WorldWideScience

Sample records for signal detection methods

  1. Sensing Methods for Detecting Analog Television Signals

    Science.gov (United States)

    Rahman, Mohammad Azizur; Song, Chunyi; Harada, Hiroshi

    This paper introduces a unified method of spectrum sensing for all existing analog television (TV) signals including NTSC, PAL and SECAM. We propose a correlation based method (CBM) with a single reference signal for sensing any analog TV signals. In addition we also propose an improved energy detection method. The CBM approach has been implemented in a hardware prototype specially designed for participating in Singapore TV white space (WS) test trial conducted by Infocomm Development Authority (IDA) of the Singapore government. Analytical and simulation results of the CBM method will be presented in the paper, as well as hardware testing results for sensing various analog TV signals. Both AWGN and fading channels will be considered. It is shown that the theoretical results closely match with those from simulations. Sensing performance of the hardware prototype will also be presented in fading environment by using a fading simulator. We present performance of the proposed techniques in terms of probability of false alarm, probability of detection, sensing time etc. We also present a comparative study of the various techniques.

  2. System and Method for Multi-Wavelength Optical Signal Detection

    Science.gov (United States)

    McGlone, Thomas D. (Inventor)

    2017-01-01

    The system and method for multi-wavelength optical signal detection enables the detection of optical signal levels significantly below those processed at the discrete circuit level by the use of mixed-signal processing methods implemented with integrated circuit technologies. The present invention is configured to detect and process small signals, which enables the reduction of the optical power required to stimulate detection networks, and lowers the required laser power to make specific measurements. The present invention provides an adaptation of active pixel networks combined with mixed-signal processing methods to provide an integer representation of the received signal as an output. The present invention also provides multi-wavelength laser detection circuits for use in various systems, such as a differential absorption light detection and ranging system.

  3. System and method for detection of dispersed broadband signals

    Science.gov (United States)

    Qian, S.; Dunham, M.E.

    1999-06-08

    A system and method for detecting the presence of dispersed broadband signals in real time are disclosed. The present invention utilizes a bank of matched filters for detecting the received dispersed broadband signals. Each matched filter uses a respective robust time template that has been designed to approximate the dispersed broadband signals of interest, and each time template varies across a spectrum of possible dispersed broadband signal time templates. The received dispersed broadband signal x(t) is received by each of the matched filters, and if one or more matches occurs, then the received data is determined to have signal data of interest. This signal data can then be analyzed and/or transmitted to Earth for analysis, as desired. The system and method of the present invention will prove extremely useful in many fields, including satellite communications, plasma physics, and interstellar research. The varying time templates used in the bank of matched filters are determined as follows. The robust time domain template is assumed to take the form w(t)=A(t)cos[l brace]2[phi](t)[r brace]. Since the instantaneous frequency f(t) is known to be equal to the derivative of the phase [phi](t), the trajectory of a joint time-frequency representation of x(t) is used as an approximation of [phi][prime](t). 10 figs.

  4. Signal anomaly detection using modified CUSUM [cumulative sum] method

    International Nuclear Information System (INIS)

    Morgenstern, V.; Upadhyaya, B.R.; Benedetti, M.

    1988-01-01

    An important aspect of detection of anomalies in signals is the identification of changes in signal behavior caused by noise, jumps, changes in band-width, sudden pulses and signal bias. A methodology is developed to identify, isolate and characterize these anomalies using a modification of the cumulative sum (CUSUM) approach. The new algorithm performs anomaly detection at three levels and is implemented on a general purpose computer. 7 refs., 4 figs

  5. Generation and coherent detection of QPSK signal using a novel method of digital signal processing

    Science.gov (United States)

    Zhao, Yuan; Hu, Bingliang; He, Zhen-An; Xie, Wenjia; Gao, Xiaohui

    2018-02-01

    We demonstrate an optical quadrature phase-shift keying (QPSK) signal transmitter and an optical receiver for demodulating optical QPSK signal with homodyne detection and digital signal processing (DSP). DSP on the homodyne detection scheme is employed without locking the phase of the local oscillator (LO). In this paper, we present an extracting one-dimensional array of down-sampling method for reducing unwanted samples of constellation diagram measurement. Such a novel scheme embodies the following major advantages over the other conventional optical QPSK signal detection methods. First, this homodyne detection scheme does not need strict requirement on LO in comparison with linear optical sampling, such as having a flat spectral density and phase over the spectral support of the source under test. Second, the LabVIEW software is directly used for recovering the QPSK signal constellation without employing complex DSP circuit. Third, this scheme is applicable to multilevel modulation formats such as M-ary PSK and quadrature amplitude modulation (QAM) or higher speed signals by making minor changes.

  6. An Alternative Method for Tilecal Signal Detection and Amplitude Estimation

    CERN Document Server

    Sotto-Maior Peralva, B; The ATLAS collaboration; Manhães de Andrade Filho, L; Manoel de Seixas, J

    2011-01-01

    The Barrel Hadronic calorimeter of ATLAS (Tilecal) is a detector used in the reconstruction of hadrons, jets, muons and missing transverse energy from the proton-proton collisions at the Large Hadron Collider (LHC). It comprises 10,000 channels in four readout partitions and each calorimeter cell is made of two readout channels for redundancy. The energy deposited by the particles produced in the collisions is read out by the several readout channels and its value is estimated by an optimal filtering algorithm, which reconstructs the amplitude and the time of the digitized signal pulse sampled every 25 ns. This work deals with signal detection and amplitude estimation for the Tilecal under low signal-to-noise ratio (SNR) conditions. It explores the applicability (at the cell level) of a Matched Filter (MF), which is known to be the optimal signal detector in terms of the SNR. Moreover, it investigates the impact of signal detection when summing both signals from the same cell before estimating the amplitude, ...

  7. Signal detection

    International Nuclear Information System (INIS)

    Tholomier, M.

    1985-01-01

    In a scanning electron microscope, whatever is the measured signal, the same set is found: incident beam, sample, signal detection, signal amplification. The resulting signal is used to control the spot luminosity with the observer cathodoscope. This is synchronized with the beam scanning on the sample; on the cathodoscope, the image in secondary electrons, backscattered electrons,... of the sample surface is reconstituted. The best compromise must be found between a register time low enough to remove eventual variations (under the incident beam) of the nature of the observed phenomenon, and a good spatial resolution of the image and a signal-to-noise ratio high enough. The noise is one of the basic limitations of the scanning electron microscope performance. The whose measurement line must be optimized to reduce it [fr

  8. A new ultrasonic signal amplification method for detection of bacteria

    Science.gov (United States)

    Kant Shukla, Shiva; Resa López, Pablo; Sierra Sánchez, Carlos; Urréjola, José; Segura, Luis Elvira

    2012-10-01

    A new method is presented that increases the sensitivity of ultrasound-based techniques for detection of bacteria. The technique was developed for the detection of catalase-positive microorganisms. It uses a bubble trapping medium containing hydrogen peroxide that is mixed with the sample for microbiological evaluation. The enzyme catalase is present in catalase-positive bacteria, which induces a rapid hydrolysis of hydrogen peroxide, forming bubbles which remain in the medium. This reaction results in the amplification of the mechanical changes that the microorganisms produce in the medium. The effect can be detected by means of ultrasonic wave amplitude continuous measurement since the bubbles increase the ultrasonic attenuation significantly. It is shown that microorganism concentrations of the order of 105 cells ml-1 can be detected using this method. This allows an improvement of three orders of magnitude in the ultrasonic detection threshold of microorganisms in conventional culture media, and is competitive with modern rapid microbiological methods. It can also be used for the characterization of the enzymatic activity.

  9. A new ultrasonic signal amplification method for detection of bacteria

    International Nuclear Information System (INIS)

    Shukla, Shiva Kant; López, Pablo Resa; Sánchez, Carlos Sierra; Segura, Luis Elvira; Urréjola, José

    2012-01-01

    A new method is presented that increases the sensitivity of ultrasound-based techniques for detection of bacteria. The technique was developed for the detection of catalase-positive microorganisms. It uses a bubble trapping medium containing hydrogen peroxide that is mixed with the sample for microbiological evaluation. The enzyme catalase is present in catalase-positive bacteria, which induces a rapid hydrolysis of hydrogen peroxide, forming bubbles which remain in the medium. This reaction results in the amplification of the mechanical changes that the microorganisms produce in the medium. The effect can be detected by means of ultrasonic wave amplitude continuous measurement since the bubbles increase the ultrasonic attenuation significantly. It is shown that microorganism concentrations of the order of 10 5 cells ml −1 can be detected using this method. This allows an improvement of three orders of magnitude in the ultrasonic detection threshold of microorganisms in conventional culture media, and is competitive with modern rapid microbiological methods. It can also be used for the characterization of the enzymatic activity. (paper)

  10. Boiling anomaly detection by various signal characterization methods

    International Nuclear Information System (INIS)

    Sakuma, M.; Kozma, R.; Kitamura, M.; Schoonewelle, H.; Hoogenboom, J.E.

    1996-01-01

    In order to detect anomalies in the early stage for complex dynamical systems like nuclear power plants, it is important to characterize various statistical features of the data acquired in normal operating condition. In this paper, concept of hierarchical anomaly monitoring method is outlined, which is based on the diversification principle. In addition to usual time and frequency domain analysis (FFT, APDF, MAR-SPRT), other analysis (wavelet, fractal, etc.) are performed. As soon as any inconsistency arises in the results of the analysis on the upper level, a thorough analysis is initiated. A comparison among these methods is performed and the efficiency of the diversification approach has been demonstrated through simulated boiling anomalies in nuclear reactors. (authors)

  11. A Universal Fast Colorimetric Method for DNA Signal Detection with DNA Strand Displacement and Gold Nanoparticles

    Directory of Open Access Journals (Sweden)

    Xin Li

    2015-01-01

    Full Text Available DNA or gene signal detection is of great significance in many fields including medical examination, intracellular molecular monitoring, and gene disease signal diagnosis, but detection of DNA or gene signals in a low concentration with instant visual results remains a challenge. In this work, a universal fast and visual colorimetric detection method for DNA signals is proposed. Specifically, a DNA signal amplification “circuit” based on DNA strand displacement is firstly designed to amplify the target DNA signals, and then thiol modified hairpin DNA strands and gold nanoparticles are used to make signal detection results visualized in a colorimetric manner. If the target DNA signal exists, the gold nanoparticles aggregate and settle down with color changing from dark red to grey quickly; otherwise, the gold nanoparticles’ colloids remain stable in dark red. The proposed method provides a novel way to detect quickly DNA or gene signals in low concentrations with instant visual results. When applied in real-life, it may provide a universal colorimetric method for gene disease signal diagnosis.

  12. Small Displacement Detection of Biological Signals Using the Cyclic Frequency Method

    Directory of Open Access Journals (Sweden)

    Dan Zhang

    2015-01-01

    Full Text Available A new signal processing method called the Cyclic Frequency method is proposed for small displacement detection of vital signals such as heart rate and respiration using the CW radar method. We have presented experimental results of small displacement detection to confirm the validity of the method. The displacement amplitude 2.5 mm can be detected with a propagation frequency of 24.15 GHz. We may increase the propagation frequency for smaller displacement amplitude or target velocity.

  13. Novel method for detection of Sleep Apnoea using respiration signals

    DEFF Research Database (Denmark)

    Nielsen, Kristine Carmes; Kempfner, Lykke; Sørensen, Helge Bjarup Dissing

    2014-01-01

    desaturations > 3%, extracted from the thorax and abdomen respiration effort belts, and the oxyhemoglobin saturation (SaO2), fed to an Elastic Net classifier and validated according to American Academy of Sleep Medicine (AASM) using the patients' AHI value. The method was applied to 109 patient recordings......Polysomnography (PSG) studies are considered the “gold standard” for the diagnosis of Sleep Apnoea (SA). Identifying cessations of breathing from long-lasting PSG recordings manually is a labour-intensive and time-consuming task for sleep specialist, associated with inter-scorer variability...

  14. A method for detecting nonlinear determinism in normal and epileptic brain EEG signals.

    Science.gov (United States)

    Meghdadi, Amir H; Fazel-Rezai, Reza; Aghakhani, Yahya

    2007-01-01

    A robust method of detecting determinism for short time series is proposed and applied to both healthy and epileptic EEG signals. The method provides a robust measure of determinism through characterizing the trajectories of the signal components which are obtained through singular value decomposition. Robustness of the method is shown by calculating proposed index of determinism at different levels of white and colored noise added to a simulated chaotic signal. The method is shown to be able to detect determinism at considerably high levels of additive noise. The method is then applied to both intracranial and scalp EEG recordings collected in different data sets for healthy and epileptic brain signals. The results show that for all of the studied EEG data sets there is enough evidence of determinism. The determinism is more significant for intracranial EEG recordings particularly during seizure activity.

  15. Onset Detection in Surface Electromyographic Signals: A Systematic Comparison of Methods

    Directory of Open Access Journals (Sweden)

    Claus Flachenecker

    2001-06-01

    Full Text Available Various methods to determine the onset of the electromyographic activity which occurs in response to a stimulus have been discussed in the literature over the last decade. Due to the stochastic characteristic of the surface electromyogram (SEMG, onset detection is a challenging task, especially in weak SEMG responses. The performance of the onset detection methods were tested, mostly by comparing their automated onset estimations to the manually determined onsets found by well-trained SEMG examiners. But a systematic comparison between methods, which reveals the benefits and the drawbacks of each method compared to the other ones and shows the specific dependence of the detection accuracy on signal parameters, is still lacking. In this paper, several classical threshold-based approaches as well as some statistically optimized algorithms were tested on large samples of simulated SEMG data with well-known signal parameters. Rating between methods is performed by comparing their performance to that of a statistically optimal maximum likelihood estimator which serves as reference method. In addition, performance was evaluated on real SEMG data obtained in a reaction time experiment. Results indicate that detection behavior strongly depends on SEMG parameters, such as onset rise time, signal-to-noise ratio or background activity level. It is shown that some of the threshold-based signal-power-estimation procedures are very sensitive to signal parameters, whereas statistically optimized algorithms are generally more robust.

  16. Delay Pressure Detection Method to Eliminate Pump Pressure Interference on the Downhole Mud Pressure Signals

    Directory of Open Access Journals (Sweden)

    Yue Shen

    2013-01-01

    Full Text Available The feasibility of applying delay pressure detection method to eliminate mud pump pressure interference on the downhole mud pressure signals is studied. Two pressure sensors mounted on the mud pipe in some distance apart are provided to detect the downhole mud continuous pressure wave signals on the surface according to the delayed time produced by mud pressure wave transmitting between the two sensors. A mathematical model of delay pressure detection is built by analysis of transmission path between mud pump pressure interference and downhole mud pressure signals. Considering pressure signal transmission characteristics of the mud pipe, a mathematical model of ideal low-pass filter for limited frequency band signal is introduced to study the pole frequency impact on the signal reconstruction and the constraints of pressure sensor distance are obtained by pole frequencies analysis. Theoretical calculation and numerical simulation show that the method can effectively eliminate mud pump pressure interference and the downhole mud continuous pressure wave signals can be reconstructed successfully with a significant improvement in signal-to-noise ratio (SNR in the condition of satisfying the constraints of pressure sensor distance.

  17. Early detection of pharmacovigilance signals with automated methods based on false discovery rates: a comparative study.

    Science.gov (United States)

    Ahmed, Ismaïl; Thiessard, Frantz; Miremont-Salamé, Ghada; Haramburu, Françoise; Kreft-Jais, Carmen; Bégaud, Bernard; Tubert-Bitter, Pascale

    2012-06-01

    Improving the detection of drug safety signals has led several pharmacovigilance regulatory agencies to incorporate automated quantitative methods into their spontaneous reporting management systems. The three largest worldwide pharmacovigilance databases are routinely screened by the lower bound of the 95% confidence interval of proportional reporting ratio (PRR₀₂.₅), the 2.5% quantile of the Information Component (IC₀₂.₅) or the 5% quantile of the Gamma Poisson Shrinker (GPS₀₅). More recently, Bayesian and non-Bayesian False Discovery Rate (FDR)-based methods were proposed that address the arbitrariness of thresholds and allow for a built-in estimate of the FDR. These methods were also shown through simulation studies to be interesting alternatives to the currently used methods. The objective of this work was twofold. Based on an extensive retrospective study, we compared PRR₀₂.₅, GPS₀₅ and IC₀₂.₅ with two FDR-based methods derived from the Fisher's exact test and the GPS model (GPS(pH0) [posterior probability of the null hypothesis H₀ calculated from the Gamma Poisson Shrinker model]). Secondly, restricting the analysis to GPS(pH0), we aimed to evaluate the added value of using automated signal detection tools compared with 'traditional' methods, i.e. non-automated surveillance operated by pharmacovigilance experts. The analysis was performed sequentially, i.e. every month, and retrospectively on the whole French pharmacovigilance database over the period 1 January 1996-1 July 2002. Evaluation was based on a list of 243 reference signals (RSs) corresponding to investigations launched by the French Pharmacovigilance Technical Committee (PhVTC) during the same period. The comparison of detection methods was made on the basis of the number of RSs detected as well as the time to detection. Results comparing the five automated quantitative methods were in favour of GPS(pH0) in terms of both number of detections of true signals and

  18. Detection method of nonlinearity errors by statistical signal analysis in heterodyne Michelson interferometer.

    Science.gov (United States)

    Hu, Juju; Hu, Haijiang; Ji, Yinghua

    2010-03-15

    Periodic nonlinearity that ranges from tens of nanometers to a few nanometers in heterodyne interferometer limits its use in high accuracy measurement. A novel method is studied to detect the nonlinearity errors based on the electrical subdivision and the analysis method of statistical signal in heterodyne Michelson interferometer. Under the movement of micropositioning platform with the uniform velocity, the method can detect the nonlinearity errors by using the regression analysis and Jackknife estimation. Based on the analysis of the simulations, the method can estimate the influence of nonlinearity errors and other noises for the dimensions measurement in heterodyne Michelson interferometer.

  19. Damage Detection Method of Wind Turbine Blade Using Acoustic Emission Signal Mapping

    Energy Technology Data Exchange (ETDEWEB)

    Han, Byeong Hee; Yoon, Dong JIn [Korea Research Institute of Standards and Seience, Daejeon (Korea, Republic of)

    2011-02-15

    Acoustic emission(AE) has emerged as a powerful nondestructive tool to detect any further growth or expansion of preexisting defects or to characterize failure mechanisms. Recently, this kind of technique, that is an in-situ monitoring of inside damages of materials or structures, becomes increasingly popular for monitoring the integrity of large structures like a huge wind turbine blade. Therefore, it is required to find a symptom of damage propagation before catastrophic failure through a continuous monitoring. In this study, a new damage location method has been proposed by using signal napping algorithm, and an experimental verification is conducted by using small wind turbine blade specimen: a part of 750 kW real blade. The results show that this new signal mapping method has high advantages such as a flexibility for sensor location, improved accuracy, high detectability. The newly proposed method was compared with traditional AE source location method based on arrival time difference

  20. Very Weak Signals (VWS detected by stacking method according to different astronomical periodicities (HiCum

    Directory of Open Access Journals (Sweden)

    M. van Ruymbeke

    2007-11-01

    Full Text Available A stacking method to detect very weak signals is introduced in this paper. This method is to stack observed data in different well known periodicities according to the astronomical clock since majority geophysical observations are time based. We validated this method by applying it in four different cases. Interactions behind the observed parameters become obviously after it is stacked in two diurnal and semidiurnal tidal periodical waves. Amplitude and phase variations will be also measurable when a sliding windows stacking is used. This could be an important reference to find precursors before some earthquakes and volcanic events, corresponding to attenuations of medium patterns.

  1. "Utilizing" signal detection theory.

    Science.gov (United States)

    Lynn, Spencer K; Barrett, Lisa Feldman

    2014-09-01

    What do inferring what a person is thinking or feeling, judging a defendant's guilt, and navigating a dimly lit room have in common? They involve perceptual uncertainty (e.g., a scowling face might indicate anger or concentration, for which different responses are appropriate) and behavioral risk (e.g., a cost to making the wrong response). Signal detection theory describes these types of decisions. In this tutorial, we show how incorporating the economic concept of utility allows signal detection theory to serve as a model of optimal decision making, going beyond its common use as an analytic method. This utility approach to signal detection theory clarifies otherwise enigmatic influences of perceptual uncertainty on measures of decision-making performance (accuracy and optimality) and on behavior (an inverse relationship between bias magnitude and sensitivity optimizes utility). A "utilized" signal detection theory offers the possibility of expanding the phenomena that can be understood within a decision-making framework. © The Author(s) 2014.

  2. System and method for constructing filters for detecting signals whose frequency content varies with time

    Science.gov (United States)

    Qian, S.; Dunham, M.E.

    1996-11-12

    A system and method are disclosed for constructing a bank of filters which detect the presence of signals whose frequency content varies with time. The present invention includes a novel system and method for developing one or more time templates designed to match the received signals of interest and the bank of matched filters use the one or more time templates to detect the received signals. Each matched filter compares the received signal x(t) with a respective, unique time template that has been designed to approximate a form of the signals of interest. The robust time domain template is assumed to be of the order of w(t)=A(t)cos(2{pi}{phi}(t)) and the present invention uses the trajectory of a joint time-frequency representation of x(t) as an approximation of the instantaneous frequency function {phi}{prime}(t). First, numerous data samples of the received signal x(t) are collected. A joint time frequency representation is then applied to represent the signal, preferably using the time frequency distribution series. The joint time-frequency transformation represents the analyzed signal energy at time t and frequency f, P(t,f), which is a three-dimensional plot of time vs. frequency vs. signal energy. Then P(t,f) is reduced to a multivalued function f(t), a two dimensional plot of time vs. frequency, using a thresholding process. Curve fitting steps are then performed on the time/frequency plot, preferably using Levenberg-Marquardt curve fitting techniques, to derive a general instantaneous frequency function {phi}{prime}(t) which best fits the multivalued function f(t). Integrating {phi}{prime}(t) along t yields {phi}{prime}(t), which is then inserted into the form of the time template equation. A suitable amplitude A(t) is also preferably determined. Once the time template has been determined, one or more filters are developed which each use a version or form of the time template. 7 figs.

  3. Data-driven drug safety signal detection methods in pharmacovigilance using electronic primary care records: A population based study

    Directory of Open Access Journals (Sweden)

    Shang-Ming Zhou

    2017-04-01

    Data-driven analytic methods are a valuable aid to signal detection of ADEs from large electronic health records for drug safety monitoring. This study finds the methods can detect known ADE and so could potentially be used to detect unknown ADE.

  4. Accurate method for luminous transmittance and signal detection quotients measurements in sunglasses lenses

    Science.gov (United States)

    Loureiro, A. D.; Gomes, L. M.; Ventura, L.

    2018-02-01

    The international standard ISO 12312-1 proposes transmittance tests that quantify how dark sunglasses lenses are and whether or not they are suitable for driving. To perform these tests a spectrometer is required. In this study, we present and analyze theoretically an accurate alternative method for performing these measurements using simple components. Using three LEDs and a four-channel sensor we generated weighting functions similar to the standard ones for luminous and traffic lights transmittances. From 89 sunglasses lens spectroscopy data, we calculated luminous transmittance and signal detection quotients using our obtained weighting functions and the standard ones. Mean-difference Tukey plots were used to compare the results. All tested sunglasses lenses were classified in the right category and correctly as suitable or not for driving. The greatest absolute errors for luminous transmittance and red, yellow, green and blue signal detection quotients were 0.15%, 0.17, 0.06, 0.04 and 0.18, respectively. This method will be used in a device capable to perform transmittance tests (visible, traffic lights and ultraviolet (UV)) according to the standard. It is important to measure rightly luminous transmittance and relative visual attenuation quotients to report correctly whether or not sunglasses are suitable for driving. Moreover, standard UV requirements depend on luminous transmittance.

  5. Weak wide-band signal detection method based on small-scale periodic state of Duffing oscillator

    Science.gov (United States)

    Hou, Jian; Yan, Xiao-peng; Li, Ping; Hao, Xin-hong

    2018-03-01

    The conventional Duffing oscillator weak signal detection method, which is based on a strong reference signal, has inherent deficiencies. To address these issues, the characteristics of the Duffing oscillatorʼs phase trajectory in a small-scale periodic state are analyzed by introducing the theory of stopping oscillation system. Based on this approach, a novel Duffing oscillator weak wide-band signal detection method is proposed. In this novel method, the reference signal is discarded, and the to-be-detected signal is directly used as a driving force. By calculating the cosine function of a phase space angle, a single Duffing oscillator can be used for weak wide-band signal detection instead of an array of uncoupled Duffing oscillators. Simulation results indicate that, compared with the conventional Duffing oscillator detection method, this approach performs better in frequency detection intervals, and reduces the signal-to-noise ratio detection threshold, while improving the real-time performance of the system. Project supported by the National Natural Science Foundation of China (Grant No. 61673066).

  6. Classification methods to detect sleep apnea in adults based on respiratory and oximetry signals: a systematic review.

    Science.gov (United States)

    Uddin, M B; Chow, C M; Su, S W

    2018-03-26

    Sleep apnea (SA), a common sleep disorder, can significantly decrease the quality of life, and is closely associated with major health risks such as cardiovascular disease, sudden death, depression, and hypertension. The normal diagnostic process of SA using polysomnography is costly and time consuming. In addition, the accuracy of different classification methods to detect SA varies with the use of different physiological signals. If an effective, reliable, and accurate classification method is developed, then the diagnosis of SA and its associated treatment will be time-efficient and economical. This study aims to systematically review the literature and present an overview of classification methods to detect SA using respiratory and oximetry signals and address the automated detection approach. Sixty-two included studies revealed the application of single and multiple signals (respiratory and oximetry) for the diagnosis of SA. Both airflow and oxygen saturation signals alone were effective in detecting SA in the case of binary decision-making, whereas multiple signals were good for multi-class detection. In addition, some machine learning methods were superior to the other classification methods for SA detection using respiratory and oximetry signals. To deal with the respiratory and oximetry signals, a good choice of classification method as well as the consideration of associated factors would result in high accuracy in the detection of SA. An accurate classification method should provide a high detection rate with an automated (independent of human action) analysis of respiratory and oximetry signals. Future high-quality automated studies using large samples of data from multiple patient groups or record batches are recommended.

  7. Methods for detection and characterization of signals in noisy data with the Hilbert-Huang transform

    International Nuclear Information System (INIS)

    Stroeer, Alexander; Cannizzo, John K.; Camp, Jordan B.; Gagarin, Nicolas

    2009-01-01

    The Hilbert-Huang transform is a novel, adaptive approach to time series analysis that does not make assumptions about the data form. Its adaptive, local character allows the decomposition of nonstationary signals with high time-frequency resolution but also renders it susceptible to degradation from noise. We show that complementing the Hilbert-Huang transform with techniques such as zero-phase filtering, kernel density estimation and Fourier analysis allows it to be used effectively to detect and characterize signals with low signal-to-noise ratios.

  8. A Hybrid Wavelet-Based Method for the Peak Detection of Photoplethysmography Signals

    Directory of Open Access Journals (Sweden)

    Suyi Li

    2017-01-01

    Full Text Available The noninvasive peripheral oxygen saturation (SpO2 and the pulse rate can be extracted from photoplethysmography (PPG signals. However, the accuracy of the extraction is directly affected by the quality of the signal obtained and the peak of the signal identified; therefore, a hybrid wavelet-based method is proposed in this study. Firstly, we suppressed the partial motion artifacts and corrected the baseline drift by using a wavelet method based on the principle of wavelet multiresolution. And then, we designed a quadratic spline wavelet modulus maximum algorithm to identify the PPG peaks automatically. To evaluate this hybrid method, a reflective pulse oximeter was used to acquire ten subjects’ PPG signals under sitting, raising hand, and gently walking postures, and the peak recognition results on the raw signal and on the corrected signal were compared, respectively. The results showed that the hybrid method not only corrected the morphologies of the signal well but also optimized the peaks identification quality, subsequently elevating the measurement accuracy of SpO2 and the pulse rate. As a result, our hybrid wavelet-based method profoundly optimized the evaluation of respiratory function and heart rate variability analysis.

  9. A Hybrid Wavelet-Based Method for the Peak Detection of Photoplethysmography Signals.

    Science.gov (United States)

    Li, Suyi; Jiang, Shanqing; Jiang, Shan; Wu, Jiang; Xiong, Wenji; Diao, Shu

    2017-01-01

    The noninvasive peripheral oxygen saturation (SpO 2 ) and the pulse rate can be extracted from photoplethysmography (PPG) signals. However, the accuracy of the extraction is directly affected by the quality of the signal obtained and the peak of the signal identified; therefore, a hybrid wavelet-based method is proposed in this study. Firstly, we suppressed the partial motion artifacts and corrected the baseline drift by using a wavelet method based on the principle of wavelet multiresolution. And then, we designed a quadratic spline wavelet modulus maximum algorithm to identify the PPG peaks automatically. To evaluate this hybrid method, a reflective pulse oximeter was used to acquire ten subjects' PPG signals under sitting, raising hand, and gently walking postures, and the peak recognition results on the raw signal and on the corrected signal were compared, respectively. The results showed that the hybrid method not only corrected the morphologies of the signal well but also optimized the peaks identification quality, subsequently elevating the measurement accuracy of SpO 2 and the pulse rate. As a result, our hybrid wavelet-based method profoundly optimized the evaluation of respiratory function and heart rate variability analysis.

  10. A Hybrid Wavelet-Based Method for the Peak Detection of Photoplethysmography Signals

    Science.gov (United States)

    Jiang, Shanqing; Jiang, Shan; Wu, Jiang; Xiong, Wenji

    2017-01-01

    The noninvasive peripheral oxygen saturation (SpO2) and the pulse rate can be extracted from photoplethysmography (PPG) signals. However, the accuracy of the extraction is directly affected by the quality of the signal obtained and the peak of the signal identified; therefore, a hybrid wavelet-based method is proposed in this study. Firstly, we suppressed the partial motion artifacts and corrected the baseline drift by using a wavelet method based on the principle of wavelet multiresolution. And then, we designed a quadratic spline wavelet modulus maximum algorithm to identify the PPG peaks automatically. To evaluate this hybrid method, a reflective pulse oximeter was used to acquire ten subjects' PPG signals under sitting, raising hand, and gently walking postures, and the peak recognition results on the raw signal and on the corrected signal were compared, respectively. The results showed that the hybrid method not only corrected the morphologies of the signal well but also optimized the peaks identification quality, subsequently elevating the measurement accuracy of SpO2 and the pulse rate. As a result, our hybrid wavelet-based method profoundly optimized the evaluation of respiratory function and heart rate variability analysis. PMID:29250135

  11. Fault Detection in High Speed Helical Gears Considering Signal Processing Method in Real Simulation

    Directory of Open Access Journals (Sweden)

    Amir Ali Tabatabai Adnani

    Full Text Available Abstract In the present study, in order to detect the fault of the gearmeshs, two engaged gears based on research department of a major automotive company have been modeled. First off, by using the CATIA software the fault was induced to the output gear. Then, the faulty gearmesh and non-faulty gearmesh is modeled to find the fault pattern to predict and estimate the failure of the gearmesh. The induced defect is according to the frequently practical fault that takes place to the teeth of gears. In order to record the acceleration signals to calculate the decomposition algorithm, mount the accelerometer on accessible place of the output shaft to recognize the pattern. Then, for more realistic simulation, noise is added to the output signal. At the first step by means of Butterworth low pass digital, the noise has to be removed from signals after that by using the Empirical Mode Decomposition (EMD, signals have decomposed into the Instinct Mode Function (IMF and every IMF were tested by using the Instantaneous Frequency (IF in way of Hillbert Transform (HT. For this purpose a code was developed in MATLAB software. Then, in order to detect the presence of the fault the frequency spectrum of IMF's are created and defect is detected in gearmesh frequency of the spectrum.

  12. Time-frequency energy density precipitation method for time-of-flight extraction of narrowband Lamb wave detection signals

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Y., E-mail: thuzhangyu@foxmail.com; Huang, S. L., E-mail: huangsling@tsinghua.edu.cn; Wang, S.; Zhao, W. [State Key Laboratory of Power Systems, Department of Electrical Engineering, Tsinghua University, Beijing 100084 (China)

    2016-05-15

    The time-of-flight of the Lamb wave provides an important basis for defect evaluation in metal plates and is the input signal for Lamb wave tomographic imaging. However, the time-of-flight can be difficult to acquire because of the Lamb wave dispersion characteristics. This work proposes a time-frequency energy density precipitation method to accurately extract the time-of-flight of narrowband Lamb wave detection signals in metal plates. In the proposed method, a discrete short-time Fourier transform is performed on the narrowband Lamb wave detection signals to obtain the corresponding discrete time-frequency energy density distribution. The energy density values at the center frequency for all discrete time points are then calculated by linear interpolation. Next, the time-domain energy density curve focused on that center frequency is precipitated by least squares fitting of the calculated energy density values. Finally, the peak times of the energy density curve obtained relative to the initial pulse signal are extracted as the time-of-flight for the narrowband Lamb wave detection signals. An experimental platform is established for time-of-flight extraction of narrowband Lamb wave detection signals, and sensitivity analysis of the proposed time-frequency energy density precipitation method is performed in terms of propagation distance, dispersion characteristics, center frequency, and plate thickness. For comparison, the widely used Hilbert–Huang transform method is also implemented for time-of-flight extraction. The results show that the time-frequency energy density precipitation method can accurately extract the time-of-flight with relative error of <1% and thus can act as a universal time-of-flight extraction method for narrowband Lamb wave detection signals.

  13. Time-frequency energy density precipitation method for time-of-flight extraction of narrowband Lamb wave detection signals

    International Nuclear Information System (INIS)

    Zhang, Y.; Huang, S. L.; Wang, S.; Zhao, W.

    2016-01-01

    The time-of-flight of the Lamb wave provides an important basis for defect evaluation in metal plates and is the input signal for Lamb wave tomographic imaging. However, the time-of-flight can be difficult to acquire because of the Lamb wave dispersion characteristics. This work proposes a time-frequency energy density precipitation method to accurately extract the time-of-flight of narrowband Lamb wave detection signals in metal plates. In the proposed method, a discrete short-time Fourier transform is performed on the narrowband Lamb wave detection signals to obtain the corresponding discrete time-frequency energy density distribution. The energy density values at the center frequency for all discrete time points are then calculated by linear interpolation. Next, the time-domain energy density curve focused on that center frequency is precipitated by least squares fitting of the calculated energy density values. Finally, the peak times of the energy density curve obtained relative to the initial pulse signal are extracted as the time-of-flight for the narrowband Lamb wave detection signals. An experimental platform is established for time-of-flight extraction of narrowband Lamb wave detection signals, and sensitivity analysis of the proposed time-frequency energy density precipitation method is performed in terms of propagation distance, dispersion characteristics, center frequency, and plate thickness. For comparison, the widely used Hilbert–Huang transform method is also implemented for time-of-flight extraction. The results show that the time-frequency energy density precipitation method can accurately extract the time-of-flight with relative error of <1% and thus can act as a universal time-of-flight extraction method for narrowband Lamb wave detection signals.

  14. Time-frequency energy density precipitation method for time-of-flight extraction of narrowband Lamb wave detection signals.

    Science.gov (United States)

    Zhang, Y; Huang, S L; Wang, S; Zhao, W

    2016-05-01

    The time-of-flight of the Lamb wave provides an important basis for defect evaluation in metal plates and is the input signal for Lamb wave tomographic imaging. However, the time-of-flight can be difficult to acquire because of the Lamb wave dispersion characteristics. This work proposes a time-frequency energy density precipitation method to accurately extract the time-of-flight of narrowband Lamb wave detection signals in metal plates. In the proposed method, a discrete short-time Fourier transform is performed on the narrowband Lamb wave detection signals to obtain the corresponding discrete time-frequency energy density distribution. The energy density values at the center frequency for all discrete time points are then calculated by linear interpolation. Next, the time-domain energy density curve focused on that center frequency is precipitated by least squares fitting of the calculated energy density values. Finally, the peak times of the energy density curve obtained relative to the initial pulse signal are extracted as the time-of-flight for the narrowband Lamb wave detection signals. An experimental platform is established for time-of-flight extraction of narrowband Lamb wave detection signals, and sensitivity analysis of the proposed time-frequency energy density precipitation method is performed in terms of propagation distance, dispersion characteristics, center frequency, and plate thickness. For comparison, the widely used Hilbert-Huang transform method is also implemented for time-of-flight extraction. The results show that the time-frequency energy density precipitation method can accurately extract the time-of-flight with relative error of wave detection signals.

  15. Overview of frequency bandwidth determination techniques of useful signal in case of leaks detection by correlation method

    International Nuclear Information System (INIS)

    Faerman, V A; Avramchuk, V S; Luneva, E E

    2014-01-01

    In this paper an overview of useful signal detection methods on the background of intense noise and limits determination methods of useful signal is presented. The following features are considered: peculiarities of usage of correlation analysis, cross-amplitude spectrum, coherence function, cross-phase spectrum, time-frequency correlation function in case of frequency limits determination as well as leaks detection in pipelines. The possibility of using time-frequency correlation function for solving above named issues is described. Time- frequency correlation function provides information about the signals correlation for each of the investigated frequency bands. Data about location of peaks on the surface plot of a time- frequency correlation function allows making an assumption about the spectral composition of useful signal and its frequency boundaries

  16. Detection of a periodic structure hidden in random background: the role of signal amplitude in the matched filter detection method

    International Nuclear Information System (INIS)

    Vani, V C; Chatterjee, S

    2010-01-01

    The matched filter method for detecting a periodic structure on a surface hidden behind randomness is known to detect up to (r 0 /Λ)≥0.11, where r 0 is the coherence length of light on scattering from the rough part and Λ is the wavelength of the periodic part of the surface-the above limit being much lower than what is allowed by conventional detection methods. The primary goal of this technique is the detection and characterization of the periodic structure hidden behind randomness without the use of any complicated experimental or computational procedures. This paper examines this detection procedure for various values of the amplitude a of the periodic part beginning from a=0 to small finite values of a. We thus address the importance of the following quantities: '(a/λ)', which scales the amplitude of the periodic part with the wavelength of light, and (r 0 /Λ), in determining the detectability of the intensity peaks.

  17. A Novel Method for Detection of Epilepsy in Short and Noisy EEG Signals Using Ordinal Pattern Analysis

    Directory of Open Access Journals (Sweden)

    Iman Veisi

    2010-03-01

    Full Text Available Introduction: In this paper, a novel complexity measure is proposed to detect dynamical changes in nonlinear systems using ordinal pattern analysis of time series data taken from the system. Epilepsy is considered as a dynamical change in nonlinear and complex brain system. The ability of the proposed measure for characterizing the normal and epileptic EEG signals when the signal is short or is contaminated with noise is investigated and compared with some traditional chaos-based measures. Materials and Methods: In the proposed method, the phase space of the time series is reconstructed and then partitioned using ordinal patterns. The partitions can be labeled using a set of symbols. Therefore, the state trajectory is converted to a symbol sequence. A finite state machine is then constructed to model the sequence. A new complexity measure is proposed to detect dynamical changes using the state transition matrix of the state machine. The proposed complexity measure was applied to detect epilepsy in short and noisy EEG signals and the results were compared with some chaotic measures. Results: The results indicate that this complexity measure can distinguish normal and epileptic EEG signals with an accuracy of more than 97% for clean EEG and more than 75% for highly noised EEG signals. Discussion and Conclusion: The complexity measure can be computed in a very fast and easy way and, unlike traditional chaotic measures, is robust with respect to noise corrupting the data. This measure is also capable of dynamical change detection in short time series data.

  18. Beamspace dual signal space projection (bDSSP): a method for selective detection of deep sources in MEG measurements

    Science.gov (United States)

    Sekihara, Kensuke; Adachi, Yoshiaki; Kubota, Hiroshi K.; Cai, Chang; Nagarajan, Srikantan S.

    2018-06-01

    Objective. Magnetoencephalography (MEG) has a well-recognized weakness at detecting deeper brain activities. This paper proposes a novel algorithm for selective detection of deep sources by suppressing interference signals from superficial sources in MEG measurements. Approach. The proposed algorithm combines the beamspace preprocessing method with the dual signal space projection (DSSP) interference suppression method. A prerequisite of the proposed algorithm is prior knowledge of the location of the deep sources. The proposed algorithm first derives the basis vectors that span a local region just covering the locations of the deep sources. It then estimates the time-domain signal subspace of the superficial sources by using the projector composed of these basis vectors. Signals from the deep sources are extracted by projecting the row space of the data matrix onto the direction orthogonal to the signal subspace of the superficial sources. Main results. Compared with the previously proposed beamspace signal space separation (SSS) method, the proposed algorithm is capable of suppressing much stronger interference from superficial sources. This capability is demonstrated in our computer simulation as well as experiments using phantom data. Significance. The proposed bDSSP algorithm can be a powerful tool in studies of physiological functions of midbrain and deep brain structures.

  19. Signal analysis for failure detection

    International Nuclear Information System (INIS)

    Parpaglione, M.C.; Perez, L.V.; Rubio, D.A.; Czibener, D.; D'Attellis, C.E.; Brudny, P.I.; Ruzzante, J.E.

    1994-01-01

    Several methods for analysis of acoustic emission signals are presented. They are mainly oriented to detection of changes in noisy signals and characterization of higher amplitude discrete pulses or bursts. The aim was to relate changes and events with failure, crack or wear in materials, being the final goal to obtain automatic means of detecting such changes and/or events. Performance evaluation was made using both simulated and laboratory test signals. The methods being presented are the following: 1. Application of the Hopfield Neural Network (NN) model for classifying faults in pipes and detecting wear of a bearing. 2. Application of the Kohonnen and Back Propagation Neural Network model for the same problem. 3. Application of Kalman filtering to determine time occurrence of bursts. 4. Application of a bank of Kalman filters (KF) for failure detection in pipes. 5. Study of amplitude distribution of signals for detecting changes in their shape. 6. Application of the entropy distance to measure differences between signals. (author). 10 refs, 11 figs

  20. EUROmediCAT signal detection

    DEFF Research Database (Denmark)

    Given, Joanne E; Loane, Maria; Luteijn, Johannes Michiel

    2016-01-01

    AIMS: To evaluate congenital anomaly (CA)-medication exposure associations produced by the new EUROmediCAT signal detection system and determine which require further investigation. METHODS: Data from 15 EUROCAT registries (1995-2011) with medication exposures at the chemical substance (5th level...

  1. A novel SNP analysis method to detect copy number alterations with an unbiased reference signal directly from tumor samples

    Directory of Open Access Journals (Sweden)

    LaFramboise William A

    2011-01-01

    Full Text Available Abstract Background Genomic instability in cancer leads to abnormal genome copy number alterations (CNA as a mechanism underlying tumorigenesis. Using microarrays and other technologies, tumor CNA are detected by comparing tumor sample CN to normal reference sample CN. While advances in microarray technology have improved detection of copy number alterations, the increase in the number of measured signals, noise from array probes, variations in signal-to-noise ratio across batches and disparity across laboratories leads to significant limitations for the accurate identification of CNA regions when comparing tumor and normal samples. Methods To address these limitations, we designed a novel "Virtual Normal" algorithm (VN, which allowed for construction of an unbiased reference signal directly from test samples within an experiment using any publicly available normal reference set as a baseline thus eliminating the need for an in-lab normal reference set. Results The algorithm was tested using an optimal, paired tumor/normal data set as well as previously uncharacterized pediatric malignant gliomas for which a normal reference set was not available. Using Affymetrix 250K Sty microarrays, we demonstrated improved signal-to-noise ratio and detected significant copy number alterations using the VN algorithm that were validated by independent PCR analysis of the target CNA regions. Conclusions We developed and validated an algorithm to provide a virtual normal reference signal directly from tumor samples and minimize noise in the derivation of the raw CN signal. The algorithm reduces the variability of assays performed across different reagent and array batches, methods of sample preservation, multiple personnel, and among different laboratories. This approach may be valuable when matched normal samples are unavailable or the paired normal specimens have been subjected to variations in methods of preservation.

  2. Classification of ECG signal with Support Vector Machine Method for Arrhythmia Detection

    Science.gov (United States)

    Turnip, Arjon; Ilham Rizqywan, M.; Kusumandari, Dwi E.; Turnip, Mardi; Sihombing, Poltak

    2018-03-01

    An electrocardiogram is a potential bioelectric record that occurs as a result of cardiac activity. QRS Detection with zero crossing calculation is one method that can precisely determine peak R of QRS wave as part of arrhythmia detection. In this paper, two experimental scheme (2 minutes duration with different activities: relaxed and, typing) were conducted. From the two experiments it were obtained: accuracy, sensitivity, and positive predictivity about 100% each for the first experiment and about 79%, 93%, 83% for the second experiment, respectively. Furthermore, the feature set of MIT-BIH arrhythmia using the support vector machine (SVM) method on the WEKA software is evaluated. By combining the available attributes on the WEKA algorithm, the result is constant since all classes of SVM goes to the normal class with average 88.49% accuracy.

  3. An estimation method for echo signal energy of pipe inner surface longitudinal crack detection by 2-D energy coefficients integration

    Energy Technology Data Exchange (ETDEWEB)

    Zhou, Shiyuan, E-mail: redaple@bit.edu.cn; Sun, Haoyu, E-mail: redaple@bit.edu.cn; Xu, Chunguang, E-mail: redaple@bit.edu.cn; Cao, Xiandong, E-mail: redaple@bit.edu.cn; Cui, Liming, E-mail: redaple@bit.edu.cn; Xiao, Dingguo, E-mail: redaple@bit.edu.cn [School of Mechanical Engineering, Beijing Institute of Technology, Beijing, China NO.5 Zhongguancun South Street, Haidian District, Beijing 100081 (China)

    2015-03-31

    The echo signal energy is directly affected by the incident sound beam eccentricity or angle for thick-walled pipes inner longitudinal cracks detection. A method for analyzing the relationship between echo signal energy between the values of incident eccentricity is brought forward, which can be used to estimate echo signal energy when testing inside wall longitudinal crack of pipe, using mode-transformed compression wave adaptation of shear wave with water-immersion method, by making a two-dimension integration of “energy coefficient” in both circumferential and axial directions. The calculation model is founded for cylinder sound beam case, in which the refraction and reflection energy coefficients of different rays in the whole sound beam are considered different. The echo signal energy is calculated for a particular cylinder sound beam testing different pipes: a beam with a diameter of 0.5 inch (12.7mm) testing a φ279.4mm pipe and a φ79.4mm one. As a comparison, both the results of two-dimension integration and one-dimension (circumferential direction) integration are listed, and only the former agrees well with experimental results. The estimation method proves to be valid and shows that the usual method of simplifying the sound beam as a single ray for estimating echo signal energy and choosing optimal incident eccentricity is not so appropriate.

  4. Detection method based on Kalman filter for high speed rail defect AE signal on wheel-rail rolling rig

    Science.gov (United States)

    Hao, Qiushi; Shen, Yi; Wang, Yan; Zhang, Xin

    2018-01-01

    Nondestructive test (NDT) of rails has been carried out intermittently in traditional approaches, which highly restricts the detection efficiency under rapid development of high speed railway nowadays. It is necessary to put forward a dynamic rail defect detection method for rail health monitoring. Acoustic emission (AE) as a practical real-time detection technology takes advantage of dynamic AE signal emitted from plastic deformation of material. Detection capacities of AE on rail defects have been verified due to its sensitivity and dynamic merits. Whereas the application under normal train service circumstance has been impeded by synchronous background noises, which are directly linked to the wheel speed. In this paper, surveys on a wheel-rail rolling rig are performed to investigate defect AE signals with varying speed. A dynamic denoising method based on Kalman filter is proposed and its detection effectiveness and flexibility are demonstrated by theory and computational results. Moreover, after comparative analysis of modelling precision at different speeds, it is predicted that the method is also applicable for high speed condition beyond experiments.

  5. Methods and systems for detecting gas flow by photoacoustic signal generation

    Science.gov (United States)

    Choudhury, Niloy; Challener, William Albert

    2018-03-06

    A method for the detection of a gas flowing from a location in a structure is described. A hollow-core optical fiber is placed in a position adjacent the structure. The fiber includes a sound-conductive cladding layer; and further includes at least one aperture extending into its cross-sectional diameter. A beam of pulsed, optical is transmitted into the fiber with a tunable laser. The optical energy is characterized by a wavelength that can be absorbed by the gas that flows into the fiber through the aperture. This causes a temperature fluctuation in the region of gas absorption, which in turn generates an acoustic wave in the absorption region. The acoustic wave travels through the cladding layer, and can be detected with a microphone, so as to provide the location of gas flow, based on the recorded position and movement of the acoustic wave. A related system is also described.

  6. On-line leak detection method for OWL-1 loop by ARX modeling using dewpoint signals

    International Nuclear Information System (INIS)

    Oguma, Ritsuo; Hayashi, Koji; Kitajima, Toshio.

    1981-01-01

    Model identification technique based on ARX (autoregressive model with exogenous variable) process was applied to dewpoint data recorded at OWL-1 (Oarai Water Loop No. 1) loop cubicle in JMTR (Japan Materials Testing Reactor) and the dynamical interrelationship between the supply and exhaust dewpoints in the ventilation system of the cubicle was empirically determined. It was shown that the information so derived on the dewpoint dynamics can assist to enhance the sensitivity of leak detection, if it was incorporated into a leak monitoring system for the OWL-1 loop. A simple digital filter incorporating the dewpoint dynamics was designed in an attempt to develop an efficient leak monitor for the OWL-1 loop. This filter was applied to the dewpoint data recordings during an abnormal leak that had occurred at the OWL-1 loop in the 43 rd cycle of JMTR operation, which demonstrated the effectiveness of the present method for leak detection at its early stage. (author)

  7. A new physics-based method for detecting weak nuclear signals via spectral decomposition

    International Nuclear Information System (INIS)

    Chan, Kung-Sik; Li, Jinzheng; Eichinger, William; Bai, Erwei

    2012-01-01

    We propose a new physics-based method to determine the presence of the spectral signature of one or more nuclides from a poorly resolved spectra with weak signatures. The method is different from traditional methods that rely primarily on peak finding algorithms. The new approach considers each of the signatures in the library to be a linear combination of subspectra. These subspectra are obtained by assuming a signature consisting of just one of the unique gamma rays emitted by the nuclei. We propose a Poisson regression model for deducing which nuclei are present in the observed spectrum. In recognition that a radiation source generally comprises few nuclear materials, the underlying Poisson model is sparse, i.e. most of the regression coefficients are zero (positive coefficients correspond to the presence of nuclear materials). We develop an iterative algorithm for a penalized likelihood estimation that prompts sparsity. We illustrate the efficacy of the proposed method by simulations using a variety of poorly resolved, low signal-to-noise ratio (SNR) situations, which show that the proposed approach enjoys excellent empirical performance even with SNR as low as to -15 db.

  8. A new method for detecting signal regions in ordered sequences of real numbers, and application to viral genomic data.

    Science.gov (United States)

    Gog, Julia R; Lever, Andrew M L; Skittrall, Jordan P

    2018-01-01

    We present a fast, robust and parsimonious approach to detecting signals in an ordered sequence of numbers. Our motivation is in seeking a suitable method to take a sequence of scores corresponding to properties of positions in virus genomes, and find outlying regions of low scores. Suitable statistical methods without using complex models or making many assumptions are surprisingly lacking. We resolve this by developing a method that detects regions of low score within sequences of real numbers. The method makes no assumptions a priori about the length of such a region; it gives the explicit location of the region and scores it statistically. It does not use detailed mechanistic models so the method is fast and will be useful in a wide range of applications. We present our approach in detail, and test it on simulated sequences. We show that it is robust to a wide range of signal morphologies, and that it is able to capture multiple signals in the same sequence. Finally we apply it to viral genomic data to identify regions of evolutionary conservation within influenza and rotavirus.

  9. A coherent method for the detection and parameter estimation of continuous gravitational wave signals using a pulsar timing array

    International Nuclear Information System (INIS)

    Wang, Yan; Mohanty, Soumya D.; Jenet, Fredrick A.

    2014-01-01

    The use of a high precision pulsar timing array is a promising approach to detecting gravitational waves in the very low frequency regime (10 –6 -10 –9 Hz) that is complementary to ground-based efforts (e.g., LIGO, Virgo) at high frequencies (∼10-10 3 Hz) and space-based ones (e.g., LISA) at low frequencies (10 –4 -10 –1 Hz). One of the target sources for pulsar timing arrays is individual supermassive black hole binaries which are expected to form in galactic mergers. In this paper, a likelihood-based method for detection and parameter estimation is presented for a monochromatic continuous gravitational wave signal emitted by such a source. The so-called pulsar terms in the signal that arise due to the breakdown of the long-wavelength approximation are explicitly taken into account in this method. In addition, the method accounts for equality and inequality constraints involved in the semi-analytical maximization of the likelihood over a subset of the parameters. The remaining parameters are maximized over numerically using Particle Swarm Optimization. Thus, the method presented here solves the monochromatic continuous wave detection and parameter estimation problem without invoking some of the approximations that have been used in earlier studies.

  10. A coherent method for the detection and parameter estimation of continuous gravitational wave signals using a pulsar timing array

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Yan; Mohanty, Soumya D.; Jenet, Fredrick A. [Department of Physics and Astronomy, University of Texas at Brownsville, 1 West University Boulevard, Brownsville, TX 78520 (United States)

    2014-11-01

    The use of a high precision pulsar timing array is a promising approach to detecting gravitational waves in the very low frequency regime (10{sup –6}-10{sup –9} Hz) that is complementary to ground-based efforts (e.g., LIGO, Virgo) at high frequencies (∼10-10{sup 3} Hz) and space-based ones (e.g., LISA) at low frequencies (10{sup –4}-10{sup –1} Hz). One of the target sources for pulsar timing arrays is individual supermassive black hole binaries which are expected to form in galactic mergers. In this paper, a likelihood-based method for detection and parameter estimation is presented for a monochromatic continuous gravitational wave signal emitted by such a source. The so-called pulsar terms in the signal that arise due to the breakdown of the long-wavelength approximation are explicitly taken into account in this method. In addition, the method accounts for equality and inequality constraints involved in the semi-analytical maximization of the likelihood over a subset of the parameters. The remaining parameters are maximized over numerically using Particle Swarm Optimization. Thus, the method presented here solves the monochromatic continuous wave detection and parameter estimation problem without invoking some of the approximations that have been used in earlier studies.

  11. Method of signal detection from silicon photomultipliers using fully differential Charge to Time Converter and fast shaper

    International Nuclear Information System (INIS)

    Baszczyk, M.; Dorosz, P.; Glab, S.; Kucewicz, W.; Mik, L.; Sapor, M.

    2016-01-01

    The paper presents an implementation of fully differential readout method for Silicon Photomultipliers (SiPM). Front-end electronics consists of a fast and slow path. The former creates the trigger signal while the latter produces a pulse of width proportional to the input charge. The fast shaper generates unipolar pulse and utilizes the pole-zero cancelation circuit. The peaking time for single photoelectron is equal to 3.6 ns and the FWHM is 3.8 ns. The pulse width of the Charge to Time Converter (QTC) depends on the number of photons entering the SiPM at the moment of measurement. The QTC response is nonlinear but it allows us to work with signals in a wide dynamic range. The proposed readout method is effective in measurements of random signals where frequent events tend to pile-up. Thermal generation and afterpulses have a strong influence on the width of pulses from QTC. The proposed method enables us to distinguish those overlapping signals and get the reliable information on the number of detected photons.

  12. Method of signal detection from silicon photomultipliers using fully differential Charge to Time Converter and fast shaper

    Energy Technology Data Exchange (ETDEWEB)

    Baszczyk, M., E-mail: baszczyk@agh.edu.pl [AGH University of Science and Technology, Department of Electronics, Krakow (Poland); Dorosz, P.; Glab, S.; Kucewicz, W. [AGH University of Science and Technology, Department of Electronics, Krakow (Poland); Mik, L. [AGH University of Science and Technology, Department of Electronics, Krakow (Poland); State Higher Vocational School, Tarnow (Poland); Sapor, M. [AGH University of Science and Technology, Department of Electronics, Krakow (Poland)

    2016-07-11

    The paper presents an implementation of fully differential readout method for Silicon Photomultipliers (SiPM). Front-end electronics consists of a fast and slow path. The former creates the trigger signal while the latter produces a pulse of width proportional to the input charge. The fast shaper generates unipolar pulse and utilizes the pole-zero cancelation circuit. The peaking time for single photoelectron is equal to 3.6 ns and the FWHM is 3.8 ns. The pulse width of the Charge to Time Converter (QTC) depends on the number of photons entering the SiPM at the moment of measurement. The QTC response is nonlinear but it allows us to work with signals in a wide dynamic range. The proposed readout method is effective in measurements of random signals where frequent events tend to pile-up. Thermal generation and afterpulses have a strong influence on the width of pulses from QTC. The proposed method enables us to distinguish those overlapping signals and get the reliable information on the number of detected photons.

  13. Detection of signals in noise

    CERN Document Server

    Whalen, Anthony D; Declaris, Nicholas

    1971-01-01

    Detection of Signals in Noise serves as an introduction to the principles and applications of the statistical theory of signal detection. The book discusses probability and random processes; narrowband signals, their complex representation, and their properties described with the aid of the Hilbert transform; and Gaussian-derived processes. The text also describes the application of hypothesis testing for the detection of signals and the fundamentals required for statistical detection of signals in noise. Problem exercises, references, and a supplementary bibliography are included after each c

  14. Method of signal analysis

    International Nuclear Information System (INIS)

    Berthomier, Charles

    1975-01-01

    A method capable of handling the amplitude and the frequency time laws of a certain kind of geophysical signals is described here. This method is based upon the analytical signal idea of Gabor and Ville, which is constructed either in the time domain by adding an imaginary part to the real signal (in-quadrature signal), or in the frequency domain by suppressing negative frequency components. The instantaneous frequency of the initial signal is then defined as the time derivative of the phase of the analytical signal, and his amplitude, or envelope, as the modulus of this complex signal. The method is applied to three types of magnetospheric signals: chorus, whistlers and pearls. The results obtained by analog and numerical calculations are compared to results obtained by classical systems using filters, i.e. based upon a different definition of the concept of frequency. The precision with which the frequency-time laws are determined leads then to the examination of the principle of the method and to a definition of instantaneous power density spectrum attached to the signal, and to the first consequences of this definition. In this way, a two-dimensional representation of the signal is introduced which is less deformed by the analysis system properties than the usual representation, and which moreover has the advantage of being obtainable practically in real time [fr

  15. Inspection method of cable-stayed bridge using magnetic flux leakage detection: principle, sensor design, and signal processing

    International Nuclear Information System (INIS)

    Xu, Fengyu; Wang, Xingsong; Wu, Hongtao

    2012-01-01

    A nondestructive testing technique based on magnetic flux leakage is presented to inspect automatically the stay cables with large diameters of a cable-stayed bridge. Using the proposed inspection method, an online nondestructive testing (NDT) modular sensor is developed. The wreath-like sensor is composed of several sensor units that embrace the cable at equal angles. Each sensor unit consists of two permanent magnets and a hall sensor to detect the magnetic flux density. The modular sensor can be installed conveniently on cables with various diameters by increasing the number of sensor units and adjusting the relative distances between adjacent sensor units. Results of the experiments performed on a man-made cable with faults prove that the proposed sensor can inspect the status signals of the inner wires of the cables. To filter the interfering signals, three processing algorithms are discussed, including the moving average method, improved detrending algorithm, and signal processing based on a digital filter. Results show that the developed NDT sensor carried by a cable inspection robot can move along the cable and monitor the state of the stay cables

  16. Statistical theory of signal detection

    CERN Document Server

    Helstrom, Carl Wilhelm; Costrell, L; Kandiah, K

    1968-01-01

    Statistical Theory of Signal Detection, Second Edition provides an elementary introduction to the theory of statistical testing of hypotheses that is related to the detection of signals in radar and communications technology. This book presents a comprehensive survey of digital communication systems. Organized into 11 chapters, this edition begins with an overview of the theory of signal detection and the typical detection problem. This text then examines the goals of the detection system, which are defined through an analogy with the testing of statistical hypotheses. Other chapters consider

  17. EUROmediCAT signal detection

    DEFF Research Database (Denmark)

    Luteijn, Johannes Michiel; Morris, Joan K; Garne, Ester

    2016-01-01

    AIMS: Information about medication safety in pregnancy is inadequate. We aimed to develop a signal detection methodology to routinely identify unusual associations between medications and congenital anomalies using data collected by 15 European congenital anomaly registries. METHODS: EUROmedi...... for 40 385 medication anomaly combinations in the data. Simes multiple testing procedure with a 50% false discovery rate (FDR) identified associations least likely to be due to chance and those associations with more than two cases with the exposure and the anomaly were selected for further investigation...

  18. Modeling binaural signal detection

    NARCIS (Netherlands)

    Breebaart, D.J.

    2001-01-01

    With the advent of multimedia technology and powerful signal processing systems, audio processing and reproduction has gained renewed interest. Examples of products that have been developed are audio coding algorithms to efficiently store and transmit music and speech, or audio reproduction systems

  19. Comparison of the analog and digital pulse-shaping methods in signal processing in nuclear detections

    International Nuclear Information System (INIS)

    Golnabi, H.

    2002-01-01

    The goal of this article is to describe the potential applications of the new improved digital techniques and provide a meaningful figure of merit for the comparison of the analog and digital methods. The experimental operation of a typical digital pulse shaper used in a spectrometer with the 23 Na source and a Ge y-ray detector is discussed. The effect of different imposed dead time on the counted pulses is investigated. It is noticed that nuclear events distribution in all ranges of dead time does not obey Poisson's law and deviation from this distribution depends on the counting rate. For a given dead time, deviation from this distribution increases linearly by increasing imposed dead time. For a fixed dead time, when counting rate increases deviation from Poisson's distribution law increases accordingly, and vice versa. (Author)

  20. method for ranging and noise reduction of low coherence interferometry LCI and optical coherence tomography OCT signals by parallel detection of spectral bands

    NARCIS (Netherlands)

    Boer, JF De; Tearney, G. J.; Bouma, BE

    2008-01-01

    Apparatus and method for increasing the sensitivity in the detection of optical coherence tomography and loW coher ence interferometry (“LCI”) signals by detecting a parallel set of spectral bands, each band being a unique combination of optical frequencies. The LCI broad bandwidth source is split

  1. Signal anomaly detection and characterization

    International Nuclear Information System (INIS)

    Morgenstern, V.M.; Upadhyaya, B.R.; Gloeckler, O.

    1988-08-01

    As part of a comprehensive signal validation system, we have developed a signal anomaly detector, without specifically establishing the cause of the anomaly. A signal recorded from process instrumentation is said to have an anomaly, if during steady-state operation, the deviation in the level of the signal, its root-mean-square (RMS) value, or its statistical distribution changes by a preset value. This deviation could be an unacceptable increase or a decrease in the quantity being monitored. An anomaly in a signal may be characterized by wideband or single-frequency noise, bias error, pulse-type error, nonsymmetric behavior, or a change in the signal bandwidth. Various signatures can be easily computed from data samples and compared against specified threshold values. We want to point out that in real processes, pulses can appear with different time widths, and at different rates of change of the signal. Thus, in characterizing an anomaly as a pulse-type, the fastest pulse width is constrained by the signal sampling interval. For example, if a signal is sampled at 100 Hz, we will not be able to detect pulses occurring at kHz rates. Discussion with utility and Combustion Engineering personnel indicated that it is not practical to detect pulses having a narrow time width. 9 refs., 11 figs., 8 tabs

  2. An intuitive method to automatically detect the common and not common frequencies for two or more time-varying signals

    International Nuclear Information System (INIS)

    Doca, C.; Paunoiu, C.; Doca, L.

    2013-01-01

    Sampling a time-varying signal and his spectral analysis are, both, subjected to theoretically compelling, such as Shannon's theorem and the objectively limiting of the frequencys resolution. After obtaining the signals (Fourier) spectrum, this is processed and interpreted usually by a scientist who, presumably, has sufficient prior information about the monitored signal to conclude, for example, on the significant frequencies. Obviously, processing and interpretation of individual spectra are routine tasks that can be automated by suitable software (PC application). The problems complicate if we need to compare two or more spectra corresponding to different signals and/or phenomena. In the above context, this paper presents an intuitive method for automatic identification of the common and not common frequencies for two or more congruent spectra. The method is illustrated by numerical simulations, and by the results obtained in the analysis of the noise from some experimental measured signals. (authors)

  3. Detection of signals in noise

    CERN Document Server

    McDonough, Robert N

    1995-01-01

    The Second Edition is an updated revision to the authors highly successful and widely used introduction to the principles and application of the statistical theory of signal detection. This book emphasizes those theories that have been found to be particularly useful in practice including principles applied to detection problems encountered in digital communications, radar, and sonar.Detection processing based upon the fast Fourier transform

  4. Seizure detection algorithms based on EMG signals

    DEFF Research Database (Denmark)

    Conradsen, Isa

    Background: the currently used non-invasive seizure detection methods are not reliable. Muscle fibers are directly connected to the nerves, whereby electric signals are generated during activity. Therefore, an alarm system on electromyography (EMG) signals is a theoretical possibility. Objective...... on the amplitude of the signal. The other algorithm was based on information of the signal in the frequency domain, and it focused on synchronisation of the electrical activity in a single muscle during the seizure. Results: The amplitude-based algorithm reliably detected seizures in 2 of the patients, while...... the frequency-based algorithm was efficient for detecting the seizures in the third patient. Conclusion: Our results suggest that EMG signals could be used to develop an automatic seizuredetection system. However, different patients might require different types of algorithms /approaches....

  5. Subgraph detection using graph signals

    KAUST Repository

    Chepuri, Sundeep Prabhakar

    2017-03-06

    In this paper we develop statistical detection theory for graph signals. In particular, given two graphs, namely, a background graph that represents an usual activity and an alternative graph that represents some unusual activity, we are interested in answering the following question: To which of the two graphs does the observed graph signal fit the best? To begin with, we assume both the graphs are known, and derive an optimal Neyman-Pearson detector. Next, we derive a suboptimal detector for the case when the alternative graph is not known. The developed theory is illustrated with numerical experiments.

  6. Subgraph detection using graph signals

    KAUST Repository

    Chepuri, Sundeep Prabhakar; Leus, Geert

    2017-01-01

    In this paper we develop statistical detection theory for graph signals. In particular, given two graphs, namely, a background graph that represents an usual activity and an alternative graph that represents some unusual activity, we are interested in answering the following question: To which of the two graphs does the observed graph signal fit the best? To begin with, we assume both the graphs are known, and derive an optimal Neyman-Pearson detector. Next, we derive a suboptimal detector for the case when the alternative graph is not known. The developed theory is illustrated with numerical experiments.

  7. Automatic Smoker Detection from Telephone Speech Signals

    DEFF Research Database (Denmark)

    Poorjam, Amir Hossein; Hesaraki, Soheila; Safavi, Saeid

    2017-01-01

    This paper proposes an automatic smoking habit detection from spontaneous telephone speech signals. In this method, each utterance is modeled using i-vector and non-negative factor analysis (NFA) frameworks, which yield low-dimensional representation of utterances by applying factor analysis...... method is evaluated on telephone speech signals of speakers whose smoking habits are known drawn from the National Institute of Standards and Technology (NIST) 2008 and 2010 Speaker Recognition Evaluation databases. Experimental results over 1194 utterances show the effectiveness of the proposed approach...... for the automatic smoking habit detection task....

  8. [Detection of quadratic phase coupling between EEG signal components by nonparamatric and parametric methods of bispectral analysis].

    Science.gov (United States)

    Schmidt, K; Witte, H

    1999-11-01

    Recently the assumption of the independence of individual frequency components in a signal has been rejected, for example, for the EEG during defined physiological states such as sleep or sedation [9, 10]. Thus, the use of higher-order spectral analysis capable of detecting interrelations between individual signal components has proved useful. The aim of the present study was to investigate the quality of various non-parametric and parametric estimation algorithms using simulated as well as true physiological data. We employed standard algorithms available for the MATLAB. The results clearly show that parametric bispectral estimation is superior to non-parametric estimation in terms of the quality of peak localisation and the discrimination from other peaks.

  9. Epileptic Seizure Detection based on Wavelet Transform Statistics Map and EMD Method for Hilbert-Huang Spectral Analyzing in Gamma Frequency Band of EEG Signals

    Directory of Open Access Journals (Sweden)

    Morteza Behnam

    2015-08-01

    Full Text Available Seizure detection using brain signal (EEG analysis is the important clinical methods in drug therapy and the decisions before brain surgery. In this paper, after signal conditioning using suitable filtering, the Gamma frequency band has been extracted and the other brain rhythms, ambient noises and the other bio-signal are canceled. Then, the wavelet transform of brain signal and the map of wavelet transform in multi levels are computed. By dividing the color map to different epochs, the histogram of each sub-image is obtained and the statistics of it based on statistical momentums and Negentropy values are calculated. Statistical feature vector using Principle Component Analysis (PCA is reduced to one dimension. By EMD algorithm and sifting procedure for analyzing the data by Intrinsic Mode Function (IMF and computing the residues of brain signal using spectrum of Hilbert transform and Hilbert – Huang spectrum forming, one spatial feature based on the Euclidian distance for signal classification is obtained. By K-Nearest Neighbor (KNN classifier and by considering the optimal neighbor parameter, EEG signals are classified in two classes, seizure and non-seizure signal, with the rate of accuracy 76.54% and with variance of error 0.3685 in the different tests.

  10. Expert AE signal arrival detection

    Czech Academy of Sciences Publication Activity Database

    Chlada, Milan; Převorovský, Zdeněk

    2011-01-01

    Roč. 6, 3/4 (2011), s. 191-205 ISSN 1741-8410. [NDT in PROGRESS /4./. Praha, 05.11.2007-07.11.2007] R&D Projects: GA MPO(CZ) FR-TI1/274; GA ČR GA101/07/1518 Institutional research plan: CEZ:AV0Z20760514 Keywords : acoustic emission * signal arrival detection Subject RIV: BI - Acoustics http://www.inderscience.com/search/index.php?mainAction=search& action =record&rec_id=43215&prevQuery=&ps=10&m=or

  11. Optics based signal processing methods for intraoperative blood vessel detection and quantification in real time (Conference Presentation)

    Science.gov (United States)

    Chaturvedi, Amal; Shukair, Shetha A.; Le Rolland, Paul; Vijayvergia, Mayank; Subramanian, Hariharan; Gunn, Jonathan W.

    2016-03-01

    Minimally invasive operations require surgeons to make difficult cuts to blood vessels and other tissues with impaired tactile and visual feedback. This leads to inadvertent cuts to blood vessels hidden beneath tissue, causing serious health risks to patients and a non-reimbursable financial burden to hospitals. Intraoperative imaging technologies have been developed, but these expensive systems can be cumbersome and provide only a high-level view of blood vessel networks. In this research, we propose a lean reflectance-based system, comprised of a dual wavelength LED, photodiode, and novel signal processing algorithms for rapid vessel characterization. Since this system takes advantage of the inherent pulsatile light absorption characteristics of blood vessels, no contrast agent is required for its ability to detect the presence of a blood vessel buried deep inside any tissue type (up to a cm) in real time. Once a vessel is detected, the system is able to estimate the distance of the vessel from the probe and the diameter size of the vessel (with a resolution of ~2mm), as well as delineate the type of tissue surrounding the vessel. The system is low-cost, functions in real-time, and could be mounted on already existing surgical tools, such as Kittner dissectors or laparoscopic suction irrigation cannulae. Having been successfully validated ex vivo, this technology will next be tested in a live porcine study and eventually in clinical trials.

  12. “UTILIZING” SIGNAL DETECTION THEORY

    Science.gov (United States)

    Lynn, Spencer K.; Barrett, Lisa Feldman

    2014-01-01

    What do inferring what a person is thinking or feeling, deciding to report a symptom to your doctor, judging a defendant’s guilt, and navigating a dimly lit room have in common? They involve perceptual uncertainty (e.g., a scowling face might indicate anger or concentration, which engender different appropriate responses), and behavioral risk (e.g., a cost to making the wrong response). Signal detection theory describes these types of decisions. In this tutorial we show how, by incorporating the economic concept of utility, signal detection theory serves as a model of optimal decision making, beyond its common use as an analytic method. This utility approach to signal detection theory highlights potentially enigmatic influences of perceptual uncertainty on measures of decision-making performance (accuracy and optimality) and on behavior (a functional relationship between bias and sensitivity). A “utilized” signal detection theory offers the possibility of expanding the phenomena that can be understood within a decision-making framework. PMID:25097061

  13. Algebraic Methods to Design Signals

    Science.gov (United States)

    2015-08-27

    to date on designing signals using algebraic and combinatorial methods. Mathematical tools from algebraic number theory, representation theory and... combinatorial objects in designing signals for communication purposes. Sequences and arrays with desirable autocorrelation properties have many...multiple access methods in mobile radio communication systems. We continue our mathematical framework based on group algebras, character theory

  14. Detecting double compression of audio signal

    Science.gov (United States)

    Yang, Rui; Shi, Yun Q.; Huang, Jiwu

    2010-01-01

    MP3 is the most popular audio format nowadays in our daily life, for example music downloaded from the Internet and file saved in the digital recorder are often in MP3 format. However, low bitrate MP3s are often transcoded to high bitrate since high bitrate ones are of high commercial value. Also audio recording in digital recorder can be doctored easily by pervasive audio editing software. This paper presents two methods for the detection of double MP3 compression. The methods are essential for finding out fake-quality MP3 and audio forensics. The proposed methods use support vector machine classifiers with feature vectors formed by the distributions of the first digits of the quantized MDCT (modified discrete cosine transform) coefficients. Extensive experiments demonstrate the effectiveness of the proposed methods. To the best of our knowledge, this piece of work is the first one to detect double compression of audio signal.

  15. Detection of Transient Signals in Doppler Spectra

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Signal processing is used to detect transient signals in the presence of noise. Two embodiments are disclosed. In both embodiments, the time series from a remote...

  16. Detection of uranium with a wireless sensing method by using salophen as receptor and magnetic nanoparticles as signal-amplifying tags

    International Nuclear Information System (INIS)

    Miao Yang; Lifu Liao; Guangliang Zhang; Bo He; Xilin Xiao; Yingwu Lin; Changming Nie

    2013-01-01

    A new wireless sensing method for the detection of uranium in water samples has been reported in this paper. The method is based on a sandwich-type detection strategy. Salophen, a tetradentate ligand of uranyl ion, was immobilized on the surface of the polyurethane-protected magnetoelastic sensor as receptor for the capture of uranyl ion. The phosphorylated polyvinyl alcohol coated magnetic Fe 3 O 4 nanoparticles were used as signal-amplifying tags of uranyl ion. In a procedure of determining uranium, firstly uranyl ion in sample solution was captured on the sensor surface. Then the captured uranyl bound the nanoparticle through its coordination with the phosphate group. The amount of uranium was detected through the measure of the resonance frequency shift caused by the enhanced mass loading on the sensor surface. A linear range was found to be 0.2-20.0 μg/L under optimal conditions with a detection limit of 0.11 μg/L. The method has been applied to determine uranium in environmental water samples with the relative standard deviations of 2.1-3.6 % and the recoveries of 98.0-101.5 %. The present technique is one of the most suitable techniques for assay of uranium at trace level in environmental water samples collected from different sources. (author)

  17. Comparison of Methods for Oscillation Detection

    DEFF Research Database (Denmark)

    Odgaard, Peter Fogh; Trangbæk, Klaus

    2006-01-01

    This paper compares a selection of methods for detecting oscillations in control loops. The methods are tested on measurement data from a coal-fired power plant, where some oscillations are occurring. Emphasis is put on being able to detect oscillations without having a system model and without...... using process knowledge. The tested methods show potential for detecting the oscillations, however, transient components in the signals cause false detections as well, motivating usage of models in order to remove the expected signals behavior....

  18. Signal processing for boiling noise detection

    International Nuclear Information System (INIS)

    Ledwidge, T.J.; Black, J.L.

    1989-01-01

    The present paper deals with investigations of acoustic signals from a boiling experiment performed on the KNS I loop at KfK Karlsruhe. Signals have been analysed in frequency as well as in time domain. Signal characteristics successfully used to detect the boiling process have been found in time domain. (author). 6 refs, figs

  19. Process Dissociation and Mixture Signal Detection Theory

    Science.gov (United States)

    DeCarlo, Lawrence T.

    2008-01-01

    The process dissociation procedure was developed in an attempt to separate different processes involved in memory tasks. The procedure naturally lends itself to a formulation within a class of mixture signal detection models. The dual process model is shown to be a special case. The mixture signal detection model is applied to data from a widely…

  20. Spectral integration in binaural signal detection

    NARCIS (Netherlands)

    Breebaart, D.J.; Par, van de S.L.J.D.E.; Kohlrausch, A.G.

    1997-01-01

    For both monaural and binaural masking, the spectral content of the masker and of the signal to be detected are important stimulus properties influencing the detection process. It is generally accepted that the auditory system separates the incoming signals in several frequency bands. It is not

  1. BURAR: Detection and signal processing capabilities

    International Nuclear Information System (INIS)

    Ghica, Daniela; Radulian, Mircea; Popa, Mihaela

    2004-01-01

    Since July 2002, a new seismic monitoring station, the Bucovina Seismic Array (BURAR), has been installed in the northern part of Romania, in a joint effort of the Air Force Technical Applications Center, USA, and the National Institute for Earth Physics (NIEP), Romania. The array consists of 10 seismic sensors (9 short-period and one broad band) located in boreholes and distributed in a 5 x 5 km area. At present, the seismic data are continuously recorded by BURAR and transmitted in real-time to the Romanian National Data Centre (ROM N DC), at Bucharest and to the National Data Center of USA, in Florida. The statistical analysis for the seismic information gathered at ROM N DC by the BURAR in the August 2002 - December 2003 time interval points out a much better efficiency of the BURAR system in detecting teleseismic events and local events occurred in the N-NE part of Romanian territory, in comparison with the actual Romanian Telemetered Network. Furthermore, the BURAR monitoring system has proven to be an important source of reliable data for NIEP efforts in elaborating of the seismic bulletins. Signal processing capability of the system provides useful information in order to improve the location of the local seismic events, using the array beamforming facility. This method increases significantly the signal-to-noise ratio of the seismic signal by summing up the coherent signals from the array components. In this way, eventual source nucleation phases can be detected. At the same time, using the slowness and backazimuth estimations by f-k analysis, locations for the seismic events can be performed based only on the information recorded by the BURAR array, acting like a single seismic station recording system. Additionally, f-k analysis techniques are useful in the local site effects estimation and interpretation of the local geological structure. (authors)

  2. Sensitive detection of nanomechanical motion using piezoresistive signal downmixing

    International Nuclear Information System (INIS)

    Bargatin, I.; Myers, E.B.; Arlett, J.; Gudlewski, B.; Roukes, M.L.

    2005-01-01

    We have developed a method of measuring rf-range resonance properties of nanoelectromechanical systems (NEMS) with integrated piezoresistive strain detectors serving as signal downmixers. The technique takes advantage of the high strain sensitivity of semiconductor-based piezoresistors, while overcoming the problem of rf signal attenuation due to a high source impedance. Our technique also greatly reduces the effect of the cross-talk between the detector and actuator circuits. We achieve thermomechanical noise detection of cantilever resonance modes up to 71 MHz at room temperature, demonstrating that downmixed piezoresistive signal detection is a viable high-sensitivity method of displacement detection in high-frequency NEMS

  3. Weak signal detection: A discrete window of opportunity for ...

    African Journals Online (AJOL)

    weak signal detection' as a potential opportunity to fill this void. Method: Combining futures and complexity theory, we reflect on two pilot case studies that involved the Archetype Extraction technique and the SenseMakerw CollectorTM tool.

  4. An automatic method for detection and classification of Ionospheric Alfvén Resonances using signal and image processing techniques

    Science.gov (United States)

    Beggan, Ciaran

    2014-05-01

    Induction coils permit us to measure the very rapid changes of the magnetic field. In June 2012, the British Geological Survey Geomagnetism team installed two high frequency (100 Hz) induction coil magnetometers at the Eskdalemuir Observatory (55.3° N, 3.2° W, L~3), in the Scottish Borders of the United Kingdom. The Eskdalemuir Observatory is one of the longest running geophysical sites in the UK (beginning operation in 1908) and is located in a rural valley with a quiet magnetic environment. The coils record magnetic field changes over an effective frequency range of about 0.1-40Hz, and encompass phenomena such as the Schumann resonances, magnetospheric pulsations and Ionospheric Alfvén Resonances (IAR). In this study we focus on the IAR, which are related to the vibration of magnetic field lines passing through the ionosphere, believed to be mainly excited by lower atmospheric electrical discharges. The IAR typically manifest as a series of spectral resonances structures (SRS) within the 1-6Hz frequency range, usually appearing a fine bands or fringes in spectrogram plots. The SRS tend to occur daily between 18.00-06.00UT at the Eskdalemuir site, disappearing during the daylight hours. They usually start as a single low frequency before bifurcating into 5-10 separate fringes, increasing in frequency until around midnight. The fringes also widen in frequency before fading around 06.00UT. Occasionally, the fringes decrease in frequency slightly around 03.00UT before fading. In order to quantify the daily, seasonal and annual changes of the SRS, we developed a new method to identify the fringes and to quantify their occurrence in frequency (f) and the change in frequency (Δf). The method uses short time-series of 100 seconds to produce an FFT spectral plot from which the non-stationary peaks are identified using the residuals from a best-fit six order spline. This is repeated for an entire day of data. The peaks from each time-slice are placed into a matrix

  5. Detection of myasthenia gravis using electrooculography signals.

    Science.gov (United States)

    Liang, T; Boulos, M I; Murray, B J; Krishnan, S; Katzberg, H; Umapathy, K

    2016-08-01

    Myasthenia gravis (MG) is an autoimmune neuromuscular disorder resulting from skeletal muscle weakness and fatigue. An early common symptom is fatigable weakness of the extrinsic ocular muscles; if symptoms remain confined to the ocular muscles after a few years, this is classified as ocular myasthenia gravis (OMG). Diagnosis of MG when there are mild, isolated ocular symptoms can be difficult, and currently available diagnostic techniques are insensitive, non-specific or technically cumbersome. In addition, there are no accurate biomarkers to follow severity of ocular dysfunction in MG over time. Single-fiber electromyography (SFEMG) and repetitive nerve stimulation (RNS) offers a way of detecting and measuring ocular muscle dysfunction in MG, however, challenges of these methods include a poor signal to noise ratio in quantifying eye muscle weakness especially in mild cases. This paper presents one of the attempts to use the electric potentials from the eyes or electrooculography (EOG) signals but obtained from three different forms of sleep testing to differentiate MG patients from age- and gender-matched controls. We analyzed 8 MG patients and 8 control patients and demonstrated a difference in the average eye movements detected between the groups. A classification accuracy as high as 68.8% was achieved using a linear discriminant analysis based classifier.

  6. BURAR: Detection and signal processing capabilities

    International Nuclear Information System (INIS)

    Ghica, Daniela; Radulian, Mircea; Popa, Mihaela

    2004-01-01

    Since July 2002, a new seismic monitoring station, the Bucovina Seismic Array (BURAR), has been installed in the northern part of Romania, in a joint effort of the Air Force Technical Applications Center, USA, and the National Institute for Earth Physics (NIEP), Romania. The array consists of 10 seismic sensors (9 short-period and one broad band) located in boreholes and distributed in a 5 x 5 km 2 area. At present, the seismic data are continuously recorded by BURAR and transmitted in real-time to the Romanian National Data Centre (ROM N DC), in Bucharest and to the National Data Center of USA, in Florida. The statistical analysis for the seismic information gathered at ROM N DC by the BURAR in the August 2002 - December 2003 time interval points out a much better efficiency of the BURAR system in detecting teleseismic events and local events occurred in the N-NE part of Romanian territory, in comparison with the actual Romanian Telemetered Network. Furthermore, the BURAR monitoring system has proven to be an important source of reliable data for NIEP efforts in issuing the seismic bulletins. Signal processing capability of the system provides useful information in order to improve the location of the local seismic events, using the array beamforming procedure. This method increases significantly the signal-to-noise ratio by summing up the coherent signals from the array components. In this way, possible source nucleation phases can be detected. At the same time, using the slowness and back azimuth estimations by f-k analysis, locations for the seismic events can be established based only on the information recorded by the BURAR array, acting like a single seismic station recording system. (authors)

  7. Nonlinear Multiantenna Detection Methods

    Directory of Open Access Journals (Sweden)

    Chen Sheng

    2004-01-01

    Full Text Available A nonlinear detection technique designed for multiple-antenna assisted receivers employed in space-division multiple-access systems is investigated. We derive the optimal solution of the nonlinear spatial-processing assisted receiver for binary phase shift keying signalling, which we refer to as the Bayesian detector. It is shown that this optimal Bayesian receiver significantly outperforms the standard linear beamforming assisted receiver in terms of a reduced bit error rate, at the expense of an increased complexity, while the achievable system capacity is substantially enhanced with the advent of employing nonlinear detection. Specifically, when the spatial separation expressed in terms of the angle of arrival between the desired and interfering signals is below a certain threshold, a linear beamformer would fail to separate them, while a nonlinear detection assisted receiver is still capable of performing adequately. The adaptive implementation of the optimal Bayesian detector can be realized using a radial basis function network. Two techniques are presented for constructing block-data-based adaptive nonlinear multiple-antenna assisted receivers. One of them is based on the relevance vector machine invoked for classification, while the other on the orthogonal forward selection procedure combined with the Fisher ratio class-separability measure. A recursive sample-by-sample adaptation procedure is also proposed for training nonlinear detectors based on an amalgam of enhanced -means clustering techniques and the recursive least squares algorithm.

  8. Signal existence verification (SEV) for GPS low received power signal detection using the time-frequency approach.

    Science.gov (United States)

    Jan, Shau-Shiun; Sun, Chih-Cheng

    2010-01-01

    The detection of low received power of global positioning system (GPS) signals in the signal acquisition process is an important issue for GPS applications. Improving the miss-detection problem of low received power signal is crucial, especially for urban or indoor environments. This paper proposes a signal existence verification (SEV) process to detect and subsequently verify low received power GPS signals. The SEV process is based on the time-frequency representation of GPS signal, and it can capture the characteristic of GPS signal in the time-frequency plane to enhance the GPS signal acquisition performance. Several simulations and experiments are conducted to show the effectiveness of the proposed method for low received power signal detection. The contribution of this work is that the SEV process is an additional scheme to assist the GPS signal acquisition process in low received power signal detection, without changing the original signal acquisition or tracking algorithms.

  9. Assessment of Quadrivalent Human Papillomavirus Vaccine Safety Using the Self-Controlled Tree-Temporal Scan Statistic Signal-Detection Method in the Sentinel System.

    Science.gov (United States)

    Yih, W Katherine; Maro, Judith C; Nguyen, Michael; Baker, Meghan A; Balsbaugh, Carolyn; Cole, David V; Dashevsky, Inna; Mba-Jonas, Adamma; Kulldorff, Martin

    2018-06-01

    The self-controlled tree-temporal scan statistic-a new signal-detection method-can evaluate whether any of a wide variety of health outcomes are temporally associated with receipt of a specific vaccine, while adjusting for multiple testing. Neither health outcomes nor postvaccination potential periods of increased risk need be prespecified. Using US medical claims data in the Food and Drug Administration's Sentinel system, we employed the method to evaluate adverse events occurring after receipt of quadrivalent human papillomavirus vaccine (4vHPV). Incident outcomes recorded in emergency department or inpatient settings within 56 days after first doses of 4vHPV received by 9- through 26.9-year-olds in 2006-2014 were identified using International Classification of Diseases, Ninth Revision, diagnosis codes and analyzed by pairing the new method with a standard hierarchical classification of diagnoses. On scanning diagnoses of 1.9 million 4vHPV recipients, 2 statistically significant categories of adverse events were found: cellulitis on days 2-3 after vaccination and "other complications of surgical and medical procedures" on days 1-3 after vaccination. Cellulitis is a known adverse event. Clinically informed investigation of electronic claims records of the patients with "other complications" did not suggest any previously unknown vaccine safety problem. Considering that thousands of potential short-term adverse events and hundreds of potential risk intervals were evaluated, these findings add significantly to the growing safety record of 4vHPV.

  10. Toward multimodal signal detection of adverse drug reactions.

    Science.gov (United States)

    Harpaz, Rave; DuMouchel, William; Schuemie, Martijn; Bodenreider, Olivier; Friedman, Carol; Horvitz, Eric; Ripple, Anna; Sorbello, Alfred; White, Ryen W; Winnenburg, Rainer; Shah, Nigam H

    2017-12-01

    Improving mechanisms to detect adverse drug reactions (ADRs) is key to strengthening post-marketing drug safety surveillance. Signal detection is presently unimodal, relying on a single information source. Multimodal signal detection is based on jointly analyzing multiple information sources. Building on, and expanding the work done in prior studies, the aim of the article is to further research on multimodal signal detection, explore its potential benefits, and propose methods for its construction and evaluation. Four data sources are investigated; FDA's adverse event reporting system, insurance claims, the MEDLINE citation database, and the logs of major Web search engines. Published methods are used to generate and combine signals from each data source. Two distinct reference benchmarks corresponding to well-established and recently labeled ADRs respectively are used to evaluate the performance of multimodal signal detection in terms of area under the ROC curve (AUC) and lead-time-to-detection, with the latter relative to labeling revision dates. Limited to our reference benchmarks, multimodal signal detection provides AUC improvements ranging from 0.04 to 0.09 based on a widely used evaluation benchmark, and a comparative added lead-time of 7-22 months relative to labeling revision dates from a time-indexed benchmark. The results support the notion that utilizing and jointly analyzing multiple data sources may lead to improved signal detection. Given certain data and benchmark limitations, the early stage of development, and the complexity of ADRs, it is currently not possible to make definitive statements about the ultimate utility of the concept. Continued development of multimodal signal detection requires a deeper understanding the data sources used, additional benchmarks, and further research on methods to generate and synthesize signals. Copyright © 2017 Elsevier Inc. All rights reserved.

  11. Signal classification for acoustic neutrino detection

    International Nuclear Information System (INIS)

    Neff, M.; Anton, G.; Enzenhöfer, A.; Graf, K.; Hößl, J.; Katz, U.; Lahmann, R.; Richardt, C.

    2012-01-01

    This article focuses on signal classification for deep-sea acoustic neutrino detection. In the deep sea, the background of transient signals is very diverse. Approaches like matched filtering are not sufficient to distinguish between neutrino-like signals and other transient signals with similar signature, which are forming the acoustic background for neutrino detection in the deep-sea environment. A classification system based on machine learning algorithms is analysed with the goal to find a robust and effective way to perform this task. For a well-trained model, a testing error on the level of 1% is achieved for strong classifiers like Random Forest and Boosting Trees using the extracted features of the signal as input and utilising dense clusters of sensors instead of single sensors.

  12. Detection Of Cracks In Composite Materials Using Hybrid Non-Destructive Testing Method Based On Vibro-Thermography And Time-Frequency Analysis Of Ultrasonic Excitation Signal

    Directory of Open Access Journals (Sweden)

    Prokopowicz Wojciech

    2015-09-01

    Full Text Available The theme of the publication is to determine the possibility of diagnosing damage in composite materials using vibrio-thermography and frequency analysis and time-frequency of excitation signal. In order to verify the proposed method experiments were performed on a sample of the composite made in the technology of pressing prepregs. Analysis of the recorded signals and the thermograms were performed in MatLab environment. Hybrid non-destructive testing method based on thermogram and appropriate signal processing algorithm clearly showed damage in the sample composite material.

  13. Leak detection method

    International Nuclear Information System (INIS)

    1978-01-01

    This invention provides a method for removing nuclear fuel elements from a fabrication building while at the same time testing the fuel elements for leaks without releasing contaminants from the fabrication building or from the fuel elements. The vacuum source used, leak detecting mechanism and fuel element fabrication building are specified to withstand environmental hazards. (UK)

  14. Echo detected EPR as a tool for detecting radiation-induced defect signals in pottery

    International Nuclear Information System (INIS)

    Zoleo, Alfonso; Bortolussi, Claudia; Brustolon, Marina

    2011-01-01

    Archaeological fragments of pottery have been investigated by using CW-EPR and Echo Detected EPR (EDEPR). EDEPR allows to remove the CW-EPR dominant Fe(III) background spectrum, hiding much weaker signals potentially useful for dating purpose. EDEPR spectra attributed to a methyl radical and to feldspar defects have been recorded at room and low temperature for an Iron Age cooking ware (700 B.C.). A study on the dependence of EDEPR intensity over absorbed dose on a series of γ-irradiated brick samples (estimated age of 562 ± 140 B.C.) has confirmed the potential efficacy of the proposed method for spotting defect signals out of the strong iron background. - Highlights: → Fe(III) CW-EPR signals cover CW-EPR-detectable defects in ceramics. → Echo detected EPR gets rid of Fe(III) signals, disclosing defect signals. → Echo detected EPR detects defect signals even at relatively low doses.

  15. Microphone detected ionacoustic signal from metals

    International Nuclear Information System (INIS)

    Dioszeghy, T.; Szoekefalvi-Nagy, Z.; Biro, T.

    1986-12-01

    An experimental system for studying the radiation-induced acoustic signal generated by a modulated 2 MeV He + ion beam in metals is described. For detection, a closed cell on the rear side of the copper or aluminium sample, a half-inch condenser microphone, and a lock-in amplifier were employed. The signal was found to be proportional to beam current and particle energy, and inversely proportional to cell length. A decrease of the signal magnitude and an increase of the phase delay with increasing modulation frequency and sample thickness were also observed. (author)

  16. Signal processing techniques for sodium boiling noise detection

    International Nuclear Information System (INIS)

    1989-05-01

    At the Specialists' Meeting on Sodium Boiling Detection organized by the International Working Group on Fast Reactors (IWGFR) of the International Atomic Energy Agency at Chester in the United Kingdom in 1981 various methods of detecting sodium boiling were reported. But, it was not possible to make a comparative assessment of these methods because the signal condition in each experiment was different from others. That is why participants of this meeting recommended that a benchmark test should be carried out in order to evaluate and compare signal processing methods for boiling detection. Organization of the Co-ordinated Research Programme (CRP) on signal processing techniques for sodium boiling noise detection was also recommended at the 16th meeting of the IWGFR. The CRP on Signal Processing Techniques for Sodium Boiling Noise Detection was set up in 1984. Eight laboratories from six countries have agreed to participate in this CRP. The overall objective of the programme was the development of reliable on-line signal processing techniques which could be used for the detection of sodium boiling in an LMFBR core. During the first stage of the programme a number of existing processing techniques used by different countries have been compared and evaluated. In the course of further work, an algorithm for implementation of this sodium boiling detection system in the nuclear reactor will be developed. It was also considered that the acoustic signal processing techniques developed for boiling detection could well make a useful contribution to other acoustic applications in the reactor. This publication consists of two parts. Part I is the final report of the co-ordinated research programme on signal processing techniques for sodium boiling noise detection. Part II contains two introductory papers and 20 papers presented at four research co-ordination meetings since 1985. A separate abstract was prepared for each of these 22 papers. Refs, figs and tabs

  17. Working Group 3: Greenhouse signal detection

    International Nuclear Information System (INIS)

    Barnett, T.; Ellsaesser, H.; Groisman, P.Ya.; Grotch, S.; Jenkins, G.; Karoly, D.; Riches, M.; Santer, B.; Schoenwiese, C.; Vinnikov, K.; Zwiers, F.

    1990-01-01

    Quantitative efforts to detect the greenhouse-gas signal (GHG) in nature are in their infancy. The reasons for this state of affairs are numerous. It is only in the last few years that GCMs have advanced to the point where their simulations of GHG signals might be marginally believable. Without reasonably good a priori predictions of expected GHG signals from the models, the detection problem is moot. The observational data sets describing changes in the global climate system over the last 50-100 years needed for adequate detection studies have also only come into existence in the last five years. Finally, no coherent, generally-agreed-on detection strategy has been developed by the scientific community interested in the GHG problem. The lack of adequate model predictions and observational sets are largely responsible for this latter condition. The rudimentary detection efforts that have been conducted have generally been based on recognizing the fingerprint of GHG signals in the oceans and atmosphere. GCM results for 1 x 2 x CO 2 equilibrium runs have been used to search for GHG effects induced in tropospheric air and ocean surface temperature fields since the early 1900s. No significant effect has been found

  18. Detection of Doppler Microembolic Signals Using High Order Statistics

    Directory of Open Access Journals (Sweden)

    Maroun Geryes

    2016-01-01

    Full Text Available Robust detection of the smallest circulating cerebral microemboli is an efficient way of preventing strokes, which is second cause of mortality worldwide. Transcranial Doppler ultrasound is widely considered the most convenient system for the detection of microemboli. The most common standard detection is achieved through the Doppler energy signal and depends on an empirically set constant threshold. On the other hand, in the past few years, higher order statistics have been an extensive field of research as they represent descriptive statistics that can be used to detect signal outliers. In this study, we propose new types of microembolic detectors based on the windowed calculation of the third moment skewness and fourth moment kurtosis of the energy signal. During energy embolus-free periods the distribution of the energy is not altered and the skewness and kurtosis signals do not exhibit any peak values. In the presence of emboli, the energy distribution is distorted and the skewness and kurtosis signals exhibit peaks, corresponding to the latter emboli. Applied on real signals, the detection of microemboli through the skewness and kurtosis signals outperformed the detection through standard methods. The sensitivities and specificities reached 78% and 91% and 80% and 90% for the skewness and kurtosis detectors, respectively.

  19. Stochastic model for detection of signals in noise

    OpenAIRE

    Klein, Stanley A.; Levi, Dennis M.

    2009-01-01

    Fifty years ago Birdsall, Tanner, and colleagues made rapid progress in developing signal detection theory into a powerful psychophysical tool. One of their major insights was the utility of adding external noise to the signals of interest. These methods have been enhanced in recent years by the addition of multipass and classification-image methods for opening up the black box. There remain a number of as yet unresolved issues. In particular, Birdsall developed a theorem that large amounts o...

  20. Detection methods of irradiated foodstuffs

    Energy Technology Data Exchange (ETDEWEB)

    Ponta, C C; Cutrubinis, M; Georgescu, R [IRASM Center, Horia Hulubei National Institute for Physics and Nuclear Engineering, PO Box MG-6, RO-077125 Magurele-Bucharest (Romania); Mihai, R [Life and Environmental Physics Department, Horia Hulubei National Institute for Physics and Nuclear Engineering, PO Box MG-6, RO-077125 Magurele-Bucharest (Romania); Secu, M [National Institute of Materials Physics, Bucharest (Romania)

    2005-07-01

    food is marketed as irradiated or if irradiated goods are sold without the appropriate labeling, then detection tests should be able to prove the authenticity of the product. For the moment in Romania there is not any food control laboratory able to detect irradiated foodstuffs. The Technological Irradiation Department coordinates and co finances a research project aimed to establish the first Laboratory of Irradiated Foodstuffs Detection. The detection methods studied in this project are the ESR methods (for cellulose EN 1787/2000, bone EN 1786/1996 and crystalline sugar EN 13708/2003), the TL method (EN 1788/2001), the PSL method (EN 13751/2002) and the DNA Comet Assay method (EN 13784/2001). The above detection methods will be applied on various foodstuffs such: garlic, onion, potatoes, rice, beans, wheat, maize, pistachio, sunflower seeds, raisins, figs, strawberries, chicken, beef, fish, pepper, paprika, thyme, laurel and mushrooms. As an example of the application of a detection method there are presented the ESR spectra of irradiated and nonirradiated paprika acquired according to ESR detection method for irradiated foodstuffs containing cellulose. First of all it can be noticed that the intensity of the signal of cellulose is much higher for the irradiated sample than that for the nonirradiated one and second that appear two radiation specific signals symmetrical to the cellulose signal. These two radiation specific signals prove the irradiation treatment of paprika. (author)

  1. Remote detection device and detection method therefor

    International Nuclear Information System (INIS)

    Kogure, Sumio; Yoshida, Yoji; Matsuo, Takashiro; Takehara, Hidetoshi; Kojima, Shinsaku.

    1997-01-01

    The present invention provides a non-destructive detection device for collectively, efficiently and effectively conducting maintenance and detection for confirming the integrity of a nuclear reactor by way of a shielding member for shielding radiation rays generated from an objective portion to be detected. Namely, devices for direct visual detection using an under water TV camera as a sensor, an eddy current detection using a coil as a sensor and each magnetic powder flow detection are integrated and applied collectively. Specifically, the visual detection by using the TV camera and the eddy current flaw detection are adopted together. The flaw detection with magnetic powder is applied as a means for confirming the results of the two kinds of detections by other method. With such procedures, detection techniques using respective specific theories are combined thereby enabling to enhance the accuracy for the evaluation of the detection. (I.S.)

  2. Subsurface Event Detection and Classification Using Wireless Signal Networks

    Directory of Open Access Journals (Sweden)

    Muhannad T. Suleiman

    2012-11-01

    Full Text Available Subsurface environment sensing and monitoring applications such as detection of water intrusion or a landslide, which could significantly change the physical properties of the host soil, can be accomplished using a novel concept, Wireless Signal Networks (WSiNs. The wireless signal networks take advantage of the variations of radio signal strength on the distributed underground sensor nodes of WSiNs to monitor and characterize the sensed area. To characterize subsurface environments for event detection and classification, this paper provides a detailed list and experimental data of soil properties on how radio propagation is affected by soil properties in subsurface communication environments. Experiments demonstrated that calibrated wireless signal strength variations can be used as indicators to sense changes in the subsurface environment. The concept of WSiNs for the subsurface event detection is evaluated with applications such as detection of water intrusion, relative density change, and relative motion using actual underground sensor nodes. To classify geo-events using the measured signal strength as a main indicator of geo-events, we propose a window-based minimum distance classifier based on Bayesian decision theory. The window-based classifier for wireless signal networks has two steps: event detection and event classification. With the event detection, the window-based classifier classifies geo-events on the event occurring regions that are called a classification window. The proposed window-based classification method is evaluated with a water leakage experiment in which the data has been measured in laboratory experiments. In these experiments, the proposed detection and classification method based on wireless signal network can detect and classify subsurface events.

  3. Subsurface event detection and classification using Wireless Signal Networks.

    Science.gov (United States)

    Yoon, Suk-Un; Ghazanfari, Ehsan; Cheng, Liang; Pamukcu, Sibel; Suleiman, Muhannad T

    2012-11-05

    Subsurface environment sensing and monitoring applications such as detection of water intrusion or a landslide, which could significantly change the physical properties of the host soil, can be accomplished using a novel concept, Wireless Signal Networks (WSiNs). The wireless signal networks take advantage of the variations of radio signal strength on the distributed underground sensor nodes of WSiNs to monitor and characterize the sensed area. To characterize subsurface environments for event detection and classification, this paper provides a detailed list and experimental data of soil properties on how radio propagation is affected by soil properties in subsurface communication environments. Experiments demonstrated that calibrated wireless signal strength variations can be used as indicators to sense changes in the subsurface environment. The concept of WSiNs for the subsurface event detection is evaluated with applications such as detection of water intrusion, relative density change, and relative motion using actual underground sensor nodes. To classify geo-events using the measured signal strength as a main indicator of geo-events, we propose a window-based minimum distance classifier based on Bayesian decision theory. The window-based classifier for wireless signal networks has two steps: event detection and event classification. With the event detection, the window-based classifier classifies geo-events on the event occurring regions that are called a classification window. The proposed window-based classification method is evaluated with a water leakage experiment in which the data has been measured in laboratory experiments. In these experiments, the proposed detection and classification method based on wireless signal network can detect and classify subsurface events.

  4. The erroneous signals of detection theory.

    Science.gov (United States)

    Trimmer, Pete C; Ehlman, Sean M; McNamara, John M; Sih, Andrew

    2017-10-25

    Signal detection theory has influenced the behavioural sciences for over 50 years. The theory provides a simple equation that indicates numerous 'intuitive' results; e.g. prey should be more prone to take evasive action (in response to an ambiguous cue) if predators are more common. Here, we use analytical and computational models to show that, in numerous biological scenarios, the standard results of signal detection theory do not apply; more predators can result in prey being less responsive to such cues. The standard results need not apply when the probability of danger pertains not just to the present, but also to future decisions. We identify how responses to risk should depend on background mortality and autocorrelation, and that predictions in relation to animal welfare can also be reversed from the standard theory. © 2017 The Author(s).

  5. MICROSLEEPS AND THEIR DETECTION FROM THE BIOLOGICAL SIGNALS

    Directory of Open Access Journals (Sweden)

    Martin Holub

    2017-12-01

    Full Text Available Microsleeps (MS are a frequently discussed topic due to their fatal consequences. Their detection is necessary for the purpose of sleep laboratories, where they provide an option for the quantifying rate of sleep deprivation level and objective evaluation of subjective sleepiness. Many studies are dealing with this topic for automotive usage to design a fatigue countermeasure device. We made a research of recent attitude to the development of the automated MS detection methods. We created an overview of several MS detection approaches based on the measurement of biological signals. We also summarized the changes in EEG, EOG and ECG signals, which have been published over the last few years. The reproducible changes in the entire EEG spectrum, primarily with the increased activity of delta and theta, were noticed during a transition to fatigue. There were observed changes of blinking rate and reduction of eye movements during the fatigue tasks. MS correspond with variations in the autonomic regulation of the cardiovascular function, which can be quantified by HRV parameters. The decrease in HR, VLF, and LF/HF before falling asleep was revealed. EEG signal, especially its slow wave activity, considered to be the most predictive and reliable for the level of alertness. In spite of the detection from EEG signal is the most common method, EOG based approaches can also be very efficient and more driver-friendly. Besides, the signal processing in the time domain can improve the detection accuracy of the short events like MS.

  6. Subliminal stimulation and somatosensory signal detection.

    Science.gov (United States)

    Ferrè, Elisa Raffaella; Sahani, Maneesh; Haggard, Patrick

    2016-10-01

    Only a small fraction of sensory signals is consciously perceived. The brain's perceptual systems may include mechanisms of feedforward inhibition that protect the cortex from subliminal noise, thus reserving cortical capacity and conscious awareness for significant stimuli. Here we provide a new view of these mechanisms based on signal detection theory, and gain control. We demonstrated that subliminal somatosensory stimulation decreased sensitivity for the detection of a subsequent somatosensory input, largely due to increased false alarm rates. By delivering the subliminal somatosensory stimulus and the to-be-detected somatosensory stimulus to different digits of the same hand, we show that this effect spreads across the sensory surface. In addition, subliminal somatosensory stimulation tended to produce an increased probability of responding "yes", whether the somatosensory stimulus was present or not. Our results suggest that subliminal stimuli temporarily reduce input gain, avoiding excessive responses to further small inputs. This gain control may be automatic, and may precede discriminative classification of inputs into signals or noise. Crucially, we found that subliminal inputs influenced false alarm rates only on blocks where the to-be-detected stimuli were present, and not on pre-test control blocks where they were absent. Participants appeared to adjust their perceptual criterion according to a statistical distribution of stimuli in the current context, with the presence of supraliminal stimuli having an important role in the criterion-setting process. These findings clarify the cognitive mechanisms that reserve conscious perception for salient and important signals. Copyright © 2016 Elsevier B.V. All rights reserved.

  7. “UTILIZING” SIGNAL DETECTION THEORY

    OpenAIRE

    Lynn, Spencer K.; Barrett, Lisa Feldman

    2014-01-01

    What do inferring what a person is thinking or feeling, deciding to report a symptom to your doctor, judging a defendant’s guilt, and navigating a dimly lit room have in common? They involve perceptual uncertainty (e.g., a scowling face might indicate anger or concentration, which engender different appropriate responses), and behavioral risk (e.g., a cost to making the wrong response). Signal detection theory describes these types of decisions. In this tutorial we show how, by incorporating ...

  8. Detection and Processing Techniques of FECG Signal for Fetal Monitoring

    Directory of Open Access Journals (Sweden)

    Hasan MA

    2009-03-01

    Full Text Available Abstract Fetal electrocardiogram (FECG signal contains potentially precise information that could assist clinicians in making more appropriate and timely decisions during labor. The ultimate reason for the interest in FECG signal analysis is in clinical diagnosis and biomedical applications. The extraction and detection of the FECG signal from composite abdominal signals with powerful and advance methodologies are becoming very important requirements in fetal monitoring. The purpose of this review paper is to illustrate the various methodologies and developed algorithms on FECG signal detection and analysis to provide efficient and effective ways of understanding the FECG signal and its nature for fetal monitoring. A comparative study has been carried out to show the performance and accuracy of various methods of FECG signal analysis for fetal monitoring. Finally, this paper further focused some of the hardware implementations using electrical signals for monitoring the fetal heart rate. This paper opens up a passage for researchers, physicians, and end users to advocate an excellent understanding of FECG signal and its analysis procedures for fetal heart rate monitoring system.

  9. Failed fuel detection method

    International Nuclear Information System (INIS)

    Utamura, Motoaki; Urata, Megumu.

    1976-01-01

    Object: To detect failed fuel element in a reactor with high precision by measuring the radioactivity concentrations for more than one nuclides of fission products ( 131 I and 132 I, for example) contained in each sample of coolant in fuel channel. Method: The radioactivity concentrations in the sampled coolant are obtained from gamma spectra measured by a pulse height analyser after suitable cooling periods according to the half-lives of the fission products to be measured. The first measurement for 132 I is made in two hours after sampling, and the second for 131 I is started one day after the sampling. Fuel element corresponding to the high radioactivity concentrations for both 131 I and 132 I is expected with certainty to have failed

  10. Detection and Classification of Whale Acoustic Signals

    Science.gov (United States)

    Xian, Yin

    This dissertation focuses on two vital challenges in relation to whale acoustic signals: detection and classification. In detection, we evaluated the influence of the uncertain ocean environment on the spectrogram-based detector, and derived the likelihood ratio of the proposed Short Time Fourier Transform detector. Experimental results showed that the proposed detector outperforms detectors based on the spectrogram. The proposed detector is more sensitive to environmental changes because it includes phase information. In classification, our focus is on finding a robust and sparse representation of whale vocalizations. Because whale vocalizations can be modeled as polynomial phase signals, we can represent the whale calls by their polynomial phase coefficients. In this dissertation, we used the Weyl transform to capture chirp rate information, and used a two dimensional feature set to represent whale vocalizations globally. Experimental results showed that our Weyl feature set outperforms chirplet coefficients and MFCC (Mel Frequency Cepstral Coefficients) when applied to our collected data. Since whale vocalizations can be represented by polynomial phase coefficients, it is plausible that the signals lie on a manifold parameterized by these coefficients. We also studied the intrinsic structure of high dimensional whale data by exploiting its geometry. Experimental results showed that nonlinear mappings such as Laplacian Eigenmap and ISOMAP outperform linear mappings such as PCA and MDS, suggesting that the whale acoustic data is nonlinear. We also explored deep learning algorithms on whale acoustic data. We built each layer as convolutions with either a PCA filter bank (PCANet) or a DCT filter bank (DCTNet). With the DCT filter bank, each layer has different a time-frequency scale representation, and from this, one can extract different physical information. Experimental results showed that our PCANet and DCTNet achieve high classification rate on the whale

  11. Aiding the Detection of QRS Complex in ECG Signals by Detecting S Peaks Independently.

    Science.gov (United States)

    Sabherwal, Pooja; Singh, Latika; Agrawal, Monika

    2018-03-30

    In this paper, a novel algorithm for the accurate detection of QRS complex by combining the independent detection of R and S peaks, using fusion algorithm is proposed. R peak detection has been extensively studied and is being used to detect the QRS complex. Whereas, S peaks, which is also part of QRS complex can be independently detected to aid the detection of QRS complex. In this paper, we suggest a method to first estimate S peak from raw ECG signal and then use them to aid the detection of QRS complex. The amplitude of S peak in ECG signal is relatively weak than corresponding R peak, which is traditionally used for the detection of QRS complex, therefore, an appropriate digital filter is designed to enhance the S peaks. These enhanced S peaks are then detected by adaptive thresholding. The algorithm is validated on all the signals of MIT-BIH arrhythmia database and noise stress database taken from physionet.org. The algorithm performs reasonably well even for the signals highly corrupted by noise. The algorithm performance is confirmed by sensitivity and positive predictivity of 99.99% and the detection accuracy of 99.98% for QRS complex detection. The number of false positives and false negatives resulted while analysis has been drastically reduced to 80 and 42 against the 98 and 84 the best results reported so far.

  12. Signal trend identification with fuzzy methods

    International Nuclear Information System (INIS)

    Reifman, J.; Tsoukalas, L. H.; Wang, X.; Wei, T. Y. C.

    1999-01-01

    A fuzzy-logic-based methodology for on-line signal trend identification is introduced. Although signal trend identification is complicated by the presence of noise, fuzzy logic can help capture important features of on-line signals and classify incoming power plant signals into increasing, decreasing and steady-state trend categories. In order to verify the methodology, a code named PROTREN is developed and tested using plant data. The results indicate that the code is capable of detecting transients accurately, identifying trends reliably, and not misinterpreting a steady-state signal as a transient one

  13. Detection method of internal leakage from valve using acoustic method

    International Nuclear Information System (INIS)

    Kumagai, Hiromichi; Kitajima, Akira; Suzuki, Akio.

    1990-01-01

    The objective of this study is to estimate the feasibility of the acoustic method for the internal leakage from the valves in power plants. From the experimental results, it was suggested that the acoustic method for the monitoring of leakage was feasible. When the background levels are higher than the acoustic signals from leakage, we can detect the leakage analyzing the spectrum of the remainders which take the background noise from the acoustic signals. (author)

  14. Singularity detection by wavelet approach: application to electrocardiogram signal

    Science.gov (United States)

    Jalil, Bushra; Beya, Ouadi; Fauvet, Eric; Laligant, Olivier

    2010-01-01

    In signal processing, the region of abrupt changes contains the most of the useful information about the nature of the signal. The region or the points where these changes occurred are often termed as singular point or singular region. The singularity is considered to be an important character of the signal, as it refers to the discontinuity and interruption present in the signal and the main purpose of the detection of such singular point is to identify the existence, location and size of those singularities. Electrocardiogram (ECG) signal is used to analyze the cardiovascular activity in the human body. However the presence of noise due to several reasons limits the doctor's decision and prevents accurate identification of different pathologies. In this work we attempt to analyze the ECG signal with energy based approach and some heuristic methods to segment and identify different signatures inside the signal. ECG signal has been initially denoised by empirical wavelet shrinkage approach based on Steins Unbiased Risk Estimate (SURE). At the second stage, the ECG signal has been analyzed by Mallat approach based on modulus maximas and Lipschitz exponent computation. The results from both approaches has been discussed and important aspects has been highlighted. In order to evaluate the algorithm, the analysis has been done on MIT-BIH Arrhythmia database; a set of ECG data records sampled at a rate of 360 Hz with 11 bit resolution over a 10mv range. The results have been examined and approved by medical doctors.

  15. Hall Sensor Output Signal Fault-Detection & Safety Implementation Logic

    Directory of Open Access Journals (Sweden)

    Lee SangHun

    2016-01-01

    Full Text Available Recently BLDC motors have been popular in various industrial applications and electric mobility. Recently BLDC motors have been popular in various industrial applications and electric mobility. In most brushless direct current (BLDC motor drives, there are three hall sensors as a position reference. Low resolution hall effect sensor is popularly used to estimate the rotor position because of its good comprehensive performance such as low cost, high reliability and sufficient precision. Various possible faults may happen in a hall effect sensor. This paper presents a fault-tolerant operation method that allows the control of a BLDC motor with one faulty hall sensor and presents the hall sensor output fault-tolerant control strategy. The situations considered are when the output from a hall sensor stays continuously at low or high levels, or a short-time pulse appears on a hall sensor signal. For fault detection, identification of a faulty signal and generating a substitute signal, this method only needs the information from the hall sensors. There are a few research work on hall effect sensor failure of BLDC motor. The conventional fault diagnosis methods are signal analysis, model based analysis and knowledge based analysis. The proposed method is signal based analysis using a compensation signal for reconfiguration and therefore fault diagnosis can be fast. The proposed method is validated to execute the simulation using PSIM.

  16. Sound card based digital correlation detection of weak photoelectrical signals

    International Nuclear Information System (INIS)

    Tang Guanghui; Wang Jiangcheng

    2005-01-01

    A simple and low-cost digital correlation method is proposed to investigate weak photoelectrical signals, using a high-speed photodiode as detector, which is directly connected to a programmably triggered sound card analogue-to-digital converter and a personal computer. Two testing experiments, autocorrelation detection of weak flickering signals from a computer monitor under background of noisy outdoor stray light and cross-correlation measurement of the surface velocity of a motional tape, are performed, showing that the results are reliable and the method is easy to implement

  17. Early detection of structual changes in random signal

    International Nuclear Information System (INIS)

    Kuroda, Yoshiteru; Yokota, Katsuhiro

    1981-01-01

    Early detection of structual changes in observed random signal is very important from the point of system diagnosis. In this paper, the following procedures are applied to this problem and the results are compared. (1) auto-regressive model to random signal to calculate the prediction error, i.e., the defference between observed and predicted values. (2) auto-regressive method to caluculate the sum of the prediction error. (3) a method is based on AIC (Akaike Information Criterion). Simulation is made of these procedures, indicating their merits and demerits as a diagostic tools. (author)

  18. Optimal and adaptive methods of processing hydroacoustic signals (review)

    Science.gov (United States)

    Malyshkin, G. S.; Sidel'nikov, G. B.

    2014-09-01

    Different methods of optimal and adaptive processing of hydroacoustic signals for multipath propagation and scattering are considered. Advantages and drawbacks of the classical adaptive (Capon, MUSIC, and Johnson) algorithms and "fast" projection algorithms are analyzed for the case of multipath propagation and scattering of strong signals. The classical optimal approaches to detecting multipath signals are presented. A mechanism of controlled normalization of strong signals is proposed to automatically detect weak signals. The results of simulating the operation of different detection algorithms for a linear equidistant array under multipath propagation and scattering are presented. An automatic detector is analyzed, which is based on classical or fast projection algorithms, which estimates the background proceeding from median filtering or the method of bilateral spatial contrast.

  19. Detecting Volcanic Ash Plumes with GNSS Signals

    Science.gov (United States)

    Rainville, N.; Larson, K. M.; Palo, S. E.; Mattia, M.; Rossi, M.; Coltelli, M.; Roesler, C.; Fee, D.

    2016-12-01

    Global Navigation Satellite Systems (GNSS) receivers are commonly placed near volcanic sites to measure ground deformation. In addition to the carrier phase data used to measure ground position, these receivers also record Signal to Noise ratio (SNR) data. Larson (2013) showed that attenuations in SNR data strongly correlate with ash emissions at a series of eruptions of Redoubt Volcano. This finding has been confirmed at eruptions for Tongariro, Mt Etna, Mt Shindake, and Sakurajima. In each of these detections, very expensive geodetic quality GNSS receivers were used. If low-cost GNSS instruments could be used instead, a networked array could be deployed and optimized for plume detection and tomography. The outputs of this sensor array could then be used by both local volcanic observatories and Volcano Ash Advisory Centers. Here we will describe progress in developing such an array. The sensors we are working with are intended for navigation use, and thus lack the supporting power and communications equipment necessary for a networked system. Reliably providing those features is major challenge for the overall sensor design. We have built prototypes of our Volcano Ash Plume Receiver (VAPR), with solar panels, lithium-ion batteries and onboard data storage for preliminary testing. We will present results of our field tests of both receivers and antennas. A second critical need for our array is a reliable detection algorithm. We have tested our algorithm on data from recent eruptions and have incorporated the noise characteristics of the low-cost GNSS receiver. We have also developed a simulation capability so that the receivers can be deployed to optimize vent crossing GNSS signals.

  20. Signal Detection, Target Tracking and Differential Geometry Applications to Statistical Inference

    National Research Council Canada - National Science Library

    Rao, C

    1997-01-01

    Signal detection and target tracking. A novel method known as polynomial rooting approach is proposed to obtain estimates of frequencies, amplitudes and noise variance of two-dimensional exponential signals...

  1. Crack detecting method

    International Nuclear Information System (INIS)

    Narita, Michiko; Aida, Shigekazu

    1998-01-01

    A penetration liquid or a slow drying penetration liquid prepared by mixing a penetration liquid and a slow drying liquid is filled to the inside of an artificial crack formed to a member to be detected such as of boiler power generation facilities and nuclear power facilities. A developing liquid is applied to the periphery of the artificial crack on the surface of a member to be detected. As the slow-drying liquid, an oil having a viscosity of 56 is preferably used. Loads are applied repeatedly to the member to be detected, and when a crack is caused to the artificial crack, the permeation liquid penetrates into the crack. The penetration liquid penetrated into the crack is developed by the developing liquid previously coated to the periphery of the artificial crack of the surface of the member to be detected. When a crack is caused, since the crack is developed clearly even if it is a small opening, the crack can be recognized visually reliably. (I.N.)

  2. Machine Learning Techniques for Optical Performance Monitoring from Directly Detected PDM-QAM Signals

    DEFF Research Database (Denmark)

    Thrane, Jakob; Wass, Jesper; Piels, Molly

    2017-01-01

    Linear signal processing algorithms are effective in dealing with linear transmission channel and linear signal detection, while the nonlinear signal processing algorithms, from the machine learning community, are effective in dealing with nonlinear transmission channel and nonlinear signal...... detection. In this paper, a brief overview of the various machine learning methods and their application in optical communication is presented and discussed. Moreover, supervised machine learning methods, such as neural networks and support vector machine, are experimentally demonstrated for in-band optical...

  3. Parametric roll resonance monitoring using signal-based detection

    DEFF Research Database (Denmark)

    Galeazzi, Roberto; Blanke, Mogens; Falkenberg, Thomas

    2015-01-01

    Extreme roll motion of ships can be caused by several phenomena, one of which is parametric roll resonance. Several incidents occurred unexpectedly around the millennium and caused vast fiscal losses on large container vessels. The phenomenon is now well understood and some consider parametric roll...... algorithms in real conditions, and to evaluate the frequency of parametric roll events on the selected vessels. Detection performance is scrutinised through the validation of the detected events using owners’ standard methods, and supported by available wave radar data. Further, a bivariate statistical...... analysis of the outcome of the signal-based detectors is performed to assess the real life false alarm probability. It is shown that detection robustness and very low false warning rates are obtained. The study concludes that small parametric roll events are occurring, and that the proposed signal...

  4. Multilevel electrochemical signal detections of metalloprotein heterolayers for bioelectronic device

    Energy Technology Data Exchange (ETDEWEB)

    Chung, Yong-Ho; Yoo, Si-Youl; Lee, Taek [Department of Chemical and Biomolecular Engineering, Sogang University, 35 Baekbeom-ro(Sinsu-dong), Mapo-gu, Seoul 121-742 (Korea, Republic of); Lee, Hun Joo [Interdisciplinary Program of Integrated Biotechnology, Sogang University, 35 Baekbeomro(Sinsu-dong), Mapo-gu, Seoul 121-742 (Korea, Republic of); Min, Junhong [School of Integrative Engineering, Chung-Ang University, Heukseok-dong, Dongjak-gu, Seoul 156-756 (Korea, Republic of); Choi, Jeong-Woo, E-mail: jwchoi@sogang.ac.kr [Department of Chemical and Biomolecular Engineering, Sogang University, 35 Baekbeom-ro(Sinsu-dong), Mapo-gu, Seoul 121-742 (Korea, Republic of); Interdisciplinary Program of Integrated Biotechnology, Sogang University, 35 Baekbeomro(Sinsu-dong), Mapo-gu, Seoul 121-742 (Korea, Republic of)

    2014-01-31

    In the present study, we investigated the simultaneous detection of multilevel electrochemical signals from various metalloprotein heterolayers for the bioelectronic devices. A layer-by-layer assembly method based on simple electrostatic interaction was introduced to form protein bilayers. The gold substrate was modified with poly (ethylene glycol) thiol acid as the precursor, which introduced negative charges to the surface. Based on the isoelectric point, net-charge controlled metalloproteins by pH adjustment were sequentially immobilized on this negatively charged substrate. The degree of protein immobilization on the gold substrate was confirmed by surface plasmon resonance spectroscopy, and the surface topology changes due to the protein immobilization were confirmed by atomic force microscopy. Redox signals in the protein layers were measured by cyclic voltammetry. As a result, various redox signals generated from different metalloproteins on a single electrode were monitored. This proposed method for the detection of multi-level electrochemical signals can be directly applied to bioelectronic devices that store multi-information in a single electrode. - Highlights: • We fabricated heterolayers composed of various metalloproteins. • Metalloproteins were immobilized by layer-by-layer assembly. • The degree of immobilization was controlled by the net charge of metalloproteins. • Various redox signals generated from heterolayers were well monitored.

  5. Digital signal processing with kernel methods

    CERN Document Server

    Rojo-Alvarez, José Luis; Muñoz-Marí, Jordi; Camps-Valls, Gustavo

    2018-01-01

    A realistic and comprehensive review of joint approaches to machine learning and signal processing algorithms, with application to communications, multimedia, and biomedical engineering systems Digital Signal Processing with Kernel Methods reviews the milestones in the mixing of classical digital signal processing models and advanced kernel machines statistical learning tools. It explains the fundamental concepts from both fields of machine learning and signal processing so that readers can quickly get up to speed in order to begin developing the concepts and application software in their own research. Digital Signal Processing with Kernel Methods provides a comprehensive overview of kernel methods in signal processing, without restriction to any application field. It also offers example applications and detailed benchmarking experiments with real and synthetic datasets throughout. Readers can find further worked examples with Matlab source code on a website developed by the authors. * Presents the necess...

  6. Confidence Measurement in the Light of Signal Detection Theory

    Directory of Open Access Journals (Sweden)

    Sébastien eMassoni

    2014-12-01

    Full Text Available We compare three alternative methods for eliciting retrospective confidence in the context of a simple perceptual task: the Simple Confidence Rating (a direct report on a numerical scale, the Quadratic Scoring Rule (a post-wagering procedure and the Matching Probability (a generalization of the no-loss gambling method. We systematically compare the results obtained with these three rules to the theoretical confidence levels that can be inferred from performance in the perceptual task using Signal Detection Theory. We find that the Matching Probability provides better results in that respect. We conclude that Matching Probability is particularly well suited for studies of confidence that use Signal Detection Theory as a theoretical framework.

  7. Signal detection by active, noisy hair bundles

    Science.gov (United States)

    O'Maoiléidigh, Dáibhid; Salvi, Joshua D.; Hudspeth, A. J.

    2018-05-01

    Vertebrate ears employ hair bundles to transduce mechanical movements into electrical signals, but their performance is limited by noise. Hair bundles are substantially more sensitive to periodic stimulation when they are mechanically active, however, than when they are passive. We developed a model of active hair-bundle mechanics that predicts the conditions under which a bundle is most sensitive to periodic stimulation. The model relies only on the existence of mechanotransduction channels and an active adaptation mechanism that recloses the channels. For a frequency-detuned stimulus, a noisy hair bundle's phase-locked response and degree of entrainment as well as its detection bandwidth are maximized when the bundle exhibits low-amplitude spontaneous oscillations. The phase-locked response and entrainment of a bundle are predicted to peak as functions of the noise level. We confirmed several of these predictions experimentally by periodically forcing hair bundles held near the onset of self-oscillation. A hair bundle's active process amplifies the stimulus preferentially over the noise, allowing the bundle to detect periodic forces less than 1 pN in amplitude. Moreover, the addition of noise can improve a bundle's ability to detect the stimulus. Although, mechanical activity has not yet been observed in mammalian hair bundles, a related model predicts that active but quiescent bundles can oscillate spontaneously when they are loaded by a sufficiently massive object such as the tectorial membrane. Overall, this work indicates that auditory systems rely on active elements, composed of hair cells and their mechanical environment, that operate on the brink of self-oscillation.

  8. [Detection of surface EMG signal using active electrode].

    Science.gov (United States)

    He, Qinghua; Peng, Chenglin; Wu, Baoming; Wang, He

    2003-09-01

    Research of surface electromyogram(EMG) signal is important in rehabilitation medicine, sport medicine and clinical diagnosis, accurate detection of signal is the base of quantitative analysis of surface EMG signal. In this article were discussed how to reduce possible noise in the detection of surface EMG. Considerations on the design of electrode unit were presented. Instrumentation amplifier AD620 was employed to design a bipolar active electrode for use in surface EMG detection. The experiments showed that active electrode could be used to improve signal/noise ratio, reduce noise and detect surface EMG signal effectively.

  9. Detecting Seismic Infrasound Signals on Balloon Platforms

    Science.gov (United States)

    Krishnamoorthy, S.; Komjathy, A.; Cutts, J. A.; Pauken, M.; Garcia, R.; Mimoun, D.; Jackson, J. M.; Kedar, S.; Smrekar, S. E.; Hall, J. L.

    2017-12-01

    The determination of the interior structure of a planet requires detailed seismic investigations - a process that entails the detection and characterization of seismic waves due to geological activities (e.g., earthquakes, volcanoes, etc.). For decades, this task has primarily been performed on Earth by an ever-expanding network of terrestrial seismic stations. However, on planets such as Venus, where the surface pressure and temperature can reach as high as 90 atmospheres and 450 degrees Celsius respectively, placing seismometers on the planet's surface poses a vexing technological challenge. However, the upper layers of the Venusian atmosphere are more benign and capable of hosting geophysical payloads for longer mission lifetimes. In order to achieve the aim of performing geophysical experiments from an atmospheric platform, JPL and its partners (ISAE-SUPAERO and California Institute of Technology) are in the process of developing technologies for detection of infrasonic waves generated by earthquakes from a balloon. The coupling of seismic energy into the atmosphere critically depends on the density differential between the surface of the planet and the atmosphere. Therefore, the successful demonstration of this technique on Earth would provide ample reason to expect success on Venus, where the atmospheric impedance is approximately 60 times that of Earth. In this presentation, we will share results from the first set of Earth-based balloon experiments performed in Pahrump, Nevada in June 2017. These tests involved the generation of artificial sources of known intensity using a seismic hammer and their detection using a complex network of sensors, including highly sensitive micro-barometers suspended from balloons, GPS receivers, geophones, microphones, and seismometers. This experiment was the first of its kind and was successful in detecting infrasonic waves from the earthquakes generated by the seismic hammer. We will present the first comprehensive analysis

  10. A Voltage Quality Detection Method

    DEFF Research Database (Denmark)

    Chen, Zhe; Wei, Mu

    2008-01-01

    This paper presents a voltage quality detection method based on a phase-locked loop (PLL) technique. The technique can detect the voltage magnitude and phase angle of each individual phase under both normal and fault power system conditions. The proposed method has the potential to evaluate various...

  11. Signal processing for passive detection and classification of underwater acoustic signals

    Science.gov (United States)

    Chung, Kil Woo

    2011-12-01

    This dissertation examines signal processing for passive detection, classification and tracking of underwater acoustic signals for improving port security and the security of coastal and offshore operations. First, we consider the problem of passive acoustic detection of a diver in a shallow water environment. A frequency-domain multi-band matched-filter approach to swimmer detection is presented. The idea is to break the frequency contents of the hydrophone signals into multiple narrow frequency bands, followed by time averaged (about half of a second) energy calculation over each band. Then, spectra composed of such energy samples over the chosen frequency bands are correlated to form a decision variable. The frequency bands with highest Signal/Noise ratio are used for detection. The performance of the proposed approach is demonstrated for experimental data collected for a diver in the Hudson River. We also propose a new referenceless frequency-domain multi-band detector which, unlike other reference-based detectors, does not require a diver specific signature. Instead, our detector matches to a general feature of the diver spectrum in the high frequency range: the spectrum is roughly periodic in time and approximately flat when the diver exhales. The performance of the proposed approach is demonstrated by using experimental data collected from the Hudson River. Moreover, we present detection, classification and tracking of small vessel signals. Hydroacoustic sensors can be applied for the detection of noise generated by vessels, and this noise can be used for vessel detection, classification and tracking. This dissertation presents recent improvements aimed at the measurement and separation of ship DEMON (Detection of Envelope Modulation on Noise) acoustic signatures in busy harbor conditions. Ship signature measurements were conducted in the Hudson River and NY Harbor. The DEMON spectra demonstrated much better temporal stability compared with the full ship

  12. A new signal-on method for the detection of protein based on binding-induced strategy and photoinduced electron transfer between Ag nanoclusters and split G-quadruplex-hemin complexes

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Kai, E-mail: zhangkai@jsinm.org; Wang, Ke; Zhu, Xue; Xie, Minhao

    2015-08-05

    Proteins play important roles in biological and cellular processes. The levels of proteins can be useful biomarkers for cellular events or disease diagnosis, thus the method for sensitive and selective detection of proteins is imperative to proteins express, study, and clinical diagnosis. Herein, we report a “signal-on” platform for the assay of protein based on binding-induced strategy and photoinduced electron transfer between Ag nanoclusters and split G-quadruplex-hemin complexes. By using biotin as the affinity ligand, this simple protocol could sensitively detect streptavidin with a detection limit down to 10 pM. With the use of an antibody as the affinity ligand, a method for homogeneous fluorescence detection of Prostate Specific Antigen (PSA) was also proposed with a detection limit of 10 pM. The one-step and wash-free assay showed good selectivity. Its high sensitivity, acceptable accuracy, and satisfactory versatility of analytes led to various applications in bioanalysis. - Highlights: • AgNCs have great potential for application in biomedicine. • Binding of two affinity ligands can result in binding-induced DNA assemblies. • PET can be happened between DNA/AgNCs and G-quadruplex/hemin complexes. • A platform for the detection of proteins was proposed by using PET and binding-induced strategy.

  13. Detection of oscillatory components in noise signals and its application to fast detection of sodium boiling in LMFBR's

    International Nuclear Information System (INIS)

    Ehrhardt, J.

    1975-09-01

    In general, the surveillance of technical plants is performed by observating the mean value of measured signals. In this method not all information included in these signals is used. On the other hand - for example in a reactor - disturbances are possible which generate small oscillatory components in the measured signals. In general, these oscillatory components do not influence the mean value of the signals and consequently do not activate the conventional control system; however they can be found by analysis of the signal's noise component. For the detection of these oscillatory signals the observation of the frequency spectra of the noise signals is particularly advantageous because they produce peaks at the oscillation frequencies. In this paper a new detection system for the fast detection of suddenly appearing peaks in the frequency spectra of noise signals is presented. The prototype of a compact detection unit was developed which continuously computes the power spectral density (PSD) of noise signals and simultaneously supervises the PSD for peaks in the relevant frequency range. The detection method is not affected by the frequency dependance of the PSD and is applicable to any noise signal. General criteria were developed to enable the determination of the optimal detection system and its sensitivity. The upper limits of false alarm rate and detection time were taken into account. The detection criteria are applicable to all noise signals with approximately normally distributed amplitudes. Theoretical results were confirmed in a number of experiments; special experimental and theoretical parameter studies were done for the optimal detection of sodium boiling in LMFBR's. Computations based on these results showed that local and integral sodium boiling can be detected in a wide core range of SNR 300 by observing fluctuations of the neutron flux. In this connection it is important to point out that no additional core instrumentation is necessary because the

  14. A novel method, digital genome scanning detects KRAS gene amplification in gastric cancers: involvement of overexpressed wild-type KRAS in downstream signaling and cancer cell growth

    Directory of Open Access Journals (Sweden)

    Yanagihara Kazuyoshi

    2009-06-01

    Full Text Available Abstract Background Gastric cancer is the third most common malignancy affecting the general population worldwide. Aberrant activation of KRAS is a key factor in the development of many types of tumor, however, oncogenic mutations of KRAS are infrequent in gastric cancer. We have developed a novel quantitative method of analysis of DNA copy number, termed digital genome scanning (DGS, which is based on the enumeration of short restriction fragments, and does not involve PCR or hybridization. In the current study, we used DGS to survey copy-number alterations in gastric cancer cells. Methods DGS of gastric cancer cell lines was performed using the sequences of 5000 to 15000 restriction fragments. We screened 20 gastric cancer cell lines and 86 primary gastric tumors for KRAS amplification by quantitative PCR, and investigated KRAS amplification at the DNA, mRNA and protein levels by mutational analysis, real-time PCR, immunoblot analysis, GTP-RAS pull-down assay and immunohistochemical analysis. The effect of KRAS knock-down on the activation of p44/42 MAP kinase and AKT and on cell growth were examined by immunoblot and colorimetric assay, respectively. Results DGS analysis of the HSC45 gastric cancer cell line revealed the amplification of a 500-kb region on chromosome 12p12.1, which contains the KRAS gene locus. Amplification of the KRAS locus was detected in 15% (3/20 of gastric cancer cell lines (8–18-fold amplification and 4.7% (4/86 of primary gastric tumors (8–50-fold amplification. KRAS mutations were identified in two of the three cell lines in which KRAS was amplified, but were not detected in any of the primary tumors. Overexpression of KRAS protein correlated directly with increased KRAS copy number. The level of GTP-bound KRAS was elevated following serum stimulation in cells with amplified wild-type KRAS, but not in cells with amplified mutant KRAS. Knock-down of KRAS in gastric cancer cells that carried amplified wild

  15. Evaluation of signal processing for boiling noise detection

    International Nuclear Information System (INIS)

    Black, J.L.; Ledwidge, T.J.

    1989-01-01

    As part of the co-ordinated research programme on the detection of sodium boiling some further analysis has been performed on the data from the test loop in Karlsruhe and some preliminary analysis of the data from the BOR 60 experiment. The work on the Karlsruhe data is concerned with the search for a reliable method by which the quality of signal processing strategies may be compared. The results show that the three novel methods previously reported are all markedly superior to the mean square method which is used as a benchmark. The three novel methods are nth order differentiation in the frequency domain, the mean square prediction based on nth order conditional expectation and the nth order probability density function. A preliminary analysis on the data from the BOR 60 reactor shows that 4th order differentiation is adequate for the detection of signals derived from a pressure transducer and that the map of spurious trip probability (S) and the probability of missing an event (M) is consistent with the theoretical model proposed herein, and the suggested procedures for evaluating the quality of detection strategies. (author). 15 figs, 1 tab

  16. Smartphone application for emergency signal detection.

    Science.gov (United States)

    Figueiredo, Isabel N; Leal, Carlos; Pinto, Luís; Bolito, Jason; Lemos, André

    2016-09-01

    Currently, a number of studies focus on the study and design of new healthcare technologies to improve elderly health and quality of life. Taking advantage of the popularity, portability, and inherent technology of smartphones, we present an emergency application for smartphones, designated as knock-to-panic (KTP). This innovative and novel system enables users to simply hit their devices in order to send an alarm signal to an emergency service. This application is a complete and autonomous emergency system, and can provide an economic, reliable, and unobtrusive method for elderly monitoring or safety protection. Moreover, the simple and fast activation of KTP makes it a viable and potentially superior alternative to traditional ambient assisted living emergency calls. Furthermore, KTP can be further extended to the general population as well and not just be limited for elderly persons. The proposed method is a threshold-based algorithm and is designed to require a low battery power consumption. The evaluation of the performance of the algorithm in collected data indicates that both sensitivity and specificity are above 90%. Copyright © 2016 IPEM. Published by Elsevier Ltd. All rights reserved.

  17. Detection of weak optical signals with a laser amplifier

    International Nuclear Information System (INIS)

    Kozlovskii, A. V.

    2006-01-01

    Detection of weak and extremely weak light signals amplified by linear and four-wave mixing laser amplifiers is analyzed. Photoelectron distributions are found for different input photon statistics over a wide range of gain. Signal-to-noise ratios are calculated and analyzed for preamplification schemes using linear and four-wave mixing amplifiers. Calculations show that the high signal-to-noise ratio (much higher than unity), ensuring reliable detection of weak input signals, can be attained only with a four-wave mixing preamplification scheme. Qualitative dependence of the signal-to-noise ratio on the quantum statistical properties of both signal and idler waves is demonstrated

  18. A novel method, digital genome scanning detects KRAS gene amplification in gastric cancers: involvement of overexpressed wild-type KRAS in downstream signaling and cancer cell growth

    International Nuclear Information System (INIS)

    Mita, Hiroaki; Yanagihara, Kazuyoshi; Fujita, Masahiro; Hosokawa, Masao; Kusano, Masanobu; Sabau, Sorin Vasile; Tatsumi, Haruyuki; Imai, Kohzoh; Shinomura, Yasuhisa; Tokino, Takashi; Toyota, Minoru; Aoki, Fumio; Akashi, Hirofumi; Maruyama, Reo; Sasaki, Yasushi; Suzuki, Hiromu; Idogawa, Masashi; Kashima, Lisa

    2009-01-01

    Gastric cancer is the third most common malignancy affecting the general population worldwide. Aberrant activation of KRAS is a key factor in the development of many types of tumor, however, oncogenic mutations of KRAS are infrequent in gastric cancer. We have developed a novel quantitative method of analysis of DNA copy number, termed digital genome scanning (DGS), which is based on the enumeration of short restriction fragments, and does not involve PCR or hybridization. In the current study, we used DGS to survey copy-number alterations in gastric cancer cells. DGS of gastric cancer cell lines was performed using the sequences of 5000 to 15000 restriction fragments. We screened 20 gastric cancer cell lines and 86 primary gastric tumors for KRAS amplification by quantitative PCR, and investigated KRAS amplification at the DNA, mRNA and protein levels by mutational analysis, real-time PCR, immunoblot analysis, GTP-RAS pull-down assay and immunohistochemical analysis. The effect of KRAS knock-down on the activation of p44/42 MAP kinase and AKT and on cell growth were examined by immunoblot and colorimetric assay, respectively. DGS analysis of the HSC45 gastric cancer cell line revealed the amplification of a 500-kb region on chromosome 12p12.1, which contains the KRAS gene locus. Amplification of the KRAS locus was detected in 15% (3/20) of gastric cancer cell lines (8–18-fold amplification) and 4.7% (4/86) of primary gastric tumors (8–50-fold amplification). KRAS mutations were identified in two of the three cell lines in which KRAS was amplified, but were not detected in any of the primary tumors. Overexpression of KRAS protein correlated directly with increased KRAS copy number. The level of GTP-bound KRAS was elevated following serum stimulation in cells with amplified wild-type KRAS, but not in cells with amplified mutant KRAS. Knock-down of KRAS in gastric cancer cells that carried amplified wild-type KRAS resulted in the inhibition of cell growth and

  19. A Comparison between the Decimated Padé Approximant and Decimated Signal Diagonalization Methods for Leak Detection in Pipelines Equipped with Pressure Sensors.

    Science.gov (United States)

    Lay-Ekuakille, Aimé; Fabbiano, Laura; Vacca, Gaetano; Kitoko, Joël Kidiamboko; Kulapa, Patrice Bibala; Telesca, Vito

    2018-06-04

    Pipelines conveying fluids are considered strategic infrastructures to be protected and maintained. They generally serve for transportation of important fluids such as drinkable water, waste water, oil, gas, chemicals, etc. Monitoring and continuous testing, especially on-line, are necessary to assess the condition of pipelines. The paper presents findings related to a comparison between two spectral response algorithms based on the decimated signal diagonalization (DSD) and decimated Padé approximant (DPA) techniques that allow to one to process signals delivered by pressure sensors mounted on an experimental pipeline.

  20. A Comparison between the Decimated Padé Approximant and Decimated Signal Diagonalization Methods for Leak Detection in Pipelines Equipped with Pressure Sensors

    Directory of Open Access Journals (Sweden)

    Aimé Lay-Ekuakille

    2018-06-01

    Full Text Available Pipelines conveying fluids are considered strategic infrastructures to be protected and maintained. They generally serve for transportation of important fluids such as drinkable water, waste water, oil, gas, chemicals, etc. Monitoring and continuous testing, especially on-line, are necessary to assess the condition of pipelines. The paper presents findings related to a comparison between two spectral response algorithms based on the decimated signal diagonalization (DSD and decimated Padé approximant (DPA techniques that allow to one to process signals delivered by pressure sensors mounted on an experimental pipeline.

  1. Detection methods for irradiated food

    International Nuclear Information System (INIS)

    Stevenson, M.H.

    1993-01-01

    The plenary lecture gives a brief historical review of the development of methods for the detection of food irradiation and defines the demands on such methods. The methods described in detail are as follows: 1) Physical methods: As examples of luminescence methods, thermoluminescence and chermoluminescence are mentioned; ESR spectroscopy is discussed in detail by means of individual examples (crustaceans, frutis and vegetables, spieces and herbs, nuts). 2) Chemical methods: Examples given for these are methods that make use of alterations in lipids through radiation (formation of long-chain hydrocarbons, formation of 2-alkyl butanones), respectively radiation-induced alterations in the DNA. 3) Microbiological methods. An extensive bibliography is appended. (VHE) [de

  2. A Bayesian method for detecting stellar flares

    Science.gov (United States)

    Pitkin, M.; Williams, D.; Fletcher, L.; Grant, S. D. T.

    2014-12-01

    We present a Bayesian-odds-ratio-based algorithm for detecting stellar flares in light-curve data. We assume flares are described by a model in which there is a rapid rise with a half-Gaussian profile, followed by an exponential decay. Our signal model also contains a polynomial background model required to fit underlying light-curve variations in the data, which could otherwise partially mimic a flare. We characterize the false alarm probability and efficiency of this method under the assumption that any unmodelled noise in the data is Gaussian, and compare it with a simpler thresholding method based on that used in Walkowicz et al. We find our method has a significant increase in detection efficiency for low signal-to-noise ratio (S/N) flares. For a conservative false alarm probability our method can detect 95 per cent of flares with S/N less than 20, as compared to S/N of 25 for the simpler method. We also test how well the assumption of Gaussian noise holds by applying the method to a selection of `quiet' Kepler stars. As an example we have applied our method to a selection of stars in Kepler Quarter 1 data. The method finds 687 flaring stars with a total of 1873 flares after vetos have been applied. For these flares we have made preliminary characterizations of their durations and and S/N.

  3. A signal detection theory analysis of an unconscious perception effect.

    Science.gov (United States)

    Haase, S J; Theios, J; Jenison, R

    1999-07-01

    The independent observation model (Macmillan & Creelman, 1991) is fitted to detection-identification data collected under conditions of heavy masking. The model accurately predicts a quantitative relationship between stimulus detection and stimulus identification over a wide range of detection performance. This model can also be used to offer a signal detection interpretation of the common finding of above-chance identification following a missed signal. While our finding is not a new one, the stimuli used in this experiment (redundant three-letter strings) differ slightly from those used in traditional signal detection work. Also, the stimuli were presented very briefly and heavily masked, conditions typical in the study of unconscious perception effects.

  4. Detection method of internal leakage from valve using acoustic method

    International Nuclear Information System (INIS)

    Kumagai, Horomichi

    1990-01-01

    The purpose of this study is to estimate the availability of acoustic method for detecting the internal leakage of valves at power plants. Experiments have been carried out on the characteristics of acoustic noise caused by the leak simulated flow. From the experimental results, the mechanism of the acoustic noisegenerated from flow, the relation between acoustic intensity and leak flow velocity, and the characteristics of the acoustic frequency spectrum were clarified. The acoustic method was applied to valves at site, and the background noises were measured in abnormal plant conditions. When the background level is higher than the acoustic signal, the difference between the background noise frequency spectrum and the acoustic signal spectrum provide a very useful leak detection method. (author)

  5. Signal processing methods for MFE plasma diagnostics

    International Nuclear Information System (INIS)

    Candy, J.V.; Casper, T.; Kane, R.

    1985-02-01

    The application of various signal processing methods to extract energy storage information from plasma diamagnetism sensors occurring during physics experiments on the Tandom Mirror Experiment-Upgrade (TMX-U) is discussed. We show how these processing techniques can be used to decrease the uncertainty in the corresponding sensor measurements. The algorithms suggested are implemented using SIG, an interactive signal processing package developed at LLNL

  6. A real-time radar pulse signal detection method and its performance analysis%一种实时雷达脉冲信号检测算法及其性能分析

    Institute of Scientific and Technical Information of China (English)

    王芳; 王旭东; 潘明海

    2012-01-01

    提出了一种新的实时雷达脉冲信号检测算法,该算法首先将数据分为两路,对一路进行单点滑动、取共轭,然后与另一路信号相乘,再累加、取模,最后与门限比较,得到检测结果.算法具有递推和流水结构,硬件实现时只需一个复数乘法器、一个复数加法器、一个复数减法器和一个复数取模运算器.在此采用一阶扰动分析,推导了算法起始点检测误差的解析式,给出了算法性能边界,仿真结果验证了理论推导的正确性.与其他信号检测算法相比,该算法结构规整,易于硬件应用,可实现实时检测.%A real-time radar pulse signal detection method is proposed. Firstly, two input data sequence are got by a demultiplexer, then taking conjugate and one point delay operation is applied to one of them. Secondly, multiplying these two sequence, accumulating the multiply result and outputting its complex magnitude. Finally, after comparing with a threshold, the detection result can be gained. Since the detection algorithm is very simple, the hardware can be designed using a small a-mount of circuitry, consisting of only 1 complex multiplier, 1 complex adder, 1 complex subtracter and 1 complex magnitude calculator. Therefore, it can realize the high-speed detection of target signals by constructing a pipeline architecture. The start-point estimation error is derived based upon first order purterbation analysis, and then the performance boundary of this method is presented. Simulation results confirm the derivation. Comparing with other radar pulse signal detection method, this proposed algorithm leads to clear and neat structure, good real-time and suitable for hardware implementation.

  7. Detection of Noise in Composite Step Signal Pattern by Visualizing Signal Waveforms

    Directory of Open Access Journals (Sweden)

    Chaman Verma

    2018-03-01

    Full Text Available The Step Composite Signals is the combination of vital informative signals that are compressed and coded to produce a predefined test image on a display device. It carries the desired sequence of information from source to destination. This information may be transmitted as digital signal, video information or data signal required as an input for the destination module. For testing of display panels, Composite Test Signals are the most important attribute of test signal transmission system. In the current research paper we present an approach for the noise detection in Composite Step Signal by analysing Composite Step Signal waveforms. The analysis of the signal waveforms reveals that the noise affected components of the signal and subsequently noise reduction process is initiated which targets noisy signal component only. Thus the quality of signal is not compromised during noise reduction process.

  8. Detecting impact signal in mechanical fault diagnosis under chaotic and Gaussian background noise

    Science.gov (United States)

    Hu, Jinfeng; Duan, Jie; Chen, Zhuo; Li, Huiyong; Xie, Julan; Chen, Hanwen

    2018-01-01

    In actual fault diagnosis, useful information is often submerged in heavy noise, and the feature information is difficult to extract. Traditional methods, such like stochastic resonance (SR), which using noise to enhance weak signals instead of suppressing noise, failed in chaotic background. Neural network, which use reference sequence to estimate and reconstruct the background noise, failed in white Gaussian noise. To solve these problems, a novel weak signal detection method aimed at the problem of detecting impact signal buried under heavy chaotic and Gaussian background noise is proposed. First, the proposed method obtains the virtual reference sequence by constructing the Hankel data matrix. Then an M-order optimal FIR filter is designed, which can minimize the output power of background noise and pass the weak periodic signal undistorted. Finally, detection and reconstruction of the weak periodic signal are achieved from the output SBNR (signal to background noise ratio). The simulation shows, compared with the stochastic resonance (SR) method, the proposed method can detect the weak periodic signal in chaotic noise background while stochastic resonance (SR) method cannot. Compared with the neural network method, (a) the proposed method does not need a reference sequence while neural network method needs one; (b) the proposed method can detect the weak periodic signal in white Gaussian noise background while the neural network method fails, in chaotic noise background, the proposed method can detect the weak periodic signal under a lower SBNR (about 8-17 dB lower) than the neural network method; (c) the proposed method can reconstruct the weak periodic signal precisely.

  9. Signal Detection with Criterion Noise: Applications to Recognition Memory

    Science.gov (United States)

    Benjamin, Aaron S.; Diaz, Michael; Wee, Serena

    2009-01-01

    A tacit but fundamental assumption of the theory of signal detection is that criterion placement is a noise-free process. This article challenges that assumption on theoretical and empirical grounds and presents the noisy decision theory of signal detection (ND-TSD). Generalized equations for the isosensitivity function and for measures of…

  10. A Signal Detection Theory Approach to Evaluating Oculometer Data Quality

    Science.gov (United States)

    Latorella, Kara; Lynn, William, III; Barry, John S.; Kelly, Lon; Shih, Ming-Yun

    2013-01-01

    Currently, data quality is described in terms of spatial and temporal accuracy and precision [Holmqvist et al. in press]. While this approach provides precise errors in pixels, or visual angle, often experiments are more concerned with whether subjects'points of gaze can be said to be reliable with respect to experimentally-relevant areas of interest. This paper proposes a method to characterize oculometer data quality using Signal Detection Theory (SDT) [Marcum 1947]. SDT classification results in four cases: Hit (correct report of a signal), Miss (failure to report a ), False Alarm (a signal falsely reported), Correct Reject (absence of a signal correctly reported). A technique is proposed where subjects' are directed to look at points in and outside of an AOI, and the resulting Points of Gaze (POG) are classified as Hits (points known to be internal to an AOI are classified as such), Misses (AOI points are not indicated as such), False Alarms (points external to AOIs are indicated as in the AOI), or Correct Rejects (points external to the AOI are indicated as such). SDT metrics describe performance in terms of discriminability, sensitivity, and specificity. This paper presentation will provide the procedure for conducting this assessment and an example of data collected for AOIs in a simulated flightdeck environment.

  11. An attempt to detect the greenhouse-gas signal in a transient GCM simulation

    International Nuclear Information System (INIS)

    Barnett, T.P.

    1990-01-01

    Results from the GISS model forced by transient greenhouse-gas (GHG) increases are used to demonstrate methods of detecting the theoretically predicted GHG signal. The signal predicted to occur in the surface temperature of the world's ocean since 1958 is not found in the observations but this is not surprising since the signal was small in the first place. The main result of the study is to demonstrate many of the key issues/difficulties that attend the detection problem

  12. Spices, irradiation and detection methods

    International Nuclear Information System (INIS)

    Sjoeberg, A.M.; Manninen, M.

    1991-01-01

    This paper is about microbiological aspects of spices and microbiological methods to detect irradiated food. The proposed method is a combination of the Direct Epifluorescence Filter Technique (DEFT) and the Aerobic Plate Count (APC). The evidence for irradiation of spices is based on the demonstration of a higher DEFT count than the APC. The principle was first tested in our earlier investigation in the detection of irradiation of whole spices. The combined DEFT+APC procedure was found to give a fairly reliable indication of whether or not a whole spice sample had been irradiated. The results are given (8 figs, 22 refs)

  13. Detection and Localization of Random Signals

    DEFF Research Database (Denmark)

    Sporring, Jon; Olsen, Niels Holm; Nielsen, Mads

    2003-01-01

    filtering techniques. It is therefore interesting to extend the application to objects with many but small degrees of freedom in their geometry. These geometric variations deteriorate the linear correlation signal, both regarding its strength and localization with multiple peaks from a single object...

  14. Detection of anomalous signals in temporally correlated data (Invited)

    Science.gov (United States)

    Langbein, J. O.

    2010-12-01

    Detection of transient tectonic signals in data obtained from large geodetic networks requires the ability to detect signals that are both temporally and spatially coherent. In this report I will describe a modification to an existing method that estimates both the coefficients of temporally correlated noise model and an efficient filter based on the noise model. This filter, when applied to the original time-series, effectively whitens (or flattens) the power spectrum. The filtered data provide the means to calculate running averages which are then used to detect deviations from the background trends. For large networks, time-series of signal-to-noise ratio (SNR) can be easily constructed since, by filtering, each of the original time-series has been transformed into one that is closer to having a Gaussian distribution with a variance of 1.0. Anomalous intervals may be identified by counting the number of GPS sites for which the SNR exceeds a specified value. For example, during one time interval, if there were 5 out of 20 time-series with SNR>2, this would be considered anomalous; typically, one would expect at 95% confidence that there would be at least 1 out of 20 time-series with an SNR>2. For time intervals with an anomalously large number of high SNR, the spatial distribution of the SNR is mapped to identify the location of the anomalous signal(s) and their degree of spatial clustering. Estimating the filter that should be used to whiten the data requires modification of the existing methods that employ maximum likelihood estimation to determine the temporal covariance of the data. In these methods, it is assumed that the noise components in the data are a combination of white, flicker and random-walk processes and that they are derived from three different and independent sources. Instead, in this new method, the covariance matrix is constructed assuming that only one source is responsible for the noise and that source can be represented as a white

  15. Detection methods for irradiated foods

    International Nuclear Information System (INIS)

    Dyakova, A.; Tsvetkova, E.; Nikolova, R.

    2005-01-01

    In connection with the ongoing world application of irradiation as a technology in Food industry for increasing food safety, it became a need for methods of identification of irradiation. It was required to control international trade of irradiated foods, because of the certain that legally imposed food laws are not violated; supervise correct labeling; avoid multiple irradiation. Physical, chemical and biological methods for detection of irradiated foods as well principle that are based, are introducing in this summary

  16. Adjunct methods for caries detection

    DEFF Research Database (Denmark)

    Twetman, Svante; Axelsson, Susanna Bihari; Dahlén, Gunnar

    2012-01-01

    Abstract Objective. To assess the diagnostic accuracy of adjunct methods used to detect and quantify dental caries. Study design. A systematic literature search for relevant papers was conducted with pre-determined inclusion and exclusion criteria. Abstracts and full text articles were assessed...

  17. Continuous emotion detection using EEG signals and facial expressions

    NARCIS (Netherlands)

    Soleymani, Mohammad; Asghari-Esfeden, Sadjad; Pantic, Maja; Fu, Yun

    Emotions play an important role in how we select and consume multimedia. Recent advances on affect detection are focused on detecting emotions continuously. In this paper, for the first time, we continuously detect valence from electroencephalogram (EEG) signals and facial expressions in response to

  18. Enhancement of crack detection in stud bolts of nuclear reactor by ultrasonic signal processing technique

    International Nuclear Information System (INIS)

    Lee, J.H.; Oh, W.D.; Choi, S.W.; Park, M.H.

    2004-01-01

    'Full-text:' The stud bolts is one of the most critical parts for safety of reactor vessels in the nuclear power plants. However, in the application of ultrasonic technique for crack detection in stud bolt, some difficulties encountered are classification of crack signal from the signals reflected from threads part in stud bolt. In this study, shadow effect technique combined with new signal processing method is Investigated to enhance the detectability of small crack initiated from root of thread in stud bolt. The key idea of signal processing is based on the fact that the shape of waveforms from the threads is uniform since the shape of the threads in a bolt is same. If some cracks exist in the thread, the flaw signals are different to the reference signals. It is demonstrated that the small flaws are efficiently detected by novel ultrasonic technique combined with this new signal processing concept. (author)

  19. Electromagnetic Methods of Lightning Detection

    Science.gov (United States)

    Rakov, V. A.

    2013-11-01

    Both cloud-to-ground and cloud lightning discharges involve a number of processes that produce electromagnetic field signatures in different regions of the spectrum. Salient characteristics of measured wideband electric and magnetic fields generated by various lightning processes at distances ranging from tens to a few hundreds of kilometers (when at least the initial part of the signal is essentially radiation while being not influenced by ionospheric reflections) are reviewed. An overview of the various lightning locating techniques, including magnetic direction finding, time-of-arrival technique, and interferometry, is given. Lightning location on global scale, when radio-frequency electromagnetic signals are dominated by ionospheric reflections, is also considered. Lightning locating system performance characteristics, including flash and stroke detection efficiencies, percentage of misclassified events, location accuracy, and peak current estimation errors, are discussed. Both cloud and cloud-to-ground flashes are considered. Representative examples of modern lightning locating systems are reviewed. Besides general characterization of each system, the available information on its performance characteristics is given with emphasis on those based on formal ground-truth studies published in the peer-reviewed literature.

  20. Balanced detection for self-mixing interferometry to improve signal-to-noise ratio

    Science.gov (United States)

    Zhao, Changming; Norgia, Michele; Li, Kun

    2018-01-01

    We apply balanced detection to self-mixing interferometry for displacement and vibration measurement, using two photodiodes for implementing a differential acquisition. The method is based on the phase opposition of the self-mixing signal measured between the two laser diode facet outputs. The balanced signal obtained by enlarging the self-mixing signal, also by canceling of the common-due noises mainly due to disturbances on laser supply and transimpedance amplifier. Experimental results demonstrate the signal-to-noise ratio significantly improves, with almost twice signals enhancement and more than half noise decreasing. This method allows for more robust, longer-distance measurement systems, especially using fringe-counting.

  1. Understanding driver behavior at grade crossings through signal detection theory.

    Science.gov (United States)

    2013-01-01

    This report uses signal detection theory (SDT) to model motorists decisionmaking strategies at grade crossings in order to understand the factors that influence such decisions and to establish a framework for evaluating the impact of proposed coun...

  2. Understanding driver behavior at grade crossings through signal detection theory.

    Science.gov (United States)

    2013-01-31

    This report uses signal detection theory (SDT) to model motorists decisionmaking strategies at grade crossings in order to understand the factors that influence such decisions and to establish a framework for evaluating the impact of proposed coun...

  3. Method of detecting failed fuels

    International Nuclear Information System (INIS)

    Ishizaki, Hideaki; Suzumura, Takeshi.

    1982-01-01

    Purpose: To enable the settlement of the temperature of an adequate filling high temperature pure water by detecting the outlet temperature of a high temperature pure water filling tube to a fuel assembly to control the heating of the pure water and detecting the failed fuel due to the sampling of the pure water. Method: A temperature sensor is provided at a water tube connected to a sipping cap for filling high temperature pure water to detect the temperature of the high temperature pure water at the outlet of the tube, and the temperature is confirmed by a temperature indicator. A heater is controlled on the basis of this confirmation, an adequate high temperature pure water is filled in the fuel assembly, and the pure water is replaced with coolant. Then, it is sampled to settle the adequate temperature of the high temperature coolant used for detecting the failure of the fuel assembly. As a result, the sipping effect does not decrease, and the failed fuel can be precisely detected. (Yoshihara, H.)

  4. Signal detection without finite-energy limits to quantum resolution

    OpenAIRE

    Luis Aina, Alfredo

    2013-01-01

    We show that there are extremely simple signal detection schemes where the finiteness of energy resources places no limit on the resolution. On the contrary, larger resolution can be obtained with lower energy. To this end the generator of the signal-dependent transformation encoding the signal information on the probe state must be different from the energy. We show that the larger the deviation of the probe state from being the minimum-uncertainty state, the better the resolution.

  5. The application of signal detection theory to optics

    Science.gov (United States)

    Helstrom, C. W.

    1972-01-01

    The role of measurements of noncommuting quantum observables is considered in the detection of signals and estimation of signal parameters by quantum receivers. The restoration of images focused on a photosensitive surface is discussed for data as numbers of photoelectrons ejected from various parts of the surface. The detection of an image formed on a photosensitive surface in the presence of background illumination for similar data is also considered.

  6. Signal Detection Framework Using Semantic Text Mining Techniques

    Science.gov (United States)

    Sudarsan, Sithu D.

    2009-01-01

    Signal detection is a challenging task for regulatory and intelligence agencies. Subject matter experts in those agencies analyze documents, generally containing narrative text in a time bound manner for signals by identification, evaluation and confirmation, leading to follow-up action e.g., recalling a defective product or public advisory for…

  7. Application of wavelet analysis to signal processing methods for eddy-current test

    International Nuclear Information System (INIS)

    Chen, G.; Yoneyama, H.; Yamaguchi, A.; Uesugi, N.

    1998-01-01

    This study deals with the application of wavelet analysis to detection and characterization of defects from eddy-current and ultrasonic testing signals of a low signal-to-noise ratio. Presented in this paper are the methods for processing eddy-current testing signals of heat exchanger tubes of a steam generator in a nuclear power plant. The results of processing eddy-current testing signals of tube testpieces with artificial flaws show that the flaw signals corrupted by noise and/or non-defect signals can be effectively detected and characterized by using the wavelet methods. (author)

  8. Adaptive endpoint detection of seismic signal based on auto-correlated function

    International Nuclear Information System (INIS)

    Fan Wanchun; Shi Ren

    2001-01-01

    Based on the analysis of auto-correlation function, the notion of the distance between auto-correlation function was quoted, and the characterization of the noise and the signal with noise were discussed by using the distance. Then, the method of auto- adaptable endpoint detection of seismic signal based on auto-correlated similarity was summed up. The steps of implementation and determining of the thresholds were presented in detail. The experimental results that were compared with the methods based on artificial detecting show that this method has higher sensitivity even in a low signal with noise ratio circumstance

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

    Directory of Open Access Journals (Sweden)

    Zhang Haijian

    2010-01-01

    Full Text Available 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.

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

    National Research Council Canada - National Science Library

    Nolte, Loren

    2002-01-01

    The hypothesis is that one can use signal detection theory to improve the performance in detecting tumors in the breast by using this theory to develop task-oriented information processing techniques...

  11. Adaptive Fourier decomposition based R-peak detection for noisy ECG Signals.

    Science.gov (United States)

    Ze Wang; Chi Man Wong; Feng Wan

    2017-07-01

    An adaptive Fourier decomposition (AFD) based R-peak detection method is proposed for noisy ECG signals. Although lots of QRS detection methods have been proposed in literature, most detection methods require high signal quality. The proposed method extracts the R waves from the energy domain using the AFD and determines the R-peak locations based on the key decomposition parameters, achieving the denoising and the R-peak detection at the same time. Validated by clinical ECG signals in the MIT-BIH Arrhythmia Database, the proposed method shows better performance than the Pan-Tompkin (PT) algorithm in both situations of a native PT and the PT with a denoising process.

  12. Method of detecting irradiated pepper

    International Nuclear Information System (INIS)

    Doumaru, Takaaki; Furuta, Masakazu; Katayama, Tadashi; Toratani, Hirokazu; Takeda, Atsuhiko

    1989-01-01

    Spices represented by pepper are generally contaminated by microorganisms, and for using them as foodstuffs, some sterilizing treatment is indispensable. However, heating is not suitable to spices, accordingly ethylene oxide gas sterilization has been inevitably carried out, but its carcinogenic property is a problem. Food irradiation is the technology for killing microorganisms and noxious insects which cause the rotting and spoiling of foods and preventing the germination, which is an energy-conserving method without the fear of residual chemicals, therefore, it is most suitable to the sterilization of spices. In the irradiation of lower than 10 kGy, the toxicity test is not required for any food, and the irradiation of spices is permitted in 20 countries. However, in order to establish the international distribution organization for irradiated foods, the PR to consumers and the development of the means of detecting irradiation are the important subjects. The authors used pepper, and examined whether the hydrogen generated by irradiation remains in seeds and it can be detected or not. The experimental method and the results are reported. From the samples without irradiation, hydrogen was scarcely detected. The quantity of hydrogen generated was proportional to dose. The measuring instrument is only a gas chromatograph. (K.I.)

  13. Seismic Methods of Infrasonic Signal Detection

    Science.gov (United States)

    1982-09-30

    Volcanol. & Geothermal Res., 6, pp. 139-164. Le Guern, F., Bernard, A., and Chevrier, R. M., (1980), Soufriere of Guadeloupe 1976-1977 eruption-mass...eruptions-V. Obser vations of plume dynamics during the 1979 Soufriere eruption, St. Vincent, Geophys. J. R. Astr. Soc., 69, pp. 551-570. -9b- TR 82-5...volcanic event, Bull. Volcanol., 27, pp. 5-24. Le Guern, F., Bernard, A., and Chevrier, R. M., (1980), Soufriere of Guadeloupe 1976-1977 eruption-mass

  14. Sensitivity of Quantitative Signal Detection in Regards to Pharmacological Neuroenhancement

    Directory of Open Access Journals (Sweden)

    Maximilian Gahr

    2017-01-01

    Full Text Available Pharmacological neuroenhancement (PNE is a form of abuse and has not yet been addressed by methods of pharmacovigilance. In the present study, we tested if quantitative signal detection may be sensitive in regards to PNE. We evaluated the risk of drug abuse and dependence (DAAD related to substances that are known to be used for PNE and divided this group into agents with (methylphenidate and without a known abuse potential outside the field of PNE (atomoxetine, modafinil, acetylcholine esterase inhibitors, and memantine. Reporting odds ratios (RORs were calculated using a case/non-case approach based on global and country-specific drug safety data from the Uppsala Monitoring Centre (UMC. Both control substances (diazepam and lorazepam and methylphenidate were statistically associated with DAAD in all datasets (except methylphenidate in Italy. Modafinil was associated with DAAD in the total dataset (ROR, 2.7 (95% confidence interval (CI, 2.2–3.3, Germany (ROR, 4.6 (95% CI, 1.8–11.5, and the USA (ROR, 2.0 (95% CI, 1.6–2.5. Atomoxetine was associated with DAAD in the total dataset (ROR, 1.3 (95% CI, 1.2–1.5 and in the UK (ROR, 3.3 (95% CI, 1.8–6.1. Apart from memantine, which was associated with DAAD in Germany (ROR, 1.8 (95% CI, 1.0–3.2, no other antidementia drug was associated with DAAD. Quantitative signal detection is suitable to detect agents with a risk for DAAD. Its sensitivity regarding PNE is limited, although atomoxetine and modafinil, which do not have a known abuse potential outside PNE, and no antidementia drugs, whose use in PNE is presumably low, were associated with DAAD in our analysis.

  15. Double Solvent Sensing Method for Improving Sensitivity and Accuracy of Hg(II) Detection Based on Different Signal Transduction of a Tetrazine-Functionalized Pillared Metal-Organic Framework.

    Science.gov (United States)

    Razavi, Sayed Ali Akbar; Masoomi, Mohammad Yaser; Morsali, Ali

    2017-08-21

    To design a robust, π-conjugated, low-cost, and easy to synthesize metal-organic framework (MOF) for cation sensing by the photoluminescence (PL) method, 4,4'-oxybis(benzoic acid) (H 2 OBA) has been used in combination with 3,6-di(pyridin-4-yl)-1,2,4,5-tetrazine (DPT) as a tetrazine-functionalized spacer to construct [Zn(OBA)(DPT) 0.5 ]·DMF (TMU-34(-2H)). The tetrazine motif is a π-conjugated, water-soluble/stable fluorophore with relatively weak σ-donating Lewis basic sites. These characteristics of tetrazine make TMU-34(-2H) a good candidate for cation sensing. Because of hydrogen bonding between tetrazine moieties and water molecules, TMU-34(-2H) shows different PL emissions in water and acetonitrile. Cation sensing in these two solvents revealed that TMU-34(-2H) can selectively detect Hg 2+ in water (by 243% enhancement) and in acetonitrile (by 90% quenching). The contribution of electron-donating/accepting characteristics along with solvation effects on secondary interactions of the tetrazine motifs inside the TMU-34(-2H) framework results in different signal transductions. Improved sensitivity and accuracy of detection were obtained using the double solvent sensing method (DSSM), in which different signal transductions of TMU-34(-2H) in water and acetonitrile were combined simultaneously to construct a double solvent sensing curve and formulate a sensitivity factor. Calculation of sensitivity factors for all of the tested cations demonstrated that it is possible to detect Hg 2+ by DSSM with ultrahigh sensitivity. Such a tremendous distinction in the Hg 2+ sensitivity factor is visualizable in the double solvent sensing curve. Thus, by application of DSSM instead of one-dimensional sensing, the interfering effects of other cations are completely eliminated and the sensitivity toward Hg(II) is highly improved. Strong interactions between Hg 2+ and the nitrogen atoms of the tetrazine groups along with easy accessibility of Hg 2+ to the tetrazine groups lead

  16. Unsupervised Event Characterization and Detection in Multichannel Signals: An EEG application

    Directory of Open Access Journals (Sweden)

    Angel Mur

    2016-04-01

    Full Text Available In this paper, we propose a new unsupervised method to automatically characterize and detect events in multichannel signals. This method is used to identify artifacts in electroencephalogram (EEG recordings of brain activity. The proposed algorithm has been evaluated and compared with a supervised method. To this end an example of the performance of the algorithm to detect artifacts is shown. The results show that although both methods obtain similar classification, the proposed method allows detecting events without training data and can also be applied in signals whose events are unknown a priori. Furthermore, the proposed method provides an optimal window whereby an optimal detection and characterization of events is found. The detection of events can be applied in real-time.

  17. On jet substructure methods for signal jets

    Energy Technology Data Exchange (ETDEWEB)

    Dasgupta, Mrinal [Consortium for Fundamental Physics, School of Physics & Astronomy, University of Manchester,Oxford Road, Manchester M13 9PL (United Kingdom); Powling, Alexander [School of Physics & Astronomy, University of Manchester,Oxford Road, Manchester M13 9PL (United Kingdom); Siodmok, Andrzej [Institute of Nuclear Physics, Polish Academy of Sciences,ul. Radzikowskiego 152, 31-342 Kraków (Poland); CERN, PH-TH,CH-1211 Geneva 23 (Switzerland)

    2015-08-17

    We carry out simple analytical calculations and Monte Carlo studies to better understand the impact of QCD radiation on some well-known jet substructure methods for jets arising from the decay of boosted Higgs bosons. Understanding differences between taggers for these signal jets assumes particular significance in situations where they perform similarly on QCD background jets. As an explicit example of this we compare the Y-splitter method to the more recently proposed Y-pruning technique. We demonstrate how the insight we gain can be used to significantly improve the performance of Y-splitter by combining it with trimming and show that this combination outperforms the other taggers studied here, at high p{sub T}. We also make analytical estimates for optimal parameter values, for a range of methods and compare to results from Monte Carlo studies.

  18. Compressive Detection Using Sub-Nyquist Radars for Sparse Signals

    Directory of Open Access Journals (Sweden)

    Ying Sun

    2016-01-01

    Full Text Available This paper investigates the compression detection problem using sub-Nyquist radars, which is well suited to the scenario of high bandwidths in real-time processing because it would significantly reduce the computational burden and save power consumption and computation time. A compressive generalized likelihood ratio test (GLRT detector for sparse signals is proposed for sub-Nyquist radars without ever reconstructing the signal involved. The performance of the compressive GLRT detector is analyzed and the theoretical bounds are presented. The compressive GLRT detection performance of sub-Nyquist radars is also compared to the traditional GLRT detection performance of conventional radars, which employ traditional analog-to-digital conversion (ADC at Nyquist sampling rates. Simulation results demonstrate that the former can perform almost as well as the latter with a very small fraction of the number of measurements required by traditional detection in relatively high signal-to-noise ratio (SNR cases.

  19. Method for traceable measurement of LTE signals

    Science.gov (United States)

    Sunder Dash, Soumya; Pythoud, Frederic; Leuchtmann, Pascal; Leuthold, Juerg

    2018-04-01

    This contribution presents a reference setup to measure the power of the cell-specific resource elements present in downlink long term evolution (LTE) signals in a way that the measurements are traceable to the international system of units. This setup can be used to calibrate the LTE code-selective field probes that are used to measure the radiation of base stations for mobile telephony. It can also be used to calibrate LTE signal generators and receivers. The method is based on traceable scope measurements performed directly at the output of a measuring antenna. It implements offline digital signal processing demodulation algorithms that consider the digital down-conversion, timing synchronization, frequency synchronization, phase synchronization and robust LTE cell identification to produce the downlink time-frequency LTE grid. Experimental results on conducted test scenarios, both single-input-single-output and multiple-input-multiple-output antenna configuration, show promising results confirming measurement uncertainties of the order of 0.05 dB with a coverage factor of 2.

  20. OPTIMAL SIGNAL PROCESSING METHODS IN GPR

    Directory of Open Access Journals (Sweden)

    Saeid Karamzadeh

    2014-01-01

    Full Text Available In the past three decades, a lot of various applications of Ground Penetrating Radar (GPR took place in real life. There are important challenges of this radar in civil applications and also in military applications. In this paper, the fundamentals of GPR systems will be covered and three important signal processing methods (Wavelet Transform, Matched Filter and Hilbert Huang will be compared to each other in order to get most accurate information about objects which are in subsurface or behind the wall.

  1. Radiation sensitive area detection device and method

    Science.gov (United States)

    Carter, Daniel C. (Inventor); Hecht, Diana L. (Inventor); Witherow, William K. (Inventor)

    1991-01-01

    A radiation sensitive area detection device for use in conjunction with an X ray, ultraviolet or other radiation source is provided which comprises a phosphor containing film which releases a stored diffraction pattern image in response to incoming light or other electromagnetic wave. A light source such as a helium-neon laser, an optical fiber capable of directing light from the laser source onto the phosphor film and also capable of channelling the fluoresced light from the phosphor film to an integrating sphere which directs the light to a signal processing means including a light receiving means such as a photomultiplier tube. The signal processing means allows translation of the fluoresced light in order to detect the original pattern caused by the diffraction of the radiation by the original sample. The optical fiber is retained directly in front of the phosphor screen by a thin metal holder which moves up and down across the phosphor screen and which features a replaceable pinhole which allows easy adjustment of the resolution of the light projected onto the phosphor film. The device produces near real time images with high spatial resolution and without the distortion that accompanies prior art devices employing photomultiplier tubes. A method is also provided for carrying out radiation area detection using the device of the invention.

  2. Resonance detection of EEG signals using two-layer wavelet analysis

    International Nuclear Information System (INIS)

    Abdallah, H. M; Odeh, F.S.

    2000-01-01

    This paper presents the hybrid quadrature mirror filter (HQMF) algorithm applied to the electroencephalogram (EEG) signal during mental activity. The information contents of this signal, i.e., its medical diagnosis, lie in its power spectral density (PSD). The HQMF algorithm is a modified technique that is based on the shape and the details of the signal. If applied efficiently, the HQMF algorithm will produce much better results than conventional wavelet methods in detecting (diagnosing) the information of the EEG signal from its PSD. This technique is applicable not only to EEG signals, but is highly recommended to compression analysis and de noising techniques. (authors). 16 refs., 9 figs

  3. Mine detection using SF-GPR: A signal processing approach for resolution enhancement and clutter reduction

    DEFF Research Database (Denmark)

    Karlsen, Brian; Jakobsen, Kaj Bjarne; Larsen, Jan

    2001-01-01

    Proper clutter reduction is essential for Ground Penetrating Radar data since low signal-to-clutter ratio prevent correct detection of mine objects. A signal processing approach for resolution enhancement and clutter reduction used on Stepped-Frequency Ground Penetrating Radar (SF-GPR) data is pr....... The clutter reduction method is based on basis function decomposition of the SF-GPR time-series from which the clutter and the signal are separated....

  4. Development Of Signal Detection For Radar Navigation System

    Directory of Open Access Journals (Sweden)

    Theingi Win Hlaing

    2017-09-01

    Full Text Available This paper aims to evaluate the performance of target detection in the presence of sea clutter. Radar detection of a background of unwanted clutter due to echoes from sea clutter or land is a problem of interest in the radar field. Radar detector has been developed by assuming the radar clutter is Gaussian distributed. However as technology emerges the radar distribution is seen to deviates from the Gaussian assumption. Thus detectors designs based on Gaussian assumption are no longer optimum for detection in non-Gaussian nature. The theory of target detection in Gaussian distributed clutter has been well established and the closed form of the detection performances can be easily obtained. However that is not the case in non-Gaussian clutter distributions. The operation of radar detection is determined by radar detection theory with different types of Swerling target models such as Swerling I II III IV and V. By using MATLAB these signal detection techniques are developed.

  5. Developing a reliable method for signal wire attachment : [research results].

    Science.gov (United States)

    2013-03-01

    Railroad signaling systems detect trains on the track, identify track fractures, prevent derailments, and alert signal crossing stations when trains approach. These systems are vital to safe train operation; therefore, each component of this system h...

  6. Detection of non-stationary leak signals at NPP primary circuit by cross-correlation analysis

    International Nuclear Information System (INIS)

    Shimanskij, S.B.

    2007-01-01

    A leak-detection system employing high-temperature microphones has been developed for the RBMK and ATR (Japan) reactors. Further improvement of the system focused on using cross-correlation analysis of the spectral components of the signal to detect a small leak at an early stage of development. Since envelope processes are less affected by distortions than are wave processes, they give a higher-degree of correlation and can be used to detect leaks with lower signal-noise ratios. Many simulation tests performed at nuclear power plants have shown that the proposed methods can be used to detect and find the location of a small leak [ru

  7. Reliably detectable flaw size for NDE methods that use calibration

    Science.gov (United States)

    Koshti, Ajay M.

    2017-04-01

    Probability of detection (POD) analysis is used in assessing reliably detectable flaw size in nondestructive evaluation (NDE). MIL-HDBK-1823 and associated mh18232 POD software gives most common methods of POD analysis. In this paper, POD analysis is applied to an NDE method, such as eddy current testing, where calibration is used. NDE calibration standards have known size artificial flaws such as electro-discharge machined (EDM) notches and flat bottom hole (FBH) reflectors which are used to set instrument sensitivity for detection of real flaws. Real flaws such as cracks and crack-like flaws are desired to be detected using these NDE methods. A reliably detectable crack size is required for safe life analysis of fracture critical parts. Therefore, it is important to correlate signal responses from real flaws with signal responses form artificial flaws used in calibration process to determine reliably detectable flaw size.

  8. Integrated Giant Magnetoresistance Technology for Approachable Weak Biomagnetic Signal Detections.

    Science.gov (United States)

    Shen, Hui-Min; Hu, Liang; Fu, Xin

    2018-01-07

    With the extensive applications of biomagnetic signals derived from active biological tissue in both clinical diagnoses and human-computer-interaction, there is an increasing need for approachable weak biomagnetic sensing technology. The inherent merits of giant magnetoresistance (GMR) and its high integration with multiple technologies makes it possible to detect weak biomagnetic signals with micron-sized, non-cooled and low-cost sensors, considering that the magnetic field intensity attenuates rapidly with distance. This paper focuses on the state-of-art in integrated GMR technology for approachable biomagnetic sensing from the perspective of discipline fusion between them. The progress in integrated GMR to overcome the challenges in weak biomagnetic signal detection towards high resolution portable applications is addressed. The various strategies for 1/ f noise reduction and sensitivity enhancement in integrated GMR technology for sub-pT biomagnetic signal recording are discussed. In this paper, we review the developments of integrated GMR technology for in vivo/vitro biomagnetic source imaging and demonstrate how integrated GMR can be utilized for biomagnetic field detection. Since the field sensitivity of integrated GMR technology is being pushed to fT/Hz 0.5 with the focused efforts, it is believed that the potential of integrated GMR technology will make it preferred choice in weak biomagnetic signal detection in the future.

  9. Advanced radar detection schemes under mismatched signal models

    CERN Document Server

    Bandiera, Francesco

    2009-01-01

    Adaptive detection of signals embedded in correlated Gaussian noise has been an active field of research in the last decades. This topic is important in many areas of signal processing such as, just to give some examples, radar, sonar, communications, and hyperspectral imaging. Most of the existing adaptive algorithms have been designed following the lead of the derivation of Kelly's detector which assumes perfect knowledge of the target steering vector. However, in realistic scenarios, mismatches are likely to occur due to both environmental and instrumental factors. When a mismatched signal

  10. Selection of the signal synchronization method in software GPS receivers

    Directory of Open Access Journals (Sweden)

    Vlada S. Sokolović

    2011-04-01

    Full Text Available Introduction This paper presents a critical analysis of the signal processing flow carried out in a software GPS receiver and a critical comparison of different architectures for signal processing within the GPS receiver. A model of software receivers is shown. Based on the displayed model, a receiver has been realized in the MATLAB software package, in which the simulations of signal processing were carried out. The aim of this paper is to demonstrate the advantages and disadvantages of different methods of the synchronization of signals in the receiver, and to propose a solution acceptable for possible implementation. The signal processing flow was observed from the input circuit to the extraction of the bits of the navigation message. The entire signal processing was performed on the L1 signal and the data collected by the input circuit SE4110. A radio signal from the satellite was accepted with the input circuit, filtered and translated into a digital form. The input circuit ends with the hardware of the receiver. A digital signal from the input circuit is brought into the PC Pentium 4 (AMD 3000 + where the receiver is realized in Matlab. Model of software GPS receiver The first level of processing is signal acquisition. Signal acquisition was realized using the cyclic convolution. The acquisition process was carried out by measuring signals from satellites, and these parameters are passed to the next level of processing. The next level was done by monitoring the synchronization signal and extracting the navigation message bits. On the basis of the detection of the navigation message the receiver calculates the position of a satellite and then, based on the position of the satellite, its own position. Tracking of GPS signal synchronization In order to select the most acceptable method of signal synchronization in the receiver, different methods of signal synchronization are compared. The early-late-DLL (Delay Lock Loop, TDL (Tau Dither Loop

  11. Method to detect biological particles

    International Nuclear Information System (INIS)

    Giaever, I.

    1976-01-01

    A medical-diagnostic method to detect immunological as well as other specific reactions is described. According to the invention, first reactive particles (e.g. antibodies) are adsorbed on the surface of a solid, non-reactive substrate. The coated substrate is subjected to a solution which one assumes to contain the second biological particles (e.g. antigens) which are specific to the first and form complexes with these. A preferential radioactive labelling (e.g. with iodine 125) of the second biological particle is then directly or indirectly carried out. Clearage follows labelling in order to separate the second biological particles from the first ones. A specific splitting agent can selectively break the bond of both types of particle. The splitting agent solution is finally separated off and its content is investigated for the presence of labelling. (VJ) [de

  12. Pipeline Defects Detection Using MFL Signals and Self Quotient Image

    International Nuclear Information System (INIS)

    Kim, Min Ho; Choi, Doo Hyun; Rho, Yong Woo

    2010-01-01

    Defects positioning of underground gas pipelines using MFL(magnetic flux leakage) inspection which is one of non-destructive evaluation techniques is proposed in this paper. MFL signals acquired from MFL PIG(pipeline inspection gauge) have nonlinearity and distortion caused by various extemal disturbances. SQI(self quotient image), a compensation technique for nonlinearity and distortion of MFL signal, is used to correct positioning of pipeline defects. Through the experiments using artificial defects carved in the KOGAS pipeline simulation facility, it is found that the performance of proposed defect detection is greatly improved compared to that of the conventional DCT(discrete cosine transform) coefficients based detection

  13. Cophylogenetic signal is detectable in pollination interactions across ecological scales.

    Science.gov (United States)

    Hutchinson, Matthew C; Cagua, Edgar Fernando; Stouffer, Daniel B

    2017-10-01

    That evolutionary history can influence the way that species interact is a basic tenet of evolutionary ecology. However, when the role of evolution in determining ecological interactions is investigated, focus typically centers on just one side of the interaction. A cophylogenetic signal, the congruence of evolutionary history across both sides of an ecological interaction, extends these previous explorations and provides a more complete picture of how evolutionary patterns influence the way species interact. To date, cophylogenetic signal has most typically been studied in interactions that occur between fine taxonomic clades that show high intimacy. In this study, we took an alternative approach and made an exhaustive assessment of cophylogeny in pollination interactions. To do so, we assessed the strength of cophylogenetic signal at four distinct scales of pollination interaction: (1) across plant-pollinator associations globally, (2) in local pollination communities, (3) within the modular structure of those communities, and (4) in individual modules. We did so using a globally distributed dataset comprised of 54 pollination networks, over 4000 species, and over 12,000 interactions. Within these data, we detected cophylogenetic signal at all four scales. Cophylogenetic signal was found at the level of plant-pollinator interactions on a global scale and in the majority of pollination communities. At the scale defined by the modular structure within those communities, however, we observed a much weaker cophylogenetic signal. Cophylogenetic signal was detectable in a significant proportion of individual modules and most typically when within-module phylogenetic diversity was low. In sum, the detection of cophylogenetic signal in pollination interactions across scales provides a new dimension to the story of how past evolution shapes extant pollinator-angiosperm interactions. © 2017 by the Ecological Society of America.

  14. Three-dimensional image signals: processing methods

    Science.gov (United States)

    Schiopu, Paul; Manea, Adrian; Craciun, Anca-Ileana; Craciun, Alexandru

    2010-11-01

    Over the years extensive studies have been carried out to apply coherent optics methods in real-time processing, communications and transmission image. This is especially true when a large amount of information needs to be processed, e.g., in high-resolution imaging. The recent progress in data-processing networks and communication systems has considerably increased the capacity of information exchange. We describe the results of literature investigation research of processing methods for the signals of the three-dimensional images. All commercially available 3D technologies today are based on stereoscopic viewing. 3D technology was once the exclusive domain of skilled computer-graphics developers with high-end machines and software. The images capture from the advanced 3D digital camera can be displayed onto screen of the 3D digital viewer with/ without special glasses. For this is needed considerable processing power and memory to create and render the complex mix of colors, textures, and virtual lighting and perspective necessary to make figures appear three-dimensional. Also, using a standard digital camera and a technique called phase-shift interferometry we can capture "digital holograms." These are holograms that can be stored on computer and transmitted over conventional networks. We present some research methods to process "digital holograms" for the Internet transmission and results.

  15. Compressive Sensing of Roller Bearing Faults via Harmonic Detection from Under-Sampled Vibration Signals.

    Science.gov (United States)

    Tang, Gang; Hou, Wei; Wang, Huaqing; Luo, Ganggang; Ma, Jianwei

    2015-10-09

    The Shannon sampling principle requires substantial amounts of data to ensure the accuracy of on-line monitoring of roller bearing fault signals. Challenges are often encountered as a result of the cumbersome data monitoring, thus a novel method focused on compressed vibration signals for detecting roller bearing faults is developed in this study. Considering that harmonics often represent the fault characteristic frequencies in vibration signals, a compressive sensing frame of characteristic harmonics is proposed to detect bearing faults. A compressed vibration signal is first acquired from a sensing matrix with information preserved through a well-designed sampling strategy. A reconstruction process of the under-sampled vibration signal is then pursued as attempts are conducted to detect the characteristic harmonics from sparse measurements through a compressive matching pursuit strategy. In the proposed method bearing fault features depend on the existence of characteristic harmonics, as typically detected directly from compressed data far before reconstruction completion. The process of sampling and detection may then be performed simultaneously without complete recovery of the under-sampled signals. The effectiveness of the proposed method is validated by simulations and experiments.

  16. Evaluation of blind signal separation methods

    NARCIS (Netherlands)

    Schobben, D.W.E.; Torkkola, K.; Smaragdis, P.

    1999-01-01

    Recently many new Blind Signal Separation BSS algorithms have been introduced Authors evaluate the performance of their algorithms in various ways Among these are speech recognition rates plots of separated signals plots of cascaded mixingunmixing impulse responses and signal to noise ratios Clearly

  17. RMOD: a tool for regulatory motif detection in signaling network.

    Directory of Open Access Journals (Sweden)

    Jinki Kim

    Full Text Available Regulatory motifs are patterns of activation and inhibition that appear repeatedly in various signaling networks and that show specific regulatory properties. However, the network structures of regulatory motifs are highly diverse and complex, rendering their identification difficult. Here, we present a RMOD, a web-based system for the identification of regulatory motifs and their properties in signaling networks. RMOD finds various network structures of regulatory motifs by compressing the signaling network and detecting the compressed forms of regulatory motifs. To apply it into a large-scale signaling network, it adopts a new subgraph search algorithm using a novel data structure called path-tree, which is a tree structure composed of isomorphic graphs of query regulatory motifs. This algorithm was evaluated using various sizes of signaling networks generated from the integration of various human signaling pathways and it showed that the speed and scalability of this algorithm outperforms those of other algorithms. RMOD includes interactive analysis and auxiliary tools that make it possible to manipulate the whole processes from building signaling network and query regulatory motifs to analyzing regulatory motifs with graphical illustration and summarized descriptions. As a result, RMOD provides an integrated view of the regulatory motifs and mechanism underlying their regulatory motif activities within the signaling network. RMOD is freely accessible online at the following URL: http://pks.kaist.ac.kr/rmod.

  18. Bias and discriminability during emotional signal detection in melancholic depression.

    Science.gov (United States)

    Hyett, Matthew; Parker, Gordon; Breakspear, Michael

    2014-04-27

    Cognitive disturbances in depression are pernicious and so contribute strongly to the burden of the disorder. Cognitive function has been traditionally studied by challenging subjects with modality-specific psychometric tasks and analysing performance using standard analysis of variance. Whilst informative, such an approach may miss deeper perceptual and inferential mechanisms that potentially unify apparently divergent emotional and cognitive deficits. Here, we sought to elucidate basic psychophysical processes underlying the detection of emotionally salient signals across individuals with melancholic and non-melancholic depression. Sixty participants completed an Affective Go/No-Go (AGN) task across negative, positive and neutral target stimuli blocks. We employed hierarchical Bayesian signal detection theory (SDT) to model psychometric performance across three equal groups of those with melancholic depression, those with a non-melancholic depression and healthy controls. This approach estimated likely response profiles (bias) and perceptual sensitivity (discriminability). Differences in the means of these measures speak to differences in the emotional signal detection between individuals across the groups, while differences in the variance reflect the heterogeneity of the groups themselves. Melancholic participants showed significantly decreased sensitivity to positive emotional stimuli compared to those in the non-melancholic group, and also had a significantly lower discriminability than healthy controls during the detection of neutral signals. The melancholic group also showed significantly higher variability in bias to both positive and negative emotionally salient material. Disturbances of emotional signal detection in melancholic depression appear dependent on emotional context, being biased during the detection of positive stimuli, consistent with a noisier representation of neutral stimuli. The greater heterogeneity of the bias across the melancholic

  19. Fast optical signal not detected in awake behaving monkeys.

    Science.gov (United States)

    Radhakrishnan, Harsha; Vanduffel, Wim; Deng, Hong Ping; Ekstrom, Leeland; Boas, David A; Franceschini, Maria Angela

    2009-04-01

    While the ability of near-infrared spectroscopy (NIRS) to measure cerebral hemodynamic evoked responses (slow optical signal) is well established, its ability to measure non-invasively the 'fast optical signal' is still controversial. Here, we aim to determine the feasibility of performing NIRS measurements of the 'fast optical signal' or Event-Related Optical Signals (EROS) under optimal experimental conditions in awake behaving macaque monkeys. These monkeys were implanted with a 'recording well' to expose the dura above the primary visual cortex (V1). A custom-made optical probe was inserted and fixed into the well. The close proximity of the probe to the brain maximized the sensitivity to changes in optical properties in the cortex. Motion artifacts were minimized by physical restraint of the head. Full-field contrast-reversing checkerboard stimuli were presented to monkeys trained to perform a visual fixation task. In separate sessions, two NIRS systems (CW4 and ISS FD oximeter), which previously showed the ability to measure the fast signal in human, were used. In some sessions EEG was acquired simultaneously with the optical signal. The increased sensitivity to cortical optical changes with our experimental setup was quantified with 3D Monte Carlo simulations on a segmented MRI monkey head. Averages of thousands of stimuli in the same animal, or grand averages across the two animals and across repeated sessions, did not lead to detection of the fast optical signal using either amplitude or phase of the optical signal. Hemodynamic responses and visual evoked potentials were instead always detected with single trials or averages of a few stimuli. Based on these negative results, despite the optimal experimental conditions, we doubt the usefulness of non-invasive fast optical signal measurements with NIRS.

  20. Signal Detection using ICA: Application to Chat Room Topic Spotting

    DEFF Research Database (Denmark)

    Kolenda, Thomas; Hansen, Lars Kai; Larsen, Jan

    2001-01-01

    signals with weak a priori assumptions in multimedia contexts. ICA of real world data is typically performed without knowledge of the number of non-trivial independent components, hence, it is of interest to test hypotheses concerning the number of components or simply to test whether a given set...... can detect meaningful context structures in a chat room log file....

  1. Two-phase xenon detector with gas amplification and electroluminescent signal detection

    International Nuclear Information System (INIS)

    Akimov, D.Yu.; Burenkov, A.A.; Grishkin, Yu.L.; Kovalenko, A.G.; Lebedenko, V.N.; Stekhanov, V.N.

    2008-01-01

    An optical technique for detecting ionization electrons produced during ionization of the liquid phase has been experimentally tested in two-phase (liquid-gas) xenon. The effects of gas and electroluminescent amplifications at the wire anode are simultaneously used for detection. This method allows construction of a supersensitive detector of small ionization signals-down to those corresponding to the detection of single electrons [ru

  2. Automatic detection of service initiation signals used in bars

    Directory of Open Access Journals (Sweden)

    Sebastian eLoth

    2013-08-01

    Full Text Available Recognising the intention of others is important in all social interactions, especially in the service domain. Enabling a bartending robot to serve customers is particularly challenging as the system has to recognise the social signals produced by customers and respond appropriately. Detecting whether a customer would like to order is essential for the service encounter to succeed. This detection is particularly challenging in a noisy environment with multiple customers. Thus, a bartending robot has to be able to distinguish between customers intending to order, chatting with friends or just passing by. In order to study which signals customers use to initiate a service interaction in a bar, we recorded real-life customer-staff interactions in several German bars. These recordings were used to generate initial hypotheses about the signals customers produce when bidding for the attention of bar staff. Two experiments using snapshots and short video sequences then tested the validity of these hypothesised candidate signals. The results revealed that bar staff responded to a set of two non-verbal signals: first, customers position themselves directly at the bar counter and, secondly, they look at a member of staff. Both signals were necessary and, when occurring together, sufficient. The participants also showed a strong agreement about when these cues occurred in the videos. Finally, a signal detection analysis revealed that ignoring a potential order is deemed worse than erroneously inviting customers to order. We conclude that a these two easily recognisable actions are sufficient for recognising the intention of customers to initiate a service interaction, but other actions such as gestures and speech were not necessary, and b the use of reaction time experiments using natural materials is feasible and provides ecologically valid results.

  3. Automatic detection of service initiation signals used in bars.

    Science.gov (United States)

    Loth, Sebastian; Huth, Kerstin; De Ruiter, Jan P

    2013-01-01

    Recognizing the intention of others is important in all social interactions, especially in the service domain. Enabling a bartending robot to serve customers is particularly challenging as the system has to recognize the social signals produced by customers and respond appropriately. Detecting whether a customer would like to order is essential for the service encounter to succeed. This detection is particularly challenging in a noisy environment with multiple customers. Thus, a bartending robot has to be able to distinguish between customers intending to order, chatting with friends or just passing by. In order to study which signals customers use to initiate a service interaction in a bar, we recorded real-life customer-staff interactions in several German bars. These recordings were used to generate initial hypotheses about the signals customers produce when bidding for the attention of bar staff. Two experiments using snapshots and short video sequences then tested the validity of these hypothesized candidate signals. The results revealed that bar staff responded to a set of two non-verbal signals: first, customers position themselves directly at the bar counter and, secondly, they look at a member of staff. Both signals were necessary and, when occurring together, sufficient. The participants also showed a strong agreement about when these cues occurred in the videos. Finally, a signal detection analysis revealed that ignoring a potential order is deemed worse than erroneously inviting customers to order. We conclude that (a) these two easily recognizable actions are sufficient for recognizing the intention of customers to initiate a service interaction, but other actions such as gestures and speech were not necessary, and (b) the use of reaction time experiments using natural materials is feasible and provides ecologically valid results.

  4. System and method for traffic signal timing estimation

    KAUST Repository

    Dumazert, Julien; Claudel, Christian G.

    2015-01-01

    A method and system for estimating traffic signals. The method and system can include constructing trajectories of probe vehicles from GPS data emitted by the probe vehicles, estimating traffic signal cycles, combining the estimates, and computing the traffic signal timing by maximizing a scoring function based on the estimates. Estimating traffic signal cycles can be based on transition times of the probe vehicles starting after a traffic signal turns green.

  5. System and method for traffic signal timing estimation

    KAUST Repository

    Dumazert, Julien

    2015-12-30

    A method and system for estimating traffic signals. The method and system can include constructing trajectories of probe vehicles from GPS data emitted by the probe vehicles, estimating traffic signal cycles, combining the estimates, and computing the traffic signal timing by maximizing a scoring function based on the estimates. Estimating traffic signal cycles can be based on transition times of the probe vehicles starting after a traffic signal turns green.

  6. Signal processing techniques for damage detection with piezoelectric wafer active sensors and embedded ultrasonic structural radar

    Science.gov (United States)

    Yu, Lingyu; Bao, Jingjing; Giurgiutiu, Victor

    2004-07-01

    Embedded ultrasonic structural radar (EUSR) algorithm is developed for using piezoelectric wafer active sensor (PWAS) array to detect defects within a large area of a thin-plate specimen. Signal processing techniques are used to extract the time of flight of the wave packages, and thereby to determine the location of the defects with the EUSR algorithm. In our research, the transient tone-burst wave propagation signals are generated and collected by the embedded PWAS. Then, with signal processing, the frequency contents of the signals and the time of flight of individual frequencies are determined. This paper starts with an introduction of embedded ultrasonic structural radar algorithm. Then we will describe the signal processing methods used to extract the time of flight of the wave packages. The signal processing methods being used include the wavelet denoising, the cross correlation, and Hilbert transform. Though hardware device can provide averaging function to eliminate the noise coming from the signal collection process, wavelet denoising is included to ensure better signal quality for the application in real severe environment. For better recognition of time of flight, cross correlation method is used. Hilbert transform is applied to the signals after cross correlation in order to extract the envelope of the signals. Signal processing and EUSR are both implemented by developing a graphical user-friendly interface program in LabView. We conclude with a description of our vision for applying EUSR signal analysis to structural health monitoring and embedded nondestructive evaluation. To this end, we envisage an automatic damage detection application utilizing embedded PWAS, EUSR, and advanced signal processing.

  7. Fault detection of gearbox using time-frequency method

    Science.gov (United States)

    Widodo, A.; Satrijo, Dj.; Prahasto, T.; Haryanto, I.

    2017-04-01

    This research deals with fault detection and diagnosis of gearbox by using vibration signature. In this work, fault detection and diagnosis are approached by employing time-frequency method, and then the results are compared with cepstrum analysis. Experimental work has been conducted for data acquisition of vibration signal thru self-designed gearbox test rig. This test-rig is able to demonstrate normal and faulty gearbox i.e., wears and tooth breakage. Three accelerometers were used for vibration signal acquisition from gearbox, and optical tachometer was used for shaft rotation speed measurement. The results show that frequency domain analysis using fast-fourier transform was less sensitive to wears and tooth breakage condition. However, the method of short-time fourier transform was able to monitor the faults in gearbox. Wavelet Transform (WT) method also showed good performance in gearbox fault detection using vibration signal after employing time synchronous averaging (TSA).

  8. Adaptive endpoint detection of seismic signal based on auto-correlated function

    International Nuclear Information System (INIS)

    Fan Wanchun; Shi Ren

    2000-01-01

    There are certain shortcomings for the endpoint detection by time-waveform envelope and/or by checking the travel table (both labelled as the artificial detection method). Based on the analysis of the auto-correlation function, the notion of the distance between auto-correlation functions was quoted, and the characterizations of the noise and the signal with noise were discussed by using the distance. Then, the method of auto-adaptable endpoint detection of seismic signal based on auto-correlated similarity was summed up. The steps of implementation and determining of the thresholds were presented in detail. The experimental results that were compared with the methods based on artificial detecting show that this method has higher sensitivity even in a low SNR circumstance

  9. Advanced Methods of Biomedical Signal Processing

    CERN Document Server

    Cerutti, Sergio

    2011-01-01

    This book grew out of the IEEE-EMBS Summer Schools on Biomedical Signal Processing, which have been held annually since 2002 to provide the participants state-of-the-art knowledge on emerging areas in biomedical engineering. Prominent experts in the areas of biomedical signal processing, biomedical data treatment, medicine, signal processing, system biology, and applied physiology introduce novel techniques and algorithms as well as their clinical or physiological applications. The book provides an overview of a compelling group of advanced biomedical signal processing techniques, such as mult

  10. Detection methods for irradiated mites and insects

    International Nuclear Information System (INIS)

    Ignatowicz, S.

    1999-01-01

    Results of the study on the following tests for separation of irradiated pests from untreated ones are reported: (a) test for identification of irradiated mites (Acaridae) based on lack of fecundity of treated females; (b) test for identification of irradiated beetles based on their locomotor activity; (c) test for identification of irradiated pests based on electron spin resonance (ESR) signal derived from treated insects; (d) test for identification of irradiated pests based on changes in the midgut induced by gamma radiation; and (e) test for identification of irradiated pests based on the alterations in total proteins of treated adults. Of these detection methods, only the test based on the pathological changes induced by irradiation in the insect midgut may identify consistently either irradiated larvae or adults. This test is simple and convenient when a rapid processing technique for dehydrating and embedding the midgut is used. (author)

  11. High-resolution imaging methods in array signal processing

    DEFF Research Database (Denmark)

    Xenaki, Angeliki

    in active sonar signal processing for detection and imaging of submerged oil contamination in sea water from a deep-water oil leak. The submerged oil _eld is modeled as a uid medium exhibiting spatial perturbations in the acoustic parameters from their mean ambient values which cause weak scattering...... of the incident acoustic energy. A highfrequency active sonar is selected to insonify the medium and receive the backscattered waves. High-frequency acoustic methods can both overcome the optical opacity of water (unlike methods based on electromagnetic waves) and resolve the small-scale structure...... of the submerged oil field (unlike low-frequency acoustic methods). The study shows that high-frequency acoustic methods are suitable not only for large-scale localization of the oil contamination in the water column but also for statistical characterization of the submerged oil field through inference...

  12. Variable threshold method for ECG R-peak detection.

    Science.gov (United States)

    Kew, Hsein-Ping; Jeong, Do-Un

    2011-10-01

    In this paper, a wearable belt-type ECG electrode worn around the chest by measuring the real-time ECG is produced in order to minimize the inconvenient in wearing. ECG signal is detected using a potential instrument system. The measured ECG signal is transmits via an ultra low power consumption wireless data communications unit to personal computer using Zigbee-compatible wireless sensor node. ECG signals carry a lot of clinical information for a cardiologist especially the R-peak detection in ECG. R-peak detection generally uses the threshold value which is fixed. There will be errors in peak detection when the baseline changes due to motion artifacts and signal size changes. Preprocessing process which includes differentiation process and Hilbert transform is used as signal preprocessing algorithm. Thereafter, variable threshold method is used to detect the R-peak which is more accurate and efficient than fixed threshold value method. R-peak detection using MIT-BIH databases and Long Term Real-Time ECG is performed in this research in order to evaluate the performance analysis.

  13. The detection of cavitation in hydraulic machines by use of ultrasonic signal analysis

    International Nuclear Information System (INIS)

    Gruber, P; Odermatt, P; Etterlin, M; Lerch, T; Frei, M; Farhat, M

    2014-01-01

    This presentation describes an experimental approach for the detection of cavitation in hydraulic machines by use of ultrasonic signal analysis. Instead of using the high frequency pulses (typically 1MHz) only for transit time measurement different other signal characteristics are extracted from the individual signals and its correlation function with reference signals in order to gain knowledge of the water conditions. As the pulse repetition rate is high (typically 100Hz), statistical parameters can be extracted of the signals. The idea is to find patterns in the parameters by a classifier that can distinguish between the different water states. This classification scheme has been applied to different cavitation sections: a sphere in a water flow in circular tube at the HSLU in Lucerne, a NACA profile in a cavitation tunnel and a Francis model test turbine both at LMH in Lausanne. From the signal raw data several statistical parameters in the time and frequency domain as well as from the correlation function with reference signals have been determined. As classifiers two methods were used: neural feed forward networks and decision trees. For both classification methods realizations with lowest complexity as possible are of special interest. It is shown that three signal characteristics, two from the signal itself and one from the correlation function are in many cases sufficient for the detection capability. The final goal is to combine these results with operating point, vibration, acoustic emission and dynamic pressure information such that a distinction between dangerous and not dangerous cavitation is possible

  14. Mathematical properties of a semi-classical signal analysis method: Noisy signal case

    KAUST Repository

    Liu, Dayan

    2012-08-01

    Recently, a new signal analysis method based on a semi-classical approach has been proposed [1]. The main idea in this method is to interpret a signal as a potential of a Schrodinger operator and then to use the discrete spectrum of this operator to analyze the signal. In this paper, we are interested in a mathematical analysis of this method in discrete case considering noisy signals. © 2012 IEEE.

  15. Mathematical properties of a semi-classical signal analysis method: Noisy signal case

    KAUST Repository

    Liu, Dayan; Laleg-Kirati, Taous-Meriem

    2012-01-01

    Recently, a new signal analysis method based on a semi-classical approach has been proposed [1]. The main idea in this method is to interpret a signal as a potential of a Schrodinger operator and then to use the discrete spectrum of this operator to analyze the signal. In this paper, we are interested in a mathematical analysis of this method in discrete case considering noisy signals. © 2012 IEEE.

  16. Particle detection systems and methods

    Science.gov (United States)

    Morris, Christopher L.; Makela, Mark F.

    2010-05-11

    Techniques, apparatus and systems for detecting particles such as muons and neutrons. In one implementation, a particle detection system employs a plurality of drift cells, which can be for example sealed gas-filled drift tubes, arranged on sides of a volume to be scanned to track incoming and outgoing charged particles, such as cosmic ray-produced muons. The drift cells can include a neutron sensitive medium to enable concurrent counting of neutrons. The system can selectively detect devices or materials, such as iron, lead, gold, uranium, plutonium, and/or tungsten, occupying the volume from multiple scattering of the charged particles passing through the volume and can concurrently detect any unshielded neutron sources occupying the volume from neutrons emitted therefrom. If necessary, the drift cells can be used to also detect gamma rays. The system can be employed to inspect occupied vehicles at border crossings for nuclear threat objects.

  17. Automatic detection of atrial fibrillation in cardiac vibration signals.

    Science.gov (United States)

    Brueser, C; Diesel, J; Zink, M D H; Winter, S; Schauerte, P; Leonhardt, S

    2013-01-01

    We present a study on the feasibility of the automatic detection of atrial fibrillation (AF) from cardiac vibration signals (ballistocardiograms/BCGs) recorded by unobtrusive bedmounted sensors. The proposed system is intended as a screening and monitoring tool in home-healthcare applications and not as a replacement for ECG-based methods used in clinical environments. Based on BCG data recorded in a study with 10 AF patients, we evaluate and rank seven popular machine learning algorithms (naive Bayes, linear and quadratic discriminant analysis, support vector machines, random forests as well as bagged and boosted trees) for their performance in separating 30 s long BCG epochs into one of three classes: sinus rhythm, atrial fibrillation, and artifact. For each algorithm, feature subsets of a set of statistical time-frequency-domain and time-domain features were selected based on the mutual information between features and class labels as well as first- and second-order interactions among features. The classifiers were evaluated on a set of 856 epochs by means of 10-fold cross-validation. The best algorithm (random forests) achieved a Matthews correlation coefficient, mean sensitivity, and mean specificity of 0.921, 0.938, and 0.982, respectively.

  18. Directionality and signal amplification in cryogenic dark matter detection

    International Nuclear Information System (INIS)

    More, T.

    1996-05-01

    A mounting body of evidence suggests that most of the mass in our universe is not contained in stars, but rather exists in some non- luminous form. The evidence comes independently from astronomical observation, cosmological theory, and particle physics. All of this missing mass is collectively referred to as dark matter. In this thesis we discuss two ways to improve the performance of dark matter detectors based on the measurement of ballistic phonons. First, we address the issue of signal identification through solitons. Secondly, we discuss a method for lowering the detection threshold and improving the energy sensitivity: amplifying phonons through the evaporation of helium atoms from a superfluid film coating the target and the adsorption of the evaporated atoms onto a helium-free substrate. A phonon amplifier would also be of use in many other applications in which a few phonons are to be measured at low temperatures. Factors contributing to the low amplifier gains achieved thus far are described and proposals for avoiding them are analyzed and discussed. 101 refs., 30 figs., 2 tabs

  19. Modelling of polysomnographic respiratory measurements for artefact detection and signal restoration

    International Nuclear Information System (INIS)

    Rathnayake, S I; Abeyratne, U R; Hukins, C; Duce, B

    2008-01-01

    Polysomnography (PSG), which incorporates measures of sleep with measures of EEG arousal, air flow, respiratory movement and oxygenation, is universally regarded as the reference standard in diagnosing sleep-related respiratory diseases such as obstructive sleep apnoea syndrome. Over 15 channels of physiological signals are measured from a subject undergoing a typical overnight PSG session. The signals often suffer from data losses, interferences and artefacts. In a typical sleep scoring session, artefact-corrupted signal segments are visually detected and removed from further consideration. This is a highly time-consuming process, and subjective judgement is required for the job. During typical sleep scoring sessions, the target is the detection of segments of diagnostic interest, and signal restoration is not utilized for distorted segments. In this paper, we propose a novel framework for artefact detection and signal restoration based on the redundancy among respiratory flow signals. We focus on the air flow (thermistor sensors) and nasal pressure signals which are clinically significant in detecting respiratory disturbances. The method treats the respiratory system and other organs that provide respiratory-related inputs/outputs to it (e.g., cardiovascular, brain) as a possibly nonlinear coupled-dynamical system, and uses the celebrated Takens embedding theorem as the theoretical basis for signal prediction. Nonlinear prediction across time (self-prediction) and signals (cross-prediction) provides us with a mechanism to detect artefacts as unexplained deviations. In addition to detection, the proposed method carries the potential to correct certain classes of artefacts and restore the signal. In this study, we categorize commonly occurring artefacts and distortions in air flow and nasal pressure measurements into several groups and explore the efficacy of the proposed technique in detecting/recovering them. The results we obtained from a database of clinical

  20. Detection of transient disturbing signals on PC boards

    Directory of Open Access Journals (Sweden)

    S. Korte

    2008-05-01

    Full Text Available This paper shows a possibility to visualize signal propagation in electronic circuits. Instead of using various galvanic measurement points all over the circuit, a test method is shown which measures the radiated field of the printed circuit board. By use of a 2-dimensional positionable field probe it is possible to get an overview over the signals running on the different parts of the PCB. In order to measure transient disturbing signals and distinguish them from normal device operation, problems of probe design and triggering need to be discussed.

  1. A novel non-invasive detection method for the FGFR3 gene mutation in maternal plasma for a fetal achondroplasia diagnosis based on signal amplification by hemin-MOFs/PtNPs.

    Science.gov (United States)

    Chen, Jun; Yu, Chao; Zhao, Yilin; Niu, Yazhen; Zhang, Lei; Yu, Yujie; Wu, Jing; He, Junlin

    2017-05-15

    The small amount of cell-free fetal DNA (cffDNA) can be a useful biomarker for early non-invasive prenatal diagnosis (NIPD) of achondroplasia. In this study, a novel non-invasive electrochemical DNA sensor for ultrasensitive detecting FGFR3 mutation gene, a pathogenic gene of achondroplasia, based on biocatalytic signal materials and the biotin-streptavidin system are presented. Notably encapsulation of hemin in metal-organic frameworks-based materials (hemin-MOFs) and platinum nanoparticles (PtNPs) were used to prepare hemin-MOFs/PtNPs composites via a one-beaker-one-step reduction. We utilized hemin-MOFs/PtNPs for signal amplification because the promising hemin-MOFs/PtNPs nanomaterial has remarkable ability of catalyze H 2 O 2 as well as excellent conductivity. To further amplify the electrochemical signal, reduced graphene oxide-tetraethylene pentamine (rGO-TEPA), gold nanoparticles and streptavidin were selected for modification of the electrode to enhance the conductivity and immobilize more biotin-modified capture probe (Bio-CP) through the high specificity and superior affinity between streptavidin and biotin. The electrochemical signal was primarily derived from the synergistic catalysis of H 2 O 2 by hemin and PtNPs and recorded by Chronoamperometry. Under the optimal conditions, this newly designed biosensor exhibited sensitive detection of FGFR3 from 0.1fM to 1nM with a low detection limit of 0.033fM (S/N=3). We proposed that this ultrasensitive biosensor is useful for the early non-invasive prenatal diagnosis of achondroplasia. Copyright © 2016 Elsevier B.V. All rights reserved.

  2. Detection of food irradiation with luminescence methods

    International Nuclear Information System (INIS)

    Anderle, H.

    1997-06-01

    Food irradiation is applied as method for the preservation of foods, the prevention of food spoilage and the inhibition of food-borne pathogens. Doses exceeding 10 kGy (10 kJ/kg) are not recommended by the WHO. The different legislation requires methods for the detection and the closimetry of irradiated foods. Among the physical methods based on the radiation-induced changes in inorganic, nonhygroscopic crystalline solids are thermoluminescence (TL), photostimulated luminescence (PSL) and lyoluminescence (LL) measurement. The luminescence methods were tested on natural minerals. Pure quartz, feldspars, calcite, aragonite and dolomite of known origin were irradiated, read out and analyzed to determine the influence of luminescence-activators and deactivators. Carbonate minerals show an orange-red TL easily detectable by blue-sensitive photomultiplier tubes. TIL-inactive carbonate samples may be identified by a lyoluminescence method using the reaction of trapped irradiation-generated charge carriers with the solvent during crystal-lattice breakup. The fine-ground mineral is dissolved in an alkaline complexing agent/chemiluminescence sensitizer/chemiluminescence catalyst (EDTA/luminol/hemin) reagent mixture. The TL and PSL of quartz is too weak to contribute a significant part for the corresponding signals in polymineral dust. Alkali and soda feldspar show intense TL and PSL. The temperature maxima in the TL glow curves allow a clear distinction. PSL does not give this additional information, it suffers from bleaching by ambient light and requires light-protection. Grain disinfestated with low irradiation doses (500 Gy) may not identified by both TL and PSL measurement. The natural TL of feldspar particles may be overlap with the irradiation-induced TL of other minerals. As a routine method, irradiated spices are identified with TL measurement. The dust particles have to be enriched by heavy-liquid flotation and centrifugation. The PSL method allows a clear

  3. The proportion of patient reports of suspected ADRs to signal detection in the Netherlands : case-control study

    NARCIS (Netherlands)

    van Hunsel, Florence; Talsma, Attje; van Puijenbroek, Eugène; de Jong-van den Berg, Lolkje; van Grootheest, Kees

    Aim To determine the contribution of patients' adverse drug reaction (ADR) reports to signals detection, through a study of the signals sent by Lareb to the Dutch Medicines Evaluation Board. Methods The percentage of patient's ADR reports contributing to generate signals of adverse drug reactions

  4. All-Optical envelope detection and fiber transmission of wireless signals by external injection of a DFB laser

    DEFF Research Database (Denmark)

    Prince, Kamau; Tafur Monroy, Idelfonso

    2008-01-01

    We outline a novel method for all-optical envelope detection of wireless signals by exploiting cross-gain modulation effects in a distributed feedback laser operating with optical injection. We successfully demonstrate envelope detection of a 20-GHz carrier amplitude-shift-keying modulated signal...

  5. A method for extracting chaotic signal from noisy environment

    International Nuclear Information System (INIS)

    Shang, L.-J.; Shyu, K.-K.

    2009-01-01

    In this paper, we propose a approach for extracting chaos signal from noisy environment where the chaotic signal has been contaminated by white Gaussian noise. The traditional type of independent component analysis (ICA) is capable of separating mixed signals and retrieving them independently; however, the separated signal shows unreal amplitude. The results of this study show with our method the real chaos signal can be effectively recovered.

  6. Limiter discriminator detection of M-ary FSK signals

    Science.gov (United States)

    Fonseka, John P.

    1990-10-01

    The performance of limiter discriminator detection of M-ary FSK signals is analyzed at arbitrary modulation indices. It is shown that the error rate performance of limiter discriminator detection can be significantly improved by increasing the modulation index above 1/M. The optimum modulation index that minimizes the overall error probability is determined for the cases M = 2, 4 and 8. The analysis is carried out for wideband and bandlimited channels with Gaussian and second-order Butterworth filters. It is shown that the optimum modulation index depends on the signal/noise ratio (SNR), in a wideband channel, and on both SNR and time-bandwidth product in a bandlimited channel. Finally, it is shown that the optimum sampling instance in presence of a nonzero phase IF filter can be approximately determined by using only the worst case symbol pattern.

  7. Signal modulation in cold-dark-matter detection

    International Nuclear Information System (INIS)

    Freese, K.; Frieman, J.; Gould, A.

    1988-01-01

    If weakly interacting massive particles (WIMP's) are the dark matter in the galactic halo, they may be detected in low-background ionization detectors now operating or with low-temperature devices under development. In detecting WIMP's of low mass or WIMP's with spin-dependent nuclear interactions (e.g., photinos), a principal technical difficulty appears to be achieving very low thresholds (approx. < keV) in large (∼ kg) detectors with low background noise. We present an analytic treatment of WIMP detection and show that the seasonal modulation of the signal can be used to detect WIMP's even at low-signal-to-background levels and thus without the necessity of going to very-low-energy thresholds. As a result, the prospects for detecting a variety of cold-dark-matter candidates may be closer at hand than previously thought. We discuss in detail the detector characteristics required for a number of WIMP candidates, and carefully work out expected event rates for several present and proposed detectors

  8. Chaos weak signal detecting algorithm and its application in the ultrasonic Doppler bloodstream speed measuring

    International Nuclear Information System (INIS)

    Chen, H Y; Lv, J T; Zhang, S Q; Zhang, L G; Li, J

    2005-01-01

    At the present time, the ultrasonic Doppler measuring means has been extensively used in the human body's bloodstream speed measuring. The ultrasonic Doppler measuring means can achieve the measuring of liquid flux by detecting Doppler frequency shift of ultrasonic in the process of liquid spread. However, the detected sound wave is a weak signal that is flooded in the strong noise signal. The traditional measuring method depends on signal-to-noise ratio. Under the very low signal-to-noise ratio or the strong noise signal background, the signal frequency is not measured. This article studied on chaotic movement of Duffing oscillator and intermittent chaotic characteristic on chaotic oscillator of Duffing equation. In the light of the range of the bloodstream speed of human body and the principle of Doppler shift, the paper determines the frequency shift range. An oscillator array including many oscillators is designed according to it. The reflected ultrasonic frequency information can be ascertained accurately by the intermittent chaos quality of the oscillator. The signal-to-noise ratio of -26.5 dB is obtained by the result of the experiment. Compared with the tradition the frequency method compare, the dependence to signal-to-noise ratio is lowered consumedly. The measuring precision of the bloodstream speed is heightened

  9. Effect of sample storage time on detection of hybridization signals in Checkerboard DNA-DNA hybridization.

    Science.gov (United States)

    do Nascimento, Cássio; Muller, Katia; Sato, Sandra; Albuquerque Junior, Rubens Ferreira

    2012-04-01

    Long-term sample storage can affect the intensity of the hybridization signals provided by molecular diagnostic methods that use chemiluminescent detection. The aim of this study was to evaluate the effect of different storage times on the hybridization signals of 13 bacterial species detected by the Checkerboard DNA-DNA hybridization method using whole-genomic DNA probes. Ninety-six subgingival biofilm samples were collected from 36 healthy subjects, and the intensity of hybridization signals was evaluated at 4 different time periods: (1) immediately after collecting (n = 24) and (2) after storage at -20 °C for 6 months (n = 24), (3) for 12 months (n = 24), and (4) for 24 months (n = 24). The intensity of hybridization signals obtained from groups 1 and 2 were significantly higher than in the other groups (p  0.05). The Checkerboard DNA-DNA hybridization method was suitable to detect hybridization signals from all groups evaluated, and the intensity of signals decreased significantly after long periods of sample storage.

  10. Cancer Detection and Diagnosis Methods - Annual Plan

    Science.gov (United States)

    Early cancer detection is a proven life-saving strategy. Learn about the research opportunities NCI supports, including liquid biopsies and other less-invasive methods, for detecting early cancers and precancerous growths.

  11. Epileptic seizure detection in EEG signal with GModPCA and support vector machine.

    Science.gov (United States)

    Jaiswal, Abeg Kumar; Banka, Haider

    2017-01-01

    Epilepsy is one of the most common neurological disorders caused by recurrent seizures. Electroencephalograms (EEGs) record neural activity and can detect epilepsy. Visual inspection of an EEG signal for epileptic seizure detection is a time-consuming process and may lead to human error; therefore, recently, a number of automated seizure detection frameworks were proposed to replace these traditional methods. Feature extraction and classification are two important steps in these procedures. Feature extraction focuses on finding the informative features that could be used for classification and correct decision-making. Therefore, proposing effective feature extraction techniques for seizure detection is of great significance. Principal Component Analysis (PCA) is a dimensionality reduction technique used in different fields of pattern recognition including EEG signal classification. Global modular PCA (GModPCA) is a variation of PCA. In this paper, an effective framework with GModPCA and Support Vector Machine (SVM) is presented for epileptic seizure detection in EEG signals. The feature extraction is performed with GModPCA, whereas SVM trained with radial basis function kernel performed the classification between seizure and nonseizure EEG signals. Seven different experimental cases were conducted on the benchmark epilepsy EEG dataset. The system performance was evaluated using 10-fold cross-validation. In addition, we prove analytically that GModPCA has less time and space complexities as compared to PCA. The experimental results show that EEG signals have strong inter-sub-pattern correlations. GModPCA and SVM have been able to achieve 100% accuracy for the classification between normal and epileptic signals. Along with this, seven different experimental cases were tested. The classification results of the proposed approach were better than were compared the results of some of the existing methods proposed in literature. It is also found that the time and space

  12. Supersonic wave detection method and supersonic detection device

    International Nuclear Information System (INIS)

    Machida, Koichi; Seto, Takehiro; Ishizaki, Hideaki; Asano, Rin-ichi.

    1996-01-01

    The present invention provides a method of and device for a detection suitable to a channel box which is used while covering a fuel assembly of a BWR type reactor. Namely, a probe for transmitting/receiving supersonic waves scans on the surface of the channel box. A data processing device determines an index showing a selective orientation degree of crystal direction of the channel box based on the signals received by the probe. A judging device compares the determined index with a previously determined allowable range to judge whether the channel box is satisfactory or not based on the result of the comparison. The judgement are on the basis that (1) the bending of the channel box is caused by the difference of elongation of opposed surfaces, (2) the elongation due to irradiation is caused by the selective orientation of crystal direction, and (3) the bending of the channel box can be suppressed within a predetermined range by suppressing the index determined by the measurement of supersonic waves having a correlation with the selective orientation of the crystal direction. As a result, the performance of the channel box capable of enduring high burnup region can be confirmed in a nondestructive manner. (I.S.)

  13. Nasal chemosensory cells use bitter taste signaling to detect irritants and bacterial signals.

    Science.gov (United States)

    Tizzano, Marco; Gulbransen, Brian D; Vandenbeuch, Aurelie; Clapp, Tod R; Herman, Jake P; Sibhatu, Hiruy M; Churchill, Mair E A; Silver, Wayne L; Kinnamon, Sue C; Finger, Thomas E

    2010-02-16

    The upper respiratory tract is continually assaulted with harmful dusts and xenobiotics carried on the incoming airstream. Detection of such irritants by the trigeminal nerve evokes protective reflexes, including sneezing, apnea, and local neurogenic inflammation of the mucosa. Although free intra-epithelial nerve endings can detect certain lipophilic irritants (e.g., mints, ammonia), the epithelium also houses a population of trigeminally innervated solitary chemosensory cells (SCCs) that express T2R bitter taste receptors along with their downstream signaling components. These SCCs have been postulated to enhance the chemoresponsive capabilities of the trigeminal irritant-detection system. Here we show that transduction by the intranasal solitary chemosensory cells is necessary to evoke trigeminally mediated reflex reactions to some irritants including acyl-homoserine lactone bacterial quorum-sensing molecules, which activate the downstream signaling effectors associated with bitter taste transduction. Isolated nasal chemosensory cells respond to the classic bitter ligand denatonium as well as to the bacterial signals by increasing intracellular Ca(2+). Furthermore, these same substances evoke changes in respiration indicative of trigeminal activation. Genetic ablation of either G alpha-gustducin or TrpM5, essential elements of the T2R transduction cascade, eliminates the trigeminal response. Because acyl-homoserine lactones serve as quorum-sensing molecules for gram-negative pathogenic bacteria, detection of these substances by airway chemoreceptors offers a means by which the airway epithelium may trigger an epithelial inflammatory response before the bacteria reach population densities capable of forming destructive biofilms.

  14. Device and method for redirecting electromagnetic signals

    Science.gov (United States)

    Garcia, Ernest J.

    1999-01-01

    A device fabricated to redirect electromagnetic signals, the device including a primary driver adapted to provide a predetermined force, a linkage system coupled to the primary driver, a pusher rod rotationally coupled to the linkage system, a flexible rod element attached to the pusher rod and adapted to buckle upon the application of the predetermined force, and a mirror structure attached to the flexible rod element at one end and to the substrate at another end. When the predetermined force buckles the flexible rod element, the mirror structure and the flexible rod element both move to thereby allow a remotely-located electromagnetic signal directed towards the device to be redirected.

  15. Signal Processing Methods Monitor Cranial Pressure

    Science.gov (United States)

    2010-01-01

    Dr. Norden Huang, of Goddard Space Flight Center, invented a set of algorithms (called the Hilbert-Huang Transform, or HHT) for analyzing nonlinear and nonstationary signals that developed into a user-friendly signal processing technology for analyzing time-varying processes. At an auction managed by Ocean Tomo Federal Services LLC, licenses of 10 U.S. patents and 1 domestic patent application related to HHT were sold to DynaDx Corporation, of Mountain View, California. DynaDx is now using the licensed NASA technology for medical diagnosis and prediction of brain blood flow-related problems, such as stroke, dementia, and traumatic brain injury.

  16. Signal Detection of Imipenem Compared to Other Drugs from Korea Adverse Event Reporting System Database.

    Science.gov (United States)

    Park, Kyounghoon; Soukavong, Mick; Kim, Jungmee; Kwon, Kyoung Eun; Jin, Xue Mei; Lee, Joongyub; Yang, Bo Ram; Park, Byung Joo

    2017-05-01

    To detect signals of adverse drug events after imipenem treatment using the Korea Institute of Drug Safety & Risk Management-Korea adverse event reporting system database (KIDS-KD). We performed data mining using KIDS-KD, which was constructed using spontaneously reported adverse event (AE) reports between December 1988 and June 2014. We detected signals calculated the proportional reporting ratio, reporting odds ratio, and information component of imipenem. We defined a signal as any AE that satisfied all three indices. The signals were compared with drug labels of nine countries. There were 807582 spontaneous AEs reports in the KIDS-KD. Among those, the number of antibiotics related AEs was 192510; 3382 reports were associated with imipenem. The most common imipenem-associated AE was the drug eruption; 353 times. We calculated the signal by comparing with all other antibiotics and drugs; 58 and 53 signals satisfied the three methods. We compared the drug labelling information of nine countries, including the USA, the UK, Japan, Italy, Switzerland, Germany, France, Canada, and South Korea, and discovered that the following signals were currently not included in drug labels: hypokalemia, cardiac arrest, cardiac failure, Parkinson's syndrome, myocardial infarction, and prostate enlargement. Hypokalemia was an additional signal compared with all other antibiotics, and the other signals were not different compared with all other antibiotics and all other drugs. We detected new signals that were not listed on the drug labels of nine countries. However, further pharmacoepidemiologic research is needed to evaluate the causality of these signals. © Copyright: Yonsei University College of Medicine 2017

  17. Method and apparatus for stabilizing signals in radioactive well logging tools

    International Nuclear Information System (INIS)

    Kampfer, J.G.; Ingram, L.A.

    1977-01-01

    A method and apparatus are presented for stabilizing signals in radioactive well logging tools. In the tool a main scintillating crystal and photomultiplier tube for detecting radiation induced in the borehole by a source of radiation are provided and a reference crystal, including a source of mono-energetic radiation, for producing continuous reference signals of a predetermined energy level. The signals are monitored and the spectrum is stabilized to correct for drift of the data signals introduced by the photomultiplier tube and the data transmission system. The preferred mono-energetic reference signals are selected to appear in the energy spectrum at a level which minimizes error. An electronic circuit at the surface provides a correction signal for adjusting the gain of a data signal amplifier responsive to changes in the reference signal, thereby correcting for drift in the data signal

  18. A comparison of three time-domain anomaly detection methods

    Energy Technology Data Exchange (ETDEWEB)

    Schoonewelle, H.; Hagen, T.H.J.J. van der; Hoogenboom, J.E. [Delft University of Technology (Netherlands). Interfaculty Reactor Institute

    1996-01-01

    Three anomaly detection methods based on a comparison of signal values with predictions from an autoregressive model are presented. These methods are: the extremes method, the {chi}{sup 2} method and the sequential probability ratio test. The methods are used to detect a change of the standard deviation of the residual noise obtained from applying an autoregressive model. They are fast and can be used in on-line applications. For each method some important anomaly detection parameters are determined by calculation or simulation. These parameters are: the false alarm rate, the average time to alarm and - being of minor importance -the alarm failure rate. Each method is optimized with respect to the average time to alarm for a given value of the false alarm rate. The methods are compared with each other, resulting in the sequential probability ratio test being clearly superior. (author).

  19. A comparison of three time-domain anomaly detection methods

    International Nuclear Information System (INIS)

    Schoonewelle, H.; Hagen, T.H.J.J. van der; Hoogenboom, J.E.

    1996-01-01

    Three anomaly detection methods based on a comparison of signal values with predictions from an autoregressive model are presented. These methods are: the extremes method, the χ 2 method and the sequential probability ratio test. The methods are used to detect a change of the standard deviation of the residual noise obtained from applying an autoregressive model. They are fast and can be used in on-line applications. For each method some important anomaly detection parameters are determined by calculation or simulation. These parameters are: the false alarm rate, the average time to alarm and - being of minor importance -the alarm failure rate. Each method is optimized with respect to the average time to alarm for a given value of the false alarm rate. The methods are compared with each other, resulting in the sequential probability ratio test being clearly superior. (author)

  20. The availability of the detection method of internal valve leakage using acoustic method

    International Nuclear Information System (INIS)

    Kumagai, Hiromichi; Suzuki, Akio

    1989-01-01

    The purpose of this study is to estimate the availability of acoustic method to the internal leakage of the valves at power plants. The acoustic method was applied to the valves at the site, and the background noise was measured for the abnormal plantcondition. From the comparison of the background noise date with the experimental results as to relation between leakage flow and acoust signal, the minimum leakage flow rates that can be detected by the acoust signal was suggested. When the background levels are higher than the acoust signal, the method described below was considered that the analysis the remainder among the background noise frequency spectrum and the acoustic signal spectrum become a very useful leak detection method. A few experimental examples of the spectrum analysis that varied the background noise characteristic were given. (author)

  1. Rapid methods for detection of bacteria

    DEFF Research Database (Denmark)

    Corfitzen, Charlotte B.; Andersen, B.Ø.; Miller, M.

    2006-01-01

    Traditional methods for detection of bacteria in drinking water e.g. Heterotrophic Plate Counts (HPC) or Most Probable Number (MNP) take 48-72 hours to give the result. New rapid methods for detection of bacteria are needed to protect the consumers against contaminations. Two rapid methods...

  2. Optimal Noise Enhanced Signal Detection in a Unified Framework

    Directory of Open Access Journals (Sweden)

    Ting Yang

    2016-06-01

    Full Text Available In this paper, a new framework for variable detectors is formulated in order to solve different noise enhanced signal detection optimal problems, where six different disjoint sets of detector and discrete vector pairs are defined according to the two inequality-constraints on detection and false-alarm probabilities. Then theorems and algorithms constructed based on the new framework are presented to search the optimal noise enhanced solutions to maximize the relative improvements of the detection and the false-alarm probabilities, respectively. Further, the optimal noise enhanced solution of the maximum overall improvement is obtained based on the new framework and the relationship among the three maximums is presented. In addition, the sufficient conditions for improvability or non-improvability under the two certain constraints are given. Finally, numerous examples are presented to illustrate the theoretical results and the proofs of the main theorems are given in the Appendix.

  3. Methods for Signal Filtering in NMR Tomography

    Czech Academy of Sciences Publication Activity Database

    Gescheidtová, E.; Kubásek, R.; Bartušek, Karel

    2006-01-01

    Roč. 4, č. 1 (2006), 3404:1-10 ISSN 1738-9682 Institutional research plan: CEZ:AV0Z20650511 Keywords : FID signal * pre-emphasis * gradient pulse * bank of digital filters * threshold Subject RIV: JA - Electronics ; Optoelectronics, Electrical Engineering

  4. Regularized non-stationary morphological reconstruction algorithm for weak signal detection in microseismic monitoring: methodology

    Science.gov (United States)

    Huang, Weilin; Wang, Runqiu; Chen, Yangkang

    2018-05-01

    Microseismic signal is typically weak compared with the strong background noise. In order to effectively detect the weak signal in microseismic data, we propose a mathematical morphology based approach. We decompose the initial data into several morphological multiscale components. For detection of weak signal, a non-stationary weighting operator is proposed and introduced into the process of reconstruction of data by morphological multiscale components. The non-stationary weighting operator can be obtained by solving an inversion problem. The regularized non-stationary method can be understood as a non-stationary matching filtering method, where the matching filter has the same size as the data to be filtered. In this paper, we provide detailed algorithmic descriptions and analysis. The detailed algorithm framework, parameter selection and computational issue for the regularized non-stationary morphological reconstruction (RNMR) method are presented. We validate the presented method through a comprehensive analysis through different data examples. We first test the proposed technique using a synthetic data set. Then the proposed technique is applied to a field project, where the signals induced from hydraulic fracturing are recorded by 12 three-component geophones in a monitoring well. The result demonstrates that the RNMR can improve the detectability of the weak microseismic signals. Using the processed data, the short-term-average over long-term average picking algorithm and Geiger's method are applied to obtain new locations of microseismic events. In addition, we show that the proposed RNMR method can be used not only in microseismic data but also in reflection seismic data to detect the weak signal. We also discussed the extension of RNMR from 1-D to 2-D or a higher dimensional version.

  5. Research on Quality Detection Methods for Automotive Transmission

    Directory of Open Access Journals (Sweden)

    Sheng FU

    2014-04-01

    Full Text Available Given the problems in intelligent diagnosis methods for automotive transmission, it is difficult to obtain the fault signal features and a large enough sample size to study. To solve these problems, a method integrating order tracking, cepstrum, support vector machine (SVM and extremal curve is proposed in this paper. Order tracking and cepstrum are combined for processing the non- stationary vibration signal emitted by automotive transmission. As conventional intelligent methods cannot produce true results for insufficient samples, a method that combines SVM and extremal curve is presented. Input the vector acquired from the feature signals into the SVM model for the first detection, and then do the second detection by means of extremal curve which in turn can enrich the training samples in SVM model thus making the SVM model be more perfect. Analytical description and experimental studies are presented for the methods of signal processing and quality detection. The experimental results demonstrate the effectiveness and practicability of the proposed method.

  6. Lightweight MAC-Spoof Detection Exploiting Received Signal Power and Median Filtering

    DEFF Research Database (Denmark)

    Papini, Davide

    2011-01-01

    this kind of attack based on signal power monitoring. The main contribution of our work is the introduction of a median l- ter that enables the detection of the attack by looking at the variance of the signal power. We take into account two types of references for the samples, time and number of frames......IEEE 802.11 networks are subject to MAC-spoof attacks. An attacker can easily steal the identity of a legitimate station, even Access Points, thus enabling him to take full control over network basic mech- anisms or even access restricted resources. In this paper we propose a method to detect...

  7. Leak detection by vibrational diagnostic methods

    International Nuclear Information System (INIS)

    Siklossy, P.

    1983-01-01

    The possibilities and methods of leak detection due to mechanical failures in nuclear power plants are reviewed on the basis of the literature. Great importance is attributed to vibrational diagnostic methods for their adventageous characteristics which enable them to become final leak detecting methods. The problems of noise analysis, e.g. leak detection by impact sound measurements, probe characteristics, gain problems, probe selection, off-line analysis and correlation functions, types of leak noises etc. are summarized. Leak detection based on noise analysis can be installed additionally to power plants. Its maintenance and testing is simple. On the other hand, it requires special training and measuring methods. (Sz.J.)

  8. Alternative method for determining the constant offset in lidar signal

    Science.gov (United States)

    Vladimir A. Kovalev; Cyle Wold; Alexander Petkov; Wei Min Hao

    2009-01-01

    We present an alternative method for determining the total offset in lidar signal created by a daytime background-illumination component and electrical or digital offset. Unlike existing techniques, here the signal square-range-correction procedure is initially performed using the total signal recorded by lidar, without subtraction of the offset component. While...

  9. A device and method for generating a polybinary signal

    DEFF Research Database (Denmark)

    2018-01-01

    The present disclosure relates to a method for generating an L-level polybinary signal, comprising the steps of: providing a baseband signal with a spectrum defined by a predefined frequency period, f p ; filtering the baseband signal using a low-pass filter having a pre-defined cut-off frequency...

  10. Extraction of ECG signal with adaptive filter for hearth abnormalities detection

    Science.gov (United States)

    Turnip, Mardi; Saragih, Rijois. I. E.; Dharma, Abdi; Esti Kusumandari, Dwi; Turnip, Arjon; Sitanggang, Delima; Aisyah, Siti

    2018-04-01

    This paper demonstrates an adaptive filter method for extraction ofelectrocardiogram (ECG) feature in hearth abnormalities detection. In particular, electrocardiogram (ECG) is a recording of the heart's electrical activity by capturing a tracingof cardiac electrical impulse as it moves from the atrium to the ventricles. The applied algorithm is to evaluate and analyze ECG signals for abnormalities detection based on P, Q, R and S peaks. In the first phase, the real-time ECG data is acquired and pre-processed. In the second phase, the procured ECG signal is subjected to feature extraction process. The extracted features detect abnormal peaks present in the waveform. Thus the normal and abnormal ECG signal could be differentiated based on the features extracted.

  11. Signal processing method for Johnson noise thermometry

    International Nuclear Information System (INIS)

    Hwang, I. G.; Moon, B. S.; Kinser, Rpger

    2003-01-01

    The development of Johnson Noise Thermometry requires a high sensitive preamplifier circuit to pick up the temperature-related noise on the sensing element. However, the random noise generated in this amplification circuit causes a significant erroneous influence to the measurement. This paper describes signal processing mechanism of the Johnson Noise Thermometry system which is underway of development in collaboration between KAERI and ORNL. It adopts two identical amplifier channels and utilizes a digital signal processing technique to remove the independent noise of each channel. The CPSD(Cross Power Spectral Density) function is used to cancel the independent noise and the differentiation of narrow or single frequency peak from the CPSD data separates the common mode electromagnetic interference noise

  12. Nuclear pulse signal processing technique based on blind deconvolution method

    International Nuclear Information System (INIS)

    Hong Pengfei; Yang Lei; Fu Tingyan; Qi Zhong; Li Dongcang; Ren Zhongguo

    2012-01-01

    In this paper, we present a method for measurement and analysis of nuclear pulse signal, with which pile-up signal is removed, the signal baseline is restored, and the original signal is obtained. The data acquisition system includes FPGA, ADC and USB. The FPGA controls the high-speed ADC to sample the signal of nuclear radiation, and the USB makes the ADC work on the Slave FIFO mode to implement high-speed transmission status. Using the LabVIEW, it accomplishes online data processing of the blind deconvolution algorithm and data display. The simulation and experimental results demonstrate advantages of the method. (authors)

  13. Application of signal processing techniques for islanding detection of distributed generation in distribution network: A review

    International Nuclear Information System (INIS)

    Raza, Safdar; Mokhlis, Hazlie; Arof, Hamzah; Laghari, J.A.; Wang, Li

    2015-01-01

    Highlights: • Pros & cons of conventional islanding detection techniques (IDTs) are discussed. • Signal processing techniques (SPTs) ability in detecting islanding is discussed. • SPTs ability in improving performance of passive techniques are discussed. • Fourier, s-transform, wavelet, HHT & tt-transform based IDTs are reviewed. • Intelligent classifiers (ANN, ANFIS, Fuzzy, SVM) application in SPT are discussed. - Abstract: High penetration of distributed generation resources (DGR) in distribution network provides many benefits in terms of high power quality, efficiency, and low carbon emissions in power system. However, efficient islanding detection and immediate disconnection of DGR is critical in order to avoid equipment damage, grid protection interference, and personnel safety hazards. Islanding detection techniques are mainly classified into remote, passive, active, and hybrid techniques. From these, passive techniques are more advantageous due to lower power quality degradation, lower cost, and widespread usage by power utilities. However, the main limitations of these techniques are that they possess a large non detection zones and require threshold setting. Various signal processing techniques and intelligent classifiers have been used to overcome the limitations of passive islanding. Signal processing techniques, in particular, are adopted due to their versatility, stability, cost effectiveness, and ease of modification. This paper presents a comprehensive overview of signal processing techniques used to improve common passive islanding detection techniques. A performance comparison between the signal processing based islanding detection techniques with existing techniques are also provided. Finally, this paper outlines the relative advantages and limitations of the signal processing techniques in order to provide basic guidelines for researchers and field engineers in determining the best method for their system

  14. Residual signal feature extraction for gearbox planetary stage fault detection

    DEFF Research Database (Denmark)

    Skrimpas, Georgios Alexandros; Ursin, Thomas; Sweeney, Christian Walsted

    2017-01-01

    Faults in planetary gears and related bearings, e.g. planet bearings and planet carrier bearings, pose inherent difficulties on their accurate and consistent detection associated mainly to the low energy in slow rotating stages and the operating complexity of planetary gearboxes. In this work......, identification of the expected spectral signature for proper residual signal calculation and filtering of any frequency component not related to the planetary stage. Two field cases of planet carrier bearing defect and planet wheel spalling are presented and discussed, showing the efficiency of the followed...

  15. Ultrasonic signal analysis according to laser ultrasound generation position for the detection of delamination in composites

    Energy Technology Data Exchange (ETDEWEB)

    Hong, Kyung Min; Choi In Young; Kim, Seong Jong; Kang, Young June [Chonbuk National University, Jeonju (Korea, Republic of); Lee, Gil Dong [GP Inc., Daejeon (Korea, Republic of)

    2015-11-15

    Carbon-fiber-reinforced plastic should be inspected in the fabrication process to enhance quality by preventing defects, such as delamination and voids. Conventional ultrasonic evaluation methods cannot be applied during the fabrication process because they require contact measurement by a transducer. Thus, an optical method using a laser was employed in this study for non-contact ultrasonic evaluation. Ultrasonic signals were generated by a pulsed laser and received by using a laser interferometer. First, an ultrasonic signal was generated from the back side of a material sample with artificial internal defects in the composite. The ultrasonic signal directed through the interior of the specimen was then detected at the front side. After determining the locations of the internal defects, the defects were quantitatively evaluated from the front side of the composite by using ultrasonic signal generation and reception.

  16. Frequency-domain method for separating signal and noise

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    A new method for separation of signal and noise (SSN) is put forward. Frequency is redefined according to the features of signal and its derivative in the sampl ing time interval, thus double orthogonal basis (DOB) is constructed so that a signal can be precisely signified with a linear combination of low-frequency DOB . Under joint consideration in time domain (TD) and frequency domain (FD), a method on SSN with high accuracy is derived and a matched algorithm is designed and analyzed. This method is applicable to SSN in multiple frequency bands, and convenient in applying signal characteristics in TD and FD synthetically with highe raccuracy.

  17. Frequency-domain method for separating signal and noise

    Institute of Scientific and Technical Information of China (English)

    王正明; 段晓君

    2000-01-01

    A new method for separation of signal and noise (SSN) is put forward. Frequency is redefined according to the features of signal and its derivative in the sampling time interval, thus double orthogonal basis (DOB) is constructed so that a signal can be precisely signified with a linear combination of low-frequency DOB. Under joint consideration in time domain (TD) and frequency domain (FD), a method on SSN with high accuracy is derived and a matched algorithm is designed and analyzed. This method is applicable to SSN in multiple frequency bands, and convenient in applying signal characteristics in TD and FD synthetically with higher accuracy.

  18. Leak detection in pipelines through spectral analysis of pressure signals

    Directory of Open Access Journals (Sweden)

    Souza A.L.

    2000-01-01

    Full Text Available The development and test of a technique for leak detection in pipelines is presented. The technique is based on the spectral analysis of pressure signals measured in pipeline sections where the formation of stationary waves is favoured, allowing leakage detection during the start/stop of pumps. Experimental tests were performed in a 1250 m long pipeline for various operational conditions of the pipeline (liquid flow rate and leakage configuration. Pressure transients were obtained by four transducers connected to a PC computer. The obtained results show that the spectral analysis of pressure transients, together with the knowledge of reflection points provide a simple and efficient way of identifying leaks during the start/stop of pumps in pipelines.

  19. Thermoluminescence method for detection of irradiated food

    International Nuclear Information System (INIS)

    Pinnioja, S.

    1998-01-01

    A method of thermoluminescence (TL) analysis was developed for the detection of irradiated foods. The TL method is based on the determination of thermoluminescence of adhering or contaminating minerals separated from foods by wet sieving and treatment with high density liquid. Carbon tetrachloride provided a suitable alternative for foods that form gels with water. Thermoluminescence response of minerals in a first TL measurement is normalised with a second TL measurement of the same mineral sample after calibration irradiation to a dose of 5 kGy. The decision about irradiation is made on the basis of a comparison of the two TL spectra: if the two TL glow curves match in shape and intensity the sample has been irradiated, and if they are clearly different it has not been irradiated. An attractive feature of TL analysis is that the mineral material itself is used for calibration; no reference material is required. Foods of interest in the investigation were herbs, spices, berries and seafood. The presence of minerals in samples is a criterion for application of the method, and appropriate minerals were found in all herbs, spices and berries. The most common minerals in terrestrial food were tecto-silicates - quartz and feldspars - which with their intense and stable thermoluminescence were well suited for the analysis. Mica proved to be useless for detection purposes, whereas carbonate in the form of calcite separated from intestines of seafood was acceptable. Fading of the TL signal is considerable in the low temperature part of the glow curve during a storage of several months after irradiation. However, spices and herbs could easily be identified as irradiated even after two years storage. Conditions for seafood, which is stored in a freezer, are different, and only slight fading was observed after one year. The effect of mineral composition and structure on TL was studied for feldspars. Feldspars originating from subtropical and tropical regions exhibit lower TL

  20. Thermoluminescence method for detection of irradiated food

    Energy Technology Data Exchange (ETDEWEB)

    Pinnioja, S

    1998-12-31

    A method of thermoluminescence (TL) analysis was developed for the detection of irradiated foods. The TL method is based on the determination of thermoluminescence of adhering or contaminating minerals separated from foods by wet sieving and treatment with high density liquid. Carbon tetrachloride provided a suitable alternative for foods that form gels with water. Thermoluminescence response of minerals in a first TL measurement is normalised with a second TL measurement of the same mineral sample after calibration irradiation to a dose of 5 kGy. The decision about irradiation is made on the basis of a comparison of the two TL spectra: if the two TL glow curves match in shape and intensity the sample has been irradiated, and if they are clearly different it has not been irradiated. An attractive feature of TL analysis is that the mineral material itself is used for calibration; no reference material is required. Foods of interest in the investigation were herbs, spices, berries and seafood. The presence of minerals in samples is a criterion for application of the method, and appropriate minerals were found in all herbs, spices and berries. The most common minerals in terrestrial food were tecto-silicates - quartz and feldspars - which with their intense and stable thermoluminescence were well suited for the analysis. Mica proved to be useless for detection purposes, whereas carbonate in the form of calcite separated from intestines of seafood was acceptable. Fading of the TL signal is considerable in the low temperature part of the glow curve during a storage of several months after irradiation. However, spices and herbs could easily be identified as irradiated even after two years storage. Conditions for seafood, which is stored in a freezer, are different, and only slight fading was observed after one year. The effect of mineral composition and structure on TL was studied for feldspars. Feldspars originating from subtropical and tropical regions exhibit lower TL

  1. Stochastic Resonance in an Underdamped System with Pinning Potential for Weak Signal Detection

    Directory of Open Access Journals (Sweden)

    Haibin Zhang

    2015-08-01

    Full Text Available Stochastic resonance (SR has been proved to be an effective approach for weak sensor signal detection. This study presents a new weak signal detection method based on a SR in an underdamped system, which consists of a pinning potential model. The model was firstly discovered from magnetic domain wall (DW in ferromagnetic strips. We analyze the principle of the proposed underdamped pinning SR (UPSR system, the detailed numerical simulation and system performance. We also propose the strategy of selecting the proper damping factor and other system parameters to match a weak signal, input noise and to generate the highest output signal-to-noise ratio (SNR. Finally, we have verified its effectiveness with both simulated and experimental input signals. Results indicate that the UPSR performs better in weak signal detection than the conventional SR (CSR with merits of higher output SNR, better anti-noise and frequency response capability. Besides, the system can be designed accurately and efficiently owing to the sensibility of parameters and potential diversity. The features also weaken the limitation of small parameters on SR system.

  2. Stochastic Resonance in an Underdamped System with Pinning Potential for Weak Signal Detection.

    Science.gov (United States)

    Zhang, Haibin; He, Qingbo; Kong, Fanrang

    2015-08-28

    Stochastic resonance (SR) has been proved to be an effective approach for weak sensor signal detection. This study presents a new weak signal detection method based on a SR in an underdamped system, which consists of a pinning potential model. The model was firstly discovered from magnetic domain wall (DW) in ferromagnetic strips. We analyze the principle of the proposed underdamped pinning SR (UPSR) system, the detailed numerical simulation and system performance. We also propose the strategy of selecting the proper damping factor and other system parameters to match a weak signal, input noise and to generate the highest output signal-to-noise ratio (SNR). Finally, we have verified its effectiveness with both simulated and experimental input signals. Results indicate that the UPSR performs better in weak signal detection than the conventional SR (CSR) with merits of higher output SNR, better anti-noise and frequency response capability. Besides, the system can be designed accurately and efficiently owing to the sensibility of parameters and potential diversity. The features also weaken the limitation of small parameters on SR system.

  3. Signal-based Gas Leakage Detection for Fluid Power Accumulators in Wind Turbines

    DEFF Research Database (Denmark)

    Liniger, Jesper; Sepehri, Nariman; N. Soltani, Mohsen

    2017-01-01

    This paper describes the development and application of a signal-based fault detection method for identifying gas leakage in hydraulic accumulators used in wind turbines. The method uses Multiresolution Signal Decomposition (MSD) based on wavelets for feature extraction from a~single fluid pressure...... measurement located close to the accumulator. Gas leakage is shown to create increased variations in this pressure signal. The Root Mean Square (RMS) of the detail coefficient Level 9 from the MSD is found as the most sensitive and robust fault indicator of gas leakage. The method is verified...... on an experimental setup allowing for the replication of the conditions for accumulators in wind turbines. Robustness is tested in a multi-fault environment where gas and external fluid leakage occurs simultaneously. In total, 24 experiments are performed, which show that the method is sensitive to gas leakage...

  4. A Signal Processing Method to Explore Similarity in Protein Flexibility

    Directory of Open Access Journals (Sweden)

    Simina Vasilache

    2010-01-01

    Full Text Available Understanding mechanisms of protein flexibility is of great importance to structural biology. The ability to detect similarities between proteins and their patterns is vital in discovering new information about unknown protein functions. A Distance Constraint Model (DCM provides a means to generate a variety of flexibility measures based on a given protein structure. Although information about mechanical properties of flexibility is critical for understanding protein function for a given protein, the question of whether certain characteristics are shared across homologous proteins is difficult to assess. For a proper assessment, a quantified measure of similarity is necessary. This paper begins to explore image processing techniques to quantify similarities in signals and images that characterize protein flexibility. The dataset considered here consists of three different families of proteins, with three proteins in each family. The similarities and differences found within flexibility measures across homologous proteins do not align with sequence-based evolutionary methods.

  5. Method for forecasting an earthquake from precursor signals

    International Nuclear Information System (INIS)

    Farnworth, D.F.

    1996-01-01

    A method for forecasting an earthquake from precursor signals by employing characteristic first electromagnetic signals, second, seismically induced electromagnetic signals, seismically induced mechanical signals, and infrasonic acoustic signals which have been observed to precede an earthquake. From a first electromagnetic signal, a magnitude, depth beneath the surface of the earth, distance, latitude, longitude, and first and second forecasts of the time of occurrence of the impending earthquake may be derived. From a second, seismically induced electromagnetic signal and the mechanical signal, third and fourth forecasts of the time of occurrence of an impending earthquake determined from the analysis above, a magnitude, depth beneath the surface of the earth and fourth and fifth forecasts of the time of occurrence of the impending earthquake may be derived. The forecasts of time available from the above analyses range from up to five weeks to substantially within one hour in advance of the earthquake. (author)

  6. A Monte Carlo technique for signal level detection in implanted intracranial pressure monitoring.

    Science.gov (United States)

    Avent, R K; Charlton, J D; Nagle, H T; Johnson, R N

    1987-01-01

    Statistical monitoring techniques like CUSUM, Trigg's tracking signal and EMP filtering have a major advantage over more recent techniques, such as Kalman filtering, because of their inherent simplicity. In many biomedical applications, such as electronic implantable devices, these simpler techniques have greater utility because of the reduced requirements on power, logic complexity and sampling speed. The determination of signal means using some of the earlier techniques are reviewed in this paper, and a new Monte Carlo based method with greater capability to sparsely sample a waveform and obtain an accurate mean value is presented. This technique may find widespread use as a trend detection method when reduced power consumption is a requirement.

  7. Data Fusion to Develop a Driver Drowsiness Detection System with Robustness to Signal Loss

    Directory of Open Access Journals (Sweden)

    Sajjad Samiee

    2014-09-01

    Full Text Available This study proposes a drowsiness detection approach based on the combination of several different detection methods, with robustness to the input signal loss. Hence, if one of the methods fails for any reason, the whole system continues to work properly. To choose correct combination of the available methods and to utilize the benefits of methods of different categories, an image processing-based technique as well as a method based on driver-vehicle interaction is used. In order to avoid driving distraction, any use of an intrusive method is prevented. A driving simulator is used to gather real data and then artificial neural networks are used in the structure of the designed system. Several tests were conducted on twelve volunteers while their sleeping situations during one day prior to the tests, were fully under control. Although the impact of the proposed system on the improvement of the detection accuracy is not remarkable, the results indicate the main advantages of the system are the reliability of the detections and robustness to the loss of the input signals. The high reliability of the drowsiness detection systems plays an important role to reduce drowsiness related road accidents and their associated costs.

  8. How to detect a cuckoo egg : A signal-detection theory model for recognition and learning

    NARCIS (Netherlands)

    Rodriguez-Girones, MA; Lotem, A

    This article presents a model of egg rejection in cases of brood parasitism. The model is developed in three stages in the framework of signal-detection theory. We first assume that the behavior of host females is adapted to the relevant parameters concerning the appearance of the eggs they lay. In

  9. Detecting and Predicting Muscle Fatigue during Typing By SEMG Signal Processing and Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Elham Ghoochani

    2011-03-01

    Full Text Available Introduction: Repetitive strain injuries are one of the most prevalent problems in occupational diseases. Repetition, vibration and bad postures of the extremities are physical risk factors related to work that can cause chronic musculoskeletal disorders. Repetitive work on a computer with low level contraction requires the posture to be maintained for a long time, which can cause muscle fatigue. Muscle fatigue in shoulders and neck is one of the most prevalent problems reported with computer users especially during typing. Surface electromyography (SEMG signals are used for detecting muscle fatigue as a non-invasive method. Material and Methods: Nine healthy females volunteered for signal recoding during typing. EMG signals were recorded from the trapezius muscle, which is subjected to muscle fatigue during typing.  After signal analysis and feature extraction, detecting and predicting muscle fatigue was performed by using the MLP artificial neural network. Results: Recorded signals were analyzed in time and frequency domains for feature extraction. Results of classification showed that the MLP neural network can detect and predict muscle fatigue during typing with 80.79 % ± 1.04% accuracy. Conclusion: Intelligent classification and prediction of muscle fatigue can have many applications in human factors engineering (ergonomics, rehabilitation engineering and biofeedback equipment for mitigating the injuries of repetitive works.

  10. Detection of driving fatigue by using noncontact EMG and ECG signals measurement system.

    Science.gov (United States)

    Fu, Rongrong; Wang, Hong

    2014-05-01

    Driver fatigue can be detected by constructing a discriminant mode using some features obtained from physiological signals. There exist two major challenges of this kind of methods. One is how to collect physiological signals from subjects while they are driving without any interruption. The other is to find features of physiological signals that are of corresponding change with the loss of attention caused by driver fatigue. Driving fatigue is detected based on the study of surface electromyography (EMG) and electrocardiograph (ECG) during the driving period. The noncontact data acquisition system was used to collect physiological signals from the biceps femoris of each subject to tackle the first challenge. Fast independent component analysis (FastICA) and digital filter were utilized to process the original signals. Based on the statistical analysis results given by Kolmogorov-Smirnov Z test, the peak factor of EMG (p fatigue of drivers. The discriminant criterion of fatigue was obtained from the training samples by using Mahalanobis distance, and then the average classification accuracy was given by 10-fold cross-validation. The results showed that the method proposed in this paper can give well performance in distinguishing the normal state and fatigue state. The noncontact, onboard vehicle drivers' fatigue detection system was developed to reduce fatigue-related risks.

  11. Developing a reliable signal wire attachment method for rail.

    Science.gov (United States)

    2014-11-01

    The goal of this project was to develop a better attachment method for rail signal wires to improve the reliability of signaling : systems. EWI conducted basic research into the failure mode of current attachment methods and developed and tested a ne...

  12. A deafening flash! Visual interference of auditory signal detection.

    Science.gov (United States)

    Fassnidge, Christopher; Cecconi Marcotti, Claudia; Freeman, Elliot

    2017-03-01

    In some people, visual stimulation evokes auditory sensations. How prevalent and how perceptually real is this? 22% of our neurotypical adult participants responded 'Yes' when asked whether they heard faint sounds accompanying flash stimuli, and showed significantly better ability to discriminate visual 'Morse-code' sequences. This benefit might arise from an ability to recode visual signals as sounds, thus taking advantage of superior temporal acuity of audition. In support of this, those who showed better visual relative to auditory sequence discrimination also had poorer auditory detection in the presence of uninformative visual flashes, though this was independent of awareness of visually-evoked sounds. Thus a visually-evoked auditory representation may occur subliminally and disrupt detection of real auditory signals. The frequent natural correlation between visual and auditory stimuli might explain the surprising prevalence of this phenomenon. Overall, our results suggest that learned correspondences between strongly correlated modalities may provide a precursor for some synaesthetic abilities. Copyright © 2016 Elsevier Inc. All rights reserved.

  13. Suggestibility and signal detection performance in hallucination-prone students.

    Science.gov (United States)

    Alganami, Fatimah; Varese, Filippo; Wagstaff, Graham F; Bentall, Richard P

    2017-03-01

    Auditory hallucinations are associated with signal detection biases. We examine the extent to which suggestions influence performance on a signal detection task (SDT) in highly hallucination-prone and low hallucination-prone students. We also explore the relationship between trait suggestibility, dissociation and hallucination proneness. In two experiments, students completed on-line measures of hallucination proneness (the revised Launay-Slade Hallucination Scale; LSHS-R), trait suggestibility (Inventory of Suggestibility) and dissociation (Dissociative Experiences Scale-II). Students in the upper and lower tertiles of the LSHS-R performed an auditory SDT. Prior to the task, suggestions were made pertaining to the number of expected targets (Experiment 1, N = 60: high vs. low suggestions; Experiment 2, N = 62, no suggestion vs. high suggestion vs. no voice suggestion). Correlational and regression analyses indicated that trait suggestibility and dissociation predicted hallucination proneness. Highly hallucination-prone students showed a higher SDT bias in both studies. In Experiment 1, both bias scores were significantly affected by suggestions to the same degree. In Experiment 2, highly hallucination-prone students were more reactive to the high suggestion condition than the controls. Suggestions may affect source-monitoring judgments, and this effect may be greater in those who have a predisposition towards hallucinatory experiences.

  14. Automatic Threshold Determination for a Local Approach of Change Detection in Long-Term Signal Recordings

    Directory of Open Access Journals (Sweden)

    David Hewson

    2007-01-01

    Full Text Available CUSUM (cumulative sum is a well-known method that can be used to detect changes in a signal when the parameters of this signal are known. This paper presents an adaptation of the CUSUM-based change detection algorithms to long-term signal recordings where the various hypotheses contained in the signal are unknown. The starting point of the work was the dynamic cumulative sum (DCS algorithm, previously developed for application to long-term electromyography (EMG recordings. DCS has been improved in two ways. The first was a new procedure to estimate the distribution parameters to ensure the respect of the detectability property. The second was the definition of two separate, automatically determined thresholds. One of them (lower threshold acted to stop the estimation process, the other one (upper threshold was applied to the detection function. The automatic determination of the thresholds was based on the Kullback-Leibler distance which gives information about the distance between the detected segments (events. Tests on simulated data demonstrated the efficiency of these improvements of the DCS algorithm.

  15. Using the PLUM procedure of SPSS to fit unequal variance and generalized signal detection models.

    Science.gov (United States)

    DeCarlo, Lawrence T

    2003-02-01

    The recent addition of aprocedure in SPSS for the analysis of ordinal regression models offers a simple means for researchers to fit the unequal variance normal signal detection model and other extended signal detection models. The present article shows how to implement the analysis and how to interpret the SPSS output. Examples of fitting the unequal variance normal model and other generalized signal detection models are given. The approach offers a convenient means for applying signal detection theory to a variety of research.

  16. A novel signal compression method based on optimal ensemble empirical mode decomposition for bearing vibration signals

    Science.gov (United States)

    Guo, Wei; Tse, Peter W.

    2013-01-01

    Today, remote machine condition monitoring is popular due to the continuous advancement in wireless communication. Bearing is the most frequently and easily failed component in many rotating machines. To accurately identify the type of bearing fault, large amounts of vibration data need to be collected. However, the volume of transmitted data cannot be too high because the bandwidth of wireless communication is limited. To solve this problem, the data are usually compressed before transmitting to a remote maintenance center. This paper proposes a novel signal compression method that can substantially reduce the amount of data that need to be transmitted without sacrificing the accuracy of fault identification. The proposed signal compression method is based on ensemble empirical mode decomposition (EEMD), which is an effective method for adaptively decomposing the vibration signal into different bands of signal components, termed intrinsic mode functions (IMFs). An optimization method was designed to automatically select appropriate EEMD parameters for the analyzed signal, and in particular to select the appropriate level of the added white noise in the EEMD method. An index termed the relative root-mean-square error was used to evaluate the decomposition performances under different noise levels to find the optimal level. After applying the optimal EEMD method to a vibration signal, the IMF relating to the bearing fault can be extracted from the original vibration signal. Compressing this signal component obtains a much smaller proportion of data samples to be retained for transmission and further reconstruction. The proposed compression method were also compared with the popular wavelet compression method. Experimental results demonstrate that the optimization of EEMD parameters can automatically find appropriate EEMD parameters for the analyzed signals, and the IMF-based compression method provides a higher compression ratio, while retaining the bearing defect

  17. Amplitude-aware permutation entropy: Illustration in spike detection and signal segmentation.

    Science.gov (United States)

    Azami, Hamed; Escudero, Javier

    2016-05-01

    Signal segmentation and spike detection are two important biomedical signal processing applications. Often, non-stationary signals must be segmented into piece-wise stationary epochs or spikes need to be found among a background of noise before being further analyzed. Permutation entropy (PE) has been proposed to evaluate the irregularity of a time series. PE is conceptually simple, structurally robust to artifacts, and computationally fast. It has been extensively used in many applications, but it has two key shortcomings. First, when a signal is symbolized using the Bandt-Pompe procedure, only the order of the amplitude values is considered and information regarding the amplitudes is discarded. Second, in the PE, the effect of equal amplitude values in each embedded vector is not addressed. To address these issues, we propose a new entropy measure based on PE: the amplitude-aware permutation entropy (AAPE). AAPE is sensitive to the changes in the amplitude, in addition to the frequency, of the signals thanks to it being more flexible than the classical PE in the quantification of the signal motifs. To demonstrate how the AAPE method can enhance the quality of the signal segmentation and spike detection, a set of synthetic and realistic synthetic neuronal signals, electroencephalograms and neuronal data are processed. We compare the performance of AAPE in these problems against state-of-the-art approaches and evaluate the significance of the differences with a repeated ANOVA with post hoc Tukey's test. In signal segmentation, the accuracy of AAPE-based method is higher than conventional segmentation methods. AAPE also leads to more robust results in the presence of noise. The spike detection results show that AAPE can detect spikes well, even when presented with single-sample spikes, unlike PE. For multi-sample spikes, the changes in AAPE are larger than in PE. We introduce a new entropy metric, AAPE, that enables us to consider amplitude information in the

  18. Nuclear pulse signal processing techniques based on blind deconvolution method

    International Nuclear Information System (INIS)

    Hong Pengfei; Yang Lei; Qi Zhong; Meng Xiangting; Fu Yanyan; Li Dongcang

    2012-01-01

    This article presents a method of measurement and analysis of nuclear pulse signal, the FPGA to control high-speed ADC measurement of nuclear radiation signals and control the high-speed transmission status of the USB to make it work on the Slave FIFO mode, using the LabVIEW online data processing and display, using the blind deconvolution method to remove the accumulation of signal acquisition, and to restore the nuclear pulse signal with a transmission speed, real-time measurements show that the advantages. (authors)

  19. Improved GLR method to instrument failure detection

    International Nuclear Information System (INIS)

    Jeong, Hak Yeoung; Chang, Soon Heung

    1985-01-01

    The generalized likehood radio(GLR) method performs statistical tests on the innovations sequence of a Kalman-Buchy filter state estimator for system failure detection and its identification. However, the major drawback of the convensional GLR is to hypothesize particular failure type in each case. In this paper, a method to solve this drawback is proposed. The improved GLR method is applied to a PWR pressurizer and gives successful results in detection and identification of any failure. Furthmore, some benefit on the processing time per each cycle of failure detection and its identification can be accompanied. (Author)

  20. Implication of two-coupled differential Van der Pol Duffing oscillator in weak signal detection

    International Nuclear Information System (INIS)

    Peng Hanghang; Xu Xuemei; Yang Bingchu; Yin Linzi

    2016-01-01

    The principle of the Van der Pol Duffing oscillator for state transition and for determining critical value is described, which has been studied to indicate that the application of the Van der Pol Duffing oscillator in weak signal detection is feasible. On the basis of this principle, an improved two-coupled differential Van der Pol Duffing oscillator is proposed which can identify signals under any frequency and ameliorate signal-to-noise ratio (SNR). The analytical methods of the proposed model and the construction of the proposed oscillator are introduced in detail. Numerical experiments on the properties of the proposed oscillator compared with those of the Van der Pol Duffing oscillator are carried out. Our numerical simulations have confirmed the analytical treatment. The results demonstrate that this novel oscillator has better detection performance than the Van der Pol Duffing oscillator. (author)

  1. Implication of Two-Coupled Differential Van der Pol Duffing Oscillator in Weak Signal Detection

    Science.gov (United States)

    Peng, Hang-hang; Xu, Xue-mei; Yang, Bing-chu; Yin, Lin-zi

    2016-04-01

    The principle of the Van der Pol Duffing oscillator for state transition and for determining critical value is described, which has been studied to indicate that the application of the Van der Pol Duffing oscillator in weak signal detection is feasible. On the basis of this principle, an improved two-coupled differential Van der Pol Duffing oscillator is proposed which can identify signals under any frequency and ameliorate signal-to-noise ratio (SNR). The analytical methods of the proposed model and the construction of the proposed oscillator are introduced in detail. Numerical experiments on the properties of the proposed oscillator compared with those of the Van der Pol Duffing oscillator are carried out. Our numerical simulations have confirmed the analytical treatment. The results demonstrate that this novel oscillator has better detection performance than the Van der Pol Duffing oscillator.

  2. Coherence method of identifying signal noise model

    International Nuclear Information System (INIS)

    Vavrin, J.

    1981-01-01

    The noise analysis method is discussed in identifying perturbance models and their parameters by a stochastic analysis of the noise model of variables measured on a reactor. The analysis of correlations is made in the frequency region using coherence analysis methods. In identifying an actual specific perturbance, its model should be determined and recognized in a compound model of the perturbance system using the results of observation. The determination of the optimum estimate of the perturbance system model is based on estimates of related spectral densities which are determined from the spectral density matrix of the measured variables. Partial and multiple coherence, partial transfers, the power spectral densities of the input and output variables of the noise model are determined from the related spectral densities. The possibilities of applying the coherence identification methods were tested on a simple case of a simulated stochastic system. Good agreement was found of the initial analytic frequency filters and the transfers identified. (B.S.)

  3. Bilinear Time-frequency Analysis for Lamb Wave Signal Detected by Electromagnetic Acoustic Transducer

    Science.gov (United States)

    Sun, Wenxiu; Liu, Guoqiang; Xia, Hui; Xia, Zhengwu

    2018-03-01

    Accurate acquisition of the detection signal travel time plays a very important role in cross-hole tomography. The experimental platform of aluminum plate under the perpendicular magnetic field is established and the bilinear time-frequency analysis methods, Wigner-Ville Distribution (WVD) and the pseudo-Wigner-Ville distribution (PWVD), are applied to analyse the Lamb wave signals detected by electromagnetic acoustic transducer (EMAT). By extracting the same frequency component of the time-frequency spectrum as the excitation frequency, the travel time information can be obtained. In comparison with traditional linear time-frequency analysis method such as short-time Fourier transform (STFT), the bilinear time-frequency analysis method PWVD is more appropriate in extracting travel time and recognizing patterns of Lamb wave.

  4. GMDD: a database of GMO detection methods.

    Science.gov (United States)

    Dong, Wei; Yang, Litao; Shen, Kailin; Kim, Banghyun; Kleter, Gijs A; Marvin, Hans J P; Guo, Rong; Liang, Wanqi; Zhang, Dabing

    2008-06-04

    Since more than one hundred events of genetically modified organisms (GMOs) have been developed and approved for commercialization in global area, the GMO analysis methods are essential for the enforcement of GMO labelling regulations. Protein and nucleic acid-based detection techniques have been developed and utilized for GMOs identification and quantification. However, the information for harmonization and standardization of GMO analysis methods at global level is needed. GMO Detection method Database (GMDD) has collected almost all the previous developed and reported GMOs detection methods, which have been grouped by different strategies (screen-, gene-, construct-, and event-specific), and also provide a user-friendly search service of the detection methods by GMO event name, exogenous gene, or protein information, etc. In this database, users can obtain the sequences of exogenous integration, which will facilitate PCR primers and probes design. Also the information on endogenous genes, certified reference materials, reference molecules, and the validation status of developed methods is included in this database. Furthermore, registered users can also submit new detection methods and sequences to this database, and the newly submitted information will be released soon after being checked. GMDD contains comprehensive information of GMO detection methods. The database will make the GMOs analysis much easier.

  5. Fuel failure detection and location methods in CAGRs

    International Nuclear Information System (INIS)

    Harris, A.M.

    1982-06-01

    The release of fission products from AGR fuel failures and the way in which the signals from such failures must be detected against the background signal from uranium contamination of the fuel is considered. Theoretical assessments of failure detection are used to show the limitations of the existing Electrostatic Wire Precipitator Burst Can Detection system (BCD) and how its operating parameters can be optimised. Two promising alternative methods, the 'split count' technique and the use of iodine measurements, are described. The results of a detailed study of the mechanical and electronic performance of the present BCD trolleys are given. The limited experience of detection and location of two fuel failures in CAGR using conventional and alternative methods is reviewed. The larger failure was detected and located using the conventional BCD equipment with a high confidence level. It is shown that smaller failures may not be easy to detect and locate using the current BCD equipment, and the second smaller failure probably remained in the reactor for about a year before it was discharged. The split count technique used with modified BCD equipment was able to detect the smaller failure after careful inspection of the data. (author)

  6. Detection of early warning signals of forest mortality in California

    Science.gov (United States)

    Liu, Y.; Kumar, M.; Katul, G. G.; Porporato, A. M.

    2017-12-01

    Massive forest mortality was observed in California during the most recent drought. Owing to complex interactions of physiological mechanisms under stress, prediction of climate-induced forest mortality using dynamic global vegetation models remains fraught with uncertainty. Given that forest ecosystems approaching mortality tend to exhibit reduction in resilience, we evaluate the time-varying resilience from time series of satellite images to detect early warning signals (EWSs) of mortality. Four metrics of EWSs are used: (1) low greenness, (2) high empirical autocorrelation of greenness, (3) high autocorrelation inferred using a Bayesian dynamic linear model considering the influence of seasonality and climate conditions, and (4) low recovery rate inferred from the drift term in the Langevin equation describing stochastic dynamics. Spatial accuracy and lead-time of these EWSs are evaluated by comparing the EWSs against observed mortality from aerial surveys conducted by the US Forest Service. Our results show that most forested areas in California that underwent mortality exhibit a EWS with a lead time of three months to two years ahead of observed mortality. Notably, EWS is also detected in some areas without mortality, suggesting reduced resilience during drought. Furthermore, the influence of the previous drought (2007-2009) may have propagated into the recent drought (2012-2016) through reduced resilience, hence contributing to the massive forest mortality observed recently. Methodologies developed in this study for detection of EWS will improve the near-term predictability of forest mortality, thus providing crucial information for forest and water resource management.

  7. Correntropy measures to detect daytime sleepiness from EEG signals

    International Nuclear Information System (INIS)

    Melia, Umberto; Vallverdú, Montserrat; Caminal, Pere; Guaita, Marc; Montserrat, Josep M; Vilaseca, Isabel; Salamero, Manel; Gaig, Carles; Santamaria, Joan

    2014-01-01

    Excessive daytime sleepiness (EDS) is one of the main symptoms of several sleep related disorders and has a great impact on patients’ lives. While many studies have been carried out in order to assess daytime sleepiness, automatic EDS detection still remains an open problem. In this work, a novel approach to this issue based on correntropy function analysis of EEG signals was proposed in order to detect patients suffering from EDS. Multichannel EEG signals were recorded during five Maintenance of Wakefulness Tests (MWT) and Multiple Sleep Latency Tests (MSLT) alternated throughout the day for patients suffering from sleep disordered breathing (SDB). A group of 20 patients with EDS was compared with a group of 20 patients without daytime sleepiness (WDS), by analyzing 60 s EEG windows in a waking state. Measures obtained from the cross-correntropy function (CCORR) and auto-correntropy function (ACORR) were calculated in the EEG frequency bands: δ, 0.1–4 Hz; θ, 4–8 Hz; α, 8–12 Hz; β, 12–30 Hz; total band TB, 0.1–45 Hz. These functions permitted the quantification of complex signal properties and the non-linear couplings between different areas of the scalp. Statistical differences between EDS and WDS groups were mainly found in the β band during MSLT events (p-value < 0.0001). The WDS group presented more complexity in the occipital zone than the EDS group, while a stronger nonlinear coupling between the occipital and frontal regions was detected in EDS patients than in the WDS group. At best, ACORR and CCORR measures yielded sensitivity and specificity above 80% and the area under ROC curve (AUC) was above 0.85 in classifying EDS and WDS patients. These performances represent an improvement with respect to classical EEG indices applied in the same database (sensitivity and specificity were never above 80% and AUC was under 0.75). (paper)

  8. Detection of auditory signals in quiet and noisy backgrounds while performing a visuo-spatial task

    Directory of Open Access Journals (Sweden)

    Vishakha W Rawool

    2016-01-01

    Full Text Available Context: The ability to detect important auditory signals while performing visual tasks may be further compounded by background chatter. Thus, it is important to know how task performance may interact with background chatter to hinder signal detection. Aim: To examine any interactive effects of speech spectrum noise and task performance on the ability to detect signals. Settings and Design: The setting was a sound-treated booth. A repeated measures design was used. Materials and Methods: Auditory thresholds of 20 normal adults were determined at 0.5, 1, 2 and 4 kHz in the following conditions presented in a random order: (1 quiet with attention; (2 quiet with a visuo-spatial task or puzzle (distraction; (3 noise with attention and (4 noise with task. Statistical Analysis: Multivariate analyses of variance (MANOVA with three repeated factors (quiet versus noise, visuo-spatial task versus no task, signal frequency. Results: MANOVA revealed significant main effects for noise and signal frequency and significant noise–frequency and task–frequency interactions. Distraction caused by performing the task worsened the thresholds for tones presented at the beginning of the experiment and had no effect on tones presented in the middle. At the end of the experiment, thresholds (4 kHz were better while performing the task than those obtained without performing the task. These effects were similar across the quiet and noise conditions. Conclusion: Detection of auditory signals is difficult at the beginning of a distracting visuo-spatial task but over time, task learning and auditory training effects can nullify the effect of distraction and may improve detection of high frequency sounds.

  9. Feature Optimize and Classification of EEG Signals: Application to Lie Detection Using KPCA and ELM

    Directory of Open Access Journals (Sweden)

    GAO Junfeng

    2014-04-01

    Full Text Available EEG signals had been widely used to detect liars recent years. To overcome the shortcomings of current signals processing, kernel principal component analysis (KPCA and extreme learning machine (ELM was combined to detect liars. We recorded the EEG signals at Pz from 30 randomly divided guilty and innocent subjects. Each five Probe responses were averaged within subject and then extracted wavelet features. KPCA was employed to select feature subset with deduced dimensions based on initial wavelet features, which was fed into ELM. To date, there is no perfect solution for the number of its hidden nodes (NHN. We used grid searching algorithm to select simultaneously the optimal values of the dimension of feature subset and NHN based on cross- validation method. The best classification mode was decided with the optimal searching values. Experimental results show that for EEG signals from the experiment of lie detection, KPCA_ELM has higher classification accuracy with faster training speed than other widely-used classification modes, which is especially suitable for online EEG signals processing system.

  10. A non-linear algorithm for current signal filtering and peak detection in SiPM

    International Nuclear Information System (INIS)

    Putignano, M; Intermite, A; Welsch, C P

    2012-01-01

    Read-out of Silicon Photomultipliers is commonly achieved by means of charge integration, a method particularly susceptible to after-pulsing noise and not efficient for low level light signals. Current signal monitoring, characterized by easier electronic implementation and intrinsically faster than charge integration, is also more suitable for low level light signals and can potentially result in much decreased after-pulsing noise effects. However, its use is to date limited by the need of developing a suitable read-out algorithm for signal analysis and filtering able to achieve current peak detection and measurement with the needed precision and accuracy. In this paper we present an original algorithm, based on a piecewise linear-fitting approach, to filter the noise of the current signal and hence efficiently identifying and measuring current peaks. The proposed algorithm is then compared with the optimal linear filtering algorithm for time-encoded peak detection, based on a moving average routine, and assessed in terms of accuracy, precision, and peak detection efficiency, demonstrating improvements of 1÷2 orders of magnitude in all these quality factors.

  11. Method of detecting genetic deletions identified with chromosomal abnormalities

    Energy Technology Data Exchange (ETDEWEB)

    Gray, Joe W; Pinkel, Daniel; Tkachuk, Douglas

    2013-11-26

    Methods and compositions for staining based upon nucleic acid sequence that employ nucleic acid probes are provided. Said methods produce staining patterns that can be tailored for specific cytogenetic analyzes. Said probes are appropriate for in situ hybridization and stain both interphase and metaphase chromosomal material with reliable signals. The nucleic acids probes are typically of a complexity greater tha 50 kb, the complexity depending upon the cytogenetic application. Methods and reagents are provided for the detection of genetic rearrangements. Probes and test kits are provided for use in detecting genetic rearrangements, particlularly for use in tumor cytogenetics, in the detection of disease related loci, specifically cancer, such as chronic myelogenous leukemia (CML) and for biological dosimetry. Methods and reagents are described for cytogenetic research, for the differentiation of cytogenetically similar ut genetically different diseases, and for many prognostic and diagnostic applications.

  12. GC ‘Multi-Analyte’ Detection Method

    Energy Technology Data Exchange (ETDEWEB)

    Dudar, E. [Plant Protection & Soil Conservation Service of Budapest, Budapest (Hungary)

    2009-07-15

    Elaborated methodologies for GC multi-analyte detection are presented, comprising the steps of method development, chromatographic conditions and procedures including the determination of relative retention times and summary results tables. (author)

  13. Infrasonic detection performance in presence of nuisance signal

    Science.gov (United States)

    Charbit, Maurice; Arrowsmith, Stephen; Che, Il-young; Le Pichon, Alexis; Nouvellet, Adrien; Park, Junghyun; Roueff, Francois

    2014-05-01

    The infrasound network of the International Monitoring System (IMS) consists of sixty stations deployed all over the World by the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO). The IMS has been designed to reliably detect, at least by two stations, an explosion greater than 1 kiloton located anywhere on the Earth [1]. Each station is an array of at least four microbarometers with an aperture of 1 to 3 km. The first important issue is to detect the presence of the signal of interest (SOI) embedded in noise. The detector is commonly based on the property that the SOI provides coherent observations on the sensors but not the noise. The statistic of test, called F-stat [2], [5], [6] , calculated in a time cell a few seconds, is commonly used for this purpose. In this paper, we assume that a coherent source is permanently present arriving from an unknown direction of arrivals (DOA). The typical case is the presence of microbaroms or the presence of wind. This source is seen as a nuisance signal (NS). In [4], [3] authors assume that a time cell without the SOI (CH0) is available, whereas a following time cell is considered as the cell under test (CUT). Therefore the DOA and the SNR of the NS can be estimated. If the signal-to-noise ration SNR of the NS is large enough, the distribution of the F-stat under the absence of SOI is known to be a non central Fisher. It follows that the threshold can be performed from a given value of the FAR. The major drawback to keep the NS is that the NS could hide the SOI, this phenomena is similar to the leakage which is a well-known phenomena in the Fourier analysis. An other approach consists to use the DOA estimate of the NS to mitigate the NS by spatial notch filter in the frequency domain. On this approach a new algorithm is provided. To illustrate, numerical results on synthetical and real data are presented, in term of Receiver Operating Characteristic ROC curves. REFERENCES [1] Christie D.R. and Campus P., The IMS

  14. Detecting malicious chaotic signals in wireless sensor network

    Science.gov (United States)

    Upadhyay, Ranjit Kumar; Kumari, Sangeeta

    2018-02-01

    In this paper, an e-epidemic Susceptible-Infected-Vaccinated (SIV) model has been proposed to analyze the effect of node immunization and worms attacking dynamics in wireless sensor network. A modified nonlinear incidence rate with cyrtoid type functional response has been considered using sleep and active mode approach. Detailed stability analysis and the sufficient criteria for the persistence of the model system have been established. We also established different types of bifurcation analysis for different equilibria at different critical points of the control parameters. We performed a detailed Hopf bifurcation analysis and determine the direction and stability of the bifurcating periodic solutions using center manifold theorem. Numerical simulations are carried out to confirm the theoretical results. The impact of the control parameters on the dynamics of the model system has been investigated and malicious chaotic signals are detected. Finally, we have analyzed the effect of time delay on the dynamics of the model system.

  15. EUROmediCAT signal detection: an evaluation of selected congenital anomaly‐medication associations

    Science.gov (United States)

    Given, Joanne E.; Loane, Maria; Luteijn, Johannes M.; Morris, Joan K.; de Jong van den Berg, Lolkje T.W.; Garne, Ester; Addor, Marie‐Claude; Barisic, Ingeborg; de Walle, Hermien; Gatt, Miriam; Klungsoyr, Kari; Khoshnood, Babak; Latos‐Bielenska, Anna; Nelen, Vera; Neville, Amanda J.; O'Mahony, Mary; Pierini, Anna; Tucker, David; Wiesel, Awi

    2016-01-01

    Aims To evaluate congenital anomaly (CA)‐medication exposure associations produced by the new EUROmediCAT signal detection system and determine which require further investigation. Methods Data from 15 EUROCAT registries (1995–2011) with medication exposures at the chemical substance (5th level of Anatomic Therapeutic Chemical classification) and chemical subgroup (4th level) were analysed using a 50% false detection rate. After excluding antiepileptics, antidiabetics, antiasthmatics and SSRIs/psycholeptics already under investigation, 27 associations were evaluated. If evidence for a signal persisted after data validation, a literature review was conducted for prior evidence of human teratogenicity. Results Thirteen out of 27 CA‐medication exposure signals, based on 389 exposed cases, passed data validation. There was some prior evidence in the literature to support six signals (gastroschisis and levonorgestrel/ethinylestradiol (OR 4.10, 95% CI 1.70–8.53; congenital heart disease/pulmonary valve stenosis and nucleoside/tide reverse transcriptase inhibitors (OR 5.01, 95% CI 1.99–14.20/OR 28.20, 95% CI 4.63–122.24); complete absence of a limb and pregnen (4) derivatives (OR 6.60, 95% CI 1.70–22.93); hypospadias and pregnadien derivatives (OR 1.40, 95% CI 1.10–1.76); hypospadias and synthetic ovulation stimulants (OR 1.89, 95% CI 1.28–2.70). Antipropulsives produced a signal for syndactyly while the literature revealed a signal for hypospadias. There was no prior evidence to support the remaining six signals involving the ordinary salt combinations, propulsives, bulk‐forming laxatives, hydrazinophthalazine derivatives, gonadotropin releasing hormone analogues and selective serotonin agonists. Conclusion Signals which strengthened prior evidence should be prioritized for further investigation, and independent evidence sought to confirm the remaining signals. Some chance associations are expected and confounding by indication is possible. PMID

  16. High efficiency processing for reduced amplitude zones detection in the HRECG signal

    Science.gov (United States)

    Dugarte, N.; Álvarez, A.; Balacco, J.; Mercado, G.; Gonzalez, A.; Dugarte, E.; Olivares, A.

    2016-04-01

    Summary - This article presents part of a more detailed research proposed in the medium to long term, with the intention of establishing a new philosophy of electrocardiogram surface analysis. This research aims to find indicators of cardiovascular disease in its early stage that may go unnoticed with conventional electrocardiography. This paper reports the development of a software processing which collect some existing techniques and incorporates novel methods for detection of reduced amplitude zones (RAZ) in high resolution electrocardiographic signal (HRECG).The algorithm consists of three stages, an efficient processing for QRS detection, averaging filter using correlation techniques and a step for RAZ detecting. Preliminary results show the efficiency of system and point to incorporation of techniques new using signal analysis with involving 12 leads.

  17. Detecting Parkinson's disease from sustained phonation and speech signals.

    Directory of Open Access Journals (Sweden)

    Evaldas Vaiciukynas

    Full Text Available This study investigates signals from sustained phonation and text-dependent speech modalities for Parkinson's disease screening. Phonation corresponds to the vowel /a/ voicing task and speech to the pronunciation of a short sentence in Lithuanian language. Signals were recorded through two channels simultaneously, namely, acoustic cardioid (AC and smart phone (SP microphones. Additional modalities were obtained by splitting speech recording into voiced and unvoiced parts. Information in each modality is summarized by 18 well-known audio feature sets. Random forest (RF is used as a machine learning algorithm, both for individual feature sets and for decision-level fusion. Detection performance is measured by the out-of-bag equal error rate (EER and the cost of log-likelihood-ratio. Essentia audio feature set was the best using the AC speech modality and YAAFE audio feature set was the best using the SP unvoiced modality, achieving EER of 20.30% and 25.57%, respectively. Fusion of all feature sets and modalities resulted in EER of 19.27% for the AC and 23.00% for the SP channel. Non-linear projection of a RF-based proximity matrix into the 2D space enriched medical decision support by visualization.

  18. Automated embolic signal detection using Deep Convolutional Neural Network.

    Science.gov (United States)

    Sombune, Praotasna; Phienphanich, Phongphan; Phuechpanpaisal, Sutanya; Muengtaweepongsa, Sombat; Ruamthanthong, Anuchit; Tantibundhit, Charturong

    2017-07-01

    This work investigated the potential of Deep Neural Network in detection of cerebral embolic signal (ES) from transcranial Doppler ultrasound (TCD). The resulting system is aimed to couple with TCD devices in diagnosing a risk of stroke in real-time with high accuracy. The Adaptive Gain Control (AGC) approach developed in our previous study is employed to capture suspected ESs in real-time. By using spectrograms of the same TCD signal dataset as that of our previous work as inputs and the same experimental setup, Deep Convolutional Neural Network (CNN), which can learn features while training, was investigated for its ability to bypass the traditional handcrafted feature extraction and selection process. Extracted feature vectors from the suspected ESs are later determined whether they are of an ES, artifact (AF) or normal (NR) interval. The effectiveness of the developed system was evaluated over 19 subjects going under procedures generating emboli. The CNN-based system could achieve in average of 83.0% sensitivity, 80.1% specificity, and 81.4% accuracy, with considerably much less time consumption in development. The certainly growing set of training samples and computational resources will contribute to high performance. Besides having potential use in various clinical ES monitoring settings, continuation of this promising study will benefit developments of wearable applications by leveraging learnable features to serve demographic differentials.

  19. Customized Multiwavelets for Planetary Gearbox Fault Detection Based on Vibration Sensor Signals

    Directory of Open Access Journals (Sweden)

    Lue Chen

    2013-01-01

    Full Text Available Planetary gearboxes exhibit complicated dynamic responses which are more difficult to detect in vibration signals than fixed-axis gear trains because of the special gear transmission structures. Diverse advanced methods have been developed for this challenging task to reduce or avoid unscheduled breakdown and catastrophic accidents. It is feasible to make fault features distinct by using multiwavelet denoising which depends on the feature separation and the threshold denoising. However, standard and fixed multiwavelets are not suitable for accurate fault feature detections because they are usually independent of the measured signals. To overcome this drawback, a method to construct customized multiwavelets based on the redundant symmetric lifting scheme is proposed in this paper. A novel indicator which combines kurtosis and entropy is applied to select the optimal multiwavelets, because kurtosis is sensitive to sharp impulses and entropy is effective for periodic impulses. The improved neighboring coefficients method is introduced into multiwavelet denoising. The vibration signals of a planetary gearbox from a satellite communication antenna on a measurement ship are captured under various motor speeds. The results show the proposed method could accurately detect the incipient pitting faults on two neighboring teeth in the planetary gearbox.

  20. A Channelization-Based DOA Estimation Method for Wideband Signals

    Directory of Open Access Journals (Sweden)

    Rui Guo

    2016-07-01

    Full Text Available In this paper, we propose a novel direction of arrival (DOA estimation method for wideband signals with sensor arrays. The proposed method splits the wideband array output into multiple frequency sub-channels and estimates the signal parameters using a digital channelization receiver. Based on the output sub-channels, a channelization-based incoherent signal subspace method (Channelization-ISM and a channelization-based test of orthogonality of projected subspaces method (Channelization-TOPS are proposed. Channelization-ISM applies narrowband signal subspace methods on each sub-channel independently. Then the arithmetic mean or geometric mean of the estimated DOAs from each sub-channel gives the final result. Channelization-TOPS measures the orthogonality between the signal and the noise subspaces of the output sub-channels to estimate DOAs. The proposed channelization-based method isolates signals in different bandwidths reasonably and improves the output SNR. It outperforms the conventional ISM and TOPS methods on estimation accuracy and dynamic range, especially in real environments. Besides, the parallel processing architecture makes it easy to implement on hardware. A wideband digital array radar (DAR using direct wideband radio frequency (RF digitization is presented. Experiments carried out in a microwave anechoic chamber with the wideband DAR are presented to demonstrate the performance. The results verify the effectiveness of the proposed method.

  1. Electromagnetic modeling method for eddy current signal analysis

    International Nuclear Information System (INIS)

    Lee, D. H.; Jung, H. K.; Cheong, Y. M.; Lee, Y. S.; Huh, H.; Yang, D. J.

    2004-10-01

    An electromagnetic modeling method for eddy current signal analysis is necessary before an experiment is performed. Electromagnetic modeling methods consists of the analytical method and the numerical method. Also, the numerical methods can be divided by Finite Element Method(FEM), Boundary Element Method(BEM) and Volume Integral Method(VIM). Each modeling method has some merits and demerits. Therefore, the suitable modeling method can be chosen by considering the characteristics of each modeling. This report explains the principle and application of each modeling method and shows the comparison modeling programs

  2. Steam leak detection in advance reactors via acoustics method

    International Nuclear Information System (INIS)

    Singh, Raj Kumar; Rao, A. Rama

    2011-01-01

    Highlights: → Steam leak detection system is developed to detect any leak inside the reactor vault. → The technique uses leak noise frequency spectrum for leak detection. → Testing of system and method to locate the leak is also developed and discussed in present paper. - Abstract: Prediction of LOCA (loss of coolant activity) plays very important role in safety of nuclear reactor. Coolant is responsible for heat transfer from fuel bundles. Loss of coolant is an accidental situation which requires immediate shut down of reactor. Fall in system pressure during LOCA is the trip parameter used for initiating automatic reactor shut down. However, in primary heat transport system operating in two phase regimes, detection of small break LOCA is not simple. Due to very slow leak rates, time for the fall of pressure is significantly slow. From reactor safety point of view, it is extremely important to find reliable and effective alternative for detecting slow pressure drop in case of small break LOCA. One such technique is the acoustic signal caused by LOCA in small breaks. In boiling water reactors whose primary heat transport is to be driven by natural circulation, small break LOCA detection is important. For prompt action on post small break LOCA, steam leak detection system is developed to detect any leak inside the reactor vault. The detection technique is reliable and plays a very important role in ensuring safety of the reactor. Methodology developed for steam leak detection is discussed in present paper. The methods to locate the leak is also developed and discussed in present paper which is based on analysis of the signal.

  3. A Detection Algorithm for the BOC Signal Based on Quadrature Channel Correlation

    Directory of Open Access Journals (Sweden)

    Bo Qian

    2018-01-01

    Full Text Available In order to solve the problem of detecting a BOC signal, which uses a long-period pseudo random sequence, an algorithm is presented based on quadrature channel correlation. The quadrature channel correlation method eliminates the autocorrelation component of the carrier wave, allowing for the extraction of the absolute autocorrelation peaks of the BOC sequence. If the same lag difference and height difference exist for the adjacent peaks, the BOC signal can be detected effectively using a statistical analysis of the multiple autocorrelation peaks. The simulation results show that the interference of the carrier wave component is eliminated and the autocorrelation peaks of the BOC sequence are obtained effectively without demodulation. The BOC signal can be detected effectively when the SNR is greater than −12 dB. The detection ability can be improved further by increasing the number of sampling points. The higher the ratio of the square wave subcarrier speed to the pseudo random sequence speed is, the greater the detection ability is with a lower SNR. The algorithm presented in this paper is superior to the algorithm based on the spectral correlation.

  4. Quench detection/protection of an HTS coil by AE signals

    International Nuclear Information System (INIS)

    Yoneda, M.; Nanato, N.; Aoki, D.; Kato, T.; Murase, S.

    2011-01-01

    A quench detection/protection system based on measuring AE signals was developed. The system was tested for a Bi2223 coil. Temperature rise after a quench occurrence was restrained at very low value. The normal zone propagation velocities in high T c superconductors are slow at high operation temperature and therefore local and excessive temperature rise generates at quench occurrence, and then the superconductors are degraded or burned. Therefore it is essential to detect the temperature rise in high T c superconducting (HTS) coils as soon as possible and protect them. The authors have presented a quench detection method for HTS coils by time-frequency visualization of AE signals and have shown its usefulness for a HTS coil with height and outer diameter of 40-50 mm. In this paper, the authors present a quench detection/protection system based on superior method in quench detection time to the previous method and show its usefulness for a larger HTS coil (height and outer diameter: 160-190 mm) than the previous coil.

  5. DETECT: a MATLAB toolbox for event detection and identification in time series, with applications to artifact detection in EEG signals.

    Science.gov (United States)

    Lawhern, Vernon; Hairston, W David; Robbins, Kay

    2013-01-01

    Recent advances in sensor and recording technology have allowed scientists to acquire very large time-series datasets. Researchers often analyze these datasets in the context of events, which are intervals of time where the properties of the signal change relative to a baseline signal. We have developed DETECT, a MATLAB toolbox for detecting event time intervals in long, multi-channel time series. Our primary goal is to produce a toolbox that is simple for researchers to use, allowing them to quickly train a model on multiple classes of events, assess the accuracy of the model, and determine how closely the results agree with their own manual identification of events without requiring extensive programming knowledge or machine learning experience. As an illustration, we discuss application of the DETECT toolbox for detecting signal artifacts found in continuous multi-channel EEG recordings and show the functionality of the tools found in the toolbox. We also discuss the application of DETECT for identifying irregular heartbeat waveforms found in electrocardiogram (ECG) data as an additional illustration.

  6. DETECT: a MATLAB toolbox for event detection and identification in time series, with applications to artifact detection in EEG signals.

    Directory of Open Access Journals (Sweden)

    Vernon Lawhern

    Full Text Available Recent advances in sensor and recording technology have allowed scientists to acquire very large time-series datasets. Researchers often analyze these datasets in the context of events, which are intervals of time where the properties of the signal change relative to a baseline signal. We have developed DETECT, a MATLAB toolbox for detecting event time intervals in long, multi-channel time series. Our primary goal is to produce a toolbox that is simple for researchers to use, allowing them to quickly train a model on multiple classes of events, assess the accuracy of the model, and determine how closely the results agree with their own manual identification of events without requiring extensive programming knowledge or machine learning experience. As an illustration, we discuss application of the DETECT toolbox for detecting signal artifacts found in continuous multi-channel EEG recordings and show the functionality of the tools found in the toolbox. We also discuss the application of DETECT for identifying irregular heartbeat waveforms found in electrocardiogram (ECG data as an additional illustration.

  7. Measuring methods, registration and signal processing for magnetic field research

    International Nuclear Information System (INIS)

    Nagiello, Z.

    1981-01-01

    Some measuring methods and signal processing systems based on analogue and digital technics, which have been applied in magnetic field research using magnetometers with ferromagnetic transducers, are presented. (author)

  8. Method and apparatus for current-output peak detection

    Science.gov (United States)

    De Geronimo, Gianluigi

    2017-01-24

    A method and apparatus for a current-output peak detector. A current-output peak detector circuit is disclosed and works in two phases. The peak detector circuit includes switches to switch the peak detector circuit from the first phase to the second phase upon detection of the peak voltage of an input voltage signal. The peak detector generates a current output with a high degree of accuracy in the second phase.

  9. Power-efficient method for IM-DD optical transmission of multiple OFDM signals.

    Science.gov (United States)

    Effenberger, Frank; Liu, Xiang

    2015-05-18

    We propose a power-efficient method for transmitting multiple frequency-division multiplexed (FDM) orthogonal frequency-division multiplexing (OFDM) signals in intensity-modulation direct-detection (IM-DD) optical systems. This method is based on quadratic soft clipping in combination with odd-only channel mapping. We show, both analytically and experimentally, that the proposed approach is capable of improving the power efficiency by about 3 dB as compared to conventional FDM OFDM signals under practical bias conditions, making it a viable solution in applications such as optical fiber-wireless integrated systems where both IM-DD optical transmission and OFDM signaling are important.

  10. High sensitive quench detection method using an integrated test wire

    International Nuclear Information System (INIS)

    Fevrier, A.; Tavergnier, J.P.; Nithart, H.; Kiblaire, M.; Duchateau, J.L.

    1981-01-01

    A high sensitive quench detection method which works even in the presence of an external perturbing magnetic field is reported. The quench signal is obtained from the difference in voltages at the superconducting winding terminals and at the terminals at a secondary winding strongly coupled to the primary. The secondary winding could consist of a ''zero-current strand'' of the superconducting cable not connected to one of the winding terminals or an integrated normal test wire inside the superconducting cable. Experimental results on quench detection obtained by this method are described. It is shown that the integrated test wire method leads to efficient and sensitive quench detection, especially in the presence of an external perturbing magnetic field

  11. An Advanced Detecting Scheme against a Signal Distortion with a Smart Transmitter

    International Nuclear Information System (INIS)

    Son, Jun Young; Kim, Young Mi

    2013-01-01

    The analog signal distortion could be detected. Also the data integrity for information security could be provided. The assurance of the integrity in digital information as well as analog signals is necessary. The above proposed schemes can be utilized for detecting the modification of the digital information or analog signal distortion without any of authentication. These effects have merits of the defenses for analog signals and cyber security in terms of information integrity. There are many kinds of measuring nuclear I and C system. Thus, the applicable algorithms may be different according to the lightness or the level of the security in each measuring system. In the future, finding and applying the efficient algorithms in each measuring systems in the nuclear power plant should be studied. As the I and C system will be gradually digitalized, the requirements for basic security concepts should be considered and applied. As IT technology has been much developed, measuring nuclear I and C (Instrument and Control) systems also is going to be evolving. At this point, the smart transmitter has been developed and tried to be applied. Recently, constructed nuclear power plants in Korea have adopted the smart meters. In case of Shin-Kori unit 3, about 59 safety grade smart transmitters and about 180 non-safety grade smart transmitters are used for measuring various signals. In the field of measuring nuclear I and C (Instrument and Control) systems, the cyber security problems can happen more. Thus, providing defense methods against possible cyber attacks are essential. In particular, the defense schemes for providing data information integrity will be essential. In addition, it is necessary to detect the analog signal distortion between the host smart transmitters and the client cabinet. In this paper, applicable one of directions and methods against the above two problems are proposed

  12. An Advanced Detecting Scheme against a Signal Distortion with a Smart Transmitter

    Energy Technology Data Exchange (ETDEWEB)

    Son, Jun Young; Kim, Young Mi [Korea Institute of Nuclear Safety, Daejeon (Korea, Republic of)

    2013-10-15

    The analog signal distortion could be detected. Also the data integrity for information security could be provided. The assurance of the integrity in digital information as well as analog signals is necessary. The above proposed schemes can be utilized for detecting the modification of the digital information or analog signal distortion without any of authentication. These effects have merits of the defenses for analog signals and cyber security in terms of information integrity. There are many kinds of measuring nuclear I and C system. Thus, the applicable algorithms may be different according to the lightness or the level of the security in each measuring system. In the future, finding and applying the efficient algorithms in each measuring systems in the nuclear power plant should be studied. As the I and C system will be gradually digitalized, the requirements for basic security concepts should be considered and applied. As IT technology has been much developed, measuring nuclear I and C (Instrument and Control) systems also is going to be evolving. At this point, the smart transmitter has been developed and tried to be applied. Recently, constructed nuclear power plants in Korea have adopted the smart meters. In case of Shin-Kori unit 3, about 59 safety grade smart transmitters and about 180 non-safety grade smart transmitters are used for measuring various signals. In the field of measuring nuclear I and C (Instrument and Control) systems, the cyber security problems can happen more. Thus, providing defense methods against possible cyber attacks are essential. In particular, the defense schemes for providing data information integrity will be essential. In addition, it is necessary to detect the analog signal distortion between the host smart transmitters and the client cabinet. In this paper, applicable one of directions and methods against the above two problems are proposed.

  13. Median Filtering Methods for Non-volcanic Tremor Detection

    Science.gov (United States)

    Damiao, L. G.; Nadeau, R. M.; Dreger, D. S.; Luna, B.; Zhang, H.

    2016-12-01

    Various properties of median filtering over time and space are used to address challenges posed by the Non-volcanic tremor detection problem. As part of a "Big-Data" effort to characterize the spatial and temporal distribution of ambient tremor throughout the Northern San Andreas Fault system, continuous seismic data from multiple seismic networks with contrasting operational characteristics and distributed over a variety of regions are being used. Automated median filtering methods that are flexible enough to work consistently with these data are required. Tremor is characterized by a low-amplitude, long-duration signal-train whose shape is coherent at multiple stations distributed over a large area. There are no consistent phase arrivals or mechanisms in a given tremor's signal and even the durations and shapes among different tremors vary considerably. A myriad of masquerading noise, anthropogenic and natural-event signals must also be discriminated in order to obtain accurate tremor detections. We present here results of the median methods applied to data from four regions of the San Andreas Fault system in northern California (Geysers Geothermal Field, Napa, Bitterwater and Parkfield) to illustrate the ability of the methods to detect tremor under diverse conditions.

  14. GPR Signal Denoising and Target Extraction With the CEEMD Method

    KAUST Repository

    Li, Jing

    2015-04-17

    In this letter, we apply a time and frequency analysis method based on the complete ensemble empirical mode decomposition (CEEMD) method in ground-penetrating radar (GPR) signal processing. It decomposes the GPR signal into a sum of oscillatory components, with guaranteed positive and smoothly varying instantaneous frequencies. The key idea of this method relies on averaging the modes obtained by empirical mode decomposition (EMD) applied to several realizations of Gaussian white noise added to the original signal. It can solve the mode-mixing problem in the EMD method and improve the resolution of ensemble EMD (EEMD) when the signal has a low signal-to-noise ratio. First, we analyze the difference between the basic theory of EMD, EEMD, and CEEMD. Then, we compare the time and frequency analysis with Hilbert-Huang transform to test the results of different methods. The synthetic and real GPR data demonstrate that CEEMD promises higher spectral-spatial resolution than the other two EMD methods in GPR signal denoising and target extraction. Its decomposition is complete, with a numerically negligible error.

  15. Signal post-processing for acoustic velocimeters: detecting and replacing spikes

    International Nuclear Information System (INIS)

    Razaz, Mahdi; Kawanisi, Kiyosi

    2011-01-01

    Time series recorded by acoustic velocimeters are often affected by a combination of factors, including turbulent velocity fluctuations, Doppler noise and signal aliasing. Although it is not possible to find a comprehensive threshold for identifying spurious data, the present work attempts to describe an effective technique for detecting spikes. This technique is based on transforming data into wavelet space and thresholding the wavelet basis by a consistent threshold. The universal threshold modified by a robust scale estimator such as Q n is proven to work extremely well. The suggested methods for replacing identified spikes combine times series analyses (linear time series modelling or a Kalman predictor) with a straightforward method, polynomial interpolation, to generate substitutions retaining both the trends and the fluctuations in the surrounding clean data. Then, tests were performed to reveal the influence of replacing methods on the total number of detected spikes, required iterations and physical properties of the restored signal. From the overall results, it is inferred that using the wavelet-Q n as the detecting module and integrating it with linear time series modelling/Kalman filtering as the replacement module constitutes an effective despiking algorithm. This methodology is capable of restoring the contaminated signal in such a way that its statistical and physical properties correlate well with those of the original record

  16. Leak detection in gas pipeline by acoustic and signal processing - A review

    Science.gov (United States)

    Adnan, N. F.; Ghazali, M. F.; Amin, M. M.; Hamat, A. M. A.

    2015-12-01

    The pipeline system is the most important part in media transport in order to deliver fluid to another station. The weak maintenance and poor safety will contribute to financial losses in term of fluid waste and environmental impacts. There are many classifications of techniques to make it easier to show their specific method and application. This paper's discussion about gas leak detection in pipeline system using acoustic method will be presented in this paper. The wave propagation in the pipeline is a key parameter in acoustic method when the leak occurs and the pressure balance of the pipe will generated by the friction between wall in the pipe. The signal processing is used to decompose the raw signal and show in time- frequency. Findings based on the acoustic method can be used for comparative study in the future. Acoustic signal and HHT is the best method to detect leak in gas pipelines. More experiments and simulation need to be carried out to get the fast result of leaking and estimation of their location.

  17. Performance of Narrowband Signal Detection under Correlated Rayleigh Fading Based on Synthetic Array

    Directory of Open Access Journals (Sweden)

    Ali Broumandan

    2009-01-01

    design parameters of probability of detection (Pd and probability of false alarm (Pfa. An optimum detector based on Estimator-Correlator (EC is developed, and its performance is compared with that of suboptimal Equal-Gain (EG combiner in different channel correlation scenarios. It is shown that in moderate channel correlation scenarios the detection performance of EC and EG is identical. The sensitivity of the proposed method to knowledge of motion parameters is also investigated. An extensive set of measurements based on CDMA-2000 pilot signals using the static antenna and synthetic array are used to experimentally verify these theoretical findings.

  18. Radiation detection device and a radiation detection method

    International Nuclear Information System (INIS)

    Blum, A.

    1975-01-01

    A radiation detection device is described including at least one scintillator in the path of radiation emissions from a distributed radiation source; a plurality of photodetectors for viewing each scintillator; a signal processing means, a storage means, and a data processing means that are interconnected with one another and connected to said photodetectors; and display means connected to the data processing means to locate a plurality of radiation sources in said distributed radiation source and to provide an image of the distributed radiation sources. The storage means includes radiation emission response data and location data from a plurality of known locations for use by the data processing means to derive a more accurate image by comparison of radiation responses from known locations with radiation responses from unknown locations. (auth)

  19. International law implications of the detection of extraterrestrial intelligent signals

    Science.gov (United States)

    Kopal, Vladimir

    This paper first considers whether the present law of outer space, as it has been enshrined in five United Nations treaties and other legal documents concerning outer space, provides a satisfactory basis for SETI/CETI activities. In the author's opinion, these activities may serve "the common interest of all mankind in the progress of the exploration and use of outer space for peaceful purposes," as recognized in the 1967 Outer Space Treaty. The use of the radio frequency spectrum for SETI/CETI purposes should be in conformity with the legal principles governing this valuable natural resource, as expressed in the International Telecommunication Convention and related documents, and with allocations of the relevant segments of the spectrum by the competent bodies of the International Telecommunication Union. In the second part the author examines the impact that the detection of extraterrestrial intelligent signals may have on the present body of space law. A possible role for the United Nations in this respect is also explored and a timely interest of the world body in discussing questions relating to this subject is recommended. Consideration of these questions could become a tool helping to concentrate the attention of the world community on problems of common concern and thus to strengthen international cooperation. However, the author believes that a law-making process that would aim at elaborating a special regulation of activities in this field would be premature at this stage. It should be initiated only when the boundary between possibilities and realities is crossed. Finally, the paper outlines some likely transformation in our space law thinking that would be the consequence of the detection of extraterrestrial intelligent signals. Elaboration of the principles and norms to govern relations between the international community of our own planet and other intelligent communities in the universe would add a new dimension to the present body of outer space

  20. Development of detection methods for irradiated foods

    International Nuclear Information System (INIS)

    Yang, Jae Seung; Kim, Chong Ki; Lee, Hae Jung; Kim, Kyong Su

    1999-04-01

    To identify irradiated foods, studies have been carried out with electron spin resonance (ESR) spectroscopy on bone containing foods, such as chicken, pork, and beef. The intensity of the signal induced in bones increased linearly with irradiation doses in the range of 1.0 kGy to 5.0 kGy, and it was possible to distinguish between samples given low and high doses of irradiation. The signal stability for 6 weeks made them ideal for the quick and easy identification of irradiated meats. The analysis of DNA damage made on single cells by agarose gel electrophoresis (DNA 'comet assay') can be used to detect irradiated food. All the samples irradiated with over 0.3 kGy were identified to detect post-irradiation by the tail length of their comets. Irradiated samples showed comets with long tails, and the tail length of the comets increased with the dose, while unirradiated samples showed no or very short tails. As a result of the above experiment, the DNA 'comet assay' might be applied to the detection of irradiated grains as a simple, low-cost and rapid screening test. When fats are irradiated, hydrocarbons contained one or two fewer carbon atoms are formed from the parent fatty acids. The major hydrocarbons in irradiated beef, pork and chicken were 1,7-hexadecadiene and 8-heptadecene originating from leic acid. 1,7 hexadecadiene was the highest amount in irradiated beef, pork and chicken. Eight kinds of hydrocarbons were identified from irradiated chicken, among which 1,7-hexadecadiene and 8-heptadecen were detected as major compounds. The concentration of radiation-induced hydrocarbons was relatively constant during 16 weeks

  1. Development of detection methods for irradiated foods

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Jae Seung; Kim, Chong Ki; Lee, Hae Jung [Korea Atomic Energy Research Insitiute, Taejon (Korea, Republic of); Kim, Kyong Su [Chosun University, Kwangju (Korea, Republic of)

    1999-04-01

    To identify irradiated foods, studies have been carried out with electron spin resonance (ESR) spectroscopy on bone containing foods, such as chicken, pork, and beef. The intensity of the signal induced in bones increased linearly with irradiation doses in the range of 1.0 kGy to 5.0 kGy, and it was possible to distinguish between samples given low and high doses of irradiation. The signal stability for 6 weeks made them ideal for the quick and easy identification of irradiated meats. The analysis of DNA damage made on single cells by agarose gel electrophoresis (DNA 'comet assay') can be used to detect irradiated food. All the samples irradiated with over 0.3 kGy were identified to detect post-irradiation by the tail length of their comets. Irradiated samples showed comets with long tails, and the tail length of the comets increased with the dose, while unirradiated samples showed no or very short tails. As a result of the above experiment, the DNA 'comet assay' might be applied to the detection of irradiated grains as a simple, low-cost and rapid screening test. When fats are irradiated, hydrocarbons contained one or two fewer carbon atoms are formed from the parent fatty acids. The major hydrocarbons in irradiated beef, pork and chicken were 1,7-hexadecadiene and 8-heptadecene originating from leic acid. 1,7 hexadecadiene was the highest amount in irradiated beef, pork and chicken. Eight kinds of hydrocarbons were identified from irradiated chicken, among which 1,7-hexadecadiene and 8-heptadecen were detected as major compounds. The concentration of radiation-induced hydrocarbons was relatively constant during 16 weeks.

  2. Hierarchical Leak Detection and Localization Method in Natural Gas Pipeline Monitoring Sensor Networks

    OpenAIRE

    Ning Yu; Renjian Feng; Jiangwen Wan; Yinfeng Wu; Yang Yu

    2011-01-01

    In light of the problems of low recognition efficiency, high false rates and poor localization accuracy in traditional pipeline security detection technology, this paper proposes a type of hierarchical leak detection and localization method for use in natural gas pipeline monitoring sensor networks. In the signal preprocessing phase, original monitoring signals are dealt with by wavelet transform technology to extract the single mode signals as well as characteristic parameters. In the initia...

  3. Detecting signals of seasonal influenza severity through age dynamics

    DEFF Research Database (Denmark)

    Lee, Elizabeth C.; Viboud, Cécile; Simonsen, Lone

    2015-01-01

    stages of an outbreak. To address the limitations of traditional indicators, we propose a novel severity index based on influenza age dynamics estimated from routine physician diagnosis data that can be used retrospectively and for early warning. METHODS: We developed a quantitative 'ground truth......' severity benchmark that synthesizes multiple traditional severity indicators from publicly available influenza surveillance data in the United States. Observing that the age distribution of cases may signal severity early in an epidemic, we constructed novel retrospective and early warning severity indexes....... The retrospective index was well correlated with the severity benchmark and correctly identified the two most severe seasons. The early warning index performance varied, but it projected 2007-08 as relatively severe 10 weeks prior to the epidemic peak. Influenza severity varied significantly among states within...

  4. Automatic Seizure Detection in Rats Using Laplacian EEG and Verification with Human Seizure Signals

    Science.gov (United States)

    Feltane, Amal; Boudreaux-Bartels, G. Faye; Besio, Walter

    2012-01-01

    Automated detection of seizures is still a challenging problem. This study presents an approach to detect seizure segments in Laplacian electroencephalography (tEEG) recorded from rats using the tripolar concentric ring electrode (TCRE) configuration. Three features, namely, median absolute deviation, approximate entropy, and maximum singular value were calculated and used as inputs into two different classifiers: support vector machines and adaptive boosting. The relative performance of the extracted features on TCRE tEEG was examined. Results are obtained with an overall accuracy between 84.81 and 96.51%. In addition to using TCRE tEEG data, the seizure detection algorithm was also applied to the recorded EEG signals from Andrzejak et al. database to show the efficiency of the proposed method for seizure detection. PMID:23073989

  5. Hidden corrosion detection in aircraft aluminum structures using laser ultrasonics and wavelet transform signal analysis.

    Science.gov (United States)

    Silva, M Z; Gouyon, R; Lepoutre, F

    2003-06-01

    Preliminary results of hidden corrosion detection in aircraft aluminum structures using a noncontact laser based ultrasonic technique are presented. A short laser pulse focused to a line spot is used as a broadband source of ultrasonic guided waves in an aluminum 2024 sample cut from an aircraft structure and prepared with artificially corroded circular areas on its back surface. The out of plane surface displacements produced by the propagating ultrasonic waves were detected with a heterodyne Mach-Zehnder interferometer. Time-frequency analysis of the signals using a continuous wavelet transform allowed the identification of the generated Lamb modes by comparison with the calculated dispersion curves. The presence of back surface corrosion was detected by noting the loss of the S(1) mode near its cutoff frequency. This method is applicable to fast scanning inspection techniques and it is particularly suited for early corrosion detection.

  6. Robust QRS peak detection by multimodal information fusion of ECG and blood pressure signals.

    Science.gov (United States)

    Ding, Quan; Bai, Yong; Erol, Yusuf Bugra; Salas-Boni, Rebeca; Zhang, Xiaorong; Hu, Xiao

    2016-11-01

    QRS peak detection is a challenging problem when ECG signal is corrupted. However, additional physiological signals may also provide information about the QRS position. In this study, we focus on a unique benchmark provided by PhysioNet/Computing in Cardiology Challenge 2014 and Physiological Measurement focus issue: robust detection of heart beats in multimodal data, which aimed to explore robust methods for QRS detection in multimodal physiological signals. A dataset of 200 training and 210 testing records are used, where the testing records are hidden for evaluating the performance only. An information fusion framework for robust QRS detection is proposed by leveraging existing ECG and ABP analysis tools and combining heart beats derived from different sources. Results show that our approach achieves an overall accuracy of 90.94% and 88.66% on the training and testing datasets, respectively. Furthermore, we observe expected performance at each step of the proposed approach, as an evidence of the effectiveness of our approach. Discussion on the limitations of our approach is also provided.

  7. Detection of magnetic resonance signals using a magnetoresistive sensor

    Science.gov (United States)

    Budker, Dmitry; Pines, Alexander; Xu, Shoujun; Hilty, Christian; Ledbetter, Micah P; Bouchard, Louis S

    2013-10-01

    A method and apparatus are described wherein a micro sample of a fluidic material may be assayed without sample contamination using NMR techniques, in combination with magnetoresistive sensors. The fluidic material to be assayed is first subject to pre-polarization, in one embodiment, by passage through a magnetic field. The magnetization of the fluidic material is then subject to an encoding process, in one embodiment an rf-induced inversion by passage through an adiabatic fast-passage module. Thereafter, the changes in magnetization are detected by a pair of solid-state magnetoresistive sensors arranged in gradiometer mode. Miniaturization is afforded by the close spacing of the various modules.

  8. Development of Pulsar Detection Methods for a Galactic Center Search

    Science.gov (United States)

    Thornton, Stephen; Wharton, Robert; Cordes, James; Chatterjee, Shami

    2018-01-01

    Finding pulsars within the inner parsec of the galactic center would be incredibly beneficial: for pulsars sufficiently close to Sagittarius A*, extremely precise tests of general relativity in the strong field regime could be performed through measurement of post-Keplerian parameters. Binary pulsar systems with sufficiently short orbital periods could provide the same laboratories with which to test existing theories. Fast and efficient methods are needed to parse large sets of time-domain data from different telescopes to search for periodicity in signals and differentiate radio frequency interference (RFI) from pulsar signals. Here we demonstrate several techniques to reduce red noise (low-frequency interference), generate signals from pulsars in binary orbits, and create plots that allow for fast detection of both RFI and pulsars.

  9. Ionization detector, electrode configuration and single polarity charge detection method

    Science.gov (United States)

    He, Z.

    1998-07-07

    An ionization detector, an electrode configuration and a single polarity charge detection method each utilize a boundary electrode which symmetrically surrounds first and second central interlaced and symmetrical electrodes. All of the electrodes are held at a voltage potential of a first polarity type. The first central electrode is held at a higher potential than the second central or boundary electrodes. By forming the first and second central electrodes in a substantially interlaced and symmetrical pattern and forming the boundary electrode symmetrically about the first and second central electrodes, signals generated by charge carriers are substantially of equal strength with respect to both of the central electrodes. The only significant difference in measured signal strength occurs when the charge carriers move to within close proximity of the first central electrode and are received at the first central electrode. The measured signals are then subtracted and compared to quantitatively measure the magnitude of the charge. 10 figs.

  10. Processing of Instantaneous Angular Speed Signal for Detection of a Diesel Engine Failure

    Directory of Open Access Journals (Sweden)

    Adam Charchalis

    2013-01-01

    Full Text Available Continuous monitoring of diesel engine performance under its operating is critical for the prediction of malfunction development and subsequently functional failure detection. Analysis of instantaneous angular speed (IAS of the crankshaft is considered as one of the nonintrusive and effective methods of the detection of combustion quality deterioration. In this paper results of experimental verification of fuel system's malfunction detecting, using optical encoder for IAS recording are presented. The implemented method relies on the comparison of measurement results, recorded under healthy and faulty conditions of the engine. Elaborated dynamic model of angular speed variations enables us to build templates of engine behavior. Recorded during experiment, values of cylinder pressure were taken for the approximation of pressure basic waveform. The main task of data processing is smoothing the raw angular speed signal. The noise is due to sensor mount vibrations, signal emitter machining, engine body vibrations, and crankshaft torsional vibrations. Smoothing of the measurement data was carried out by the implementation of the Savitzky-Golay filter. Measured signal after smoothing was compared with the model of IAS run.

  11. Fuzzy approximate entropy analysis of chaotic and natural complex systems: detecting muscle fatigue using electromyography signals.

    Science.gov (United States)

    Xie, Hong-Bo; Guo, Jing-Yi; Zheng, Yong-Ping

    2010-04-01

    In the present contribution, a complexity measure is proposed to assess surface electromyography (EMG) in the study of muscle fatigue during sustained, isometric muscle contractions. Approximate entropy (ApEn) is believed to provide quantitative information about the complexity of experimental data that is often corrupted with noise, short data length, and in many cases, has inherent dynamics that exhibit both deterministic and stochastic behaviors. We developed an improved ApEn measure, i.e., fuzzy approximate entropy (fApEn), which utilizes the fuzzy membership function to define the vectors' similarity. Tests were conducted on independent, identically distributed (i.i.d.) Gaussian and uniform noises, a chirp signal, MIX processes, Rossler equation, and Henon map. Compared with the standard ApEn, the fApEn showed better monotonicity, relative consistency, and more robustness to noise when characterizing signals with different complexities. Performance analysis on experimental EMG signals demonstrated that the fApEn significantly decreased during the development of muscle fatigue, which is a similar trend to that of the mean frequency (MNF) of the EMG signal, while the standard ApEn failed to detect this change. Moreover, fApEn of EMG demonstrated a better robustness to the length of the analysis window in comparison with the MNF of EMG. The results suggest that the fApEn of an EMG signal may potentially become a new reliable method for muscle fatigue assessment and be applicable to other short noisy physiological signal analysis.

  12. Methods and systems for the processing of physiological signals

    International Nuclear Information System (INIS)

    Cosnac, B. de; Gariod, R.; Max, J.; Monge, V.

    1975-01-01

    This note is a general survey of the processing of physiological signals. After an introduction about electrodes and their limitations, the physiological nature of the main signals are shortly recalled. Different methods (signal averaging, spectral analysis, shape morphological analysis) are described as applications to the fields of magnetocardiography, electro-encephalography, cardiography, electronystagmography. As for processing means (single portable instruments and programmable), they are described through the example of application to rheography and to the Plurimat'S general system. As a conclusion the methods of signal processing are dominated by the morphological analysis of curves and by the necessity of a more important introduction of the statistical classification. As for the instruments, microprocessors will appear but specific operators linked to computer will certainly grow [fr

  13. Novel methods for detecting buried explosive devices

    Energy Technology Data Exchange (ETDEWEB)

    Kercel, S.W.; Burlage, R.S.; Patek, D.R.; Smith, C.M. [Oak Ridge National Lab., TN (United States); Hibbs, A.D.; Rayner, T.J. [Quantum Magnetics, Inc., San Diego, CA (United States)

    1997-04-01

    Oak Ridge National Laboratory (ORNL) and Quantum Magnetics, Inc. (QM) are exploring novel landmine detection technologies. Technologies considered here include bioreporter bacteria, swept acoustic resonance, nuclear quadrupole resonance (NQR), and semiotic data fusion. Bioreporter bacteria look promising for third-world humanitarian applications; they are inexpensive, and deployment does not require high-tech methods. Swept acoustic resonance may be a useful adjunct to magnetometers in humanitarian demining. For military demining, NQR is a promising method for detecting explosive substances; of 50,000 substances that have been tested, none has an NQR signature that can be mistaken for RDX or TNT. For both military and commercial demining, sensor fusion entails two daunting tasks, identifying fusible features in both present-day and emerging technologies, and devising a fusion algorithm that runs in real-time on cheap hardware. Preliminary research in these areas is encouraging. A bioreporter bacterium for TNT detection is under development. Investigation has just started in swept acoustic resonance as an approach to a cheap mine detector for humanitarian use. Real-time wavelet processing appears to be a key to extending NQR bomb detection into mine detection, including TNT-based mines. Recent discoveries in semiotics may be the breakthrough that will lead to a robust fused detection scheme.

  14. Performance Analysis of Recurrence Matrix Statistics for the Detection of Deterministic Signals in Noise

    National Research Council Canada - National Science Library

    Michalowicz, Joseph V; Nichols, Jonathan M; Bucholtz, Frank

    2008-01-01

    Understanding the limitations to detecting deterministic signals in the presence of noise, especially additive, white Gaussian noise, is of importance for the design of LPI systems and anti-LPI signal defense...

  15. A Novel Approach of Sensitive Infrared Signal Detection for Space Applications

    Data.gov (United States)

    National Aeronautics and Space Administration — Develop an innovative frequency up-conversion device that will efficiently convert the infrared signals into visible/near-infrared signals to enable detection of...

  16. Large-signal modeling method for power FETs and diodes

    Energy Technology Data Exchange (ETDEWEB)

    Sun Lu; Wang Jiali; Wang Shan; Li Xuezheng; Shi Hui; Wang Na; Guo Shengping, E-mail: sunlu_1019@126.co [School of Electromechanical Engineering, Xidian University, Xi' an 710071 (China)

    2009-06-01

    Under a large signal drive level, a frequency domain black box model of the nonlinear scattering function is introduced into power FETs and diodes. A time domain measurement system and a calibration method based on a digital oscilloscope are designed to extract the nonlinear scattering function of semiconductor devices. The extracted models can reflect the real electrical performance of semiconductor devices and propose a new large-signal model to the design of microwave semiconductor circuits.

  17. Large-signal modeling method for power FETs and diodes

    International Nuclear Information System (INIS)

    Sun Lu; Wang Jiali; Wang Shan; Li Xuezheng; Shi Hui; Wang Na; Guo Shengping

    2009-01-01

    Under a large signal drive level, a frequency domain black box model of the nonlinear scattering function is introduced into power FETs and diodes. A time domain measurement system and a calibration method based on a digital oscilloscope are designed to extract the nonlinear scattering function of semiconductor devices. The extracted models can reflect the real electrical performance of semiconductor devices and propose a new large-signal model to the design of microwave semiconductor circuits.

  18. Fixed-point data-collection method of video signal

    International Nuclear Information System (INIS)

    Tang Yu; Yin Zejie; Qian Weiming; Wu Xiaoyi

    1997-01-01

    The author describes a Fixed-point data-collection method of video signal. The method provides an idea of fixed-point data-collection, and has been successfully applied in the research of real-time radiography on dose field, a project supported by National Science Fund

  19. Development of acoustic leak detection and localization methods for inlet piping of fugen nuclear power plant

    International Nuclear Information System (INIS)

    Shimanskiy, Sergey; Iijima, Takashi; Naoi, Yosuke

    2004-01-01

    The development work carried out on Fugen NPP is focused on detection of a small leakage on the reactor's inlet feeder pipes at an early stage by an acoustic leak detection method with usage of high-temperature resistant microphones. Specifically, the leak rate of 0.046m 3 /h has been chosen as a target detection capability for this system. A cross-correlation technique has been studied for leak detection under low signal-noise ratios. The study shows that the sound diffusion on piping causes distortion of leak signals that results in their low correlation. A leak-location estimator and multi-channel correlation value, associated with estimated leak position, have been employed to detect such low-correlated leak signals. A method based on cross-correlation of signal spectral components has been proposed to deal with non-stationary leak signals. Joint-Time-Frequency-Analysis has been applied to analyze such signals, whilst a Wavelet decomposition technique has been used to extract their short-term spectral fluctuations. Since the spectral components are less affected by signal distortion, they provide higher correlation value and can be applied for leak detection under lower signal-noise ratios. The possibility of detecting and locating a small leakage by the methods proposed has been demonstrated by a number of simulation tests conducted on the Fugen NPP site. (author)

  20. Fuel rod failure detection method and system

    International Nuclear Information System (INIS)

    Assmann, H.; Janson, W.; Stehle, H.; Wahode, P.

    1975-01-01

    The inventor claims a method for the detection of a defective fuel rod cladding tube or of inleaked water in the cladding tube of a fuel rod in the fuel assembly of a pressurized-water reactor. The fuel assembly is not disassembled but examined as a whole. In the examination, the cladding tube is heated near one of its two end plugs, e.g. with an attached high-frequency inductor. The water contained in the cladding tube evaporates, and steam bubbles or a condensate are detected by the ultrasonic impulse-echo method. It is also possible to measure the delay of the temperature rise at the end plug or to determine the cooling energy required to keep the end plug temperature stable and thus to detect water ingression. (DG/AK) [de

  1. On the bi-dimensional variational decomposition applied to nonstationary vibration signals for rolling bearing crack detection in coal cutters

    International Nuclear Information System (INIS)

    Jiang, Yu; Li, Zhixiong; Zhang, Chao; Peng, Z; Hu, Chao

    2016-01-01

    This work aims to detect rolling bearing cracks using a variational approach. An original method that appropriately incorporates bi-dimensional variational mode decomposition (BVMD) into discriminant diffusion maps (DDM) is proposed to analyze the nonstationary vibration signals recorded from the cracked rolling bearings in coal cutters. The advantage of this variational decomposition based diffusion map (VDDM) method in comparison to the current DDM is that the intrinsic vibration mode of the crack can be filtered into a limited bandwidth in the frequency domain with an estimated central frequency, thus discarding the interference signal components in the vibration signals and significantly improving the crack detection performance. In addition, the VDDM is able to simultaneously process two-channel sensor signals to reduce information leakage. Experimental validation using rolling bearing crack vibration signals demonstrates that the VDDM separated the raw signals into four intrinsic modes, including one roller vibration mode, one roller cage vibration mode, one inner race vibration mode, and one outer race vibration mode. Hence, reliable fault features were extracted from the outer race vibration mode, and satisfactory crack identification performance was achieved. The comparison between the proposed VDDM and existing approaches indicated that the VDDM method was more efficient and reliable for crack detection in coal cutter rolling bearings. As an effective catalyst for rolling bearing crack detection, this newly proposed method is useful for practical applications. (paper)

  2. The Signal Validation method of Digital Process Instrumentation System on signal conditioner for SMART

    International Nuclear Information System (INIS)

    Moon, Hee Gun; Park, Sang Min; Kim, Jung Seon; Shon, Chang Ho; Park, Heui Youn; Koo, In Soo

    2005-01-01

    The function of PIS(Process Instrumentation System) for SMART is to acquire the process data from sensor or transmitter. The PIS consists of signal conditioner, A/D converter, DSP(Digital Signal Process) and NIC(Network Interface Card). So, It is fully digital system after A/D converter. The PI cabinet and PDAS(Plant Data Acquisition System) in commercial plant is responsible for data acquisition of the sensor or transmitter include RTD, TC, level, flow, pressure and so on. The PDAS has the software that processes each sensor data and PI cabinet has the signal conditioner, which is need for maintenance and test. The signal conditioner has the potentiometer to adjust the span and zero for test and maintenance. The PIS of SMART also has the signal conditioner which has the span and zero adjust same as the commercial plant because the signal conditioner perform the signal condition for AD converter such as 0∼10Vdc. But, To adjust span and zero is manual test and calibration. So, This paper presents the method of signal validation and calibration, which is used by digital feature in SMART. There are I/E(current to voltage), R/E(resistor to voltage), F/E(frequency to voltage), V/V(voltage to voltage). Etc. In this paper show only the signal validation and calibration about I/E converter that convert level, pressure, flow such as 4∼20mA into signal for AD conversion such as 0∼10Vdc

  3. A method for detecting hydrophobic patches protein

    NARCIS (Netherlands)

    Lijnzaad, P.; Berendsen, H.J.C.; Argos, P.

    1996-01-01

    A method for the detection of hydrophobic patches on the surfaces of protein tertiary structures is presented, it delineates explicit contiguous pieces of surface of arbitrary size and shape that consist solely of carbon and sulphur atoms using a dot representation of the solvent-accessible surface,

  4. Radioimmunoassay method for detection of gonorrhea antibodies

    International Nuclear Information System (INIS)

    1975-01-01

    A novel radioimmunoassay for the detection of gonorrhea antibodies in serum is described. A radionuclide is bound to gonorrhea antigens produced by a growth culture. In the presence of gonorrhea antibodies in the serum, an antigen-antibody conjugate is formed, the concentration of which can be measured with conventional radiometric methods. The radioimmunoassay is highly specific

  5. GMDD: a database of GMO detection methods

    NARCIS (Netherlands)

    Dong, W.; Yang, L.; Shen, K.; Kim, B.; Kleter, G.A.; Marvin, H.J.P.; Guo, R.; Liang, W.; Zhang, D.

    2008-01-01

    Since more than one hundred events of genetically modified organisms (GMOs) have been developed and approved for commercialization in global area, the GMO analysis methods are essential for the enforcement of GMO labelling regulations. Protein and nucleic acid-based detection techniques have been

  6. Prescription-event monitoring: developments in signal detection.

    Science.gov (United States)

    Ferreira, Germano

    2007-01-01

    Prescription-event monitoring (PEM) is a non-interventional intensive method for post-marketing drug safety monitoring of newly licensed medicines. PEM studies are cohort studies where exposure is obtained from a centralised service and outcomes from simple questionnaires completed by general practitioners. Follow-up forms are sent for selected events. Because PEM captures all events and not only the suspected adverse drug reactions, PEM cohorts potentially differ in respect to the distribution of number of events per person depending on the nature of the drug under study. This variance can be related either with the condition for which the drug is prescribed (e.g. a condition causing high morbidity will have, in average, a higher number of events per person compared with a condition with lower morbidity) or with the drug effect itself. This paper describes an exploratory investigation of the distortion caused by product-related variations of the number of events to the interpretation of the proportional reporting ratio (PRR) values ("the higher the PRR, the greater the strength of the signal") computed using drug-cohort data. We studied this effect by assessing the agreement between the PRR based on events (event of interest vs all other events) and PRR based on cases (cases with the event of interest vs cases with any other events). PRR were calculated for all combinations reported to ten selected drugs against a comparator of 81 other drugs. Three of the ten drugs had a cohort with an apparent higher proportion of patients with lower number of events. The PRRs based on events were systematically higher than the PRR based on cases for the combinations reported to these three drugs. Additionally, when applying the threshold criteria for signal screening (n > or =3, PRR > or =1.5 and Chi-squared > or =4), the binary agreement was generally high but apparently lower for these three drugs. In conclusion, the distribution of events per patient in drug cohorts shall be

  7. Comparison of methods for removing electromagnetic noise from electromyographic signals.

    Science.gov (United States)

    Defreitas, Jason M; Beck, Travis W; Stock, Matt S

    2012-02-01

    The purpose of this investigation was to compare three different methods of removing noise from monopolar electromyographic (EMG) signals: (a) electrical shielding with a Faraday cage, (b) denoising with a digital notch-filter and (c) applying a bipolar differentiation with another monopolar EMG signal. Ten men and ten women (mean age = 24.0 years) performed isometric muscle actions of the leg extensors at 10-100% of their maximal voluntary contraction on two separate occasions. One trial was performed inside a Faraday tent (a flexible Faraday cage made from conductive material), and the other was performed outside the Faraday tent. The EMG signals collected outside the Faraday tent were analyzed three separate ways: as a raw signal, as a bipolar signal, and as a signal digitally notch filtered to remove 60 Hz noise and its harmonics. The signal-to-noise ratios were greatest after notch-filtering (range: 3.0-33.8), and lowest for the bipolar arrangement (1.6-10.2). Linear slope coefficients for the EMG amplitude versus force relationship were also used to compare the methods of noise removal. The results showed that a bipolar arrangement had a significantly lower linear slope coefficient when compared to the three other conditions (raw, notch and tent). These results suggested that an appropriately filtered monopolar EMG signal can be useful in situations that require a large pick-up area. Furthermore, although it is helpful, a Faraday tent (or cage) is not required to achieve an appropriate signal-to-noise ratio, as long as the correct filters are applied.

  8. Comparison of methods for removing electromagnetic noise from electromyographic signals

    International Nuclear Information System (INIS)

    DeFreitas, Jason M; Beck, Travis W; Stock, Matt S

    2012-01-01

    The purpose of this investigation was to compare three different methods of removing noise from monopolar electromyographic (EMG) signals: (a) electrical shielding with a Faraday cage, (b) denoising with a digital notch-filter and (c) applying a bipolar differentiation with another monopolar EMG signal. Ten men and ten women (mean age = 24.0 years) performed isometric muscle actions of the leg extensors at 10–100% of their maximal voluntary contraction on two separate occasions. One trial was performed inside a Faraday tent (a flexible Faraday cage made from conductive material), and the other was performed outside the Faraday tent. The EMG signals collected outside the Faraday tent were analyzed three separate ways: as a raw signal, as a bipolar signal, and as a signal digitally notch filtered to remove 60 Hz noise and its harmonics. The signal-to-noise ratios were greatest after notch-filtering (range: 3.0–33.8), and lowest for the bipolar arrangement (1.6–10.2). Linear slope coefficients for the EMG amplitude versus force relationship were also used to compare the methods of noise removal. The results showed that a bipolar arrangement had a significantly lower linear slope coefficient when compared to the three other conditions (raw, notch and tent). These results suggested that an appropriately filtered monopolar EMG signal can be useful in situations that require a large pick-up area. Furthermore, although it is helpful, a Faraday tent (or cage) is not required to achieve an appropriate signal-to-noise ratio, as long as the correct filters are applied. (paper)

  9. Method for increasing nuclear magnetic resonance signals in living biological tissue

    International Nuclear Information System (INIS)

    Krongrad, A.

    1995-01-01

    A method of enhancing a magnetic resonance comprising the steps of administering a quantity of a selected magnetic isotope to a living biological tissue at a concentration greater than the naturally occurring concentration of such isotope and detecting magnetic resonance signal from the administered magnetic isotope in the living biological tissue. (author)

  10. Improvement of Source Number Estimation Method for Single Channel Signal.

    Directory of Open Access Journals (Sweden)

    Zhi Dong

    Full Text Available Source number estimation methods for single channel signal have been investigated and the improvements for each method are suggested in this work. Firstly, the single channel data is converted to multi-channel form by delay process. Then, algorithms used in the array signal processing, such as Gerschgorin's disk estimation (GDE and minimum description length (MDL, are introduced to estimate the source number of the received signal. The previous results have shown that the MDL based on information theoretic criteria (ITC obtains a superior performance than GDE at low SNR. However it has no ability to handle the signals containing colored noise. On the contrary, the GDE method can eliminate the influence of colored noise. Nevertheless, its performance at low SNR is not satisfactory. In order to solve these problems and contradictions, the work makes remarkable improvements on these two methods on account of the above consideration. A diagonal loading technique is employed to ameliorate the MDL method and a jackknife technique is referenced to optimize the data covariance matrix in order to improve the performance of the GDE method. The results of simulation have illustrated that the performance of original methods have been promoted largely.

  11. Underwater Cylindrical Object Detection Using the Spectral Features of Active Sonar Signals with Logistic Regression Models

    Directory of Open Access Journals (Sweden)

    Yoojeong Seo

    2018-01-01

    Full Text Available The issue of detecting objects bottoming on the sea floor is significant in various fields including civilian and military areas. The objective of this study is to investigate the logistic regression model to discriminate the target from the clutter and to verify the possibility of applying the model trained by the simulated data generated by the mathematical model to the real experimental data because it is not easy to obtain sufficient data in the underwater field. In the first stage of this study, when the clutter signal energy is so strong that the detection of a target is difficult, the logistic regression model is employed to distinguish the strong clutter signal and the target signal. Previous studies have found that if the clutter energy is larger, false detection occurs even for the various existing detection schemes. For this reason, the discrete Fourier transform (DFT magnitude spectrum of acoustic signals received by active sonar is applied to train the model to distinguish whether the received signal contains a target signal or not. The goodness of fit of the model is verified in terms of receiver operation characteristic (ROC, area under ROC curve (AUC, and classification table. The detection performance of the proposed model is evaluated in terms of detection rate according to target to clutter ratio (TCR. Furthermore, the real experimental data are employed to test the proposed approach. When using the experimental data to test the model, the logistic regression model is trained by the simulated data that are generated based on the mathematical model for the backscattering of the cylindrical object. The mathematical model is developed according to the size of the cylinder used in the experiment. Since the information on the experimental environment including the sound speed, the sediment type and such is not available, once simulated data are generated under various conditions, valid simulated data are selected using 70% of the

  12. Exploiting Wireless Received Signal Strength Indicators to Detect Evil-Twin Attacks in Smart Homes

    Directory of Open Access Journals (Sweden)

    Zhanyong Tang

    2017-01-01

    Full Text Available Evil-Twin is becoming a common attack in smart home environments where an attacker can set up a fake AP to compromise the security of the connected devices. To identify the fake APs, The current approaches of detecting Evil-Twin attacks all rely on information such as SSIDs, the MAC address of the genuine AP, or network traffic patterns. However, such information can be faked by the attacker, often leading to low detection rates and weak protection. This paper presents a novel Evil-Twin attack detection method based on the received signal strength indicator (RSSI. Our approach considers the RSSI as a fingerprint of APs and uses the fingerprint of the genuine AP to identify fake ones. We provide two schemes to detect a fake AP in two different scenarios where the genuine AP can be located at either a single or multiple locations in the property, by exploiting the multipath effect of the Wi-Fi signal. As a departure from prior work, our approach does not rely on any professional measurement devices. Experimental results show that our approach can successfully detect 90% of the fake APs, at the cost of a one-off, modest connection delay.

  13. Dual-signal amplification strategy for ultrasensitive chemiluminescence detection of PDGF-BB in capillary electrophoresis.

    Science.gov (United States)

    Cao, Jun-Tao; Wang, Hui; Ren, Shu-Wei; Chen, Yong-Hong; Liu, Yan-Ming

    2015-12-01

    Many efforts have been made toward the achievement of high sensitivity in capillary electrophoresis coupled with chemiluminescence detection (CE-CL). This work describes a novel dual-signal amplification strategy for highly specific and ultrasensitive CL detection of human platelet-derived growth factor-BB (PDGF-BB) using both aptamer and horseradish peroxidase (HRP) modified gold nanoparticles (HRP-AuNPs-aptamer) as nanoprobes in CE. Both AuNPs and HRP in the nanoprobes could amplify the CL signals in the luminol-H2 O2 CL system, owing to the excellent catalytic behavior of AuNPs and HRP in the CL system. Meanwhile, the high affinity of aptamer modified on the AuNPs allows detection with high specificity. As proof-of-concept, the proposed method was employed to quantify the concentration of PDGF-BB from 0.50 to 250 fm with a detection limit of 0.21 fm. The applicability of the assay was further demonstrated in the analysis of PDGF-BB in human serum samples with acceptable accuracy and reliability. The result of this study exhibits distinct advantages, such as high sensitivity, good specificity, simplicity, and very small sample consumption. The good performances of the proposed strategy provide a powerful avenue for ultrasensitive detection of rare proteins in biological sample, showing great promise in biochemical analysis. Copyright © 2015 John Wiley & Sons, Ltd.

  14. Three different signal amplification strategies for the impedimetric sandwich detection of thrombin

    Energy Technology Data Exchange (ETDEWEB)

    Ocaña, Cristina; Valle, Manel del, E-mail: manel.delvalle@uab.cat

    2016-03-17

    In this work, we report a comparative study on three highly specific amplification strategies for the ultrasensitive detection of thrombin with the use of aptamer sandwich protocol. The protocol consisted on the use of a first thrombin aptamer immobilized on the electrode surface, the recognition of thrombin protein, and the reaction with a second biotinylated thrombin aptamer forming the sandwich. Through the exposed biotin end, three variants have been tested to amplify the electrochemical impedance signal. The strategies included (a) silver enhancement treatment, (b) gold enhancement treatment and (c) insoluble product produced by the combination of the enzyme horseradish peroxidase (HRP) and 3-amino-9-ethylcarbazole (AEC). The properties of the sensing surface were probed by electrochemical impedance measurements in the presence of the ferrocyanide/ferricyanide redox marker. Insoluble product strategy and silver enhancement treatment resulted in the lowest detection limit (0.3 pM), while gold enhancement method resulted in the highest reproducibility, 8.8% RSD at the pM thrombin concentration levels. Results of silver and gold enhancement treatment also permitted direct inspection by scanning electron microscopy (SEM). - Highlights: • Aptasensor to detect thrombin reaching the femtomolar level. • Biosensing protocol employs two thrombin aptamers in a sandwich capture scheme. • Use of second biotinylated aptamer allows many amplification and detection variants. • Precipitation reaction provides the highest signal amplification of ca. 3 times. • Double recognition event improves remarkably selectivity for thrombin detection.

  15. Three different signal amplification strategies for the impedimetric sandwich detection of thrombin

    International Nuclear Information System (INIS)

    Ocaña, Cristina; Valle, Manel del

    2016-01-01

    In this work, we report a comparative study on three highly specific amplification strategies for the ultrasensitive detection of thrombin with the use of aptamer sandwich protocol. The protocol consisted on the use of a first thrombin aptamer immobilized on the electrode surface, the recognition of thrombin protein, and the reaction with a second biotinylated thrombin aptamer forming the sandwich. Through the exposed biotin end, three variants have been tested to amplify the electrochemical impedance signal. The strategies included (a) silver enhancement treatment, (b) gold enhancement treatment and (c) insoluble product produced by the combination of the enzyme horseradish peroxidase (HRP) and 3-amino-9-ethylcarbazole (AEC). The properties of the sensing surface were probed by electrochemical impedance measurements in the presence of the ferrocyanide/ferricyanide redox marker. Insoluble product strategy and silver enhancement treatment resulted in the lowest detection limit (0.3 pM), while gold enhancement method resulted in the highest reproducibility, 8.8% RSD at the pM thrombin concentration levels. Results of silver and gold enhancement treatment also permitted direct inspection by scanning electron microscopy (SEM). - Highlights: • Aptasensor to detect thrombin reaching the femtomolar level. • Biosensing protocol employs two thrombin aptamers in a sandwich capture scheme. • Use of second biotinylated aptamer allows many amplification and detection variants. • Precipitation reaction provides the highest signal amplification of ca. 3 times. • Double recognition event improves remarkably selectivity for thrombin detection.

  16. A Novel Voice Sensor for the Detection of Speech Signals

    Directory of Open Access Journals (Sweden)

    Kun-Ching Wang

    2013-12-01

    Full Text Available In order to develop a novel voice sensor to detect human voices, the use of features which are more robust to noise is an important issue. Voice sensor is also called voice activity detection (VAD. Due to that the inherent nature of the formant structure only occurred on the speech spectrogram (well-known as voiceprint, Wu et al. were the first to use band-spectral entropy (BSE to describe the characteristics of voiceprints. However, the performance of VAD based on BSE feature was degraded in colored noise (or voiceprint-like noise environments. In order to solve this problem, we propose the two-dimensional part-band energy entropy (TD-PBEE parameter based on two variables: part-band partition number upon frequency index and long-term window size upon time index to further improve the BSE-based VAD algorithm. The two variables can efficiently represent the characteristics of voiceprints on each critical frequency band and use long-term information for noisy speech spectrograms, respectively. The TD-PBEE parameter can be regarded as a PBEE parameter over time. First, the strength of voiceprints can be partly enhanced by using four entropies applied to four part-bands. We can use the four part-band energy entropies for describing the voiceprints in detail. Due to the characteristics of non-stationary for speech and various noises, we will then use long-term information processing to refine the PBEE, so the voice-like noise can be distinguished from noisy speech through the concept of PBEE with long-term information. Our experiments show that the proposed feature extraction with the TD-PBEE parameter is quite insensitive to background noise. The proposed TD-PBEE-based VAD algorithm is evaluated for four types of noises and five signal-to-noise ratio (SNR levels. We find that the accuracy of the proposed TD-PBEE-based VAD algorithm averaged over all noises and all SNR levels is better than that of other considered VAD algorithms.

  17. Measures of metacognition on signal-detection theoretic models.

    Science.gov (United States)

    Barrett, Adam B; Dienes, Zoltan; Seth, Anil K

    2013-12-01

    Analyzing metacognition, specifically knowledge of accuracy of internal perceptual, memorial, or other knowledge states, is vital for many strands of psychology, including determining the accuracy of feelings of knowing and discriminating conscious from unconscious cognition. Quantifying metacognitive sensitivity is however more challenging than quantifying basic stimulus sensitivity. Under popular signal-detection theory (SDT) models for stimulus classification tasks, approaches based on Type II receiver-operating characteristic (ROC) curves or Type II d-prime risk confounding metacognition with response biases in either the Type I (classification) or Type II (metacognitive) tasks. A new approach introduces meta-d': The Type I d-prime that would have led to the observed Type II data had the subject used all the Type I information. Here, we (a) further establish the inconsistency of the Type II d-prime and ROC approaches with new explicit analyses of the standard SDT model and (b) analyze, for the first time, the behavior of meta-d' under nontrivial scenarios, such as when metacognitive judgments utilize enhanced or degraded versions of the Type I evidence. Analytically, meta-d' values typically reflect the underlying model well and are stable under changes in decision criteria; however, in relatively extreme cases, meta-d' can become unstable. We explore bias and variance of in-sample measurements of meta-d' and supply MATLAB code for estimation in general cases. Our results support meta-d' as a useful measure of metacognition and provide rigorous methodology for its application. Our recommendations are useful for any researchers interested in assessing metacognitive accuracy. PsycINFO Database Record (c) 2014 APA, all rights reserved.

  18. Bayesian Methods for Radiation Detection and Dosimetry

    CERN Document Server

    Groer, Peter G

    2002-01-01

    We performed work in three areas: radiation detection, external and internal radiation dosimetry. In radiation detection we developed Bayesian techniques to estimate the net activity of high and low activity radioactive samples. These techniques have the advantage that the remaining uncertainty about the net activity is described by probability densities. Graphs of the densities show the uncertainty in pictorial form. Figure 1 below demonstrates this point. We applied stochastic processes for a method to obtain Bayesian estimates of 222Rn-daughter products from observed counting rates. In external radiation dosimetry we studied and developed Bayesian methods to estimate radiation doses to an individual with radiation induced chromosome aberrations. We analyzed chromosome aberrations after exposure to gammas and neutrons and developed a method for dose-estimation after criticality accidents. The research in internal radiation dosimetry focused on parameter estimation for compartmental models from observed comp...

  19. Theoretical and numerical investigations into the SPRT method for anomaly detection

    Energy Technology Data Exchange (ETDEWEB)

    Schoonewelle, H.; Hagen, T.H.J.J. van der; Hoogenboom, J.E. [Interuniversitair Reactor Inst., Delft (Netherlands)

    1995-11-01

    The sequential probability ratio test developed by Wald is a powerful method of testing an alternative hypothesis against a null hypothesis. This makes the method applicable for anomaly detection. In this paper the method is used to detect a change of the standard deviation of a Gaussian distributed white noise signal. The false alarm probability, the alarm failure probability and the average time to alarm of the method, which are important parameters for anomaly detection, are determined by simulation and compared with theoretical results. Each of the three parameters is presented in dependence of the other two and the ratio of the standard deviation of the anomalous signal and that of the normal signal. Results show that the method is very well suited for anomaly detection. It can detect for example a 50% change in standard deviation within 1 second with a false alarm and alarm failure rate of less than once per month. (author).

  20. Theoretical and numerical investigations into the SPRT method for anomaly detection

    International Nuclear Information System (INIS)

    Schoonewelle, H.; Hagen, T.H.J.J. van der; Hoogenboom, J.E.

    1995-01-01

    The sequential probability ratio test developed by Wald is a powerful method of testing an alternative hypothesis against a null hypothesis. This makes the method applicable for anomaly detection. In this paper the method is used to detect a change of the standard deviation of a Gaussian distributed white noise signal. The false alarm probability, the alarm failure probability and the average time to alarm of the method, which are important parameters for anomaly detection, are determined by simulation and compared with theoretical results. Each of the three parameters is presented in dependence of the other two and the ratio of the standard deviation of the anomalous signal and that of the normal signal. Results show that the method is very well suited for anomaly detection. It can detect for example a 50% change in standard deviation within 1 second with a false alarm and alarm failure rate of less than once per month. (author)

  1. Endogenous field feedback promotes the detectability for exogenous electric signal in the hybrid coupled population

    Energy Technology Data Exchange (ETDEWEB)

    Wei, Xile; Zhang, Danhong; Wang, Jiang; Yu, Haitao, E-mail: htyu@tju.edu.cn [Tianjin Key Laboratory of Process Measurement and Control, School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072 (China); Lu, Meili [School of Informational Technology and Engineering, Tianjin University of Technology and Education, Tianjin 300222 (China); Che, Yanqiu [School of Automation and Electrical Engineering, Tianjin University of Technology and Education, Tianjin 300222 (China)

    2015-01-15

    This paper presents the endogenous electric field in chemical or electrical synaptic coupled networks, aiming to study the role of endogenous field feedback in the signal propagation in neural systems. It shows that the feedback of endogenous fields to network activities can reduce the required energy of the noise and enhance the transmission of input signals in hybrid coupled populations. As a common and important nonsynaptic interactive method among neurons, particularly, the endogenous filed feedback can not only promote the detectability of exogenous weak signal in hybrid coupled neural population but also enhance the robustness of the detectability against noise. Furthermore, with the increasing of field coupling strengths, the endogenous field feedback is conductive to the stochastic resonance by facilitating the transition of cluster activities from the no spiking to spiking regions. Distinct from synaptic coupling, the endogenous field feedback can play a role as internal driving force to boost the population activities, which is similar to the noise. Thus, it can help to transmit exogenous weak signals within the network in the absence of noise drive via the stochastic-like resonance.

  2. Endogenous field feedback promotes the detectability for exogenous electric signal in the hybrid coupled population

    International Nuclear Information System (INIS)

    Wei, Xile; Zhang, Danhong; Wang, Jiang; Yu, Haitao; Lu, Meili; Che, Yanqiu

    2015-01-01

    This paper presents the endogenous electric field in chemical or electrical synaptic coupled networks, aiming to study the role of endogenous field feedback in the signal propagation in neural systems. It shows that the feedback of endogenous fields to network activities can reduce the required energy of the noise and enhance the transmission of input signals in hybrid coupled populations. As a common and important nonsynaptic interactive method among neurons, particularly, the endogenous filed feedback can not only promote the detectability of exogenous weak signal in hybrid coupled neural population but also enhance the robustness of the detectability against noise. Furthermore, with the increasing of field coupling strengths, the endogenous field feedback is conductive to the stochastic resonance by facilitating the transition of cluster activities from the no spiking to spiking regions. Distinct from synaptic coupling, the endogenous field feedback can play a role as internal driving force to boost the population activities, which is similar to the noise. Thus, it can help to transmit exogenous weak signals within the network in the absence of noise drive via the stochastic-like resonance

  3. Endogenous field feedback promotes the detectability for exogenous electric signal in the hybrid coupled population.

    Science.gov (United States)

    Wei, Xile; Zhang, Danhong; Lu, Meili; Wang, Jiang; Yu, Haitao; Che, Yanqiu

    2015-01-01

    This paper presents the endogenous electric field in chemical or electrical synaptic coupled networks, aiming to study the role of endogenous field feedback in the signal propagation in neural systems. It shows that the feedback of endogenous fields to network activities can reduce the required energy of the noise and enhance the transmission of input signals in hybrid coupled populations. As a common and important nonsynaptic interactive method among neurons, particularly, the endogenous filed feedback can not only promote the detectability of exogenous weak signal in hybrid coupled neural population but also enhance the robustness of the detectability against noise. Furthermore, with the increasing of field coupling strengths, the endogenous field feedback is conductive to the stochastic resonance by facilitating the transition of cluster activities from the no spiking to spiking regions. Distinct from synaptic coupling, the endogenous field feedback can play a role as internal driving force to boost the population activities, which is similar to the noise. Thus, it can help to transmit exogenous weak signals within the network in the absence of noise drive via the stochastic-like resonance.

  4. Metagenomic Detection Methods in Biopreparedness Outbreak Scenarios

    DEFF Research Database (Denmark)

    Karlsson, Oskar Erik; Hansen, Trine; Knutsson, Rickard

    2013-01-01

    In the field of diagnostic microbiology, rapid molecular methods are critically important for detecting pathogens. With rapid and accurate detection, preventive measures can be put in place early, thereby preventing loss of life and further spread of a disease. From a preparedness perspective...... of a clinical sample, creating a metagenome, in a single week of laboratory work. As new technologies emerge, their dissemination and capacity building must be facilitated, and criteria for use, as well as guidelines on how to report results, must be established. This article focuses on the use of metagenomics...

  5. Limitations and Strengths of the Fourier Transform Method to Detect Accelerating Targets

    National Research Council Canada - National Science Library

    Thayaparan, Thayananthan

    2000-01-01

    .... In using a Pulse Doppler Radar to detect a non-accelerating target in additive white Gaussian noise and to estimate its radial velocity, the Fourier method provides an output signal-to-noise ratio (SNR...

  6. Suitable or optimal noise benefits in signal detection

    International Nuclear Information System (INIS)

    Liu, Shujun; Yang, Ting; Tang, Mingchun; Wang, Pin; Zhang, Xinzheng

    2016-01-01

    Highlights: • Six intervals of additive noises divided according to the two constraints. • Derivation of the suitable additive noise to meet the two constraints. • Formulation of the suitable noise for improvability or nonimprovability. • Optimal noises to minimize P FA , maximize P D and maximize the overall improvement. - Abstract: We present an effective way to generate the suitable or the optimal additive noises which can achieve the three goals of the noise enhanced detectability, i.e., the maximum detection probability (P D ), the minimum false alarm probability (P FA ) and the maximum overall improvement of P D and P FA , without increasing P FA and decreasing P D in a binary hypothesis testing problem. The mechanism of our method is that we divide the discrete vectors into six intervals and choose the useful or partial useful vectors from these intervals to form the additive noise according to different requirements. The form of the optimal noise is derived and proven as a randomization of no more than two discrete vectors in our way. Moreover, how to choose suitable and optimal noises from the six intervals are given. Finally, numerous examples are presented to illustrate the theoretical analysis, where the background noises are Gaussian, symmetric and asymmetric Gaussian mixture noise, respectively.

  7. Visual method for detecting critical damage in railway contact strips

    Science.gov (United States)

    Judek, S.; Skibicki, J.

    2018-05-01

    Ensuring an uninterrupted supply of power in the electric traction is vital for the safety of this important transport system. For this purpose, monitoring and diagnostics of the technical condition of the vehicle’s power supply elements are becoming increasingly common. This paper presents a new visual method for detecting contact strip damage, based on measurement and analysis of the movement of the overhead contact line (OCL) wire. A measurement system configuration with a 2D camera was proposed. The experimental method has shown that contact strips damage can be detected by transverse displacement signal analysis. It has been proven that the velocity signal numerically established on that basis has a comparable level in the case of identical damage, regardless of its location on the surface of the contact strip. The proposed method belongs to the group of contact-less measurements, so it does not require interference with the structure of the catenary network nor the mounting of sensors in its vicinity. Measurement of displacements of the contact wire in 2D space makes it possible to combine the functions of existing diagnostic stands assessing the correctness of the mean contact force control adjustment of the current collector with the elements of the contact strip diagnostics, which involves detecting their damage which may result in overhead contact line rupture.

  8. A sensitive detection assay based on signal amplification technology for Alzheimer's disease's early biomarker in exosome.

    Science.gov (United States)

    Zhou, Jie; Meng, Lingchang; Ye, Weiran; Wang, Qiaolei; Geng, Shizhen; Sun, Chong

    2018-08-31

    Alzheimer's disease (AD) considered as the third health "killer" has seriously threatened the health of the elderly. However, the modern diagnostic strategies of AD present several disadvantages: the low accuracy and specificity resulting in some false-negative diagnoses, and the poor sensitivity leading to a delayed treatment. In view of this situation, a enzyme-free and target-triggered signal amplification strategy, based on graphene oxide (GO) and entropy-driven strand displacement reaction (ESDR) principle, was proposed. In this strategy, when the hairpin structure probes (H)specially binds with beta-amyloid-(1-42) oligomers (Aβ42 oligomers), it's structure will be opened, causing the bases complementary to FAM-labeled replacement probes R (R1 and R2) exposed. At this time, R1 and R2 will hybridize with H, resulting in the bound Aβ42 oligomers released. The released Aβ42 oligomers would participate in the next cycle reaction, making the signal amplified. As a quencher, GO could absorb the free single-stranded DNA R1 and R2 and quench their fluorescence; however, the DNA duplex still exists free and keeps its signal-on. Through the detection of Aβ42 oligomers in exosomes, this ultrasensitive detection method with the advantages of low limit of detection (LOD, 20 pM), great accuracy, excellent precision and convenience provides an excellent prospect for AD's early diagnosis. Copyright © 2018 Elsevier B.V. All rights reserved.

  9. Frequency hopping signal detection based on wavelet decomposition and Hilbert-Huang transform

    Science.gov (United States)

    Zheng, Yang; Chen, Xihao; Zhu, Rui

    2017-07-01

    Frequency hopping (FH) signal is widely adopted by military communications as a kind of low probability interception signal. Therefore, it is very important to research the FH signal detection algorithm. The existing detection algorithm of FH signals based on the time-frequency analysis cannot satisfy the time and frequency resolution requirement at the same time due to the influence of window function. In order to solve this problem, an algorithm based on wavelet decomposition and Hilbert-Huang transform (HHT) was proposed. The proposed algorithm removes the noise of the received signals by wavelet decomposition and detects the FH signals by Hilbert-Huang transform. Simulation results show the proposed algorithm takes into account both the time resolution and the frequency resolution. Correspondingly, the accuracy of FH signals detection can be improved.

  10. Detection of Fatigue Damage by Using High Frequency Nonlinear Laser Ultrasonic Signals

    International Nuclear Information System (INIS)

    Park, Seung Kyu; Park, Nak Kyu; Baik, Sung Hoon; Cheong, Yong Moo; Cha, Byung Heon

    2012-01-01

    The detection of fatigue damage for the components of a nuclear power plant is one of key techniques to prevent a catastrophic accident and the subsequent severe losses. Specifically, it is preferred to detect at an early stage of the fatigue damage. If the fatigue damage that is in danger of growing into a fracture is accurately detected, an appropriate treatment could be carried out to improve the condition. Although most engineers and designers take precautions against fatigue, some breakdowns of nuclear power plant components still occur due to fatigue damage. It is considered that ultrasound testing technique is the most promising method to detect the fatigue damage in many nondestructive testing methods. Laser ultrasound has attracted attention as a noncontact testing technique. Especially, laser ultrasonic signal has wide band frequency spectrum which can provide more accurate information for a testing material. The conventional linear ultrasonic technique is sensitive to gross defects or opened cracks whereas it is less sensitive to evenly distributed micro-cracks or degradation. An alternative technique to overcome this limitation is nonlinear ultrasound. The principal difference between linear and nonlinear technique is that in the latter the existence and characteristics of defects are often related to an acoustic signal whose frequency differs from that of the input signal. This is related to the radiation and propagation of finite amplitude, especially high power, ultrasound and its interaction with discontinuities, such as cracks, interfaces and voids. Since material failure or degradation is usually preceded by some kind of nonlinear mechanical behavior before significant plastic deformation or material damage occurs. The presence of nonlinear terms in the wave equation causes intense acoustic waves to generate new waves at frequencies which are multiples of the initial sound wave frequency. The nonlinear effect can exert a strong effect on the

  11. The impact of signal normalization on seizure detection using line length features.

    Science.gov (United States)

    Logesparan, Lojini; Rodriguez-Villegas, Esther; Casson, Alexander J

    2015-10-01

    Accurate automated seizure detection remains a desirable but elusive target for many neural monitoring systems. While much attention has been given to the different feature extractions that can be used to highlight seizure activity in the EEG, very little formal attention has been given to the normalization that these features are routinely paired with. This normalization is essential in patient-independent algorithms to correct for broad-level differences in the EEG amplitude between people, and in patient-dependent algorithms to correct for amplitude variations over time. It is crucial, however, that the normalization used does not have a detrimental effect on the seizure detection process. This paper presents the first formal investigation into the impact of signal normalization techniques on seizure discrimination performance when using the line length feature to emphasize seizure activity. Comparing five normalization methods, based upon the mean, median, standard deviation, signal peak and signal range, we demonstrate differences in seizure detection accuracy (assessed as the area under a sensitivity-specificity ROC curve) of up to 52 %. This is despite the same analysis feature being used in all cases. Further, changes in performance of up to 22 % are present depending on whether the normalization is applied to the raw EEG itself or directly to the line length feature. Our results highlight the median decaying memory as the best current approach for providing normalization when using line length features, and they quantify the under-appreciated challenge of providing signal normalization that does not impair seizure detection algorithm performance.

  12. Molecular methods for the detection of mutations.

    Science.gov (United States)

    Monteiro, C; Marcelino, L A; Conde, A R; Saraiva, C; Giphart-Gassler, M; De Nooij-van Dalen, A G; Van Buuren-van Seggelen, V; Van der Keur, M; May, C A; Cole, J; Lehmann, A R; Steinsgrimsdottir, H; Beare, D; Capulas, E; Armour, J A

    2000-01-01

    We report the results of a collaborative study aimed at developing reliable, direct assays for mutation in human cells. The project used common lymphoblastoid cell lines, both with and without mutagen treatment, as a shared resource to validate the development of new molecular methods for the detection of low-level mutations in the presence of a large excess of normal alleles. As the "gold standard, " hprt mutation frequencies were also measured on the same samples. The methods under development included i) the restriction site mutation (RSM) assay, in which mutations lead to the destruction of a restriction site; ii) minisatellite length-change mutation, in which mutations lead to alleles containing new numbers of tandem repeat units; iii) loss of heterozygosity for HLA epitopes, in which antibodies can be used to direct selection for mutant cells; iv) multiple fluorescence-based long linker arm nucleotides assay (mf-LLA) technology, for the detection of substitutional mutations; v) detection of alterations in the TP53 locus using a (CA) array as the target for the screening; and vi) PCR analysis of lymphocytes for the presence of the BCL2 t(14:18) translocation. The relative merits of these molecular methods are discussed, and a comparison made with more "traditional" methods.

  13. A novel method for detection of apoptosis

    International Nuclear Information System (INIS)

    Zagariya, Alexander M.

    2012-01-01

    There are two different Angiotensin II (ANG II) peptides in nature: Human type (ANG II) and Bovine type (ANG II*). These eight amino acid peptides differ only at position 5 where Valine is replaced by Isoleucine in the Bovine type. They are present in all species studied so far. These amino acids are different by only one atom of carbon. This difference is so small, that it will allow any of ANG II, Bovine or Human antibodies to interact with all species and create a universal method for apoptosis detection. ANG II concentrations are found at substantially higher levels in apoptotic, compared to non-apoptotic, tissues. ANG II accumulation can lead to DNA damage, mutations, carcinogenesis and cell death. We demonstrate that Bovine antiserum can be used for universal detection of apoptosis. In 2010, the worldwide market for apoptosis detection reached the $20 billion mark and significantly increases each year. Most commercially available methods are related to Annexin V and TUNNEL. Our new method based on ANG II is more widely known to physicians and scientists compared to previously used methods. Our approach offers a novel alternative for assessing apoptosis activity with enhanced sensitivity, at a lower cost and ease of use.

  14. Hough transform methods used for object detection

    International Nuclear Information System (INIS)

    Qussay A Salih; Abdul Rahman Ramli; Md Mahmud Hassan Prakash

    2001-01-01

    The Hough transform (HT) is a robust parameter estimator of multi-dimensional features in images. The HT is an established technique which evidences a shape by mapping image edge points into a parameter space. The HT is technique which is used to isolate curves of a give shape in an image. The classical HT requires that the curve be specified in some parametric from and, hence is most commonly used in the detection of regular curves. The HT has been generalized so that it is capable of detecting arbitrary curved shapes. The main advantage of this transform technique is that it is very tolerant of gaps in the actual object boundaries the classical HT for the detection of line , we will indicate how it can be applied to the detection of arbitrary shapes. Sometimes the straight line HT is efficient enough to detect features such as artificial curves. The HT is an established technique for extracting geometric shapes based on the duality definition of the points on a curve and their parameters. This technique has been developed for extracting simple geometric shapes such as lines, circles and ellipses as well as arbitrary shapes. The HT provides robustness against discontinuous or missing features, points or edges are mapped into a partitioned parameter of Hough space as individual votes where peaks denote the feature of interest represented in a non-analytically tabular form. The main drawback of the HT technique is the computational requirement which has an exponential growth of memory space and processing time as the number of parameters used to represent a primitive increases. For this reason most of the research on the HT has focused on reducing the computational burden for extracting of arbitrary shapes under more general transformations include a overview of describing the methods for the detection image processing programs are frequently required to detect and particle classification in an industrial setting, a standard algorithms for this detection lines

  15. Methods for the selective detection of alkyne-presenting molecules and related compositions and systems

    Science.gov (United States)

    Valdez, Carlos A.; Vu, Alexander K.

    2017-10-17

    Provided herein are methods for selectively detecting an alkyne-presenting molecule in a sample and related detection reagents, compositions, methods and systems. The methods include contacting a detection reagent with the sample for a time and under a condition to allow binding of the detection reagent to the one or more alkyne-presenting molecules possibly present in the matrix to the detection reagent. The detection reagent includes an organic label moiety presenting an azide group. The binding of the azide group to the alkyne-presenting molecules results in emission of a signal from the organic label moiety.

  16. Detection of food irradiation - two analytical methods

    International Nuclear Information System (INIS)

    1994-01-01

    This publication summarizes the activities of Nordic countries in the field of detection of irradiated food. The National Food Agency of Denmark has coordinated the project. The two analytical methods investigated were: the gas-chromatographic determination of the hydrocarbon/lipid ratio in irradiated chicken meat, and a bioassay based on microelectrophoresis of DNA from single cells. Also a method for determination of o-tyrosine in the irradiated and non-irradiated chicken meat has been tested. The first method based on radiolytical changes in fatty acids, contained in chicken meat, has been tested and compared in the four Nordic countries. Four major hydrocarbons (C16:2, C16:3, C17:1 and C17:2) have been determined and reasonable agreement was observed between the dose level and hydrocarbons concentration. Results of a bioassay, where strand breaks of DNA are demonstrated by microelectrophoresis of single cells, prove a correlation between the dose levels and the pattern of DNA fragments migration. The hydrocarbon method can be applied to detect other irradiated, fat-containing foods, while the DNA method can be used for some animal and some vegetable foods as well.Both methods allow to determine the fact of food irradiation beyond any doubt, thus making them suitable for food control analysis. The detailed determination protocols are given. (EG)

  17. Research and Design of Rootkit Detection Method

    Science.gov (United States)

    Liu, Leian; Yin, Zuanxing; Shen, Yuli; Lin, Haitao; Wang, Hongjiang

    Rootkit is one of the most important issues of network communication systems, which is related to the security and privacy of Internet users. Because of the existence of the back door of the operating system, a hacker can use rootkit to attack and invade other people's computers and thus he can capture passwords and message traffic to and from these computers easily. With the development of the rootkit technology, its applications are more and more extensive and it becomes increasingly difficult to detect it. In addition, for various reasons such as trade secrets, being difficult to be developed, and so on, the rootkit detection technology information and effective tools are still relatively scarce. In this paper, based on the in-depth analysis of the rootkit detection technology, a new kind of the rootkit detection structure is designed and a new method (software), X-Anti, is proposed. Test results show that software designed based on structure proposed is much more efficient than any other rootkit detection software.

  18. Digitally generated excitation and near-baseband quadrature detection of rapid scan EPR signals.

    Science.gov (United States)

    Tseitlin, Mark; Yu, Zhelin; Quine, Richard W; Rinard, George A; Eaton, Sandra S; Eaton, Gareth R

    2014-12-01

    The use of multiple synchronized outputs from an arbitrary waveform generator (AWG) provides the opportunity to perform EPR experiments differently than by conventional EPR. We report a method for reconstructing the quadrature EPR spectrum from periodic signals that are generated with sinusoidal magnetic field modulation such as continuous wave (CW), multiharmonic, or rapid scan experiments. The signal is down-converted to an intermediate frequency (IF) that is less than the field scan or field modulation frequency and then digitized in a single channel. This method permits use of a high-pass analog filter before digitization to remove the strong non-EPR signal at the IF, that might otherwise overwhelm the digitizer. The IF is the difference between two synchronized X-band outputs from a Tektronix AWG 70002A, one of which is for excitation and the other is the reference for down-conversion. To permit signal averaging, timing was selected to give an exact integer number of full cycles for each frequency. In the experiments reported here the IF was 5kHz and the scan frequency was 40kHz. To produce sinusoidal rapid scans with a scan frequency eight times IF, a third synchronized output generated a square wave that was converted to a sine wave. The timing of the data acquisition with a Bruker SpecJet II was synchronized by an external clock signal from the AWG. The baseband quadrature signal in the frequency domain was reconstructed. This approach has the advantages that (i) the non-EPR response at the carrier frequency is eliminated, (ii) both real and imaginary EPR signals are reconstructed from a single physical channel to produce an ideal quadrature signal, and (iii) signal bandwidth does not increase relative to baseband detection. Spectra were obtained by deconvolution of the reconstructed signals for solid BDPA (1,3-bisdiphenylene-2-phenylallyl) in air, 0.2mM trityl OX63 in water, 15 N perdeuterated tempone, and a nitroxide with a 0.5G partially-resolved proton

  19. Detection test of wireless network signal strength and GPS positioning signal in underground pipeline

    Science.gov (United States)

    Li, Li; Zhang, Yunwei; Chen, Ling

    2018-03-01

    In order to solve the problem of selecting positioning technology for inspection robot in underground pipeline environment, the wireless network signal strength and GPS positioning signal testing are carried out in the actual underground pipeline environment. Firstly, the strength variation of the 3G wireless network signal and Wi-Fi wireless signal provided by China Telecom and China Unicom ground base stations are tested, and the attenuation law of these wireless signals along the pipeline is analyzed quantitatively and described. Then, the receiving data of the GPS satellite signal in the pipeline are tested, and the attenuation of GPS satellite signal under underground pipeline is analyzed. The testing results may be reference for other related research which need to consider positioning in pipeline.

  20. Detection method of a failed fuel

    International Nuclear Information System (INIS)

    Urata, Megumu; Uchida, Shunsuke; Utamura, Motoaki.

    1976-01-01

    Object: To divide a tank arrangement into a heating tank for the exclusive use of heating and a mixing tank for the exclusive use of mixing to thereby minimize the purifying amount of reactor water pumped from the interior of reactor and to considerably minimize the capacity of a purifier. Structure: In a detection method of a failed fuel comprising stopping a flow of coolant within fuel assemblies arranged in the coolant in a reactor container, sampling said coolant within the fuel assemblies, and detecting a radioactivity level of sampling liquid, the improvement of the method comprising the steps of heating a part of said coolant removed from the interior of said reactor container, mixing said heated coolant into the remainder of said removed coolant, pouring said mixed liquid into said fuel assemblies, and after a lapse of given time, sampling the liquid poured into said fuel assemblies. (Kawakami, Y.)

  1. Method for detecting a failed fuel

    International Nuclear Information System (INIS)

    Utamura, Motoaki; Urata, Megumu; Uchida, Shunsuke.

    1976-01-01

    Purpose: To provide a method for the detection of failed fuel by pouring hot water, in which pouring speed of liquid to be poured and temperature of the liquid are controlled to prevent the leakage of the liquid. Constitution: The method comprises blocking the top of a fuel assembly arranged in coolant to stop a flow of coolant, pouring a liquid higher in temperature than that of coolant into the fuel assembly, sampling the liquid poured, and measuring the concentration of radioactivity of coolant already subjected to sampling to detect a failed fuel. At this time, controlling is made so that the pouring speed of the poured liquid is set to about 25 l/min, and an increased portion of temperature from the temperature of liquid to the temperature of coolant is set to a level less than about 15 0 C. (Furukawa, Y.)

  2. System and method for anomaly detection

    Science.gov (United States)

    Scherrer, Chad

    2010-06-15

    A system and method for detecting one or more anomalies in a plurality of observations is provided. In one illustrative embodiment, the observations are real-time network observations collected from a stream of network traffic. The method includes performing a discrete decomposition of the observations, and introducing derived variables to increase storage and query efficiencies. A mathematical model, such as a conditional independence model, is then generated from the formatted data. The formatted data is also used to construct frequency tables which maintain an accurate count of specific variable occurrence as indicated by the model generation process. The formatted data is then applied to the mathematical model to generate scored data. The scored data is then analyzed to detect anomalies.

  3. Mental-disorder detection using chaos and nonlinear dynamical analysis of photoplethysmographic signals

    International Nuclear Information System (INIS)

    Pham, Tuan D.; Thang, Truong Cong; Oyama-Higa, Mayumi; Sugiyama, Masahide

    2013-01-01

    Highlights: • Chaos and nonlinear dynamical analysis are applied for mental-disorder detection. • Experimental results show significant detection improvement with feature synergy. • Proposed approach is effective for analysis of photoplethysmographic signals. • Proposed approach is promising for developing automated mental-health systems. -- Abstract: Mental disorder can be defined as a psychological disturbance of thought or emotion. In particular, depression is a mental disease which can ultimately lead to death from suicide. If depression is identified, it can be treated with medication and psychotherapy. However, the diagnosis of depression is difficult and there are currently no any quick and reliable medical tests to detect if someone is depressed. This is because the exact cause of depression is still unknown given the belief that depression results in chemical brain changes, genetic disorder, stress, or the combination of these problems. Photoplethysmography has recently been realized as a non-invasive optical technique that can give new insights into the physiology and pathophysiology of the central and peripheral nervous systems. We present in this paper an automated mental-disorder detection approach in a general sense based on a novel synergy of chaos and nonlinear dynamical methods for the analysis of photoplethysmographic finger pulse waves of mental and control subjects. Such an approach can be applied for automated detection of depression as a special case. Because of the computational effectiveness of the studied methods and low cost of generation of the physiological signals, the proposed automated detection of mental illness is feasible for real-life applications including self-assessment, self-monitoring, and computerized health care

  4. Automated Detection of Driver Fatigue Based on AdaBoost Classifier with EEG Signals

    Directory of Open Access Journals (Sweden)

    Jianfeng Hu

    2017-08-01

    Full Text Available Purpose: Driving fatigue has become one of the important causes of road accidents, there are many researches to analyze driver fatigue. EEG is becoming increasingly useful in the measuring fatigue state. Manual interpretation of EEG signals is impossible, so an effective method for automatic detection of EEG signals is crucial needed.Method: In order to evaluate the complex, unstable, and non-linear characteristics of EEG signals, four feature sets were computed from EEG signals, in which fuzzy entropy (FE, sample entropy (SE, approximate Entropy (AE, spectral entropy (PE, and combined entropies (FE + SE + AE + PE were included. All these feature sets were used as the input vectors of AdaBoost classifier, a boosting method which is fast and highly accurate. To assess our method, several experiments including parameter setting and classifier comparison were conducted on 28 subjects. For comparison, Decision Trees (DT, Support Vector Machine (SVM and Naive Bayes (NB classifiers are used.Results: The proposed method (combination of FE and AdaBoost yields superior performance than other schemes. Using FE feature extractor, AdaBoost achieves improved area (AUC under the receiver operating curve of 0.994, error rate (ERR of 0.024, Precision of 0.969, Recall of 0.984, F1 score of 0.976, and Matthews correlation coefficient (MCC of 0.952, compared to SVM (ERR at 0.035, Precision of 0.957, Recall of 0.974, F1 score of 0.966, and MCC of 0.930 with AUC of 0.990, DT (ERR at 0.142, Precision of 0.857, Recall of 0.859, F1 score of 0.966, and MCC of 0.716 with AUC of 0.916 and NB (ERR at 0.405, Precision of 0.646, Recall of 0.434, F1 score of 0.519, and MCC of 0.203 with AUC of 0.606. It shows that the FE feature set and combined feature set outperform other feature sets. AdaBoost seems to have better robustness against changes of ratio of test samples for all samples and number of subjects, which might therefore aid in the real-time detection of driver

  5. Method and device for detecting radiatons

    International Nuclear Information System (INIS)

    Borel, J.; Goascoz, V.

    1979-01-01

    The method consists in fabricating an MOS transistor comprising a drain region and a source region separated from each other by a bulk region of opposite doping type relative to the first two regions, in delivering the radiation to be detected into the carrier-collection region of the MOS transistor, in leaving the bulk region at a floating potential and in collecting the drain-source current of the transistor

  6. Noise texture and signal detectability in propagation-based x-ray phase-contrast tomography

    International Nuclear Information System (INIS)

    Chou, Cheng-Ying; Anastasio, Mark A.

    2010-01-01

    Purpose: X-ray phase-contrast tomography (PCT) is a rapidly emerging imaging modality for reconstructing estimates of an object's three-dimensional x-ray refractive index distribution. Unlike conventional x-ray computed tomography methods, the statistical properties of the reconstructed images in PCT remain unexplored. The purpose of this work is to quantitatively investigate noise propagation in PCT image reconstruction. Methods: The authors derived explicit expressions for the autocovariance of the reconstructed absorption and refractive index images to characterize noise texture and understand how the noise properties are influenced by the imaging geometry. Concepts from statistical detection theory were employed to understand how the imaging geometry-dependent statistical properties affect the signal detection performance in a signal-known-exactly/background-known-exactly task. Results: The analytical formulas for the phase and absorption autocovariance functions were implemented numerically and compared to the corresponding empirical values, and excellent agreement was found. They observed that the reconstructed refractive images are highly spatially correlated, while the absorption images are not. The numerical results confirm that the strength of the covariance is scaled by the detector spacing. Signal detection studies were conducted, employing a numerical observer. The detection performance was found to monotonically increase as the detector-plane spacing was increased. Conclusions: The authors have conducted the first quantitative investigation of noise propagation in PCT image reconstruction. The reconstructed refractive images were found to be highly spatially correlated, while absorption images were not. This is due to the presence of a Fourier space singularity in the reconstruction formula for the refraction images. The statistical analysis may facilitate the use of task-based image quality measures to further develop and optimize this emerging

  7. Noise texture and signal detectability in propagation-based x-ray phase-contrast tomography

    Energy Technology Data Exchange (ETDEWEB)

    Chou, Cheng-Ying; Anastasio, Mark A. [Department of Bio-Industrial Mechatronics Engineering, National Taiwan University, 1, Section 4, Roosevelt Road, Taipei, Taiwan 106, Taiwan (China); Department of Biomedical Engineering, Medical Imaging Research Center, Illinois Institute of Technology, 3440 S. Dearborn Street, E1-116, Chicago, Illinois 60616 (United States)

    2010-01-15

    Purpose: X-ray phase-contrast tomography (PCT) is a rapidly emerging imaging modality for reconstructing estimates of an object's three-dimensional x-ray refractive index distribution. Unlike conventional x-ray computed tomography methods, the statistical properties of the reconstructed images in PCT remain unexplored. The purpose of this work is to quantitatively investigate noise propagation in PCT image reconstruction. Methods: The authors derived explicit expressions for the autocovariance of the reconstructed absorption and refractive index images to characterize noise texture and understand how the noise properties are influenced by the imaging geometry. Concepts from statistical detection theory were employed to understand how the imaging geometry-dependent statistical properties affect the signal detection performance in a signal-known-exactly/background-known-exactly task. Results: The analytical formulas for the phase and absorption autocovariance functions were implemented numerically and compared to the corresponding empirical values, and excellent agreement was found. They observed that the reconstructed refractive images are highly spatially correlated, while the absorption images are not. The numerical results confirm that the strength of the covariance is scaled by the detector spacing. Signal detection studies were conducted, employing a numerical observer. The detection performance was found to monotonically increase as the detector-plane spacing was increased. Conclusions: The authors have conducted the first quantitative investigation of noise propagation in PCT image reconstruction. The reconstructed refractive images were found to be highly spatially correlated, while absorption images were not. This is due to the presence of a Fourier space singularity in the reconstruction formula for the refraction images. The statistical analysis may facilitate the use of task-based image quality measures to further develop and optimize this emerging

  8. Driver Fatigue Detection System Using Electroencephalography Signals Based on Combined Entropy Features

    Directory of Open Access Journals (Sweden)

    Zhendong Mu

    2017-02-01

    Full Text Available Driver fatigue has become one of the major causes of traffic accidents, and is a complicated physiological process. However, there is no effective method to detect driving fatigue. Electroencephalography (EEG signals are complex, unstable, and non-linear; non-linear analysis methods, such as entropy, maybe more appropriate. This study evaluates a combined entropy-based processing method of EEG data to detect driver fatigue. In this paper, 12 subjects were selected to take part in an experiment, obeying driving training in a virtual environment under the instruction of the operator. Four types of enthrones (spectrum entropy, approximate entropy, sample entropy and fuzzy entropy were used to extract features for the purpose of driver fatigue detection. Electrode selection process and a support vector machine (SVM classification algorithm were also proposed. The average recognition accuracy was 98.75%. Retrospective analysis of the EEG showed that the extracted features from electrodes T5, TP7, TP8 and FP1 may yield better performance. SVM classification algorithm using radial basis function as kernel function obtained better results. A combined entropy-based method demonstrates good classification performance for studying driver fatigue detection.

  9. An Adaptive S-Method to Analyze Micro-Doppler Signals for Human Activity Classification.

    Science.gov (United States)

    Li, Fangmin; Yang, Chao; Xia, Yuqing; Ma, Xiaolin; Zhang, Tao; Zhou, Zhou

    2017-11-29

    In this paper, we propose the multiwindow Adaptive S-method (AS-method) distribution approach used in the time-frequency analysis for radar signals. Based on the results of orthogonal Hermite functions that have good time-frequency resolution, we vary the length of window to suppress the oscillating component caused by cross-terms. This method can bring a better compromise in the auto-terms concentration and cross-terms suppressing, which contributes to the multi-component signal separation. Finally, the effective micro signal is extracted by threshold segmentation and envelope extraction. To verify the proposed method, six states of motion are separated by a classifier of a support vector machine (SVM) trained to the extracted features. The trained SVM can detect a human subject with an accuracy of 95.4% for two cases without interference.

  10. An Adaptive S-Method to Analyze Micro-Doppler Signals for Human Activity Classification

    Directory of Open Access Journals (Sweden)

    Fangmin Li

    2017-11-01

    Full Text Available In this paper, we propose the multiwindow Adaptive S-method (AS-method distribution approach used in the time-frequency analysis for radar signals. Based on the results of orthogonal Hermite functions that have good time-frequency resolution, we vary the length of window to suppress the oscillating component caused by cross-terms. This method can bring a better compromise in the auto-terms concentration and cross-terms suppressing, which contributes to the multi-component signal separation. Finally, the effective micro signal is extracted by threshold segmentation and envelope extraction. To verify the proposed method, six states of motion are separated by a classifier of a support vector machine (SVM trained to the extracted features. The trained SVM can detect a human subject with an accuracy of 95.4% for two cases without interference.

  11. Development of precursors recognition methods in vector signals

    Science.gov (United States)

    Kapralov, V. G.; Elagin, V. V.; Kaveeva, E. G.; Stankevich, L. A.; Dremin, M. M.; Krylov, S. V.; Borovov, A. E.; Harfush, H. A.; Sedov, K. S.

    2017-10-01

    Precursor recognition methods in vector signals of plasma diagnostics are presented. Their requirements and possible options for their development are considered. In particular, the variants of using symbolic regression for building a plasma disruption prediction system are discussed. The initial data preparation using correlation analysis and symbolic regression is discussed. Special attention is paid to the possibility of using algorithms in real time.

  12. DIAGNOSTIC METHODS IN BREAST CANCER DETECTION

    Directory of Open Access Journals (Sweden)

    Kristijana Hertl

    2018-02-01

    Full Text Available Background. In the world as well as in Slovenia, breast cancer is the most frequent female cancer. Due to its high incidence, it appears to be a serious health and economic problem. Content. Among other, tumour size at diagnosis, is an important prognostic factors of the course of the disease. The probability of axillary lymph node involvement as well as distant metastases is greater in larger tumours. This is the reason that encouraged the development of various diagnostic methods for early detection of small, clinically non-palpable breast tumours. Mammography, however, remains the »golden standard« of early breast cancer detection. It is the basic diagnostic method applied in all symptomatic women over 35 years of age and in asymptomatic women over 40 years of age. Ultrasonography (US, additional projections, magnetic resonance imaging (MRI and ductography are regarded as complementary diagnostic breast imaging techniques in addition to mammography. The detected changes in the breast can be further confirmed by US-, MR-guided or stereotactic biopsy. If necessary, surgical biopsy and the excision of a tissue sample, after wire or isotope localisation of the nonpalpable lesion, can be performed. Conclusions. Any of the above mentioned diagnostic methods has advantages as well as drawbacks and only detailed knowledge and understanding of each of them may assure the best option.

  13. FAULT DETECTION AND LOCALIZATION IN MOTORCYCLES BASED ON THE CHAIN CODE OF PSEUDOSPECTRA AND ACOUSTIC SIGNALS

    Directory of Open Access Journals (Sweden)

    B. S. Anami

    2013-06-01

    Full Text Available Vehicles produce sound signals with varying temporal and spectral properties under different working conditions. These sounds are indicative of the condition of the engine. Fault diagnosis is a significantly difficult task in geographically remote places where expertise is scarce. Automated fault diagnosis can assist riders to assess the health condition of their vehicles. This paper presents a method for fault detection and location in motorcycles based on the chain code of the pseudospectra and Mel-frequency cepstral coefficient (MFCC features of acoustic signals. The work comprises two stages: fault detection and fault location. The fault detection stage uses the chain code of the pseudospectrum as a feature vector. If the motorcycle is identified as faulty, the MFCCs of the same sample are computed and used as features for fault location. Both stages employ dynamic time warping for the classification of faults. Five types of faults in motorcycles are considered in this work. Observed classification rates are over 90% for the fault detection stage and over 94% for the fault location stage. The work identifies other interesting applications in the development of acoustic fingerprints for fault diagnosis of machinery, tuning of musical instruments, medical diagnosis, etc.

  14. Analytical detection methods for irradiated foods

    International Nuclear Information System (INIS)

    1991-03-01

    The present publication is a review of scientific literature on the analytical identification of foods treated with ionizing radiation and the quantitative determination of absorbed dose of radiation. Because of the extremely low level of chemical changes resulting from irradiation or because of the lack of specificity to irradiation of any chemical changes, a few methods of quantitative determination of absorbed dose have shown promise until now. On the other hand, the present review has identified several possible methods, which could be used, following further research and testing, for the identification of irradiated foods. An IAEA Co-ordinated Research Programme on Analytical Detection Methods for Irradiation Treatment of Food ('ADMIT'), established in 1990, is currently investigating many of the methods cited in the present document. Refs and tab

  15. Detecting Activation in fMRI Data: An Approach Based on Sparse Representation of BOLD Signal

    Directory of Open Access Journals (Sweden)

    Blanca Guillen

    2018-01-01

    Full Text Available This paper proposes a simple yet effective approach for detecting activated voxels in fMRI data by exploiting the inherent sparsity property of the BOLD signal in temporal and spatial domains. In the time domain, the approach combines the General Linear Model (GLM with a Least Absolute Deviation (LAD based regression method regularized by the pseudonorm l0 to promote sparsity in the parameter vector of the model. In the spatial domain, detection of activated regions is based on thresholding the spatial map of estimated parameters associated with a particular stimulus. The threshold is calculated by exploiting the sparseness of the BOLD signal in the spatial domain assuming a Laplacian distribution model. The proposed approach is validated using synthetic and real fMRI data. For synthetic data, results show that the proposed approach is able to detect most activated voxels without any false activation. For real data, the method is evaluated through comparison with the SPM software. Results indicate that this approach can effectively find activated regions that are similar to those found by SPM, but using a much simpler approach. This study may lead to the development of robust spatial approaches to further simplifying the complexity of classical schemes.

  16. Can Technical Analysis Signals Detect Price Reactions Around Earnings Announcement?: Evidence from Indonesia

    OpenAIRE

    Dedhy Sulistiawan; Jogiyanto Hartono

    2014-01-01

    This study examines whether technical analysis signals can detect price reactions before and after earnings announcement dates in Indonesian stock market. Earnings announcements produce reactions, both before and after the announcements. Informed investors may use private information before earnings announcements (Christophe, Ferri and Angel, 2004; Porter, 1992). Using technical analysis signals, this study expects that retail investors (uninformed investors) can detect preannouncements react...

  17. Methods and tools to detect thermal noise in fast reactors

    International Nuclear Information System (INIS)

    Motta, M.; Giovannini, R.

    1985-07-01

    The Specialists' Meeting on ''Methods and Tools to Detect Thermal Noise in Fast Reactors'' was held in Bologna on 8-10 October 1984. The meeting was hosted by the ENEA and was sponsored by the IAEA on the recommendation of the International Working Group on Fast Reactors. 17 participants attended the meeting from France, the Federal Republic of Germany, Italy, Japan, the United Kingdom, Joint Research Centre of CEC and from IAEA. The meeting was presided over by Prof. Mario Motta of Italy. The purpose of the meeting was to review and discuss methods and tools for temperature noise detection and related analysis as a potential means for detecting local blockages in fuel and blanket subassemblies and other faults in LMFBR. The meeting was divided into four technical sessions as follows: 1. National review presentations on application purposes and research activities for thermal noise detection. (5 papers); 2. Detection instruments and electronic equipment for temperature measurements in fast reactors. (5 papers); 3. Physical models. (2 papers); 4. Signal processing techniques. (3 papers). A separate abstract was prepared for each of these papers

  18. Postural Response Signal Characteristics Identified by Method of Developed Statokinesigram

    Directory of Open Access Journals (Sweden)

    Barbolyas Boris

    2015-12-01

    Full Text Available Human postural system is taken as complex biological system with specific input and output time characteristics, in this study. Evaluation of measured output characteristics is useful in medical diagnostics or in describing postural system disorders. System theory principle provide suitable basis for postural signals analysis. Participating volunteers were instructed to maintain quiet upright stance posture on firm support surface of stabilometric platform for 60s. Postural system actuation was realized by vibration stimuli applied bilaterally on Achilles tendons for 20s. Postural reaction signal, its time profile and static and dynamic characteristics were evaluated by Method of Developed Statokinesigram Trajectory (MDST.

  19. A case of reocclusion of the renal artery diagnosed by the color Doppler method with evaluation of blood flow direction in the collateral circulation of the kidney in addition to the non-detectable blood signal in the renal artery.

    Science.gov (United States)

    Hirano, Megumi; Ohta, Tomoyuki; Nakata, Norio; Kawakami, Reina; Takamura, Kimihiro; Matsuda, Tosiharu; Nishioka, Makiko; Sakurai, Tomoo; Matsuo, Kouichi; Miyamoto, Yukio

    2014-10-01

    A 23-year-old woman was referred to our hospital for an interventional procedure for chronic total occlusion of the right renal artery, probably due to fibromuscular dysplasia (FMD), and for control of renal vascular hypertension. Before percutaneous transluminal renal angioplasty (PTRA), aortography revealed collateral circulation to the right kidney from the lower lumbar artery. After PTRA, however, blood flow in the renal side of the collateral circulation flowed outside from the right renal parenchyma. 4 months later, we could not find a blood flow signal in the right renal artery, and there was a contrary flow signal in the right kidney parenchyma continuously from the extrahilar vessel, possibly a collateral artery. These findings indicated reocclusion of the right artery. We confirmed reocclusion of the renal artery and collateral feeding by contrast dynamic computed tomography (CT), and PTRA was performed again without any complications or reocclusion for 5 months. This is the first case report showing that a back-flowing signal in the right renal parenchyma from the extrahilar artery is useful as an indirect finding suggesting reocclusion.

  20. Early Warning Signals of Ecological Transitions: Methods for Spatial Patterns

    Science.gov (United States)

    Brock, William A.; Carpenter, Stephen R.; Ellison, Aaron M.; Livina, Valerie N.; Seekell, David A.; Scheffer, Marten; van Nes, Egbert H.; Dakos, Vasilis

    2014-01-01

    A number of ecosystems can exhibit abrupt shifts between alternative stable states. Because of their important ecological and economic consequences, recent research has focused on devising early warning signals for anticipating such abrupt ecological transitions. In particular, theoretical studies show that changes in spatial characteristics of the system could provide early warnings of approaching transitions. However, the empirical validation of these indicators lag behind their theoretical developments. Here, we summarize a range of currently available spatial early warning signals, suggest potential null models to interpret their trends, and apply them to three simulated spatial data sets of systems undergoing an abrupt transition. In addition to providing a step-by-step methodology for applying these signals to spatial data sets, we propose a statistical toolbox that may be used to help detect approaching transitions in a wide range of spatial data. We hope that our methodology together with the computer codes will stimulate the application and testing of spatial early warning signals on real spatial data. PMID:24658137

  1. Waterborne Pathogens: Detection Methods and Challenges

    Directory of Open Access Journals (Sweden)

    Flor Yazmín Ramírez-Castillo

    2015-05-01

    Full Text Available Waterborne pathogens and related diseases are a major public health concern worldwide, not only by the morbidity and mortality that they cause, but by the high cost that represents their prevention and treatment. These diseases are directly related to environmental deterioration and pollution. Despite the continued efforts to maintain water safety, waterborne outbreaks are still reported globally. Proper assessment of pathogens on water and water quality monitoring are key factors for decision-making regarding water distribution systems’ infrastructure, the choice of best water treatment and prevention waterborne outbreaks. Powerful, sensitive and reproducible diagnostic tools are developed to monitor pathogen contamination in water and be able to detect not only cultivable pathogens but also to detect the occurrence of viable but non-culturable microorganisms as well as the presence of pathogens on biofilms. Quantitative microbial risk assessment (QMRA is a helpful tool to evaluate the scenarios for pathogen contamination that involve surveillance, detection methods, analysis and decision-making. This review aims to present a research outlook on waterborne outbreaks that have occurred in recent years. This review also focuses in the main molecular techniques for detection of waterborne pathogens and the use of QMRA approach to protect public health.

  2. Doppler method leak detection for LMFBR steam generators. Pt. 3. Investigation of detection sensitivity and method

    International Nuclear Information System (INIS)

    Kumagai, Hiromichi; Kinoshita, Izumi

    2001-01-01

    To prevent the expansion of tube damage and to maintain structural integrity in the steam generators (SGs) of a fast breeder reactor (FBR), it is necessary to detect precisely and immediately any leakage of water from heat transfer tubes. Therefore, the Doppler method was developed. Previous studies have revealed that, in the SG full-sector model that simulates actual SGs, the Doppler method can detect bubbles of 0.4 l/s within a few seconds. However in consideration of the dissolution rate of hydrogen generated by a sodium-water reaction even from a small water leak, it is necessary to detect smaller leakages of water from the heat transfer tubes. The detection sensitivity of the Doppler method and the influence of background noise were experimentally investigated. In-water experiments were performed using the SG model. The results show that the Doppler method can detect bubbles of 0.01 l/s (equivalent to a water leak rate of about 0.01 g/s) within a few seconds and that the background noise has little effect on water leak detection performance. The Doppler method thus has great potential for the detection of water leakage in SGs. (author)

  3. Novel Methods of Hydrogen Leak Detection

    International Nuclear Information System (INIS)

    Pushpinder S Puri

    2006-01-01

    With the advent of the fuel cell technology and a drive for clean fuel, hydrogen gas is emerging as a leading candidate for the fuel of choice. For hydrogen to become a consumer fuel for automotive and domestic power generation, safety is paramount. It is, therefore, desired to have a method and system for hydrogen leak detection using odorant which can incorporate a uniform concentration of odorant in the hydrogen gas, when odorants are mixed in the hydrogen storage or delivery means. It is also desired to develop methods where the odorant is not added to the bulk hydrogen, keeping it free of the odorization additives. When odorants are not added to the hydrogen gas in the storage or delivery means, methods must be developed to incorporate odorant in the leaking gas so that leaks can be detected by small. Further, when odorants are not added to the stored hydrogen, it may also be desirable to observe leaks by sight by discoloration of the surface of the storage or transportation vessels. A series of novel solutions are proposed which address the issues raised above. These solutions are divided into three categories as follows: 1. Methods incorporating an odorant in the path of hydrogen leak as opposed to adding it to the hydrogen gas. 2. Methods where odorants are generated in-situ by chemical reaction with the leaking hydrogen 3. Methods of dispensing and storing odorants in high pressure hydrogen gas which release odorants to the gas at a uniform and predetermined rates. Use of one or more of the methods described here in conjunction with appropriate engineering solutions will assure the ultimate safety of hydrogen use as a commercial fuel. (authors)

  4. Tiny Grains Give Huge Gains: Nanocrystal–Based Signal Amplification for Biomolecule Detection

    Science.gov (United States)

    Tong, Sheng; Ren, Binbin; Zheng, Zhilan; Shen, Han; Bao, Gang

    2013-01-01

    Nanocrystals, despite their tiny sizes, contain thousands to millions of atoms. Here we show that the large number of atoms packed in each metallic nanocrystal can provide a huge gain in signal amplification for biomolecule detection. We have devised a highly sensitive, linear amplification scheme by integrating the dissolution of bound nanocrystals and metal-induced stoichiometric chromogenesis, and demonstrated that signal amplification is fully defined by the size and atom density of nanocrystals, which can be optimized through well-controlled nanocrystal synthesis. Further, the rich library of chromogenic reactions allows implementation of this scheme in various assay formats, as demonstrated by the iron oxide nanoparticle linked immunosorbent assay (ILISA) and blotting assay developed in this study. Our results indicate that, owing to the inherent simplicity, high sensitivity and repeatability, the nanocrystal based amplification scheme can significantly improve biomolecule quantification in both laboratory research and clinical diagnostics. This novel method adds a new dimension to current nanoparticle-based bioassays. PMID:23659350

  5. Novel method for detecting weak magnetic fields at low frequencies

    Science.gov (United States)

    González-Martínez, S.; Castillo-Torres, J.; Mendoza-Santos, J. C.; Zamorano-Ulloa, R.

    2005-06-01

    A low-level-intensity magnetic field detection system has been designed and developed based on the amplification-selection process of signals. This configuration is also very sensitive to magnetic field changes produced by harmonic-like electrical currents transported in finite-length wires. Experimental and theoretical results of magnetic fields detection as low as 10-9T at 120Hz are also presented with an accuracy of around 13%. The assembled equipment is designed to measure an electromotive force induced in a free-magnetic-core coil in order to recover signals which are previously selected, despite the fact that their intensities are much lower than the environment electromagnetic radiation. The prototype has a signal-to-noise ratio of 60dB. This system also presents the advantage for using it as a portable unit of measurement. The concept and prototype may be applied, for example, as a nondestructive method to analyze any corrosion formation in metallic oil pipelines which are subjected to cathodic protection.

  6. New methods for leaks detection and localisation using acoustic emission

    International Nuclear Information System (INIS)

    Boulanger, P.

    1993-01-01

    Real time monitoring of Pressurized Water nuclear Reactor secondary coolant system tends to integrate digital processing machines. In this context, the method of acoustic emission seems to exhibit good performances. Its principle is based on passive listening of noises emitted by local micro-displacements inside a material under stress which propagate as elastic waves. The lack of a priori knowledge on leak signals leads us to go deeper into understanding flow induced noise generation. Our studies are conducted using a simple leak model depending on the geometry and the king of flow inside the slit. Detection and localization problems are formulated according to the maximum likelihood principle. For detection, the methods using a indicator of similarity (correlation, higher order correlation) seems to give better results than classical ones (rms value, envelope, filter banks). For leaks location, a large panel of classical (generalized inter-correlation) and innovative (convolution, adaptative, higher order statistics) methods of time delay estimation are presented. The last part deals with the applications of higher order statistics. The analysis of higher order estimators of a non linear non Gaussian stochastic process family, the improvement of non linear prediction performances and the optimal-order choice problem are addressed in simple analytic cases. At last, possible applications to leak signals analysis are pointed out. (authors).264 refs., 7 annexes

  7. Bat detective-Deep learning tools for bat acoustic signal detection.

    Science.gov (United States)

    Mac Aodha, Oisin; Gibb, Rory; Barlow, Kate E; Browning, Ella; Firman, Michael; Freeman, Robin; Harder, Briana; Kinsey, Libby; Mead, Gary R; Newson, Stuart E; Pandourski, Ivan; Parsons, Stuart; Russ, Jon; Szodoray-Paradi, Abigel; Szodoray-Paradi, Farkas; Tilova, Elena; Girolami, Mark; Brostow, Gabriel; Jones, Kate E

    2018-03-01

    Passive acoustic sensing has emerged as a powerful tool for quantifying anthropogenic impacts on biodiversity, especially for echolocating bat species. To better assess bat population trends there is a critical need for accurate, reliable, and open source tools that allow the detection and classification of bat calls in large collections of audio recordings. The majority of existing tools are commercial or have focused on the species classification task, neglecting the important problem of first localizing echolocation calls in audio which is particularly problematic in noisy recordings. We developed a convolutional neural network based open-source pipeline for detecting ultrasonic, full-spectrum, search-phase calls produced by echolocating bats. Our deep learning algorithms were trained on full-spectrum ultrasonic audio collected along road-transects across Europe and labelled by citizen scientists from www.batdetective.org. When compared to other existing algorithms and commercial systems, we show significantly higher detection performance of search-phase echolocation calls with our test sets. As an example application, we ran our detection pipeline on bat monitoring data collected over five years from Jersey (UK), and compared results to a widely-used commercial system. Our detection pipeline can be used for the automatic detection and monitoring of bat populations, and further facilitates their use as indicator species on a large scale. Our proposed pipeline makes only a small number of bat specific design decisions, and with appropriate training data it could be applied to detecting other species in audio. A crucial novelty of our work is showing that with careful, non-trivial, design and implementation considerations, state-of-the-art deep learning methods can be used for accurate and efficient monitoring in audio.

  8. Compressive sensing-based electrostatic sensor array signal processing and exhausted abnormal debris detecting

    Science.gov (United States)

    Tang, Xin; Chen, Zhongsheng; Li, Yue; Yang, Yongmin

    2018-05-01

    When faults happen at gas path components of gas turbines, some sparsely-distributed and charged debris will be generated and released into the exhaust gas. The debris is called abnormal debris. Electrostatic sensors can detect the debris online and further indicate the faults. It is generally considered that, under a specific working condition, a more serious fault generates more and larger debris, and a piece of larger debris carries more charge. Therefore, the amount and charge of the abnormal debris are important indicators of the fault severity. However, because an electrostatic sensor can only detect the superposed effect on the electrostatic field of all the debris, it can hardly identify the amount and position of the debris. Moreover, because signals of electrostatic sensors depend on not only charge but also position of debris, and the position information is difficult to acquire, measuring debris charge accurately using the electrostatic detecting method is still a technical difficulty. To solve these problems, a hemisphere-shaped electrostatic sensors' circular array (HSESCA) is used, and an array signal processing method based on compressive sensing (CS) is proposed in this paper. To research in a theoretical framework of CS, the measurement model of the HSESCA is discretized into a sparse representation form by meshing. In this way, the amount and charge of the abnormal debris are described as a sparse vector. It is further reconstructed by constraining l1-norm when solving an underdetermined equation. In addition, a pre-processing method based on singular value decomposition and a result calibration method based on weighted-centroid algorithm are applied to ensure the accuracy of the reconstruction. The proposed method is validated by both numerical simulations and experiments. Reconstruction errors, characteristics of the results and some related factors are discussed.

  9. DETECTION OF POTENTIAL TRANSIT SIGNALS IN 16 QUARTERS OF KEPLER MISSION DATA

    International Nuclear Information System (INIS)

    Tenenbaum, Peter; Jenkins, Jon M.; Seader, Shawn; Burke, Christopher J.; Christiansen, Jessie L.; Rowe, Jason F.; Caldwell, Douglas A.; Clarke, Bruce D.; Coughlin, Jeffrey L.; Li, Jie; Quintana, Elisa V.; Smith, Jeffrey C.; Thompson, Susan E.; Twicken, Joseph D.; Haas, Michael R.; Henze, Christopher E.; Hunter, Roger C.; Sanderfer, Dwight T.; Campbell, Jennifer R.; Girouard, Forrest R.

    2014-01-01

    We present the results of a search for potential transit signals in 4 yr of photometry data acquired by the Kepler mission. The targets of the search include 111,800 stars which were observed for the entire interval and 85,522 stars which were observed for a subset of the interval. We found that 9743 targets contained at least one signal consistent with the signature of a transiting or eclipsing object where the criteria for detection are periodicity of the detected transits, adequate signal-to-noise ratio, and acceptance by a number of tests which reject false positive detections. When targets that had produced a signal were searched repeatedly, an additional 6542 signals were detected on 3223 target stars, for a total of 16,285 potential detections. Comparison of the set of detected signals with a set of known and vetted transit events in the Kepler field of view shows that the recovery rate for these signals is 96.9%. The ensemble properties of the detected signals are reviewed

  10. DETECTION OF POTENTIAL TRANSIT SIGNALS IN 16 QUARTERS OF KEPLER MISSION DATA

    Energy Technology Data Exchange (ETDEWEB)

    Tenenbaum, Peter; Jenkins, Jon M.; Seader, Shawn; Burke, Christopher J.; Christiansen, Jessie L.; Rowe, Jason F.; Caldwell, Douglas A.; Clarke, Bruce D.; Coughlin, Jeffrey L.; Li, Jie; Quintana, Elisa V.; Smith, Jeffrey C.; Thompson, Susan E.; Twicken, Joseph D. [SETI Institute/NASA Ames Research Center, Moffett Field, CA 94305 (United States); Haas, Michael R.; Henze, Christopher E.; Hunter, Roger C.; Sanderfer, Dwight T. [NASA Ames Research Center, Moffett Field, CA 94305 (United States); Campbell, Jennifer R.; Girouard, Forrest R., E-mail: peter.tenenbaum@nasa.gov [Orbital Sciences Corporation/NASA Ames Research Center, Moffett Field, CA 94305 (United States); and others

    2014-03-01

    We present the results of a search for potential transit signals in 4 yr of photometry data acquired by the Kepler mission. The targets of the search include 111,800 stars which were observed for the entire interval and 85,522 stars which were observed for a subset of the interval. We found that 9743 targets contained at least one signal consistent with the signature of a transiting or eclipsing object where the criteria for detection are periodicity of the detected transits, adequate signal-to-noise ratio, and acceptance by a number of tests which reject false positive detections. When targets that had produced a signal were searched repeatedly, an additional 6542 signals were detected on 3223 target stars, for a total of 16,285 potential detections. Comparison of the set of detected signals with a set of known and vetted transit events in the Kepler field of view shows that the recovery rate for these signals is 96.9%. The ensemble properties of the detected signals are reviewed.

  11. Bayesian Methods for Radiation Detection and Dosimetry

    International Nuclear Information System (INIS)

    Peter G. Groer

    2002-01-01

    We performed work in three areas: radiation detection, external and internal radiation dosimetry. In radiation detection we developed Bayesian techniques to estimate the net activity of high and low activity radioactive samples. These techniques have the advantage that the remaining uncertainty about the net activity is described by probability densities. Graphs of the densities show the uncertainty in pictorial form. Figure 1 below demonstrates this point. We applied stochastic processes for a method to obtain Bayesian estimates of 222Rn-daughter products from observed counting rates. In external radiation dosimetry we studied and developed Bayesian methods to estimate radiation doses to an individual with radiation induced chromosome aberrations. We analyzed chromosome aberrations after exposure to gammas and neutrons and developed a method for dose-estimation after criticality accidents. The research in internal radiation dosimetry focused on parameter estimation for compartmental models from observed compartmental activities. From the estimated probability densities of the model parameters we were able to derive the densities for compartmental activities for a two compartment catenary model at different times. We also calculated the average activities and their standard deviation for a simple two compartment model

  12. Detecting effects of donepezil on visual selective attention using signal detection parameters in Alzheimer's disease.

    Science.gov (United States)

    Foldi, Nancy S; White, Richard E C; Schaefer, Lynn A

    2005-05-01

    Attentional function is impaired in Alzheimer's disease (AD). Moreover, attention is mediated by acetylcholine. But, despite the widespread use of acetylcholinesterase inhibitors (AChE-I) to augment available acetylcholine in AD, measures of attentional function have not been used to assess the drug response. We hypothesized that as cholinergic augmentation impacts directly on the attentional system, higher-order measures of visual selective attention would be sensitive to effects of treatment using an AChE-I (donepezil hydrochloride). We also sought to determine whether these attentional measures were more sensitive to treatment than other measures of cognitive function. Seventeen patients with AD (8 untreated, 9 treated with donepezil) were contrasted on performance of a selective cancellation task. Two signal detection parameters were used as outcome measures: decision strategy (beta, beta) and discriminability (d-prime, d'). Standard screening and cognitive domain measures of vigilance, language, memory, and executive function were also contrasted. Treated patients judged stimuli more conservatively (p = 0.29) by correctly endorsing targets and rejecting false alarms. They also discriminated targets from distractors more easily (p = 0.58). The screening and neuropsychological measures failed to differentiate the groups. Higher-order attentional measures captured the effects of donepezil treatment in small groups of patients with AD. The results suggest that cholinergic availability may directly affect the attentional system, and that these selective attention measures are sensitive markers to detect treatment response. Copyright 2005 John Wiley & Sons, Ltd.

  13. Detection and Correction of Under-/Overexposed Optical Soundtracks by Coupling Image and Audio Signal Processing

    Directory of Open Access Journals (Sweden)

    Etienne Decenciere

    2008-10-01

    Full Text Available Film restoration using image processing, has been an active research field during the last years. However, the restoration of the soundtrack has been mainly performed in the sound domain, using signal processing methods, despite the fact that it is recorded as a continuous image between the images of the film and the perforations. While the very few published approaches focus on removing dust particles or concealing larger corrupted areas, no published works are devoted to the restoration of soundtracks degraded by substantial underexposure or overexposure. Digital restoration of optical soundtracks is an unexploited application field and, besides, scientifically rich, because it allows mixing both image and signal processing approaches. After introducing the principles of optical soundtrack recording and playback, this contribution focuses on our first approaches to detect and cancel the effects of under and overexposure. We intentionally choose to get a quantification of the effect of bad exposure in the 1D audio signal domain instead of 2D image domain. Our measurement is sent as feedback value to an image processing stage where the correction takes place, building up a “digital image and audio signal” closed loop processing. The approach is validated on both simulated alterations and real data.

  14. Direct modulation and detection link using polybinary signaling

    DEFF Research Database (Denmark)

    Suhr, L.F.; Vegas Olmos, Juan José; Peucheret, Christophe

    2014-01-01

    This paper presents experimental results on a spectral efficient optical fiber link by using a novel seven-level polybinary signaling at 14.32 Gbps achieving a potential 7.95 b/s/Hz with very little complexity and processing footprint.......This paper presents experimental results on a spectral efficient optical fiber link by using a novel seven-level polybinary signaling at 14.32 Gbps achieving a potential 7.95 b/s/Hz with very little complexity and processing footprint....

  15. Detectability of CO2 Flux Signals by a Space-Based Lidar Mission

    Science.gov (United States)

    Hammerling, Dorit M.; Kawa, S. Randolph; Schaefer, Kevin; Doney, Scott; Michalak, Anna M.

    2015-01-01

    Satellite observations of carbon dioxide (CO2) offer novel and distinctive opportunities for improving our quantitative understanding of the carbon cycle. Prospective observations include those from space-based lidar such as the Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS) mission. Here we explore the ability of such a mission to detect regional changes in CO2 fluxes. We investigate these using three prototypical case studies, namely the thawing of permafrost in the Northern High Latitudes, the shifting of fossil fuel emissions from Europe to China, and changes in the source-sink characteristics of the Southern Ocean. These three scenarios were used to design signal detection studies to investigate the ability to detect the unfolding of these scenarios compared to a baseline scenario. Results indicate that the ASCENDS mission could detect the types of signals investigated in this study, with the caveat that the study is based on some simplifying assumptions. The permafrost thawing flux perturbation is readily detectable at a high level of significance. The fossil fuel emission detectability is directly related to the strength of the signal and the level of measurement noise. For a nominal (lower) fossil fuel emission signal, only the idealized noise-free instrument test case produces a clearly detectable signal, while experiments with more realistic noise levels capture the signal only in the higher (exaggerated) signal case. For the Southern Ocean scenario, differences due to the natural variability in the ENSO climatic mode are primarily detectable as a zonal increase.

  16. Electrochemical immunoassay for thyroxine detection using cascade catalysis as signal amplified enhancer and multi-functionalized magnetic graphene sphere as signal tag

    Energy Technology Data Exchange (ETDEWEB)

    Han, Jing; Zhuo, Ying, E-mail: yingzhuo@swu.edu.cn; Chai, Yaqin; Yu, Yanqing; Liao, Ni; Yuan, Ruo, E-mail: yuanruo@swu.edu.cn

    2013-08-06

    Graphical abstract: -- Highlights: •A reusable electrochemical immunosensor is developed for thyroxine detection. •Cascade catalysis as signal amplified enhancer. •Multi-functionalized magnetic graphene sphere as signal tag. •The novel strategy has the advantages of high sensitivity, good selectivity and reproducibility. -- Abstract: This paper constructed a reusable electrochemical immunosensor for the detection of thyroxine at an ultralow concentration using cascade catalysis of cytochrome c (Cyt c) and glucose oxidase (GOx) as signal amplified enhancer. It is worth pointing out that numerous Cyt c and GOx were firstly carried onto the double-stranded DNA polymers based on hybridization chain reaction (HCR), and then the amplified responses could be achieved by cascade catalysis of Cyt c and GOx recycling with the help of glucose. Moreover, multi-functionalized magnetic graphene sphere was synthesized and used as signal tag, which not only exhibited good mechanical properties, large surface area and an excellent electron transfer rate of graphene, but also possessed excellent redox activity and desirable magnetic property. With a sandwich-type immunoreaction, the proposed cascade catalysis amplification strategy could greatly enhance the sensitivity for the detection of thyroxine. Under the optimal conditions, the immunosensor showed a wide linear ranged from 0.05 pg mL{sup −1} to 5 ng mL{sup −1} and a low detection limit down to 15 fg mL{sup −1}. Importantly, the proposed method offers promise for reproducible and cost-effective analysis of biological samples.

  17. Processing of the quench detection signals in W7-X

    International Nuclear Information System (INIS)

    Birus, Dietrich; Schneider, Matthias; Rummel, Thomas; Fricke, Marko; Petry, Klaus; Ebersoldt, Andreas

    2009-01-01

    The Wendelstein 7-X (W7-X) project uses superconductive coils for generation of the magnetic field to keep the plasma. One of the important safety systems is the protection against quench events. The quench detection system of W7-X protects the superconducting coils, the superconducting bus bar sections and the high temperature superconductor of the current leads against the damage because of a quench and against the high stress by a fast discharge of the magnet system. Therefore, the present design of the quench detection system (QDS) uses a two-stage safety concept for discharging the magnetic system. This paper describes the present design of the system assembly from the quench detection unit (QDU) for the detection of the quench to the quench detection interface (QDI) to implement the two-stage safety concept.

  18. Apparatus and method for detecting explosives

    International Nuclear Information System (INIS)

    Griffith, B.

    1976-01-01

    An apparatus is described for use in situations such as airports to detect explosives hidden in containers (for eg. suitcases). The method involves the evaluation of the quantities of oxygen and nitrogen within the container by neutron activation analysis and the determination of whether these quantities exceed predetermined limits. The equipment includes a small sub-critical lower powered reactor for thermal (0.01 to 0.10 eV) neutron production, a radium beryllium primary source, a deuterium-tritium reactor as a high energy (> 1.06 MeV) neutron source and Geiger counter detector arrays. (UK)

  19. Mobile/android application for QRS detection using zero cross method

    Science.gov (United States)

    Rizqyawan, M. I.; Simbolon, A. I.; Suhendra, M. A.; Amri, M. F.; Kusumandari, D. E.

    2018-03-01

    In automatic ECG signal processing, one of the main topics of research is QRS complex detection. Detecting correct QRS complex or R peak is important since it is used to measure several other ECG metrics. One of the robust methods for QRS detection is Zero Cross method. This method uses an addition of high-frequency signal and zero crossing count to detect QRS complex which has a low-frequency oscillation. This paper presents an application of QRS detection using Zero Cross algorithm in the Android-based system. The performance of the algorithm in the mobile environment is measured. The result shows that this method is suitable for real-time QRS detection in a mobile application.

  20. Novel Methods of Hydrogen Leak Detection

    International Nuclear Information System (INIS)

    Pushpinder S Puri

    2006-01-01

    For hydrogen to become a consumer fuel for automotive and domestic power generation, safety is paramount. Today's hydrogen systems are built with inherent safety measures and multiple levels of protection. However, human senses, in particular, the sense of smell, is considered the ultimate safeguards against leaks. Since hydrogen is an odorless gas, use of odorants to detect leaks, as is done in case of natural gas, is obvious solution. The odorants required for hydrogen used in fuel cells have a unique requirement which must be met. This is because almost all of the commercial odorants used in gas leak detection contain sulfur which acts as poison for the catalysts used in hydrogen based fuel cells, most specifically for the PEM (polymer electrolyte membrane or proton exchange membrane) fuel cells. A possible solution to this problem is to use non-sulfur containing odorants. Chemical compounds based on mixtures of acrylic acid and nitrogen compounds have been adopted to achieve a sulfur-free odorization of a gas. It is, therefore, desired to have a method and system for hydrogen leak detection using odorant which can incorporate a uniform concentration of odorant in the hydrogen gas, when odorants are mixed in the hydrogen storage or delivery means. It is also desired to develop methods where the odorant is not added to the bulk hydrogen, keeping it free of the odorization additives. A series of novel solutions are proposed which address the issues raised above. These solutions are divided into three categories as follows: 1. Methods incorporating an odorant in the path of hydrogen leak as opposed to adding it to the hydrogen gas. 2. Methods where odorants are generated in-situ by chemical reaction with the leaking hydrogen 3. Methods of dispensing and storing odorants in high pressure hydrogen gas which release odorants to the gas at a uniform and predetermined rates. Use of one or more of the methods described here in conjunction with appropriate engineering

  1. Lagrangian based methods for coherent structure detection

    Energy Technology Data Exchange (ETDEWEB)

    Allshouse, Michael R., E-mail: mallshouse@chaos.utexas.edu [Center for Nonlinear Dynamics and Department of Physics, University of Texas at Austin, Austin, Texas 78712 (United States); Peacock, Thomas, E-mail: tomp@mit.edu [Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139 (United States)

    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.

  2. Some methods for the detection of fissionable matter; Quelques methodes de detection des corps fissiles

    Energy Technology Data Exchange (ETDEWEB)

    Guery, M [Commissariat a l' Energie Atomique, Saclay (France). Centre d' Etudes Nucleaires

    1967-03-01

    A number of equipments or processes allowing to detect uranium or plutonium in industrial plants, and in particular to measure solution concentrations, are studied here. Each method has its own field of applications and has its own performances, which we have tried to define by calculations and by experiments. The following topics have been treated: {gamma} absorptiometer with an Am source, detection test by neutron multiplication, apparatus for the measurement of the {alpha} activity of a solution, fissionable matter detection by {gamma} emission, fissionable matter detection by neutron emission. (author) [French] On examine ici plusieurs appareils ou procedes qui permettent de detecter l'uranium ou le plutonium dans les installations industrielles, et en particulier de mesurer les concentrations de solutions. Chacune des methodes a son domaine d'application et ses performances, qu'on a tente de definir par le calcul et par des experiences. Les sujets traites sont les suivants: absorptiometre {gamma} a source d'americium, essais de detection par multiplication neutronique, appareil de mesure de l'activite {alpha} d'une solution, detection des matieres fissiles par leur emission {gamma}, detection des matieres fissiles par leur emission neutronique. (auteur)

  3. Bearing failure detection of micro wind turbine via power spectral density analysis for stator current signals spectrum

    Science.gov (United States)

    Mahmood, Faleh H.; Kadhim, Hussein T.; Resen, Ali K.; Shaban, Auday H.

    2018-05-01

    The failure such as air gap weirdness, rubbing, and scrapping between stator and rotor generator arise unavoidably and may cause extremely terrible results for a wind turbine. Therefore, we should pay more attention to detect and identify its cause-bearing failure in wind turbine to improve the operational reliability. The current paper tends to use of power spectral density analysis method of detecting internal race and external race bearing failure in micro wind turbine by estimation stator current signal of the generator. The failure detector method shows that it is well suited and effective for bearing failure detection.

  4. Controlling a human-computer interface system with a novel classification method that uses electrooculography signals.

    Science.gov (United States)

    Wu, Shang-Lin; Liao, Lun-De; Lu, Shao-Wei; Jiang, Wei-Ling; Chen, Shi-An; Lin, Chin-Teng

    2013-08-01

    Electrooculography (EOG) signals can be used to control human-computer interface (HCI) systems, if properly classified. The ability to measure and process these signals may help HCI users to overcome many of the physical limitations and inconveniences in daily life. However, there are currently no effective multidirectional classification methods for monitoring eye movements. Here, we describe a classification method used in a wireless EOG-based HCI device for detecting eye movements in eight directions. This device includes wireless EOG signal acquisition components, wet electrodes and an EOG signal classification algorithm. The EOG classification algorithm is based on extracting features from the electrical signals corresponding to eight directions of eye movement (up, down, left, right, up-left, down-left, up-right, and down-right) and blinking. The recognition and processing of these eight different features were achieved in real-life conditions, demonstrating that this device can reliably measure the features of EOG signals. This system and its classification procedure provide an effective method for identifying eye movements. Additionally, it may be applied to study eye functions in real-life conditions in the near future.

  5. Parameters of explosives detection through tagged neutron method

    Energy Technology Data Exchange (ETDEWEB)

    Bagdasaryan, Kh.E.; Batyaev, V.F.; Belichenko, S.G., E-mail: consul757@mail.ru; Bestaev, R.R.; Gavryuchenkov, A.V.; Karetnikov, M.D.

    2015-06-01

    The potentialities of tagged neutron method (TNM) for explosives detection are examined on the basis of an idealized geometrical model. The model includes ING-27 14 MeV neutron generator with a built-in α-detector, a LYSO γ-detector and samples of material to be identified of approximately 0.3 kg each: explosives imitators (trinitrotoluene - TNT, tetryl, RDX and ammonium nitrate), legal materials (sugar, water, silk and polyethylene). The samples were unshielded or shielded by a paper layer of various thicknesses. The experimental data were interpreted by numerical simulation using a Poisson distribution of signals with the statistical parameters defined experimentally. The detection parameters were obtained by a pattern classification theory and a Bayes classifier.

  6. Detecting modulated signals in modulated noise: (II) neural thresholds in the songbird forebrain.

    Science.gov (United States)

    Bee, Mark A; Buschermöhle, Michael; Klump, Georg M

    2007-10-01

    Sounds in the real world fluctuate in amplitude. The vertebrate auditory system exploits patterns of amplitude fluctuations to improve signal detection in noise. One experimental paradigm demonstrating these general effects has been used in psychophysical studies of 'comodulation detection difference' (CDD). The CDD effect refers to the fact that thresholds for detecting a modulated, narrowband noise signal are lower when the envelopes of flanking bands of modulated noise are comodulated with each other, but fluctuate independently of the signal compared with conditions in which the envelopes of the signal and flanking bands are all comodulated. Here, we report results from a study of the neural correlates of CDD in European starlings (Sturnus vulgaris). We manipulated: (i) the envelope correlations between a narrowband noise signal and a masker comprised of six flanking bands of noise; (ii) the signal onset delay relative to masker onset; (iii) signal duration; and (iv) masker spectrum level. Masked detection thresholds were determined from neural responses using signal detection theory. Across conditions, the magnitude of neural CDD ranged between 2 and 8 dB, which is similar to that reported in a companion psychophysical study of starlings [U. Langemann & G.M. Klump (2007) Eur. J. Neurosci., 26, 1969-1978]. We found little evidence to suggest that neural CDD resulted from the across-channel processing of auditory grouping cues related to common envelope fluctuations and synchronous onsets between the signal and flanking bands. We discuss a within-channel model of peripheral processing that explains many of our results.

  7. New method to estimate the frequency stability of laser signals

    International Nuclear Information System (INIS)

    McFerran, J.J.; Maric, M.; Luiten, A.N.

    2004-01-01

    A frequent challenge in the scientific and commercial use of lasers is the need to determine the frequency stability of the output optical signal. In this article we present a new method to estimate this quantity while avoiding the complexity of the usual technique. The new technique displays the result in terms of the usual time domain measure of frequency stability: the square root Allan variance

  8. Nucleic acid detection system and method for detecting influenza

    Science.gov (United States)

    Cai, Hong; Song, Jian

    2015-03-17

    The invention provides a rapid, sensitive and specific nucleic acid detection system which utilizes isothermal nucleic acid amplification in combination with a lateral flow chromatographic device, or DNA dipstick, for DNA-hybridization detection. The system of the invention requires no complex instrumentation or electronic hardware, and provides a low cost nucleic acid detection system suitable for highly sensitive pathogen detection. Hybridization to single-stranded DNA amplification products using the system of the invention provides a sensitive and specific means by which assays can be multiplexed for the detection of multiple target sequences.

  9. Signal predictions for a proposed fast neutron interrogation method

    International Nuclear Information System (INIS)

    Sale, K.E.

    1992-12-01

    We have applied the Monte Carlo radiation transport code COG) to assess the utility of a proposed explosives detection scheme based on neutron emission. In this scheme a pulsed neutron beam is generated by an approximately seven MeV deuteron beam incident on a thick Be target. A scintillation detector operating in the current mode measures the neutrons transmitted through the object as a function of time. The flight time of unscattered neutrons from the source to the detector is simply related to the neutron energy. This information along with neutron cross section excitation functions is used to infer the densities of H, C, N and O in the volume sampled. The code we have chosen to use enables us to create very detailed and realistic models of the geometrical configuration of the system, the neutron source and of the detector response. By calculating the signals that will be observed for several configurations and compositions of interrogated object we can investigate and begin to understand how a system that could actually be fielded will perform. Using this modeling capability many early on with substantial savings in time and cost and with improvements in performance. We will present our signal predictions for simple single element test cases and for explosive compositions. From these studies it is dear that the interpretation of the signals from such an explosives identification system will pose a substantial challenge

  10. Alternative vehicle detection technologies for traffic signal systems : technical report.

    Science.gov (United States)

    2009-02-01

    Due to the well-documented problems associated with inductive loops, most jurisdictions have : replaced many intersection loops with video image vehicle detection systems (VIVDS). While VIVDS : have overcome some of the problems with loops such as tr...

  11. A Fast Detection Algorithm for the X-Ray Pulsar Signal

    Directory of Open Access Journals (Sweden)

    Hao Liang

    2017-01-01

    Full Text Available The detection of the X-ray pulsar signal is important for the autonomous navigation system using X-ray pulsars. In the condition of short observation time and limited number of photons for detection, the noise does not obey the Gaussian distribution. This fact has been little considered extant. In this paper, the model of the X-ray pulsar signal is rebuilt as the nonhomogeneous Poisson distribution and, in the condition of a fixed false alarm rate, a fast detection algorithm based on maximizing the detection probability is proposed. Simulation results show the effectiveness of the proposed detection algorithm.

  12. Development Of Signal Detection For Radar Navigation System

    OpenAIRE

    Theingi Win Hlaing; Hla Myo Tun; Zaw Min Naing; Win Khaing Moe

    2017-01-01

    This paper aims to evaluate the performance of target detection in the presence of sea clutter. Radar detection of a background of unwanted clutter due to echoes from sea clutter or land is a problem of interest in the radar field. Radar detector has been developed by assuming the radar clutter is Gaussian distributed. However as technology emerges the radar distribution is seen to deviates from the Gaussian assumption. Thus detectors designs based on Gaussian assumption are no longer optimum...

  13. Comparative evaluation of Oxoid Signal and BACTEC radiometric blood culture systems for the detection of bacteremia and fungemia

    International Nuclear Information System (INIS)

    Weinstein, M.P.; Mirrett, S.; Reller, L.B.

    1988-01-01

    The Oxoid Signal blood culture system is a newly described, innovative method for visually detecting growth of microorganisms. We did 5,999 paired comparisons of equal volumes (10 ml) of blood in the Oxoid Signal and BACTEC radiometric blood culture systems at two university hospitals that use identical methods of obtaining and processing specimens. Overall, more microorganisms were detected in the BACTEC system (P less than 0.001), in particular, streptococci (P less than 0.01), fungi (P less than 0.001), and nonfermentative gram-negative rods, especially Acinetobacter species (P less than 0.001). Trends favoring the BACTEC system for detection of Pseudomonas aeruginosa, Haemophilus species, and Neisseria species were noted. There were no differences in the yield of staphylococci, members of the family Enterobacteriaceae, and anaerobic bacteria. When both systems detected sepsis, the BACTEC did so earlier (P less than 0.001). This advantage was most notable at 24 h (70% of BACTEC positives detected versus 48% of Oxoid positives). The proportion of positives detected after 48 h, however, was similar (BACTEC, 84%; Oxoid, 78%). Revisions in the Oxoid Signal system itself or in the processing of Oxoid bottles appear to be necessary to improve its performance in detecting certain microorganism groups, especially fungi

  14. Photodetectors for weak-signal detection fabricated from ZnO:(Li,N) films

    Energy Technology Data Exchange (ETDEWEB)

    He, G.H. [State Key Laboratory of Luminescence and Applications, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences Changchun 130033 (China); University of Chinese Academy of Sciences, Beijing 100049 (China); Zhou, H. [Key Laboratory of Semiconductors and Applications of Fujian Province, Collaborative Innovation Center for Optoelectronic Semiconductors and Efficient Devices, Department of Physics, Xiamen University, Xiamen 361005 (China); Shen, H. [State Key Laboratory of Luminescence and Applications, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences Changchun 130033 (China); Lu, Y.J. [Henan Key Laboratory of Diamond Optoelectronic Materials and Devices, School of Physics and Engineering, Zhengzhou University, Zhengzhou 450001 (China); Wang, H.Q.; Zheng, J.C. [Key Laboratory of Semiconductors and Applications of Fujian Province, Collaborative Innovation Center for Optoelectronic Semiconductors and Efficient Devices, Department of Physics, Xiamen University, Xiamen 361005 (China); Li, B.H. [State Key Laboratory of Luminescence and Applications, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences Changchun 130033 (China); Shan, C.X., E-mail: shancx@ciomp.ac.cn [State Key Laboratory of Luminescence and Applications, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences Changchun 130033 (China); Henan Key Laboratory of Diamond Optoelectronic Materials and Devices, School of Physics and Engineering, Zhengzhou University, Zhengzhou 450001 (China); Shen, D.Z. [State Key Laboratory of Luminescence and Applications, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences Changchun 130033 (China)

    2017-08-01

    Highlights: • ZnO films with carrier concentration as low as 5.0 × 10{sup 13} cm{sup −3} have been prepared via a lithium and nitrogen codoping method. • Ultraviolet photodetector that can detect weak signal with power density as low as 20 nw/cm{sup 2} have been fabricated from the ZnO:(Li,N) films. • The detectivity and noise equivalent power of the photodetector can reach 3.60 × 10{sup 15} cmHz{sup 1/2}/W and 6.67 × 10{sup −18} W{sup −1}, both of which are amongst the best values ever reported for ZnO photodetectors. - Abstract: ZnO films with carrier concentration as low as 5.0 × 10{sup 13} cm{sup −3} have been prepared via a lithium and nitrogen codoping method, and ultraviolet photodetectors have been fabricated from the films. The photodetectors can be used to detect weak signals with power density as low as 20 nw/cm{sup 2}, and the detectivity and noise equivalent power of the photodetector can reach 3.60 × 10{sup 15} cmHz{sup 1/2}/W and 6.67 × 10{sup −18} W{sup −1}, respectively, both of which are amongst the best values ever reported for ZnO based photodetectors. The high-performance of the photodetector can be attributed to the relatively low carrier concentration of the ZnO:(Li,N) films.

  15. General theory of detection of signal induced in vibrating magnetometer

    International Nuclear Information System (INIS)

    Pacyna, A.W.

    1980-01-01

    Assuming the point dipole approximation only and making use of the vectorial notation, signal (EMF) induced in a single-turn pick-up coil of the vibrating magnetometer are calculated for the case of any orientation of the coil, of vibration axis and of the magnetic moment of the sample. On the basis of formula obtained, three types of measurement geometries have been distinquished and for these the qualitative analysis is made. (author)

  16. Doppler Radar Vital Signs Detection Method Based on Higher Order Cyclostationary.

    Science.gov (United States)

    Yu, Zhibin; Zhao, Duo; Zhang, Zhiqiang

    2017-12-26

    Due to the non-contact nature, using Doppler radar sensors to detect vital signs such as heart and respiration rates of a human subject is getting more and more attention. However, the related detection-method research meets lots of challenges due to electromagnetic interferences, clutter and random motion interferences. In this paper, a novel third-order cyclic cummulant (TOCC) detection method, which is insensitive to Gaussian interference and non-cyclic signals, is proposed to investigate the heart and respiration rate based on continuous wave Doppler radars. The k -th order cyclostationary properties of the radar signal with hidden periodicities and random motions are analyzed. The third-order cyclostationary detection theory of the heart and respiration rate is studied. Experimental results show that the third-order cyclostationary approach has better estimation accuracy for detecting the vital signs from the received radar signal under low SNR, strong clutter noise and random motion interferences.

  17. Photoplethysmographic signal waveform index for detection of increased arterial stiffness

    International Nuclear Information System (INIS)

    Pilt, K; Meigas, K; Ferenets, R; Temitski, K; Viigimaa, M

    2014-01-01

    The aim of this research was to assess the validity of the photoplethysmographic (PPG) waveform index PPGAI for the estimation of increased arterial stiffness. For this purpose, PPG signals were recorded from 24 healthy subjects and from 20 type II diabetes patients. The recorded PPG signals were processed with the analysis algorithm developed and the waveform index PPGAI similar to the augmentation index (AIx) was calculated. As a reference, the aortic AIx was assessed and normalized for a heart rate of 75 bpm (AIx@75) by a SphygmoCor device. A strong correlation (r = 0.85) between the PPGAI and the aortic AIx@75 and a positive correlation of both indices with age were found. Age corrections for the indices PPGAI and AIx@75 as regression models from the signals of healthy subjects were constructed. Both indices revealed a significant difference between the groups of diabetes patients and healthy controls. However, the PPGAI provided the best statistical discrimination for the group of subjects with increased arterial stiffness. The waveform index PPGAI based on the inexpensive PPG technology can be considered as a perspective measure of increased arterial stiffness estimation in clinical screenings. (paper)

  18. Evaluation and Uncertainty of a New Method to Detect Suspected Nuclear and WMD Activity: Project Report

    Energy Technology Data Exchange (ETDEWEB)

    Kurzeja, R. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Werth, D. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL); Buckley, R. [Savannah River Site (SRS), Aiken, SC (United States). Savannah River National Lab. (SRNL)

    2017-09-29

    The Atmospheric Technology Group at SRNL developed a new method to detect signals from Weapons of Mass Destruction (WMD) activities in a time series of chemical measurements at a downwind location. This method was tested with radioxenon measured in Russia and Japan after the 2013 underground test in North Korea. This LDRD calculated the uncertainty in the method with the measured data and also for a case with the signal reduced to 1/10 its measured value. The research showed that the uncertainty in the calculated probability of origin from the NK test site was small enough to confirm the test. The method was also wellbehaved for small signal strengths.

  19. An Evaluation of the Acoustic Signal processing Techniques for Sodium-Water Reaction Detection in KALIMER-600

    International Nuclear Information System (INIS)

    Hur, Seop; Seong, S. H.; Kim, T. J.; Kim, S. O.; Lee, M. K.

    2005-02-01

    KALIMER-600 is a pool type fast breeder reactor using liquid sodium as a coolant. Although it has the several advantages such as long-term fuel cycle and enhanced safety concepts, it is possible to leak the secondary side water/steam into sodium boundary. This event could make the plant abnormal condition. One of the major design issues in KALIMER-600 is, therefore, to develop the system which can early detect the sodium-water reaction to protect the sodium-water reaction event. After evaluating the various signal processing techniques for passive acoustic leak detection, we have proposed the early leak detection logics. the signal processing techniques for evaluation were the spectral estimation using the linear modeling, the estimation error of linear modeling, the system adaptation rate using an adaptive signal processing, and the background noise cancellation using adaptive and fixed filtering. As the analysis results regarding the stationary and the cross-correlation of leak signals and background noises, the two signal systems met a wide-dense stationary process and there was only the week cross correlation relationship between two signals. It is ,therefore, possible to use the linear/harmonic modeling of signal systems, and the leak signal in sensor outputs can be discriminated. As the results of the evaluation of the various spectral estimation methods, the spectral estimation method based on autoregressive modeling was more practical comparing with other methods in the sodium-water reaction detection. The passive acoustic leak detection logics were suggested based on above evaluations. the logics consist of 3 levels; transient identification, leak determination and leak symptom identification. The simulation results using sodium-water reaction signals showed that it was possible to determine the leak at above -3dB of SNR, while between -3 dB and -10 dB of SNR the logics determined the leak symptom identification. The detection sensitivity can be enhanced

  20. A formal language to describe a wide class of failure detection and signal validation procedures

    Energy Technology Data Exchange (ETDEWEB)

    Racz, A. [Hungarian Academy of Sciences, Budapest (Hungary). Atomic Energy Research Inst.

    1996-01-01

    In the present article we make the first step towards the implementation of a user-friendly, object-oriented system devoted to failure detection and signal validation purposes. After overviewing different signal modelling, residual making and hypothesis testing procedures, a mathematical tool is suggested to describe a general failure detection problem. Three different levels of the abstraction are distinguished; direct examination, preliminary decision support mechanism and indirect examination. Possible scenarios are introduced depending both on the objective properties of the investigated signal and the particular requirements prescribed by the expert himself. Finally it is showed how to build up systematically a complete, general failure detection procedure. (author).

  1. Proposal and Implementation of a Robust Sensing Method for DVB-T Signal

    Science.gov (United States)

    Song, Chunyi; Rahman, Mohammad Azizur; Harada, Hiroshi

    This paper proposes a sensing method for TV signals of DVB-T standard to realize effective TV White Space (TVWS) Communication. In the TVWS technology trial organized by the Infocomm Development Authority (iDA) of Singapore, with regard to the sensing level and sensing time, detecting DVB-T signal at the level of -120dBm over an 8MHz channel with a sensing time below 1 second is required. To fulfill such a strict sensing requirement, we propose a smart sensing method which combines feature detection and energy detection (CFED), and is also characterized by using dynamic threshold selection (DTS) based on a threshold table to improve sensing robustness to noise uncertainty. The DTS based CFED (DTS-CFED) is evaluated by computer simulations and is also implemented into a hardware sensing prototype. The results show that the DTS-CFED achieves a detection probability above 0.9 for a target false alarm probability of 0.1 for DVB-T signals at the level of -120dBm over an 8MHz channel with the sensing time equals to 0.1 second.

  2. Spontaneous Alpha Power Lateralization Predicts Detection Performance in an Un-Cued Signal Detection Task.

    Directory of Open Access Journals (Sweden)

    Gonzalo Boncompte

    Full Text Available Focusing one's attention by external guiding stimuli towards a specific area of the visual field produces systematical neural signatures. One of the most robust is the change in topological distribution of oscillatory alpha band activity across parieto-occipital cortices. In particular, decreases in alpha activity over contralateral and/or increases over ipsilateral scalp sites, respect to the side of the visual field where attention was focused. This evidence comes mainly from experiments where an explicit cue informs subjects where to focus their attention, thus facilitating detection of an upcoming target stimulus. However, recent theoretical models of attention have highlighted a stochastic or non-deterministic component related to visuospatial attentional allocation. In an attempt to evidence this component, here we analyzed alpha activity in a signal detection paradigm in the lack of informative cues; in the absence of preceding information about the location (and time of appearance of target stimuli. We believe that the unpredictability of this situation could be beneficial for unveiling this component. Interestingly, although total alpha power did not differ between Seen and Unseen conditions, we found a significant lateralization of alpha activity over parieto-occipital electrodes, which predicted behavioral performance. This effect had a smaller magnitude compared to paradigms in which attention is externally guided (cued. However we believe that further characterization of this spontaneous component of attention is of great importance in the study of visuospatial attentional dynamics. These results support the presence of a spontaneous component of visuospatial attentional allocation and they advance pre-stimulus alpha-band lateralization as one of its neural signatures.

  3. Odour detection methods: olfactometry and chemical sensors.

    Science.gov (United States)

    Brattoli, Magda; de Gennaro, Gianluigi; de Pinto, Valentina; Loiotile, Annamaria Demarinis; Lovascio, Sara; Penza, Michele

    2011-01-01

    The complexity of the odours issue arises from the sensory nature of smell. From the evolutionary point of view olfaction is one of the oldest senses, allowing for seeking food, recognizing danger or communication: human olfaction is a protective sense as it allows the detection of potential illnesses or infections by taking into account the odour pleasantness/unpleasantness. Odours are mixtures of light and small molecules that, coming in contact with various human sensory systems, also at very low concentrations in the inhaled air, are able to stimulate an anatomical response: the experienced perception is the odour. Odour assessment is a key point in some industrial production processes (i.e., food, beverages, etc.) and it is acquiring steady importance in unusual technological fields (i.e., indoor air quality); this issue mainly concerns the environmental impact of various industrial activities (i.e., tanneries, refineries, slaughterhouses, distilleries, civil and industrial wastewater treatment plants, landfills and composting plants) as sources of olfactory nuisances, the top air pollution complaint. Although the human olfactory system is still regarded as the most important and effective "analytical instrument" for odour evaluation, the demand for more objective analytical methods, along with the discovery of materials with chemo-electronic properties, has boosted the development of sensor-based machine olfaction potentially imitating the biological system. This review examines the state of the art of both human and instrumental sensing currently used for the detection of odours. The olfactometric techniques employing a panel of trained experts are discussed and the strong and weak points of odour assessment through human detection are highlighted. The main features and the working principles of modern electronic noses (E-Noses) are then described, focusing on their better performances for environmental analysis. Odour emission monitoring carried out through

  4. Odour Detection Methods: Olfactometry and Chemical Sensors

    Directory of Open Access Journals (Sweden)

    Sara Lovascio

    2011-05-01

    Full Text Available The complexity of the odours issue arises from the sensory nature of smell. From the evolutionary point of view olfaction is one of the oldest senses, allowing for seeking food, recognizing danger or communication: human olfaction is a protective sense as it allows the detection of potential illnesses or infections by taking into account the odour pleasantness/unpleasantness. Odours are mixtures of light and small molecules that, coming in contact with various human sensory systems, also at very low concentrations in the inhaled air, are able to stimulate an anatomical response: the experienced perception is the odour. Odour assessment is a key point in some industrial production processes (i.e., food, beverages, etc. and it is acquiring steady importance in unusual technological fields (i.e., indoor air quality; this issue mainly concerns the environmental impact of various industrial activities (i.e., tanneries, refineries, slaughterhouses, distilleries, civil and industrial wastewater treatment plants, landfills and composting plants as sources of olfactory nuisances, the top air pollution complaint. Although the human olfactory system is still regarded as the most important and effective “analytical instrument” for odour evaluation, the demand for more objective analytical methods, along with the discovery of materials with chemo-electronic properties, has boosted the development of sensor-based machine olfaction potentially imitating the biological system. This review examines the state of the art of both human and instrumental sensing currently used for the detection of odours. The olfactometric techniques employing a panel of trained experts are discussed and the strong and weak points of odour assessment through human detection are highlighted. The main features and the working principles of modern electronic noses (E-Noses are then described, focusing on their better performances for environmental analysis. Odour emission monitoring

  5. An adaptive segment method for smoothing lidar signal based on noise estimation

    Science.gov (United States)

    Wang, Yuzhao; Luo, Pingping

    2014-10-01

    An adaptive segmentation smoothing method (ASSM) is introduced in the paper to smooth the signal and suppress the noise. In the ASSM, the noise is defined as the 3σ of the background signal. An integer number N is defined for finding the changing positions in the signal curve. If the difference of adjacent two points is greater than 3Nσ, the position is recorded as an end point of the smoothing segment. All the end points detected as above are recorded and the curves between them will be smoothed separately. In the traditional method, the end points of the smoothing windows in the signals are fixed. The ASSM creates changing end points in different signals and the smoothing windows could be set adaptively. The windows are always set as the half of the segmentations and then the average smoothing method will be applied in the segmentations. The Iterative process is required for reducing the end-point aberration effect in the average smoothing method and two or three times are enough. In ASSM, the signals are smoothed in the spacial area nor frequent area, that means the frequent disturbance will be avoided. A lidar echo was simulated in the experimental work. The echo was supposed to be created by a space-born lidar (e.g. CALIOP). And white Gaussian noise was added to the echo to act as the random noise resulted from environment and the detector. The novel method, ASSM, was applied to the noisy echo to filter the noise. In the test, N was set to 3 and the Iteration time is two. The results show that, the signal could be smoothed adaptively by the ASSM, but the N and the Iteration time might be optimized when the ASSM is applied in a different lidar.

  6. Total focusing method with correlation processing of antenna array signals

    Science.gov (United States)

    Kozhemyak, O. A.; Bortalevich, S. I.; Loginov, E. L.; Shinyakov, Y. A.; Sukhorukov, M. P.

    2018-03-01

    The article proposes a method of preliminary correlation processing of a complete set of antenna array signals used in the image reconstruction algorithm. The results of experimental studies of 3D reconstruction of various reflectors using and without correlation processing are presented in the article. Software ‘IDealSystem3D’ by IDeal-Technologies was used for experiments. Copper wires of different diameters located in a water bath were used as a reflector. The use of correlation processing makes it possible to obtain more accurate reconstruction of the image of the reflectors and to increase the signal-to-noise ratio. The experimental results were processed using an original program. This program allows varying the parameters of the antenna array and sampling frequency.

  7. Molecular methods for the study of signal transduction in plants

    KAUST Repository

    Irving, Helen R.

    2013-09-03

    Novel and improved analytical methods have led to a rapid increase in our understanding of the molecular mechanism underlying plant signal transduction. Progress has been made both at the level of single-component analysis and in vivo imaging as well as at the systems level where transcriptomics and particularly phosphoproteomics afford a window into complex biological responses. Here we review the role of the cyclic nucleotides cAMP and cGMP in plant signal transduction as well as the discovery and biochemical and biological characterization of an increasing number of complex multi-domain nucleotide cyclases that catalyze the synthesis of cAMP and cGMP from ATP and GTP, respectively. © Springer Science+Business Media New York 2013.

  8. Signal processing methods for in-situ creep specimen monitoring

    Science.gov (United States)

    Guers, Manton J.; Tittmann, Bernhard R.

    2018-04-01

    Previous work investigated using guided waves for monitoring creep deformation during accelerated life testing. The basic objective was to relate observed changes in the time-of-flight to changes in the environmental temperature and specimen gage length. The work presented in this paper investigated several signal processing strategies for possible application in the in-situ monitoring system. Signal processing methods for both group velocity (wave-packet envelope) and phase velocity (peak tracking) time-of-flight were considered. Although the Analytic Envelope found via the Hilbert transform is commonly applied for group velocity measurements, erratic behavior in the indicated time-of-flight was observed when this technique was applied to the in-situ data. The peak tracking strategies tested had generally linear trends, and tracking local minima in the raw waveform ultimately showed the most consistent results.

  9. SCREENING METHODS FOR THE DETECTION OF CARTELS

    Directory of Open Access Journals (Sweden)

    Mihail BUŞU

    2014-06-01

    Full Text Available During their everyday activities, the economic operators conclude a multitude of agreements in tacit or written form, such as: contracts or conventions. Some of these arrangements are absolutely necessary for the development of their current activities. These are agreements which, by respecting the rules of competition, are able to bring benefits to consumers and to the entire economy, as a whole. On the other hand, the economic operators often conclude agreements which are harmful to the economy as well as to the consumers, violating the competition rules. Some examples in this respect are: operators’ agreements on price fixing, on market or customers sharing. Before investigating the violation of competition rules, the relevant authorities should identify the possibility of the existence of such illegalities. The theoretical models for detecting the cartels do represent a proactive tool concerning the antitrust activity of competition authorities. The present paper furnishes a review of the methods for detecting cartels as well as a part of their practical application.

  10. A Method to Detect AAC Audio Forgery

    Directory of Open Access Journals (Sweden)

    Qingzhong Liu

    2015-08-01

    Full Text Available Advanced Audio Coding (AAC, a standardized lossy compression scheme for digital audio, which was designed to be the successor of the MP3 format, generally achieves better sound quality than MP3 at similar bit rates. While AAC is also the default or standard audio format for many devices and AAC audio files may be presented as important digital evidences, the authentication of the audio files is highly needed but relatively missing. In this paper, we propose a scheme to expose tampered AAC audio streams that are encoded at the same encoding bit-rate. Specifically, we design a shift-recompression based method to retrieve the differential features between the re-encoded audio stream at each shifting and original audio stream, learning classifier is employed to recognize different patterns of differential features of the doctored forgery files and original (untouched audio files. Experimental results show that our approach is very promising and effective to detect the forgery of the same encoding bit-rate on AAC audio streams. Our study also shows that shift recompression-based differential analysis is very effective for detection of the MP3 forgery at the same bit rate.

  11. Improvement of detection limits of PIXE by substrate signal reduction

    International Nuclear Information System (INIS)

    Beaulieu, S.; Nejedly, Z.; Campbell, J.L.; Edwards, G.C.; Dias, G.M.

    2002-01-01

    Limits of detection (LODs) for aerosol samples collected using PIXE International cascade impactors, were improved approximately 50% after reducing the cross-sectional area of the analytical beam based on results obtained from microscope photographs of aerosol deposits. Improvements in LODs were most noticeable for selected elements collected on the smaller stages of the impactor (stages 1-3)

  12. Joint Iterative Carrier Synchronization and Signal Detection Employing Expectation Maximization

    DEFF Research Database (Denmark)

    Zibar, Darko; de Carvalho, Luis Henrique Hecker; Estaran Tolosa, Jose Manuel

    2014-01-01

    and nonlinear phase noise, compared to digital phase-locked loop (PLL) followed by hard decisions. Additionally, soft decision driven joint carrier synchronization and detection offers an improvement of 0.5 dB in terms of input power compared to hard decision digital PLL based carrier synchronization...

  13. Simultaneous detection of longitudinal and transverse bunch signals at ANKA

    Energy Technology Data Exchange (ETDEWEB)

    Kehrer, Benjamin; Blomley, Edmund; Brosi, Miriam; Bruendermann, Erik; Hiller, Nicole; Mueller, Anke-Susanne; Steinmann, Johannes; Schedler, Manuel; Schuh, Marcel; Schoenfeldt, Patrik; Smale, Nigel [Karlsruhe Institute of Technology, Karlsruhe (Germany); Schuetze, Paul [Deutsches Elektronen-Synchrotron DESY, Hamburg (Germany)

    2016-07-01

    The ANKA storage ring offers different operation modes including the short-bunch mode with bunch lengths tuned down to a few picoseconds. This can lead to the occurrence of microwave instabilities coupled to the emission of coherent synchrotron radiation (CSR) in the so-called 'bursts'. To study this CSR instability we use several turn-by-turn enabled detector systems to synchronously measure both the THz signal as well as bunch profiles. The different detectors are placed at different locations around the storage ring. Here we discuss the experimental setup and calibration of the various systems' synchronisation.

  14. Method of detecting a fuel element failure

    International Nuclear Information System (INIS)

    Cohen, P.

    1975-01-01

    A method is described for detecting a fuel element failure in a liquid-sodium-cooled fast breeder reactor consisting of equilibrating a sample of the coolant with a molten salt consisting of a mixture of barium iodide and strontium iodide (or other iodides) whereby a large fraction of any radioactive iodine present in the liquid sodium coolant exchanges with the iodine present in the salt; separating the molten salt and sodium; if necessary, equilibrating the molten salt with nonradioactive sodium and separating the molten salt and sodium; and monitoring the molten salt for the presence of iodine, the presence of iodine indicating that the cladding of a fuel element has failed. (U.S.)

  15. Liquid chromatography detection unit, system, and method

    Science.gov (United States)

    Derenzo, Stephen E.; Moses, William W.

    2015-10-27

    An embodiment of a liquid chromatography detection unit includes a fluid channel and a radiation detector. The radiation detector is operable to image a distribution of a radiolabeled compound as the distribution travels along the fluid channel. An embodiment of a liquid chromatography system includes an injector, a separation column, and a radiation detector. The injector is operable to inject a sample that includes a radiolabeled compound into a solvent stream. The position sensitive radiation detector is operable to image a distribution of the radiolabeled compound as the distribution travels along a fluid channel. An embodiment of a method of liquid chromatography includes injecting a sample that comprises radiolabeled compounds into a solvent. The radiolabeled compounds are then separated. A position sensitive radiation detector is employed to image distributions of the radiolabeled compounds as the radiolabeled compounds travel along a fluid channel.

  16. Application of FMEA method in railway signalling projects

    Directory of Open Access Journals (Sweden)

    Szmel Dariusz

    2017-06-01

    Full Text Available The article presents the FMEA method application, which is relevant in verification of design of two separated railway signalling systems. The efficiency of the method at the stage of the design was discussed. The method was identified as an important element of safety management process and as safety analysis method, which is included in the Safety Case and is applied for the sake of safety arguments and its assessment. Safety process management comprises several phases and appropriate actions, linked with each other in the way to create safety life cycle consistent with system life cycle. The safety case is a set of documents demonstrating that the product is compliant with defined safety requirements including analysis that indicates the correctness of the design and the correct reaction of the system to the failures, with appropriate and requested fail-safe reaction. It is necessary that railway signalling system should fulfil SIL4 requirement and remain safe in case of occurrence any kind of single failure of the equipment considered as possible.

  17. Devices, systems, and methods for detecting nucleic acids using sedimentation

    Energy Technology Data Exchange (ETDEWEB)

    Koh, Chung-Yan; Schaff, Ulrich Y.; Sommer, Gregory J.

    2017-10-24

    Embodiments of the present invention are directed toward devices, systems, and method for conducting nucleic acid purification and quantification using sedimentation. In one example, a method includes generating complexes which bind to a plurality of beads in a fluid sample, individual ones of the complexes comprising a nucleic acid molecule such as DNA or RNA and a labeling agent. The plurality of beads including the complexes may be transported through a density media, wherein the density media has a density lower than a density of the beads and higher than a density of the fluid sample, and wherein the transporting occurs, at least in part, by sedimentation. Signal may be detected from the labeling agents of the complexes.

  18. Circuit Design for Sensor Detection Signal Conditioner Nitrate Content

    Directory of Open Access Journals (Sweden)

    Robeth Manurung

    2011-09-01

    Full Text Available Nitrate is one of macro nutrients very important for agriculture. The availability of nitrate in soil is limited because it is very easy to leaching by rain, therefore nitrate could be contaminated ground water by  over-process of fertilizer. This process could also produce inefficiency in agriculture if it happened continuesly without pre-analysis of farm field. The answer those problems, it is need to develop the ion sensor system to measure concentrations of nitrat in soil. The system is consist of nitrate ion sensor device, signal conditioning and data acquisition circuit. The design and fabrications of signal conditioning circuit which integrated into ion nitrate sensor system and will apply for agriculture. This sensor has been used amperometric with three electrodes configuration: working, reference  and auxiliarry; the ion senstive membrane has use conductive polymer. The screen printing technique has been choosen to fabricate electrodes and deposition technique for ion sensitive membrane is electropolymerization. The characterization of sensor has been conducted using nitrate standard solution with range of concentration between 1 µM–1 mM. The characterization has shown that sensor has a good response with cureent output between 2.8–4.71 µA, liniearity factor is 99.65% and time response 250 second.

  19. Detection of multiple AE signal by triaxial hodogram analysis; Sanjiku hodogram ho ni yoru taju acoustic emission no kenshutsu

    Energy Technology Data Exchange (ETDEWEB)

    Nagano, K; Yamashita, T [Muroran Institute of Technology, Hokkaido (Japan)

    1997-05-27

    In order to evaluate dynamic behavior of underground cracks, analysis and detection were attempted on multiple acoustic emission (AE) events. The multiple AE is a phenomenon in which multiple AE signals generated by underground cracks developed in an extremely short time interval are superimposed, and observed as one AE event. The multiple AE signal consists of two AE signals, whereas the second P-wave is supposed to have been inputted before the first S-wave is inputted. The first P-wave is inputted first, where linear three-dimensional particle movements are observed, but the movements are made random due to scattering and sensor characteristics. When the second P-wave is inputted, the linear particle movements are observed again, but are superimposed with the existing input signals and become multiple AE, which creates poor S/N ratio. The multiple AE detection determines it a multiple AE event when three conditions are met, i. e. a condition of equivalent time interval of a maximum value in a scalogram analysis, a condition of P-wave vibrating direction, and a condition of the linear particle movement. Seventy AE signals observed in the Kakkonda geothermal field were analyzed and AE signals that satisfy the multiple AE were detected. However, further development is required on an analysis method with high resolution for the time. 4 refs., 4 figs.

  20. Signal detection circuit design of HCN measurement system based on TDLAS

    Science.gov (United States)

    He, Chungui; Zhang, Yujun; Chen, Chen; Lu, Yibing; Liu, Guohua; Gao, Yanwei; You, Kun; He, Ying; Zhang, Kai; Liu, Wenqing

    2016-10-01

    Hydrogen cyanide gas leakage may exist in the petrochemical industry, smelting plant, and other industrial processes, causing serious harm to the environment, and even threatening the safety of personnel. So the continuous detection of HCN gas plays an important role in the prevention of risk in production process and storage environment that existing hydrogen cyanide gas. The Tunable Diode Laser Technology (TDLAS) has advantages of non-contact, high sensitivity, high selectivity, and fast response time, etc., which is one of the ideal method of gas detection technologies and can be used to measure the hydrogen cyanide concentration. This paper studies the HCN detection system based on TDLAS technology, selects the absorption lines of hydrogen cyanide in 6539.12cm-1, and utilizes the center wavelength of 1.529μm distributed feedback (DFB) laser as a light source. It is discussed in detail on technical requirements of a high frequency modulated laser signal detection circuit, including noise level, gain, and bandwidth. Based on the above theory, the high frequency modulation preamplifier circuit and main amplifier circuit are designed for InGaAs photoelectric detector. The designed circuits are calculation analyzed with corresponding formula and simulation analyzed based on the Multisim software.

  1. SQUID magnetometer using sensitivity correction signal for non-magnetic metal contaminants detection

    Energy Technology Data Exchange (ETDEWEB)

    Yagi, Toshifumi, E-mail: sakuta.k@usp.ac.jp; Ohashi, Masaharu; Sakuta, Ken

    2016-11-15

    Highlights: • A high-frequency excitation is necessary to detect nonmagnetic metals using SQUID. • It is possible to detect a high-frequency magnetic field using the open loop technique. • Open loop operation leads to a change in the conversion factor. • Conversion between voltage and magnetic field for open loop operation are examined. - Abstract: Measurement methods with SQUID can accurately detect small magnetic metal contaminants based on their magnetic remanence. But, a high-frequency excitation is necessary to detect nonmagnetic metals, on the base of contrasts in electric conductivity. In this work, an open loop technique is introduced to facilitate this. The SQUID is negative feedback controlled (flux locked loop (FLL) operation) for the low frequency range, which includes significant noise due to the movement of the magnetic body or the change of the ambient magnetic field composed of the geomagnetic field and technical signals, and it operates in an open loop configuration for the high frequency range. When using the open loop technique, negative feedback is not applied to the high frequency range. Consequently, the V–Φ characteristic changes due to various causes, which leads to variations in the conversion factor between the SQUID output voltage and the magnetic field. In this study, conversion techniques for the magnetic field for open loop operation of SQUID in the high frequency range are examined.

  2. SQUID magnetometer using sensitivity correction signal for non-magnetic metal contaminants detection

    International Nuclear Information System (INIS)

    Yagi, Toshifumi; Ohashi, Masaharu; Sakuta, Ken

    2016-01-01

    Highlights: • A high-frequency excitation is necessary to detect nonmagnetic metals using SQUID. • It is possible to detect a high-frequency magnetic field using the open loop technique. • Open loop operation leads to a change in the conversion factor. • Conversion between voltage and magnetic field for open loop operation are examined. - Abstract: Measurement methods with SQUID can accurately detect small magnetic metal contaminants based on their magnetic remanence. But, a high-frequency excitation is necessary to detect nonmagnetic metals, on the base of contrasts in electric conductivity. In this work, an open loop technique is introduced to facilitate this. The SQUID is negative feedback controlled (flux locked loop (FLL) operation) for the low frequency range, which includes significant noise due to the movement of the magnetic body or the change of the ambient magnetic field composed of the geomagnetic field and technical signals, and it operates in an open loop configuration for the high frequency range. When using the open loop technique, negative feedback is not applied to the high frequency range. Consequently, the V–Φ characteristic changes due to various causes, which leads to variations in the conversion factor between the SQUID output voltage and the magnetic field. In this study, conversion techniques for the magnetic field for open loop operation of SQUID in the high frequency range are examined.

  3. Intelligent Security IT System for Detecting Intruders Based on Received Signal Strength Indicators

    Directory of Open Access Journals (Sweden)

    Yunsick Sung

    2016-10-01

    Full Text Available Given that entropy-based IT technology has been applied in homes, office buildings and elsewhere for IT security systems, diverse kinds of intelligent services are currently provided. In particular, IT security systems have become more robust and varied. However, access control systems still depend on tags held by building entrants. Since tags can be obtained by intruders, an approach to counter the disadvantages of tags is required. For example, it is possible to track the movement of tags in intelligent buildings in order to detect intruders. Therefore, each tag owner can be judged by analyzing the movements of their tags. This paper proposes a security approach based on the received signal strength indicators (RSSIs of beacon-based tags to detect intruders. The normal RSSI patterns of moving entrants are obtained and analyzed. Intruders can be detected when abnormal RSSIs are measured in comparison to normal RSSI patterns. In the experiments, one normal and one abnormal scenario are defined for collecting the RSSIs of a Bluetooth-based beacon in order to validate the proposed method. When the RSSIs of both scenarios are compared to pre-collected RSSIs, the RSSIs of the abnormal scenario are about 61% more different compared to the RSSIs of the normal scenario. Therefore, intruders in buildings can be detected by considering RSSI differences.

  4. IWGFR benchmark test on signal processing for boiling noise detection, stage 2: Analysis of data from BOR-60

    International Nuclear Information System (INIS)

    Rowley, R.; Waites, C.; Macleod, I.D.

    1989-01-01

    Data from boiling experiments in the BOR 60 reactor in USSR has been supplied by IAEA to enable analysis techniques to be compared. The signals have been analysed at RNL using two basic techniques, High Frequency RMS analysis and Pulse Counting analysis and two more sophisticated methods, Pattern Recognition and Pulse Timing Analysis. All methods indicated boiling successfully, pulse counting proved more sensitive than RMS for the detection of the onset of boiling. Pattern Recognition shows promise of a very reliable detector provided the background can be defined. Data from an Ionisation chamber was also supplied and there was good correlation between the neutronic and acoustic signals. (author). 25 figs, 4 tabs

  5. Two different hematocrit detection methods: Different methods, different results?

    Directory of Open Access Journals (Sweden)

    Schuepbach Reto A

    2010-03-01

    Full Text Available Abstract Background Less is known about the influence of hematocrit detection methodology on transfusion triggers. Therefore, the aim of the present study was to compare two different hematocrit-assessing methods. In a total of 50 critically ill patients hematocrit was analyzed using (1 blood gas analyzer (ABLflex 800 and (2 the central laboratory method (ADVIA® 2120 and compared. Findings Bland-Altman analysis for repeated measurements showed a good correlation with a bias of +1.39% and 2 SD of ± 3.12%. The 24%-hematocrit-group showed a correlation of r2 = 0.87. With a kappa of 0.56, 22.7% of the cases would have been transfused differently. In the-28%-hematocrit group with a similar correlation (r2 = 0.8 and a kappa of 0.58, 21% of the cases would have been transfused differently. Conclusions Despite a good agreement between the two methods used to determine hematocrit in clinical routine, the calculated difference of 1.4% might substantially influence transfusion triggers depending on the employed method.

  6. Wall lizards display conspicuous signals to conspecifics and reduce detection by avian predators

    Science.gov (United States)

    Stevens, Martin

    2014-01-01

    Visual signals are often under conflicting selection to be hidden from predators while being conspicuous to mates and rivals. Here, we investigated whether 3 different island populations of Aegean wall lizards (Podarcis erhardii) with variable coloration among diverse island habitats exhibit simultaneous camouflage and sexual signals. We examined whether signals appear better tuned to conspecific vision as opposed to that of avian predators, and whether background-matching camouflage and sexual signals are partitioned to specific body regions. This could facilitate both covert sexual signaling and camouflage according to the viewing perspectives of predators and conspecifics. We found that lizards typically appeared twice as conspicuous to conspecifics than to avian predators against the same visual background, largely due to lizards’ enhanced sensitivity to ultraviolet, suggesting that P. erhardii signals are tuned to conspecific vision to reduce detection by predators. Males were more conspicuous than females to both predators and conspecifics. In 2 populations, male backs were relatively more camouflaged to predators compared to signaling flanks, whereas in females, exposed and concealed surfaces were camouflaged to predators and generally did not differ in background matching. These findings indicate that lizard coloration evolves under the competing demands of natural and sexual selection to promote signals that are visible to conspecifics while being less perceptible to avian predators. They also elucidate how interactions between natural and sexual selection influence signal detectability and partitioning to different body regions, highlighting the importance of considering receiver vision, viewing perspectives, and signaling environments in studies of signal evolution. PMID:25419083

  7. Evaluating the impact of grade crossing safety factors through signal detection theory

    Science.gov (United States)

    2012-10-22

    The purpose of this effort was to apply signal detection theory to descriptively model the impact : of five grade crossing safety factors to understand their effect on driver decision making. The : safety factors consisted of: improving commercial mo...

  8. Movement and respiration detection using statistical properties of the FMCW radar signal

    KAUST Repository

    Kiuru, Tero; Metso, Mikko; Jardak, Seifallah; Pursula, Pekka; Hakli, Janne; Hirvonen, Mervi; Sepponen, Raimo

    2016-01-01

    This paper presents a 24 GHz FMCW radar system for detection of movement and respiration using change in the statistical properties of the received radar signal, both amplitude and phase. We present the hardware and software segments of the radar

  9. Time-Frequency Analysis of Terahertz Radar Signals for Rapid Heart and Breath Rate Detection

    National Research Council Canada - National Science Library

    Massar, Melody L

    2008-01-01

    We develop new time-frequency analytic techniques which facilitate the detection of a person's heart and breath rates from the Doppler shift the movement of their body induces in a terahertz radar signal...

  10. Rapid and robust detection methods for poison and microbial contamination.

    Science.gov (United States)

    Hoehl, Melanie M; Lu, Peter J; Sims, Peter A; Slocum, Alexander H

    2012-06-27

    Real-time on-site monitoring of analytes is currently in high demand for food contamination, water, medicines, and ingestible household products that were never tested appropriately. Here we introduce chemical methods for the rapid quantification of a wide range of chemical and microbial contaminations using a simple instrument. Within the testing procedure, we used a multichannel, multisample, UV-vis spectrophotometer/fluorometer that employs two frequencies of light simultaneously to interrogate the sample. We present new enzyme- and dye-based methods to detect (di)ethylene glycol in consumables above 0.1 wt % without interference and alcohols above 1 ppb. Using DNA intercalating dyes, we can detect a range of pathogens ( E. coli , Salmonella , V. Cholera, and a model for Malaria) in water, foods, and blood without background signal. We achieved universal scaling independent of pathogen size above 10(4) CFU/mL by taking advantage of the simultaneous measurement at multiple wavelengths. We can detect contaminants directly, without separation, purification, concentration, or incubation. Our chemistry is stable to ± 1% for >3 weeks without refrigeration, and measurements require <5 min.

  11. Signal processing for solar array monitoring, fault detection, and optimization

    CERN Document Server

    Braun, Henry; Spanias, Andreas

    2012-01-01

    Although the solar energy industry has experienced rapid growth recently, high-level management of photovoltaic (PV) arrays has remained an open problem. As sensing and monitoring technology continues to improve, there is an opportunity to deploy sensors in PV arrays in order to improve their management. In this book, we examine the potential role of sensing and monitoring technology in a PV context, focusing on the areas of fault detection, topology optimization, and performance evaluation/data visualization. First, several types of commonly occurring PV array faults are considered and detection algorithms are described. Next, the potential for dynamic optimization of an array's topology is discussed, with a focus on mitigation of fault conditions and optimization of power output under non-fault conditions. Finally, monitoring system design considerations such as type and accuracy of measurements, sampling rate, and communication protocols are considered. It is our hope that the benefits of monitoring presen...

  12. Theoretical and experimental investigation of multispectral photoacoustic osteoporosis detection method

    Science.gov (United States)

    Steinberg, Idan; Hershkovich, Hadas Sara; Gannot, Israel; Eyal, Avishay

    2014-03-01

    Osteoporosis is a widespread disorder, which has a catastrophic impact on patients lives and overwhelming related to healthcare costs. Recently, we proposed a multispectral photoacoustic technique for early detection of osteoporosis. Such technique has great advantages over pure ultrasonic or optical methods as it allows the deduction of both bone functionality from the bone absorption spectrum and bone resistance to fracture from the characteristics of the ultrasound propagation. We demonstrated the propagation of multiple acoustic modes in animal bones in-vitro. To further investigate the effects of multiple wavelength excitations and of induced osteoporosis on the PA signal a multispectral photoacoustic system is presented. The experimental investigation is based on measuring the interference of multiple acoustic modes. The performance of the system is evaluated and a simple two mode theoretical model is fitted to the measured phase signals. The results show that such PA technique is accurate and repeatable. Then a multiple wavelength excitation is tested. It is shown that the PA response due to different excitation wavelengths revels that absorption by the different bone constitutes has a profound effect on the mode generation. The PA response is measured in single wavelength before and after induced osteoporosis. Results show that induced osteoporosis alters the measured amplitude and phase in a consistent manner which allows the detection of the onset of osteoporosis. These results suggest that a complete characterization of the bone over a region of both acoustic and optical frequencies might be used as a powerful tool for in-vivo bone evaluation.

  13. Electromagnetic Signal Feedback Control for Proximity Detection Systems

    Science.gov (United States)

    Smith, Adam K.

    Coal is the most abundant fossil fuel in the United States and remains an essential source of energy. While more than half of coal production comes from surface mining, nearly twice as many workers are employed by underground operations. One of the key pieces of equipment used in underground coal mining is the continuous mining machine. These large and powerful machines are operated in confined spaces by remote control. Since 1984, 40 mine workers in the U. S. have been killed when struck or pinned by a continuous mining machine. It is estimated that a majority of these accidents could have been prevented with the application of proximity detection systems. While proximity detection systems can significantly increase safety around a continuous mining machine, there are some system limitations. Commercially available proximity warning systems for continuous mining machines use magnetic field generators to detect workers and establish safe work areas around the machines. Several environmental factors, however, can influence and distort the magnetic fields. To minimize these effects, a control system has been developed using electromagnetic field strength and generator current to stabilize and control field drift induced by internal and external environmental factors. A laboratory test set-up was built using a ferrite-core magnetic field generator to produce a stable magnetic field. Previous work based on a field-invariant magnetic flux density model, which generically describes the electromagnetic field, is expanded upon. The analytically established transferable shell-based flux density distribution model is used to experimentally validate the control system. By controlling the current input to the ferrite-core generator, a more reliable and consistent magnetic field is produced. Implementation of this technology will improve accuracy and performance of existing commercial proximity detection systems. These research results will help reduce the risk of traumatic

  14. Advanced Signal Processing for Thermal Flaw Detection; TOPICAL

    International Nuclear Information System (INIS)

    VALLEY, MICHAEL T.; HANSCHE, BRUCE D.; PAEZ, THOMAS L.; URBINA, ANGEL; ASHBAUGH, DENNIS M.

    2001-01-01

    Dynamic thermography is a promising technology for inspecting metallic and composite structures used in high-consequence industries. However, the reliability and inspection sensitivity of this technology has historically been limited by the need for extensive operator experience and the use of human judgment and visual acuity to detect flaws in the large volume of infrared image data collected. To overcome these limitations new automated data analysis algorithms and software is needed. The primary objectives of this research effort were to develop a data processing methodology that is tied to the underlying physics, which reduces or removes the data interpretation requirements, and which eliminates the need to look at significant numbers of data frames to determine if a flaw is present. Considering the strengths and weakness of previous research efforts, this research elected to couple both the temporal and spatial attributes of the surface temperature. Of the possible algorithms investigated, the best performing was a radiance weighted root mean square Laplacian metric that included a multiplicative surface effect correction factor and a novel spatio-temporal parametric model for data smoothing. This metric demonstrated the potential for detecting flaws smaller than 0.075 inch in inspection areas on the order of one square foot. Included in this report is the development of a thermal imaging model, a weighted least squares thermal data smoothing algorithm, simulation and experimental flaw detection results, and an overview of the ATAC (Automated Thermal Analysis Code) software that was developed to analyze thermal inspection data

  15. Eyewitness decisions in simultaneous and sequential lineups: a dual-process signal detection theory analysis.

    Science.gov (United States)

    Meissner, Christian A; Tredoux, Colin G; Parker, Janat F; MacLin, Otto H

    2005-07-01

    Many eyewitness researchers have argued for the application of a sequential alternative to the traditional simultaneous lineup, given its role in decreasing false identifications of innocent suspects (sequential superiority effect). However, Ebbesen and Flowe (2002) have recently noted that sequential lineups may merely bring about a shift in response criterion, having no effect on discrimination accuracy. We explored this claim, using a method that allows signal detection theory measures to be collected from eyewitnesses. In three experiments, lineup type was factorially combined with conditions expected to influence response criterion and/or discrimination accuracy. Results were consistent with signal detection theory predictions, including that of a conservative criterion shift with the sequential presentation of lineups. In a fourth experiment, we explored the phenomenological basis for the criterion shift, using the remember-know-guess procedure. In accord with previous research, the criterion shift in sequential lineups was associated with a reduction in familiarity-based responding. It is proposed that the relative similarity between lineup members may create a context in which fluency-based processing is facilitated to a greater extent when lineup members are presented simultaneously.

  16. Augmented Reality for Real-Time Detection and Interpretation of Colorimetric Signals Generated by Paper-Based Biosensors.

    Science.gov (United States)

    Russell, Steven M; Doménech-Sánchez, Antonio; de la Rica, Roberto

    2017-06-23

    Colorimetric tests are becoming increasingly popular in point-of-need analyses due to the possibility of detecting the signal with the naked eye, which eliminates the utilization of bulky and costly instruments only available in laboratories. However, colorimetric tests may be interpreted incorrectly by nonspecialists due to disparities in color perception or a lack of training. Here we solve this issue with a method that not only detects colorimetric signals but also interprets them so that the test outcome is understandable for anyone. It consists of an augmented reality (AR) app that uses a camera to detect the colored signals generated by a nanoparticle-based immunoassay, and that yields a warning symbol or message when the concentration of analyte is higher than a certain threshold. The proposed method detected the model analyte mouse IgG with a limit of detection of 0.3 μg mL -1 , which was comparable to the limit of detection afforded by classical densitometry performed with a nonportable device. When adapted to the detection of E. coli, the app always yielded a "hazard" warning symbol when the concentration of E. coli in the sample was above the infective dose (10 6 cfu mL -1 or higher). The proposed method could help nonspecialists make a decision about drinking from a potentially contaminated water source by yielding an unambiguous message that is easily understood by anyone. The widespread availability of smartphones along with the inexpensive paper test that requires no enzymes to generate the signal makes the proposed assay promising for analyses in remote locations and developing countries.

  17. Detection of Artificially Generated Seismic Signals using Balloon-borne Infrasound Sensors

    OpenAIRE

    Krishnamoorthy, Siddharth; Komjathy, Attila; Pauken, Michael T.; Cutts, James A.; Garcia, Raphael F.; Mimoun, David; Cadu, Alexandre; Sournac, Anthony; Jackson, Jennifer M.; Lai, Voon Hui; Bowman, Daniel C.

    2018-01-01

    We conducted an experiment in Pahrump, Nevada, in June 2017, where artificial seismic signals were created using a seismic hammer, and the possibility of detecting them from their acoustic signature was examined. In this work, we analyze the pressure signals recorded by highly sensitive barometers deployed on the ground and on tethers suspended from balloons. Our signal processing results show that wind noise experienced by a barometer on a free‐flying balloon is lower compared to one on a mo...

  18. Evaluation of signal processing for boiling noise detection. Further analysis of BOR-60 reactor noise data

    International Nuclear Information System (INIS)

    Ledwidge, T.J.; Black, J.L.

    1989-01-01

    The present paper deals with investigations of acoustic signals from a boiling experiment performed on the BOR 60 reactor in the USSR. Signals have been analysed in frequency as well as in time domain. Signal characteristics successfully used to detect the boiling process have been found in time domain. A proposal for in-service boiling monitoring by acoustic means is described. (author). 3 refs, 16 figs

  19. A new detection method used to calibrate Fabry-Perot interferometers in the infrared range

    International Nuclear Information System (INIS)

    Talvard, M.; Javon, C.; Garcin, M.; Thouvenin, D.

    1993-06-01

    Fabry-Perot interferometers are routinely used in the Tore Supra Tokamak in order to measure the time evolution of the electron temperature of the confined plasmas. Calibration of such interferometers requires the detection of very low DC levels (0.1 nV) with signal-to-noise ratios less than 10 -5 , which is generally not compatible with standard detection methods. A new correlation method to achieve this absolute calibration is proposed. It is based on a proper noise auto-correlation technique combined with an optimized signal filtering involving Fourier analysis. The advantages of the method are detailed and experimentally compared to standard averaging techniques, such as coherent addition and synchronous detection. The method can be used in a more general context every time very small amplitude signals are to be measured

  20. Recent developments in optical detection methods for microchip separations

    NARCIS (Netherlands)

    Götz, S.; Karst, U.

    2007-01-01

    This paper summarizes the features and performances of optical detection systems currently applied in order to monitor separations on microchip devices. Fluorescence detection, which delivers very high sensitivity and selectivity, is still the most widely applied method of detection. Instruments

  1. Heat Shock Proteins as Danger Signals for Cancer Detection

    International Nuclear Information System (INIS)

    Seigneuric, Renaud; Mjahed, Hajare; Gobbo, Jessica; Joly, Anne-Laure; Berthenet, Kevin; Shirley, Sarah; Garrido, Carmen

    2011-01-01

    First discovered in 1962, heat shock proteins (HSPs) are highly studied with about 35,500 publications on the subject to date. HSPs are highly conserved, function as molecular chaperones for a large panel of “client” proteins and have strong cytoprotective properties. Induced by many different stress signals, they promote cell survival in adverse conditions. Therefore, their roles have been investigated in several conditions and pathologies where HSPs accumulate, such as in cancer. Among the diverse mammalian HSPs, some members share several features that may qualify them as cancer biomarkers. This review focuses mainly on three inducible HSPs: HSP27, HPS70, and HSP90. Our survey of recent literature highlights some recurring weaknesses in studies of the HSPs, but also identifies findings that indicate that some HSPs have potential as cancer biomarkers for successful clinical applications.

  2. Criteria for assessing the quality of signal processing techniques for acoustic leak detection

    International Nuclear Information System (INIS)

    Prabhakar, R.; Singh, O.P.

    1990-01-01

    In this paper the criteria used in the first IAEA coordinated research programme to assess the quality of signal processing techniques for sodium boiling noise detection are highlighted. Signal processing techniques, using new features sensitive to boiling and a new approach for achieving higher reliability of detection, which were developed at Indira Gandhi Centre for Atomic Research are also presented. 10 refs, 3 figs, 2 tabs

  3. Equation-Method for correcting clipping errors in OFDM signals.

    Science.gov (United States)

    Bibi, Nargis; Kleerekoper, Anthony; Muhammad, Nazeer; Cheetham, Barry

    2016-01-01

    Orthogonal frequency division multiplexing (OFDM) is the digital modulation technique used by 4G and many other wireless communication systems. OFDM signals have significant amplitude fluctuations resulting in high peak to average power ratios which can make an OFDM transmitter susceptible to non-linear distortion produced by its high power amplifiers (HPA). A simple and popular solution to this problem is to clip the peaks before an OFDM signal is applied to the HPA but this causes in-band distortion and introduces bit-errors at the receiver. In this paper we discuss a novel technique, which we call the Equation-Method, for correcting these errors. The Equation-Method uses the Fast Fourier Transform to create a set of simultaneous equations which, when solved, return the amplitudes of the peaks before they were clipped. We show analytically and through simulations that this method can, correct all clipping errors over a wide range of clipping thresholds. We show that numerical instability can be avoided and new techniques are needed to enable the receiver to differentiate between correctly and incorrectly received frequency-domain constellation symbols.

  4. Heterodyne detection of CPFSK signals with and without wavelength conversion up to 5 Gb/s

    DEFF Research Database (Denmark)

    Pedersen, Rune Johan Skullerud; Ebskamp, F.; Mikkelsen, Benny

    1993-01-01

    Detection of wavelength converted signals by a coherent continuous-phase frequency-shift-keying receiver is reported. The signals are wavelength converted over 35 nm, and record receiver sensitivities of -38.7 dBm at 4.0Gb/s and -35.6 dBm at 4.8Gb/s are obtained. Comparison between results...

  5. Image Signal Transfer Method in Artificial Retina using Laser

    Energy Technology Data Exchange (ETDEWEB)

    Yoon, I.Y.; Lee, B.H.; Kim, S.J. [Seoul National University, Seoul (Korea)

    2002-05-01

    Recently, the research on artificial retina for the blind is active. In this paper a new optical link method for the retinal prosthesis is proposed. Laser diode system was chosen to transfer image into the eye in this project and the new optical system was designed and evaluated. The use of laser diode array in artificial retina system makes system simple for lack of signal processing part inside of the eyeball. Designed optical system is enough to focus laser diode array on photodiode array in 20X20 application. (author). 11 refs., 7 figs., 2 tabs.

  6. Detection of Epileptic Seizures with Multi-modal Signal Processing

    DEFF Research Database (Denmark)

    Conradsen, Isa

    convulsive seizures tested. Another study was performed, involving quantitative parameters in the time and frequency domain. The study showed, that there are several differences between tonic seizures and the tonic phase of GTC seizures and furthermore revealed differences of the epileptic (tonic and tonic...... phase of GTC) and simulated seizures. This was valuable information concerning a seizure detection algorithm, and the findings from this research provided evidence for a change in the definition of these seizures by the International League Against Epilepsy (ILAE). Our final study presents a novel...

  7. Observer performance in detecting multiple radiographic signals: prediction and analysis using a generalized ROC approach

    International Nuclear Information System (INIS)

    Metz, C.E.; Starr, S.J.; Lusted, L.B.

    1975-01-01

    The theories of decision processes and signal detection provide a framework for the evaluation of observer performance. Some radiologic procedures involve a search for multiple similar lesions, as in gallstone or pneumoconiosis examinations. A model is presented which attempts to predict, from the conventional receiver operating characteristic (ROC) curve describing the detectability of a single visual signal in a radiograph, observer performance in an experiment requiring detection of more than one such signal. An experiment is described which tests the validity of this model for the case of detecting the presence of zero, one, or two low-contrast radiographic images of a two-mm.-diameter lucite bead embedded in radiographic mottle. Results from six observers, including three radiologists, confirm the validity of the model and suggest that human observer performance for relatively complex detection tasks can be predicted from the results of simpler experiments

  8. Novel method for detection of glycogen in cells.

    Science.gov (United States)

    Skurat, Alexander V; Segvich, Dyann M; DePaoli-Roach, Anna A; Roach, Peter J

    2017-05-01

    Glycogen, a branched polymer of glucose, functions as an energy reserve in many living organisms. Abnormalities in glycogen metabolism, usually excessive accumulation, can be caused genetically, most often through mutation of the enzymes directly involved in synthesis and degradation of the polymer leading to a variety of glycogen storage diseases (GSDs). Microscopic visualization of glycogen deposits in cells and tissues is important for the study of normal glycogen metabolism as well as diagnosis of GSDs. Here, we describe a method for the detection of glycogen using a renewable, recombinant protein which contains the carbohydrate-binding module (CBM) from starch-binding domain containing protein 1 (Stbd1). We generated a fusion protein containing g lutathione S-transferase, a cM c eptitope and the tbd1 BM (GYSC) for use as a glycogen-binding probe, which can be detected with secondary antibodies against glutathione S-transferase or cMyc. By enzyme-linked immunosorbent assay, we demonstrate that GYSC binds glycogen and two other polymers of glucose, amylopectin and amylose. Immunofluorescence staining of cultured cells indicate a GYSC-specific signal that is co-localized with signals obtained with anti-glycogen or anti-glycogen synthase antibodies. GYSC-positive staining inside of lysosomes is observed in individual muscle fibers isolated from mice deficient in lysosomal enzyme acid alpha-glucosidase, a well-characterized model of GSD II (Pompe disease). Co-localized GYSC and glycogen signals are also found in muscle fibers isolated from mice deficient in malin, a model for Lafora disease. These data indicate that GYSC is a novel probe that can be used to study glycogen metabolism under normal and pathological conditions. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

  9. A Genetic Programming Method for the Identification of Signal Peptides and Prediction of Their Cleavage Sites

    Directory of Open Access Journals (Sweden)

    David Lennartsson

    2004-01-01

    Full Text Available A novel approach to signal peptide identification is presented. We use an evolutionary algorithm for automatic evolution of classification programs, so-called programmatic motifs. The variant of evolutionary algorithm used is called genetic programming where a population of solution candidates in the form of full computer programs is evolved, based on training examples consisting of signal peptide sequences. The method is compared with a previous work using artificial neural network (ANN approaches. Some advantages compared to ANNs are noted. The programmatic motif can perform computational tasks beyond that of feed-forward neural networks and has also other advantages such as readability. The best motif evolved was analyzed and shown to detect the h-region of the signal peptide. A powerful parallel computer cluster was used for the experiment.

  10. Time-Frequency Analysis and Hermite Projection Method Applied to Swallowing Accelerometry Signals

    Directory of Open Access Journals (Sweden)

    Ervin Sejdić

    2010-01-01

    Full Text Available Fast Hermite projections have been often used in image-processing procedures such as image database retrieval, projection filtering, and texture analysis. In this paper, we propose an innovative approach for the analysis of one-dimensional biomedical signals that combines the Hermite projection method with time-frequency analysis. In particular, we propose a two-step approach to characterize vibrations of various origins in swallowing accelerometry signals. First, by using time-frequency analysis we obtain the energy distribution of signal frequency content in time. Second, by using fast Hermite projections we characterize whether the analyzed time-frequency regions are associated with swallowing or other phenomena (vocalization, noise, bursts, etc.. The numerical analysis of the proposed scheme clearly shows that by using a few Hermite functions, vibrations of various origins are distinguishable. These results will be the basis for further analysis of swallowing accelerometry to detect swallowing difficulties.

  11. Zero-inflated Poisson model based likelihood ratio test for drug safety signal detection.

    Science.gov (United States)

    Huang, Lan; Zheng, Dan; Zalkikar, Jyoti; Tiwari, Ram

    2017-02-01

    In recent decades, numerous methods have been developed for data mining of large drug safety databases, such as Food and Drug Administration's (FDA's) Adverse Event Reporting System, where data matrices are formed by drugs such as columns and adverse events as rows. Often, a large number of cells in these data matrices have zero cell counts and some of them are "true zeros" indicating that the drug-adverse event pairs cannot occur, and these zero counts are distinguished from the other zero counts that are modeled zero counts and simply indicate that the drug-adverse event pairs have not occurred yet or have not been reported yet. In this paper, a zero-inflated Poisson model based likelihood ratio test method is proposed to identify drug-adverse event pairs that have disproportionately high reporting rates, which are also called signals. The maximum likelihood estimates of the model parameters of zero-inflated Poisson model based likelihood ratio test are obtained using the expectation and maximization algorithm. The zero-inflated Poisson model based likelihood ratio test is also modified to handle the stratified analyses for binary and categorical covariates (e.g. gender and age) in the data. The proposed zero-inflated Poisson model based likelihood ratio test method is shown to asymptotically control the type I error and false discovery rate, and its finite sample performance for signal detection is evaluated through a simulation study. The simulation results show that the zero-inflated Poisson model based likelihood ratio test method performs similar to Poisson model based likelihood ratio test method when the estimated percentage of true zeros in the database is small. Both the zero-inflated Poisson model based likelihood ratio test and likelihood ratio test methods are applied to six selected drugs, from the 2006 to 2011 Adverse Event Reporting System database, with varying percentages of observed zero-count cells.

  12. Damage detection in composite materials using Lamb wave methods

    Science.gov (United States)

    Kessler, Seth S.; Spearing, S. Mark; Soutis, Constantinos

    2002-04-01

    Cost-effective and reliable damage detection is critical for the utilization of composite materials. This paper presents part of an experimental and analytical survey of candidate methods for in situ damage detection of composite materials. Experimental results are presented for the application of Lamb wave techniques to quasi-isotropic graphite/epoxy test specimens containing representative damage modes, including delamination, transverse ply cracks and through-holes. Linear wave scans were performed on narrow laminated specimens and sandwich beams with various cores by monitoring the transmitted waves with piezoceramic sensors. Optimal actuator and sensor configurations were devised through experimentation, and various types of driving signal were explored. These experiments provided a procedure capable of easily and accurately determining the time of flight of a Lamb wave pulse between an actuator and sensor. Lamb wave techniques provide more information about damage presence and severity than previously tested methods (frequency response techniques), and provide the possibility of determining damage location due to their local response nature. These methods may prove suitable for structural health monitoring applications since they travel long distances and can be applied with conformable piezoelectric actuators and sensors that require little power.

  13. Detection and recognition of mechanical, digging and vehicle signals in the optical fiber pre-warning system

    Science.gov (United States)

    Tian, Qing; Yang, Dan; Zhang, Yuan; Qu, Hongquan

    2018-04-01

    This paper presents detection and recognition method to locate and identify harmful intrusions in the optical fiber pre-warning system (OFPS). Inspired by visual attention architecture (VAA), the process flow is divided into two parts, i.e., data-driven process and task-driven process. At first, data-driven process takes all the measurements collected by the system as input signals, which is handled by detection method to locate the harmful intrusion in both spatial domain and time domain. Then, these detected intrusion signals are taken over by task-driven process. Specifically, we get pitch period (PP) and duty cycle (DC) of the intrusion signals to identify the mechanical and manual digging (MD) intrusions respectively. For the passing vehicle (PV) intrusions, their strong low frequency component can be used as good feature. In generally, since the harmful intrusion signals only account for a small part of whole measurements, the data-driven process reduces the amount of input data for subsequent task-driven process considerably. Furthermore, the task-driven process determines the harmful intrusions orderly according to their severity, which makes a priority mechanism for the system as well as targeted processing for different harmful intrusion. At last, real experiments are performed to validate the effectiveness of this method.

  14. Signal de-noising methods for fault diagnosis and troubleshooting at CANDU{sup ®} stations

    Energy Technology Data Exchange (ETDEWEB)

    Nasimi, Elnara; Gabbar, Hossam A., E-mail: hossam.gabbar@uoit.ca

    2014-12-15

    Highlights: • Fault modelling using a Fault Semantic Network (FSN). • Intelligent filtering techniques for signal de-noise in NPP. • Signal feature extraction is applied as integrated with FSN. • Increase signal-to-noise ratio (SNR). - Abstract: Over the past several years a number of domestic CANDU{sup ®} stations have experienced issues with neutron detection systems that challenged safety and operation. Intelligent troubleshooting methodology is required to aid in making risk-informed decisions related to design and operational activities, which can aid current stations and be used for the future generation of CANDU{sup ®} designs. Fault modelling approach using Fault Semantic Network (FSN) with risk estimation is proposed for this purpose. One major challenge in troubleshooting is the determination of accurate data. It is typical to have missing, incomplete or corrupted data points in large process data sets from dynamically changing systems. Therefore, it is expected that quality of obtained data will have a direct impact on the system's ability to recognize developing trends in the process upset situations. In order to enable fault detection process, intelligent filtering techniques are required to de-noise process data and extract valuable signal features in the presence of background noise. In this study, the impact of applying an optimized and intelligent filtering of process signals prior to data analysis is discussed. This is particularly important for neutronic signals in order to increase signal-to-noise ratio (SNR) which suffers the most during start-ups and low power operation. This work is complimentary to the previously published studies on FSN-based fault modelling in CANDU stations. The main objective of this work is to explore the potential research methods using a specific case study and, based on the results and outcomes from this work, to note the possible future improvements and innovation areas.

  15. MMSE-based algorithm for joint signal detection, channel and noise variance estimation for OFDM systems

    CERN Document Server

    Savaux, Vincent

    2014-01-01

    This book presents an algorithm for the detection of an orthogonal frequency division multiplexing (OFDM) signal in a cognitive radio context by means of a joint and iterative channel and noise estimation technique. Based on the minimum mean square criterion, it performs an accurate detection of a user in a frequency band, by achieving a quasi-optimal channel and noise variance estimation if the signal is present, and by estimating the noise level in the band if the signal is absent. Organized into three chapters, the first chapter provides the background against which the system model is pr

  16. Image Processing Methods Usable for Object Detection on the Chessboard

    Directory of Open Access Journals (Sweden)

    Beran Ladislav

    2016-01-01

    Full Text Available Image segmentation and object detection is challenging problem in many research. Although many algorithms for image segmentation have been invented, there is no simple algorithm for image segmentation and object detection. Our research is based on combination of several methods for object detection. The first method suitable for image segmentation and object detection is colour detection. This method is very simply, but there is problem with different colours. For this method it is necessary to have precisely determined colour of segmented object before all calculations. In many cases it is necessary to determine this colour manually. Alternative simply method is method based on background removal. This method is based on difference between reference image and detected image. In this paper several methods suitable for object detection are described. Thisresearch is focused on coloured object detection on chessboard. The results from this research with fusion of neural networks for user-computer game checkers will be applied.

  17. Detectability and acceptability of continuous pulse signals for the MemoPatch® device, an electronic skin patch intended to deliver tactile medication reminder signals

    Directory of Open Access Journals (Sweden)

    Abraham I

    2015-02-01

    Full Text Available Ivo Abraham,1–3 Jan De Geest,2 Wim De Geest,2 Elke De Troy,4 Karen MacDonald3 1Center for Health Outcomes and PharmacoEconomic Research, University of Arizona, Tucson, AZ, USA; 2TheraSolve, Diepenbeek, Belgium; 3Matrix45, Tucson, AZ, USA; 4Jessa Ziekenhuis, Hasselt, Belgium Background: Unintended forgetfulness is the most common cause of medication nonadherence. MemoPatch® is an electronic skin patch intended to deliver discreet tactile medication reminder stimuli. This study aimed 1 to evaluate, within an experimental setup, the detectability and acceptability of fifteen continuous bipolar pulse signals; 2 to identify variables, if any, associated with differential perception of the candidate reminder signals; and 3 to collect safety data as reported by subjects or observed by staff. Methods: This was a laboratory experiment involving 147 healthy adult volunteers (55.1% female, 98.0% Caucasian, with age 41.8±16.0 years, body mass index [BMI] 24.7±4.4, upper body adiposity 28.5%±8.3% body fat, and skin impedance 367.6±140.8Ω and using an experimental version of the MemoPatch®. Following four training signals administered in fixed order, subjects were exposed to a set of fifteen randomly sequenced signals varying in rise and fall time, width, and current, to be rated in terms of detectability ("too weak", "appropriate", or "too strong" and acceptability. Results: Ratings of "appropriate" were virtually independent of such variables as sex, BMI, upper body adiposity, and skin impedance at the patch location. Five signals were rated as "appropriate" by ≥67% of subjects and acceptable by ≥95% of subjects, virtually independently of the indicators of interest, and were retained as candidate signals for use in next stages of development and commercialization. Nine adverse events, none serious, were observed in six subjects. Conclusion: This study yielded five effective and safe candidate signals for potential use in the Memo

  18. Automatic diagnostic methods of nuclear reactor collected signals

    International Nuclear Information System (INIS)

    Lavison, P.

    1978-03-01

    This work is the first phase of an opwall study of diagnosis limited to problems of monitoring the operating state; this allows to show all what the pattern recognition methods bring at the processing level. The present problem is the research of the control operations. The analysis of the state of the reactor gives a decision which is compared with the history of the control operations, and if there is not correspondence, the state subjected to the analysis will be said 'abnormal''. The system subjected to the analysis is described and the problem to solve is defined. Then, one deals with the gaussian parametric approach and the methods to evaluate the error probability. After one deals with non parametric methods and an on-line detection has been tested experimentally. Finally a non linear transformation has been studied to reduce the error probability previously obtained. All the methods presented have been tested and compared to a quality index: the error probability [fr

  19. Dual fiber Bragg gratings configuration-based fiber acoustic sensor for low-frequency signal detection

    Science.gov (United States)

    Yang, Dong; Wang, Shun; Lu, Ping; Liu, Deming

    2014-11-01

    We propose and fabricate a new type fiber acoustic sensor based on dual fiber Bragg gratings (FBGs) configuration. The acoustic sensor head is constructed by putting the sensing cells enclosed in an aluminum cylinder space built by two Cband FBGs and a titanium diaphragm of 50 um thickness. One end of each FBG is longitudinally adhered to the diaphragm by UV glue. Both of the two FBGs are employed for reflecting light. The dual FBGs play roles not only as signal transmission system but also as sensing component, and they demodulate each other's optical signal mutually during the measurement. Both of the two FBGs are pre-strained and the output optical power experiences fluctuation in a linear relationship along with a variation of axial strain and surrounding acoustic interference. So a precise approach to measure the frequency and sound pressure of the acoustic disturbance is achieved. Experiments are performed and results show that a relatively flat frequency response in a range from 200 Hz to 1 kHz with the average signal-to-noise ratio (SNR) above 21 dB is obtained. The maximum sound pressure sensitivity of 11.35mV/Pa is achieved with the Rsquared value of 0.99131 when the sound pressure in the range of 87.7-106.6dB. It has potential applications in low frequency signal detection. Owing to its direct self-demodulation method, the sensing system reveals the advantages of easy to demodulate, good temperature stability and measurement reliability. Besides, performance of the proposed sensor could be improved by optimizing the parameters of the sensor, especially the diaphragm.

  20. Detection of weak transitions in signal dynamics using recurrence time statistics

    International Nuclear Information System (INIS)

    Gao, J.B.; Cao Yinhe; Gu Lingyun; Harris, J.G.; Principe, J.C.

    2003-01-01

    Signal detection in noisy and nonstationary environments is very challenging. In this Letter, we study why the two types of recurrence times [Phys. Rev. Lett. 83 (1999) 3178] may be very useful for detecting weak transitions in signal dynamics. We particularly emphasize that the recurrence times of the second type may be more powerful in detecting transitions with very low energy. These features are illustrated by studying a number of speech signals with fricatives and plosives. We have also shown that the recurrence times of the first type, nevertheless, has the distinguished feature of being more robust to the noise level and less sensitive to the parameter change of the algorithm. Since throughout our study, we have not explored any features unique to the speech signals, the results shown here may indicate that these tools may be useful in many different applications