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Sample records for based correlation detection

  1. Structural Plasticity Controlled by Calcium Based Correlation Detection

    PubMed Central

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

    2008-01-01

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

  2. 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.

  3. Stochastic quantum Zeno-based detection of noise correlations

    PubMed Central

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

    2016-01-01

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

  4. Stochastic quantum Zeno-based detection of noise correlations

    NASA Astrophysics Data System (ADS)

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

    2016-12-01

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

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

    PubMed

    Manzur, Tariq; Zeller, John; Serati, Steve

    2012-07-20

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

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

    NASA Astrophysics Data System (ADS)

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

    2017-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Gibbons, Steven J.; Ringdal, Frode

    2010-05-01

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

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

    PubMed

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

    2013-01-01

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

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

    PubMed

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

    2012-10-10

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

  10. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-12-01

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

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

    NASA Astrophysics Data System (ADS)

    Yang, Yin-xian; Yang, Ding-li

    2013-03-01

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

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

    NASA Astrophysics Data System (ADS)

    Topiwala, Pankaj N.; Casasent, David P.

    2004-09-01

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

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

    NASA Astrophysics Data System (ADS)

    Dai, Meifeng; Hou, Jie; Ye, Dandan

    2016-02-01

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

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

    PubMed

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

    2007-10-03

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

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

    PubMed Central

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

    2010-01-01

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

  17. Spatial correlation coefficient images for ultrasonic detection.

    PubMed

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

    2007-09-01

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

  18. Ultrasonic Detection Using Correlation Images (Preprint)

    DTIC Science & Technology

    2006-08-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. Electrophysiological correlates of change detection.

    PubMed

    Eimer, Martin; Mazza, Veronica

    2005-05-01

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

  5. 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.

  6. 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

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

    DTIC Science & Technology

    2010-06-01

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

  8. 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

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

    USGS Publications Warehouse

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

    2013-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2013-01-01

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

  11. 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

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

    NASA Technical Reports Server (NTRS)

    Clem, Michelle M.; Woike, Mark R.

    2013-01-01

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

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

    PubMed

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

    2016-12-13

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

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

    PubMed Central

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

    2016-01-01

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

  15. WCEDS: A waveform correlation event detection system

    SciTech Connect

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

    1995-08-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-04-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2014-01-01

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

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

    PubMed

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

    2017-03-20

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

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

    DTIC Science & Technology

    2006-07-01

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

  20. Gas correlation lidar for methane detection

    NASA Technical Reports Server (NTRS)

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

    1986-01-01

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

  1. Distortion-insensitive correlation constellation detection

    NASA Astrophysics Data System (ADS)

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

    2011-04-01

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

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

    PubMed

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

    2013-02-10

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

  3. Change Point Detection in Correlation Networks

    PubMed Central

    Barnett, Ian; Onnela, Jukka-Pekka

    2016-01-01

    Many systems of interacting elements can be conceptualized as networks, where network nodes represent the elements and network ties represent interactions between the elements. In systems where the underlying network evolves, it is useful to determine the points in time where the network structure changes significantly as these may correspond to functional change points. We propose a method for detecting change points in correlation networks that, unlike previous change point detection methods designed for time series data, requires minimal distributional assumptions. We investigate the difficulty of change point detection near the boundaries of the time series in correlation networks and study the power of our method and competing methods through simulation. We also show the generalizable nature of the method by applying it to stock price data as well as fMRI data. PMID:26739105

  4. Change Point Detection in Correlation Networks

    NASA Astrophysics Data System (ADS)

    Barnett, Ian; Onnela, Jukka-Pekka

    2016-01-01

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

  5. Fatigue Crack Detection Using Digital Image Correlation

    NASA Astrophysics Data System (ADS)

    Cawley, P.; Hutt, T. D.

    2009-03-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2015-01-01

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

  7. Correlation Based Geomagnetic Field Modeling

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  8. Correlation fluorescence method of amine detection

    NASA Astrophysics Data System (ADS)

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

    1997-12-01

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

  9. Neuroanatomical correlates of biological motion detection

    PubMed Central

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

    2013-01-01

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

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

    PubMed

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

    2016-07-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-07-01

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

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

    PubMed

    Carns, Bhavini; Fadare, Oluwole

    2008-01-01

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

  13. Edge-based correlation image registration for multispectral imaging

    DOEpatents

    Nandy, Prabal

    2009-11-17

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

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

    PubMed

    Brand, Andrew; Bradley, Michael T

    2012-01-01

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

  15. Detection Performance of the Circular Correlation Coefficient Receiver,

    DTIC Science & Technology

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

  16. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2017-01-01

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

  18. Endotoxemia: methods of detection and clinical correlates.

    PubMed Central

    Hurley, J C

    1995-01-01

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

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

    SciTech Connect

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

    2016-03-15

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

  20. Correlation studies on surface particle detection methods

    NASA Technical Reports Server (NTRS)

    Peterson, Ronald V.; White, James C.

    1988-01-01

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

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

    PubMed Central

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

    2016-01-01

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

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

    DOE PAGES

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

    2016-03-15

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

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

    PubMed Central

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

    2014-01-01

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

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

    PubMed

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

    2014-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  6. A method for detecting complex correlation in time series

    NASA Astrophysics Data System (ADS)

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

    2007-06-01

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

  7. Noninvasive deep Raman detection with 2D correlation analysis

    NASA Astrophysics Data System (ADS)

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

    2014-07-01

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

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

    NASA Astrophysics Data System (ADS)

    Tahari, Abdel Kader

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

  9. Unzipping of DNA with correlated base sequence.

    PubMed

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

    2004-06-01

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

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

    PubMed

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

    2016-12-02

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

  11. Interevent Correlations from Avalanches Hiding Below the Detection Threshold

    NASA Astrophysics Data System (ADS)

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

    2016-12-01

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

  12. Diffraction-based optical correlator

    NASA Technical Reports Server (NTRS)

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

    2005-01-01

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

  13. Intrinsic Correlations for Flaring Blazars Detected by Fermi

    NASA Astrophysics Data System (ADS)

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

    2017-02-01

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

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

    SciTech Connect

    Smid, Petr; Horvath, Pavel; Hrabovsky, Miroslav

    2006-09-20

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

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

    PubMed

    Smíd, Petr; Horváth, Pavel; Hrabovský, Miroslav

    2006-09-20

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

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

    NASA Astrophysics Data System (ADS)

    Contreras, Viridiana; Díaz-Ramírez, Víctor H.

    2016-09-01

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

  17. 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.

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

    PubMed Central

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

    2016-01-01

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

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

    DTIC Science & Technology

    2010-09-01

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

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

    NASA Astrophysics Data System (ADS)

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

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

  1. Low-cost gas correlation detection of methane

    NASA Astrophysics Data System (ADS)

    Chapman, O. M.; Hilton, M.

    2006-04-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2005-01-01

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

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

    SciTech Connect

    Oberer, Richard B.

    2002-10-01

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

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

    NASA Astrophysics Data System (ADS)

    Schlichting, A.; Brenner, C.

    2016-06-01

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

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

    ERIC Educational Resources Information Center

    Levy, Gary D.; And Others

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

  6. Upper Subcritical Calculations Based on Correlated Data

    SciTech Connect

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

    2015-01-01

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

  7. Motion detection based on recurrent network dynamics

    PubMed Central

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

    2014-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Miśkiewicz, Janusz; Ausloos, Marcel

    2008-11-01

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

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

    NASA Astrophysics Data System (ADS)

    Jackson, Christopher; van Enk, S. J.

    2015-10-01

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

  10. Long-term visual tracking based on correlation filters

    NASA Astrophysics Data System (ADS)

    Wei, Quanlu; Lao, Songyang; Bai, Liang

    2017-03-01

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

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

    PubMed

    Hongda Wang; Chiu-Sing Choy

    2016-08-01

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

  12. 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

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

    NASA Astrophysics Data System (ADS)

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

    2009-12-01

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

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

    NASA Astrophysics Data System (ADS)

    He, Hai-Tao; Marguet, Didier

    2011-05-01

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

  15. HEALPix Based Cross-Correlation in Astronomy

    NASA Astrophysics Data System (ADS)

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

    2013-10-01

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

  16. Ionizing particle detection based on phononic crystals

    SciTech Connect

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

    2015-08-14

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

  17. Ionizing particle detection based on phononic crystals

    NASA Astrophysics Data System (ADS)

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

    2015-08-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2017-03-01

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

  19. Bacteriophage-Based Pathogen Detection

    NASA Astrophysics Data System (ADS)

    Ripp, Steven

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

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

    PubMed Central

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

    2014-01-01

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

  1. A Random Motility Assay Based on Image Correlation Spectroscopy

    PubMed Central

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

    2013-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2011-05-01

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

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

    NASA Astrophysics Data System (ADS)

    Ikuta, Akira; Orimoto, Hisako; Ogawa, Hitoshi

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

  4. 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.

  5. Visible light communication based motion detection.

    PubMed

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

    2015-07-13

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

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

    DTIC Science & Technology

    2007-04-01

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

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

    SciTech Connect

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

    2016-12-19

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

  8. 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

  9. 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.

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

    NASA Astrophysics Data System (ADS)

    Fernandez, Paz; Whitworth, Malcolm

    2016-10-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

  12. 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.

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

    PubMed

    Gao, Fei; Zheng, Yuanjin

    2012-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-03-01

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

  15. DSN Beowulf Cluster-Based VLBI Correlator

    NASA Technical Reports Server (NTRS)

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

    2009-01-01

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

  16. 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

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

    SciTech Connect

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

    2016-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Fleet, R.

    2015-01-01

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

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

    PubMed

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

    2013-08-15

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

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

    PubMed Central

    Fisher, Diana O.; Blomberg, Simon P.

    2011-01-01

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

  1. 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.

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

    NASA Astrophysics Data System (ADS)

    alinne solano, ericka; Hjorleifsdottir, Vala

    2016-04-01

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

  3. Cellular telephone-based radiation detection instrument

    DOEpatents

    Craig, William W.; Labov, Simon E.

    2011-06-14

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

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

    DTIC Science & Technology

    2002-11-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2009-12-01

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

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

    SciTech Connect

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

    2015-11-15

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

  7. A SAR ATR algorithm based on coherent change detection

    SciTech Connect

    Harmony, D.W.

    2000-12-01

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

  8. Knowledge-based pitch detection

    NASA Astrophysics Data System (ADS)

    Dove, W. P.

    1986-06-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2017-02-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-12-01

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

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

    PubMed

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

    2013-02-01

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

  12. Visualizing confusion matrices for multidimensional signal detection correlational methods

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

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

    SciTech Connect

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

    2010-09-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2012-01-01

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

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

    PubMed

    Gao, Huihui; Liu, Feifei; Zhu, Qunxiong

    2016-11-01

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

  16. Experimental results for correlation-based wavefront sensing

    SciTech Connect

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

    2005-07-01

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

  17. Optical flow based finger stroke detection

    NASA Astrophysics Data System (ADS)

    Zhu, Zhongdi; Li, Bin; Wang, Kongqiao

    2010-07-01

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

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

    SciTech Connect

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

    2015-03-15

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

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

    PubMed

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

    2017-02-14

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

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

    NASA Astrophysics Data System (ADS)

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

    2017-02-01

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

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

    DTIC Science & Technology

    2008-09-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  3. Daytime Water Detection Based on Sky Reflections

    NASA Technical Reports Server (NTRS)

    Rankin, Arturo; Matthies, Larry; Bellutta, Paolo

    2011-01-01

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

  4. Contour detection based on wavelet differentiation

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

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

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

    PubMed

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

    2016-06-01

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

  6. Sociolect-Based Community Detection

    SciTech Connect

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

    2013-06-06

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

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

    PubMed

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

    2014-03-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-03-01

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

  9. Collaborative Regression-based Anatomical Landmark Detection

    PubMed Central

    Gao, Yaozong; Shen, Dinggang

    2015-01-01

    Anatomical landmark detection plays an important role in medical image analysis, e.g., for registration, segmentation and quantitative analysis. Among various existing methods for landmark detection, regression-based methods recently have drawn much attention due to robustness and efficiency. In such methods, landmarks are localized through voting from all image voxels, which is completely different from classification-based methods that use voxel-wise classification to detect landmarks. Despite robustness, the accuracy of regression-based landmark detection methods is often limited due to 1) inclusion of uninformative image voxels in the voting procedure, and 2) lack of effective ways to incorporate inter-landmark spatial dependency into the detection step. In this paper, we propose a collaborative landmark detection framework to address these limitations. The concept of collaboration is reflected in two aspects. 1) Multi-resolution collaboration. A multi-resolution strategy is proposed to hierarchically localize landmarks by gradually excluding uninformative votes from faraway voxels. Moreover, for the informative voxels near the landmark, a spherical sampling strategy is also designed in the training stage to improve their prediction accuracy. 2) Inter-landmark collaboration. A confidence-based landmark detection strategy is proposed to improve the detection accuracy of “difficult-to-detect” landmarks by using spatial guidance from “easy-to-detect” landmarks. To evaluate our method, we conducted experiments extensively on three datasets for detecting prostate landmarks and head & neck landmarks in computed tomography (CT) images, and also dental landmarks in cone beam computed tomography (CBCT) images. The results show the effectiveness of our collaborative landmark detection framework in improving landmark detection accuracy, compared to other state-of-the-art methods. PMID:26579736

  10. Collaborative regression-based anatomical landmark detection

    NASA Astrophysics Data System (ADS)

    Gao, Yaozong; Shen, Dinggang

    2015-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2010-10-01

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

  13. Daytime Water Detection Based on Sky Reflections

    NASA Technical Reports Server (NTRS)

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

    2011-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-03-01

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

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

    PubMed

    Zhou, Jinzhi; Tang, Xiaofang

    2015-08-01

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

  16. Optical-Correlator Neural Network Based On Neocognitron

    NASA Technical Reports Server (NTRS)

    Chao, Tien-Hsin; Stoner, William W.

    1994-01-01

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

  17. Pedestrian detection based on redundant wavelet transform

    NASA Astrophysics Data System (ADS)

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

    2016-10-01

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

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

    NASA Technical Reports Server (NTRS)

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

    1978-01-01

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

  19. GaAs-based photorefractive time-integrating correlator

    NASA Technical Reports Server (NTRS)

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

    1992-01-01

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

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

    NASA Technical Reports Server (NTRS)

    Ulbrich, N.; Volden, T.

    2014-01-01

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

  1. Recent advances in biosensor based endotoxin detection.

    PubMed

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

    2014-01-15

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-08-01

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

  3. Immunity-Based Aircraft Fault Detection System

    NASA Technical Reports Server (NTRS)

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

    2004-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Shen, Yan-lin; Tu, Ya-qing

    2016-06-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-12-01

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

  6. Laser-based detection of chemical contraband

    NASA Astrophysics Data System (ADS)

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

    1997-02-01

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

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

    PubMed

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

    2005-03-01

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

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

    NASA Astrophysics Data System (ADS)

    Ontiveros-Gallardo, Sergio E.; Kober, Vitaly

    2016-09-01

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

  9. On event-based optical flow detection

    PubMed Central

    Brosch, Tobias; Tschechne, Stephan; Neumann, Heiko

    2015-01-01

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

  10. Head tracker based on a compact optical correlator

    NASA Astrophysics Data System (ADS)

    Wilkinson, Tim D.; New, Nicholas J.

    2001-08-01

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

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

    PubMed Central

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

    2014-01-01

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

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

    PubMed

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

    2011-04-01

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

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

    ERIC Educational Resources Information Center

    Kirby, Peggy C.; Abernathy, Mari W.

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

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

    ERIC Educational Resources Information Center

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

    2006-01-01

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

  15. Water Detection Based on Sky Reflections

    NASA Technical Reports Server (NTRS)

    Rankin, Arturo L.; Matthies, Larry H.

    2010-01-01

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

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

    PubMed

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

    2017-02-01

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

  17. Mine detection training based on expert skill

    NASA Astrophysics Data System (ADS)

    Staszewski, James J.; Davison, Alan

    2000-08-01

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

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

    SciTech Connect

    Mao, Kanmi

    2011-01-01

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

  19. Light Scattering based detection of food pathogens

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

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

    NASA Astrophysics Data System (ADS)

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

    2009-06-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2001-08-01

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

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

    NASA Astrophysics Data System (ADS)

    Guckes, Amber; Barzilov, Alexander; Richardson, Norman

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

  3. Water Detection Based on Object Reflections

    NASA Technical Reports Server (NTRS)

    Rankin, Arturo L.; Matthies, Larry H.

    2012-01-01

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

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

    PubMed

    Stoykova, Elena; Ivanov, Branimir; Nikova, Tania

    2014-01-01

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

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

    PubMed

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

    2009-12-01

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

  6. Mutation detection in plasmid-based biopharmaceuticals.

    PubMed

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

    2011-04-01

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

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

    NASA Technical Reports Server (NTRS)

    Menyuk, N.; Killinger, D. K.

    1981-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2011-07-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-07-01

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

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

    NASA Astrophysics Data System (ADS)

    Shi, Zhiping; Yan, Bing

    2010-08-01

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

  11. GPU Based Software Correlators - Perspectives for VLBI2010

    NASA Technical Reports Server (NTRS)

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

    2010-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Smith, Rachel Clara

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

  13. Future enhancements to ground-based microburst detection

    NASA Technical Reports Server (NTRS)

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

    1994-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-10-01

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

  15. Nanomaterials based biosensors for cancer biomarker detection

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2011-08-01

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

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

    NASA Astrophysics Data System (ADS)

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

    1982-11-01

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

  18. Skeleton-Based Abnormal Gait Detection.

    PubMed

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

    2016-10-26

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

  19. Skeleton-Based Abnormal Gait Detection

    PubMed Central

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

    2016-01-01

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

  20. Water Detection Based on Color Variation

    NASA Technical Reports Server (NTRS)

    Rankin, Arturo L.

    2012-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2008-10-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-08-01

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

  3. SERS-based detection of biomolecules

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  4. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2013-08-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

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

    PubMed

    Wagner, J W

    1981-10-15

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

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

    PubMed Central

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

    2016-01-01

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

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

    SciTech Connect

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

    2010-09-02

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

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

    PubMed

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

    2016-09-30

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

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

    PubMed

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

    2010-09-03

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

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

    USGS Publications Warehouse

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

    2013-01-01

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

  13. Raman LIDAR Detection of Cloud Base

    NASA Technical Reports Server (NTRS)

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

    1999-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

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

    PubMed

    Arunajadai, Srikesh G; Cheng, Wei

    2013-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2011-06-01

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

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

    NASA Technical Reports Server (NTRS)

    Fortunato, G.

    1979-01-01

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

  18. Biotoxin Detection Using Cell-Based Sensors

    PubMed Central

    Banerjee, Pratik; Kintzios, Spyridon; Prabhakarpandian, Balabhaskar

    2013-01-01

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

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

    PubMed Central

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

    2016-01-01

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

  20. Fast dual graph-based hotspot detection

    NASA Astrophysics Data System (ADS)

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

    2006-10-01

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

  1. Automated image based prominent nucleoli detection

    PubMed Central

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

    2015-01-01

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

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

    PubMed

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

    2017-02-09

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

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

    PubMed

    Mahmood, Arif; Khan, Sohaib

    2012-04-01

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

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

    NASA Technical Reports Server (NTRS)

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

    1989-01-01

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

  5. Advances in neutron based bulk explosive detection

    NASA Astrophysics Data System (ADS)

    Gozani, Tsahi; Strellis, Dan

    2007-08-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2006-09-01

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

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

    PubMed

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

    2016-01-01

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

  8. 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

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

    NASA Astrophysics Data System (ADS)

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

    2013-09-01

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

  10. NO2 Detection Using Microcantilever Based Potentiometry

    PubMed Central

    Qazi, Muhammad; Koley, Goutam

    2008-01-01

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

  11. NO₂ Detection Using Microcantilever Based Potentiometry.

    PubMed

    Qazi, Muhammad; Koley, Goutam

    2008-11-12

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

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

    PubMed Central

    Rotter, Stefan; Grün, Sonja

    2009-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Saltos, Andrea

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

  14. 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

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

    PubMed

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

    2009-11-26

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

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

    SciTech Connect

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

    2012-04-10

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-03-01

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

  19. Quantum Image Encryption Algorithm Based on Image Correlation Decomposition

    NASA Astrophysics Data System (ADS)

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

    2015-02-01

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

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

    NASA Astrophysics Data System (ADS)

    New, Nicholas J.; Wilkinson, Tim D.

    2001-03-01

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

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

    PubMed

    Li, Hongliang; Liu, Guizhong; Zhang, Zhongwei

    2005-11-01

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

  2. Reset Tree-Based Optical Fault Detection

    PubMed Central

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

    2013-01-01

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

  3. Contour based object detection using part bundles

    PubMed Central

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

    2016-01-01

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

  4. An SPR based sensor for allergens detection.

    PubMed

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

    2017-02-15

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

  5. 3D shape measurement with phase correlation based fringe projection

    NASA Astrophysics Data System (ADS)

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

    2007-06-01

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

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

    PubMed

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

    2005-12-01

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

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed Central

    2016-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

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

    SciTech Connect

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

    2014-02-01

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

  11. Covariance based outlier detection with feature selection.

    PubMed

    Zwilling, Chris E; Wang, Michelle Y

    2016-08-01

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

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

    NASA Astrophysics Data System (ADS)

    Gladilin, Evgeny; Eils, Roland

    2009-02-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-08-01

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

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

    PubMed

    Hiriote, Sasiprapa; Chinchilli, Vernon M

    2011-09-01

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

  15. The correlation-based law of effect1

    PubMed Central

    Baum, William M.

    1973-01-01

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

  16. Phase transition transistors based on strongly-correlated materials

    NASA Astrophysics Data System (ADS)

    Nakano, Masaki

    2013-03-01

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

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

    SciTech Connect

    Paglieroni, David W.

    2016-06-07

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

  18. Waveguide-Based Biosensors for Pathogen Detection

    PubMed Central

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

    2009-01-01

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

  19. Scene change detection based on multimodal integration

    NASA Astrophysics Data System (ADS)

    Zhu, Yingying; Zhou, Dongru

    2003-09-01

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

  20. Laser-Based Pulsed Photoacoustic Ammonia Detection

    NASA Astrophysics Data System (ADS)

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

    2013-09-01

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

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

    NASA Astrophysics Data System (ADS)

    Sun, W.; Fu, L.

    2012-12-01

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

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

    PubMed

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

    2010-12-31

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

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

    PubMed

    Kirchhübel, Christin; Howard, David M

    2013-09-01

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

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

    SciTech Connect

    Paglieroni, David W.; Beer, Reginald N.

    2016-01-19

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

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

    NASA Astrophysics Data System (ADS)

    Caetano, Marco Antonio Leonel; Yoneyama, Takashi

    2012-10-01

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

  6. Brain structure correlates of emotion-based rash impulsivity

    PubMed Central

    Muhlert, N.; Lawrence, A.D.

    2015-01-01

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

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

    SciTech Connect

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

    2016-06-28

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

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

    DOE PAGES

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

    2016-06-28

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

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

    PubMed

    Alm, Magnus; Behne, Dawn

    2014-11-01

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

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

    NASA Astrophysics Data System (ADS)

    Chen, Fang-han; Wang, Wen-sheng

    2011-06-01

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

  11. Digital image correlation-based optical coherence elastography.

    PubMed

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

    2013-12-01

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

  12. Digital image correlation-based optical coherence elastography

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

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

    PubMed

    Yoshitake, Yasuhide; Masani, Kei; Shinohara, Minoru

    2008-08-30

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

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

    PubMed

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

    2012-12-17

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

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

    NASA Astrophysics Data System (ADS)

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

    2010-02-01

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

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

    SciTech Connect

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

    1998-04-01

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

  17. Comic image understanding based on polygon detection

    NASA Astrophysics Data System (ADS)

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

    2013-01-01

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

  18. Smell Detection Agent Based Optimization Algorithm

    NASA Astrophysics Data System (ADS)

    Vinod Chandra, S. S.

    2016-09-01

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

  19. Detecting Soft Errors in Stencil based Computations

    SciTech Connect

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

    2015-05-06

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

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

    NASA Astrophysics Data System (ADS)

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

    2002-04-01

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

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

    PubMed

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

    2016-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-09-01

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

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

    PubMed

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

    2012-02-27

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

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

    PubMed

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

    2015-10-06

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

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed

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

    2011-07-01

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

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

    PubMed

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

    2017-04-06

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

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

    PubMed

    Wang, Yue; Wu, Xintao

    2013-08-01

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

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

    PubMed Central

    Wang, Yue; Wu, Xintao

    2014-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2011-05-01

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

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

    NASA Astrophysics Data System (ADS)

    Trendafilova, I.

    2011-07-01

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

  12. Effects of spatial smoothing on inter-subject correlation based analysis of FMRI.

    PubMed

    Pajula, Juha; Tohka, Jussi

    2014-11-01

    This study evaluates the effects of spatial smoothing on inter-subject correlation (ISC) analysis for FMRI data using the traditional model based analysis as a reference. So far within ISC analysis the effects of smoothing have not been studied systematically and linear Gaussian filters with varying kernel widths have been used without better knowledge about the effects of filtering. Instead, with the traditional general linear model (GLM) based analysis, the effects of smoothing have been studied extensively. In this study, ISC and GLM analyses were computed with two experimental and one simulated block-design datasets. The test statistics and the detected activation areas were compared numerically with correlation and Dice similarity measures, respectively. The study verified that (1) the choice of the filter substantially affected the activations detected by ISC analysis, (2) the detected activations according to ISC and GLM methods were highly similar regardless of the smoothing kernel and (3) the effect of spatial smoothing was mildly smaller on ISC than GLM analysis. Our results indicated that a good selection of the full width at half maximum of the Gaussian smoothing kernel for ISC was slightly larger than double the original voxel size.

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

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2012-01-01

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

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

    Numpacharoen, Kawee; Atsawarungruangkit, Amporn

    2012-01-01

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

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

    PubMed

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

    2013-09-01

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

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

    PubMed

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

    2014-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-07-01

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

  1. 3D Detection, Quantification and Correlation of Slope Failures with Geologic Structure in the Mont Blanc massif

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  2. Ultrafast Target Recognition via Super-Parallel Holograph Based Correlator, RAM and Associative Memory

    DTIC Science & Technology

    2008-03-11

    CORRELATOR In many pattern- recognition and target tracking applications, the speed of the detection system is of critical importance [1-3]. Optical...time target identification and recognition is usually performed by correlating an acquired image with images stored in a database. Current image... recognition and target -tracking applications, the speed of the detection system is of critical importance [1-3]. Optical correlation techniques in which

  3. Improving SVDD classification performance on hyperspectral images via correlation based ensemble technique

    NASA Astrophysics Data System (ADS)

    Uslu, Faruk Sukru; Binol, Hamidullah; Ilarslan, Mustafa; Bal, Abdullah

    2017-02-01

    Support Vector Data Description (SVDD) is a nonparametric and powerful method for target detection and classification. The SVDD constructs a minimum hypersphere enclosing the target objects as much as possible. It has advantages of sparsity, good generalization and using kernel machines. In many studies, different methods have been offered in order to improve the performance of the SVDD. In this paper, we have presented ensemble methods to improve classification performance of the SVDD in remotely sensed hyperspectral imagery (HSI) data. Among various ensemble approaches we have selected bagging technique for training data set with different combinations. As a novel technique for weighting we have proposed a correlation based weight coefficients assignment. In this technique, correlation between each bagged classifier is calculated to give coefficients to weighted combinators. To verify the improvement performance, two hyperspectral images are processed for classification purpose. The obtained results show that the ensemble SVDD has been found to be significantly better than conventional SVDD in terms of classification accuracy.

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

    NASA Astrophysics Data System (ADS)

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

    2013-09-01

    A fiber optic white-light interferometry based on cross-correlation calculation is presented. The detected white-light spectrum signal of fiber optic extrinsic Fabry-Perot interferometric (EFPI) sensor is firstly decomposed by discrete wavelet transform for denoising before interrogating the cavity length of the EFPI sensor. In measurement experiment, the cross-correlation algorithm with multiple-level calculations is performed both for achieving the high measurement resolution and for improving the efficiency of the measurement. The experimental results show that the variation range of the measurement results was 1.265 nm, and the standard deviation of the measurement results can reach 0.375 nm when an EFPI sensor with cavity length of 1500 μm was interrogated.

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

    NASA Astrophysics Data System (ADS)

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

    2016-10-01

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

  6. Lagrangian based methods for coherent structure detection

    SciTech Connect

    Allshouse, Michael R.; Peacock, Thomas

    2015-09-15

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

  7. Intelligent-based Structural Damage Detection Model

    SciTech Connect

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

    2010-05-21

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

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

    SciTech Connect

    Pack, Chan-Gi; Ahn, Sang-Gun

    2015-07-31

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

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

    NASA Astrophysics Data System (ADS)

    Gladilin, Evgeny; Kappel, Constantin; Eils, Roland

    2007-03-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2001-01-01

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

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

    PubMed Central

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

    2011-01-01

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

  12. Ground-Based Detection of Exoatmospheric Calcium

    NASA Astrophysics Data System (ADS)

    Rojo, Patricio M.; Astudillo-Defru, Nicola

    2014-11-01

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

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

    PubMed

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

    2011-01-01

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

  14. Optical cross-correlator based on supercontinuum generation

    SciTech Connect

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

    2006-03-20

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

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

    DTIC Science & Technology

    2002-08-01

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

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

    SciTech Connect

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

    2013-07-01

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

  17. STOCK Market Differences in Correlation-Based Weighted Network

    NASA Astrophysics Data System (ADS)

    Youn, Janghyuk; Lee, Junghoon; Chang, Woojin

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

  18. Dependence-Based Anomaly Detection Methodologies

    DTIC Science & Technology

    2012-08-16

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

  19. Nuclear based techniques for detection of contraband

    SciTech Connect

    Gozani, T.

    1993-12-31

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

  20. Video quality assessment based on correlation between spatiotemporal motion energies

    NASA Astrophysics Data System (ADS)

    Yan, Peng; Mou, Xuanqin

    2016-09-01

    Video quality assessment (VQA) has been a hot research topic because of rapid increase of huge demand of video communications. From the earliest PSNR metric to advanced models that are perceptual aware, researchers have made great progress in this field by introducing properties of human vision system (HVS) into VQA model design. Among various algorithms that model the property of HVS perceiving motion, the spatiotemporal energy model has been validated to be high consistent with psychophysical experiments. In this paper, we take the spatiotemporal energy model into VQA model design by the following steps. 1) According to the pristine spatiotemporal energy model proposed by Adelson et al, we apply the linear filters, which are oriented in space-time and tuned in spatial frequency, to filter the reference and test videos respectively. The outputs of quadrature pairs of above filters are then squared and summed to give two measures of motion energy, which are named rightward and leftward energy responses, respectively. 2) Based on the pristine model, we calculate summation of the rightward and leftward energy responses as spatiotemporal features to represent perceptual quality information for videos, named total spatiotemporal motion energy maps. 3) The proposed FR-VQA model, named STME, is calculated with statistics based on the pixel-wise correlation between the total spatiotemporal motion energy maps of the reference and distorted videos. The STME model was validated on the LIVE VQA Database by comparing with existing FR-VQA models. Experimental results show that STME performs with excellent prediction accuracy and stays in state-of-the-art VQA models.

  1. Laser-based Sensors for Chemical Detection

    SciTech Connect

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

    2010-05-10

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-03-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-01-01

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

  4. GPU-based image registration in aperture correlation microscopy, and reflection mode correlation microscopy

    NASA Astrophysics Data System (ADS)

    Fafchamps, Lionel J.; Neil, Mark A. A.; Juskaitis, Rimas

    2013-02-01

    Aperture Correlation Microscopy (ACM) is a fluorescence microscopy technique capable of depth resolved imaging and enhanced lateral resolution at real-time acquisition rates. It relies on the subtraction of 2 separate images from different cameras which must be registered to the sub-pixel level. In order to achieve real-time registration and subtraction, the graphics processing unit (GPU) is used to apply a transformation from one frame to the other, resulting in a system capable of processing over 200 frames per second on modest hardware (GeForce 330M). Currently, this rate is limited by camera acquision to 16fps. Additionally, a novel reflection mode correlation microscope is introduced which functions on similar principles as the fluorescent system but can be used to examine reflective samples. Images and z-stacks taken with this system are presented here.

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

    PubMed

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

    2008-06-01

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

  6. Dynamical lag correlation exponent based method for gas-solid flow velocity measurement using twin-plane electrical capacitance tomography

    NASA Astrophysics Data System (ADS)

    Xue, Qian; Wang, Huaxiang; Yang, Chengyi; Cui, Ziqiang

    2012-08-01

    In a twin-plane electrical capacitance tomography (ECT) system, velocity measurement of two-phase flow is transformed into the time delay estimation problem, while the nongaussianity and nonstationarity of two-phase flow signals have put the validity of the conventional cross-correlation algorithm in jeopardy. To improve the robustness and reliability of flow velocity measurement, an alternative method is proposed based on the dynamical lag correlation exponent and applied to coal ash measurement in a pneumatic pipeline. Different from the cross-correlation method which picks the peak point of the cross-correlation function as the delayed frames between the upstream and downstream signals, the proposed method determines the delayed frames by finding the minimum point of the dynamical lag correlation exponent. The preliminary results of flow velocity measurement indicate that the proposed method is capable of detecting various velocities (8-25 m s-1), which is useful for monitoring and predicting flow instability.

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

    DOEpatents

    Craig, William W.; Labov, Simon E.

    2009-06-09

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

  8. Ground-based Detection of Exoatmospheric Calcium

    NASA Astrophysics Data System (ADS)

    Rojo, P.; Astudillo-Defru, N.

    2014-03-01

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

  9. Detection of cm to sub-mm band radio and gamma-ray correlated variability in Fermi bright blazars

    NASA Astrophysics Data System (ADS)

    Fuhrmann, Lars; Larsson, S.; Chiang, J.; Angelakis, E.; Zensus, A.; F-GAMMA Team; Fermi Collaboration

    2014-01-01

    The exact location of the gamma-ray emitting region in blazars is still controversial. In order to attack this problem we performed a detailed statistical cross-correlation analysis between radio (cm/mm/sub-mm wavelengths, F-GAMMA program) and gamma-ray 3.5 year light curves of 54 Fermi bright blazars. In this talk, the main results of this analysis are highlighted including the first significant detection of multi-band radio/gamma-ray correlations using a stacking analysis. The radio bands are usually lagging the gamma rays with average time delays (source frame) ranging between 76+/-23 and 7+/-9 days, systematically decreasing from cm to mm/sub-mm bands following a power-law frequency dependence. The latter is in good agreement with synchrotron self-absorption dominated opacity effects, whereas a (positive) time lag of 12+/-8 days at 3 mm strongly suggests that the bulk gamma-ray production region is usually located within or even upstream of the innermost mm core region of these sources. Based on our findings we finally demonstrate that the gamma-ray emitting region of quasar 3C 454.3 is located at a distance of > 0.8-1.6 pc from the central supermassive black hole, i.e. at the outer edge of the Broad Line Region or beyond.

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

    PubMed Central

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

    2014-01-01

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

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

    SciTech Connect

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

    1993-11-01

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

  12. Onboard and Parts-based Object Detection from Aerial Imagery

    DTIC Science & Technology

    2011-09-01

    reduced operator workload. Additionally, a novel parts- based detection method was developed. A whole-object detector is not well suited for deformable and...reduced operator workload. Additionally, a novel parts- based detection method was developed. A whole-object detector is not well suited for deformable and...Methodology This chapter details the challenges of transitioning from ground station processing to onboard processing, the part- based detection method

  13. Seismic wave detection system based on fully distributed acoustic sensing

    NASA Astrophysics Data System (ADS)

    Jiang, Yue; Xu, Tuanwei; Feng, Shengwen; Huang, Jianfen; Yang, Yang; Guo, Gaoran; Li, Fang

    2016-11-01

    This paper presents a seismic wave detection system based on fully distributed acoustic sensing. Combined with Φ- OTDR and PGC demodulation technology, the system can detect and acquire seismic wave in real time. The system has a frequency response of 3.05 dB from 5 Hz to 1 kHz, whose sampling interval of each channel of 1 meter on total sensing distance up to 10 km. By comparing with the geophone in laboratory, the data show that in the time domain and frequency domain, two waveforms coincide consistently, and the correlation coefficient could be larger than 0.98. Through the analysis of the data of the array experiment and the oil well experiment, DAS system shows a consistent time domain and frequency domain response and a clearer trail of seismic wave signal as well as a higher signal-noise rate which indicate that the system we proposed is expected to become the next generation of seismic exploration equipment.

  14. Cavitating vortex characterization based on acoustic signal detection

    NASA Astrophysics Data System (ADS)

    Digulescu, A.; Murgan, I.; Candel, I.; Bunea, F.; Ciocan, G.; Bucur, D. M.; Dunca, G.; Ioana, C.; Vasile, G.; Serbanescu, A.

    2016-11-01

    In hydraulic turbines operating at part loads, a cavitating vortex structure appears at runner outlet. This helical vortex, called vortex rope, can be cavitating in its core if the local pressure is lower that the vaporization pressure. An actual concern is the detection of the cavitation apparition and the characterization of its level. This paper presents a potentially innovative method for the detection of the cavitating vortex presence based on acoustic methods. The method is tested on a reduced scale facility using two acoustic transceivers positioned in ”V” configuration. The received signals were continuously recorded and their frequency content was chosen to fit the flow and the cavitating vortex. Experimental results showed that due to the increasing flow rate, the signal - vortex interaction is observed as modifications on the received signal's high order statistics and bandwidth. Also, the signal processing results were correlated with the data measured with a pressure sensor mounted in the cavitating vortex section. Finally it is shown that this non-intrusive acoustic approach can indicate the apparition, development and the damping of the cavitating vortex. For real scale facilities, applying this method is a work in progress.

  15. Meson production based on the Thomson energy correlation

    SciTech Connect

    Aspden, H.

    1986-07-01

    Attention is drawn to a remarkable energy correlation which uniquely determines the rest-mass energies of all the intermediate particles in the electron-proton energy spectrum. The correlation formula uses a classical expression formulated by J. J. Thomson, which represents the charge of a particle as confined within a sphere of radius 2e/sup 2//3mc/sup 2/.

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

    PubMed

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

    2010-08-15

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

  17. Nanopore-Based Target Sequence Detection

    PubMed Central

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

    2016-01-01

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

  18. Biosensor based on Butyrylcholinesterase for Detection of Carbofuran

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  19. Correlation-based Transition Modeling for External Aerodynamic Flows

    NASA Astrophysics Data System (ADS)

    Medida, Shivaji

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

  20. Antibody-based biological toxin detection

    SciTech Connect

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

    1995-12-01

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

  1. Adaptive skin detection based on online training

    NASA Astrophysics Data System (ADS)

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

    2007-11-01

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

  2. Antibody-based bacterial toxin detection

    NASA Astrophysics Data System (ADS)

    Menking, Darrell E.; Heitz, Jonathon M.; Anis, Nabil A.; Thompson, Roy G.

    1994-03-01

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

  3. Correlation of Aggregatibacter actinomycetemcomitans Detection with Clinical/Immunoinflammatory Profile of Localized Aggressive Periodontitis Using a 16S rRNA Microarray Method: A Cross-Sectional Study

    PubMed Central

    Gonçalves, Patricia F.; Klepac-Ceraj, Vanja; Huang, Hong; Paster, Bruce J.; Aukhil, Ikramuddin; Wallet, Shannon M.; Shaddox, Luciana M.

    2013-01-01

    Objective The objective of this study was to determine whether the detection of Aggregatibacter actinomycetemcomitans (Aa) correlates with the clinical and immunoinflammatory profile of Localized Aggressive Periodontitis (LAP), as determined by by 16S rRNA gene-based microarray. Subjects and Methods Subgingival plaque samples from the deepest diseased site of 30 LAP patients [PD ≥ 5 mm, BoP and bone loss] were analyzed by 16S rRNA gene-based microarrays. Gingival crevicular fluid (GCF) samples were analyzed for 14 cyto/chemokines. Peripheral blood was obtained and stimulated in vitro with P.gingivalis and E.coli to evaluate inflammatory response profiles. Plasma lipopolysaccharide (LPS) levels were also measured. Results Aa was detected in 56% of LAP patients and was shown to be an indicator for different bacterial community structures (p<0.01). Elevated levels of pro-inflammatory cyto/chemokines were detected in LPS-stimulated blood samples in both Aa-detected and Aa-non-detected groups (p>0.05). Clinical parameters and serum LPS levels were similar between groups. However, Aa-non-detected GCF contained higher concentration of IL-8 than Aa-detected sites (p<0.05). TNFα and IL1β were elevated upon E.coli LPS stimulation of peripheral blood cells derived from patients with Aa-detected sites. Conclusions Our findings demonstrate that the detection of Aa in LAP affected sites, did not correlate with clinical severity of the disease at the time of sampling in this cross-sectional study, although it did associate with lower local levels of IL-8, a different subgingival bacterial profile and elevated LPS-induced levels of TNFα and IL1β. PMID:24376864

  4. Decision optimization for face recognition based on an alternate correlation plane quantification metric.

    PubMed

    Alfalou, A; Brosseau, C; Katz, P; Alam, M S

    2012-05-01

    We consider a new approach for enhancing the discrimination performance of the VanderLugt correlator. Instead of trying to optimize the correlation filter, or propose a new decision correlation peak detection criterion, we propose herein to denoise the correlation plane before applying the peak-to-correlation energy (PCE) criterion. For that purpose, we use a linear functional model to express a given correlation plane as a linear combination of the correlation peak, noise, and residual components. The correlation peak is modeled using an orthonormalized function and the singular value decomposition method. A set of training correlation planes is then selected to create the correlation noise components. Finally, an optimized correlation plane is reconstructed while discarding the noise components. Independently of the filter correlation used, this technique denoises the correlation plane by lowering the correlation noise magnitude in case of true correlation and decreases the false alarm rate when the target image does not belong to the desired class. Test results are presented, using a composite filter and a face recognition application, to verify the effectiveness of the proposed technique.

  5. Fractal-based image edge detection

    NASA Astrophysics Data System (ADS)

    Luo, Huiguo; Zhu, Yaoting; Zhu, Guang-Xi; Wan, Faguang; Zhang, Ping

    1993-08-01

    Image edge is an important feature of image. Usually, we use Laplacian or Sober operator to get an image edge. In this paper, we use fractal method to get the edge. After introducing Fractal Brownian Random (FBR) field, we give the definition of Discrete Fractal Brownian Increase Random (DFBIR) field and discuss its properties, then we apply the DFBIR field to detect the edge of an image. According to the parameters H and D of DFBIR, we give a measure M equals (alpha) H + (beta) D. From the M value of each pixel, we can detect the edge of image.

  6. Effects of model-based physiological noise correction on default mode network anti-correlations and correlations.

    PubMed

    Chang, Catie; Glover, Gary H

    2009-10-01

    Previous studies have reported that the spontaneous, resting-state time course of the default-mode network is negatively correlated with that of the "task-positive network", a collection of regions commonly recruited in demanding cognitive tasks. However, all studies of negative correlations between the default-mode and task-positive networks have employed some form of normalization or regression of the whole-brain average signal ("global signal"); these processing steps alter the time series of voxels in an uninterpretable manner as well as introduce spurious negative correlations. Thus, the extent of negative correlations with the default mode network without global signal removal has not been well characterized, and it is has recently been hypothesized that the apparent negative correlations in many of the task-positive regions could be artifactually induced by global signal pre-processing. The present study aimed to examine negative and positive correlations with the default-mode network when model-based corrections for respiratory and cardiac noise are applied in lieu of global signal removal. Physiological noise correction consisted of (1) removal of time-locked cardiac and respiratory artifacts using RETROICOR (Glover, G.H., Li, T.Q., Ress, D., 2000. Image-based method for retrospective correction of physiological motion effects in fMRI: RETROICOR. Magn. Reson. Med. 44, 162-167), and (2) removal of low-frequency respiratory and heart rate variations by convolving these waveforms with pre-determined transfer functions (Birn et al., 2008; Chang et al., 2009) and projecting the resulting two signals out of the data. It is demonstrated that negative correlations between the default-mode network and regions of the task-positive network are present in the majority of individual subjects both with and without physiological noise correction. Physiological noise correction increased the spatial extent and magnitude of negative correlations, yielding negative

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

    PubMed

    Kleinberg, Bennett; Verschuere, Bruno

    2015-01-01

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

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

    PubMed Central

    Kleinberg, Bennett; Verschuere, Bruno

    2015-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-08-01

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

  11. Automatic background updating for video-based vehicle detection

    NASA Astrophysics Data System (ADS)

    Hu, Chunhai; Li, Dongmei; Liu, Jichuan

    2008-03-01

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

  12. Statistical and spatiotemporal correlation based low-complexity video coding for high-efficiency video coding

    NASA Astrophysics Data System (ADS)

    Shang, Xiwu; Wang, Guozhong; Fan, Tao; Li, Yan

    2015-03-01

    High-efficiency video coding (HEVC) is a new coding standard that adopts the quadtree splitting structure based on coding tree units instead of macroblocks, and can support more coding modes and more partitions. Although it can improve compression efficiency, the flexible quadtree block partition and mode selection result in high computational complexity in real-time applications. We propose a low-complexity video coding algorithm for HEVC by utilizing statistical correlation and spatiotemporal correlation, which consists of an early determination of SKIP mode (EDSM) method and an early termination of reference frame selection (ETRFS) method. Since there is a strong correlation for the rate distortion (RD) cost for the SKIP mode between adjacent frames, EDSM detects the SKIP mode according to the threshold derived from the former training frame. Meanwhile, ETRFS terminates the process of reference frame selection using the motion vector and reference frame information from neighboring blocks to skip unnecessary candidate frames. Experimental results demonstrate that the proposed method can achieve about 45.01% complexity reduction on average with a 1.11% BD-rate increase and 0.04 BD-PSNR decrease for random access. The complexity reduction, BD-rate increase, and BD-PSNR decrease for low delay are 46.16%, 0.99%, and 0.03, respectively.

  13. Vibration-Based Damage Detection in Rotating Machinery

    SciTech Connect

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

    1999-06-28

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

  14. Neural Correlates of Familiarity-Based Associative Retrieval

    ERIC Educational Resources Information Center

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

    2010-01-01

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

  15. Tests of Fit Based on the Correlation Coefficient

    DTIC Science & Technology

    1990-10-04

    function. Regional Conference Series in Appl. Math., 9. Philadelphia: SIAM. 2. Gerlach, B., (1979). A consistent correlation-type goodness-of-fit test; with...the distribution of quadratic forms in normal variables. Biometrika, 48, 419-426. 4. Sarkadi, K., (1975). The consistency of the Shapiro- Francia test

  16. Clustering and information in correlation based financial networks

    NASA Astrophysics Data System (ADS)

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

    2004-03-01

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

  17. On Bitstream Based Edge Detection Techniques

    DTIC Science & Technology

    2009-01-01

    IEEE Transactions on, vol. 38, no. 1, pp. xviii– iv, Feb 1992. [5] Rafael C. Gonzalez and Richard E. Woods, Digital Image Processing, Addison-Wesley...Carmona-Poyato, R. Medina- Carnicer, and F. J. Madrid- Cuevas , “Automatic genera- tion of consensus ground truth for the comparison of edge detection techniques,” Image Vision Comput., vol. 26, no. 4, pp. 496–511, 2008.

  18. Daytime Water Detection Based on Color Variation

    NASA Technical Reports Server (NTRS)

    Rankin, Arturo L.; Matthies, Larry H.

    2010-01-01

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

  19. Fake fingerprint detection based on image analysis

    NASA Astrophysics Data System (ADS)

    Jin, Sang-il; Bae, You-suk; Maeng, Hyun-ju; Lee, Hyun-suk

    2010-01-01

    Fingerprint recognition systems have become prevalent in various security applications. However, recent studies have shown that it is not difficult to deceive the system with fake fingerprints made of silicon or gelatin. The fake fingerprints have almost the same ridge-valley patterns as ones of genuine fingerprints so that conventional systems are unable to detect fake fingerprints without a particular detection method. Many previous works against fake fingers required extra sensors; thus, they lacked practicality. This paper proposes a practical and effective method that detects fake fingerprints, using only an image sensor. Two criteria are introduced to differentiate genuine and fake fingerprints: the histogram distance and Fourier spectrum distance. In the proposed method, after identifying an input fingerprint of a user, the system computes two distances between the input and the reference that comes from the registered fingerprints of the user. Depending on the two distances, the system classifies the input as a genuine fingerprint or a fake. In the experiment, 2,400 fingerprint images including 1,600 fakes were tested, and the proposed method has shown a high recognition rate of 95%. The fake fingerprints were all accepted by a commercial system; thus, the use of these fake fingerprints qualifies the experiment.

  20. Parkinson's disease detection based on dysphonia measurements

    NASA Astrophysics Data System (ADS)

    Lahmiri, Salim

    2017-04-01

    Assessing dysphonic symptoms is a noninvasive and effective approach to detect Parkinson's disease (PD) in patients. The main purpose of this study is to investigate the effect of different dysphonia measurements on PD detection by support vector machine (SVM). Seven categories of dysphonia measurements are considered. Experimental results from ten-fold cross-validation technique demonstrate that vocal fundamental frequency statistics yield the highest accuracy of 88 % ± 0.04. When all dysphonia measurements are employed, the SVM classifier achieves 94 % ± 0.03 accuracy. A refinement of the original patterns space by removing dysphonia measurements with similar variation across healthy and PD subjects allows achieving 97.03 % ± 0.03 accuracy. The latter performance is larger than what is reported in the literature on the same dataset with ten-fold cross-validation technique. Finally, it was found that measures of ratio of noise to tonal components in the voice are the most suitable dysphonic symptoms to detect PD subjects as they achieve 99.64 % ± 0.01 specificity. This finding is highly promising for understanding PD symptoms.

  1. Goal-dependent modulation of declarative memory: neural correlates of temporal recency decisions and novelty detection.

    PubMed

    Dudukovic, Nicole M; Wagner, Anthony D

    2007-06-18

    Declarative memory allows an organism to discriminate between previously encountered and novel items, and to place past encounters in time. Numerous imaging studies have investigated the neural processes supporting item recognition, whereas few have examined retrieval of temporal information. In the present study, functional magnetic resonance imaging (fMRI) was conducted while subjects engaged in temporal recency and item novelty decisions. Subjects encountered three-alternative forced-choice retrieval trials, each consisting of two words from a preceding study phase and one novel word, and were instructed to either identify the novel item (Novelty trials) or the more recently presented study item (Recency trials). Relative to correct Novelty decisions, correct Recency decisions elicited greater activation in a network of left-lateralized regions, including frontopolar and dorsolateral prefrontal cortex and intraparietal sulcus. A conjunction analysis revealed that these left-lateralized regions overlapped with those previously observed to be engaged during source recollection versus novelty detection, suggesting that during Recency trials subjects attempted to recollect event details. Consistent with this interpretation, correct Recency decisions activated posterior hippocampus and parahippocampal cortex, whereas incorrect Recency decisions elicited greater anterior cingulate activation. The magnitude of this latter effect positively correlated with activation in right dorsolateral prefrontal cortex. Finally, correct Novelty decisions activated the anterior medial temporal lobe to a greater extent than did correct Recency decisions, suggesting that medial temporal novelty responses are not obligatory but rather can be modulated by the goal-directed allocation of attention. Collectively, these findings advance understanding of how subjects strategically engage frontal and parietal mechanisms in the service of attempting to remember the temporal order of events

  2. Detection of interaural correlation by neurons in the superior olivary complex, inferior colliculus and auditory cortex of the unanesthetized rabbit.

    PubMed

    Coffey, Charles S; Ebert, Charles S; Marshall, Allen F; Skaggs, John D; Falk, Stephanie E; Crocker, William D; Pearson, James M; Fitzpatrick, Douglas C

    2006-11-01

    A critical binaural cue important for sound localization and detection of signals in noise is the interaural time difference (ITD), or difference in the time of arrival of sounds at each ear. The ITD can be determined by cross-correlating the sounds at the two ears and finding the ITD where the correlation is maximal. The amount of interaural correlation is affected by properties of spaces and can therefore be used to assess spatial attributes. To examine the neural basis for sensitivity to the overall level of the interaural correlation, we identified subcollicular neurons and neurons in the inferior colliculus (IC) and auditory cortex of unanesthetized rabbits that were sensitive to ITDs and examined their responses as the interaural correlation was varied. Neurons at each brain level could show linear or non-linear responses to changes in interaural correlation. The direction of the non-linearities in most neurons was to increase the slope of the response change for correlations near 1.0. The proportion of neurons with non-linear responses was similar in subcollicular and IC neurons but increased in the auditory cortex. Non-linear response functions to interaural correlation were not related to the type of response as determined by the tuning to ITDs across frequencies. The responses to interaural correlation were also not related to the frequency tuning of the neuron, unlike the responses to ITD, which broadens for neurons tuned to lower frequencies. The neural discriminibility of the ITD using frozen noise in the best neurons was similar to the behavioral acuity in humans at a reference correlation of 1.0. However, for other reference ITDs the neural discriminibility was more linear and generally better than the human discriminibility of the interaural correlation, suggesting that stimulus rather than neural variability is the basis for the decline in human performance at lower levels of interaural correlation.

  3. Correlation of satellite lightning observations with ground-based lightning experiments in Florida, Texas and Oklahoma

    NASA Technical Reports Server (NTRS)

    Edgar, B. C.; Turman, B. N.

    1982-01-01

    Satellite observations of lightning were correlated with ground-based measurements of lightning from data bases obtained at three separate sites. The percentage of ground-based observations of lightning that would be seen by an orbiting satellite was determined.

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

    PubMed Central

    2011-01-01

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

  5. Neutron Detection with Water Cerenkov Based Detectors

    SciTech Connect

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

    2009-05-13

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-05-01

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

  7. Malfunction diagnosis of sensors based on correlation of measurements

    NASA Astrophysics Data System (ADS)

    Lu, Wei; Teng, Jun; Wen, Runfa; Zhu, Jiayi; Li, Chao

    2017-02-01

    Structural health monitoring (SHM) is a type of on-site characterization of a real-world full-scale structure that is subjected to the real-world load cases. The fundamental element of SHM is the structural response measurements by sensors, the reliability of which is significant for safety assessment and other SHM applications. The paper proposed a method to diagnosis the fault in sensors using the correlation of measurements. The correlation of the variations of the measurements is examined using the sliding time windows, which is the principle to determine the fault in the sensors. The strain measurements from the SHM system of a real world structure, Shenzhen Bay Stadium, are performed to simulate the faults in sensors and to verify the effectiveness of the proposed method.

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

    PubMed

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

    2014-05-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

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

    PubMed Central

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

    2016-01-01

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

  11. Background-Error Correlation Model Based on the Implicit Solution of a Diffusion Equation

    DTIC Science & Technology

    2010-01-01

    1 Background- Error Correlation Model Based on the Implicit Solution of a Diffusion Equation Matthew J. Carrier* and Hans Ngodock...4. TITLE AND SUBTITLE Background- Error Correlation Model Based on the Implicit Solution of a Diffusion Equation 5a. CONTRACT NUMBER 5b. GRANT...2001), which sought to model error correlations based on the explicit solution of a generalized diffusion equation. The implicit solution is

  12. Extracting Coherent Information from Noise Based Correlation Processing

    DTIC Science & Technology

    2013-09-30

    correlations [1]. 3 CTBT result: The acoustic data is from the 2004 Great Sumatra earthquake as monitored on the IMS triad array in the Indian Ocean ...opportunity was selected from the Diego-Garcia CTBT IMS hydroiacoustic triad in the Indian Ocean and converted to vector quantities and then favorably compared...GOALS The goal of this research is to establish methodologies to utilize ambient noise in the ocean and to determine what scenarios are best suited

  13. Extracting Coherent Information from Noise Based Correlation Processing

    DTIC Science & Technology

    2014-09-30

    LONG-TERM GOALS The goal of this research is to establish methodologies to utilize ambient noise in the ocean and to determine what scenarios...is a spinoff from a fish tank experiment in which our noise correlation methods were applied to the buildings ambient vibrations in which the...tank was located. We showed that we were able to determind the acoustical properties of tank from this ambient noise. This work has been reported in

  14. Extracting Coherent Information from Noise Based Correlation Processing

    DTIC Science & Technology

    2015-09-30

    signal processing that overcome the effects of the fluctuating ocean by essentilly developing techniques that speed up the processing to time scales...appropriate signal processing methods. WORK COMPLETED There have been two thrusts –the first has been related to extending the range/ valdity of the...Correlation Processing W. A. Kuperman and W. S. Hodgkiss Marine Physical Laboratory of the Scripps Institution of Ocenaography Univeritiy of

  15. Real-Time Optical Correlator Based On GaAs

    NASA Technical Reports Server (NTRS)

    Liu, Tsuen-Hsi; Cheng, Li-Jen

    1992-01-01

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

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

    PubMed Central

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

    2009-01-01

    In this article, we show the potential for utilizing proton-detected heteronuclear single quantum correlation (HSQC) NMR in rigid solids under ultra-fast magic angle spinning (MAS) conditions. The indirect detection of carbon-13 from coupled neighboring hydrogen nuclei provides a sensitivity enhancement of 3 - 4 fold in crystalline amino acids over direct-detected versions. Furthermore, the sensitivity enhancement is shown to be significantly larger for disordered solids that display inhomogeneously broadened carbon-13 spectra. Latrodectus hesperus (Black Widow) dragline silk is given as an example where the sample is mass-limited and the sensitivity enhancement for the proton-detected experiment is 8 - 13 fold. The ultra-fast MAS proton-detected HSQC solid-state NMR technique has the added advantage that no proton homonuclear decoupling is applied during the experiment. Further, well-resolved, indirectly observed carbon-13 spectra can be obtained in some cases without heteronuclear proton decoupling. PMID:19857977

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

    PubMed

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

    2010-01-01

    In this article, we show the potential for utilizing proton-detected heteronuclear single quantum correlation (HSQC) NMR in rigid solids under ultra-fast magic angle spinning (MAS) conditions. The indirect detection of carbon-13 from coupled neighboring hydrogen nuclei provides a sensitivity enhancement of 3- to 4-fold in crystalline amino acids over direct-detected versions. Furthermore, the sensitivity enhancement is shown to be significantly larger for disordered solids that display inhomogeneously broadened carbon-13 spectra. Latrodectus hesperus (Black Widow) dragline silk is given as an example where the sample is mass-limited and the sensitivity enhancement for the proton-detected experiment is 8- to 13-fold. The ultra-fast MAS proton-detected HSQC solid-state NMR technique has the added advantage that no proton homonuclear decoupling is applied during the experiment. Further, well-resolved, indirectly observed carbon-13 spectra can be obtained in some cases without heteronuclear proton decoupling.

  18. Retinal imaging analysis based on vessel detection.

    PubMed

    Jamal, Arshad; Hazim Alkawaz, Mohammed; Rehman, Amjad; Saba, Tanzila

    2017-03-13

    With an increase in the advancement of digital imaging and computing power, computationally intelligent technologies are in high demand to be used in ophthalmology cure and treatment. In current research, Retina Image Analysis (RIA) is developed for optometrist at Eye Care Center in Management and Science University. This research aims to analyze the retina through vessel detection. The RIA assists in the analysis of the retinal images and specialists are served with various options like saving, processing and analyzing retinal images through its advanced interface layout. Additionally, RIA assists in the selection process of vessel segment; processing these vessels by calculating its diameter, standard deviation, length, and displaying detected vessel on the retina. The Agile Unified Process is adopted as the methodology in developing this research. To conclude, Retina Image Analysis might help the optometrist to get better understanding in analyzing the patient's retina. Finally, the Retina Image Analysis procedure is developed using MATLAB (R2011b). Promising results are attained that are comparable in the state of art.

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

    ERIC Educational Resources Information Center

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

    2012-01-01

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

  20. 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.

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

    PubMed

    Shukla, Ashish; Macchiarulo, Luca

    2008-01-01

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

  2. Sequential Bayesian Detection: A Model-Based Approach

    SciTech Connect

    Sullivan, E J; Candy, J V

    2007-08-13

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

  3. Sequential Bayesian Detection: A Model-Based Approach

    SciTech Connect

    Candy, J V

    2008-12-08

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

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

    PubMed

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

    2016-08-01

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

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

    NASA Astrophysics Data System (ADS)

    Kumar, Munesh; Siddique, Shoaib; Noor, Humera

    2009-04-01

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

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

    NASA Astrophysics Data System (ADS)

    Fu, Hongwei; Li, Dongguang; Zhang, Xinyuan

    2008-12-01

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

  7. Aptamer-Based Technologies in Foodborne Pathogen Detection

    PubMed Central

    Teng, Jun; Yuan, Fang; Ye, Yingwang; Zheng, Lei; Yao, Li; Xue, Feng; Chen, Wei; Li, Baoguang

    2016-01-01

    Aptamers are single stranded DNA or RNA ligands, which can be selected by a method called systematic evolution of ligands by exponential enrichment (SELEX); and they can specifically recognize and bind to their targets. These unique characteristics of aptamers offer great potentials in applications such as pathogen detection and biomolecular screening. Pathogen detection is the critical means in detecting and identifying the problems related to public health and food safety; and only the rapid, sensitive and efficient detection technologies can enable the users to make the accurate assessments on the risks of infections (humans and animals) or contaminations (foods and other commodities) caused by various pathogens. This article reviews the development in the field of the aptamer-based approaches for pathogen detection, including whole-cell SELEX and Genomic SELEX. Nowadays, a variety of aptamer-based biosensors have been developed for pathogen detection. Thus, in this review, we also cover the development in aptamer-based biosensors including optical biosensors for multiple pathogen detection by multiple-labeling or label-free models such as fluorescence detection and surface plasmon resonance, electrochemical biosensors and lateral chromatography test strips, and their applications in pathogen detection and biomolecular screening. While notable progress has been made in the field in the last decade, challenges or drawbacks in their applications such as pathogen detection and biomolecular screening remain to be overcome. PMID:27672383

  8. REVIEW OF METHODS OF OPTICAL GAS Detection by Direct Optical Spectroscopy, with Emphasis on Correlation Spectroscopy

    NASA Astrophysics Data System (ADS)

    Dakin, John P.; Chambers, Paul

    This chapter reviews the development of optical gas sensors, starting with an initial emphasis on optical-fibre remoted techniques and finishing with a particular focus on our own group's work on highly selective methods using correlation spectroscopy. This latter section includes extensive theoretical modelling of a correlation spectroscopy method, and compares theory with practice for a CO2 sensor.

  9. Local-hybrid functional based on the correlation length

    SciTech Connect

    Johnson, Erin R.

    2014-09-28

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

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

    PubMed Central

    Siegel, Nisan; Storrie, Brian; Bruce, Marc

    2016-01-01

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

  11. Laser Spot Detection Based on Reaction Diffusion

    PubMed Central

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

    2016-01-01

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

  12. Laser Spot Detection Based on Reaction Diffusion.

    PubMed

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

    2016-03-01

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

  13. Correlated Attack Modeling (CAM)

    DTIC Science & Technology

    2003-10-01

    eywell’s Scyllarus correlation framework [18], and a simulated-annealing-based approach for detecting stealthy portscans [35]. For detecting multistep...California, May 12–15, 2002. [35] S. Staniford, J. A. Hoagland, and J. M. McAlerney. Practical automated detection of stealthy portscans . Journal of

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

    SciTech Connect

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

    2008-11-10

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

  15. Nonlinear ultrasonic measurements based on cross-correlation filtering techniques

    NASA Astrophysics Data System (ADS)

    Yee, Andrew; Stewart, Dylan; Bunget, Gheorghe; Kramer, Patrick; Farinholt, Kevin; Friedersdorf, Fritz; Pepi, Marc; Ghoshal, Anindya

    2017-02-01

    Cyclic loading of mechanical components promotes the formation of dislocation dipoles in metals, which can serve as precursors to crack nucleation and ultimately lead to failure. In the laboratory setting, an acoustic nonlinearity parameter has been assessed as an effective indicator for characterizing the progression of fatigue damage precursors. However, the need to use monochromatic waves of medium-to-high acoustic energy has presented a constraint, making it problematic for use in field applications. This paper presents a potential approach for field measurement of acoustic nonlinearity by using general purpose ultrasonic pulser-receivers. Nonlinear ultrasonic measurements during fatigue testing were analyzed by the using contact and immersion pulse-through method. A novel cross-correlation filtering technique was developed to extract the fundamental and higher harmonic waves from the signals. As in the case of the classic harmonic generation, the nonlinearity parameters of the second and third harmonics indicate a strong correlation with fatigue cycles. Consideration was given to potential nonlinearities in the measurement system, and tests have confirmed that measured second harmonic signals exhibit a linear dependence on the input signal strength, further affirming the conclusion that this parameter relates to damage precursor formation from cyclic loading.

  16. Two-Dimensional UV Absorption Correlation Spectroscopy as a Method for the Detection of Thiamethoxam Residue in Tea

    NASA Astrophysics Data System (ADS)

    Zhang, J.; Zhao, Zh.; Wang, L.; Zhu, X.; Shen, L.; Yu, Y.

    2015-05-01

    Two-dimensional correlation spectroscopy (2D-COS) combined with UV absorption spectroscopy was evaluated as a technique for the identification of spectral regions associated with the residues of thiamethoxam in tea. There is only one absorption peak at 275 nm in the absorption spectrum of a mixture of thiamethoxam and tea, which is the absorption peak of tea. Based on 2D-COS, the absorption peak of thiamethoxam at 250 nm is extracted from the UV spectra of the mixture. To determine the residue of thiamethoxam in tea, 250 nm is selected as the measured wavelength, at which the fitting result is as follows: the residual sum of squares is 0.01375, standard deviation R2 is 0.99068, and F value is 426. Statistical analysis shows that there is a significant linear relationship between the concentration of thiamethoxam in tea and the absorbance at 250 nm in the UV spectra of the mixture. Moreover, the average prediction error is 0.0033 and the prediction variance is 0.1654, indicating good predictive result. Thus, the UV absorption spectrum can be used as a measurement method for rapid detection of thiamethoxam residues in tea.

  17. ERP correlates of pitch error detection in complex tone and voice auditory feedback with missing fundamental.

    PubMed

    Behroozmand, Roozbeh; Korzyukov, Oleg; Larson, Charles R

    2012-04-11

    Previous studies have shown that the pitch of a sound is perceived in the absence of its fundamental frequency (F0), suggesting that a distinct mechanism may resolve pitch based on a pattern that exists between harmonic frequencies. The present study investigated whether such a mechanism is active during voice pitch control. ERPs were recorded in response to +200 cents pitch shifts in the auditory feedback of self-vocalizations and complex tones with and without the F0. The absence of the fundamental induced no difference in ERP latencies. However, a right-hemisphere difference was found in the N1 amplitudes with larger responses to complex tones that included the fundamental compared to when it was missing. The P1 and N1 latencies were shorter in the left hemisphere, and the N1 and P2 amplitudes were larger bilaterally for pitch shifts in voice and complex tones compared with pure tones. These findings suggest hemispheric differences in neural encoding of pitch in sounds with missing fundamental. Data from the present study suggest that the right cortical auditory areas, thought to be specialized for spectral processing, may utilize different mechanisms to resolve pitch in sounds with missing fundamental. The left hemisphere seems to perform faster processing to resolve pitch based on the rate of temporal variations in complex sounds compared with pure tones. These effects indicate that the differential neural processing of pitch in the left and right hemispheres may enable the audio-vocal system to detect temporal and spectral variations in the auditory feedback for vocal pitch control.

  18. Accelerator based techniques for contraband detection

    NASA Astrophysics Data System (ADS)

    Vourvopoulos, George

    1994-05-01

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

  19. A new edge detection based on pyramid-structure wavelet transform

    NASA Astrophysics Data System (ADS)

    Yi, Sheng; Cao, Hanqiang; Li, Xutao; Liu, Miao

    2006-05-01

    Many advance image processing, like segmentation and recognition, are based on contour extraction which usually lack of ability to allocate edge precisely in the image of heavy noise with low computation burden. For such problem, in this paper, we proposed a new approach of edge detection based on pyramid-structure wavelet transform. In order to suppress noise and keep good continuity of edge, the proposed edge representation considered both inter-correlations across the multi-scales and intra-correlations within the single-scale. The former one is described by point-wise singularity. The later one is described by the magnitude and ratio of wavelet coefficients in different sub-bands. Based on such edge modeling, the edge point allocation is then complemented in wavelet domain by synthesizing the edge information in multi-scales. The experimental results shows that our approaches achieve the pixel-level edge detection with strong resistant against noise due to scattering in water.

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

    NASA Astrophysics Data System (ADS)

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

    2016-09-01

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

  1. Saliency-based abnormal event detection in crowded scenes

    NASA Astrophysics Data System (ADS)

    Shi, Yanjiao; Liu, Yunxiang; Zhang, Qing; Yi, Yugen; Li, Wenju

    2016-11-01

    Abnormal event detection plays a critical role for intelligent video surveillance, and detection in crowded scenes is a challenging but more practical task. We present an abnormal event detection method for crowded video. Region-wise modeling is proposed to address the inconsistent detected motion of the same object due to different depths of field. Comparing to traditional block-wise modeling, the region-wise method not only can reduce heavily the number of models to be built but also can enrich the samples for training the normal events model. In order to reduce the computational burden and make the region-based anomaly detection feasible, a saliency detection technique is adopted in this paper. By identifying the salient parts of the image sequences, the irrelevant blocks are ignored, which removes the disturbance and improves the detection performance further. Experiments on the benchmark dataset and comparisons with the state-of-the-art algorithms validate the advantages of the proposed method.

  2. Unsupervised abnormality detection using saliency and Retinex based color enhancement.

    PubMed

    Deeba, Farah; Mohammed, Shahed K; Bui, Francis M; Wahid, Khan A

    2016-08-01

    An efficient and automated abnormality detection method can significantly reduce the burden of screening of the enormous visual information resulting from capsule endoscopic procedure. As a pre-processing stage, color enhancement could be useful to improve the image quality and the detection performance. Therefore, in this paper, we have proposed a two-stage automated abnormality detection algorithm. In the first stage, an adaptive color enhancement method based on Retinex theory is applied on the endoscopic images. In the second stage, an efficient salient region detection algorithm is applied to detect the clinically significant regions. The proposed algorithm is applied on a dataset containing images with diverse pathologies. The algorithm can successfully detect a significant percentage of the abnormal regions. From our experiment, it was evident that color enhancement method improves the performance of abnormality detection. The proposed algorithm can achieve a sensitivity of 97.33% and specificity of 79%, higher than state-of-the-art performance.

  3. Research about Memory Detection Based on the Embedded Platform

    NASA Astrophysics Data System (ADS)

    Sun, Hao; Chu, Jian

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

  4. Diffusion Geometry Based Nonlinear Methods for Hyperspectral Change Detection

    DTIC Science & Technology

    2010-05-12

    Schaum and A. Stocker, “Hyperspectral change detection and supervised matched filtering based on covariance equalization,” Proceedings of the SPIE, vol...5425, pp. 77- 90 (2004). 10. A. Schaum and A. Stocker, “Linear chromodynamics models for hyperspectral target detection,” Proceedings of the IEEE...Aerospace Conference (February 2003). 11. A. Schaum and A. Stocker, “Linear chromodynamics models for hyperspectral target detection

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

  6. Developing nucleic acid-based electrical detection systems

    PubMed Central

    Gabig-Ciminska, Magdalena

    2006-01-01

    Development of nucleic acid-based detection systems is the main focus of many research groups and high technology companies. The enormous work done in this field is particularly due to the broad versatility and variety of these sensing devices. From optical to electrical systems, from label-dependent to label-free approaches, from single to multi-analyte and array formats, this wide range of possibilities makes the research field very diversified and competitive. New challenges and requirements for an ideal detector suitable for nucleic acid analysis include high sensitivity and high specificity protocol that can be completed in a relatively short time offering at the same time low detection limit. Moreover, systems that can be miniaturized and automated present a significant advantage over conventional technology, especially if detection is needed in the field. Electrical system technology for nucleic acid-based detection is an enabling mode for making miniaturized to micro- and nanometer scale bio-monitoring devices via the fusion of modern micro- and nanofabrication technology and molecular biotechnology. The electrical biosensors that rely on the conversion of the Watson-Crick base-pair recognition event into a useful electrical signal are advancing rapidly, and recently are receiving much attention as a valuable tool for microbial pathogen detection. Pathogens may pose a serious threat to humans, animal and plants, thus their detection and analysis is a significant element of public health. Although different conventional methods for detection of pathogenic microorganisms and their toxins exist and are currently being applied, improvements of molecular-based detection methodologies have changed these traditional detection techniques and introduced a new era of rapid, miniaturized and automated electrical chip detection technologies into pathogen identification sector. In this review some developments and current directions in nucleic acid-based electrical

  7. Frequency analysis and data correlation for beam displacement measurements based on the ISTIMES campaign in Montagnole

    NASA Astrophysics Data System (ADS)

    Nordebo, S.; Gustafsson, M.; Dumoulin, J.; Perrone, A.; Pignatti, S.; Soldovieri, F.

    2012-04-01

    Time-frequency analysis is an interdisciplinary subject, which originates from mathematics, signal analysis and physics (Grochenig, 2001). From a signal theoretical and mathematical point of view the primary purpose has been to understand how signals, operators and other mathematical objects can be understood simultaneously in the time and frequency variables, which correspond to the phase space variables in physics (Grochenig, 2001; Claasen, 1980). Perhaps the most popular time-frequency representations are the short-time Fourier transform (STFT) and the Wigner distribution (Grochenig, 2001). Their common feature is to localize a function before taking the Fourier transform, thereby obtaining a time-frequency representation. Here, we employ the classical Kaiser window (Kaiser and Schafer, 1980) which is well known in spectrum analysis, since it provides a flexible approach to control the frequency resolution as well as the amplitude dynamics (sidelobe rejection) for a given measurement interval (or resolution) in time. In this contribution, we employ frequency analysis and data correlation for beam displacement measurements based on the ISTIMES campaign (Proto et al., 2010) conducted at the rock fall test center in Montagnole, France, on October 14, 2010. Several test cases are considered based on direct and indirect impact from a steel sphere dropped on a reinforced concrete beam. Several measurement technologies were used to measure the deformation of the beam based on IRT (InfraRed Thermography), GBSAR (Ground Based Synthetic Aperture Radar), and ODM (Optical Diode Measurements). A time-frequency analysis was used to analyze the evolution of the resonance frequencies of the beam. A short-time cross-correlation followed by Fourier transformation was used to integrate data based on two different signal sources (sensor technologies). The results were compared to a frequency analysis based on video data and image processing to yield a high-accuracy reference

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

    NASA Technical Reports Server (NTRS)

    Lane, Arthur L.; Domingue, Deborah L.

    1997-01-01

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

  9. Video-Based Affect Detection in Noninteractive Learning Environments

    ERIC Educational Resources Information Center

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

    2015-01-01

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

  10. Polypyrrole based gas sensor for ammonia detection

    NASA Astrophysics Data System (ADS)

    Dunst, K. J.; Cysewska, K.; Kalinowski, P.; Jasiński, P.

    2016-01-01

    The nature of polypyrrole response to toxic gases does not allow using the sensor in a conventional way. The main aim of this study is to acquire the information about the concentration using different approaches: a linear approximation, a non-linear approximation and a tangent method. In this paper a two-steps procedure for sensor response measurements has been utilized. Polypyrrole films were electrochemically synthesized on the interdigitated electrodes. Gas sensing measurements of polypyrrole based sensor were carried out at room temperature. The influence of the flow rate on the sensing performance to NH3 were investigated. The preliminary studies of aging of the sensor were also explored.

  11. Inequivalence of correlation-based measures of non-Markovianity

    NASA Astrophysics Data System (ADS)

    Neto, Alaor Cervati; Karpat, Göktuǧ; Fanchini, Felipe Fernandes

    2016-09-01

    We conclusively show that the entanglement- and the mutual-information-based measures of quantum non-Markovianity are inequivalent. To this aim, we first analytically solve the optimization problem in the definition of the entanglement-based measure for a two-level system. We demonstrate that the optimal initial bipartite state of the open system and the ancillary is always given by one of the Bell states for any one-qubit dynamics. On top of this result, we present an explicit example dynamics where memory effects emerge according to the mutual-information-based measure, even though the time evolution remains memoryless with respect to the entanglement-based measure. Finally, we explain this disagreement between the two measures in terms of the information dynamics of the open system, exploring the accessible and inaccessible parts of information.

  12. 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.

  13. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-11-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2003-07-01

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

  16. Run-Length and Edge Statistics Based Approach for Image Splicing Detection

    NASA Astrophysics Data System (ADS)

    Dong, Jing; Wang, Wei; Tan, Tieniu; Shi, Yun Q.

    In this paper, a simple but efficient approach for blind image splicing detection is proposed. Image splicing is a common and fundamental operation used for image forgery. The detection of image splicing is a preliminary but desirable study for image forensics. Passive detection approaches of image splicing are usually regarded as pattern recognition problems based on features which are sensitive to splicing. In the proposed approach, we analyze the discontinuity of image pixel correlation and coherency caused by splicing in terms of image run-length representation and sharp image characteristics. The statistical features extracted from image run-length representation and image edge statistics are used for splicing detection. The support vector machine (SVM) is used as the classifier. Our experimental results demonstrate that the two proposed features outperform existing ones both in detection accuracy and computational complexity.

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

    NASA Astrophysics Data System (ADS)

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

    2015-09-01

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

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

    PubMed Central

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

    2009-01-01

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

  19. Coherent pulse detection and multi-channel coherent detection based on a single balanced homodyne receiver.

    PubMed

    Lee, Wangkuen; Izadpanah, Hoss; Delfyett, Peter J; Menendez, Ron; Etemad, Shahab

    2007-03-05

    The performance of coherent pulse detection (CPD) and multichannel coherent detection (MCCD) based on a single dual-balanced homodyne receiver was experimentally demonstrated using a gratingcoupled hybridly mode-locked semiconductor laser. Compared with direct detection, a high coherent gain of over 10 dB, as well as an SNR improvement of over 5 dB, was obtained in both detection schemes. Our experimental results have confirmed that the coherent detection processes in CPD and MCCD are nearly the same based on a square-root LO power dependence. Nevertheless, the MCCD scheme has shown an advantage in a path-length error over the CPD scheme, revealing 2~3 dB improvement in sensitivities.

  20. Vibration Based Sun Gear Damage Detection

    NASA Technical Reports Server (NTRS)

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

    2013-01-01

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

  1. Vehicle Detection Based on Probability Hypothesis Density Filter

    PubMed Central

    Zhang, Feihu; Knoll, Alois

    2016-01-01

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

  2. Drag reduction - Jet breakup correlation with kerosene-based additives

    NASA Technical Reports Server (NTRS)

    Hoyt, J. W.; Altman, R. L.; Taylor, J. J.

    1980-01-01

    The drag-reduction effectiveness of a number of high-polymer additives dissolved in aircraft fuel has been measured in a turbulent-flow rheometer. These solutions were further subjected to high elongational stress and breakup forces in a jet discharging in air. The jet was photographed using a high-resolution camera with special lighting. The object of the work was to study the possible spray-suppression ability of high-polymer additives to aircraft fuel and to correlate this with the drag-reducing properties of the additives. It was found, in fact, that the rheometer results indicate the most effective spray-suppressing additives. Using as a measure the minimum polymer concentration to give a maximum friction-reducing effect, the order of effectiveness of eight different polymer additives as spray-suppressing agents was predicted. These results may find application in the development of antimisting additives for aircraft fuel which may increase fire safety in case of crash or accident.

  3. A new corner detecting method based on contourlet transfrom

    NASA Astrophysics Data System (ADS)

    Xiang, Jingbo

    2009-10-01

    Comer point is one of the most important feature points in computer vision and pattern recognition. In the paper, a novel corner detection algorithm is proposed. In the improved algorithm, firstly transform the image using the Contourlet transform. Then the corner candidates are selected using the SUSAN algorithm. Lastly, the real corners are selected according to both directional information and correlation of the corner candidates. Experiment results show that the proposed corner detector is more effective than the traditional SUSAN algorithm.

  4. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2013-01-01

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

  6. Infrared small target detection based on Danger Theory

    NASA Astrophysics Data System (ADS)

    Lan, Jinhui; Yang, Xiao

    2009-11-01

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

  7. Transistor-based particle detection systems and methods

    SciTech Connect

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

    2015-06-09

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

  8. Flow-Based Detection of Bar Coded Particles

    SciTech Connect

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

    2005-06-24

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

  9. Ultrasonic Detection of Cracks in a Complex Aircraft Structure Using a Local Correlation Method for Signals from a Moving Transducer

    NASA Astrophysics Data System (ADS)

    Aldrin, John C.; Mandeville, John R.; Kropas-Hughes, Claudia V.

    2004-02-01

    A challenge in nondestructive evaluation is the ability to discern signals that are closely spaced or superimposed in time. A feature extraction methodology is proposed where signals from a moving transducer are accurately aligned to a primary part feature and analyzed within multiple time gates for shifting signals from a defect. The local correlation method functions to detect the relative shift of signals in time for adjacent transducer locations due to differing echo dynamics from cracks and part geometries.

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

    SciTech Connect

    Hartford, A. Jr.; Sander, R.K.; Quigley, G.P.; Radziemski, L.J.; Cremers, D.A.

    1982-01-01

    Several laser-based techniques are being evaluated for the remote, point, and surface detection of chemical agents. Among the methods under investigation are optoacoustic spectroscopy, laser-induced breakdown spectroscopy (LIBS), and synchronous detection of laser-induced fluorescence (SDLIF). Optoacoustic detection has already been shown to be capable of extremely sensitive point detection. Its application to remote sensing of chemical agents is currently being evaluated. Atomic emission from the region of a laser-generated plasma has been used to identify the characteristic elements contained in nerve (P and F) and blister (S and Cl) agents. Employing this LIBS approach, detection of chemical agent simulants dispersed in air and adsorbed on a variety of surfaces has been achieved. Synchronous detection of laser-induced fluorescence provides an attractive alternative to conventional LIF, in that an artificial narrowing of the fluorescence emission is obtained. The application of this technique to chemical agent simulants has been successfully demonstrated. 19 figures.

  11. Region duplication forgery detection technique based on SURF and HAC.

    PubMed

    Mishra, Parul; Mishra, Nishchol; Sharma, Sanjeev; Patel, Ravindra

    2013-01-01

    Region duplication forgery detection is a special type of forgery detection approach and widely used research topic under digital image forensics. In copy move forgery, a specific area is copied and then pasted into any other region of the image. Due to the availability of sophisticated image processing tools, it becomes very hard to detect forgery with naked eyes. From the forged region of an image no visual clues are often detected. For making the tampering more robust, various transformations like scaling, rotation, illumination changes, JPEG compression, noise addition, gamma correction, and blurring are applied. So there is a need for a method which performs efficiently in the presence of all such attacks. This paper presents a detection method based on speeded up robust features (SURF) and hierarchical agglomerative clustering (HAC). SURF detects the keypoints and their corresponding features. From these sets of keypoints, grouping is performed on the matched keypoints by HAC that shows copied and pasted regions.

  12. Region Duplication Forgery Detection Technique Based on SURF and HAC

    PubMed Central

    Mishra, Parul; Sharma, Sanjeev; Patel, Ravindra

    2013-01-01

    Region duplication forgery detection is a special type of forgery detection approach and widely used research topic under digital image forensics. In copy move forgery, a specific area is copied and then pasted into any other region of the image. Due to the availability of sophisticated image processing tools, it becomes very hard to detect forgery with naked eyes. From the forged region of an image no visual clues are often detected. For making the tampering more robust, various transformations like scaling, rotation, illumination changes, JPEG compression, noise addition, gamma correction, and blurring are applied. So there is a need for a method which performs efficiently in the presence of all such attacks. This paper presents a detection method based on speeded up robust features (SURF) and hierarchical agglomerative clustering (HAC). SURF detects the keypoints and their corresponding features. From these sets of keypoints, grouping is performed on the matched keypoints by HAC that shows copied and pasted regions. PMID:24311972

  13. Spectral evolution of gamma-ray bursts detected by the SIGNE experiment. 1: Correlation between intensity and spectral hardness

    NASA Technical Reports Server (NTRS)

    Kargatis, Vincent E.; Liang, Edison P.; Hurley, Kevin C.; Barat, C.; Eveno, E.; Niel, M.

    1994-01-01

    We study the continuum spectral evolution of 16 gamma-ray bursts detected by the Franco-Soviet SIGNE experiment in 1981-1982 by fitting time resolved (0.5 s) spectra in count space with simple thermal bremsstrahlung and synchrotron models. We find that there is no single characteristic of spectral evolution: we see hard-to-soft, soft-to-hard, luminosity-hardness tracking, and chaotic evolution. We perform correlation studies between instantaneous burst intensity and spectral temperature for seven bursts. While we basically confirm the existence of a correlation between these variables as originally claimed by Golenetskii et al. (1983) we find higher values and a broader range of correlation indices.

  14. Estimation and inference on correlations between biomarkers with repeated measures and left-censoring due to minimum detection levels

    PubMed Central

    Xie, Xianhong; Xue, Xiaonan; Gange, Stephen J.; Strickler, Howard D.; Kim, Mimi Y.

    2013-01-01

    Statistical approaches for estimating and drawing inference on the correlation between two biomarkers which are repeatedly assessed over time and subject to left-censoring due to minimum detection levels are lacking. We propose a linear mixed-effects model and estimate the parameters with the Monte Carlo Expectation Maximization (MCEM) method. Inferences regarding the model parameters and the correlation between the biomarkers are performed by applying Louis’s method and the delta method. Simulation studies were conducted to compare the proposed MCEM method with existing methods including the MLE method, the multiple imputation (MI) method, and two widely used ad hoc approaches: replacing the censored values with the detection limit (DL) or with half of the detection limit (HDL). The results show that the performance of the MCEM with respect to relative bias and coverage probability for the 95% confidence interval is superior to the DL and HDL approaches and exceeds that of the MI method at medium to high levels of censoring, and the standard error estimates from the MCEM method are close to ideal. The MLE method can estimate the parameters accurately; however, a non-positive definite information matrix can occur so that the variances are not estimable. These five methods are illustrated with data from a longitudinal HIV study to estimate and draw inference on the correlation between HIV RNA levels measured in plasma and in cervical secretions at multiple time points. PMID:22714546

  15. Detection of heavy metal by paper-based microfluidics.

    PubMed

    Lin, Yang; Gritsenko, Dmitry; Feng, Shaolong; Teh, Yi Chen; Lu, Xiaonan; Xu, Jie

    2016-09-15

    Heavy metal pollution has shown great threat to the environment and public health worldwide. Current methods for the detection of heavy metals require expensive instrumentation and laborious operation, which can only be accomplished in centralized laboratories. Various microfluidic paper-based analytical devices have been developed recently as simple, cheap and disposable alternatives to conventional ones for on-site detection of heavy metals. In this review, we first summarize current development of paper-based analytical devices and discuss the selection of paper substrates, methods of device fabrication, and relevant theories in these devices. We then compare and categorize recent reports on detection of heavy metals using paper-based microfluidic devices on the basis of various detection mechanisms, such as colorimetric, fluorescent, and electrochemical methods. To finalize, the future development and trend in this field are discussed.

  16. Detection of infrastructure manipulation with knowledge-based video surveillance

    NASA Astrophysics Data System (ADS)

    Muench, David; Hilsenbeck, Barbara; Kieritz, Hilke; Becker, Stefan; Grosselfinger, Ann-Kristin; Huebner, Wolfgang; Arens, Michael

    2016-10-01

    We are living in a world dependent on sophisticated technical infrastructure. Malicious manipulation of such critical infrastructure poses an enormous threat for all its users. Thus, running a critical infrastructure needs special attention to log the planned maintenance or to detect suspicious events. Towards this end, we present a knowledge-based surveillance approach capable of logging visual observable events in such an environment. The video surveillance modules are based on appearance-based person detection, which further is used to modulate the outcome of generic processing steps such as change detection or skin detection. A relation between the expected scene behavior and the underlying basic video surveillance modules is established. It will be shown that the combination already provides sufficient expressiveness to describe various everyday situations in indoor video surveillance. The whole approach is qualitatively and quantitatively evaluated on a prototypical scenario in a server room.

  17. 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

  18. Optical character recognition based on nonredundant correlation measurements.

    PubMed

    Braunecker, B; Hauck, R; Lohmann, A W

    1979-08-15

    The essence of character recognition is a comparison between the unknown character and a set of reference patterns. Usually, these reference patterns are all possible characters themselves, the whole alphabet in the case of letter characters. Obviously, N analog measurements are highly redundant, since only K = log(2)N binary decisions are enough to identify one out of N characters. Therefore, we devised K reference patterns accordingly. These patterns, called principal components, are found by digital image processing, but used in an optical analog computer. We will explain the concept of principal components, and we will describe experiments with several optical character recognition systems, based on this concept.

  19. Epstein-Barr virus detection in kidney biopsy specimens correlates with glomerular mesangial injury.

    PubMed

    Iwama, H; Horikoshi, S; Shirato, I; Tomino, Y

    1998-11-01

    To determine the relationship between the detection of Epstein-Barr virus (EBV)-specific DNA and glomerular injury, 33 renal needle-biopsy specimens that had been formalin-fixed and paraffin-embedded were analyzed using polymerase chain reaction (PCR) with subsequent nonradioactive Southern blot technique. Light microscopic examination and immunofluorescence were also performed. In 30 of 33 renal biopsy specimens, the beta globin gene could be successfully amplified as integrity controls. These 30 patients consisted of 12 patients with immunoglobulin A nephropathy (IgAN), 10 patients with minor glomerular abnormalities, 6 patients with membranous nephropathy, and 2 patients with focal/segmental lesions. EBV was detected in 7 of 12 patients with IgAN (58%), 3 of 6 patients with membranous nephropathy (50%), 0 of 10 patients with minor glomerular abnormalities (0%), and 2 of 2 patients with focal/segmental lesions. EBV detection was not disease specific. The EBV detection ratio of the group with glomerular mesangial lesions (64%; 9 of 14 patients) was significantly greater than those without (19%; 3 of 16 patients; P < 0.012, chi-square test). The EBV detection ratio of the group with glomerular lesions (60%; 12 of 20 patients) was significantly greater than those without (0%; 0 of 10 patients; P < 0.0016, Fisher's exact test), and the EBV detection ratio of the group with fibrinogen deposits observed in immunofluorescence (73%; 11 of 15 patients) was significantly greater than those without (7%; 1 of 15 patients; P < 0.0002, chi-square test). The EBV detection ratio of the group with immunoglobulin deposits (57%; 12 of 21 patients) was also significantly greater than those without (0%; 0 of 9 patients; P < 0.0040, Fisher's exact test). These data suggest that EBV can damage the glomerular mesangium beyond disease units and be mediated by immunoglobulin in patients with various chronic glomerulonephritides.

  20. Effective and Efficient Correlation Analysis with Application to Market Basket Analysis and Network Community Detection

    ERIC Educational Resources Information Center

    Duan, Lian

    2012-01-01

    Finding the most interesting correlations among items is essential for problems in many commercial, medical, and scientific domains. For example, what kinds of items should be recommended with regard to what has been purchased by a customer? How to arrange the store shelf in order to increase sales? How to partition the whole social network into…

  1. A feature-based model of symmetry detection.

    PubMed Central

    Scognamillo, Renata; Rhodes, Gillian; Morrone, Concetta; Burr, David

    2003-01-01

    Symmetry detection is important for many biological visual systems, including those of mammals, insects and birds. We constructed a symmetry-detection algorithm with two stages: location of the visually salient features of the image, then evaluating the symmetry of these features over a long range, by means of a simple Gaussian filter. The algorithm detects the axis of maximum symmetry for human faces (or any arbitrary image) and calculates the magnitude of the asymmetry. We have evaluated the algorithm on the dataset of Rhodes et al. (1998 Psychonom. Bull. Rev. 5, 659-669) and found that the algorithm is able to discriminate small variations of symmetry created by computer-manipulating the symmetry levels in individual faces, and that the values measured by the algorithm correlate well with human psycho-physical symmetry ratings. PMID:12965001

  2. Differential Characteristics Based Iterative Multiuser Detection for Wireless Sensor Networks

    PubMed Central

    Chen, Xiaoguang; Jiang, Xu; Wu, Zhilu; Zhuang, Shufeng

    2017-01-01

    High throughput, low latency and reliable communication has always been a hot topic for wireless sensor networks (WSNs) in various applications. Multiuser detection is widely used to suppress the bad effect of multiple access interference in WSNs. In this paper, a novel multiuser detection method based on differential characteristics is proposed to suppress multiple access interference. The proposed iterative receive method consists of three stages. Firstly, a differential characteristics function is presented based on the optimal multiuser detection decision function; then on the basis of differential characteristics, a preliminary threshold detection is utilized to find the potential wrongly received bits; after that an error bit corrector is employed to correct the wrong bits. In order to further lower the bit error ratio (BER), the differential characteristics calculation, threshold detection and error bit correction process described above are iteratively executed. Simulation results show that after only a few iterations the proposed multiuser detection method can achieve satisfactory BER performance. Besides, BER and near far resistance performance are much better than traditional suboptimal multiuser detection methods. Furthermore, the proposed iterative multiuser detection method also has a large system capacity. PMID:28212328

  3. A CORRELATION BETWEEN THE HIGHEST ENERGY COSMIC RAYS AND NEARBY ACTIVE GALACTIC NUCLEI DETECTED BY FERMI

    SciTech Connect

    Nemmen, Rodrigo S.; Bonatto, Charles; Storchi-Bergmann, Thaisa

    2010-10-10

    We analyze the correlation of the positions of {gamma}-ray sources in the Fermi Large Area Telescope (LAT) First Source Catalog (1FGL) and the First LAT Active Galactic Nuclei (AGNs) Catalog (1LAC) with the arrival directions of ultra-high-energy cosmic rays (UHECRs) observed with the Pierre Auger Observatory, in order to investigate the origin of UHECRs. We find that Galactic sources and blazars identified in the 1FGL are not significantly correlated with UHECRs, while the 1LAC sources display a mild correlation (2.6{sigma} level) on an {approx}2.{sup 0}4 angular scale. When selecting only the 1LAC AGNs closer than 200 Mpc, we find a strong association (5.4{sigma}) between their positions and the directions of UHECRs on an {approx}17{sup 0} angular scale; the probability of the observed configuration being due to an isotropic flux of cosmic rays is 5 x 10{sup -8}. There is also a 5{sigma} correlation with nearby 1LAC sources on a 6.{sup 0}5 scale. We identify seven '{gamma}-ray loud' AGNs which are associated with UHECRs within {approx}17{sup 0} and are likely candidates for the production sites of UHECRs: Centaurus A, NGC 4945, ESO 323-G77, 4C+04.77, NGC 1218, RX J0008.0+1450, and NGC 253. We interpret these results as providing additional support to the hypothesis of the origin of UHECRs in nearby extragalactic objects. As the angular scales of the correlations are large, we discuss the possibility that intervening magnetic fields might be considerably deflecting the trajectories of the particles on their way to Earth.

  4. Neural correlates of auditory scene analysis based on inharmonicity in monkey primary auditory cortex.

    PubMed

    Fishman, Yonatan I; Steinschneider, Mitchell

    2010-09-15

    Segregation of concurrent sounds in complex acoustic environments is a fundamental feature of auditory scene analysis. A powerful cue used by the auditory system to segregate concurrent sounds, such as speakers' voices at a cocktail party, is inharmonicity. This can be demonstrated when a component of a harmonic complex tone is perceived as a separate tone "popping out" from the complex as a whole when it is sufficiently mistuned from its harmonic value. The neural bases of perceptual "pop out" of mistuned harmonics are unclear. We recorded multiunit activity from primary auditory cortex (A1) of behaving monkeys elicited by harmonic complex tones that were either "in tune" or that contained a mistuned third harmonic set at the best frequency of the neural populations. Responses to mistuned sounds were enhanced relative to responses to "in-tune" sounds, thus correlating with the enhanced perceptual salience of the mistuned component. Consistent with human psychophysics of "pop out," response enhancements increased with the degree of mistuning, were maximal for neural populations tuned to the frequency of the mistuned component, and were not observed under comparable stimulus conditions that do not elicit perceptual "pop out." Mistuning was also associated with changes in neuronal temporal response patterns phase locked to "beats" in the stimuli. Intracortical auditory evoked potentials paralleled noninvasive neurophysiological correlates of perceptual "pop out" in humans, further augmenting the translational relevance of the results. Findings suggest two complementary neural mechanisms for "pop out," based on the detection of local differences in activation level or coherence of temporal response patterns across A1.

  5. Adaptive Rule Based Fetal QRS Complex Detection Using Hilbert Transform

    PubMed Central

    Ulusar, Umit D.; Govindan, R.B.; Wilson, James D.; Lowery, Curtis L.; Preissl, Hubert; Eswaran, Hari

    2010-01-01

    In this paper we introduce an adaptive rule based QRS detection algorithm using the Hilbert transform (adHQRS) for fetal magnetocardiography processing. Hilbert transform is used to combine multiple channel measurements and the adaptive rule based decision process is used to eliminate spurious beats. The algorithm has been tested with a large number of datasets and promising results were obtained. PMID:19964648

  6. Adaptive rule based fetal QRS complex detection using Hilbert transform.

    PubMed

    Ulusar, Umit D; Govindan, R B; Wilson, James D; Lowery, Curtis L; Preissl, Hubert; Eswaran, Hari

    2009-01-01

    In this paper we introduce an adaptive rule based QRS detection algorithm using the Hilbert transform (adHQRS) for fetal magnetocardiography processing. Hilbert transform is used to combine multiple channel measurements and the adaptive rule based decision process is used to eliminate spurious beats. The algorithm has been tested with a large number of datasets and promising results were obtained.

  7. Oxidative base damage in RNA detected by reverse transcriptase.

    PubMed Central

    Rhee, Y; Valentine, M R; Termini, J

    1995-01-01

    Oxidative base damage in DNA and metabolic defects in the recognition and removal of such damage play important roles in mutagenesis and human disease. The extent to which cellular RNA is a substrate for oxidative damage and the possible biological consequences of RNA base oxidation, however, remain largely unexplored. Since oxidatively modified RNA may contribute to the high mutability of retroviral genomic DNA, we have been interested in developing methods for the sequence specific detection of such damage. We show here that a primer extension assay using AMV reverse transcriptase (RT) can be used to reveal oxidatively damaged sites in RNA. This finding extends the currently known range of RNA modifications detectable with AMV reverse transcriptase. Analogous assays using DNA polymerases to detect base damage in DNA substrates appear to be restricted to lesions at thymine. Oxidative base damage in the absence of any detectable chain breaks was produced by dye photosensitization of RNA. Six out of 20 dyes examined were capable of producing RT detectable lesions. RT stops were seen predominantly at purines, although many pyrimidine sites were also detected. Dye specific photofootprints revealed by RT analysis suggests differential dye binding to the RNA substrate. Some of the photoreactive dyes described here may have potential utility in RNA structural analysis, particularly in the identification of stem-loop regions in complex RNAs. Images PMID:7545285

  8. Magnetic wire trap arrays for biomarker-based molecular detection

    NASA Astrophysics Data System (ADS)

    Vieira, Gregory; Mahajan, Kalpesh; Ruan, Gang; Winter, Jessica; Sooryakumar, R.

    2012-02-01

    Submicrometer-scale magnetic devices built on chip-based platforms have recently been shown to present opportunities for new particle trapping and manipulation technologies. Meanwhile, advances in nanoparticle fabrication allow for the building of custom-made particles with precise control of their size, composition, and other properties such as magnetism, fluorescence, and surface biomarker characteristics. In particular, carefully tailored surface biomarkers facilitate precise binding to targeted molecules, self-actuated construction of hybrid structures, and fluorescence-based detection schemes. Based on these progresses, we present an on-chip detection mechanism for molecules with known surface markers. Hybrid nanostructures consisting of micelle nanoparticles, fluorescent quantum dots, and superparamagnetic iron oxide nanoparticles are used to detect proteins or DNA molecules. The target is detected by the magnetic and fluorescent functionalities of the composite nanostructure, whereas in the absence of the target these signals are not present. Underlying this approach is the simultaneous manipulation via ferromagnetic zigzag nanowire arrays and imaging via quantum dot excitation. This chip-based detection technique could provide a powerful, low cost tool for ultrasensitive molecule detection with ramifications in healthcare diagnostics and small-scale chemical synthesis.

  9. Ion Beam Analysis Of Silicon-Based Surfaces And Correlation With Surface Energy Measurements

    SciTech Connect

    Xing Qian; Herbots, N.; Hart, M.; Bradley, J. D.; Wilkens, B. J.; Sell, D. A.; Culbertson, R. J.; Whaley, S. D.; Sell, Clive H.; Kwong, Henry Mark Jr.

    2011-06-01

    The water affinity of Si-based surfaces is quantified by contact angle measurement and surface free energy to explain hydrophobic or hydrophilic behavior of silicone, silicates, and silicon surfaces. Surface defects such as dangling bonds, surface free energy including Lewis acid-base and Lifshitz-van der Waals components are discussed. Water nucleation and condensation is further explained by surface topography. Tapping mode atomic force microscopy (TMAFM) provides statistical analysis of the topography of these Si-based surfaces. The correlation of the above two characteristics describes the behavior of water condensation at Si-based surfaces. Surface root mean square roughness increasing from several A ring to several nm is found to provide nucleation sites that expedite water condensation visibly for silica and silicone. Hydrophilic surfaces have a condensation pattern that forms puddles of water while hydrophobic surfaces form water beads. Polymer adsorption on these surfaces alters the water affinity as well as the surface topography, and therefore controls condensation on Si-based surfaces including silicone intraocular lens (IOL). The polymer film is characterized by Rutherford backscattering spectrometry (RBS) in conjunction with 4.265 MeV {sup 12}C({alpha}, {alpha}){sup 12}C, 3.045 MeV {sup 16}O({alpha},{alpha}){sup 16}O nuclear resonance scattering (NRS), and 2.8 MeV elastic recoil detection (ERD) of hydrogen for high resolution composition and areal density measurements. The areal density of hydroxypropyl methylcellulose (HPMC) film ranges from 10{sup 18} atom/cm{sup 2} to 10{sup 19} atom/cm{sup 2} gives the silica or silicone surface a roughness of several A ring and a wavelength of 0.16{+-}0.02 {mu}m, and prevents fogging by forming a complete wetting layer during water condensation.

  10. EOVSA Implementation of a Spectral Kurtosis Correlator for Transient Detection and Classification

    NASA Astrophysics Data System (ADS)

    Nita, Gelu M.; Hickish, Jack; MacMahon, David; Gary, Dale E.

    We describe in general terms the practical use in astronomy of a higher-order statistical quantity called spectral kurtosis (SK), and describe the first implementation of SK-enabled firmware in the Fourier transform-engine (F-engine) of a digital FX correlator for the Expanded Owens Valley Solar Array (EOVSA). The development of the theory for SK is summarized, leading to an expression for generalized SK that is applicable to both SK spectrometers and those not specifically designed for SK. We also give the means for computing both the SK̂ estimator and thresholds for its application as a discriminator of RFI contamination. Tests of the performance of EOVSA as an SK spectrometer are shown to agree precisely with theoretical expectations, and the methods for configuring the correlator for correct SK operation are described.

  11. [The detection of antibodies against HIV-1 24-kd protein. A clinico-serological correlation].

    PubMed

    Díaz Torres, H; Silva Cabrera, E; Rodríguez García, O; Bárcenas Moses, J; Lubián Caballero, A L

    1996-01-01

    The presence of antibodies against the HIV protein of 24 kd was studies by the parallel use of the DAVIH BLOT western blot and of the DAVIH AC P24 ELISA in serum samples from 176 patients at different HIV-1 infection stages. The results were correlated with the clinical classification of the patient at the moment of taking the sample and with the further evolution during 6 months. 57% of the patients with opportunistic minor infections and 96% of AIDS patients had low antibodies titres. Dead patients showed no reactivity or presented very low titres in samples taken before dying. Different titrations were observed in serum groups with an apparently uniform reactivity in the western blot. The results show and adequate clinical and serological correlation. Therefore, the DAVIH AC P24 ELISA could be useful in the clinical follow-up of HIV-1 infected persons.

  12. Nanomaterial-Based Biosensors for Detection of Pesticides and Explosives

    SciTech Connect

    Wang, Jun; Lin, Yuehe

    2009-01-01

    In this chapter, we describe nanomaterial-based biosensors for detecting OP pesticides and explosives. CNTs and functionalized silica nanoparticles have been chosen for this study. The biosensors were combined with the flow-injection system, providing great advantages for onsite, real-time, and continuous detection of environmental pollutants such as OPs and TNT. The sensors take advantage of the electrocatalytic properties of CNTs, which makes it feasible to achieve a sensitive electrochemical detection of the products from enzymatic reactions at low potential. This approach uses a large aspect ratio of silica nanoparticles, which can be used as a carrier for loading a large amount of electroactive species, such as poly(guanine), for amplified detection of explosives. These methods offer a new environmental monitoring tool for rapid, inexpensive, and highly sensitive detection of OPs or TNT compounds.

  13. Wavelet-based target detection using multiscale directional analysis

    NASA Astrophysics Data System (ADS)

    Chambers, Bradley J.; Reynolds, William D., Jr.; Campbell, Derrick S.; Fennell, Darius K.; Ansari, Rashid

    2007-04-01

    Efficient processing of imagery derived from remote sensing systems has become ever more important due to increasing data sizes, rates, and bit depths. This paper proposes a target detection method that uses a special class of wavelets based on highly frequency-selective directional filter banks. The approach helps isolate object features in different directional filter output components. These components lend themselves well to the application of powerful denoising and edge detection procedures in the wavelet domain. Edge information is derived from directional wavelet decompositions to detect targets of known dimension in electro optical imagery. Results of successful detection of objects using the proposed method are presented in the paper. The approach highlights many of the benefits of working with directional wavelet analysis for image denoising and detection.

  14. Exploiting identifiability and intergene correlation for improved detection of differential expression.

    PubMed

    Deller, J R; Radha, Hayder; McCormick, J Justin

    2013-01-01

    Accurate differential analysis of microarray data strongly depends on effective treatment of intergene correlation. Such dependence is ordinarily accounted for in terms of its effect on significance cutoffs. In this paper, it is shown that correlation can, in fact, be exploited to share information across tests and reorder expression differentials for increased statistical power, regardless of the threshold. Significantly improved differential analysis is the result of two simple measures: (i) adjusting test statistics to exploit information from identifiable genes (the large subset of genes represented on a microarray that can be classified a priori as nondifferential with very high confidence], but (ii) doing so in a way that accounts for linear dependencies among identifiable and nonidentifiable genes. A method is developed that builds upon the widely used two-sample t-statistic approach and uses analysis in Hilbert space to decompose the nonidentified gene vector into two components that are correlated and uncorrelated with the identified set. In the application to data derived from a widely studied prostate cancer database, the proposed method outperforms some of the most highly regarded approaches published to date. Algorithms in MATLAB and in R are available for public download.

  15. Correlation between automatic detection of malaria on thin film and experts' parasitaemia scores

    NASA Astrophysics Data System (ADS)

    Sunarko, Budi; Williams, Simon; Prescott, William R.; Byker, Scott M.; Bottema, Murk J.

    2017-03-01

    An algorithm was developed to diagnose the presence of malaria and to estimate the depth of infection by automatically counting individual normal and infected erythrocytes in images of thin blood smears. During the training stage, the parameters of the algorithm were optimized to maximize correlation with estimates of parasitaemia from expert human observers. The correlation was tested on a set of 1590 images from seven thin film blood smears. The correlation between the results from the algorithm and expert human readers was r = 0.836. Results indicate that reliable estimates of parasitaemia may be achieved by computational image analysis methods applied to images of thin film smears. Meanwhile, compared to biological experiments, the algorithm fitted well the three high parasitaemia slides and a mid-level parasitaemia slide, and overestimated the three low parasitaemia slides. To improve the parasitaemia estimation, the sources of the overestimation were identified. Emphasis is laid on the importance of further research in order to identify parasites independently of their erythrocyte hosts

  16. Detection of material property errors in handbooks and databases using artificial neural networks with hidden correlations

    NASA Astrophysics Data System (ADS)

    Zhang, Y. M.; Evans, J. R. G.; Yang, S. F.

    2010-11-01

    The authors have discovered a systematic, intelligent and potentially automatic method to detect errors in handbooks and stop their transmission using unrecognised relationships between materials properties. The scientific community relies on the veracity of scientific data in handbooks and databases, some of which have a long pedigree covering several decades. Although various outlier-detection procedures are employed to detect and, where appropriate, remove contaminated data, errors, which had not been discovered by established methods, were easily detected by our artificial neural network in tables of properties of the elements. We started using neural networks to discover unrecognised relationships between materials properties and quickly found that they were very good at finding inconsistencies in groups of data. They reveal variations from 10 to 900% in tables of property data for the elements and point out those that are most probably correct. Compared with the statistical method adopted by Ashby and co-workers [Proc. R. Soc. Lond. Ser. A 454 (1998) p. 1301, 1323], this method locates more inconsistencies and could be embedded in database software for automatic self-checking. We anticipate that our suggestion will be a starting point to deal with this basic problem that affects researchers in every field. The authors believe it may eventually moderate the current expectation that data field error rates will persist at between 1 and 5%.

  17. Tomosynthesis-detected Architectural Distortion: Management Algorithm with Radiologic-Pathologic Correlation.

    PubMed

    Durand, Melissa A; Wang, Steven; Hooley, Regina J; Raghu, Madhavi; Philpotts, Liane E

    2016-01-01

    As use of digital breast tomosynthesis becomes increasingly widespread, new management challenges are inevitable because tomosynthesis may reveal suspicious lesions not visible at conventional two-dimensional (2D) full-field digital mammography. Architectural distortion is a mammographic finding associated with a high positive predictive value for malignancy. It is detected more frequently at tomosynthesis than at 2D digital mammography and may even be occult at conventional 2D imaging. Few studies have focused on tomosynthesis-detected architectural distortions to date, and optimal management of these distortions has yet to be well defined. Since implementing tomosynthesis at our institution in 2011, we have learned some practical ways to assess architectural distortion. Because distortions may be subtle, tomosynthesis localization tools plus improved visualization of adjacent landmarks are crucial elements in guiding mammographic identification of elusive distortions. These same tools can guide more focused ultrasonography (US) of the breast, which facilitates detection and permits US-guided tissue sampling. Some distortions may be sonographically occult, in which case magnetic resonance imaging may be a reasonable option, both to increase diagnostic confidence and to provide a means for image-guided biopsy. As an alternative, tomosynthesis-guided biopsy, conventional stereotactic biopsy (when possible), or tomosynthesis-guided needle localization may be used to achieve tissue diagnosis. Practical uses for tomosynthesis in evaluation of architectural distortion are highlighted, potential complications are identified, and a working algorithm for management of tomosynthesis-detected architectural distortion is proposed.

  18. Stratification-Based Outlier Detection over the Deep Web

    PubMed Central

    Xian, Xuefeng; Zhao, Pengpeng; Sheng, Victor S.; Fang, Ligang; Gu, Caidong; Yang, Yuanfeng; Cui, Zhiming

    2016-01-01

    For many applications, finding rare instances or outliers can be more interesting than finding common patterns. Existing work in outlier detection never considers the context of deep web. In this paper, we argue that, for many scenarios, it is more meaningful to detect outliers over deep web. In the context of deep web, users must submit queries through a query interface to retrieve corresponding data. Therefore, traditional data mining methods cannot be directly applied. The primary contribution of this paper is to develop a new data mining method for outlier detection over deep web. In our approach, the query space of a deep web data source is stratified based on a pilot sample. Neighborhood sampling and uncertainty sampling are developed in this paper with the goal of improving recall and precision based on stratification. Finally, a careful performance evaluation of our algorithm confirms that our approach can effectively detect outliers in deep web. PMID:27313603

  19. The Unknown Computer Viruses Detection Based on Similarity

    NASA Astrophysics Data System (ADS)

    Liu, Zhongda; Nakaya, Naoshi; Koui, Yuuji

    New computer viruses are continually being generated and they cause damage all over the world. In general, current anti-virus software detects viruses by matching a pattern based on the signature; thus, unknown viruses without any signature cannot be detected. Although there are some static analysis technologies that do not depend on signatures, virus writers often use code obfuscation techniques, which make it difficult to execute a code analysis. As is generally known, unknown viruses and known viruses share a common feature. In this paper we propose a new static analysis technology that can circumvent code obfuscation to extract the common feature and detect unknown viruses based on similarity. The results of evaluation experiments demonstrated that this technique is able to detect unknown viruses without false positives.

  20. Efficient method of image edge detection based on FSVM

    NASA Astrophysics Data System (ADS)

    Cai, Aiping; Xiong, Xiaomei

    2013-07-01

    For efficient object cover edge detection in digital images, this paper studied traditional methods and algorithm based on SVM. It analyzed Canny edge detection algorithm existed some pseudo-edge and poor anti-noise capability. In order to provide a reliable edge extraction method, propose a new detection algorithm based on FSVM. Which contains several steps: first, trains classify sample and gives the different membership function to different samples. Then, a new training sample is formed by increase the punishment some wrong sub-sample, and use the new FSVM classification model for train and test them. Finally the edges are extracted of the object image by using the model. Experimental result shows that good edge detection image will be obtained and adding noise experiments results show that this method has good anti-noise.

  1. Enhancing Community Detection By Affinity-based Edge Weighting Scheme

    SciTech Connect

    Yoo, Andy; Sanders, Geoffrey; Henson, Van; Vassilevski, Panayot

    2015-10-05

    Community detection refers to an important graph analytics problem of finding a set of densely-connected subgraphs in a graph and has gained a great deal of interest recently. The performance of current community detection algorithms is limited by an inherent constraint of unweighted graphs that offer very little information on their internal community structures. In this paper, we propose a new scheme to address this issue that weights the edges in a given graph based on recently proposed vertex affinity. The vertex affinity quantifies the proximity between two vertices in terms of their clustering strength, and therefore, it is ideal for graph analytics applications such as community detection. We also demonstrate that the affinity-based edge weighting scheme can improve the performance of community detection algorithms significantly.

  2. Arduino-based noise robust online heart-rate detection.

    PubMed

    Das, Sangita; Pal, Saurabh; Mitra, Madhuchhanda

    2017-04-01

    This paper introduces a noise robust real time heart rate detection system from electrocardiogram (ECG) data. An online data acquisition system is developed to collect ECG signals from human subjects. Heart rate is detected using window-based autocorrelation peak localisation technique. A low-cost Arduino UNO board is used to implement the complete automated process. The performance of the system is compared with PC-based heart rate detection technique. Accuracy of the system is validated through simulated noisy ECG data with various levels of signal to noise ratio (SNR). The mean percentage error of detected heart rate is found to be 0.72% for the noisy database with five different noise levels.

  3. Stratification-Based Outlier Detection over the Deep Web.

    PubMed

    Xian, Xuefeng; Zhao, Pengpeng; Sheng, Victor S; Fang, Ligang; Gu, Caidong; Yang, Yuanfeng; Cui, Zhiming

    2016-01-01

    For many applications, finding rare instances or outliers can be more interesting than finding common patterns. Existing work in outlier detection never considers the context of deep web. In this paper, we argue that, for many scenarios, it is more meaningful to detect outliers over deep web. In the context of deep web, users must submit queries through a query interface to retrieve corresponding data. Therefore, traditional data mining methods cannot be directly applied. The primary contribution of this paper is to develop a new data mining method for outlier detection over deep web. In our approach, the query space of a deep web data source is stratified based on a pilot sample. Neighborhood sampling and uncertainty sampling are developed in this paper with the goal of improving recall and precision based on stratification. Finally, a careful performance evaluation of our algorithm confirms that our approach can effectively detect outliers in deep web.

  4. a Uav-Based ROE Deer Fawn Detection System

    NASA Astrophysics Data System (ADS)

    Israel, M.

    2011-09-01

    This paper presents a UAV based remote sensing system for the detection of fawns in the meadows. There is a high demand because during pasture mowing many wild animals, especially roe deer fawns are killed by mowing machines. The system was tested in several real situations especially with differing weather and iluminating conditions. Its primary sensor is a lightweight thermal infrared camera. The images are captured onboard of the flight system and also transmitted as analog video stream to the ground station, where the user can follow the camera live stream on a monitor for manual animal detection. Beside a high detection rate a fast workflow is another very important objective for this application. Therefore a waypoint planning software was developed that accelerates the workflow. At adequate illuminating and weather conditions the presented UAV-based fawn detection via thermal imaging is a comfortable, fast and reliable method.

  5. A dynamic bead-based microarray for parallel DNA detection

    NASA Astrophysics Data System (ADS)

    Sochol, R. D.; Casavant, B. P.; Dueck, M. E.; Lee, L. P.; Lin, L.

    2011-05-01

    A microfluidic system has been designed and constructed by means of micromachining processes to integrate both microfluidic mixing of mobile microbeads and hydrodynamic microbead arraying capabilities on a single chip to simultaneously detect multiple bio-molecules. The prototype system has four parallel reaction chambers, which include microchannels of 18 × 50 µm2 cross-sectional area and a microfluidic mixing section of 22 cm length. Parallel detection of multiple DNA oligonucleotide sequences was achieved via molecular beacon probes immobilized on polystyrene microbeads of 16 µm diameter. Experimental results show quantitative detection of three distinct DNA oligonucleotide sequences from the Hepatitis C viral (HCV) genome with single base-pair mismatch specificity. Our dynamic bead-based microarray offers an effective microfluidic platform to increase parallelization of reactions and improve microbead handling for various biological applications, including bio-molecule detection, medical diagnostics and drug screening.

  6. Correlates of HIV infection among street-based and venue-based sex workers in Vietnam.

    PubMed

    Le, Thuy Tc; Nguyen, Quoc C; Tran, Ha Tt; Schwandt, Michael; Lim, Hyun J

    2016-10-01

    SummaryCommercial sex work is one of the driving forces of the HIV epidemic across the world. In Vietnam, although female sex workers (FSWs) carry a disproportionate burden of HIV, little is known about the risk profile and associated factors for HIV infection among this population. There is a need for large-scale research to obtain reliable and representative estimates of the measures of association. This study involved secondary data analysis of the 'HIV/STI Integrated Biological and Behavioral Surveillance' study in Vietnam in 2009-2010 to examine the correlates of HIV among FSWs. Data collected from 5298 FSWs, including 2530 street-based sex workers and 2768 venue-based sex workers from 10 provinces in Vietnam, were analyzed using descriptive statistics and bivariate and multivariate logistic regression analyses. HIV prevalence among the overall FSW population was 8.6% (n = 453). However, when stratified by FSW subpopulations, HIV prevalence was 10.6% (n = 267) for street-based sex workers and 6.7% (n = 186) for venue-based sex workers. Factors independently associated with HIV infection in the multivariate analysis, regardless of sex work types, were injecting drug use, high self-perceived HIV risk, and age ≥ 25 years. Additional factors independently associated with HIV risk within each FSW subpopulation included having ever been married among street-based sex workers and inconsistent condom use with clients and having sex partners who injected drugs among venue-based sex workers. Apart from strategies addressing modifiable risk behaviours among all FSWs, targeted strategies to address specific risk behaviours within each FSW subpopulation should be adopted.

  7. Knowledge-based architecture for airborne mine and minefield detection

    NASA Astrophysics Data System (ADS)

    Agarwal, Sanjeev; Menon, Deepak; Swonger, C. W.

    2004-09-01

    One of the primary lessons learned from airborne mid-wave infrared (MWIR) based mine and minefield detection research and development over the last few years has been the fact that no single algorithm or static detection architecture is able to meet mine and minefield detection performance specifications. This is true not only because of the highly varied environmental and operational conditions under which an airborne sensor is expected to perform but also due to the highly data dependent nature of sensors and algorithms employed for detection. Attempts to make the algorithms themselves more robust to varying operating conditions have only been partially successful. In this paper, we present a knowledge-based architecture to tackle this challenging problem. The detailed algorithm architecture is discussed for such a mine/minefield detection system, with a description of each functional block and data interface. This dynamic and knowledge-driven architecture will provide more robust mine and minefield detection for a highly multi-modal operating environment. The acquisition of the knowledge for this system is predominantly data driven, incorporating not only the analysis of historical airborne mine and minefield imagery data collection, but also other "all source data" that may be available such as terrain information and time of day. This "all source data" is extremely important and embodies causal information that drives the detection performance. This information is not being used by current detection architectures. Data analysis for knowledge acquisition will facilitate better understanding of the factors that affect the detection performance and will provide insight into areas for improvement for both sensors and algorithms. Important aspects of this knowledge-based architecture, its motivations and the potential gains from its implementation are discussed, and some preliminary results are presented.

  8. a Enzyme-Based Electrochemical Sensor for Sensitive Detection of Organophosphorus Pesticides

    NASA Astrophysics Data System (ADS)

    Zhou, Nong; Li, Chengyong; Mo, Rijian; Zhang, Peng; He, Lei; Nie, Fanghong; Su, Weiming; Liu, Shucheng; Gao, Jing; Shao, Haiyan; Qian, Zhong-Ji; Ji, Hongwu

    2016-12-01

    A sensitive and fast sensor for quantitative detection of organophosphorus pesticides (OPs) is obtained using acetylcholinesterase (AChE) biosensor based on graphene oxide (GO)-chitosan (CS) composite film. This new biosensor is prepared via depositing GO-CS composite film on glassy carbon electrode (GCE) and then assembling AChE on the composite film. The GO-CS composite film shows an excellent biocompatibility with AChE and enhances immobilization efficiency of AChE. GO homogeneously disperses in the GO-CS composite films and exhibits excellent electrocatalytic activity to thiocholine oxidation, which is from acetylthiocholine catalyzed by AChE. The results show that the inhibition of carbaryl/trichlorfon on AChE activity is proportional to the concentration of carbaryl/trichlorfon. The detection of linear range for carbaryl is from 10nM to 100nM and the correlation coefficients of 0.993. The detection limit for carbaryl is calculated to be about 2.5nM. In addition, the detection of linear range for trichlorfon is from 10nM to 60nM and the correlation coefficients of 0.994. The detection limit for trichlorfon is calculated to be about 1.2nM. This biosensor provides a new promising tool for trace organophosphorus pesticide detection.

  9. A GPU-based Real-time Software Correlation System for the Murchison Widefield Array Prototype

    NASA Astrophysics Data System (ADS)

    Wayth, Randall B.; Greenhill, Lincoln J.; Briggs, Frank H.

    2009-08-01

    Modern graphics processing units (GPUs) are inexpensive commodity hardware that offer Tflop/s theoretical computing capacity. GPUs are well suited to many compute-intensive tasks including digital signal processing. We describe the implementation and performance of a GPU-based digital correlator for radio astronomy. The correlator is implemented using the NVIDIA CUDA development environment. We evaluate three design options on two generations of NVIDIA hardware. The different designs utilize the internal registers, shared memory, and multiprocessors in different ways. We find that optimal performance is achieved with the design that minimizes global memory reads on recent generations of hardware. The GPU-based correlator outperforms a single-threaded CPU equivalent by a factor of 60 for a 32-antenna array, and runs on commodity PC hardware. The extra compute capability provided by the GPU maximizes the correlation capability of a PC while retaining the fast development time associated with using standard hardware, networking, and programming languages. In this way, a GPU-based correlation system represents a middle ground in design space between high performance, custom-built hardware, and pure CPU-based software correlation. The correlator was deployed at the Murchison Widefield Array 32-antenna prototype system where it ran in real time for extended periods. We briefly describe the data capture, streaming, and correlation system for the prototype array.

  10. [Quantitative specific detection of Staphylococcus aureus based on recombinant lysostaphin and ATP bioluminescence].

    PubMed

    Li, Yuyuan; Mi, Zhiqiang; An, Xiaoping; Zhou, Yusen; Tong, Yigang

    2014-08-01

    Quantitative specific detection of Staphylococcus aureus is based on recombinant lysostaphin and ATP bioluminescence. To produce recombinant lysostaphin, the lysostaphin gene was chemically synthesized and inserted it into prokaryotic expression vector pQE30, and the resulting expression plasmid pQE30-Lys was transformed into E. coli M15 for expressing lysostaphin with IPTG induction. The recombinant protein was purified by Ni(2+)-NTA affinity chromatography. Staphylococcus aureus was detected by the recombinant lysostaphin with ATP bioluminescence, and plate count method. The results of the two methods were compared. The recombinant lysostaphin was successfully expressed, and a method of quantitative specific detection of S. aureus has been established, which showed a significant linear correlation with the colony counting. The detection method developed has good perspective to quantify S. aureus.

  11. Development of a wearable-sensor-based fall detection system.

    PubMed

    Wu, Falin; Zhao, Hengyang; Zhao, Yan; Zhong, Haibo

    2015-01-01

    Fall detection is a major challenge in the public healthcare domain, especially for the elderly as the decline of their physical fitness, and timely and reliable surveillance is necessary to mitigate the negative effects of falls. This paper develops a novel fall detection system based on a wearable device. The system monitors the movements of human body, recognizes a fall from normal daily activities by an effective quaternion algorithm, and automatically sends request for help to the caregivers with the patient's location.

  12. Algorithm for detecting human faces based on convex-hull.

    PubMed

    Park, Minsick; Park, Chang-Woo; Park, Mignon; Lee, Chang-Hoon

    2002-03-25

    In this paper, we proposed a new method to detect faces in color based on the convex-hull. We detect two kinds of regions that are skin and hair likeness region. After preprocessing, we apply the convex-hull to their regions and can find a face from their intersection relationship. The proposed algorithm can accomplish face detection in an image involving rotated and turned faces as well as several faces. To validity the effectiveness of the proposed method, we make experiment with various cases.

  13. Sonoclot(®)-based method to detect iron enhanced coagulation.

    PubMed

    Nielsen, Vance G; Henderson, Jon

    2016-07-01

    Thrombelastographic methods have been recently introduced to detect iron mediated hypercoagulability in settings such as sickle cell disease, hemodialysis, mechanical circulatory support, and neuroinflammation. However, these inflammatory situations may have heme oxygenase-derived, coexistent carbon monoxide present, which also enhances coagulation as assessed by the same thrombelastographic variables that are affected by iron. This brief report presents a novel, Sonoclot-based method to detect iron enhanced coagulation that is independent of carbon monoxide influence. Future investigation will be required to assess the sensitivity of this new method to detect iron mediated hypercoagulability in clinical settings compared to results obtained with thrombelastographic techniques.

  14. Fiber-Optic Based Compact Gas Leak Detection System

    NASA Technical Reports Server (NTRS)

    deGroot, Wim A.

    1995-01-01

    A propellant leak detection system based on Raman scattering principles is introduced. The proposed system is flexible and versatile as the result of the use of optical fibers. It is shown that multiple species can be monitored simultaneously. In this paper oxygen, nitrogen, carbon monoxide, and hydrogen are detected and monitored. The current detection sensitivity for both hydrogen and carbon monoxide is 1% partial pressure at ambient conditions. The sensitivity for oxygen and nitrogen is 0.5% partial pressure. The response time to changes in species concentration is three minutes. This system can be used to monitor multiple species at several locations.

  15. Research on fiber diameter automatic measurement based on image detection

    NASA Astrophysics Data System (ADS)

    Chen, Xiaogang; Jiang, Yu; Shen, Wen; Han, Guangjie

    2010-10-01

    In this paper, we present a method of Fiber Diameter Automatic Measurement(FDAM). This design is based on image detection technology in order to provide a rapid and accurate measurement of average fiber diameter. Firstly, a preprocessing mechanism is proposed to the sample fiber image by using improved median filtering algorithm, then we introduce edge detection with Sobel operator to detect target fiber, finally diameter of random point and average diameter of the fiber can be measured precisely with searching shortest path algorithm. Experiments are conducted to prove the accuracy of the measurement, and simulations show that measurement errors caused by human factors could be eliminated to a desirable level.

  16. Vision-Based People Detection System for Heavy Machine Applications

    PubMed Central

    Fremont, Vincent; Bui, Manh Tuan; Boukerroui, Djamal; Letort, Pierrick

    2016-01-01

    This paper presents a vision-based people detection system for improving safety in heavy machines. We propose a perception system composed of a monocular fisheye camera and a LiDAR. Fisheye cameras have the advantage of a wide field-of-view, but the strong distortions that they create must be handled at the detection stage. Since people detection in fisheye images has not been well studied, we focus on investigating and quantifying the impact that strong radial distortions have on the appearance of people, and we propose approaches for handling this specificity, adapted from state-of-the-art people detection approaches. These adaptive approaches nevertheless have the drawback of high computational cost and complexity. Consequently, we also present a framework for harnessing the LiDAR modality in order to enhance the detection algorithm for different camera positions. A sequential LiDAR-based fusion architecture is used, which addresses directly the problem of reducing false detections and computational cost in an exclusively vision-based system. A heavy machine dataset was built, and different experiments were carried out to evaluate the performance of the system. The results are promising, in terms of both processing speed and performance. PMID:26805838

  17. Deceiving entropy-based DoS detection

    NASA Astrophysics Data System (ADS)

    Özçelik, Ä.°lker; Brooks, Richard R.

    2014-06-01

    Denial of Service (DoS) attacks disable network services for legitimate users. A McAfee report shows that eight out of ten Critical Infrastructure Providers (CIPs) surveyed had a significant Distributed DoS (DDoS) attack in 2010.1 Researchers proposed many approaches for detecting these attacks in the past decade. Anomaly based DoS detection is the most common. In this approach, the detector uses statistical features; such as the entropy of incoming packet header fields like source IP addresses or protocol type. It calculates the observed statistical feature and triggers an alarm if an extreme deviation occurs. However, intrusion detection systems (IDS) using entropy based detection can be fooled by spoofing. An attacker can sniff the network to collect header field data of network packets coming from distributed nodes on the Internet and fuses them to calculate the entropy of normal background traffic. Then s/he can spoof attack packets to keep the entropy value in the expected range during the attack. In this study, we present a proof of concept entropy spoofing attack that deceives entropy based detection approaches. Our preliminary results show that spoofing attacks cause significant detection performance degradation.

  18. Cell-based detection of microbial biomaterial contaminations.

    PubMed

    Roch, Toralf; Ma, Nan; Kratz, Karl; Lendlein, Andreas

    2015-01-01

    A major challenge in biomaterial synthesis and functionalization is the prevention of microbial contaminations such as endotoxins (lipopolysaccharides (LPS)). In addition to LPS, which are exclusively expressed by Gram negative bacteria, also other microbial products derived from fungi or Gram positive bacteria can be found as contaminations in research laboratories. Typically, the Limulus amebocyte lysate (LAL)-test is used to determine the endotoxin levels of medical devices. However, this test fails to detect material-bound LPS and other microbial contaminations and, as demonstrated in this study, detects LPS from various bacterial species with different sensitivities.In this work, a cell-based assay using genetically engineered RAW macrophages, which detect not only soluble but also material-bound microbial contaminations is introduced.The sensitivity of this cell-line towards different LPS species and different heat-inactivated microbes was investigated. As proof of principle a soft hydrophobic poly(n-butyl acrylate) network (cPnBA), which may due to adhesive properties strongly bind microbes, was deliberately contaminated with heat-inactivated bacteria. While the LAL-test failed to detect the microbial contamination, the cell-based assay clearly detected material-bound microbial contaminations. Our data demonstrate that a cell-based detection system should routinely be used as supplement to the LAL-test to determine microbial contaminations of biomaterials.

  19. [A Hyperspectral Imagery Anomaly Detection Algorithm Based on Gauss-Markov Model].

    PubMed

    Gao, Kun; Liu, Ying; Wang, Li-jing; Zhu, Zhen-yu; Cheng, Hao-bo

    2015-10-01

    With the development of spectral imaging technology, hyperspectral anomaly detection is getting more and more widely used in remote sensing imagery processing. The traditional RX anomaly detection algorithm neglects spatial correlation of images. Besides, it does not validly reduce the data dimension, which costs too much processing time and shows low validity on hyperspectral data. The hyperspectral images follow Gauss-Markov Random Field (GMRF) in space and spectral dimensions. The inverse matrix of covariance matrix is able to be directly calculated by building the Gauss-Markov parameters, which avoids the huge calculation of hyperspectral data. This paper proposes an improved RX anomaly detection algorithm based on three-dimensional GMRF. The hyperspectral imagery data is simulated with GMRF model, and the GMRF parameters are estimated with the Approximated Maximum Likelihood method. The detection operator is constructed with GMRF estimation parameters. The detecting pixel is considered as the centre in a local optimization window, which calls GMRF detecting window. The abnormal degree is calculated with mean vector and covariance inverse matrix, and the mean vector and covariance inverse matrix are calculated within the window. The image is detected pixel by pixel with the moving of GMRF window. The traditional RX detection algorithm, the regional hypothesis detection algorithm based on GMRF and the algorithm proposed in this paper are simulated with AVIRIS hyperspectral data. Simulation results show that the proposed anomaly detection method is able to improve the detection efficiency and reduce false alarm rate. We get the operation time statistics of the three algorithms in the same computer environment. The results show that the proposed algorithm improves the operation time by 45.2%, which shows good computing efficiency.

  20. Analog Signal Correlating Using an Analog-Based Signal Conditioning Front End

    NASA Technical Reports Server (NTRS)

    Prokop, Norman; Krasowski, Michael

    2013-01-01

    This innovation is capable of correlating two analog signals by using an analog-based signal conditioning front end to hard-limit the analog signals through adaptive thresholding into a binary bit stream, then performing the correlation using a Hamming "similarity" calculator function embedded in a one-bit digital correlator (OBDC). By converting the analog signal into a bit stream, the calculation of the correlation function is simplified, and less hardware resources are needed. This binary representation allows the hardware to move from a DSP where instructions are performed serially, into digital logic where calculations can be performed in parallel, greatly speeding up calculations.

  1. Detection of luminescent single ultrasmall silicon nanoparticles using fluctuation correlation spectroscopy

    SciTech Connect

    Akcakir, O.; Therrien, J.; Belomoin, G.; Barry, N.; Muller, J. D.; Gratton, E.; Nayfeh, M.

    2000-04-03

    We dispersed electrochemical etched Si into a colloid of ultrasmall blue luminescent nanoparticles, observable with the naked eye, in room light. We use two-photon near-infrared femtosecond excitation at 780 nm to record the fluctuating time series of the luminescence, and determine the number density, brightness, and size of diffusing fluorescent particles. The luminescence efficiency of particles is high enough such that we are able to detect a single particle, in a focal volume, of 1 pcm3. The measurements yield a particle size of 1 nm, consistent with direct imaging by transmission electron microscopy. They also yield an excitation efficiency under two-photon excitation two to threefold larger than that of fluorescein. Detection of single particles paves the way for their use as labels in biosensing applications. (c) 2000 American Institute of Physics.

  2. Analysis of vehicle detection with WSN-based ultrasonic sensors.

    PubMed

    Jo, Youngtae; Jung, Inbum

    2014-08-04

    Existing traffic information acquisition systems suffer from high cost and low scalability. To address these problems, the application of wireless sensor networks (WSNs) has been studied, as WSN-based systems are highly scalable and have a low cost of installing and replacing the systems. Magnetic, acoustic and accelerometer sensors have been considered for WSN-based traffic surveillance, but the use of ultrasonic sensors has not been studied. The limitations of WSN-based systems make it necessary to employ power saving methods and vehicle detection algorithms with low computational complexity. In this paper, we model and analyze optimal power saving methodologies for an ultrasonic sensor and present a computationally-efficient vehicle detection algorithm using ultrasonic data. The proposed methodologies are implemented and evaluated with a tiny microprocessor on real roads. The evaluation results show that the low computational complexity of our algorithm does not compromise the accuracy of vehicle detection.

  3. Analysis of Vehicle Detection with WSN-Based Ultrasonic Sensors

    PubMed Central

    Jo, Youngtae.; Jung, Inbum.

    2014-01-01

    Existing traffic information acquisition systems suffer from high cost and low scalability. To address these problems, the application of wireless sensor networks (WSNs) has been studied, as WSN-based systems are highly scalable and have a low cost of installing and replacing the systems. Magnetic, acoustic and accelerometer sensors have been considered for WSN-based traffic surveillance, but the use of ultrasonic sensors has not been studied. The limitations of WSN-based systems make it necessary to employ power saving methods and vehicle detection algorithms with low computational complexity. In this paper, we model and analyze optimal power saving methodologies for an ultrasonic sensor and present a computationally-efficient vehicle detection algorithm using ultrasonic data. The proposed methodologies are implemented and evaluated with a tiny microprocessor on real roads. The evaluation results show that the low computational complexity of our algorithm does not compromise the accuracy of vehicle detection. PMID:25093342

  4. Detection Optimization of the Progressive Multi-Channel Correlation Algorithm Used in Infrasound Nuclear Treaty Monitoring

    DTIC Science & Technology

    2013-03-01

    microbaroms, mountain associated waves, volcanic eruptions , auroras, earthquakes, rockets, and explosions [5] [6]. Examination of infrasound dating...progressive search for distant sensors to add to initial sub- arrays, a PMCC pitfall more comprehensively addressed in Section 2.3. WinPMCC’s solution to this...the goal is to minimize the total number of false alarm and missed detection categorization decisions. Specifically, the solution to this approach

  5. The detection of bulk explosives using nuclear-based techniques

    SciTech Connect

    Morgado, R.E.; Gozani, T.; Seher, C.C.

    1988-01-01

    In 1986 we presented a rationale for the detection of bulk explosives based on nuclear techniques that addressed the requirements of civil aviation security in the airport environment. Since then, efforts have intensified to implement a system based on thermal neutron activation (TNA), with new work developing in fast neutron and energetic photon reactions. In this paper we will describe these techniques and present new results from laboratory and airport testing. Based on preliminary results, we contended in our earlier paper that nuclear-based techniques did provide sufficiently penetrating probes and distinguishable detectable reaction products to achieve the FAA operational goals; new data have supported this contention. The status of nuclear-based techniques for the detection of bulk explosives presently under investigation by the US Federal Aviation Administration (FAA) is reviewed. These include thermal neutron activation (TNA), fast neutron activation (FNA), the associated particle technique, nuclear resonance absorption, and photoneutron activation. The results of comprehensive airport testing of the TNA system performed during 1987-88 are summarized. From a technical point of view, nuclear-based techniques now represent the most comprehensive and feasible approach for meeting the operational criteria of detection, false alarms, and throughput. 9 refs., 5 figs., 2 tabs.

  6. Sensitive measurement of radiation trapping in cold-atom clouds by intensity correlation detection

    NASA Astrophysics Data System (ADS)

    Stites, Ronald; Beeler, Matthew; Feeney, Laura; Kim, Soo; Bali, Samir

    2004-12-01

    We present experimental evidence that the intensity correlations of light scattered from a cold-atom cloud are sensitive to the presence of small amounts of radiation trapping in an atomic sample of density 6×10^8/cm3, with an optical depth (for a resonant light beam) of 0.4. This density and optical depth are approximately an order of magnitude less than the density and on-resonance optical depth at which effects of multiple scattering in cold-atom clouds have been previously observed [Phys.Rev.Lett.64, 408 (1990)].

  7. Perceptual detection as a dynamical bistability phenomenon: A neurocomputational correlate of sensation

    PubMed Central

    Deco, Gustavo; Pérez-Sanagustín, Mar; de Lafuente, Victor; Romo, Ranulfo

    2007-01-01

    Recent studies that combined psychophysical/neurophysiological experiments [de Lafuente V, Romo R (2005) Nat Neurosci 8:1698–1703] analyzed the responses from single neurons, recorded in several cortical areas of parietal and frontal lobes, while trained monkeys reported the presence or absence of a mechanical vibration of varying amplitude applied to skin of one fingertip. The analysis showed that the activity of primary somatosensory cortex neurons covaried with the stimulus strength but did not covary with the animal's perceptual reports. In contrast, the activity of medial premotor cortex (MPC) neurons did not covary with the stimulus strength but did covary with the animal's perceptual reports. Here, we address the question of how perceptual detection is computed in MPC. In particular, we regard perceptual detection as a bistable neurodynamical phenomenon reflected in the activity of MPC. We show that the activity of MPC is consistent with a decision-making-like scenario of fluctuation-driven computation that causes a probabilistic transition between two bistable states, one corresponding to the case in which the monkey detects the sensory input, the other corresponding to the case in which the monkey does not. Moreover, the high variability activity of MPC neurons both within and between trials reflects stochastic fluctuations that may play a crucial role in the monkey's probabilistic perceptual reports. PMID:18077434

  8. Detection of Circulating Tumour Cells in Urothelial Cancers and Clinical Correlations: Comparison of Two Methods

    PubMed Central

    Fina, Emanuela; Necchi, Andrea; Bottelli, Stefano; Reduzzi, Carolina; Pizzamiglio, Sara; Iacona, Chiara; Daidone, Maria Grazia

    2017-01-01

    Circulating tumour cells (CTC) are identified exploiting their protein/gene expression patterns or distinct size compared to blood cells. Data on CTC in bladder cancer (BC) are still scarce. We comparatively analyzed CTC enrichment by AdnaTest ProstateCancerSelect (AT) and ScreenCell®Cyto (SC) kits, combined with identification by EPCAM, MUC1, and ERBB2 expression and by cytological criteria, respectively, in 19 nonmetastatic (M0) and 47 metastatic (M+) BC patients, at baseline (T0) and during treatment (T1). At T0, CTC positivity rates by AT were higher in M+ compared to M0 cases (57.4% versus 25%, p = 0.041). EPCAM was detected in 75% of CTC-positive samples by AT, showing increasing expression levels from T0 to T1 (median (interquartile range, IQR): 0.18 (0.07–0.42) versus 0.84 (0.33–1.84), p = 0.005) in M+ cases. Overall, CTC positivity by SC was around 80% regardless of clinical setting and time point of analysis, except for a lower occurrence at T1 in M0 cases. At T0, circulating tumour microemboli were more frequently (25% versus 8%) detected and more numerous in M+ compared to M0 patients. The approach used for CTC detection impacts the outcome of CTC studies. Further investigations are required to clarify the clinical validity of AT and SC in specific BC clinical contexts. PMID:28321147

  9. Land-based infrared imagery for marine mammal detection

    NASA Astrophysics Data System (ADS)

    Graber, Joseph; Thomson, Jim; Polagye, Brian; Jessup, Andrew

    2011-09-01

    A land-based infrared (IR) camera is used to detect endangered Southern Resident killer whales in Puget Sound, Washington, USA. The observations are motivated by a proposed tidal energy pilot project, which will be required to monitor for environmental effects. Potential monitoring methods also include visual observation, passive acoustics, and active acoustics. The effectiveness of observations in the infrared spectrum is compared to observations in the visible spectrum to assess the viability of infrared imagery for cetacean detection and classification. Imagery was obtained at Lime Kiln Park, Washington from 7/6/10-7/9/10 using a FLIR Thermovision A40M infrared camera (7.5-14μm, 37°HFOV, 320x240 pixels) under ideal atmospheric conditions (clear skies, calm seas, and wind speed 0-4 m/s). Whales were detected during both day (9 detections) and night (75 detections) at distances ranging from 42 to 162 m. The temperature contrast between dorsal fins and the sea surface ranged from 0.5 to 4.6 °C. Differences in emissivity from sea surface to dorsal fin are shown to aid detection at high incidence angles (near grazing). A comparison to theory is presented, and observed deviations from theory are investigated. A guide for infrared camera selection based on site geometry and desired target size is presented, with specific considerations regarding marine mammal detection. Atmospheric conditions required to use visible and infrared cameras for marine mammal detection are established and compared with 2008 meteorological data for the proposed tidal energy site. Using conservative assumptions, infrared observations are predicted to provide a 74% increase in hours of possible detection, compared with visual observations.

  10. Temporal Correlation-Based Spatial Filtering of Rician Noise for Functional MRIs

    NASA Astrophysics Data System (ADS)

    Amir., A. Khaliq; M. Qureshi, I.; Jawad., A. Shah

    2012-01-01

    A novel correlation-based filter is presented for de-noising functional magnetic resonance imaging (fMRI) data. Temporal correlation-based exponential weights are defined for spatial smoothing of the data, with bias reduction using estimated noise variance. The proposed scheme is tested on simulated and real fMRI data. Finally, the results are compared with conventional filters. The method is found to be effectively suppressing the Rician noise in fMRI data, while improving the SNR.

  11. Physico-chemical characterization and property correlations in base oils and fractions

    SciTech Connect

    Singh, H.; Swarup, S.; Chaudhary, G.S.

    1993-04-01

    Three high viscosity index base oils of Middle Eastern origin and their twelve hydrocarbon type fractions, separated using elution chromatography, have been characterized and their data used in physical property correlations. Relationships of chemical composition with the viscosity index and the neutralization number are reported. The neutralization number has been found to correlate with two derived parameters representing the degree of refining of base oils. 25 refs., 5 figs., 2 tabs.

  12. Detecting Chemically Modified DNA Bases Using Surface Enhanced Raman Spectroscopy.

    PubMed

    Barhoumi, Aoune; Halas, Naomi J

    2011-12-15

    Post-translational modifications of DNA- changes in the chemical structure of individual bases that occur without changes in the DNA sequence- are known to alter gene expression. They are believed to result in frequently deleterious phenotypic changes, such as cancer. Methylation of adenine, methylation and hydroxymethylation of cytosine, and guanine oxidation are the primary DNA base modifications identified to date. Here we show it is possible to use surface enhanced Raman spectroscopy (SERS) to detect these primary DNA base modifications. SERS detection of modified DNA bases is label-free and requires minimal additional sample preparation, reducing the possibility of additional chemical modifications induced prior to measurement. This approach shows the feasibility of DNA base modification assessment as a potentially routine analysis that may be further developed for clinical diagnostics.

  13. Broad base biological assay using liquid based detection assays

    SciTech Connect

    Milanovich, F; Albala, J; Colston, B; Langlois, R; Venkateswaren, K

    2000-10-31

    The release of a biological agent by terrorists represents a serious threat to the safety of US citizens. At present there are over 50 pathogens and toxins on various agency threat lists. Most of these pathogens are rarely seen by public health personnel so the ability to rapidly identify their infection is limited. Since many pathogenic infections have symptomatic delays as long as several days, effective treatment is often compromised. This translates into two major deficiencies in our ability to counter biological terrorism (1) the lack of any credible technology to rapidly detect and identify all the pathogens or toxins on current threat lists and (2) the lack of a credible means to rapidly diagnose thousands of potential victims. In this SI we are developing a rapid, flexible, inexpensive, high throughput, and deeply multiplex-capable biological assay technology. The technology, which we call the Liquid Array (LA), utilizes optical encoding of small diameter beads which serve as the templates for biological capture assays. Once exposed to a fluid sample these beads can be identified and probed for target pathogens at rates of several thousand beads per second. Since each bead can be separately identified, one can perform parallel assays by assigning a different assay to each bead in the encoded set. The goal for this development is a detection technology capable of simultaneously identifying 100s of different bioagents and/or of rapidly diagnosing several thousand individuals. We are pursuing this research in three thrusts. In the first we are exploring the fundamental interactions of the beads with proteins and nucleic acids in complex mixtures. This will provide us with a complete understanding of the limits of the technology with respect to throughput and complex environment. A major spin-off of this activity is in the rapidly emerging field of proteomics where we may be able to rapidly assess the interactions responsible for cell metabolism, structural

  14. Longitudinal correlation of 3D OCT to detect early stage erosion in bovine enamel.

    PubMed

    Aden, Abdirahman; Anderson, Paul; Burnett, Gary R; Lynch, Richard J M; Tomlins, Peter H

    2017-02-01

    Erosive tissue-loss in dental enamel is of significant clinical concern because the net loss of enamel is irreversible, however, initial erosion is reversible. Micro-hardness testing is a standard method for measuring initial erosion, but its invasive nature has led to the investigation of alternative measurement techniques. Optical coherence tomography (OCT) is an attractive alternative because of its ability to non-invasively image three-dimensional volumes. In this study, a four-dimensional OCT system is used to longitudinally measure bovine enamel undergoing a continuous erosive challenge. A new method of analyzing 3D OCT volumes is introduced that compares intensity projections of the specimen surface by calculating the slope of a linear regression line between corresponding pixel intensities and the associated correlation coefficient. The OCT correlation measurements are compared to micro-hardness data and found to exhibit a linear relationship. The results show that this method is a sensitive technique for the investigation of the formation of early stage erosive lesions.

  15. Longitudinal correlation of 3D OCT to detect early stage erosion in bovine enamel

    PubMed Central

    Aden, Abdirahman; Anderson, Paul; Burnett, Gary R.; Lynch, Richard J. M.; Tomlins, Peter H.

    2017-01-01

    Erosive tissue-loss in dental enamel is of significant clinical concern because the net loss of enamel is irreversible, however, initial erosion is reversible. Micro-hardness testing is a standard method for measuring initial erosion, but its invasive nature has led to the investigation of alternative measurement techniques. Optical coherence tomography (OCT) is an attractive alternative because of its ability to non-invasively image three-dimensional volumes. In this study, a four-dimensional OCT system is used to longitudinally measure bovine enamel undergoing a continuous erosive challenge. A new method of analyzing 3D OCT volumes is introduced that compares intensity projections of the specimen surface by calculating the slope of a linear regression line between corresponding pixel intensities and the associated correlation coefficient. The OCT correlation measurements are compared to micro-hardness data and found to exhibit a linear relationship. The results show that this method is a sensitive technique for the investigation of the formation of early stage erosive lesions. PMID:28270996

  16. Contour detection based on brightness and contour completion

    NASA Astrophysics Data System (ADS)

    Zou, Lamei; Wan, Min; Jin, Liujia; Gao, Yahong; Yang, Weidong

    2015-12-01

    The further research of visual processing mechanism provides a new idea for contour detection. On the primary visual cortex, the non-classical receptive field of the neurons has the orientation selectivity exerts suppression effect on the response of classical receptive field, which influences edge or line perception. Based on the suppression property of non-classical receptive field and contour completion, this paper proposed a contour detection method based on brightness and contour completion. The experiment shows that the proposed method can not only effectively eliminate clutter information, but also connect the broken contour points by taking advantage of contour completion.

  17. Detection of polyaromatic compounds using antibody-based fiberoptics fluoroimmunosensors

    SciTech Connect

    Vo-Dinh, T.; Tromberg, B.J.; Griffin, G.D.; Ambrose, K.R.; Sepaniak, M.J.; Alarie, J.P.

    1987-01-01

    In this work we have investigated the performance of an antibody-based fiberoptics sensor for the detection of the carcinogen benzo(a)pyrene and its DNA-adduct product BP-tetrol. The excellent sensitivity of this device - femtomole limits of detection for BP - illustrates that it has considerable potential to perform analyses of chemical and biological samples at trace levels in complex matrices. The results indicate that fiberoptics-based fluoroimmunosensors can be useful in a wide spectrum of biochemical and clinical analyses. 17 refs., 4 figs., 1 tab.

  18. DNA methylation detection based on difference of base content

    NASA Astrophysics Data System (ADS)

    Sato, Shinobu; Ohtsuka, Keiichi; Honda, Satoshi; Sato, Yusuke; Takenaka, Shigeori

    2016-04-01

    Methylation frequently occurs in cytosines of CpG sites to regulate gene expression. The identification of aberrant methylation of certain genes is important for cancer marker analysis. The aim of this study was to determine the methylation frequency in DNA samples of unknown length and/or concentration. Unmethylated cytosine is known to be converted to thymine following bisulfite treatment and subsequent PCR. For this reason, the AT content in DNA increases with an increasing number of methylation sites. In this study, the fluorescein-carrying bis-acridinyl peptide (FKA) molecule was used for the detection of methylation frequency. FKA contains fluorescein and two acridine moieties, which together allow for the determination of the AT content of double-stranded DNA fragments. Methylated and unmethylated human genomes were subjected to bisulfide treatment and subsequent PCR using primers specific for the CFTR, CDH4, DBC1, and NPY genes. The AT content in the resulting PCR products was estimated by FKA, and AT content estimations were found to be in good agreement with those determined by DNA sequencing. This newly developed method may be useful for determining methylation frequencies of many PCR products by measuring the fluorescence in samples excited at two different wavelengths.

  19. VoIP attacks detection engine based on neural network

    NASA Astrophysics Data System (ADS)

    Safarik, Jakub; Slachta, Jiri

    2015-05-01

    The security is crucial for any system nowadays, especially communications. One of the most successful protocols in the field of communication over IP networks is Session Initiation Protocol. It is an open-source project used by different kinds of applications, both open-source and proprietary. High penetration and text-based principle made SIP number one target in IP telephony infrastructure, so security of SIP server is essential. To keep up with hackers and to detect potential malicious attacks, security administrator needs to monitor and evaluate SIP traffic in the network. But monitoring and following evaluation could easily overwhelm the security administrator in networks, typically in networks with a number of SIP servers, users and logically or geographically separated networks. The proposed solution lies in automatic attack detection systems. The article covers detection of VoIP attacks through a distributed network of nodes. Then the gathered data analyze aggregation server with artificial neural network. Artificial neural network means multilayer perceptron network trained with a set of collected attacks. Attack data could also be preprocessed and verified with a self-organizing map. The source data is detected by distributed network of detection nodes. Each node contains a honeypot application and traffic monitoring mechanism. Aggregation of data from each node creates an input for neural networks. The automatic classification on a centralized server with low false positive detection reduce the cost of attack detection resources. The detection system uses modular design for easy deployment in final infrastructure. The centralized server collects and process detected traffic. It also maintains all detection nodes.

  20. Correlation of Transcranial Color Doppler to N20 Somatosensory Evoked Potential Detects Ischemic Penumbra in Subarachnoid Hemorrhage

    PubMed Central

    Di Pasquale, Piero; Zanatta, Paolo; Morghen, Ilaria; Bosco, Enrico; Forini, Elena

    2011-01-01

    Background: Normal subjects present interhemispheric symmetry of middle cerebral artery (MCA) mean flow velocity and N20 cortical somatosensory evoked potential (SSEP). Subarachnoid haemorrhage (SAH) can modify this pattern, since high regional brain vascular resistances increase blood flow velocity, and impaired regional brain perfusion reduces N20 amplitude. The aim of the study is to investigate the variability of MCA resistances and N20 amplitude between hemispheres in SAH. Methods: Measurements of MCA blood flow velocity (vMCA) by transcranial color-Doppler and median nerve SSEP were bilaterally performed in sixteen patients. MCA vascular changes on the compromised hemisphere were calculated as a ratio of the reciprocal of mean flow velocity (1/vMCA) to contralateral value and correlated to the simultaneous variations of interhemispheric ratio of N20 amplitude, within each subject. Data were analysed with respect to neuroimaging of MCA supplied areas. Results: Both interhemispheric ratios of 1/vMCA and N20 amplitude were detected >0.65 (p <0,01) in patients without neuroimages of injury. Both ratios became <0.65 (p <0.01) when patients showed unilateral images of ischemic penumbra and returned >0.65 if penumbra disappeared. The two ratios no longer correlated after structural lesion developed, as N20 detected in the damaged side remained pathological (ratio <0.65), whereas 1/vMCA reverted to symmetric interhemispheric state (ratio >0.65), suggesting a luxury perfusion. Conclusion: Variations of interhemispheric ratios of MCA resistance and cortical N20 amplitude correlate closely in SAH and allow identification of the reversible ischemic penumbra threshold, when both ratios become <0.65. The correlation is lost when structural damage develops. PMID:21660110