Signal generation and mixing electronics for frequency-domain lifetime and spectral fluorometry

NASA Technical Reports Server (NTRS)

Cruce, Tommy Clay (Inventor); Hallidy, William H. (Inventor); Chin, Robert C. (Inventor)

2007-01-01

The present invention additionally comprises a method and apparatus for generating and mixing signals for frequency-domain lifetime and spectral fluorometry. The present invention comprises a plurality of signal generators that generate a plurality of signals where the signal generators modulate the amplitude and/or the frequency of the signals. The present invention uses one of these signals to drive an excitation signal that the present invention then directs and transmits at a target mixture, which absorbs the energy from the excitation signal. The property of fluorescence causes the target mixture to emit an emitted signal that the present invention detects with a signal detector. The present invention uses a plurality of mixers to produce a processor reference signal and a data signal. The present invention then uses a processor to compare the processor reference signal with the data signal by analyzing the differences in the phase and the differences in the amplitude between the two signals. The processor then extracts the fluorescence lifetime and fluorescence spectrum of the emitted signal from the phase and amplitude information using a chemometric analysis.

Singular value decomposition based feature extraction technique for physiological signal analysis.

PubMed

Chang, Cheng-Ding; Wang, Chien-Chih; Jiang, Bernard C

2012-06-01

Multiscale entropy (MSE) is one of the popular techniques to calculate and describe the complexity of the physiological signal. Many studies use this approach to detect changes in the physiological conditions in the human body. However, MSE results are easily affected by noise and trends, leading to incorrect estimation of MSE values. In this paper, singular value decomposition (SVD) is adopted to replace MSE to extract the features of physiological signals, and adopt the support vector machine (SVM) to classify the different physiological states. A test data set based on the PhysioNet website was used, and the classification results showed that using SVD to extract features of the physiological signal could attain a classification accuracy rate of 89.157%, which is higher than that using the MSE value (71.084%). The results show the proposed analysis procedure is effective and appropriate for distinguishing different physiological states. This promising result could be used as a reference for doctors in diagnosis of congestive heart failure (CHF) disease.

Frequency stabilization for multilocation optical FDM networks

NASA Astrophysics Data System (ADS)

Jiang, Quan; Kavehrad, Mohsen

1993-04-01

In a multi-location optical FDM network, the frequency of each user's transmitter can be offset-locked, through a Fabry-Perot, to an absolute frequency standard which is distributed to the users. To lock the local Fabry-Perot to the frequency standard, the standard has to be frequency-dithered by a sinusoidal signal and the sinusoidal reference has to be transmitted to the user location since the lock-in amplifier in the stabilization system requires the reference for synchronous detection. We proposed two solutions to avoid transmitting the reference. One uses an extraction circuit to obtain the sinusoidal signal from the incoming signal. A nonlinear circuit following the photodiode produces a strong second-order harmonic of the sinusoidal signal and a phase-locked loop is locked to it. The sinusoidal reference is obtained by a divide- by-2 circuit. The phase ambiguity (0 degree(s) or 180 degree(s)) is resolved by using a selection- circuit and an initial scan. The other method uses a pseudo-random sequence instead of a sinusoidal signal to dither the frequency standard and a surface-acoustic-wave (SAW) matched-filter instead of a lock-in amplifier to obtain the frequency error. The matched-filter serves as a correlator and does not require the dither reference.

Reference-based source separation method for identification of brain regions involved in a reference state from intracerebral EEG

PubMed Central

Samadi, Samareh; Amini, Ladan; Cosandier-Rimélé, Delphine; Soltanian-Zadeh, Hamid; Jutten, Christian

2013-01-01

In this paper, we present a fast method to extract the sources related to interictal epileptiform state. The method is based on general eigenvalue decomposition using two correlation matrices during: 1) periods including interictal epileptiform discharges (IED) as a reference activation model and 2) periods excluding IEDs or abnormal physiological signals as background activity. After extracting the most similar sources to the reference or IED state, IED regions are estimated by using multiobjective optimization. The method is evaluated using both realistic simulated data and actual intracerebral electroencephalography recordings of patients suffering from focal epilepsy. These patients are seizure-free after the resective surgery. Quantitative comparisons of the proposed IED regions with the visually inspected ictal onset zones by the epileptologist and another method of identification of IED regions reveal good performance. PMID:23428609

A simple iterative independent component analysis algorithm for vibration source signal identification of complex structures

NASA Astrophysics Data System (ADS)

Lee, Dong-Sup; Cho, Dae-Seung; Kim, Kookhyun; Jeon, Jae-Jin; Jung, Woo-Jin; Kang, Myeng-Hwan; Kim, Jae-Ho

2015-01-01

Independent Component Analysis (ICA), one of the blind source separation methods, can be applied for extracting unknown source signals only from received signals. This is accomplished by finding statistical independence of signal mixtures and has been successfully applied to myriad fields such as medical science, image processing, and numerous others. Nevertheless, there are inherent problems that have been reported when using this technique: instability and invalid ordering of separated signals, particularly when using a conventional ICA technique in vibratory source signal identification of complex structures. In this study, a simple iterative algorithm of the conventional ICA has been proposed to mitigate these problems. The proposed method to extract more stable source signals having valid order includes an iterative and reordering process of extracted mixing matrix to reconstruct finally converged source signals, referring to the magnitudes of correlation coefficients between the intermediately separated signals and the signals measured on or nearby sources. In order to review the problems of the conventional ICA technique and to validate the proposed method, numerical analyses have been carried out for a virtual response model and a 30 m class submarine model. Moreover, in order to investigate applicability of the proposed method to real problem of complex structure, an experiment has been carried out for a scaled submarine mockup. The results show that the proposed method could resolve the inherent problems of a conventional ICA technique.

[Study on the experimental application of floating-reference method to noninvasive blood glucose sensing].

PubMed

Yu, Hui; Qi, Dan; Li, Heng-da; Xu, Ke-xin; Yuan, Wei-jie

2012-03-01

Weak signal, low instrument signal-to-noise ratio, continuous variation of human physiological environment and the interferences from other components in blood make it difficult to extract the blood glucose information from near infrared spectrum in noninvasive blood glucose measurement. The floating-reference method, which analyses the effect of glucose concentration variation on absorption coefficient and scattering coefficient, gets spectrum at the reference point and the measurement point where the light intensity variations from absorption and scattering are counteractive and biggest respectively. By using the spectrum from reference point as reference, floating-reference method can reduce the interferences from variation of physiological environment and experiment circumstance. In the present paper, the effectiveness of floating-reference method working on improving prediction precision and stability was assessed through application experiments. The comparison was made between models whose data were processed with and without floating-reference method. The results showed that the root mean square error of prediction (RMSEP) decreased by 34.7% maximally. The floating-reference method could reduce the influences of changes of samples' state, instrument noises and drift, and improve the models' prediction precision and stability effectively.

Nonlinear ultrasonic wave modulation for online fatigue crack detection

NASA Astrophysics Data System (ADS)

Sohn, Hoon; Lim, Hyung Jin; DeSimio, Martin P.; Brown, Kevin; Derriso, Mark

2014-02-01

This study presents a fatigue crack detection technique using nonlinear ultrasonic wave modulation. Ultrasonic waves at two distinctive driving frequencies are generated and corresponding ultrasonic responses are measured using permanently installed lead zirconate titanate (PZT) transducers with a potential for continuous monitoring. Here, the input signal at the lower driving frequency is often referred to as a 'pumping' signal, and the higher frequency input is referred to as a 'probing' signal. The presence of a system nonlinearity, such as a crack formation, can provide a mechanism for nonlinear wave modulation, and create spectral sidebands around the frequency of the probing signal. A signal processing technique combining linear response subtraction (LRS) and synchronous demodulation (SD) is developed specifically to extract the crack-induced spectral sidebands. The proposed crack detection method is successfully applied to identify actual fatigue cracks grown in metallic plate and complex fitting-lug specimens. Finally, the effect of pumping and probing frequencies on the amplitude of the first spectral sideband is investigated using the first sideband spectrogram (FSS) obtained by sweeping both pumping and probing signals over specified frequency ranges.

Digital PCM bit synchronizer and detector

NASA Astrophysics Data System (ADS)

Moghazy, A. E.; Maral, G.; Blanchard, A.

1980-08-01

A theoretical analysis of a digital self-bit synchronizer and detector is presented and supported by the implementation of an experimental model that utilizes standard TTL logic circuits. This synchronizer is based on the generation of spectral line components by nonlinear filtering of the received bit stream, and extracting the line by a digital phase-locked loop (DPLL). The extracted reference signal instructs a digital matched filter (DMF) data detector. This realization features a short acquisition time and an all-digital structure.

Kmeans-ICA based automatic method for ocular artifacts removal in a motorimagery classification.

PubMed

Bou Assi, Elie; Rihana, Sandy; Sawan, Mohamad

2014-01-01

Electroencephalogram (EEG) recordings aroused as inputs of a motor imagery based BCI system. Eye blinks contaminate the spectral frequency of the EEG signals. Independent Component Analysis (ICA) has been already proved for removing these artifacts whose frequency band overlap with the EEG of interest. However, already ICA developed methods, use a reference lead such as the ElectroOculoGram (EOG) to identify the ocular artifact components. In this study, artifactual components were identified using an adaptive thresholding by means of Kmeans clustering. The denoised EEG signals have been fed into a feature extraction algorithm extracting the band power, the coherence and the phase locking value and inserted into a linear discriminant analysis classifier for a motor imagery classification.

Robust real-time extraction of respiratory signals from PET list-mode data

NASA Astrophysics Data System (ADS)

Salomon, André; Zhang, Bin; Olivier, Patrick; Goedicke, Andreas

2018-06-01

Respiratory motion, which typically cannot simply be suspended during PET image acquisition, affects lesions’ detection and quantitative accuracy inside or in close vicinity to the lungs. Some motion compensation techniques address this issue via pre-sorting (‘binning’) of the acquired PET data into a set of temporal gates, where each gate is assumed to be minimally affected by respiratory motion. Tracking respiratory motion is typically realized using dedicated hardware (e.g. using respiratory belts and digital cameras). Extracting respiratory signals directly from the acquired PET data simplifies the clinical workflow as it avoids handling additional signal measurement equipment. We introduce a new data-driven method ‘combined local motion detection’ (CLMD). It uses the time-of-flight (TOF) information provided by state-of-the-art PET scanners in order to enable real-time respiratory signal extraction without additional hardware resources. CLMD applies center-of-mass detection in overlapping regions based on simple back-positioned TOF event sets acquired in short time frames. Following a signal filtering and quality-based pre-selection step, the remaining extracted individual position information over time is then combined to generate a global respiratory signal. The method is evaluated using seven measured FDG studies from single and multiple scan positions of the thorax region, and it is compared to other software-based methods regarding quantitative accuracy and statistical noise stability. Correlation coefficients around 90% between the reference and the extracted signal have been found for those PET scans where motion affected features such as tumors or hot regions were present in the PET field-of-view. For PET scans with a quarter of typically applied radiotracer doses, the CLMD method still provides similar high correlation coefficients which indicates its robustness to noise. Each CLMD processing needed less than 0.4 s in total on a standard multi-core CPU and thus provides a robust and accurate approach enabling real-time processing capabilities using standard PC hardware.

Ionospheric Profiling Through Nonlinear Dielectric Response to Electron Density*

NASA Astrophysics Data System (ADS)

Moses, R. W.; Jacobson, A. R.

2002-12-01

It is well known that the total electron content (TEC) along a line of sight in the ionosphere can be extracted from the frequency-dependent time lag measured in transionospheric RF signals [1]. For five years the FORTE satellite has been used to develop a substantial data base of transionospheric signals originating in both lightning and man-made sources. Here, we use signals generated by the Los Alamos Portable Pulser (LAPP) [2] and recorded by FORTE as input to a multi-layer computer model of RF wave propagation in the ionosphere, including Faraday rotation in the Earth's magnetic field. Nonlinearities in both the frequency dependence of the group velocity and the optical pathlength are modeled and matched to FORTE data to infer details of the vertical profile of electron density. Using the International Reference Ionosphere [3] as a profile model, we show how the vertical TEC, peak electron density, and ionospheric thickness can be extracted even at large transmitter-to-satellite separations. [1] Roussel-Dupre, R. A., A. R. Jacobson, and L. A. Triplett, Radio Sci., 36, 1615 (2001). [2] Massey, R.S., S.O. Knox, R.C. Franz, D.N. Holden, and C.T. Rhodes, Radio Sci., 33, 1739 (1998). [3] Bilitza, D., "International Reference Ionosphere 1990," NSSDC/WDC-A-R&S 90-92. *Work supported by USDOE

Global 21 cm Signal Extraction from Foreground and Instrumental Effects. I. Pattern Recognition Framework for Separation Using Training Sets

NASA Astrophysics Data System (ADS)

Tauscher, Keith; Rapetti, David; Burns, Jack O.; Switzer, Eric

2018-02-01

The sky-averaged (global) highly redshifted 21 cm spectrum from neutral hydrogen is expected to appear in the VHF range of ∼20–200 MHz and its spectral shape and strength are determined by the heating properties of the first stars and black holes, by the nature and duration of reionization, and by the presence or absence of exotic physics. Measurements of the global signal would therefore provide us with a wealth of astrophysical and cosmological knowledge. However, the signal has not yet been detected because it must be seen through strong foregrounds weighted by a large beam, instrumental calibration errors, and ionospheric, ground, and radio-frequency-interference effects, which we collectively refer to as “systematics.” Here, we present a signal extraction method for global signal experiments which uses Singular Value Decomposition of “training sets” to produce systematics basis functions specifically suited to each observation. Instead of requiring precise absolute knowledge of the systematics, our method effectively requires precise knowledge of how the systematics can vary. After calculating eigenmodes for the signal and systematics, we perform a weighted least square fit of the corresponding coefficients and select the number of modes to include by minimizing an information criterion. We compare the performance of the signal extraction when minimizing various information criteria and find that minimizing the Deviance Information Criterion most consistently yields unbiased fits. The methods used here are built into our widely applicable, publicly available Python package, pylinex, which analytically calculates constraints on signals and systematics from given data, errors, and training sets.

Biosensor method and system based on feature vector extraction

DOEpatents

Greenbaum, Elias; Rodriguez, Jr., Miguel; Qi, Hairong; Wang, Xiaoling

2013-07-02

A system for biosensor-based detection of toxins includes providing at least one time-dependent control signal generated by a biosensor in a gas or liquid medium, and obtaining a time-dependent biosensor signal from the biosensor in the gas or liquid medium to be monitored or analyzed for the presence of one or more toxins selected from chemical, biological or radiological agents. The time-dependent biosensor signal is processed to obtain a plurality of feature vectors using at least one of amplitude statistics and a time-frequency analysis. At least one parameter relating to toxicity of the gas or liquid medium is then determined from the feature vectors based on reference to the control signal.

Leveraging Pattern Semantics for Extracting Entities in Enterprises

PubMed Central

Tao, Fangbo; Zhao, Bo; Fuxman, Ariel; Li, Yang; Han, Jiawei

2015-01-01

Entity Extraction is a process of identifying meaningful entities from text documents. In enterprises, extracting entities improves enterprise efficiency by facilitating numerous applications, including search, recommendation, etc. However, the problem is particularly challenging on enterprise domains due to several reasons. First, the lack of redundancy of enterprise entities makes previous web-based systems like NELL and OpenIE not effective, since using only high-precision/low-recall patterns like those systems would miss the majority of sparse enterprise entities, while using more low-precision patterns in sparse setting also introduces noise drastically. Second, semantic drift is common in enterprises (“Blue” refers to “Windows Blue”), such that public signals from the web cannot be directly applied on entities. Moreover, many internal entities never appear on the web. Sparse internal signals are the only source for discovering them. To address these challenges, we propose an end-to-end framework for extracting entities in enterprises, taking the input of enterprise corpus and limited seeds to generate a high-quality entity collection as output. We introduce the novel concept of Semantic Pattern Graph to leverage public signals to understand the underlying semantics of lexical patterns, reinforce pattern evaluation using mined semantics, and yield more accurate and complete entities. Experiments on Microsoft enterprise data show the effectiveness of our approach. PMID:26705540

Leveraging Pattern Semantics for Extracting Entities in Enterprises.

PubMed

Tao, Fangbo; Zhao, Bo; Fuxman, Ariel; Li, Yang; Han, Jiawei

2015-05-01

Entity Extraction is a process of identifying meaningful entities from text documents. In enterprises, extracting entities improves enterprise efficiency by facilitating numerous applications, including search, recommendation, etc. However, the problem is particularly challenging on enterprise domains due to several reasons. First, the lack of redundancy of enterprise entities makes previous web-based systems like NELL and OpenIE not effective, since using only high-precision/low-recall patterns like those systems would miss the majority of sparse enterprise entities, while using more low-precision patterns in sparse setting also introduces noise drastically. Second, semantic drift is common in enterprises ("Blue" refers to "Windows Blue"), such that public signals from the web cannot be directly applied on entities. Moreover, many internal entities never appear on the web. Sparse internal signals are the only source for discovering them. To address these challenges, we propose an end-to-end framework for extracting entities in enterprises, taking the input of enterprise corpus and limited seeds to generate a high-quality entity collection as output. We introduce the novel concept of Semantic Pattern Graph to leverage public signals to understand the underlying semantics of lexical patterns, reinforce pattern evaluation using mined semantics, and yield more accurate and complete entities. Experiments on Microsoft enterprise data show the effectiveness of our approach.

Analog CMOS design for optical coherence tomography signal detection and processing.

PubMed

Xu, Wei; Mathine, David L; Barton, Jennifer K

2008-02-01

A CMOS circuit was designed and fabricated for optical coherence tomography (OCT) signal detection and processing. The circuit includes a photoreceiver, differential gain stage and lock-in amplifier based demodulator. The photoreceiver consists of a CMOS photodetector and low noise differential transimpedance amplifier which converts the optical interference signal into a voltage. The differential gain stage further amplifies the signal. The in-phase and quadrature channels of the lock-in amplifier each include an analog mixer and switched-capacitor low-pass filter with an external mixer reference signal. The interferogram envelope and phase can be extracted with this configuration, enabling Doppler OCT measurements. A sensitivity of -80 dB is achieved with faithful reproduction of the interferometric signal envelope. A sample image of finger tip is presented.

Extraction of the respiratory signal from small-animal CT projections for a retrospective gating method

NASA Astrophysics Data System (ADS)

Chavarrías, C.; Vaquero, J. J.; Sisniega, A.; Rodríguez-Ruano, A.; Soto-Montenegro, M. L.; García-Barreno, P.; Desco, M.

2008-09-01

We propose a retrospective respiratory gating algorithm to generate dynamic CT studies. To this end, we compared three different methods of extracting the respiratory signal from the projections of small-animal cone-beam computed tomography (CBCT) scanners. Given a set of frames acquired from a certain axial angle, subtraction of their average image from each individual frame produces a set of difference images. Pixels in these images have positive or negative values (according to the respiratory phase) in those areas where there is lung movement. The respiratory signals were extracted by analysing the shape of the histogram of these difference images: we calculated the first four central and non-central moments. However, only odd-order moments produced the desired breathing signal, as the even-order moments lacked information about the phase. Each of these curves was compared to a reference signal recorded by means of a pneumatic pillow. Given the similar correlation coefficients yielded by all of them, we selected the mean to implement our retrospective protocol. Respiratory phase bins were separated, reconstructed independently and included in a dynamic sequence, suitable for cine playback. We validated our method in five adult rat studies by comparing profiles drawn across the diaphragm dome, with and without retrospective respiratory gating. Results showed a sharper transition in the gated reconstruction, with an average slope improvement of 60.7%.

Spatiotemporal signal space separation method for rejecting nearby interference in MEG measurements

NASA Astrophysics Data System (ADS)

Taulu, S.; Simola, J.

2006-04-01

Limitations of traditional magnetoencephalography (MEG) exclude some important patient groups from MEG examinations, such as epilepsy patients with a vagus nerve stimulator, patients with magnetic particles on the head or having magnetic dental materials that cause severe movement-related artefact signals. Conventional interference rejection methods are not able to remove the artefacts originating this close to the MEG sensor array. For example, the reference array method is unable to suppress interference generated by sources closer to the sensors than the reference array, about 20-40 cm. The spatiotemporal signal space separation method proposed in this paper recognizes and removes both external interference and the artefacts produced by these nearby sources, even on the scalp. First, the basic separation into brain-related and external interference signals is accomplished with signal space separation based on sensor geometry and Maxwell's equations only. After this, the artefacts from nearby sources are extracted by a simple statistical analysis in the time domain, and projected out. Practical examples with artificial current dipoles and interference sources as well as data from real patients demonstrate that the method removes the artefacts without altering the field patterns of the brain signals.

Robust real-time extraction of respiratory signals from PET list-mode data.

PubMed

Salomon, Andre; Zhang, Bin; Olivier, Patrick; Goedicke, Andreas

2018-05-01

Respiratory motion, which typically cannot simply be suspended during PET image acquisition, affects lesions' detection and quantitative accuracy inside or in close vicinity to the lungs. Some motion compensation techniques address this issue via pre-sorting ("binning") of the acquired PET data into a set of temporal gates, where each gate is assumed to be minimally affected by respiratory motion. Tracking respiratory motion is typically realized using dedicated hardware (e.g. using respiratory belts and digital cameras). Extracting respiratory signalsdirectly from the acquired PET data simplifies the clinical workflow as it avoids to handle additional signal measurement equipment. We introduce a new data-driven method "Combined Local Motion Detection" (CLMD). It uses the Time-of-Flight (TOF) information provided by state-of-the-art PET scanners in order to enable real-time respiratory signal extraction without additional hardware resources. CLMD applies center-of-mass detection in overlapping regions based on simple back-positioned TOF event sets acquired in short time frames. Following a signal filtering and quality-based pre-selection step, the remaining extracted individual position information over time is then combined to generate a global respiratory signal. The method is evaluated using 7 measured FDG studies from single and multiple scan positions of the thorax region, and it is compared to other software-based methods regarding quantitative accuracy and statistical noise stability. Correlation coefficients around 90% between the reference and the extracted signal have been found for those PET scans where motion affected features such as tumors or hot regions were present in the PET field-of-view. For PET scans with a quarter of typically applied radiotracer doses, the CLMD method still provides similar high correlation coefficients which indicates its robustness to noise. Each CLMD processing needed less than 0.4s in total on a standard multi-core CPU and thus provides a robust and accurate approach enabling real-time processing capabilities using standard PC hardware. © 2018 Institute of Physics and Engineering in Medicine.

An adaptive Kalman filter approach for cardiorespiratory signal extraction and fusion of non-contacting sensors

PubMed Central

2014-01-01

Background Extracting cardiorespiratory signals from non-invasive and non-contacting sensor arrangements, i.e. magnetic induction sensors, is a challenging task. The respiratory and cardiac signals are mixed on top of a large and time-varying offset and are likely to be disturbed by measurement noise. Basic filtering techniques fail to extract relevant information for monitoring purposes. Methods We present a real-time filtering system based on an adaptive Kalman filter approach that separates signal offsets, respiratory and heart signals from three different sensor channels. It continuously estimates respiration and heart rates, which are fed back into the system model to enhance performance. Sensor and system noise covariance matrices are automatically adapted to the aimed application, thus improving the signal separation capabilities. We apply the filtering to two different subjects with different heart rates and sensor properties and compare the results to the non-adaptive version of the same Kalman filter. Also, the performance, depending on the initialization of the filters, is analyzed using three different configurations ranging from best to worst case. Results Extracted data are compared with reference heart rates derived from a standard pulse-photoplethysmographic sensor and respiration rates from a flowmeter. In the worst case for one of the subjects the adaptive filter obtains mean errors (standard deviations) of -0.2 min −1 (0.3 min −1) and -0.7 bpm (1.7 bpm) (compared to -0.2 min −1 (0.4 min −1) and 42.0 bpm (6.1 bpm) for the non-adaptive filter) for respiration and heart rate, respectively. In bad conditions the heart rate is only correctly measurable when the Kalman matrices are adapted to the target sensor signals. Also, the reduced mean error between the extracted offset and the raw sensor signal shows that adapting the Kalman filter continuously improves the ability to separate the desired signals from the raw sensor data. The average total computational time needed for the Kalman filters is under 25% of the total signal length rendering it possible to perform the filtering in real-time. Conclusions It is possible to measure in real-time heart and breathing rates using an adaptive Kalman filter approach. Adapting the Kalman filter matrices improves the estimation results and makes the filter universally deployable when measuring cardiorespiratory signals. PMID:24886253

An adaptive Kalman filter approach for cardiorespiratory signal extraction and fusion of non-contacting sensors.

PubMed

Foussier, Jerome; Teichmann, Daniel; Jia, Jing; Misgeld, Berno; Leonhardt, Steffen

2014-05-09

Extracting cardiorespiratory signals from non-invasive and non-contacting sensor arrangements, i.e. magnetic induction sensors, is a challenging task. The respiratory and cardiac signals are mixed on top of a large and time-varying offset and are likely to be disturbed by measurement noise. Basic filtering techniques fail to extract relevant information for monitoring purposes. We present a real-time filtering system based on an adaptive Kalman filter approach that separates signal offsets, respiratory and heart signals from three different sensor channels. It continuously estimates respiration and heart rates, which are fed back into the system model to enhance performance. Sensor and system noise covariance matrices are automatically adapted to the aimed application, thus improving the signal separation capabilities. We apply the filtering to two different subjects with different heart rates and sensor properties and compare the results to the non-adaptive version of the same Kalman filter. Also, the performance, depending on the initialization of the filters, is analyzed using three different configurations ranging from best to worst case. Extracted data are compared with reference heart rates derived from a standard pulse-photoplethysmographic sensor and respiration rates from a flowmeter. In the worst case for one of the subjects the adaptive filter obtains mean errors (standard deviations) of -0.2 min(-1) (0.3 min(-1)) and -0.7 bpm (1.7 bpm) (compared to -0.2 min(-1) (0.4 min(-1)) and 42.0 bpm (6.1 bpm) for the non-adaptive filter) for respiration and heart rate, respectively. In bad conditions the heart rate is only correctly measurable when the Kalman matrices are adapted to the target sensor signals. Also, the reduced mean error between the extracted offset and the raw sensor signal shows that adapting the Kalman filter continuously improves the ability to separate the desired signals from the raw sensor data. The average total computational time needed for the Kalman filters is under 25% of the total signal length rendering it possible to perform the filtering in real-time. It is possible to measure in real-time heart and breathing rates using an adaptive Kalman filter approach. Adapting the Kalman filter matrices improves the estimation results and makes the filter universally deployable when measuring cardiorespiratory signals.

Phase shifting diffraction interferometer

DOEpatents

Sommargren, Gary E.

1996-01-01

An interferometer which has the capability of measuring optical elements and systems with an accuracy of .lambda./1000 where .lambda. is the wavelength of visible light. Whereas current interferometers employ a reference surface, which inherently limits the accuracy of the measurement to about .lambda./50, this interferometer uses an essentially perfect spherical reference wavefront generated by the fundamental process of diffraction. This interferometer is adjustable to give unity fringe visibility, which maximizes the signal-to-noise, and has the means to introduce a controlled prescribed relative phase shift between the reference wavefront and the wavefront from the optics under test, which permits analysis of the interference fringe pattern using standard phase extraction algorithms.

Phase shifting diffraction interferometer

DOEpatents

Sommargren, G.E.

1996-08-29

An interferometer which has the capability of measuring optical elements and systems with an accuracy of {lambda}/1000 where {lambda} is the wavelength of visible light. Whereas current interferometers employ a reference surface, which inherently limits the accuracy of the measurement to about {lambda}/50, this interferometer uses an essentially perfect spherical reference wavefront generated by the fundamental process of diffraction. This interferometer is adjustable to give unity fringe visibility, which maximizes the signal-to-noise, and has the means to introduce a controlled prescribed relative phase shift between the reference wavefront and the wavefront from the optics under test, which permits analysis of the interference fringe pattern using standard phase extraction algorithms. 8 figs.

40 CFR Appendix G to Part 50 - Reference Method for the Determination of Lead in Total Suspended Particulate Matter

Code of Federal Regulations, 2014 CFR

2014-07-01

... Study of Procedures Evaluated by the Federal Advisory Committee on Detection and Quantitation Approaches... placed in a heated ultrasonic bath for one hour to facilitate the extraction of Pb. Following... the summation of signal intensities for the isotopic masses 206, 207, and 208. In most cases, the...

Method and apparatus for sensorless operation of brushless permanent magnet motors

DOEpatents

Sriram, Tillasthanam V.

1998-01-01

A sensorless method and apparatus for providing commutation timing signals for a brushless permanent magnet motor extracts the third harmonic back-emf of a three-phase stator winding and independently cyclically integrates the positive and negative half-cycles thereof and compares the results to a reference level associated with a desired commutation angle.

Method and apparatus for sensorless operation of brushless permanent magnet motors

DOEpatents

Sriram, T.V.

1998-04-14

A sensorless method and apparatus for providing commutation timing signals for a brushless permanent magnet motor extracts the third harmonic back-emf of a three-phase stator winding and independently cyclically integrates the positive and negative half-cycles thereof and compares the results to a reference level associated with a desired commutation angle. 23 figs.

Response of a lock-in amplifier to noise

NASA Astrophysics Data System (ADS)

Van Baak, D. A.; Herold, George

2014-08-01

The "lock-in" detection technique can extract, from a possibly noisy waveform, the amplitude of a signal that is synchronous with a known reference signal. This paper examines the effects of input noise on the output of a lock-in amplifier. We present quantitative predictions for the root-mean-square size of the resulting fluctuations and for the spectral density of the noise at the output of a lock-in amplifier. Our results show how a lock-in amplifier can be used to measure the spectral density of noise in the case of a noise-only input signal. Some implications of the theory, familiar and surprising, are tested against experimental data.

Frequency-domain preprocessing and directional correlation-based feature extraction for classification of the buried objects using GPR B-scan data

NASA Astrophysics Data System (ADS)

Bahadirlar, Yildirim; Kaplan, Gulay B.

2004-09-01

A new preprocessing and feature extracting approach for classification of non-metallic buried objects are aimed using GPR B-scan data. A frequency-domain adaptive filter without a reference channel effectively removes the background signal resulting mostly from the discontinuity on the air-to-ground path of the electromagnetic waves. The filter only needs average of the first five A-scans as the reference signal for this elimination, and also serves for masking of the B-scan in the frequency-domain. A preprocessed GPR data with significantly suppressed clutter is then obtained by precisely positioning the Hanning window in the frequency-domain. A directional correlation function defined over a B-scan frame gives distinctive curves of buried objects. The main axis of directional correlation, on which the pivotal correlating pixels and short lines of pixels being correlated are considered, makes an angle to the scanning direction of the B-scan. This form of correlation is applied to the frame from the left-hand and the right-hand side and two over-plotted curves are obtained. Nine measures as features emphasizing directional signatures are extracted from these curves. Nine-element feature vectors are applied to the two-layer Artificial Neural Network and preliminary results over test set are promising to continue to comprehensive training and testing processes.

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.

Robust Averaging of Covariances for EEG Recordings Classification in Motor Imagery Brain-Computer Interfaces.

PubMed

Uehara, Takashi; Sartori, Matteo; Tanaka, Toshihisa; Fiori, Simone

2017-06-01

The estimation of covariance matrices is of prime importance to analyze the distribution of multivariate signals. In motor imagery-based brain-computer interfaces (MI-BCI), covariance matrices play a central role in the extraction of features from recorded electroencephalograms (EEGs); therefore, correctly estimating covariance is crucial for EEG classification. This letter discusses algorithms to average sample covariance matrices (SCMs) for the selection of the reference matrix in tangent space mapping (TSM)-based MI-BCI. Tangent space mapping is a powerful method of feature extraction and strongly depends on the selection of a reference covariance matrix. In general, the observed signals may include outliers; therefore, taking the geometric mean of SCMs as the reference matrix may not be the best choice. In order to deal with the effects of outliers, robust estimators have to be used. In particular, we discuss and test the use of geometric medians and trimmed averages (defined on the basis of several metrics) as robust estimators. The main idea behind trimmed averages is to eliminate data that exhibit the largest distance from the average covariance calculated on the basis of all available data. The results of the experiments show that while the geometric medians show little differences from conventional methods in terms of classification accuracy in the classification of electroencephalographic recordings, the trimmed averages show significant improvement for all subjects.

Biosensor method and system based on feature vector extraction

DOEpatents

Greenbaum, Elias [Knoxville, TN; Rodriguez, Jr., Miguel; Qi, Hairong [Knoxville, TN; Wang, Xiaoling [San Jose, CA

2012-04-17

A method of biosensor-based detection of toxins comprises the steps of providing at least one time-dependent control signal generated by a biosensor in a gas or liquid medium, and obtaining a time-dependent biosensor signal from the biosensor in the gas or liquid medium to be monitored or analyzed for the presence of one or more toxins selected from chemical, biological or radiological agents. The time-dependent biosensor signal is processed to obtain a plurality of feature vectors using at least one of amplitude statistics and a time-frequency analysis. At least one parameter relating to toxicity of the gas or liquid medium is then determined from the feature vectors based on reference to the control signal.

Removal of BCG artefact from concurrent fMRI-EEG recordings based on EMD and PCA.

PubMed

Javed, Ehtasham; Faye, Ibrahima; Malik, Aamir Saeed; Abdullah, Jafri Malin

2017-11-01

Simultaneous electroencephalography (EEG) and functional magnetic resonance image (fMRI) acquisitions provide better insight into brain dynamics. Some artefacts due to simultaneous acquisition pose a threat to the quality of the data. One such problematic artefact is the ballistocardiogram (BCG) artefact. We developed a hybrid algorithm that combines features of empirical mode decomposition (EMD) with principal component analysis (PCA) to reduce the BCG artefact. The algorithm does not require extra electrocardiogram (ECG) or electrooculogram (EOG) recordings to extract the BCG artefact. The method was tested with both simulated and real EEG data of 11 participants. From the simulated data, the similarity index between the extracted BCG and the simulated BCG showed the effectiveness of the proposed method in BCG removal. On the other hand, real data were recorded with two conditions, i.e. resting state (eyes closed dataset) and task influenced (event-related potentials (ERPs) dataset). Using qualitative (visual inspection) and quantitative (similarity index, improved normalized power spectrum (INPS) ratio, power spectrum, sample entropy (SE)) evaluation parameters, the assessment results showed that the proposed method can efficiently reduce the BCG artefact while preserving the neuronal signals. Compared with conventional methods, namely, average artefact subtraction (AAS), optimal basis set (OBS) and combined independent component analysis and principal component analysis (ICA-PCA), the statistical analyses of the results showed that the proposed method has better performance, and the differences were significant for all quantitative parameters except for the power and sample entropy. The proposed method does not require any reference signal, prior information or assumption to extract the BCG artefact. It will be very useful in circumstances where the reference signal is not available. Copyright © 2017 Elsevier B.V. All rights reserved.

Noncontact measurement of heart rate using facial video illuminated under natural light and signal weighted analysis.

PubMed

Yan, Yonggang; Ma, Xiang; Yao, Lifeng; Ouyang, Jianfei

2015-01-01

Non-contact and remote measurements of vital physical signals are important for reliable and comfortable physiological self-assessment. We presented a novel optical imaging-based method to measure the vital physical signals. Using a digital camera and ambient light, the cardiovascular pulse waves were extracted better from human color facial videos correctly. And the vital physiological parameters like heart rate were measured using a proposed signal-weighted analysis method. The measured HRs consistent with those measured simultaneously with reference technologies (r=0.94, p<0.001 for HR). The results show that the imaging-based method is suitable for measuring the physiological parameters, and provide a reliable and comfortable measurement mode. The study lays a physical foundation for measuring multi-physiological parameters of human noninvasively.

Research on the fault diagnosis of bearing based on wavelet and demodulation

NASA Astrophysics Data System (ADS)

Li, Jiapeng; Yuan, Yu

2017-05-01

As a most commonly-used machine part, antifriction bearing is extensively used in mechanical equipment. Vibration signal analysis is one of the methods to monitor and diagnose the running status of antifriction bearings. Therefore, using wavelet analysis for demising is of great importance in the engineering practice. This paper firstly presented the basic theory of wavelet analysis to study the transformation, decomposition and reconstruction of wavelet. In addition, edition software LabVIEW was adopted to conduct wavelet and demodulation upon the vibration signal of antifriction bearing collected. With the combination of Hilbert envelop demodulation analysis, the fault character frequencies of the demised signal were extracted to conduct fault diagnosis analysis, which serves as a reference for the wavelet and demodulation of the vibration signal in engineering practice.

Extracts of Artocarpus communis Decrease α-Melanocyte Stimulating Hormone-Induced Melanogenesis through Activation of ERK and JNK Signaling Pathways

PubMed Central

Fu, Yi-Tzu; Lee, Chiang-Wen; Ko, Horng-Huey; Yen, Feng-Lin

2014-01-01

Artocarpus communis is an agricultural plant that is also used in folk medicine to prevent skin diseases, including acne and dermatitis. Extracts of A. communis have been used to effectively inhibit melanogenesis; however, the antimelanogenesis mechanism of these extracts has not yet been investigated. The present study utilized a cell-free tyrosinase assay as well as α-melanocyte stimulating hormone- (-MSH-) induced tyrosinase assay conducted in B16F10 cells, performed a cytotoxicity assay, and determined cellular melanin content to examine the effects of a methanolic extract of A. communis (ACM) and various organic partition fractions of A. communis on melanogenesis. In addition, we performed western blot analysis to elucidate the mechanism of their antimelanogenesis effect. Our results indicated that, except for the n-hexane extract, ACM and the various partition extracts at noncytotoxic concentrations effectively decreased melanin content and tyrosinase activity by downregulating microphthalmia-associated transcription factor (MITF) and phosphorylated cAMP response element-binding protein (p-CREB). Moreover, ACM and the partition fractions activated phosphorylation of extracellular signal-regulated kinase (ERK) and c-Jun N-terminal kinase (JNK) to inhibit the synthesis of MITF and finally to decrease melanin production. In conclusion, we suggest that noncytotoxic concentrations of ACM and the various partition fractions may be useful as references for developing skin-lighting agents for use in medicines or cosmetics. PMID:24737988

Beat-to-beat heart rate estimation fusing multimodal video and sensor data

PubMed Central

Antink, Christoph Hoog; Gao, Hanno; Brüser, Christoph; Leonhardt, Steffen

2015-01-01

Coverage and accuracy of unobtrusively measured biosignals are generally relatively low compared to clinical modalities. This can be improved by exploiting redundancies in multiple channels with methods of sensor fusion. In this paper, we demonstrate that two modalities, skin color variation and head motion, can be extracted from the video stream recorded with a webcam. Using a Bayesian approach, these signals are fused with a ballistocardiographic signal obtained from the seat of a chair with a mean absolute beat-to-beat estimation error below 25 milliseconds and an average coverage above 90% compared to an ECG reference. PMID:26309754

Beat-to-beat heart rate estimation fusing multimodal video and sensor data.

PubMed

Antink, Christoph Hoog; Gao, Hanno; Brüser, Christoph; Leonhardt, Steffen

2015-08-01

Coverage and accuracy of unobtrusively measured biosignals are generally relatively low compared to clinical modalities. This can be improved by exploiting redundancies in multiple channels with methods of sensor fusion. In this paper, we demonstrate that two modalities, skin color variation and head motion, can be extracted from the video stream recorded with a webcam. Using a Bayesian approach, these signals are fused with a ballistocardiographic signal obtained from the seat of a chair with a mean absolute beat-to-beat estimation error below 25 milliseconds and an average coverage above 90% compared to an ECG reference.

Investigations of the possibility of determination of thermal parameters of Si and SiGe samples based on the Photo Thermal Radiometry technique

NASA Astrophysics Data System (ADS)

Chrobak, Ł.; Maliński, M.

2018-03-01

This paper presents results of investigations of the possibility of determination of thermal parameters (thermal conductivity, thermal diffusivity) of silicon and silicon germanium crystals from the frequency characteristics of the Photo Thermal Radiometry (PTR) signal. The theoretical analysis of the influence of the mentioned parameters on the PTR signal has been presented and discussed. The values of the thermal and recombination parameters have been extracted from the fittings of the theoretical to experimental data. The presented approach uses the reference Si sample whose thermal and recombination parameters are known.

ICA-Based Imagined Conceptual Words Classification on EEG Signals.

PubMed

Imani, Ehsan; Pourmohammad, Ali; Bagheri, Mahsa; Mobasheri, Vida

2017-01-01

Independent component analysis (ICA) has been used for detecting and removing the eye artifacts conventionally. However, in this research, it was used not only for detecting the eye artifacts, but also for detecting the brain-produced signals of two conceptual danger and information category words. In this cross-sectional research, electroencephalography (EEG) signals were recorded using Micromed and 19-channel helmet devices in unipolar mode, wherein Cz electrode was selected as the reference electrode. In the first part of this research, the statistical community test case included four men and four women, who were 25-30 years old. In the designed task, three groups of traffic signs were considered, in which two groups referred to the concept of danger, and the third one referred to the concept of information. In the second part, the three volunteers, two men and one woman, who had the best results, were chosen from among eight participants. In the second designed task, direction arrows (up, down, left, and right) were used. For the 2/8 volunteers in the rest times, very high-power alpha waves were observed from the back of the head; however, in the thinking times, they were different. According to this result, alpha waves for changing the task from thinking to rest condition took at least 3 s for the two volunteers, and it was at most 5 s until they went to the absolute rest condition. For the 7/8 volunteers, the danger and information signals were well classified; these differences for the 5/8 volunteers were observed in the right hemisphere, and, for the other three volunteers, the differences were observed in the left hemisphere. For the second task, simulations showed that the best classification accuracies resulted when the time window was 2.5 s. In addition, it also showed that the features of the autoregressive (AR)-15 model coefficients were the best choices for extracting the features. For all the states of neural network except hardlim discriminator function, the classification accuracies were almost the same and not very different. Linear discriminant analysis (LDA) in comparison with the neural network yielded higher classification accuracies. ICA is a suitable algorithm for recognizing of the word's concept and its place in the brain. Achieved results from this experiment were the same compared with the results from other methods such as functional magnetic resonance imaging and methods based on the brain signals (EEG) in the vowel imagination and covert speech. Herein, the highest classification accuracy was obtained by extracting the target signal from the output of the ICA and extracting the features of coefficients AR model with time interval of 2.5 s. Finally, LDA resulted in the highest classification accuracy more than 60%.

Wnt pathway curation using automated natural language processing: combining statistical methods with partial and full parse for knowledge extraction.

PubMed

Santos, Carlos; Eggle, Daniela; States, David J

2005-04-15

Wnt signaling is a very active area of research with highly relevant publications appearing at a rate of more than one per day. Building and maintaining databases describing signal transduction networks is a time-consuming and demanding task that requires careful literature analysis and extensive domain-specific knowledge. For instance, more than 50 factors involved in Wnt signal transduction have been identified as of late 2003. In this work we describe a natural language processing (NLP) system that is able to identify references to biological interaction networks in free text and automatically assembles a protein association and interaction map. A 'gold standard' set of names and assertions was derived by manual scanning of the Wnt genes website (http://www.stanford.edu/~rnusse/wntwindow.html) including 53 interactions involved in Wnt signaling. This system was used to analyze a corpus of peer-reviewed articles related to Wnt signaling including 3369 Pubmed and 1230 full text papers. Names for key Wnt-pathway associated proteins and biological entities are identified using a chi-squared analysis of noun phrases over-represented in the Wnt literature as compared to the general signal transduction literature. Interestingly, we identified several instances where generic terms were used on the website when more specific terms occur in the literature, and one typographic error on the Wnt canonical pathway. Using the named entity list and performing an exhaustive assertion extraction of the corpus, 34 of the 53 interactions in the 'gold standard' Wnt signaling set were successfully identified (64% recall). In addition, the automated extraction found several interactions involving key Wnt-related molecules which were missing or different from those in the canonical diagram, and these were confirmed by manual review of the text. These results suggest that a combination of NLP techniques for information extraction can form a useful first-pass tool for assisting human annotation and maintenance of signal pathway databases. The pipeline software components are freely available on request to the authors. dstates@umich.edu http://stateslab.bioinformatics.med.umich.edu/software.html.

Method and apparatus for autonomous, in-receiver prediction of GNSS ephemerides

NASA Technical Reports Server (NTRS)

Bar-Sever, Yoaz E. (Inventor); Bertiger, William I. (Inventor)

2012-01-01

Methods and apparatus for autonomous in-receiver prediction of orbit and clock states of Global Navigation Satellite Systems (GNSS) are described. Only the GNSS broadcast message is used, without need for periodic externally-communicated information. Earth orientation information is extracted from the GNSS broadcast ephemeris. With the accurate estimation of the Earth orientation parameters it is possible to propagate the best-fit GNSS orbits forward in time in an inertial reference frame. Using the estimated Earth orientation parameters, the predicted orbits are then transformed into Earth-Centered-Earth-Fixed (ECEF) coordinates to be used to assist the GNSS receiver in the acquisition of the signals. GNSS satellite clock states are also extracted from the broadcast ephemeris and a parameterized model of clock behavior is fit to that data. The estimated modeled clocks are then propagated forward in time to enable, together with the predicted orbits, quicker GNSS signal acquisition.

EEG and MEG source localization using recursively applied (RAP) MUSIC

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

Mosher, J.C.; Leahy, R.M.

1996-12-31

The multiple signal characterization (MUSIC) algorithm locates multiple asynchronous dipolar sources from electroencephalography (EEG) and magnetoencephalography (MEG) data. A signal subspace is estimated from the data, then the algorithm scans a single dipole model through a three-dimensional head volume and computes projections onto this subspace. To locate the sources, the user must search the head volume for local peaks in the projection metric. Here we describe a novel extension of this approach which we refer to as RAP (Recursively APplied) MUSIC. This new procedure automatically extracts the locations of the sources through a recursive use of subspace projections, which usesmore » the metric of principal correlations as a multidimensional form of correlation analysis between the model subspace and the data subspace. The dipolar orientations, a form of `diverse polarization,` are easily extracted using the associated principal vectors.« less

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

Tang, Yanmei; Li, Xinli; Bai, Yan

The measurement of multiphase flow parameters is of great importance in a wide range of industries. In the measurement of multiphase, the signals from the sensors are extremely weak and often buried in strong background noise. It is thus desirable to develop effective signal processing techniques that can detect the weak signal from the sensor outputs. In this paper, two methods, i.e., lock-in-amplifier (LIA) and improved Duffing chaotic oscillator are compared to detect and process the weak signal. For sinusoidal signal buried in noise, the correlation detection with sinusoidal reference signal is simulated by using LIA. The improved Duffing chaoticmore » oscillator method, which based on the Wigner transformation, can restore the signal waveform and detect the frequency. Two methods are combined to detect and extract the weak signal. Simulation results show the effectiveness and accuracy of the proposed improved method. The comparative analysis shows that the improved Duffing chaotic oscillator method can restrain noise strongly since it is sensitive to initial conditions.« less

Microwave signal processing with photorefractive dynamic holography

NASA Astrophysics Data System (ADS)

Fotheringham, Edeline B.

Have you ever found yourself listening to the music playing from the closest stereo rather than to the bromidic (uninspiring) person speaking to you? Your ears receive information from two sources but your brain listens to only one. What if your cell phone could distinguish among signals sharing the same bandwidth too? There would be no "full" channels to stop you from placing or receiving a call. This thesis presents a nonlinear optical circuit capable of distinguishing uncorrelated signals that have overlapping temporal bandwidths. This so called autotuning filter is the size of a U.S. quarter dollar and requires less than 3 mW of optical power to operate. It is basically an oscillator in which the losses are compensated with dynamic holographic gain. The combination of two photorefractive crystals in the resonator governs the filter's winner-take-all dynamics through signal-competition for gain. This physical circuit extracts what is mathematically referred to as the largest principal component of its spatio-temporal input space. The circuit's practicality is demonstrated by its incorporation in an RF-photonic system. An unknown mixture of unknown microwave signals, received by an antenna array, constitutes the input to the system. The output electronically returns one of the original microwave signals. The front-end of the system down converts the 10 GHz microwave signals and amplifies them before the signals phase modulate optical beams. The optical carrier is suppressed from these beams so that it may not be considered as a signal itself to the autotuning filter. The suppression is achieved with two-beam coupling in a single photorefractive crystal. The filter extracts the more intense of the signals present on the carrier-suppressed input beams. The detection of the extracted signal restores the microwave signal to an electronic form. The system, without the receiving antenna array, is packaged in a 13 x 18 x 6″ briefcase. Its power consumption equals that of a regular 50 W household light bulb. The system was shipped to different parts of the country for real-time demonstrations of signal separation thus also validating its claim to robustness.

Accounting for phase drifts in SSVEP-based BCIs by means of biphasic stimulation.

PubMed

Wu, Hung-Yi; Lee, Po-Lei; Chang, Hsiang-Chih; Hsieh, Jen-Chuen

2011-05-01

This study proposes a novel biphasic stimulation technique to solve the issue of phase drifts in steady-state visual evoked potential (SSVEPs) in phase-tagged systems. Phase calibration was embedded in stimulus sequences using a biphasic flicker, which is driven by a sequence with alternating reference and phase-shift states. Nine subjects were recruited to participate in off-line and online tests. Signals were bandpass filtered and segmented by trigger signals into reference and phase-shift epochs. Frequency components of SSVEP in the reference and phase-shift epochs were extracted using the Fourier method with a 50% overlapped sliding window. The real and imaginary parts of the SSVEP frequency components were organized into complex vectors in each epoch. Hotelling's t-square test was used to determine the significances of nonzero mean vectors. The rejection of noisy data segments and the validation of gaze detections were made based on p values. The phase difference between the valid mean vectors of reference and phase-shift epochs was used to identify user's gazed targets in this system. Data showed an average information transfer rate of 44.55 and 38.21 bits/min in off-line and online tests, respectively. © 2011 IEEE

Full field vertical scanning in short coherence digital holographic microscope.

PubMed

Monemahghdoust, Zahra; Montfort, Frederic; Cuche, Etienne; Emery, Yves; Depeursinge, Christian; Moser, Christophe

2013-05-20

In Digital holography Microscopes (DHM) implemented in the so-called "off axis" configuration, the object and reference wave fronts are not co-planar but form an angle of a few degrees. This results into two main drawbacks. First, the contrast of the interference is not uniform spatially when the light source has low coherence. The interference contrast is optimal along a line, but decreases when moving away from it, resulting in a lower image quality. Second, the non-coplanarity between the coherence plane of both wavefronts impacts the coherence vertical scanning measurement mode: when the optical path difference between the signal and the reference beam is changed, the region of maximum interference contrast shifts laterally in the plane of the objective. This results in more complex calculations to extract the topography of the sample and requires scanning over a much larger vertical range, leading to a longer measurement time. We have previously shown that by placing a volume diffractive optical element (VDOE) in the reference arm, the wavefront can be made coplanar with the object wavefront and the image plane of the microscope objective, resulting in a uniform and optimal interferogram. In this paper, we demonstrate a vertical scanning speed improvement by an order of magnitude. Noise in the phase and intensity images caused by scattering and non-uniform diffraction in the VDOE is analyzed quantitatively. Five VDOEs were fabricated with an identical procedure. We observe that VDOEs introduce a small intensity non-uniformity in the reference beam which results in a 20% noise increase in the extracted phase image as compared to the noise in extracted phase image when the VDOE is removed. However, the VDOE has no impact on the temporal noise measured from extracted phase images.

Improving Signal-to-Noise Ratio in Scanning Transmission Electron Microscopy Energy-Dispersive X-Ray (STEM-EDX) Spectrum Images Using Single-Atomic-Column Cross-Correlation Averaging.

PubMed

Jeong, Jong Seok; Mkhoyan, K Andre

2016-06-01

Acquiring an atomic-resolution compositional map of crystalline specimens has become routine practice, thus opening possibilities for extracting subatomic information from such maps. A key challenge for achieving subatomic precision is the improvement of signal-to-noise ratio (SNR) of compositional maps. Here, we report a simple and reliable solution for achieving high-SNR energy-dispersive X-ray (EDX) spectroscopy spectrum images for individual atomic columns. The method is based on standard cross-correlation aided by averaging of single-column EDX maps with modifications in the reference image. It produces EDX maps with minimal specimen drift, beam drift, and scan distortions. Step-by-step procedures to determine a self-consistent reference map with a discussion on the reliability, stability, and limitations of the method are presented here.

Low-power hardware implementation of movement decoding for brain computer interface with reduced-resolution discrete cosine transform.

PubMed

Minho Won; Albalawi, Hassan; Xin Li; Thomas, Donald E

2014-01-01

This paper describes a low-power hardware implementation for movement decoding of brain computer interface. Our proposed hardware design is facilitated by two novel ideas: (i) an efficient feature extraction method based on reduced-resolution discrete cosine transform (DCT), and (ii) a new hardware architecture of dual look-up table to perform discrete cosine transform without explicit multiplication. The proposed hardware implementation has been validated for movement decoding of electrocorticography (ECoG) signal by using a Xilinx FPGA Zynq-7000 board. It achieves more than 56× energy reduction over a reference design using band-pass filters for feature extraction.

A combined cICA-EEMD analysis of EEG recordings from depressed or schizophrenic patients during olfactory stimulation

NASA Astrophysics Data System (ADS)

Götz, Th; Stadler, L.; Fraunhofer, G.; Tomé, A. M.; Hausner, H.; Lang, E. W.

2017-02-01

Objective. We propose a combination of a constrained independent component analysis (cICA) with an ensemble empirical mode decomposition (EEMD) to analyze electroencephalographic recordings from depressed or schizophrenic subjects during olfactory stimulation. Approach. EEMD serves to extract intrinsic modes (IMFs) underlying the recorded EEG time. The latter then serve as reference signals to extract the most similar underlying independent component within a constrained ICA. The extracted modes are further analyzed considering their power spectra. Main results. The analysis of the extracted modes reveals clear differences in the related power spectra between the disease characteristics of depressed and schizophrenic patients. Such differences appear in the high frequency γ-band in the intrinsic modes, but also in much more detail in the low frequency range in the α-, θ- and δ-bands. Significance. The proposed method provides various means to discriminate both disease pictures in a clinical environment.

[Recording and data processing of electrical signals of the specific atrioventricular conduction pathways in man].

PubMed

Héron, F; Mialet, G; Schuller, C; Breton, D; Perrin, J; Degeorges, M

1979-01-01

Signals of the electrical activity of the specific atrioventricular conduction pathways were recorded with an unipolar lead to obtain an exact time reference. The amplifier used had special characteristics: high gain settings (up to 300,000), very low noise levels, and wide filter range (2 Hz - 1,600 Hz). The low amplitude of the signals under study, of the order of a microvolt, and the wide filter range of the amplifier necessitated placing the patient in a Faraday cage. The signals recorded on magnetic tape were treated by a system of analysis for signal treatment. The method of averaging was used to extract the signal from background noise especially that arising from somatic muscle. The amplitude of the Hisian signal was much larger than that usually obtained with other methods. The intervals were determined with precision of the order of 1 millisecond. Frequential analysis of the signals gave another representation of the information contained in the time signals. This new representation seems to give better discrimination of the different zones of activation of the specific atrioventricular conduction pathways.

A Signal Processing Module for the Analysis of Heart Sounds and Heart Murmurs

NASA Astrophysics Data System (ADS)

Javed, Faizan; Venkatachalam, P. A.; H, Ahmad Fadzil M.

2006-04-01

In this paper a Signal Processing Module (SPM) for the computer-aided analysis of heart sounds has been developed. The module reveals important information of cardiovascular disorders and can assist general physician to come up with more accurate and reliable diagnosis at early stages. It can overcome the deficiency of expert doctors in rural as well as urban clinics and hospitals. The module has five main blocks: Data Acquisition & Pre-processing, Segmentation, Feature Extraction, Murmur Detection and Murmur Classification. The heart sounds are first acquired using an electronic stethoscope which has the capability of transferring these signals to the near by workstation using wireless media. Then the signals are segmented into individual cycles as well as individual components using the spectral analysis of heart without using any reference signal like ECG. Then the features are extracted from the individual components using Spectrogram and are used as an input to a MLP (Multiple Layer Perceptron) Neural Network that is trained to detect the presence of heart murmurs. Once the murmur is detected they are classified into seven classes depending on their timing within the cardiac cycle using Smoothed Pseudo Wigner-Ville distribution. The module has been tested with real heart sounds from 40 patients and has proved to be quite efficient and robust while dealing with a large variety of pathological conditions.

[The validation of the effect of correcting spectral background changes based on floating reference method by simulation].

PubMed

Wang, Zhu-lou; Zhang, Wan-jie; Li, Chen-xi; Chen, Wen-liang; Xu, Ke-xin

2015-02-01

There are some challenges in near-infrared non-invasive blood glucose measurement, such as the low signal to noise ratio of instrument, the unstable measurement conditions, the unpredictable and irregular changes of the measured object, and etc. Therefore, it is difficult to extract the information of blood glucose concentrations from the complicated signals accurately. Reference measurement method is usually considered to be used to eliminate the effect of background changes. But there is no reference substance which changes synchronously with the anylate. After many years of research, our research group has proposed the floating reference method, which is succeeded in eliminating the spectral effects induced by the instrument drifts and the measured object's background variations. But our studies indicate that the reference-point will changes following the changing of measurement location and wavelength. Therefore, the effects of floating reference method should be verified comprehensively. In this paper, keeping things simple, the Monte Carlo simulation employing Intralipid solution with the concentrations of 5% and 10% is performed to verify the effect of floating reference method used into eliminating the consequences of the light source drift. And the light source drift is introduced through varying the incident photon number. The effectiveness of the floating reference method with corresponding reference-points at different wavelengths in eliminating the variations of the light source drift is estimated. The comparison of the prediction abilities of the calibration models with and without using this method shows that the RMSEPs of the method are decreased by about 98.57% (5%Intralipid)and 99.36% (10% Intralipid)for different Intralipid. The results indicate that the floating reference method has obvious effect in eliminating the background changes.

Video monitoring of oxygen saturation during controlled episodes of acute hypoxia.

PubMed

Addison, Paul S; Foo, David M H; Jacquel, Dominique; Borg, Ulf

2016-08-01

A method for extracting video photoplethysmographic information from an RGB video stream is tested on data acquired during a porcine model of acute hypoxia. Cardiac pulsatile information was extracted from the acquired signals and processed to determine a continuously reported oxygen saturation (SvidO2). A high degree of correlation was found to exist between the video and a reference from a pulse oximeter. The calculated mean bias and accuracy across all eight desaturation episodes were -0.03% (range: -0.21% to 0.24%) and accuracy 4.90% (range: 3.80% to 6.19%) respectively. The results support the hypothesis that oxygen saturation trending can be evaluated accurately from a video system during acute hypoxia.

Self-referenced continuous-variable quantum key distribution protocol

DOE PAGES

Soh, Daniel Beom Soo; Sarovar, Mohan; Brif, Constantin; ...

2015-10-21

We introduce a new continuous-variable quantum key distribution (CV-QKD) protocol, self-referenced CV-QKD, that eliminates the need for transmission of a high-power local oscillator between the communicating parties. In this protocol, each signal pulse is accompanied by a reference pulse (or a pair of twin reference pulses), used to align Alice’s and Bob’s measurement bases. The method of phase estimation and compensation based on the reference pulse measurement can be viewed as a quantum analog of intradyne detection used in classical coherent communication, which extracts the phase information from the modulated signal. We present a proof-of-principle, fiber-based experimental demonstration of themore » protocol and quantify the expected secret key rates by expressing them in terms of experimental parameters. Our analysis of the secret key rate fully takes into account the inherent uncertainty associated with the quantum nature of the reference pulse(s) and quantifies the limit at which the theoretical key rate approaches that of the respective conventional protocol that requires local oscillator transmission. The self-referenced protocol greatly simplifies the hardware required for CV-QKD, especially for potential integrated photonics implementations of transmitters and receivers, with minimum sacrifice of performance. Furthermore, it provides a pathway towards scalable integrated CV-QKD transceivers, a vital step towards large-scale QKD networks.« less

Self-referenced continuous-variable quantum key distribution protocol

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

Soh, Daniel Beom Soo; Sarovar, Mohan; Brif, Constantin

We introduce a new continuous-variable quantum key distribution (CV-QKD) protocol, self-referenced CV-QKD, that eliminates the need for transmission of a high-power local oscillator between the communicating parties. In this protocol, each signal pulse is accompanied by a reference pulse (or a pair of twin reference pulses), used to align Alice’s and Bob’s measurement bases. The method of phase estimation and compensation based on the reference pulse measurement can be viewed as a quantum analog of intradyne detection used in classical coherent communication, which extracts the phase information from the modulated signal. We present a proof-of-principle, fiber-based experimental demonstration of themore » protocol and quantify the expected secret key rates by expressing them in terms of experimental parameters. Our analysis of the secret key rate fully takes into account the inherent uncertainty associated with the quantum nature of the reference pulse(s) and quantifies the limit at which the theoretical key rate approaches that of the respective conventional protocol that requires local oscillator transmission. The self-referenced protocol greatly simplifies the hardware required for CV-QKD, especially for potential integrated photonics implementations of transmitters and receivers, with minimum sacrifice of performance. Furthermore, it provides a pathway towards scalable integrated CV-QKD transceivers, a vital step towards large-scale QKD networks.« less

Self-Referenced Continuous-Variable Quantum Key Distribution Protocol

NASA Astrophysics Data System (ADS)

Soh, Daniel B. S.; Brif, Constantin; Coles, Patrick J.; Lütkenhaus, Norbert; Camacho, Ryan M.; Urayama, Junji; Sarovar, Mohan

2015-10-01

We introduce a new continuous-variable quantum key distribution (CV-QKD) protocol, self-referenced CV-QKD, that eliminates the need for transmission of a high-power local oscillator between the communicating parties. In this protocol, each signal pulse is accompanied by a reference pulse (or a pair of twin reference pulses), used to align Alice's and Bob's measurement bases. The method of phase estimation and compensation based on the reference pulse measurement can be viewed as a quantum analog of intradyne detection used in classical coherent communication, which extracts the phase information from the modulated signal. We present a proof-of-principle, fiber-based experimental demonstration of the protocol and quantify the expected secret key rates by expressing them in terms of experimental parameters. Our analysis of the secret key rate fully takes into account the inherent uncertainty associated with the quantum nature of the reference pulse(s) and quantifies the limit at which the theoretical key rate approaches that of the respective conventional protocol that requires local oscillator transmission. The self-referenced protocol greatly simplifies the hardware required for CV-QKD, especially for potential integrated photonics implementations of transmitters and receivers, with minimum sacrifice of performance. As such, it provides a pathway towards scalable integrated CV-QKD transceivers, a vital step towards large-scale QKD networks.

System for monitoring non-coincident, nonstationary process signals

DOEpatents

Gross, Kenneth C.; Wegerich, Stephan W.

2005-01-04

An improved system for monitoring non-coincident, non-stationary, process signals. The mean, variance, and length of a reference signal is defined by an automated system, followed by the identification of the leading and falling edges of a monitored signal and the length of the monitored signal. The monitored signal is compared to the reference signal, and the monitored signal is resampled in accordance with the reference signal. The reference signal is then correlated with the resampled monitored signal such that the reference signal and the resampled monitored signal are coincident in time with each other. The resampled monitored signal is then compared to the reference signal to determine whether the resampled monitored signal is within a set of predesignated operating conditions.

Multivariate reference technique for quantitative analysis of fiber-optic tissue Raman spectroscopy.

PubMed

Bergholt, Mads Sylvest; Duraipandian, Shiyamala; Zheng, Wei; Huang, Zhiwei

2013-12-03

We report a novel method making use of multivariate reference signals of fused silica and sapphire Raman signals generated from a ball-lens fiber-optic Raman probe for quantitative analysis of in vivo tissue Raman measurements in real time. Partial least-squares (PLS) regression modeling is applied to extract the characteristic internal reference Raman signals (e.g., shoulder of the prominent fused silica boson peak (~130 cm(-1)); distinct sapphire ball-lens peaks (380, 417, 646, and 751 cm(-1))) from the ball-lens fiber-optic Raman probe for quantitative analysis of fiber-optic Raman spectroscopy. To evaluate the analytical value of this novel multivariate reference technique, a rapid Raman spectroscopy system coupled with a ball-lens fiber-optic Raman probe is used for in vivo oral tissue Raman measurements (n = 25 subjects) under 785 nm laser excitation powers ranging from 5 to 65 mW. An accurate linear relationship (R(2) = 0.981) with a root-mean-square error of cross validation (RMSECV) of 2.5 mW can be obtained for predicting the laser excitation power changes based on a leave-one-subject-out cross-validation, which is superior to the normal univariate reference method (RMSE = 6.2 mW). A root-mean-square error of prediction (RMSEP) of 2.4 mW (R(2) = 0.985) can also be achieved for laser power prediction in real time when we applied the multivariate method independently on the five new subjects (n = 166 spectra). We further apply the multivariate reference technique for quantitative analysis of gelatin tissue phantoms that gives rise to an RMSEP of ~2.0% (R(2) = 0.998) independent of laser excitation power variations. This work demonstrates that multivariate reference technique can be advantageously used to monitor and correct the variations of laser excitation power and fiber coupling efficiency in situ for standardizing the tissue Raman intensity to realize quantitative analysis of tissue Raman measurements in vivo, which is particularly appealing in challenging Raman endoscopic applications.

In Vitro Monitoring of Total Choline Levels in a Bioartificial Pancreas: 1H NMR Spectroscopic Studies of the Effects of Oxygen Level

NASA Astrophysics Data System (ADS)

Long, Robert C.; Papas, Klearchos K.; Sambanis, Athanassios; Constantinidis, Ioannis

2000-09-01

This investigation implements specifically designed solvent-suppressed adiabatic pulses whose properties make possible the long-term monitoring of 1H NMR detectable metabolites from alginate/poly-l-lysine/alginate (APA)-encapsulated βTC3 cells. Our encapsulated preparations were maintained in a perfusion bioreactor for periods exceeding 30 days. During this prolonged cultivation period, the cells were exposed to repetitive hypoxic episodes of 4 and 24 h. The ratio of the total choline signal (3.20 ppm) to the reference signal (observed at 0.94 ppm assigned to isoleucine, leucine, and valine) decreased by 8-10% for the 4-h and by 20-32% for the 24-h episodes and returned to its prehypoxic level upon reoxygenation. The decrease in the mean value of total choline to reference signal ratio for three 4-h and two 24-h episodes in two different cultures was highly significant (P < 0.01). The rate of recovery by this ratio was slower than the rates of recovery by oxygen consumption, lactate production, or glucose consumption. A step-up in oxygen level led to a new, higher value for the total choline to reference ratio. From spectra of extracts at 400 MHz, it was determined that 63.6% of the total choline signal is due to intracellular phosphorylcholine. Therefore, it is inferred that the observed changes in total choline signal are linked to an oxygen level dependence of the intracellular phosphorylcholine. Several possible mechanisms in which oxygen may influence phosphorylcholine metabolism are suggested. In addition, the implications of these findings to the development of a noninvasive monitoring method for tissue-engineered constructs composed of encapsulated cells are discussed.

Analysis of signal transduction in cell-free extracts and rafts of Xenopus eggs.

PubMed

Tokmakov, Alexander A; Iwasaki, Tetsushi; Sato, Ken-Ichi; Fukami, Yasuo

2010-05-01

Intracellular signaling during egg activation/fertilization has been extensively studied using intact eggs, which can be manipulated by microinjection of different mRNAs, proteins, or chemical drugs. Furthermore, egg extracts, which retain high CSF activity (CSF-arrested extracts), were developed for studying fertilization/activation signal transduction, which have significant advantages as a model system. The addition of calcium to CSF-arrested extracts initiates a plethora of signaling events that take place during egg activation. Hence, the signaling downstream of calcium mobilization has been successfully studied in the egg extracts. Moreover, despite disruption of membrane-associated signaling compartments and ordered compartmentalization during extract preparation, CSF-arrested extracts can be successfully used to study early signaling events, which occur upstream of calcium release during egg activation/fertilization. In combination with the CSF-arrested extracts, activated egg rafts can reproduce some events of egg activation, including PLCgamma activation, IP3 production, transient calcium release, MAPK inactivation, and meiotic exit. This becomes possible due to complementation of the sperm-induced egg activation signaling machinery present in the rafts with the components of signal transduction system localized in the extracts. Herein, we describe protocols for studying molecular mechanisms of egg fertilization/activation using cell-free extracts and membrane rafts prepared from metaphase-arrested Xenopus eggs.

FPGA-based real-time swept-source OCT systems for B-scan live-streaming or volumetric imaging

NASA Astrophysics Data System (ADS)

Bandi, Vinzenz; Goette, Josef; Jacomet, Marcel; von Niederhäusern, Tim; Bachmann, Adrian H.; Duelk, Marcus

2013-03-01

We have developed a Swept-Source Optical Coherence Tomography (Ss-OCT) system with high-speed, real-time signal processing on a commercially available Data-Acquisition (DAQ) board with a Field-Programmable Gate Array (FPGA). The Ss-OCT system simultaneously acquires OCT and k-clock reference signals at 500MS/s. From the k-clock signal of each A-scan we extract a remap vector for the k-space linearization of the OCT signal. The linear but oversampled interpolation is followed by a 2048-point FFT, additional auxiliary computations, and a data transfer to a host computer for real-time, live-streaming of B-scan or volumetric C-scan OCT visualization. We achieve a 100 kHz A-scan rate by parallelization of our hardware algorithms, which run on standard and affordable, commercially available DAQ boards. Our main development tool for signal analysis as well as for hardware synthesis is MATLAB® with add-on toolboxes and 3rd-party tools.

Acoustic sensor array extracts physiology during movement

NASA Astrophysics Data System (ADS)

Scanlon, Michael V.

2001-08-01

An acoustic sensor attached to a person's neck can extract heart and breath sounds, as well as voice and other physiology related to their health and performance. Soldiers, firefighters, law enforcement, and rescue personnel, as well as people at home or in health care facilities, can benefit form being remotely monitored. ARLs acoustic sensor, when worn around a person's neck, picks up the carotid artery and breath sounds very well by matching the sensor's acoustic impedance to that of the body via a gel pad, while airborne noise is minimized by an impedance mismatch. Although the physiological sounds have high SNR, the acoustic sensor also responds to motion-induced artifacts that obscure the meaningful physiology. To exacerbate signal extraction, these interfering signals are usually covariant with the heart sounds, in that as a person walks faster the heart tends to beat faster, and motion noises tend to contain low frequency component similar to the heart sounds. A noise-canceling configuration developed by ARL uses two acoustic sensor on the front sides of the neck as physiology sensors, and two additional acoustic sensor on the back sides of the neck as noise references. Breath and heart sounds, which occur with near symmetry and simultaneously at the two front sensor, will correlate well. The motion noise present on all four sensor will be used to cancel the noise on the two physiology sensors. This report will compare heart rate variability derived from both the acoustic array and from ECG data taken simultaneously on a treadmill test. Acoustically derived breath rate and volume approximations will be introduced as well. A miniature 3- axis accelerometer on the same neckband provides additional noise references to validate footfall and motion activity.

Cascaded multiplexed optical link on a telecommunication network for frequency dissemination.

PubMed

Lopez, Olivier; Haboucha, Adil; Kéfélian, Fabien; Jiang, Haifeng; Chanteau, Bruno; Roncin, Vincent; Chardonnet, Christian; Amy-Klein, Anne; Santarelli, Giorgio

2010-08-02

We demonstrate a cascaded optical link for ultrastable frequency dissemination comprised of two compensated links of 150 km and a repeater station. Each link includes 114 km of Internet fiber simultaneously carrying data traffic through a dense wavelength division multiplexing technology, and passes through two routing centers of the telecommunication network. The optical reference signal is inserted in and extracted from the communication network using bidirectional optical add-drop multiplexers. The repeater station operates autonomously ensuring noise compensation on the two links and the ultra-stable signal optical regeneration. The compensated link shows a fractional frequency instability of 3 x 10(-15) at one second measurement time and 5 x 10(-20) at 20 hours. This work paves the way to a wide dissemination of ultra-stable optical clock signals between distant laboratories via the Internet network.

Rational chemical design of the next generation of molecular imaging probes based on physics and biology: mixing modalities, colors and signals

PubMed Central

Longmire, Michelle R.; Ogawa, Mikako; Choyke, Peter L.

2012-01-01

In recent years, numerous in vivo molecular imaging probes have been developed. As a consequence, much has been published on the design and synthesis of molecular imaging probes focusing on each modality, each type of material, or each target disease. More recently, second generation molecular imaging probes with unique, multi-functional, or multiplexed characteristics have been designed. This critical review focuses on (i) molecular imaging using combinations of modalities and signals that employ the full range of the electromagnetic spectra, (ii) optimized chemical design of molecular imaging probes for in vivo kinetics based on biology and physiology across a range of physical sizes, (iii) practical examples of second generation molecular imaging probes designed to extract complementary data from targets using multiple modalities, color, and comprehensive signals (277 references). PMID:21607237

Model-based Bayesian signal extraction algorithm for peripheral nerves

NASA Astrophysics Data System (ADS)

Eggers, Thomas E.; Dweiri, Yazan M.; McCallum, Grant A.; Durand, Dominique M.

2017-10-01

Objective. Multi-channel cuff electrodes have recently been investigated for extracting fascicular-level motor commands from mixed neural recordings. Such signals could provide volitional, intuitive control over a robotic prosthesis for amputee patients. Recent work has demonstrated success in extracting these signals in acute and chronic preparations using spatial filtering techniques. These extracted signals, however, had low signal-to-noise ratios and thus limited their utility to binary classification. In this work a new algorithm is proposed which combines previous source localization approaches to create a model based method which operates in real time. Approach. To validate this algorithm, a saline benchtop setup was created to allow the precise placement of artificial sources within a cuff and interference sources outside the cuff. The artificial source was taken from five seconds of chronic neural activity to replicate realistic recordings. The proposed algorithm, hybrid Bayesian signal extraction (HBSE), is then compared to previous algorithms, beamforming and a Bayesian spatial filtering method, on this test data. An example chronic neural recording is also analyzed with all three algorithms. Main results. The proposed algorithm improved the signal to noise and signal to interference ratio of extracted test signals two to three fold, as well as increased the correlation coefficient between the original and recovered signals by 10-20%. These improvements translated to the chronic recording example and increased the calculated bit rate between the recovered signals and the recorded motor activity. Significance. HBSE significantly outperforms previous algorithms in extracting realistic neural signals, even in the presence of external noise sources. These results demonstrate the feasibility of extracting dynamic motor signals from a multi-fascicled intact nerve trunk, which in turn could extract motor command signals from an amputee for the end goal of controlling a prosthetic limb.

Method and apparatus for large motor control

DOEpatents

Rose, Chris R [Santa Fe, NM; Nelson, Ronald O [White Rock, NM

2003-08-12

Apparatus and method for providing digital signal processing method for controlling the speed and phase of a motor involves inputting a reference signal having a frequency and relative phase indicative of a time based signal; modifying the reference signal to introduce a slew-rate limited portion of each cycle of the reference signal; inputting a feedback signal having a frequency and relative phase indicative of the operation of said motor; modifying the feedback signal to introduce a slew-rate limited portion of each cycle of the feedback signal; analyzing the modified reference signal and the modified feedback signal to determine the frequency of the modified reference signal and of the modified feedback signal and said relative phase between said modified reference signal and said modified feedback signal; and outputting control signals to the motor for adjusting said speed and phase of the motor based on the frequency determination and determination of the relative phase.

Frequency to Voltage Converter Analog Front-End Prototype

NASA Technical Reports Server (NTRS)

Mata, Carlos; Raines, Matthew

2012-01-01

The frequency to voltage converter analog front end evaluation prototype (F2V AFE) is an evaluation board designed for comparison of different methods of accurately extracting the frequency of a sinusoidal input signal. A configurable input stage is routed to one or several of five separate, configurable filtering circuits, and then to a configurable output stage. Amplifier selection and gain, filter corner frequencies, and comparator hysteresis and voltage reference are all easily configurable through the use of jumpers and potentiometers.

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

Data quality enhancement and knowledge discovery from relevant signals in acoustic emission

NASA Astrophysics Data System (ADS)

Mejia, Felipe; Shyu, Mei-Ling; Nanni, Antonio

2015-10-01

The increasing popularity of structural health monitoring has brought with it a growing need for automated data management and data analysis tools. Of great importance are filters that can systematically detect unwanted signals in acoustic emission datasets. This study presents a semi-supervised data mining scheme that detects data belonging to unfamiliar distributions. This type of outlier detection scheme is useful detecting the presence of new acoustic emission sources, given a training dataset of unwanted signals. In addition to classifying new observations (herein referred to as "outliers") within a dataset, the scheme generates a decision tree that classifies sub-clusters within the outlier context set. The obtained tree can be interpreted as a series of characterization rules for newly-observed data, and they can potentially describe the basic structure of different modes within the outlier distribution. The data mining scheme is first validated on a synthetic dataset, and an attempt is made to confirm the algorithms' ability to discriminate outlier acoustic emission sources from a controlled pencil-lead-break experiment. Finally, the scheme is applied to data from two fatigue crack-growth steel specimens, where it is shown that extracted rules can adequately describe crack-growth related acoustic emission sources while filtering out background "noise." Results show promising performance in filter generation, thereby allowing analysts to extract, characterize, and focus only on meaningful signals.

Developing a Reference of Normal Lung Sounds in Healthy Peruvian Children

PubMed Central

Ellington, Laura E.; Emmanouilidou, Dimitra; Elhilali, Mounya; Gilman, Robert H.; Tielsch, James M.; Chavez, Miguel A.; Marin-Concha, Julio; Figueroa, Dante; West, James

2018-01-01

Purpose Lung auscultation has long been a standard of care for the diagnosis of respiratory diseases. Recent advances in electronic auscultation and signal processing have yet to find clinical acceptance; however, computerized lung sound analysis may be ideal for pediatric populations in settings, where skilled healthcare providers are commonly unavailable. We described features of normal lung sounds in young children using a novel signal processing approach to lay a foundation for identifying pathologic respiratory sounds. Methods 186 healthy children with normal pulmonary exams and without respiratory complaints were enrolled at a tertiary care hospital in Lima, Peru. Lung sounds were recorded at eight thoracic sites using a digital stethoscope. 151 (81 %) of the recordings were eligible for further analysis. Heavy-crying segments were automatically rejected and features extracted from spectral and temporal signal representations contributed to profiling of lung sounds. Results Mean age, height, and weight among study participants were 2.2 years (SD 1.4), 84.7 cm (SD 13.2), and 12.0 kg (SD 3.6), respectively; and, 47 % were boys. We identified ten distinct spectral and spectro-temporal signal parameters and most demonstrated linear relationships with age, height, and weight, while no differences with genders were noted. Older children had a faster decaying spectrum than younger ones. Features like spectral peak width, lower-frequency Mel-frequency cepstral coefficients, and spectro-temporal modulations also showed variations with recording site. Conclusions Lung sound extracted features varied significantly with child characteristics and lung site. A comparison with adult studies revealed differences in the extracted features for children. While sound-reduction techniques will improve analysis, we offer a novel, reproducible tool for sound analysis in real-world environments. PMID:24943262

Developing a reference of normal lung sounds in healthy Peruvian children.

PubMed

Ellington, Laura E; Emmanouilidou, Dimitra; Elhilali, Mounya; Gilman, Robert H; Tielsch, James M; Chavez, Miguel A; Marin-Concha, Julio; Figueroa, Dante; West, James; Checkley, William

2014-10-01

Lung auscultation has long been a standard of care for the diagnosis of respiratory diseases. Recent advances in electronic auscultation and signal processing have yet to find clinical acceptance; however, computerized lung sound analysis may be ideal for pediatric populations in settings, where skilled healthcare providers are commonly unavailable. We described features of normal lung sounds in young children using a novel signal processing approach to lay a foundation for identifying pathologic respiratory sounds. 186 healthy children with normal pulmonary exams and without respiratory complaints were enrolled at a tertiary care hospital in Lima, Peru. Lung sounds were recorded at eight thoracic sites using a digital stethoscope. 151 (81%) of the recordings were eligible for further analysis. Heavy-crying segments were automatically rejected and features extracted from spectral and temporal signal representations contributed to profiling of lung sounds. Mean age, height, and weight among study participants were 2.2 years (SD 1.4), 84.7 cm (SD 13.2), and 12.0 kg (SD 3.6), respectively; and, 47% were boys. We identified ten distinct spectral and spectro-temporal signal parameters and most demonstrated linear relationships with age, height, and weight, while no differences with genders were noted. Older children had a faster decaying spectrum than younger ones. Features like spectral peak width, lower-frequency Mel-frequency cepstral coefficients, and spectro-temporal modulations also showed variations with recording site. Lung sound extracted features varied significantly with child characteristics and lung site. A comparison with adult studies revealed differences in the extracted features for children. While sound-reduction techniques will improve analysis, we offer a novel, reproducible tool for sound analysis in real-world environments.

Variability and robustness of scatterers in HRR/ISAR ground target data and its influence on the ATR performance

NASA Astrophysics Data System (ADS)

Schumacher, R.; Schimpf, H.; Schiller, J.

2011-06-01

The most challenging problem of Automatic Target Recognition (ATR) is the extraction of robust and independent target features which describe the target unambiguously. These features have to be robust and invariant in different senses: in time, between aspect views (azimuth and elevation angle), between target motion (translation and rotation) and between different target variants. Especially for ground moving targets in military applications an irregular target motion is typical, so that a strong variation of the backscattered radar signal with azimuth and elevation angle makes the extraction of stable and robust features most difficult. For ATR based on High Range Resolution (HRR) profiles and / or Inverse Synthetic Aperture Radar (ISAR) images it is crucial that the reference dataset consists of stable and robust features, which, among others, will depend on the target aspect and depression angle amongst others. Here it is important to find an adequate data grid for an efficient data coverage in the reference dataset for ATR. In this paper the variability of the backscattered radar signals of target scattering centers is analyzed for different HRR profiles and ISAR images from measured turntable datasets of ground targets under controlled conditions. Especially the dependency of the features on the elevation angle is analyzed regarding to the ATR of large strip SAR data with a large range of depression angles by using available (I)SAR datasets as reference. In this work the robustness of these scattering centers is analyzed by extracting their amplitude, phase and position. Therefore turntable measurements under controlled conditions were performed targeting an artificial military reference object called STANDCAM. Measures referring to variability, similarity, robustness and separability regarding the scattering centers are defined. The dependency of the scattering behaviour with respect to azimuth and elevation variations is analyzed. Additionally generic types of features (geometrical, statistical), which can be derived especially from (I)SAR images, are applied to the ATR-task. Therefore subsequently the dependence of individual feature values as well as the feature statistics on aspect (i.e. azimuth and elevation) are presented. The Kolmogorov-Smirnov distance will be used to show how the feature statistics is influenced by varying elevation angles. Finally, confusion matrices are computed between the STANDCAM target at all eleven elevation angles. This helps to assess the robustness of ATR performance under the influence of aspect angle deviations between training set and test set.

Optical probe with reference fiber

DOEpatents

Da Silva, Luiz B [Danville, CA; Chase, Charles L [Dublin, CA

2006-03-14

A system for characterizing tissue includes the steps of generating an emission signal, generating a reference signal, directing the emission signal to and from the tissue, directing the reference signal in a predetermined manner relative to the emission signal, and using the reference signal to compensate the emission signal. In one embodiment compensation is provided for fluctuations in light delivery to the tip of the probe due to cable motion.

Modified fast frequency acquisition via adaptive least squares algorithm

NASA Technical Reports Server (NTRS)

Kumar, Rajendra (Inventor)

1992-01-01

A method and the associated apparatus for estimating the amplitude, frequency, and phase of a signal of interest are presented. The method comprises the following steps: (1) inputting the signal of interest; (2) generating a reference signal with adjustable amplitude, frequency and phase at an output thereof; (3) mixing the signal of interest with the reference signal and a signal 90 deg out of phase with the reference signal to provide a pair of quadrature sample signals comprising respectively a difference between the signal of interest and the reference signal and a difference between the signal of interest and the signal 90 deg out of phase with the reference signal; (4) using the pair of quadrature sample signals to compute estimates of the amplitude, frequency, and phase of an error signal comprising the difference between the signal of interest and the reference signal employing a least squares estimation; (5) adjusting the amplitude, frequency, and phase of the reference signal from the numerically controlled oscillator in a manner which drives the error signal towards zero; and (6) outputting the estimates of the amplitude, frequency, and phase of the error signal in combination with the reference signal to produce a best estimate of the amplitude, frequency, and phase of the signal of interest. The preferred method includes the step of providing the error signal as a real time confidence measure as to the accuracy of the estimates wherein the closer the error signal is to zero, the higher the probability that the estimates are accurate. A matrix in the estimation algorithm provides an estimate of the variance of the estimation error.

Eco-friendly sonoluminescent determination of free glycerol in biodiesel samples.

PubMed

Diniz, Paulo Henrique Gonçalves Dias; Pistonesi, Marcelo Fabián; de Araújo, Mário César Ugulino; Band, Beatriz Susana Fernández

2013-09-30

This paper proposes a flow-batch methodology for the determination of free glycerol in biodiesel that is notably eco-friendly, since non-chemical reagents are used. Deionized water (the solvent) was used alone for glycerol (sample) extractions from the biodiesel. The same water was used to generate water-cavitation sonoluminescence signals, which were modulated by the quenching effect associated with the amount of extracted glycerol. The necessarily reproducible signal generation was achieved by using a simple and inexpensive piezoelectric device. A linear response was observed for glycerol within the 0.001-100 mg/L range, equivalent to 0.004-400 mg/kg free glycerol in biodiesel. The lowest measurable concentration of free glycerol was estimated at 1.0 µg/L. The selectivity of the proposed method was confirmed by comparing the shape and retention of both real and calibration samples to standard solution chromatograms, presenting no peaks other than glycerol. All samples (after extraction) are greatly diluted; this minimizes (toward non-detectability) potential interference effects. The methodology was successfully applied to biodiesel analysis at a high sampling rate, with neither reagent nor solvent (other than water), and with minimum waste generation. The results agreed with the reference method (ASTM D6584-07), at a 95% confidence level. Copyright © 2013 Elsevier B.V. All rights reserved.

Sticker-type ECG/PPG concurrent monitoring system hybrid integration of CMOS SoC and organic sensor device.

PubMed

Yongsu Lee; Hyeonwoo Lee; Seunghyup Yoo; Hoi-Jun Yoo

2016-08-01

The sticker-type sensor system is proposed targeting ECG/PPG concurrent monitoring for cardiovascular diseases. The stickers are composed of two types: Hub and Sensor-node (SN) sticker. Low-power CMOS SoC for measuring ECG and PPG signal is hybrid integrated with organic light emitting diodes (OLEDs) and organic photo detector (OPD). The sticker has only 2g weight and only consumes 141μW. The optical calibration loop is adopted for maintaining SNR of PPG signal higher than 30dB. The pulse arrival time (PAT) and SpO2 value can be extracted from various body parts and verified comparing with the reference device from 20 people in-vivo experiments.

Design of a cavity ring-down spectroscopy diagnostic for negative ion rf source SPIDER

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

Pasqualotto, R.; Alfier, A.; Lotto, L.

2010-10-15

The rf source test facility SPIDER will test and optimize the source of the 1 MV neutral beam injection systems for ITER. Cavity ring-down spectroscopy (CRDS) will measure the absolute line-of-sight integrated density of negative (H{sup -} and D{sup -}) ions, produced in the extraction region of the source. CRDS takes advantage of the photodetachment process: negative ions are converted to neutral hydrogen atoms by electron stripping through absorption of a photon from a laser. The design of this diagnostic is presented with the corresponding simulation of the expected performance. A prototype operated without plasma has provided CRDS reference signals,more » design validation, and results concerning the signal-to-noise ratio.« less

Phase shifting interferometer

DOEpatents

Sommargren, Gary E.

1999-01-01

An interferometer which has the capability of measuring optical elements and systems with an accuracy of .lambda./1000 where .lambda. is the wavelength of visible light. Whereas current interferometers employ a reference surface, which inherently limits the accuracy of the measurement to about .lambda./50, this interferometer uses an essentially perfect spherical reference wavefront generated by the fundamental process of diffraction. Whereas current interferometers illuminate the optic to be tested with an aberrated wavefront which also limits the accuracy of the measurement, this interferometer uses an essentially perfect spherical measurement wavefront generated by the fundamental process of diffraction. This interferometer is adjustable to give unity fringe visibility, which maximizes the signal-to-noise, and has the means to introduce a controlled prescribed relative phase shift between the reference wavefront and the wavefront from the optics under test, which permits analysis of the interference fringe pattern using standard phase extraction algorithms.

Phase shifting interferometer

DOEpatents

Sommargren, G.E.

1999-08-03

An interferometer is disclosed which has the capability of measuring optical elements and systems with an accuracy of {lambda}/1000 where {lambda} is the wavelength of visible light. Whereas current interferometers employ a reference surface, which inherently limits the accuracy of the measurement to about {lambda}/50, this interferometer uses an essentially perfect spherical reference wavefront generated by the fundamental process of diffraction. Whereas current interferometers illuminate the optic to be tested with an aberrated wavefront which also limits the accuracy of the measurement, this interferometer uses an essentially perfect spherical measurement wavefront generated by the fundamental process of diffraction. This interferometer is adjustable to give unity fringe visibility, which maximizes the signal-to-noise, and has the means to introduce a controlled prescribed relative phase shift between the reference wavefront and the wavefront from the optics under test, which permits analysis of the interference fringe pattern using standard phase extraction algorithms. 11 figs.

Reference-free fatigue crack detection using nonlinear ultrasonic modulation under various temperature and loading conditions

NASA Astrophysics Data System (ADS)

Lim, Hyung Jin; Sohn, Hoon; DeSimio, Martin P.; Brown, Kevin

2014-04-01

This study presents a reference-free fatigue crack detection technique using nonlinear ultrasonic modulation. When low frequency (LF) and high frequency (HF) inputs generated by two surface-mounted lead zirconate titanate (PZT) transducers are applied to a structure, the presence of a fatigue crack can provide a mechanism for nonlinear ultrasonic modulation and create spectral sidebands around the frequency of the HF signal. The crack-induced spectral sidebands are isolated using a combination of linear response subtraction (LRS), synchronous demodulation (SD) and continuous wavelet transform (CWT) filtering. Then, a sequential outlier analysis is performed on the extracted sidebands to identify the crack presence without referring any baseline data obtained from the intact condition of the structure. Finally, the robustness of the proposed technique is demonstrated using actual test data obtained from simple aluminum plate and complex aircraft fitting-lug specimens under varying temperature and loading variations.

Development of an Optical Gas Leak Sensor for Detecting Ethylene, Dimethyl Ether and Methane

PubMed Central

Tan, Qiulin; Pei, Xiangdong; Zhu, Simin; Sun, Dong; Liu, Jun; Xue, Chenyang; Liang, Ting; Zhang, Wendong; Xiong, Jijun

2013-01-01

In this paper, we present an approach to develop an optical gas leak sensor that can be used to measure ethylene, dimethyl ether, and methane. The sensor is designed based on the principles of IR absorption spectrum detection, and comprises two crossed elliptical surfaces with a folded reflection-type optical path. We first analyze the optical path and the use of this structure to design a miniature gas sensor. The proposed sensor includes two detectors (one to acquire the reference signal and the other for the response signal), the light source, and the filter, all of which are integrated in a miniature gold-plated chamber. We also designed a signal detection device to extract the sensor signal and a microprocessor to calculate and control the entire process. The produced sensor prototype had an accuracy of ±0.05%. Experiments which simulate the transportation of hazardous chemicals demonstrated that the developed sensor exhibited a good dynamic response and adequately met technical requirements. PMID:23539025

Self-regulating proportionally controlled heating apparatus and technique

NASA Technical Reports Server (NTRS)

Strange, M. G. (Inventor)

1975-01-01

A self-regulating proportionally controlled heating apparatus and technique is provided wherein a single electrical resistance heating element having a temperature coefficient of resistance serves simultaneously as a heater and temperature sensor. The heating element is current-driven and the voltage drop across the heating element is monitored and a component extracted which is attributable to a change in actual temperature of the heating element from a desired reference temperature, so as to produce a resulting error signal. The error signal is utilized to control the level of the heater drive current and the actual heater temperature in a direction to reduce the noted temperature difference. The continuous nature of the process for deriving the error signal feedback information results in true proportional control of the heating element without the necessity for current-switching which may interfere with nearby sensitive circuits, and with no cyclical variation in the controlled temperature.

SPS pilot signal design and power transponder analysis, volume 2, phase 3

NASA Technical Reports Server (NTRS)

Lindsey, W. C.; Scholtz, R. A.; Chie, C. M.

1980-01-01

The problem of pilot signal parameter optimization and the related problem of power transponder performance analysis for the Solar Power Satellite reference phase control system are addressed. Signal and interference models were established to enable specifications of the front end filters including both the notch filter and the antenna frequency response. A simulation program package was developed to be included in SOLARSIM to perform tradeoffs of system parameters based on minimizing the phase error for the pilot phase extraction. An analytical model that characterizes the overall power transponder operation was developed. From this model, the effects of different phase noise disturbance sources that contribute to phase variations at the output of the power transponders were studied and quantified. Results indicate that it is feasible to hold the antenna array phase error to less than one degree per power module for the type of disturbances modeled.

Quantum neural network-based EEG filtering for a brain-computer interface.

PubMed

Gandhi, Vaibhav; Prasad, Girijesh; Coyle, Damien; Behera, Laxmidhar; McGinnity, Thomas Martin

2014-02-01

A novel neural information processing architecture inspired by quantum mechanics and incorporating the well-known Schrodinger wave equation is proposed in this paper. The proposed architecture referred to as recurrent quantum neural network (RQNN) can characterize a nonstationary stochastic signal as time-varying wave packets. A robust unsupervised learning algorithm enables the RQNN to effectively capture the statistical behavior of the input signal and facilitates the estimation of signal embedded in noise with unknown characteristics. The results from a number of benchmark tests show that simple signals such as dc, staircase dc, and sinusoidal signals embedded within high noise can be accurately filtered and particle swarm optimization can be employed to select model parameters. The RQNN filtering procedure is applied in a two-class motor imagery-based brain-computer interface where the objective was to filter electroencephalogram (EEG) signals before feature extraction and classification to increase signal separability. A two-step inner-outer fivefold cross-validation approach is utilized to select the algorithm parameters subject-specifically for nine subjects. It is shown that the subject-specific RQNN EEG filtering significantly improves brain-computer interface performance compared to using only the raw EEG or Savitzky-Golay filtered EEG across multiple sessions.

Polydyne displacement interferometer using frequency-modulated light

NASA Astrophysics Data System (ADS)

Arablu, Masoud; Smith, Stuart T.

2018-05-01

A radio-frequency Frequency-Modulated (FM) signal is used to diffract a He-Ne laser beam through an Acousto-Optic Modulator (AOM). Due to the modulation of the FM signal, the measured spectra of the diffracted beams comprise a series of phase-synchronized harmonics that have exact integer frequency separation. The first diffraction side-beam emerging from the AOM is selected by a slit to be used in a polydyne displacement interferometer in a Michelson interferometer topology. The displacement measurement is derived from the phase measurement of selected modulation harmonic pairs. Individual harmonic frequency amplitudes are measured using discrete Fourier transform applied to the signal from a single photodetector. Phase signals are derived from the changes in the amplitudes of different harmonic pairs (typically odd-even pairs) with the phase being extracted using a standard quadrature method. In this study, two different modulation frequencies of 5 and 10 kHz are used at different modulation depths. The measured displacements by different harmonic pairs are compared with a commercial heterodyne interferometer being used as a reference for these studies. Measurements obtained from five different harmonic pairs when the moving mirror of the interferometer is scanned over ranges up to 10 μm all show differences of less than 50 nm from the reference interferometer measurements. A drift test was also used to evaluate the differences between the polydyne interferometer and reference measurements that had different optical path lengths of approximately 25 mm and 50 mm, respectively. The drift test results indicate that about half of the differences can be attributed to temperature, pressure, and humidity variations. Other influences include Abbe and thermal expansion effects. Rough magnitude estimates using simple models for these two effects can account for remaining observed deviations.

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.

Biological network extraction from scientific literature: state of the art and challenges.

PubMed

Li, Chen; Liakata, Maria; Rebholz-Schuhmann, Dietrich

2014-09-01

Networks of molecular interactions explain complex biological processes, and all known information on molecular events is contained in a number of public repositories including the scientific literature. Metabolic and signalling pathways are often viewed separately, even though both types are composed of interactions involving proteins and other chemical entities. It is necessary to be able to combine data from all available resources to judge the functionality, complexity and completeness of any given network overall, but especially the full integration of relevant information from the scientific literature is still an ongoing and complex task. Currently, the text-mining research community is steadily moving towards processing the full body of the scientific literature by making use of rich linguistic features such as full text parsing, to extract biological interactions. The next step will be to combine these with information from scientific databases to support hypothesis generation for the discovery of new knowledge and the extension of biological networks. The generation of comprehensive networks requires technologies such as entity grounding, coordination resolution and co-reference resolution, which are not fully solved and are required to further improve the quality of results. Here, we analyse the state of the art for the extraction of network information from the scientific literature and the evaluation of extraction methods against reference corpora, discuss challenges involved and identify directions for future research. © The Author 2013. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

The Redox Potential of the Plastoquinone Pool of the Cyanobacterium Synechocystis Species Strain PCC 6803 Is under Strict Homeostatic Control1[C][W

PubMed Central

Schuurmans, R. Milou; Schuurmans, J. Merijn; Bekker, Martijn; Kromkamp, Jacco C.; Matthijs, Hans C.P.; Hellingwerf, Klaas J.

2014-01-01

A method is presented for rapid extraction of the total plastoquinone (PQ) pool from Synechocystis sp. strain PCC 6803 cells that preserves the in vivo plastoquinol (PQH2) to -PQ ratio. Cells were rapidly transferred into ice-cold organic solvent for instantaneous extraction of the cellular PQ plus PQH2 content. After high-performance liquid chromatography fractionation of the organic phase extract, the PQH2 content was quantitatively determined via its fluorescence emission at 330 nm. The in-cell PQH2-PQ ratio then followed from comparison of the PQH2 signal in samples as collected and in an identical sample after complete reduction with sodium borohydride. Prior to PQH2 extraction, cells from steady-state chemostat cultures were exposed to a wide range of physiological conditions, including high/low availability of inorganic carbon, and various actinic illumination conditions. Well-characterized electron-transfer inhibitors were used to generate a reduced or an oxidized PQ pool for reference. The in vivo redox state of the PQ pool was correlated with the results of pulse-amplitude modulation-based chlorophyll a fluorescence emission measurements, oxygen exchange rates, and 77 K fluorescence emission spectra. Our results show that the redox state of the PQ pool of Synechocystis sp. strain PCC 6803 is subject to strict homeostatic control (i.e. regulated between narrow limits), in contrast to the more dynamic chlorophyll a fluorescence signal. PMID:24696521

NMR and MALDI-TOF MS based characterization of exopolysaccharides in anaerobic microbial aggregates from full-scale reactors

PubMed Central

Gonzalez-Gil, Graciela; Thomas, Ludivine; Emwas, Abdul-Hamid; Lens, Piet N. L.; Saikaly, Pascal E.

2015-01-01

Anaerobic granular sludge is composed of multispecies microbial aggregates embedded in a matrix of extracellular polymeric substances (EPS). Here we characterized the chemical fingerprint of the polysaccharide fraction of EPS in anaerobic granules obtained from full-scale reactors treating different types of wastewater. Nuclear magnetic resonance (NMR) signals of the polysaccharide region from the granules were very complex, likely as a result of the diverse microbial population in the granules. Using nonmetric multidimensional scaling (NMDS), the 1H NMR signals of reference polysaccharides (gellan, xanthan, alginate) and those of the anaerobic granules revealed that there were similarities between the polysaccharides extracted from granules and the reference polysaccharide alginate. Further analysis of the exopolysaccharides from anaerobic granules, and reference polysaccharides using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) revealed that exopolysaccharides from two of the anaerobic granular sludges studied exhibited spectra similar to that of alginate. The presence of sequences related to the synthesis of alginate was confirmed in the metagenomes of the granules. Collectively these results suggest that alginate-like exopolysaccharides are constituents of the EPS matrix in anaerobic granular sludge treating different industrial wastewater. This finding expands the engineered environments where alginate has been found as EPS constituent of microbial aggregates. PMID:26391984

NMR and MALDI-TOF MS based characterization of exopolysaccharides in anaerobic microbial aggregates from full-scale reactors.

PubMed

Gonzalez-Gil, Graciela; Thomas, Ludivine; Emwas, Abdul-Hamid; Lens, Piet N L; Saikaly, Pascal E

2015-09-22

Anaerobic granular sludge is composed of multispecies microbial aggregates embedded in a matrix of extracellular polymeric substances (EPS). Here we characterized the chemical fingerprint of the polysaccharide fraction of EPS in anaerobic granules obtained from full-scale reactors treating different types of wastewater. Nuclear magnetic resonance (NMR) signals of the polysaccharide region from the granules were very complex, likely as a result of the diverse microbial population in the granules. Using nonmetric multidimensional scaling (NMDS), the (1)H NMR signals of reference polysaccharides (gellan, xanthan, alginate) and those of the anaerobic granules revealed that there were similarities between the polysaccharides extracted from granules and the reference polysaccharide alginate. Further analysis of the exopolysaccharides from anaerobic granules, and reference polysaccharides using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) revealed that exopolysaccharides from two of the anaerobic granular sludges studied exhibited spectra similar to that of alginate. The presence of sequences related to the synthesis of alginate was confirmed in the metagenomes of the granules. Collectively these results suggest that alginate-like exopolysaccharides are constituents of the EPS matrix in anaerobic granular sludge treating different industrial wastewater. This finding expands the engineered environments where alginate has been found as EPS constituent of microbial aggregates.

Laboratory Simulation and Measurement of Instrument Drift in Quartz-Resonant Pressure Gauges

NASA Astrophysics Data System (ADS)

Sasagawa, G. S.; Zumberge, M. A.

2017-12-01

Marine geodesy uses ocean bottom pressure sensors to measure vertical deformation of the sea floor, including that due to volcanic inflation and subsidence, episodic tremor and slip, plate subduction, and deformation due to hydrocarbon extraction at offshore reservoirs. Instrumental drift is inherent in existing pressure sensors and introduce uncertainties in data interpretation. Different methods have been developed to control drift, using varying techniques and instrumentation. Laboratory measurements of sensor drift, under controlled conditions that simulate seafloor pressures and temperatures, would allow for evaluating pressure gauge drift and the efficacy of new drift control methods. We have constructed and operated a laboratory system to monitor the drift of 15 quartz resonant pressure gauges over a year. The temperature and pressure are maintained and controlled at approximately 5 °C and 1900 dbar. A deadweight tester was used to provide a reference signal at frequent intervals; the time series of reference pressure signals is a direct measure of each gauge's drift. Several other tests were conducted, including a) evaluation of a custom outgassing sensor used as proxy for instrument drift, b) determination of the oscillator drift in the pressure gauge signal conditioning electronics, and c) a test of ambient air pressure calibration, also known as the A-0-A method. First results will be presented.

Feasibility study on measurement of magnetocardiography (MCG) using fluxgate magnetometer

NASA Astrophysics Data System (ADS)

Sengottuvel, S.; Sharma, Akash; Biswal, Deepak; Khan, Pathan Fayaz; Swain, Pragyna Parimita; Patel, Rajesh; Gireesan, K.

2018-04-01

This paper reports the feasibility of measuring weak magnetic fields generated by the electrical activity of the heart using a portable tri-axial fluxgate magnetometer inside a magnetically shielded room. Measurement of Magnetocardiogram (MCG) signals could be successfully demonstrated from a healthy subject using a novel set-up involving a reference fluxgate sensor which simultaneously measures the magnetic fields associated with the ECG waveform measured on the same subject. The timing information provided by R wave peaks of ECG recorded by the reference sensor is utilized to generate trigger locked average of the sensor output of the measurement fluxgate, and extract MCG signals in all the three orthogonal directions (X, Y and Z) on the anterior thorax. It is expected that such portable room temperature measurements using fluxgate sensor could assist in validating the direction of the equivalent current dipole associated with the electrical activity of the human heart. This is somewhat difficult in conventional MCG measurements using SQUID sensors, which usually furnish only the z component of the magnetic field and its spatial derivatives.

Research on the feature extraction and pattern recognition of the distributed optical fiber sensing signal

NASA Astrophysics Data System (ADS)

Wang, Bingjie; Sun, Qi; Pi, Shaohua; Wu, Hongyan

2014-09-01

In this paper, feature extraction and pattern recognition of the distributed optical fiber sensing signal have been studied. We adopt Mel-Frequency Cepstral Coefficient (MFCC) feature extraction, wavelet packet energy feature extraction and wavelet packet Shannon entropy feature extraction methods to obtain sensing signals (such as speak, wind, thunder and rain signals, etc.) characteristic vectors respectively, and then perform pattern recognition via RBF neural network. Performances of these three feature extraction methods are compared according to the results. We choose MFCC characteristic vector to be 12-dimensional. For wavelet packet feature extraction, signals are decomposed into six layers by Daubechies wavelet packet transform, in which 64 frequency constituents as characteristic vector are respectively extracted. In the process of pattern recognition, the value of diffusion coefficient is introduced to increase the recognition accuracy, while keeping the samples for testing algorithm the same. Recognition results show that wavelet packet Shannon entropy feature extraction method yields the best recognition accuracy which is up to 97%; the performance of 12-dimensional MFCC feature extraction method is less satisfactory; the performance of wavelet packet energy feature extraction method is the worst.

Event-driven processing for hardware-efficient neural spike sorting

NASA Astrophysics Data System (ADS)

Liu, Yan; Pereira, João L.; Constandinou, Timothy G.

2018-02-01

Objective. The prospect of real-time and on-node spike sorting provides a genuine opportunity to push the envelope of large-scale integrated neural recording systems. In such systems the hardware resources, power requirements and data bandwidth increase linearly with channel count. Event-based (or data-driven) processing can provide here a new efficient means for hardware implementation that is completely activity dependant. In this work, we investigate using continuous-time level-crossing sampling for efficient data representation and subsequent spike processing. Approach. (1) We first compare signals (synthetic neural datasets) encoded with this technique against conventional sampling. (2) We then show how such a representation can be directly exploited by extracting simple time domain features from the bitstream to perform neural spike sorting. (3) The proposed method is implemented in a low power FPGA platform to demonstrate its hardware viability. Main results. It is observed that considerably lower data rates are achievable when using 7 bits or less to represent the signals, whilst maintaining the signal fidelity. Results obtained using both MATLAB and reconfigurable logic hardware (FPGA) indicate that feature extraction and spike sorting accuracies can be achieved with comparable or better accuracy than reference methods whilst also requiring relatively low hardware resources. Significance. By effectively exploiting continuous-time data representation, neural signal processing can be achieved in a completely event-driven manner, reducing both the required resources (memory, complexity) and computations (operations). This will see future large-scale neural systems integrating on-node processing in real-time hardware.

Highly Simple Deep Eutectic Solvent Extraction of Manganese in Vegetable Samples Prior to Its ICP-OES Analysis.

PubMed

Bağda, Esra; Altundağ, Hüseyin; Soylak, Mustafa

2017-10-01

In the present work, simple and sensitive extraction methods for selective determination of manganese have been successfully developed. The methods were based on solubilization of manganese in deep eutectic solvent medium. Three deep eutectic solvents with choline chloride (vitamin B4) and tartaric/oxalic/citric acids have been prepared. Extraction parameters were optimized with using standard reference material (1573a tomato leaves). The quantitative recovery values were obtained with 1.25 g/L sample to deep eutectic solvent (DES) volume, at 95 °C for 2 h. The limit of detection was found as 0.50, 0.34, and 1.23 μg/L for DES/tartaric, DES/oxalic, and DES/citric acid, respectively. At optimum conditions, the analytical signal was linear for the range of 10-3000 μg/L for all studied DESs with the correlation coefficient >0.99. The extraction methods were applied to different real samples such as basil herb, spinach, dill, and cucumber barks. The known amount of manganese was spiked to samples, and good recovery results were obtained.

An open-source framework for stress-testing non-invasive foetal ECG extraction algorithms.

PubMed

Andreotti, Fernando; Behar, Joachim; Zaunseder, Sebastian; Oster, Julien; Clifford, Gari D

2016-05-01

Over the past decades, many studies have been published on the extraction of non-invasive foetal electrocardiogram (NI-FECG) from abdominal recordings. Most of these contributions claim to obtain excellent results in detecting foetal QRS (FQRS) complexes in terms of location. A small subset of authors have investigated the extraction of morphological features from the NI-FECG. However, due to the shortage of available public databases, the large variety of performance measures employed and the lack of open-source reference algorithms, most contributions cannot be meaningfully assessed. This article attempts to address these issues by presenting a standardised methodology for stress testing NI-FECG algorithms, including absolute data, as well as extraction and evaluation routines. To that end, a large database of realistic artificial signals was created, totaling 145.8 h of multichannel data and over one million FQRS complexes. An important characteristic of this dataset is the inclusion of several non-stationary events (e.g. foetal movements, uterine contractions and heart rate fluctuations) that are critical for evaluating extraction routines. To demonstrate our testing methodology, three classes of NI-FECG extraction algorithms were evaluated: blind source separation (BSS), template subtraction (TS) and adaptive methods (AM). Experiments were conducted to benchmark the performance of eight NI-FECG extraction algorithms on the artificial database focusing on: FQRS detection and morphological analysis (foetal QT and T/QRS ratio). The overall median FQRS detection accuracies (i.e. considering all non-stationary events) for the best performing methods in each group were 99.9% for BSS, 97.9% for AM and 96.0% for TS. Both FQRS detections and morphological parameters were shown to heavily depend on the extraction techniques and signal-to-noise ratio. Particularly, it is shown that their evaluation in the source domain, obtained after using a BSS technique, should be avoided. Data, extraction algorithms and evaluation routines were released as part of the fecgsyn toolbox on Physionet under an GNU GPL open-source license. This contribution provides a standard framework for benchmarking and regulatory testing of NI-FECG extraction algorithms.

Technical Note: Kinect V2 surface filtering during gantry motion for radiotherapy applications.

PubMed

Nazir, Souha; Rihana, Sandy; Visvikis, Dimitris; Fayad, Hadi

2018-04-01

In radiotherapy, the Kinect V2 camera, has recently received a lot of attention concerning many clinical applications including patient positioning, respiratory motion tracking, and collision detection during the radiotherapy delivery phase. However, issues associated with such applications are related to some materials and surfaces reflections generating an offset in depth measurements especially during gantry motion. This phenomenon appears in particular when the collimator surface is observed by the camera; resulting in erroneous depth measurements, not only in Kinect surfaces itself, but also as a large peak when extracting a 1D respiratory signal from these data. In this paper, we proposed filtering techniques to reduce the noise effect in the Kinect-based 1D respiratory signal, using a trend removal filter, and in associated 2D surfaces, using a temporal median filter. Filtering process was validated using a phantom, in order to simulate a patient undergoing radiotherapy treatment while having the ground truth. Our results indicate a better correlation between the reference respiratory signal and its corresponding filtered signal (Correlation coefficient of 0.76) than that of the nonfiltered signal (Correlation coefficient of 0.13). Furthermore, surface filtering results show a decrease in the mean square distance error (85%) between the reference and the measured point clouds. This work shows a significant noise compensation and surface restitution after surface filtering and therefore a potential use of the Kinect V2 camera for different radiotherapy-based applications, such as respiratory tracking and collision detection. © 2018 American Association of Physicists in Medicine.

Coping with Trial-to-Trial Variability of Event Related Signals: A Bayesian Inference Approach

NASA Technical Reports Server (NTRS)

Ding, Mingzhou; Chen, Youghong; Knuth, Kevin H.; Bressler, Steven L.; Schroeder, Charles E.

2005-01-01

In electro-neurophysiology, single-trial brain responses to a sensory stimulus or a motor act are commonly assumed to result from the linear superposition of a stereotypic event-related signal (e.g. the event-related potential or ERP) that is invariant across trials and some ongoing brain activity often referred to as noise. To extract the signal, one performs an ensemble average of the brain responses over many identical trials to attenuate the noise. To date, h s simple signal-plus-noise (SPN) model has been the dominant approach in cognitive neuroscience. Mounting empirical evidence has shown that the assumptions underlying this model may be overly simplistic. More realistic models have been proposed that account for the trial-to-trial variability of the event-related signal as well as the possibility of multiple differentially varying components within a given ERP waveform. The variable-signal-plus-noise (VSPN) model, which has been demonstrated to provide the foundation for separation and characterization of multiple differentially varying components, has the potential to provide a rich source of information for questions related to neural functions that complement the SPN model. Thus, being able to estimate the amplitude and latency of each ERP component on a trial-by-trial basis provides a critical link between the perceived benefits of the VSPN model and its many concrete applications. In this paper we describe a Bayesian approach to deal with this issue and the resulting strategy is referred to as the differentially Variable Component Analysis (dVCA). We compare the performance of dVCA on simulated data with Independent Component Analysis (ICA) and analyze neurobiological recordings from monkeys performing cognitive tasks.

Extraction and analysis of neuron firing signals from deep cortical video microscopy

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

Kerekes, Ryan A; Blundon, Jay

We introduce a method for extracting and analyzing neuronal activity time signals from video of the cortex of a live animal. The signals correspond to the firing activity of individual cortical neurons. Activity signals are based on the changing fluorescence of calcium indicators in the cells over time. We propose a cell segmentation method that relies on a user-specified center point, from which the signal extraction method proceeds. A stabilization approach is used to reduce tissue motion in the video. The extracted signal is then processed to flatten the baseline and detect action potentials. We show results from applying themore » method to a cortical video of a live mouse.« less

Improving the signal subtle feature extraction performance based on dual improved fractal box dimension eigenvectors

NASA Astrophysics Data System (ADS)

Chen, Xiang; Li, Jingchao; Han, Hui; Ying, Yulong

2018-05-01

Because of the limitations of the traditional fractal box-counting dimension algorithm in subtle feature extraction of radiation source signals, a dual improved generalized fractal box-counting dimension eigenvector algorithm is proposed. First, the radiation source signal was preprocessed, and a Hilbert transform was performed to obtain the instantaneous amplitude of the signal. Then, the improved fractal box-counting dimension of the signal instantaneous amplitude was extracted as the first eigenvector. At the same time, the improved fractal box-counting dimension of the signal without the Hilbert transform was extracted as the second eigenvector. Finally, the dual improved fractal box-counting dimension eigenvectors formed the multi-dimensional eigenvectors as signal subtle features, which were used for radiation source signal recognition by the grey relation algorithm. The experimental results show that, compared with the traditional fractal box-counting dimension algorithm and the single improved fractal box-counting dimension algorithm, the proposed dual improved fractal box-counting dimension algorithm can better extract the signal subtle distribution characteristics under different reconstruction phase space, and has a better recognition effect with good real-time performance.

Automated Design Tools for Integrated Mixed-Signal Microsystems (NeoCAD)

DTIC Science & Technology

2005-02-01

method, Model Order Reduction (MOR) tools, system-level, mixed-signal circuit synthesis and optimization tools, and parsitic extraction tools. A unique...Mission Area: Command and Control mixed signal circuit simulation parasitic extraction time-domain simulation IC design flow model order reduction... Extraction 1.2 Overall Program Milestones CHAPTER 2 FAST TIME DOMAIN MIXED-SIGNAL CIRCUIT SIMULATION 2.1 HAARSPICE Algorithms 2.1.1 Mathematical Background

ECG Identification System Using Neural Network with Global and Local Features

ERIC Educational Resources Information Center

Tseng, Kuo-Kun; Lee, Dachao; Chen, Charles

2016-01-01

This paper proposes a human identification system via extracted electrocardiogram (ECG) signals. Two hierarchical classification structures based on global shape feature and local statistical feature is used to extract ECG signals. Global shape feature represents the outline information of ECG signals and local statistical feature extracts the…

Intensity fading MALDI-TOF mass spectrometry and functional proteomics assignments to identify protease inhibitors in marine invertebrates.

PubMed

Covaleda, Giovanni; Trejo, Sebastian A; Salas-Sarduy, Emir; Del Rivero, Maday Alonso; Chavez, Maria Angeles; Aviles, Francesc X

2017-08-08

Proteases and their inhibitors have become molecules of increasing fundamental and applicative value. Here we report an integrated strategy to identify and analyze such inhibitors from Caribbean marine invertebrates extracts by a fast and sensitive functional proteomics-like approach. The strategy works in three steps: i) multiplexed enzymatic inhibition kinetic assays, ii) Intensity Fading MALDI-TOF MS to establish a link between inhibitory molecules and the related MALDI signal(s) detected in the extract(s), and iii) ISD-CID-T 3 MS fragmentation on the parent MALDI signals selected in the previous step, enabling the partial or total top-down sequencing of the molecules. The present study has allowed validation of the whole approach, identification of a substantial number of novel protein protease inhibitors, as well as full or partial sequencing of reference molecular species and of many unknown ones, respectively. Such inhibitors correspond to six protease subfamilies (metallocarboxypeptidases-A and -B, pepsin, papain, trypsin and subtilisin), are small (1-10KDa) disulfide-rich proteins, and have been found at diverse frequencies among the invertebrates (13 to 41%). The overall procedure could be tailored to other enzyme-inhibitor and protein interacting systems, analyzing samples at medium-throughput level and leading to the functional and structural characterization of proteinaceous ligands from complex biological extracts. Invertebrate animals, and marine ones among, display a remarkable diversity of species and contained biomolecules. Many of their proteins-peptides have high biological, biotechnological and biomedical potential interest but, because of the lack of sequenced genomes behind, their structural and functional characterization constitutes a great challenge. Here, looking at the small, disulfide-rich, proteinaceous inhibitors of proteases found in them, it is shown that such problem can be significatively facilitated by integrative multiplexed enzymatic assays, affinity-based Intensity-Fading (IF-) MALDI-TOF mass spectrometry (MS), and on-line MS fragmentation, in a fast and easy approach. Copyright © 2017. Published by Elsevier B.V.

Improvement of absolute positioning of precision stage based on cooperation the zero position pulse signal and incremental displacement signal

NASA Astrophysics Data System (ADS)

Wang, H. H.; Shi, Y. P.; Li, X. H.; Ni, K.; Zhou, Q.; Wang, X. H.

2018-03-01

In this paper, a scheme to measure the position of precision stages, with a high precision, is presented. The encoder is composed of a scale grating and a compact two-probe reading head, to read the zero position pulse signal and continuous incremental displacement signal. The scale grating contains different codes, multiple reference codes with different spacing superimposed onto the incremental grooves with an equal spacing structure. The codes of reference mask in the reading head is the same with the reference codes on the scale grating, and generate pulse signal to locate the reference position primarily when the reading head moves along the scale grating. After locating the reference position in a section by means of the pulse signal, the reference position can be located precisely with the amplitude of the incremental displacement signal. A kind of reference codes and scale grating were designed, and experimental results show that the primary precision of the design achieved is 1 μ m. The period of the incremental signal is 1μ m, and 1000/N nm precision can be achieved by subdivide the incremental signal in N times.

Extraction of temporal information in functional MRI

NASA Astrophysics Data System (ADS)

Singh, M.; Sungkarat, W.; Jeong, Jeong-Won; Zhou, Yongxia

2002-10-01

The temporal resolution of functional MRI (fMRI) is limited by the shape of the haemodynamic response function (hrf) and the vascular architecture underlying the activated regions. Typically, the temporal resolution of fMRI is on the order of 1 s. We have developed a new data processing approach to extract temporal information on a pixel-by-pixel basis at the level of 100 ms from fMRI data. Instead of correlating or fitting the time-course of each pixel to a single reference function, which is the common practice in fMRI, we correlate each pixel's time-course to a series of reference functions that are shifted with respect to each other by 100 ms. The reference function yielding the highest correlation coefficient for a pixel is then used as a time marker for that pixel. A Monte Carlo simulation and experimental study of this approach were performed to estimate the temporal resolution as a function of signal-to-noise ratio (SNR) in the time-course of a pixel. Assuming a known and stationary hrf, the simulation and experimental studies suggest a lower limit in the temporal resolution of approximately 100 ms at an SNR of 3. The multireference function approach was also applied to extract timing information from an event-related motor movement study where the subjects flexed a finger on cue. The event was repeated 19 times with the event's presentation staggered to yield an approximately 100-ms temporal sampling of the haemodynamic response over the entire presentation cycle. The timing differences among different regions of the brain activated by the motor task were clearly visualized and quantified by this method. The results suggest that it is possible to achieve a temporal resolution of /spl sim/200 ms in practice with this approach.

Reference in human and non-human primate communication: What does it take to refer?

PubMed

Sievers, Christine; Gruber, Thibaud

2016-07-01

The concept of functional reference has been used to isolate potentially referential vocal signals in animal communication. However, its relatedness to the phenomenon of reference in human language has recently been brought into question. While some researchers have suggested abandoning the concept of functional reference altogether, others advocate a revision of its definition to include contextual cues that play a role in signal production and perception. Empirical and theoretical work on functional reference has also put much emphasis on how the receiver understands the referential signal. However, reference, as defined in the linguistic literature, is an action of the producer, and therefore, any definition describing reference in non-human animals must also focus on the producer. To successfully determine whether a signal is used to refer, we suggest an approach from the field of pragmatics, taking a closer look at specific situations of signal production, specifically at the factors that influence the production of a signal by an individual. We define the concept of signaller's reference to identify intentional acts of reference produced by a signaller independently of the communicative modality, and illustrate it with a case study of the hoo vocalizations produced by wild chimpanzees during travel. This novel framework introduces an intentional approach to referentiality. It may therefore permit a closer comparison of human and non-human animal referential behaviour and underlying cognitive processes, allowing us to identify what may have emerged solely in the human lineage.

SU-F-T-582: Small Field Dosimetry in Radiosurgery Collimators with a Stealth Chamber

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

Azcona, J; Barbes, B

2016-06-15

Purpose: The extraction of a reference signal for measuring small fields in scanning mode can be problematic. In this work we describe the use of a transmission chamber in small field dosimetry for radiosurgery collimators and compare TMR curves obtained with stereotactic diode and microionization chamber. Methods: Four radiosurgery cones of diameters 5, 10, 12.5, and 15mm supplied by Elekta Medical were commissioned in a 6MV FFF beam from an Elekta Versa linac. A transmission chamber manufactured by IBA (Stealth chamber) was attached to the lower part of the collimators and used for PDD and profile measurements in scanning modemore » with a Scanditronix stereotactic diode. It was also used for centering the stereotactic diode in the water tank to measure TMR and output factors, by integrating the signal. TMR measurements for all collimators and the OF for the largest collimator were also acquired on a polystyrene PTW 29672 phantom with a PTW PinPoint 3D chamber 0.016 cm3 volume. Results: Measured TMR with diode and microionization chamber agreed very well with differences larger than 1% only for depths above 15cm, except the smaller collimator, for which differences were always smaller than 2%. Calculated TMR were significantly different (up to 7%) from measured TMR. The differences are attributed to the change in response of the diode with depth, because the effective field aperture varies with depth. Furthermore, neglecting the ratio of phantom-scatter factors in the conversion formula also contributes to this difference. OF measured with diode and chamber showed a difference of 3.5%. Conclusion: The transmission chamber overcomes the problem of extracting a reference signal and is of great help for small field commissioning. Calculating TMR from PDD is strongly discouraged. Good agreement was found when comparing measurements of TMR with stereotactic diode in water with measurements with microionization chamber in polystyrene.« less

DT-CWT Robust Filtering Algorithm for The Extraction of Reference and Waviness from 3-D Nano Scalar Surfaces

NASA Astrophysics Data System (ADS)

Ren, Zhi Ying.; Gao, ChengHui.; Han, GuoQiang.; Ding, Shen; Lin, JianXing.

2014-04-01

Dual tree complex wavelet transform (DT-CWT) exhibits superiority of shift invariance, directional selectivity, perfect reconstruction (PR), and limited redundancy and can effectively separate various surface components. However, in nano scale the morphology contains pits and convexities and is more complex to characterize. This paper presents an improved approach which can simultaneously separate reference and waviness and allows an image to remain robust against abnormal signals. We included a bilateral filtering (BF) stage in DT-CWT to solve imaging problems. In order to verify the feasibility of the new method and to test its performance we used a computer simulation based on three generations of Wavelet and Improved DT-CWT and we conducted two case studies. Our results show that the improved DT-CWT not only enhances the robustness filtering under the conditions of abnormal interference, but also possesses accuracy and reliability of the reference and waviness from the 3-D nano scalar surfaces.

Multicomponent quantitative spectroscopic analysis without reference substances based on ICA modelling.

PubMed

Monakhova, Yulia B; Mushtakova, Svetlana P

2017-05-01

A fast and reliable spectroscopic method for multicomponent quantitative analysis of targeted compounds with overlapping signals in complex mixtures has been established. The innovative analytical approach is based on the preliminary chemometric extraction of qualitative and quantitative information from UV-vis and IR spectral profiles of a calibration system using independent component analysis (ICA). Using this quantitative model and ICA resolution results of spectral profiling of "unknown" model mixtures, the absolute analyte concentrations in multicomponent mixtures and authentic samples were then calculated without reference solutions. Good recoveries generally between 95% and 105% were obtained. The method can be applied to any spectroscopic data that obey the Beer-Lambert-Bouguer law. The proposed method was tested on analysis of vitamins and caffeine in energy drinks and aromatic hydrocarbons in motor fuel with 10% error. The results demonstrated that the proposed method is a promising tool for rapid simultaneous multicomponent analysis in the case of spectral overlap and the absence/inaccessibility of reference materials.

Comparison of continuously acquired resting state and extracted analogues from active tasks.

PubMed

Ganger, Sebastian; Hahn, Andreas; Küblböck, Martin; Kranz, Georg S; Spies, Marie; Vanicek, Thomas; Seiger, René; Sladky, Ronald; Windischberger, Christian; Kasper, Siegfried; Lanzenberger, Rupert

2015-10-01

Functional connectivity analysis of brain networks has become an important tool for investigation of human brain function. Although functional connectivity computations are usually based on resting-state data, the application to task-specific fMRI has received growing attention. Three major methods for extraction of resting-state data from task-related signal have been proposed (1) usage of unmanipulated task data for functional connectivity; (2) regression against task effects, subsequently using the residuals; and (3) concatenation of baseline blocks located in-between task blocks. Despite widespread application in current research, consensus on which method best resembles resting-state seems to be missing. We, therefore, evaluated these techniques in a sample of 26 healthy controls measured at 7 Tesla. In addition to continuous resting-state, two different task paradigms were assessed (emotion discrimination and right finger-tapping) and five well-described networks were analyzed (default mode, thalamus, cuneus, sensorimotor, and auditory). Investigating the similarity to continuous resting-state (Dice, Intraclass correlation coefficient (ICC), R(2) ) showed that regression against task effects yields functional connectivity networks most alike to resting-state. However, all methods exhibited significant differences when compared to continuous resting-state and similarity metrics were lower than test-retest of two resting-state scans. Omitting global signal regression did not change these findings. Visually, the networks are highly similar, but through further investigation marked differences can be found. Therefore, our data does not support referring to resting-state when extracting signals from task designs, although functional connectivity computed from task-specific data may indeed yield interesting information. © 2015 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Comparison of continuously acquired resting state and extracted analogues from active tasks

PubMed Central

Ganger, Sebastian; Hahn, Andreas; Küblböck, Martin; Kranz, Georg S.; Spies, Marie; Vanicek, Thomas; Seiger, René; Sladky, Ronald; Windischberger, Christian; Kasper, Siegfried

2015-01-01

Abstract Functional connectivity analysis of brain networks has become an important tool for investigation of human brain function. Although functional connectivity computations are usually based on resting‐state data, the application to task‐specific fMRI has received growing attention. Three major methods for extraction of resting‐state data from task‐related signal have been proposed (1) usage of unmanipulated task data for functional connectivity; (2) regression against task effects, subsequently using the residuals; and (3) concatenation of baseline blocks located in‐between task blocks. Despite widespread application in current research, consensus on which method best resembles resting‐state seems to be missing. We, therefore, evaluated these techniques in a sample of 26 healthy controls measured at 7 Tesla. In addition to continuous resting‐state, two different task paradigms were assessed (emotion discrimination and right finger‐tapping) and five well‐described networks were analyzed (default mode, thalamus, cuneus, sensorimotor, and auditory). Investigating the similarity to continuous resting‐state (Dice, Intraclass correlation coefficient (ICC), R 2) showed that regression against task effects yields functional connectivity networks most alike to resting‐state. However, all methods exhibited significant differences when compared to continuous resting‐state and similarity metrics were lower than test‐retest of two resting‐state scans. Omitting global signal regression did not change these findings. Visually, the networks are highly similar, but through further investigation marked differences can be found. Therefore, our data does not support referring to resting‐state when extracting signals from task designs, although functional connectivity computed from task‐specific data may indeed yield interesting information. Hum Brain Mapp 36:4053–4063, 2015. © 2015 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. PMID:26178250

A contactless approach for respiratory gating in PET using continuous-wave radar

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

Ersepke, Thomas, E-mail: Thomas.Ersepke@rub.de; Büther, Florian; Heß, Mirco

Purpose: Respiratory gating is commonly used to reduce motion artifacts in positron emission tomography (PET). Clinically established methods for respiratory gating in PET require contact to the patient or a direct optical line between the sensor and the patient’s torso and time consuming preparation. In this work, a contactless method for capturing a respiratory signal during PET is presented based on continuous-wave radar. Methods: The proposed method relies on the principle of emitting an electromagnetic wave and detecting the phase shift of the reflected wave, modulated due to the respiratory movement of the patient’s torso. A 24 GHz carrier frequencymore » was chosen allowing wave propagation through plastic and clothing with high reflections at the skin surface. A detector module and signal processing algorithms were developed to extract a quantitative respiratory signal. The sensor was validated using a high precision linear table. During volunteer measurements and [{sup 18}F] FDG PET scans, the radar sensor was positioned inside the scanner bore of a PET/computed tomography scanner. As reference, pressure belt (one volunteer), depth camera-based (two volunteers, two patients), and PET data-driven (six patients) signals were acquired simultaneously and the signal correlation was quantified. Results: The developed system demonstrated a high measurement accuracy for movement detection within the submillimeter range. With the proposed method, small displacements of 25 μm could be detected, not considerably influenced by clothing or blankets. From the patient studies, the extracted respiratory radar signals revealed high correlation (Pearson correlation coefficient) to those derived from the external pressure belt and depth camera signals (r = 0.69–0.99) and moderate correlation to those of the internal data-driven signals (r = 0.53–0.70). In some cases, a cardiac signal could be visualized, due to the representation of the mechanical heart motion on the skin. Conclusions: Accurate respiratory signals were obtained successfully by the proposed method with high spatial and temporal resolution. By working without contact and passing through clothing and blankets, this approach minimizes preparation time and increases the convenience of the patient during the scan.« less

Production of acyl-homoserine lactone quorum-sensing signals is widespread in gram-negative Methylobacterium.

PubMed

Poonguzhali, Selvaraj; Madhaiyan, Munusamy; Sa, Tongmin

2007-02-01

Members of Methylobacterium, referred as pink-pigmented facultative methylotrophic bacteria, are frequently associated with terrestrial and aquatic plants, tending to form aggregates on the phyllosphere. We report here that the production of autoinducer molecules involved in the cell-to-cell signaling process, which is known as quorum sensing, is common among Methylobacterium species. Several strains of Methylobacterium were tested for their ability to produce N-acyl-homoserine lactone (AHL) signal molecules using different indicators. Most strains of Methylobacterium tested could elicit a positive response in Agrobacterium tumefaciens harboring lacZ fused to a gene that is regulated by autoinduction. The synthesis of these compounds was cell-density dependent, and the maximal activity was reached during the late exponential to stationary phases. The bacterial extracts were separated by thin-layer chromatography and bioassayed with A. tumefaciens NT1 (traR, tra::lacZ749). They revealed the production of various patterns of the signal molecules, which are strain dependent. At least two signal molecules could be detected in most of the strains tested, and comparison of their relative mobilities suggested that they are homologs of N-octanoyl-DL-homoserine lactone (C8-HSL) and N-decanoyl-DL-homoserine lactone (C10-HSL).

A new critical dimension metrology for chrome-on-glass substrates based on s-parameter measurements extracted from coplanar waveguide test structures

NASA Astrophysics Data System (ADS)

Nwokoye, Chidubem A.; Zaghloul, Mona; Cresswell, Michael W.; Allen, Richard A.; Murabito, Christine E.

2006-10-01

The technical objective of the work reported here is to assess whether radio-frequency (RF) measurements made on coplanar waveguide (CPW) test structures, which are replicated in conducting material on insulating substrates, could be employed to extract the critical dimension (CD) of the signal line using its center-to-center separation from the groundlines as a reference. The specific near-term objective is to assess whether this CPW-based CD-metrology has sensitivity and repeatability competitive with the other metrology techniques that are now used for chrome-on-glass (COG) photomasks. An affirmative answer is encouraging because advancing to a non-contact and non-vacuum implementation would then seem possible for this application. Our modeling of specific cases shows that, when the pitch of the replicated lines of the CPW is maintained constant, the sensitivity of its characteristic impedance to the CDs of the signal and ground lines is approximately 60 Ω/μm. This is a potentially useful result. For the same implementation, the quantity ∂C/∂w has a value of approximately 45 (pF/m)/μm, which appears to be large enough to provide acceptable accuracy.

System for monitoring an industrial or biological process

DOEpatents

Gross, Kenneth C.; Wegerich, Stephan W.; Vilim, Rick B.; White, Andrew M.

1998-01-01

A method and apparatus for monitoring and responding to conditions of an industrial process. Industrial process signals, such as repetitive manufacturing, testing and operational machine signals, are generated by a system. Sensor signals characteristic of the process are generated over a time length and compared to reference signals over the time length. The industrial signals are adjusted over the time length relative to the reference signals, the phase shift of the industrial signals is optimized to the reference signals and the resulting signals output for analysis by systems such as SPRT.

System for monitoring an industrial or biological process

DOEpatents

Gross, K.C.; Wegerich, S.W.; Vilim, R.B.; White, A.M.

1998-06-30

A method and apparatus are disclosed for monitoring and responding to conditions of an industrial process. Industrial process signals, such as repetitive manufacturing, testing and operational machine signals, are generated by a system. Sensor signals characteristic of the process are generated over a time length and compared to reference signals over the time length. The industrial signals are adjusted over the time length relative to the reference signals, the phase shift of the industrial signals is optimized to the reference signals and the resulting signals output for analysis by systems such as SPRT. 49 figs.

Peripheral vasomotor activity assessment using a continuous wavelet analysis on webcam photoplethysmographic signals.

PubMed

Bousefsaf, F; Maaoui, C; Pruski, A

2016-11-25

Vasoconstriction and vasodilation phenomena reflect the relative changes in the vascular bed. They induce particular modifications in the pulse wave magnitude. Webcams correspond to remote sensors that can be employed to measure the pulse wave in order to compute the pulse frequency. Record and analyze pulse wave signal with a low-cost webcam to extract the amplitude information and assess the vasomotor activity of the participant. Photoplethysmographic signals obtained from a webcam are analyzed through a continuous wavelet transform. The performance of the proposed filtering technique was evaluated using approved contact probes on a set of 12 healthy subjects after they perform a short but intense physical exercise. During the rest period, a cutaneous vasodilation is observable. High degrees of correlation between the webcam and a reference sensor were obtained. Webcams are low-cost and non-contact devices that can be used to reliably estimate both heart rate and peripheral vasomotor activity, notably during physical exertion.

The Zigbee wireless ECG measurement system design with a motion artifact remove algorithm by using adaptive filter and moving weighted factor

NASA Astrophysics Data System (ADS)

Kwon, Hyeokjun; Oh, Sechang; Varadan, Vijay K.

2012-04-01

The Electrocardiogram(ECG) signal is one of the bio-signals to check body status. Traditionally, the ECG signal was checked in the hospital. In these days, as the number of people who is interesting with periodic their health check increase, the requirement of self-diagnosis system development is being increased as well. Ubiquitous concept is one of the solutions of the self-diagnosis system. Zigbee wireless sensor network concept is a suitable technology to satisfy the ubiquitous concept. In measuring ECG signal, there are several kinds of methods in attaching electrode on the body called as Lead I, II, III, etc. In addition, several noise components occurred by different measurement situation such as experimenter's respiration, sensor's contact point movement, and the wire movement attached on sensor are included in pure ECG signal. Therefore, this paper is based on the two kinds of development concept. The first is the Zibee wireless communication technology, which can provide convenience and simpleness, and the second is motion artifact remove algorithm, which can detect clear ECG signal from measurement subject. The motion artifact created by measurement subject's movement or even respiration action influences to distort ECG signal, and the frequency distribution of the noises is around from 0.2Hz to even 30Hz. The frequencies are duplicated in actual ECG signal frequency, so it is impossible to remove the artifact without any distortion of ECG signal just by using low-pass filter or high-pass filter. The suggested algorithm in this paper has two kinds of main parts to extract clear ECG signal from measured original signal through an electrode. The first part is to extract motion noise signal from measured signal, and the second part is to extract clear ECG by using extracted motion noise signal and measured original signal. The paper suggests several techniques in order to extract motion noise signal such as predictability estimation theory, low pass filter, a filter including a moving weighted factor, peak to peak detection, and interpolation techniques. In addition, this paper introduces an adaptive filter in order to extract clear ECG signal by using extracted baseline noise signal and measured signal from sensor.

New developments in electronic reference controls for frequency domain optical sensing

NASA Astrophysics Data System (ADS)

Chatni, M. R.; Li, G.; Porterfield, D. M.

2009-05-01

The reference optical path is essential for optical systems which function on the basis of light interference. In the case of frequency domain (FD) fluorescence life-time optrodes, a reference LED is used as a standard for calculating the phase angle. The reference LED is configured so that radiation travels the same length to the detector as that of the fluorescence signal being analyzed. The phase shift, which provides details of fluorescence lifetime, is measured between these two signals - the fluorescence signal and reference LED signal, using a photodetector. We have designed, developed and implemented a FD optrode system without a reference LED. The key requirement of such a system is that phase shifts due to optics at wavelength of fluorescence and electronics have to be calibrated. In the reference-free system, the reference signal comes from the lock-in-amplifier which also drives the excitation LED. The lock-in-amplifier measures the phase shift between the excitation signal and the fluorescence emission signal from the photodetector and is locked at the frequency of modulation of the excitation signal. This insures higher signal to noise ratio and low-noise measurements. The reference-free optrode system removes some constraints on the coupling optics, which help improve the overall performance of the system. After development of electronics, and optimization of coupling optics, the system was calibrated in different oxygen concentration solutions to measure fluorescence intensity and lifetime of the oxygen sensitive dye platinum tetrakis (pentafluorophenyl) porphine (PtTFPP).

Apparatus and Method to Enable Precision and Fast Laser Frequency Tuning

NASA Technical Reports Server (NTRS)

Chen, Jeffrey R. (Inventor); Numata, Kenji (Inventor); Wu, Stewart T. (Inventor); Yang, Guangning (Inventor)

2015-01-01

An apparatus and method is provided to enable precision and fast laser frequency tuning. For instance, a fast tunable slave laser may be dynamically offset-locked to a reference laser line using an optical phase-locked loop. The slave laser is heterodyned against a reference laser line to generate a beatnote that is subsequently frequency divided. The phase difference between the divided beatnote and a reference signal may be detected to generate an error signal proportional to the phase difference. The error signal is converted into appropriate feedback signals to phase lock the divided beatnote to the reference signal. The slave laser frequency target may be rapidly changed based on a combination of a dynamically changing frequency of the reference signal, the frequency dividing factor, and an effective polarity of the error signal. Feed-forward signals may be generated to accelerate the slave laser frequency switching through laser tuning ports.

[A novel method of multi-channel feature extraction combining multivariate autoregression and multiple-linear principal component analysis].

PubMed

Wang, Jinjia; Zhang, Yanna

2015-02-01

Brain-computer interface (BCI) systems identify brain signals through extracting features from them. In view of the limitations of the autoregressive model feature extraction method and the traditional principal component analysis to deal with the multichannel signals, this paper presents a multichannel feature extraction method that multivariate autoregressive (MVAR) model combined with the multiple-linear principal component analysis (MPCA), and used for magnetoencephalography (MEG) signals and electroencephalograph (EEG) signals recognition. Firstly, we calculated the MVAR model coefficient matrix of the MEG/EEG signals using this method, and then reduced the dimensions to a lower one, using MPCA. Finally, we recognized brain signals by Bayes Classifier. The key innovation we introduced in our investigation showed that we extended the traditional single-channel feature extraction method to the case of multi-channel one. We then carried out the experiments using the data groups of IV-III and IV - I. The experimental results proved that the method proposed in this paper was feasible.

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.

Expected geoneutrino signal at JUNO

NASA Astrophysics Data System (ADS)

Strati, Virginia; Baldoncini, Marica; Callegari, Ivan; Mantovani, Fabio; McDonough, William F.; Ricci, Barbara; Xhixha, Gerti

2015-12-01

Constraints on the Earth's composition and on its radiogenic energy budget come from the detection of geoneutrinos. The Kamioka Liquid scintillator Antineutrino Detector (KamLAND) and Borexino experiments recently reported the geoneutrino flux, which reflects the amount and distribution of U and Th inside the Earth. The Jiangmen Underground Neutrino Observatory (JUNO) neutrino experiment, designed as a 20 kton liquid scintillator detector, will be built in an underground laboratory in South China about 53 km from the Yangjiang and Taishan nuclear power plants, each one having a planned thermal power of approximately 18 GW. Given the large detector mass and the intense reactor antineutrino flux, JUNO aims not only to collect high statistics antineutrino signals from reactors but also to address the challenge of discriminating the geoneutrino signal from the reactor background. The predicted geoneutrino signal at JUNO is terrestrial neutrino unit (TNU), based on the existing reference Earth model, with the dominant source of uncertainty coming from the modeling of the compositional variability in the local upper crust that surrounds (out to approximately 500 km) the detector. A special focus is dedicated to the 6° × 4° local crust surrounding the detector which is estimated to contribute for the 44% of the signal. On the basis of a worldwide reference model for reactor antineutrinos, the ratio between reactor antineutrino and geoneutrino signals in the geoneutrino energy window is estimated to be 0.7 considering reactors operating in year 2013 and reaches a value of 8.9 by adding the contribution of the future nuclear power plants. In order to extract useful information about the mantle's composition, a refinement of the abundance and distribution of U and Th in the local crust is required, with particular attention to the geochemical characterization of the accessible upper crust where 47% of the expected geoneutrino signal originates and this region contributes the major source of uncertainty.

Passive RFID Rotation Dimension Reduction via Aggregation

NASA Astrophysics Data System (ADS)

Matthews, Eric

Radio Frequency IDentification (RFID) has applications in object identification, position, and orientation tracking. RFID technology can be applied in hospitals for patient and equipment tracking, stores and warehouses for product tracking, robots for self-localisation, tracking hazardous materials, or locating any other desired object. Efficient and accurate algorithms that perform localisation are required to extract meaningful data beyond simple identification. A Received Signal Strength Indicator (RSSI) is the strength of a received radio frequency signal used to localise passive and active RFID tags. Many factors affect RSSI such as reflections, tag rotation in 3D space, and obstacles blocking line-of-sight. LANDMARC is a statistical method for estimating tag location based on a target tag's similarity to surrounding reference tags. LANDMARC does not take into account the rotation of the target tag. By either aggregating multiple reference tag positions at various rotations, or by determining a rotation value for a newly read tag, we can perform an expected value calculation based on a comparison to the k-most similar training samples via an algorithm called K-Nearest Neighbours (KNN) more accurately. By choosing the average as the aggregation function, we improve the relative accuracy of single-rotation LANDMARC localisation by 10%, and any-rotation localisation by 20%.

Constrained Null Space Component Analysis for Semiblind Source Separation Problem.

PubMed

Hwang, Wen-Liang; Lu, Keng-Shih; Ho, Jinn

2018-02-01

The blind source separation (BSS) problem extracts unknown sources from observations of their unknown mixtures. A current trend in BSS is the semiblind approach, which incorporates prior information on sources or how the sources are mixed. The constrained independent component analysis (ICA) approach has been studied to impose constraints on the famous ICA framework. We introduced an alternative approach based on the null space component (NCA) framework and referred to the approach as the c-NCA approach. We also presented the c-NCA algorithm that uses signal-dependent semidefinite operators, which is a bilinear mapping, as signatures for operator design in the c-NCA approach. Theoretically, we showed that the source estimation of the c-NCA algorithm converges with a convergence rate dependent on the decay of the sequence, obtained by applying the estimated operators on corresponding sources. The c-NCA can be formulated as a deterministic constrained optimization method, and thus, it can take advantage of solvers developed in optimization society for solving the BSS problem. As examples, we demonstrated electroencephalogram interference rejection problems can be solved by the c-NCA with proximal splitting algorithms by incorporating a sparsity-enforcing separation model and considering the case when reference signals are available.

Auditory Warnings, Signal-Referent Relations, and Natural Indicators: Re-Thinking Theory and Application

ERIC Educational Resources Information Center

Petocz, Agnes; Keller, Peter E.; Stevens, Catherine J.

2008-01-01

In auditory warning design the idea of the strength of the association between sound and referent has been pivotal. Research has proceeded via constructing classification systems of signal-referent associations and then testing predictions about ease of learning of different levels of signal-referent relation strength across and within different…

Biologically-based signal processing system applied to noise removal for signal extraction

DOEpatents

Fu, Chi Yung; Petrich, Loren I.

2004-07-13

The method and system described herein use a biologically-based signal processing system for noise removal for signal extraction. A wavelet transform may be used in conjunction with a neural network to imitate a biological system. The neural network may be trained using ideal data derived from physical principles or noiseless signals to determine to remove noise from the signal.

Tags, wireless communication systems, tag communication methods, and wireless communications methods

DOEpatents

Scott,; Jeff W. , Pratt; Richard, M [Richland, WA

2006-09-12

Tags, wireless communication systems, tag communication methods, and wireless communications methods are described. In one aspect, a tag includes a plurality of antennas configured to receive a plurality of first wireless communication signals comprising data from a reader, a plurality of rectifying circuits coupled with. respective individual ones of the antennas and configured to provide rectified signals corresponding to the first wireless communication signals, wherein the rectified signals are combined to produce a composite signal, an adaptive reference circuit configured to vary a reference signal responsive to the composite signal, a comparator coupled with the adaptive reference circuit and the rectifying circuits and configured to compare the composite signal with respect to the reference signal and to output the data responsive to the comparison, and processing circuitry configured to receive the data from the comparator and to process the data.

Method and Apparatus for Non-Invasive Measurement of Changes in Intracranial Pressure

NASA Technical Reports Server (NTRS)

Yost, William T. (Inventor); Cantrell, John H., Jr. (Inventor)

2004-01-01

A method and apparatus for measuring intracranial pressure. In one embodiment, the method comprises the steps of generating an information signal that comprises components (e.g., pulsatile changes and slow changes) that are related to intracranial pressure and blood pressure, generating a reference signal comprising pulsatile components that are solely related to blood pressure, processing the information and reference signals to determine the pulsatile components of the information signal that have generally the same phase as the pulsatile components of the reference signal, and removing from the information signal the pulsatile components determined to have generally the same phase as the pulsatile components of the reference signal so as to provide a data signal having components wherein substantially all of the components are related to intracranial pressure.

System and Method for Measuring the Transfer Function of a Guided Wave Device

NASA Technical Reports Server (NTRS)

Froggatt, Mark E. (Inventor); Erdogan, Turan (Inventor)

2002-01-01

A method/system are provided for measuring the NxN scalar transfer function elements for an N-port guided wave device. Optical energy of a selected wavelength is generated at a source and directed along N reference optical paths having N reference path lengths. Each reference optical path terminates in one of N detectors such that N reference signals are produced at the N detectors. The reference signals are indicative of amplitude, phase and frequency of the optical energy carried along the N reference optical paths. The optical energy from the source is also directed to the N-ports of the guided wave device and then on to each of the N detectors such that N measurement optical paths are defined between the source and each of the N detectors. A portion of the optical energy is modified in terms of at least one of the amplitude and phase to produce N modified signals at each of the N detectors. At each of the N detectors, each of the N modified signals is combined with a corresponding one of the N reference signals to produce corresponding N combined signals at each of the N detectors. A total of N(sup 2) measurement signals are generated by the N detectors. Each of the N(sup 2) measurement signals is sampled at a wave number increment (Delta)k so that N(sup 2) sampled signals are produced. The NxN transfer function elements are generated using the N(sup 2) sampled signals. Reference and measurement path length constraints are defined such that the N combined signals at each of the N detectors are spatially separated from one another in the time domain.

Kurtosis-Based Blind Source Extraction of Complex Non-Circular Signals with Application in EEG Artifact Removal in Real-Time

PubMed Central

Javidi, Soroush; Mandic, Danilo P.; Took, Clive Cheong; Cichocki, Andrzej

2011-01-01

A new class of complex domain blind source extraction algorithms suitable for the extraction of both circular and non-circular complex signals is proposed. This is achieved through sequential extraction based on the degree of kurtosis and in the presence of non-circular measurement noise. The existence and uniqueness analysis of the solution is followed by a study of fast converging variants of the algorithm. The performance is first assessed through simulations on well understood benchmark signals, followed by a case study on real-time artifact removal from EEG signals, verified using both qualitative and quantitative metrics. The results illustrate the power of the proposed approach in real-time blind extraction of general complex-valued sources. PMID:22319461

Average combination difference morphological filters for fault feature extraction of bearing

NASA Astrophysics Data System (ADS)

Lv, Jingxiang; Yu, Jianbo

2018-02-01

In order to extract impulse components from vibration signals with much noise and harmonics, a new morphological filter called average combination difference morphological filter (ACDIF) is proposed in this paper. ACDIF constructs firstly several new combination difference (CDIF) operators, and then integrates the best two CDIFs as the final morphological filter. This design scheme enables ACIDF to extract positive and negative impacts existing in vibration signals to enhance accuracy of bearing fault diagnosis. The length of structure element (SE) that affects the performance of ACDIF is determined adaptively by a new indicator called Teager energy kurtosis (TEK). TEK further improves the effectiveness of ACDIF for fault feature extraction. Experimental results on the simulation and bearing vibration signals demonstrate that ACDIF can effectively suppress noise and extract periodic impulses from bearing vibration signals.

Saw Palmetto Extract Inhibits Metastasis and Antiangiogenesis through STAT3 Signal Pathway in Glioma Cell.

PubMed

Ding, Hong; Shen, Jinglian; Yang, Yang; Che, Yuqin

2015-01-01

Signal transducer and activator of transcription factor 3 (STAT3) plays an important role in the proliferation and angiogenesis in human glioma. Previous research indicated that saw palmetto extract markedly inhibited the proliferation of human glioma cells through STAT3 signal pathway. But its effect on tumor metastasis and antiangiogenesis is not clear. This study is to further clear the impact of saw palmetto extract on glioma cell metastasis, antiangiogenesis, and its mechanism. TUNEL assay indicated that the apoptotic cells in the saw palmetto treated group are higher than that in the control group (p < 0.05). The apoptosis related protein is detected and the results revealed that saw palmetto extract inhibits the proliferation of human glioma. Meanwhile pSTAT3 is lower in the experimental group and CD34 is also inhibited in the saw palmetto treated group. This means that saw palmetto extract could inhibit the angiogenesis in glioma. We found that saw palmetto extract was an important phytotherapeutic drug against the human glioma through STAT3 signal pathway. Saw palmetto extract may be useful as an adjunctive therapeutic agent for treatment of individuals with glioma and other types of cancer in which STAT3 signaling is activated.

Piezoelectric extraction of ECG signal

NASA Astrophysics Data System (ADS)

Ahmad, Mahmoud Al

2016-11-01

The monitoring and early detection of abnormalities or variations in the cardiac cycle functionality are very critical practices and have significant impact on the prevention of heart diseases and their associated complications. Currently, in the field of biomedical engineering, there is a growing need for devices capable of measuring and monitoring a wide range of cardiac cycle parameters continuously, effectively and on a real-time basis using easily accessible and reusable probes. In this paper, the revolutionary generation and extraction of the corresponding ECG signal using a piezoelectric transducer as alternative for the ECG will be discussed. The piezoelectric transducer pick up the vibrations from the heart beats and convert them into electrical output signals. To this end, piezoelectric and signal processing techniques were employed to extract the ECG corresponding signal from the piezoelectric output voltage signal. The measured electrode based and the extracted piezoelectric based ECG traces are well corroborated. Their peaks amplitudes and locations are well aligned with each other.

Classification of vocal aging using parameters extracted from the glottal signal.

PubMed

Forero Mendoza, Leonardo A; Cataldo, Edson; Vellasco, Marley M B R; Silva, Marco A; Apolinário, José A

2014-09-01

This article proposes and evaluates a method to classify vocal aging using artificial neural network (ANN) and support vector machine (SVM), using the parameters extracted from the speech signal as inputs. For each recorded speech, from a corpus of male and female speakers of different ages, the corresponding glottal signal is obtained using an inverse filtering algorithm. The Mel Frequency Cepstrum Coefficients (MFCC) also extracted from the voice signal and the features extracted from the glottal signal are supplied to an ANN and an SVM with a previous selection. The selection is performed by a wrapper approach of the most relevant parameters. Three groups are considered for the aging-voice classification: young (aged 15-30 years), adult (aged 31-60 years), and senior (aged 61-90 years). The results are compared using different possibilities: with only the parameters extracted from the glottal signal, with only the MFCC, and with a combination of both. The results demonstrate that the best classification rate is obtained using the glottal signal features, which is a novel result and the main contribution of this article. Copyright © 2014 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

Study on common seasonal signals in GPS time series and environmental loadings using Multichannel Singular Spectrum Analysis

NASA Astrophysics Data System (ADS)

Gruszczynska, Marta; Rosat, Severine; Klos, Anna; Bogusz, Janusz

2017-04-01

Seasonal oscillations in the GPS position time series can arise from real geophysical effects and numerical artefacts. According to Dong et al. (2002) environmental loading effects can account for approximately 40% of the total variance of the annual signals in GPS time series, however using generally acknowledged methods (e.g. Least Squares Estimation, Wavelet Decomposition, Singular Spectrum Analysis) to model seasonal signals we are not able to separate real from spurious signals (effects of mismodelling aliased into annual period as well as draconitic). Therefore, we propose to use Multichannel Singular Spectrum Analysis (MSSA) to determine seasonal oscillations (with annual and semi-annual periods) from GPS position time series and environmental loading displacement models. The MSSA approach is an extension of the classical Karhunen-Loève method and it is a special case of SSA for multivariate time series. The main advantage of MSSA is the possibility to extract common seasonal signals for stations from selected area and to investigate the causality between a set of time series as well. In this research, we explored the ability of MSSA application to separate real geophysical effects from spurious effects in GPS time series. For this purpose, we used GPS position changes and environmental loading models. We analysed the topocentric time series from 250 selected stations located worldwide, delivered from Network Solution obtained by the International GNSS Service (IGS) as a contribution to the latest realization of the International Terrestrial Reference System (namely ITRF2014, Rebishung et al., 2016). We also researched atmospheric, hydrological and non-tidal oceanic loading models provided by the EOST/IPGS Loading Service in the Centre-of-Figure (CF) reference frame. The analysed displacements were estimated from ERA-Interim (surface pressure), MERRA-land (soil moisture and snow) as well as ECCO2 ocean bottom pressure. We used Multichannel Singular Spectrum Analysis to determine common seasonal signals in two case studies with adopted a 3-years lag-window as the optimal window size. We also inferred the statistical significance of oscillations through the Monte Carlo MSSA method (Allen and Robertson, 1996). In the first case study, we investigated the common spatio-temporal seasonal signals for all stations. For this purpose, we divided selected stations with respect to the continents. For instance, for stations located in Europe, seasonal oscillations accounts for approximately 45% of the GPS-derived data variance. Much higher variance of seasonal signals is explained by hydrological loadings of about 92%, while the non-tidal oceanic loading accounted for 31% of total variance. In the second case study, we analysed the capability of the MSSA method to establish a causality between several time series. Each of estimated Principal Component represents pattern of the common signal for all analysed data. For ZIMM station (Zimmerwald, Switzerland), the 1st, 2nd and 9th, 10th Principal Components, which accounts for 35% of the variance, corresponds to the annual and semi-annual signals. In this part, we applied the non-parametric MSSA approach to extract the common seasonal signals for GPS time series and environmental loadings for each of the 250 stations with clear statement, that some part of seasonal signal reflects the real geophysical effects. REFERENCES: 1. Allen, M. and Robertson, A.: 1996, Distinguishing modulated oscillations from coloured noise in multivariate datasets. Climate Dynamics, 12, No. 11, 775-784. DOI: 10.1007/s003820050142. 2. Dong, D., Fang, P., Bock, Y., Cheng, M.K. and Miyazaki, S.: 2002, Anatomy of apparent seasonal variations from GPS-derived site position time series. Journal of Geophysical Research, 107, No. B4, 2075. DOI: 10.1029/2001JB000573. 3. Rebischung, P., Altamimi, Z., Ray, J. and Garayt, B.: 2016, The IGS contribution to ITRF2014. Journal of Geodesy, 90, No. 7, 611-630. DOI:10.1007/s00190-016-0897-6.

Ridge extraction from the time-frequency representation (TFR) of signals based on an image processing approach: application to the analysis of uterine electromyogram AR TFR.

PubMed

Terrien, Jérémy; Marque, Catherine; Germain, Guy

2008-05-01

Time-frequency representations (TFRs) of signals are increasingly being used in biomedical research. Analysis of such representations is sometimes difficult, however, and is often reduced to the extraction of ridges, or local energy maxima. In this paper, we describe a new ridge extraction method based on the image processing technique of active contours or snakes. We have tested our method on several synthetic signals and for the analysis of uterine electromyogram or electrohysterogram (EHG) recorded during gestation in monkeys. We have also evaluated a postprocessing algorithm that is especially suited for EHG analysis. Parameters are evaluated on real EHG signals in different gestational periods. The presented method gives good results when applied to synthetic as well as EHG signals. We have been able to obtain smaller ridge extraction errors when compared to two other methods specially developed for EHG. The gradient vector flow (GVF) snake method, or GVF-snake method, appears to be a good ridge extraction tool, which could be used on TFR of mono or multicomponent signals with good results.

Independent Component Analysis applied to Ground-based observations

NASA Astrophysics Data System (ADS)

Martins-Filho, Walter; Griffith, Caitlin; Pearson, Kyle; Waldmann, Ingo; Alvarez-Candal, Alvaro; Zellem, Robert Thomas

2018-01-01

Transit measurements of Jovian-sized exoplanetary atmospheres allow one to study the composition of exoplanets, largely independent of the planet’s temperature profile. However, measurements of hot-Jupiter transits must archive a level of accuracy in the flux to determine the spectral modulation of the exoplanetary atmosphere. To accomplish this level of precision, we need to extract systematic errors, and, for ground-based measurements, the effects of Earth’s atmosphere, from signal due to the exoplanet, which is several orders of magnitude smaller. The effects of the terrestrial atmosphere and some of the time-dependent systematic errors of ground-based transit measurements are treated mainly by dividing the host star by a reference star at each wavelength and time step of the transit. Recently, Independent Component Analysis (ICA) have been used to remove systematics effects from the raw data of space-based observations (Waldmann, 2014, 2012; Morello et al., 2016, 2015). ICA is a statistical method born from the ideas of the blind-source separations studies, which can be used to de-trend several independent source signals of a data set (Hyvarinen and Oja, 2000). This technique requires no additional prior knowledge of the data set. In addition, this technique has the advantage of requiring no reference star. Here we apply the ICA to ground-based photometry of the exoplanet XO-2b recorded by the 61” Kuiper Telescope and compare the results of the ICA to those of a previous analysis from Zellem et al. (2015), which does not use ICA. We also simulate the effects of various conditions (concerning the systematic errors, noise and the stability of object on the detector) to determine the conditions under which an ICA can be used with high precision to extract the light curve of exoplanetary photometry measurements

Independent Component Analysis applied to Ground-based observations

NASA Astrophysics Data System (ADS)

Martins-Filho, Walter; Griffith, Caitlin Ann; Pearson, Kyle; Waldmann, Ingo; Alvarez-Candal, Alvaro; Zellem, Robert

2017-10-01

Transit measurements of Jovian-sized exoplanetary atmospheres allow one to study the composition of exoplanets, largely independent of the planet’s temperature profile. However, measurements of hot-Jupiter transits must archive a level of accuracy in the flux to determine the spectral modulations of the exoplanetary atmosphere. To accomplish this level of precision, we need to extract systematic errors, and, for ground-based measurements, the effects of Earth’s atmosphere, from signal due to the exoplanet, which is several orders of magnitudes smaller.The effects of the terrestrial atmosphere and some of the time dependent systematic errors of ground-based transit measurements are treated mainly by dividing the host star by a reference star at each wavelength and time step of the transit. Recently, Independent Component Analyses (ICA) have been used to remove systematics effects from the raw data of space-based observations (Waldmann, 2014, 2012; Morello et al., 2016, 2015). ICA is a statistical method born from the ideas of the blind-source separations studies, which can be used to de-trend several independent source signals of a data set (Hyvarinen and Oja, 2000). This technique requires no additional prior knowledge of the data set. In addition this technique has the advantage of requiring no reference star.Here we apply the ICA to ground-based photometry of the exoplanet XO-2b recorded by the 61” Kuiper Telescope and compare the results of the ICA to those of a previous analysis from Zellem et al. (2015), which does not use ICA. We also simulate the effects of various conditions (concerning the systematic errors, noise and the stability of object on the detector) to determine the conditions under which an ICA can be used with high precision to extract the light curve of exoplanetary photometry measurements.

European and Mexican vs US diagnostic extracts of Bermuda grass and cat in skin testing.

PubMed

Larenas-Linnemann, Désirée; Cruz, Alfredo Arias; Gutierrez, Isabel Rojo; Rodriguez, Pablo; Shah-Hosseini, Kijawasch; Michels, Alexandra; Mösges, Ralph

2011-05-01

Laboratory testing of various diagnostic extracts has shown lower potencies for several European and Mexican extracts relative to the US Food and Drug Administration (FDA) reference (10,000 BAU/mL). Quantitative skin prick testing (QSPT) with Dermatophagoides pteronyssinus extracts have previously shown a similar picture. To compare European and Mexican Bermuda grass (BG) and cat diagnostic extracts against an FDA-validated extract using QSPT. Six diagnostic BG and cat extracts (1 reference FDA extract, 3 European extracts, 1 imported nonstandardized extract from the United States, and 1 Mexican extract) were tested with quadruplicate QSPT, as a concentrate and as 2 serial 2-fold dilutions, in cat and BG allergic individuals. BG showed good dose response in wheal size for the concentrate (1:2-1:4 dilutions; steep part of the curve). Cat showed poorer dose response. The Wilcoxon test for linked random samples was used to investigate whether the distribution of the reference differed from each of the test extracts to a statistically significant degree (2-sided asymptotic significance, α = .05). All BG and 2 cat extracts were statistically less potent than the 10,000 BAU/mL US reference. European BG extracts were 7,700, 4,100, and 1,600 BAU/mL, and cat extracts were 12,500, 4,400, and 5,100 BAU/mL. The potency of some diagnostic extracts of BG and cat used in Europe, Mexico, and the United States differs, with the US extracts being generally more potent. On the basis of provocation tests, optimal diagnostic concentrations should be determined. Similar comparisons using other manufacturers and therapeutic extracts might be interesting. Copyright © 2011 American College of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

Acoustic⁻Seismic Mixed Feature Extraction Based on Wavelet Transform for Vehicle Classification in Wireless Sensor Networks.

PubMed

Zhang, Heng; Pan, Zhongming; Zhang, Wenna

2018-06-07

An acoustic⁻seismic mixed feature extraction method based on the wavelet coefficient energy ratio (WCER) of the target signal is proposed in this study for classifying vehicle targets in wireless sensor networks. The signal was decomposed into a set of wavelet coefficients using the à trous algorithm, which is a concise method used to implement the wavelet transform of a discrete signal sequence. After the wavelet coefficients of the target acoustic and seismic signals were obtained, the energy ratio of each layer coefficient was calculated as the feature vector of the target signals. Subsequently, the acoustic and seismic features were merged into an acoustic⁻seismic mixed feature to improve the target classification accuracy after the acoustic and seismic WCER features of the target signal were simplified using the hierarchical clustering method. We selected the support vector machine method for classification and utilized the data acquired from a real-world experiment to validate the proposed method. The calculated results show that the WCER feature extraction method can effectively extract the target features from target signals. Feature simplification can reduce the time consumption of feature extraction and classification, with no effect on the target classification accuracy. The use of acoustic⁻seismic mixed features effectively improved target classification accuracy by approximately 12% compared with either acoustic signal or seismic signal alone.

Extracting fingerprint of wireless devices based on phase noise and multiple level wavelet decomposition

NASA Astrophysics Data System (ADS)

Zhao, Weichen; Sun, Zhuo; Kong, Song

2016-10-01

Wireless devices can be identified by the fingerprint extracted from the signal transmitted, which is useful in wireless communication security and other fields. This paper presents a method that extracts fingerprint based on phase noise of signal and multiple level wavelet decomposition. The phase of signal will be extracted first and then decomposed by multiple level wavelet decomposition. The statistic value of each wavelet coefficient vector is utilized for constructing fingerprint. Besides, the relationship between wavelet decomposition level and recognition accuracy is simulated. And advertised decomposition level is revealed as well. Compared with previous methods, our method is simpler and the accuracy of recognition remains high when Signal Noise Ratio (SNR) is low.

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

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

Zhang, Y., E-mail: thuzhangyu@foxmail.com; Huang, S. L., E-mail: huangsling@tsinghua.edu.cn; Wang, S.

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

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

PubMed

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

2016-05-01

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

Extraction of features from ultrasound acoustic emissions: a tool to assess the hydraulic vulnerability of Norway spruce trunkwood?

PubMed Central

Rosner, Sabine; Klein, Andrea; Wimmer, Rupert; Karlsson, Bo

2011-01-01

Summary • The aim of this study was to assess the hydraulic vulnerability of Norway spruce (Picea abies) trunkwood by extraction of selected features of acoustic emissions (AEs) detected during dehydration of standard size samples. • The hydraulic method was used as the reference method to assess the hydraulic vulnerability of trunkwood of different cambial ages. Vulnerability curves were constructed by plotting the percentage loss of conductivity vs an overpressure of compressed air. • Differences in hydraulic vulnerability were very pronounced between juvenile and mature wood samples; therefore, useful AE features, such as peak amplitude, duration and relative energy, could be filtered out. The AE rates of signals clustered by amplitude and duration ranges and the AE energies differed greatly between juvenile and mature wood at identical relative water losses. • Vulnerability curves could be constructed by relating the cumulated amount of relative AE energy to the relative loss of water and to xylem tension. AE testing in combination with feature extraction offers a readily automated and easy to use alternative to the hydraulic method. PMID:16771986

The protein-protein interaction network of eyestalk, Y-organ and hepatopancreas in Chinese mitten crab Eriocheir sinensis.

PubMed

Hao, Tong; Zeng, Zheng; Wang, Bin; Zhang, Yichen; Liu, Yichen; Geng, Xuyun; Sun, Jinsheng

2014-03-27

The protein-protein interaction network (PIN) is an effective information tool for understanding the complex biological processes inside the cell and solving many biological problems such as signaling pathway identification and prediction of protein functions. Eriocheir sinensis is a highly-commercial aquaculture species with an unclear proteome background which hinders the construction and development of PIN for E. sinensis. However, in recent years, the development of next-generation deep-sequencing techniques makes it possible to get high throughput data of E. sinensis tanscriptome and subsequently obtain a systematic overview of the protein-protein interaction system. In this work we sequenced the transcriptional RNA of eyestalk, Y-organ and hepatopancreas in E. sinensis and generated a PIN of E. sinensis which included 3,223 proteins and 35,787 interactions. Each protein-protein interaction in the network was scored according to the homology and genetic relationship. The signaling sub-network, representing the signal transduction pathways in E. sinensis, was extracted from the global network, which depicted a global view of the signaling systems in E. sinensis. Seven basic signal transduction pathways were identified in E. sinensis. By investigating the evolution paths of the seven pathways, we found that these pathways got mature in different evolutionary stages. Moreover, the functions of unclassified proteins and unigenes in the PIN of E. sinensis were predicted. Specifically, the functions of 549 unclassified proteins related to 864 unclassified unigenes were assigned, which respectively covered 76% and 73% of all the unclassified proteins and unigenes in the network. The PIN generated in this work is the first large-scale PIN of aquatic crustacean, thereby providing a paradigmatic blueprint of the aquatic crustacean interactome. Signaling sub-network extracted from the global PIN depicts the interaction of different signaling proteins and the evolutionary paths of the identified signal transduction pathways. Furthermore, the function assignment of unclassified proteins based on the PIN offers a new reference in protein function exploration. More importantly, the construction of the E. sinensis PIN provides necessary experience for the exploration of PINs in other aquatic crustacean species.

Compensated intruder-detection systems

DOEpatents

McNeilly, David R.; Miller, William R.

1984-01-01

Intruder-detection systems in which intruder-induced signals are transmitted through a medium also receive spurious signals induced by changes in a climatic condition affecting the medium. To combat this, signals received from the detection medium are converted to a first signal. The system also provides a reference signal proportional to climate-induced changes in the medium. The first signal and the reference signal are combined for generating therefrom an output signal which is insensitive to the climatic changes in the medium. An alarm is energized if the output signal exceeds a preselected value. In one embodiment, an acoustic cable is coupled to a fence to generate a first electrical signal proportional to movements thereof. False alarms resulting from wind-induced movements of the fence (detection medium) are eliminated by providing an anemometer-driven voltage generator to provide a reference voltage proportional to the velocity of wind incident on the fence. An analog divider receives the first electrical signal and the reference signal as its numerator and denominator inputs, respectively, and generates therefrom an output signal which is insensitive to the wind-induced movements in the fence.

Constrained independent component analysis approach to nonobtrusive pulse rate measurements

NASA Astrophysics Data System (ADS)

Tsouri, Gill R.; Kyal, Survi; Dianat, Sohail; Mestha, Lalit K.

2012-07-01

Nonobtrusive pulse rate measurement using a webcam is considered. We demonstrate how state-of-the-art algorithms based on independent component analysis suffer from a sorting problem which hinders their performance, and propose a novel algorithm based on constrained independent component analysis to improve performance. We present how the proposed algorithm extracts a photoplethysmography signal and resolves the sorting problem. In addition, we perform a comparative study between the proposed algorithm and state-of-the-art algorithms over 45 video streams using a finger probe oxymeter for reference measurements. The proposed algorithm provides improved accuracy: the root mean square error is decreased from 20.6 and 9.5 beats per minute (bpm) for existing algorithms to 3.5 bpm for the proposed algorithm. An error of 3.5 bpm is within the inaccuracy expected from the reference measurements. This implies that the proposed algorithm provided performance of equal accuracy to the finger probe oximeter.

Constrained independent component analysis approach to nonobtrusive pulse rate measurements.

PubMed

Tsouri, Gill R; Kyal, Survi; Dianat, Sohail; Mestha, Lalit K

2012-07-01

Nonobtrusive pulse rate measurement using a webcam is considered. We demonstrate how state-of-the-art algorithms based on independent component analysis suffer from a sorting problem which hinders their performance, and propose a novel algorithm based on constrained independent component analysis to improve performance. We present how the proposed algorithm extracts a photoplethysmography signal and resolves the sorting problem. In addition, we perform a comparative study between the proposed algorithm and state-of-the-art algorithms over 45 video streams using a finger probe oxymeter for reference measurements. The proposed algorithm provides improved accuracy: the root mean square error is decreased from 20.6 and 9.5 beats per minute (bpm) for existing algorithms to 3.5 bpm for the proposed algorithm. An error of 3.5 bpm is within the inaccuracy expected from the reference measurements. This implies that the proposed algorithm provided performance of equal accuracy to the finger probe oximeter.

[Preparation of flavonoid reference standards from Scutellariae Radix under the guidance of high performance liquid chromatography-mass spectrometry analysis].

PubMed

Guo, Henan; Yang, Xuedong; Liu, Jun; Zheng, Wenfeng

2012-07-01

Flavonoid reference standards were targeted-prepared from Scutellariae Radix under the guidance of high performance liquid chromatography-mass spectrometry (HPLC-MS) analysis. With HPLC-MS analysis of Scutellariae Radix, 19 flavonoid components were identified by analyzing and comparing their retention times, ultraviolet spectra, and mass spectrometry data with literature. The separation and purification protocols of all targeted flavonoid reference standards were optimally designed according to the results of HPLC-MS analysis and related literature. The ethanol extract of Scutellariae Radix was suspended in water and extracted with petroleum ether, ethyl acetate, and n-butanol successively. The ethyl acetate extract and n-butanol extract were separately subjected to primary separation by low pressure reverse phase preparative chromatography. Then the fractions containing targeted compounds were further purified by low pressure reverse and normal phases preparative chromatography. Finally, baicalin and wogonoside reference standards were obtained from n-butanol extract; baicaelin, wogonin, and oroxylin A reference standards were obtained from ethyl acetate extract. The structures of the 5 reference standards were identified by mass spectrometry (MS) and 1H nuclear magnetic resonance (1H NMR) spectroscopy. The HPLC analytical results showed that the purities of the 5 reference standards were all above 98%. It is demonstrated that the rapid targeted-preparation method under the guidance of the HPLC-MS analysis is applicable for the isolation and preparation of chemical components in traditional Chinese medicines.

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

Vibration Sensor Monitoring of Nickel-Titanium Alloy Turning for Machinability Evaluation.

PubMed

Segreto, Tiziana; Caggiano, Alessandra; Karam, Sara; Teti, Roberto

2017-12-12

Nickel-Titanium (Ni-Ti) alloys are very difficult-to-machine materials causing notable manufacturing problems due to their unique mechanical properties, including superelasticity, high ductility, and severe strain-hardening. In this framework, the aim of this paper is to assess the machinability of Ni-Ti alloys with reference to turning processes in order to realize a reliable and robust in-process identification of machinability conditions. An on-line sensor monitoring procedure based on the acquisition of vibration signals was implemented during the experimental turning tests. The detected vibration sensorial data were processed through an advanced signal processing method in time-frequency domain based on wavelet packet transform (WPT). The extracted sensorial features were used to construct WPT pattern feature vectors to send as input to suitably configured neural networks (NNs) for cognitive pattern recognition in order to evaluate the correlation between input sensorial information and output machinability conditions.

Vibration Sensor Monitoring of Nickel-Titanium Alloy Turning for Machinability Evaluation

PubMed Central

Segreto, Tiziana; Karam, Sara; Teti, Roberto

2017-01-01

Nickel-Titanium (Ni-Ti) alloys are very difficult-to-machine materials causing notable manufacturing problems due to their unique mechanical properties, including superelasticity, high ductility, and severe strain-hardening. In this framework, the aim of this paper is to assess the machinability of Ni-Ti alloys with reference to turning processes in order to realize a reliable and robust in-process identification of machinability conditions. An on-line sensor monitoring procedure based on the acquisition of vibration signals was implemented during the experimental turning tests. The detected vibration sensorial data were processed through an advanced signal processing method in time-frequency domain based on wavelet packet transform (WPT). The extracted sensorial features were used to construct WPT pattern feature vectors to send as input to suitably configured neural networks (NNs) for cognitive pattern recognition in order to evaluate the correlation between input sensorial information and output machinability conditions. PMID:29231864

Saw Palmetto Extract Inhibits Metastasis and Antiangiogenesis through STAT3 Signal Pathway in Glioma Cell

PubMed Central

Ding, Hong; Shen, Jinglian; Yang, Yang; Che, Yuqin

2015-01-01

Signal transducer and activator of transcription factor 3 (STAT3) plays an important role in the proliferation and angiogenesis in human glioma. Previous research indicated that saw palmetto extract markedly inhibited the proliferation of human glioma cells through STAT3 signal pathway. But its effect on tumor metastasis and antiangiogenesis is not clear. This study is to further clear the impact of saw palmetto extract on glioma cell metastasis, antiangiogenesis, and its mechanism. TUNEL assay indicated that the apoptotic cells in the saw palmetto treated group are higher than that in the control group (p < 0.05). The apoptosis related protein is detected and the results revealed that saw palmetto extract inhibits the proliferation of human glioma. Meanwhile pSTAT3 is lower in the experimental group and CD34 is also inhibited in the saw palmetto treated group. This means that saw palmetto extract could inhibit the angiogenesis in glioma. We found that saw palmetto extract was an important phytotherapeutic drug against the human glioma through STAT3 signal pathway. Saw palmetto extract may be useful as an adjunctive therapeutic agent for treatment of individuals with glioma and other types of cancer in which STAT3 signaling is activated. PMID:26788112

Method and apparatus for frequency spectrum analysis

NASA Technical Reports Server (NTRS)

Cole, Steven W. (Inventor)

1992-01-01

A method for frequency spectrum analysis of an unknown signal in real-time is discussed. The method is based upon integration of 1-bit samples of signal voltage amplitude corresponding to sine or cosine phases of a controlled center frequency clock which is changed after each integration interval to sweep the frequency range of interest in steps. Integration of samples during each interval is carried out over a number of cycles of the center frequency clock spanning a number of cycles of an input signal to be analyzed. The invention may be used to detect the frequency of at least two signals simultaneously. By using a reference signal of known frequency and voltage amplitude (added to the two signals for parallel processing in the same way, but in a different channel with a sampling at the known frequency and phases of the reference signal), the absolute voltage amplitude of the other two signals may be determined by squaring the sine and cosine integrals of each channel and summing the squares to obtain relative power measurements in all three channels and, from the known voltage amplitude of the reference signal, obtaining an absolute voltage measurement for the other two signals by multiplying the known voltage of the reference signal with the ratio of the relative power of each of the other two signals to the relative power of the reference signal.

Selection of Mother Wavelet Functions for Multi-Channel EEG Signal Analysis during a Working Memory Task

PubMed Central

Al-Qazzaz, Noor Kamal; Hamid Bin Mohd Ali, Sawal; Ahmad, Siti Anom; Islam, Mohd Shabiul; Escudero, Javier

2015-01-01

We performed a comparative study to select the efficient mother wavelet (MWT) basis functions that optimally represent the signal characteristics of the electrical activity of the human brain during a working memory (WM) task recorded through electro-encephalography (EEG). Nineteen EEG electrodes were placed on the scalp following the 10–20 system. These electrodes were then grouped into five recording regions corresponding to the scalp area of the cerebral cortex. Sixty-second WM task data were recorded from ten control subjects. Forty-five MWT basis functions from orthogonal families were investigated. These functions included Daubechies (db1–db20), Symlets (sym1–sym20), and Coiflets (coif1–coif5). Using ANOVA, we determined the MWT basis functions with the most significant differences in the ability of the five scalp regions to maximize their cross-correlation with the EEG signals. The best results were obtained using “sym9” across the five scalp regions. Therefore, the most compatible MWT with the EEG signals should be selected to achieve wavelet denoising, decomposition, reconstruction, and sub-band feature extraction. This study provides a reference of the selection of efficient MWT basis functions. PMID:26593918

Selection of Mother Wavelet Functions for Multi-Channel EEG Signal Analysis during a Working Memory Task.

PubMed

Al-Qazzaz, Noor Kamal; Bin Mohd Ali, Sawal Hamid; Ahmad, Siti Anom; Islam, Mohd Shabiul; Escudero, Javier

2015-11-17

We performed a comparative study to select the efficient mother wavelet (MWT) basis functions that optimally represent the signal characteristics of the electrical activity of the human brain during a working memory (WM) task recorded through electro-encephalography (EEG). Nineteen EEG electrodes were placed on the scalp following the 10-20 system. These electrodes were then grouped into five recording regions corresponding to the scalp area of the cerebral cortex. Sixty-second WM task data were recorded from ten control subjects. Forty-five MWT basis functions from orthogonal families were investigated. These functions included Daubechies (db1-db20), Symlets (sym1-sym20), and Coiflets (coif1-coif5). Using ANOVA, we determined the MWT basis functions with the most significant differences in the ability of the five scalp regions to maximize their cross-correlation with the EEG signals. The best results were obtained using "sym9" across the five scalp regions. Therefore, the most compatible MWT with the EEG signals should be selected to achieve wavelet denoising, decomposition, reconstruction, and sub-band feature extraction. This study provides a reference of the selection of efficient MWT basis functions.

E&V (Evaluation and Validation) Reference Manual, Version 1.0.

DTIC Science & Technology

1988-07-01

references featured in the Reference Manual. G-05097a GENERAL REFERENCE INFORMATION EXTRACTED , FROM * INDEXES AND CROSS REFERENCES CHAPTER 4...at E&V techniques through many different paths, and provides a means to extract useful information along the way. /^c^^s; /r^ ^yr*•**•»» * L...electronically (preferred) to szymansk@ajpo.sei.cmu.edu or by regular mail to Mr. Raymond Szymanski . AFWAUAAAF, Wright Patterson AFB, OH 45433-6543. ES-2

Weak characteristic information extraction from early fault of wind turbine generator gearbox

NASA Astrophysics Data System (ADS)

Xu, Xiaoli; Liu, Xiuli

2017-09-01

Given the weak early degradation characteristic information during early fault evolution in gearbox of wind turbine generator, traditional singular value decomposition (SVD)-based denoising may result in loss of useful information. A weak characteristic information extraction based on μ-SVD and local mean decomposition (LMD) is developed to address this problem. The basic principle of the method is as follows: Determine the denoising order based on cumulative contribution rate, perform signal reconstruction, extract and subject the noisy part of signal to LMD and μ-SVD denoising, and obtain denoised signal through superposition. Experimental results show that this method can significantly weaken signal noise, effectively extract the weak characteristic information of early fault, and facilitate the early fault warning and dynamic predictive maintenance.

Method and apparatus for measuring response time

DOEpatents

Johanson, Edward W.; August, Charles

1985-01-01

A method of measuring the response time of an electrical instrument which generates an output signal in response to the application of a specified input, wherein the output signal varies as a function of time and when subjected to a step input approaches a steady-state value, comprises the steps of: (a) applying a step input of predetermined value to the electrical instrument to generate an output signal; (b) simultaneously starting a timer; (c) comparing the output signal to a reference signal to generate a stop signal when the output signal is substantially equal to the reference signal, the reference signal being a specified percentage of the steady-state value of the output signal corresponding to the predetermined value of the step input; and (d) applying the stop signal when generated to stop the timer.

Method and apparatus for measuring response time

DOEpatents

Johanson, E.W.; August, C.

1983-08-11

A method of measuring the response time of an electrical instrument which generates an output signal in response to the application of a specified input, wherein the output signal varies as a function of time and when subjected to a step input approaches a steady-state value, comprises the steps of: (a) applying a step input of predetermined value to the electrical instrument to generate an output signal; (b) simultaneously starting a timer; (c) comparing the output signal to a reference signal to generate a stop signal when the output signal is substantially equal to the reference signal, the reference signal being a specified percentage of the steady-state value of the output signal corresponding to the predetermined value of the step input; and (d) applying the stop signal when generated to stop the timer.

PyEEG: an open source Python module for EEG/MEG feature extraction.

PubMed

Bao, Forrest Sheng; Liu, Xin; Zhang, Christina

2011-01-01

Computer-aided diagnosis of neural diseases from EEG signals (or other physiological signals that can be treated as time series, e.g., MEG) is an emerging field that has gained much attention in past years. Extracting features is a key component in the analysis of EEG signals. In our previous works, we have implemented many EEG feature extraction functions in the Python programming language. As Python is gaining more ground in scientific computing, an open source Python module for extracting EEG features has the potential to save much time for computational neuroscientists. In this paper, we introduce PyEEG, an open source Python module for EEG feature extraction.

PyEEG: An Open Source Python Module for EEG/MEG Feature Extraction

PubMed Central

Bao, Forrest Sheng; Liu, Xin; Zhang, Christina

2011-01-01

Computer-aided diagnosis of neural diseases from EEG signals (or other physiological signals that can be treated as time series, e.g., MEG) is an emerging field that has gained much attention in past years. Extracting features is a key component in the analysis of EEG signals. In our previous works, we have implemented many EEG feature extraction functions in the Python programming language. As Python is gaining more ground in scientific computing, an open source Python module for extracting EEG features has the potential to save much time for computational neuroscientists. In this paper, we introduce PyEEG, an open source Python module for EEG feature extraction. PMID:21512582

Low complexity feature extraction for classification of harmonic signals

NASA Astrophysics Data System (ADS)

William, Peter E.

In this dissertation, feature extraction algorithms have been developed for extraction of characteristic features from harmonic signals. The common theme for all developed algorithms is the simplicity in generating a significant set of features directly from the time domain harmonic signal. The features are a time domain representation of the composite, yet sparse, harmonic signature in the spectral domain. The algorithms are adequate for low-power unattended sensors which perform sensing, feature extraction, and classification in a standalone scenario. The first algorithm generates the characteristic features using only the duration between successive zero-crossing intervals. The second algorithm estimates the harmonics' amplitudes of the harmonic structure employing a simplified least squares method without the need to estimate the true harmonic parameters of the source signal. The third algorithm, resulting from a collaborative effort with Daniel White at the DSP Lab, University of Nebraska-Lincoln, presents an analog front end approach that utilizes a multichannel analog projection and integration to extract the sparse spectral features from the analog time domain signal. Classification is performed using a multilayer feedforward neural network. Evaluation of the proposed feature extraction algorithms for classification through the processing of several acoustic and vibration data sets (including military vehicles and rotating electric machines) with comparison to spectral features shows that, for harmonic signals, time domain features are simpler to extract and provide equivalent or improved reliability over the spectral features in both the detection probabilities and false alarm rate.

Diagnostic features of Alzheimer's disease extracted from PET sinograms

NASA Astrophysics Data System (ADS)

Sayeed, A.; Petrou, M.; Spyrou, N.; Kadyrov, A.; Spinks, T.

2002-01-01

Texture analysis of positron emission tomography (PET) images of the brain is a very difficult task, due to the poor signal to noise ratio. As a consequence, very few techniques can be implemented successfully. We use a new global analysis technique known as the Trace transform triple features. This technique can be applied directly to the raw sinograms to distinguish patients with Alzheimer's disease (AD) from normal volunteers. FDG-PET images of 18 AD and 10 normal controls obtained from the same CTI ECAT-953 scanner were used in this study. The Trace transform triple feature technique was used to extract features that were invariant to scaling, translation and rotation, referred to as invariant features, as well as features that were sensitive to rotation but invariant to scaling and translation, referred to as sensitive features in this study. The features were used to classify the groups using discriminant function analysis. Cross-validation tests using stepwise discriminant function analysis showed that combining both sensitive and invariant features produced the best results, when compared with the clinical diagnosis. Selecting the five best features produces an overall accuracy of 93% with sensitivity of 94% and specificity of 90%. This is comparable with the classification accuracy achieved by Kippenhan et al (1992), using regional metabolic activity.

The feature extraction of "cat-eye" targets based on bi-spectrum

NASA Astrophysics Data System (ADS)

Zhang, Tinghua; Fan, Guihua; Sun, Huayan

2016-10-01

In order to resolve the difficult problem of detection and identification of optical targets in complex background or in long-distance transmission, this paper mainly study the range profiles of "cat-eye" targets using bi-spectrum. For the problems of laser echo signal attenuation serious and low Signal-Noise Ratio (SNR), the multi-pulse laser signal echo signal detection algorithm which is based on high-order cumulant, filter processing and the accumulation of multi-pulse is proposed. This could improve the detection range effectively. In order to extract the stable characteristics of the one-dimensional range profile coming from the cat-eye targets, a method is proposed which extracts the bi-spectrum feature, and uses the singular value decomposition to simplify the calculation. Then, by extracting data samples of different distance, type and incidence angle, verify the stability of the eigenvector and effectiveness extracted by bi-spectrum.

Combing signals from spontaneous reports and electronic health records for detection of adverse drug reactions

PubMed Central

Harpaz, Rave; Vilar, Santiago; DuMouchel, William; Salmasian, Hojjat; Haerian, Krystl; Shah, Nigam H; Chase, Herbert S; Friedman, Carol

2013-01-01

Objective Data-mining algorithms that can produce accurate signals of potentially novel adverse drug reactions (ADRs) are a central component of pharmacovigilance. We propose a signal-detection strategy that combines the adverse event reporting system (AERS) of the Food and Drug Administration and electronic health records (EHRs) by requiring signaling in both sources. We claim that this approach leads to improved accuracy of signal detection when the goal is to produce a highly selective ranked set of candidate ADRs. Materials and methods Our investigation was based on over 4 million AERS reports and information extracted from 1.2 million EHR narratives. Well-established methodologies were used to generate signals from each source. The study focused on ADRs related to three high-profile serious adverse reactions. A reference standard of over 600 established and plausible ADRs was created and used to evaluate the proposed approach against a comparator. Results The combined signaling system achieved a statistically significant large improvement over AERS (baseline) in the precision of top ranked signals. The average improvement ranged from 31% to almost threefold for different evaluation categories. Using this system, we identified a new association between the agent, rasburicase, and the adverse event, acute pancreatitis, which was supported by clinical review. Conclusions The results provide promising initial evidence that combining AERS with EHRs via the framework of replicated signaling can improve the accuracy of signal detection for certain operating scenarios. The use of additional EHR data is required to further evaluate the capacity and limits of this system and to extend the generalizability of these results. PMID:23118093

Oryza sativa (Rice) Hull Extract Inhibits Lipopolysaccharide-Induced Inflammatory Response in RAW264.7 Macrophages by Suppressing Extracellular Signal-regulated Kinase, c-Jun N-terminal Kinase, and Nuclear Factor-κB Activation.

PubMed

Ha, Sang Keun; Sung, Jeehye; Choi, Inwook; Kim, Yoonsook

2016-01-01

Rice ( Oryza sativa ) is a major cereal crop in many Asian countries and an important staple food source. Rice hulls have been reported to possess antioxidant activities. In this study, we evaluated the antiinflammatory effects of rice hull extract and associated signal transduction mechanisms in lipopolysaccharide (LPS)-stimulated RAW 264.7 macrophages. We found that rice hull extract inhibited nitric oxide (NO) and prostaglandin E 2 by suppressing the expression of inducible NO synthase and cyclooxygenase-2, respectively. The release of interleukin-1β and tumor necrosis factor-α was also reduced in a dose-dependent manner. Furthermore, rice hull extract attenuated the activation of nuclear factor-kappa B (NF-κB), as well as the phosphorylation of mitogen-activated protein kinases, extracellular signal-regulated kinase (ERK), and c-Jun N-terminal kinase (JNK), in LPS-stimulated RAW264.7 cells. This suggests that rice hull extract decreases the production of inflammatory mediators by downregulating ERK and JNK and the NF-κB signal pathway in RAW 264.7 cells. Rice hull extract inhibits the lipopolysaccharide-induced inflammatory response in RAW264.7 macrophages.Rice hull extract inhibited nitric oxide and prostaglandin E 2 by suppressing the expression of inducible NO synthase and cyclooxygenase-2, respectively.Rice hull extract exerted anti-inflammatory effect through inhibition of nuclear factor-kappa B, extracellular signal-regulated kinase and c-Jun N-terminal kinase signaling pathways.Rice hull extract may provide a potential therapeutic approach for inflammatory diseases. Abbreviations used: COX-2: cyclooxygenase-2, ERK: extracellular signal-regulated kinase, IκB: inhibitory kappa B, IL-1β: interleukin-1β, iNOS: inducible NO synthase, JNK: c-Jun N-terminal kinase, LPS: lipopolysaccharide, MAPKs: mitogen-activated protein kinases, NF-κB: nuclear factor-κB, NO: nitric oxide, PGE2: prostaglandin E2, RHE: rice hull extract, ROS: reactive oxygen species, TNF-α: tumor necrosis factor-α.

[Evaluation of the total biological activity and allergenic composition of allergenic extracts].

PubMed

Lombardero, M; González, R; Duffort, O; Juan, F; Ayuso, R; Ventas, P; Cortés, C; Carreira, J

1986-01-01

In the present study, a complete procedure is presented in order to standardize allergenic extracts, the meaning of which is the measurement of the total allergenic activity and the determination of the allergenic composition. The measurement of the biological activity comprises 2 steps: Preparation of Reference Extracts and determination of their "in vivo" activity. Evaluation of the total allergenic activity of extracts for clinical use. Reference extracts were prepared from the main allergens and their "in vivo" biological activity was determined by a quantitative skin prick test in a sample of at least 30 allergic patients. By definition, the protein concentration of Reference Extract that produces, in the allergic population, a geometric mean wheal of 75 mm.2 has an activity of 100 biological units (BUs). The determination of the biological activity of a problem extract is made by RAST inhibition. The sample is compared with the corresponding Reference Extract by this technique and, from this comparison, it is possible to quantify the activity of the problem extract in biologic units (BUs) with clinical significance. Likewise, different techniques have been used to determine the allergenic composition of extracts. These techniques comprise 2 steps: Separation of the components of the extract. Identification of the components that bind specific human IgE. The separation of the components of the extract has been carried out by isoelectric focusing (IEF) and electrophoresis in the presence of sodium dodecyl sulphate (SDS-PAGE). In order to identify the allergenic components, an immunoblotting technique has been employed. The separated components in the IEF gel or SDS-PAGE gel are transferred to a nitrocellulose sheet and later on, this membrane is overlaid with a serum pool from allergic patients and a mouse monoclonal anti-human IgE, labelled with 125I. Finally, the autoradiography of the nitrocellulose membrane is obtained. In this way it is possible to compare the allergenic composition of an extract with the corresponding Reference Extract and so to employ for clinical use only those extracts with the right allergenic composition.

Wire bonding quality monitoring via refining process of electrical signal from ultrasonic generator

NASA Astrophysics Data System (ADS)

Feng, Wuwei; Meng, Qingfeng; Xie, Youbo; Fan, Hong

2011-04-01

In this paper, a technique for on-line quality detection of ultrasonic wire bonding is developed. The electrical signals from the ultrasonic generator supply, namely, voltage and current, are picked up by a measuring circuit and transformed into digital signals by a data acquisition system. A new feature extraction method is presented to characterize the transient property of the electrical signals and further evaluate the bond quality. The method includes three steps. First, the captured voltage and current are filtered by digital bandpass filter banks to obtain the corresponding subband signals such as fundamental signal, second harmonic, and third harmonic. Second, each subband envelope is obtained using the Hilbert transform for further feature extraction. Third, the subband envelopes are, respectively, separated into three phases, namely, envelope rising, stable, and damping phases, to extract the tiny waveform changes. The different waveform features are extracted from each phase of these subband envelopes. The principal components analysis (PCA) method is used for the feature selection in order to remove the relevant information and reduce the dimension of original feature variables. Using the selected features as inputs, an artificial neural network (ANN) is constructed to identify the complex bond fault pattern. By analyzing experimental data with the proposed feature extraction method and neural network, the results demonstrate the advantages of the proposed feature extraction method and the constructed artificial neural network in detecting and identifying bond quality.

Determination of sub-microgram amounts of selenium in geological materials by atomic-absorption spectrophotometry with electrothermal atomisation after solvent extraction

USGS Publications Warehouse

Sanzolone, R.F.; Chao, T.T.

1981-01-01

An atomic-absorption spectrophotometric method with electrothermal atomisation has been developed for the determination of selenium in geological materials. The sample is decomposed with a mixture of nitric, perchloric and hydrofluoric acids and heated with hydrochloric acid to reduce selenium to selenium (IV). Selenium is then extracted into toluene from a hydrochloric acid - hydrobromic acid medium containing iron. A few microlitres of the toluene extract are injected into a carbon rod atomiser, using a nickel solution as a matrix modifier. The limits of determination are 0.2-200 p.p.m. of selenium in a geological sample. For concentrations between 0.05 and 0.2 p.p.m., back-extraction of the selenium into dilute hydrochloric acid is employed before atomisation. Selenium values for reference samples obtained by replicate analysis are in general agreement with those reported by other workers, with relative standard deviations ranging from 4.1 to 8.8%. Recoveries of selenium spiked at two levels were 98-108%. Major and trace elements commonly encountered in geological materials do not interfere. Arsenic has a suppressing effect on the selenium signals, but only when its concentration is greater than 1000 p.p.m. Nitric acid interferes seriously with the extraction of selenium and must be removed by evaporation in the sample-digestion step.

Extracting hurricane eye morphology from spaceborne SAR images using morphological analysis

NASA Astrophysics Data System (ADS)

Lee, Isabella K.; Shamsoddini, Ali; Li, Xiaofeng; Trinder, John C.; Li, Zeyu

2016-07-01

Hurricanes are among the most destructive global natural disasters. Thus recognizing and extracting their morphology is important for understanding their dynamics. Conventional optical sensors, due to cloud cover associated with hurricanes, cannot reveal the intense air-sea interaction occurring at the sea surface. In contrast, the unique capabilities of spaceborne synthetic aperture radar (SAR) data for cloud penetration, and its backscattering signal characteristics enable the extraction of the sea surface roughness. Therefore, SAR images enable the measurement of the size and shape of hurricane eyes, which reveal their evolution and strength. In this study, using six SAR hurricane images, we have developed a mathematical morphology method for automatically extracting the hurricane eyes from C-band SAR data. Skeleton pruning based on discrete skeleton evolution (DSE) was used to ensure global and local preservation of the hurricane eye shape. This distance weighted algorithm applied in a hierarchical structure for extraction of the edges of the hurricane eyes, can effectively avoid segmentation errors by reducing redundant skeletons attributed to speckle noise along the edges of the hurricane eye. As a consequence, the skeleton pruning has been accomplished without deficiencies in the key hurricane eye skeletons. A morphology-based analyses of the subsequent reconstructions of the hurricane eyes shows a high degree of agreement with the hurricane eye areas derived from reference data based on NOAA manual work.

Theoretical analysis of a method for extracting the phase of a phase-amplitude modulated signal generated by a direct-modulated optical injection-locked semiconductor laser

NASA Astrophysics Data System (ADS)

Lee, Hwan; Cho, Jun-Hyung; Sung, Hyuk-Kee

2017-05-01

The phase modulation (PM) and amplitude modulation (AM) of optical signals can be achieved using a direct-modulated (DM) optical injection-locked (OIL) semiconductor laser. We propose and theoretically analyze a simple method to extract the phase component of a PM signal produced by a DM-OIL semiconductor laser. The pure AM component of the combined PM-AM signal can be isolated by square-law detection in a photodetector and can then be used to compensate for the PM-AM signal based on an optical homodyne method. Using the AM compensation technique, we successfully developed a simple and cost-effective phase extraction method applicable to the PM-AM optical signal of a DM-OIL semiconductor laser.

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.

Controllers for Battery Chargers and Battery Chargers Therefrom

NASA Technical Reports Server (NTRS)

Elmes, John (Inventor); Kersten, Rene (Inventor); Pepper, Michael (Inventor)

2014-01-01

A controller for a battery charger that includes a power converter has parametric sensors for providing a sensed Vin signal, a sensed Vout signal and a sensed Iout signal. A battery current regulator (BCR) is coupled to receive the sensed Iout signal and an Iout reference, and outputs a first duty cycle control signal. An input voltage regulator (IVR) receives the sensed Vin signal and a Vin reference. The IVR provides a second duty cycle control signal. A processor receives the sensed Iout signal and utilizes a Maximum Power Point Tracking (MPPT) algorithm, and provides the Vin reference to the IVR. A selection block forwards one of the first and second duty cycle control signals as a duty cycle control signal to the power converter. Dynamic switching between the first and second duty cycle control signals maximizes the power delivered to the battery.

Noninvasive extraction of fetal electrocardiogram based on Support Vector Machine

NASA Astrophysics Data System (ADS)

Fu, Yumei; Xiang, Shihan; Chen, Tianyi; Zhou, Ping; Huang, Weiyan

2015-10-01

The fetal electrocardiogram (FECG) signal has important clinical value for diagnosing the fetal heart diseases and choosing suitable therapeutics schemes to doctors. So, the noninvasive extraction of FECG from electrocardiogram (ECG) signals becomes a hot research point. A new method, the Support Vector Machine (SVM) is utilized for the extraction of FECG with limited size of data. Firstly, the theory of the SVM and the principle of the extraction based on the SVM are studied. Secondly, the transformation of maternal electrocardiogram (MECG) component in abdominal composite signal is verified to be nonlinear and fitted with the SVM. Then, the SVM is trained, and the training results are compared with the real data to ensure the effect of the training. Meanwhile, the parameters of the SVM are optimized to achieve the best performance so that the learning machine can be utilized to fit the unknown samples. Finally, the FECG is extracted by removing the optimal estimation of MECG component from the abdominal composite signal. In order to evaluate the performance of FECG extraction based on the SVM, the Signal-to-Noise Ratio (SNR) and the visual test are used. The experimental results show that the FECG with good quality can be extracted, its SNR ratio is significantly increased as high as 9.2349 dB and the time cost is significantly decreased as short as 0.802 seconds. Compared with the traditional method, the noninvasive extraction method based on the SVM has a simple realization, the shorter treatment time and the better extraction quality under the same conditions.

Automated extraction of temporal motor activity signals from video recordings of neonatal seizures based on adaptive block matching.

PubMed

Karayiannis, Nicolaos B; Sami, Abdul; Frost, James D; Wise, Merrill S; Mizrahi, Eli M

2005-04-01

This paper presents an automated procedure developed to extract quantitative information from video recordings of neonatal seizures in the form of motor activity signals. This procedure relies on optical flow computation to select anatomical sites located on the infants' body parts. Motor activity signals are extracted by tracking selected anatomical sites during the seizure using adaptive block matching. A block of pixels is tracked throughout a sequence of frames by searching for the most similar block of pixels in subsequent frames; this search is facilitated by employing various update strategies to account for the changing appearance of the block. The proposed procedure is used to extract temporal motor activity signals from video recordings of neonatal seizures and other events not associated with seizures.

Extending the upper age limit for luminescence dating using the thermally transferred optically stimulated luminescence signal from quartz

NASA Astrophysics Data System (ADS)

Duller, Geoff A. T.; Wintle, Ann G.

2010-05-01

The optically stimulated luminescence (OSL) signal from quartz has been exploited for the last 20 years to date heated and unheated materials. While methods based on this signal have been extremely successful and are now widely adopted in laboratories around the world, growth of the signal with dose is affected by saturation and this commonly limits application to samples with equivalent doses of ~100 to 300 Gy. In most environments this limits application of the method to the last 100-150 ka. Studies of OSL from quartz in the late 1980's showed that if the OSL signal from a sample was reduced to background level by measurement, and the sample then heated, further optical stimulation gave a significant signal. This recuperated OSL was viewed as a problem to be avoided, particularly for young samples. Three years ago papers were published showing that this recuperated signal has the potential to be valuable in dosimetry, and in particular that the signal continues to grow to doses in excess of 10,000 Gy offering the possibility of extending the age range over which quartz can be used to as much as 1 Ma. The first work on this signal was undertaken on fine grain quartz extracted from Chinese loess, and ages back to the Brunhes-Matuyama boundary were obtained. The signal is now commonly referred to as thermally transferred optically stimulated luminescence (TT-OSL). Intense research on the signal has focussed on a number of areas, including, (a) understanding the origin of the charge measured in TT-OSL, (b) improving methods for measuring the TT-OSL signal, and (c) developing protocols for using TT-OSL in dose estimation, and these are reviewed in this presentation.

The Effects of Aronia melanocarpa 'Viking' Extracts in Attenuating RANKL-Induced Osteoclastic Differentiation by Inhibiting ROS Generation and c-FOS/NFATc1 Signaling.

PubMed

Ghosh, Mithun; Kim, In Sook; Lee, Young Min; Hong, Seong Min; Lee, Taek Hwan; Lim, Ji Hong; Debnath, Trishna; Lim, Beong Ou

2018-03-08

This study aimed to determine the anti-osteoclastogenic effects of extracts from Aronia melanocarpa 'Viking' (AM) and identify the underlying mechanisms in vitro. Reactive oxygen species (ROS) are signal mediators in osteoclast differentiation. AM extracts inhibited ROS production in RAW 264.7 cells in a dose-dependent manner and exhibited strong radical scavenging activity. The extracts also attenuated the number of tartrate-resistant acid phosphatase (TRAP)-positive multinucleated osteoclasts. To attain molecular insights, the effect of the extracts on the signaling pathways induced by receptor activator of nuclear factor kappa B ligand (RANKL) were also investigated. RANKL triggers many transcription factors through the activation of mitogen-activated protein kinase (MAPK) and ROS, leading to the induction of osteoclast-specific genes. The extracts significantly suppressed RANKL-induced activation of MAPKs, such as extracellular signal-regulated kinase (ERK), c-Jun- N -terminal kinase (JNK) and p38 and consequently led to the downregulation of c-Fos and nuclear factor of activated T cells 1 (NFATc1) protein expression which ultimately suppress the activation of the osteoclast-specific genes, cathepsin K, TRAP, calcitonin receptor and integrin β₃. In conclusion, our findings suggest that AM extracts inhibited RANKL-induced osteoclast differentiation by downregulating ROS generation and inactivating JNK/ERK/p38, nuclear factor kappa B (NF-κB)-mediated c-Fos and NFATc1 signaling pathway.

Perceptual full-reference quality assessment of stereoscopic images by considering binocular visual characteristics.

PubMed

Shao, Feng; Lin, Weisi; Gu, Shanbo; Jiang, Gangyi; Srikanthan, Thambipillai

2013-05-01

Perceptual quality assessment is a challenging issue in 3D signal processing research. It is important to study 3D signal directly instead of studying simple extension of the 2D metrics directly to the 3D case as in some previous studies. In this paper, we propose a new perceptual full-reference quality assessment metric of stereoscopic images by considering the binocular visual characteristics. The major technical contribution of this paper is that the binocular perception and combination properties are considered in quality assessment. To be more specific, we first perform left-right consistency checks and compare matching error between the corresponding pixels in binocular disparity calculation, and classify the stereoscopic images into non-corresponding, binocular fusion, and binocular suppression regions. Also, local phase and local amplitude maps are extracted from the original and distorted stereoscopic images as features in quality assessment. Then, each region is evaluated independently by considering its binocular perception property, and all evaluation results are integrated into an overall score. Besides, a binocular just noticeable difference model is used to reflect the visual sensitivity for the binocular fusion and suppression regions. Experimental results show that compared with the relevant existing metrics, the proposed metric can achieve higher consistency with subjective assessment of stereoscopic images.

Video-based respiration monitoring with automatic region of interest detection.

PubMed

Janssen, Rik; Wang, Wenjin; Moço, Andreia; de Haan, Gerard

2016-01-01

Vital signs monitoring is ubiquitous in clinical environments and emerging in home-based healthcare applications. Still, since current monitoring methods require uncomfortable sensors, respiration rate remains the least measured vital sign. In this paper, we propose a video-based respiration monitoring method that automatically detects a respiratory region of interest (RoI) and signal using a camera. Based on the observation that respiration induced chest/abdomen motion is an independent motion system in a video, our basic idea is to exploit the intrinsic properties of respiration to find the respiratory RoI and extract the respiratory signal via motion factorization. We created a benchmark dataset containing 148 video sequences obtained on adults under challenging conditions and also neonates in the neonatal intensive care unit (NICU). The measurements obtained by the proposed video respiration monitoring (VRM) method are not significantly different from the reference methods (guided breathing or contact-based ECG; p-value  =  0.6), and explain more than 99% of the variance of the reference values with low limits of agreement (-2.67 to 2.81 bpm). VRM seems to provide a valid solution to ECG in confined motion scenarios, though precision may be reduced for neonates. More studies are needed to validate VRM under challenging recording conditions, including upper-body motion types.

Decoupling feedforward and feedback structures in hybrid active noise control systems for uncorrelated narrowband disturbances

NASA Astrophysics Data System (ADS)

Wu, Lifu; Qiu, Xiaojun; Burnett, Ian S.; Guo, Yecai

2015-08-01

Hybrid feedforward and feedback structures are useful for active noise control (ANC) applications where the noise can only be partially obtained with reference sensors. The traditional method uses the secondary signals of both the feedforward and feedback structures to synthesize a reference signal for the feedback structure in the hybrid structure. However, this approach introduces coupling between the feedforward and feedback structures and parameter changes in one structure affect the other during adaptation such that the feedforward and feedback structures must be optimized simultaneously in practical ANC system design. Two methods are investigated in this paper to remove such coupling effects. One is a simplified method, which uses the error signal directly as the reference signal in the feedback structure, and the second method generates the reference signal for the feedback structure by using only the secondary signal from the feedback structure and utilizes the generated reference signal as the error signal of the feedforward structure. Because the two decoupling methods can optimize the feedforward and feedback structures separately, they provide more flexibility in the design and optimization of the adaptive filters in practical ANC applications.

Model benchmarking and reference signals for angled-beam shear wave ultrasonic nondestructive evaluation (NDE) inspections

NASA Astrophysics Data System (ADS)

Aldrin, John C.; Hopkins, Deborah; Datuin, Marvin; Warchol, Mark; Warchol, Lyudmila; Forsyth, David S.; Buynak, Charlie; Lindgren, Eric A.

2017-02-01

For model benchmark studies, the accuracy of the model is typically evaluated based on the change in response relative to a selected reference signal. The use of a side drilled hole (SDH) in a plate was investigated as a reference signal for angled beam shear wave inspection for aircraft structure inspections of fastener sites. Systematic studies were performed with varying SDH depth and size, and varying the ultrasonic probe frequency, focal depth, and probe height. Increased error was observed with the simulation of angled shear wave beams in the near-field. Even more significant, asymmetry in real probes and the inherent sensitivity of signals in the near-field to subtle test conditions were found to provide a greater challenge with achieving model agreement. To achieve quality model benchmark results for this problem, it is critical to carefully align the probe with the part geometry, to verify symmetry in probe response, and ideally avoid using reference signals from the near-field response. Suggested reference signals for angled beam shear wave inspections include using the `through hole' corner specular reflection signal and the full skip' signal off of the far wall from the side drilled hole.

Fetal source extraction from magnetocardiographic recordings by dependent component analysis

NASA Astrophysics Data System (ADS)

de Araujo, Draulio B.; Kardec Barros, Allan; Estombelo-Montesco, Carlos; Zhao, Hui; Roque da Silva Filho, A. C.; Baffa, Oswaldo; Wakai, Ronald; Ohnishi, Noboru

2005-10-01

Fetal magnetocardiography (fMCG) has been extensively reported in the literature as a non-invasive, prenatal technique that can be used to monitor various functions of the fetal heart. However, fMCG signals often have low signal-to-noise ratio (SNR) and are contaminated by strong interference from the mother's magnetocardiogram signal. A promising, efficient tool for extracting signals, even under low SNR conditions, is blind source separation (BSS), or independent component analysis (ICA). Herein we propose an algorithm based on a variation of ICA, where the signal of interest is extracted using a time delay obtained from an autocorrelation analysis. We model the system using autoregression, and identify the signal component of interest from the poles of the autocorrelation function. We show that the method is effective in removing the maternal signal, and is computationally efficient. We also compare our results to more established ICA methods, such as FastICA.

Application of solid/liquid extraction for the gravimetric determination of lipids in royal jelly.

PubMed

Antinelli, Jean-François; Davico, Renée; Rognone, Catherine; Faucon, Jean-Paul; Lizzani-Cuvelier, Louisette

2002-04-10

Gravimetric lipid determination is a major parameter for the characterization and the authentication of royal jelly quality. A solid/liquid extraction was compared to the reference method, which is based on liquid/liquid extraction. The amount of royal jelly and the time of the extraction were optimized in comparison to the reference method. Boiling/rinsing ratio and spread of royal jelly onto the extraction thimble were identified as critical parameters, resulting in good accuracy and precision for the alternative method. Comparison of reproducibility and repeatability of both methods associated with gas chromatographic analysis of the composition of the extracted lipids showed no differences between the two methods. As the intra-laboratory validation tests were comparable to the reference method, while offering rapidity and a decrease in amount of solvent used, it was concluded that the proposed method should be used with no modification of quality criteria and norms established for royal jelly characterization.

Development of a HS-SPME-GC/MS protocol assisted by chemometric tools to study herbivore-induced volatiles in Myrcia splendens.

PubMed

Souza Silva, Érica A; Saboia, Giovanni; Jorge, Nina C; Hoffmann, Camila; Dos Santos Isaias, Rosy Mary; Soares, Geraldo L G; Zini, Claudia A

2017-12-01

A headspace solid phase microextraction (HS-SPME) method combined with gas chromatography-mass spectrometry (GC/MS) was developed and optimized for extraction and analysis of volatile organic compounds (VOC) of leaves and galls of Myrcia splendens. Through a process of optimization of main factors affecting HS-SPME efficiency, the coating divivnilbenzene-carboxen-polydimethylsiloxane (DVB/Car/PDMS) was chosen as the optimum extraction phase, not only in terms of extraction efficiency, but also for its broader analyte coverage. Optimum extraction temperature was 30°C, while an extraction time of 15min provided the best compromise between extraction efficiencies of lower and higher molecular weight compounds. The optimized protocol was demonstrated to be capable of sampling plant material with high reproducibility, considering that most classes of analytes met the 20% RSD FDA criterion. The optimized method was employed for the analysis of three classes of M. splendens samples, generating a final list of 65 tentatively identified VOC, including alcohols, aldehydes, esters, ketones, phenol derivatives, as well as mono and sesquiterpenes. Significant differences were evident amongst the volatile profiles obtained from non-galled leaves (NGL) and leaf-folding galls (LFG) of M. splendens. Several differences pertaining to amounts of alcohols and aldehydes were detected between samples, particularly regarding quantities of green leaf volatiles (GLV). Alcohols represented about 14% of compounds detected in gall samples, whereas in non-galled samples, alcohol content was below 5%. Phenolic derived compounds were virtually absent in reference samples, while in non-galled leaves and galls their content ranged around 0.2% and 0.4%, respectively. Likewise, methyl salicylate, a well-known signal of plant distress, amounted for 1.2% of the sample content of galls, whereas it was only present in trace levels in reference samples. Chemometric analysis based on Heatmap associated with Hierarchical Cluster Analysis (HCA) and Principal Component Analysis (PCA) provided a suitable tool to differentiate VOC profiles in vegetal material, and could open new perspectives and opportunities in agricultural and ecological studies for the detection and identification of herbivore-induced plant VOC emissions. Copyright © 2017 Elsevier B.V. All rights reserved.

Spectral identification of minerals using imaging spectrometry data: Evaluating the effects of signal to noise and spectral resolution using the tricorder algorithm

NASA Technical Reports Server (NTRS)

Swayze, Gregg A.; Clark, Roger N.

1995-01-01

The rapid development of sophisticated imaging spectrometers and resulting flood of imaging spectrometry data has prompted a rapid parallel development of spectral-information extraction technology. Even though these extraction techniques have evolved along different lines (band-shape fitting, endmember unmixing, near-infrared analysis, neural-network fitting, and expert systems to name a few), all are limited by the spectrometer's signal to noise (S/N) and spectral resolution in producing useful information. This study grew from a need to quantitatively determine what effects these parameters have on our ability to differentiate between mineral absorption features using a band-shape fitting algorithm. We chose to evaluate the AVIRIS, HYDICE, MIVIS, GERIS, VIMS, NIMS, and ASTER instruments because they collect data over wide S/N and spectral-resolution ranges. The study evaluates the performance of the Tricorder algorithm, in differentiating between mineral spectra in the 0.4-2.5 micrometer spectral region. The strength of the Tricorder algorithm is in its ability to produce an easily understood comparison of band shape that can concentrate on small relevant portions of the spectra, giving it an advantage over most unmixing schemes, and in that it need not spend large amounts of time reoptimizing each time a new mineral component is added to its reference library, as is the case with neural-network schemes. We believe the flexibility of the Tricorder algorithm is unparalleled among spectral-extraction techniques and that the results from this study, although dealing with minerals, will have direct applications to spectral identification in other disciplines.

Intercomparison of Lab-Based Soil Water Extraction Methods for Stable Water Isotope Analysis

NASA Astrophysics Data System (ADS)

Pratt, D.; Orlowski, N.; McDonnell, J.

2016-12-01

The effect of pore water extraction technique on resultant isotopic signature is poorly understood. Here we present results of an intercomparison of five common lab-based soil water extraction techniques: high pressure mechanical squeezing, centrifugation, direct vapor equilibration, microwave extraction, and cryogenic extraction. We applied five extraction methods to two physicochemically different standard soil types (silty sand and clayey loam) that were oven-dried and rewetted with water of known isotopic composition at three different gravimetric water contents (8, 20, and 30%). We tested the null hypothisis that all extraction techniques would provide the same isotopic result independent from soil type and water content. Our results showed that the extraction technique had a significant effect on the soil water isotopic composition. Each method exhibited deviations from spiked reference water, with soil type and water content showing a secondary effect. Cryogenic extraction showed the largest deviations from the reference water, whereas mechanical squeezing and centrifugation provided the closest match to the reference water for both soil types. We also compared results for each extraction technique that produced liquid water on both an OA-ICOS and IRMS; differences between them were negligible.

The utilization of modified BCR three-step sequential extraction procedure for the fractionation of Cd, Cr, Cu, Ni, Pb and Zn in soil reference materials of different origins.

PubMed

Zemberyová, Mária; Barteková, Jana; Hagarová, Ingrid

2006-12-15

A modified three-step sequential extraction procedure for the fractionation of heavy metals, proposed by the Commission of the European Communities Bureau of Reference (BCR) has been applied to the Slovak reference materials of soils (soil orthic luvisols, soil rendzina and soil eutric cambisol), which represent pedologically different types of soils in Slovakia. Analyses were carried out by flame or electrothermal atomic absorption spectrometry (FAAS or ETAAS). The fractions extracted were: exchangeable (extraction step 1), reducible-iron/manganese oxides (extraction step 2), oxidizable-organic matter and sulfides (extraction step 3). The sum of the element contents in the three fractions plus aqua-regia extractable content of the residue was compared to the aqua-regia extractable content of the elements in the origin soils. The accuracy obtained by comparing the determined contents of the elements with certified values, using BCR CRM 701, certified for the extractable contents (mass fractions) of Cd, Cr, Cu, Ni, Pb and Zn in sediment following a modified BCR-three step sequential extraction procedure, was found to be satisfactory.

Audio Watermark Embedding Technique Applying Auditory Stream Segregation: "G-encoder Mark" Able to Be Extracted by Mobile Phone

NASA Astrophysics Data System (ADS)

Modegi, Toshio

We are developing audio watermarking techniques which enable extraction of embedded data by cell phones. For that we have to embed data onto frequency ranges, where our auditory response is prominent, therefore data embedding will cause much auditory noises. Previously we have proposed applying a two-channel stereo play-back feature, where noises generated by a data embedded left-channel signal will be reduced by the other right-channel signal. However, this proposal has practical problems of restricting extracting terminal location. In this paper, we propose synthesizing the noise reducing right-channel signal with the left-signal and reduces noises completely by generating an auditory stream segregation phenomenon to users. This newly proposed makes the noise reducing right-channel signal unnecessary and supports monaural play-back operations. Moreover, we propose a wide-band embedding method causing dual auditory stream segregation phenomena, which enables data embedding on whole public phone frequency ranges and stable extractions with 3-G mobile phones. From these proposals, extraction precisions become higher than those by the previously proposed method whereas the quality damages of embedded signals become smaller. In this paper we present an abstract of our newly proposed method and experimental results comparing with those by the previously proposed method.

Synchrosqueezing an effective method for analyzing Doppler radar physiological signals.

PubMed

Yavari, Ehsan; Rahman, Ashikur; Jia Xu; Mandic, Danilo P; Boric-Lubecke, Olga

2016-08-01

Doppler radar can monitor vital sign wirelessly. Respiratory and heart rate have time-varying behavior. Capturing the rate variability provides crucial physiological information. However, the common time-frequency methods fail to detect key information. We investigate Synchrosqueezing method to extract oscillatory components of the signal with time varying spectrum. Simulation and experimental result shows the potential of the proposed method for analyzing signals with complex time-frequency behavior like physiological signals. Respiration and heart signals and their components are extracted with higher resolution and without any pre-filtering and signal conditioning.

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

Smith, Stephen F; Moore, James A

Systems and methods are described for carrier-frequency synchronization for improved AM and TV broadcast reception. A method includes synchronizing a carrier frequency of a broadcast signal with a remote reference frequency. An apparatus includes a reference signal receiver; a phase comparator coupled to the reference signal receiver; a voltage controlled oscillator coupled to the phase comparator; and a radio frequency output coupled to the voltage controlled oscillator.

Four reference soil and rock samples for measuring element availability in the Western Energy Regions

USGS Publications Warehouse

Crock, J.G.; Severson, R.C.

1980-01-01

Attaining acceptable precision in extractable element determinations is more difficult than in total element determinations. In total element determinations, dissolution of the sample is qualitatively checked by the clarity of the solution and the absence of residues. These criteria cannot be used for extracts. Possibilities for error are introduced in virtually every step in soil extractions. Therefore, the use of reference materials whose homogeneity and element content are reasonably well known is essential for determination of extractable elements. In this report, estimates of homogeneity and element content are presented for four reference samples. Bulk samples of about 100 kilograms of each sample were ground to pass an 80-mesh sieve. The samples were homogenized and split using a Jones-type splitter. Fourteen splits of each reference sample were analyzed for total content of Ca, Co, Cu, Fe, K, Mg, Mn, Na, and Zn; DTPA-extractable Cd, Co, Cu, Fe, Mn, Ni, Pb, and Zn; exchangeable Ca, Mg, K, and Na; cation exchange capacity water-saturation-extractable Ca, Mg, K, Na, C1, and SO4; soil pH; and hot-water-extractable boron. Error measured between splits was small, indicating that the samples were homogenized adequately and that the laboratory procedure provided reproducible results.

Expanding the potential of standard flow cytometry by extracting fluorescence lifetimes from cytometric pulse shifts

PubMed Central

Cao, Ruofan; Naivar, Mark A; Wilder, Mark; Houston, Jessica P

2014-01-01

Fluorescence lifetime measurements provide information about the fluorescence relaxation, or intensity decay, of organic fluorophores, fluorescent proteins, and other inorganic molecules that fluoresce. The fluorescence lifetime is emerging in flow cytometry and is helpful in a variety of multiparametric, single cell measurements because it is not impacted by nonlinearity that can occur with fluorescence intensity measurements. Yet time-resolved cytometry systems rely on major hardware modifications making the methodology difficult to reproduce. The motivation of this work is, by taking advantage of the dynamic nature of flow cytometry sample detection and applying digital signal processing methods, to measure fluorescence lifetimes using an unmodified flow cytometer. We collect a new lifetime-dependent parameter, referred to herein as the fluorescence-pulse-delay (FPD), and prove it is a valid representation of the average fluorescence lifetime. To verify we generated cytometric pulses in simulation, with light emitting diode (LED) pulsation, and with true fluorescence measurements of cells and microspheres. Each pulse is digitized and used in algorithms to extract an average fluorescence lifetime inherent in the signal. A range of fluorescence lifetimes is measurable with this approach including standard organic fluorophore lifetimes (∼1 to 22 ns) as well as small, simulated shifts (0.1 ns) under standard conditions (reported herein). This contribution demonstrates how digital data acquisition and signal processing can reveal time-dependent information foreshadowing the exploitation of full waveform analysis for quantification of similar photo-physical events within single cells. © 2014 The Authors. Published by Wiley Periodicals, Inc. PMID:25274073

Fetal ECG extraction via Type-2 adaptive neuro-fuzzy inference systems.

PubMed

Ahmadieh, Hajar; Asl, Babak Mohammadzadeh

2017-04-01

We proposed a noninvasive method for separating the fetal ECG (FECG) from maternal ECG (MECG) by using Type-2 adaptive neuro-fuzzy inference systems. The method can extract FECG components from abdominal signal by using one abdominal channel, including maternal and fetal cardiac signals and other environmental noise signals, and one chest channel. The proposed algorithm detects the nonlinear dynamics of the mother's body. So, the components of the MECG are estimated from the abdominal signal. By subtracting estimated mother cardiac signal from abdominal signal, fetal cardiac signal can be extracted. This algorithm was applied on synthetic ECG signals generated based on the models developed by McSharry et al. and Behar et al. and also on DaISy real database. In environments with high uncertainty, our method performs better than the Type-1 fuzzy method. Specifically, in evaluation of the algorithm with the synthetic data based on McSharry model, for input signals with SNR of -5dB, the SNR of the extracted FECG was improved by 38.38% in comparison with the Type-1 fuzzy method. Also, the results show that increasing the uncertainty or decreasing the input SNR leads to increasing the percentage of the improvement in SNR of the extracted FECG. For instance, when the SNR of the input signal decreases to -30dB, our proposed algorithm improves the SNR of the extracted FECG by 71.06% with respect to the Type-1 fuzzy method. The same results were obtained on synthetic data based on Behar model. Our results on real database reflect the success of the proposed method to separate the maternal and fetal heart signals even if their waves overlap in time. Moreover, the proposed algorithm was applied to the simulated fetal ECG with ectopic beats and achieved good results in separating FECG from MECG. The results show the superiority of the proposed Type-2 neuro-fuzzy inference method over the Type-1 neuro-fuzzy inference and the polynomial networks methods, which is due to its capability to capture the nonlinearities of the model better. Copyright © 2017 Elsevier B.V. All rights reserved.

Simultaneous and co-localized acousto-optic measurements of spectral and temporal properties of diffusive media

NASA Astrophysics Data System (ADS)

Balberg, Michal; Shechter, Revital; Girshovitz, Pinhas; Breskin, Ilan; Fantini, Sergio

2017-02-01

Acousto-optic (AO) modulation of light is used to extract both temporal and spectral information of diffusive media such as biological tissue, where they provide measures of blood flow and oxygen saturation of hemoglobin, respectively. The temporal information is extracted from the width of the power spectrum of the light intensity, whereas the spectral information is calculated from the spatial decay of the cross correlation between the light intensity and the generated ultrasonic signal. The ultrasonic signal is a coded phase modulated signal with a narrow autocorrelation, enabling localization of the measurement volume. Two different liquid phantoms are used, with similar scattering but different absorption properties. The difference in absorption calculated with the AO signal is compared to calculations based on the modified Beer Lambert law. As the same AO signal is used to extract both modalities, it might be used to extract hemodynamic related changes in the brain for diagnostic and functional assessment.

Non-stationary component extraction in noisy multicomponent signal using polynomial chirping Fourier transform.

PubMed

Lu, Wenlong; Xie, Junwei; Wang, Heming; Sheng, Chuan

2016-01-01

Inspired by track-before-detection technology in radar, a novel time-frequency transform, namely polynomial chirping Fourier transform (PCFT), is exploited to extract components from noisy multicomponent signal. The PCFT combines advantages of Fourier transform and polynomial chirplet transform to accumulate component energy along a polynomial chirping curve in the time-frequency plane. The particle swarm optimization algorithm is employed to search optimal polynomial parameters with which the PCFT will achieve a most concentrated energy ridge in the time-frequency plane for the target component. The component can be well separated in the polynomial chirping Fourier domain with a narrow-band filter and then reconstructed by inverse PCFT. Furthermore, an iterative procedure, involving parameter estimation, PCFT, filtering and recovery, is introduced to extract components from a noisy multicomponent signal successively. The Simulations and experiments show that the proposed method has better performance in component extraction from noisy multicomponent signal as well as provides more time-frequency details about the analyzed signal than conventional methods.

Three-Dimensional Terahertz Coded-Aperture Imaging Based on Matched Filtering and Convolutional Neural Network.

PubMed

Chen, Shuo; Luo, Chenggao; Wang, Hongqiang; Deng, Bin; Cheng, Yongqiang; Zhuang, Zhaowen

2018-04-26

As a promising radar imaging technique, terahertz coded-aperture imaging (TCAI) can achieve high-resolution, forward-looking, and staring imaging by producing spatiotemporal independent signals with coded apertures. However, there are still two problems in three-dimensional (3D) TCAI. Firstly, the large-scale reference-signal matrix based on meshing the 3D imaging area creates a heavy computational burden, thus leading to unsatisfactory efficiency. Secondly, it is difficult to resolve the target under low signal-to-noise ratio (SNR). In this paper, we propose a 3D imaging method based on matched filtering (MF) and convolutional neural network (CNN), which can reduce the computational burden and achieve high-resolution imaging for low SNR targets. In terms of the frequency-hopping (FH) signal, the original echo is processed with MF. By extracting the processed echo in different spike pulses separately, targets in different imaging planes are reconstructed simultaneously to decompose the global computational complexity, and then are synthesized together to reconstruct the 3D target. Based on the conventional TCAI model, we deduce and build a new TCAI model based on MF. Furthermore, the convolutional neural network (CNN) is designed to teach the MF-TCAI how to reconstruct the low SNR target better. The experimental results demonstrate that the MF-TCAI achieves impressive performance on imaging ability and efficiency under low SNR. Moreover, the MF-TCAI has learned to better resolve the low-SNR 3D target with the help of CNN. In summary, the proposed 3D TCAI can achieve: (1) low-SNR high-resolution imaging by using MF; (2) efficient 3D imaging by downsizing the large-scale reference-signal matrix; and (3) intelligent imaging with CNN. Therefore, the TCAI based on MF and CNN has great potential in applications such as security screening, nondestructive detection, medical diagnosis, etc.

Mach-zehnder based optical marker/comb generator for streak camera calibration

DOEpatents

Miller, Edward Kirk

2015-03-03

This disclosure is directed to a method and apparatus for generating marker and comb indicia in an optical environment using a Mach-Zehnder (M-Z) modulator. High speed recording devices are configured to record image or other data defining a high speed event. To calibrate and establish time reference, the markers or combs are indicia which serve as timing pulses (markers) or a constant-frequency train of optical pulses (comb) to be imaged on a streak camera for accurate time based calibration and time reference. The system includes a camera, an optic signal generator which provides an optic signal to an M-Z modulator and biasing and modulation signal generators configured to provide input to the M-Z modulator. An optical reference signal is provided to the M-Z modulator. The M-Z modulator modulates the reference signal to a higher frequency optical signal which is output through a fiber coupled link to the streak camera.

Extraction of the gate capacitance coupling coefficient in floating gate non-volatile memories: Statistical study of the effect of mismatching between floating gate memory and reference transistor in dummy cell extraction methods

NASA Astrophysics Data System (ADS)

Rafhay, Quentin; Beug, M. Florian; Duane, Russell

2007-04-01

This paper presents an experimental comparison of dummy cell extraction methods of the gate capacitance coupling coefficient for floating gate non-volatile memory structures from different geometries and technologies. These results show the significant influence of mismatching floating gate devices and reference transistors on the extraction of the gate capacitance coupling coefficient. In addition, it demonstrates the accuracy of the new bulk bias dummy cell extraction method and the importance of the β function, introduced recently in [Duane R, Beug F, Mathewson A. Novel capacitance coupling coefficient measurement methodology for floating gate non-volatile memory devices. IEEE Electr Dev Lett 2005;26(7):507-9], to determine matching pairs of floating gate memory and reference transistor.

Analysis of polycyclic aromatic hydrocarbons in sediment reference materials by microwave-assisted extraction.

PubMed

Shu, Y Y; Lao, R C; Chiu, C H; Turle, R

2000-12-01

The microwave-assisted extraction (MAE) of polycyclic aromatic hydrocarbons (PAHs) from harbor sediment reference material EC-1, marine sediment reference material HS-2 and PAH-spiked river bed soil was conducted. The extraction conditions for EC-1 were carried out at 70 degrees C and 100 degrees C under pressure in closed vessels with cyclohexane acetone (1:1), cyclohexane-water (3:1), hexane acetone (1:1), and hexane-water (3:1) for 10 min. A comparison between MAE and a 16-h Soxhlet extraction (SX) method showed that both techniques gave comparable results with certified values. MAE has advantages over the currently used Soxhlet technique due to a faster extraction time and lower quantity of solvent used. The consumption of organic solvent of the microwave method was less than one-tenth compared to Soxhlet.

Previous radiographic experience of children referred for dental extractions under general anaesthesia in the U.K.

PubMed

Young, N L; Rodd, H D; Craig, S A

2009-03-01

To determine what proportion of children undergo radiographic assessment prior to referral to a dental hospital for extractions under general anaesthesia. This prospective survey was conducted over a 6-month period. A data sheet was used to record the following information: patient's age; referrer's name and place of work (general dental practice or community dental service); teeth to be extracted (primary dentition and/or permanent dentition) and reported previous radiographic examination. Patients were excluded from the study if, following a clinical examination, radiographs were not actually deemed necessary for diagnosis and treatment planning purposes. Clinical setting A paediatric dentistry clinic within a dental hospital in the North of England. Participants 161 patients with a mean age of six years (SD = 2.2, range = 3-14 years) who were referred to the dental hospital for extractions under general anaesthesia. Overall, 12.4% of children had reportedly undergone a previous radiographic assessment prior to hospital referral. A significantly greater proportion of children referred for permanent tooth extractions had been subject to radiographic examination compared to children referred for primary tooth extractions (46.2% as compared to 6.3%; P = 0.001 chi-squared test). Furthermore, patients referred from the community dental service were significantly more likely to have had previous dental radiographs than children referred from general dental practice (36.9% compared to 9.3%; P = 0.003 chi-squared test). Radiographs do not appear to be routinely employed for caries diagnosis and treatment planning in young children within general dental practice in the U.K.

Hearing aid malfunction detection system

NASA Technical Reports Server (NTRS)

Kessinger, R. L. (Inventor)

1977-01-01

A malfunction detection system for detecting malfunctions in electrical signal processing circuits is disclosed. Malfunctions of a hearing aid in the form of frequency distortion and/or inadequate amplification by the hearing aid amplifier, as well as weakening of the hearing aid power supply are detectable. A test signal is generated and a timed switching circuit periodically applies the test signal to the input of the hearing aid amplifier in place of the input signal from the microphone. The resulting amplifier output is compared with the input test signal used as a reference signal. The hearing aid battery voltage is also periodically compared to a reference voltage. Deviations from the references beyond preset limits cause a warning system to operate.

Profiling of poorly stratified smoky atmospheres with scanning lidar

Treesearch

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

2012-01-01

The multiangle data processing technique is considered based on using the signal measured in zenith (or close to zenith) as a core source for extracting the information about the vertical atmospheric aerosol loading. The multiangle signals are used as the auxiliary data to extract the vertical transmittance profile from the zenith signal. Simulated and experimental...

Study of Fourier transform spectrometer based on Michelson interferometer wave-meter

NASA Astrophysics Data System (ADS)

Peng, Yuexiang; Wang, Liqiang; Lin, Li

2008-03-01

A wave-meter based on Michelson interferometer consists of a reference and a measurement channel. The voice-coiled motor using PID means can realize to move in stable motion. The wavelength of a measurement laser can be obtained by counting interference fringes of reference and measurement laser. Reference laser with frequency stabilization creates a cosine interferogram signal whose frequency is proportional to velocity of the moving motor. The interferogram of the reference laser is converted to pulse signal, and it is subdivided into 16 times. In order to get optical spectrum, the analog signal of measurement channel should be collected. The Analog-to-Digital Converter (ADC) for measurement channel is triggered by the 16-times pulse signal of reference laser. So the sampling rate is constant only depending on frequency of reference laser and irrelative to the motor velocity. This means the sampling rate of measurement channel signals is on a uniform time-scale. The optical spectrum of measurement channel can be processed with Fast Fourier Transform (FFT) method by DSP and displayed on LCD.

Gravity Tides Extracted from Relative Gravimeter Data by Combining Empirical Mode Decomposition and Independent Component Analysis

NASA Astrophysics Data System (ADS)

Yu, Hongjuan; Guo, Jinyun; Kong, Qiaoli; Chen, Xiaodong

2018-04-01

The static observation data from a relative gravimeter contain noise and signals such as gravity tides. This paper focuses on the extraction of the gravity tides from the static relative gravimeter data for the first time applying the combined method of empirical mode decomposition (EMD) and independent component analysis (ICA), called the EMD-ICA method. The experimental results from the CG-5 gravimeter (SCINTREX Limited Ontario Canada) data show that the gravity tides time series derived by EMD-ICA are consistent with the theoretical reference (Longman formula) and the RMS of their differences only reaches 4.4 μGal. The time series of the gravity tides derived by EMD-ICA have a strong correlation with the theoretical time series and the correlation coefficient is greater than 0.997. The accuracy of the gravity tides estimated by EMD-ICA is comparable to the theoretical model and is slightly higher than that of independent component analysis (ICA). EMD-ICA could overcome the limitation of ICA having to process multiple observations and slightly improve the extraction accuracy and reliability of gravity tides from relative gravimeter data compared to that estimated with ICA.

A portable multi-channel recording system for analysis of acceleration and angular velocity in six dimension.

PubMed

Yamashita, M; Yamashita, A; Ishii, T; Naruo, Y; Nagatomo, M

1998-11-01

A portable recording system was developed for analysis of more than three analog signals collected in field works. Stereo audio recorder, available as consumer products, was made use for a core cornponent of the system. For the two tracks of recording, a multiplexed analog signal is stored on one track, and reference code on the other track. The reference code indicates the start of one cycle for multiplexing and swiching point of each channel. Multiplexed signal is playbacked and decoded with a reference of the code to reconstruct original profiles of the signal. Since commercial stereo recorders have cut DC component off, a fixed reference voltage is inserted in the sequence of multiplexing. Change of voltage at switching from the reference to the data channel is measured from playbacked signal to get the original data with its DC component. Movement of vehicles and human head were analyzed by the system. It was verified to be capable to record and analyze multi-channel signal at a sampling rate more than 10Hz.

Quantitative measurement of intervertebral disc signal using MRI.

PubMed

Niemeläinen, R; Videman, T; Dhillon, S S; Battié, M C

2008-03-01

To investigate the spinal cord as an alternative intra-body reference to cerebrospinal fluid (CSF) in evaluating thoracic disc signal intensity. T2-weighted magnetic resonance imaging (MRI) images of T6-T12 were obtained using 1.5 T machines for a population-based sample of 523 men aged 35-70 years. Quantitative data on the signal intensities were acquired using an image analysis program (SpEx). A random sample of 30 subjects and intraclass correlation coefficients (ICC) were used to examine the repeatability of the spinal cord measurements. The validity of using the spinal cord as a reference was examined by correlating cord and CSF samples. Finally, thoracic disc signal was validated by correlating it with age without adjustment and adjusting for either cord or CSF. Pearson's r was used for correlational analyses. The repeatability of the spinal cord signal measurements was extremely high (>or=0.99). The correlations between the signals of spinal cord and CSF by level were all above 0.9. The spinal cord-adjusted disc signal and age correlated similarly with CSF-adjusted disc signal and age (r=-0.30 to -0.40 versus r=-0.26 to -0.36). Adjacent spinal cord is a good alternative reference to the current reference standard, CSF, for quantitative measurements of disc signal intensity. Clearly fewer levels were excluded when using spinal cord as compared to CSF due to missing reference samples.

Current level detector

DOEpatents

Kerns, Cordon R.

1977-01-01

A device is provided for detecting the current level of a DC signal. It includes an even harmonic modulator to which a reference AC signal is applied. The unknown DC signal acts on the reference AC signal so that the output of the modulator includes an even harmonic whose amplitude is proportional to the unknown DC current.

Reference-free direct digital lock-in method and apparatus

NASA Technical Reports Server (NTRS)

Henry, James E. (Inventor); Leonard, John A. (Inventor)

2000-01-01

A reference-free direct digital lock-in system (RDDL 10) has a first input coupled to a periodic electrical signal and an output for outputting an indication of a magnitude of a desired periodic signal component. The RDDL also has a second input for receiving a signal (9) that specifies a reference period value, and operates to autonomously generate a lock-in reference signal having a specified period and a phase that is adjusted to maximize a magnitude of the outputted desired periodic signal component. In an embodiment of a measurement system that includes the RDDL 10 an optical source provides a chopped light beam having wavelengths within a predetermined range of wavelengths, and the periodic electrical signal is generated by at least one photodetector that is illuminated by the chopped light beam. In this embodiment the measurement system characterizes, for at least one wavelength of light that is generated by the optical source, a spectral response of the at least one photodetector. The RDDL can operate in nonreal-time upon previously generated and stored digital equivalent values of the periodic electrical signal or signals.

Information extraction during simultaneous motion processing.

PubMed

Rideaux, Reuben; Edwards, Mark

2014-02-01

When confronted with multiple moving objects the visual system can process them in two stages: an initial stage in which a limited number of signals are processed in parallel (i.e. simultaneously) followed by a sequential stage. We previously demonstrated that during the simultaneous stage, observers could discriminate between presentations containing up to 5 vs. 6 spatially localized motion signals (Edwards & Rideaux, 2013). Here we investigate what information is actually extracted during the simultaneous stage and whether the simultaneous limit varies with the detail of information extracted. This was achieved by measuring the ability of observers to extract varied information from low detail, i.e. the number of signals presented, to high detail, i.e. the actual directions present and the direction of a specific element, during the simultaneous stage. The results indicate that the resolution of simultaneous processing varies as a function of the information which is extracted, i.e. as the information extraction becomes more detailed, from the number of moving elements to the direction of a specific element, the capacity to process multiple signals is reduced. Thus, when assigning a capacity to simultaneous motion processing, this must be qualified by designating the degree of information extraction. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

Method and means for measurement and control of pulsed charged beams

DOEpatents

Lewis, R.N.

A beam of bunches of charged particles is controlled by generating a signal in response to the passage of a bunch and adding to that signal a phase-flipped reference signal. The sum is amplified, detected, and applied to a synchronous detector to obtain a comparison of the phase of the reference signal with the phase of the signal responsive to the bunch. The comparison provides an error signal to control bunching.

Research on vibration signal analysis and extraction method of gear local fault

NASA Astrophysics Data System (ADS)

Yang, X. F.; Wang, D.; Ma, J. F.; Shao, W.

2018-02-01

Gear is the main connection parts and power transmission parts in the mechanical equipment. If the fault occurs, it directly affects the running state of the whole machine and even endangers the personal safety. So it has important theoretical significance and practical value to study on the extraction of the gear fault signal and fault diagnosis of the gear. In this paper, the gear local fault as the research object, set up the vibration model of gear fault vibration mechanism, derive the vibration mechanism of the gear local fault and analyzes the similarities and differences of the vibration signal between the gear non fault and the gears local faults. In the MATLAB environment, the wavelet transform algorithm is used to denoise the fault signal. Hilbert transform is used to demodulate the fault vibration signal. The results show that the method can denoise the strong noise mechanical vibration signal and extract the local fault feature information from the fault vibration signal..

Contactless physiological signals extraction based on skin color magnification

NASA Astrophysics Data System (ADS)

Suh, Kun Ha; Lee, Eui Chul

2017-11-01

Although the human visual system is not sufficiently sensitive to perceive blood circulation, blood flow caused by cardiac activity makes slight changes on human skin surfaces. With advances in imaging technology, it has become possible to capture these changes through digital cameras. However, it is difficult to obtain clear physiological signals from such changes due to its fineness and noise factors, such as motion artifacts and camera sensing disturbances. We propose a method for extracting physiological signals with improved quality from skin colored-videos recorded with a remote RGB camera. The results showed that our skin color magnification method reveals the hidden physiological components remarkably in the time-series signal. A Korea Food and Drug Administration-approved heart rate monitor was used for verifying the resulting signal synchronized with the actual cardiac pulse, and comparisons of signal peaks showed correlation coefficients of almost 1.0. In particular, our method can be an effective preprocessing before applying additional postfiltering techniques to improve accuracy in image-based physiological signal extractions.

Self-calibrating threshold detector

NASA Technical Reports Server (NTRS)

Barnes, J. R.; Huang, M. Y. (Inventor)

1980-01-01

A self calibrating threshold detector comprises a single demodulating channel which includes a mixer having one input receiving the incoming signal and another input receiving a local replica code. During a short time interval, an incorrect local code is applied to the mixer to incorrectly demodulate the incoming signal and to provide a reference level that calibrates the noise propagating through the channel. A sample and hold circuit is coupled to the channel for storing a sample of the reference level. During a relatively long time interval, the correct replica code provides an output level which ranges between the reference level and a maximum level that represents incoming signal presence and synchronism with the replica code. A summer substracts the stored sample reference from the output level to provide a resultant difference signal indicative of the acquisition of the expected signal.

Evaluation of Method-Specific Extraction Variability for the Measurement of Fatty Acids in a Candidate Infant/Adult Nutritional Formula Reference Material.

PubMed

Place, Benjamin J

2017-05-01

To address community needs, the National Institute of Standards and Technology has developed a candidate Standard Reference Material (SRM) for infant/adult nutritional formula based on milk and whey protein concentrates with isolated soy protein called SRM 1869 Infant/Adult Nutritional Formula. One major component of this candidate SRM is the fatty acid content. In this study, multiple extraction techniques were evaluated to quantify the fatty acids in this new material. Extraction methods that were based on lipid extraction followed by transesterification resulted in lower mass fraction values for all fatty acids than the values measured by methods utilizing in situ transesterification followed by fatty acid methyl ester extraction (ISTE). An ISTE method, based on the identified optimal parameters, was used to determine the fatty acid content of the new infant/adult nutritional formula reference material.

A method for velocity signal reconstruction of AFDISAR/PDV based on crazy-climber algorithm

NASA Astrophysics Data System (ADS)

Peng, Ying-cheng; Guo, Xian; Xing, Yuan-ding; Chen, Rong; Li, Yan-jie; Bai, Ting

2017-10-01

The resolution of Continuous wavelet transformation (CWT) is different when the frequency is different. For this property, the time-frequency signal of coherent signal obtained by All Fiber Displacement Interferometer System for Any Reflector (AFDISAR) is extracted. Crazy-climber Algorithm is adopted to extract wavelet ridge while Velocity history curve of the measuring object is obtained. Numerical simulation is carried out. The reconstruction signal is completely consistent with the original signal, which verifies the accuracy of the algorithm. Vibration of loudspeaker and free end of Hopkinson incident bar under impact loading are measured by AFDISAR, and the measured coherent signals are processed. Velocity signals of loudspeaker and free end of Hopkinson incident bar are reconstructed respectively. Comparing with the theoretical calculation, the particle vibration arrival time difference error of the free end of Hopkinson incident bar is 2μs. It is indicated from the results that the algorithm is of high accuracy, and is of high adaptability to signals of different time-frequency feature. The algorithm overcomes the limitation of modulating the time window artificially according to the signal variation when adopting STFT, and is suitable for extracting signal measured by AFDISAR.

EXTRACTING PERIODIC TRANSIT SIGNALS FROM NOISY LIGHT CURVES USING FOURIER SERIES

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

Samsing, Johan

We present a simple and powerful method for extracting transit signals associated with a known transiting planet from noisy light curves. Assuming the orbital period of the planet is known and the signal is periodic, we illustrate that systematic noise can be removed in Fourier space at all frequencies by only using data within a fixed time frame with a width equal to an integer number of orbital periods. This results in a reconstruction of the full transit signal, which on average is unbiased despite no prior knowledge of either the noise or the transit signal itself being used inmore » the analysis. The method therefore has clear advantages over standard phase folding, which normally requires external input such as nearby stars or noise models for removing systematic components. In addition, we can extract the full orbital transit signal (360°) simultaneously, and Kepler-like data can be analyzed in just a few seconds. We illustrate the performance of our method by applying it to a dataset composed of light curves from Kepler with a fake injected signal emulating a planet with rings. For extracting periodic transit signals, our presented method is in general the optimal and least biased estimator and could therefore lead the way toward the first detections of, e.g., planet rings and exo-trojan asteroids.« less

Potent activity of nobiletin-rich Citrus reticulata peel extract to facilitate cAMP/PKA/ERK/CREB signaling associated with learning and memory in cultured hippocampal neurons: identification of the substances responsible for the pharmacological action.

PubMed

Kawahata, Ichiro; Yoshida, Masaaki; Sun, Wen; Nakajima, Akira; Lai, Yanxin; Osaka, Naoya; Matsuzaki, Kentaro; Yokosuka, Akihito; Mimaki, Yoshihiro; Naganuma, Akira; Tomioka, Yoshihisa; Yamakuni, Tohru

2013-10-01

cAMP/PKA/ERK/CREB signaling linked to CRE-mediated transcription is crucial for learning and memory. We originally found nobiletin as a natural compound that stimulates this intracellular signaling and exhibits anti-dementia action in animals. Citrus reticulata or C. unshiu peels are employed as "chinpi" and include a small amount of nobiletin. We here provide the first evidence for beneficial pharmacological actions on the cAMP/PKA/ERK/CREB cascade of extracts from nobiletin-rich C.reticulata peels designated as Nchinpi, the nobiletin content of which was 0.83 ± 0.13% of the dry weight or 16-fold higher than that of standard chinpi extracts. Nchinpi extracts potently facilitated CRE-mediated transcription in cultured hippocampal neurons, whereas the standard chinpi extracts showed no such activity. Also, the Nchinpi extract, but not the standard chinpi extract, stimulated PKA/ERK/CREB signaling. Interestingly, treatment with the Nchinpi extract at the concentration corresponding to approximately 5 μM nobiletin more potently facilitated CRE-mediated transcriptional activity than did 30 μM nobiletin alone. Consistently, sinensetin, tangeretin, 6-demethoxynobiletin, and 6-demethoxytangeretin were also identified as bioactive substances in Nchinpi that facilitated the CRE-mediated transcription. Purified sinensetin enhanced the transcription to a greater degree than nobiletin. Furthermore, samples reconstituted with the four purified compounds and nobiletin in the ratio of each constituent's content in the extract showed activity almost equal to that of the Nchinpi extract to stimulate CRE-mediated transcription. These findings suggest that above four compounds and nobiletin in the Nchinpi extract mainly cooperated to facilitate potently CRE-mediated transcription linked to the upstream cAMP/PKA/ERK/CREB pathway in hippocampal neurons.

An approach to predict Sudden Cardiac Death (SCD) using time domain and bispectrum features from HRV signal.

PubMed

Houshyarifar, Vahid; Chehel Amirani, Mehdi

2016-08-12

In this paper we present a method to predict Sudden Cardiac Arrest (SCA) with higher order spectral (HOS) and linear (Time) features extracted from heart rate variability (HRV) signal. Predicting the occurrence of SCA is important in order to avoid the probability of Sudden Cardiac Death (SCD). This work is a challenge to predict five minutes before SCA onset. The method consists of four steps: pre-processing, feature extraction, feature reduction, and classification. In the first step, the QRS complexes are detected from the electrocardiogram (ECG) signal and then the HRV signal is extracted. In second step, bispectrum features of HRV signal and time-domain features are obtained. Six features are extracted from bispectrum and two features from time-domain. In the next step, these features are reduced to one feature by the linear discriminant analysis (LDA) technique. Finally, KNN and support vector machine-based classifiers are used to classify the HRV signals. We used two database named, MIT/BIH Sudden Cardiac Death (SCD) Database and Physiobank Normal Sinus Rhythm (NSR). In this work we achieved prediction of SCD occurrence for six minutes before the SCA with the accuracy over 91%.

Method for protecting an electric generator

DOEpatents

Kuehnle, Barry W.; Roberts, Jeffrey B.; Folkers, Ralph W.

2008-11-18

A method for protecting an electrical generator which includes providing an electrical generator which is normally synchronously operated with an electrical power grid; providing a synchronizing signal from the electrical generator; establishing a reference signal; and electrically isolating the electrical generator from the electrical power grid if the synchronizing signal is not in phase with the reference signal.

EPR investigations of gamma-irradiated ground black pepper

NASA Astrophysics Data System (ADS)

Polovka, Martin; Brezová, Vlasta; Staško, Andrej; Mazúr, Milan; Suhaj, Milan; Šimko, Peter

2006-02-01

The γ-radiation treatment of ground black pepper samples resulted in the production of three paramagnetic species ( GI- GIII) which arise from a different origin and have different thermal behavior and stability. The axially symmetric spectra can be characterized by the spin Hamiltonian parameters: GI ( g⊥=2.0060, g∥=2.0032; A⊥=0.85 mT, A∥=0.70 mT) and GII ( g⊥=2.0060, g∥=2.0050; A⊥=0.50 mT, A∥=0.40 mT) assigned to carbohydrate radical structures. The parameters of EPR signal GIII ( g⊥=2.0029, g∥=2.0014; A⊥=3.00 mT, A∥=1.80 mT) possessed features characteristic of cellulose radical species. The activation energies, evaluated by Arrhenius analysis, are in order Ea( GI)< Ea( GIII)< Ea( GII). The EPR measurements performed 20 weeks after radiation process confirmed that a temperature increase from 298 to 353 K, caused a significant decrease of integral EPR signal intensity for γ-irradiated samples (˜40%), compared to the reference (non-irradiated) ground black pepper, where a decrease of ˜13% was found. The influence of γ-radiation treatment on the radical-scavenging activities of aqueous and ethanol extracts of black pepper were investigated by both an EPR spin trapping technique and DPPH assay. No changes were detected in either the water or ethanol extracts for a γ-irradiation dose of 10 kGy.

Measurement of Regional Environmental Noise by Use of a Pc-Based System. A Application to the Noise Near Airport ``G. Marconi'' in Bologna

NASA Astrophysics Data System (ADS)

Sakai, H.; Sato, S.; Prodi, N.; Pompoli, R.

2001-03-01

Measurements of aircraft noise were made at the airport "G. Marconi" in Bologna by using a measurement system for regional environmental noise. The system is based on the model of the human auditory-brain system, which is based on the interplay of autocorrelators and an interaural cross-correlator acting on the pressure signals arriving at the ear entrances, and takes into account the specialization of left and right human cerebral hemispheres (see reference [8]). Measurements were taken through dual microphones at ear entrances of a dummy head. The aircraft noise was characterized with the following physical factors calculated from the autocorrelation function (ACF) and interaural cross-correlation function (IACF) for binaural signals. From the ACF analysis, (1) energy represented at the origin of delay,Φ (0), (2) effective duration of the envelope of the normalized ACF, τe, (3) the delay time of the first peak, τ1, and (4) its amplitude, φ1were extracted. From the IACF analysis, (5) IACC, (6) interaural delay time at which the IACC is defined, τIACC, and (7) width of the IACF at the τIACC, WIACCwere extracted. The factorΦ (0) can be represented as the geometrical mean of the energies at both ears. A noise source may be identified by these factors as timbre.

A Transform-Based Feature Extraction Approach for Motor Imagery Tasks Classification

PubMed Central

Khorshidtalab, Aida; Mesbah, Mostefa; Salami, Momoh J. E.

2015-01-01

In this paper, we present a new motor imagery classification method in the context of electroencephalography (EEG)-based brain–computer interface (BCI). This method uses a signal-dependent orthogonal transform, referred to as linear prediction singular value decomposition (LP-SVD), for feature extraction. The transform defines the mapping as the left singular vectors of the LP coefficient filter impulse response matrix. Using a logistic tree-based model classifier; the extracted features are classified into one of four motor imagery movements. The proposed approach was first benchmarked against two related state-of-the-art feature extraction approaches, namely, discrete cosine transform (DCT) and adaptive autoregressive (AAR)-based methods. By achieving an accuracy of 67.35%, the LP-SVD approach outperformed the other approaches by large margins (25% compared with DCT and 6 % compared with AAR-based methods). To further improve the discriminatory capability of the extracted features and reduce the computational complexity, we enlarged the extracted feature subset by incorporating two extra features, namely, Q- and the Hotelling’s \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}$T^{2}$ \\end{document} statistics of the transformed EEG and introduced a new EEG channel selection method. The performance of the EEG classification based on the expanded feature set and channel selection method was compared with that of a number of the state-of-the-art classification methods previously reported with the BCI IIIa competition data set. Our method came second with an average accuracy of 81.38%. PMID:27170898

Acoustic emission signal processing for rolling bearing running state assessment using compressive sensing

NASA Astrophysics Data System (ADS)

Liu, Chang; Wu, Xing; Mao, Jianlin; Liu, Xiaoqin

2017-07-01

In the signal processing domain, there has been growing interest in using acoustic emission (AE) signals for the fault diagnosis and condition assessment instead of vibration signals, which has been advocated as an effective technique for identifying fracture, crack or damage. The AE signal has high frequencies up to several MHz which can avoid some signals interference, such as the parts of bearing (i.e. rolling elements, ring and so on) and other rotating parts of machine. However, acoustic emission signal necessitates advanced signal sampling capabilities and requests ability to deal with large amounts of sampling data. In this paper, compressive sensing (CS) is introduced as a processing framework, and then a compressive features extraction method is proposed. We use it for extracting the compressive features from compressively-sensed data directly, and also prove the energy preservation properties. First, we study the AE signals under the CS framework. The sparsity of AE signal of the rolling bearing is checked. The observation and reconstruction of signal is also studied. Second, we present a method of extraction AE compressive feature (AECF) from compressively-sensed data directly. We demonstrate the energy preservation properties and the processing of the extracted AECF feature. We assess the running state of the bearing using the AECF trend. The AECF trend of the running state of rolling bearings is consistent with the trend of traditional features. Thus, the method is an effective way to evaluate the running trend of rolling bearings. The results of the experiments have verified that the signal processing and the condition assessment based on AECF is simpler, the amount of data required is smaller, and the amount of computation is greatly reduced.

Quantifying cancer cell receptors with paired-agent fluorescent imaging: a novel method to account for tissue optical property effects

NASA Astrophysics Data System (ADS)

Sadeghipour, Negar; Davis, Scott C.; Tichauer, Kenneth M.

2018-02-01

Dynamic fluorescence imaging approaches can be used to estimate the concentration of cell surface receptors in vivo. Kinetic models are used to generate the final estimation by taking the targeted imaging agent concentration as a function of time. However, tissue absorption and scattering properties cause the final readout signal to be on a different scale than the real fluorescent agent concentration. In paired-agent imaging approaches, simultaneous injection of a suitable control imaging agent with a targeted one can account for non-specific uptake and retention of the targeted agent. Additionally, the signal from the control agent can be a normalizing factor to correct for tissue optical property differences. In this study, the kinetic model used for paired-agent imaging analysis (i.e., simplified reference tissue model) is modified and tested in simulation and experimental data in a way that accounts for the scaling correction within the kinetic model fit to the data to ultimately extract an estimate of the targeted biomarker concentration.

Automatic topics segmentation for TV news video

NASA Astrophysics Data System (ADS)

Hmayda, Mounira; Ejbali, Ridha; Zaied, Mourad

2017-03-01

Automatic identification of television programs in the TV stream is an important task for operating archives. This article proposes a new spatio-temporal approach to identify the programs in TV stream into two main steps: First, a reference catalogue for video features visual jingles built. We operate the features that characterize the instances of the same program type to identify the different types of programs in the flow of television. The role of video features is to represent the visual invariants for each visual jingle using appropriate automatic descriptors for each television program. On the other hand, programs in television streams are identified by examining the similarity of the video signal for visual grammars in the catalogue. The main idea of the identification process is to compare the visual similarity of the video signal features in the flow of television to the catalogue. After presenting the proposed approach, the paper overviews encouraging experimental results on several streams extracted from different channels and compounds of several programs.

Determination of the reference position in the near-infrared non-invasive blood glucose measurement in vivo

NASA Astrophysics Data System (ADS)

Han, Guang; Liu, Jin; Liu, Rong; Xu, Kexin

2016-10-01

Position-based reference measurement method is taken as one of the most promising method in non-invasive measurement of blood glucose based on spectroscopic methodology. Selecting an appropriate source-detector separation as the reference position is important for deducting the influence of background change and reducing the loss of useful signals. Our group proposed a special source-detector separation named floating-reference position where the signal contains only background change, that is to say, the signal at this source-detector separation is uncorrelated with glucose concentration. The existence of floating-reference position has been verified in a three layer skin by Monte Carlo simulation and in the in vitro experiment. But it is difficult to verify the existence of floating-reference position on the human body because the interference is more complex during in vivo experiment. Aiming at this situation, this paper studies the determination of the best reference position on human body by collecting signals at several source-detector separations on the palm and measuring the true blood glucose levels during oral glucose tolerance test (OGTT) experiments of 3 volunteers. Partial least square (PLS) calibration model is established between the signals at every source-detector separation and its corresponding blood glucose levels. The results shows that the correlation coefficient (R) between 1.32 mm to 1.88 mm is lowest and they can be used as reference for background correction. The signal of this special position is important for improving the accuracy of near-infrared non-invasive blood glucose measurement.

Accurate determination of brain metabolite concentrations using ERETIC as external reference.

PubMed

Zoelch, Niklaus; Hock, Andreas; Heinzer-Schweizer, Susanne; Avdievitch, Nikolai; Henning, Anke

2017-08-01

Magnetic Resonance Spectroscopy (MRS) can provide in vivo metabolite concentrations in standard concentration units if a reliable reference signal is available. For 1 H MRS in the human brain, typically the signal from the tissue water is used as the (internal) reference signal. However, a concentration determination based on the tissue water signal most often requires a reliable estimate of the water concentration present in the investigated tissue. Especially in clinically interesting cases, this estimation might be difficult. To avoid assumptions about the water in the investigated tissue, the Electric REference To access In vivo Concentrations (ERETIC) method has been proposed. In this approach, the metabolite signal is compared with a reference signal acquired in a phantom and potential coil-loading differences are corrected using a synthetic reference signal. The aim of this study, conducted with a transceiver quadrature head coil, was to increase the accuracy of the ERETIC method by correcting the influence of spatial B 1 inhomogeneities and to simplify the quantification with ERETIC by incorporating an automatic phase correction for the ERETIC signal. Transmit field ( B1+) differences are minimized with a volume-selective power optimization, whereas reception sensitivity changes are corrected using contrast-minimized images of the brain and by adapting the voxel location in the phantom measurement closely to the position measured in vivo. By applying the proposed B 1 correction scheme, the mean metabolite concentrations determined with ERETIC in 21 healthy subjects at three different positions agree with concentrations derived with the tissue water signal as reference. In addition, brain water concentrations determined with ERETIC were in agreement with estimations derived using tissue segmentation and literature values for relative water densities. Based on the results, the ERETIC method presented here is a valid tool to derive in vivo metabolite concentration, with potential advantages compared with internal water referencing in diseased tissue. Copyright © 2017 John Wiley & Sons, Ltd.

What Makes a Matrix so Effective? An Empirical Test of the Relative Benefits of Signaling, Extraction, and Localization

ERIC Educational Resources Information Center

Kauffman, Douglas F.; Kiewra, Kenneth A.

2010-01-01

What type of display helps students learn the most and why? This study investigated how displays differing in terms of signaling, extraction, and localization impact learning. In Experiment 1, 72 students were assigned randomly to one cell of a 4 x 2 design. Students studied a standard text, a text with key ideas extracted, an outline that…

Simple method for self-referenced and lable-free biosensing by using a capillary sensing element.

PubMed

Liu, Yun; Chen, Shimeng; Liu, Qiang; Liu, Zigeng; Wei, Peng

2017-05-15

We demonstrated a simple method for self-reference and label free biosensing based on a capillary sensing element and common optoelectronic devices. The capillary sensing element is illuminated by a light-emitting diode (LED) light source and detected by a webcam. Part of gold film that deposited on the tubing wall is functionalized to carry on the biological information in the excited SPR modes. The end face of the capillary was monitored and separate regions of interest (ROIs) were selected as the measurement channel and the reference channel. In the ROIs, the biological information can be accurately extracted from the image by simple image processing. Moreover, temperature fluctuation, bulk RI fluctuation, light source fluctuation and other factors can be effectively compensated during detection. Our biosensing device has a sensitivity of 1145%/RIU and a resolution better than 5.287 × 10 -4 RIU, considering a 0.79% noise level. We apply it for concanavalin A (Con A) biological measurement, which has an approximately linear response to the specific analyte concentration. This simple method provides a new approach for multichannel SPR sensing and reference-compensated calibration of SPR signal for label-free detection.

Carrier-frequency synchronization system for improved amplitude modulation and television broadcast reception

DOEpatents

Smith, Stephen F.; Moore, James A.

2003-05-13

Systems and methods are described for carrier-frequency synchronization for improved AM and TV broadcast reception. A method includes synchronizing a carrier frequency of a broadcast signal with a remote reference frequency. An apparatus includes a reference signal receiver; a phase comparator coupled to the reference signal receiver; a voltage controlled oscillator coupled to the phase comparator; and a radio frequency output coupled to the voltage controlled oscillator.

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

Smith, Stephen F; Moore, James A

Systems and methods are described for carrier phase synchronization for improved AM and TV broadcast reception. A method includes synchronizing the phase of a carrier frequency of a broadcast signal with the phase of a remote reference frequency. An apparatus includes a receiver to detect the phase of a reference signal; a phase comparator coupled to the reference signal-phase receiver; a voltage controlled oscillator coupled to the phase comparator; and a phase-controlled radio frequency output coupled to the voltage controlled oscillator.

[An improved algorithm for electrohysterogram envelope extraction].

PubMed

Lu, Yaosheng; Pan, Jie; Chen, Zhaoxia; Chen, Zhaoxia

2017-02-01

Extraction uterine contraction signal from abdominal uterine electromyogram(EMG) signal is considered as the most promising method to replace the traditional tocodynamometer(TOCO) for detecting uterine contractions activity. The traditional root mean square(RMS) algorithm has only some limited values in canceling the impulsive noise. In our study, an improved algorithm for uterine EMG envelope extraction was proposed to overcome the problem. Firstly, in our experiment, zero-crossing detection method was used to separate the burst of uterine electrical activity from the raw uterine EMG signal. After processing the separated signals by employing two filtering windows which have different width, we used the traditional RMS algorithm to extract uterus EMG envelope. To assess the performance of the algorithm, the improved algorithm was compared with two existing intensity of uterine electromyogram(IEMG) extraction algorithms. The results showed that the improved algorithm was better than the traditional ones in eliminating impulsive noise present in the uterine EMG signal. The measurement sensitivity and positive predictive value(PPV) of the improved algorithm were 0.952 and 0.922, respectively, which were not only significantly higher than the corresponding values(0.859 and 0.847) of the first comparison algorithm, but also higher than the values(0.928 and 0.877) of the second comparison algorithm. Thus the new method is reliable and effective.

Comparison of wavelet based denoising schemes for gear condition monitoring: An Artificial Neural Network based Approach

NASA Astrophysics Data System (ADS)

Ahmed, Rounaq; Srinivasa Pai, P.; Sriram, N. S.; Bhat, Vasudeva

2018-02-01

Vibration Analysis has been extensively used in recent past for gear fault diagnosis. The vibration signals extracted is usually contaminated with noise and may lead to wrong interpretation of results. The denoising of extracted vibration signals helps the fault diagnosis by giving meaningful results. Wavelet Transform (WT) increases signal to noise ratio (SNR), reduces root mean square error (RMSE) and is effective to denoise the gear vibration signals. The extracted signals have to be denoised by selecting a proper denoising scheme in order to prevent the loss of signal information along with noise. An approach has been made in this work to show the effectiveness of Principal Component Analysis (PCA) to denoise gear vibration signal. In this regard three selected wavelet based denoising schemes namely PCA, Empirical Mode Decomposition (EMD), Neighcoeff Coefficient (NC), has been compared with Adaptive Threshold (AT) an extensively used wavelet based denoising scheme for gear vibration signal. The vibration signals acquired from a customized gear test rig were denoised by above mentioned four denoising schemes. The fault identification capability as well as SNR, Kurtosis and RMSE for the four denoising schemes have been compared. Features extracted from the denoised signals have been used to train and test artificial neural network (ANN) models. The performances of the four denoising schemes have been evaluated based on the performance of the ANN models. The best denoising scheme has been identified, based on the classification accuracy results. PCA is effective in all the regards as a best denoising scheme.

Digital automatic gain amplifier

NASA Technical Reports Server (NTRS)

Holley, L. D.; Ward, J. O. (Inventor)

1978-01-01

A circuit is described for adjusting the amplitude of a reference signal to a predetermined level so as to permit subsequent data signals to be interpreted correctly. The circuit includes an operational amplifier having a feedback circuit connected between an output terminal and an input terminal; a bank of relays operably connected to a plurality of resistors; and a comparator comparing an output voltage of the amplifier with a reference voltage and generating a compared signal responsive thereto. Means is provided for selectively energizing the relays according to the compared signal from the comparator until the output signal from the amplifier equals to the reference signal. A second comparator is provided for comparing the output of the amplifier with a second voltage source so as to illuminate a lamp when the output signal from the amplifier exceeds the second voltage.

Radiant Temperature Nulling Radiometer

NASA Technical Reports Server (NTRS)

Ryan, Robert (Inventor)

2003-01-01

A self-calibrating nulling radiometer for non-contact temperature measurement of an object, such as a body of water, employs a black body source as a temperature reference, an optomechanical mechanism, e.g., a chopper, to switch back and forth between measuring the temperature of the black body source and that of a test source, and an infrared detection technique. The radiometer functions by measuring radiance of both the test and the reference black body sources; adjusting the temperature of the reference black body so that its radiance is equivalent to the test source; and, measuring the temperature of the reference black body at this point using a precision contact-type temperature sensor, to determine the radiative temperature of the test source. The radiation from both sources is detected by an infrared detector that converts the detected radiation to an electrical signal that is fed with a chopper reference signal to an error signal generator, such as a synchronous detector, that creates a precision rectified signal that is approximately proportional to the difference between the temperature of the reference black body and that of the test infrared source. This error signal is then used in a feedback loop to adjust the reference black body temperature until it equals that of the test source, at which point the error signal is nulled to zero. The chopper mechanism operates at one or more Hertz allowing minimization of l/f noise. It also provides pure chopping between the black body and the test source and allows continuous measurements.

A UWB Radar Signal Processing Platform for Real-Time Human Respiratory Feature Extraction Based on Four-Segment Linear Waveform Model.

PubMed

Hsieh, Chi-Hsuan; Chiu, Yu-Fang; Shen, Yi-Hsiang; Chu, Ta-Shun; Huang, Yuan-Hao

2016-02-01

This paper presents an ultra-wideband (UWB) impulse-radio radar signal processing platform used to analyze human respiratory features. Conventional radar systems used in human detection only analyze human respiration rates or the response of a target. However, additional respiratory signal information is available that has not been explored using radar detection. The authors previously proposed a modified raised cosine waveform (MRCW) respiration model and an iterative correlation search algorithm that could acquire additional respiratory features such as the inspiration and expiration speeds, respiration intensity, and respiration holding ratio. To realize real-time respiratory feature extraction by using the proposed UWB signal processing platform, this paper proposes a new four-segment linear waveform (FSLW) respiration model. This model offers a superior fit to the measured respiration signal compared with the MRCW model and decreases the computational complexity of feature extraction. In addition, an early-terminated iterative correlation search algorithm is presented, substantially decreasing the computational complexity and yielding negligible performance degradation. These extracted features can be considered the compressed signals used to decrease the amount of data storage required for use in long-term medical monitoring systems and can also be used in clinical diagnosis. The proposed respiratory feature extraction algorithm was designed and implemented using the proposed UWB radar signal processing platform including a radar front-end chip and an FPGA chip. The proposed radar system can detect human respiration rates at 0.1 to 1 Hz and facilitates the real-time analysis of the respiratory features of each respiration period.

Weak Fault Feature Extraction of Rolling Bearings Based on an Improved Kurtogram.

PubMed

Chen, Xianglong; Feng, Fuzhou; Zhang, Bingzhi

2016-09-13

Kurtograms have been verified to be an efficient tool in bearing fault detection and diagnosis because of their superiority in extracting transient features. However, the short-time Fourier Transform is insufficient in time-frequency analysis and kurtosis is deficient in detecting cyclic transients. Those factors weaken the performance of the original kurtogram in extracting weak fault features. Correlated Kurtosis (CK) is then designed, as a more effective solution, in detecting cyclic transients. Redundant Second Generation Wavelet Packet Transform (RSGWPT) is deemed to be effective in capturing more detailed local time-frequency description of the signal, and restricting the frequency aliasing components of the analysis results. The authors in this manuscript, combining the CK with the RSGWPT, propose an improved kurtogram to extract weak fault features from bearing vibration signals. The analysis of simulation signals and real application cases demonstrate that the proposed method is relatively more accurate and effective in extracting weak fault features.

LWT Based Sensor Node Signal Processing in Vehicle Surveillance Distributed Sensor Network

NASA Astrophysics Data System (ADS)

Cha, Daehyun; Hwang, Chansik

Previous vehicle surveillance researches on distributed sensor network focused on overcoming power limitation and communication bandwidth constraints in sensor node. In spite of this constraints, vehicle surveillance sensor node must have signal compression, feature extraction, target localization, noise cancellation and collaborative signal processing with low computation and communication energy dissipation. In this paper, we introduce an algorithm for light-weight wireless sensor node signal processing based on lifting scheme wavelet analysis feature extraction in distributed sensor network.

Automatic retinal blood vessel parameter calculation in spectral domain optical coherence tomography

NASA Astrophysics Data System (ADS)

Wehbe, Hassan; Ruggeri, Marco; Jiao, Shuliang; Gregori, Giovanni; Puliafito, Carmen A.

2007-02-01

Measurement of retinal blood vessel parameters like the blood blow in the vessels may have significant impact on the study and diagnosis of glaucoma, a leading blinding disease worldwide. Optical coherence tomography (OCT) is a noninvasive imaging technique that can provide not only microscopic structural imaging of the retina but also functional information like the blood flow velocity in the retina. The aim of this study is to automatically extract the parameters of retinal blood vessels like the 3D orientation, the vessel diameters, as well as the corresponding absolute blood flow velocity in the vessel. The parameters were extracted from circular OCT scans around the optic disc. By removing the surface reflection through simple segmentation of the circular OCT scans a blood vessel shadowgram can be generated. The lateral coordinates and the diameter of each blood vessel are extracted from the shadowgram through a series of signal processing. Upon determination of the lateral position and the vessel diameter, the coordinate in the depth direction of each blood vessel is calculated in combination with the Doppler information for the vessel. The extraction of the vessel coordinates and diameter makes it possible to calculate the orientation of the vessel in reference to the direction of the incident sample light, which in turn can be used to calculate the absolute blood flow velocity and the flow rate.

An ultra low-power front-end IC for wearable health monitoring system.

PubMed

Yu-Pin Hsu; Zemin Liu; Hella, Mona M

2016-08-01

This paper presents a low-power front-end IC for wearable health monitoring systems. The IC, designed in a standard 0.13μm CMOS technology, fully integrates a low-noise analog front-end (AFE) to process the weak bio-signals, followed by an analog-to-digital converter (ADC) to digitize the extracted signals. An AC-coupled driving buffer, that interfaces between the AFE and the ADC is introduced to scale down the power supply of the ADC. The power consumption decreases by 50% compared to the case without power supply scaling. The AFE passes signals from 0.5Hz to 280Hz and from 0.7Hz to 160Hz with a simulated input referred noise of 1.6μVrms and achieves a maximum gain of 35dB/41dB respectively, with a noise-efficiency factor (NEF) of the AFE is 1. The 8-bit ADC achieves a simulated 7.96-bit resolution at 10KS/s sampling rate under 0.5V supply voltage. The overall system consumes only 0.86μW at dual supply voltages of 1V (AFE) and 0.5 V (ADC).

A Machine Learning Approach to the Detection of Pilot's Reaction to Unexpected Events Based on EEG Signals

PubMed Central

Cyran, Krzysztof A.

2018-01-01

This work considers the problem of utilizing electroencephalographic signals for use in systems designed for monitoring and enhancing the performance of aircraft pilots. Systems with such capabilities are generally referred to as cognitive cockpits. This article provides a description of the potential that is carried by such systems, especially in terms of increasing flight safety. Additionally, a neuropsychological background of the problem is presented. Conducted research was focused mainly on the problem of discrimination between states of brain activity related to idle but focused anticipation of visual cue and reaction to it. Especially, a problem of selecting a proper classification algorithm for such problems is being examined. For that purpose an experiment involving 10 subjects was planned and conducted. Experimental electroencephalographic data was acquired using an Emotiv EPOC+ headset. Proposed methodology involved use of a popular method in biomedical signal processing, the Common Spatial Pattern, extraction of bandpower features, and an extensive test of different classification algorithms, such as Linear Discriminant Analysis, k-nearest neighbors, and Support Vector Machines with linear and radial basis function kernels, Random Forests, and Artificial Neural Networks. PMID:29849544

Apparatus for controlling the firing of rectifiers in polyphase rectifying circuits

DOEpatents

Yarema, R.J.

1979-09-18

A polyphase rectifier is controlled with precision by a circuit that filters and shifts a reference signal associated with each phase and that starts a ramp signal at a zero crossing of the shifted reference signal. The difference between the ramp signal and an external trigger signal is used to generate a pulse that switches power rectifiers into conduction. The circuit reduces effects of variations that introduce subharmonics into a rectified signal and it can be used for constant or time-varying external trigger signals.

A solid-phase extraction procedure coupled to 1H NMR, with chemometric analysis, to seek reliable markers of the botanical origin of honey.

PubMed

Beretta, Giangiacomo; Caneva, Enrico; Regazzoni, Luca; Bakhtyari, Nazanin Golbamaki; Maffei Facino, Roberto

2008-07-14

The aim of this work was to establish an analytical method for identifying the botanical origin of honey, as an alternative to conventional melissopalynological, organoleptic and instrumental methods (gas-chromatography coupled to mass spectrometry (GC-MS), high-performance liquid chromatography HPLC). The procedure is based on the (1)H nuclear magnetic resonance (NMR) profile coupled, when necessary, with electrospray ionisation-mass spectrometry (ESI-MS) and two-dimensional NMR analyses of solid-phase extraction (SPE)-purified honey samples, followed by chemometric analyses. Extracts of 44 commercial Italian honeys from 20 different botanical sources were analyzed. Honeydew, chestnut and linden honeys showed constant, specific, well-resolved resonances, suitable for use as markers of origin. Honeydew honey contained the typical resonances of an aliphatic component, very likely deriving from the plant phloem sap or excreted into it by sap-sucking aphids. Chestnut honey contained the typical signals of kynurenic acid and some structurally related metabolite. In linden honey the (1)H NMR profile gave strong signals attributable to the mono-terpene derivative cyclohexa-1,3-diene-1-carboxylic acid (CDCA) and to its 1-O-beta-gentiobiosyl ester (CDCA-GBE). These markers were not detectable in the other honeys, except for the less common nectar honey from rosa mosqueta. We compared and analyzed the data by multivariate techniques. Principal component analysis found different clusters of honeys based on the presence of these specific markers. The results, although obviously only preliminary, suggest that the (1)H NMR profile (with HPLC-MS analysis when necessary) can be used as a reference framework for identifying the botanical origin of honey.

Method and apparatus for a single channel digital communications system. [synchronization of received PCM signal by digital correlation with reference signal

NASA Technical Reports Server (NTRS)

Couvillon, L. A., Jr.; Carl, C.; Goldstein, R. M.; Posner, E. C.; Green, R. R. (Inventor)

1973-01-01

A method and apparatus are described for synchronizing a received PCM communications signal without requiring a separate synchronizing channel. The technique provides digital correlation of the received signal with a reference signal, first with its unmodulated subcarrier and then with a bit sync code modulated subcarrier, where the code sequence length is equal in duration to each data bit.

Adaptive Control with Reference Model Modification

NASA Technical Reports Server (NTRS)

Stepanyan, Vahram; Krishnakumar, Kalmanje

2012-01-01

This paper presents a modification of the conventional model reference adaptive control (MRAC) architecture in order to improve transient performance of the input and output signals of uncertain systems. A simple modification of the reference model is proposed by feeding back the tracking error signal. It is shown that the proposed approach guarantees tracking of the given reference command and the reference control signal (one that would be designed if the system were known) not only asymptotically but also in transient. Moreover, it prevents generation of high frequency oscillations, which are unavoidable in conventional MRAC systems for large adaptation rates. The provided design guideline makes it possible to track a reference commands of any magnitude from any initial position without re-tuning. The benefits of the method are demonstrated with a simulation example

Classification of epileptic EEG signals based on simple random sampling and sequential feature selection.

PubMed

Ghayab, Hadi Ratham Al; Li, Yan; Abdulla, Shahab; Diykh, Mohammed; Wan, Xiangkui

2016-06-01

Electroencephalogram (EEG) signals are used broadly in the medical fields. The main applications of EEG signals are the diagnosis and treatment of diseases such as epilepsy, Alzheimer, sleep problems and so on. This paper presents a new method which extracts and selects features from multi-channel EEG signals. This research focuses on three main points. Firstly, simple random sampling (SRS) technique is used to extract features from the time domain of EEG signals. Secondly, the sequential feature selection (SFS) algorithm is applied to select the key features and to reduce the dimensionality of the data. Finally, the selected features are forwarded to a least square support vector machine (LS_SVM) classifier to classify the EEG signals. The LS_SVM classifier classified the features which are extracted and selected from the SRS and the SFS. The experimental results show that the method achieves 99.90, 99.80 and 100 % for classification accuracy, sensitivity and specificity, respectively.

Hair growth-promoting effect of Aconiti Ciliare Tuber extract mediated by the activation of Wnt/β-catenin signaling.

PubMed

Park, Phil-June; Moon, Byoung-San; Lee, Soung-Hoon; Kim, Su-Na; Kim, Ah-Reum; Kim, Hyung-Jun; Park, Won-Seok; Choi, Kang-Yell; Cho, Eun-Gyung; Lee, Tae Ryong

2012-11-02

The activation of Wnt/β-catenin signaling pathway plays an important role in hair follicle morphogenesis by stimulating bulge stem cells. This study was to obtain the activator of Wnt/β-catenin signaling pathway from natural products and to determine whether this activator can induce anagen hair growth in mice. To identify materials that activate Wnt/β-catenin signaling pathway, 800 natural product extracts were screened using pTOPFlash assay and neural progenitor cell (NPC) differentiation assay. A selected extract was further tested for its effects on alkaline phosphatase (ALP) activity in human immortalized dermal papilla cell (iDPC) and the proliferation in iDPC and immortalized rat vibrissa DPC (RvDP). Finally, hair growth-promoting effects were evaluated in the dorsal skin of C57BL/6 mice. Aconiti Ciliare Tuber (ACT) extract was one of the most active materials in both pTOPFlash and NPC differentiation assays. It promoted the differentiation of NPC cells even under proliferation-stimulating conditions (basic fibroblast growth factor: bFGF). It also increased ALP activity and proliferation of iDPC in dose-dependent manners, and it stimulated the induction of the anagen hair growth in C57BL/6 mice. These results suggest that ACT extract activates the Wnt/β-catenin signaling pathway by enhancing β-catenin transcription and has the potential to promote the induction of hair growth via activation of the stem cell activity of the dermal papilla cells. This is the first report indicating benefits of ACT extract in hair loss prevention by triggering the activation of Wnt/β-catenin signaling pathway and induction of the anagen hair growth in mice. Copyright © 2012 Elsevier Inc. All rights reserved.

Randomized Hough transform filter for echo extraction in DLR

NASA Astrophysics Data System (ADS)

Liu, Tong; Chen, Hao; Shen, Ming; Gao, Pengqi; Zhao, You

2016-11-01

The signal-to-noise ratio (SNR) of debris laser ranging (DLR) data is extremely low, and the valid returns in the DLR range residuals are distributed on a curve in a long observation time. Therefore, it is hard to extract the signals from noise in the Observed-minus-Calculated (O-C) residuals with low SNR. In order to autonomously extract the valid returns, we propose a new algorithm based on randomized Hough transform (RHT). We firstly pre-process the data using histogram method to find the zonal area that contains all the possible signals to reduce large amount of noise. Then the data is processed with RHT algorithm to find the curve that the signal points are distributed on. A new parameter update strategy is introduced in the RHT to get the best parameters. We also analyze the values of the parameters in the algorithm. We test our algorithm on the 10 Hz repetition rate DLR data from Yunnan Observatory and 100 Hz repetition rate DLR data from Graz SLR station. For 10 Hz DLR data with relative larger and similar range gate, we can process it in real time and extract all the signals autonomously with a few false readings. For 100 Hz DLR data with longer observation time, we autonomously post-process DLR data of 0.9%, 2.7%, 8% and 33% return rate with high reliability. The extracted points contain almost all signals and a low percentage of noise. Additional noise is added to 10 Hz DLR data to get lower return rate data. The valid returns can also be well extracted for DLR data with 0.18% and 0.1% return rate.

Modular continuous wavelet processing of biosignals: extracting heart rate and oxygen saturation from a video signal

PubMed Central

2016-01-01

A novel method of extracting heart rate and oxygen saturation from a video-based biosignal is described. The method comprises a novel modular continuous wavelet transform approach which includes: performing the transform, undertaking running wavelet archetyping to enhance the pulse information, extraction of the pulse ridge time–frequency information [and thus a heart rate (HRvid) signal], creation of a wavelet ratio surface, projection of the pulse ridge onto the ratio surface to determine the ratio of ratios from which a saturation trending signal is derived, and calibrating this signal to provide an absolute saturation signal (SvidO2). The method is illustrated through its application to a video photoplethysmogram acquired during a porcine model of acute desaturation. The modular continuous wavelet transform-based approach is advocated by the author as a powerful methodology to deal with noisy, non-stationary biosignals in general. PMID:27382479

Modeling the Pulse Signal by Wave-Shape Function and Analyzing by Synchrosqueezing Transform

PubMed Central

Wang, Chun-Li; Yang, Yueh-Lung; Wu, Wen-Hsiang; Tsai, Tung-Hu; Chang, Hen-Hong

2016-01-01

We apply the recently developed adaptive non-harmonic model based on the wave-shape function, as well as the time-frequency analysis tool called synchrosqueezing transform (SST) to model and analyze oscillatory physiological signals. To demonstrate how the model and algorithm work, we apply them to study the pulse wave signal. By extracting features called the spectral pulse signature, and based on functional regression, we characterize the hemodynamics from the radial pulse wave signals recorded by the sphygmomanometer. Analysis results suggest the potential of the proposed signal processing approach to extract health-related hemodynamics features. PMID:27304979

Modeling the Pulse Signal by Wave-Shape Function and Analyzing by Synchrosqueezing Transform.

PubMed

Wu, Hau-Tieng; Wu, Han-Kuei; Wang, Chun-Li; Yang, Yueh-Lung; Wu, Wen-Hsiang; Tsai, Tung-Hu; Chang, Hen-Hong

2016-01-01

We apply the recently developed adaptive non-harmonic model based on the wave-shape function, as well as the time-frequency analysis tool called synchrosqueezing transform (SST) to model and analyze oscillatory physiological signals. To demonstrate how the model and algorithm work, we apply them to study the pulse wave signal. By extracting features called the spectral pulse signature, and based on functional regression, we characterize the hemodynamics from the radial pulse wave signals recorded by the sphygmomanometer. Analysis results suggest the potential of the proposed signal processing approach to extract health-related hemodynamics features.

Photoplethysmography for blood volumes and oxygenation changes during intermittent vascular occlusions.

PubMed

Abay, T Y; Kyriacou, P A

2018-06-01

Photoplethysmography (PPG) is an optical technique that measures blood volume variations. The main application of dual-wavelength PPG is pulse oximetry, in which the arterial oxygen saturation (SpO[Formula: see text]) is calculated noninvasively. However, the PPG waveform contains other significant physiological information that can be used in conjunction to SpO[Formula: see text] for the assessment of oxygenation and blood volumes changes. This paper investigates the use of near infrared spectroscopy (NIRS) processing techniques for extracting relative concentration changes of oxygenated ([Formula: see text]HbO[Formula: see text]), reduced ([Formula: see text]HHb) and total haemoglobin ([Formula: see text]tHb) from dual-wavelength PPG signals during intermittent pressure-increasing vascular occlusions. A reflectance PPG sensor was attached on the left forearm of nineteen (n = 19) volunteers, along with a reference NIRS sensor positioned on the same forearm, above the left brachioradialis. The investigation protocol consisted of seven intermittent and pressure-increasing vascular occlusions. Relative changes in haemoglobin concentrations were obtained by applying the modified Beer-Lambert law to PPG signals, while oxygenation changes were estimated by the difference between red and infrared attenuations of DC PPGs (A[Formula: see text] = [Formula: see text]A[Formula: see text] - [Formula: see text]A[Formula: see text]) and by the conventional SpO[Formula: see text]. The [Formula: see text]HbO[Formula: see text], [Formula: see text]HHb, [Formula: see text]tHb from the PPG signals indicated significant changes in perfusion induced by either partial and complete occlusions (p < 0.05). The trends in the variables extracted from PPG showed good correlation with the same parameters measured by the reference NIRS monitor. Bland and Altman analysis of agreement between PPG and NIRS showed underestimation of the magnitude of changes by the PPG. A[Formula: see text] indicated significant changes for occlusion pressures exceeding 20 mmHg (p < 0.05) and correlation with tissue oxygenation changes measured by NIRS, while SpO[Formula: see text] had significant changes after 40 mmHg (p < 0.05). Relative changes in haemoglobin concentrations can be estimated from PPG signals and they showed a good level of accuracy in the detection of perfusion and oxygenation changes induced by different degrees of intermittent vascular occlusions. These results can open up to new applications of the PPG waveform in the detection of blood volumes and oxygenation changes.

Non-linear Analysis of Scalp EEG by Using Bispectra: The Effect of the Reference Choice

PubMed Central

Chella, Federico; D'Andrea, Antea; Basti, Alessio; Pizzella, Vittorio; Marzetti, Laura

2017-01-01

Bispectral analysis is a signal processing technique that makes it possible to capture the non-linear and non-Gaussian properties of the EEG signals. It has found various applications in EEG research and clinical practice, including the assessment of anesthetic depth, the identification of epileptic seizures, and more recently, the evaluation of non-linear cross-frequency brain functional connectivity. However, the validity and reliability of the indices drawn from bispectral analysis of EEG signals are potentially biased by the use of a non-neutral EEG reference. The present study aims at investigating the effects of the reference choice on the analysis of the non-linear features of EEG signals through bicoherence, as well as on the estimation of cross-frequency EEG connectivity through two different non-linear measures, i.e., the cross-bicoherence and the antisymmetric cross-bicoherence. To this end, four commonly used reference schemes were considered: the vertex electrode (Cz), the digitally linked mastoids, the average reference, and the Reference Electrode Standardization Technique (REST). The reference effects were assessed both in simulations and in a real EEG experiment. The simulations allowed to investigated: (i) the effects of the electrode density on the performance of the above references in the estimation of bispectral measures; and (ii) the effects of the head model accuracy in the performance of the REST. For real data, the EEG signals recorded from 10 subjects during eyes open resting state were examined, and the distortions induced by the reference choice in the patterns of alpha-beta bicoherence, cross-bicoherence, and antisymmetric cross-bicoherence were assessed. The results showed significant differences in the findings depending on the chosen reference, with the REST providing superior performance than all the other references in approximating the ideal neutral reference. In conclusion, this study highlights the importance of considering the effects of the reference choice in the interpretation and comparison of the results of bispectral analysis of scalp EEG. PMID:28559790

Towards Efficient Decoding of Multiple Classes of Motor Imagery Limb Movements Based on EEG Spectral and Time Domain Descriptors.

PubMed

Samuel, Oluwarotimi Williams; Geng, Yanjuan; Li, Xiangxin; Li, Guanglin

2017-10-28

To control multiple degrees of freedom (MDoF) upper limb prostheses, pattern recognition (PR) of electromyogram (EMG) signals has been successfully applied. This technique requires amputees to provide sufficient EMG signals to decode their limb movement intentions (LMIs). However, amputees with neuromuscular disorder/high level amputation often cannot provide sufficient EMG control signals, and thus the applicability of the EMG-PR technique is limited especially to this category of amputees. As an alternative approach, electroencephalograph (EEG) signals recorded non-invasively from the brain have been utilized to decode the LMIs of humans. However, most of the existing EEG based limb movement decoding methods primarily focus on identifying limited classes of upper limb movements. In addition, investigation on EEG feature extraction methods for the decoding of multiple classes of LMIs has rarely been considered. Therefore, 32 EEG feature extraction methods (including 12 spectral domain descriptors (SDDs) and 20 time domain descriptors (TDDs)) were used to decode multiple classes of motor imagery patterns associated with different upper limb movements based on 64-channel EEG recordings. From the obtained experimental results, the best individual TDD achieved an accuracy of 67.05 ± 3.12% as against 87.03 ± 2.26% for the best SDD. By applying a linear feature combination technique, an optimal set of combined TDDs recorded an average accuracy of 90.68% while that of the SDDs achieved an accuracy of 99.55% which were significantly higher than those of the individual TDD and SDD at p < 0.05. Our findings suggest that optimal feature set combination would yield a relatively high decoding accuracy that may improve the clinical robustness of MDoF neuroprosthesis. The study was approved by the ethics committee of Institutional Review Board of Shenzhen Institutes of Advanced Technology, and the reference number is SIAT-IRB-150515-H0077.

Chemometric analysis for extraction of individual fluorescence spectrum and lifetimes from a target mixture

NASA Technical Reports Server (NTRS)

Hallidy, William H. (Inventor); Chin, Robert C. (Inventor)

1999-01-01

The present invention is a system for chemometric analysis for the extraction of the individual component fluorescence spectra and fluorescence lifetimes from a target mixture. The present invention combines a processor with an apparatus for generating an excitation signal to transmit at a target mixture and an apparatus for detecting the emitted signal from the target mixture. The present invention extracts the individual fluorescence spectrum and fluorescence lifetime measurements from the frequency and wavelength data acquired from the emitted signal. The present invention uses an iterative solution that first requires the initialization of several decision variables and the initial approximation determinations of intermediate matrices. The iterative solution compares the decision variables for convergence to see if further approximation determinations are necessary. If the solution converges, the present invention then determines the reduced best fit error for the analysis of the individual fluorescence lifetime and the fluorescence spectrum before extracting the individual fluorescence lifetime and fluorescence spectrum from the emitted signal of the target mixture.

Assessing similarity analysis of chromatographic fingerprints of Cyclopia subternata extracts as potential screening tool for in vitro glucose utilisation.

PubMed

Schulze, Alexandra E; De Beer, Dalene; Mazibuko, Sithandiwe E; Muller, Christo J F; Roux, Candice; Willenburg, Elize L; Nyunaï, Nyemb; Louw, Johan; Manley, Marena; Joubert, Elizabeth

2016-01-01

Similarity analysis of the phenolic fingerprints of a large number of aqueous extracts of Cyclopia subternata, obtained by high-performance liquid chromatography (HPLC), was evaluated as a potential tool to screen extracts for relative bioactivity. The assessment was based on the (dis)similarity of their fingerprints to that of a reference active extract of C. subternata, proven to enhance glucose uptake in vitro and in vivo. In vitro testing of extracts, selected as being most similar (n = 5; r ≥ 0.962) and most dissimilar (n = 5; r ≤ 0.688) to the reference active extract, showed that no clear pattern in terms of relative glucose uptake efficacy in C2C12 myocytes emerged, irrespective of the dose. Some of the most dissimilar extracts had higher glucose-lowering activity than the reference active extract. Principal component analysis revealed the major compounds responsible for the most variation within the chromatographic fingerprints, as mangiferin, isomangiferin, iriflophenone-3-C-β-D-glucoside-4-O-β-D-glucoside, iriflophenone-3-C-β-D-glucoside, scolymoside, and phloretin-3',5'-di-C-β-D-glucoside. Quantitative analysis of the selected extracts showed that the most dissimilar extracts contained the highest mangiferin and isomangiferin levels, whilst the most similar extracts had the highest scolymoside content. These compounds demonstrated similar glucose uptake efficacy in C2C12 myocytes. It can be concluded that (dis)similarity of chromatographic fingerprints of extracts of unknown activity to that of a proven bioactive extract does not necessarily translate to lower or higher bioactivity.

Speech-Message Extraction from Interference Introduced by External Distributed Sources

NASA Astrophysics Data System (ADS)

Kanakov, V. A.; Mironov, N. A.

2017-08-01

The problem of this study involves the extraction of a speech signal originating from a certain spatial point and calculation of the intelligibility of the extracted voice message. It is solved by the method of decreasing the influence of interference from the speech-message sources on the extracted signal. This method is based on introducing the time delays, which depend on the spatial coordinates, to the recording channels. Audio records of the voices of eight different people were used as test objects during the studies. It is proved that an increase in the number of microphones improves intelligibility of the speech message which is extracted from interference.

Validation assessment of shoreline extraction on medium resolution satellite image

NASA Astrophysics Data System (ADS)

Manaf, Syaifulnizam Abd; Mustapha, Norwati; Sulaiman, Md Nasir; Husin, Nor Azura; Shafri, Helmi Zulhaidi Mohd

2017-10-01

Monitoring coastal zones helps provide information about the conditions of the coastal zones, such as erosion or accretion. Moreover, monitoring the shorelines can help measure the severity of such conditions. Such measurement can be performed accurately by using Earth observation satellite images rather than by using traditional ground survey. To date, shorelines can be extracted from satellite images with a high degree of accuracy by using satellite image classification techniques based on machine learning to identify the land and water classes of the shorelines. In this study, the researchers validated the results of extracted shorelines of 11 classifiers using a reference shoreline provided by the local authority. Specifically, the validation assessment was performed to examine the difference between the extracted shorelines and the reference shorelines. The research findings showed that the SVM Linear was the most effective image classification technique, as evidenced from the lowest mean distance between the extracted shoreline and the reference shoreline. Furthermore, the findings showed that the accuracy of the extracted shoreline was not directly proportional to the accuracy of the image classification.

Species-specific susceptibility to cannabis-induced convulsions.

PubMed

Whalley, Benjamin J; Lin, Hong; Bell, Lynne; Hill, Thomas; Patel, Amesha; Gray, Roy A; Elizabeth Roberts, C; Devinsky, Orrin; Bazelot, Michael; Williams, Claire M; Stephens, Gary J

2018-02-19

Numerous claims are made for cannabis' therapeutic utility upon human seizures, but concerns persist about risks. A potential confounder is the presence of both Δ 9 -tetrahydrocannabinol (THC), variously reported to be pro- and anticonvulsant, and cannabidiol (CBD), widely confirmed as anticonvulsant. Therefore, we investigated effects of prolonged exposure to different THC/CBD cannabis extracts on seizure activity and associated measures of endocannabinoid (eCB) system signalling. Cannabis extract effects on in vivo neurological and behavioural responses, and on bioanalyte levels, were measured in rats and dogs. Extract effects on seizure activity were measured using electroencephalography telemetry in rats. eCB signalling was also investigated using radioligand binding in cannabis extract-treated rats and treatment-naïve rat, mouse, chicken, dog and human tissue. Prolonged exposure to cannabis extracts caused spontaneous, generalized seizures, subserved by epileptiform discharges in rats, but not dogs, and produced higher THC, but lower 11-hydroxy-THC (11-OH-THC) and CBD, plasma concentrations in rats versus dogs. In the same rats, prolonged exposure to cannabis also impaired cannabinoid type 1 receptor (CB 1 receptor)-mediated signalling. Profiling CB 1 receptor expression, basal activity, extent of activation and sensitivity to THC suggested interspecies differences in eCB signalling, being more pronounced in a species that exhibited cannabis extract-induced seizures (rat) than one that did not (dog). Sustained cannabis extract treatment caused differential seizure, behavioural and bioanalyte levels between rats and dogs. Supporting radioligand binding data suggest species differences in eCB signalling. Interspecies variations may have important implications for predicting cannabis-induced convulsions from animal models. © 2018 The Authors. British Journal of Pharmacology published by John Wiley & Sons Ltd on behalf of British Pharmacological Society.

A new fast and fully automated software based algorithm for extracting respiratory signal from raw PET data and its comparison to other methods.

PubMed

Kesner, Adam Leon; Kuntner, Claudia

2010-10-01

Respiratory gating in PET is an approach used to minimize the negative effects of respiratory motion on spatial resolution. It is based on an initial determination of a patient's respiratory movements during a scan, typically using hardware based systems. In recent years, several fully automated databased algorithms have been presented for extracting a respiratory signal directly from PET data, providing a very practical strategy for implementing gating in the clinic. In this work, a new method is presented for extracting a respiratory signal from raw PET sinogram data and compared to previously presented automated techniques. The acquisition of respiratory signal from PET data in the newly proposed method is based on rebinning the sinogram data into smaller data structures and then analyzing the time activity behavior in the elements of these structures. From this analysis, a 1D respiratory trace is produced, analogous to a hardware derived respiratory trace. To assess the accuracy of this fully automated method, respiratory signal was extracted from a collection of 22 clinical FDG-PET scans using this method, and compared to signal derived from several other software based methods as well as a signal derived from a hardware system. The method presented required approximately 9 min of processing time for each 10 min scan (using a single 2.67 GHz processor), which in theory can be accomplished while the scan is being acquired and therefore allowing a real-time respiratory signal acquisition. Using the mean correlation between the software based and hardware based respiratory traces, the optimal parameters were determined for the presented algorithm. The mean/median/range of correlations for the set of scans when using the optimal parameters was found to be 0.58/0.68/0.07-0.86. The speed of this method was within the range of real-time while the accuracy surpassed the most accurate of the previously presented algorithms. PET data inherently contains information about patient motion; information that is not currently being utilized. We have shown that a respiratory signal can be extracted from raw PET data in potentially real-time and in a fully automated manner. This signal correlates well with hardware based signal for a large percentage of scans, and avoids the efforts and complications associated with hardware. The proposed method to extract a respiratory signal can be implemented on existing scanners and, if properly integrated, can be applied without changes to routine clinical procedures.

Comparison of various extraction techniques for the determination of polycyclic aromatic hydrocarbons in worms.

PubMed

Mooibroek, D; Hoogerbrugge, R; Stoffelsen, B H G; Dijkman, E; Berkhoff, C J; Hogendoorn, E A

2002-10-25

Two less laborious extraction methods, viz. (i) a simplified liquid extraction using light petroleum or (ii) microwave-assisted solvent extraction (MASE), for the analysis of polycyclic aromatic hydrocarbons (PAHs) in samples of the compost worm Eisenia andrei, were compared with a reference method. After extraction and concentration, analytical methodology consisted of a cleanup of (part) of the extract with high-performance gel permeation chromatography (HPGPC) and instrumental analysis of 15 PAHs with reversed-phase liquid chromatography with fluorescence detection (RPLC-FLD). Comparison of the methods was done by analysing samples with incurred residues (n=15, each method) originating from an experiment in which worms were exposed to a soil contaminated with PAHs. Simultaneously, the performance of the total lipid determination of each method was established. Evaluation of the data by means of principal component analysis (PCA) and analysis of variance (ANOVA) revealed that the performance of the light petroleum method for both the extraction of PAHs (concentration range 1-30 ng/g) and lipid content corresponds very well with the reference method. Compared to the reference method, the MASE method yielded somewhat lower concentrations for the less volatile PAHs, e.g., dibenzo[ah]anthracene and benzo[ghi]perylene and provided a significant higher amount of co-extracted material.

Advanced capability RFID system

DOEpatents

Gilbert, Ronald W.; Steele, Kerry D.; Anderson, Gordon A.

2007-09-25

A radio-frequency transponder device having an antenna circuit configured to receive radio-frequency signals and to return modulated radio-frequency signals via continuous wave backscatter, a modulation circuit coupled to the antenna circuit for generating the modulated radio-frequency signals, and a microprocessor coupled to the antenna circuit and the modulation circuit and configured to receive and extract operating power from the received radio-frequency signals and to monitor inputs on at least one input pin and to generate responsive signals to the modulation circuit for modulating the radio-frequency signals. The microprocessor can be configured to generate output signals on output pins to associated devices for controlling the operation thereof. Electrical energy can be extracted and stored in an optional electrical power storage device.

[Evoked potentials extraction based on cross-talk resistant adaptive noise cancellation].

PubMed

Zeng, Qingning; Li, Ling; Liu, Qinghua; Yao, Dezhong

2004-06-01

As Evoked Potentials are much lower in amplitude with respect to the on-going EEC, many trigger-related signals are needed for common averaging technique to enable the extraction of single-trail evoked potentials (EP). How to acquire EP through fewer evocations is an important research project. This paper proposes a cross-talk resistant adaptive noise cancellation method to extract EP. Together with the use of filtering technique and the common averaging technique, the present method needs much less evocations to acquire EP signals. According to the simulating experiment, it needs only several evocations or even only one evocation to get EP signals in good quality.

Directional dual-tree rational-dilation complex wavelet transform.

PubMed

Serbes, Gorkem; Gulcur, Halil Ozcan; Aydin, Nizamettin

2014-01-01

Dyadic discrete wavelet transform (DWT) has been used successfully in processing signals having non-oscillatory transient behaviour. However, due to the low Q-factor property of their wavelet atoms, the dyadic DWT is less effective in processing oscillatory signals such as embolic signals (ESs). ESs are extracted from quadrature Doppler signals, which are the output of Doppler ultrasound systems. In order to process ESs, firstly, a pre-processing operation known as phase filtering for obtaining directional signals from quadrature Doppler signals must be employed. Only then, wavelet based methods can be applied to these directional signals for further analysis. In this study, a directional dual-tree rational-dilation complex wavelet transform, which can be applied directly to quadrature signals and has the ability of extracting directional information during analysis, is introduced.

Carrier phase synchronization system for improved amplitude modulation and television broadcast reception

DOEpatents

Smith, Stephen F [Loudon, TN; Moore, James A [Powell, TN

2011-02-01

Systems and methods are described for carrier phase synchronization for improved AM and TV broadcast reception. A method includes synchronizing the phase of a carrier frequency of a broadcast signal with the phase of a remote reference frequency. An apparatus includes a receiver to detect the phase of a reference signal; a phase comparator coupled to the reference signal-phase receiver; a voltage controlled oscillator coupled to the phase comparator; and a phase-controlled radio frequency output coupled to the voltage controlled oscillator.

Rotary head type reproducing apparatus

DOEpatents

Takayama, Nobutoshi; Edakubo, Hiroo; Kozuki, Susumu; Takei, Masahiro; Nagasawa, Kenichi

1986-01-01

In an apparatus of the kind arranged to reproduce, with a plurality of rotary heads, an information signal from a record bearing medium having many recording tracks which are parallel to each other with the information signal recorded therein and with a plurality of different pilot signals of different frequencies also recorded one by one, one in each of the recording tracks, a plurality of different reference signals of different frequencies are simultaneously generated. A tracking error is detected by using the different reference signals together with the pilot signals which are included in signals reproduced from the plurality of rotary heads.

A PCA aided cross-covariance scheme for discriminative feature extraction from EEG signals.

PubMed

Zarei, Roozbeh; He, Jing; Siuly, Siuly; Zhang, Yanchun

2017-07-01

Feature extraction of EEG signals plays a significant role in Brain-computer interface (BCI) as it can significantly affect the performance and the computational time of the system. The main aim of the current work is to introduce an innovative algorithm for acquiring reliable discriminating features from EEG signals to improve classification performances and to reduce the time complexity. This study develops a robust feature extraction method combining the principal component analysis (PCA) and the cross-covariance technique (CCOV) for the extraction of discriminatory information from the mental states based on EEG signals in BCI applications. We apply the correlation based variable selection method with the best first search on the extracted features to identify the best feature set for characterizing the distribution of mental state signals. To verify the robustness of the proposed feature extraction method, three machine learning techniques: multilayer perceptron neural networks (MLP), least square support vector machine (LS-SVM), and logistic regression (LR) are employed on the obtained features. The proposed methods are evaluated on two publicly available datasets. Furthermore, we evaluate the performance of the proposed methods by comparing it with some recently reported algorithms. The experimental results show that all three classifiers achieve high performance (above 99% overall classification accuracy) for the proposed feature set. Among these classifiers, the MLP and LS-SVM methods yield the best performance for the obtained feature. The average sensitivity, specificity and classification accuracy for these two classifiers are same, which are 99.32%, 100%, and 99.66%, respectively for the BCI competition dataset IVa and 100%, 100%, and 100%, for the BCI competition dataset IVb. The results also indicate the proposed methods outperform the most recently reported methods by at least 0.25% average accuracy improvement in dataset IVa. The execution time results show that the proposed method has less time complexity after feature selection. The proposed feature extraction method is very effective for getting representatives information from mental states EEG signals in BCI applications and reducing the computational complexity of classifiers by reducing the number of extracted features. Copyright © 2017 Elsevier B.V. All rights reserved.

Methods for automatically analyzing humpback song units.

PubMed

Rickwood, Peter; Taylor, Andrew

2008-03-01

This paper presents mathematical techniques for automatically extracting and analyzing bioacoustic signals. Automatic techniques are described for isolation of target signals from background noise, extraction of features from target signals and unsupervised classification (clustering) of the target signals based on these features. The only user-provided inputs, other than raw sound, is an initial set of signal processing and control parameters. Of particular note is that the number of signal categories is determined automatically. The techniques, applied to hydrophone recordings of humpback whales (Megaptera novaeangliae), produce promising initial results, suggesting that they may be of use in automated analysis of not only humpbacks, but possibly also in other bioacoustic settings where automated analysis is desirable.

Spectral Regression Based Fault Feature Extraction for Bearing Accelerometer Sensor Signals

PubMed Central

Xia, Zhanguo; Xia, Shixiong; Wan, Ling; Cai, Shiyu

2012-01-01

Bearings are not only the most important element but also a common source of failures in rotary machinery. Bearing fault prognosis technology has been receiving more and more attention recently, in particular because it plays an increasingly important role in avoiding the occurrence of accidents. Therein, fault feature extraction (FFE) of bearing accelerometer sensor signals is essential to highlight representative features of bearing conditions for machinery fault diagnosis and prognosis. This paper proposes a spectral regression (SR)-based approach for fault feature extraction from original features including time, frequency and time-frequency domain features of bearing accelerometer sensor signals. SR is a novel regression framework for efficient regularized subspace learning and feature extraction technology, and it uses the least squares method to obtain the best projection direction, rather than computing the density matrix of features, so it also has the advantage in dimensionality reduction. The effectiveness of the SR-based method is validated experimentally by applying the acquired vibration signals data to bearings. The experimental results indicate that SR can reduce the computation cost and preserve more structure information about different bearing faults and severities, and it is demonstrated that the proposed feature extraction scheme has an advantage over other similar approaches. PMID:23202017

Deep Learning Methods for Underwater Target Feature Extraction and Recognition

PubMed Central

Peng, Yuan; Qiu, Mengran; Shi, Jianfei; Liu, Liangliang

2018-01-01

The classification and recognition technology of underwater acoustic signal were always an important research content in the field of underwater acoustic signal processing. Currently, wavelet transform, Hilbert-Huang transform, and Mel frequency cepstral coefficients are used as a method of underwater acoustic signal feature extraction. In this paper, a method for feature extraction and identification of underwater noise data based on CNN and ELM is proposed. An automatic feature extraction method of underwater acoustic signals is proposed using depth convolution network. An underwater target recognition classifier is based on extreme learning machine. Although convolution neural networks can execute both feature extraction and classification, their function mainly relies on a full connection layer, which is trained by gradient descent-based; the generalization ability is limited and suboptimal, so an extreme learning machine (ELM) was used in classification stage. Firstly, CNN learns deep and robust features, followed by the removing of the fully connected layers. Then ELM fed with the CNN features is used as the classifier to conduct an excellent classification. Experiments on the actual data set of civil ships obtained 93.04% recognition rate; compared to the traditional Mel frequency cepstral coefficients and Hilbert-Huang feature, recognition rate greatly improved. PMID:29780407

Analyzing and Understanding Lipids of Yeast: A Challenging Endeavor.

PubMed

Kohlwein, Sepp D

2017-05-01

Lipids are essential biomolecules with diverse biological functions, ranging from building blocks for all biological membranes to energy substrates, signaling molecules, and protein modifiers. Despite advances in lipid analytics by mass spectrometry, the extraction and quantitative analysis of the diverse classes of lipids are still an experimental challenge. Yeast is a model organism that provides several advantages for studying lipid metabolism, because most biosynthetic pathways are well described and a great deal of information is available on the regulatory mechanisms that control lipid homeostasis. In addition, the composition of yeast lipids is much less complex than that of mammalian lipids, making yeast an excellent reference system for studying lipid-associated cell functions. © 2017 Cold Spring Harbor Laboratory Press.

Computational multiheterodyne spectroscopy

PubMed Central

Burghoff, David; Yang, Yang; Hu, Qing

2016-01-01

Dual-comb spectroscopy allows for high-resolution spectra to be measured over broad bandwidths, but an essential requirement for coherent integration is the availability of a phase reference. Usually, this means that the combs’ phase and timing errors must be measured and either minimized by stabilization or removed by correction, limiting the technique’s applicability. We demonstrate that it is possible to extract the phase and timing signals of a multiheterodyne spectrum completely computationally, without any extra measurements or optical elements. These techniques are viable even when the relative linewidth exceeds the repetition rate difference and can tremendously simplify any dual-comb system. By reconceptualizing frequency combs in terms of the temporal structure of their phase noise, not their frequency stability, we can greatly expand the scope of multiheterodyne techniques. PMID:27847870

System and method for tuning adjusting the central frequency of a laser while maintaining frequency stabilization to an external reference

NASA Technical Reports Server (NTRS)

Livas, Jeffrey (Inventor); Thorpe, James I. (Inventor); Numata, Kenji (Inventor)

2011-01-01

A method and system for stabilizing a laser to a frequency reference with an adjustable offset. The method locks a sideband signal generated by passing an incoming laser beam through the phase modulator to a frequency reference, and adjusts a carrier frequency relative to the locked sideband signal by changing a phase modulation frequency input to the phase modulator. The sideband signal can be a single sideband (SSB), dual sideband (DSB), or an electronic sideband (ESB) signal. Two separate electro-optic modulators can produce the DSB signal. The two electro-optic modulators can be a broadband modulator and a resonant modulator. With a DSB signal, the method can introduce two sinusoidal phase modulations at the phase modulator. With ESB signals, the method can further drive the optical phase modulator with an electrical signal with nominal frequency OMEGA(sub 1) that is phase modulated at a frequency OMEGA(sub 2)

Improved polar display technique of the phase angle of optical interference

NASA Astrophysics Data System (ADS)

Umeda, N.; Shirai, H.; Takasaki, H.

1984-02-01

A technique which displays the fractional order of optical interference by the azimuthal angle of radial arm has been improved by using a digital electronic circuit such as phase-locked loop and D flip-flop. The phase quadrature reference signals of this system are derived by reforming a reference signal and shifting it by a quarter wavelength referring to its waveform. As the result the orthogonal phase relation of the two signals is not affected by the frequency of the signal. This system has been proven to operate properly over the frequency range of 200-600 kHz without readjusting the electric system.

Dual frequency optical carrier technique for transmission of reference frequencies in dispersive media

NASA Technical Reports Server (NTRS)

Maleki, Lutfollah (Inventor)

1993-01-01

Two different carrier frequencies modulated by a reference frequency are transmitted to each receiver to be synchronized therewith. Each receiver responds to local phase differences between the two received signals to correct the phase of one of them so as to maintain the corrected signal as a reliable synchronization reference.

Multi-channel temperature measurement amplification system. [solar heating systems

NASA Technical Reports Server (NTRS)

Currie, J. R. (Inventor)

1981-01-01

A number of differential outputs of thermocouples are sequentially amplified by a common amplifier. The amplified outputs are compared with a reference temperature signal in an offset correction amplifier, and a particularly poled output signal is provided when a differential output is of a discrete level compared with a reference temperature signal.

Optical microphone

DOEpatents

Veligdan, James T.

2000-01-11

An optical microphone includes a laser and beam splitter cooperating therewith for splitting a laser beam into a reference beam and a signal beam. A reflecting sensor receives the signal beam and reflects it in a plurality of reflections through sound pressure waves. A photodetector receives both the reference beam and reflected signal beam for heterodyning thereof to produce an acoustic signal for the sound waves. The sound waves vary the local refractive index in the path of the signal beam which experiences a Doppler frequency shift directly analogous with the sound waves.

An extract of Perilla stem inhibits Src homology phosphatase-1 (SHP)-1 and influences insulin signaling.

PubMed

Peng, Liu; Lei, Zhang; Xiao-na, Xie; Deli, Wang; Jing, Sun; Yong-sen, Wang; Zhi, Wang; Shu, Xing; Jun-feng, Ma; Wan-nan, Li; Xue-qi, Fu

2015-03-01

Protein tyrosine phosphatases (PTPs) are enzymes that catalyze protein tyrosine dephosphorylation of which Src homology phosphatase-1 (SHP-1) is one of the best-validated, a widely distributed intracellular tyrosine phosphatase that contains two SH2 domains. Down regulation of SHP-1 tyrosine phosphatases was significantly increased sensitivity to insulin in insulin signaling pathway. Through in vitro enzymatic reaction kinetics experiment, we found that the extract of Perilla stem was a potential inhibitor to δSHP-1, the catalytic domain of SHP-1 protein tyrosine phosphatase, and its IC(50) was 4ug/ml, and was more sensitive towards SHP-1than other PTPs, which indicated that SHP-1 might be a target of the extract of Perilla stem. It can strengthened the level of tyrosine phosphorylation of insulin receptor (IR) and extracellular signal-regulated protein kinase (ERK) in HepG2 cells, and then activated the insulin signaling pathway through inhibiting the protein phosphorylation of SHP-1. These results demonstrated that the extract of Perilla stem could play an important role for diabetes treatment through inhibiting the level of SHP-1 in insulin signaling pathway.

Improved efficiency of extraction of polycyclic aromatic hydrocarbons (PAHs) from the National Institute of Standards and Technology (NIST) Standard Reference Material Diesel Particulate Matter (SRM 2975) using accelerated solvent extraction.

PubMed

Masala, Silvia; Ahmed, Trifa; Bergvall, Christoffer; Westerholm, Roger

2011-12-01

The efficiency of extraction of polycyclic aromatic hydrocarbons (PAHs) with molecular masses of 252, 276, 278, 300, and 302 Da from standard reference material diesel particulate matter (SRM 2975) has been investigated using accelerated solvent extraction (ASE) with dichloromethane, toluene, methanol, and mixtures of toluene and methanol. Extraction of SRM 2975 using toluene/methanol (9:1, v/v) at maximum instrumental settings (200 °C, 20.7 MPa, and five extraction cycles) with 30-min extraction times resulted in the following elevations of the measured concentration when compared with the certified and reference concentrations reported by the National Institute of Standards and Technology (NIST): benzo[b]fluoranthene, 46%; benzo[k]fluoranthene, 137%; benzo[e]pyrene, 103%; benzo[a]pyrene, 1,570%; perylene, 37%; indeno[1,2,3-cd]pyrene, 41%; benzo[ghi]perylene, 163%; and coronene, 361%. The concentrations of the following PAHs were comparable to the reference values assigned by NIST: indeno[1,2,3-cd]fluoranthene, dibenz[a,h]anthracene, and picene. The measured concentration of dibenzo[a,e]-pyrene was lower than the information value reported by the NIST. The measured concentrations of other highly carcinogenic PAHs (dibenzo[a,l]pyrene, dibenzo[a,i]pyrene, and dibenzo[a,h]pyrene) in SRM 2975 are also reported. Comparison of measurements using the optimized ASE method and using similar conditions to those applied by the NIST for the assignment of PAH concentrations in SRM 2975 indicated that the higher values obtained in the present study were associated with more complete extraction of PAHs from the diesel particulate material. Re-extraction of the particulate samples demonstrated that the deuterated internal standards were more readily recovered than the native PAHs, which may explain the lower values reported by the NIST. The analytical results obtained in the study demonstrated that the efficient extraction of PAHs from SRM 2975 is a critical requirement for the accurate determination of PAHs with high molecular masses in this standard reference material and that the optimization of extraction conditions is essential to avoid underestimation of the PAH concentrations. The requirement is especially relevant to the human carcinogen benzo[a]pyrene, which is commonly used as an indicator of the carcinogenic risk presented by PAH mixtures.

Identification and classification of transient pulses observed in magnetometer array data by time-domain principal component analysis filtering

NASA Astrophysics Data System (ADS)

Kappler, Karl N.; Schneider, Daniel D.; MacLean, Laura S.; Bleier, Thomas E.

2017-08-01

A method for identification of pulsations in time series of magnetic field data which are simultaneously present in multiple channels of data at one or more sensor locations is described. Candidate pulsations of interest are first identified in geomagnetic time series by inspection. Time series of these "training events" are represented in matrix form and transpose-multiplied to generate time-domain covariance matrices. The ranked eigenvectors of this matrix are stored as a feature of the pulsation. In the second stage of the algorithm, a sliding window (approximately the width of the training event) is moved across the vector-valued time-series comprising the channels on which the training event was observed. At each window position, the data covariance matrix and associated eigenvectors are calculated. We compare the orientation of the dominant eigenvectors of the training data to those from the windowed data and flag windows where the dominant eigenvectors directions are similar. This was successful in automatically identifying pulses which share polarization and appear to be from the same source process. We apply the method to a case study of continuously sampled (50 Hz) data from six observatories, each equipped with three-component induction coil magnetometers. We examine a 90-day interval of data associated with a cluster of four observatories located within 50 km of Napa, California, together with two remote reference stations-one 100 km to the north of the cluster and the other 350 km south. When the training data contains signals present in the remote reference observatories, we are reliably able to identify and extract global geomagnetic signals such as solar-generated noise. When training data contains pulsations only observed in the cluster of local observatories, we identify several types of non-plane wave signals having similar polarization.

Application of wavelet analysis to estimation of parameters of the gravitational-wave signal from a coalescing binary

NASA Astrophysics Data System (ADS)

Królak, Andrzej; Trzaskoma, Pawel

1996-05-01

Application of wavelet analysis to the estimation of parameters of the broad-band gravitational-wave signal emitted by a binary system is investigated. A method of instantaneous frequency extraction first proposed in this context by Innocent and Vinet is used. The gravitational-wave signal from a binary is investigated from the point of view of signal analysis theory and it is shown that such a signal is characterized by a large time - bandwidth product. This property enables the extraction of frequency modulation from the wavelet transform of the signal. The wavelet transform of the chirp signal from a binary is calculated analytically. Numerical simulations with the noisy chirp signal are performed. The gravitational-wave signal from a binary is taken in the quadrupole approximation and it is buried in noise corresponding to three different values of the signal-to-noise ratio and the wavelet method to extract the frequency modulation of the signal is applied. Then, from the frequency modulation, the chirp mass parameter of the binary is estimated. It is found that the chirp mass can be estimated to a good accuracy, typically of the order of (20/0264-9381/13/5/006/img5% where 0264-9381/13/5/006/img6 is the optimal signal-to-noise ratio. It is also shown that the post-Newtonian effects in the gravitational wave signal from a binary can be discriminated to a satisfactory accuracy.

Suppressive effects of Lithospermum erythrorhizon extracts on lipopolysaccharide-induced activation of AP-1 and NF-kappaB via mitogen-activated protein kinase pathways in mouse macrophage cells.

PubMed

Han, Kyu Yeon; Kwon, Taek Hwan; Lee, Tae Hoon; Lee, Sung-Joon; Kim, Sung-Hoon; Kim, Jiyoung

2008-04-30

A variety of anti-inflammatory agents have been shown to exert chemopreventive activity via targeting of transcription factors such as NF-kappaB and AP-1. Lithospermum erythrorhizon (LE) has long been used in traditional oriental medicine. In this study, we demonstrated the inhibitory effects of LE extracts on lipopolysaccharide (LPS)-stimulated production of inflammatory cytokines. As an underlying mechanism of inhibition, LE extracts reduced LPS-induced transactivation of AP-1 as well as NF-kappaB in mouse macrophage cells. Electrophoretic mobility shift assays indicated that LE extracts inhibited the DNA binding activities of AP-1 and NF-kappaB. In addition, phosphorylation of IkappaB-alpha protein was suppressed by LE extracts. Moreover, LE extracts inhibited c-Jun N-terminal kinase and extracellular signal-regulated signaling pathways. Our results suggest that the anti-inflammatory activity of LE extracts may be mediated by the inhibition of signal transduction pathways that normally lead to the activation of AP-1and NF-kappaB. These inhibitory effects may be useful for chemoprevention of cancer or other chronic inflammatory diseases.

ESR studies on the thermal decomposition of trimethylamine oxide to formaldehyde and dimethylamine in jumbo squid (Dosidicus gigas) extract.

PubMed

Zhu, Junli; Jia, Jia; Li, Xuepeng; Dong, Liangliang; Li, Jianrong

2013-12-15

The effects of ferrous iron, heating temperature and different additives on the decomposition of trimethylamine oxide (TMAO) to formaldehyde (FA) and dimethylamine (DMA) and generation of free radicals in jumbo squid (Dosidicus gigas) extract during heating were evaluated by electron spin resonance (ESR). The thermal decomposition of TMAO to TMA, DMA and FA and free radical signals was observed in squid extract, whereas no DMA, FA and free radical signals were detected in cod extract or in aqueous TMAO solution in vitro at high temperatures. Significant increase in levels of DMA, FA and radicals intensity were observed in squid extract and TMAO solution in the presence of ferrous iron with increasing temperature. Hydrogen peroxide stimulated the production of DMA, FA and ESR signals in squid extract, while citric acid, trisodium citrate, calcium chloride, tea polyphenols and resveratrol had the opposite effect. Similar ESR spectra of six peaks regarded as amminium radical were detected in the squid extract and TMAO-iron(II) solution, suggesting that the amminium radical was involved in the decomposition of TMAO. Copyright © 2013 Elsevier Ltd. All rights reserved.

A novel signal acquisition platform of human cardiovascular information with noninvasive method

NASA Astrophysics Data System (ADS)

Chen, Longcong; Cai, Shaoxi; Li, Bo; Jiang, Qifeng; Ke, Ming; Zhao, Yi; Chen, Sijia; Zou, Misha

2017-05-01

Cardiovascular diseases (CVDs) are considered the major cause of death worldwide, so more researchers pay more and more attention to the development of a non-invasive method to obtain as much cardiovascular information (CVI) as possible for early screening and diagnosing. It is known that considerable brain information could be probed by a variety of stimuli (such as video, light, and sound). Therefore, it is quite possible that much more CVI could be extracted via giving the human body some special interrelated stimulus. Based on this hypothesis, we designed a novel signal platform to acquire more CVI with a special stimulus, which is to give a gradual decrease and a different settable constant pressure to six air belts placed on two-side brachia, wrists, and ankles, respectively. During the stimulating process, the platform is able to collect 24-channel dynamic signals related with CVI synchronously. Moreover, to improve the measurement accuracy of signal acquisition, a high precision reference chip and a software correction are adopted in this platform. Additionally, we have also shown some collection instances and analysis results in this paper for its reliability. The results suggest that our platform can not only be applied on study in a deep-going way of relationship between collected signals and CVDs but can also serve as the basic tool for developing a new noninvasive cardiovascular function detection instrument and system that can be used both at home and in the hospital.

Design and Implementation of Multi-Input Adaptive Signal Extractions.

DTIC Science & Technology

1982-09-01

deflected gradient) algorithm requiring only N+ l multiplications per adaptation step. Additional quantization is introduced to eliminate all multiplications...noise cancellation for intermittent-signal applications," IEEE Trans. Information Theory, Vol. IT-26. Nov. 1980, pp. 746-750. 1-2 J. Kazakoff and W. A...cancellation," Proc. IEEE, July 1981, Vol. 69, pp. 846-847. *I-10 P. L . Kelly and W. A. Gardner, "Pilot-Directed Adaptive Signal Extraction," Dept. of

Considerations on the Optimal and Efficient Processing of Information-Bearing Signals

ERIC Educational Resources Information Center

Harms, Herbert Andrew

2013-01-01

Noise is a fundamental hurdle that impedes the processing of information-bearing signals, specifically the extraction of salient information. Processing that is both optimal and efficient is desired; optimality ensures the extracted information has the highest fidelity allowed by the noise, while efficiency ensures limited resource usage. Optimal…

Quantitative analysis of the major constituents of St John's wort with HPLC-ESI-MS.

PubMed

Chandrasekera, Dhammitha H; Welham, Kevin J; Ashton, David; Middleton, Richard; Heinrich, Michael

2005-12-01

A method was developed to profile the major constituents of St John's wort extracts using high-performance liquid chromatography-electrospray mass spectrometry (HPLC-ESI-MS). The objective was to simultaneously separate, identify and quantify hyperforin, hypericin, pseudohypericin, rutin, hyperoside, isoquercetrin, quercitrin and chlorogenic acid using HPLC-MS. Quantification was performed using an external standardisation method with reference standards. The method consisted of two protocols: one for the analysis of flavonoids and glycosides and the other for the analysis of the more lipophilic hypericins and hyperforin. Both protocols used a reverse phase Luna phenyl hexyl column. The separation of the flavonoids and glycosides was achieved within 35 min and that of the hypericins and hyperforin within 9 min. The linear response range in ESI-MS was established for each compound and all had linear regression coefficient values greater than 0.97. Both protocols proved to be very specific for the constituents analysed. MS analysis showed no other signals within the analyte peaks. The method was robust and applicable to alcoholic tinctures, tablet/capsule extracts in various solvents and herb extracts. The method was applied to evaluate the phytopharmaceutical quality of St John's wort preparations available in the UK in order to test the method and investigate if they contain at least the main constituents and at what concentrations.

Determination of acrylamide in coffee and chocolate by pressurised fluid extraction and liquid chromatography-tandem mass spectrometry.

PubMed

Pardo, O; Yusà, V; Coscollà, C; León, N; Pastor, A

2007-07-01

A selective and sensitive procedure has been developed and validated for the determination of acrylamide in difficult matrices, such as coffee and chocolate. The proposed method includes pressurised fluid extraction (PFE) with acetonitrile, florisil clean-up purification inside the PFE extraction cell and detection by liquid chromatography (LC) coupled to atmospheric pressure ionisation in positive mode tandem mass spectrometry (APCI-MS-MS). Comparison of ionisation sources (atmospheric pressure chemical ionisation (APCI), atmospheric pressure photoionization (APPI) and the combined APCI/APPI) and clean-up procedures were carried out to improve the analytical signal. The main parameters affecting the performance of the different ionisation sources were previously optimised using statistical design of experiments (DOE). PFE parameters were also optimised by DOE. For quantitation, an isotope dilution approach was used. The limit of quantification (LOQ) of the method was 1 microg kg(-1) for coffee and 0.6 microg kg(-1) for chocolate. Recoveries ranged between 81-105% in coffee and 87-102% in chocolate. The accuracy was evaluated using a coffee reference test material FAPAS T3008. Using the optimised method, 20 coffee and 15 chocolate samples collected from Valencian (Spain) supermarkets, were investigated for acrylamide, yielding median levels of 146 microg kg(-1) in coffee and 102 microg kg(-1) in chocolate.

Recent advances in herbal medicines treating Parkinson's disease.

PubMed

Li, Xu-Zhao; Zhang, Shuai-Nan; Liu, Shu-Min; Lu, Fang

2013-01-01

Herbal medicines have attracted considerable attention in recent years, which are used to treat Parkinson's disease (PD) in China based on traditional Chinese medicine or modern pharmacological theories. We summarized and analyzed the anti-Parkinsonian activities of herbal medicines and herbal formulations investigated in PD models and provide future references for basic and clinical investigations. All the herbal medicines and herbal formulations were tested on PD models in vitro and in vivo. The relevant compounds and herbal extracts with anti-Parkinsonian activities were included and analyzed according to their genera or pharmacological activities. A total of 38 herbal medicines and 11 herbal formulations were analyzed. The relevant compounds, herbal extracts and formulations were reported to be effective on PD models by modulating multiple key events or signaling pathways implicated in the pathogenesis of PD. The plant species of these herbal medicines belong to 24 genera and 18 families, such as Acanthopanax, Alpinia and Astragalus, etc. These herbal medicines can be an alternative and valuable source for anti-Parkinsonian drug discovery. The plant species in these genera and families may be the most promising candidates for further investigation and deserve further consideration in clinical trials. Active components in some of the herbal extracts and the compatibility law of herbal formulations remain to be further investigated. Copyright © 2012 Elsevier B.V. All rights reserved.

Determination of wear metals in engine oil by mild acid digestion and energy dispersive X-ray fluorescence spectrometry using solid phase extraction disks.

PubMed

Yang, Zheng; Hou, Xiandeng; Jones, Bradley T

2003-03-10

A simple, particle size-independent spectrometric method has been developed for the multi-element determination of wear metals in used engine oil. A small aliquot (0.5 ml) of an acid-digested oil sample is spotted onto a C-18 solid phase extraction disk to form a uniform thin film. The dried disk is then analyzed directly by energy dispersive X-ray fluorescence spectrometry. This technique provides a homogeneous and reproducible sample surface to the instrument, thus overcoming the typical problems associated with uneven particle size distribution and sedimentation. As a result, the method provides higher precision and accuracy than conventional methods. Furthermore, the disk sample may be stored and re-analyzed or extracted at a later date. The signals arising from the spotted disks, and the calibration curves constructed from them, are stable for at least 2 months. The limits of detection for Fe, Cu, Zn, Pb, and Cr are 5, 1, 4, 2, and 4 microg g(-1), respectively. Recoveries of these elements from spiked oil samples range from 92 to 110%. The analysis of two standard reference materials and a used oil sample produced results comparable to those found by inductively coupled plasma atomic emission spectrometry.

Drift correction of the dissolved signal in single particle ICPMS.

PubMed

Cornelis, Geert; Rauch, Sebastien

2016-07-01

A method is presented where drift, the random fluctuation of the signal intensity, is compensated for based on the estimation of the drift function by a moving average. It was shown using single particle ICPMS (spICPMS) measurements of 10 and 60 nm Au NPs that drift reduces accuracy of spICPMS analysis at the calibration stage and during calculations of the particle size distribution (PSD), but that the present method can again correct the average signal intensity as well as the signal distribution of particle-containing samples skewed by drift. Moreover, deconvolution, a method that models signal distributions of dissolved signals, fails in some cases when using standards and samples affected by drift, but the present method was shown to improve accuracy again. Relatively high particle signals have to be removed prior to drift correction in this procedure, which was done using a 3 × sigma method, and the signals are treated separately and added again. The method can also correct for flicker noise that increases when signal intensity is increased because of drift. The accuracy was improved in many cases when flicker correction was used, but when accurate results were obtained despite drift, the correction procedures did not reduce accuracy. The procedure may be useful to extract results from experimental runs that would otherwise have to be run again. Graphical Abstract A method is presented where a spICP-MS signal affected by drift (left) is corrected (right) by adjusting the local (moving) averages (green) and standard deviations (purple) to the respective values at a reference time (red). In combination with removing particle events (blue) in the case of calibration standards, this method is shown to obtain particle size distributions where that would otherwise be impossible, even when the deconvolution method is used to discriminate dissolved and particle signals.

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.

Signal extraction and wave field separation in tunnel seismic prediction by independent component analysis

NASA Astrophysics Data System (ADS)

Yue, Y.; Jiang, T.; Zhou, Q.

2017-12-01

In order to ensure the rationality and the safety of tunnel excavation, the advanced geological prediction has been become an indispensable step in tunneling. However, the extraction of signal and the separation of P and S waves directly influence the accuracy of geological prediction. Generally, the raw data collected in TSP system is low quality because of the numerous disturb factors in tunnel projects, such as the power interference and machine vibration interference. It's difficult for traditional method (band-pass filtering) to remove interference effectively as well as bring little loss to signal. The power interference, machine vibration interference and the signal are original variables and x, y, z component as observation signals, each component of the representation is a linear combination of the original variables, which satisfy applicable conditions of independent component analysis (ICA). We perform finite-difference simulations of elastic wave propagation to synthetic a tunnel seismic reflection record. The method of ICA was adopted to process the three-component data, and the results show that extract the estimates of signal and the signals are highly correlated (the coefficient correlation is up to more than 0.93). In addition, the estimates of interference that separated from ICA and the interference signals are also highly correlated, and the coefficient correlation is up to more than 0.99. Thus, simulation results showed that the ICA is an ideal method for extracting high quality data from mixed signals. For the separation of P and S waves, the conventional separation techniques are based on physical characteristics of wave propagation, which require knowledge of the near-surface P and S waves velocities and density. Whereas the ICA approach is entirely based on statistical differences between P and S waves, and the statistical technique does not require a priori information. The concrete results of the wave field separation will be presented in the meeting. In summary, we can safely draw the conclusion that ICA can not only extract high quality data from the mixed signals, but also can separate P and S waves effectively.

Weak Fault Feature Extraction of Rolling Bearings Based on an Improved Kurtogram

PubMed Central

Chen, Xianglong; Feng, Fuzhou; Zhang, Bingzhi

2016-01-01

Kurtograms have been verified to be an efficient tool in bearing fault detection and diagnosis because of their superiority in extracting transient features. However, the short-time Fourier Transform is insufficient in time-frequency analysis and kurtosis is deficient in detecting cyclic transients. Those factors weaken the performance of the original kurtogram in extracting weak fault features. Correlated Kurtosis (CK) is then designed, as a more effective solution, in detecting cyclic transients. Redundant Second Generation Wavelet Packet Transform (RSGWPT) is deemed to be effective in capturing more detailed local time-frequency description of the signal, and restricting the frequency aliasing components of the analysis results. The authors in this manuscript, combining the CK with the RSGWPT, propose an improved kurtogram to extract weak fault features from bearing vibration signals. The analysis of simulation signals and real application cases demonstrate that the proposed method is relatively more accurate and effective in extracting weak fault features. PMID:27649171

Motor unit action potential conduction velocity estimated from surface electromyographic signals using image processing techniques.

PubMed

Soares, Fabiano Araujo; Carvalho, João Luiz Azevedo; Miosso, Cristiano Jacques; de Andrade, Marcelino Monteiro; da Rocha, Adson Ferreira

2015-09-17

In surface electromyography (surface EMG, or S-EMG), conduction velocity (CV) refers to the velocity at which the motor unit action potentials (MUAPs) propagate along the muscle fibers, during contractions. The CV is related to the type and diameter of the muscle fibers, ion concentration, pH, and firing rate of the motor units (MUs). The CV can be used in the evaluation of contractile properties of MUs, and of muscle fatigue. The most popular methods for CV estimation are those based on maximum likelihood estimation (MLE). This work proposes an algorithm for estimating CV from S-EMG signals, using digital image processing techniques. The proposed approach is demonstrated and evaluated, using both simulated and experimentally-acquired multichannel S-EMG signals. We show that the proposed algorithm is as precise and accurate as the MLE method in typical conditions of noise and CV. The proposed method is not susceptible to errors associated with MUAP propagation direction or inadequate initialization parameters, which are common with the MLE algorithm. Image processing -based approaches may be useful in S-EMG analysis to extract different physiological parameters from multichannel S-EMG signals. Other new methods based on image processing could also be developed to help solving other tasks in EMG analysis, such as estimation of the CV for individual MUs, localization and tracking of innervation zones, and study of MU recruitment strategies.

Multi-Scale Morphological Analysis of Conductance Signals in Vertical Upward Gas-Liquid Two-Phase Flow

NASA Astrophysics Data System (ADS)

Lian, Enyang; Ren, Yingyu; Han, Yunfeng; Liu, Weixin; Jin, Ningde; Zhao, Junying

2016-11-01

The multi-scale analysis is an important method for detecting nonlinear systems. In this study, we carry out experiments and measure the fluctuation signals from a rotating electric field conductance sensor with eight electrodes. We first use a recurrence plot to recognise flow patterns in vertical upward gas-liquid two-phase pipe flow from measured signals. Then we apply a multi-scale morphological analysis based on the first-order difference scatter plot to investigate the signals captured from the vertical upward gas-liquid two-phase flow loop test. We find that the invariant scaling exponent extracted from the multi-scale first-order difference scatter plot with the bisector of the second-fourth quadrant as the reference line is sensitive to the inhomogeneous distribution characteristics of the flow structure, and the variation trend of the exponent is helpful to understand the process of breakup and coalescence of the gas phase. In addition, we explore the dynamic mechanism influencing the inhomogeneous distribution of the gas phase in terms of adaptive optimal kernel time-frequency representation. The research indicates that the system energy is a factor influencing the distribution of the gas phase and the multi-scale morphological analysis based on the first-order difference scatter plot is an effective method for indicating the inhomogeneous distribution of the gas phase in gas-liquid two-phase flow.

Intelligent measurement and compensation of linear motor force ripple: a projection-based learning approach in the presence of noise

NASA Astrophysics Data System (ADS)

Liu, Yang; Song, Fazhi; Yang, Xiaofeng; Dong, Yue; Tan, Jiubin

2018-06-01

Due to their structural simplicity, linear motors are increasingly receiving attention for use in high velocity and high precision applications. The force ripple, as a space-periodic disturbance, however, would deteriorate the achievable dynamic performance. Conventional force ripple measurement approaches are time-consuming and have high requirements on the experimental conditions. In this paper, a novel learning identification algorithm is proposed for force ripple intelligent measurement and compensation. Existing identification schemes always use all the error signals to update the parameters in the force ripple. However, the error induced by noise is non-effective for force ripple identification, and even deteriorates the identification process. In this paper only the most pertinent information in the error signal is utilized for force ripple identification. Firstly, the effective error signals caused by the reference trajectory and the force ripple are extracted by projecting the overall error signals onto a subspace spanned by the physical model of the linear motor as well as the sinusoidal model of the force ripple. The time delay in the linear motor is compensated in the basis functions. Then, a data-driven approach is proposed to design the learning gain. It balances the trade-off between convergence speed and robustness against noise. Simulation and experimental results validate the proposed method and confirm its effectiveness and superiority.

An Adaptive S-Method to Analyze Micro-Doppler Signals for Human Activity Classification

PubMed Central

Yang, Chao; Xia, Yuqing; Ma, Xiaolin; Zhang, Tao; Zhou, Zhou

2017-01-01

In this paper, we propose the multiwindow Adaptive S-method (AS-method) distribution approach used in the time-frequency analysis for radar signals. Based on the results of orthogonal Hermite functions that have good time-frequency resolution, we vary the length of window to suppress the oscillating component caused by cross-terms. This method can bring a better compromise in the auto-terms concentration and cross-terms suppressing, which contributes to the multi-component signal separation. Finally, the effective micro signal is extracted by threshold segmentation and envelope extraction. To verify the proposed method, six states of motion are separated by a classifier of a support vector machine (SVM) trained to the extracted features. The trained SVM can detect a human subject with an accuracy of 95.4% for two cases without interference. PMID:29186075

An Adaptive S-Method to Analyze Micro-Doppler Signals for Human Activity Classification.

PubMed

Li, Fangmin; Yang, Chao; Xia, Yuqing; Ma, Xiaolin; Zhang, Tao; Zhou, Zhou

2017-11-29

In this paper, we propose the multiwindow Adaptive S-method (AS-method) distribution approach used in the time-frequency analysis for radar signals. Based on the results of orthogonal Hermite functions that have good time-frequency resolution, we vary the length of window to suppress the oscillating component caused by cross-terms. This method can bring a better compromise in the auto-terms concentration and cross-terms suppressing, which contributes to the multi-component signal separation. Finally, the effective micro signal is extracted by threshold segmentation and envelope extraction. To verify the proposed method, six states of motion are separated by a classifier of a support vector machine (SVM) trained to the extracted features. The trained SVM can detect a human subject with an accuracy of 95.4% for two cases without interference.

Velocity-image model for online signature verification.

PubMed

Khan, Mohammad A U; Niazi, Muhammad Khalid Khan; Khan, Muhammad Aurangzeb

2006-11-01

In general, online signature capturing devices provide outputs in the form of shape and velocity signals. In the past, strokes have been extracted while tracking velocity signal minimas. However, the resulting strokes are larger and complicated in shape and thus make the subsequent job of generating a discriminative template difficult. We propose a new stroke-based algorithm that splits velocity signal into various bands. Based on these bands, strokes are extracted which are smaller and more simpler in nature. Training of our proposed system revealed that low- and high-velocity bands of the signal are unstable, whereas the medium-velocity band can be used for discrimination purposes. Euclidean distances of strokes extracted on the basis of medium velocity band are used for verification purpose. The experiments conducted show improvement in discriminative capability of the proposed stroke-based system.

A new organic-rich soil reference material certified for its EDTA- and acetic acid- extractable contents of Cd, Cr, Cu, Ni, Pb and Zn, following collaboratively tested and harmonised procedures.

PubMed

Pueyo, M; Rauret, G; Bacon, J R; Gomez, A; Muntau, H; Quevauviller, P; López-Sánchez, J F

2001-02-01

There is an increasing requirement for assessment of the bioavailable metal fraction and the mobility of trace elements in soils upon disposal. One of the approaches is the use of leaching procedures, but the results obtained are operationally defined; therefore, their significance is highly dependent on the extraction protocol performed. So, for this type of study, there is a need for reference materials that allow the quality of measurements to be controlled. This paper describes the steps involved in the certification of an organic-rich soil reference material, BCR-700, for the EDTA- and acetic acid-extractable contents of some trace elements, following collaboratively tested and harmonised extraction procedures. Details are given for the preparation of the soil, homogeneity and stability testing, analytical procedures and the statistical selection of data to be included in the certification.

Enabling Low-Power, Multi-Modal Neural Interfaces Through a Common, Low-Bandwidth Feature Space.

PubMed

Irwin, Zachary T; Thompson, David E; Schroeder, Karen E; Tat, Derek M; Hassani, Ali; Bullard, Autumn J; Woo, Shoshana L; Urbanchek, Melanie G; Sachs, Adam J; Cederna, Paul S; Stacey, William C; Patil, Parag G; Chestek, Cynthia A

2016-05-01

Brain-Machine Interfaces (BMIs) have shown great potential for generating prosthetic control signals. Translating BMIs into the clinic requires fully implantable, wireless systems; however, current solutions have high power requirements which limit their usability. Lowering this power consumption typically limits the system to a single neural modality, or signal type, and thus to a relatively small clinical market. Here, we address both of these issues by investigating the use of signal power in a single narrow frequency band as a decoding feature for extracting information from electrocorticographic (ECoG), electromyographic (EMG), and intracortical neural data. We have designed and tested the Multi-modal Implantable Neural Interface (MINI), a wireless recording system which extracts and transmits signal power in a single, configurable frequency band. In prerecorded datasets, we used the MINI to explore low frequency signal features and any resulting tradeoff between power savings and decoding performance losses. When processing intracortical data, the MINI achieved a power consumption 89.7% less than a more typical system designed to extract action potential waveforms. When processing ECoG and EMG data, the MINI achieved similar power reductions of 62.7% and 78.8%. At the same time, using the single signal feature extracted by the MINI, we were able to decode all three modalities with less than a 9% drop in accuracy relative to using high-bandwidth, modality-specific signal features. We believe this system architecture can be used to produce a viable, cost-effective, clinical BMI.

Mechanomyographic Parameter Extraction Methods: An Appraisal for Clinical Applications

PubMed Central

Ibitoye, Morufu Olusola; Hamzaid, Nur Azah; Zuniga, Jorge M.; Hasnan, Nazirah; Wahab, Ahmad Khairi Abdul

2014-01-01

The research conducted in the last three decades has collectively demonstrated that the skeletal muscle performance can be alternatively assessed by mechanomyographic signal (MMG) parameters. Indices of muscle performance, not limited to force, power, work, endurance and the related physiological processes underlying muscle activities during contraction have been evaluated in the light of the signal features. As a non-stationary signal that reflects several distinctive patterns of muscle actions, the illustrations obtained from the literature support the reliability of MMG in the analysis of muscles under voluntary and stimulus evoked contractions. An appraisal of the standard practice including the measurement theories of the methods used to extract parameters of the signal is vital to the application of the signal during experimental and clinical practices, especially in areas where electromyograms are contraindicated or have limited application. As we highlight the underpinning technical guidelines and domains where each method is well-suited, the limitations of the methods are also presented to position the state of the art in MMG parameters extraction, thus providing the theoretical framework for improvement on the current practices to widen the opportunity for new insights and discoveries. Since the signal modality has not been widely deployed due partly to the limited information extractable from the signals when compared with other classical techniques used to assess muscle performance, this survey is particularly relevant to the projected future of MMG applications in the realm of musculoskeletal assessments and in the real time detection of muscle activity. PMID:25479326

Extraction of global 21-cm signal from simulated data for the Dark Ages Radio Explorer (DARE) using an MCMC pipeline

NASA Astrophysics Data System (ADS)

Tauscher, Keith A.; Burns, Jack O.; Rapetti, David; Mirocha, Jordan; Monsalve, Raul A.

2017-01-01

The Dark Ages Radio Explorer (DARE) is a mission concept proposed to NASA in which a crossed dipole antenna collects low frequency (40-120 MHz) radio measurements above the farside of the Moon to detect and characterize the global 21-cm signal from the early (z~35-11) Universe's neutral hydrogen. Simulated data for DARE includes: 1) the global signal modeled using the ares code, 2) spectrally smooth Galactic foregrounds with spatial structure taken from multiple radio foreground maps averaged over a large, well characterized beam, 3) systematics introduced in the data by antenna/receiver reflections, and 4) the Moon. This simulated data is fed into a signal extraction pipeline. As the signal is 4-5 orders of magnitude below the Galactic synchrotron contribution, it is best extracted from the data using Bayesian techniques which take full advantage of prior knowledge of the instrument and foregrounds. For the DARE pipeline, we use the affine-invariant MCMC algorithm implemented in the Python package, emcee. The pipeline also employs singular value decomposition to use known spectral features of the antenna and receiver to form a natural basis with which to fit instrumental systematics. Taking advantage of high-fidelity measurements of the antenna beam (to ~20 ppm) and precise calibration of the instrument, the pipeline extracts the global 21-cm signal with an average RMS error of 10-15 mK for multiple signal models.

Non-causal spike filtering improves decoding of movement intention for intracortical BCIs

PubMed Central

Masse, Nicolas Y.; Jarosiewicz, Beata; Simeral, John D.; Bacher, Daniel; Stavisky, Sergey D.; Cash, Sydney S.; Oakley, Erin M.; Berhanu, Etsub; Eskandar, Emad; Friehs, Gerhard; Hochberg, Leigh R.; Donoghue, John P.

2014-01-01

Background Multiple types of neural signals are available for controlling assistive devices through brain-computer interfaces (BCIs). Intracortically-recorded spiking neural signals are attractive for BCIs because they can in principle provide greater fidelity of encoded information compared to electrocorticographic (ECoG) signals and electroencephalograms (EEGs). Recent reports show that the information content of these spiking neural signals can be reliably extracted simply by causally band-pass filtering the recorded extracellular voltage signals and then applying a spike detection threshold, without relying on “sorting” action potentials. New method We show that replacing the causal filter with an equivalent non-causal filter increases the information content extracted from the extracellular spiking signal and improves decoding of intended movement direction. This method can be used for real-time BCI applications by using a 4 ms lag between recording and filtering neural signals. Results Across 18 sessions from two people with tetraplegia enrolled in the BrainGate2 pilot clinical trial, we found that threshold crossing events extracted using this non-causal filtering method were significantly more informative of each participant’s intended cursor kinematics compared to threshold crossing events derived from causally filtered signals. This new method decreased the mean angular error between the intended and decoded cursor direction by 9.7° for participant S3, who was implanted 5.4 years prior to this study, and by 3.5° for participant T2, who was implanted 3 months prior to this study. Conclusions Non-causally filtering neural signals prior to extracting threshold crossing events may be a simple yet effective way to condition intracortically recorded neural activity for direct control of external devices through BCIs. PMID:25128256

Research Resource: A Reference Transcriptome for Constitutive Androstane Receptor and Pregnane X Receptor Xenobiotic Signaling

PubMed Central

Ochsner, Scott A.; Tsimelzon, Anna; Dong, Jianrong; Coarfa, Cristian

2016-01-01

The pregnane X receptor (PXR) (PXR/NR1I3) and constitutive androstane receptor (CAR) (CAR/NR1I2) members of the nuclear receptor (NR) superfamily of ligand-regulated transcription factors are well-characterized mediators of xenobiotic and endocrine-disrupting chemical signaling. The Nuclear Receptor Signaling Atlas maintains a growing library of transcriptomic datasets involving perturbations of NR signaling pathways, many of which involve perturbations relevant to PXR and CAR xenobiotic signaling. Here, we generated a reference transcriptome based on the frequency of differential expression of genes across 159 experiments compiled from 22 datasets involving perturbations of CAR and PXR signaling pathways. In addition to the anticipated overrepresentation in the reference transcriptome of genes encoding components of the xenobiotic stress response, the ranking of genes involved in carbohydrate metabolism and gonadotropin action sheds mechanistic light on the suspected role of xenobiotics in metabolic syndrome and reproductive disorders. Gene Set Enrichment Analysis showed that although acetaminophen, chlorpromazine, and phenobarbital impacted many similar gene sets, differences in direction of regulation were evident in a variety of processes. Strikingly, gene sets representing genes linked to Parkinson's, Huntington's, and Alzheimer's diseases were enriched in all 3 transcriptomes. The reference xenobiotic transcriptome will be supplemented with additional future datasets to provide the community with a continually updated reference transcriptomic dataset for CAR- and PXR-mediated xenobiotic signaling. Our study demonstrates how aggregating and annotating transcriptomic datasets, and making them available for routine data mining, facilitates research into the mechanisms by which xenobiotics and endocrine-disrupting chemicals subvert conventional NR signaling modalities. PMID:27409825

Research Resource: A Reference Transcriptome for Constitutive Androstane Receptor and Pregnane X Receptor Xenobiotic Signaling.

PubMed

Ochsner, Scott A; Tsimelzon, Anna; Dong, Jianrong; Coarfa, Cristian; McKenna, Neil J

2016-08-01

The pregnane X receptor (PXR) (PXR/NR1I3) and constitutive androstane receptor (CAR) (CAR/NR1I2) members of the nuclear receptor (NR) superfamily of ligand-regulated transcription factors are well-characterized mediators of xenobiotic and endocrine-disrupting chemical signaling. The Nuclear Receptor Signaling Atlas maintains a growing library of transcriptomic datasets involving perturbations of NR signaling pathways, many of which involve perturbations relevant to PXR and CAR xenobiotic signaling. Here, we generated a reference transcriptome based on the frequency of differential expression of genes across 159 experiments compiled from 22 datasets involving perturbations of CAR and PXR signaling pathways. In addition to the anticipated overrepresentation in the reference transcriptome of genes encoding components of the xenobiotic stress response, the ranking of genes involved in carbohydrate metabolism and gonadotropin action sheds mechanistic light on the suspected role of xenobiotics in metabolic syndrome and reproductive disorders. Gene Set Enrichment Analysis showed that although acetaminophen, chlorpromazine, and phenobarbital impacted many similar gene sets, differences in direction of regulation were evident in a variety of processes. Strikingly, gene sets representing genes linked to Parkinson's, Huntington's, and Alzheimer's diseases were enriched in all 3 transcriptomes. The reference xenobiotic transcriptome will be supplemented with additional future datasets to provide the community with a continually updated reference transcriptomic dataset for CAR- and PXR-mediated xenobiotic signaling. Our study demonstrates how aggregating and annotating transcriptomic datasets, and making them available for routine data mining, facilitates research into the mechanisms by which xenobiotics and endocrine-disrupting chemicals subvert conventional NR signaling modalities.

Fetal Electrocardiogram Extraction and Analysis Using Adaptive Noise Cancellation and Wavelet Transformation Techniques.

PubMed

Sutha, P; Jayanthi, V E

2017-12-08

Birth defect-related demise is mainly due to congenital heart defects. In the earlier stage of pregnancy, fetus problem can be identified by finding information about the fetus to avoid stillbirths. The gold standard used to monitor the health status of the fetus is by Cardiotachography(CTG), cannot be used for long durations and continuous monitoring. There is a need for continuous and long duration monitoring of fetal ECG signals to study the progressive health status of the fetus using portable devices. The non-invasive method of electrocardiogram recording is one of the best method used to diagnose fetal cardiac problem rather than the invasive methods.The monitoring of the fECG requires development of a miniaturized hardware and a efficient signal processing algorithms to extract the fECG embedded in the mother ECG. The paper discusses a prototype hardware developed to monitor and record the raw mother ECG signal containing the fECG and a signal processing algorithm to extract the fetal Electro Cardiogram signal. We have proposed two methods of signal processing, first is based on the Least Mean Square (LMS) Adaptive Noise Cancellation technique and the other method is based on the Wavelet Transformation technique. A prototype hardware was designed and developed to acquire the raw ECG signal containing the mother and fetal ECG and the signal processing techniques were used to eliminate the noises and extract the fetal ECG and the fetal Heart Rate Variability was studied. Both the methods were evaluated with the signal acquired from a fetal ECG simulator, from the Physionet database and that acquired from the subject. Both the methods are evaluated by finding heart rate and its variability, amplitude spectrum and mean value of extracted fetal ECG. Also the accuracy, sensitivity and positive predictive value are also determined for fetal QRS detection technique. In this paper adaptive filtering technique uses Sign-sign LMS algorithm and wavelet techniques with Daubechies wavelet, employed along with de noising techniques for the extraction of fetal Electrocardiogram.Both the methods are having good sensitivity and accuracy. In adaptive method the sensitivity is 96.83, accuracy 89.87, wavelet sensitivity is 95.97 and accuracy is 88.5. Additionally, time domain parameters from the plot of heart rate variability of mother and fetus are analyzed.

Noise cancellation in magnetoencephalography and electroencephalography with isolated reference sensors

DOEpatents

Kraus, Jr., Robert H.; Espy, Michelle A.; Matlachov, Andrei; Volegov, Petr

2010-06-01

An apparatus measures electromagnetic signals from a weak signal source. A plurality of primary sensors is placed in functional proximity to the weak signal source with an electromagnetic field isolation surface arranged adjacent the primary sensors and between the weak signal source and sources of ambient noise. A plurality of reference sensors is placed adjacent the electromagnetic field isolation surface and arranged between the electromagnetic isolation surface and sources of ambient noise.

Scram signal generator

DOEpatents

Johanson, Edward W.; Simms, Richard

1981-01-01

A scram signal generating circuit for nuclear reactor installations monitors a flow signal representing the flow rate of the liquid sodium coolant which is circulated through the reactor, and initiates reactor shutdown for a rapid variation in the flow signal, indicative of fuel motion. The scram signal generating circuit includes a long-term drift compensation circuit which processes the flow signal and generates an output signal representing the flow rate of the coolant. The output signal remains substantially unchanged for small variations in the flow signal, attributable to long term drift in the flow rate, but a rapid change in the flow signal, indicative of a fast flow variation, causes a corresponding change in the output signal. A comparator circuit compares the output signal with a reference signal, representing a given percentage of the steady state flow rate of the coolant, and generates a scram signal to initiate reactor shutdown when the output signal equals the reference signal.

Scram signal generator

DOEpatents

Johanson, E.W.; Simms, R.

A scram signal generating circuit for nuclear reactor installations monitors a flow signal representing the flow rate of the liquid sodium coolant which is circulated through the reactor, and initiates reactor shutdown for a rapid variation in the flow signal, indicative of fuel motion. The scram signal generating circuit includes a long-term drift compensation circuit which processes the flow signal and generates an output signal representing the flow rate of the coolant. The output signal remains substantially unchanged for small variations in the flow signal, attributable to long term drift in the flow rate, but a rapid change in the flow signal, indicative of a fast flow variation, causes a corresponding change in the output signal. A comparator circuit compares the output signal with a reference signal, representing a given percentage of the steady state flow rate of the coolant, and generates a scram signal to initiate reactor shutdown when the output signal equals the reference signal.

Distributing Frequency And Time Signals On Optical Fibers

NASA Technical Reports Server (NTRS)

Lutes, George F.

1993-01-01

Paper reports progress in distribution of frequency and time reference signals over optical fibers. Describes current performance at frequencies of 100 MHz, 1 GHz, and 8.4 GHz. Also describes transmitting and receiving equipment and discusses tradeoff between cost and performance. Concludes with discussion of likely future development and effects of developments on systems using distributed frequency reference signals.

Fractal Complexity-Based Feature Extraction Algorithm of Communication Signals

NASA Astrophysics Data System (ADS)

Wang, Hui; Li, Jingchao; Guo, Lili; Dou, Zheng; Lin, Yun; Zhou, Ruolin

How to analyze and identify the characteristics of radiation sources and estimate the threat level by means of detecting, intercepting and locating has been the central issue of electronic support in the electronic warfare, and communication signal recognition is one of the key points to solve this issue. Aiming at accurately extracting the individual characteristics of the radiation source for the increasingly complex communication electromagnetic environment, a novel feature extraction algorithm for individual characteristics of the communication radiation source based on the fractal complexity of the signal is proposed. According to the complexity of the received signal and the situation of environmental noise, use the fractal dimension characteristics of different complexity to depict the subtle characteristics of the signal to establish the characteristic database, and then identify different broadcasting station by gray relation theory system. The simulation results demonstrate that the algorithm can achieve recognition rate of 94% even in the environment with SNR of -10dB, and this provides an important theoretical basis for the accurate identification of the subtle features of the signal at low SNR in the field of information confrontation.

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

NASA Astrophysics Data System (ADS)

Yu, Lingyu; Bao, Jingjing; Giurgiutiu, Victor

2004-07-01

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

Secure Indoor Localization Based on Extracting Trusted Fingerprint

PubMed Central

Yin, Xixi; Zheng, Yanliu; Wang, Chun

2018-01-01

Indoor localization based on WiFi has attracted a lot of research effort because of the widespread application of WiFi. Fingerprinting techniques have received much attention due to their simplicity and compatibility with existing hardware. However, existing fingerprinting localization algorithms may not resist abnormal received signal strength indication (RSSI), such as unexpected environmental changes, impaired access points (APs) or the introduction of new APs. Traditional fingerprinting algorithms do not consider the problem of new APs and impaired APs in the environment when using RSSI. In this paper, we propose a secure fingerprinting localization (SFL) method that is robust to variable environments, impaired APs and the introduction of new APs. In the offline phase, a voting mechanism and a fingerprint database update method are proposed. We use the mutual cooperation between reference anchor nodes to update the fingerprint database, which can reduce the interference caused by the user measurement data. We analyze the standard deviation of RSSI, mobilize the reference points in the database to vote on APs and then calculate the trust factors of APs based on the voting results. In the online phase, we first make a judgment about the new APs and the broken APs, then extract the secure fingerprints according to the trusted factors of APs and obtain the localization results by using the trusted fingerprints. In the experiment section, we demonstrate the proposed method and find that the proposed strategy can resist abnormal RSSI and can improve the localization accuracy effectively compared with the existing fingerprinting localization algorithms. PMID:29401755

Secure Indoor Localization Based on Extracting Trusted Fingerprint.

PubMed

Luo, Juan; Yin, Xixi; Zheng, Yanliu; Wang, Chun

2018-02-05

[-5]Indoor localization based on WiFi has attracted a lot of research effort because of the widespread application of WiFi. Fingerprinting techniques have received much attention due to their simplicity and compatibility with existing hardware. However, existing fingerprinting localization algorithms may not resist abnormal received signal strength indication (RSSI), such as unexpected environmental changes, impaired access points (APs) or the introduction of new APs. Traditional fingerprinting algorithms do not consider the problem of new APs and impaired APs in the environment when using RSSI. In this paper, we propose a secure fingerprinting localization (SFL) method that is robust to variable environments, impaired APs and the introduction of new APs. In the offline phase, a voting mechanism and a fingerprint database update method are proposed. We use the mutual cooperation between reference anchor nodes to update the fingerprint database, which can reduce the interference caused by the user measurement data. We analyze the standard deviation of RSSI, mobilize the reference points in the database to vote on APs and then calculate the trust factors of APs based on the voting results. In the online phase, we first make a judgment about the new APs and the broken APs, then extract the secure fingerprints according to the trusted factors of APs and obtain the localization results by using the trusted fingerprints. In the experiment section, we demonstrate the proposed method and find that the proposed strategy can resist abnormal RSSI and can improve the localization accuracy effectively compared with the existing fingerprinting localization algorithms.

Real-Time EEG Signal Enhancement Using Canonical Correlation Analysis and Gaussian Mixture Clustering

PubMed Central

Huang, Chih-Sheng; Yang, Wen-Yu; Chuang, Chun-Hsiang; Wang, Yu-Kai

2018-01-01

Electroencephalogram (EEG) signals are usually contaminated with various artifacts, such as signal associated with muscle activity, eye movement, and body motion, which have a noncerebral origin. The amplitude of such artifacts is larger than that of the electrical activity of the brain, so they mask the cortical signals of interest, resulting in biased analysis and interpretation. Several blind source separation methods have been developed to remove artifacts from the EEG recordings. However, the iterative process for measuring separation within multichannel recordings is computationally intractable. Moreover, manually excluding the artifact components requires a time-consuming offline process. This work proposes a real-time artifact removal algorithm that is based on canonical correlation analysis (CCA), feature extraction, and the Gaussian mixture model (GMM) to improve the quality of EEG signals. The CCA was used to decompose EEG signals into components followed by feature extraction to extract representative features and GMM to cluster these features into groups to recognize and remove artifacts. The feasibility of the proposed algorithm was demonstrated by effectively removing artifacts caused by blinks, head/body movement, and chewing from EEG recordings while preserving the temporal and spectral characteristics of the signals that are important to cognitive research. PMID:29599950

Early Fault Diagnosis of Bearings Using an Improved Spectral Kurtosis by Maximum Correlated Kurtosis Deconvolution

PubMed Central

Jia, Feng; Lei, Yaguo; Shan, Hongkai; Lin, Jing

2015-01-01

The early fault characteristics of rolling element bearings carried by vibration signals are quite weak because the signals are generally masked by heavy background noise. To extract the weak fault characteristics of bearings from the signals, an improved spectral kurtosis (SK) method is proposed based on maximum correlated kurtosis deconvolution (MCKD). The proposed method combines the ability of MCKD in indicating the periodic fault transients and the ability of SK in locating these transients in the frequency domain. A simulation signal overwhelmed by heavy noise is used to demonstrate the effectiveness of the proposed method. The results show that MCKD is beneficial to clarify the periodic impulse components of the bearing signals, and the method is able to detect the resonant frequency band of the signal and extract its fault characteristic frequency. Through analyzing actual vibration signals collected from wind turbines and hot strip rolling mills, we confirm that by using the proposed method, it is possible to extract fault characteristics and diagnose early faults of rolling element bearings. Based on the comparisons with the SK method, it is verified that the proposed method is more suitable to diagnose early faults of rolling element bearings. PMID:26610501

Wavelet Packet Analysis for Angular Data Extraction from Muscle Afferent Cuff Electrode Signals

DTIC Science & Technology

2001-10-25

from rabbits. In order to estimate ankle flexion/extension angles, we recorded ENG signals from the left Tibial and Peroneal nerves, both during FES...afferent ENG. II. METHODOLOGY A. Experimental Setup Acute experiments were conducted with 2 female New Zealand rabbits. The rabbits were pre-anesthetized...fixating the knee and ankle joints in place (see [3] for more details) . For extracting the ENG signals, tripolar cuff electrodes were implanted onto the

Sliding window denoising K-Singular Value Decomposition and its application on rolling bearing impact fault diagnosis

NASA Astrophysics Data System (ADS)

Yang, Honggang; Lin, Huibin; Ding, Kang

2018-05-01

The performance of sparse features extraction by commonly used K-Singular Value Decomposition (K-SVD) method depends largely on the signal segment selected in rolling bearing diagnosis, furthermore, the calculating speed is relatively slow and the dictionary becomes so redundant when the fault signal is relatively long. A new sliding window denoising K-SVD (SWD-KSVD) method is proposed, which uses only one small segment of time domain signal containing impacts to perform sliding window dictionary learning and select an optimal pattern with oscillating information of the rolling bearing fault according to a maximum variance principle. An inner product operation between the optimal pattern and the whole fault signal is performed to enhance the characteristic of the impacts' occurrence moments. Lastly, the signal is reconstructed at peak points of the inner product to realize the extraction of the rolling bearing fault features. Both simulation and experiments verify that the method could extract the fault features effectively.

Bilinear modeling of EMG signals to extract user-independent features for multiuser myoelectric interface.

PubMed

Matsubara, Takamitsu; Morimoto, Jun

2013-08-01

In this study, we propose a multiuser myoelectric interface that can easily adapt to novel users. When a user performs different motions (e.g., grasping and pinching), different electromyography (EMG) signals are measured. When different users perform the same motion (e.g., grasping), different EMG signals are also measured. Therefore, designing a myoelectric interface that can be used by multiple users to perform multiple motions is difficult. To cope with this problem, we propose for EMG signals a bilinear model that is composed of two linear factors: 1) user dependent and 2) motion dependent. By decomposing the EMG signals into these two factors, the extracted motion-dependent factors can be used as user-independent features. We can construct a motion classifier on the extracted feature space to develop the multiuser interface. For novel users, the proposed adaptation method estimates the user-dependent factor through only a few interactions. The bilinear EMG model with the estimated user-dependent factor can extract the user-independent features from the novel user data. We applied our proposed method to a recognition task of five hand gestures for robotic hand control using four-channel EMG signals measured from subject forearms. Our method resulted in 73% accuracy, which was statistically significantly different from the accuracy of standard nonmultiuser interfaces, as the result of a two-sample t -test at a significance level of 1%.

Non-chromatographic speciation of chromium at sub-ppb levels using cloud point extraction in the presence of unmodified silver nanoparticles.

PubMed

López-García, Ignacio; Vicente-Martínez, Yesica; Hernández-Córdoba, Manuel

2015-01-01

The cloud point extraction (CPE) of silver nanoparticles (AgNPs) by Triton X-114 allows chromium (III) ions to be transferred to the surfactant-rich phase, where they can be measured by electrothermal atomic absorption spectrometry. Using 20 mL sample and 50 μL Triton X-114 (30% w/v), the enrichment factor was 1150, and calibration graphs were obtained in the 5-100 ng L(-1) chromium range in the presence of 5 µg L(-1) AgNPs. Speciation of trivalent and hexavalent chromium was achieved by carrying out two CPE experiments, one of them in the presence of ethylenediaminetetraacetate. While in the first experiment, in absence of the complexing agent, the concentration of total chromium was obtained, the analytical signal measured in the presence of this chemical allowed the chromium (VI) concentration to be measured, being that of chromium (III) calculated by difference. The reliability of the procedure was verified by using three standard reference materials before applying to water, beer and wine samples. Copyright © 2014 Elsevier B.V. All rights reserved.

Adaptive angular-velocity Vold-Kalman filter order tracking - Theoretical basis, numerical implementation and parameter investigation

NASA Astrophysics Data System (ADS)

Pan, M.-Ch.; Chu, W.-Ch.; Le, Duc-Do

2016-12-01

The paper presents an alternative Vold-Kalman filter order tracking (VKF_OT) method, i.e. adaptive angular-velocity VKF_OT technique, to extract and characterize order components in an adaptive manner for the condition monitoring and fault diagnosis of rotary machinery. The order/spectral waveforms to be tracked can be recursively solved by using Kalman filter based on the one-step state prediction. The paper comprises theoretical derivation of computation scheme, numerical implementation, and parameter investigation. Comparisons of the adaptive VKF_OT scheme with two other ones are performed through processing synthetic signals of designated order components. Processing parameters such as the weighting factor and the correlation matrix of process noise, and data conditions like the sampling frequency, which influence tracking behavior, are explored. The merits such as adaptive processing nature and computation efficiency brought by the proposed scheme are addressed although the computation was performed in off-line conditions. The proposed scheme can simultaneously extract multiple spectral components, and effectively decouple close and crossing orders associated with multi-axial reference rotating speeds.

Phase locking of a 2.7 THz quantum cascade laser to a microwave reference.

PubMed

Khosropanah, P; Baryshev, A; Zhang, W; Jellema, W; Hovenier, J N; Gao, J R; Klapwijk, T M; Paveliev, D G; Williams, B S; Kumar, S; Hu, Q; Reno, J L; Klein, B; Hesler, J L

2009-10-01

We demonstrate the phase locking of a 2.7 THz metal-metal waveguide quantum cascade laser (QCL) to an external microwave signal. The reference is the 15th harmonic, generated by a semiconductor superlattice nonlinear device, of a signal at 182 GHz, which itself is generated by a multiplier chain (x12) from a microwave synthesizer at approximately 15 GHz. Both laser and reference radiations are coupled into a bolometer mixer, resulting in a beat signal, which is fed into a phase-lock loop. The spectral analysis of the beat signal confirms that the QCL is phase locked. This result opens the possibility to extend heterodyne interferometers into the far-infrared range.

Phase Locking of a 2.7 THz Quantum Cascade Laser to a Microwave Reference

NASA Technical Reports Server (NTRS)

Khosropanah, P.; Baryshev, A.; Zhang, W.; Jellema, W.; Hovenier, J. N.; Gao, J. R.; Klapwijk, T. M.; Paveliev, D. G.; Williams, B. S.; Hu, Q.;

Independent components analysis coupled with 3D-front-face fluorescence spectroscopy to study the interaction between plastic food packaging and olive oil.

PubMed

Kassouf, Amine; El Rakwe, Maria; Chebib, Hanna; Ducruet, Violette; Rutledge, Douglas N; Maalouly, Jacqueline

2014-08-11

Olive oil is one of the most valued sources of fats in the Mediterranean diet. Its storage was generally done using glass or metallic packaging materials. Nowadays, plastic packaging has gained worldwide spread for the storage of olive oil. However, plastics are not inert and interaction phenomena may occur between packaging materials and olive oil. In this study, extra virgin olive oil samples were submitted to accelerated interaction conditions, in contact with polypropylene (PP) and polylactide (PLA) plastic packaging materials. 3D-front-face fluorescence spectroscopy, being a simple, fast and non destructive analytical technique, was used to study this interaction. Independent components analysis (ICA) was used to analyze raw 3D-front-face fluorescence spectra of olive oil. ICA was able to highlight a probable effect of a migration of substances with antioxidant activity. The signals extracted by ICA corresponded to natural olive oil fluorophores (tocopherols and polyphenols) as well as newly formed ones which were tentatively identified as fluorescent oxidation products. Based on the extracted fluorescent signals, olive oil in contact with plastics had slower aging rates in comparison with reference oils. Peroxide and free acidity values validated the results obtained by ICA, related to olive oil oxidation rates. Sorbed olive oil in plastic was also quantified given that this sorption could induce a swelling of the polymer thus promoting migration. Copyright © 2014 Elsevier B.V. All rights reserved.

Eucalyptus globulus extract protects against UVB-induced photoaging by enhancing collagen synthesis via regulation of TGF-β/Smad signals and attenuation of AP-1.

PubMed

Park, Bom; Hwang, Eunson; Seo, Seul A; Cho, Jin-Gyeong; Yang, Jung-Eun; Yi, Tae-Hoo

2018-01-01

UV irradiation triggers the overproduction of matrix metalloproteinases and collagen degradation, which in turn causes increased pigmentation, dryness, and deep wrinkling of the skin. These chronic symptoms are collectively referred to as photoaging. Eucalyptus globulus is an evergreen tree that is widely used in cosmetics because of its antimicrobial activity. In this study, we investigated the protective effect of 50% ethanol extracts of Eucalyptus globulus on UV-induced photoaging in vitro and in vivo. Normal human dermal fibroblasts were treated with Eucalyptus globulus at concentrations ranging from 1 to 100 μg/mL after UVB or non-UVB irradiation. We found that Eucalyptus globulus suppressed the expression of MMPs and IL-6, but increased the expression of TGF-β1 and procollagen type 1. In addition, Eucalyptus globulus inhibited activation of the AP-1 transcription factor, an inducer of MMPs. Eucalyptus globulus was also found to regulate TGF-β/Smad signaling by reversing the activity of negative Smad regulators. Lastly, in vivo studies showed that topical application of Eucalyptus globulus on UVB-irradiated hairless mice reduced wrinkle formation and dryness by down-regulating MMP-1 and up-regulating expression of elastin, TGF-β1, and procollagen type 1. Taken together, these data suggest that Eucalyptus globulus may be a useful agent in cosmetic products. Copyright © 2017 Elsevier Inc. All rights reserved.

Wide-range lock-in amplifier

DOEpatents

McNeilly, D.R.

1984-01-01

A lock-in amplifier is provided which allows detection of a signal buried in noise without preprocessing of the input signal. An analog signal multiplier is used to obtain a dc output which is the product of the signal being detected and a high-purity sine wave signal. A reference signal of a known selectable frequency is applied to a sine-wave generator to generate the sine wave of the same frequency. The sine wave is applied to a multiplier through a phase shift arrangement to allow the detection of both amplitude of the detected signal and the phases relative to the reference signal. The multiplier output is filtered by a low-pass filter to eliminate unwanted frequency components from the output signal.

Wide-range lock-in amplifier

DOEpatents

McNeilly, David R.

1985-01-01

A lock-in amplifier is provided which allows detection of a signal buried in noise without preprocessing of the input signal. An analog signal multiplier is used to obtain a dc output which is the product of the signal being detected and a high-purity sine wave signal. A reference signal of a known selectable frequency is applied to a sine-wave generator to generate the sine wave of the same frequency. The sine wave is applied to a multiplier through a phase shift arrangement to allow the detection of both amplitude of the detected signal and the phases relative to the reference signal. The multiplier output is filtered by a low-pass filter to eliminate unwanted frequency components from the output signal.

Extracting climate memory using Fractional Integrated Statistical Model: A new perspective on climate prediction

PubMed Central

Yuan, Naiming; Fu, Zuntao; Liu, Shida

2014-01-01

Long term memory (LTM) in climate variability is studied by means of fractional integral techniques. By using a recently developed model, Fractional Integral Statistical Model (FISM), we in this report proposed a new method, with which one can estimate the long-lasting influences of historical climate states on the present time quantitatively, and further extract the influence as climate memory signals. To show the usability of this method, two examples, the Northern Hemisphere monthly Temperature Anomalies (NHTA) and the Pacific Decadal Oscillation index (PDO), are analyzed in this study. We find the climate memory signals indeed can be extracted and the whole variations can be further decomposed into two parts: the cumulative climate memory (CCM) and the weather-scale excitation (WSE). The stronger LTM is, the larger proportion the climate memory signals will account for in the whole variations. With the climate memory signals extracted, one can at least determine on what basis the considered time series will continue to change. Therefore, this report provides a new perspective on climate prediction. PMID:25300777

Fault feature extraction of planet gear in wind turbine gearbox based on spectral kurtosis and time wavelet energy spectrum

NASA Astrophysics Data System (ADS)

Kong, Yun; Wang, Tianyang; Li, Zheng; Chu, Fulei

2017-09-01

Planetary transmission plays a vital role in wind turbine drivetrains, and its fault diagnosis has been an important and challenging issue. Owing to the complicated and coupled vibration source, time-variant vibration transfer path, and heavy background noise masking effect, the vibration signal of planet gear in wind turbine gearboxes exhibits several unique characteristics: Complex frequency components, low signal-to-noise ratio, and weak fault feature. In this sense, the periodic impulsive components induced by a localized defect are hard to extract, and the fault detection of planet gear in wind turbines remains to be a challenging research work. Aiming to extract the fault feature of planet gear effectively, we propose a novel feature extraction method based on spectral kurtosis and time wavelet energy spectrum (SK-TWES) in the paper. Firstly, the spectral kurtosis (SK) and kurtogram of raw vibration signals are computed and exploited to select the optimal filtering parameter for the subsequent band-pass filtering. Then, the band-pass filtering is applied to extrude periodic transient impulses using the optimal frequency band in which the corresponding SK value is maximal. Finally, the time wavelet energy spectrum analysis is performed on the filtered signal, selecting Morlet wavelet as the mother wavelet which possesses a high similarity to the impulsive components. The experimental signals collected from the wind turbine gearbox test rig demonstrate that the proposed method is effective at the feature extraction and fault diagnosis for the planet gear with a localized defect.

Development of a Technique for Separating Raman Scattering Signals from Background Emission with Single-Shot Measurement Potential

NASA Technical Reports Server (NTRS)

Hartfield, Roy J., Jr.; Dobson, Chris; Eskridge, Richard; Wehrmeyer, Joseph A.

1997-01-01

A novel technique for extracting Q-branch Raman signals scattered by a diatomic species from the emission spectrum resulting from the irradiation of combustion products using a broadband excimer laser has been developed. This technique is based on the polarization characteristics of vibrational Raman scattering and can be used for both single-shot Raman extraction and time-averaged data collection. The Q-branch Raman signal has a unique set of polarization characteristics which depend on the direction of the scattering while fluorescence signals are unpolarized. For the present work, a calcite crystal is used to separate the horizonal component of a collected signal from the vertical component. The two components are then sent through a UV spectrometer and imaged onto an intensified CCD camera separately. The vertical component contains both the Raman signal and the interfering fluorescence signal. The horizontal component contains the fluorescence signal and a very weak component of the Raman signal; hence, the Raman scatter can be extracted by taking the difference between the two signals. The separation of the Raman scatter from interfering fluorescence signals is critically important to the interpretation of the Raman for cases in which a broadband ultraviolet (UV) laser is used as an excitation source in a hydrogen-oxygen flame and in all hydrocarbon flames. The present work provides a demonstration of the separation of the Raman scatter from the fluorescence background in real time.

Compact self-contained electrical-to-optical converter/transmitter

DOEpatents

Seligmann, Daniel A.; Moss, William C.; Valk, Theodore C.; Conder, Alan D.

1995-01-01

A first optical receiver and a second optical receiver are provided for receiving a calibrate command and a power switching signal, respectively, from a remote processor. A third receiver is provided for receiving an analog electrical signal from a transducer. A calibrator generates a reference signal in response to the calibrate command. A combiner mixes the electrical signal with the reference signal to form a calibrated signal. A converter converts the calibrated signal to an optical signal. A transmitter transmits the optical signal to the remote processor. A primary battery supplies power to the calibrator, the combiner, the converter, and the transmitter. An optically-activated switch supplies power to the calibrator, the combiner, the converter, and the transmitter in response to the power switching signal. An auxiliary battery supplies power continuously to the switch.

Analytic processing of distance.

PubMed

Dopkins, Stephen; Galyer, Darin

2018-01-01

How does a human observer extract from the distance between two frontal points the component corresponding to an axis of a rectangular reference frame? To find out we had participants classify pairs of small circles, varying on the horizontal and vertical axes of a computer screen, in terms of the horizontal distance between them. A response signal controlled response time. The error rate depended on the irrelevant vertical as well as the relevant horizontal distance between the test circles with the relevant distance effect being larger than the irrelevant distance effect. The results implied that the horizontal distance between the test circles was imperfectly extracted from the overall distance between them. The results supported an account, derived from the Exemplar Based Random Walk model (Nosofsky & Palmieri, 1997), under which distance classification is based on the overall distance between the test circles, with relevant distance being extracted from overall distance to the extent that the relevant and irrelevant axes are differentially weighted so as to reduce the contribution of irrelevant distance to overall distance. The results did not support an account, derived from the General Recognition Theory (Ashby & Maddox, 1994), under which distance classification is based on the relevant distance between the test circles, with the irrelevant distance effect arising because a test circle's perceived location on the relevant axis depends on its location on the irrelevant axis, and with relevant distance being extracted from overall distance to the extent that this dependency is absent. Copyright © 2017 Elsevier B.V. All rights reserved.

Coherent Frequency Reference System for the NASA Deep Space Network

NASA Technical Reports Server (NTRS)

Tucker, Blake C.; Lauf, John E.; Hamell, Robert L.; Gonzaler, Jorge, Jr.; Diener, William A.; Tjoelker, Robert L.

2010-01-01

The NASA Deep Space Network (DSN) requires state-of-the-art frequency references that are derived and distributed from very stable atomic frequency standards. A new Frequency Reference System (FRS) and Frequency Reference Distribution System (FRD) have been developed, which together replace the previous Coherent Reference Generator System (CRG). The FRS and FRD each provide new capabilities that significantly improve operability and reliability. The FRS allows for selection and switching between frequency standards, a flywheel capability (to avoid interruptions when switching frequency standards), and a frequency synthesis system (to generate standardized 5-, 10-, and 100-MHz reference signals). The FRS is powered by redundant, specially filtered, and sustainable power systems and includes a monitor and control capability for station operations to interact and control the frequency-standard selection process. The FRD receives the standardized 5-, 10-, and 100-MHz reference signals and distributes signals to distribution amplifiers in a fan out fashion to dozens of DSN users that require the highly stable reference signals. The FRD is also powered by redundant, specially filtered, and sustainable power systems. The new DSN Frequency Distribution System, which consists of the FRS and FRD systems described here, is central to all operational activities of the NASA DSN. The frequency generation and distribution system provides ultra-stable, coherent, and very low phase-noise references at 5, l0, and 100 MHz to between 60 and 100 separate users at each Deep Space Communications Complex.

AN EVALUATION OF SAMPLE DISPERSION MEDIAS USED WITH ACCELERATED SOLVENT EXTRACTION FOR THE EXTRACTION AND RECOVERY OF ARSENICALS FROM LFB AND DORM-2

EPA Science Inventory

An accelerated solvent extraction (ASE) device was evaluated as a semi-automated means for extracting arsenicals from quality control (QC) samples and DORM-2 [standard reference material (SRM)]. Unlike conventional extraction procedures, the ASE requires that the sample be dispe...

Characterization of large-scale fluctuations and short-term variability of Seine river daily streamflow (France) over the period 1950-2008 by empirical mode decomposition and the Hilbert-Huang transform

NASA Astrophysics Data System (ADS)

Massei, N.; Fournier, M.

2010-12-01

Daily Seine river flow from 1950 to 2008 was analyzed using Hilbert-Huang Tranform (HHT). For the last ten years, this method which combines the so-called Empirical Mode Decomposition (EMD) multiresolution analysis and the Hilbert transform has proven its efficiency for the analysis of transient oscillatory signals, although the mathematical definition of the EMD is not totally established yet. HHT also provides an interesting alternative to other time-frequency or time-scale analysis of non-stationary signals, the most famous of which being wavelet-based approaches. In this application of HHT to the analysis of the hydrological variability of the Seine river, we seek to characterize the interannual patterns of daily flow, differenciate them from the short-term dynamics and eventually interpret them in the context of regional climate regime fluctuations. In this aim, HHT is also applied to the North-Atlantic Oscillation (NAO) through the annual winter-months NAO index time series. For both hydrological and climatic signals, dominant variability scales are extracted and their temporal variations analyzed by determination of the intantaneous frequency of each component. When compared to previous ones obtained from continuous wavelet transform (CWT) on the same data, HHT results highlighted the same scales and somewhat the same internal components for each signal. However, HHT allowed the identification and extraction of much more similar features during the 1950-2008 period (e.g., around 7-yr, between NAO and Seine flow than what was obtained from CWT, which comes to say that variability scales in flow likely to originate from climatic regime fluctuations were much properly identified in river flow. In addition, a more accurate determination of singularities in the natural processes analyzed were authorized by HHT compared to CWT, in which case the time-frequency resolution partly depends on the basic properties of the filter (i.e., the reference wavelet chosen initially). Compared to CWT or even to discrete wavelet multiresolution analysis, HHT is auto-adaptive, non-parametric, allows an orthogonal decomposition of the signal analyzed and provides a more accurate estimation of changing variability scales across time for highly transient signals.

Circular common-path point diffraction interferometer.

PubMed

Du, Yongzhao; Feng, Guoying; Li, Hongru; Vargas, J; Zhou, Shouhuan

2012-10-01

A simple and compact point-diffraction interferometer with circular common-path geometry configuration is developed. The interferometer is constructed by a beam-splitter, two reflection mirrors, and a telescope system composed by two lenses. The signal and reference waves travel along the same path. Furthermore, an opaque mask containing a reference pinhole and a test object holder or test window is positioned in the common focal plane of the telescope system. The object wave is divided into two beams that take opposite paths along the interferometer. The reference wave is filtered by the reference pinhole, while the signal wave is transmitted through the object holder. The reference and signal waves are combined again in the beam-splitter and their interference is imaged in the CCD. The new design is compact, vibration insensitive, and suitable for the measurement of moving objects or dynamic processes.

Alcoholic extraction enables EPR analysis to characterize radiation-induced cellulosic signals in spices.

PubMed

Ahn, Jae-Jun; Sanyal, Bhaskar; Akram, Kashif; Kwon, Joong-Ho

2014-11-19

Different spices such as turmeric, oregano, and cinnamon were γ-irradiated at 1 and 10 kGy. The electron paramagnetic resonance (EPR) spectra of the nonirradiated samples were characterized by a single central signal (g = 2.006), the intensity of which was significantly enhanced upon irradiation. The EPR spectra of the irradiated spice samples were characterized by an additional triplet signal at g = 2.006 with a hyperfine coupling constant of 3 mT, associated with the cellulose radical. EPR analysis on various sample pretreatments in the irradiated spice samples demonstrated that the spectral features of the cellulose radical varied on the basis of the pretreatment protocol. Alcoholic extraction pretreatment produced considerable improvements of the EPR signals of the irradiated spice samples relative to the conventional oven and freeze-drying techniques. The alcoholic extraction process is therefore proposed as the most suitable sample pretreatment for unambiguous detection of irradiated spices by EPR spectroscopy.

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.

Parallel optimization of signal detection in active magnetospheric signal injection experiments

NASA Astrophysics Data System (ADS)

Gowanlock, Michael; Li, Justin D.; Rude, Cody M.; Pankratius, Victor

2018-05-01

Signal detection and extraction requires substantial manual parameter tuning at different stages in the processing pipeline. Time-series data depends on domain-specific signal properties, necessitating unique parameter selection for a given problem. The large potential search space makes this parameter selection process time-consuming and subject to variability. We introduce a technique to search and prune such parameter search spaces in parallel and select parameters for time series filters using breadth- and depth-first search strategies to increase the likelihood of detecting signals of interest in the field of magnetospheric physics. We focus on studying geomagnetic activity in the extremely and very low frequency ranges (ELF/VLF) using ELF/VLF transmissions from Siple Station, Antarctica, received at Québec, Canada. Our technique successfully detects amplified transmissions and achieves substantial speedup performance gains as compared to an exhaustive parameter search. We present examples where our algorithmic approach reduces the search from hundreds of seconds down to less than 1 s, with a ranked signal detection in the top 99th percentile, thus making it valuable for real-time monitoring. We also present empirical performance models quantifying the trade-off between the quality of signal recovered and the algorithm response time required for signal extraction. In the future, improved signal extraction in scenarios like the Siple experiment will enable better real-time diagnostics of conditions of the Earth's magnetosphere for monitoring space weather activity.

Statistical issues in signal extraction from microarrays

NASA Astrophysics Data System (ADS)

Bergemann, Tracy; Quiaoit, Filemon; Delrow, Jeffrey J.; Zhao, Lue Ping

2001-06-01

Microarray technologies are increasingly used in biomedical research to study genome-wide expression profiles in the post genomic era. Their popularity is largely due to their high throughput and economical affordability. For example, microarrays have been applied to studies of cell cycle, regulatory circuitry, cancer cell lines, tumor tissues, and drug discoveries. One obstacle facing the continued success of applying microarray technologies, however, is the random variaton present on microarrays: within signal spots, between spots and among chips. In addition, signals extracted by available software packages seem to vary significantly. Despite a variety of software packages, it appears that there are two major approaches to signal extraction. One approach is to focus on the identification of signal regions and hence estimation of signal levels above background levels. The other approach is to use the distribution of intensity values as a way of identifying relevant signals. Building upon both approaches, the objective of our work is to develop a method that is statistically rigorous and also efficient and robust. Statistical issues to be considered here include: (1) how to refine grid alignment so that the overall variation is minimized, (2) how to estimate the signal levels relative to the local background levels as well as the variance of this estimate, and (3) how to integrate red and green channel signals so that the ratio of interest is stable, simultaneously relaxing distributional assumptions.

Combination ring cavity and backward Raman waveguide amplifier

DOEpatents

Kurnit, Norman A.

1983-01-01

A combination regenerative ring and backward Raman waveguide amplifier and a combination regenerative ring oscillator and backward Raman waveguide amplifier which produce Raman amplification, pulse compression, and efficient energy extraction from the CO.sub.2 laser pump signal for conversion into a Stokes radiation signal. The ring cavity configuration allows the CO.sub.2 laser pump signal and Stokes signal to copropagate through the Raman waveguide amplifier. The backward Raman waveguide amplifier configuration extracts a major portion of the remaining energy from the CO.sub.2 laser pump signal for conversion to Stokes radiation. Additionally, the backward Raman amplifier configuration produces a Stokes radiation signal which has a high intensity and a short duration. Adjustment of the position of overlap of the Stokes signal and the CO.sub.2 laser pump signal in the backward Raman waveguide amplifiers alters the amount of pulse compression which can be achieved.

Subaperture clutter filter with CFAR signal detection

DOEpatents

Ormesher, Richard C.; Naething, Richard M.

2016-08-30

The various technologies presented herein relate to the determination of whether a received signal comprising radar clutter further comprises a communication signal. The communication signal can comprise of a preamble, a data symbol, communication data, etc. A first portion of the radar clutter is analyzed to determine a radar signature of the first portion of the radar clutter. A second portion of the radar clutter can be extracted based on the radar signature of the first portion. Following extraction, any residual signal can be analyzed to retrieve preamble data, etc. The received signal can be based upon a linear frequency modulation (e.g., a chirp modulation) whereby the chirp frequency can be determined and the frequency of transmission of the communication signal can be based accordingly thereon. The duration and/or bandwidth of the communication signal can be a portion of the duration and/or the bandwidth of the radar clutter.

Classification of EEG Signals Based on Pattern Recognition Approach.

PubMed

Amin, Hafeez Ullah; Mumtaz, Wajid; Subhani, Ahmad Rauf; Saad, Mohamad Naufal Mohamad; Malik, Aamir Saeed

2017-01-01

Feature extraction is an important step in the process of electroencephalogram (EEG) signal classification. The authors propose a "pattern recognition" approach that discriminates EEG signals recorded during different cognitive conditions. Wavelet based feature extraction such as, multi-resolution decompositions into detailed and approximate coefficients as well as relative wavelet energy were computed. Extracted relative wavelet energy features were normalized to zero mean and unit variance and then optimized using Fisher's discriminant ratio (FDR) and principal component analysis (PCA). A high density EEG dataset validated the proposed method (128-channels) by identifying two classifications: (1) EEG signals recorded during complex cognitive tasks using Raven's Advance Progressive Metric (RAPM) test; (2) EEG signals recorded during a baseline task (eyes open). Classifiers such as, K-nearest neighbors (KNN), Support Vector Machine (SVM), Multi-layer Perceptron (MLP), and Naïve Bayes (NB) were then employed. Outcomes yielded 99.11% accuracy via SVM classifier for coefficient approximations (A5) of low frequencies ranging from 0 to 3.90 Hz. Accuracy rates for detailed coefficients were 98.57 and 98.39% for SVM and KNN, respectively; and for detailed coefficients (D5) deriving from the sub-band range (3.90-7.81 Hz). Accuracy rates for MLP and NB classifiers were comparable at 97.11-89.63% and 91.60-81.07% for A5 and D5 coefficients, respectively. In addition, the proposed approach was also applied on public dataset for classification of two cognitive tasks and achieved comparable classification results, i.e., 93.33% accuracy with KNN. The proposed scheme yielded significantly higher classification performances using machine learning classifiers compared to extant quantitative feature extraction. These results suggest the proposed feature extraction method reliably classifies EEG signals recorded during cognitive tasks with a higher degree of accuracy.

Classification of EEG Signals Based on Pattern Recognition Approach

PubMed Central

Amin, Hafeez Ullah; Mumtaz, Wajid; Subhani, Ahmad Rauf; Saad, Mohamad Naufal Mohamad; Malik, Aamir Saeed

2017-01-01

Feature extraction is an important step in the process of electroencephalogram (EEG) signal classification. The authors propose a “pattern recognition” approach that discriminates EEG signals recorded during different cognitive conditions. Wavelet based feature extraction such as, multi-resolution decompositions into detailed and approximate coefficients as well as relative wavelet energy were computed. Extracted relative wavelet energy features were normalized to zero mean and unit variance and then optimized using Fisher's discriminant ratio (FDR) and principal component analysis (PCA). A high density EEG dataset validated the proposed method (128-channels) by identifying two classifications: (1) EEG signals recorded during complex cognitive tasks using Raven's Advance Progressive Metric (RAPM) test; (2) EEG signals recorded during a baseline task (eyes open). Classifiers such as, K-nearest neighbors (KNN), Support Vector Machine (SVM), Multi-layer Perceptron (MLP), and Naïve Bayes (NB) were then employed. Outcomes yielded 99.11% accuracy via SVM classifier for coefficient approximations (A5) of low frequencies ranging from 0 to 3.90 Hz. Accuracy rates for detailed coefficients were 98.57 and 98.39% for SVM and KNN, respectively; and for detailed coefficients (D5) deriving from the sub-band range (3.90–7.81 Hz). Accuracy rates for MLP and NB classifiers were comparable at 97.11–89.63% and 91.60–81.07% for A5 and D5 coefficients, respectively. In addition, the proposed approach was also applied on public dataset for classification of two cognitive tasks and achieved comparable classification results, i.e., 93.33% accuracy with KNN. The proposed scheme yielded significantly higher classification performances using machine learning classifiers compared to extant quantitative feature extraction. These results suggest the proposed feature extraction method reliably classifies EEG signals recorded during cognitive tasks with a higher degree of accuracy. PMID:29209190

Analysis and Modeling of Echolocation Signals Emitted by Mediterranean Bottlenose Dolphins

NASA Astrophysics Data System (ADS)

Greco, Maria; Gini, Fulvio

2006-12-01

We analyzed the echolocation sounds emitted by Mediterranean bottlenose dolphins. We extracted the click trains by visual inspection of the data files recorded along the coast of the Tuscany with the collaboration of the CETUS Research Center. We modeled the extracted sonar clicks as Gaussian or exponential multicomponent signals, we estimated the characteristic parameters and compared the data with the reconstructed signals based on the estimates. Results about the estimation and the data fitting are largely shown in the paper.

Astronomical Verification of a Stabilized Frequency Reference Transfer System for the Square Kilometer Array

NASA Astrophysics Data System (ADS)

Gozzard, David R.; Schediwy, Sascha W.; Dodson, Richard; Rioja, María J.; Hill, Mike; Lennon, Brett; McFee, Jock; Mirtschin, Peter; Stevens, Jamie; Grainge, Keith

2017-07-01

In order to meet its cutting-edge scientific objectives, the Square Kilometre Array (SKA) telescope requires high-precision frequency references to be distributed to each of its antennas. The frequency references are distributed via fiber-optic links and must be actively stabilized to compensate for phase noise imposed on the signals by environmental perturbations on the links. SKA engineering requirements demand that any proposed frequency reference distribution system be proved in “astronomical verification” tests. We present results of the astronomical verification of a stabilized frequency reference transfer system proposed for SKA-mid. The dual-receiver architecture of the Australia Telescope Compact Array was exploited to subtract the phase noise of the sky signal from the data, allowing the phase noise of observations performed using a standard frequency reference, as well as the stabilized frequency reference transfer system transmitting over 77 km of fiber-optic cable, to be directly compared. Results are presented for the fractional frequency stability and phase drift of the stabilized frequency reference transfer system for celestial calibrator observations at 5 and 25 GHz. These observations plus additional laboratory results for the transferred signal stability over a 166 km metropolitan fiber-optic link are used to show that the stabilized transfer system under test exceeds all SKA phase-stability requirements within a broad range of observing conditions. Furthermore, we have shown that alternative reference dissemination systems that use multiple synthesizers to supply reference signals to sub-sections of an array may limit the imaging capability of the telescope.

EnEx-RANGE - Robust autonomous Acoustic Navigation in Glacial icE

NASA Astrophysics Data System (ADS)

Heinen, Dirk; Eliseev, Dmitry; Henke, Christoph; Jeschke, Sabina; Linder, Peter; Reuter, Sebastian; Schönitz, Sebastian; Scholz, Franziska; Weinstock, Lars Steffen; Wickmann, Stefan; Wiebusch, Christopher; Zierke, Simon

2017-03-01

Within the Enceladus Explorer Initiative of the DLR Space Administration navigation technologies for a future space mission are in development. Those technologies are the basis for the search for extraterrestrial life on the Saturn moon Enceladus. An autonomous melting probe, the EnEx probe, aims to extract a liquid sample from a water reservoir below the icy crust. A first EnEx probe was developed and demonstrated in a terrestrial scenario at the Bloodfalls, Taylor Glacier, Antarctica in November 2014. To enable navigation in glacier ice two acoustic systems were integrated into the probe in addition to conventional navigation technologies. The first acoustic system determines the position of the probe during the run based on propagation times of acoustic signals from emitters at reference positions at the glacier surface to receivers in the probe. The second system provides information about the forefield of the probe. It is based on sonographic principles with phased array technology integrated in the probe's melting head. Information about obstacles or sampling regions in the probe's forefield can be acquired. The development of both systems is now continued in the project EnEx-RANGE. The emitters of the localization system are replaced by a network of intelligent acoustic enabled melting probes. These localize each other by means of acoustic signals and create the reference system for the EnEx probe. This presentation includes the discussion of the intelligent acoustic network, the acoustic navigation systems of the EnEx probe and results of terrestrial tests.

Epileptic seizure detection from EEG signals with phase-amplitude cross-frequency coupling and support vector machine

NASA Astrophysics Data System (ADS)

Liu, Yang; Wang, Jiang; Cai, Lihui; Chen, Yingyuan; Qin, Yingmei

2018-03-01

As a pattern of cross-frequency coupling (CFC), phase-amplitude coupling (PAC) depicts the interaction between the phase and amplitude of distinct frequency bands from the same signal, and has been proved to be closely related to the brain’s cognitive and memory activities. This work utilized PAC and support vector machine (SVM) classifier to identify the epileptic seizures from electroencephalogram (EEG) data. The entropy-based modulation index (MI) matrixes are used to express the strength of PAC, from which we extracted features as the input for classifier. Based on the Bonn database, which contains five datasets of EEG segments obtained from healthy volunteers and epileptic subjects, a 100% classification accuracy is achieved for identifying seizure ictal from healthy data, and an accuracy of 97.67% is reached in the classification of ictal EEG signals from inter-ictal EEGs. Based on the CHB-MIT database which is a group of continuously recorded epileptic EEGs by scalp electrodes, a 97.50% classification accuracy is obtained and a raising sign of MI value is found at 6s before seizure onset. The classification performance in this work is effective, and PAC can be considered as a useful tool for detecting and predicting the epileptic seizures and providing reference for clinical diagnosis.

Localised photoplethysmography imaging for heart rate estimation of pre-term infants in the clinic

NASA Astrophysics Data System (ADS)

Chaichulee, Sitthichok; Villarroel, Mauricio; Jorge, João.; Arteta, Carlos; Green, Gabrielle; McCormick, Kenny; Zisserman, Andrew; Tarassenko, Lionel

2018-02-01

Non-contact vital-sign estimation allows the monitoring of physiological parameters (such as heart rate, respiratory rate, and peripheral oxygen saturation) without contact electrodes or sensors. Our recent work has demonstrated that a convolutional neural network (CNN) can be used to detect the presence of a patient and segment the patient's skin area for vital-sign estimation, thus enabling the automatic continuous monitoring of vital signs in a hospital environment. In a study approved by the local Research Ethical Committee, we made video recordings of pre-term infants nursed in a Neonatal Intensive Care Unit (NICU) at the John Radcliffe Hospital in Oxford, UK. We extended the CNN model to detect the head, torso and diaper of the infants. We extracted multiple photoplethysmographic imaging (PPGi) signals from each body part, analysed their signal quality, and compared them with the PPGi signal derived from the entire skin area. Our results demonstrated the benefits of estimating heart rate combined from multiple regions of interest using data fusion. In the test dataset, we achieved a mean absolute error of 2.4 beats per minute for 80% (31.1 hours) from a total recording time of 38.5 hours for which both reference heart rate and video data were valid.

Recognizing the degree of human attention using EEG signals from mobile sensors.

PubMed

Liu, Ning-Han; Chiang, Cheng-Yu; Chu, Hsuan-Chin

2013-08-09

During the learning process, whether students remain attentive throughout instruction generally influences their learning efficacy. If teachers can instantly identify whether students are attentive they can be suitably reminded to remain focused, thereby improving their learning effects. Traditional teaching methods generally require that teachers observe students' expressions to determine whether they are attentively learning. However, this method is often inaccurate and increases the burden on teachers. With the development of electroencephalography (EEG) detection tools, mobile brainwave sensors have become mature and affordable equipment. Therefore, in this study, whether students are attentive or inattentive during instruction is determined by observing their EEG signals. Because distinguishing between attentiveness and inattentiveness is challenging, two scenarios were developed for this study to measure the subjects' EEG signals when attentive and inattentive. After collecting EEG data using mobile sensors, various common features were extracted from the raw data. A support vector machine (SVM) classifier was used to calculate and analyze these features to identify the combination of features that best indicates whether students are attentive. Based on the experiment results, the method proposed in this study provides a classification accuracy of up to 76.82%. The study results can be used as a reference for learning system designs in the future.

A novel approach for SEMG signal classification with adaptive local binary patterns.

PubMed

Ertuğrul, Ömer Faruk; Kaya, Yılmaz; Tekin, Ramazan

2016-07-01

Feature extraction plays a major role in the pattern recognition process, and this paper presents a novel feature extraction approach, adaptive local binary pattern (aLBP). aLBP is built on the local binary pattern (LBP), which is an image processing method, and one-dimensional local binary pattern (1D-LBP). In LBP, each pixel is compared with its neighbors. Similarly, in 1D-LBP, each data in the raw is judged against its neighbors. 1D-LBP extracts feature based on local changes in the signal. Therefore, it has high a potential to be employed in medical purposes. Since, each action or abnormality, which is recorded in SEMG signals, has its own pattern, and via the 1D-LBP these (hidden) patterns may be detected. But, the positions of the neighbors in 1D-LBP are constant depending on the position of the data in the raw. Also, both LBP and 1D-LBP are very sensitive to noise. Therefore, its capacity in detecting hidden patterns is limited. To overcome these drawbacks, aLBP was proposed. In aLBP, the positions of the neighbors and their values can be assigned adaptively via the down-sampling and the smoothing coefficients. Therefore, the potential to detect (hidden) patterns, which may express an illness or an action, is really increased. To validate the proposed feature extraction approach, two different datasets were employed. Achieved accuracies by the proposed approach were higher than obtained results by employed popular feature extraction approaches and the reported results in the literature. Obtained accuracy results were brought out that the proposed method can be employed to investigate SEMG signals. In summary, this work attempts to develop an adaptive feature extraction scheme that can be utilized for extracting features from local changes in different categories of time-varying signals.

Theory of Remote Image Formation

NASA Astrophysics Data System (ADS)

Blahut, Richard E.

2004-11-01

In many applications, images, such as ultrasonic or X-ray signals, are recorded and then analyzed with digital or optical processors in order to extract information. Such processing requires the development of algorithms of great precision and sophistication. This book presents a unified treatment of the mathematical methods that underpin the various algorithms used in remote image formation. The author begins with a review of transform and filter theory. He then discusses two- and three-dimensional Fourier transform theory, the ambiguity function, image construction and reconstruction, tomography, baseband surveillance systems, and passive systems (where the signal source might be an earthquake or a galaxy). Information-theoretic methods in image formation are also covered, as are phase errors and phase noise. Throughout the book, practical applications illustrate theoretical concepts, and there are many homework problems. The book is aimed at graduate students of electrical engineering and computer science, and practitioners in industry. Presents a unified treatment of the mathematical methods that underpin the algorithms used in remote image formation Illustrates theoretical concepts with reference to practical applications Provides insights into the design parameters of real systems

Wavelet-based unsupervised learning method for electrocardiogram suppression in surface electromyograms.

PubMed

Niegowski, Maciej; Zivanovic, Miroslav

2016-03-01

We present a novel approach aimed at removing electrocardiogram (ECG) perturbation from single-channel surface electromyogram (EMG) recordings by means of unsupervised learning of wavelet-based intensity images. The general idea is to combine the suitability of certain wavelet decomposition bases which provide sparse electrocardiogram time-frequency representations, with the capacity of non-negative matrix factorization (NMF) for extracting patterns from images. In order to overcome convergence problems which often arise in NMF-related applications, we design a novel robust initialization strategy which ensures proper signal decomposition in a wide range of ECG contamination levels. Moreover, the method can be readily used because no a priori knowledge or parameter adjustment is needed. The proposed method was evaluated on real surface EMG signals against two state-of-the-art unsupervised learning algorithms and a singular spectrum analysis based method. The results, expressed in terms of high-to-low energy ratio, normalized median frequency, spectral power difference and normalized average rectified value, suggest that the proposed method enables better ECG-EMG separation quality than the reference methods. Copyright © 2015 IPEM. Published by Elsevier Ltd. All rights reserved.

Nonparametric Signal Extraction and Measurement Error in the Analysis of Electroencephalographic Activity During Sleep

PubMed Central

Crainiceanu, Ciprian M.; Caffo, Brian S.; Di, Chong-Zhi; Punjabi, Naresh M.

2009-01-01

We introduce methods for signal and associated variability estimation based on hierarchical nonparametric smoothing with application to the Sleep Heart Health Study (SHHS). SHHS is the largest electroencephalographic (EEG) collection of sleep-related data, which contains, at each visit, two quasi-continuous EEG signals for each subject. The signal features extracted from EEG data are then used in second level analyses to investigate the relation between health, behavioral, or biometric outcomes and sleep. Using subject specific signals estimated with known variability in a second level regression becomes a nonstandard measurement error problem. We propose and implement methods that take into account cross-sectional and longitudinal measurement error. The research presented here forms the basis for EEG signal processing for the SHHS. PMID:20057925

7 CFR 985.4 - Spearmint oil.

Code of Federal Regulations, 2011 CFR

2011-01-01

... oil. Spearmint oil, hereinafter referred to as oil, means essential oil extracted by distillation from... classes: Class 1: Oil extracted from the first cutting of Scotch Spearmint. Class 2: Oil extracted from the second cutting of Scotch Spearmint. Class 3: Oil extracted from Native Spearmint. Class 4: Oil...

7 CFR 985.4 - Spearmint oil.

Code of Federal Regulations, 2012 CFR

2012-01-01

... oil. Spearmint oil, hereinafter referred to as oil, means essential oil extracted by distillation from... classes: Class 1: Oil extracted from the first cutting of Scotch Spearmint. Class 2: Oil extracted from the second cutting of Scotch Spearmint. Class 3: Oil extracted from Native Spearmint. Class 4: Oil...

7 CFR 985.4 - Spearmint oil.

Code of Federal Regulations, 2013 CFR

2013-01-01

... oil. Spearmint oil, hereinafter referred to as oil, means essential oil extracted by distillation from... classes: Class 1: Oil extracted from the first cutting of Scotch Spearmint. Class 2: Oil extracted from the second cutting of Scotch Spearmint. Class 3: Oil extracted from Native Spearmint. Class 4: Oil...

7 CFR 985.4 - Spearmint oil.

Code of Federal Regulations, 2014 CFR

2014-01-01

... oil. Spearmint oil, hereinafter referred to as oil, means essential oil extracted by distillation from... classes: Class 1: Oil extracted from the first cutting of Scotch Spearmint. Class 2: Oil extracted from the second cutting of Scotch Spearmint. Class 3: Oil extracted from Native Spearmint. Class 4: Oil...

A COMPARISON OF AUTOMATED AND TRADITIONAL METHODS FOR THE EXTRACTION OF ARSENICALS FROM FISH

EPA Science Inventory

An automated extractor employing accelerated solvent extraction (ASE) has been compared with a traditional sonication method of extraction for the extraction of arsenicals from fish tissue. Four different species of fish and a standard reference material, DORM-2, were subjected t...

A novel speech-processing strategy incorporating tonal information for cochlear implants.

PubMed

Lan, N; Nie, K B; Gao, S K; Zeng, F G

2004-05-01

Good performance in cochlear implant users depends in large part on the ability of a speech processor to effectively decompose speech signals into multiple channels of narrow-band electrical pulses for stimulation of the auditory nerve. Speech processors that extract only envelopes of the narrow-band signals (e.g., the continuous interleaved sampling (CIS) processor) may not provide sufficient information to encode the tonal cues in languages such as Chinese. To improve the performance in cochlear implant users who speak tonal language, we proposed and developed a novel speech-processing strategy, which extracted both the envelopes of the narrow-band signals and the fundamental frequency (F0) of the speech signal, and used them to modulate both the amplitude and the frequency of the electrical pulses delivered to stimulation electrodes. We developed an algorithm to extract the fundatmental frequency and identified the general patterns of pitch variations of four typical tones in Chinese speech. The effectiveness of the extraction algorithm was verified with an artificial neural network that recognized the tonal patterns from the extracted F0 information. We then compared the novel strategy with the envelope-extraction CIS strategy in human subjects with normal hearing. The novel strategy produced significant improvement in perception of Chinese tones, phrases, and sentences. This novel processor with dynamic modulation of both frequency and amplitude is encouraging for the design of a cochlear implant device for sensorineurally deaf patients who speak tonal languages.

Phase-locking of a 2.7-THz Quantum Cascade Laser to a Microwave Reference

NASA Astrophysics Data System (ADS)

Baryshev, A. M.; Khosropanah, P.; Zhang, W.; Jellema, W.; Hovenier, J. N.; Gao, J. R.; Klapwijk, T. M.; Paveliev, D. G.; William, B. S.; Kumar, S.; Hu, Q.; Reno, J. L.; Klein, B.; Hesler, J. L.

2009-04-01

We demonstrate phase-locking of a 2.7-THz metal-metal waveguide quantum cascade laser (QCL) to an external microwave signal. The reference is the 15th harmonic, generated by a semiconductor superlattice nonlinear device, of a signal at 182 GHz, which itself is generated by a multiplier-chain (x2x3x2) from a microwave synthesizer at 15 GHz. Both laser and reference radiations are coupled into a hot electron bolometer mixer, resulting in a beat signal, which is fed into a phase-lock loop. Spectral analysis of the beat signal (see fig. 1) confirms that the QCL is phase locked. This result opens the possibility to extend heterodyne interferometers into the far-infrared range.

Differential capacitance probe for process control involving aqueous dielectric fluids

DOEpatents

Svoboda, John M.; Morrison, John L.

2002-10-08

A differential capacitance probe device for process control involving aqueous dielectric fluids is disclosed. The device contains a pair of matched capacitor probes configured in parallel, one immersed in a sealed container of reference fluid, and the other immersed in the process fluid. The sealed container holding the reference fluid is also immersed in the process fluid, hence both probes are operated at the same temperature. Signal conditioning measures the difference in capacitance between the reference probe and the process probe. The resulting signal is a control error signal that can be used to control the process.

Adjustable electronic load-alarm relay

DOEpatents

Mason, Charles H.; Sitton, Roy S.

1976-01-01

This invention is an improved electronic alarm relay for monitoring the current drawn by an AC motor or other electrical load. The circuit is designed to measure the load with high accuracy and to have excellent alarm repeatability. Chattering and arcing of the relay contacts are minimal. The operator can adjust the set point easily and can re-set both the high and the low alarm points by means of one simple adjustment. The relay includes means for generating a signal voltage proportional to the motor current. In a preferred form of the invention a first operational amplifier is provided to generate a first constant reference voltage which is higher than a preselected value of the signal voltage. A second operational amplifier is provided to generate a second constant reference voltage which is lower than the aforementioned preselected value of the signal voltage. A circuit comprising a first resistor serially connected to a second resistor is connected across the outputs of the first and second amplifiers, and the junction of the two resistors is connected to the inverting terminal of the second amplifier. Means are provided to compare the aforementioned signal voltage with both the first and second reference voltages and to actuate an alarm if the signal voltage is higher than the first reference voltage or lower than the second reference voltage.

Hydraulophones: Acoustic musical instruments and expressive user interfaces

NASA Astrophysics Data System (ADS)

Janzen, Ryan E.

Fluid flow creates an expansive range of acoustic possibilities, particularly in the case of water, which has unique turbulence and vortex shedding properties as compared with the air of ordinary wind instruments. Sound from water flow is explained with reference to a new class of musical instruments, hydraulophones, in which oscillation originates directly from matter in its liquid state. Several hydraulophones which were realized in practical form are described. A unique user-interface consisting of a row of water jets is presented, in terms of its expressiveness, tactility, responsiveness to derivatives and integrals of displacement, and in terms of the direct physical interaction between a user and the physical process of sound production. Signal processing algorithms are introduced, which extract further information from turbulent water flow, for industrial applications as well as musical applications.

Real-time system for extracting and monitoring the cerebral functional component during fNIRS measurements

NASA Astrophysics Data System (ADS)

Yamada, Toru; Ohashi, Mitsuo; Umeyama, Shinji

2015-12-01

Functional near-infrared spectroscopy (fNIRS) can non-invasively detect hemodynamic changes associated with cerebral neural activation in human subjects. However, its signal is often affected by changes in the optical characteristics of tissues in the head other than brain. To conduct fNIRS measurements precisely and efficiently, the extraction and realtime monitoring of the cerebral functional component is crucial. We previously developed methods for extracting the cerebral functional component—the multidistance optode arrangement (MD) method and the hemodynamic modality separation (HMS) method. In this study, we implemented these methods in a software used with the fNIRS system OEG- 17APD (Spectratech, Japan), and realized a real-time display of the extracted results. When using this system for human subject experiments, the baselines obtained with the MD and HMS methods were highly stabilized, whereas originally, the fNIRS signal fluctuated significantly when the subject moved. Through a functional experiment with repetitive single-sided hand clasping tasks, the extracted signals showed distinctively higher reproducibility than that obtained in the conventional measurements.

Compact self-contained electrical-to-optical converter/transmitter

DOEpatents

Seligmann, D.A.; Moss, W.C.; Valk, T.C.; Conder, A.D.

1995-11-21

A first optical receiver and a second optical receiver are provided for receiving a calibrate command and a power switching signal, respectively, from a remote processor. A third receiver is provided for receiving an analog electrical signal from a transducer. A calibrator generates a reference signal in response to the calibrate command. A combiner mixes the electrical signal with the reference signal to form a calibrated signal. A converter converts the calibrated signal to an optical signal. A transmitter transmits the optical signal to the remote processor. A primary battery supplies power to the calibrator, the combiner, the converter, and the transmitter. An optically-activated switch supplies power to the calibrator, the combiner, the converter, and the transmitter in response to the power switching signal. An auxiliary battery supplies power continuously to the switch. 13 figs.

Measurement of absolute concentrations of individual compounds in metabolite mixtures by gradient-selective time-zero 1H-13C HSQC with two concentration references and fast maximum likelihood reconstruction analysis.

PubMed

Hu, Kaifeng; Ellinger, James J; Chylla, Roger A; Markley, John L

2011-12-15

Time-zero 2D (13)C HSQC (HSQC(0)) spectroscopy offers advantages over traditional 2D NMR for quantitative analysis of solutions containing a mixture of compounds because the signal intensities are directly proportional to the concentrations of the constituents. The HSQC(0) spectrum is derived from a series of spectra collected with increasing repetition times within the basic HSQC block by extrapolating the repetition time to zero. Here we present an alternative approach to data collection, gradient-selective time-zero (1)H-(13)C HSQC(0) in combination with fast maximum likelihood reconstruction (FMLR) data analysis and the use of two concentration references for absolute concentration determination. Gradient-selective data acquisition results in cleaner spectra, and NMR data can be acquired in both constant-time and non-constant-time mode. Semiautomatic data analysis is supported by the FMLR approach, which is used to deconvolute the spectra and extract peak volumes. The peak volumes obtained from this analysis are converted to absolute concentrations by reference to the peak volumes of two internal reference compounds of known concentration: DSS (4,4-dimethyl-4-silapentane-1-sulfonic acid) at the low concentration limit (which also serves as chemical shift reference) and MES (2-(N-morpholino)ethanesulfonic acid) at the high concentration limit. The linear relationship between peak volumes and concentration is better defined with two references than with one, and the measured absolute concentrations of individual compounds in the mixture are more accurate. We compare results from semiautomated gsHSQC(0) with those obtained by the original manual phase-cycled HSQC(0) approach. The new approach is suitable for automatic metabolite profiling by simultaneous quantification of multiple metabolites in a complex mixture.

Locating and parsing bibliographic references in HTML medical articles

PubMed Central

Zou, Jie; Le, Daniel; Thoma, George R.

2010-01-01

The set of references that typically appear toward the end of journal articles is sometimes, though not always, a field in bibliographic (citation) databases. But even if references do not constitute such a field, they can be useful as a preprocessing step in the automated extraction of other bibliographic data from articles, as well as in computer-assisted indexing of articles. Automation in data extraction and indexing to minimize human labor is key to the affordable creation and maintenance of large bibliographic databases. Extracting the components of references, such as author names, article title, journal name, publication date and other entities, is therefore a valuable and sometimes necessary task. This paper describes a two-step process using statistical machine learning algorithms, to first locate the references in HTML medical articles and then to parse them. Reference locating identifies the reference section in an article and then decomposes it into individual references. We formulate this step as a two-class classification problem based on text and geometric features. An evaluation conducted on 500 articles drawn from 100 medical journals achieves near-perfect precision and recall rates for locating references. Reference parsing identifies the components of each reference. For this second step, we implement and compare two algorithms. One relies on sequence statistics and trains a Conditional Random Field. The other focuses on local feature statistics and trains a Support Vector Machine to classify each individual word, followed by a search algorithm that systematically corrects low confidence labels if the label sequence violates a set of predefined rules. The overall performance of these two reference-parsing algorithms is about the same: above 99% accuracy at the word level, and over 97% accuracy at the chunk level. PMID:20640222

Locating and parsing bibliographic references in HTML medical articles.

PubMed

Zou, Jie; Le, Daniel; Thoma, George R

2010-06-01

The set of references that typically appear toward the end of journal articles is sometimes, though not always, a field in bibliographic (citation) databases. But even if references do not constitute such a field, they can be useful as a preprocessing step in the automated extraction of other bibliographic data from articles, as well as in computer-assisted indexing of articles. Automation in data extraction and indexing to minimize human labor is key to the affordable creation and maintenance of large bibliographic databases. Extracting the components of references, such as author names, article title, journal name, publication date and other entities, is therefore a valuable and sometimes necessary task. This paper describes a two-step process using statistical machine learning algorithms, to first locate the references in HTML medical articles and then to parse them. Reference locating identifies the reference section in an article and then decomposes it into individual references. We formulate this step as a two-class classification problem based on text and geometric features. An evaluation conducted on 500 articles drawn from 100 medical journals achieves near-perfect precision and recall rates for locating references. Reference parsing identifies the components of each reference. For this second step, we implement and compare two algorithms. One relies on sequence statistics and trains a Conditional Random Field. The other focuses on local feature statistics and trains a Support Vector Machine to classify each individual word, followed by a search algorithm that systematically corrects low confidence labels if the label sequence violates a set of predefined rules. The overall performance of these two reference-parsing algorithms is about the same: above 99% accuracy at the word level, and over 97% accuracy at the chunk level.

Features extraction of EMG signal using time domain analysis for arm rehabilitation device

NASA Astrophysics Data System (ADS)

Jali, Mohd Hafiz; Ibrahim, Iffah Masturah; Sulaima, Mohamad Fani; Bukhari, W. M.; Izzuddin, Tarmizi Ahmad; Nasir, Mohamad Na'im

2015-05-01

Rehabilitation device is used as an exoskeleton for people who had failure of their limb. Arm rehabilitation device may help the rehab program whom suffers from arm disability. The device that is used to facilitate the tasks of the program should improve the electrical activity in the motor unit and minimize the mental effort of the user. Electromyography (EMG) is the techniques to analyze the presence of electrical activity in musculoskeletal systems. The electrical activity in muscles of disable person is failed to contract the muscle for movements. In order to prevent the muscles from paralysis becomes spasticity, the force of movements should minimize the mental efforts. Therefore, the rehabilitation device should analyze the surface EMG signal of normal people that can be implemented to the device. The signal is collected according to procedure of surface electromyography for non-invasive assessment of muscles (SENIAM). The EMG signal is implemented to set the movements' pattern of the arm rehabilitation device. The filtered EMG signal was extracted for features of Standard Deviation (STD), Mean Absolute Value (MAV) and Root Mean Square (RMS) in time-domain. The extraction of EMG data is important to have the reduced vector in the signal features with less of error. In order to determine the best features for any movements, several trials of extraction methods are used by determining the features with less of errors. The accurate features can be use for future works of rehabilitation control in real-time.

Transmit-reference methods in software defined radio platforms for communication in harsh propagation environments and systems thereof

DOEpatents

Dowla, Farid U; Nekoogar, Faranak

2015-03-03

A method for adaptive Radio Frequency (RF) jamming according to one embodiment includes dynamically monitoring a RF spectrum; detecting any undesired signals in real time from the RF spectrum; and sending a directional countermeasure signal to jam the undesired signals. A method for adaptive Radio Frequency (RF) communications according to another embodiment includes transmitting a data pulse in a RF spectrum; and transmitting a reference pulse separated by a predetermined period of time from the data pulse; wherein the data pulse is modulated with data, wherein the reference pulse is unmodulated. A method for adaptive Radio Frequency (RF) communications according to yet another embodiment includes receiving a data pulse in a RF spectrum; and receiving a reference pulse separated in time from the data pulse, wherein the data pulse is modulated with data, wherein the reference pulse is unmodulated; and demodulating the pulses.

Transmit-reference methods in software defined radio platforms for communication in harsh propagation environments and systems thereof

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

Dowla, Farid; Nekoogar, Faranak

A method for adaptive Radio Frequency (RF) jamming according to one embodiment includes dynamically monitoring a RF spectrum; detecting any undesired signals in real time from the RF spectrum; and sending a directional countermeasure signal to jam the undesired signals. A method for adaptive Radio Frequency (RF) communications according to another embodiment includes transmitting a data pulse in a RF spectrum; and transmitting a reference pulse separated by a predetermined period of time from the data pulse; wherein the data pulse is modulated with data, wherein the reference pulse is unmodulated. A method for adaptive Radio Frequency (RF) communications accordingmore » to yet another embodiment includes receiving a data pulse in a RF spectrum; and receiving a reference pulse separated in time from the data pulse, wherein the data pulse is modulated with data, wherein the reference pulse is unmodulated; and demodulating the pulses.« less

Non-invasive assessment of skeletal muscle activity

NASA Astrophysics Data System (ADS)

Merletti, Roberto; Orizio, Claudio; di Prampero, Pietro E.; Tesch, Per

2005-10-01

After the first 3 years (2002-2005), the MAP project has made available: - systems fo electrodes, signal conditioning and digital processing for multichannel simultaneously-detected EMG and MMG as well as for simultaneous electrical stimulation and EMG detection with artifact cancellation. - innovative non-invasive techniques for the extraction of individual motor unit action potentials (MUAPS) and individual motor and MMG contributions from the surface EMG interference signal and the MMG signal. - processing techniques for extractions of indicators of progressive fatigue from the electrically-elicited (M-wave) EMG signal. - techniques for the analysis of dynamic multichannel EMG during cyclic or explosive exercise (in collaboration with project EXER/MAP-MED-027).

Trend extraction using empirical mode decomposition and statistical empirical mode decomposition: Case study: Kuala Lumpur stock market

NASA Astrophysics Data System (ADS)

Jaber, Abobaker M.

2014-12-01

Two nonparametric methods for prediction and modeling of financial time series signals are proposed. The proposed techniques are designed to handle non-stationary and non-linearity behave and to extract meaningful signals for reliable prediction. Due to Fourier Transform (FT), the methods select significant decomposed signals that will be employed for signal prediction. The proposed techniques developed by coupling Holt-winter method with Empirical Mode Decomposition (EMD) and it is Extending the scope of empirical mode decomposition by smoothing (SEMD). To show performance of proposed techniques, we analyze daily closed price of Kuala Lumpur stock market index.

An energy ratio feature extraction method for optical fiber vibration signal

NASA Astrophysics Data System (ADS)

Sheng, Zhiyong; Zhang, Xinyan; Wang, Yanping; Hou, Weiming; Yang, Dan

2018-03-01

The intrusion events in the optical fiber pre-warning system (OFPS) are divided into two types which are harmful intrusion event and harmless interference event. At present, the signal feature extraction methods of these two types of events are usually designed from the view of the time domain. However, the differences of time-domain characteristics for different harmful intrusion events are not obvious, which cannot reflect the diversity of them in detail. We find that the spectrum distribution of different intrusion signals has obvious differences. For this reason, the intrusion signal is transformed into the frequency domain. In this paper, an energy ratio feature extraction method of harmful intrusion event is drawn on. Firstly, the intrusion signals are pre-processed and the power spectral density (PSD) is calculated. Then, the energy ratio of different frequency bands is calculated, and the corresponding feature vector of each type of intrusion event is further formed. The linear discriminant analysis (LDA) classifier is used to identify the harmful intrusion events in the paper. Experimental results show that the algorithm improves the recognition rate of the intrusion signal, and further verifies the feasibility and validity of the algorithm.

Heart rate calculation from ensemble brain wave using wavelet and Teager-Kaiser energy operator.

PubMed

Srinivasan, Jayaraman; Adithya, V

2015-01-01

Electroencephalogram (EEG) signal artifacts are caused by various factors, such as, Electro-oculogram (EOG), Electromyogram (EMG), Electrocardiogram (ECG), movement artifact and line interference. The relatively high electrical energy cardiac activity causes EEG artifacts. In EEG signal processing the general approach is to remove the ECG signal. In this paper, we introduce an automated method to extract the ECG signal from EEG using wavelet and Teager-Kaiser energy operator for R-peak enhancement and detection. From the detected R-peaks the heart rate (HR) is calculated for clinical diagnosis. To check the efficiency of our method, we compare the HR calculated from ECG signal recorded in synchronous with EEG. The proposed method yields a mean error of 1.4% for the heart rate and 1.7% for mean R-R interval. The result illustrates that, proposed method can be used for ECG extraction from single channel EEG and used in clinical diagnosis like estimation for stress analysis, fatigue, and sleep stages classification studies as a multi-model system. In addition, this method eliminates the dependence of additional synchronous ECG in extraction of ECG from EEG signal process.

Two-dimensional wavelet analysis based classification of gas chromatogram differential mobility spectrometry signals.

PubMed

Zhao, Weixiang; Sankaran, Shankar; Ibáñez, Ana M; Dandekar, Abhaya M; Davis, Cristina E

2009-08-04

This study introduces two-dimensional (2-D) wavelet analysis to the classification of gas chromatogram differential mobility spectrometry (GC/DMS) data which are composed of retention time, compensation voltage, and corresponding intensities. One reported method to process such large data sets is to convert 2-D signals to 1-D signals by summing intensities either across retention time or compensation voltage, but it can lose important signal information in one data dimension. A 2-D wavelet analysis approach keeps the 2-D structure of original signals, while significantly reducing data size. We applied this feature extraction method to 2-D GC/DMS signals measured from control and disordered fruit and then employed two typical classification algorithms to testify the effects of the resultant features on chemical pattern recognition. Yielding a 93.3% accuracy of separating data from control and disordered fruit samples, 2-D wavelet analysis not only proves its feasibility to extract feature from original 2-D signals but also shows its superiority over the conventional feature extraction methods including converting 2-D to 1-D and selecting distinguishable pixels from training set. Furthermore, this process does not require coupling with specific pattern recognition methods, which may help ensure wide applications of this method to 2-D spectrometry data.

Radio frequency coupling apparatus and method for measuring minority carrier lifetimes in semiconductor materials

DOEpatents

Johnston, Steven W.; Ahrenkiel, Richard K.

2002-01-01

An apparatus for measuring the minority carrier lifetime of a semiconductor sample using radio-frequency coupling. The measuring apparatus includes an antenna that is positioned a coupling distance from a semiconductor sample which is exposed to light pulses from a laser during sampling operations. A signal generator is included to generate high frequency, such as 900 MHz or higher, sinusoidal waveform signals that are split into a reference signal and a sample signal. The sample signal is transmitted into a sample branch circuit where it passes through a tuning capacitor and a coaxial cable prior to reaching the antenna. The antenna is radio-frequency coupled with the adjacent sample and transmits the sample signal, or electromagnetic radiation corresponding to the sample signal, to the sample and receives reflected power or a sample-coupled-photoconductivity signal back. To lower impedance and speed system response, the impedance is controlled by limiting impedance in the coaxial cable and the antenna reactance. In one embodiment, the antenna is a waveguide/aperture hybrid antenna having a central transmission line and an adjacent ground flange. The sample-coupled-photoconductivity signal is then transmitted to a mixer which also receives the reference signal. To enhance the sensitivity of the measuring apparatus, the mixer is operated to phase match the reference signal and the sample-coupled-photoconductivity signal.

Asymptotic Cramer-Rao bounds for Morlet wavelet filter bank transforms of FM signals

NASA Astrophysics Data System (ADS)

Scheper, Richard

2002-03-01

Wavelet filter banks are potentially useful tools for analyzing and extracting information from frequency modulated (FM) signals in noise. Chief among the advantages of such filter banks is the tendency of wavelet transforms to concentrate signal energy while simultaneously dispersing noise energy over the time-frequency plane, thus raising the effective signal to noise ratio of filtered signals. Over the past decade, much effort has gone into devising new algorithms to extract the relevant information from transformed signals while identifying and discarding the transformed noise. Therefore, estimates of the ultimate performance bounds on such algorithms would serve as valuable benchmarks in the process of choosing optimal algorithms for given signal classes. Discussed here is the specific case of FM signals analyzed by Morlet wavelet filter banks. By making use of the stationary phase approximation of the Morlet transform, and assuming that the measured signals are well resolved digitally, the asymptotic form of the Fisher Information Matrix is derived. From this, Cramer-Rao bounds are analytically derived for simple cases.

Utilization of optimized BCR three-step sequential and dilute HCl single extraction procedures for soil-plant metal transfer predictions in contaminated lands.

PubMed

Kubová, Jana; Matús, Peter; Bujdos, Marek; Hagarová, Ingrid; Medved', Ján

2008-05-30

The prediction of soil metal phytoavailability using the chemical extractions is a conventional approach routinely used in soil testing. The adequacy of such soil tests for this purpose is commonly assessed through a comparison of extraction results with metal contents in relevant plants. In this work, the fractions of selected risk metals (Al, As, Cd, Cu, Fe, Mn, Ni, Pb, Zn) that can be taken up by various plants were obtained by optimized BCR (Community Bureau of Reference) three-step sequential extraction procedure (SEP) and by single 0.5 mol L(-1) HCl extraction. These procedures were validated using five soil and sediment reference materials (SRM 2710, SRM 2711, CRM 483, CRM 701, SRM RTH 912) and applied to significantly different acidified soils for the fractionation of studied metals. The new indicative values of Al, Cd, Cu, Fe, Mn, P, Pb and Zn fractional concentrations for these reference materials were obtained by the dilute HCl single extraction. The influence of various soil genesis, content of essential elements (Ca, Mg, K, P) and different anthropogenic sources of acidification on extraction yields of individual risk metal fractions was investigated. The concentrations of studied elements were determined by atomic spectrometry methods (flame, graphite furnace and hydride generation atomic absorption spectrometry and inductively coupled plasma optical emission spectrometry). It can be concluded that the data of extraction yields from first BCR SEP acid extractable step and soil-plant transfer coefficients can be applied to the prediction of qualitative mobility of selected risk metals in different soil systems.

Signal processing method and system for noise removal and signal extraction

DOEpatents

Fu, Chi Yung; Petrich, Loren

2009-04-14

A signal processing method and system combining smooth level wavelet pre-processing together with artificial neural networks all in the wavelet domain for signal denoising and extraction. Upon receiving a signal corrupted with noise, an n-level decomposition of the signal is performed using a discrete wavelet transform to produce a smooth component and a rough component for each decomposition level. The n.sup.th level smooth component is then inputted into a corresponding neural network pre-trained to filter out noise in that component by pattern recognition in the wavelet domain. Additional rough components, beginning at the highest level, may also be retained and inputted into corresponding neural networks pre-trained to filter out noise in those components also by pattern recognition in the wavelet domain. In any case, an inverse discrete wavelet transform is performed on the combined output from all the neural networks to recover a clean signal back in the time domain.

Performance of regional oxygen saturation monitoring by near-infrared spectroscopy (NIRS) in pediatric inter-hospital transports with special reference to air ambulance transports: a methodological study.

PubMed

Hamrin, Tova Hannegård; Radell, Peter J; Fläring, Urban; Berner, Jonas; Eksborg, Staffan

2017-12-28

The aim of the present study was to evaluate the performance of regional oxygen saturation (rSO 2 ) monitoring with near infrared spectroscopy (NIRS) during pediatric inter-hospital transports and to optimize processing of the electronically stored data. Cerebral (rSO 2 -C) and abdominal (rSO 2 -A) NIRS sensors were used during transport in air ambulance and connecting ground ambulance. Data were electronically stored by the monitor during transport, extracted and analyzed off-line after the transport. After removal of all zero and floor effect values, the Savitzky-Golay algorithm of data smoothing was applied on the NIRS-signal. The second order of smoothing polynomial was used and the optimal number of neighboring points for the smoothing procedure was evaluated. NIRS-data from 38 pediatric patients was examined. Reliability, defined as measurements without values of 0 or 15%, was acceptable during transport (> 90% of all measurements). There were, however, individual patients with < 90% reliable measurements during transport, while no patient was found to have < 90% reliable measurements in hospital. Satisfactory noise reduction of the signal, without distortion of the underlying information, was achieved when 20-50 neighbors ("window-size") were used. The use of NIRS for measuring rSO 2 in clinical studies during pediatric transport in ground and air-ambulance is feasible but hampered by unreliable values and signal interference. By applying the Savitzky-Golay algorithm, the signal-to-noise ratio was improved and enabled better post-hoc signal evaluation.

Soil hydraulic material properties and layered architecture from time-lapse GPR

NASA Astrophysics Data System (ADS)

Jaumann, Stefan; Roth, Kurt

2018-04-01

Quantitative knowledge of the subsurface material distribution and its effective soil hydraulic material properties is essential to predict soil water movement. Ground-penetrating radar (GPR) is a noninvasive and nondestructive geophysical measurement method that is suitable to monitor hydraulic processes. Previous studies showed that the GPR signal from a fluctuating groundwater table is sensitive to the soil water characteristic and the hydraulic conductivity function. In this work, we show that the GPR signal originating from both the subsurface architecture and the fluctuating groundwater table is suitable to estimate the position of layers within the subsurface architecture together with the associated effective soil hydraulic material properties with inversion methods. To that end, we parameterize the subsurface architecture, solve the Richards equation, convert the resulting water content to relative permittivity with the complex refractive index model (CRIM), and solve Maxwell's equations numerically. In order to analyze the GPR signal, we implemented a new heuristic algorithm that detects relevant signals in the radargram (events) and extracts the corresponding signal travel time and amplitude. This algorithm is applied to simulated as well as measured radargrams and the detected events are associated automatically. Using events instead of the full wave regularizes the inversion focussing on the relevant measurement signal. For optimization, we use a global-local approach with preconditioning. Starting from an ensemble of initial parameter sets drawn with a Latin hypercube algorithm, we sequentially couple a simulated annealing algorithm with a Levenberg-Marquardt algorithm. The method is applied to synthetic as well as measured data from the ASSESS test site. We show that the method yields reasonable estimates for the position of the layers as well as for the soil hydraulic material properties by comparing the results to references derived from ground truth data as well as from time domain reflectometry (TDR).

Cell Wall Ultrastructure of Stem Wood, Roots, and Needles of a Conifer Varies in Response to Moisture Availability

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

Pattathil, Sivakumar; Ingwers, Miles W.; Victoriano, Olivia L.

The composition, integrity, and architecture of the macromolecular matrix of cell walls, collectively referred to as cell wall ultrastructure, exhibits variation across species and organs and among cell types within organs. Indirect approaches have suggested that modifications to cell wall ultrastructure occur in response to abiotic stress; however, modifications have not been directly observed. Glycome profiling was used to study cell wall ultrastructure by examining variation in composition and extractability of non-cellulosic glycans in cell walls of stem wood, roots, and needles of loblolly pine saplings exposed to high and low soil moisture. Soil moisture influenced physiological processes and themore » overall composition and extractability of cell wall components differed as a function of soil moisture treatments. The strongest response of cell wall ultrastructure to soil moisture was increased extractability of pectic backbone epitopes in the low soil moisture treatment. The higher abundance of these pectic backbone epitopes in the oxalate extract indicate that the loosening of cell wall pectic components could be associated with the release of pectic signals as a stress response. The increased extractability of pectic backbone epitopes in response to low soil moisture availability was more pronounced in stem wood than in roots or needles. Additional responses to low soil moisture availability were observed in lignin associated carbohydrates released in chlorite extracts of stem wood, including an increased abundance of pectic arabinogalactan epitopes. Overall, these results indicate that cell walls of loblolly pine organs undergo changes in their ultrastructural composition and extractability as a response to soil moisture availability and that cell walls of the stem wood are more responsive to low soil moisture availability compared to cell walls of roots and needles. In conclusion, to our knowledge, this is the first direct evidence, delineated by glycomic analyses, that abiotic stress affects cell wall ultrastructure. This study is also unique in that glycome profiling of pine needles has never before been reported.« less

Cell Wall Ultrastructure of Stem Wood, Roots, and Needles of a Conifer Varies in Response to Moisture Availability.

PubMed

Pattathil, Sivakumar; Ingwers, Miles W; Victoriano, Olivia L; Kandemkavil, Sindhu; McGuire, Mary Anne; Teskey, Robert O; Aubrey, Doug P

2016-01-01

The composition, integrity, and architecture of the macromolecular matrix of cell walls, collectively referred to as cell wall ultrastructure, exhibits variation across species and organs and among cell types within organs. Indirect approaches have suggested that modifications to cell wall ultrastructure occur in response to abiotic stress; however, modifications have not been directly observed. Glycome profiling was used to study cell wall ultrastructure by examining variation in composition and extractability of non-cellulosic glycans in cell walls of stem wood, roots, and needles of loblolly pine saplings exposed to high and low soil moisture. Soil moisture influenced physiological processes and the overall composition and extractability of cell wall components differed as a function of soil moisture treatments. The strongest response of cell wall ultrastructure to soil moisture was increased extractability of pectic backbone epitopes in the low soil moisture treatment. The higher abundance of these pectic backbone epitopes in the oxalate extract indicate that the loosening of cell wall pectic components could be associated with the release of pectic signals as a stress response. The increased extractability of pectic backbone epitopes in response to low soil moisture availability was more pronounced in stem wood than in roots or needles. Additional responses to low soil moisture availability were observed in lignin-associated carbohydrates released in chlorite extracts of stem wood, including an increased abundance of pectic arabinogalactan epitopes. Overall, these results indicate that cell walls of loblolly pine organs undergo changes in their ultrastructural composition and extractability as a response to soil moisture availability and that cell walls of the stem wood are more responsive to low soil moisture availability compared to cell walls of roots and needles. To our knowledge, this is the first direct evidence, delineated by glycomic analyses, that abiotic stress affects cell wall ultrastructure. This study is also unique in that glycome profiling of pine needles has never before been reported.

Cell Wall Ultrastructure of Stem Wood, Roots, and Needles of a Conifer Varies in Response to Moisture Availability

DOE PAGES

Pattathil, Sivakumar; Ingwers, Miles W.; Victoriano, Olivia L.; ...

2016-06-24

The composition, integrity, and architecture of the macromolecular matrix of cell walls, collectively referred to as cell wall ultrastructure, exhibits variation across species and organs and among cell types within organs. Indirect approaches have suggested that modifications to cell wall ultrastructure occur in response to abiotic stress; however, modifications have not been directly observed. Glycome profiling was used to study cell wall ultrastructure by examining variation in composition and extractability of non-cellulosic glycans in cell walls of stem wood, roots, and needles of loblolly pine saplings exposed to high and low soil moisture. Soil moisture influenced physiological processes and themore » overall composition and extractability of cell wall components differed as a function of soil moisture treatments. The strongest response of cell wall ultrastructure to soil moisture was increased extractability of pectic backbone epitopes in the low soil moisture treatment. The higher abundance of these pectic backbone epitopes in the oxalate extract indicate that the loosening of cell wall pectic components could be associated with the release of pectic signals as a stress response. The increased extractability of pectic backbone epitopes in response to low soil moisture availability was more pronounced in stem wood than in roots or needles. Additional responses to low soil moisture availability were observed in lignin associated carbohydrates released in chlorite extracts of stem wood, including an increased abundance of pectic arabinogalactan epitopes. Overall, these results indicate that cell walls of loblolly pine organs undergo changes in their ultrastructural composition and extractability as a response to soil moisture availability and that cell walls of the stem wood are more responsive to low soil moisture availability compared to cell walls of roots and needles. In conclusion, to our knowledge, this is the first direct evidence, delineated by glycomic analyses, that abiotic stress affects cell wall ultrastructure. This study is also unique in that glycome profiling of pine needles has never before been reported.« less

Albizia lebbeck suppresses histamine signaling by the inhibition of histamine H1 receptor and histidine decarboxylase gene transcriptions.

PubMed

Nurul, Islam Mohammed; Mizuguchi, Hiroyuki; Shahriar, Masum; Venkatesh, Pichairajan; Maeyama, Kazutaka; Mukherjee, Pulok K; Hattori, Masashi; Choudhuri, Mohamed Sahabuddin Kabir; Takeda, Noriaki; Fukui, Hiroyuki

2011-11-01

Histamine plays major roles in allergic diseases and its action is mediated mainly by histamine H(1) receptor (H1R). We have demonstrated that histamine signaling-related H1R and histidine decarboxylase (HDC) genes are allergic diseases sensitive genes and their expression level affects severity of the allergic symptoms. Therefore, compounds that suppress histamine signaling should be promising candidates as anti-allergic drugs. Here, we investigated the effect of the extract from the bark of Albizia lebbeck (AL), one of the ingredients of Ayruvedic medicines, on H1R and HDC gene expression using toluene-2,4-diisocyanate (TDI) sensitized allergy model rats and HeLa cells expressing endogenous H1R. Administration of the AL extract significantly decreased the numbers of sneezing and nasal rubbing. Pretreatment with the AL extract suppressed TDI-induced H1R and HDC mRNA elevations as well as [(3)H]mepyramine binding, HDC activity, and histamine content in the nasal mucosa. AL extract also suppressed TDI-induced up-regulation of IL-4, IL-5, and IL-13 mRNA. In HeLa cells, AL extract suppressed phorbol-12-myristate-13-acetate- or histamine-induced up-regulation of H1R mRNA. Our data suggest that AL alleviated nasal symptoms by inhibiting histamine signaling in TDI-sensitized rats through suppression of H1R and HDC gene transcriptions. Suppression of Th2-cytokine signaling by AL also suggests that it could affect the histamine-cytokine network. Copyright © 2011 Elsevier B.V. All rights reserved.

Feature Extraction from Subband Brain Signals and Its Classification

NASA Astrophysics Data System (ADS)

Mukul, Manoj Kumar; Matsuno, Fumitoshi

This paper considers both the non-stationarity as well as independence/uncorrelated criteria along with the asymmetry ratio over the electroencephalogram (EEG) signals and proposes a hybrid approach of the signal preprocessing methods before the feature extraction. A filter bank approach of the discrete wavelet transform (DWT) is used to exploit the non-stationary characteristics of the EEG signals and it decomposes the raw EEG signals into the subbands of different center frequencies called as rhythm. A post processing of the selected subband by the AMUSE algorithm (a second order statistics based ICA/BSS algorithm) provides the separating matrix for each class of the movement imagery. In the subband domain the orthogonality as well as orthonormality criteria over the whitening matrix and separating matrix do not come respectively. The human brain has an asymmetrical structure. It has been observed that the ratio between the norms of the left and right class separating matrices should be different for better discrimination between these two classes. The alpha/beta band asymmetry ratio between the separating matrices of the left and right classes will provide the condition to select an appropriate multiplier. So we modify the estimated separating matrix by an appropriate multiplier in order to get the required asymmetry and extend the AMUSE algorithm in the subband domain. The desired subband is further subjected to the updated separating matrix to extract subband sub-components from each class. The extracted subband sub-components sources are further subjected to the feature extraction (power spectral density) step followed by the linear discriminant analysis (LDA).

Paprika (Capsicum annuum) oleoresin extraction with supercritical carbon dioxide.

PubMed

Jarén-Galán, M; Nienaber, U; Schwartz, S J

1999-09-01

Paprika oleoresin was fractionated by extraction with supercritical carbon dioxide (SCF-CO(2)). Higher extraction volumes, increasing extraction pressures, and similarly, the use of cosolvents such as 1% ethanol or acetone resulted in higher pigment yields. Within the 2000-7000 psi range, total oleoresin yield always approached 100%. Pigments isolated at lower pressures consisted almost exclusively of beta-carotene, while pigments obtained at higher pressures contained a greater proportion of red carotenoids (capsorubin, capsanthin, zeaxanthin, beta-cryptoxanthin) and small amounts of beta-carotene. The varying solubility of oil and pigments in SCF-CO(2) was optimized to obtain enriched and concentrated oleoresins through a two-stage extraction at 2000 and 6000 psi. This technique removes the paprika oil and beta-carotene during the first extraction step, allowing for second-stage oleoresin extracts with a high pigment concentration (200% relative to the reference) and a red:yellow pigment ratio of 1.8 (as compared to 1.3 in the reference).

Extraction of motor activity from the cervical spinal cord of behaving rats

NASA Astrophysics Data System (ADS)

Prasad, Abhishek; Sahin, Mesut

2006-12-01

Injury at the cervical region of the spinal cord results in the loss of the skeletal muscle control from below the shoulders and hence causes quadriplegia. The brain-computer interface technique is one way of generating a substitute for the lost command signals in these severely paralyzed individuals using the neural signals from the brain. In this study, we are investigating the feasibility of an alternative method where the volitional signals are extracted from the cervical spinal cord above the point of injury. A microelectrode array assembly was implanted chronically at the C5-C6 level of the spinal cord in rats. Neural recordings were made during the face cleaning behavior with forelimbs as this task involves cyclic forelimb movements and does not require any training. The correlation between the volitional motor signals and the elbow movements was studied. Linear regression technique was used to reconstruct the arm movement from the rectified-integrated version of the principal neural components. The results of this study demonstrate the feasibility of extracting the motor signals from the cervical spinal cord and using them for reconstruction of the elbow movements.

Surface potential extraction from electrostatic and Kelvin-probe force microscopy images

NASA Astrophysics Data System (ADS)

Xu, Jie; Chen, Deyuan; Li, Wei; Xu, Jun

2018-05-01

A comprehensive comparison study of electrostatic force microscopy (EFM) and Kelvin probe force microscopy (KPFM) is conducted in this manuscript. First, it is theoretically demonstrated that for metallic or semiconductor samples, both the EFM and KPFM signals are a convolution of the sample surface potential with their respective transfer functions. Then, an equivalent point-mass model describing cantilever deflection under distributed loads is developed to reevaluate the cantilever influence on detection signals, and it is shown that the cantilever has no influence on the EFM signal, while it will affect the KPFM signal intensity but not change the resolution. Finally, EFM and KPFM experiments are carried out, and the surface potential is extracted from the EFM and KPFM images by deconvolution processing, respectively. The extracted potential intensity is well consistent with each other and the detection resolution also complies with the theoretical analysis. Our work is helpful to perform a quantitative analysis of EFM and KPFM signals, and the developed point-mass model can also be used for other cantilever beam deflection problems.

Combined distributed and concentrated transducer network for failure indication

NASA Astrophysics Data System (ADS)

Ostachowicz, Wieslaw; Wandowski, Tomasz; Malinowski, Pawel

2010-03-01

In this paper algorithm for discontinuities localisation in thin panels made of aluminium alloy is presented. Mentioned algorithm uses Lamb wave propagation methods for discontinuities localisation. Elastic waves were generated and received using piezoelectric transducers. They were arranged in concentrated arrays distributed on the specimen surface. In this way almost whole specimen could be monitored using this combined distributed-concentrated transducer network. Excited elastic waves propagate and reflect from panel boundaries and discontinuities existing in the panel. Wave reflection were registered through the piezoelectric transducers and used in signal processing algorithm. Proposed processing algorithm consists of two parts: signal filtering and extraction of obstacles location. The first part was used in order to enhance signals by removing noise from them. Second part allowed to extract features connected with wave reflections from discontinuities. Extracted features damage influence maps were a basis to create damage influence maps. Damage maps indicated intensity of elastic wave reflections which corresponds to obstacles coordinates. Described signal processing algorithms were implemented in the MATLAB environment. It should be underlined that in this work results based only on experimental signals were presented.

The Pursuit of Word Meanings

PubMed Central

Stevens, Jon Scott; Gleitman, Lila R.; Trueswell, John C.; Yang, Charles

2016-01-01

We evaluate here the performance of four models of cross-situational word learning; two global models, which extract and retain multiple referential alternatives from each word occurrence; and two local models, which extract just a single referent from each occurrence. One of these local models, dubbed Pursuit, uses an associative learning mechanism to estimate word-referent probability but pursues and tests the best referent-meaning at any given time. Pursuit is found to perform as well as global models under many conditions extracted from naturalistic corpora of parent child-interactions, even though the model maintains far less information than global models. Moreover, Pursuit is found to best capture human experimental findings from several relevant cross-situational word-learning experiments, including those of Yu and Smith (2007), the paradigm example of a finding believed to support fully global cross-situational models. Implications and limitations of these results are discussed, most notably that the model characterizes only the earliest stages of word learning, when reliance on the co-occurring referent world is at its greatest. PMID:27666335

Urtica dioica modulates hippocampal insulin signaling and recognition memory deficit in streptozotocin induced diabetic mice.

PubMed

Patel, Sita Sharan; Gupta, Sahil; Udayabanu, Malairaman

2016-06-01

Diabetes mellitus has been associated with functional abnormalities in the hippocampus and performance of cognitive function. Urtica dioica (UD) has been used in the treatment of diabetes. In our previous report we observed that UD extract attenuate diabetes mediated associative and spatial memory dysfunction. The present study aimed to evaluate the effect of UD extract on mouse model of diabetes-induced recognition memory deficit and explore the possible mechanism behind it. Streptozotocin (STZ) (50 mg/kg, i.p. consecutively for 5 days) was used to induce diabetes followed by UD extract (50 mg/kg, oral) or rosiglitazone (ROSI) (5 mg/kg, oral) administration for 8 weeks. STZ induced diabetic mice showed significant decrease in hippocampal insulin signaling and translocation of glucose transporter type 4 (GLUT4) to neuronal membrane resulting in cognitive dysfunction and hypolocomotion. UD treatment effectively improved hippocampal insulin signaling, glucose tolerance and recognition memory performance in diabetic mice, which was comparable to ROSI. Further, diabetes mediated oxidative stress and inflammation was reversed by chronic UD or ROSI administration. UD leaves extract acts via insulin signaling pathway and might prove to be effective for the diabetes mediated central nervous system complications.

LISA Framework for Enhancing Gravitational Wave Signal Extraction Techniques

NASA Technical Reports Server (NTRS)

Thompson, David E.; Thirumalainambi, Rajkumar

2006-01-01

This paper describes the development of a Framework for benchmarking and comparing signal-extraction and noise-interference-removal methods that are applicable to interferometric Gravitational Wave detector systems. The primary use is towards comparing signal and noise extraction techniques at LISA frequencies from multiple (possibly confused) ,gravitational wave sources. The Framework includes extensive hybrid learning/classification algorithms, as well as post-processing regularization methods, and is based on a unique plug-and-play (component) architecture. Published methods for signal extraction and interference removal at LISA Frequencies are being encoded, as well as multiple source noise models, so that the stiffness of GW Sensitivity Space can be explored under each combination of methods. Furthermore, synthetic datasets and source models can be created and imported into the Framework, and specific degraded numerical experiments can be run to test the flexibility of the analysis methods. The Framework also supports use of full current LISA Testbeds, Synthetic data systems, and Simulators already in existence through plug-ins and wrappers, thus preserving those legacy codes and systems in tact. Because of the component-based architecture, all selected procedures can be registered or de-registered at run-time, and are completely reusable, reconfigurable, and modular.

Non-linear control of the output stage of a solar microinverter

NASA Astrophysics Data System (ADS)

Lopez-Santos, Oswaldo; Garcia, Germain; Martinez-Salamero, Luis; Avila-Martinez, Juan C.; Seguier, Lionel

2017-01-01

This paper presents a proposal to control the output stage of a two-stage solar microinverter to inject real power into the grid. The input stage of the microinverter is used to extract the maximum available power of a photovoltaic module enforcing a power source behavior in the DC-link to feed the output stage. The work here reported is devoted to control a grid-connected power source inverter with a high power quality level at the grid side ensuring the power balance of the microinverter regulating the voltage of the DC-link. The proposed control is composed of a sinusoidal current reference generator and a cascade type controller composed by a current tracking loop and a voltage regulation loop. The current reference is obtained using a synchronized generator based on phase locked loop (PLL) which gives the shape, the frequency and phase of the current signal. The amplitude of the reference is obtained from a simple controller regulating the DC-link voltage. The tracking of the current reference is accomplished by means of a first-order sliding mode control law. The solution takes advantage of the rapidity and inherent robustness of the sliding mode current controller allowing a robust behavior in the regulation of the DC-link using a simple linear controller. The analytical expression to determine the power quality indicators of the micro-inverter's output is theoretically solved giving expressions relating the converter parameters. The theoretical approach is validated using simulation and experimental results.

[PREPARATION OF HUMAN TISSUE PROTEIN EXTRACTS ENRICHED WITH THE SPHINGOMYELIN SYNTHASE 1].

PubMed

Sudarkina, O Yu; Dergunova, L V

2015-01-01

Sphingomyelin synthase 1 (SMS 1) catalyzes sphingomyelin biosynthesis in eukaryotic cells. We previously studied the structure of the human SGMS1 gene, which encodes the enzyme and its numerous transcripts. The tissue-specific expression of the transcripts was also described. Analysis of the SMS1 protein expression in human tissues using immunoblotting of tissue extracts prepared in the RIPA (Radio Immuno-Precipitation Assay) buffer revealed a weak signal in renal cortex, testis, lung, and no signal in placenta and lymphatic node. In this work, a new method of preparation of the tissue protein extracts enriched with SMS1 was suggested. The method based on the consecutive extraction with a buffer containing 0.05 and 1 mg/ml of the Quillaja saponaria saponin allowed SMS1 to be detected in all tissues tested. The SMS1 content in the saponin extract of kidney cortex is about 12-fold higher compared to the RIPA extraction procedure.

A novel murmur-based heart sound feature extraction technique using envelope-morphological analysis

NASA Astrophysics Data System (ADS)

Yao, Hao-Dong; Ma, Jia-Li; Fu, Bin-Bin; Wang, Hai-Yang; Dong, Ming-Chui

2015-07-01

Auscultation of heart sound (HS) signals serves as an important primary approach to diagnose cardiovascular diseases (CVDs) for centuries. Confronting the intrinsic drawbacks of traditional HS auscultation, computer-aided automatic HS auscultation based on feature extraction technique has witnessed explosive development. Yet, most existing HS feature extraction methods adopt acoustic or time-frequency features which exhibit poor relationship with diagnostic information, thus restricting the performance of further interpretation and analysis. Tackling such a bottleneck problem, this paper innovatively proposes a novel murmur-based HS feature extraction method since murmurs contain massive pathological information and are regarded as the first indications of pathological occurrences of heart valves. Adapting discrete wavelet transform (DWT) and Shannon envelope, the envelope-morphological characteristics of murmurs are obtained and three features are extracted accordingly. Validated by discriminating normal HS and 5 various abnormal HS signals with extracted features, the proposed method provides an attractive candidate in automatic HS auscultation.

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

Hamlet, Jason R.; Mayo, Jackson R.

Embodiments of the invention describe a Boolean circuit having a voter circuit and a plurality of approximate circuits each based, at least in part, on a reference circuit. The approximate circuits are each to generate one or more output signals based on values of received input signals. The voter circuit is to receive the one or more output signals generated by each of the approximate circuits, and is to output one or more signals corresponding to a majority value of the received signals. At least some of the approximate circuits are to generate an output value different than the referencemore » circuit for one or more input signal values; however, for each possible input signal value, the majority values of the one or more output signals generated by the approximate circuits and received by the voter circuit correspond to output signal result values of the reference circuit.« less

Extraction of seawater-derived neodymium from different phases of deep sea sediments by selective leaching

NASA Astrophysics Data System (ADS)

Blaser, P.; Lippold, J. A.; Frank, N.; Gutjahr, M.; Böhm, E.

2014-12-01

In order to deduce reliable information about the interaction of the oceans with the climate system as a whole in the past, the reconstruction of water mass circulation is crucial. The analysis of seawater-derived neodymium isotopes (143Nd/144Nd, expressed as ɛNd) in marine sediments provides a unique proxy for deep water provenance in particular in the Atlantic [1]. The ɛNd signature and thus the mixing proportion of the local bottom water masses is archived in authigenic phases in the sediment. Obtaining seawater ɛNd from authigenic accretions bound to foraminiferal tests has lately become the preferred since most reliable method [2]. Attempts have also been made to extract the Nd-rich authigenic metal fraction by leaching it off the bulk sediment and thereby use this proxy with less effort, in the highest possible resolution and in sediments where foraminifera are not sufficiently present. However, often other sedimentary components are also leached in the process and contaminate the extracted Nd [3,4]. In this project several core-top and older sediments across the Atlantic have been leached in ten consecutive steps with either dilute buffered acetic acid or an acid-reductive solution. The leachates were analysed on their elemental and Nd isotope compositions, as well as rare earth element (REE) distributions. By graduating the total leaching procedure into smaller stages the results display which processes take place in the course of sediment leaching in the laboratory and which components of the sediment are most reactive. Thus, they help to better evaluate the quality of sediment leaches for ɛNd analysis. Clearly, organic calcite acts as a fast reacting buffer and at the point where its amount is sufficiently reduced the leaching of other components commences and the Nd concentration peaks. Corruption of the extracted ɛNd signal by non-authigenic sources in many cases occured early in the leaching sequence, indicating that only very cautious leaching can reliably extract an authigenic ɛNd signal from diverse sedimentary environments. References: [1] Crocket, K. C. et al. (2011), Geology 39, 515-518 [2] Tachikawa, K. et al. (2014), Quat. Sci. Rev. 88, 1-13 [3] Elmore, A. C. et al. (2011), G³ Vol. 12/9 [4] Wilson, D. J. et al. (2013), GCA 109, 197-221

A Novel Multiple-Access Correlation-Delay-Shift-Keying

NASA Astrophysics Data System (ADS)

Duan, J. Y.; Jiang, G. P.; Yang, H.

In Correlation-Delay-Shift-Keying (CDSK), the reference signal and the information-bearing signal are added together during a certain time delay. Because the reference signal is not strictly orthogonal to the information-bearing signal, the cross-correlation between the adjacent chaotic signal (Intra-signal Interference, ISI) will be introduced into the demodulation at the receiver. Therefore, the Bit-Error Ratio (BER) of CDSK is higher than that of Differential-Chaos-Shift-Keying (DCSK). To avoid the ISI component and enhance the BER performance of CDSK in multiuser scenario, Multiple-Access CDSK with No Intra-signal Interference (MA-CDSK-NII) is proposed. By constructing the repeated chaotic generator and applying the Walsh code sequence to modulate the reference signal, in MA-CDSK-NII, the ISI component will be eliminated during the demodulation. Gaussian approximation method is adopted here to obtain the exact performance analysis of MA-CDSK-NII over additive white Gaussian noise (AWGN) channel and Rayleigh multipath fading channels. Results show that, due to no ISI component and lower transmitting power, the BER performance of MA-CDSK-NII can be better than that of multiple-access CDSK and Code-Shifted Differential-Chaos-Shift-Keying (CS-DCSK).

Cartilage collagen damage in hip osteoarthritis similar to that seen in knee osteoarthritis; a case-control study of relationship between collagen, glycosaminoglycan and cartilage swelling.

PubMed

Hosseininia, Shahrzad; Lindberg, Lisbeth R; Dahlberg, Leif E

2013-01-09

It remains to be shown whether OA shares molecular similarities between different joints in humans. This study provides evidence for similarities in cartilage molecular damage in osteoarthritic (OA) joints. Articular cartilage from osteoarthritic hip joints were analysed and compared to non-OA controls regarding collagen, glycosaminoglycan and water content. Femoral heads from 16 osteoarthritic (OA) and 20 reference patients were obtained from hip replacement surgery due to OA and femoral neck fracture, respectively. Cartilage histological changes were assessed by Mankin grading and denatured collagen type II immunostaining and cartilage was extracted by α-chymotrypsin. Hydroxyproline and Alcian blue binding assays were used to measure collagen and glycosaminoglycan (GAG) content, respectively. Mankin and immunohistology scores were significantly higher in hip OA samples than in reference samples. Cartilage water content was 6% higher in OA samples than in references. 2.5 times more collagen was extracted from OA than from reference samples. There was a positive association between water content and percentage of extractable collagen pool (ECP) in both groups. The amounts of collagen per wet and dry weights did not differ statistically between OA and reference cartilage. % Extractable collagen was not related to collagen per dry weight in either group. However when collagen was expressed by wet weight there was a negative correlation between % extractable and collagen in OA cartilage. The amount of GAG per wet weight was similar in both groups but the amount of GAG per dry weight was higher in OA samples compared to reference samples, which suggests a capacity for GAG biosynthesis in hip OA cartilage. Neither of the studied parameters was related to age in either group. Increased collagen extractability and water content in human hip cartilage is associated with OA pathology and can be observed at early stages of the degenerative hip OA process. Our results suggest a common degradative pathway of collagen in articular cartilage of different joints. Furthermore, the study suggests that biochemical changes precede more overt OA changes and that chondrocytes may have a capability to compensate molecular loss in the early phase of OA.

Optimization of Process Parameters and Kinetic Model of Enzymatic Extraction of Polyphenols from Lonicerae Flos

PubMed Central

Kong, Fansheng; Yu, Shujuan; Bi, Yongguang; Huang, Xiaojun; Huang, Mengqian

2016-01-01

Objective: To optimize and verify the cellulase extraction of polyphenols from honeysuckle and provide a reference for enzymatic extracting polyphenols from honeysuckle. Materials and Methods: The uniform design was used According to Fick's first law and kinetic model, fitting analysis of the dynamic process of enzymatic extracting polyphenols was conducted. Results: The optimum enzymatic extraction parameters for polyphenols from honeysuckle are found to be 80% (v/v) of alcohol, 35:1 (mL/g) of liquid-solid ratio, 80°C of extraction temperature, 8.5 of pH, 6.0 mg of enzyme levels, and 130 min of extraction time. Under the optimal conditions, the extraction rate of polyphenols was 3.03%. The kinetic experiments indicated kinetic equation had a good linear relationship with t even under the conditions of different levels of enzyme and temperature, which means fitting curve tallies well with the experimental values. Conclusion: The results of quantification showed that the results provide a reference for enzymatic extracting polyphenols from honeysuckle. SUMMARY Lonicerae flos (Lonicera japonica Thunb.) is a material of traditional Chinese medicine and healthy drinks, of which active compounds mainly is polyphenols. At present, plant polyphenols are the hotspots centents of food, cosmetic and medicine, because it has strong bioactivity. Several traditional methods are available for the extraction of plant polyphenols including impregnation, solvent extraction, ultrasonic extraction, hot-water extraction, alkaline dilute alcohol or alkaline water extraction, microwave extraction and Supercritical CO2 extraction. But now, an increasing number of research on using cellulase to extract active ingredients from plants. Enzymatic method is widely used for enzyme have excellent properties of high reaction efficiency and specificity, moderate reaction conditions, shorter extraction time and easier to control, less damage to the active ingredient. At present, the enzymatic extraction of polyphenols from honeysuckle and dynamic had not been reported. In this study, using cellulase to extract polyphenols from honeysuckle is first applied. Moreover, uniform design was used to optimize process and kinetic model of extraction was established to analyze the characteristics of enzymatic extraction, in order to improve the yield of polyphenols from honeysuckle and make maximum use of Lonicerae flos, which provide references for industrial production. PMID:27018039

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

Shepard, Kenneth L.; Sturcken, Noah Andrew

Power controller includes an output terminal having an output voltage, at least one clock generator to generate a plurality of clock signals and a plurality of hardware phases. Each hardware phase is coupled to the at least one clock generator and the output terminal and includes a comparator. Each hardware phase is configured to receive a corresponding one of the plurality of clock signals and a reference voltage, combine the corresponding clock signal and the reference voltage to produce a reference input, generate a feedback voltage based on the output voltage, compare the reference input and the feedback voltage usingmore » the comparator and provide a comparator output to the output terminal, whereby the comparator output determines a duty cycle of the power controller. An integrated circuit including the power controller is also provided.« less

The Effect of Electroencephalogram (EEG) Reference Choice on Information-Theoretic Measures of the Complexity and Integration of EEG Signals

PubMed Central

Trujillo, Logan T.; Stanfield, Candice T.; Vela, Ruben D.

2017-01-01

Converging evidence suggests that human cognition and behavior emerge from functional brain networks interacting on local and global scales. We investigated two information-theoretic measures of functional brain segregation and integration—interaction complexity CI(X), and integration I(X)—as applied to electroencephalographic (EEG) signals and how these measures are affected by choice of EEG reference. CI(X) is a statistical measure of the system entropy accounted for by interactions among its elements, whereas I(X) indexes the overall deviation from statistical independence of the individual elements of a system. We recorded 72 channels of scalp EEG from human participants who sat in a wakeful resting state (interleaved counterbalanced eyes-open and eyes-closed blocks). CI(X) and I(X) of the EEG signals were computed using four different EEG references: linked-mastoids (LM) reference, average (AVG) reference, a Laplacian (LAP) “reference-free” transformation, and an infinity (INF) reference estimated via the Reference Electrode Standardization Technique (REST). Fourier-based power spectral density (PSD), a standard measure of resting state activity, was computed for comparison and as a check of data integrity and quality. We also performed dipole source modeling in order to assess the accuracy of neural source CI(X) and I(X) estimates obtained from scalp-level EEG signals. CI(X) was largest for the LAP transformation, smallest for the LM reference, and at intermediate values for the AVG and INF references. I(X) was smallest for the LAP transformation, largest for the LM reference, and at intermediate values for the AVG and INF references. Furthermore, across all references, CI(X) and I(X) reliably distinguished between resting-state conditions (larger values for eyes-open vs. eyes-closed). These findings occurred in the context of the overall expected pattern of resting state PSD. Dipole modeling showed that simulated scalp EEG-level CI(X) and I(X) reflected changes in underlying neural source dependencies, but only for higher levels of integration and with highest accuracy for the LAP transformation. Our observations suggest that the Laplacian-transformation should be preferred for the computation of scalp-level CI(X) and I(X) due to its positive impact on EEG signal quality and statistics, reduction of volume-conduction, and the higher accuracy this provides when estimating scalp-level EEG complexity and integration. PMID:28790884

Exciter For X-Band Transmitter And Receiver

NASA Technical Reports Server (NTRS)

Johns, Carl E.

1989-01-01

Report describes developmental X-band exciter for X-band uplink subsystem of Deep Space Network. X-band transmitter-exciting signal expected to have fractional frequency stability of 5.2 X 10 to negative 15th power during 1,000-second integration period. Generates coherent test signals for S- and X-band Block III translator of Deep Space Network, Doppler-reference signal for associated Doppler-extractor system, first-local-oscillator signal for associated receiver, and reference signal for associated ranging subsystem. Tests of prototype exciter show controlling and monitoring and internal phase-correcting loops perform according to applicable design criteria. Measurements of stability of frequency and of single-sideband noise spectral density of transmitter-exciting signal made subsequently.

Automated detection and location of indications in eddy current signals

DOEpatents

Brudnoy, David M.; Oppenlander, Jane E.; Levy, Arthur J.

2000-01-01

A computer implemented information extraction process that locates and identifies eddy current signal features in digital point-ordered signals, signals representing data from inspection of test materials, by enhancing the signal features relative to signal noise, detecting features of the signals, verifying the location of the signal features that can be known in advance, and outputting information about the identity and location of all detected signal features.

Design and fabrication of SiO2/TiO2 and MgO/TiO2 based high selective optical filters for diffuse reflectance and fluorescence signals extraction.

PubMed

Pimenta, S; Cardoso, S; Miranda, A; De Beule, P; Castanheira, E M S; Minas, G

2015-08-01

This paper presents the design, optimization and fabrication of 16 MgO/TiO2 and SiO2/TiO2 based high selective narrow bandpass optical filters. Their performance to extract diffuse reflectance and fluorescence signals from gastrointestinal tissue phantoms was successfully evaluated. The obtained results prove their feasibility to correctly extract those spectroscopic signals, through a Spearman's rank correlation test (Spearman's correlation coefficient higher than 0.981) performed between the original spectra and the ones obtained using those 16 fabricated optical filters. These results are an important step for the implementation of a miniaturized, low-cost and minimal invasive microsystem that could help in the detection of gastrointestinal dysplasia.

Pulsed phase locked loop strain monitor

NASA Technical Reports Server (NTRS)

Froggatt, Mark E. (Inventor)

1995-01-01

A pulse phase locked loop system according to the present invention is described. A frequency generator such as a voltage controlled oscillator (VCO) generates an output signal and a reference signal having a frequency equal to that of the output signal. A transmitting gate gates the output frequency signal and this gated signal drives a transmitting transducer which transmits an acoustic wave through a material. A sample/hold samples a signal indicative of the transmitted wave which is received by a receiving transducer. Divide-by-n counters control these gating and sampling functions in response to the reference signal of the frequency generator. Specifically, the output signal is gated at a rate of F/h, wherein F is the frequency of the output signal and h is an integer; and the received signal is sampled at a delay of F/n wherein n is an integer.

Extraction of angle deterministic signals in the presence of stationary speed fluctuations with cyclostationary blind source separation

NASA Astrophysics Data System (ADS)

Delvecchio, S.; Antoni, J.

2012-02-01

This paper addresses the use of a cyclostationary blind source separation algorithm (namely RRCR) to extract angle deterministic signals from mechanical rotating machines in presence of stationary speed fluctuations. This means that only phase fluctuations while machine is running in steady-state conditions are considered while run-up or run-down speed variations are not taken into account. The machine is also supposed to run in idle conditions so non-stationary phenomena due to the load are not considered. It is theoretically assessed that in such operating conditions the deterministic (periodic) signal in the angle domain becomes cyclostationary at first and second orders in the time domain. This fact justifies the use of the RRCR algorithm, which is able to directly extract the angle deterministic signal from the time domain without performing any kind of interpolation. This is particularly valuable when angular resampling fails because of uncontrolled speed fluctuations. The capability of the proposed approach is verified by means of simulated and actual vibration signals captured on a pneumatic screwdriver handle. In this particular case not only the extraction of the angle deterministic part can be performed but also the separation of the main sources of excitation (i.e. motor shaft imbalance, epyciloidal gear meshing and air pressure forces) affecting the user hand during operations.

Crataegus oxycantha extract attenuates apoptotic incidence in myocardial ischemia-reperfusion injury by regulating Akt and HIF-1 signaling pathways.

PubMed

Jayachandran, Kesavan S; Khan, Mahmood; Selvendiran, Karuppaiyah; Devaraj, S Niranjali; Kuppusamy, Periannan

2010-11-01

The objective of the present study was to evaluate the efficacy and mechanism of Crataegus oxycantha (COC) extract in preventing ischemia-reperfusion (IR) injury in an in vivo rat model of acute myocardial infarction induced by a 30-minute regional ischemia followed by 72 hours of reperfusion. The COC extract [100 mg/(kg body weight)] was administered 12 hours after the surgical procedure and then at 24-hour intervals for 3 days. Animals treated with COC extract showed a significant decrease in creatine kinase activity and infarct size. At the molecular level, COC administration resulted in a significant attenuation of PTEN (phosphatase and tensin homolog deleted on chromosome 10) and upregulation of phospho-Akt and c-Raf levels in the heart. As a consequence, cleaved caspase-9 and cleaved caspase-7 levels were significantly downregulated, indicating negative regulation of apoptosis by COC extract. In part with the hypoxia-inducible factor (HIF) signaling pathway, COC extract administration significantly upregulated the prolyl hydroxylase-2 level. In contrast, other proapoptotic proteins such as nuclear factor-κB, cytochrome c, apoptosis-inducing factor, and cleaved poly(adenosine diphosphate-ribose) polymerase levels were significantly downregulated in the COC-treated group when compared with the untreated control group. The results suggested that COC extract attenuated apoptotic incidence in the experimental myocardial ischemia-reperfusion model by regulating Akt and HIF-1 signaling pathways.

Wollaston prism phase-stepping point diffraction interferometer and method

DOEpatents

Rushford, Michael C.

2004-10-12

A Wollaston prism phase-stepping point diffraction interferometer for testing a test optic. The Wollaston prism shears light into reference and signal beams, and provides phase stepping at increased accuracy by translating the Wollaston prism in a lateral direction with respect to the optical path. The reference beam produced by the Wollaston prism is directed through a pinhole of a diaphragm to produce a perfect spherical reference wave. The spherical reference wave is recombined with the signal beam to produce an interference fringe pattern of greater accuracy.

Scanning probe acceleration microscopy (SPAM) in fluids: Mapping mechanical properties of surfaces at the nanoscale

NASA Astrophysics Data System (ADS)

Legleiter, Justin; Park, Matthew; Cusick, Brian; Kowalewski, Tomasz

2006-03-01

One of the major thrusts in proximal probe techniques is combination of imaging capabilities with simultaneous measurements of physical properties. In tapping mode atomic force microscopy (TMAFM), the most straightforward way to accomplish this goal is to reconstruct the time-resolved force interaction between the tip and surface. These tip-sample forces can be used to detect interactions (e.g., binding sites) and map material properties with nanoscale spatial resolution. Here, we describe a previously unreported approach, which we refer to as scanning probe acceleration microscopy (SPAM), in which the TMAFM cantilever acts as an accelerometer to extract tip-sample forces during imaging. This method utilizes the second derivative of the deflection signal to recover the tip acceleration trajectory. The challenge in such an approach is that with real, noisy data, the second derivative of the signal is strongly dominated by the noise. This problem is solved by taking advantage of the fact that most of the information about the deflection trajectory is contained in the higher harmonics, making it possible to filter the signal by “comb” filtering, i.e., by taking its Fourier transform and inverting it while selectively retaining only the intensities at integer harmonic frequencies. Such a comb filtering method works particularly well in fluid TMAFM because of the highly distorted character of the deflection signal. Numerical simulations and in situ TMAFM experiments on supported lipid bilayer patches on mica are reported to demonstrate the validity of this approach.

Auditory perception bias in speech imitation

PubMed Central

Postma-Nilsenová, Marie; Postma, Eric

2013-01-01

In an experimental study, we explored the role of auditory perception bias in vocal pitch imitation. Psychoacoustic tasks involving a missing fundamental indicate that some listeners are attuned to the relationship between all the higher harmonics present in the signal, which supports their perception of the fundamental frequency (the primary acoustic correlate of pitch). Other listeners focus on the lowest harmonic constituents of the complex sound signal which may hamper the perception of the fundamental. These two listener types are referred to as fundamental and spectral listeners, respectively. We hypothesized that the individual differences in speakers' capacity to imitate F0 found in earlier studies, may at least partly be due to the capacity to extract information about F0 from the speech signal. Participants' auditory perception bias was determined with a standard missing fundamental perceptual test. Subsequently, speech data were collected in a shadowing task with two conditions, one with a full speech signal and one with high-pass filtered speech above 300 Hz. The results showed that perception bias toward fundamental frequency was related to the degree of F0 imitation. The effect was stronger in the condition with high-pass filtered speech. The experimental outcomes suggest advantages for fundamental listeners in communicative situations where F0 imitation is used as a behavioral cue. Future research needs to determine to what extent auditory perception bias may be related to other individual properties known to improve imitation, such as phonetic talent. PMID:24204361

Block 3 X-band receiver-exciter

NASA Technical Reports Server (NTRS)

Johns, C. E.

1987-01-01

The development of an X-band exciter, for use in the X-Band Uplink Subsystem, was completed. The exciter generates the drive signal for the X-band transmitter and also generates coherent test signals for the S- and X-band Block 3 translator and a Doppler reference signal for the Doppler extractor system. In addition to the above, the exciter generates other reference signals that are described. Also presented is an overview of the exciter design and some test data taken on the prototype. A brief discussion of the Block 3 Doppler extractor is presented.

Reference analysis of the signal + background model in counting experiments

NASA Astrophysics Data System (ADS)

Casadei, D.

2012-01-01

The model representing two independent Poisson processes, labelled as ``signal'' and ``background'' and both contributing additively to the total number of counted events, is considered from a Bayesian point of view. This is a widely used model for the searches of rare or exotic events in presence of a background source, as for example in the searches performed by high-energy physics experiments. In the assumption of prior knowledge about the background yield, a reference prior is obtained for the signal alone and its properties are studied. Finally, the properties of the full solution, the marginal reference posterior, are illustrated with few examples.

[Lithology feature extraction of CASI hyperspectral data based on fractal signal algorithm].

PubMed

Tang, Chao; Chen, Jian-Ping; Cui, Jing; Wen, Bo-Tao

2014-05-01

Hyperspectral data is characterized by combination of image and spectrum and large data volume dimension reduction is the main research direction. Band selection and feature extraction is the primary method used for this objective. In the present article, the authors tested methods applied for the lithology feature extraction from hyperspectral data. Based on the self-similarity of hyperspectral data, the authors explored the application of fractal algorithm to lithology feature extraction from CASI hyperspectral data. The "carpet method" was corrected and then applied to calculate the fractal value of every pixel in the hyperspectral data. The results show that fractal information highlights the exposed bedrock lithology better than the original hyperspectral data The fractal signal and characterized scale are influenced by the spectral curve shape, the initial scale selection and iteration step. At present, research on the fractal signal of spectral curve is rare, implying the necessity of further quantitative analysis and investigation of its physical implications.

The extraction of spot signal in Shack-Hartmann wavefront sensor based on sparse representation

NASA Astrophysics Data System (ADS)

Zhang, Yanyan; Xu, Wentao; Chen, Suting; Ge, Junxiang; Wan, Fayu

2016-07-01

Several techniques have been used with Shack-Hartmann wavefront sensors to determine the local wave-front gradient across each lenslet. While the centroid error of Shack-Hartmann wavefront sensor is relatively large since the skylight background and the detector noise. In this paper, we introduce a new method based on sparse representation to extract the target signal from the background and the noise. First, an over complete dictionary of the spot signal is constructed based on two-dimensional Gaussian model. Then the Shack-Hartmann image is divided into sub blocks. The corresponding coefficients of each block is computed in the over complete dictionary. Since the coefficients of the noise and the target are large different, then extract the target by setting a threshold to the coefficients. Experimental results show that the target can be well extracted and the deviation, RMS and PV of the centroid are all smaller than the method of subtracting threshold.

Hyperpolarized xenon NMR and MRI signal amplification by gas extraction

PubMed Central

Zhou, Xin; Graziani, Dominic; Pines, Alexander

2009-01-01

A method is reported for enhancing the sensitivity of NMR of dissolved xenon by detecting the signal after extraction to the gas phase. We demonstrate hyperpolarized xenon signal amplification by gas extraction (Hyper-SAGE) in both NMR spectra and magnetic resonance images with time-of-flight information. Hyper-SAGE takes advantage of a change in physical phase to increase the density of polarized gas in the detection coil. At equilibrium, the concentration of gas-phase xenon is ≈10 times higher than that of the dissolved-phase gas. After extraction the xenon density can be further increased by several orders of magnitude by compression and/or liquefaction. Additionally, being a remote detection technique, the Hyper-SAGE effect is further enhanced in situations where the sample of interest would occupy only a small proportion of the traditional NMR receiver. Coupled with targeted xenon biosensors, Hyper-SAGE offers another path to highly sensitive molecular imaging of specific cell markers by detection of exhaled xenon gas. PMID:19805177

Promotion Effect of Apo-9'-fucoxanthinone from Sargassum muticum on Hair Growth via the Activation of Wnt/β-Catenin and VEGF-R2.

PubMed

Kang, Jung-Il; Yoo, Eun-Sook; Hyun, Jin-Won; Koh, Young-Sang; Lee, Nam Ho; Ko, Mi-Hee; Ko, Chang-Sik; Kang, Hee-Kyoung

2016-01-01

This study was conducted to evaluate the effects of Sargassum muticum extract and apo-9'-fucoxanthinone, a principal component of S. muticum, on hair growth. When rat vibrissa follicles were treated with S. muticum extract for 21 d, the hair-fiber lengths for the vibrissa follicles increased significantly. Treatment with the S. muticum extract and the EtOAc fraction of the S. muticum extract markedly increased the proliferation of dermal papilla cells (DPCs) and decreased the 5α-reductase activity. In addition, the EtOAc fraction of the S. muticum extract significantly promoted anagen initiation in C57BL/6 mice. Especially, apo-9'-fucoxanthinone, an active constituent from the S. muticum extract, caused an increase in DPC proliferation and a decrease in 5α-reductase activity. To elucidate the molecular mechanisms of apo-9'-fucoxanthinone on the proliferation of DPCs, we examined the level of various signaling proteins. Apo-9'-fucoxanthinone increased the level of vascular endothelial growth factor receptor-2 (VEGF-R2), Wnt/β-catenin signaling proteins such as phospho(ser9)-glycogen synthase kinase-3β (GSK-3β) and phospho(ser552)-β-catenin, whereas apo-9'-fucoxanthinone did not affect the transforming growth factor-β (TGF-β) signaling proteins such as Smad2/3. These results suggest that apo-9'-fucoxanthinone from S. muticum could have the potential for hair growth with DPC proliferation via the activation of Wnt/β-catenin signaling and the VEGF-R2 pathway.

An adaptive singular spectrum analysis method for extracting brain rhythms of electroencephalography

PubMed Central

Hu, Hai; Guo, Shengxin; Liu, Ran

2017-01-01

Artifacts removal and rhythms extraction from electroencephalography (EEG) signals are important for portable and wearable EEG recording devices. Incorporating a novel grouping rule, we proposed an adaptive singular spectrum analysis (SSA) method for artifacts removal and rhythms extraction. Based on the EEG signal amplitude, the grouping rule determines adaptively the first one or two SSA reconstructed components as artifacts and removes them. The remaining reconstructed components are then grouped based on their peak frequencies in the Fourier transform to extract the desired rhythms. The grouping rule thus enables SSA to be adaptive to EEG signals containing different levels of artifacts and rhythms. The simulated EEG data based on the Markov Process Amplitude (MPA) EEG model and the experimental EEG data in the eyes-open and eyes-closed states were used to verify the adaptive SSA method. Results showed a better performance in artifacts removal and rhythms extraction, compared with the wavelet decomposition (WDec) and another two recently reported SSA methods. Features of the extracted alpha rhythms using adaptive SSA were calculated to distinguish between the eyes-open and eyes-closed states. Results showed a higher accuracy (95.8%) than those of the WDec method (79.2%) and the infinite impulse response (IIR) filtering method (83.3%). PMID:28674650

Xenopus extract approaches to studying microtubule organization and signaling in cytokinesis

PubMed Central

Field, Christine M.; Pelletier, James F.; Mitchison, Timothy J.

2017-01-01

We report optimized methods for preparing actin-intact Xenopus egg extract. This extract is minimally perturbed, undiluted egg cytoplasm where the cell cycle can be experimentally controlled. It contains abundant organelles and glycogen, and supports active metabolism and cytoskeletal dynamics that closely mimic egg physiology. The concentration of the most abundant ~11,000 proteins is known from mass spectrometry. Actin-intact egg extract can be used for analysis of actin dynamics and interaction of actin with other cytoplasmic systems, as well as microtubule organization. It can be spread as thin layers, and naturally depletes oxygen though mitochondrial metabolism, which makes it ideal for fluorescence imaging. When combined with artificial lipid bilayers, it allows reconstitution and analysis of the spatially controlled signaling that positions the cleavage furrow during early cytokinesis. Actin-intact extract is generally useful for probing the biochemistry and biophysics of the large Xenopus egg. Protocols are provided for preparation of actin-intact egg extract, control of the cell cycle, fluorescent probes for cytoskeleton and cytoskeleton-dependent signaling, preparation of glass surfaces for imaging experiments, and immunodepletion to probe the role of specific proteins and protein complexes. We also describe methods for adding supported lipid bilayers to mimic the plasma membrane and for confining in microfluidic droplets to explore size scaling issues. PMID:28065319

Ethyl acetate fraction from methanol extraction of Vitis thunbergii var. taiwaniana induced G0 /G1 phase arrest via inhibition of cyclins D and E and induction of apoptosis through caspase-dependent and -independent pathways in human prostate carcinoma DU145 cells.

PubMed

Lin, Chia-Hsin; Chan, Hsiao-Sung; Tsay, Hsin-Sheng; Funayama, Shinji; Kuo, Chao-Lin; Chung, Jing-Gung

2018-01-01

Vitis thunbergii var. taiwaniana (VTT) is a wild grape native to Taiwan, belonging to the Vitaceae family and Vitis genus, and widely used as folk herbal medicine. It is traditionally used for the treatment of diarrhea, hypertension, neuroprotection, jaundice, and arthritis. We used the wild-collected VTT and sterilized them to establish the plant tissue culture, and then took the leaves for DNA sequencing to determine its original base. We use methanol to extract VTT in four different solvents: 1-butanol, n-hexane, ethyl acetate, and water. These four preliminary extracts were used to treat human prostate cancer DU145 cells in vitro. We use the flow cytometry to check the cell survival situation. Finally, we found the ethyl acetate layer roughing product (referred VTEA) in human prostate cancer apoptotic effects of cell line DU-145. In the present studies, we use the crude extract of VTT to examine whether or not it can induce apoptosis of DU145 cells in vitro. Viability assays for extracts of VTT treatment showed that it had dose-dependent effect on human prostate cancer DU145 cells. We also found that the extract of VTT induces time-dependent mitochondrial and intrinsic-dependent apoptosis pathways. The in vitro cytotoxic effects were investigated by cell cycle analysis and the determination of apoptotic DNA fragmentation in DU145 cells. The cell cycle analysis showed that extracts of VTT induced a significant increase in the number of cells in G 0 /G 1 phase. The extract of VTT induced chromatin changes and apoptosis of DU145 cells also were confirmed by DAPI and PI staining that were measured by fluorescence microscopy and flow cytometry, respectively. Finally, the expression of relevant proteins was analyzed by Western blot analysis. These results promoted us to further evaluate apoptosis associated proteins and elucidate the possible signal pathway in DU-145 cells after treated with the extract of VTT. © 2017 Wiley Periodicals, Inc.

Automated detection of discourse segment and experimental types from the text of cancer pathway results sections.

PubMed

Burns, Gully A P C; Dasigi, Pradeep; de Waard, Anita; Hovy, Eduard H

2016-01-01

Automated machine-reading biocuration systems typically use sentence-by-sentence information extraction to construct meaning representations for use by curators. This does not directly reflect the typical discourse structure used by scientists to construct an argument from the experimental data available within a article, and is therefore less likely to correspond to representations typically used in biomedical informatics systems (let alone to the mental models that scientists have). In this study, we develop Natural Language Processing methods to locate, extract, and classify the individual passages of text from articles' Results sections that refer to experimental data. In our domain of interest (molecular biology studies of cancer signal transduction pathways), individual articles may contain as many as 30 small-scale individual experiments describing a variety of findings, upon which authors base their overall research conclusions. Our system automatically classifies discourse segments in these texts into seven categories (fact, hypothesis, problem, goal, method, result, implication) with an F-score of 0.68. These segments describe the essential building blocks of scientific discourse to (i) provide context for each experiment, (ii) report experimental details and (iii) explain the data's meaning in context. We evaluate our system on text passages from articles that were curated in molecular biology databases (the Pathway Logic Datum repository, the Molecular Interaction MINT and INTACT databases) linking individual experiments in articles to the type of assay used (coprecipitation, phosphorylation, translocation etc.). We use supervised machine learning techniques on text passages containing unambiguous references to experiments to obtain baseline F1 scores of 0.59 for MINT, 0.71 for INTACT and 0.63 for Pathway Logic. Although preliminary, these results support the notion that targeting information extraction methods to experimental results could provide accurate, automated methods for biocuration. We also suggest the need for finer-grained curation of experimental methods used when constructing molecular biology databases. © The Author(s) 2016. Published by Oxford University Press.

Phytoliths in woody plants from the Miombo woodlands of Mozambique

PubMed Central

Mercader, Julio; Bennett, Tim; Esselmont, Chris; Simpson, Steven; Walde, Dale

2009-01-01

Background and Aims There are no descriptions of phytoliths produced by plants from the ‘Zambezian’ zone, where Miombo woodlands are the dominant element of the largest single phytochorion in sub-Saharan Africa. The preservation of phytoliths in fossil records of Africa makes phytoliths a tool to study early plant communities. Paleo-ethnobotanical interpretation of phytoliths relies on the comparison of ancient types with morphotypes extracted from living reference collections. Methods Phytoliths were extracted from plant samples representing 41 families, 77 genera and 90 species through sonic cleaning, dry ashing and acid treatment; and phytoliths thus extracted were quantified. For each species, an average of 216 phytoliths were counted. The percentage of each morphotype identified per species was calculated, and types were described according to the descriptors from the International Code for Phytolith Nomenclature. Phytolith assemblages were subject to discriminant analysis, cluster analysis and principal component analysis. Key Results Phytoliths were grouped into 57 morphotypes (two were articulated forms and 55 were discrete shapes), and provide a reference collection of phytolith assemblages produced by Miombo woody species. Common and unique morphotypes are described and taxonomic and grouping variables are looked into from a statistical perspective. Conclusions The first quantitative taxonomy of phytoliths from Miombos is presented here, including new types and constituting the most extensive phytolith key for any African ecoregion. Evidence is presented that local woody species are hypervariable silica producers and their phytolith morphotypes are highly polymorphic. The taxonomic significance of these phytoliths is largely poor, but there are important exceptions that include the morphotypes produced by members from >10 families and orders. The typical phytolithic signal that would allow scientists to identify ancient woodlands of ‘Zambezian’ affiliation comprises only half of the original number of phytoliths originally produced and might favour the more resilient blocky, cylindroid, globular and tabular forms. PMID:19429923

The Anti-Inflammatory Effect of Algae-Derived Lipid Extracts on Lipopolysaccharide (LPS)-Stimulated Human THP-1 Macrophages

PubMed Central

Robertson, Ruairi C.; Guihéneuf, Freddy; Bahar, Bojlul; Schmid, Matthias; Stengel, Dagmar B.; Fitzgerald, Gerald F.; Ross, R. Paul; Stanton, Catherine

2015-01-01

Algae contain a number of anti-inflammatory bioactive compounds such as omega-3 polyunsaturated fatty acids (n-3 PUFA) and chlorophyll a, hence as dietary ingredients, their extracts may be effective in chronic inflammation-linked metabolic diseases such as cardiovascular disease. In this study, anti-inflammatory potential of lipid extracts from three red seaweeds (Porphyra dioica, Palmaria palmata and Chondrus crispus) and one microalga (Pavlova lutheri) were assessed in lipopolysaccharide (LPS)-stimulated human THP-1 macrophages. Extracts contained 34%–42% total fatty acids as n-3 PUFA and 5%–7% crude extract as pigments, including chlorophyll a, β-carotene and fucoxanthin. Pretreatment of the THP-1 cells with lipid extract from P. palmata inhibited production of the pro-inflammatory cytokines interleukin (IL)-6 (p < 0.05) and IL-8 (p < 0.05) while that of P. lutheri inhibited IL-6 (p < 0.01) production. Quantitative gene expression analysis of a panel of 92 genes linked to inflammatory signaling pathway revealed down-regulation of the expression of 14 pro-inflammatory genes (TLR1, TLR2, TLR4, TLR8, TRAF5, TRAF6, TNFSF18, IL6R, IL23, CCR1, CCR4, CCL17, STAT3, MAP3K1) by the lipid extracts. The lipid extracts effectively inhibited the LPS-induced pro-inflammatory signaling pathways mediated via toll-like receptors, chemokines and nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) signaling molecules. These results suggest that lipid extracts from P. lutheri, P. palmata, P. dioica and C. crispus can inhibit LPS-induced inflammatory pathways in human macrophages. Therefore, algal lipid extracts should be further explored as anti-inflammatory ingredients for chronic inflammation-linked metabolic diseases. PMID:26308008

An Exploration of WFC3/IR Dark Current Variation

NASA Astrophysics Data System (ADS)

Sunnquist, B.; Baggett, S.; Long, K. S.

2017-02-01

We use a collection of darks spanning September 2009 to June 2016 to study variations in the dark current in the IR detector on WFC3. Although the darks possess a similar signal pattern across the detector, we find that their median dark rates vary by as much as 0.014 DN/s (0.032 e-/s). The distribution of these median values has a triangular shape with a mean and standard deviation of 0.021 ± 0.0029 DN/s (0.049 ± 0.0069 e-/s). We observe a long term time-dependence in the inboard vertical reference pixel and zeroth read signals; however, these differences do not noticeably affect the calibrated dark signals, and we conclude that the WFC3/IR dark current levels continue to remain stable since launch. The inboard reference pixel signals exhibit a unique, but consistent, pattern around the detector, but this pattern does not evolve noticeably with the median of the science pixels, and a quadrant or row-based reference pixel subtraction strategy does not reduce the spread between the median dark rates. We notice a slight drift in the inboard reference pixel signals up the dark ramps, and the intensity of this drift is related to the median dark current in the science pixels. This holds true using either the horizontal or vertical reference pixels and for darks with a variety of sample sequences.

Interactive Digital Signal Processor

NASA Technical Reports Server (NTRS)

Mish, W. H.

1985-01-01

Interactive Digital Signal Processor, IDSP, consists of set of time series analysis "operators" based on various algorithms commonly used for digital signal analysis. Processing of digital signal time series to extract information usually achieved by applications of number of fairly standard operations. IDSP excellent teaching tool for demonstrating application for time series operators to artificially generated signals.

A structural SVM approach for reference parsing.

PubMed

Zhang, Xiaoli; Zou, Jie; Le, Daniel X; Thoma, George R

2011-06-09

Automated extraction of bibliographic data, such as article titles, author names, abstracts, and references is essential to the affordable creation of large citation databases. References, typically appearing at the end of journal articles, can also provide valuable information for extracting other bibliographic data. Therefore, parsing individual reference to extract author, title, journal, year, etc. is sometimes a necessary preprocessing step in building citation-indexing systems. The regular structure in references enables us to consider reference parsing a sequence learning problem and to study structural Support Vector Machine (structural SVM), a newly developed structured learning algorithm on parsing references. In this study, we implemented structural SVM and used two types of contextual features to compare structural SVM with conventional SVM. Both methods achieve above 98% token classification accuracy and above 95% overall chunk-level accuracy for reference parsing. We also compared SVM and structural SVM to Conditional Random Field (CRF). The experimental results show that structural SVM and CRF achieve similar accuracies at token- and chunk-levels. When only basic observation features are used for each token, structural SVM achieves higher performance compared to SVM since it utilizes the contextual label features. However, when the contextual observation features from neighboring tokens are combined, SVM performance improves greatly, and is close to that of structural SVM after adding the second order contextual observation features. The comparison of these two methods with CRF using the same set of binary features show that both structural SVM and CRF perform better than SVM, indicating their stronger sequence learning ability in reference parsing.

Characterization of bioelectric potentials

NASA Technical Reports Server (NTRS)

Jorgensen, Charles C. (Inventor); Wheeler, Kevin R. (Inventor)

2004-01-01

Method and system for recognizing and characterizing bioelectric potential or electromyographic (EMG) signals associated with at least one of a coarse gesture and a fine gesture that is performed by a person, and use of the bioelectric potentials to enter data and/or commands into an electrical and/or mechanical instrument. As a gesture is performed, bioelectric signals that accompany the gesture are subjected to statistical averaging, within selected time intervals. Hidden Markov model analysis is applied to identify hidden, gesture-related states that are present. A metric is used to compare signals produced by a volitional gesture (not yet identified) with corresponding signals associated with each of a set of reference gestures, and the reference gesture that is closest to the volitional gesture is identified. Signals representing the volitional gesture are analyzed and compared with a database of reference gestures to determine if the volitional gesture is likely to be one of the reference gestures. Electronic and/or mechanical commands needed to carry out the gesture may be implemented at an interface to control an instrument. Applications include control of an aircraft, entry of data from a keyboard or other data entry device, and entry of data and commands in extreme environments that interfere with accurate entry.

Eddy current correction in volume-localized MR spectroscopy

NASA Technical Reports Server (NTRS)

Lin, C.; Wendt, R. E. 3rd; Evans, H. J.; Rowe, R. M.; Hedrick, T. D.; LeBlanc, A. D.

1994-01-01

The quality of volume-localized magnetic resonance spectroscopy is affected by eddy currents caused by gradient switching. Eddy currents can be reduced with improved gradient systems; however, it has been suggested that the distortion due to eddy currents can be compensated for during postprocessing with a single-frequency reference signal. The authors propose modifying current techniques for acquiring the single-frequency reference signal by using relaxation weighting to reduce interference from components that cannot be eliminated by digital filtering alone. Additional sequences with T1 or T2 weighting for reference signal acquisition are shown to have the same eddy current characteristics as the original signal without relaxation weighting. The authors also studied a new eddy current correction method that does not require a single-frequency reference signal. This method uses two free induction decays (FIDs) collected from the same volume with two sequences with opposite gradients. Phase errors caused by eddy currents are opposite in these two FIDs and can be canceled completely by combining the FIDs. These methods were tested in a phantom. Eddy current distortions were corrected, allowing quantitative measurement of structures such as the -CH = CH- component, which is otherwise undetectable.

Multiresolution analysis (discrete wavelet transform) through Daubechies family for emotion recognition in speech.

NASA Astrophysics Data System (ADS)

Campo, D.; Quintero, O. L.; Bastidas, M.

2016-04-01

We propose a study of the mathematical properties of voice as an audio signal. This work includes signals in which the channel conditions are not ideal for emotion recognition. Multiresolution analysis- discrete wavelet transform - was performed through the use of Daubechies Wavelet Family (Db1-Haar, Db6, Db8, Db10) allowing the decomposition of the initial audio signal into sets of coefficients on which a set of features was extracted and analyzed statistically in order to differentiate emotional states. ANNs proved to be a system that allows an appropriate classification of such states. This study shows that the extracted features using wavelet decomposition are enough to analyze and extract emotional content in audio signals presenting a high accuracy rate in classification of emotional states without the need to use other kinds of classical frequency-time features. Accordingly, this paper seeks to characterize mathematically the six basic emotions in humans: boredom, disgust, happiness, anxiety, anger and sadness, also included the neutrality, for a total of seven states to identify.

Usability flaws of medication-related alerting functions: A systematic qualitative review.

PubMed

Marcilly, Romaric; Ammenwerth, Elske; Vasseur, Francis; Roehrer, Erin; Beuscart-Zéphir, Marie-Catherine

2015-06-01

Medication-related alerting functions may include usability flaws that limit their optimal use. A first step on the way to preventing usability flaws is to understand the characteristics of these usability flaws. This systematic qualitative review aims to analyze the type of usability flaws found in medication-related alerting functions. Papers were searched via PubMed, Scopus and Ergonomics Abstracts databases, along with references lists. Paper selection, data extraction and data analysis was performed by two to three Human Factors experts. Meaningful semantic units representing instances of usability flaws were the main data extracted. They were analyzed through qualitative methods: categorization following general usability heuristics and through an inductive process for the flaws specific to medication-related alerting functions. From the 6380 papers initially identified, 26 met all eligibility criteria. The analysis of the papers identified a total of 168 instances of usability flaws that could be classified into 13 categories of usability flaws representing either violations of general usability principles (i.e. they could be found in any system, e.g. guidance and workload issues) or infractions specific to medication-related alerting functions. The latter refer to issues of low signal-to-noise ratio, incomplete content of alerts, transparency, presentation mode and timing, missing alert features, tasks and control distribution. The list of 168 instances of usability flaws of medication-related alerting functions provides a source of knowledge for checking the usability of medication-related alerting functions during their design and evaluation process and ultimately constructs evidence-based usability design principles for these functions. Copyright © 2015 Elsevier Inc. All rights reserved.

EASY-HIT: HIV full-replication technology for broad discovery of multiple classes of HIV inhibitors.

PubMed

Kremb, Stephan; Helfer, Markus; Heller, Werner; Hoffmann, Dieter; Wolff, Horst; Kleinschmidt, Andrea; Cepok, Sabine; Hemmer, Bernhard; Durner, Jörg; Brack-Werner, Ruth

2010-12-01

HIV replication assays are important tools for HIV drug discovery efforts. Here, we present a full HIV replication system (EASY-HIT) for the identification and analysis of HIV inhibitors. This technology is based on adherently growing HIV-susceptible cells, with a stable fluorescent reporter gene activated by HIV Tat and Rev. A fluorescence-based assay was designed that measures HIV infection by two parameters relating to the early and the late phases of HIV replication, respectively. Validation of the assay with a panel of nine reference inhibitors yielded effective inhibitory concentrations consistent with published data and allowed discrimination between inhibitors of early and late phases of HIV replication. Finer resolution of the effects of reference drugs on different steps of HIV replication was achieved in secondary time-of-addition assays. The EASY-HIT assay yielded high Z' scores (>0.9) and signal stabilities, confirming its robustness. Screening of the LOPAC(1280) library identified 10 compounds (0.8%), of which eight were known to inhibit HIV, validating the suitability of this assay for screening applications. Studies evaluating anti-HIV activities of natural products with the EASY-HIT technology led to the identification of three novel inhibitory compounds that apparently act at different steps of HIV-1 replication. Furthermore, we demonstrate successful evaluation of plant extracts for HIV-inhibitory activities, suggesting application of this technology for the surveillance of biological extracts with anti-HIV activities. We conclude that the EASY-HIT technology is a versatile tool for the discovery and characterization of HIV inhibitors.

Spatial reference frames of visual, vestibular, and multimodal heading signals in the dorsal subdivision of the medial superior temporal area.

PubMed

Fetsch, Christopher R; Wang, Sentao; Gu, Yong; Deangelis, Gregory C; Angelaki, Dora E

2007-01-17

Heading perception is a complex task that generally requires the integration of visual and vestibular cues. This sensory integration is complicated by the fact that these two modalities encode motion in distinct spatial reference frames (visual, eye-centered; vestibular, head-centered). Visual and vestibular heading signals converge in the primate dorsal subdivision of the medial superior temporal area (MSTd), a region thought to contribute to heading perception, but the reference frames of these signals remain unknown. We measured the heading tuning of MSTd neurons by presenting optic flow (visual condition), inertial motion (vestibular condition), or a congruent combination of both cues (combined condition). Static eye position was varied from trial to trial to determine the reference frame of tuning (eye-centered, head-centered, or intermediate). We found that tuning for optic flow was predominantly eye-centered, whereas tuning for inertial motion was intermediate but closer to head-centered. Reference frames in the two unimodal conditions were rarely matched in single neurons and uncorrelated across the population. Notably, reference frames in the combined condition varied as a function of the relative strength and spatial congruency of visual and vestibular tuning. This represents the first investigation of spatial reference frames in a naturalistic, multimodal condition in which cues may be integrated to improve perceptual performance. Our results compare favorably with the predictions of a recent neural network model that uses a recurrent architecture to perform optimal cue integration, suggesting that the brain could use a similar computational strategy to integrate sensory signals expressed in distinct frames of reference.

Control means for a gas turbine engine

NASA Technical Reports Server (NTRS)

Beitler, R. S.; Sellers, F. J.; Bennett, G. W. (Inventor)

1982-01-01

A means is provided for developing a signal representative of the actual compressor casing temperature, a second signal representative of compressor inlet gas temperature, and a third signal representative of compressor speed. Another means is provided for receiving the gas temperature and compressor speed signals and developing a schedule output signal which is a representative of a reference casing temperature at which a predetermined compressor blade stabilized clearance is provided. A means is also provided for comparing the actual compressor casing temperature signal and the reference casing temperature signal and developing a clearance control system representative of the difference. The clearance control signal is coupled to a control valve which controls a flow of air to the compressor casing to control the clearance between the compressor blades and the compressor casing. The clearance control signal can be modified to accommodate transient characteristics. Other embodiments are disclosed.

Approximate circuits for increased reliability

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

Hamlet, Jason R.; Mayo, Jackson R.

2015-08-18

Embodiments of the invention describe a Boolean circuit having a voter circuit and a plurality of approximate circuits each based, at least in part, on a reference circuit. The approximate circuits are each to generate one or more output signals based on values of received input signals. The voter circuit is to receive the one or more output signals generated by each of the approximate circuits, and is to output one or more signals corresponding to a majority value of the received signals. At least some of the approximate circuits are to generate an output value different than the referencemore » circuit for one or more input signal values; however, for each possible input signal value, the majority values of the one or more output signals generated by the approximate circuits and received by the voter circuit correspond to output signal result values of the reference circuit.« less

Detection of Acetone Processing of Castor Bean Mash for Forensic Investigation of Ricin Preparation Methods

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

Kreuzer-Martin, Helen W.; Wahl, Jon H.; Metoyer, Candace N.

The toxic protein ricin is of concern as a potential biological threat agent (BTA) Recently, several samples of ricin have been seized in connection with biocriminal activity. Analytical methods are needed that enable federal investigators to determine how the samples were prepared, to match seized samples to potential source materials, and to identify samples that may have been prepared by the same method using the same source materials. One commonly described crude ricin preparation method is acetone extraction of crushed castor beans. Here we describe the use of solid-phase microextraction and headspace analysis of crude ricin preparation samples to determinemore » whether they were processed by acetone extraction. In all cases, acetone-extracted bean mash could be distinguished from un-extracted mash or mash extracted with other organic solvents. Statistical analysis showed that storage in closed containers for up to 109 days had no effect on acetone signal intensity. Signal intensity in acetone-extracted mash decreased during storage in open containers, but extracted mash could still be distinguished from un-extracted mash after 94 days.« less

Extracting stationary segments from non-stationary synthetic and cardiac signals

NASA Astrophysics Data System (ADS)

Rodríguez, María. G.; Ledezma, Carlos A.; Perpiñán, Gilberto; Wong, Sara; Altuve, Miguel

2015-01-01

Physiological signals are commonly the result of complex interactions between systems and organs, these interactions lead to signals that exhibit a non-stationary behaviour. For cardiac signals, non-stationary heart rate variability (HRV) may produce misinterpretations. A previous work proposed to divide a non-stationary signal into stationary segments by looking for changes in the signal's properties related to changes in the mean of the signal. In this paper, we extract stationary segments from non-stationary synthetic and cardiac signals. For synthetic signals with different signal-to-noise ratio levels, we detect the beginning and end of the stationary segments and the result is compared to the known values of the occurrence of these events. For cardiac signals, RR interval (cardiac cycle length) time series, obtained from electrocardiographic records during stress tests for two populations (diabetic patients with cardiovascular autonomic neuropathy and control subjects), were divided into stationary segments. Results on synthetic signals reveal that the non-stationary sequence is divided into more stationary segments than needed. Additionally, due to HRV reduction and exercise intolerance reported on diabetic cardiovascular autonomic neuropathy patients, non-stationary RR interval sequences from these subjects can be divided into longer stationary segments compared to the control group.

Contaminated sediments from tributaries of the Great Lakes: Chemical characterization and carcinogenic effects in medaka (Oryzias latipes)

USGS Publications Warehouse

Besser, John M.; Schmitt, Christopher J.; Harshbarger, John C.; Peterman, Paul H.; Lebo, Jon A.

1991-01-01

Sediments from four inshore industrial sites and a reference site in the Great Lakes were extracted with organic solvents to produce a crude extract, which was separated on alumina into two fractions: predominantly polycyclic aromatic hydrocarbons; and predominantly nitrogencontaining polycyclic aromatic compounds. Crude extracts were redissolved in acetone and analyzed by gas chromatography and gas chromatography-mass spectrometry. The acetone-redissolved crude extracts from the four industrialized sites contained 5.6–313.3 μg total polycyclic aromatic compounds/g sediment and 3.0–36.4 μg other compounds/g sediment. In addition to the typical EPA priority pollutants, a substantial amount (228.7 μg/g sediment) of alkyl-polycyclic-aromatic compounds was detected in sediments from one of the industrialized sites. Extracts from the reference site contained 1.55 μg total polycyclic aromatic compounds/ g sediment. Medaka (Oryzias latipes) were exposed to multiple pulse doses of acetone-redissolved extracts and fractions. Medaka were also exposed to a known carcinogen, methylazoxymethanol acetate, to verify that chemicals produced tumors in the test fish. Acetone-redissolved extracts and fractions from contaminated sediments were toxic to medaka. Fin erosion and non-neoplastic liver abnormalities were more prevalent in medaka after exposure to acetoneredissolved extracts and fractions from contaminated sediments. Neoplasms previously associated with chemical exposure in wild fishes were induced in medaka exposed to acetone-redissolved extracts and fractions from two of the contaminated sites, but not from the reference site or controls. These findings further support the hypothesis that chemical contaminants in sediments are involved in epizootics of neoplasms in wild fishes at contaminated sites.

Extracting protein dynamics information from overlapped NMR signals using relaxation dispersion difference NMR spectroscopy.

PubMed

Konuma, Tsuyoshi; Harada, Erisa; Sugase, Kenji

2015-12-01

Protein dynamics plays important roles in many biological events, such as ligand binding and enzyme reactions. NMR is mostly used for investigating such protein dynamics in a site-specific manner. Recently, NMR has been actively applied to large proteins and intrinsically disordered proteins, which are attractive research targets. However, signal overlap, which is often observed for such proteins, hampers accurate analysis of NMR data. In this study, we have developed a new methodology called relaxation dispersion difference that can extract conformational exchange parameters from overlapped NMR signals measured using relaxation dispersion spectroscopy. In relaxation dispersion measurements, the signal intensities of fluctuating residues vary according to the Carr-Purcell-Meiboon-Gill pulsing interval, whereas those of non-fluctuating residues are constant. Therefore, subtraction of each relaxation dispersion spectrum from that with the highest signal intensities, measured at the shortest pulsing interval, leaves only the signals of the fluctuating residues. This is the principle of the relaxation dispersion difference method. This new method enabled us to extract exchange parameters from overlapped signals of heme oxygenase-1, which is a relatively large protein. The results indicate that the structural flexibility of a kink in the heme-binding site is important for efficient heme binding. Relaxation dispersion difference requires neither selectively labeled samples nor modification of pulse programs; thus it will have wide applications in protein dynamics analysis.

Adventitious sounds identification and extraction using temporal-spectral dominance-based features.

PubMed

Jin, Feng; Krishnan, Sridhar Sri; Sattar, Farook

2011-11-01

Respiratory sound (RS) signals carry significant information about the underlying functioning of the pulmonary system by the presence of adventitious sounds (ASs). Although many studies have addressed the problem of pathological RS classification, only a limited number of scientific works have focused on the analysis of the evolution of symptom-related signal components in joint time-frequency (TF) plane. This paper proposes a new signal identification and extraction method for various ASs based on instantaneous frequency (IF) analysis. The presented TF decomposition method produces a noise-resistant high definition TF representation of RS signals as compared to the conventional linear TF analysis methods, yet preserving the low computational complexity as compared to those quadratic TF analysis methods. The discarded phase information in conventional spectrogram has been adopted for the estimation of IF and group delay, and a temporal-spectral dominance spectrogram has subsequently been constructed by investigating the TF spreads of the computed time-corrected IF components. The proposed dominance measure enables the extraction of signal components correspond to ASs from noisy RS signal at high noise level. A new set of TF features has also been proposed to quantify the shapes of the obtained TF contours, and therefore strongly, enhances the identification of multicomponents signals such as polyphonic wheezes. An overall accuracy of 92.4±2.9% for the classification of real RS recordings shows the promising performance of the presented method.

Implantable brain computer interface: challenges to neurotechnology translation.

PubMed

Konrad, Peter; Shanks, Todd

2010-06-01

This article reviews three concepts related to implantable brain computer interface (BCI) devices being designed for human use: neural signal extraction primarily for motor commands, signal insertion to restore sensation, and technological challenges that remain. A significant body of literature has occurred over the past four decades regarding motor cortex signal extraction for upper extremity movement or computer interface. However, little is discussed regarding postural or ambulation command signaling. Auditory prosthesis research continues to represent the majority of literature on BCI signal insertion. Significant hurdles continue in the technological translation of BCI implants. These include developing a stable neural interface, significantly increasing signal processing capabilities, and methods of data transfer throughout the human body. The past few years, however, have provided extraordinary human examples of BCI implant potential. Despite technological hurdles, proof-of-concept animal and human studies provide significant encouragement that BCI implants may well find their way into mainstream medical practice in the foreseeable future.

Measurement of water-soluble B vitamins in infant formula by liquid chromatography/tandem mass spectrometry.

PubMed

Huang, Min; Winters, Doug; Crowley, Richard; Sullivan, Darryl

2009-01-01

A method has been developed for the simultaneous measurement of multiple B vitamins (i.e., B1, B2, B3, B5, and B6) in infant formulas by LC-MSIMS. The vitamins were extracted with acidic solvent, followed by protein precipitation at a pH range of 4.5 to 5.5, and filtered. This simplified procedure eliminates many of the potential sources of laboratory error and facilitates rapid and efficient analysis. As is common in most cases, isotope internal standards were added to account for variations in sample preparation, as well as changes in MS measurement. In this method, isotope-labeled internal standards of B1, B3, B5, and B6 were used. The factors affecting analytical performance were investigated and optimized. In addition, the stability of these vitamins in the extraction solution was investigated. An acidic condition (5 mM HCl) was applied to successfully stabilize B1, which had shown a decrease in signal when other solvents were used. The quantitative extraction and good stability allowed isotope standards to be added to the filtered sample solution, instead of to the extraction solvent. The addition of the isotope to the small portion of the filtered sample solution significantly reduces cost. A comprehensive evaluation of the analysis of the standard reference material and good spike recovery of the vitamins (100 +/- 6%) demonstrates the accuracy of the method. The results for commercially available infant formula samples were also compared with those obtained using the current microbiological method.

Variable frequency microprocessor clock generator

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

Branson, C.N.

A microprocessor-based system is described comprising: a digital central microprocessor provided with a clock input and having a rate of operation determined by the frequency of a clock signal input thereto; memory means operably coupled to the central microprocessor for storing programs respectively including a plurality of instructions and addressable by the central microprocessor; peripheral device operably connected to the central microprocessor, the first peripheral device being addressable by the central microprocessor for control thereby; a system clock generator for generating a digital reference clock signal having a reference frequency rate; and frequency rate reduction circuit means connected between themore » clock generator and the clock input of the central microprocessor for selectively dividing the reference clock signal to generate a microprocessor clock signal as an input to the central microprocessor for clocking the central microprocessor.« less

Apparatus configured for identification of a material and method of identifying a material

DOEpatents

Slater, John M.; Crawford, Thomas M.; Frickey, Dean A.

2001-01-01

The present invention relates to an apparatus configured for identification of a material and method of identifying a material. One embodiment of the present invention provides an apparatus configured for identification of a material including a first region configured to receive a first sample and output a first spectrum responsive to exposure of the first sample to radiation; a signal generator configured to provide a reference signal having a reference frequency and a modulation signal having a modulation frequency; a modulator configured to selectively modulate the first spectrum using the modulation signal according to the reference frequency; a second region configured to receive a second sample and output a second spectrum responsive to exposure of the second sample to the first spectrum; and a detector configured to detect the second spectrum.

Genetic algorithm for the optimization of features and neural networks in ECG signals classification

NASA Astrophysics Data System (ADS)

Li, Hongqiang; Yuan, Danyang; Ma, Xiangdong; Cui, Dianyin; Cao, Lu

2017-01-01

Feature extraction and classification of electrocardiogram (ECG) signals are necessary for the automatic diagnosis of cardiac diseases. In this study, a novel method based on genetic algorithm-back propagation neural network (GA-BPNN) for classifying ECG signals with feature extraction using wavelet packet decomposition (WPD) is proposed. WPD combined with the statistical method is utilized to extract the effective features of ECG signals. The statistical features of the wavelet packet coefficients are calculated as the feature sets. GA is employed to decrease the dimensions of the feature sets and to optimize the weights and biases of the back propagation neural network (BPNN). Thereafter, the optimized BPNN classifier is applied to classify six types of ECG signals. In addition, an experimental platform is constructed for ECG signal acquisition to supply the ECG data for verifying the effectiveness of the proposed method. The GA-BPNN method with the MIT-BIH arrhythmia database achieved a dimension reduction of nearly 50% and produced good classification results with an accuracy of 97.78%. The experimental results based on the established acquisition platform indicated that the GA-BPNN method achieved a high classification accuracy of 99.33% and could be efficiently applied in the automatic identification of cardiac arrhythmias.

A first approach to the distortion analysis of nonlinear analog circuits utilizing X-parameters

NASA Astrophysics Data System (ADS)

Weber, H.; Widemann, C.; Mathis, W.

2013-07-01

In this contribution a first approach to the distortion analysis of nonlinear 2-port-networks with X-parameters1 is presented. The X-parameters introduced by Verspecht and Root (2006) offer the possibility to describe nonlinear microwave 2-port-networks under large signal conditions. On the basis of X-parameter measurements with a nonlinear network analyzer (NVNA) behavioral models can be extracted for the networks. These models can be used to consider the nonlinear behavior during the design process of microwave circuits. The idea of the present work is to extract the behavioral models in order to describe the influence of interfering signals on the output behavior of the nonlinear circuits. Hereby, a simulator is used instead of a NVNA to extract the X-parameters. Assuming that the interfering signals are relatively small compared to the nominal input signal, the output signal can be described as a superposition of the effects of each input signal. In order to determine the functional correlation between the scattering variables, a polynomial dependency is assumed. The required datasets for the approximation of the describing functions are simulated by a directional coupler model in Cadence Design Framework. The polynomial coefficients are obtained by a least-square method. The resulting describing functions can be used to predict the system's behavior under certain conditions as well as the effects of the interfering signal on the output signal. 1 X-parameter is a registered trademark of Agilent Technologies, Inc.

Reprint of “Non-causal spike filtering improves decoding of movement intention for intracortical BCIs”☆

PubMed Central

Masse, Nicolas Y.; Jarosiewicz, Beata; Simeral, John D.; Bacher, Daniel; Stavisky, Sergey D.; Cash, Sydney S.; Oakley, Erin M.; Berhanu, Etsub; Eskandar, Emad; Friehs, Gerhard; Hochberg, Leigh R.; Donoghue, John P.

2015-01-01

Background Multiple types of neural signals are available for controlling assistive devices through brain–computer interfaces (BCIs). Intracortically recorded spiking neural signals are attractive for BCIs because they can in principle provide greater fidelity of encoded information compared to electrocorticographic (ECoG) signals and electroencephalograms (EEGs). Recent reports show that the information content of these spiking neural signals can be reliably extracted simply by causally band-pass filtering the recorded extracellular voltage signals and then applying a spike detection threshold, without relying on “sorting” action potentials. New method We show that replacing the causal filter with an equivalent non-causal filter increases the information content extracted from the extracellular spiking signal and improves decoding of intended movement direction. This method can be used for real-time BCI applications by using a 4 ms lag between recording and filtering neural signals. Results Across 18 sessions from two people with tetraplegia enrolled in the BrainGate2 pilot clinical trial, we found that threshold crossing events extracted using this non-causal filtering method were significantly more informative of each participant’s intended cursor kinematics compared to threshold crossing events derived from causally filtered signals. This new method decreased the mean angular error between the intended and decoded cursor direction by 9.7° for participant S3, who was implanted 5.4 years prior to this study, and by 3.5° for participant T2, who was implanted 3 months prior to this study. PMID:25681017

A universal reference sample derived from clone vector for improved detection of differential gene expression

PubMed Central

Khan, Rishi L; Gonye, Gregory E; Gao, Guang; Schwaber, James S

2006-01-01

Background Using microarrays by co-hybridizing two samples labeled with different dyes enables differential gene expression measurements and comparisons across slides while controlling for within-slide variability. Typically one dye produces weaker signal intensities than the other often causing signals to be undetectable. In addition, undetectable spots represent a large problem for two-color microarray designs and most arrays contain at least 40% undetectable spots even when labeled with reference samples such as Stratagene's Universal Reference RNAs™. Results We introduce a novel universal reference sample that produces strong signal for all spots on the array, increasing the average fraction of detectable spots to 97%. Maximizing detectable spots on the reference image channel also decreases the variability of microarray data allowing for reliable detection of smaller differential gene expression changes. The reference sample is derived from sequence contained in the parental EST clone vector pT7T3D-Pac and is called vector RNA (vRNA). We show that vRNA can also be used for quality control of microarray printing and PCR product quality, detection of hybridization anomalies, and simplification of spot finding and segmentation tasks. This reference sample can be made inexpensively in large quantities as a renewable resource that is consistent across experiments. Conclusion Results of this study show that vRNA provides a useful universal reference that yields high signal for almost all spots on a microarray, reduces variation and allows for comparisons between experiments and laboratories. Further, it can be used for quality control of microarray printing and PCR product quality, detection of hybridization anomalies, and simplification of spot finding and segmentation tasks. This type of reference allows for detection of small changes in differential expression while reference designs in general allow for large-scale multivariate experimental designs. vRNA in combination with reference designs enable systems biology microarray experiments of small physiologically relevant changes. PMID:16677381

Early diagnostic of concurrent gear degradation processes progressing under time-varying loads

NASA Astrophysics Data System (ADS)

Guilbault, Raynald; Lalonde, Sébastien

2016-08-01

This study develops a gear diagnostic procedure for the detection of multi- and concurrent degradation processes evolving under time-varying loads. Instead of a conventional comparison between a descriptor and an alarm level, this procedure bases its detection strategy on a descriptor evolution tracking; a lasting descriptor increase denotes the presence of ongoing degradation mechanisms. The procedure works from time domain residual signals prepared in the frequency domain, and accepts any gear conditions as reference signature. To extract the load fluctuation repercussions, the procedure integrates a scaling factor. The investigation first examines a simplification assuming a linear connection between the load and the dynamic response amplitudes. However, while generally valuable, the precision losses associated with large load variations may mask the contribution of tiny flaws. To better reflect the real non-linear relation, the paper reformulates the scaling factor; a power law with an exponent value of 0.85 produces noticeable improvements of the load effect extraction. To reduce the consequences of remaining oscillations, the procedure also includes a filtering phase. During the validation program, a synthetic wear progression assuming a commensurate relation between the wear depth and friction assured controlled evolutions of the surface degradation influence, whereas the fillet crack growth remained entirely determined by the operation conditions. Globally, the tested conditions attest that the final strategy provides accurate monitoring of coexisting isolated damages and general surface deterioration, and that its tracking-detection capacities are unaffected by severe time variations of external loads. The procedure promptly detects the presence of evolving abnormal phenomena. The tests show that the descriptor curve shapes virtually describe the constant wear progression superimposed on the crack length evolution. At the tooth fracture, the mean values of the residual signal evince strong perturbations, while after this episode, the monitoring curves continue signaling the ongoing wear process.

Automatic Detection of Seismocardiogram Sensor Misplacement for Robust Pre-Ejection Period Estimation in Unsupervised Settings.

PubMed

Ashouri, Hazar; Inan, Omer T

2017-06-15

Seismocardiography (SCG), the measurement of the local chest vibrations due to the movements of blood and the heart, is a non-invasive technique for assessing myocardial contractility via the pre-ejection period (PEP). Recently, SCG-based extraction of PEP has been shown to be an effective means of classifying decompensated from compensated heart failure patients, and thus can be potentially used for monitoring such patients at home. Accurate extraction of PEP from SCG signals hinges on lab-based population data (i.e., regression curves) linking particular time-domain features of the SCG signal to corresponding features from reference standard bulky instruments such as impedance cardiography (ICG). Such regression curves, in the case of SCG, have always been estimated based on the "ideal" positioning of the SCG sensor on the chest. However, in settings such as the home where users may position the SCG measurement hardware on the chest without supervision, it is likely that the sensor will not always be placed exactly on this "ideal" location on the sternum, but rather on other positions on the chest as well. In this study, we show for the first time that the regression curve for estimating PEP from SCG signals differs significantly as the position of the sensor changes. We further devise a method to automatically detect when the sensor is placed in any position other than the desired one in order to avoid inaccurate systolic time interval estimation. Our classification algorithm for this purpose resulted in 0.83 precision and 0.82 recall when classifying whether the sensor is placed in the desired position or not. The classifier was tested with heartbeats taken both at rest, and also during exercise recovery to ensure that waveform changes due to positioning could be accurately discriminated from those due to physiological effects.

Microwave assisted extraction for trace element analysis of plant materials by ICP-AES.

PubMed

Borkowska-Burnecka, J

2000-11-01

Application of microwave assisted extraction for the decomposition and dissolution of plant samples for trace metal determination by ICP-AES was examined. Dried onion, leaves of spinach beet and three reference materials CTA-OTL-1, CTA-VTL-2 and CL-1 were analyzed. Water, EDTA and hydrochloric acid (0.01, 0.10 and 1.0 M, respectively) were used as leaching solutions. The extraction efficiency was investigated by comparison of the results with those obtained after microwave wet digestion. HCl was found to be very suitable for quantitative extraction of B, Ba, Cd, Cu, Mn, Ni, Pb, Sr and Zn from the samples. For reference materials, the measured concentrations are well consistent with the certified values. The use of EDTA led to a complete extraction of B, Cd, Ni, Pb, Sr and Zn. Water was found to be a good leaching solution for boron. For extraction with HCl and EDTA, the RSD values for the concentrations measured were below 8% for most of the elements.

Reference analysis of the signal + background model in counting experiments II. Approximate reference prior

NASA Astrophysics Data System (ADS)

Casadei, D.

2014-10-01

The objective Bayesian treatment of a model representing two independent Poisson processes, labelled as ``signal'' and ``background'' and both contributing additively to the total number of counted events, is considered. It is shown that the reference prior for the parameter of interest (the signal intensity) can be well approximated by the widely (ab)used flat prior only when the expected background is very high. On the other hand, a very simple approximation (the limiting form of the reference prior for perfect prior background knowledge) can be safely used over a large portion of the background parameters space. The resulting approximate reference posterior is a Gamma density whose parameters are related to the observed counts. This limiting form is simpler than the result obtained with a flat prior, with the additional advantage of representing a much closer approximation to the reference posterior in all cases. Hence such limiting prior should be considered a better default or conventional prior than the uniform prior. On the computing side, it is shown that a 2-parameter fitting function is able to reproduce extremely well the reference prior for any background prior. Thus, it can be useful in applications requiring the evaluation of the reference prior for a very large number of times.

Herbal Extract SH003 Suppresses Tumor Growth and Metastasis of MDA-MB-231 Breast Cancer Cells by Inhibiting STAT3-IL-6 Signaling

PubMed Central

Woo, Sang-Mi; Park, Sunju; Shin, Yong Cheol; Ko, Seong-Gyu

2014-01-01

Cancer inflammation promotes cancer progression, resulting in a high risk of cancer. Here, we demonstrate that our new herbal extract, SH003, suppresses both tumor growth and metastasis of MDA-MB-231 breast cancer cells via inhibiting STAT3-IL-6 signaling path. Our new herbal formula, SH003, mixed extract from Astragalus membranaceus, Angelica gigas, and Trichosanthes kirilowii Maximowicz, suppressed MDA-MB-231 tumor growth and lung metastasis in vivo and reduced the viability and metastatic abilities of MDA-MB-231 cells in vitro. Furthermore, SH003 inhibited STAT3 activation, which resulted in a reduction of IL-6 production. Therefore, we conclude that SH003 suppresses highly metastatic breast cancer growth and metastasis by inhibiting STAT3-IL-6 signaling path. PMID:24976685

Design and fabrication of SiO2/TiO2 and MgO/TiO2 based high selective optical filters for diffuse reflectance and fluorescence signals extraction

PubMed Central

Pimenta, S.; Cardoso, S.; Miranda, A.; De Beule, P.; Castanheira, E.M.S.; Minas, G.

2015-01-01

This paper presents the design, optimization and fabrication of 16 MgO/TiO2 and SiO2/TiO2 based high selective narrow bandpass optical filters. Their performance to extract diffuse reflectance and fluorescence signals from gastrointestinal tissue phantoms was successfully evaluated. The obtained results prove their feasibility to correctly extract those spectroscopic signals, through a Spearman’s rank correlation test (Spearman’s correlation coefficient higher than 0.981) performed between the original spectra and the ones obtained using those 16 fabricated optical filters. These results are an important step for the implementation of a miniaturized, low-cost and minimal invasive microsystem that could help in the detection of gastrointestinal dysplasia. PMID:26309769

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

PubMed

Jaiswal, Abeg Kumar; Banka, Haider

2017-01-01

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

To perform a gyro test of general relativity in a satellite and develop associated control technology

NASA Technical Reports Server (NTRS)

Fairbank, W. M.; Everitt, C. W. F.; Debra, D. B.

1977-01-01

A satellite configuration having two gyroscopes with axes parallel to the boresight of a telescope and two at right angles to the telescope and approximately parallel and perpendicular to the earth's axis is proposed for measuring geodetic precessions due to the earth's motion about the sun, higher order geodetic terms calculated from the earth's quadrapole mass moment (0.010 arc-sec/year in a 400 nautical mile polar orbit), and deflection by the sun of the starlight signal for the reference telescope. Data from the experiment also contain large periodic signals due to the annual and orbital aberrations of starlight which are useful in providing a built in reference signal of known amplitude for scaling the relativity signals, and should yield a singularly precise measurement of the parallax of the reference star. The development of the gyroscope and its readout system are discussed, as well as signal integration, drag-free control, and attitude control.

Portable digital lock-in instrument to determine chemical constituents with single-color absorption measurements for Global Health Initiatives

NASA Astrophysics Data System (ADS)

Vacas-Jacques, Paulino; Linnes, Jacqueline; Young, Anna; Gerrard, Victoria; Gomez-Marquez, Jose

2014-03-01

Innovations in international health require the use of state-of-the-art technology to enable clinical chemistry for diagnostics of bodily fluids. We propose the implementation of a portable and affordable lock-in amplifier-based instrument that employs digital technology to perform biochemical diagnostics on blood, urine, and other fluids. The digital instrument is composed of light source and optoelectronic sensor, lock-in detection electronics, microcontroller unit, and user interface components working with either power supply or batteries. The instrument performs lock-in detection provided that three conditions are met. First, the optoelectronic signal of interest needs be encoded in the envelope of an amplitude-modulated waveform. Second, the reference signal required in the demodulation channel has to be frequency and phase locked with respect to the optoelectronic carrier signal. Third, the reference signal should be conditioned appropriately. We present three approaches to condition the signal appropriately: high-pass filtering the reference signal, precise offset tuning the reference level by low-pass filtering, and by using a voltage divider network. We assess the performance of the lock-in instrument by comparing it to a benchmark device and by determining protein concentration with single-color absorption measurements. We validate the concentration values obtained with the proposed instrument using chemical concentration measurements. Finally, we demonstrate that accurate retrieval of phase information can be achieved by using the same instrument.

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

Vacas-Jacques, Paulino; Wellman Center for Photomedicine and Harvard Medical School, Massachusetts General Hospital, Boston, Massachusetts 02114; Linnes, Jacqueline

Innovations in international health require the use of state-of-the-art technology to enable clinical chemistry for diagnostics of bodily fluids. We propose the implementation of a portable and affordable lock-in amplifier-based instrument that employs digital technology to perform biochemical diagnostics on blood, urine, and other fluids. The digital instrument is composed of light source and optoelectronic sensor, lock-in detection electronics, microcontroller unit, and user interface components working with either power supply or batteries. The instrument performs lock-in detection provided that three conditions are met. First, the optoelectronic signal of interest needs be encoded in the envelope of an amplitude-modulated waveform. Second,more » the reference signal required in the demodulation channel has to be frequency and phase locked with respect to the optoelectronic carrier signal. Third, the reference signal should be conditioned appropriately. We present three approaches to condition the signal appropriately: high-pass filtering the reference signal, precise offset tuning the reference level by low-pass filtering, and by using a voltage divider network. We assess the performance of the lock-in instrument by comparing it to a benchmark device and by determining protein concentration with single-color absorption measurements. We validate the concentration values obtained with the proposed instrument using chemical concentration measurements. Finally, we demonstrate that accurate retrieval of phase information can be achieved by using the same instrument.« less

Self-referenced continuous-variable quantum key distribution

DOEpatents

Soh, Daniel B. S.; Sarovar, Mohan; Camacho, Ryan

2017-01-24

Various technologies for continuous-variable quantum key distribution without transmitting a transmitter's local oscillator are described herein. A receiver on an optical transmission channel uses an oscillator signal generated by a light source at the receiver's location to perform interferometric detection on received signals. An optical reference pulse is sent by the transmitter on the transmission channel and the receiver computes a phase offset of the transmission based on quadrature measurements of the reference pulse. The receiver can then compensate for the phase offset between the transmitter's reference and the receiver's reference when measuring quadratures of received data pulses.

Compensated vibrating optical fiber pressure measuring device

DOEpatents

Fasching, George E.; Goff, David R.

1987-01-01

A microbending optical fiber is attached under tension to a diaphragm to se a differential pressure applied across the diaphragm which it causes it to deflect. The fiber is attached to the diaphragm so that one portion of the fiber, attached to a central portion of the diaphragm, undergoes a change in tension; proportional to the differential pressure applied to the diaphragm while a second portion attached at the periphery of the diaphragm remains at a reference tension. Both portions of the fiber are caused to vibrate at their natural frequencies. Light transmitted through the fiber is attenuated by both portions of the tensioned sections of the fiber by an amount which increases with the curvature of fiber bending so that the light signal is modulated by both portions of the fiber at separate frequencies. The modulated light signal is transduced into a electrical signal. The separate modulation signals are detected to generate separate signals having frequencies corresponding to the reference and measuring vibrating sections of the continuous fiber, respectively. A signal proportional to the difference between these signals is generated which is indicative of the measured pressure differential across the diaphragm. The reference portion of the fiber is used to compensate the pressure signal for zero and span changes resulting from ambient temperature and humidity effects upon the fiber and the transducer fixture.

Signal separation by nonlinear projections: The fetal electrocardiogram

NASA Astrophysics Data System (ADS)

Schreiber, Thomas; Kaplan, Daniel T.

1996-05-01

We apply a locally linear projection technique which has been developed for noise reduction in deterministically chaotic signals to extract the fetal component from scalar maternal electrocardiographic (ECG) recordings. Although we do not expect the maternal ECG to be deterministic chaotic, typical signals are effectively confined to a lower-dimensional manifold when embedded in delay space. The method is capable of extracting fetal heart rate even when the fetal component and the noise are of comparable amplitude. If the noise is small, more details of the fetal ECG, like P and T waves, can be recovered.

Classification of burst and suppression in the neonatal electroencephalogram

NASA Astrophysics Data System (ADS)

Löfhede, J.; Löfgren, N.; Thordstein, M.; Flisberg, A.; Kjellmer, I.; Lindecrantz, K.

2008-12-01

Fisher's linear discriminant (FLD), a feed-forward artificial neural network (ANN) and a support vector machine (SVM) were compared with respect to their ability to distinguish bursts from suppressions in electroencephalograms (EEG) displaying a burst-suppression pattern. Five features extracted from the EEG were used as inputs. The study was based on EEG signals from six full-term infants who had suffered from perinatal asphyxia, and the methods have been trained with reference data classified by an experienced electroencephalographer. The results are summarized as the area under the curve (AUC), derived from receiver operating characteristic (ROC) curves for the three methods. Based on this, the SVM performs slightly better than the others. Testing the three methods with combinations of increasing numbers of the five features shows that the SVM handles the increasing amount of information better than the other methods.

Application of Reconfigurable Computing Technology to Multi-KiloHertz Micro-Laser Altimeter (MMLA) Data Processing

NASA Technical Reports Server (NTRS)

Powell, Wesley; Dabney, Philip; Hicks, Edward; Pinchinat, Maxime; Day, John H. (Technical Monitor)

2002-01-01

The Multi-KiloHertz Micro-Laser Altimeter (MMLA) is an aircraft based instrument developed by NASA Goddard Space Flight Center with several potential spaceflight applications. This presentation describes how reconfigurable computing technology was employed to perform MMLA signal extraction in real-time under realistic operating constraints. The MMLA is a "single-photon-counting" airborne laser altimeter that is used to measure land surface features such as topography and vegetation canopy height. This instrument has to date flown a number of times aboard the NASA P3 aircraft acquiring data at a number of sites in the Mid-Atlantic region. This instrument pulses a relatively low-powered laser at a very high rate (10 kHz) and then measures the time-of-flight of discrete returns from the target surface. The instrument then bins these measurements into a two-dimensional array (vertical height vs. horizontal ground track) and selects the most likely signal path through the array. Return data that does not correspond to the selected signal path are classified as noise returns and are then discarded. The MMLA signal extraction algorithm is very compute intensive in that a score must be computed for every possible path through the two dimensional array in order to select the most likely signal path. Given a typical array size with 50 x 6, up to 33 arrays must be processed per second. And for each of these arrays, roughly 12,000 individual paths must be scored. Furthermore, the number of paths increases exponentially with the horizontal size of the array, and linearly with the vertical size. Yet, increasing the horizontal and vertical sizes of the array offer science advantages such as improved range, resolution, and noise rejection. Due to the volume of return data and the compute intensive signal extraction algorithm, the existing PC-based MMLA data system has been unable to perform signal extraction in real-time unless the array is limited in size to one column, This limits the ability of the MMLA to operate in environments with sparse signal returns and a high number of noise return. However, under an IR&D project, an FPGA-based, reconfigurable computing data system has been developed that has been demonstrated to perform real-time signal extraction under realistic operating constraints. This reconfigurable data system is based on the commercially available Firebird Board from Annapolis Microsystems. This PCI board consists of a Xilinx Virtex 2000E FPGA along with 36 MB of SRAM arranged in five separately addressable banks. This board is housed in a rackmount PC with dual 850MHz Pentium processors running the Windows 2000 operating system. This data system performs all signal extraction in hardware on the Firebird, but also runs the existing "software based" signal extraction in tandem for comparison purposes. Using a relatively small amount of the Virtex XCV2000E resources, the reconfigurable data system has demonstrated to improve performance improvement over the existing software based data system by an order of magnitude. Performance could be further improved by employing parallelism. Ground testing and a preliminary engineering test flight aboard the NASA P3 has been performed, during which the reconfigurable data system has been demonstrated to match the results of the existing data system.

Machine fault feature extraction based on intrinsic mode functions

NASA Astrophysics Data System (ADS)

Fan, Xianfeng; Zuo, Ming J.

2008-04-01

This work employs empirical mode decomposition (EMD) to decompose raw vibration signals into intrinsic mode functions (IMFs) that represent the oscillatory modes generated by the components that make up the mechanical systems generating the vibration signals. The motivation here is to develop vibration signal analysis programs that are self-adaptive and that can detect machine faults at the earliest onset of deterioration. The change in velocity of the amplitude of some IMFs over a particular unit time will increase when the vibration is stimulated by a component fault. Therefore, the amplitude acceleration energy in the intrinsic mode functions is proposed as an indicator of the impulsive features that are often associated with mechanical component faults. The periodicity of the amplitude acceleration energy for each IMF is extracted by spectrum analysis. A spectrum amplitude index is introduced as a method to select the optimal result. A comparison study of the method proposed here and some well-established techniques for detecting machinery faults is conducted through the analysis of both gear and bearing vibration signals. The results indicate that the proposed method has superior capability to extract machine fault features from vibration signals.

Pathological speech signal analysis and classification using empirical mode decomposition.

PubMed

Kaleem, Muhammad; Ghoraani, Behnaz; Guergachi, Aziz; Krishnan, Sridhar

2013-07-01

Automated classification of normal and pathological speech signals can provide an objective and accurate mechanism for pathological speech diagnosis, and is an active area of research. A large part of this research is based on analysis of acoustic measures extracted from sustained vowels. However, sustained vowels do not reflect real-world attributes of voice as effectively as continuous speech, which can take into account important attributes of speech such as rapid voice onset and termination, changes in voice frequency and amplitude, and sudden discontinuities in speech. This paper presents a methodology based on empirical mode decomposition (EMD) for classification of continuous normal and pathological speech signals obtained from a well-known database. EMD is used to decompose randomly chosen portions of speech signals into intrinsic mode functions, which are then analyzed to extract meaningful temporal and spectral features, including true instantaneous features which can capture discriminative information in signals hidden at local time-scales. A total of six features are extracted, and a linear classifier is used with the feature vector to classify continuous speech portions obtained from a database consisting of 51 normal and 161 pathological speakers. A classification accuracy of 95.7 % is obtained, thus demonstrating the effectiveness of the methodology.

An adaptive unsaturated bistable stochastic resonance method and its application in mechanical fault diagnosis

NASA Astrophysics Data System (ADS)

Qiao, Zijian; Lei, Yaguo; Lin, Jing; Jia, Feng

2017-02-01

In mechanical fault diagnosis, most traditional methods for signal processing attempt to suppress or cancel noise imbedded in vibration signals for extracting weak fault characteristics, whereas stochastic resonance (SR), as a potential tool for signal processing, is able to utilize the noise to enhance fault characteristics. The classical bistable SR (CBSR), as one of the most widely used SR methods, however, has the disadvantage of inherent output saturation. The output saturation not only reduces the output signal-to-noise ratio (SNR) but also limits the enhancement capability for fault characteristics. To overcome this shortcoming, a novel method is proposed to extract the fault characteristics, where a piecewise bistable potential model is established. Simulated signals are used to illustrate the effectiveness of the proposed method, and the results show that the method is able to extract weak fault characteristics and has good enhancement performance and anti-noise capability. Finally, the method is applied to fault diagnosis of bearings and planetary gearboxes, respectively. The diagnosis results demonstrate that the proposed method can obtain larger output SNR, higher spectrum peaks at fault characteristic frequencies and therefore larger recognizable degree than the CBSR method.

Bearing fault diagnosis under unknown time-varying rotational speed conditions via multiple time-frequency curve extraction

NASA Astrophysics Data System (ADS)

Huang, Huan; Baddour, Natalie; Liang, Ming

2018-02-01

Under normal operating conditions, bearings often run under time-varying rotational speed conditions. Under such circumstances, the bearing vibrational signal is non-stationary, which renders ineffective the techniques used for bearing fault diagnosis under constant running conditions. One of the conventional methods of bearing fault diagnosis under time-varying speed conditions is resampling the non-stationary signal to a stationary signal via order tracking with the measured variable speed. With the resampled signal, the methods available for constant condition cases are thus applicable. However, the accuracy of the order tracking is often inadequate and the time-varying speed is sometimes not measurable. Thus, resampling-free methods are of interest for bearing fault diagnosis under time-varying rotational speed for use without tachometers. With the development of time-frequency analysis, the time-varying fault character manifests as curves in the time-frequency domain. By extracting the Instantaneous Fault Characteristic Frequency (IFCF) from the Time-Frequency Representation (TFR) and converting the IFCF, its harmonics, and the Instantaneous Shaft Rotational Frequency (ISRF) into straight lines, the bearing fault can be detected and diagnosed without resampling. However, so far, the extraction of the IFCF for bearing fault diagnosis is mostly based on the assumption that at each moment the IFCF has the highest amplitude in the TFR, which is not always true. Hence, a more reliable T-F curve extraction approach should be investigated. Moreover, if the T-F curves including the IFCF, its harmonic, and the ISRF can be all extracted from the TFR directly, no extra processing is needed for fault diagnosis. Therefore, this paper proposes an algorithm for multiple T-F curve extraction from the TFR based on a fast path optimization which is more reliable for T-F curve extraction. Then, a new procedure for bearing fault diagnosis under unknown time-varying speed conditions is developed based on the proposed algorithm and a new fault diagnosis strategy. The average curve-to-curve ratios are utilized to describe the relationship of the extracted curves and fault diagnosis can then be achieved by comparing the ratios to the fault characteristic coefficients. The effectiveness of the proposed method is validated by simulated and experimental signals.

Boehmenan, a lignan from Hibiscus ficulneus, showed Wnt signal inhibitory activity.

PubMed

Shono, Takumi; Ishikawa, Naoki; Toume, Kazufumi; Arai, Midori A; Ahmed, Firoj; Sadhu, Samir K; Ishibashi, Masami

2015-07-15

The Wnt signal pathway modulates numerous biological processes, and its aberrant activation is related to various diseases. Therefore, inhibition of the Wnt signal may provide an effective (or efficient) strategy for these diseases. Cell-based luciferase assay targeting the Wnt signal (TOP assay) revealed that Hibiscus ficulneus extract inhibited the Wnt signal. The activity-guided isolation of the MeOH extract of H. ficulneus stems yielded four known (1-4) lignans along with myriceric acid (5). Compounds 1-4 potently inhibited the Wnt signal with TOPflash IC50 values of 1.0, 4.5, 6.3, and 1.9 μM, respectively. Compound 1 exhibited cytotoxicity against both Wnt-dependent (HCT116) and Wnt-independent (RKO) cells. Western blot analysis showed that 1 decreased the expression of full, cytosolic and nuclear β-catenin along with c-myc in STF/293 cells. Our results suggested that 1 may have inhibited the Wnt signal by decreasing β-catenin levels. Copyright © 2015 Elsevier Ltd. All rights reserved.

Repetitive transient extraction for machinery fault diagnosis using multiscale fractional order entropy infogram

NASA Astrophysics Data System (ADS)

Xu, Xuefang; Qiao, Zijian; Lei, Yaguo

2018-03-01

The presence of repetitive transients in vibration signals is a typical symptom of local faults of rotating machinery. Infogram was developed to extract the repetitive transients from vibration signals based on Shannon entropy. Unfortunately, the Shannon entropy is maximized for random processes and unable to quantify the repetitive transients buried in heavy random noise. In addition, the vibration signals always contain multiple intrinsic oscillatory modes due to interaction and coupling effects between machine components. Under this circumstance, high values of Shannon entropy appear in several frequency bands or high value of Shannon entropy doesn't appear in the optimal frequency band, and the infogram becomes difficult to interpret. Thus, it also becomes difficult to select the optimal frequency band for extracting the repetitive transients from the whole frequency bands. To solve these problems, multiscale fractional order entropy (MSFE) infogram is proposed in this paper. With the help of MSFE infogram, the complexity and nonlinear signatures of the vibration signals can be evaluated by quantifying spectral entropy over a range of scales in fractional domain. Moreover, the similarity tolerance of MSFE infogram is helpful for assessing the regularity of signals. A simulation and two experiments concerning a locomotive bearing and a wind turbine gear are used to validate the MSFE infogram. The results demonstrate that the MSFE infogram is more robust to the heavy noise than infogram and the high value is able to only appear in the optimal frequency band for the repetitive transient extraction.

A two-dimensional matrix image based feature extraction method for classification of sEMG: A comparative analysis based on SVM, KNN and RBF-NN.

PubMed

Wen, Tingxi; Zhang, Zhongnan; Qiu, Ming; Zeng, Ming; Luo, Weizhen

2017-01-01

The computer mouse is an important human-computer interaction device. But patients with physical finger disability are unable to operate this device. Surface EMG (sEMG) can be monitored by electrodes on the skin surface and is a reflection of the neuromuscular activities. Therefore, we can control limbs auxiliary equipment by utilizing sEMG classification in order to help the physically disabled patients to operate the mouse. To develop a new a method to extract sEMG generated by finger motion and apply novel features to classify sEMG. A window-based data acquisition method was presented to extract signal samples from sEMG electordes. Afterwards, a two-dimensional matrix image based feature extraction method, which differs from the classical methods based on time domain or frequency domain, was employed to transform signal samples to feature maps used for classification. In the experiments, sEMG data samples produced by the index and middle fingers at the click of a mouse button were separately acquired. Then, characteristics of the samples were analyzed to generate a feature map for each sample. Finally, the machine learning classification algorithms (SVM, KNN, RBF-NN) were employed to classify these feature maps on a GPU. The study demonstrated that all classifiers can identify and classify sEMG samples effectively. In particular, the accuracy of the SVM classifier reached up to 100%. The signal separation method is a convenient, efficient and quick method, which can effectively extract the sEMG samples produced by fingers. In addition, unlike the classical methods, the new method enables to extract features by enlarging sample signals' energy appropriately. The classical machine learning classifiers all performed well by using these features.

Hardware Verification of Laser Noise Cancellation and Gravitational Wave Extraction using Time-Delay Interferometry

NASA Astrophysics Data System (ADS)

Mitryk, Shawn; Mueller, Guido

The Laser Interferometer Space Antenna (LISA) is a space-based modified Michelson interfer-ometer designed to measure gravitational radiation in the frequency range from 30 uHz to 1 Hz. The interferometer measurement system (IMS) utilizes one-way laser phase measurements to cancel the laser phase noise, reconstruct the proof-mass motion, and extract the gravitational wave (GW) induced laser phase modulations in post-processing using a technique called time-delay interferometry (TDI). Unfortunately, there exist few hard-ware verification experiments of the IMS. The University of Florida LISA Interferometry Simulator (UFLIS) is designed to perform hardware-in-the-loop simulations of the LISA interferometry system, modeling the characteris-tics of the LISA mission as accurately as possible. This depends, first, on replicating the laser pre-stabilization by locking the laser phase to an ultra-stable Zerodur cavity length reference using the PDH locking method. Phase measurements of LISA-like photodetector beat-notes are taken using the UF-phasemeter (PM) which can measure the laser BN frequency to within an accuracy of 0.22 uHz. The inter-space craft (SC) laser links including the time-delay due to the 5 Gm light travel time along the LISA arms, the laser Doppler shifts due to differential SC motion, and the GW induced laser phase modulations are simulated electronically using the electronic phase delay (EPD) unit. The EPD unit replicates the laser field propagation between SC by measuring a photodetector beat-note frequency with the UF-phasemeter and storing the information in memory. After the requested delay time, the frequency information is added to a Doppler offset and a GW-like frequency modulation. The signal is then regenerated with the inter-SC laser phase affects applied. Utilizing these components, I will present the first complete TDI simulations performed using the UFLIS. The LISA model is presented along-side the simulation, comparing the generation and measurement of LISA-like signals. Phasemeter measurements are used in post-processing and combined in the linear combinations defined by TDI, thus, canceling the laser phase and phase-lock loop noise to extract the applied GW modulation buried under the noise. Nine order of magnitude common mode laser noise cancellation is achieved at a frequency of 1 mHz and the GW signal is clearly visible after the laser and PLL noise cancellation.

Mining association patterns of drug-interactions using post marketing FDA's spontaneous reporting data.

PubMed

Ibrahim, Heba; Saad, Amr; Abdo, Amany; Sharaf Eldin, A

2016-04-01

Pharmacovigilance (PhV) is an important clinical activity with strong implications for population health and clinical research. The main goal of PhV is the timely detection of adverse drug events (ADEs) that are novel in their clinical nature, severity and/or frequency. Drug interactions (DI) pose an important problem in the development of new drugs and post marketing PhV that contribute to 6-30% of all unexpected ADEs. Therefore, the early detection of DI is vital. Spontaneous reporting systems (SRS) have served as the core data collection system for post marketing PhV since the 1960s. The main objective of our study was to particularly identify signals of DI from SRS. In addition, we are presenting an optimized tailored mining algorithm called "hybrid Apriori". The proposed algorithm is based on an optimized and modified association rule mining (ARM) approach. A hybrid Apriori algorithm has been applied to the SRS of the United States Food and Drug Administration's (U.S. FDA) adverse events reporting system (FAERS) in order to extract significant association patterns of drug interaction-adverse event (DIAE). We have assessed the resulting DIAEs qualitatively and quantitatively using two different triage features: a three-element taxonomy and three performance metrics. These features were applied on two random samples of 100 interacting and 100 non-interacting DIAE patterns. Additionally, we have employed logistic regression (LR) statistic method to quantify the magnitude and direction of interactions in order to test for confounding by co-medication in unknown interacting DIAE patterns. Hybrid Apriori extracted 2933 interacting DIAE patterns (including 1256 serious ones) and 530 non-interacting DIAE patterns. Referring to the current knowledge using four different reliable resources of DI, the results showed that the proposed method can extract signals of serious interacting DIAEs. Various association patterns could be identified based on the relationships among the elements which composed a pattern. The average performance of the method showed 85% precision, 80% negative predictive value, 81% sensitivity and 84% specificity. The LR modeling could provide the statistical context to guard against spurious DIAEs. The proposed method could efficiently detect DIAE signals from SRS data as well as, identifying rare adverse drug reactions (ADRs). Copyright © 2016 Elsevier Inc. All rights reserved.

Evaluation of RNA extraction methods and identification of putative reference genes for real-time quantitative polymerase chain reaction expression studies on olive (Olea europaea L.) fruits.

PubMed

Nonis, Alberto; Vezzaro, Alice; Ruperti, Benedetto

2012-07-11

Genome wide transcriptomic surveys together with targeted molecular studies are uncovering an ever increasing number of differentially expressed genes in relation to agriculturally relevant processes in olive (Olea europaea L). These data need to be supported by quantitative approaches enabling the precise estimation of transcript abundance. qPCR being the most widely adopted technique for mRNA quantification, preliminary work needs to be done to set up robust methods for extraction of fully functional RNA and for the identification of the best reference genes to obtain reliable quantification of transcripts. In this work, we have assessed different methods for their suitability for RNA extraction from olive fruits and leaves and we have evaluated thirteen potential candidate reference genes on 21 RNA samples belonging to fruit developmental/ripening series and to leaves subjected to wounding. By using two different algorithms, GAPDH2 and PP2A1 were identified as the best reference genes for olive fruit development and ripening, and their effectiveness for normalization of expression of two ripening marker genes was demonstrated.