Land Covers Classification Based on Random Forest Method Using Features from Full-Waveform LIDAR Data

NASA Astrophysics Data System (ADS)

Ma, L.; Zhou, M.; Li, C.

2017-09-01

In this study, a Random Forest (RF) based land covers classification method is presented to predict the types of land covers in Miyun area. The returned full-waveforms which were acquired by a LiteMapper 5600 airborne LiDAR system were processed, including waveform filtering, waveform decomposition and features extraction. The commonly used features that were distance, intensity, Full Width at Half Maximum (FWHM), skewness and kurtosis were extracted. These waveform features were used as attributes of training data for generating the RF prediction model. The RF prediction model was applied to predict the types of land covers in Miyun area as trees, buildings, farmland and ground. The classification results of these four types of land covers were obtained according to the ground truth information acquired from CCD image data of the same region. The RF classification results were compared with that of SVM method and show better results. The RF classification accuracy reached 89.73% and the classification Kappa was 0.8631.

Artificial Intelligence Assists Ultrasonic Inspection

NASA Technical Reports Server (NTRS)

Schaefer, Lloyd A.; Willenberg, James D.

1992-01-01

Subtle indications of flaws extracted from ultrasonic waveforms. Ultrasonic-inspection system uses artificial intelligence to help in identification of hidden flaws in electron-beam-welded castings. System involves application of flaw-classification logic to analysis of ultrasonic waveforms.

A Robust Gold Deconvolution Approach for LiDAR Waveform Data Processing to Characterize Vegetation Structure

NASA Astrophysics Data System (ADS)

Zhou, T.; Popescu, S. C.; Krause, K.; Sheridan, R.; Ku, N. W.

2014-12-01

Increasing attention has been paid in the remote sensing community to the next generation Light Detection and Ranging (lidar) waveform data systems for extracting information on topography and the vertical structure of vegetation. However, processing waveform lidar data raises some challenges compared to analyzing discrete return data. The overall goal of this study was to present a robust de-convolution algorithm- Gold algorithm used to de-convolve waveforms in a lidar dataset acquired within a 60 x 60m study area located in the Harvard Forest in Massachusetts. The waveform lidar data was collected by the National Ecological Observatory Network (NEON). Specific objectives were to: (1) explore advantages and limitations of various waveform processing techniques to derive topography and canopy height information; (2) develop and implement a novel de-convolution algorithm, the Gold algorithm, to extract elevation and canopy metrics; and (3) compare results and assess accuracy. We modeled lidar waveforms with a mixture of Gaussian functions using the Non-least squares (NLS) algorithm implemented in R and derived a Digital Terrain Model (DTM) and canopy height. We compared our waveform-derived topography and canopy height measurements using the Gold de-convolution algorithm to results using the Richardson-Lucy algorithm. Our findings show that the Gold algorithm performed better than the Richardson-Lucy algorithm in terms of recovering the hidden echoes and detecting false echoes for generating a DTM, which indicates that the Gold algorithm could potentially be applied to processing of waveform lidar data to derive information on terrain elevation and canopy characteristics.

Material parameter estimation with terahertz time-domain spectroscopy.

PubMed

Dorney, T D; Baraniuk, R G; Mittleman, D M

2001-07-01

Imaging systems based on terahertz (THz) time-domain spectroscopy offer a range of unique modalities owing to the broad bandwidth, subpicosecond duration, and phase-sensitive detection of the THz pulses. Furthermore, the possibility exists for combining spectroscopic characterization or identification with imaging because the radiation is broadband in nature. To achieve this, we require novel methods for real-time analysis of THz waveforms. This paper describes a robust algorithm for extracting material parameters from measured THz waveforms. Our algorithm simultaneously obtains both the thickness and the complex refractive index of an unknown sample under certain conditions. In contrast, most spectroscopic transmission measurements require knowledge of the sample's thickness for an accurate determination of its optical parameters. Our approach relies on a model-based estimation, a gradient descent search, and the total variation measure. We explore the limits of this technique and compare the results with literature data for optical parameters of several different materials.

Radial artery pulse waveform analysis based on curve fitting using discrete Fourier series.

PubMed

Jiang, Zhixing; Zhang, David; Lu, Guangming

2018-04-19

Radial artery pulse diagnosis has been playing an important role in traditional Chinese medicine (TCM). For its non-invasion and convenience, the pulse diagnosis has great significance in diseases analysis of modern medicine. The practitioners sense the pulse waveforms in patients' wrist to make diagnoses based on their non-objective personal experience. With the researches of pulse acquisition platforms and computerized analysis methods, the objective study on pulse diagnosis can help the TCM to keep up with the development of modern medicine. In this paper, we propose a new method to extract feature from pulse waveform based on discrete Fourier series (DFS). It regards the waveform as one kind of signal that consists of a series of sub-components represented by sine and cosine (SC) signals with different frequencies and amplitudes. After the pulse signals are collected and preprocessed, we fit the average waveform for each sample using discrete Fourier series by least squares. The feature vector is comprised by the coefficients of discrete Fourier series function. Compared with the fitting method using Gaussian mixture function, the fitting errors of proposed method are smaller, which indicate that our method can represent the original signal better. The classification performance of proposed feature is superior to the other features extracted from waveform, liking auto-regression model and Gaussian mixture model. The coefficients of optimized DFS function, who is used to fit the arterial pressure waveforms, can obtain better performance in modeling the waveforms and holds more potential information for distinguishing different psychological states. Copyright © 2018 Elsevier B.V. All rights reserved.

Rapid updating of optical arbitrary waveforms via time-domain multiplexing.

PubMed

Scott, R P; Fontaine, N K; Yang, C; Geisler, D J; Okamoto, K; Heritage, J P; Yoo, S J B

2008-05-15

We demonstrate high-fidelity optical arbitrary waveform generation with 5 GHz waveform switching via time-domain multiplexing. Compact, integrated waveform shapers based on silica arrayed-waveguide grating pairs with 10 GHz channel spacing are used to shape (line-by-line) two different waveforms from the output of a 10-mode x 10 GHz optical frequency comb generator. Characterization of the time multiplexer's complex transfer function (amplitude and phase) by frequency-resolved optical gating permits compensation of its impact on the switched waveforms and matching of the measured and target waveforms to better than G'=5%.

Aging Wire Insulation Assessment by Phase Spectrum Examination of Ultrasonic Guided Waves

NASA Technical Reports Server (NTRS)

Anastasi, Robert F.; Madaras, Eric I.

2003-01-01

Wire integrity has become an area of concern to the aerospace community including DoD, NASA, FAA, and Industry. Over time and changing environmental conditions, wire insulation can become brittle and crack. The cracks expose the wire conductor and can be a source of equipment failure, short circuits, smoke, and fire. The technique of using the ultrasonic phase spectrum to extract material properties of the insulation is being examined. Ultrasonic guided waves will propagate in both the wire conductor and insulation. Assuming the condition of the conductor remains constant then the stiffness of the insulator can be determined by measuring the ultrasonic guided wave velocity. In the phase spectrum method the guided wave velocity is obtained by transforming the time base waveform to the frequency domain and taking the phase difference between two waveforms. The result can then be correlated with a database, derived by numerical model calculations, to extract material properties of the wire insulator. Initial laboratory tests were performed on a simple model consisting of a solid cylinder and then a solid cylinder with a polymer coating. For each sample the flexural mode waveform was identified. That waveform was then transformed to the frequency domain and a phase spectrum was calculated from a pair of waveforms. Experimental results on the simple model compared well to numerical calculations. Further tests were conducted on aircraft or mil-spec wire samples, to see if changes in wire insulation stiffness can be extracted using the phase spectrum technique.

Stability of the Cortical Sensory Waveforms, the P1-N1-P2 Complex and T-Complex, of Auditory Evoked Potentials

ERIC Educational Resources Information Center

Wagner, Monica; Shafer, Valerie L.; Haxhari, Evis; Kiprovski, Kevin; Behrmann, Katherine; Griffiths, Tara

2017-01-01

Purpose: Atypical cortical sensory waveforms reflecting impaired encoding of auditory stimuli may result from inconsistency in cortical response to the acoustic feature changes within spoken words. Thus, the present study assessed intrasubject stability of the P1-N1-P2 complex and T-complex to multiple productions of spoken nonwords in 48 adults…

Decoding Mode-mixing in Black-hole Merger Ringdown

NASA Technical Reports Server (NTRS)

Kelly, Bernard J.; Baker, John G.

2013-01-01

Optimal extraction of information from gravitational-wave observations of binary black-hole coalescences requires detailed knowledge of the waveforms. Current approaches for representing waveform information are based on spin-weighted spherical harmonic decomposition. Higher-order harmonic modes carrying a few percent of the total power output near merger can supply information critical to determining intrinsic and extrinsic parameters of the binary. One obstacle to constructing a full multi-mode template of merger waveforms is the apparently complicated behavior of some of these modes; instead of settling down to a simple quasinormal frequency with decaying amplitude, some |m| = modes show periodic bumps characteristic of mode-mixing. We analyze the strongest of these modes the anomalous (3, 2) harmonic mode measured in a set of binary black-hole merger waveform simulations, and show that to leading order, they are due to a mismatch between the spherical harmonic basis used for extraction in 3D numerical relativity simulations, and the spheroidal harmonics adapted to the perturbation theory of Kerr black holes. Other causes of mode-mixing arising from gauge ambiguities and physical properties of the quasinormal ringdown modes are also considered and found to be small for the waveforms studied here.

Use of the Kalman Filter for Aortic Pressure Waveform Noise Reduction

PubMed Central

Lu, Hsiang-Wei; Wu, Chung-Che; Aliyazicioglu, Zekeriya; Kang, James S.

2017-01-01

Clinical applications that require extraction and interpretation of physiological signals or waveforms are susceptible to corruption by noise or artifacts. Real-time hemodynamic monitoring systems are important for clinicians to assess the hemodynamic stability of surgical or intensive care patients by interpreting hemodynamic parameters generated by an analysis of aortic blood pressure (ABP) waveform measurements. Since hemodynamic parameter estimation algorithms often detect events and features from measured ABP waveforms to generate hemodynamic parameters, noise and artifacts integrated into ABP waveforms can severely distort the interpretation of hemodynamic parameters by hemodynamic algorithms. In this article, we propose the use of the Kalman filter and the 4-element Windkessel model with static parameters, arterial compliance C, peripheral resistance R, aortic impedance r, and the inertia of blood L, to represent aortic circulation for generating accurate estimations of ABP waveforms through noise and artifact reduction. Results show the Kalman filter could very effectively eliminate noise and generate a good estimation from the noisy ABP waveform based on the past state history. The power spectrum of the measured ABP waveform and the synthesized ABP waveform shows two similar harmonic frequencies. PMID:28611850

Method and apparatus for resonant frequency waveform modulation

DOEpatents

Taubman, Matthew S [Richland, WA

2011-06-07

A resonant modulator device and process are described that provide enhanced resonant frequency waveforms to electrical devices including, e.g., laser devices. Faster, larger, and more complex modulation waveforms are obtained than can be obtained by use of conventional current controllers alone.

Alternate Waveforms for a Low-Cost Civil Global Positioning System Receiver

DOT National Transportation Integrated Search

1980-06-01

This report examines the technical feasibility of alternate waveforms to perform the GPS functions and to result in less complex receivers than is possible with the GPS C/A waveform. The approach taken to accomplish this objective is (a) to identify,...

Observations and Bayesian location methodology of transient acoustic signals (likely blue whales) in the Indian Ocean, using a hydrophone triplet.

PubMed

Le Bras, Ronan J; Kuzma, Heidi; Sucic, Victor; Bokelmann, Götz

2016-05-01

A notable sequence of calls was encountered, spanning several days in January 2003, in the central part of the Indian Ocean on a hydrophone triplet recording acoustic data at a 250 Hz sampling rate. This paper presents signal processing methods applied to the waveform data to detect, group, extract amplitude and bearing estimates for the recorded signals. An approximate location for the source of the sequence of calls is inferred from extracting the features from the waveform. As the source approaches the hydrophone triplet, the source level (SL) of the calls is estimated at 187 ± 6 dB re: 1 μPa-1 m in the 15-60 Hz frequency range. The calls are attributed to a subgroup of blue whales, Balaenoptera musculus, with a characteristic acoustic signature. A Bayesian location method using probabilistic models for bearing and amplitude is demonstrated on the calls sequence. The method is applied to the case of detection at a single triad of hydrophones and results in a probability distribution map for the origin of the calls. It can be extended to detections at multiple triads and because of the Bayesian formulation, additional modeling complexity can be built-in as needed.

On the application of neural networks to the classification of phase modulated waveforms

NASA Astrophysics Data System (ADS)

Buchenroth, Anthony; Yim, Joong Gon; Nowak, Michael; Chakravarthy, Vasu

2017-04-01

Accurate classification of phase modulated radar waveforms is a well-known problem in spectrum sensing. Identification of such waveforms aids situational awareness enabling radar and communications spectrum sharing. While various feature extraction and engineering approaches have sought to address this problem, the use of a machine learning algorithm that best utilizes these features is becomes foremost. In this effort, a comparison of a standard shallow and a deep learning approach are explored. Experiments provide insights into classifier architecture, training procedure, and performance.

Generalization of the Child-Langmuir law to the alternate extraction of positive and negative ions

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

Lafleur, T., E-mail: trevor.lafleur@lpp.polytechnique.fr; ONERA-The French Aerospace Lab, 91120 Palaiseau; Aanesland, A.

Using a combined analytical and simulation approach, we investigate positive and negative ion extraction between two electrodes from an ion-ion plasma source. With a square voltage waveform applied to the electrodes, we obtain approximate analytical solutions for the time-averaged extracted current densities, which are given simply by: J{sub p}{sup ac}=[α−fL√((M{sub p})/(q{sub p}V{sub 0}) )]J{sub p}{sup dc}, and J{sub n}{sup ac}=[(1−α)−fL√((M{sub n})/(q{sub n}V{sub 0}) )]J{sub n}{sup dc}, where J{sup ac} is the time-averaged current density, α is the square waveform duty cycle, f is the frequency, L is the electrode gap length, M is the ion mass, q is the ionmore » charge, V{sub 0} is the applied voltage amplitude, J{sup dc} is the dc extracted current density, and the subscripts p and n refer to positive and negative ions, respectively. In particular, if J{sup dc} is the dc space-charge limited current density, then these equations describe the square waveform generalization of the Child-Langmuir law.« less

Study of ultrasonic cavitation during extraction of the peanut oil at varying frequencies.

PubMed

Zhang, Lei; Zhou, Cunshan; Wang, Bei; Yagoub, Abu El-Gasim A; Ma, Haile; Zhang, Xiao; Wu, Mian

2017-07-01

The ultrasonic extraction of oils is a typical physical processing technology. The extraction process was monitored from the standpoint of the oil quality and efficiency of oil extraction. In this study, the ultrasonic cavitation fields were measured by polyvinylidene fluoride (PVDF) sensor. Waveform of ultrasonic cavitation fields was gained and analyzed. The extraction yield and oxidation properties were compared. The relationship between the fields and cavitation oxidation was established. Numerical calculation of oscillation cycle was done for the cavitation bubbles. Results showed that the resonance frequency, f r , of the oil extraction was 40kHz. At f r , the voltage amplitude was the highest; the time was the shortest as reaching the amplitude of the waveform. Accordingly, the cavitation effect worked most rapidly, resulting in the strongest cavitation intensity. The extraction yield and oxidation properties were closely related to the cavitation effect. It controlled the cavitation oxidation effectively from the viewpoint of chemical and physical aspects. Copyright © 2017 Elsevier B.V. All rights reserved.

A Compressed Sensing Based Method for Reducing the Sampling Time of A High Resolution Pressure Sensor Array System

PubMed Central

Sun, Chenglu; Li, Wei; Chen, Wei

2017-01-01

For extracting the pressure distribution image and respiratory waveform unobtrusively and comfortably, we proposed a smart mat which utilized a flexible pressure sensor array, printed electrodes and novel soft seven-layer structure to monitor those physiological information. However, in order to obtain high-resolution pressure distribution and more accurate respiratory waveform, it needs more time to acquire the pressure signal of all the pressure sensors embedded in the smart mat. In order to reduce the sampling time while keeping the same resolution and accuracy, a novel method based on compressed sensing (CS) theory was proposed. By utilizing the CS based method, 40% of the sampling time can be decreased by means of acquiring nearly one-third of original sampling points. Then several experiments were carried out to validate the performance of the CS based method. While less than one-third of original sampling points were measured, the correlation degree coefficient between reconstructed respiratory waveform and original waveform can achieve 0.9078, and the accuracy of the respiratory rate (RR) extracted from the reconstructed respiratory waveform can reach 95.54%. The experimental results demonstrated that the novel method can fit the high resolution smart mat system and be a viable option for reducing the sampling time of the pressure sensor array. PMID:28796188

Waveform Similarity Analysis: A Simple Template Comparing Approach for Detecting and Quantifying Noisy Evoked Compound Action Potentials.

PubMed

Potas, Jason Robert; de Castro, Newton Gonçalves; Maddess, Ted; de Souza, Marcio Nogueira

2015-01-01

Experimental electrophysiological assessment of evoked responses from regenerating nerves is challenging due to the typical complex response of events dispersed over various latencies and poor signal-to-noise ratio. Our objective was to automate the detection of compound action potential events and derive their latencies and magnitudes using a simple cross-correlation template comparison approach. For this, we developed an algorithm called Waveform Similarity Analysis. To test the algorithm, challenging signals were generated in vivo by stimulating sural and sciatic nerves, whilst recording evoked potentials at the sciatic nerve and tibialis anterior muscle, respectively, in animals recovering from sciatic nerve transection. Our template for the algorithm was generated based on responses evoked from the intact side. We also simulated noisy signals and examined the output of the Waveform Similarity Analysis algorithm with imperfect templates. Signals were detected and quantified using Waveform Similarity Analysis, which was compared to event detection, latency and magnitude measurements of the same signals performed by a trained observer, a process we called Trained Eye Analysis. The Waveform Similarity Analysis algorithm could successfully detect and quantify simple or complex responses from nerve and muscle compound action potentials of intact or regenerated nerves. Incorrectly specifying the template outperformed Trained Eye Analysis for predicting signal amplitude, but produced consistent latency errors for the simulated signals examined. Compared to the trained eye, Waveform Similarity Analysis is automatic, objective, does not rely on the observer to identify and/or measure peaks, and can detect small clustered events even when signal-to-noise ratio is poor. Waveform Similarity Analysis provides a simple, reliable and convenient approach to quantify latencies and magnitudes of complex waveforms and therefore serves as a useful tool for studying evoked compound action potentials in neural regeneration studies.

Waveform Similarity Analysis: A Simple Template Comparing Approach for Detecting and Quantifying Noisy Evoked Compound Action Potentials

PubMed Central

Potas, Jason Robert; de Castro, Newton Gonçalves; Maddess, Ted; de Souza, Marcio Nogueira

2015-01-01

Experimental electrophysiological assessment of evoked responses from regenerating nerves is challenging due to the typical complex response of events dispersed over various latencies and poor signal-to-noise ratio. Our objective was to automate the detection of compound action potential events and derive their latencies and magnitudes using a simple cross-correlation template comparison approach. For this, we developed an algorithm called Waveform Similarity Analysis. To test the algorithm, challenging signals were generated in vivo by stimulating sural and sciatic nerves, whilst recording evoked potentials at the sciatic nerve and tibialis anterior muscle, respectively, in animals recovering from sciatic nerve transection. Our template for the algorithm was generated based on responses evoked from the intact side. We also simulated noisy signals and examined the output of the Waveform Similarity Analysis algorithm with imperfect templates. Signals were detected and quantified using Waveform Similarity Analysis, which was compared to event detection, latency and magnitude measurements of the same signals performed by a trained observer, a process we called Trained Eye Analysis. The Waveform Similarity Analysis algorithm could successfully detect and quantify simple or complex responses from nerve and muscle compound action potentials of intact or regenerated nerves. Incorrectly specifying the template outperformed Trained Eye Analysis for predicting signal amplitude, but produced consistent latency errors for the simulated signals examined. Compared to the trained eye, Waveform Similarity Analysis is automatic, objective, does not rely on the observer to identify and/or measure peaks, and can detect small clustered events even when signal-to-noise ratio is poor. Waveform Similarity Analysis provides a simple, reliable and convenient approach to quantify latencies and magnitudes of complex waveforms and therefore serves as a useful tool for studying evoked compound action potentials in neural regeneration studies. PMID:26325291

Photonic generation of low phase noise arbitrary chirped microwave waveforms with large time-bandwidth product.

PubMed

Xie, Weilin; Xia, Zongyang; Zhou, Qian; Shi, Hongxiao; Dong, Yi; Hu, Weisheng

2015-07-13

We present a photonic approach for generating low phase noise, arbitrary chirped microwave waveforms based on heterodyne beating between high order correlated comb lines extracted from frequency-agile optical frequency comb. Using the dual heterodyne phase transfer scheme, extrinsic phase noises induced by the separate optical paths are efficiently suppressed by 42-dB at 1-Hz offset frequency. Linearly chirped microwave waveforms are achieved within 30-ms temporal duration, contributing to a large time-bandwidth product. The linearity measurement leads to less than 90 kHz RMS frequency error during the entire chirp duration, exhibiting excellent linearity for the microwave and sub-THz waveforms. The capability of generating arbitrary waveforms up to sub-THz band with flexible temporal duration, long repetition period, broad bandwidth, and large time-bandwidth product is investigated and discussed.

Application of complex discrete wavelet transform in classification of Doppler signals using complex-valued artificial neural network.

PubMed

Ceylan, Murat; Ceylan, Rahime; Ozbay, Yüksel; Kara, Sadik

2008-09-01

In biomedical signal classification, due to the huge amount of data, to compress the biomedical waveform data is vital. This paper presents two different structures formed using feature extraction algorithms to decrease size of feature set in training and test data. The proposed structures, named as wavelet transform-complex-valued artificial neural network (WT-CVANN) and complex wavelet transform-complex-valued artificial neural network (CWT-CVANN), use real and complex discrete wavelet transform for feature extraction. The aim of using wavelet transform is to compress data and to reduce training time of network without decreasing accuracy rate. In this study, the presented structures were applied to the problem of classification in carotid arterial Doppler ultrasound signals. Carotid arterial Doppler ultrasound signals were acquired from left carotid arteries of 38 patients and 40 healthy volunteers. The patient group included 22 males and 16 females with an established diagnosis of the early phase of atherosclerosis through coronary or aortofemoropopliteal (lower extremity) angiographies (mean age, 59 years; range, 48-72 years). Healthy volunteers were young non-smokers who seem to not bear any risk of atherosclerosis, including 28 males and 12 females (mean age, 23 years; range, 19-27 years). Sensitivity, specificity and average detection rate were calculated for comparison, after training and test phases of all structures finished. These parameters have demonstrated that training times of CVANN and real-valued artificial neural network (RVANN) were reduced using feature extraction algorithms without decreasing accuracy rate in accordance to our aim.

Application of Carbonate Reservoir using waveform inversion and reverse-time migration methods

NASA Astrophysics Data System (ADS)

Kim, W.; Kim, H.; Min, D.; Keehm, Y.

2011-12-01

Recent exploration targets of oil and gas resources are deeper and more complicated subsurface structures, and carbonate reservoirs have become one of the attractive and challenging targets in seismic exploration. To increase the rate of success in oil and gas exploration, it is required to delineate detailed subsurface structures. Accordingly, migration method is more important factor in seismic data processing for the delineation. Seismic migration method has a long history, and there have been developed lots of migration techniques. Among them, reverse-time migration is promising, because it can provide reliable images for the complicated model even in the case of significant velocity contrasts in the model. The reliability of seismic migration images is dependent on the subsurface velocity models, which can be extracted in several ways. These days, geophysicists try to obtain velocity models through seismic full waveform inversion. Since Lailly (1983) and Tarantola (1984) proposed that the adjoint state of wave equations can be used in waveform inversion, the back-propagation techniques used in reverse-time migration have been used in waveform inversion, which accelerated the development of waveform inversion. In this study, we applied acoustic waveform inversion and reverse-time migration methods to carbonate reservoir models with various reservoir thicknesses to examine the feasibility of the methods in delineating carbonate reservoir models. We first extracted subsurface material properties from acoustic waveform inversion, and then applied reverse-time migration using the inverted velocities as a background model. The waveform inversion in this study used back-propagation technique, and conjugate gradient method was used in optimization. The inversion was performed using the frequency-selection strategy. Finally waveform inversion results showed that carbonate reservoir models are clearly inverted by waveform inversion and migration images based on the inversion results are quite reliable. Different thicknesses of reservoir models were also described and the results revealed that the lower boundary of the reservoir was not delineated because of energy loss. From these results, it was noted that carbonate reservoirs can be properly imaged and interpreted by waveform inversion and reverse-time migration methods. This work was supported by the Energy Resources R&D program of the Korea Institute of Energy Technology Evaluation and Planning (KETEP) grant funded by the Korea government Ministry of Knowledge Economy (No. 2009201030001A, No. 2010T100200133) and the Brain Korea 21 project of Energy System Engineering.

A Framework for Land Cover Classification Using Discrete Return LiDAR Data: Adopting Pseudo-Waveform and Hierarchical Segmentation

NASA Technical Reports Server (NTRS)

Jung, Jinha; Pasolli, Edoardo; Prasad, Saurabh; Tilton, James C.; Crawford, Melba M.

2014-01-01

Acquiring current, accurate land-use information is critical for monitoring and understanding the impact of anthropogenic activities on natural environments.Remote sensing technologies are of increasing importance because of their capability to acquire information for large areas in a timely manner, enabling decision makers to be more effective in complex environments. Although optical imagery has demonstrated to be successful for land cover classification, active sensors, such as light detection and ranging (LiDAR), have distinct capabilities that can be exploited to improve classification results. However, utilization of LiDAR data for land cover classification has not been fully exploited. Moreover, spatial-spectral classification has recently gained significant attention since classification accuracy can be improved by extracting additional information from the neighboring pixels. Although spatial information has been widely used for spectral data, less attention has been given to LiDARdata. In this work, a new framework for land cover classification using discrete return LiDAR data is proposed. Pseudo-waveforms are generated from the LiDAR data and processed by hierarchical segmentation. Spatial featuresare extracted in a region-based way using a new unsupervised strategy for multiple pruning of the segmentation hierarchy. The proposed framework is validated experimentally on a real dataset acquired in an urban area. Better classification results are exhibited by the proposed framework compared to the cases in which basic LiDAR products such as digital surface model and intensity image are used. Moreover, the proposed region-based feature extraction strategy results in improved classification accuracies in comparison with a more traditional window-based approach.

Gauge invariant spectral Cauchy characteristic extraction

NASA Astrophysics Data System (ADS)

Handmer, Casey J.; Szilágyi, Béla; Winicour, Jeffrey

2015-12-01

We present gauge invariant spectral Cauchy characteristic extraction. We compare gravitational waveforms extracted from a head-on black hole merger simulated in two different gauges by two different codes. We show rapid convergence, demonstrating both gauge invariance of the extraction algorithm and consistency between the legacy Pitt null code and the much faster spectral Einstein code (SpEC).

Analysis and demonstration of vibration waveform reconstruction in distributed optical fiber vibration sensing system

NASA Astrophysics Data System (ADS)

Zhu, Hui; Shan, Xuekang; Sun, Xiaohan

2017-10-01

A method for reconstructing the vibration waveform from the optical time-domain backscattering pulses in the distributed optical fiber sensing system (DOFSS) is proposed, which allows for extracting and recovering the external vibration signal from the tested pulses by analog signal processing, so that can obtain vibration location and waveform simultaneously. We establish the response model of DOFSS to the external vibration and analyze the effects of system parameters on the operational performance. The main parts of the DOFSS are optimized, including delay fiber length and wavelength, to improve the sensitivity of the system. The experimental system is set up and the vibration amplitudes and reconstructed waveforms are fit well with the original driving signal. The experimental results demonstrate that the performance of vibration waveform reconstruction is good with SNR of 15 dB whenever the external vibrations with different intensities and frequencies exert on the sensing fiber.

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

Cavanaugh, J.E.; McQuarrie, A.D.; Shumway, R.H.

Conventional methods for discriminating between earthquakes and explosions at regional distances have concentrated on extracting specific features such as amplitude and spectral ratios from the waveforms of the P and S phases. We consider here an optimum nonparametric classification procedure derived from the classical approach to discriminating between two Gaussian processes with unequal spectra. Two robust variations based on the minimum discrimination information statistic and Renyi's entropy are also considered. We compare the optimum classification procedure with various amplitude and spectral ratio discriminants and show that its performance is superior when applied to a small population of 8 land-based earthquakesmore » and 8 mining explosions recorded in Scandinavia. Several parametric characterizations of the notion of complexity based on modeling earthquakes and explosions as autoregressive or modulated autoregressive processes are also proposed and their performance compared with the nonparametric and feature extraction approaches.« less

Evaluation of human exposure to complex waveform magnetic fields generated by arc-welding equipment according to European safety standards.

PubMed

Zoppetti, Nicola; Bogi, Andrea; Pinto, Iole; Andreuccetti, Daniele

2015-02-01

In this paper, a procedure is described for the assessment of human exposure to magnetic fields with complex waveforms generated by arc-welding equipment. The work moves from the analysis of relevant guidelines and technical standards, underlining their strengths and their limits. Then, the procedure is described with particular attention to the techniques used to treat complex waveform fields. Finally, the procedure is applied to concrete cases encountered in the workplace. The discussion of the results highlights the critical points in the procedure, as well as those related to the evolution of the technical and exposure standards. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Locating and Modeling Regional Earthquakes with Broadband Waveform Data

NASA Astrophysics Data System (ADS)

Tan, Y.; Zhu, L.; Helmberger, D.

2003-12-01

Retrieving source parameters of small earthquakes (Mw < 4.5), including mechanism, depth, location and origin time, relies on local and regional seismic data. Although source characterization for such small events achieves a satisfactory stage in some places with a dense seismic network, such as TriNet, Southern California, a worthy revisit to the historical events in these places or an effective, real-time investigation of small events in many other places, where normally only a few local waveforms plus some short-period recordings are available, is still a problem. To address this issue, we introduce a new type of approach that estimates location, depth, origin time and fault parameters based on 3-component waveform matching in terms of separated Pnl, Rayleigh and Love waves. We show that most local waveforms can be well modeled by a regionalized 1-D model plus different timing corrections for Pnl, Rayleigh and Love waves at relatively long periods, i.e., 4-100 sec for Pnl, and 8-100 sec for surface waves, except for few anomalous paths involving greater structural complexity, meanwhile, these timing corrections reveal similar azimuthal patterns for well-located cluster events, despite their different focal mechanisms. Thus, we can calibrate the paths separately for Pnl, Rayleigh and Love waves with the timing corrections from well-determined events widely recorded by a dense modern seismic network or a temporary PASSCAL experiment. In return, we can locate events and extract their fault parameters by waveform matching for available waveform data, which could be as less as from two stations, assuming timing corrections from the calibration. The accuracy of the obtained source parameters is subject to the error carried by the events used for the calibration. The detailed method requires a Green­_s function library constructed from a regionalized 1-D model together with necessary calibration information, and adopts a grid search strategy for both hypercenter and focal mechanism. We show that the whole process can be easily automated and routinely provide reliable source parameter estimates with a couple of broadband stations. Two applications in the Tibet Plateau and Southern California will be presented along with comparisons of results against other methods.

Ionization Electron Signal Processing in Single Phase LArTPCs II. Data/Simulation Comparison and Performance in MicroBooNE

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

Adams, C.; et al.

The single-phase liquid argon time projection chamber (LArTPC) provides a large amount of detailed information in the form of fine-grained drifted ionization charge from particle traces. To fully utilize this information, the deposited charge must be accurately extracted from the raw digitized waveforms via a robust signal processing chain. Enabled by the ultra-low noise levels associated with cryogenic electronics in the MicroBooNE detector, the precise extraction of ionization charge from the induction wire planes in a single-phase LArTPC is qualitatively demonstrated on MicroBooNE data with event display images, and quantitatively demonstrated via waveform-level and track-level metrics. Improved performance of inductionmore » plane calorimetry is demonstrated through the agreement of extracted ionization charge measurements across different wire planes for various event topologies. In addition to the comprehensive waveform-level comparison of data and simulation, a calibration of the cryogenic electronics response is presented and solutions to various MicroBooNE-specific TPC issues are discussed. This work presents an important improvement in LArTPC signal processing, the foundation of reconstruction and therefore physics analyses in MicroBooNE.« less

surrkick: Black-hole kicks from numerical-relativity surrogate models

NASA Astrophysics Data System (ADS)

Gerosa, Davide; Hébert, François; Stein, Leo C.

2018-04-01

surrkick quickly and reliably extract recoils imparted to generic, precessing, black hole binaries. It uses a numerical-relativity surrogate model to obtain the gravitational waveform given a set of binary parameters, and from this waveform directly integrates the gravitational-wave linear momentum flux. This entirely bypasses the need of fitting formulae which are typically used to model black-hole recoils in astrophysical contexts.

Waveform shape analysis: extraction of physiologically relevant information from Doppler recordings.

PubMed

Ramsay, M M; Broughton Pipkin, F; Rubin, P C; Skidmore, R

1994-05-01

1. Doppler recordings were made from the brachial artery of healthy female subjects during a series of manoeuvres which altered the pressure-flow characteristics of the vessel. 2. Changes were induced in the peripheral circulation of the forearm by the application of heat or ice-packs. A sphygmomanometer cuff was used to create graded occlusion of the vessel above and below the point of measurement. Recordings were also made whilst the subjects performed a standardized Valsalva manoeuvre. 3. The Doppler recordings were analysed both with the standard waveform indices (systolic/diastolic ratio, pulsatility index and resistance index) and by the method of Laplace transform analysis. 4. The waveform parameters obtained by Laplace transform analysis distinguished the different changes in flow conditions; they thus had direct physiological relevance, unlike the standard waveform indices.

Towards full waveform ambient noise inversion

NASA Astrophysics Data System (ADS)

Sager, Korbinian; Ermert, Laura; Boehm, Christian; Fichtner, Andreas

2018-01-01

In this work we investigate fundamentals of a method—referred to as full waveform ambient noise inversion—that improves the resolution of tomographic images by extracting waveform information from interstation correlation functions that cannot be used without knowing the distribution of noise sources. The fundamental idea is to drop the principle of Green function retrieval and to establish correlation functions as self-consistent observables in seismology. This involves the following steps: (1) We introduce an operator-based formulation of the forward problem of computing correlation functions. It is valid for arbitrary distributions of noise sources in both space and frequency, and for any type of medium, including 3-D elastic, heterogeneous and attenuating media. In addition, the formulation allows us to keep the derivations independent of time and frequency domain and it facilitates the application of adjoint techniques, which we use to derive efficient expressions to compute first and also second derivatives. The latter are essential for a resolution analysis that accounts for intra- and interparameter trade-offs. (2) In a forward modelling study we investigate the effect of noise sources and structure on different observables. Traveltimes are hardly affected by heterogeneous noise source distributions. On the other hand, the amplitude asymmetry of correlations is at least to first order insensitive to unmodelled Earth structure. Energy and waveform differences are sensitive to both structure and the distribution of noise sources. (3) We design and implement an appropriate inversion scheme, where the extraction of waveform information is successively increased. We demonstrate that full waveform ambient noise inversion has the potential to go beyond ambient noise tomography based on Green function retrieval and to refine noise source location, which is essential for a better understanding of noise generation. Inherent trade-offs between source and structure are quantified using Hessian-vector products.

Black-hole kicks from numerical-relativity surrogate models

NASA Astrophysics Data System (ADS)

Gerosa, Davide; Hébert, François; Stein, Leo C.

2018-05-01

Binary black holes radiate linear momentum in gravitational waves as they merge. Recoils imparted to the black-hole remnant can reach thousands of km /s , thus ejecting black holes from their host galaxies. We exploit recent advances in gravitational waveform modeling to quickly and reliably extract recoils imparted to generic, precessing, black-hole binaries. Our procedure uses a numerical-relativity surrogate model to obtain the gravitational waveform given a set of binary parameters; then, from this waveform we directly integrate the gravitational-wave linear momentum flux. This entirely bypasses the need for fitting formulas which are typically used to model black-hole recoils in astrophysical contexts. We provide a thorough exploration of the black-hole kick phenomenology in the parameter space, summarizing and extending previous numerical results on the topic. Our extraction procedure is made publicly available as a module for the Python programming language named surrkick. Kick evaluations take ˜0.1 s on a standard off-the-shelf machine, thus making our code ideal to be ported to large-scale astrophysical studies.

Waveform Analysis Optimization for the 45Ca Beta Decay Experiment

NASA Astrophysics Data System (ADS)

Whitehead, Ryan; ⁴⁵Ca Collaboration

2017-09-01

The 45Ca experiment is searching for a non-zero Fierz interference term, which would imply a tensor type contribution to the low-energy weak interaction, possibly signaling Beyond-the-Standard-Model (BSM) physics. Beta spectrum measurements are being performed at LANL, using the segmented, large area, Si detectors developed for the Nab and UCNB experiments. 109 events have been recorded, with 38 of the 254 pixels instrumented, during the summers of 2016 and 2017. An important step to extracting the energy spectra is the correction of the waveform for pile-up events. A set of analysis tools has been developed to address this issue. A trapezoidal filter has been characterized and optimized for the experimental waveforms. This filter is primarily used for energy extraction, but, by adjusting certain parameters, it has been modified to identify pile-up events. The efficiency varies with the total energy of the particle and the amount deposited with each detector interaction. Preliminary results of this analysis will be presented.

A Data Hiding Technique to Synchronously Embed Physiological Signals in H.264/AVC Encoded Video for Medicine Healthcare.

PubMed

Peña, Raul; Ávila, Alfonso; Muñoz, David; Lavariega, Juan

2015-01-01

The recognition of clinical manifestations in both video images and physiological-signal waveforms is an important aid to improve the safety and effectiveness in medical care. Physicians can rely on video-waveform (VW) observations to recognize difficult-to-spot signs and symptoms. The VW observations can also reduce the number of false positive incidents and expand the recognition coverage to abnormal health conditions. The synchronization between the video images and the physiological-signal waveforms is fundamental for the successful recognition of the clinical manifestations. The use of conventional equipment to synchronously acquire and display the video-waveform information involves complex tasks such as the video capture/compression, the acquisition/compression of each physiological signal, and the video-waveform synchronization based on timestamps. This paper introduces a data hiding technique capable of both enabling embedding channels and synchronously hiding samples of physiological signals into encoded video sequences. Our data hiding technique offers large data capacity and simplifies the complexity of the video-waveform acquisition and reproduction. The experimental results revealed successful embedding and full restoration of signal's samples. Our results also demonstrated a small distortion in the video objective quality, a small increment in bit-rate, and embedded cost savings of -2.6196% for high and medium motion video sequences.

Comparison of Decision Assist and Clinical Judgment of Experts for Prediction of Lifesaving Interventions

DTIC Science & Technology

2015-03-01

min of pulse oximeter photopletysmograph waveforms and extracted features to predict LSIs. We compared this with clinical judgment of LSIs by...Curve (AUROC). We obtained clinical judgment of need for LSI from 405 expert clinicians in135 trauma patients. The pulse oximeter algorithm...15 min of pulse oximeter waveforms predicts the need for LSIs during initial trauma resuscitation as accurately as judgment of expert trauma

The Waveform Suite: A robust platform for accessing and manipulating seismic waveforms in MATLAB

NASA Astrophysics Data System (ADS)

Reyes, C. G.; West, M. E.; McNutt, S. R.

2009-12-01

The Waveform Suite, developed at the University of Alaska Geophysical Institute, is an open-source collection of MATLAB classes that provide a means to import, manipulate, display, and share waveform data while ensuring integrity of the data and stability for programs that incorporate them. Data may be imported from a variety of sources, such as Antelope, Winston databases, SAC files, SEISAN, .mat files, or other user-defined file formats. The waveforms being manipulated in MATLAB are isolated from their stored representations, relieving the overlying programs from the responsibility of understanding the specific format in which data is stored or retrieved. The waveform class provides an object oriented framework that simplifies manipulations to waveform data. Playing with data becomes easier because the tedious aspects of data manipulation have been automated. The user is able to change multiple waveforms simultaneously using standard mathematical operators and other syntactically familiar functions. Unlike MATLAB structs or workspace variables, the data stored within waveform class objects are protected from modification, and instead are accessed through standardized functions, such as get and set; these are already familiar to users of MATLAB’s graphical features. This prevents accidental or nonsensical modifications to the data, which in turn simplifies troubleshooting of complex programs. Upgrades to the internal structure of the waveform class are invisible to applications which use it, making maintenance easier. We demonstrate the Waveform Suite’s capabilities on seismic data from Okmok and Redoubt volcanoes. Years of data from Okmok were retrieved from Antelope and Winston databases. Using the Waveform Suite, we built a tremor-location program. Because the program was built on the Waveform Suite, modifying it to operate on real-time data from Redoubt involved only minimal code changes. The utility of the Waveform Suite as a foundation for large developments is demonstrated with the Correlation Toolbox for MATLAB. This mature package contains 50+ codes for carrying out various type of waveform correlation analyses (multiplet analysis, clustering, interferometry, …) This package is greatly strengthened by delegating numerous book-keeping and signal processing tasks to the underlying Waveform Suite. The Waveform Suite’s built-in tools for searching arbitrary directory/file structures is demonstrated with matched video and audio from the recent eruption of Redoubt Volcano. These tools were used to find subsets of photo images corresponding to specific seismic traces. Using Waveform’s audio file routines, matched video and audio were assembled to produce outreach-quality eruption products. The Waveform Suite is not designed as a ready-to-go replacement for more comprehensive packages such as SAC or AH. Rather, it is a suite of classes which provide core time series functionality in a MATLAB environment. It is designed to be a more robust alternative to the numerous ad hoc MATLAB formats that exist. Complex programs may be created upon the Waveform Suite’s framework, while existing programs may be modified to take advantage of the Waveform Suites capabilities.

Ultra-wideband electronics, design methods, algorithms, and systems for dielectric spectroscopy of isolated B16 tumor cells in liquid medium

NASA Astrophysics Data System (ADS)

Maxwell, Erick N.

Quantifying and characterizing isolated tumor cells (ITCs) is of interest in surgical pathology and cytology for its potential to provide data for cancer staging, classification, and treatment. Although the independent prognostic significance of circulating ITCs has not been proven, their presence is gaining clinical relevance as an indicator. However, researchers have not established an optimal method for detecting ITCs. Consequently, this Ph.D. dissertation is concerned with the development and evaluation of dielectric spectroscopy as a low-cost method for cell characterization and quantification. In support of this goal, ultra-wideband (UWB), microwave pulse generator circuits, coaxial transmission line fixtures, permittivity extraction algorithms, and dielectric spectroscopy measurement systems were developed for evaluating the capacity to quantify B16-F10 tumor cells in suspension. First, this research addressed challenges in developing tunable UWB circuits for pulse generation. In time-domain dielectric spectroscopy, a tunable UWB pulse generator facilitates exploration of microscopic dielectric mechanisms, which contribute to dispersion characteristics. Conventional approaches to tunable pulse generator design have resulted in complex circuit topologies and unsymmetrical waveform morphologies. In this research, a new design approach for low-complexity, tunable, sub-nanosecond and UWB pulse generator was developed. This approach was applied to the development of a novel generator that produces symmetrical waveforms (patent pending 60/597,746). Next, this research addressed problems with transmission-reflection (T/R) measurement of cell suspensions. In T/R measurement, coaxial transmission line fixtures have historically required an elaborate sample holder for containing liquids, resulting in high cost and complexity. Furthermore, the algorithms used to extract T/R dielectric properties have suffered from myriad problems including local minima and halfwavelength resonance. In this dissertation, a simple coaxial transmission line fixture for holding liquids by dispensing with the air-core assumption inherent in previous designs was developed (patent pending 60/916,042). In addition, a genetic algorithm was applied towards extracting dielectric properties from measurement data to circumvent problems of local minima and half wavelength resonance. Finally, in this research the capacity for using dielectric properties to quantify isolated B16-F10 tumor cells in McCoy's liquid medium was investigated. In so doing, the utility of the Maxwell-Wagner mixture formula for cell quantification was demonstrated by measuring distinct dielectric properties for differing volumes of cell suspensions using frequency- and time-domain dielectric spectroscopy.

Measurement and Modeling of Dispersive Pulse Propagation in Drawn Wire Waveguides

NASA Technical Reports Server (NTRS)

Madaras, Eric I.; Kohl, Thomas W.; Rogers, Wayne P.

1995-01-01

An analytical model of dispersive pulse propagation in semi-infinite cylinders due to transient axially symmetric end conditions has been experimentally investigated. Specifically, the dispersive propagation of the first axially symmetric longitudinal mode in thin wire waveguides, which have ends in butt contact with longitudinal piezoelectric ultrasonic transducers, is examined. The method allows for prediction of a propagated waveform given a measured source waveform, together with the material properties of the cylinder. Alternatively, the source waveform can be extracted from measurement of the propagated waveform. The material properties required for implementation of the pulse propagation model are determined using guided wave phase velocity measurements. Hard tempered aluminum 1100 and 304 stainless steel wires, with 127, 305, and 406 micron diam., were examined. In general, the drawn wires were found to behave as transversely isotropic media.

Measurement and modeling of dispersive pulse propagation in draw wire waveguides

NASA Technical Reports Server (NTRS)

Madaras, Eric I.; Kohl, Thomas W.; Rogers, Wayne P.

1995-01-01

An analytical model of dispersive pulse propagation in semi-infinite cylinders due to transient axially symmetric end conditions has been experimentally investigated. Specifically, the dispersive propagation of the first axially symmetric longitudinal mode in thin wire waveguides, which have ends in butt contact with longitudinal piezoelectric ultrasonic transducers, is examined. The method allows for prediction of a propagated waveform given a measured source waveform, together with the material properties of the cylinder. Alternatively, the source waveform can be extracted from measurement of the propagated waveform. The material properties required for implementation of the pulse propagation model are determined using guided wave phase velocity measurements. Hard tempered aluminum 1100 and 304 stainless steel wires, with 127, 305, and 406 micron diam., were examined. In general, the drawn wires were found to behave as transversely isotropic media.

Motion Tolerant Unfocused Imaging of Physiological Waveforms for Blood Pressure Waveform Estimation Using Ultrasound.

PubMed

Seo, Joohyun; Pietrangelo, Sabino J; Sodini, Charles G; Lee, Hae-Seung

2018-05-01

This paper details unfocused imaging using single-element ultrasound transducers for motion tolerant arterial blood pressure (ABP) waveform estimation. The ABP waveform is estimated based on pulse wave velocity and arterial pulsation through Doppler and M-mode ultrasound. This paper discusses approaches to mitigate the effect of increased clutter due to unfocused imaging on blood flow and diameter waveform estimation. An intensity reduction model (IRM) estimator is described to track the change of diameter, which outperforms a complex cross-correlation model (C3M) estimator in low contrast environments. An adaptive clutter filtering approach is also presented, which reduces the increased Doppler angle estimation error due to unfocused imaging. Experimental results in a flow phantom demonstrate that flow velocity and diameter waveforms can be reliably measured with wide lateral offsets of the transducer position. The distension waveform estimated from human carotid M-mode imaging using the IRM estimator shows physiological baseline fluctuations and 0.6-mm pulsatile diameter change on average, which is within the expected physiological range. These results show the feasibility of this low cost and portable ABP waveform estimation device.

Self-sustained vibrations in volcanic areas extracted by Independent Component Analysis: a review and new results

NASA Astrophysics Data System (ADS)

de Lauro, E.; de Martino, S.; Falanga, M.; Palo, M.

2011-12-01

We investigate the physical processes associated with volcanic tremor and explosions. A volcano is a complex system where a fluid source interacts with the solid edifice so generating seismic waves in a regime of low turbulence. Although the complex behavior escapes a simple universal description, the phases of activity generate stable (self-sustained) oscillations that can be described as a non-linear dynamical system of low dimensionality. So, the system requires to be investigated with non-linear methods able to individuate, decompose, and extract the main characteristics of the phenomenon. Independent Component Analysis (ICA), an entropy-based technique is a good candidate for this purpose. Here, we review the results of ICA applied to seismic signals acquired in some volcanic areas. We emphasize analogies and differences among the self-oscillations individuated in three cases: Stromboli (Italy), Erebus (Antarctica) and Volcán de Colima (Mexico). The waveforms of the extracted independent components are specific for each volcano, whereas the similarity can be ascribed to a very general common source mechanism involving the interaction between gas/magma flow and solid structures (the volcanic edifice). Indeed, chocking phenomena or inhomogeneities in the volcanic cavity can play the same role in generating self-oscillations as the languid and the reed do in musical instruments. The understanding of these background oscillations is relevant not only for explaining the volcanic source process and to make a forecast into the future, but sheds light on the physics of complex systems developing low turbulence.

The Instagram: A Novel Sounding Technique for Enhanced HF Propagation Advice

DTIC Science & Technology

2010-05-01

precautions are necessary before such a scheme is attempted, and an ultimate aim might be to have the technique as close to subliminal as possible...waveform on reception has been reduced to subliminal levels. Figure 4 PSD plot of the weighted instagram waveform as received on a...wideband system with simulated background noise level included. Although the signal appears subliminal to other users it can still be extracted with

Strategies for efficient resolution analysis in full-waveform inversion

NASA Astrophysics Data System (ADS)

Fichtner, A.; van Leeuwen, T.; Trampert, J.

2016-12-01

Full-waveform inversion is developing into a standard method in the seismological toolbox. It combines numerical wave propagation for heterogeneous media with adjoint techniques in order to improve tomographic resolution. However, resolution becomes increasingly difficult to quantify because of the enormous computational requirements. Here we present two families of methods that can be used for efficient resolution analysis in full-waveform inversion. They are based on the targeted extraction of resolution proxies from the Hessian matrix, which is too large to store and to compute explicitly. Fourier methods rest on the application of the Hessian to Earth models with harmonic oscillations. This yields the Fourier spectrum of the Hessian for few selected wave numbers, from which we can extract properties of the tomographic point-spread function for any point in space. Random probing methods use uncorrelated, random test models instead of harmonic oscillations. Auto-correlating the Hessian-model applications for sufficiently many test models also characterises the point-spread function. Both Fourier and random probing methods provide a rich collection of resolution proxies. These include position- and direction-dependent resolution lengths, and the volume of point-spread functions as indicator of amplitude recovery and inter-parameter trade-offs. The computational requirements of these methods are equivalent to approximately 7 conjugate-gradient iterations in full-waveform inversion. This is significantly less than the optimisation itself, which may require tens to hundreds of iterations to reach convergence. In addition to the theoretical foundations of the Fourier and random probing methods, we show various illustrative examples from real-data full-waveform inversion for crustal and mantle structure.

Assessment of Gait Characteristics in Total Knee Arthroplasty Patients Using a Hierarchical Partial Least Squares Method.

PubMed

Wang, Wei; Ackland, David C; McClelland, Jodie A; Webster, Kate E; Halgamuge, Saman

2018-01-01

Quantitative gait analysis is an important tool in objective assessment and management of total knee arthroplasty (TKA) patients. Studies evaluating gait patterns in TKA patients have tended to focus on discrete data such as spatiotemporal information, joint range of motion and peak values of kinematics and kinetics, or consider selected principal components of gait waveforms for analysis. These strategies may not have the capacity to capture small variations in gait patterns associated with each joint across an entire gait cycle, and may ultimately limit the accuracy of gait classification. The aim of this study was to develop an automatic feature extraction method to analyse patterns from high-dimensional autocorrelated gait waveforms. A general linear feature extraction framework was proposed and a hierarchical partial least squares method derived for discriminant analysis of multiple gait waveforms. The effectiveness of this strategy was verified using a dataset of joint angle and ground reaction force waveforms from 43 patients after TKA surgery and 31 healthy control subjects. Compared with principal component analysis and partial least squares methods, the hierarchical partial least squares method achieved generally better classification performance on all possible combinations of waveforms, with the highest classification accuracy . The novel hierarchical partial least squares method proposed is capable of capturing virtually all significant differences between TKA patients and the controls, and provides new insights into data visualization. The proposed framework presents a foundation for more rigorous classification of gait, and may ultimately be used to evaluate the effects of interventions such as surgery and rehabilitation.

Waveform complexity caused by near trench structure and its impact on earthquake source study: application to the 2015 Illapel earthquake sequence

NASA Astrophysics Data System (ADS)

Qian, Y.; Wei, S.; Wu, W.; Ni, S.

2017-12-01

Among various types of 3D heterogeneity in the Earth, trench might be the most complex systems, which includes rapidly varying bathymetry and usually thick sediment below water layer. These structure complexities can cause substantial waveform complexities on seismograms, but their corresponding impact on the earthquake source studies has not yet been well understood. Here we explore those effects via studies of two moderate aftershocks (one near the coast while the other close to the Peru-Chile trench axis) in the 2015 Illapel earthquake sequence. The horizontal locations and depths of these two events are poorly constrained and the reported results of various agencies display substantial variations. Thus, we first relocated the epicenters using the P-wave first arrivals and determined other parameters by waveform fitting. In a jackknifing way, we found that the trench event has large differences between regional and teleseismic solutions, in particular for depth, while the coastal event shows consistent results. The teleseismic P/Pdiff waves between these two events also display distinctly different features. More specifically, the trench event has more complex P/Pdiff waves and stronger coda waves, in terms of amplitude and duration (longer than 100s). The coda waves are coherent across stations at different distances and azimuths, indicating a more likely origin of scattering waves due to 3D heterogeneity near trench. To quantitatively model those 3D effects, we adopted a hybrid waveform simulation approach that computes the 3D wavefield in the source region by the Spectral Element Method (SEM) and then propagates the wavefield to teleseismic and shadow zone distances through the Direct Solution Method (DSM). We incorporated the GEBCO bathymetry and water layer into the SEM simulations and assumed the IASP91 1D model for DSM computation. Comparing with the poor 1D synthetics fitting to the data, we do obtain dramatic improvement in 3D waveform fittings across a series of frequency bands. With sensitivity tests of 3D waveform modeling, the centroid longitude and depth for the near trench event are refined. Our study suggests that the complex trench structure must be taken into account for a reliable analysis of shallow earthquake near trench, in particular for the shallowest tsunamigenic earthquakes.

Noise-tolerant instantaneous heart rate and R-peak detection using short-term autocorrelation for wearable healthcare systems.

PubMed

Fujii, Takahide; Nakano, Masanao; Yamashita, Ken; Konishi, Toshihiro; Izumi, Shintaro; Kawaguchi, Hiroshi; Yoshimoto, Masahiko

2013-01-01

This paper describes a robust method of Instantaneous Heart Rate (IHR) and R-peak detection from noisy electrocardiogram (ECG) signals. Generally, the IHR is calculated from the R-wave interval. Then, the R-waves are extracted from the ECG using a threshold. However, in wearable bio-signal monitoring systems, noise increases the incidence of misdetection and false detection of R-peaks. To prevent incorrect detection, we introduce a short-term autocorrelation (STAC) technique and a small-window autocorrelation (SWAC) technique, which leverages the similarity of QRS complex waveforms. Simulation results show that the proposed method improves the noise tolerance of R-peak detection.

Error-analysis and comparison to analytical models of numerical waveforms produced by the NRAR Collaboration

NASA Astrophysics Data System (ADS)

Hinder, Ian; Buonanno, Alessandra; Boyle, Michael; Etienne, Zachariah B.; Healy, James; Johnson-McDaniel, Nathan K.; Nagar, Alessandro; Nakano, Hiroyuki; Pan, Yi; Pfeiffer, Harald P.; Pürrer, Michael; Reisswig, Christian; Scheel, Mark A.; Schnetter, Erik; Sperhake, Ulrich; Szilágyi, Bela; Tichy, Wolfgang; Wardell, Barry; Zenginoğlu, Anıl; Alic, Daniela; Bernuzzi, Sebastiano; Bode, Tanja; Brügmann, Bernd; Buchman, Luisa T.; Campanelli, Manuela; Chu, Tony; Damour, Thibault; Grigsby, Jason D.; Hannam, Mark; Haas, Roland; Hemberger, Daniel A.; Husa, Sascha; Kidder, Lawrence E.; Laguna, Pablo; London, Lionel; Lovelace, Geoffrey; Lousto, Carlos O.; Marronetti, Pedro; Matzner, Richard A.; Mösta, Philipp; Mroué, Abdul; Müller, Doreen; Mundim, Bruno C.; Nerozzi, Andrea; Paschalidis, Vasileios; Pollney, Denis; Reifenberger, George; Rezzolla, Luciano; Shapiro, Stuart L.; Shoemaker, Deirdre; Taracchini, Andrea; Taylor, Nicholas W.; Teukolsky, Saul A.; Thierfelder, Marcus; Witek, Helvi; Zlochower, Yosef

2013-01-01

The Numerical-Relativity-Analytical-Relativity (NRAR) collaboration is a joint effort between members of the numerical relativity, analytical relativity and gravitational-wave data analysis communities. The goal of the NRAR collaboration is to produce numerical-relativity simulations of compact binaries and use them to develop accurate analytical templates for the LIGO/Virgo Collaboration to use in detecting gravitational-wave signals and extracting astrophysical information from them. We describe the results of the first stage of the NRAR project, which focused on producing an initial set of numerical waveforms from binary black holes with moderate mass ratios and spins, as well as one non-spinning binary configuration which has a mass ratio of 10. All of the numerical waveforms are analysed in a uniform and consistent manner, with numerical errors evaluated using an analysis code created by members of the NRAR collaboration. We compare previously-calibrated, non-precessing analytical waveforms, notably the effective-one-body (EOB) and phenomenological template families, to the newly-produced numerical waveforms. We find that when the binary's total mass is ˜100-200M⊙, current EOB and phenomenological models of spinning, non-precessing binary waveforms have overlaps above 99% (for advanced LIGO) with all of the non-precessing-binary numerical waveforms with mass ratios ⩽4, when maximizing over binary parameters. This implies that the loss of event rate due to modelling error is below 3%. Moreover, the non-spinning EOB waveforms previously calibrated to five non-spinning waveforms with mass ratio smaller than 6 have overlaps above 99.7% with the numerical waveform with a mass ratio of 10, without even maximizing on the binary parameters.

Estimating Extracellular Spike Waveforms from CA1 Pyramidal Cells with Multichannel Electrodes

PubMed Central

Molden, Sturla; Moldestad, Olve; Storm, Johan F.

2013-01-01

Extracellular (EC) recordings of action potentials from the intact brain are embedded in background voltage fluctuations known as the “local field potential” (LFP). In order to use EC spike recordings for studying biophysical properties of neurons, the spike waveforms must be separated from the LFP. Linear low-pass and high-pass filters are usually insufficient to separate spike waveforms from LFP, because they have overlapping frequency bands. Broad-band recordings of LFP and spikes were obtained with a 16-channel laminar electrode array (silicone probe). We developed an algorithm whereby local LFP signals from spike-containing channel were modeled using locally weighted polynomial regression analysis of adjoining channels without spikes. The modeled LFP signal was subtracted from the recording to estimate the embedded spike waveforms. We tested the method both on defined spike waveforms added to LFP recordings, and on in vivo-recorded extracellular spikes from hippocampal CA1 pyramidal cells in anaesthetized mice. We show that the algorithm can correctly extract the spike waveforms embedded in the LFP. In contrast, traditional high-pass filters failed to recover correct spike shapes, albeit produceing smaller standard errors. We found that high-pass RC or 2-pole Butterworth filters with cut-off frequencies below 12.5 Hz, are required to retrieve waveforms comparable to our method. The method was also compared to spike-triggered averages of the broad-band signal, and yielded waveforms with smaller standard errors and less distortion before and after the spike. PMID:24391714

A Fiber Bragg Grating Sensor for Radial Artery Pulse Waveform Measurement.

PubMed

Jia, Dagong; Chao, Jing; Li, Shuai; Zhang, Hongxia; Yan, Yingzhan; Liu, Tiegen; Sun, Ye

2018-04-01

In this paper, we report the design and experimental validation of a novel optical sensor for radial artery pulse measurement based on fiber Bragg grating (FBG) and lever amplification mechanism. Pulse waveform analysis is a diagnostic tool for clinical examination and disease diagnosis. High fidelity radial artery pulse waveform has been investigated in clinical studies for estimating central aortic pressure, which is proved to be predictors of cardiovascular diseases. As a three-dimensional cylinder, the radial artery needs to be examined from different locations to achieve optimal pulse waveform for estimation and diagnosis. The proposed optical sensing system is featured as high sensitivity and immunity to electromagnetic interference for multilocation radial artery pulse waveform measurement. The FBG sensor can achieve the sensitivity of 8.236 nm/N, which is comparable to a commonly used electrical sensor. This FBG-based system can provide high accurate measurement, and the key characteristic parameters can be then extracted from the raw signals for clinical applications. The detecting performance is validated through experiments guided by physicians. In the experimental validation, we applied this sensor to measure the pulse waveforms at various positions and depths of the radial artery in the wrist according to the diagnostic requirements. The results demonstrate the high feasibility of using optical systems for physiological measurement and using this FBG sensor for radial artery pulse waveform in clinical applications.

A Computational Method to Quantify Fly Circadian Activity.

PubMed

Lazopulo, Andrey; Syed, Sheyum

2017-10-28

In most animals and plants, circadian clocks orchestrate behavioral and molecular processes and synchronize them to the daily light-dark cycle. Fundamental mechanisms that underlie this temporal control are widely studied using the fruit fly Drosophila melanogaster as a model organism. In flies, the clock is typically studied by analyzing multiday locomotor recording. Such a recording shows a complex bimodal pattern with two peaks of activity: a morning peak that happens around dawn, and an evening peak that happens around dusk. These two peaks together form a waveform that is very different from sinusoidal oscillations observed in clock genes, suggesting that mechanisms in addition to the clock have profound effects in producing the observed patterns in behavioral data. Here we provide instructions on using a recently developed computational method that mathematically describes temporal patterns in fly activity. The method fits activity data with a model waveform that consists of four exponential terms and nine independent parameters that fully describe the shape and size of the morning and evening peaks of activity. The extracted parameters can help elucidate the kinetic mechanisms of substrates that underlie the commonly observed bimodal activity patterns in fly locomotor rhythms.

Application of stored waveform ion modulation 2D-FTICR MS/MS to the analysis of complex mixtures.

PubMed

Ross, Charles W; Simonsick, William J; Aaserud, David J

2002-09-15

Component identification of complex mixtures, whether they are from polymeric formulations or combinatorial synthesis, by conventional MS/MS techniques generally requires component separation by chromatography or mass spectrometry. An automated means of acquiring simultaneous MS/MS data from a complex mixture without prior separation is obtained from stored waveform ion modulation (SWIM) two-dimensional FTICR MS/MS. The technique applies a series of SWIFT excitation waveforms whose frequency domain magnitude spectrum is a sinusoid increasing in frequency from one waveform to the next. The controlled dissociation of the precursor ions produces an associated modulation of the product ion abundances. Fourier transformation of these abundances reveals the encoded modulation frequency from which connectivities of precursor and product ions are observed. The final result is total assignment of product ions for each precursor ion in a mixture from one automated experiment. We demonstrated the applicability of SWIM 2D-FTICR MS/MS to two diverse samples of industrial importance. We characterized structured polyester oligomers and products derived from combinatorial synthesis. Fragmentation pathways identified in standard serial ion isolation MS/MS experiments were observed for trimethylolpropane/methyl hexahydrophthalic anhydride. A 20-component sample derived from combinatorial synthesis was fragmented, and the template ion along with another key fragment ion was identified for each of the 20 components.

Surface atrial frequency analysis in patients with atrial fibrillation: a tool for evaluating the effects of intervention.

PubMed

Raine, Dan; Langley, Philip; Murray, Alan; Dunuwille, Asunga; Bourke, John P

2004-09-01

The aims of this study were to evaluate (1) principal component analysis as a technique for extracting the atrial signal waveform from the standard 12-lead ECG and (2) its ability to distinguish changes in atrial fibrillation (AF) frequency parameters over time and in response to pharmacologic manipulation using drugs with different effects on atrial electrophysiology. Twenty patients with persistent AF were studied. Continuous 12-lead Holter ECGs were recorded for 60 minutes, first, in the drug-free state. Mean and variability of atrial waveform frequency were measured using an automated computer technique. This extracted the atrial signal by principal component analysis and identified the main frequency component using Fourier analysis. Patients were then allotted sequentially to receive 1 of 4 drugs intravenously (amiodarone, flecainide, sotalol, or metoprolol), and changes induced in mean and variability of atrial waveform frequency measured. Mean and variability of atrial waveform frequency did not differ within patients between the two 30-minute sections of the drug-free state. As hypothesized, significant changes in mean and variability of atrial waveform frequency were detected after manipulation with amiodarone (mean: 5.77 vs 4.86 Hz; variability: 0.55 vs 0.31 Hz), flecainide (mean: 5.33 vs 4.72 Hz; variability: 0.71 vs 0.31 Hz), and sotalol (mean: 5.94 vs 4.90 Hz; variability: 0.73 vs 0.40 Hz) but not with metoprolol (mean: 5.41 vs 5.17 Hz; variability: 0.81 vs 0.82 Hz). A technique for continuously analyzing atrial frequency characteristics of AF from the surface ECG has been developed and validated.

Mismodeling in gravitational-wave astronomy: The trouble with templates

NASA Astrophysics Data System (ADS)

Sampson, Laura; Cornish, Neil; Yunes, Nicolás

2014-03-01

Waveform templates are a powerful tool for extracting and characterizing gravitational wave signals, acting as highly restrictive priors on the signal morphologies that allow us to extract weak events buried deep in the instrumental noise. The templates map the waveform shapes to physical parameters, thus allowing us to produce posterior probability distributions for these parameters. However, there are attendant dangers in using highly restrictive signal priors. If strong field gravity is not accurately described by general relativity (GR), then using GR templates may result in fundamental bias in the recovered parameters, or even worse, a complete failure to detect signals. Here we study such dangers, concentrating on three distinct possibilities. First, we show that there exist modified theories compatible with all existing observations that would fail to be detected by the LIGO/Virgo network using searches based on GR templates, but which would be detected using a one parameter post-Einsteinian extension. Second, we study modified theories that produce departures from GR that turn on suddenly at a critical frequency, producing waveforms that do not directly fit into the simplest parametrized post-Einsteinian (ppE) scheme. We show that even the simplest ppE templates are still capable of picking up these strange signals and diagnosing a departure from GR. Third, we study whether using inspiral-only ppE waveforms for signals that include merger and ringdown can lead to problems in misidentifying a GR departure. We present a simple technique that allows us to self-consistently identify the inspiral portion of the signal, and thus remove these potential biases, allowing GR tests to be performed on higher mass signals that merge within the detector band. We close by studying a parametrized waveform model that may allow us to test GR using the full inspiral-merger-ringdown signal.

Velocity Structure Determination Through Seismic Waveform Modeling and Time Deviations

NASA Astrophysics Data System (ADS)

Savage, B.; Zhu, L.; Tan, Y.; Helmberger, D. V.

2001-12-01

Through the use of seismic waveforms recorded by TriNet, a dataset of earthquake focal mechanisms and deviations (time shifts) relative to a standard model facilitates the investigation of the crust and uppermost mantle of southern California. The CAP method of focal mechanism determination, in use by TriNet on a routine basis, provides time shifts for surface waves and Pnl arrivals independently relative to the reference model. These shifts serve as initial data for calibration of local and regional seismic paths. Time shifts from the CAP method are derived by splitting the Pnl section of the waveform, the first arriving Pn to just before the arrival of the S wave, from the much slower surface waves then cross-correlating the data with synthetic waveforms computed from a standard model. Surface waves interact with the entire crust, but the upper crust causes the greatest effect. Whereas, Pnl arrivals sample the deeper crust, upper mantle, and source region. This natural division separates the upper from lower crust for regional calibration and structural modeling and allows 3-D velocity maps to be created using the resulting time shifts. Further examination of Pnl and other arrivals which interact with the Moho illuminate the complex nature of this boundary. Initial attempts at using the first 10 seconds of the Pnl section to determine upper most mantle structure have proven insightful. Two large earthquakes north of southern California in Nevada and Mammoth Lakes, CA allow the creation of record sections from 200 to 600 km. As the paths swing from east to west across southern California, simple 1-D models turn into complex structure, dramatically changing the waveform character. Using finite difference models to explain the structure, we determine that a low velocity zone is present at the base of the crust and extends to 100 km in depth. Velocity variations of 5 percent of the mantle in combination with steeply sloping edges produces complex waveform variations. Characteristics of this complex propagation appear from the southern Sierra Nevada Mountains, in the west, to Death Valley in the east. The structure does not cross the Garlock fault to the south, but we are unsure of the structures northern extent.

Single pulse analysis of intracranial pressure for a hydrocephalus implant.

PubMed

Elixmann, I M; Hansinger, J; Goffin, C; Antes, S; Radermacher, K; Leonhardt, S

2012-01-01

The intracranial pressure (ICP) waveform contains important diagnostic information. Changes in ICP are associated with changes of the pulse waveform. This change has explicitly been observed in 13 infusion tests by analyzing 100 Hz ICP data. An algorithm is proposed which automatically extracts the pulse waves and categorizes them into predefined patterns. A developed algorithm determined 88 %±8 % (mean ±SD) of all classified pulse waves correctly on predefined patterns. This algorithm has low computational cost and is independent of a pressure drift in the sensor by using only the relationship between special waveform characteristics. Hence, it could be implemented on a microcontroller of a future electromechanic hydrocephalus shunt system to control the drainage of cerebrospinal fluid (CSF).

Electron current extraction from radio frequency excited micro-dielectric barrier discharges

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

Wang, Jun-Chieh; Kushner, Mark J.; Leoni, Napoleon

Micro dielectric barrier discharges (mDBDs) consist of micro-plasma devices (10-100 {mu}m diameter) in which the electrodes are fully or partially covered by dielectrics, and often operate at atmospheric pressure driven with radio frequency (rf) waveforms. In certain applications, it may be desirable to extract electron current out of the mDBD plasma, which necessitates a third electrode. As a result, the physical structure of the m-DBD and the electron emitting properties of its materials are important to its operation. In this paper, results from a two-dimensional computer simulation of current extraction from mDBDs sustained in atmospheric pressure N{sub 2} will bemore » discussed. The mDBDs are sandwich structures with an opening of tens-of-microns excited with rf voltage waveforms of up to 25 MHz. Following avalanche by electron impact ionization in the mDBD cavity, the plasma can be expelled from the cavity towards the extraction electrode during the part of the rf cycle when the extraction electrode appears anodic. The electron current extraction can be enhanced by biasing this electrode. The charge collection can be controlled by choice of rf frequency, rf driving voltage, and permittivity of the dielectric barrier.« less

A Decade Remote Sensing River Bathymetry with the Experimental Advanced Airborne Research LiDAR

NASA Astrophysics Data System (ADS)

Kinzel, P. J.; Legleiter, C. J.; Nelson, J. M.; Skinner, K.

2012-12-01

Since 2002, the first generation of the Experimental Advanced Airborne Research LiDAR (EAARL-A) sensor has been deployed for mapping rivers and streams. We present and summarize the results of comparisons between ground truth surveys and bathymetry collected by the EAARL-A sensor in a suite of rivers across the United States. These comparisons include reaches on the Platte River (NE), Boise and Deadwood Rivers (ID), Blue and Colorado Rivers (CO), Klamath and Trinity Rivers (CA), and the Shenandoah River (VA). In addition to diverse channel morphologies (braided, single thread, and meandering) these rivers possess a variety of substrates (sand, gravel, and bedrock) and a wide range of optical characteristics which influence the attenuation and scattering of laser energy through the water column. Root mean square errors between ground truth elevations and those measured by the EAARL-A ranged from 0.15-m in rivers with relatively low turbidity and highly reflective sandy bottoms to over 0.5-m in turbid rivers with less reflective substrates. Mapping accuracy with the EAARL-A has proved challenging in pools where bottom returns are either absent in waveforms or are of such low intensity that they are treated as noise by waveform processing algorithms. Resolving bathymetry in shallow depths where near surface and bottom returns are typically convolved also presents difficulties for waveform processing routines. The results of these evaluations provide an empirical framework to discuss the capabilities and limitations of the EAARL-A sensor as well as previous generations of post-processing software for extracting bathymetry from complex waveforms. These experiences and field studies not only provide benchmarks for the evaluation of the next generation of bathymetric LiDARs for use in river mapping, but also highlight the importance of developing and standardizing more rigorous methods to characterize substrate reflectance and in-situ optical properties at study sites. They also point out the continued necessity of ground truth data for algorithm refinement and survey verification.

Direct Extraction of Tumor Response Based on Ensemble Empirical Mode Decomposition for Image Reconstruction of Early Breast Cancer Detection by UWB.

PubMed

Li, Qinwei; Xiao, Xia; Wang, Liang; Song, Hang; Kono, Hayato; Liu, Peifang; Lu, Hong; Kikkawa, Takamaro

2015-10-01

A direct extraction method of tumor response based on ensemble empirical mode decomposition (EEMD) is proposed for early breast cancer detection by ultra-wide band (UWB) microwave imaging. With this approach, the image reconstruction for the tumor detection can be realized with only extracted signals from as-detected waveforms. The calibration process executed in the previous research for obtaining reference waveforms which stand for signals detected from the tumor-free model is not required. The correctness of the method is testified by successfully detecting a 4 mm tumor located inside the glandular region in one breast model and by the model located at the interface between the gland and the fat, respectively. The reliability of the method is checked by distinguishing a tumor buried in the glandular tissue whose dielectric constant is 35. The feasibility of the method is confirmed by showing the correct tumor information in both simulation results and experimental results for the realistic 3-D printed breast phantom.

Asymmetric Waveforms Decrease Lethal Thresholds in High Frequency Irreversible Electroporation Therapies

PubMed Central

Sano, Michael B.; Fan, Richard E.; Xing, Lei

2017-01-01

Irreversible electroporation (IRE) is a promising non-thermal treatment for inoperable tumors which uses short (50–100 μs) high voltage monopolar pulses to disrupt the membranes of cells within a well-defined volume. Challenges with IRE include complex treatment planning and the induction of intense muscle contractions. High frequency IRE (H-FIRE) uses bursts of ultrashort (0.25–5 μs) alternating polarity pulses to produce more predictable ablations and alleviate muscle contractions associated with IRE. However, H-FIRE generally ablates smaller volumes of tissue than IRE. This study shows that asymmetric H-FIRE waveforms can be used to create ablation volumes equivalent to standard IRE treatments. Lethal thresholds (LT) of 505 V/cm and 1316 V/cm were found for brain cancer cells when 100 μs IRE and 2 μs symmetric H-FIRE waveforms were used. In contrast, LT as low as 536 V/cm were found for 2 μs asymmetric H-FIRE waveforms. Reversible electroporation thresholds were 54% lower than LTs for symmetric waveforms and 33% lower for asymmetric waveforms indicating that waveform symmetry can be used to tune the relative sizes of reversible and irreversible ablation zones. Numerical simulations predicted that asymmetric H-FIRE waveforms are capable of producing ablation volumes which were 5.8–6.3x larger than symmetric H-FIRE waveforms indicating that in vivo investigation of asymmetric waveforms is warranted. PMID:28106146

Asymmetric Waveforms Decrease Lethal Thresholds in High Frequency Irreversible Electroporation Therapies

NASA Astrophysics Data System (ADS)

Sano, Michael B.; Fan, Richard E.; Xing, Lei

2017-01-01

Irreversible electroporation (IRE) is a promising non-thermal treatment for inoperable tumors which uses short (50-100 μs) high voltage monopolar pulses to disrupt the membranes of cells within a well-defined volume. Challenges with IRE include complex treatment planning and the induction of intense muscle contractions. High frequency IRE (H-FIRE) uses bursts of ultrashort (0.25-5 μs) alternating polarity pulses to produce more predictable ablations and alleviate muscle contractions associated with IRE. However, H-FIRE generally ablates smaller volumes of tissue than IRE. This study shows that asymmetric H-FIRE waveforms can be used to create ablation volumes equivalent to standard IRE treatments. Lethal thresholds (LT) of 505 V/cm and 1316 V/cm were found for brain cancer cells when 100 μs IRE and 2 μs symmetric H-FIRE waveforms were used. In contrast, LT as low as 536 V/cm were found for 2 μs asymmetric H-FIRE waveforms. Reversible electroporation thresholds were 54% lower than LTs for symmetric waveforms and 33% lower for asymmetric waveforms indicating that waveform symmetry can be used to tune the relative sizes of reversible and irreversible ablation zones. Numerical simulations predicted that asymmetric H-FIRE waveforms are capable of producing ablation volumes which were 5.8-6.3x larger than symmetric H-FIRE waveforms indicating that in vivo investigation of asymmetric waveforms is warranted.

A comparison of waveform processing algorithms for single-wavelength LiDAR bathymetry

NASA Astrophysics Data System (ADS)

Wang, Chisheng; Li, Qingquan; Liu, Yanxiong; Wu, Guofeng; Liu, Peng; Ding, Xiaoli

2015-03-01

Due to the low-cost and lightweight units, single-wavelength LiDAR bathymetric systems are an ideal option for shallow-water (<12 m) bathymetry. However, one disadvantage of such systems is the lack of near-infrared and Raman channels, which results in difficulties in extracting the water surface. Therefore, the choice of a suitable waveform processing method is extremely important to guarantee the accuracy of the bathymetric retrieval. In this paper, we test six algorithms for single-wavelength bathymetric waveform processing, i.e. peak detection (PD), the average square difference function (ASDF), Gaussian decomposition (GD), quadrilateral fitting (QF), Richardson-Lucy deconvolution (RLD), and Wiener filter deconvolution (WD). To date, most of these algorithms have previously only been applied in topographic LiDAR waveforms captured over land. A simulated dataset and an Optech Aquarius dataset were used to assess the algorithms, with the focus being on their capability of extracting the depth and the bottom response. The influences of a number of water and equipment parameters were also investigated by the use of a Monte Carlo method. The results showed that the RLD method had a superior performance in terms of a high detection rate and low errors in the retrieved depth and magnitude. The attenuation coefficient, noise level, water depth, and bottom reflectance had significant influences on the measurement error of the retrieved depth, while the effects of scan angle and water surface roughness were not so obvious.

Spatial probabilistic pulsatility model for enhancing photoplethysmographic imaging systems

NASA Astrophysics Data System (ADS)

Amelard, Robert; Clausi, David A.; Wong, Alexander

2016-11-01

Photoplethysmographic imaging (PPGI) is a widefield noncontact biophotonic technology able to remotely monitor cardiovascular function over anatomical areas. Although spatial context can provide insight into physiologically relevant sampling locations, existing PPGI systems rely on coarse spatial averaging with no anatomical priors for assessing arterial pulsatility. Here, we developed a continuous probabilistic pulsatility model for importance-weighted blood pulse waveform extraction. Using a data-driven approach, the model was constructed using a 23 participant sample with a large demographic variability (11/12 female/male, age 11 to 60 years, BMI 16.4 to 35.1 kg·m-2). Using time-synchronized ground-truth blood pulse waveforms, spatial correlation priors were computed and projected into a coaligned importance-weighted Cartesian space. A modified Parzen-Rosenblatt kernel density estimation method was used to compute the continuous resolution-agnostic probabilistic pulsatility model. The model identified locations that consistently exhibited pulsatility across the sample. Blood pulse waveform signals extracted with the model exhibited significantly stronger temporal correlation (W=35,p<0.01) and spectral SNR (W=31,p<0.01) compared to uniform spatial averaging. Heart rate estimation was in strong agreement with true heart rate [r2=0.9619, error (μ,σ)=(0.52,1.69) bpm].

Utilization of multiple spinal cord stimulation (SCS) waveforms in chronic pain patients.

PubMed

Berg, Anthony P; Mekel-Bobrov, Nitzan; Goldberg, Edward; Huynh, Dat; Jain, Roshini

2017-08-01

Advances in spinal cord stimulation (SCS) have improved patient outcomes, leading to its increased utilization for chronic pain. Chronic pain is dynamic showing exacerbations, variable severity, and evolving pain patterns. Given this complexity, SCS systems that provide a broad range of stimulation waveforms may be valuable. The aim of this research was to characterize the usage pattern of stimulation waveforms and field shapes in chronic pain patients implanted with the Spectra System. A review of daily device usage in a cohort of 250 patients implanted for a minimum duration of one month was conducted. With follow-ups ranging between 1 month and 1 year post-implant, 72.8% of patients used Standard Rate, 34.8% Anode Intensification, 23.2% Higher Rate, and 8.4% Burst stimulation waveforms. Collectively, 60% used 1 or more advanced waveforms, either exclusively or along with Standard Rate. A trend showed patients continuing to use up to 3 programs one year post-implant. When given a choice, SCS patients often utilize a variety of waveforms, suggesting that patients may benefit from a single system that provides multiple waveforms and field shapes to customize therapy and improve efficacy.

A Software Platform for Post-Processing Waveform-Based NDE

NASA Technical Reports Server (NTRS)

Roth, Donald J.; Martin, Richard E.; Seebo, Jeff P.; Trinh, Long B.; Walker, James L.; Winfree, William P.

2007-01-01

Ultrasonic, microwave, and terahertz nondestructive evaluation imaging systems generally require the acquisition of waveforms at each scan point to form an image. For such systems, signal and image processing methods are commonly needed to extract information from the waves and improve resolution of, and highlight, defects in the image. Since some similarity exists for all waveform-based NDE methods, it would seem a common software platform containing multiple signal and image processing techniques to process the waveforms and images makes sense where multiple techniques, scientists, engineers, and organizations are involved. This presentation describes NASA Glenn Research Center's approach in developing a common software platform for processing waveform-based NDE signals and images. This platform is currently in use at NASA Glenn and at Lockheed Martin Michoud Assembly Facility for processing of pulsed terahertz and ultrasonic data. Highlights of the software operation will be given. A case study will be shown for use with terahertz data. The authors also request scientists and engineers who are interested in sharing customized signal and image processing algorithms to contribute to this effort by letting the authors code up and include these algorithms in future releases.

OFDM inspired waveforms for 5G

DOE PAGES

Farhang-Boroujeny, Behrouz; Moradi, Hussein

2016-05-12

As the standardization activities are being formed to lay the foundation of 5G wireless networks, there is a common consensus on the need to replace the celebrated OFDM by a more effective air interface that better serves the challenging needs of 5G. The main reason that has made OFDM popular in the past is related to the fact that information symbols are carried over a number of pure tones/sinusoidal signals. Moreover, with the use of cyclic prefix (CP), it is assured that the information carrying tones are only affected by the channel (complex) gains at the respective frequencies. Accordingly, themore » channel effect can be trivially compensated for (equalized) in the frequency domain through a single complex tap per subcarrier. However, as network air interfaces become more complex and the demand for multiuser services grows, OFDM is found to be incapable of handling the inevitable loss of synchronization among users. In the recent past, two novel waveforms (namely, GFDM and C-FBMC) have been discussed in the literature to overcome this and other drawbacks of OFDM. Interestingly, and at the same time not surprising, these methods share a common fundamental property with OFDM: each data packet is made up of a number of tones that are modulated by information symbols. In this tutorial article, we build a common framework based on the said OFDM principle and derive GFDM and C-FBMC waveforms from this point of view. This derivation provides a new prospective that facilitates straightforward understanding of channel equalization and the application of these new waveforms to MIMO channels. As a result, it also facilitates derivation of new structures for more efficient synthesis/analysis of these waveforms than those that have been reported in the literature.« less

Designing Waveform Sets with Good Correlation and Stopband Properties for MIMO Radar via the Gradient-Based Method

PubMed Central

Tang, Liang; Zhu, Yongfeng; Fu, Qiang

2017-01-01

Waveform sets with good correlation and/or stopband properties have received extensive attention and been widely used in multiple-input multiple-output (MIMO) radar. In this paper, we aim at designing unimodular waveform sets with good correlation and stopband properties. To formulate the problem, we construct two criteria to measure the correlation and stopband properties and then establish an unconstrained problem in the frequency domain. After deducing the phase gradient and the step size, an efficient gradient-based algorithm with monotonicity is proposed to minimize the objective function directly. For the design problem without considering the correlation weights, we develop a simplified algorithm, which only requires a few fast Fourier transform (FFT) operations and is more efficient. Because both of the algorithms can be implemented via the FFT operations and the Hadamard product, they are computationally efficient and can be used to design waveform sets with a large waveform number and waveform length. Numerical experiments show that the proposed algorithms can provide better performance than the state-of-the-art algorithms in terms of the computational complexity. PMID:28468308

Designing Waveform Sets with Good Correlation and Stopband Properties for MIMO Radar via the Gradient-Based Method.

PubMed

Tang, Liang; Zhu, Yongfeng; Fu, Qiang

2017-05-01

Waveform sets with good correlation and/or stopband properties have received extensive attention and been widely used in multiple-input multiple-output (MIMO) radar. In this paper, we aim at designing unimodular waveform sets with good correlation and stopband properties. To formulate the problem, we construct two criteria to measure the correlation and stopband properties and then establish an unconstrained problem in the frequency domain. After deducing the phase gradient and the step size, an efficient gradient-based algorithm with monotonicity is proposed to minimize the objective function directly. For the design problem without considering the correlation weights, we develop a simplified algorithm, which only requires a few fast Fourier transform (FFT) operations and is more efficient. Because both of the algorithms can be implemented via the FFT operations and the Hadamard product, they are computationally efficient and can be used to design waveform sets with a large waveform number and waveform length. Numerical experiments show that the proposed algorithms can provide better performance than the state-of-the-art algorithms in terms of the computational complexity.

State of the art techniques for preservation and reuse of hard copy electrocardiograms.

PubMed

Lobodzinski, Suave M; Teppner, Ulrich; Laks, Michael

2003-01-01

Baseline examinations and periodic reexaminations in longitudinal population studies, together with ongoing surveillance for morbidity and mortality, provide unique opportunities for seeking ways to enhance the value of electrocardiography (ECG) as an inexpensive and noninvasive tool for prognosis and diagnosis. We used newly developed optical ECG waveform recognition (OEWR) technique capable of extracting raw waveform data from legacy hard copy ECG recording. Hardcopy ECG recordings were scanned and processed by the OEWR algorithm. The extracted ECG datasets were formatted into a newly proposed, vendor-neutral, ECG XML data format. Oracle database was used as a repository for ECG records in XML format. The proposed technique for XML encapsulation of OEWR processed hard copy records resulted in an efficient method for inclusion of paper ECG records into research databases, thus providing their preservation, reuse and accession.

Classification and machine recognition of severe weather patterns

NASA Technical Reports Server (NTRS)

Wang, P. P.; Burns, R. C.

1976-01-01

Forecasting and warning of severe weather conditions are treated from the vantage point of pattern recognition by machine. Pictorial patterns and waveform patterns are distinguished. Time series data on sferics are dealt with by considering waveform patterns. A severe storm patterns recognition machine is described, along with schemes for detection via cross-correlation of time series (same channel or different channels). Syntactic and decision-theoretic approaches to feature extraction are discussed. Active and decayed tornados and thunderstorms, lightning discharges, and funnels and their related time series data are studied.

[The extraction and analysis of a- and b- wave from electroretinogram in human].

PubMed

Chen, Zi-he; Zheng, Chang-wei; Lei, Bo

2013-12-01

To determine the frequency range of a-b wave complex in the dark- and light-adapted electroretinogram (ERG) and to isolate the pure a- and b- waves. Case series study. Full-field ERGs were recorded in 16 eyes of 8 normal volunteers from October to November 2011. Digital filtering technique was used to extract the a- and b-waves from dark- and light-adapted ERG responses. The timings of a- and b-wave were measured to determine the frequency range of a-b wave complex. Major frequency components were determined from power spectra using fast Fourier transform (FFT). The effect of different order settings in the digital filter were compared to investigate the optimum condition, where the oscillatory potential (OP) was completely removed while the amplitudes and phases of the a- and b- waves were less affected. The Student-t test was used to compare the frequency range of a-b wave complex in dark- and light-adapted ERG. The averaged frequency range of the dark-adapted a-b wave complex was from (14.99 ± 2.39) to (25.35 ± 3.77) Hz, compared with (25.22 ± 6.56) to (32.47 ± 3.68) Hz for the light-adapted a-b wave complex, respectively, indicating the frequency range of the dark-adapted a-b wave complex was significantly less than the light-adapted a-b wave complex (t = 7.910, 7.693; both P < 0.01). The third order of the digital filter and a passband of 1 to 45 Hz was the best choice in term of removing the high frequency OP from the waveform of ERG and keeping the amplitude and phase of the a- and b- waves. The frequency of a-b wave complex is lower than that of OP. Therefore the a- and b- waves can be isolated from OP using different digital filter settings in human ERG. A third order and a passband of 1 to 45 Hz is the best choice to extract pure a- and b- waves from the original ERG.

Development of a low-frequency physiotherapeutic device for diabetes manipulated by microcontroller.

PubMed

Guo, Jin-Song; Gong, Jian

2001-01-01

OBJECTIVE: To develop a physiotherapeutic device for diabetes that generates special low-frequency waveform manipulated by a microcontroller. METHODS: A microcontoller and a digital-to-analog converter were utilized along with a keyboard and LED display circuit, to generate desired low-frequecy waveform with the assistance of a software. RESULTS: The complex waveform generated by this device met the demands for diabetes physiotherapy, and the frequency and amplitude could be freely adjusted. CONCLUSIONS: The utilization of a digital-to-analog converter controlled by a microcontroller can very well serve the purpose of a low-frequency physiotherapy for diabetes.

Sparsity Aware Adaptive Radar Sensor Imaging in Complex Scattering Environments

DTIC Science & Technology

2015-06-15

while meeting the requirement on the peak to average power ratio. Third, we study impact of waveform encoding on nonlinear electromagnetic tomographic...Enyue Lu. Time Domain Electromagnetic Tomography Using Propagation and Backpropagation Method, IEEE International Conference on Image Processing...Received Paper 3.00 4.00 Yuanwei Jin, Chengdon Dong, Enyue Lu. Waveform Encoding for Nonlinear Electromagnetic Tomographic Imaging, IEEE Global

Development of a Software-Defined Radar

DTIC Science & Technology

2017-10-01

waveform to the widest available (unoccupied) instantaneous bandwidth in real time. Consequently, the radar range resolution and target detection are...LabVIEW The matched filter range profile is calculated in real time using fast Fourier transform (FFT) operations to perform a cross-correlation...between the transmitted waveform and the received complex data. Figure 4 demonstrates the block logic used to achieve real -time range profile

Multi-input multioutput orthogonal frequency division multiplexing radar waveform design for improving the detection performance of space-time adaptive processing

NASA Astrophysics Data System (ADS)

Wang, Hongyan

2017-04-01

This paper addresses the waveform optimization problem for improving the detection performance of multi-input multioutput (MIMO) orthogonal frequency division multiplexing (OFDM) radar-based space-time adaptive processing (STAP) in the complex environment. By maximizing the output signal-to-interference-and-noise-ratio (SINR) criterion, the waveform optimization problem for improving the detection performance of STAP, which is subjected to the constant modulus constraint, is derived. To tackle the resultant nonlinear and complicated optimization issue, a diagonal loading-based method is proposed to reformulate the issue as a semidefinite programming one; thereby, this problem can be solved very efficiently. In what follows, the optimized waveform can be obtained to maximize the output SINR of MIMO-OFDM such that the detection performance of STAP can be improved. The simulation results show that the proposed method can improve the output SINR detection performance considerably as compared with that of uncorrelated waveforms and the existing MIMO-based STAP method.

Automatic cardiac cycle determination directly from EEG-fMRI data by multi-scale peak detection method.

PubMed

Wong, Chung-Ki; Luo, Qingfei; Zotev, Vadim; Phillips, Raquel; Chan, Kam Wai Clifford; Bodurka, Jerzy

2018-03-31

In simultaneous EEG-fMRI, identification of the period of cardioballistic artifact (BCG) in EEG is required for the artifact removal. Recording the electrocardiogram (ECG) waveform during fMRI is difficult, often causing inaccurate period detection. Since the waveform of the BCG extracted by independent component analysis (ICA) is relatively invariable compared to the ECG waveform, we propose a multiple-scale peak-detection algorithm to determine the BCG cycle directly from the EEG data. The algorithm first extracts the high contrast BCG component from the EEG data by ICA. The BCG cycle is then estimated by band-pass filtering the component around the fundamental frequency identified from its energy spectral density, and the peak of BCG artifact occurrence is selected from each of the estimated cycle. The algorithm is shown to achieve a high accuracy on a large EEG-fMRI dataset. It is also adaptive to various heart rates without the needs of adjusting the threshold parameters. The cycle detection remains accurate with the scan duration reduced to half a minute. Additionally, the algorithm gives a figure of merit to evaluate the reliability of the detection accuracy. The algorithm is shown to give a higher detection accuracy than the commonly used cycle detection algorithm fmrib_qrsdetect implemented in EEGLAB. The achieved high cycle detection accuracy of our algorithm without using the ECG waveforms makes possible to create and automate pipelines for processing large EEG-fMRI datasets, and virtually eliminates the need for ECG recordings for BCG artifact removal. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Compression strategies for LiDAR waveform cube

NASA Astrophysics Data System (ADS)

Jóźków, Grzegorz; Toth, Charles; Quirk, Mihaela; Grejner-Brzezinska, Dorota

2015-01-01

Full-waveform LiDAR data (FWD) provide a wealth of information about the shape and materials of the surveyed areas. Unlike discrete data that retains only a few strong returns, FWD generally keeps the whole signal, at all times, regardless of the signal intensity. Hence, FWD will have an increasingly well-deserved role in mapping and beyond, in the much desired classification in the raw data format. Full-waveform systems currently perform only the recording of the waveform data at the acquisition stage; the return extraction is mostly deferred to post-processing. Although the full waveform preserves most of the details of the real data, it presents a serious practical challenge for a wide use: much larger datasets compared to those from the classical discrete return systems. Atop the need for more storage space, the acquisition speed of the FWD may also limit the pulse rate on most systems that cannot store data fast enough, and thus, reduces the perceived system performance. This work introduces a waveform cube model to compress waveforms in selected subsets of the cube, aimed at achieving decreased storage while maintaining the maximum pulse rate of FWD systems. In our experiments, the waveform cube is compressed using classical methods for 2D imagery that are further tested to assess the feasibility of the proposed solution. The spatial distribution of airborne waveform data is irregular; however, the manner of the FWD acquisition allows the organization of the waveforms in a regular 3D structure similar to familiar multi-component imagery, as those of hyper-spectral cubes or 3D volumetric tomography scans. This study presents the performance analysis of several lossy compression methods applied to the LiDAR waveform cube, including JPEG-1, JPEG-2000, and PCA-based techniques. Wide ranges of tests performed on real airborne datasets have demonstrated the benefits of the JPEG-2000 Standard where high compression rates incur fairly small data degradation. In addition, the JPEG-2000 Standard-compliant compression implementation can be fast and, thus, used in real-time systems, as compressed data sequences can be formed progressively during the waveform data collection. We conclude from our experiments that 2D image compression strategies are feasible and efficient approaches, thus they might be applied during the acquisition of the FWD sensors.

Spectral Cauchy characteristic extraction of strain, news and gravitational radiation flux

NASA Astrophysics Data System (ADS)

Handmer, Casey J.; Szilágyi, Béla; Winicour, Jeffrey

2016-11-01

We present a new approach for the Cauchy-characteristic extraction (CCE) of gravitational radiation strain, news function, and the flux of the energy-momentum, supermomentum and angular momentum associated with the Bondi-Metzner-Sachs asymptotic symmetries. In CCE, a characteristic evolution code takes numerical data on an inner worldtube supplied by a Cauchy evolution code, and propagates it outwards to obtain the space-time metric in a neighborhood of null infinity. The metric is first determined in a scrambled form in terms of coordinates determined by the Cauchy formalism. In prior treatments, the waveform is first extracted from this metric and then transformed into an asymptotic inertial coordinate system. This procedure provides the physically proper description of the waveform and the radiated energy but it does not generalize to determine the flux of angular momentum or supermomentum. Here we formulate and implement a new approach which transforms the full metric into an asymptotic inertial frame and provides a uniform treatment of all the radiation fluxes associated with the asymptotic symmetries. Computations are performed and calibrated using the spectral Einstein code.

Arbitrary magnetic field gradient waveform correction using an impulse response based pre-equalization technique.

PubMed

Goora, Frédéric G; Colpitts, Bruce G; Balcom, Bruce J

2014-01-01

The time-varying magnetic fields used in magnetic resonance applications result in the induction of eddy currents on conductive structures in the vicinity of both the sample under investigation and the gradient coils. These eddy currents typically result in undesired degradations of image quality for MRI applications. Their ubiquitous nature has resulted in the development of various approaches to characterize and minimize their impact on image quality. This paper outlines a method that utilizes the magnetic field gradient waveform monitor method to directly measure the temporal evolution of the magnetic field gradient from a step-like input function and extracts the system impulse response. With the basic assumption that the gradient system is sufficiently linear and time invariant to permit system theory analysis, the impulse response is used to determine a pre-equalized (optimized) input waveform that provides a desired gradient response at the output of the system. An algorithm has been developed that calculates a pre-equalized waveform that may be accurately reproduced by the amplifier (is physically realizable) and accounts for system limitations including system bandwidth, amplifier slew rate capabilities, and noise inherent in the initial measurement. Significant improvements in magnetic field gradient waveform fidelity after pre-equalization have been realized and are summarized. Copyright © 2013 Elsevier Inc. All rights reserved.

Development of a glottal area index that integrates glottal gap size and open quotient

PubMed Central

Chen, Gang; Kreiman, Jody; Gerratt, Bruce R.; Neubauer, Juergen; Shue, Yen-Liang; Alwan, Abeer

2013-01-01

Because voice signals result from vocal fold vibration, perceptually meaningful vibratory measures should quantify those aspects of vibration that correspond to differences in voice quality. In this study, glottal area waveforms were extracted from high-speed videoendoscopy of the vocal folds. Principal component analysis was applied to these waveforms to investigate the factors that vary with voice quality. Results showed that the first principal component derived from tokens without glottal gaps was significantly (p < 0.01) associated with the open quotient (OQ). The alternating-current (AC) measure had a significant effect (p < 0.01) on the first principal component among tokens exhibiting glottal gaps. A measure AC/OQ, defined as the ratio of AC to OQ, was proposed to combine both amplitude and temporal characteristics of the glottal area waveform for both complete and incomplete glottal closures. Analyses of “glide” phonations in which quality varied continuously from breathy to pressed showed that the AC/OQ measure was able to characterize the corresponding continuum of glottal area waveform variation, regardless of the presence or absence of glottal gaps. PMID:23464035

Interaural time sensitivity of high-frequency neurons in the inferior colliculus.

PubMed

Yin, T C; Kuwada, S; Sujaku, Y

1984-11-01

Recent psychoacoustic experiments have shown that interaural time differences provide adequate cues for lateralizing high-frequency sounds, provided the stimuli are complex and not pure tones. We present here physiological evidence in support of these findings. Neurons of high best frequency in the cat inferior colliculus respond to interaural phase differences of amplitude modulated waveforms, and this response depends upon preservation of phase information of the modulating signal. Interaural phase differences were introduced in two ways: by interaural delays of the entire waveform and by binaural beats in which there was an interaural frequency difference in the modulating waveform. Results obtained with these two methods are similar. Our results show that high-frequency cells can respond to interaural time differences of amplitude modulated signals and that they do so by a sensitivity to interaural phase differences of the modulating waveform.

An event database for rotational seismology

NASA Astrophysics Data System (ADS)

Salvermoser, Johannes; Hadziioannou, Celine; Hable, Sarah; Chow, Bryant; Krischer, Lion; Wassermann, Joachim; Igel, Heiner

2016-04-01

The ring laser sensor (G-ring) located at Wettzell, Germany, routinely observes earthquake-induced rotational ground motions around a vertical axis since its installation in 2003. Here we present results from a recently installed event database which is the first that will provide ring laser event data in an open access format. Based on the GCMT event catalogue and some search criteria, seismograms from the ring laser and the collocated broadband seismometer are extracted and processed. The ObsPy-based processing scheme generates plots showing waveform fits between rotation rate and transverse acceleration and extracts characteristic wavefield parameters such as peak ground motions, noise levels, Love wave phase velocities and waveform coherence. For each event, these parameters are stored in a text file (json dictionary) which is easily readable and accessible on the website. The database contains >10000 events starting in 2007 (Mw>4.5). It is updated daily and therefore provides recent events at a time lag of max. 24 hours. The user interface allows to filter events for epoch, magnitude, and source area, whereupon the events are displayed on a zoomable world map. We investigate how well the rotational motions are compatible with the expectations from the surface wave magnitude scale. In addition, the website offers some python source code examples for downloading and processing the openly accessible waveforms.

Extracting Low-Frequency Information from Time Attenuation in Elastic Waveform Inversion

NASA Astrophysics Data System (ADS)

Guo, Xuebao; Liu, Hong; Shi, Ying; Wang, Weihong

2017-03-01

Low-frequency information is crucial for recovering background velocity, but the lack of low-frequency information in field data makes inversion impractical without accurate initial models. Laplace-Fourier domain waveform inversion can recover a smooth model from real data without low-frequency information, which can be used for subsequent inversion as an ideal starting model. In general, it also starts with low frequencies and includes higher frequencies at later inversion stages, while the difference is that its ultralow frequency information comes from the Laplace-Fourier domain. Meanwhile, a direct implementation of the Laplace-transformed wavefield using frequency domain inversion is also very convenient. However, because broad frequency bands are often used in the pure time domain waveform inversion, it is difficult to extract the wavefields dominated by low frequencies in this case. In this paper, low-frequency components are constructed by introducing time attenuation into the recorded residuals, and the rest of the method is identical to the traditional time domain inversion. Time windowing and frequency filtering are also applied to mitigate the ambiguity of the inverse problem. Therefore, we can start at low frequencies and to move to higher frequencies. The experiment shows that the proposed method can achieve a good inversion result in the presence of a linear initial model and records without low-frequency information.

Time-lapse seismic waveform inversion for monitoring near-surface microbubble injection

NASA Astrophysics Data System (ADS)

Kamei, R.; Jang, U.; Lumley, D. E.; Mouri, T.; Nakatsukasa, M.; Takanashi, M.

2016-12-01

Seismic monitoring of the Earth provides valuable information regarding the time-varying changes in subsurface physical properties that are caused by natural or man-made processes. However, the resulting changes in subsurface properties are often small both in terms of magnitude and spatial extent, leading to seismic data differences that are difficult to detect at typical non-repeatable noise levels. In order to better extract information from the time-lapse data, exploiting the full seismic waveform information can be critical, since detected amplitude or traveltime changes may be minimal. We explore methods of waveform inversion that estimate an optimal model of time-varying elastic parameters at the wavelength scale to fit the observed time-lapse seismic data with modelled waveforms based on numerical solutions of the wave equation. We apply acoustic waveform inversion to time-lapse cross-well monitoring surveys of 64-m well intervals, and estimate the velocity changes that occur during the injection of microbubble water into shallow unconsolidated Quaternary sediments in the Kanto basin of Japan at a depth of 25 m below the surface. Microbubble water is comprised of water infused with air bubbles of a diameter less than 0.1mm, and may be useful to improve resistance to ground liquefaction during major earthquakes. Monitoring the space-time distribution and physical properties of microbubble injection is therefore important to understanding the full potential of the technique. Repeated monitoring surveys (>10) reveal transient behaviours in waveforms during microbubble injection. Time-lapse waveform inversion detects changes in P-wave velocity of less than 1 percent, initially as velocity increases and subsequently as velocity decreases. The velocity changes are mainly imaged within a thin (1 m) layer between the injection and the receiver well, inferring the fluid-flow influence of the fluvial sediment depositional environment. The resulting velocity models fit the observed waveforms very well, supporting the validity of the estimated velocity changes. In order to further improve the estimation of velocity changes, we investigate the limitations of acoustic waveform inversion, and apply elastic waveform inversion to the time-lapse data set.

Optically activated switches for the generation of complex electrical waveforms with multigigahertz bandwidth

NASA Astrophysics Data System (ADS)

Skeldon, Mark D.; Okishev, Andrey V.; Letzring, Samuel A.; Donaldson, William R.; Green, Kenton; Seka, Wolf D.; Fuller, Lynn F.

1995-01-01

An electrical pulse-generation system using two optically activated Si photoconductive switches can generate shaped electrical pulses with multigigahertz bandwidth. The Si switches are activated by an optical pulse whose leading edge is steepened by stimulated Brillouin scattering (SBS) in CCl4. With the bandwidth generated by the SBS process, a laser having a 1- to 3-ns pulse width is used to generate electrical pulses with approximately 80-ps rise times (approximately 4-GHz bandwidth). Variable impedance microstrip lines are used to generate complex electrical waveforms that can be transferred to a matched load with minimal loss of bandwidth.

Extraction of AE events to estimate their b values under a triaxial compressive condition Examination using continuous broadband records

NASA Astrophysics Data System (ADS)

Yoneda, N.; Kawakata, H.; Hirano, S.; Yoshimitsu, N.; Takahashi, N.

2017-12-01

Seismic b values estimated in previous laboratory compressive tests had been utilized for natural earthquake studies. Randomly sampled enough number of events over a wide magnitude range are essential for accurate b value estimation. In former triaxial tests, PZTs had sensitivity only in a narrow frequency range. In addition, the recording system could not extract all signals because of mask times or threshold setting. Recently, Yoshimitsu et al. (2014) enabled to use broadband transducers under triaxial conditions and achieved to acquire waveforms continuously in several hours. With such a system, they estimated the seismic moment of AE at very small magnitude scale. We expected that their continuous broadband recording system made it possible to record much more AE with a wider magnitude range for credible b value estimation in a laboratory. In this study, we performed a compressive test under a higher confining pressure as an updated experiment of Yoshimitsu et al. (2014) and extracted an enough amount of AE. We prepared an intact cylindrical Westerly Granite sample, 100 mm long by 50 mm in diameter. We conducted a triaxial compressive test under a confining pressure of 50 MPa, at a room temperature with drying conditions. Seven broadband transducers (sensitive range; 100 kHz - 1,000 kHz) were located in different height, respectively. Besides, a PZT was mounted to transmit elastic waves for velocity estimation during the experiment. At first, we increased the confining pressure and then started the loading. We switched the load control method from the axial load control to the circumferential displacement one. After exceeding the peak stress, compressive stress was unloaded with a high speed and the sample was recovered. A potential fault was observed on the recovered sample surface. Waveform recording was continued throughout the test for more than 200 minutes. The result of extracting signals by an STA/LTA ratio method for the waveforms recorded by each transducer, we detected about 2,170,000 signals at the most and about 450,000 at the minimum. Recorded waveforms may also include the elastic waves from the PZT and electrical noises. To find the combination of the signals derived from the same event, we used the largest differences in travel times for all transducer pairs. Finally, we obtained about 450,000 combinations.

Event-related brain potentials preceding speech and nonspeech oral movements of varying complexity.

PubMed

Wohlert, A B

1993-10-01

Cortical preparation for movement is reflected in the readiness potential (RP) waveform preceding voluntary limb movements. In the case of oral movements, the RP may be affected by the complexity or linguistic nature of the tasks. In this experiment, EEG potentials before a nonspeech task (lip pursing), a speech-like task (lip rounding), and single word production were recorded from scalp electrodes placed at the cranial vertex (Cz) and over the left and right motor strips (C3' and C4'). Seven right-handed female subjects produced at least 70 repetitions of the three tasks, in each of five repeated sessions. EEG records were averaged with respect to EMG onset at the lip. The word task, as opposed to the other tasks, was associated with greater negative amplitude in the RP waveform at the vertex site. Differences between the waveforms recorded at the right- and left-hemisphere sites were insignificant. Although intersubject variability was high, individuals had relatively stable patterns of response across sessions. Results suggest that the RP recorded at the vertex site is sensitive to changes in task complexity. The RP did not reflect lateralized activity indicative of hemispheric dominance.

Advanced Waveform Simulation for Seismic Monitoring

DTIC Science & Technology

2008-09-01

velocity model. The method separates the main arrivals of the regional waveform into 5 windows: Pnl (vertical and radial components), Rayleigh (vertical and...ranges out to 10°, including extensive observations of crustal thinning and thickening and various Pnl complexities. Broadband modeling in 1D, 2D...existing models perform in predicting the various regional phases, Rayleigh waves, Love waves, and Pnl waves. Previous events from this Basin-and-Range

A radio-frequency sheath model for complex waveforms

NASA Astrophysics Data System (ADS)

Turner, M. M.; Chabert, P.

2014-04-01

Plasma sheaths driven by radio-frequency voltages occur in contexts ranging from plasma processing to magnetically confined fusion experiments. An analytical understanding of such sheaths is therefore important, both intrinsically and as an element in more elaborate theoretical structures. Radio-frequency sheaths are commonly excited by highly anharmonic waveforms, but no analytical model exists for this general case. We present a mathematically simple sheath model that is in good agreement with earlier models for single frequency excitation, yet can be solved for arbitrary excitation waveforms. As examples, we discuss dual-frequency and pulse-like waveforms. The model employs the ansatz that the time-averaged electron density is a constant fraction of the ion density. In the cases we discuss, the error introduced by this approximation is small, and in general it can be quantified through an internal consistency condition of the model. This simple and accurate model is likely to have wide application.

Time-domain full waveform inversion using instantaneous phase information with damping

NASA Astrophysics Data System (ADS)

Luo, Jingrui; Wu, Ru-Shan; Gao, Fuchun

2018-06-01

In time domain, the instantaneous phase can be obtained from the complex seismic trace using Hilbert transform. The instantaneous phase information has great potential in overcoming the local minima problem and improving the result of full waveform inversion. However, the phase wrapping problem, which comes from numerical calculation, prevents its application. In order to avoid the phase wrapping problem, we choose to use the exponential phase combined with the damping method, which gives instantaneous phase-based multi-stage inversion. We construct the objective functions based on the exponential instantaneous phase, and also derive the corresponding gradient operators. Conventional full waveform inversion and the instantaneous phase-based inversion are compared with numerical examples, which indicates that in the case without low frequency information in seismic data, our method is an effective and efficient approach for initial model construction for full waveform inversion.

Noninvasive iPhone Measurement of Left Ventricular Ejection Fraction Using Intrinsic Frequency Methodology.

PubMed

Pahlevan, Niema M; Rinderknecht, Derek G; Tavallali, Peyman; Razavi, Marianne; Tran, Thao T; Fong, Michael W; Kloner, Robert A; Csete, Marie; Gharib, Morteza

2017-07-01

The study is based on previously reported mathematical analysis of arterial waveform that extracts hidden oscillations in the waveform that we called intrinsic frequencies. The goal of this clinical study was to compare the accuracy of left ventricular ejection fraction derived from intrinsic frequencies noninvasively versus left ventricular ejection fraction obtained with cardiac MRI, the most accurate method for left ventricular ejection fraction measurement. After informed consent, in one visit, subjects underwent cardiac MRI examination and noninvasive capture of a carotid waveform using an iPhone camera (The waveform is captured using a custom app that constructs the waveform from skin displacement images during the cardiac cycle.). The waveform was analyzed using intrinsic frequency algorithm. Outpatient MRI facility. Adults able to undergo MRI were referred by local physicians or self-referred in response to local advertisement and included patients with heart failure with reduced ejection fraction diagnosed by a cardiologist. Standard cardiac MRI sequences were used, with periodic breath holding for image stabilization. To minimize motion artifact, the iPhone camera was held in a cradle over the carotid artery during iPhone measurements. Regardless of neck morphology, carotid waveforms were captured in all subjects, within seconds to minutes. Seventy-two patients were studied, ranging in age from 20 to 92 years old. The main endpoint of analysis was left ventricular ejection fraction; overall, the correlation between ejection fraction-iPhone and ejection fraction-MRI was 0.74 (r = 0.74; p < 0.0001; ejection fraction-MRI = 0.93 × [ejection fraction-iPhone] + 1.9). Analysis of carotid waveforms using intrinsic frequency methods can be used to document left ventricular ejection fraction with accuracy comparable with that of MRI. The measurements require no training to perform or interpret, no calibration, and can be repeated at the bedside to generate almost continuous analysis of left ventricular ejection fraction without arterial cannulation.

Wavefield complexity and stealth structures: Resolution constraints by wave physics

NASA Astrophysics Data System (ADS)

Nissen-Meyer, T.; Leng, K.

2017-12-01

Imaging the Earth's interior relies on understanding how waveforms encode information from heterogeneous multi-scale structure. This relation is given by elastodynamics, but forward modeling in the context of tomography primarily serves to deliver synthetic waveforms and gradients for the inversion procedure. While this is entirely appropriate, it depreciates a wealth of complementary inference that can be obtained from the complexity of the wavefield. Here, we are concerned with the imprint of realistic multi-scale Earth structure on the wavefield, and the question on the inherent physical resolution limit of structures encoded in seismograms. We identify parameter and scattering regimes where structures remain invisible as a function of seismic wavelength, structural multi-scale geometry, scattering strength, and propagation path. Ultimately, this will aid in interpreting tomographic images by acknowledging the scope of "forgotten" structures, and shall offer guidance for optimising the selection of seismic data for tomography. To do so, we use our novel 3D modeling method AxiSEM3D which tackles global wave propagation in visco-elastic, anisotropic 3D structures with undulating boundaries at unprecedented resolution and efficiency by exploiting the inherent azimuthal smoothness of wavefields via a coupled Fourier expansion-spectral-element approach. The method links computational cost to wavefield complexity and thereby lends itself well to exploring the relation between waveforms and structures. We will show various examples of multi-scale heterogeneities which appear or disappear in the waveform, and argue that the nature of the structural power spectrum plays a central role in this. We introduce the concept of wavefield learning to examine the true wavefield complexity for a complexity-dependent modeling framework and discriminate which scattering structures can be retrieved by surface measurements. This leads to the question of physical invisibility and the tomographic resolution limit, and offers insight as to why tomographic images still show stark differences for smaller-scale heterogeneities despite progress in modeling and data resolution. Finally, we give an outlook on how we expand this modeling framework towards an inversion procedure guided by wavefield complexity.

Waveform identification and retracking analyses of Jason-2 altimeter satellite data for improving sea surface height estimation in Southern Java Island Waters and Java Sea, Indonesia

NASA Astrophysics Data System (ADS)

Nababan, Bisman; Hakim, Muhammad R.; Panjaitan, James P.

2018-05-01

Indonesian waters containing many small islands and shallow waters leads to a less accurate of sea surface height (SSH) estimation from satellite altimetry. Little efforts are also given for the validation of SSH estimation from the satellite in Indonesian waters. The purpose of this research was to identify and retrack waveforms of Jason-2 altimeter satellite data in southern Java island waters and Java Sea using several retrackers and performed improvement percentage analyses for new SSH estimation. The study used data of the Sensor Geophysical Data Record type D (SGDR-D) of Jason-2 satellite altimeter of the year 2010 in the southern Java island waters and 2012-2014 in Java Sea. Waveform retracking analyses were conducted using several retrackers (Offset Center of Gravity, Ice, Threshold, and Improved Threshold) and examined using a world reference undulation geoid of EGM08 and Oceanic retracker. Result showed that shape and pattern of waveforms were varied in all passes, seasons, and locations specifically along the coastal regions. In general, non-Brownish and complex waveforms were identified along coastal region specifically within the distance of 0-10 km from the shoreline. In contrary, generally Brownish waveforms were found in offshore. However, Brownish waveform can also be found within coastal region and non-Brownish waveforms within offshore region. The results were also showed that the four retrackers produced a better SSH estimation in coastal region. However, there was no dominant retracker to improve the accuracy of the SSH estimate.

Reliable Real-time Calculation of Heart-rate Complexity in Critically Ill Patients Using Multiple Noisy Waveform Sources

DTIC Science & Technology

2014-01-01

systems Machine learning Automatic data processing 1 Introduction Heart-rate complexity (HRC) is a method of quantifying the amount of complex...5. Batchinsky AI, Skinner J, Necsoiu C, et al. New measures of heart-rate complexity: effect of chest trauma and hemorrhage. J Trauma. 2010;68:1178–85

Laplace-domain waveform modeling and inversion for the 3D acoustic-elastic coupled media

NASA Astrophysics Data System (ADS)

Shin, Jungkyun; Shin, Changsoo; Calandra, Henri

2016-06-01

Laplace-domain waveform inversion reconstructs long-wavelength subsurface models by using the zero-frequency component of damped seismic signals. Despite the computational advantages of Laplace-domain waveform inversion over conventional frequency-domain waveform inversion, an acoustic assumption and an iterative matrix solver have been used to invert 3D marine datasets to mitigate the intensive computing cost. In this study, we develop a Laplace-domain waveform modeling and inversion algorithm for 3D acoustic-elastic coupled media by using a parallel sparse direct solver library (MUltifrontal Massively Parallel Solver, MUMPS). We precisely simulate a real marine environment by coupling the 3D acoustic and elastic wave equations with the proper boundary condition at the fluid-solid interface. In addition, we can extract the elastic properties of the Earth below the sea bottom from the recorded acoustic pressure datasets. As a matrix solver, the parallel sparse direct solver is used to factorize the non-symmetric impedance matrix in a distributed memory architecture and rapidly solve the wave field for a number of shots by using the lower and upper matrix factors. Using both synthetic datasets and real datasets obtained by a 3D wide azimuth survey, the long-wavelength component of the P-wave and S-wave velocity models is reconstructed and the proposed modeling and inversion algorithm are verified. A cluster of 80 CPU cores is used for this study.

A 6 kV arbitrary waveform generator for the Tevatron Electron Lens

DOE PAGES

Pfeffer, H.; Saewert, G.

2011-11-09

This paper reports on a 6 kV modulator built and installed at Fermilab to drive the electron gun anode for the Tevatron Electron Lens (TEL). The TEL was built with the intention of shifting the individual (anti)proton bunch tunes to even out the tune spread among all 36 bunches with the desire of improving Tevatron integrated luminosity. This modulator is essentially a 6 kV arbitrary waveform generator that enables the TEL to define the electron beam intensity on a bunch-by-bunch basis. A voltage waveform is constructed having a 7 μs duration that corresponds to the tune shift requirements of amore » 12-bunch (anti)proton beam pulse train. This waveform is played out for any one or all three bunch trains in the Tevatron. The programmed waveform voltages transition to different levels at time intervals corresponding to the 395 ns bunch spacing. In addition, complex voltage waveforms can be played out at a sustained rate of 143 kHz over the full 6 kV output range. This paper describes the novel design of the inductive adder topology employing five transformers. It describes the design aspects that minimize switching losses for this multi-kilovolt, high repetition rate and high duty factor application.« less

GRAVITATIONAL WAVE EXTRACTION FROM AN INSPIRALING CONFIGURATION OF MERGING BLACK HOLES

NASA Technical Reports Server (NTRS)

Baker, John G.; Centrella, Joan; Dae-Il, Choi; Koppitz, Michael; van Meter, James

2005-01-01

We present new techniques for evolving binary black hole systems which allow the accurate determination of gravitational waveforms directly from the wave zone region of the numerical simulations. Rather than excising the black hole interiors, our approach follows the "puncture" treatment of black holes, but utilizing a new gauge condition which allows the black holes to move successfully through the computational domain. We apply these techniques to an inspiraling binary, modeling the radiation generated during the final plunge and ringdown. We demonstrate convergence of the waveforms and and good conservation of mass-energy, with just over 3% of the system s mass converted to gravitational radiation.

MINEMOTION3D: A new set of Programs for Predicting Ground Motion From Explosions in Complex 3D Media

NASA Astrophysics Data System (ADS)

Tibuleac, I. M.; Bonner, J. L.; Orrey, J. L.; Yang, X.

2004-12-01

Predicting ground motion from complicated mining explosions is important for mines developing new blasting programs in regions where vibrations must be kept below certain levels. Additionally, predicting ground motion from mining explosions in complex 3D media is important for moment estimation for nuclear test treaty monitoring. Both problems have been addressed under the development of a new series of numerical prediction programs called MINEMOTION3D including 1) Generalized Fourier Methods to generate Green's functions in 3D media for a moment tensor source implementation and 2) MineSeis3D, a program that simulates seismograms for delay-fired mining explosions with a linear relationship between signals from small size individual shots. To test the programs, local recordings (5 - 23 km) of three production shots at a mine in northern Minnesota were compared to synthetic waveforms in 3D media. A non-zero value of the moment tensor component M12 was considered, to introduce a horizontal spall component into the waveform synthesis when the Green's functions were generated for each model. Methods using seismic noise crosscorrelation for improved inter-element subsurface structure estimation were also evaluated. Comparison of the observed and synthetic waveforms shows promising results. The shape and arrival times of the normalized synthetic and observed waveforms are similar for most of the stations. The synthetic and observed waveform amplitude fit is best for the vertical components in the mean 3D model and worst for the transversal components. The observed effect of spall on the waveform spectra was weak in the case of fragmentation delay fired commercial explosions. Commercial applications of the code could provide data needed for designing explosions which do not exceed ground vibration requirements posed by the U.S. Department of the Interior, Office of Surface Mining.

Classifiers utilized to enhance acoustic based sensors to identify round types of artillery/mortar

NASA Astrophysics Data System (ADS)

Grasing, David; Desai, Sachi; Morcos, Amir

2008-04-01

Feature extraction methods based on the statistical analysis of the change in event pressure levels over a period and the level of ambient pressure excitation facilitate the development of a robust classification algorithm. The features reliably discriminates mortar and artillery variants via acoustic signals produced during the launch events. Utilizing acoustic sensors to exploit the sound waveform generated from the blast for the identification of mortar and artillery variants as type A, etcetera through analysis of the waveform. Distinct characteristics arise within the different mortar/artillery variants because varying HE mortar payloads and related charges emphasize varying size events at launch. The waveform holds various harmonic properties distinct to a given mortar/artillery variant that through advanced signal processing and data mining techniques can employed to classify a given type. The skewness and other statistical processing techniques are used to extract the predominant components from the acoustic signatures at ranges exceeding 3000m. Exploiting these techniques will help develop a feature set highly independent of range, providing discrimination based on acoustic elements of the blast wave. Highly reliable discrimination will be achieved with a feedforward neural network classifier trained on a feature space derived from the distribution of statistical coefficients, frequency spectrum, and higher frequency details found within different energy bands. The processes that are described herein extend current technologies, which emphasis acoustic sensor systems to provide such situational awareness.

Artillery/mortar type classification based on detected acoustic transients

NASA Astrophysics Data System (ADS)

Morcos, Amir; Grasing, David; Desai, Sachi

2008-04-01

Feature extraction methods based on the statistical analysis of the change in event pressure levels over a period and the level of ambient pressure excitation facilitate the development of a robust classification algorithm. The features reliably discriminates mortar and artillery variants via acoustic signals produced during the launch events. Utilizing acoustic sensors to exploit the sound waveform generated from the blast for the identification of mortar and artillery variants as type A, etcetera through analysis of the waveform. Distinct characteristics arise within the different mortar/artillery variants because varying HE mortar payloads and related charges emphasize varying size events at launch. The waveform holds various harmonic properties distinct to a given mortar/artillery variant that through advanced signal processing and data mining techniques can employed to classify a given type. The skewness and other statistical processing techniques are used to extract the predominant components from the acoustic signatures at ranges exceeding 3000m. Exploiting these techniques will help develop a feature set highly independent of range, providing discrimination based on acoustic elements of the blast wave. Highly reliable discrimination will be achieved with a feed-forward neural network classifier trained on a feature space derived from the distribution of statistical coefficients, frequency spectrum, and higher frequency details found within different energy bands. The processes that are described herein extend current technologies, which emphasis acoustic sensor systems to provide such situational awareness.

Artillery/mortar round type classification to increase system situational awareness

NASA Astrophysics Data System (ADS)

Desai, Sachi; Grasing, David; Morcos, Amir; Hohil, Myron

2008-04-01

Feature extraction methods based on the statistical analysis of the change in event pressure levels over a period and the level of ambient pressure excitation facilitate the development of a robust classification algorithm. The features reliably discriminates mortar and artillery variants via acoustic signals produced during the launch events. Utilizing acoustic sensors to exploit the sound waveform generated from the blast for the identification of mortar and artillery variants as type A, etcetera through analysis of the waveform. Distinct characteristics arise within the different mortar/artillery variants because varying HE mortar payloads and related charges emphasize varying size events at launch. The waveform holds various harmonic properties distinct to a given mortar/artillery variant that through advanced signal processing and data mining techniques can employed to classify a given type. The skewness and other statistical processing techniques are used to extract the predominant components from the acoustic signatures at ranges exceeding 3000m. Exploiting these techniques will help develop a feature set highly independent of range, providing discrimination based on acoustic elements of the blast wave. Highly reliable discrimination will be achieved with a feedforward neural network classifier trained on a feature space derived from the distribution of statistical coefficients, frequency spectrum, and higher frequency details found within different energy bands. The processes that are described herein extend current technologies, which emphasis acoustic sensor systems to provide such situational awareness.

The t-CWT: a new ERP detection and quantification method based on the continuous wavelet transform and Student's t-statistics.

PubMed

Bostanov, Vladimir; Kotchoubey, Boris

2006-12-01

This study was aimed at developing a method for extraction and assessment of event-related brain potentials (ERP) from single-trials. This method should be applicable in the assessment of single persons' ERPs and should be able to handle both single ERP components and whole waveforms. We adopted a recently developed ERP feature extraction method, the t-CWT, for the purposes of hypothesis testing in the statistical assessment of ERPs. The t-CWT is based on the continuous wavelet transform (CWT) and Student's t-statistics. The method was tested in two ERP paradigms, oddball and semantic priming, by assessing individual-participant data on a single-trial basis, and testing the significance of selected ERP components, P300 and N400, as well as of whole ERP waveforms. The t-CWT was also compared to other univariate and multivariate ERP assessment methods: peak picking, area computation, discrete wavelet transform (DWT) and principal component analysis (PCA). The t-CWT produced better results than all of the other assessment methods it was compared with. The t-CWT can be used as a reliable and powerful method for ERP-component detection and testing of statistical hypotheses concerning both single ERP components and whole waveforms extracted from either single persons' or group data. The t-CWT is the first such method based explicitly on the criteria of maximal statistical difference between two average ERPs in the time-frequency domain and is particularly suitable for ERP assessment of individual data (e.g. in clinical settings), but also for the investigation of small and/or novel ERP effects from group data.

Complexity of intracranial pressure correlates with outcome after traumatic brain injury

PubMed Central

Lu, Cheng-Wei; Czosnyka, Marek; Shieh, Jiann-Shing; Smielewska, Anna; Pickard, John D.

2012-01-01

This study applied multiscale entropy analysis to investigate the correlation between the complexity of intracranial pressure waveform and outcome after traumatic brain injury. Intracranial pressure and arterial blood pressure waveforms were low-pass filtered to remove the respiratory and pulse components and then processed using a multiscale entropy algorithm to produce a complexity index. We identified significant differences across groups classified by the Glasgow Outcome Scale in intracranial pressure, pressure-reactivity index and complexity index of intracranial pressure (P < 0.0001; P = 0.001; P < 0.0001, respectively). Outcome was dichotomized as survival/death and also as favourable/unfavourable. The complexity index of intracranial pressure achieved the strongest statistical significance (F = 28.7; P < 0.0001 and F = 17.21; P < 0.0001, respectively) and was identified as a significant independent predictor of mortality and favourable outcome in a multivariable logistic regression model (P < 0.0001). The results of this study suggest that complexity of intracranial pressure assessed by multiscale entropy was significantly associated with outcome in patients with brain injury. PMID:22734128

Bayesian decoding using unsorted spikes in the rat hippocampus

PubMed Central

Layton, Stuart P.; Chen, Zhe; Wilson, Matthew A.

2013-01-01

A fundamental task in neuroscience is to understand how neural ensembles represent information. Population decoding is a useful tool to extract information from neuronal populations based on the ensemble spiking activity. We propose a novel Bayesian decoding paradigm to decode unsorted spikes in the rat hippocampus. Our approach uses a direct mapping between spike waveform features and covariates of interest and avoids accumulation of spike sorting errors. Our decoding paradigm is nonparametric, encoding model-free for representing stimuli, and extracts information from all available spikes and their waveform features. We apply the proposed Bayesian decoding algorithm to a position reconstruction task for freely behaving rats based on tetrode recordings of rat hippocampal neuronal activity. Our detailed decoding analyses demonstrate that our approach is efficient and better utilizes the available information in the nonsortable hash than the standard sorting-based decoding algorithm. Our approach can be adapted to an online encoding/decoding framework for applications that require real-time decoding, such as brain-machine interfaces. PMID:24089403

Onboard Processing on PWE OFA/WFC (Onboard Frequency Analyzer/Waveform Capture) aboard the ERG (ARASE) Satellite

NASA Astrophysics Data System (ADS)

Matsuda, S.; Kasahara, Y.; Kojima, H.; Kasaba, Y.; Yagitani, S.; Ozaki, M.; Imachi, T.; Ishisaka, K.; Kurita, S.; Ota, M.; Kumamoto, A.; Tsuchiya, F.; Yoshizumi, M.; Matsuoka, A.; Teramoto, M.; Shinohara, I.

2017-12-01

Exploration of energization and Radiation in Geospace (ERG) is a mission for understanding particle acceleration, loss mechanisms, and the dynamic evolution of space storms in the context of cross-energy and cross-regional coupling [Miyoshi et al., 2012]. The ERG (ARASE) satellite was launched on December 20, 2016, and successfully inserted into an orbit. The Plasma Wave Experiment (PWE) is one of the science instruments on board the ERG satellite to measure electric field and magnetic field in the inner magnetosphere. PWE consists of three sub-components, EFD (Electric Field Detector), OFA/WFC (Onboard Frequency Analyzer and Waveform Capture), and HFA (High Frequency Analyzer). Especially, OFA/WFC measures electric and magnetic field spectrum and waveform from a few Hz to 20 kHz. OFA/WFC processes signals detected by a couple of dipole wire-probe antenna (WPT) and tri-axis magnetic search coils (MSC) installed onboard the satellite. The PWE-OFA subsystem calculates and produces three kind of data; OFA-SPEC (power spectrum), OFA-MATRIX (spectrum matrix), and OFA-COMPLEX (complex spectrum). They are continuously processed 24 hours per day and all data are sent to the ground. OFA-MATRIX and OFA-COMPLEX are used for polarization analyses and direction finding of the plasma waves. The PWE-WFC subsystem measures raw (64 kHz sampled) and down-sampled (1 kHz sampled) burst waveform detected by the WPT and the MSC sensors. It activates by a command, automatic triggering, and scheduling. The initial check-out process of the PWE successfully completed, and initial data has been obtained. In this presentation, we introduce onboard processing technique on PWE OFA/WFC and its initial results.

Topographic effects on infrasound propagation.

PubMed

McKenna, Mihan H; Gibson, Robert G; Walker, Bob E; McKenna, Jason; Winslow, Nathan W; Kofford, Aaron S

2012-01-01

Infrasound data were collected using portable arrays in a region of variable terrain elevation to quantify the effects of topography on observed signal amplitude and waveform features at distances less than 25 km from partially contained explosive sources during the Frozen Rock Experiment (FRE) in 2006. Observed infrasound signals varied in amplitude and waveform complexity, indicating propagation effects that are due in part to repeated local maxima and minima in the topography on the scale of the dominant wavelengths of the observed data. Numerical simulations using an empirically derived pressure source function combining published FRE accelerometer data and historical data from Project ESSEX, a time-domain parabolic equation model that accounted for local terrain elevation through terrain-masking, and local meteorological atmospheric profiles were able to explain some but not all of the observed signal features. Specifically, the simulations matched the timing of the observed infrasound signals but underestimated the waveform amplitude observed behind terrain features, suggesting complex scattering and absorption of energy associated with variable topography influences infrasonic energy more than previously observed. © 2012 Acoustical Society of America.

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

Pfeffer, H.; Saewert, G.

This paper reports on a 6 kV modulator built and installed at Fermilab to drive the electron gun anode for the Tevatron Electron Lens (TEL). The TEL was built with the intention of shifting the individual (anti)proton bunch tunes to even out the tune spread among all 36 bunches with the desire of improving Tevatron integrated luminosity. This modulator is essentially a 6 kV arbitrary waveform generator that enables the TEL to define the electron beam intensity on a bunch-by-bunch basis. A voltage waveform is constructed having a 7 μs duration that corresponds to the tune shift requirements of amore » 12-bunch (anti)proton beam pulse train. This waveform is played out for any one or all three bunch trains in the Tevatron. The programmed waveform voltages transition to different levels at time intervals corresponding to the 395 ns bunch spacing. In addition, complex voltage waveforms can be played out at a sustained rate of 143 kHz over the full 6 kV output range. This paper describes the novel design of the inductive adder topology employing five transformers. It describes the design aspects that minimize switching losses for this multi-kilovolt, high repetition rate and high duty factor application.« less

Extracting equation of state parameters from black hole-neutron star mergers: Aligned-spin black holes and a preliminary waveform model

NASA Astrophysics Data System (ADS)

Lackey, Benjamin D.; Kyutoku, Koutarou; Shibata, Masaru; Brady, Patrick R.; Friedman, John L.

2014-02-01

Information about the neutron-star equation of state is encoded in the waveform of a black hole-neutron star system through tidal interactions and the possible tidal disruption of the neutron star. During the inspiral this information depends on the tidal deformability Λ of the neutron star, and we find that the best-measured parameter during the merger and ringdown is consistent with Λ as well. We performed 134 simulations where we systematically varied the equation of state as well as the mass ratio, neutron star mass, and aligned spin of the black hole. Using these simulations we develop an analytic representation of the full inspiral-merger-ringdown waveform calibrated to these numerical waveforms; we use this analytic waveform and a Fisher matrix analysis to estimate the accuracy to which Λ can be measured with gravitational-wave detectors. We find that although the inspiral tidal signal is small, coherently combining this signal with the merger-ringdown matter effect improves the measurability of Λ by a factor of ˜3 over using just the merger-ringdown matter effect alone. However, incorporating correlations between all the waveform parameters then decreases the measurability of Λ by a factor of ˜3. The uncertainty in Λ increases with the mass ratio, but decreases as the black hole spin increases. Overall, a single Advanced LIGO detector can only marginally measure Λ for mass ratios Q =2-5, black hole spins JBH/MBH2=-0.5-0.75, and neutron star masses MNS=1.2M⊙-1.45M⊙ at an optimally oriented distance of 100 Mpc. For the proposed Einstein Telescope, however, the uncertainty in Λ is an order of magnitude smaller.

Satellite altimetry in sea ice regions - detecting open water for estimating sea surface heights

NASA Astrophysics Data System (ADS)

Müller, Felix L.; Dettmering, Denise; Bosch, Wolfgang

2017-04-01

The Greenland Sea and the Farm Strait are transporting sea ice from the central Arctic ocean southwards. They are covered by a dynamic changing sea ice layer with significant influences on the Earth climate system. Between the sea ice there exist various sized open water areas known as leads, straight lined open water areas, and polynyas exhibiting a circular shape. Identifying these leads by satellite altimetry enables the extraction of sea surface height information. Analyzing the radar echoes, also called waveforms, provides information on the surface backscatter characteristics. For example waveforms reflected by calm water have a very narrow and single-peaked shape. Waveforms reflected by sea ice show more variability due to diffuse scattering. Here we analyze altimeter waveforms from different conventional pulse-limited satellite altimeters to separate open water and sea ice waveforms. An unsupervised classification approach employing partitional clustering algorithms such as K-medoids and memory-based classification methods such as K-nearest neighbor is used. The classification is based on six parameters derived from the waveform's shape, for example the maximum power or the peak's width. The open-water detection is quantitatively compared to SAR images processed while accounting for sea ice motion. The classification results are used to derive information about the temporal evolution of sea ice extent and sea surface heights. They allow to provide evidence on climate change relevant influences as for example Arctic sea level rise due to enhanced melting rates of Greenland's glaciers and an increasing fresh water influx into the Arctic ocean. Additionally, the sea ice cover extent analyzed over a long-time period provides an important indicator for a globally changing climate system.

Determination of acrylamide and acrylic acid by isocratic liquid chromatography with pulsed electrochemical detection.

PubMed

Casella, Innocenzo G; Pierri, Marianna; Contursi, Michela

2006-02-24

The electrochemical behaviour of the polycrystalline platinum electrode towards the oxidation/reduction of short-chain unsaturated aliphatic molecules such as acrylamide and acrylic acid was investigated in acidic solutions. Analytes were separated by reverse phase liquid chromatographic and quantified using a pulsed amperometric detection. A new two-step waveform, is introduced for detection of acrylamide and acrylic acid. Detection limits (LOD) of 20 nM (1. 4 microg/kg) and 45 nM (3.2 microg/kg) were determined in water solutions containing acrylamide and acrylic acid, respectively. Compared to the classical three-step waveform, the proposed two-step waveform shows favourable analytical performance in terms of LOD, linear range, precision and improved long-term reproducibility. The proposed analytical method combined with clean-up procedure accomplished by Carrez clearing reagent and subsequent extraction with a strong cation exchanger cartridges (SPE), was successfully used for the quantification of low concentrations of acrylamide in foodstuffs such as coffee and potato fries.

Evaluation of Waveform Structure Features on Time Domain Target Recognition under Cross Polarization

NASA Astrophysics Data System (ADS)

Selver, M. A.; Seçmen, M.; Zoral, E. Y.

2016-08-01

Classification of aircraft targets from scattered electromagnetic waves is a challenging application, which suffers from aspect angle dependency. In order to eliminate the adverse effects of aspect angle, various strategies were developed including the techniques that rely on extraction of several features and design of suitable classification systems to process them. Recently, a hierarchical method, which uses features that take advantage of waveform structure of the scattered signals, is introduced and shown to have effective results. However, this approach has been applied to the special cases that consider only a single planar component of electric field that cause no-cross polarization at the observation point. In this study, two small scale aircraft models, Boeing-747 and DC-10, are selected as the targets and various polarizations are used to analyse the cross-polarization effects on system performance of the aforementioned method. The results reveal the advantages and the shortcomings of using waveform structures in time-domain target identification.

On estimating the phase of a periodic waveform in additive Gaussian noise, part 3

NASA Technical Reports Server (NTRS)

Rauch, L. L.

1991-01-01

Motivated by advances in signal processing technology that support more complex algorithms, researchers have taken a new look at the problem of estimating the phase and other parameters of a nearly periodic waveform in additive Gaussian noise, based on observation during a given time interval. Parts 1 and 2 are very briefly reviewed. In part 3, the actual performances of some of the highly nonlinear estimation algorithms of parts 1 and 2 are evaluated by numerical simulation using Monte Carlo techniques.

Extraction of ECG signal with adaptive filter for hearth abnormalities detection

NASA Astrophysics Data System (ADS)

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.

The shallow elastic structure of the lunar crust: New insights from seismic wavefield gradient analysis

NASA Astrophysics Data System (ADS)

Sollberger, David; Schmelzbach, Cedric; Robertsson, Johan O. A.; Greenhalgh, Stewart A.; Nakamura, Yosio; Khan, Amir

2016-10-01

Enigmatic lunar seismograms recorded during the Apollo 17 mission in 1972 have so far precluded the identification of shear-wave arrivals and hence the construction of a comprehensive elastic model of the shallow lunar subsurface. Here, for the first time, we extract shear-wave information from the Apollo active seismic data using a novel waveform analysis technique based on spatial seismic wavefield gradients. The star-like recording geometry of the active seismic experiment lends itself surprisingly well to compute spatial wavefield gradients and rotational ground motion as a function of time. These observables, which are new to seismic exploration in general, allowed us to identify shear waves in the complex lunar seismograms, and to derive a new model of seismic compressional and shear-wave velocities in the shallow lunar crust, critical to understand its lithology and constitution, and its impact on other geophysical investigations of the Moon's deep interior.

Mismatch Negativity with Visual-only and Audiovisual Speech

PubMed Central

Ponton, Curtis W.; Bernstein, Lynne E.; Auer, Edward T.

2009-01-01

The functional organization of cortical speech processing is thought to be hierarchical, increasing in complexity and proceeding from primary sensory areas centrifugally. The current study used the mismatch negativity (MMN) obtained with electrophysiology (EEG) to investigate the early latency period of visual speech processing under both visual-only (VO) and audiovisual (AV) conditions. Current density reconstruction (CDR) methods were used to model the cortical MMN generator locations. MMNs were obtained with VO and AV speech stimuli at early latencies (approximately 82-87 ms peak in time waveforms relative to the acoustic onset) and in regions of the right lateral temporal and parietal cortices. Latencies were consistent with bottom-up processing of the visible stimuli. We suggest that a visual pathway extracts phonetic cues from visible speech, and that previously reported effects of AV speech in classical early auditory areas, given later reported latencies, could be attributable to modulatory feedback from visual phonetic processing. PMID:19404730

Large Footprint LiDAR Data Processing for Ground Detection and Biomass Estimation

NASA Astrophysics Data System (ADS)

Zhuang, Wei

Ground detection in large footprint waveform Light Detection And Ranging (LiDAR) data is important in calculating and estimating downstream products, especially in forestry applications. For example, tree heights are calculated as the difference between the ground peak and first returned signal in a waveform. Forest attributes, such as aboveground biomass, are estimated based on the tree heights. This dissertation investigated new metrics and algorithms for estimating aboveground biomass and extracting ground peak location in large footprint waveform LiDAR data. In the first manuscript, an accurate and computationally efficient algorithm, named Filtering and Clustering Algorithm (FICA), was developed based on a set of multiscale second derivative filters for automatically detecting the ground peak in an waveform from Land, Vegetation and Ice Sensor. Compared to existing ground peak identification algorithms, FICA was tested in different land cover type plots and showed improved accuracy in ground detections of the vegetation plots and similar accuracy in developed area plots. Also, FICA adopted a peak identification strategy rather than following a curve-fitting process, and therefore, exhibited improved efficiency. In the second manuscript, an algorithm was developed specifically for shrub waveforms. The algorithm only partially fitted the shrub canopy reflection and detected the ground peak by investigating the residual signal, which was generated by deducting a Gaussian fitting function from the raw waveform. After the deduction, the overlapping ground peak was identified as the local maximum of the residual signal. In addition, an applicability model was built for determining waveforms where the proposed PCF algorithm should be applied. In the third manuscript, a new set of metrics was developed to increase accuracy in biomass estimation models. The metrics were based on the results of Gaussian decomposition. They incorporated both waveform intensity represented by the area covered by a Gaussian function and its associated heights, which was the centroid of the Gaussian function. By considering signal reflection of different vegetation layers, the developed metrics obtained better estimation accuracy in aboveground biomass when compared to existing metrics. In addition, the new developed metrics showed strong correlation with other forest structural attributes, such as mean Diameter at Breast Height (DBH) and stem density. In sum, the dissertation investigated the various techniques for large footprint waveform LiDAR processing for detecting the ground peak and estimating biomass. The novel techniques developed in this dissertation showed better performance than existing methods or metrics.

Improving the Accuracy of Coastal Sea Surface Heights by Retracking Decontaminated Radar Altimetry Waveforms

NASA Astrophysics Data System (ADS)

Huang, Zhengkai; Wang, Haihong; Luo, Zhicai

2017-04-01

Due to the complex coastal topography and energetic ocean dynamics effect, the return echoes are contaminated while the satellite footprint approaches or leaves the coastline. Specular peaks are often induced in the trailing edges of contaminated waveforms, thus leading the error in the determination of the leading edge and associated track offset in the waveform retracking process. We propose an improved algorithm base on Tseng's modification method to decontaminated coastal (0-7 km from coastline) waveforms, thus improving both the utilization and precision of coastal sea surface height (SSH). Using the Envisat/Jason-2 SGDR data, the shortcoming of Tseng's method is pointed out and the novel algorithm is proposed by revising the strategy of selecting reference waveform and determining weight for removing outlier. The reference waveform of the decontaminated technology is closer to the real waveform of the offshore area, which avoids the over-modification problem of Tseng method. The sea-level measurements from tide gauge station and geoid height from EGM2008 model were used to validate the retracking strategy. Experimental results show that decontaminated waveform was more suitable than original and Tseng modified waveform and has uniform performance in both compare to the tide gauge and geoid. The retrieved altimetry data in the 0-1km and 1-7km coastal zone indicate that threshold retracker with decontaminated waveform have STD of 73.8cm and 33cm as compared with in situ gauge data,which correspond to 62.1% and 58% in precession compared to the unretracked altimetry measurements. The retracked SSHs are better in two coastal (0-1 km and 1-7km) zones, which have STD of 11.9cm and 22.7cm as compared with geoid height. Furthermore, the comparisons shows that the precision of decontaminated technology improve 0.3cm and 3.3cm than the best result of PISTACH product in coastal sea. This work is supported by the National Natural Science Foundation of China (Grant Nos. 41174020, 41174021, 41131067) and the open fund of Guangxi Key Laboratory of Spatial Information and Geometrics (Grant No. 15-140-07-26). Index Terms: retracking, Envisat, Jason-2, Coastal sea, decontamination.

Sound stream segregation: a neuromorphic approach to solve the “cocktail party problem” in real-time

PubMed Central

Thakur, Chetan Singh; Wang, Runchun M.; Afshar, Saeed; Hamilton, Tara J.; Tapson, Jonathan C.; Shamma, Shihab A.; van Schaik, André

2015-01-01

The human auditory system has the ability to segregate complex auditory scenes into a foreground component and a background, allowing us to listen to specific speech sounds from a mixture of sounds. Selective attention plays a crucial role in this process, colloquially known as the “cocktail party effect.” It has not been possible to build a machine that can emulate this human ability in real-time. Here, we have developed a framework for the implementation of a neuromorphic sound segregation algorithm in a Field Programmable Gate Array (FPGA). This algorithm is based on the principles of temporal coherence and uses an attention signal to separate a target sound stream from background noise. Temporal coherence implies that auditory features belonging to the same sound source are coherently modulated and evoke highly correlated neural response patterns. The basis for this form of sound segregation is that responses from pairs of channels that are strongly positively correlated belong to the same stream, while channels that are uncorrelated or anti-correlated belong to different streams. In our framework, we have used a neuromorphic cochlea as a frontend sound analyser to extract spatial information of the sound input, which then passes through band pass filters that extract the sound envelope at various modulation rates. Further stages include feature extraction and mask generation, which is finally used to reconstruct the targeted sound. Using sample tonal and speech mixtures, we show that our FPGA architecture is able to segregate sound sources in real-time. The accuracy of segregation is indicated by the high signal-to-noise ratio (SNR) of the segregated stream (90, 77, and 55 dB for simple tone, complex tone, and speech, respectively) as compared to the SNR of the mixture waveform (0 dB). This system may be easily extended for the segregation of complex speech signals, and may thus find various applications in electronic devices such as for sound segregation and speech recognition. PMID:26388721

Sound stream segregation: a neuromorphic approach to solve the "cocktail party problem" in real-time.

PubMed

Thakur, Chetan Singh; Wang, Runchun M; Afshar, Saeed; Hamilton, Tara J; Tapson, Jonathan C; Shamma, Shihab A; van Schaik, André

2015-01-01

The human auditory system has the ability to segregate complex auditory scenes into a foreground component and a background, allowing us to listen to specific speech sounds from a mixture of sounds. Selective attention plays a crucial role in this process, colloquially known as the "cocktail party effect." It has not been possible to build a machine that can emulate this human ability in real-time. Here, we have developed a framework for the implementation of a neuromorphic sound segregation algorithm in a Field Programmable Gate Array (FPGA). This algorithm is based on the principles of temporal coherence and uses an attention signal to separate a target sound stream from background noise. Temporal coherence implies that auditory features belonging to the same sound source are coherently modulated and evoke highly correlated neural response patterns. The basis for this form of sound segregation is that responses from pairs of channels that are strongly positively correlated belong to the same stream, while channels that are uncorrelated or anti-correlated belong to different streams. In our framework, we have used a neuromorphic cochlea as a frontend sound analyser to extract spatial information of the sound input, which then passes through band pass filters that extract the sound envelope at various modulation rates. Further stages include feature extraction and mask generation, which is finally used to reconstruct the targeted sound. Using sample tonal and speech mixtures, we show that our FPGA architecture is able to segregate sound sources in real-time. The accuracy of segregation is indicated by the high signal-to-noise ratio (SNR) of the segregated stream (90, 77, and 55 dB for simple tone, complex tone, and speech, respectively) as compared to the SNR of the mixture waveform (0 dB). This system may be easily extended for the segregation of complex speech signals, and may thus find various applications in electronic devices such as for sound segregation and speech recognition.

Analytic family of post-merger template waveforms

NASA Astrophysics Data System (ADS)

Del Pozzo, Walter; Nagar, Alessandro

2017-06-01

Building on the analytical description of the post-merger (ringdown) waveform of coalescing, nonprecessing, spinning binary black holes introduced by Damour and Nagar [Phys. Rev. D 90, 024054 (2014), 10.1103/PhysRevD.90.024054], we propose an analytic, closed form, time-domain, representation of the ℓ=m =2 gravitational radiation mode emitted after merger. This expression is given as a function of the component masses and dimensionless spins (m1 ,2,χ1 ,2) of the two inspiraling objects, as well as of the mass MBH and (complex) frequency σ1 of the fundamental quasinormal mode of the remnant black hole. Our proposed template is obtained by fitting the post-merger waveform part of several publicly available numerical relativity simulations from the Simulating eXtreme Spacetimes (SXS) catalog and then suitably interpolating over (symmetric) mass ratio and spins. We show that this analytic expression accurately reproduces (˜0.01 rad ) the phasing of the post-merger data of other data sets not used in its construction. This is notably the case of the spin-aligned run SXS:BBH:0305, whose intrinsic parameters are consistent with the 90% credible intervals reported in the parameter-estimation followup of GW150914 by B.P. Abbott et al. [Phys. Rev. Lett. 116, 241102 (2016), 10.1103/PhysRevLett.116.241102]. Using SXS waveforms as "experimental" data, we further show that our template could be used on the actual GW150914 data to perform a new measure of the complex frequency of the fundamental quasinormal mode so as to exploit the complete (high signal-to-noise-ratio) post-merger waveform. We assess the usefulness of our proposed template by analyzing, in a realistic setting, SXS full inspiral-merger-ringdown waveforms and constructing posterior probability distribution functions for the central frequency damping time of the first overtone of the fundamental quasinormal mode as well as for the physical parameters of the systems. We also briefly explore the possibility opened by our waveform model to test the second law of black hole dynamics. Our model will help improve current tests of general relativity, in particular the general-relativistic no-hair theorem, and allow for novel tests, such as that of the area theorem.

Pooling sexes when assessing ground reaction forces during walking: Statistical Parametric Mapping versus traditional approach.

PubMed

Castro, Marcelo P; Pataky, Todd C; Sole, Gisela; Vilas-Boas, Joao Paulo

2015-07-16

Ground reaction force (GRF) data from men and women are commonly pooled for analyses. However, it may not be justifiable to pool sexes on the basis of discrete parameters extracted from continuous GRF gait waveforms because this can miss continuous effects. Forty healthy participants (20 men and 20 women) walked at a cadence of 100 steps per minute across two force plates, recording GRFs. Two statistical methods were used to test the null hypothesis of no mean GRF differences between sexes: (i) Statistical Parametric Mapping-using the entire three-component GRF waveform; and (ii) traditional approach-using the first and second vertical GRF peaks. Statistical Parametric Mapping results suggested large sex differences, which post-hoc analyses suggested were due predominantly to higher anterior-posterior and vertical GRFs in early stance in women compared to men. Statistically significant differences were observed for the first GRF peak and similar values for the second GRF peak. These contrasting results emphasise that different parts of the waveform have different signal strengths and thus that one may use the traditional approach to choose arbitrary metrics and make arbitrary conclusions. We suggest that researchers and clinicians consider both the entire gait waveforms and sex-specificity when analysing GRF data. Copyright © 2015 Elsevier Ltd. All rights reserved.

Assessing the blood pressure waveform of the carotid artery using an ultrasound image processing method

PubMed Central

Fatouraee, Nasser; Saberi, Hazhir

2017-01-01

Purpose The aim of this study was to introduce and implement a noninvasive method to derive the carotid artery pressure waveform directly by processing diagnostic sonograms of the carotid artery. Methods Ultrasound image sequences of 20 healthy male subjects (age, 36±9 years) were recorded during three cardiac cycles. The internal diameter and blood velocity waveforms were extracted from consecutive sonograms over the cardiac cycles by using custom analysis programs written in MATLAB. Finally, the application of a mathematical equation resulted in time changes of the arterial pressure. The resulting pressures were calibrated using the mean and the diastolic pressure of the radial artery. Results A good correlation was found between the mean carotid blood pressure obtained from the ultrasound image processing and the mean radial blood pressure obtained using a standard digital sphygmomanometer (R=0.91). The mean absolute difference between the carotid calibrated pulse pressures and those measured clinically was -1.333±6.548 mm Hg. Conclusion The results of this study suggest that consecutive sonograms of the carotid artery can be used for estimating a blood pressure waveform. We believe that our results promote a noninvasive technique for clinical applications that overcomes the reproducibility problems of common carotid artery tonometry with technical and anatomical causes. PMID:27776401

Study on a Biometric Authentication Model based on ECG using a Fuzzy Neural Network

NASA Astrophysics Data System (ADS)

Kim, Ho J.; Lim, Joon S.

2018-03-01

Traditional authentication methods use numbers or graphic passwords and thus involve the risk of loss or theft. Various studies are underway regarding biometric authentication because it uses the unique biometric data of a human being. Biometric authentication technology using ECG from biometric data involves signals that record electrical stimuli from the heart. It is difficult to manipulate and is advantageous in that it enables unrestrained measurements from sensors that are attached to the skin. This study is on biometric authentication methods using the neural network with weighted fuzzy membership functions (NEWFM). In the biometric authentication process, normalization and the ensemble average is applied during preprocessing, characteristics are extracted using Haar-wavelets, and a registration process called “training” is performed in the fuzzy neural network. In the experiment, biometric authentication was performed on 73 subjects in the Physionet Database. 10-40 ECG waveforms were tested for use in the registration process, and 15 ECG waveforms were deemed the appropriate number for registering ECG waveforms. 1 ECG waveforms were used during the authentication stage to conduct the biometric authentication test. Upon testing the proposed biometric authentication method based on 73 subjects from the Physionet Database, the TAR was 98.32% and FAR was 5.84%.

Multiresolution Approach for Noncontact Measurements of Arterial Pulse Using Thermal Imaging

NASA Astrophysics Data System (ADS)

Chekmenev, Sergey Y.; Farag, Aly A.; Miller, William M.; Essock, Edward A.; Bhatnagar, Aruni

This chapter presents a novel computer vision methodology for noncontact and nonintrusive measurements of arterial pulse. This is the only investigation that links the knowledge of human physiology and anatomy, advances in thermal infrared (IR) imaging and computer vision to produce noncontact and nonintrusive measurements of the arterial pulse in both time and frequency domains. The proposed approach has a physical and physiological basis and as such is of a fundamental nature. A thermal IR camera was used to capture the heat pattern from superficial arteries, and a blood vessel model was proposed to describe the pulsatile nature of the blood flow. A multiresolution wavelet-based signal analysis approach was applied to extract the arterial pulse waveform, which lends itself to various physiological measurements. We validated our results using a traditional contact vital signs monitor as a ground truth. Eight people of different age, race and gender have been tested in our study consistent with Health Insurance Portability and Accountability Act (HIPAA) regulations and internal review board approval. The resultant arterial pulse waveforms exactly matched the ground truth oximetry readings. The essence of our approach is the automatic detection of region of measurement (ROM) of the arterial pulse, from which the arterial pulse waveform is extracted. To the best of our knowledge, the correspondence between noncontact thermal IR imaging-based measurements of the arterial pulse in the time domain and traditional contact approaches has never been reported in the literature.

Improved Measurement of Blood Pressure by Extraction of Characteristic Features from the Cuff Oscillometric Waveform

PubMed Central

Lim, Pooi Khoon; Ng, Siew-Cheok; Jassim, Wissam A.; Redmond, Stephen J.; Zilany, Mohammad; Avolio, Alberto; Lim, Einly; Tan, Maw Pin; Lovell, Nigel H.

2015-01-01

We present a novel approach to improve the estimation of systolic (SBP) and diastolic blood pressure (DBP) from oscillometric waveform data using variable characteristic ratios between SBP and DBP with mean arterial pressure (MAP). This was verified in 25 healthy subjects, aged 28 ± 5 years. The multiple linear regression (MLR) and support vector regression (SVR) models were used to examine the relationship between the SBP and the DBP ratio with ten features extracted from the oscillometric waveform envelope (OWE). An automatic algorithm based on relative changes in the cuff pressure and neighbouring oscillometric pulses was proposed to remove outlier points caused by movement artifacts. Substantial reduction in the mean and standard deviation of the blood pressure estimation errors were obtained upon artifact removal. Using the sequential forward floating selection (SFFS) approach, we were able to achieve a significant reduction in the mean and standard deviation of differences between the estimated SBP values and the reference scoring (MLR: mean ± SD = −0.3 ± 5.8 mmHg; SVR and −0.6 ± 5.4 mmHg) with only two features, i.e., Ratio2 and Area3, as compared to the conventional maximum amplitude algorithm (MAA) method (mean ± SD = −1.6 ± 8.6 mmHg). Comparing the performance of both MLR and SVR models, our results showed that the MLR model was able to achieve comparable performance to that of the SVR model despite its simplicity. PMID:26087370

Blind source deconvolution for deep Earth seismology

NASA Astrophysics Data System (ADS)

Stefan, W.; Renaut, R.; Garnero, E. J.; Lay, T.

2007-12-01

We present an approach to automatically estimate an empirical source characterization of deep earthquakes recorded teleseismically and subsequently remove the source from the recordings by applying regularized deconvolution. A principle goal in this work is to effectively deblur the seismograms, resulting in more impulsive and narrower pulses, permitting better constraints in high resolution waveform analyses. Our method consists of two stages: (1) we first estimate the empirical source by automatically registering traces to their 1st principal component with a weighting scheme based on their deviation from this shape, we then use this shape as an estimation of the earthquake source. (2) We compare different deconvolution techniques to remove the source characteristic from the trace. In particular Total Variation (TV) regularized deconvolution is used which utilizes the fact that most natural signals have an underlying spareness in an appropriate basis, in this case, impulsive onsets of seismic arrivals. We show several examples of deep focus Fiji-Tonga region earthquakes for the phases S and ScS, comparing source responses for the separate phases. TV deconvolution is compared to the water level deconvolution, Tikenov deconvolution, and L1 norm deconvolution, for both data and synthetics. This approach significantly improves our ability to study subtle waveform features that are commonly masked by either noise or the earthquake source. Eliminating source complexities improves our ability to resolve deep mantle triplications, waveform complexities associated with possible double crossings of the post-perovskite phase transition, as well as increasing stability in waveform analyses used for deep mantle anisotropy measurements.

Time-lapse seismic waveform modelling and attribute analysis using hydromechanical models for a deep reservoir undergoing depletion

NASA Astrophysics Data System (ADS)

He, Y.-X.; Angus, D. A.; Blanchard, T. D.; Wang, G.-L.; Yuan, S.-Y.; Garcia, A.

2016-04-01

Extraction of fluids from subsurface reservoirs induces changes in pore pressure, leading not only to geomechanical changes, but also perturbations in seismic velocities and hence observable seismic attributes. Time-lapse seismic analysis can be used to estimate changes in subsurface hydromechanical properties and thus act as a monitoring tool for geological reservoirs. The ability to observe and quantify changes in fluid, stress and strain using seismic techniques has important implications for monitoring risk not only for petroleum applications but also for geological storage of CO2 and nuclear waste scenarios. In this paper, we integrate hydromechanical simulation results with rock physics models and full-waveform seismic modelling to assess time-lapse seismic attribute resolution for dynamic reservoir characterization and hydromechanical model calibration. The time-lapse seismic simulations use a dynamic elastic reservoir model based on a North Sea deep reservoir undergoing large pressure changes. The time-lapse seismic traveltime shifts and time strains calculated from the modelled and processed synthetic data sets (i.e. pre-stack and post-stack data) are in a reasonable agreement with the true earth models, indicating the feasibility of using 1-D strain rock physics transform and time-lapse seismic processing methodology. Estimated vertical traveltime shifts for the overburden and the majority of the reservoir are within ±1 ms of the true earth model values, indicating that the time-lapse technique is sufficiently accurate for predicting overburden velocity changes and hence geomechanical effects. Characterization of deeper structure below the overburden becomes less accurate, where more advanced time-lapse seismic processing and migration is needed to handle the complex geometry and strong lateral induced velocity changes. Nevertheless, both migrated full-offset pre-stack and near-offset post-stack data image the general features of both the overburden and reservoir units. More importantly, the results from this study indicate that integrated seismic and hydromechanical modelling can help constrain time-lapse uncertainty and hence reduce risk due to fluid extraction and injection.

The shift-invariant discrete wavelet transform and application to speech waveform analysis.

PubMed

Enders, Jörg; Geng, Weihua; Li, Peijun; Frazier, Michael W; Scholl, David J

2005-04-01

The discrete wavelet transform may be used as a signal-processing tool for visualization and analysis of nonstationary, time-sampled waveforms. The highly desirable property of shift invariance can be obtained at the cost of a moderate increase in computational complexity, and accepting a least-squares inverse (pseudoinverse) in place of a true inverse. A new algorithm for the pseudoinverse of the shift-invariant transform that is easier to implement in array-oriented scripting languages than existing algorithms is presented together with self-contained proofs. Representing only one of the many and varied potential applications, a recorded speech waveform illustrates the benefits of shift invariance with pseudoinvertibility. Visualization shows the glottal modulation of vowel formants and frication noise, revealing secondary glottal pulses and other waveform irregularities. Additionally, performing sound waveform editing operations (i.e., cutting and pasting sections) on the shift-invariant wavelet representation automatically produces quiet, click-free section boundaries in the resulting sound. The capabilities of this wavelet-domain editing technique are demonstrated by changing the rate of a recorded spoken word. Individual pitch periods are repeated to obtain a half-speed result, and alternate individual pitch periods are removed to obtain a double-speed result. The original pitch and formant frequencies are preserved. In informal listening tests, the results are clear and understandable.

The shift-invariant discrete wavelet transform and application to speech waveform analysis

NASA Astrophysics Data System (ADS)

Enders, Jörg; Geng, Weihua; Li, Peijun; Frazier, Michael W.; Scholl, David J.

2005-04-01

The discrete wavelet transform may be used as a signal-processing tool for visualization and analysis of nonstationary, time-sampled waveforms. The highly desirable property of shift invariance can be obtained at the cost of a moderate increase in computational complexity, and accepting a least-squares inverse (pseudoinverse) in place of a true inverse. A new algorithm for the pseudoinverse of the shift-invariant transform that is easier to implement in array-oriented scripting languages than existing algorithms is presented together with self-contained proofs. Representing only one of the many and varied potential applications, a recorded speech waveform illustrates the benefits of shift invariance with pseudoinvertibility. Visualization shows the glottal modulation of vowel formants and frication noise, revealing secondary glottal pulses and other waveform irregularities. Additionally, performing sound waveform editing operations (i.e., cutting and pasting sections) on the shift-invariant wavelet representation automatically produces quiet, click-free section boundaries in the resulting sound. The capabilities of this wavelet-domain editing technique are demonstrated by changing the rate of a recorded spoken word. Individual pitch periods are repeated to obtain a half-speed result, and alternate individual pitch periods are removed to obtain a double-speed result. The original pitch and formant frequencies are preserved. In informal listening tests, the results are clear and understandable. .

Motor performance of tongue with a computer-integrated system under different levels of background physical exertion

PubMed Central

Huo, Xueliang; Johnson-Long, Ashley N.; Ghovanloo, Maysam; Shinohara, Minoru

2015-01-01

The purpose of this study was to compare the motor performance of tongue, using Tongue Drive System, to hand operation for relatively complex tasks under different levels of background physical exertion. Thirteen young able-bodied adults performed tasks that tested the accuracy and variability in tracking a sinusoidal waveform, and the performance in playing two video games that require accurate and rapid movements with cognitive processing using tongue and hand under two levels of background physical exertion. Results show additional background physical activity did not influence rapid and accurate displacement motor performance, but compromised the slow waveform tracking and shooting performances in both hand and tongue. Slow waveform tracking performance by the tongue was compromised with an additional motor or cognitive task, but with an additional motor task only for the hand. Practitioner Summary We investigated the influence of task complexity and background physical exertion on the motor performance of tongue and hand. Results indicate the task performance degrades with an additional concurrent task or physical exertion due to the limited attentional resources available for handling both the motor task and background exertion. PMID:24003900

Waveform Modeling Reveals Important Features of the Subduction Zone Seismic Structure Beneath the Tyrrhenian Sea, Italy

NASA Astrophysics Data System (ADS)

Di Luccio, F.; Persaud, P.; Pino, N. A.; Clayton, R. W.; Helmberger, D. V.; Li, D.

2016-12-01

Seismic images of the slab in southern Italy indicate a complex geodynamic system, although these images are strongly affected by limitations due to instrumental coverage, in terms of depth resolution and lateral extent. To help improve our knowledge of the structure of the Calabrian subduction zone, we analyze waveforms of regional events that occurred between 2001 and 2015 beneath the Tyrrhenian sea in the western Mediterranean. The selected events are deeper than 200 km and they were recorded at the Italian seismic network managed by Istituto Nazionale di Geofisica e Vulcanologia in Italy. We have also included recordings at ocean bottom seismometers and hydrophones, which were installed for a few months in 2000-2001, 2004-2005 and 2007-2008. Accurate selection of the source-to receiver raypaths can reveal significant differences at receivers, which are perpendicular to the trench with respect to other stations. P-wave complexity, converted phases and frequency content are some of the features we have observed for selected events. To investigate the slab structure, we model the waveforms using the 2D staggered grid Finite Difference method on graphics processing units developed by Li et al. (Geophys. J. Int., 2014).

Algorithmic processing of intrinsic signals in affixed transmission speckle analysis (ATSA) (Conference Presentation)

NASA Astrophysics Data System (ADS)

Ghijsen, Michael T.; Tromberg, Bruce J.

2017-03-01

Affixed Transmission Speckle Analysis (ATSA) is a method recently developed to measure blood flow that is based on laser speckle imaging miniaturized into a clip-on form factor the size of a pulse-oximeter. Measuring at a rate of 250 Hz, ATSA is capable or obtaining the cardiac waveform in blood flow data, referred to as the Speckle-Plethysmogram (SPG). ATSA is also capable of simultaneously measuring the Photoplethysmogram (PPG), a more conventional signal related to light intensity. In this work we present several novel algorithms for extracting physiologically relevant information from the combined SPG-PPG waveform data. First we show that there is a slight time-delay between the SPG and PPG that can be extracted computationally. Second, we present a set of frequency domain algorithms that measure harmonic content on pulse-by-pulse basis for both the SPG and PPG. Finally, we apply these algorithms to data obtained from a set of subjects including healthy controls and individuals with heightened cardiovascular risk. We hypothesize that the time-delay and frequency content are correlated with cardiovascular health; specifically with vascular stiffening.

Simulations of inspiraling and merging double neutron stars using the Spectral Einstein Code

NASA Astrophysics Data System (ADS)

Haas, Roland; Ott, Christian D.; Szilagyi, Bela; Kaplan, Jeffrey D.; Lippuner, Jonas; Scheel, Mark A.; Barkett, Kevin; Muhlberger, Curran D.; Dietrich, Tim; Duez, Matthew D.; Foucart, Francois; Pfeiffer, Harald P.; Kidder, Lawrence E.; Teukolsky, Saul A.

2016-06-01

We present results on the inspiral, merger, and postmerger evolution of a neutron star-neutron star (NSNS) system. Our results are obtained using the hybrid pseudospectral-finite volume Spectral Einstein Code (SpEC). To test our numerical methods, we evolve an equal-mass system for ≈22 orbits before merger. This waveform is the longest waveform obtained from fully general-relativistic simulations for NSNSs to date. Such long (and accurate) numerical waveforms are required to further improve semianalytical models used in gravitational wave data analysis, for example, the effective one body models. We discuss in detail the improvements to SpEC's ability to simulate NSNS mergers, in particular mesh refined grids to better resolve the merger and postmerger phases. We provide a set of consistency checks and compare our results to NSNS merger simulations with the independent bam code. We find agreement between them, which increases confidence in results obtained with either code. This work paves the way for future studies using long waveforms and more complex microphysical descriptions of neutron star matter in SpEC.

Modeling EEG Waveforms with Semi-Supervised Deep Belief Nets: Fast Classification and Anomaly Measurement

PubMed Central

Wulsin, D. F.; Gupta, J. R.; Mani, R.; Blanco, J. A.; Litt, B.

2011-01-01

Clinical electroencephalography (EEG) records vast amounts of human complex data yet is still reviewed primarily by human readers. Deep Belief Nets (DBNs) are a relatively new type of multi-layer neural network commonly tested on two-dimensional image data, but are rarely applied to times-series data such as EEG. We apply DBNs in a semi-supervised paradigm to model EEG waveforms for classification and anomaly detection. DBN performance was comparable to standard classifiers on our EEG dataset, and classification time was found to be 1.7 to 103.7 times faster than the other high-performing classifiers. We demonstrate how the unsupervised step of DBN learning produces an autoencoder that can naturally be used in anomaly measurement. We compare the use of raw, unprocessed data—a rarity in automated physiological waveform analysis—to hand-chosen features and find that raw data produces comparable classification and better anomaly measurement performance. These results indicate that DBNs and raw data inputs may be more effective for online automated EEG waveform recognition than other common techniques. PMID:21525569

Computational Intelligence and Wavelet Transform Based Metamodel for Efficient Generation of Not-Yet Simulated Waveforms.

PubMed

Oltean, Gabriel; Ivanciu, Laura-Nicoleta

2016-01-01

The design and verification of complex electronic systems, especially the analog and mixed-signal ones, prove to be extremely time consuming tasks, if only circuit-level simulations are involved. A significant amount of time can be saved if a cost effective solution is used for the extensive analysis of the system, under all conceivable conditions. This paper proposes a data-driven method to build fast to evaluate, but also accurate metamodels capable of generating not-yet simulated waveforms as a function of different combinations of the parameters of the system. The necessary data are obtained by early-stage simulation of an electronic control system from the automotive industry. The metamodel development is based on three key elements: a wavelet transform for waveform characterization, a genetic algorithm optimization to detect the optimal wavelet transform and to identify the most relevant decomposition coefficients, and an artificial neuronal network to derive the relevant coefficients of the wavelet transform for any new parameters combination. The resulted metamodels for three different waveform families are fully reliable. They satisfy the required key points: high accuracy (a maximum mean squared error of 7.1x10-5 for the unity-based normalized waveforms), efficiency (fully affordable computational effort for metamodel build-up: maximum 18 minutes on a general purpose computer), and simplicity (less than 1 second for running the metamodel, the user only provides the parameters combination). The metamodels can be used for very efficient generation of new waveforms, for any possible combination of dependent parameters, offering the possibility to explore the entire design space. A wide range of possibilities becomes achievable for the user, such as: all design corners can be analyzed, possible worst-case situations can be investigated, extreme values of waveforms can be discovered, sensitivity analyses can be performed (the influence of each parameter on the output waveform).

Computational Intelligence and Wavelet Transform Based Metamodel for Efficient Generation of Not-Yet Simulated Waveforms

PubMed Central

Oltean, Gabriel; Ivanciu, Laura-Nicoleta

2016-01-01

The design and verification of complex electronic systems, especially the analog and mixed-signal ones, prove to be extremely time consuming tasks, if only circuit-level simulations are involved. A significant amount of time can be saved if a cost effective solution is used for the extensive analysis of the system, under all conceivable conditions. This paper proposes a data-driven method to build fast to evaluate, but also accurate metamodels capable of generating not-yet simulated waveforms as a function of different combinations of the parameters of the system. The necessary data are obtained by early-stage simulation of an electronic control system from the automotive industry. The metamodel development is based on three key elements: a wavelet transform for waveform characterization, a genetic algorithm optimization to detect the optimal wavelet transform and to identify the most relevant decomposition coefficients, and an artificial neuronal network to derive the relevant coefficients of the wavelet transform for any new parameters combination. The resulted metamodels for three different waveform families are fully reliable. They satisfy the required key points: high accuracy (a maximum mean squared error of 7.1x10-5 for the unity-based normalized waveforms), efficiency (fully affordable computational effort for metamodel build-up: maximum 18 minutes on a general purpose computer), and simplicity (less than 1 second for running the metamodel, the user only provides the parameters combination). The metamodels can be used for very efficient generation of new waveforms, for any possible combination of dependent parameters, offering the possibility to explore the entire design space. A wide range of possibilities becomes achievable for the user, such as: all design corners can be analyzed, possible worst-case situations can be investigated, extreme values of waveforms can be discovered, sensitivity analyses can be performed (the influence of each parameter on the output waveform). PMID:26745370

Gravitational waves from plunges into Gargantua

NASA Astrophysics Data System (ADS)

Compère, Geoffrey; Fransen, Kwinten; Hertog, Thomas; Long, Jiang

2018-05-01

We analytically compute time domain gravitational waveforms produced in the final stages of extreme mass ratio inspirals of non-spinning compact objects into supermassive nearly extremal Kerr black holes. Conformal symmetry relates all corotating equatorial orbits in the geodesic approximation to circular orbits through complex conformal transformations. We use this to obtain the time domain Teukolsky perturbations for generic equatorial corotating plunges in closed form. The resulting gravitational waveforms consist of an intermediate polynomial ringdown phase in which the decay rate depends on the impact parameters, followed by an exponential quasi-normal mode decay. The waveform amplitude exhibits critical behavior when the orbital angular momentum tends to a minimal value determined by the innermost stable circular orbit. We show that either near-critical or large angular momentum leads to a significant extension of the LISA observable volume of gravitational wave sources of this kind.

Highly Scalable Matching Pursuit Signal Decomposition Algorithm

NASA Technical Reports Server (NTRS)

Christensen, Daniel; Das, Santanu; Srivastava, Ashok N.

2009-01-01

Matching Pursuit Decomposition (MPD) is a powerful iterative algorithm for signal decomposition and feature extraction. MPD decomposes any signal into linear combinations of its dictionary elements or atoms . A best fit atom from an arbitrarily defined dictionary is determined through cross-correlation. The selected atom is subtracted from the signal and this procedure is repeated on the residual in the subsequent iterations until a stopping criterion is met. The reconstructed signal reveals the waveform structure of the original signal. However, a sufficiently large dictionary is required for an accurate reconstruction; this in return increases the computational burden of the algorithm, thus limiting its applicability and level of adoption. The purpose of this research is to improve the scalability and performance of the classical MPD algorithm. Correlation thresholds were defined to prune insignificant atoms from the dictionary. The Coarse-Fine Grids and Multiple Atom Extraction techniques were proposed to decrease the computational burden of the algorithm. The Coarse-Fine Grids method enabled the approximation and refinement of the parameters for the best fit atom. The ability to extract multiple atoms within a single iteration enhanced the effectiveness and efficiency of each iteration. These improvements were implemented to produce an improved Matching Pursuit Decomposition algorithm entitled MPD++. Disparate signal decomposition applications may require a particular emphasis of accuracy or computational efficiency. The prominence of the key signal features required for the proper signal classification dictates the level of accuracy necessary in the decomposition. The MPD++ algorithm may be easily adapted to accommodate the imposed requirements. Certain feature extraction applications may require rapid signal decomposition. The full potential of MPD++ may be utilized to produce incredible performance gains while extracting only slightly less energy than the standard algorithm. When the utmost accuracy must be achieved, the modified algorithm extracts atoms more conservatively but still exhibits computational gains over classical MPD. The MPD++ algorithm was demonstrated using an over-complete dictionary on real life data. Computational times were reduced by factors of 1.9 and 44 for the emphases of accuracy and performance, respectively. The modified algorithm extracted similar amounts of energy compared to classical MPD. The degree of the improvement in computational time depends on the complexity of the data, the initialization parameters, and the breadth of the dictionary. The results of the research confirm that the three modifications successfully improved the scalability and computational efficiency of the MPD algorithm. Correlation Thresholding decreased the time complexity by reducing the dictionary size. Multiple Atom Extraction also reduced the time complexity by decreasing the number of iterations required for a stopping criterion to be reached. The Course-Fine Grids technique enabled complicated atoms with numerous variable parameters to be effectively represented in the dictionary. Due to the nature of the three proposed modifications, they are capable of being stacked and have cumulative effects on the reduction of the time complexity.

The Effects of Structure and Source Complexity on Waveforms: Crustal Structure of Tibet and the Recovery of Complex Seismic Sources

DTIC Science & Technology

1989-09-07

features such as the northern Anatolian fault are observed. After considerable convergence and shortening within Asia, lithospheric delamination perhaps...history of an earthquake as viewed by geologists and seismologists. There are many examples of earthquakes which show an apparent poor correlation of

Uncertainty of High Intensity Therapeutic Ultrasound (HITU) Field Characterization with Hydrophones: Effects of Nonlinearity, Spatial Averaging, and Complex Sensitivity

PubMed Central

Liu, Yunbo; Wear, Keith A.; Harris, Gerald R.

2017-01-01

Reliable acoustic characterization is fundamental for patient safety and clinical efficacy during high intensity therapeutic ultrasound (HITU) treatment. Technical challenges, such as measurement uncertainty and signal analysis still exist for HITU exposimetry using ultrasound hydrophones. In this work, four hydrophones were compared for pressure measurement: a robust needle hydrophone, a small PVDF capsule hydrophone and two different fiber-optic hydrophones. The focal waveform and beam distribution of a single element HITU transducer (1.05 MHz and 3.3 MHz) were evaluated. Complex deconvolution between the hydrophone voltage signal and frequency-dependent complex sensitivity was performed to obtain pressure waveform. Compressional pressure, rarefactional pressure, and focal beam distribution were compared up to 10.6/−6.0 MPa (p+ and p−) (1.05 MHz) and 20.65/−7.20 MPa (3.3 MHz). In particular, the effects of spatial averaging, local nonlinear distortion, complex deconvolution and hydrophone damage thresholds were investigated. This study showed an uncertainty of no better than 10–15% on hydrophone-based HITU pressure characterization. PMID:28735734

Variation of High-Intensity Therapeutic Ultrasound (HITU) Pressure Field Characterization: Effects of Hydrophone Choice, Nonlinearity, Spatial Averaging and Complex Deconvolution.

PubMed

Liu, Yunbo; Wear, Keith A; Harris, Gerald R

2017-10-01

Reliable acoustic characterization is fundamental for patient safety and clinical efficacy during high-intensity therapeutic ultrasound (HITU) treatment. Technical challenges, such as measurement variation and signal analysis, still exist for HITU exposimetry using ultrasound hydrophones. In this work, four hydrophones were compared for pressure measurement: a robust needle hydrophone, a small polyvinylidene fluoride capsule hydrophone and two fiberoptic hydrophones. The focal waveform and beam distribution of a single-element HITU transducer (1.05 MHz and 3.3 MHz) were evaluated. Complex deconvolution between the hydrophone voltage signal and frequency-dependent complex sensitivity was performed to obtain pressure waveforms. Compressional pressure (p + ), rarefactional pressure (p - ) and focal beam distribution were compared up to 10.6/-6.0 MPa (p + /p - ) (1.05 MHz) and 20.65/-7.20 MPa (3.3 MHz). The effects of spatial averaging, local non-linear distortion, complex deconvolution and hydrophone damage thresholds were investigated. This study showed a variation of no better than 10%-15% among hydrophones during HITU pressure characterization. Published by Elsevier Inc.

Speaker recognition through NLP and CWT modeling.

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

Brown-VanHoozer, A.; Kercel, S. W.; Tucker, R. W.

The objective of this research is to develop a system capable of identifying speakers on wiretaps from a large database (>500 speakers) with a short search time duration (<30 seconds), and with better than 90% accuracy. Much previous research in speaker recognition has led to algorithms that produced encouraging preliminary results, but were overwhelmed when applied to populations of more than a dozen or so different speakers. The authors are investigating a solution to the ''huge population'' problem by seeking two completely different kinds of characterizing features. These features are extracted using the techniques of Neuro-Linguistic Programming (NLP) and themore » continuous wavelet transform (CWT). NLP extracts precise neurological, verbal and non-verbal information, and assimilates the information into useful patterns. These patterns are based on specific cues demonstrated by each individual, and provide ways of determining congruency between verbal and non-verbal cues. The primary NLP modalities are characterized through word spotting (or verbal predicates cues, e.g., see, sound, feel, etc.) while the secondary modalities would be characterized through the speech transcription used by the individual. This has the practical effect of reducing the size of the search space, and greatly speeding up the process of identifying an unknown speaker. The wavelet-based line of investigation concentrates on using vowel phonemes and non-verbal cues, such as tempo. The rationale for concentrating on vowels is there are a limited number of vowels phonemes, and at least one of them usually appears in even the shortest of speech segments. Using the fast, CWT algorithm, the details of both the formant frequency and the glottal excitation characteristics can be easily extracted from voice waveforms. The differences in the glottal excitation waveforms as well as the formant frequency are evident in the CWT output. More significantly, the CWT reveals significant detail of the glottal excitation waveform.« less

The dE/dt and E Waveforms Radiated by Leader Steps Just Before the First Return Stroke in Cloud-to-Ocean Lightning

NASA Astrophysics Data System (ADS)

Krider, E. P.; Baffou, G.; Murray, N. D.; Willett, J. C.

2004-12-01

We have analyzed the shapes and other characteristics of the electric field, E, and dE/dt waveforms that were radiated by leader steps just before the first return stroke in cloud-to-ocean lightning. dE/dt waveforms were recorded using an 8-bit digitizer sampling at 100 MHz, and an integrated waveform, Eint, was computed by numerically integrating dE/dt and comparing the result with an analog E waveform digitized at 10 MHz. All signals were recorded under conditions where the lightning locations were known and there was minimal distortion in the fields due to the effects of ground-wave propagation. The dE/dt waveforms radiated by leader steps tend to fall into three categories: (1) "simple" - an isolated negative peak that is immediately followed by a positive overshoot (where negative polarity follows the normal physics convention), (2) "double" - two simple waveforms that occur at almost the same time, and (3) "burst" - a complex cluster of pulses with a total duration of about one microsecond. In this paper, we will give examples of each of these waveform types, and we will summarize their characteristics on a submicrosecond time-scale. For example, in an interval starting 9 μ s before to 4 μ s before the largest, negative (dominant) peak in dE/dt peak in the return stroke, 131 first strokes produced a total of 296 impulses with a peak amplitude greater than 10% of the dominant peak, and the average amplitude of these pulses was 0.21 of the dominant peak. The last leader step in a 12 μ s interval before the dominant peak was a simple waveform in 51 first strokes, and in these cases, the average time-interval between the peak dE/dt of the step and the dominant peak of the stroke was 5.8 ± 1.7 μ s, a value that is in good agreement with prior measurements. The median full-width-at-half-maximum (FWHM) of 274 simple Eint signatures was 141 ns, and the associated mean and standard deviation were 187 ± 131 ns.

Full-waveform inversion of GPR data for civil engineering applications

NASA Astrophysics Data System (ADS)

van der Kruk, Jan; Kalogeropoulos, Alexis; Hugenschmidt, Johannes; Klotzsche, Anja; Busch, Sebastian; Vereecken, Harry

2014-05-01

Conventional GPR ray-based techniques are often limited in their capability to image complex structures due to the pertaining approximations. Due to the increased computational power, it is becoming more easy to use modeling and inversion tools that explicitly take into account the detailed electromagnetic wave propagation characteristics. In this way, new civil engineering application avenues are opening up that enable an improved high resolution imaging of quantitative medium properties. In this contribution, we show recent developments that enable the full-waveform inversion of off-ground, on-ground and crosshole GPR data. For a successful inversion, a proper start model must be used that generates synthetic data that overlaps the measured data with at least half a wavelength. In addition, the GPR system must be calibrated such that an effective wavelet is obtained that encompasses the complexity of the GPR source and receiver antennas. Simple geometries such as horizontal layers can be described with a limited number of model parameters, which enable the use of a combined global and local search using the Simplex search algorithm. This approach has been implemented for the full-waveform inversion of off-ground and on-ground GPR data measured over horizontally layered media. In this way, an accurate 3D frequency domain forward model of Maxwell's equation can be used where the integral representation of the electric field is numerically evaluated. The full-waveform inversion (FWI) for a large number of unknowns uses gradient-based optimization methods where a 3D to 2D conversion is used to apply this method to experimental data. Off-ground GPR data, measured over homogeneous concrete specimens, were inverted using the full-waveform inversion. In contrast to traditional ray-based techniques we were able to obtain quantitative values for the permittivity and conductivity and in this way distinguish between moisture and chloride effects. For increasing chloride content increasing frequency-dependent conductivity values were obtained. The off-ground full-waveform inversion was extended to invert for positive and negative gradients in conductivity and the conductivity gradient direction could be correctly identified. Experimental specimen containing gradients were generated by exposing a concrete slab to controlled wetting-drying cycles using a saline solution. Full-waveform inversion of the measured data correctly identified the conductivity gradient direction which was confirmed by destructive analysis. On-ground CMP GPR data measured over a concrete layer overlying a metal plate show interfering multiple reflections, which indicates that the structure acts as a waveguide. Calculation of the phase-velocity spectrum shows the presence of several higher order modes. Whereas the dispersion inversion returns the thickness and layer height, the full-waveform inversion was also able to estimate quantitative conductivity values. This abstract is a contribution to COST Action TU1208

Neural network for photoplethysmographic respiratory rate monitoring

NASA Astrophysics Data System (ADS)

Johansson, Anders

2001-10-01

The photoplethysmographic signal (PPG) includes respiratory components seen as frequency modulation of the heart rate (respiratory sinus arrhythmia, RSA), amplitude modulation of the cardiac pulse, and respiratory induced intensity variations (RIIV) in the PPG baseline. The aim of this study was to evaluate the accuracy of these components in determining respiratory rate, and to combine the components in a neural network for improved accuracy. The primary goal is to design a PPG ventilation monitoring system. PPG signals were recorded from 15 healthy subjects. From these signals, the systolic waveform, diastolic waveform, respiratory sinus arrhythmia, pulse amplitude and RIIV were extracted. By using simple algorithms, the rates of false positive and false negative detection of breaths were calculated for each of the five components in a separate analysis. Furthermore, a simple neural network (NN) was tried out in a combined pattern recognition approach. In the separate analysis, the error rates (sum of false positives and false negatives) ranged from 9.7% (pulse amplitude) to 14.5% (systolic waveform). The corresponding value of the NN analysis was 9.5-9.6%.

Co-adaptation of Electric Organ Discharges and Chirps in South American Ghost Knifefishes (Apteronotidae)

PubMed Central

Petzold, Jacquelyn M.; Marsat, Gary; Smith, G. Troy

2016-01-01

Animal communication signals that simultaneously share the same sensory channel are likely to coevolve to maximize the transmission of each signal component. Weakly electric fish continuously produce a weakly electric field that functions in communication. Fish modulate the electric organ discharge (EOD) on short timescales to produce context-specific signals called chirps. EODs and chirps are simultaneously detected by electroreceptors and processed in the electrosensory system. We analyzed these signals, first to explore whether EOD waveform is encoded in the signal received by electroreceptors and then to examine how EODs and chirps interact to influence conspicuousness. Our findings show that gross discrimination of sinusoidal from complex EOD waveforms is feasible for all species, but fine discrimination of waveform may be possible only for species with waveforms of intermediate complexity. The degree of chirp frequency modulation and chirp relative decay strongly influenced chirp conspicuousness, but other chirp parameters were less influential. The frequency difference between the interacting EODs also strongly impacted chirp conspicuousness. Finally, we developed a method for creating hybrid chirp/EOD combinations to independently analyze the impact of chirp species, EOD species, and EOD difference frequency on chirp conspicuousness. All three components and their interactions strongly influenced chirp conspicuousness, which suggests that evolutionary changes in parameters of either chirps or EODs are likely to influence chirp detection. Examining other environmental factors such as noise created by fish movement and species-typical patterns of sociality may enrich our understanding of how interacting EODs affect the detection and discrimination of chirps across species. PMID:27989653

Intercorrelation of P and Pn Recordings for the North Korean Nuclear Tests

NASA Astrophysics Data System (ADS)

Lay, T.; Voytan, D.; Ohman, J.

2017-12-01

The relative waveform analysis procedure called Intercorrelation is applied to Pn and P waveforms at regional and teleseismic distances, respectively, for the 5 underground nuclear tests at the North Korean nuclear test site. Intercorrelation is a waveform equalization procedure that parameterizes the effective source function for a given explosion, including the reduced velocity potential convolved with a simplified Green's function that accounts for the free surface reflections (pPn and pP), and possibly additional arrivals such as spall. The source function for one event is convolved with the signal at a given station for a second event, and the recording at the same station for the first event is convolved with the source function for the second event. This procedure eliminates the need to predict the complex receiver function effects at the station, which are typically not well-known for short-period response. The parameters of the source function representation are yield and burial depth, and an explosion source model is required. Here we use the Mueller-Murphy representation of the explosion reduced velocity potential, which explicitly depends on yield and burial depth. We then search over yield and burial depth ranges for both events, constrained by a priori information about reasonable ranges of parameters, to optimize the simultaneous match of multiple station signals for the two events. This procedure, applied to the apparently overburied North Korean nuclear tests (no indications of spall complexity), assuming simple free surface interactions (elastic reflection from a flat surface), provides excellent waveform equalization for all combinations of 5 nuclear tests.

Numerical results for near surface time domain electromagnetic exploration: a full waveform approach

NASA Astrophysics Data System (ADS)

Sun, H.; Li, K.; Li, X., Sr.; Liu, Y., Sr.; Wen, J., Sr.

2015-12-01

Time domain or Transient electromagnetic (TEM) survey including types with airborne, semi-airborne and ground play important roles in applicants such as geological surveys, ground water/aquifer assess [Meju et al., 2000; Cox et al., 2010], metal ore exploration [Yang and Oldenburg, 2012], prediction of water bearing structures in tunnels [Xue et al., 2007; Sun et al., 2012], UXO exploration [Pasion et al., 2007; Gasperikova et al., 2009] etc. The common practice is introducing a current into a transmitting (Tx) loop and acquire the induced electromagnetic field after the current is cut off [Zhdanov and Keller, 1994]. The current waveforms are different depending on instruments. Rectangle is the most widely used excitation current source especially in ground TEM. Triangle and half sine are commonly used in airborne and semi-airborne TEM investigation. In most instruments, only the off time responses are acquired and used in later analysis and data inversion. Very few airborne instruments acquire the on time and off time responses together. Although these systems acquire the on time data, they usually do not use them in the interpretation.This abstract shows a novel full waveform time domain electromagnetic method and our recent modeling results. The benefits comes from our new algorithm in modeling full waveform time domain electromagnetic problems. We introduced the current density into the Maxwell's equation as the transmitting source. This approach allows arbitrary waveforms, such as triangle, half-sine, trapezoidal waves or scatter record from equipment, being used in modeling. Here, we simulate the establishing and induced diffusion process of the electromagnetic field in the earth. The traditional time domain electromagnetic with pure secondary fields can also be extracted from our modeling results. The real time responses excited by a loop source can be calculated using the algorithm. We analyze the full time gates responses of homogeneous half space and two layered models with half sine current waveform as examples. We find the on time responses are quite sensitive to resistivity or depth changes. The results show the potential use of full waveform responses in time domain electromagnetic surveys.

Validation of simulated earthquake ground motions based on evolution of intensity and frequency content

USGS Publications Warehouse

Rezaeian, Sanaz; Zhong, Peng; Hartzell, Stephen; Zareian, Farzin

2015-01-01

Simulated earthquake ground motions can be used in many recent engineering applications that require time series as input excitations. However, applicability and validation of simulations are subjects of debate in the seismological and engineering communities. We propose a validation methodology at the waveform level and directly based on characteristics that are expected to influence most structural and geotechnical response parameters. In particular, three time-dependent validation metrics are used to evaluate the evolving intensity, frequency, and bandwidth of a waveform. These validation metrics capture nonstationarities in intensity and frequency content of waveforms, making them ideal to address nonlinear response of structural systems. A two-component error vector is proposed to quantify the average and shape differences between these validation metrics for a simulated and recorded ground-motion pair. Because these metrics are directly related to the waveform characteristics, they provide easily interpretable feedback to seismologists for modifying their ground-motion simulation models. To further simplify the use and interpretation of these metrics for engineers, it is shown how six scalar key parameters, including duration, intensity, and predominant frequency, can be extracted from the validation metrics. The proposed validation methodology is a step forward in paving the road for utilization of simulated ground motions in engineering practice and is demonstrated using examples of recorded and simulated ground motions from the 1994 Northridge, California, earthquake.

Quantitative analysis of ground penetrating radar data in the Mu Us Sandland

NASA Astrophysics Data System (ADS)

Fu, Tianyang; Tan, Lihua; Wu, Yongqiu; Wen, Yanglei; Li, Dawei; Duan, Jinlong

2018-06-01

Ground penetrating radar (GPR), which can reveal the sedimentary structure and development process of dunes, is widely used to evaluate aeolian landforms. The interpretations for GPR profiles are mostly based on qualitative descriptions of geometric features of the radar reflections. This research quantitatively analyzed the waveform parameter characteristics of different radar units by extracting the amplitude and time interval parameters of GPR data in the Mu Us Sandland in China, and then identified and interpreted different sedimentary structures. The results showed that different types of radar units had specific waveform parameter characteristics. The main waveform parameter characteristics of sand dune radar facies and sandstone radar facies included low amplitudes and wide ranges of time intervals, ranging from 0 to 0.25 and 4 to 33 ns respectively, and the mean amplitudes changed gradually with time intervals. The amplitude distribution curves of various sand dune radar facies were similar as unimodal distributions. The radar surfaces showed high amplitudes with time intervals concentrated in high-value areas, ranging from 0.08 to 0.61 and 9 to 34 ns respectively, and the mean amplitudes changed drastically with time intervals. The amplitude and time interval values of lacustrine radar facies were between that of sand dune radar facies and radar surfaces, ranging from 0.08 to 0.29 and 11 to 30 ns respectively, and the mean amplitude and time interval curve was approximately trapezoidal. The quantitative extraction and analysis of GPR reflections could help distinguish various radar units and provide evidence for identifying sedimentary structure in aeolian landforms.

Using convolutional neural networks to estimate time-of-flight from PET detector waveforms

NASA Astrophysics Data System (ADS)

Berg, Eric; Cherry, Simon R.

2018-01-01

Although there have been impressive strides in detector development for time-of-flight positron emission tomography, most detectors still make use of simple signal processing methods to extract the time-of-flight information from the detector signals. In most cases, the timing pick-off for each waveform is computed using leading edge discrimination or constant fraction discrimination, as these were historically easily implemented with analog pulse processing electronics. However, now with the availability of fast waveform digitizers, there is opportunity to make use of more of the timing information contained in the coincident detector waveforms with advanced signal processing techniques. Here we describe the application of deep convolutional neural networks (CNNs), a type of machine learning, to estimate time-of-flight directly from the pair of digitized detector waveforms for a coincident event. One of the key features of this approach is the simplicity in obtaining ground-truth-labeled data needed to train the CNN: the true time-of-flight is determined from the difference in path length between the positron emission and each of the coincident detectors, which can be easily controlled experimentally. The experimental setup used here made use of two photomultiplier tube-based scintillation detectors, and a point source, stepped in 5 mm increments over a 15 cm range between the two detectors. The detector waveforms were digitized at 10 GS s-1 using a bench-top oscilloscope. The results shown here demonstrate that CNN-based time-of-flight estimation improves timing resolution by 20% compared to leading edge discrimination (231 ps versus 185 ps), and 23% compared to constant fraction discrimination (242 ps versus 185 ps). By comparing several different CNN architectures, we also showed that CNN depth (number of convolutional and fully connected layers) had the largest impact on timing resolution, while the exact network parameters, such as convolutional filter size and number of feature maps, had only a minor influence.

The development of the miniaturized waveform receiver with the function measuring Antenna Impedance in space plasmas

NASA Astrophysics Data System (ADS)

Ishii, H.; Kojima, H.; Fukuhara, H.; Okada, S.; Yamakawa, H.

2012-04-01

Plasma wave is one of the most essential physical quantities in the solar terrestrial physics. The role of plasma wave receiver onboard satellites is to detect plasma waves in space with a good signal to noise ratio. There are two types of plasma wave receivers, the sweep frequency analyzer and the waveform capture. While the sweep frequency analyzer provides plasma wave spectra, the waveform capture obtains waveforms with phase information that is significant in studying nonlinear phenomena. Antenna sensors to observe electric fields of the plasma waves show different features in plasmas from in vacuum. The antenna impedances have specific characteristics in the frequency domain because of the dispersion of plasmas. These antenna impedances are expressed with complex number. We need to know not only the antenna impedances but also the transfer functions of plasma wave receiver's circuits in order to calibrate observed waveforms precisely. The impedances of the electric field antennas are affected by a state of surrounding plasmas. Since satellites run through various regions with different plasma parameters, we precisely should measure the antenna impedances onboard spacecraft. On the contrary, we can obtain the plasma density and by measuring the antenna impedances. Several formulas of the antenna impedance measurement system were proposed. A synchronous detection method is used on the BepiColombo Mercury Magnetospheric Orbiter (MMO), which will be launched in 2014. The digital data are stored in the onboard memory. They are read out and converted to the analog waveforms by D/A converter. They are fed into the input of the preamplifiers of antenna sensors through a resistor. We can calculate a transfer function of the circuit by applying the synchronous detection method to the output waveform from waveform receivers and digital data as a signal source. The size of this system is same as an A5 board. In recent years, Application Specific Integrated Circuit (ASIC) is in attention which is a technique to integrate large scale and complicated circuits. Lots of ASICs have been applied to high energy astrophysics. In this paper, we show our attempt to miniaturize the antennas impedances measurement system and Waveform Capture using the analogue ASIC. We design 8bits segment D/A converter that is implemented inside the waveform receiver ASIC chip. We improve input logic of the D/A converter to generate very weak signals accurately. The designed chip realizes the measurement of the antenna impedance as well as the waveform observation in the board size of business cards.

Auditory Processing of Complex Sounds Across Frequency Channels.

DTIC Science & Technology

1992-06-26

towards gaining an understanding how the auditory system processes complex sounds. "The results of binaural psychophysical experiments in human subjects...suggest (1) that spectrally synthetic binaural processing is the rule when the number of components in the tone complex are relatively few (less than...10) and there are no dynamic binaural cues to aid segregation of the target from the background, and (2) that waveforms having large effective

The Ellipticity Filter-A Proposed Solution to the Mixed Event Problem in Nuclear Seismic Discrimination

DTIC Science & Technology

1974-09-07

ellipticity filter. The source waveforms are recreated by an inverse transform of those complex ampli- tudes associated with the same azimuth...terms of the three complex data points and the ellipticity. Having solved the equations for all frequency bins, the inverse transform of...Transform of those complex amplitudes associated with Source 1, yielding the signal a (t). Similarly, take the inverse Transform of all

Experimenting with musical intervals

NASA Astrophysics Data System (ADS)

Lo Presto, Michael C.

2003-07-01

When two tuning forks of different frequency are sounded simultaneously the result is a complex wave with a repetition frequency that is the fundamental of the harmonic series to which both frequencies belong. The ear perceives this 'musical interval' as a single musical pitch with a sound quality produced by the harmonic spectrum responsible for the waveform. This waveform can be captured and displayed with data collection hardware and software. The fundamental frequency can then be calculated and compared with what would be expected from the frequencies of the tuning forks. Also, graphing software can be used to determine equations for the waveforms and predict their shapes. This experiment could be used in an introductory physics or musical acoustics course as a practical lesson in superposition of waves, basic Fourier series and the relationship between some of the ear's subjective perceptions of sound and the physical properties of the waves that cause them.

Ultrasonic real-time in-die monitoring of the tablet compaction process-a proof of concept study.

PubMed

Stephens, James D; Kowalczyk, Brian R; Hancock, Bruno C; Kaul, Goldi; Cetinkaya, Cetin

2013-02-14

The mechanical properties of a drug tablet can affect its performance (e.g., dissolution profile and its physical robustness. An ultrasonic system for real-time in-die tablet mechanical property monitoring during compaction has been demonstrated. The reported set-up is a proof of concept compaction monitoring system which includes an ultrasonic transducer mounted inside the upper punch of the compaction apparatus. This upper punch is utilized to acquire ultrasonic pressure wave phase velocity waveforms and extract the time-of-flight of pressure waves travelling within the compact at a number of compaction force levels during compaction. The reflection coefficients for the waves reflecting from punch tip-powder bed interface are extracted from the acquired waveforms. The reflection coefficient decreases with an increase in compaction force, indicating solidification. The data acquisition methods give an average apparent Young's moduli in the range of 8-20 GPa extracted during the compaction and release/decompression phases in real-time. A monitoring system employing such methods is capable of determining material properties and the integrity of the tablet during compaction. As compared to the millisecond time-scale dwell time of a typical commercial compaction press, the micro-second pulse duration and ToF of an acoustic pulse are sufficiently fast for real-time monitoring. Copyright © 2012 Elsevier B.V. All rights reserved.

Application of an iterative least-squares waveform inversion of strong-motion and teleseismic records to the 1978 Tabas, Iran, earthquake

USGS Publications Warehouse

Hartzell, S.; Mendoza, C.

1991-01-01

An iterative least-squares technique is used to simultaneously invert the strong-motion records and teleseismic P waveforms for the 1978 Tabas, Iran, earthquake to deduce the rupture history. The effects of using different data sets and different parametrizations of the problem (linear versus nonlinear) are considered. A consensus of all the inversion runs indicates a complex, multiple source for the Tabas earthquake, with four main source regions over a fault length of 90 km and an average rupture velocity of 2.5 km/sec. -from Authors

Static inverter with synchronous output waveform synthesized by time-optimal-response feedback

NASA Technical Reports Server (NTRS)

Kernick, A.; Stechschulte, D. L.; Shireman, D. W.

1976-01-01

Time-optimal-response 'bang-bang' or 'bang-hang' technique, using four feedback control loops, synthesizes static-inverter sinusoidal output waveform by self-oscillatory but yet synchronous pulse-frequency-modulation (SPFM). A single modular power stage per phase of ac output entails the minimum of circuit complexity while providing by feedback synthesis individual phase voltage regulation, phase position control and inherent compensation simultaneously for line and load disturbances. Clipped sinewave performance is described under off-limit load or input voltage conditions. Also, approaches to high power levels, 3-phase arraying and parallel modular connection are given.

Respiratory variation of systolic and diastolic time intervals within radial arterial waveform: a comparison with dynamic preload index.

PubMed

Park, Ji Hyun; Hwang, Gyu-Sam

2016-08-01

A blood pressure (BP) waveform contains various pieces of information related to respiratory variation. Systolic time interval (STI) reflects myocardial performance, and diastolic time interval (DTI) represents diastolic filling. This study examined whether respiratory variations of STI and DTI within radial arterial waveform are comparable to dynamic indices. During liver transplantation, digitally recorded BP waveform and stroke volume variation (SVV) were retrospectively analyzed. Beat-to-beat STI and DTI were extracted within each BP waveform, which were separated by dicrotic notch. Systolic time variation (STV) was calculated by the average of 3 consecutive respiratory cycles: [(STImax- STImin)/STImean]. Similar formula was used for diastolic time variation (DTV) and pulse pressure variation (PPV). Receiver operating characteristic analysis with area under the curve (AUC) was used to assess thresholds predictive of SVV ≥12% and PPV ≥12%. STV and DTV showed significant correlations with SVV (r= 0.78 and r= 0.67, respectively) and PPV (r= 0.69 and r= 0.69, respectively). Receiver operating characteristic curves demonstrated that STV ≥11% identified to predict SVV ≥12% with 85.7% sensitivity and 89.3% specificity (AUC = 0.935; P< .001). DTV ≥11% identified to predict SVV ≥12% with 71.4% sensitivity and 85.7% specificity (AUC = 0.829; P< .001). STV ≥12% and DTV ≥11% identified to predict PPV ≥12% with an AUC of 0.881 and 0.885, respectively. Respiratory variations of STI and DTI derived from radial arterial contour have a potential to predict hemodynamic response as a surrogate for SVV or PPV. Copyright © 2016 Elsevier Inc. All rights reserved.

Effects of Neutron-Star Dynamic Tides on Gravitational Waveforms within the Effective-One-Body Approach

NASA Astrophysics Data System (ADS)

Hinderer, Tanja; Taracchini, Andrea; Foucart, Francois; Buonanno, Alessandra; Steinhoff, Jan; Duez, Matthew; Kidder, Lawrence E.; Pfeiffer, Harald P.; Scheel, Mark A.; Szilagyi, Bela; Hotokezaka, Kenta; Kyutoku, Koutarou; Shibata, Masaru; Carpenter, Cory W.

2016-05-01

Extracting the unique information on ultradense nuclear matter from the gravitational waves emitted by merging neutron-star binaries requires robust theoretical models of the signal. We develop a novel effective-one-body waveform model that includes, for the first time, dynamic (instead of only adiabatic) tides of the neutron star as well as the merger signal for neutron-star-black-hole binaries. We demonstrate the importance of the dynamic tides by comparing our model against new numerical-relativity simulations of nonspinning neutron-star-black-hole binaries spanning more than 24 gravitational-wave cycles, and to other existing numerical simulations for double neutron-star systems. Furthermore, we derive an effective description that makes explicit the dependence of matter effects on two key parameters: tidal deformability and fundamental oscillation frequency.

Effects of Neutron-Star Dynamic Tides on Gravitational Waveforms within the Effective-One-Body Approach.

PubMed

Hinderer, Tanja; Taracchini, Andrea; Foucart, Francois; Buonanno, Alessandra; Steinhoff, Jan; Duez, Matthew; Kidder, Lawrence E; Pfeiffer, Harald P; Scheel, Mark A; Szilagyi, Bela; Hotokezaka, Kenta; Kyutoku, Koutarou; Shibata, Masaru; Carpenter, Cory W

2016-05-06

Extracting the unique information on ultradense nuclear matter from the gravitational waves emitted by merging neutron-star binaries requires robust theoretical models of the signal. We develop a novel effective-one-body waveform model that includes, for the first time, dynamic (instead of only adiabatic) tides of the neutron star as well as the merger signal for neutron-star-black-hole binaries. We demonstrate the importance of the dynamic tides by comparing our model against new numerical-relativity simulations of nonspinning neutron-star-black-hole binaries spanning more than 24 gravitational-wave cycles, and to other existing numerical simulations for double neutron-star systems. Furthermore, we derive an effective description that makes explicit the dependence of matter effects on two key parameters: tidal deformability and fundamental oscillation frequency.

A graph-Laplacian-based feature extraction algorithm for neural spike sorting.

PubMed

Ghanbari, Yasser; Spence, Larry; Papamichalis, Panos

2009-01-01

Analysis of extracellular neural spike recordings is highly dependent upon the accuracy of neural waveform classification, commonly referred to as spike sorting. Feature extraction is an important stage of this process because it can limit the quality of clustering which is performed in the feature space. This paper proposes a new feature extraction method (which we call Graph Laplacian Features, GLF) based on minimizing the graph Laplacian and maximizing the weighted variance. The algorithm is compared with Principal Components Analysis (PCA, the most commonly-used feature extraction method) using simulated neural data. The results show that the proposed algorithm produces more compact and well-separated clusters compared to PCA. As an added benefit, tentative cluster centers are output which can be used to initialize a subsequent clustering stage.

Improved linearity using harmonic error rejection in a full-field range imaging system

NASA Astrophysics Data System (ADS)

Payne, Andrew D.; Dorrington, Adrian A.; Cree, Michael J.; Carnegie, Dale A.

2008-02-01

Full field range imaging cameras are used to simultaneously measure the distance for every pixel in a given scene using an intensity modulated illumination source and a gain modulated receiver array. The light is reflected from an object in the scene, and the modulation envelope experiences a phase shift proportional to the target distance. Ideally the waveforms are sinusoidal, allowing the phase, and hence object range, to be determined from four measurements using an arctangent function. In practice these waveforms are often not perfectly sinusoidal, and in some cases square waveforms are instead used to simplify the electronic drive requirements. The waveforms therefore commonly contain odd harmonics which contribute a nonlinear error to the phase determination, and therefore an error in the range measurement. We have developed a unique sampling method to cancel the effect of these harmonics, with the results showing an order of magnitude improvement in the measurement linearity without the need for calibration or lookup tables, while the acquisition time remains unchanged. The technique can be applied to existing range imaging systems without having to change or modify the complex illumination or sensor systems, instead only requiring a change to the signal generation and timing electronics.

Electronic switching circuit uses complementary non-linear components

NASA Technical Reports Server (NTRS)

Zucker, O. S.

1972-01-01

Inherent switching properties of saturable inductors and storage diodes are combined to perform large variety of electronic functions, such as pulse shaping, gating, and multiplexing. Passive elements replace active switching devices in generation of complex waveforms.

The signatures of acoustic emission waveforms from fatigue crack advancing in thin metallic plates

NASA Astrophysics Data System (ADS)

Yeasin Bhuiyan, Md; Giurgiutiu, Victor

2018-01-01

The acoustic emission (AE) waveforms from a fatigue crack advancing in a thin metallic plate possess diverse and complex spectral signatures. In this article, we analyze these waveform signatures in coordination with the load level during cyclic fatigue. The advancing fatigue crack may generate numerous AE hits while it grows under fatigue loading. We found that these AE hits can be sorted into various groups based on their AE waveform signatures. Each waveform group has a particular time-domain signal pattern and a specific frequency spectrum. This indicates that each group represents a certain AE event related to the fatigue crack growth behavior. In situ AE-fatigue experiments were conducted to monitor the fatigue crack growth with simultaneous measurement of AE signals, fatigue loading, and optical crack growth measurement. An in situ microscope was installed in the load-frame of the mechanical testing system (MTS) to optically monitor the fatigue crack growth and relate the AE signals with the crack growth measurement. We found the AE signal groups at higher load levels (75%-85% of maximum load) were different from the AE signal groups that happened at lower load levels (below 60% of load level). These AE waveform groups are highly related to the fatigue crack-related AE events. These AE signals mostly contain the higher frequency peaks (100 kHz, 230 kHz, 450 kHz, 550 kHz). Some AE signal groups happened as a clustered form that relates a sequence of small AE events within the fatigue crack. They happened at relatively lower load level (50%-60% of the maximum load). These AE signal groups may be related to crack friction and micro-fracture during the friction process. These AE signals mostly contain the lower frequency peaks (60 kHz, 100 kHz, 200 kHz). The AE waveform based analysis may give us comprehensive information of the metal fatigue.

2-D traveltime and waveform inversion for improved seismic imaging: Naga Thrust and Fold Belt, India

NASA Astrophysics Data System (ADS)

Jaiswal, Priyank; Zelt, Colin A.; Bally, Albert W.; Dasgupta, Rahul

2008-05-01

Exploration along the Naga Thrust and Fold Belt in the Assam province of Northeast India encounters geological as well as logistic challenges. Drilling for hydrocarbons, traditionally guided by surface manifestations of the Naga thrust fault, faces additional challenges in the northeast where the thrust fault gradually deepens leaving subtle surface expressions. In such an area, multichannel 2-D seismic data were collected along a line perpendicular to the trend of the thrust belt. The data have a moderate signal-to-noise ratio and suffer from ground roll and other acquisition-related noise. In addition to data quality, the complex geology of the thrust belt limits the ability of conventional seismic processing to yield a reliable velocity model which in turn leads to poor subsurface image. In this paper, we demonstrate the application of traveltime and waveform inversion as supplements to conventional seismic imaging and interpretation processes. Both traveltime and waveform inversion utilize the first arrivals that are typically discarded during conventional seismic processing. As a first step, a smooth velocity model with long wavelength characteristics of the subsurface is estimated through inversion of the first-arrival traveltimes. This velocity model is then used to obtain a Kirchhoff pre-stack depth-migrated image which in turn is used for the interpretation of the fault. Waveform inversion is applied to the central part of the seismic line to a depth of ~1 km where the quality of the migrated image is poor. Waveform inversion is performed in the frequency domain over a series of iterations, proceeding from low to high frequency (11-19 Hz) using the velocity model from traveltime inversion as the starting model. In the end, the pre-stack depth-migrated image and the waveform inversion model are jointly interpreted. This study demonstrates that a combination of traveltime and waveform inversion with Kirchhoff pre-stack depth migration is a promising approach for the interpretation of geological structures in a thrust belt.

Studies Of Coherent Synchrotron Radiation And Longitudinal Space Charge In The Jefferson Lab FEL Driver

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

Tennant, Christopher D.; Douglas, David R.; Li, Rui

2014-12-01

The Jefferson Laboratory IR FEL Driver provides an ideal test bed for studying a variety of beam dynamical effects. Recent studies focused on characterizing the impact of coherent synchrotron radiation (CSR) with the goal of benchmarking measurements with simulation. Following measurements to characterize the beam, we quantitatively characterized energy extraction via CSR by measuring beam position at a dispersed location as a function of bunch compression. In addition to operating with the beam on the rising part of the linac RF waveform, measurements were also made while accelerating on the falling part. For each, the full compression point was movedmore » along the backleg of the machine and the response of the beam (distribution, extracted energy) measured. Initial results of start-to-end simulations using a 1D CSR algorithm show remarkably good agreement with measurements. A subsequent experiment established lasing with the beam accelerated on the falling side of the RF waveform in conjunction with positive momentum compaction (R56) to compress the bunch. The success of this experiment motivated the design of a modified CEBAF-style arc with control of CSR and microbunching effects.« less

Wavelet-based multiscale adjoint waveform-difference tomography using body and surface waves

NASA Astrophysics Data System (ADS)

Yuan, Y. O.; Simons, F. J.; Bozdag, E.

2014-12-01

We present a multi-scale scheme for full elastic waveform-difference inversion. Using a wavelet transform proves to be a key factor to mitigate cycle-skipping effects. We start with coarse representations of the seismogram to correct a large-scale background model, and subsequently explain the residuals in the fine scales of the seismogram to map the heterogeneities with great complexity. We have previously applied the multi-scale approach successfully to body waves generated in a standard model from the exploration industry: a modified two-dimensional elastic Marmousi model. With this model we explored the optimal choice of wavelet family, number of vanishing moments and decomposition depth. For this presentation we explore the sensitivity of surface waves in waveform-difference tomography. The incorporation of surface waves is rife with cycle-skipping problems compared to the inversions considering body waves only. We implemented an envelope-based objective function probed via a multi-scale wavelet analysis to measure the distance between predicted and target surface-wave waveforms in a synthetic model of heterogeneous near-surface structure. Our proposed method successfully purges the local minima present in the waveform-difference misfit surface. An elastic shallow model with 100~m in depth is used to test the surface-wave inversion scheme. We also analyzed the sensitivities of surface waves and body waves in full waveform inversions, as well as the effects of incorrect density information on elastic parameter inversions. Based on those numerical experiments, we ultimately formalized a flexible scheme to consider both body and surface waves in adjoint tomography. While our early examples are constructed from exploration-style settings, our procedure will be very valuable for the study of global network data.

Upper Mantle Velocity Structure beneath the Northeastern Philippine Sea Constrained by Waveform Modeling of P Triplicated Phases

NASA Astrophysics Data System (ADS)

Cho, S.; Rhie, J.; Lee, S. H.; Kim, S.; Kang, T. S.

2017-12-01

A study on the detailed velocity structures of the stagnant Pacific slab is important to understand the complex processes happening in the upper mantle. Although waveform modeling of P triplicated phases can reveal the detailed velocity structures especially for the discontinuities, the regions where the method can be applied are limited due to uneven distribution of earthquakes and stations. In this study, we used waveforms generated by two deep earthquakes near Izu-Bonin Trench and recorded by stations in South Korea. These event-station pairs are appropriate to study the upper mantle structures beneath the northeastern Philippine Sea, where no previous results by triplicated waveform modeling have been reported. In this region, the subducting Pacific slab seems to hit the 660 km discontinuity and become stagnant. We applied the reflectivity method to calculate waveforms and found the best fitting model by trial-and-error and manual inspection. In general, our best model is similar to M3.11, which is widely accepted 1D model for the regions where the stagnant slab exists and the 660 km discontinuity is depressed by the slab. The most noticeable feature of our model is that P wave velocities of inside and above the slab are considerably higher and lower than ones for M3.11, respectively. This specific velocity model is necessary to explain arrivals of two distinct phases identified in observed waveforms; one refracts inside the slab and the other reflects on the upper boundary of the slab. To understand the cause of the differences between our model and M3.11, further studies including thermal and mechanical modelling of the slab in this region will be recommended.

The complex frequencies of long-period seismic events as probes of fluid composition beneath volcanoes

USGS Publications Warehouse

Kumagai, H.; Chouet, B.A.

1999-01-01

Long-period (LP) events have been widely observed in relation to magmatic and hydrothermal activities in volcanic areas. LP waveforms characterized by their harmonic signature have been interpreted as oscillations of a fluid-filled resonator, and mixtures of liquid and gas in the form of bubbly liquids have been mainly assumed for the fluid. To investigate the characteristic properties of the resonator system, we analyse waveforms of LP events observed at four different volcanoes in Hawaii, Alaska, Colombia and Japan using a newly developed spectral method. This method allows an estimation of the complex frequencies of decaying sinusoids based on an autoregressive model. The results of our analysis show a wide variety of Q factors, ranging from tens to several hundred. We compare these complex frequencies with those predicted by the fluid-filled crack model for various mixtures of liquid, gas and ash. Although the oscillations of LP events with Q smaller than 50 can be explained by various combinations of liquids and gases, we find that ash-laden gases are required to explain long-lasting oscillations with Q larger than 100. The complex frequencies of LP events yield useful information on the types of fluids. Temporal and spatial variations of the complex frequencies can be used as probes of fluid composition beneath volcanoes.

Evaluation and characterization of fetal exposures to low frequency magnetic fields generated by laptop computers.

PubMed

Zoppetti, Nicola; Andreuccetti, Daniele; Bellieni, Carlo; Bogi, Andrea; Pinto, Iole

2011-12-01

Portable - or "laptop" - computers (LCs) are widely and increasingly used all over the world. Since LCs are often used in tight contact with the body even by pregnant women, fetal exposures to low frequency magnetic fields generated by these units can occur. LC emissions are usually characterized by complex waveforms and are often generated by the main AC power supply (when connected) and by the display power supply sub-system. In the present study, low frequency magnetic field emissions were measured for a set of five models of portable computers. For each of them, the magnetic flux density was characterized in terms not just of field amplitude, but also of the so called "weighted peak" (WP) index, introduced in the 2003 ICNIRP Statement on complex waveforms and confirmed in the 2010 ICNIRP Guidelines for low frequency fields. For the model of LC presenting the higher emission, a deeper analysis was also carried out, using numerical dosimetry techniques to calculate internal quantities (current density and in-situ electric field) with reference to a digital body model of a pregnant woman. Since internal quantities have complex waveforms too, the concept of WP index was extended to them, considering the ICNIRP basic restrictions defined in the 1998 Guidelines for the current density and in the 2010 Guidelines for the in-situ electric field. Induced quantities and WP indexes were computed using an appropriate original formulation of the well known Scalar Potential Finite Difference (SPFD) numerical method for electromagnetic dosimetry in quasi-static conditions. Copyright © 2011 Elsevier Ltd. All rights reserved.

Detecting Earthquakes over a Seismic Network using Single-Station Similarity Measures

NASA Astrophysics Data System (ADS)

Bergen, Karianne J.; Beroza, Gregory C.

2018-03-01

New blind waveform-similarity-based detection methods, such as Fingerprint and Similarity Thresholding (FAST), have shown promise for detecting weak signals in long-duration, continuous waveform data. While blind detectors are capable of identifying similar or repeating waveforms without templates, they can also be susceptible to false detections due to local correlated noise. In this work, we present a set of three new methods that allow us to extend single-station similarity-based detection over a seismic network; event-pair extraction, pairwise pseudo-association, and event resolution complete a post-processing pipeline that combines single-station similarity measures (e.g. FAST sparse similarity matrix) from each station in a network into a list of candidate events. The core technique, pairwise pseudo-association, leverages the pairwise structure of event detections in its network detection model, which allows it to identify events observed at multiple stations in the network without modeling the expected move-out. Though our approach is general, we apply it to extend FAST over a sparse seismic network. We demonstrate that our network-based extension of FAST is both sensitive and maintains a low false detection rate. As a test case, we apply our approach to two weeks of continuous waveform data from five stations during the foreshock sequence prior to the 2014 Mw 8.2 Iquique earthquake. Our method identifies nearly five times as many events as the local seismicity catalog (including 95% of the catalog events), and less than 1% of these candidate events are false detections.

Mortar and artillery variants classification by exploiting characteristics of the acoustic signature

NASA Astrophysics Data System (ADS)

Hohil, Myron E.; Grasing, David; Desai, Sachi; Morcos, Amir

2007-10-01

Feature extraction methods based on the discrete wavelet transform and multiresolution analysis facilitate the development of a robust classification algorithm that reliably discriminates mortar and artillery variants via acoustic signals produced during the launch/impact events. Utilizing acoustic sensors to exploit the sound waveform generated from the blast for the identification of mortar and artillery variants. Distinct characteristics arise within the different mortar variants because varying HE mortar payloads and related charges emphasize concussive and shrapnel effects upon impact employing varying magnitude explosions. The different mortar variants are characterized by variations in the resulting waveform of the event. The waveform holds various harmonic properties distinct to a given mortar/artillery variant that through advanced signal processing techniques can employed to classify a given set. The DWT and other readily available signal processing techniques will be used to extract the predominant components of these characteristics from the acoustic signatures at ranges exceeding 2km. Exploiting these techniques will help develop a feature set highly independent of range, providing discrimination based on acoustic elements of the blast wave. Highly reliable discrimination will be achieved with a feed-forward neural network classifier trained on a feature space derived from the distribution of wavelet coefficients, frequency spectrum, and higher frequency details found within different levels of the multiresolution decomposition. The process that will be described herein extends current technologies, which emphasis multi modal sensor fusion suites to provide such situational awareness. A two fold problem of energy consumption and line of sight arise with the multi modal sensor suites. The process described within will exploit the acoustic properties of the event to provide variant classification as added situational awareness to the solider.

Artificial arterial blood pressure artifact models and an evaluation of a robust blood pressure and heart rate estimator

PubMed Central

Li, Qiao; Mark, Roger G; Clifford, Gari D

2009-01-01

Background Within the intensive care unit (ICU), arterial blood pressure (ABP) is typically recorded at different (and sometimes uneven) sampling frequencies, and from different sensors, and is often corrupted by different artifacts and noise which are often non-Gaussian, nonlinear and nonstationary. Extracting robust parameters from such signals, and providing confidences in the estimates is therefore difficult and requires an adaptive filtering approach which accounts for artifact types. Methods Using a large ICU database, and over 6000 hours of simultaneously acquired electrocardiogram (ECG) and ABP waveforms sampled at 125 Hz from a 437 patient subset, we documented six general types of ABP artifact. We describe a new ABP signal quality index (SQI), based upon the combination of two previously reported signal quality measures weighted together. One index measures morphological normality, and the other degradation due to noise. After extracting a 6084-hour subset of clean data using our SQI, we evaluated a new robust tracking algorithm for estimating blood pressure and heart rate (HR) based upon a Kalman Filter (KF) with an update sequence modified by the KF innovation sequence and the value of the SQI. In order to do this, we have created six novel models of different categories of artifacts that we have identified in our ABP waveform data. These artifact models were then injected into clean ABP waveforms in a controlled manner. Clinical blood pressure (systolic, mean and diastolic) estimates were then made from the ABP waveforms for both clean and corrupted data. The mean absolute error for systolic, mean and diastolic blood pressure was then calculated for different levels of artifact pollution to provide estimates of expected errors given a single value of the SQI. Results Our artifact models demonstrate that artifact types have differing effects on systolic, diastolic and mean ABP estimates. We show that, for most artifact types, diastolic ABP estimates are less noise-sensitive than mean ABP estimates, which in turn are more robust than systolic ABP estimates. We also show that our SQI can provide error bounds for both HR and ABP estimates. Conclusion The KF/SQI-fusion method described in this article was shown to provide an accurate estimate of blood pressure and HR derived from the ABP waveform even in the presence of high levels of persistent noise and artifact, and during extreme bradycardia and tachycardia. Differences in error between artifact types, measurement sensors and the quality of the source signal can be factored into physiological estimation using an unbiased adaptive filter, signal innovation and signal quality measures. PMID:19586547

Three-Dimensional Anisotropic Acoustic and Elastic Full-Waveform Seismic Inversion

NASA Astrophysics Data System (ADS)

Warner, M.; Morgan, J. V.

2013-12-01

Three-dimensional full-waveform inversion is a high-resolution, high-fidelity, quantitative, seismic imaging technique that has advanced rapidly within the oil and gas industry. The method involves the iterative improvement of a starting model using a series of local linearized updates to solve the full non-linear inversion problem. During the inversion, forward modeling employs the full two-way three-dimensional heterogeneous anisotropic acoustic or elastic wave equation to predict the observed raw field data, wiggle-for-wiggle, trace-by-trace. The method is computationally demanding; it is highly parallelized, and runs on large multi-core multi-node clusters. Here, we demonstrate what can be achieved by applying this newly practical technique to several high-density 3D seismic datasets that were acquired to image four contrasting sedimentary targets: a gas cloud above an oil reservoir, a radially faulted dome, buried fluvial channels, and collapse structures overlying an evaporate sequence. We show that the resulting anisotropic p-wave velocity models match in situ measurements in deep boreholes, reproduce detailed structure observed independently on high-resolution seismic reflection sections, accurately predict the raw seismic data, simplify and sharpen reverse-time-migrated reflection images of deeper horizons, and flatten Kirchhoff-migrated common-image gathers. We also show that full-elastic 3D full-waveform inversion of pure pressure data can generate a reasonable shear-wave velocity model for one of these datasets. For two of the four datasets, the inclusion of significant transversely isotropic anisotropy with a vertical axis of symmetry was necessary in order to fit the kinematics of the field data properly. For the faulted dome, the full-waveform-inversion p-wave velocity model recovers the detailed structure of every fault that can be seen on coincident seismic reflection data. Some of the individual faults represent high-velocity zones, some represent low-velocity zones, some have more-complex internal structure, and some are visible merely as offsets between two regions with contrasting velocity. Although this has not yet been demonstrated quantitatively for this dataset, it seems likely that at least some of this fine structure in the recovered velocity model is related to the detailed lithology, strain history and fluid properties within the individual faults. We have here applied this technique to seismic data that were acquired by the extractive industries, however this inversion scheme is immediately scalable and applicable to a much wider range of problems given sufficient quality and density of observed data. Potential targets range from shallow magma chambers beneath active volcanoes, through whole-crustal sections across plate boundaries, to regional and whole-Earth models.

Accuracy and precision of gravitational-wave models of inspiraling neutron star-black hole binaries with spin: Comparison with matter-free numerical relativity in the low-frequency regime

NASA Astrophysics Data System (ADS)

Kumar, Prayush; Barkett, Kevin; Bhagwat, Swetha; Afshari, Nousha; Brown, Duncan A.; Lovelace, Geoffrey; Scheel, Mark A.; Szilágyi, Béla

2015-11-01

Coalescing binaries of neutron stars and black holes are one of the most important sources of gravitational waves for the upcoming network of ground-based detectors. Detection and extraction of astrophysical information from gravitational-wave signals requires accurate waveform models. The effective-one-body and other phenomenological models interpolate between analytic results and numerical relativity simulations, that typically span O (10 ) orbits before coalescence. In this paper we study the faithfulness of these models for neutron star-black hole binaries. We investigate their accuracy using new numerical relativity (NR) simulations that span 36-88 orbits, with mass ratios q and black hole spins χBH of (q ,χBH)=(7 ,±0.4 ),(7 ,±0.6 ) , and (5 ,-0.9 ). These simulations were performed treating the neutron star as a low-mass black hole, ignoring its matter effects. We find that (i) the recently published SEOBNRv1 and SEOBNRv2 models of the effective-one-body family disagree with each other (mismatches of a few percent) for black hole spins χBH≥0.5 or χBH≤-0.3 , with waveform mismatch accumulating during early inspiral; (ii) comparison with numerical waveforms indicates that this disagreement is due to phasing errors of SEOBNRv1, with SEOBNRv2 in good agreement with all of our simulations; (iii) phenomenological waveforms agree with SEOBNRv2 only for comparable-mass low-spin binaries, with overlaps below 0.7 elsewhere in the neutron star-black hole binary parameter space; (iv) comparison with numerical waveforms shows that most of this model's dephasing accumulates near the frequency interval where it switches to a phenomenological phasing prescription; and finally (v) both SEOBNR and post-Newtonian models are effectual for neutron star-black hole systems, but post-Newtonian waveforms will give a significant bias in parameter recovery. Our results suggest that future gravitational-wave detection searches and parameter estimation efforts would benefit from using SEOBNRv2 waveform templates when focused on neutron star-black hole systems with q ≲7 and χBH≈[-0.9 ,+0.6 ] . For larger black hole spins and/or binary mass ratios, we recommend the models be further investigated as NR simulations in that region of the parameter space become available.

Toward Near Real-Time Tomography of the Upper Mantle

NASA Astrophysics Data System (ADS)

Debayle, E.; Dubuffet, F.

2014-12-01

We added a layer of automation to the Debayle and Ricard (2012)'s waveform modeling scheme for fundamental and higher mode surface waves in the period range 50-160s. We processed all the Rayleigh waveforms recorded on the LHZ channel by the virtual networks GSN_broadband, FDSN_all, and US_backbone between January 1996 and December 2013. Six millions of waveforms were obtained from IRIS DMC. We check that all the necessary information (instrument response, global CMT determination) is available and that each record includes a velocity window which encompasses the surface wave. Selected data must also have a signal-to-noise ratio greater than 3 in a range covering at least the periods between 50 and 100 s. About 3 millions of waveforms are selected (92% of the rejections are due to the signal to noise ratio criterion) and processed using Debayle and Ricard (2012)'s scheme, which allows the successful modeling of about 1.5 millions of waveforms. We complete this database with 60,000 waveforms recorded between 1976 and 1996 or after 1996 during various temporary experiments and with 161,730 Rayleigh waveforms analyzed at longer period, between 120 and 360 s. The whole data set is inverted using Debayle and Sambridge (2004)'s scheme to produce a 3D shear velocity model. A simple shell command "update_tomo" can then update our seismic model in an entirely automated way. Currently, this command checks from the CMT catalog what are the potential data available at the GSN_broadband, FDSN_all, and US_backbone virtual networks, uses web services to request these data from IRIS DMC and applies the processing chain described above to update our seismic model. We plan to update our seismic model on a regular basis in a near future, and to make it available on the web. Our most recent seismic model includes azimuthal anisotropy, achieves a lateral resolution of few hundred kilometers and a vertical resolution of a few tens of kilometers. The correlation with surface tectonics is very strong in the uppermost 200 km. Regions deeper than 400 km show no velocity contrasts larger than 1%, except for high velocity slabs which produce broad high velocity regions within the transition zone. The use of higher modes and long period surface waves allows us to extract the shear velocity structure down to about 1000 km depth.

Construction and development of IGP DMC of China National Seismological Network

NASA Astrophysics Data System (ADS)

Zheng, X.; Zheng, J.; Lin, P.; Yao, Z.; Liang, J.

2011-12-01

In 2003, CEA (China Earthquake Administration) commenced the construction of China Digital Seismological Observation Network. By the end of 2007, a new-generation digital seismological observation system had been established, which consists of 1 National Seismic Network, 32 regional seismic networks, 2 small-aperture seismic arrays, 6 volcano monitoring networks and 19 mobile seismic networks, as well as CENC (China Earthquake Network Center) DMC (Data Management Centre) and IGP (Institute of Geophysics) DMC. Since then, the seismological observation system of China has completely entered a digital time. For operational, data backup and data security considerations, the DMC at the Institute of Geophysics (IGP), CEA was established at the end of 2007. IGP DMC now receives and archives waveform data from more than 1000 permanent seismic stations around China in real-time. After the great Wenchuan and Yushu earthquakes, the real-time waveform data from 56 and 8 portable seismic stations deployed in the aftershock area are added to IGP DMC. The technical system of IGP DMC is designed to conduct data management, processing and service through the network of CEA. We developed and integrated a hardware system with high-performance servers, large-capacity disc arrays, tape library and other facilities, as well as software packages for real-time waveform data receiving, storage, quality control, processing and service. Considering the demands from researchers for large quantities of seismic event waveform data, IGP DMC adopts an innovative "user order" method to extract event waveform data. Users can specify seismic stations, epicenter distance and record length. In a short period of 3 years, IGP DMC has supplied about 350 Terabytes waveform data to over 200 researches of more than 40 academic institutions. According to incomplete statistics, over 40 papers have been published in professional journals, in which 30 papers were indexed by SCI. Now, IGP DMC has become an important platform of promoting seismological researches in China. In the future, IGP DMC will continue to improve its technical system with powerful ability of waveform data processing, management and service, and to provide better and more data service to the research community. We expect IGP DMC to become an exchange and collaboration platform for geo-scientific researchers around the world.

Comparison of Discrete-return ranging and Full-waveform digitization for Bathymetric Lidar Mapping of a Shallow Water Bay

NASA Astrophysics Data System (ADS)

Starek, M. J.; Fernandez-diaz, J.; Pan, Z.; Glennie, C. L.; Shrestha, R. L.; Gibeaut, J. C.; Singhania, A.

2013-12-01

Researchers with the National Center for Airborne Laser Mapping (NCALM) at the University of Houston (UH) and the Coastal and Marine Geospatial Sciences Lab (CMGL) of the Harte Research Institute at Texas A&M University-Corpus Christi conducted a coordinated airborne and field-based survey of the Redfish Bay State Scientific Area to investigate the capabilities of shallow water bathymetric lidar for benthic mapping. Redfish Bay, located along the middle Texas coast of the Gulf of Mexico, is a state scientific area designated for the purposes of protecting and studying the native seagrasses. The mapped region is very shallow (< 1 m in most locations) and consists of a variety of benthic cover including sandy bottom, oyster reef, subaqueous vegetation, and submerged structures. For this survey, UH acquired high resolution (2.5 shots per square meter) bathymetry data using their new Optech Aquarius 532 nm green lidar. The field survey conducted by CMGL used an airboat to collect in-situ radiometer measurements, GPS position, depth, and ground-truth data of benthic type at over 80 locations within the bay. The return signal of an Aquarius lidar pulse is analyzed in real time by a hardware-based constant fraction discriminator (CFD) to detect returns from the surface and determine ranges (x,y,z points). This approach is commonly called discrete-return ranging, and Aquarius can record up to 4 returns per an emitted laser pulse. In contrast, full-waveform digitization records the incoming energy of an emitted pulse by sampling it at very high-frequency. Post-processing algorithms can then be applied to detect returns (ranges) from the digitized waveform. For this survey, a waveform digitizer was simultaneously operated to record the return waveforms at a rate of 1GHz with 12 bit dynamic range. High-resolution digital elevation models (DEMs) of the topo-bathymetry were derived from the discrete-return and full-waveform data to evaluate the relative and absolute accuracy using the collected ground-truth data. Results of this evaluation will be presented including an overview of the method used to extract peaks from the waveform data. Potential advantages and disadvantages of the different ranging modes in terms of observed accuracy, increased processing load, and information gain will also be discussed.

Full Seismic Waveform Tomography of the Japan region using Adjoint Methods

NASA Astrophysics Data System (ADS)

Steptoe, Hamish; Fichtner, Andreas; Rickers, Florian; Trampert, Jeannot

2013-04-01

We present a full-waveform tomographic model of the Japan region based on spectral-element wave propagation, adjoint techniques and seismic data from dense station networks. This model is intended to further our understanding of both the complex regional tectonics and the finite rupture processes of large earthquakes. The shallow Earth structure of the Japan region has been the subject of considerable tomographic investigation. The islands of Japan exist in an area of significant plate complexity: subduction related to the Pacific and Philippine Sea plates is responsible for the majority of seismicity and volcanism of Japan, whilst smaller micro-plates in the region, including the Okhotsk, and Okinawa and Amur, part of the larger North America and Eurasia plates respectively, contribute significant local intricacy. In response to the need to monitor and understand the motion of these plates and their associated faults, numerous seismograph networks have been established, including the 768 station high-sensitivity Hi-net network, 84 station broadband F-net and the strong-motion seismograph networks K-net and KiK-net in Japan. We also include the 55 station BATS network of Taiwan. We use this exceptional coverage to construct a high-resolution model of the Japan region from the full-waveform inversion of over 15,000 individual component seismograms from 53 events that occurred between 1997 and 2012. We model these data using spectral-element simulations of seismic wave propagation at a regional scale over an area from 120°-150°E and 20°-50°N to a depth of around 500 km. We quantify differences between observed and synthetic waveforms using time-frequency misfits allowing us to separate both phase and amplitude measurements whilst exploiting the complete waveform at periods of 15-60 seconds. Fréchet kernels for these misfits are calculated via the adjoint method and subsequently used in an iterative non-linear conjugate-gradient optimization. Finally, we employ custom smoothing algorithms to remove the singularities of the Fréchet kernels and artifacts introduced by the heterogeneous coverage in oceanic regions of the model.

Intrinsic frequency for a systems approach to haemodynamic waveform analysis with clinical applications

PubMed Central

Pahlevan, Niema M.; Tavallali, Peyman; Rinderknecht, Derek G.; Petrasek, Danny; Matthews, Ray V.; Hou, Thomas Y.; Gharib, Morteza

2014-01-01

The reductionist approach has dominated the fields of biology and medicine for nearly a century. Here, we present a systems science approach to the analysis of physiological waveforms in the context of a specific case, cardiovascular physiology. Our goal in this study is to introduce a methodology that allows for novel insight into cardiovascular physiology and to show proof of concept for a new index for the evaluation of the cardiovascular system through pressure wave analysis. This methodology uses a modified version of sparse time–frequency representation (STFR) to extract two dominant frequencies we refer to as intrinsic frequencies (IFs; ω1 and ω2). The IFs are the dominant frequencies of the instantaneous frequency of the coupled heart + aorta system before the closure of the aortic valve and the decoupled aorta after valve closure. In this study, we extract the IFs from a series of aortic pressure waves obtained from both clinical data and a computational model. Our results demonstrate that at the heart rate at which the left ventricular pulsatile workload is minimized the two IFs are equal (ω1 = ω2). Extracted IFs from clinical data indicate that at young ages the total frequency variation (Δω = ω1 − ω2) is close to zero and that Δω increases with age or disease (e.g. heart failure and hypertension). While the focus of this paper is the cardiovascular system, this approach can easily be extended to other physiological systems or any biological signal. PMID:25008087

Understanding Human Motion Skill with Peak Timing Synergy

NASA Astrophysics Data System (ADS)

Ueno, Ken; Furukawa, Koichi

The careful observation of motion phenomena is important in understanding the skillful human motion. However, this is a difficult task due to the complexities in timing when dealing with the skilful control of anatomical structures. To investigate the dexterity of human motion, we decided to concentrate on timing with respect to motion, and we have proposed a method to extract the peak timing synergy from multivariate motion data. The peak timing synergy is defined as a frequent ordered graph with time stamps, which has nodes consisting of turning points in motion waveforms. A proposed algorithm, PRESTO automatically extracts the peak timing synergy. PRESTO comprises the following 3 processes: (1) detecting peak sequences with polygonal approximation; (2) generating peak-event sequences; and (3) finding frequent peak-event sequences using a sequential pattern mining method, generalized sequential patterns (GSP). Here, we measured right arm motion during the task of cello bowing and prepared a data set of the right shoulder and arm motion. We successfully extracted the peak timing synergy on cello bowing data set using the PRESTO algorithm, which consisted of common skills among cellists and personal skill differences. To evaluate the sequential pattern mining algorithm GSP in PRESTO, we compared the peak timing synergy by using GSP algorithm and the one by using filtering by reciprocal voting (FRV) algorithm as a non time-series method. We found that the support is 95 - 100% in GSP, while 83 - 96% in FRV and that the results by GSP are better than the one by FRV in the reproducibility of human motion. Therefore we show that sequential pattern mining approach is more effective to extract the peak timing synergy than non-time series analysis approach.

Expanding the frontiers of waveform imaging with Salvus

NASA Astrophysics Data System (ADS)

Afanasiev, M.; Boehm, C.; van Driel, M.; Krischer, L.; Fichtner, A.

2017-12-01

Mechanical waves are natural harbingers of information. From medical ultrasound to the normal modes of Sun, wave motion is often our best window into the character of some underlying continuum. For over a century, geophysicists have been using this window to peer deep into the Earth, developing techniques that have gone on to underlie much of world's energy economy. As computers and numerical techniques have become more powerful over the last several decades, seismologists have begun to scale back classical simplifying approximations of wave propagation physics. As a result, we are now approaching the ideal of `full-waveform inversion'; maximizing the aperture of our window by taking the full complexity of wave motion into account.Salvus is a modern high-performance software suite which aims to bring recent developments in geophysical waveform inversion to new and exciting domains. In this short presentation we will look at the connections between these applications, with examples from non-destructive testing, medical imaging, seismic exploration, and (extra-) planetary seismology.

Ultrasonographic Detection of Tooth Flaws

NASA Astrophysics Data System (ADS)

Bertoncini, C. A.; Hinders, M. K.; Ghorayeb, S. R.

2010-02-01

The goal of our work is to adapt pulse-echo ultrasound into a high resolution imaging modality for early detection of oral diseases and for monitoring treatment outcome. In this talk we discuss our preliminary results in the detection of: demineralization of the enamel and dentin, demineralization or caries under and around existing restorations, caries on occlusal and interproximal surfaces, cracks of enamel and dentin, calculus, and periapical lesions. In vitro immersion tank experiments are compared to results from a handpiece which uses a compliant delay line to couple the ultrasound to the tooth surface. Because the waveform echoes are complex, and in order to make clinical interpretation of ultrasonic waveform data in real time, it is necessary to automatically interpret the signals. We apply the dynamic wavelet fingerprint algorithms to identify and delineate echographic features that correspond to the flaws of interest in teeth. The resulting features show a clear distinction between flawed and unflawed waveforms collected with an ultrasonic handpiece on both phantom and human cadaver teeth.

Improved source inversion from joint measurements of translational and rotational ground motions

NASA Astrophysics Data System (ADS)

Donner, S.; Bernauer, M.; Reinwald, M.; Hadziioannou, C.; Igel, H.

2017-12-01

Waveform inversion for seismic point (moment tensor) and kinematic sources is a standard procedure. However, especially in the local and regional distances a lack of appropriate velocity models, the sparsity of station networks, or a low signal-to-noise ratio combined with more complex waveforms hamper the successful retrieval of reliable source solutions. We assess the potential of rotational ground motion recordings to increase the resolution power and reduce non-uniquenesses for point and kinematic source solutions. Based on synthetic waveform data, we perform a Bayesian (i.e. probabilistic) inversion. Thus, we avoid the subjective selection of the most reliable solution according the lowest misfit or other constructed criterion. In addition, we obtain unbiased measures of resolution and possible trade-offs. Testing different earthquake mechanisms and scenarios, we can show that the resolution of the source solutions can be improved significantly. Especially depth dependent components show significant improvement. Next to synthetic data of station networks, we also tested sparse-network and single station cases.

Pulse transit time differential measurement by fiber Bragg grating pulse recorder.

PubMed

Umesh, Sharath; Padma, Srivani; Ambastha, Shikha; Kalegowda, Anand; Asokan, Sundarrajan

2015-05-01

The present study reports a noninvasive technique for the measurement of the pulse transit time differential (PTTD) from the pulse pressure waveforms obtained at the carotid artery and radial artery using fiber Bragg grating pulse recorders (FBGPR). PTTD is defined as the time difference between the arrivals of a pulse pressure waveform at the carotid and radial arterial sites. The PTTD is investigated as an indicator of variation in the systolic blood pressure. The results are validated against blood pressure variation obtained from a Mindray Patient Monitor. Furthermore, the pulse wave velocity computed from the obtained PTTD is compared with the pulse wave velocity obtained from the color Doppler ultrasound system and is found to be in good agreement. The major advantage of the PTTD measurement via FBGPRs is that the data acquisition system employed can simultaneously acquire pulse pressure waveforms from both FBGPRs placed at carotid and radial arterial sites with a single time scale, which eliminates time synchronization complexity.

The 2017 North Korea M6 seismic sequence: moment tensor, source time function, and aftershocks

NASA Astrophysics Data System (ADS)

Ni, S.; Zhan, Z.; Chu, R.; He, X.

2017-12-01

On September 3rd, 2017, an M6 seismic event occurred in North Korea, with location near previous nuclear test sites. The event features strong P waves and short period Rayleigh waves are observed in contrast to weak S waves, suggesting mostly explosion mechanism. We performed joint inversion for moment tensor and depth with both local and teleseismic waveforms, and find that the event is shallow with mostly isotropic yet substantial non-isotropic components. Deconvolution of seismic waveforms of this event with respect to previous nuclear test events shows clues of complexity in source time function. The event is followed by smaller earthquakes, as early as 8.5 minutes and lasted at least to October. The later events occurred in a compact region, and show clear S waves, suggesting double couple focal mechanism. Via analyzing Rayleigh wave spectrum, these smaller events are found to be shallow. Relative locations, difference in waveforms of the events are used to infer their possible links and generation mechanism.

Seismological constraints on the down-dip shape of normal faults

NASA Astrophysics Data System (ADS)

Reynolds, Kirsty; Copley, Alex

2018-04-01

We present a seismological technique for determining the down-dip shape of seismogenic normal faults. Synthetic models of non-planar source geometries reveal the important signals in teleseismic P and SH waveforms that are diagnostic of down-dip curvature. In particular, along-strike SH waveforms are the most sensitive to variations in source geometry, and have significantly more complex and larger-amplitude waveforms for curved source geometries than planar ones. We present the results of our forward-modelling technique for 13 earthquakes. Most continental normal-faulting earthquakes that rupture through the full seismogenic layer are planar and have dips of 30°-60°. There is evidence for faults with a listric shape from some of the earthquakes occurring in two regions; Tibet and East Africa. These ruptures occurred on antithetic faults, or minor faults within the hanging walls of the rifts affected, which may suggest a reason for the down-dip curvature. For these earthquakes, the change in dip across the seismogenic part of the fault plane is ≤30°.

Robust breathing signal extraction from cone beam CT projections based on adaptive and global optimization techniques

PubMed Central

Chao, Ming; Wei, Jie; Li, Tianfang; Yuan, Yading; Rosenzweig, Kenneth E; Lo, Yeh-Chi

2017-01-01

We present a study of extracting respiratory signals from cone beam computed tomography (CBCT) projections within the framework of the Amsterdam Shroud (AS) technique. Acquired prior to the radiotherapy treatment, CBCT projections were preprocessed for contrast enhancement by converting the original intensity images to attenuation images with which the AS image was created. An adaptive robust z-normalization filtering was applied to further augment the weak oscillating structures locally. From the enhanced AS image, the respiratory signal was extracted using a two-step optimization approach to effectively reveal the large-scale regularity of the breathing signals. CBCT projection images from five patients acquired with the Varian Onboard Imager on the Clinac iX System Linear Accelerator (Varian Medical Systems, Palo Alto, CA) were employed to assess the proposed technique. Stable breathing signals can be reliably extracted using the proposed algorithm. Reference waveforms obtained using an air bellows belt (Philips Medical Systems, Cleveland, OH) were exported and compared to those with the AS based signals. The average errors for the enrolled patients between the estimated breath per minute (bpm) and the reference waveform bpm can be as low as −0.07 with the standard deviation 1.58. The new algorithm outperformed the original AS technique for all patients by 8.5% to 30%. The impact of gantry rotation on the breathing signal was assessed with data acquired with a Quasar phantom (Modus Medical Devices Inc., London, Canada) and found to be minimal on the signal frequency. The new technique developed in this work will provide a practical solution to rendering markerless breathing signal using the CBCT projections for thoracic and abdominal patients. PMID:27008349

Single-trial laser-evoked potentials feature extraction for prediction of pain perception.

PubMed

Huang, Gan; Xiao, Ping; Hu, Li; Hung, Yeung Sam; Zhang, Zhiguo

2013-01-01

Pain is a highly subjective experience, and the availability of an objective assessment of pain perception would be of great importance for both basic and clinical applications. The objective of the present study is to develop a novel approach to extract pain-related features from single-trial laser-evoked potentials (LEPs) for classification of pain perception. The single-trial LEP feature extraction approach combines a spatial filtering using common spatial pattern (CSP) and a multiple linear regression (MLR). The CSP method is effective in separating laser-evoked EEG response from ongoing EEG activity, while MLR is capable of automatically estimating the amplitudes and latencies of N2 and P2 from single-trial LEP waveforms. The extracted single-trial LEP features are used in a Naïve Bayes classifier to classify different levels of pain perceived by the subjects. The experimental results show that the proposed single-trial LEP feature extraction approach can effectively extract pain-related LEP features for achieving high classification accuracy.

Tomographic inversion of P-wave velocity and Q structures beneath the Kirishima volcanic complex, Southern Japan, based on finite difference calculations of complex traveltimes

USGS Publications Warehouse

Tomatsu, T.; Kumagai, H.; Dawson, P.B.

2001-01-01

We estimate the P-wave velocity and attenuation structures beneath the Kirishima volcanic complex, southern Japan, by inverting the complex traveltimes (arrival times and pulse widths) of waveform data obtained during an active seismic experiment conducted in 1994. In this experiment, six 200-250 kg shots were recorded at 163 temporary seismic stations deployed on the volcanic complex. We use first-arrival times for the shots, which were hand-measured interactively. The waveform data are Fourier transformed into the frequency domain and analysed using a new method based on autoregressive modelling of complex decaying oscillations in the frequency domain to determine pulse widths for the first-arrival phases. A non-linear inversion method is used to invert 893 first-arrival times and 325 pulse widths to estimate the velocity and attenuation structures of the volcanic complex. Wavefronts for the inversion are calculated with a finite difference method based on the Eikonal equation, which is well suited to estimating the complex traveltimes for the structures of the Kirishima volcano complex, where large structural heterogeneities are expected. The attenuation structure is derived using ray paths derived from the velocity structure. We obtain 3-D velocity and attenuation structures down to 1.5 and 0.5 km below sea level, respectively. High-velocity pipe-like structures with correspondingly low attenuation are found under the summit craters. These pipe-like structures are interpreted as remnant conduits of solidified magma. No evidence of a shallow magma chamber is visible in the tomographic images.

Inversion of ocean-bottom seismometer (OBS) waveforms for oceanic crust structure: a synthetic study

NASA Astrophysics Data System (ADS)

Li, Xueyan; Wang, Yanbin; Chen, Yongshun John

2016-08-01

The waveform inversion method is applied—using synthetic ocean-bottom seismometer (OBS) data—to study oceanic crust structure. A niching genetic algorithm (NGA) is used to implement the inversion for the thickness and P-wave velocity of each layer, and to update the model by minimizing the objective function, which consists of the misfit and cross-correlation of observed and synthetic waveforms. The influence of specific NGA method parameters is discussed, and suitable values are presented. The NGA method works well for various observation systems, such as those with irregular and sparse distribution of receivers as well as single receiver systems. A strategy is proposed to accelerate the convergence rate by a factor of five with no increase in computational complexity; this is achieved using a first inversion with several generations to impose a restriction on the preset range of each parameter and then conducting a second inversion with the new range. Despite the successes of this method, its usage is limited. A shallow water layer is not favored because the direct wave in water will suppress the useful reflection signals from the crust. A more precise calculation of the air-gun source signal should be considered in order to better simulate waveforms generated in realistic situations; further studies are required to investigate this issue.

Vibrotactile Discrimination of Musical Timbre

ERIC Educational Resources Information Center

Russo, Frank A.; Ammirante, Paolo; Fels, Deborah I.

2012-01-01

Five experiments investigated the ability to discriminate between musical timbres based on vibrotactile stimulation alone. Participants made same/different judgments on pairs of complex waveforms presented sequentially to the back through voice coils embedded in a conforming chair. Discrimination between cello, piano, and trombone tones matched…

Golay Complementary Waveforms in Reed–Müller Sequences for Radar Detection of Nonzero Doppler Targets

PubMed Central

Wang, Xuezhi; Huang, Xiaotao; Suvorova, Sofia; Moran, Bill

2018-01-01

Golay complementary waveforms can, in theory, yield radar returns of high range resolution with essentially zero sidelobes. In practice, when deployed conventionally, while high signal-to-noise ratios can be achieved for static target detection, significant range sidelobes are generated by target returns of nonzero Doppler causing unreliable detection. We consider signal processing techniques using Golay complementary waveforms to improve radar detection performance in scenarios involving multiple nonzero Doppler targets. A signal processing procedure based on an existing, so called, Binomial Design algorithm that alters the transmission order of Golay complementary waveforms and weights the returns is proposed in an attempt to achieve an enhanced illumination performance. The procedure applies one of three proposed waveform transmission ordering algorithms, followed by a pointwise nonlinear processor combining the outputs of the Binomial Design algorithm and one of the ordering algorithms. The computational complexity of the Binomial Design algorithm and the three ordering algorithms are compared, and a statistical analysis of the performance of the pointwise nonlinear processing is given. Estimation of the areas in the Delay–Doppler map occupied by significant range sidelobes for given targets are also discussed. Numerical simulations for the comparison of the performances of the Binomial Design algorithm and the three ordering algorithms are presented for both fixed and randomized target locations. The simulation results demonstrate that the proposed signal processing procedure has a better detection performance in terms of lower sidelobes and higher Doppler resolution in the presence of multiple nonzero Doppler targets compared to existing methods. PMID:29324708

Electrophysiological and morphological features underlying neurotransmission efficacy at the splanchnic nerve-chromaffin cell synapse of bovine adrenal medulla.

PubMed

de Diego, Antonio M G

2010-02-01

The ability of adrenal chromaffin cells to fast-release catecholamines relies on their capacity to fire action potentials (APs). However, little attention has been paid to the requirements needed to evoke the controlled firing of APs. Few data are available in rodents and none on the bovine chromaffin cell, a model extensively used by researchers. The aim of this work was to clarify this issue. Short puffs of acetylcholine (ACh) were fast perifused to current-clamped chromaffin cells and produced the firing of single APs. Based on the currents generated by such ACh applications and previous literature, current waveforms that efficiently elicited APs at frequencies up to 20 Hz were generated. Complex waveforms were also generated by adding simple waveforms with different delays; these waveforms aimed at modeling the stimulation patterns that a chromaffin cell would conceivably undergo upon strong synaptic stimulation. Cholinergic innervation was assessed using the acetylcholinesterase staining technique on the supposition that the innervation pattern is a determinant of the kind of stimuli chromaffin cells can receive. It is concluded that 1) a reliable method to produce frequency-controlled APs by applying defined current injection waveforms is achieved; 2) the APs thus generated have essentially the same features as those spontaneously emitted by the cell and those elicited by fast-ACh perifusion; 3) the higher frequencies attainable peak at around 30 Hz; and 4) the bovine adrenal medulla shows abundant cholinergic innervation, and chromaffin cells show strong acetylcholinesterase staining, consistent with a tight cholinergic presynaptic control of firing frequency.

Infrasound Waveform Inversion and Mass Flux Validation from Sakurajima Volcano, Japan

NASA Astrophysics Data System (ADS)

Fee, D.; Kim, K.; Yokoo, A.; Izbekov, P. E.; Lopez, T. M.; Prata, F.; Ahonen, P.; Kazahaya, R.; Nakamichi, H.; Iguchi, M.

2015-12-01

Recent advances in numerical wave propagation modeling and station coverage have permitted robust inversion of infrasound data from volcanic explosions. Complex topography and crater morphology have been shown to substantially affect the infrasound waveform, suggesting that homogeneous acoustic propagation assumptions are invalid. Infrasound waveform inversion provides an exciting tool to accurately characterize emission volume and mass flux from both volcanic and non-volcanic explosions. Mass flux, arguably the most sought-after parameter from a volcanic eruption, can be determined from the volume flux using infrasound waveform inversion if the volcanic flow is well-characterized. Thus far, infrasound-based volume and mass flux estimates have yet to be validated. In February 2015 we deployed six infrasound stations around the explosive Sakurajima Volcano, Japan for 8 days. Here we present our full waveform inversion method and volume and mass flux estimates of numerous high amplitude explosions using a high resolution DEM and 3-D Finite Difference Time Domain modeling. Application of this technique to volcanic eruptions may produce realistic estimates of mass flux and plume height necessary for volcanic hazard mitigation. Several ground-based instruments and methods are used to independently determine the volume, composition, and mass flux of individual volcanic explosions. Specifically, we use ground-based ash sampling, multispectral infrared imagery, UV spectrometry, and multigas data to estimate the plume composition and flux. Unique tiltmeter data from underground tunnels at Sakurajima also provides a way to estimate the volume and mass of each explosion. In this presentation we compare the volume and mass flux estimates derived from the different methods and discuss sources of error and future improvements.

Detecting earthquakes over a seismic network using single-station similarity measures

NASA Astrophysics Data System (ADS)

Bergen, Karianne J.; Beroza, Gregory C.

2018-06-01

New blind waveform-similarity-based detection methods, such as Fingerprint and Similarity Thresholding (FAST), have shown promise for detecting weak signals in long-duration, continuous waveform data. While blind detectors are capable of identifying similar or repeating waveforms without templates, they can also be susceptible to false detections due to local correlated noise. In this work, we present a set of three new methods that allow us to extend single-station similarity-based detection over a seismic network; event-pair extraction, pairwise pseudo-association, and event resolution complete a post-processing pipeline that combines single-station similarity measures (e.g. FAST sparse similarity matrix) from each station in a network into a list of candidate events. The core technique, pairwise pseudo-association, leverages the pairwise structure of event detections in its network detection model, which allows it to identify events observed at multiple stations in the network without modeling the expected moveout. Though our approach is general, we apply it to extend FAST over a sparse seismic network. We demonstrate that our network-based extension of FAST is both sensitive and maintains a low false detection rate. As a test case, we apply our approach to 2 weeks of continuous waveform data from five stations during the foreshock sequence prior to the 2014 Mw 8.2 Iquique earthquake. Our method identifies nearly five times as many events as the local seismicity catalogue (including 95 per cent of the catalogue events), and less than 1 per cent of these candidate events are false detections.

Extraction of nonlinear waveform in turbulent plasma

NASA Astrophysics Data System (ADS)

Kin, F.; Itoh, K.; Fujisawa, A.; Kosuga, Y.; Sasaki, M.; Yamada, T.; Inagaki, S.; Itoh, S.-I.; Kobayashi, T.; Nagashima, Y.; Kasuya, N.; Arakawa, H.; Yamasaki, K.; Hasamada, K.

2018-06-01

Streamers and their mediator have been known to exist in linear cylindrical plasmas [Yamada et al., Nat. Phys. 4, 721 (2008)]. Conditional averaging is applied to extract the nonlinear characteristics of a mediator, which has been simply treated as a linear wave. This paper reports that a mediator should have higher harmonic components generated by self-couplings, and the envelope of a streamer should be generated with not only fundamental but also higher harmonic components of the mediator. Moreover, both the mediator and the envelope of the streamer have common features with solitary waves, i.e., the height should increase inversely as the square of their localization width.

Speech transformation system (spectrum and/or excitation) without pitch extraction

NASA Astrophysics Data System (ADS)

Seneff, S.

1980-07-01

A speech analysis synthesis system was developed which is capable of independent manipulation of the fundamental frequency and spectral envelope of a speech waveform. The system deconvolved the original speech with the spectral envelope estimate to obtain a model for the excitation, explicit pitch extraction was not required and as a consequence, the transformed speech was more natural sounding than would be the case if the excitation were modeled as a sequence of pulses. It is shown that the system has applications in the areas of voice modifications, baseband excited vocoders, time scale modifications, and frequency compression as an aid to the partially deaf.

Robust spike classification based on frequency domain neural waveform features.

PubMed

Yang, Chenhui; Yuan, Yuan; Si, Jennie

2013-12-01

We introduce a new spike classification algorithm based on frequency domain features of the spike snippets. The goal for the algorithm is to provide high classification accuracy, low false misclassification, ease of implementation, robustness to signal degradation, and objectivity in classification outcomes. In this paper, we propose a spike classification algorithm based on frequency domain features (CFDF). It makes use of frequency domain contents of the recorded neural waveforms for spike classification. The self-organizing map (SOM) is used as a tool to determine the cluster number intuitively and directly by viewing the SOM output map. After that, spike classification can be easily performed using clustering algorithms such as the k-Means. In conjunction with our previously developed multiscale correlation of wavelet coefficient (MCWC) spike detection algorithm, we show that the MCWC and CFDF detection and classification system is robust when tested on several sets of artificial and real neural waveforms. The CFDF is comparable to or outperforms some popular automatic spike classification algorithms with artificial and real neural data. The detection and classification of neural action potentials or neural spikes is an important step in single-unit-based neuroscientific studies and applications. After the detection of neural snippets potentially containing neural spikes, a robust classification algorithm is applied for the analysis of the snippets to (1) extract similar waveforms into one class for them to be considered coming from one unit, and to (2) remove noise snippets if they do not contain any features of an action potential. Usually, a snippet is a small 2 or 3 ms segment of the recorded waveform, and differences in neural action potentials can be subtle from one unit to another. Therefore, a robust, high performance classification system like the CFDF is necessary. In addition, the proposed algorithm does not require any assumptions on statistical properties of the noise and proves to be robust under noise contamination.

Topics in the Detection of Gravitational Waves from Compact Binary Inspirals

NASA Astrophysics Data System (ADS)

Kapadia, Shasvath Jagat

Orbiting compact binaries - such as binary black holes, binary neutron stars and neutron star-black hole binaries - are among the most promising sources of gravitational waves observable by ground-based interferometric detectors. Despite numerous sophisticated engineering techniques, the gravitational wave signals will be buried deep within noise generated by various instrumental and environmental processes, and need to be extracted via a signal processing technique referred to as matched filtering. Matched filtering requires large banks of signal templates that are faithful representations of the true gravitational waveforms produced by astrophysical binaries. The accurate and efficient production of templates is thus crucial to the success of signal processing and data analysis. To that end, the dissertation presents a numerical technique that calibrates existing analytical (Post-Newtonian) waveforms, which are relatively inexpensive, to more accurate fiducial waveforms that are computationally expensive to generate. The resulting waveform family is significantly more accurate than the analytical waveforms, without incurring additional computational costs of production. Certain kinds of transient background noise artefacts, called "glitches'', can masquerade as gravitational wave signals for short durations and throw-off the matched-filter algorithm. Identifying glitches from true gravitational wave signals is a highly non-trivial exercise in data analysis which has been attempted with varying degrees of success. We present here a machine-learning based approach that exploits the various attributes of glitches and signals within detector data to provide a classification scheme that is a significant improvement over previous methods. The dissertation concludes by investigating the possibility of detecting a non-linear DC imprint, called the Christodoulou memory, produced in the arms of ground-based interferometers by the recently detected gravitational waves. The memory, which is even smaller in amplitude than the primary (detected) gravitational waves, will almost certainly not be seen in the current detection event. Nevertheless, future space-based detectors will likely be sensitive enough to observe the memory.

A wideband software reconfigurable modem

NASA Astrophysics Data System (ADS)

Turner, J. H., Jr.; Vickers, H.

A wideband modem is described which provides signal processing capability for four Lx-band signals employing QPSK, MSK and PPM waveforms and employs a software reconfigurable architecture for maximum system flexibility and graceful degradation. The current processor uses a 2901 and two 8086 microprocessors per channel and performs acquisition, tracking, and data demodulation for JITDS, GPS, IFF and TACAN systems. The next generation processor will be implemented using a VHSIC chip set employing a programmable complex array vector processor module, a GP computer module, customized gate array modules, and a digital array correlator. This integrated processor has application to a wide number of diverse system waveforms, and will bring the benefits of VHSIC technology insertion into avionic antijam communications systems.

Including Short Period Constraints In the Construction of Full Waveform Tomographic Models

NASA Astrophysics Data System (ADS)

Roy, C.; Calo, M.; Bodin, T.; Romanowicz, B. A.

2015-12-01

Thanks to the introduction of the Spectral Element Method (SEM) in seismology, which allows accurate computation of the seismic wavefield in complex media, the resolution of regional and global tomographic models has improved in recent years. However, due to computational costs, only long period waveforms are considered, and only long wavelength structure can be constrained. Thus, the resulting 3D models are smooth, and only represent a small volumetric perturbation around a smooth reference model that does not include upper-mantle discontinuities (e.g. MLD, LAB). Extending the computations to shorter periods, necessary for the resolution of smaller scale features, is computationally challenging. In order to overcome these limitations and to account for layered structure in the upper mantle in our full waveform tomography, we include information provided by short period seismic observables (receiver functions and surface wave dispersion), sensitive to sharp boundaries and anisotropic structure respectively. In a first step, receiver functions and dispersion curves are used to generate a number of 1D radially anisotropic shear velocity profiles using a trans-dimensional Markov-chain Monte Carlo (MCMC) algorithm. These 1D profiles include both isotropic and anisotropic discontinuities in the upper mantle (above 300 km depth) beneath selected stationsand are then used to build a 3D starting model for the full waveform tomographic inversion. This model is built after 1) interpolation between the available 1D profiles, and 2) homogeneization of the layered 1D models to obtain an equivalent smooth 3D starting model in the period range of interest for waveform inversion. The waveforms used in the inversion are collected for paths contained in the region of study and filtered at periods longer than 40s. We use the spectral element code "RegSEM" (Cupillard et al., 2012) for forward computations and a quasi-Newton inversion approach in which kernels are computed using normal mode perturbation theory. We present here the first reults of such an approach after successive iterations of a full waveform tomography of the North American continent.

Integration of ALS and TLS for calibration and validation of LAI profiles from large footprint lidar

NASA Astrophysics Data System (ADS)

Armston, J.; Tang, H.; Hancock, S.; Hofton, M. A.; Dubayah, R.; Duncanson, L.; Fatoyinbo, T. E.; Blair, J. B.; Disney, M.

2016-12-01

The Global Ecosystem Dynamics Investigation (GEDI) is designed to provide measurements of forest vertical structure and above-ground biomass density (AGBD) over tropical and temperate regions. The GEDI is a multi-beam waveform lidar that will acquire transects of forest canopy vertical profiles in conditions of up to 99% canopy cover. These are used to produce a number of canopy height and profile metrics to model habitat suitability and AGBD. These metrics include vertical leaf area index (LAI) profiles, which require some pre-launch refinement of large-footprint waveform processing methods for separating canopy and ground returns and estimation of their reflectance. Previous research developments in modelling canopy gap probability to derive canopy and ground reflectance from waveforms have primarily used data from small-footprint instruments, however development of a generalized spatial model with uncertainty will be useful for interpreting and modelling waveforms from large-footprint instruments such as the NASA Land Vegetation and Ice Sensor (LVIS) with a view to implementation for GEDI. Here we present an analysis of waveform lidar data from the NASA Land Vegetation and Ice Sensor (LVIS), which were acquired in Gabon in February 2016 to support the NASA/ESA AfriSAR campaign. AfriSAR presents a unique opportunity to test refined methods for retrieval of LAI profiles in high above-ground biomass rainforests (up to 600 Mg/ha) with dense canopies (>90% cover), where the greatest uncertainty exists. Airborne and Terrestrial Laser Scanning data (TLS) were also collected, enabling quantification of algorithm performance in plots of dense canopy cover. Refinement of canopy gap probability and LAI profile modelling from large-footprint lidar was based on solving for canopy and ground reflectance parameters spatially by penalized least-squares. The sensitivities of retrieved cover and LAI profiles to variation in canopy and ground reflectance showed improvement compared to assuming a constant ratio. We evaluated the use of spatially proximate simple waveforms to interpret more complex waveforms with poor separation of canopy and ground returns. This work has direct implications for GEDI algorithm refinement.

Self-referenced single-shot THz detection

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

Russell, Brandon K.; Ofori-Okai, Benjamin K.; Chen, Zhijiang

We demonstrate a self-referencing method to reduce noise in a single-shot terahertz detection scheme. By splitting a single terahertz pulse and using a reflective echelon, both the signal and reference terahertz time-domain waveforms were measured using one laser pulse. Simultaneous acquisition of these waveforms significantly reduces noise originating from shot-to-shot fluctuations. Here, we show that correlation function based referencing, which is not limited to polarization dependent measurements, can achieve a noise floor that is comparable to state-of-the-art polarization-gated balanced detection. Lastly, we extract the DC conductivity of a 30 nm free-standing gold film using a single THz pulse. The measuredmore » value of σ 0 = 1.3 ± 0.4 × 10 7 S m -1 is in good agreement with the value measured by four-point probe, indicating the viability of this method for measuring dynamical changes and small signals.« less

Self-referenced single-shot THz detection

DOE PAGES

Russell, Brandon K.; Ofori-Okai, Benjamin K.; Chen, Zhijiang; ...

2017-06-29

We demonstrate a self-referencing method to reduce noise in a single-shot terahertz detection scheme. By splitting a single terahertz pulse and using a reflective echelon, both the signal and reference terahertz time-domain waveforms were measured using one laser pulse. Simultaneous acquisition of these waveforms significantly reduces noise originating from shot-to-shot fluctuations. Here, we show that correlation function based referencing, which is not limited to polarization dependent measurements, can achieve a noise floor that is comparable to state-of-the-art polarization-gated balanced detection. Lastly, we extract the DC conductivity of a 30 nm free-standing gold film using a single THz pulse. The measuredmore » value of σ 0 = 1.3 ± 0.4 × 10 7 S m -1 is in good agreement with the value measured by four-point probe, indicating the viability of this method for measuring dynamical changes and small signals.« less

Improvement on Gabor order tracking and objective comparison with Vold Kalman filtering order tracking

NASA Astrophysics Data System (ADS)

Pan, Min-Chun; Liao, Shiu-Wei; Chiu, Chun-Chin

2007-02-01

The waveform-reconstruction schemes of order tracking (OT) such as the Gabor and the Vold-Kalman filtering (VKF) techniques can extract specific order and/or spectral components in addition to characterizing the processed signal in rpm-frequency domain. The study first improves the Gabor OT (GOT) technique to handle the order-crossing problem, and then objectively compares the features of the improved GOT scheme and the angular-displacement VKF OT technique. It is numerically observed the improved method performs less accurately than the VKF_OT scheme at the crossing occurrences, but without end effect in the reconstructed waveform. As OT is not exact science, it may well be that the decrease in computation time can justify the reduced accuracy. The characterisation and discrimination of riding noise with crossing orders emitted by an electrical scooter are conducted as an example of the application.

Implementation of a portable device for real-time ECG signal analysis.

PubMed

Jeon, Taegyun; Kim, Byoungho; Jeon, Moongu; Lee, Byung-Geun

2014-12-10

Cardiac disease is one of the main causes of catastrophic mortality. Therefore, detecting the symptoms of cardiac disease as early as possible is important for increasing the patient's survival. In this study, a compact and effective architecture for detecting atrial fibrillation (AFib) and myocardial ischemia is proposed. We developed a portable device using this architecture, which allows real-time electrocardiogram (ECG) signal acquisition and analysis for cardiac diseases. A noisy ECG signal was preprocessed by an analog front-end consisting of analog filters and amplifiers before it was converted into digital data. The analog front-end was minimized to reduce the size of the device and power consumption by implementing some of its functions with digital filters realized in software. With the ECG data, we detected QRS complexes based on wavelet analysis and feature extraction for morphological shape and regularity using an ARM processor. A classifier for cardiac disease was constructed based on features extracted from a training dataset using support vector machines. The classifier then categorized the ECG data into normal beats, AFib, and myocardial ischemia. A portable ECG device was implemented, and successfully acquired and processed ECG signals. The performance of this device was also verified by comparing the processed ECG data with high-quality ECG data from a public cardiac database. Because of reduced computational complexity, the ARM processor was able to process up to a thousand samples per second, and this allowed real-time acquisition and diagnosis of heart disease. Experimental results for detection of heart disease showed that the device classified AFib and ischemia with a sensitivity of 95.1% and a specificity of 95.9%. Current home care and telemedicine systems have a separate device and diagnostic service system, which results in additional time and cost. Our proposed portable ECG device provides captured ECG data and suspected waveform to identify sporadic and chronic events of heart diseases. This device has been built and evaluated for high quality of signals, low computational complexity, and accurate detection.

Electric organ discharges and near-field spatiotemporal patterns of the electromotive force in a sympatric assemblage of Neotropical electric knifefish.

PubMed

Waddell, Joseph C; Rodríguez-Cattáneo, Alejo; Caputi, Angel A; Crampton, William G R

2016-10-01

Descriptions of the head-to-tail electric organ discharge (ht-EOD) waveform - typically recorded with electrodes at a distance of approximately 1-2 body lengths from the center of the subject - have traditionally been used to characterize species diversity in gymnotiform electric fish. However, even taxa with relatively simple ht-EODs show spatiotemporally complex fields near the body surface that are determined by site-specific electrogenic properties of the electric organ and electric filtering properties of adjacent tissues and skin. In Brachyhypopomus, a pulse-discharging genus in the family Hypopomidae, the regional characteristics of the electric organ and the role that the complex 'near field' plays in communication and/or electrolocation are not well known. Here we describe, compare, and discuss the functional significance of diversity in the ht-EOD waveforms and near-field spatiotemporal patterns of the electromotive force (emf-EODs) among a species-rich sympatric community of Brachyhypopomus from the upper Amazon. Copyright © 2016 Elsevier Ltd. All rights reserved.

Improvement of Quantitative Measurements in Multiplex Proteomics Using High-Field Asymmetric Waveform Spectrometry.

PubMed

Pfammatter, Sibylle; Bonneil, Eric; Thibault, Pierre

2016-12-02

Quantitative proteomics using isobaric reagent tandem mass tags (TMT) or isobaric tags for relative and absolute quantitation (iTRAQ) provides a convenient approach to compare changes in protein abundance across multiple samples. However, the analysis of complex protein digests by isobaric labeling can be undermined by the relative large proportion of co-selected peptide ions that lead to distorted reporter ion ratios and affect the accuracy and precision of quantitative measurements. Here, we investigated the use of high-field asymmetric waveform ion mobility spectrometry (FAIMS) in proteomic experiments to reduce sample complexity and improve protein quantification using TMT isobaric labeling. LC-FAIMS-MS/MS analyses of human and yeast protein digests led to significant reductions in interfering ions, which increased the number of quantifiable peptides by up to 68% while significantly improving the accuracy of abundance measurements compared to that with conventional LC-MS/MS. The improvement in quantitative measurements using FAIMS is further demonstrated for the temporal profiling of protein abundance of HEK293 cells following heat shock treatment.

An automated approach towards detecting complex behaviours in deep brain oscillations.

PubMed

Mace, Michael; Yousif, Nada; Naushahi, Mohammad; Abdullah-Al-Mamun, Khondaker; Wang, Shouyan; Nandi, Dipankar; Vaidyanathan, Ravi

2014-03-15

Extracting event-related potentials (ERPs) from neurological rhythms is of fundamental importance in neuroscience research. Standard ERP techniques typically require the associated ERP waveform to have low variance, be shape and latency invariant and require many repeated trials. Additionally, the non-ERP part of the signal needs to be sampled from an uncorrelated Gaussian process. This limits methods of analysis to quantifying simple behaviours and movements only when multi-trial data-sets are available. We introduce a method for automatically detecting events associated with complex or large-scale behaviours, where the ERP need not conform to the aforementioned requirements. The algorithm is based on the calculation of a detection contour and adaptive threshold. These are combined using logical operations to produce a binary signal indicating the presence (or absence) of an event with the associated detection parameters tuned using a multi-objective genetic algorithm. To validate the proposed methodology, deep brain signals were recorded from implanted electrodes in patients with Parkinson's disease as they participated in a large movement-based behavioural paradigm. The experiment involved bilateral recordings of local field potentials from the sub-thalamic nucleus (STN) and pedunculopontine nucleus (PPN) during an orientation task. After tuning, the algorithm is able to extract events achieving training set sensitivities and specificities of [87.5 ± 6.5, 76.7 ± 12.8, 90.0 ± 4.1] and [92.6 ± 6.3, 86.0 ± 9.0, 29.8 ± 12.3] (mean ± 1 std) for the three subjects, averaged across the four neural sites. Furthermore, the methodology has the potential for utility in real-time applications as only a single-trial ERP is required. Copyright © 2013 Elsevier B.V. All rights reserved.

Frequency spectrum analysis of finger photoplethysmographic waveform variability during haemodialysis.

PubMed

Javed, Faizan; Middleton, Paul M; Malouf, Philip; Chan, Gregory S H; Savkin, Andrey V; Lovell, Nigel H; Steel, Elizabeth; Mackie, James

2010-09-01

This study investigates the peripheral circulatory and autonomic response to volume withdrawal in haemodialysis based on spectral analysis of photoplethysmographic waveform variability (PPGV). Frequency spectrum analysis was performed on the baseline and pulse amplitude variabilities of the finger infrared photoplethysmographic (PPG) waveform and on heart rate variability extracted from the ECG signal collected from 18 kidney failure patients undergoing haemodialysis. Spectral powers were calculated from the low frequency (LF, 0.04-0.145 Hz) and high frequency (HF, 0.145-0.45 Hz) bands. In eight stable fluid overloaded patients (fluid removal of >2 L) not on alpha blockers, progressive reduction in relative blood volume during haemodialysis resulted in significant increase in LF and HF powers of PPG baseline and amplitude variability (P < 0.01), when expressed in mean-scaled units. The augmentation of LF powers in PPGV during haemodialysis may indicate the recovery and possibly further enhancement of peripheral sympathetic vascular modulation subsequent to volume unloading, whilst the increase in respiratory HF power in PPGV is most likely a sign of preload reduction. Spectral analysis of finger PPGV may provide valuable information on the autonomic vascular response to blood volume reduction in haemodialysis, and can be potentially utilized as a non-invasive tool for assessing peripheral circulatory control during routine dialysis procedure.

Envelope filter sequence to delete blinks and overshoots.

PubMed

Merino, Manuel; Gómez, Isabel María; Molina, Alberto J

2015-05-30

Eye movements have been used in control interfaces and as indicators of somnolence, workload and concentration. Different techniques can be used to detect them: we focus on the electrooculogram (EOG) in which two kinds of interference occur: blinks and overshoots. While they both draw bell-shaped waveforms, blinks are caused by the eyelid, whereas overshoots occur due to target localization error and are placed on saccade. They need to be extracted from the EOG to increase processing effectiveness. This paper describes off- and online processing implementations based on lower envelope for removing bell-shaped noise; they are compared with a 300-ms-median filter. Techniques were analyzed using two kinds of EOG data: those modeled from our own design, and real signals. Using a model signal allowed to compare filtered outputs with ideal data, so that it was possible to quantify processing precision to remove noise caused by blinks, overshoots, and general interferences. We analyzed the ability to delete blinks and overshoots, and waveform preservation. Our technique had a high capacity for reducing interference amplitudes (>97%), even exceeding median filter (MF) results. However, the MF obtained better waveform preservation, with a smaller dependence on fixation width. The proposed technique is better at deleting blinks and overshoots than the MF in model and real EOG signals.

Non-contact arrhythmia assessment in natural settings: a step toward preventive cardiac care

NASA Astrophysics Data System (ADS)

Amelard, Robert; Hughson, Richard L.; Clausi, David A.; Wong, Alexander

2017-02-01

Cardiovascular disease is a major contributor to US morbidity. Taking preventive action can greatly reduce or eliminate the impact on quality of life. However, many issues often go undetected until the patient presents a physical symptom. Non-intrusive continuous cardiovascular monitoring systems may make detecting and monitoring abnormalities earlier feasible. One candidate system is photoplethysmographic imaging (PPGI), which is able to assess arterial blood pulse characteristics in one or multiple individuals remotely from a distance. In this case study, we showed that PPGI can be used to detect cardiac arrhythmia that would otherwise require contact-based monitoring techniques. Using a novel system, coded hemodynamic imaging (CHI), strong temporal blood pulse waveform signals were extracted at a distance of 1.5 m from the participant using 850-1000 nm diffuse illumination for deep tissue penetration. Data were recorded at a sampling rate of 60 Hz, providing a temporal resolution of 17 ms. The strong fidelity of the signal allowed for both temporal and spectral assessment of abnormal blood pulse waveforms, ultimately to detect the onset of abnormal cardiac events. Data from a participant with arrhythmia was analyzed and compared against normal blood pulse waveform data to validate CHI's ability to assess cardiac arrhythmia. Results indicate that CHI can be used as a non-intrusive continuous cardiac monitoring system.

Moment tensor inversions using strong motion waveforms of Taiwan TSMIP data, 1993–2009

USGS Publications Warehouse

Chang, Kaiwen; Chi, Wu-Cheng; Gung, Yuancheng; Dreger, Douglas; Lee, William H K.; Chiu, Hung-Chie

2011-01-01

Earthquake source parameters are important for earthquake studies and seismic hazard assessment. Moment tensors are among the most important earthquake source parameters, and are now routinely derived using modern broadband seismic networks around the world. Similar waveform inversion techniques can also apply to other available data, including strong-motion seismograms. Strong-motion waveforms are also broadband, and recorded in many regions since the 1980s. Thus, strong-motion data can be used to augment moment tensor catalogs with a much larger dataset than that available from the high-gain, broadband seismic networks. However, a systematic comparison between the moment tensors derived from strong motion waveforms and high-gain broadband waveforms has not been available. In this study, we inverted the source mechanisms of Taiwan earthquakes between 1993 and 2009 by using the regional moment tensor inversion method using digital data from several hundred stations in the Taiwan Strong Motion Instrumentation Program (TSMIP). By testing different velocity models and filter passbands, we were able to successfully derive moment tensor solutions for 107 earthquakes of Mw >= 4.8. The solutions for large events agree well with other available moment tensor catalogs derived from local and global broadband networks. However, for Mw = 5.0 or smaller events, we consistently over estimated the moment magnitudes by 0.5 to 1.0. We have tested accelerograms, and velocity waveforms integrated from accelerograms for the inversions, and found the results are similar. In addition, we used part of the catalogs to study important seismogenic structures in the area near Meishan Taiwan which was the site of a very damaging earthquake a century ago, and found that the structures were dominated by events with complex right-lateral strike-slip faulting during the recent decade. The procedures developed from this study may be applied to other strong-motion datasets to compliment or fill gaps in catalogs from regional broadband networks and teleseismic networks.

Full-Waveform Envelope Templates for Low Magnitude Discrimination and Yield Estimation at Local and Regional Distances with Application to the North Korean Nuclear Tests

NASA Astrophysics Data System (ADS)

Yoo, S. H.

2017-12-01

Monitoring seismologists have successfully used seismic coda for event discrimination and yield estimation for over a decade. In practice seismologists typically analyze long-duration, S-coda signals with high signal-to-noise ratios (SNR) at regional and teleseismic distances, since the single back-scattering model reasonably predicts decay of the late coda. However, seismic monitoring requirements are shifting towards smaller, locally recorded events that exhibit low SNR and short signal lengths. To be successful at characterizing events recorded at local distances, we must utilize the direct-phase arrivals, as well as the earlier part of the coda, which is dominated by multiple forward scattering. To remedy this problem, we have developed a new hybrid method known as full-waveform envelope template matching to improve predicted envelope fits over the entire waveform and account for direct-wave and early coda complexity. We accomplish this by including a multiple forward-scattering approximation in the envelope modeling of the early coda. The new hybrid envelope templates are designed to fit local and regional full waveforms and produce low-variance amplitude estimates, which will improve yield estimation and discrimination between earthquakes and explosions. To demonstrate the new technique, we applied our full-waveform envelope template-matching method to the six known North Korean (DPRK) underground nuclear tests and four aftershock events following the September 2017 test. We successfully discriminated the event types and estimated the yield for all six nuclear tests. We also applied the same technique to the 2015 Tianjin explosions in China, and another suspected low-yield explosion at the DPRK test site on May 12, 2010. Our results show that the new full-waveform envelope template-matching method significantly improves upon longstanding single-scattering coda prediction techniques. More importantly, the new method allows monitoring seismologists to extend coda-based techniques to lower magnitude thresholds and low-yield local explosions.

Swarms of repeating long-period earthquakes at Shishaldin Volcano, Alaska, 2001-2004

USGS Publications Warehouse

Petersen, Tanja

2007-01-01

During 2001–2004, a series of four periods of elevated long-period seismic activity, each lasting about 1–2 months, occurred at Shishaldin Volcano, Aleutian Islands, Alaska. The time periods are termed swarms of repeating events, reflecting an abundance of earthquakes with highly similar waveforms that indicate stable, non-destructive sources. These swarms are characterized by increased earthquake amplitudes, although the seismicity rate of one event every 0.5–5 min has remained more or less constant since Shishaldin last erupted in 1999. A method based on waveform cross-correlation is used to identify highly repetitive events, suggestive of spatially distinct source locations. The waveform analysis shows that several different families of similar events co-exist during a given swarm day, but generally only one large family dominates. A network of hydrothermal fractures may explain the events that do not belong to a dominant repeating event group, i.e. multiple sources at different locations exist next to a dominant source. The dominant waveforms exhibit systematic changes throughout each swarm, but some of these waveforms do reappear over the course of 4 years indicating repeatedly activated source locations. The choked flow model provides a plausible trigger mechanism for the repeating events observed at Shishaldin, explaining the gradual changes in waveforms over time by changes in pressure gradient across a constriction within the uppermost part of the conduit. The sustained generation of Shishaldin's long-period events may be attributed to complex dynamics of a multi-fractured hydrothermal system: the pressure gradient within the main conduit may be regulated by temporarily sealing and reopening of parallel flow pathways, by the amount of debris within the main conduit and/or by changing gas influx into the hydrothermal system. The observations suggest that Shishaldin's swarms of repeating events represent time periods during which a dominant source is activated.

A Structural Theory of Pitch1,2,3

PubMed Central

Laudanski, Jonathan; Zheng, Yi

2014-01-01

Abstract Musical notes can be ordered from low to high along a perceptual dimension called “pitch”. A characteristic property of these sounds is their periodic waveform, and periodicity generally correlates with pitch. Thus, pitch is often described as the perceptual correlate of the periodicity of the sound’s waveform. However, the existence and salience of pitch also depends in a complex way on other factors, in particular harmonic content. For example, periodic sounds made of high-order harmonics tend to have a weaker pitch than those made of low-order harmonics. Here we examine the theoretical proposition that pitch is the perceptual correlate of the regularity structure of the vibration pattern of the basilar membrane, across place and time—a generalization of the traditional view on pitch. While this proposition also attributes pitch to periodic sounds, we show that it predicts differences between resolved and unresolved harmonic complexes and a complex domain of existence of pitch, in agreement with psychophysical experiments. We also present a possible neural mechanism for pitch estimation based on coincidence detection, which does not require long delays, in contrast with standard temporal models of pitch. PMID:26464959

Seismic attribute analysis for reservoir and fluid prediction, Malay Basin

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

Mansor, M.N.; Rudolph, K.W.; Richards, F.B.

1994-07-01

The Malay Basin is characterized by excellent seismic data quality, but complex clastic reservoir architecture. With these characteristics, seismic attribute analysis is a very important tool in exploration and development geoscience and is routinely used for mapping fluids and reservoir, recognizing and risking traps, assessment, depth conversion, well placement, and field development planning. Attribute analysis can be successfully applied to both 2-D and 3-D data as demonstrated by comparisons of 2-D and 3-D amplitude maps of the same area. There are many different methods of extracting amplitude information from seismic data, including amplitude mapping, horizon slice, summed horizon slice, isochronmore » slice, and horizon slice from AVO (amplitude versus offset) cube. Within the Malay Basin, horizon/isochron slice techniques have several advantages over simply extracting amplitudes from a picked horizon: they are much faster, permit examination of the amplitude structure of the entire cube, yield better results for weak/variable signatures, and aid summation of amplitudes. Summation in itself often yields improved results because it incorporates the signature from the entire reservoir interval, reducing any effects due to noise, mispicking, or waveform variations. Dip and azimuth attributes have been widely applied by industry for fault identification. In addition, these attributes can also be used to map signature variations associated with hydrocarbon contacts or stratigraphic changes, and this must be considered when using these attributes for structural interpretation.« less

Low frequency AC waveform generator

DOEpatents

Bilharz, Oscar W.

1986-01-01

Low frequency sine, cosine, triangle and square waves are synthesized in circuitry which allows variation in the waveform amplitude and frequency while exhibiting good stability and without requiring significant stabilization time. A triangle waveform is formed by a ramped integration process controlled by a saturation amplifier circuit which produces the necessary hysteresis for the triangle waveform. The output of the saturation circuit is tapped to produce the square waveform. The sine waveform is synthesized by taking the absolute value of the triangular waveform, raising this absolute value to a predetermined power, multiplying the raised absolute value of the triangle wave with the triangle wave itself and properly scaling the resultant waveform and subtracting it from the triangular waveform itself. The cosine is synthesized by squaring the triangular waveform, raising the triangular waveform to a predetermined power and adding the squared waveform raised to the predetermined power with a DC reference and subtracting the squared waveform therefrom, with all waveforms properly scaled. The resultant waveform is then multiplied with a square wave in order to correct the polarity and produce the resultant cosine waveform.

bop5 mutations reveal new roles for the IC138 phosphoprotein in the regulation of flagellar motility and asymmetric waveforms

PubMed Central

VanderWaal, Kristyn E.; Yamamoto, Ryosuke; Wakabayashi, Ken-ichi; Fox, Laura; Kamiya, Ritsu; Dutcher, Susan K.; Bayly, Phillip V.; Sale, Winfield S.; Porter, Mary E.

2011-01-01

I1 dynein, or dynein f, is a highly conserved inner arm isoform that plays a key role in the regulation of flagellar motility. To understand how the IC138 IC/LC subcomplex modulates I1 activity, we characterized the molecular lesions and motility phenotypes of several bop5 alleles. bop5-3, bop5-4, and bop5-5 are null alleles, whereas bop5-6 is an intron mutation that reduces IC138 expression. I1 dynein assembles into the axoneme, but the IC138 IC/LC subcomplex is missing. bop5 strains, like other I1 mutants, swim forward with reduced swimming velocities and display an impaired reversal response during photoshock. Unlike mutants lacking the entire I1 dynein, however, bop5 strains exhibit normal phototaxis. bop5 defects are rescued by transformation with the wild-type IC138 gene. Analysis of flagellar waveforms reveals that loss of the IC138 subcomplex reduces shear amplitude, sliding velocities, and the speed of bend propagation in vivo, consistent with the reduction in microtubule sliding velocities observed in vitro. The results indicate that the IC138 IC/LC subcomplex is necessary to generate an efficient waveform for optimal motility, but it is not essential for phototaxis. These findings have significant implications for the mechanisms by which IC/LC complexes regulate dynein motor activity independent of effects on cargo binding or complex stability. PMID:21697502

Low frequency ac waveform generator

DOEpatents

Bilharz, O.W.

1983-11-22

Low frequency sine, cosine, triangle and square waves are synthesized in circuitry which allows variation in the waveform amplitude and frequency while exhibiting good stability and without requiring significant stablization time. A triangle waveform is formed by a ramped integration process controlled by a saturation amplifier circuit which produces the necessary hysteresis for the triangle waveform. The output of the saturation circuit is tapped to produce the square waveform. The sine waveform is synthesized by taking the absolute value of the triangular waveform, raising this absolute value to a predetermined power, multiplying the raised absolute value of the triangle wave with the triangle wave itself and properly scaling the resultant waveform and subtracting it from the triangular waveform to a predetermined power and adding the squared waveform raised to the predetermined power with a DC reference and subtracting the squared waveform therefrom, with all waveforms properly scaled. The resultant waveform is then multiplied with a square wave in order to correct the polarity and produce the resultant cosine waveform.

Optimal waveforms design for ultra-wideband impulse radio sensors.

PubMed

Li, Bin; Zhou, Zheng; Zou, Weixia; Li, Dejian; Zhao, Chong

2010-01-01

Ultra-wideband impulse radio (UWB-IR) sensors should comply entirely with the regulatory spectral limits for elegant coexistence. Under this premise, it is desirable for UWB pulses to improve frequency utilization to guarantee the transmission reliability. Meanwhile, orthogonal waveform division multiple-access (WDMA) is significant to mitigate mutual interferences in UWB sensor networks. Motivated by the considerations, we suggest in this paper a low complexity pulse forming technique, and its efficient implementation on DSP is investigated. The UWB pulse is derived preliminarily with the objective of minimizing the mean square error (MSE) between designed power spectrum density (PSD) and the emission mask. Subsequently, this pulse is iteratively modified until its PSD completely conforms to spectral constraints. The orthogonal restriction is then analyzed and different algorithms have been presented. Simulation demonstrates that our technique can produce UWB waveforms with frequency utilization far surpassing the other existing signals under arbitrary spectral mask conditions. Compared to other orthogonality design schemes, the designed pulses can maintain mutual orthogonality without any penalty on frequency utilization, and hence, are much superior in a WDMA network, especially with synchronization deviations.

Reflection full-waveform inversion using a modified phase misfit function

NASA Astrophysics Data System (ADS)

Cui, Chao; Huang, Jian-Ping; Li, Zhen-Chun; Liao, Wen-Yuan; Guan, Zhe

2017-09-01

Reflection full-waveform inversion (RFWI) updates the low- and highwavenumber components, and yields more accurate initial models compared with conventional full-waveform inversion (FWI). However, there is strong nonlinearity in conventional RFWI because of the lack of low-frequency data and the complexity of the amplitude. The separation of phase and amplitude information makes RFWI more linear. Traditional phase-calculation methods face severe phase wrapping. To solve this problem, we propose a modified phase-calculation method that uses the phase-envelope data to obtain the pseudo phase information. Then, we establish a pseudophase-information-based objective function for RFWI, with the corresponding source and gradient terms. Numerical tests verify that the proposed calculation method using the phase-envelope data guarantees the stability and accuracy of the phase information and the convergence of the objective function. The application on a portion of the Sigsbee2A model and comparison with inversion results of the improved RFWI and conventional FWI methods verify that the pseudophase-based RFWI produces a highly accurate and efficient velocity model. Moreover, the proposed method is robust to noise and high frequency.

Adaptive thresholding with inverted triangular area for real-time detection of the heart rate from photoplethysmogram traces on a smartphone.

PubMed

Jiang, Wen Jun; Wittek, Peter; Zhao, Li; Gao, Shi Chao

2014-01-01

Photoplethysmogram (PPG) signals acquired by smartphone cameras are weaker than those acquired by dedicated pulse oximeters. Furthermore, the signals have lower sampling rates, have notches in the waveform and are more severely affected by baseline drift, leading to specific morphological characteristics. This paper introduces a new feature, the inverted triangular area, to address these specific characteristics. The new feature enables real-time adaptive waveform detection using an algorithm of linear time complexity. It can also recognize notches in the waveform and it is inherently robust to baseline drift. An implementation of the algorithm on Android is available for free download. We collected data from 24 volunteers and compared our algorithm in peak detection with two competing algorithms designed for PPG signals, Incremental-Merge Segmentation (IMS) and Adaptive Thresholding (ADT). A sensitivity of 98.0% and a positive predictive value of 98.8% were obtained, which were 7.7% higher than the IMS algorithm in sensitivity, and 8.3% higher than the ADT algorithm in positive predictive value. The experimental results confirmed the applicability of the proposed method.

Reconfigurable, Intelligently-Adaptive, Communication System, an SDR Platform

NASA Technical Reports Server (NTRS)

Roche, Rigoberto

2016-01-01

The Space Telecommunications Radio System (STRS) provides a common, consistent framework to abstract the application software from the radio platform hardware. STRS aims to reduce the cost and risk of using complex, configurable and reprogrammable radio systems across NASA missions. The Glenn Research Center (GRC) team made a software-defined radio (SDR) platform STRS compliant by adding an STRS operating environment and a field programmable gate array (FPGA) wrapper, capable of implementing each of the platforms interfaces, as well as a test waveform to exercise those interfaces. This effort serves to provide a framework toward waveform development on an STRS compliant platform to support future space communication systems for advanced exploration missions. Validated STRS compliant applications provided tested code with extensive documentation to potentially reduce risk, cost and efforts in development of space-deployable SDRs. This paper discusses the advantages of STRS, the integration of STRS onto a Reconfigurable, Intelligently-Adaptive, Communication System (RIACS) SDR platform, the sample waveform, and wrapper development efforts. The paper emphasizes the infusion of the STRS Architecture onto the RIACS platform for potential use in next generation SDRs for advance exploration missions.

Modeling Nonlinear Acoustic Standing Waves in Resonators: Theory and Experiments

NASA Technical Reports Server (NTRS)

Raman, Ganesh; Li, Xiaofan; Finkbeiner, Joshua

2004-01-01

The overall goal of the cooperative research with NASA Glenn is to fundamentally understand, computationally model, and experimentally validate non-linear acoustic waves in enclosures with the ultimate goal of developing a non-contact acoustic seal. The longer term goal is to transition the Glenn acoustic seal innovation to a prototype sealing device. Lucas and coworkers are credited with pioneering work in Resonant Macrosonic Synthesis (RMS). Several Patents and publications have successfully illustrated the concept of Resonant Macrosonic Synthesis. To utilize this concept in practical application one needs to have an understanding of the details of the phenomenon and a predictive tool that can examine the waveforms produced within resonators of complex shapes. With appropriately shaped resonators one can produce un-shocked waveforms of high amplitude that would result in very high pressures in certain regions. Our goal is to control the waveforms and exploit the high pressures to produce an acoustic seal. Note that shock formation critically limits peak-to-peak pressure amplitudes and also causes excessive energy dissipation. Proper shaping of the resonator is thus critical to the use of this innovation.

Optimal Waveforms Design for Ultra-Wideband Impulse Radio Sensors

PubMed Central

Li, Bin; Zhou, Zheng; Zou, Weixia; Li, Dejian; Zhao, Chong

2010-01-01

Ultra-wideband impulse radio (UWB-IR) sensors should comply entirely with the regulatory spectral limits for elegant coexistence. Under this premise, it is desirable for UWB pulses to improve frequency utilization to guarantee the transmission reliability. Meanwhile, orthogonal waveform division multiple-access (WDMA) is significant to mitigate mutual interferences in UWB sensor networks. Motivated by the considerations, we suggest in this paper a low complexity pulse forming technique, and its efficient implementation on DSP is investigated. The UWB pulse is derived preliminarily with the objective of minimizing the mean square error (MSE) between designed power spectrum density (PSD) and the emission mask. Subsequently, this pulse is iteratively modified until its PSD completely conforms to spectral constraints. The orthogonal restriction is then analyzed and different algorithms have been presented. Simulation demonstrates that our technique can produce UWB waveforms with frequency utilization far surpassing the other existing signals under arbitrary spectral mask conditions. Compared to other orthogonality design schemes, the designed pulses can maintain mutual orthogonality without any penalty on frequency utilization, and hence, are much superior in a WDMA network, especially with synchronization deviations. PMID:22163511

Measuring the misfit between seismograms using an optimal transport distance: application to full waveform inversion

NASA Astrophysics Data System (ADS)

Métivier, L.; Brossier, R.; Mérigot, Q.; Oudet, E.; Virieux, J.

2016-04-01

Full waveform inversion using the conventional L2 distance to measure the misfit between seismograms is known to suffer from cycle skipping. An alternative strategy is proposed in this study, based on a measure of the misfit computed with an optimal transport distance. This measure allows to account for the lateral coherency of events within the seismograms, instead of considering each seismic trace independently, as is done generally in full waveform inversion. The computation of this optimal transport distance relies on a particular mathematical formulation allowing for the non-conservation of the total energy between seismograms. The numerical solution of the optimal transport problem is performed using proximal splitting techniques. Three synthetic case studies are investigated using this strategy: the Marmousi 2 model, the BP 2004 salt model, and the Chevron 2014 benchmark data. The results emphasize interesting properties of the optimal transport distance. The associated misfit function is less prone to cycle skipping. A workflow is designed to reconstruct accurately the salt structures in the BP 2004 model, starting from an initial model containing no information about these structures. A high-resolution P-wave velocity estimation is built from the Chevron 2014 benchmark data, following a frequency continuation strategy. This estimation explains accurately the data. Using the same workflow, full waveform inversion based on the L2 distance converges towards a local minimum. These results yield encouraging perspectives regarding the use of the optimal transport distance for full waveform inversion: the sensitivity to the accuracy of the initial model is reduced, the reconstruction of complex salt structure is made possible, the method is robust to noise, and the interpretation of seismic data dominated by reflections is enhanced.

Path-Specific Effects on Shear Motion Generation Using LargeN Array Waveform Data at the Source Physics Experiment (SPE) Site

NASA Astrophysics Data System (ADS)

Pitarka, A.; Mellors, R. J.; Walter, W. R.

2016-12-01

Depending on emplacement conditions and underground structure, and contrary to what is theoretically predicted for isotropic sources, recorded local, regional, and teleseismic waveforms from chemical explosions often contain shear waves with substantial energy. Consequently, the transportability of empirical techniques for yield estimation and source discrimination to regions with complex underground structure becomes problematic. Understanding the mechanisms of generation and conversion of shear waves caused by wave path effects during explosions can help improve techniques used in nuclear explosion monitoring. We used seismic data from LargeN, a dense array of three and one component geophones, to analyze far-field waveforms from the underground chemical explosion recorded during shot 5 of the Source Physics Experiment (SPE-5) at the Nevada National Security Site. Combined 3D elastic wave propagation modeling and frequency-wavenumber beam-forming on small arrays containing selected stations were used to detect and identify several wave phases, including primary and secondary S waves, and Rgwaves, and determine their direction of propagation. We were able to attribute key features of the waveforms, and wave phases to either source processes or propagation path effects, such as focusing and wave conversions. We also found that coda waves were more likely generated by path effects outside the source region, rather than by interaction of source generated waves with the emplacement structure. Waveform correlation and statistical analysis were performed to estimate average correlation length of small-scale heterogeneity in the upper sedimentary layers of the Yucca Flat basin in the area covered by the array. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. LLNL-ABS- 699180

Noncontact blood perfusion mapping in clinical applications

NASA Astrophysics Data System (ADS)

Iakovlev, Dmitry; Dwyer, Vincent; Hu, Sijung; Silberschmidt, Vadim

2016-04-01

Non-contact imaging photoplethysmography (iPPG) to detect pulsatile blood microcirculation in tissue has been selected as a successor to low spatial resolution and slow scanning blood perfusion techniques currently employed by clinicians. The proposed iPPG system employs a novel illumination source constructed of multiple high power LEDs with narrow spectral emission, which are temporally modulated and synchronised with a high performance sCMOS sensor. To ensure spectrum stability and prevent thermal wavelength drift due to junction temperature variations, each LED features a custom-designed thermal management system to effectively dissipate generated heat and auto-adjust current flow. The use of a multi-wavelength approach has resulted in simultaneous microvascular perfusion monitoring at various tissue depths, which is an added benefit for specific clinical applications. A synchronous detection algorithm to extract weak photoplethysmographic pulse-waveforms demonstrated robustness and high efficiency when applied to even small regions of 5 mm2. The experimental results showed evidences that the proposed system could achieve noticeable accuracy in blood perfusion monitoring by creating complex amplitude and phase maps for the tissue under examination.

Laser beam pulse formatting method

DOEpatents

Daly, T.P.; Moses, E.I.; Patterson, R.W.; Sawicki, R.H.

1994-08-09

A method for formatting a laser beam pulse using one or more delay loops is disclosed. The delay loops have a partially reflective beam splitter and a plurality of highly reflective mirrors arranged such that the laser beam pulse enters into the delay loop through the beam splitter and circulates therein along a delay loop length defined by the mirrors. As the laser beam pulse circulates within the delay loop a portion thereof is emitted upon each completed circuit when the laser beam pulse strikes the beam splitter. The laser beam pulse is thereby formatted into a plurality of sub-pulses. The delay loops are used in combination to produce complex waveforms by combining the sub-pulses using additive waveform synthesis. 8 figs.

Monitoring of Volcanic Activity by Sub-mm Geodetic Analyses

NASA Astrophysics Data System (ADS)

Miura, S.; Mare, Y.; Ichiki, M.; Demachi, T.; Tachibana, K.; Nishimura, T.

2017-12-01

Volcanic earthquakes have been occurring beneath Zao volcano in northern Honshu, Japan since 2013, following the increase of deep low frequency earthquakes from 2012. On account of a burst of seismicity initiated in April 2015, the JMA announced a warning of eruption, however, the seismicity gradually decreased for the next two months and the warning was canceled in June. In the same time period, minor expansive deformation was observed by GNSS. Small earthquakes are still occurring, and low-freq. earthquakes (LPE) occur sometimes accompanied by static tilt changes. In this study, we try to extract the sub-mm displacements from the LPE waveforms observed by broadband seismometers (BBS) and utilize them for geodetic inversion to monitor volcanic activities. Thun et al. (2015, 2016) devised an efficient method using a running median filter (RMF) to remove LP noises, which contaminate displacement waveforms. They demonstrated the reproducibility of the waveforms corresponding to the experimentally given sub-mm displacements in the laboratory. They also apply the method to the field LPE data obtained from several volcanoes to show static displacements. The procedure is outlined as follows: (1) Unfiltered removal of the instrument response, (2) LP noise estimate by LPF with a corner frequency of 5/M, where M (seconds) is the time window of the RMF and should be at least three times the length of the rise time. (3) Subtract the noise estimated from step (2). (4) Integrate to obtain displacement waveforms. We apply the method to the BBS waveform at a distance of about 1.5 km ESE from the summit crater of Zao Volcano associated with a LPE on April 1, 2017. Assuming the time window M as 300 seconds, we successfully obtained the displacement history: taking the rise time of about 2 minutes, the site was gradually uplifted with the amount of about 50-60 µm and then subsided with HF displacements in the next 2 minutes resulting about 20-30 µm static upheaval. Comparing the waveforms obtained by the RMF and the conventional methods, the onset of the upheaval is delayed a little in the former one, while the latter one is consistent with the inclination change observed by the tiltmeter installed at the same site. It may be caused by the characteristics of the RMF and attention should be paid to detailed discussions of the source time histories.

Micro-seismic imaging using a source function independent full waveform inversion method

NASA Astrophysics Data System (ADS)

Wang, Hanchen; Alkhalifah, Tariq

2018-03-01

At the heart of micro-seismic event measurements is the task to estimate the location of the source micro-seismic events, as well as their ignition times. The accuracy of locating the sources is highly dependent on the velocity model. On the other hand, the conventional micro-seismic source locating methods require, in many cases manual picking of traveltime arrivals, which do not only lead to manual effort and human interaction, but also prone to errors. Using full waveform inversion (FWI) to locate and image micro-seismic events allows for an automatic process (free of picking) that utilizes the full wavefield. However, full waveform inversion of micro-seismic events faces incredible nonlinearity due to the unknown source locations (space) and functions (time). We developed a source function independent full waveform inversion of micro-seismic events to invert for the source image, source function and the velocity model. It is based on convolving reference traces with these observed and modeled to mitigate the effect of an unknown source ignition time. The adjoint-state method is used to derive the gradient for the source image, source function and velocity updates. The extended image for the source wavelet in Z axis is extracted to check the accuracy of the inverted source image and velocity model. Also, angle gathers is calculated to assess the quality of the long wavelength component of the velocity model. By inverting for the source image, source wavelet and the velocity model simultaneously, the proposed method produces good estimates of the source location, ignition time and the background velocity for synthetic examples used here, like those corresponding to the Marmousi model and the SEG/EAGE overthrust model.

Eccentric, nonspinning, inspiral, Gaussian-process merger approximant for the detection and characterization of eccentric binary black hole mergers

NASA Astrophysics Data System (ADS)

Huerta, E. A.; Moore, C. J.; Kumar, Prayush; George, Daniel; Chua, Alvin J. K.; Haas, Roland; Wessel, Erik; Johnson, Daniel; Glennon, Derek; Rebei, Adam; Holgado, A. Miguel; Gair, Jonathan R.; Pfeiffer, Harald P.

2018-01-01

We present ENIGMA, a time domain, inspiral-merger-ringdown waveform model that describes nonspinning binary black holes systems that evolve on moderately eccentric orbits. The inspiral evolution is described using a consistent combination of post-Newtonian theory, self-force and black hole perturbation theory. Assuming eccentric binaries that circularize prior to coalescence, we smoothly match the eccentric inspiral with a stand-alone, quasicircular merger, which is constructed using machine learning algorithms that are trained with quasicircular numerical relativity waveforms. We show that ENIGMA reproduces with excellent accuracy the dynamics of quasicircular compact binaries. We validate ENIGMA using a set of Einstein Toolkit eccentric numerical relativity waveforms, which describe eccentric binary black hole mergers with mass-ratios between 1 ≤q ≤5.5 , and eccentricities e0≲0.2 ten orbits before merger. We use this model to explore in detail the physics that can be extracted with moderately eccentric, nonspinning binary black hole mergers. In particular, we use ENIGMA to show that the gravitational wave transients GW150914, GW151226, GW170104, GW170814 and GW170608 can be effectively recovered with spinning, quasicircular templates if the eccentricity of these events at a gravitational wave frequency of 10 Hz satisfies e0≤{0.175 ,0.125 ,0.175 ,0.175 ,0.125 }, respectively. We show that if these systems have eccentricities e0˜0.1 at a gravitational wave frequency of 10 Hz, they can be misclassified as quasicircular binaries due to parameter space degeneracies between eccentricity and spin corrections. Using our catalog of eccentric numerical relativity simulations, we discuss the importance of including higher-order waveform multipoles in gravitational wave searches of eccentric binary black hole mergers.

CryoSat-2 SAR and SARin Inland Water Heights from the CRUCIAL project

NASA Astrophysics Data System (ADS)

Benveniste, J.; Restano, M.; Ambrózio, A.; Moore, P.; Birkinshaw, S.

2017-12-01

CRUCIAL was an ESA/STSE funded project investigating innovative land and inland water applications from CryoSat-2 with a forward-look component to the Sentinel-3 and Jason-CS/Sentinel-6 missions. The high along-track sampling of CryoSat-2 in its SAR and SARin modes offers the opportunity to recover high frequency signals over inland waters. A methodology was developed to process the FBR L1A Doppler beams to form a waveform product using ground cell gridding, beam steering and beam stacking. Inland water heights from CryoSat-2 are derived by using a set of empirical retrackers formulated for inland water applications. Results of the processing strategy include a comparison of waveforms and heights from the burst echoes (80 m along-track) and from multi-look waveforms (320 m along-track). SAR and SARin FBR data are available for the Amazon, Brahmaputra and Mekong for 2011-2015. FBR SAR results are compared against stage data from the nearest gauge. Heights from Tonlé Sap are also compared against Jason-2 data from the United States Department of Agriculture. A strategy to select the number of multi-looks over rivers was designed based on the rms of heights across Tonlé Sap. Comparisons include results from the empirical retrackers and from waveforms and heights obtained via ESA's Grid Processing on Demand (G-POD/SARvatore) using the SAMOSA2 retracker. Results of FBR SARin processing for the Amazon and Brahmaputra are presented including comparison of heights from the two antennae, extraction of slope of the ground surface and validation against ground data where appropriate.

New template family for the detection of gravitational waves from comparable-mass black hole binaries

NASA Astrophysics Data System (ADS)

Porter, Edward K.

2007-11-01

In order to improve the phasing of the comparable-mass waveform as we approach the last stable orbit for a system, various resummation methods have been used to improve the standard post-Newtonian waveforms. In this work we present a new family of templates for the detection of gravitational waves from the inspiral of two comparable-mass black hole binaries. These new adiabatic templates are based on reexpressing the derivative of the binding energy and the gravitational wave flux functions in terms of shifted Chebyshev polynomials. The Chebyshev polynomials are a useful tool in numerical methods as they display the fastest convergence of any of the orthogonal polynomials. In this case they are also particularly useful as they eliminate one of the features that plagues the post-Newtonian expansion. The Chebyshev binding energy now has information at all post-Newtonian orders, compared to the post-Newtonian templates which only have information at full integer orders. In this work, we compare both the post-Newtonian and Chebyshev templates against a fiducially exact waveform. This waveform is constructed from a hybrid method of using the test-mass results combined with the mass dependent parts of the post-Newtonian expansions for the binding energy and flux functions. Our results show that the Chebyshev templates achieve extremely high fitting factors at all post-Newtonian orders and provide excellent parameter extraction. We also show that this new template family has a faster Cauchy convergence, gives a better prediction of the position of the last stable orbit and in general recovers higher Signal-to-Noise ratios than the post-Newtonian templates.

Extraction of Pn seismic signals from air-gun shots recorded by the Cascadia Amphibious seismic experiment

NASA Astrophysics Data System (ADS)

Rathnayaka, S.; Gao, H.

2017-12-01

The goal of this study is to extract Pn (head wave) seismic waveforms recorded by both offshore and onshore (broadband and short period) seismic stations and evaluate the data quality. Two offshore active-source seismic experiments, MGL 1211 and MGL 1212, were conducted from 13th June to 24th July 2012, during the first year deployment of the Cascadia Initiative Amphibious Array. In total, we choose 110 ocean bottom seismometers and 209 inland stations that are located along the entire Cascadia subduction zone. We first remove the instrument response, and then explore the potential frequency ranges and the diurnal effect. We make the common receiver gathering for each seismic station and filter the seismic waveforms at multiple frequency bands, ranging from 3-5 Hz, 5-10 Hz, 10-20 Hz, to 20-40 Hz, respectively. To quantitatively evaluate the data quality, we calculate the signal-to-noise ratio (SNR) of the waveforms for usable stations that record clear Pn arrivals at multiple frequency bands. Our results show that most offshore stations located at deep water (>1.5 km) record clear air-gun shot signals at frequencies higher than 3 Hz and up to 550 km away from the source. For most stations located on the shallow continental shelf, the seismic recordings appear much noisier at all the frequencies compared to stations at deep water. Three general trends are observed for the SNR distribution; First, the SNR ratio increases from lower to higher frequency bands; Second, the ratio decreases with the increasing source-to-receiver distance; And third, the ratio increases from shallow to deep water. We also observe a rough negative relationship of the signal-to-noise ratio with the thickness of the marine sediment. Only 5 inland stations record clear air-gun shot arrivals up to 200 km away from the source. More detailed data quality analysis with more results will also be present.

Speaker Recognition Through NLP and CWT Modeling

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

Brown-VanHoozer, S.A.; Kercel, S.W.; Tucker, R.W.

The objective of this research is to develop a system capable of identifying speakers on wiretaps from a large database (>500 speakers) with a short search time duration (<30 seconds), and with better than 90% accuracy. Much previous research in speaker recognition has led to algorithms that produced encouraging preliminary results, but were overwhelmed when applied to populations of more than a dozen or so different speakers. The authors are investigating a solution to the "large population" problem by seeking two completely different kinds of characterizing features. These features are he techniques of Neuro-Linguistic Programming (NLP) and the continuous waveletmore » transform (CWT). NLP extracts precise neurological, verbal and non-verbal information, and assimilates the information into useful patterns. These patterns are based on specific cues demonstrated by each individual, and provide ways of determining congruency between verbal and non-verbal cues. The primary NLP modalities are characterized through word spotting (or verbal predicates cues, e.g., see, sound, feel, etc.) while the secondary modalities would be characterized through the speech transcription used by the individual. This has the practical effect of reducing the size of the search space, and greatly speeding up the process of identifying an unknown speaker. The wavelet-based line of investigation concentrates on using vowel phonemes and non-verbal cues, such as tempo. The rationale for concentrating on vowels is there are a limited number of vowels phonemes, and at least one of them usually appears in even the shortest of speech segments. Using the fast, CWT algorithm, the details of both the formant frequency and the glottal excitation characteristics can be easily extracted from voice waveforms. The differences in the glottal excitation waveforms as well as the formant frequency are evident in the CWT output. More significantly, the CWT reveals significant detail of the glottal excitation waveform.« less

Seismic body wave separation in volcano-tectonic activity inferred by the Convolutive Independent Component Analysis

NASA Astrophysics Data System (ADS)

Capuano, Paolo; De Lauro, Enza; De Martino, Salvatore; Falanga, Mariarosaria; Petrosino, Simona

2015-04-01

One of the main challenge in volcano-seismological literature is to locate and characterize the source of volcano/tectonic seismic activity. This passes through the identification at least of the onset of the main phases, i.e. the body waves. Many efforts have been made to solve the problem of a clear separation of P and S phases both from a theoretical point of view and developing numerical algorithms suitable for specific cases (see, e.g., Küperkoch et al., 2012). Recently, a robust automatic procedure has been implemented for extracting the prominent seismic waveforms from continuously recorded signals and thus allowing for picking the main phases. The intuitive notion of maximum non-gaussianity is achieved adopting techniques which involve higher-order statistics in frequency domain., i.e, the Convolutive Independent Component Analysis (CICA). This technique is successful in the case of the blind source separation of convolutive mixtures. In seismological framework, indeed, seismic signals are thought as the convolution of a source function with path, site and the instrument response. In addition, time-delayed versions of the same source exist, due to multipath propagation typically caused by reverberations from some obstacle. In this work, we focus on the Volcano Tectonic (VT) activity at Campi Flegrei Caldera (Italy) during the 2006 ground uplift (Ciaramella et al., 2011). The activity was characterized approximately by 300 low-magnitude VT earthquakes (Md < 2; for the definition of duration magnitude, see Petrosino et al. 2008). Most of them were concentrated in distinct seismic sequences with hypocenters mainly clustered beneath the Solfatara-Accademia area, at depths ranging between 1 and 4 km b.s.l.. The obtained results show the clear separation of P and S phases: the technique not only allows the identification of the S-P time delay giving the timing of both phases but also provides the independent waveforms of the P and S phases. This is an enormous advantage for all the problems related to the source inversion and location In addition, the VT seismicity was accompanied by hundreds of LP events (characterized by spectral peaks in the 0.5-2-Hz frequency band) that were concentrated in a 7-day interval. The main interest is to establish whether the occurrence of LPs is only limited to the swarm that reached a climax on days 26-28 October as indicated by Saccorotti et al. (2007), or a longer period is experienced. The automatically extracted waveforms with improved signal-to-noise ratio via CICA coupled with automatic phase picking allowed to compile a more complete seismic catalog and to better quantify the seismic energy release including the presence of LP events from the beginning of October until mid of November. Finally, a further check of the volcanic nature of extracted signals is achieved by looking at the seismological properties and the content of entropy held in the traces (Falanga and Petrosino 2012; De Lauro et al., 2012). Our results allow us to move towards a full description of the complexity of the source, which can be used for hazard-model development and forecast-model testing, showing an illustrative example of the applicability of the CICA method to regions with low seismicity in high ambient noise

Imaging Faults in Carbonate Reservoir using Full Waveform Inversion and Reverse Time Migration of Walkaway VSP Data

NASA Astrophysics Data System (ADS)

Takam Takougang, E. M.; Bouzidi, Y.

2016-12-01

Multi-offset Vertical Seismic Profile (walkaway VSP) data were collected in an oil field located in a shallow water environment dominated by carbonate rocks, offshore the United Arab Emirates. The purpose of the survey was to provide structural information of the reservoir, around and away from the borehole. Five parallel lines were collected using an air gun at 25 m shot interval and 4 m source depth. A typical recording tool with 20 receivers spaced every 15.1 m, and located in a deviated borehole with an angle varying between 0 and 24 degree from the vertical direction, was used to record the data. The recording tool was deployed at different depths for each line, from 521 m to 2742 m depth. Smaller offsets were used for shallow receivers and larger offsets for deeper receivers. The lines merged to form the input dataset for waveform tomography. The total length of the combined lines was 9 km, containing 1344 shots and 100 receivers in the borehole located half-way down. Acoustic full waveform inversion was applied in the frequency domain to derive a high resolution velocity model. The final velocity model derived after the inversion using the frequencies 5-40 Hz, showed good correlation with velocities estimated from vertical incidence VSP and sonic log, confirming the success of the inversion. The velocity model showed anomalous low values in areas that correlate with known location of hydrocarbon reservoir. Pre-stack depth Reverse time migration was then applied using the final velocity model from waveform inversion and the up-going wavefield from the input data. The final estimated source signature from waveform inversion was used as input source for reverse time migration. To save computational memory and time, every 3 shots were used during reverse time migration and the data were low-pass filtered to 30 Hz. Migration artifacts were attenuated using a second order derivative filter. The final migration image shows a good correlation with the waveform tomography velocity model, and highlights a complex network of faults in the reservoir, that could be useful in understanding fluid and hydrocarbon movements. This study shows that the combination of full waveform tomography and reverse time migration can provide high resolution images that can enhance interpretation and characterization of oil reservoirs.

One-dimensional terahertz imaging of surfactant-stabilized dodecane-brine emulsion

NASA Astrophysics Data System (ADS)

Nickel, Daniel Vincent

Terahertz line-images of surfactant-stabilized dodecane(C12H 26)-brine emulsions are obtained by translating the emulsified region through the focus of a terahertz time-domain spectrometer, capturing a time-domain waveform at each vertical position. From these images, relative dodecane content, emulsion size, and stability can be extracted to evaluate the efficacy of the surfactant in solvating the dodecane. In addition, the images provide insight into the dynamics of concentrated emulsions after mixing.

An investigation of the observability of ocean-surface parameters using GEOS-3 backscatter data

NASA Technical Reports Server (NTRS)

Miller, L. S.; Priester, R. W.

1978-01-01

The degree to which ocean surface roughness can be synoptically observed through use of the information extracted from the GEOS-3 backscattered waveform data was evaluated. Algorithms are given for use in estimating the radar sensed waveheight distribution or ocean-surface impulse response. Other factors discussed include comparisons between theoretical and experimental radar cross section values, sea state bias effects, spatial variability of significant waveheight data, and sensor-related considerations.

Relative Position of the Third Characteristic Peak of the Intracranial Pressure Pulse Waveform Morphology Differentiates Normal-Pressure Hydrocephalus Shunt Responders and Nonresponders.

PubMed

Hamilton, Robert; Fuller, Jennifer; Baldwin, Kevin; Vespa, Paul; Hu, Xiao; Bergsneider, Marvin

2016-01-01

The diversion of cerebrospinal fluid (CSF) remains the principal treatment option for patients with normal-pressure hydrocephalus (NPH). External lumbar drain (ELD) and overnight intracranial pressure (ICP) monitoring are popular prognostic tests for differentiating which patients will benefit from shunting. Using the morphological clustering and analysis of continuous intracranial pulse (MOCAIP) algorithm to extract morphological metrics from the overnight ICP signal, we hypothesize that changes in the third peak of the ICP pulse pressure waveform can be used to differentiate ELD responders and nonresponders. Our study involved 66 patients (72.2 ± 9.8 years) undergoing evaluation for possible NPH, which included overnight ICP monitoring and ELD. ELD outcome was based on clinical notes and divided into nonresponders and responders. MOCAIP was used to extract mean ICP, ICP wave amplitude (waveAmp), and a metric derived to study P3 elevation (P3ratio). Of the 66 patients, 7 were classified as nonresponders and 25 as significant responders. The mean ICP and waveAmp did not vary significantly (p = 0.19 and p = 0.41) between the outcome groups; however, the P3ratio did show a significant difference (p = 0.04). Initial results suggest that the P3ratio might be used as a prognostic indicator for ELD outcome.

Extracellular voltage threshold settings can be tuned for optimal encoding of movement and stimulus parameters

NASA Astrophysics Data System (ADS)

Oby, Emily R.; Perel, Sagi; Sadtler, Patrick T.; Ruff, Douglas A.; Mischel, Jessica L.; Montez, David F.; Cohen, Marlene R.; Batista, Aaron P.; Chase, Steven M.

2016-06-01

Objective. A traditional goal of neural recording with extracellular electrodes is to isolate action potential waveforms of an individual neuron. Recently, in brain-computer interfaces (BCIs), it has been recognized that threshold crossing events of the voltage waveform also convey rich information. To date, the threshold for detecting threshold crossings has been selected to preserve single-neuron isolation. However, the optimal threshold for single-neuron identification is not necessarily the optimal threshold for information extraction. Here we introduce a procedure to determine the best threshold for extracting information from extracellular recordings. We apply this procedure in two distinct contexts: the encoding of kinematic parameters from neural activity in primary motor cortex (M1), and visual stimulus parameters from neural activity in primary visual cortex (V1). Approach. We record extracellularly from multi-electrode arrays implanted in M1 or V1 in monkeys. Then, we systematically sweep the voltage detection threshold and quantify the information conveyed by the corresponding threshold crossings. Main Results. The optimal threshold depends on the desired information. In M1, velocity is optimally encoded at higher thresholds than speed; in both cases the optimal thresholds are lower than are typically used in BCI applications. In V1, information about the orientation of a visual stimulus is optimally encoded at higher thresholds than is visual contrast. A conceptual model explains these results as a consequence of cortical topography. Significance. How neural signals are processed impacts the information that can be extracted from them. Both the type and quality of information contained in threshold crossings depend on the threshold setting. There is more information available in these signals than is typically extracted. Adjusting the detection threshold to the parameter of interest in a BCI context should improve our ability to decode motor intent, and thus enhance BCI control. Further, by sweeping the detection threshold, one can gain insights into the topographic organization of the nearby neural tissue.

Extracellular voltage threshold settings can be tuned for optimal encoding of movement and stimulus parameters

PubMed Central

Oby, Emily R; Perel, Sagi; Sadtler, Patrick T; Ruff, Douglas A; Mischel, Jessica L; Montez, David F; Cohen, Marlene R; Batista, Aaron P; Chase, Steven M

2018-01-01

Objective A traditional goal of neural recording with extracellular electrodes is to isolate action potential waveforms of an individual neuron. Recently, in brain–computer interfaces (BCIs), it has been recognized that threshold crossing events of the voltage waveform also convey rich information. To date, the threshold for detecting threshold crossings has been selected to preserve single-neuron isolation. However, the optimal threshold for single-neuron identification is not necessarily the optimal threshold for information extraction. Here we introduce a procedure to determine the best threshold for extracting information from extracellular recordings. We apply this procedure in two distinct contexts: the encoding of kinematic parameters from neural activity in primary motor cortex (M1), and visual stimulus parameters from neural activity in primary visual cortex (V1). Approach We record extracellularly from multi-electrode arrays implanted in M1 or V1 in monkeys. Then, we systematically sweep the voltage detection threshold and quantify the information conveyed by the corresponding threshold crossings. Main Results The optimal threshold depends on the desired information. In M1, velocity is optimally encoded at higher thresholds than speed; in both cases the optimal thresholds are lower than are typically used in BCI applications. In V1, information about the orientation of a visual stimulus is optimally encoded at higher thresholds than is visual contrast. A conceptual model explains these results as a consequence of cortical topography. Significance How neural signals are processed impacts the information that can be extracted from them. Both the type and quality of information contained in threshold crossings depend on the threshold setting. There is more information available in these signals than is typically extracted. Adjusting the detection threshold to the parameter of interest in a BCI context should improve our ability to decode motor intent, and thus enhance BCI control. Further, by sweeping the detection threshold, one can gain insights into the topographic organization of the nearby neural tissue. PMID:27097901

Extracellular voltage threshold settings can be tuned for optimal encoding of movement and stimulus parameters.

PubMed

Oby, Emily R; Perel, Sagi; Sadtler, Patrick T; Ruff, Douglas A; Mischel, Jessica L; Montez, David F; Cohen, Marlene R; Batista, Aaron P; Chase, Steven M

2016-06-01

A traditional goal of neural recording with extracellular electrodes is to isolate action potential waveforms of an individual neuron. Recently, in brain-computer interfaces (BCIs), it has been recognized that threshold crossing events of the voltage waveform also convey rich information. To date, the threshold for detecting threshold crossings has been selected to preserve single-neuron isolation. However, the optimal threshold for single-neuron identification is not necessarily the optimal threshold for information extraction. Here we introduce a procedure to determine the best threshold for extracting information from extracellular recordings. We apply this procedure in two distinct contexts: the encoding of kinematic parameters from neural activity in primary motor cortex (M1), and visual stimulus parameters from neural activity in primary visual cortex (V1). We record extracellularly from multi-electrode arrays implanted in M1 or V1 in monkeys. Then, we systematically sweep the voltage detection threshold and quantify the information conveyed by the corresponding threshold crossings. The optimal threshold depends on the desired information. In M1, velocity is optimally encoded at higher thresholds than speed; in both cases the optimal thresholds are lower than are typically used in BCI applications. In V1, information about the orientation of a visual stimulus is optimally encoded at higher thresholds than is visual contrast. A conceptual model explains these results as a consequence of cortical topography. How neural signals are processed impacts the information that can be extracted from them. Both the type and quality of information contained in threshold crossings depend on the threshold setting. There is more information available in these signals than is typically extracted. Adjusting the detection threshold to the parameter of interest in a BCI context should improve our ability to decode motor intent, and thus enhance BCI control. Further, by sweeping the detection threshold, one can gain insights into the topographic organization of the nearby neural tissue.

High-order numerical simulations of pulsatile flow in a curved artery model

NASA Astrophysics Data System (ADS)

Cox, Christopher; Liang, Chunlei; Plesniak, Michael W.

2016-11-01

Cardiovascular flows are pulsatile, incompressible and occur in complex geometries with compliant walls. Together, these factors can produce an environment that can affect the progression of cardiovascular disease by altering wall shear stresses. Unstructured high-order CFD methods are well suited for capturing unsteady vortex-dominated viscous flows, and these methods provide high accuracy for similar cost as low-order methods. We use an in-house three-dimensional flux reconstruction Navier-Stokes solver to simulate secondary flows and vortical structures within a rigid 180-degree curved artery model under pulsatile flow of a Newtonian blood-analog fluid. Our simulations use a physiological flowrate waveform taken from the carotid artery. We are particularly interested in the dynamics during the deceleration phase of the waveform, where we observe the deformed-Dean, Dean, Lyne and Wall vortices. Our numerical results reveal the complex nature of these vortices both in space and time and their effect on overall wall shear stress. Numerical results agree with and complement experimental results obtained in our laboratory using particle image velocimetry. Supported by the GW Center for Biomimetics and Bioinspired Engineering.

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

Eken Tuna, Kevin Mayeda, Abraham Hofstetter, Rengin Gok, Gonca Orgulu, Niyazi Turkelli

A recently developed coda magnitude methodology was applied to selected broadband stations in Turkey for the purpose of testing the coda method in a large, laterally complex region. As found in other, albeit smaller regions, coda envelope amplitude measurements are significantly less variable than distance-corrected direct wave measurements (i.e., L{sub g} and surface waves) by roughly a factor 3-to-4. Despite strong lateral crustal heterogeneity in Turkey, they found that the region could be adequately modeled assuming a simple 1-D, radially symmetric path correction. After calibrating the stations ISP, ISKB and MALT for local and regional distances, single-station moment-magnitude estimates (M{submore » W}) derived from the coda spectra were in excellent agreement with those determined from multistation waveform modeling inversions, exhibiting a data standard deviation of 0.17. Though the calibration was validated using large events, the results of the calibration will extend M{sub W} estimates to significantly smaller events which could not otherwise be waveform modeled. The successful application of the method is remarkable considering the significant lateral complexity in Turkey and the simple assumptions used in the coda method.« less

Nonspinning black hole-neutron star mergers: A model for the amplitude of gravitational waveforms

NASA Astrophysics Data System (ADS)

Pannarale, Francesco; Berti, Emanuele; Kyutoku, Koutarou; Shibata, Masaru

2013-10-01

Black hole-neutron star binary mergers display a much richer phenomenology than black hole-black hole mergers, even in the relatively simple case—considered in this paper—in which both the black hole and the neutron star are nonspinning. When the neutron star is tidally disrupted, the gravitational wave emission is radically different from the black hole-black hole case and it can be broadly classified in two groups, depending on the spatial extent of the disrupted material. We present a phenomenological model for the gravitational waveform amplitude in the frequency domain that encompasses the three possible outcomes of the merger: no tidal disruption, “mild,” and “strong” tidal disruption. The model is calibrated to general relativistic numerical simulations using piecewise polytropic neutron star equations of state. It should prove useful to extract information on the nuclear equation of state from future gravitational-wave observations, and also to obtain more accurate estimates of black hole-neutron star merger event rates in second- and third-generation interferometric gravitational-wave detectors. We plan to extend and improve the model as longer and more accurate gravitational waveforms become available, and we will make it publicly available online as a Mathematica package. We also present in the Appendix analytical fits of the projected KAGRA noise spectral density, which should be useful in data analysis applications.

Earthquake detection through computationally efficient similarity search

PubMed Central

Yoon, Clara E.; O’Reilly, Ossian; Bergen, Karianne J.; Beroza, Gregory C.

2015-01-01

Seismology is experiencing rapid growth in the quantity of data, which has outpaced the development of processing algorithms. Earthquake detection—identification of seismic events in continuous data—is a fundamental operation for observational seismology. We developed an efficient method to detect earthquakes using waveform similarity that overcomes the disadvantages of existing detection methods. Our method, called Fingerprint And Similarity Thresholding (FAST), can analyze a week of continuous seismic waveform data in less than 2 hours, or 140 times faster than autocorrelation. FAST adapts a data mining algorithm, originally designed to identify similar audio clips within large databases; it first creates compact “fingerprints” of waveforms by extracting key discriminative features, then groups similar fingerprints together within a database to facilitate fast, scalable search for similar fingerprint pairs, and finally generates a list of earthquake detections. FAST detected most (21 of 24) cataloged earthquakes and 68 uncataloged earthquakes in 1 week of continuous data from a station located near the Calaveras Fault in central California, achieving detection performance comparable to that of autocorrelation, with some additional false detections. FAST is expected to realize its full potential when applied to extremely long duration data sets over a distributed network of seismic stations. The widespread application of FAST has the potential to aid in the discovery of unexpected seismic signals, improve seismic monitoring, and promote a greater understanding of a variety of earthquake processes. PMID:26665176

Improved Analysis of GW150914 Using a Fully Spin-Precessing Waveform Model

NASA Astrophysics Data System (ADS)

Abbott, B. P.; Abbott, R.; Abbott, T. D.; Abernathy, M. R.; Acernese, F.; Ackley, K.; Adams, C.; Adams, T.; Addesso, P.; Adhikari, R. X.; Adya, V. B.; Affeldt, C.; Agathos, M.; Agatsuma, K.; Aggarwal, N.; Aguiar, O. D.; Aiello, L.; Ain, A.; Ajith, P.; Allen, B.; Allocca, A.; Altin, P. A.; Anderson, S. B.; Anderson, W. G.; Arai, K.; Araya, M. C.; Arceneaux, C. C.; Areeda, J. S.; Arnaud, N.; Arun, K. G.; Ascenzi, S.; Ashton, G.; Ast, M.; Aston, S. M.; Astone, P.; Aufmuth, P.; Aulbert, C.; Babak, S.; Bacon, P.; Bader, M. K. M.; Baker, P. T.; Baldaccini, F.; Ballardin, G.; Ballmer, S. W.; Barayoga, J. C.; Barclay, S. E.; Barish, B. C.; Barker, D.; Barone, F.; Barr, B.; Barsotti, L.; Barsuglia, M.; Barta, D.; Bartlett, J.; Bartos, I.; Bassiri, R.; Basti, A.; Batch, J. C.; Baune, C.; Bavigadda, V.; Bazzan, M.; Bejger, M.; Bell, A. S.; Berger, B. K.; Bergmann, G.; Berry, C. P. L.; Bersanetti, D.; Bertolini, A.; Betzwieser, J.; Bhagwat, S.; Bhandare, R.; Bilenko, I. A.; Billingsley, G.; Birch, J.; Birney, R.; Birnholtz, O.; Biscans, S.; Bisht, A.; Bitossi, M.; Biwer, C.; Bizouard, M. A.; Blackburn, J. K.; Blair, C. D.; Blair, D. G.; Blair, R. M.; Bloemen, S.; Bock, O.; Boer, M.; Bogaert, G.; Bogan, C.; Bohe, A.; Bond, C.; Bondu, F.; Bonnand, R.; Boom, B. A.; Bork, R.; Boschi, V.; Bose, S.; Bouffanais, Y.; Bozzi, A.; Bradaschia, C.; Brady, P. R.; Braginsky, V. B.; Branchesi, M.; Brau, J. E.; Briant, T.; Brillet, A.; Brinkmann, M.; Brisson, V.; Brockill, P.; Broida, J. E.; Brooks, A. F.; Brown, D. A.; Brown, D. D.; Brown, N. M.; Brunett, S.; Buchanan, C. C.; Buikema, A.; Bulik, T.; Bulten, H. J.; Buonanno, A.; Buskulic, D.; Buy, C.; Byer, R. L.; Cabero, M.; Cadonati, L.; Cagnoli, G.; Cahillane, C.; Calderón Bustillo, J.; Callister, T.; Calloni, E.; Camp, J. B.; Cannon, K. C.; Cao, J.; Capano, C. D.; Capocasa, E.; Carbognani, F.; Caride, S.; Casanueva Diaz, C.; Casentini, J.; Caudill, S.; Cavaglià, M.; Cavalier, F.; Cavalieri, R.; Cella, G.; Cepeda, C. B.; Cerboni Baiardi, L.; Cerretani, G.; Cesarini, E.; Chamberlin, S. J.; Chan, M.; Chao, S.; Charlton, P.; Chassande-Mottin, E.; Cheeseboro, B. D.; Chen, H. Y.; Chen, Y.; Cheng, C.; Chincarini, A.; Chiummo, A.; Cho, H. S.; Cho, M.; Chow, J. H.; Christensen, N.; Chu, Q.; Chua, S.; Chung, S.; Ciani, G.; Clara, F.; Clark, J. A.; Cleva, F.; Coccia, E.; Cohadon, P.-F.; Colla, A.; Collette, C. G.; Cominsky, L.; Constancio, M.; Conte, A.; Conti, L.; Cook, D.; Corbitt, T. R.; Cornish, N.; Corsi, A.; Cortese, S.; Costa, C. A.; Coughlin, M. W.; Coughlin, S. B.; Coulon, J.-P.; Countryman, S. T.; Couvares, P.; Cowan, E. E.; Coward, D. M.; Cowart, M. J.; Coyne, D. C.; Coyne, R.; Craig, K.; Creighton, J. D. E.; Cripe, J.; Crowder, S. G.; Cumming, A.; Cunningham, L.; Cuoco, E.; Dal Canton, T.; Danilishin, S. L.; D'Antonio, S.; Danzmann, K.; Darman, N. S.; Dasgupta, A.; Da Silva Costa, C. F.; Dattilo, V.; Dave, I.; Davier, M.; Davies, G. S.; Daw, E. J.; Day, R.; De, S.; DeBra, D.; Debreczeni, G.; Degallaix, J.; De Laurentis, M.; Deléglise, S.; Del Pozzo, W.; Denker, T.; Dent, T.; Dergachev, V.; De Rosa, R.; DeRosa, R. T.; DeSalvo, R.; Devine, R. C.; Dhurandhar, S.; Díaz, M. C.; Di Fiore, L.; Di Giovanni, M.; Di Girolamo, T.; Di Lieto, A.; Di Pace, S.; Di Palma, I.; Di Virgilio, A.; Dolique, V.; Donovan, F.; Dooley, K. L.; Doravari, S.; Douglas, R.; Downes, T. P.; Drago, M.; Drever, R. W. P.; Driggers, J. C.; Ducrot, M.; Dwyer, S. E.; Edo, T. B.; Edwards, M. C.; Effler, A.; Eggenstein, H.-B.; Ehrens, P.; Eichholz, J.; Eikenberry, S. S.; Engels, W.; Essick, R. C.; Etienne, Z.; Etzel, T.; Evans, M.; Evans, T. M.; Everett, R.; Factourovich, M.; Fafone, V.; Fair, H.; Fairhurst, S.; Fan, X.; Fang, Q.; Farinon, S.; Farr, B.; Farr, W. M.; Fauchon-Jones, E.; Favata, M.; Fays, M.; Fehrmann, H.; Fejer, M. M.; Fenyvesi, E.; Ferrante, I.; Ferreira, E. C.; Ferrini, F.; Fidecaro, F.; Fiori, I.; Fiorucci, D.; Fisher, R. P.; Flaminio, R.; Fletcher, M.; Fournier, J.-D.; Frasca, S.; Frasconi, F.; Frei, Z.; Freise, A.; Frey, R.; Frey, V.; Fritschel, P.; Frolov, V. V.; Fulda, P.; Fyffe, M.; Gabbard, H. A. G.; Gaebel, S.; Gair, J. R.; Gammaitoni, L.; Gaonkar, S. G.; Garufi, F.; Gaur, G.; Gehrels, N.; Gemme, G.; Geng, P.; Genin, E.; Gennai, A.; George, J.; Gergely, L.; Germain, V.; Ghosh, Abhirup; Ghosh, Archisman; Ghosh, S.; Giaime, J. A.; Giardina, K. D.; Giazotto, A.; Gill, K.; Glaefke, A.; Goetz, E.; Goetz, R.; Gondan, L.; González, G.; Gonzalez Castro, J. M.; Gopakumar, A.; Gordon, N. A.; Gorodetsky, M. L.; Gossan, S. E.; Gosselin, M.; Gouaty, R.; Grado, A.; Graef, C.; Graff, P. B.; Granata, M.; Grant, A.; Gras, S.; Gray, C.; Greco, G.; Green, A. C.; Groot, P.; Grote, H.; Grunewald, S.; Guidi, G. M.; Guo, X.; Gupta, A.; Gupta, M. K.; Gushwa, K. E.; Gustafson, E. K.; Gustafson, R.; Hacker, J. J.; Hall, B. R.; Hall, E. D.; Hammond, G.; Haney, M.; Hanke, M. M.; Hanks, J.; Hanna, C.; Hannam, M. D.; Hanson, J.; Hardwick, T.; Harms, J.; Harry, G. M.; Harry, I. W.; Hart, M. J.; Hartman, M. T.; Haster, C.-J.; Haughian, K.; Healy, J.; Heidmann, A.; Heintze, M. C.; Heitmann, H.; Hello, P.; Hemming, G.; Hendry, M.; Heng, I. S.; Hennig, J.; Henry, J.; Heptonstall, A. W.; Heurs, M.; Hild, S.; Hoak, D.; Hofman, D.; Holt, K.; Holz, D. E.; Hopkins, P.; Hough, J.; Houston, E. A.; Howell, E. J.; Hu, Y. M.; Huang, S.; Huerta, E. A.; Huet, D.; Hughey, B.; Husa, S.; Huttner, S. H.; Huynh-Dinh, T.; Indik, N.; Ingram, D. R.; Inta, R.; Isa, H. N.; Isac, J.-M.; Isi, M.; Isogai, T.; Iyer, B. R.; Izumi, K.; Jacqmin, T.; Jang, H.; Jani, K.; Jaranowski, P.; Jawahar, S.; Jian, L.; Jiménez-Forteza, F.; Johnson, W. W.; Johnson-McDaniel, N. K.; Jones, D. I.; Jones, R.; Jonker, R. J. G.; Ju, L.; K, Haris; Kalaghatgi, C. V.; Kalogera, V.; Kandhasamy, S.; Kang, G.; Kanner, J. B.; Kapadia, S. J.; Karki, S.; Karvinen, K. S.; Kasprzack, M.; Katsavounidis, E.; Katzman, W.; Kaufer, S.; Kaur, T.; Kawabe, K.; Kéfélian, F.; Kehl, M. S.; Keitel, D.; Kelley, D. B.; Kells, W.; Kennedy, R.; Key, J. S.; Khalili, F. Y.; Khan, I.; Khan, S.; Khan, Z.; Khazanov, E. A.; Kijbunchoo, N.; Kim, Chi-Woong; Kim, Chunglee; Kim, J.; Kim, K.; Kim, N.; Kim, W.; Kim, Y.-M.; Kimbrell, S. J.; King, E. J.; King, P. J.; Kissel, J. S.; Klein, B.; Kleybolte, L.; Klimenko, S.; Koehlenbeck, S. M.; Koley, S.; Kondrashov, V.; Kontos, A.; Korobko, M.; Korth, W. Z.; Kowalska, I.; Kozak, D. B.; Kringel, V.; Królak, A.; Krueger, C.; Kuehn, G.; Kumar, P.; Kumar, R.; Kuo, L.; Kutynia, A.; Lackey, B. D.; Landry, M.; Lange, J.; Lantz, B.; Lasky, P. D.; Laxen, M.; Lazzarini, A.; Lazzaro, C.; Leaci, P.; Leavey, S.; Lebigot, E. O.; Lee, C. H.; Lee, H. K.; Lee, H. M.; Lee, K.; Lenon, A.; Leonardi, M.; Leong, J. R.; Leroy, N.; Letendre, N.; Levin, Y.; Lewis, J. B.; Li, T. G. F.; Libson, A.; Littenberg, T. B.; Lockerbie, N. A.; Lombardi, A. L.; London, L. T.; Lord, J. E.; Lorenzini, M.; Loriette, V.; Lormand, M.; Losurdo, G.; Lough, J. D.; Lousto, C. O.; Lovelace, G.; Lück, H.; Lundgren, A. P.; Lynch, R.; Ma, Y.; Machenschalk, B.; MacInnis, M.; Macleod, D. M.; Magaña-Sandoval, F.; Magaña Zertuche, L.; Magee, R. M.; Majorana, E.; Maksimovic, I.; Malvezzi, V.; Man, N.; Mandic, V.; Mangano, V.; Mansell, G. L.; Manske, M.; Mantovani, M.; Marchesoni, F.; Marion, F.; Márka, S.; Márka, Z.; Markosyan, A. S.; Maros, E.; Martelli, F.; Martellini, L.; Martin, I. W.; Martynov, D. V.; Marx, J. N.; Mason, K.; Masserot, A.; Massinger, T. J.; Masso-Reid, M.; Mastrogiovanni, S.; Matichard, F.; Matone, L.; Mavalvala, N.; Mazumder, N.; McCarthy, R.; McClelland, D. E.; McCormick, S.; McGuire, S. C.; McIntyre, G.; McIver, J.; McManus, D. J.; McRae, T.; McWilliams, S. T.; Meacher, D.; Meadors, G. D.; Meidam, J.; Melatos, A.; Mendell, G.; Mercer, R. A.; Merilh, E. L.; Merzougui, M.; Meshkov, S.; Messenger, C.; Messick, C.; Metzdorff, R.; Meyers, P. M.; Mezzani, F.; Miao, H.; Michel, C.; Middleton, H.; Mikhailov, E. E.; Milano, L.; Miller, A. L.; Miller, A.; Miller, B. B.; Miller, J.; Millhouse, M.; Minenkov, Y.; Ming, J.; Mirshekari, S.; Mishra, C.; Mitra, S.; Mitrofanov, V. P.; Mitselmakher, G.; Mittleman, R.; Moggi, A.; Mohan, M.; Mohapatra, S. R. P.; Montani, M.; Moore, B. C.; Moore, C. J.; Moraru, D.; Moreno, G.; Morriss, S. R.; Mossavi, K.; Mours, B.; Mow-Lowry, C. M.; Mueller, G.; Muir, A. W.; Mukherjee, Arunava; Mukherjee, D.; Mukherjee, S.; Mukund, N.; Mullavey, A.; Munch, J.; Murphy, D. J.; Murray, P. G.; Mytidis, A.; Nardecchia, I.; Naticchioni, L.; Nayak, R. K.; Nedkova, K.; Nelemans, G.; Nelson, T. J. N.; Neri, M.; Neunzert, A.; Newton, G.; Nguyen, T. T.; Nielsen, A. B.; Nissanke, S.; Nitz, A.; Nocera, F.; Nolting, D.; Normandin, M. E. N.; Nuttall, L. K.; Oberling, J.; Ochsner, E.; O'Dell, J.; Oelker, E.; Ogin, G. H.; Oh, J. J.; Oh, S. H.; Ohme, F.; Oliver, M.; Oppermann, P.; Oram, Richard J.; O'Reilly, B.; O'Shaughnessy, R.; Ottaway, D. J.; Overmier, H.; Owen, B. J.; Pai, A.; Pai, S. A.; Palamos, J. R.; Palashov, O.; Palomba, C.; Pal-Singh, A.; Pan, H.; Pankow, C.; Pannarale, F.; Pant, B. C.; Paoletti, F.; Paoli, A.; Papa, M. A.; Paris, H. R.; Parker, W.; Pascucci, D.; Pasqualetti, A.; Passaquieti, R.; Passuello, D.; Patricelli, B.; Patrick, Z.; Pearlstone, B. L.; Pedraza, M.; Pedurand, R.; Pekowsky, L.; Pele, A.; Penn, S.; Perreca, A.; Perri, L. M.; Pfeiffer, H. P.; Phelps, M.; Piccinni, O. J.; Pichot, M.; Piergiovanni, F.; Pierro, V.; Pillant, G.; Pinard, L.; Pinto, I. M.; Pitkin, M.; Poe, M.; Poggiani, R.; Popolizio, P.; Post, A.; Powell, J.; Prasad, J.; Predoi, V.; Prestegard, T.; Price, L. R.; Prijatelj, M.; Principe, M.; Privitera, S.; Prix, R.; Prodi, G. A.; Prokhorov, L.; Puncken, O.; Punturo, M.; Puppo, P.; Pürrer, M.; Qi, H.; Qin, J.; Qiu, S.; Quetschke, V.; Quintero, E. A.; Quitzow-James, R.; Raab, F. J.; Rabeling, D. S.; Radkins, H.; Raffai, P.; Raja, S.; Rajan, C.; Rakhmanov, M.; Rapagnani, P.; Raymond, V.; Razzano, M.; Re, V.; Read, J.; Reed, C. M.; Regimbau, T.; Rei, L.; Reid, S.; Reitze, D. H.; Rew, H.; Reyes, S. D.; Ricci, F.; Riles, K.; Rizzo, M.; Robertson, N. A.; Robie, R.; Robinet, F.; Rocchi, A.; Rolland, L.; Rollins, J. G.; Roma, V. J.; Romano, R.; Romanov, G.; Romie, J. H.; Rosińska, D.; Rowan, S.; Rüdiger, A.; Ruggi, P.; Ryan, K.; Sachdev, S.; Sadecki, T.; Sadeghian, L.; Sakellariadou, M.; Salconi, L.; Saleem, M.; Salemi, F.; Samajdar, A.; Sammut, L.; Sanchez, E. J.; Sandberg, V.; Sandeen, B.; Sanders, J. R.; Sassolas, B.; Sathyaprakash, B. S.; Saulson, P. R.; Sauter, O. E. S.; Savage, R. L.; Sawadsky, A.; Schale, P.; Schilling, R.; Schmidt, J.; Schmidt, P.; Schnabel, R.; Schofield, R. M. S.; Schönbeck, A.; Schreiber, E.; Schuette, D.; Schutz, B. F.; Scott, J.; Scott, S. M.; Sellers, D.; Sengupta, A. S.; Sentenac, D.; Sequino, V.; Sergeev, A.; Setyawati, Y.; Shaddock, D. A.; Shaffer, T.; Shahriar, M. S.; Shaltev, M.; Shapiro, B.; Shawhan, P.; Sheperd, A.; Shoemaker, D. H.; Shoemaker, D. M.; Siellez, K.; Siemens, X.; Sieniawska, M.; Sigg, D.; Silva, A. D.; Singer, A.; Singer, L. P.; Singh, A.; Singh, R.; Singhal, A.; Sintes, A. M.; Slagmolen, B. J. J.; Smith, J. R.; Smith, N. D.; Smith, R. J. E.; Son, E. J.; Sorazu, B.; Sorrentino, F.; Souradeep, T.; Srivastava, A. K.; Staley, A.; Steinke, M.; Steinlechner, J.; Steinlechner, S.; Steinmeyer, D.; Stephens, B. C.; Stevenson, S. P.; Stone, R.; Strain, K. A.; Straniero, N.; Stratta, G.; Strauss, N. A.; Strigin, S.; Sturani, R.; Stuver, A. L.; Summerscales, T. Z.; Sun, L.; Sunil, S.; Sutton, P. J.; Swinkels, B. L.; Szczepańczyk, M. J.; Tacca, M.; Talukder, D.; Tanner, D. B.; Tápai, M.; Tarabrin, S. P.; Taracchini, A.; Taylor, R.; Theeg, T.; Thirugnanasambandam, M. P.; Thomas, E. G.; Thomas, M.; Thomas, P.; Thorne, K. A.; Thorne, K. S.; Thrane, E.; Tiwari, S.; Tiwari, V.; Tokmakov, K. V.; Toland, K.; Tomlinson, C.; Tonelli, M.; Tornasi, Z.; Torres, C. V.; Torrie, C. I.; Töyrä, D.; Travasso, F.; Traylor, G.; Trifirò, D.; Tringali, M. C.; Trozzo, L.; Tse, M.; Turconi, M.; Tuyenbayev, D.; Ugolini, D.; Unnikrishnan, C. S.; Urban, A. L.; Usman, S. A.; Vahlbruch, H.; Vajente, G.; Valdes, G.; Vallisneri, M.; van Bakel, N.; van Beuzekom, M.; van den Brand, J. F. J.; Van Den Broeck, C.; Vander-Hyde, D. C.; van der Schaaf, L.; van der Sluys, M. V.; van Heijningen, J. V.; Vano-Vinuales, A.; van Veggel, A. A.; Vardaro, M.; Vass, S.; Vasúth, M.; Vaulin, R.; Vecchio, A.; Vedovato, G.; Veitch, J.; Veitch, P. J.; Venkateswara, K.; Verkindt, D.; Vetrano, F.; Viceré, A.; Vinciguerra, S.; Vine, D. J.; Vinet, J.-Y.; Vitale, S.; Vo, T.; Vocca, H.; Vorvick, C.; Voss, D. V.; Vousden, W. D.; Vyatchanin, S. P.; Wade, A. R.; Wade, L. E.; Wade, M.; Walker, M.; Wallace, L.; Walsh, S.; Wang, G.; Wang, H.; Wang, M.; Wang, X.; Wang, Y.; Ward, R. L.; Warner, J.; Was, M.; Weaver, B.; Wei, L.-W.; Weinert, M.; Weinstein, A. J.; Weiss, R.; Wen, L.; Weßels, P.; Westphal, T.; Wette, K.; Whelan, J. T.; Whiting, B. F.; Williams, R. D.; Williamson, A. R.; Willis, J. L.; Willke, B.; Wimmer, M. H.; Winkler, W.; Wipf, C. C.; Wittel, H.; Woan, G.; Woehler, J.; Worden, J.; Wright, J. L.; Wu, D. S.; Wu, G.; Yablon, J.; Yam, W.; Yamamoto, H.; Yancey, C. C.; Yu, H.; Yvert, M.; ZadroŻny, A.; Zangrando, L.; Zanolin, M.; Zendri, J.-P.; Zevin, M.; Zhang, L.; Zhang, M.; Zhang, Y.; Zhao, C.; Zhou, M.; Zhou, Z.; Zhu, X. J.; Zucker, M. E.; Zuraw, S. E.; Zweizig, J.; Boyle, M.; Brügmann, B.; Campanelli, M.; Chu, T.; Clark, M.; Haas, R.; Hemberger, D.; Hinder, I.; Kidder, L. E.; Kinsey, M.; Laguna, P.; Ossokine, S.; Pan, Y.; Röver, C.; Scheel, M.; Szilagyi, B.; Teukolsky, S.; Zlochower, Y.; LIGO Scientific Collaboration; Virgo Collaboration

2016-10-01

This paper presents updated estimates of source parameters for GW150914, a binary black-hole coalescence event detected by the Laser Interferometer Gravitational-wave Observatory (LIGO) in 2015 [Abbott et al. Phys. Rev. Lett. 116, 061102 (2016).]. Abbott et al. [Phys. Rev. Lett. 116, 241102 (2016).] presented parameter estimation of the source using a 13-dimensional, phenomenological precessing-spin model (precessing IMRPhenom) and an 11-dimensional nonprecessing effective-one-body (EOB) model calibrated to numerical-relativity simulations, which forces spin alignment (nonprecessing EOBNR). Here, we present new results that include a 15-dimensional precessing-spin waveform model (precessing EOBNR) developed within the EOB formalism. We find good agreement with the parameters estimated previously [Abbott et al. Phys. Rev. Lett. 116, 241102 (2016).], and we quote updated component masses of 35-3+5 M⊙ and 3 0-4+3 M⊙ (where errors correspond to 90% symmetric credible intervals). We also present slightly tighter constraints on the dimensionless spin magnitudes of the two black holes, with a primary spin estimate <0.65 and a secondary spin estimate <0.75 at 90% probability. Abbott et al. [Phys. Rev. Lett. 116, 241102 (2016).] estimated the systematic parameter-extraction errors due to waveform-model uncertainty by combining the posterior probability densities of precessing IMRPhenom and nonprecessing EOBNR. Here, we find that the two precessing-spin models are in closer agreement, suggesting that these systematic errors are smaller than previously quoted.

Platform for Post-Processing Waveform-Based NDE

NASA Technical Reports Server (NTRS)

Roth, Don J.

2010-01-01

Signal- and image-processing methods are commonly needed to extract information from the waves, improve resolution of, and highlight defects in an image. Since some similarity exists for all waveform-based nondestructive evaluation (NDE) methods, it would seem that a common software platform containing multiple signal- and image-processing techniques to process the waveforms and images makes sense where multiple techniques, scientists, engineers, and organizations are involved. NDE Wave & Image Processor Version 2.0 software provides a single, integrated signal- and image-processing and analysis environment for total NDE data processing and analysis. It brings some of the most useful algorithms developed for NDE over the past 20 years into a commercial-grade product. The software can import signal/spectroscopic data, image data, and image series data. This software offers the user hundreds of basic and advanced signal- and image-processing capabilities including esoteric 1D and 2D wavelet-based de-noising, de-trending, and filtering. Batch processing is included for signal- and image-processing capability so that an optimized sequence of processing operations can be applied to entire folders of signals, spectra, and images. Additionally, an extensive interactive model-based curve-fitting facility has been included to allow fitting of spectroscopy data such as from Raman spectroscopy. An extensive joint-time frequency module is included for analysis of non-stationary or transient data such as that from acoustic emission, vibration, or earthquake data.

Quantitative assessment of 12-lead ECG synthesis using CAVIAR.

PubMed

Scherer, J A; Rubel, P; Fayn, J; Willems, J L

1992-01-01

The objective of this study is to assess the performance of patient-specific segment-specific (PSSS) synthesis in QRST complexes using CAVIAR, a new method of the serial comparison for electrocardiograms and vectorcardiograms. A collection of 250 multi-lead recordings from the Common Standards for Quantitative Electrocardiography (CSE) diagnostic pilot study is employed. QRS and ST-T segments are independently synthesized using the PSSS algorithm so that the mean-squared error between the original and estimated waveforms is minimized. CAVIAR compares the recorded and synthesized QRS and ST-T segments and calculates the mean-quadratic deviation as a measure of error. The results of this study indicate that estimated QRS complexes are good representatives of their recorded counterparts, and the integrity of the spatial information is maintained by the PSSS synthesis process. Analysis of the ST-T segments suggests that the deviations between recorded and synthesized waveforms are considerably greater than those associated with the QRS complexes. The poorer performance of the ST-T segments is attributed to magnitude normalization of the spatial loops, low-voltage passages, and noise interference. Using the mean-quadratic deviation and CAVIAR as methods of performance assessment, this study indicates that the PSSS-synthesis algorithm accurately maintains the signal information within the 12-lead electrocardiogram.

The automatic extraction of pitch perturbation using microcomputers: some methodological considerations.

PubMed

Deem, J F; Manning, W H; Knack, J V; Matesich, J S

1989-09-01

A program for the automatic extraction of jitter (PAEJ) was developed for the clinical measurement of pitch perturbations using a microcomputer. The program currently includes 12 implementations of an algorithm for marking the boundary criteria for a fundamental period of vocal fold vibration. The relative sensitivity of these extraction procedures for identifying the pitch period was compared using sine waves. Data obtained to date provide information for each procedure concerning the effects of waveform peakedness and slope, sample duration in cycles, noise level of the analysis system with both direct and tape recorded input, and the influence of interpolation. Zero crossing extraction procedures provided lower jitter values regardless of sine wave frequency or sample duration. The procedures making use of positive- or negative-going zero crossings with interpolation provided the lowest measures of jitter with the sine wave stimuli. Pilot data obtained with normal-speaking adults indicated that jitter measures varied as a function of the speaker, vowel, and sample duration.

Time-Scale Modification of Complex Acoustic Signals in Noise

DTIC Science & Technology

1994-02-04

of a response from a closing stapler . 15 6 Short-time processing of long waveforms. 16 7 Time-scale expansion (x 2) of sequence of transients using...filter bank/overlap- add. 17 8 Time-scale expansion (x2) of a closing stapler using filter bank/overlap-add. 18 9 Composite subband time-scale...INTRODUCTION Short-duration complex sounds, as from the closing of a stapler or the tapping of a drum stick, often consist of a series of brief

Photonic microwave waveforms generation based on pulse carving and superposition in time-domain

NASA Astrophysics Data System (ADS)

Xia, Yi; Jiang, Yang; Zi, Yuejiao; He, Yutong; Tian, Jing; Zhang, Xiaoyu; Luo, Hao; Dong, Ruyang

2018-05-01

A novel photonic approach for various microwave waveforms generation based on time-domain synthesis is theoretically analyzed and experimentally investigated. In this scheme, two single-drive Mach-Zehnder modulators are used for pulses shaping. After shifting the phase and implementing envelopes superposition of the pulses, desired waveforms can be achieved in time-domain. The theoretic analysis and simulations are presented. In the experimental demonstrations, a triangular waveform, square waveform, and half duty cycle sawtooth (or reversed-sawtooth) waveform are generated successfully. By utilizing time multiplexing technique, a frequency-doubled sawtooth (or reversed-sawtooth) waveform with 100% duty cycle can be obtained. In addition, a fundamental frequency sawtooth (or reversed-sawtooth) waveform with 100% duty cycle can also be achieved by the superposition of square waveform and frequency-doubled sawtooth waveform.

Core-Mantle Boundary Complexities beneath the Mid-Pacific

NASA Astrophysics Data System (ADS)

Sun, D.; Helmberger, D. V.; Jackson, J. M.

2016-12-01

The detailed core-mantle boundary (CMB) structures beneath the Mid-Pacific are important to map the boundary of Large Low Shear Velocity Province (LLSVP) and the location of ultra-low velocity zone (ULVZ) related to the LLSVP and the D" layer, which are crucial for answering the key questions regarding to the mantle dynamics. Seismic data from deep earthquakes in the Fiji-Tonga region recorded by stations of USArray provide great sampling of the CMB beneath the Mid-Pacific. Here we explore the USArray data with different seismic phases to study the CMB complexities beneath the Mid-Pacific. First, we examined the differential travel time and amplitude between ScS and S for data at western US and confirm the northeastern boundary of the mid-Pacific LLSVP. The delayed ScS-S travel times and smaller amplitude of ScS require the existence of ULVZ locally. Secondly, the Sdiff data recorded by stations at central US shows variation in multi-pathing, that is, the presence of secondary arrivals following the S phase at diffracted distances (Sdiff) which suggests that the waveform complexity is due to structures at the eastern edge of the mid-Pacific LLSVP. This study reinforces previous studies that indicate late arrivals occurring after the primary Sdiff arrivals. A tapered wedge structure with low shear velocity allows for wave energy trapping, producing the observed waveform complexity and delayed arrivals at large distances. The location of the low velocity anomaly agrees with that inferred from the ScS-S measurements. We also observed advanced SV arrivals, which can be explained by the emerging of the D" discontinuity to the east of the boundary of the LLSVP to produce a "pseudo anisotropy". Thirdly, the arrivals of the SPdKS phase support the presence of an ULVZ within a two-humped LLSVP. A sharp 10 secs jump of the differential travel time between S and SKS (TS-SKS) across distance range of 5° is observed. The associated SKS waveform distortions suggest that the differential travel time anomaly is mainly controlled by the SKS, which is explained by a possible slab subducted to the lower mantle.

Characterizing Micro- and Macro-Scale Seismicity from Bayou Corne, Louisiana

NASA Astrophysics Data System (ADS)

Baig, A. M.; Urbancic, T.; Karimi, S.

2013-12-01

The initiation of felt seismicity in Bayou Corne, Louisiana, coupled with other phenomena detected by residents on the nearby housing development, prompted a call to install a broadband seismic network to monitor subsurface deformation. The initial deployment was in place to characterize the deformation contemporaneous with the formation of a sinkhole located in close proximity to a salt dome. Seismic events generated during this period followed a swarm-like behaviour with moment magnitudes culminating around Mw2.5. However, the seismic data recorded during this sequence suffer from poor signal to noise, onsets that are very difficult to pick, and the presence of a significant amount of energy arriving later in the waveforms. Efforts to understand the complexity in these waveforms are ongoing, and involve invoking the complexities inherent in recording in a highly attenuating swamp overlying a complex three-dimensional structure with the strong material property contrast of the salt dome. In order to understand the event character, as well as to locally lower the completeness threshold of the sequence, a downhole array of 15 Hz sensors was deployed in a newly drilled well around the salt dome. Although the deployment lasted a little over a month in duration, over 1000 events were detected down to moment magnitude -Mw3. Waveform quality tended to be excellent, with very distinct P and S wave arrivals observable across the array for most events. The highest magnitude events were seen as well on the surface network and allowed for the opportunity to observe the complexities introduced by the site effects, while overcoming the saturation effects on the higher-frequency downhole geophones. This hybrid downhole and surface array illustrates how a full picture of subsurface deformation is only made possible by combining the high-frequency downhole instrumentation to see the microseismicity complemented with a broadband array to accurately characterize the source parameters for the larger magnitude events. Our presentation is focused on investigating this deformation, characterizing the scaling behaviour and the other source processes by taking advantage of the wide-band afforded to us through the deployment.

Retrieving rupture history using waveform inversions in time sequence

NASA Astrophysics Data System (ADS)

Yi, L.; Xu, C.; Zhang, X.

2017-12-01

The rupture history of large earthquakes is generally regenerated using the waveform inversion through utilizing seismological waveform records. In the waveform inversion, based on the superposition principle, the rupture process is linearly parameterized. After discretizing the fault plane into sub-faults, the local source time function of each sub-fault is usually parameterized using the multi-time window method, e.g., mutual overlapped triangular functions. Then the forward waveform of each sub-fault is synthesized through convoluting the source time function with its Green function. According to the superposition principle, these forward waveforms generated from the fault plane are summarized in the recorded waveforms after aligning the arrival times. Then the slip history is retrieved using the waveform inversion method after the superposing of all forward waveforms for each correspond seismological waveform records. Apart from the isolation of these forward waveforms generated from each sub-fault, we also realize that these waveforms are gradually and sequentially superimposed in the recorded waveforms. Thus we proposed a idea that the rupture model is possibly detachable in sequent rupture times. According to the constrained waveform length method emphasized in our previous work, the length of inverted waveforms used in the waveform inversion is objectively constrained by the rupture velocity and rise time. And one essential prior condition is the predetermined fault plane that limits the duration of rupture time, which means the waveform inversion is restricted in a pre-set rupture duration time. Therefore, we proposed a strategy to inverse the rupture process sequentially using the progressively shift rupture times as the rupture front expanding in the fault plane. And we have designed a simulation inversion to test the feasibility of the method. Our test result shows the prospect of this idea that requiring furthermore investigation.

A Quantitative Evaluation of SCEC Community Velocity Model Version 3.0

NASA Astrophysics Data System (ADS)

Chen, P.; Zhao, L.; Jordan, T. H.

2003-12-01

We present a systematic methodology for evaluating and improving 3D seismic velocity models using broadband waveform data from regional earthquakes. The operator that maps a synthetic waveform into an observed waveform is expressed in the Rytov form D(ω ) = {exp}[{i} ω δ τ {p}(ω ) - ω δ τ {q}(ω )]. We measure the phase delay time δ τ p(ω ) and the amplitude reduction time δ τ q(ω ) as a function of frequency ω using Gee & Jordan's [1992] isolation-filter technique, and we correct the data for frequency-dependent interference and frequency-independent source statics. We have applied this procedure to a set of small events in Southern California. Synthetic seismograms were computed using three types of velocity models: the 1D Standard Southern California Crustal Model (SoCaL) [Dreger & Helmberger, 1993], the 3D SCEC Community Velocity Model, Version 3.0 (CVM3.0) [Magistrale et al., 2000], and a set of path-averaged 1D models (A1D) extracted from CVM3.0 by horizontally averaging wave slownesses along source-receiver paths. The 3D synthetics were computed using K. Olsen's finite difference code. More than 1000 measurements were made on both P and S waveforms at frequencies ranging from 0.2 to 1 Hz. Overall, the 3D model provided a substantially better fit to the waveform data than either laterally homogeneous or path-dependent 1D models. Relative to SoCaL, CVM3.0 provided a variance reduction of about 64% in δ τ p, and 41% in δ τ q. Relative to A1D, the variance reduction is about 46% and 20%, respectively. The same set of measurements can be employed to invert for both seismic source properties and seismic velocity structures. Fully numerical methods are being developed to compute the Fréchet kernels for these measurements [L. Zhao et. al., this meeting]. This methodology thus provides a unified framework for regional studies of seismic sources and Earth structure in Southern California and elsewhere.

Accuracy and precision of gravitational-wave models of inspiraling neutron star-black hole binaries with spin: Comparison with matter-free numerical relativity in the low-frequency regime

NASA Astrophysics Data System (ADS)

Bhagwat, Swetha; Kumar, Prayush; Barkett, Kevin; Afshari, Nousha; Brown, Duncan A.; Lovelace, Geoffrey; Scheel, Mark A.; Szilagyi, Bela; LIGO Collaboration

2016-03-01

Detection of gravitational wave involves extracting extremely weak signal from noisy data and their detection depends crucially on the accuracy of the signal models. The most accurate models of compact binary coalescence are known to come from solving the Einstein's equation numerically without any approximations. However, this is computationally formidable. As a more practical alternative, several analytic or semi analytic approximations are developed to model these waveforms. However, the work of Nitz et al. (2013) demonstrated that there is disagreement between these models. We present a careful follow up study on accuracies of different waveform families for spinning black-hole neutron star binaries, in context of both detection and parameter estimation and find that SEOBNRv2 to be the most faithful model. Post Newtonian models can be used for detection but we find that they could lead to large parameter bias. Supported by National Science Foundation (NSF) Awards No. PHY-1404395 and No. AST-1333142.

Automated Epileptiform Spike Detection via Affinity Propagation-Based Template Matching

PubMed Central

Thomas, John; Jin, Jing; Dauwels, Justin; Cash, Sydney S.; Westover, M. Brandon

2018-01-01

Interictal epileptiform spikes are the key diagnostic biomarkers for epilepsy. The clinical gold standard of spike detection is visual inspection performed by neurologists. This is a tedious, time-consuming, and expert-centered process. The development of automated spike detection systems is necessary in order to provide a faster and more reliable diagnosis of epilepsy. In this paper, we propose an efficient template matching spike detector based on a combination of spike and background waveform templates. We generate a template library by clustering a collection of spikes and background waveforms extracted from a database of 50 patients with epilepsy. We benchmark the performance of five clustering techniques based on the receiver operating characteristic (ROC) curves. In addition, background templates are integrated with existing spike templates to improve the overall performance. The affinity propagation-based template matching system with a combination of spike and background templates is shown to outperform the other four conventional methods with the highest area-under-curve (AUC) of 0.953. PMID:29060543

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

Wang, C. L.; Funk, L. L.; Riedel, R. A.

3He gas based neutron linear-position-sensitive detectors (LPSDs) have been applied for many neutron scattering instruments. Traditional Pulse-Height Analysis (PHA) for Neutron-Gamma Discrimination (NGD) resulted in the neutron-gamma efficiency ratio on the orders of 10 5-10 6. The NGD ratios of 3He detectors need to be improved for even better scientific results from neutron scattering. Digital Signal Processing (DSP) analyses of waveforms were proposed for obtaining better NGD ratios, based on features extracted from rise-time, pulse amplitude, charge integration, a simplified Wiener filter, and the cross-correlation between individual and template waveforms of neutron and gamma events. Fisher linear discriminant analysis (FLDA)more » and three multivariate analyses (MVAs) of the features were performed. The NGD ratios are improved by about 10 2-10 3 times compared with the traditional PHA method. Finally, our results indicate the NGD capabilities of 3He tube detectors can be significantly improved with subspace-learning based methods, which may result in a reduced data-collection time and better data quality for further data reduction.« less

Implementation of an iPhone wireless accelerometer application for the quantification of reflex response.

PubMed

LeMoyne, Robert; Mastroianni, Timothy; Grundfest, Warren; Nishikawa, Kiisa

2013-01-01

The patellar tendon reflex represents an inherent aspect of the standard neurological evaluation. The features of the reflex response provide initial perspective regarding the status of the nervous system. An iPhone wireless accelerometer application integrated with a potential energy impact pendulum attached to a reflex hammer has been successfully developed, tested, and evaluated for quantifying the patellar tendon reflex. The iPhone functions as a wireless accelerometer platform. The wide coverage range of the iPhone enables the quantification of reflex response samples in rural and remote settings. The iPhone has the capacity to transmit the reflex response acceleration waveform by wireless transmission through email. Automated post-processing of the acceleration waveform provides feature extraction of the maximum acceleration of the reflex response ascertained after evoking the patellar tendon reflex. The iPhone wireless accelerometer application demonstrated the utility of the smartphone as a biomedical device, while providing accurate and consistent quantification of the reflex response.

A method to calibrate phase fluctuation in polarization-sensitive swept-source optical coherence tomography

NASA Astrophysics Data System (ADS)

Lu, Zenghai; Kasaragod, Deepa K.; Matcher, Stephen J.

2011-06-01

A phase fluctuation calibration method is presented for polarization-sensitive swept-source optical coherence tomography (PS-SS-OCT) using continuous polarization modulation. The method consists of the generation of a continuous triggered tone-burst waveform rather than an asynchronous waveform by use of a function generator and the removal of the global phases of the measured Jones matrices by use of matrix normalization. This could remove the use of auxiliary optical components for the phase fluctuation compensation in the system, which reduces the system complexity. Phase fluctuation calibration is necessary to obtain the reference Jones matrix by averaging the measured Jones matrices at sample surfaces. Measurements on an equine tendon sample were made by the PS-SS-OCT system to validate the proposed method.

Pulse oximeter as a sensor of fluid responsiveness: do we have our finger on the best solution?

PubMed Central

Monnet, Xavier; Lamia, Bouchra; Teboul, Jean-Louis

2005-01-01

The pulse oximetry plethysmographic signal resembles the peripheral arterial pressure waveform, and the degree of respiratory variation in the pulse oximetry wave is close to the degree of respiratory arterial pulse pressure variation. Thus, it is tempting to speculate that pulse oximetry can be used to assess preload responsiveness in mechanically ventilated patients. In this commentary we briefly review the complex meaning of the pulse oximetry plethysmographic signal and highlight the advantages, limitations and pitfalls of the pulse oximetry method. Future studies including volume challenge must be performed to test whether the pulse oximetry waveform can really serve as a nonivasive tool for the guidance of fluid therapy in patients receiving mechanical ventilation in intensive care units and in operating rooms. PMID:16277729

Seismic Observations of the Mid-Pacific Large Low Shear Velocity Province

NASA Astrophysics Data System (ADS)

Chan, A.; Helmberger, D. V.; Sun, D.; Li, D.; Jackson, J. M.

2015-12-01

Seismic data from earthquakes originating in the Fiji-Tonga region exhibits waveform complexity of a number of phases which may be attributed to various structures along ray paths to stations of USArray, including anomalous structures at the core-mantle boundary. The data shows variation in multipathing, that is, the presence of secondary arrivals following the S phase at diffracted distances (Sdiff) which suggests that the waveform complexity is due to structures at the eastern edge of the mid-Pacific Large Low Shear Velocity Province (LLSVP). This study examines data from earthquake events while the Transportable Array portion of USArray was situated in the midwest United States, reinforcing previous studies that indicate late arrivals occurring as long as 26 seconds after the primary arrivals (To et al., 2011). Using earth flattening transformations and finite difference methods, simulations of tapered wedge structures of low velocity material allow for wave energy trapping, producing the observed waveform complexity and delayed arrivals at large distances, with such structures having characteristic properties of, for example, a height of 70 km, in-plane extent more than 1000 km, and shear wave velocity drop of 3% at the top to 15% at the bottom relative to PREM. Differential arrival times for SH and SV components suggest anisotropy and possible wave propagation through downgoing slabs beneath the source region. The arrivals of the SPdKS phase further support the presence of an ultra-low velocity zone (ULVZ) within a two-humped LLSVP. Some systematic delays in arrival times of multiple phases for distances less than 102º are accounted for and attributed to the presence of a mantle slab underneath the continental United States. Comparisons to seismic data from earthquakes originating from other locations further constrain depths of the deep mantle structures. Possible explanations include iron-enrichment of deep mantle phases.

Onboard software of Plasma Wave Experiment aboard Arase: instrument management and signal processing of Waveform Capture/Onboard Frequency Analyzer

NASA Astrophysics Data System (ADS)

Matsuda, Shoya; Kasahara, Yoshiya; Kojima, Hirotsugu; Kasaba, Yasumasa; Yagitani, Satoshi; Ozaki, Mitsunori; Imachi, Tomohiko; Ishisaka, Keigo; Kumamoto, Atsushi; Tsuchiya, Fuminori; Ota, Mamoru; Kurita, Satoshi; Miyoshi, Yoshizumi; Hikishima, Mitsuru; Matsuoka, Ayako; Shinohara, Iku

2018-05-01

We developed the onboard processing software for the Plasma Wave Experiment (PWE) onboard the Exploration of energization and Radiation in Geospace, Arase satellite. The PWE instrument has three receivers: Electric Field Detector, Waveform Capture/Onboard Frequency Analyzer (WFC/OFA), and the High-Frequency Analyzer. We designed a pseudo-parallel processing scheme with a time-sharing system and achieved simultaneous signal processing for each receiver. Since electric and magnetic field signals are processed by the different CPUs, we developed a synchronized observation system by using shared packets on the mission network. The OFA continuously measures the power spectra, spectral matrices, and complex spectra. The OFA obtains not only the entire ELF/VLF plasma waves' activity but also the detailed properties (e.g., propagation direction and polarization) of the observed plasma waves. We performed simultaneous observation of electric and magnetic field data and successfully obtained clear wave properties of whistler-mode chorus waves using these data. In order to measure raw waveforms, we developed two modes for the WFC, `chorus burst mode' (65,536 samples/s) and `EMIC burst mode' (1024 samples/s), for the purpose of the measurement of the whistler-mode chorus waves (typically in a frequency range from several hundred Hz to several kHz) and the EMIC waves (typically in a frequency range from a few Hz to several hundred Hz), respectively. We successfully obtained the waveforms of electric and magnetic fields of whistler-mode chorus waves and ion cyclotron mode waves along the Arase's orbit. We also designed the software-type wave-particle interaction analyzer mode. In this mode, we measure electric and magnetic field waveforms continuously and transfer them to the mission data recorder onboard the Arase satellite. We also installed an onboard signal calibration function (onboard SoftWare CALibration; SWCAL). We performed onboard electric circuit diagnostics and antenna impedance measurement of the wire-probe antennas along the orbit. We utilize the results obtained using the SWCAL function when we calibrate the spectra and waveforms obtained by the PWE.[Figure not available: see fulltext.

Extraction of fault component from abnormal sound in diesel engines using acoustic signals

NASA Astrophysics Data System (ADS)

Dayong, Ning; Changle, Sun; Yongjun, Gong; Zengmeng, Zhang; Jiaoyi, Hou

2016-06-01

In this paper a method for extracting fault components from abnormal acoustic signals and automatically diagnosing diesel engine faults is presented. The method named dislocation superimposed method (DSM) is based on the improved random decrement technique (IRDT), differential function (DF) and correlation analysis (CA). The aim of DSM is to linearly superpose multiple segments of abnormal acoustic signals because of the waveform similarity of faulty components. The method uses sample points at the beginning of time when abnormal sound appears as the starting position for each segment. In this study, the abnormal sound belonged to shocking faulty type; thus, the starting position searching method based on gradient variance was adopted. The coefficient of similar degree between two same sized signals is presented. By comparing with a similar degree, the extracted fault component could be judged automatically. The results show that this method is capable of accurately extracting the fault component from abnormal acoustic signals induced by faulty shocking type and the extracted component can be used to identify the fault type.

ECG Based Heart Arrhythmia Detection Using Wavelet Coherence and Bat Algorithm

NASA Astrophysics Data System (ADS)

Kora, Padmavathi; Sri Rama Krishna, K.

2016-12-01

Atrial fibrillation (AF) is a type of heart abnormality, during the AF electrical discharges in the atrium are rapid, results in abnormal heart beat. The morphology of ECG changes due to the abnormalities in the heart. This paper consists of three major steps for the detection of heart diseases: signal pre-processing, feature extraction and classification. Feature extraction is the key process in detecting the heart abnormality. Most of the ECG detection systems depend on the time domain features for cardiac signal classification. In this paper we proposed a wavelet coherence (WTC) technique for ECG signal analysis. The WTC calculates the similarity between two waveforms in frequency domain. Parameters extracted from WTC function is used as the features of the ECG signal. These features are optimized using Bat algorithm. The Levenberg Marquardt neural network classifier is used to classify the optimized features. The performance of the classifier can be improved with the optimized features.

Gas Reservoir Identification Basing on Deep Learning of Seismic-print Characteristics

NASA Astrophysics Data System (ADS)

Cao, J.; Wu, S.; He, X.

2016-12-01

Reservoir identification based on seismic data analysis is the core task in oil and gas geophysical exploration. The essence of reservoir identification is to identify the properties of rock pore fluid. We developed a novel gas reservoir identification method named seismic-print analysis by imitation of the vocal-print analysis techniques in speaker identification. The term "seismic-print" is referred to the characteristics of the seismic waveform which can identify determinedly the property of the geological objectives, for instance, a nature gas reservoir. Seismic-print can be characterized by one or a few parameters named as seismic-print parameters. It has been proven that gas reservoirs are of characteristics of negative 1-order cepstrum coefficient anomaly and Positive 2-order cepstrum coefficient anomaly, concurrently. The method is valid for sandstone gas reservoir, carbonate reservoir and shale gas reservoirs, and the accuracy rate may reach up to 90%. There are two main problems to deal with in the application of seismic-print analysis method. One is to identify the "ripple" of a reservoir on the seismogram, and another is to construct the mapping relationship between the seismic-print and the gas reservoirs. Deep learning developed in recent years is of the ability to reveal the complex non-linear relationship between the attribute and the data, and of ability to extract automatically the features of the objective from the data. Thus, deep learning could been used to deal with these two problems. There are lots of algorithms to carry out deep learning. The algorithms can be roughly divided into two categories: Belief Networks Network (DBNs) and Convolutional Neural Network (CNN). DBNs is a probabilistic generative model, which can establish a joint distribution of the observed data and tags. CNN is a feedforward neural network, which can be used to extract the 2D structure feature of the input data. Both DBNs and CNN can be used to deal with seismic data. We use an improved DBNs to identify carbonate rocks from log data, the accuracy rate can reach up to 83%. DBNs is used to deal with seismic waveform data, more information is obtained. The work was supported by NSFC under grant No. 41430323 and No. 41274128, and State Key Lab. of Oil and Gas Reservoir Geology and Exploration.

Using time-frequency analysis of the photoplethysmographic waveform to detect the withdrawal of 900 mL of blood.

PubMed

Scully, Christopher G; Selvaraj, Nandakumar; Romberg, Frederick W; Wardhan, Richa; Ryan, John; Florian, John P; Silverman, David G; Shelley, Kirk H; Chon, Ki H

2012-07-01

We designed this study to determine if 900 mL of blood withdrawal during spontaneous breathing in healthy volunteers could be detected by examining the time-varying spectral amplitude of the photoplethysmographic (PPG) waveform in the heart rate frequency band and/or in the breathing rate frequency band before significant changes occurred in heart rate or arterial blood pressure. We also identified the best PPG probe site for early detection of blood volume loss by testing ear, finger, and forehead sites. Eight subjects had 900 mL of blood withdrawn followed by reinfusion of 900 mL of blood. Physiological monitoring included PPG waveforms from ear, finger, and forehead probe sites, standard electrocardiogram, and standard blood pressure cuff measurements. The time-varying amplitude sequences in the heart rate frequency band and breathing rate frequency band present in the PPG waveform were extracted from high-resolution time-frequency spectra. These amplitudes were used as a parameter for blood loss detection. Heart rate and arterial blood pressure did not significantly change during the protocol. Using time-frequency analysis of the PPG waveform from ear, finger, and forehead probe sites, the amplitude signal extracted at the frequency corresponding to the heart rate significantly decreased when 900 mL of blood was withdrawn, relative to baseline (all P < 0.05); for the ear, the corresponding signal decreased when only 300 mL of blood was withdrawn. The mean percent decrease in the amplitude of the heart rate component at 900 mL blood loss relative to baseline was 45.2% (38.2%), 42.0% (29.2%), and 42.3% (30.5%) for ear, finger, and forehead probe sites, respectively, with the lower 95% confidence limit shown in parentheses. After 900 mL blood reinfusion, the amplitude signal at the heart rate frequency showed a recovery towards baseline. There was a clear separation of amplitude values at the heart rate frequency between baseline and 900 mL blood withdrawal. Specificity and sensitivity were both found to be 87.5% with 95% confidence intervals (47.4%, 99.7%) for ear PPG signals for a chosen threshold value that was optimized to separate the 2 clusters of amplitude values (baseline and blood loss) at the heart rate frequency. Meanwhile, no significant changes in the spectral amplitude in the frequency band corresponding to respiration were found. A time-frequency spectral method detected blood loss in spontaneously breathing subjects before the onset of significant changes in heart rate or blood pressure. Spectral amplitudes at the heart rate frequency band were found to significantly decrease during blood loss in spontaneously breathing subjects, whereas those at the breathing rate frequency band did not significantly change. This technique may serve as a valuable tool in intraoperative and trauma settings to detect and monitor hemorrhage.

Detailed investigation of Long-Period activity at Campi Flegrei by Convolutive Independent Component Analysis

NASA Astrophysics Data System (ADS)

Capuano, P.; De Lauro, E.; De Martino, S.; Falanga, M.

2016-04-01

This work is devoted to the analysis of seismic signals continuously recorded at Campi Flegrei Caldera (Italy) during the entire year 2006. The radiation pattern associated with the Long-Period energy release is investigated. We adopt an innovative Independent Component Analysis algorithm for convolutive seismic series adapted and improved to give automatic procedures for detecting seismic events often buried in the high-level ambient noise. The extracted waveforms characterized by an improved signal-to-noise ratio allows the recognition of Long-Period precursors, evidencing that the seismic activity accompanying the mini-uplift crisis (in 2006), which climaxed in the three days from 26-28 October, had already started at the beginning of the month of October and lasted until mid of November. Hence, a more complete seismic catalog is then provided which can be used to properly quantify the seismic energy release. To better ground our results, we first check the robustness of the method by comparing it with other blind source separation methods based on higher order statistics; secondly, we reconstruct the radiation patterns of the extracted Long-Period events in order to link the individuated signals directly to the sources. We take advantage from Convolutive Independent Component Analysis that provides basic signals along the three directions of motion so that a direct polarization analysis can be performed with no other filtering procedures. We show that the extracted signals are mainly composed of P waves with radial polarization pointing to the seismic source of the main LP swarm, i.e. a small area in the Solfatara, also in the case of the small-events, that both precede and follow the main activity. From a dynamical point of view, they can be described by two degrees of freedom, indicating a low-level of complexity associated with the vibrations from a superficial hydrothermal system. Our results allow us to move towards a full description of the complexity of the source, which can be used, by means of the small-intensity precursors, for hazard-model development and forecast-model testing, showing an illustrative example of the applicability of the CICA method to regions with low seismicity in high ambient noise.

Harmonic arbitrary waveform generator

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

Roberts, Brock Franklin

2017-11-28

High frequency arbitrary waveforms have applications in radar, communications, medical imaging, therapy, electronic warfare, and charged particle acceleration and control. State of the art arbitrary waveform generators are limited in the frequency they can operate by the speed of the Digital to Analog converters that directly create their arbitrary waveforms. The architecture of the Harmonic Arbitrary Waveform Generator allows the phase and amplitude of the high frequency content of waveforms to be controlled without taxing the Digital to Analog converters that control them. The Harmonic Arbitrary Waveform Generator converts a high frequency input, into a precision, adjustable, high frequency arbitrarymore » waveform.« less

Frequency-domain gravitational waveform models for inspiraling binary neutron stars

NASA Astrophysics Data System (ADS)

Kawaguchi, Kyohei; Kiuchi, Kenta; Kyutoku, Koutarou; Sekiguchi, Yuichiro; Shibata, Masaru; Taniguchi, Keisuke

2018-02-01

We develop a model for frequency-domain gravitational waveforms from inspiraling binary neutron stars. Our waveform model is calibrated by comparison with hybrid waveforms constructed from our latest high-precision numerical-relativity waveforms and the SEOBNRv2T waveforms in the frequency range of 10-1000 Hz. We show that the phase difference between our waveform model and the hybrid waveforms is always smaller than 0.1 rad for the binary tidal deformability Λ ˜ in the range 300 ≲Λ ˜ ≲1900 and for a mass ratio between 0.73 and 1. We show that, for 10-1000 Hz, the distinguishability for the signal-to-noise ratio ≲50 and the mismatch between our waveform model and the hybrid waveforms are always smaller than 0.25 and 1.1 ×10-5 , respectively. The systematic error of our waveform model in the measurement of Λ ˜ is always smaller than 20 with respect to the hybrid waveforms for 300 ≲Λ ˜≲1900 . The statistical error in the measurement of binary parameters is computed employing our waveform model, and we obtain results consistent with the previous studies. We show that the systematic error of our waveform model is always smaller than 20% (typically smaller than 10%) of the statistical error for events with a signal-to-noise ratio of 50.

Electrochemical sensing using comparison of voltage-current time differential values during waveform generation and detection

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

Woo, Leta Yar-Li; Glass, Robert Scott; Fitzpatrick, Joseph Jay

2018-01-02

A device for signal processing. The device includes a signal generator, a signal detector, and a processor. The signal generator generates an original waveform. The signal detector detects an affected waveform. The processor is coupled to the signal detector. The processor receives the affected waveform from the signal detector. The processor also compares at least one portion of the affected waveform with the original waveform. The processor also determines a difference between the affected waveform and the original waveform. The processor also determines a value corresponding to a unique portion of the determined difference between the original and affected waveforms.more » The processor also outputs the determined value.« less

Automatic microseismic event picking via unsupervised machine learning

NASA Astrophysics Data System (ADS)

Chen, Yangkang

2018-01-01

Effective and efficient arrival picking plays an important role in microseismic and earthquake data processing and imaging. Widely used short-term-average long-term-average ratio (STA/LTA) based arrival picking algorithms suffer from the sensitivity to moderate-to-strong random ambient noise. To make the state-of-the-art arrival picking approaches effective, microseismic data need to be first pre-processed, for example, removing sufficient amount of noise, and second analysed by arrival pickers. To conquer the noise issue in arrival picking for weak microseismic or earthquake event, I leverage the machine learning techniques to help recognizing seismic waveforms in microseismic or earthquake data. Because of the dependency of supervised machine learning algorithm on large volume of well-designed training data, I utilize an unsupervised machine learning algorithm to help cluster the time samples into two groups, that is, waveform points and non-waveform points. The fuzzy clustering algorithm has been demonstrated to be effective for such purpose. A group of synthetic, real microseismic and earthquake data sets with different levels of complexity show that the proposed method is much more robust than the state-of-the-art STA/LTA method in picking microseismic events, even in the case of moderately strong background noise.

Reconfigurable, Intelligently-Adaptive, Communication System, an SDR Platform

NASA Technical Reports Server (NTRS)

Roche, Rigoberto J.; Shalkhauser, Mary Jo; Hickey, Joseph P.; Briones, Janette C.

2016-01-01

The Space Telecommunications Radio System (STRS) provides a common, consistent framework to abstract the application software from the radio platform hardware. STRS aims to reduce the cost and risk of using complex, configurable and reprogrammable radio systems across NASA missions. The NASA Glenn Research Center (GRC) team made a software defined radio (SDR) platform STRS compliant by adding an STRS operating environment and a field programmable gate array (FPGA) wrapper, capable of implementing each of the platforms interfaces, as well as a test waveform to exercise those interfaces. This effort serves to provide a framework toward waveform development onto an STRS compliant platform to support future space communication systems for advanced exploration missions. The use of validated STRS compliant applications provides tested code with extensive documentation to potentially reduce risk, cost and e ort in development of space-deployable SDRs. This paper discusses the advantages of STRS, the integration of STRS onto a Reconfigurable, Intelligently-Adaptive, Communication System (RIACS) SDR platform, and the test waveform and wrapper development e orts. The paper emphasizes the infusion of the STRS Architecture onto the RIACS platform for potential use in next generation flight system SDRs for advanced exploration missions.

High-Frequency Normal Mode Propagation in Aluminum Cylinders

USGS Publications Warehouse

Lee, Myung W.; Waite, William F.

2009-01-01

Acoustic measurements made using compressional-wave (P-wave) and shear-wave (S-wave) transducers in aluminum cylinders reveal waveform features with high amplitudes and with velocities that depend on the feature's dominant frequency. In a given waveform, high-frequency features generally arrive earlier than low-frequency features, typical for normal mode propagation. To analyze these waveforms, the elastic equation is solved in a cylindrical coordinate system for the high-frequency case in which the acoustic wavelength is small compared to the cylinder geometry, and the surrounding medium is air. Dispersive P- and S-wave normal mode propagations are predicted to exist, but owing to complex interference patterns inside a cylinder, the phase and group velocities are not smooth functions of frequency. To assess the normal mode group velocities and relative amplitudes, approximate dispersion relations are derived using Bessel functions. The utility of the normal mode theory and approximations from a theoretical and experimental standpoint are demonstrated by showing how the sequence of P- and S-wave normal mode arrivals can vary between samples of different size, and how fundamental normal modes can be mistaken for the faster, but significantly smaller amplitude, P- and S-body waves from which P- and S-wave speeds are calculated.

Modulation of distributed feedback (DFB) laser diode with the autonomous Chua's circuit: Theory and experiment

NASA Astrophysics Data System (ADS)

Talla Mbé, Jimmi Hervé; Woafo, Paul

2018-03-01

We report on a simple way to generate complex optical waveforms with very cheap and accessible equipments. The general idea consists in modulating a laser diode with an autonomous electronic oscillator, and in the case of this study, we use a distributed feedback (DFB) laser diode pumped with an electronic Chua's circuit. Based on the adiabatic P-I characteristics of the laser diode at low frequencies, we show that when the total pump is greater than the laser threshold, it is possible to convert the electrical waveforms of the Chua's circuit into optical carriers. But, if that is not the case, the on-off dynamical behavior of the laser permits to obtain many other optical waveform signals, mainly pulses. Our numerical results are consistent with experimental measurements. The work presents the advantage of extending the range of possible chaotic dynamics of the laser diodes in the time domains (millisecond) where it is not usually expected with conventional modulation techniques. Moreover, this new technique of laser diodes modulation brings a general benefit in the physical equipment, reduces their cost and congestion so that, it can constitute a step towards photonic integrated circuits.

Velocity and Attenuation Structure of the Earth's Inner Core Boundary From Semi-Automatic Waveform Modeling

NASA Astrophysics Data System (ADS)

Jin, J.; Song, X.; Sun, D.; Helmberger, D. V.

2013-12-01

The structure of the Earth's inner core boundary (ICB) is complex. Hemispherical differences and local variations of velocity and attenuation structures, as well as the ICB topography have been reported in previous studies. We are using an automatic waveform modeling method to improve the resolution of the ICB structures. The full waveforms of triplicated PKP phases at distance ranges from 120 to 165 degrees are used to model the lowermost 200 km of the outer core and the uppermost 600km of the inner core. Given a 1D velocity and attenuation model, synthetic seismograms are generated by Generalized Ray Theory. We are also experimenting 2D synthetic methods (WKM, AXISEM, and 2D FD) for 2D models (in the mantle and the inner core). The source time function is determined by observed seismic data. We use neighborhood algorithm to search for a group of models that minimize the misfit between predictions and observations. Tests on synthetic data show the efficiency of this method in resolving detailed velocity and attenuation structures of the ICB simultaneously. We are analyzing seismic record sections at dense arrays along different paths and will report our modeling and inversion results in the meeting.

Application of Wave Distribution Function Method to the ERG/PWE Data

NASA Astrophysics Data System (ADS)

Ota, M.; Kasahara, Y.; Matsuda, S.; Kojima, H.; Matsuoka, A.; Hikishima, M.; Kasaba, Y.; Ozaki, M.; Yagitani, S.; Tsuchiya, F.; Kumamoto, A.

2017-12-01

The ERG (Arase) satellite was launched on 20 December 2016 to study acceleration and loss mechanisms of relativistic electrons in the Earth's magnetosphere. The Plasma Wave Experiment (PWE), which is one of the science instruments on board the ERG satellite, measures electric field and magnetic field. The PWE consists of three sub-systems; EFD (Electric Field Detector), OFA/WFC (Onboard Frequency Analyzer and Waveform Capture), and HFA (High Frequency Analyzer).The OFA/WFC measures electromagnetic field spectra and raw waveforms in the frequency range from few Hz to 20 kHz. The OFA produces three kind of data; OFA-SPEC (power spectrum), OFA-MATRIX (spectral matrix), and OFA-COMPLEX (complex spectrum). The OFA-MATRIX measures ensemble averaged complex cross-spectra of two electric field components, and of three magnetic field components. The OFA-COMPLEX measures instantaneous complex spectra of electric and magnetic fields. These data are produced every 8 seconds in the nominal mode, and it can be used for polarization analysis and wave propagation direction finding.In general, spectral matrix composed by cross-spectra of observed signals is used for direction finding, and many algorithms have been proposed. For example, Means method and SVD method can be applied on the assumption that the spectral matrix is consists of a single plane wave, while wave distribution function (WDF) method is applicable even to the data in which multiple numbers of plane waves are simultaneously included. In this presentation, we introduce the results when the WDF method is applied to the ERG/PWE data.

TRENCADIS--a WSRF grid MiddleWare for managing DICOM structured reporting objects.

PubMed

Blanquer, Ignacio; Hernandez, Vicente; Segrelles, Damià

2006-01-01

The adoption of the digital processing of medical data, especially on radiology, has leaded to the availability of millions of records (images and reports). However, this information is mainly used at patient level, being the extraction of information, organised according to administrative criteria, which make the extraction of knowledge difficult. Moreover, legal constraints make the direct integration of information systems complex or even impossible. On the other side, the widespread of the DICOM format has leaded to the inclusion of other information different from just radiological images. The possibility of coding radiology reports in a structured form, adding semantic information about the data contained in the DICOM objects, eases the process of structuring images according to content. DICOM Structured Reporting (DICOM-SR) is a specification of tags and sections to code and integrate radiology reports, with seamless references to findings and regions of interests of the associated images, movies, waveforms, signals, etc. The work presented in this paper aims at developing of a framework to efficiently and securely share medical images and radiology reports, as well as to provide high throughput processing services. This system is based on a previously developed architecture in the framework of the TRENCADIS project, and uses other components such as the security system and the Grid processing service developed in previous activities. The work presented here introduces a semantic structuring and an ontology framework, to organise medical images considering standard terminology and disease coding formats (SNOMED, ICD9, LOINC..).

Nonlocal sparse model with adaptive structural clustering for feature extraction of aero-engine bearings

NASA Astrophysics Data System (ADS)

Zhang, Han; Chen, Xuefeng; Du, Zhaohui; Li, Xiang; Yan, Ruqiang

2016-04-01

Fault information of aero-engine bearings presents two particular phenomena, i.e., waveform distortion and impulsive feature frequency band dispersion, which leads to a challenging problem for current techniques of bearing fault diagnosis. Moreover, although many progresses of sparse representation theory have been made in feature extraction of fault information, the theory also confronts inevitable performance degradation due to the fact that relatively weak fault information has not sufficiently prominent and sparse representations. Therefore, a novel nonlocal sparse model (coined NLSM) and its algorithm framework has been proposed in this paper, which goes beyond simple sparsity by introducing more intrinsic structures of feature information. This work adequately exploits the underlying prior information that feature information exhibits nonlocal self-similarity through clustering similar signal fragments and stacking them together into groups. Within this framework, the prior information is transformed into a regularization term and a sparse optimization problem, which could be solved through block coordinate descent method (BCD), is formulated. Additionally, the adaptive structural clustering sparse dictionary learning technique, which utilizes k-Nearest-Neighbor (kNN) clustering and principal component analysis (PCA) learning, is adopted to further enable sufficient sparsity of feature information. Moreover, the selection rule of regularization parameter and computational complexity are described in detail. The performance of the proposed framework is evaluated through numerical experiment and its superiority with respect to the state-of-the-art method in the field is demonstrated through the vibration signals of experimental rig of aircraft engine bearings.

ECG fiducial point extraction using switching Kalman filter.

PubMed

Akhbari, Mahsa; Ghahjaverestan, Nasim Montazeri; Shamsollahi, Mohammad B; Jutten, Christian

2018-04-01

In this paper, we propose a novel method for extracting fiducial points (FPs) of the beats in electrocardiogram (ECG) signals using switching Kalman filter (SKF). In this method, according to McSharry's model, ECG waveforms (P-wave, QRS complex and T-wave) are modeled with Gaussian functions and ECG baselines are modeled with first order auto regressive models. In the proposed method, a discrete state variable called "switch" is considered that affects only the observation equations. We denote a mode as a specific observation equation and switch changes between 7 modes and corresponds to different segments of an ECG beat. At each time instant, the probability of each mode is calculated and compared among two consecutive modes and a path is estimated, which shows the relation of each part of the ECG signal to the mode with the maximum probability. ECG FPs are found from the estimated path. For performance evaluation, the Physionet QT database is used and the proposed method is compared with methods based on wavelet transform, partially collapsed Gibbs sampler (PCGS) and extended Kalman filter. For our proposed method, the mean error and the root mean square error across all FPs are 2 ms (i.e. less than one sample) and 14 ms, respectively. These errors are significantly smaller than those obtained using other methods. The proposed method achieves lesser RMSE and smaller variability with respect to others. Copyright © 2018 Elsevier B.V. All rights reserved.

Spherical Harmonic Decomposition of Gravitational Waves Across Mesh Refinement Boundaries

NASA Technical Reports Server (NTRS)

Fiske, David R.; Baker, John; vanMeter, James R.; Centrella, Joan M.

2005-01-01

We evolve a linearized (Teukolsky) solution of the Einstein equations with a non-linear Einstein solver. Using this testbed, we are able to show that such gravitational waves, defined by the Weyl scalars in the Newman-Penrose formalism, propagate faithfully across mesh refinement boundaries, and use, for the first time to our knowledge, a novel algorithm due to Misner to compute spherical harmonic components of our waveforms. We show that the algorithm performs extremely well, even when the extraction sphere intersects refinement boundaries.

An Approach to Co-Channel Talker Interference Suppression Using a Sinusoidal Model for Speech

DTIC Science & Technology

1988-02-05

Massachusetts Institute of Technologp, with the ’Apport of the Department of the Air Force under Contract F19628-85-C-0002. ŕir re-port tniay be...Extracted from Summed Vocalic Waveforms 28 5-1 Failure of the Least Squares Solution with Closely-Spaced Frequencies. (a) Crossing Frequency Tracks, (b... Crossing Pitch Contours. 31 5-2 Multi-Frame Interpolation 33 5-3 Different Forms of Multi-Frame Interpolation 33 5-4 Recovery of Missing Lobe with Multi

Fetal electrocardiogram (ECG) for fetal monitoring during labour.

PubMed

Neilson, James P

2015-12-21

Hypoxaemia during labour can alter the shape of the fetal electrocardiogram (ECG) waveform, notably the relation of the PR to RR intervals, and elevation or depression of the ST segment. Technical systems have therefore been developed to monitor the fetal ECG during labour as an adjunct to continuous electronic fetal heart rate monitoring with the aim of improving fetal outcome and minimising unnecessary obstetric interference. To compare the effects of analysis of fetal ECG waveforms during labour with alternative methods of fetal monitoring. The Cochrane Pregnancy and Childbirth Group's Trials Register (latest search 23 September 2015) and reference lists of retrieved studies. Randomised trials comparing fetal ECG waveform analysis with alternative methods of fetal monitoring during labour. One review author independently assessed trials for inclusion and risk of bias, extracted data and checked them for accuracy. One review author assessed the quality of the evidence using the GRADE approach. Seven trials (27,403 women) were included: six trials of ST waveform analysis (26,446 women) and one trial of PR interval analysis (957 women). The trials were generally at low risk of bias for most domains and the quality of evidence for ST waveform analysis trials was graded moderate to high. In comparison to continuous electronic fetal heart rate monitoring alone, the use of adjunctive ST waveform analysis made no obvious difference to primary outcomes: births by caesarean section (risk ratio (RR) 1.02, 95% confidence interval (CI) 0.96 to 1.08; six trials, 26,446 women; high quality evidence); the number of babies with severe metabolic acidosis at birth (cord arterial pH less than 7.05 and base deficit greater than 12 mmol/L) (average RR 0.72, 95% CI 0.43 to 1.20; six trials, 25,682 babies; moderate quality evidence); or babies with neonatal encephalopathy (RR 0.61, 95% CI 0.30 to 1.22; six trials, 26,410 babies; high quality evidence). There were, however, on average fewer fetal scalp samples taken during labour (average RR 0.61, 95% CI 0.41 to 0.91; four trials, 9671 babies; high quality evidence) although the findings were heterogeneous and there were no data from the largest trial (from the USA). There were marginally fewer operative vaginal births (RR 0.92, 95% CI 0.86 to 0.99; six trials, 26,446 women); but no obvious difference in the number of babies with low Apgar scores at five minutes or babies requiring neonatal intubation, or babies requiring admission to the special care unit (RR 0.96, 95% CI 0.89 to 1.04, six trials, 26,410 babies; high quality evidence). There was little evidence that monitoring by PR interval analysis conveyed any benefit of any sort. The modest benefits of fewer fetal scalp samplings during labour (in settings in which this procedure is performed) and fewer instrumental vaginal births have to be considered against the disadvantages of needing to use an internal scalp electrode, after membrane rupture, for ECG waveform recordings. We found little strong evidence that ST waveform analysis had an effect on the primary outcome measures in this systematic review.There was a lack of evidence showing that PR interval analysis improved any outcomes; and a larger future trial may possibly demonstrate beneficial effects.There is little information about the value of fetal ECG waveform monitoring in preterm fetuses in labour. Information about long-term development of the babies included in the trials would be valuable.

Probabilistic terrain models from waveform airborne LiDAR: AutoProbaDTM project results

NASA Astrophysics Data System (ADS)

Jalobeanu, A.; Goncalves, G. R.

2012-12-01

The main objective of the AutoProbaDTM project was to develop new methods for automated probabilistic topographic map production using the latest LiDAR scanners. It included algorithmic development, implementation and validation over a 200 km2 test area in continental Portugal, representing roughly 100 GB of raw data and half a billion waveforms. We aimed to generate digital terrain models automatically, including ground topography as well as uncertainty maps, using Bayesian inference for model estimation and error propagation, and approaches based on image processing. Here we are presenting the results of the completed project (methodological developments and processing results from the test dataset). In June 2011, the test data were acquired in central Portugal, over an area of geomorphological and ecological interest, using a Riegl LMS-Q680i sensor. We managed to survey 70% of the test area at a satisfactory sampling rate, the angular spacing matching the laser beam divergence and the ground spacing nearly equal to the footprint (almost 4 pts/m2 for a 50cm footprint at 1500 m AGL). This is crucial for a correct processing as aliasing artifacts are significantly reduced. A reverse engineering had to be done as the data were delivered in a proprietary binary format, so we were able to read the waveforms and the essential parameters. A robust waveform processing method has been implemented and tested, georeferencing and geometric computations have been coded. Fast gridding and interpolation techniques have been developed. Validation is nearly completed, as well as geometric calibration, IMU error correction, full error propagation and large-scale DEM reconstruction. A probabilistic processing software package has been implemented and code optimization is in progress. This package includes new boresight calibration procedures, robust peak extraction modules, DEM gridding and interpolation methods, and means to visualize the produced uncertain surfaces (topography and accuracy map). Vegetation filtering for bare ground extraction has been left aside, and we wish to explore this research area in the future. A thorough validation of the new techniques and computed models has been conducted, using large numbers of ground control points (GCP) acquired with GPS, evenly distributed and classified according to ground cover and terrain characteristics. More than 16,000 GCP have been acquired during field work. The results are now freely accessible online through a web map service (GeoServer) thus allowing users to visualize data interactively without having to download the full processed dataset.

System and Method for Generating a Frequency Modulated Linear Laser Waveform

NASA Technical Reports Server (NTRS)

Pierrottet, Diego F. (Inventor); Petway, Larry B. (Inventor); Amzajerdian, Farzin (Inventor); Barnes, Bruce W. (Inventor); Lockard, George E. (Inventor); Hines, Glenn D. (Inventor)

2017-01-01

A system for generating a frequency modulated linear laser waveform includes a single frequency laser generator to produce a laser output signal. An electro-optical modulator modulates the frequency of the laser output signal to define a linear triangular waveform. An optical circulator passes the linear triangular waveform to a band-pass optical filter to filter out harmonic frequencies created in the waveform during modulation of the laser output signal, to define a pure filtered modulated waveform having a very narrow bandwidth. The optical circulator receives the pure filtered modulated laser waveform and transmits the modulated laser waveform to a target.

System and Method for Generating a Frequency Modulated Linear Laser Waveform

NASA Technical Reports Server (NTRS)

Pierrottet, Diego F. (Inventor); Petway, Larry B. (Inventor); Amzajerdian, Farzin (Inventor); Barnes, Bruce W. (Inventor); Lockard, George E. (Inventor); Hines, Glenn D. (Inventor)

2014-01-01

A system for generating a frequency modulated linear laser waveform includes a single frequency laser generator to produce a laser output signal. An electro-optical modulator modulates the frequency of the laser output signal to define a linear triangular waveform. An optical circulator passes the linear triangular waveform to a band-pass optical filter to filter out harmonic frequencies created in the waveform during modulation of the laser output signal, to define a pure filtered modulated waveform having a very narrow bandwidth. The optical circulator receives the pure filtered modulated laser waveform and transmits the modulated laser waveform to a target.

JTRS/SCA and Custom/SDR Waveform Comparison

NASA Technical Reports Server (NTRS)

Oldham, Daniel R.; Scardelletti, Maximilian C.

2007-01-01

This paper compares two waveform implementations generating the same RF signal using the same SDR development system. Both waveforms implement a satellite modem using QPSK modulation at 1M BPS data rates with one half rate convolutional encoding. Both waveforms are partitioned the same across the general purpose processor (GPP) and the field programmable gate array (FPGA). Both waveforms implement the same equivalent set of radio functions on the GPP and FPGA. The GPP implements the majority of the radio functions and the FPGA implements the final digital RF modulator stage. One waveform is implemented directly on the SDR development system and the second waveform is implemented using the JTRS/SCA model. This paper contrasts the amount of resources to implement both waveforms and demonstrates the importance of waveform partitioning across the SDR development system.

Command-line cellular electrophysiology for conventional and real-time closed-loop experiments.

PubMed

Linaro, Daniele; Couto, João; Giugliano, Michele

2014-06-15

Current software tools for electrophysiological experiments are limited in flexibility and rarely offer adequate support for advanced techniques such as dynamic clamp and hybrid experiments, which are therefore limited to laboratories with a significant expertise in neuroinformatics. We have developed lcg, a software suite based on a command-line interface (CLI) that allows performing both standard and advanced electrophysiological experiments. Stimulation protocols for classical voltage and current clamp experiments are defined by a concise and flexible meta description that allows representing complex waveforms as a piece-wise parametric decomposition of elementary sub-waveforms, abstracting the stimulation hardware. To perform complex experiments lcg provides a set of elementary building blocks that can be interconnected to yield a large variety of experimental paradigms. We present various cellular electrophysiological experiments in which lcg has been employed, ranging from the automated application of current clamp protocols for characterizing basic electrophysiological properties of neurons, to dynamic clamp, response clamp, and hybrid experiments. We finally show how the scripting capabilities behind a CLI are suited for integrating experimental trials into complex workflows, where actual experiment, online data analysis and computational modeling seamlessly integrate. We compare lcg with two open source toolboxes, RTXI and RELACS. We believe that lcg will greatly contribute to the standardization and reproducibility of both simple and complex experiments. Additionally, on the long run the increased efficiency due to a CLI will prove a great benefit for the experimental community. Copyright © 2014 Elsevier B.V. All rights reserved.

ASDF - A Modern Data Format for Seismology

NASA Astrophysics Data System (ADS)

Krischer, Lion; Smith, James; Lei, Wenjie; Lefebvre, Matthieu; Ruan, Youyi; Sales de Andrade, Elliot; Podhorszki, Norbert; Bozdag, Ebru; Tromp, Jeroen

2017-04-01

Seismology as a science is driven by observing and understanding data and it is thus vital to make this as easy and accessible as possible. The growing volume of freely available data coupled with ever expanding computational power enables scientists to take on new and bigger problems. This evolution is to some part hindered as existing data formats have not been designed with it in mind. We present ASDF (http://seismic-data.org), the Adaptable Seismic Data Format, a novel, modern, and especially practical data format for all branches of seismology with particular focus on how it is incorporated into seismic full waveform inversion workflows. The format aims to solve five key issues: Efficiency: Fast I/O operations especially in high performance computing environments, especially limiting the total number of files. Data organization: Different types of data are needed for a variety of tasks. This results in ad hoc data organization and formats that are hard to maintain, integrate, reproduce, and exchange. Data exchange: We want to exchange complex and complete data sets. Reproducibility: Oftentimes just not existing but crucial to advance our science. Mining, visualization, and understanding of data: As data volumes grow, more complex, new techniques to query and visualize large datasets are needed. ASDF tackles these by defining a structure on top of HDF5 reusing as many existing standards (QuakeML, StationXML, PROV) as possible. An essential trait of ASDF is that it empowers the construction of completely self-describing data sets including waveform, station, and event data together with non-waveform data and a provenance description of everything. This for example for the first time enables the proper archival and exchange of processed or synthetic waveforms. To aid community adoption we developed mature tools in Python as well as in C and Fortran. Additionally we provide a formal definition of the format, a validation tool, and integration into widely used tools like ObsPy (http://obspy.org), SPECFEM GLOBE (https://geodynamics.org/cig/software/specfem3d_globe/), and Salvus (http://salvus.io).

Vocoders and Speech Perception: Uses of Computer-Based Speech Analysis-Synthesis in Stimulus Generation.

ERIC Educational Resources Information Center

Tierney, Joseph; Mack, Molly

1987-01-01

Stimuli used in research on the perception of the speech signal have often been obtained from simple filtering and distortion of the speech waveform, sometimes accompanied by noise. However, for more complex stimulus generation, the parameters of speech can be manipulated, after analysis and before synthesis, using various types of algorithms to…

ERP Evidence of Early Cross-Modal Links between Auditory Selective Attention and Visuo-Spatial Memory

ERIC Educational Resources Information Center

Bomba, Marie D.; Singhal, Anthony

2010-01-01

Previous dual-task research pairing complex visual tasks involving non-spatial cognitive processes during dichotic listening have shown effects on the late component (Ndl) of the negative difference selective attention waveform but no effects on the early (Nde) response suggesting that the Ndl, but not the Nde, is affected by non-spatial…

Combining high fidelity simulations and real data for improved small-footprint waveform lidar assessment of vegetation structure (Invited)

NASA Astrophysics Data System (ADS)

van Aardt, J. A.; Wu, J.; Asner, G. P.

2010-12-01

Our understanding of vegetation complexity and biodiversity, from a remote sensing perspective, has evolved from 2D species diversity to also include 3D vegetation structural diversity. Attempts at using image-based approaches for structural assessment have met with reasonable success, but 3D remote sensing technologies, such as radar and light detection and ranging (lidar), are arguably more adept at sensing vegetation structure. While radar-derived structure metrics tend to break down at high biomass levels, novel waveform lidar systems present us with new opportunities for detailed and scalable structural characterization of vegetation. These sensors digitize the entire backscattered energy profile at high spatial and vertical resolutions and often at off-nadir angles. Research teams at Rochester Institute of Technology (RIT) and Carnegie Institution for Science have been using airborne data from the Carnegie Airborne Observatory (CAO) to assess vegetation structure and variation in savanna ecosystems in and around the Kruger National Park, South Africa. It quickly became evident that (i) pre-processing of small-footprint waveform data is a critical step prior to testing scientific hypotheses, (ii) a number of assumptions of how vegetation structure is expressed in these 3D signals need to be evaluated, and very importantly (iii) we need to re-evaluate our linkages between coarse in-field measurements, e.g., volume, biomass, leaf area index (LAI), and metrics derived from waveform lidar. Research has progressed to the stage where we have evaluated various pre-processing steps, e.g., convolution via the Wiener filter, Richardson-Lucy, and non-negative least squares algorithms, and the coupling of waveform voxels to tree structure in a simulation environment. This was done in the MODTRAN-based Digital Imaging and Remote Sensing Image Generation (DIRSIG) simulation environment, developed at RIT. We generated "truth" cross-section datasets of detailed virtual trees in this environment and evaluated inversion approaches to tree structure estimation. Various outgoing pulse widths, tree structures, and a noise component were included as part of the simulation effort. Results, for example, have shown that the Richardson-Lucy algorithm outperforms other approaches in terms of retrieval of known structural information, that our assumption regarding the position of the ground surface needs re-evaluation, and has shed light on herbaceous biomass and waveform interactions and the impact of outgoing pulse width on assessments. These efforts have gone a long way in providing a solid foundation for analysis and interpretation of actual waveform data from the savanna study area. We expect that newfound knowledge with respect to waveform-target interactions from these simulations will also aid efforts to reconstruct 3D trees from real data and better describe associated structural diversity. Results will be presented at the conference.

Ascending-ramp biphasic waveform has a lower defibrillation threshold and releases less troponin I than a truncated exponential biphasic waveform.

PubMed

Huang, Jian; Walcott, Gregory P; Ruse, Richard B; Bohanan, Scott J; Killingsworth, Cheryl R; Ideker, Raymond E

2012-09-11

We tested the hypothesis that the shape of the shock waveform affects not only the defibrillation threshold but also the amount of cardiac damage. Defibrillation thresholds were determined for 11 waveforms-3 ascending-ramp waveforms, 3 descending-ramp waveforms, 3 rectilinear first-phase biphasic waveforms, a Gurvich waveform, and a truncated exponential biphasic waveform-in 6 pigs with electrodes in the right ventricular apex and superior vena cava. The ascending, descending, and rectilinear waveforms had 4-, 8-, and 16-millisecond first phases and a 3.5-millisecond rectilinear second phase that was half the voltage of the first phase. The exponential biphasic waveform had a 60% first-phase and a 50% second-phase tilt. In a second study, we attempted to defibrillate after 10 seconds of ventricular fibrillation with a single ≈30-J shock (6 pigs successfully defibrillated with 8-millisecond ascending, 8-millisecond rectilinear, and truncated exponential biphasic waveforms). Troponin I blood levels were determined before and 2 to 10 hours after the shock. The lowest-energy defibrillation threshold was for the 8-milliseconds ascending ramp (14.6±7.3 J [mean±SD]), which was significantly less than for the truncated exponential (19.6±6.3 J). Six hours after shock, troponin I was significantly less for the ascending-ramp waveform (0.80±0.54 ng/mL) than for the truncated exponential (1.92±0.47 ng/mL) or the rectilinear waveform (1.17±0.45 ng/mL). The ascending ramp has a significantly lower defibrillation threshold and at ≈30 J causes 58% less troponin I release than the truncated exponential biphasic shock. Therefore, the shock waveform affects both the defibrillation threshold and the amount of cardiac damage.

Electrochemical sensing using voltage-current time differential

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

Woo, Leta Yar-Li; Glass, Robert Scott; Fitzpatrick, Joseph Jay

2017-02-28

A device for signal processing. The device includes a signal generator, a signal detector, and a processor. The signal generator generates an original waveform. The signal detector detects an affected waveform. The processor is coupled to the signal detector. The processor receives the affected waveform from the signal detector. The processor also compares at least one portion of the affected waveform with the original waveform. The processor also determines a difference between the affected waveform and the original waveform. The processor also determines a value corresponding to a unique portion of the determined difference between the original and affected waveforms.more » The processor also outputs the determined value.« less

Adaptive waveform optimization design for target detection in cognitive radar

NASA Astrophysics Data System (ADS)

Zhang, Xiaowen; Wang, Kaizhi; Liu, Xingzhao

2017-01-01

The problem of adaptive waveform design for target detection in cognitive radar (CR) is investigated. This problem is analyzed in signal-dependent interference, as well as additive channel noise for extended target with unknown target impulse response (TIR). In order to estimate the TIR accurately, the Kalman filter is used in target tracking. In each Kalman filtering iteration, a flexible online waveform spectrum optimization design taking both detection and range resolution into account is modeled in Fourier domain. Unlike existing CR waveform, the proposed waveform can be simultaneously updated according to the environment information fed back by receiver and radar performance demands. Moreover, the influence of waveform spectral phase to radar performance is analyzed. Simulation results demonstrate that CR with the proposed waveform performs better than a traditional radar system with a fixed waveform and offers more flexibility and suitability. In addition, waveform spectral phase will not influence tracking, detection, and range resolution performance but will greatly influence waveform forming speed and peak-to-average power ratio.

High-resolution Imaging of the Philippine Sea Plate subducting beneath Central Japan

NASA Astrophysics Data System (ADS)

Padhy, S.; Furumura, T.

2016-12-01

Thermal models predict that the oceanic crust of the young (<20 Ma) and warmer Philippine-sea plate (PHP) is more prone to melting. Deriving a high-resolution image of the PHP, including slab melting and other features of the subduction zone, is a key to understand the basics of earthquake occurrence and origin of magma in complex subduction zone like central Japan, where both the PHP and Pacific (PAC) Plates subduct. To this purpose, we analyzed high-resolution waveforms of moderate sized (M 4-6), intermediate-to-deep (>150 km) PAC earthquakes occurring in central Japan and conducted numerical simulation to derive a fine-scale PHP model, which is not constrained in earlier studies. Observations show spindle-shaped seismograms with strong converted phases and extended coda with very slow decay from a group of PAC events occurring in northern part of central Japan and recorded by high-sensitivity seismograph network (Hi-net) stations in the region. We investigate the mechanism of propagation of these anomalous waveforms using the finite difference method (FDM) simulation of wave propagation through the subduction zone. We examine the effects on waveform changes of major subduction zone features, such as the melting of oceanic crust in PHP, serpentinized mantle wedge, hydrated layer on the PAC due to slab dehydration, and anomaly in upper mantle between the PAC and PHP. Simulation results show that the waveform anomaly is primarily explained by strong scattering and absorption of high-frequency energy by the low-velocity anomalous mantle structure, with a strong coda excitation yielding spindle-shaped waveforms. The data are secondarily explained by melting of PHP in the basaltic crust. The location of the mantle anomaly is tightly constrained by the observation and evidence of PAC thinning in the region; these localized low-velocity structures aid in ascending the slab-derived fluids around the slab thinning. We expect that the results of this study will enhance our present understanding on the mechanism of intermediate to deep earthquakes in the region.

Full waveform time domain solutions for source and induced magnetotelluric and controlled-source electromagnetic fields using quasi-equivalent time domain decomposition and GPU parallelization

NASA Astrophysics Data System (ADS)

Imamura, N.; Schultz, A.

2015-12-01

Recently, a full waveform time domain solution has been developed for the magnetotelluric (MT) and controlled-source electromagnetic (CSEM) methods. The ultimate goal of this approach is to obtain a computationally tractable direct waveform joint inversion for source fields and earth conductivity structure in three and four dimensions. This is desirable on several grounds, including the improved spatial resolving power expected from use of a multitude of source illuminations of non-zero wavenumber, the ability to operate in areas of high levels of source signal spatial complexity and non-stationarity, etc. This goal would not be obtainable if one were to adopt the finite difference time-domain (FDTD) approach for the forward problem. This is particularly true for the case of MT surveys, since an enormous number of degrees of freedom are required to represent the observed MT waveforms across the large frequency bandwidth. It means that for FDTD simulation, the smallest time steps should be finer than that required to represent the highest frequency, while the number of time steps should also cover the lowest frequency. This leads to a linear system that is computationally burdensome to solve. We have implemented our code that addresses this situation through the use of a fictitious wave domain method and GPUs to speed up the computation time. We also substantially reduce the size of the linear systems by applying concepts from successive cascade decimation, through quasi-equivalent time domain decomposition. By combining these refinements, we have made good progress toward implementing the core of a full waveform joint source field/earth conductivity inverse modeling method. From results, we found the use of previous generation of CPU/GPU speeds computations by an order of magnitude over a parallel CPU only approach. In part, this arises from the use of the quasi-equivalent time domain decomposition, which shrinks the size of the linear system dramatically.

Efficient calculation of full waveform time domain inversion for electromagnetic problem using fictitious wave domain method and cascade decimation decomposition

NASA Astrophysics Data System (ADS)

Imamura, N.; Schultz, A.

2016-12-01

Recently, a full waveform time domain inverse solution has been developed for the magnetotelluric (MT) and controlled-source electromagnetic (CSEM) methods. The ultimate goal of this approach is to obtain a computationally tractable direct waveform joint inversion to solve simultaneously for source fields and earth conductivity structure in three and four dimensions. This is desirable on several grounds, including the improved spatial resolving power expected from use of a multitude of source illuminations, the ability to operate in areas of high levels of source signal spatial complexity, and non-stationarity. This goal would not be obtainable if one were to adopt the pure time domain solution for the inverse problem. This is particularly true for the case of MT surveys, since an enormous number of degrees of freedom are required to represent the observed MT waveforms across a large frequency bandwidth. This means that for the forward simulation, the smallest time steps should be finer than that required to represent the highest frequency, while the number of time steps should also cover the lowest frequency. This leads to a sensitivity matrix that is computationally burdensome to solve a model update. We have implemented a code that addresses this situation through the use of cascade decimation decomposition to reduce the size of the sensitivity matrix substantially, through quasi-equivalent time domain decomposition. We also use a fictitious wave domain method to speed up computation time of the forward simulation in the time domain. By combining these refinements, we have developed a full waveform joint source field/earth conductivity inverse modeling method. We found that cascade decimation speeds computations of the sensitivity matrices dramatically, keeping the solution close to that of the undecimated case. For example, for a model discretized into 2.6x105 cells, we obtain model updates in less than 1 hour on a 4U rack-mounted workgroup Linux server, which is a practical computational time for the inverse problem.

On estimating the phase of periodic waveform in additive Gaussian noise, part 2

NASA Astrophysics Data System (ADS)

Rauch, L. L.

1984-11-01

Motivated by advances in signal processing technology that support more complex algorithms, a new look is taken at the problem of estimating the phase and other parameters of a periodic waveform in additive Gaussian noise. The general problem was introduced and the maximum a posteriori probability criterion with signal space interpretation was used to obtain the structures of optimum and some suboptimum phase estimators for known constant frequency and unknown constant phase with an a priori distribution. Optimal algorithms are obtained for some cases where the frequency is a parameterized function of time with the unknown parameters and phase having a joint a priori distribution. In the last section, the intrinsic and extrinsic geometry of hypersurfaces is introduced to provide insight to the estimation problem for the small noise and large noise cases.

On Estimating the Phase of Periodic Waveform in Additive Gaussian Noise, Part 2

NASA Technical Reports Server (NTRS)

Rauch, L. L.

1984-01-01

Motivated by advances in signal processing technology that support more complex algorithms, a new look is taken at the problem of estimating the phase and other parameters of a periodic waveform in additive Gaussian noise. The general problem was introduced and the maximum a posteriori probability criterion with signal space interpretation was used to obtain the structures of optimum and some suboptimum phase estimators for known constant frequency and unknown constant phase with an a priori distribution. Optimal algorithms are obtained for some cases where the frequency is a parameterized function of time with the unknown parameters and phase having a joint a priori distribution. In the last section, the intrinsic and extrinsic geometry of hypersurfaces is introduced to provide insight to the estimation problem for the small noise and large noise cases.

High-field asymmetric waveform ion mobility spectrometry for mass spectrometry-based proteomics.

PubMed

Swearingen, Kristian E; Moritz, Robert L

2012-10-01

High-field asymmetric waveform ion mobility spectrometry (FAIMS) is an atmospheric pressure ion mobility technique that separates gas-phase ions by their behavior in strong and weak electric fields. FAIMS is easily interfaced with electrospray ionization and has been implemented as an additional separation mode between liquid chromatography (LC) and mass spectrometry (MS) in proteomic studies. FAIMS separation is orthogonal to both LC and MS and is used as a means of on-line fractionation to improve the detection of peptides in complex samples. FAIMS improves dynamic range and concomitantly the detection limits of ions by filtering out chemical noise. FAIMS can also be used to remove interfering ion species and to select peptide charge states optimal for identification by tandem MS. Here, the authors review recent developments in LC-FAIMS-MS and its application to MS-based proteomics.

Impulse propagation over a complex site: a comparison of experimental results and numerical predictions.

PubMed

Dragna, Didier; Blanc-Benon, Philippe; Poisson, Franck

2014-03-01

Results from outdoor acoustic measurements performed in a railway site near Reims in France in May 2010 are compared to those obtained from a finite-difference time-domain solver of the linearized Euler equations. During the experiments, the ground profile and the different ground surface impedances were determined. Meteorological measurements were also performed to deduce mean vertical profiles of wind and temperature. An alarm pistol was used as a source of impulse signals and three microphones were located along a propagation path. The various measured parameters are introduced as input data into the numerical solver. In the frequency domain, the numerical results are in good accordance with the measurements up to a frequency of 2 kHz. In the time domain, except a time shift, the predicted waveforms match the measured waveforms with a close agreement.

Optimisation of a Generic Ionic Model of Cardiac Myocyte Electrical Activity

PubMed Central

Guo, Tianruo; Al Abed, Amr; Lovell, Nigel H.; Dokos, Socrates

2013-01-01

A generic cardiomyocyte ionic model, whose complexity lies between a simple phenomenological formulation and a biophysically detailed ionic membrane current description, is presented. The model provides a user-defined number of ionic currents, employing two-gate Hodgkin-Huxley type kinetics. Its generic nature allows accurate reconstruction of action potential waveforms recorded experimentally from a range of cardiac myocytes. Using a multiobjective optimisation approach, the generic ionic model was optimised to accurately reproduce multiple action potential waveforms recorded from central and peripheral sinoatrial nodes and right atrial and left atrial myocytes from rabbit cardiac tissue preparations, under different electrical stimulus protocols and pharmacological conditions. When fitted simultaneously to multiple datasets, the time course of several physiologically realistic ionic currents could be reconstructed. Model behaviours tend to be well identified when extra experimental information is incorporated into the optimisation. PMID:23710254

Applying Numerical Relativity to Gravitational Wave Astronomy using LISA

NASA Astrophysics Data System (ADS)

McWilliams, Sean T.

2007-12-01

We present recently calculated waveforms from numerical relativity and their application to the search for and precision measurement of black hole binary coalescences using LISA. In particular, we focus on the advances made in moving beyond the equal mass, nonspinning case into other regions of parameter space, particularly the case of nonspinning holes with ever-increasing mass ratios as the state of the art has progressed. Also, we investigate the potential contribution from the merger portion of the waveform to measurement uncertainties of the binary's parameters. Until now, only the inspiral has been investigated due to the lack of availability of mergers and the increased complexity required in moving beyond the low frequency approximation of the interferometer, which is necessary when mergers are included. We discuss the subtleties of the problem, and present preliminary results.

Laser beam pulse formatting method

DOEpatents

Daly, Thomas P.; Moses, Edward I.; Patterson, Ralph W.; Sawicki, Richard H.

1994-01-01

A method for formatting a laser beam pulse (20) using one or more delay loops (10). The delay loops (10) have a partially reflective beam splitter (12) and a plurality of highly reflective mirrors (14) arranged such that the laser beam pulse (20) enters into the delay loop (10) through the beam splitter (12) and circulates therein along a delay loop length (24) defined by the mirrors (14). As the laser beam pulse (20) circulates within the delay loop (10) a portion thereof is emitted upon each completed circuit when the laser beam pulse (20) strikes the beam splitter (12). The laser beam pulse (20) is thereby formatted into a plurality of sub-pulses (50, 52, 54 and 56). The delay loops (10) are used in combination to produce complex waveforms by combining the sub-pulses (50, 52, 54 and 56) using additive waveform synthesis.

Time-dependent phase error correction using digital waveform synthesis

DOEpatents

Doerry, Armin W.; Buskirk, Stephen

2017-10-10

The various technologies presented herein relate to correcting a time-dependent phase error generated as part of the formation of a radar waveform. A waveform can be pre-distorted to facilitate correction of an error induced into the waveform by a downstream operation/component in a radar system. For example, amplifier power droop effect can engender a time-dependent phase error in a waveform as part of a radar signal generating operation. The error can be quantified and an according complimentary distortion can be applied to the waveform to facilitate negation of the error during the subsequent processing of the waveform. A time domain correction can be applied by a phase error correction look up table incorporated into a waveform phase generator.

Radar altimeter waveform modeled parameter recovery. [SEASAT-1 data

NASA Technical Reports Server (NTRS)

1981-01-01

Satellite-borne radar altimeters include waveform sampling gates providing point samples of the transmitted radar pulse after its scattering from the ocean's surface. Averages of the waveform sampler data can be fitted by varying parameters in a model mean return waveform. The theoretical waveform model used is described as well as a general iterative nonlinear least squares procedures used to obtain estimates of parameters characterizing the modeled waveform for SEASAT-1 data. The six waveform parameters recovered by the fitting procedure are: (1) amplitude; (2) time origin, or track point; (3) ocean surface rms roughness; (4) noise baseline; (5) ocean surface skewness; and (6) altitude or off-nadir angle. Additional practical processing considerations are addressed and FORTRAN source listing for subroutines used in the waveform fitting are included. While the description is for the Seasat-1 altimeter waveform data analysis, the work can easily be generalized and extended to other radar altimeter systems.

FWT2D: A massively parallel program for frequency-domain full-waveform tomography of wide-aperture seismic data—Part 1: Algorithm

NASA Astrophysics Data System (ADS)

Sourbier, Florent; Operto, Stéphane; Virieux, Jean; Amestoy, Patrick; L'Excellent, Jean-Yves

2009-03-01

This is the first paper in a two-part series that describes a massively parallel code that performs 2D frequency-domain full-waveform inversion of wide-aperture seismic data for imaging complex structures. Full-waveform inversion methods, namely quantitative seismic imaging methods based on the resolution of the full wave equation, are computationally expensive. Therefore, designing efficient algorithms which take advantage of parallel computing facilities is critical for the appraisal of these approaches when applied to representative case studies and for further improvements. Full-waveform modelling requires the resolution of a large sparse system of linear equations which is performed with the massively parallel direct solver MUMPS for efficient multiple-shot simulations. Efficiency of the multiple-shot solution phase (forward/backward substitutions) is improved by using the BLAS3 library. The inverse problem relies on a classic local optimization approach implemented with a gradient method. The direct solver returns the multiple-shot wavefield solutions distributed over the processors according to a domain decomposition driven by the distribution of the LU factors. The domain decomposition of the wavefield solutions is used to compute in parallel the gradient of the objective function and the diagonal Hessian, this latter providing a suitable scaling of the gradient. The algorithm allows one to test different strategies for multiscale frequency inversion ranging from successive mono-frequency inversion to simultaneous multifrequency inversion. These different inversion strategies will be illustrated in the following companion paper. The parallel efficiency and the scalability of the code will also be quantified.

New Frontiers in Characterization of Sub-Catalog Microseismicity: Utilizing Inter-Event Waveform Cross Correlation for Estimating Precise Locations, Magnitudes, and Focal Mechanisms of Tiny Earthquakes

NASA Astrophysics Data System (ADS)

Ellsworth, W. L.; Shelly, D. R.; Hardebeck, J.; Hill, D. P.

2017-12-01

Microseismicity often conveys the most direct information about active processes in the earth's subsurface. However, routine network processing typically leaves most earthquakes uncharacterized. These "sub-catalog" events can provide critical clues to ongoing processes in the source region. To address this issue, we have developed waveform-based processing that leverages the existing routine catalog of earthquakes to detect and characterize "sub-catalog" events (those absent in routine catalogs). By correlating waveforms of cataloged events with the continuous data stream, we 1) identify events with similar waveform signatures in the continuous data across multiple stations, 2) precisely measure relative time lags across these stations for both P- and S-wave time windows, and 3) estimate the relative polarity between events by the sign of the peak absolute value correlations and its height above the secondary peak. When combined, these inter-event comparisons yield robust measurements, which enable sensitive event detection, relative relocation, and relative magnitude estimation. The most recent addition, focal mechanisms derived from correlation-based relative polarities, addresses a significant shortcoming in microseismicity analyses (see Shelly et al., JGR, 2016). Depending on the application, we can characterize 2-10 times as many events as included in the initial catalog. This technique is particularly well suited for compact zones of active seismicity such as seismic swarms. Application to a 2014 swarm in Long Valley Caldera, California, illuminates complex patterns of faulting that would have otherwise remained obscured. The prevalence of such features in other environments remains an important, as yet unresolved, question.

Total variation regularization for seismic waveform inversion using an adaptive primal dual hybrid gradient method

NASA Astrophysics Data System (ADS)

Yong, Peng; Liao, Wenyuan; Huang, Jianping; Li, Zhenchuan

2018-04-01

Full waveform inversion is an effective tool for recovering the properties of the Earth from seismograms. However, it suffers from local minima caused mainly by the limited accuracy of the starting model and the lack of a low-frequency component in the seismic data. Because of the high velocity contrast between salt and sediment, the relation between the waveform and velocity perturbation is strongly nonlinear. Therefore, salt inversion can easily get trapped in the local minima. Since the velocity of salt is nearly constant, we can make the most of this characteristic with total variation regularization to mitigate the local minima. In this paper, we develop an adaptive primal dual hybrid gradient method to implement total variation regularization by projecting the solution onto a total variation norm constrained convex set, through which the total variation norm constraint is satisfied at every model iteration. The smooth background velocities are first inverted and the perturbations are gradually obtained by successively relaxing the total variation norm constraints. Numerical experiment of the projection of the BP model onto the intersection of the total variation norm and box constraints has demonstrated the accuracy and efficiency of our adaptive primal dual hybrid gradient method. A workflow is designed to recover complex salt structures in the BP 2004 model and the 2D SEG/EAGE salt model, starting from a linear gradient model without using low-frequency data below 3 Hz. The salt inversion processes demonstrate that wavefield reconstruction inversion with a total variation norm and box constraints is able to overcome local minima and inverts the complex salt velocity layer by layer.

Wave detection in acceleration plethysmogram.

PubMed

Ahn, Jae Mok

2015-04-01

Acceleration plethysmogram (APG) obtained from the second derivative of photoplethysmography (PPG) is used to predict risk factors for atherosclerosis with age. This technique is promising for early screening of atherosclerotic pathologies. However, extraction of the wave indices of APG signals measured from the fingertip is challenging. In this paper, the development of a wave detection algorithm including a preamplifier based on a microcontroller that can detect the a, b, c, and d wave indices is proposed. The 4(th) order derivative of a PPG under real measurements of an APG waveform was introduced to clearly separate the components of the waveform, and to improve the rate of successful wave detection. A preamplifier with a Sallen-Key low pass filter and a wave detection algorithm with programmable gain control, mathematical differentials, and a digital IIR notch filter were designed. The frequency response of the digital IIR filter was evaluated, and a pulse train consisting of a specific area in which the wave indices existed was generated. The programmable gain control maintained a constant APG amplitude at the output for varying PPG amplitudes. For 164 subjects, the mean values and standard deviation of the a wave index corresponding to the magnitude of the APG signal were 1,106.45 and ±47.75, respectively. We conclude that the proposed algorithm and preamplifier designed to extract the wave indices of an APG in real-time are useful for evaluating vascular aging in the cardiovascular system in a simple healthcare device.

Determination of biogenic amines in chocolate by ion chromatographic separation and pulsed integrated amperometric detection with implemented wave-form at Au disposable electrode.

PubMed

Pastore, Paolo; Favaro, Gabriella; Badocco, Denis; Tapparo, Andrea; Cavalli, Silvano; Saccani, Giovanna

2005-12-09

A rapid and selective cation exchange chromatographic method coupled to integrated pulsed amperometric detection (PAD) has been developed to quantify biogenic amines in chocolate. The method is based on gradient elution of aqueous methanesulfonic acid with post column addition of strong base to obtain suitable conditions for amperometric detection. A potential waveform able to keep long time performance of the Au disposable electrode was set up. Total analysis time is less than 20min. Concentration levels of dopamine, serotonin, tyramine, histamine and 2-phenylethylamine were measured, after extraction with perchloric acid from 2g samples previously defatted twice with petroleum ether. The method was used to determine the analytes in chocolate real matrices and their quantification was made with standard addition method. Only dopamine, histamine and serotonin were found in the analysed real samples. Repeatabilities of their signals, computed on their amounts in the real samples, were 5% for all of them. Repeatabilities of tyramine and phenethylamine were relative to standard additions to real samples (close to 1mg/l in the extract) and were 7 and 3%, respectively. Detection limits were computed with the 3s of the baseline noise combined with the calibration plot regression parameters. They were satisfactorily low for all amines: 3mg/kg for dopamine, 2mg/kg for tyramine, 1mg/kg for histamine, 2mg/kg for serotonin, 3mg/kg for 2-phenylethylamine.

Acoustic Full Waveform Inversion to Characterize Near-surface Chemical Explosions

NASA Astrophysics Data System (ADS)

Kim, K.; Rodgers, A. J.

2015-12-01

Recent high-quality, atmospheric overpressure data from chemical high-explosive experiments provide a unique opportunity to characterize near-surface explosions, specifically estimating yield and source time function. Typically, yield is estimated from measured signal features, such as peak pressure, impulse, duration and/or arrival time of acoustic signals. However, the application of full waveform inversion to acoustic signals for yield estimation has not been fully explored. In this study, we apply a full waveform inversion method to local overpressure data to extract accurate pressure-time histories of acoustics sources during chemical explosions. A robust and accurate inversion technique for acoustic source is investigated using numerical Green's functions that take into account atmospheric and topographic propagation effects. The inverted pressure-time history represents the pressure fluctuation at the source region associated with the explosion, and thus, provides a valuable information about acoustic source mechanisms and characteristics in greater detail. We compare acoustic source properties (i.e., peak overpressure, duration, and non-isotropic shape) of a series of explosions having different emplacement conditions and investigate the relationship of the acoustic sources to the yields of explosions. The time histories of acoustic sources may refine our knowledge of sound-generation mechanisms of shallow explosions, and thereby allow for accurate yield estimation based on acoustic measurements. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

Supervised machine learning on a network scale: application to seismic event classification and detection

NASA Astrophysics Data System (ADS)

Reynen, Andrew; Audet, Pascal

2017-09-01

A new method using a machine learning technique is applied to event classification and detection at seismic networks. This method is applicable to a variety of network sizes and settings. The algorithm makes use of a small catalogue of known observations across the entire network. Two attributes, the polarization and frequency content, are used as input to regression. These attributes are extracted at predicted arrival times for P and S waves using only an approximate velocity model, as attributes are calculated over large time spans. This method of waveform characterization is shown to be able to distinguish between blasts and earthquakes with 99 per cent accuracy using a network of 13 stations located in Southern California. The combination of machine learning with generalized waveform features is further applied to event detection in Oklahoma, United States. The event detection algorithm makes use of a pair of unique seismic phases to locate events, with a precision directly related to the sampling rate of the generalized waveform features. Over a week of data from 30 stations in Oklahoma, United States are used to automatically detect 25 times more events than the catalogue of the local geological survey, with a false detection rate of less than 2 per cent. This method provides a highly confident way of detecting and locating events. Furthermore, a large number of seismic events can be automatically detected with low false alarm, allowing for a larger automatic event catalogue with a high degree of trust.

A Single-Channel EOG-Based Speller.

PubMed

He, Shenghong; Li, Yuanqing

2017-11-01

Electrooculography (EOG) signals, which can be used to infer the intentions of a user based on eye movements, are widely used in human-computer interface (HCI) systems. Most existing EOG-based HCI systems incorporate a limited number of commands because they generally associate different commands with a few different types of eye movements, such as looking up, down, left, or right. This paper presents a novel single-channel EOG-based HCI that allows users to spell asynchronously by only blinking. Forty buttons corresponding to 40 characters displayed to the user via a graphical user interface are intensified in a random order. To select a button, the user must blink his/her eyes in synchrony as the target button is flashed. Two data processing procedures, specifically support vector machine (SVM) classification and waveform detection, are combined to detect eye blinks. During detection, we simultaneously feed the feature vectors extracted from the ongoing EOG signal into the SVM classification and waveform detection modules. Decisions are made based on the results of the SVM classification and waveform detection. Three online experiments were conducted with eight healthy subjects. We achieved an average accuracy of 94.4% and a response time of 4.14 s for selecting a character in synchronous mode, as well as an average accuracy of 93.43% and a false positive rate of 0.03/min in the idle state in asynchronous mode. The experimental results, therefore, demonstrated the effectiveness of this single-channel EOG-based speller.

Statistical Properties of Real-Time Amplitude Estimate of Harmonics Affected by Frequency Instability

NASA Astrophysics Data System (ADS)

Bellan, Diego; Pignari, Sergio A.

2016-07-01

This work deals with the statistical characterization of real-time digital measurement of the amplitude of harmonics affected by frequency instability. In fact, in modern power systems both the presence of harmonics and frequency instability are well-known and widespread phenomena mainly due to nonlinear loads and distributed generation, respectively. As a result, real-time monitoring of voltage/current frequency spectra is of paramount importance as far as power quality issues are addressed. Within this framework, a key point is that in many cases real-time continuous monitoring prevents the application of sophisticated algorithms to extract all the information from the digitized waveforms because of the required computational burden. In those cases only simple evaluations such as peak search of discrete Fourier transform are implemented. It is well known, however, that a slight change in waveform frequency results in lack of sampling synchronism and uncertainty in amplitude estimate. Of course the impact of this phenomenon increases with the order of the harmonic to be measured. In this paper an approximate analytical approach is proposed in order to describe the statistical properties of the measured magnitude of harmonics affected by frequency instability. By providing a simplified description of the frequency behavior of the windows used against spectral leakage, analytical expressions for mean value, variance, cumulative distribution function, and probability density function of the measured harmonics magnitude are derived in closed form as functions of waveform frequency treated as a random variable.

Improved Analysis of GW150914 Using a Fully Spin-Precessing Waveform Model

NASA Technical Reports Server (NTRS)

Abbott, B. P.; Abbott, R.; Abbott, T. D.; Abernathy, M. R.; Acernese, F.; Ackley, K.; Adams, C.; Adams, T.; Addesso, P.; Camp, J. B.;

Structures of Xishan village landslide in Li County, Sichuan, China, inferred from high-frequency receiver functions of local earthquakes

NASA Astrophysics Data System (ADS)

Wei, Z.; Chu, R.

2017-12-01

Teleseismic receiver function methods are widely used to study the deep structural information beneath the seismic station. However, teleseismic waveforms are difficult to extract the high-frequency receiver function, which are insufficient to constrain the shallow structure because of the inelastic attenuation effect of the earth. In this study, using the local earthquake waveforms collected from 3 broadband stations deployed on the Xishan village landslide in Li County in Sichuan Province, we used the high-frequency receiver function method to study the shallow structure beneath the landslide. We developed the Vp-k (Vp/Vs) staking method of receiver functions, and combined with the H-k stacking and waveform inversion methods of receiver functions to invert the landslide's thickness, S-wave velocity and average Vp/Vs ratio beneath these stations, and compared the thickness with the borehole results. Our results show small-scale lateral variety of velocity structure, a 78-143m/s lower S-wave velocity in the bottom layer and 2.4-3.1 Vp/Vs ratio in the landslide. The observed high Vp/Vs ratio and low S-wave velocity in the bottom layer of the landslide are consistent with low electrical resistivity and water-rich in the bottom layer, suggesting a weak shear strength and potential danger zone in landslide h1. Our study suggest that the local earthquake receiver function can obtain the shallow velocity structural information and supply some seismic constrains for the landslide catastrophe mitigation.

Micro-seismic waveform matching inversion based on gravitational search algorithm and parallel computation

NASA Astrophysics Data System (ADS)

Jiang, Y.; Xing, H. L.

2016-12-01

Micro-seismic events induced by water injection, mining activity or oil/gas extraction are quite informative, the interpretation of which can be applied for the reconstruction of underground stress and monitoring of hydraulic fracturing progress in oil/gas reservoirs. The source characterises and locations are crucial parameters that required for these purposes, which can be obtained through the waveform matching inversion (WMI) method. Therefore it is imperative to develop a WMI algorithm with high accuracy and convergence speed. Heuristic algorithm, as a category of nonlinear method, possesses a very high convergence speed and good capacity to overcome local minimal values, and has been well applied for many areas (e.g. image processing, artificial intelligence). However, its effectiveness for micro-seismic WMI is still poorly investigated; very few literatures exits that addressing this subject. In this research an advanced heuristic algorithm, gravitational search algorithm (GSA) , is proposed to estimate the focal mechanism (angle of strike, dip and rake) and source locations in three dimension. Unlike traditional inversion methods, the heuristic algorithm inversion does not require the approximation of green function. The method directly interacts with a CPU parallelized finite difference forward modelling engine, and updating the model parameters under GSA criterions. The effectiveness of this method is tested with synthetic data form a multi-layered elastic model; the results indicate GSA can be well applied on WMI and has its unique advantages. Keywords: Micro-seismicity, Waveform matching inversion, gravitational search algorithm, parallel computation

Cylinder pressure reconstruction based on complex radial basis function networks from vibration and speed signals

NASA Astrophysics Data System (ADS)

Johnsson, Roger

2006-11-01

Methods to measure and monitor the cylinder pressure in internal combustion engines can contribute to reduced fuel consumption, noise and exhaust emissions. As direct measurements of the cylinder pressure are expensive and not suitable for measurements in vehicles on the road indirect methods which measure cylinder pressure have great potential value. In this paper, a non-linear model based on complex radial basis function (RBF) networks is proposed for the reconstruction of in-cylinder pressure pulse waveforms. Input to the network is the Fourier transforms of both engine structure vibration and crankshaft speed fluctuation. The primary reason for the use of Fourier transforms is that different frequency regions of the signals are used for the reconstruction process. This approach also makes it easier to reduce the amount of information that is used as input to the RBF network. The complex RBF network was applied to measurements from a 6-cylinder ethanol powered diesel engine over a wide range of running conditions. Prediction accuracy was validated by comparing a number of parameters between the measured and predicted cylinder pressure waveform such as maximum pressure, maximum rate of pressure rise and indicated mean effective pressure. The performance of the network was also evaluated for a number of untrained running conditions that differ both in speed and load from the trained ones. The results for the validation set were comparable to the trained conditions.

Automated Analysis, Classification, and Display of Waveforms

NASA Technical Reports Server (NTRS)

Kwan, Chiman; Xu, Roger; Mayhew, David; Zhang, Frank; Zide, Alan; Bonggren, Jeff

2004-01-01

A computer program partly automates the analysis, classification, and display of waveforms represented by digital samples. In the original application for which the program was developed, the raw waveform data to be analyzed by the program are acquired from space-shuttle auxiliary power units (APUs) at a sampling rate of 100 Hz. The program could also be modified for application to other waveforms -- for example, electrocardiograms. The program begins by performing principal-component analysis (PCA) of 50 normal-mode APU waveforms. Each waveform is segmented. A covariance matrix is formed by use of the segmented waveforms. Three eigenvectors corresponding to three principal components are calculated. To generate features, each waveform is then projected onto the eigenvectors. These features are displayed on a three-dimensional diagram, facilitating the visualization of the trend of APU operations.

Lamb wave detection of limpet mines on ship hulls.

PubMed

Bingham, Jill; Hinders, Mark; Friedman, Adam

2009-12-01

This paper describes the use of ultrasonic guided waves for identifying the mass loading due to underwater limpet mines on ship hulls. The Dynamic Wavelet Fingerprint Technique (DFWT) is used to render the guided wave mode information in two-dimensional binary images because the waveform features of interest are too subtle to identify in time domain. The use of wavelets allows both time and scale features from the original signals to be retained, and image processing can be used to automatically extract features that correspond to the arrival times of the guided wave modes. For further understanding of how the guided wave modes propagate through the real structures, a parallel processing, 3D elastic wave simulation is developed using the finite integration technique (EFIT). This full field, technique models situations that are too complex for analytical solutions, such as built up 3D structures. The simulations have produced informative visualizations of the guided wave modes in the structures as well as mimicking directly the output from sensors placed in the simulation space for direct comparison to experiments. Results from both drydock and in-water experiments with dummy mines are also shown.

Frequency shifts in distortion-product otoacoustic emissions evoked by swept tones

PubMed Central

Shera, Christopher A.; Abdala, Carolina

2016-01-01

When distortion-product otoacoustic emissions (DPOAEs) are evoked using stimuli whose instantaneous frequencies change rapidly and continuously with time (swept tones), the oscillatory interference pattern known as distortion-product fine structure shifts slightly along the frequency axis in the same direction as the sweep. By analogy with the temporal mechanisms thought to underlie the differing efficacies of up- and down-swept stimuli as perceptual maskers (e.g., Schroeder-phase complexes), fine-structure shifts have been ascribed to the phase distortion associated with dispersive wave propagation in the cochlea. This paper tests an alternative hypothesis and finds that the observed shifts arise predominantly as a methodological side effect of the analysis procedures commonly used to extract delayed emissions from the measured time waveform. Approximate expressions for the frequency shifts of DPOAE distortion and reflection components are derived, validated with computer simulations, and applied to account for DPOAE fine-structure shifts measured in human subjects. Component magnitudes are shown to shift twice as much as component phases. Procedures for compensating swept-tone measurements to obtain estimates of the total DPOAE and its components measured at other sweep rates or in the sinusoidal steady state are presented. PMID:27586726

Detection strategies for extreme mass ratio inspirals

NASA Astrophysics Data System (ADS)

Cornish, Neil J.

2011-05-01

The capture of compact stellar remnants by galactic black holes provides a unique laboratory for exploring the near-horizon geometry of the Kerr spacetime, or possible departures from general relativity if the central cores prove not to be black holes. The gravitational radiation produced by these extreme mass ratio inspirals (EMRIs) encodes a detailed map of the black hole geometry, and the detection and characterization of these signals is a major scientific goal for the LISA mission. The waveforms produced are very complex, and the signals need to be coherently tracked for tens of thousands of cycles to produce a detection, making EMRI signals one of the most challenging data analysis problems in all of gravitational wave astronomy. Estimates for the number of templates required to perform an exhaustive grid-based matched-filter search for these signals are astronomically large, and far out of reach of current computational resources. Here I describe an alternative approach that employs a hybrid between genetic algorithms and Markov chain Monte Carlo techniques, along with several time-saving techniques for computing the likelihood function. This approach has proven effective at the blind extraction of relatively weak EMRI signals from simulated LISA data sets.

New Modular Ultrasonic Signal Processing Building Blocks for Real-Time Data Acquisition and Post Processing

NASA Astrophysics Data System (ADS)

Weber, Walter H.; Mair, H. Douglas; Jansen, Dion

2003-03-01

A suite of basic signal processors has been developed. These basic building blocks can be cascaded together to form more complex processors without the need for programming. The data structures between each of the processors are handled automatically. This allows a processor built for one purpose to be applied to any type of data such as images, waveform arrays and single values. The processors are part of Winspect Data Acquisition software. The new processors are fast enough to work on A-scan signals live while scanning. Their primary use is to extract features, reduce noise or to calculate material properties. The cascaded processors work equally well on live A-scan displays, live gated data or as a post-processing engine on saved data. Researchers are able to call their own MATLAB or C-code from anywhere within the processor structure. A built-in formula node processor that uses a simple algebraic editor may make external user programs unnecessary. This paper also discusses the problems associated with ad hoc software development and how graphical programming languages can tie up researchers writing software rather than designing experiments.

Seismic waveform inversion using neural networks

NASA Astrophysics Data System (ADS)

De Wit, R. W.; Trampert, J.

2012-12-01

Full waveform tomography aims to extract all available information on Earth structure and seismic sources from seismograms. The strongly non-linear nature of this inverse problem is often addressed through simplifying assumptions for the physical theory or data selection, thus potentially neglecting valuable information. Furthermore, the assessment of the quality of the inferred model is often lacking. This calls for the development of methods that fully appreciate the non-linear nature of the inverse problem, whilst providing a quantification of the uncertainties in the final model. We propose to invert seismic waveforms in a fully non-linear way by using artificial neural networks. Neural networks can be viewed as powerful and flexible non-linear filters. They are very common in speech, handwriting and pattern recognition. Mixture Density Networks (MDN) allow us to obtain marginal posterior probability density functions (pdfs) of all model parameters, conditioned on the data. An MDN can approximate an arbitrary conditional pdf as a linear combination of Gaussian kernels. Seismograms serve as input, Earth structure parameters are the so-called targets and network training aims to learn the relationship between input and targets. The network is trained on a large synthetic data set, which we construct by drawing many random Earth models from a prior model pdf and solving the forward problem for each of these models, thus generating synthetic seismograms. As a first step, we aim to construct a 1D Earth model. Training sets are constructed using the Mineos package, which computes synthetic seismograms in a spherically symmetric non-rotating Earth by summing normal modes. We train a network on the body waveforms present in these seismograms. Once the network has been trained, it can be presented with new unseen input data, in our case the body waves in real seismograms. We thus obtain the posterior pdf which represents our final state of knowledge given the information in the training set and the real data.

Optimization of an electrokinetic mixer for microfluidic applications.

PubMed

Bockelmann, Hendryk; Heuveline, Vincent; Barz, Dominik P J

2012-06-01

This work is concerned with the investigation of the concentration fields in an electrokinetic micromixer and its optimization in order to achieve high mixing rates. The mixing concept is based on the combination of an alternating electrical excitation applied to a pressure-driven base flow in a meandering microchannel geometry. The electrical excitation induces a secondary electrokinetic velocity component, which results in a complex flow field within the meander bends. A mathematical model describing the physicochemical phenomena present within the micromixer is implemented in an in-house finite-element-method code. We first perform simulations comparable to experiments concerned with the investigation of the flow field in the bends. The comparison of the complex flow topology found in simulation and experiment reveals excellent agreement. Hence, the validated model and numerical schemes are employed for a numerical optimization of the micromixer performance. In detail, we optimize the secondary electrokinetic flow by finding the best electrical excitation parameters, i.e., frequency and amplitude, for a given waveform. Two optimized electrical excitations featuring a discrete and a continuous waveform are discussed with respect to characteristic time scales of our mixing problem. The results demonstrate that the micromixer is able to achieve high mixing degrees very rapidly.

Optimization of an electrokinetic mixer for microfluidic applications

PubMed Central

Bockelmann, Hendryk; Heuveline, Vincent; Barz, Dominik P. J.

2012-01-01

This work is concerned with the investigation of the concentration fields in an electrokinetic micromixer and its optimization in order to achieve high mixing rates. The mixing concept is based on the combination of an alternating electrical excitation applied to a pressure-driven base flow in a meandering microchannel geometry. The electrical excitation induces a secondary electrokinetic velocity component, which results in a complex flow field within the meander bends. A mathematical model describing the physicochemical phenomena present within the micromixer is implemented in an in-house finite-element-method code. We first perform simulations comparable to experiments concerned with the investigation of the flow field in the bends. The comparison of the complex flow topology found in simulation and experiment reveals excellent agreement. Hence, the validated model and numerical schemes are employed for a numerical optimization of the micromixer performance. In detail, we optimize the secondary electrokinetic flow by finding the best electrical excitation parameters, i.e., frequency and amplitude, for a given waveform. Two optimized electrical excitations featuring a discrete and a continuous waveform are discussed with respect to characteristic time scales of our mixing problem. The results demonstrate that the micromixer is able to achieve high mixing degrees very rapidly. PMID:22712034

Investigations of black-hole spectra: Purely-imaginary modes and Kerr ringdown radiation

NASA Astrophysics Data System (ADS)

Zalutskiy, Maxim P.

When black holes are perturbed they give rise to characteristic waves that propagate outwards carrying information about the black hole. In the linear regime these waves are described in terms of quasinormal modes (QNM). Studying QNM is an important topic which may provide a connection to the quantum theory of gravity in addition to their astrophysical applications. Quasinormal modes correspond to complex frequencies where the real part represents oscillation and the imaginary part represents damping. We have developed a new code for calculating QNM with high precision and accuracy, which we applied to the Schwarzschild and Kerr geometries. The high accuracy of our calculations was a significant improvement over prior work, allowing us to compute QNM much closer to the negative imaginary axis (NIA) than it was possible before. The existence of QNM on the NIA has remained poorly understood, but our high accuracy studies have highlighted the importance of understanding their nature. In this work we show how the purely-imaginary modes can be calculated with the help of the theory of confluent Heun polynomials with the conclusion that all modes on the NIA correspond to polynomial solutions. We also show that certain types of these modes correspond to Kerr QNM. Finally, using our highly accurate QNM data we model the ringdown, a remnant black hole's decaying radiation. Ringdown occurs in the final stages of such violent astrophysical events as supernovae and black hole collisions. We use our model to analyse the ringdown waveforms from the publicly available binary black hole coalescence catalog maintained by the SXS collaboration. In our analysis we use a number of methods: Fourier transform, multi-mode nonlinear fitting and waveform overlap. Both our fitting and overlap approach allow inclusion of many modes in the ringdown model with the goal being to extract information about the nature of the astrophysical source of the ringdown signal.

Restoration of clipped seismic waveforms using projection onto convex sets method

PubMed Central

Zhang, Jinhai; Hao, Jinlai; Zhao, Xu; Wang, Shuqin; Zhao, Lianfeng; Wang, Weimin; Yao, Zhenxing

2016-01-01

The seismic waveforms would be clipped when the amplitude exceeds the upper-limit dynamic range of seismometer. Clipped waveforms are typically assumed not useful and seldom used in waveform-based research. Here, we assume the clipped components of the waveform share the same frequency content with the un-clipped components. We leverage this similarity to convert clipped waveforms to true waveforms by iteratively reconstructing the frequency spectrum using the projection onto convex sets method. Using artificially clipped data we find that statistically the restoration error is ~1% and ~5% when clipped at 70% and 40% peak amplitude, respectively. We verify our method using real data recorded at co-located seismometers that have different gain controls, one set to record large amplitudes on scale and the other set to record low amplitudes on scale. Using our restoration method we recover 87 out of 93 clipped broadband records from the 2013 Mw6.6 Lushan earthquake. Estimating that we recover 20 clipped waveforms for each M5.0+ earthquake, so for the ~1,500 M5.0+ events that occur each year we could restore ~30,000 clipped waveforms each year, which would greatly enhance useable waveform data archives. These restored waveform data would also improve the azimuthal station coverage and spatial footprint. PMID:27966618

One-Dimensional Signal Extraction Of Paper-Written ECG Image And Its Archiving

NASA Astrophysics Data System (ADS)

Zhang, Zhi-ni; Zhang, Hong; Zhuang, Tian-ge

1987-10-01

A method for converting paper-written electrocardiograms to one dimensional (1-D) signals for archival storage on floppy disk is presented here. Appropriate image processing techniques were employed to remove the back-ground noise inherent to ECG recorder charts and to reconstruct the ECG waveform. The entire process consists of (1) digitization of paper-written ECGs with an image processing system via a TV camera; (2) image preprocessing, including histogram filtering and binary image generation; (3) ECG feature extraction and ECG wave tracing, and (4) transmission of the processed ECG data to IBM-PC compatible floppy disks for storage and retrieval. The algorithms employed here may also be used in the recognition of paper-written EEG or EMG and may be useful in robotic vision.

Analysis and suppression of passive noise in surface microseismic data

NASA Astrophysics Data System (ADS)

Forghani-Arani, Farnoush

Surface microseismic surveys are gaining popularity in monitoring the hydraulic fracturing process. The effectiveness of these surveys, however, is strongly dependent on the signal-to-noise ratio of the acquired data. Cultural and industrial noise generated during hydraulic fracturing operations usually dominate the data, thereby decreasing the effectiveness of using these data in identifying and locating microseismic events. Hence, noise suppression is a critical step in surface microseismic monitoring. In this thesis, I focus on two important aspects in using surface-recorded microseismic seismic data: first, I take advantage of the unwanted surface noise to understand the characteristics of these noise and extract information about the propagation medium from the noise; second, I propose effective techniques to suppress the surface noise while preserving the waveforms that contain information about the source of microseisms. Automated event identification on passive seismic data using only a few receivers is challenging especially when the record lengths span over long durations of time. I introduce an automatic event identification algorithm that is designed specifically for detecting events in passive data acquired with a small number of receivers. I demonstrate that the conventional STA/LTA (Short-term Average/Long-term Average) algorithm is not sufficiently effective in event detection in the common case of low signal-to-noise ratio. With a cross-correlation based method as an extension of the STA/LTA algorithm, even low signal-to-noise events (that were not detectable with conventional STA/LTA) were revealed. Surface microseismic data contains surface-waves (generated primarily from hydraulic fracturing activities) and body-waves in the form of microseismic events. It is challenging to analyze the surface-waves on the recorded data directly because of the randomness of their source and their unknown source signatures. I use seismic interferometry to extract the surface-wave arrivals. Interferometry is a powerful tool to extract waves (including body-wave and surface-waves) that propagate from any receiver in the array (called a pseudo source) to the other receivers across the array. Since most of the noise sources in surface microseismic data lie on the surface, seismic interferometry yields pseudo source gathers dominated by surface-wave energy. The dispersive characteristics of these surface-waves are important properties that can be used to extract information necessary for suppressing these waves. I demonstrate the application of interferometry to surface passive data recorded during the hydraulic fracturing operation of a tight gas reservoir and extract the dispersion properties of surface-waves corresponding to a pseudo-shot gather. Comparison of the dispersion characteristics of the surface waves from the pseudo-shot gather with that of an active shot-gather shows interesting similarities and differences. The dispersion character (e.g. velocity change with frequency) of the fundamental mode was observed to have the same behavior for both the active and passive data. However, for the higher mode surface-waves, the dispersion properties are extracted at different frequency ranges. Conventional noise suppression techniques in passive data are mostly stacking-based that rely on enforcing the amplitude of the signal by stacking the waveforms at the receivers and are unable to preserve the waveforms at the individual receivers necessary for estimating the microseismic source location and source mechanism. Here, I introduce a technique based on the tau - p transform, that effectively identifies and separates microseismic events from surface-wave noise in the tau -p domain. This technique is superior to conventional stacking-based noise suppression techniques, because it preserves the waveforms at individual receivers. Application of this methodology to microseismic events with isotropic and double-couple source mechanism, show substantial improvement in the signal-to-noise ratio. Imaging of the processed field data also show improved imaging of the hypocenter location of the microseismic source. In the case of double-couple source mechanism, I suggest two approaches for unifying the polarities at the receivers, a cross-correlation approach and a semblance-based prediction approach. The semblance-based approach is more effective at unifying the polarities, especially for low signal-to-noise ratio data.

Analysis of Waveform Retracking Methods in Antarctic Ice Sheet Based on CRYOSAT-2 Data

NASA Astrophysics Data System (ADS)

Xiao, F.; Li, F.; Zhang, S.; Hao, W.; Yuan, L.; Zhu, T.; Zhang, Y.; Zhu, C.

2017-09-01

Satellite altimetry plays an important role in many geoscientific and environmental studies of Antarctic ice sheet. The ranging accuracy is degenerated near coasts or over nonocean surfaces, due to waveform contamination. A postprocess technique, known as waveform retracking, can be used to retrack the corrupt waveform and in turn improve the ranging accuracy. In 2010, the CryoSat-2 satellite was launched with the Synthetic aperture Interferometric Radar ALtimeter (SIRAL) onboard. Satellite altimetry waveform retracking methods are discussed in the paper. Six retracking methods including the OCOG method, the threshold method with 10 %, 25 % and 50 % threshold level, the linear and exponential 5-β parametric methods are used to retrack CryoSat-2 waveform over the transect from Zhongshan Station to Dome A. The results show that the threshold retracker performs best with the consideration of waveform retracking success rate and RMS of retracking distance corrections. The linear 5-β parametric retracker gives best waveform retracking precision, but cannot make full use of the waveform data.

A simple accurate chest-compression depth gauge using magnetic coils during cardiopulmonary resuscitation

NASA Astrophysics Data System (ADS)

Kandori, Akihiko; Sano, Yuko; Zhang, Yuhua; Tsuji, Toshio

2015-12-01

This paper describes a new method for calculating chest compression depth and a simple chest-compression gauge for validating the accuracy of the method. The chest-compression gauge has two plates incorporating two magnetic coils, a spring, and an accelerometer. The coils are located at both ends of the spring, and the accelerometer is set on the bottom plate. Waveforms obtained using the magnetic coils (hereafter, "magnetic waveforms"), which are proportional to compression-force waveforms and the acceleration waveforms were measured at the same time. The weight factor expressing the relationship between the second derivatives of the magnetic waveforms and the measured acceleration waveforms was calculated. An estimated-compression-displacement (depth) waveform was obtained by multiplying the weight factor and the magnetic waveforms. Displacements of two large springs (with similar spring constants) within a thorax and displacements of a cardiopulmonary resuscitation training manikin were measured using the gauge to validate the accuracy of the calculated waveform. A laser-displacement detection system was used to compare the real displacement waveform and the estimated waveform. Intraclass correlation coefficients (ICCs) between the real displacement using the laser system and the estimated displacement waveforms were calculated. The estimated displacement error of the compression depth was within 2 mm (<1 standard deviation). All ICCs (two springs and a manikin) were above 0.85 (0.99 in the case of one of the springs). The developed simple chest-compression gauge, based on a new calculation method, provides an accurate compression depth (estimation error < 2 mm).

Global shear speed structure of the upper mantle and transition zone

NASA Astrophysics Data System (ADS)

Schaeffer, A. J.; Lebedev, S.

2013-07-01

The rapid expansion of broad-band seismic networks over the last decade has paved the way for a new generation of global tomographic models. Significantly improved resolution of global upper-mantle and crustal structure can now be achieved, provided that structural information is extracted effectively from both surface and body waves and that the effects of errors in the data are controlled and minimized. Here, we present a new global, vertically polarized shear speed model that yields considerable improvements in resolution, compared to previous ones, for a variety of features in the upper mantle and crust. The model, SL2013sv, is constrained by an unprecedentedly large set of waveform fits (˜3/4 of a million broad-band seismograms), computed in seismogram-dependent frequency bands, up to a maximum period range of 11-450 s. Automated multimode inversion of surface and S-wave forms was used to extract a set of linear equations with uncorrelated uncertainties from each seismogram. The equations described perturbations in elastic structure within approximate sensitivity volumes between sources and receivers. Going beyond ray theory, we calculated the phase of every mode at every frequency and its derivative with respect to S- and P-velocity perturbations by integration over a sensitivity area in a 3-D reference model; the (normally small) perturbations of the 3-D model required to fit the waveforms were then linearized using these accurate derivatives. The equations yielded by the waveform inversion of all the seismograms were simultaneously inverted for a 3-D model of shear and compressional speeds and azimuthal anisotropy within the crust and upper mantle. Elaborate outlier analysis was used to control the propagation of errors in the data (source parameters, timing at the stations, etc.). The selection of only the most mutually consistent equations exploited the data redundancy provided by our data set and strongly reduced the effect of the errors, increasing the resolution of the imaging. Our new shear speed model is parametrized on a triangular grid with a ˜280 km spacing. In well-sampled continental domains, lateral resolution approaches or exceeds that of regional-scale studies. The close match of known surface expressions of deep structure with the distribution of anomalies in the model provides a useful benchmark. In oceanic regions, spreading ridges are very well resolved, with narrow anomalies in the shallow mantle closely confined near the ridge axis, and those deeper, down to 100-120 km, showing variability in their width and location with respect to the ridge. Major subduction zones worldwide are well captured, extending from shallow depths down to the transition zone. The large size of our waveform fit data set also provides a strong statistical foundation to re-examine the validity field of the JWKB approximation and surface wave ray theory. Our analysis shows that the approximations are likely to be valid within certain time-frequency portions of most seismograms with high signal-to-noise ratios, and these portions can be identified using a set of consistent criteria that we apply in the course of waveform fitting.

Sonic spectrometer and treatment system

DOEpatents

Slomka, B.J.

1997-06-03

A novel system and method is developed for treating an object with sonic waveforms. A traveling broad-band sonic waveform containing a broad-band of sonic frequencies is radiated at the object. A traveling reflected sonic waveform containing sonic frequencies reflected by the object is received in response to the traveling broad-band sonic waveform. A traveling transmitted sonic waveform containing sonic frequencies transmitted through the object is also received in response to the traveling broad-band sonic waveform. In a resonance mode, the frequency spectra of the broad-band and reflected sonic waveforms is analyzed so as to select one or more sonic frequencies that cause the object to resonate. An electrical resonance treatment sonic waveform containing the sonic frequencies that cause the object to resonate is then radiated at the object so as to treat the object. In an absorption mode, the frequency spectra of the electrical broad-band, reflected, and transmitted sonic waveforms is compared so as to select one or more sonic frequencies that are absorbed by the object. An electrical absorption treatment sonic waveform containing the sonic frequencies that are absorbed by the object is then radiated at the object so as to treat the object. 1 fig.

Sonic spectrometer and treatment system

DOEpatents

Slomka, Bogdan J.

1997-06-03

A novel system and method for treating an object with sonic waveforms. A traveling broad-band sonic waveform containing a broad-band of sonic frequencies is radiated at the object. A traveling reflected sonic waveform containing sonic frequencies reflected by the object is received in response to the traveling broad-band sonic waveform. A traveling transmitted sonic waveform containing sonic frequencies transmitted through the object is also received in response to the traveling broad-band sonic waveform. In a resonance mode, the frequency spectra of the broad-band and reflected sonic waveforms is analyzed so as to select one or more sonic frequencies that cause the object to resonate. An electrical resonance treatment sonic waveform containing the sonic frequencies that cause the object to resonate is then radiated at the object so as to treat the object. In an absorption mode, the frequency spectra of the electrical broad-band, reflected, and transmitted sonic waveforms is compared so as to select one or more sonic frequencies that are absorbed by the object. An electrical absorption treatment sonic waveform containing the sonic frequencies that are absorbed by the object is then radiated at the object so as to treat the object.

Statistics of natural binaural sounds.

PubMed

Młynarski, Wiktor; Jost, Jürgen

2014-01-01

Binaural sound localization is usually considered a discrimination task, where interaural phase (IPD) and level (ILD) disparities at narrowly tuned frequency channels are utilized to identify a position of a sound source. In natural conditions however, binaural circuits are exposed to a stimulation by sound waves originating from multiple, often moving and overlapping sources. Therefore statistics of binaural cues depend on acoustic properties and the spatial configuration of the environment. Distribution of cues encountered naturally and their dependence on physical properties of an auditory scene have not been studied before. In the present work we analyzed statistics of naturally encountered binaural sounds. We performed binaural recordings of three auditory scenes with varying spatial configuration and analyzed empirical cue distributions from each scene. We have found that certain properties such as the spread of IPD distributions as well as an overall shape of ILD distributions do not vary strongly between different auditory scenes. Moreover, we found that ILD distributions vary much weaker across frequency channels and IPDs often attain much higher values, than can be predicted from head filtering properties. In order to understand the complexity of the binaural hearing task in the natural environment, sound waveforms were analyzed by performing Independent Component Analysis (ICA). Properties of learned basis functions indicate that in natural conditions soundwaves in each ear are predominantly generated by independent sources. This implies that the real-world sound localization must rely on mechanisms more complex than a mere cue extraction.

Statistics of Natural Binaural Sounds

PubMed Central

Młynarski, Wiktor; Jost, Jürgen

2014-01-01

Binaural sound localization is usually considered a discrimination task, where interaural phase (IPD) and level (ILD) disparities at narrowly tuned frequency channels are utilized to identify a position of a sound source. In natural conditions however, binaural circuits are exposed to a stimulation by sound waves originating from multiple, often moving and overlapping sources. Therefore statistics of binaural cues depend on acoustic properties and the spatial configuration of the environment. Distribution of cues encountered naturally and their dependence on physical properties of an auditory scene have not been studied before. In the present work we analyzed statistics of naturally encountered binaural sounds. We performed binaural recordings of three auditory scenes with varying spatial configuration and analyzed empirical cue distributions from each scene. We have found that certain properties such as the spread of IPD distributions as well as an overall shape of ILD distributions do not vary strongly between different auditory scenes. Moreover, we found that ILD distributions vary much weaker across frequency channels and IPDs often attain much higher values, than can be predicted from head filtering properties. In order to understand the complexity of the binaural hearing task in the natural environment, sound waveforms were analyzed by performing Independent Component Analysis (ICA). Properties of learned basis functions indicate that in natural conditions soundwaves in each ear are predominantly generated by independent sources. This implies that the real-world sound localization must rely on mechanisms more complex than a mere cue extraction. PMID:25285658

Synchronous Motions Across the Instrumental Climate Record

NASA Astrophysics Data System (ADS)

Carl, Peter

The Earth's climate system bears a rich variety of feedback mechanisms that may give rise to complex, evolving modal structures under internal and external control. Various types of synchronization may be identified in the system's motion when looking at representative time series of the instrumental period through the glasses of an advanced technique of sparse data approximation, the Matching Pursuit (MP) approach. To disentangle the emerging network of oscillatory modes to the degree that climate dynamics turns out to be separable, a large dictionary of "Gaussian logons," i.e. frequency modulated (FM) Gabor atoms, is applied. Though the extracted modes make up linear decompositions, this flexible analyzing signal matches highly nonlinear waveforms. Univariate analyses over the period 1870-1997 are presented of a set of customary time series in annual resolution, comprising global and regional climate, central European synoptic systems, German precipitation, and runoff of the Elbe river near Dresden. All the evidence from this first-generation MP-FM study, obtained in subsequent multivariate syntheses, points to dynamically excited regimes of an organized yet complex climate system under permanent change—perhaps a (pre)chaotic one at centennial timescales, suggesting a "chaos control" perspective on global climate dynamics and change. Findings and conclusions include, among others, internal structure of reconstructed insolation, the episodic nature of global warming as reflected in multidecadal temperature modes, their swarm of "interdomain" companions across the whole system that unveils an unknown regime character of interannual climate dynamics, and the apparent onset early in the 1990s of the present thermal stagnation.

The auditory scene: an fMRI study on melody and accompaniment in professional pianists.

PubMed

Spada, Danilo; Verga, Laura; Iadanza, Antonella; Tettamanti, Marco; Perani, Daniela

2014-11-15

The auditory scene is a mental representation of individual sounds extracted from the summed sound waveform reaching the ears of the listeners. Musical contexts represent particularly complex cases of auditory scenes. In such a scenario, melody may be seen as the main object moving on a background represented by the accompaniment. Both melody and accompaniment vary in time according to harmonic rules, forming a typical texture with melody in the most prominent, salient voice. In the present sparse acquisition functional magnetic resonance imaging study, we investigated the interplay between melody and accompaniment in trained pianists, by observing the activation responses elicited by processing: (1) melody placed in the upper and lower texture voices, leading to, respectively, a higher and lower auditory salience; (2) harmonic violations occurring in either the melody, the accompaniment, or both. The results indicated that the neural activation elicited by the processing of polyphonic compositions in expert musicians depends upon the upper versus lower position of the melodic line in the texture, and showed an overall greater activation for the harmonic processing of melody over accompaniment. Both these two predominant effects were characterized by the involvement of the posterior cingulate cortex and precuneus, among other associative brain regions. We discuss the prominent role of the posterior medial cortex in the processing of melodic and harmonic information in the auditory stream, and propose to frame this processing in relation to the cognitive construction of complex multimodal sensory imagery scenes. Copyright © 2014 Elsevier Inc. All rights reserved.

Waveform Generator Signal Processing Software

DOT National Transportation Integrated Search

1988-09-01

This report describes the software that was developed to process test waveforms that were recorded by crash test data acquisition systems. The test waveforms are generated by an electronic waveform generator developed by MGA Research Corporation unde...

Uncertainty quantification of wall shear stress in intracranial aneurysms using a data-driven statistical model of systemic blood flow variability.

PubMed

Sarrami-Foroushani, Ali; Lassila, Toni; Gooya, Ali; Geers, Arjan J; Frangi, Alejandro F

2016-12-08

Adverse wall shear stress (WSS) patterns are known to play a key role in the localisation, formation, and progression of intracranial aneurysms (IAs). Complex region-specific and time-varying aneurysmal WSS patterns depend both on vascular morphology as well as on variable systemic flow conditions. Computational fluid dynamics (CFD) has been proposed for characterising WSS patterns in IAs; however, CFD simulations often rely on deterministic boundary conditions that are not representative of the actual variations in blood flow. We develop a data-driven statistical model of internal carotid artery (ICA) flow, which is used to generate a virtual population of waveforms used as inlet boundary conditions in CFD simulations. This allows the statistics of the resulting aneurysmal WSS distributions to be computed. It is observed that ICA waveform variations have limited influence on the time-averaged WSS (TAWSS) on the IA surface. In contrast, in regions where the flow is locally highly multidirectional, WSS directionality and harmonic content are strongly affected by the ICA flow waveform. As a consequence, we argue that the effect of blood flow variability should be explicitly considered in CFD-based IA rupture assessment to prevent confounding the conclusions. Copyright © 2016 Elsevier Ltd. All rights reserved.

Ecological connectivity in the three-dimensional urban green volume using waveform airborne lidar

PubMed Central

Casalegno, Stefano; Anderson, Karen; Cox, Daniel T. C.; Hancock, Steven; Gaston, Kevin J.

2017-01-01

The movements of organisms and the resultant flows of ecosystem services are strongly shaped by landscape connectivity. Studies of urban ecosystems have relied on two-dimensional (2D) measures of greenspace structure to calculate connectivity. It is now possible to explore three-dimensional (3D) connectivity in urban vegetation using waveform lidar technology that measures the full 3D structure of the canopy. Making use of this technology, here we evaluate urban greenspace 3D connectivity, taking into account the full vertical stratification of the vegetation. Using three towns in southern England, UK, all with varying greenspace structures, we describe and compare the structural and functional connectivity using both traditional 2D greenspace models and waveform lidar-generated vegetation strata (namely, grass, shrubs and trees). Measures of connectivity derived from 3D greenspace are lower than those derived from 2D models, as the latter assumes that all vertical vegetation strata are connected, which is rarely true. Fragmented landscapes that have more complex 3D vegetation showed greater functional connectivity and we found highest 2D to 3D functional connectivity biases for short dispersal capacities of organisms (6 m to 16 m). These findings are particularly pertinent in urban systems where the distribution of greenspace is critical for delivery of ecosystem services. PMID:28382936

Ecological connectivity in the three-dimensional urban green volume using waveform airborne lidar

NASA Astrophysics Data System (ADS)

Casalegno, Stefano; Anderson, Karen; Cox, Daniel T. C.; Hancock, Steven; Gaston, Kevin J.

2017-04-01

The movements of organisms and the resultant flows of ecosystem services are strongly shaped by landscape connectivity. Studies of urban ecosystems have relied on two-dimensional (2D) measures of greenspace structure to calculate connectivity. It is now possible to explore three-dimensional (3D) connectivity in urban vegetation using waveform lidar technology that measures the full 3D structure of the canopy. Making use of this technology, here we evaluate urban greenspace 3D connectivity, taking into account the full vertical stratification of the vegetation. Using three towns in southern England, UK, all with varying greenspace structures, we describe and compare the structural and functional connectivity using both traditional 2D greenspace models and waveform lidar-generated vegetation strata (namely, grass, shrubs and trees). Measures of connectivity derived from 3D greenspace are lower than those derived from 2D models, as the latter assumes that all vertical vegetation strata are connected, which is rarely true. Fragmented landscapes that have more complex 3D vegetation showed greater functional connectivity and we found highest 2D to 3D functional connectivity biases for short dispersal capacities of organisms (6 m to 16 m). These findings are particularly pertinent in urban systems where the distribution of greenspace is critical for delivery of ecosystem services.

Transdimensional inversion of scattered body waves for 1D S-wave velocity structure - Application to the Tengchong volcanic area, Southwestern China

NASA Astrophysics Data System (ADS)

Li, Mengkui; Zhang, Shuangxi; Bodin, Thomas; Lin, Xu; Wu, Tengfei

2018-06-01

Inversion of receiver functions is commonly used to recover the S-wave velocity structure beneath seismic stations. Traditional approaches are based on deconvolved waveforms, where the horizontal component of P-wave seismograms is deconvolved by the vertical component. Deconvolution of noisy seismograms is a numerically unstable process that needs to be stabilized by regularization parameters. This biases noise statistics, making it difficult to estimate uncertainties in observed receiver functions for Bayesian inference. This study proposes a method to directly invert observed radial waveforms and to better account for data noise in a Bayesian formulation. We illustrate its feasibility with two synthetic tests having different types of noises added to seismograms. Then, a real site application is performed to obtain the 1-D S-wave velocity structure beneath a seismic station located in the Tengchong volcanic area, Southwestern China. Surface wave dispersion measurements spanning periods from 8 to 65 s are jointly inverted with P waveforms. The results show a complex S-wave velocity structure, as two low velocity zones are observed in the crust and uppermost mantle, suggesting the existence of magma chambers, or zones of partial melt. The upper magma chambers may be the heart source that cause the thermal activity on the surface.

A LabVIEW model incorporating an open-loop arterial impedance and a closed-loop circulatory system.

PubMed

Cole, R T; Lucas, C L; Cascio, W E; Johnson, T A

2005-11-01

While numerous computer models exist for the circulatory system, many are limited in scope, contain unwanted features or incorporate complex components specific to unique experimental situations. Our purpose was to develop a basic, yet multifaceted, computer model of the left heart and systemic circulation in LabVIEW having universal appeal without sacrificing crucial physiologic features. The program we developed employs Windkessel-type impedance models in several open-loop configurations and a closed-loop model coupling a lumped impedance and ventricular pressure source. The open-loop impedance models demonstrate afterload effects on arbitrary aortic pressure/flow inputs. The closed-loop model catalogs the major circulatory waveforms with changes in afterload, preload, and left heart properties. Our model provides an avenue for expanding the use of the ventricular equations through closed-loop coupling that includes a basic coronary circuit. Tested values used for the afterload components and the effects of afterload parameter changes on various waveforms are consistent with published data. We conclude that this model offers the ability to alter several circulatory factors and digitally catalog the most salient features of the pressure/flow waveforms employing a user-friendly platform. These features make the model a useful instructional tool for students as well as a simple experimental tool for cardiovascular research.

Anatomy of Old Faithful hydrothermal system from subsurface seismic imaging of the Yellowstone Upper Geyser Basin

NASA Astrophysics Data System (ADS)

Wu, S. M.; Lin, F. C.; Farrell, J.; Ward, K. M.; Karplus, M. S.; Smith, R. B.

2017-12-01

The Upper Geyser Basin (UGB) in Yellowstone National Park contains one of the highest concentrations of hydrothermal features on Earth including the iconic Old Faithful Geyser (OFG). Although this system has been the focus of many geological, geochemical, and geophysical studies, the shallow (<200 m) subsurface structure and the hydrothermal tremor behavior remain poorly characterized. To probe the detailed structure that relates to the hydrothermal plumbing of the UGB, we deployed dense arrays of 3-C 5-Hz geophones in both November of 2015 and 2016, composed of 133 stations with 50 m spacing, and 519 station locations, with an 20 m spacing, respectively. By applying seismic interferometry techniques, we extracted Rayleigh-wave signals between 1-10 Hz via seismic signals excited by nearby hydrothermal features (e.g. geysers and pools). We observe a clear lateral velocity boundary at 3.3 Hz frequency that delineates a higher phase velocity of 1.6 km/sec in the NE and a lower phase velocity of 1.0 km/sec in the SW corresponding to the local geologic formation of rhyolitic and glacial deposits, respectively. We also image a relatively shallow (20-60 m deep) large reservoir with an estimated porosity 30% located 100 meters southwest of the OFG from the significant spatial-dependent waveform distortions and delays between 5-10 Hz frequency. This reservoir is likely controlled by the local geology with a rhyolitic deposit in the NE acting as a relatively impermeable barrier to vertical fluid ascent. To understand the pre-eruption tremor signals from OFG, we first study the seismic waveforms recorded at the closest station to the OFG cone. Many highly repetitive seismic pulses associated with bubble collapse, which compose the tremor signal, can be identified. Using a reference event template and the cross-correlation method, we can determine the onset of each individual bubbling event using a cross-correlation coefficient threshold of 0.8. Based on the detected timing, we then inspect the spatial and temporal variation of the event waveforms across the dense arrays. Clear correlation between temporal waveform variation and air temperature is observed. In this presentation, we will discuss the potential mechanisms of tremor waveform variation and how that can be used to improve our understanding of geyser dynamics.

Extracting the building response using seismic interferometry: Theory and application to the Millikan Library in Pasadena, California

USGS Publications Warehouse

Snieder, R.; Safak, E.

2006-01-01

The motion of a building depends on the excitation, the coupling of the building to the ground, and the mechanical properties of the building. We separate the building response from the excitation and the ground coupling by deconvolving the motion recorded at different levels in the building and apply this to recordings of the motion in the Robert A. Millikan Library in Pasadena, California. This deconvolution allows for the separation of instrinsic attenuation and radiation damping. The waveforms obtained from deconvolution with the motion in the top floor show a superposition of one upgoing and one downgoing wave. The waveforms obtained by deconvolution with the motion in the basement can be formulated either as a sum of upgoing and downgoing waves, or as a sum over normal modes. Because these deconvolved waves for late time have a monochromatic character, they are most easily analyzed with normal-mode theory. For this building we estimate a shear velocity c = 322 m/sec and a quality factor Q = 20. These values explain both the propagating waves and the normal modes.

A Pulsed Thermographic Imaging System for Detection and Identification of Cotton Foreign Matter

PubMed Central

Kuzy, Jesse; Li, Changying

2017-01-01

Detection of foreign matter in cleaned cotton is instrumental to accurately grading cotton quality, which in turn impacts the marketability of the cotton. Current grading systems return estimates of the amount of foreign matter present, but provide no information about the identity of the contaminants. This paper explores the use of pulsed thermographic analysis to detect and identify cotton foreign matter. The design and implementation of a pulsed thermographic analysis system is described. A sample set of 240 foreign matter and cotton lint samples were collected. Hand-crafted waveform features and frequency-domain features were extracted and analyzed for statistical significance. Classification was performed on these features using linear discriminant analysis and support vector machines. Using waveform features and support vector machine classifiers, detection of cotton foreign matter was performed with 99.17% accuracy. Using frequency-domain features and linear discriminant analysis, identification was performed with 90.00% accuracy. These results demonstrate that pulsed thermographic imaging analysis produces data which is of significant utility for the detection and identification of cotton foreign matter. PMID:28273848

Improved neutron-gamma discrimination for a 3He neutron detector using subspace learning methods

DOE PAGES

Wang, C. L.; Funk, L. L.; Riedel, R. A.; ...

2017-02-10

3He gas based neutron linear-position-sensitive detectors (LPSDs) have been applied for many neutron scattering instruments. Traditional Pulse-Height Analysis (PHA) for Neutron-Gamma Discrimination (NGD) resulted in the neutron-gamma efficiency ratio on the orders of 10 5-10 6. The NGD ratios of 3He detectors need to be improved for even better scientific results from neutron scattering. Digital Signal Processing (DSP) analyses of waveforms were proposed for obtaining better NGD ratios, based on features extracted from rise-time, pulse amplitude, charge integration, a simplified Wiener filter, and the cross-correlation between individual and template waveforms of neutron and gamma events. Fisher linear discriminant analysis (FLDA)more » and three multivariate analyses (MVAs) of the features were performed. The NGD ratios are improved by about 10 2-10 3 times compared with the traditional PHA method. Finally, our results indicate the NGD capabilities of 3He tube detectors can be significantly improved with subspace-learning based methods, which may result in a reduced data-collection time and better data quality for further data reduction.« less

Ship-borne Radio and GLD360 Measurements of Intense Oceanic Lightning

NASA Astrophysics Data System (ADS)

Zoghzoghy, F. G.; Cohen, M.; Said, R.; Lehtinen, N. G.; Inan, U.

2013-12-01

Recent studies with the GLD360 lightning geo-location network have shown that the peak current intensity of cloud-to-ground (CG) lightning is more powerful over the ocean than over land. This remains a poorly understood phenomenon. The Stanford VLF group has recently deployed a Very Low Frequency (1 MHz sampling rate) radio receiver system aboard the NOAA Ronald W. Brown research vessel. The goal of this transatlantic experiment is to improve our understanding of oceanic lightning and to investigate the physical difference between oceanic and land lightning. When positioned reasonably close to deep oceanic thunderstorms, the LF-VLF receiver aboard the Ronald W. Brown detects the impulsive radio emissions from the return stroke, up to 1 MHz, which enables us to estimate the return-stroke waveform shapes generated by the lightning channel. In this presentation, we present our experimental setup and a summary of the data collected during the transatlantic voyages of the NOAA ship. We process lightning-generated waveforms, compare them to LF-VLF data from land lightning over Oklahoma, extract statistical patterns, and compare the data to numerical and analytical models.

Seismpol_ a visual-basic computer program for interactive and automatic earthquake waveform analysis

NASA Astrophysics Data System (ADS)

Patanè, Domenico; Ferrari, Ferruccio

1997-11-01

A Microsoft Visual-Basic computer program for waveform analysis of seismic signals is presented. The program combines interactive and automatic processing of digital signals using data recorded by three-component seismic stations. The analysis procedure can be used in either an interactive earthquake analysis or an automatic on-line processing of seismic recordings. The algorithm works in the time domain using the Covariance Matrix Decomposition method (CMD), so that polarization characteristics may be computed continuously in real time and seismic phases can be identified and discriminated. Visual inspection of the particle motion in hortogonal planes of projection (hodograms) reduces the danger of misinterpretation derived from the application of the polarization filter. The choice of time window and frequency intervals improves the quality of the extracted polarization information. In fact, the program uses a band-pass Butterworth filter to process the signals in the frequency domain by analysis of a selected signal window into a series of narrow frequency bands. Significant results supported by well defined polarizations and source azimuth estimates for P and S phases are also obtained for short-period seismic events (local microearthquakes).

Linear-phase delay filters for ultra-low-power signal processing in neural recording implants.

PubMed

Gosselin, Benoit; Sawan, Mohamad; Kerherve, Eric

2010-06-01

We present the design and implementation of linear-phase delay filters for ultra-low-power signal processing in neural recording implants. We use these filters as low-distortion delay elements along with an automatic biopotential detector to perform integral waveform extraction and efficient power management. The presented delay elements are realized employing continuous-time OTA-C filters featuring 9th-order equiripple transfer functions with constant group delay. Such analog delay enables processing neural waveforms with reduced overhead compared to a digital delay since it does not requires sampling and digitization. It uses an allpass transfer function for achieving wider constant-delay bandwidth than all-pole does. Two filters realizations are compared for implementing the delay element: the Cascaded structure and the Inverse follow-the-leader feedback filter. Their respective strengths and drawbacks are assessed by modeling parasitics and non-idealities of OTAs, and by transistor-level simulations. A budget of 200 nA is used in both filters. Experimental measurements with the chosen filter topology are presented and discussed.

A computationally efficient method for incorporating spike waveform information into decoding algorithms.

PubMed

Ventura, Valérie; Todorova, Sonia

2015-05-01

Spike-based brain-computer interfaces (BCIs) have the potential to restore motor ability to people with paralysis and amputation, and have shown impressive performance in the lab. To transition BCI devices from the lab to the clinic, decoding must proceed automatically and in real time, which prohibits the use of algorithms that are computationally intensive or require manual tweaking. A common choice is to avoid spike sorting and treat the signal on each electrode as if it came from a single neuron, which is fast, easy, and therefore desirable for clinical use. But this approach ignores the kinematic information provided by individual neurons recorded on the same electrode. The contribution of this letter is a linear decoding model that extracts kinematic information from individual neurons without spike-sorting the electrode signals. The method relies on modeling sample averages of waveform features as functions of kinematics, which is automatic and requires minimal data storage and computation. In offline reconstruction of arm trajectories of a nonhuman primate performing reaching tasks, the proposed method performs as well as decoders based on expertly manually and automatically sorted spikes.

Order-crossing removal in Gabor order tracking by independent component analysis

NASA Astrophysics Data System (ADS)

Guo, Yu; Tan, Kok Kiong

2009-08-01

Order-crossing problems in Gabor order tracking (GOT) of rotating machinery often occur when noise due to power-frequency interference, local structure resonance, etc., is prominent in applications. They can render the analysis results and the waveform-reconstruction tasks in GOT inaccurate or even meaningless. An approach is proposed in this paper to address the order-crossing problem by independent component analysis (ICA). With the approach, accurate order analysis results can be obtained and the waveforms of the order components of interest can be reconstructed or extracted from the recorded noisy data series. In addition, the ambiguities (permutation and scaling) of ICA results are also solved with the approach. The approach is amenable to applications in condition monitoring and fault diagnosis of rotating machinery. The evaluation of the approach is presented in detail based on simulations and an experiment on a rotor test rig. The results obtained using the proposed approach are compared with those obtained using the standard GOT. The comparison shows that the presented approach is more effective to solve order-crossing problems in GOT.

Numerical predictions and experiments for optimizing hidden corrosion detection in aircraft structures using Lamb modes.

PubMed

Terrien, N; Royer, D; Lepoutre, F; Déom, A

2007-06-01

To increase the sensitivity of Lamb waves to hidden corrosion in aircraft structures, a preliminary step is to understand the phenomena governing this interaction. A hybrid model combining a finite element approach and a modal decomposition method is used to investigate the interaction of Lamb modes with corrosion pits. The finite element mesh is used to describe the region surrounding the corrosion pits while the modal decomposition method permits to determine the waves reflected and transmitted by the damaged area. Simulations make easier the interpretation of some parts of the measured waveform corresponding to superposition of waves diffracted by the corroded area. Numerical results permit to extract significant information from the transmitted waveform and thus to optimize the signal processing for the detection of corrosion at an early stage. Now, we are able to detect corrosion pits down to 80-mum depth distributed randomly on a square centimeter of an aluminum plate. Moreover, thickness variations present on aircraft structures can be discriminated from a slightly corroded area. Finally, using this experimental setup, aircraft structures have been tested.

Parameters Comparsion of Leads Detection in Arctic Sea Ice Using CRYOSAT-2 Waveform Data

NASA Astrophysics Data System (ADS)

Li, J.; Zhang, S.; Xiao, F.; Zhu, C.; Zhang, Y.; Zhu, T.; Yuan, L.

2018-04-01

Leads are only a small part of the polar sea ice structure, but they play a dominant role on the turbulence exchange between the ocean and the atmosphere, they are also important factors about sea ice thickness inversion. Since the early 2000s, Satellite altimetry has been applied to monitor the Arctic sea ice thickness, Satellite altimetry data can be used to distinguish leads and sea ice. In this paper, four parameters including Pulse peakiness (PP), stack standard deviation (SSD), stack kurtosis (SKU) and stack skewness (SSK) are extracted from CryoSat-2 satellite altimetry waveform data. The four parameters are combined into five combinations (PP, PP&SSD, PP&SSD&SKU, PP&SSD&SSK, PP&SSD&SSK&SKU) with constrain conditions to detect the leads. The results of the five methods are compared with MODIS (moderate-resolution imagining spectroradiometer) images and show that, the combination of PP&SSD is better than the single PP, the rest of combinations are the same as the combination of PP&SSD. It turns out, there is no promotion when we add SSK and SKU, successively or simultaneously.

Contrast in Terahertz Images of Archival Documents—Part II: Influence of Topographic Features

NASA Astrophysics Data System (ADS)

Bardon, Tiphaine; May, Robert K.; Taday, Philip F.; Strlič, Matija

2017-04-01

We investigate the potential of terahertz time-domain imaging in reflection mode to reveal archival information in documents in a non-invasive way. In particular, this study explores the parameters and signal processing tools that can be used to produce well-contrasted terahertz images of topographic features commonly found in archival documents, such as indentations left by a writing tool, as well as sieve lines. While the amplitude of the waveforms at a specific time delay can provide the most contrasted and legible images of topographic features on flat paper or parchment sheets, this parameter may not be suitable for documents that have a highly irregular surface, such as water- or fire-damaged documents. For analysis of such documents, cross-correlation of the time-domain signals can instead yield images with good contrast. Analysis of the frequency-domain representation of terahertz waveforms can also provide well-contrasted images of topographic features, with improved spatial resolution when utilising high-frequency content. Finally, we point out some of the limitations of these means of analysis for extracting information relating to topographic features of interest from documents.

PKP Waveform Complexity and Its Implications to Fine Structure Near the Edge of African Large Low Shear Velocity Province

NASA Astrophysics Data System (ADS)

Song, Teh-Ru Alex; Tanaka, Satoru; Takeuchi, Nozomu

2010-05-01

P wave traveling through the Earth's core typically includes three distinct phases, PKPdf (or PKIKP), PKPbc and PKPab and these waves have been frequently analyzed to study the structure of the outer-core and inner-core. It is well known that PKPab waveform suffers a 90-degree phase shift when encountering an internal acoustics in the outer-core and it is theoretically equivalent to Hilbert-transformed PKPbc (or PKPdf) waveform. Here, we report a dataset from an intermediate-depth earthquake in Vanuatu Islands recorded by a PASSCAL broadband array in Cameroon, West Africa. Two anomalous features stand out in this record section. First, in the period of a few seconds and longer, most PKPab waveforms recorded by this array are anomalous in a way that they do not display a 90-degree phase shift that is observed in other stations in Europe. Secondly, in the high frequency band of 0.5 Hz to 2 Hz, two large arrivals separated by about 3.4 seconds are observed in the time window of PKPab phase and they are often absent in the time window of PKPdf and PKPbc phases. In addition, the second arrival seems suffer some degree of phase shift relative to the first arrival. We examine several other record sections from nearby events in Tonga and they do not show such an anomalous feature, suggesting that receiver structures are probably not the cause of this observation. Note that the take-off angle of PKPab is typically 9-12 degrees shallower than that of PKPdf and PKPbc and it is possible that near-source scattering from the slab may account for such an anomalous feature. We make Hilbert transform of P waveforms recorded at shorter range of less than 90 degrees and compare them with these anomalous PKPab waveforms. However, these Hilbert-transformed P wave show a clear 90-degree phase shift relative to PKPdf and PKPbc and they are different from PKPab waveforms, despite a difference in take-off angles of less than 5 degrees in some cases. It appears that near-source scatterings and receiver-side structure do not play a predominant role in generating these anomalous PKPab waveforms. We then look into structural anomaly near the core-mantle-boundary (CMB) since PKPab grazes the CMB at a very shallow angle and it can effectively interact with it and possibly produce anomalous PKPab waveforms. We first explore 1-D model space by introducing velocity anomaly directly above the CMB, with a velocity perturbation up to a few tens of percents in S wave velocity and P wave velocity. We calculate synthetics up to 2 Hz by Direct Solution Method (DSM) and Reflectivity Method to examine waveform anomaly at long period band (0.01-0.2 Hz) as well as short-period band (0.5-2 Hz). Our preliminary result indicates that the model with a thin (~ 15 km) ultra-low velocity zone (ULVZ, 30% reduction in P wave and S wave velocity) is capable of reproducing characteristics of these anomalous PKPab waveforms at both frequency bands. The pierce points of PKPab in the source side at CMB are near the southeast Indian Ocean where S wave velocity is only slightly faster than PREM. On the other hand, the pierce points in the receiver side are at the eastern edge of the African Large Low Shear Velocity Province (LLSVP). One interesting feature of our ULVZ model is that dlnVs/dlnVp is about 1, which is different from most ULVZ models where dlnVs/dlnVp is about 3.

Micropower RF transponder with superregenerative receiver and RF receiver with sampling mixer

DOEpatents

McEwan, Thomas E.

1997-01-01

A micropower RF transdponder employs a novel adaptation of the superregenerative receiver wherein the quench oscillator is external to the regenerative transistor. The quench oscillator applies an exponentially decaying waveform rather than the usual sinewave to achieve high sensitivity at microampere current levels. Further improvements include circuit simplifications for antenna coupling, extraction of the detected signal, and a low-voltage bias configuration that allows operation with less than a 1-volt rail voltage. The inventive transponder is expected to operate as long as the battery shelf life.

Micropower RF transponder with superregenerative receiver and RF receiver with sampling mixer

DOEpatents

McEwan, T.E.

1997-05-13

A micropower RF transponder employs a novel adaptation of the superregenerative receiver wherein the quench oscillator is external to the regenerative transistor. The quench oscillator applies an exponentially decaying waveform rather than the usual sinewave to achieve high sensitivity at microampere current levels. Further improvements include circuit simplifications for antenna coupling, extraction of the detected signal, and a low-voltage bias configuration that allows operation with less than a 1-volt rail voltage. The inventive transponder is expected to operate as long as the battery shelf life. 13 figs.

Planetary Gears Feature Extraction and Fault Diagnosis Method Based on VMD and CNN.

PubMed

Liu, Chang; Cheng, Gang; Chen, Xihui; Pang, Yusong

2018-05-11

Given local weak feature information, a novel feature extraction and fault diagnosis method for planetary gears based on variational mode decomposition (VMD), singular value decomposition (SVD), and convolutional neural network (CNN) is proposed. VMD was used to decompose the original vibration signal to mode components. The mode matrix was partitioned into a number of submatrices and local feature information contained in each submatrix was extracted as a singular value vector using SVD. The singular value vector matrix corresponding to the current fault state was constructed according to the location of each submatrix. Finally, by training a CNN using singular value vector matrices as inputs, planetary gear fault state identification and classification was achieved. The experimental results confirm that the proposed method can successfully extract local weak feature information and accurately identify different faults. The singular value vector matrices of different fault states have a distinct difference in element size and waveform. The VMD-based partition extraction method is better than ensemble empirical mode decomposition (EEMD), resulting in a higher CNN total recognition rate of 100% with fewer training times (14 times). Further analysis demonstrated that the method can also be applied to the degradation recognition of planetary gears. Thus, the proposed method is an effective feature extraction and fault diagnosis technique for planetary gears.

Planetary Gears Feature Extraction and Fault Diagnosis Method Based on VMD and CNN

PubMed Central

Cheng, Gang; Chen, Xihui

2018-01-01

Given local weak feature information, a novel feature extraction and fault diagnosis method for planetary gears based on variational mode decomposition (VMD), singular value decomposition (SVD), and convolutional neural network (CNN) is proposed. VMD was used to decompose the original vibration signal to mode components. The mode matrix was partitioned into a number of submatrices and local feature information contained in each submatrix was extracted as a singular value vector using SVD. The singular value vector matrix corresponding to the current fault state was constructed according to the location of each submatrix. Finally, by training a CNN using singular value vector matrices as inputs, planetary gear fault state identification and classification was achieved. The experimental results confirm that the proposed method can successfully extract local weak feature information and accurately identify different faults. The singular value vector matrices of different fault states have a distinct difference in element size and waveform. The VMD-based partition extraction method is better than ensemble empirical mode decomposition (EEMD), resulting in a higher CNN total recognition rate of 100% with fewer training times (14 times). Further analysis demonstrated that the method can also be applied to the degradation recognition of planetary gears. Thus, the proposed method is an effective feature extraction and fault diagnosis technique for planetary gears. PMID:29751671

Research on the Multiple Factors Influencing Human Identification Based on Pyroelectric Infrared Sensors

PubMed Central

Lou, Ping; Hu, Jianmin

2018-01-01

Analysis of the multiple factors affecting human identification ability based on pyroelectric infrared technology is a complex problem. First, we examine various sensed pyroelectric waveforms of the human body thermal infrared signal and reveal a mechanism for affecting human identification. Then, we find that the mechanism is decided by the distance, human target, pyroelectric infrared (PIR) sensor, the body type, human moving velocity, signal modulation mask, and Fresnel lens. The mapping relationship between the sensed waveform and multiple influencing factors is established, and a group of mathematical models are deduced which fuse the macro factors and micro factors. Finally, the experimental results show the macro-factors indirectly affect the recognition ability of human based on the pyroelectric technology. At the same time, the correctness and effectiveness of the mathematical models is also verified, which make it easier to obtain more pyroelectric infrared information about the human body for discriminating human targets. PMID:29462908

Constant flow-driven microfluidic oscillator for different duty cycles

PubMed Central

Kim, Sung-Jin; Yokokawa, Ryuji; Lesher-Perez, Sasha Cai; Takayama, Shuichi

2012-01-01

This paper presents microfluidic devices that autonomously convert two constant flow inputs into an alternating oscillatory flow output. We accomplish this hardware embedded self-control programming using normally closed membrane valves that have an inlet, an outlet, and a membrane-pressurization chamber connected to a third terminal. Adjustment of threshold opening pressures in these 3-terminal flow switching valves enabled adjustment of oscillation periods to between 57–360 s with duty cycles of 0.2–0.5. These values are in relatively good agreement with theoretical values, providing the way for rational design of an even wider range of different waveform oscillations. We also demonstrate the ability to use these oscillators to perform temporally patterned delivery of chemicals to living cells. The device only needs a syringe pump, thus removing the use of complex, expensive external actuators. These tunable waveform microfluidic oscillators are envisioned to facilitate cell-based studies that require temporal stimulation. PMID:22206453

High Field Asymmetric Waveform Ion Mobility Spectrometry (FAIMS) for Mass Spectrometry-Based Proteomics

PubMed Central

Swearingen, Kristian E.; Moritz, Robert L.

2013-01-01

SUMMARY High field asymmetric waveform ion mobility spectrometry (FAIMS) is an atmospheric pressure ion mobility technique that separates gas-phase ions by their behavior in strong and weak electric fields. FAIMS is easily interfaced with electrospray ionization and has been implemented as an additional separation mode between liquid chromatography (LC) and mass spectrometry (MS) in proteomic studies. FAIMS separation is orthogonal to both LC and MS and is used as a means of on-line fractionation to improve detection of peptides in complex samples. FAIMS improves dynamic range and concomitantly the detection limits of ions by filtering out chemical noise. FAIMS can also be used to remove interfering ion species and to select peptide charge states optimal for identification by tandem MS. Here, we review recent developments in LC-FAIMS-MS and its application to MS-based proteomics. PMID:23194268

The effect of inlet waveforms on computational hemodynamics of patient-specific intracranial aneurysms.

PubMed

Xiang, J; Siddiqui, A H; Meng, H

2014-12-18

Due to the lack of patient-specific inlet flow waveform measurements, most computational fluid dynamics (CFD) simulations of intracranial aneurysms usually employ waveforms that are not patient-specific as inlet boundary conditions for the computational model. The current study examined how this assumption affects the predicted hemodynamics in patient-specific aneurysm geometries. We examined wall shear stress (WSS) and oscillatory shear index (OSI), the two most widely studied hemodynamic quantities that have been shown to predict aneurysm rupture, as well as maximal WSS (MWSS), energy loss (EL) and pressure loss coefficient (PLc). Sixteen pulsatile CFD simulations were carried out on four typical saccular aneurysms using 4 different waveforms and an identical inflow rate as inlet boundary conditions. Our results demonstrated that under the same mean inflow rate, different waveforms produced almost identical WSS distributions and WSS magnitudes, similar OSI distributions but drastically different OSI magnitudes. The OSI magnitude is correlated with the pulsatility index of the waveform. Furthermore, there is a linear relationship between aneurysm-averaged OSI values calculated from one waveform and those calculated from another waveform. In addition, different waveforms produced similar MWSS, EL and PLc in each aneurysm. In conclusion, inlet waveform has minimal effects on WSS, OSI distribution, MWSS, EL and PLc and a strong effect on OSI magnitude, but aneurysm-averaged OSI from different waveforms has a strong linear correlation with each other across different aneurysms, indicating that for the same aneurysm cohort, different waveforms can consistently stratify (rank) OSI of aneurysms. Copyright © 2014 Elsevier Ltd. All rights reserved.

Acoustic Green's function extraction in the ocean

NASA Astrophysics Data System (ADS)

Zang, Xiaoqin

The acoustic Green's function (GF) is the key to understanding the acoustic properties of ocean environments. With knowledge of the acoustic GF, the physics of sound propagation, such as dispersion, can be analyzed; underwater communication over thousands of miles can be understood; physical properties of the ocean, including ocean temperature, ocean current speed, as well as seafloor bathymetry, can be investigated. Experimental methods of acoustic GF extraction can be categorized as active methods and passive methods. Active methods are based on employment of man-made sound sources. These active methods require less computational complexity and time, but may cause harm to marine mammals. Passive methods cost much less and do not harm marine mammals, but require more theoretical and computational work. Both methods have advantages and disadvantages that should be carefully tailored to fit the need of each specific environment and application. In this dissertation, we study one passive method, the noise interferometry method, and one active method, the inverse filter processing method, to achieve acoustic GF extraction in the ocean. The passive method of noise interferometry makes use of ambient noise to extract an approximation to the acoustic GF. In an environment with a diffusive distribution of sound sources, sound waves that pass through two hydrophones at two locations carry the information of the acoustic GF between these two locations; by listening to the long-term ambient noise signals and cross-correlating the noise data recorded at two locations, the acoustic GF emerges from the noise cross-correlation function (NCF); a coherent stack of many realizations of NCFs yields a good approximation to the acoustic GF between these two locations, with all the deterministic structures clearly exhibited in the waveform. To test the performance of noise interferometry in different types of ocean environments, two field experiments were performed and ambient noise data were collected in a 100-meter deep coastal ocean environment and a 600-meter deep ocean environment. In the coastal ocean environment, the collected noise data were processed by coherently stacking five days of cross-correlation functions between pairs of hydrophones separated by 5 km, 10 km and 15 km, respectively. NCF waveforms were modeled using the KRAKEN normal mode model, with the difference between the NCFs and the acoustic GFs quantified by a weighting function. Through waveform inversion of NCFs, an optimal geoacoustic model was obtained by minimizing the two-norm misfit between the simulation and the measurement. Using a simulated time-reversal mirror, the extracted GF was back propagated from the receiver location to the virtual source, and a strong focus was found in the vicinity of the source, which provides additional support for the optimality of the aforementioned geoacoustic model. With the extracted GF, dispersion in experimental shallow water environment was visualized in the time-frequency representation. Normal modes of GFs were separated using the time-warping transformation. By separating the modes in the frequency domain of the time-warped signal, we isolated modal arrivals and reconstructed the NCF by summing up the isolated modes, thereby significantly improving the signal-to-noise ratio of NCFs. Finally, these reconstructed NCFs were employed to estimate the depth-averaged current speed in the Florida Straits, based on an effective sound speed approximation. In the mid-deep ocean environment, the noise data were processed using the same noise interferometry method, but the obtained NCFs were not as good as those in the coastal ocean environment. Several highly possible reasons of the difference in the noise interferometry performance were investigated and discussed. The first one is the noise source composition, which is different in the spectrograms of noise records in two environments. The second is strong ocean current variability that can result in coherence loss and undermine the utility of coherent stacking. The third one is the downward refracting sound speed profile, which impedes strong coupling between near surface noise sources and the near-bottom instruments. The active method of inverse filter processing was tested in a long-range deep-ocean environment. The high-power sound source, which was located near the sound channel axis, transmitted a pre-designed signal that was composed of a precursor signal and a communication signal. After traveling 1428.5 km distance in the north Pacific Ocean, the transmitted signal was detected by the receiver and was processed using the inverse filter. The probe signal, which was composed of M sequences and was known at the receiver, was utilized for the GF extraction in the inverse filter; the communication signal was then interpreted with the extracted GF. With a glitch in the length of communication signal, the inverse filter processing method was shown to be effective for long-range low-frequency deep ocean acoustic communication. (Abstract shortened by ProQuest.).

Tree species classification using within crown localization of waveform LiDAR attributes

NASA Astrophysics Data System (ADS)

Blomley, Rosmarie; Hovi, Aarne; Weinmann, Martin; Hinz, Stefan; Korpela, Ilkka; Jutzi, Boris

2017-11-01

Since forest planning is increasingly taking an ecological, diversity-oriented perspective into account, remote sensing technologies are becoming ever more important in assessing existing resources with reduced manual effort. While the light detection and ranging (LiDAR) technology provides a good basis for predictions of tree height and biomass, tree species identification based on this type of data is particularly challenging in structurally heterogeneous forests. In this paper, we analyse existing approaches with respect to the geometrical scale of feature extraction (whole tree, within crown partitions or within laser footprint) and conclude that currently features are always extracted separately from the different scales. Since multi-scale approaches however have proven successful in other applications, we aim to utilize the within-tree-crown distribution of within-footprint signal characteristics as additional features. To do so, a spin image algorithm, originally devised for the extraction of 3D surface features in object recognition, is adapted. This algorithm relies on spinning an image plane around a defined axis, e.g. the tree stem, collecting the number of LiDAR returns or mean values of returns attributes per pixel as respective values. Based on this representation, spin image features are extracted that comprise only those components of highest variability among a given set of library trees. The relative performance and the combined improvement of these spin image features with respect to non-spatial statistical metrics of the waveform (WF) attributes are evaluated for the tree species classification of Scots pine (Pinus sylvestris L.), Norway spruce (Picea abies (L.) Karst.) and Silver/Downy birch (Betula pendula Roth/Betula pubescens Ehrh.) in a boreal forest environment. This evaluation is performed for two WF LiDAR datasets that differ in footprint size, pulse density at ground, laser wavelength and pulse width. Furthermore, we evaluate the robustness of the proposed method with respect to internal parameters and tree size. The results reveal, that the consideration of the crown-internal distribution of within-footprint signal characteristics captured in spin image features improves the classification results in nearly all test cases.

Evaluating coastal sea surface heights based on a novel sub-waveform approach using sparse representation and conditional random fields

NASA Astrophysics Data System (ADS)

Uebbing, Bernd; Roscher, Ribana; Kusche, Jürgen

2016-04-01

Satellite radar altimeters allow global monitoring of mean sea level changes over the last two decades. However, coastal regions are less well observed due to influences on the returned signal energy by land located inside the altimeter footprint. The altimeter emits a radar pulse, which is reflected at the nadir-surface and measures the two-way travel time, as well as the returned energy as a function of time, resulting in a return waveform. Over the open ocean the waveform shape corresponds to a theoretical model which can be used to infer information on range corrections, significant wave height or wind speed. However, in coastal areas the shape of the waveform is significantly influenced by return signals from land, located in the altimeter footprint, leading to peaks which tend to bias the estimated parameters. Recently, several approaches dealing with this problem have been published, including utilizing only parts of the waveform (sub-waveforms), estimating the parameters in two steps or estimating additional peak parameters. We present a new approach in estimating sub-waveforms using conditional random fields (CRF) based on spatio-temporal waveform information. The CRF piece-wise approximates the measured waveforms based on a pre-derived dictionary of theoretical waveforms for various combinations of the geophysical parameters; neighboring range gates are likely to be assigned to the same underlying sub-waveform model. Depending on the choice of hyperparameters in the CRF estimation, the classification into sub-waveforms can either be more fine or coarse resulting in multiple sub-waveform hypotheses. After the sub-waveforms have been detected, existing retracking algorithms can be applied to derive water heights or other desired geophysical parameters from particular sub-waveforms. To identify the optimal heights from the multiple hypotheses, instead of utilizing a known reference height, we apply a Dijkstra-algorithm to find the "shortest path" of all possible heights. We apply our approach to Jason-2 data in different coastal areas, such as the Bangladesh coast or in the North Sea and compare our sea surface heights to various existing retrackers. Using the sub-waveform approach, we are able to derive meaningful water heights up to a few kilometers off the coast, where conventional retrackers, such as the standard ocean retracker, no longer provide useful data.

Ionization Electron Signal Processing in Single Phase LArTPCs I. Algorithm Description and Quantitative Evaluation with MicroBooNE Simulation

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

Adams, C.; et al.

We describe the concept and procedure of drifted-charge extraction developed in the MicroBooNE experiment, a single-phase liquid argon time projection chamber (LArTPC). This technique converts the raw digitized TPC waveform to the number of ionization electrons passing through a wire plane at a given time. A robust recovery of the number of ionization electrons from both induction and collection anode wire planes will augment the 3D reconstruction, and is particularly important for tomographic reconstruction algorithms. A number of building blocks of the overall procedure are described. The performance of the signal processing is quantitatively evaluated by comparing extracted charge withmore » the true charge through a detailed TPC detector simulation taking into account position-dependent induced current inside a single wire region and across multiple wires. Some areas for further improvement of the performance of the charge extraction procedure are also discussed.« less

STRS Compliant FPGA Waveform Development

NASA Technical Reports Server (NTRS)

Nappier, Jennifer; Downey, Joseph; Mortensen, Dale

2008-01-01

The Space Telecommunications Radio System (STRS) Architecture Standard describes a standard for NASA space software defined radios (SDRs). It provides a common framework that can be used to develop and operate a space SDR in a reconfigurable and reprogrammable manner. One goal of the STRS Architecture is to promote waveform reuse among multiple software defined radios. Many space domain waveforms are designed to run in the special signal processing (SSP) hardware. However, the STRS Architecture is currently incomplete in defining a standard for designing waveforms in the SSP hardware. Therefore, the STRS Architecture needs to be extended to encompass waveform development in the SSP hardware. The extension of STRS to the SSP hardware will promote easier waveform reconfiguration and reuse. A transmit waveform for space applications was developed to determine ways to extend the STRS Architecture to a field programmable gate array (FPGA). These extensions include a standard hardware abstraction layer for FPGAs and a standard interface between waveform functions running inside a FPGA. A FPGA-based transmit waveform implementation of the proposed standard interfaces on a laboratory breadboard SDR will be discussed.

Waveform Tomography of the South Atlantic Region

NASA Astrophysics Data System (ADS)

Celli, N. L.; Lebedev, S.; Schaeffer, A. J.; Gaina, C.

2016-12-01

The rapid growth in broadband seismic data, along with developments in waveform tomography techniques, allow us to greatly improve the data sampling in the southern hemisphere and resolve the upper-mantle structure beneath the South Atlantic region at a new level of detail. We have gathered a very large waveform dataset, including all publicly available data from permanent and temporary networks. Our S-velocity tomographic model is constrained by vertical-component waveform fits, computed using the Automated Multimode Inversion of surface, S and multiple S waves. Each seismogram fit provides a set of linear equations describing 1D average velocity perturbations within approximate sensitivity volumes, with respect to a 3D reference model. All the equations are then combined into a large linear system and inverted jointly for a model of shear- and compressional-wave speeds and azimuthal anisotropy within the lithosphere and underlying mantle. The isotropic-average shear speeds are proxies for temperature and composition at depth, while azimuthal anisotropy provides evidence on the past and present deformation in the lithosphere and asthenosphere beneath the region. We resolve the complex boundaries of the mantle roots of South America's and Africa's cratons and the deep low-velocity anomalies beneath volcanic areas in South America. Pronounced lithospheric high seismic velocity anomalies beneath the Argentine Basin suggest that its anomalously deep seafloor, previously attributed to dynamic topography, is mainly due to anomalously cold, thick lithosphere. Major hotspots show low-velocity anomalies extending substantially deeper than those beneath the mid-ocean ridge. The Vema Hotspot shows a major, hot asthenospheric anomaly beneath thick, cold oceanic lithosphere. The mantle lithosphere beneath the Walvis Ridge—a hotspot track—shows normal cooling. The volcanic Cameroon Line, in contrast, is characterized by thin lithosphere beneath the locations of recent volcanism.

Local infrasound observations of large ash explosions at Augustine Volcano, Alaska, during January 11–28, 2006

USGS Publications Warehouse

Petersen, Tanja; De Angelis, Silvio; Tytgat, Guy; McNutt, Stephen R.

2006-01-01

We present and interpret acoustic waveforms associated with a sequence of large explosion events that occurred during the initial stages of the 2006 eruption of Augustine Volcano, Alaska. During January 11–28, 2006, 13 large explosion events created ash-rich plumes that reached up to 14 km a.s.l., and generated atmospheric pressure waves that were recorded on scale by a microphone located at a distance of 3.2 km from the active vent. The variety of recorded waveforms included sharp N-shaped waves with durations of a few seconds, impulsive signals followed by complex codas, and extended signals with emergent character and durations up to minutes. Peak amplitudes varied between 14 and 105 Pa; inferred acoustic energies ranged between 2×108 and 4×109 J. A simple N-shaped short-duration signal recorded on January 11, 2006 was associated with the vent-opening blast that marked the beginning of the explosive eruption sequence. During the following days, waveforms with impulsive onsets and extended codas accompanied the eruptive activity, which was characterized by explosion events that generated large ash clouds and pyroclastic flows along the flanks of the volcano. Continuous acoustic waveforms that lacked a clear onset were more common during this period. On January 28, 2006, the occurrence of four large explosion events marked the end of this explosive eruption phase at Augustine Volcano. After a transitional period of about two days, characterized by many small discrete bursts, the eruption changed into a stage of more sustained and less explosive activity accompanied by the renewed growth of a summit lava dome.

Optimal space communications techniques. [using digital and phase locked systems for signal processing

NASA Technical Reports Server (NTRS)

Schilling, D. L.

1974-01-01

Digital multiplication of two waveforms using delta modulation (DM) is discussed. It is shown that while conventional multiplication of two N bit words requires N2 complexity, multiplication using DM requires complexity which increases linearly with N. Bounds on the signal-to-quantization noise ratio (SNR) resulting from this multiplication are determined and compared with the SNR obtained using standard multiplication techniques. The phase locked loop (PLL) system, consisting of a phase detector, voltage controlled oscillator, and a linear loop filter, is discussed in terms of its design and system advantages. Areas requiring further research are identified.

Stochastic-Constraints Method in Nonstationary Hot-Clutter Cancellation Part I: Fundamentals and Supervised Training Applications

DTIC Science & Technology

2003-04-01

any of the P interfering sources, and Hkt i (1) (P)] T is defined below. The P-variate vector = t kt , • t J consists of complex waveforms radiated by...line. More precisely, the (i, j ) t element of the matrix Hke is a complex 4-4 coefficient which is practically constant over the kth PRI, and is a...multivariate auto-regressive (AR) model of order n: Ykt + Z Bj Yk- j , t = tkt (25) j =l In the above equation, Bj are the M-variate matrices which are the

Computational Stimulation of the Basal Ganglia Neurons with Cost Effective Delayed Gaussian Waveforms

PubMed Central

Daneshzand, Mohammad; Faezipour, Miad; Barkana, Buket D.

2017-01-01

Deep brain stimulation (DBS) has compelling results in the desynchronization of the basal ganglia neuronal activities and thus, is used in treating the motor symptoms of Parkinson's disease (PD). Accurate definition of DBS waveform parameters could avert tissue or electrode damage, increase the neuronal activity and reduce energy cost which will prolong the battery life, hence avoiding device replacement surgeries. This study considers the use of a charge balanced Gaussian waveform pattern as a method to disrupt the firing patterns of neuronal cell activity. A computational model was created to simulate ganglia cells and their interactions with thalamic neurons. From the model, we investigated the effects of modified DBS pulse shapes and proposed a delay period between the cathodic and anodic parts of the charge balanced Gaussian waveform to desynchronize the firing patterns of the GPe and GPi cells. The results of the proposed Gaussian waveform with delay outperformed that of rectangular DBS waveforms used in in-vivo experiments. The Gaussian Delay Gaussian (GDG) waveforms achieved lower number of misses in eliciting action potential while having a lower amplitude and shorter length of delay compared to numerous different pulse shapes. The amount of energy consumed in the basal ganglia network due to GDG waveforms was dropped by 22% in comparison with charge balanced Gaussian waveforms without any delay between the cathodic and anodic parts and was also 60% lower than a rectangular charged balanced pulse with a delay between the cathodic and anodic parts of the waveform. Furthermore, by defining a Synchronization Level metric, we observed that the GDG waveform was able to reduce the synchronization of GPi neurons more effectively than any other waveform. The promising results of GDG waveforms in terms of eliciting action potential, desynchronization of the basal ganglia neurons and reduction of energy consumption can potentially enhance the performance of DBS devices. PMID:28848417

Computational Stimulation of the Basal Ganglia Neurons with Cost Effective Delayed Gaussian Waveforms.

PubMed

Daneshzand, Mohammad; Faezipour, Miad; Barkana, Buket D

2017-01-01

Deep brain stimulation (DBS) has compelling results in the desynchronization of the basal ganglia neuronal activities and thus, is used in treating the motor symptoms of Parkinson's disease (PD). Accurate definition of DBS waveform parameters could avert tissue or electrode damage, increase the neuronal activity and reduce energy cost which will prolong the battery life, hence avoiding device replacement surgeries. This study considers the use of a charge balanced Gaussian waveform pattern as a method to disrupt the firing patterns of neuronal cell activity. A computational model was created to simulate ganglia cells and their interactions with thalamic neurons. From the model, we investigated the effects of modified DBS pulse shapes and proposed a delay period between the cathodic and anodic parts of the charge balanced Gaussian waveform to desynchronize the firing patterns of the GPe and GPi cells. The results of the proposed Gaussian waveform with delay outperformed that of rectangular DBS waveforms used in in-vivo experiments. The Gaussian Delay Gaussian (GDG) waveforms achieved lower number of misses in eliciting action potential while having a lower amplitude and shorter length of delay compared to numerous different pulse shapes. The amount of energy consumed in the basal ganglia network due to GDG waveforms was dropped by 22% in comparison with charge balanced Gaussian waveforms without any delay between the cathodic and anodic parts and was also 60% lower than a rectangular charged balanced pulse with a delay between the cathodic and anodic parts of the waveform. Furthermore, by defining a Synchronization Level metric, we observed that the GDG waveform was able to reduce the synchronization of GPi neurons more effectively than any other waveform. The promising results of GDG waveforms in terms of eliciting action potential, desynchronization of the basal ganglia neurons and reduction of energy consumption can potentially enhance the performance of DBS devices.

Gravitational Waveforms in the Early Inspiral of Binary Black Hole Systems

NASA Astrophysics Data System (ADS)

Barkett, Kevin; Kumar, Prayush; Bhagwat, Swetha; Brown, Duncan; Scheel, Mark; Szilagyi, Bela; Simulating eXtreme Spacetimes Collaboration

2015-04-01

The inspiral, merger and ringdown of compact object binaries are important targets for gravitational wave detection by aLIGO. Detection and parameter estimation will require long, accurate waveforms for comparison. There are a number of analytical models for generating gravitational waveforms for these systems, but the only way to ensure their consistency and correctness is by comparing with numerical relativity simulations that cover many inspiral orbits. We've simulated a number of binary black hole systems with mass ratio 7 and a moderate, aligned spin on the larger black hole. We have attached these numerical waveforms to analytical waveform models to generate long hybrid gravitational waveforms that span the entire aLIGO frequency band. We analyze the robustness of these hybrid waveforms and measure the faithfulness of different hybrids with each other to obtain an estimate on how long future numerical simulations need to be in order to ensure that waveforms are accurate enough for use by aLIGO.

[Study of sharing platform of web-based enhanced extracorporeal counterpulsation hemodynamic waveform data].

PubMed

Huang, Mingbo; Hu, Ding; Yu, Donglan; Zheng, Zhensheng; Wang, Kuijian

2011-12-01

Enhanced extracorporeal counterpulsation (EECP) information consists of both text and hemodynamic waveform data. At present EECP text information has been successfully managed through Web browser, while the management and sharing of hemodynamic waveform data through Internet has not been solved yet. In order to manage EECP information completely, based on the in-depth analysis of EECP hemodynamic waveform file of digital imaging and communications in medicine (DICOM) format and its disadvantages in Internet sharing, we proposed the use of the extensible markup language (XML), which is currently the Internet popular data exchange standard, as the storage specification for the sharing of EECP waveform data. Then we designed a web-based sharing system of EECP hemodynamic waveform data via ASP. NET 2.0 platform. Meanwhile, we specifically introduced the four main system function modules and their implement methods, including DICOM to XML conversion module, EECP waveform data management module, retrieval and display of EECP waveform module and the security mechanism of the system.

Ultrasound tomography imaging with waveform sound speed: parenchymal changes in women undergoing tamoxifen therapy

NASA Astrophysics Data System (ADS)

Sak, Mark; Duric, Neb; Littrup, Peter; Sherman, Mark; Gierach, Gretchen

2017-03-01

Ultrasound tomography (UST) is an emerging modality that can offer quantitative measurements of breast density. Recent breakthroughs in UST image reconstruction involve the use of a waveform reconstruction as opposed to a raybased reconstruction. The sound speed (SS) images that are created using the waveform reconstruction have a much higher image quality. These waveform images offer improved resolution and contrasts between regions of dense and fatty tissues. As part of a study that was designed to assess breast density changes using UST sound speed imaging among women undergoing tamoxifen therapy, UST waveform sound speed images were then reconstructed for a subset of participants. These initial results show that changes to the parenchymal tissue can more clearly be visualized when using the waveform sound speed images. Additional quantitative testing of the waveform images was also started to test the hypothesis that waveform sound speed images are a more robust measure of breast density than ray-based reconstructions. Further analysis is still needed to better understand how tamoxifen affects breast tissue.

Rapidly reconfigurable high-fidelity optical arbitrary waveform generation in heterogeneous photonic integrated circuits.

PubMed

Feng, Shaoqi; Qin, Chuan; Shang, Kuanping; Pathak, Shibnath; Lai, Weicheng; Guan, Binbin; Clements, Matthew; Su, Tiehui; Liu, Guangyao; Lu, Hongbo; Scott, Ryan P; Ben Yoo, S J

2017-04-17

This paper demonstrates rapidly reconfigurable, high-fidelity optical arbitrary waveform generation (OAWG) in a heterogeneous photonic integrated circuit (PIC). The heterogeneous PIC combines advantages of high-speed indium phosphide (InP) modulators and low-loss, high-contrast silicon nitride (Si₃N₄) arrayed waveguide gratings (AWGs) so that high-fidelity optical waveform syntheses with rapid waveform updates are possible. The generated optical waveforms spanned a 160 GHz spectral bandwidth starting from an optical frequency comb consisting of eight comb lines separated by 20 GHz channel spacing. The Error Vector Magnitude (EVM) values of the generated waveforms were approximately 16.4%. The OAWG module can rapidly and arbitrarily reconfigure waveforms upon every pulse arriving at 2 ns repetition time. The result of this work indicates the feasibility of truly dynamic optical arbitrary waveform generation where the reconfiguration rate or the modulator bandwidth must exceed the channel spacing of the AWG and the optical frequency comb.

Brachial artery vasomotion and transducer pressure effect on measurements by active contour segmentation on ultrasound

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

Cary, Theodore W.; Sultan, Laith R.; Sehgal, Chandra M., E-mail: sehgalc@uphs.upenn.edu

Purpose: To use feed-forward active contours (snakes) to track and measure brachial artery vasomotion on ultrasound images recorded in both transverse and longitudinal views; and to compare the algorithm's performance in each view. Methods: Longitudinal and transverse view ultrasound image sequences of 45 brachial arteries were segmented by feed-forward active contour (FFAC). The segmented regions were used to measure vasomotion artery diameter, cross-sectional area, and distention both as peak-to-peak diameter and as area. ECG waveforms were also simultaneously extracted frame-by-frame by thresholding a running finite-difference image between consecutive images. The arterial and ECG waveforms were compared as they traced eachmore » phase of the cardiac cycle. Results: FFAC successfully segmented arteries in longitudinal and transverse views in all 45 cases. The automated analysis took significantly less time than manual tracing, but produced superior, well-behaved arterial waveforms. Automated arterial measurements also had lower interobserver variability as measured by correlation, difference in mean values, and coefficient of variation. Although FFAC successfully segmented both the longitudinal and transverse images, transverse measurements were less variable. The cross-sectional area computed from the longitudinal images was 27% lower than the area measured from transverse images, possibly due to the compression of the artery along the image depth by transducer pressure. Conclusions: FFAC is a robust and sensitive vasomotion segmentation algorithm in both transverse and longitudinal views. Transverse imaging may offer advantages over longitudinal imaging: transverse measurements are more consistent, possibly because the method is less sensitive to variations in transducer pressure during imaging.« less

Optimizing Waveform Maximum Determination for Specular Point Tracking in Airborne GNSS-R.

PubMed

Motte, Erwan; Zribi, Mehrez

2017-08-16

Airborne GNSS-R campaigns are crucial to the understanding of signal interactions with the Earth's surface. As a consequence of the specific geometric configurations arising during measurements from aircraft, the reflected signals can be difficult to interpret under certain conditions like over strongly attenuating media such as forests, or when the reflected signal is contaminated by the direct signal. For these reasons, there are many cases where the reflectivity is overestimated, or a portion of the dataset has to be flagged as unusable. In this study we present techniques that have been developed to optimize the processing of airborne GNSS-R data, with the goal of improving its accuracy and robustness under non-optimal conditions. This approach is based on the detailed analysis of data produced by the instrument GLORI, which was recorded during an airborne campaign in the south west of France in June 2015. Our technique relies on the improved determination of reflected waveform peaks in the delay dimension, which is related to the loci of the signals contributed by the zone surrounding the specular point. It is shown that when developing techniques for the correct localization of waveform maxima under conditions of surfaces of low reflectivity, and/or contamination from the direct signal, it is possible to correct and extract values corresponding to the real reflectivity of the zone in the neighborhood of the specular point. This algorithm was applied to a reanalysis of the complete campaign dataset, following which the accuracy and sensitivity improved, and the usability of the dataset was improved by 30%.

Brachial artery vasomotion and transducer pressure effect on measurements by active contour segmentation on ultrasound.

PubMed

Cary, Theodore W; Reamer, Courtney B; Sultan, Laith R; Mohler, Emile R; Sehgal, Chandra M

2014-02-01

To use feed-forward active contours (snakes) to track and measure brachial artery vasomotion on ultrasound images recorded in both transverse and longitudinal views; and to compare the algorithm's performance in each view. Longitudinal and transverse view ultrasound image sequences of 45 brachial arteries were segmented by feed-forward active contour (FFAC). The segmented regions were used to measure vasomotion artery diameter, cross-sectional area, and distention both as peak-to-peak diameter and as area. ECG waveforms were also simultaneously extracted frame-by-frame by thresholding a running finite-difference image between consecutive images. The arterial and ECG waveforms were compared as they traced each phase of the cardiac cycle. FFAC successfully segmented arteries in longitudinal and transverse views in all 45 cases. The automated analysis took significantly less time than manual tracing, but produced superior, well-behaved arterial waveforms. Automated arterial measurements also had lower interobserver variability as measured by correlation, difference in mean values, and coefficient of variation. Although FFAC successfully segmented both the longitudinal and transverse images, transverse measurements were less variable. The cross-sectional area computed from the longitudinal images was 27% lower than the area measured from transverse images, possibly due to the compression of the artery along the image depth by transducer pressure. FFAC is a robust and sensitive vasomotion segmentation algorithm in both transverse and longitudinal views. Transverse imaging may offer advantages over longitudinal imaging: transverse measurements are more consistent, possibly because the method is less sensitive to variations in transducer pressure during imaging.

Preliminary Results of the Full-waveform Tomography of South America and Surrounding Oceans using Spectral Elements and Adjoint Methods

NASA Astrophysics Data System (ADS)

Ciardelli, C.; Assumpcao, M.

2017-12-01

In the last years, the ray coverage in the South American continent has greatly improved thanks to the increasing number of seismographic stations. A major contribution came from the recently installed Brazilian Seismographic Network.On the other hand, more advanced tomographic methods like full-waveform tomography have been developed and are gradually becoming more extensively used due to the exponential growth in computers processing power, allowing for more and more information to be extracted from the seismograms. In this work, we are using all the available seismographic data acquired in the period of 2011 to 2016 for the South American and surrounding oceans region, including the new data provided by the recently deployed stations to perform a full-waveform tomography in the area. Our goal is that this new velocity model will provide a more accurate and detailed picture of the mantle structures beneath the region, better constraining our geodynamical interpretations. A total of 161 earthquakes with magnitudes in the range of 6.0-7.0 Mw were found in the Centroid Moment Tensor solutions from the global catalog (Dziewonski, Chou and Woodhouse, 1981; Ekström, Nettles and Dziewonski, 2012). The CMTs were used to model the earthquakes propagation using SPECFEM3D Global software (Komatitsch and Tromp, 2000) with S362wmani, a global S wave velocity model developed by Kustowski et al. (2006) as starting model and 96 events were chosen to be used in the tomography, based on their better initial misfits and ray coverage. Results of the first iterations will be presented.

Brachial artery vasomotion and transducer pressure effect on measurements by active contour segmentation on ultrasound

PubMed Central

Cary, Theodore W.; Reamer, Courtney B.; Sultan, Laith R.; Mohler, Emile R.; Sehgal, Chandra M.

2014-01-01

Purpose: To use feed-forward active contours (snakes) to track and measure brachial artery vasomotion on ultrasound images recorded in both transverse and longitudinal views; and to compare the algorithm's performance in each view. Methods: Longitudinal and transverse view ultrasound image sequences of 45 brachial arteries were segmented by feed-forward active contour (FFAC). The segmented regions were used to measure vasomotion artery diameter, cross-sectional area, and distention both as peak-to-peak diameter and as area. ECG waveforms were also simultaneously extracted frame-by-frame by thresholding a running finite-difference image between consecutive images. The arterial and ECG waveforms were compared as they traced each phase of the cardiac cycle. Results: FFAC successfully segmented arteries in longitudinal and transverse views in all 45 cases. The automated analysis took significantly less time than manual tracing, but produced superior, well-behaved arterial waveforms. Automated arterial measurements also had lower interobserver variability as measured by correlation, difference in mean values, and coefficient of variation. Although FFAC successfully segmented both the longitudinal and transverse images, transverse measurements were less variable. The cross-sectional area computed from the longitudinal images was 27% lower than the area measured from transverse images, possibly due to the compression of the artery along the image depth by transducer pressure. Conclusions: FFAC is a robust and sensitive vasomotion segmentation algorithm in both transverse and longitudinal views. Transverse imaging may offer advantages over longitudinal imaging: transverse measurements are more consistent, possibly because the method is less sensitive to variations in transducer pressure during imaging. PMID:24506648

Signal Waveform Detection with Statistical Automaton for Internet and Web Service Streaming

PubMed Central

Liu, Yiming; Huang, Nai-Lun; Zeng, Fufu; Lin, Fang-Ying

2014-01-01

In recent years, many approaches have been suggested for Internet and web streaming detection. In this paper, we propose an approach to signal waveform detection for Internet and web streaming, with novel statistical automatons. The system records network connections over a period of time to form a signal waveform and compute suspicious characteristics of the waveform. Network streaming according to these selected waveform features by our newly designed Aho-Corasick (AC) automatons can be classified. We developed two versions, that is, basic AC and advanced AC-histogram waveform automata, and conducted comprehensive experimentation. The results confirm that our approach is feasible and suitable for deployment. PMID:25032231

Motor control for a brushless DC motor

NASA Technical Reports Server (NTRS)

Peterson, William J. (Inventor); Faulkner, Dennis T. (Inventor)

1985-01-01

This invention relates to a motor control system for a brushless DC motor having an inverter responsively coupled to the motor control system and in power transmitting relationship to the motor. The motor control system includes a motor rotor speed detecting unit that provides a pulsed waveform signal proportional to rotor speed. This pulsed waveform signal is delivered to the inverter to thereby cause an inverter fundamental current waveform output to the motor to be switched at a rate proportional to said rotor speed. In addition, the fundamental current waveform is also pulse width modulated at a rate proportional to the rotor speed. A fundamental current waveform phase advance circuit is controllingly coupled to the inverter. The phase advance circuit is coupled to receive the pulsed waveform signal from the motor rotor speed detecting unit and phase advance the pulsed waveform signal as a predetermined function of motor speed to thereby cause the fundamental current waveform to be advanced and thereby compensate for fundamental current waveform lag due to motor winding reactance which allows the motor to operate at higher speeds than the motor is rated while providing optimal torque and therefore increased efficiency.

A method of ECG template extraction for biometrics applications.

PubMed

Zhou, Xiang; Lu, Yang; Chen, Meng; Bao, Shu-Di; Miao, Fen

2014-01-01

ECG has attracted widespread attention as one of the most important non-invasive physiological signals in healthcare-system related biometrics for its characteristics like ease-of-monitoring, individual uniqueness as well as important clinical value. This study proposes a method of dynamic threshold setting to extract the most stable ECG waveform as the template for the consequent ECG identification process. With the proposed method, the accuracy of ECG biometrics using the dynamic time wraping for difference measures has been significantly improved. Analysis results with the self-built electrocardiogram database show that the deployment of the proposed method was able to reduce the half total error rate of the ECG biometric system from 3.35% to 1.45%. Its average running time on the platform of android mobile terminal was around 0.06 seconds, and thus demonstrates acceptable real-time performance.

Insights into Fourier Synthesis and Analysis: Part 2--A Simplified Mathematics.

ERIC Educational Resources Information Center

Moore, Guy S. M.

1988-01-01

Introduced is an analysis of a waveform into its Fourier components. Topics included are simplified analysis of a square waveform, a triangular waveform, half-wave rectified alternating current (AC), and impulses. Provides the mathematical expression and simplified analysis diagram of each waveform. (YP)

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

PubMed

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

2014-01-01

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

CD-SEM real time bias correction using reference metrology based modeling

NASA Astrophysics Data System (ADS)

Ukraintsev, V.; Banke, W.; Zagorodnev, G.; Archie, C.; Rana, N.; Pavlovsky, V.; Smirnov, V.; Briginas, I.; Katnani, A.; Vaid, A.

2018-03-01

Accuracy of patterning impacts yield, IC performance and technology time to market. Accuracy of patterning relies on optical proximity correction (OPC) models built using CD-SEM inputs and intra die critical dimension (CD) control based on CD-SEM. Sub-nanometer measurement uncertainty (MU) of CD-SEM is required for current technologies. Reported design and process related bias variation of CD-SEM is in the range of several nanometers. Reference metrology and numerical modeling are used to correct SEM. Both methods are slow to be used for real time bias correction. We report on real time CD-SEM bias correction using empirical models based on reference metrology (RM) data. Significant amount of currently untapped information (sidewall angle, corner rounding, etc.) is obtainable from SEM waveforms. Using additional RM information provided for specific technology (design rules, materials, processes) CD extraction algorithms can be pre-built and then used in real time for accurate CD extraction from regular CD-SEM images. The art and challenge of SEM modeling is in finding robust correlation between SEM waveform features and bias of CD-SEM as well as in minimizing RM inputs needed to create accurate (within the design and process space) model. The new approach was applied to improve CD-SEM accuracy of 45 nm GATE and 32 nm MET1 OPC 1D models. In both cases MU of the state of the art CD-SEM has been improved by 3x and reduced to a nanometer level. Similar approach can be applied to 2D (end of line, contours, etc.) and 3D (sidewall angle, corner rounding, etc.) cases.

Investigation of Doppler Effects on the Detection of Polyphase Coded Radar Waveforms

DTIC Science & Technology

2003-02-01

wave2 = amp * sin(2*pi*two+(2*pi/7)); %the second modulated waveform %wave = [wavec wave1 wave2 wavec]; %the wave form put togther wave = amp...waveform wave1 = sin(2*pi*two+(pi/2)); %the first modulated waveform wave2 = sin(2*pi*two+(2*pi/7)); %the second modulated waveform...wave = [wavec wave1 wave2 wavec]; %the wave form put togther normval = max(abs(xcorr(wave,wave))); N=length

Super-resolution processing for multi-functional LPI waveforms

NASA Astrophysics Data System (ADS)

Li, Zhengzheng; Zhang, Yan; Wang, Shang; Cai, Jingxiao

2014-05-01

Super-resolution (SR) is a radar processing technique closely related to the pulse compression (or correlation receiver). There are many super-resolution algorithms developed for the improved range resolution and reduced sidelobe contaminations. Traditionally, the waveforms used for the SR have been either phase-coding (such as LKP3 code, Barker code) or the frequency modulation (chirp, or nonlinear frequency modulation). There are, however, an important class of waveforms which are either random in nature (such as random noise waveform), or randomly modulated for multiple function operations (such as the ADS-B radar signals in [1]). These waveforms have the advantages of low-probability-of-intercept (LPI). If the existing SR techniques can be applied to these waveforms, there will be much more flexibility for using these waveforms in actual sensing missions. Also, SR usually has great advantage that the final output (as estimation of ground truth) is largely independent of the waveform. Such benefits are attractive to many important primary radar applications. In this paper the general introduction of the SR algorithms are provided first, and some implementation considerations are discussed. The selected algorithms are applied to the typical LPI waveforms, and the results are discussed. It is observed that SR algorithms can be reliably used for LPI waveforms, on the other hand, practical considerations should be kept in mind in order to obtain the optimal estimation results.

Tone signal generator for producing multioperator tone signals using an operator circuit including a waveform generator, a selector and an enveloper

DOEpatents

Dong, Qiujie; Jenkins, Michael V.; Bernadas, Salvador R.

1997-01-01

A frequency modulation (FM) tone signal generator for generating a FM tone signal is disclosed. The tone signal generator includes a waveform generator having a plurality of wave tables, a selector and an enveloper. The waveform generator furnishes a waveform signal in response to a phase angle address signal. Each wave table stores a different waveform. The selector selects one of the wave tables in response to a plurality of selection signals such that the selected wave table largely provides the waveform signal upon being addressed largely by the phase angle address signal. Selection of the selected wave table varies with each selection signal. The enveloper impresses an envelope signal on the waveform signal. The envelope signal is used as a carrier or modulator for generating the FM tone signal.

Lightning-channel morphology by return-stroke radiation field waveforms

NASA Technical Reports Server (NTRS)

Willett, J. C.; Le Vine, D. M.; Idone, V. P.

1995-01-01

Simultaneous video and wideband electric field recordings of 32 cloud-to-ground lightning flashes in Florida were analyzed to show the formation of new channels to ground can be detected by examination of the return-stroke radiation fields alone. The return-stroke E and dE/dt waveforms were subjectively classified according to their fine structure. Then the video images were examined field by field to identify each waveform with a visible channel to ground. Fifty-five correlated waveforms and channel images were obtained. Of these, all 34 first-stroke waveforms (multiple jagged E peaks, noisy dE/dt), 8 of which were not radiated by the chronologically first stroke in the flash, came from new channels to ground (not previously seen on video). All 18 subsequent-stroke waveforms (smoothly rounded E and quiet dE/dt after initial peak) were radiated by old channels (illuminated by a previous stroke). Two double-ground waveforms (two distinct first-return-stroke pulses separated by tens of microseconds or less) coincided with video fields showing two new channels. One `anomalous-stroke' waveform (beginning like a first stroke and ending like a subsequent) was produced by a new channel segment to ground branching off an old channel. This waveform classification depends on the presence or absence of high-frequency fine structure. Fourier analysis shows that first-stroke waveforms contain about 18 dB more spectral power in the frequency interval from 500 kHz to at least 7 MHz than subsequent-stroke waveforms for at least 13 microseconds after the main peak.

A spatio-temporal index for aerial full waveform laser scanning data

NASA Astrophysics Data System (ADS)

Laefer, Debra F.; Vo, Anh-Vu; Bertolotto, Michela

2018-04-01

Aerial laser scanning is increasingly available in the full waveform version of the raw signal, which can provide greater insight into and control over the data and, thus, richer information about the scanned scenes. However, when compared to conventional discrete point storage, preserving raw waveforms leads to vastly larger and more complex data volumes. To begin addressing these challenges, this paper introduces a novel bi-level approach for storing and indexing full waveform (FWF) laser scanning data in a relational database environment, while considering both the spatial and the temporal dimensions of that data. In the storage scheme's upper level, the full waveform datasets are partitioned into spatial and temporal coherent groups that are indexed by a two-dimensional R∗-tree. To further accelerate intra-block data retrieval, at the lower level a three-dimensional local octree is created for each pulse block. The local octrees are implemented in-memory and can be efficiently written to a database for reuse. The indexing solution enables scalable and efficient three-dimensional (3D) spatial and spatio-temporal queries on the actual pulse data - functionalities not available in other systems. The proposed FWF laser scanning data solution is capable of managing multiple FWF datasets derived from large flight missions. The flight structure is embedded into the data storage model and can be used for querying predicates. Such functionality is important to FWF data exploration since aircraft locations and orientations are frequently required for FWF data analyses. Empirical tests on real datasets of up to 1 billion pulses from Dublin, Ireland prove the almost perfect scalability of the system. The use of the local 3D octree in the indexing structure accelerated pulse clipping by 1.2-3.5 times for non-axis-aligned (NAA) polyhedron shaped clipping windows, while axis-aligned (AA) polyhedron clipping was better served using only the top indexing layer. The distinct behaviours of the hybrid indexing for AA and NAA clipping windows are attributable to the different proportion of the local-index-related overheads with respect to the total querying costs. When temporal constraints were added, generally the number of costly spatial checks were reduced, thereby shortening the querying times.

Non-linear 3-D Born shear waveform tomography in Southeast Asia

NASA Astrophysics Data System (ADS)

Panning, Mark P.; Cao, Aimin; Kim, Ahyi; Romanowicz, Barbara A.

2012-07-01

Southeast (SE) Asia is a tectonically complex region surrounded by many active source regions, thus an ideal test bed for developments in seismic tomography. Much recent development in tomography has been based on 3-D sensitivity kernels based on the first-order Born approximation, but there are potential problems with this approach when applied to waveform data. In this study, we develop a radially anisotropic model of SE Asia using long-period multimode waveforms. We use a theoretical 'cascade' approach, starting with a large-scale Eurasian model developed using 2-D Non-linear Asymptotic Coupling Theory (NACT) sensitivity kernels, and then using a modified Born approximation (nBorn), shown to be more accurate at modelling waveforms, to invert a subset of the data for structure in a subregion (longitude 75°-150° and latitude 0°-45°). In this subregion, the model is parametrized at a spherical spline level 6 (˜200 km). The data set is also inverted using NACT and purely linear 3-D Born kernels. All three final models fit the data well, with just under 80 per cent variance reduction as calculated using the corresponding theory, but the nBorn model shows more detailed structure than the NACT model throughout and has much better resolution at depths greater than 250 km. Based on variance analysis, the purely linear Born kernels do not provide as good a fit to the data due to deviations from linearity for the waveform data set used in this modelling. The nBorn isotropic model shows a stronger fast velocity anomaly beneath the Tibetan Plateau in the depth range of 150-250 km, which disappears at greater depth, consistent with other studies. It also indicates moderate thinning of the high-velocity plate in the middle of Tibet, consistent with a model where Tibet is underplated by Indian lithosphere from the south and Eurasian lithosphere from the north, in contrast to a model with continuous underplating by Indian lithosphere across the entire plateau. The nBorn anisotropic model detects negative ξ anomalies suggestive of vertical deformation associated with subducted slabs and convergent zones at the Himalayan front and Tien Shan at depths near 150 km.

Geophysical characterization of peatlands using crosshole GPR full-waveform inversion: Case study from a bog in northwestern Germany

NASA Astrophysics Data System (ADS)

Schmäck, J.; Klotzsche, A.; Van Der Kruk, J.; Vereecken, H.; Bechtold, M.

2017-12-01

The characterization of peatlands is of particular interest, since areas with peat soils represent global hotspots for the exchange of greenhouse gases. Their effect on global warming depends on several parameters, like mean annual water level and land use. Models of greenhouse gas emissions and carbon accumulation in peatlands can be improved by including small-scale soil properties that e.g. act as gas traps and periodically release gases to the atmosphere during ebullition events. Ground penetrating radar (GPR) is well suited to non- or minimal invasively characterize and improve our understanding of dynamic processes that take place in the critical zone. It uses high frequency electromagnetic waves to image and characterize the dielectric permittivity and electrical conductivity of the critical zone, which can be related to hydrogeological properties like porosity, soil water content, salinity and clay content. In the last decade, the full-waveform inversion of crosshole GPR data has proved to be a powerful tool to improve the image resolution compared to standard ray-based methods. This approach was successfully applied to several different aquifers and was able to provide decimeter-scale resolution images including small-scale high contrast layers that can be related to zones of high porosity, zones of preferential flow or clay lenses. The comparison to independently measured e.g. logging data proved the reliability of the method. Here, for the first time crosshole GPR full-waveform inversion is used to image three peatland plots with different land use that are part of the "Ahlen-Falkenberger Moor peat bog complex" in northwestern Germany. The full-waveform inversion of the acquired data returned higher resolution images than standard ray-based GPR methods, and, is able to improve our understanding of subsurface structures. The comparison of the different plots is expected to provide new insights into gas content and gas trapping structures across different land uses. Additionally, season-related changes of peatland soil properties are investigated. The crosshole GPR full-waveform inversion was successfully applied to several datasets and the results show the utility and credibility of GPR FWI to analyze peatland properties.

SAMPLING OSCILLOSCOPE

DOEpatents

Sugarman, R.M.

1960-08-30

An oscilloscope is designed for displaying transient signal waveforms having random time and amplitude distributions. The oscilloscopc is a sampling device that selects for display a portion of only those waveforms having a particular range of amplitudes. For this purpose a pulse-height analyzer is provided to screen the pulses. A variable voltage-level shifter and a time-scale rampvoltage generator take the pulse height relative to the start of the waveform. The variable voltage shifter produces a voltage level raised one step for each sequential signal waveform to be sampled and this results in an unsmeared record of input signal waveforms. Appropriate delay devices permit each sample waveform to pass its peak amplitude before the circuit selects it for display.

Noncoherent detection of periodic signals

NASA Technical Reports Server (NTRS)

Gagliardi, R. M.

1974-01-01

The optimal Bayes detector for a general periodic waveform having uniform delay and additive white Gaussian noise is examined. It is shown that the detector is much more complex than that for the well known cases of pure sine waves (i.e. classical noncoherent detection) and narrowband signals. An interpretation of the optimal processing is presented, and several implementations are discussed. The results have application to the noncoherent detection of optical square waves.

On Algorithms for Generating Computationally Simple Piecewise Linear Classifiers

DTIC Science & Technology

1989-05-01

suffers. - Waveform classification, e.g. speech recognition, seismic analysis (i.e. discrimination between earthquakes and nuclear explosions), target...assuming Gaussian distributions (B-G) d) Bayes classifier with probability densities estimated with the k-N-N method (B- kNN ) e) The -arest neighbour...range of classifiers are chosen including a fast, easy computable and often used classifier (B-G), reliable and complex classifiers (B- kNN and NNR

Moment tensor solutions estimated using optimal filter theory for 51 selected earthquakes, 1980-1984

USGS Publications Warehouse

Sipkin, S.A.

1987-01-01

The 51 global events that occurred from January 1980 to March 1984, which were chosen by the convenors of the Symposium on Seismological Theory and Practice, have been analyzed using a moment tensor inversion algorithm (Sipkin). Many of the events were routinely analyzed as part of the National Earthquake Information Center's (NEIC) efforts to publish moment tensor and first-motion fault-plane solutions for all moderate- to large-sized (mb>5.7) earthquakes. In routine use only long-period P-waves are used and the source-time function is constrained to be a step-function at the source (??-function in the far-field). Four of the events were of special interest, and long-period P, SH-wave solutions were obtained. For three of these events, an unconstrained inversion was performed. The resulting time-dependent solutions indicated that, for many cases, departures of the solutions from pure double-couples are caused by source complexity that has not been adequately modeled. These solutions also indicate that source complexity of moderate-sized events can be determined from long-period data. Finally, for one of the events of special interest, an inversion of the broadband P-waveforms was also performed, demonstrating the potential for using broadband waveform data in inversion procedures. ?? 1987.

The effect of buildings on acoustic pulse propagation in an urban environment.

PubMed

Albert, Donald G; Liu, Lanbo

2010-03-01

Experimental measurements were conducted using acoustic pulse sources in a full-scale artificial village to investigate the reverberation, scattering, and diffraction produced as acoustic waves interact with buildings. These measurements show that a simple acoustic source pulse is transformed into a complex signature when propagating through this environment, and that diffraction acts as a low-pass filter on the acoustic pulse. Sensors located in non-line-of-sight (NLOS) positions usually recorded lower positive pressure maxima than sensors in line-of-sight positions. Often, the first arrival on a NLOS sensor located around a corner was not the largest arrival, as later reflection arrivals that traveled longer distances without diffraction had higher amplitudes. The waveforms are of such complexity that human listeners have difficulty identifying replays of the signatures generated by a single pulse, and the usual methods of source location based on the direction of arrivals may fail in many cases. Theoretical calculations were performed using a two-dimensional finite difference time domain (FDTD) method and compared to the measurements. The predicted peak positive pressure agreed well with the measured amplitudes for all but two sensor locations directly behind buildings, where the omission of rooftop ray paths caused the discrepancy. The FDTD method also produced good agreement with many of the measured waveform characteristics.

Design of pulse waveform for waveform division multiple access UWB wireless communication system.

PubMed

Yin, Zhendong; Wang, Zhirui; Liu, Xiaohui; Wu, Zhilu

2014-01-01

A new multiple access scheme, Waveform Division Multiple Access (WDMA) based on the orthogonal wavelet function, is presented. After studying the correlation properties of different categories of single wavelet functions, the one with the best correlation property will be chosen as the foundation for combined waveform. In the communication system, each user is assigned to different combined orthogonal waveform. Demonstrated by simulation, combined waveform is more suitable than single wavelet function to be a communication medium in WDMA system. Due to the excellent orthogonality, the bit error rate (BER) of multiuser with combined waveforms is so close to that of single user in a synchronous system. That is to say, the multiple access interference (MAI) is almost eliminated. Furthermore, even in an asynchronous system without multiuser detection after matched filters, the result is still pretty ideal and satisfactory by using the third combination mode that will be mentioned in the study.

Tone signal generator for producing multioperator tone signals using an operator circuit including a waveform generator, a selector and an enveloper

DOEpatents

Dong, Q.; Jenkins, M.V.; Bernadas, S.R.

1997-09-09

A frequency modulation (FM) tone signal generator for generating a FM tone signal is disclosed. The tone signal generator includes a waveform generator having a plurality of wave tables, a selector and an enveloper. The waveform generator furnishes a waveform signal in response to a phase angle address signal. Each wave table stores a different waveform. The selector selects one of the wave tables in response to a plurality of selection signals such that the selected wave table largely provides the waveform signal upon being addressed largely by the phase angle address signal. Selection of the selected wave table varies with each selection signal. The enveloper impresses an envelope signal on the waveform signal. The envelope signal is used as a carrier or modulator for generating the FM tone signal. 17 figs.

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

Smallwood, D.O.

It is recognized that some dynamic and noise environments are characterized by time histories which are not Gaussian. An example is high intensity acoustic noise. Another example is some transportation vibration. A better simulation of these environments can be generated if a zero mean non-Gaussian time history can be reproduced with a specified auto (or power) spectral density (ASD or PSD) and a specified probability density function (pdf). After the required time history is synthesized, the waveform can be used for simulation purposes. For example, modem waveform reproduction techniques can be used to reproduce the waveform on electrodynamic or electrohydraulicmore » shakers. Or the waveforms can be used in digital simulations. A method is presented for the generation of realizations of zero mean non-Gaussian random time histories with a specified ASD, and pdf. First a Gaussian time history with the specified auto (or power) spectral density (ASD) is generated. A monotonic nonlinear function relating the Gaussian waveform to the desired realization is then established based on the Cumulative Distribution Function (CDF) of the desired waveform and the known CDF of a Gaussian waveform. The established function is used to transform the Gaussian waveform to a realization of the desired waveform. Since the transformation preserves the zero-crossings and peaks of the original Gaussian waveform, and does not introduce any substantial discontinuities, the ASD is not substantially changed. Several methods are available to generate a realization of a Gaussian distributed waveform with a known ASD. The method of Smallwood and Paez (1993) is an example. However, the generation of random noise with a specified ASD but with a non-Gaussian distribution is less well known.« less

Coastal retracking using along-track echograms and its dependency on coastal topography

NASA Astrophysics Data System (ADS)

Ichikawa, K.; Wang, X.

2017-12-01

Although the Brown mathematical model is the standard model for waveform retracking over open oceans, coastal waveforms usually deviate from open ocean waveform shapes due to inhomogeneous surface reflections within altimeter footprints, and thus cannot be directly interpreted by the Brown model. Generally, the two primary sources of heterogeneous surface reflections are land surfaces and bright targets such as calm surface water. The former reduces echo power, while the latter often produces particularly strong echoes. In previous studies, sub-waveform retrackers, which use waveform samples collected from around leading edges in order to avoid trailing edge noise, have been recommended for coastal waveform retracking. In the present study, the peaky-type noise caused by fixed-point bright targets is explicitly detected and masked using the parabolic signature in the sequential along-track waveforms (or, azimuth-range echograms). Moreover, the power deficit of waveform trailing edges caused by weak land reflections is compensated for by estimating the ratio of sea surface area within each annular footprint in order to produce pseudo-homogeneous reflected waveforms suitable for the Brown model. Using this method, Jason-2 altimeter waveforms are retracked in several coastal areas. Our results show that both the correlation coefficient and root mean square difference between the derived sea surface height anomalies and tide gauge records retain similar values at the open ocean (0.9 and 20 cm) level, even in areas approaching 3 km from coastlines, which is considerably improved from the 10 km correlation coefficient limit of the conventional MLE4 retracker and the 7 km sub-waveform ALES retracker limit. These values, however, depend on the coastal topography of the study areas because the approach distance limit increases (decreases) in areas with complicated (straight) coastlines

Fast Prediction and Evaluation of Gravitational Waveforms Using Surrogate Models

NASA Astrophysics Data System (ADS)

Field, Scott E.; Galley, Chad R.; Hesthaven, Jan S.; Kaye, Jason; Tiglio, Manuel

2014-07-01

We propose a solution to the problem of quickly and accurately predicting gravitational waveforms within any given physical model. The method is relevant for both real-time applications and more traditional scenarios where the generation of waveforms using standard methods can be prohibitively expensive. Our approach is based on three offline steps resulting in an accurate reduced order model in both parameter and physical dimensions that can be used as a surrogate for the true or fiducial waveform family. First, a set of m parameter values is determined using a greedy algorithm from which a reduced basis representation is constructed. Second, these m parameters induce the selection of m time values for interpolating a waveform time series using an empirical interpolant that is built for the fiducial waveform family. Third, a fit in the parameter dimension is performed for the waveform's value at each of these m times. The cost of predicting L waveform time samples for a generic parameter choice is of order O(mL+mcfit) online operations, where cfit denotes the fitting function operation count and, typically, m ≪L. The result is a compact, computationally efficient, and accurate surrogate model that retains the original physics of the fiducial waveform family while also being fast to evaluate. We generate accurate surrogate models for effective-one-body waveforms of nonspinning binary black hole coalescences with durations as long as 105M, mass ratios from 1 to 10, and for multiple spherical harmonic modes. We find that these surrogates are more than 3 orders of magnitude faster to evaluate as compared to the cost of generating effective-one-body waveforms in standard ways. Surrogate model building for other waveform families and models follows the same steps and has the same low computational online scaling cost. For expensive numerical simulations of binary black hole coalescences, we thus anticipate extremely large speedups in generating new waveforms with a surrogate. As waveform generation is one of the dominant costs in parameter estimation algorithms and parameter space exploration, surrogate models offer a new and practical way to dramatically accelerate such studies without impacting accuracy. Surrogates built in this paper, as well as others, are available from GWSurrogate, a publicly available python package.

Source rupture process of the 2016 Kaikoura, New Zealand earthquake estimated from the kinematic waveform inversion of strong-motion data

NASA Astrophysics Data System (ADS)

Zheng, Ao; Wang, Mingfeng; Yu, Xiangwei; Zhang, Wenbo

2018-03-01

On 2016 November 13, an Mw 7.8 earthquake occurred in the northeast of the South Island of New Zealand near Kaikoura. The earthquake caused severe damages and great impacts on local nature and society. Referring to the tectonic environment and defined active faults, the field investigation and geodetic evidence reveal that at least 12 fault sections ruptured in the earthquake, and the focal mechanism is one of the most complicated in historical earthquakes. On account of the complexity of the source rupture, we propose a multisegment fault model based on the distribution of surface ruptures and active tectonics. We derive the source rupture process of the earthquake using the kinematic waveform inversion method with the multisegment fault model from strong-motion data of 21 stations (0.05-0.35 Hz). The inversion result suggests the rupture initiates in the epicentral area near the Humps fault, and then propagates northeastward along several faults, until the offshore Needles fault. The Mw 7.8 event is a mixture of right-lateral strike and reverse slip, and the maximum slip is approximately 19 m. The synthetic waveforms reproduce the characteristics of the observed ones well. In addition, we synthesize the coseismic offsets distribution of the ruptured region from the slips of upper subfaults in the fault model, which is roughly consistent with the surface breaks observed in the field survey.

Waveform Developer's Guide for the Integrated Power, Avionics, and Software (iPAS) Space Telecommunications Radio System (STRS) Radio

NASA Technical Reports Server (NTRS)

Shalkhauser, Mary Jo W.; Roche, Rigoberto

2017-01-01

The Space Telecommunications Radio System (STRS) provides a common, consistent framework for software defined radios (SDRs) to abstract the application software from the radio platform hardware. The STRS standard aims to reduce the cost and risk of using complex, configurable and reprogrammable radio systems across NASA missions. To promote the use of the STRS architecture for future NASA advanced exploration missions, NASA Glenn Research Center (GRC) developed an STRS-compliant SDR on a radio platform used by the Advance Exploration System program at the Johnson Space Center (JSC) in their Integrated Power, Avionics, and Software (iPAS) laboratory. The iPAS STRS Radio was implemented on the Reconfigurable, Intelligently-Adaptive Communication System (RIACS) platform, currently being used for radio development at JSC. The platform consists of a Xilinx(Trademark) ML605 Virtex(Trademark)-6 FPGA board, an Analog Devices FMCOMMS1-EBZ RF transceiver board, and an Embedded PC (Axiomtek(Trademark) eBox 620-110-FL) running the Ubuntu 12.4 operating system. The result of this development is a very low cost STRS compliant platform that can be used for waveform developments for multiple applications. The purpose of this document is to describe how to develop a new waveform using the RIACS platform and the Very High Speed Integrated Circuits (VHSIC) Hardware Description Language (VHDL) FPGA wrapper code and the STRS implementation on the Axiomtek processor.

Blood Pressure Monitoring for the Anesthesiologist: A Practical Review.

PubMed

Bartels, Karsten; Esper, Stephen A; Thiele, Robert H

2016-06-01

Periodic, quantitative measurement of blood pressure (BP) in humans, predating the era of evidence-based medicine by over a century, is a component of the American Society of Anesthesiologists standards for basic anesthetic monitoring and is a staple of anesthetic management worldwide. Adherence to traditional BP parameters complicates the ability of investigators to determine whether particular BP ranges confer any clinical benefits. The BP waveform is a complex amalgamation of both antegrade and retrograde (reflected) pressure waves and is affected by vascular compliance, distance from the left ventricle, and the 3D structure of the vascular tree. Although oscillometry is the standard method of measuring BP semicontinuously in anesthetized patients and is the primary form of measurement in >80% of general anesthetics, major shortcomings of oscillometry are its poor performance at the extremes and its lack of information concerning BP waveform. Although arterial catheterization remains the gold standard for accurate BP measurement, 2 classes of devices have been developed to noninvasively measure the BP waveform continuously, including tonometric and volume clamp devices. Described in terms of a feedback loop, control of BP requires measurement, an algorithm (usually human), and an intervention. This narrative review article discusses the details of BP measurement and the advantages and disadvantages of both noninvasive and invasive monitoring, as well as the principles and algorithms associated with each technique.

Generalized Feature Extraction for Wrist Pulse Analysis: From 1-D Time Series to 2-D Matrix.

PubMed

Dimin Wang; Zhang, David; Guangming Lu

2017-07-01

Traditional Chinese pulse diagnosis, known as an empirical science, depends on the subjective experience. Inconsistent diagnostic results may be obtained among different practitioners. A scientific way of studying the pulse should be to analyze the objectified wrist pulse waveforms. In recent years, many pulse acquisition platforms have been developed with the advances in sensor and computer technology. And the pulse diagnosis using pattern recognition theories is also increasingly attracting attentions. Though many literatures on pulse feature extraction have been published, they just handle the pulse signals as simple 1-D time series and ignore the information within the class. This paper presents a generalized method of pulse feature extraction, extending the feature dimension from 1-D time series to 2-D matrix. The conventional wrist pulse features correspond to a particular case of the generalized models. The proposed method is validated through pattern classification on actual pulse records. Both quantitative and qualitative results relative to the 1-D pulse features are given through diabetes diagnosis. The experimental results show that the generalized 2-D matrix feature is effective in extracting both the periodic and nonperiodic information. And it is practical for wrist pulse analysis.

Agile waveforms for joint SAR-GMTI processing

NASA Astrophysics Data System (ADS)

Jaroszewski, Steven; Corbeil, Allan; McMurray, Stephen; Majumder, Uttam; Bell, Mark R.; Corbeil, Jeffrey; Minardi, Michael

2016-05-01

Wideband radar waveforms that employ spread-spectrum techniques were investigated and experimentally tested. The waveforms combine bi-phase coding with a traditional LFM chirp and are applicable to joint SAR-GMTI processing. After de-spreading, the received signals can be processed to support simultaneous GMTI and high resolution SAR imaging missions by airborne radars. The spread spectrum coding techniques can provide nearly orthogonal waveforms and offer enhanced operations in some environments by distributing the transmitted energy over a large instantaneous bandwidth. The LFM component offers the desired Doppler tolerance. In this paper, the waveforms are formulated and a shift-register approach for de-spreading the received signals is described. Hardware loop-back testing has shown the feasibility of using these waveforms in experimental radar test bed.

Anomalous waveforms observed in laboratory-formed gas hydrate-bearing and ice-bearing sediments

PubMed Central

Lee, Myung W.; Waite, William F.

2011-01-01

Acoustic transmission measurements of compressional, P, and shear, S, wave velocities rely on correctly identifying the P- and S-body wave arrivals in the measured waveform. In cylindrical samples for which the sample is much longer than the acoustic wavelength, these body waves can be obscured by high-amplitude waveform features arriving just after the relatively small-amplitude P-body wave. In this study, a normal mode approach is used to analyze this type of waveform, observed in sediment containing gas hydrate or ice. This analysis extends an existing normal-mode waveform propagation theory by including the effects of the confining medium surrounding the sample, and provides guidelines for estimating S-wave velocities from waveforms containing multiple large-amplitude arrivals. PMID:21476628

Characterizing Tityus discrepans scorpion venom from a fractal perspective: Venom complexity, effects of captivity, sexual dimorphism, differences among species.

PubMed

D'Suze, Gina; Sandoval, Moisés; Sevcik, Carlos

2015-12-15

A characteristic of venom elution patterns, shared with many other complex systems, is that many their features cannot be properly described with statistical or euclidean concepts. The understanding of such systems became possible with Mandelbrot's fractal analysis. Venom elution patterns were produced using the reversed phase high performance liquid chromatography (HPLC) with 1 mg of venom. One reason for the lack of quantitative analyses of the sources of venom variability is parametrizing the venom chromatograms' complexity. We quantize this complexity by means of an algorithm which estimates the contortedness (Q) of a waveform. Fractal analysis was used to compare venoms and to measure inter- and intra-specific venom variability. We studied variations in venom complexity derived from gender, seasonal and environmental factors, duration of captivity in the laboratory, technique used to milk venom. Copyright © 2015 Elsevier Ltd. All rights reserved.

Airborne laser topographic mapping results from initial joint NASA/US Army Corps of Engineers experiment

NASA Technical Reports Server (NTRS)

Krabill, W. B.; Collins, J. G.; Swift, R. N.; Butler, M. L.

1980-01-01

Initial results from a series of joint NASA/US Army Corps of Engineers experiments are presented. The NASA Airborne Oceanographic Lidar (AOL) was exercised over various terrain conditions, collecting both profile and scan data from which river basin cross sections are extracted. Comparisons of the laser data with both photogrammetry and ground surveys are made, with 12 to 27 cm agreement observed over open ground. Foliage penetration tests, utilizing the unique time-waveform sampling capability of the AOL, indicate 50 cm agreement with photogrammetry (known to have difficulty in foliage covered terrain).

The gravitational wave strain in the characteristic formalism of numerical relativity

NASA Astrophysics Data System (ADS)

Bishop, Nigel T.; Reisswig, Christian

2014-01-01

The extraction of the gravitational wave signal, within the context of a characteristic numerical evolution is revisited. A formula for the gravitational wave strain is developed and tested, and is made publicly available as part of the PITT code within the Einstein Toolkit. Using the new strain formula, we show that artificial non-linear drifts inherent in time integrated waveforms can be reduced for the case of a binary black hole merger configuration. For the test case of a rapidly spinning stellar core collapse model, however, we find that the drift must have different roots.

THE SOLVENT EXTRACTION OF NITROSYLRUTHENIUM BY TRILAURYLAMINE IN NITRATE SYSTEM. Summary Report for the Period, July 1, 1960 to March 31, 1962

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

Skavdahl, R.E.; Mason, E.A.

1962-06-01

An investigation of the solvent extraction characteristics of the nitro and nitrato complexes of nitrosylruthenium in nitric acid- sodium nitrate aqueous media was conducted. As the organic extractant phase, a solution of trilaurylamine (TLA) in toluene was utilized. In addition to the usual process parameter variation tyne of experiment, a rapid dilution type of experiment was used extensively to determine qualitative and semiquantitative results regarding the degree of extractability and concentration of the more extractable species of the nitrato complexes of nitrosylruthenium. It was found that the acids of the tetra-nitrato and pentanitrato complexes were the more extractable species formore » that set of complexes and that the acid of the penta-nitrato complex was the more extractable of the two. It was observed that for freshly prepared solutions, the dinitro complex of nitrosylruthenium was much more extractable than the gross nitrato complexes solutions. Nitro complexes in general, and the dinitro complex in particular, may be the controlling agent in ruthenium decontamination of spent nuclear fuel processed by solvent extraction methods. The experimental results from both sets of complexes could be more meaningfully correlated on the basis of unbound nitric acid concentration in the organic phase than on the basis of nitric acid concentration in the aqueous phase. The extraction of nitric acid by TLA from nitric acid-sodium nitrate aqueous solutions was investigated and the results correlated on the basis of activity of the undissociated nitric acid in the aqueous phase. (auth)« less

Salvus: A flexible open-source package for waveform modelling and inversion from laboratory to global scales

NASA Astrophysics Data System (ADS)

Afanasiev, M.; Boehm, C.; van Driel, M.; Krischer, L.; May, D.; Rietmann, M.; Fichtner, A.

2016-12-01

Recent years have been witness to the application of waveform inversion to new and exciting domains, ranging from non-destructive testing to global seismology. Often, each new application brings with it novel wave propagation physics, spatial and temporal discretizations, and models of variable complexity. Adapting existing software to these novel applications often requires a significant investment of time, and acts as a barrier to progress. To combat these problems we introduce Salvus, a software package designed to solve large-scale full-waveform inverse problems, with a focus on both flexibility and performance. Based on a high order finite (spectral) element discretization, we have built Salvus to work on unstructured quad/hex meshes in both 2 or 3 dimensions, with support for P1-P3 bases on triangles and tetrahedra. A diverse (and expanding) collection of wave propagation physics are supported (i.e. coupled solid-fluid). With a focus on the inverse problem, functionality is provided to ease integration with internal and external optimization libraries. Additionally, a python-based meshing package is included to simplify the generation and manipulation of regional to global scale Earth models (quad/hex), with interfaces available to external mesh generators for complex engineering-scale applications (quad/hex/tri/tet). Finally, to ensure that the code remains accurate and maintainable, we build upon software libraries such as PETSc and Eigen, and follow modern software design and testing protocols. Salvus bridges the gap between research and production codes with a design based on C++ mixins and Python wrappers that separates the physical equations from the numerical core. This allows domain scientists to add new equations using a high-level interface, without having to worry about optimized implementation details. Our goal in this presentation is to introduce the code, show several examples across the scales, and discuss some of the extensible design points.

Salvus: A flexible high-performance and open-source package for waveform modelling and inversion from laboratory to global scales

NASA Astrophysics Data System (ADS)

Afanasiev, Michael; Boehm, Christian; van Driel, Martin; Krischer, Lion; May, Dave; Rietmann, Max; Fichtner, Andreas

2017-04-01

Recent years have been witness to the application of waveform inversion to new and exciting domains, ranging from non-destructive testing to global seismology. Often, each new application brings with it novel wave propagation physics, spatial and temporal discretizations, and models of variable complexity. Adapting existing software to these novel applications often requires a significant investment of time, and acts as a barrier to progress. To combat these problems we introduce Salvus, a software package designed to solve large-scale full-waveform inverse problems, with a focus on both flexibility and performance. Currently based on an abstract implementation of high order finite (spectral) elements, we have built Salvus to work on unstructured quad/hex meshes in both 2 or 3 dimensions, with support for P1-P3 bases on triangles and tetrahedra. A diverse (and expanding) collection of wave propagation physics are supported (i.e. viscoelastic, coupled solid-fluid). With a focus on the inverse problem, functionality is provided to ease integration with internal and external optimization libraries. Additionally, a python-based meshing package is included to simplify the generation and manipulation of regional to global scale Earth models (quad/hex), with interfaces available to external mesh generators for complex engineering-scale applications (quad/hex/tri/tet). Finally, to ensure that the code remains accurate and maintainable, we build upon software libraries such as PETSc and Eigen, and follow modern software design and testing protocols. Salvus bridges the gap between research and production codes with a design based on C++ template mixins and Python wrappers that separates the physical equations from the numerical core. This allows domain scientists to add new equations using a high-level interface, without having to worry about optimized implementation details. Our goal in this presentation is to introduce the code, show several examples across the scales, and discuss some of the extensible design points.

Waveform generation in the weakly electric fish Gymnotus coropinae (Hoedeman): the electric organ and the electric organ discharge.

PubMed

Castelló, María E; Rodríguez-Cattáneo, Alejo; Aguilera, Pedro A; Iribarne, Leticia; Pereira, Ana Carolina; Caputi, Angel A

2009-05-01

This article deals with the electric organ and its discharge in Gymnotus coropinae, a representative species of one of the three main clades of the genus. Three regions with bilateral symmetry are described: (1) subopercular (medial and lateral columns of complex shaped electrocytes); (2) abdominal (medial and lateral columns of cuboidal and fusiform electrocytes); and (3) main [four columns, one dorso-lateral (containing fusiform electrocytes) and three medial (containing cuboidal electrocytes)]. Subopercular electrocytes are all caudally innervated whereas two of the medial subopercular ones are also rostrally innervated. Fusiform electrocytes are medially innervated at the abdominal portion, and at their rostral and caudal poles at the main portion. Cuboidal electrocytes are always caudally innervated. The subopercular portion generates a slow head-negative wave (V(1r)) followed by a head-positive spike (V(3r)). The abdominal and main portions generate a fast tetra-phasic complex (V(2345ct)). Since subopercular components prevail in the near field and the rest in the far field, time coincidence of V(3r) with V(2) leads to different waveforms depending on the position of the receiver. This confirms the splitting hypothesis of communication and exploration channels based on the different timing, frequency band and reach of the regional waveforms. The following hypothesis is compatible with the observed anatomo-functional organization: V(1r) corresponds to the rostral activation of medial subopercular electrocytes and V(3r) to the caudal activation of all subopercular electrocytes; V(2), and part of V(3ct), corresponds to the successive activation of the rostral and caudal poles of dorso-lateral fusiform electrocytes; and V(345ct) is initiated in the caudal face of cuboidal electrocytes by synaptic activation (V(3ct)) and it is completed (V(45ct)) by the successive activation of rostral and caudal faces by the action currents evoked in the opposite face.

Doppler waveform study as indicator of change of portal pressure after administration of octreotide

PubMed Central

Haider, Shahbaz; Hussain, Qurban; Tabassum, Sumera; Hussain, Bilal; Durrani, Muhammad Rasheed; Ahmed, Fayyaz

2016-01-01

Objective: To estimate the effect of portal pressure lowering drug ‘octreotide’, by observing the Doppler waveform before and after the administration of intravenous bolus of octreotide and thus to assess indirectly its efficacy to lower the portal pressure. Methods: This quassi experimental study was carried out in Medical Department in collaboration with Radiology Department of Jinnah Postgraduate Medical Center Karachi Pakistan from September 10, 2015 to February 5, 2016. Cases were selected from patients admitted in Medical Wards and those attending Medical OPD. Diagnosis of cirrhosis was confirmed by Clinical Examination and Lab & Imaging investigation in Medical Department. Doppler waveform study was done by experienced radiologist in Radiology Department before and after administration of octreotide. Doppler signals were obtained from the right hepatic vein. Waveform tracings were recorded for five seconds and categorized as ‘monophasic’, ‘biphasic’ and ‘triphasic’. Waveform changes from one waveform to other were noted and analyzed. Results: Significant change i.e. from ‘monophasic’ to ‘biphasic’ or ‘biphasic’ to ‘triphasic’ was seen in 56% cases while ‘monophasic’ to ‘triphasic’ was seen in 20% cases. No change was seen in 24% cases. Improvement in waveform reflects lowering of portal vein pressure. Conclusion: Non invasive Hepatic vein Doppler waveform study showed improvement in Doppler waveform after administration of octreotide in 76% cases. Doppler waveform study has the potential of becoming non invasive ‘follow up tool’ of choice for assessing portal pressure in patients having variceal bleed due to portal hypertension. PMID:27648043

EAARL coastal topography--Alligator Point, Louisiana, 2010

USGS Publications Warehouse

Nayegandhi, Amar; Bonisteel-Cormier, J.M.; Wright, C.W.; Brock, J.C.; Nagle, D.B.; Vivekanandan, Saisudha; Fredericks, Xan; Barras, J.A.

2012-01-01

This project provides highly detailed and accurate datasets of a portion of Alligator Point, Louisiana, acquired on March 5 and 6, 2010. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the National Aeronautics and Space Administration (NASA) Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multispectral color-infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine aircraft, but the instrument was deployed on a Pilatus PC-6. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the "bare earth" under vegetation from a point cloud of last return elevations.

Bathymetry and composition of Titan's Ontario Lacus derived from Monte Carlo-based waveform inversion of Cassini RADAR altimetry data

NASA Astrophysics Data System (ADS)

Mastrogiuseppe, M.; Hayes, A. G.; Poggiali, V.; Lunine, J. I.; Lorenz, R. D.; Seu, R.; Le Gall, A.; Notarnicola, C.; Mitchell, K. L.; Malaska, M.; Birch, S. P. D.

2018-01-01

Recently, the Cassini RADAR was used to sound hydrocarbon lakes and seas on Saturn's moon Titan. Since the initial discovery of echoes from the seabed of Ligeia Mare, the second largest liquid body on Titan, a dedicated radar processing chain has been developed to retrieve liquid depth and microwave absorptivity information from RADAR altimetry of Titan's lakes and seas. Herein, we apply this processing chain to altimetry data acquired over southern Ontario Lacus during Titan fly-by T49 in December 2008. The new signal processing chain adopts super resolution techniques and dedicated taper functions to reveal the presence of reflection from Ontario's lakebed. Unfortunately, the extracted waveforms from T49 are often distorted due to signal saturation, owing to the extraordinarily strong specular reflections from the smooth lake surface. This distortion is a function of the saturation level and can introduce artifacts, such as signal precursors, which complicate data interpretation. We use a radar altimetry simulator to retrieve information from the saturated bursts and determine the liquid depth and loss tangent of Ontario Lacus. Received waveforms are represented using a two-layer model, where Cassini raw radar data are simulated in order to reproduce the effects of receiver saturation. A Monte Carlo based approach along with a simulated waveform look-up table is used to retrieve parameters that are given as inputs to a parametric model which constrains radio absorption of Ontario Lacus and retrieves information about the dielectric properties of the liquid. We retrieve a maximum depth of 50 m along the radar transect and a best-fit specific attenuation of the liquid equal to 0.2 ± 0.09 dB m-1 that, when converted into loss tangent, gives tanδ = 7 ± 3 × 10-5. When combined with laboratory measured cryogenic liquid alkane dielectric properties and the variable solubility of nitrogen in ethane-methane mixtures, the best-fit loss tangent is consistent with a ternary mixture of 51% methane, 38% ethane and 11% nitrogen by volume.

Cross-Sectional Elasticity Imaging of Arterial Wall by Comparing Measured Change in Thickness with Model Waveform

NASA Astrophysics Data System (ADS)

Tang, Jiang; Hasegawa, Hideyuki; Kanai, Hiroshi

2005-06-01

For the assessment of the elasticity of the arterial wall, we have developed the phased tracking method [H. Kanai et al.: IEEE Trans. Ultrason. Ferroelectr. Freq. Control 43 (1996) 791] for measuring the minute change in thickness due to heartbeats and the elasticity of the arterial wall with transcutaneous ultrasound. For various reasons, for example, an extremely small deformation of the wall, the minute change in wall thickness during one heartbeat is largely influenced by noise in these cases and the reliability of the elasticity distribution obtained from the maximum change in thickness deteriorates because the maximum value estimation is largely influenced by noise. To obtain a more reliable cross-sectional image of the elasticity of the arterial wall, in this paper, a matching method is proposed to evaluate the waveform of the measured change in wall thickness by comparing the measured waveform with a template waveform. The maximum deformation, which is used in the calculation of elasticity, was determined from the amplitude of the matched model waveform to reduce the influence of noise. The matched model waveform was obtained by minimizing the difference between the measured and template waveforms. Furthermore, a random error, which was obtained from the reproducibility among the heartbeats of the measured waveform, was considered useful for the evaluation of the reliability of the measured waveform.

NEW APPLICATIONS IN THE INVERSION OF ACOUSTIC FULL WAVEFORM LOGS - RELATING MODE EXCITATION TO LITHOLOGY.

USGS Publications Warehouse

Paillet, Frederick L.; Cheng, C.H.; Meredith, J.A.

1987-01-01

Existing techniques for the quantitative interpretation of waveform data have been based on one of two fundamental approaches: (1) simultaneous identification of compressional and shear velocities; and (2) least-squares minimization of the difference between experimental waveforms and synthetic seismograms. Techniques based on the first approach do not always work, and those based on the second seem too numerically cumbersome for routine application during data processing. An alternative approach is tested here, in which synthetic waveforms are used to predict relative mode excitation in the composite waveform. Synthetic waveforms are generated for a series of lithologies ranging from hard, crystalline rocks (Vp equals 6. 0 km/sec. and Poisson's ratio equals 0. 20) to soft, argillaceous sediments (Vp equals 1. 8 km/sec. and Poisson's ratio equals 0. 40). The series of waveforms illustrates a continuous change within this range of rock properties. Mode energy within characteristic velocity windows is computed for each of the modes in the set of synthetic waveforms. The results indicate that there is a consistent variation in mode excitation in lithology space that can be used to construct a unique relationship between relative mode excitation and lithology.

Length requirements for numerical-relativity waveforms

NASA Astrophysics Data System (ADS)

Hannam, Mark; Husa, Sascha; Ohme, Frank; Ajith, P.

2010-12-01

One way to produce complete inspiral-merger-ringdown gravitational waveforms from black-hole-binary systems is to connect post-Newtonian (PN) and numerical-relativity (NR) results to create “hybrid” waveforms. Hybrid waveforms are central to the construction of some phenomenological models for gravitational-wave (GW) search templates, and for tests of GW search pipelines. The dominant error source in hybrid waveforms arises from the PN contribution, and can be reduced by increasing the number of NR GW cycles that are included in the hybrid. Hybrid waveforms are considered sufficiently accurate for GW detection if their mismatch error is below 3% (i.e., a fitting factor above 0.97). We address the question of the length requirements of NR waveforms such that the final hybrid waveforms meet this requirement, considering nonspinning binaries with q=M2/M1∈[1,4] and equal-mass binaries with χ=Si/Mi2∈[-0.5,0.5]. We conclude that, for the cases we study, simulations must contain between three (in the equal-mass nonspinning case) and ten (the χ=0.5 case) orbits before merger, but there is also evidence that these are the regions of parameter space for which the least number of cycles will be needed.

Surface Fitting Filtering of LIDAR Point Cloud with Waveform Information

NASA Astrophysics Data System (ADS)

Xing, S.; Li, P.; Xu, Q.; Wang, D.; Li, P.

2017-09-01

Full-waveform LiDAR is an active technology of photogrammetry and remote sensing. It provides more detailed information about objects along the path of a laser pulse than discrete-return topographic LiDAR. The point cloud and waveform information with high quality can be obtained by waveform decomposition, which could make contributions to accurate filtering. The surface fitting filtering method with waveform information is proposed to present such advantage. Firstly, discrete point cloud and waveform parameters are resolved by global convergent Levenberg Marquardt decomposition. Secondly, the ground seed points are selected, of which the abnormal ones are detected by waveform parameters and robust estimation. Thirdly, the terrain surface is fitted and the height difference threshold is determined in consideration of window size and mean square error. Finally, the points are classified gradually with the rising of window size. The filtering process is finished until window size is larger than threshold. The waveform data in urban, farmland and mountain areas from "WATER (Watershed Allied Telemetry Experimental Research)" are selected for experiments. Results prove that compared with traditional method, the accuracy of point cloud filtering is further improved and the proposed method has highly practical value.

Bandwidth scalable, coherent transmitter based on the parallel synthesis of multiple spectral slices using optical arbitrary waveform generation.

PubMed

Geisler, David J; Fontaine, Nicolas K; Scott, Ryan P; He, Tingting; Paraschis, Loukas; Gerstel, Ori; Heritage, Jonathan P; Yoo, S J B

2011-04-25

We demonstrate an optical transmitter based on dynamic optical arbitrary waveform generation (OAWG) which is capable of creating high-bandwidth (THz) data waveforms in any modulation format using the parallel synthesis of multiple coherent spectral slices. As an initial demonstration, the transmitter uses only 5.5 GHz of electrical bandwidth and two 10-GHz-wide spectral slices to create 100-ns duration, 20-GHz optical waveforms in various modulation formats including differential phase-shift keying (DPSK), quaternary phase-shift keying (QPSK), and eight phase-shift keying (8PSK) with only changes in software. The experimentally generated waveforms showed clear eye openings and separated constellation points when measured using a real-time digital coherent receiver. Bit-error-rate (BER) performance analysis resulted in a BER < 9.8 × 10(-6) for DPSK and QPSK waveforms. Additionally, we experimentally demonstrate three-slice, 4-ns long waveforms that highlight the bandwidth scalable nature of the optical transmitter. The various generated waveforms show that the key transmitter properties (i.e., packet length, modulation format, data rate, and modulation filter shape) are software definable, and that the optical transmitter is capable of acting as a flexible bandwidth transmitter.

A Novel Approach to ECG Classification Based upon Two-Layered HMMs in Body Sensor Networks

PubMed Central

Liang, Wei; Zhang, Yinlong; Tan, Jindong; Li, Yang

2014-01-01

This paper presents a novel approach to ECG signal filtering and classification. Unlike the traditional techniques which aim at collecting and processing the ECG signals with the patient being still, lying in bed in hospitals, our proposed algorithm is intentionally designed for monitoring and classifying the patient's ECG signals in the free-living environment. The patients are equipped with wearable ambulatory devices the whole day, which facilitates the real-time heart attack detection. In ECG preprocessing, an integral-coefficient-band-stop (ICBS) filter is applied, which omits time-consuming floating-point computations. In addition, two-layered Hidden Markov Models (HMMs) are applied to achieve ECG feature extraction and classification. The periodic ECG waveforms are segmented into ISO intervals, P subwave, QRS complex and T subwave respectively in the first HMM layer where expert-annotation assisted Baum-Welch algorithm is utilized in HMM modeling. Then the corresponding interval features are selected and applied to categorize the ECG into normal type or abnormal type (PVC, APC) in the second HMM layer. For verifying the effectiveness of our algorithm on abnormal signal detection, we have developed an ECG body sensor network (BSN) platform, whereby real-time ECG signals are collected, transmitted, displayed and the corresponding classification outcomes are deduced and shown on the BSN screen. PMID:24681668

STRS Compliant FPGA Waveform Development

NASA Technical Reports Server (NTRS)

Nappier, Jennifer; Downey, Joseph

2008-01-01

The Space Telecommunications Radio System (STRS) Architecture Standard describes a standard for NASA space software defined radios (SDRs). It provides a common framework that can be used to develop and operate a space SDR in a reconfigurable and reprogrammable manner. One goal of the STRS Architecture is to promote waveform reuse among multiple software defined radios. Many space domain waveforms are designed to run in the special signal processing (SSP) hardware. However, the STRS Architecture is currently incomplete in defining a standard for designing waveforms in the SSP hardware. Therefore, the STRS Architecture needs to be extended to encompass waveform development in the SSP hardware. A transmit waveform for space applications was developed to determine ways to extend the STRS Architecture to a field programmable gate array (FPGA). These extensions include a standard hardware abstraction layer for FPGAs and a standard interface between waveform functions running inside a FPGA. Current standards were researched and new standard interfaces were proposed. The implementation of the proposed standard interfaces on a laboratory breadboard SDR will be presented.

Modeling measured glottal volume velocity waveforms.

PubMed

Verneuil, Andrew; Berry, David A; Kreiman, Jody; Gerratt, Bruce R; Ye, Ming; Berke, Gerald S

2003-02-01

The source-filter theory of speech production describes a glottal energy source (volume velocity waveform) that is filtered by the vocal tract and radiates from the mouth as phonation. The characteristics of the volume velocity waveform, the source that drives phonation, have been estimated, but never directly measured at the glottis. To accomplish this measurement, constant temperature anemometer probes were used in an in vivo canine constant pressure model of phonation. A 3-probe array was positioned supraglottically, and an endoscopic camera was positioned subglottically. Simultaneous recordings of airflow velocity (using anemometry) and glottal area (using stroboscopy) were made in 3 animals. Glottal airflow velocities and areas were combined to produce direct measurements of glottal volume velocity waveforms. The anterior and middle parts of the glottis contributed significantly to the volume velocity waveform, with less contribution from the posterior part of the glottis. The measured volume velocity waveforms were successfully fitted to a well-known laryngeal airflow model. A noninvasive measured volume velocity waveform holds promise for future clinical use.

An improved driving waveform reference grayscale of electrophoretic displays

NASA Astrophysics Data System (ADS)

Wang, Li; Yi, Zichuan; Peng, Bao; Zhou, Guofu

2015-10-01

Driving waveform is an important component for gray scale display on the electrophoretic display (EPD). In the traditional driving waveform, a white reference gray scale is formed before writing a new image. However, the reflectance value can not reach agreement in each gray scale transformation. In this paper, a new driving waveform, which has a short waiting time after the formation of reference gray scale, is proposed to improve the consistency of reference gray scale. Firstly, the property of the particles in the microcapsule is analyzed and the change of the EPD reflectance after the white reference gray scale formation is studied. Secondly, the reflectance change curve is fitted by using polynomial and the duration of the waiting time is determined. Thirdly, a set of the new driving waveform is designed by using the rule of DC balance and some real E-ink commercial EPDs are used to test the performance. Experimental results show that the effect of the new driving waveform has a better performance than traditional waveforms.

Adaptive phase k-means algorithm for waveform classification

NASA Astrophysics Data System (ADS)

Song, Chengyun; Liu, Zhining; Wang, Yaojun; Xu, Feng; Li, Xingming; Hu, Guangmin

2018-01-01

Waveform classification is a powerful technique for seismic facies analysis that describes the heterogeneity and compartments within a reservoir. Horizon interpretation is a critical step in waveform classification. However, the horizon often produces inconsistent waveform phase, and thus results in an unsatisfied classification. To alleviate this problem, an adaptive phase waveform classification method called the adaptive phase k-means is introduced in this paper. Our method improves the traditional k-means algorithm using an adaptive phase distance for waveform similarity measure. The proposed distance is a measure with variable phases as it moves from sample to sample along the traces. Model traces are also updated with the best phase interference in the iterative process. Therefore, our method is robust to phase variations caused by the interpretation horizon. We tested the effectiveness of our algorithm by applying it to synthetic and real data. The satisfactory results reveal that the proposed method tolerates certain waveform phase variation and is a good tool for seismic facies analysis.

Seismic waveform classification using deep learning

NASA Astrophysics Data System (ADS)

Kong, Q.; Allen, R. M.

2017-12-01

MyShake is a global smartphone seismic network that harnesses the power of crowdsourcing. It has an Artificial Neural Network (ANN) algorithm running on the phone to distinguish earthquake motion from human activities recorded by the accelerometer on board. Once the ANN detects earthquake-like motion, it sends a 5-min chunk of acceleration data back to the server for further analysis. The time-series data collected contains both earthquake data and human activity data that the ANN confused. In this presentation, we will show the Convolutional Neural Network (CNN) we built under the umbrella of supervised learning to find out the earthquake waveform. The waveforms of the recorded motion could treat easily as images, and by taking the advantage of the power of CNN processing the images, we achieved very high successful rate to select the earthquake waveforms out. Since there are many non-earthquake waveforms than the earthquake waveforms, we also built an anomaly detection algorithm using the CNN. Both these two methods can be easily extended to other waveform classification problems.

Accurate inspiral-merger-ringdown gravitational waveforms for nonspinning black-hole binaries including the effect of subdominant modes

NASA Astrophysics Data System (ADS)

Mehta, Ajit Kumar; Mishra, Chandra Kant; Varma, Vijay; Ajith, Parameswaran

2017-12-01

We present an analytical waveform family describing gravitational waves (GWs) from the inspiral, merger, and ringdown of nonspinning black-hole binaries including the effect of several nonquadrupole modes [(ℓ=2 ,m =±1 ),(ℓ=3 ,m =±3 ),(ℓ=4 ,m =±4 ) apart from (ℓ=2 ,m =±2 )]. We first construct spin-weighted spherical harmonics modes of hybrid waveforms by matching numerical-relativity simulations (with mass ratio 1-10) describing the late inspiral, merger, and ringdown of the binary with post-Newtonian/effective-one-body waveforms describing the early inspiral. An analytical waveform family is constructed in frequency domain by modeling the Fourier transform of the hybrid waveforms making use of analytical functions inspired by perturbative calculations. The resulting highly accurate, ready-to-use waveforms are highly faithful (unfaithfulness ≃10-4- 10-2 ) for observation of GWs from nonspinning black-hole binaries and are extremely inexpensive to generate.

Statistical characteristics of transient enclosure voltage in ultra-high-voltage gas-insulated switchgear

NASA Astrophysics Data System (ADS)

Cai, Yuanji; Guan, Yonggang; Liu, Weidong

2017-06-01

Transient enclosure voltage (TEV), which is a phenomenon induced by the inner dielectric breakdown of SF6 during disconnector operations in a gas-insulated switchgear (GIS), may cause issues relating to shock hazard and electromagnetic interference to secondary equipment. This is a critical factor regarding the electromagnetic compatibility of ultra-high-voltage (UHV) substations. In this paper, the statistical characteristics of TEV at UHV level are collected from field experiments, and are analyzed and compared to those from a repeated strike process. The TEV waveforms during disconnector operations are recorded by a self-developed measurement system first. Then, statistical characteristics, such as the pulse number, duration of pulses, frequency components, magnitude and single pulse duration, are extracted. The transmission line theory is introduced to analyze the TEV and is validated by the experimental results. Finally, the relationship between the TEV and the repeated strike process is analyzed. This proves that the pulse voltage of the TEV is proportional to the corresponding breakdown voltage. The results contribute to the definition of the standard testing waveform of the TEV, and can aid the protection of electronic devices in substations by minimizing the threat of this phenomenon.

An information-theoretic approach to the gravitational-wave burst detection problem

NASA Astrophysics Data System (ADS)

Katsavounidis, E.; Lynch, R.; Vitale, S.; Essick, R.; Robinet, F.

2016-03-01

The advanced era of gravitational-wave astronomy, with data collected in part by the LIGO gravitational-wave interferometers, has begun as of fall 2015. One potential type of detectable gravitational waves is short-duration gravitational-wave bursts, whose waveforms can be difficult to predict. We present the framework for a new detection algorithm - called oLIB - that can be used in relatively low-latency to turn calibrated strain data into a detection significance statement. This pipeline consists of 1) a sine-Gaussian matched-filter trigger generator based on the Q-transform - known as Omicron -, 2) incoherent down-selection of these triggers to the most signal-like set, and 3) a fully coherent analysis of this signal-like set using the Markov chain Monte Carlo (MCMC) Bayesian evidence calculator LALInferenceBurst (LIB). We optimally extract this information by using a likelihood-ratio test (LRT) to map these search statistics into a significance statement. Using representative archival LIGO data, we show that the algorithm can detect gravitational-wave burst events of realistic strength in realistic instrumental noise with good detection efficiencies across different burst waveform morphologies. With support from the National Science Foundation under Grant PHY-0757058.

Theoretical simulation of the multipole seismoelectric logging while drilling

NASA Astrophysics Data System (ADS)

Guan, Wei; Hu, Hengshan; Zheng, Xiaobo

2013-11-01

Acoustic logging-while-drilling (LWD) technology has been commercially used in the petroleum industry. However it remains a rather difficult task to invert formation compressional and shear velocities from acoustic LWD signals due to the unwanted strong collar wave, which covers or interferes with signals from the formation. In this paper, seismoelectric LWD is investigated for solving that problem. The seismoelectric field is calculated by solving a modified Poisson's equation, whose source term is the electric disturbance induced electrokinetically by the travelling seismic wave. The seismic wavefield itself is obtained by solving Biot's equations for poroelastic waves. From the simulated waveforms and the semblance plots for monopole, dipole and quadrupole sources, it is found that the electric field accompanies the collar wave as well as other wave groups of the acoustic pressure, despite the fact that seismoelectric conversion occurs only in porous formations. The collar wave in the electric field, however, is significantly weakened compared with that in the acoustic pressure, in terms of its amplitude relative to the other wave groups in the full waveforms. Thus less and shallower grooves are required to damp the collar wave if the seismoelectric LWD signals are recorded for extracting formation compressional and shear velocities.

Mis-modelling in Gravitational Wave Astronomy: The Trouble with Templates

NASA Astrophysics Data System (ADS)

Sampson, Laura; Cornish, Neil; Yunes, Nicolas

2014-03-01

Waveform templates are a powerful tool for extracting and characterizing gravitational wave signals. There are, however, attendant dangers in using these highly restrictive signal priors. If strong field gravity is not accurately described by General Relativity (GR), then using GR templates may result in fundamental bias in the recovered parameters, or worse - a complete failure to detect signals. Here we study such dangers, concentrating on three distinct possibilities. First, we show that there exist modified theories compatible with all existing tests that would fail to be detected by the LIGO/Virgo network using searches based on GR templates, but which would be detected using a one parameter post-Einsteinian extension. Second, we study modified theories that produce departures from GR that do not naively fit into the simplest parameterized post-Einsteinian (ppE) scheme. We show that even the simplest ppE templates are still capable of picking up these strange signals and diagnosing a departure from GR. Third, we study how using inspiral-only ppE waveforms for signals that include merger and ringdown can lead to problems in misidentifying a GR departure. We present an easy technique that allows us to self-consistently identify the inspiral portion of the signal.

Waveform-based Bayesian full moment tensor inversion and uncertainty determination for the induced seismicity in an oil/gas field

NASA Astrophysics Data System (ADS)

Gu, Chen; Marzouk, Youssef M.; Toksöz, M. Nafi

2018-03-01

Small earthquakes occur due to natural tectonic motions and are induced by oil and gas production processes. In many oil/gas fields and hydrofracking processes, induced earthquakes result from fluid extraction or injection. The locations and source mechanisms of these earthquakes provide valuable information about the reservoirs. Analysis of induced seismic events has mostly assumed a double-couple source mechanism. However, recent studies have shown a non-negligible percentage of non-double-couple components of source moment tensors in hydraulic fracturing events, assuming a full moment tensor source mechanism. Without uncertainty quantification of the moment tensor solution, it is difficult to determine the reliability of these source models. This study develops a Bayesian method to perform waveform-based full moment tensor inversion and uncertainty quantification for induced seismic events, accounting for both location and velocity model uncertainties. We conduct tests with synthetic events to validate the method, and then apply our newly developed Bayesian inversion approach to real induced seismicity in an oil/gas field in the sultanate of Oman—determining the uncertainties in the source mechanism and in the location of that event.

Resolution of VTI anisotropy with elastic full-waveform inversion: theory and basic numerical examples

NASA Astrophysics Data System (ADS)

Podgornova, O.; Leaney, S.; Liang, L.

2018-07-01

Extracting medium properties from seismic data faces some limitations due to the finite frequency content of the data and restricted spatial positions of the sources and receivers. Some distributions of the medium properties make low impact on the data (including none). If these properties are used as the inversion parameters, then the inverse problem becomes overparametrized, leading to ambiguous results. We present an analysis of multiparameter resolution for the linearized inverse problem in the framework of elastic full-waveform inversion. We show that the spatial and multiparameter sensitivities are intertwined and non-sensitive properties are spatial distributions of some non-trivial combinations of the conventional elastic parameters. The analysis accounts for the Hessian information and frequency content of the data; it is semi-analytical (in some scenarios analytical), easy to interpret and enhances results of the widely used radiation pattern analysis. Single-type scattering is shown to have limited sensitivity, even for full-aperture data. Finite-frequency data lose multiparameter sensitivity at smooth and fine spatial scales. Also, we establish ways to quantify a spatial-multiparameter coupling and demonstrate that the theoretical predictions agree well with the numerical results.

Analysis of intracranial pressure: past, present, and future.

PubMed

Di Ieva, Antonio; Schmitz, Erika M; Cusimano, Michael D

2013-12-01

The monitoring of intracranial pressure (ICP) is an important tool in medicine for its ability to portray the brain's compliance status. The bedside monitor displays the ICP waveform and intermittent mean values to guide physicians in the management of patients, particularly those having sustained a traumatic brain injury. Researchers in the fields of engineering and physics have investigated various mathematical analysis techniques applicable to the waveform in order to extract additional diagnostic and prognostic information, although they largely remain limited to research applications. The purpose of this review is to present the current techniques used to monitor and interpret ICP and explore the potential of using advanced mathematical techniques to provide information about system perturbations from states of homeostasis. We discuss the limits of each proposed technique and we propose that nonlinear analysis could be a reliable approach to describe ICP signals over time, with the fractal dimension as a potential predictive clinically meaningful biomarker. Our goal is to stimulate translational research that can move modern analysis of ICP using these techniques into widespread practical use, and to investigate to the clinical utility of a tool capable of simplifying multiple variables obtained from various sensors.

Energy-optimal electrical excitation of nerve fibers.

PubMed

Jezernik, Saso; Morari, Manfred

2005-04-01

We derive, based on an analytical nerve membrane model and optimal control theory of dynamical systems, an energy-optimal stimulation current waveform for electrical excitation of nerve fibers. Optimal stimulation waveforms for nonleaky and leaky membranes are calculated. The case with a leaky membrane is a realistic case. Finally, we compare the waveforms and energies necessary for excitation of a leaky membrane in the case where the stimulation waveform is a square-wave current pulse, and in the case of energy-optimal stimulation. The optimal stimulation waveform is an exponentially rising waveform and necessitates considerably less energy to excite the nerve than a square-wave pulse (especially true for larger pulse durations). The described theoretical results can lead to drastically increased battery lifetime and/or decreased energy transmission requirements for implanted biomedical systems.

Anomalous waveforms observed in laboratory-formed gas hydrate-bearing and ice-bearing sediments

USGS Publications Warehouse

Lee, M.W.; Waite, W.F.

2011-01-01

Acoustic transmission measurements of compressional, P, and shear, S, wave velocities rely on correctly identifying the P- and S-body wave arrivals in the measured waveform. In cylindrical samples for which the sample is much longer than the acoustic wavelength, these body waves can be obscured by high-amplitude waveform features arriving just after the relatively small-amplitude P-body wave. In this study, a normal mode approach is used to analyze this type of waveform, observed in sediment containing gas hydrate or ice. This analysis extends an existing normal-mode waveform propagation theory by including the effects of the confining medium surrounding the sample, and provides guidelines for estimating S-wave velocities from waveforms containing multiple large-amplitude arrivals. ?? 2011 Acoustical Society of America.

A Novel Automatic Detection System for ECG Arrhythmias Using Maximum Margin Clustering with Immune Evolutionary Algorithm

PubMed Central

Zhu, Bohui; Ding, Yongsheng; Hao, Kuangrong

2013-01-01

This paper presents a novel maximum margin clustering method with immune evolution (IEMMC) for automatic diagnosis of electrocardiogram (ECG) arrhythmias. This diagnostic system consists of signal processing, feature extraction, and the IEMMC algorithm for clustering of ECG arrhythmias. First, raw ECG signal is processed by an adaptive ECG filter based on wavelet transforms, and waveform of the ECG signal is detected; then, features are extracted from ECG signal to cluster different types of arrhythmias by the IEMMC algorithm. Three types of performance evaluation indicators are used to assess the effect of the IEMMC method for ECG arrhythmias, such as sensitivity, specificity, and accuracy. Compared with K-means and iterSVR algorithms, the IEMMC algorithm reflects better performance not only in clustering result but also in terms of global search ability and convergence ability, which proves its effectiveness for the detection of ECG arrhythmias. PMID:23690875

Surface characteristics modeling and performance evaluation of urban building materials using LiDAR data.

PubMed

Li, Xiaolu; Liang, Yu

2015-05-20

Analysis of light detection and ranging (LiDAR) intensity data to extract surface features is of great interest in remote sensing research. One potential application of LiDAR intensity data is target classification. A new bidirectional reflectance distribution function (BRDF) model is derived for target characterization of rough and smooth surfaces. Based on the geometry of our coaxial full-waveform LiDAR system, the integration method is improved through coordinate transformation to establish the relationship between the BRDF model and intensity data of LiDAR. A series of experiments using typical urban building materials are implemented to validate the proposed BRDF model and integration method. The fitting results show that three parameters extracted from the proposed BRDF model can distinguish the urban building materials from perspectives of roughness, specular reflectance, and diffuse reflectance. A comprehensive analysis of these parameters will help characterize surface features in a physically rigorous manner.

Control volume based hydrocephalus research; analysis of human data

NASA Astrophysics Data System (ADS)

Cohen, Benjamin; Wei, Timothy; Voorhees, Abram; Madsen, Joseph; Anor, Tomer

2010-11-01

Hydrocephalus is a neuropathophysiological disorder primarily diagnosed by increased cerebrospinal fluid volume and pressure within the brain. To date, utilization of clinical measurements have been limited to understanding of the relative amplitude and timing of flow, volume and pressure waveforms; qualitative approaches without a clear framework for meaningful quantitative comparison. Pressure volume models and electric circuit analogs enforce volume conservation principles in terms of pressure. Control volume analysis, through the integral mass and momentum conservation equations, ensures that pressure and volume are accounted for using first principles fluid physics. This approach is able to directly incorporate the diverse measurements obtained by clinicians into a simple, direct and robust mechanics based framework. Clinical data obtained for analysis are discussed along with data processing techniques used to extract terms in the conservation equation. Control volume analysis provides a non-invasive, physics-based approach to extracting pressure information from magnetic resonance velocity data that cannot be measured directly by pressure instrumentation.

Exploratory Development for a High Reliability Flaw Characterization Module.

DTIC Science & Technology

1985-03-01

deconvolution), and displaying the waveforms and the complex Fourier spectra (magnitude and phase or real and imaginary parts) on hard copies. The Born...shifted, and put into the Born inver- sion algorithm. Hard copies of the Born inversion results of the type dis- played in Figure 6 were obtained for each...nickel alloys than in titanium alloys because melt practice is not yet sufficiently developed to prevent the introduction of voids and hard oxide

Modularized seismic full waveform inversion based on waveform sensitivity kernels - The software package ASKI

NASA Astrophysics Data System (ADS)

Schumacher, Florian; Friederich, Wolfgang; Lamara, Samir; Gutt, Phillip; Paffrath, Marcel

2015-04-01

We present a seismic full waveform inversion concept for applications ranging from seismological to enineering contexts, based on sensitivity kernels for full waveforms. The kernels are derived from Born scattering theory as the Fréchet derivatives of linearized frequency-domain full waveform data functionals, quantifying the influence of elastic earth model parameters and density on the data values. For a specific source-receiver combination, the kernel is computed from the displacement and strain field spectrum originating from the source evaluated throughout the inversion domain, as well as the Green function spectrum and its strains originating from the receiver. By storing the wavefield spectra of specific sources/receivers, they can be re-used for kernel computation for different specific source-receiver combinations, optimizing the total number of required forward simulations. In the iterative inversion procedure, the solution of the forward problem, the computation of sensitivity kernels and the derivation of a model update is held completely separate. In particular, the model description for the forward problem and the description of the inverted model update are kept independent. Hence, the resolution of the inverted model as well as the complexity of solving the forward problem can be iteratively increased (with increasing frequency content of the inverted data subset). This may regularize the overall inverse problem and optimizes the computational effort of both, solving the forward problem and computing the model update. The required interconnection of arbitrary unstructured volume and point grids is realized by generalized high-order integration rules and 3D-unstructured interpolation methods. The model update is inferred solving a minimization problem in a least-squares sense, resulting in Gauss-Newton convergence of the overall inversion process. The inversion method was implemented in the modularized software package ASKI (Analysis of Sensitivity and Kernel Inversion), which provides a generalized interface to arbitrary external forward modelling codes. So far, the 3D spectral-element code SPECFEM3D (Tromp, Komatitsch and Liu, 2008) and the 1D semi-analytical code GEMINI (Friederich and Dalkolmo, 1995) in both, Cartesian and spherical framework are supported. The creation of interfaces to further forward codes is planned in the near future. ASKI is freely available under the terms of the GPL at www.rub.de/aski . Since the independent modules of ASKI must communicate via file output/input, large storage capacities need to be accessible conveniently. Storing the complete sensitivity matrix to file, however, permits the scientist full manual control over each step in a customized procedure of sensitivity/resolution analysis and full waveform inversion. In the presentation, we will show some aspects of the theory behind the full waveform inversion method and its practical realization by the software package ASKI, as well as synthetic and real-data applications from different scales and geometries.

ECCM Waveform Investigation

DTIC Science & Technology

1977-08-01

period, duration/ peak power, and side lobe levels. A recommended waveform library is presented. One of the program results is that an optimum waveform...Areas a. Coding b. Pulse Repetition Period c. Peak Power/Pulse Duration d. Sidelobes 3. Performance Dependence Upon Bandwidth/Bandspan a... peak power and pulse duration, and range and Doppler sldelobe levels. The constraints upon waveforms due to the In- ability of the radar components

Predicting Electrocardiogram and Arterial Blood Pressure Waveforms with Different Echo State Network Architectures

DTIC Science & Technology

2014-11-01

networks were trained to predict an individual’s electrocardiogram (ECG) and arterial blood pressure ( ABP ) waveform data, which can potentially help...various ESN architectures for prediction tasks, and establishes the benefits of using ESN architecture designs for predicting ECG and ABP waveforms...arterial blood pressure ( ABP ) waveforms immediately prior to the machine generated alarms. When tested, the algorithm suppressed approximately 59.7

Apparatus Characterizes Transient Voltages in Real Time

NASA Technical Reports Server (NTRS)

Medelius, Pedro

2005-01-01

The figure shows a prototype of a relatively inexpensive electronic monitoring apparatus that measures and records selected parameters of lightning-induced transient voltages on communication and power cables. The selected parameters, listed below, are those most relevant to the ability of lightning-induced transients to damage electronic equipment. This apparatus bridges a gap between some traditional transient-voltage recorders that record complete waveforms and other traditional transient-voltage recorders that record only peak values: By recording the most relevant parameters and only those parameters this apparatus yields more useful information than does a traditional peak-value (only) recorder while imposing much smaller data-storage and data-transmission burdens than does a traditional complete-waveform recorder. Also, relative to a complete-waveform recorder, this apparatus is more reliable and can be built at lower cost because it contains fewer electronic components. The transients generated by sources other than lightning tend to have frequency components well below 1 MHz. Most commercial transient recorders can detect and record such transients, but cannot respond rapidly enough for recording lightning-induced transient voltage peaks, which can rise from 10 to 90 percent of maximum amplitude in a fraction of a microsecond. Moreover, commercial transient recorders cannot rearm themselves rapidly enough to respond to the multiple transients that occur within milliseconds of each other on some lightning strikes. One transient recorder, designed for Kennedy Space Center earlier [ Fast Transient-Voltage Recorder (KSC- 11991), NASA Tech Briefs, Vol. 23, No. 10, page 6a (October 1999)], is capable of sampling transient voltages at peak values up to 50 V in four channels at a rate of 20 MHz. That recorder contains a trigger circuit that continuously compares the amplitudes of the signals on four channels to a preset triggering threshold. When a trigger signal is received, a volatile memory is filled with data for a total time of 200 ms. After the data are transferred to nonvolatile memory, the recorder rearms itself within 400 ms to enable recording of subsequent transients. Unfortunately, the recorded data must be retrieved through a serial communication link. Depending on the amount of data recorded, the memory can be filled before retrieval is completed. Although large amounts of data are recorded and retrieved, only a small part of the information (the selected parameters) is usually required. The present transient-voltage recorder provides the required information, without incurring the overhead associated with the recording, storage, and retrieval of complete transient-waveform data. In operation, this apparatus processes transient voltage waveforms in real time to extract and record the selected parameters. An analog-to-digital converter that operates at a speed of as much as 100 mega-samples per second is used to sample a transient waveform. A real-time comparator and peak detector are implemented by use of fast field-programmable gate arrays.

Identification of complex stiffness tensor from waveform reconstruction

NASA Astrophysics Data System (ADS)

Leymarie, N.; Aristégui, C.; Audoin, B.; Baste, S.

2002-03-01

An inverse method is proposed in order to determine the viscoelastic properties of composite-material plates from the plane-wave transmitted acoustic field. Analytical formulations of both the plate transmission coefficient and its first and second derivatives are established, and included in a two-step inversion scheme. Two objective functions to be minimized are then designed by considering the well-known maximum-likelihood principle and by using an analytic signal formulation. Through these innovative objective functions, the robustness of the inversion process against high level of noise in waveforms is improved and the method can be applied to a very thin specimen. The suitability of the inversion process for viscoelastic property identification is demonstrated using simulated data for composite materials with different anisotropy and damping degrees. A study of the effect of the rheologic model choice on the elastic property identification emphasizes the relevance of using a phenomenological description considering viscosity. Experimental characterizations show then the good reliability of the proposed approach. Difficulties arise experimentally for particular anisotropic media.

Information Object Definition–based Unified Modeling Language Representation of DICOM Structured Reporting

PubMed Central

Tirado-Ramos, Alfredo; Hu, Jingkun; Lee, K.P.

2002-01-01

Supplement 23 to DICOM (Digital Imaging and Communications for Medicine), Structured Reporting, is a specification that supports a semantically rich representation of image and waveform content, enabling experts to share image and related patient information. DICOM SR supports the representation of textual and coded data linked to images and waveforms. Nevertheless, the medical information technology community needs models that work as bridges between the DICOM relational model and open object-oriented technologies. The authors assert that representations of the DICOM Structured Reporting standard, using object-oriented modeling languages such as the Unified Modeling Language, can provide a high-level reference view of the semantically rich framework of DICOM and its complex structures. They have produced an object-oriented model to represent the DICOM SR standard and have derived XML-exchangeable representations of this model using World Wide Web Consortium specifications. They expect the model to benefit developers and system architects who are interested in developing applications that are compliant with the DICOM SR specification. PMID:11751804

High Efficiency Traveling-Wave Tube Power Amplifier for Ka-Band Software Defined Radio on International Space Station-A Platform for Communications Technology Development

NASA Technical Reports Server (NTRS)

Simons, Rainee N.; Force, Dale A.; Kacpura, Thomas J.

2013-01-01

The design, fabrication and RF performance of the output traveling-wave tube amplifier (TWTA) for a space based Ka-band software defined radio (SDR) is presented. The TWTA, the SDR and the supporting avionics are integrated to forms a testbed, which is currently located on an exterior truss of the International Space Station (ISS). The SDR in the testbed communicates at Ka-band frequencies through a high-gain antenna directed to NASA s Tracking and Data Relay Satellite System (TDRSS), which communicates to the ground station located at White Sands Complex. The application of the testbed is for demonstrating new waveforms and software designed to enhance data delivery from scientific spacecraft and, the waveforms and software can be upgraded and reconfigured from the ground. The construction and the salient features of the Ka-band SDR are discussed. The testbed is currently undergoing on-orbit checkout and commissioning and is expected to operate for 3 to 5 years in space.

Separation of Opiate Isomers Using Electrospray Ionization and Paper Spray Coupled to High-Field Asymmetric Waveform Ion Mobility Spectrometry

NASA Astrophysics Data System (ADS)

Manicke, Nicholas E.; Belford, Michael

2015-05-01

One limitation in the growing field of ambient or direct analysis methods is reduced selectivity caused by the elimination of chromatographic separations prior to mass spectrometric analysis. We explored the use of high-field asymmetric waveform ion mobility spectrometry (FAIMS), an ambient pressure ion mobility technique, to separate the closely related opiate isomers of morphine, hydromorphone, and norcodeine. These isomers cannot be distinguished by tandem mass spectrometry. Separation prior to MS analysis is, therefore, required to distinguish these compounds, which are important in clinical chemistry and toxicology. FAIMS was coupled to a triple quadrupole mass spectrometer, and ionization was performed using either a pneumatically assisted heated electrospray ionization source (H-ESI) or paper spray, a direct analysis method that has been applied to the direct analysis of dried blood spots and other complex samples. We found that FAIMS was capable of separating the three opiate structural isomers using both H-ESI and paper spray as the ionization source.

Source analysis using regional empirical Green's functions: The 2008 Wells, Nevada, earthquake

USGS Publications Warehouse

Mendoza, C.; Hartzell, S.

2009-01-01

We invert three-component, regional broadband waveforms recorded for the 21 February 2008 Wells, Nevada, earthquake using a finite-fault methodology that prescribes subfault responses using eight MW∼4 aftershocks as empirical Green's functions (EGFs) distributed within a 20-km by 21.6-km fault area. The inversion identifies a seismic moment of 6.2 x 1024 dyne-cm (5.8 MW) with slip concentrated in a compact 6.5-km by 4-km region updip from the hypocenter. The peak slip within this localized area is 88 cm and the stress drop is 72 bars, which is higher than expected for Basin and Range normal faults in the western United States. The EGF approach yields excellent fits to the complex regional waveforms, accounting for strong variations in wave propagation and site effects. This suggests that the procedure is useful for studying moderate-size earthquakes with limited teleseismic or strong-motion data and for examining uncertainties in slip models obtained using theoretical Green's functions.

Fine Structure of Plasmaspheric Hiss

NASA Astrophysics Data System (ADS)

Summers, D.; Omura, Y.; Nakamura, S.; Kletzing, C.

2014-12-01

Plasmaspheric hiss plays a key role in controlling the structure and dynamics of Earth's radiation belts.The quiet time slot region between the inner and outer belts can be explained as a steady-state balance between earthward radial diffusion and pitch-angle scattering loss of energetic electrons to the atmosphere induced by plasmaspheric hiss. Plasmaspheric hiss can also induce gradual precipitation loss of MeV electrons from the outer radiation belt. Plasmaspheric hiss has been widely regarded as a broadband,structureless,incoherent emission. Here, by examining burst-mode vector waveform data from the EMFISIS instrument on the Van Allen Probes mission,we show that plasmaspheric hiss is a coherent emission with complex fine structure. Specifically, plasmaspheric hiss appears as discrete rising tone and falling tone elements. By means of waveform analysis we identify typical amplitudes,phase profiles,and sweep rates of the rising and falling tone elements. The new observations reported here can be expected to fuel a re-examination of the properties of plasmaspheric hiss, including a further re-analysis of the generation mechanism for hiss.

New families of low frequency earthquakes beneath the Olympic Peninsula, Washington

NASA Astrophysics Data System (ADS)

Chestler, S.; Creager, K. C.; Sweet, J. R.

2013-12-01

Using data from the Array of Arrays (AofA) and Cascadia Arrays for Earthscope (CAFÉ) experiments we search for new families of low frequency earthquakes (LFEs) beneath the Olympic Peninsula, Washington. LFE families are clusters of repeating LFEs that occur in approximately the same location. Following methodology similar to Bostock et al. [2012, G3], we cross correlate 6-second long windows within an hour of data during the 2010 and 2011 ETS events. We apply this to 99 hours of tremor data. For each hour, we stack the autocorrelation functions from a set of 7 3-component base stations chosen for their high signal-to-noise ratios (SNRs). We extract a maximum of 10 windows per hour with correlation coefficients higher than 9 times the median absolute deviation (MAD). These time windows contain our preliminary LFE detections. We then cross correlate these data and group them using a hierarchical clustering algorithm. We produce template waveforms by stacking the waveforms corresponding to a given cluster. To strengthen the templates we scan them through on day of tremor and stack all waveforms that correlate with the original template. Our efforts have yielded dozens of new families scattered beneath the AofA stations. These additional LFE families add to the 9 known families beneath the Olympic Peninsula [Sweet et al., AGU fall meeting, 2012]. The detection of more LFE families will allow us to (1) interpolate the pattern of stress transfer through the transition zone [Wech et al., Nature Geoscie., 2011], (2) gain insight into the distribution of asperities, or sticky spots, on the plate interface [Ghosh et al., JGR, 2012], and (3) track slow slip rupture propagation with unprecedented spatial and temporal accuracy.

Delay grid multiplexing: simple time-based multiplexing and readout method for silicon photomultipliers

NASA Astrophysics Data System (ADS)

Won, Jun Yeon; Ko, Guen Bae; Lee, Jae Sung

2016-10-01

In this paper, we propose a fully time-based multiplexing and readout method that uses the principle of the global positioning system. Time-based multiplexing allows simplifying the multiplexing circuits where the only innate traces that connect the signal pins of the silicon photomultiplier (SiPM) channels to the readout channels are used as the multiplexing circuit. Every SiPM channel is connected to the delay grid that consists of the traces on a printed circuit board, and the inherent transit times from each SiPM channel to the readout channels encode the position information uniquely. Thus, the position of each SiPM can be identified using the time difference of arrival (TDOA) measurements. The proposed multiplexing can also allow simplification of the readout circuit using the time-to-digital converter (TDC) implemented in a field-programmable gate array (FPGA), where the time-over-threshold (ToT) is used to extract the energy information after multiplexing. In order to verify the proposed multiplexing method, we built a positron emission tomography (PET) detector that consisted of an array of 4  ×  4 LGSO crystals, each with a dimension of 3  ×  3  ×  20 mm3, and one- to-one coupled SiPM channels. We first employed the waveform sampler as an initial study, and then replaced the waveform sampler with an FPGA-TDC to further simplify the readout circuits. The 16 crystals were clearly resolved using only the time information obtained from the four readout channels. The coincidence resolving times (CRTs) were 382 and 406 ps FWHM when using the waveform sampler and the FPGA-TDC, respectively. The proposed simple multiplexing and readout methods can be useful for time-of-flight (TOF) PET scanners.

Cortical Signal Analysis and Advances in Functional Near-Infrared Spectroscopy Signal: A Review.

PubMed

Kamran, Muhammad A; Mannan, Malik M Naeem; Jeong, Myung Yung

2016-01-01

Functional near-infrared spectroscopy (fNIRS) is a non-invasive neuroimaging modality that measures the concentration changes of oxy-hemoglobin (HbO) and de-oxy hemoglobin (HbR) at the same time. It is an emerging cortical imaging modality with a good temporal resolution that is acceptable for brain-computer interface applications. Researchers have developed several methods in last two decades to extract the neuronal activation related waveform from the observed fNIRS time series. But still there is no standard method for analysis of fNIRS data. This article presents a brief review of existing methodologies to model and analyze the activation signal. The purpose of this review article is to give a general overview of variety of existing methodologies to extract useful information from measured fNIRS data including pre-processing steps, effects of differential path length factor (DPF), variations and attributes of hemodynamic response function (HRF), extraction of evoked response, removal of physiological noises, instrumentation, and environmental noises and resting/activation state functional connectivity. Finally, the challenges in the analysis of fNIRS signal are summarized.

Cortical Signal Analysis and Advances in Functional Near-Infrared Spectroscopy Signal: A Review

PubMed Central

Kamran, Muhammad A.; Mannan, Malik M. Naeem; Jeong, Myung Yung

2016-01-01

Functional near-infrared spectroscopy (fNIRS) is a non-invasive neuroimaging modality that measures the concentration changes of oxy-hemoglobin (HbO) and de-oxy hemoglobin (HbR) at the same time. It is an emerging cortical imaging modality with a good temporal resolution that is acceptable for brain-computer interface applications. Researchers have developed several methods in last two decades to extract the neuronal activation related waveform from the observed fNIRS time series. But still there is no standard method for analysis of fNIRS data. This article presents a brief review of existing methodologies to model and analyze the activation signal. The purpose of this review article is to give a general overview of variety of existing methodologies to extract useful information from measured fNIRS data including pre-processing steps, effects of differential path length factor (DPF), variations and attributes of hemodynamic response function (HRF), extraction of evoked response, removal of physiological noises, instrumentation, and environmental noises and resting/activation state functional connectivity. Finally, the challenges in the analysis of fNIRS signal are summarized. PMID:27375458

Average current is better than peak current as therapeutic dosage for biphasic waveforms in a ventricular fibrillation pig model of cardiac arrest.

PubMed

Chen, Bihua; Yu, Tao; Ristagno, Giuseppe; Quan, Weilun; Li, Yongqin

2014-10-01

Defibrillation current has been shown to be a clinically more relevant dosing unit than energy. However, the effects of average and peak current in determining shock outcome are still undetermined. The aim of this study was to investigate the relationship between average current, peak current and defibrillation success when different biphasic waveforms were employed. Ventricular fibrillation (VF) was electrically induced in 22 domestic male pigs. Animals were then randomized to receive defibrillation using one of two different biphasic waveforms. A grouped up-and-down defibrillation threshold-testing protocol was used to maintain the average success rate of 50% in the neighborhood. In 14 animals (Study A), defibrillations were accomplished with either biphasic truncated exponential (BTE) or rectilinear biphasic waveforms. In eight animals (Study B), shocks were delivered using two BTE waveforms that had identical peak current but different waveform durations. Both average and peak currents were associated with defibrillation success when BTE and rectilinear waveforms were investigated. However, when pathway impedance was less than 90Ω for the BTE waveform, bivariate correlation coefficient was 0.36 (p=0.001) for the average current, but only 0.21 (p=0.06) for the peak current in Study A. In Study B, a high defibrillation success (67.9% vs. 38.8%, p<0.001) was observed when the waveform delivered more average current (14.9±2.1A vs. 13.5±1.7A, p<0.001) while keeping the peak current unchanged. In this porcine model of VF, average current was better than peak current to be an adequate parameter to describe the therapeutic dosage when biphasic defibrillation waveforms were used. The institutional protocol number: P0805. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

A Waveform Archiving System for the GE Solar 8000i Bedside Monitor.

PubMed

Fanelli, Andrea; Jaishankar, Rohan; Filippidis, Aristotelis; Holsapple, James; Heldt, Thomas

2018-01-01

Our objective was to develop, deploy, and test a data-acquisition system for the reliable and robust archiving of high-resolution physiological waveform data from a variety of bedside monitoring devices, including the GE Solar 8000i patient monitor, and for the logging of ancillary clinical and demographic information. The data-acquisition system consists of a computer-based archiving unit and a GE Tram Rac 4A that connects to the GE Solar 8000i monitor. Standard physiological front-end sensors connect directly to the Tram Rac, which serves as a port replicator for the GE monitor and provides access to these waveform signals through an analog data interface. Together with the GE monitoring data streams, we simultaneously collect the cerebral blood flow velocity envelope from a transcranial Doppler ultrasound system and a non-invasive arterial blood pressure waveform along a common time axis. All waveform signals are digitized and archived through a LabView-controlled interface that also allows for the logging of relevant meta-data such as clinical and patient demographic information. The acquisition system was certified for hospital use by the clinical engineering team at Boston Medical Center, Boston, MA, USA. Over a 12-month period, we collected 57 datasets from 11 neuro-ICU patients. The system provided reliable and failure-free waveform archiving. We measured an average temporal drift between waveforms from different monitoring devices of 1 ms every 66 min of recorded data. The waveform acquisition system allows for robust real-time data acquisition, processing, and archiving of waveforms. The temporal drift between waveforms archived from different devices is entirely negligible, even for long-term recording.

Waveform Fingerprinting for Efficient Seismic Signal Detection

NASA Astrophysics Data System (ADS)

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

2013-12-01

Cross-correlating an earthquake waveform template with continuous waveform data has proven a powerful approach for detecting events missing from earthquake catalogs. If templates do not exist, it is possible to divide the waveform data into short overlapping time windows, then identify window pairs with similar waveforms. Applying these approaches to earthquake monitoring in seismic networks has tremendous potential to improve the completeness of earthquake catalogs, but because effort scales quadratically with time, it rapidly becomes computationally infeasible. We develop a fingerprinting technique to identify similar waveforms, using only a few compact features of the original data. The concept is similar to human fingerprints, which utilize key diagnostic features to identify people uniquely. Analogous audio-fingerprinting approaches have accurately and efficiently found similar audio clips within large databases; example applications include identifying songs and finding copyrighted content within YouTube videos. In order to fingerprint waveforms, we compute a spectrogram of the time series, and segment it into multiple overlapping windows (spectral images). For each spectral image, we apply a wavelet transform, and retain only the sign of the maximum magnitude wavelet coefficients. This procedure retains just the large-scale structure of the data, providing both robustness to noise and significant dimensionality reduction. Each fingerprint is a high-dimensional, sparse, binary data object that can be stored in a database without significant storage costs. Similar fingerprints within the database are efficiently searched using locality-sensitive hashing. We test this technique on waveform data from the Northern California Seismic Network that contains events not detected in the catalog. We show that this algorithm successfully identifies similar waveforms and detects uncataloged low magnitude events in addition to cataloged events, while running to completion faster than a comparison waveform autocorrelation code.

Comparison of pulmonary artery and central venous pressure waveform measurements via digital and graphic measurement methods.

PubMed

Ahrens, T S; Schallom, L

2001-01-01

Techniques to measure pulmonary artery (PA) pressure waveforms include digital measurement, graphic measurement, and freeze-cursor measurement. Previous studies reported the inaccuracy of digital and freeze-cursor measurements. However, many of the previous studies were small and did not thoroughly examine the circumstances of when digital measurements might be inaccurate. To compare digital measurements and graphic measurements of PA and central venous pressure (CVP) waveforms in patients with a variety of respiratory patterns, and to compare digital measurements and graphic measurements of CVPs in patients with abnormal or right ventricular waveforms. A total of 928 patients were enrolled in this study. Waveforms from the PA and CVP were collected from each patient. The monitor pressure value (digital measurement) printed on the recorded waveform was compared with the pressure value obtained by a graphic strip recording and measured by one of the primary investigators (graphic measurement). Digital measurements were found to be inaccurate in measuring waveforms in all respiratory categories and in measuring right ventricular waveforms. PA diastolic values and CVP values were the most inaccurately measured waveforms. Digital errors of more than 4 mm Hg were common. There were instances in which the monitor's digital measurement was substantially different from the graphically measured value. This difference has the potential to mislead interpretation of clinical situations. The monitor's ability to occasionally give digital measurement values similar to the graphic measurements may lead to a false sense of security in clinicians. Because the accuracy of the monitor is inconsistent, the bedside clinician should interpret waveforms through use of a graphic recording rather than rely on the digital measurement on the monitor.

Carrier Modulation Via Waveform Probability Density Function

NASA Technical Reports Server (NTRS)

Williams, Glenn L.

2006-01-01

Beyond the classic modes of carrier modulation by varying amplitude (AM), phase (PM), or frequency (FM), we extend the modulation domain of an analog carrier signal to include a class of general modulations which are distinguished by their probability density function histogram. Separate waveform states are easily created by varying the pdf of the transmitted waveform. Individual waveform states are assignable as proxies for digital one's or zero's. At the receiver, these states are easily detected by accumulating sampled waveform statistics and performing periodic pattern matching, correlation, or statistical filtering. No fundamental physical laws are broken in the detection process. We show how a typical modulation scheme would work in the digital domain and suggest how to build an analog version. We propose that clever variations of the modulating waveform (and thus the histogram) can provide simple steganographic encoding.

Carrier Modulation Via Waveform Probability Density Function

NASA Technical Reports Server (NTRS)

Williams, Glenn L.

2004-01-01

Beyond the classic modes of carrier modulation by varying amplitude (AM), phase (PM), or frequency (FM), we extend the modulation domain of an analog carrier signal to include a class of general modulations which are distinguished by their probability density function histogram. Separate waveform states are easily created by varying the pdf of the transmitted waveform. Individual waveform states are assignable as proxies for digital ONEs or ZEROs. At the receiver, these states are easily detected by accumulating sampled waveform statistics and performing periodic pattern matching, correlation, or statistical filtering. No fundamental natural laws are broken in the detection process. We show how a typical modulation scheme would work in the digital domain and suggest how to build an analog version. We propose that clever variations of the modulating waveform (and thus the histogram) can provide simple steganographic encoding.

Design of a 9-loop quasi-exponential waveform generator

NASA Astrophysics Data System (ADS)

Banerjee, Partha; Shukla, Rohit; Shyam, Anurag

2015-12-01

We know in an under-damped L-C-R series circuit, current follows a damped sinusoidal waveform. But if a number of sinusoidal waveforms of decreasing time period, generated in an L-C-R circuit, be combined in first quarter cycle of time period, then a quasi-exponential nature of output current waveform can be achieved. In an L-C-R series circuit, quasi-exponential current waveform shows a rising current derivative and thereby finds many applications in pulsed power. Here, we have described design and experiment details of a 9-loop quasi-exponential waveform generator. In that, design details of magnetic switches have also been described. In the experiment, output current of 26 kA has been achieved. It has been shown that how well the experimentally obtained output current profile matches with the numerically computed output.

Design of a 9-loop quasi-exponential waveform generator.

PubMed

Banerjee, Partha; Shukla, Rohit; Shyam, Anurag

2015-12-01

We know in an under-damped L-C-R series circuit, current follows a damped sinusoidal waveform. But if a number of sinusoidal waveforms of decreasing time period, generated in an L-C-R circuit, be combined in first quarter cycle of time period, then a quasi-exponential nature of output current waveform can be achieved. In an L-C-R series circuit, quasi-exponential current waveform shows a rising current derivative and thereby finds many applications in pulsed power. Here, we have described design and experiment details of a 9-loop quasi-exponential waveform generator. In that, design details of magnetic switches have also been described. In the experiment, output current of 26 kA has been achieved. It has been shown that how well the experimentally obtained output current profile matches with the numerically computed output.