Roman; Fadel, Matteo; Treutlein, Philipp; Sangouard, Nicolas; Bancal, Jean-Daniel

2017-10-27

A recent experiment reported the first violation of a Bell correlation witness in a many-body system [Science 352, 441 (2016)]. Following discussions in this Letter, we address here the question of the statistics required to witness Bell correlated states, i.e., states violating a Bell inequality, in such experiments. We start by deriving multipartite Bell inequalities involving an arbitrary number of measurement settings, two outcomes per party and one- and two-body correlators only. Based on these inequalities, we then build up improved witnesses able to detect Bell correlated states in many-body systems using two collective measurements only. These witnesses can potentially detect Bell correlations in states with an arbitrarily low amount of spin squeezing. We then establish an upper bound on the statistics needed to convincingly conclude that a measured state is Bell correlated.

Binaural comodulation masking release: Effects of masker interaural correlation

PubMed Central

Hall, Joseph W.; Buss, Emily; Grose, John H.

2007-01-01

Binaural detection was examined for a signal presented in a narrow band of noise centered on the on-signal masking band (OSB) or in the presence of flanking noise bands that were random or comodulated with respect to the OSB. The noise had an interaural correlation of 1.0 (No), 0.99 or 0.95. In No noise, random flanking bands worsened Sπ detection and comodulated bands improved Sπ detection for some listeners but had no effect for other listeners. For the 0.99 or 0.95 interaural correlation conditions, random flanking bands were less detrimental to Sπ detection and comodulated flanking bands improved Sπ detection for all listeners. Analyses based on signal detection theory indicated that the improvement in Sπ thresholds obtained with comodulated bands was not compatible with an optimal combination of monaural and binaural cues or to across-frequency analyses of dynamic interaural phase differences. Two accounts consistent with the improvement in Sπ thresholds in comodulated noise were (1) envelope information carried by the flanking bands improves the weighting of binaural cues associated with the signal; (2) the auditory system is sensitive to across-frequency differences in ongoing interaural correlation. PMID:17225415

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

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tibi, Rigobert; Young, Christopher; Gonzales, Antonio

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

Fluorescence hyperspectral imaging technique for the foreign substance detection on fresh-cut lettuce

USDA-ARS?s Scientific Manuscript database

Nondestructive methods based on fluorescence hyperspectral imaging (HSI) techniques were developed in order to detect worms on fresh-cut lettuce. The optimal wavebands for detecting worms on fresh-cut lettuce were investigated using the one-way ANOVA analysis and correlation analysis. The worm detec...

Confined detection volume of fluorescence correlation spectroscopy by bare fiber probes.

PubMed

Lu, Guowei; Lei, Franck H; Angiboust, Jean-François; Manfait, Michel

2010-04-01

A fiber-tip-based near-field fluorescence correlation spectroscopy (FCS) has been developed for confining the detection volume to sub-diffraction-limited dimensions. This near-field FCS is based on near-field illumination by coupling a scanning near-field optical microscope (SNOM) to a conventional confocal FCS. Single-molecule FCS analysis at 100 nM Rhodamine 6G has been achieved by using bare chemically etched, tapered fiber tips. The detection volume under control of the SNOM system has been reduced over one order of magnitude compared to that of the conventional confocal FCS. Related factors influencing the near-field FCS performance are investigated and discussed in detail. In this proof-of-principle study, the preliminary experimental results suggest that the fiber-tip-based near-field FCS might be a good alternative to realize localized analysis at the single-molecule level.

Features of Cross-Correlation Analysis in a Data-Driven Approach for Structural Damage Assessment

PubMed Central

Camacho Navarro, Jhonatan; Ruiz, Magda; Villamizar, Rodolfo; Mujica, Luis

2018-01-01

This work discusses the advantage of using cross-correlation analysis in a data-driven approach based on principal component analysis (PCA) and piezodiagnostics to obtain successful diagnosis of events in structural health monitoring (SHM). In this sense, the identification of noisy data and outliers, as well as the management of data cleansing stages can be facilitated through the implementation of a preprocessing stage based on cross-correlation functions. Additionally, this work evidences an improvement in damage detection when the cross-correlation is included as part of the whole damage assessment approach. The proposed methodology is validated by processing data measurements from piezoelectric devices (PZT), which are used in a piezodiagnostics approach based on PCA and baseline modeling. Thus, the influence of cross-correlation analysis used in the preprocessing stage is evaluated for damage detection by means of statistical plots and self-organizing maps. Three laboratory specimens were used as test structures in order to demonstrate the validity of the methodology: (i) a carbon steel pipe section with leak and mass damage types, (ii) an aircraft wing specimen, and (iii) a blade of a commercial aircraft turbine, where damages are specified as mass-added. As the main concluding remark, the suitability of cross-correlation features combined with a PCA-based piezodiagnostic approach in order to achieve a more robust damage assessment algorithm is verified for SHM tasks. PMID:29762505

Features of Cross-Correlation Analysis in a Data-Driven Approach for Structural Damage Assessment.

PubMed

Camacho Navarro, Jhonatan; Ruiz, Magda; Villamizar, Rodolfo; Mujica, Luis; Quiroga, Jabid

2018-05-15

This work discusses the advantage of using cross-correlation analysis in a data-driven approach based on principal component analysis (PCA) and piezodiagnostics to obtain successful diagnosis of events in structural health monitoring (SHM). In this sense, the identification of noisy data and outliers, as well as the management of data cleansing stages can be facilitated through the implementation of a preprocessing stage based on cross-correlation functions. Additionally, this work evidences an improvement in damage detection when the cross-correlation is included as part of the whole damage assessment approach. The proposed methodology is validated by processing data measurements from piezoelectric devices (PZT), which are used in a piezodiagnostics approach based on PCA and baseline modeling. Thus, the influence of cross-correlation analysis used in the preprocessing stage is evaluated for damage detection by means of statistical plots and self-organizing maps. Three laboratory specimens were used as test structures in order to demonstrate the validity of the methodology: (i) a carbon steel pipe section with leak and mass damage types, (ii) an aircraft wing specimen, and (iii) a blade of a commercial aircraft turbine, where damages are specified as mass-added. As the main concluding remark, the suitability of cross-correlation features combined with a PCA-based piezodiagnostic approach in order to achieve a more robust damage assessment algorithm is verified for SHM tasks.

[Detection of Heart Rate of Fetal ECG Based on STFT and BSS].

PubMed

Wang, Xu; Cai, Kun

2016-01-01

Changes in heart rate of fetal is function regulating performance of the circulatory system and the central nervous system, it is significant to detect heart rate of fetus in perinatal fetal. This paper puts forward the fetal heart rate detection method based on short time Fourier transform and blind source separation. First of all, the mixed ECG signal was preprocessed, and then the wavelet transform technique was used to separate the fetal ECG signal with noise from mixed ECG signal, after that, the short-time Fourier transform and the blind separation were carried on it, and then calculated the correlation coefficient of it, Finally, An independent component that it has strongest correlation with the original signal was selected to make FECG peak detection and calculated the fetal instantaneous heart rate. The experimental results show that the method can improve the detection rate of the FECG peak (R), and it has high accuracy in fixing peak(R) location in the case of low signal-noise ratio.

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.

Implementation of a direct-imaging and FX correlator for the BEST-2 array

NASA Astrophysics Data System (ADS)

Foster, G.; Hickish, J.; Magro, A.; Price, D.; Zarb Adami, K.

2014-04-01

A new digital backend has been developed for the Basic Element for SKA Training II (BEST-2) array at Radiotelescopi di Medicina, INAF-IRA, Italy, which allows concurrent operation of an FX correlator, and a direct-imaging correlator and beamformer. This backend serves as a platform for testing some of the spatial Fourier transform concepts which have been proposed for use in computing correlations on regularly gridded arrays. While spatial Fourier transform-based beamformers have been implemented previously, this is, to our knowledge, the first time a direct-imaging correlator has been deployed on a radio astronomy array. Concurrent observations with the FX and direct-imaging correlator allow for direct comparison between the two architectures. Additionally, we show the potential of the direct-imaging correlator for time-domain astronomy, by passing a subset of beams though a pulsar and transient detection pipeline. These results provide a timely verification for spatial Fourier transform-based instruments that are currently in commissioning. These instruments aim to detect highly redshifted hydrogen from the epoch of reionization and/or to perform wide-field surveys for time-domain studies of the radio sky. We experimentally show the direct-imaging correlator architecture to be a viable solution for correlation and beamforming.

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.

Improved target detection algorithm using Fukunaga-Koontz transform and distance classifier correlation filter

NASA Astrophysics Data System (ADS)

Bal, A.; Alam, M. S.; Aslan, M. S.

2006-05-01

Often sensor ego-motion or fast target movement causes the target to temporarily go out of the field-of-view leading to reappearing target detection problem in target tracking applications. Since the target goes out of the current frame and reenters at a later frame, the reentering location and variations in rotation, scale, and other 3D orientations of the target are not known thus complicating the detection algorithm has been developed using Fukunaga-Koontz Transform (FKT) and distance classifier correlation filter (DCCF). The detection algorithm uses target and background information, extracted from training samples, to detect possible candidate target images. The detected candidate target images are then introduced into the second algorithm, DCCF, called clutter rejection module, to determine the target coordinates are detected and tracking algorithm is initiated. The performance of the proposed FKT-DCCF based target detection algorithm has been tested using real-world forward looking infrared (FLIR) video sequences.

Cross-correlation spin noise spectroscopy of heterogeneous interacting spin systems

DOE PAGES

Roy, Dibyendu; Yang, Luyi; Crooker, Scott A.; ...

2015-04-30

Interacting multi-component spin systems are ubiquitous in nature and in the laboratory. As such, investigations of inter-species spin interactions are of vital importance. Traditionally, they are studied by experimental methods that are necessarily perturbative: e.g., by intentionally polarizing or depolarizing one spin species while detecting the response of the other(s). Here, we describe and demonstrate an alternative approach based on multi-probe spin noise spectroscopy, which can reveal inter-species spin interactions - under conditions of strict thermal equilibrium - by detecting and cross-correlating the stochastic fluctuation signals exhibited by each of the constituent spin species. Specifically, we consider a two-component spinmore » ensemble that interacts via exchange coupling, and we determine cross-correlations between their intrinsic spin fluctuations. The model is experimentally confirmed using “two-color” optical spin noise spectroscopy on a mixture of interacting Rb and Cs vapors. Noise correlations directly reveal the presence of inter-species spin exchange, without ever perturbing the system away from thermal equilibrium. These non-invasive and noise-based techniques should be generally applicable to any heterogeneous spin system in which the fluctuations of the constituent components are detectable.« less

Gear Tooth Wear Detection Algorithm

NASA Technical Reports Server (NTRS)

Delgado, Irebert R.

2015-01-01

Vibration-based condition indicators continue to be developed for Health Usage Monitoring of rotorcraft gearboxes. Testing performed at NASA Glenn Research Center have shown correlations between specific condition indicators and specific types of gear wear. To speed up the detection and analysis of gear teeth, an image detection program based on the Viola-Jones algorithm was trained to automatically detect spiral bevel gear wear pitting. The detector was tested using a training set of gear wear pictures and a blind set of gear wear pictures. The detector accuracy for the training set was 75 percent while the accuracy for the blind set was 15 percent. Further improvements on the accuracy of the detector are required but preliminary results have shown its ability to automatically detect gear tooth wear. The trained detector would be used to quickly evaluate a set of gear or pinion pictures for pits, spalls, or abrasive wear. The results could then be used to correlate with vibration or oil debris data. In general, the program could be retrained to detect features of interest from pictures of a component taken over a period of time.

The detection error of thermal test low-frequency cable based on M sequence correlation algorithm

NASA Astrophysics Data System (ADS)

Wu, Dongliang; Ge, Zheyang; Tong, Xin; Du, Chunlin

2018-04-01

The problem of low accuracy and low efficiency of off-line detecting on thermal test low-frequency cable faults could be solved by designing a cable fault detection system, based on FPGA export M sequence code(Linear feedback shift register sequence) as pulse signal source. The design principle of SSTDR (Spread spectrum time-domain reflectometry) reflection method and hardware on-line monitoring setup figure is discussed in this paper. Testing data show that, this detection error increases with fault location of thermal test low-frequency cable.

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

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.

Development and evaluation of novel sensing materials for detecting food contamination

NASA Astrophysics Data System (ADS)

Sankaran, Sindhuja

Rapid detection of food-borne volatile organic compounds (VOCs) such as organic acids and alcohols released by bacterial pathogens is being used as an indicator for detecting bacterial contamination in food by our research group. One of our current research thrusts is to develop novel sensors that will be sensitive to specific compounds (at low operating temperature) associated with food safety. This study evaluates two approaches employed to develop sensors for detecting acid and alcohols at low concentrations. Chemoresistive and piezoelectric sensors were developed based on metal oxides and olfactory system based biomaterials, respectively to detect acetic acid, butanol, 3-methyl-1-butanol, 1-pentanol, and 1-hexanol. The metal oxide based sensors were developed by the sol-gel method. A zinc oxide (ZnO) sensor was found to be sensitive to acetic acid with lower detection limit ranging from 13-40 ppm. The three-layered dip-coated gold electrode based ZnO sensors had a LDL of 18 ppm for acetic acid detection. The ZnO-iron oxide (Fe2O3) based nanocomposite sensors were developed to detect butanol operating at 100°C. The 5% Fe/Zn mole ratio based ZnO-Fe2O3 nanocomposite sensors had high correlation coefficients (>0.90) of calibration curves, low butanol LDLs (26 +/- 7 ppm), and lower variation among the sensor responses. The ZnO and ZnO-Fe2O3 nanocomposite sensors showed potential to detect acetic acid and butanol at low concentrations, respectively at 100°C. QCM based olfactory sensors were developed from olfactory receptor and odorant binding protein based sequences to detect low concentrations of acetic acid and alcohols (3-methyl-1-butanol and 1-hexanol), respectively. The average LDLs for acetic acid as well as alcohols detection of the QCM sensors were < 5 ppm. The linear calibration curve based correlation coefficients of the QCM sensors were > 0.80. Finally, a computational simulation based peptide sequences was designed from olfactory receptors and evaluated as sensor material for the detection of alcohols at low concentrations. The results indicated that the QCM sensors exhibited a good sensitivity to 1-hexanol and 1-pentanol with the estimated LDLs in the range of 2-3 ppm and 3-5 ppm, respectively. This research work was successful in developing multiple novel sensing materials to detect alcohols and acid associated with meat contaminations at low concentrations.

A PLSPM-Based Test Statistic for Detecting Gene-Gene Co-Association in Genome-Wide Association Study with Case-Control Design

PubMed Central

Zhang, Xiaoshuai; Yang, Xiaowei; Yuan, Zhongshang; Liu, Yanxun; Li, Fangyu; Peng, Bin; Zhu, Dianwen; Zhao, Jinghua; Xue, Fuzhong

2013-01-01

For genome-wide association data analysis, two genes in any pathway, two SNPs in the two linked gene regions respectively or in the two linked exons respectively within one gene are often correlated with each other. We therefore proposed the concept of gene-gene co-association, which refers to the effects not only due to the traditional interaction under nearly independent condition but the correlation between two genes. Furthermore, we constructed a novel statistic for detecting gene-gene co-association based on Partial Least Squares Path Modeling (PLSPM). Through simulation, the relationship between traditional interaction and co-association was highlighted under three different types of co-association. Both simulation and real data analysis demonstrated that the proposed PLSPM-based statistic has better performance than single SNP-based logistic model, PCA-based logistic model, and other gene-based methods. PMID:23620809

A PLSPM-based test statistic for detecting gene-gene co-association in genome-wide association study with case-control design.

PubMed

Zhang, Xiaoshuai; Yang, Xiaowei; Yuan, Zhongshang; Liu, Yanxun; Li, Fangyu; Peng, Bin; Zhu, Dianwen; Zhao, Jinghua; Xue, Fuzhong

2013-01-01

For genome-wide association data analysis, two genes in any pathway, two SNPs in the two linked gene regions respectively or in the two linked exons respectively within one gene are often correlated with each other. We therefore proposed the concept of gene-gene co-association, which refers to the effects not only due to the traditional interaction under nearly independent condition but the correlation between two genes. Furthermore, we constructed a novel statistic for detecting gene-gene co-association based on Partial Least Squares Path Modeling (PLSPM). Through simulation, the relationship between traditional interaction and co-association was highlighted under three different types of co-association. Both simulation and real data analysis demonstrated that the proposed PLSPM-based statistic has better performance than single SNP-based logistic model, PCA-based logistic model, and other gene-based methods.

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.

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.

Deep Spatial-Temporal Joint Feature Representation for Video Object Detection.

PubMed

Zhao, Baojun; Zhao, Boya; Tang, Linbo; Han, Yuqi; Wang, Wenzheng

2018-03-04

With the development of deep neural networks, many object detection frameworks have shown great success in the fields of smart surveillance, self-driving cars, and facial recognition. However, the data sources are usually videos, and the object detection frameworks are mostly established on still images and only use the spatial information, which means that the feature consistency cannot be ensured because the training procedure loses temporal information. To address these problems, we propose a single, fully-convolutional neural network-based object detection framework that involves temporal information by using Siamese networks. In the training procedure, first, the prediction network combines the multiscale feature map to handle objects of various sizes. Second, we introduce a correlation loss by using the Siamese network, which provides neighboring frame features. This correlation loss represents object co-occurrences across time to aid the consistent feature generation. Since the correlation loss should use the information of the track ID and detection label, our video object detection network has been evaluated on the large-scale ImageNet VID dataset where it achieves a 69.5% mean average precision (mAP).

Phone camera detection of glucose blood level based on magnetic particles entrapped inside bubble wrap.

PubMed

Martinkova, Pavla; Pohanka, Miroslav

2016-12-18

Glucose is an important diagnostic biochemical marker of diabetes but also for organophosphates, carbamates, acetaminophens or salicylates poisoning. Hence, innovation of accurate and fast detection assay is still one of priorities in biomedical research. Glucose sensor based on magnetic particles (MPs) with immobilized enzymes glucose oxidase (GOx) and horseradish peroxidase (HRP) was developed and the GOx catalyzed reaction was visualized by a smart-phone-integrated camera. Exponential decay concentration curve with correlation coefficient 0.997 and with limit of detection 0.4 mmol/l was achieved. Interfering and matrix substances were measured due to possibility of assay influencing and no effect of the tested substances was observed. Spiked plasma samples were also measured and no influence of plasma matrix on the assay was proved. The presented assay showed complying results with reference method (standard spectrophotometry based on enzymes glucose oxidase and peroxidase inside plastic cuvettes) with linear dependence and correlation coefficient 0.999 in concentration range between 0 and 4 mmol/l. On the grounds of measured results, method was considered as highly specific, accurate and fast assay for detection of glucose.

A fluorescent immunochromatographic strip test using a quantum dot-antibody probe for rapid and quantitative detection of 1-aminohydantoin in edible animal tissues.

PubMed

Le, Tao; Zhang, Zhihao; Wu, Juan; Shi, Haixing; Cao, Xudong

2018-01-01

A rapid, simple, and sensitive fluorescent immunochromatographic strip test (ICST) based on quantum dots (QDs) has been developed to detect 1-aminohydantoin (AHD), a major metabolite of nitrofurantoin in animal tissues. To achieve this, QD-labeled antibody conjugates, which consist of CdSe/ZnS QDs and monoclonal antibodies, were prepared by an activated ester method. Under optimal conditions, with the nitrophenyl derivative of AHD as the target, the ICST had a linear range from 0.1 to 100 ng/mL, with a correlation coefficient of 0.9656 and a 50% inhibitory concentration of 4.51 ng/mL. The limit of detection was 0.14 ng/g, which was below the minimum required performance limit of 1 μg/kg for AHD established by the European Commission. The recoveries for AHD ranged from 81.5% to 108.2%, with coefficients of variation below 13%, based on intraday and interday analysis. Furthermore, for AHD in real samples, the ICST showed high reliability and high correlation with liquid chromatography-tandem mass spectrometry (correlation coefficient of 0.9916). To the best of our knowledge, this is the first report of a novel and sensitive method based on a fluorescent ICST to detect AHD below the minimum required performance limit. The ICST demonstrated high reliability, and could be ideally suited for rapid, simple, and on-site screening of AHD contamination in animal tissues. Graphical abstract A rapid, simple, and sensitive fluorescent immunochromatographic strip test that is based on quantum dots was developed to detect 1-aminohydantoin (AHD), a major metabolite of nitrofurantoin in animal tissues. 2-NBA 2-nitrobenzaldehyde, NP nitrophenyl.

A Study of Dim Object Detection for the Space Surveillance Telescope

DTIC Science & Technology

2013-03-21

ENG-13-M-32 Abstract Current methods of dim object detection for space surveillance make use of a Gaussian log-likelihood-ratio-test-based...quantitatively comparing the efficacy of two methods for dim object detection , termed in this paper the point detector and the correlator, both of which rely... applications . It is used in national defense for detecting satellites. It is used to detecting space debris, which threatens both civilian and

Discriminative correlation filter tracking with occlusion detection

NASA Astrophysics Data System (ADS)

Zhang, Shuo; Chen, Zhong; Yu, XiPeng; Zhang, Ting; He, Jing

2018-03-01

Aiming at the problem that the correlation filter-based tracking algorithm can not track the target of severe occlusion, a target re-detection mechanism is proposed. First of all, based on the ECO, we propose the multi-peak detection model and the response value to distinguish the occlusion and deformation in the target tracking, which improve the success rate of tracking. And then we add the confidence model to update the mechanism to effectively prevent the model offset problem which due to similar targets or background during the tracking process. Finally, the redetection mechanism of the target is added, and the relocation is performed after the target is lost, which increases the accuracy of the target positioning. The experimental results demonstrate that the proposed tracker performs favorably against state-of-the-art methods in terms of robustness and accuracy.

A KST framework for correlation network construction from time series signals

NASA Astrophysics Data System (ADS)

Qi, Jin-Peng; Gu, Quan; Zhu, Ying; Zhang, Ping

2018-04-01

A KST (Kolmogorov-Smirnov test and T statistic) method is used for construction of a correlation network based on the fluctuation of each time series within the multivariate time signals. In this method, each time series is divided equally into multiple segments, and the maximal data fluctuation in each segment is calculated by a KST change detection procedure. Connections between each time series are derived from the data fluctuation matrix, and are used for construction of the fluctuation correlation network (FCN). The method was tested with synthetic simulations and the result was compared with those from using KS or T only for detection of data fluctuation. The novelty of this study is that the correlation analyses was based on the data fluctuation in each segment of each time series rather than on the original time signals, which would be more meaningful for many real world applications and for analysis of large-scale time signals where prior knowledge is uncertain.

LEAKAGE CHARACTERISTICS OF BASE OF RIVERBANK BY SELF POTENTIAL METHOD AND EXAMINATION OF EFFECTIVENESS OF SELF POTENTIAL METHOD TO HEALTH MONITORING OF BASE OF RIVERBANK

NASA Astrophysics Data System (ADS)

Matsumoto, Kensaku; Okada, Takashi; Takeuchi, Atsuo; Yazawa, Masato; Uchibori, Sumio; Shimizu, Yoshihiko

Field Measurement of Self Potential Method using Copper Sulfate Electrode was performed in base of riverbank in WATARASE River, where has leakage problem to examine leakage characteristics. Measurement results showed typical S-shape what indicates existence of flow groundwater. The results agreed with measurement results by Ministry of Land, Infrastructure and Transport with good accuracy. Results of 1m depth ground temperature detection and Chain-Array detection showed good agreement with results of the Self Potential Method. Correlation between Self Potential value and groundwater velocity was examined model experiment. The result showed apparent correlation. These results indicate that the Self Potential Method was effective method to examine the characteristics of ground water of base of riverbank in leakage problem.

Optical correlation based pose estimation using bipolar phase grayscale amplitude spatial light modulators

NASA Astrophysics Data System (ADS)

Outerbridge, Gregory John, II

Pose estimation techniques have been developed on both optical and digital correlator platforms to aid in the autonomous rendezvous and docking of spacecraft. This research has focused on the optical architecture, which utilizes high-speed bipolar-phase grayscale-amplitude spatial light modulators as the image and correlation filter devices. The optical approach has the primary advantage of optical parallel processing: an extremely fast and efficient way of performing complex correlation calculations. However, the constraints imposed on optically implementable filters makes optical correlator based posed estimation technically incompatible with the popular weighted composite filter designs successfully used on the digital platform. This research employs a much simpler "bank of filters" approach to optical pose estimation that exploits the inherent efficiency of optical correlation devices. A novel logarithmically mapped optically implementable matched filter combined with a pose search algorithm resulted in sub-degree standard deviations in angular pose estimation error. These filters were extremely simple to generate, requiring no complicated training sets and resulted in excellent performance even in the presence of significant background noise. Common edge detection and scaling of the input image was the only image pre-processing necessary for accurate pose detection at all alignment distances of interest.

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.

Sandwich enzyme-linked immunosorbent assay (ELISA) for measuring the concentration of, and detection of antibodies to, Aujeszky's disease virus.

PubMed

Kardi, V; Szegletes, E; Perényi, T; Pergel, I; Smal, Z

1990-01-01

A double antibody sandwich enzyme-linked immunosorbent assay (ELISA) was developed for measuring Aujeszky's disease virus (ADV) antigen concentration and an inhibition technique based on the former was developed for detection of antibodies to ADV. The results were checked by determining the cytopathic and serum neutralization titres. The correlation was satisfactory in both cases, with correlation coefficients above 0.8. When measuring ADV antigen concentration, the lower limit of detection was 10(3) TCID 50/0.2 ml. The sensitivity of ELISA in detecting antibodies to ADV was found to be superior to that of the serum neutralization test and, thus, enabled the testing of rabbit and guinea-pig sera.

Correlation-based motion vector processing with adaptive interpolation scheme for motion-compensated frame interpolation.

PubMed

Huang, Ai-Mei; Nguyen, Truong

2009-04-01

In this paper, we address the problems of unreliable motion vectors that cause visual artifacts but cannot be detected by high residual energy or bidirectional prediction difference in motion-compensated frame interpolation. A correlation-based motion vector processing method is proposed to detect and correct those unreliable motion vectors by explicitly considering motion vector correlation in the motion vector reliability classification, motion vector correction, and frame interpolation stages. Since our method gradually corrects unreliable motion vectors based on their reliability, we can effectively discover the areas where no motion is reliable to be used, such as occlusions and deformed structures. We also propose an adaptive frame interpolation scheme for the occlusion areas based on the analysis of their surrounding motion distribution. As a result, the interpolated frames using the proposed scheme have clearer structure edges and ghost artifacts are also greatly reduced. Experimental results show that our interpolated results have better visual quality than other methods. In addition, the proposed scheme is robust even for those video sequences that contain multiple and fast motions.

Detecting event-related changes in organizational networks using optimized neural network models.

PubMed

Li, Ze; Sun, Duoyong; Zhu, Renqi; Lin, Zihan

2017-01-01

Organizational external behavior changes are caused by the internal structure and interactions. External behaviors are also known as the behavioral events of an organization. Detecting event-related changes in organizational networks could efficiently be used to monitor the dynamics of organizational behaviors. Although many different methods have been used to detect changes in organizational networks, these methods usually ignore the correlation between the internal structure and external events. Event-related change detection considers the correlation and could be used for event recognition based on social network modeling and supervised classification. Detecting event-related changes could be effectively useful in providing early warnings and faster responses to both positive and negative organizational activities. In this study, event-related change in an organizational network was defined, and artificial neural network models were used to quantitatively determine whether and when a change occurred. To achieve a higher accuracy, Back Propagation Neural Networks (BPNNs) were optimized using Genetic Algorithms (GAs) and Particle Swarm Optimization (PSO). We showed the feasibility of the proposed method by comparing its performance with that of other methods using two cases. The results suggested that the proposed method could identify organizational events based on a correlation between the organizational networks and events. The results also suggested that the proposed method not only has a higher precision but also has a better robustness than the previously used techniques.

Detecting event-related changes in organizational networks using optimized neural network models

PubMed Central

Sun, Duoyong; Zhu, Renqi; Lin, Zihan

2017-01-01

Organizational external behavior changes are caused by the internal structure and interactions. External behaviors are also known as the behavioral events of an organization. Detecting event-related changes in organizational networks could efficiently be used to monitor the dynamics of organizational behaviors. Although many different methods have been used to detect changes in organizational networks, these methods usually ignore the correlation between the internal structure and external events. Event-related change detection considers the correlation and could be used for event recognition based on social network modeling and supervised classification. Detecting event-related changes could be effectively useful in providing early warnings and faster responses to both positive and negative organizational activities. In this study, event-related change in an organizational network was defined, and artificial neural network models were used to quantitatively determine whether and when a change occurred. To achieve a higher accuracy, Back Propagation Neural Networks (BPNNs) were optimized using Genetic Algorithms (GAs) and Particle Swarm Optimization (PSO). We showed the feasibility of the proposed method by comparing its performance with that of other methods using two cases. The results suggested that the proposed method could identify organizational events based on a correlation between the organizational networks and events. The results also suggested that the proposed method not only has a higher precision but also has a better robustness than the previously used techniques. PMID:29190799

Robust Small Target Co-Detection from Airborne Infrared Image Sequences.

PubMed

Gao, Jingli; Wen, Chenglin; Liu, Meiqin

2017-09-29

In this paper, a novel infrared target co-detection model combining the self-correlation features of backgrounds and the commonality features of targets in the spatio-temporal domain is proposed to detect small targets in a sequence of infrared images with complex backgrounds. Firstly, a dense target extraction model based on nonlinear weights is proposed, which can better suppress background of images and enhance small targets than weights of singular values. Secondly, a sparse target extraction model based on entry-wise weighted robust principal component analysis is proposed. The entry-wise weight adaptively incorporates structural prior in terms of local weighted entropy, thus, it can extract real targets accurately and suppress background clutters efficiently. Finally, the commonality of targets in the spatio-temporal domain are used to construct target refinement model for false alarms suppression and target confirmation. Since real targets could appear in both of the dense and sparse reconstruction maps of a single frame, and form trajectories after tracklet association of consecutive frames, the location correlation of the dense and sparse reconstruction maps for a single frame and tracklet association of the location correlation maps for successive frames have strong ability to discriminate between small targets and background clutters. Experimental results demonstrate that the proposed small target co-detection method can not only suppress background clutters effectively, but also detect targets accurately even if with target-like interference.

Ionospheric earthquake effects detection based on Total Electron Content (TEC) GPS Correlation

NASA Astrophysics Data System (ADS)

Sunardi, Bambang; Muslim, Buldan; Eka Sakya, Andi; Rohadi, Supriyanto; Sulastri; Murjaya, Jaya

2018-03-01

Advances in science and technology showed that ground-based GPS receiver was able to detect ionospheric Total Electron Content (TEC) disturbances caused by various natural phenomena such as earthquakes. One study of Tohoku (Japan) earthquake, March 11, 2011, magnitude M 9.0 showed TEC fluctuations observed from GPS observation network spread around the disaster area. This paper discussed the ionospheric earthquake effects detection using TEC GPS data. The case studies taken were Kebumen earthquake, January 25, 2014, magnitude M 6.2, Sumba earthquake, February 12, 2016, M 6.2 and Halmahera earthquake, February 17, 2016, M 6.1. TEC-GIM (Global Ionosphere Map) correlation methods for 31 days were used to monitor TEC anomaly in ionosphere. To ensure the geomagnetic disturbances due to solar activity, we also compare with Dst index in the same time window. The results showed anomalous ratio of correlation coefficient deviation to its standard deviation upon occurrences of Kebumen and Sumba earthquake, but not detected a similar anomaly for the Halmahera earthquake. It was needed a continous monitoring of TEC GPS data to detect the earthquake effects in ionosphere. This study giving hope in strengthening the earthquake effect early warning system using TEC GPS data. The method development of continuous TEC GPS observation derived from GPS observation network that already exists in Indonesia is needed to support earthquake effects early warning systems.

A novel infrared small moving target detection method based on tracking interest points under complicated background

NASA Astrophysics Data System (ADS)

Dong, Xiabin; Huang, Xinsheng; Zheng, Yongbin; Bai, Shengjian; Xu, Wanying

2014-07-01

Infrared moving target detection is an important part of infrared technology. We introduce a novel infrared small moving target detection method based on tracking interest points under complicated background. Firstly, Difference of Gaussians (DOG) filters are used to detect a group of interest points (including the moving targets). Secondly, a sort of small targets tracking method inspired by Human Visual System (HVS) is used to track these interest points for several frames, and then the correlations between interest points in the first frame and the last frame are obtained. Last, a new clustering method named as R-means is proposed to divide these interest points into two groups according to the correlations, one is target points and another is background points. In experimental results, the target-to-clutter ratio (TCR) and the receiver operating characteristics (ROC) curves are computed experimentally to compare the performances of the proposed method and other five sophisticated methods. From the results, the proposed method shows a better discrimination of targets and clutters and has a lower false alarm rate than the existing moving target detection methods.

1H-detected MAS solid-state NMR experiments enable the simultaneous mapping of rigid and dynamic domains of membrane proteins

NASA Astrophysics Data System (ADS)

Gopinath, T.; Nelson, Sarah E. D.; Veglia, Gianluigi

2017-12-01

Magic angle spinning (MAS) solid-state NMR (ssNMR) spectroscopy is emerging as a unique method for the atomic resolution structure determination of native membrane proteins in lipid bilayers. Although 13C-detected ssNMR experiments continue to play a major role, recent technological developments have made it possible to carry out 1H-detected experiments, boosting both sensitivity and resolution. Here, we describe a new set of 1H-detected hybrid pulse sequences that combine through-bond and through-space correlation elements into single experiments, enabling the simultaneous detection of rigid and dynamic domains of membrane proteins. As proof-of-principle, we applied these new pulse sequences to the membrane protein phospholamban (PLN) reconstituted in lipid bilayers under moderate MAS conditions. The cross-polarization (CP) based elements enabled the detection of the relatively immobile residues of PLN in the transmembrane domain using through-space correlations; whereas the most dynamic region, which is in equilibrium between folded and unfolded states, was mapped by through-bond INEPT-based elements. These new 1H-detected experiments will enable one to detect not only the most populated (ground) states of biomacromolecules, but also sparsely populated high-energy (excited) states for a complete characterization of protein free energy landscapes.

Multiple targets detection method in detection of UWB through-wall radar

NASA Astrophysics Data System (ADS)

Yang, Xiuwei; Yang, Chuanfa; Zhao, Xingwen; Tian, Xianzhong

2017-11-01

In this paper, the problems and difficulties encountered in the detection of multiple moving targets by UWB radar are analyzed. The experimental environment and the penetrating radar system are established. An adaptive threshold method based on local area is proposed to effectively filter out clutter interference The objective of the moving target is analyzed, and the false target is further filtered out by extracting the target feature. Based on the correlation between the targets, the target matching algorithm is proposed to improve the detection accuracy. Finally, the effectiveness of the above method is verified by practical experiment.

Distribution of Response Time, Cortical, and Cardiac Correlates during Emotional Interference in Persons with Subclinical Psychotic Symptoms

PubMed Central

Holper, Lisa K. B.; Aleksandrowicz, Alekandra; Müller, Mario; Ajdacic-Gross, Vladeta; Haker, Helene; Fallgatter, Andreas J.; Hagenmuller, Florence; Kawohl, Wolfram; Rössler, Wulf

2016-01-01

A psychosis phenotype can be observed below the threshold of clinical detection. The study aimed to investigate whether subclinical psychotic symptoms are associated with deficits in controlling emotional interference, and whether cortical brain and cardiac correlates of these deficits can be detected using functional near-infrared spectroscopy (fNIRS). A data set derived from a community sample was obtained from the Zurich Program for Sustainable Development of Mental Health Services. 174 subjects (mean age 29.67 ± 6.41, 91 females) were assigned to four groups ranging from low to high levels of subclinical psychotic symptoms (derived from the Symptom Checklist-90-R). Emotional interference was assessed using the emotional Stroop task comprising neutral, positive, and negative conditions. Statistical distributional methods based on delta plots [behavioral response time (RT) data] and quantile analysis (fNIRS data) were applied to evaluate the emotional interference effects. Results showed that both interference effects and disorder-specific (i.e., group-specific) effects could be detected, based on behavioral RTs, cortical hemodynamic signals (brain correlates), and heart rate variability (cardiac correlates). Subjects with high compared to low subclinical psychotic symptoms revealed significantly reduced amplitudes in dorsolateral prefrontal cortices (interference effect, p < 0.001) and middle temporal gyrus (disorder-specific group effect, p < 0.001), supported by behavioral and heart rate results. The present findings indicate that distributional analyses methods can support the detection of emotional interference effects in the emotional Stroop. The results suggested that subjects with high subclinical psychosis exhibit enhanced emotional interference effects. Based on these observations, subclinical psychosis may therefore prove to represent a valid extension of the clinical psychosis phenotype. PMID:27660608

Distribution of Response Time, Cortical, and Cardiac Correlates during Emotional Interference in Persons with Subclinical Psychotic Symptoms.

PubMed

Holper, Lisa K B; Aleksandrowicz, Alekandra; Müller, Mario; Ajdacic-Gross, Vladeta; Haker, Helene; Fallgatter, Andreas J; Hagenmuller, Florence; Kawohl, Wolfram; Rössler, Wulf

2016-01-01

A psychosis phenotype can be observed below the threshold of clinical detection. The study aimed to investigate whether subclinical psychotic symptoms are associated with deficits in controlling emotional interference, and whether cortical brain and cardiac correlates of these deficits can be detected using functional near-infrared spectroscopy (fNIRS). A data set derived from a community sample was obtained from the Zurich Program for Sustainable Development of Mental Health Services. 174 subjects (mean age 29.67 ± 6.41, 91 females) were assigned to four groups ranging from low to high levels of subclinical psychotic symptoms (derived from the Symptom Checklist-90-R). Emotional interference was assessed using the emotional Stroop task comprising neutral, positive, and negative conditions. Statistical distributional methods based on delta plots [behavioral response time (RT) data] and quantile analysis (fNIRS data) were applied to evaluate the emotional interference effects. Results showed that both interference effects and disorder-specific (i.e., group-specific) effects could be detected, based on behavioral RTs, cortical hemodynamic signals (brain correlates), and heart rate variability (cardiac correlates). Subjects with high compared to low subclinical psychotic symptoms revealed significantly reduced amplitudes in dorsolateral prefrontal cortices (interference effect, p < 0.001) and middle temporal gyrus (disorder-specific group effect, p < 0.001), supported by behavioral and heart rate results. The present findings indicate that distributional analyses methods can support the detection of emotional interference effects in the emotional Stroop. The results suggested that subjects with high subclinical psychosis exhibit enhanced emotional interference effects. Based on these observations, subclinical psychosis may therefore prove to represent a valid extension of the clinical psychosis phenotype.

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

NASA Astrophysics Data System (ADS)

Pavlov, A. V.

2016-08-01

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

Influence of Fiber Bragg Grating Spectrum Degradation on the Performance of Sensor Interrogation Algorithms

PubMed Central

Lamberti, Alfredo; Vanlanduit, Steve; De Pauw, Ben; Berghmans, Francis

2014-01-01

The working principle of fiber Bragg grating (FBG) sensors is mostly based on the tracking of the Bragg wavelength shift. To accomplish this task, different algorithms have been proposed, from conventional maximum and centroid detection algorithms to more recently-developed correlation-based techniques. Several studies regarding the performance of these algorithms have been conducted, but they did not take into account spectral distortions, which appear in many practical applications. This paper addresses this issue and analyzes the performance of four different wavelength tracking algorithms (maximum detection, centroid detection, cross-correlation and fast phase-correlation) when applied to distorted FBG spectra used for measuring dynamic loads. Both simulations and experiments are used for the analyses. The dynamic behavior of distorted FBG spectra is simulated using the transfer-matrix approach, and the amount of distortion of the spectra is quantified using dedicated distortion indices. The algorithms are compared in terms of achievable precision and accuracy. To corroborate the simulation results, experiments were conducted using three FBG sensors glued on a steel plate and subjected to a combination of transverse force and vibration loads. The analysis of the results showed that the fast phase-correlation algorithm guarantees the best combination of versatility, precision and accuracy. PMID:25521386

Damage detection and isolation via autocorrelation: a step toward passive sensing

NASA Astrophysics Data System (ADS)

Chang, Y. S.; Yuan, F. G.

2018-03-01

Passive sensing technique may eliminate the need of expending power from actuators and thus provide a means of developing a compact and simple structural health monitoring system. More importantly, it may provide a solution for monitoring the aircraft subjected to environmental loading from air flow during operation. In this paper, a non-contact auto-correlation based technique is exploited as a feasibility study for passive sensing application to detect damage and isolate the damage location. Its theoretical basis bears some resemblance to reconstructing Green's function from diffusive wavefield through cross-correlation. Localized high pressure air from air compressor are randomly and continuously applied on the one side surface of the aluminum panels through the air blow gun. A laser Doppler vibrometer (LDV) was used to scan a 90 mm × 90 mm area to create a 6 × 6 2D-array signals from the opposite side of the panels. The scanned signals were auto-correlated to reconstruct a "selfimpulse response" (or Green's function). The premise for stably reconstructing the accurate Green's function requires long sensing times. For a 609.6 mm × 609.6 mm flat aluminum panel, the sensing times roughly at least four seconds is sufficient to establish converged Green's function through correlation. For the integral stiffened aluminum panel, the geometrical features of the panel expedite the formation of the diffusive wavefield and thus shorten the sensing times. The damage is simulated by gluing a magnet onto the panels. Reconstructed Green's functions (RGFs) are used for damage detection and damage isolation based on an imaging condition with mean square deviation of the RGFs from the pristine and the damaged structure and the results are shown in color maps. The auto-correlation based technique is shown to consistently detect the simulated damage, image and isolate the damage in the structure subjected to high pressure air excitation. This technique may be transformed into passive sensing applied on the aircraft during operation.

Leak Detection and Location of Water Pipes Using Vibration Sensors and Modified ML Prefilter.

PubMed

Choi, Jihoon; Shin, Joonho; Song, Choonggeun; Han, Suyong; Park, Doo Il

2017-09-13

This paper proposes a new leak detection and location method based on vibration sensors and generalised cross-correlation techniques. Considering the estimation errors of the power spectral densities (PSDs) and the cross-spectral density (CSD), the proposed method employs a modified maximum-likelihood (ML) prefilter with a regularisation factor. We derive a theoretical variance of the time difference estimation error through summation in the discrete-frequency domain, and find the optimal regularisation factor that minimises the theoretical variance in practical water pipe channels. The proposed method is compared with conventional correlation-based techniques via numerical simulations using a water pipe channel model, and it is shown through field measurement that the proposed modified ML prefilter outperforms conventional prefilters for the generalised cross-correlation. In addition, we provide a formula to calculate the leak location using the time difference estimate when different types of pipes are connected.

Leak Detection and Location of Water Pipes Using Vibration Sensors and Modified ML Prefilter

PubMed Central

Shin, Joonho; Song, Choonggeun; Han, Suyong; Park, Doo Il

2017-01-01

This paper proposes a new leak detection and location method based on vibration sensors and generalised cross-correlation techniques. Considering the estimation errors of the power spectral densities (PSDs) and the cross-spectral density (CSD), the proposed method employs a modified maximum-likelihood (ML) prefilter with a regularisation factor. We derive a theoretical variance of the time difference estimation error through summation in the discrete-frequency domain, and find the optimal regularisation factor that minimises the theoretical variance in practical water pipe channels. The proposed method is compared with conventional correlation-based techniques via numerical simulations using a water pipe channel model, and it is shown through field measurement that the proposed modified ML prefilter outperforms conventional prefilters for the generalised cross-correlation. In addition, we provide a formula to calculate the leak location using the time difference estimate when different types of pipes are connected. PMID:28902154

Rapid Isolation and Detection for RNA Biomarkers for TBI Diagnostics

DTIC Science & Technology

2015-10-01

V., Grape and wine sensory attributes correlate with pattern- based discrimination of Cabernet Sauvignon wines by a peptidic sensor array, Tetrahedron... wine samples. Partial Least Squares Regression (PLSR) was used for the correlation of wine sensory attributes to the peptide-based receptor...responses. Data analysis was done using the software XLSTAT Addinsoft, NewYork) and R.Absorbance values due to wine without the sensing ensembles were

Improved Resolution and Reduced Clutter in Ultra-Wideband Microwave Imaging Using Cross-Correlated Back Projection: Experimental and Numerical Results

PubMed Central

Jacobsen, S.; Birkelund, Y.

2010-01-01

Microwave breast cancer detection is based on the dielectric contrast between healthy and malignant tissue. This radar-based imaging method involves illumination of the breast with an ultra-wideband pulse. Detection of tumors within the breast is achieved by some selected focusing technique. Image formation algorithms are tailored to enhance tumor responses and reduce early-time and late-time clutter associated with skin reflections and heterogeneity of breast tissue. In this contribution, we evaluate the performance of the so-called cross-correlated back projection imaging scheme by using a scanning system in phantom experiments. Supplementary numerical modeling based on commercial software is also presented. The phantom is synthetically scanned with a broadband elliptical antenna in a mono-static configuration. The respective signals are pre-processed by a data-adaptive RLS algorithm in order to remove artifacts caused by antenna reverberations and signal clutter. Successful detection of a 7 mm diameter cylindrical tumor immersed in a low permittivity medium was achieved in all cases. Selecting the widely used delay-and-sum (DAS) beamforming algorithm as a benchmark, we show that correlation based imaging methods improve the signal-to-clutter ratio by at least 10 dB and improves spatial resolution through a reduction of the imaged peak full-width half maximum (FWHM) of about 40–50%. PMID:21331362

Improved resolution and reduced clutter in ultra-wideband microwave imaging using cross-correlated back projection: experimental and numerical results.

PubMed

Jacobsen, S; Birkelund, Y

2010-01-01

Microwave breast cancer detection is based on the dielectric contrast between healthy and malignant tissue. This radar-based imaging method involves illumination of the breast with an ultra-wideband pulse. Detection of tumors within the breast is achieved by some selected focusing technique. Image formation algorithms are tailored to enhance tumor responses and reduce early-time and late-time clutter associated with skin reflections and heterogeneity of breast tissue. In this contribution, we evaluate the performance of the so-called cross-correlated back projection imaging scheme by using a scanning system in phantom experiments. Supplementary numerical modeling based on commercial software is also presented. The phantom is synthetically scanned with a broadband elliptical antenna in a mono-static configuration. The respective signals are pre-processed by a data-adaptive RLS algorithm in order to remove artifacts caused by antenna reverberations and signal clutter. Successful detection of a 7 mm diameter cylindrical tumor immersed in a low permittivity medium was achieved in all cases. Selecting the widely used delay-and-sum (DAS) beamforming algorithm as a benchmark, we show that correlation based imaging methods improve the signal-to-clutter ratio by at least 10 dB and improves spatial resolution through a reduction of the imaged peak full-width half maximum (FWHM) of about 40-50%.

Pipeline Processing With an Iterative, Context-Based Detection Model

DTIC Science & Technology

2015-04-19

pattern detectors , correlation detectors , subspace detectors , matched field detectors , nuclear explosion monitoring 16. SECURITY CLASSIFICATION OF: 17...38 13. 3 days of SPAO-BHZ data which is dominated by signals from nearby icequakes. .... 39 14. (Top) 94 detections produced by detector ...92532 and (bottom) 148 detections from detector 92541 produced during the first run of the framework. .................................. 40 15. The 49

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.

Expert systems for automated correlation and interpretation of wireline logs

USGS Publications Warehouse

Olea, R.A.

1994-01-01

CORRELATOR is an interactive computer program for lithostratigraphic correlation of wireline logs able to store correlations in a data base with a consistency, accuracy, speed, and resolution that are difficult to obtain manually. The automatic determination of correlations is based on the maximization of a weighted correlation coefficient using two wireline logs per well. CORRELATOR has an expert system to scan and flag incongruous correlations in the data base. The user has the option to accept or disregard the advice offered by the system. The expert system represents knowledge through production rules. The inference system is goal-driven and uses backward chaining to scan through the rules. Work in progress is used to illustrate the potential that a second expert system with a similar architecture for interpreting dip diagrams could have to identify episodes-as those of interest in sequence stratigraphy and fault detection- and annotate them in the stratigraphic column. Several examples illustrate the presentation. ?? 1994 International Association for Mathematical Geology.

I Environmental DNA sampling is more sensitive than a traditional survey technique for detecting an aquatic invader.

PubMed

Smart, Adam S; Tingley, Reid; Weeks, Andrew R; van Rooyen, Anthony R; McCarthy, Michael A

2015-10-01

Effective management of alien species requires detecting populations in the early stages of invasion. Environmental DNA (eDNA) sampling can detect aquatic species at relatively low densities, but few studies have directly compared detection probabilities of eDNA sampling with those of traditional sampling methods. We compare the ability of a traditional sampling technique (bottle trapping) and eDNA to detect a recently established invader, the smooth newt Lissotriton vulgaris vulgaris, at seven field sites in Melbourne, Australia. Over a four-month period, per-trap detection probabilities ranged from 0.01 to 0.26 among sites where L. v. vulgaris was detected, whereas per-sample eDNA estimates were much higher (0.29-1.0). Detection probabilities of both methods varied temporally (across days and months), but temporal variation appeared to be uncorrelated between methods. Only estimates of spatial variation were strongly correlated across the two sampling techniques. Environmental variables (water depth, rainfall, ambient temperature) were not clearly correlated with detection probabilities estimated via trapping, whereas eDNA detection probabilities were negatively correlated with water depth, possibly reflecting higher eDNA concentrations at lower water levels. Our findings demonstrate that eDNA sampling can be an order of magnitude more sensitive than traditional methods, and illustrate that traditional- and eDNA-based surveys can provide independent information on species distributions when occupancy surveys are conducted over short timescales.

Quantifying the range of cross-correlated fluctuations using a q- L dependent AHXA coefficient

NASA Astrophysics Data System (ADS)

Wang, Fang; Wang, Lin; Chen, Yuming

2018-03-01

Recently, based on analogous height cross-correlation analysis (AHXA), a cross-correlation coefficient ρ×(L) has been proposed to quantify the levels of cross-correlation on different temporal scales for bivariate series. A limitation of this coefficient is that it cannot capture the full information of cross-correlations on amplitude of fluctuations. In fact, it only detects the cross-correlation at a specific order fluctuation, which might neglect some important information inherited from other order fluctuations. To overcome this disadvantage, in this work, based on the scaling of the qth order covariance and time delay L, we define a two-parameter dependent cross-correlation coefficient ρq(L) to detect and quantify the range and level of cross-correlations. This new version of ρq(L) coefficient leads to the formation of a ρq(L) surface, which not only is able to quantify the level of cross-correlations, but also allows us to identify the range of fluctuation amplitudes that are correlated in two given signals. Applications to the classical ARFIMA models and the binomial multifractal series illustrate the feasibility of this new coefficient ρq(L) . In addition, a statistical test is proposed to quantify the existence of cross-correlations between two given series. Applying our method to the real life empirical data from the 1999-2000 California electricity market, we find that the California power crisis in 2000 destroys the cross-correlation between the price and the load series but does not affect the correlation of the load series during and before the crisis.

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.

Detection of moisture and moisture related phenomena from Skylab. [Texas and Kansas

NASA Technical Reports Server (NTRS)

Eagleman, J. R. (Principal Investigator); Lin, W. C.

1974-01-01

The author has identified the following significant results. The high correlations between radiometric temperature and soil moisture content are shown to remain quite high for independent footprints of the S194 sensor. Since an analysis based on overlapping footprints had previously been reported with a high correlation, it was necessary to verify that the correlation did not arise from dependent data.

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

USGS Publications Warehouse

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

2012-01-01

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

Application of the differentiation process into the correlation-based leak detection in urban pipeline networks

NASA Astrophysics Data System (ADS)

Gao, Yan; Liu, Yuyou; Ma, Yifan; Cheng, Xiaobin; Yang, Jun

2018-11-01

One major challenge currently facing pipeline networks across the world is the improvement of leak detection technologies in urban environments. There is an imperative to locate accurately leaks in buried water pipes to avoid serious environmental, social and economic consequences. Much attention has been paid to time delay estimation (TDE) in determining the position of a leak by utilising cross-correlation, which has been proven to be effective with varying degrees of success over the past half century. Previous research in published literature has demonstrated the effectiveness of the pre-whitening process for accentuating the peak in the cross-correlation associated with the time delay. This paper is concerned with the implementation of the differentiation process for TDE, with particular focus on the problem of determining a leak in pipelines by means of pipe pressure measurements. Rather than the pre-whitening operation, the proposed cross-correlation via the differentiation process, termed here DIF, changes the characteristics of the pipe system so that the pipe effectively acts as a band-pass filter. This method has the potential to eliminate some ambiguity caused by the interference at low frequencies and to allow more high frequency information to pass. Given an appropriate differentiation order, a more pronounced and reliable peak is obtained in the cross-correlation result. The use of differentiation process may provide a viable cross-correlation method suited to water leak detection. Its performance in relation to leak detection is further compared to the basic cross-correlation and pre-whitening methods for TDE in detecting a leak from actual PVC water pipes. Experimental results are presented to show an additional property of the DIF compensating for the resonance effects that may exist in cross-spectral density measurements, and hence better performance for TDE.

Radar mechanocardiography: a novel analysis of the mechanical behavior of the heart.

PubMed

Tavakolian, Kouhyar; Zadeh, Faranak M; Chuo, Yindar; Siu, Tiffany; Vaseghi, Ali; Kaminska, Bozena

2008-01-01

In this paper a novel system for detection of the mechanical movement of heart, mechanocardiography (MCG), with no connection to the subject's body is presented. This signal is based on radar technology. The acquired signal is highly correlated to the acceleration-based ballistocardiograph signal (BCG) recorded directly from the sternum. It is shown that the heart and breathing rates can be reliably detected using this system.

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

Multi-Object Tracking with Correlation Filter for Autonomous Vehicle.

PubMed

Zhao, Dawei; Fu, Hao; Xiao, Liang; Wu, Tao; Dai, Bin

2018-06-22

Multi-object tracking is a crucial problem for autonomous vehicle. Most state-of-the-art approaches adopt the tracking-by-detection strategy, which is a two-step procedure consisting of the detection module and the tracking module. In this paper, we improve both steps. We improve the detection module by incorporating the temporal information, which is beneficial for detecting small objects. For the tracking module, we propose a novel compressed deep Convolutional Neural Network (CNN) feature based Correlation Filter tracker. By carefully integrating these two modules, the proposed multi-object tracking approach has the ability of re-identification (ReID) once the tracked object gets lost. Extensive experiments were performed on the KITTI and MOT2015 tracking benchmarks. Results indicate that our approach outperforms most state-of-the-art tracking approaches.

Correlation between He-Ne scatter and 2.7-microm pulsed laser damage at coating defects.

PubMed

Porteus, J O; Spiker, C J; Franck, J B

1986-11-01

A reported correlation between defect-initiated pulsed laser damage and local predamage scatter in multilayer infrared mirror coatings has been analyzed in detail. Examination of a much larger data base confirms the previous result on dielectric-enhanced reflectors with polished substrates over a wide range of energy densities above the damage onset. Scatter signals from individual undamaged defects were detected using a He-Ne scatter probe with a focal spot that nearly coincides with the 150-microm-diam (D1/e(2)) focal spot of the damage-probe beam. Subsequent damage frequency measurements (1-on-1) were made near normal or at 45 degrees incidence with 100-ns pulses at 2.7-microm wavelength. The correlation is characterized by an increase in damage frequency with increasing predamage scatter signal and by equivalence of the defect densities indicated by the two probes. Characteristics of the correlation are compared with a simple model based on focal spot intensity profiles. Conditions that limit correlation are discussed, including variable scatter from defects and background scatter from diamond-turned substrates. Results have implication for nondestructive defect detection and coating quality control.

Experiments in Coherent Change Detection for Synthetic Aperture Sonar

DTIC Science & Technology

2010-06-01

data from synthetic aperture sonars mounted on autonomous undersea ve- hicles and actively navigated tow bodies. A noncoherent example carried out...III of this paper describe approaches for au- tomatic change detection and introduces CCD. Section IV pro- vides an example of noncoherent change...registration insufficiently robust to support correlation-based change detection (whether cohe- rent or noncoherent ). Fig. 6. Baseline (a) and

Cest Analysis: Automated Change Detection from Very-High Remote Sensing Images

NASA Astrophysics Data System (ADS)

Ehlers, M.; Klonus, S.; Jarmer, T.; Sofina, N.; Michel, U.; Reinartz, P.; Sirmacek, B.

2012-08-01

A fast detection, visualization and assessment of change in areas of crisis or catastrophes are important requirements for coordination and planning of help. Through the availability of new satellites and/or airborne sensors with very high spatial resolutions (e.g., WorldView, GeoEye) new remote sensing data are available for a better detection, delineation and visualization of change. For automated change detection, a large number of algorithms has been proposed and developed. From previous studies, however, it is evident that to-date no single algorithm has the potential for being a reliable change detector for all possible scenarios. This paper introduces the Combined Edge Segment Texture (CEST) analysis, a decision-tree based cooperative suite of algorithms for automated change detection that is especially designed for the generation of new satellites with very high spatial resolution. The method incorporates frequency based filtering, texture analysis, and image segmentation techniques. For the frequency analysis, different band pass filters can be applied to identify the relevant frequency information for change detection. After transforming the multitemporal images via a fast Fourier transform (FFT) and applying the most suitable band pass filter, different methods are available to extract changed structures: differencing and correlation in the frequency domain and correlation and edge detection in the spatial domain. Best results are obtained using edge extraction. For the texture analysis, different 'Haralick' parameters can be calculated (e.g., energy, correlation, contrast, inverse distance moment) with 'energy' so far providing the most accurate results. These algorithms are combined with a prior segmentation of the image data as well as with morphological operations for a final binary change result. A rule-based combination (CEST) of the change algorithms is applied to calculate the probability of change for a particular location. CEST was tested with high-resolution satellite images of the crisis areas of Darfur (Sudan). CEST results are compared with a number of standard algorithms for automated change detection such as image difference, image ratioe, principal component analysis, delta cue technique and post classification change detection. The new combined method shows superior results averaging between 45% and 15% improvement in accuracy.

Long-range correlation and market segmentation in bond market

NASA Astrophysics Data System (ADS)

Wang, Zhongxing; Yan, Yan; Chen, Xiaosong

2017-09-01

This paper investigates the long-range auto-correlations and cross-correlations in bond market. Based on Detrended Moving Average (DMA) method, empirical results present a clear evidence of long-range persistence that exists in one year scale. The degree of long-range correlation related to maturities has an upward tendency with a peak in short term. These findings confirm the expectations of fractal market hypothesis (FMH). Furthermore, we have developed a method based on a complex network to study the long-range cross-correlation structure and applied it to our data, and found a clear pattern of market segmentation in the long run. We also detected the nature of long-range correlation in the sub-period 2007-2012 and 2011-2016. The result from our research shows that long-range auto-correlations are decreasing in the recent years while long-range cross-correlations are strengthening.

The Effects of Observation and Intervention on the Judgment of Causal and Correlational Relationships

DTIC Science & Technology

2009-07-28

further referred to as normative models of causation. A second type of model, which are based on Pavlovian classical conditioning , is associative... conditions of high cognitive load), the likelihood of the accuracy of the perception is compromised. If an inaccurate perception translates to an inaccurate...correlation and causation detection in specific military operations and under conditions of operational stress. Background Models of correlation

Aircraft target detection algorithm based on high resolution spaceborne SAR imagery

NASA Astrophysics Data System (ADS)

Zhang, Hui; Hao, Mengxi; Zhang, Cong; Su, Xiaojing

2018-03-01

In this paper, an image classification algorithm for airport area is proposed, which based on the statistical features of synthetic aperture radar (SAR) images and the spatial information of pixels. The algorithm combines Gamma mixture model and MRF. The algorithm using Gamma mixture model to obtain the initial classification result. Pixel space correlation based on the classification results are optimized by the MRF technique. Additionally, morphology methods are employed to extract airport (ROI) region where the suspected aircraft target samples are clarified to reduce the false alarm and increase the detection performance. Finally, this paper presents the plane target detection, which have been verified by simulation test.

Learning curve of office-based ultrasonography for rotator cuff tendons tears.

PubMed

Ok, Ji-Hoon; Kim, Yang-Soo; Kim, Jung-Man; Yoo, Tae-Wook

2013-07-01

To compare the accuracy of ultrasonography and MR arthrography (MRA) imaging in detecting of rotator cuff tears with arthroscopic finding used as the reference standard. The ultrasonography and MRA findings of 51 shoulders that underwent the arthroscopic surgery were prospectively analysed. Two orthopaedic doctors independently performed ultrasonography and interpreted the findings at the office. The tear size measured at ultrasonography and MRA was compared with the size measured at surgery using Pearson correlation coefficients (r). The sensitivity, specificity, accuracy, positive predictive value, negative predictive value and false-positive rate were calculated for a diagnosis of partial-and full-thickness rotator cuff tears. The kappa coefficient was calculated to verify the inter-observer agreement. The sensitivity of ultrasonography and MRA for detecting partial-thickness tears was 45.5 and 72.7 %, and that for full-thickness tears was 80.0 and 100 %, respectively. The accuracy of ultrasonograpy and MRA for detecting partial-thickness tears was 45.1 and 88.2 %, and that for full-thickness tears was 82.4 and 98 %, respectively. Tear size measured based on ultrasonography examination showed a poor correlation with the size measured at arthroscopic surgery (r = 0.21; p < 0.05). However, tear size estimated by MRA showed a strong correlation (r = 0.75; p < 0.05). The kappa coefficient was 0.47 between the two independent examiners. The accuracy of office-based ultrasonography for beginner orthopaedic surgeons to detect full-thickness rotator cuff tears was comparable to that of MRA but was less accurate for detecting partial-thickness tears and torn size measurement. Inter-observer agreement on the interpretation was fair. These results highlight the importance of the correct technique and experience in operation of ultrasonography in shoulder joint. Diagnostic study, Level II.

Ontology-aided feature correlation for multi-modal urban sensing

NASA Astrophysics Data System (ADS)

Misra, Archan; Lantra, Zaman; Jayarajah, Kasthuri

2016-05-01

The paper explores the use of correlation across features extracted from different sensing channels to help in urban situational understanding. We use real-world datasets to show how such correlation can improve the accuracy of detection of city-wide events by combining metadata analysis with image analysis of Instagram content. We demonstrate this through a case study on the Singapore Haze. We show that simple ontological relationships and reasoning can significantly help in automating such correlation-based understanding of transient urban events.

Correlating subcortical interhemispheric connectivity and cortical hemispheric dominance in brain tumor patients: A repetitive navigated transcranial magnetic stimulation study.

PubMed

Sollmann, Nico; Ille, Sebastian; Tussis, Lorena; Maurer, Stefanie; Hauck, Theresa; Negwer, Chiara; Bauer, Jan S; Ringel, Florian; Meyer, Bernhard; Krieg, Sandro M

2016-02-01

The present study aims to investigate the relationship between transcallosal interhemispheric connectivity (IC) and hemispheric language lateralization by using a novel approach including repetitive navigated transcranial magnetic stimulation (rTMS), hemispheric dominance ratio (HDR) calculation, and rTMS-based diffusion tensor imaging fiber tracking (DTI FT). 31 patients with left-sided perisylvian brain lesions underwent diffusion tensor imaging (DTI) and rTMS language mapping. Cortical language-positive rTMS spots were used to calculate HDRs (HDR: quotient of the left-sided divided by right-sided naming error rates for corresponding left- and right-sided cortical regions) and to create regions of interest (ROIs) for DTI FT. Then, fibers connecting the rTMS-based ROIs of both hemispheres were tracked, and the correlation of IC to HDRs was calculated via Spearman's rank correlation coefficient (rs). Fibers connecting rTMS-based ROIs of both hemispheres were detected in 12 patients (38.7%). Within the patients in which IC was detected, the mean number of subcortical IC fibers ± standard deviation (SD) was 138.0 ± 346.5 (median: 7.5; range: 1-1,217 fibers). Regarding rs for the correlation of HDRs and fiber numbers of patients that showed IC, only moderate correlation was revealed. Our approach might be beneficial and technically feasible for further investigation of the relationship between IC and language lateralization. However, only moderate correlation was revealed in the present study. Copyright © 2015 Elsevier B.V. All rights reserved.

Mindfulness-based stress reduction teachers, practice characteristics, cancer incidence, and health: a nationwide ecological description.

PubMed

Robb, Sara Wagner; Benson, Kelsey; Middleton, Lauren; Meyers, Christine; Hébert, James R

2015-02-14

Studies have demonstrated the potential of the Mindfulness-Based Stress Reduction (MBSR) program to improve the condition of individuals with health outcomes such as hypertension, diabetes, and chronic pain; improve psychological well-being; reduce stress levels; and increase survival among cancer patients. To date, only one study has focused on the effect of long-term meditation on stress, showing a positive protective relationship. However, the relationship between meditation and cancer incidence remains unexplored. The objective of this study was to describe the state-level relationship between MBSR instructors and their practices and county-level health outcomes, including cancer incidence, in the United States. This ecologic study was performed using geospatial mapping and descriptive epidemiology of statewide MBSR characteristics and overall health, mental health state rankings, and age-adjusted cancer incidence rates. Weak to moderate state-level correlations between meditation characteristics and colorectal and cervical cancer incidence were detected, with states with more meditation (e.g., more MBSR teachers per population) correlated with a decreased cancer incidence. A negative correlation was detected between lung & bronchus cancer and years teaching MBSR only. Moderate positive correlations were detected between Hodgkin's Lymphoma and female breast cancer in relation to all meditation characteristics. Statistically significant correlations with moderate coefficients were detected for overall health ranks and all meditation characteristics, most strongly for total number of years teaching MBSR and total number of years of general meditation practice. Our analyses might suggest that a relationship exists between the total number of MBSR teachers per state and the total number of years of general meditation practice per state, and colorectal and cervical cancer incidence. Positive correlations were observed with overall health rankings. Despite this study's limitations, its findings could serve to generate hypotheses and to inform and motivate a new focus on meditation and stress reduction in relation to cancer incidence, with specific relevance to colorectal and cervical cancer.

Noise reduction algorithm with the soft thresholding based on the Shannon entropy and bone-conduction speech cross- correlation bands.

PubMed

Na, Sung Dae; Wei, Qun; Seong, Ki Woong; Cho, Jin Ho; Kim, Myoung Nam

2018-01-01

The conventional methods of speech enhancement, noise reduction, and voice activity detection are based on the suppression of noise or non-speech components of the target air-conduction signals. However, air-conduced speech is hard to differentiate from babble or white noise signals. To overcome this problem, the proposed algorithm uses the bone-conduction speech signals and soft thresholding based on the Shannon entropy principle and cross-correlation of air- and bone-conduction signals. A new algorithm for speech detection and noise reduction is proposed, which makes use of the Shannon entropy principle and cross-correlation with the bone-conduction speech signals to threshold the wavelet packet coefficients of the noisy speech. The proposed method can be get efficient result by objective quality measure that are PESQ, RMSE, Correlation, SNR. Each threshold is generated by the entropy and cross-correlation approaches in the decomposed bands using the wavelet packet decomposition. As a result, the noise is reduced by the proposed method using the MATLAB simulation. To verify the method feasibility, we compared the air- and bone-conduction speech signals and their spectra by the proposed method. As a result, high performance of the proposed method is confirmed, which makes it quite instrumental to future applications in communication devices, noisy environment, construction, and military operations.

A comparison of five approaches to measurement of anatomic knee alignment from radiographs.

PubMed

McDaniel, G; Mitchell, K L; Charles, C; Kraus, V B

2010-02-01

The recent recognition of the correlation of the hip-knee-ankle angle (HKA) with femur-tibia angle (FTA) on a standard knee radiograph has led to the increasing inclusion of FTA assessments in OA studies due to its clinical relevance, cost effectiveness and minimal radiation exposure. Our goal was to investigate the performance metrics of currently used methods of FTA measurement to determine whether a specific protocol could be recommended based on these results. Inter- and intra-rater reliability of FTA measurements were determined by intraclass correlation coefficient (ICC) of two independent analysts. Minimal detectable differences were determined and the correlation of FTA and HKA was analyzed by linear regression. Differences among methods of measuring HKA were assessed by ANOVA. All five methods of FTA measurement demonstrated high precision by inter- and intra-rater reproducibility (ICCs>or=0.93). All five methods displayed good accuracy, but after correction for the offset of FTA from HKA, the femoral notch landmark method was the least accurate. However, the methods differed according to their minimal detectable differences; the FTA methods utilizing the center of the base of the tibial spines or the center of the tibial plateau as knee center landmarks yielded the smallest minimal detectable differences (1.25 degrees and 1.72 degrees, respectively). All methods of FTA were highly reproducible, but varied in their accuracy and sensitivity to detect meaningful differences. Based on these parameters we recommend standardizing measurement angles with vertices at the base of the tibial spines or the center of the tibia and comparing single-point and two-point methods in larger studies. Copyright 2009 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

Profiling of adrenocorticotropic hormone and arginine vasopressin in human pituitary gland and tumor thin tissue sections using droplet-based liquid-microjunction surface-sampling-HPLC–ESI-MS–MS

DOE PAGES

Kertesz, Vilmos; Calligaris, David; Feldman, Daniel R.; ...

2015-06-18

Described here are the results from the profiling of the proteins arginine vasopressin (AVP) and adrenocorticotropic hormone (ACTH) from normal human pituitary gland and pituitary adenoma tissue sections using a fully automated droplet-based liquid microjunction surface sampling-HPLC-ESI-MS/MS system for spatially resolved sampling, HPLC separation, and mass spectral detection. Excellent correlation was found between the protein distribution data obtained with this droplet-based liquid microjunction surface sampling-HPLC-ESI-MS/MS system and those data obtained with matrix assisted laser desorption ionization (MALDI) chemical imaging analyses of serial sections of the same tissue. The protein distributions correlated with the visible anatomic pattern of the pituitary gland.more » AVP was most abundant in the posterior pituitary gland region (neurohypophysis) and ATCH was dominant in the anterior pituitary gland region (adenohypophysis). The relative amounts of AVP and ACTH sampled from a series of ACTH secreting and non-secreting pituitary adenomas correlated with histopathological evaluation. ACTH was readily detected at significantly higher levels in regions of ACTH secreting adenomas and in normal anterior adenohypophysis compared to non-secreting adenoma and neurohypophysis. AVP was mostly detected in normal neurohypophysis as anticipated. This work demonstrates that a fully automated droplet-based liquid microjunction surface sampling system coupled to HPLC-ESI-MS/MS can be readily used for spatially resolved sampling, separation, detection, and semi-quantitation of physiologically-relevant peptide and protein hormones, such as AVP and ACTH, directly from human tissue. In addition, the relative simplicity, rapidity and specificity of the current methodology support the potential of this basic technology with further advancement for assisting surgical decision-making.« less

Profiling of adrenocorticotropic hormone and arginine vasopressin in human pituitary gland and tumor thin tissue sections using droplet-based liquid-microjunction surface-sampling-HPLC-ESI-MS-MS.

PubMed

Kertesz, Vilmos; Calligaris, David; Feldman, Daniel R; Changelian, Armen; Laws, Edward R; Santagata, Sandro; Agar, Nathalie Y R; Van Berkel, Gary J

2015-08-01

Described here are the results from the profiling of the proteins arginine vasopressin (AVP) and adrenocorticotropic hormone (ACTH) from normal human pituitary gland and pituitary adenoma tissue sections, using a fully automated droplet-based liquid-microjunction surface-sampling-HPLC-ESI-MS-MS system for spatially resolved sampling, HPLC separation, and mass spectrometric detection. Excellent correlation was found between the protein distribution data obtained with this method and data obtained with matrix-assisted laser desorption/ionization (MALDI) chemical imaging analyses of serial sections of the same tissue. The protein distributions correlated with the visible anatomic pattern of the pituitary gland. AVP was most abundant in the posterior pituitary gland region (neurohypophysis), and ATCH was dominant in the anterior pituitary gland region (adenohypophysis). The relative amounts of AVP and ACTH sampled from a series of ACTH-secreting and non-secreting pituitary adenomas correlated with histopathological evaluation. ACTH was readily detected at significantly higher levels in regions of ACTH-secreting adenomas and in normal anterior adenohypophysis compared with non-secreting adenoma and neurohypophysis. AVP was mostly detected in normal neurohypophysis, as expected. This work reveals that a fully automated droplet-based liquid-microjunction surface-sampling system coupled to HPLC-ESI-MS-MS can be readily used for spatially resolved sampling, separation, detection, and semi-quantitation of physiologically-relevant peptide and protein hormones, including AVP and ACTH, directly from human tissue. In addition, the relative simplicity, rapidity, and specificity of this method support the potential of this basic technology, with further advancement, for assisting surgical decision-making. Graphical Abstract Mass spectrometry based profiling of hormones in human pituitary gland and tumor thin tissue sections.

Profiling of adrenocorticotropic hormone and arginine vasopressin in human pituitary gland and tumor thin tissue sections using droplet-based liquid-microjunction surface-sampling-HPLC–ESI-MS–MS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kertesz, Vilmos; Calligaris, David; Feldman, Daniel R.

Described here are the results from the profiling of the proteins arginine vasopressin (AVP) and adrenocorticotropic hormone (ACTH) from normal human pituitary gland and pituitary adenoma tissue sections using a fully automated droplet-based liquid microjunction surface sampling-HPLC-ESI-MS/MS system for spatially resolved sampling, HPLC separation, and mass spectral detection. Excellent correlation was found between the protein distribution data obtained with this droplet-based liquid microjunction surface sampling-HPLC-ESI-MS/MS system and those data obtained with matrix assisted laser desorption ionization (MALDI) chemical imaging analyses of serial sections of the same tissue. The protein distributions correlated with the visible anatomic pattern of the pituitary gland.more » AVP was most abundant in the posterior pituitary gland region (neurohypophysis) and ATCH was dominant in the anterior pituitary gland region (adenohypophysis). The relative amounts of AVP and ACTH sampled from a series of ACTH secreting and non-secreting pituitary adenomas correlated with histopathological evaluation. ACTH was readily detected at significantly higher levels in regions of ACTH secreting adenomas and in normal anterior adenohypophysis compared to non-secreting adenoma and neurohypophysis. AVP was mostly detected in normal neurohypophysis as anticipated. This work demonstrates that a fully automated droplet-based liquid microjunction surface sampling system coupled to HPLC-ESI-MS/MS can be readily used for spatially resolved sampling, separation, detection, and semi-quantitation of physiologically-relevant peptide and protein hormones, such as AVP and ACTH, directly from human tissue. In addition, the relative simplicity, rapidity and specificity of the current methodology support the potential of this basic technology with further advancement for assisting surgical decision-making.« less

Processing methods for photoacoustic Doppler flowmetry with a clinical ultrasound scanner

NASA Astrophysics Data System (ADS)

Bücking, Thore M.; van den Berg, Pim J.; Balabani, Stavroula; Steenbergen, Wiendelt; Beard, Paul C.; Brunker, Joanna

2018-02-01

Photoacoustic flowmetry (PAF) based on time-domain cross correlation of photoacoustic signals is a promising technique for deep tissue measurement of blood flow velocity. Signal processing has previously been developed for single element transducers. Here, the processing methods for acoustic resolution PAF using a clinical ultrasound transducer array are developed and validated using a 64-element transducer array with a -6 dB detection band of 11 to 17 MHz. Measurements were performed on a flow phantom consisting of a tube (580 μm inner diameter) perfused with human blood flowing at physiological speeds ranging from 3 to 25 mm / s. The processing pipeline comprised: image reconstruction, filtering, displacement detection, and masking. High-pass filtering and background subtraction were found to be key preprocessing steps to enable accurate flow velocity estimates, which were calculated using a cross-correlation based method. In addition, the regions of interest in the calculated velocity maps were defined using a masking approach based on the amplitude of the cross-correlation functions. These developments enabled blood flow measurements using a transducer array, bringing PAF one step closer to clinical applicability.

Development of a chemiluminescence competitive PCR for the detection and quantification of parvovirus B19 DNA using a microplate luminometer.

PubMed

Fini, F; Gallinella, G; Girotti, S; Zerbini, M; Musiani, M

1999-09-01

Quantitative PCR of viral nucleic acids can be useful clinically in diagnosis, risk assessment, and monitoring of antiviral therapy. We wished to develop a chemiluminescence competitive PCR (cPCR) for parvovirus B19. Parvovirus DNA target sequences and competitor sequences were coamplified and directly labeled. Amplified products were then separately hybridized by specific biotin-labeled probes, captured onto streptavidin-coated ELISA microplates, and detected immunoenzymatically using chemiluminescent substrates of peroxidase. Chemiluminescent signals were quantitatively analyzed by a microplate luminometer and were correlated to the amounts of amplified products. Luminol-based systems displayed constant emission but had a higher detection limit (100-1000 genome copies) than the acridan-based system (20 genome copies). The detection limit of chemiluminescent substrates was lower (20 genome copies) than colorimetric substrates (50 genome copies). In chemiluminescence cPCR, the titration curves showed linear correlation above 100 target genome copies. Chemiluminescence cPCR was positive in six serum samples from patients with parvovirus infections and negative in six control sera. The chemiluminescence cPCR appears to be a sensitive and specific method for the quantitative detection of viral DNAs.

Design of infrasound-detection system via adaptive LMSTDE algorithm

NASA Technical Reports Server (NTRS)

Khalaf, C. S.; Stoughton, J. W.

1984-01-01

A proposed solution to an aviation safety problem is based on passive detection of turbulent weather phenomena through their infrasonic emission. This thesis describes a system design that is adequate for detection and bearing evaluation of infrasounds. An array of four sensors, with the appropriate hardware, is used for the detection part. Bearing evaluation is based on estimates of time delays between sensor outputs. The generalized cross correlation (GCC), as the conventional time-delay estimation (TDE) method, is first reviewed. An adaptive TDE approach, using the least mean square (LMS) algorithm, is then discussed. A comparison between the two techniques is made and the advantages of the adaptive approach are listed. The behavior of the GCC, as a Roth processor, is examined for the anticipated signals. It is shown that the Roth processor has the desired effect of sharpening the peak of the correlation function. It is also shown that the LMSTDE technique is an equivalent implementation of the Roth processor in the time domain. A LMSTDE lead-lag model, with a variable stability coefficient and a convergence criterion, is designed.

LLNL Location and Detection Research

DOE Office of Scientific and Technical Information (OSTI.GOV)

Myers, S C; Harris, D B; Anderson, M L

2003-07-16

We present two LLNL research projects in the topical areas of location and detection. The first project assesses epicenter accuracy using a multiple-event location algorithm, and the second project employs waveform subspace Correlation to detect and identify events at Fennoscandian mines. Accurately located seismic events are the bases of location calibration. A well-characterized set of calibration events enables new Earth model development, empirical calibration, and validation of models. In a recent study, Bondar et al. (2003) develop network coverage criteria for assessing the accuracy of event locations that are determined using single-event, linearized inversion methods. These criteria are conservative andmore » are meant for application to large bulletins where emphasis is on catalog completeness and any given event location may be improved through detailed analysis or application of advanced algorithms. Relative event location techniques are touted as advancements that may improve absolute location accuracy by (1) ensuring an internally consistent dataset, (2) constraining a subset of events to known locations, and (3) taking advantage of station and event correlation structure. Here we present the preliminary phase of this work in which we use Nevada Test Site (NTS) nuclear explosions, with known locations, to test the effect of travel-time model accuracy on relative location accuracy. Like previous studies, we find that the reference velocity-model and relative-location accuracy are highly correlated. We also find that metrics based on travel-time residual of relocated events are not a reliable for assessing either velocity-model or relative-location accuracy. In the topical area of detection, we develop specialized correlation (subspace) detectors for the principal mines surrounding the ARCES station located in the European Arctic. Our objective is to provide efficient screens for explosions occurring in the mines of the Kola Peninsula (Kovdor, Zapolyarny, Olenogorsk, Khibiny) and the major iron mines of northern Sweden (Malmberget, Kiruna). In excess of 90% of the events detected by the ARCES station are mining explosions, and a significant fraction are from these northern mining groups. The primary challenge in developing waveform correlation detectors is the degree of variation in the source time histories of the shots, which can result in poor correlation among events even in close proximity. Our approach to solving this problem is to use lagged subspace correlation detectors, which offer some prospect of compensating for variation and uncertainty in source time functions.« less

Integrator or Coincidence Detector: A Novel Measure Based on the Discrete Reverse Correlation to Determine a Neuron's Operational Mode.

PubMed

Kanev, Jacob; Koutsou, Achilleas; Christodoulou, Chris; Obermayer, Klaus

2016-10-01

In this letter, we propose a definition of the operational mode of a neuron, that is, whether a neuron integrates over its input or detects coincidences. We complete the range of possible operational modes by a new mode we call gap detection, which means that a neuron responds to gaps in its stimulus. We propose a measure consisting of two scalar values, both ranging from -1 to +1: the neural drive, which indicates whether its stimulus excites the neuron, serves as background noise, or inhibits it; the neural mode, which indicates whether the neuron's response is the result of integration over its input, of coincidence detection, or of gap detection; with all three modes possible for all neural drive values. This is a pure spike-based measure and can be applied to measure the influence of either all or subset of a neuron's stimulus. We derive the measure by decomposing the reverse correlation, test it in several artificial and biological settings, and compare it to other measures, finding little or no correlation between them. We relate the results of the measure to neural parameters and investigate the effect of time delay during spike generation. Our results suggest that a neuron can use several different modes simultaneously on different subsets of its stimulus to enable it to respond to its stimulus in a complex manner.

Studying Irony Detection Beyond Ironic Criticism: Let's Include Ironic Praise

PubMed Central

Bruntsch, Richard; Ruch, Willibald

2017-01-01

Studies of irony detection have commonly used ironic criticisms (i.e., mock positive evaluation of negative circumstances) as stimulus materials. Another basic type of verbal irony, ironic praise (i.e., mock negative evaluation of positive circumstances) is largely absent from studies on individuals' aptitude to detect verbal irony. However, it can be argued that ironic praise needs to be considered in order to investigate the detection of irony in the variety of its facets. To explore whether the detection ironic praise has a benefit beyond ironic criticism, three studies were conducted. In Study 1, an instrument (Test of Verbal Irony Detection Aptitude; TOVIDA) was constructed and its factorial structure was tested using N = 311 subjects. The TOVIDA contains 26 scenario-based items and contains two scales for the detection of ironic criticism vs. ironic praise. To validate the measurement method, the two scales of the TOVIDA were experimentally evaluated with N = 154 subjects in Study 2. In Study 3, N = 183 subjects were tested to explore personality and ability correlates of the two TOVIDA scales. Results indicate that the co-variance between the ironic TOVIDA items was organized by two inter-correlated but distinct factors: one representing ironic praise detection aptitude and one representing ironic criticism detection aptitude. Experimental validation showed that the TOVIDA items truly contain irony and that item scores reflect irony detection. Trait bad mood and benevolent humor (as a facet of the sense of humor) were found as joint correlates for both ironic criticism and ironic praise detection scores. In contrast, intelligence, trait cheerfulness, and corrective humor were found as unique correlates of ironic praise detection scores, even when statistically controlling for the aptitude to detect ironic criticism. Our results indicate that the aptitude to detect ironic praise can be seen as distinct from the aptitude to detect ironic criticism. Generating unique variance in irony detection, ironic praise can be postulated as worthwhile to include in future studies—especially when studying the role of mental ability, personality, and humor in irony detection. PMID:28484409

Cross-correlating Planck tSZ with RCSLenS weak lensing: implications for cosmology and AGN feedback

NASA Astrophysics Data System (ADS)

Hojjati, Alireza; Tröster, Tilman; Harnois-Déraps, Joachim; McCarthy, Ian G.; van Waerbeke, Ludovic; Choi, Ami; Erben, Thomas; Heymans, Catherine; Hildebrandt, Hendrik; Hinshaw, Gary; Ma, Yin-Zhe; Miller, Lance; Viola, Massimo; Tanimura, Hideki

2017-10-01

We present measurements of the spatial mapping between (hot) baryons and the total matter in the Universe, via the cross-correlation between the thermal Sunyaev-Zeldovich (tSZ) map from Planck and the weak gravitational lensing maps from the Red Cluster Sequence Lensing Survey (RCSLenS). The cross-correlations are performed on the map level where all the sources (including diffuse intergalactic gas) contribute to the signal. We consider two configuration-space correlation function estimators, ξy-κ and ξ ^ {y-γ t}, and a Fourier-space estimator, C_{ℓ}^{y-κ}, in our analysis. We detect a significant correlation out to 3° of angular separation on the sky. Based on statistical noise only, we can report 13σ and 17σ detections of the cross-correlation using the configuration-space y-κ and y-γt estimators, respectively. Including a heuristic estimate of the sampling variance yields a detection significance of 7σ and 8σ, respectively. A similar level of detection is obtained from the Fourier-space estimator, C_{ℓ}^{y-κ}. As each estimator probes different dynamical ranges, their combination improves the significance of the detection. We compare our measurements with predictions from the cosmo-OverWhelmingly Large Simulations suite of cosmological hydrodynamical simulations, where different galactic feedback models are implemented. We find that a model with considerable active galactic nuclei (AGN) feedback that removes large quantities of hot gas from galaxy groups and Wilkinson Microwave Anisotropy Probe 7-yr best-fitting cosmological parameters provides the best match to the measurements. All baryonic models in the context of a Planck cosmology overpredict the observed signal. Similar cosmological conclusions are drawn when we employ a halo model with the observed 'universal' pressure profile.

A hybrid method based on Band Pass Filter and Correlation Algorithm to improve debris sensor capacity

NASA Astrophysics Data System (ADS)

Hong, Wei; Wang, Shaoping; Liu, Haokuo; Tomovic, Mileta M.; Chao, Zhang

2017-01-01

The inductive debris detection is an effective method for monitoring mechanical wear, and could be used to prevent serious accidents. However, debris detection during early phase of mechanical wear, when small debris (<100 um) is generated, requires that the sensor has high sensitivity with respect to background noise. In order to detect smaller debris by existing sensors, this paper presents a hybrid method which combines Band Pass Filter and Correlation Algorithm to improve sensor signal-to-noise ratio (SNR). The simulation results indicate that the SNR will be improved at least 2.67 times after signal processing. In other words, this method ensures debris identification when the sensor's SNR is bigger than -3 dB. Thus, smaller debris will be detected in the same SNR. Finally, effectiveness of the proposed method is experimentally validated.

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

NASA Astrophysics Data System (ADS)

Elbouz, Marwa; Alfalou, Ayman; Brosseau, Christian

2011-06-01

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

Detection of Unknown LEO Satellite Using Radar Measurements

NASA Astrophysics Data System (ADS)

Kamensky, S.; Samotokhin, A.; Khutorovsky, Z.; Alfriend, T.

While processing of the radar information aimed at satellite catalog maintenance some measurements do not correlate with cataloged and tracked satellites. These non-correlated measurements participate in the detection (primary orbit determination) of new (not cataloged) satellites. The satellite is considered newly detected when it is missing in the catalog and the primary orbit determination on the basis of the non-correlated measurements provides the accuracy sufficient for reliable correlation of future measurements. We will call this the detection condition. One non-correlated measurement in real conditions does not have enough accuracy and thus does not satisfy the detection condition. Two measurements separated by a revolution or more normally provides orbit determination with accuracy sufficient for selection of other measurements. However, it is not always possible to say with high probability (close to 1) that two measurements belong to one satellite. Three measurements for different revolutions, which are included into one orbit, have significantly higher chances to belong to one satellite. Thus the suggested detection (primary orbit determination) algorithm looks for three uncorrelated measurements in different revolutions for which we can determine the orbit inscribing them. The detection procedure based on search for the triplets is rather laborious. Thus only relatively high efficiency can be the reason for its practical implementation. The work presents the detailed description of the suggested detection procedure based on the search for triplets of uncorrelated measurements (for radar measurements). The break-ups of the tracked satellites provide the most difficult conditions for the operation of the detection algorithm and reveal explicitly its characteristics. The characteristics of time efficiency and reliability of the detected orbits are of maximum interest. Within this work we suggest to determine these characteristics using simulation of break-ups with further acquisition of measurements generated by the fragments. In particular, using simulation we can not only evaluate the characteristics of the algorithm but adjust its parameters for certain conditions: the orbit of the fragmented satellite, the features of the break-up, capabilities of detection radars etc. We describe the algorithm performing the simulation of radar measurements produced by the fragments of the parent satellite. This algorithm accounts of the basic factors affecting the characteristics of time efficiency and reliability of the detection. The catalog maintenance algorithm includes two major components detection and tracking. These are two processes permanently interacting with each other. This is actually in place for the processing of real radar data. The simulation must take this into account since one cannot obtain reliable characteristics of detection procedure simulating only this process. Thus we simulated both processes in their interaction. The work presents the results of simulation for the simplest case of a break-up in near-circular orbit with insignificant atmospheric drag. The simulations show rather high efficiency. We demonstrate as well that the characteristics of time efficiency and reliability of determined orbits essentially depend on the density of the observed break-up fragments.

Truncated feature representation for automatic target detection using transformed data-based decomposition

NASA Astrophysics Data System (ADS)

Riasati, Vahid R.

2016-05-01

In this work, the data covariance matrix is diagonalized to provide an orthogonal bases set using the eigen vectors of the data. The eigen-vector decomposition of the data is transformed and filtered in the transform domain to truncate the data for robust features related to a specified set of targets. These truncated eigen features are then combined and reconstructed to utilize in a composite filter and consequently utilized for the automatic target detection of the same class of targets. The results associated with the testing of the current technique are evaluated using the peak-correlation and peak-correlation energy metrics and are presented in this work. The inverse transformed eigen-bases of the current technique may be thought of as an injected sparsity to minimize data in representing the skeletal data structure information associated with the set of targets under consideration.

Eye gaze tracking using correlation filters

NASA Astrophysics Data System (ADS)

Karakaya, Mahmut; Bolme, David; Boehnen, Chris

2014-03-01

In this paper, we studied a method for eye gaze tracking that provide gaze estimation from a standard webcam with a zoom lens and reduce the setup and calibration requirements for new users. Specifically, we have developed a gaze estimation method based on the relative locations of points on the top of the eyelid and eye corners. Gaze estimation method in this paper is based on the distances between top point of the eyelid and eye corner detected by the correlation filters. Advanced correlation filters were found to provide facial landmark detections that are accurate enough to determine the subjects gaze direction up to angle of approximately 4-5 degrees although calibration errors often produce a larger overall shift in the estimates. This is approximately a circle of diameter 2 inches for a screen that is arm's length from the subject. At this accuracy it is possible to figure out what regions of text or images the subject is looking but it falls short of being able to determine which word the subject has looked at.

A Method for Detecting Circulating Tumor Cells Based on the Measurement of Single-Cell Metabolism in Droplet-Based Microfluidics.

PubMed

Del Ben, Fabio; Turetta, Matteo; Celetti, Giorgia; Piruska, Aigars; Bulfoni, Michela; Cesselli, Daniela; Huck, Wilhelm T S; Scoles, Giacinto

2016-07-18

The number of circulating tumor cells (CTCs) in blood is strongly correlated with the progress of metastatic cancer. Current methods to detect CTCs are based on immunostaining or discrimination of physical properties. Herein, a label-free method is presented exploiting the abnormal metabolic behavior of cancer cells. A single-cell analysis technique is used to measure the secretion of acid from individual living tumor cells compartmentalized in microfluidically prepared, monodisperse, picoliter (pL) droplets. As few as 10 tumor cells can be detected in a background of 200 000 white blood cells and proof-of-concept data is shown on the detection of CTCs in the blood of metastatic patients. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Multi-Level Pre-Correlation RFI Flagging for Real-Time Implementation on UniBoard

NASA Astrophysics Data System (ADS)

Dumez-Viou, Cédric; Weber, Rodolphe; Ravier, Philippe

2016-03-01

Because of the denser active use of the spectrum, and because of radio telescopes higher sensitivity, radio frequency interference (RFI) mitigation has become a sensitive topic for current and future radio telescope designs. Even if quite sophisticated approaches have been proposed in the recent years, the majority of RFI mitigation operational procedures are based on post-correlation corrupted data flagging. Moreover, given the huge amount of data delivered by current and next generation radio telescopes, all these RFI detection procedures have to be at least automatic and, if possible, real-time. In this paper, the implementation of a real-time pre-correlation RFI detection and flagging procedure into generic high-performance computing platforms based on field programmable gate arrays (FPGA) is described, simulated and tested. One of these boards, UniBoard, developed under a Joint Research Activity in the RadioNet FP7 European programme is based on eight FPGAs interconnected by a high speed transceiver mesh. It provides up to 4 TMACs with ®Altera Stratix IV FPGA and 160 Gbps data rate for the input data stream. The proposed concept is to continuously monitor the data quality at different stages in the digital preprocessing pipeline between the antennas and the correlator, at the station level and the core level. In this way, the detectors are applied at stages where different time-frequency resolutions can be achieved and where the interference-to-noise ratio (INR) is maximum right before any dilution of RFI characteristics by subsequent channelizations or signal recombinations. The detection decisions could be linked to a RFI statistics database or could be attached to the data for later stage flagging. Considering the high in-out data rate in the pre-correlation stages, only real-time and go-through detectors (i.e. no iterative processing) can be implemented. In this paper, a real-time and adaptive detection scheme is described. An ongoing case study has been set up with the Electronic Multi-Beam Radio Astronomy Concept (EMBRACE) radio telescope facility at Nançay Observatory. The objective is to evaluate the performances of this concept in term of hardware complexity, detection efficiency and additional RFI metadata rate cost. The UniBoard implementation scheme is described.

Detection of elemental mercury by multimode diode laser correlation spectroscopy.

PubMed

Lou, Xiutao; Somesfalean, Gabriel; Svanberg, Sune; Zhang, Zhiguo; Wu, Shaohua

2012-02-27

We demonstrate a method for elemental mercury detection based on correlation spectroscopy employing UV laser radiation generated by sum-frequency mixing of two visible multimode diode lasers. Resonance matching of the multimode UV laser is achieved in a wide wavelength range and with good tolerance for various operating conditions. Large mode-hops provide an off-resonance baseline, eliminating interferences from other gas species with broadband absorption. A sensitivity of 1 μg/m3 is obtained for a 1-m path length and 30-s integration time. The performance of the system shows promise for mercury monitoring in industrial applications.

Improving membrane based multiplex immunoassays for semi-quantitative detection of multiple cytokines in a single sample

PubMed Central

2014-01-01

Background Inflammatory mediators can serve as biomarkers for the monitoring of the disease progression or prognosis in many conditions. In the present study we introduce an adaptation of a membrane-based technique in which the level of up to 40 cytokines and chemokines can be determined in both human and rodent blood in a semi-quantitative way. The planar assay was modified using the LI-COR (R) detection system (fluorescence based) rather than chemiluminescence and semi-quantitative outcomes were achieved by normalizing the outcomes using the automated exposure settings of the Odyssey readout device. The results were compared to the gold standard assay, namely ELISA. Results The improved planar assay allowed the detection of a considerably higher number of analytes (n = 30 and n = 5 for fluorescent and chemiluminescent detection, respectively). The improved planar method showed high sensitivity up to 17 pg/ml and a linear correlation of the normalized fluorescence intensity with the results from the ELISA (r = 0.91). Conclusions The results show that the membrane-based technique is a semi-quantitative assay that correlates satisfactorily to the gold standard when enhanced by the use of fluorescence and subsequent semi-quantitative analysis. This promising technique can be used to investigate inflammatory profiles in multiple conditions, particularly in studies with constraints in sample sizes and/or budget. PMID:25022797

Application of image recognition-based automatic hyphae detection in fungal keratitis.

PubMed

Wu, Xuelian; Tao, Yuan; Qiu, Qingchen; Wu, Xinyi

2018-03-01

The purpose of this study is to evaluate the accuracy of two methods in diagnosis of fungal keratitis, whereby one method is automatic hyphae detection based on images recognition and the other method is corneal smear. We evaluate the sensitivity and specificity of the method in diagnosis of fungal keratitis, which is automatic hyphae detection based on image recognition. We analyze the consistency of clinical symptoms and the density of hyphae, and perform quantification using the method of automatic hyphae detection based on image recognition. In our study, 56 cases with fungal keratitis (just single eye) and 23 cases with bacterial keratitis were included. All cases underwent the routine inspection of slit lamp biomicroscopy, corneal smear examination, microorganism culture and the assessment of in vivo confocal microscopy images before starting medical treatment. Then, we recognize the hyphae images of in vivo confocal microscopy by using automatic hyphae detection based on image recognition to evaluate its sensitivity and specificity and compare with the method of corneal smear. The next step is to use the index of density to assess the severity of infection, and then find the correlation with the patients' clinical symptoms and evaluate consistency between them. The accuracy of this technology was superior to corneal smear examination (p < 0.05). The sensitivity of the technology of automatic hyphae detection of image recognition was 89.29%, and the specificity was 95.65%. The area under the ROC curve was 0.946. The correlation coefficient between the grading of the severity in the fungal keratitis by the automatic hyphae detection based on image recognition and the clinical grading is 0.87. The technology of automatic hyphae detection based on image recognition was with high sensitivity and specificity, able to identify fungal keratitis, which is better than the method of corneal smear examination. This technology has the advantages when compared with the conventional artificial identification of confocal microscope corneal images, of being accurate, stable and does not rely on human expertise. It was the most useful to the medical experts who are not familiar with fungal keratitis. The technology of automatic hyphae detection based on image recognition can quantify the hyphae density and grade this property. Being noninvasive, it can provide an evaluation criterion to fungal keratitis in a timely, accurate, objective and quantitative manner.

Causal Entropies – a measure for determining changes in the temporal organization of neural systems

PubMed Central

Waddell, Jack; Dzakpasu, Rhonda; Booth, Victoria; Riley, Brett; Reasor, Jonathan; Poe, Gina; Zochowski, Michal

2009-01-01

We propose a novel measure to detect temporal ordering in the activity of individual neurons in a local network, which is thought to be a hallmark of activity-dependent synaptic modifications during learning. The measure, called Causal Entropy, is based on the time-adaptive detection of asymmetries in the relative temporal patterning between neuronal pairs. We characterize properties of the measure on both simulated data and experimental multiunit recordings of hippocampal neurons from the awake, behaving rat, and show that the metric can more readily detect those asymmetries than standard cross correlation-based techniques, especially since the temporal sensitivity of causal entropy can detect such changes rapidly and dynamically. PMID:17275095

Raman spectroscopy-based detection of chemical contaminants in food powders

NASA Astrophysics Data System (ADS)

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

2016-05-01

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

Detection of potato beetle damage using remote sensing from small unmanned aircraft systems

NASA Astrophysics Data System (ADS)

Hunt, E. Raymond; Rondon, Silvia I.

2017-04-01

Colorado potato beetle (CPB) adults and larvae devour leaves of potato and other solanaceous crops and weeds, and may quickly develop resistance to pesticides. With early detection of CPB damage, more options are available for precision integrated pest management, which reduces the amount of pesticides applied in a field. Remote sensing with small unmanned aircraft systems (sUAS) has potential for CPB detection because low flight altitudes allow image acquisition at very high spatial resolution. A five-band multispectral sensor and up-looking incident light sensor were mounted on a six-rotor sUAS, which was flown at altitudes of 60 and 30 m in June 2014. Plants went from visibly undamaged to having some damage in just 1 day. Whole-plot normalized difference vegetation index (NDVI) and the number of pixels classified as damaged (0.70≤NDVI≤0.80) were not correlated with visible CPB damage ranked from least to most. Area of CPB damage estimated using object-based image analysis was highly correlated to the visual ranking of damage. Furthermore, plant height calculated using structure-from-motion point clouds was related to CPB damage, but this method required extensive operator intervention for success. Object-based image analysis has potential for early detection based on high spatial resolution sUAS remote sensing.

Automatic detection of articulation disorders in children with cleft lip and palate.

PubMed

Maier, Andreas; Hönig, Florian; Bocklet, Tobias; Nöth, Elmar; Stelzle, Florian; Nkenke, Emeka; Schuster, Maria

2009-11-01

Speech of children with cleft lip and palate (CLP) is sometimes still disordered even after adequate surgical and nonsurgical therapies. Such speech shows complex articulation disorders, which are usually assessed perceptually, consuming time and manpower. Hence, there is a need for an easy to apply and reliable automatic method. To create a reference for an automatic system, speech data of 58 children with CLP were assessed perceptually by experienced speech therapists for characteristic phonetic disorders at the phoneme level. The first part of the article aims to detect such characteristics by a semiautomatic procedure and the second to evaluate a fully automatic, thus simple, procedure. The methods are based on a combination of speech processing algorithms. The semiautomatic method achieves moderate to good agreement (kappa approximately 0.6) for the detection of all phonetic disorders. On a speaker level, significant correlations between the perceptual evaluation and the automatic system of 0.89 are obtained. The fully automatic system yields a correlation on the speaker level of 0.81 to the perceptual evaluation. This correlation is in the range of the inter-rater correlation of the listeners. The automatic speech evaluation is able to detect phonetic disorders at an experts'level without any additional human postprocessing.

Intensity-based masking: A tool to improve functional connectivity results of resting-state fMRI.

PubMed

Peer, Michael; Abboud, Sami; Hertz, Uri; Amedi, Amir; Arzy, Shahar

2016-07-01

Seed-based functional connectivity (FC) of resting-state functional MRI data is a widely used methodology, enabling the identification of functional brain networks in health and disease. Based on signal correlations across the brain, FC measures are highly sensitive to noise. A somewhat neglected source of noise is the fMRI signal attenuation found in cortical regions in close vicinity to sinuses and air cavities, mainly in the orbitofrontal, anterior frontal and inferior temporal cortices. BOLD signal recorded at these regions suffers from dropout due to susceptibility artifacts, resulting in an attenuated signal with reduced signal-to-noise ratio in as many as 10% of cortical voxels. Nevertheless, signal attenuation is largely overlooked during FC analysis. Here we first demonstrate that signal attenuation can significantly influence FC measures by introducing false functional correlations and diminishing existing correlations between brain regions. We then propose a method for the detection and removal of the attenuated signal ("intensity-based masking") by fitting a Gaussian-based model to the signal intensity distribution and calculating an intensity threshold tailored per subject. Finally, we apply our method on real-world data, showing that it diminishes false correlations caused by signal dropout, and significantly improves the ability to detect functional networks in single subjects. Furthermore, we show that our method increases inter-subject similarity in FC, enabling reliable distinction of different functional networks. We propose to include the intensity-based masking method as a common practice in the pre-processing of seed-based functional connectivity analysis, and provide software tools for the computation of intensity-based masks on fMRI data. Hum Brain Mapp 37:2407-2418, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Noise/spike detection in phonocardiogram signal as a cyclic random process with non-stationary period interval.

PubMed

Naseri, H; Homaeinezhad, M R; Pourkhajeh, H

2013-09-01

The major aim of this study is to describe a unified procedure for detecting noisy segments and spikes in transduced signals with a cyclic but non-stationary periodic nature. According to this procedure, the cycles of the signal (onset and offset locations) are detected. Then, the cycles are clustered into a finite number of groups based on appropriate geometrical- and frequency-based time series. Next, the median template of each time series of each cluster is calculated. Afterwards, a correlation-based technique is devised for making a comparison between a test cycle feature and the associated time series of each cluster. Finally, by applying a suitably chosen threshold for the calculated correlation values, a segment is prescribed to be either clean or noisy. As a key merit of this research, the procedure can introduce a decision support for choosing accurately orthogonal-expansion-based filtering or to remove noisy segments. In this paper, the application procedure of the proposed method is comprehensively described by applying it to phonocardiogram (PCG) signals for finding noisy cycles. The database consists of 126 records from several patients of a domestic research station acquired by a 3M Littmann(®) 3200, 4KHz sampling frequency electronic stethoscope. By implementing the noisy segments detection algorithm with this database, a sensitivity of Se=91.41% and a positive predictive value, PPV=92.86% were obtained based on physicians assessments. Copyright © 2013 Elsevier Ltd. All rights reserved.

Simultaneous Range/Velocity Detection with an Ultra-Wideband Random Noise Radar Through Fully Digital Cross-Correlation in the Time Domain

DTIC Science & Technology

2011-03-24

equates to N < 2.237×108 samples . For the hardware used in this paper where B ≈ 370MHz [29], the limit on the correlation time becomes T < 0.30 s. This...When implementing the digital correlator in the time domain, each discrete sample of the reference signal, sref , must be interpolated based on the...through digital correlation comes from the number of samples in the measurement vector, L. The computational re- quirements grow with L. As Figure 2.9

[Development of operation patient security detection system].

PubMed

Geng, Shu-Qin; Tao, Ren-Hai; Zhao, Chao; Wei, Qun

2008-11-01

This paper describes a patient security detection system developed with two dimensional bar codes, wireless communication and removal storage technique. Based on the system, nurses and correlative personnel check code wait operation patient to prevent the defaults. The tests show the system is effective. Its objectivity and currency are more scientific and sophisticated than current traditional method in domestic hospital.

Application of a molecular beacon based real-time isothermal amplification (MBRTIA) technology for simultaneous detection of Bacillus cereus and Staphylococcus aureus.

PubMed

Mandappa, I M; Joglekar, Prasanna; Manonmani, H K

2015-07-01

A multiplex real-time isothermal amplification assay was developed using molecular beacons for the detection of Bacillus cereus and Staphylococcus aureus by targeting four important virulence genes. A correlation between targeting highly accessible DNA sequences and isothermal amplification based molecular beacon efficiency and sensitivity was demonstrated using phi(Φ)29 DNA polymerase at a constant isothermal temperature of 30 °C. It was very selective and consistently detected down to 10(1) copies of DNA. The specificity and sensitivity of this assay, when tested with pure culture were high, surpassing those of currently used PCR assays for the detection of these organisms. The molecular beacon based real-time isothermal amplification (MBRTIA) assay could be carried out entirely in 96 well plates or well strips, enabling a rapid and high-throughput detection of food borne pathogens.

Lenses in the forest: cross correlation of the Lyman-alpha flux with cosmic microwave background lensing.

PubMed

Vallinotto, Alberto; Das, Sudeep; Spergel, David N; Viel, Matteo

2009-08-28

We present a theoretical estimate for a new observable: the cross correlation between the Lyman-alpha flux fluctuations in quasar spectra and the convergence of the cosmic microwave background as measured along the same line of sight. As a first step toward the assessment of its detectability, we estimate the signal-to-noise ratio using linear theory. Although the signal-to-noise is small for a single line of sight and peaks at somewhat smaller redshifts than those probed by the Lyman-alpha forest, we estimate a total signal-to-noise of 9 for cross correlating quasar spectra of SDSS-III with Planck and 20 for cross correlating with a future polarization based cosmic microwave background experiment. The detection of this effect would be a direct measure of the neutral hydrogen-matter cross correlation and could provide important information on the growth of structures at large scales in a redshift range which is still poorly probed.

Detection of periodicity based on independence tests - III. Phase distance correlation periodogram

NASA Astrophysics Data System (ADS)

Zucker, Shay

2018-02-01

I present the Phase Distance Correlation (PDC) periodogram - a new periodicity metric, based on the Distance Correlation concept of Gábor Székely. For each trial period, PDC calculates the distance correlation between the data samples and their phases. PDC requires adaptation of the Székely's distance correlation to circular variables (phases). The resulting periodicity metric is best suited to sparse data sets, and it performs better than other methods for sawtooth-like periodicities. These include Cepheid and RR-Lyrae light curves, as well as radial velocity curves of eccentric spectroscopic binaries. The performance of the PDC periodogram in other contexts is almost as good as that of the Generalized Lomb-Scargle periodogram. The concept of phase distance correlation can be adapted also to astrometric data, and it has the potential to be suitable also for large evenly spaced data sets, after some algorithmic perfection.

Quantum correlation of fiber-based telecom-band photon pairs through standard loss and random media.

PubMed

Sua, Yong Meng; Malowicki, John; Lee, Kim Fook

2014-08-15

We study quantum correlation and interference of fiber-based telecom-band photon pairs with one photon of the pair experiencing multiple scattering in a random medium. We measure joint probability of two-photon detection for signal photon in a normal channel and idler photon in a channel, which is subjected to two independent conditions: standard loss (neutral density filter) and random media. We observe that both conditions degrade the correlation of signal and idler photons, and depolarization of the idler photon in random medium can enhance two-photon interference at certain relative polarization angles. Our theoretical calculation on two-photon polarization correlation and interference as a function of mean free path is in agreement with our experiment data. We conclude that quantum correlation of a polarization-entangled photon pair is better preserved than a polarization-correlated photon pair as one photon of the pair scatters through a random medium.

Sensitive albuminuria analysis using dye-binding based test strips.

PubMed

Delanghe, Joris R; Himpe, Jonas; De Cock, Naomi; Delanghe, Sigurd; De Herde, Kevin; Stove, Veronique; Speeckaert, Marijn M

2017-08-01

Populations at increased risk for chronic kidney disease should be screened for albuminuria. Possibilities of advanced urine strip readers based on complementary metal oxide semiconductor (CMOS) sensor technology were investigated for obtaining quantitative albuminuria results. Reflectance data of test strips (Sysmex UFC 3500 reader+CMOS) were compared with albuminuria (BNII) and with proteinuria (Cobas 8000). Urinary creatinine was assayed using a Jaffe-based creatinine assay (Cobas 8000). Calibration curve was made between 11.5 and 121.5mg/L with detection limit of 5.5mg/L. Within-run CV values of reflectance data were 0.21% (UC-Control L; 10mg/L) and 0.37% (UC-Control H; >150mg/L) for albumin, and 0.71%/3.97% for creatinine. Between-run CV values were 0.24%/0.42% for albumin and 0.93%/5.13% for creatinine. A strong correlation (r=0.92) was obtained between albuminuria (BNII) and protein strip reflectance data. Creatinine reflectance data correlated well with Jaffe-based urinary creatinine data (r=0.90). Albumin:creatinine ratio obtained by test strip and by wet chemistry showed a good correlation (r=0.59). Carbamylated, glycated and partially hydrolyzed isoforms of albumin could be detected by test strip. Dye-binding based albumin test strip assay in combination with a CMOS based reader would potentially allow quantitative analysis of albuminuria and determination of albumin:creatinine ratio. Copyright © 2017 Elsevier B.V. All rights reserved.

A study of the cross-correlation and time lag in black hole X-ray binary XTE J1859+226

NASA Astrophysics Data System (ADS)

Pei, Songpeng; Ding, Guoqiang; Li, Zhibing; Lei, Yajuan; Yuen, Rai; Qu, Jinlu

2017-07-01

With Rossi X-ray Timing Explorer (RXTE) data, we systematically study the cross-correlation and time lag in all spectral states of black hole X-ray binary (BHXB) XTE J1859+226 in detail during its entire 1999-2000 outburst that lasted for 166 days. Anti-correlations and positive correlations and their respective soft and hard X-ray lags are only detected in the first 100 days of the outburst when the luminosity is high. This suggests that the cross-correlations may be related to high luminosity. Positive correlations are detected in every state of XTE J1859+226, viz., hard state, hard-intermediate state (HIMS), soft-intermediate state (SIMS) and soft state. However, anti-correlations are only detected in HIMS and SIMS, anti-correlated hard lags are only detected in SIMS, while anti-correlated soft lags are detected in both HIMS and SIMS. Moreover, the ratio of the observations with anti-correlated soft lags to hard lags detected in XTE J1859+226 is significantly different from that in neutron star low-mass X-ray binaries (NS LMXBs). So far, anti-correlations are never detected in the soft state of BHXBs but detected in every branch or state of NS LMXBs. This may be due to the origin of soft seed photons in BHXBs is confined to the accretion disk and, for NS LMXBs, from both accretion disk and the surface of the NS. We notice that the timescale of anti-correlated time lags detected in XTE J1859+226 is similar with that of other BHXBs and NS LMXBs. We suggest that anti-correlated soft lag detected in BHXB may result from fluctuation in the accretion disk as well as NS LMXB.

Planck 2015 results. XXIII. The thermal Sunyaev-Zeldovich effect-cosmic infrared background correlation

NASA Astrophysics Data System (ADS)

Planck Collaboration; Ade, P. A. R.; Aghanim, N.; Arnaud, M.; Aumont, J.; Baccigalupi, C.; Banday, A. J.; Barreiro, R. B.; Bartlett, J. G.; Bartolo, N.; Battaner, E.; Benabed, K.; Benoit-Lévy, A.; Bernard, J.-P.; Bersanelli, M.; Bielewicz, P.; Bock, J. J.; Bonaldi, A.; Bonavera, L.; Bond, J. R.; Borrill, J.; Bouchet, F. R.; Burigana, C.; Butler, R. C.; Calabrese, E.; Catalano, A.; Chamballu, A.; Chiang, H. C.; Christensen, P. R.; Churazov, E.; Clements, D. L.; Colombo, L. P. L.; Combet, C.; Comis, B.; Couchot, F.; Coulais, A.; Crill, B. P.; Curto, A.; Cuttaia, F.; Danese, L.; Davies, R. D.; Davis, R. J.; de Bernardis, P.; de Rosa, A.; de Zotti, G.; Delabrouille, J.; Dickinson, C.; Diego, J. M.; Dole, H.; Donzelli, S.; Doré, O.; Douspis, M.; Ducout, A.; Dupac, X.; Efstathiou, G.; Elsner, F.; Enßlin, T. A.; Eriksen, H. K.; Finelli, F.; Flores-Cacho, I.; Forni, O.; Frailis, M.; Fraisse, A. A.; Franceschi, E.; Galeotta, S.; Galli, S.; Ganga, K.; Génova-Santos, R. T.; Giard, M.; Giraud-Héraud, Y.; Gjerløw, E.; González-Nuevo, J.; Górski, K. M.; Gregorio, A.; Gruppuso, A.; Gudmundsson, J. E.; Hansen, F. K.; Harrison, D. L.; Helou, G.; Hernández-Monteagudo, C.; Herranz, D.; Hildebrandt, S. R.; Hivon, E.; Hobson, M.; Hornstrup, A.; Hovest, W.; Huffenberger, K. M.; Hurier, G.; Jaffe, A. H.; Jaffe, T. R.; Jones, W. C.; Keihänen, E.; Keskitalo, R.; Kisner, T. S.; Kneissl, R.; Knoche, J.; Kunz, M.; Kurki-Suonio, H.; Lagache, G.; Lamarre, J.-M.; Langer, M.; Lasenby, A.; Lattanzi, M.; Lawrence, C. R.; Leonardi, R.; Levrier, F.; Lilje, P. B.; Linden-Vørnle, M.; López-Caniego, M.; Lubin, P. M.; Macías-Pérez, J. F.; Maffei, B.; Maggio, G.; Maino, D.; Mak, D. S. Y.; Mandolesi, N.; Mangilli, A.; Maris, M.; Martin, P. G.; Martínez-González, E.; Masi, S.; Matarrese, S.; Melchiorri, A.; Mennella, A.; Migliaccio, M.; Mitra, S.; Miville-Deschênes, M.-A.; Moneti, A.; Montier, L.; Morgante, G.; Mortlock, D.; Munshi, D.; Murphy, J. A.; Nati, F.; Natoli, P.; Noviello, F.; Novikov, D.; Novikov, I.; Oxborrow, C. A.; Paci, F.; Pagano, L.; Pajot, F.; Paoletti, D.; Partridge, B.; Pasian, F.; Pearson, T. J.; Perdereau, O.; Perotto, L.; Pettorino, V.; Piacentini, F.; Piat, M.; Pierpaoli, E.; Plaszczynski, S.; Pointecouteau, E.; Polenta, G.; Ponthieu, N.; Pratt, G. W.; Prunet, S.; Puget, J.-L.; Rachen, J. P.; Reinecke, M.; Remazeilles, M.; Renault, C.; Renzi, A.; Ristorcelli, I.; Rocha, G.; Rosset, C.; Rossetti, M.; Roudier, G.; Rubiño-Martín, J. A.; Rusholme, B.; Sandri, M.; Santos, D.; Savelainen, M.; Savini, G.; Scott, D.; Spencer, L. D.; Stolyarov, V.; Stompor, R.; Sunyaev, R.; Sutton, D.; Suur-Uski, A.-S.; Sygnet, J.-F.; Tauber, J. A.; Terenzi, L.; Toffolatti, L.; Tomasi, M.; Tristram, M.; Tucci, M.; Umana, G.; Valenziano, L.; Valiviita, J.; Van Tent, B.; Vielva, P.; Villa, F.; Wade, L. A.; Wandelt, B. D.; Wehus, I. K.; Welikala, N.; Yvon, D.; Zacchei, A.; Zonca, A.

2016-09-01

We use Planck data to detect the cross-correlation between the thermal Sunyaev-Zeldovich (tSZ) effect and the infrared emission from the galaxies that make up the the cosmic infrared background (CIB). We first perform a stacking analysis towards Planck-confirmed galaxy clusters. We detect infrared emission produced by dusty galaxies inside these clusters and demonstrate that the infrared emission is about 50% more extended than the tSZ effect. Modelling the emission with a Navarro-Frenk-White profile, we find that the radial profile concentration parameter is c500 = 1.00+0.18-0.15 . This indicates that infrared galaxies in the outskirts of clusters have higher infrared flux than cluster-core galaxies. We also study the cross-correlation between tSZ and CIB anisotropies, following three alternative approaches based on power spectrum analyses: (I) using a catalogue of confirmed clusters detected in Planck data; (II) using an all-sky tSZ map built from Planck frequency maps; and (III) using cross-spectra between Planck frequency maps. With the three different methods, we detect the tSZ-CIB cross-power spectrum at significance levels of (I) 6σ; (II) 3σ; and (III) 4σ. We model the tSZ-CIB cross-correlation signature and compare predictions with the measurements. The amplitude of the cross-correlation relative to the fiducial model is AtSZ-CIB = 1.2 ± 0.3. This result is consistent with predictions for the tSZ-CIB cross-correlation assuming the best-fit cosmological model from Planck 2015 results along with the tSZ and CIB scaling relations.

Chirp echo Fourier transform EPR-detected NMR

NASA Astrophysics Data System (ADS)

Wili, Nino; Jeschke, Gunnar

2018-04-01

A new ultra-wide band (UWB) pulse EPR method is introduced for observing all nuclear frequencies of a paramagnetic center in a single shot. It is based on burning spectral holes with a high turning angle (HTA) pulse that excites forbidden transitions and subsequent detection of the hole pattern by a chirp echo. We term this method Chirp Echo Epr SpectroscopY (CHEESY)-detected NMR. The approach is a revival of FT EPR-detected NMR. It yields similar spectra and the same type of information as electron-electron double resonance (ELDOR)-detected NMR, but with a multiplex advantage. We apply CHEESY-detected NMR in Q band to nitroxides and correlate the hyperfine spectrum to the EPR spectrum by varying the frequency of the HTA pulse. Furthermore, a selective π pulse before the HTA pulse allows for detecting hyperfine sublevel correlations between transitions of one nucleus and for elucidating the coupling regime, the same information as revealed by the HYSCORE experiment. This is demonstrated on hexaaquamanganese(II). We expect that CHEESY-detected NMR is generally applicable to disordered systems and that our results further motivate the development of EPR spectrometers capable of coherent UWB excitation and detection, especially at higher fields and frequencies.

Brain dopamine and serotonin transporter binding are associated with visual attention bias for food in lean men.

PubMed

Koopman, K E; Roefs, A; Elbers, D C E; Fliers, E; Booij, J; Serlie, M J; la Fleur, S E

2016-06-01

In rodents, the striatal dopamine (DA) system and the (hypo)thalamic serotonin (5-HT) system are involved in the regulation of feeding behavior. In lean humans, little is known about the relationship between these brain neurotransmitter systems and feeding. We studied the relationship between striatal DA transporters (DAT) and diencephalic 5-HT transporters (SERT), behavioral tasks and questionnaires, and food intake. We measured striatal DAT and diencephalic SERT binding with [123I]FP-CIT SPECT in 36 lean male subjects. Visual attention bias for food (detection speed and distraction time) and degree of impulsivity were measured using response-latency-based computer tasks. Craving and emotional eating were assessed with questionnaires and ratings of hunger by means of VAS scores. Food intake was assessed through a self-reported online diet journal. Striatal DAT and diencephalic SERT binding negatively correlated with food detection speed (p = 0.008, r = -0.50 and p = 0.002, r = -0.57, respectively), but not with food distraction time, ratings of hunger, craving or impulsivity. Striatal DAT and diencephalic SERT binding did not correlate with free choice food intake, whereas food detection speed positively correlated with total caloric intake (p = 0.001, r = 0.60), protein intake (p = 0.01, r = 0.44), carbohydrate intake (p = 0.03, r = 0.39) and fat intake (p = 0.06, r = 0.35). These results indicate a role for the central 5-HT and DA system in the regulation of visual attention bias for food, which contributes to the motivation to eat, in non-obese, healthy humans. In addition, this study confirms that food detection speed, measured with the latency-based computer task, positively correlates with total food and macronutrient intake.

Improved Automatic Detection of New T2 Lesions in Multiple Sclerosis Using Deformation Fields.

PubMed

Cabezas, M; Corral, J F; Oliver, A; Díez, Y; Tintoré, M; Auger, C; Montalban, X; Lladó, M; Pareto, D; Rovira, À

2016-06-09

Detection of disease activity, defined as new/enlarging T2 lesions on brain MR imaging, has been proposed as a biomarker in MS. However, detection of new/enlarging T2 lesions can be hindered by several factors that can be overcome with image subtraction. The purpose of this study was to improve automated detection of new T2 lesions and reduce user interaction to eliminate inter- and intraobserver variability. Multiparametric brain MR imaging was performed at 2 time points in 36 patients with new T2 lesions. Images were registered by using an affine transformation and the Demons algorithm to obtain a deformation field. After affine registration, images were subtracted and a threshold was applied to obtain a lesion mask, which was then refined by using the deformation field, intensity, and local information. This pipeline was compared with only applying a threshold, and with a state-of-the-art approach relying only on image intensities. To assess improvements, we compared the results of the different pipelines with the expert visual detection. The multichannel pipeline based on the deformation field obtained a detection Dice similarity coefficient close to 0.70, with a false-positive detection of 17.8% and a true-positive detection of 70.9%. A statistically significant correlation (r = 0.81, P value = 2.2688e-09) was found between visual detection and automated detection by using our approach. The deformation field-based approach proposed in this study for detecting new/enlarging T2 lesions resulted in significantly fewer false-positives while maintaining most true-positives and showed a good correlation with visual detection annotations. This approach could reduce user interaction and inter- and intraobserver variability. © 2016 American Society of Neuroradiology.

The fabrication of magnetic particle-based chemiluminescence immunoassay for human epididymis protein-4 detection in ovarian cancer.

PubMed

Fu, Xiaoling; Liu, Yangyang; Qiu, Ruiyun; Foda, Mohamed F; Zhang, Yong; Wang, Tao; Li, Jinshan

2018-03-01

The magnetic particles have a significant influence on the immunoassay detection and cancer therapy. Herein, the chemiluminescence immunoassay combined with the magnetic particles (MPCLIA) was presented for the clinical determination and analysis of human epididymis protein 4 (HE4) in the human serum. Under the optimized experiment conditions, the secure MPCLIA method can detect HE4 in the broader range of 0-1000 pmol/L, with a lower detection limit of 1.35 pmol/L. The satisfactory recovery rate of the method in the serum ranged from 83.62% to 105.10%, which was well within the requirement of clinical analysis. Moreover, the results showed the good correlation with enzyme-linked immunosorbent assay (ELISA), with the correlation coefficient of 0.9589. This proposed method has been successfully applied to the clinical determination of HE4 in the human serum.

A cyber-event correlation framework and metrics

NASA Astrophysics Data System (ADS)

Kang, Myong H.; Mayfield, Terry

2003-08-01

In this paper, we propose a cyber-event fusion, correlation, and situation assessment framework that, when instantiated, will allow cyber defenders to better understand the local, regional, and global cyber-situation. This framework, with associated metrics, can be used to guide assessment of our existing cyber-defense capabilities, and to help evaluate the state of cyber-event correlation research and where we must focus our future cyber-event correlation research. The framework, based on the cyber-event gathering activities and analysis functions, consists of five operational steps, each of which provides a richer set of contextual information to support greater situational understanding. The first three steps are categorically depicted as increasingly richer and broader-scoped contexts achieved through correlation activity, while in the final two steps, these richer contexts are achieved through analytical activities (situation assessment, and threat analysis & prediction). Category 1 Correlation focuses on the detection of suspicious activities and the correlation of events from a single cyber-event source. Category 2 Correlation clusters the same or similar events from multiple detectors that are located at close proximity and prioritizes them. Finally, the events from different time periods and event sources at different location/regions are correlated at Category 3 to recognize the relationship among different events. This is the category that focuses on the detection of large-scale and coordinated attacks. The situation assessment step (Category 4) focuses on the assessment of cyber asset damage and the analysis of the impact on missions. The threat analysis and prediction step (Category 5) analyzes attacks based on attack traces and predicts the next steps. Metrics that can distinguish correlation and cyber-situation assessment tools for each category are also proposed.

Trial-Level Regressor Modulation for Functional Magnetic Resonance Imaging Designs Requiring Strict Periodicity of Stimulus Presentations: Illustrated Using a Go/No-Go Task

PubMed Central

Motes, Michael A; Rao, Neena K; Shokri-Kojori, Ehsan; Chiang, Hsueh-Sheng; Kraut, Michael A; Hart, John

2017-01-01

Computer-based assessment of many cognitive processes (eg, anticipatory and response readiness processes) requires the use of invariant stimulus display times (SDT) and intertrial intervals (ITI). Although designs with invariant SDTs and ITIs have been used in functional magnetic resonance imaging (fMRI) research, such designs are problematic for fMRI studies because of collinearity issues. This study examined regressor modulation with trial-level reaction times (RT) as a method for improving signal detection in a go/no-go task with invariant SDTs and ITIs. The effects of modulating the go regressor were evaluated with respect to the detection of BOLD signal-change for the no-go condition. BOLD signal-change to no-go stimuli was examined when the go regressor was based on a (a) canonical hemodynamic response function (HRF), (b) RT-based amplitude-modulated (AM) HRF, and (c) RT-based amplitude and duration modulated (A&DM) HRF. Reaction time–based modulation reduced the collinearity between the go and no-go regressors, with A&DM producing the greatest reductions in correlations between the regressors, and greater reductions in the correlations between regressors were associated with longer mean RTs and greater RT variability. Reaction time–based modulation increased statistical power for detecting group-level no-go BOLD signal-change across a broad set of brain regions. The findings show the efficacy of using regressor modulation to increase power in detecting BOLD signal-change in fMRI studies in which circumstances dictate the use of temporally invariant stimulus presentations. PMID:29276390

Trial-Level Regressor Modulation for Functional Magnetic Resonance Imaging Designs Requiring Strict Periodicity of Stimulus Presentations: Illustrated Using a Go/No-Go Task.

PubMed

Motes, Michael A; Rao, Neena K; Shokri-Kojori, Ehsan; Chiang, Hsueh-Sheng; Kraut, Michael A; Hart, John

2017-01-01

Computer-based assessment of many cognitive processes (eg, anticipatory and response readiness processes) requires the use of invariant stimulus display times (SDT) and intertrial intervals (ITI). Although designs with invariant SDTs and ITIs have been used in functional magnetic resonance imaging (fMRI) research, such designs are problematic for fMRI studies because of collinearity issues. This study examined regressor modulation with trial-level reaction times (RT) as a method for improving signal detection in a go / no-go task with invariant SDTs and ITIs. The effects of modulating the go regressor were evaluated with respect to the detection of BOLD signal-change for the no-go condition. BOLD signal-change to no-go stimuli was examined when the go regressor was based on a (a) canonical hemodynamic response function (HRF), (b) RT-based amplitude-modulated (AM) HRF, and (c) RT-based amplitude and duration modulated (A&DM) HRF. Reaction time-based modulation reduced the collinearity between the go and no-go regressors, with A&DM producing the greatest reductions in correlations between the regressors, and greater reductions in the correlations between regressors were associated with longer mean RTs and greater RT variability. Reaction time-based modulation increased statistical power for detecting group-level no-go BOLD signal-change across a broad set of brain regions. The findings show the efficacy of using regressor modulation to increase power in detecting BOLD signal-change in fMRI studies in which circumstances dictate the use of temporally invariant stimulus presentations.

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.

An efficient signal processing tool for impedance-based structural health monitoring

NASA Astrophysics Data System (ADS)

O'Brien, Megan K.; Taylor, Stuart G.; Farinholt, Kevin M.; Park, Gyuhae; Farrar, Charles R.

2009-03-01

Various experimental studies have demonstrated that an impedance-based approach to structural health monitoring can be an effective means of damage detection. Using the self-sensing and active-sensing capabilities of piezoelectric materials, the electromechanical impedance response can be monitored to provide a qualitative indication of the overall health of a structure. Although impedance analyzers are commonly used to collect such data, they are bulky and impractical for long-term field implementation, so a smaller and more portable device is desired. However, impedance measurements often contain a sizeable number of data points, and a smaller device may not possess enough memory to store the required information, particularly for real-time analysis. Therefore, the amount of data used to assess the integrity of a structure must be significantly reduced. A new type of cross correlation analysis, for which impedance data is instantaneously correlated between different sensor sets and different frequency ranges, as opposed to be correlated to pre-stored baseline data, is proposed to drastically reduce the amount of data to a single correlation coefficient and provide a quantitative means of detecting damage relative to the sensor positions. The proposed analysis is carried out on a 3-story representative structure and its efficiency is demonstrated.

Windowed multitaper correlation analysis of multimodal brain monitoring parameters.

PubMed

Faltermeier, Rupert; Proescholdt, Martin A; Bele, Sylvia; Brawanski, Alexander

2015-01-01

Although multimodal monitoring sets the standard in daily practice of neurocritical care, problem-oriented analysis tools to interpret the huge amount of data are lacking. Recently a mathematical model was presented that simulates the cerebral perfusion and oxygen supply in case of a severe head trauma, predicting the appearance of distinct correlations between arterial blood pressure and intracranial pressure. In this study we present a set of mathematical tools that reliably detect the predicted correlations in data recorded at a neurocritical care unit. The time resolved correlations will be identified by a windowing technique combined with Fourier-based coherence calculations. The phasing of the data is detected by means of Hilbert phase difference within the above mentioned windows. A statistical testing method is introduced that allows tuning the parameters of the windowing method in such a way that a predefined accuracy is reached. With this method the data of fifteen patients were examined in which we found the predicted correlation in each patient. Additionally it could be shown that the occurrence of a distinct correlation parameter, called scp, represents a predictive value of high quality for the patients outcome.

Joint multifractal analysis based on wavelet leaders

NASA Astrophysics Data System (ADS)

Jiang, Zhi-Qiang; Yang, Yan-Hong; Wang, Gang-Jin; Zhou, Wei-Xing

2017-12-01

Mutually interacting components form complex systems and these components usually have long-range cross-correlated outputs. Using wavelet leaders, we propose a method for characterizing the joint multifractal nature of these long-range cross correlations; we call this method joint multifractal analysis based on wavelet leaders (MF-X-WL). We test the validity of the MF-X-WL method by performing extensive numerical experiments on dual binomial measures with multifractal cross correlations and bivariate fractional Brownian motions (bFBMs) with monofractal cross correlations. Both experiments indicate that MF-X-WL is capable of detecting cross correlations in synthetic data with acceptable estimating errors. We also apply the MF-X-WL method to pairs of series from financial markets (returns and volatilities) and online worlds (online numbers of different genders and different societies) and determine intriguing joint multifractal behavior.

Automated Threshold Selection for Template-Based Sonar Target Detection

DTIC Science & Technology

2017-08-01

test based on the distribution of the matched filter correlations. From the matched filter output we evaluate target sized areas and surrounding...synthetic aperture sonar data that were part of the evaluation . Figure 3 shows a nearly uniform seafloor. Figure 4 is more complex, with

Brain tumor segmentation with Vander Lugt correlator based active contour.

PubMed

Essadike, Abdelaziz; Ouabida, Elhoussaine; Bouzid, Abdenbi

2018-07-01

The manual segmentation of brain tumors from medical images is an error-prone, sensitive, and time-absorbing process. This paper presents an automatic and fast method of brain tumor segmentation. In the proposed method, a numerical simulation of the optical Vander Lugt correlator is used for automatically detecting the abnormal tissue region. The tumor filter, used in the simulated optical correlation, is tailored to all the brain tumor types and especially to the Glioblastoma, which considered to be the most aggressive cancer. The simulated optical correlation, computed between Magnetic Resonance Images (MRI) and this filter, estimates precisely and automatically the initial contour inside the tumorous tissue. Further, in the segmentation part, the detected initial contour is used to define an active contour model and presenting the problematic as an energy minimization problem. As a result, this initial contour assists the algorithm to evolve an active contour model towards the exact tumor boundaries. Equally important, for a comparison purposes, we considered different active contour models and investigated their impact on the performance of the segmentation task. Several images from BRATS database with tumors anywhere in images and having different sizes, contrast, and shape, are used to test the proposed system. Furthermore, several performance metrics are computed to present an aggregate overview of the proposed method advantages. The proposed method achieves a high accuracy in detecting the tumorous tissue by a parameter returned by the simulated optical correlation. In addition, the proposed method yields better performance compared to the active contour based methods with the averages of Sensitivity=0.9733, Dice coefficient = 0.9663, Hausdroff distance = 2.6540, Specificity = 0.9994, and faster with a computational time average of 0.4119 s per image. Results reported on BRATS database reveal that our proposed system improves over the recently published state-of-the-art methods in brain tumor detection and segmentation. Copyright © 2018 Elsevier B.V. All rights reserved.

Fast Metabolite Identification in Nuclear Magnetic Resonance Metabolomic Studies: Statistical Peak Sorting and Peak Overlap Detection for More Reliable Database Queries.

PubMed

Hoijemberg, Pablo A; Pelczer, István

2018-01-05

A lot of time is spent by researchers in the identification of metabolites in NMR-based metabolomic studies. The usual metabolite identification starts employing public or commercial databases to match chemical shifts thought to belong to a given compound. Statistical total correlation spectroscopy (STOCSY), in use for more than a decade, speeds the process by finding statistical correlations among peaks, being able to create a better peak list as input for the database query. However, the (normally not automated) analysis becomes challenging due to the intrinsic issue of peak overlap, where correlations of more than one compound appear in the STOCSY trace. Here we present a fully automated methodology that analyzes all STOCSY traces at once (every peak is chosen as driver peak) and overcomes the peak overlap obstacle. Peak overlap detection by clustering analysis and sorting of traces (POD-CAST) first creates an overlap matrix from the STOCSY traces, then clusters the overlap traces based on their similarity and finally calculates a cumulative overlap index (COI) to account for both strong and intermediate correlations. This information is gathered in one plot to help the user identify the groups of peaks that would belong to a single molecule and perform a more reliable database query. The simultaneous examination of all traces reduces the time of analysis, compared to viewing STOCSY traces by pairs or small groups, and condenses the redundant information in the 2D STOCSY matrix into bands containing similar traces. The COI helps in the detection of overlapping peaks, which can be added to the peak list from another cross-correlated band. POD-CAST overcomes the generally overlooked and underestimated presence of overlapping peaks and it detects them to include them in the search of all compounds contributing to the peak overlap, enabling the user to accelerate the metabolite identification process with more successful database queries and searching all tentative compounds in the sample set.

A pilot study on bladder wall thickness at different filling stages

NASA Astrophysics Data System (ADS)

Zhang, Xi; Liu, Yang; Li, Baojuan; Zhang, Guopeng; Liang, Zhengrong; Lu, Hongbing

2015-03-01

The ever-growing death rate and the high recurrence of bladder cancer make the early detection and appropriate followup procedure of bladder cancer attract more attention. Compare to optical cystoscopy, image-based studies have revealed its potentials in non-invasive observations of the abnormities of bladder recently, in which MR imaging turns out to be a better choice for bladder evaluation due to its non-ionizing and high contrast between urine and wall tissue. Recent studies indicate that bladder wall thickness tends to be a good indicator for detecting bladder wall abnormalities. However, it is difficult to quantitatively compare wall thickness of the same subject at different filling stages or among different subjects. In order to explore thickness variations at different bladder filling stages, in this study, we preliminarily investigate the relationship between bladder wall thickness and bladder volume based on a MRI database composed of 40 datasets acquired from 10 subjects at different filling stages, using a pipeline for thickness measurement and analysis proposed in our previous work. The Student's t-test indicated that there was no significant different on wall thickness between the male group and the female group. The Pearson correlation analysis result indicated that negative correlation with a correlation coefficient of -0.8517 existed between the wall thickness and bladder volume, and the correlation was significant(p <0.01). The corresponding linear regression equation was then estimated by the unary linear regression. Compared to the absolute value of wall thickness, the z-score of wall thickness would be more appropriate to reflect the thickness variations. For possible abnormality detection of a bladder based on wall thickness, the intra-subject and inter-subject thickness variation should be considered.

Inferring gene regression networks with model trees

PubMed Central

2010-01-01

Background Novel strategies are required in order to handle the huge amount of data produced by microarray technologies. To infer gene regulatory networks, the first step is to find direct regulatory relationships between genes building the so-called gene co-expression networks. They are typically generated using correlation statistics as pairwise similarity measures. Correlation-based methods are very useful in order to determine whether two genes have a strong global similarity but do not detect local similarities. Results We propose model trees as a method to identify gene interaction networks. While correlation-based methods analyze each pair of genes, in our approach we generate a single regression tree for each gene from the remaining genes. Finally, a graph from all the relationships among output and input genes is built taking into account whether the pair of genes is statistically significant. For this reason we apply a statistical procedure to control the false discovery rate. The performance of our approach, named REGNET, is experimentally tested on two well-known data sets: Saccharomyces Cerevisiae and E.coli data set. First, the biological coherence of the results are tested. Second the E.coli transcriptional network (in the Regulon database) is used as control to compare the results to that of a correlation-based method. This experiment shows that REGNET performs more accurately at detecting true gene associations than the Pearson and Spearman zeroth and first-order correlation-based methods. Conclusions REGNET generates gene association networks from gene expression data, and differs from correlation-based methods in that the relationship between one gene and others is calculated simultaneously. Model trees are very useful techniques to estimate the numerical values for the target genes by linear regression functions. They are very often more precise than linear regression models because they can add just different linear regressions to separate areas of the search space favoring to infer localized similarities over a more global similarity. Furthermore, experimental results show the good performance of REGNET. PMID:20950452

Interference Cancellation Technique Based on Discovery of Spreading Codes of Interference Signals and Maximum Correlation Detection for DS-CDMA System

NASA Astrophysics Data System (ADS)

Hettiarachchi, Ranga; Yokoyama, Mitsuo; Uehara, Hideyuki

This paper presents a novel interference cancellation (IC) scheme for both synchronous and asynchronous direct-sequence code-division multiple-access (DS-CDMA) wireless channels. In the DS-CDMA system, the multiple access interference (MAI) and the near-far problem (NFP) are the two factors which reduce the capacity of the system. In this paper, we propose a new algorithm that is able to detect all interference signals as an individual MAI signal by maximum correlation detection. It is based on the discovery of all the unknowing spreading codes of the interference signals. Then, all possible MAI patterns so called replicas are generated as a summation of interference signals. And the true MAI pattern is found by taking correlation between the received signal and the replicas. Moreover, the receiver executes MAI cancellation in a successive manner, removing all interference signals by single-stage. Numerical results will show that the proposed IC strategy, which alleviates the detrimental effect of the MAI and the near-far problem, can significantly improve the system performance. Especially, we can obtain almost the same receiving characteristics as in the absense of interference for asynchrnous system when received powers are equal. Also, the same performances can be seen under any received power state for synchronous system.

Electropysiologic evaluation of the visual pathway in patients with multiple sclerosis.

PubMed

Rodriguez-Mena, Diego; Almarcegui, Carmen; Dolz, Isabel; Herrero, Raquel; Bambo, Maria P; Fernandez, Javier; Pablo, Luis E; Garcia-Martin, Elena

2013-08-01

To evaluate the ability of visual evoked potentials and pattern electroretinograms (PERG) to detect subclinical axonal damage in patients during the early diagnostic stage of multiple sclerosis (MS). The authors also compared the ability of optical coherence tomography (OCT), PERG, and visual evoked potentials to detect axonal loss in MS patients and correlated the functional and structural properties of the retinal nerve fiber layer. Two hundred twenty-eight eyes of 114 subjects (57 MS patients and 57 age- and sex-matched healthy controls) were included. The visual pathway was evaluated based on functional and structural assessments. All patients underwent a complete ophthalmic examination that included assessment of visual acuity, ocular motility, intraocular pressure, visual field, papillary morphology, OCT, visual evoked potentials, and PERG. Visual evoked potentials (P100 latency and amplitude), PERG (N95 amplitude and N95/P50 ratio), and OCT parameters differed significantly between MS patients and healthy subjects. Moderate significant correlations were found between visual evoked potentials or PERG parameters and OCT measurements. Axonal damage in ganglion cells of the visual pathway can be detected based on structural measures provided by OCT in MS patients and by the N95 component and N95/P50 index of PERG, thus providing good correlation between function and structure.

Detection of Cryptosporidium and Cyclospora Oocysts from Environmental Water for Drinking and Recreational Activities in Sarawak, Malaysia.

PubMed

Bilung, Lesley Maurice; Tahar, Ahmad Syatir; Yunos, Nur Emyliana; Apun, Kasing; Lim, Yvonne Ai-Lian; Nillian, Elexson; Hashim, Hashimatul Fatma

2017-01-01

Cryptosporidiosis and cyclosporiasis are caused by waterborne coccidian protozoan parasites of the genera Cryptosporidium and Cyclospora, respectively. This study was conducted to detect Cryptosporidium and Cyclospora oocysts from environmental water abstracted by drinking water treatment plants and recreational activities in Sarawak, Malaysia. Water samples (12 each) were collected from Sungai Sarawak Kanan in Bau and Sungai Sarawak Kiri in Batu Kitang, respectively. In addition, 6 water samples each were collected from Ranchan Recreational Park and UNIMAS Lake at Universiti Malaysia Sarawak, Kota Samarahan, respectively. Water physicochemical parameters were also recorded. All samples were concentrated by the iron sulfate flocculation method followed by the sucrose floatation technique. Cryptosporidium and Cyclospora were detected by modified Ziehl-Neelsen technique. Correlation of the parasites distribution with water physicochemical parameters was analysed using bivariate Pearson correlation. Based on the 24 total samples of environmental water abstracted by drinking water treatment plants, all the samples (24/24; 100%) were positive with Cryptosporidium , and only 2 samples (2/24; 8.33%) were positive with Cyclospora . Based on the 12 total samples of water for recreational activities, 4 samples (4/12; 33%) were positive with Cryptosporidium , while 2 samples (2/12; 17%) were positive with Cyclospora . Cryptosporidium oocysts were negatively correlated with dissolved oxygen (DO).

Detection of Cryptosporidium and Cyclospora Oocysts from Environmental Water for Drinking and Recreational Activities in Sarawak, Malaysia

PubMed Central

Tahar, Ahmad Syatir; Yunos, Nur Emyliana; Apun, Kasing; Nillian, Elexson; Hashim, Hashimatul Fatma

2017-01-01

Cryptosporidiosis and cyclosporiasis are caused by waterborne coccidian protozoan parasites of the genera Cryptosporidium and Cyclospora, respectively. This study was conducted to detect Cryptosporidium and Cyclospora oocysts from environmental water abstracted by drinking water treatment plants and recreational activities in Sarawak, Malaysia. Water samples (12 each) were collected from Sungai Sarawak Kanan in Bau and Sungai Sarawak Kiri in Batu Kitang, respectively. In addition, 6 water samples each were collected from Ranchan Recreational Park and UNIMAS Lake at Universiti Malaysia Sarawak, Kota Samarahan, respectively. Water physicochemical parameters were also recorded. All samples were concentrated by the iron sulfate flocculation method followed by the sucrose floatation technique. Cryptosporidium and Cyclospora were detected by modified Ziehl-Neelsen technique. Correlation of the parasites distribution with water physicochemical parameters was analysed using bivariate Pearson correlation. Based on the 24 total samples of environmental water abstracted by drinking water treatment plants, all the samples (24/24; 100%) were positive with Cryptosporidium, and only 2 samples (2/24; 8.33%) were positive with Cyclospora. Based on the 12 total samples of water for recreational activities, 4 samples (4/12; 33%) were positive with Cryptosporidium, while 2 samples (2/12; 17%) were positive with Cyclospora. Cryptosporidium oocysts were negatively correlated with dissolved oxygen (DO). PMID:29234679

Optimized signal detection and analysis methods for in vivo photoacoustic flow cytometry

NASA Astrophysics Data System (ADS)

Wang, Qiyan; Zhou, Quanyu; Yang, Ping; Wang, Xiaoling; Niu, Zhenyu; Suo, Yuanzhen; He, Hao; Gao, Wenyuan; Tang, Shuo; Wei, Xunbin

2017-02-01

Melanoma is known as a malignant tumor of melanocytes, which usually appear in the blood circulation at the metastasis stage of cancer. Thus the detection of circulating melanoma cells is useful for early diagnosis and therapy of cancer. Here we have developed an in vivo photoacoustic flow cytometry (PAFC) based on the photoacoustic effect to detect melanoma cells. However, the raw signals we obtain from the target cells contain noises such as environmental sonic noises and electronic noises. Therefore we apply correlation comparison and feature separation methods to the detection and verification of the in vivo signals. Due to similar shape and structure of cells, the photoacoustic signals usually have similar vibration mode. By analyzing the correlations and the signal features in time domain and frequency domain, we are able to provide a method for separating photoacoustic signals generated by target cells from background noises. The method introduced here has proved to optimize the signal acquisition and signal processing, which can improve the detection accuracy in PAFC.

Signal averaging limitations in heterodyne- and direct-detection laser remote sensing measurements

NASA Technical Reports Server (NTRS)

Menyuk, N.; Killinger, D. K.; Menyuk, C. R.

1983-01-01

The improvement in measurement uncertainty brought about by the averaging of increasing numbers of pulse return signals in both heterodyne- and direct-detection lidar systems is investigated. A theoretical analysis is presented which shows the standard deviation of the mean measurement to decrease as the inverse square root of the number of measurements, except in the presence of temporal correlation. Experimental measurements based on a dual-hybrid-TEA CO2 laser differential absorption lidar system are reported which demonstrate that the actual reduction in the standard deviation of the mean in both heterodyne- and direct-detection systems is much slower than the inverse square-root dependence predicted for uncorrelated signals, but is in agreement with predictions in the event of temporal correlation. Results thus favor the use of direct detection at relatively short range where the lower limit of the standard deviation of the mean is about 2 percent, but advantages of heterodyne detection at longer ranges are noted.

Human detection in sensitive security areas through recognition of omega shapes using MACH filters

NASA Astrophysics Data System (ADS)

Rehman, Saad; Riaz, Farhan; Hassan, Ali; Liaquat, Muwahida; Young, Rupert

2015-03-01

Human detection has gained considerable importance in aggravated security scenarios over recent times. An effective security application relies strongly on detailed information regarding the scene under consideration. A larger accumulation of humans than the number of personal authorized to visit a security controlled area must be effectively detected, amicably alarmed and immediately monitored. A framework involving a novel combination of some existing techniques allows an immediate detection of an undesirable crowd in a region under observation. Frame differencing provides a clear visibility of moving objects while highlighting those objects in each frame acquired by a real time camera. Training of a correlation pattern recognition based filter on desired shapes such as elliptical representations of human faces (variants of an Omega Shape) yields correct detections. The inherent ability of correlation pattern recognition filters caters for angular rotations in the target object and renders decision regarding the existence of the number of persons exceeding an allowed figure in the monitored area.

Correlation of crAssphage-based qPCR markers with culturable and molecular indicators of human fecal pollution in an impacted urban watershed.

PubMed

Stachler, Elyse; Akyon, Benay; Aquino de Carvalho, Nathalia; Ference, Christian; Bibby, Kyle

2018-06-06

Environmental waters are monitored for fecal pollution to protect public health. Many previously developed human-specific fecal pollution indicators lack adequate sensitivity to be reliably detected in environmental waters or do not correlate well with viral pathogens. Recently, two novel human sewage-associated source tracking qPCR markers were developed based on the bacteriophage crAssphage, CPQ_056 and CPQ_064. These assays are highly human specific, abundant in sewage, and are viral-based, suggesting great promise for environmental application as human fecal pollution indicators. A 30-day sampling study was conducted in an urban stream impacted by combined sewer overflows to evaluate the crAssphage markers' performance in an environmental system. The crAssphage markers were present at concentrations of 4.02-6.04 log10 copies/100 mL throughout the study period, indicating their high abundance and ease of detection in polluted environmental waters. In addition, the crAssphage assays were correlated with rain events, molecular markers for human polyomavirus and HF183, as well as culturable E. coli, enterococci, and somatic coliphage. The CPQ_064 assay correlated strongly to a greater number of biological indicators than the CPQ_056 assay. This study is the first to evaluate both crAssphage qPCR assays in an extended environmental application of crAssphage markers for monitoring of environmental waters. It is also the first study to compare crAssphage marker concentration with other viral-based indicators.

Detection of ground motions using high-rate GPS time-series

NASA Astrophysics Data System (ADS)

Psimoulis, Panos A.; Houlié, Nicolas; Habboub, Mohammed; Michel, Clotaire; Rothacher, Markus

2018-05-01

Monitoring surface deformation in real-time help at planning and protecting infrastructures and populations, manage sensitive production (i.e. SEVESO-type) and mitigate long-term consequences of modifications implemented. We present RT-SHAKE, an algorithm developed to detect ground motions associated with landslides, sub-surface collapses, subsidences, earthquakes or rock falls. RT-SHAKE detects first transient changes in individual GPS time series before investigating for spatial correlation(s) of observations made at neighbouring GPS sites and eventually issue a motion warning. In order to assess our algorithm on fast (seconds to minute), large (from 1 cm to meters) and spatially consistent surface motions, we use the 1 Hz GEONET GNSS network data of the Tohoku-Oki MW9.0 2011 as a test scenario. We show the delay of detection of seismic wave arrival by GPS records is of ˜10 seconds with respect to an identical analysis based on strong-motion data and this time delay depends on the level of the time-variable noise. Nevertheless, based on the analysis of the GPS network noise level and ground motion stochastic model, we show that RT-SHAKE can narrow the range of earthquake magnitude, by setting a lower threshold of detected earthquakes to MW6.5-7, if associated with a real-time automatic earthquake location system.

Techniques of contributing-area delineation for analysis of nonpoint-source contamination of Long Island, New York

USGS Publications Warehouse

Misut, P.

1995-01-01

Ninety shallow monitoring wells on Long Island, N.Y., were used to test the hypothesis that the correlation between the detection of volatile organic compounds (VOC's) at a well and explanatory variables representing land use, population density, and hydrogeologic conditions around the well is affected by the size and shape of the area defined as the contributing area. Explanatory variables are quantified through overlay of various specified contributing areas on 1:24 000-scale landuse and population-density geographic information system (GIS) coverages. Four methods of contributing-area delineation were used: (a) centering a circle of selected radius on the well site, (b) orienting a triangular area along the direction of horizontal ground-water flow to the well, (c) generating a shaped based on direction and magnitude of horizontal flow to the well, and (d) generating a shape based on three-dimensional particle pathlines backtracked from the well screen to the water table. The strongest correlations with VOC detections were obtained from circles of 400- to 1 000-meter radius. Improvement in correlation through delineations based on ground-water flow would require geographic overlay on more highly detailed GIS coverages than those used in the study.

A Space Object Detection Algorithm using Fourier Domain Likelihood Ratio Test

NASA Astrophysics Data System (ADS)

Becker, D.; Cain, S.

Space object detection is of great importance in the highly dependent yet competitive and congested space domain. Detection algorithms employed play a crucial role in fulfilling the detection component in the situational awareness mission to detect, track, characterize and catalog unknown space objects. Many current space detection algorithms use a matched filter or a spatial correlator to make a detection decision at a single pixel point of a spatial image based on the assumption that the data follows a Gaussian distribution. This paper explores the potential for detection performance advantages when operating in the Fourier domain of long exposure images of small and/or dim space objects from ground based telescopes. A binary hypothesis test is developed based on the joint probability distribution function of the image under the hypothesis that an object is present and under the hypothesis that the image only contains background noise. The detection algorithm tests each pixel point of the Fourier transformed images to make the determination if an object is present based on the criteria threshold found in the likelihood ratio test. Using simulated data, the performance of the Fourier domain detection algorithm is compared to the current algorithm used in space situational awareness applications to evaluate its value.

Target Detection of Quantum Illumination Receiver Based on Photon-subtracted Entanglement State

NASA Astrophysics Data System (ADS)

Chi, Jiao; Liu, HongJun; Huang, Nan; Wang, ZhaoLu

2017-12-01

We theoretically propose a quantum illumination receiver based on the ideal photon-subtracted two-mode squeezed state (PSTMSS) to efficiently detect the noise-hidden target. This receiver is generated by applying an optical parametric amplifier (OPA) to the cross correlation detection. With analyzing the output performance, it is found that OPA as a preposition technology of the receiver can contribute to the PSTMSS by significantly reducing the error probability than that of the general two-mode squeezed state (TMSS). Comparing with TMSS, the signal-to-noise ratio of quantum illumination based on ideal PSTMSS and OPA is improved more than 4 dB under an optimal gain of OPA. This work may provide a potential improvement in the application of accurate target detection when two kinds of resource have the identical real squeezing parameter.

Application Of The Wigner-Ville Distribution To The Identification Of Machine Noise

NASA Astrophysics Data System (ADS)

Boashash, Boualem; O'Shea, Peter

1988-02-01

The theory of signal detection using the Wigner-Ville Distribution (WVD) and the Cross Wagner-Ville Distribution (XWVD) is reviewed, and applied to the signaturing, detection, and identification of some specific machine sounds - the individual cylinder firings of a marine engine. For this task, a 4 step procedure has been devised. The Autocorrelation Function (ACF) is first employed for ascertaining the number of engine cylinders and the firing rate of the engine. Cross-correlation techniques are then used for detecting the occurrence of cylinder firing events. This is followed by the use WVD and XWVD based analyses to produce high resolution Time-Frequency signatures, and finally 2D correlations are employed for identification of the cylinders. The proposed methodology is applied to real data.

Mixed Signal Learning by Spike Correlation Propagation in Feedback Inhibitory Circuits

PubMed Central

Hiratani, Naoki; Fukai, Tomoki

2015-01-01

The brain can learn and detect mixed input signals masked by various types of noise, and spike-timing-dependent plasticity (STDP) is the candidate synaptic level mechanism. Because sensory inputs typically have spike correlation, and local circuits have dense feedback connections, input spikes cause the propagation of spike correlation in lateral circuits; however, it is largely unknown how this secondary correlation generated by lateral circuits influences learning processes through STDP, or whether it is beneficial to achieve efficient spike-based learning from uncertain stimuli. To explore the answers to these questions, we construct models of feedforward networks with lateral inhibitory circuits and study how propagated correlation influences STDP learning, and what kind of learning algorithm such circuits achieve. We derive analytical conditions at which neurons detect minor signals with STDP, and show that depending on the origin of the noise, different correlation timescales are useful for learning. In particular, we show that non-precise spike correlation is beneficial for learning in the presence of cross-talk noise. We also show that by considering excitatory and inhibitory STDP at lateral connections, the circuit can acquire a lateral structure optimal for signal detection. In addition, we demonstrate that the model performs blind source separation in a manner similar to the sequential sampling approximation of the Bayesian independent component analysis algorithm. Our results provide a basic understanding of STDP learning in feedback circuits by integrating analyses from both dynamical systems and information theory. PMID:25910189

Satellite-based overshooting top detection methods and an analysis of correlated weather conditions

NASA Astrophysics Data System (ADS)

Mikuš, Petra; Strelec Mahović, Nataša

2013-04-01

The paper addresses two topics: the possibilities of satellite-based automatic detection of overshooting convective cloud tops and the connection between the overshootings and the occurrence of severe weather on the ground. Because the use of visible images is restricted to daytime, four detection methods based on the Meteosat Second Generation SEVIRI 10.8 μm infra-red window channel and the absorption channels of water vapor (6.2 μm), ozone (9.7 μm) and carbon dioxide (13.4 μm) in the form of brightness temperature differences were used. The theoretical background of all four methods is explained, and the detection results are compared with daytime high-resolution visible (HRV) satellite images to validate each method. Of the four tested methods, the best performance is found for the combination of brightness temperature differences 6.2-10.8 and 9.7-10.8 μm, which are correlated to overshootings in HRV images in 80% of the cases. The second part of the research is focused on determining whether the appearance of the overshooting top, a manifestation of a very strong updraft in the cloud, can be connected to an abrupt change of certain weather elements on the ground. For all overshooting tops found by the above-mentioned combined method, automatic station data within the range of 0.1° and available hail observations within 0.2° were analyzed. The results show that the overshootings are connected to precipitation in 80% and to wind gusts in 70% of the cases; in contrast, a slightly lower correlation was found for temperature and humidity changes. Hail is observed in the vicinity of the overshooting in 38% of the cases.

Phase-specific Surround suppression in Mouse Primary Visual Cortex Correlates with Figure Detection Behavior Based on Phase Discontinuity.

PubMed

Li, Fengling; Jiang, Weiqian; Wang, Tian-Yi; Xie, Taorong; Yao, Haishan

2018-05-21

In the primary visual cortex (V1), neuronal responses to stimuli within the receptive field (RF) are modulated by stimuli in the RF surround. A common effect of surround modulation is surround suppression, which is dependent on the feature difference between stimuli within and surround the RF and is suggested to be involved in the perceptual phenomenon of figure-ground segregation. In this study, we examined the relationship between feature-specific surround suppression of V1 neurons and figure detection behavior based on figure-ground feature difference. We trained freely moving mice to perform a figure detection task using figure and ground gratings that differed in spatial phase. The performance of figure detection increased with the figure-ground phase difference, and was modulated by stimulus contrast. Electrophysiological recordings from V1 in head-fixed mice showed that the increase in phase difference between stimuli within and surround the RF caused a reduction in surround suppression, which was associated with an increase in V1 neural discrimination between stimuli with and without RF-surround phase difference. Consistent with the behavioral performance, the sensitivity of V1 neurons to RF-surround phase difference could be influenced by stimulus contrast. Furthermore, inhibiting V1 by optogenetically activating either parvalbumin (PV)- or somatostatin (SOM)-expressing inhibitory neurons both decreased the behavioral performance of figure detection. Thus, the phase-specific surround suppression in V1 represents a neural correlate of figure detection behavior based on figure-ground phase discontinuity. Copyright © 2018 IBRO. Published by Elsevier Ltd. All rights reserved.

Structural damage continuous monitoring by using a data driven approach based on principal component analysis and cross-correlation analysis

NASA Astrophysics Data System (ADS)

Camacho-Navarro, Jhonatan; Ruiz, Magda; Villamizar, Rodolfo; Mujica, Luis; Moreno-Beltrán, Gustavo; Quiroga, Jabid

2017-05-01

Continuous monitoring for damage detection in structural assessment comprises implementation of low cost equipment and efficient algorithms. This work describes the stages involved in the design of a methodology with high feasibility to be used in continuous damage assessment. Specifically, an algorithm based on a data-driven approach by using principal component analysis and pre-processing acquired signals by means of cross-correlation functions, is discussed. A carbon steel pipe section and a laboratory tower were used as test structures in order to demonstrate the feasibility of the methodology to detect abrupt changes in the structural response when damages occur. Two types of damage cases are studied: crack and leak for each structure, respectively. Experimental results show that the methodology is promising in the continuous monitoring of real structures.

Planning Community-Based Assessments of HIV Educational Intervention Programs in Sub-Saharan Africa

ERIC Educational Resources Information Center

Kelcey, Ben; Shen, Zuchao

2017-01-01

A key consideration in planning studies of community-based HIV education programs is identifying a sample size large enough to ensure a reasonable probability of detecting program effects if they exist. Sufficient sample sizes for community- or group-based designs are proportional to the correlation or similarity of individuals within communities.…

Assessing the role of spectral and intensity cues in spectral ripple detection and discrimination in cochlear-implant users.

PubMed

Anderson, Elizabeth S; Oxenham, Andrew J; Nelson, Peggy B; Nelson, David A

2012-12-01

Measures of spectral ripple resolution have become widely used psychophysical tools for assessing spectral resolution in cochlear-implant (CI) listeners. The objective of this study was to compare spectral ripple discrimination and detection in the same group of CI listeners. Ripple detection thresholds were measured over a range of ripple frequencies and were compared to spectral ripple discrimination thresholds previously obtained from the same CI listeners. The data showed that performance on the two measures was correlated, but that individual subjects' thresholds (at a constant spectral modulation depth) for the two tasks were not equivalent. In addition, spectral ripple detection was often found to be possible at higher rates than expected based on the available spectral cues, making it likely that temporal-envelope cues played a role at higher ripple rates. Finally, spectral ripple detection thresholds were compared to previously obtained speech-perception measures. Results confirmed earlier reports of a robust relationship between detection of widely spaced ripples and measures of speech recognition. In contrast, intensity difference limens for broadband noise did not correlate with spectral ripple detection measures, suggesting a dissociation between the ability to detect small changes in intensity across frequency and across time.

Correlation of scanning microwave interferometry and digital X-ray images for damage detection in ceramic composite armor

NASA Astrophysics Data System (ADS)

Schmidt, Karl F.; Goitia, Ryan M.; Ellingson, William A.; Green, William

2012-05-01

Application of non-contact, scanning, microwave interferometry for inspection of ceramic-based composite armor facilitates detection of defects which may occur in manufacturing or in service. Non-contact, one-side access permits inspection of panels while on the vehicle. The method was applied as a base line inspection and post-damage inspection of composite ceramic armor containing artificial defects, fiduciaries, and actual damage. Detection, sizing, and depth location capabilities were compared using microwave interferometry system and micro-focus digital x-ray imaging. The data demonstrates corroboration of microwave interference scanning detection of cracks and laminar features. The authors present details of the system operation, descriptions of the test samples used, and recent results obtained.

Texture metric that predicts target detection performance

NASA Astrophysics Data System (ADS)

Culpepper, Joanne B.

2015-12-01

Two texture metrics based on gray level co-occurrence error (GLCE) are used to predict probability of detection and mean search time. The two texture metrics are local clutter metrics and are based on the statistics of GLCE probability distributions. The degree of correlation between various clutter metrics and the target detection performance of the nine military vehicles in complex natural scenes found in the Search_2 dataset are presented. Comparison is also made between four other common clutter metrics found in the literature: root sum of squares, Doyle, statistical variance, and target structure similarity. The experimental results show that the GLCE energy metric is a better predictor of target detection performance when searching for targets in natural scenes than the other clutter metrics studied.

Efficient seeding and defragmentation of curvature streamlines for colonic polyp detection

NASA Astrophysics Data System (ADS)

Zhao, Lingxiao; Botha, Charl P.; Truyen, Roel; Vos, Frans M.; Post, Frits H.

2008-03-01

Many computer aided diagnosis (CAD) schemes have been developed for colon cancer detection using Virtual Colonoscopy (VC). In earlier work, we developed an automatic polyp detection method integrating flow visualization techniques, that forms part of the CAD functionality of an existing Virtual Colonoscopy pipeline. Curvature streamlines were used to characterize polyp surface shape. Features derived from curvature streamlines correlated highly with true polyp detections. During testing with a large number of patient data sets, we found that the correlation between streamline features and true polyps could be affected by noise and our streamline generation technique. The seeding and spacing constraints and CT noise could lead to streamline fragmentation, which reduced the discriminating power of our streamline features. In this paper, we present two major improvements of our curvature streamline generation. First, we adapted our streamline seeding strategy to the local surface properties and made the streamline generation faster. It generates a significantly smaller number of seeds but still results in a comparable and suitable streamline distribution. Second, based on our observation that longer streamlines are better surface shape descriptors, we improved our streamline tracing algorithm to produce longer streamlines. Our improved techniques are more effcient and also guide the streamline geometry to correspond better to colonic surface shape. These two adaptations support a robust and high correlation between our streamline features and true positive detections and lead to better polyp detection results.

Development and test of photon counting lidar

NASA Astrophysics Data System (ADS)

Wang, Chun-hui; Wang, Ao-you; Tao, Yu-liang; Li, Xu; Peng, Huan; Meng, Pei-bei

2018-02-01

In order to satisfy the application requirements of spaceborne three dimensional imaging lidar , a prototype of nonscanning multi-channel lidar based on receiver field of view segmentation was designed and developed. High repetition frequency micro-pulse lasers, optics fiber array and Geiger-mode APD, combination with time-correlated single photon counting technology, were adopted to achieve multi-channel detection. Ranging experiments were carried out outdoors. In low echo photon condition, target photon counting showed time correlated and noise photon counting were random. Detection probability and range precision versus threshold were described and range precision increased from 0.44 to 0.11 when threshold increased from 4 to 8.

Modeling Patterns of Activities using Activity Curves

PubMed Central

Dawadi, Prafulla N.; Cook, Diane J.; Schmitter-Edgecombe, Maureen

2016-01-01

Pervasive computing offers an unprecedented opportunity to unobtrusively monitor behavior and use the large amount of collected data to perform analysis of activity-based behavioral patterns. In this paper, we introduce the notion of an activity curve, which represents an abstraction of an individual’s normal daily routine based on automatically-recognized activities. We propose methods to detect changes in behavioral routines by comparing activity curves and use these changes to analyze the possibility of changes in cognitive or physical health. We demonstrate our model and evaluate our change detection approach using a longitudinal smart home sensor dataset collected from 18 smart homes with older adult residents. Finally, we demonstrate how big data-based pervasive analytics such as activity curve-based change detection can be used to perform functional health assessment. Our evaluation indicates that correlations do exist between behavior and health changes and that these changes can be automatically detected using smart homes, machine learning, and big data-based pervasive analytics. PMID:27346990

Modeling Patterns of Activities using Activity Curves.

PubMed

Dawadi, Prafulla N; Cook, Diane J; Schmitter-Edgecombe, Maureen

2016-06-01

Pervasive computing offers an unprecedented opportunity to unobtrusively monitor behavior and use the large amount of collected data to perform analysis of activity-based behavioral patterns. In this paper, we introduce the notion of an activity curve , which represents an abstraction of an individual's normal daily routine based on automatically-recognized activities. We propose methods to detect changes in behavioral routines by comparing activity curves and use these changes to analyze the possibility of changes in cognitive or physical health. We demonstrate our model and evaluate our change detection approach using a longitudinal smart home sensor dataset collected from 18 smart homes with older adult residents. Finally, we demonstrate how big data-based pervasive analytics such as activity curve-based change detection can be used to perform functional health assessment. Our evaluation indicates that correlations do exist between behavior and health changes and that these changes can be automatically detected using smart homes, machine learning, and big data-based pervasive analytics.

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

PubMed Central

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

2016-01-01

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

Microbial Fuels Cell-Based Biosensor for Toxicity Detection: A Review

PubMed Central

Zhou, Tuoyu; Han, Huawen; Liu, Pu; Xiong, Jian; Tian, Fake; Li, Xiangkai

2017-01-01

With the unprecedented deterioration of environmental quality, rapid recognition of toxic compounds is paramount for performing in situ real-time monitoring. Although several analytical techniques based on electrochemistry or biosensors have been developed for the detection of toxic compounds, most of them are time-consuming, inaccurate, or cumbersome for practical applications. More recently, microbial fuel cell (MFC)-based biosensors have drawn increasing interest due to their sustainability and cost-effectiveness, with applications ranging from the monitoring of anaerobic digestion process parameters (VFA) to water quality detection (e.g., COD, BOD). When a MFC runs under correct conditions, the voltage generated is correlated with the amount of a given substrate. Based on this linear relationship, several studies have demonstrated that MFC-based biosensors could detect heavy metals such as copper, chromium, or zinc, as well as organic compounds, including p-nitrophenol (PNP), formaldehyde and levofloxacin. Both bacterial consortia and single strains can be used to develop MFC-based biosensors. Biosensors with single strains show several advantages over systems integrating bacterial consortia, such as selectivity and stability. One of the limitations of such sensors is that the detection range usually exceeds the actual pollution level. Therefore, improving their sensitivity is the most important for widespread application. Nonetheless, MFC-based biosensors represent a promising approach towards single pollutant detection. PMID:28956857

Microbial Fuels Cell-Based Biosensor for Toxicity Detection: A Review.

PubMed

Zhou, Tuoyu; Han, Huawen; Liu, Pu; Xiong, Jian; Tian, Fake; Li, Xiangkai

2017-09-28

With the unprecedented deterioration of environmental quality, rapid recognition of toxic compounds is paramount for performing in situ real-time monitoring. Although several analytical techniques based on electrochemistry or biosensors have been developed for the detection of toxic compounds, most of them are time-consuming, inaccurate, or cumbersome for practical applications. More recently, microbial fuel cell (MFC)-based biosensors have drawn increasing interest due to their sustainability and cost-effectiveness, with applications ranging from the monitoring of anaerobic digestion process parameters (VFA) to water quality detection (e.g., COD, BOD). When a MFC runs under correct conditions, the voltage generated is correlated with the amount of a given substrate. Based on this linear relationship, several studies have demonstrated that MFC-based biosensors could detect heavy metals such as copper, chromium, or zinc, as well as organic compounds, including p -nitrophenol (PNP), formaldehyde and levofloxacin. Both bacterial consortia and single strains can be used to develop MFC-based biosensors. Biosensors with single strains show several advantages over systems integrating bacterial consortia, such as selectivity and stability. One of the limitations of such sensors is that the detection range usually exceeds the actual pollution level. Therefore, improving their sensitivity is the most important for widespread application. Nonetheless, MFC-based biosensors represent a promising approach towards single pollutant detection.

Electrochemical cell-based chip for the detection of toxic effects of bisphenol-A on neuroblastoma cells.

PubMed

Kafi, Md Abdul; Kim, Tae-Hyung; An, Jeung Hee; Choi, Jeong-Woo

2011-03-15

A cell-based chip was fabricated for the electrochemical detection of the dose-dependent effects of bisphenol-A (BPA) on neuroblastoma cells (SH-SY5Y), which showed dual-mode correlation as a standard curve. Toxicity assessment of BPA became very important in environmental toxicants detection since BPA can be reached out easily from various common plastic-based product and give negative cellular effects on living organism. Cell chip was fabricated by immobilizing cells on C(RGD)(4) peptide coated electrode to detect the cytotoxicity of BPA electrochemically. Redox properties in living cells were determined by cyclic voltammetry using a home-made three-electrode system, and the cathodic peak current (I(pc)) was used as a parameter for measurement of the effect of BPA on cell viability. The peak current, I(pc) value increased with the concentration of BPA up to 300 nM and then decreased because of the stimulation of cancer cell activity at the concentration of BPA below 300nM and cytotoxicity at the concentration of BPA above 300 nM, respectively. MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) assay and optical microscopy-based morphological analysis confirmed the results of electrochemical study. This dual-mode correlation between the concentration of BPA and voltammetric signal intensity should be firstly considered to analyze its dose-dependent stimulus and cytotoxic effects on neuroblastoma cells by cell chip. Copyright © 2010 Elsevier B.V. All rights reserved.

Spectroscopic techniques to study the immune response in human saliva

NASA Astrophysics Data System (ADS)

Nepomnyashchaya, E.; Savchenko, E.; Velichko, E.; Bogomaz, T.; Aksenov, E.

2018-01-01

Studies of the immune response dynamics by means of spectroscopic techniques, i.e., laser correlation spectroscopy and fluorescence spectroscopy, are described. The laser correlation spectroscopy is aimed at measuring sizes of particles in biological fluids. The fluorescence spectroscopy allows studying of the conformational and other structural changings in immune complex. We have developed a new scheme of a laser correlation spectrometer and an original signal processing algorithm. We have suggested a new fluorescence detection scheme based on a prism and an integrating pin diode. The developed system based on the spectroscopic techniques allows studies of complex process in human saliva and opens some prospects for an individual treatment of immune diseases.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Corre, G.; Boudergui, K.; Sannie, G.

Homeland security requests the use Radiation Portal Monitor (RPM). They must be able to detect and differentiate gamma and neutron radiation. Gamma detection is required for illicit transportation of radioactive matter detection. Neutron detection is important to control nonproliferation of enriched material. Manufacturers worldwide propose sensors based on {sup 3}He which give the actual state of art in term of neutron detection. The imminent shortage of {sup 3}He forces manufacturers to find viable alternative. From 10 years sensors providers have the challenge to replace previous {sup 3}He detectors that are known to be the most commonly deployed neutron sensor. Asmore » {sup 3}He detectors can only detect neutron, they must be completed with gamma detector. The proposed approach is based on pulse time correlation between adjacent sensors from signal collected by EJ200 plastic scintillators. Results obtained during FP7 Scintilla project test campaigns show the system relevance for replacement of today's {sup 3}He detectors. (authors)« less

An object-based classification method for automatic detection of lunar impact craters from topographic data

NASA Astrophysics Data System (ADS)

Vamshi, Gasiganti T.; Martha, Tapas R.; Vinod Kumar, K.

2016-05-01

Identification of impact craters is a primary requirement to study past geological processes such as impact history. They are also used as proxies for measuring relative ages of various planetary or satellite bodies and help to understand the evolution of planetary surfaces. In this paper, we present a new method using object-based image analysis (OBIA) technique to detect impact craters of wide range of sizes from topographic data. Multiresolution image segmentation of digital terrain models (DTMs) available from the NASA's LRO mission was carried out to create objects. Subsequently, objects were classified into impact craters using shape and morphometric criteria resulting in 95% detection accuracy. The methodology developed in a training area in parts of Mare Imbrium in the form of a knowledge-based ruleset when applied in another area, detected impact craters with 90% accuracy. The minimum and maximum sizes (diameters) of impact craters detected in parts of Mare Imbrium by our method are 29 m and 1.5 km, respectively. Diameters of automatically detected impact craters show good correlation (R2 > 0.85) with the diameters of manually detected impact craters.

A Portable Smart-Phone Readout Device for the Detection of Mercury Contamination Based on an Aptamer-Assay Nanosensor.

PubMed

Xiao, Wei; Xiao, Meng; Fu, Qiangqiang; Yu, Shiting; Shen, Haicong; Bian, Hongfen; Tang, Yong

2016-11-08

The detection of environmental mercury (Hg) contamination requires complex and expensive instruments and professional technicians. We present a simple, sensitive, and portable Hg 2+ detection system based on a smartphone and colorimetric aptamer nanosensor. A smartphone equipped with a light meter app was used to detect, record, and process signals from a smartphone-based microwell reader (MR S-phone), which is composed of a simple light source and a miniaturized assay platform. The colorimetric readout of the aptamer nanosensor is based on a specific interaction between the selected aptamer and Hg 2+ , which leads to a color change in the reaction solution due to an aggregation of gold nanoparticles (AuNPs). The MR S-phone-based AuNPs-aptamer colorimetric sensor system could reliably detect Hg 2+ in both tap water and Pearl River water samples and produced a linear colorimetric readout of Hg 2+ concentration in the range of 1 ng/mL-32 ng/mL with a correlation of 0.991, and a limit of detection (LOD) of 0.28 ng/mL for Hg 2+ . The detection could be quickly completed in only 20 min. Our novel mercury detection assay is simple, rapid, and sensitive, and it provides new strategies for the on-site detection of mercury contamination in any environment.

A Portable Smart-Phone Readout Device for the Detection of Mercury Contamination Based on an Aptamer-Assay Nanosensor

PubMed Central

Xiao, Wei; Xiao, Meng; Fu, Qiangqiang; Yu, Shiting; Shen, Haicong; Bian, Hongfen; Tang, Yong

2016-01-01

The detection of environmental mercury (Hg) contamination requires complex and expensive instruments and professional technicians. We present a simple, sensitive, and portable Hg2+ detection system based on a smartphone and colorimetric aptamer nanosensor. A smartphone equipped with a light meter app was used to detect, record, and process signals from a smartphone-based microwell reader (MR S-phone), which is composed of a simple light source and a miniaturized assay platform. The colorimetric readout of the aptamer nanosensor is based on a specific interaction between the selected aptamer and Hg2+, which leads to a color change in the reaction solution due to an aggregation of gold nanoparticles (AuNPs). The MR S-phone-based AuNPs-aptamer colorimetric sensor system could reliably detect Hg2+ in both tap water and Pearl River water samples and produced a linear colorimetric readout of Hg2+ concentration in the range of 1 ng/mL–32 ng/mL with a correlation of 0.991, and a limit of detection (LOD) of 0.28 ng/mL for Hg2+. The detection could be quickly completed in only 20 min. Our novel mercury detection assay is simple, rapid, and sensitive, and it provides new strategies for the on-site detection of mercury contamination in any environment. PMID:27834794

68Ga-PSMA PET/CT vs. mpMRI for locoregional prostate cancer staging: correlation with final histopathology.

PubMed

Berger, I; Annabattula, C; Lewis, J; Shetty, D V; Kam, J; Maclean, F; Arianayagam, M; Canagasingham, B; Ferguson, R; Khadra, M; Ko, R; Winter, M; Loh, H; Varol, C

2018-06-01

Prostate-specific membrane antigen (PSMA) positron emission tomography (PET) can be used to locate lesions based on PSMA avidity, however guidelines on its use are limited by its infancy. We aimed to compare multiparametric magnetic resonance imaging (mpMRI) and PSMA PET/CT to prostatectomy histopathology. We conducted a chart review from February 2015 to January 2017 of 50 male patients staged for prostate cancer using PSMA PET/CT and mpMRI who then underwent radical prostatectomy. Pre-operative PSMA PET/CT and mpMRI were paired with corresponding histopathology. Correlations, sensitivity, and specificity were used for comparisons. A total of 81 lesions were confirmed by histopathology. Fifty index lesions were detected by histopathology, all of which were detected by PSMA PET/CT (100% detection), and 47 by mpMRI (94% detection). Thirty-one histologically confirmed secondary lesions were detected, 29 of which were detected by PSMA PET/CT (93.5% detection), and 16 by mpMRI (51.6% detection). PSMA had better sensitivity for index lesion localization than mpMRI (81.1 vs. 64.8%). Specificity was similar for PSMA PET/CT and mpMRI (84.6 vs. 82.7%). SUV max of index lesions ranged from 2.9 to 39.6 (M = 9.27 ± 6.41). Index lesion SUV max was positively correlated with PSA (rho = 0.48, p < 0.001) and ISUP grade (rho = 0.51, p < 0.001). PSMA-PET/CT provided superior detection of prostate cancer lesions with better sensitivity than mpMRI. PSMA-PET/CT can be used to enhance locoregional mpMRI to provide improved detection and characterization of lesions.

Perspectives of Cross-Correlation in Seismic Monitoring at the International Data Centre

NASA Astrophysics Data System (ADS)

Bobrov, Dmitry; Kitov, Ivan; Zerbo, Lassina

2014-03-01

We demonstrate that several techniques based on waveform cross-correlation are able to significantly reduce the detection threshold of seismic sources worldwide and to improve the reliability of arrivals by a more accurate estimation of their defining parameters. A master event and the events it can find using waveform cross-correlation at array stations of the International Monitoring System (IMS) have to be close. For the purposes of the International Data Centre (IDC), one can use the spatial closeness of the master and slave events in order to construct a new automatic processing pipeline: all qualified arrivals detected using cross-correlation are associated with events matching the current IDC event definition criteria (EDC) in a local association procedure. Considering the repeating character of global seismicity, more than 90 % of events in the reviewed event bulletin (REB) can be built in this automatic processing. Due to the reduced detection threshold, waveform cross-correlation may increase the number of valid REB events by a factor of 1.5-2.0. Therefore, the new pipeline may produce a more comprehensive bulletin than the current pipeline—the goal of seismic monitoring. The analysts' experience with the cross correlation event list (XSEL) shows that the workload of interactive processing might be reduced by a factor of two or even more. Since cross-correlation produces a comprehensive list of detections for a given master event, no additional arrivals from primary stations are expected to be associated with the XSEL events. The number of false alarms, relative to the number of events rejected from the standard event list 3 (SEL3) in the current interactive processing—can also be reduced by the use of several powerful filters. The principal filter is the difference between the arrival times of the master and newly built events at three or more primary stations, which should lie in a narrow range of a few seconds. In this study, one event at a distance of about 2,000 km from the main shock was formed by three stations, with the stations and both events on the same great circle. Such spurious events are rejected by checking consistency between detections at stations at different back azimuths from the source region. Two additional effective pre-filters are f-k analysis and F prob based on correlation traces instead of original waveforms. Overall, waveform cross-correlation is able to improve the REB completeness, to reduce the workload related to IDC interactive analysis, and to provide a precise tool for quality check for both arrivals and events. Some major improvements in automatic and interactive processing achieved by cross-correlation are illustrated using an aftershock sequence from a large continental earthquake. Exploring this sequence, we describe schematically the next steps for the development of a processing pipeline parallel to the existing IDC one in order to improve the quality of the REB together with the reduction of the magnitude threshold.

Planck 2015 results: XXIII. The thermal Sunyaev-Zeldovich effect-cosmic infrared background correlation

DOE PAGES

Ade, P. A. R.; Aghanim, N.; Arnaud, M.; ...

2016-09-20

In this paper, we use Planck data to detect the cross-correlation between the thermal Sunyaev-Zeldovich (tSZ) effect and the infrared emission from the galaxies that make up the the cosmic infrared background (CIB). We first perform a stacking analysis towards Planck-confirmed galaxy clusters. We detect infrared emission produced by dusty galaxies inside these clusters and demonstrate that the infrared emission is about 50% more extended than the tSZ effect. Modelling the emission with a Navarro-Frenk-White profile, we find that the radial profile concentration parameter is c 500 = 1.00 +0.18 -0.15 . This indicates that infrared galaxies in the outskirtsmore » of clusters have higher infrared flux than cluster-core galaxies. We also study the cross-correlation between tSZ and CIB anisotropies, following three alternative approaches based on power spectrum analyses: (i) using a catalogue of confirmed clusters detected in Planck data; (ii) using an all-sky tSZ map built from Planck frequency maps; and (iii) using cross-spectra between Planck frequency maps. With the three different methods, we detect the tSZ-CIB cross-power spectrum at significance levels of (i) 6σ; (ii) 3σ; and (iii) 4σ. We model the tSZ-CIB cross-correlation signature and compare predictions with the measurements. The amplitude of the cross-correlation relative to the fiducial model is A tSZ-CIB = 1.2 ± 0.3. Finally, this result is consistent with predictions for the tSZ-CIB cross-correlation assuming the best-fit cosmological model from Planck 2015 results along with the tSZ and CIB scaling relations.« less

Planck 2015 results: XXIII. The thermal Sunyaev-Zeldovich effect-cosmic infrared background correlation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ade, P. A. R.; Aghanim, N.; Arnaud, M.

In this paper, we use Planck data to detect the cross-correlation between the thermal Sunyaev-Zeldovich (tSZ) effect and the infrared emission from the galaxies that make up the the cosmic infrared background (CIB). We first perform a stacking analysis towards Planck-confirmed galaxy clusters. We detect infrared emission produced by dusty galaxies inside these clusters and demonstrate that the infrared emission is about 50% more extended than the tSZ effect. Modelling the emission with a Navarro-Frenk-White profile, we find that the radial profile concentration parameter is c 500 = 1.00 +0.18 -0.15 . This indicates that infrared galaxies in the outskirtsmore » of clusters have higher infrared flux than cluster-core galaxies. We also study the cross-correlation between tSZ and CIB anisotropies, following three alternative approaches based on power spectrum analyses: (i) using a catalogue of confirmed clusters detected in Planck data; (ii) using an all-sky tSZ map built from Planck frequency maps; and (iii) using cross-spectra between Planck frequency maps. With the three different methods, we detect the tSZ-CIB cross-power spectrum at significance levels of (i) 6σ; (ii) 3σ; and (iii) 4σ. We model the tSZ-CIB cross-correlation signature and compare predictions with the measurements. The amplitude of the cross-correlation relative to the fiducial model is A tSZ-CIB = 1.2 ± 0.3. Finally, this result is consistent with predictions for the tSZ-CIB cross-correlation assuming the best-fit cosmological model from Planck 2015 results along with the tSZ and CIB scaling relations.« less

Rapid detection of highly pathogenic porcine reproductive and respiratory syndrome virus by a fluorescent probe-based isothermal recombinase polymerase amplification assay.

PubMed

Yang, Yang; Qin, Xiaodong; Sun, Yingjun; Chen, Ting; Zhang, Zhidong

2016-12-01

A novel fluorescent probe-based real-time reverse transcription recombinase polymerase amplification (real-time RT-RPA) assay was developed for rapid detection of highly pathogenic type 2 porcine reproductive and respiratory syndrome virus (HP-PRRSV). The sensitivity analysis showed that the detection limit of RPA was 70 copies of HP-PRRSV RNA/reaction. The real-time RT-RPA highly specific amplified HP-PRRSV with no cross-reaction with classic PRRSV, classic swine fever virus, pseudorabies virus, and foot-and-mouth disease virus. Assessment with 125 clinical samples showed that the developed real-time RT-RPA assay was well correlated with real-time RT-qPCR assays for detection of HP-PRRSV. These results suggest that the developed real-time RT-RPA assay is suitable for rapid detection of HP-PRRSV.

Eye Gaze Tracking using Correlation Filters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Karakaya, Mahmut; Boehnen, Chris Bensing; Bolme, David S

In this paper, we studied a method for eye gaze tracking that provide gaze estimation from a standard webcam with a zoom lens and reduce the setup and calibration requirements for new users. Specifically, we have developed a gaze estimation method based on the relative locations of points on the top of the eyelid and eye corners. Gaze estimation method in this paper is based on the distances between top point of the eyelid and eye corner detected by the correlation filters. Advanced correlation filters were found to provide facial landmark detections that are accurate enough to determine the subjectsmore » gaze direction up to angle of approximately 4-5 degrees although calibration errors often produce a larger overall shift in the estimates. This is approximately a circle of diameter 2 inches for a screen that is arm s length from the subject. At this accuracy it is possible to figure out what regions of text or images the subject is looking but it falls short of being able to determine which word the subject has looked at.« less

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.

Evaluation of three read-depth based CNV detection tools using whole-exome sequencing data.

PubMed

Yao, Ruen; Zhang, Cheng; Yu, Tingting; Li, Niu; Hu, Xuyun; Wang, Xiumin; Wang, Jian; Shen, Yiping

2017-01-01

Whole exome sequencing (WES) has been widely accepted as a robust and cost-effective approach for clinical genetic testing of small sequence variants. Detection of copy number variants (CNV) within WES data have become possible through the development of various algorithms and software programs that utilize read-depth as the main information. The aim of this study was to evaluate three commonly used, WES read-depth based CNV detection programs using high-resolution chromosomal microarray analysis (CMA) as a standard. Paired CMA and WES data were acquired for 45 samples. A total of 219 CNVs (size ranged from 2.3 kb - 35 mb) identified on three CMA platforms (Affymetrix, Agilent and Illumina) were used as standards. CNVs were called from WES data using XHMM, CoNIFER, and CNVnator with modified settings. All three software packages detected an elevated proportion of small variants (< 20 kb) compared to CMA. XHMM and CoNIFER had poor detection sensitivity (22.2 and 14.6%), which correlated with the number of capturing probes involved. CNVnator detected most variants and had better sensitivity (87.7%); however, suffered from an overwhelming detection of small CNVs below 20 kb, which required further confirmation. Size estimation of variants was exaggerated by CNVnator and understated by XHMM and CoNIFER. Low concordances of CNV, detected by three different read-depth based programs, indicate the immature status of WES-based CNV detection. Low sensitivity and uncertain specificity of WES-based CNV detection in comparison with CMA based CNV detection suggests that CMA will continue to play an important role in detecting clinical grade CNV in the NGS era, which is largely based on WES.

Chirp echo Fourier transform EPR-detected NMR.

PubMed

Wili, Nino; Jeschke, Gunnar

2018-04-01

A new ultra-wide band (UWB) pulse EPR method is introduced for observing all nuclear frequencies of a paramagnetic center in a single shot. It is based on burning spectral holes with a high turning angle (HTA) pulse that excites forbidden transitions and subsequent detection of the hole pattern by a chirp echo. We term this method Chirp Echo Epr SpectroscopY (CHEESY)-detected NMR. The approach is a revival of FT EPR-detected NMR. It yields similar spectra and the same type of information as electron-electron double resonance (ELDOR)-detected NMR, but with a multiplex advantage. We apply CHEESY-detected NMR in Q band to nitroxides and correlate the hyperfine spectrum to the EPR spectrum by varying the frequency of the HTA pulse. Furthermore, a selective π pulse before the HTA pulse allows for detecting hyperfine sublevel correlations between transitions of one nucleus and for elucidating the coupling regime, the same information as revealed by the HYSCORE experiment. This is demonstrated on hexaaquamanganese(II). We expect that CHEESY-detected NMR is generally applicable to disordered systems and that our results further motivate the development of EPR spectrometers capable of coherent UWB excitation and detection, especially at higher fields and frequencies. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

[Quantitative measures for assessing the functional state of the human body during diagnostic procedure].

PubMed

Artemenko, M V

2008-01-01

Two approaches to calculation of the qualitative measures for assessing the functional state level of human body are considered. These approaches are based on image and fuzzy set recognition theories and are used to construct diagnostic decision rules. The first approach uses the data on deviation of detected parameters from those for healthy persons; the second approach analyzes the degree of deviation of detected parameters from the approximants characterizing the correlation differences between the parameters. A method for synthesis of decision rules and the results of blood count-based research for a number of diseases (hemophilia, thrombocytopathy, hypertension, arrhythmia, hepatic cirrhosis, trichophytia) are considered. An effect of a change in the functional link between the cholesterol content in blood and the relative rate of variation of AST and ALT enzymes in blood from direct proportional (healthy state) to inverse proportional (hepatic cirrhosis) is discussed. It is shown that analysis of correlation changes in detected parameters of the human body state during diagnostic process is more effective for application in decision support systems than the state space analysis.

A combined approach based on MAF analysis and AHP method to fault detection mapping: A case study from a gas field, southwest of Iran

NASA Astrophysics Data System (ADS)

Shakiba, Sima; Asghari, Omid; Khah, Nasser Keshavarz Faraj

2018-01-01

A combined geostatitical methodology based on Min/Max Auto-correlation Factor (MAF) analysis and Analytical Hierarchy Process (AHP) is presented to generate a suitable Fault Detection Map (FDM) through seismic attributes. Five seismic attributes derived from a 2D time slice obtained from data related to a gas field located in southwest of Iran are used including instantaneous amplitude, similarity, energy, frequency, and Fault Enhancement Filter (FEF). The MAF analysis is implemented to reduce dimension of input variables, and then AHP method is applied on three obtained de-correlated MAF factors as evidential layer. Three Decision Makers (DMs) are used to construct PCMs for determining weights of selected evidential layer. Finally, weights obtained by AHP were multiplied in normalized valued of each alternative (MAF layers) and the concluded weighted layers were integrated in order to prepare final FDM. Results proved that applying algorithm proposed in this study generate a map more acceptable than the each individual attribute and sharpen the non-surface discontinuities as well as enhancing continuity of detected faults.

Determination of adenine based on the fluorescence recovery of the L-Tryptophan-Cu(2+) complex.

PubMed

Duan, Ruilin; Li, Chunyan; Liu, Shaopu; Liu, Zhongfang; Li, Yuanfang; Yuan, Yusheng; Hu, Xiaoli

2016-01-05

A simple and sensitive method for determination of adenine was developed based on fluorescence quenching and recovery of L-Tryptophan (L-Trp). The fluorescence of L-Trp could efficiently quenched by copper ion compared with other common metal ions. Upon addition of adenine (Ade) in L-Trp-Cu(II) system, the fluorescence was reoccurred. Under the optimum conditions, the recovery fluorescence intensity was linearly correlated with the concentration of adenine in the range from 0.34 to 25.0μmolL(-1), with a correlation coefficient (R(2)) of 0.9994. The detection limit (3σ/k) was 0.046μmolL(-1), indicating that this method could applied to detect trace adenine. In this study, amino acids including L-Trp, D-Trp, L-Tyr, D-Tyr, L-Phe, D-Phe were investigated and only L-Trp could well chelated copper ion. Additionally, the mechanism of quench and recovery also were discussed and the method was successfully applied to detect the adenine in DNA with satisfactory results. Copyright © 2015 Elsevier B.V. All rights reserved.

Correlations of Prompt and Afterglow Emission in Swift Long and Short Gamma Ray Bursts

NASA Technical Reports Server (NTRS)

Gehrel, Neil; Barthelmy, S. d.; Burrows, D. N.; Cannizzo, J. K.; Chincarini, G.; Feinmore, E.; Kouveliotou, C.; O'Brien, P.; Palmer, D. M.; Racusin, J.;

Bio-barcode gel assay for microRNA

NASA Astrophysics Data System (ADS)

Lee, Hyojin; Park, Jeong-Eun; Nam, Jwa-Min

2014-02-01

MicroRNA has been identified as a potential biomarker because expression level of microRNA is correlated with various cancers. Its detection at low concentrations would be highly beneficial for cancer diagnosis. Here, we develop a new type of a DNA-modified gold nanoparticle-based bio-barcode assay that uses a conventional gel electrophoresis platform and potassium cyanide chemistry and show this assay can detect microRNA at aM levels without enzymatic amplification. It is also shown that single-base-mismatched microRNA can be differentiated from perfectly matched microRNA and the multiplexed detection of various combinations of microRNA sequences is possible with this approach. Finally, differently expressed microRNA levels are selectively detected from cancer cells using the bio-barcode gel assay, and the results are compared with conventional polymerase chain reaction-based results. The method and results shown herein pave the way for practical use of a conventional gel electrophoresis for detecting biomolecules of interest even at aM level without polymerase chain reaction amplification.

Incoherent coincidence imaging of space objects

NASA Astrophysics Data System (ADS)

Mao, Tianyi; Chen, Qian; He, Weiji; Gu, Guohua

2016-10-01

Incoherent Coincidence Imaging (ICI), which is based on the second or higher order correlation of fluctuating light field, has provided great potentialities with respect to standard conventional imaging. However, the deployment of reference arm limits its practical applications in the detection of space objects. In this article, an optical aperture synthesis with electronically connected single-pixel photo-detectors was proposed to remove the reference arm. The correlation in our proposed method is the second order correlation between the intensity fluctuations observed by any two detectors. With appropriate locations of single-pixel detectors, this second order correlation is simplified to absolute-square Fourier transform of source and the unknown object. We demonstrate the image recovery with the Gerchberg-Saxton-like algorithms and investigate the reconstruction quality of our approach. Numerical experiments has been made to show that both binary and gray-scale objects can be recovered. This proposed method provides an effective approach to promote detection of space objects and perhaps even the exo-planets.

Illumination Invariant Change Detection (iicd): from Earth to Mars

NASA Astrophysics Data System (ADS)

Wan, X.; Liu, J.; Qin, M.; Li, S. Y.

2018-04-01

Multi-temporal Earth Observation and Mars orbital imagery data with frequent repeat coverage provide great capability for planetary surface change detection. When comparing two images taken at different times of day or in different seasons for change detection, the variation of topographic shades and shadows caused by the change of sunlight angle can be so significant that it overwhelms the real object and environmental changes, making automatic detection unreliable. An effective change detection algorithm therefore has to be robust to the illumination variation. This paper presents our research on developing and testing an Illumination Invariant Change Detection (IICD) method based on the robustness of phase correlation (PC) to the variation of solar illumination for image matching. The IICD is based on two key functions: i) initial change detection based on a saliency map derived from pixel-wise dense PC matching and ii) change quantization which combines change type identification, motion estimation and precise appearance change identification. Experiment using multi-temporal Landsat 7 ETM+ satellite images, Rapid eye satellite images and Mars HiRiSE images demonstrate that our frequency based image matching method can reach sub-pixel accuracy and thus the proposed IICD method can effectively detect and precisely segment large scale change such as landslide as well as small object change such as Mars rover, under daily and seasonal sunlight changes.

Wayside Bearing Fault Diagnosis Based on a Data-Driven Doppler Effect Eliminator and Transient Model Analysis

PubMed Central

Liu, Fang; Shen, Changqing; He, Qingbo; Zhang, Ao; Liu, Yongbin; Kong, Fanrang

2014-01-01

A fault diagnosis strategy based on the wayside acoustic monitoring technique is investigated for locomotive bearing fault diagnosis. Inspired by the transient modeling analysis method based on correlation filtering analysis, a so-called Parametric-Mother-Doppler-Wavelet (PMDW) is constructed with six parameters, including a center characteristic frequency and five kinematic model parameters. A Doppler effect eliminator containing a PMDW generator, a correlation filtering analysis module, and a signal resampler is invented to eliminate the Doppler effect embedded in the acoustic signal of the recorded bearing. Through the Doppler effect eliminator, the five kinematic model parameters can be identified based on the signal itself. Then, the signal resampler is applied to eliminate the Doppler effect using the identified parameters. With the ability to detect early bearing faults, the transient model analysis method is employed to detect localized bearing faults after the embedded Doppler effect is eliminated. The effectiveness of the proposed fault diagnosis strategy is verified via simulation studies and applications to diagnose locomotive roller bearing defects. PMID:24803197

Cold-Rolled Strip Steel Stress Detection Technology Based on a Magnetoresistance Sensor and the Magnetoelastic Effect

PubMed Central

Guan, Ben; Zang, Yong; Han, Xiaohui; Zheng, Kailun

2018-01-01

Driven by the demands for contactless stress detection, technologies are being used for shape control when producing cold-rolled strips. This paper presents a novel contactless stress detection technology based on a magnetoresistance sensor and the magnetoelastic effect, enabling the detection of internal stress in manufactured cold-rolled strips. An experimental device was designed and produced. Characteristics of this detection technology were investigated through experiments assisted by theoretical analysis. Theoretically, a linear correlation exists between the internal stress of strip steel and the voltage output of a magneto-resistive sensor. Therefore, for this stress detection system, the sensitivity of the stress detection was adjusted by adjusting the supply voltage of the magnetoresistance sensor, detection distance, and other relevant parameters. The stress detection experimental results showed that this detection system has good repeatability and linearity. The detection error was controlled within 1.5%. Moreover, the intrinsic factors of the detected strip steel, including thickness, carbon percentage, and crystal orientation, also affected the sensitivity of the detection system. The detection technology proposed in this research enables online contactless detection and meets the requirements for cold-rolled steel strips. PMID:29883387

Cold-Rolled Strip Steel Stress Detection Technology Based on a Magnetoresistance Sensor and the Magnetoelastic Effect.

PubMed

Guan, Ben; Zang, Yong; Han, Xiaohui; Zheng, Kailun

2018-05-21

Driven by the demands for contactless stress detection, technologies are being used for shape control when producing cold-rolled strips. This paper presents a novel contactless stress detection technology based on a magnetoresistance sensor and the magnetoelastic effect, enabling the detection of internal stress in manufactured cold-rolled strips. An experimental device was designed and produced. Characteristics of this detection technology were investigated through experiments assisted by theoretical analysis. Theoretically, a linear correlation exists between the internal stress of strip steel and the voltage output of a magneto-resistive sensor. Therefore, for this stress detection system, the sensitivity of the stress detection was adjusted by adjusting the supply voltage of the magnetoresistance sensor, detection distance, and other relevant parameters. The stress detection experimental results showed that this detection system has good repeatability and linearity. The detection error was controlled within 1.5%. Moreover, the intrinsic factors of the detected strip steel, including thickness, carbon percentage, and crystal orientation, also affected the sensitivity of the detection system. The detection technology proposed in this research enables online contactless detection and meets the requirements for cold-rolled steel strips.

Detection of Upscale-Crop and Partial Manipulation in Surveillance Video Based on Sensor Pattern Noise

PubMed Central

Hyun, Dai-Kyung; Ryu, Seung-Jin; Lee, Hae-Yeoun; Lee, Heung-Kyu

2013-01-01

In many court cases, surveillance videos are used as significant court evidence. As these surveillance videos can easily be forged, it may cause serious social issues, such as convicting an innocent person. Nevertheless, there is little research being done on forgery of surveillance videos. This paper proposes a forensic technique to detect forgeries of surveillance video based on sensor pattern noise (SPN). We exploit the scaling invariance of the minimum average correlation energy Mellin radial harmonic (MACE-MRH) correlation filter to reliably unveil traces of upscaling in videos. By excluding the high-frequency components of the investigated video and adaptively choosing the size of the local search window, the proposed method effectively localizes partially manipulated regions. Empirical evidence from a large database of test videos, including RGB (Red, Green, Blue)/infrared video, dynamic-/static-scene video and compressed video, indicates the superior performance of the proposed method. PMID:24051524

A New Intrusion Detection Method Based on Antibody Concentration

NASA Astrophysics Data System (ADS)

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

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

129 Xe NMR Relaxation-Based Macromolecular Sensing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gomes, Muller D.; Dao, Phuong; Jeong, Keunhong

2016-07-29

A 129Xe NMR relaxation-based sensing approach is reported on that exploits changes in the bulk xenon relaxation rate induced by slowed tumbling of a cryptophane-based sensor upon target binding. The amplification afforded by detection of the bulk dissolved xenon allows sensitive detection of targets. The sensor comprises a xenon-binding cryptophane cage, a target interaction element, and a metal chelating agent. Xenon associated with the target-bound cryptophane cage is rapidly relaxed and then detected after exchange with the bulk. Here we show that large macromolecular targets increase the rotational correlation time of xenon, increasing its relaxation rate. Upon binding of amore » biotin-containing sensor to avidin at 1.5 μM concentration, the free xenon T 2 is reduced by a factor of 4.« less

Using Activity-Related Behavioural Features towards More Effective Automatic Stress Detection

PubMed Central

Giakoumis, Dimitris; Drosou, Anastasios; Cipresso, Pietro; Tzovaras, Dimitrios; Hassapis, George; Gaggioli, Andrea; Riva, Giuseppe

2012-01-01

This paper introduces activity-related behavioural features that can be automatically extracted from a computer system, with the aim to increase the effectiveness of automatic stress detection. The proposed features are based on processing of appropriate video and accelerometer recordings taken from the monitored subjects. For the purposes of the present study, an experiment was conducted that utilized a stress-induction protocol based on the stroop colour word test. Video, accelerometer and biosignal (Electrocardiogram and Galvanic Skin Response) recordings were collected from nineteen participants. Then, an explorative study was conducted by following a methodology mainly based on spatiotemporal descriptors (Motion History Images) that are extracted from video sequences. A large set of activity-related behavioural features, potentially useful for automatic stress detection, were proposed and examined. Experimental evaluation showed that several of these behavioural features significantly correlate to self-reported stress. Moreover, it was found that the use of the proposed features can significantly enhance the performance of typical automatic stress detection systems, commonly based on biosignal processing. PMID:23028461

SCOUP: a probabilistic model based on the Ornstein-Uhlenbeck process to analyze single-cell expression data during differentiation.

PubMed

Matsumoto, Hirotaka; Kiryu, Hisanori

2016-06-08

Single-cell technologies make it possible to quantify the comprehensive states of individual cells, and have the power to shed light on cellular differentiation in particular. Although several methods have been developed to fully analyze the single-cell expression data, there is still room for improvement in the analysis of differentiation. In this paper, we propose a novel method SCOUP to elucidate differentiation process. Unlike previous dimension reduction-based approaches, SCOUP describes the dynamics of gene expression throughout differentiation directly, including the degree of differentiation of a cell (in pseudo-time) and cell fate. SCOUP is superior to previous methods with respect to pseudo-time estimation, especially for single-cell RNA-seq. SCOUP also successfully estimates cell lineage more accurately than previous method, especially for cells at an early stage of bifurcation. In addition, SCOUP can be applied to various downstream analyses. As an example, we propose a novel correlation calculation method for elucidating regulatory relationships among genes. We apply this method to a single-cell RNA-seq data and detect a candidate of key regulator for differentiation and clusters in a correlation network which are not detected with conventional correlation analysis. We develop a stochastic process-based method SCOUP to analyze single-cell expression data throughout differentiation. SCOUP can estimate pseudo-time and cell lineage more accurately than previous methods. We also propose a novel correlation calculation method based on SCOUP. SCOUP is a promising approach for further single-cell analysis and available at https://github.com/hmatsu1226/SCOUP.

Windowed Multitaper Correlation Analysis of Multimodal Brain Monitoring Parameters

PubMed Central

Proescholdt, Martin A.; Bele, Sylvia; Brawanski, Alexander

2015-01-01

Although multimodal monitoring sets the standard in daily practice of neurocritical care, problem-oriented analysis tools to interpret the huge amount of data are lacking. Recently a mathematical model was presented that simulates the cerebral perfusion and oxygen supply in case of a severe head trauma, predicting the appearance of distinct correlations between arterial blood pressure and intracranial pressure. In this study we present a set of mathematical tools that reliably detect the predicted correlations in data recorded at a neurocritical care unit. The time resolved correlations will be identified by a windowing technique combined with Fourier-based coherence calculations. The phasing of the data is detected by means of Hilbert phase difference within the above mentioned windows. A statistical testing method is introduced that allows tuning the parameters of the windowing method in such a way that a predefined accuracy is reached. With this method the data of fifteen patients were examined in which we found the predicted correlation in each patient. Additionally it could be shown that the occurrence of a distinct correlation parameter, called scp, represents a predictive value of high quality for the patients outcome. PMID:25821507

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.

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.

Anomalous Quantum Correlations of Squeezed Light

NASA Astrophysics Data System (ADS)

Kühn, B.; Vogel, W.; Mraz, M.; Köhnke, S.; Hage, B.

2017-04-01

Three different noise moments of field strength, intensity, and their correlations are simultaneously measured. For this purpose a homodyne cross-correlation measurement [1] is implemented by superimposing the signal field and a weak local oscillator on an unbalanced beam splitter. The relevant information is obtained via the intensity noise correlation of the output modes. Detection details like quantum efficiencies or uncorrelated dark noise are meaningless for our technique. Yet unknown insight in the quantumness of a squeezed signal field is retrieved from the anomalous moment, correlating field strength with intensity noise. A classical inequality including this moment is violated for almost all signal phases. Precognition on quantum theory is superfluous, as our analysis is solely based on classical physics.

A method to detect layover and shadow based on distributed spaceborne single-baseline InSAR

NASA Astrophysics Data System (ADS)

Yun, Ren; Huanxin, Zou; Shilin, Zhou; Hao, Sun; Kefeng, Ji

2014-03-01

Layover and Shadow are inevitable phenomenena in InSAR, which seriously destroy the continuity of interferometric phase images and present difficulties in the follow-up phase unwrapping. Thus, it's significant to detect layover and shadow. This paper presents an approach to detect layover and shadow using the auto-correlation matrix and amplitude of the two images. The method can make full use of the spatial information of neighboring pixels and effectively detect layover and shadow regions in the case of low registration accuracy. Experiment result on the simulated data verifies effectiveness of the algorithm.

Exploiting vibrational resonance in weak-signal detection

NASA Astrophysics Data System (ADS)

Ren, Yuhao; Pan, Yan; Duan, Fabing; Chapeau-Blondeau, François; Abbott, Derek

2017-08-01

In this paper, we investigate the first exploitation of the vibrational resonance (VR) effect to detect weak signals in the presence of strong background noise. By injecting a series of sinusoidal interference signals of the same amplitude but with different frequencies into a generalized correlation detector, we show that the detection probability can be maximized at an appropriate interference amplitude. Based on a dual-Dirac probability density model, we compare the VR method with the stochastic resonance approach via adding dichotomous noise. The compared results indicate that the VR method can achieve a higher detection probability for a wider variety of noise distributions.

Exploiting vibrational resonance in weak-signal detection.

PubMed

Ren, Yuhao; Pan, Yan; Duan, Fabing; Chapeau-Blondeau, François; Abbott, Derek

2017-08-01

In this paper, we investigate the first exploitation of the vibrational resonance (VR) effect to detect weak signals in the presence of strong background noise. By injecting a series of sinusoidal interference signals of the same amplitude but with different frequencies into a generalized correlation detector, we show that the detection probability can be maximized at an appropriate interference amplitude. Based on a dual-Dirac probability density model, we compare the VR method with the stochastic resonance approach via adding dichotomous noise. The compared results indicate that the VR method can achieve a higher detection probability for a wider variety of noise distributions.

Legally Sustainable Solutions for Privacy Issues in Collaborative Fraud Detection

NASA Astrophysics Data System (ADS)

Flegel, Ulrich; Kerschbaum, Florian; Miseldine, Philip; Monakova, Ganna; Wacker, Richard; Leymann, Frank

One company by itself cannot detect all instances of fraud or insider attacks. An example is the simple case of buyer fraud: a fraudulent buyer colludes with a supplier creating fake orders for supplies that are never delivered. They circumvent internal controls in place to prevent this kind of fraud, such as a goods receipt, e.g., by ordering services instead of goods. Based on the evidence collected at one company, it is often extremely difficult to detect such fraud, but if companies collaborate and correlate their evidence, they could detect that the ordered services have never actually been provided.

Molecular-based approaches to characterize coastal microbial community and their potential relation to the trophic state of Red Sea

PubMed Central

Ansari, Mohd Ikram; Harb, Moustapha; Jones, Burton; Hong, Pei-Ying

2015-01-01

Molecular-based approaches were used to characterize the coastal microbiota and to elucidate the trophic state of Red Sea. Nutrient content and enterococci numbers were monitored, and used to correlate with the abundance of microbial markers. Microbial source tracking revealed the presence of >1 human-associated Bacteroides spp. at some of the near-shore sampling sites and at a heavily frequented beach. Water samples collected from the beaches had occasional exceedances in enterococci numbers, higher total organic carbon (TOC, 1.48–2.18 mg/L) and nitrogen (TN, 0.15–0.27 mg/L) than that detected in the near-shore waters. Enterococci abundances obtained from next-generation sequencing did not correlate well with the cultured enterococci numbers. The abundance of certain genera, for example Arcobacter, Pseudomonas and unclassified Campylobacterales, was observed to exhibit slight correlation with TOC and TN. Low abundance of functional genes accounting for up to 41 copies/L of each Pseudomonas aeruginosa and Campylobacter coli were detected. Arcobacter butzleri was also detected in abundance ranging from 111 to 238 copies/L. Operational taxonomic units (OTUs) associated with cyanobacteria, Prochlorococcus, Ostreococcus spp. and Gramella were more prevalent in waters that were likely impacted by urban runoffs and recreational activities. These OTUs could potentially serve as quantifiable markers indicative of the water quality. PMID:25758166

Epileptic seizure detection in EEG signal using machine learning techniques.

PubMed

Jaiswal, Abeg Kumar; Banka, Haider

2018-03-01

Epilepsy is a well-known nervous system disorder characterized by seizures. Electroencephalograms (EEGs), which capture brain neural activity, can detect epilepsy. Traditional methods for analyzing an EEG signal for epileptic seizure detection are time-consuming. Recently, several automated seizure detection frameworks using machine learning technique have been proposed to replace these traditional methods. The two basic steps involved in machine learning are feature extraction and classification. Feature extraction reduces the input pattern space by keeping informative features and the classifier assigns the appropriate class label. In this paper, we propose two effective approaches involving subpattern based PCA (SpPCA) and cross-subpattern correlation-based PCA (SubXPCA) with Support Vector Machine (SVM) for automated seizure detection in EEG signals. Feature extraction was performed using SpPCA and SubXPCA. Both techniques explore the subpattern correlation of EEG signals, which helps in decision-making process. SVM is used for classification of seizure and non-seizure EEG signals. The SVM was trained with radial basis kernel. All the experiments have been carried out on the benchmark epilepsy EEG dataset. The entire dataset consists of 500 EEG signals recorded under different scenarios. Seven different experimental cases for classification have been conducted. The classification accuracy was evaluated using tenfold cross validation. The classification results of the proposed approaches have been compared with the results of some of existing techniques proposed in the literature to establish the claim.

Distributed Fault Detection Based on Credibility and Cooperation for WSNs in Smart Grids.

PubMed

Shao, Sujie; Guo, Shaoyong; Qiu, Xuesong

2017-04-28

Due to the increasingly important role in monitoring and data collection that sensors play, accurate and timely fault detection is a key issue for wireless sensor networks (WSNs) in smart grids. This paper presents a novel distributed fault detection mechanism for WSNs based on credibility and cooperation. Firstly, a reasonable credibility model of a sensor is established to identify any suspicious status of the sensor according to its own temporal data correlation. Based on the credibility model, the suspicious sensor is then chosen to launch fault diagnosis requests. Secondly, the sending time of fault diagnosis request is discussed to avoid the transmission overhead brought about by unnecessary diagnosis requests and improve the efficiency of fault detection based on neighbor cooperation. The diagnosis reply of a neighbor sensor is analyzed according to its own status. Finally, to further improve the accuracy of fault detection, the diagnosis results of neighbors are divided into several classifications to judge the fault status of the sensors which launch the fault diagnosis requests. Simulation results show that this novel mechanism can achieve high fault detection ratio with a small number of fault diagnoses and low data congestion probability.

Distributed Fault Detection Based on Credibility and Cooperation for WSNs in Smart Grids

PubMed Central

Shao, Sujie; Guo, Shaoyong; Qiu, Xuesong

2017-01-01

Due to the increasingly important role in monitoring and data collection that sensors play, accurate and timely fault detection is a key issue for wireless sensor networks (WSNs) in smart grids. This paper presents a novel distributed fault detection mechanism for WSNs based on credibility and cooperation. Firstly, a reasonable credibility model of a sensor is established to identify any suspicious status of the sensor according to its own temporal data correlation. Based on the credibility model, the suspicious sensor is then chosen to launch fault diagnosis requests. Secondly, the sending time of fault diagnosis request is discussed to avoid the transmission overhead brought about by unnecessary diagnosis requests and improve the efficiency of fault detection based on neighbor cooperation. The diagnosis reply of a neighbor sensor is analyzed according to its own status. Finally, to further improve the accuracy of fault detection, the diagnosis results of neighbors are divided into several classifications to judge the fault status of the sensors which launch the fault diagnosis requests. Simulation results show that this novel mechanism can achieve high fault detection ratio with a small number of fault diagnoses and low data congestion probability. PMID:28452925

Providing data for serrated polyp detection rate benchmarks: an analysis of the New Hampshire Colonoscopy Registry.

PubMed

Anderson, Joseph C; Butterly, Lynn F; Weiss, Julia E; Robinson, Christina M

2017-06-01

Similar to achieving adenoma detection rate (ADR) benchmarks to prevent colorectal cancer (CRC), achieving adequate serrated polyp detection rates (SDRs) may be essential to the prevention of CRC associated with the serrated pathway. Previous studies have been based on data from high-volume endoscopists at single academic centers. Based on a hypothesis that ADR is correlated with SDR, we stratified a large, diverse group of endoscopists (n = 77 practicing at 28 centers) into high performers and low performers, based on ADR, to provide data for corresponding target SDR benchmarks. By using colonoscopies in adults aged ≥50 years (4/09-12/14), we stratified endoscopists by high and low ADRs (<15%, 15%-<25%, 25%-<35%, ≥35%) to determine corresponding SDRs by using 2 SDR measures, for screening and surveillance colonoscopies separately: (1) Clinically significant SDR (CSSDR), meaning colonoscopies with any sessile serrated adenoma/polyp (SSA/P), traditional serrated adenoma (TSA), or hyperplastic polyp (HP) >1 cm anywhere in the colon or HP >5 mm in the proximal colon only divided by the total number of screening and surveillance colonoscopies, respectively. (2) Proximal SDR (PSDR) meaning colonoscopies with any serrated polyp (SSA/P, HP, TSA) of any size proximal to the sigmoid colon divided by the total number of screening and surveillance colonoscopies, respectively. A total of 45,996 (29,960 screening) colonoscopies by 77 endoscopists (28 facilities) were included. Moderately strong positive correlation coefficients were observed for screening ADR/CSSDR (P = .69) and ADR/PSDR (P = .79) and a strong positive correlation (P = .82) for CSSDR/PSDR (P < .0001 for all) was observed. For ADR ≥25%, endoscopists' median (interquartile range) screening CSSDR was 6.8% (4.3%-8.6%) and PSDR was 10.8% (8.6%-16.1%). Derived from ADR, the primary colonoscopy quality indicator, our results suggest potential SDR benchmarks (CSSDR = 7% and PSDR = 11%) that may guide adequate serrated polyp detection. Because CSSDR and PSDR are strongly correlated, endoscopists could use the simpler PSDR calculation to assess quality. Published by Elsevier Inc.

Development and Characterization of Embedded Sensory Particles Using Multi-Scale 3D Digital Image Correlation

NASA Technical Reports Server (NTRS)

Cornell, Stephen R.; Leser, William P.; Hochhalter, Jacob D.; Newman, John A.; Hartl, Darren J.

2014-01-01

A method for detecting fatigue cracks has been explored at NASA Langley Research Center. Microscopic NiTi shape memory alloy (sensory) particles were embedded in a 7050 aluminum alloy matrix to detect the presence of fatigue cracks. Cracks exhibit an elevated stress field near their tip inducing a martensitic phase transformation in nearby sensory particles. Detectable levels of acoustic energy are emitted upon particle phase transformation such that the existence and location of fatigue cracks can be detected. To test this concept, a fatigue crack was grown in a mode-I single-edge notch fatigue crack growth specimen containing sensory particles. As the crack approached the sensory particles, measurements of particle strain, matrix-particle debonding, and phase transformation behavior of the sensory particles were performed. Full-field deformation measurements were performed using a novel multi-scale optical 3D digital image correlation (DIC) system. This information will be used in a finite element-based study to determine optimal sensory material behavior and density.

Gadolinium-doped water cerenkov-based neutron and high energy gamma-ray detector and radiation portal monitoring system

DOEpatents

Dazeley, Steven A; Svoboda, Robert C; Bernstein, Adam; Bowden, Nathaniel

2013-02-12

A water Cerenkov-based neutron and high energy gamma ray detector and radiation portal monitoring system using water doped with a Gadolinium (Gd)-based compound as the Cerenkov radiator. An optically opaque enclosure is provided surrounding a detection chamber filled with the Cerenkov radiator, and photomultipliers are optically connected to the detect Cerenkov radiation generated by the Cerenkov radiator from incident high energy gamma rays or gamma rays induced by neutron capture on the Gd of incident neutrons from a fission source. The PMT signals are then used to determine time correlations indicative of neutron multiplicity events characteristic of a fission source.

Comparison of impedimetric detection of DNA hybridization on the various biosensors based on modified glassy carbon electrodes with PANHS and nanomaterials of RGO and MWCNTs.

PubMed

Benvidi, Ali; Tezerjani, Marzieh Dehghan; Jahanbani, Shahriar; Mazloum Ardakani, Mohammad; Moshtaghioun, Seyed Mohammad

2016-01-15

In this research, we have developed lable free DNA biosensors based on modified glassy carbon electrodes (GCE) with reduced graphene oxide (RGO) and carbon nanotubes (MWCNTs) for detection of DNA sequences. This paper compares the detection of BRCA1 5382insC mutation using independent glassy carbon electrodes (GCE) modified with RGO and MWCNTs. A probe (BRCA1 5382insC mutation detection (ssDNA)) was then immobilized on the modified electrodes for a specific time. The immobilization of the probe and its hybridization with the target DNA (Complementary DNA) were performed under optimum conditions using different electrochemical techniques such as cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS). The proposed biosensors were used for determination of complementary DNA sequences. The non-modified DNA biosensor (1-pyrenebutyric acid-N- hydroxysuccinimide ester (PANHS)/GCE), revealed a linear relationship between ∆Rct and logarithm of the complementary target DNA concentration ranging from 1.0×10(-16)molL(-1) to 1.0×10(-10)mol L(-1) with a correlation coefficient of 0.992, for DNA biosensors modified with multi-wall carbon nanotubes (MWCNTs) and reduced graphene oxide (RGO) wider linear range and lower detection limit were obtained. For ssDNA/PANHS/MWCNTs/GCE a linear range 1.0×10(-17)mol L(-1)-1.0×10(-10)mol L(-1) with a correlation coefficient of 0.993 and for ssDNA/PANHS/RGO/GCE a linear range from 1.0×10(-18)mol L(-1) to 1.0×10(-10)mol L(-1) with a correlation coefficient of 0.985 were obtained. In addition, the mentioned biosensors were satisfactorily applied for discriminating of complementary sequences from noncomplementary sequences, so the mentioned biosensors can be used for the detection of BRCA1-associated breast cancer. Copyright © 2015. Published by Elsevier B.V.

Unsupervised Approaches for Post-Processing in Computationally Efficient Waveform-Similarity-Based Earthquake Detection

NASA Astrophysics Data System (ADS)

Bergen, K.; Yoon, C. E.; OReilly, O. J.; Beroza, G. C.

2015-12-01

Recent improvements in computational efficiency for waveform correlation-based detections achieved by new methods such as Fingerprint and Similarity Thresholding (FAST) promise to allow large-scale blind search for similar waveforms in long-duration continuous seismic data. Waveform similarity search applied to datasets of months to years of continuous seismic data will identify significantly more events than traditional detection methods. With the anticipated increase in number of detections and associated increase in false positives, manual inspection of the detection results will become infeasible. This motivates the need for new approaches to process the output of similarity-based detection. We explore data mining techniques for improved detection post-processing. We approach this by considering similarity-detector output as a sparse similarity graph with candidate events as vertices and similarities as weighted edges. Image processing techniques are leveraged to define candidate events and combine results individually processed at multiple stations. Clustering and graph analysis methods are used to identify groups of similar waveforms and assign a confidence score to candidate detections. Anomaly detection and classification are applied to waveform data for additional false detection removal. A comparison of methods will be presented and their performance will be demonstrated on a suspected induced and non-induced earthquake sequence.

Insect detection and nitrogen management for irrigated potatoes using remote sensing from small unmanned aircraft systems

NASA Astrophysics Data System (ADS)

Hunt, E. Raymond; Rondon, Silvia I.; Hamm, Philip B.; Turner, Robert W.; Bruce, Alan E.; Brungardt, Josh J.

2016-05-01

Remote sensing with small unmanned aircraft systems (sUAS) has potential applications in agriculture because low flight altitudes allow image acquisition at very high spatial resolution. We set up experiments at the Oregon State University Hermiston Agricultural Research and Extension Center with different platforms and sensors to assess advantages and disadvantages of sUAS for precision farming. In 2013, we conducted an experiment with 4 levels of N fertilizer, and followed the changes in the normalized difference vegetation index (NDVI) over time. In late June, there were no differences in chlorophyll content or leaf area index (LAI) among the 3 higher application rates. Consistent with the field data, only plots with the lowest rate of applied N were distinguished by low NDVI. In early August, N deficiency was determined by NDVI, but it was too late to mitigate losses in potato yield and quality. Populations of the Colorado potato beetle (CPB) may rapidly increase, devouring the shoots, thus early detection and treatment could prevent yield losses. In 2014, we conducted an experiment with 4 levels of CPB infestation. Over one day, damage from CPB in some plots increased from 0 to 19%. A visual ranking of damage was not correlated with the total number of CPB or treatment. Plot-scale vegetation indices were not correlated with damage, although the damaged area determined by object-based feature extraction was highly correlated. Methods based on object-based image analysis of sUAS data have potential for early detection and reduced cost.

Quantitative molecular diagnostic assays of grain washes for Claviceps purpurea are correlated with visual determinations of ergot contamination.

PubMed

Comte, Alexia; Gräfenhan, Tom; Links, Matthew G; Hemmingsen, Sean M; Dumonceaux, Tim J

2017-01-01

We examined the epiphytic microbiome of cereal grain using the universal barcode chaperonin-60 (cpn60). Microbial community profiling of seed washes containing DNA extracts prepared from field-grown cereal grain detected sequences from a fungus identified only to Class Sordariomycetes. To identify the fungal sequence and to improve the reference database, we determined cpn60 sequences from field-collected and reference strains of the ergot fungus, Claviceps purpurea. These data allowed us to identify this fungal sequence as deriving from C. purpurea, and suggested that C. purpurea DNA is readily detectable on agricultural commodities, including those for which ergot was not identified as a grading factor. To get a sense of the prevalence and level of C. purpurea DNA in cereal grains, we developed a quantitative PCR assay based on the fungal internal transcribed spacer (ITS) and applied it to 137 samples from the 2014 crop year. The amount of Claviceps DNA quantified correlated strongly with the proportion of ergot sclerotia identified in each grain lot, although there was evidence that non-target organisms were responsible for some false positives with the ITS-based assay. We therefore developed a cpn60-targeted loop-mediated isothermal amplification assay and applied it to the same grain wash samples. The time to positive displayed a significant, inverse correlation to ergot levels determined by visual ratings. These results indicate that both laboratory-based and field-adaptable molecular diagnostic assays can be used to detect and quantify pathogen load in bulk commodities using cereal grain washes.

Quantitative molecular diagnostic assays of grain washes for Claviceps purpurea are correlated with visual determinations of ergot contamination

PubMed Central

Comte, Alexia; Gräfenhan, Tom; Links, Matthew G.; Hemmingsen, Sean M.

2017-01-01

We examined the epiphytic microbiome of cereal grain using the universal barcode chaperonin-60 (cpn60). Microbial community profiling of seed washes containing DNA extracts prepared from field-grown cereal grain detected sequences from a fungus identified only to Class Sordariomycetes. To identify the fungal sequence and to improve the reference database, we determined cpn60 sequences from field-collected and reference strains of the ergot fungus, Claviceps purpurea. These data allowed us to identify this fungal sequence as deriving from C. purpurea, and suggested that C. purpurea DNA is readily detectable on agricultural commodities, including those for which ergot was not identified as a grading factor. To get a sense of the prevalence and level of C. purpurea DNA in cereal grains, we developed a quantitative PCR assay based on the fungal internal transcribed spacer (ITS) and applied it to 137 samples from the 2014 crop year. The amount of Claviceps DNA quantified correlated strongly with the proportion of ergot sclerotia identified in each grain lot, although there was evidence that non-target organisms were responsible for some false positives with the ITS-based assay. We therefore developed a cpn60-targeted loop-mediated isothermal amplification assay and applied it to the same grain wash samples. The time to positive displayed a significant, inverse correlation to ergot levels determined by visual ratings. These results indicate that both laboratory-based and field-adaptable molecular diagnostic assays can be used to detect and quantify pathogen load in bulk commodities using cereal grain washes. PMID:28257512

Lameness detection based on multivariate continuous sensing of milk yield, rumination, and neck activity.

PubMed

Van Hertem, T; Maltz, E; Antler, A; Romanini, C E B; Viazzi, S; Bahr, C; Schlageter-Tello, A; Lokhorst, C; Berckmans, D; Halachmi, I

2013-07-01

The objective of this study was to develop and validate a mathematical model to detect clinical lameness based on existing sensor data that relate to the behavior and performance of cows in a commercial dairy farm. Identification of lame (44) and not lame (74) cows in the database was done based on the farm's daily herd health reports. All cows were equipped with a behavior sensor that measured neck activity and ruminating time. The cow's performance was measured with a milk yield meter in the milking parlor. In total, 38 model input variables were constructed from the sensor data comprising absolute values, relative values, daily standard deviations, slope coefficients, daytime and nighttime periods, variables related to individual temperament, and milk session-related variables. A lame group, cows recognized and treated for lameness, to not lame group comparison of daily data was done. Correlations between the dichotomous output variable (lame or not lame) and the model input variables were made. The highest correlation coefficient was obtained for the milk yield variable (rMY=0.45). In addition, a logistic regression model was developed based on the 7 highest correlated model input variables (the daily milk yield 4d before diagnosis; the slope coefficient of the daily milk yield 4d before diagnosis; the nighttime to daytime neck activity ratio 6d before diagnosis; the milk yield week difference ratio 4d before diagnosis; the milk yield week difference 4d before diagnosis; the neck activity level during the daytime 7d before diagnosis; the ruminating time during nighttime 6d before diagnosis). After a 10-fold cross-validation, the model obtained a sensitivity of 0.89 and a specificity of 0.85, with a correct classification rate of 0.86 when based on the averaged 10-fold model coefficients. This study demonstrates that existing farm data initially used for other purposes, such as heat detection, can be exploited for the automated detection of clinically lame animals on a daily basis as well. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

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.

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

A correlation analysis-based detection and delineation of ECG characteristic events using template waveforms extracted by ensemble averaging of clustered heart cycles.

PubMed

Homaeinezhad, M R; Erfanianmoshiri-Nejad, M; Naseri, H

2014-01-01

The goal of this study is to introduce a simple, standard and safe procedure to detect and to delineate P and T waves of the electrocardiogram (ECG) signal in real conditions. The proposed method consists of four major steps: (1) a secure QRS detection and delineation algorithm, (2) a pattern recognition algorithm designed for distinguishing various ECG clusters which take place between consecutive R-waves, (3) extracting template of the dominant events of each cluster waveform and (4) application of the correlation analysis in order to delineate automatically the P- and T-waves in noisy conditions. The performance characteristics of the proposed P and T detection-delineation algorithm are evaluated versus various ECG signals whose qualities are altered from the best to the worst cases based on the random-walk noise theory. Also, the method is applied to the MIT-BIH Arrhythmia and the QT databases for comparing some parts of its performance characteristics with a number of P and T detection-delineation algorithms. The conducted evaluations indicate that in a signal with low quality value of about 0.6, the proposed method detects the P and T events with sensitivity Se=85% and positive predictive value of P+=89%, respectively. In addition, at the same quality, the average delineation errors associated with those ECG events are 45 and 63ms, respectively. Stable delineation error, high detection accuracy and high noise tolerance were the most important aspects considered during development of the proposed method. © 2013 Elsevier Ltd. All rights reserved.

Salmonella rarely detected in Mississippi coastal waters and sediment.

PubMed

Carr, M R; Wang, S Y; McLean, T I; Flood, C J; Ellender, R D

2010-12-01

Standards for the rapid detection of individual pathogens from environmental samples have not been developed, but in their absence, the use of molecular-based detection methods coupled with traditional microbiology techniques allows for rapid and accurate pathogen detection from environmental waters and sediment. The aim of this research was to combine the use of enrichment with PCR for detection of Salmonella in Mississippi coastal waters and sediment and observe if that presence correlated with levels of enterococci and climatological variables. Salmonella were primarily found in samples that underwent nutrient enrichment and were present more frequently in freshwater than marine waters. Salmonella were detected infrequently in marine and freshwater sediments. There was a significant positive correlation between the presence of detectable Salmonella and the average enterococcal count. An inverse relationship, however, was observed between the frequency of detection and the levels of salinity, turbidity and sunlight exposure. Results from this study indicated the presence of Salmonella in Mississippi coastal waters, and sediments are very low with significant differences between freshwater and marine environments. Using pathogenic and novel nonpathogenic molecular markers, Salmonella do not appear to be a significant pathogenic genus along the Mississippi Coast. © 2010 The Authors. Journal of Applied Microbiology © 2010 The Society for Applied Microbiology.

Assessing the role of spectral and intensity cues in spectral ripple detection and discrimination in cochlear-implant users

PubMed Central

Anderson, Elizabeth S.; Oxenham, Andrew J.; Nelson, Peggy B.; Nelson, David A.

2012-01-01

Measures of spectral ripple resolution have become widely used psychophysical tools for assessing spectral resolution in cochlear-implant (CI) listeners. The objective of this study was to compare spectral ripple discrimination and detection in the same group of CI listeners. Ripple detection thresholds were measured over a range of ripple frequencies and were compared to spectral ripple discrimination thresholds previously obtained from the same CI listeners. The data showed that performance on the two measures was correlated, but that individual subjects’ thresholds (at a constant spectral modulation depth) for the two tasks were not equivalent. In addition, spectral ripple detection was often found to be possible at higher rates than expected based on the available spectral cues, making it likely that temporal-envelope cues played a role at higher ripple rates. Finally, spectral ripple detection thresholds were compared to previously obtained speech-perception measures. Results confirmed earlier reports of a robust relationship between detection of widely spaced ripples and measures of speech recognition. In contrast, intensity difference limens for broadband noise did not correlate with spectral ripple detection measures, suggesting a dissociation between the ability to detect small changes in intensity across frequency and across time. PMID:23231122

COSMOLOGY WITH THE Ep,i - Eiso CORRELATION OF GAMMA-RAY BURSTS

NASA Astrophysics Data System (ADS)

Amati, Lorenzo

2012-03-01

Gamma-Ray Bursts (GRBs) are the brightest sources in the universe, emit mostly in the hard X-ray energy band and have been detected at redshifts up to about 8.2. Thus, they are in principle very powerful probes for cosmology. I shortly review the researches aimed to use GRBs for the measurement of cosmological parameters, which are mainly based on the correlation between spectral peak photon energy and total radiated energy or luminosity. In particular, based on an enriched sample of 120 GRBs, I will provide an update of the analysis by Amati et al. (2008) aimed at extracting information on ΩM and, to a less extent, on ΩΛ, from the Ep,i - Eiso correlation.

Multivariate analysis: A statistical approach for computations

NASA Astrophysics Data System (ADS)

Michu, Sachin; Kaushik, Vandana

2014-10-01

Multivariate analysis is a type of multivariate statistical approach commonly used in, automotive diagnosis, education evaluating clusters in finance etc and more recently in the health-related professions. The objective of the paper is to provide a detailed exploratory discussion about factor analysis (FA) in image retrieval method and correlation analysis (CA) of network traffic. Image retrieval methods aim to retrieve relevant images from a collected database, based on their content. The problem is made more difficult due to the high dimension of the variable space in which the images are represented. Multivariate correlation analysis proposes an anomaly detection and analysis method based on the correlation coefficient matrix. Anomaly behaviors in the network include the various attacks on the network like DDOs attacks and network scanning.

Evolution of correlation structure of industrial indices of U.S. equity markets.

PubMed

Buccheri, Giuseppe; Marmi, Stefano; Mantegna, Rosario N

2013-07-01

We investigate the dynamics of correlations present between pairs of industry indices of U.S. stocks traded in U.S. markets by studying correlation-based networks and spectral properties of the correlation matrix. The study is performed by using 49 industry index time series computed by K. French and E. Fama during the time period from July 1969 to December 2011, which spans more than 40 years. We show that the correlation between industry indices presents both a fast and a slow dynamics. The slow dynamics has a time scale longer than 5 years, showing that a different degree of diversification of the investment is possible in different periods of time. Moreover, we also detect a fast dynamics associated with exogenous or endogenous events. The fast time scale we use is a monthly time scale and the evaluation time period is a 3-month time period. By investigating the correlation dynamics monthly, we are able to detect two examples of fast variations in the first and second eigenvalue of the correlation matrix. The first occurs during the dot-com bubble (from March 1999 to April 2001) and the second occurs during the period of highest impact of the subprime crisis (from August 2008 to August 2009).

Evolution of correlation structure of industrial indices of U.S. equity markets

NASA Astrophysics Data System (ADS)

Buccheri, Giuseppe; Marmi, Stefano; Mantegna, Rosario N.

2013-07-01

We investigate the dynamics of correlations present between pairs of industry indices of U.S. stocks traded in U.S. markets by studying correlation-based networks and spectral properties of the correlation matrix. The study is performed by using 49 industry index time series computed by K. French and E. Fama during the time period from July 1969 to December 2011, which spans more than 40 years. We show that the correlation between industry indices presents both a fast and a slow dynamics. The slow dynamics has a time scale longer than 5 years, showing that a different degree of diversification of the investment is possible in different periods of time. Moreover, we also detect a fast dynamics associated with exogenous or endogenous events. The fast time scale we use is a monthly time scale and the evaluation time period is a 3-month time period. By investigating the correlation dynamics monthly, we are able to detect two examples of fast variations in the first and second eigenvalue of the correlation matrix. The first occurs during the dot-com bubble (from March 1999 to April 2001) and the second occurs during the period of highest impact of the subprime crisis (from August 2008 to August 2009).

Person detection, tracking and following using stereo camera

NASA Astrophysics Data System (ADS)

Wang, Xiaofeng; Zhang, Lilian; Wang, Duo; Hu, Xiaoping

2018-04-01

Person detection, tracking and following is a key enabling technology for mobile robots in many human-robot interaction applications. In this article, we present a system which is composed of visual human detection, video tracking and following. The detection is based on YOLO(You only look once), which applies a single convolution neural network(CNN) to the full image, thus can predict bounding boxes and class probabilities directly in one evaluation. Then the bounding box provides initial person position in image to initialize and train the KCF(Kernelized Correlation Filter), which is a video tracker based on discriminative classifier. At last, by using a stereo 3D sparse reconstruction algorithm, not only the position of the person in the scene is determined, but also it can elegantly solve the problem of scale ambiguity in the video tracker. Extensive experiments are conducted to demonstrate the effectiveness and robustness of our human detection and tracking system.

Development of a rapid optic bacteria detecting system based on ATP bioluminescence

NASA Astrophysics Data System (ADS)

Liu, Jun Tao; Luo, JinPing; Liu, XiaoHong; Cai, XinXia

2014-12-01

A rapid optic bacteria detecting system based on the principle of Adenosine triphosphate(ATP) bioluminescence was presented in this paper. This system consisted of bioluminescence-based biosensor and the high-sensitivity optic meter. A photon counting photomultiplier tube (PMT) module was used to improve the detection sensitivity, and a NIOS II/f processor based on a Field Programmable Gate Array(FPGA) was used to control the system. In this work, Micrococcus luteus were chosen as the test sample. Several Micrococcus luteus suspension with different concentration was tested by both T2011 and plate counting method. By comparing the two group results, an calibration curve was obtained from the bioluminescence intensity for Micrococcus luteus in the range of 2.3×102 ~ 2.3×106 CFU/mL with a good correlation coefficient of 0.960. An impacting Air microorganism sampler was used to capture Airborne Bacteria, and 8 samples were collected in different place. The TBC results of 8 samples by T2011 were between 10 ~ 2×103 cfu/mL, consistent with that of plate counting method, which indicated that 8 samples were between 10 ~ 3×103 cfu/mL. For total airborne bacteria count was small, correlation coefficient was poor. Also no significant difference was found between T2011 and plate counting method by statistical analyses.

Global Membrane Protein Interactome Analysis using In vivo Crosslinking and Mass Spectrometry-based Protein Correlation Profiling*

PubMed Central

Larance, Mark; Kirkwood, Kathryn J.; Tinti, Michele; Brenes Murillo, Alejandro; Ferguson, Michael A. J.; Lamond, Angus I.

2016-01-01

We present a methodology using in vivo crosslinking combined with HPLC-MS for the global analysis of endogenous protein complexes by protein correlation profiling. Formaldehyde crosslinked protein complexes were extracted with high yield using denaturing buffers that maintained complex solubility during chromatographic separation. We show this efficiently detects both integral membrane and membrane-associated protein complexes,in addition to soluble complexes, allowing identification and analysis of complexes not accessible in native extracts. We compare the protein complexes detected by HPLC-MS protein correlation profiling in both native and formaldehyde crosslinked U2OS cell extracts. These proteome-wide data sets of both in vivo crosslinked and native protein complexes from U2OS cells are freely available via a searchable online database (www.peptracker.com/epd). Raw data are also available via ProteomeXchange (identifier PXD003754). PMID:27114452

Cooperative multi-user detection and ranging based on pseudo-random codes

NASA Astrophysics Data System (ADS)

Morhart, C.; Biebl, E. M.

2009-05-01

We present an improved approach for a Round Trip Time of Flight distance measurement system. The system is intended for the usage in a cooperative localisation system for automotive applications. Therefore, it is designed to address a large number of communication partners per measurement cycle. By using coded signals in a time divison multiple access order, we can detect a large number of pedestrian sensors with just one car sensor. We achieve this by using very short transmit bursts in combination with a real time correlation algorithm. Futhermore, the correlation approach offers real time data, concerning the time of arrival, that can serve as a trigger impulse for other comunication systems. The distance accuracy of the correlation result was further increased by adding a fourier interpolation filter. The system performance was checked with a prototype at 2.4 GHz. We reached a distance measurement accuracy of 12 cm at a range up to 450 m.

Are biotic indices sensitive to river toxicants? A comparison of metrics based on diatoms and macro-invertebrates.

PubMed

Blanco, S; Bécares, E

2010-03-01

Biotic indices based on macro-invertebrates and diatoms are frequently used to diagnose ecological quality in watercourses, but few published works have assessed their effectiveness as biomonitors of the concentration of micropollutants. A biological survey performed at 188 sites in the basin of the River Duero in north-western Spain. Nineteen diatom and six macro-invertebrate indices were calculated and compared with the concentrations of 37 different toxicants by means of a correlation analysis. Several chemical variables analysed correlated significantly with at least one biotic index. Sládecek's diatom index and the number of macro-invertebrate families exhibited particularly high correlation coefficients. Methods based on macro-invertebrates performed better in detecting biocides, while diatom indices showed stronger correlations with potentially toxic elements such as heavy metals. All biotic indices, and particularly diatom indices, were especially sensitive to the concentration of fats and oils and trichloroethene. Copyright 2010 Elsevier Ltd. All rights reserved.

A portable fluorescence detector for fast ultra trace detection of explosive vapors

NASA Astrophysics Data System (ADS)

Xin, Yunhong; He, Gang; Wang, Qi; Fang, Yu

2011-10-01

This paper developed a portable detector based on a specific material-based fluorescent sensing film for an ultra trace detection of explosives, such as 2,4,6-trinitrotoluene (TNT) or its derivate 2,4-dinitrotoluene (DNT), in ambient air or on objects tainted by explosives. The fluorescent sensing films are based on single-layer chemistry and the signal amplification effect of conjugated polymers, which exhibited higher sensitivity and shorter response time to TNT or DNT at their vapor pressures. Due to application of the light emitting diode and the solid state photomultiplier and the cross-correlation-based circuit design technology, the device has the advantages of low-power, low-cost, small size, and an improved signal to noise ratio. The results of the experiments showed that the detector can real-time detect and identify of explosive vapors at extremely low levels; it is suitable for the identification of suspect luggage, forensic analyses, or battlefields clearing.

Aptamer-Based Paper Strip Sensor for Detecting Vibrio fischeri.

PubMed

Shin, Woo-Ri; Sekhon, Simranjeet Singh; Rhee, Sung-Keun; Ko, Jung Ho; Ahn, Ji-Young; Min, Jiho; Kim, Yang-Hoon

2018-05-14

Aptamer-based paper strip sensor for detecting Vibrio fischeri was developed. Our method was based on the aptamer sandwich assay between whole live cells, V. fischeri and DNA aptamer probes. Following 9 rounds of Cell-SELEX and one of the negative-SELEX, V. fischeri Cell Aptamer (VFCA)-02 and -03 were isolated, with the former showing approximately 10-fold greater avidity (in the subnanomolar range) for the target cells when arrayed on a surface. The colorimetric response of a paper sensor based on VFCA-02 was linear in the range of 4 × 10 1 to 4 × 10 5 CFU/mL of target cell by using scanning reader. The linear regression correlation coefficient ( R 2 ) was 0.9809. This system shows promise for use in aptamer-conjugated gold nanoparticle probes in paper strip format for in-field detection of marine bioindicating bacteria.

A portable fluorescence detector for fast ultra trace detection of explosive vapors.

PubMed

Xin, Yunhong; He, Gang; Wang, Qi; Fang, Yu

2011-10-01

This paper developed a portable detector based on a specific material-based fluorescent sensing film for an ultra trace detection of explosives, such as 2,4,6-trinitrotoluene (TNT) or its derivate 2,4-dinitrotoluene (DNT), in ambient air or on objects tainted by explosives. The fluorescent sensing films are based on single-layer chemistry and the signal amplification effect of conjugated polymers, which exhibited higher sensitivity and shorter response time to TNT or DNT at their vapor pressures. Due to application of the light emitting diode and the solid state photomultiplier and the cross-correlation-based circuit design technology, the device has the advantages of low-power, low-cost, small size, and an improved signal to noise ratio. The results of the experiments showed that the detector can real-time detect and identify of explosive vapors at extremely low levels; it is suitable for the identification of suspect luggage, forensic analyses, or battlefields clearing.

An estimation of distribution method for infrared target detection based on Copulas

NASA Astrophysics Data System (ADS)

Wang, Shuo; Zhang, Yiqun

2015-10-01

Track-before-detect (TBD) based target detection involves a hypothesis test of merit functions which measure each track as a possible target track. Its accuracy depends on the precision of the distribution of merit functions, which determines the threshold for a test. Generally, merit functions are regarded Gaussian, and on this basis the distribution is estimated, which is true for most methods such as the multiple hypothesis tracking (MHT). However, merit functions for some other methods such as the dynamic programming algorithm (DPA) are non-Guassian and cross-correlated. Since existing methods cannot reasonably measure the correlation, the exact distribution can hardly be estimated. If merit functions are assumed Guassian and independent, the error between an actual distribution and its approximation may occasionally over 30 percent, and is divergent by propagation. Hence, in this paper, we propose a novel estimation of distribution method based on Copulas, by which the distribution can be estimated precisely, where the error is less than 1 percent without propagation. Moreover, the estimation merely depends on the form of merit functions and the structure of a tracking algorithm, and is invariant to measurements. Thus, the distribution can be estimated in advance, greatly reducing the demand for real-time calculation of distribution functions.

Cellular telephone-based radiation sensor and wide-area detection network

DOEpatents

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

2006-12-12

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.

Cellular telephone-based radiation detection instrument

DOEpatents

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

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.

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.

Parameter Optimization for Selected Correlation Analysis of Intracranial Pathophysiology.

PubMed

Faltermeier, Rupert; Proescholdt, Martin A; Bele, Sylvia; Brawanski, Alexander

2015-01-01

Recently we proposed a mathematical tool set, called selected correlation analysis, that reliably detects positive and negative correlations between arterial blood pressure (ABP) and intracranial pressure (ICP). Such correlations are associated with severe impairment of the cerebral autoregulation and intracranial compliance, as predicted by a mathematical model. The time resolved selected correlation analysis is based on a windowing technique combined with Fourier-based coherence calculations and therefore depends on several parameters. For real time application of this method at an ICU it is inevitable to adjust this mathematical tool for high sensitivity and distinct reliability. In this study, we will introduce a method to optimize the parameters of the selected correlation analysis by correlating an index, called selected correlation positive (SCP), with the outcome of the patients represented by the Glasgow Outcome Scale (GOS). For that purpose, the data of twenty-five patients were used to calculate the SCP value for each patient and multitude of feasible parameter sets of the selected correlation analysis. It could be shown that an optimized set of parameters is able to improve the sensitivity of the method by a factor greater than four in comparison to our first analyses.

Parameter Optimization for Selected Correlation Analysis of Intracranial Pathophysiology

PubMed Central

Faltermeier, Rupert; Proescholdt, Martin A.; Bele, Sylvia; Brawanski, Alexander

2015-01-01

Recently we proposed a mathematical tool set, called selected correlation analysis, that reliably detects positive and negative correlations between arterial blood pressure (ABP) and intracranial pressure (ICP). Such correlations are associated with severe impairment of the cerebral autoregulation and intracranial compliance, as predicted by a mathematical model. The time resolved selected correlation analysis is based on a windowing technique combined with Fourier-based coherence calculations and therefore depends on several parameters. For real time application of this method at an ICU it is inevitable to adjust this mathematical tool for high sensitivity and distinct reliability. In this study, we will introduce a method to optimize the parameters of the selected correlation analysis by correlating an index, called selected correlation positive (SCP), with the outcome of the patients represented by the Glasgow Outcome Scale (GOS). For that purpose, the data of twenty-five patients were used to calculate the SCP value for each patient and multitude of feasible parameter sets of the selected correlation analysis. It could be shown that an optimized set of parameters is able to improve the sensitivity of the method by a factor greater than four in comparison to our first analyses. PMID:26693250

Noise reduction in Lidar signal using correlation-based EMD combined with soft thresholding and roughness penalty

NASA Astrophysics Data System (ADS)

Chang, Jianhua; Zhu, Lingyan; Li, Hongxu; Xu, Fan; Liu, Binggang; Yang, Zhenbo

2018-01-01

Empirical mode decomposition (EMD) is widely used to analyze the non-linear and non-stationary signals for noise reduction. In this study, a novel EMD-based denoising method, referred to as EMD with soft thresholding and roughness penalty (EMD-STRP), is proposed for the Lidar signal denoising. With the proposed method, the relevant and irrelevant intrinsic mode functions are first distinguished via a correlation coefficient. Then, the soft thresholding technique is applied to the irrelevant modes, and the roughness penalty technique is applied to the relevant modes to extract as much information as possible. The effectiveness of the proposed method was evaluated using three typical signals contaminated by white Gaussian noise. The denoising performance was then compared to the denoising capabilities of other techniques, such as correlation-based EMD partial reconstruction, correlation-based EMD hard thresholding, and wavelet transform. The use of EMD-STRP on the measured Lidar signal resulted in the noise being efficiently suppressed, with an improved signal to noise ratio of 22.25 dB and an extended detection range of 11 km.

Dynamic Vehicle Detection via the Use of Magnetic Field Sensors

PubMed Central

Markevicius, Vytautas; Navikas, Dangirutis; Zilys, Mindaugas; Andriukaitis, Darius; Valinevicius, Algimantas; Cepenas, Mindaugas

2016-01-01

The vehicle detection process plays the key role in determining the success of intelligent transport management system solutions. The measurement of distortions of the Earth’s magnetic field using magnetic field sensors served as the basis for designing a solution aimed at vehicle detection. In accordance with the results obtained from research into process modeling and experimentally testing all the relevant hypotheses an algorithm for vehicle detection using the state criteria was proposed. Aiming to evaluate all of the possibilities, as well as pros and cons of the use of anisotropic magnetoresistance (AMR) sensors in the transport flow control process, we have performed a series of experiments with various vehicles (or different series) from several car manufacturers. A comparison of 12 selected methods, based on either the process of determining the peak signal values and their concurrence in time whilst calculating the delay, or by measuring the cross-correlation of these signals, was carried out. It was established that the relative error can be minimized via the Z component cross-correlation and Kz criterion cross-correlation methods. The average relative error of vehicle speed determination in the best case did not exceed 1.5% when the distance between sensors was set to 2 m. PMID:26797615

Capnography as a tool to detect metabolic changes in patients cared for in the emergency setting

PubMed Central

Cereceda-Sánchez, Francisco José; Molina-Mula, Jesús

2017-01-01

ABSTRACT Objective: to evaluate the usefulness of capnography for the detection of metabolic changes in spontaneous breathing patients, in the emergency and intensive care settings. Methods: in-depth and structured bibliographical search in the databases EBSCOhost, Virtual Health Library, PubMed, Cochrane Library, among others, identifying studies that assessed the relationship between capnography values and the variables involved in blood acid-base balance. Results: 19 studies were found, two were reviews and 17 were observational studies. In nine studies, capnography values were correlated with carbon dioxide (CO2), eight with bicarbonate (HCO3), three with lactate, and four with blood pH. Conclusions: most studies have found a good correlation between capnography values and blood biomarkers, suggesting the usefulness of this parameter to detect patients at risk of severe metabolic change, in a fast, economical and accurate way. PMID:28513767

Bearing Fault Detection Based on Empirical Wavelet Transform and Correlated Kurtosis by Acoustic Emission.

PubMed

Gao, Zheyu; Lin, Jing; Wang, Xiufeng; Xu, Xiaoqiang

2017-05-24

Rolling bearings are widely used in rotating equipment. Detection of bearing faults is of great importance to guarantee safe operation of mechanical systems. Acoustic emission (AE), as one of the bearing monitoring technologies, is sensitive to weak signals and performs well in detecting incipient faults. Therefore, AE is widely used in monitoring the operating status of rolling bearing. This paper utilizes Empirical Wavelet Transform (EWT) to decompose AE signals into mono-components adaptively followed by calculation of the correlated kurtosis (CK) at certain time intervals of these components. By comparing these CK values, the resonant frequency of the rolling bearing can be determined. Then the fault characteristic frequencies are found by spectrum envelope. Both simulation signal and rolling bearing AE signals are used to verify the effectiveness of the proposed method. The results show that the new method performs well in identifying bearing fault frequency under strong background noise.

Autocorrel I: A Neural Network Based Network Event Correlation Approach

DTIC Science & Technology

2005-05-01

which concern any component of the network. 2.1.1 Existing Intrusion Detection Systems EMERALD [8] is a distributed, scalable, hierarchal, customizable...writing this paper, the updaters of this system had not released their correlation unit to the public. EMERALD ex- plicitly divides statistical analysis... EMERALD , NetSTAT is scalable and composi- ble. QuidSCOR [12] is an open-source IDS, though it requires a subscription from its publisher, Qualys Inc

Mapping correlations between ventricular expansion and CSF amyloid and tau biomarkers in 240 subjects with Alzheimer’s disease, mild cognitive impairment and elderly controls

PubMed Central

Chou, Yi-Yu; Leporé, Natasha; Avedissian, Christina; Madsen, Sarah K.; Parikshak, Neelroop; Hua, Xue; Shaw, Leslie M.; Trojanowski, John Q.; Weiner, Michael W.; Toga, Arthur W.; Thompson, Paul M.

2009-01-01

Automated ventricular mapping with multi-atlas fluid image alignment reveals genetic effects in Alzheimer’s disease, NeuroImage 40(2): 615–630); with this method, we calculated minimal numbers of subjects needed to detect correlations between clinical scores and ventricular maps. We also assessed correlations between emerging CSF biomarkers of Alzheimer’s disease pathology and localizable deficits in the brain, in 80 AD, 80 mild cognitive impairment (MCI), and 80 healthy controls from the Alzheimer’s Disease Neuroimaging Initiative. Six expertly segmented images and their embedded parametric mesh surfaces were fluidly registered to each brain; segmentations were averaged within subjects to reduce errors. Surface-based statistical maps revealed powerful correlations between surface morphology and 4 variables: (1) diagnosis, (2) depression severity, (3) cognitive function at baseline, and (4) future cognitive decline over the following year. Cognitive function was assessed using the mini-mental state exam (MMSE), global and sum-of-boxes clinical dementia rating (CDR) scores, at baseline and 1-year follow-up. Lower CSF Aβ1–42 protein levels, a biomarker of AD pathology assessed in 138 of the 240 subjects, were correlated with lateral ventricular expansion. Using false discovery rate (FDR) methods, 40 and 120 subjects, respectively, were needed to discriminate AD and MCI from normal groups. 120 subjects were required to detect correlations between ventricular enlargement and MMSE, global CDR, sum-of-boxes CDR and clinical depression scores. Ventricular expansion maps correlate with pathological and cognitive measures in AD, and may be useful in future imaging-based clinical trials. PMID:19236926

Statistical characteristics of the sequential detection of signals in correlated noise

NASA Astrophysics Data System (ADS)

Averochkin, V. A.; Baranov, P. E.

1985-10-01

A solution is given to the problem of determining the distribution of the duration of the sequential two-threshold Wald rule for the time-discrete detection of determinate and Gaussian correlated signals on a background of Gaussian correlated noise. Expressions are obtained for the joint probability densities of the likelihood ratio logarithms, and an analysis is made of the effect of correlation and SNR on the duration distribution and the detection efficiency. Comparison is made with Neumann-Pearson detection.

Short-term change detection for UAV video

NASA Astrophysics Data System (ADS)

Saur, Günter; Krüger, Wolfgang

2012-11-01

In the last years, there has been an increased use of unmanned aerial vehicles (UAV) for video reconnaissance and surveillance. An important application in this context is change detection in UAV video data. Here we address short-term change detection, in which the time between observations ranges from several minutes to a few hours. We distinguish this task from video motion detection (shorter time scale) and from long-term change detection, based on time series of still images taken between several days, weeks, or even years. Examples for relevant changes we are looking for are recently parked or moved vehicles. As a pre-requisite, a precise image-to-image registration is needed. Images are selected on the basis of the geo-coordinates of the sensor's footprint and with respect to a certain minimal overlap. The automatic imagebased fine-registration adjusts the image pair to a common geometry by using a robust matching approach to handle outliers. The change detection algorithm has to distinguish between relevant and non-relevant changes. Examples for non-relevant changes are stereo disparity at 3D structures of the scene, changed length of shadows, and compression or transmission artifacts. To detect changes in image pairs we analyzed image differencing, local image correlation, and a transformation-based approach (multivariate alteration detection). As input we used color and gradient magnitude images. To cope with local misalignment of image structures we extended the approaches by a local neighborhood search. The algorithms are applied to several examples covering both urban and rural scenes. The local neighborhood search in combination with intensity and gradient magnitude differencing clearly improved the results. Extended image differencing performed better than both the correlation based approach and the multivariate alternation detection. The algorithms are adapted to be used in semi-automatic workflows for the ABUL video exploitation system of Fraunhofer IOSB, see Heinze et. al. 2010.1 In a further step we plan to incorporate more information from the video sequences to the change detection input images, e.g., by image enhancement or by along-track stereo which are available in the ABUL system.

Anthropogenic constituents in shallow ground water in the Upper Illinois River Basin

USGS Publications Warehouse

Morrow, William S.

2003-01-01

The potential for anthropogenic effects on ground water is becoming of increasing concern as land throughout the Nation becomes more urbanized. The possible contamination of water resources by volatile organic compounds (VOCs), pesticides (including transformation products), and nitrate, from current urban land use and past agricultural land use, is of particular concern. As part of the U.S. Geological Survey's National Water-Quality Assessment program, water samples for analysis of VOCs, pesticides, and nitrate were collected from 43 wells in shallow (175 feet deep or less) ground water in glacial deposits overlying a major bedrock aquifer in recently urbanized areas in the Chicago, Ill. and Milwaukee, Wis. metropolitan counties.Constituents were reported using two reporting levels. For the laboratory reporting level, the risk of a false positive or false negative detection is less than or equal to 1 percent. For the information-rich method level, estimated concentrations are identified positively and are qualified to be present on the basis of quality-control criteria, but have a higher risk of false positive detections.VOCs were detected in 32 percent (12 of 38) of the well samples with 15 detections of 7 VOCs, based on laboratory reporting levels. Concentrations ranged from 0.03 (estimated) to 4.6 micrograms per liter (?g/L), with a median concentration of 0.13 ?g/L. Methyl tert-butyl ether (MTBE) and trichloromethane (chloroform) were the most common with detections in 10 percent (4 of 38) of the well samples. Using information-rich method reporting levels, VOCs were detected in 74 percent of the wells with 37 detections of 15 VOCs. Chloroform was most common with detections in 24 percent (9 of 38) of the well samples.Pesticides were detected in 62 percent (26 of 42) of the well samples with 83 detections of 20 pesticides, based on laboratory reporting levels for the respective constituent. Concentrations ranged from 0.003 (estimated) to 3.6 (estimated) ?g/L, with a median concentration of 0.06 ?g/L. Deethylatrazine was most common with detections in 43 percent (18 of 42) of the well samples. Using information-rich method reporting levels, pesticides were detected in 74 percent (31 of 42) of the well samples with 134 detections of 29 pesticides. Deethylatrazine was most common with detections in 45 percent (19 of 42) of the well samples.Nitrate concentrations ranged from less than 0.047 to 12.5 milligrams per liter (mg/L) with a median concentration of 0.068 mg/L. Nitrate concentrations were greater than 2 mg/L in 30 percent (13 of 43) of the wells sampled. Total VOC detections did not correlate well (less than Spearman Rank correlation value of plus or minus 0.10) with well depth, age, or dissolved oxygen. Total pesticide detections did correlate with dissolved oxygen and negatively correlated with well depth. Nitrate concentrations correlated with dissolved oxygen and apparent recharge date.No VOC or pesticide concentrations exceeded U.S. Environmental Protection Agency drinking-water standards and only one nitrate 2 Anthropogenic Constituents in Shallow Ground Water in the Upper Illinois River Basin detection exceeded the standards. However, of the 43 wells sampled for VOCs or pesticides using information-rich methods, or nitrate at laboratory reporting levels, 40 of 43 (93 percent) well samples had at least one detection of a VOC or pesticide, or a detection of nitrate above 2.0 mg/L. This result indicates that most of these wells are anthropogenically affected, but presently not at U.S. Environmental Protection Agency drinking-water regulation levels of concern. The wells sampled were not public drinking-water supplies; therefore, these wells were not subject to U.S. Environmental Protection Agency drinking-water regulations.

Is the aligning prism measured with the Mallett unit correlated with fusional vergence reserves?

PubMed

Conway, Miriam L; Thomas, Jennifer; Subramanian, Ahalya

2012-01-01

The Mallett Unit is a clinical test designed to detect the fixation disparity that is most likely to occur in the presence of a decompensated heterophoria. It measures the associated phoria, which is the "aligning prism" needed to nullify the subjective disparity. The technique has gained widespread acceptance within professions such as optometry, for investigating suspected cases of decompensating heterophoria; it is, however, rarely used by orthoptists and ophthalmologists. The aim of this study was to investigate whether fusional vergence reserves, measured routinely by both orthoptists and ophthalmologists to detect heterophoria decompensation, were correlated with aligning prism (associated phoria) in a normal clinical population. Aligning prism (using the Mallett Unit) and fusional vergence reserves (using a prism bar) were measured in 500 participants (mean 41.63 years; standard deviation 11.86 years) at 40 cm and 6 m. At 40 cm a strong correlation (p<0.001) between base in aligning prism (Exo FD) and positive fusional reserves was found. Of the participants with zero aligning prism 30% had reduced fusional reserves. At 6 m a weak correlation between base out aligning prism (Eso FD) and negative fusional reserves was found to break (p = 0.01) and to recovery (p = 0.048). Of the participants with zero aligning prism 12% reported reduced fusional reserves. For near vision testing, the strong inverse correlation between base in aligning prism (Exo FD) and fusional vergence reserves supports the notion that both measures are indicators of decompensation of heterophoria. For distance vision testing and for those patients reporting zero aligning prism further research is required to determine why the relationship appears to be weak/non-existent?

Is the Aligning Prism Measured with the Mallett Unit Correlated with Fusional Vergence Reserves?

PubMed Central

Conway, Miriam L.; Thomas, Jennifer; Subramanian, Ahalya

2012-01-01

Background The Mallett Unit is a clinical test designed to detect the fixation disparity that is most likely to occur in the presence of a decompensated heterophoria. It measures the associated phoria, which is the “aligning prism” needed to nullify the subjective disparity. The technique has gained widespread acceptance within professions such as optometry, for investigating suspected cases of decompensating heterophoria; it is, however, rarely used by orthoptists and ophthalmologists. The aim of this study was to investigate whether fusional vergence reserves, measured routinely by both orthoptists and ophthalmologists to detect heterophoria decompensation, were correlated with aligning prism (associated phoria) in a normal clinical population. Methodology/Principal Findings Aligning prism (using the Mallett Unit) and fusional vergence reserves (using a prism bar) were measured in 500 participants (mean 41.63 years; standard deviation 11.86 years) at 40 cm and 6 m. At 40 cm a strong correlation (p<0.001) between base in aligning prism (Exo FD) and positive fusional reserves was found. Of the participants with zero aligning prism 30% had reduced fusional reserves. At 6 m a weak correlation between base out aligning prism (Eso FD) and negative fusional reserves was found to break (p = 0.01) and to recovery (p = 0.048). Of the participants with zero aligning prism 12% reported reduced fusional reserves. Conclusions/Significance For near vision testing, the strong inverse correlation between base in aligning prism (Exo FD) and fusional vergence reserves supports the notion that both measures are indicators of decompensation of heterophoria. For distance vision testing and for those patients reporting zero aligning prism further research is required to determine why the relationship appears to be weak/non-existent? PMID:22905174

Dysregulated Pathway Identification of Alzheimer's Disease Based on Internal Correlation Analysis of Genes and Pathways.

PubMed

Kong, Wei; Mou, Xiaoyang; Di, Benteng; Deng, Jin; Zhong, Ruxing; Wang, Shuaiqun

2017-11-20

Dysregulated pathway identification is an important task which can gain insight into the underlying biological processes of disease. Current pathway-identification methods focus on a set of co-expression genes and single pathways and ignore the correlation between genes and pathways. The method proposed in this study, takes into account the internal correlations not only between genes but also pathways to identifying dysregulated pathways related to Alzheimer's disease (AD), the most common form of dementia. In order to find the significantly differential genes for AD, mutual information (MI) is used to measure interdependencies between genes other than expression valves. Then, by integrating the topology information from KEGG, the significant pathways involved in the feature genes are identified. Next, the distance correlation (DC) is applied to measure the pairwise pathway crosstalks since DC has the advantage of detecting nonlinear correlations when compared to Pearson correlation. Finally, the pathway pairs with significantly different correlations between normal and AD samples are known as dysregulated pathways. The molecular biology analysis demonstrated that many dysregulated pathways related to AD pathogenesis have been discovered successfully by the internal correlation detection. Furthermore, the insights of the dysregulated pathways in the development and deterioration of AD will help to find new effective target genes and provide important theoretical guidance for drug design. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

A Spatially and Temporally Continuous LFE Catalogue for the Southern Alps, New Zealand

NASA Astrophysics Data System (ADS)

Chamberlain, C. J.; Townend, J.; Baratin, L. M.

2015-12-01

Using a brightness-based beamforming approach coupled with a matched-filter correlation method, we have developed a 6.5 year record of low-frequency earthquakes (LFEs) occuring on and near the deep extent of New Zealand's Alpine Fault. Our brightness template detection method, based on that of Frank et al. (2014), scans a pre-determined grid of possible seismic sources to automatically find LFE templates based on the stack of bandpassed squared seismic data. Previous work (Wech et al., 2012, Chamberlain et al., 2014) has shown that the depths of standard seismicity are anti-correlated with those of tremor and LFEs in the central Southern Alps: hence, by careful grid selection, shallow seismic sources can effectively be discriminated against. This beamforming approach produces many (>900) possible events. Initial beamforming detections are grouped by moveout and stacked to produce a subset of higher-quality events for use as templates in a cross-correlation detector. Events detected by cross-correlation are stacked to increase their signal-to-noise charectaristics before being located using a 3D velocity model. This method produces a spatially and temporally continuous catalogue of LFEs throughout the 6.5 year study period. The catalogue highlights quasi-continuous slow deformation occuring beneath the seismogenic zone near the Alpine Fault, punctuated by periods of increased LFE generation associated with tremor, and following large regional earthquakes. To date we have found no evidence of LFE generation north-east of Mt. Cook, the highest point in the Southern Alps, despite systematic searching throughout the region. We suggest that the along-strike cessation of tremor is due to changes in the fault's dip and the hypothesised presence of partially subducted passive margin material. This remnant passive margin would lie benath the tremor-generating region and has been linked to along-strike changes in subcrustal earthquake distributions (Boese et al., 2013).

MCP-1 in urine as biomarker of disease activity in Systemic Lupus Erythematosus.

PubMed

Barbado, Julia; Martin, Debora; Vega, Luisa; Almansa, Raquel; Gonçalves, Lisbeth; Nocito, Mercedes; Jimeno, Antonio; Ortiz de Lejarazu, Raúl; Bermejo-Martin, Jesus F

2012-11-01

Conventional clinical parameters are not sensitive or specific enough for detecting ongoing disease activity in the Systemic Lupus Erythematosus (SLE). Measurement of cytokines in urine is an encouraging approach to detection of early flares in this disease. Here we have profiled 27 different cytokines, chemokines and celular growth factors in the urine of 48 patients previously diagnosed of SLE as potential biomarkers of disease activity. Correlation analysis with Bonferroni correction showed that MCP-1 was the only immune mediator which levels in urine correlated directly with the SLE Disease Activity Index 2000 (SLEDAI-2K) score (correlation coefficient, p): MCP-1 (0.45,0.003). MCP-1 correlated inversely with levels of C3 complement protein in serum (-0.50,0.001). MCP-1 showed significant higher levels in patients with severe disease activity in comparison with those exhibiting mild activity. Levels of this chemokine were also higher in patients with severe disease activity in comparison with patients with inactive disease and healthy controls. Areas under receiver operating characteristic curves (AUROC) for detection of severe disease (SLEDAI⩾8) was as follows for MCP-1: [AUROC, (IC95%), p]: [0.81 (0.65-0.96) 0.003]. In addition, MCP-1 showed a good result in the AUROC analysis for detecting renal involvement [0.70 (0.52-0.87) 0.050]. When correlation analysis were repeated excluding those patients with active renal disease (n=14), levels of MCP-1 in urine kept on showing a significant positive association with SLEDAI-2K score. In conclusion, multiplex-based cytokine profiling in urine demonstrated the superiority of MCP-1 over a wide range of cytokines as biomarker of disease activity in SLE. Copyright © 2012 Elsevier Ltd. All rights reserved.

Fast Legendre moment computation for template matching

NASA Astrophysics Data System (ADS)

Li, Bing C.

2017-05-01

Normalized cross correlation (NCC) based template matching is insensitive to intensity changes and it has many applications in image processing, object detection, video tracking and pattern recognition. However, normalized cross correlation implementation is computationally expensive since it involves both correlation computation and normalization implementation. In this paper, we propose Legendre moment approach for fast normalized cross correlation implementation and show that the computational cost of this proposed approach is independent of template mask sizes which is significantly faster than traditional mask size dependent approaches, especially for large mask templates. Legendre polynomials have been widely used in solving Laplace equation in electrodynamics in spherical coordinate systems, and solving Schrodinger equation in quantum mechanics. In this paper, we extend Legendre polynomials from physics to computer vision and pattern recognition fields, and demonstrate that Legendre polynomials can help to reduce the computational cost of NCC based template matching significantly.

Hypothesis testing for differentially correlated features.

PubMed

Sheng, Elisa; Witten, Daniela; Zhou, Xiao-Hua

2016-10-01

In a multivariate setting, we consider the task of identifying features whose correlations with the other features differ across conditions. Such correlation shifts may occur independently of mean shifts, or differences in the means of the individual features across conditions. Previous approaches for detecting correlation shifts consider features simultaneously, by computing a correlation-based test statistic for each feature. However, since correlations involve two features, such approaches do not lend themselves to identifying which feature is the culprit. In this article, we instead consider a serial testing approach, by comparing columns of the sample correlation matrix across two conditions, and removing one feature at a time. Our method provides a novel perspective and favorable empirical results compared with competing approaches. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Detection of mercury compounds using invertase-glucose oxidase-based biosensor

NASA Astrophysics Data System (ADS)

Amine, A.; Cremisini, C.; Palleschi, G.

1995-10-01

Mercury compounds have been determined with an electrochemical biosensor based on invertase inhibition. When invertase is in the presence of mercury its activity decreases; this causes a decrease of glucose production which is monitored by the glucose sensor and correlated to the concentration of mercury in solution. Parameters as pH, enzyme concentration, substrate concentration, and reaction and incubation time were optimized. Mercury compounds determination using soluble or immobilized invertase were reported. Results show that the inhibition was competitive and reversible. Mercury compounds can be detected directly in aqueous solution in the range 2 - 10 ppb.

Remote detection of weak aftershocks of the DPRK underground explosions using waveform cross correlation

NASA Astrophysics Data System (ADS)

Le Bras, R.; Rozhkov, M.; Bobrov, D.; Kitov, I. O.; Sanina, I.

2017-12-01

Association of weak seismic signals generated by low-magnitude aftershocks of the DPRK underground tests into event hypotheses represent a challenge for routine automatic and interactive processing at the International Data Centre (IDC) of the Comprehensive Nuclear-Test-Ban Treaty Organization, due to the relatively low station density of the International Monitoring System (IMS) seismic network. Since 2011, as an alternative, the IDC has been testing various prototype techniques of signal detection and event creation based on waveform cross correlation. Using signals measured by seismic stations of the IMS from DPRK explosions as waveform templates, the IDC detected several small (estimated mb between 2.2 and 3.6) seismic events after two DPRK tests conducted on September 9, 2016 and September 3, 2017. The obtained detections were associated with reliable event hypothesis and then used to locate these events relative to the epicenters of the DPRK explosions. We observe high similarity of the detected signals with the corresponding waveform templates. The newly found signals also correlate well between themselves. In addition, the values of the signal-to-noise ratios (SNR) estimated using the traces of cross correlation coefficients, increase with template length (from 5 s to 150 s), providing strong evidence in favour of their spatial closeness, which allows interpreting them as explosion aftershocks. We estimated the relative magnitudes of all aftershocks using the ratio of RMS amplitudes of the master and slave signal in the cross correlation windows characterized by the highest SNR. Additional waveform data from regional non-IMS stations MDJ and SEHB provide independent validation of these aftershock hypotheses. Since waveform templates from any single master event may be sub-efficient at some stations, we have also developed a method of joint usage of the DPRK and the biggest aftershocks templates to build more robust event hypotheses.

Segmentation of the Speaker's Face Region with Audiovisual Correlation

NASA Astrophysics Data System (ADS)

Liu, Yuyu; Sato, Yoichi

The ability to find the speaker's face region in a video is useful for various applications. In this work, we develop a novel technique to find this region within different time windows, which is robust against the changes of view, scale, and background. The main thrust of our technique is to integrate audiovisual correlation analysis into a video segmentation framework. We analyze the audiovisual correlation locally by computing quadratic mutual information between our audiovisual features. The computation of quadratic mutual information is based on the probability density functions estimated by kernel density estimation with adaptive kernel bandwidth. The results of this audiovisual correlation analysis are incorporated into graph cut-based video segmentation to resolve a globally optimum extraction of the speaker's face region. The setting of any heuristic threshold in this segmentation is avoided by learning the correlation distributions of speaker and background by expectation maximization. Experimental results demonstrate that our method can detect the speaker's face region accurately and robustly for different views, scales, and backgrounds.

Comparisons of predictors for typhoid and paratyphoid fever in Kolkata, India

PubMed Central

Sur, Dipika; Ali, Mohammad; von Seidlein, Lorenz; Manna, Byomkesh; Deen, Jacqueline L; Acosta, Camilo J; Clemens, John D; Bhattacharya, Sujit K

2007-01-01

Background: Exposure of the individual to contaminated food or water correlates closely with the risk for enteric fever. Since public health interventions such as water improvement or vaccination campaigns are implemented for groups of individuals we were interested whether risk factors not only for the individual but for households, neighbourhoods and larger areas can be recognised? Methods: We conducted a large enteric fever surveillance study and analyzed factors which correlate with enteric fever on an individual level and factors associated with high and low risk areas with enteric fever incidence. Individual level data were linked to a population based geographic information systems. Individual and household level variables were fitted in Generalized Estimating Equations (GEE) with the logit link function to take into account the likelihood that household factors correlated within household members. Results: Over a 12-month period 80 typhoid fever cases and 47 paratyphoid fever cases were detected among 56,946 residents in two bustees (slums) of Kolkata, India. The incidence of paratyphoid fever was lower (0.8/1000/year), and the mean age of paratyphoid patients was older (17.1 years) than for typhoid fever (incidence 1.4/1000/year, mean age 14.7 years). Residents in areas with a high risk for typhoid fever had lower literacy rates and economic status, bigger household size, and resided closer to waterbodies and study treatment centers than residents in low risk areas. Conclusion: There was a close correlation between the characteristics detected based on individual cases and characteristics associated with high incidence areas. Because the comparison of risk factors of populations living in high versus low risk areas is statistically very powerful this methodology holds promise to detect risk factors associated with diseases using geographic information systems. PMID:17935611

Covariance descriptor fusion for target detection

NASA Astrophysics Data System (ADS)

Cukur, Huseyin; Binol, Hamidullah; Bal, Abdullah; Yavuz, Fatih

2016-05-01

Target detection is one of the most important topics for military or civilian applications. In order to address such detection tasks, hyperspectral imaging sensors provide useful images data containing both spatial and spectral information. Target detection has various challenging scenarios for hyperspectral images. To overcome these challenges, covariance descriptor presents many advantages. Detection capability of the conventional covariance descriptor technique can be improved by fusion methods. In this paper, hyperspectral bands are clustered according to inter-bands correlation. Target detection is then realized by fusion of covariance descriptor results based on the band clusters. The proposed combination technique is denoted Covariance Descriptor Fusion (CDF). The efficiency of the CDF is evaluated by applying to hyperspectral imagery to detect man-made objects. The obtained results show that the CDF presents better performance than the conventional covariance descriptor.

Reversible thrombin detection by aptamer functionalized STING sensors

PubMed Central

Actis, Paolo; Rogers, Adam; Nivala, Jeff; Vilozny, Boaz; Seger, R. Adam; Jejelowo, Olufisayo; Pourmand, Nader

2011-01-01

Signal Transduction by Ion NanoGating (STING) is a label-free technology based on functionalized quartz nanopipettes. The nanopipette pore can be decorated with a variety of recognition elements and the molecular interaction is transduced via a simple electrochemical system. A STING sensor can be easily and reproducibly fabricated and tailored at the bench starting from inexpensive quartz capillaries. The analytical application of this new biosensing platform, however, was limited due to the difficult correlation between the measured ionic current and the analyte concentration in solution. Here we show that STING sensors functionalized with aptamers allow the quantitative detection of thrombin. The binding of thrombin generates a signal that can be directly correlated to its concentration in the bulk solution. PMID:21636261

Water conservation study. Badger Army Ammunition Plant, Baraboo, Wisconsin. Final report

DOE Office of Scientific and Technical Information (OSTI.GOV)

NONE

1995-05-01

The purpose of this water conservation study is to identify projects which result in energy maintenance and cost savings in the process water distribution system at Badger Army Ammunition Plant (BAAP) in Baraboo, Wisconsin. A leak detection survey was performed on all process water piping with a diameter of 6 inches or greater. The leak detection analysis was performed using a combination of listening devices and preamplified-transducer systems to identify the majority of leak locations. When the location of the leak could not be readily identified using these methods, a leak correlator was used. The leak correlator determines leak locationmore » based on the time it takes for sound to travel from the leak to a waterline connection point.« less

Distributed strain measurement and possible breakage detection of optical-fiber-embedded composite structure using slope-assisted Brillouin optical correlation-domain reflectometry

NASA Astrophysics Data System (ADS)

Lee, Heeyoung; Ochi, Yutaka; Matsui, Takahiro; Matsumoto, Yukihiro; Tanaka, Yosuke; Nakamura, Hitoshi; Mizuno, Yosuke; Nakamura, Kentaro

2018-07-01

Slope-assisted Brillouin optical correlation-domain reflectometry (SA-BOCDR) is a recently developed structural health monitoring technique for measurements of strain, temperature, and loss distributions along optical fibers. Although the basic operational principle of this method has been clarified, no measurements using optical fibers embedded in actual structures have been reported. As a first step towards such practical applications, in this study, we present an example of an SA-BOCDR-based diagnosis using a composite structure with carbon fiber-reinforced plastics. The system’s output agrees well with the actual strain distributions. We were also able to detect the breakage of the embedded fiber, thus demonstrating the promise of SA-BOCDR for practical applications.

Correlated ion and neutral time of flight technique combined with velocity map imaging: Quantitative measurements for dissociation processes in excited molecular nano-systems

NASA Astrophysics Data System (ADS)

Berthias, F.; Feketeová, L.; Della Negra, R.; Dupasquier, T.; Fillol, R.; Abdoul-Carime, H.; Farizon, B.; Farizon, M.; Märk, T. D.

2018-01-01

The combination of the Dispositif d'Irradiation d'Agrégats Moléculaire with the correlated ion and neutral time of flight-velocity map imaging technique provides a new way to explore processes occurring subsequent to the excitation of charged nano-systems. The present contribution describes in detail the methods developed for the quantitative measurement of branching ratios and cross sections for collision-induced dissociation processes of water cluster nano-systems. These methods are based on measurements of the detection efficiency of neutral fragments produced in these dissociation reactions. Moreover, measured detection efficiencies are used here to extract the number of neutral fragments produced for a given charged fragment.

The correlation study of parallel feature extractor and noise reduction approaches

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dewi, Deshinta Arrova; Sundararajan, Elankovan; Prabuwono, Anton Satria

2015-05-15

This paper presents literature reviews that show variety of techniques to develop parallel feature extractor and finding its correlation with noise reduction approaches for low light intensity images. Low light intensity images are normally displayed as darker images and low contrast. Without proper handling techniques, those images regularly become evidences of misperception of objects and textures, the incapability to section them. The visual illusions regularly clues to disorientation, user fatigue, poor detection and classification performance of humans and computer algorithms. Noise reduction approaches (NR) therefore is an essential step for other image processing steps such as edge detection, image segmentation,more » image compression, etc. Parallel Feature Extractor (PFE) meant to capture visual contents of images involves partitioning images into segments, detecting image overlaps if any, and controlling distributed and redistributed segments to extract the features. Working on low light intensity images make the PFE face challenges and closely depend on the quality of its pre-processing steps. Some papers have suggested many well established NR as well as PFE strategies however only few resources have suggested or mentioned the correlation between them. This paper reviews best approaches of the NR and the PFE with detailed explanation on the suggested correlation. This finding may suggest relevant strategies of the PFE development. With the help of knowledge based reasoning, computational approaches and algorithms, we present the correlation study between the NR and the PFE that can be useful for the development and enhancement of other existing PFE.« less

Optical remote sensing and correlation of office equipment functional state and stress levels via power quality disturbances inefficiencies

NASA Astrophysics Data System (ADS)

Sternberg, Oren; Bednarski, Valerie R.; Perez, Israel; Wheeland, Sara; Rockway, John D.

2016-09-01

Non-invasive optical techniques pertaining to the remote sensing of power quality disturbances (PQD) are part of an emerging technology field typically dominated by radio frequency (RF) and invasive-based techniques. Algorithms and methods to analyze and address PQD such as probabilistic neural networks and fully informed particle swarms have been explored in industry and academia. Such methods are tuned to work with RF equipment and electronics in existing power grids. As both commercial and defense assets are heavily power-dependent, understanding electrical transients and failure events using non-invasive detection techniques is crucial. In this paper we correlate power quality empirical models to the observed optical response. We also empirically demonstrate a first-order approach to map household, office and commercial equipment PQD to user functions and stress levels. We employ a physics-based image and signal processing approach, which demonstrates measured non-invasive (remote sensing) techniques to detect and map the base frequency associated with the power source to the various PQD on a calibrated source.

Solvent-accessible surface area: How well can be applied to hot-spot detection?

PubMed

Martins, João M; Ramos, Rui M; Pimenta, António C; Moreira, Irina S

2014-03-01

A detailed comprehension of protein-based interfaces is essential for the rational drug development. One of the key features of these interfaces is their solvent accessible surface area profile. With that in mind, we tested a group of 12 SASA-based features for their ability to correlate and differentiate hot- and null-spots. These were tested in three different data sets, explicit water MD, implicit water MD, and static PDB structure. We found no discernible improvement with the use of more comprehensive data sets obtained from molecular dynamics. The features tested were shown to be capable of discerning between hot- and null-spots, while presenting low correlations. Residue standardization such as rel SASAi or rel/res SASAi , improved the features as a tool to predict ΔΔGbinding values. A new method using support machine learning algorithms was developed: SBHD (Sasa-Based Hot-spot Detection). This method presents a precision, recall, and F1 score of 0.72, 0.81, and 0.76 for the training set and 0.91, 0.73, and 0.81 for an independent test set. Copyright © 2013 Wiley Periodicals, Inc.

Figures of merit for detectors in digital radiography. II. Finite number of secondaries and structured backgrounds.

PubMed

Pineda, Angel R; Barrett, Harrison H

2004-02-01

The current paradigm for evaluating detectors in digital radiography relies on Fourier methods. Fourier methods rely on a shift-invariant and statistically stationary description of the imaging system. The theoretical justification for the use of Fourier methods is based on a uniform background fluence and an infinite detector. In practice, the background fluence is not uniform and detector size is finite. We study the effect of stochastic blurring and structured backgrounds on the correlation between Fourier-based figures of merit and Hotelling detectability. A stochastic model of the blurring leads to behavior similar to what is observed by adding electronic noise to the deterministic blurring model. Background structure does away with the shift invariance. Anatomical variation makes the covariance matrix of the data less amenable to Fourier methods by introducing long-range correlations. It is desirable to have figures of merit that can account for all the sources of variation, some of which are not stationary. For such cases, we show that the commonly used figures of merit based on the discrete Fourier transform can provide an inaccurate estimate of Hotelling detectability.

Empirical Determination of Efficient Sensing Frequencies for Magnetometer-Based Continuous Human Contact Monitoring.

PubMed

Kuk, Seungho; Kim, Junha; Park, Yongtae; Kim, Hyogon

2018-04-27

The high linear correlation between the smartphone magnetometer readings in close proximity can be exploited for physical human contact detection, which could be useful for such applications as infectious disease contact tracing or social behavior monitoring. Alternative approaches using other capabilities in smartphones have aspects that do not fit well with the human contact detection. Using Wi-Fi or cellular fingerprints have larger localization errors than close human contact distances. Bluetooth beacons could reveal the identity of the transmitter, threatening the privacy of the user. Also, using sensors such as GPS does not work for indoor contacts. However, the magnetometer correlation check works best in human contact distances that matter in infectious disease transmissions or social interactions. The omni-present geomagnetism makes it work both indoors and outdoors, and the measured magnetometer values do not easily reveal the identity and the location of the smartphone. One issue with the magnetometer-based contact detection, however, is the energy consumption. Since the contacts can take place anytime, the magnetometer sensing and recording should be running continuously. Therefore, how we address the energy requirement for the extended and continuous operation can decide the viability of the whole idea. However, then, we note that almost all existing magnetometer-based applications such as indoor location and navigation have used high sensing frequencies, ranging from 10 Hz to 200 Hz. At these frequencies, we measure that the time to complete battery drain in a typical smartphone is shortened by three to twelve hours. The heavy toll raises the question as to whether the magnetometer-based contact detection can avoid such high sensing rates while not losing the contact detection accuracy. In order to answer the question, we conduct a measurement-based study using independently produced magnetometer traces from three different countries. Specifically, we gradually remove high frequency components in the traces, while observing the correlation changes. As a result, we find that the human coexistence detection indeed tends to be no less, if not more, effective at the sampling frequency of 1 Hz or even less. This is because unlike the other applications that require centimeter-level precision, the human contacts detected anywhere within a couple of meters are valid for our purpose. With the typical smartphone battery capacity and at the 1 Hz sensing, the battery consumption is well below an hour, which is smaller by more than two hours compared with 10 Hz sampling and by almost eleven hours compared with 200 Hz sampling. With other tasks running simultaneously on smartphones, the energy saving aspect will only become more critical. Therefore, we conclude that sensing the ambient magnetic field at 1 Hz is sufficient for the human contact monitoring purpose. We expect that this finding will have a significant practicability implication in the smartphone magnetometer-based contact monitoring applications in general.

Empirical Determination of Efficient Sensing Frequencies for Magnetometer-Based Continuous Human Contact Monitoring

PubMed Central

Kuk, Seungho; Kim, Junha; Park, Yongtae; Kim, Hyogon

2018-01-01

The high linear correlation between the smartphone magnetometer readings in close proximity can be exploited for physical human contact detection, which could be useful for such applications as infectious disease contact tracing or social behavior monitoring. Alternative approaches using other capabilities in smartphones have aspects that do not fit well with the human contact detection. Using Wi-Fi or cellular fingerprints have larger localization errors than close human contact distances. Bluetooth beacons could reveal the identity of the transmitter, threatening the privacy of the user. Also, using sensors such as GPS does not work for indoor contacts. However, the magnetometer correlation check works best in human contact distances that matter in infectious disease transmissions or social interactions. The omni-present geomagnetism makes it work both indoors and outdoors, and the measured magnetometer values do not easily reveal the identity and the location of the smartphone. One issue with the magnetometer-based contact detection, however, is the energy consumption. Since the contacts can take place anytime, the magnetometer sensing and recording should be running continuously. Therefore, how we address the energy requirement for the extended and continuous operation can decide the viability of the whole idea. However, then, we note that almost all existing magnetometer-based applications such as indoor location and navigation have used high sensing frequencies, ranging from 10 Hz to 200 Hz. At these frequencies, we measure that the time to complete battery drain in a typical smartphone is shortened by three to twelve hours. The heavy toll raises the question as to whether the magnetometer-based contact detection can avoid such high sensing rates while not losing the contact detection accuracy. In order to answer the question, we conduct a measurement-based study using independently produced magnetometer traces from three different countries. Specifically, we gradually remove high frequency components in the traces, while observing the correlation changes. As a result, we find that the human coexistence detection indeed tends to be no less, if not more, effective at the sampling frequency of 1 Hz or even less. This is because unlike the other applications that require centimeter-level precision, the human contacts detected anywhere within a couple of meters are valid for our purpose. With the typical smartphone battery capacity and at the 1 Hz sensing, the battery consumption is well below an hour, which is smaller by more than two hours compared with 10 Hz sampling and by almost eleven hours compared with 200 Hz sampling. With other tasks running simultaneously on smartphones, the energy saving aspect will only become more critical. Therefore, we conclude that sensing the ambient magnetic field at 1 Hz is sufficient for the human contact monitoring purpose. We expect that this finding will have a significant practicability implication in the smartphone magnetometer-based contact monitoring applications in general. PMID:29702586

A study on new method of noninvasive esophageal venous pressure measurement based on the airflow and laser detection technology.

PubMed

Hu, Chenghuan; Huang, Feizhou; Zhang, Rui; Zhu, Shaihong; Nie, Wanpin; Liu, Xunyang; Liu, Yinglong; Li, Peng

2015-01-01

Using optics combined with automatic control and computer real-time image detection technology, a novel noninvasive method of noncontact pressure manometry was developed based on the airflow and laser detection technology in this study. The new esophageal venous pressure measurement system was tested in-vitro experiments. A stable and adjustable pulse stream was produced from a self-developed pump and a laser emitting apparatus could generate optical signals which can be captured by image acquisition and analysis system program. A synchronization system simultaneous measured the changes of air pressure and the deformation of the vein wall to capture the vascular deformation while simultaneously record the current pressure value. The results of this study indicated that the pressure values tested by the new method have good correlation with the actual pressure value in animal experiments. The new method of noninvasive pressure measurement based on the airflow and laser detection technology is accurate, feasible, repeatable and has a good application prospects.

Evaluation of selective control information detection scheme in orthogonal frequency division multiplexing-based radio-over-fiber and visible light communication links

NASA Astrophysics Data System (ADS)

Dalarmelina, Carlos A.; Adegbite, Saheed A.; Pereira, Esequiel da V.; Nunes, Reginaldo B.; Rocha, Helder R. O.; Segatto, Marcelo E. V.; Silva, Jair A. L.

2017-05-01

Block-level detection is required to decode what may be classified as selective control information (SCI) such as control format indicator in 4G-long-term evolution systems. Using optical orthogonal frequency division multiplexing over radio-over-fiber (RoF) links, we report the experimental evaluation of an SCI detection scheme based on a time-domain correlation (TDC) technique in comparison with the conventional maximum likelihood (ML) approach. When compared with the ML method, it is shown that the TDC method improves detection performance over both 20 and 40 km of standard single mode fiber (SSMF) links. We also report a performance analysis of the TDC scheme in noisy visible light communication channel models after propagation through 40 km of SSMF. Experimental and simulation results confirm that the TDC method is attractive for practical orthogonal frequency division multiplexing-based RoF and fiber-wireless systems. Unlike the ML method, another key benefit of the TDC is that it requires no channel estimation.

Silver nanoparticles-based colorimetric array for the detection of Thiophanate-methyl

NASA Astrophysics Data System (ADS)

Zheng, Mingda; Wang, Yingying; Wang, Chenge; Wei, Wei; Ma, Shuang; Sun, Xiaohan; He, Jiang

2018-06-01

A simple and selective colorimetric sensor based on citrate capped silver nanoparticles (Cit-AgNPs) is proposed for the detection of Thiophanate-methyl (TM) with high sensitivity and selectivity. The method based on the color change of Cit-AgNPs from yellow to cherry red with the addition of TM to Cit-AgNPs that caused a red-shift on the surface plasmon resonance (SPR) band from 394 nm to 525 nm due to the hydrogen-bonding and substitution. The density functional theory (DFT) method was also calculated the interactions between the TM and citrate ions. Under the optimized conditions, a linear relationship between the absorption ratio (A525nm/A394nm) and TM concentration was found in the range of 2-100 μM with correlation coefficient (R2) of 0.988. The detection limit of TM was 0.12 μM by UV-vis spectrometer. Moreover, the applicability of colorimetric sensor is successfully verified by the detection of TM in environmental samples with good recoveries.

Epidermal segmentation in high-definition optical coherence tomography.

PubMed

Li, Annan; Cheng, Jun; Yow, Ai Ping; Wall, Carolin; Wong, Damon Wing Kee; Tey, Hong Liang; Liu, Jiang

2015-01-01

Epidermis segmentation is a crucial step in many dermatological applications. Recently, high-definition optical coherence tomography (HD-OCT) has been developed and applied to imaging subsurface skin tissues. In this paper, a novel epidermis segmentation method using HD-OCT is proposed in which the epidermis is segmented by 3 steps: the weighted least square-based pre-processing, the graph-based skin surface detection and the local integral projection-based dermal-epidermal junction detection respectively. Using a dataset of five 3D volumes, we found that this method correlates well with the conventional method of manually marking out the epidermis. This method can therefore serve to effectively and rapidly delineate the epidermis for study and clinical management of skin diseases.

A new method to detect event-related potentials based on Pearson's correlation.

PubMed

Giroldini, William; Pederzoli, Luciano; Bilucaglia, Marco; Melloni, Simone; Tressoldi, Patrizio

2016-12-01

Event-related potentials (ERPs) are widely used in brain-computer interface applications and in neuroscience.  Normal EEG activity is rich in background noise, and therefore, in order to detect ERPs, it is usually necessary to take the average from multiple trials to reduce the effects of this noise.  The noise produced by EEG activity itself is not correlated with the ERP waveform and so, by calculating the average, the noise is decreased by a factor inversely proportional to the square root of N , where N is the number of averaged epochs. This is the easiest strategy currently used to detect ERPs, which is based on calculating the average of all ERP's waveform, these waveforms being time- and phase-locked.  In this paper, a new method called GW6 is proposed, which calculates the ERP using a mathematical method based only on Pearson's correlation. The result is a graph with the same time resolution as the classical ERP and which shows only positive peaks representing the increase-in consonance with the stimuli-in EEG signal correlation over all channels.  This new method is also useful for selectively identifying and highlighting some hidden components of the ERP response that are not phase-locked, and that are usually hidden in the standard and simple method based on the averaging of all the epochs.  These hidden components seem to be caused by variations (between each successive stimulus) of the ERP's inherent phase latency period (jitter), although the same stimulus across all EEG channels produces a reasonably constant phase. For this reason, this new method could be very helpful to investigate these hidden components of the ERP response and to develop applications for scientific and medical purposes. Moreover, this new method is more resistant to EEG artifacts than the standard calculations of the average and could be very useful in research and neurology.  The method we are proposing can be directly used in the form of a process written in the well-known Matlab programming language and can be easily and quickly written in any other software language.

Detection and Analysis of Enamel Cracks by Quantitative Light-induced Fluorescence Technology.

PubMed

Jun, Mi-Kyoung; Ku, Hye-Min; Kim, Euiseong; Kim, Hee-Eun; Kwon, Ho-Keun; Kim, Baek-Il

2016-03-01

The ability to accurately detect tooth cracks and quantify their depth would allow the prediction of crack progression and treatment success. The aim of this in vitro study was to determine the capabilities of quantitative light-induced fluorescence (QLF) technology in the detection of enamel cracks. Ninety-six extracted human teeth were selected for examining naturally existing or suspected cracked teeth surfaces using a photocuring unit. QLF performed with a digital camera (QLF-D) images were used to assess the ability to detect enamel cracks based on the maximum fluorescence loss value (ΔFmax, %), which was then analyzed using the QLF-D software. A histologic evaluation was then performed in which the samples were sectioned and observed with the aid of a polarized light microscope. The relationship between ΔFmax and the histology findings was assessed based on the Spearman rank correlation. The sensitivity and specificity were calculated to evaluate the validity of using QLF-D to analyze enamel inner-half cracks and cracks extending to the dentin-enamel junction. There was a strong correlation between the results of histologic evaluations of enamel cracks and the ΔFmax value, with a correlation coefficient of 0.84. The diagnostic accuracy of QLF-D had a sensitivity of 0.87 and a specificity of 0.98 for enamel inner-half cracks and a sensitivity of 0.90 and a specificity of 1.0 for cracks extending to the dentin-enamel junction. These results indicate that QLF technology would be a useful clinical tool for diagnosing enamel cracks, especially given that this is a nondestructive method. Copyright © 2016 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.

Validation of TICS for detection of dementia and mild cognitive impairment among individuals characterized by low levels of education or illiteracy: a population-based study in rural Greece.

PubMed

Georgakis, Marios K; Papadopoulos, Fotios C; Beratis, Ion; Michelakos, Theodoros; Kanavidis, Prodromos; Dafermos, Vasilios; Tousoulis, Dimitrios; Papageorgiou, Sokratis G; Petridou, Eleni Th

2017-01-01

The efficacy of the most widely used tests for dementia screening is limited in populations characterized by low levels of education. This study aimed to validate the face-to-face administered Telephone Interview for Cognitive Status (TICS) for detection of dementia and mild cognitive impairment (MCI) in a population-based sample of community dwelling individuals characterized by low levels of education or illiteracy in rural Greece. The translated Greek version of TICS was administered through face-to-face interview in 133 elderly residents of Velestino of low educational level (<12 years). We assessed its internal consistency and test-retest reliability, its correlation with sociodemographic parameters, and its discriminant ability for cognitive impairment and dementia, as defined by a brief neurological evaluation, including assessment of cognitive status and level of independence. TICS was characterized by adequate internal consistency (Cronbach's α: .72) and very high test-retest reliability (intra-class correlation coefficient: .93); it was positively correlated with age and educational years. MCI and dementia were diagnosed in 18 and 10.5% of the population, respectively. Its discriminant ability for detection of dementia was high (Area under the curve, AUC: .85), with a sensitivity and specificity of 86 and 82%, respectively, at a cut-off point of 24/25. TICS did not perform well in differentiating MCI from cognitively normal individuals though (AUC: .67). The directly administered TICS questionnaire provides an easily applicable and brief option for detection of dementia in populations of low educational level and might be useful in the context of both clinical and research purposes.

Weighted parallel contributions of binocular correlation and match signals to conscious perception of depth

PubMed Central

2016-01-01

Binocular disparity is detected in the primary visual cortex by a process similar to calculation of local cross-correlation between left and right retinal images. As a consequence, correlation-based neural signals convey information about false disparities as well as the true disparity. The false responses in the initial disparity detectors are eliminated at later stages in order to encode only disparities of the features correctly matched between the two eyes. For a simple stimulus configuration, a feed-forward nonlinear process can transform the correlation signal into the match signal. For human observers, depth judgement is determined by a weighted sum of the correlation and match signals rather than depending solely on the latter. The relative weight changes with spatial and temporal parameters of the stimuli, allowing adaptive recruitment of the two computations under different visual circumstances. A full transformation from correlation-based to match-based representation occurs at the neuronal population level in cortical area V4 and manifests in single-neuron responses of inferior temporal and posterior parietal cortices. Neurons in area V5/MT represent disparity in a manner intermediate between the correlation and match signals. We propose that the correlation and match signals in these areas contribute to depth perception in a weighted, parallel manner. This article is part of the themed issue ‘Vision in our three-dimensional world’. PMID:27269600

Weighted parallel contributions of binocular correlation and match signals to conscious perception of depth.

PubMed

Fujita, Ichiro; Doi, Takahiro

2016-06-19

Binocular disparity is detected in the primary visual cortex by a process similar to calculation of local cross-correlation between left and right retinal images. As a consequence, correlation-based neural signals convey information about false disparities as well as the true disparity. The false responses in the initial disparity detectors are eliminated at later stages in order to encode only disparities of the features correctly matched between the two eyes. For a simple stimulus configuration, a feed-forward nonlinear process can transform the correlation signal into the match signal. For human observers, depth judgement is determined by a weighted sum of the correlation and match signals rather than depending solely on the latter. The relative weight changes with spatial and temporal parameters of the stimuli, allowing adaptive recruitment of the two computations under different visual circumstances. A full transformation from correlation-based to match-based representation occurs at the neuronal population level in cortical area V4 and manifests in single-neuron responses of inferior temporal and posterior parietal cortices. Neurons in area V5/MT represent disparity in a manner intermediate between the correlation and match signals. We propose that the correlation and match signals in these areas contribute to depth perception in a weighted, parallel manner.This article is part of the themed issue 'Vision in our three-dimensional world'. © 2016 The Author(s).

A simple clot based assay for detection of procoagulant cell-derived microparticles.

PubMed

Patil, Rucha; Ghosh, Kanjaksha; Shetty, Shrimati

2016-05-01

Cell-derived microparticles (MPs) are important biomarkers in many facets of medicine. However, the MP detection methods used till date are costly and time consuming. The main aim of this study was to standardize an in-house clot based screening method for MP detection which would not only be specific and sensitive, but also inexpensive. Four different methods of MP assessment were performed and the results correlated. Using the flow cytometry technique as the gold standard, 25 samples with normal phosphatidylserine (PS) expressing MP levels and 25 samples with elevated levels were selected, which was cross checked by the commercial STA Procoag PPL clotting time (CT) assay. A simple recalcification time and an in-house clot assay were the remaining two tests. The in-house test measures the CT after the addition of calcium chloride to MP rich plasma, following incubation with Russell viper venom and phospholipid free plasma. The CT obtained by the in-house assay significantly correlated with the results obtained by flow cytometry (R2=0.87, p<0.01). Though preliminary, the in-house assay seems to be efficient, inexpensive and promising. It could definitely be utilized routinely for procoagulant MP assessment in various clinical settings.

Case-Based Multi-Sensor Intrusion Detection

NASA Astrophysics Data System (ADS)

Schwartz, Daniel G.; Long, Jidong

2009-08-01

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

Improvement of correlation-based centroiding methods for point source Shack-Hartmann wavefront sensor

NASA Astrophysics Data System (ADS)

Li, Xuxu; Li, Xinyang; wang, Caixia

2018-03-01

This paper proposes an efficient approach to decrease the computational costs of correlation-based centroiding methods used for point source Shack-Hartmann wavefront sensors. Four typical similarity functions have been compared, i.e. the absolute difference function (ADF), ADF square (ADF2), square difference function (SDF), and cross-correlation function (CCF) using the Gaussian spot model. By combining them with fast search algorithms, such as three-step search (TSS), two-dimensional logarithmic search (TDL), cross search (CS), and orthogonal search (OS), computational costs can be reduced drastically without affecting the accuracy of centroid detection. Specifically, OS reduces calculation consumption by 90%. A comprehensive simulation indicates that CCF exhibits a better performance than other functions under various light-level conditions. Besides, the effectiveness of fast search algorithms has been verified.

Surface Transient Binding-Based Fluorescence Correlation Spectroscopy (STB-FCS), a Simple and Easy-to-Implement Method to Extend the Upper Limit of the Time Window to Seconds.

PubMed

Peng, Sijia; Wang, Wenjuan; Chen, Chunlai

2018-05-10

Fluorescence correlation spectroscopy is a powerful single-molecule tool that is able to capture kinetic processes occurring at the nanosecond time scale. However, the upper limit of its time window is restricted by the dwell time of the molecule of interest in the confocal detection volume, which is usually around submilliseconds for a freely diffusing biomolecule. Here, we present a simple and easy-to-implement method, named surface transient binding-based fluorescence correlation spectroscopy (STB-FCS), which extends the upper limit of the time window to seconds. We further demonstrated that STB-FCS enables capture of both intramolecular and intermolecular kinetic processes whose time scales cross several orders of magnitude.

On-chip surface-enhanced Raman spectroscopy (SERS)-linked immuno-sensor assay (SLISA) for rapid environmental-surveillance of chemical toxins

NASA Astrophysics Data System (ADS)

Bhardwaj, Vinay; Srinivasan, Supriya; McGoron, Anthony J.

2005-05-01

The increasing threat of an intentional (attack) or accidental release of toxins, in particular chemical toxins, including chemical warfare agents (CWAs) and toxic industrial chemicals (TICs) has increased public fear. The major problem in such attacks/accidents is to detect toxins present in very low levels. Indeed, several detection techniques are currently being used for the same. However, none of them meet the most critical requirements of a RISE (Rapid, Inexpensive, Simple and Effective) detect-to-protect class of biosensors. To address this critical demand our group has developed a prototype lab-on-a-chip (LOC) using a colloidal silver-based, surface-enhanced Raman spectroscopy (SERS)-linked immuno-sensor assay (SLISA). The LOC-SLISA was tested for the measurement of RAD54, a stress-marker protein expressed by yeast in response to hydrogen peroxide (H2O2), a toxin in the EPA priority list of chemical toxins. We found SLISA has good correlation in accuracy with the traditional ELISA technique and outperforms the latter by being rapid and easy-to-use. SLISA is more sensitive, provides qualitative information on immuno-sensor's chemical characterization and antigen-antibody binding, and allows direct detection with minimal or no chance of uncertainty, which is a stringent limitation of all label-based biosensor technologies including ELISA. For translational significance of our work, we correlated our results to U.S. EPA (environmental protection agency) defined risk exposure guideline levels of H2O2 to validate the commercial potential of our on-chip SLISA. The label-free, cell-based and RISE detection offered by SERS can allow development of biomedical and environmental sensor technology (BEST) needed for direct, rapid and continuous monitoring of human health and environment

Quantitative detection of glucose level based on radiofrequency patch biosensor combined with volume-fixed structures.

PubMed

Qiang, Tian; Wang, Cong; Kim, Nam-Young

2017-12-15

A concept for characterizing a radiofrequency (RF) patch biosensor combined with volume-fixed structures is presented for timely monitoring of an individual's glucose levels based on frequency variation. Two types of patch biosensors-separately integrated with a backside slot (0.53μL) and a front-side tank (0.70μL) structure-were developed to achieve precise and efficient detection while excluding the effects of interference due to the liquidity, shape, and thickness of the tested glucose sample. A glucose test analyte at different concentrations (50-600mg/dL) was dropped into the volume-fixed structures. It fully interacted with the RF patch electromagnetic field, effectively and sensitively changing the resonance frequency and magnitude of the reflection coefficient. Measurement results based on the resonance frequency showed high sensitivity up to 1.13MHz and 1.97MHz per mg/dL, and low detection limits of 26.54mg/dL and 15.22mg/dL, for the two types of patch biosensors, respectively, as well as a short response time of less than 1s. Excellent reusability of the proposed biosensors was verified through three sets of measurements for each individual glucose sample. Regression analysis revealed a good linear correlation between glucose concentrations and the resonance frequency shift. Moreover, to facilitate a multi-parameter-sensitive detection of glucose, the magnitude of the reflection coefficient was also tested, and it showed a good linear correlation with the glucose concentration. Thus, the proposed approach can be adopted for distinguishing glucose solution levels, and it is a potential candidate for early-stage detection of glucose levels in diabetes patients. Copyright © 2017 Elsevier B.V. All rights reserved.

Comparison of monthly nighttime cloud fraction products from MODIS and AIRS and ground-based camera over Manila Observatory (14.64N, 121.07E)

NASA Astrophysics Data System (ADS)

Gacal, G. F. B.; Lagrosas, N.

2017-12-01

Cloud detection nowadays is primarily achieved by the utilization of various sensors aboard satellites. These include MODIS Aqua, MODIS Terra, and AIRS with products that include nighttime cloud fraction. Ground-based instruments are, however, only secondary to these satellites when it comes to cloud detection. Nonetheless, these ground-based instruments (e.g., LIDARs, ceilometers, and sky-cameras) offer significant datasets about a particular region's cloud cover values. For nighttime operations of cloud detection instruments, satellite-based instruments are more reliably and prominently used than ground-based ones. Therefore if a ground-based instrument for nighttime operations is operated, it ought to produce reliable scientific datasets. The objective of this study is to do a comparison between the results of a nighttime ground-based instrument (sky-camera) and that of MODIS Aqua and MODIS Terra. A Canon Powershot A2300 is placed ontop of Manila Observatory (14.64N, 121.07E) and is configured to take images of the night sky at 5min intervals. To detect pixels with clouds, the pictures are converted to grayscale format. Thresholding technique is used to screen pixels with cloud and pixels without clouds. If the pixel value is greater than 17, it is considered as a cloud; otherwise, a noncloud (Gacal et al., 2016). This algorithm is applied to the data gathered from Oct 2015 to Oct 2016. A scatter plot between satellite cloud fraction in the area covering the area 14.2877N, 120.9869E, 14.7711N and 121.4539E and ground cloud cover is graphed to find the monthly correlation. During wet season (June - November), the satellite nighttime cloud fraction vs ground measured cloud cover produce an acceptable R2 (Aqua= 0.74, Terra= 0.71, AIRS= 0.76). However, during dry season, poor R2 values are obtained (AIRS= 0.39, Aqua & Terra = 0.01). The high correlation during wet season can be attributed to a high probability that the camera and satellite see the same clouds. However during dry season, the satellite sees high altitude clouds and the camera can not detect these clouds from the ground as it relies on city lights reflected from low level clouds. With this acknowledged disparity, the ground-based camera has the advantage of detecting haze and thin clouds near the ground that are hardly or not detected by the satellites.

Quantification of transuranic elements by time interval correlation spectroscopy of the detected neutrons

PubMed

Baeten; Bruggeman; Paepen; Carchon

2000-03-01

The non-destructive quantification of transuranic elements in nuclear waste management or in safeguards verifications is commonly performed by passive neutron assay techniques. To minimise the number of unknown sample-dependent parameters, Neutron Multiplicity Counting (NMC) is applied. We developed a new NMC-technique, called Time Interval Correlation Spectroscopy (TICS), which is based on the measurement of Rossi-alpha time interval distributions. Compared to other NMC-techniques, TICS offers several advantages.

Stormwater plume detection by MODIS imagery in the southern California coastal ocean

USGS Publications Warehouse

Nezlin, N.P.; DiGiacomo, P.M.; Diehl, D.W.; Jones, B.H.; Johnson, S.C.; Mengel, M.J.; Reifel, K.M.; Warrick, J.A.; Wang, M.

2008-01-01

Stormwater plumes in the southern California coastal ocean were detected by MODIS-Aqua satellite imagery and compared to ship-based data on surface salinity and fecal indicator bacterial (FIB) counts collected during the Bight'03 Regional Water Quality Program surveys in February-March of 2004 and 2005. MODIS imagery was processed using a combined near-infrared/shortwave-infrared (NIR-SWIR) atmospheric correction method, which substantially improved normalized water-leaving radiation (nLw) optical spectra in coastal waters with high turbidity. Plumes were detected using a minimum-distance supervised classification method based on nLw spectra averaged within the training areas, defined as circular zones of 1.5-5.0-km radii around field stations with a surface salinity of S 33.0 ('ocean'). The plume optical signatures (i.e., the nLw differences between 'plume' and 'ocean') were most evident during the first 2 days after the rainstorms. To assess the accuracy of plume detection, stations were classified into 'plume' and 'ocean' using two criteria: (1) 'plume' included the stations with salinity below a certain threshold estimated from the maximum accuracy of plume detection; and (2) FIB counts in 'plume' exceeded the California State Water Board standards. The salinity threshold between 'plume' and 'ocean' was estimated as 32.2. The total accuracy of plume detection in terms of surface salinity was not high (68% on average), seemingly because of imperfect correlation between plume salinity and ocean color. The accuracy of plume detection in terms of FIB exceedances was even lower (64% on average), resulting from low correlation between ocean color and bacterial contamination. Nevertheless, satellite imagery was shown to be a useful tool for the estimation of the extent of potentially polluted plumes, which was hardly achievable by direct sampling methods (in particular, because the grids of ship-based stations covered only small parts of the plumes detected via synoptic MODIS imagery). In most southern California coastal areas, the zones of bacterial contamination were much smaller than the areas of turbid plumes; an exception was the plume of the Tijuana River, where the zone of bacterial contamination was comparable with the zone of plume detected by ocean color. ?? 2008 Elsevier Ltd.

Stormwater plume detection by MODIS imagery in the southern California coastal ocean

NASA Astrophysics Data System (ADS)

Nezlin, Nikolay P.; DiGiacomo, Paul M.; Diehl, Dario W.; Jones, Burton H.; Johnson, Scott C.; Mengel, Michael J.; Reifel, Kristen M.; Warrick, Jonathan A.; Wang, Menghua

2008-10-01

Stormwater plumes in the southern California coastal ocean were detected by MODIS-Aqua satellite imagery and compared to ship-based data on surface salinity and fecal indicator bacterial (FIB) counts collected during the Bight'03 Regional Water Quality Program surveys in February-March of 2004 and 2005. MODIS imagery was processed using a combined near-infrared/shortwave-infrared (NIR-SWIR) atmospheric correction method, which substantially improved normalized water-leaving radiation (nLw) optical spectra in coastal waters with high turbidity. Plumes were detected using a minimum-distance supervised classification method based on nLw spectra averaged within the training areas, defined as circular zones of 1.5-5.0-km radii around field stations with a surface salinity of S < 32.0 ("plume") and S > 33.0 ("ocean"). The plume optical signatures (i.e., the nLw differences between "plume" and "ocean") were most evident during the first 2 days after the rainstorms. To assess the accuracy of plume detection, stations were classified into "plume" and "ocean" using two criteria: (1) "plume" included the stations with salinity below a certain threshold estimated from the maximum accuracy of plume detection; and (2) FIB counts in "plume" exceeded the California State Water Board standards. The salinity threshold between "plume" and "ocean" was estimated as 32.2. The total accuracy of plume detection in terms of surface salinity was not high (68% on average), seemingly because of imperfect correlation between plume salinity and ocean color. The accuracy of plume detection in terms of FIB exceedances was even lower (64% on average), resulting from low correlation between ocean color and bacterial contamination. Nevertheless, satellite imagery was shown to be a useful tool for the estimation of the extent of potentially polluted plumes, which was hardly achievable by direct sampling methods (in particular, because the grids of ship-based stations covered only small parts of the plumes detected via synoptic MODIS imagery). In most southern California coastal areas, the zones of bacterial contamination were much smaller than the areas of turbid plumes; an exception was the plume of the Tijuana River, where the zone of bacterial contamination was comparable with the zone of plume detected by ocean color.

Detecting Functional Connectivity During Audiovisual Integration with MEG: A Comparison of Connectivity Metrics.

PubMed

Ard, Tyler; Carver, Frederick W; Holroyd, Tom; Horwitz, Barry; Coppola, Richard

2015-08-01

In typical magnetoencephalography and/or electroencephalography functional connectivity analysis, researchers select one of several methods that measure a relationship between regions to determine connectivity, such as coherence, power correlations, and others. However, it is largely unknown if some are more suited than others for various types of investigations. In this study, the authors investigate seven connectivity metrics to evaluate which, if any, are sensitive to audiovisual integration by contrasting connectivity when tracking an audiovisual object versus connectivity when tracking a visual object uncorrelated with the auditory stimulus. The authors are able to assess the metrics' performances at detecting audiovisual integration by investigating connectivity between auditory and visual areas. Critically, the authors perform their investigation on a whole-cortex all-to-all mapping, avoiding confounds introduced in seed selection. The authors find that amplitude-based connectivity measures in the beta band detect strong connections between visual and auditory areas during audiovisual integration, specifically between V4/V5 and auditory cortices in the right hemisphere. Conversely, phase-based connectivity measures in the beta band as well as phase and power measures in alpha, gamma, and theta do not show connectivity between audiovisual areas. The authors postulate that while beta power correlations detect audiovisual integration in the current experimental context, it may not always be the best measure to detect connectivity. Instead, it is likely that the brain utilizes a variety of mechanisms in neuronal communication that may produce differential types of temporal relationships.

Volumetric Security Alarm Based on a Spherical Ultrasonic Transducer Array

NASA Astrophysics Data System (ADS)

Sayin, Umut; Scaini, Davide; Arteaga, Daniel

Most of the existent alarm systems depend on physical or visual contact. The detection area is often limited depending on the type of the transducer, creating blind spots. Our proposition is a truly volumetric alarm system that can detect any movement in the intrusion area, based on monitoring the change over time of the impulse response of the room, which acts as an acoustic footprint. The device depends on an omnidirectional ultrasonic transducer array emitting sweep signals to calculate the impulse response in short intervals. Any change in the room conditions is monitored through a correlation function. The sensitivity of the alarm to different objects and different environments depends on the sweep duration, sweep bandwidth, and sweep interval. Successful detection of intrusions also depends on the size of the monitoring area and requires an adjustment of emitted ultrasound power. Strong air flow affects the performance of the alarm. A method for separating moving objects from strong air flow is devised using an adaptive thresholding on the correlation function involving a series of impulse response measurements. The alarm system can be also used for fire detection since air flow sourced from heating objects differ from random nature of the present air flow. Several measurements are made to test the integrity of the alarm in rooms sizing from 834-2080m3 with irregular geometries and various objects. The proposed system can efficiently detect intrusion whilst adequate emitting power is provided.

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 score could guide clinicians in identifying patients at risk for significant PCa and selecting patients for further radiological diagnostics to reduce unnecessary procedures. © 2017 Wiley Periodicals, Inc.

Model observer for assessing digital breast tomosynthesis for multi-lesion detection in the presence of anatomical noise

NASA Astrophysics Data System (ADS)

Wen, Gezheng; Markey, Mia K.; Miner Haygood, Tamara; Park, Subok

2018-02-01

Model observers are widely used in task-based assessments of medical image quality. The presence of multiple abnormalities in a single set of images, such as in multifocal multicentric breast cancer (MFMC), has an immense clinical impact on treatment planning and survival outcomes. Detecting multiple breast tumors is challenging as MFMC is relatively uncommon, and human observers do not know the number or locations of tumors a priori. Digital breast tomosynthesis (DBT), in which an x-ray beam sweeps over a limited angular range across the breast, has the potential to improve the detection of multiple tumors. However, prior studies of DBT image quality all focus on unifocal breast cancers. In this study, we extended our 2D multi-lesion (ML) channelized Hotelling observer (CHO) into a 3D ML-CHO that detects multiple lesions from volumetric imaging data. Then we employed the 3D ML-CHO to identify optimal DBT acquisition geometries for detection of MFMC. Digital breast phantoms with multiple embedded synthetic lesions were scanned by simulated DBT scanners of different geometries (wide/narrow angular span, different number of projections per scan) to simulate MFMC cases. With new implementations of 3D partial least squares (PLS) and modified Laguerre-Gauss (LG) channels, the 3D ML-CHO made detection decisions based upon the overall information from individual DBT slices and their correlations. Our evaluation results show that: (1) the 3D ML-CHO could achieve good detection performance with a small number of channels, and 3D PLS channels on average outperform the counterpart LG channels; (2) incorporating locally varying anatomical backgrounds and their correlations as in the 3D ML-CHO is essential for multi-lesion detection; (3) the most effective DBT geometry for detection of MFMC may vary when the task of clinical interest changes, and a given DBT geometry may not yield images that are equally informative for detecting MF, MC, and unifocal cancers.

Detecting unresolved binary stars in Euclid VIS images

NASA Astrophysics Data System (ADS)

Kuntzer, T.; Courbin, F.

2017-10-01

Measuring a weak gravitational lensing signal to the level required by the next generation of space-based surveys demands exquisite reconstruction of the point-spread function (PSF). However, unresolved binary stars can significantly distort the PSF shape. In an effort to mitigate this bias, we aim at detecting unresolved binaries in realistic Euclid stellar populations. We tested methods in numerical experiments where (I) the PSF shape is known to Euclid requirements across the field of view; and (II) the PSF shape is unknown. We drew simulated catalogues of PSF shapes for this proof-of-concept paper. Following the Euclid survey plan, the objects were observed four times. We propose three methods to detect unresolved binary stars. The detection is based on the systematic and correlated biases between exposures of the same object. One method is a simple correlation analysis, while the two others use supervised machine-learning algorithms (random forest and artificial neural network). In both experiments, we demonstrate the ability of our methods to detect unresolved binary stars in simulated catalogues. The performance depends on the level of prior knowledge of the PSF shape and the shape measurement errors. Good detection performances are observed in both experiments. Full complexity, in terms of the images and the survey design, is not included, but key aspects of a more mature pipeline are discussed. Finding unresolved binaries in objects used for PSF reconstruction increases the quality of the PSF determination at arbitrary positions. We show, using different approaches, that we are able to detect at least binary stars that are most damaging for the PSF reconstruction process. The code corresponding to the algorithms used in this work and all scripts to reproduce the results are publicly available from a GitHub repository accessible via http://lastro.epfl.ch/software

Real-Time Model-Based Leak-Through Detection within Cryogenic Flow Systems

NASA Technical Reports Server (NTRS)

Walker, M.; Figueroa, F.

2015-01-01

The timely detection of leaks within cryogenic fuel replenishment systems is of significant importance to operators on account of the safety and economic impacts associated with material loss and operational inefficiencies. Associated loss in control of pressure also effects the stability and ability to control the phase of cryogenic fluids during replenishment operations. Current research dedicated to providing Prognostics and Health Management (PHM) coverage of such cryogenic replenishment systems has focused on the detection of leaks to atmosphere involving relatively simple model-based diagnostic approaches that, while effective, are unable to isolate the fault to specific piping system components. The authors have extended this research to focus on the detection of leaks through closed valves that are intended to isolate sections of the piping system from the flow and pressurization of cryogenic fluids. The described approach employs model-based detection of leak-through conditions based on correlations of pressure changes across isolation valves and attempts to isolate the faults to specific valves. Implementation of this capability is enabled by knowledge and information embedded in the domain model of the system. The approach has been used effectively to detect such leak-through faults during cryogenic operational testing at the Cryogenic Testbed at NASA's Kennedy Space Center.

Detection of Fusarium verticillioides by PCR-ELISA based on FUM21 gene.

PubMed

Omori, Aline Myuki; Ono, Elisabete Yurie Sataque; Bordini, Jaqueline Gozzi; Hirozawa, Melissa Tiemi; Fungaro, Maria Helena Pelegrinelli; Ono, Mario Augusto

2018-08-01

Fusarium verticillioides is a primary corn pathogen and fumonisin producer which is associated with toxic effects in humans and animals. The traditional methods for detection of fungal contamination based on morphological characteristics are time-consuming and show low sensitivity and specificity. Therefore, the objective of this study was to develop a PCR-ELISA based on the FUM21 gene for F. verticillioides detection. The DNA of the F. verticillioides, Fusarium sp., Aspergillus sp. and Penicillium sp. isolates was analyzed by conventional PCR and PCR-ELISA to determine the specificity. The PCR-ELISA was specific to F. verticillioides isolates, showed a 2.5 pg detection limit and was 100-fold more sensitive than conventional PCR. In corn samples inoculated with F. verticillioides conidia, the detection limit of the PCR-ELISA was 1 × 10 4 conidia/g and was also 100-fold more sensitive than conventional PCR. Naturally contaminated corn samples were analyzed by PCR-ELISA based on the FUM21 gene and PCR-ELISA absorbance values correlated positively (p < 0.05) with Fusarium sp. counts (CFU/g). These results suggest that the PCR-ELISA developed in this study can be useful for F. verticillioides detection in corn samples. Copyright © 2018 Elsevier Ltd. All rights reserved.

Capillary-driven surface-enhanced Raman scattering (SERS)-based microfluidic chip for abrin detection

NASA Astrophysics Data System (ADS)

Yang, Hao; Deng, Min; Ga, Shan; Chen, Shouhui; Kang, Lin; Wang, Junhong; Xin, Wenwen; Zhang, Tao; You, Zherong; An, Yuan; Wang, Jinglin; Cui, Daxiang

2014-03-01

Herein, we firstly demonstrate the design and the proof-of-concept use of a capillary-driven surface-enhanced Raman scattering (SERS)-based microfluidic chip for abrin detection. The micropillar array substrate was etched and coated with a gold film by microelectromechanical systems (MEMS) process to integrate into a lateral flow test strip. The detection of abrin solutions of various concentrations was performed by the as-prepared microfluidic chip. It was shown that the correlation between the abrin concentration and SERS signal was found to be linear within the range of 0.1 ng/mL to 1 μg/mL with a limit of detection of 0.1 ng/mL. Our microfluidic chip design enhanced the operability of SERS-based immunodiagnostic techniques, significantly reducing the complication and cost of preparation as compared to previous SERS-based works. Meanwhile, this design proved the superiority to conventional lateral flow test strips in respect of both sensitivity and quantitation and showed great potential in the diagnosis and treatment for abrin poisoning as well as on-site screening of abrin-spiked materials.

Development of a biomimetic enzyme-linked immunosorbent assay based on molecularly imprinted polymers on paper for the detection of carbaryl.

PubMed

Zhang, Can; Cui, Hanyu; Han, Yufeng; Yu, Fangfang; Shi, Xiaoman

2018-02-01

A biomimetic enzyme-linked immunosorbent assay (BELISA) which was based on molecularly imprinted polymers on paper (MIPs-paper) with specific recognition was developed. As a detector, the surface of paper was modified with γ-MAPS by hydrolytic action and anchored the MIP layer on γ-MAPS modified-paper by copolymerization to construct the artificial antibody Through a series of experimentation and verification, we successful got the MIPs-paper and established BELISA for the detection of carbaryl. The development of MIPs-paper based on BELISA was applied to detect carbaryl in real samples and validated by an enzyme-linked immunosorbent assay (ELISA) based on anti-carbaryl biological antibody. The results of these two methods (BELISA and ELISA) were well correlated (R 2 =0.944). The established method of MIPs-paper BELISA exhibits the advantages of low cost, higher stability and being re-generable, which can be applied as a convenient tool for the fast and efficient detection of carbaryl. Copyright © 2017. Published by Elsevier Ltd.

Passive detection and localization of fatigue cracking in aluminum plates using Green's function reconstruction from ambient noise.

PubMed

Yang, Yang; Xiao, Li; Qu, Wenzhong; Lu, Ye

2017-11-01

Recent theoretical and experimental studies have demonstrated that a local Green's function can be retrieved from the cross-correlation of ambient noise field. This technique can be used to detect fatigue cracking in metallic structures, owing to the fact that the presence of crack can lead to a change in Green's function. This paper presents a method of structural fatigue cracking characterization method by measuring Green's function reconstruction from noise excitation and verifies the feasibility of crack detection in poor noise source distribution. Fatigue cracks usually generate nonlinear effects, in which different wave amplitudes and frequency compositions can cause different nonlinear responses. This study also undertakes analysis of the capacity of the proposed approach to identify fatigue cracking under different noise amplitudes and frequency ranges. Experimental investigations of an aluminum plate are conducted to assess the cross-correlations of received noise between sensor pairs and finally to detect the introduced fatigue crack. A damage index is proposed according to the variation between cross-correlations obtained from the pristine crack closed state and the crack opening-closure state when sufficient noise amplitude is used to generate nonlinearity. A probability distribution map of damage is calculated based on damage indices. The fatigue crack introduced in the aluminum plate is successfully identified and oriented, verifying that a fatigue crack can be detected by reconstructing Green's functions from an imperfect diffuse field in which ambient noise sources exist locally. Copyright © 2017 Elsevier B.V. All rights reserved.

Mutation detection of E6 and LCR genes from HPV 16 associated with carcinogenesis.

PubMed

Mosmann, Jessica P; Monetti, Marina S; Frutos, Maria C; Kiguen, Ana X; Venezuela, Raul F; Cuffini, Cecilia G

2015-01-01

Human papillomavirus (HPV) is responsible for one of the most frequent sexually transmitted infections. The first phylogenetic analysis was based on a LCR region fragment. Nowadays, 4 variants are known: African (Af-1, Af-2), Asian-American (AA) and European (E). However the existence of sub-lineages of the European variant havs been proposed, specific mutations in the E6 and LCR sequences being possibly related to persistent viral infections. The aim of this study was a phylogenetic study of HPV16 sequences of endocervical samples from Cordoba, in order to detect the circulating lineages and analyze the presence of mutations that could be correlated with malignant disease. The phylogenetic analysis determined that 86% of the samples belonged to the E variant, 7% to AF-1 and the remaining 7% to AF-2. The most frequent mutation in LCR sequences was G7521A, in 80% of the analyzed samples; it affects the binding site of a transcription factor that could contribute to carcinogenesis. In the E6 sequences, the most common mutation was T350G (L83V), detected in 67% of the samples, associated with increased risk of persistent infection. The high detection rate of the European lineage correlated with patterns of human migration. This study emphasizes the importance of recognizing circulating lineages, as well as the detection of mutations associated with high-grade neoplastic lesions that could be correlated to the development of carcinogenic lesions.

Robust Observation Detection for Single Object Tracking: Deterministic and Probabilistic Patch-Based Approaches

PubMed Central

Zulkifley, Mohd Asyraf; Rawlinson, David; Moran, Bill

2012-01-01

In video analytics, robust observation detection is very important as the content of the videos varies a lot, especially for tracking implementation. Contrary to the image processing field, the problems of blurring, moderate deformation, low illumination surroundings, illumination change and homogenous texture are normally encountered in video analytics. Patch-Based Observation Detection (PBOD) is developed to improve detection robustness to complex scenes by fusing both feature- and template-based recognition methods. While we believe that feature-based detectors are more distinctive, however, for finding the matching between the frames are best achieved by a collection of points as in template-based detectors. Two methods of PBOD—the deterministic and probabilistic approaches—have been tested to find the best mode of detection. Both algorithms start by building comparison vectors at each detected points of interest. The vectors are matched to build candidate patches based on their respective coordination. For the deterministic method, patch matching is done in 2-level test where threshold-based position and size smoothing are applied to the patch with the highest correlation value. For the second approach, patch matching is done probabilistically by modelling the histograms of the patches by Poisson distributions for both RGB and HSV colour models. Then, maximum likelihood is applied for position smoothing while a Bayesian approach is applied for size smoothing. The result showed that probabilistic PBOD outperforms the deterministic approach with average distance error of 10.03% compared with 21.03%. This algorithm is best implemented as a complement to other simpler detection methods due to heavy processing requirement. PMID:23202226

Astrometric detectability of systems with unseen companions: effects of the Earth orbital motion

NASA Astrophysics Data System (ADS)

Butkevich, Alexey G.

2018-06-01

The astrometric detection of an unseen companion is based on an analysis of the apparent motion of its host star around the system's barycentre. Systems with an orbital period close to 1 yr may escape detection if the orbital motion of their host stars is observationally indistinguishable from the effects of parallax. Additionally, an astrometric solution may produce a biased parallax estimation for such systems. We examine the effects of the orbital motion of the Earth on astrometric detectability in terms of a correlation between the Earth's orbital position and the position of the star relative to its system barycentre. The χ2 statistic for parallax estimation is calculated analytically, leading to expressions that relate the decrease in detectability and accompanying parallax bias to the position correlation function. The impact of the Earth's motion critically depends on the exoplanet's orbital period, diminishing rapidly as the period deviates from 1 yr. Selection effects against 1-yr-period systems is, therefore, expected. Statistical estimation shows that the corresponding loss of sensitivity results in a typical 10 per cent increase in the detection threshold. Consideration of eccentric orbits shows that the Earth's motion has no effect on detectability for e≳ 0.5. The dependence of the detectability on other parameters, such as orbital phases and inclination of the orbital plane to the ecliptic, are smooth and monotonic because they are described by simple trigonometric functions.

Motion-Based Immunological Detection of Zika Virus Using Pt-Nanomotors and a Cellphone.

PubMed

Draz, Mohamed Shehata; Lakshminaraasimulu, Nivethitha Kota; Krishnakumar, Sanchana; Battalapalli, Dheerendranath; Vasan, Anish; Kanakasabapathy, Manoj Kumar; Sreeram, Aparna; Kallakuri, Shantanu; Thirumalaraju, Prudhvi; Li, Yudong; Hua, Stephane; Yu, Xu G; Kuritzkes, Daniel R; Shafiee, Hadi

2018-05-16

Zika virus (ZIKV) infection is an emerging pandemic threat to humans that can be fatal in newborns. Advances in digital health systems and nanoparticles can facilitate the development of sensitive and portable detection technologies for timely management of emerging viral infections. Here we report a nanomotor-based bead-motion cellphone (NBC) system for the immunological detection of ZIKV. The presence of virus in a testing sample results in the accumulation of platinum (Pt)-nanomotors on the surface of beads, causing their motion in H 2 O 2 solution. Then the virus concentration is detected in correlation with the change in beads motion. The developed NBC system was capable of detecting ZIKV in samples with virus concentrations as low as 1 particle/μL. The NBC system allowed a highly specific detection of ZIKV in the presence of the closely related dengue virus and other neurotropic viruses, such as herpes simplex virus type 1 and human cytomegalovirus. The NBC platform technology has the potential to be used in the development of point-of-care diagnostics for pathogen detection and disease management in developed and developing countries.

Fluorescence correlation spectroscopy as a method for assessment of interactions between phage displaying antibodies and soluble antigen

PubMed Central

Lagerkvist, Ann Catrin; Földes-Papp, Zeno; Persson, Mats A.A.; Rigler, Rudolf

2001-01-01

Phage display is widely used for expression of combinatorial libraries, not least for protein engineering purposes. Precise selection at the single molecule level will provide an improved tool for generating proteins with complex and distinct properties from large molecular libraries. To establish such an improved selection system, we here report the detection of specific interactions between phage with displayed antibody fragments and fluorescently labeled soluble antigen based on Fluorescence Correlation Spectroscopy (FCS). Our novel strategy comprises the use of two separate fluorochromes for detection of the phage–antigen complex, either with labeled antiphage antibody or using a labeled antigen. As a model system, we studied a human monoclonal antibody to the hepatitis-C virus (HCV) envelope protein E2 and its cognate antigen (rE2 or rE1/E2). We could thus assess the specific interactions and determine the fraction of specific versus background phage (26% specific phage). Aggregation of these particular antigens made it difficult to reliably utilize the full potential of cross-correlation studies using the two labels simultaneously. However, with true monomeric proteins, this will certainly be possible, offering a great advantage in a safer and highly specific detection system. PMID:11468349

Novel wavelet threshold denoising method in axle press-fit zone ultrasonic detection

NASA Astrophysics Data System (ADS)

Peng, Chaoyong; Gao, Xiaorong; Peng, Jianping; Wang, Ai

2017-02-01

Axles are important part of railway locomotives and vehicles. Periodic ultrasonic inspection of axles can effectively detect and monitor axle fatigue cracks. However, in the axle press-fit zone, the complex interface contact condition reduces the signal-noise ratio (SNR). Therefore, the probability of false positives and false negatives increases. In this work, a novel wavelet threshold function is created to remove noise and suppress press-fit interface echoes in axle ultrasonic defect detection. The novel wavelet threshold function with two variables is designed to ensure the precision of optimum searching process. Based on the positive correlation between the correlation coefficient and SNR and with the experiment phenomenon that the defect and the press-fit interface echo have different axle-circumferential correlation characteristics, a discrete optimum searching process for two undetermined variables in novel wavelet threshold function is conducted. The performance of the proposed method is assessed by comparing it with traditional threshold methods using real data. The statistic results of the amplitude and the peak SNR of defect echoes show that the proposed wavelet threshold denoising method not only maintains the amplitude of defect echoes but also has a higher peak SNR.

Detecting and Quantifying Topography in Neural Maps

PubMed Central

Yarrow, Stuart; Razak, Khaleel A.; Seitz, Aaron R.; Seriès, Peggy

2014-01-01

Topographic maps are an often-encountered feature in the brains of many species, yet there are no standard, objective procedures for quantifying topography. Topographic maps are typically identified and described subjectively, but in cases where the scale of the map is close to the resolution limit of the measurement technique, identifying the presence of a topographic map can be a challenging subjective task. In such cases, an objective topography detection test would be advantageous. To address these issues, we assessed seven measures (Pearson distance correlation, Spearman distance correlation, Zrehen's measure, topographic product, topological correlation, path length and wiring length) by quantifying topography in three classes of cortical map model: linear, orientation-like, and clusters. We found that all but one of these measures were effective at detecting statistically significant topography even in weakly-ordered maps, based on simulated noisy measurements of neuronal selectivity and sparse sampling of the maps. We demonstrate the practical applicability of these measures by using them to examine the arrangement of spatial cue selectivity in pallid bat A1. This analysis shows that significantly topographic arrangements of interaural intensity difference and azimuth selectivity exist at the scale of individual binaural clusters. PMID:24505279

Detection of sleep disordered breathing and its central/obstructive character using nasal cannula and finger pulse oximeter.

PubMed

Sommermeyer, Dirk; Zou, Ding; Grote, Ludger; Hedner, Jan

2012-10-15

To assess the accuracy of novel algorithms using an oximeter-based finger plethysmographic signal in combination with a nasal cannula for the detection and differentiation of central and obstructive apneas. The validity of single pulse oximetry to detect respiratory disturbance events was also studied. Patients recruited from four sleep laboratories underwent an ambulatory overnight cardiorespiratory polygraphy recording. The nasal flow and photoplethysmographic signals of the recording were analyzed by automated algorithms. The apnea hypopnea index (AHI(auto)) was calculated using both signals, and a respiratory disturbance index (RDI(auto)) was calculated from photoplethysmography alone. Apnea events were classified into obstructive and central types using the oximeter derived pulse wave signal and compared with manual scoring. Sixty-six subjects (42 males, age 54 ± 14 yrs, body mass index 28.5 ± 5.9 kg/m(2)) were included in the analysis. AHI(manual) (19.4 ± 18.5 events/h) correlated highly significantly with AHI(auto) (19.9 ± 16.5 events/h) and RDI(auto) (20.4 ± 17.2 events/h); the correlation coefficients were r = 0.94 and 0.95, respectively (p < 0.001) with a mean difference of -0.5 ± 6.6 and -1.0 ± 6.1 events/h. The automatic analysis of AHI(auto) and RDI(auto) detected sleep apnea (cutoff AHI(manual) ≥ 15 events/h) with a sensitivity/specificity of 0.90/0.97 and 0.86/0.94, respectively. The automated obstructive/central apnea indices correlated closely with manually scoring (r = 0.87 and 0.95, p < 0.001) with mean difference of -4.3 ± 7.9 and 0.3 ± 1.5 events/h, respectively. Automatic analysis based on routine pulse oximetry alone may be used to detect sleep disordered breathing with accuracy. In addition, the combination of photoplethysmographic signals with a nasal flow signal provides an accurate distinction between obstructive and central apneic events during sleep.

Road sign recognition using Viapix module and correlation

NASA Astrophysics Data System (ADS)

Ouerhani, Y.; Desthieux, M.; Alfalou, A.

2015-03-01

In this paper, we propose and validate a new system used to explore road assets. In this work we are interested on the vertical road signs. To do this, we are based on the combination of road signs detection, recognition and identification using data provides by sensors. The proposed approach consists on using panoramic views provided by the innovative device, VIAPIX®1, developed by our company ACTRIS2. We are based also on the optimized correlation technique for road signs recognition and identification on pictures. Obtained results shows the interest on using panoramic views compared to results obtained using images provided using only one camera.

Linear high-boost fusion of Stokes vector imagery for effective discrimination and recognition of real targets in the presence of multiple identical decoys

NASA Astrophysics Data System (ADS)

El-Saba, Aed; Sakla, Wesam A.

2010-04-01

Recently, the use of imaging polarimetry has received considerable attention for use in automatic target recognition (ATR) applications. In military remote sensing applications, there is a great demand for sensors that are capable of discriminating between real targets and decoys. Accurate discrimination of decoys from real targets is a challenging task and often requires the fusion of various sensor modalities that operate simultaneously. In this paper, we use a simple linear fusion technique known as the high-boost fusion method for effective discrimination of real targets in the presence of multiple decoys. The HBF assigns more weight to the polarization-based imagery in forming the final fused image that is used for detection. We have captured both intensity and polarization-based imagery from an experimental laboratory arrangement containing a mixture of sand/dirt, rocks, vegetation, and other objects for the purpose of simulating scenery that would be acquired in a remote sensing military application. A target object and three decoys that are identical in physical appearance (shape, surface structure and color) and different in material composition have also been placed in the scene. We use the wavelet-filter joint transform correlation (WFJTC) technique to perform detection between input scenery and the target object. Our results show that use of the HBF method increases the correlation performance metrics associated with the WFJTC-based detection process when compared to using either the traditional intensity or polarization-based images.

Hypothesis tests for the detection of constant speed radiation moving sources

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dumazert, Jonathan; Coulon, Romain; Kondrasovs, Vladimir

2015-07-01

Radiation Portal Monitors are deployed in linear network to detect radiological material in motion. As a complement to single and multichannel detection algorithms, inefficient under too low signal to noise ratios, temporal correlation algorithms have been introduced. Test hypothesis methods based on empirically estimated mean and variance of the signals delivered by the different channels have shown significant gain in terms of a tradeoff between detection sensitivity and false alarm probability. This paper discloses the concept of a new hypothesis test for temporal correlation detection methods, taking advantage of the Poisson nature of the registered counting signals, and establishes amore » benchmark between this test and its empirical counterpart. The simulation study validates that in the four relevant configurations of a pedestrian source carrier under respectively high and low count rate radioactive background, and a vehicle source carrier under the same respectively high and low count rate radioactive background, the newly introduced hypothesis test ensures a significantly improved compromise between sensitivity and false alarm, while guaranteeing the stability of its optimization parameter regardless of signal to noise ratio variations between 2 to 0.8. (authors)« less

Mouse epileptic seizure detection with multiple EEG features and simple thresholding technique

NASA Astrophysics Data System (ADS)

Tieng, Quang M.; Anbazhagan, Ashwin; Chen, Min; Reutens, David C.

2017-12-01

Objective. Epilepsy is a common neurological disorder characterized by recurrent, unprovoked seizures. The search for new treatments for seizures and epilepsy relies upon studies in animal models of epilepsy. To capture data on seizures, many applications require prolonged electroencephalography (EEG) with recordings that generate voluminous data. The desire for efficient evaluation of these recordings motivates the development of automated seizure detection algorithms. Approach. A new seizure detection method is proposed, based on multiple features and a simple thresholding technique. The features are derived from chaos theory, information theory and the power spectrum of EEG recordings and optimally exploit both linear and nonlinear characteristics of EEG data. Main result. The proposed method was tested with real EEG data from an experimental mouse model of epilepsy and distinguished seizures from other patterns with high sensitivity and specificity. Significance. The proposed approach introduces two new features: negative logarithm of adaptive correlation integral and power spectral coherence ratio. The combination of these new features with two previously described features, entropy and phase coherence, improved seizure detection accuracy significantly. Negative logarithm of adaptive correlation integral can also be used to compute the duration of automatically detected seizures.

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. © 2013 John Wiley & Sons Ltd.

Pipeline Processing with an Iterative, Context-based Detection Model

DTIC Science & Technology

2014-04-19

stripping the incoming data stream of repeating and irrelevant signals prior to running primary detectors , adaptive beamforming and matched field processing...framework, pattern detectors , correlation detectors , subspace detectors , matched field detectors , nuclear explosion monitoring 16. SECURITY CLASSIFICATION...10 5. Teleseismic paths from earthquakes in

A method based on infrared detection for determining the moisture content of ceramic plaster materials.

PubMed

Macias-Melo, E V; Aguilar-Castro, K M; Alvarez-Lemus, M A; Flores-Prieto, J J

2015-09-01

In this work, we describe a methodology for developing a mathematical model based on infrared (IR) detection to determine the moisture content (M) in solid samples. For this purpose, an experimental setup was designed, developed and calibrated against the gravimetric method. The experimental arrangement allowed for the simultaneous measurement of M and the electromotive force (EMF), fitting the experimental variables as much as possible. These variables were correlated by a mathematical model, and the obtained correlation was M=1.12×exp(3.47×EMF), ±2.54%. This finding suggests that it is feasible to measure the moisture content when it has greater values than 2.54%. The proposed methodology could be used for different conditions of temperature, relative humidity and drying rates to evaluate the influence of these variables on the amount of energy received by the IR detector. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Community detection for fluorescent lifetime microscopy image segmentation

NASA Astrophysics Data System (ADS)

Hu, Dandan; Sarder, Pinaki; Ronhovde, Peter; Achilefu, Samuel; Nussinov, Zohar

2014-03-01

Multiresolution community detection (CD) method has been suggested in a recent work as an efficient method for performing unsupervised segmentation of fluorescence lifetime (FLT) images of live cell images containing fluorescent molecular probes.1 In the current paper, we further explore this method in FLT images of ex vivo tissue slices. The image processing problem is framed as identifying clusters with respective average FLTs against a background or "solvent" in FLT imaging microscopy (FLIM) images derived using NIR fluorescent dyes. We have identified significant multiresolution structures using replica correlations in these images, where such correlations are manifested by information theoretic overlaps of the independent solutions ("replicas") attained using the multiresolution CD method from different starting points. In this paper, our method is found to be more efficient than a current state-of-the-art image segmentation method based on mixture of Gaussian distributions. It offers more than 1:25 times diversity based on Shannon index than the latter method, in selecting clusters with distinct average FLTs in NIR FLIM images.

Long-range depth profiling of camouflaged targets using single-photon detection

NASA Astrophysics Data System (ADS)

Tobin, Rachael; Halimi, Abderrahim; McCarthy, Aongus; Ren, Ximing; McEwan, Kenneth J.; McLaughlin, Stephen; Buller, Gerald S.

2018-03-01

We investigate the reconstruction of depth and intensity profiles from data acquired using a custom-designed time-of-flight scanning transceiver based on the time-correlated single-photon counting technique. The system had an operational wavelength of 1550 nm and used a Peltier-cooled InGaAs/InP single-photon avalanche diode detector. Measurements were made of human figures, in plain view and obscured by camouflage netting, from a stand-off distance of 230 m in daylight using only submilliwatt average optical powers. These measurements were analyzed using a pixelwise cross correlation approach and compared to analysis using a bespoke algorithm designed for the restoration of multilayered three-dimensional light detection and ranging images. This algorithm is based on the optimization of a convex cost function composed of a data fidelity term and regularization terms, and the results obtained show that it achieves significant improvements in image quality for multidepth scenarios and for reduced acquisition times.

Visual object tracking by correlation filters and online learning

NASA Astrophysics Data System (ADS)

Zhang, Xin; Xia, Gui-Song; Lu, Qikai; Shen, Weiming; Zhang, Liangpei

2018-06-01

Due to the complexity of background scenarios and the variation of target appearance, it is difficult to achieve high accuracy and fast speed for object tracking. Currently, correlation filters based trackers (CFTs) show promising performance in object tracking. The CFTs estimate the target's position by correlation filters with different kinds of features. However, most of CFTs can hardly re-detect the target in the case of long-term tracking drifts. In this paper, a feature integration object tracker named correlation filters and online learning (CFOL) is proposed. CFOL estimates the target's position and its corresponding correlation score using the same discriminative correlation filter with multi-features. To reduce tracking drifts, a new sampling and updating strategy for online learning is proposed. Experiments conducted on 51 image sequences demonstrate that the proposed algorithm is superior to the state-of-the-art approaches.

Vibration-based structural health monitoring of the aircraft large component

NASA Astrophysics Data System (ADS)

Pavelko, V.; Kuznetsov, S.; Nevsky, A.; Marinbah, M.

2017-10-01

In the presented paper there are investigated the basic problems of the local system of SHM of large scale aircraft component. Vibration-based damage detection is accepted as a basic condition, and main attention focused to a low-cost solution that would be attractive for practice. The conditions of small damage detection in the full scale structural component at low-frequency excitation were defined in analytical study and modal FEA. In experimental study the dynamic test of the helicopter Mi-8 tail beam was performed at harmonic excitation with frequency close to first natural frequency of the beam. The index of correlation coefficient deviation (CCD) was used for extraction of the features due to embedded pseudo-damage. It is shown that the problem of vibration-based detection of a small damage in the large scale structure at low-frequency excitation can be solved successfully.

Developments on a SEM-based X-ray tomography system: Stabilization scheme and performance evaluation

NASA Astrophysics Data System (ADS)

Gomes Perini, L. A.; Bleuet, P.; Filevich, J.; Parker, W.; Buijsse, B.; Kwakman, L. F. Tz.

2017-06-01

Recent improvements in a SEM-based X-ray tomography system are described. In this type of equipment, X-rays are generated through the interaction between a highly focused electron-beam and a geometrically confined anode target. Unwanted long-term drifts of the e-beam can lead to loss of X-ray flux or decrease of spatial resolution in images. To circumvent this issue, a closed-loop control using FFT-based image correlation is integrated to the acquisition routine, in order to provide an in-line drift correction. The X-ray detection system consists of a state-of-the-art scientific CMOS camera (indirect detection), featuring high quantum efficiency (˜60%) and low read-out noise (˜1.2 electrons). The system performance is evaluated in terms of resolution, detectability, and scanning times for applications covering three different scientific fields: microelectronics, technical textile, and material science.

Adapted all-numerical correlator for face recognition applications

NASA Astrophysics Data System (ADS)

Elbouz, M.; Bouzidi, F.; Alfalou, A.; Brosseau, C.; Leonard, I.; Benkelfat, B.-E.

2013-03-01

In this study, we suggest and validate an all-numerical implementation of a VanderLugt correlator which is optimized for face recognition applications. The main goal of this implementation is to take advantage of the benefits (detection, localization, and identification of a target object within a scene) of correlation methods and exploit the reconfigurability of numerical approaches. This technique requires a numerical implementation of the optical Fourier transform. We pay special attention to adapt the correlation filter to this numerical implementation. One main goal of this work is to reduce the size of the filter in order to decrease the memory space required for real time applications. To fulfil this requirement, we code the reference images with 8 bits and study the effect of this coding on the performances of several composite filters (phase-only filter, binary phase-only filter). The saturation effect has for effect to decrease the performances of the correlator for making a decision when filters contain up to nine references. Further, an optimization is proposed based for an optimized segmented composite filter. Based on this approach, we present tests with different faces demonstrating that the above mentioned saturation effect is significantly reduced while minimizing the size of the learning data base.

An Evaluation of Pixel-Based Methods for the Detection of Floating Objects on the Sea Surface

NASA Astrophysics Data System (ADS)

Borghgraef, Alexander; Barnich, Olivier; Lapierre, Fabian; Van Droogenbroeck, Marc; Philips, Wilfried; Acheroy, Marc

2010-12-01

Ship-based automatic detection of small floating objects on an agitated sea surface remains a hard problem. Our main concern is the detection of floating mines, which proved a real threat to shipping in confined waterways during the first Gulf War, but applications include salvaging, search-and-rescue operation, perimeter, or harbour defense. Detection in infrared (IR) is challenging because a rough sea is seen as a dynamic background of moving objects with size order, shape, and temperature similar to those of the floating mine. In this paper we have applied a selection of background subtraction algorithms to the problem, and we show that the recent algorithms such as ViBe and behaviour subtraction, which take into account spatial and temporal correlations within the dynamic scene, significantly outperform the more conventional parametric techniques, with only little prior assumptions about the physical properties of the scene.

Imaging and Elastometry of Blood Clots Using Magnetomotive Optical Coherence Tomography and Labeled Platelets.

PubMed

Oldenburg, Amy L; Wu, Gongting; Spivak, Dmitry; Tsui, Frank; Wolberg, Alisa S; Fischer, Thomas H

2011-07-21

Improved methods for imaging and assessment of vascular defects are needed for directing treatment of cardiovascular pathologies. In this paper, we employ magnetomotive optical coherence tomography (MMOCT) as a platform both to detect and to measure the elasticity of blood clots. Detection is enabled through the use of rehydrated, lyophilized platelets loaded with superparamagnetic iron oxides (SPIO-RL platelets) that are functional infusion agents that adhere to sites of vascular endothelial damage. Evidence suggests that the sensitivity for detection is improved over threefold by magnetic interactions between SPIOs inside RL platelets. Using the same MMOCT system, we show how elastometry of simulated clots, using resonant acoustic spectroscopy, is correlated with the fibrin content of the clot. Both methods are based upon magnetic actuation and phase-sensitive optical monitoring of nanoscale displacements using MMOCT, underscoring its utility as a broad-based platform to detect and measure the molecular structure and composition of blood clots.

A new approach based on the median filter to T-wave detection in ECG signal.

PubMed

Kholkhal, Mourad; Bereksi Reguig, Fethi

2014-07-01

The electrocardiogram (ECG) is one of the most used signals in the diagnosis of heart disease. It contains different waves which directly correlate to heart activity. Different methods have been used in order to detect these waves and consequently lead to heart activity diagnosis. This paper is interested more particularly to the detection of the T-wave. Such a wave represents the re-polarization state of the heart activity. The proposed approach is based on the algorithm procedure which allows the detection of the T-wave using a lot of filter including mean and median filter. The proposed algorithm is implemented and tested on a set of ECG recordings taken from, respectively, the European STT, MITBIH and MITBIH ST databases. The results are found to be very satisfactory in terms of sensitivity, predictivity and error compared to other works in the field.

The impact of absorption coefficient on polarimetric determination of Berry phase based depth resolved characterization of biomedical scattering samples: a polarized Monte Carlo investigation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Baba, Justin S; Koju, Vijay; John, Dwayne O

2016-01-01

The modulation of the state of polarization of photons due to scatter generates associated geometric phase that is being investigated as a means for decreasing the degree of uncertainty in back-projecting the paths traversed by photons detected in backscattered geometry. In our previous work, we established that polarimetrically detected Berry phase correlates with the mean photon penetration depth of the backscattered photons collected for image formation. In this work, we report on the impact of state-of-linear-polarization (SOLP) filtering on both the magnitude and population distributions of image forming detected photons as a function of the absorption coefficient of the scatteringmore » sample. The results, based on Berry phase tracking implemented Polarized Monte Carlo Code, indicate that sample absorption plays a significant role in the mean depth attained by the image forming backscattered detected photons.« less

High effective algorithm of the detection and identification of substance using the noisy reflected THz pulse

NASA Astrophysics Data System (ADS)

Trofimov, Vyacheslav A.; Varentsova, Svetlana A.; Trofimov, Vladislav V.; Tikhomirov, Vasily V.

2015-08-01

Principal limitations of the standard THz-TDS method for the detection and identification are demonstrated under real conditions (at long distance of about 3.5 m and at a high relative humidity more than 50%) using neutral substances thick paper bag, paper napkins and chocolate. We show also that the THz-TDS method detects spectral features of dangerous substances even if the THz signals were measured in laboratory conditions (at distance 30-40 cm from the receiver and at a low relative humidity less than 2%); silicon-based semiconductors were used as the samples. However, the integral correlation criteria, based on SDA method, allows us to detect the absence of dangerous substances in the neutral substances. The discussed algorithm shows high probability of the substance identification and a reliability of realization in practice, especially for security applications and non-destructive testing.

Single neuron firing properties impact correlation-based population coding

PubMed Central

Hong, Sungho; Ratté, Stéphanie; Prescott, Steven A.; De Schutter, Erik

2012-01-01

Correlated spiking has been widely observed but its impact on neural coding remains controversial. Correlation arising from co-modulation of rates across neurons has been shown to vary with the firing rates of individual neurons. This translates into rate and correlation being equivalently tuned to the stimulus; under those conditions, correlated spiking does not provide information beyond that already available from individual neuron firing rates. Such correlations are irrelevant and can reduce coding efficiency by introducing redundancy. Using simulations and experiments in rat hippocampal neurons, we show here that pairs of neurons receiving correlated input also exhibit correlations arising from precise spike-time synchronization. Contrary to rate co-modulation, spike-time synchronization is unaffected by firing rate, thus enabling synchrony- and rate-based coding to operate independently. The type of output correlation depends on whether intrinsic neuron properties promote integration or coincidence detection: “ideal” integrators (with spike generation sensitive to stimulus mean) exhibit rate co-modulation whereas “ideal” coincidence detectors (with spike generation sensitive to stimulus variance) exhibit precise spike-time synchronization. Pyramidal neurons are sensitive to both stimulus mean and variance, and thus exhibit both types of output correlation proportioned according to which operating mode is dominant. Our results explain how different types of correlations arise based on how individual neurons generate spikes, and why spike-time synchronization and rate co-modulation can encode different stimulus properties. Our results also highlight the importance of neuronal properties for population-level coding insofar as neural networks can employ different coding schemes depending on the dominant operating mode of their constituent neurons. PMID:22279226

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tura, J., E-mail: jordi.tura@icfo.es; Augusiak, R.; Sainz, A.B.

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,more » 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.« less

Clock Synchronization Through Time-Variant Underwater Acoustic Channels

DTIC Science & Technology

2012-09-01

stage, we analyze a series of chirp responses to identify the least time -varying multipath present in the channel between the two nodes. Based on the... based on the detected arrivals and determines the most stable one based on the correlation coefficient of a model fit to the time -of-arrival estimates...short periods of time . Nevertheless, signal fluctuations can occur due to transceiver motion or inherent changes within the propagation medium

Near-infrared diode laser based spectroscopic detection of ammonia: a comparative study of photoacoustic and direct optical absorption methods

NASA Technical Reports Server (NTRS)

Bozoki, Zoltan; Mohacsi, Arpad; Szabo, Gabor; Bor, Zsolt; Erdelyi, Miklos; Chen, Weidong; Tittel, Frank K.

2002-01-01

A photoacoustic spectroscopic (PAS) and a direct optical absorption spectroscopic (OAS) gas sensor, both using continuous-wave room-temperature diode lasers operating at 1531.8 nm, were compared on the basis of ammonia detection. Excellent linear correlation between the detector signals of the two systems was found. Although the physical properties and the mode of operation of both sensors were significantly different, their performances were found to be remarkably similar, with a sub-ppm level minimum detectable concentration of ammonia and a fast response time in the range of a few minutes.

Subdecoherence time generation and detection of orbital entanglement in quantum dots.

PubMed

Brange, F; Malkoc, O; Samuelsson, P

2015-05-01

Recent experiments have demonstrated subdecoherence time control of individual single-electron orbital qubits. Here we propose a quantum-dot-based scheme for generation and detection of pairs of orbitally entangled electrons on a time scale much shorter than the decoherence time. The electrons are entangled, via two-particle interference, and transferred to the detectors during a single cotunneling event, making the scheme insensitive to charge noise. For sufficiently long detector dot lifetimes, cross-correlation detection of the dot charges can be performed with real-time counting techniques, providing for an unambiguous short-time Bell inequality test of orbital entanglement.

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.

Automated batch fiducial-less tilt-series alignment in Appion using Protomo

PubMed Central

Noble, Alex J.; Stagg, Scott M.

2015-01-01

The field of electron tomography has benefited greatly from manual and semi-automated approaches to marker-based tilt-series alignment that have allowed for the structural determination of multitudes of in situ cellular structures as well as macromolecular structures of individual protein complexes. The emergence of complementary metal-oxide semiconductor detectors capable of detecting individual electrons has enabled the collection of low dose, high contrast images, opening the door for reliable correlation-based tilt-series alignment. Here we present a set of automated, correlation-based tilt-series alignment, contrast transfer function (CTF) correction, and reconstruction workflows for use in conjunction with the Appion/Leginon package that are primarily targeted at automating structure determination with cryogenic electron microscopy. PMID:26455557

Analysis of confidence level scores from an ROC study: comparison of three mammographic systems for detection of simulated calcifications

NASA Astrophysics Data System (ADS)

Lai, Chao-Jen; Shaw, Chris C.; Whitman, Gary J.; Yang, Wei T.; Dempsey, Peter J.

2005-04-01

The purpose of this study is to compare the detection performance of three different mammography systems: screen/film (SF) combination, a-Si/CsI flat-panel (FP-), and charge-coupled device (CCD-) based systems. A 5-cm thick 50% adipose/50% glandular breast tissue equivalent slab phantom was used to provide an uniform background. Calcium carbonate grains of three different size groups were used to simulate microcalcifications (MCs): 112-125, 125-140, and 140-150 μm overlapping with the uniform background. Calcification images were acquired with the three mammography systems. Digital images were printed on hardcopy films. All film images were displayed on a mammographic viewer and reviewed by 5 mammographers. The visibility of the MC was rated with a 5-point confidence rating scale for each detection task, including the negative controls. Scores were averaged over all readers for various detectors and size groups. Receiver operating characteristic (ROC) analysis was performed and the areas under the ROC curves (Az"s) were computed for various imaging conditions. The results shows that (1) the FP-based system performed significantly better than the SF and CCD-based systems for individual size groups using ROC analysis (2) the FP-based system also performed significantly better than the SF and CCD-based systems for individual size groups using averaged confidence scale, and (3) the results obtained from the Az"s were largely correlated with these from confidence level scores. However, the correlation varied slightly among different imaging conditions.

Miniaturized Sample Preparation and Rapid Detection of Arsenite in Contaminated Soil Using a Smartphone.

PubMed

Siddiqui, Mohd Farhan; Kim, Soocheol; Jeon, Hyoil; Kim, Taeho; Joo, Chulmin; Park, Seungkyung

2018-03-04

Conventional methods for analyzing heavy metal contamination in soil and water generally require laboratory equipped instruments, complex procedures, skilled personnel and a significant amount of time. With the advancement in computing and multitasking performances, smartphone-based sensors potentially allow the transition of the laboratory-based analytical processes to field applicable, simple methods. In the present work, we demonstrate the novel miniaturized setup for simultaneous sample preparation and smartphone-based optical sensing of arsenic As(III) in the contaminated soil. Colorimetric detection protocol utilizing aptamers, gold nanoparticles and NaCl have been optimized and tested on the PDMS-chip to obtain the high sensitivity with the limit of detection of 0.71 ppm (in the sample) and a correlation coefficient of 0.98. The performance of the device is further demonstrated through the comparative analysis of arsenic-spiked soil samples with standard laboratory method, and a good agreement with a correlation coefficient of 0.9917 and the average difference of 0.37 ppm, are experimentally achieved. With the android application on the device to run the experiment, the whole process from sample preparation to detection is completed within 3 hours without the necessity of skilled personnel. The approximate cost of setup is estimated around 1 USD, weight 55 g. Therefore, the presented method offers the simple, rapid, portable and cost-effective means for onsite sensing of arsenic in soil. Combined with the geometric information inside the smartphones, the system will allow the monitoring of the contamination status of soils in a nation-wide manner.

Dictionary-Driven Ischemia Detection From Cardiac Phase-Resolved Myocardial BOLD MRI at Rest.

PubMed

Bevilacqua, Marco; Dharmakumar, Rohan; Tsaftaris, Sotirios A

2016-01-01

Cardiac Phase-resolved Blood-Oxygen-Level Dependent (CP-BOLD) MRI provides a unique opportunity to image an ongoing ischemia at rest. However, it requires post-processing to evaluate the extent of ischemia. To address this, here we propose an unsupervised ischemia detection (UID) method which relies on the inherent spatio-temporal correlation between oxygenation and wall motion to formalize a joint learning and detection problem based on dictionary decomposition. Considering input data of a single subject, it treats ischemia as an anomaly and iteratively learns dictionaries to represent only normal observations (corresponding to myocardial territories remote to ischemia). Anomaly detection is based on a modified version of One-class Support Vector Machines (OCSVM) to regulate directly the margins by incorporating the dictionary-based representation errors. A measure of ischemic extent (IE) is estimated, reflecting the relative portion of the myocardium affected by ischemia. For visualization purposes an ischemia likelihood map is created by estimating posterior probabilities from the OCSVM outputs, thus obtaining how likely the classification is correct. UID is evaluated on synthetic data and in a 2D CP-BOLD data set from a canine experimental model emulating acute coronary syndromes. Comparing early ischemic territories identified with UID against infarct territories (after several hours of ischemia), we find that IE, as measured by UID, is highly correlated (Pearson's r=0.84) with respect to infarct size. When advances in automated registration and segmentation of CP-BOLD images and full coverage 3D acquisitions become available, we hope that this method can enable pixel-level assessment of ischemia with this truly non-invasive imaging technique.

Detection of sub-threshold periodic signal by multiplicative and additive cross-correlated sine-Wiener noises in the FitzHugh-Nagumo neuron

NASA Astrophysics Data System (ADS)

Yao, Yuangen; Ma, Chengzhang; Wang, Canjun; Yi, Ming; Gui, Rong

2018-02-01

We study the effects of multiplicative and additive cross-correlated sine-Wiener (CCSW) noises on the performance of sub-threshold periodic signal detection in the FitzHugh-Nagumo (FHN) neuron by calculating Fourier coefficients Q for measuring synchronization between sub-threshold input signal and the response of system. CCSW noises-induced transitions of electrical activity in the FHN neuron model can be observed. Moreover, the performance of sub-threshold periodic signal detection is achieved at moderate noise strength, cross-correlation time and cross-correlation strength of CCSW noises, which indicate the occurrence of CCSW noises-induced stochastic resonance. Furthermore, the performance of sub-threshold signal detection is strongly sensitive to cross-correlation time of CCSW noises. Therefore, the performance can be effectively controlled by regulating cross-correlation time of CCSW noises. These results provide a possible mechanism for amplifying or detecting the sub-threshold signal in the nervous system.

Human Papillomavirus (HPV) Infection in Squamous Cell Carcinomas Arising From the Oropharynx: Detection of HPV DNA and p16 Immunohistochemistry as Diagnostic and Prognostic Indicators—A Pilot Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bussu, Francesco, E-mail: francesco.bussu.md@gmail.com; Sali, Michela; Gallus, Roberto

Purpose: Human papillomavirus (HPV) 16 infection is associated with oropharyngeal carcinogenesis and is likely the cause of the reported increase in disease incidence. We evaluated the prevalence of HPV infection and the reliability of different diagnostic tools using primary tumor samples from a cohort of 50 patients. Methods and Materials: Formalin-fixed paraffin-embedded (FFPE) tumor samples were collected from all 50 consecutive primary oropharyngeal SCC patients who were enrolled in the study; fresh tumor samples were available in 22 cases. NucliSENS EasyQ HPVv1 was used for RNA, and Digene Hybrid Capture-2(HC2) was used for DNA detection. p16 Expression was evaluated bymore » immunohistochemistry in FPPE specimens. Results: Based on the DNA detection assay on FFPE samples, the frequency of high-risk HPV infection was 32%. The agreement rate between HPV RNA and HPV DNA detection in fresh samples was 100%. The agreement rate between p16 immunohistochemistry (IHC) and the detection of HPV DNA in the FFPE samples was fair but not excellent (κ = 0.618). HPV DNA detection was highly significant, as measured by disease-specific survival and determined using a Wilcoxon test (P=.001). p16 IHC also exhibited a prognostic value but with a lower statistical significance (P=.0475). The detection of HPV DNA, but not p16 IHC, was also significantly correlated with locoregional control (P=.0461). Conclusion: Diagnostic methods based on the detection of HPV nucleic acids appear to be more reliable and objective because they do not require reading by a trained histopathologist. Furthermore, the detection of HPV DNA exhibits an improved correlation with survival, and therefore appears definitely more reliable than p16 IHC for routine use in clinical practice.« less

Hybrid optical CDMA-FSO communications network under spatially correlated gamma-gamma scintillation.

PubMed

Jurado-Navas, Antonio; Raddo, Thiago R; Garrido-Balsells, José María; Borges, Ben-Hur V; Olmos, Juan José Vegas; Monroy, Idelfonso Tafur

2016-07-25

In this paper, we propose a new hybrid network solution based on asynchronous optical code-division multiple-access (OCDMA) and free-space optical (FSO) technologies for last-mile access networks, where fiber deployment is impractical. The architecture of the proposed hybrid OCDMA-FSO network is thoroughly described. The users access the network in a fully asynchronous manner by means of assigned fast frequency hopping (FFH)-based codes. In the FSO receiver, an equal gain-combining technique is employed along with intensity modulation and direct detection. New analytical formalisms for evaluating the average bit error rate (ABER) performance are also proposed. These formalisms, based on the spatially correlated gamma-gamma statistical model, are derived considering three distinct scenarios, namely, uncorrelated, totally correlated, and partially correlated channels. Numerical results show that users can successfully achieve error-free ABER levels for the three scenarios considered as long as forward error correction (FEC) algorithms are employed. Therefore, OCDMA-FSO networks can be a prospective alternative to deliver high-speed communication services to access networks with deficient fiber infrastructure.

Methods to detect, characterize, and remove motion artifact in resting state fMRI

PubMed Central

Power, Jonathan D; Mitra, Anish; Laumann, Timothy O; Snyder, Abraham Z; Schlaggar, Bradley L; Petersen, Steven E

2013-01-01

Head motion systematically alters correlations in resting state functional connectivity fMRI (RSFC). In this report we examine impact of motion on signal intensity and RSFC correlations. We find that motion-induced signal changes (1) are often complex and variable waveforms, (2) are often shared across nearly all brain voxels, and (3) often persist more than 10 seconds after motion ceases. These signal changes, both during and after motion, increase observed RSFC correlations in a distance-dependent manner. Motion-related signal changes are not removed by a variety of motion-based regressors, but are effectively reduced by global signal regression. We link several measures of data quality to motion, changes in signal intensity, and changes in RSFC correlations. We demonstrate that improvements in data quality measures during processing may represent cosmetic improvements rather than true correction of the data. We demonstrate a within-subject, censoring-based artifact removal strategy based on volume censoring that reduces group differences due to motion to chance levels. We note conditions under which group-level regressions do and do not correct motion-related effects. PMID:23994314

Essential Limitations of the Standard THz TDS Method for Substance Detection and Identification and a Way of Overcoming Them

PubMed Central

Trofimov, Vyacheslav A.; Varentsova, Svetlana A.

2016-01-01

Low efficiency of the standard THz TDS method of the detection and identification of substances based on a comparison of the spectrum for the signal under investigation with a standard signal spectrum is demonstrated using the physical experiments conducted under real conditions with a thick paper bag as well as with Si-based semiconductors under laboratory conditions. In fact, standard THz spectroscopy leads to false detection of hazardous substances in neutral samples, which do not contain them. This disadvantage of the THz TDS method can be overcome by using time-dependent THz pulse spectrum analysis. For a quality assessment of the standard substance spectral features presence in the signal under analysis, one may use time-dependent integral correlation criteria. PMID:27070617

Essential Limitations of the Standard THz TDS Method for Substance Detection and Identification and a Way of Overcoming Them.

PubMed

Trofimov, Vyacheslav A; Varentsova, Svetlana A

2016-04-08

Low efficiency of the standard THz TDS method of the detection and identification of substances based on a comparison of the spectrum for the signal under investigation with a standard signal spectrum is demonstrated using the physical experiments conducted under real conditions with a thick paper bag as well as with Si-based semiconductors under laboratory conditions. In fact, standard THz spectroscopy leads to false detection of hazardous substances in neutral samples, which do not contain them. This disadvantage of the THz TDS method can be overcome by using time-dependent THz pulse spectrum analysis. For a quality assessment of the standard substance spectral features presence in the signal under analysis, one may use time-dependent integral correlation criteria.

Respiration-rate estimation of a moving target using impulse-based ultra wideband radars.

PubMed

Sharafi, Azadeh; Baboli, Mehran; Eshghi, Mohammad; Ahmadian, Alireza

2012-03-01

Recently, Ultra-wide band signals have become attractive for their particular advantage of having high spatial resolution and good penetration ability which makes them suitable in medical applications. One of these applications is wireless detection of heart rate and respiration rate. Two hypothesis of static environment and fixed patient are considered in the method presented in previous literatures which are not valid for long term monitoring of ambulant patients. In this article, a new method to detect the respiration rate of a moving target is presented. The first algorithm is applied to the simulated and experimental data for detecting respiration rate of a fixed target. Then, the second algorithm is developed to detect respiration rate of a moving target. The proposed algorithm uses correlation for body movement cancellation, and then detects the respiration rate based on energy in frequency domain. The results of algorithm prove an accuracy of 98.4 and 97% in simulated and experimental data, respectively.

The relationship between stereoacuity and stereomotion thresholds.

PubMed

Cumming, B G

1995-01-01

There are in principle at least two binocular sources of information that could be used to determine the motion of an object towards or away from an observer; such motion produces changes in binocular disparities over time and also generates different image velocities in the two eyes. It has been argued in the past that stereomotion is detected by a mechanism that is independent of that which detects static disparities. More recently this conclusion has been questioned. If stereomotion detection in fact depends upon detecting disparities, there should be a clear correlation between static stereo-detection thresholds and stereomotion thresholds. If the systems are separate, there need be no such correlation. Four types of threshold measurement were performed by means of random-dot stereograms: (1) static stereo detection/discrimination; (2) stereomotion detection in random-dot stereograms (temporally uncorrelated); (3) stereomotion detection in temporally correlated random-dot stereograms; and (4) binocular detection of frontoparallel motion. Three normal subjects and five subjects with unusually high stereoacuities were studied. In addition, two manipulations were performed that altered stereomotion thresholds: changes in mean disparity, and image defocus produced by positive spectacle lenses. Across subjects and conditions, stereomotion thresholds were well correlated with stereo-discrimination thresholds. Stereomotion was poorly correlated with binocular frontoparallel-motion thresholds. These results suggest that stereomotion is detected by means of registering changes in the output of the same disparity detectors that are used to detect static disparities.

Ranking Causal Anomalies via Temporal and Dynamical Analysis on Vanishing Correlations.

PubMed

Cheng, Wei; Zhang, Kai; Chen, Haifeng; Jiang, Guofei; Chen, Zhengzhang; Wang, Wei

2016-08-01

Modern world has witnessed a dramatic increase in our ability to collect, transmit and distribute real-time monitoring and surveillance data from large-scale information systems and cyber-physical systems. Detecting system anomalies thus attracts significant amount of interest in many fields such as security, fault management, and industrial optimization. Recently, invariant network has shown to be a powerful way in characterizing complex system behaviours. In the invariant network, a node represents a system component and an edge indicates a stable, significant interaction between two components. Structures and evolutions of the invariance network, in particular the vanishing correlations, can shed important light on locating causal anomalies and performing diagnosis. However, existing approaches to detect causal anomalies with the invariant network often use the percentage of vanishing correlations to rank possible casual components, which have several limitations: 1) fault propagation in the network is ignored; 2) the root casual anomalies may not always be the nodes with a high-percentage of vanishing correlations; 3) temporal patterns of vanishing correlations are not exploited for robust detection. To address these limitations, in this paper we propose a network diffusion based framework to identify significant causal anomalies and rank them. Our approach can effectively model fault propagation over the entire invariant network, and can perform joint inference on both the structural, and the time-evolving broken invariance patterns. As a result, it can locate high-confidence anomalies that are truly responsible for the vanishing correlations, and can compensate for unstructured measurement noise in the system. Extensive experiments on synthetic datasets, bank information system datasets, and coal plant cyber-physical system datasets demonstrate the effectiveness of our approach.

Mapping Base Modifications in DNA by Transverse-Current Sequencing

NASA Astrophysics Data System (ADS)

Alvarez, Jose R.; Skachkov, Dmitry; Massey, Steven E.; Kalitsov, Alan; Velev, Julian P.

2018-02-01

Sequencing DNA modifications and lesions, such as methylation of cytosine and oxidation of guanine, is even more important and challenging than sequencing the genome itself. The traditional methods for detecting DNA modifications are either insensitive to these modifications or require additional processing steps to identify a particular type of modification. Transverse-current sequencing in nanopores can potentially identify the canonical bases and base modifications in the same run. In this work, we demonstrate that the most common DNA epigenetic modifications and lesions can be detected with any predefined accuracy based on their tunneling current signature. Our results are based on simulations of the nanopore tunneling current through DNA molecules, calculated using nonequilibrium electron-transport methodology within an effective multiorbital model derived from first-principles calculations, followed by a base-calling algorithm accounting for neighbor current-current correlations. This methodology can be integrated with existing experimental techniques to improve base-calling fidelity.

Large-Scale in-House Cell-Based Assay for Evaluating the Serostatus in Patients with Neuromyelitis Optica Spectrum Disorder Based on New Diagnostic Criteria.

PubMed

Kim, Yeseul; Kim, Gayoung; Kong, Byung Soo; Lee, Ji Eun; Oh, Yu Mi; Hyun, Jae Won; Kim, Su Hyun; Joung, AeRan; Kim, Byoung Joon; Choi, Kyungho; Kim, Ho Jin

2017-04-01

The detection of aquaporin 4-IgG (AQP4-IgG) is now a critical diagnostic criterion for neuromyelitis optica spectrum disorder (NMOSD). To evaluate the serostatus of NMOSD patients based on the 2015 new diagnostic criteria using a new in-house cell-based assay (CBA). We generated a stable cell line using internal ribosome entry site-containing bicistronic vectors, which allow the simultaneous expression of two proteins (AQP4 and green fluorescent protein) separately from the same RNA transcript. We performed in-house CBA using serum from 386 patients: 178 NMOSD patients diagnosed according to the new diagnostic criteria without AQP4-IgG, 63 high risk NMOSD patients presenting 1 of the 6 core clinical characteristics of NMOSD but not fulfilling dissemination in space, and 145 patients with other neurological diseases, including 66 with multiple sclerosis. The serostatus of 111 definite and high risk NMOSD patients were also tested using a commercial CBA kit with identical serum to evaluate the correlation between the 2 methods. All assays were performed by two independent and blinded investigators. Our in-house assay yielded a specificity of 100% and sensitivities of 80% (142 of 178) and 76% (48 of 63) when detecting definite- and high risk NMOSD patients, respectively. The comparison with the commercial CBA kit revealed a correlation for 102 of the 111 patients: no correlation was present in 7 patients who were seronegative using the commercial method but seropositive using the in-house method, and in 2 patients who were seropositive using the commercial method but seronegative using the in-house method. These results demonstrate that our in-house CBA is a highly specific and sensitive method for detecting AQP4-IgG in NMOSD patients. Copyright © 2017 Korean Neurological Association

Bacterial Membrane Depolarization-Linked Fuel Cell Potential Burst as Signal for Selective Detection of Alcohol.

PubMed

Kaushik, Sharbani; Goswami, Pranab

2018-06-06

The biosensing application of microbial fuel cell (MFC) is hampered by its long response time, poor selectivity, and technical difficulty in developing portable devices. Herein, a novel signal form for rapid detection of ethanol was generated in a photosynthetic MFC (PMFC). First, a dual chambered (100 mL each) PMFC was fabricated by using cyanobacteria-based anode and abiotic cathode, and its performance was examined for detection of alcohols. A graphene-based nanobiocomposite matrix was layered over graphite anode to support cyanobacterial biofilm growth and to facilitate electron transfer. Injection of alcohols into the anodic chamber caused a transient potential burst of the PMFC within 60 s (load 1000 Ω), and the magnitude of potential could be correlated to the ethanol concentrations in the range 0.001-20% with a limit of detection (LOD) of 0.13% ( R 2 = 0.96). The device exhibited higher selectivity toward ethanol than methanol as discerned from the corresponding cell-alcohol interaction constant ( K i ) of 780 and 1250 mM. The concept was then translated to a paper-based PMFC (p-PMFC) (size ∼20 cm 2 ) wherein, the cells were merely immobilized over the anode. The device with a shelf life of ∼3 months detected ethanol within 10 s with a dynamic range of 0.005-10% and LOD of 0.02% ( R 2 = 0.99). The fast response time was attributed to the higher wettability of ethanol on the immobilized cell surface as validated by the contact angle data. Alcohols degraded the cell membrane on the order of ethanol > methanol, enhanced the redox current of the membrane-bound electron carrier proteins, and pushed the anodic band gap toward more negative value. The consequence was the potential burst, the magnitude of which was correlated to the ethanol concentrations. This novel approach has a great application potential for selective, sensitive, rapid, and portable detection of ethanol.

Introduction of the hybcell-based compact sequencing technology and comparison to state-of-the-art methodologies for KRAS mutation detection.

PubMed

Zopf, Agnes; Raim, Roman; Danzer, Martin; Niklas, Norbert; Spilka, Rita; Pröll, Johannes; Gabriel, Christian; Nechansky, Andreas; Roucka, Markus

2015-03-01

The detection of KRAS mutations in codons 12 and 13 is critical for anti-EGFR therapy strategies; however, only those methodologies with high sensitivity, specificity, and accuracy as well as the best cost and turnaround balance are suitable for routine daily testing. Here we compared the performance of compact sequencing using the novel hybcell technology with 454 next-generation sequencing (454-NGS), Sanger sequencing, and pyrosequencing, using an evaluation panel of 35 specimens. A total of 32 mutations and 10 wild-type cases were reported using 454-NGS as the reference method. Specificity ranged from 100% for Sanger sequencing to 80% for pyrosequencing. Sanger sequencing and hybcell-based compact sequencing achieved a sensitivity of 96%, whereas pyrosequencing had a sensitivity of 88%. Accuracy was 97% for Sanger sequencing, 85% for pyrosequencing, and 94% for hybcell-based compact sequencing. Quantitative results were obtained for 454-NGS and hybcell-based compact sequencing data, resulting in a significant correlation (r = 0.914). Whereas pyrosequencing and Sanger sequencing were not able to detect multiple mutated cell clones within one tumor specimen, 454-NGS and the hybcell-based compact sequencing detected multiple mutations in two specimens. Our comparison shows that the hybcell-based compact sequencing is a valuable alternative to state-of-the-art methodologies used for detection of clinically relevant point mutations.

Electrical response of culture media during bacterial growth on a paper-based device

NASA Astrophysics Data System (ADS)

Srimongkon, Tithimanan; Buerkle, Marius; Nakamura, Akira; Enomae, Toshiharu; Ushijima, Hirobumi; Fukuda, Nobuko

2017-05-01

In this work, we evaluated the feasibility of a paper-based bacterial detection system. The paper served as a substrate for the measurement electrodes and the culture medium. Using a printing technique, we patterned gold electrodes onto the paper substrate and applied Luria broth (LB) agar gel as a culture medium on top of the electrodes. As the first step towards the development of a bacterial detection system, we determined changes in the surface potential during bacterial growth and monitored these changes over 24 h. This allowed us to correlate changes in the surface potential with the different growth phases of the bacteria.

Spectroscopic thermoacoustic imaging of water and fat composition

NASA Astrophysics Data System (ADS)

Bauer, Daniel R.; Wang, Xiong; Vollin, Jeff; Xin, Hao; Witte, Russell S.

2012-07-01

During clinical studies, thermoacoustic imaging (TAI) failed to reliably identify malignant breast tissue. To increase detection capability, we propose spectroscopic TAI to differentiate samples based on the slope of their dielectric absorption. Phantoms composed of different ratios of water and fat were imaged using excitation frequencies between 2.7 and 3.1 GHz. The frequency-dependent slope of the TA signal was highly correlated with that of its absorption coefficient (R2 = 0.98 and p < 0.01), indicating spectroscopic TAI can distinguish materials based on their intrinsic dielectric properties. This approach potentially enhances cancer detection due to the increased water content of many tumors.

Optical reading of contaminants in aqueous media based on gold nanoparticles.

PubMed

Du, Jianjun; Zhu, Bowen; Peng, Xiaojun; Chen, Xiaodong

2014-09-10

With increasing trends of global population growth, urbanization, pollution over-exploitation, and climate change, the safe water supply has become a global issue and is threatening our society in terms of sustainable development. Therefore, there is a growing need for a water-monitoring platform with the capability of rapidness, specificity, low-cost, and robustness. This review summarizes the recent developments in the design and application of gold nanoparticles (AuNPs) based optical assays to detect contaminants in aqueous media with a high performance. First, a brief discussion on the correlation between the optical reading strategy and the optical properties of AuNPs is presented. Then, we summarize the principle behind AuNP-based optical assays to detect different contaminants, such as toxic metal ion, anion, and pesticides, according to different optical reading strategies: colorimetry, scattering, and fluorescence. Finally, the comparison of these assays and the outlook of AuNP-based optical detection are discussed. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Degree-strength correlation reveals anomalous trading behavior.

PubMed

Sun, Xiao-Qian; Shen, Hua-Wei; Cheng, Xue-Qi; Wang, Zhao-Yang

2012-01-01

Manipulation is an important issue for both developed and emerging stock markets. Many efforts have been made to detect manipulation in stock markets. However, it is still an open problem to identify the fraudulent traders, especially when they collude with each other. In this paper, we focus on the problem of identifying the anomalous traders using the transaction data of eight manipulated stocks and forty-four non-manipulated stocks during a one-year period. By analyzing the trading networks of stocks, we find that the trading networks of manipulated stocks exhibit significantly higher degree-strength correlation than the trading networks of non-manipulated stocks and the randomized trading networks. We further propose a method to detect anomalous traders of manipulated stocks based on statistical significance analysis of degree-strength correlation. Experimental results demonstrate that our method is effective at distinguishing the manipulated stocks from non-manipulated ones. Our method outperforms the traditional weight-threshold method at identifying the anomalous traders in manipulated stocks. More importantly, our method is difficult to be fooled by colluded traders.

Reversible thrombin detection by aptamer functionalized STING sensors.

PubMed

Actis, Paolo; Rogers, Adam; Nivala, Jeff; Vilozny, Boaz; Seger, R Adam; Jejelowo, Olufisayo; Pourmand, Nader

2011-07-15

Signal Transduction by Ion NanoGating (STING) is a label-free technology based on functionalized quartz nanopipettes. The nanopipette pore can be decorated with a variety of recognition elements and the molecular interaction is transduced via a simple electrochemical system. A STING sensor can be easily and reproducibly fabricated and tailored at the bench starting from inexpensive quartz capillaries. The analytical application of this new biosensing platform, however, was limited due to the difficult correlation between the measured ionic current and the analyte concentration in solution. Here we show that STING sensors functionalized with aptamers allow the quantitative detection of thrombin. The binding of thrombin generates a signal that can be directly correlated to its concentration in the bulk solution. Copyright © 2011 Elsevier B.V. All rights reserved.

Fiber fault location utilizing traffic signal in optical network.

PubMed

Zhao, Tong; Wang, Anbang; Wang, Yuncai; Zhang, Mingjiang; Chang, Xiaoming; Xiong, Lijuan; Hao, Yi

2013-10-07

We propose and experimentally demonstrate a method for fault location in optical communication network. This method utilizes the traffic signal transmitted across the network as probe signal, and then locates the fault by correlation technique. Compared with conventional techniques, our method has a simple structure and low operation expenditure, because no additional device is used, such as light source, modulator and signal generator. The correlation detection in this method overcomes the tradeoff between spatial resolution and measurement range in pulse ranging technique. Moreover, signal extraction process can improve the location result considerably. Experimental results show that we achieve a spatial resolution of 8 cm and detection range of over 23 km with -8-dBm mean launched power in optical network based on synchronous digital hierarchy protocols.

Adaptation of reference volumes for correlation-based digital holographic particle tracking

NASA Astrophysics Data System (ADS)

Hesseling, Christina; Peinke, Joachim; Gülker, Gerd

2018-04-01

Numerically reconstructed reference volumes tailored to particle images are used for particle position detection by means of three-dimensional correlation. After a first tracking of these positions, the experimentally recorded particle images are retrieved as a posteriori knowledge about the particle images in the system. This knowledge is used for a further refinement of the detected positions. A transparent description of the individual algorithm steps including the results retrieved with experimental data complete the paper. The work employs extraordinarily small particles, smaller than the pixel pitch of the camera sensor. It is the first approach known to the authors that combines numerical knowledge about particle images and particle images retrieved from the experimental system to an iterative particle tracking approach for digital holographic particle tracking velocimetry.

DNA condensation and size effects of DNA condensation agent

NASA Astrophysics Data System (ADS)

Liu, Yan-Hui; Jiang, Chong-Ming; Guo, Xin-Miao; Tang, Yan-Lin; Hu, Lin

2013-08-01

Based on the model of the strong correlation of counterions condensed on DNA molecule, by tailoring interaction potential, interduplex spacing and correlation spacing between condensed counterions on DNA molecule and interduplex spacing fluctuation strength, toroidal configuration, rod-like configuration and two-hole configurations are possible. The size effects of counterion structure on the toroidal structure can be detected by this model. The autocorrelation function of the tangent vectors is found as an effective way to detect the structure of toroidal conformations and the generic pathway of the process of DNA condensation. The generic pathway of all of the configurations involves an initial nucleation loop, and the next part of the DNA chain is folded on the top of the initial nucleation loop with different manners, in agreement with the recent experimental results.

IVGTT-based simple assessment of glucose tolerance in the Zucker fatty rat: Validation against minimal models.

PubMed

Morettini, Micaela; Faelli, Emanuela; Perasso, Luisa; Fioretti, Sandro; Burattini, Laura; Ruggeri, Piero; Di Nardo, Francesco

2017-01-01

For the assessment of glucose tolerance from IVGTT data in Zucker rat, minimal model methodology is reliable but time- and money-consuming. This study aimed to validate for the first time in Zucker rat, simple surrogate indexes of insulin sensitivity and secretion against the glucose-minimal-model insulin sensitivity index (SI) and against first- (Φ1) and second-phase (Φ2) β-cell responsiveness indexes provided by C-peptide minimal model. Validation of the surrogate insulin sensitivity index (ISI) and of two sets of coupled insulin-based indexes for insulin secretion, differing from the cut-off point between phases (FPIR3-SPIR3, t = 3 min and FPIR5-SPIR5, t = 5 min), was carried out in a population of ten Zucker fatty rats (ZFR) and ten Zucker lean rats (ZLR). Considering the whole rat population (ZLR+ZFR), ISI showed a significant strong correlation with SI (Spearman's correlation coefficient, r = 0.88; P<0.001). Both FPIR3 and FPIR5 showed a significant (P<0.001) strong correlation with Φ1 (r = 0.76 and r = 0.75, respectively). Both SPIR3 and SPIR5 showed a significant (P<0.001) strong correlation with Φ2 (r = 0.85 and r = 0.83, respectively). ISI is able to detect (P<0.001) the well-recognized reduction in insulin sensitivity in ZFRs, compared to ZLRs. The insulin-based indexes of insulin secretion are able to detect in ZFRs (P<0.001) the compensatory increase of first- and second-phase secretion, associated to the insulin-resistant state. The ability of the surrogate indexes in describing glucose tolerance in the ZFRs was confirmed by the Disposition Index analysis. The model-based validation performed in the present study supports the utilization of low-cost, insulin-based indexes for the assessment of glucose tolerance in Zucker rat, reliable animal model of human metabolic syndrome.

Detection of Sleep Disordered Breathing and Its Central/Obstructive Character Using Nasal Cannula and Finger Pulse Oximeter

PubMed Central

Sommermeyer, Dirk; Zou, Ding; Grote, Ludger; Hedner, Jan

2012-01-01

Study Objective: To assess the accuracy of novel algorithms using an oximeter-based finger plethysmographic signal in combination with a nasal cannula for the detection and differentiation of central and obstructive apneas. The validity of single pulse oximetry to detect respiratory disturbance events was also studied. Methods: Patients recruited from four sleep laboratories underwent an ambulatory overnight cardiorespiratory polygraphy recording. The nasal flow and photoplethysmographic signals of the recording were analyzed by automated algorithms. The apnea hypopnea index (AHIauto) was calculated using both signals, and a respiratory disturbance index (RDIauto) was calculated from photoplethysmography alone. Apnea events were classified into obstructive and central types using the oximeter derived pulse wave signal and compared with manual scoring. Results: Sixty-six subjects (42 males, age 54 ± 14 yrs, body mass index 28.5 ± 5.9 kg/m2) were included in the analysis. AHImanual (19.4 ± 18.5 events/h) correlated highly significantly with AHIauto (19.9 ± 16.5 events/h) and RDIauto (20.4 ± 17.2 events/h); the correlation coefficients were r = 0.94 and 0.95, respectively (p < 0.001) with a mean difference of −0.5 ± 6.6 and −1.0 ± 6.1 events/h. The automatic analysis of AHIauto and RDIauto detected sleep apnea (cutoff AHImanual ≥ 15 events/h) with a sensitivity/specificity of 0.90/0.97 and 0.86/0.94, respectively. The automated obstructive/central apnea indices correlated closely with manually scoring (r = 0.87 and 0.95, p < 0.001) with mean difference of −4.3 ± 7.9 and 0.3 ± 1.5 events/h, respectively. Conclusions: Automatic analysis based on routine pulse oximetry alone may be used to detect sleep disordered breathing with accuracy. In addition, the combination of photoplethysmographic signals with a nasal flow signal provides an accurate distinction between obstructive and central apneic events during sleep. Citation: Sommermeyer D; Zou D; Grote L; Hedner J. Detection of sleep disordered breathing and its central/obstructive character using nasal cannula and finger pulse oximeter. J Clin Sleep Med 2012;8(5):527-533. PMID:23066364

A novel fast phase correlation algorithm for peak wavelength detection of Fiber Bragg Grating sensors.

PubMed

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

2014-03-24

Fiber Bragg Gratings (FBGs) can be used as sensors for strain, temperature and pressure measurements. For this purpose, the ability to determine the Bragg peak wavelength with adequate wavelength resolution and accuracy is essential. However, conventional peak detection techniques, such as the maximum detection algorithm, can yield inaccurate and imprecise results, especially when the Signal to Noise Ratio (SNR) and the wavelength resolution are poor. Other techniques, such as the cross-correlation demodulation algorithm are more precise and accurate but require a considerable higher computational effort. To overcome these problems, we developed a novel fast phase correlation (FPC) peak detection algorithm, which computes the wavelength shift in the reflected spectrum of a FBG sensor. This paper analyzes the performance of the FPC algorithm for different values of the SNR and wavelength resolution. Using simulations and experiments, we compared the FPC with the maximum detection and cross-correlation algorithms. The FPC method demonstrated a detection precision and accuracy comparable with those of cross-correlation demodulation and considerably higher than those obtained with the maximum detection technique. Additionally, FPC showed to be about 50 times faster than the cross-correlation. It is therefore a promising tool for future implementation in real-time systems or in embedded hardware intended for FBG sensor interrogation.

Quantitative detection method of Enterocytozoon hepatopenaei using TaqMan probe real-time PCR.

PubMed

Liu, Ya-Mei; Qiu, Liang; Sheng, An-Zhi; Wan, Xiao-Yuan; Cheng, Dong-Yuan; Huang, Jie

2018-01-01

A TaqMan probe and a pair of specific primers were selected from the small subunit ribosomal DNA (SSU rDNA) sequence of Enterocytozoon hepatopenaei (EHP); this real-time PCR assay was developed and optimized. It showed a good linearity in detecting standards of EHP SSU rDNA fragments from 4 × 10 2 to 4 × 10 8 copies/reaction using the established method. The detection limit of the qPCR method was as low as 4 × 10 1 copies per reaction, which was higher than the conventional PCR and SYBR Green I-based EHP qPCR reported. Using the qPCR assay, EHP was detected in four batches of slow-growing Penaeus vannamei specimens collected from Tianjin and Zhejiang Province in China was detected using qPCR. The results showed that all the hepatopancreas from the slow-growing P. vannamei specimens were detected as EHP-positive. EHP copies of hepatopancreas in some batches had a negative correlation with the body mass index (BMI) of shrimps; however, not all batches of specimens had this negative correlation between EHP copies of hepatopancreas and BMI. This qPCR technique is sensitive, specific and easy to perform (96 tests in <3 h), which provides technical support for the detection and prevention of EHP. Copyright © 2017 Elsevier Inc. All rights reserved.

Improving the performance of lesion-based computer-aided detection schemes of breast masses using a case-based adaptive cueing method

NASA Astrophysics Data System (ADS)

Tan, Maxine; Aghaei, Faranak; Wang, Yunzhi; Qian, Wei; Zheng, Bin

2016-03-01

Current commercialized CAD schemes have high false-positive (FP) detection rates and also have high correlations in positive lesion detection with radiologists. Thus, we recently investigated a new approach to improve the efficacy of applying CAD to assist radiologists in reading and interpreting screening mammograms. Namely, we developed a new global feature based CAD approach/scheme that can cue the warning sign on the cases with high risk of being positive. In this study, we investigate the possibility of fusing global feature or case-based scores with the local or lesion-based CAD scores using an adaptive cueing method. We hypothesize that the information from the global feature extraction (features extracted from the whole breast regions) are different from and can provide supplementary information to the locally-extracted features (computed from the segmented lesion regions only). On a large and diverse full-field digital mammography (FFDM) testing dataset with 785 cases (347 negative and 438 cancer cases with masses only), we ran our lesion-based and case-based CAD schemes "as is" on the whole dataset. To assess the supplementary information provided by the global features, we used an adaptive cueing method to adaptively adjust the original CAD-generated detection scores (Sorg) of a detected suspicious mass region based on the computed case-based score (Scase) of the case associated with this detected region. Using the adaptive cueing method, better sensitivity results were obtained at lower FP rates (<= 1 FP per image). Namely, increases of sensitivities (in the FROC curves) of up to 6.7% and 8.2% were obtained for the ROI and Case-based results, respectively.

Development of a low-cost detection method for miRNA microarray.

PubMed

Li, Wei; Zhao, Botao; Jin, Youxin; Ruan, Kangcheng

2010-04-01

MicroRNA (miRNA) microarray is a powerful tool to explore the expression profiling of miRNA. The current detection method used in miRNA microarray is mainly fluorescence based, which usually requires costly detection system such as laser confocal scanner of tens of thousands of dollars. Recently, we developed a low-cost yet sensitive detection method for miRNA microarray based on enzyme-linked assay. In this approach, the biotinylated miRNAs were captured by the corresponding oligonucleotide probes immobilized on microarray slide; and then the biotinylated miRNAs would capture streptavidin-conjugated alkaline phosphatase. A purple-black precipitation on each biotinylated miRNA spot was produced by the enzyme catalytic reaction. It could be easily detected by a charge-coupled device digital camera mounted on a microscope, which lowers the detection cost more than 100 fold compared with that of fluorescence method. Our data showed that signal intensity of the spot correlates well with the biotinylated miRNA concentration and the detection limit for miRNAs is at least 0.4 fmol and the detection dynamic range spans about 2.5 orders of magnitude, which is comparable to that of fluorescence method.

On comprehensive recovery of an aftershock sequence with cross correlation

NASA Astrophysics Data System (ADS)

Kitov, I.; Bobrov, D.; Coyne, J.; Turyomurugyendo, G.

2012-04-01

We have introduced cross correlation between seismic waveforms as a technique for signal detection and automatic event building at the International Data Centre (IDC) of the Comprehensive Nuclear-Test-Ban Treaty Organization. The intuition behind signal detection is simple - small and mid-sized seismic events close in space should produce similar signals at the same seismic stations. Equivalently, these signals have to be characterized by a high cross correlation coefficient. For array stations with many individual sensors distributed over a large area, signals from events at distances beyond, say, 50 km, are subject to destructive interference when cross correlated due to changing time delays between various channels. Thus, any cross correlation coefficient above some predefined threshold can be considered as a signature of a valid signal. With a dense grid of master events (spacing between adjacent masters between 20 km and 50 km corresponds to the statistically estimated correlation distance) with high quality (signal-to-noise ratio above 10) template waveforms at primary array stations of the International Monitoring System one can detect signals from and then build natural and manmade seismic events close to the master ones. The use of cross correlation allows detecting smaller signals (sometimes below noise level) than provided by the current IDC detecting techniques. As a result it is possible to automatically build from 50% to 100% more valid seismic events than included in the Reviewed Event Bulletin (REB). We have developed a tentative pipeline for automatic processing at the IDC. It includes three major stages. Firstly, we calculate cross correlation coefficient for a given master and continuous waveforms at the same stations and carry out signal detection as based on the statistical behavior of signal-to-noise ratio of the cross correlation coefficient. Secondly, a thorough screening is performed for all obtained signals using f-k analysis and F-statistics as applied to the cross-correlation traces at individual channels of all included array stations. Thirdly, local (i.e. confined to the correlation distance around the master event) association of origin times of all qualified signals is fulfilled. These origin times are calculated from the arrival times of these signals, which are reduced to the origin times by the travel times from the master event. An aftershock sequence of a mid-size earthquake is an ideal case to test cross correlation techniques for autiomatic event building. All events should be close to the mainshock and occur within several days. Here we analyse the aftershock sequence of an earthquake in the North Atlantic Ocean with mb(IDC)=4.79. The REB includes 38 events at distances less than 150 km from the mainshock. Our ultimate goal is to excersice the complete iterative procedure to find all possible aftershocks. We start with the mainshock and recover ten aftershocks with the largest number of stations to produce an initial set of master events with the highest quality templates. Then we find all aftershocks in the REB and many additional events, which were not originally found by the IDC. Using all events found after the first iteration as master events we find new events, which are also used in the next iteration. The iterative process stops when no new events can be found. In that sense the final set of aftershocks obtained with cross correlation is a comprehensive one.

Interpreting null results from measurements with uncertain correlations: an info-gap approach.

PubMed

Ben-Haim, Yakov

2011-01-01

Null events—not detecting a pernicious agent—are the basis for declaring the agent is absent. Repeated nulls strengthen confidence in the declaration. However, correlations between observations are difficult to assess in many situations and introduce uncertainty in interpreting repeated nulls. We quantify uncertain correlations using an info-gap model, which is an unbounded family of nested sets of possible probabilities. An info-gap model is nonprobabilistic and entails no assumption about a worst case. We then evaluate the robustness, to uncertain correlations, of estimates of the probability of a null event. This is then the basis for evaluating a nonprobabilistic robustness-based confidence interval for the probability of a null. © 2010 Society for Risk Analysis.

A modified cross-correlation method for white-light optical fiber extrinsic Fabry-Perot interferometric hydrogen sensors

NASA Astrophysics Data System (ADS)

Yang, Zhen; Zhang, Min; Liao, Yanbiao; Lai, Shurong; Tian, Qian; Li, Qisheng; Zhang, Yi; Zhuang, Zhi

2009-11-01

An extrinsic Fabry-Perot interferometric (EFPI) optical fiber hydrogen sensor based on palladium silver (Pd-Ag) film is designed for hydrogen leakage detection. A modified cross correlation signal processing method for an optical fiber EFPI hydrogen sensor is presented. As the applying of a special correlating factor which advises the effect on the fringe visibility of the gap length and wavelength, the cross correlation method has a high accuracy which is insensitive to light source power drift or changes in attenuation in the fiber, and the segment search method is employed to reduce computation and demodulating speed is fast. The Fabry-Perot gap length resolution of better than 0.2nm is achieved in a certain concentration of hydrogen.

Do craniopharyngioma molecular signatures correlate with clinical characteristics?

PubMed

Omay, Sacit Bulent; Chen, Yu-Ning; Almeida, Joao Paulo; Ruiz-Treviño, Armando Saul; Boockvar, John A; Stieg, Philip E; Greenfield, Jeffrey P; Souweidane, Mark M; Kacker, Ashutosh; Pisapia, David J; Anand, Vijay K; Schwartz, Theodore H

2018-05-01

OBJECTIVE Exome sequencing studies have recently demonstrated that papillary craniopharyngiomas (PCPs) and adamantinomatous craniopharyngiomas (ACPs) have distinct genetic origins, each primarily driven by mutually exclusive alterations: either BRAF ( V600E), observed in 95% of PCPs, or CTNNB1, observed in 75%-96% of ACPs. How the presence of these molecular signatures, or their absence, correlates with clinical, radiographic, and outcome variables is unknown. METHODS The pathology records for patients who underwent surgery for craniopharyngiomas between May 2000 and March 2015 at Weill Cornell Medical College were reviewed. Craniopharyngiomas were identified and classified as PCP or ACP. Patients were placed into 1 of 3 groups based on their genomic mutations: BRAF mutation only, CTNNB1 mutation only, and tumors with neither of these mutations detected (not detected [ND]). Demographic, radiological, and clinical variables were collected, and their correlation with each genomic group was tested. RESULTS Histology correlated strongly with mutation group. All BRAF tumors with mutations were PCPs, and all CTNNB1 with mutations and ND tumors were ACPs. Preoperative and postoperative clinical symptoms and radiographic features did not correlate with any mutation group. There was a statistically significant relationship (p = 0.0323) between the age group (pediatric vs adult) and the mutation groups. The ND group tumors were more likely to involve the sella (p = 0.0065). CONCLUSIONS The mutation signature in craniopharyngioma is highly predictive of histology. The subgroup of tumors in which these 2 mutations are not detected is more likely to occur in children, be located in the sella, and be of ACP histology.

Comparison of the QuantiGene 2.0 Assay and Real-Time RT-PCR in the Detection of p53 Isoform mRNA Expression in Formalin-Fixed Paraffin-Embedded Tissues- A Preliminary Study

PubMed Central

Morten, Brianna C.; Scott, Rodney J.; Avery-Kiejda, Kelly A.

2016-01-01

p53 is expressed as multiple smaller isoforms whose functions in cancer are not well understood. The p53 isoforms demonstrate abnormal expression in different cancers, suggesting they are important in modulating the function of full-length p53 (FLp53). The quantification of relative mRNA expression has routinely been performed using real-time PCR (qPCR). However, there are serious limitations when detecting p53 isoforms using this method, particularly for formalin-fixed paraffin-embedded (FFPE) tissues. The use of FFPE tumours would be advantageous to correlate expression of p53 isoforms with important clinical features of cancer. One alternative method of RNA detection is the hybridization-based QuantiGene 2.0 Assay, which has been shown to be advantageous for the detection of RNA from FFPE tissues. In this pilot study, we compared the QuantiGene 2.0 Assay to qPCR for the detection of FLp53 and its isoform Δ40p53 in matched fresh frozen (FF) and FFPE breast tumours. FLp53 mRNA expression was detected using qPCR in FF and FFPE tissues, but Δ40p53 mRNA was only detectable in FF tissues. Similar results were obtained for the QuantiGene 2.0 Assay. FLp53 relative mRNA expression was shown to be strongly correlated between the two methods (R2 = 0.9927, p = 0.0031) in FF tissues, however Δ40p53 was not (R2 = 0.4429, p = 0.3345). When comparing the different methods for the detection of FLp53 mRNA from FFPE and FF samples, no correlation (R2 = 0.0002, p = 0.9863) was shown using the QuantiGene 2.0 Assay, and in contrast, the level of expression was highly correlated between the two tissues using qPCR (R2 = 0.8753, p = 0.0644). These results suggest that both the QuantiGene 2.0 Assay and qPCR methods are inadequate for the quantification of Δ40p53 mRNA in FFPE tissues. Therefore, alternative methods of RNA detection and quantification are required to study the relative expression of Δ40p53 in FFPE samples. PMID:27832134

A Fast Approach to Automatic Detection of Brain Lesions

PubMed Central

Koley, Subhranil; Chakraborty, Chandan; Mainero, Caterina; Fischl, Bruce; Aganj, Iman

2017-01-01

Template matching is a popular approach to computer-aided detection of brain lesions from magnetic resonance (MR) images. The outcomes are often sufficient for localizing lesions and assisting clinicians in diagnosis. However, processing large MR volumes with three-dimensional (3D) templates is demanding in terms of computational resources, hence the importance of the reduction of computational complexity of template matching, particularly in situations in which time is crucial (e.g. emergent stroke). In view of this, we make use of 3D Gaussian templates with varying radii and propose a new method to compute the normalized cross-correlation coefficient as a similarity metric between the MR volume and the template to detect brain lesions. Contrary to the conventional fast Fourier transform (FFT) based approach, whose runtime grows as O(N logN) with the number of voxels, the proposed method computes the cross-correlation in O(N). We show through our experiments that the proposed method outperforms the FFT approach in terms of computational time, and retains comparable accuracy. PMID:29082383

Phase-detected Brillouin optical correlation-domain reflectometry

NASA Astrophysics Data System (ADS)

Mizuno, Yosuke; Hayashi, Neisei; Fukuda, Hideyuki; Nakamura, Kentaro

2018-05-01

Optical fiber sensing techniques based on Brillouin scattering have been extensively studied for structural health monitoring owing to their capability of distributed strain and temperature measurement. Although a higher signal-to-noise ratio (leading to high spatial resolution and high-speed measurement) is generally obtained for two-end-access systems, they reduce the degree of freedom in embedding the sensors into structures, and render the measurement no longer feasible when extremely high loss or breakage occurs at a point of the sensing fiber. To overcome these drawbacks, a one-end-access sensing technique called Brillouin optical correlation-domain reflectometry (BOCDR) has been developed. BOCDR has a high spatial resolution and cost efficiency, but its conventional configuration suffered from relatively low-speed operation. In this paper, we review the recently developed high-speed configurations of BOCDR, including phase-detected BOCDR, with which we demonstrate real-time distributed measurement by tracking a propagating mechanical wave. We also demonstrate breakage detection with a wide strain dynamic range.

Application of CdSe quantum dots for the direct detection of TNT.

PubMed

Yi, Kui-Yu

2016-02-01

CdSe quantum dots were synthesized through a simple, green organic-phase method. Paraffin was used as the reaction solvent and a reducing agent, oleic acid was the reaction ligand, and oleyl amine was the stabilizer. Based on the phenomenon of TNT quenched oil-soluble CdSe quantum dot fluorescence, a simple, fast, and direct method of TNT detection was established. Under optimum conditions, the degree of fluorescence quenching of oil-soluble CdSe quantum dots had a good linear correlation with TNT concentration in the 1.0×10(-7)-5.0×10(-5) mol/L range, and the correlation coefficient was 0.9990. TNT detection limit was 2.1×10(-8)mol/L. The method was successfully used to determine TNT-explosion dust samples, results were satisfactory. The fluorescence quenching mechanism of oil-soluble CdSe quantum dots by TNT was also discussed. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Phase-detected Brillouin optical correlation-domain reflectometry

NASA Astrophysics Data System (ADS)

Mizuno, Yosuke; Hayashi, Neisei; Fukuda, Hideyuki; Nakamura, Kentaro

2018-06-01

Optical fiber sensing techniques based on Brillouin scattering have been extensively studied for structural health monitoring owing to their capability of distributed strain and temperature measurement. Although a higher signal-to-noise ratio (leading to high spatial resolution and high-speed measurement) is generally obtained for two-end-access systems, they reduce the degree of freedom in embedding the sensors into structures, and render the measurement no longer feasible when extremely high loss or breakage occurs at a point of the sensing fiber. To overcome these drawbacks, a one-end-access sensing technique called Brillouin optical correlation-domain reflectometry (BOCDR) has been developed. BOCDR has a high spatial resolution and cost efficiency, but its conventional configuration suffered from relatively low-speed operation. In this paper, we review the recently developed high-speed configurations of BOCDR, including phase-detected BOCDR, with which we demonstrate real-time distributed measurement by tracking a propagating mechanical wave. We also demonstrate breakage detection with a wide strain dynamic range.

Martian Atmospheric Methane Plumes from Meteor Shower Infall: A Hypothesis

NASA Technical Reports Server (NTRS)

Fries, M.; Christou, A.; Archer, D.; Conrad, P.; Cooke, W.; Eigenbrode, J.; ten Kate, I. L.; Matney, M.; Niles, P.; Sykes, M.

2016-01-01

Methane plumes in the martian atmosphere have been detected using Earth-based spectroscopy, the Planetary Fourier Spectrometer on the ESA Mars Express mission, and the NASA Mars Science Laboratory. The methane's origin remains a mystery, with proposed sources including volcanism, exogenous sources like impacts and interplanetary dust, aqueous alteration of olivine in the presence of carbonaceous material, release from ancient deposits of methane clathrates, and/or biological activity. To date, none of these phenomena have been found to reliably correlate with the detection of methane plumes. An additional source exists, however: meteor showers could generate martian methane via UV pyrolysis of carbon-rich infall material. We find a correlation between the dates of Mars/cometary orbit encounters and detections of methane on Mars. We hypothesize that cometary debris falls onto Mars during these interactions, depositing freshly disaggregated meteor shower material in a regional concentration. The material generates methane via UV photolysis, resulting in a localized "plume" of short-lived methane.

Long-term scale adaptive tracking with kernel correlation filters

NASA Astrophysics Data System (ADS)

Wang, Yueren; Zhang, Hong; Zhang, Lei; Yang, Yifan; Sun, Mingui

2018-04-01

Object tracking in video sequences has broad applications in both military and civilian domains. However, as the length of input video sequence increases, a number of problems arise, such as severe object occlusion, object appearance variation, and object out-of-view (some portion or the entire object leaves the image space). To deal with these problems and identify the object being tracked from cluttered background, we present a robust appearance model using Speeded Up Robust Features (SURF) and advanced integrated features consisting of the Felzenszwalb's Histogram of Oriented Gradients (FHOG) and color attributes. Since re-detection is essential in long-term tracking, we develop an effective object re-detection strategy based on moving area detection. We employ the popular kernel correlation filters in our algorithm design, which facilitates high-speed object tracking. Our evaluation using the CVPR2013 Object Tracking Benchmark (OTB2013) dataset illustrates that the proposed algorithm outperforms reference state-of-the-art trackers in various challenging scenarios.

Airplane wing deformation and flight flutter detection method by using three-dimensional speckle image correlation technology.

PubMed

Wu, Jun; Yu, Zhijing; Wang, Tao; Zhuge, Jingchang; Ji, Yue; Xue, Bin

2017-06-01

Airplane wing deformation is an important element of aerodynamic characteristics, structure design, and fatigue analysis for aircraft manufacturing, as well as a main test content of certification regarding flutter for airplanes. This paper presents a novel real-time detection method for wing deformation and flight flutter detection by using three-dimensional speckle image correlation technology. Speckle patterns whose positions are determined through the vibration characteristic of the aircraft are coated on the wing; then the speckle patterns are imaged by CCD cameras which are mounted inside the aircraft cabin. In order to reduce the computation, a matching technique based on Geodetic Systems Incorporated coded points combined with the classical epipolar constraint is proposed, and a displacement vector map for the aircraft wing can be obtained through comparing the coordinates of speckle points before and after deformation. Finally, verification experiments containing static and dynamic tests by using an aircraft wing model demonstrate the accuracy and effectiveness of the proposed method.

Distributing entanglement and single photons through an intra-city, free-space quantum channel.

PubMed

Resch, K; Lindenthal, M; Blauensteiner, B; Böhm, H; Fedrizzi, A; Kurtsiefer, C; Poppe, A; Schmitt-Manderbach, T; Taraba, M; Ursin, R; Walther, P; Weier, H; Weinfurter, H; Zeilinger, A

2005-01-10

We have distributed entangled photons directly through the atmosphere to a receiver station 7.8 km away over the city of Vienna, Austria at night. Detection of one photon from our entangled pairs constitutes a triggered single photon source from the sender. With no direct time-stable connection, the two stations found coincidence counts in the detection events by calculating the cross-correlation of locally-recorded time stamps shared over a public internet channel. For this experiment, our quantum channel was maintained for a total of 40 minutes during which time a coincidence lock found approximately 60000 coincident detection events. The polarization correlations in those events yielded a Bell parameter, S=2.27+/-0.019, which violates the CHSH-Bell inequality by 14 standard deviations. This result is promising for entanglement-based freespace quantum communication in high-density urban areas. It is also encouraging for optical quantum communication between ground stations and satellites since the length of our free-space link exceeds the atmospheric equivalent.

Validity of the Indicator Organism Paradigm for Pathogen Reduction in Reclaimed Water and Public Health Protection†

PubMed Central

Harwood, Valerie J.; Levine, Audrey D.; Scott, Troy M.; Chivukula, Vasanta; Lukasik, Jerzy; Farrah, Samuel R.; Rose, Joan B.

2005-01-01

The validity of using indicator organisms (total and fecal coliforms, enterococci, Clostridium perfringens, and F-specific coliphages) to predict the presence or absence of pathogens (infectious enteric viruses, Cryptosporidium, and Giardia) was tested at six wastewater reclamation facilities. Multiple samplings conducted at each facility over a 1-year period. Larger sample volumes for indicators (0.2 to 0.4 liters) and pathogens (30 to 100 liters) resulted in more sensitive detection limits than are typical of routine monitoring. Microorganisms were detected in disinfected effluent samples at the following frequencies: total coliforms, 63%; fecal coliforms, 27%; enterococci, 27%; C. perfringens, 61%; F-specific coliphages, ∼40%; and enteric viruses, 31%. Cryptosporidium oocysts and Giardia cysts were detected in 70% and 80%, respectively, of reclaimed water samples. Viable Cryptosporidium, based on cell culture infectivity assays, was detected in 20% of the reclaimed water samples. No strong correlation was found for any indicator-pathogen combination. When data for all indicators were tested using discriminant analysis, the presence/absence patterns for Giardia cysts, Cryptosporidium oocysts, infectious Cryptosporidium, and infectious enteric viruses were predicted for over 71% of disinfected effluents. The failure of measurements of single indicator organism to correlate with pathogens suggests that public health is not adequately protected by simple monitoring schemes based on detection of a single indicator, particularly at the detection limits routinely employed. Monitoring a suite of indicator organisms in reclaimed effluent is more likely to be predictive of the presence of certain pathogens, and a need for additional pathogen monitoring in reclaimed water in order to protect public health is suggested by this study. PMID:15933017

Intra- and Inter-database Study for Arabic, English, and German Databases: Do Conventional Speech Features Detect Voice Pathology?

PubMed

Ali, Zulfiqar; Alsulaiman, Mansour; Muhammad, Ghulam; Elamvazuthi, Irraivan; Al-Nasheri, Ahmed; Mesallam, Tamer A; Farahat, Mohamed; Malki, Khalid H

2017-05-01

A large population around the world has voice complications. Various approaches for subjective and objective evaluations have been suggested in the literature. The subjective approach strongly depends on the experience and area of expertise of a clinician, and human error cannot be neglected. On the other hand, the objective or automatic approach is noninvasive. Automatic developed systems can provide complementary information that may be helpful for a clinician in the early screening of a voice disorder. At the same time, automatic systems can be deployed in remote areas where a general practitioner can use them and may refer the patient to a specialist to avoid complications that may be life threatening. Many automatic systems for disorder detection have been developed by applying different types of conventional speech features such as the linear prediction coefficients, linear prediction cepstral coefficients, and Mel-frequency cepstral coefficients (MFCCs). This study aims to ascertain whether conventional speech features detect voice pathology reliably, and whether they can be correlated with voice quality. To investigate this, an automatic detection system based on MFCC was developed, and three different voice disorder databases were used in this study. The experimental results suggest that the accuracy of the MFCC-based system varies from database to database. The detection rate for the intra-database ranges from 72% to 95%, and that for the inter-database is from 47% to 82%. The results conclude that conventional speech features are not correlated with voice, and hence are not reliable in pathology detection. Copyright © 2017 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

Pollution Detection Devices

NASA Technical Reports Server (NTRS)

1980-01-01

Barringer Research, Inc.'s COSPEC IVB (correlation spectrometer) can sense from a considerable distance emissions from a volcanic eruption. Remote sensor is capable of measuring sulfur dioxide and nitrogen dioxide in the atmosphere. An associated product, GASPEC, a compression of Non-dispersive Gas Filter Spectrometer, is an infrared/ultraviolet gas analyzer which can be used as either a ground based detector or in aircraft/spacecraft applications. Extremely sensitive, it is useful in air pollution investigations for detecting a variety of trace elements, vapors, which exist in the atmosphere in small amounts.

Chromatic dispersion estimation based on heterodyne detection for coherent optical communication systems

NASA Astrophysics Data System (ADS)

Li, Yong; Yang, Aiying; Guo, Peng; Qiao, Yaojun; Lu, Yueming

2018-01-01

We propose an accurate and nondata-aided chromatic dispersion (CD) estimation method involving the use of the cross-correlation function of two heterodyne detection signals for coherent optical communication systems. Simulations are implemented to verify the feasibility of the proposed method for 28-GBaud coherent systems with different modulation formats. The results show that the proposed method has high accuracy for measuring CD and has good robustness against laser phase noise, amplified spontaneous emission noise, and nonlinear impairments.

[Relationship between alcohol dependence and new detected hypertension in adult residents of Xuzhou city].

PubMed

Dong, Zongmei; Lou, Pei'an; Zhang, Pan; Chen, Peipei; Qiao, Cheng; Li, Ting

2015-12-01

To observe the relationship between alcohol dependence and new detected hypertension in adult residents of Xuzhou city. Participants were sampled by stratified multi-stage randomly cluster sampling method from February 2013 to June 2013 among permanent residents aged 18 and more in Xuzhou city. The alcohol dependence was defined with Michigan Alcoholism Screening Test (MAST). Other information was obtained by questionnaire. Spearman correlation analysis and multivariate logistic regression analysis were performed to identify the relationship between alcohol dependence and new detected hypertension. The alcohol dependence rate was 11.56% on the whole cohort (n=36 157), and 22.02%(3 854/17 501) for male and 1.74%(324/18 656) for female(P<0.01). The new detected hypertension rate was 9.46%(3 422/36 157) in the whole cohort. The new detected hypertension rate increased in proportion with the severity of alcohol dependence (P<0.01). Spearman correlation analysis showed that alcohol dependence was positively correlated with systemic blood pressure(r=0.071, P<0.01) and diastolic blood pressure (r=0.077, P<0.01). After adjusting for gender, age, marital status, body mass index, smoking status, physical activity level, educational level, income level and region, multivariate logistic regression analysis showed that alcohol dependence was an independent risk factor for hypertension (low alcohol dependence: OR=1.44, 95%CI 1.14-1.81, P<0.01; light alcohol dependence: OR=1.35, 95%CI 1.11-1.64, P<0.01; medium alcohol dependence: OR=1.83, 95%CI 1.40-2.41, P<0.01). The alcohol dependence is an independent risk factor for new detected hypertension in adult residents of Xuzhou city. Intensive hypertension prevention and treatment strategies should be performed on this population based on our results.

Analogous detection of circulating tumor cells using the AccuCyte® -CyteFinder® system and ISET system in patients with locally advanced and metastatic prostate cancer.

PubMed

van der Toom, Emma E; Groot, Vincent P; Glavaris, Stephanie A; Gemenetzis, Georgios; Chalfin, Heather J; Wood, Laura D; Wolfgang, Christopher L; de la Rosette, Jean J M C H; de Reijke, Theo M; Pienta, Kenneth J

2018-03-01

Circulating tumor cells (CTCs) can provide important information on patient's prognosis and treatment efficacy. Currently, a plethora of methods is available for the detection of these rare cells. We compared the outcomes of two of those methods to enumerate and characterize CTCs in patients with locally advanced and metastatic prostate cancer (PCa). First, the selection-free AccuCyte ® - CyteFinder ® system (RareCyte ® , Inc., Seattle, WA) and second, the ISET system (Rarecells Diagnostics, France), a CTC detection method based on cell size-exclusion. Peripheral blood samples were obtained from 15 patients with metastatic PCa and processed in parallel, using both methods according to manufacturer's protocol. CTCs were identified by immunofluorescence, using commercially available antibodies to pancytokeratin (PanCK), EpCAM, CD45/CD66b/CD34/CD11b/CD14 (AccuCyte ® - CyteFinder ® system), and pancytokeratin, vimentin (Vim) and CD45 (ISET system). The median CTC count was 5 CTCs/7.5 mL (range, 0-20) for the AccuCyte ® - CyteFinder ® system and 37 CTCs/7.5 mL (range, 8-139) for the ISET system (P < 0.001). Total CTC counts obtained for the two methods were correlated (r = 0.750, P = 0.001). When separating the total CTC count obtained with the ISET system in PanCK+/Vim- and PanCK+/Vim+ CTCs, the total CTC count obtained with the AccuCyte ® - CyteFinder ® system was moderately correlated with the PanCK+/Vim- CTCs, and strongly correlated with the PanCK+/Vim+ CTCs (r = 0.700, P = 0.004 and r = 0.810, P < 0.001, respectively). Our results highlight significant disparities in the enumeration and phenotype of CTCs detected by both techniques. Although the median amount of CTCs/7.5 mL differed significantly, total CTC counts of both methods were strongly correlated. For future studies, a more uniform approach to the isolation and definition of CTCs based on immunofluorescent stains is needed to provide reproducible results that can be correlated with clinical outcomes. © 2017 Wiley Periodicals, Inc.

Anomaly detection of flight routes through optimal waypoint

NASA Astrophysics Data System (ADS)

Pusadan, M. Y.; Buliali, J. L.; Ginardi, R. V. H.

2017-01-01

Deciding factor of flight, one of them is the flight route. Flight route determined by coordinate (latitude and longitude). flight routed is determined by its coordinates (latitude and longitude) as defined is waypoint. anomaly occurs, if the aircraft is flying outside the specified waypoint area. In the case of flight data, anomalies occur by identifying problems of the flight route based on data ADS-B. This study has an aim of to determine the optimal waypoints of the flight route. The proposed methods: i) Agglomerative Hierarchical Clustering (AHC) in several segments based on range area coordinates (latitude and longitude) in every waypoint; ii) The coefficient cophenetics correlation (c) to determine the correlation between the members in each cluster; iii) cubic spline interpolation as a graphic representation of the has connected between the coordinates on every waypoint; and iv). Euclidean distance to measure distances between waypoints with 2 centroid result of clustering AHC. The experiment results are value of coefficient cophenetics correlation (c): 0,691≤ c ≤ 0974, five segments the generated of the range area waypoint coordinates, and the shortest and longest distance between the centroid with waypoint are 0.46 and 2.18. Thus, concluded that the shortest distance is used as the reference coordinates of optimal waypoint, and farthest distance can be indicated potentially detected anomaly.

Major herbicides in ground water: Results from the National Water-Quality Assessment

USGS Publications Warehouse

Barbash, J.E.; Thelin, G.P.; Kolpin, D.W.; Gilliom, R.J.

2001-01-01

To improve understanding of the factors affecting pesticide occurrence in ground water, patterns of detection were examined for selected herbicides, based primarily on results from the National Water-Quality Assessment (NAWQA) program. The NAWQA data were derived from 2227 sites (wells and springs) sampled in 20 major hydrologic basins across the USA from 1993 to 1995. Results are presented for six high-use herbicides - atrazine (2-chloro-4-ethylamino-6-iso-propylamino-s-triazine), cyanazine (2-[4-chloro-6-ethylamino-l,3,5-triazin-2-yl]amino]-2-methylpropionitrile), simazine (2-chloro-4,6-bis[ethylamino]-s-triazine), alachlor (2-chloro-N-[2,6-diethylphenyl]-N-[methoxymethyl]acetamide), acetochlor (2-chloro-N-[ethoxymethyl]. N-[2-ethyl-6-methylphenyl]acetamide), and metolachlor (2-chloro-N-[2-ethyl-6-methylphenyl]-N-[2-methoxy-l- methylethyl]acetamide) - as well as for prometon (2,4-bis[isopropylamino]-6-methoxy-s-triazine), a nonagricultural herbicide detected frequently during the study. Concentrations were <1 ??g L-1 at 98% of the sites with detections, but exceeded drinking-water criteria (for atrazine) at two sites. In urban areas, frequencies of detection (at or above 0.01 ??g L-1) of atrazine, cyanazine, simazine, alachlor, and metolachlor in shallow ground water were positively correlated with their nonagricultural use nationwide (P < 0.05). Among different agricultural areas, frequencies of detection were positively correlated with nearby agricultural use for atrazine, cyanazine, alachlor, and metolachlor, but not simazine. Multivariate analysis demonstrated that for these five herbicides, frequencies of detection beneath agricultural areas were positively correlated with their agricultural use and persistence in aerobic soil. Acetochlor, an agricultural herbicide first registered in 1994 for use in the USA, was detected in shallow ground water by 1995, consistent with previous field-scale studies indicating that some pesticides may be detected in ground water within 1 yr following application. The NAWQA results agreed closely with those from other multistate studies with similar designs.

Long-Term Structural Health Monitoring System for a High-Speed Railway Bridge Structure.

PubMed

Ding, You-Liang; Wang, Gao-Xin; Sun, Peng; Wu, Lai-Yi; Yue, Qing

2015-01-01

Nanjing Dashengguan Bridge, which serves as the shared corridor crossing Yangtze River for both Beijing-Shanghai high-speed railway and Shanghai-Wuhan-Chengdu railway, is the first 6-track high-speed railway bridge with the longest span throughout the world. In order to ensure safety and detect the performance deterioration during the long-time service of the bridge, a Structural Health Monitoring (SHM) system has been implemented on this bridge by the application of modern techniques in sensing, testing, computing, and network communication. The SHM system includes various sensors as well as corresponding data acquisition and transmission equipment for automatic data collection. Furthermore, an evaluation system of structural safety has been developed for the real-time condition assessment of this bridge. The mathematical correlation models describing the overall structural behavior of the bridge can be obtained with the support of the health monitoring system, which includes cross-correlation models for accelerations, correlation models between temperature and static strains of steel truss arch, and correlation models between temperature and longitudinal displacements of piers. Some evaluation results using the mean value control chart based on mathematical correlation models are presented in this paper to show the effectiveness of this SHM system in detecting the bridge's abnormal behaviors under the varying environmental conditions such as high-speed trains and environmental temperature.

Automated measurement and classification of pulmonary blood-flow velocity patterns using phase-contrast MRI and correlation analysis.

PubMed

van Amerom, Joshua F P; Kellenberger, Christian J; Yoo, Shi-Joon; Macgowan, Christopher K

2009-01-01

An automated method was evaluated to detect blood flow in small pulmonary arteries and classify each as artery or vein, based on a temporal correlation analysis of their blood-flow velocity patterns. The method was evaluated using velocity-sensitive phase-contrast magnetic resonance data collected in vitro with a pulsatile flow phantom and in vivo in 11 human volunteers. The accuracy of the method was validated in vitro, which showed relative velocity errors of 12% at low spatial resolution (four voxels per diameter), but was reduced to 5% at increased spatial resolution (16 voxels per diameter). The performance of the method was evaluated in vivo according to its reproducibility and agreement with manual velocity measurements by an experienced radiologist. In all volunteers, the correlation analysis was able to detect and segment peripheral pulmonary vessels and distinguish arterial from venous velocity patterns. The intrasubject variability of repeated measurements was approximately 10% of peak velocity, or 2.8 cm/s root-mean-variance, demonstrating the high reproducibility of the method. Excellent agreement was obtained between the correlation analysis and radiologist measurements of pulmonary velocities, with a correlation of R2=0.98 (P<.001) and a slope of 0.99+/-0.01.

Signal Detection Theory as a Tool for Successful Student Selection

ERIC Educational Resources Information Center

van Ooijen-van der Linden, Linda; van der Smagt, Maarten J.; Woertman, Liesbeth; te Pas, Susan F.

2017-01-01

Prediction accuracy of academic achievement for admission purposes requires adequate "sensitivity" and "specificity" of admission tools, yet the available information on the validity and predictive power of admission tools is largely based on studies using correlational and regression statistics. The goal of this study was to…

Detection of gear cracks in a complex gearbox of wind turbines using supervised bounded component analysis of vibration signals collected from multi-channel sensors

NASA Astrophysics Data System (ADS)

Li, Zhixiong; Yan, Xinping; Wang, Xuping; Peng, Zhongxiao

2016-06-01

In the complex gear transmission systems, in wind turbines a crack is one of the most common failure modes and can be fatal to the wind turbine power systems. A single sensor may suffer with issues relating to its installation position and direction, resulting in the collection of weak dynamic responses of the cracked gear. A multi-channel sensor system is hence applied in the signal acquisition and the blind source separation (BSS) technologies are employed to optimally process the information collected from multiple sensors. However, literature review finds that most of the BSS based fault detectors did not address the dependence/correlation between different moving components in the gear systems; particularly, the popular used independent component analysis (ICA) assumes mutual independence of different vibration sources. The fault detection performance may be significantly influenced by the dependence/correlation between vibration sources. In order to address this issue, this paper presents a new method based on the supervised order tracking bounded component analysis (SOTBCA) for gear crack detection in wind turbines. The bounded component analysis (BCA) is a state of art technology for dependent source separation and is applied limitedly to communication signals. To make it applicable for vibration analysis, in this work, the order tracking has been appropriately incorporated into the BCA framework to eliminate the noise and disturbance signal components. Then an autoregressive (AR) model built with prior knowledge about the crack fault is employed to supervise the reconstruction of the crack vibration source signature. The SOTBCA only outputs one source signal that has the closest distance with the AR model. Owing to the dependence tolerance ability of the BCA framework, interfering vibration sources that are dependent/correlated with the crack vibration source could be recognized by the SOTBCA, and hence, only useful fault information could be preserved in the reconstructed signal. The crack failure thus could be precisely identified by the cyclic spectral correlation analysis. A series of numerical simulations and experimental tests have been conducted to illustrate the advantages of the proposed SOTBCA method for fatigue crack detection. Comparisons to three representative techniques, i.e. Erdogan's BCA (E-BCA), joint approximate diagonalization of eigen-matrices (JADE), and FastICA, have demonstrated the effectiveness of the SOTBCA. Hence the proposed approach is suitable for accurate gear crack detection in practical applications.

Hierarchical multivariate covariance analysis of metabolic connectivity.

PubMed

Carbonell, Felix; Charil, Arnaud; Zijdenbos, Alex P; Evans, Alan C; Bedell, Barry J

2014-12-01

Conventional brain connectivity analysis is typically based on the assessment of interregional correlations. Given that correlation coefficients are derived from both covariance and variance, group differences in covariance may be obscured by differences in the variance terms. To facilitate a comprehensive assessment of connectivity, we propose a unified statistical framework that interrogates the individual terms of the correlation coefficient. We have evaluated the utility of this method for metabolic connectivity analysis using [18F]2-fluoro-2-deoxyglucose (FDG) positron emission tomography (PET) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. As an illustrative example of the utility of this approach, we examined metabolic connectivity in angular gyrus and precuneus seed regions of mild cognitive impairment (MCI) subjects with low and high β-amyloid burdens. This new multivariate method allowed us to identify alterations in the metabolic connectome, which would not have been detected using classic seed-based correlation analysis. Ultimately, this novel approach should be extensible to brain network analysis and broadly applicable to other imaging modalities, such as functional magnetic resonance imaging (MRI).

Detection of defects in laser welding of AZ31B magnesium alloy in zero-gap lap joint configuration by a real-time spectroscopic analysis

NASA Astrophysics Data System (ADS)

Harooni, Masoud; Carlson, Blair; Kovacevic, Radovan

2014-05-01

The effect of surface oxide layer existing at the lap-joint faying surface of magnesium sheets is investigated on the keyhole dynamics of the weld pool and weld bead qualities. It is observed that by removing the oxide layer from the faying surface of the lap joint, a high quality weld can be achieved in the laser welding process. However, the presence of an oxide layer deteriorates the quality of the weld by forming pores at the interface of the two overlapped sheets. The purpose of this paper is to identify the correlation between the integrity of the weld and the interaction between the laser and material. A spectroscopy sensor was applied to detect the spectra emitted from a plasma plume during the laser welding of AZ31B magnesium alloy in a zero-gap lap joint configuration. The electron temperature was calculated by applying a Boltzmann plot method based on the detected spectra, and the correlation between the pore formation and the spectral signals was studied. The laser molten pool and the keyhole condition were monitored in real-time by a high speed charge-coupled device (CCD) camera. A green laser was used as an illumination source in order to detect the influence of the oxide layer on the dynamic behavior of the molten pool. Results revealed that the detected spectrum and weld defects had a meaningful correlation for real-time monitoring of the weld quality during laser welding of magnesium alloys.

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

Accuracy of a Radiological Evaluation Method for Thoracic and Lumbar Spinal Curvatures Using Spinous Processes.

PubMed

Marchetti, Bárbara V; Candotti, Cláudia T; Raupp, Eduardo G; Oliveira, Eduardo B C; Furlanetto, Tássia S; Loss, Jefferson F

The purpose of this study was to assess a radiographic method for spinal curvature evaluation in children, based on spinous processes, and identify its normality limits. The sample consisted of 90 radiographic examinations of the spines of children in the sagittal plane. Thoracic and lumbar curvatures were evaluated using angular (apex angle [AA]) and linear (sagittal arrow [SA]) measurements based on the spinous processes. The same curvatures were also evaluated using the Cobb angle (CA) method, which is considered the gold standard. For concurrent validity (AA vs CA), Pearson's product-moment correlation coefficient, root-mean-square error, Pitman- Morgan test, and Bland-Altman analysis were used. For reproducibility (AA, SA, and CA), the intraclass correlation coefficient, standard error of measurement, and minimal detectable change measurements were used. A significant correlation was found between CA and AA measurements, as was a low root-mean-square error. The mean difference between the measurements was 0° for thoracic and lumbar curvatures, and the mean standard deviations of the differences were ±5.9° and 6.9°, respectively. The intraclass correlation coefficients of AA and SA were similar to or higher than the gold standard (CA). The standard error of measurement and minimal detectable change of the AA were always lower than the CA. This study determined the concurrent validity, as well as intra- and interrater reproducibility, of the radiographic measurements of kyphosis and lordosis in children. Copyright © 2017. Published by Elsevier Inc.

Brain structural changes and their correlation with vascular disease in type 2 diabetes mellitus patients: a voxel-based morphometric study.

PubMed

Wang, Chunxia; Fu, Kailiang; Liu, Huaijun; Xing, Fei; Zhang, Songyun

2014-08-15

Voxel-based morphometry has been used in the study of alterations in brain structure in type 1 diabetes mellitus patients. These changes are associated with clinical indices. The age at onset, pathogenesis, and treatment of type 1 diabetes mellitus are different from those for type 2 diabetes mellitus. Thus, type 1 and type 2 diabetes mellitus may have different impacts on brain structure. Only a few studies of the alterations in brain structure in type 2 diabetes mellitus patients using voxel-based morphometry have been conducted, with inconsistent results. We detected subtle changes in the brain structure of 23 cases of type 2 diabetes mellitus, and demonstrated that there was no significant difference between the total volume of gray and white matter of the brain of type 2 diabetes mellitus patients and that in controls. Regional atrophy of gray matter mainly occurred in the right temporal and left occipital cortex, while regional atrophy of white matter involved the right temporal lobe and the right cerebellar hemisphere. The ankle-brachial index in patients with type 2 diabetes mellitus strongly correlated with the volume of brain regions in the default mode network. The ankle-brachial index, followed by the level of glycosylated hemoglobin, most strongly correlated with the volume of gray matter in the right temporal lobe. These data suggest that voxel-based morphometry could detect small structural changes in patients with type 2 diabetes mellitus. Early macrovascular atherosclerosis may play a crucial role in subtle brain atrophy in type 2 diabetes mellitus patients, with chronic hyperglycemia playing a lesser role.

Retinal and Optic Nerve Degeneration in Patients with Multiple Sclerosis Followed up for 5 Years.

PubMed

Garcia-Martin, Elena; Ara, Jose R; Martin, Jesus; Almarcegui, Carmen; Dolz, Isabel; Vilades, Elisa; Gil-Arribas, Laura; Fernandez, Francisco J; Polo, Vicente; Larrosa, Jose M; Pablo, Luis E; Satue, Maria

2017-05-01

To quantify retinal nerve fiber layer (RNFL) changes in patients with multiple sclerosis (MS) and healthy controls with a 5-year follow-up and to analyze correlations between disability progression and RNFL degeneration. Observational and longitudinal study. One hundred patients with relapsing-remitting MS and 50 healthy controls. All participants underwent a complete ophthalmic and electrophysiologic exploration and were re-evaluated annually for 5 years. Visual acuity (Snellen chart), color vision (Ishihara pseudoisochromatic plates), visual field examination, optical coherence tomography (OCT), scanning laser polarimetry (SLP), and visual evoked potentials. Expanded Disability Status Scale (EDSS) scores, disease duration, treatments, prior optic neuritis episodes, and quality of life (QOL; based on the 54-item Multiple Sclerosis Quality of Life Scale score). Optical coherence tomography (OCT) revealed changes in all RNFL thicknesses in both groups. In the MS group, changes were detected in average thickness and in the mean deviation using the GDx-VCC nerve fiber analyzer (Laser Diagnostic Technologies, San Diego, CA) and in the P100 latency of visual evoked potentials; no changes were detected in visual acuity, color vision, or visual fields. Optical coherence tomography showed greater differences in the inferior and temporal RNFL thicknesses in both groups. In MS patients only, OCT revealed a moderate correlation between the increase in EDSS and temporal and superior RNFL thinning. Temporal RNFL thinning based on OCT results was correlated moderately with decreased QOL. Multiple sclerosis patients exhibit a progressive axonal loss in the optic nerve fiber layer. Retinal nerve fiber layer thinning based on OCT results is a useful marker for assessing MS progression and correlates with increased disability and reduced QOL. Copyright © 2017 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

Fluorescence hyperspectral imaging technique for foreign substance detection on fresh-cut lettuce.

PubMed

Mo, Changyeun; Kim, Giyoung; Kim, Moon S; Lim, Jongguk; Cho, Hyunjeong; Barnaby, Jinyoung Yang; Cho, Byoung-Kwan

2017-09-01

Non-destructive methods based on fluorescence hyperspectral imaging (HSI) techniques were developed to detect worms on fresh-cut lettuce. The optimal wavebands for detecting the worms were investigated using the one-way ANOVA and correlation analyses. The worm detection imaging algorithms, RSI-I (492-626)/492 , provided a prediction accuracy of 99.0%. The fluorescence HSI techniques indicated that the spectral images with a pixel size of 1 × 1 mm had the best classification accuracy for worms. The overall results demonstrate that fluorescence HSI techniques have the potential to detect worms on fresh-cut lettuce. In the future, we will focus on developing a multi-spectral imaging system to detect foreign substances such as worms, slugs and earthworms on fresh-cut lettuce. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

A signal-based fault detection and classification method for heavy haul wagons

NASA Astrophysics Data System (ADS)

Li, Chunsheng; Luo, Shihui; Cole, Colin; Spiryagin, Maksym; Sun, Yanquan

2017-12-01

This paper proposes a signal-based fault detection and isolation (FDI) system for heavy haul wagons considering the special requirements of low cost and robustness. The sensor network of the proposed system consists of just two accelerometers mounted on the front left and rear right of the carbody. Seven fault indicators (FIs) are proposed based on the cross-correlation analyses of the sensor-collected acceleration signals. Bolster spring fault conditions are focused on in this paper, including two different levels (small faults and moderate faults) and two locations (faults in the left and right bolster springs of the first bogie). A fully detailed dynamic model of a typical 40t axle load heavy haul wagon is developed to evaluate the deterioration of dynamic behaviour under proposed fault conditions and demonstrate the detectability of the proposed FDI method. Even though the fault conditions considered in this paper did not deteriorate the wagon dynamic behaviour dramatically, the proposed FIs show great sensitivity to the bolster spring faults. The most effective and efficient FIs are chosen for fault detection and classification. Analysis results indicate that it is possible to detect changes in bolster stiffness of ±25% and identify the fault location.

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), 91.4% (V8-V9), and 100% (V4R-V9, V4R-V8, V3R-V9, V3R-V8), which is reasonable considering the low prevalence of lead swaps in clinical environment. Inter-lead correlation analysis is able to provide robust detection of cable reversals in standard 12-lead ECG, effectively extended to 16-lead ECG applications that have not previously been addressed. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Hard Fusion Based Spectrum Sensing over Mobile Fading Channels in Cognitive Vehicular Networks

PubMed Central

Hao, Li; Ni, Dadong; Tran, Quang Thanh

2018-01-01

An explosive growth in vehicular wireless applications gives rise to spectrum resource starvation. Cognitive radio has been used in vehicular networks to mitigate the impending spectrum starvation problem by allowing vehicles to fully exploit spectrum opportunities unoccupied by licensed users. Efficient and effective detection of licensed user is a critical issue to realize cognitive radio applications. However, spectrum sensing in vehicular environments is a very challenging task due to vehicle mobility. For instance, vehicle mobility has a large effect on the wireless channel, thereby impacting the detection performance of spectrum sensing. Thus, gargantuan efforts have been made in order to analyze the fading properties of mobile radio channel in vehicular environments. Indeed, numerous studies have demonstrated that the wireless channel in vehicular environments can be characterized by a temporally correlated Rayleigh fading. In this paper, we focus on energy detection for spectrum sensing and a counting rule for cooperative sensing based on Neyman-Pearson criteria. Further, we go into the effect of the sensing and reporting channel conditions on the sensing performance under the temporally correlated Rayleigh channel. For local and cooperative sensing, we derive some alternative expressions for the average probability of misdetection. The pertinent numerical and simulating results are provided to further validate our theoretical analyses under a variety of scenarios. PMID:29415452

A Doppler Transient Model Based on the Laplace Wavelet and Spectrum Correlation Assessment for Locomotive Bearing Fault Diagnosis

PubMed Central

Shen, Changqing; Liu, Fang; Wang, Dong; Zhang, Ao; Kong, Fanrang; Tse, Peter W.

2013-01-01

The condition of locomotive bearings, which are essential components in trains, is crucial to train safety. The Doppler effect significantly distorts acoustic signals during high movement speeds, substantially increasing the difficulty of monitoring locomotive bearings online. In this study, a new Doppler transient model based on the acoustic theory and the Laplace wavelet is presented for the identification of fault-related impact intervals embedded in acoustic signals. An envelope spectrum correlation assessment is conducted between the transient model and the real fault signal in the frequency domain to optimize the model parameters. The proposed method can identify the parameters used for simulated transients (periods in simulated transients) from acoustic signals. Thus, localized bearing faults can be detected successfully based on identified parameters, particularly period intervals. The performance of the proposed method is tested on a simulated signal suffering from the Doppler effect. Besides, the proposed method is used to analyze real acoustic signals of locomotive bearings with inner race and outer race faults, respectively. The results confirm that the periods between the transients, which represent locomotive bearing fault characteristics, can be detected successfully. PMID:24253191

A Doppler transient model based on the laplace wavelet and spectrum correlation assessment for locomotive bearing fault diagnosis.

PubMed

Shen, Changqing; Liu, Fang; Wang, Dong; Zhang, Ao; Kong, Fanrang; Tse, Peter W

2013-11-18

The condition of locomotive bearings, which are essential components in trains, is crucial to train safety. The Doppler effect significantly distorts acoustic signals during high movement speeds, substantially increasing the difficulty of monitoring locomotive bearings online. In this study, a new Doppler transient model based on the acoustic theory and the Laplace wavelet is presented for the identification of fault-related impact intervals embedded in acoustic signals. An envelope spectrum correlation assessment is conducted between the transient model and the real fault signal in the frequency domain to optimize the model parameters. The proposed method can identify the parameters used for simulated transients (periods in simulated transients) from acoustic signals. Thus, localized bearing faults can be detected successfully based on identified parameters, particularly period intervals. The performance of the proposed method is tested on a simulated signal suffering from the Doppler effect. Besides, the proposed method is used to analyze real acoustic signals of locomotive bearings with inner race and outer race faults, respectively. The results confirm that the periods between the transients, which represent locomotive bearing fault characteristics, can be detected successfully.

Chondromalacia patellae: diagnosis with MR imaging.

PubMed

McCauley, T R; Kier, R; Lynch, K J; Jokl, P

1992-01-01

Most previous studies of MR imaging for detection of chondromalacia have used T1-weighted images. We correlated findings on axial MR images of the knee with arthroscopic findings to determine MR findings of chondromalacia patellae on T2-weighted and proton density-weighted images. The study population included 52 patients who had MR examination of the knee with a 1.5-T unit and subsequent arthroscopy, which documented chondromalacia patellae in 29 patients and normal cartilage in 23. The patellar cartilage was assessed retrospectively for MR signal and contour characteristics. MR diagnosis based on the criteria of focal signal or focal contour abnormality on either the T2-weighted or proton density-weighted images yielded the highest correlation with the arthroscopic diagnosis of chondromalacia. When these criteria were used, patients with chondromalacia were detected with 86% sensitivity, 74% specificity, and 81% accuracy. MR diagnosis based on T2-weighted images alone was more sensitive and accurate than was diagnosis based on proton density-weighted images alone. In conclusion, most patients with chondromalacia patellae have focal signal or focal contour defects in the patellar cartilage on T2-weighted MR images. These findings are absent in most patients with arthroscopically normal cartilage.

Ghost detection and removal based on super-pixel grouping in exposure fusion

NASA Astrophysics Data System (ADS)

Jiang, Shenyu; Xu, Zhihai; Li, Qi; Chen, Yueting; Feng, Huajun

2014-09-01

A novel multi-exposure images fusion method for dynamic scenes is proposed. The commonly used techniques for high dynamic range (HDR) imaging are based on the combination of multiple differently exposed images of the same scene. The drawback of these methods is that ghosting artifacts will be introduced into the final HDR image if the scene is not static. In this paper, a super-pixel grouping based method is proposed to detect the ghost in the image sequences. We introduce the zero mean normalized cross correlation (ZNCC) as a measure of similarity between a given exposure image and the reference. The calculation of ZNCC is implemented in super-pixel level, and the super-pixels which have low correlation with the reference are excluded by adjusting the weight maps for fusion. Without any prior information on camera response function or exposure settings, the proposed method generates low dynamic range (LDR) images which can be shown on conventional display devices directly with details preserving and ghost effects reduced. Experimental results show that the proposed method generates high quality images which have less ghost artifacts and provide a better visual quality than previous approaches.

Psychophysical Models for Signal Detection with Time Varying Uncertainty. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Gai, E.

1975-01-01

Psychophysical models for the behavior of the human operator in detection tasks which include change in detectability, correlation between observations and deferred decisions are developed. Classical Signal Detection Theory (SDT) is discussed and its emphasis on the sensory processes is contrasted to decision strategies. The analysis of decision strategies utilizes detection tasks with time varying signal strength. The classical theory is modified to include such tasks and several optimal decision strategies are explored. Two methods of classifying strategies are suggested. The first method is similar to the analysis of ROC curves, while the second is based on the relation between the criterion level (CL) and the detectability. Experiments to verify the analysis of tasks with changes of signal strength are designed. The results show that subjects are aware of changes in detectability and tend to use strategies that involve changes in the CL's.

Unsupervised frequency-recognition method of SSVEPs using a filter bank implementation of binary subband CCA.

PubMed

Rabiul Islam, Md; Khademul Islam Molla, Md; Nakanishi, Masaki; Tanaka, Toshihisa

2017-04-01

Recently developed effective methods for detection commands of steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) that need calibration for visual stimuli, which cause more time and fatigue prior to the use, as the number of commands increases. This paper develops a novel unsupervised method based on canonical correlation analysis (CCA) for accurate detection of stimulus frequency. A novel unsupervised technique termed as binary subband CCA (BsCCA) is implemented in a multiband approach to enhance the frequency recognition performance of SSVEP. In BsCCA, two subbands are used and a CCA-based correlation coefficient is computed for the individual subbands. In addition, a reduced set of artificial reference signals is used to calculate CCA for the second subband. The analyzing SSVEP is decomposed into multiple subband and the BsCCA is implemented for each one. Then, the overall recognition score is determined by a weighted sum of the canonical correlation coefficients obtained from each band. A 12-class SSVEP dataset (frequency range: 9.25-14.75 Hz with an interval of 0.5 Hz) for ten healthy subjects are used to evaluate the performance of the proposed method. The results suggest that BsCCA significantly improves the performance of SSVEP-based BCI compared to the state-of-the-art methods. The proposed method is an unsupervised approach with averaged information transfer rate (ITR) of 77.04 bits min -1 across 10 subjects. The maximum individual ITR is 107.55 bits min -1 for 12-class SSVEP dataset, whereas, the ITR of 69.29 and 69.44 bits min -1 are achieved with CCA and NCCA respectively. The statistical test shows that the proposed unsupervised method significantly improves the performance of the SSVEP-based BCI. It can be usable in real world applications.

Filter bank canonical correlation analysis for implementing a high-speed SSVEP-based brain-computer interface

NASA Astrophysics Data System (ADS)

Chen, Xiaogang; Wang, Yijun; Gao, Shangkai; Jung, Tzyy-Ping; Gao, Xiaorong

2015-08-01

Objective. Recently, canonical correlation analysis (CCA) has been widely used in steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs) due to its high efficiency, robustness, and simple implementation. However, a method with which to make use of harmonic SSVEP components to enhance the CCA-based frequency detection has not been well established. Approach. This study proposed a filter bank canonical correlation analysis (FBCCA) method to incorporate fundamental and harmonic frequency components to improve the detection of SSVEPs. A 40-target BCI speller based on frequency coding (frequency range: 8-15.8 Hz, frequency interval: 0.2 Hz) was used for performance evaluation. To optimize the filter bank design, three methods (M1: sub-bands with equally spaced bandwidths; M2: sub-bands corresponding to individual harmonic frequency bands; M3: sub-bands covering multiple harmonic frequency bands) were proposed for comparison. Classification accuracy and information transfer rate (ITR) of the three FBCCA methods and the standard CCA method were estimated using an offline dataset from 12 subjects. Furthermore, an online BCI speller adopting the optimal FBCCA method was tested with a group of 10 subjects. Main results. The FBCCA methods significantly outperformed the standard CCA method. The method M3 achieved the highest classification performance. At a spelling rate of ˜33.3 characters/min, the online BCI speller obtained an average ITR of 151.18 ± 20.34 bits min-1. Significance. By incorporating the fundamental and harmonic SSVEP components in target identification, the proposed FBCCA method significantly improves the performance of the SSVEP-based BCI, and thereby facilitates its practical applications such as high-speed spelling.

Wilkinson Microwave Anisotropy Probe (WMAP) First Year Observations: TE Polarization

NASA Technical Reports Server (NTRS)

Kogut, A.; Spergel, D. N.; Barnes, C.; Bennett, C. L.; Halpern, M.; Hinshaw, G.; Jarosik, N.; Limon, M.; Meyer, S. S.; Page, L.;

[A research in speech endpoint detection based on boxes-coupling generalization dimension].

PubMed

Wang, Zimei; Yang, Cuirong; Wu, Wei; Fan, Yingle

2008-06-01

In this paper, a new calculating method of generalized dimension, based on boxes-coupling principle, is proposed to overcome the edge effects and to improve the capability of the speech endpoint detection which is based on the original calculating method of generalized dimension. This new method has been applied to speech endpoint detection. Firstly, the length of overlapping border was determined, and through calculating the generalized dimension by covering the speech signal with overlapped boxes, three-dimension feature vectors including the box dimension, the information dimension and the correlation dimension were obtained. Secondly, in the light of the relation between feature distance and similarity degree, feature extraction was conducted by use of common distance. Lastly, bi-threshold method was used to classify the speech signals. The results of experiment indicated that, by comparison with the original generalized dimension (OGD) and the spectral entropy (SE) algorithm, the proposed method is more robust and effective for detecting the speech signals which contain different kinds of noise in different signal noise ratio (SNR), especially in low SNR.

DOA Estimation for Underwater Wideband Weak Targets Based on Coherent Signal Subspace and Compressed Sensing.

PubMed

Li, Jun; Lin, Qiu-Hua; Kang, Chun-Yu; Wang, Kai; Yang, Xiu-Ting

2018-03-18

Direction of arrival (DOA) estimation is the basis for underwater target localization and tracking using towed line array sonar devices. A method of DOA estimation for underwater wideband weak targets based on coherent signal subspace (CSS) processing and compressed sensing (CS) theory is proposed. Under the CSS processing framework, wideband frequency focusing is accompanied by a two-sided correlation transformation, allowing the DOA of underwater wideband targets to be estimated based on the spatial sparsity of the targets and the compressed sensing reconstruction algorithm. Through analysis and processing of simulation data and marine trial data, it is shown that this method can accomplish the DOA estimation of underwater wideband weak targets. Results also show that this method can considerably improve the spatial spectrum of weak target signals, enhancing the ability to detect them. It can solve the problems of low directional resolution and unreliable weak-target detection in traditional beamforming technology. Compared with the conventional minimum variance distortionless response beamformers (MVDR), this method has many advantages, such as higher directional resolution, wider detection range, fewer required snapshots and more accurate detection for weak targets.

Multiple correlation analyses revealed complex relationship between DNA methylation and mRNA expression in human peripheral blood mononuclear cells.

PubMed

Xie, Fang-Fei; Deng, Fei-Yan; Wu, Long-Fei; Mo, Xing-Bo; Zhu, Hong; Wu, Jian; Guo, Yu-Fan; Zeng, Ke-Qin; Wang, Ming-Jun; Zhu, Xiao-Wei; Xia, Wei; Wang, Lan; He, Pei; Bing, Peng-Fei; Lu, Xin; Zhang, Yong-Hong; Lei, Shu-Feng

2018-01-01

DNA methylation is an important regulator on the mRNA expression. However, a genome-wide correlation pattern between DNA methylation and mRNA expression in human peripheral blood mononuclear cells (PBMCs) is largely unknown. The comprehensive relationship between mRNA and DNA methylation was explored by using four types of correlation analyses and a genome-wide methylation-mRNA expression quantitative trait locus (eQTL) analysis in PBMCs in 46 unrelated female subjects. An enrichment analysis was performed to detect biological function for the detected genes. Single pair correlation coefficient (r T1 ) between methylation level and mRNA is moderate (-0.63-0.62) in intensity, and the negative and positive correlations are nearly equal in quantity. Correlation analysis on each gene (T4) found 60.1% genes showed correlations between mRNA and gene-based methylation at P < 0.05 and more than 5.96% genes presented very strong correlation (R T4  > 0.8). Methylation sites have regulation effects on mRNA expression in eQTL analysis, with more often observations in region of transcription start site (TSS). The genes under significant methylation regulation both in correlation analysis and eQTL analysis tend to cluster to the categories (e.g., transcription, translation, regulation of transcription) that are essential for maintaining the basic life activities of cells. Our findings indicated that DNA methylation has predictive regulation effect on mRNA with a very complex pattern in PBMCs. The results increased our understanding on correlation of methylation and mRNA and also provided useful clues for future epigenetic studies in exploring biological and disease-related regulatory mechanisms in PBMC.

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.

Genetic Basis Underlying Correlations Among Growth Duration and Yield Traits Revealed by GWAS in Rice (Oryza sativa L.).

PubMed

Li, Fengmei; Xie, Jianyin; Zhu, Xiaoyang; Wang, Xueqiang; Zhao, Yan; Ma, Xiaoqian; Zhang, Zhanying; Rashid, Muhammad A R; Zhang, Zhifang; Zhi, Linran; Zhang, Shuyang; Li, Jinjie; Li, Zichao; Zhang, Hongliang

2018-01-01

Avoidance of disadvantageous genetic correlations among growth duration and yield traits is critical in developing crop varieties that efficiently use light and energy resources and produce high yields. To understand the genetic basis underlying the correlations among heading date and three major yield traits in rice, we investigated the four traits in a diverse and representative core collection of 266 cultivated rice accessions in both long-day and short-day environments, and conducted the genome-wide association study using 4.6 million single nucleotide polymorphisms (SNPs). There were clear positive correlation between heading date and grain number per panicle, and negative correlation between grain number per panicle and panicle number, as well as different degrees of correlations among other traits in different subspecies and environments. We detected 47 pleiotropic genes in 15 pleiotropic quantitative trait loci (pQTLs), 18 pleiotropic genes containing 37 pleiotropic SNPs in 8 pQTLs, 27 pQTLs with r 2 of linkage disequilibrium higher than 0.2, and 39 pairs of interactive genes from 8 metabolic pathways that may contribute to the above phenotypic correlations, but these genetic bases were different for correlations among different traits. Distributions of haplotypes revealed that selection for pleiotropic genes or interactive genes controlling different traits focused on genotypes with weak effect or on those balancing two traits that maximized production but sometimes their utilization strategies depend on the traits and environment. Detection of pQTLs and interactive genes and associated molecular markers will provide an ability to overcome disadvantageous correlations and to utilize the advantageous correlations among traits through marker-assisted selection in breeding.

Surface modification of alignment layer by ultraviolet irradiation to dramatically improve the detection limit of liquid-crystal-based immunoassay for the cancer biomarker CA125.

PubMed

Su, Hui-Wen; Lee, Mon-Juan; Lee, Wei

2015-05-01

Liquid crystal (LC)-based biosensing has attracted much attention in recent years. We focus on improving the detection limit of LC-based immunoassay techniques by surface modification of the surfactant alignment layer consisting of dimethyloctadecyl[3-(trimethoxysilyl)propyl]ammonium chloride (DMOAP). The cancer biomarker CA125 was detected with an array of anti-CA125 antibodies immobilized on the ultraviolet (UV)-modified DMOAP monolayer. Compared with a pristine counterpart, UV irradiation enhanced the binding affinity of the CA125 antibody and reproducibility of immunodetection in which a detection limit of 0.01 ng∕ml for the cancer biomarker CA125 was achieved. Additionally, the optical texture observed under a crossed polarized microscope was correlated with the analyte concentration. In a proof-of-concept experiment using CA125-spiked human serum as the analyte, specific binding between the CA125 antigen and the anti-CA125 antibody resulted in a distinct and concentration-dependent optical response despite the high background caused by nonspecific binding of other biomolecules in the human serum. Results from this study indicate that UVmodification of the alignment layer, as well as detection with LCs of large birefringence, contributes to the enhanced performance of the label-free LC-based immunodetection, which may be considered a promising alternative to conventional label-based methods.

Automated batch fiducial-less tilt-series alignment in Appion using Protomo.

PubMed

Noble, Alex J; Stagg, Scott M

2015-11-01

The field of electron tomography has benefited greatly from manual and semi-automated approaches to marker-based tilt-series alignment that have allowed for the structural determination of multitudes of in situ cellular structures as well as macromolecular structures of individual protein complexes. The emergence of complementary metal-oxide semiconductor detectors capable of detecting individual electrons has enabled the collection of low dose, high contrast images, opening the door for reliable correlation-based tilt-series alignment. Here we present a set of automated, correlation-based tilt-series alignment, contrast transfer function (CTF) correction, and reconstruction workflows for use in conjunction with the Appion/Leginon package that are primarily targeted at automating structure determination with cryogenic electron microscopy. Copyright © 2015 Elsevier Inc. All rights reserved.

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

Assessment of circulating copy number variant detection for cancer screening.

PubMed

Molparia, Bhuvan; Nichani, Eshaan; Torkamani, Ali

2017-01-01

Current high-sensitivity cancer screening methods, largely utilizing correlative biomarkers, suffer from false positive rates that lead to unnecessary medical procedures and debatable public health benefit overall. Detection of circulating tumor DNA (ctDNA), a causal biomarker, has the potential to revolutionize cancer screening. Thus far, the majority of ctDNA studies have focused on detection of tumor-specific point mutations after cancer diagnosis for the purpose of post-treatment surveillance. However, ctDNA point mutation detection methods developed to date likely lack either the scope or analytical sensitivity necessary to be useful for cancer screening, due to the low (<1%) ctDNA fraction derived from early stage tumors. On the other hand, tumor-derived copy number variant (CNV) detection is hypothetically a superior means of ctDNA-based cancer screening for many tumor types, given that, relative to point mutations, each individual tumor CNV contributes a much larger number of ctDNA fragments to the overall pool of circulating free DNA (cfDNA). A small number of studies have demonstrated the potential of ctDNA CNV-based screening in select cancer types. Here we perform an in silico assessment of the potential for ctDNA CNV-based cancer screening across many common cancers, and suggest ctDNA CNV detection shows promise as a broad cancer screening methodology.

A Tensor-Based Structural Damage Identification and Severity Assessment

PubMed Central

Anaissi, Ali; Makki Alamdari, Mehrisadat; Rakotoarivelo, Thierry; Khoa, Nguyen Lu Dang

2018-01-01

Early damage detection is critical for a large set of global ageing infrastructure. Structural Health Monitoring systems provide a sensor-based quantitative and objective approach to continuously monitor these structures, as opposed to traditional engineering visual inspection. Analysing these sensed data is one of the major Structural Health Monitoring (SHM) challenges. This paper presents a novel algorithm to detect and assess damage in structures such as bridges. This method applies tensor analysis for data fusion and feature extraction, and further uses one-class support vector machine on this feature to detect anomalies, i.e., structural damage. To evaluate this approach, we collected acceleration data from a sensor-based SHM system, which we deployed on a real bridge and on a laboratory specimen. The results show that our tensor method outperforms a state-of-the-art approach using the wavelet energy spectrum of the measured data. In the specimen case, our approach succeeded in detecting 92.5% of induced damage cases, as opposed to 61.1% for the wavelet-based approach. While our method was applied to bridges, its algorithm and computation can be used on other structures or sensor-data analysis problems, which involve large series of correlated data from multiple sensors. PMID:29301314

Infrared imaging based hyperventilation monitoring through respiration rate estimation

NASA Astrophysics Data System (ADS)

Basu, Anushree; Routray, Aurobinda; Mukherjee, Rashmi; Shit, Suprosanna

2016-07-01

A change in the skin temperature is used as an indicator of physical illness which can be detected through infrared thermography. Thermograms or thermal images can be used as an effective diagnostic tool for monitoring and diagnosis of various diseases. This paper describes an infrared thermography based approach for detecting hyperventilation caused due to stress and anxiety in human beings by computing their respiration rates. The work employs computer vision techniques for tracking the region of interest from thermal video to compute the breath rate. Experiments have been performed on 30 subjects. Corner feature extraction using Minimum Eigenvalue (Shi-Tomasi) algorithm and registration using Kanade Lucas-Tomasi algorithm has been used here. Thermal signature around the extracted region is detected and subsequently filtered through a band pass filter to compute the respiration profile of an individual. If the respiration profile shows unusual pattern and exceeds the threshold we conclude that the person is stressed and tending to hyperventilate. Results obtained are compared with standard contact based methods which have shown significant correlations. It is envisaged that the thermal image based approach not only will help in detecting hyperventilation but can assist in regular stress monitoring as it is non-invasive method.

Optofluidic devices with integrated solid-state nanopores

PubMed Central

Hawkins, Aaron R.; Schmidt, Holger

2016-01-01

This review (with 90 refs.) covers the state of the art in optofluidic devices with integrated solid-state nanopores for use in detection and sensing. Following an introduction into principles of optofluidics and solid-state nanopore technology, we discuss features of solid-state nanopore based assays using optofluidics. This includes the incorporation of solid-state nanopores into optofluidic platforms based on liquid-core anti-resonant reflecting optical waveguides (ARROWs), methods for their fabrication, aspects of single particle detection and particle manipulation. We then describe the new functionalities provided by solid-state nanopores integrated into optofluidic chips, in particular acting as smart gates for correlated electro-optical detection and discrimination of nanoparticles. This enables the identification of viruses and λ-DNA, particle trajectory simulations, enhancing sensitivity by tuning the shape of nanopores. The review concludes with a summary and an outlook. PMID:27046940

Spatial Analysis of Land Subsidence and Flood Pattern Based on DInSAR Method in Sentinel Sar Imagery and Weighting Method in Geo-Hazard Parameters Combination in North Jakarta Region

NASA Astrophysics Data System (ADS)

Prasetyo, Y.; Yuwono, B. D.; Ramadhanis, Z.

2018-02-01

The reclamation program carried out in most cities in North Jakarta is directly adjacent to the Jakarta Bay. Beside this program, the density of population and development center in North Jakarta office has increased the need for underground water excessively. As a result of these things, land subsidence in North Jakarta area is relatively high and so intense. The research methodology was developed based on the method of remote sensing and geographic information systems, expected to describe the spatial correlation between the land subsidence and flood phenomenon in North Jakarta. The DInSAR (Differential Interferometric Synthetic Aperture Radar) method with satellite image data Radar (SAR Sentinel 1A) for the years 2015 to 2016 acquisitions was used in this research. It is intended to obtain a pattern of land subsidence in North Jakarta and then combined with flood patterns. For the preparation of flood threat zoning pattern, this research has been modeling in spatial technique based on a weighted parameter of rainfall, elevation, flood zones and land use. In the final result, we have obtained a flood hazard zonation models then do the overlap against DInSAR processing results. As a result of the research, Geo-hazard modelling has a variety results as: 81% of flood threat zones consist of rural area, 12% consists of un-built areas and 7% consists of water areas. Furthermore, the correlation of land subsidence to flood risk zone is divided into three levels of suitability with 74% in high class, 22% in medium class and 4% in low class. For the result of spatial correlation area between land subsidence and flood risk zone are 77% detected in rural area, 17% detected in un-built area and 6% detected in a water area. Whereas the research product is the geo-hazard maps in North Jakarta as the basis of the spatial correlation analysis between the land subsidence and flooding phenomena.double point.

Quantum dots-based immunofluorescent imaging of stromal fibroblasts Caveolin-1 and light chain 3B expression and identification of their clinical significance in human gastric cancer.

PubMed

He, Yuyu; Zhao, Xianda; Gao, Jun; Fan, Lifang; Yang, Guifang; Cho, William Chi-Shing; Chen, Honglei

2012-10-24

Caveolin-1 (Cav-1) expression deficiency and autophagy in tumor stromal fibroblasts (hereafter fibroblasts) are involved in tumor proliferation and progression, particularly in breast and prostate cancer. The aim of this study was to detect the expression of fibroblastic Cav-1 and LC3B, markers of autophagy, in gastric cancer (GC) and to analyze their clinical significances. Furthermore, because Epstein-Barr virus (EBV)-associated GC (EBVaGC) is a unique subtype of GC; we compared the differential expression of fibroblastic Cav-1 and LC3B in EBVaGC and non-EBVaGC. Quantum dots (QDs)-based immunofluorescence histochemistry was used to examine the expression of fibroblastic Cav-1 and LC3B in 118 cases of GC with adequate stroma. QDs-based double immunofluorescence labeling was performed to detect the coexpression of Cav-1 and LC3B proteins. EBV-encoded small RNA was detected by QDs-based fluorescence in situ hybridization to identify EBVaGC. Multivariate analysis indicated that low fibroblastic Cav-1 level was an independent prognosticator (p = 0.029) that predicted poorer survival of GC patients. Positive fibroblastic LC3B was correlated with lower invasion (p = 0.032) and was positively associated with Cav-1 expression (r = 0.432, p < 0.001). EBV infection did not affect fibroblastic Cav-1 and LC3B expression. In conclusion, positive fibroblastic LC3B correlates with lower invasion, and low expression of fibroblastic Cav-1 is a novel predictor of poor GC prognosis.

Passive micromixer for luminol-peroxide chemiluminescence detection.

PubMed

Lok, Khoi Seng; Kwok, Yien Chian; Nguyen, Nam-Trung

2011-06-21

This paper reports a microchip with an integrated passive micromixer based on chaotic advection. The micromixer with staggered herringbone structures was used for luminol-peroxide chemiluminescence detection. The micromixer was examined to assess its suitability for chemiluminescence reaction. The relationship between the flow rate and the location of maximum chemiluminescence intensity was investigated. The light intensity was detected using an optical fiber attached along the mixing channel and a photon detector. A linear correlation between chemiluminescence intensity and the concentration of cobalt(ii) ions or hydrogen peroxide was observed. This microchip has a potential application in environmental monitoring for industries involved in heavy metals and in medical diagnostics.

Detecting Earthquakes over a Seismic Network using Single-Station Similarity Measures

NASA Astrophysics Data System (ADS)

Bergen, Karianne J.; Beroza, Gregory C.

2018-03-01

New blind waveform-similarity-based detection methods, such as Fingerprint and Similarity Thresholding (FAST), have shown promise for detecting weak signals in long-duration, continuous waveform data. While blind detectors are capable of identifying similar or repeating waveforms without templates, they can also be susceptible to false detections due to local correlated noise. In this work, we present a set of three new methods that allow us to extend single-station similarity-based detection over a seismic network; event-pair extraction, pairwise pseudo-association, and event resolution complete a post-processing pipeline that combines single-station similarity measures (e.g. FAST sparse similarity matrix) from each station in a network into a list of candidate events. The core technique, pairwise pseudo-association, leverages the pairwise structure of event detections in its network detection model, which allows it to identify events observed at multiple stations in the network without modeling the expected move-out. Though our approach is general, we apply it to extend FAST over a sparse seismic network. We demonstrate that our network-based extension of FAST is both sensitive and maintains a low false detection rate. As a test case, we apply our approach to two weeks of continuous waveform data from five stations during the foreshock sequence prior to the 2014 Mw 8.2 Iquique earthquake. Our method identifies nearly five times as many events as the local seismicity catalog (including 95% of the catalog events), and less than 1% of these candidate events are false detections.

Status and understanding of groundwater quality in the San Diego Drainages Hydrogeologic Province, 2004: California GAMA Priority Basin Project

USGS Publications Warehouse

Wright, Michael T.; Belitz, Kenneth

2011-01-01

Groundwater quality in the approximately 3,900-square-mile (mi2) San Diego Drainages Hydrogeologic Province (hereinafter San Diego) study unit was investigated from May through July 2004 as part of the Priority Basin Project of the Groundwater Ambient Monitoring and Assessment (GAMA) Program. The study unit is located in southwestern California in the counties of San Diego, Riverside, and Orange. The GAMA Priority Basin Project is being conducted by the California State Water Resources Control Board in collaboration with the U.S. Geological Survey (USGS) and the Lawrence Livermore National Laboratory. The GAMA San Diego study was designed to provide a statistically robust assessment of untreated-groundwater quality within the primary aquifer systems. The assessment is based on water-quality and ancillary data collected by the USGS from 58 wells in 2004 and water-quality data from the California Department of Public Health (CDPH) database. The primary aquifer systems (hereinafter referred to as the primary aquifers) were defined by the depth interval of the wells listed in the California Department of Public Health (CDPH) database for the San Diego study unit. The San Diego study unit consisted of four study areas: Temecula Valley (140 mi2), Warner Valley (34 mi2), Alluvial Basins (166 mi2), and Hard Rock (850 mi2). The quality of groundwater in shallow or deep water-bearing zones may differ from that in the primary aquifers. For example, shallow groundwater may be more vulnerable to surficial contamination than groundwater in deep water-bearing zones. This study had two components: the status assessment and the understanding assessment. The first component of this study-the status assessment of the current quality of the groundwater resource-was assessed by using data from samples analyzed for volatile organic compounds (VOC), pesticides, and naturally occurring inorganic constituents, such as major ions and trace elements. The status assessment is intended to characterize the quality of groundwater resources within the primary aquifers of the San Diego study unit, not the treated drinking water delivered to consumers by water purveyors. The second component of this study-the understanding assessment-identified the natural and human factors that affect groundwater quality by evaluating land use, well construction, and geochemical conditions of the aquifer. Results from these evaluations were used to help explain the occurrence and distribution of selected constituents in the study unit. Relative-concentrations (sample concentration divided by benchmark concentration) were used as the primary metric for relating concentrations of constituents in groundwater samples to water-quality benchmarks for those constituents that have Federal and (or) California benchmarks. For organic and special-interest constituents, relative-concentrations were classified as high (> 1.0), moderate (> 0.1 and ≤1.0), and low (≤0.1). For inorganic constituents, relative concentrations were classified as high (> 1.0), moderate (> 0.5 and ≤1.0), and low (≤0.5). Grid-based and spatially weighted approaches were then used to evaluate the proportion of the primary aquifers (aquifer-scale proportions) with high, moderate, and low relative-concentrations for individual compounds and classes of constituents. One or more of the inorganic constituents with health-based benchmarks were high (relative to those benchmarks) in 17.6 percent of the primary aquifers in the Temecula Valley, Warner Valley, and Alluvial Basins study areas (hereinafter also collectively referred to as the Alluvial Fill study areas because they are composed of alluvial fill aquifers), and in 25.0 percent of the Hard Rock study area. Inorganic constituents with health-based benchmarks that were frequently detected at high relative-concentrations included vanadium (V), arsenic (As), and boron (B). Vanadium and As concentrations were not significantly correlated to either urban or agricultural land use indicating natural sources as the primary contributors of these constituents to groundwater. The positive correlation of B concentration to urban land-use was significant which indicates that anthropogenic activities are a contributing source of B to groundwater. The correlation of V, As and B concentrations to pH was positive, indicating that in alkaline groundwater these constituents are being desorbed from, or being inhibited from adsorbing to, particle surfaces. Inorganic constituents with aesthetic benchmarks that were detected at high relative-concentrations include manganese (Mn), iron (Fe), and total dissolved solids (TDS). In the Alluvial Fill study areas, Mn and TDS were detected at high relative-concentrations in 13.7 percent of the primary aquifers, and Fe in 6.9 percent. In the Hard Rock study area, Mn was detected at high relative-concentrations in 33.3 percent of the primary aquifers, and TDS in 16.7 percent; Fe was not detected at high relative-concentrations. Total dissolved solids concentrations were significantly correlated to agricultural land use suggesting that agricultural practices are a contributing source of TDS to groundwater. Manganese and Fe concentrations were highest in groundwater with low dissolved oxygen and pH indicating that the reductive dissolution of oxyhydroxides may be an important mechanism for the mobilization of Mn and Fe in groundwater. TDS concentrations were highest in shallow wells and in modern (< 50 yrs) groundwater which indicates anthropogenic activities as a source of TDS concentrations in groundwater. The relative-concentrations of organic constituents with health-based benchmarks were high in 3.0 percent of the primary aquifers in the Alluvial Fill study areas. A single detection in the Alluvial Basins study area of the discontinued gasoline oxygenate methyl tert-butyl ether (MTBE) was the only organic constituent detected at a high relative-concentration; high relative-concentrations of these constituents were not detected in the Hard Rock study area. Twelve of 88 VOCs and 14 of 123 pesticides and pesticide degradates analyzed in grid wells were detected. Chloroform was the only VOC detected in more than 10 percent of the grid wells. The herbicides simazine, atrazine, and prometon were each detected in greater than 10 percent of the grid wells. Perchlorate was detected in 22 percent of the grid wells sampled. The understanding assessment showed a significant correlation of trihalomethanes (THMs) and solvents to urban land-use, indicating that detections of these constituents are more likely to occur in groundwater underlying urbanized areas of the study unit. MTBE concentrations were negatively correlated to the distance from the nearest leaking underground fuel tank, indicating that point sources are the most significant contributing factor for MTBE concentrations to groundwater in the study unit. The positive correlation of THM and herbicide concentrations to modern groundwater was significant, as was the negative correlation of herbicide concentrations to pH and anoxic groundwater. The negative correlation of herbicides to pH and anoxic groundwater was likely due to the fact that these constituents were detected more frequently in shallow wells where groundwater conditions tend to be oxic with relatively low pH.

DISCO: Distance and Spectrum Correlation Optimization Alignment for Two Dimensional Gas Chromatography Time-of-Flight Mass Spectrometry-based Metabolomics

PubMed Central

Wang, Bing; Fang, Aiqin; Heim, John; Bogdanov, Bogdan; Pugh, Scott; Libardoni, Mark; Zhang, Xiang

2010-01-01

A novel peak alignment algorithm using a distance and spectrum correlation optimization (DISCO) method has been developed for two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC/TOF-MS) based metabolomics. This algorithm uses the output of the instrument control software, ChromaTOF, as its input data. It detects and merges multiple peak entries of the same metabolite into one peak entry in each input peak list. After a z-score transformation of metabolite retention times, DISCO selects landmark peaks from all samples based on both two-dimensional retention times and mass spectrum similarity of fragment ions measured by Pearson’s correlation coefficient. A local linear fitting method is employed in the original two-dimensional retention time space to correct retention time shifts. A progressive retention time map searching method is used to align metabolite peaks in all samples together based on optimization of the Euclidean distance and mass spectrum similarity. The effectiveness of the DISCO algorithm is demonstrated using data sets acquired under different experiment conditions and a spiked-in experiment. PMID:20476746

Metabolic and miRNA Profiling of TMV Infected Plants Reveals Biphasic Temporal Changes

PubMed Central

Bazzini, Ariel A.; Manacorda, Carlos A.; Tohge, Takayuki; Conti, Gabriela; Rodriguez, Maria C.; Nunes-Nesi, Adriano; Villanueva, Sofía; Fernie, Alisdair R.; Carrari, Fernando; Asurmendi, Sebastian

2011-01-01

Plant viral infections induce changes including gene expression and metabolic components. Identification of metabolites and microRNAs (miRNAs) differing in abundance along infection may provide a broad view of the pathways involved in signaling and defense that orchestrate and execute the response in plant-pathogen interactions. We used a systemic approach by applying both liquid and gas chromatography coupled to mass spectrometry to determine the relative level of metabolites across the viral infection, together with a miRs profiling using a micro-array based procedure. Systemic changes in metabolites were characterized by a biphasic response after infection. The first phase, detected at one dpi, evidenced the action of a systemic signal since no virus was detected systemically. Several of the metabolites increased at this stage were hormone-related. miRs profiling after infection also revealed a biphasic alteration, showing miRs alteration at 5 dpi where no virus was detected systemically and a late phase correlating with virus accumulation. Correlation analyses revealed a massive increase in the density of correlation networks after infection indicating a complex reprogramming of the regulatory pathways, either in response to the plant defense mechanism or to the virus infection itself. Our data propose the involvement of a systemic signaling on early miRs alteration. PMID:22174812

Development of a homogeneous assay format for p53 antibodies using fluorescence correlation spectroscopy

NASA Astrophysics Data System (ADS)

Neuweiler, Hannes; Scheffler, Silvia; Sauer, Markus

2005-08-01

The development of reliable methods for the detection of minute amounts of antibodies directly in homogeneous solution represents one of the major tasks in the current research field of molecular diagnostics. We demonstrate the potential of fluorescence correlation spectroscopy (FCS) in combination with quenched peptide-based fluorescence probes for sensitive detection of p53 antibodies directly in homogeneous solution. Single tryptophan (Trp) residues in the sequences of short, synthetic peptide epitopes of the human p53 protein efficiently quench the fluorescence of an oxazine fluorophore attached to the amino terminal ends of the peptides. The fluorescence quenching mechanism is thought to be a photoinduced electron transfer reaction from Trp to the dye enabled by the formation of intramolecular complexes between dye and Trp. Specific recognition of the epitope by the antibody confines the conformational flexibility of the peptide. Consequently, complex formation between dye and Trp is abolished and fluorescence is recovered. Using fluorescence correlation spectroscopy (FCS), antibody binding can be monitored observing two parameters simultaneously: the diffusional mobility of the peptide as well as the quenching amplitude induced by the conformational flexibility of the peptide change significantly upon antibody binding. Our data demonstrate that FCS in combination with fluorescence-quenched peptide epitopes opens new possibilities for the reliable detection of antibody binding events in homogeneous solution.

Sentinel surveillance of influenza and other respiratory viruses, Brazil, 2000-2010.

PubMed

Freitas, Felipe Teixeira de Mello

2013-01-01

There are scanty data on the epidemiology of influenza and other respiratory viruses in South America and Brazil. The aim of this study was to summarize the data from the Brazilian surveillance system of influenza and other respiratory viruses and discuss the patterns of viral circulation. The system is based on detecting cases of influenza-like illness in sentinel sites and weekly collection of five nasopharyngeal secretions samples, which are processed in state public health laboratories for respiratory viruses by indirect immunofluorescence assay. Data from 2000 to 2010 were described over time, by region, gender, and age group, and an analysis of Spearman correlation was performed between monthly influenza detection and rainfall and temperature data in two state capitals with the highest number of positive samples, one from the northeast region (Maceió) and other from the southern region (Curitiba). There were 3,291,946 visits for influenza-like illness; of these, 37,120 had samples collected and 6421 tested positive: 1690 (26%) influenza A, 567 (9%) influenza B, 277 (4%) parainfluenza 1, 571 (9%) parainfluenza 2, 589 (9%) parainfluenza 3, 742 (12%) adenovirus, and 1985 (31%) respiratory syncytial virus. Overall, increased activity of respiratory syncytial virus was observed from March to June, preceding the peak of influenza activity, from May to August, but with regional differences. In Maceió, there was a weak correlation between temperature and influenza detection (ρ=0.05), but a moderate positive correlation between rainfall and influenza detection (ρ=0.36). In Curitiba, a high correlation was observed between the decrease in temperature and rainfall and the increase in influenza detection (ρ=-0.83 and -0.78 respectively). These data are important to guide public health control measures as the best time for influenza vaccination and use of antivirals. Copyright © 2013 Elsevier Editora Ltda. All rights reserved.

A robust hypothesis test for the sensitive detection of constant speed radiation moving sources

NASA Astrophysics Data System (ADS)

Dumazert, Jonathan; Coulon, Romain; Kondrasovs, Vladimir; Boudergui, Karim; Moline, Yoann; Sannié, Guillaume; Gameiro, Jordan; Normand, Stéphane; Méchin, Laurence

2015-09-01

Radiation Portal Monitors are deployed in linear networks to detect radiological material in motion. As a complement to single and multichannel detection algorithms, inefficient under too low signal-to-noise ratios, temporal correlation algorithms have been introduced. Test hypothesis methods based on empirically estimated mean and variance of the signals delivered by the different channels have shown significant gain in terms of a tradeoff between detection sensitivity and false alarm probability. This paper discloses the concept of a new hypothesis test for temporal correlation detection methods, taking advantage of the Poisson nature of the registered counting signals, and establishes a benchmark between this test and its empirical counterpart. The simulation study validates that in the four relevant configurations of a pedestrian source carrier under respectively high and low count rate radioactive backgrounds, and a vehicle source carrier under the same respectively high and low count rate radioactive backgrounds, the newly introduced hypothesis test ensures a significantly improved compromise between sensitivity and false alarm. It also guarantees that the optimal coverage factor for this compromise remains stable regardless of signal-to-noise ratio variations between 2 and 0.8, therefore allowing the final user to parametrize the test with the sole prior knowledge of background amplitude.

The effect of hybridization-induced secondary structure alterations on RNA detection using backscattering interferometry

PubMed Central

Adams, Nicholas M.; Olmsted, Ian R.; Haselton, Frederick R.; Bornhop, Darryl J.; Wright, David W.

2013-01-01

Backscattering interferometry (BSI) has been used to successfully monitor molecular interactions without labeling and with high sensitivity. These properties suggest that this approach might be useful for detecting biomarkers of infection. In this report, we identify interactions and characteristics of nucleic acid probes that maximize BSI signal upon binding the respiratory syncytial virus nucleocapsid gene RNA biomarker. The number of base pairs formed upon the addition of oligonucleotide probes to a solution containing the viral RNA target correlated with the BSI signal magnitude. Using RNA folding software mfold, we found that the predicted number of unpaired nucleotides in the targeted regions of the RNA sequence generally correlated with BSI sensitivity. We also demonstrated that locked nucleic acid (LNA) probes improved sensitivity approximately 4-fold compared to DNA probes of the same sequence. We attribute this enhancement in BSI performance to the increased A-form character of the LNA:RNA hybrid. A limit of detection of 624 pM, corresponding to ∼105 target molecules, was achieved using nine distinct ∼23-mer DNA probes complementary to regions distributed along the RNA target. Our results indicate that BSI has promise as an effective tool for sensitive RNA detection and provides a road map for further improving detection limits. PMID:23519610

Detection of Nanophyetus salmincola in water, snails, and fish tissues by quantitative polymerase chain reaction

USGS Publications Warehouse

Purcell, Maureen K.; Powers, Rachel L.; Besijn, Bonnie; Hershberger, Paul K.

2017-01-01

We report the development and validation of two quantitative PCR (qPCR) assays to detect Nanophyetus salmincola DNA in water samples and in fish and snail tissues. Analytical and diagnostic validation demonstrated good sensitivity, specificity, and repeatability of both qPCR assays. The N. salmincola DNA copy number in kidney tissue was significantly correlated with metacercaria counts based on microscopy. Extraction methods were optimized for the sensitive qPCR detection of N. salmincola DNA in settled water samples. Artificially spiked samples suggested that the 1-cercaria/L threshold corresponded to an estimated log10 copies per liter ≥ 6.0. Significant correlation of DNA copy number per liter and microscopic counts indicated that the estimated qPCR copy number was a good predictor of the number of waterborne cercariae. However, the detection of real-world samples below the estimated 1-cercaria/L threshold suggests that the assays may also detect other N. salmincola life stages, nonintact cercariae, or free DNA that settles with the debris. In summary, the qPCR assays reported here are suitable for identifying and quantifying all life stages of N. salmincola that occur in fish tissues, snail tissues, and water.

Phylogeny-based comparative methods question the adaptive nature of sporophytic specializations in mosses.

PubMed

Huttunen, Sanna; Olsson, Sanna; Buchbender, Volker; Enroth, Johannes; Hedenäs, Lars; Quandt, Dietmar

2012-01-01

Adaptive evolution has often been proposed to explain correlations between habitats and certain phenotypes. In mosses, a high frequency of species with specialized sporophytic traits in exposed or epiphytic habitats was, already 100 years ago, suggested as due to adaptation. We tested this hypothesis by contrasting phylogenetic and morphological data from two moss families, Neckeraceae and Lembophyllaceae, both of which show parallel shifts to a specialized morphology and to exposed epiphytic or epilithic habitats. Phylogeny-based tests for correlated evolution revealed that evolution of four sporophytic traits is correlated with a habitat shift. For three of them, evolutionary rates of dual character-state changes suggest that habitat shifts appear prior to changes in morphology. This suggests that they could have evolved as adaptations to new habitats. Regarding the fourth correlated trait the specialized morphology had already evolved before the habitat shift. In addition, several other specialized "epiphytic" traits show no correlation with a habitat shift. Besides adaptive diversification, other processes thus also affect the match between phenotype and environment. Several potential factors such as complex genetic and developmental pathways yielding the same phenotypes, differences in strength of selection, or constraints in phenotypic evolution may lead to an inability of phylogeny-based comparative methods to detect potential adaptations.

A SVM-based quantitative fMRI method for resting-state functional network detection.

PubMed

Song, Xiaomu; Chen, Nan-kuei

2014-09-01

Resting-state functional magnetic resonance imaging (fMRI) aims to measure baseline neuronal connectivity independent of specific functional tasks and to capture changes in the connectivity due to neurological diseases. Most existing network detection methods rely on a fixed threshold to identify functionally connected voxels under the resting state. Due to fMRI non-stationarity, the threshold cannot adapt to variation of data characteristics across sessions and subjects, and generates unreliable mapping results. In this study, a new method is presented for resting-state fMRI data analysis. Specifically, the resting-state network mapping is formulated as an outlier detection process that is implemented using one-class support vector machine (SVM). The results are refined by using a spatial-feature domain prototype selection method and two-class SVM reclassification. The final decision on each voxel is made by comparing its probabilities of functionally connected and unconnected instead of a threshold. Multiple features for resting-state analysis were extracted and examined using an SVM-based feature selection method, and the most representative features were identified. The proposed method was evaluated using synthetic and experimental fMRI data. A comparison study was also performed with independent component analysis (ICA) and correlation analysis. The experimental results show that the proposed method can provide comparable or better network detection performance than ICA and correlation analysis. The method is potentially applicable to various resting-state quantitative fMRI studies. Copyright © 2014 Elsevier Inc. All rights reserved.

Herbicides and herbicide degradation products in upper midwest agricultural streams during august base-flow conditions

USGS Publications Warehouse

Kalkhoff, S.J.; Lee, K.E.; Porter, S.D.; Terrio, P.J.; Thurman, E.M.

2003-01-01

Herbicide concentrations in streams of the U.S. Midwest have been shown to decrease through the growing season due to a variety of chemical and physical factors. The occurrence of herbicide degradation products at the end of the growing season is not well known. This study was conducted to document the occurrence of commonly used herbicides and their degradation products in Illinois, Iowa, and Minnesota streams during base-flow conditions in August 1997. Atrazine, the most frequently detected herbicide (94%), was present at relatively low concentrations (median 0.17 μg L−1). Metolachlor was detected in 59% and cyanazine in 37% of the samples. Seven of nine compounds detected in more than 50% of the samples were degradation products. The total concentration of the degradation products (median of 4.4 μg L−1) was significantly greater than the total concentration of parent compounds (median of 0.26 μg L−1). Atrazine compounds were present less frequently and in significantly smaller concentrations in streams draining watersheds with soils developed on less permeable tills than in watersheds with soils developed on more permeable loess. The detection and concentration of triazine compounds was negatively correlated with antecedent rainfall (April–July). In contrast, acetanalide compounds were positively correlated with antecedant rainfall in late spring and early summer that may transport the acetanalide degradates into ground water and subsequently into nearby streams. The distribution of atrazine degradation products suggests regional differences in atrazine degradation processes.

Progressively expanded neural network for automatic material identification in hyperspectral imagery

NASA Astrophysics Data System (ADS)

Paheding, Sidike

The science of hyperspectral remote sensing focuses on the exploitation of the spectral signatures of various materials to enhance capabilities including object detection, recognition, and material characterization. Hyperspectral imagery (HSI) has been extensively used for object detection and identification applications since it provides plenty of spectral information to uniquely identify materials by their reflectance spectra. HSI-based object detection algorithms can be generally classified into stochastic and deterministic approaches. Deterministic approaches are comparatively simple to apply since it is usually based on direct spectral similarity such as spectral angles or spectral correlation. In contrast, stochastic algorithms require statistical modeling and estimation for target class and non-target class. Over the decades, many single class object detection methods have been proposed in the literature, however, deterministic multiclass object detection in HSI has not been explored. In this work, we propose a deterministic multiclass object detection scheme, named class-associative spectral fringe-adjusted joint transform correlation. Human brain is capable of simultaneously processing high volumes of multi-modal data received every second of the day. In contrast, a machine sees input data simply as random binary numbers. Although machines are computationally efficient, they are inferior when comes to data abstraction and interpretation. Thus, mimicking the learning strength of human brain has been current trend in artificial intelligence. In this work, we present a biological inspired neural network, named progressively expanded neural network (PEN Net), based on nonlinear transformation of input neurons to a feature space for better pattern differentiation. In PEN Net, discrete fixed excitations are disassembled and scattered in the feature space as a nonlinear line. Each disassembled element on the line corresponds to a pattern with similar features. Unlike the conventional neural network where hidden neurons need to be iteratively adjusted to achieve better accuracy, our proposed PEN Net does not require hidden neurons tuning which achieves better computational efficiency, and it has also shown superior performance in HSI classification tasks compared to the state-of-the-arts. Spectral-spatial features based HSI classification framework has shown stronger strength compared to spectral-only based methods. In our lastly proposed technique, PEN Net is incorporated with multiscale spatial features (i.e., multiscale complete local binary pattern) to perform a spectral-spatial classification of HSI. Several experiments demonstrate excellent performance of our proposed technique compared to the more recent developed approaches.

Seeing diabetes: visual detection of glucose based on the intrinsic peroxidase-like activity of MoS2 nanosheets

NASA Astrophysics Data System (ADS)

Lin, Tianran; Zhong, Liangshuang; Guo, Liangqia; Fu, Fengfu; Chen, Guonan

2014-09-01

Molybdenum disulfide (MoS2) has attracted increasing research interest recently due to its unique physical, optical and electrical properties, correlated with its 2D ultrathin atomic-layered structure. Until now, however, great efforts have focused on its applications such as lithium ion batteries, transistors, and hydrogen evolution reactions. Herein, for the first time, MoS2 nanosheets are discovered to possess an intrinsic peroxidase-like activity and can catalytically oxidize 3,3',5,5'-tetramethylbenzidine (TMB) by H2O2 to produce a color reaction. The catalytic activity follows the typical Michaelis-Menten kinetics and is dependent on temperature, pH, H2O2 concentration, and reaction time. Based on this finding, a highly sensitive and selective colorimetric method for H2O2 and glucose detection is developed and applied to detect glucose in serum samples. Moreover, a simple, inexpensive, instrument-free and portable test kit for the visual detection of glucose in normal and diabetic serum samples is constructed by utilizing agarose hydrogel as a visual detection platform.Molybdenum disulfide (MoS2) has attracted increasing research interest recently due to its unique physical, optical and electrical properties, correlated with its 2D ultrathin atomic-layered structure. Until now, however, great efforts have focused on its applications such as lithium ion batteries, transistors, and hydrogen evolution reactions. Herein, for the first time, MoS2 nanosheets are discovered to possess an intrinsic peroxidase-like activity and can catalytically oxidize 3,3',5,5'-tetramethylbenzidine (TMB) by H2O2 to produce a color reaction. The catalytic activity follows the typical Michaelis-Menten kinetics and is dependent on temperature, pH, H2O2 concentration, and reaction time. Based on this finding, a highly sensitive and selective colorimetric method for H2O2 and glucose detection is developed and applied to detect glucose in serum samples. Moreover, a simple, inexpensive, instrument-free and portable test kit for the visual detection of glucose in normal and diabetic serum samples is constructed by utilizing agarose hydrogel as a visual detection platform. Electronic supplementary information (ESI) available. See DOI: 10.1039/c4nr03393k

Dictionary-driven Ischemia Detection from Cardiac Phase-Resolved Myocardial BOLD MRI at Rest

PubMed Central

Bevilacqua, Marco; Dharmakumar, Rohan; Tsaftaris, Sotirios A.

2016-01-01

Cardiac Phase-resolved Blood-Oxygen-Level Dependent (CP–BOLD) MRI provides a unique opportunity to image an ongoing ischemia at rest. However, it requires post-processing to evaluate the extent of ischemia. To address this, here we propose an unsupervised ischemia detection (UID) method which relies on the inherent spatio-temporal correlation between oxygenation and wall motion to formalize a joint learning and detection problem based on dictionary decomposition. Considering input data of a single subject, it treats ischemia as an anomaly and iteratively learns dictionaries to represent only normal observations (corresponding to myocardial territories remote to ischemia). Anomaly detection is based on a modified version of One-class Support Vector Machines (OCSVM) to regulate directly the margins by incorporating the dictionary-based representation errors. A measure of ischemic extent (IE) is estimated, reflecting the relative portion of the myocardium affected by ischemia. For visualization purposes an ischemia likelihood map is created by estimating posterior probabilities from the OCSVM outputs, thus obtaining how likely the classification is correct. UID is evaluated on synthetic data and in a 2D CP–BOLD data set from a canine experimental model emulating acute coronary syndromes. Comparing early ischemic territories identified with UID against infarct territories (after several hours of ischemia), we find that IE, as measured by UID, is highly correlated (Pearson’s r = 0.84) w.r.t. infarct size. When advances in automated registration and segmentation of CP–BOLD images and full coverage 3D acquisitions become available, we hope that this method can enable pixel-level assessment of ischemia with this truly non-invasive imaging technique. PMID:26292338

INNOVATIVE ACOUSTIC SENSOR TECHNOLOGIES FOR LEAK DETECTION IN CHALLENGING PIPE TYPES

DTIC Science & Technology

2016-12-30

through focused acoustic surveys that are typically conducted at the correlated location prior to marking the leak location. All three technologies were...shift” survey with cross- correlation Echologics LeakFinderRTT M Field survey of leak signatures. Recommended every 3-5 years Contractor...cross- correlation features to detect and pinpoint leaks in challenging pipe types, as well as metallic pipes. 15. SUBJECT TERMS Leak detection

Express immunochromatographic detection of antibodies against Brucella abortus in cattle sera based on quantitative photometric registration and modulated cut-off level.

PubMed

Sotnikov, Dmitriy V; Byzova, Nadezhda A; Zherdev, Anatoly V; Eskendirova, Saule Z; Baltin, Kairat K; Mukanov, Kasim K; Ramankulov, Erlan M; Sadykhov, Elchin G; Dzantiev, Boris B

2015-01-01

An immunochromatographic test system was developed for rapid detection of the levels of specific IgG antibodies to Brucella abortus lipopolysaccharide, as a tool for diagnosis of brucellosis in cattle. The pilot test strips were examined using blood sera from sick (78 samples) and healthy (35 samples) cows. The results obtained by immunochromatographic assay, using a portable optical densitometer for digital video detection, correlate well with the results obtained by immunoenzyme assay and are in agreement with the results of the disease diagnosis. The new test system allows detection of antibodies within 10 min and can be proposed as an alternative to the methods available for serodiagnosis of brucellosis.

Time-resolved measurements in diffuse reflectance: effects of the instrument response function of different detection systems on the depth sensitivity

NASA Astrophysics Data System (ADS)

Puszka, Agathe; Planat-Chrétien, Anne; Berger, Michel; Hervé, Lionel; Dinten, Jean-Marc

2014-02-01

We demonstrate the loss of depth sensitivity induced by the instrument response function on reflectance time-resolved diffuse optical tomography through the comparison of 3 detection systems: on one hand a photomultiplier tube (PMT) and a hybrid PMT coupled with a time-correlated single-photon counting card and on the other hand a high rate intensified camera. We experimentally evaluate the depth sensitivity achieved for each detection module with an absorbing inclusion embedded in a turbid medium. The different interfiber distances of 5, 10 and 15 mm are considered. Finally, we determine a maximal depth reached for each detection system by using 3D tomographic reconstructions based on the Mellin-Laplace transform.

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

A Coffee Ring Aptasensor for Rapid Protein Detection

PubMed Central

Wen, Jessica T.; Ho, Chih-Ming; Lillehoj, Peter B.

2013-01-01

We introduce a new biosensing platform for rapid protein detection that combines one of the simplest methods for biomolecular concentration, coffee ring formation, with a sensitive aptamer-based optical detection scheme. In this approach, aptamer beacons are utilized for signal transduction where a fluorescence signal is emitted in the presence of the target molecule. Signal amplification is achieved by concentrating aptamer-target complexes within liquid droplets, resulting in the formation of coffee ring “spots”. Surfaces with various chemical coatings were utilized to investigate the correlation between surface hydrophobicity, concentration efficiency and signal amplification. Based on our results, we found that the increase in coffee ring diameter with larger droplet volumes is independent of surface hydrophobicity. Furthermore, we show that highly hydrophobic surfaces produce enhanced particle concentration, via coffee ring formation, resulting in signal intensities 6-fold greater than those on hydrophilic surfaces. To validate this biosensing platform for the detection of clinical samples, we detected α-thrombin in human serum and 4x diluted whole blood. Based on our results, coffee ring spots produced detection signals 40x larger than samples in liquid droplets. Additionally, this biosensor exhibits a lower limit of detection of 2 ng/mL (54 pM) in serum, and 4 ng/mL (105 pM) in blood. Based on its simplicity and high performance, this platform demonstrates immense potential as an inexpensive diagnostic tool for the detection of disease biomarkers, particularly for use in developing countries that lack the resources and facilities required for conventional biodetection practices. PMID:23540796

Effects of threshold on single-target detection by using modified amplitude-modulated joint transform correlator

NASA Astrophysics Data System (ADS)

Kaewkasi, Pitchaya; Widjaja, Joewono; Uozumi, Jun

2007-03-01

Effects of threshold value on detection performance of the modified amplitude-modulated joint transform correlator are quantitatively studied using computer simulation. Fingerprint and human face images are used as test scenes in the presence of noise and a contrast difference. Simulation results demonstrate that this correlator improves detection performance for both types of image used, but moreso for human face images. Optimal detection of low-contrast human face images obscured by strong noise can be obtained by selecting an appropriate threshold value.

Pesticides in streams in the Tar-Pamlico drainage basin, North Carolina, 1992-94

USGS Publications Warehouse

Woodside, Michael D.; Ruhl, Kelly E.

2001-01-01

From 1992 to 1994, 147 water samples were collected at 5 sites in the Tar-Pamlico drainage basin in North Carolina and analyzed for 46 herbicides, insecticides, and pesticide metabolites as part of the U.S. Geological Survey's National Water-Quality Assessment Program. Based on a common adjusted detection limit of 0.01 microgram per liter, the most frequently detected herbicides were metolachlor (84 percent), atrazine (78 percent), alachlor (72 percent), and prometon (57 percent). The insecticides detected most frequently were carbaryl (12 percent), carbofuran (7 percent), and diazinon (4 percent). Although the pesticides with the highest estimated uses generally were the compounds detected most frequently, there was not a strong correlation between estimated use and detection frequency. The development of statistical correlations between pesticide use and detection frequency was limited by the lack of information on pesticides commonly applied in urban and agricultural areas, such as prometon, chlorpyrifos, and diazinon, and the small number of basins included in this study. For example, prometon had the fourth highest detection frequency, but use information was not available. Nevertheless, the high detection frequency of prometon indicates that nonagricultural uses also contribute to pesticide levels in streams in the Tar-Pamlico drainage basin.Concentrations of the herbicides atrazine, alachlor, and trifluralin varied seasonally, with elevated concentrations generally occurring in the spring, during and immediately following application periods, and in the summer. Seasonal concentration patterns were less evident for prometon, diazinon, and chlorpyrifos. Alachlor is the only pesticide detected in concentrations that exceeded current (2000) drinking-water standards.

Enhanced interoceptive awareness during anticipation of public speaking is associated with fear of negative evaluation.

PubMed

Durlik, Caroline; Brown, Gary; Tsakiris, Manos

2014-04-01

Interoceptive awareness (IA)--the ability to detect internal body signals--has been linked to various aspects of emotional processing. However, it has been examined mostly as a trait variable, with few studies also investigating state dependent fluctuations in IA. Based on the known positive correlation between IA and emotional reactivity, negative affectivity, and trait anxiety, the current study examined whether IA, as indexed by heartbeat detection accuracy, would change during an anxiety-provoking situation. Participants in the experimental condition, in which they anticipated giving a speech in front of a small audience, displayed significant IA increases from baseline to anticipation. Enhancement in IA was positively correlated with fear of negative evaluation. Implications of the results are discussed in relation to the role of trait and state IA in emotional experience.